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Genetically distant American Canine distemper virus lineages have recently caused epizootics with somewhat different characteristics in raccoons living around a large suburban zoo in the USA

Background Mortality rates have differed during distemper outbreaks among free-ranging raccoons ( Procyon lotor ) living around a large Chicago-area zoo, and appeared higher in year 2001 than in 1998 and 2000. We hypothesized that a more lethal variant of the local Canine distemper virus (CDV) lineage had emerged in 2001, and sought the genetic basis that led to increased virulence. However, a more complex model surfaced during preliminary analyses of CDV genomic sequences in infected tissues and of virus isolated in vitro from the raccoons. Results Phylogenetic analyses of subgenomic CDV fusion ( F ) -, phosphoprotein ( P ) -, and complete hemagglutinin ( H ) – gene sequences indicated that distinct American CDV lineages caused the distemper epizootics. The 1998 outbreak was caused by viruses that are likely from an old CDV lineage that includes CDV Snyder Hill and Lederle, which are CDV strains from the early 1950's. The 2000 and 2001 viruses appear to stem from the lineage of CDV A75/17, which was isolated in the mid 1970's. Only the 2001 viruses formed large syncytia in brain and/or lung tissue, and during primary isolation in-vitro in Vero cells, demonstrating at least one phenotypic property by which they differed from the other viruses. Conclusions Two different American CDV lineages caused the raccoon distemper outbreaks. The 1998 viruses are genetically distant to the 2000/2001 viruses. Since CDV does not cause persistent infections, the cycling of different CDV lineages within the same locale suggests multiple reintroductions of the virus to area raccoons. Our findings establish a precedent for determining whether the perceived differences in mortality rates are actual and attributable in part to inherent differences between CDV strains arising from different CDV lineages.

Background Canine distemper virus (CDV) (family Paramyxoviridae , genus Morbillivirus ) is a single-stranded (negative-sense) enveloped RNA virus that is highly contagious and transmitted predominantly by aerosols [ 1 ]. Long known to cause potentially lethal disease among members of the Canidae , Mustelidae , and Procyonidae , CDV has recently been detected as a cause of morbidity and mortality in large felids [ 2 ], fresh-water seals ( Phoca sibirica ) [ 3 ], and various other animals. CDV killed more than 10,000 Caspian seals ( Phoca caspica ) in year 2000 [ 4 ], and decimated an African wild dog (an endangered species) breeding pack [ 5 ], demonstrating that CDV epidemics can be catastrophic. It also killed 1/3 of the Serengeti lions ( Panthera leo ) in 1994, whereas mortality due to CDV had not been previously described in large felids [ 6 ]. However, CDV is not uniformly lethal in related species; unlike the situation with lions, house cats ( Felis sylvestris catus ) can be infected by CDV wherein pathogenesis is unclear [ 7 , 8 ]. The increased importance of emerging pathogens has been most commonly attributed to changes in interactions between species or other ecological parameters [ 9 ], though changes in the pathogens or host susceptibility could also play a role. Closely related genomic variants of a particular RNA virus can arise within a host, forming a population of viruses referred to as quasispecies [ 10 , 11 ]. Viral quasispeciation can generate new disease patterns and broaden host ranges [ 10 - 12 ]. It is possible that CDV quasispeciation may account for the increasing number of clinically typical distemper cases in dogs [including those vaccinated against CDV). This implies the emergence of CDVs with different antigenic properties from the vaccine strains [ 5 , 13 - 15 , 23 ]. Serological tests of various captive carnivores in 1997 indicated seroconversion to CDV occurred among 28% of large felids after they were housed in outdoor exhibits at a large zoo located near Chicago (Illinois, USA) (T. Meehan and L. Hungerford, unpublished). The animals were CDV seronegative prior to outdoor display, and had not been vaccinated against CDV. Seroconversion did not occur among large felids kept indoors. It was thus apparent that the large felids acquired CDV infections during outdoor display. Distemper epizootics occur sporadically among area raccoons ( Procyon lotor ), and free-ranging raccoons were implicated as the source of CDV to the susceptible animals of the zoo, as large numbers of raccoons from adjoining forest preserves forage on the zoo grounds. The raccoons potentially transmit CDV to zoo animals indirectly through droplet infection and perhaps also through contact infection of nasal and oropharyngeal mucosa, since they are sometimes caught and consumed by zoo carnivores. Although CDV can cause high mortality in raccoons [ 16 , 17 ], it can also circulate widely in a population with many survivors, as documented by seroprevalence studies [ 18 ]. This suggests not only a substantial disease reservoir, but also the possibility of CDV strains with different levels of virulence. The latter notion cannot be readily resolved by current serology approaches, especially considering that CDV is presently considered monotypic by serology. For zoos where free-ranging raccoons can regularly be found, there is concern that CDV carried by raccoons might pose a health risk to susceptible collection species for two reasons: (a) CDV is highly infectious and an acknowledged lethal pathogen of many carnivores, and (b) CDV might mutate into a variant capable of broad-spectrum lethality. Wild raccoons were previously incriminated as the source of epizootics in captive carnivores in zoological collections and conservation parks [ 2 , 19 ]. Also, clinically apparent CDV infections occur in some omnivores such as Japanese snow monkeys ( Macaca fuscata ) [ 20 ] and collared peccaries ( Tayassu tajacu ) [ 21 ], raising the possibility that CDV might also cause lethal epidemics among non-carnivores. Live raccoons are trapped on zoo grounds. Those with clinical neurologic signs are euthanized, necropsied, and examined for evidence of distemper or other infections. Dead raccoons found on-site are similarly evaluated whenever possible [ 22 ]. These procedures are routinely conducted as part of disease surveillance initiatives of the zoo and local and state agencies, especially because rabies is a major concern, and neurological signs that occur in distemper sometimes mimic rabies [ 22 ]. Distemper was detected in raccoons on zoo grounds in years 1998, 2000, and 2001 but not in 1999, 2002, and 2003. A total of 9/25 (36%) of the animals submitted for necropsy in 1998 and 1/14 (7%) in 2000 had lesions consistent with CDV infection. The number of animals submitted in 2001 was higher (n = 49) than for years 1998 and 2000, as was the percentage positive for CDV: 26/49 (45%). Precise data about the number of animals living within the forest preserve was not available. It was also not known whether significantly different numbers of animals utilized the zoo during the time line of this study (1998–2002). Nevertheless, there appeared to be a surge in distemper mortality in 2001, and comprehensive necropsy evaluations (performed by the same pathologist) revealed that the CDV lesions of the 2001 animals differed somewhat from those seen in the 1998 and 2000 animals. Since phylogenetic analyses suggest that wild-type CDVs differ according to geographical distribution rather than to host species [ 6 , 23 ], we asked whether a local CDV strain had mutated into a more virulent variant in 2001, causing the perceived rise in mortality and differences in histological presentation. We first sought to identify the local lineage of CDV through direct sequence analysis of viral RNA (vRNA) in infected raccoon tissues and also attempted virus isolation from the specimens. Virus isolation was important not only to confirm direct sequence analyses but also: (a) because it was possible that direct sequence analyses might not work for various technical reasons, and (b) for future vaccine development in the event that unusual viral variants were detected for which current vaccines were ineffective. Following the example of previous investigators, we tried to obtain the identity of the circulating local CDV by determining the sequence of a subsection of the CDV phosphoprotein ( P ) gene, since the P -gene tends to remain conserved within clades of a given CDV lineage [ 24 ], and is useful for phylogenetic analysis [ 5 , 24 , 25 ]. To reduce the risk of bias arising from analysis of only one section of the CDV genome, we also examined a subsection of the CDV fusion ( F ) gene sequence that encodes a protein cleavage site [subtilisin-like endoprotease motif (-R-X-K/R-R-)] and the fusion domain [ 26 ]. The F-protein is the most conserved among morbilliviruses [ 27 ], and the F -gene sequence can be used to determine phylogenetic relationships between different morbillivirus species, such as the relationship between CDV and the closely related morbillivirus of salt-water seals called Phocine distemper virus-1 (PDV-1) [ 28 ]. F- gene analysis would thus help establish whether the virus was authentic CDV and not a related raccoon morbillivirus. Finally, the entire CDV receptorbinding hemagglutinin (H ) gene was analyzed, since the H protein is the major determinant of tropism and cytopathogenicity [ 29 ], and is useful for phylogenetic analyses [ 6 , 23 ]. Whereas all the viruses were related to American CDV strains, the 1998 and 2001 viruses were clearly resolved by phylogenetic analyses into two genetically distant CDV clusters (lineages). The 2000 virus apparently stems from a sublineage related to the 2001 viruses. Results Pathology evaluation In general, the results obtained from gross and histologic examinations of the animals were typical for CDV-induced distemper. Major findings included non-suppurative encephalitis and necrotizing bronchointerstitial pneumonia of variable severity (Table 1 ). As expected for wild raccoons of this area, multicentric parasitism was common, but additional underlying diseases were generally not noted. The presence of Encephalomyocarditis virus (EMCV) in animals 01-2641 and 01-2690, however, was unexpected. Table 1 Histologic lesions of CDV-infected raccoons. Raccoon Sex M/Y a Site b Presentation Encephalitis f Pneumonia h Other findings EMCV k 98-2645 F 8/98 FP c Euthanized ++; Demyelination; axonal loss; few IB g +++; Chronic; no IB Lymphoid depletion (LN i ); IB – other sites - 98-2646 M 8/98 ZG d Dead - ++; Sub-acute to chronic; no IB IB – other sites j - 98-2654 M 10/98 ZG Euthanized Rare axonal loss ++ Ocular discharge; CDV in footpad ("Hardpad" disease); lymphoid depletion (LN and spleen) - 98-2655 F 10/98 ZG Dead ++; IB common None Lymphoid depletion (LN and spleen); IB – other sites - 98-2666 F 12/98 ZG Euthanized ++; Axonal loss; rare neuronal IB ++; Chronic; no IB Lymphoid depletion (LN and spleen); IB – other sites - 00-2601 M 1/00 ZG Euthanized ++; Rare neuronal IB; severe axonal loss None IB – other sites - 01-2641 M 5/01 OFP e Euthanized +; IB; syncytia in hippocampus +++ with syncytia; IB Lymphoid depletion (LN and spleen); IB – other sites + brain, LN, spleen) 01-2663 F 6/01 ZG Euthanized None +++ with syncytia; IB Lymphoid depletion (LN and spleen); IB – other sites - 01-2676 F 7/01 ZG Euthanized +; Axonal loss; neuronal necrosis; IB; syncytia in hippocampus +++; IB Lymphoid depletion (LN); IB – other sites - 01-2689 F 8/01 ZG Euthanized +; IB ++ with syncytia; IB Lymphoid depletion (LN and spleen); IB – other sites; rhinitis; purulent conjunctivitis - 01-2690 M 8/01 ZG Euthanized Rare neuronal necrosis; IB None Lymphoid depletion (LN); IB – other sites + (spleen) a M/Y; Month and year animal examined by necropsy and specimens frozen. b Site; Location where animal was trapped or found dead. c FP; Forest preserve at border of zoo. d ZG; Zoo grounds. e OFP; Off-site forest preserve f Encephalitis: -, none; +, mild; ++, moderate. g IB; Characteristic intracytoplasmic or intranuclear inclusion bodies formed by Canine distemper virus . h Pneumonia: +, mild; ++, moderate; +++, severe. i LN; Lymph node. J IB – other sites: Inclusion bodies in other epithelial sites. k EMCV, Encephalomyocarditis virus . Histologic differences in the CDV lesions were apparent. While lymphoid depletion and characteristic eosinophilic intracytoplasmic inclusions in various epithelial tissues were observed in all years, inclusion bodies were more plentiful in the brain and lung tissues of raccoons examined in year 2001 than those of years 1998 and 2000. Of note, small and large (multinucleated) syncytia were present in the central nervous system and (Fig. 1A ) and lung (Fig. 1B ) of some raccoons from year 2001 but not in animals from 1998 and 2000 (Table 1 ). Figure 1 Panel A. Hematoxylin and eosin (H & E) – stained thin section of hippocampus tissue from raccoon 01-2676. Syncytia are identified by large arrows. Some CDV inclusion bodies are indicated (small arrows). Original magnification × 200. Panel B. Thin section (H & E-stained) of lung tissue from raccoon 01-2663. Syncytia and CDV inclusion bodies are identified as in panel A. Isolation of virus from infected tissues Virus was isolated from the tissues of 11/11 animals (Table 2 ) [ 22 ]. Viral cytopathic effects (CPE) in Vero cells consisted of the formation of granular-appearing cytoplasm with vacuolization (small vacuoles), followed by rounding of the cells and detachment, and rare formation of small stellate syncytia (consisting of 2–3 cells fused together) for viruses isolated from year 1998 and 2000 specimens or frequent larger rounded syncytia typically containing >8 nuclei in viruses from year 2001 [ 22 ]. Thus, the 2001 viruses appeared to form large syncytia in vivo (Table 1 ) and in vitro [ 22 ]. Table 2 CDV detection by direct RT-PCR of tissue and by virus isolation. Raccoon Tissue Direct RT-PCR of Tissue Virus isolation 98-2645 brain - + 98-2646 brain - + 98-2654 brain + + 98-2655 brain - + 98-2666 brain + + 00-2601 brain + + 01-2641 brain + + lung + + lymph node - + spleen + + 01-2663 brain + + lung + + lymph node - + spleen + + 01-2676 lung + + lymph node + + 01-2689 brain + + lymph node + + spleen + + 01-2690 brain + + kidney - - liver - - lung + + spleen - + RT-PCR and nucleotide sequence analyses Where direct comparisons were possible, viral genomic sequence analyses indicated that the subgenomic viral F - and P - and full-genomic H -gene sequences did not change during primary isolation in three different cell lines (MDCK, MV1 Lu, and Vero [ 22 ]. Thus, for viruses from animals 98-2645, 98-2646, and 98-2655, for which direct RT-PCR from infected tissues failed (Table 2 ), it was likely that the sequences obtained were authentic. The subgenomic F - and P- gene of this study were previously reported [ 22 ] and deposited at GenBank (Table 3 ). The full-genomic H- gene sequences are available at GenBank (Table 3 ); since the H -gene sequences are relatively long (1,824 bp), only the deduced aa sequences are shown (Fig. 2 ). As for the P -gene, virus CDV 98-2666 had two slightly different H -gene sequences that were detected in vRNA in infected tissues; the same H -gene sequences were detected in corresponding virus isolates. The dominant H -gene sequence determined directly from infected tissues is labelled 98-2666 (Fig. 2 , and H -gene sequence 98-2666 in Table 3 ), and is identical to the sequence of variant 98-2666-1 (Fig. 2 , and H -gene sequence 98-2666-1 in Table 3 ), whereas the H -gene sequence of the second variant is labelled 98-2666-2. An example of RT-PCR for the CDV H -gene of a primary virus isolate in Vero cells is shown in figure 3 . Figure 2 Deduced H-protein amino acid sequences of raccoon CDVs. Numbers above the sequences identify aa positions in the H-protein of CDV reference strain Onderstepoort. Table 3 GenBank accession numbers of raccoon CDVsequences. Virus F -gene H -gene P -gene 98-2645 AY445077 (entire genome) 98-2646 AY542312 (entire genome) 98-2654-1 AY466011 (entire genome) 98-2654-2 AY289612 (AY466011) d AY286485 98-2655 (AY289612) a AY548109 AY263373 98-2666-1 (AY289612) a AY548110 AY286486 98-2666-2 (AY289612) a AY548111 AY286487 00-2601 AY443350 (entire genome) 01-2641-1 AY289614 AY526496 AY288310 01-2641-2 (AY289614) b (AY526496) e AY321298 01-2663 AY289615 ND f AY288308 01-2676 (AY289615) c AY498692 AY288309 01-2689 (AY289615) c AY465925 AY286488 01-2690 (AY289615) c (AY465925) g AY264266 a Identical to the sequence of AY289612. b Identical to the sequence of AY289614. c Identical to the sequence of AY289615. d Identical to the sequence of AY466011. e Identical to the sequence of AY526496. f ND, Not determined. g Identical to the sequence of AY465925. Figure 3 Ethidium-bromide gel electrophoresis analysis of subgenomic H -gene RT-PCR amplicons. For CDV-2676, shown are the 1104 bp product (lane 1) using primers CDV-HforD and CDV-Hrev75, and the 1026 bo product (lane 2) using primers CDVH-forB and CDV-HrevC (29). A 2% agarose gel was used. Molecular weight markers are loaded in the lane marked "M". Positive and negative controls were run separately and are not shown. Phylogenetic analyses The 70% majority-rule consensus parsimony (Fig. 4 ) and neighbor-joining (not shown) cladograms for the P- gene sequences are almost identical. Both analyses grouped the 1998 sequences together in a single clade with CDV-Lederle and -Snyder Hill with high bootstrap support. These viruses have P -gene sequences similar to those of CDVs Onderstepoort and Rockport, from S. Africa and Sweden, respectively. The cluster of the 2001 sequences (01-2663, -2676, -2689, -2690) was also the same in both cladograms. However, while parsimony joined the 01-2641 sequence from an offsite raccoon to the base, the distance based tree grouped this sequence with CDV A75/17. The 2000 virus was also not resolved by either method of analysis. Of the 390 bases, 34 were informative. Derivatives of the 1998 cluster form a distantly related lineage to that of 2001 cluster that is nevertheless rooted in the CDV group when compared to PDV-1 as an outgroup. CDV Lederle appears to be more derived than A9224/14b (detected in 1992 in a California (USA) raccoon [ 6 ]). Figure 4 P -gene 70% majority rule parsimony consensus tree. Viruses from this study are high-lighted by a grey background. The animal source and GenBank numbers from top to bottom are: (1) (South African dog) AF305419, (2) (Swedish dog) AF181446, (3) (American dog) AY286480, (4) (American dog) AY286481, (5 – 17) Illinois raccoons, GenBank numbers in Table 3, (18) (German dog) AY386315, (19) (Bulgarian dog) AF259549, (20) (American dog) AF164967, (21) (German ferret) AF259550, (22) (Siberian seal) AF259551, (23) (Japanese dog) AB028916, (24) (Californa raccoon A9224/14b, reference 6), (25) ( Phocine distemper virus ) D10371. There were a total of 335 nucleotides in the F -gene and 32 of these were parsimony informative. Both parsimony (Fig. 5 ) and distance based (not shown) analyses produced the same topology. The off-site raccoon 01-2641 failed to group with any other sequences, joining at the base. The 1998 sequences formed a single cluster within a clade that included Lederle, Snyder Hill, and vaccine strains Onderstepoort and Bul. 170 (originally isolated from a Bulgarian dog) [ 30 ]. This clade also included the 00-2601 sequence. The remaining 2001 viruses formed a single clade with high bootstrap support. Figure 5 F -gene 70% majority rule parsimony consensus tree. Viruses from this study are high-lighted by a grey background. GenBank accession numbers are: (1) CDV Lederle (AY288311); (2) Snyder Hill (AY288312); (3 – 10, Illinois raccoons, Table 3); (11) Onder., Onderstepoort (AF378705); (12) Bul. 170, Bulgarian dog (AF259549); (13 – 17, Illinois raccoons, Table 3); (18) CDV A75/17 (AF164967); (19) PDV2, Phocine distemper virus 2 (L07075); (20) Danish dog (AF355188); (21) CDV 5804 (from German dog) (AF026241); (22) Hyena (AF026233); (23) Marten (AF026230); (24) PDV-1 (L07075). The H -gene parsimony (Fig. 6 ) and neighbor-joining (not shown) topologies were identical with respect to the clades that include the raccoon viruses from this study. Out of 1,824 nucleotides, 420 of these were parsimony informative. As with the previous genes, the 1998 isolates and the 2000/2001 viruses formed separate clusters. The 1998 sequences joined the tree at a basal position in both analyses. The 2000 and off-site raccoon 01-2641 sequences grouped with the large felids from another zoo in Illinois. Figure 6 H -gene 70% majority rule parsimony consensus tree. Arrows or boxes demarcate locations of viruses from this study. GenBank accession numbers are: (1) CDV 00-2601 (Illinois raccoon, Table 3); (2) Chinese leopard (Z54156); (3) 01-2641 (Illinois raccoon, Table 3); (4) black leopard (Z47763); (5) black panther (Z54166); (6 – 8, Illinois raccoons, Table 3); (9) raccoon (Z47765); (10) A75/17 (AF164967); (11) dog (USA) (Z47762); (12) javelina (Z47764); (13) raccoon dog Tanu (AB016776); (14) dog (Taiwan) (AY378091); (15) dog Hamam (D85754); (16) dog KDK1 (AB025271); (17) dog Ueno (D85753); (18) dog Yanaka (D85755); (19) giant panda (AF178038); (20) dog 5804 (AY386315); (21) dog Denmark (Z47761); (22) dog 91A (AF478544); (23) dog isolate A (AF478543); (24) dog 91B (AF478546); (25) dog 91C (AF478548); (26) dog 91D (AF478550); (27) dog isolate C (AF478547); (28) dog isolate B (AF478545); (29) dog isolate D (AF478549); (30) dog isolate 2544 (Z77672); (31) dog isolate 404 (Z77671); (32) dog isolate 4513 (Z77673); (33) dog (Turkey) (AY093674); (34) ferret (X84999); (35) mink (Z47759); (36) lesser panda (AF178039); (37) Siberian seal (X84998); (38) dog (China) (AF172411); (39) dog (Greenland) (Z47760); (40) dog 26D (AB040766); (41) dog 5B (AY297453); (42) dog 5VD (AY297454); (43) dog 98-002 (AB025270); (44) dog HM-3 (AB040767); (45) dog HM-6 (AB040768); (46 – 54, Illinois raccoons, Table 3), (55) Snyder Hill (AF259552); (56) Onderstepoort (AF378705); (57) PDV-1 (AF479274). Noteworthy, P -, F - and H - gene analyses indicate that the CDV sequences segregate according to geography and not to species. Since the H gene had the largest number of nucleotides, pairwise genetic distances were calculated. The 1998 isolates were most similar to the Onderstepoort and Snyder Hill (D = 4% and 1% respectively) while the 2001 isolates were most distant (D = 9% and 10% respectively). Distances within 1998 viruses were low (D ≤ 0.2%); within 2001, distances were slightly higher (D = 1%); and comparing years 1998 with 2000 and 2001, distances were highest (D = 7% to 9% respectively). When the P -, F - and H - genes were combined into a single linear sequence and analyzed using parsimony and neighbor-joining algorithms with only PDV-1 as an outgroup, two independent clades are formed, the 1998 clade and the 2000/2001 clade (data not shown). In the later group, both methods join the 2000 sequence (00-2601) at a basal position to the 01-2641 off-site raccoon followed by the 2001 isolates. Discussion This report shows that different CDV sublineages stemming from at least two genetically distant CDV lineages recently circulated through the local raccoon population. Our conclusion is based on numerous observations: differences in the lesions observed in animal tissues, possible dissimilarities of virulence between the viruses, variation in one viral phenotype in tissue culture (formation of large syncytia by the 2001 viruses), and from the results of nucleotide sequence and phylogenetic analyses. CDV is not maintained in hosts that recover from distemper, and persistent CDV infections do not occur. However, CDV infects a wide range of genera, and though each individual population may be small, the number of alternative host species may be substantial [ 1 ]. Forest preserves around the zoo contain many species susceptible to CDV, and it appears by inference there are separate reservoirs of different CDV lineages within the area of this study. Since past studies indicated that wild-type CDVs differed according to geographical distribution [ 6 , 23 ], we initially surmised that the local CDV occasionally formed clades of highly virulent CDV variants, resulting in periodic high mortality distemper outbreaks. We also speculated that over time, highly virulent viruses would undergo extinction, and ensuing epizootics would arise from less virulent CDV variants that could affect most of the hosts without killing them. Thus, there would be an apparent oscillation (periodicity) of the mortality rates. The situation is not as straightforward, however. As shown in figures 4 , 5 , 6 , at least two different CDV lineages circulated in the raccoons from 1998 – 2001. Our findings thus suggest that the outcomes of distemper might also be influenced by properties unique to different CDV lineages and their genetic variants ("strains"). The viruses from year 2001 formed syncytia in vivo and in vitro . Previously, an inverse relationship between the proficiency of syncytium formation and the level of CDV virulence was reported: the more attenuated a strain is, the higher its fusogenicity, and fusogenicity was attributed to the viral H-protein [ 31 - 34 ]. Therefore, the findings of this study may appear antidogmatic because increased mortality was associated with the 2001 viruses, which formed large syncytia in vivo and in vitro. However, past notions concerning the inverse relationship between fusogenicity and virulence may be imprecise. Indeed, virulent wild-type CDVs that formed syncytia in Vero cells were recently reported; the same study demonstrated that genetic changes within the H -gene were not required for CDV growth in Vero cells [ 35 ], as was found in this and our previous study [ 22 ]. Also, newer studies indicate that syncytium formation by CDV requires the concerted activities of both the H- and F- proteins [ 36 - 38 ], and that CDV virulence is the combined affect of various proteins including the F- and H- proteins [ 39 ]. Thus, whereas animal studies were not performed with the virus isolates of this study to directly test whether they differ in virulence, the formation of large syncytia does not rule out the possibility that the 2001 viruses are highly virulent. Noteworthy, the 2001 viruses were detected in the hippocampus and alveoli of the raccoons. Both sites were considered unusual targets of a CDV variant that was lethal to Serengeti lions, whereas CDV in dogs was said to most frequently target the brain stem and bronchi [ 40 , 41 ]. It is possible that tissue localization, especially with regard to the hippocampus, correlates with virus strain. In our experience, CDV in raccoons does not preferentially target the brain stem but rather infects all portions of the brain, with the possible exception of the hippocampus. We will be able to address the question whether specific CDV strains localize in the hippocampus of raccoons as we accumulate additional data from future outbreak, and after we conduct animal tests with the viruses we isolated. In contrast, CDV targets epithelial cells, and the presence of CDV in the alveoli of raccoons with distemper is common. H -gene phylogenetic analyses (figure 6 ) suggest that a viral lineage that includes CDV A75/17 (isolated in 1975) [ 32 ] and the 2000 and 2001 viruses had infected various species including large felids [Fig. 6 and reference 6] for at least 28 years on both coasts and a midwestern state (and thus presumably throughout the continental USA). The seemingly widespread distribution suggests that viruses stemming from this lineage may be the dominant "American" CDV currently in circulation in the continental USA. The F -, H -, and P -gene sequence analyses (figures 4 , 5 , 6 ) indicate that the 1998 viruses stem from a different CDV lineage that includes American CDV strains Lederle and Snyder Hill. A recent phylogenetic analysis of the P -gene by an independent laboratory that utilized some of our P -gene data generated similar results [ 42 ]. Because they were isolated before CDV Lederle and Snyder Hill were acquired from the ATCC for this study and have distinguishable F - and H -gene sequences [ 22 ], it is certain that the 1998 CDV isolates are not due to laboratory contamination. Yet, phylogenetic analyses indicate that the CDV Lederle and Snyder Hill sequences are distant to, and in the case of the H -gene, ancestral to, those of the 2000 and 2001 viruses, which are as genetically distant from the 1998 viruses as they are from Snyder Hill. The source of the 1998 viruses is thus intriguing. Prior to 1997, some area raccoons were trapped, vaccinated against CDV, then released in an attempt to curtail CDV epidemics within the local raccoon population. CDV Lederle has been used as a vaccine strain in the past [ 3 ]. The vaccine used for the raccoons, (Galaxy-D, from Schering-Plough, Kenilworth, NJ), though, was made with CDV Onderstepoort, which is easily distinguished from the 1998 viruses by F -, H -, and P -gene analyses. However, we still could not rule out the possibility that the 1998 viruses are vaccine escape viruses from a dog vaccinated with CDV Lederle. Dogs and raccoons often frequent the same feeding sites (such as refuse disposal zones) in urban areas. The possibility of reversion to virulence of attenuated CDV exists [ 43 ], and a vaccine escape virus was proposed as a cause of distemper in a dog in Belfast, Northern Ireland [ 3 ]. We could not find a current manufacturer of anti-CDV vaccine in the USA that uses CDV Lederle. However, such vaccines were in distribution overseas around 1998 [ 22 ], and the Chicago area undergoes constant population flux, including translocation of inhabitants (and their pets) from outside of the continental USA. Related to this, the live attenuated CDV vaccine (Galaxy-D) used by the zoo up to 1997 caused vaccine-mediated distemper in different species at the zoo that had been vaccinated. For this reason, use of that particular vaccine was discontinued; instead, Purevax™, a recombinant CDV-canary pox virus vaccine (Merial, Duluth, GA) is used; the CDV insert in the canary pox virus genome is incomplete and cannot be infectious. CDV-Lederle was isolated in 1951 from a dog with encephalitis (information provided by ATCC). An alternative interpretation of our findings is that the CDV lineage that gave rise to CDV Lederle has stabilized in the local animals and is still actively circulating; more studies are needed to resolve this matter. EMCV has been isolated or detected in raccoons before [ 44 , 45 ]. However, pathogenesis was uncertain, and it was thought that raccoons are a dead-end host for this virus [ 45 ]. It is known that mortality during an active case of distemper is increased in the presence of polymicrobial disease [ 46 ]. For example, a lethal outcome occurs in dogs co-infected with CDV, Bordetella bronchiseptica , and Toxoplasma gondii. It is possible that the increased mortality in 2001 was due to secondary infections with EMCV; however, no lesions attributable to EMCV were observed in pathology exams of the animals of this study, and EMCV was not isolated from all of the 2001 specimens. The significance of isolating EMCV from the brain tissue of animal 01-2641 is thus uncertain. Our findings are especially useful for the molecular epidemiology of CDV in local wildlife, as they provide a molecular basis for CDV surveillance in area wildlife. Whereas it is considered difficult to obtain field isolates of CDV, we succeeded and can now obtain complete viral genomic sequence data (it would be difficult to do so relying solely on the limited amount of archived CDV-infected tissues from the animals of this work). Taken together, we can now monitor viral genetic drift during a long-term study of CDV in local raccoons, and will be able to conduct animal studies with the newly isolated viruses. We can also clone relevant CDV virulence genes, and express and study the biochemical properties of their specific products in vitro . The baseline genetic values established here will be helpful toward the development of a contemporary field-based model (since the animals are free-ranging) for studies on the emergence, evolution, maintenance, and transmission of morbilliviruses, and the efficacy of vaccines against changing viruses. Conclusions The 1998 and 2001 distemper outbreaks were caused by two genetically distant American CDV lineages. Since CDV does not cause persistent infections, the cycling of different CDV lineages within the same locale suggests multiple reservoirs were responsible for the reintroduction of the virus to area raccoons. Whereas different susceptible species of the forest preserves and perhaps also some caged animals of the zoo are the most likely reservoirs, our study raises the possibility that vaccines might also be a source of CDV. The perceived differences in mortality rates that occur during intermittent distemper epizootics may be attributed in part to inherent differences between CDV strains. Methods Raccoon tissues The raccoon tissues used in this study were described previously [ 22 ]; relevant clinical and histologic findings are presented in Table 1 . Brain tissue was available for animals 98-2645, -2646, -2654, -2655, -2666 (n = 5, each collected in year 1998) and 00-2601 (n = 1, from year 2000) (Table 1 ). Additional tissues were available for animals 01-2641, -2663, -2676, -2689, and -2690 (n = 5, each collected in year 2001) (Table 2 ). Virus isolation Detailed virus isolation procedures were described previously [ 22 ]. Briefly, CDV was isolated in vitro in MDCK, MV1-Lu, and Vero cells, eliminating the need for virus isolation in specific pathogen-free animals or in primary macrophages or other suitable cells derived thereof [ 29 ]. RNA purification and RT-PCR RNA purification and RT-PCR methods were previously detailed [ 22 ]. Briefly, vRNA was extracted directly from infected tissues when possible, as well as from CDV-infected tissue culture cells or from liberated CDV virions in spent cell growth media, using dedicated commercial kits (Qiagen Inc., Valencia, CA). For the American CDV strains of this work, many RT-PCR primers based on the sequence of American CDV isolate A75/17 (GenBank No. AF164967) were more effective than primers described for foreign CDV strains [ 22 ]. Nucleic acid sequencing Methods used for nucleic acid sequencing were previously described [ 22 ]. Briefly, all sequences were determined at least twice, starting from the purification of new RNA samples from each specimen, and both strands of each PCR amplicon were sequenced. Slab-gel sequencing utilizing dye-terminator chemistries (LI-COR, Lincoln, NE) was used at the inception of the project, then replaced by capillary sequencing using ABI-PRISM technology (Applied Biosystems, Foster City, CA). The CDV gene sequences in infected tissues were exactly like those in matched primary viral isolates [ 22 ]. The GenBank accession numbers for all the virus sequences of this work are given in Table 3 . Phylogenetic analyses Phylogenetic trees of the P -, F -, and H -gene sequences were constructed using the maximum-parsimony and neighbor-joining algorithms in Phylogeny Analysis Using Parsimony (PAUP) Beta Version 4.0B10 for Macintosh [ 47 ]. Heuristic searches were conducted with "simple" addition and the tree-bisection-reconnection method of branch swapping. Distance-based analyses using the minimum-evolution criterion were also conducted within PAUP using Kimura's-two-parameter model [ 48 ]. Phylogenetic tree reliability was estimated with 1000 bootstrap replications [ 49 , 50 ]. The appropriate Phocine distemper virus sequence (PDV-1) was included for outgroup rooting. P -gene phylogenetic analyses were performed after an alignment of 25 P -gene sequences. Each P -gene sequence consisted of 390 ungapped positions (nucleotides 2154 to 2543 of CDV reference strain Onderstepoort) within the P -gene PCR amplicon. Only the internal 390 bp section of the P -gene PCR amplicon (432 bp) was analyzed because many relevant GenBank entries did not include the entire sequence amplified by the P -gene primers of this study. An additional P -gene sequence for raccoon A9224/14b was obtained from published data currently not deposited at GenBank [ 6 ]. Similarly, 24 ungapped F -gene sequences corresponding to nt 5399–5733 (335 bp) of CDV Onderstepoort were analyzed. Unlike the P- and F- genes, the entire H -gene was analyzed since many complete H -gene sequences were available at GenBank. Phocine distemper virus 1 (PDV1) sequences were included in the analyses for outgroup rooting. Competing interests None declared. Authors' contributions JAL co-conceived, designed, and coordinated the study, isolated virus, participated in the molecular genetic studies and sequence alignment, interpreted data, oversaw the training of technicians, and drafted the manuscript; JD performed phylogenetic analyses, interpreted data, and helped draft the manuscript; MJK performed pathology examinations, provided tissue specimens, helped draft the manuscript, and interpreted data; TPM co-conceived the study, provided serology data, helped draft the manuscript, and interpreted data; MB performed phylogenetic analyses, interpreted data, and helped draft the manuscript; LLH provided serology data and epidemiology perspectives, and helped draft the manuscript; NAS participated in virus isolation, molecular genetic studies, sequence alignment, and proofreading of the manuscript; KEW participated in virus isolation and molecular genetic studies, and MDB, CP, and CMH performed molecular genetic studies. All authors read and approved the final manuscript

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521177

DJ-1 Is a Redox-Dependent Molecular Chaperone That Inhibits α-Synuclein Aggregate Formation

Parkinson's disease (PD) pathology is characterized by the degeneration of midbrain dopamine neurons (DNs) ultimately leading to a progressive movement disorder in patients. The etiology of DN loss in sporadic PD is unknown, although it is hypothesized that aberrant protein aggregation and cellular oxidative stress may promote DN degeneration. Homozygous mutations in DJ-1 were recently described in two families with autosomal recessive inherited PD ( Bonifati et al. 2003 ). In a companion article ( Martinat et al. 2004 ), we show that mutations in DJ-1 alter the cellular response to oxidative stress and proteasomal inhibition. Here we show that DJ-1 functions as a redox-sensitive molecular chaperone that is activated in an oxidative cytoplasmic environment. We further demonstrate that DJ-1 chaperone activity in vivo extends to α-synuclein, a protein implicated in PD pathogenesis.

Introduction Parkinson's disease (PD) is a progressive movement disorder that is characterized pathologically by the relatively selective degeneration of midbrain DNs and the presence of prominent intracytoplasmic neuronal inclusions, termed Lewy bodies ( Dauer and Przedborski 2003 ). The identification of several genes that underlie familial forms of primary parkinsonism has allowed for the molecular dissection of mechanisms of dopamine neuron (DN) survival. Autosomal dominant mutations in α-synuclein (αSyn) lead to a rare familial form of primary Parkinsonism ( Polymeropoulos et al. 1997 ), and there is evidence that these mutations generate toxic, abnormal protein aggregates ( Goldberg and Lansbury 2000 ) and proteasomal dysfunction ( Rideout et al. 2001 ). Of note, Lewy body inclusions are particularly enriched for αSyn ( Spillantini et al. 1998 ) and neurofilament protein subunits ( Trojanowski and Lee 1998 ). Mutations in a second gene, Parkin, lead to autosomal recessive primary Parkinsonism ( Hattori et al. 2000 ). Parkin is a ubiquitin ligase that appears to participate in the proteasome-mediated degradation of several substrates ( Staropoli et al. 2003 ). Homozygous mutations in a third gene, DJ-1, were recently associated with autosomal recessive primary Parkinsonism ( Bonifati et al. 2003 ). DJ-1 encodes a ThiJ domain protein of 189 amino acids that is broadly expressed in mammalian tissues ( Nagakubo et al. 1997 ). Interestingly, DJ-1 was independently identified in a screen for human endothelial cell proteins that are modified with respect to isoelectric point in response to sublethal doses of paraquat ( Mitsumoto and Nakagawa 2001 ; Mitsumoto et al. 2001 ), a toxin which generates reactive oxygen species (ROS) within cells and has been associated with DN toxicity ( McCormack et al. 2002 ). Gene expression of a yeast homolog of DJ-1, YDR533C, is upregulated in response to sorbic acid ( de Nobel et al. 2001 ), an inducer of cellular oxidative stress. These data suggest a causal role for DJ-1 in the cellular oxidative stress response. ThiJ domain proteins are highly conserved and have been associated with several functions including protease and chaperone activities ( Halio et al. 1996 ; Du et al. 2000 ). The crystal structure of DJ-1 demonstrates the presence of a highly conserved nucleophile elbow-like domain at cysteine 106, but the relative position of this residue differs from that of a structurally related ThiJ protease, PH1704, and does not appear to be permissible for proton transfer and protease catalysis ( Wilson et al. 2003 ). Furthermore, DJ-1 forms an asymmetric homodimer with a prominent carboxy-terminal helical region present at the dimerization interface, which appears to limit access to the nucleophile elbow-like domain ( Huai et al. 2003 ; Lee et al. 2003 ; Wilson et al. 2003 ). DJ-1 displays significant homology to the carboxy-terminal domain of the Escherichia coli HPII catalase, as both proteins are divergent members of the type I glutamine amidotransferase family. Interestingly, the carboxy-terminal DJ-1 homology domain of HPII catalase lacks catalase activity, but rather appears to function as a chaperone in the correct folding of the catalytic core of the protein, and in thermal enzyme stability ( Chelikani et al. 2003 ). Taira et al. (2004) recently reported that purified DJ-1 harbors catalase activity, and that overexpression of DJ-1 by transfection of neuroblastoma tumor cells inhibits the accumulation of ROS. In contrast, analysis of DJ-1-deficient cells ( Martinat et al. 2004 ) revealed that such cells display an apparently normal initial accumulation of ROS, indicating that DJ-1 likely functions in a protective role downstream of ROS insult. Consistent with this, DJ-1-deficient cells are predisposed to apoptotic death in the context of oxidative stress ( Martinat et al. 2004 ). Here we demonstrate that DJ-1 functions as a redox-regulated molecular chaperone that is activated in an oxidizing environment. DJ-1 chaperone activity extends in vivo to αSyn, a protein that has been implicated in PD pathogenesis. DJ-1 activity is abrogated by the L166P mutation, associated with primary Parkinsonism, as a consequence of defective dimerization and reduced stability. Results DJ-1 Lacks Apparent Protease and Antioxidant Activities In Vitro DJ-1 homologs have been reported to harbor protease ( Halio et al. 1996 ; Du et al. 2000 ; Lee et al. 2003 ) and amidotransferase activities ( Horvath and Grishin 2001 ). However, crystal structure analyses of DJ-1 suggest that this protein may not retain such catalytic activities ( Honbou et al. 2003a ; Huai et al. 2003 ; Lee et al. 2003 ; Tao and Tong 2003 ; Wilson et al. 2003 ). Consistent with this, purified DJ-1 preparations failed to display in vitro protease activity toward a variety of synthetic or natural substrates, and, similarly, DJ-1 lacked antioxidant ( Table S1 ) or catalase activities ( Figure S1 ) in vitro. Furthermore, cells deficient in DJ-1 appear unaltered in the initial accumulation of ROS in the context of acute oxidative stress ( Martinat et al. 2004 ). DJ-1 Is a Redox-Dependent Molecular Chaperone Every organism responds to ROS and other toxic environmental stresses by overexpressing a highly conserved set of heat shock proteins (Hsps), many of which function as molecular chaperones to assist other proteins in folding. Hsp31, an E. coli ThiJ domain protein , has been shown to function as a molecular chaperone in vitro ( Sastry et al. 2002 ; Malki et al. 2003 ). We hypothesized that DJ-1 may similarly function as a protein chaperone to protect cells from ROS. DJ-1 chaperone activity was quantified in the suppression of heat-induced aggregation of citrate synthase (CS) and glutathione S-transferase (GST), two well-characterized protein chaperone assays. These proteins lose their native conformation and undergo aggregation during incubation at 43 °C and 60 °C, respectively. Addition of 0.5–4.0 μM polyhistidine (His)-tagged DJ-1 was found to effectively suppress the heat-induced aggregation of 0.8 μM CS ( Figure 1 A). The chaperone activity was independent of the His tag used for purification, as cleavage and removal of the His tag did not alter DJ-1 chaperone function (unpublished data). DJ-1 chaperone activity is comparable to that of a well-described small cytoplasmic chaperone, human Hsp27. In contrast, RNase A failed to demonstrate chaperone activity and served as a negative control. Interestingly, the Parkinsonism-associated L166P DJ-1 mutation abrogated chaperone activity relative to the wild-type (WT) protein ( Figure 1 B). Figure 1 DJ-1 Is a Redox-Dependent Molecular Chaperone (A) Aggregation of CS was monitored at 43 °C after addition of either 0.8 μM CS alone (black), or along with 8.0 μM RNase A (purple), 0.5 μM DJ-1 (aqua), 2.0 μM DJ-1 (blue), 4.0 μM DJ-1 (red), or 2.0 μM Hsp27 (green). (B) Aggregation of 0.8 μM CS after 30 min at 4 °C (unfilled bar) is inhibited by 4.0 μM WT DJ-1 (black bar) but not 4.0 μM L166P mutant DJ-1 (gray bar). Data are shown as the mean ± SEM and were analyzed by ANOVA with Fisher's post-hoc test. * p < 0.05. (C) Aggregation of insulin (26 μM) B chains induced by 20 mM DTT at 25 °C. Insulin alone (black) or in the presence of 4.0 μM RNase A (purple), 0.5 μM DJ-1 (aqua), 2.0 μM DJ-1 (blue), 4.0 μM DJ-1 (red), or 2.0 μM Hsp27 (green). (D) CS thermal aggregation (unfilled bar) is suppressed by 4 μM DJ-1 (black bar), but chaperone activity is abrogated upon incubation of DJ-1 with 0.5 mM DTT for 10 min at 4 °C (gray bar). Further treatment of DTT-reduced DJ-1 with 10 mM H 2 O 2 for 10 min at 4 °C leads to reactivation of CS suppression (hatched bar). Data are shown as the mean ± SEM and were analyzed by ANOVA with Fisher's post-hoc test. * p < 0.05. DJ-1 similarly functioned as a molecular chaperone in the context of the heat-induced aggregation of GST (see Figure S1 ). In contrast, DJ-1 failed to display activity in a third chaperone assay, aggregation suppression of reduced insulin ( Figure 1 C). Reduction of the disulfide bonds between the A and B chains of insulin with dithiothreitol (DTT) leads to aggregation of the B chains. Hsp27 effectively inhibited the aggregation of insulin in the presence of 20 mM DTT, whereas neither DJ-1 nor the negative control protein RNase A displayed chaperone activity in this assay. As the insulin aggregation assay is performed in a reduced environment, we hypothesized that DJ-1 chaperone activity may be redox regulated. Interestingly, such a redox switch in a molecular chaperone has been described in Hsp33 ( Jakob et al. 1999 ), a dimeric bacterial Hsp unrelated to DJ-1. To test the redox regulation of DJ-1, we assayed chaperone activity in the CS aggregation assay in the presence or absence of the reducing agent DTT. DJ-1 chaperone activity in the CS aggregation assay was completely abrogated by preincubation of DJ-1 with 0.5 mM DTT in aggregation buffer for 10 min at 4 °C ( Figure 1 D). DTT did not significantly alter CS aggregation in the absence of DJ-1 and did not modify suppression of CS aggregation by Hsp27 (unpublished data). To further test whether redox regulation might govern DJ-1 chaperone activity, reactivation studies using reduced DJ-1 were performed. DTT-reduced DJ-1 was incubated with H 2 O 2 (10 mM in aggregation buffer for 10 min at 4 °C followed by dialysis against aggregation buffer for 2 h), and subsequently chaperone activity was measured in the CS thermal aggregation assay. H 2 O 2 effectively reactivated the chaperone activity of DTT-treated DJ-1 ( Figure 1 D). This was not an indirect effect of residual H 2 O 2 on CS aggregation, as H 2 O 2 treatment of CS increased aggregation (unpublished data). These results suggest that redox regulation of DJ-1 is reversible and is regulated by the redox environment. Molecular chaperones typically display marked stability to thermal stress ( Sastry et al. 2002 ). Consistent with this, the ultraviolet-circular dichroism (CD) spectrum of WT DJ-1 is consistent with a well-folded protein, and thermal denaturation of WT DJ-1 revealed a cooperative thermal unfolding transition at approximately 75 °C (see Figure S1 ). In contrast, the CD spectrum of the DJ-1 L166P mutant protein is typical of a partially unfolded polypeptide, suggesting that the L166P mutation causes a significant loss of helical structure. The mutant protein does not exhibit a thermal unfolding transition in the range studied (0–90 °C). DJ-1 Inhibits the Generation of αSyn Aggregates We extended the analysis of DJ-1 chaperone function to a candidate DJ-1 substrate, αSyn ( Figure 2 ). The aggregation of αSyn has been implicated in familial and sporadic forms of PD, as mutations associated with autosomal dominant familial primary Parkinsonism alter the propensity of αSyn to aggregate ( Conway et al. 2000a ), and as αSyn fibrils are a major constituent of the Lewy body intracytoplasmic inclusions that typify PD pathology ( Spillantini et al. 1997 ). In vitro, monomeric αSyn is disordered or “natively unfolded” in dilute solution ( Weinreb et al. 1996 ). Incubation of purified WT human αSyn for 2 h at 55 °C results in the generation of high molecular weight multimers that likely represent protofibrils ( Figure 2 A and 2 B) ( Volles et al. 2001 ; Gosavi et al. 2002 ). This treatment does not result in formation of mature amyloid fibrils, as determined by Congo red staining (see Figure S1 ). WT DJ-1 effectively inhibits the formation of soluble αSyn protofibrils at a molar ratio of 1:2 (DJ-1: αSyn). In contrast, L166P mutant DJ-1, GST, and Hsp27 ( Figure 2 A and 2 B) failed to inhibit the generation of αSyn protofibrils. Figure 2 DJ-1 Inhibits Formation of αSyn Protofibrils and Fibrils In Vitro (A) Purified αSyn (200 μM) was incubated for 2 h at 55 °C in the presence of WT DJ-1, L166P mutant DJ-1, GST, or Hsp27 (all at 100 μM). WT DJ-1 inhibits accumulation of αSyn protofibrils in vitro, while L166P mutant DJ-1, GST, and Hsp27 do not. (B) Suppression of αSyn protofibril formation by WT DJ-1 (in triplicate) was quantified as compared to GST (as a negative control) and mutant L166P DJ-1. Data are shown as the mean ± SEM and were analyzed by ANOVA with Fisher's post-hoc test. * p < 0.05. (C) Purified αSyn (200 μM) was incubated for 1 wk at 37 °C in the presence of WT DJ-1, L166P mutant DJ-1, or GST (all at 100 μM). WT DJ-1 inhibits formation of mature Congo red–positive αSyn fibrils. Data are shown as the mean ± SEM and were analyzed by ANOVA with Fisher's post-hoc test. * p < 0.05. αSyn protofibrils have been shown to be an intermediate in the formation of mature amyloid fibrils. Because DJ-1 chaperone activity is effective at inhibiting the accumulation of αSyn protofibrils, we sought to investigate the role of this activity in the generation of Congo red–positive mature fibrils. Congruently, WT DJ-1 inhibited formation of Congo red-positive αSyn fibrils, while L166P DJ-1 and GST did not ( Figure 2 C). Thus, DJ-1 seems to inhibit formation of αSyn fibrils by preventing formation of αSyn high molecular weight oligomers, or protofibrils. Interestingly, PD-associated clinical mutations in αSyn appear to accelerate oligomerization and protofibril formation ( Volles et al. 2001 ). DJ-1 Chaperone Activity In Vivo We sought to investigate the chaperone activity of DJ-1 toward αSyn in vivo. αSyn has been shown to form aggregates that consist of both protofibrils and mature amyloid fibrils in the context of oxidative stress (such as FeCl 2 treatment [ Lee and Lee 2002 ; Lee et al. 2002 ]) in neuroblastoma cells. We evaluated the activity of DJ-1 overexpression on αSyn aggregation in this tissue culture model system. Briefly, CAD murine neuroblastoma cells ( Staropoli et al. 2003 ) were transfected with Flag epitope-tagged αSyn (Flag-αSyn), differentiated via serum withdrawal, and exposed to FeCl 2 (2 mM) for 18 h. Treatment with FeCl 2 induced accumulation of αSyn in the Triton X-100-insoluble fraction, which has been shown to correlate with αSyn protofibrils ( Lee and Lee 2002 ). Overexpression of WT DJ-1, but not L166P clinical mutant DJ-1, significantly inhibited the accumulation of Triton X-100-insoluble αSyn ( Figure 3 A and 3 B). DJ-1 overexpression did not alter the accumulation ( Figure 3 A) or half-life of soluble αSyn, as determined by pulse-chase kinetic analysis ( Figure S2 ). Thus, DJ-1 overexpression is sufficient to inhibit the formation of αSyn aggregates in vivo, consistent with the in vitro analysis. Figure 3 Overexpression of WT DJ-1 Inhibits Aggregation of αSyn In Vivo (A) CAD murine neuroblastoma cells were transfected with Flag-αSyn along with WT DJ-1, L166P clinical mutant, or vector alone, and were differentiated in vitro via serum withdrawal. Cells were subsequently treated with 2 mM FeCl 2 (Fe), 5 μM lactacystin (LC), or media alone (0). Triton X-100-soluble (Tx-100 sol) and Triton X-100-insoluble (Tx-100 insol) fractions were analyzed by Western blotting. Upon FeCl 2 treatment, αSyn accumulates in the Triton X-100-insoluble fraction, and accumulation of insoluble αSyn is inhibited by overexpression of WT DJ-1 (left) but not the L166P clinical mutant (right). (B) Triton X-100-insoluble αSyn as quantified by NIH Image J of a Western blot (from [A]). (C) Heterozygous (+/–) and DJ-1 deficient (–/–) ES cells were differentiated using the embryoid body protocol. Cells were transfected with Flag-αSyn (F-αSyn), and, after 48 h, treated with 2 mM FeCl 2 or with media alone for 18 h. Cell lysates were analyzed by Western blotting for αSyn or β-actin. In the Triton X-100-soluble fraction (Tx-100 sol), DJ-1 accumulated to a similar extent in the knockout and control cells. In contrast, αSyn accumulation in the insoluble pool (Tx-100 insol) was detectable only in the knockout cells, and this was further promoted by FeCl 2 treatment. (D) CAD cells transfected with Flag-αSyn (F-αSyn) along with WT DJ-1 (or vector alone) were treated with 2 mM FeCl 2 or media alone for 18 h. Triton X-100-soluble cell lysates were immunoprecipitated with a mouse monoclonal antibody for the Flag epitope and Western blotted for DJ-1. FeCl 2 treatment induces association of Flag-αSyn with WT DJ-1. Lysates represent 20% input of the immunoprecipitation (IP α-Flag). The Triton X-100 soluble pool of DJ-1 is reduced by αSyn overexpression (but not vector control), particularly in the context of FeCl 2 treatment (bottom). (E) DJ-1 colocalizes with αSyn in the Triton X-100-insoluble fraction upon FeCl 2 treatment. The Western blot from (A) was stripped and reprobed for DJ-1. To investigate whether DJ-1 is necessary to inhibit αSyn aggregation in vivo, we utilized DJ-1 “knockout” embryonic stem (ES) cells, which display increased sensitivity to oxidative stress. DJ-1 homozygous knockout or control heterozygous ES cells (heterozygous cells were used as controls because they were the source of the knockout subclones) were differentiated in vitro using the embryoid body protocol ( Martinat et al. 2004 ) and transfected with Flag-αSyn or control vector. Upon differentiation, both endogenous αSyn and transfected Flag-αSyn are accumulated to a similar extent in the soluble fraction of knockout and control cell lysates, as determined by Western blotting with an antibody for αSyn. In contrast, DJ-1-deficient cells (but not control cells) additionally accumulate Triton X-100-insoluble αSyn (both endogenous αSyn and transfected Flag-αSyn), which likely corresponds to protofibril aggregates ( Lee and Lee 2002 ). As predicted, FeCl 2 treatment further promoted the accumulation of insoluble αSyn in DJ-1-deficient cells but not in control heterozygous cells ( Figure 3 C). Interestingly, transfection of Flag-αSyn into undifferentiated knockout or control ES cells in the presence or absence of FeCl 2 treatment did not lead to the accumulation of insoluble Flag-αSyn (see Figure S2 ), consistent with a prior study suggesting a role for neuronal differentiation in the generation of insoluble αSyn aggregates ( Lee et al. 2002 ). To investigate the mechanism of DJ-1 activity toward αSyn, we performed coimmunoprecipitation experiments on untreated and FeCl 2 -treated CAD cells transfected with DJ-1 and Flag-αSyn (or control vector) as above. Triton X-100-soluble cell lysates were immunoprecipitated with a mouse monoclonal antibody for the Flag epitope, and Western blots were probed with a rabbit polyclonal antibody for DJ-1. DJ-1 failed to interact with Flag-αSyn in the absence of pretreatment with FeCl 2 , but an association was evident in FeCl 2 -treated cell lysates ( Figure 3 D). Furthermore, overexpression of αSyn (but not vector control) leads to a reduction in the soluble pool of DJ-1, particularly in the context of FeCl 2 treatment, indicating that DJ-1 additionally associates with an insoluble fraction of αSyn ( Figure 3 D, bottom panel). Consistent with this, we found that a significant fraction of DJ-1 protein localizes to the insoluble fraction upon FeCl 2 treatment ( Figure 3 E) in cells that have been cotransfected with Flag-αSyn. To further evaluate αSyn aggregation, we performed immunohistochemical analyses of CAD cells transfected with αSyn along with DJ-1 or control vector ( Figure 4 ). Overexpression of αSyn in neuroblastoma cells induces the formation of visible cytoplasmic aggregates ( Lee and Lee 2002 ) ( Figure 4 J– 4 L). Additional overexpression of WT DJ-1 significantly decreased the number of cells containing αSyn aggregates ( Figure 4 D– 4 F and 4 M), whereas the L166P DJ-1 mutant fails to do so ( Figure 4 G– 4 I and 4 M). However, DJ-1 does not appear to colocalize with αSyn aggregates, suggesting that DJ-1 functions at an early step in the formation of mature aggregates ( Figure 4 N– 4 S). Figure 4 DJ-1 Inhibits Formation of αSyn Intracytoplasmic Inclusions (A–L) CAD murine neuroblastoma cells were transfected with WT DJ-1 (A–F), L166P DJ-1 (G–I) or vector control (J–L), along with Flag-αSyn (D–L) or vector control (A–C) and differentiated in vitro by serum withdrawal for 72 h. Cells were fixed and stained with a mouse monoclonal antibody for αSyn and ToPro3, a nuclear dye, and images were obtained by confocal microscopy. Transfection of Flag-αSyn induced formation of intracytoplasmic inclusions (arrows). Scale bar, 20 μm. (M) Quantification of cells with inclusions was performed on ten random images from each of three wells per condition. Images were quantified by an observer blinded to the experiment. A significantly lower percentage of cells harbor inclusions in the context of WT DJ-1 overexpression. Aggregation is expressed as the percentage of cells containing αSyn aggregates per frame. Total cell number per frame, as determined by ToPro3 staining, did not differ significantly ( Figure S3 ). Data are shown as the mean ± SEM, and were analyzed by ANOVA with Fisher's post-hoc test. * p < 0.05. (N–S) Cells were fixed and stained with a monoclonal antibody for αSyn and a polyclonal antibody that recognizes both transfected human DJ-1 and endogenous murine DJ-1. DJ-1 does not appear to colocalize with the αSyn aggregates. Scale bar, 20 μm. In a separate set of experiments, we assayed the ability of DJ-1 to inhibit aggregation of a second substrate, neurofilament light subunit (NFL). Overexpression of a mutant form of human NFL, Q333P, by transient transfection of CAD murine neuroblastoma cells, leads to the accumulation of intracytoplasmic inclusions ( Perez-Olle et al. 2002 ). Co-overexpression of WT DJ-1 along with mutant NFL significantly inhibited the accumulation of NFL inclusions ( Figure 5 ), whereas overexpression of the L166P Parkinsonism-associated mutant form of DJ-1 with NFL failed to inhibit the accumulation of aggregates. Coimmunostaining for DJ-1 and NFL indicated that DJ-1 does not colocalize with the NFL inclusions ( Figure 5 M– 5 R). DJ-1 did not appear to alter the expression of NFL ( Figure S3 ). These data are consistent with our analysis of DJ-1 chaperone activity toward αSyn and indicate that DJ-1 harbors chaperone activity toward a range of substrates in vivo. Figure 5 DJ-1 Inhibits Formation of NFL Intracytoplasmic Inclusions (A–L) CAD cells were transfected with an aggregation-prone mutant NFL (Q333P) plasmid, as well as WT human DJ-1 plasmid (that also harbors GFP; E–H), L166P mutant DJ-1 (that also harbors GFP; I–L), or control GFP vector (A–D). After 72 h in culture, cells were fixed and stained with a mouse monoclonal antibody for NFL and ToPro3, a nuclear dye. Scale bar, 100 μm. (M–R) CAD cell transfectants, as above, were fixed and stained with a polyclonal antibody for NFL ( Perez-Olle et al. 2002 ) along with a mouse monoclonal antibody specific for the transfected human DJ-1. Scale bar, 20 μm. (S) Quantification of CAD cell NFL aggregates was performed using confocal microscopy. Images from tenrandomly selected fields in each of three wells were quantified for the presence of aggregates for each condition and presented as a percentage of total cells per field. Total cell number was determined by ToPro3 nuclear staining and did not differ significantly ( Figure S3 ). Data are shown as the mean ± SEM and were analyzed by ANOVA with Fisher's post-hoc test. * p < 0.05. DJ-1 Function Requires Cysteine 53 The DJ-1 crystal structure suggests the presence of two highly reactive cysteines, cysteine 106 ( Lee et al. 2003 ; Wilson et al. 2003 ) and cysteine 53 ( Honbou et al. 2003b ). To test whether reactive cysteines play a critical role in the function or regulation of DJ-1 activity, we mutagenized each cysteine in DJ-1 to alanine ( Figure 6 ). Surprisingly, mutation of cysteine 106, at the predicted nucleophile elbow of DJ-1, does not alter the basal activity ( Figure 6 A) or the DTT sensitivity (See Figure S1 ) of DJ-1 chaperone function. In contrast, mutation of cysteine 53, which is present at the dimeric interface of DJ-1, completely abrogates chaperone activity. Similarly, mutation of all three cysteines in DJ-1 (cysteine 106, cysteine 53, and cysteine 47) leads to the loss of chaperone function. The cysteine mutations do not alter DJ-1 dimerization ( Figure 6 D) or the apparent stability of DJ-1 in vivo (unpublished data), unlike the L166P Parkinsonism-associated mutation. Figure 6 DJ-1 In Vitro Chaperone Activity and In Vivo Oxidative Stress Protection Activity Require Cysteine 53 but Not Cysteine 106 (A) DJ-1 cysteine-to-alanine mutants C106A, C53A, and a triple mutant that harbors mutations at all three cysteines in DJ-1 (C106A/C53A/C46A), as well as L166P, were tested for in vitro chaperone activity by CS aggregation suppression assay. (B) Self-association of DJ-1 cysteine mutants. Murine neuroblastoma CAD cells were transiently cotransfected with Flag-tagged human DJ-1 vectors (either WT or mutant) along with WT YFP-tagged human DJ-1. Lysates were immunoprecipitated with anti-Flag antibodies and probed by Western blotting with an antibody specific for human DJ-1. WT Flag-DJ-1, C106A DJ-1, C53A DJ-1, and C106A/C53A/C46A DJ-1 effectively coprecipitated WT GFP-DJ-1, whereas the L166P mutant Flag-DJ-1 failed to do so. Lysates represent 20% of the input for the immunoprecipitate; Flag-DJ-1 migrates at 22 kDa, and YFP-DJ-1 migrates at 50 kDa. (C) DJ-1-deficient ES cells were transiently transfected with vector alone, WT DJ-1, or DJ-1 cysteine mutants, and exposed to 10 μM H 2 O 2 for 15 h followed by MTT assay. The viability of the cells in the absence of drug treatment was not altered by the expression of WT or mutant DJ-1). Data are shown as the mean ± SEM and were analyzed by ANOVA with Fisher's post-hoc test. * p < 0.05 (D) Expression levels of WT and mutant forms of DJ-1 were comparable as determined by Western blotting for human DJ-1 and β-actin. DJ-1-deficient ES cells display increased sensitivity to oxidative stress, and this phenotype can be “rescued” by overexpression of WT DJ-1 but not PD-associated L166P mutant DJ-1 ( Martinat et al. 2004 ). We further investigated the activity of the cysteine-mutant forms of human DJ-1 in vivo in the complementation of DJ-1-deficient ES cells. Cysteine 106–mutant DJ-1 robustly rescued DJ-1 knockout cells from H 2 O 2 toxicity, consistent with the in vitro chaperone activity assay ( Figure 6 C). In contrast, cysteine 53 and the triple-cysteine mutant forms of DJ-1 failed to protect from H 2 O 2 toxicity. These data support a role for cysteine 53–dependent chaperone activity in DJ-1-mediated ROS protection, and demonstrate a direct correlation between DJ-1 in vitro chaperone activity and cellular protection from oxidative stress. Our data are consistent with the prior observation that mutation of cysteine 53 to alanine abrogates the low–isoelectric point variant that is induced by oxidative stress ( Honbou et al. 2003a ). Discussion We provide evidence that DJ-1 functions as a cytoplasmic redox-sensitive molecular chaperone in vitro and in vivo. This activity extends to αSyn and the neurofilament subunit NFL, proteins implicated in PD pathology. In a companion article ( Martinat et al. 2004 ), we show that DJ-1 deficiency sensitizes cells to oxidative stress, leading to increased apoptosis in the context of an ROS burst. Taken together, our data strongly support the notion that DJ-1 functions as a redox-dependent protein chaperone to mitigate molecular insults downstream of an ROS burst. Oxidation-modified proteins have been shown to accumulate in the context of normal aging and PD, and may participate in the generation of protein aggregates in neurodegenerative disorders ( Jenner 2003 ). It is of interest to identify relevant in vivo substrates for DJ-1 activity in the context of DNs in PD. Our data suggest that DJ-1 activity extends to multiple targets, reminiscent of other small protein chaperones ( Gusev et al. 2002 ), and consistent with this, DJ-1 activity is not ATP-dependent (unpublished data). Candidate substrates for DJ-1 chaperone activity in the context of PD include αSyn and neurofilament proteins, based on their presence in PD protein inclusions. Our data suggest that DJ-1 functions to suppress protein aggregates in the cytoplasm. It is possible that DJ-1 plays additional roles in the mitochondria or nucleus, as has been suggested ( Bonifati 2003 ; Canet-Aviles 2004 ), although DJ-1 appears to remain localized diffusely in the cytoplasm with or without toxin treatment in our studies (see Figure S2 ). Our data indicate that DJ-1 can suppress an early step in the formation of αSyn aggregates, the generation of high molecular weight oligomers (protofibrils). Interestingly, it has been suggested that such protofibrils, rather than the large fibrillar aggregates, may underlie αSyn toxicity in vivo ( Volles et al. 2001 ). DJ-1 inhibits the aggregation of αSyn in differentiated cells in vivo, and loss of DJ-1 leads to increased accumulation of insoluble αSyn. DJ-1 appears to associate with αSyn in the Triton X-100-soluble fraction of FeCl 2 -treated lysates, and DJ-1 colocalizes with αSyn in the Triton X-100-insoluble fraction in the context of FeCl 2 treatment. However, DJ-1 does not colocalize with the punctate protein aggregates visible by immunostaining in the case of either αSyn or NFL. This supports the notion that DJ-1 functions at an early step in the aggregation process, when the substrate protein may be misfolded, but has not yet formed a mature aggregate. We hypothesize that DJ-1 may promote the degradation of such misfolded proteins, either through the proteasome or through other cellular pathways such as chaperone-mediated autophagy. A recent study investigated the chaperone activity of WT DJ-1 in vitro toward CS and concluded that redox regulation was not a significant factor ( Lee et al. 2003 ). This is most likely a consequence of the use of only oxidizing conditions (0.5 mM H 2 O 2 ) but not reducing conditions in the described chaperone assays ( Lee et al. 2003 ). A second report failed to detect DJ-1 chaperone activity in vitro ( Olzmann et al. 2003 ), but importantly, this study employed only reducing conditions in which DJ-1 chaperone activity is abrogated. In the present study we demonstrate that DJ-1 chaperone activity is inhibited by reducing conditions, and can be stimulated by oxidation. Thus, in the normal reducing environment of the cell, DJ-1 may be inactive. Production of ROS and alteration of the redox state of the cytoplasm may activate DJ-1 chaperone activity as a mechanism of coping with protein aggregation and misfolding. We find that that the PD-associated L166P mutant DJ-1 fails to function as a molecular chaperone in vivo or in vitro. Consistent with this, in a companion article ( Martinat et al. 2004 ), we show that this mutant fails to complement DJ-1 knockout cells in vivo, even when overexpressed at artificially high levels ( Martinat et al. 2004 ). Furthermore, the L166P mutant form fails to dimerize even when expressed at WT levels. Thus, although prior studies ( Miller et al. 2003 ) and our analyses (unpublished data) have found that the L166P PD-associated DJ-1 mutation leads to decreased protein stability, it is apparent that even overexpression of the L166P mutant protein does not restore function. The L166P clinical phenotype is not due simply to reduced levels of DJ-1 protein, and, furthermore, we do not observe evidence of altered subcellular localization of the L166P mutant protein ( Figure 4 M- 4 R). Rather, our studies favor a model by which the pathological mechanism of this mutation is a consequence of altered structure and resultant loss of function. Mutation of cysteine 53 in DJ-1 abrogates both chaperone and protective functions of this protein. Interestingly, cysteine 53 has previously been implicated as a reactive cysteine required for the in vivo modification of DJ-1 to a lower isoelectric point in response to oxidative stress ( Honbou et al. 2003a ), consistent with a role for such redox regulation in vivo. In contrast, cysteine 106, which has been reported to be sensitive to oxidative modification in vitro ( Wilson et al. 2003 ), does not appear to be required for the in vitro and in vivo DJ-1 activities. Materials and Methods Cell culture and in vivo assays. Undifferentiated ES cells, CAD neuroblastoma cells, and HeLa cells were cultured using standard techniques ( Abeliovich et al. 2000 ; Staropoli et al. 2003 ). Transfections were performed using Lipofectamine 2000 (Life Technologies, Carlsbad, California, United States) for 18–36 h according to the manufacturer's instructions. For in vivo αSyn aggregation assays, CAD cells were transfected with Flag-αSyn (pcDNA3) or DJ-1 (pCMS), and medium was replaced with medium without serum. Cells were cultured without serum to induce differentiation for 48 h post-transfection, at which time the medium was exchanged for medium alone or containing 2 mM FeCl 2 and 5 μM lactacystin. Cells were treated with toxin for 18 h, then lysed or fixed with 4% PFA. Cell lysis was performed by resuspending cells in 50 mM Tris (pH 7.6), 150 mM sodium chloride, 0.2% Triton X-100, and protease inhibitor cocktail (Sigma, St. Louis, Missouri, United States). Cells were incubated on ice for 20 min and Triton X-100-soluble and -insoluble fractions were separated via centrifugation at 13,000 rpm for 15 min. Quantification of CAD cell aggregates was performed using a Zeiss LSM Pascal confocal microscope (Zeiss, Oberkochen, Germany) with a 20× long working distance lens. Images were imported to NIH Image J for analysis. Images from tenrandomly selected fields in each of three wells were quantified for each condition. Cells containing at least one intracytoplasmic aggregate, independent of size or number per cell, were scored as positive for aggregates. This number was divided by the number of transfected cells per field, determined by GFP fluorescence. ES cell culture and in vitro differentiation Mouse ES cells were propagated and differentiated as described ( Martinat et al. 2004 ). ES cells were differentiated via the embryoid body protocol. Cells were transfected with Flag-αSyn (pCMS) using Lipofectamine 2000 as per the manufacturer's instructions. 48 h post-transfection, cells were treated with 2 mM FeCl 2 (or media alone) for 18 h. Antibodies. An anti-DJ-1 rabbit polyclonal antibody was generated against the synthetic polypeptide QNLSESPMVKEILKEQESR, which corresponds to amino acids 64–82 of the mouse protein. Antiserum was produced using the Polyquick polyclonal antibody production service of Zymed Laboratories (South San Francisco, California, United States). The antiserum was affinity purified on a peptide-coupled Sulfolink column (Pierce Biotechnology, Rockford, Illinois, United States) according to the manufacturer's instructions. Antibody was used at a dilution of 1:200 for immunohistochemistry and Western blotting as described ( Staropoli et al. 2003 ). Immunohistochemistry was performed with a rabbit polyclonal antibody to DJ-1 ( Martinat et al. 2004 ), TH (PelFreez, Rogers, Arizona, United States; dilution 1:1000), and a rabbit polyclonal antibody to GABA (Sigma; dilution 1:1000). Western blotting was performed using monoclonal antibody to DJ-1 (Stressgen Biotechnologies, San Diego, California, United States; dilution 1:1000), a monoclonal antibody to αSyn LB509 antibody (Zymed), and a monoclonal antibody to β-actin (Sigma; dilution 1:500). Mouse monoclonal antibody to NFL (Sigma; dilution 1:200) and rabbit polyclonal antibody to NFL ( Perez-Olle et al. 2002 ). ToPro3 (Molecular Probes, Eugene, Oregon, United States; dilution 1:1000) was used as a nuclear dye. Expression vectors. DJ-1 cDNA was PCR amplified from human liver cDNA (Clontech, Palo Alto, California, United States) and cloned into the expression vectors pET-28a (Novagen, Madison, Wisconsin, United States) or pcDNA3.1 (Invitrogen, Carlsbad, California, United States). Flag-DJ-1 and all described mutants were generated by PCR-mediated mutagenesis using standard techniques. In vitro preparation of WT and mutant DJ-1. His-tagged recombinant human WT or L166P DJ-1 was produced in E. coli BL21 cells induced with 1 mM IPTG for 4 h at 37 °C. Bacterial pellets were resuspended in 50 mM sodium phosphate (pH 6.8) and 300 mM sodium chloride, and lysed by sonication. Lysates were cleared by centrifugation at 20,000 × g for 20 min, and the supernatant was incubated with NTA-Ni-conjugated agarose resin for 1 h at 4 °C. The resin was subsequently washed five times with 20 resin volumes of lysis buffer containing 20 mM imidazole, and protein was eluted in five fractions of two resin volumes of lysis buffer containing 250 mM imidazole. Recombinant protein elutions were confirmed to be of > 99% purity by SDS-PAGE and colloidal Coomassie staining. Aggregation assays. CS aggregation was performed in 40 mM HEPES (pH 7.8), 20 mM potassium hydroxinde, 50 mM potassium chloride, and 10 mM ammonium sulfate, and monitored in a thermostat-controlled fluorescence spectrophotometer with excitation and emission wavelengths at 500 nm and slit widths at 2.5 nm. Insulin aggregation was performed as described ( Giasson et al. 2000 ). CS, insulin, RNase A, and GST were obtained from Sigma; human Hsp27 was obtained from Stressgen. αSyn protofibril and fibril formation assays were performed essentially as described (Uversky et al.). Briefly, protofibrils were formed by incubation of 200 μM WT synuclein with 100 μM DJ-1 or control chaperone protein in PBS for 2 h at 55 °C. Samples were mixed with SDS loading buffer and analyzed by SDS-PAGE and Western blotting using αSyn LB509 antibody (Zymed). Quantitation of high molecular weight αSyn was performed using NIH Image J. Integrated pixel intensity of high molecular weight synuclein for each sample was normalized to monomeric synuclein intensity. For fibril formation, αSyn and chaperone proteins (as described above) were incubated with shaking for 1 wk at 37 °C. Fibril formation was assessed by Congo red ( Conway et al. 2000b ). Supporting Information Figure S1 Additional Structural and Functional Analyses of DJ-1 In Vitro (A) DJ-1 catalase activity was quantified as compared to catalase I (5 μg/ml). DJ-1 does not display catalase activity even at concentrations as high as 5 mg/ml. (B) Addition of DJ-1 at 5 mg/ml does not alter catalase activity of the catalase I-positive control, indicating that there are no inhibitory elements present in the DJ-1 preparation. (C) Purity of bacterially produced DJ-1 utilized in the in vitro assays was assessed to be > 99% by SDS-PAGE and colloidal Coomassie staining. (D) GST thermal aggregation (0.4 μM, black circles) is suppressed by WT DJ-1 (2 μM, red squares) and by positive control Hsp27 (2 μM, green stars), but not by L166P mutant DJ-1 (2 μM, blue triangles) or by RNase A (2 μM, purple diamonds). (E) Far-ultraviolet CD spectra of WT DJ-1 (blue triangles) and the L166P mutant (red squares); mean residue ellipticity (Θ) equals °C · cm 2 · dmol −1 . The mutant protein displays significantly reduced secondary structure. CD spectra of DJ-1 (40 μM in 10 mM PBS [pH 7.4]) were recorded on an Aviv 62A sCD spectrometer at 4 °C in a 0.02-cm path length cuvette, and α-helix and β-sheet content were estimated as described ( Sreerama and Woody 2003 ). Based on an initial evaluation of the spectra, the WT spectrum was analyzed using a basis set appropriate for folded proteins, whereas the mutant spectrum was analyzed using a basis set suited for unstructured proteins. Thermal stability was determined by monitoring the change in mean residue ellipticity ([Θ], equal to °C · cm 2 · dmol −1 ) at 222 nm as a function of temperature. Thermal melts were performed in 4 °C increments with an equilibration time of 1 min and an integration time of 30 sec, using a 0.1-cm path length cuvette. (F) Thermal denaturation curves for WT and mutant L166P DJ-1; mean residue ellipticity (Θ) 222 is equal to °C · cm 2 · dmol −1 at 222 nm. (G) Redox regulation is unaffected by the C106A mutation. Redox regulation of C106A DJ-1 was assayed via DTT inactivation (0.5 mM) in the CS aggregation suppression assay. (H) Protofibril preparations (as in Figure 2 A and 2 B, incubated for 2 h at 55 °C) do not contain Congo red–positive mature fibrils. Untreated αSyn preparations (open bars) and protofibril preparations (filled bars) were subjected to Congo red analysis as in Figure 2 C. (1.2 MB PDF). Click here for additional data file. Figure S2 Additional Studies of DJ-1 Chaperone Activity In Vivo (A) Undifferentiated ES cells were transfected with Flag-αSyn and treated with 2 mM FeCl 2 (Fe) or media alone (0) as described in Figure 3 . As expected, undifferentiated ES cultures do not express endogenous αSyn. Furthermore, the transfected Flag-αSyn does not accumulate in the Triton X-100-insoluble fraction of undifferentiated cells, in contrast to differentiated cultures. (B) Overexpression of WT DJ-1 does not significantly alter the half-life of soluble Flag-αSyn. CAD murine neuroblastoma cells were stably transfected with Flag-tagged human α-synuclein using standard techniques. 2 × 10 5 cells in a 24-well format were transiently transfected with eukaryotic expression constructs encoding WT human DJ-1 or empty vector. After 36 h, cells were starved for 1 h with DMEM lacking cysteine and methionine and supplemented with 8% dialyzed FBS. Cells were pulsed for 2 h with 10 μCi[ 35 S]-L-Met/L-Cys (EasyTides; Perkin Elmer, Wellesley, California, United States) per well, washed twice, and chased at the indicated intervals with complete medium. Flag-αSyn was immunoprecipitated with Flag antibody-conjugated agarose beads (Sigma), subjected to SDS-PAGE, and visualized by autoradiography. (C) Flag-αSyn from (B) was quantitated using NIH Image J. (815 KB PDF). Click here for additional data file. Figure S3 Additional Studies of DJ-1 Mutations (A) Overexpression of WT DJ-1 or L166P DJ-1 in the context of αSyn aggregation does not alter cell number. Cells from Figure 4 M were quantified via ToPro3 nuclear staining and are expressed as number of cells per field from ten independent fields in each of three wells. Data are shown as the mean ± SEM and were analyzed by ANOVA with Fisher's post-hoc test. * p < 0. (B) Overexpression of WT DJ-1 or L166P mutant DJ-1 in the context of Q333P mutant NFL aggregation does not alter cell number. GFP positive transfected cells from Figure 5 A– 5 L were quantified and are expressed as number of transfected cells per field from ten independent fields in each of three wells. Data are shown as the mean ± SEM and were analyzed by ANOVA with Fisher's post-hoc test. * p < 0. (C) Overexpression of WT DJ-1, but not L166P mutant DJ-1, rescues cells from Q333P mutant NFL toxicity. HeLa cells were transfected with Q333P mutant NFL along with WT human DJ-1, L166P mutant DJ-1, or vector control. After 72 h, cells were assayed by MTT reduction assay (which detects reduction of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide by metabolic enzymes) ( Martinat et al. 2004 ). Data are shown as the mean ± SEM and were analyzed by ANOVA with Fisher's post-hoc test. * p < 0. (D) C53A mutant DJ-1 is unable to rescue cells from Q333P mutant NFL toxicity. Undifferentiated ES cells were transfected with Q333P mutant NFL along with WT human DJ-1, C53A mutant DJ-1, or vector control. After 72 h, cells were assayed by MTT reduction assay ( Martinat et al. 2004 ). Data are shown as the mean ± SEM and were analyzed by ANOVA with Fisher's post-hoc test. * p < 0. (E) Coexpression of DJ-1 with NFL does not alter NFL expression levels. CAD cells were transfected with Q333P mutant NFL and vector, WT DJ-1, C53A mutant DJ-1, or L166P mutant DJ-1. Cells were differentiated for 72 h and lysed to produce Triton X-100-soluble and -insoluble fractions. Lysates were exposed to Western blotting with an antibody against transfected human NFL. NFL is present only in the insoluble fraction, and expression of WT or mutant DJ-1 does not alter NFL expression levels. (685 KB PDF). Click here for additional data file. Figure S4 DJ-1 Localization Does Not Appear Altered by FeCl 2 Treatment CAD cells were transfected with WT DJ-1 and differentiated by serum withdrawal for 72 h. Cells were treated with medium alone (A–F) or medium with 2 mM FeCl 2 (G–L) for 18 h prior to fixation with PFA. Cells were immunostained with rabbit anti-DJ-1 as described, followed by donkey anti-rabbit Cy5 (A, D, G, and J). Nuclei (B, E, H, and K) were visualized by incubation with the nuclear stain ToPro3 prior to imaging. (1.6 MB PDF). Click here for additional data file. Table S1 DJ-1 Lacks Protease and Antioxidant Activities (45 KB DOC). Click here for additional data file.

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Design and testing of low intensity laser biostimulator

Background The non-invasive nature of laser biostimulation has made lasers an attractive alternative in Medical Acupuncture at the last 25 years. However, there is still an uncertainty as to whether they work or their effect is just placebo. Although a plethora of scientific papers published about the topic showing positive clinical results, there is still a lack of objective scientific proofs about the biostimulation effect of lasers in Medical Acupuncture. The objective of this work was to design and build a low cost portable laser device for stimulation of acupuncture points, considered here as small localized biosources (SLB), without stimulating any sensory nerves via shock or heat and to find out a suitable method for objectively evaluating its stimulating effect. The design is aimed for studying SLB potentials provoked by laser stimulus, in search for objective proofs of the biostimulation effect of lasers used in Medical Acupuncture. Methods The proposed biostimulator features two operational modes: program mode and stimulation mode and two output polarization modes: linearly and circularly polarized laser emission. In program mode, different user-defined stimulation protocols can be created and memorized. The laser output can be either continuous or pulse modulated. Each stimulation session consists of a pre-defined number of successive continuous or square pulse modulated sequences of laser emission. The variable parameters of the laser output are: average output power, pulse width, pulse period, and continuous or pulsed sequence duration and repetition period. In stimulation mode the stimulus is automatically applied according to the pre-programmed protocol. The laser source is 30 mW AlGaInP laser diode with an emission wavelength of 685 nm, driven by a highly integrated driver. The optical system designed for beam collimation and polarization change uses single collimating lens with large numerical aperture, linear polarizer and a quarter-wave retardation plate. The proposed method for testing the device efficiency employs a biofeedback from the subject by recording the biopotentials evoked by the laser stimulus at related distant SLB sites. Therefore measuring of SLB biopotentials caused by the stimulus would indicate that a biopotential has been evoked at the irradiated site and has propagated to the measurement sites, rather than being caused by local changes of the electrical skin conductivity. Results A prototype device was built according to the proposed design using relatively inexpensive and commercially available components. The laser output can be pulse modulated from 0.1 to 1000 Hz with a duty factor from 10 to 90 %. The average output power density can be adjusted in the range 24 – 480 mW/cm2, where the total irradiation is limited to 2 Joule per stimulation session. The device is controlled by an 8-bit RISC Flash microcontroller with internal RAM and EEPROM memory, which allows for a wide range of different stimulation protocols to be implemented and memorized. The integrated laser diode driver with its onboard light power control loop provides safe and consistent laser modulation. The prototype was tested on the right Tri-Heater (TH) acupuncture meridian according to the proposed method. Laser evoked potentials were recorded from most of the easily accessible SLB along the meridian under study. They appear like periodical spikes with a repetition rate from 0.05 to 10 Hz and amplitude range 0.1 – 1 mV. Conclusion The prototype's specifications were found to be better or comparable to those of other existing devices. It features low component count, small size and low power consumption. Because of the low power levels used the possibility of sensory nerve stimulation via the phenomenon of shock or heat is excluded. Thus senseless optical stimulation is achieved. The optical system presented offers simple and cost effective way for beam collimation and polarization change. The novel method proposed for testing the device efficiency allows for objectively recording of SLB potentials evoked by laser stimulus. Based on the biopotential records obtained with this method, a scientifically based conclusion can be drawn about the effectiveness of the commercially available devices for low-level laser therapy used in Medical Acupuncture. The prototype tests showed that with the biostimulator presented, SLB could be effectively stimulated at low power levels. However more studies are needed to derive a general conclusion about the SLB biostimulation mechanism of lasers and their most effective power and optical settings.

Background Nowadays lasers are widely used in therapy and diagnostics. They have been adapted to many medical procedures ranging from surgery, oncology, physiotherapy, dentistry, dermatology and biostimulation. The non-invasive nature of laser biostimulation have made lasers an attractive alternative in Medical Acupuncture at the last 25 years. Unfortunately, there is still an uncertainty as to whether they work or their effect is just placebo. Although a plethora of scientific papers published about the topic showing positive clinical results, there is still a lack of objective scientific proofs about the biostimulation effect of lasers in Medical Acupuncture. The properties of acupuncture points, considered here as small localized biosources (SLB), have been extensively studied over the past 50 years. Research has shown SLB to be small area body regions, which exhibit unique, electrical, physiological and anatomical properties (e.g. high density of gap junctions, relatively low impedance etc.). They are considered to form groups, each group being arranged along a line, called meridian and related to an internal organ [ 1 - 4 ]. SLBs appear to be highly sensitive to mechanical, thermal, electrical or electromagnetic stimulation and are found to take place from the epidermis to a maximum depth of 2 cm [ 5 - 8 ]. It has been shown that with proper laser wavelength, intensity and collimation, low-level laser energy could be effectively delivered to SLB up to a 10 mm beneath the skin surface [ 9 ]. The objective of this work was to design and build a low cost portable laser device for effectively stimulation of SLB without exciting sensory nerves, and to find out a suitable method for objectively evaluating its efficiency. The attempt to define the optimal device parameters was based on the SLB properties, data about existing devices for low level laser therapy and on preliminary measurements performed in our laboratory. The latter suggest that the effect of SLB stimulation is also dependent on the polarization of the coherent emission in addition to its intensity, wavelength and modulation frequency. Therefore the device should provide a polarization adjustment, wide range of modulation frequencies, precise power settings and to have minimum size and cost. Methods Basic design and operating principle The block diagram of the proposed biostimulator design is shown in Fig. 1 . A laser diode is used as a coherent source of radiation because of its high brightness, efficiency, low cost and possibility for direct modulation. The emission wavelength is chosen in the visible range for minimum water absorption and haemoglobin reflection. The diode is driven by a microcontroller through an integrated driver and digital-to-analog converter (DAC). The user interface includes a liquid crystal display (LCD) and control buttons. The connection with the programmer is optional and is used only for in-circuit serial programming (ICSP). The optical system serves for beam collimation and polarization adjustment. Each stimulation session contains certain number of consecutive sequences of laser emission, where every sequence consists of continuous or pulse modulated laser emission as shown in Fig. 2 . There are two main operational modes: program mode and stimulation mode, and two output polarization modes: linearly and circularly polarized laser emission. In program mode, a set of different user-defined stimulation protocols can be created and memorized according to the requirements of the specific study. Figure 1 Block diagram of the of the laser biostimulator. Figure 2 Time diagram of pulse modulated laser output. The variable parameters of the laser output are: average output power, pulse width, pulse period, and sequence duration and repetition period. After each input parameter is selected, the total energy that would be delivered at the end of the stimulation session is automatically calculated and displayed. When defining the stimulation protocol, the software program reads the selected parameter value and automatically re-calculates the possible set of the other parameters, so that the user could not select inconsistent values or ones that would result in a total energy delivered that exceeds a certain safety limit. In stimulation mode the laser stimulus is applied according to the pre-programmed protocol. A quarter-wave retardation plate realizes the laser output polarization change, as shown in Fig. 3 . Within the retarder plane, the crystalline optic axis and the axis normal to it are also called fast or slow axis, depending on whether the uniaxial crystal is positive or negative. By rotating the retarder slightly about one of these axes, the retardation amount or the phase shift is varied. If the electric field vector of the incident linearly polarized beam and the quarter-wave retarder principal plane coincide, the emergent beam polarization remains the same as shown in Fig. 3a . If the angle θ between the electric field vector of the incident linearly polarized beam and the quarter-wave retarder principal plane is +45 degrees, the emergent beam is circularly polarized as shown in Fig. 3b . Reversing θ to -45 degrees reverses the sense of the circular polarization. The output from a single cavity laser diode is mainly linearly polarized, parallel to the laser junction. Although, spontaneous emission with a random polarization and with a polarization perpendicular to the laser junction is also present. For a diode operating near its maximum power the polarization ratio is typically greater than 100:1 but when operating near the threshold point, the ratio is considerably lower as spontaneous emission becomes more significant. Therefore a collimating lens followed by a linear polarizer is used since the retarder requires linearly polarized and normally incident light upon its plate over the whole power range. A single collimating lens, with good anti-reflection coating and large numerical aperture to efficiently capture the widely divergent perpendicular axis of the laser diode, is the most efficient and cost effective solution for the current application. Polarizers typically utilize birefringence, dichroism, optical activity, and polarization by reflection or by a metallic thin film [ 10 ]. For low-power and visual applications like the current one, sheet-type polarizers utilizing dichroism are normally used. Dichroic sheet polarizers subject one of the two orthogonal polarizations to strong absorption. They offer large apertures and acceptance angles, excellent extinction ratios and are simple to mount. Figure 3 Polarization change principle. The application can tolerate an elliptical beam shape and waveform aberrations, so circularization of the laser beam or correction of the waveform aberrations is not required. Method for testing the device efficiency The best way for testing the device efficiency is to obtain a biofeedback from the site of stimulation. A suitable non-invasive method is to measure the surface biopotential of the irradiated SLB site. However simultaneous stimulation and biopotential recording from a single SLB is technically difficult and inadequate, since the record may contain sham potentials due to local changes of the electrical conductivity of the irradiated skin. So a new method is proposed to avoid this problem. The method uses separate stimulation and measurement sites. Thus the laser stimulus is applied at SLB situated at the beginning of the meridian (e.g. the first point), where biopotential records are obtained from all the other easily accessible SLB lying distantly on the same meridian (see Fig. 4 ). Therefore measuring of SLB biopotentials caused by the stimulus would indicate that a biopotential has been evoked at the irradiated site and has propagated to the measurement sites, rather than being caused by local changes of the electrical skin conductivity. Extra electrodes have to be placed at non-SLB sites at close proximity to individual or group of closely spaced SLB recording electrodes, as a control. Due to the low intensity of the biostimulator output, even after prolonged irradiation, the subject has no thermal or tactile sensation and remains unaware of the application of the stimulus. Further more, there should be no visual, auditory or tactile cues that may indicate the activation of the laser. Figure 4 Method for testing the device efficiency. Practical biostimulator circuit The schematic of the practical biostimulator circuit, built according to the proposed design is shown in Fig. 5 . The microcontroller is implemented with the 8-bit RISC Flash microcontroller PIC16F84 with built in RAM and EEPROM memory [ 11 ]. It operates in HS oscillator mode with an 8 MHz crystal resonator. Power-on reset (POR), power-up timer and the oscillator start-up timer are enabled to allow for the power supply to rise to an acceptable level. The input/output ports are configured as follows: Figure 5 Practical biostimulator circuit. • RA0-RA2 – outputs used as LCD control signals • RA3-RA4 – outputs, used as DAC control signals • RB0-RB3 – either inputs or outputs, shared between the input control buttons B1-B4 and the LCD data bus DB4-DB7 • RB4-RB6 – outputs, used as control signals for the laser diode driver The LCD is implemented with the dot matrix alphanumeric character module U4 (Seiko Instruments L1682). It features low power consumption, high contrast, wide viewing angle, on-board controller and LSI driver (Samsung S6A0069). All functions required for the LCD drive are internally provided on the chip. Its internal operation is determined by signals sent from the microcontroller. These signals include: • Register select – RS • Read/Write – R/W • Data bus – DB4-DB7 (configured as inputs) • Read/Write Enable – E When ports RB0-RB3 are configured as inputs, the LCD data inputs DB4-DB7 have no practical influence on the logic levels set by push buttons B1-B4. LCD operation is also not affected since DB4-DB7 content is read only on logic high at E (U4-pin 6), set by the microcontroller [ 12 ]. When ports RB0-RB3 are configured as outputs, input buttons B1-B4 cannot alter their output logic levels because of resistor R2 connecting B1-B4 to common. Connector J1 is used for the microcontroller ICSP. The laser diode driver is implemented with the highly integrated circuit U1 (Analog Devices AD9660), which combines a very fast output current switch with onboard analog light power control loops. It gets feedback current from the laser diode built-in photo detector (U1-pin 8), feeds it to a transimpedance amplifier (TZA) and then to two analog feedback loops where the bias and the active power levels of the laser are set [ 13 ]. The two levels are proportional to the analog input voltage at the bias level input (U1-pin 14) and at the active level input (U1-pin 3). These inputs drive track and hold amplifiers with hold capacitors C4 and C5. The input voltage range on both inputs ranges from V ref to V ref + 1.6 V, requiring an offset of V ref to be created for common based signals. The bias level is chosen to be equal to V ref , where the active level is determined by the circuit realized with op-amp U5. It performs the level shift and scales the DAC output from V ref to V ref + 1.6 V. This solution is attractive because both DAC and op-amp can run off a single 5 V supply, and the op-amp does not have to swing rail-to-rail. The op-amp U5 output voltage level is given by: Since the monitor current is proportional to the laser diode light power, the feedback loops effectively control the laser power to a level proportional to the analog inputs. The bias control loops is periodically calibrated via U1-pin 15, where the active control loop is continuously calibrated via U1-pin 1. Resistors R3 and R4 are used to avoid floating of inputs U1-pin 15 and U1-pin 2 when microcontroller ports are in a high impedance mode. The laser pulse modulation is done by switching between the bias and the active power levels according to the logic level at U1-pin 2, where logic high turns the modulation current on. The gain resistor R5 matches the feedback loop transfer function to the laser/photo diode D1. Capacitor C6 optimizes the TZA response, with larger values to slow TZA response. Lower values increase TZA bandwidth but may cause oscillations. When input U1-pin 16 is logic high, the onboard disable circuit turns off the output drivers and returns the light power control loops to a safe state. It is used during initial power up of U1 and when the laser is inactive. In case that input U1-pin 16 floats (after POR or other reset conditions) the driver is disabled. When U1 is re-enabled the control loops are recalibrated. The DAC is implemented with the single 8-bit voltage output MAX517 (U3). It is controlled by the microcontroller via 2-wire serial interface (U3-pin 3, U3-pin 4), operates from a single power supply and swings rail-to-rail. POR ensures the DAC output is at zero volts when power is initially applied. It uses the power supply V dd as reference (U3-pin 8) filtered by R12 and C9. The DAC's full-scale output voltage ranges from 0 to V dd . Special attention was paid to the PCB layout design to minimize the crosstalk between analog inputs and digital outputs. The drawing of the practical optical system assembly is shown in Fig. 6 . It includes an aluminium housing, collimating lens, linear polarizer and a quarter-wave retarder. Turning manually the polarization adjustment cap, clockwise or anti-clockwise at 45°, changes the polarization from linear to circular left or right-handed. The laser source used is a high power AlGaInP (Mitsubishi ML1412R) laser diode, which provides a stable, single transverse mode oscillation with a typical emission wavelength of 685 nm and a maximum continuous output power of 30 mW. The diode is matched with a single collimating lens with a relatively large numerical aperture (NA) and a single layer of anti-reflection coating (MgF 2 ), optimized for 670 nm. The polarizer used is a linear polarizing film produced by aligning long chain polymers, which is then laminated in cellulose acetate butyrate (CAB) for durability and stiffness [ 14 ]. The quarter-wave retarder is implemented with polyvinyl-alcohol film supported by CAB. Figure 6 Optical system assembly. Results A prototype device was built according to the proposed design using inexpensive and commercially available components. Its optical and electrical characteristics are given in Table 1 . The microcontroller's internal RAM and EEPROM memory allows for a wide range of different stimulation protocols to be implemented and memorized. The integrated laser diode with its onboard light power control loop provides safe and consistent laser modulation. Because the application of the stimulus throughout the stimulation session is entirely controlled by the microcontroller, once the procedure is started, both subject and operator are unaware of whether the stimulus is active or not, except if intentionally staring the stimulated location. Thus true double-blind studies can be performed. The optical system presented, offers simple and cost effective way for beam collimation and polarization change. With the power levels used the possibility of sensory nerve stimulation via shock or heat is excluded. Table 1 Device specifications. Parameter Value Beam dimensions (-3dB) D ┴ D \\ 3.12 mm 1.7 mm Average output power 1–20 mW Average output power density 24–480 mW/cm 2 Maximum irradiation per stimulation session 2 Joule Collimating lens coupling efficiency (685 nm, f = 4.6 mm, NA = 0.53) 96 % Polarizer transmittance (685 nm, optic axis parallel to the diode junction) 75 % Quarter-wave retarder transmittance, (685 nm) 93 % Total optical system transmittance (685 nm) 67 % Output polarization linear/circular Laser class IIIb Pulse modulation 0–10 000 Hz Duty factor 10–90 % Pulse sequence duration 1–30 sec Pulse sequence repetition period 1–5 min Number of pulse sequences 1–20 Maximum power consumption (5 V) 600 mW The biostimulator was tested on the right Tri-Heater (TH) meridian of ten subjects according to the proposed method (see Fig. 4 ). The laser stimulus was applied at point TH-1, where recording electrodes were placed along the same meridian on points TH-3, 4, 5, 6, 7, 8, 9, 13, 15, 16, 17, 18, 21, 22 and 23, which were relatively easily accessible (see Fig. 7 ). Additional control electrodes were placed at non-SLB sites, approximately 2 cm apart from each SLB electrode, and the reference was positioned at the right ear lobe. Sample records of unprocessed real time SLB laser evoked potentials obtained from points TH-8, TH-15, TH-17 and their controls are shown in Fig. 8 . These signals were recorded with an active electrode amplifier [ 15 ] from one subject and are responses to the same stimulation, where the biostimulator settings used are given in Table 2 . The SLB evoked potentials appear like periodical spikes with a repetition rate from 0.05 to 10 Hz and amplitude range 0.1 – 1 mV. The preliminary results suggest that the repetition rate of the evoked SLB signals is proportional to the total energy delivered by the stimulus. Figure 7 Photo of the electrodes placement and stimulus application during a preliminary measurement. Figure 8 Evoked biopotentials acquired from points TH-8, TH-15, and TH-17 and their controls. Table 2 Device settings used during the preliminary measurements. Parameter Value Average output power 10 mW Average output power density 240 mW/cm 2 Pulse modulation 2000 Hz Duty factor 50 % Pulse sequence duration 10 sec Pulse sequence repetition period 1 min Number of pulse sequences 10 Output polarization Circular The noise present in the signals is mainly composed of electromyographic signals and noise from the electrode-skin interface. The first two signal records (TH-8 and control) contain ECG artifacts and additional electromyographic noise since those two electrodes were positioned relatively distant from the reference electrode. The frequency bandwidth was limited to 200 Hz by sixth order low-pass Bessel filter and the signals were sampled with 1 kHz. Recording to the EU regulation (Medical Device Directive 93/94) this device falls under class IIb in order to obtain the CE mark. The biostimulator prototype was categorized as Class IIIb laser product according to the International Standard for the Safety of Medical Laser Products IEC 601-2-22, as stated in Table 1 . Discussion The best solution for building a compact hand held biostimulator would be to design a custom made integrated circuit, but the cost would be much higher. We found a good alternative in using surface mount technology (SMT), commercially available integrated laser diode driver and a RISC Flash microcontroller. This solution resulted in a reduction in parts, size and power consumption. The proposed method for testing the device efficiency is very sensitive to precise electrode and stimulus positioning. Even a deviation of 3 mm from the exact SLB location may prevent the recording electrode from capturing signals from the source. The same deviation of the stimulus position also results of ineffective excitation of the targeted SLB and thus no SLB evoked potentials can be recorded. The method is also susceptible to the electrode-skin pressure, but not only due to its strong influence on the contact impedance. It was observed that the excessive electrode-skin pressure led to diminishing or even disappearing of the SLB signal, although the contact impedance was lower. This is most probably due to the pressure exerted on the SLB source that may affect the signal generation or transduction. Alternatively insufficient electrode-skin pressure led to excessive contact impedance and noise from the electrode-skin interface. The preliminary results suggest that a circularly polarized laser emission is most effective when used on the so-called Yang acupuncture meridians but not on Yin types. However more studies are needed to validate or disprove this observation. Conclusions The specifications of the prototype, built according to the proposed design, were found to be better or comparable to those of other existing devices. It features small size and low component count and power consumption. Because of the low power levels used the possibility of sensory nerve stimulation via the phenomenon of shock or heat is excluded. Thus senseless optical stimulation is achieved. The optical system presented offers simple and cost effective way for beam collimation and polarization change. The novel method proposed for testing the device efficiency allows for objectively recording of SLB potentials evoked by laser stimulus. Based on the biopotential records obtained with this method, a scientifically based conclusion can be drawn about the effectiveness of the commercially available devices for low level laser therapy used in Medical Acupuncture. The prototype tests showed that with the biostimulator presented, SLB could be effectively stimulated at low power levels. However more studies are needed to derive a general conclusion about the biostimulation mechanism of lasers in Medical Acupuncture and their most effective power and optical settings. Authors' contributions The authors contributed equally to this work

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539260

Quantitative evaluation of recall and precision of CAT Crawler, a search engine specialized on retrieval of Critically Appraised Topics

Background Critically Appraised Topics (CATs) are a useful tool that helps physicians to make clinical decisions as the healthcare moves towards the practice of Evidence-Based Medicine (EBM). The fast growing World Wide Web has provided a place for physicians to share their appraised topics online, but an increasing amount of time is needed to find a particular topic within such a rich repository. Methods A web-based application, namely the CAT Crawler, was developed by Singapore's Bioinformatics Institute to allow physicians to adequately access available appraised topics on the Internet. A meta-search engine, as the core component of the application, finds relevant topics following keyword input. The primary objective of the work presented here is to evaluate the quantity and quality of search results obtained from the meta-search engine of the CAT Crawler by comparing them with those obtained from two individual CAT search engines. From the CAT libraries at these two sites, all possible keywords were extracted using a keyword extractor. Of those common to both libraries, ten were randomly chosen for evaluation. All ten were submitted to the two search engines individually, and through the meta-search engine of the CAT Crawler. Search results were evaluated for relevance both by medical amateurs and professionals, and the respective recall and precision were calculated. Results While achieving an identical recall, the meta-search engine showed a precision of 77.26% (±14.45) compared to the individual search engines' 52.65% (±12.0) (p < 0.001). Conclusion The results demonstrate the validity of the CAT Crawler meta-search engine approach. The improved precision due to inherent filters underlines the practical usefulness of this tool for clinicians.

Background Healthcare has been steadily moving towards Evidence-Based Medicine (EBM) since the term was formally introduced in 1992 by a group led by Gordon Guyatt at McMaster University, Canada [ 1 - 3 ]. EBM promotes systematic literature review, critical appraisal skills and integrates scientific evidence with clinical expertise in the daily management of patients. The first three steps involved in the practice of EBM can comprehensively be summarized as a one-page written paper on a particular clinical topic, which is most commonly called a 'Critically Appraised Topic' (CAT) [ 4 ]. Different acronyms have emerged in various specialties, such as Best Evidence Topics (BET) [ 5 ] in emergency medicine and Evidence-Based Journal Club Reviews (EBJCR) [ 6 ] in pediatric critical care medicine. All these essentially provide physicians with a systematic method of formulating a clinical question and then critically evaluating the literature to answer the question posed. With the use of resources on the World Wide Web becoming common practice, several academic and healthcare organizations have built online CAT libraries for knowledge sharing with peer physicians. The repository of CATs has been growing steadily since the setup of the first accessible CATBank developed by the Centre for Evidence Based Medicine, Oxford in 1992 [ 7 ]. Among those, BestBETs developed by the Emergency Department, Manchester Royal Infirmary [ 8 ] and UMHS by the Department of Pediatric, University of Michigan Health System, Ann Arbor [ 9 ] hold hundreds of distinct topics. They are furnished with individual search engines for fast and direct access to a particular topic. Given the wealth of such medical information scattered in cyberspace, the effectiveness of locating the correct information has become an important issue [ 10 ]. The CAT Crawler application It is believed that more CATs will be added into the repositories as more people participate in EBM practice. However, the non-standardized electronic format of CATs has created much difficulty for physicians to access a particular topic. Accordingly, the CAT Crawler was developed at the Bioinformatics Institute, Singapore [ 11 , 12 ] to provide a one-stop search and download site for physicians by setting up a common platform to access eight popular online CAT libraries. CAT Crawler is freely accessible online [ 12 ]. The core component of the CAT Crawler is a meta-search engine. Its search is currently based on CAT resources from eight public online libraries [ 11 ]. Once the user chooses the libraries he intends to use in the search, information tailored to his needs can be produced. The matched results are sorted according to their origins. Following the user input of a query keyword, a partial search is done through information extracted during an off-line process from six websites that do not hold search engines. The remaining search is carried out by querying the two individual search engines at BestBETs and UMHS. Use of the CAT Crawler is expected to have a quantitative and qualitative improvement of the retrieved results by post-processing obtained raw results from both libraries. Motivation of the evaluation The work presented here aims to evaluate the quantity and quality of the obtained results from the CAT Crawler meta-search engine, and thus to evaluate the validity and the usefulness of the application. Recall and precision were estimated to measure the performance of this meta-search engine versus the two individual search engines at BestBETs and UMHS. Methods The workflow of this study is demonstrated in Figure 1 . Selection of ten query keywords To find a viable sample of keywords for a test search, the titles of all CATs stored in the two CAT libraries, namely BestBETs and UMHS were submitted to AnalogX Keyword Extractor , which is freely available online [ 13 ]. This led to a list of around 2000 keywords, of which approximately 500 were present in both libraries, of which ten were randomly chosen. In a second step, that list was curated so that only medically relevant keywords remained, excluding words such as and and day . Search for technically relevant documents in the dataset In order to be able to calculate recall as detailed below, the technical relevance of all documents in the dataset must be assessed. In this study, a document is called technically relevant for a given search term if it contains this term in the full-text. Perl scripts were developed to examine all CATs in the two libraries BestBETs and UMHS and the total number of relevant documents as per the above definition in each library was collected for further calculation. This was done for each selected keyword and the process was independent from the search using the three search engines: the CAT Crawler, BestBETs and UMHS. Relevance evaluation of the retrieval results In the next step, those ten keywords were submitted to the search engines at BestBETs and UMHS, and to the CAT Crawler meta-search engine. The retrieved links were evaluated for their relevance by 13 volunteers, who are categorized into three groups. Among them, one physician in Group I represents medical professionals, six persons in Group II represent people who were trained in biology or medicine, and six persons in Group III represent people who do not have any medical background. Calculation of recall and precision Recall and precision are two accepted measurements to determine the utility of an information retrieval system or search strategy [ 14 ]. They are defined as: Despite the relevance evaluation from 13 volunteers, it is necessary to know the total number of the relevant documents in a database for each query keyword in order to estimate the recall. In the present study, a particular CAT in a database was defined as technically relevant if the keyword could be found in its full-text article. The CAT Crawler is designed not to hold permanently any full-text CATs [ 11 ]. When a query is done choosing the option to search only BestBETs and UMHS, the total number of relevant document in its acute database is equivalent to the sum of the number of relevant documents in the two libraries BestBETs and UMHS. Accordingly, the recall and precision of the CAT Crawler meta-search engine are revised as: Similarly, the recall and precision of the search engines at BestBETs and UMHS are estimated based on the combined repository of the two individual sites. The revised formula are shown below: Performance evaluation of the CAT Crawler versus BestBETs and UMHS The averaged precision and recall over all evaluators are used to evaluate the performance of the CAT Crawler meta-search engine. These values are compared to the estimate based on the search results from the two individual search engines at BestBETs and UMHS. Results Ten keywords for the search engine evaluation According to the predefined selection criteria, the ten keywords listed in Table 1 were selected as the seed for a test search. The number of retrieved results from each search engine was gathered with respect to each keyword query. For the selected ten medically relevant keywords, the total number of matched results are 116, 65 and132 corresponding to the three search engines at BestBETs, UMHS and CAT Crawler. The difference of 49 retrievals between the CAT Crawler and the sum of BestBETs and UMHS reflects the meta-search engine's inherent filter function which is described previously [ 11 ]. Performance evaluation of the CAT Crawler versus BestBETs and UMHS To compare the performance of the CAT Crawler meta-search engine to that of the two individual search engines, recall and precision were computed and averaged over the evaluation of all 13 participators. The data recorded are shown in Table 2 . As the CAT Crawler meta-search engine is built upon the two individual search engines, the document collection for evaluation is the combined repository of BestBETs and UMHS. The retrieved relevant documents from the CAT Crawler are the same as that from the individual search engines. This leads to the identical recall for both cases (Table 2 ). The average precision is increased from the individual search engines' 52.65% (±12.0) to the CAT Crawler's 77.26% (±14.45). Figure 2 provides a more intuitive comparison corresponding to each keyword. Discussion The performance evaluation clearly places the CAT Crawler meta-search engine on par with the individual search engines at BestBETs and UMHS as far as recall is concerned, and well above them for precision (see Table 2 and Figure 2 ). According to these results, the application can be called successful: by using the CAT Crawler to look for relevant information at specific sites, the medical professional will obtain as much information as by going to the sites directly, but the precision of the obtained results will be higher. Benoit [ 15 ] has analyzed various methods of information retrieval and their impact on user behavior. He finds that users wish for greater interactive opportunities to determine for themselves the potential relevance of documents, and that a parts-of-document approach is preferable for many information retrieval situations. At present, the CAT Crawler allows a number of interactive opportunities [ 11 ], but their implementation would have no impact on the calculation of recall and precision under the condition of the present study. Benoit's reasoning should be kept in mind, however, for improving the user friendliness in the sense that some further useful filter functions can be included in future versions of the application. While such advanced search functions will be profitable when large datasets are studied, the currently still manageable information in the online CAT libraries [ 11 ] will serve the user better if initially displayed in a broader way. For example, some of the information displayed here may be older than 18 months, which makes it undesirable according to the strict rules for CAT updating as defined by Sackett et al [ 3 ]. Formally outdated information, however, may in a given situation still be "best evidence" and positively influence the decision-making. Use of filters to block aged information will certainly influence this process. Despite the encouraging results, some fundamental questions regarding the evaluation of this meta-search engine in particular, and also meta-search engines in general remain unsolved. With regard to recall, there is the theoretical possibility that manually searching all documents at a given repository will yield a higher recall for a given search term. In view of hundreds of CAT documents per repository, however, it seems unlikely that a human evaluator's attention will not wander, leading to less than optimal scrutiny of the documents and introducing a non-quantifiable error to the evaluation. This is a general problem of knowledge databases, especially when indexing is done by humans, whose decisions are not consistent. In a study of 700 Medline references indexed in duplicate, the consistency of main subject-heading indexing was only 68% and that for heading-subheading combinations was significantly less [ 16 ]. Also, in two studies [ 17 , 18 ] on Medline searching, there was considerable disagreement by those judging relevance of the retrieved documents regarding which documents were relevant to a given query. In order to overcome this problem, the number of documents that contained a given keyword as found by the keyword extractor was used as the basis for calculating the technical recall. This may (or may not) lead to numerical results for recall that differ from the absolute true value as determined above. As the same numbers are used throughout, however, the comparison of search results obtained by the individual search engines and the CAT Crawler meta-search engine remains valid. Critics have pointed out the over-reliance of researchers on the use of recall and precision in evaluation studies [ 18 ] and the difficulty to design an experiment that allows both laboratory-style control and operational realism [ 19 ]. For instance, recall may be of only little consequence once the user has found a useful document. Rhodes and Maes [ 20 ] evaluated both with a traditional field user test and then asked for relevance feedback. In their experiment, users gave a score 1–5 to each document that was delivered to calculate an overall average value for perceived precision. While a document can get a high score for precision, it may at the same time get a low score for practical usefulness. This was often due to the fact that the documents were already known to the users, in some cases had even been written by them. Accordingly, Rhodes and Maes [ 20 ] added features to the system that weeded out relevant documents that by some predefined criteria would not be useful. As a result, the measurable precision could be worse, but the overall usefulness could be better. In the study presented here, a similar approach was chosen in the instructions to the evaluators in the sense that they could make the distinction between 'irrelevant' (e.g. the retrieved document was only a web hosted clinical question) and 'medically irrelevant' (e.g. the word Appendicitis appeared only in the reference section of a document dealing with questions of abdominal pain relief). Due to the relatively small number, no difference could be detected between the various grades of relevance, and results were pooled to relevant/irrelevant and used for calculating recall and precision as described above. If a larger number of volunteers could be recruited, repetition of this evaluation might yield interesting results. Other approaches have been spawned to evaluating system effectiveness in order to minimize these problems with recall and precision. One example are task-oriented methods that measure how well the user can perform certain tasks [ 21 - 24 ]. These different approaches were not chosen in this study for a reason: the primary aim was to compare the search engines. Under the present restrictions, recall and precision allow to answer this question. Conclusions In summary, the data obtained from the analysis of search results obtained from identical queries submitted to the two CAT libraries at BestBETs and UMHS, using either their respective search engines or the CAT Crawler meta-search engine, showed a competitive recall, and superior precision of the meta-search engine compared to the individual search engines. Competing interests The author(s) declare that they have no competing interests. Authors' contributions PD participated in the design of the study, data analysis and drafting of the manuscript. LLW and SN generated raw data for the study. ML was involved in drafting the manuscript. AM designed the study and participated in the drafting of the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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548670

Activation of α7 nicotinic acetylcholine receptor by nicotine selectively up-regulates cyclooxygenase-2 and prostaglandin E2 in rat microglial cultures

Background Nicotinic acetylcholine (Ach) receptors are ligand-gated pentameric ion channels whose main function is to transmit signals for the neurotransmitter Ach in peripheral and central nervous system. However, the α7 nicotinic receptor has been recently found in several non-neuronal cells and described as an important regulator of cellular function. Nicotine and ACh have been recently reported to inhibit tumor necrosis factor-α (TNF-α) production in human macrophages as well as in mouse microglial cultures. In the present study, we investigated whether the stimulation of α7 nicotinic receptor by the specific agonist nicotine could affect the functional state of activated microglia by promoting and/or inhibiting the release of other important pro-inflammatory and lipid mediator such as prostaglandin E 2 . Methods Expression of α7 nicotinic receptor in rat microglial cell was examined by RT-PCR, immunofluorescence staining and Western blot. The functional effects of α7 receptor activation were analyzed in resting or lipopolysaccharide (LPS) stimulated microglial cells pre-treated with nicotine. Culture media were assayed for the levels of tumor necrosis factor, interleukin-1β, nitric oxide, interleukin-10 and prostaglandin E 2 . Total RNA was assayed by RT-PCR for the expression of COX-2 mRNA. Results Rat microglial cells express α7 nicotinic receptor, and its activation by nicotine dose-dependently reduces the LPS-induced release of TNF-α, but has little or no effect on nitric oxide, interleukin-10 and interleukin-1β. By contrast, nicotine enhances the expression of cyclooxygenase-2 and the synthesis of one of its major products, prostaglandin E 2 . Conclusions Since prostaglandin E 2 modulates several macrophage and lymphocyte functions, which are instrumental for inflammatory resolution, our study further supports the existence of a brain cholinergic anti-inflammatory pathway mediated by α7 nicotinic receptor that could be potentially exploited for novel treatments of several neuropathologies in which local inflammation, sustained by activated microglia, plays a crucial role.

Background The inflammatory response is in the first instance a mechanism of self-defense, set by the innate immune system against endogenous and exogenous insults, and essential for the survival of the organism. Inflammation must be tightly regulated as deficiency as well as excess in its response will result in pathological conditions, such as immunodeficiency or chronic inflammatory diseases [ 1 ]. In the last decade increasing evidence has highlighted the role of inflammation in most brain pathologies, including immune-mediated diseases such as multiple sclerosis, acute neurodegeneration following ischemia or trauma, and, more recently, chronic neurodegenerative diseases [ 2 ]. Among the endogenous mechanisms that regulate the inflammatory response, cross-talk between the immune and nervous systems play an important role. In particular, it has been shown that electric stimulation of the vagus nerve attenuates the inflammation during endotoxemia in rats [ 3 ], and that acetylcholine (ACh), the main parasympathetic neurotransmitter, effectively deactivates peripheral macrophages and inhibits the release of pro-inflammatory mediators, including the cytokine tumor necrosis factor-α (TNF-α). The ACh-dependent macrophage deactivation is mediated by the α7 subunit of the nicotinic ACh receptor (herein referred as α7 subunit), which is expressed in peripheral macrophages and has been described as essential for the so called "cholinergic anti-inflammatory pathway" [ 4 , 5 ]. Neuronal acetylcholine receptors (nAChRs) are ligand-gated ion channels, which belong to a large family of neurotransmitter receptors that includes the GABA A , glycine and 5-HT 3 receptors [ 6 ]. Each nAChR consists of five homologous or identical subunits arranged around a central ion channel whose opening is controlled by ACh, nicotine and other receptor agonists [ 6 ]. At least 8 α subunits (α2–9) and three β subunits (β2–4) have been identified and the combinatorial association of different α and β subunits results in a variety of nAChRs [ 7 ]. In addition to neurons and peripheral macrophages, several studies have demonstrated the expression of nAChRs in cell types both within and outside the nervous system [ 8 ]. In the CNS, the presence of nAChRs has been demonstrated in O 2 A-oligodendrocyte precursor cells but not in adult differentiated oligodendrocytes, suggesting that receptor expression is developmentally regulated [ 9 ]. Cultured hippocampal astrocytes express functional α7 receptors [ 10 ] and cortical astrocytes express both nicotinic and muscarinic receptors [ 11 ]. A functional α7 nicotinic receptor has been recently described in murine microglial cells [ 12 ]. In peripheral organs, human and rat epithelial and endothelial cells express functional α7 receptors, as well as other nicotinic subunits such as α3, α5, β2 and β4 [ 13 , 14 ]. Acute or chronic exposure to nicotine has been shown to influence cell viability and motility of bronchial epithelial and endothelial cells [ 13 ]. Furthermore, nicotine has been shown to suppress the antimicrobial activities of murine alveolar macrophages [ 15 ]. Lymphocytes present both muscarinic and nicotinic receptors and it has been demonstrated that the interaction with antigen presenting cells enhances the synthesis and release of ACh [ 16 ]. These observations suggest that ACh might function as an important modulator of cellular interactions and immune functions. Epidemiological studies indicate that nicotine, besides its immunosuppressive effects, may be protective against the development of neurodegenerative diseases such as Alzheimer disease (AD) and Parkinson's disease (PD) [ 17 ], in which a local inflammatory response is sustained by microglial cells, the largest population of phagocytes associated with the CNS. In normal healthy brain, microglial cells show a typical down-regulated or "resting" phenotype when compared to other tissue macrophages, but they rapidly react in response to a number of acute and chronic insults. Activated microglial cells could cause neuronal damage via liberation of free radicals as well as cytokines and toxic factors. Alternatively, microglia can exert neuroprotective functions by secreting growth factors or diffusible anti-inflammatory mediators, which contribute to resolve inflammation and restore tissue homeostasis [ 18 , 19 ]. Thus, understanding the molecular mechanisms governing microglial activation is essential to prevent tissue damage related to excessive activation. Since nicotine and ACh have been recently reported to inhibit TNF-α production in mouse microglial cultures, the aim of our study was to extend our knowledge on the effect of α7 subunit stimulation on the functional state of activated microglia. We first confirmed that rat microglia express the α7 subunit and we demonstrated that, in addition to inhibit TNF-α, the α7 agonist nicotine significantly up-regulated COX-2 expression and PGE 2 synthesis. Other important microglial products, such as interleukin-1β (IL-1β), nitric oxide (NO) and interleukin-10 (IL-10) were not affected or moderately decreased. Materials and methods Reagents All cell culture reagents were from Gibco (Grand Island, NY, U.S.A) and virtually endotoxin free (less then 10 E.U./ml as determined by the manufacturer). BCA protein assay was from Pierce (Rockford, Illinois). ELISA-kits for rat TNF-α and IL-10 were from Endogen Inc. (Woburn, MA). ED-1 monoclonal antibody was from Serotec (Oxford, UK). (±) Nicotine, α-bungarotoxin, FITC-α-bungarotoxin and lipopolysaccharide LPS (from Escherichia coli, serotype 026:B6) were from Sigma Chemical (St.Louis, MO). Rabbit polyclonal antibody against alpha 7 subunit was from Santa Cruz Biotechnology. Cell cultures Microglial cultures were prepared from 10–14 day mixed primary glial cultures obtained from the cerebral cortex of 1-day-old rats, as previously described [ 20 ] and in accordance with the European Communities Council Directive N. 86/609/EEC. Microglial cells, harvested from the mixed primary glial cultures by mild shaking, were resuspended in Basal Eagle's Medium (BME) supplemented with 10 % fetal calf serum, 2 mM glutamine and 100 μg/ml gentamicin, and plated on uncoated plastic wells at a density of 1.25 × 10 5 cells/cm 2 . Cells were allowed to adhere for 20 min and then washed to remove non-adhering cells. After a 24 h of incubation, the medium was replaced with fresh medium containing the substance(s) under study. Cell viability was greater than 95%, as tested by Trypan Blue exclusion. Immunostaining, performed as previously described [ 20 ], revealed that cultures consisted of ≥ 99% positive cells for the microglia/macrophage marker ED1. Microglial cells were pre-stimulated for 30 min with nicotine and then stimulated for 24 h in the presence of 10 ng/ml LPS. A rat pheochromocytoma cell line, PC12, was propagated and maintained in RPMI-1640 medium supplemented with 5% heat-inactivated fetal bovine serum (FBS) and 10% heat-inactivated horse serum (HS) 100 U/ml penicillin, 100 μg/ml of streptomycin, and 2 mM L-glutamine. The cells were plated in 12-well plates for 24 h before performing RNA extraction. Cytokines nitric oxide and PGE 2 determination At the end of the incubation time, cell supernatants were collected, centrifuged, and stored at -70°C until tested. The levels of TNF-α and IL-10 were assayed by specific ELISAs, following the manufacturer's instructions. The ranges of determination were: 31–2500 pg/ml for TNF-α, 10–1000 pg/ml and 8–500 pg/ml for IL-10. The production of NO by measuring the content of nitrite, one of the end products of NO oxidation, as previously described [ 21 ]. PGE 2 content was quantified using a specific radioimmunoassay [ 21 ]. The assay detection limit was 25 pg/ml and cross-reactivity of the antibody for PGE 2 with other prostaglandins less than 0.25%. Immunostaining of microglial cells with α-bungarotoxin and western blot analysis Microglial cells were plated on uncoated glass coverslips (2.5 × 10 5 cells/cm 2 ), allowed to adhere for 20 min and then washed to remove non-adhering cells. After a 24 h of incubation, the complete BME medium was replaced with fresh BME medium without serum. Cells were incubated at 4°C for 15 min with FITC-labeled α-bungarotoxin at 1.5 μg/ml. Where indicated, nicotine was added at the concentration of 500 μM for 10 min, in order to saturate all the binding sites before the addition of FITC-labeled α-bungarotoxin. Cells were washed 3 times with BME medium and then fixed with 4% paraformaldehyde at room temperature for 15 min. After fixation, coverslips were washed twice with PBS solution, mounted in PBS:glycerol and examined using a fluorescent microscope. Cell culture lysates from microglial cells and PC12 cells (used as positive control) were analyzed for α7 subunit expression. Total protein content was estimated using the Bio-Rad protein assay. An aliquot corresponding to 50 μg (microglia cells) and 20 μg (PC12 cells) of total protein for each sample was separated by sodium dodecyl sulphate polyacrylamide gel elecrophoresis (SDS-PAGE) and transferred electrophoretically to nylon membranes. Membranes were blocked with 10% non-fat milk and incubated with a rabbit policlonal antibodies against α7 subunit (1:2000) overnight at 4°C. Horseradish peroxidase conjugated anti-rabbit IgG (1:5000, 1 h at 25°C) and ECL reagents were used as detection system. RNA extraction and semiquantitative RT-PCR analysis Total RNA was prepared from rat microglia, PC12 cells and rat hippocampus using Trizol reagent according to manufacturer's protocol. Two μg of denatured total RNA were converted into first-strand cDNA using the SuperScript™synthesis system (Life Technologies™) in a total reaction volume of 20 μl following the conditions provided by the manufacturer's protocol. Oligonucleotide primers with similar Tm were designed to generate a PCR fragment of 754 bp for the α7 subunit. PCR conditions (number of cycles and cDNA and primer concentration) that ensure the data to be obtained within the exponential phase of amplification of each template were carefully assessed. The amplification of the β-actin, COX-2 and α7 subunit within the exponential phase of amplification was achieved with 25, 30 and 40 cycles respectively. Five μl, 15 μl and 40 μl of diluted cDNAs were amplified for β-actin, COX-2 and α7 respectively. PCR-amplification was done in a final volume of 50 μl containing 1x PCR buffer, the four dNTPs (0.2 mM), MgSO 4 (2 mM), 1 Unit of Platinium Taq DNA polymerase High Fidelity (Invitrogen). The primers were: α7 subunit (Gene bank accession number S53987 ), sense 5'-TCT GTG CCC TTG ATA GCAC, antisense 5'-CTT CAT GCA ACC AGG ATC AG, product length 754; COX-2 [ 22 ], sense 5'-TGA TGA CTG CCC AAC TCC CATG; antisense 5'-AAT GTT GAA GGT GTC CGG CAGC, product length 702 bp; β-actin (accession number NM031144 ) sense 5'-GTC GAC AAC GGC TCC GGC ATG; antisense 5'-CTC TTG CTC TGG GCC TCG TCGC, product length 158 bp. A sample containing all reaction reagents except cDNA was used as PCR negative control in each experiment. The absence of genomic DNA was verified using 2 μg of RNA from microglia that was reverse-transcribed without the enzyme (-RT). The PCR conditions for COX-2 were as follows: initial denaturation at 94°C for 2 min followed by 30 cycles of 94°C for 30 sec, 58°C for 45 sec, 68°C for 1 min, and an additional cycle with extension at 72°C for 7 min. The PCR conditions for β-actin were as follows: initial denaturation at 94°C for 5 min followed by 25 cycles of 94°C for 30 sec, 68°C for 30 sec, 68°C for 45 sec and an additional cycle with extension at 72°C for 1 min. The PCR conditions for α7 subunit were as follows: initial denaturation at 94°C for 5 min followed by 40 cycles of 94°C for 30 sec, 57°C for 1 min, 68°C for 45 sec and an additional cycle with extension at 72°C for 7 min. PCR products were analyzed by electrophoresis, stained with ethidium bromide and photographed. Transcript levels were analyzed by Fluor-STM Multimager analyser (Biorad). For each experiment, the ratio between optical density (arbitrary units) of bands corresponding to COX-2 and β-actin (used as internal standard) was calculated to quantify the level of the transcripts for COX-2 mRNAs. Statistical analysis Data are expressed as mean ± SEM with the number of independent experiments, run in duplicate, indicated in figure legends. Comparison between treatment groups was made by Student's t -test. A two-tailed probability of less than 5 % (i.e. p < 0.05) was taken as statistically significant. Results Expression of α7 subunit mRNA in microglial cultures The expression of the mRNA for α7 subunit in rat microglial cells was investigated by RT-PCR. As shown in Figure 1A , we detected a band of the expected size of 754-bp, which was then confirmed to correspond to α7 subunit by sequencing (M-Medical, Pomezia, I). The absence of genomic DNA contamination was demonstrated amplifying 2 μg of total RNA from microglia that was reverse-transcribed without the enzyme (Fig. 1B ). As positive controls, we analyzed the expression of α7 subunit mRNA in rat hippocampus and PC12 cells (Fig. 1C ), known to express the α7 subunit at high levels [ 23 , 24 ]. The expression of α7 subunit at protein level was established by western blot analysis using a specific antibody for the α7 subunit, which recognized a clear band with a molecular mass of approximately 55 kD from both microglial cells and PC12 cells, used as a positive control (Fig. 2A ). The expression of the receptor was confirmed by labeling microglial cells with FITC-labeleled-α-bungarotoxin (α-Bgtx), a selective nicotinic antagonist. Microglial cells were pre-treated for 10 min in the absence (Fig. 2B , left panel) or in the presence (Fig 2B , right panel) of nicotine (500 μM) before adding 1.5 μg/ml FITC-α-Bgtx. As shown in Figure 2 , a strong binding of α-Bgtx was observed on the cell surface of microglial cells (left panel), while nicotine pre-treatment resulted in a marked reduction of the intensity of the fluorescent signal (right panel). Figure 1 α7 nAChR subunit is expressed in rat microglial cultures. Semiquantitative RT-PCR analysis of α7 nAChR mRNA expression in rat microglial cells (A) and in PC12 cells and rat hippocampus (C). A 754-bp band corresponding to α7 nAChR was specifically amplified (acc. number S53987 ; amplified region: 906–1660). Expression of β-actin is shown as internal control. No contamination of genomic DNA was present as shown in panel B (-RT: RNA from microglia that was reverse transcribed without the enzyme and amplified for α7 subunit). Figure 2 Western blot and fluorescent immunostaining of α7 nAChR in rat microglial cultures. A: Proteins from microglial cultures and PC12 cells were analysed by western blot (50 ug/lane) using specific polyclonal anti AChRα7 antibodies. B: microglial cells were pre-incubated in the absence (B, left panel) or presence of 500 μM nicotine (B, right panel) for 10 min and then incubated with FITC-labeleled-α-Bgtx (1.5 μg/ml) for 15 min at 4°C. A strong binding of α-Bgtx was observed on the cell surface of microglial cells. Nicotine pre-treatment resulted in a marked reduction of the intensity of binding. Effects of nicotine and α7 subunit activation on TNF-α release by rat microglial cells Once we had demonstrated the presence of α7 subunit mRNA and protein in microglial cells, we studied the functional consequences of receptor activation using the specific agonist nicotine. Microglial cells were pre-treated for 30 min with increasing concentrations of nicotine and then incubated for 4 or 24 h in the absence or the presence of 10 ng/ml LPS. In resting microglial cultures nicotine did not affect the basal level TNF-α(data not shown). As previously demonstrated using mouse microglial cultures, nicotine pre-treatments dose-dependently inhibited the release of TNF-α(Fig. 3 ). At 1 μM concentration, nicotine reduced the release of TNF-α after 4 h of LPS stimulation by approximately 35%, an effect similar to that recently reported for murine microglial cultures [ 12 ]. The inhibitory effect of nicotine on TNF-α release was still significant in microglial cultures exposed to LPS for 24 h (data not shown). Figure 3 Effects of specific α7 nAChR agonist and antagonist on TNF-α production by activated rat microglial cultures. Microglial cells were subcultured for 24 h in 10% FCS-containing medium, which was replaced with fresh medium before stimulation. Nicotine (0.1–1 μM) and/or α-Bgtx were added 30 min before LPS stimulation (10 ng/ml). Supernatants were collected after 4 h and analyzed for TNF-α content. Data are shown as mean ± SEM for 3 independent experiments, run in duplicate. *p < 0.03 vs LPS. To verify that the effect of nicotine was mediated by α7 subunit, we measured the level of TNF-α in activated microglial cells exposed to nicotine in the presence or in the absence of α-Bgtx. The addition of 0.01 μM α-Bgtx almost totally prevented the inhibitory effect of nicotine (Fig. 3 ). In addition to TNF-α, we also analyzed the release of two important microglial mediators such as NO and IL-1β and we found that nicotine pre-treatment only slightly reduced the release of NO (9 ± 4 and 14 ± 6 % of inhibition vs LPS activated microglia; n = 9; p < 0.04, for 1 and 10 μM nicotine, respectively) and did not modify the release of IL-1β (data not shown). Effects of nicotine and α7 subunit activation on interleukin-10 and prostaglandin E 2 synthesis by rat microglial cells We then analyzed the effects of nicotine on the production of interleukin-10 (IL-10) and prostaglandin E 2 (PGE 2 ), two important local mediators with anti-inflammatory and immunoregulatory functions. Nicotine pre-treatment only moderately reduced (18.6 ± 7% of inhibition vs LPS activated microglia; n = 4; p < 0.03, for 1 μM) the level of IL-10 in the culture media of microglia cells stimulated for 24 h with LPS (data not shown). Figure 4 Effect of specific α7 nAChR agonist and antagonist on PGE 2 synthesis by activated rat microglial cultures. Microglial cells were subcultured as in Fig. 3, and nicotine (0.1–1 μM) added 30 min before LPS stimulation (10 ng/ml). Supernatants were collected after 24 h and analyzed for PGE 2 content. Data, with induction expressed as a percentage of LPS-induced PGE 2 production, are shown as mean ± SEM for 5 independent experiments, run in duplicate. The levels of PGE 2 were undetectable in basal conditions, and were 24 ± 6 ng/mg protein after LPS-stimulation for 24 h. *p < 0.05 vs LPS; **p < 0.02 vs LPS. By contrast, nicotine pre-treatments dose-dependently enhanced the synthesis of PGE 2 in LPS-activated microglial cells. The presence of 0.01 μM α-Bgtx, blocked the nicotine-dependent increase of PGE 2 released by LPS-activated microglia (Fig. 4 ). At this concentration, α-Bgtx did not by itself affect basal (not shown) or LPS-induced PGE 2 . We investigated the molecular mechanism underlying the increased synthesis of PGE 2 induced by α7 subunit stimulation by measuring by RT-PCR the levels of COX-2 mRNA. COX-2 is the enzyme responsible for the first committed step in prostaglandin synthesis, and is known to be readily induced by LPS in both peripheral macrophages and microglia [ 25 ]. As expected, COX-2 mRNA was expressed at low levels in resting microglial cultures and was remarkably increased after 7 h and 24 h of LPS treatment (Fig. 5 ). The basal COX-2 mRNA level was not significantly altered by nicotine pre-treatment at any tested concentration (0.1 μM and 1 μM) or incubation time (7 and 24 h). However, nicotine pre-treatment strongly increased the levels of COX-2 mRNA induced by 7 h treatment with 10 ng/ml LPS; the maximal effect was reached at 0.1 μM concentration (Fig. 5A ). The enhancing effect of nicotine pre-treatment persisted after 24 h of LPS-treatment, although the increase was significant only at the lower concentration of nicotine (Fig. 5B ). Figure 5 Semiquantitative RT-PCR analysis of COX-2 mRNA. Representative semi-quantitative RT-PCR analysis of COX-2 mRNA in microglial cultures, subcultured as in Fig. 3, pre-treated with nicotine (Nic, 0.1–1 μM) for 30 min and stimulated for 7 h (A, upper panels) or 24 h (B upper panels) with LPS (10 ng/ml). The amount of COX-2 mRNA, expressed as the ratio of densitometric measurement of the sample to the corresponding internal standard (β-actin), is shown in the lower panels. Data are shown as mean ± SEM for 3 to 4 independent experiments, with the exception of 1 μM nicotine, panel A (n = 2); all run in duplicate. * p < 0.05 vs fcs; **p < 0.05 vs fcs. Discussion The present study provides evidence that supports the existence of a cholinergic control of microglial activation. First, we have confirmed using rat microglial cells previous data showing that murine microglia express the α7 subunit and that their exposure to the specific agonist nicotine reduces LPS-induced release of the pro-inflammatory molecule TNF-α, thus suggesting that these events are not species specific. Furthermore, we extended the analysis of α7 subunit activation to other important microglial functions, including the synthesis of mediators possessing anti-inflammatory and immunomodulatory activities. We found that in LPS-activated microglial cells, the interaction of α7 subunit with its agonist nicotine had moderate or no effect on the release of NO, IL-1β and IL-10. By contrast, nicotine treatment significantly increased the expression of COX-2 and the synthesis of PGE 2 . The effect of nicotine on the LPS-induced PGE 2 release was significantly reversed by the specific antagonist of α7 subunit, α-bungarotoxin, demonstrating the involvement of α7 nicotinic receptors in the induction of PGE 2 production by activated microglial cells. COX-2 is the inducible isoform of the enzyme responsible for the first committed step in PGE 2 synthesis, one of the major prostaglandins produced during inflammatory response and potent modulator of several macrophage and lymphocyte functions [ 26 ]. Within the brain, COX-2 activity and PGE 2 production, depending on their levels of induction, have been associated with both protective and harmful effects on neurons and glial cells [ 27 ]. In microglial cells, COX-2 is the major isoform, rapidly induced by LPS stimulation or interaction with apoptotic neurons [ 28 ]. The constitutive isoform COX-1 is only moderately expressed by these cells and is not up-regulated during their activation [ 25 , 27 ]. PGE 2 has been found to be neuroprotective in several experimental settings. At nanomolar concentrations, PGE 2 protects hippocampal and cortical neuronal cultures against excitotoxic injury or LPS-induced cytotoxicity [ 29 - 32 ]. In hippocampal neuronal and organotypic cultures, the protective effect of PGE 2 against glutamate and oxygen deprivation is mediated by the activation of the EP2 receptor, one of the four PGE 2 receptor subtypes whose activation leads to cAMP formation [ 31 ]. The protective effect of EP2 receptor activity has been confirmed in vivo, in a model of transient forebrain ischemia, in which the genetic deletion of this PGE 2 receptor exacerbates the extent of neuronal damage [ 31 ]. On the other hand, at concentrations in the μM – mM range, PGE 2 contributes to neuronal death and stimulates release of glutamate by astrocytes [ 33 - 35 ]. PGE 2 has also been shown to down-regulate microglial activation and expression of pro-inflammatory genes, including TNF-α, both in vitro and in vivo [ 36 , 37 ]. We have recently found that the interaction of microglial cells with apoptotic neurons promotes the synthesis of PGE 2 along with neuroprotective and immunoregulatory molecules such as TGF-β and NGF [ 38 , 28 ]. In this system, the release of PGE 2 is triggered by the specific interaction between phosphatidylserine, a phospholipid exposed on the cell surface during the initial phase of apoptosis, with its cognate receptor expressed by microglia [ 39 ], consistent with previous studies on peripheral macrophages [ 40 ]. It has been suggested that the PGE 2 , released by macrophages engulfing apoptotic cells, contributes to one of the main features of apoptotic cell death, namely the efficient removal of dying cells without eliciting inflammation in the surrounding tissue [ 41 ]. It is therefore tempting to speculate that the α7 subunit-dependent increase of PGE 2 in activated microglia cells is part of an anti-inflammatory pathway regulated by the cholinergic system. The detection of microglial cells, astrocyte processes and choline acetyltransferase- (ChAT-) positive fibers around β-amyloid plaques in transgenic APP SW mice suggests a close connection between cholinergic terminals and microglial cells [ 42 ]. A deficit in ACh level due to loss of cholinergic neurons associated with AD as well as aging could contribute to the establishment of chronic inflammation rendering microglial cells more susceptible towards environmental changes and orientating them towards a pro-inflammatory phenotype. However, to date there is no definitive evidence of a causal link between loss of cholinergic neurons and increased levels of pro-inflammatory cytokines such as TNF. In the last few years, several lines of evidence have suggested that activation of α7 subunits plays an important role in the maintenance of cognitive functions in several neurodegenerative disorders [ 43 ]. Epidemiological studies have shown that cigarette smoking can be protective against the development of AD, PD and other types of dementia, suggesting that chronic inhalation of nicotine may slow the progression of these neurodegenerative diseases or improve some cognitive responses in AD patients [ 44 , 17 ]. Loss of nAChRs has been reported in patients with diverse forms of dementia [ 45 ]. In particular, a reduction in α7 subunit number was detected in AD and PD brain tissue specimens [ 46 ]. The administration of ligands targeting nicotinic receptors in animal models of neurodegeneration, as well as in humans, induced cognitive improvement [ 47 ] and conferred neuroprotection against several neurotoxic agents [ 48 , 49 ]. Furthermore, cholinesterase inhibitors used in the symptomatic treatment of AD have been reported to exert additional benefits through the increased density of specific nicotinic receptor subunits (including the α7) [ 50 ]. This effect could be relevant in view of the anti-inflammatory role suggested for the α7 subunit. As mentioned in the introduction, the presence of α7 subunit on immune cells as well as on other non-excitable cells has provided a molecular basis for a non-neuronal cholinergic pathway that might function as an essential regulator of inflammation as well as immune responses [ 4 , 5 ]. Primary cultures of astrocytes and microglia show ChAT activity and synthesize acetylcholine [ 51 ]. Accordingly, we have found the expression of ChAT mRNA in both resting and activated microglia cells (unpublished results). This suggests that this neurotransmitter may act as a local hormone and contribute to the regulation of microglial functions. It should be noted that although our study focused on the effects of nicotine on the process of microglial activation induced by LPS, our findings may have broader implications since other microglial activators, such as pro-inflammatory cytokines and fibrillogenic peptides, share some common signaling pathways with LPS [ 52 , 53 ]. In addition, it has been recently reported that the LPS receptor CD14 interacts with fibrils of Alzheimer amyloid peptide and a deficiency of this receptor significantly reduces fibril-induced microglial activation [ 54 ]. At present, the signaling pathways downstream to α7 subunit activation and leading, in particular, to COX-2 and PGE 2 up-regulation is under investigation. Shytle et al. [ 12 ] have reported that either ACh or nicotine inhibit LPS-induced phosphorylation of the mitogen-activated protein kinases p44/42 and p38 in murine microglia. We have recently found a reduction of p38 phosphorylation in two experimental settings in which exposure of microglial cells to phosphatidylserine vesicles – mimicking apopototic neurons – or to chronic activation stimuli, resulted in downregulation of pro-inflammatory cytokines and in enhancement of PGE 2 synthetic pathway [ 55 , 56 ], thus suggesting that p38 may also have a role in α7 dependent up-regulation of COX-2. Conclusions Activation of α7 nicotinic receptors in microglial cells by nicotine controls some important microglial functions, thus preventing chronic inflammation. Since microglial activation and chronic inflammation have been associated with most neurodegenerative pathologies [ 57 ] the understanding of the molecular pathway(s) triggered by α7 subunit activation in microglial cells will offer new venues for potential pharmacological regulation of microglial activation in neurodegenerative diseases. At the same time, the development of molecules able to stimulate the α7 subunit may represent a potential promising approach for the treatment of these disorders. List of abbreviations Lipopolysaccharide (LPS) Acetylcholine (ACh) Neuronal acetylcholine receptors (nAChRs) Tumor necrosis factor-α (TNF-α) Prostaglandin E 2 (PGE 2 ) Interleukin-1β (IL-1β) Nitric oxide (NO) Interleukin-10 (IL-10) Competing interests The author(s) declare that they have no competing interests. Authors' contributions RDS conceived of the study, participated in its design and coordination, produced the primary microglial cultures, performed the ELISA and the immunofluorescence staining, was primarily responsible of the RT-PCR review the data and drafted the manuscript. MAAC participated in the design and coordination of the study, produced the primary microglial cultures, performed the ELISA and the immunofluorescence staining, was primarily responsible for western blot analysis and review the data. DC participated in the production of the primary microglial cultures and in RT-PCR. LM contributed to the design of the study, guided data interpretation and presentation and assisted in the preparation of the manuscript.

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545195

Coccidioidomycosis—A Fungal Disease of the Americas

Coccidioidomycosis was first recognized as a serious disease over 100 years ago, but the disease remains an enigma and often goes undiagnosed, even in endemic areas

It has been more than a century since coccidioidomycosis was first recognized as a serious disease, and its etiology and epidemiology have been well documented. But the disease remains an enigma to many, and it often goes undiagnosed, even in endemic areas. As management of this chronic disease remains problematic, new preventive or therapeutic options are needed. Etiology and Epidemiology Coccidioidomycosis is a fungal disease found only in the Western Hemisphere. It is caused by two nearly identical species, Coccidioides immitis and C. posadasii , generically referred to as the “Californian” and “non-Californian” species respectively [1] . The fungus grows in a mycelial phase (see Box 1 ) in the soil within a geographically delineated area of the United States known as the Lower Sonoran Life Zone [2] . This semiarid zone encompasses the southern parts of Texas, Arizona, New Mexico, and much of central and southern California ( Figure 1 ). Box 1. Glossary Mycelial phase —The growth form in the soil, composed of filamentous hyphae and reproductive spores called arthroconidia. Arthroconidia —Reproductive spores, highly resistant to dessication, which are the infectious particles inhaled by man and animals. Spherules —The parasitic phase of this dimorphic fungus; spherules are round cells of 30–100 µM or more that reproduce the progeny endospores. Endospores —The progeny units of the parasitic phase, derived from spherules. Figure 1 Geographic Distribution of Coccidioidomycosis (Illustration: Margaret Shear) Endemic regions for coccidioidomycosis have long been identified in semiarid areas in Mexico [3] , and smaller endemic foci have been described in areas of Central and South America [ 4 , 5 ]. More recently, Brazil has also been found to contain endemic areas in the semiarid northeastern states of the country [6] . The climatic conditions and flora of these states are similar to those in endemic regions in North, Central, and South America. In Latin America, Mexico has the largest number of reported cases, with the prevalence of infection in northern Mexico reported to be between 10%–40% [ 7 , 8 ]. C. posadasii is thought to be the predominant species in Mexico [3] . As the soil dries or nutrients become limiting, the fungus reproduces asexually by disarticulating the hyphae into small, environmentally-resistant arthroconidia (reproductive spores) ( Figure 2 ). These are easily aerosolized when the soil is disturbed by wind or human activities. Consequently, it is the inhalation of the dust-borne arthroconidia that leads to infection by this pathogenic fungus in both humans and domestic or wild mammals. Upon inhalation, the fungus converts to a unique life cycle of alternating spherules and progeny endospores, which comprises the parasitic phase of this dimorphic fungus ( Figure 2 ) [9] . Mycelial elements are only occasionally found in diseased tissue [10] . Coccidioidomycosis is not contagious; reports of human-to-human spread are extremely rare. Hence, primary exposure to contaminated dust is the sole risk factor for the acquisition of this disease. Figure 2 Life Cycle of Coccidioides immitis (Illustration: Michael Borjon/ The Bakersfield Californian ) It is estimated that upwards of 100,000 primary coccidioidal infections occur in humans each year in the endemic areas of the United States [11] . In recent years, the incidence of the disease has increased in California and Arizona, which may be partially due to the rapid immigration of previously unexposed persons from states outside the endemic areas (in other words, the pool of susceptible people has increased) [12] . In the United States, diagnosis in patients who have symptoms is established by serodiagnosis in conjunction with patient history. In previous decades, a coccidioidal skin test antigen was a useful adjunct in the diagnosis, but it became unavailable in the 1980s [13] . The incidence of primary pulmonary disease outside the United States is not established; most reports are limited to disseminated or unusual cases [14] . Diagnosis in Latin America is usually based on microbiologic findings, as serology is not always available [14] . Clinical Features In their pioneering epidemiologic studies, Smith and colleagues found that about 60% of exposures to the fungus result in asymptomatic infection [15] . In the 40% of patients who have symptomatic disease, there are protean manifestations. These range from a primary, or benign, pulmonary infection (commonly known as “Valley Fever”) to a progressive pulmonary or extrapulmonary disease involving the skin, bones and/or joints, the central nervous system, and other organ systems. Fortunately, most patients with primary disease recover spontaneously and retain lifelong immunity to exogenous reinfection. Chronic and disseminated disease is estimated to occur in up to 5% of infected individuals, with comparatively more cases occurring in older individuals and in males [12] . The most dangerous form of the disease is meningeal infection, which occurs in about 0.15%–0.75% of extrapulmonary coccidioidomycosis cases and requires treatment for life [16] . In regions where tuberculosis rates are high, the two diseases may occur together. Tuberculosis and coccidioidomycosis share common epidemiological, clinical, radiographic, and even histopathological features, making a correct diagnosis extremely difficult in cases where both diseases coexist. In areas where both diseases are endemic, the pertinent studies for diagnosing both conditions should be performed in every patient with compatible clinical features. The diagnosis of one of them does not exclude the possible existence of the other [17] . Treatment Historically, patients with the primary respiratory form of the disease were not treated because the vast majority recovered on their own. Instead, such patients were given supportive care and were monitored, often with radiographs, until the disease resolved. In recent years, however, an increasing number of physicians are prescribing azole antifungals in cases of primary disease, both because drugs like fluconazole have a good safety record, and because there is a perception that treatment may prevent progression to more serious forms of the disease. This latter presumption, however, is not supported by controlled trial data. All cases of chronic or disseminated disease call for antifungal therapy, but the choice of drugs, route, and duration of therapy is highly dependent on the form of the disease, the severity and site(s) of infection, and the immune status of the patient. Galgiani and colleagues have published clinical practice guidelines on the choice of drug and duration of therapy for a given form of the disease [18] . There are only two classes of antifungal therapy routinely used for treatment of coccidioidomycosis. The first class is the polyenes, with amphotericin B desoxycholate and the newer lipid formulations used for the more serious forms of disease. The second class is the azoles, with ketoconazole, fluconazole, itraconazole, and the newer analogue voriconazole as available options. Voriconazole, in particular, is being used more and more often in life-threatening mycoses, and was found to be better than amphotericin B in the primary therapy of invasive aspergillosis [19] . According to available reports, treatment in Latin America usually consists of one of the azoles (fluconazole or itraconazole) and/or amphotericin B desoxycholate; lipid formulations are too costly to be accessible [20] . Treatment of the more serious or aggressive forms of the disease is typically of long duration and often results in less than complete resolution of disease; relapse is common [21] . Unfortunately, information on the treatment of coccidioidomycosis is limited, due to the small numbers of controlled trials performed for what is perceived to be a niche market. Clearly, newer, more powerful drugs are needed. In addition to drugs, surgery is sometimes indicated to remove focalized infections, such as pulmonary cavities, or to debride osseous forms of the disease [22] . Immunology and the Basis for a Vaccine Acquired resistance to coccidioidomycosis strongly correlates with the development of a delayed-type hypersensitivity skin test response to coccidioidal antigens [23] and the production of T-helper-1 (Th1)-associated cytokines to coccidioidal antigens, such as interferon-gamma (IFN-γ) and Interleukin-2 (IL-2) [24] . Humoral immunity plays no known role in overcoming infection. Although all humans are equally susceptible to initial infection, there is evidence of genetic predisposition to dissemination, independent of socioeconomic or environmental factors, particularly among African-Americans and Filipinos [25] . Pregnancy is also a risk factor. In cases of marked immunosuppression, either in advanced AIDS or other forms of depressed cellular immunity, the management of coccidioidomycosis is particularly challenging and requires aggressive treatment [26] . As previously mentioned, recovery from disease confers lifelong immunity to reinfection, and is a rationale for the development and implementation of a vaccine for the prevention of symptomatic or serious forms of the disease. The combination of increasing incidence of disease, a growing population in the endemic area, and the lack of a highly effective drug treatment justifies efforts to prevent (rather than treat) this disease. To that end, a university-based consortium, the Valley Fever Vaccine Project ( www.valleyfever.com ), has identified and cloned immunogenic proteins that have proven effective in the prevention of deaths and fungal burdens in mouse models of coccidioidomycosis. This suggests that a vaccine for use in humans could be created [27] . A candidate vaccine comprised of a fusion protein based on two antigens has been selected and is currently in pharmaceutical development under the sponsorship of this project, with the goal of evaluating the safety and immunogenicity in humans. Conclusion Although the vast majority of infected individuals emerge from coccidioidomycosis without complications, an unlucky minority are faced with a debilitating disease that lacks adequate drug options for rapid and completely effective treatment. In the absence of newer therapeutics, discoveries that lead to immunologic intervention [28] or prevention by vaccines may ultimately bring a measure of relief.

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549552

Troglitazone, a PPAR-γ activator prevents endothelial cell adhesion molecule expression and lymphocyte adhesion mediated by TNF-α

Background Cytokine mediated induction of the mucosal addressin cell adhesion molecule-1(MAdCAM-1) expression is associated with the onset and progression of inflammatory bowel disease ( IBD ). Results Using western blotting and cell-based ELISA, we show in this study that troglitazone, an activator of the peroxisome proliferator-activated receptor-γ (PPAR-γ), widely used in the treatment of diabetes, has as well recently been highlighted as protective in models of inflammation and cancer. We found that troglitazone (10–40 μM), significantly reduced the TNF-α (1 ng/ml) mediated induction of endothelial MAdCAM-1 in a dose-dependent manner, achieving a 34.7% to 98.4% reduction in induced MAdCAM-1. Trogliazone (20μM) reduced TNF-α induced VCAM-1, ICAM-1 and E-selectin expression. Moreover, troglitazone significantly reduced α4β7-integrin dependent lymphocyte adhesion to TNF-α cultured endothelial cells. Conclusions These results suggest that PPAR-γ agonists like troglitazone may be useful in the clinical treatment of IBD.

Background Endothelial cell adhesion molecules or 'ECAMs' play essential roles in the development of chronic inflammation by recruiting leukocytes, especially lymphocytes through their ability to promote leukocyte rolling, firm adhesion and extravasation [ 15 ]. Tissue infiltration by leukocytes is a common hallmark in several chronic inflammatory states which include the inflammatory bowel diseases, ulcerative colitis (UC), and Crohn's disease (CD), but also several other chronic inflammatory states such as arthritis, lupus, diabetes [ 17 , 47 , 58 ]. In the setting of IBD, the expression of ECAMs like ICAM-1, VCAM-1, and MAdCAM-1 is observed in experimental models of colitis, [ 11 , 33 , 34 , 48 ] and also within the inflamed human colon in Crohn's disease and ulcerative colitis [ 3 , 49 ]. Among the adhesion molecules that are up-regulated in IBD, MAdCAM-1, the mucosal cell adhesion molecule is thought to be preeminent in the development of chronic gut inflammation. MAdCAM-1 is normally expressed in the gut, and its expression is dramatically increased during inflammation [ 11 , 48 ]. The functional significance of increased expression of MAdCAM-1 in IBD is supported by several reports which demonstrate that immunoneutralization of either MAdCAM-1 or its lymphocyte ligand, the α4β7 integrin, attenuate inflammation and mucosal damage in a variety of animal models of colitis [ 14 , 24 , 55 ]. However, since monoclonal antibodies directed against other ECAMs, particularly VCAM-1, can as well reduce disease activity in animal models of colitis [ 2 , 16 , 46 , 53 ], the literature suggests that MAdCAM-1 is probably necessary, but insufficient for the maximal penetrance of experimental and clinical IBD. Based on these results, it is apparent that an improved understanding of the mechanisms regulating ECAM expression, especially MAdCAM-1, might help to design improved therapies for colitis. Peroxisome proliferator-activated receptors (PPARs) are members of the nuclear hormone receptor superfamily of transcription factors, whose activities are regulated through the high affinity binding of small lipophilic ligands that include steroid hormones [ 29 ]. A new class of antidiabetic drugs, known as 'glitazones' which includes troglitazone, rosiglitazone, and pioglitazone, have been developed as agonists that bind to the gamma (γ)-subtype of the PPARs. While glitazones have been extensively used in the treatment of diabetes, several investigators have now demonstrated that PPAR-γ ligands will markedly reduce colonic inflammation of in two different mouse models of colitis [ 12 , 51 ]. In addition, glitazones provide some benefit in the treatment of ulcerative colitis in humans as well [ 27 ]. Although PPAR-γ is expressed at high levels in adipose tissues, PPAR-γ has also been described in many other kinds of cells, including those in the vasculature like endothelial cells, vascular smooth muscle cells and monocytes and macrophages [ 19 ]. Although it not yet completely clear, the literature suggests that glitazones may be therapeutic in these models through the ability of these PPAR-γ activators to inhibit several events in inflammation particularly leukocyte infiltration into tissues mediated by NF-kB-dependent ECAM expression [ 6 , 21 , 32 , 38 , 51 ]. However, the literature does not uniformly support protective roles for all PPARs. For example, it has been suggested that activation of PPAR -α, rather than PPAR-γ activation is responsible for blocking cytokine induced ECAM expression [ 30 , 41 ] and these differences may reflect tissue- and/or species specific responses to glitazones. Regardless, glitazones might be therapeutic in the setting of IBD through their ability to restrict expression of MAdCAM-1 , one of the more important regulators of gut inflammation in IBD. However, this has not yet been investigated. In the present study we have examined the ability of a candidate glitazone PPAR-γ ligand, troglitazone , to limit cytokine induction of MAdCAM-1 and also VCAM-1, ICAM-1 and E-selectin, and decrease MAdCAM-1 dependent lymphocyte endothelial adhesion in vitro . Results PPAR-γ expression by endothelial cells To confirm the presence of PPAR-γ on SVEC endothelial cells, western blotting for PPAR-γ was performed using an antibody generated to a synthetic peptide corresponding to amino acid residues 284–298 of murine PPAR-γ; importantly, this antibody exhibits no significant homology to PPAR-α. This antibody recognized a PPAR-γ specific band at 55 kD by western blotting in SVEC cells (Fig. 1 ). TNF-α induced MAdCAM-1 protein expression is reduced by troglitazone, a PPAR-γ ligand To examine the effect of PPAR-γ activation on endothelial cell inflammatory responses, SVEC endothelial cells were treated with TNF-α either with or without a pre- and co-treatment with troglitazone. TNF-α (1 ng/ml, 24 h) increased MAdCAM-1 expression to 13.4 times that of the untreated control level. This TNF-α induced MAdCAM-1 was dose dependently attenuated by pre- and co-treatment with troglitazone (i.e. from 69% to 7% of TNF-α stimulated levels) at concentrations of 10 to 40 μM (Fig. 2 ). At 40 μM troglitazone, the MAdCAM-1 expression (7% of TNF-α stimulated) was not significantly different from untreated controls. Troglitazone alone did not alter the expression of MAdCAM-1 ( data not shown ). Troglitazone was not overtly toxic, and did not affect cell protein content (i.e. protein content per well), or change the expression of either actin or vimentin, two cell structural proteins (measured by total protein staining of transferred western blots) ( data not shown ). To examine the effect of troglitazone on other ECAMs expression stimulated by TNF-α surface expression assay was performed. TNF-α induced VCAM-1 protein expression is reduced by troglitazone, a PPAR-γ ligand TNF-α (1 ng/ml, 24 h) enhanced VCAM-1 expression to 8.5 times that of untreated controls. This elevated expression was significantly reduced (to only 80% of the TNF-α stimulated level) by troglitazone at 20 μM (Fig. 3 ). Alone, this compound had no effect on the expression of VCAM-1 (Fig. 3 ). TNF-αinduced ICAM-1 protein expression is reduced by troglitazone, a PPAR-γ ligand TNF-α (1 ng/ml, 24 h) increased ICAM-1 expression to a level 4.7 times greater than untreated control levels. This TNF-α enhanced ICAM-1 expression was strongly attenuated (to 32% of the TNF-α stimulated level) by troglitazone at 20 μM (Fig. 4 ). Again, troglitazone alone had no effect on the expression of ICAM-1 (Fig. 4 ). TNF-α induced E-selectin protein expression is reduced by troglitazone, a PPAR-γ ligand TNF-α (1 ng/ml, 24 h) increased the expression of E-selectin 4 times over untreated control levels; this increase in E-selectin was also blocked by troglitazone (to 22% of the TNF-α stimulated level) at 20 μM (Fig. 5 ). Alone, troglitazone had no effect on E-selectin expression (Fig. 5 ). Adhesion of α4β7 expressing lymphocytes to TNF-α stimulated endothelium Having established that troglitazone exerts a significantly protective effect against TNF-α stimulated endothelial MAdCAM-1 induction, we examined the effects of troglitazone on the adhesion of α4β7 expressing mouse lymphocytes (using the cell line TK-1) to endothelial monolayers following TNF-α treatment. TNF-stimulation (24 h) significantly increased the adhesion of TK-1 lymphocytes to SVEC monolayers. Troglitazone (20 μM) significantly reduced TK-1 adhesion in response to TNF-α stimulation at 24 h (Fig. 6 ). Troglitazone did not modify the basal level of lymphocyte adhesion to the endothelium without TNF-α treatment. TNF-α induced phosphorylation of NF-kB p65 is prevented by troglitazone, a PPAR-γ ligand Mechanistically, the expression of all of these adhesion molecules is known to depend on the activation of NF-kB following TNF-α stimulation. Therefore, we examined whether troglitazone-mediated protection against TNF-α induced MAdCAM-1 expression and lymphocyte adhesion were related to the activation and/or inhibition of NF-kB. In this study, phosphorylation of the p65 subunit of NF-kB was used as an index of NF-kB activation. TNF-α (1 ng/ml, 1 h) induced the phosphorylation of NF-kB p65; this activation was significantly reduced by the PPAR-γ ligand, troglitazone at 20 μM (Fig. 7 ). Alone, troglitazone significantly attenuated the phosphorylation of NF-kB p65 compared to untreated controls (Fig. 7 ). Discussion MAdCAM-1 is a 60 KD endothelial cell surface molecule that is strongly expressed by mucosal endothelial cells, particularly following exposure of these cells to pro-inflammatory cytokines such as TNF-α. Expression of MAdCAM-1 has as well been reported in the brain, and in the heart, [ 23 , 47 ], and based on these findings, it has now been suggested that MAdCAM-1 might play roles in chronic inflammation of these organs as well. With respect to inflammatory bowel disease, MAdCAM-1 appears to be necessary for lymphocyte homing to mucosa associated lymphoid tissue [ 3 - 5 , 50 ]. Since MAdCAM-1 is normally expressed within the gut microvasculature, and is dramatically increased during IBD, it has been suggested that increased MAdCAM-1 expression participates in the etiology of IBD through its ability to control homing of lymphocytes to the gut. This notion is supported by several observations that show that antibodies directed against either MAdCAM-1, or its lymphocyte ligand, the α4β7 integrin will significantly attenuate several indices of injury in experimental models of colitis [ 24 , 39 ]. TNF-α is thought to be perhaps the most important cytokine responsible for driving the onset and progression of IBD. Because of this primary role of TNF-α in IBD, anti-TNF-α antibody therapy has been successfully used in IBD to reduce both colonic injury and expression of ECAMs in IBD [ 1 ]. While TNF-α significantly increased the expression of MAdCAM-1, it also increases the expression of intercellular cell adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1), E-selectin, P-selectin [ 15 , 37 ]. It should be noted that in colitis, all of these adhesion molecules are elevated in the colon [ 25 ], and likely contribute to the development of chronic gut injury. This is the first study to demonstrate that a PPAR-γ ligand, troglitazone, can significantly reduce the expression of MAdCAM-1, an endothelial cell adhesion molecule which is closely linked to chronic gut inflammation. Troglitazone significantly reduced TNF-α induced expression of several other ECAMs as well [ 6 , 21 , 30 , 32 , 38 , 41 , 57 ], and decreased the adhesion of α4β7-expressing lymphocytes (TK-1) to TNF-α stimulated endothelium. Since at least 50% of the adhesion of these lymphocytes to TNF-stimulated endothelium is MAdCAM-1-dependent [ 35 ], our results suggest that MAdCAM-1 mediates most of the stimulated adhesion, with more minor contributions from other ECAMs. The results strongly support a novel therapeutic action of PPAR-γ activators like troglitazone which might explain their beneficial effects PPAR-γ agonists in murine models of colitis [ 12 , 51 ] and in human ulcerative colitis [ 27 ]. NF-kB is a member of the Rel family of dimeric transcription factor complexes key transcription factor that modulates expression of MAdCAM-1 in inflammation, and is governs the expression of several other endothelial adhesion molecules in response to cytokines [ 9 , 22 , 33 , 35 , 40 , 52 ]. Prior to cytokine stimulation, NF-kB is restricted to the cytosol as an inactive complex with its inhibitor, Ik-B. Upon activation by cytokines, Ik-B is phosphorylated, dissociates from the NF-kB, and is subsequently ubiquitinated and degraded. This allows active NF-kB to enter the nucleus and bind kB consensus regulatory elements in the promoters of the genes for several ECAM (ICAM-1, VCAM-1, E-selectin, and MAdCAM-1) [ 9 , 33 - 36 , 54 ]. NF-kB can be activated through several kinases including IkB kinases (IKKs). IKKs phosphorylate IkB, but also phosphorylate the p65 NF-kB subunit on Serine-536 as part of the activation of the NF-kB complex. Phosphorylation of the p65 subunit is an important step in the activation of the NF-kB complex which permits this complex to enter the nucleus and activate NF-kB dependent genes [ 45 ]. Consequently, phosphorylation of p65 has been proposed as a simple index of NF-kB activation [ 45 ], although it may not be as sensitive as the electrophoretic mobility shift assay (EMSA). PPAR-γ ligands like troglitazone apparently suppress activation of NF-kB, and in our hands reduce both basal and TNF-stimulated NF-kB p65 phosphorylation (figure 7 ). Consequently, glitazones like troglitazone should reduce the expression of both cytokines and ECAMs driven by NF-kB [ 6 , 41 , 57 ]. Interestingly, under control culture conditions, we observe basal phosphorylation of p65, suggesting that normally, p65 is at least partially activated. This may be related to the role of basal NF-kB activity in maintaining cell survival and blocking apoptosis [ 8 , 42 ]. Since excessive inhibition of NF-kB can propel cells into apoptosis, agents like troglitazone, (which may inhibit NF-kB) could have a limited therapeutic window, and should be administered cautiously. However, under the conditions used in our study, (10–40 μM) we did not see evidence for the loss of cell viability assessed by trypan blue staining; all cells remained >99% viable by this method. In addition, the concentration of troglitazone in our study (10–40 μM) is near the therapeutic level since the physiological levels of glitazones, like troglitazone are 5–20 μM, with an average dose of 15 μM [ 28 ]. PPAR-γ ligands like glitazones should not only attenuate MAdCAM-1, but also diminish the expression of other ECAMs like ICAM-1, VCAM-1 and E-selectin. This reflects a decrease in the synthesis of some, but not all proteins, since densitometry of troglitazone treated monolayers shows no difference in total protein content between wells following troglitazone, but western blotting or surface expression assay find a significant decrease in the expression of ECAMs. While studies with glitazones in endothelial models for the most part demonstrate an inhibition of ECAMs such as ICAM-1 in response to TNF-α [ 10 , 38 ], Chen et al. [ 6 , 7 ] have reported that the ECV304 cell line showed an increase in the expression of ICAM-1 in response to troglitazone. This stands in sharp contrast to our current study. However, since The ECV304 cell line has been mistakenly designated as ' endothelial ' in many cases, (and is actually a bladder carcinoma in many instances) [ 56 ], those results may be called into question. It is also possible that PPAR-γ activators might well affect inflammation through NF-kB independent pathways. Some described PPAR-γ ligands, like the cyclopentanone prostanoids, exert anti-inflammatory effects through a PPAR-γ-independent pathways [ 43 ] specifically the inhibition of the IKK beta subunit which would suppress NF-kB activation. Further, troglitazone also activates ERK1/2 [ 20 ] and blocks c-fos synthesis [ 6 ] which could also modulate these effects. Therefore, we cannot completely exclude the possibility that troglitazone similarly protects in these models through direct inhibition of IKK, as well as indirect blockade through PPAR-γ. Since high levels of PPAR-γ protein are expressed within the colon, [ 13 ] it is possible that agonists for this pathway could have an important role in the regulation of normal colon functioning and disease progress. Conclusions Our results indicate that troglitazone and other glitazones may provide an effective means of treating forms of chronic inflammation including inflammatory bowel disease through their ability to interfere with steps in the activation of NF-kB, effectively blocking the expression of adhesion molecules like MAdCAM-1 which increase infiltration of tissues by leukocytes. Methods Reagents Recombinant mouse TNF-α was purchased from ENDOGEN (Stoughton, MA), and troglitazone was provided as a generous donation from Sankyo corp., Japan. Cell culture The SVEC4-10 line is an endothelial cell line derived by SV40 (strain 4A) transformation of murine small vessel endothelial cells, originally isolated from the axillary lymph node vessels of an adult male C3H/Hej mouse [ 4 , 5 ]. These cell types were all maintained in Dulbecco's modified Eagle's medium (DMEM) with 10% fetal calf serum with 1% antibiotic/ antimycotic. Cells were seeded into 24-well tissue culture plates at approximately 20,000 cells/cm 2 , and cultures were used immediately upon reaching confluence (usually 3–4 days after seeding). Lymphocytes The mouse CD8 + T cell lymphoma TK-1 cells (that constitutively expresses the α4β7 integrin [ 44 ] were obtained as a generous gift from Dr. Eugene Butcher (Stanford University, CA). These cells were cultured in RPMI-1640 medium supplemented with 10% FCS and 0.05 mM 2-mercaptoethanol (minus antibiotic/ antimycotic). PPAR-γ expression on SVEC endothelial cell – Western analysis of cell lysates Cell lysates were electrophoretically separated on 7.5% SDS- PAGE gels, transferred to nitrocellulose, blocked and incubated in primary anti-PPAR-γ synthetic peptide (Affinity Bioreagents Inc., Golden, CO) at a 1: 500 dilution overnight (4°C). Membranes were washed 2× with wash buffer. Secondary goat anti-rabbit horseradish peroxidase conjugated secondary antibody (Sigma) was added at a 1:2,000 dilution for 1 h. Membranes were washed 3 times and developed using the ECL detection system (Amersham, La Jolla, CA). Western analysis of cell lysates Monolayers were either pretreated (1 h) with blockers, and then incubated with cytokines (24 h), or treated without test agents and then treated with cytokines (24 h). All cell samples were harvested at 24 hours. Equal quantities of protein (75 μg) from each sample were electrophoretically separated on 7.5% SDS- PAGE gels. Gels were transferred to nitrocellulose membranes (Sigma) and blocked with 5% milk powder in PBS at 4°C (overnight). These membranes were washed twice for 10 min with wash buffer (0.1% milk powder in PBS). Primary rat anti-mouse MAdCAM-1 mAb (MECA 367; generous gift from Dr. Sharon Evans, RPMI, NY) was added at a concentration of 10 μg/ml and incubated at room temperature for 2 h. In p65 NF-kB phosphorylation studies, membranes were incubated with anti-phospho p65 antibody (Cell Signaling Technology, Beverly, MA) diluted 1:1000 overnight (4°C). These membranes were washed twice with wash buffer. Secondary goat anti-rat horseradish peroxidase conjugated secondary antibody (Sigma) was added at a 1:2000 dilution for 2 h for MAdCAM-1, while goat anti-rabbit antibody was used for detecting phospho-p65 NF-kB. Lastly, membranes were washed 3 times and developed using the enhanced chemiluminescence (ECL) detection system. The density of MAdCAM-1 staining was measured by scanning the 60 KD band, using a HP ScanJet™ flatbed scanner. Images were analyzed for density using Image Pro Plus™ image analysis software (Media Cybernetics, Silver Springs, MD). The data are expressed as a percentage of TNF-α-induced level of density. Endothelial cell surface adhesion molecule expression assay Surface expressions of ECAMs were measured using the method of Khan et al. [ 26 ]. SVEC monolayers were grown in 48-well plates as described and were pretreated (1 h) with troglitazone and of 1 μg/ml in HBSS/PBS + 5% FCS at 37°C for 30 min. Monolayers were then washed twice with 0.5 ml HBSS/PBS, and incubated with horseradish peroxidase conjugated rabbit anti-rat IgG (1:2,000 diluted, Sigma) in HBSS/PBS + 5% FCS at 37°C for 30 min. Monolayers we then co-treated with TNF-α (1 ng/ml) at 37°C in medium for 24 h. The cells were washed three times with 0.5 ml HBSS/PBS [1:1] at 24 hours, and monolayers incubated with anti-mouse VCAM-1, anti-ICAM-1 or anti-E-selectin. All antibodies were added to cultures after treatment at a concentration re washed four times with 0.5 ml HBSS/PBS followed by incubation with 0.25 ml of 0.003% hydrogen peroxide + 0.1 mg/ml 3, 3', 5, 5'-tetramethlbenzidine (Sigma) at 37°C for 60 min in the dark. The color reaction was stopped by adding 75 μl of 8 N H 2 SO 4 , and the samples were transferred to 96-well plates. Plates were read on a Titertek MCC340 plate reader (Titertek Instruments, Inc., Huntsville, AL) at 450 nm. Blanking (i.e. background) was performed on monolayers stained only with second antibody and reacted as above. TK-1 lymphocyte adhesion assay Briefly, TK-1 cells were suspended in culture medium and fluorescence labeled by incubating TK-1 cells at 2 × 10 6 cells/ml with 0.02 mg fluorescein diacetate (FDA) (Sigma) at 37°C for 30 min. The cells were then washed twice with ice-cold HBSS, spun at 250 g for 5 min to remove unincorporated fluorescence and suspended in HBSS. The TK-1 lymphocyte cell line used in this assay expresses high levels of the α4β7 integrin, [ 35 , 44 ] which can interact with multiple ligands including mucosal addressin-1 (MAdCAM-1), as well as VCAM-1, L-selectin and fibronectin [ 18 ]. In this system, TNF stimulated TK-1 adhesion to SVEC4-10 endothelial cells is at least 50% MAdCAM-1 dependent [ 35 ]. SVEC monolayers were grown in 48-well plates as described, and to activate endothelium, the monolayers were incubated with TNF-α (1 ng/ml) for 24 h. Cytokine treated endothelial cells were washed three times with media. Labeled TK-1 cells were then added to the endothelium at a 5:1 lymphocyte to endothelial cell ratio [ 31 ] and allowed to bind for 30 min under static conditions. At the end of the incubation period, the supernatant was removed and the Monolayers were washed twice with HBSS. Plates were read on a Fluorescent Ascent (Lab systems, Helsinki, Finland) set for excitation at 485 nm, and emission at 515 nm. Blank wells (0% TK-1 adhesion) were run as controls that did not contain labeled TK-1 cells; 100% adhesion was measured on monolayers where TK-1 cells were not removed from the supernatant. Abbreviations PPAR-γ – peroxisome proliferative activated receptor gamma MAdCAM-1 – Mucosal Addressin Cell Adhesion Molecule-1 VCAM-1 – Vascular Cell Adhesion Molecule-1 E-selectin – Endothelial Selectin ICAM-1 – Intercellular Adhesion Molecule-1 IBD – Inflammatory Bowel Disease TNF-α – Tumor Necrosis Factor-α Authors' contributions Dr. Sasaki accomplished the studies described in this manuscript, all authors contributed equally in the design, interpretation and execution of this article.

/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC549552.xml

517823

Mechanism of Association and Reciprocal Activation of Two GTPases

The signal recognition particle (SRP) mediates the cotranslational targeting of nascent proteins to the eukaryotic endoplasmic reticulum membrane or the bacterial plasma membrane. During this process, two GTPases, one in SRP and one in the SRP receptor (named Ffh and FtsY in bacteria, respectively), form a complex in which both proteins reciprocally activate the GTPase reaction of one another. Here, we explore by site-directed mutagenesis the role of 45 conserved surface residues in the Ffh-FtsY interaction. Mutations of a large number of residues at the interface impair complex formation, supporting the importance of an extensive interaction surface. Surprisingly, even after a stable complex is formed, single mutations in FtsY can block the activation of GTP hydrolysis in both active sites. Thus, activation requires conformational changes across the interface that coordinate the positioning of catalytic residues in both GTPase sites. A distinct class of mutants exhibits half-site reactivity and thus allows us to further uncouple the activation of individual GTPases. Our dissection of the activation process suggests discrete conformational stages during formation of the active SRP•SRP receptor complex. Each stage provides a potential control point in the targeting reaction at which regulation by additional components can be exerted, thus ensuring the binding and release of cargo at the appropriate time.

Introduction GTPases comprise a superfamily of proteins that provide molecular switches to regulate many cellular processes, including translation, signal transduction, cytoskeletal organization, vesicle transport, nuclear transport, and spindle assembly ( Gilman 1987 ; Bourne et al. 1991 ). In many cases, the GTPases exert their regulatory function through a “GTPase switch” mechanism ( Bourne et al. 1991 ) in which the GTPase assumes two alternative conformational states: an active, GTP-bound state and an inactive, GDP-bound state. Each state is kinetically stable, and interconversion between these states is facilitated by external regulatory factors, such as GTPase-activating proteins (GAPs) and guanine nucleotide exchange factors (GEFs). Two homologous GTPases, one in the signal recognition particle (SRP) and one in the SRP receptor (SR; called Ffh and FtsY in bacteria, respectively), mediate the cotranslational targeting of membrane and secretory proteins to the eukaryotic endoplasmic reticulum (ER) membrane or the bacterial plasma membrane. During the targeting reaction, SRP and SR switch between different functional states ( Walter and Johnson 1994 ; Keenan et al. 2001 ). SRP first binds to a nascent polypeptide that contains a signal sequence as it emerges from the ribosome ( Walter et al. 1981 ; Pool et al. 2002 ). The ribosome•nascent chain complex (RNC) is then delivered to the membrane via an interaction between the GTP-bound forms of SRP and SR. Upon arrival at the membrane, SRP releases its “cargo,” the RNC, to the translocation apparatus or the translocon ( Walter et al. 1981 ; Gilmore et al. 1982a , 1982b ). Once the RNC is released, both SRP and SR hydrolyze their bound GTPs to drive dissociation of the SRP•SR complex, allowing the SRP and SR components to be recycled ( Connolly and Gilmore 1989 ; Connolly et al. 1991 ). Analogous to other GTPases, the switch in the functional states of SRP and SR is coordinated by their GTPase cycles. However, the regulatory mechanism of the SRP family GTPases provides a notable exception to the “GTPase switch” paradigm. Unlike many other GTPases, no external GEFs or GAPs are known for the SRP and SR GTPases. Instead, Ffh and FtsY bind nucleotides weakly, and nucleotide dissociation and exchange are very fast ( Moser et al. 1997 ; Jagath et al. 1998 ; Peluso et al. 2001 ); thus, there is no requirement for external GEFs to facilitate their conversion from the GDP- to GTP-bound forms. In addition, Ffh and FtsY reciprocally activate each other's GTPase activity upon formation of the Ffh•FtsY complex ( Powers and Walter 1995 ; Peluso et al. 2001 ); thus, there is no requirement for external GAPs to facilitate their conversion from the GTP- to GDP-bound forms. The structure of Ffh and FtsY also defines them as a unique subgroup in the GTPase superfamily ( Freymann et al. 1997 ; Montoya et al. 1997 ). Both proteins contain a central GTPase “G” domain that shares homology with the classical Ras GTPase fold. In addition, all SRP family GTPases contain a unique “N” domain, which together with the G domain forms a structural and functional unit called the NG domain. The crystal structures of the individual Ffh and FtsY NG domains show that both proteins have a wide-open GTP-binding pocket, and the apoforms of these proteins are stabilized by a network of side-chain interactions in the empty active site ( Freymann et al. 1997 ; Montoya et al. 1997 ); the need to reposition the active-site residues for binding nucleotides may contribute to the low nucleotide affinities of these GTPases. Recently, the crystal structure of the GTP analog-bound Ffh•FtsY complex was determined ( Egea et al. 2004 ; Focia et al. 2004 ). The two proteins form a pseudosymmetrical heterodimer via an extensive interaction surface that includes both the G and N domains. A composite active site is formed at the interface in which the two nucleotides are “twinned” in a head-to-tail manner, forming reciprocal hydrogen bonds between the ribose 3′-OH of one GTP and the γ-phosphate of the other. Hydrolysis of the nucleotide at each active site is also facilitated by multiple catalytic groups from its own protein, brought into the active site by conformational rearrangements that occur upon complex formation. These substrate-substrate interactions in trans and active site-substrate interactions in cis thus provide a novel mechanism for the GTP-dependent association and reciprocal activation between the two GTPases. The unique structural and functional properties of the SRP and SR GTPases raise intriguing questions: (i) How do these GTPases act as reciprocal activating proteins for one another, and (ii) how does the SRP family of GTPases switch between the “on” and “off” states, as the GTPases are predominantly in the GTP-bound state as they enter the targeting cycle and no stable, GDP-bound state exists under cellular conditions? In a previous paper, we described a scanning mutagenesis study of the conserved surface residues of Escherichia coli FtsY and showed that mutations that have deleterious effects on the Ffh-FtsY interaction define a large surface patch on FtsY that lies on its interaction surface with Ffh identified in the crystal structure ( Egea et al. 2004 ). Here we show that these mutants can be categorized into distinct classes, each defective at a different step during the Ffh-FtsY interaction, suggesting that the Ffh-FtsY interaction is a dynamic process that involves multiple experimentally separable conformational changes. Thus, the mutants allow us to glean mechanistic insights into the alternative molecular switch that allows the SRP and SR to change their functional states. Results In light of the recently published structures of the Ffh•FtsY complex, kinetic analyses become increasingly valuable in unraveling the dynamic nature of the Ffh-FtsY interaction. To this end, we generated 45 site-directed mutants that were made in surface residues of FtsY. As previously described ( Egea et al. 2004 ), all but one mutation that functionally compromise the Ffh-FtsY interaction map to the extensive interaction surface between the two proteins ( Figure 1 ). As we show below, dissection of the mutational effect on individual steps allows us to divide the deleterious mutants into distinct classes: Class I mutants primarily affect complex formation, Class II mutants primarily affect the reciprocal GTPase activation, Class III mutants are defective in both steps, and Class IV or half-site mutants block the activation of only one GTPase site in the complex ( Table 1 ). Figure 1 The Mutational Effects in E. coli FtsY Mapped onto the Crystal Structure of the Ffh•FtsY Complex The bound nucleotides are shown as black sticks, and the dotted white lines in the interface view outline the contact surface of Ffh with FtsY. The colors denote different classes of mutational effects: blue, Class I mutants defective in complex formation; red, Class II mutants defective in the reciprocal GTPase activation; magenta, Class III mutants defective in both steps; green, Class IV mutants exhibiting half-site reactivity; yellow, Class V or neutral mutants. Table 1 Summary of Different Classes of Mutational Effects To facilitate comparison with the crystal structures solved using the Thermus aquaticus proteins, for each residue mutated in E. coli FtsY, the corresponding residue number in the T. aquaticus Ffh sequence is indicated in parentheses The k cat /K m values for each mutant were previously reported as supplementary material in Egea et al. (2004) . The compromised activity of these mutants is not due to defects in the folding of the mutant protein, as the basal GTP-binding and hydrolysis activities of all the mutants are either unaffected or only moderately (2- to 8-fold) reduced ( Egea et al. 2004 ) All of the Class I–III mutants have deleterious effects on the reciprocally stimulated GTPase reaction between Ffh and FtsY ( Figure 2 ). The protein concentration dependence of this reaction further indicates that the defects in these mutants can be functionally distinguished, allowing us to group them into different classes. For Class I mutants (see Figure 1 , blue), the maximal rate of GTP hydrolysis is within 3-fold of that of wild-type FtsY, although a significantly higher concentration of mutant than wild-type FtsY is required to reach saturation (data for a representative mutant are shown in Figure 2 A). Thus, these mutants are primarily defective in the Ffh-FtsY complex formation step, but the reciprocal activation of GTP hydrolysis is not significantly affected once the complex is forced to form at the higher FtsY concentrations. Figure 2 The Effect of FtsY Mutations on the Reciprocally Stimulated GTPase Reaction between Ffh and FtsY The stimulated GTPase reactions of (A) mutant FtsYE475(274)K (•), (B) FtsY T307(112)A (•), (C) FtsYA335(140)W (•), (D) FtsYR333(138)A (•), and wild-type FtsY (○) were determined as described in Materials and Methods . The insets show the reaction curve of the mutant FtsYs on an expanded scale. In contrast, for Class II and III mutants, the rate of GTPase reaction remains slow even at saturating concentrations of FtsY (data for representative mutants are shown in Figure 2 B– 2 D). There are two possible explanations for the defects of these mutants: (i) The reciprocal GTPase activation in the Ffh•FtsY complex is compromised, or (ii) both complex formation and reciprocal GTPase activation are affected. The concentration dependence of the stimulated GTPase reaction, however, does not provide an unambiguous way to distinguish between these possibilities, because different steps become rate limiting at different concentration regimes. For wild-type FtsY, the reaction is limited by complex formation with subsaturating FtsY, but becomes limited by GTP hydrolysis with saturating FtsY ( Peluso et al. 2001 ). Thus, for wild-type FtsY the K m of the reaction (1 μM) does not equal the K d (16 nM) of the Ffh•FtsY complex. Likewise, the K m of the reaction with mutant FtsY does not necessarily equal the K d of the mutant Ffh•FtsY complex, and thus cannot meaningfully distinguish between mutational effects on complex formation and GTPase activation. To circumvent these problems, we devised an assay to determine the ability of each FtsY mutant to inhibit the interaction of wild-type FtsY with Ffh. This assay allowed us to monitor selectively complex formation between Ffh and the FtsY mutants. The conditions of the assay were designed so that in the absence of any mutant FtsY as an inhibitor, a robust GTPase reaction mediated by Ffh and wild-type FtsY was observed ( Figure 3 A, k 0 ). Addition of mutant FtsY [FtsY(mt)], which can form a complex with Ffh, will sequester the Ffh molecules into a less active Ffh•FtsY(mt) complex ( k 1 ≪ k 0 ; see Figure 2 B– D), thus inhibiting the observed GTPase reaction. The reaction was carried out with subsaturating concentrations of wild-type FtsY to ensure that Ffh molecules were predominantly in the free form and able to bind FtsY(mt); under these conditions, the inhibition constant K i equals K d , the dissociation constant of the Ffh•FtsY(mt) complex. Figure 3 Determination of Complex Formation between Ffh and FtsY Mutants (A) Inhibition assay for determining the affinity of mutant FtsY proteins for Ffh, as described in the text and in Materials and Methods . (B and C) Representative inhibition curves are shown for FtsY mutants (B) T307(112)A and (C) A335(140)W. The data were fit to equation 3 in Materials and Methods . Most of the mutants inhibit the reaction only weakly, with inhibition constants about 10 2 -fold weaker than the affinity of wild-type FtsY for Ffh (data for a representative mutant are shown in Figure 3 B; a complete list of K i values is given in Table 2 ). These mutants are therefore defective in both complex formation and GTPase activation (defined as Class III mutants; see Figure 1 , magenta). These mutations involve residues throughout the entire G domain, including the interface between the N and G domains (see Figure 1 ). Thus, complex formation and GTPase activation are highly coupled. This is presumably due to the fact that the two GTPs are bound at a composite active site formed at the interface, so that many residues that contribute to GTP hydrolysis are also crucial for formation of the interface. Table 2 Affinity of FtsY Mutants for Ffh Determined from the Inhibition Assay In contrast, six mutants (involving mutation of five residues) stood out as strong inhibitors. These mutants (here defined as Class II mutants; see Figure 1 , red) can therefore form tight complexes with Ffh and are primarily compromised in the reciprocal activation of GTP hydrolysis. One of these, FtsY A335(140)W, showed an inhibition constant of 16 nM ( Figure 3 C), indistinguishable from the K d of the wild-type Ffh•FtsY complex ( Peluso et al. 2000 ). Moreover, the association and dissociation rate constants ( Figure 4 B and 4 C, respectively) for complex formation are also indistinguishable between mutant FtsY A335(140)W and wild-type FtsY, as measured using tryptophan fluorescence changes upon complex formation ( Figure 4 A) as previously described ( Jagath et al. 2000 ; Peluso et al. 2000 ). Like the wild-type FtsY, this fluorescence change upon complex formation requires the presence of GTP or the nonhydrolyzable GTP analog GMPPNP (5′-guanylylimidodiphosphate; unpublished data), indicating that the interaction of the Class II mutants with Ffh remains nucleotide dependent. The remaining Class II mutants also have inhibition constants well in the submicromolar range, albeit 10-fold higher than that of FtsY A335(140)W ( Table 2 ). Figure 4 Fluorescence Characterization of Complex Formation between Ffh and Mutant FtsYA335(140)W (A) The tryptophan fluorescence of mutant FtsYA335(140)W changes upon complex formation with Ffh. Complex formation was initiated by the addition of Mg 2+ , as described previously ( Shan and Walter 2003 ). Other Class II mutants do not exhibit as significant a fluorescence change (unpublished data). Thus, the conformational change that alters the environment surrounding the fluorescent W343(148) does not occur even though these mutants can form stable complexes with Ffh. (B) Association rate constants for complex formation with mutant FtsYA335(140)W (○) and wild-type FtsY(•). Linear fits to the data gave association rate constants of 6.36 × 10 4 and 6.34 × 104 M −1 s −1 for wild-type and mutant FtsY, respectively. (C) Dissociation rate constants of the Ffh•FtsY complexes formed by mutant FtsYA335(140)W (upper curve) and wild-type FtsY (lower curve). First-order fits to the data gave dissociation rate constants of 3.6 × 10 −3 and 4.2 × 10 −3 s −1 for wild-type and mutant FtsY, respectively. The mutants described above were identified by analyzing the sum of the two GTP hydrolysis reactions from both Ffh and FtsY. All of the Class II and III mutants must be defective in both GTP hydrolysis events; inhibition of only one GTPase site would be predicted to give at most a 2-fold effect because both sites hydrolyze GTP at about the same rate. Half-site mutants defective in GTP hydrolysis in only one active site, however, could be hidden among the Class I and the neutral mutants. To explore this possibility, we monitored the two hydrolysis events individually. To this end, we took advantage of a xanthosine-5′-triphosphate (XTP)-specific Ffh mutant, Ffh D251(248)N. Asp251(248), located in the GTP-binding consensus motif, is conserved throughout the GTPase superfamily and forms a hydrogen bonding network with the N2 and N3 amino protons on the guanine ring ( Hwang and Miller 1987 ; Weijland and Parmeggiani 1993 ). The Asp → Asn mutation weakens the affinity of Ffh for GTP by 200-fold and increases its affinity for XTP by 10 2 -fold, resulting in a 10 4 -fold switch in nucleotide specificity (SS and PW, unpublished data). In the presence of XTP, Ffh D251(248)N stimulates the GTPase reaction of FtsY and, reciprocally, its XTPase reaction is stimulated by FtsY in the presence of GTP. We therefore used Ffh D251(248)N to monitor the individual hydrolysis events—XTP hydrolysis from Ffh D251(248)N and GTP hydrolysis from the mutant FtsY constructs—in the Ffh D251(248)N•FtsY complex. As expected, all of the Class II and Class III mutants were defective in both hydrolysis reactions and, similarly, all but one Class I mutant and most of the neutral mutants showed no significant defect in either of the two reactions (unpublished data). Five half-site mutants, however, stood out from the pool of originally categorized Class I and neutral mutants (see Table 1 , Class IV mutants, and Figure 1 , green). As expected, the sum of the two GTP hydrolysis reactions was impaired by less than 2-fold in the Class IV mutants (data for a representative mutant are shown in Figure 5 A; data for all the Class IV mutants are summarized in Table 3 , first column). In contrast, the rates of GTP hydrolysis of all Class IV mutants are reduced by 20- to more than 100-fold ( Figure 5 B and Table 3 , second column). The reciprocal reaction reveals the striking asymmetry of the inhibition: XTP hydrolysis from Ffh D251(248)N is reduced by only 2- to 5-fold ( Figure 5 C and Table 3 , third column). Figure 5 Half-Site Mutants Are Compromised in the Hydrolysis Reaction from the FtsY but Not Ffh Active Site (A) The reciprocally stimulated GTPase reaction with wild-type Ffh for wild-type FtsY (○) and mutant FtsYG455(254)W (•). (B) The FfhD251N-stimulated GTPase reaction from wild-type FtsY (○) and mutant FtsYG455(254)W (•), determined as described in Materials and Methods . (C) The XTP hydrolysis reaction from FfhD251N stimulated by wild-type FtsY (○) and mutant FtsYG455(254)W (•), determined as described in Materials and Methods . Table 3 Summary of the Relative Reactivity of Class IV(Half-Site) Mutants in the Individual Nucleotide Hydrolysis Reactions from the Two Active Sites: Reaction of FtsY Mutants with XTP-Specific FfhD251N The reaction rates were determined as described in Materials and Methods , and are listed as relative to that of wild-type FtsY a It is interesting to note that the G454(253)A mutant has the same rate constant as wild-type FtsY for GTP hydrolysis from the *GTP• Ffh•FtsY •GTP* complex, even though only one of the two GTPase sites, that from Ffh, is active in the complex formed by the mutant. It is possible that the G454(253) mutation, situated at the interface between the two GTPases, might have slightly altered the conformation of the Ffh GTPase site to allow a faster reaction from this site. Nevertheless, the small magnitude of this effect (<2-fold) does not warrant a more specific molecular interpretation To provide additional evidence for half-site reactivity, we introduced three of the Class IV mutations into an XTP-specific FtsY, FtsY D449(248)N, thereby reversing the nucleotide specificity of the two binding partners. Upon complex formation, FtsY D449(248)N becomes XTP specific and reciprocally activates GTP hydrolysis in Ffh. Consistent with the results observed with Ffh D251(248)N, all Class IV mutations thus analyzed reduce the rate of XTP hydrolysis from mutant FtsYs by more than 10 2 -fold, whereas the reciprocal reaction, GTP hydrolysis by Ffh, is reduced only 2- to 4-fold ( Table 4 ). Thus taken together, Class IV mutations break the symmetry and the remarkable coupling between the two GTPase sites in the Ffh•FtsY complex, such that the nucleotide bound at one active site is hydrolyzed much faster than the nucleotide at the other site. Table 4 Summary of the Relative Reactivity of Class IV(Half-Site) Mutants in the Individual Nucleotide Hydrolysis Reactions from the Two Active Sites (Continued from Table 3 ): Reaction of Ffh with Mutant FtsYs that also Bear the XTP-Specific D449(248)N Mutation The reaction rates were determined as described in Materials and Methods , and are listed as relative to that of FtsY D449(248)N Discussion The mutational analyses described here define four distinct classes of mutants that map to the Ffh-FtsY interface. Each mutant class blocks the reaction in a different way and at a distinct stage, demonstrating that (i) multiple conformational rearrangements are required to form an activated Ffh•FtsY complex and (ii) some rearrangements can be blocked without preventing other rearrangements from taking place. The different classes of mutant interrupt the reaction in different ways, as represented by the states depicted in Figure 6 A, in the pathway of Ffh•FtsY complex formation and reciprocal GTPase activation. The most plausible interpretation of our analysis and the crystallographic analysis of the Ffh•FtsY complex suggest that each of the states blocked by the mutants represents a step on the pathway for the wild-type protein. However, we cannot rule out that some of the rearrangements could occur independently of one another, in which case their depicted order represents only one of the possibilities. Our analysis leads to the conclusion that perturbations, such as those introduced here by site-specific mutations, can modulate specific conformational changes during the Ffh-FtsY interaction. Each of these states provides a potential regulatory point during the protein-targeting reaction, at which analogous effects could be exerted by the cargoes of SRP and SR—the ribosome, signal sequence, and translocon. Figure 6 Model for Conformational Changes during Ffh-FtsY Reciprocal GTPase Activation and Implications for the Protein-Targeting Reaction (A) Model for conformational changes during formation of an activated Ffh-FtsY complex. Step a is the rearrangement of both proteins from the open to the closed state during complex formation. Step b is the coordinate docking of the IBD loops into the active sites, and step c is the docking of the Arg191s. Step d is the additional rearrangement of residues that completes one or the other GTPase site. Step e is the rearrangement that completes the other active site. GTP can be hydrolyzed from either the hemiactivated complexes (step f) or the activated complex (step g) to drive complex dissociation. (B–D) Catalytic interactions made by residues exhibiting the Class II phenotype. FtsY is in surface representation, the catalytic residues from FtsY are depicted as red sticks, the nucleotides bound to FtsY and Ffh are in dark green and dark blue, respectively, and the dotted lines depict hydrogen bonds or van der Waals contacts. (B) Interaction of IBD loop with GTP in the FtsY active site. The blue ball represents the attacking water molecule (A.W.); the violet red ball represents the active site Mg 2+ . (C) Interactions of Asn111(107) at the Ffh-FtsY interface. The residue homologous to Asn111, Gln107 in Ffh, is in violet red. (D) Arg195(191) is in a “pending” position. The residue homologous to Arg191 in Ras, Gln61, is in violet red. (E) Conformational changes in the GTPase domains of SRP and SR provide potential regulatory points during the protein-targeting reaction. Step 1, SR undergoes an open → closed conformational change upon association with the membrane translocon. Step 2, SRP undergoes an open → closed conformational change upon association with the ribosome and nascent polypeptide. Step 3, complex formation between SRP and SR delivers the cargo to the membrane. Step 4, cargo release from SRP allows the SRP•SR complex to undergo additional conformational changes to activate GTP hydrolysis. Step 5, SRP dissociates from SR after GTP is hydrolyzed. Note that steps 1–3 correspond to Ffh-FtsY binding (step a) in the model shown in (A), step 4 corresponds to Ffh•FtsY activation (steps b–e) in the model shown in (A), and step 5 corresponds to Ffh•FtsY complex dissociation (step g) in the model shown in (A). Step A: An “Open”-to-“Closed” Conformational Change upon Complex Formation We previously showed that FtsY exhibits little discrimination between different nucleotides in its free, uncomplexed form, but gains substantial specificity for GTP only in the Ffh•FtsY complex ( Shan and Walter 2003 ). We therefore proposed that upon complex formation, FtsY changes from a floppy, nonspecific “open” state to a more specific, “closed” state in which the nucleotide is better positioned at the active site and contacts between the guanine ring and Asp449(248), the nucleotide specificity determinant, are established ( Figure 6 A, step a). The recently determined crystal structures of the Ffh•FtsY complex support this notion ( Egea et al. 2004 ; Focia et al. 2004 ). Upon complex formation, a major rearrangement occurs at the N-G domain interface, allowing Asp449(248) to move closer to the guanine ring and form hydrogen bonds, thus explaining the enhanced nucleotide specificity of FtsY upon complex formation. We therefore propose that the N-G domain rearrangement during complex formation is central to the open → closed conformational change. The crystal structure of the Ffh•FtsY complex also shows that Ffh undergoes similar N-G domain rearrangements upon complex formation, although the effects of this rearrangement on nucleotide specificity are less apparent, as free Ffh already displays significant discrimination between nucleotides (SS and PW, unpublished data). Indeed, mutations at the N-G domain interface in either Ffh or FtsY impair complex formation, supporting the functional importance of this rearrangement in both binding partners ( Lu et al. 2001 ). We propose that both free GTPases oscillate between the open and closed states, and that complex formation drives the equilibrium to the closed state ( Figure 6 A, step a). Steps B and C: Docking of Active-Site Residues at the Interface The Class II mutants allow stable complexes to form but are specifically defective in reciprocal GTPase activation, thus suggesting that the reaction occurs in two steps that can be uncoupled. Further, all of the Class II mutants exhibit significant nucleotide specificity in their interaction with Ffh (unpublished data), suggesting that the mutant proteins have assumed the closed conformation in the complex. Because single mutations in FtsY can disrupt GTPase activation in both active sites, the defect in these mutants is not a consequence of simply removing a catalytic residue. Rather, this suggests that even after a stable, closed complex is formed, activation requires additional conformational changes (the “docking” process) that align active-site residues with respect to the bound nucleotides in both GTPase sites ( Figure 6 A, closed →→ docked). Furthermore, as both sites are affected, these rearrangements are highly cooperative and bridge the interface between the two GTPases. The model in Figure 6 portrays the docking event as two sequential steps: Step b represents the concerted rearrangements of the IBD loops that lead to the predocked state ( Egea et al. 2004 ; Focia et al. 2004 ). Step c represents the additional rearrangements of the Arg191s in both Ffh and FtsY to form the docked complex. The observation that the crystal structure is “trapped” in a state with the IBD loop docked but with the Arg191s undocked suggests that docking of the IBD loop either precedes that of the Arg191s, as depicted in Figure 6 A, or that these two rearrangements can occur independently of one another. Evidence for the importance of a concerted rearrangement of the IBD loops (step b) comes from three of the Class II mutants, [R333(138)A, A335(140)W, and A336(141)W], which all map to the conserved IBD loop (D 135 TFRAAA). As concluded from the structure, this loop can move relatively independently from the rest of the protein ( Egea et al. 2004 ; Focia et al. 2004 ). As a result, additional interface contacts are formed between the two loops, and multiple catalytic residues are brought into the active site and positioned close to the nucleotides. Figure 6 B highlights the catalytic interactions contributed by these residues: Asp139(135) coordinates the attacking water (A.W.), Arg142(138) coordinates the γ-phosphate oxygen, and Gln148(144) coordinates the β-phosphate oxygen and the active site Mg 2+ . Most importantly, disruption of any of these contacts also destroys activation of the other GTPase site. Therefore, coordinate docking of the IBD loops from both interacting partners into their respective active sites is crucial for reciprocal GTPase activation ( Figure 6 A, step b). Mutation of Asn302(107) to either Ala or Trp also results in a Class II phenotype. This residue in FtsY hydrogen bonds across the interface to the ribose 3′-OH of the nucleotide bound to Ffh. The ribose 3′-OH reciprocally donates a hydrogen bond back to the γ-phosphate of the twinned substrate in FtsY [ Figure 6 C, N111(107)]. This interaction is matched by a contact between Q107 of Ffh and the ribose of the nucleotide bound to FtsY ( Figure 6 C, Q107). These side chains are the only ones that interact with the opposing substrate, and, in addition to the IBD loops, form a second network of catalytically important interactions that bridges the two active sites. Because both of these networks are observed in the crystal structures, we cannot distinguish at this time whether the two networks are assembled coordinately, sequentially, or independently. Potentially, therefore, step b in Figure 6 A could be further subdivided. In contrast to the other Class II mutants, the side chains of the Arg191s point away from the γ-phosphate group in the crystal structure. By analogy to the homologous residue Gln61 in the Ras • Ras GAP structure, which contacts the γ-phosphate, Focia et al. (2004) proposed that Arg191s are in a “pending” position, forming a “latch” structure that requires additional rearrangements to activate the GTPases, as depicted in Figure 6 A (step c) and 6 D. The deleterious effect on catalysis displayed by the Arg386(191) mutant strongly supports this notion. Because both active sites are affected by the Arg386(191) mutation, the consequences of this additional contact must be transmitted across the interface, perhaps resulting in a slight rearrangement of the twinned GTP molecule to optimize active site-substrate interactions in the other GTPase. Step D: Conformational Changes to Activate Individual GTPases Remarkably, the Class IV, or half-site, mutants demonstrate that activation of the individual GTPase sites can be further uncoupled from one another. This suggests that after all the molecular rearrangements required to activate the interacting GTPase have been accomplished, additional rearrangements are required to complete each active site. Further, these rearrangements either occur late in the docking process ( Figure 6 A) or they occur independently of the various docking steps. In contrast to the docking steps that are tightly coupled between the two active sites, these additional rearrangements can occur independently in one GTPase but not the other, leading to the formation of “hemiactivated” intermediates ( Figure 6 A, step d). Four of the five Class IV half-site mutants (see Figure 1 , green) are positioned away from the γ-phosphate group: G454(253) and G455(254) map to the conserved DARGG motif at the NG domain interface, L480(279) maps to the “closing loop” that packs against the guanine base, and Q430(229) is situated away from any residue for which a function can be assigned intuitively. The mechanistic interpretation of these mutants will have to await structural information from crystallization of the mutant proteins and additional characterization of the dynamics during Ffh-FtsY association and activation. Importantly, all of the half-site mutants are less than 2-fold reduced in the rate of multiple-turnover GTPase reactions, indicating that multiple cycles of Ffh•FtsY complex formation and dissociation can still occur efficiently. Thus, only one of the two bound GTPs needs to be hydrolyzed in order for the Ffh•FtsY complex to dissociate ( Figure 6 A, step f). In the wild-type Ffh•FtsY complex, it is well established that both nucleotides are hydrolyzed during each turnover. Thus, after a hemiactivated state is formed, rearrangement of the other GTPase site must follow on a time scale faster than the rate of GTP hydrolysis or complex dissociation ( Figure 6 A, step e), so that a fully activated complex is formed and both GTP molecules are hydrolyzed ( Figure 6 A, step g). Implications for the Protein-Targeting Reaction During protein targeting, SRP and SR are thought to interact with their respective cargoes, the RNC and the translocon. Thus, targeting involves a series of ordered steps in which cargo binding and release must occur at the proper stages. Each of the conformational changes in the GTPase domains of SRP and SR described above provides a potential point at which such control can be exerted, thereby coordinating the loading and unloading of cargoes ( Figure 6 E). One possible view is that the switch from open to closed conformation provides the regulatory point that distinguishes free from cargo-loaded SRP and SR. Under cellular conditions, both SRP and SR are likely to be GTP bound before entering the targeting reaction. Thus, GTP binding per se cannot be the switch that sets these GTPases to the “on” state, as happens with classical signaling GTPases. Free SRP receptor is predominantly in the open conformation; interaction with phospholipid membranes and the translocon could shift its conformational equilibrium towards the closed state ( Figure 6 E, step 1), thereby facilitating its interaction with SRP. Reciprocally, the SRP could undergo a similar open-to-closed conformational change, facilitated by association with the RNC ( Figure 6 E, step 2). In this view, the SRP and receptor molecules that are prebound to their respective cargoes are “primed” to interact with each other, ensuring efficient delivery of cargo proteins to the membrane and avoiding futile cycles of SRP-receptor interactions ( Figure 6 E, step 3). Once at the membrane, it is crucial that SRP releases its cargo to the translocon before it dissociates from the SRP receptor. Because both GTPases reciprocally activate each other, regulation of GTP hydrolysis must involve mechanisms different from regulation by external GAPs, as happens with classical signaling GTPases. The conformational changes required for GTPase activation ( Figure 6 A, steps b–d) provide the potential to control the relative timing of the cargo release versus GTP hydrolysis steps. In solution, the SRP•SR complex exists only transiently, with a half-life of less than 1 s, because rapid GTP hydrolysis drives complex dissociation. However, RNC, SRP, and SR can be cross-linked to each other in the absence of the translocon ( Song et al. 2000 ). Although this does not provide conclusive evidence, it is an attractive possibility that RNC could delay GTP hydrolysis, possibly by inhibiting one of the docking steps described here ( Figure 6 A, steps b–d), thereby ensuring that the cargo is released from SRP before GTP is hydrolyzed ( Figure 6 E, step 4). Release of the cargo then allows the SRP•SR complex to undergo the additional rearrangements to activate GTP hydrolysis, leading to complex dissociation ( Figure 6 E, step 5). The demonstration that hemiactivated complexes can exist and that hydrolysis of a single GTP is sufficient for complex dissociation ( Figure 6 A, steps d and f) raises intriguing questions as to the precise role of the individual GTP hydrolysis events during each cycle of the targeting reaction. Potentially, asymmetric, half-site hydrolysis could be used to introduce branches into the pathway, leading to abortive targeting reactions. In this way, the GTP hydrolysis events could have proofreading roles similar to those proposed for translation elongation factors to help ensure the fidelity of protein targeting. The analysis described here therefore not only dissects the reciprocal GTPase activation events into a set of conformational rearrangements, but also provides invaluable tools to assess the role of these states as potential control points in the targeting reaction. Materials and Methods Cloning and purification of mutant proteins. Expression plasmids for mutant FtsYs were constructed from that for wild-type FtsY(47–497) using the QuickChange Mutagenesis protocol (Stratagene, La Jolla, California, United States). Mutant FtsY proteins were expressed and purified using the same procedure as that for wild-type FtsY ( Powers and Walter 1997 ; Peluso et al. 2001 ). Kinetics. GTP hydrolysis reactions were followed and analyzed as described in Peluso et al. (2001) . The reciprocally stimulated GTPase reactions between Ffh and FtsY were measured in multiple-turnover experiments ([GTP] > [E]) with a small fixed amount of Ffh and varying amounts of wild-type or mutant FtsY, and the FtsY concentration dependences were analyzed as described in Peluso et al. (2001) . The Ffh(D251N)-stimulated GTPase reaction of FtsY was determined in single-turnover experiments in the presence of 10 μM FtsY and varying amounts of Ffh(D251N), with 50 μM XTP present to selectively occupy the Ffh(D251N) active site [ K XTP d = 0.37 and 460 μM for Ffh(D251N) and FtsY, respectively; SS and PW, unpublished data; Shan and Walter 2003 ]. The concentration dependence of the observed GTPase rate constant is fit to equation 1 , in which k max is the maximal rate constant with saturating Ffh(D251N), and K 1/2 is the concentration of Ffh(D251N) required to reach half saturation. The reciprocal reaction, the FtsY-stimulated XTPase reaction of Ffh(D251N), was determined in single-turnover experiments with 1 μM Ffh(D251N) and varying amounts of FtsY. 50 μM GTP was present to ensure that FtsY was selectively bound with GTP [ K GTP d = 15 μM and 101 μM for FtsY and Ffh(D251N), respectively; SS and PW, unpublished data; Shan and Walter 2003 ]. The FtsY concentration dependence is fit to equation 2 , in which k max is the maximal rate constant with saturating FtsY, and K 1/2 is the concentration of FtsY required to reach half saturation. The affinity of mutant FtsY proteins for Ffh was determined using an inhibition assay that measures the ability of mutant FtsYs [FtsY(mt)] to inhibit the interaction between Ffh and wild-type FtsY, as described in detail in the text (see Figure 3 A). The data are fit to equation 3 , derived from Figure 3 A. Fluorescence measurements. Fluorescence emission spectra were acquired as described in Peluso et al. (2000) in the presence of 1 μM mutant or wild-type FtsY, 2 μM SRP, and 100 μM GppNHp, and complex formation was initiated by addition of Mg 2+ as described in Shan and Walter (2003) . The rate constants for association and dissociation of the Ffh•FtsY complex were determined by following the time course of the fluorescence change at 335 nm as described in Peluso et al. (2000 , 2001 ).

/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517823.xml

554098

A novel replication-independent histone H2a gene in mouse

Background An uncharacterized histone H2a-coding transcript (E130307C13) has been cloned from a mouse full-length cDNA library. This transcript is encoded on chromosome 6, approximately 4 kb upstream of a histone H4 gene, Hist4h4 . The proteins encoded by this transcript and the human H2afj mRNA isoform-2 have the highest amino acid similarity. In this paper, we characterize it from the expression pattern given by quantitative RT-PCR. Results Quantitative RT-PCR indicated that the gene that encodes E130307C13 ( E130307C13 ) is regulated in a replication-independent manner, and therefore it is H2afj . Certainly, H2afj transcript lacks a stem-loop structure at the 3'-UTR but contains a poly (A) signal. In addition, its promoter region has a different structure from those of the replication-dependent histone H2a genes. Conclusion The bioinformatics imply that E130307C13 is a replication-independent H2a gene. In addition, quantitative RT-PCR analysis shows that it is replication-independent. Thus, it is H2afj , a novel replication-independent H2a gene in mouse.

Background Replication of the eukaryotic chromosomes requires the synthesis of histones to package the newly replicated DNA into chromatin. Control of the level of histone mRNA accounts for much of the control of histone protein synthesis [ 1 ]. Mouse has 18 replication-dependent histone H2a genes [ 2 ]. Among these 18 genes, 13 genes are located in the Hist1 cluster on chromosome 13, 4 in the Hist2 cluster on chromosome 3 and 1 in the Hist3 cluster on chromosome 11 [ 2 ]. The histone mRNAs that are cell-cycle-regulated increase 35-fold as cells progress from mitosis through G1-phase and into S-phase [ 3 ]. The promoters of histone genes contain CCAAT and TATA boxes [ 4 ]. The replication-dependent histone H2a genes lack introns and a poly (A) signal. They have a conserved stem-loop structure (5'-GGCTCTTTTCAGAGCC-3') at the 3'-UTR, which plays an important role in mRNA processing and stability [ 5 - 7 ]. Mouse also has two replication-independent histone H2a genes, H2afx on chromosome 9 and H2afz chromosome 3. These two genes encode polyadenylated mRNAs. H2afx mRNA has both a polyadenylated tail and a stem-loop structure [ 8 ]. Mouse replication-dependent histone H2a mRNAs and H2afx mRNA have a nuclear export element (5'-ACAACAAGAAGACGCGCATCAT-3') in the protein-coding region that functions to export the mRNA from the nucleus to the cytoplasm [ 9 ]. An uncharacterized histone H2a-coding transcript (E130307C13, FANTOM clone ID; NM_177688, Genebank accession number) has been cloned from a mouse full-length cDNA library. E130307C13 lies on chromosome 6, approximately 4 kb upstream of Hist4h4 . In this paper, we characterize it from the expression pattern given by quantitative RT-PCR. In addition to this, we compared the structure with the sequences deposited in the international DNA/protein database. Results and discussion Comparison of the putative amino acid sequence encoded by E130307C13 with the amino acid sequences deposited in the international DNA/protein database showed that it has the highest similarity to that encoded by human H2afj mRNA isoform-2 (NM_177925, Genebank accession number; Figs. 1 , 2 ). Human has two isoforms of H2afj [ 10 , 11 ]. Isoform-1 (NM_018267, Genebank accession number) is produced after splicing of two introns; isoform-2 does not need intron splicing for maturation. Interestingly, H2afj also lies near a histone H4 gene, on human chromosome 12. According to the nomenclature of histone genes [ 2 ], if E130307C13 is regulated in a replication-dependent manner, it is recognized as Hist4h2a . But if it is regulated in a replication-independent manner, it is recognized as H2afj . Figure 1 Phylogenetic relationships among 44 amino acids sequences from human and mouse histone H2a related proteins. The bar indicates 5% difference of sequence. The numbers at the branches indicate percentage of 1000 bootstrap analyses. (H) and (M) indicate the human sequence and mouse sequence, respectively. Figure 2 Alignment of the human and mouse histone H2a proteins in Fig. 1. Each product of the quantitative RT-PCR gave a single band on the agarose gel of the expected size (Fig. 3 ). Observation using the quantitative RT-PCR showed that the expression pattern of E130307C13 is typical of replication-independent histone gene (Table 1 , Fig. 3 ). The expression pattern of E130307C13 is more similar to that of the replication-independent H2afz than to that of the replication-dependent Hist2h2aa2 . The expression of Hist2h2aa2 increased along with cell cycle progression from the beginning of S-phase (0 h), peaked at 2 h, and then decreased (Fig. 3 ). On the other hand, E130307C13 and H2afz were expressed constantly (Fig. 3 ). These results suggest that E130307C13 is a replication-independent histone H2a gene in mouse. According to the nomenclature of histone genes [ 2 ], E130307C13 is recognized not as Hist4h2a but as H2afj . Table 1 C T values, ΔC T , and ΔΔC T Time (h) GAPDH E130307C13_1 ΔC T ΔΔC T Expression E130307C13_2 ΔC T ΔΔC T Expression Hist2h2aa_1 ΔCt ΔΔC T Expression Hist2h2aa_2 ΔC T ΔΔC T Expression H2afz ΔC T ΔΔC T Expression 0 14.4 19.1 4.65 0 1 20 5.61 0 1 18.1 3.63 0 1 19.3 4.9 0 1 16.8 2.35 0 1 1 14.4 19 4.64 -0.01 1.01 20.1 5.71 0.1 0.93 17.5 3.1 -0.53 1.44 19.2 4.79 -0.11 1.08 16.6 2.26 -0.09 1.06 2 14.4 18.9 4.54 -0.11 1.08 19.7 5.32 -0.29 1.22 16.8 2.42 -1.21 2.31 18.3 3.92 -0.98 1.97 16.7 2.33 -0.02 1.01 3 14.3 18.8 4.5 -0.15 1.11 19.7 5.4 -0.21 1.16 16.8 2.48 -1.15 2.22 18.3 3.92 -0.98 1.97 16.8 2.46 0.11 0.93 4 14.4 19.2 4.78 0.13 0.91 19.9 5.49 -0.12 1.09 17.2 2.79 -0.84 1.79 18.3 3.93 -0.97 1.96 16.8 2.43 0.08 0.95 5 14.4 19.2 4.82 0.17 0.89 20 5.61 0 1 17.1 2.66 -0.97 1.96 18.6 4.17 -0.73 1.66 16.8 2.42 0.07 0.95 6 14.1 19.8 5.69 1.04 0.49 20.4 6.33 0.72 0.61 18.4 4.29 0.66 0.63 19.9 5.8 0.9 0.54 16.8 2.71 0.36 0.78 7 14.2 19.7 5.45 0.8 0.57 20.3 6.11 0.5 0.71 17.6 3.35 -0.28 1.21 19 4.83 -0.07 1.05 16.9 2.7 0.35 0.78 8 14.3 19.2 4.87 0.22 0.86 20.1 5.71 0.1 0.93 17.6 3.3 -0.33 1.26 19.2 4.81 -0.09 1.06 16.9 2.55 0.2 0.87 9 14.3 19.3 5.03 0.38 0.77 20 5.76 0.15 0.9 17.8 3.54 -0.09 1.06 19.3 5.01 0.11 0.93 16.6 2.34 -0.01 1.01 10 14.2 19.1 4.83 0.18 0.88 19.8 5.58 -0.03 1.02 17.8 3.6 -0.03 1.02 18.7 4.5 -0.4 1.32 16.6 2.4 0.05 0.97 11 14.3 19.8 5.5 0.85 0.55 20.2 5.87 0.26 0.84 18.3 4 0.37 0.77 19.2 4.91 0.01 0.99 16.2 1.94 -0.41 1.33 Figure 3 RT-PCR products on agarose gel and expression patterns. Lanes 1, 100 bp ladder; 2, RT-PCR product amplified with E130307C13 primer set 2; 3, that with E130307C13 primer set 1; 4, that with Hist2h2aa2 primer set 1; 5, that with Hist2h2aa2 primer set 2; 6, that with H2afz primer set. Upstream of the 5'-end of E130307C13 , no TATA box was found. In addition, the first CCAAT box lies 230 bases upstream of the translation start codon (Fig. 4 ). The other replication-dependent H2a genes have the first CCAAT and TATA boxes within 100 bases upstream of the translation start codon (Fig. 4 ). The replication-independent genes H2afx and H2afz also have a TATA box (Fig. 4 ). Thus, histone H2a genes have a TATA box in the promoters, except for E130307C13 . Interestingly, the promoter of H2afz lacks CCAAT box but includes TATA box, on the other hand, that of E130307C13 lacks TATA box but includes CCAAT box (Fig. 4 ). Figure 4 Sequences between CCAAT and TATA boxes upstream of the histone H2a and E130307C13 coding regions. Underlines indicate CCAAT and TATA boxes. The ATGs located at the 3'-end indicate translation start codon. Numbers in parentheses represent numbers of bases not shown. The Hist1h2aj is a pseudogene, lacking a start codon. In addition, the 3'-UTR of the E130307C13 mRNA does not include the conserved stem-loop structure (Fig. 5 ). But the E130307C13 mRNA has two poly (A) signals at the middle and near the 3'-end. It indicates that the E130307C13 gives rise to two differentially polyadenylated mRNA transcripts. Considering the position at the 3'-UTR, it has a possibility that the poly (A) signal near the 3'-end is functional. Except for the pseudogene Hist1h2aj , the replication-dependent H2a mRNAs have the conserved stem-loop structure at the 3'-UTR. H2afx gives rise to a cell-cycle-regulated mRNA ending in the stem-loop when it is transcribed during S-phase, and a polyadenylated mRNA that is present in G1-phase cells [ 2 , 8 ]. H2afz mRNA lacks the stem-loop structure and has poly (A) signals. H2afz contains four introns in the protein-coding region and needs a splicing mechanism to produce the mature mRNA. Interestingly, E130307C13 lacks introns. Comparing the transcript structure of E130307C13 with those of the other histone H2a genes suggests that E130307C13 has replication-independent characteristics. Figure 5 Alignment of nuclear export elements and stem-loop structures. ATG indicates translation start codon. TAA or TGA indicates translation stop codon. Conclusion The bioinformatics imply that E130307C13 is a replication-independent H2a gene. In addition, quantitative RT-PCR analysis shows that it is replication-independent. Thus, it is H2afj , a novel replication-independent H2a gene in mouse. Methods Phylogenetic tree construction Multiple alignment of 44 amino acids sequences of histone H2a related proteins from human and mouse was created using the CLUSTAL W [ 12 ] on the DNA Databank of Japan. The phylogenetic tree by the neighbor-joining method with 1000 bootstrap analyses was constructed based on the multiple alignment using MEGA version 2.1 [ 13 ]. Cell cycle synchronization The cell cycle of Hepa 1–6 cells was synchronized at the end of G1-phase by the addition of thymidine-hydroxyurea. The cell cycle arrest was released by washing out the thymidine-hydroxyurea, then the cells were harvested at intervals of 1 h from 0 h to 11 h. RNA extraction Total RNA was extracted by using the RNeasy mini kit (Qiagen) according to the manual for the cell line. After that, each sample was treated with DNase I. cDNA synthesis RNA (approximately 0.5 μg) and random hexamer primers were heated to 70°C for 10 min, followed by cooling on ice for 5 min. The cDNA was synthesized using Superscript III First Strand buffer (Invitrogen) according to the manual. The reverse transcriptase was inactivated by a 15-min incubation at 70°C. Quantitative PCR The following primers were used: 5'-AACTGTAGCCCGGCCCG-3' and 5'-TTCGTCTGTTTGCGCTTT-3' (primer set 1, product size 100 bp) and 5'-CAACAAGCTGCTGGGCAAA-3' and 5'-TCGCCTTATGGTGGCTCTCC-3' (primer set 2, product size 101 bp) for transcripts of Hist2h2aa2 ; 5'-ACTCCGGAAAGGCCAAGACA-3' and 5'-GTTGTCCTAGATTTCAGGTG-3' for H2afz , product size 100 bp; 5'-CGTCCTGCCCAATATCCAG-3' and 5'-TCTGCACCCGTCTGTCG-3' (primer set 1, product size 90 bp) and 5'-AAGCAGGGCGGTAAGGTG-3' and 5'-TCCGCGTAGTTGCCCTTC-3' (primer set 2, product size 110 bp) for E130307C13 ; and 5'-TGTGTCCGTCGTGGATCTGA-3' and 5'-CCTGCTTCACCACCTTCTTGA-3' for GAPDH (glyceraldehyde-3-phosphate dehydrogenase), product size 76 bp. Quantification of GAPDH mRNA was used as a control for data normalization. PCR amplification was performed on an ABI PRISM 7700 Sequence Detection System (Applied Biosystems). The PCR conditions were an initial step of 30 s at 95°C, followed by 40 cycles of 5 s at 95°C and 30 s at 60°C. The SYBR premix Ex Taq (Takara) was used according to the manual. Expression was assessed by evaluating threshold cycle (C T ) values. The relative amount of expressed RNA was calculated using Livak and Schmittgen's method [ 14 ]. Authors' contributions HN designed this study, carried out the molecular biological studies, and the molecular evolutionary studies. TS and YT carried out synchronization of cells and quantitative RT-PCR. YH participated in the design of this study.

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539274

Calibration and assessment of channel-specific biases in microarray data with extended dynamical range

Background Non-linearities in observed log-ratios of gene expressions, also known as intensity dependent log-ratios, can often be accounted for by global biases in the two channels being compared. Any step in a microarray process may introduce such offsets and in this article we study the biases introduced by the microarray scanner and the image analysis software. Results By scanning the same spotted oligonucleotide microarray at different photomultiplier tube (PMT) gains, we have identified a channel-specific bias present in two-channel microarray data. For the scanners analyzed it was in the range of 15–25 (out of 65,535). The observed bias was very stable between subsequent scans of the same array although the PMT gain was greatly adjusted. This indicates that the bias does not originate from a step preceding the scanner detector parts. The bias varies slightly between arrays. When comparing estimates based on data from the same array, but from different scanners, we have found that different scanners introduce different amounts of bias. So do various image analysis methods. We propose a scanning protocol and a constrained affine model that allows us to identify and estimate the bias in each channel. Backward transformation removes the bias and brings the channels to the same scale. The result is that systematic effects such as intensity dependent log-ratios are removed, but also that signal densities become much more similar. The average scan, which has a larger dynamical range and greater signal-to-noise ratio than individual scans, can then be obtained. Conclusions The study shows that microarray scanners may introduce a significant bias in each channel. Such biases have to be calibrated for, otherwise systematic effects such as intensity dependent log-ratios will be observed. The proposed scanning protocol and calibration method is simple to use and is useful for evaluating scanner biases or for obtaining calibrated measurements with extended dynamical range and better precision. The cross-platform R package aroma, which implements all described methods, is available for free from .

Background The microarray technology provides a way of simultaneously measuring transcript abundances of 10 3 – 10 5 genes from one or more cell or tissue samples. A microarray, also known as a gene chip, has well defined regions that each consists of immobilized sequences of DNA, which each is unique to a specific gene. These regions are referred to as probes [ 1 ]. When fluorophore labeled cDNA, referred to as targets , obtained by reverse transcription of mRNA extracted from the samples of interest is let to hybridize to the probes for a few hours, each region on the microarray will specifically bind a certain amount of hybridized DNA unique to the corresponding gene. Depending on if a two-channel or single-channel microarray platform is used, either several and differentially labeled targets are hybridized to the same array, or different targets are each hybridized to separate arrays using identical labels. Next, the array is scanned at different wavelengths to excite the fluorescent molecules using a light source, for instance a laser. Shortly after the fluorophores have been excited they emit photons, which are registered and quantified in each position by the scanner, which results in a high-resolution digitized image for each channel. Using image analysis methods, the pixels that belong to the regions that contain the probes are identified and averaged, and an estimate of the transcript abundance for each gene is obtained. Since these estimates are obtained from a complex measurement process of several steps, it is likely that the observed signals contain not only measurement noise, but also systematic variations of different kinds [ 2 ]. In this report, we show the existence of a channel-specific bias introduced by the scanner and most likely its detector parts. Our results indicate that the image analysis may also contribute with a small bias. The effects channel-specific biases have on the downstream microarray analysis are many [ 2 , 3 ]. We suggest a scan protocol and a model that will allow us to estimate the biases and calibrate the observed signals accordingly. The result will be that the intensity dependent effects are removed, but also that the effective dynamical range of the scanner is increased several times. Model General model Consider a microarray experiment involving genes i = 1 ,..., I from RNA extracts c = 1 ,..., C . In single-channel microarrays each array measures the gene expression levels in one RNA extract, whereas in two-color microarrays each array measures two RNA extracts, one in each channel. We will refer to each set of signals from each RNA extract as channels . Let μ c , i be the true gene expression (transcription) level of gene i in channel c . Ideally, statistical analysis can then be done on these quantities. For instance, by comparing the relative abundances in two channels, that is r i = μ 1, i / μ 2, i for all genes i , it is possible to identify genes that are significantly differentially expressed ( r i ≠ 1). However, in reality we do not observe the true expression levels, but only the quantified spot intensities y c , i . The general relation between the observed and the true expression levels can be written as y c , i = f c ( μ c,i ) + ε c,i ,     (1) where f c (·) is an unknown channel-specific function, which we refer to as the measurement function , that includes all steps in the microarray process. Moreover, we assume independent intensity dependent error terms ε c , i such that E [ ε c , i ] = 0. Because we want to do inference based on μ c , i , it must be possible to find the inverse of f c (·), which (at least in theory) is possible if it is strictly increasing. To be able to find the form of f c (·), high quality calibration data from several stages along the microarray process is required. Here we will consider a simpler case. Split the overall measurement function into two parts. The first part x c , i = g c ( μ c , i ) models, in channel c , the amount of light from spot i that enters the photomultiplier tube (PMT) [ 4 ] as a function of the transcription level of clone i . The second part, which is studied in this report, is y c , i = h c ( x c , i ) and models the observed signal as a function of the amount of photons in channel c and spot i that enters the PMT. That is, it captures the characteristics of the scanner's light detector, but also of the image analysis methods. We want to emphasize that the light from one spot does not necessarily originate solely from the fluorescent molecules that are attached to the hybridized target DNA. Light from other sources such as cross-hybridized target, intrinsic fluorescence from spot buffer, and scatter light may also contribute with photons of similar wavelengths. Next we will show that h c (·) is almost perfectly affine. This measurement function also depends on the scanner settings, especially the scanner sensitivity, which is indicated below with the super index ( k ). In other words, where for each fix scanner setting k , and are channel-specific bias and scale parameters, respectively. Assume that x c , i is fix for all PMT voltages. Note that the above relationship is not necessarily linear. Here we refer to linear in the strict sense where a c = 0 so that the output is proportional to the input. Lack of linearity has important implications on downstream analysis. For instance, when spotted as well as in-situ synthesized microarrays are used it is common to do statistical analysis on the log-ratios M i = log 2 ( y R , i / y G , i ) and the log-intensities for all genes i [ 5 ], where we for convenience have denoted the two channels to be compared by R and G although such comparisons are not limited to within-array measurements. One of the rationales for this bijective transform is that under ideal conditions the main measure of interest, the fold change, is contained in one variable only. However, a channel specific bias introduced by f c (·) will introduce a so called intensity dependent bias in the observed log-ratios. Commonly observed intensity dependent effects in the log-ratios [ 6 ] can partly be explained by the fact that the logarithm is taken on affinely transformed signals [ 2 , 3 , 7 ]. Constrained model The model in equation (2) is not identifiable. We address this problem as follows. Consider the case where the same array has been scanned at K different PMT settings. Let be the vector of the K quantified signals for gene i and channel c . In the noise-free case it follows from (2) that lies on the line L ( a c , b c ) in K , which has direction and goes through the point . The 2 K parameters of a c and b c are not identifiable, since L has only 2 K - 2 degrees of freedom. In fact, any transformation b c ← k · b c and a c ← a c + l · b c , where k and l are scalars, will leave L intact. In this paper, we make a c and b c identifiable by choosing k and l so that = 1 and a c is the point on L closest to the (diagonal) line L ' = { e c (1,..., 1); e c ∈ }. The choice of a c can be motivated by looking at observed data. By inspection, we observe that the bias in Model (2) is not varying much when the PMT gain is changed. To demonstrate this, have been plotted for each of the six possible PMT pairs in Figure 1 . First, the close fit of the lines to data is evidence that the scanner is linear in its dynamical range. Second, all lines go through approximately the same point, lets call it ( e c , e c ), suggesting that there is a common PMT-independent bias e c . More precisely, we split the bias term into two parts, one dependent and one independent on the PMT gain according to and define ∈ K . For this split, data indicates that || d c || ≈ 0, where ||·|| is the norm in, say, L 2 (Euclidean distance). Let d = y - e (1,..., 1) where y ∈ L and e ∈ . The constraint that a c is the point of L closest to L ' can then be formulated as where the minimization is with respect to y and e . Equivalently, this means that d c is orthogonal to b c and (1,..., 1). The above can be interpreted geometrically as follows. By definition, a c is a point on the line L ( a c , b c ). Similarly, e c = e c (1,..., 1) is a point on the diagonal line that goes through (0,..., 0) and (1,..., 1) in K , i.e. L '. Minimizing d c according to (4) is the same as finding the shortest distance between the line L and the diagonal line, which is also the distance between the two points a c and e c . From this geometrical interpretation it is also clear that in order for the parameters to be uniquely identifiable the line L must not be parallel to the diagonal line, that is, must be different from for some k . A robust estimate of L was proposed in [ 2 ], using iteratively re-weighted principal component analysis (IWPCA). This estimate of L , together with the above parametrization of a c and b c , give us estimates and of all 2 K - 2 parameters of a c and b c , as well as an estimate of e c . Let us illustrate the parametrization and estimation procedure for K = 2. Since two (non-parallel) lines will always intersect, constraint (4) degenerates to the assumption that d c = 0 or, equivalently, that = e c In the noise-free case the line L is described by where and . By setting in (5) and applying the constraint , we get that a c = ( e c , e c ) and b c = (1, β c ) where e c = α c /(1 - β c ). To further illustrate the stability of the PMT independency, the parameters ( e c , β c ) have been estimated for each of the six PMT pairs independently based on data from array A scanned by the Axon scanner and quantified by GenePix. The various estimates for both channels are listed in Table 1 . The average estimate of the bias across all PMT pairs in the red channel was = 18.0 (with standard deviation 1.12). For the green channel the average bias estimate was = 20.3 (with standard deviation 0.80). The small standard deviations confirm that d c is indeed small. Results This analysis was done with eight arrays (A-H) that were scanned on two different scanners at four different PMT settings. Two different image analysis applications were used. See Methods for details. Parameter estimates For every combination of array, scanner and signal quantification method (image analysis or raw pixel intensities), we estimated the parameters a c (including e c and d c ), and b c in Model (2)-(4) for both channels (see Methods). To get a better understanding of the properties of the estimates, we used a non-parametric bootstrap approach to obtain not only bias corrected estimates, but also their standard deviations. Data was resampled over gene index in a way such that the same bootstrap data sets were used whenever pairwise comparison was done, e.g. when comparing bias estimates in red and green channels. For GenePix and Spot quantified signals a bootstrap sample of size 100 was used. For the estimates based on the raw pixel intensities a different approach was taken. Because the number of pixels for one scan is about 10 7 (per channel) and we had four scans, our computer system limited us to estimate the model based on a subset of 10 6 pixel intensities. This was done for 100 random subsets and the mean and standard deviation of the parameter estimates were calculated, much like the bootstrap method above. The mean and the standard deviation of and for all possible setups are listed in Tables 2 & 3 . The mean and standard deviation of over all arrays are shown in Table 4 . Comparison of arrays The bias estimates for all bootstrap replicates in Tables 2 & 3 have been depicted as box plots in Figure 2 . Considered that the signals are in [0, 65535], the bias estimates are very stable between different arrays. The biases span 9.8 units (0.15‰) in the red channel and 7.8 units (0.12‰) in the green channel. Comparison of scanners For the two scanners, we found that the estimated bias based on signals obtained by the Agilent scanner are consequently higher than the estimates from the Axon scanner. The box plots of their differences in the common bias e c (for each bootstrap sample) between the Agilent and the Axon scanner in Figure 3 confirm this divergence. See also Table 4 . This significant difference could be an effect of scan order, that is, all arrays were first scanned on the Agilent scanner and then on the Axon scanner. The arrays in hand were part of a much bigger project based solely on Agilent scanned data. To keep a consistent scan protocol and to minimize bleaching, we could not balance the experimental design by letting some arrays be scanned in the reverse order. Instead, to test for scan order trends we scanned one array first on Agilent (H-1), then on Axon (H-1) and then again on Agilent (H-2). No apparent trend was found. Comparison of image analysis methods Estimates of the common bias e c based on GenePix quantified signals are consistently greater than the corresponding ones based on Spot signals, cf. Tables 2 , 3 , 4 . The box plots in Figure 4 show differences in estimates of the common bias (for each bootstrap sample) between GenePix and Spot. The difference may be explained by the fact that the two applications use different spot segmentation algorithms [ 8 , 9 ]. Because the concentration of fluorophores is not homogeneous across a spot, the result is that the distribution of pixel intensities will vary with the segmentation method. This effect can be more profound for spots with strong donut effects. Robust estimates such as the median pixel value will to some extent protect against this variance, but not completely. It has been suggested [ 10 ] that the median of (pixel) ratios is a better estimate of the ratio of hybridized cDNA than the ratio of median (pixels). However, the former requires that the images are perfectly aligned with respect to shift, rotation, shear and so on. Also, it applies exclusively to two sample comparisons. Because of this, we do not believe that pixel-ratio signals are useful in practice. Pixel-based estimates To better understand the underlying reasons for the observed channel biases, the proposed affine model was also applied to pixel intensities (instead of spot signals). The estimated biases for the two channels for different arrays using IWPCA based on pixel values are shown in Tables 2 & 3 . Except for the green channel in the second scan round of Array H, the pixel-based estimates are consistently higher than the estimates based on GenePix and the Spot foreground signals. As noted above, pixel-based estimates are very sensitive to image distortions. This is especially a concern for the Agilent scanner since it reloads the arrays between subsequent scans. To investigate the effect of image distortion, we did a test where a person with experience in microarray analysis was asked to subjectively rank how badly aligned the four images in the red channel with different PMT gains from the Agilent scanner were for each of the (unlabeled) nine arrays. The person rated the images from Arrays A, B, D, and H-1 to be "extremely" misaligned. The images from Array E were considered to be "quite" misaligned, and the images from Array C to be "slightly" misaligned. For the rest of the arrays the images were considered to be aligned (less than a pixel off). This is perfectly in line with the discrepancies in Table 2 , which confirms our hypothesis. Another disadvantages with pixel-based methods is that they are extremely memory and time consuming. For instance, estimation with 10 6 pixels is approximately 50 times slower than with 55,488 signals. Comparison of channels As Figure 5 shows, the common bias e c is greater in the green channel than in the red channel, especially for GenePix quantified signals, when estimated based on data from the Axon scanner. For the Agilent scanner this trend is less clear although the Spot quantified signals seem to give higher bias in the green channel than in the red channel. Furthermore, the biases in the red and the green channels are stable between arrays, which give further evidence to our hypothesis that the bias originates from the scanner (and/or the image analysis methods). Deviation in bias estimates between PMT gains In Figure 6 the distribution of the "bias residuals" are depicted for different scans k and channels c , for each separate array, but also for all arrays together, and for both scanners and both image analysis methods. Most apparent is that the estimates based on signals from the Axon scanner and especially those quantified by the Spot software are greater than for the others, cf. Tables 2 & 3 . The reason for this difference is not clear to us. For some arrays the estimates from the red and the green channels are strongly correlated, but it is not clear to us when this occurs. Although not in general, for some combinations of scanner and image analysis method, there is a trend in the PMT order (or possibly scan order). Again, we do not know why. To summarize, we have by means of exploratory data analysis (not shown) tried to understand what sometimes looks like patterns in the :s, but we found no apparent relationships. However, systematic effects indicate that may be modeled further. Calibration When data was calibrated according to the backward transformation in (8)-(10) estimates (up to a scale factor) of all x c , i :s were obtained. Since we do not know the true values we can not verify the estimates directly. However, partly we can do it indirectly by looking for remaining systematic effects in the log-ratios, but also by comparing the empirical densities of the calibrated scans. For a detailed study on systematic effects introduced by affine transformations, see [ 2 ]. For instance, the amount of intensity-dependent curvature in the log-ratios is related to the bias and the relative scale factor via the product assuming || d c || = 0. To demonstrate this relationship, we have for different PMT pairs compared the within-channel log-ratios and log-intensities respectively, with the corresponding ones for the backward transformed data, which we denote by and . The log-ratios versus the log-intensities for the raw signals of all six PMT pairs are shown in the left scatter plot in Figure 7 . The corresponding plot for the backward transformed signals is shown to the very right. For each of the six data clouds, the curvature, but also the overall bias, in the log-ratios is removed. To further underline the effect that a channel-specific bias has, we have calculated the log-ratios for the bias-subtracted signals (no rescaling), which makes Model (2) linear . As seen in the middle scatter plot, the curvature introduced by the bias and the logarithm is removed. The overall bias in the log-ratios which remains is and is removed when the signals are rescaled. It is not correct to shift only the log-ratios towards zero, because then the log-intensities will be incorrect. The various M versus A plots become very similar and so do the four empirical density functions of the signals as seen in Figure 8 . The small bumps at high intensities are due to the saturated signals, cf. Figure 7 . Extended dynamical range For the Agilent scanner the effective scale parameters / were estimated to be in the order of approximately 1 : 3.5. For the Axon scanner they were in the order of approximately 1 : 40, cf. Table 1 . Thus, the calibration method extends the effective dynamical range, with preserving linearity, by a factor of 3.5 for signals from the Agilent scanner and a factor of 40 for signals from the Axon scanner. Discussion Sources of the bias Because bias introduced before the PMT would be amplified differently at different gains, we suspect that the observed bias is due to the scanner and most likely its detector parts such as the analogue-to-digital converter (ADC) after the PMT, but possibly also due to the image analysis method. The observed differences between the channels can be explained by the fact that there is one PMT and one ADC per channel, which may have slightly different properties. Although there are differences in bias between the two scanners, they are still of the same order, which we find remarkable. Another lab with a GenePix scanner reported biases also around 15–20 (personal communication). A possible reason for this is that the scanners consist of similar parts. Other estimates To rule out the obvious situation where all pixel intensities are biased we compared the above estimates with the minimum pixel intensities . For example, for Array A (scanned on Axon and analyzed with GenePix Pro), the minimum pixel intensities in the red channel were 9, 0, 8, and 9 for PMT 500, 600, 700 and 800 volts, respectively. In the green channel the minimum pixel intensity is 0 for all scans. It is not useful to use the minimum spot signals , , either. For example, for the above scan the average minimum signal across all scans in the red channel is 19.8 (median 19.5, std. dev. 0.96), but in the green channel it is 34.8 (median 28.0, std. dev. 19.6), cf. Table 3 . On background subtraction If the scanner is the main source for the observed bias, then the background estimates should be affected by this bias as well and subtracting the background from the foreground estimates will therefore not only correct for physical background noise from the array itself, but also for the scanner bias. The strong intensity dependent effects of the log-ratios that are due to the bias, are much less apparent if we apply background subtraction (not shown), giving more evidence to our hypothesis that the observed systematic effects originate from the scanner. Thus doing background correction might correct for the bias, but it will also introduce more noise at any given intensity. Also, for the data set in hand background subtraction results in 4050 (7.3%), 6237 (11%), 7015 (13%) and 7349 (13%) negative values (in either channel), respectively, whereas bias subtraction results in no negative values. If we assume that the noise is additive such that the background is added to the foreground signals, then for probes with few or no fluorescent molecules the true foreground signal should be close or identical to the true background signal. As both are estimates , approximately half of the foreground signals for non-signal spots are less or equal to the corresponding background signals. Thus, about half of such spots results in negative signals. However, the different numbers of negative signals for different PMT voltages suggest that this can not be the full explanation. One reason could be that the background estimates are likely to be biased [ 9 ]. An error model that incorporates different noise sources, but also different scan parameters, might give some answers to this problem. Some models in this context have already been suggested [ 3 , 7 , 11 ], as well as models based on empirical Bayesian methods [ 12 ]. Another way to put it is that the background estimate is local and based on individual spots/pixels whereas the bias estimate is global, that is, there is one estimate for the whole array (although local estimation of bias is possible). Therefore, the background subtracted intensity estimates are noisier, resulting in more negative estimates for low intensity spots. The problem of non-positive estimates, but also high variance close to zero, are limitations of the logarithmic transform and alternatives such as the generalized logarithmic transform etc. have been suggested [ 7 , 13 , 14 ]. Photo bleaching We estimated the red dye (Cy5™) to bleach about 2% and the green dye (Cy3™) about 1% in a typical microarray experiment (not shown). Because the amount of bleaching is relatively small, but also because it is a very complex phenomenon, we decided to not try to incorporate it in the above model. Some of the systematic variation seen in the bias estimates for the different PMT settings may be due to bleaching. Signal density normalization As the results show, the empirical distributions of signals match each other remarkably well after calibration. It is interesting to compare this method with the quantile normalization methods proposed by [ 15 - 17 ]. The latter is based on the "statistical" assumption that the signals in all channels (scans) should be equal whereas the former is based on a "physical" assumption that the signals should be linear in the dynamical range. For a further discussion on this see [ 2 ]. Incremental robust estimates It turned out to be infeasible to estimate the model parameters based on all pixel intensities , which limited us to use only on a 10% subset of data. As argued above, pixel-based estimates are not reliable and therefore not of interest. However, for spot-based estimates the same limitations may apply as larger data sets are made available. We wish to overcome such memory constraints. For this reason, we investigate the possibility to use (approximative) incremental re-weighted PCA methods [ 18 , 19 ]. Related work Another method that combines multiple scans is the masliner (Microarray Spot LINEar Regression) algorithm [ 20 ]. It works by combining one low-PMT scan and one high-PMT scan into a new virtual scan. If a signal in the high-PMT scan is within a specified linear range its value is used, otherwise the corresponding signal from the low-intensity range is used after being transformed affinely to fit the high-PMT scan. To combine three or more scans, the new virtual scan can be combined with another PMT scan and so on. The result is that the effective dynamical range is extended. However, there are several unnecessary drawbacks. First, although several observations of the same spot concentration exist, which all may be within the dynamical range of the scanner, only one observation is used. Statistically, the average (calibrated) scan would be a more precise estimate. Second, since the scans are combined pairwise the estimate of the affine relationship between the scans is less robust. Third, although a sensitivity discussion is carried out in the supplementary materials, masliner fits the affine models in a non-robust fashion (in L 2 ). Also, classical linear regression is used, which assumes no error in the explanatory variable. Since masliner makes the signals from different PMT settings proportional to each other it will indeed remove for instance curvature in within-channel M versus A scatter plots. However, masliner does not model the possibility of a PMT-independent bias and will therefore not correct for it. We believe this is the reason why the authors observe a "curvilinear effect" [[ 20 ], supplementary material]. For these reasons, we believe that the robust multiscan calibration method presented in this paper is superior to the masliner algorithm and should be used instead. Conclusions By scanning the same microarray at various PMT settings we have shown that there exists a bias in the measurement of the concentration of fluorescent molecules in the spots on the microarray. Our analysis indicates that this bias is mainly due to the scanner, but also due to the image analysis methods. By using a constrained affine model for the relationship between the obtained fluorescent intensities and fluorophore concentrations in the spots, we have been able to estimate the aforementioned bias. With estimates of the bias and scale parameters in each channel back transformation gave estimates of the amount (up to a scale factor) of photons from each spot that enters the PMT. Although not all photons originate solely from fluorophores in the target DNA, this is still a far better estimate of the amount of hybridized target DNA in each spot than the corresponding signal quantified by the scanner and the image analysis. Before calibration, our data show a strong intensity dependent effect in the log-ratios, whereas after calibration there is no apparent intensity dependent trend. Furthermore, the distributions of signals from subsequent PMT scans are almost identical after calibration. In addition, the signal-to-noise ratio is increased with multiple scans. Finally, scanning at both low and high PMT settings extends the dynamical range of data, which gives higher resolution at low intensities without having to pay the price of saturated signals. The proposed method can be applied to other microarray technologies such as single-channel oligonucleotide arrays or nylon arrays, and possibly to other gene expression technologies such as quantitative real-time polymerase chain reaction (QRT-PCR). To conclude, we suggest that hybridized microarrays are scanned at two (preferably more) PMT gain levels to identify channel dependent bias terms. Knowing the exact PMT settings is not important, but the larger the differences are, the more precise the estimates will be. We recommend that the scans are done in decreasing PMT-gain order (although we did not do so here). Given estimates, data can then be calibrated easily. For practical reasons it might, however, be sufficient to estimate bias terms for a specific scanner once and then use estimates for calibration of subsequent microarrays. The small inter-array variation observed for channel specific bias in our data suggests that this would be possible. On the other hand, without multiple scans, afore mentioned increase in signal-to-noise and dynamical range will be lost. Also, not investigated within the scope of this study, bias terms for a specific scanner might change over time. For these reasons, we suggest that microarrays are scanned multiple times. For two-channel microarrays, after calibrating each channel separately, a similar strategy can be applied once more to bring differently labeled channels to the same scale as suggested in [ 2 ]. This would rely on the assumption that the amounts of hybridized DNA in all channels are approximately equal for the majority of the spots, which in turn is based on the commonly used assumption that most genes are non-differentially expressed. This also applies to normalization between arrays. All necessary methods are made available in a free R package named aroma [ 21 ]. A typical usage is calibrateMultiscan(rg) where rg is the object containing the red and green signals. In addition, we are currently implementing the methods as a plug-in module for the BASE system [ 22 ]. Methods Arrays and hybridization The analysis was based on eight different hybridizations of spotted oligonucleotide microarrays (A-H). Arrays A and B were hybridized in October 2003. Arrays C-G were hybridized the following day and Array H was hybridized seven weeks later. All arrays contain the same human oligonucleotide set (QIA GEN) and all have an identical layout of 12-by-4 print-tip groups each containing 34-by-34 (1156) spots. In total there are 55488 spots on each array. The average (GenePix) spot area is 45–50 pixels and the average center-to-center distance between the spots is approximately 12–13 pixels (120–130 μm ). Arrays were produced by the SWEGENE DNA Microarray Resource Centre, Department of Oncology at Lund University using a MicroGrid II 600R arrayer fitted with MicroSpot 10 K pins (BioRobotics). All arrays except Array H were spotted in the same print batch on UltraGAPS™ coated slides (Corning Incorporated) during August 2003. Array H was spotted in October the same year. Printing was performed in a temperature (18–20°C) and humidity (44–49% RH) controlled area. After printing was completed, arrays were left in a desiccator to dry for 48 hours, rehydrated for 1 second over steaming water, snap dried on a hot plate (98°C), UV-cross-linked (800 mJ/cm 2 ) and subsequently hybridized with various test and reference RNA samples. Samples were labeled, purified and hybridized using Pronto!™ Plus System 6 (Corning Incorporated) according to manufacturer's instructions. Scanning Each array was scanned at four different PMT settings on two different types of scanners. First the arrays were scanned on an Agilent G2505A DNA microarray scanner (Agilent Technologies) at PMT gains 100%, 30%, 50%, and 80% (in that order). The so called dark offset intentionally added to all signals by the Agilent scanner [[ 23 ], p. 18] has been uninstalled. Arrays were then re-scanned on an Axon GenePix 4000 A scanner (Axon Instruments) at PMT gains 600, 700, 800, and 500 volts (in that order), except for Array A, which was scanned at 700, 800, 500 and 600 volts, and Array H, which was scanned at 600, 400, 500 and 700 volts. Thus, the images obtained by the Axon scanner were bleached more than the preceding ones obtained by the Agilent scanner. For both scanners the power of the 532 nm and the 635 nm lasers was set to 100% and the scan resolution to 10 μm /pixel. Moreover, a one-pass (both channels scanned simultaneously) and one-sample-per-pixel ("lines to average" equals one) procedure was used. The Agilent scanner has a special loading mechanism for microarrays, which allows automatic scanning of subsequent arrays without human intervention. However, due to limitations in the software or the scanner, each batch of arrays can only be scanned at a single PMT gain. To scan at more PMT gains with the Agilent scanner, it was therefore necessary to eject and reload the arrays between different settings, which means that the alignment between the scanned images may not be perfect. Contrary, for the Axon scanner the arrays were put in the scanner one by one, then scanned at all PMT settings without being moved. Image analysis – spot segmentation and registration To quantify the foreground and the background signals, the scanned images (65536 gray scales and approximately 2000-by-5600 pixels) were analyzed using both the Axon GenePix Pro v4.1.1 software (Axon Instruments) and the Spot v2 software [ 8 , 24 ]. We first analyzed each image with GenePix. For each of them, the grid and spot positions were manually set and then the alignment was optimized by GenePix. These positions were then re-entered and re-optimized by Spot with visual inspection to verify the correctness. Moreover, for each individual scan the image analysis software was let to find the optimal spot segmentation. Thus, what is defined as a foreground pixel may vary with PMT setting although the images are from the same array. We decided on this schema for various reasons. The first reason was that the Agilent arrays are loaded and unloaded between subsequent scans and therefore require a separate spot segmentation. To be able to compare the results from the Axon and the Agilent scanner we choose the same procedure for the images scanned on the Axon scanner, even though, the optimized segmentation for the strongest image could have been reused. We further believe that this allows us compare Spot and GenePix more fairly. For both Spot and GenePix the median spot pixel intensity was used as foreground signal. Background estimates were not considered in this analysis. No spot signals were discarded. Calibration Given estimates of and data can be calibrated using backward transformation. Let be the backward transformed observed signal and the rescaled error terms, respectively. The affine Model (2) can then be rewritten as Moreover, let be the average backward transformed signal for gene i in channel c . Now, if , then when all and are known. Thus, if (8) is applied with estimates of and that are consistent as I → ∞, and the error terms have zero mean, the mean of the backward transformed signals will converge to x c , i as I grows. Even though is not observable, we can estimate it consistently by increasing the number of scans K . Inspection of the residuals of calibrated signals (not shown) indicates that the variance of the calibrated noise is independent of PMT setting, that is . Assuming independent noise terms, the variance of the sample mean decrease with K as In summary, we obtain consistent estimates (up to a multiplicative constant) of all x c , i with increasing I and K . Finally, signals that are saturated by the scanner have to be excluded before calculating the average. If the quantified signal for a spot happens to be saturated in all scans, then that spot is marked as saturated, which still may be informative when compared to other non-saturated signals. Data analysis All further analysis was carried out using R [ 25 , 26 ] and the aroma package (f.k.a. com.braju.sma) [ 21 ]. All methods used can be found in the latter. Authors' contributions GJ and JVC carried out the practical microarray laboratory work and the scanning of hybridized arrays. Image analysis using GenePix software was carried out by JVC whereas HB carried out image analysis using Spot software. HB performed all the statistical analysis and conceived the constrained affine model used to identify and estimate channel-specific bias in microarray data. All authors participated in the design of the study and approved the final manuscript.

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547972

Nuclear Hormone Receptor NHR-49 Controls Fat Consumption and Fatty Acid Composition in C. elegans

Mammalian nuclear hormone receptors (NHRs), such as liver X receptor, farnesoid X receptor, and peroxisome proliferator-activated receptors (PPARs), precisely control energy metabolism. Consequently, these receptors are important targets for the treatment of metabolic diseases, including diabetes and obesity. A thorough understanding of NHR fat regulatory networks has been limited, however, by a lack of genetically tractable experimental systems. Here we show that deletion of the Caenorhabditis elegans NHR gene nhr-49 yielded worms with elevated fat content and shortened life span. Employing a quantitative RT-PCR screen, we found that nhr-49 influenced the expression of 13 genes involved in energy metabolism. Indeed, nhr-49 served as a key regulator of fat usage, modulating pathways that control the consumption of fat and maintain a normal balance of fatty acid saturation. We found that the two phenotypes of the nhr-49 knockout were linked to distinct pathways and were separable: The high-fat phenotype was due to reduced expression of enzymes in fatty acid β-oxidation, and the shortened adult life span resulted from impaired expression of a stearoyl-CoA desaturase. Despite its sequence relationship with the mammalian hepatocyte nuclear factor 4 receptor, the biological activities of nhr-49 were most similar to those of the mammalian PPARs, implying an evolutionarily conserved role for NHRs in modulating fat consumption and composition. Our findings in C. elegans provide novel insights into how NHR regulatory networks are coordinated to govern fat metabolism.

Introduction Due to their ability to interact with fatty acids and other lipids, nuclear hormone receptors (NHRs), including peroxisome proliferator-activated receptors (PPARs), liver X receptor, and farnesoid X receptor, are important regulators of mammalian fat metabolism; accordingly, these small-molecule-gated transcription factors have been favored targets for therapies designed to combat diabetes, obesity, and atherosclerosis [ 1 , 2 , 3 ]. Although the molecular mechanisms employed by NHRs have been intensively probed, their pleiotropic effects on overall animal physiology are only partially understood. Thus, developing a broader range of experimental systems would be useful for characterizing the fat regulatory networks integrated by NHRs and for revealing the breadth of their physiological influence. The study of invertebrates, such as Caenorhabditis elegans , has facilitated the elucidation and interpretation of biological networks, particularly in the context of the whole animal. However, despite the fact that C. elegans contains 284 NHR genes, compared to only 48 in mammals, there is a notable absence of worm NHRs orthologous to mammalian receptors involved in fat metabolism [ 4 , 5 ]. In fact, it has been suggested that fat-regulating NHRs, along with several other NHR types, were lost from the C. elegans and Drosophila lineages as these organisms simplified their body plans [ 6 ]. Conceivably, then, the biological activities associated with these NHRs may also have vanished. Therefore, it is still not clear if worm receptors mediate control over fat metabolism comparable to that of mammalian NHRs. Whether or not C. elegans employs NHRs to regulate fat metabolism, the evolution of the C. elegans NHR family is intrinsically interesting. Only 15 of the 284 worm NHRs are members of the broadly conserved subfamilies found in mammals and other metazoans [ 4 , 5 ]. The biological activities of most of these “conserved” NHRs have been broadly defined, revealing roles in development, molting, dauer formation, and sex determination [ 7 , 8 ]. The remaining 269 “divergent” NHRs have thus far been found only in nematodes and are predicted to have originated from repeated duplication of an ancestral gene that also gave rise to the hepatocyte nuclear factor 4 (HNF4) family of receptors [ 6 ]. Although mammalian HNF4 receptors have been implicated in liver development and glucose homeostasis [ 9 ], virtually nothing is known about the functions of these 269 C. elegans “nematode-specific” HNF4-like receptors. It will be interesting to determine if these divergent NHRs have adopted novel regulatory functions or whether they carry out physiological tasks similar to those of other metazoan NHRs. Elucidating the physiological responsibilities of even one of the worm HNF4-like receptors will likely advance our understanding of NHR-regulated gene networks and provide insight into the evolution and diversification of the NHR family in nematodes. To this end, we have been systematically investigating the function of HNF4-like receptors in C. elegans. In this study, we present a physiological characterization of nhr-49 (K10C3.6), one of the C. elegans receptor genes most closely related to the mammalian HNF4. Our findings reveal a surprising role for this HNF4-like receptor in the regulation of fat storage and metabolism. Results nhr-49 Is Necessary for Normal Life Span In an RNA interference (RNAi) screen designed to identify the role of C. elegans HNF4-like receptors in worm development and longevity, we found that interference of nhr-49 resulted in dramatically reduced life span ( Figure 1 A). For further characterization, we obtained a C. elegans strain, nhr-49(nr2041), which harbors a deletion in the nhr-49 gene encompassing part of the DNA binding domain and more than half of the ligand binding domain (LBD); this deletion likely results in complete loss of function [ 10 ]. At 23 °C, nhr-49(nr2041) worms lived only 6–8 d as adults, significantly shorter than the 15 to 18-d life span of N2 wild-type (WT) animals ( Figure 1 A). Although nhr-49 deletion did not noticeably affect development or fertility, nhr-49(nr2041) worms experienced rapid decline in function beginning around day 3 of adulthood, when vacuoles appeared in the intestine and gonad ( Figure 1 B). By days 4 and 5, nhr-49(nr2041) animals were significantly smaller than WT, vacuoles were ubiquitous, and there was widespread gonadal necrosis. By days 5–7, the gonad had completely deteriorated, and the worms died shortly thereafter. Thus, nhr-49 function is not required for development or fertility, but is clearly essential for normal longevity. Even though the increased vacuole formation was consistent with reported aging characteristics [ 11 ], we have not determined whether the shortened life span of nhr-49(nr2041) reflects accelerated aging or an unrelated pathology. Figure 1 nhr-49(nr2041) Animals Have Reduced Life Span and Higher Fat Content (A) Adult life span of WT (black squares, solid line), nhr-49(nr2041) (black circles, dotted line), and nhr-49 RNAi animals (black diamonds, dashed line). (B) Nomarksi images of nhr-49(nr2041) at days 3, 5, and 7 of adulthood. The arrow in the day 3 image points to a gonadal vacuole that is typical of day 3 worms; the arrow in the day 5 image shows the continued deterioration of oocytes in the gonad, and the arrow in the day 7 image points to the clearing that results from complete gonadal necrosis and collapse. (C) Nile Red intestinal fat staining of WT and nhr-49(nr2041). Each image displays two representative worms from a population of L4 animals. nhr-49(nr2041) Animals Display Abnormally High Fat Content nhr-49 was recently identified in a C. elegans genomewide RNAi screen as one of 112 genes that, when knocked down by RNAi, resulted in abnormally high Nile Red fat staining [ 12 ]. To determine whether deletion of nhr-49 also yielded a high-fat phenotype, we used a similar Nile Red assay to visualize fat content in nhr-49(nr2041). Indeed, we found that nhr-49(nr2041) animals stained more brightly with Nile Red than did WT worms ( Figure 1 C). The difference in fat content between WT and nhr-49(nr2041) animals was most pronounced in the L3 and L4 stages of larval development; by day 2 of adulthood there was only a slight change in Nile Red staining, suggesting that the effects of nhr-49 on visible fat content may vary during development (data not shown). nhr-49 Regulates Genes Involved in Energy Metabolism The high-fat phenotype of the nhr-49(nr2041) mutant led us to suspect that nhr-49 might regulate genes involved in energy metabolism. To test this hypothesis, we identified from a survey of the C. elegans genome 65 genes predicted to participate in fatty acid synthesis, β-oxidation, desaturation, elongation, and binding/transport, in addition to 16 genes expected to function in glycolysis, gluconeogenesis, and glucose transport, and eight genes involved in the glyoxylate pathway ( Figure 2 ). We then employed quantitative RT-PCR (QRT-PCR) to measure the expression of all 89 of these genes in WT and nhr-49(nr2041) mutant worms. For the purpose of our survey, gene expression was measured in all four larval stages (for a complete dataset, see Table S1 ). Figure 2 nhr-49 Deletion Affects the Expression of 13 Energy Metabolism Genes Putative C. elegans fatty acid, glucose, and glyoxylate metabolism pathways are shown here; each box represents a gene predicted by sequence homology to code for the enzyme indicated in the figure. The fatty acid desaturation elongation pathway is adapted from previously published studies [ 14 , 17 ]. Mitochondrial localization of β-oxidation enzymes was predicted by TargetP and PSORT (see Materials and Methods ); peroxisomal β-oxidation enzymes all contain a carboxy-terminal peroxisomal localization signal. QRT-PCR was used to measure the expression of these 89 genes in WT and nhr-49(nr2041). Genes expressed at lower levels in nhr-49(nr2041) are shown in red (>32-fold lower); orange (8- to 32-fold lower); or yellow (2- to 8-fold lower); and genes expressed at higher levels are shown in light green (2- to 8-fold higher) or dark green (>8-fold higher). Online QRT-PCR data for this analysis are available in Table S1 . Our screen revealed that deletion of nhr-49 significantly altered the expression of 13 genes, including six genes predicted to be involved in fatty acid β-oxidation, three genes involved in fatty acid desaturation, two genes involved in fatty acid binding/transport, and two genes involved in the glyoxylate pathway ( Figure 2 ). Similar changes in gene expression were observed when nhr-49 was knocked down in WT animals using RNAi (data not shown). Overall, nhr-49 deletion displayed the most dramatic effects on two metabolic pathways, mitochondrial β-oxidation and fatty acid desaturation, as the expression of multiple genes in each of these pathways was significantly compromised by loss of nhr-49 function ( Figure 2 ). In contrast, nhr-49 deletion had smaller and mixed consequences for genes that participate in peroxisomal β-oxidation and lipid binding/transport. nhr-49 knockout also marginally reduced expression of two enzymes involved in the glyoxylate pathway, a pathway that facilitates the conversion of fatty acid β-oxidation products to glucose ( Figure 2 ). nhr-49 deletion did not, however, significantly affect the expression of any genes predicted to be involved in glucose metabolism. Thus, it is clear that nhr-49 is extensively involved in the control of fatty acid metabolism, with a pronounced role in the promotion of mitochondrial β-oxidation and fatty acid desaturation. nhr-49(nr2041) Animals are High in Fat Due to Reduced Expression of β-Oxidation Genes Three genes predicted to participate in mitochondrial β-oxidation, ech-1 (C29F3.1), F09F3.9, and an acyl-CoA synthetase gene (acs-2) (F28F8.2), were expressed at significantly lower levels in nhr-49(nr2041) animals throughout development ( Figure 3 A). acs-2 is predicted to encode a mitochondrial acyl-CoA synthetase, whereas F09F3.9 likely codes for a carnitine palmitoyl transferase, and ech-1 appears to encode a mitochondrial β-oxidation trifunctional enzyme. Because mitochondrial β-oxidation facilitates the degradation of stored fats for the production of energy, we suspected that nhr-49(nr2041) worms might be high in fat due to the reduced expression of these key β-oxidation enzymes. To test this hypothesis, we used RNAi to reduce separately the expression of acs-2, F09F3.9, and ech-1 in WT animals. Indeed, we found that RNAi of either acs-2 or ech-1 resulted in worms with elevated Nile Red fat staining ( Figure 3 B). acs-2 was previously identified for a similar effect on fat storage [ 12 ]. We conclude that nhr-49 promotes the expression of three β-oxidation genes, two of which, in WT worms, reduce overall fat storage. Thus, nhr-49(nr2041) mutant worms are likely to be high in fat due to the impaired expression of these genes. Figure 3 Regulation of β-Oxidation Gene Expression by nhr-49 (A) QRT-PCR measurement of acs-2, F09F9.3, and ech-1 expression in WT (gray bars) and nhr-49(nr2041) animals (blue bars). Expression was measured in all four stages of larval development. Error bars represent standard error of measurement. (B) RNAi of nhr-49, acs-2, or ech-1 resulted in increased Nile Red fat staining. Each image shows 3 or 4 representative worms from a population of L4 animals grown on plates containing RNAi bacteria and Nile Red fat-staining dye. (C) acs-2::gfp is expressed in many tissues including hypodermis (hyp), intestine (int), body wall muscle (bwm), neurons (neu), and pharynx (pha). ACS-2::GFP localizes to subcellular structures in a pattern similar to what has been reported for mitochondrial proteins [ 13 ]. (D) Expression of acs-2::gfp was lower in nhr-49(nr2041) mutant animals. (E) Expression of P nhr-49 ::gfp promoter fusion in WT animals revealed that nhr-49 is expressed in multiple tissues, including hypodermis (hyp), body wall muscle (bwm), pharynx (pha), and intestine (int). The animals shown here are genetically mosaic, harboring the P nhr-49 ::gfp construct in only a fraction of total cells. (F) Ectopic expression of acs-2::gfp in nhr-49(nr2041) was sufficient to reduce Nile Red staining to WT levels. ACS-2 Is Expressed in Multiple Tissues and Localizes to Mitochondria Out of five predicted mitochondrial acs genes in C. elegans, nhr-49 affected only the expression of acs-2, suggesting that nhr-49 may only influence a subset of mitochondrial β-oxidation pathways in worms. To determine if acs-2 was expressed in a specific set of tissues, we fused the full-length acs-2 gene and promoter to gfp (acs-2::gfp); injection of this construct into WT worms revealed that the ACS-2::green fluorescent protein (GFP) was widely expressed in many cell types, including intestine, hypodermis, pharynx, body wall muscle, and several neurons ( Figure 3 C). Moreover, ACS-2::GFP expression was reduced in all of these tissues in nhr-49(nr2041) worms, indicating that the effects of nhr-49 on acs-2 expression were widespread ( Figure 3 D). Notably, the expression pattern of acs-2 overlapped extensively with that of an nhr-49 promoter/GFP fusion, consistent with the idea that nhr-49 could control acs-2 through direct transcriptional activation ( Figure 3 E). As predicted, ACS-2::GFP localized to subcellular structures in patterns similar to those reported for other mitochondrial proteins [ 13 ] ( Figure 3 C). Overexpression of ACS-2::GFP Is Sufficient to Suppress the High-Fat Phenotype of nhr-49(nr2041) Strikingly, overexpression of the ACS-2::GFP fusion was able to suppress the high-fat phenotype of nhr-49(nr2041) animals ( Figure 3 F). These data suggest that acs-2 expression is reduced in nhr-49(nr2041) such that it becomes a rate-limiting factor in the consumption of fat; thus, high fat levels can be overcome simply by increasing acs-2 expression. Overexpression of acs-2 in WT animals did not affect fat content, however, indicating that WT levels of acs-2 expression are not rate limiting. These data further support the conclusion that reduced expression of acs-2 is a significant contributor to the high-fat phenotype of the nhr-49(nr2041) mutant. nhr-49 Modulates Fatty Acid Composition by Promoting Expression of Δ9-Desaturases In addition to stimulating genes in the mitochondrial β-oxidation pathway, nhr-49 also promoted the expression of three C. elegans fatty acid desaturases (see Figure 2 ). fat-5 (W06D12.3) and fat-7 (F10D2.9) expression was dramatically lowered in nhr-49(nr2041) worms (>30-fold) in all four larval stages, whereas fat-6 (VZK8221.1) expression was marginally reduced (approximately 2-fold) only in L3 and L4 animals ( Figure 4 A). Figure 4 Deletion of nhr-49 Hinders Fatty Acid Desaturation (A) QRT-PCR measurement of fat-5, fat-6, and fat-7 expression in WT (gray bars) and in nhr-49(nr2041) mutant worms (blue bars). Expression was measured in all four stages of larval development. Error bars represent standard error of measurement. (B) Relative abundance of individual fatty acid species expressed as percentage of total measured fatty acid. Fatty acids included in total fatty acid measurement but not shown in the figure include C14:0, C15:0, and C17:Δ. Fatty acids were isolated and quantified by GC/MS from WT (dark gray bars), nhr-49(nr2041) (blue bars), fat-7 RNAi animals (red bars), and nhr-49 RNAi animals (light gray bars). Error bars represent standard error. The fatty acid desaturation/elongation pathway, along with enzymes involved in desaturation and elongation, is shown in the inset; this pathway was adapted from previous studies [ 14 , 17 ]. Studies in yeast have shown that the C. elegans fat-5, fat-6, and fat-7 genes encode Δ9-desaturases, which preferentially convert saturated C16:0 and C18:0 fatty acids to monounsaturated C16:1 and C18:1 fatty acids [ 14 ]. fat-5 is a palmitoyl-CoA desaturase, specifically acting on palmitic acid (C16:0), and fat-6 and fat-7 are stearoyl-CoA desaturases (SCDs), preferentially functioning to desaturate stearic acid (C18:0). Mammalian SCDs have been shown to be important for maintaining an appropriate level of fatty acid desaturation, vital for modulating membrane fluidity and for controlling lipid metabolism [ 15 , 16 ]. Furthermore, in C. elegans, SCDs are also involved in catalyzing the first step in the synthesis of polyunsaturated fatty acids (PUFAs) [ 17 ] (see Figure 4 B inset). Because the expression of these three C. elegans Δ9-desaturases was significantly impaired by nhr-49 deletion, we used gas chromatography/mass spectrometry (GC/MS) to determine whether overall fatty acid desaturation and PUFA synthesis were altered in nhr-49(nr2041) animals. The most significant consequence of nhr-49 deletion on fatty acid composition was a marked increase in the abundance of stearic acid (C18:0) and a corresponding decrease in the level of oleic acid (C18:1n9) ( Figure 4 B). This result is consistent with a reduction in SCD activity. In mammals, a primary role of SCD is to control the ratio of fully saturated stearic acid to monounsaturated oleic acid (C18:0/C18:1n9), and this ratio has been employed as an indicator of the activity of the mammalian SCD1 [ 15 , 16 ]. In C. elegans we found that the ratio of stearic acid to oleic acid (C18:0/C18:1n9) was increased from 1.9 in WT animals to 4.3 in nhr-49(nr2041) ( Table 1 ). A similar but less pronounced alteration in the ratio of stearic acid to oleic acid was observed when nhr-49 was knocked down in WT animals using RNAi ( Figure 4 B and Table 1 ). This smaller influence on fatty acid desaturation likely resulted from the fact that nhr-49 RNAi did not reduce Δ9-desaturase expression as dramatically as nhr-49 knockout (data not shown). Table 1 Life Span, Fat Content, and Relative C18:0 Fatty Acid Abundance Fat content was determined by Nile Red staining. Life span indicated is the day when half of the worms in a given population expired. Fatty acid abundance is indicated by percent of total fatty acid measured by GC/MS C. elegans SCDs are also important for the synthesis of PUFAs; however, we did not observe any measurable changes in PUFA abundance in nhr-49(nr2041) animals ( Figure 4 B). Therefore, despite the dramatic effect of nhr-49 on SCD activity, nhr-49 does not appear to play an appreciable role in overall PUFA synthesis. To determine which of the Δ9-desaturases accounted for the influence of nhr-49 deletion on fatty acid composition, we used RNAi to individually knock down expression of fat-5 and fat-7 (because fat-6 expression is only reduced by approximately 2-fold in nhr-49[nr2041], we did not examine fat-6 RNAi animals). Although we did not observe a significant consequence of fat-5 RNAi on fatty acid desaturation, fat-7 RNAi altered fatty acid composition in a manner very similar to that of nhr-49 deletion ( Figure 4 B and Table 1 ). fat-7 RNAi animals displayed a significant increase in the abundance of C18:0 fatty acid, as well as a decrease in the levels of C18:1n9 and C18:2n6 fatty acids. The influence of fat-7 RNAi on fatty acid composition was stronger than that of nhr-49 deletion, increasing the ratio of stearic to oleic acid (C18:0/C18:1n9) to 8.0. fat-7 RNAi animals also exhibited a slight lowering of PUFA abundance. The stronger effect of fat-7 RNAi on fatty acid composition suggests that fat-7 expression was reduced to levels even lower than those observed in nhr-49(nr2041). Because fat-7 shares significant homology (approximately 85% nucleotide identity) with fat-6, it was possible that fat-7 RNAi also partially interfered with fat-6 expression; however, we found by QRT-PCR that the overall levels of fat-6 mRNA were not noticeably reduced by fat-7 RNAi. (data not shown). Therefore, we conclude that by strongly promoting SCD expression, nhr-49 influences fatty acid composition in C. elegans. Although it appears that the primary effect of nhr-49 deletion is a modulation of stearic and oleic acid levels, not PUFA abundance, we cannot rule out the possibility that nhr-49 influences PUFA synthesis in a more localized manner, such that the changes in PUFA composition are not detectable by our whole-worm analysis. Interference of fat-7 Expression Reproduces Shortened Life-Span Phenotype Using RNAi to knock down the nhr-49 -dependent genes identified in this study, we found that interference of only fat-7 resulted in a shortened life-span phenotype similar to that of nhr-49(nr2041) (see Table 1 ). fat-7 RNAi animals displayed many of the same characteristics of the nhr-49(nr2041) mutant, including widespread vacuole formation and germ line necrosis ( Figure 5 ). Figure 5 fat-7 Is Necessary for Normal Life Span and Inhibits β-Oxidation (A) Nomarski images of WT worms subjected to fat-7 RNAi at days 1 and 3 of adulthood. The arrow in the day 1 image points to vacuole formation in the intestine, and the arrow in the day 3 image points to clearing that results from collapse of the gonad. These characteristics are nearly identical to those observed for nhr-49(nr2041) worms (see Figure 1 B). (B) QRT-PCR measurement of acs-2 and ech-1 expression in WT and nhr-49(nr2041) L4 animals grown on control RNAi bacteria (dark gray bars) or on fat-7 RNAi bacteria (blue bars). Error bars represent standard error of measurement. (C) RNAi knockdown of fat-7 expression in WT animals reduced Nile Red fat staining (D) RNAi of fat-7 in nhr-49(nr2041) also decreased fat staining. Interestingly, the effect of fat-7 RNAi on life span was even more potent than nhr-49 deletion, reducing adult life span to 3–5 d, as opposed to the 5- to 7-d life span of nhr-49(nr2041) (see Table 1 ). This is consistent with the finding that SCD activity is more dramatically compromised in fat-7 RNAi animals than it is in the nhr-49(nr2041) mutant. In fact, we observed a striking correlation between fat-7 activity, as determined by the ratio of stearic to oleic acid in our various mutants, and life span (see Table 1 ). WT animals (stearic/oleic = 1.9) lived approximately 16–18 d, nhr-49 RNAi animals (stearic/oleic = 2.3) lived approximately 10–12 d, nhr-49(nr2041) animals (stearic/oleic = 4.3) lived approximately 6–8 d, and fat-7 RNAi animals (stearic/oleic = 8.0) lived approximately 3–5 d. Because fat-7 expression is significantly compromised by nhr-49 deletion, and because lowered fat-7 expression can lead to shortened life span, we suggest that the reduced life-span phenotype of nhr-49(nr2041) likely reflects, at least in part, diminished fat-7 expression. Stimulation of fat-7 by nhr-49 Feeds Back to Inhibit β-Oxidation By promoting β-oxidation gene expression, nhr-49 stimulates fat consumption, and by enhancing fat-7 expression, nhr-49 modulates fat desaturation and ensures normal longevity. We next set out to determine whether nhr-49 regulates these two pathways independently. Although RNAi of acs-2 or ech-1 was sufficient to cause a high-fat phenotype, acs-2 or ech-1 interference did not significantly impact life span, fatty acid composition, or desaturase gene expression, demonstrating that the effects of nhr-49 deletion on fat-7 expression and life span were not a downstream consequence of compromised β-oxidation or increased fat content (see Table 1 ). In contrast, RNAi of fat-7 significantly impacted fat storage and β-oxidation. The effect was paradoxical, however, as fat-7 interference produced the opposite result of nhr-49 deletion, causing reduced fat content and increased expression of genes in β-oxidation, including acs-2 and ech-1 ( Figure 5 ). As the influence of fat-7 on the expression of β-oxidation genes is opposite that of nhr-49, it is clear that the stimulation of β-oxidation by nhr-49 does not result from promotion of fat-7 expression. In fact, by enhancing fat-7 expression, nhr-49 indirectly causes inhibition of the very same β-oxidation genes that it is independently stimulating ( Figure 6 ). Figure 6 Model for nhr-49 Regulation of Fat Storage and Composition By stimulating expression of genes predicted to be involved in fatty acid β-oxidation, nhr-49 promotes fat consumption; likely by facilitating the flow of fatty acids (FA) into the mitochondrial matrix. Through an independent pathway, nhr-49 modulates fatty acid desaturation by enhancing the expression of the fat-7 SCD. Stimulation of fat-7 is necessary for normal adult life span. Finally, fat-7 also feeds back to partially inhibit expression of β-oxidation genes. Because fat-7 targets some of the same β-oxidation genes as nhr-49, we wondered if the effects of fat-7 on fat storage might be dependent on nhr-49; for example, perhaps fat-7 represses ech-1 and acs-2 expression by blocking the nhr-49 mediated induction of these genes. However, we found that both ech-1 and acs-2 were induced when fat-7 was knocked down even further in the nhr-49(nr2041) mutant using RNAi, indicating that fat-7 hinders the expression of ech-1 and acs-2 through a mechanism that is independent of nhr-49 (see Figure 5 B). Furthermore, RNAi of fat-7 reduced fat content in nhr-49(nr2041) worms, demonstrating that the stimulation of fat storage by fat-7 is also not dependent upon nhr-49 (see Figure 5 D). Taken together, our findings demonstrate that nhr-49 controls two distinct circuits within a gene network: The stimulation of β-oxidation gene expression is independent of fat-7, and the promotion of fat-7 expression is independent of nhr-49 's effects on β-oxidation. However, because fat-7 expression inhibits the same β-oxidation genes induced by nhr-49, the regulation of fat-7 by nhr-49 connects these two circuits into a single regulatory network, serving to limit β-oxidation through an apparent feedback mechanism ( Figure 6 ). Discussion Here we demonstrated that deletion of the C. elegans nhr-49 gene produced two global phenotypes: shortened life span and high fat content. Using a QRT-PCR strategy, we found 13 genes involved in energy metabolism that depend upon nhr-49 for expression. The phenotypes of nhr-49(nr2041) were attributable to deficiencies in two different metabolic pathways, fatty acid β-oxidation and fatty acid desaturation. The high-fat phenotype is explained by lowered expression of β-oxidation enzymes, and the shortened life-span phenotype results from reduced expression of the fat-7 SCD. Interestingly, these pathways are linked by an apparent feedback mechanism, as fat-7 also serves to inhibit the expression of fatty acid β-oxidation genes ( Figure 6 ). These results represent the first detailed characterization of a divergent HNF4-like receptor in C. elegans and provide the first description of an NHR-controlled fat-regulatory network in invertebrates. Due to their evolutionary relationship to nhr-49, it seems conceivable that many of the C. elegans HNF4-like NHRs might participate in the regulation of fat metabolism. However, we have found that several other worm HNF4-like receptors, including those previously implicated for affecting overall fat storage [ 12 ], do not significantly impact the expression of fatty acid metabolism genes (M. R. Van Gilst and K. R. Yamamoto, unpublished data). Thus, the regulation of fat metabolism does not appear to be a general mechanism common to all of the divergent NHRs; whether or not nhr-49 is unique in its control of C. elegans fat metabolism remains to be determined. The mechanism by which nhr-49 influences fat storage is likely to be through modulation of β-oxidation gene expression ( Figure 6 ). Overexpression of acs-2 alone was sufficient to suppress the high-fat phenotype of nhr-49(nr2041), indicating that acs-2 expression is rate-limiting in nhr-49 deletion mutants, thus leading to reduced fat breakdown and excessive fat accumulation. Acyl-CoA synthetases activate fatty acids for many different metabolic pathways; in particular, mitochondrial acyl-CoA synthetases are likely to activate fatty acids for transport into the mitochondrial matrix, where the fatty acids are then subject to β-oxidation [ 18 , 19 ]. Notably, mitochondrial acyl-CoA synthetases are commonly regulatory targets for factors that control fat consumption [ 18 ]. We propose that by stimulating acs-2 expression, nhr-49 likely acts by increasing the flow of fatty acids into the mitochondria for β-oxidation ( Figure 6 ). Out of 11 acs genes in C. elegans, five of which are predicted to be mitochondrial, nhr-49 specifically affected the expression of only acs-2, suggesting that nhr-49 may be promoting transport of a specific subset of fatty acids into mitochondria. These subsets may differ by fatty acid chain length or tissue distribution. As both acs-2 and nhr-49 are expressed in numerous C. elegans tissues, regulation of fat consumption by nhr-49 may occur throughout the animal. Although acs-2 is related (with approximately 25% identity) to multiple mammalian acyl-CoA synthetases, mammals contain a particular homolog with approximately 41% identity to the C. elegans ACS-2 protein; this mammalian ACS protein is yet to be characterized. It will be interesting to determine whether the mammalian counterpart of acs-2 also serves as an important focal point for gene networks that regulate fat utilization in mammals. Interestingly, we also found that nhr-49 stimulates expression of a carnitine palmitoyl transferase (F09F3.9). Carnitine palmitoyl transferases execute the step immediately downstream of acyl-CoA synthetase in mitochondrial β-oxidation, directly shuttling activated acyl-CoAs into the mitochondrial matrix. Thus, nhr-49 appears to target multiple enzymes involved in transporting fatty acids across the mitochondrial membrane for β-oxidation ( Figure 6 ). RNAi of F09F3.9 did not detectably alter overall fat content, however, suggesting that interference of F09F3.9 expression alone is not sufficient to affect overall fat consumption under the conditions surveyed in our study. In contrast, we found that RNAi of ech-1, another β-oxidation gene targeted by nhr-49, was sufficient to increase overall fat content; thus it is likely that the reduced expression of ech-1 also contributes, in some fashion, to the high-fat phenotype of nhr-49(nr2041). Thus, we have demonstrated that nhr-49 strongly promotes the expression of three separate enzymes predicted to participate in mitochondrial β-oxidation. Consequently, we suggest that nhr-49 plays a prominent role in promoting the breakdown of fatty acids in mitochondria, and that, through control of β-oxidation, nhr-49 influences overall fat storage. In addition to its effect on β-oxidation, we found that nhr-49 helps to maintain the balance of saturated and monounsaturated fatty acids. By stimulating the expression of three fatty acid Δ9-desaturase genes, nhr-49 facilitates the conversion of saturated fatty acids to monounsaturated fatty acids, and consequently, nhr-49(nr2041) mutant animals are high in saturated fat and lower in monounsaturated fat. In C. elegans, the FAT-6 and FAT-7 SCDs may also be involved in the synthesis of PUFAs [ 17 ]. However, a dramatic reduction in fat-7 expression, either by nhr-49(nr2041) deletion or by fat-7 RNAi, did not significantly affect PUFA synthesis. This result suggests that a normal level of FAT-7 expression is not necessary for PUFA synthesis, likely because FAT-6 is the principle enzyme in this pathway, or because FAT-6 is capable of substituting for reduced FAT-7 activity. In either event, we propose that the primary effect of nhr-49 on fatty acid composition is a modulation of the ratio of C18:0 to C18:1n9 fatty acid ( Figure 6 ). However, we cannot rule out the possibility that nhr-49 and fat-7 also affect PUFA synthesis in a more localized manner, for example, specific cell types, such that changes in PUFA abundance are not detected in our whole-worm analysis. Our results also indicate that the short life-span phenotype of nhr-49(nr2041) is due, at least in part, to reduced expression of fat-7. The strong correlation between the increase in C18:0 saturated fatty acid and the shortening of life span is compelling. Several reports in mammals have described changes in fatty acid composition during aging, and it has been argued that an alteration of fatty acid saturation ratios in mitochondrial membranes may affect the rate of aging [ 20 ]. Additionally, imbalance of fatty acid saturation has also been linked to numerous pathological conditions [ 15 , 16 ]. Although SCDs have not yet been linked to life span in mammals, studies in C. elegans have identified fat-7 as one of the targets of the mechanisms that extend longevity through the insulin pathway [ 21 ]. Thus, it will be interesting to determine if the shortened life-span phenotype of nhr-49(nr2041) and fat-7 RNAi animals results from an improper ratio of saturated and monounsaturated fats, and if the mechanistic cause of the reduced life span is related to accelerated aging or to another pathology. Although it is clear that nhr-49 independently promotes the expression of genes in fatty acid β-oxidation and desaturation, we found that downstream components of these pathways do indeed communicate with each other. By inhibiting the expression of genes involved in β-oxidation, including the nhr-49 -dependent genes acs-2 and ech-1, fat-7 works against the actions of nhr-49, acting to hinder fat consumption ( Figure 6 ). Thus, our results reveal an elegant feedback mechanism: nhr-49 induces the expression of β-oxidation enzymes—thus promoting fat consumption—yet by independently stimulating fat-7 expression, nhr-49 tempers the expression of the very same β-oxidation genes ( Figure 6 ). Thus, we suggest that nhr-49 serves as a key regulator of fat usage, governing pathways that consume fat for energy and partition fat for storage, potentially shifting the balance in response to changing energy needs. Indeed, we have found that in response to starvation, nhr-49 selectively modulates the expression of these two pathways in order to increase fat consumption (M. R. Van Gilst and K. R. Yamamoto, unpublished data). As the predominant function of fat-7 is to convert C18:0 to C18:1n9 fatty acid, it is tempting to speculate that one of these two fatty acid species serves as a signal to modulate the feedback effect of fat-7 on fatty acid β-oxidation ( Figure 6 ). In this scenario, C18:0 could be serving as an activator of β-oxidation gene expression, C18:1n9 could be functioning as a repressor, or both ( Figure 6 ). Although it seems reasonable to propose that an NHR would communicate this fatty acid signal, we found that the effects of fat-7 on fatty acid β-oxidation were not dependent on nhr-49; hence, one of the other 283 C. elegans NHRs may mediate this effect. Despite its strong sequence similarity with the mammalian HNF4 receptors, the overall biological effects of nhr-49 on metabolism, fat storage, and life span are remarkably similar to those of the mammalian PPARs. Perhaps most striking is the finding that nhr-49 and the PPARs, particularly PPARα and PPARδ, positively influence similar genes in multiple metabolic processes, including fatty acid β-oxidation, fatty acid desaturation, and fatty acid binding/transport [ 22 , 23 ]. Moreover, knockout of PPARα or PPARδ can lead to high-fat phenotypes [ 23 , 24 ], demonstrating that the physiological effects of these receptors on fat storage are similar to those of nhr-49. The regulation of SCDs by nhr-49 also parallels the regulation of the SCD1 gene by PPARα. In mammals, the Δ9-desaturase SCD1 is a lipogenic enzyme that is controlled by several key regulators of fat storage, including PPARα, leptin, and sterol response element-binding protein [ 15 , 25 , 26 ]. When SCD1 expression is left unchecked, as occurs in leptin knockout mice, severe obesity can result. Similar to what we found for the C. elegans fat-7 gene, mammalian SCD1 affects fat storage by inhibiting β-oxidation [ 27 ]. Thus, because PPARα also promotes fat consumption by stimulating β-oxidation gene expression[ 28 ], it is clear that PPARα is independently regulating pathways that promote fat consumption and stimulate fat storage. In fact, a similar feedback mechanism to what we have described here for nhr-49 has been proposed for PPARα and SCD1 [ 27 , 29 ]. Taken together, these results demonstrate that the multicircuited regulatory networks governing fat usage appear well conserved between C. elegans nhr-49 and the mammalian PPARα. Although we have not yet determined whether or not the nhr-49 -dependent genes identified in this study are direct transcriptional targets, each is homologous to known transcriptional targets of the PPARs [ 22 , 23 ]. Because NHR-49 and the PPARs are clearly regulating similar physiological processes and gene networks, we believe that they are likely to be using similar molecular mechanisms, including direct transcriptional regulation. However, it is possible that nhr-49 controls fatty acid β-oxidation and desaturation through an indirect mechanism, functioning upstream of the transcription factors that directly act on the nhr-49 -dependent genes identified in this study. The latter possibility would also be intriguing, as it would demonstrate NHR involvement in fat regulation at a point upstream of a PPAR-like factor. As the physiological functions and regulatory targets of nhr-49 are highly similar to those of the mammalian PPARs, it seems reasonable to speculate that, like the PPARs, NHR-49 may be regulated by fatty acid ligands. By binding directly to ingested lipids and/or their metabolic products, NHR-49 could serve both as a sensor of intracellular fatty acid levels and an effector, responding to changes in fatty acid composition through modulation of fatty acid β-oxidation and desaturation. Interestingly, the mammalian HNF4 receptors, whose LBDs share 33% identity with the NHR-49 LBD, can bind to several saturated and monounsaturated fatty acids, including stearic and oleic acid [ 30 , 31 ]; the mammalian PPARs also bind to many types of fatty acids, although they interact preferentially with PUFAs [ 22 ]. It will be interesting to determine if mammalian HNF4 receptors harbor an undiscovered capacity to regulate fat metabolism in mammals, or if PPARs have adopted their regulatory functions by evolving from an ancestral HNF4 gene that had properties similar to nhr-49 and the modern PPARs. Alternatively, the PPARs and nhr-49 may have acquired their activities through convergent evolution. Precise regulation of fatty acid β-oxidation and desaturation is crucial for physiological homeostasis; imbalance in these metabolic pathways in humans can lead to disorders such as diabetes, obesity, atherosclerosis, and accelerated aging. However, although NHRs are important targets for drugs that moderate these metabolic disorders, the NHR-mediated regulatory networks that govern fat usage are notably complex and poorly understood. We showed here that many features of C. elegans nhr-49 regulation of fat metabolism are closely analogous to those of the mammalian PPARs, key targets for the treatment of metabolic disease. Moreover, our C. elegans studies revealed that nhr-49, like PPARα, oversees a branch point for two separate circuits within a network that controls fatty acid consumption and composition. The extent of the functional homology between nhr-49 and PPARα remains to be determined, that is, whether or not nhr-49 also functions by binding to fatty acid ligands and directly regulating gene transcription. Nevertheless, our finding that nhr-49 is a key regulator of fat metabolism in C. elegans represents a considerable advance in our understanding of NHR control of fat storage and composition in invertebrates. Consequently, we suggest that these and future studies in C. elegans will continue to enhance our understanding of the complex roles of NHRs and their ligands on gene networks governing fat physiology. Materials and Methods RNAi constructs All of the RNAi constructs used in the NHR screen were created by cloning full-length NHR cDNAs into the vector L4440 (Andy Fire, Stanford University). The fat-7 RNAi vector was a gift from Jennifer Watts (Washington State University). All of the other RNAi constructs were obtained from the Ahringer RNAi library [ 32 ]. Life span assays Approximately 30–40 starved L1 worms were transferred to RNAi bacteria (HT115 transformed with RNAi clone) and life-span assays were carried out at 23 °C as described previously [ 33 ]. nhr-49(nr2041) and WT life-span assays were carried out at 23 °C on OP50 bacteria. Nile Red assays Nile Red fat-staining assays were carried out as described previously [ 12 ]. Selection of fatty acid and glucose metabolism genes Most of the fatty acid and glucose metabolism candidate genes examined in this study were initially identified using the KEGG pathway database ( http://www.genome.ad.jp/kegg/pathway.html ). Other genes were identified using BLAST searches designed to find C. elegans open reading frames that were highly related to known mammalian glucose and fat metabolism enzymes, or to plant glyoxylate cycle genes. For prediction of β-oxidation enzyme subcellular localization, we used the following online prediction tools. TargetP server version 1.01 ( http://www.cbs.dtu.dk/services/TargetP/ ) [ 34 ] and PSORT ( http://psort.nibb.ac.jp/form.html ). Preparation of nematode total RNA Both C. elegans N2-Bristol (WT) and nhr-49(nr2041) were grown at 23 °C on high-growth plates seeded with OP50 bacteria. Gravid adults from 30 10-cm plates were bleached, and embryos were dispersed onto 15-cm nematode growth media (NGM)-lite plates seeded with OP50. The worms were distributed as follows: for L1 harvest, 80,000 embryos/plate; for L2 harvest, 40,000 embryos/plate; for L3 harvest, 20,000 embryos/plate; and for L4 harvest, 10,000 embryos/plate. The remaining embryos were saved for embryonic RNA preparation. Worms were harvested at the appropriate stage, washed twice with M9, and frozen in liquid nitrogen. For RNAi experiments, 10,000 embryos were placed onto NGM-lite plates containing 8 mM IPTG and 100 μg/ml carbenicillin seeded with control bacteria (HT115 transformed with empty L4440 vector) or nhr-49 RNAi bacteria (HT115 transformed with L4440- nhr-49 ). Worms were harvested at the L4 stage of development, washed twice with M9, and frozen in liquid nitrogen. For RNA preparation, worms were thawed at 65 °C for 10 min, and RNA was isolated using the Tri-Reagent Kit (Molecular Research Center, Cincinnati, Ohio, United States). Isolated total RNA was subjected to DNAase treatment and further purification using RNAeasy (Qiagen, Valencia, California, United States). QRT-PCR cDNA was prepared from 5 μg of total RNA in a 100-μl reaction using the Protoscript cDNA preparation kit (New England Biolabs, Beverly, Massachusetts, United States). Primer pairs (primer sequences available upon request) were diluted into 96-well cell culture plates at a concentration of 3 μM. Next, 30-μl PCR reactions were prepared in 96-well plates. Each PCR reaction was carried out with Taq DNA Polymerase (Invitrogen, Carlsbad, California, United States) and consisted of the following reaction mixture: 0.3 μM primers, 1/500th of the cDNA reaction (corresponds to cDNA derived from 10 ng of total RNA), 125 μM dNTPs, 1.5 mM MgCl 2 , and 1X reaction buffer (20 mM Tris pH 8.4, 50 mM KCl). 0.15 μl (0.75 units) of Taq DNA Polymerase was used for each reaction. Formation of double-stranded DNA product was monitored using SYBR-Green (Molecular Probes, Eugene, Oregon, United States). All QRT-PCR reactions were carried out and analyzed on a DNA Engine-Opticon 2 (MJ Research, Waltham, Massachusetts, United States). Data were collected using RNA from at least three independent C. elegans growths. To determine the relationship between mRNA abundance and PCR cycle number, all primer sets were calibrated using serial dilutions of cDNA preparations. Primer sets were also calibrated by performing QRT-PCR reactions on serial dilutions of C. elegans genomic DNA. Relative abundance is reported as the mRNA abundance of each gene relative to the mRNA abundance of several control genes, which are expressed at constant levels throughout development. GC/MS Fatty acids were isolated from 10,000 L4 animals grown on a single 15-cm NGM-Lite plate. For WT and nhr-49(nr2041) experiments, worms were grown at 23 °C on a lawn of OP50. For RNAi, 10,000 embryos were placed on control bacteria, or on fat-5, fat-7, ech-1, acs-2, or nhr-49 RNAi bacteria. Fatty acid extract was prepared as described previously [ 17 ]. GC/MS spectra were collected on an HP 6890 gas chromatograph outfitted with a J&W DB-XLB column. The mass spectrometer was an HP MSD 5973 (Agilent, Palo Alto, California, United States) and data were analyzed using Chemstation version A.03.00 software (Agilent). Peaks were assigned using fatty acid standards. GFP reporter analysis and ectopic expression of ACS-2::GFP To make the P nhr-49 GFP plasmid, a genomic fragment including 3.5 kb of the nhr-49 upstream sequence and 88 bp of the first exon of nhr-49 was ligated into the L3691 GFP expression vector (a gift of A. Fire). Germ-line transformation was performed following standard procedures [ 35 ]. P nhr-49 GFP was injected at the following concentrations: 1 ng/μl, 5 ng/μl and 20 ng/μl along with the co-injection marker pRF4 rol-6(su1006) injected at 60 ng/μl. At all three P nhr-49 GFP concentrations, we were unable to obtain stably transmitting lines. Animals used for GFP imaging were derived from the F1 generation and were mosaic, hosting the P nhr-49 GFP transgene in only a subset of tissues. To construct acs-2::gfp, a 4-kb genomic fragment, including the full-length acs-2 gene plus 2 kb of upstream sequence, was cloned into the vector L3691. Germ-line transformation was performed using 50 ng/μl of acs:2::gfp and 50 ng/μl pRF4 rol-6(su1006). For N2/ acs-2::gfp and nhr-49(nr2041)/acs-2::gfp, over ten independent transmitting lines were obtained and analyzed by GFP microscopy. GFP reporter expression was observed using a Zeiss Axiovert S100 fluorescence microscope (Carl Zeiss, Thornwood, New York, United States) under a 40X objective. For rescue experiments, 50–100 ng/μl of acs-2::gfp was injected into nhr-49(nr2041) and WT animals along with 50 ng/μl of pRF4 rol-6(su1006). Transgenic adults, selected for rolling behavior, were placed on Nile Red plates and assayed for fat content as described above. pRF4 rol-6(su1006) was injected into nhr-49(nr2041) in combination with unrelated plasmids to demonstrate that the lowered fat content was not a result of hosting a transgenic array or caused by expression of the rol-6(su1006) marker gene. Supporting Information Table S1 Raw Data for QRT-PCR Screen Data are shown as C t , the number of cycles required for amplification of a particular target gene from a cDNA preparation. Changes in gene expression in the nhr-49(nr2041) mutant were measured as ΔC t . ΔC t are obtained by subtracting nhr-49 (C t ) from N2(C t ) and adjusting for RNA concentration differences with a correction factor (CF). The CF was determined by aligning the data to a set of standard genes. Thus the equation for ΔC t is as follows: Genes were designated as nhr-49 dependent if the C t was >1.0 in multiple developmental stages (and was greater than the standard error). nhr-49 targets are marked with an X. The QRT-PCR results of the major nhr-49 targets, acs-2, ech-1, fat-5, and fat-7, were confirmed with a second primer pair. (100 KB XLS). Click here for additional data file.

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509412

A Case for a Functional Actin Network in the Nucleus

In June, muscular dystrophy patients lost one of their most passionate advocates to a rare form of this degenerative neuromuscular disorder—thirteen-year-old Mattie Stepanek. In his short life, Stepanek wrote five volumes of inspirational poetry, topping the New York Times bestseller list and winning accolades from the likes of Jimmy Carter. A wide range of inherited disorders falls under the rubric of muscular dystrophy, but all involve some form of progressive muscle wasting. Stepanek's condition impaired nearly all of his body's functions, but other more common forms, including Emery-Dreifuss muscular dystrophy (EDMD), selectively target skeletal muscle and induce cardiac abnormalities. EDMD is caused by mutations in either of two genes: one encodes lamin A, a structural protein associated with the nucleus, and the other encodes a nuclear membrane protein called emerin. Lamins, a major component of the structural network that supports the nuclear envelope, help the nuclear envelope maintain structural integrity and absorb mechanical stress without rupturing. (Structures that support the nucleus and regulate molecular traffic between the cytoplasm and nucleus are collectively referred to as the nuclear envelope. They include the inner and outer nuclear membranes, the nuclear pore complexes, and a network of lamin filaments, called the nuclear lamina, near the inner membrane.) Emerin binds to proteins that regulate gene transcription. Emerin and lamins are found in most cell types, yet EDMD attacks only skeletal muscles, major tendons, and the cells that regulate cardiac muscle contraction. So where does this tissue specificity come from? One theory suggests that emerin selectively targets proteins that specifically regulate gene expression in EDMD-affected tissues. Another theory proposes that emerin provides structural support to the nuclear envelope and that emerin mutations are most destructive in tissues subjected to mechanical stress—like skeletal muscle and tendons. Current evidence supports both models. Recent studies suggest that emerin forms complexes with actin—the mother of all structural proteins. Actin proteins can join together (polymerize) to form a variety of filaments. However, given longstanding doubts that actin exists in the nucleus, let alone functions there, researchers were unsure what the findings might indicate. Now James Holaska, Amy Kowalski, and Katherine Wilson propose that emerin not only functions as a structural protein in the nucleus but that it does so by interacting with actin. Interactions of structural proteins at the nuclear membrane Evidence that emerin and lamin A can form multiprotein complexes comes primarily from experiments in test tubes. To get a sense of the physiological significance of these findings, Wilson and colleagues purified emerin-binding proteins from the nuclei of living cells. They found that emerin binds to polymerized actin and, in fact, appears to stimulate polymerization. By binding and “capping” a specific end of the actin filament, emerin prevents filament de-polymerization (disassembly), effectively increasing the rate of actin polymerization by four- to twelve-fold. The authors propose that emerin “promotes the formation of a nuclear actin cortical network,” which could serve to anchor membrane proteins and lamin filaments to the inner nuclear membrane and thus enhance the structural integrity of the nuclear envelope. Whether emerin also interconnects the lamin and actin filament networks at the nuclear envelope—which could significantly reinforce its mechanical strength—will have to await further study. Muscle contraction places enormous stress on cell membranes. These results suggest that actin-based networks, in addition to lamin networks, support the structural integrity of the nuclear envelope. Defects in proteins involved in either network could compromise nuclear structure, which could in turn disrupt the cell's gene expression program, for example, or rupture the cell membrane, killing the cell. Subtle defects in proteins important for muscle cell integrity can cause several forms of muscular dystrophy. Now it appears that emerin defects could cause EDMD in part by compromising the mechanical integrity of nuclei in muscle cells and tendons.

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539248

Successful obstetrical management of 110-day intertwin delivery interval without cerclage: counseling and conservative management approach to extreme asynchronous twin birth

Background This report describes a patient counseling approach and non-surgical management of a dichorionic-diamniotic twin pregnancy where delivery of the second twin followed the delivery of the first by 110 days. Case presentation An early transvaginal sonogram at 19 1/2 weeks suggested cervical dilation with protruding amniotic membranes. Tocolytic and antibiotic therapy was initiated; no cerclage was placed. Spontaneous rupture of membranes and cord prolapse occurred 48 h later, resulting in delivery of a stillborn female infant. Conservative management was offered after counseling for possible risks associated with maternal sepsis, need for extended hospitalization, potential for hysterectomy and death. The cervix appeared closed after delivery and the umbilical cord was ligated, with subsequent spontaneous cord retraction in utero . Reassuring fetal status was observed for twin B without evidence of contractions or chorioamnionitis. A viable male infant (2894 g) was delivered vaginally at 35 1/2 weeks. Conclusions This report outlines a counseling approach useful for patients with premature delivery of one twin, and presents application of conservative obstetrical management principles for the aftercoming twin even when delivery interval is extreme.

Background The incidence of twin gestation has increased in recent years, a trend influenced in part by greater utilization of the assisted reproductive technologies. In this report, we describe a conservative approach culminating in vaginal delivery of a viable second twin 110 days after delivery of a preterm stillbirth. Case presentation A 30 year-old non-smoking Caucasian G 3 P 1011 presented for initial prenatal assessment at six weeks gestation. The conception was established without medical assistance. The patient had no significant medical or surgical history. She underwent an uncomplicated curettage for missed abortion four years before presentation and an uneventful term vaginal delivery occurred two years later. Transvaginal ultrasound at seven weeks gestation revealed a dichorionic-diamniotic twin pregnancy. At 18 weeks gestation no growth discordance was noted, but cervical length was two cm with funneling. Based on these findings, the patient was counseled about maternal and neonatal risks associated with twin pregnancy, particularly the risk of preterm labor due to cervical shortening. Although rescue cerclage was offered to the patient, this option was declined. She was therefore placed on bedrest for two weeks with follow-up ultrasonography for assessment of cervical length. At 19 2/7 weeks gestation the patient experienced abdominal cramping and non-purulent blood-tinged vaginal discharge. The patient remained afebrile. She was hospitalized and placed on bed rest in Trendelenburg position after sterile speculum exam found the cervix two cm dilated with protruding "hourglass membranes". One day later, amniotic membranes had fully retracted and were no longer visible above a closed cervix. Microscopic examination of vaginal fluid found occasional clue cells. External monitoring identified occasional uterine contractions; heart rates at ~150/min were measured for both twins. The patient was again counseled about the implications of preterm labor at this early stage, and the uncertainty of preventing further cervical dilation. After consideration of all therapeutic options (including cerclage), the patient elected tocolysis with a view to save her pregnancy. A 4 g loading dose of magnesium sulfate was administered intravenously, followed by a maintenance dose of 2 g/h. Oral metronidazole (500 mg) was given every 8 h, and 500 mg ampicillin was given intravenously every 6 h after a 2 gm loading dose according to hospital protocol. Additionally, oral indomethacin (50 mg) was given every 6 h for 3 days. Just as the magnesium sulfate was initiated, the patient experienced spontaneous rupture of membranes and prolapse of umbilical cord of twin A was noted several hours later. Fetal demise was confirmed approximately 1 h later, but there was no evidence of labor or infection over the next 24 h. After discussing the potential dangers of prolonged rupture of membranes, retention of dead fetus, maternal sepsis, the potential for prolonged hospitalization, need for hysterectomy and risk of death, the patient elected to continue limited oxytocin augmentation in an attempt to deliver twin A and salvage twin B. The risk of losing both fetuses was carefully discussed, and the patient agreed with this management approach despite the acknowledged uncertainty of outcome. After 8 h of oxytocin therapy, a stillborn female fetus (319 g) was delivered. The placenta remained in situ and the umbilical cord of twin A was divided and ligated near the cervix with 3-0 chromic gut suture. Oxytocin was immediately discontinued. Monitoring of twin B confirmed stable heart tones and appropriate fetal movement throughout delivery of the non-viable twin. Intravenous ampicillin and metronidazole were continued postpartum but MgSO 4 was not reinitiated. Immediately following delivery of twin A, sterile speculum exam found a closed cervix with the umbilical cord completely retracted in utero . Maternal vital signs remained stable and she was discharged home one week later on full bed rest, preterm labor precautions, and oral amoxicillin-clavulanate (875 mg) twice daily × 5 d. At 25 weeks gestation, 12 mg betamethasone was administered intramuscularly with an additional dose 24 h later. There was no evidence of infection or coagulopathy at biweekly clinical evaluations, which included serial ultrasounds until 34 weeks to assess cervical length. Formal biophysical profiles (BPP) began at 28 weeks, when the estimated fetal weight was 1250 g and the BPP score was 8/8. At this time mild uterine irritability was detected and 5 mg oral terbutaline was given every 4 h until 34 weeks. Uterine activity was reduced following oral terbutaline therapy. Spontaneous labor began at 35 1/7 weeks. At readmission, the cervix was 5 cm dilated with intact membranes and vertex presentation. Epidural anesthesia was established, an amniotomy was performed, and the patient had a normal progress of labor. She delivered a viable male infant weighting 2894 g (1 and 5 min Apgar 9 and 9, respectively) over an intact perineum. Approximately 5 min later, two placentas were delivered spontaneously (Figure 1 ). The postpartum course was uncomplicated; mother and baby were discharged home in stable condition 48 h later. Figure 1 Gross post-delivery image of dichorionic-diamnionic placenta showing sites of umbilical cord insertions (*). The placenta associated with the nonviable 19-week spontaneous abortion (A) demonstrates atrophy, in contrast with normal placenta from the aftercoming liveborn twin (B). Conclusion The incidence of twins has increased substantially due to advancements in the assisted reproductive technologies [ 1 ]. With more twin gestations have come more variations on the twin birth experience, sometimes including very prolonged intervals between deliveries of the twins themselves. Important risks associated with asynchronous twins include ascending infection and subsequent chorioamnionitis after delivery of the first twin. For our patient, the development of intrauterine infection and possible septic abortion of twin B was carefully discussed [ 2 ], as was the potential for severe coagulopathy in the setting of undelivered placental tissue [ 3 ]. Controversy persists on the matter of how best to manage such patients with delayed delivery interval of the second twin, perhaps because of the overall rarity of this clinical presentation. Since cases with positive outcomes (including the current report) are more likely to appear in the medical literature than those describing an unsatisfactory result, a publishing bias may favor the former. While the longest known intertwin delivery interval with cerclage is 153 d [ 4 ], our experience of twin pregnancy with a 110 d delivery interval illustrates the potential for a satisfactory obstetrical course without cerclage. Even as our report describes one of the longest known inter-twin delivery intervals managed without cerclage, others have described even longer delivery intervals, also without cerclage [ 5 ]. Our management validates the principle that when the first twin is delivered very prematurely, extending the gestational age for an undelivered co-twin is advantageous for the second twin without significant morbidity in the mother. In selected multiple gestations achieved with medical assistance ( i.e ., conceptions following use of the advanced reproductive technologies), some authors have suggested that attempts to prolong the pregnancy following spontaneous abortion or extremely premature birth of one fetus is efficacious and justified [ 6 ]. Competing interests The author(s) declare that they have no competing interests. Authors' contributions LMG and SAW were the resident physicians associated with the case. SAS was the lead obstetrician and primary physician at delivery. ESS conceived of the research, directed the residents, and coordinated manuscript revisions. Pre-publication history The pre-publication history for this paper can be accessed here:

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534787

Increasing response to a postal survey of sedentary patients – a randomised controlled trial [ISRCTN45665423]

Background A systematic review identified a range of methods, which can influence response rates. However, analysis specific to a healthcare setting, and in particular, involving people expected to be poor responders, was missing, We examined the effect of pre-warning letters on response rates to a postal survey of sedentary patients whom we expected a low rate of response. Methods Participants were randomised to receive a pre-warning letter or no pre-warning letter, seven days before sending the main questionnaire. The main questionnaire included a covering letter and pre-paid return envelope. After seven days, non-responders were sent a reminder letter and seven days later, another reminder letter with a further copy of the questionnaire and return envelope. Results 627 adults, with a mean age of 48 years (SD 13, range 18 to 78) of whom 69.2% (434/627) were women, were randomised. 49.0% (307/627) of patients were allocated to receive a pre-warning letter and 51.0% (320/627) no pre-warning letter, seven days in advance of posting the main questionnaire. The final response rate to the main questionnaire was 30.0% (92/307) amongst those sent a pre-warning letter and 20.9% (67/320) not sent a pre-warning letter, with an adjusted odds ratio of 1.60 (95% CI 1.1, 2.30). Conclusions The relatively low cost method of sending a pre-warning letter had a modest impact on increasing response rates to a postal questionnaire sent to a group of patients for whom a low response rate was anticipated. Investigators should consider incorporating this simple intervention when conducting postal surveys, to reduce the potential for nonresponse bias and to increase the study power. Methods other than postal surveys may be needed however when a low response rate to postal surveys is likely.

Background Postal surveys are routinely used to obtain information from patients and groups within the general population, over a range of topics. Postal surveys are a cost-efficient method compared with intensive methods such as face-to-face interviews and capable of obtaining systematically, information on many thousands of people. A key quality component of postal surveys relates to the number of people sampled, and the proportion returning a completed useable questionnaire [ 1 ]. Lower response rates can reduce the statistical power of the study, and mask statistically significant relationships, which 'truly' exist within the population studied. Responders may also be different to non-responders. This can introduce bias into the survey findings, if the decision to respond (or not) relates to the outcome being analysed within the survey, thereby reducing generalisability to the initial reference population [ 2 ]. Many studies conclude that non-responders in surveys and other epidemiological studies can differ to responders with respect to a range of specific health, lifestyle and social variables. Non-responders have been found to differ with respect to their sex, age, race, social class, home circumstances, education, and healthy lifestyle behaviours [ 3 - 7 ]. They can also differ in terms of existing health and healthcare utilisation [ 8 - 11 ] with differences extending through to higher rates of mortality [ 12 ] compared with responders. However, it can be difficult to make clear conclusions about the characteristics of non-responders in surveys and other types of studies, as factors such as the purpose of the study and the way in which it was carried out, will no-doubt have some effect. Furthermore, differences have not always been found between responders and non-responders, at least in terms of what factors were assessed, and nonresponse will not always affect estimates of prevalence [ 13 - 15 ]. Nevertheless, nonresponse bias should always be considered a possibility [ 16 , 17 ]. Moreover, there is evidence that in general, response rates to postal questionnaires are falling, [ 18 ], making this topic worthy of continued investigation. There is however, no agreed level of acceptable response in postal surveys [ 19 - 21 ]. A systematic review [ 22 ] found a number of factors associated with postal questionnaires can influence the likelihood of response. This included providing incentives; questionnaire length and appearance, method of delivery, method for return, if any pre-warning/contact was given, the content and layout of the questions, through to the origin/sponsor of the questionnaire and how it was communicated. The review found that monetary incentives, recorded delivery and using an 'interesting' questionnaire were the three strongest influences on response rates. Statistical heterogeneity was found for all of these factors, thus limiting the extent that pooling of results was viable. Moreover, only a third of studies were from medical/epidemiological/healthcare journals and with no distinction between studies of patients or of staff and subgroup analyses were absent. As such, it is difficult to generalise the findings from the review to particular groups of patients in a healthcare setting. In the current study, we carried out a randomised controlled trial to examine the effect of a pre-warning letter on response rates to a postal questionnaire. The questionnaire was sent to patients who had previously been referred to a community based exercise referral scheme because of a sedentary lifestyle and sought information on the quality of the service offered. An earlier study [ 23 ] of a similar population suggested poor response rates could be a problem. With a limited budget, we were unable to offer financial incentives, as suggested in the review by Edwards et al [ 22 ], but wanted to explore the suggestion that pre-warning letters might increase final response. Methods The sample consisted of patients who had been referred to a community based exercise referral scheme during the past 12 months, identified from the service register. Patients were referred by a primary care practitioner because of concerns about their sedentary behaviour and its impact on their health. The questionnaire formed part of a project examining the relationship between patient service-expectations and service outcomes. We examined the effect of a pre-warning letter, posted to patients seven-days before sending the main questionnaire, compared with no pre-warning letter. The pre-warning letter was printed on one-side of letter-headed paper, and informed the respondent that a survey would be sent to them within the next few days. It informed them about the purpose of the survey and the importance of it being completed and returned. The main questionnaire was sent with a covering letter and a pre-paid business franked addressed envelope for its return [ 24 ]. A standard reminder letter was sent to all non-responders seven days after posting the questionnaire, and after a further seven days, persistent non-responders were sent a further copy of the questionnaire, with a standard letter and return envelope. Randomisation was done using computer generated random numbers, and stratifying by age and sex. Participants remained unaware as to group allocation. The primary outcome was the final response rate to postal questionnaires after sending all reminder letters. This was calculated at least 6 weeks after sending the initial questionnaire, to allow for late responders. Differences in proportions between groups were examined using Pearson's chi-square test and logistic regression to adjust for age and sex with 95% confidence intervals (95% CI). To observe a difference of at least 10% between trial arms required 752 participants, based on a return rate of 60% in the control groups, with 80% power. Approval for the study was received in advance from the local research ethics committee and the research governance committee. Results The number of patients referred to the exercise referral scheme in the past year with complete name and address information was 627. Their mean age was 48 years (SD 13, range 18 to 78) and 69.2% (434/627) were women. Randomisation allocated 49.0% (307/627) of patients to receive a pre-warning letter and 51.0% (320/627) no pre-warning letter (Figure 1 ). The two groups were balanced with respect to sex (66.8% female in the pre-warning group compared with 71.6% in the control group) and age (mean 48.7 years, SD 13.3, in the pre-warning group compared with mean 47.6 years, SD 13.9 in the control group). The final response rate to the postal survey, after completing two stages of follow-up was 25.4% (159/627). In the pre-warning group, the response rate was 30.0% (92/307) compared with 20.9% (67/320) in the control group (χ 2 6.75, p = 0.009) (Figure 2 ). Thus giving a difference between the two groups of 9.1% (95% CI for risk difference, 2.2% to 15.8%) (Figure 2 ). In a logistic regression model, the pre-warning letter increased the odds of returning the questionnaire by 1.61 (95% confidence interval 1.12, 2.32) and this was not altered after adjusting for age (in years) or sex (OR adj age sex 1.60, 95% CI 1.11, 2.30). Conclusions Sending a pre-warning letter seven days in advance of mailing out a postal questionnaire had a modest impact on increasing final response rates by almost 10%, with a relative 43% increase compared with sending no pre-warning letter. Patients in our study were selected on the basis of a previous referral to a community based exercise referral scheme, and the questionnaire sent to them sought information about their perceptions of the service quality. An earlier trial examining the impact of this service on a similar group of patients, in terms of increasing physical activity, had achieved average response rates of 60% [ 23 ]. The much lower than expected response rate in the current study could have been influenced by the topic and purpose of the questionnaire along with the layout of the questionnaire [ 22 ]. Our findings are consistent with the evidence from a systematic review [ 22 ] that pre-contact can lead to an increased odds of response by as much as 50%. Our study confirms that this benefit extends to groups of sedentary patients known in advance, to be reluctant to reply. Pre-warning letters are simple to administer and relatively low cost compared with more labour intensive methods to increase response rates, such as telephone reminders or face-to-face visits. Moreover, this intervention method does not require any additional information or administrative systems over and above those required for sending the main questionnaire. Give that the response rate in the intervention group still remained low, at 30%, we may need to consider alternative approaches to postal questionnaires to obtain information from this group of patients, particularly if non-response could be associated with the outcomes examined within the survey – in this case, the patient experience of the exercise referral service. Competing interests The authors declare that they have no competing interests. Authors' contributions RAH conceived the study design, drafted the main protocol, carried out randomisation, analysed the results and wrote the first draft of the paper. DC was responsible for completing the study, for data entry, for assisting with data analysis and significant comments on the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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549036

Validation of the Clinical COPD questionnaire in Italian language

Background The development and validation study of the Clinical Chronic Obstructive Disease (COPD) Questionnaire (CCQ) has recently been published in this journal. The CCQ is the first questionnaire that incorporates both clinician and patient guideline goals in the clinical control evaluation of patients with COPD in general clinical practice. The aim of this study is the validation of the CCQ questionnaire in Italian, in specific pulmonary disease clinical practice. Methods Validity was tested on a population of healthy subjects and patients with COPD, using the Italian validated version of the Short Form Health Survey (SF-36) and guideline recommended routine measurement in COPD patients (FEV 1 , FVC, BMI and functional dyspnoea). Test-retest reliability was tested by re-administering the CCQ after 2 weeks. Responsiveness was tested by re-administering the CCQ after three weeks of hospital pulmonary rehabilitation. Distance walked and Borg breathlessness rating were measured at the end of the six-minute walking test (6 MWT), before and after rehabilitation. Results Cross-sectional data were collected from 175 subjects (55 healthy; 40 mild-moderate, 50 severe and 25 very severe COPD). Cronbach's alpha was high (0.89). The CCQ scores in patients were significantly worse than in healthy subjects. The CCQ total score in patients with COPD was significantly worse in those with BMI < = 21. Significant correlations were found between the CCQ total score and domains of the SF-36 (rho = -0.43 to rho = -0.72). The correlation between the CCQ and FEV1 % predicted was rho = -0.57. The correlation between the CCQ and MRC was rho = 0.63. Test-retest reliability was determined in 112 subjects over a period of two weeks (Intra Class Coefficient = 0.99). Forty-six patients with COPD showed significant improvement in CCQ scores, distance-walked and Borg breathlessness rating after 3 weeks of pulmonary rehabilitation, indicating CCQ responsiveness. Conclusions The CCQ is self-administered and has been specially developed to measure clinical control in patients with COPD. Data support its validity, reliability and responsiveness in Italian and in specific pulmonary disease clinical practice.

Background The American Thoracic Society (ATS) and European Respiratory Society (ERS) have jointly proposed standards [ 1 ] for the diagnosis, treatment and spirometric classification of patients with chronic obstructive pulmonary disease (COPD). According to the GOLD (Global Obstructive Lung Disease) guideline [ 2 ], the goals of clinical control in patients with COPD include health-related quality of life goals (improved exercise tolerance and emotional function) and clinical goals (prevention of disease progression and minimization of symptoms). The Clinical COPD questionnaire (CCQ) [ 3 ] is the first practical clinical instrument to be used for routine evaluation of clinical control (symptom, functional state and mental state) concerning patients with COPD, in general practice. The development and validation study has been published in this journal and data were collected from 119 subjects. The aim of the present study is the validation of the CCQ in Italian in specific pulmonary disease clinical practice. In this practice, the ATS/ERS [ 1 ] recommended routine measurements, in all patients with COPD, are the following: forced expiratory volume in one second (FEV 1 ) and forced vital capacity (FVC), body mass index (BMI) and functional dyspnoea (Medical Research Council – MRC). Methods Subjects Healthy subjects were selected in social meeting places. Subjects were asked, individually, to answer a simple questionnaire after the study had been explained to them. Only subjects over 40 years of age were interviewed. We excluded subjects with any disease symptoms, or any limitation in daily activities for any reason, or who mentioned suffering from disabling chronic diseases (COPD, asthma, arthritis, angina or heart insufficiency). All subjects gave their informed written consent for baseline spirometry and questionnaires administration, as approved by the local Medical Ethics Committee. We enrolled 55 subjects, 52 non-smokers and 3 ex-smokers. Subject data are shown in Table 1 . Table 1 Characteristics and results of the study population in subgroups Healthy subjects Mild-moderate COPD-class I-II Severe COPD-class III Very severe COPD-class IV N 55 40 55 25 Males (%) 62.0 85.0 63.6 72.0 Age (yr) 70 abcd (41–82) 72 abcd (58–84) 71 abcd (41–86) 71 abcd (42–86) LTOT (%) 0.0 0.0 32.7 72.0 HMV (%) 0.0 0.0 7.2 8.0 BMI (kg/m 2 ) 25.7 abcd (18.0–30.0) 26.7 abcd (18.6–37.8) 25.1 abcd (16.4–36.4) 26.6 abcd (16.2–34.6) FEV 1 /FVC (%) 79.2 (70.4–94.5) 59.7 (40.4–68.2) 44.2 (27.9–66.2) 35.1 (21.1–57.3) FEV 1 (% predicted) 108.0 (69–132) 69.5 (51.4–117.1) 40.7 (30.2–49.8) 26.4 (16.4–29.7) MRC functional dyspnoea 0.6 ± 3.4 (0–1) 1.1 ± 0.8 (0–2) 1.6 ± 0.7 (0–4) 2.3 ± 0.9 (0–4) CCQ symptom 0.5 (0.0–4.0) 1.3 b (0.0–4.0) 1.5 b (0.3–5.8) 2.5 (0.3–3.8) CCQ functional state 0.5 a (0.0–5.3) 1.0 a (0.0–3.5) 1.5 (0.0–5.3) 3.0 (0.3–5.0) CCQ mental state 0.0 (0.0–4.5) 0.0 (0.0–5.0) 1.0 c (0.0–6.0) 1.5 c (0.0–6.0) CCQ total 0.4 (0.0–3.8) 0.9 (0.0–3.5) 1.4 (0.3–5.2) 2.6 (0.4–4.3) CCQ = Clinical COPD Questionnaire; range 0–6; 0 indicating best possible control and 6 indicating worst clinical control. LTOT = long term oxygen therapy. HMV = home assisted mechanical ventilation during night. BMI = body mass index. FVC = forced vital capacity. FEV 1 = forced expired volume in one second. MRC = Medical Research Council. Healthy: normal spirometry, no chronic symptoms (cough, sputum production and/or dyspnoea). COPD classification by post-bronchodilator spirometry according to GOLD guidelines: mild-moderate FEV 1 /FVC <= 0.70 and FEV 1 >= 50% predicted, severe FEV 1 /FVC <= 0.70 and FEV 1 >= 30% predicted, very-severe FEV 1 /FVC <= 0.70 and FEV 1 < 30% predicted. Medians not sharing a common superscript (a,b,c,d) are significantly different at p < 0.05 after Mann-Wittney U test. MRC data are reported as mean value with standard deviation and range. Patients with COPD were consecutively enrolled in the outpatient section of our Division during medical consultation. According to the guidelines [ 1 , 2 ], COPD was defined by the presence of chronic cough, sputum production and/or dyspnoea. Patients with airways obstruction (FEV 1 /FVC <= 0.70) were classified as mild (FEV 1 post-bronchodilator (pb) >= 80% predicted), moderate (FEV 1 pb >= 50% predicted), severe (FEV 1 pb >= 30% predicted) and very severe (FEV 1 pb < 30% predicted). We excluded COPD patients with: a) significant improvement of FEV 1 pb (>= 15 % and/or 200 ml) compared with baseline, b) disease exacerbation in the previous four weeks, c) asthma, chronic heart failure, obstructive sleep apnoea syndrome, cancer or other disabling diseases except COPD. We enrolled 120 patients (77 ex-smokers, 19 smokers). In 1999, the local health service authority approved the standard evaluation procedures used in our outpatient clinic for patients with COPD. The patients' data are shown in Table 1 . Forty-six patients with COPD (exclusion criteria as mentioned above) were enrolled in a continuous pulmonary rehabilitation program, 31 males, 30 ex-smokers, 6 smokers, 13 in long-term oxygen therapy (LTOT), 2 in home-assisted mechanical ventilation during the night (HMV), median age 72 (range 41–83), median FEV 1 pb 46 % predicted (range 18–68). In 1999, the local health service authority approved our continuous pulmonary rehab program for patients with COPD. Cross sectional validity The CCQ was administered to all subjects. They were instructed to recall their experiences during the previous week. The CCQ is self-administered and contains only 10 items, subdivided into three domains: symptom (item 1–2–5–6), functional state (item 7–8–9–10) and mental state (item 3–4). Subjects responded to each question using a 7 point scale from 0 = asymptomatic or no-limitation, to 6 = extremely symptomatic or totally limited. The overall clinical COPD control score and the score of the three domains was calculated by adding all the scores together and dividing the sum by the number of questions. The Italian translation of the copyrighted questionnaire and permission for use was obtained from T. van der Molen [ 3 ] in February 2004 by one of the team (SD). Lung function (FEV1 and FVC) was measured according to ERS guidelines [ 4 ] using a portable turbine spirometer (Pony, Cosmed, Italy) in base condition (all subjects) and 20 minutes after metered inhalation of 200 mcg of salbutamol (COPD patients only). The copyrighted Italian validated version [ 5 ] of the 36-item Short Form Health Survey (SF-36) [ 6 ], a generic health-related quality of life questionnaire, was administered to 120 patients with COPD and 55 healthy subjects. The validated Italian version of SF-36 and permission for use was obtained from GlaxoSmithKline in June 2002 by one of the team (SP). Functional dyspnoea was assessed in all subjects using the Medical Research Council (MRC) scale as proposed by ATS/ERS guidelines [ 1 ]: 0 = not subject to breathlessness except with strenuous exercise, 1 = subject to shortness of breath when hurrying or walking up a gradually sloping hill, 2 = walks slower than people of the same age due to breathlessness or has to stop for breath when walking at a normal pace on a level, 3 = stops for breath after walking about 100 m or after a few minutes on a level, 4 = too breathless to leave the house or breathless when dressing or undressing. BMI was calculated by dividing weight (in kg) over height (in m 2 ), for all subjects. Longitudinal validity The CCQ was re-administered after 2 weeks (where there was no variation of the previous therapy or introduction of new therapy) in 112 subjects (53 healthy and 59 patients with COPD), 75 males, median age 71 years (range 41–84), median FEV 1 60 % predicted (range 19–117). We tested the CCQ responsiveness in patients with COPD undergoing continuous pulmonary rehabilitation. Patients were treated in four successive groups in our hospital following a standard three-week protocol. According to guidelines [ 7 ], the program was individually tailored and designed to optimize physical and social performance and autonomy, and to be integrated into overall patient treatment. It was a mix of physical retraining, thoracic and general physiotherapy, education, self-monitoring. At the end of the three-week hospitalization period, patients received: a) their individual continuous pulmonary rehabilitation home program together with optimized pharmacological therapy, b) the next three-month appointment for the outpatient evaluation visit, c) the next six-month appointment for successive inpatient three-week pulmonary rehabilitation. The CCQ was administered, on admission and on discharge from hospital, to 46 COPD patients. Patients were submitted to a 6-minute walking test (6 MWT) on hospital admission and discharge, according to guidelines [ 8 ]. In each occasion, we measured distance-walked and breathlessness at the end of 6 MWT, using the standard Borg rating scale [ 9 ]. This is a category scale in which simple verbal expressions, that describe increasing degrees of breathlessness in exercise, are linked to numbers (range from 0 = nothing at all to 10 = maximal). The CCQ was also administered after two more weeks during home-based comprehensive treatment. All patients gave their informed written consent for re-administration of CCQ, at home or in the outpatient section. Statistical Analysis We applied the same analysis undertaken in the original English validation study [ 3 ], taking for granted the same a priori assumptions. Data analysis was performed using SPSS version 12.0 (SPSS Inc, USA). Data are expressed as median (range) unless otherwise stated. CCQ internal consistency was evaluated by calculating Cronbach's alpha coefficient (for the three domains and the total). Non-parametrical testing (Mann-Whitney U test) was used to determine the discriminant validity of the CCQ to differentiate between healthy subjects and COPD patients with different degrees of airways obstruction (mild, moderate, severe, very severe). Spearman's rank correlations were used to examine convergent and divergent validity. Test-retest reliability analysis was done by calculating the Intra-class Correlation Coefficient (ICC). Responsiveness was tested using Wilcoxon U test. A value of p < 0.05 was considered as statistically significant. Results Score distributions The distributions for all domains and the overall scores were skewed. In the population study, 12 subjects (7%) scored optimally (= 0) in the total score, whereas 87 subjects (50%) scored optimally in the mental state domain. In the COPD group (120 subjects), 3% of the patients scored optimally in the total score, whereas 35% scored optimally in the mental state. Internal consistency Cronbach's alpha was 0.89 for the total score. Internal consistencies of symptom, functional state and mental state were 0.71, 0.88 and 0.80, respectively. Discriminant validity Healthy subjects had significantly lower (better) CCQ score only in the symptom domain (p = 0,05) compared with the small number (6 subjects) of patients with mild COPD (FEV 1 pb >= 80% predicted). At the same time, this small group did not differ significantly (all CCQ scores) from the group (34 patients) with moderate COPD (FEV 1 pb < 80% and >= 50% predicted). For this reason, Table 1 shows CCQ scores in subgroups of healthy, mild-moderate COPD, severe COPD, and very severe COPD subjects. Healthy subjects had significantly lower CCQ scores than patients with mild-moderate COPD with respect to total score (p = 0.001), symptom domain (p = 0.000), mental state domain (p = 0.005), except functional state domain. Patients with mild-moderate COPD had better CCQ values compared with patients with severe COPD, with respect to total score (p = 0.041), functional state (p = 0.017), mental state (p = 0.037), except symptom domain. Patients with severe COPD had lower CCQ scores than patients with very severe COPD, with respect to total score (p = 0.007), functional state domain (p = 0.003), symptom domain (p = 0.032) except mental state domain. The healthy subjects group had a significantly (p = 0.003) lower (better) MRC score than patients with mild-moderate COPD. Patients with severe COPD had a significantly (p = 0.003) higher (worse) MRC score than patients with mild-moderate COPD. Patients with very severe COPD had a significantly (p = 0.000) worse MRC score compared with those with severe COPD (Table 1 ). We did not find (Table 1 ) any significant difference in BMI between healthy and diseased subjects and among patients with increasing airways obstruction. In agreement with Celli BR et al. [ 10 ], we considered 21 as a cut-off BMI value for COPD patients' clinical control. Table 2 shows the data of 120 patients with COPD subdivided into three different classes: subjects having BMI <= 21 (low-range), BMI <= 28 (acceptable-range) and BMI > 28 (high-range). In these three groups, no significant difference was found for FEV 1 pb % predicted, age and MRC score. CCQ scores were higher in both low and high BMI groups, with respect to the acceptable BMI range group. CCQ scores did not indicate any significant difference between acceptable-range and high-range groups, except in the CCQ mental state domain (p = 0.02). On the other hand, there was a statistically significant difference between low-range BMI and acceptable-range BMI groups for CCQ total (p = 0.01), CCQ symptom (p = 0.01), CCQ mental state (p = 0.04) except CCQ functional state. Table 2 Characteristics and results of 120 patients in subgroups by BMI BMI <= 21 BMI <= 28 BMI >28 N 15 66 39 Males (%) 60.0 78.8 66.7 Age (yr) 71 abc (42–86) 72 abc (41–86) 71 abc (50–82) BMI (kg/m 2 ) 19.7 (16.2–20.8) 25.0 (21.3–27.8) 29.9 (28.0–37.8) FEV 1 /FVC (%) 39.0 abc (21.1–64.8) 49.3 abc (23.6–68.0) 50.3 abc (27.5–68.2) FEV 1 (% predicted) 43.5 abc (18.9–68.1) 44.5 abc (19.5–117.1) 40.8 abc (16.4–85.9) MRC functional dyspnoea 1.8 ± 1.4 abc (1–4) 1.4 ± 0.4 abc (0–4) 1.7 ± 0.9 abc (0–4) CCQ symptom 2.5 (0.3–5.8) 1.3 a (0.0–4.0) 1.5 a (0.0–5.0) CCQ functional state 2.3 a (0.0–5.0) 1.3 ab (0.0–5.3) 1.9 ab (0.0–4.5) CCQ mental state 2.0 (0.0–5.5) 0.5 (0.0–6.0) 1.5 (0.0–6.0) CCQ total 2.2 (0.4–5.2) 1.2 a (0.0–4.3) 1.7 a (0.0–4.6) BMI = body mass index. FVC = forced vital capacity. FEV 1 = forced expired volume in one second. CCQ = Clinical COPD Questionnaire. MRC = Medical Research Council. Medians not sharing a common superscript (a,b,c) are significant different at p < 0.05 after Mann-Wittney U test. Convergent and divergent validity The CCQ score showed significant correlations with all SF-36 components except the pain component(Table 3 ). Table 3 Correlations between CCQ, SF-36, FEV 1 and functional dyspnoea CCQ Symptom CCQ Functional state CCQ Mental state CCQ Total SF-36 Physical functioning -0.51** -0.78** -0.45** -0.72** SF-36 Social functioning -0.36* -0.40** -0.40** -0.43** SF-36 Role physical -0.34* -0.38** -0.43** -0.43** SF-36 Role emotional -0.31* -0.30* -0.39* -0.36* SF-36 Mental health -0.35* -0.47** -0.54** -0.48** SF-36 Vitality -0.47** -0.58** -0.44** -0.57** SF-36 Pain -0.15 -0.23 -0.05 -0.20 SF-36 Health perceptions -0.56** -0.58** -0.49** -0.64** MRC functional dyspnoea +0.52** +0.64** +0.44** +0.63** FEV 1 (% predicted) -0.51** -0.50** -0.51** -0.57** SF-36 = Medical Outcome Survey Form-36 (higher score indicates better health status); FEV 1 = forced expired volume in one second; MRC = Medical Research Council functional dyspnoea; *p < 0.05; **p < 0.01, Spearman's rank correlation. The CCQ scores and the FEV 1 % predicted values correlated significantly with respect to the whole population, the highest correlation (Figure 1 ) being that of CCQ total score (rho = -0.57; p < 0.01). The correlation (rho = -0.41) was highly significant (p < 0.01) even if only the group of 120 COPD patients is considered. Figure 1 Correlation between CCQ and FEV1 %predicted in 175 subjects. CCQ = Clinical COPD Questionnaire. FEV 1 = forced expired volume in one second. The functional dyspnoea MRC score correlated strongly with CCQ total (rho = 0.63), functional state (rho = 0,64), symptom (rho = 0.52) and mental state (rho = 0.44). No significant correlation was found between BMI and all the CCQ scores. Test-Retest Reliability and Responsiveness The intra-class correlation coefficient was 0.99 for the overall CCQ score. In table 4 we see the results concerning responsiveness to change of the CCQ, as tested in 46 COPD patients undergoing pulmonary rehabilitation. The group's CCQ scores significantly (p = 0.000) improved after three weeks of pulmonary rehabilitation in hospital. A statistically significant (p = 0.000) improvement was found also for walked distance and Borg breathlessness rating at the end of 6 MWT. At the same time, no significant change was found for the FEV 1 pb %. After two successive weeks of individualized home rehabilitation there was a worsening of CCQ scores compared with the scores when hospital discharge took place. Nevertheless, CCQ scores were still significantly better than in baseline condition (hospital admission) for total (p = 0.01), functional state (p = 0.01), symptom (p = 0.02) and mental state (p = 0.03). Table 4 Changes of CCQ scores in 46 patients submitted to pulmonary rehabilitation Baseline HospitalR HomeR CCQ functional state 2.2 (0.5–5.0) 1.5 (0.0–4.7)* 1.7 (0.0–4.7)* CCQ symptom 1.8 (0.2–4.7) 1.3 (0.0–3.5)* 1.7 (0.0–4.2)* CCQ mental state 2.0 (0.5–4.0) 1.0 (0.0–3.5)* 1.5 (0.0–4.5)* CCQ total 2.0 (0.0–3.9) 1.3 (0.0–3.8)* 1.7 (0.0–4.0)* Distance_walked (m) 264 (104–380) 306 (156–459) ----- Borg end-walking 2 (1–9) 1 (0–8) ----- CCQ = Clinical COPD Questionnaire, HospitalR = end of hospital pulmonary rehabilitation, HomeR = during home rehabilitation. Borg = breathlessness rating scale. *p < 0.05 after Wilcoxon U test (HospitalR or HomeR versus Baseline) Discussion The validated Italian version of SF-36 was used as an instrument to measure the convergent validity of the clinical COPD questionnaire. Moderate to high correlations were found in the present study supporting the convergent validity in the Italian version, reflecting the original English development and validation study [ 3 ]. FEV 1 was used to measure divergent validity with the same a priori assumption behind the original English version (range from -0.20 to -0.4). The correlation was stronger than expected also in the Italian version, concerning the whole population study and the COPD population alone. In addition to the FEV 1 , also MRC functional dyspnoea has proved to be useful in predicting outcomes in patients with COPD, thus MRC functional dyspnoea measurement is recommended in the routine handling and evaluation of these patients [ 1 ]. In the present study, both MRC score and CCQ scores values were able to discriminate healthy subjects and COPD patients with different degree of airways obstruction (from mild-moderate to very severe). We had the opportunity of testing the correlation between CCQ scores and MRC score and it was statistically highly significant. We found no significant difference, as far as the CCQ functional state is concerned, between healthy subjects and mild-moderate patients with COPD. This reflects COPD guidelines [ 1 ], which state that restrictions in daily living activities only become significantly apparent once the FEV 1 falls below 50% predicted, i.e., as a result of the transition from mild-moderate to severe airways obstruction in patients with COPD. BMI calculation has also proved to be useful in the routine handling of patients with COPD [ 1 ]. In the present study, BMI does not differ significantly between healthy and diseased subjects and among groups of COPD patients with different degrees of airways obstruction. According to Celli BR et al. [ 10 ], BMI <= 21 is associated with poor prognosis in patients with COPD. Therefore, this condition can be considered an indication of less than optimal clinical control in patients with COPD. In our study, CCQ scores were able to discriminate the patients with COPD and BMI <= 21 in the COPD population. The relation between BMI and CCQ scores in our COPD population is non-linear, since scores tend to be worse with both decreasing BMI values below 22 and increasing values above 28. This trend, which is statistically significant only in the low BMI range, explains the non-significant overall correlation that was found between BMI values and CCQ scores in patients with COPD. Only the CCQ mental state score is significantly worse in the overweight group, compared with the acceptable BMI range group. This would suggest the presence in these subjects of emotional problems, possibly related also to overfeeding. We have been able, by means of the CCQ scores, to detect significant changes in response to the inpatient portion of a comprehensive and continuous standard pulmonary rehabilitation program for patients with COPD. Disease control improvement is also documented with independent outcome measurements of variables at the end of 6 MWT. It is a well-known fact that improvements in clinical disease control and health status occur with pulmonary rehabilitation, despite a minimal effect on pulmonary function measurement, i.e., FEV1 % predicted [ 1 , 7 , 11 ]. The present study wishes to validate the Italian language version of the CCQ questionnaire; it does not intend to validate the optimal duration of a time-limited pulmonary rehab program. The GOLD guidelines [ 2 ] state that there is type B scientific evidence for two-month duration of a time-limited pulmonary rehab program in patients with COPD. In our clinical practice, we have never succeeded in obtaining the compliance of patients with stable COPD over such a long pulmonary rehab hospitalization period. The comparison of our data with the results presented in the original CCQ article [ 3 ] show similar CCQ scores as far as the healthy subjects group is concerned (total score < 1). A separate comparison for severe and very severe groups of patients with COPD was impossible since the original CCQ article [ 3 ] presents data in these patients, grouped according to the classification criteria available in January 2003. Indeed, the classification of patients into different groups has been changed from one based upon the relation between airways obstruction and clinical features (respiratory failure or clinical signs of heart failure) [ 12 ] into another based upon airways obstruction alone [ 1 , 2 ]. However, we excluded from the study the patients with signs of heart failure or acute respiratory failure. In our study, a separate comparison between mild and moderate COPD was impossible, since patients with mild COPD seldom refer to our specialized outpatient clinic. Furthermore, in our clinical setting, we have been unable to find any subject presenting symptoms of COPD in the absence of airways obstruction (subjects who risk developing COPD). We believe such patients are more typical in a general practice setting, as is the case in the original CCQ development and validation study [ 3 ]. Conclusions The clinical COPD questionnaire is the first to have been specifically developed and validated to measure clinical control in patients with COPD in general practice [ 3 ]. The validation of the questionnaire, in Italian and in specific pulmonary disease clinical practice, confirms strong discriminative properties, test-retest reliability and responsiveness. Furthermore, the CCQ scores are highly correlated with the usual functional dyspnoea MRC scale and are able to discriminate COPD patients with already known poor prognosis according to the critical BMI index. Authors' contributions SD designed the study, analyzed the results, performed the statistical analysis and drafted the manuscript. SP participated to the study design and organization, collected and elaborated the SF-36 data and helped to draft the manuscript. CB-VF-CR-RR-FR participated in the organization of the study, in the individual subjects clinical selection and in the results discussion. All Authors read and approved the final manuscript.

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Microarray analysis of gene expression profiles of cardiac myocytes and fibroblasts after mechanical stress, ionising or ultraviolet radiation

Background During excessive pressure or volume overload, cardiac cells are subjected to increased mechanical stress (MS). We set out to investigate how the stress response of cardiac cells to MS can be compared to genotoxic stresses induced by DNA damaging agents. We chose for this purpose to use ionising radiation (IR), which during mediastinal radiotherapy can result in cardiac tissue remodelling and diminished heart function, and ultraviolet radiation (UV) that in contrast to IR induces high concentrations of DNA replication- and transcription-blocking lesions. Results Cultures enriched for neonatal rat cardiac myocytes (CM) or fibroblasts were subjected to any one of the three stressors. Affymetrix microarrays, analysed with Linear Modelling on Probe Level, were used to determine gene expression patterns at 24 hours after (the start of) treatment. The numbers of differentially expressed genes after UV were considerably higher than after IR or MS. Remarkably, after all three stressors the predominant gene expression response in CM-enriched fractions was up-regulation, while in fibroblasts genes were more frequently down-regulated. To investigate the activation or repression of specific cellular pathways, genes present on the array were assigned to 25 groups, based on their biological function. As an example, in the group of cholesterol biosynthesis a significant proportion of genes was up-regulated in CM-enriched fractions after MS, but down-regulated after IR or UV. Conclusion Gene expression responses after the types of cellular stress investigated (MS, IR or UV) have a high stressor and cell type specificity.

Background The mammalian myocardium contains several cell types, of which the cardiac myocytes (CM) make up most of the heart's mass. Although a small proportion of CM in the adult myocardium remains mitotic, most CM lose the capacity to undergo cell division shortly after birth [ 1 ]. In the adult heart, approximately 70% of the cells is represented by non-myocytes, most of which belong to the fibroblast compartment. In this study, we investigate how the stress response of cardiac cells to increased mechanical stress (MS) can be compared to genotoxic stresses induced by two DNA damaging agents, ionising radiation (IR) and ultraviolet radiation (UV). In cardiac cells, MS is increased during excessive pressure or volume load of the heart, as seen in hypertensive and valvular heart disease. This results in an adaptive growth response leading to structural and functional cardiac changes, including CM hypertrophy and hyperplasia of fibroblasts, to compensate for the increased workload [ 2 ]. In vitro cyclic stretch of rat cardiac cells has been shown to be an appropriate model for cellular changes that occur during overload of cardiac muscle in vivo [ 3 ]. Mechanical signals may be transferred to the nucleus of cells through integrin receptors, cytoskeletal filaments and nuclear scaffolds [ 4 ] and through ion channels, ion exchangers and hormone receptors [ 5 ]. Radiation induced heart disease (RIHD) has been recognised as a late adverse effect of thoracic radiotherapy if the heart was situated in the radiation field [ 6 ]. IR induces the formation of reactive oxygen species that react with different components of the cell, thereby inducing macromolecular lesions. IR can activate several signal transduction pathways, involving growth factor receptors, death receptors and DNA damage sensing proteins [ 7 ]. Primary fibroblasts in culture are known to go into senescence shortly after IR [ 8 ], after which terminal differentiation of these cells is induced [ 9 ]. Cultures of CM do not demonstrate cell death, nor a loss of function upon a single dose of 10,000 rad (~100 Gy) [ 10 , 11 ]. The density of DNA damaging events after UVC, which include helix-distorting photolesions, is three orders of magnitude higher than the density of DNA damage that occurs after IR [ 12 ] and sufficient to block cellular DNA replication and transcription. Signal transduction after UV is mediated via components of the cellular membrane, involving growth factor receptors, and via DNA damage sensing proteins [ 7 ]. UV is known to induce cell cycle arrest and apoptosis in several cell types [ 13 , 14 ]. The aim of the study was to identify and compare differentially expressed genes (up-regulated or down-regulated when compared with untreated controls) in cardiac cells in response to MS, IR or UV. To this purpose, cultures enriched for ventricular CM or fibroblasts were exposed to one of the three stressors. Differentially expressed genes were identified using Affymetrix GeneChips. Several statistical methods have been developed to analyse Affymetrix gene expression microarrays. We used a method based on Linear Modelling on Probe Level [ 15 ] to describe the signal of every perfect match (PM) probe. Because overall changes in the expression of functionally related genes are more informative than the expression pattern of single genes, genes in microarray studies can be assigned to functional groups [ 16 ]. In the present study, such an approach was used to classify genes, based on biological function or on the role of a gene product in common intracellular pathways. Results Accuracy of the linear model As an example for the accuracy of the linear model that was used to describe the PM probe signals, Figure 1A shows a dot plot of all PM probe signals as calculated by the linear model, against the actual PM probe signals determined from fibroblasts after UV. These data were used to calculate correlation coefficients (R 2 ) between the signals calculated by the model and the actual PM signals obtained. Figure 1B shows the distribution of R 2 values for fibroblasts after UV. The majority of probe-sets have a correlation coefficient ≥ 0.90, indicating that the model used fitted the data accurately. Figure 1 Accuracy of the linear model . Dot plot of all PM probe signals as calculated by the linear model, against actual PM probe signals determined from fibroblasts after UV (A). The data presented in Figure 1A were used to calculate correlation coefficients (R 2 ) between the signals calculated by the linear model and the actual PM signals of fibroblasts after UV (B). Numbers of differentially expressed genes A Series entry (accession number GSE2032) at Gene Expression Omnibus (GEO), a public gene expression database of NCBI [ 17 ], gives access to all microarray data generated in this study. Figure 2 represents the numbers of genes with a unique LocusLink ID that were up-regulated or down-regulated (q < 0.005) in CM-enriched cultures/fractions and cultures of fibroblasts after one of the three stressors. When using these criteria, the numbers of differentially expressed genes (up-regulated or down-regulated) after UV were considerably higher than after IR or MS. After each of the three stressors more genes were up-regulated in CM-enriched cultures/fractions than in cultures of fibroblasts. Conversely, higher numbers of down-regulated genes were determined in fibroblasts. These differences were most pronounced after MS (Figure 2A ). Figure 2 Numbers of differentially expressed genes . Numbers of differentially expressed genes (q < 0.005) with a unique LocusLink ID in cultures of fibroblasts (dotted) and CM-enriched cultures after MS (A), in cultures of fibroblasts (dotted) and CM-enriched fractions after IR (B), or in cultures of fibroblasts (dotted) and CM-enriched fractions after UV (C). Overlapping parts of the circles represent genes that show differential expression both in CM-enriched cultures/fractions and cultures of fibroblasts. Based on information available at NettAffx™ [ 18 ], extended with standard textbooks and recent literature, genes with a unique LocusLink ID were assigned to several functional groups. Subsequently, the status of each gene within a functional group was determined in both cell populations (CM-enriched cultures/fractions and cultures of fibroblasts). Individual probe-sets within these functional groups and their q-value after the three stressors are listed in table 1 (see additional file 1 ). In this table, down-regulated genes are distinguished from up-regulated genes by a minus-sign in front of their q-value. Figure 3 shows the percentage of genes in a functional group that are differentially expressed after MS, IR or UV. In accordance with Figure 2 , the highest percentages of genes were differentially expressed after UV (on average 39.4% for both cell populations), followed by IR (13.0%). In general, the percentages of differentially expressed genes were lowest after MS (8.3%). Several functional groups, including heat shock proteins and genes involved in cholesterol biosynthesis, showed high proportions of differentially expressed genes with a hypergeometric probability P < 0.005. These functional groups were considered to have significantly high percentages of differentially expressed genes. On the other hand, in the group of genes encoding for ion channels and exchangers, low percentages of differentially expressed genes with a hypergeometric probability P < 0.005 were determined, both after IR and UV. Figure 3 Percentages of differentially expressed genes . Percentage of total number of genes within functional groups that are differentially expressed in CM-enriched cultures/fractions and cultures of fibroblasts after MS, IR or UV. Numbers between brackets represent total numbers of genes within a functional group. For example, of the 22 MAPkinases and phosphatases found to be represented by the array, 27% were differentially expressed in CM-enriched fractions after UV. AA: amino acid. *Hypergeometric probability P < 0.005 Percentages of up-regulated genes Figure 4 shows the percentages of differentially expressed genes that were up-regulated after IR or after UV. In several functional groups, including p53 target genes and genes involved in mitosis, a significant percentage of differentially expressed genes was up-regulated (hypergeometric probability P < 0.005). Other functional groups, including cytoskeletal components and genes involved in cholesterol biosynthesis mainly had down-regulated genes. In all 25 functional groups, the hypergeometric probability P of the percentage of up-regulated genes after MS was not below the pre-set threshold of 0.005. Therefore, no significant percentages of up-regulated genes were determined in any of the functional groups after MS (data not shown). Figure 4 Percentages of up-regulated genes . Percentage of changed genes that were up-regulated per functional group after IR or UV. Numbers between brackets represent numbers of differentially expressed genes in CM-enriched fractions and cultures of fibroblasts, respectively. For example, of the 8 MAPkinases and phosphatases that were differentially expressed in CM-enriched fractions after UV, 63% were up-regulated. *Hypergeometric probability P < 0.005 General stress response genes Probe-sets that showed an up-regulation or down-regulation after more than one stressor are listed in table 2 (see additional file 2 ). The overlap in responsive genes between IR and UV was larger than the overlap between MS and one of the radiation types. Both after IR and UV, several genes that are known to play a central role in the radiation response of cells, including p21, GADD153 and mdm2, were up-regulated. These genes were not up-regulated after MS. A striking large proportion of genes encoding cytoskeletal components were down-regulated both after IR and UV. Validation of microarray results by semi-quantitative PCR Gene expression changes detected using microarrays were validated by semi-quantitative PCR, using RNA from CM-enriched cultures at 24 hours after MS. The increased gene expression of Tenascin C and biglycan were confirmed with PCR in two independent experiments. In these two experiments, Tenascin C gene expression increased 1.59 and 1.64 times, respectively. Biglycan gene expression increased 1.42 and 1.25 times, respectively. Figure 5 shows a representative result of the Tenascin C PCR. Figure 5 Representative result of the Tenascin C PCR Total RNA was isolated from CM-enriched cultures at 24 hours after MS or control treatment. After cDNA synthesis, semi-quantitative PCR was used to determine Tenascin C gene expression. Lane 1: smart ladder; lane 2: negative control; lane 3: positive control; lanes 4 and 5: CM-enriched after control treatment; lanes 6 and 7: CM-enriched after MS. Discussion In this study, a linear model was used to describe GeneChip PM probe signals and to determine effects of three types of stressors on gene expression in two neonatal rat heart cell populations, consisting of CM that are known to be terminally differentiated cells and fibroblasts that still have the capacity to undergo mitosis. Several studies have shown a good correlation between Affymetrix GeneChip data and RT-PCR [ 16 ] or Northern-blot [ 19 , 20 ]. In a previous study neonatal rat CM-enriched cultures and cultures of neonatal rat cardiac fibroblasts were irradiated with a single dose of 8.5 Gy and some mRNA transcripts were quantified by competitive PCR [ 21 ]. In accordance with the present study, no significant changes in gene expression of transforming growth factor-β1 (TGF-β1), fibroblast growth factor-2 (FGF-2) and collagen type I were determined at 24 h after IR in cultures of cardiac fibroblasts. Moreover, no significant IR-induced changes were determined in gene expression of atrial natriuretic peptide (ANP) in CM-enriched cell populations in both the latter and the present study. On the other hand, CM-enriched cultures showed a reduced TGF-β1 expression (by PCR) at 24 h after 8.5 Gy, which was not observed in the present study. This might be due to differences in experimental design between the two studies, as in the former study CM-enriched cultures were obtained by incubation with bromodeoxyuridine to prevent fibroblast proliferation. Also, during and after irradiation, the cells were incubated in higher serum concentration than used in the present study. Here, differences between the two cell populations are observed in the predominant type of gene expression response, i.e. up-regulation versus down-regulation. After all three stressors, differentially expressed genes were mostly up-regulated (q < 0.005) in CM-enriched fractions, while in cultures of fibroblasts the majority of changed genes were down-regulated. After MS, these differences were most pronounced. Paracrine signalling is involved in the response of CM and cardiac fibroblasts in co-cultures subjected to MS [ 22 ]. In the CM-enriched cultures used in this study, remaining fibroblasts might stimulate gene transcription of the CM, resulting in higher numbers of up-regulated genes. It cannot be excluded that differences in level of toxicity between the three stressors applied in this study caused differences in gene expression levels. Of the three stressors examined in this study, both IR and UV are known to induce oxidative stress. Accordingly, both stressors induced high numbers of up-regulated genes involved in anti-oxidative processes. The high percentages of up-regulated genes encoding heat shock proteins in both cell populations after IR and UV might indicate oxidative stress induced protein damage in these cells. In comparison, after MS only few genes encoding heat shock proteins were up-regulated in either cell population. Heinloth et al. (2003) proposed a model for the regulation of several gene expression patterns after IR and UV in human dermal fibroblasts, based on microarray analysis. The general view that p53 plays a central role in signal transduction after IR and UV was confirmed in their study. Moreover, IR down-regulated the expression of genes involved in mitosis. UV, on the other hand, induced the expression of genes involved in protein degradation and the MAPK pathway [ 23 ]. The latter data are in accordance with the data of the present study, showing that UV did affect genes participating in the MAPK pathway (although not significantly) in both cell populations, but IR did not. Moreover, in CM-enriched fractions, IR resulted in a down-regulation of a large percentage of genes involved in mitosis. Several genes, involved in cell cycle regulation and mitosis are expressed in foetal cardiac myocytes and down-regulated in adult myocytes, in accordance with their terminal differentiation [ 24 , 25 ]. Due to the close relation between foetal and neonatal cells, an expression of mitotic genes in the neonatal CM used in this study can be expected. The high numbers of up-regulated genes involved in ubiquitination and protein degradation in both cell populations after UV are also in accordance with the study of Heinloth et al. (2003) and with other studies on cultured cells after UV [ 20 ]. These results might reflect the need of cells to replace molecules that were damaged by UV irradiation, although the proteasome is also proposed to play a role in several cellular processes, including DNA-repair, cell cycle regulation and cell survival after irradiation [ 26 ]. In CM-enriched cultures, MS led to a relatively high proportion of up-regulated genes that are involved in cholesterol biosynthesis. Among these genes, expression of 3-hydroxy-3-methylglutaryl-Coenzyme A reductase, which forms the starting enzyme of the mevalonate pathway and is considered to be the key enzyme in cholesterol biosynthesis, was up-regulated. This suggests that in neonatal rat cardiac myocytes cholesterol biosynthesis is stimulated after MS. Neonatal rat heart myocytes that undergo hypertrophy in culture show an increased biosynthesis and intracellular accumulation of cholesterol [ 27 ]. Moreover, the mevalonate pathway has been proposed to play a role in Ras activation in neonatal rat cardiac myocytes subjected to MS in culture, leading to hypertrophy [ 28 ]. In vivo hypertrophy of the heart is also associated with elevated myocardial cholesterol contents [ 29 ]. An increased cholesterol biosynthesis in cardiac myocytes that undergo MS might therefore accompany a hypertrophic response of these cells. However, of the three foetal genes that are known to be re-expressed in hypertrophic myocytes, i.e. smooth muscle alpha-actin, ANP and beta-myosin heavy chain, only the last gene was up-regulated at the time point of investigation. In contrast to MS, IR and UV led to a down-regulation of genes involved in cholesterol biosynthesis in CM-enriched fractions. In previous studies, alterations in cholesterol contents of cardiac myocytes and fibroblasts were associated with alterations in protein to DNA ratios, levels of several enzymes including ATPases and phosphatases, and diffusion rates of membrane proteins [ 30 - 32 ]. Moreover, a decrease in beating rate observed in aging cultures of CM was opposed by increased membrane amounts of cholesterol [ 33 ]. The role of cholesterol biosynthesis in the cellular functions of cardiac cells after MS, IR or UV needs further investigation. Higher numbers of differentially expressed genes involved in ECM formation, including genes encoding collagens, fibronectin and laminin, were determined in CM-enriched cultures after MS than in cultures of fibroblasts. As mentioned before, paracrine signalling between CM and remaining fibroblasts might play a role in cellular responses in these CM-enriched cultures. Alterations in expression of genes involved in ECM formation might originate from remaining fibroblasts after stimulation by CM. Interestingly, MS does not affect the expression of these genes in cultures of fibroblasts, which suggests that paracrine signalling from CM is necessary for alterations in expression profiles of genes involved in ECM formation in fibroblasts. The down-regulated genes encoding cytoskeletal components in cultures of fibroblasts after IR and UV, including myosin and troponin, are mostly CM-specific. Therefore, these genes are likely to originate from remaining CM in the fibroblast cultures, although their numbers were low (3–5%). The extremely low numbers of differentially expressed genes encoding for ion channels and exchangers might be explained by a low number of cardiac cell type-specific genes within this functional group. Conclusions MS, IR and UV mainly induce stress-specific and cell-type specific gene expression profiles in neonatal rat CM-enriched cultures and cultures of neonatal rat heart fibroblasts. Functional groups that show significant percentages of differentially expressed genes suggest that certain cellular pathways are activated after one or more stresses. Methods Cell culturing The experiments were performed with permission of the local committee on animal experiments, installed by the University of Leiden according to the Dutch law. Cardiac cells were isolated from ventricles of neonatal rat hearts, and cultured as described before [ 14 , 34 ]. By applying a pre-plating method, cultures enriched for CM and cultures of fibroblasts were obtained. After 2 days of culturing with 5% horse serum (HS), culture media of CM-enriched cultures were replaced by media containing 2.5% HS. One day later, these cultures were subjected to UV, IR or MS. Three days after isolation, cultures of fibroblasts were subcultured for 6 days in medium containing 10% foetal bovine serum (FBS). Then, culture medium was replaced by medium containing 2.5% FBS. One day later, confluent cell cultures were subjected to UV, IR or MS. Irradiation and cyclic stretch Cells were subjected to a single dose of 8.5 Gy of X-rays at room temperature, using a 6 MV accelerator (SL 75-5 Philips), operated at a dose rate of 8 Gy min -1 . During irradiation, sham-irradiated control cells were kept at room temperature. After irradiation, cell cultures were maintained at 37°C for 24 h. In another experiment cells were irradiated with 10 J/m 2 UVC at room temperature at a dose rate of 0.2 J/m 2 per s. Before irradiation, medium was collected and cells were rinsed with PBS. Following irradiation, growth medium was returned to the cultures and the cells were incubated for an additional 24 h. Control cells received a similar treatment except for UV irradiation. To subject cells to cyclic stretch, CM-enriched cells (54 ± 5% CM) and fibroblasts (95 ± 2% non-myocytes) were cultured in 6-well Flex I culture plates (Flexcell, Hillsborough, NC, USA), coated with collagen I. Medium was changed to medium containing 2.5% serum and after 24 h plates were placed in the Flexercell Strain Unit FX-2000 ® (Flexcell) in which the frequency and magnitude of stretch were regulated by a computer-controlled vacuum pump. The apparatus applied an equiaxial cyclic stretch of 20% elongation to the wells at a frequency of 60 cycles/min (1 Hz). Stretch was applied for 24 h. Control cells were grown in identical culture plates and incubated in the same incubator as the stretched cultures, but were not mounted in the Flexercell Strain Unit. Cell harvesting after irradiation Twenty-four hours after IR or UV, non-irradiated and irradiated CM-enriched cultures were trypsinised and subjected to centrifugal elutriation [ 35 ]. The proportion of CM in each elutriation fraction was determined by flow cytometric analysis of myosin expression, as described before [ 35 ]. After elutriation of IR-exposed cultures, CM-enriched fractions contained 74 ± 3% CM and after elutriation of UV-exposed cultures, CM-enriched fractions contained 85 ± 3% CM. Because of the high purity of the fibroblast cultures (95 ± 2% non-myocytes), no centrifugal elutriation was applied on these cells. CM-enriched fractions and cultures of fibroblasts were used for RNA isolation. Cell harvesting after MS After undergoing MS or control treatment for 24 h, cells were collected from CM-enriched cultures and from cultures of fibroblasts by trypsinisation. The proportion of CM in the cell cultures was determined by flow cytometric analysis of myosin expression as described before [ 35 ]. CM-enriched cell cultures, containing 54 ± 5% CM, and fibroblast cultures, containing 95 ± 2% non-myocytes, were used for RNA isolation. RNA isolation and labelling RNA was isolated applying an RNeasy ® kit (Qiagen GmbH, Hilden, Germany), according to the manufacturer's instructions. Ten to 14 μg of total RNA from CM-enriched fractions and 7.5 to 14 μg of total RNA from fibroblast cultures was used for labelling. Per experiment, the quantities of total RNA from irradiated and control cells were equal. cDNA was synthesised using the Gibco BRL Superscript system (Invitrogen, Carlsbad CA, USA). Briefly, single stranded cDNA was synthesised using Superscript II reverse transcriptase and T7-oligo(dT)24 primers at 42°C for 1 h. Double stranded cDNA was obtained by using DNA ligase, DNA polymerase I and RNAse H at 16°C for 2 h, followed by T4 DNA polymerase at 16°C for 5 min. After clean up with a phase lock gel (Qiagen), ds-cDNA was used for in vitro transcription (IVT). cDNA was transcribed using the BioArray HighYield ® RNA transcript labelling kit (Enzo Lifesciences, Pharmingdale NY, USA) in the presence of biotin-labelled ribonucleotides, or using the MEGAScript T7 ® kit (Ambion, Austin TX, USA), in the presence of biotin-labelled CTP and UTP. In each experiment, cDNAs from control cells and stressed cells were labelled simultaneously using the same labelling kit. After clean up with a RNeasy kit (Qiagen), the biotin-labelled IVT-RNA was fragmented in a buffer containing 40 mM Tris-acetate (pH 8.1), 100 mM potassium-acetate and 30 mM magnesium-acetate, at 94°C for 35 min. Hybridisation of IVT-RNA RG-U34A arrays (Affymetrix, Santa Clara CA, USA) were used, representing ~7000 transcripts, of which 6399 had a unique LocusLink identification number (ID) at the time of data analysis. Biotin-labelled IVT-RNA was hybridised to the arrays at 45°C for 16 h according to the manufacturer's instructions. After hybridisation, the arrays were washed in a GeneChip Fluidics Station 400 with a non-stringent wash buffer at 25°C followed by a stringent wash buffer at 50°C. After washing, the arrays were stained with a streptavidin-phycoerythrin complex. After staining, intensities were determined with a GeneChip scanner, controlled by GeneChip software (Affymetrix). The intensities were background corrected using gcrma [ 36 ] and normalized at the probe level by VSN [ 37 ]. Data analysis For each stressor, three independent experiments were performed. To describe the signal of every PM probe, the following linear model was used: signal ~P + T + E + TE, based on a method described before [ 15 ]. In our model, the symbols P, T, E and TE represent the effects of probe, treatment, experiment per stressor (1, 2, or 3) and the interaction between treatment and experiment, respectively. Subsequently, analysis of variance was applied on the treatment effect to determine the p-value for each probe-set. The p-values were corrected for multiple testing using the Benjamini Hochberg step-up procedure [ 38 ] which yielded q-values for the false discovery rates (FDR). The FDR level of control was set to 0.005, equivalent to selecting genes with a q-value<0.005 (keeping up- and down-regulated genes separate by the sign of the treatment coefficient). Some genes are represented by more than one probe-set. A gene was determined to be differentially expressed when at least 50% of the probe-sets representing this gene showed significant up-regulation or down-regulation. To determine significant proportions of differentially expressed genes within functional groups, the hypergeometric probability P was calculated. P < 0.005 was considered significant. To determine the accuracy of the linear model that was used to describe PM signals, R 2 was calculated for every probe-set, using the following standard formula: R 2 = 1-ΣR i 2 /Σ(signal i -mean signal) 2 , where R i = observed-fitted value for signal i and mean signal = the mean of observed signal i . To compare data on differentially expressed genes with microarray data in literature on species other than rat, RESOURCERER of the Institute of Genomic Research [ 39 ] was used. RNA isolation and semi-quantitative PCR Total RNA isolation, cDNA synthesis and semi-quantitative PCR were performed as described before [ 40 ]. In short, total RNA was isolated using an RNeasy ® kit (Qiagen). Following DNAse (Amersham Pharmacia Biotech, Uppsala, Sweden) treatment, cDNA was synthesised using M-MLV reverse transcriptase (Life Technologies, Rockville, MD, USA) and oligo(dT) primers (Amersham). Semi-quantitative PCR was performed, using the following primers and annealing temperatures: Tenascin C sense: CGA CAG TTT TGT TAT CAG GAT CAG, Tenascin C antisense: GGC ACA TAA GTA ATC CGG AAA T, 60°C; Biglycan sense: CAA CAA CCC TGT GCC CTA CT, Biglycan antisense: GGT GT GCT TCT TTG CTT CC, 65°C. A competitive PCR was performed on GAPDH to correct for differences in cDNA concentrations. After agarose gel electrophoresis, intensities of PCR product bands were determined by Scion image analysis software (Scion Corporation, Frederick, MD, USA). Authors' contributions MB performed experiments, developed and analyzed functional groups of genes and prepared the manuscript. CGCW performed experiments, developed and analyzed functional groups of genes and participated in discussions. HV and AL participated in discussions and gave textual advice. PS performed microarray normalization and data analysis. JW and LHFM participated in discussions. AAZ participated in discussions, suggested the assignment of genes to functional groups and gave textual advice. All authors read and approved the final manuscript. Supplementary Material Additional File 1 q-values of genes within functional groups Table 1. Excel-file containing the 25 functional groups of genes used in this study. Of every gene, Affymetrix probe-set IDs and q-values after the three types of stress are listed. Down-regulated genes are represented by a minus-sign in front of their q-value. q-values < 0.005 are marked red (in case of up-regulation) and green (in case of down-regulation). Click here for file Additional File 2 General stress response genes Table 2. Excel file containing Affymetrix probe-set IDs, LocusLink ID and gene description of all probe-sets that showed an up-regulation or down-regulation after two or more stresses. Click here for file

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534786

The Menopause Rating Scale (MRS) as outcome measure for hormone treatment? A validation study

Background The Menopause Rating Scale is a health-related Quality of Life scale developed in the early 1990s and step-by-step validated since then. No methodologically detailed work on the utility of the scale to assess health-related changes after treatment was published before. Method We analysed an open, uncontrolled post-marketing study with over 9000 women with pre- and post-treatment data of the MRS scale to critically evaluate the capacity of the scale to measure the health-related effects of hormone treatment independent from the severity of complaints at baseline. Results The improvement of complaints during treatment relative to the baseline score was 36% in average. Patients with little/no complaints before therapy improved by 11%, those with mild complaints at entry by 32%, with moderate by 44%, and with severe symptoms by 55% – compared with the baseline score. We showed that the distribution of complaints in women before therapy returned to norm values after 6 months of hormone treatment. We also provided weak evidence that the MRS results may well predict the assessment of the treating physician. Limitations of the study, however, may have lead to overestimating the utility of the MRS scale as outcome measure. Conclusion The MRS scale showed some evidence for its ability to measure treatment effects on quality of life across the full range of severity of complaints in aging women. This however needs confirmation in other and better-designed clinical/outcome studies.

Background The Menopause Rating Scale (MRS) was initially developed in the early 1990s [ 1 , 2 ] to measure the severity of age-/menopause-related complaints by rating a profile of symptoms. The validation of the MRS began some years ago [ 2 - 6 ] with the objectives (1) to enable comparisons of the symptoms of aging between groups of women under different conditions, (2) to compare severity of symptoms over time, and (3) to measure changes pre- and post-treatment [ 4 - 6 ]. Development and standardization of the scale were published elsewhere [ 2 ]. In brief, the standardization of this scale was performed on the basis of a representative sample of 500 German women aged 45–60 years in 1996. A factorial analysis was applied to establish the raw scale of complaints or symptoms. Statistical methods were used to identify the dimensions of the scale. Finally, three dimensions of symptoms/complaints were identified: a psychological, a somatic-vegetative, and a urogenital factor that explained 59 % of the total variance [ 2 ]. This is indicative for a high efficiency of a scale with only 11 items – compared to other international scales. Reference values for the severity of symptoms or complaints were calculated based on a population sample [ 2 ]. The scale consisting of 11 items is self-completed by the woman. A 5-point rating scale permits to describe the perceived severity of complaints of each item (severity 0 [no complaints]...4 scoring points [very severe symptoms]) by checking the appropriate box. The composite scores for each of the dimensions (sub-scales) are based on adding up the scores of the items of the respective dimensions. The composite score (total score) is the sum of the dimension scores. Details as how to apply and evaluate the scale were published [ 8 , 9 ] and can be also obtained from the website . The scale was defined as a menopause-specifc, health-related quality of life scale (HRQoL), because the profil of complaints in this scale importantly determines the HRQoL of women in this age span. Moreover, a good correlation between the results obtained with the MRS scale and the generic QoL scale was observed [ 6 ]. The MRS scale became internationally well accepted as far as the usage many countries is concerned. The first translation was into English [ 7 ]. Other translations followed [ 8 ], i.e. taking international methodological recommendations [ 10 - 12 ] into consideration. Currently, the following versions are available: Brazilian, English, French, German, Indonesian, Italian, Mexican/Argentine, Spanish, Swedish, and Turkish language. These versions are available in a published form, and can be downloaded in PDF-format from the internet (see reference 8 and ). Like in other health-related QoL scales, it is a challenge to satisfy the demands of a clinical utility and outcomes sensitivity. A comprehensive overview regarding conventional psychometric requirements of test reliability and validity were recently published elsewhere [ 9 ]. It is the aim of this paper is to share methodological information about the capacity of the scale to assess changes after hormone treatment since no methodologically detailed work in this regard was published before. Methods A multicenter, open post-marketing study was conducted with a product for hormone therapy (CLIMEN ® = 2 mg estradiol valerate/2 mg estradiol valerate + 1 mg cyproterone acetate) using the MRS scale as outcome measure under routine conditions of office-based gynaecologists. The study was described in detail elsewhere [ 6 ]. In brief, 1801 gynaecologists from all parts of Germany participated in the study on a voluntary basis. 10,904 women who required hormone treatment were included. The median age was 49 years. Beside others, the MRS scale was documented before therapy and 6 months after starting the hormone treatment. A specific problem was the transformation of an older MRS version into the advanced, relatively broad validated current version of MRS. The old version of the MRS was read by the physician and the patient answered to which extend she perceived suffering from a specific symptom, and if yes to which extend. The new scale is self-completed by the woman without interaction with the physician. The symptoms itself are the same in both scales. Nevertheless, this is a methodological limitation. We, however, are not interested in the absolute score values but relative changes after treatment compared to before. In addition, the scoring system of the old version was adjusted into the new coding system using a linear transformation. Additionally, one question of the old version was split into two questions – as recommended for the current version of the MRS (see later discussion on limitations of the study). The statistical analyses were performed with the commercial statistical package SAS 8.2. Results Altogether, data of 9311 women were available for most of our analysis. However, the sample size varied slightly depending on the variables used because we had also missing information in a few variables. The mean age was 49.8 years (SD 6.4). About half of the participating women were still perimenopausal (51.9%) or were already in the postmenopausal phase (48.1%). The mean body mass index was not eye-catching with 24.7 (SD 3.7). The improvement of the health-related quality of life (HRQoL) – measured with the MRS scale – is described in Table 1 . The means and SD of the scoring points of the total scale (and the three subscales) can be seen at baseline (before therapy) and after six months of hormone treatment. Significant declines of the mean scores were observed after treatment indicating an improvement of HRQoL altogether and in the three subscales of the MRS. Table 1 Means (SD) of MRS scores at baseline (before therapy) and at end of observation (after therapy. Improvement of scores after therapy by absolute difference in scoring points. § Total scale and for each subscale. n Scores before Scores after Absolute change Percent (%) change P** Total scale 9311 11.0 (8.2) 1.7 (3.2) 9.3 (7.4) 36.1 (20.6) <0.0001 Psychological subscale 9311 4.5 (4.1) 0.7 (1.7) 3.8 (3.7) 34.5 (27.1) <0.0001 Somatic subscale 9311 4.2 (3.2) 0.5 (1.2) 3.6 (3.0) 37.3 (23.1) <0.0001 Urogenital subscale 9311 2.3 (2.6) 0.5 (1.1) 1.8 (2.3) 24.5 (25.3) <0.0001 § Summary score "before therapy" minus "after therapy" * Percent (%) change compared with the change before treatment: pre-treatment score minus post-treatment divided by pre-treatment score multiplied by 100 (%) ** Paired t-test for dependent samples: significance of the absolute difference Apart from the comparison of means, we calculated the relative improvement compared with the situation before therapy (baseline) to better understand the magnitude of change after therapy (Table 1 ), i.e. in absolute and relative terms. There was not much difference in relative improvement (%) among subscales (all highly significant): In average, the scores improved by one third after six months hormone treatment. The scale is able to measure an improvement in patients starting with "no/little complaints" (total score = 0–4), "mild" (5–8), "moderate"(9–15), and "severe" (16 + points) before therapy (= baseline). This is presented in Table 2 : The more severe the complaints were before treatment the better the effect regarding relative improvement of symptoms measured by the MRS, which gives evidence for the clinical utility of the MRS as outcome measure. Table 2 Relative change of MRS scoring points as percent of the baseline total score: Mean values (SD) of the relative change (% improvement of the complaints) in four categories of severity at baseline. Severity of complaints at baseline No/little (0–4) Mild (5–8) Moderate (9–15) Severe (16+) Means (SD) (n = 2460) Means (SD) (n = 1693) Means (SD) (n = 2592) Means (SD) (n = 2566) Total score 10.8 (10.6) 32.2 (9.8) 43.9 (11.8) 55.1 (13.8) Psychological score 6.0 (14.7) 27.6 (21.5) 43.7 (20.6) 57.1 (17.9) Somatic score 13.8 (17.3) 34.4 (18.5) 44.1 (16.9) 54.8 (15.9) Urogenital score 5.7 (13.9) 17.0 (20.6) 27.5 (23.6) 44.4 (22.6) It is interesting to compare the HRQoL before and after hormone treatment with the norm values of MRS obtained in an average population of aging women, i.e. not patients as in our post-marketing study. To this end, we compared only the MRS total scores in patients with the average female population (Table 3 ). It became evident in this crude and simple comparison, that the severely deteriorated distribution of complaints in the patient group before therapy – compared with the normal population – improved after therapy remarkable, i.e., at least as far as the total score of the MRS is concerned. The three subscales showed a similar tendency towards the better. The extremely high proportion of patients without complaints immediately after therapy could be due to a selection problem in this post-marketing study and the application of the physician-administered version of the MRS (see discussion). Table 3 Level of complaints in the population in percent (%) compared with patients of the Climen treatment study: Frequency distribution before/after therapy compared with population norm values* Frequency in patients : Percent (%)in four categories of severity Severity of complaints Population % Standard Before therapy % After therapy % Total score No or little (-4) 48 26.4 86.8 Mild (5–8) 25 18.2 8.4 Moderate (9–15) 20 27.8 4.0 Severe (16+) 8 27.6 0.8 Psychological score No or little (-1) 48 30.7 82.5 Mild (2–3) 23 17.0 10.4 Moderate (4–6) 20 22.2 5.5 Severe (7+) 9 30.1 1.6 Somatic score No or little (-2) 53 35.7 93.0 Mild (3–4) 24 22.7 5.1 Moderate (5–7) 15 25.5 1.6 Severe (8+) 8 16.1 0.3 Sexual score No or little (0) 64 37.3 76.8 Mild (1) 13 13.3 11.6 Moderate (2–3) 16 22.2 8.7 Severe (4+) 7 27.3 2.9 * The population data came from the standardization of the MRS scale [2,3] The treating gynaecologist (who also applied the MRS scale) assessed individually the efficiency of the hormone treatment in the above mentioned intervention study. The gynaecologist's expert opinion regarding treatment efficiency was categorized into two categories for the purpose of this analysis: successful (very effective and effective) and not successful (little, no, or negative effects). This alternative variable was then used for the comparison with the alternative "success-variable" based on MRS (total score only): " successful " (5 and more points reduction after therapy compared with baseline test) and " not successful " (less than 5 scoring points reduction after therapy compared with baseline test). The prediction of the expert opinion of the treating gynaecologist with the MRS data seems to be good: sensitivity (correct prediction of a positive assessment by the physician) 70.8% and specificity (correct prediction of a negative assessment by the physician) 73.5% (Table 4 ). Table 4 Prediction of a positive assessment by the physician concerning "successful treatment" by means of the MRS scale (total score)."Not successful" was defined for the MRS as: less than 5 scoring points improvement at the end of the HRT treatment compared with "before treatment". MRS: not successful MRS: successful Total Doctor: not successful 311 112 423 Doctor: successful 2570 6227 8797 Total 2881 6339 9220 Sensitivity: 70.8% Specificity: 73.5 Discussion The MRS scale was developed (a) to assess symptoms of aging/menopause (independent from those that are disease-related) or HRQoL between groups of women under different conditions, (b) to evaluate the severity of symptoms over time, and (c) to measure changes pre- and post hormone replacement therapy. The aim of this paper was to empirically demonstrate that the latter claim is evident. Reliability and validity are important to show the usefulness of the scale as a clinical utility in monitoring treatment effects – once all other methodological requirements are successfully demonstrated before. Reliability measures (internal consistency and test-retest stability) were found to be good across countries [ 9 ]. Regarding validity it was shown that the internal structure of the MRS across countries was sufficiently similar to conclude that the scale really measures the same phenomenon [ 9 ]. The comparison with another scale for aging women – although not a validated HRQoL scale (Kupperman) – showed sufficiently good correlations of the total score, which is compatible with the notion of a good criterion-oriented validity. The same is true for the comparison with the generic quality-of-life scale SF36 where also high correlation coefficients have been shown [ 3 - 5 ]. Another fact in favor of the scale is that it was translated into 10 languages so already [ 7 - 9 ]. Having the above-mentioned psychometric data available, a point was reached to critically evaluate the capacity of the scale to reliably measure health-related effects of hormone treatment independent from the severity of complaints and – in addition – to the comparison of treatment effects measured by the MRS scale and the subjective assessment by the treating physician. To this end, many clinicians use the term "validity" and mean high utility for clinical work or research. The only hormone treatment study with the MRS scale as outcome measure in women during menopausal transition we could get data for methodological analysis was the above described postmarketing study. We hope to repeat/confirm this analysis with data of a more stringently designed clinical trial. But even on the basis of a methodologically weak dataset, in absence of other data, we got re-assuring methodological information about the MRS scale. It is a well-established experience that women with menopausal complaints respond to hormone therapy with a marked improvement of the HRQoL. This is what the MRS scale should be able to detect. We saw that the increased mean MRS total score at baseline (before treatment) markedly decreased after 6 months under treatment indicating a significant improvement of complaints & HRQoL. This was also the case for the mean scores of the three subscales. These data cannot disentangle the effect of treatment and "natural variation" of complaints over time. This however was not the point: It was not the intention of this paper to evaluate effectiveness of hormone therapy in an uncontrolled post-marketing study. The absolute improvement of symptoms during treatment was 9.3 points of the MRS total score on average. This is equivalent to 36% of the baseline score, and similar also for all three subscales. In other words, the MRS scale was shown to be successful in detecting treatment effects. The impressive magnitude of the therapy-related improvement of HRQoL should be obviously discussed in the context of selection of women with complaints susceptible for this kind of treatment by the participating gynaecologists. Another critical remark is that we cannot comment as to what extend the MRS scale is able to measure true or placebo treatment effects. But this is more a question concerning efficacy and the study draw any conclusions in this regard by definition of the study design. To answer the question whether the sensitivity of the MRS scale is good enough to detect even treatment-related changes in women with only little or mild symptoms as compared with severe ones, the analysis was stratified. An improvement of complaints/QoL was seen in an increasing degree in patients with little, mild, moderate and severe symptoms at baseline. The relative improvement increased with the degree of severity of symptoms at baseline, which is consistent with the general expectation. It seems to be important to underscore: The MRS scale seems to detect also a positive treatment effect in women with little complaints – although to a lesser degree. Moreover, we showed the capacity of the MRS scale to determine therapeutic efficiency with another approach: a face-value-comparison with norm values of the population [ 2 , 3 ]. The level of complaints in patients before therapy expressed a higher degree of severity (higher MRS total score). After 6 months of hormone treatment the frequency distribution of patients with a certain severity of complaints returned towards a similar distribution as observed in the general population. The extreme proportion of patients with no/ little complaints after therapy should be again seen in the context of apparent patient selection (patients were not only treated because of their symptoms but also for other indications such as prevention) and/or effects of the interaction of patients with the treating physician (who also administered the MRS. Thus, we cannot exclude that such a biases have inflated the impression of a "too positive therapy efficiency". But we do not intent to draw conclusions about therapeutic efficiency anyway. It is another way to look at therapeutic efficiency with the assistance of the MRS scale. Although this indicates at least that comparisons with norm values could be helpful for interpreting results of intervention studies, we are not recommending formal statistical testing of differences between patient groups and the reference values of the population: Patients are usually too different from the general population, a difference hard to adjust for. It is just a visual comparison (as in Table 3 ) to get a crude idea for the interpretation of results. The MRS scale was also tested whether it predicts the therapeutic assessment of the treating physician. At face value, the individually assessed efficiency of hormone treatment by the treating gynaecologists was comparable with the assessment by the MRS scale, i.e. using a simple dichotomization of the treatment effect in " successful " and " not successful " for both the subjective opinion of the physician and the result of the MRS scale: The sensitivity (correct prediction of a positive assessment by the physician) was 70.8% and specificity (correct prediction of a negative assessment by the physician) 73.5%. In other words, the MRS scale fits well with the subjective assessment of the treatment effect estimated by the physician. However, conclusions have to be drawn very carefully because of a possibly inherent bias that may have inflated the positive result: The subjective assessment of "success" by the treating physician was obviously not as independent from the assessment by the MRS scale as desirable because the physician applied the scale to the patient. Even without being able to recall the result of the MRS six month ago or to calculate and compare the total score of both administrations, the interaction with the patients is likely to have introduced this bias in the direction of a higher compatibility between both assessments. Although the result may too positive compared with a blinded, really independent assessment, it permits to generate the working hypothesis of a sufficiently good prediction of the therapeutic effect by means of the MRS scale. This needs to be confirmed with better data, i.e. data from a blinded, independent comparison, i.e. with the currently used, self-administered MRS scale. The aim of this exercise was only to demonstrate that the MRS scale may well predict the clinical opinion about efficiency of hormone therapy, what was not empirically shown before. We recommend the MRS as standardized/validated "objective" scale for use in clinical studies, although some aspects discussed above need confirmation in a new study. Moreover, since the scale is already broadly used at the international level, it is important to sensitise users about some lacking information or weak evidence. The limitations of this study should be shortly summarized. First of all, this study was performed in a dataset where an earlier version of the MRS scale was used, i.e. the scale was not self-administered but completed in an interview of the physician with the patient. This could have influenced the magnitude of the absolute scores of the total and sub-scales. As far as pre-/post-treatment changes are concerned, the magnitude of the absolute changes may have been more influenced than the relative changes of the HRQoL assessment of the patients as discussed in this paper. Another problem along the same line is that we had to transform the old coding system into the new one. This was done with a simple linear transformation and is not likely to have introduced any bias. Another limitation is that this is the first study we are aware of for this kind of assessment of the validity to measure therapeutic intervention. It is not likely that the main conclusions of the study are materially biased. However, the results should be cautiously used (e.g., for planning clinical trials or outcomes studies) as long as not confirmed with data obtained with the currently used self-administered MRS scale without potential influence of the physician. It can be assumed that a new study with the currently recommended MRS scale – in the sense of "patient-reported-outcome" – would demonstrate positive results but to a lesser degree. Conclusions The MRS scale showed some evidence for its ability to measure treatment effects on quality of life across the full range of severity of complaints in aging women. This however needs confirmation in other and better-designed clinical studies. Competing interests The authors FS and SG are employees of the company that produces HRT products. We cannot however see any conflict of interest as far as the methodological aspects of the validation of the MRS scale are concerned. Authors' contributions LAJH: responsible for the collection and evaluation of the data, and involved in writing of the paper. DMT: responsible for building the database of this publication, responsible for the statistical evaluation, and contributed to writing of the paper. FS: responsible for the post-marketing study and designing this paper, contributed to the manuscript. SG: responsible for designing and overseeing the post-marketing study of Climen, contributed to writing and revising of the paper JS: responsible for the field work of the post-marketing study, setting up the initial database, and for the preparation of the subset of data used for this publication. HPGS: Major responsibility in developing the MRS scale, contributed to writing/revision of the manuscript.

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548300

Inference of demographic history from genealogical trees using reversible jump Markov chain Monte Carlo

Background Coalescent theory is a general framework to model genetic variation in a population. Specifically, it allows inference about population parameters from sampled DNA sequences. However, most currently employed variants of coalescent theory only consider very simple demographic scenarios of population size changes, such as exponential growth. Results Here we develop a coalescent approach that allows Bayesian non-parametric estimation of the demographic history using genealogies reconstructed from sampled DNA sequences. In this framework inference and model selection is done using reversible jump Markov chain Monte Carlo (MCMC). This method is computationally efficient and overcomes the limitations of related non-parametric approaches such as the skyline plot. We validate the approach using simulated data. Subsequently, we reanalyze HIV-1 sequence data from Central Africa and Hepatitis C virus (HCV) data from Egypt. Conclusions The new method provides a Bayesian procedure for non-parametric estimation of the demographic history. By construction it additionally provides confidence limits and may be used jointly with other MCMC-based coalescent approaches.

Background The coalescent is a very versatile stochastic model of the genetic variation in a set of sequences sampled from a population. It allows to accommodate a wide range of assumptions about rates and modes of evolution, and of population history [ 1 - 5 ]. As the observed sequence data are positively correlated due to common ancestry, coalescent theory also provides a framework for understanding the relationship between a population's history and its genealogy. For instance, it has long been noted that genealogies of samples taken from exponentially growing populations tend to be "star-like" with short branch lengths near the root of the tree. In contrast, the inter-node distances in genealogies from constant-size populations typically are much more evenly spaced. Thus, coalescent theory quantifies the imprint that demographic development of a population leaves in the data. While the original theory was outlined for constant population size [ 1 , 2 ], Slatkin and Hudson [ 6 ] soon developed a coalescent model for the case of an exponentially growing population. Subsequently, a general approach allowing arbitrary population size variation through time was presented by Griffith and Tavaré [ 7 ]. Therefore at least in principle the coalescent model provides a basis for statistically inferring the demographic history as a function of time from the sampled sequences [ 3 , 8 - 12 ] or, alternatively, from the corresponding inferred genealogies [ 13 - 15 ]. In practice, however, application of coalescent theory to this problem has been restricted to very simple demographic scenarios such as constant size, exponential or logistic growth. Only recently methods have emerged that attempt the completely non-parametric estimation of the demographic function from the data. Polanski et al. proposed an approach based on pairwise distances [ 16 ], hence generalizing the method by Slatkin and Hudson [ 6 ]. Pybus et al. [ 14 ] presented the "skyline plot" method that uses a step-function to approximate the population history obtained from an estimated genealogy. This method was subsequently refined to the "generalized skyline plot" [ 17 ] which is essentially a regularized version of the classic skyline plot. If the population size is truly constant through time the generalized skyline plot estimate of population size collapses to the phylogenetic coalescent estimator proposed by Felsenstein [ 13 ]. The advantage of the skyline plot over the method suggested by Polanski et al. [ 16 ] is that it takes into account the genealogical relationship among the sequences. This helps to decrease bias and improves the efficiency of the resulting estimator compared to methods based on summary statistics and pairwise distances [ 13 ]. Unfortunately, the skyline plot approach also has several deficiencies. First, it is unclear how to extend the approach to allow multiple genealogies as input. This is important in order to accommodate phylogenetic error, and to allow non-parametric inference of population history in coalescent approaches that take all possible genealogies into account [ 7 - 10 ]. Second, and perhaps more critical, the (generalized) skyline plot only provides a population size trend rather than a realistic estimate of population size changes, as by construction the population function is modeled by a step function. Moreover, the change-points of this function are fixed at the inter-nodes of the underlying tree. In this paper we propose a novel framework to non-parametric estimation of the demographic history. This approach relies on Bayesian reversible-jump MCMC inference [ 18 ] to obtain a smooth population size function from a given set of genealogies. The new method not only renders many deficiencies of the classic and generalized skyline plot obsolete but it is also computationally efficient, with running times of the algorithm for typical data in the order of minutes on standard PC hardware. The framework has been implemented in the computer language R [ 19 ] and incorporated in the R package APE [ 20 ]. The remainder of the paper is organized as follows. In the next section we describe the mathematical and statistical theory of the new framework. Subsequently, we apply the method to simulated and biological sequence data and discuss the results. In the last section we briefly outline possible further extensions and related directions of research. Results Background in coalescent theory Basic model In a pan-mictic population with constant effective population size N e , where every individual has a single parent, the waiting time w n until any two of n sampled lineages coalesce is exponentially distributed with rate [ 1 , 2 ]. For n sequences there are therefore n - 1 intervals I n , I n -1 ,..., I 2 with rates r n , r n -1 ,..., r 2 and interval lengths w n , w n -1 ,..., w 2 . With we denote the time until all samples have reached the most recent common ancestor. The coalescent model implies that the waiting time to the next coalescent event follows an inhomogeneous Poisson-process with a hazard rate r n that varies in time t because of the change in the number of lineages. Thus, it is straightforward to also include variable population size in the coalescent simply by using the hazard rate . From standard theory in survival analysis [ 21 ] it follows that the corresponding density for the waiting times is given by where τ i is the time at the beginning of the interval I i . This is exactly the distribution from the variable population size coalescent as developed in [ 7 ]. The coalescent model can be further expanded to diploid populations [ 22 ] or to include other effects like selection, recombination or geographical structures [ 4 ]. In this paper, however, we focus solely on the coalescent/survival model given by Eq. 2. Estimation of population size If the waiting times w i are known Eq. 2 can be used directly to estimate N e ( t ). This is typically done by maximizing the likelihood assuming a simple parametric model for the population size change. For constant population size this has been done in [ 13 ], for more complicated scenarios such as logistic growth see, e.g., [ 14 ]. In a typical setting, however, the waiting times are themselves estimated from sequence data. In this case the total likelihood function will be a weighted sum of the likelihoods for all possible waiting times, so that in effect the w i are marginalized out in favor of the actually observed data. In practice exact calculation of this sum is prohibitive, hence one relies on approximating MCMC methods [ 8 - 10 ]. As a shortcut to avoid these computationally very expensive procedures one may also substitute the "true" waiting times by those obtained from inter-node distances of a single estimated gene tree (see, e.g., [ 23 ] for an overview of relevant likelihood-based tree inference methods) and proceed as above. Note that the resulting plug-in approximation ignores the uncertainty from estimating the w i in the inference of demographic parameters. However, this is justifiable if the phylogenetic error is much smaller than the error introduced by the coalescent. This will be the case if sequences are sufficiently long and the substitution rate is comparatively high (a typical example would be virus data). For non-parametric estimation of population size, Pybus et al. suggested the "skyline plot" [ 14 ]. This method assumes a piece-wise constant function for the population size N e ( t ) and allows population size changes only at the beginning and end of an interval I i . The estimated effective population size in interval I i according to the skyline plot is given by the simple relation This is the maximum likelihood estimate under the assumed model of fixed change-points. The "generalized skyline plot" subsequently introduced by Strimmer and Pybus [ 17 ] reduces the over-fitting present in the classic skyline plot by applying a simple form of regularization: adjacent intervals that alone are likely to have high stochastic noise are pooled together (cf. Fig. 2b and 2d ). Choice of an optimal grouping of intervals (i.e. model selection) is performed by employing a second-order variant of the Akaike criterion [ 24 ]. Figure 2 Comparison of prior and posterior demographic functions Top row : Bayesian inference using a prior demographic function with constant mean and constant variance (a 95% confidence band is indicated by showing the 2.5% and 97.5% quantiles). Bottom row : Bayesian inference using the "skyline plot" prior function. A Bayesian non-parametric approach to estimating demographic history Outline In this paper we present a non-parametric approach to infer population size changes in time that overcomes the limitations of previous approaches. More specifically, we develop a non-parametric Bayesian estimator for the function N e ( t ) conditioned on observed or sampled inter-node distances w n , w n -1 ,..., w 2 by determining the posterior distribution P( N e ( t )| w n , w n -1 ,..., w 2 ). In order to sample the non-parametric demographic function from this posterior we use the reversible jump Markov chain Monte Carlo (rjMCMC) algorithm [ 18 ]. As a result, we obtain for any given time t both a point estimate – here we choose the posterior median – as well as the associated credible interval (e.g., the lower and upper 2.5% quantiles). If the considered inter-node distances w n , w n -1 ,..., w 2 are fixed and obtained from a single estimated tree, the resulting method is already directly applicable to phylogenetically informative data such as viral sequences (this is the focus of this paper). However, sampling of non-parametric demographic functions can also be combined in a conceptually straightforward fashion with sampling of trees, as outlined below. Bayesian inference using reversible jump MCMC In a nutshell, Bayesian inference of a parameter x consists of updating its prior distribution P( x ) to a posterior distribution P( x | D ) that takes account of the information in the observed data D . The relative evidence of the data for different values of x is summarized in the likelihood L = P( D | x ) that accordingly plays a central role in the computation of the posterior via Bayes' theorem For most realistic problems the posterior distribution cannot be computed analytically, in particular if x is a high-dimensional vector. Instead, one utilizes computational procedures to efficiently draw random samples from the posterior. This in turn allows computation of summary statistics such as the median or the upper and lower 2.5% quantiles. Markov chain Monte Carlo (MCMC) is one particularly useful sampling algorithm as it doesn't require calculation of the sum (or integral) in the nominator of Eq. 4. Briefly, sampling via MCMC is done by constructing a Markov chain with the possible combinations of parameter values as "states", and the desired posterior as its stationary distribution. These properties can be guaranteed by following certain rules for accepting or rejecting proposed new parameter values. Here we use the Metropolis-Hastings-Green method, i.e. the reversible jump MCMC algorithm [ 18 ], that has the advantage of not only allowing changes in the parameters values but also in the dimension of the parameter vector itself. Specifically, if x is the initial state, and a proposed new state with proposal density , then the acceptance probability according to Green [ 18 ] is where is the likelihood ratio P( D | )/P( D | x ), is the prior ratio P( )/P( x ), is the proposal ratio q ( )/ q ( x ), and is the determinant of the Jacobian resulting from the potential change of dimension of the parameter vector. Accordingly, for the application of MCMC to infer the functional form of demographic history a variety of components need to be specified: • a suitable parameterization of the estimated function N e ( t ) • the likelihood function , • a prior distribution for each considered variable, and, • rules to construct the Markov chain (i.e. acceptance probabilities). In the following sections we now describe each of these elements in detail. For further general information on the statistical and mathematical background of the MCMC algorithm we refer to the many excellent monographs on this topic (e.g., [ 25 ]). Parameterization of N e ( t ) In our suggested procedure we approximate the sampled demographic history N e ( t ) by a piecewise linear function. This spline of first order degree consists of a first node at position a 0 = 0 and height h 0 , followed by k internal supporting nodes at ( a 1 ; h 1 ), ( a 2 ; h 2 ),..., ( a k ; h k ), and a terminal node at with height h k +1 Hence, the spline is defined for all t ∈ [0, T ], and for any given k the it contains k free position parameters and k + 2 free height parameters. Note that, unlike in the skyline plot, we do not constrain the change-points a 1 ,..., a k to lie on the grid points defined by the inter-node distances w i . Moreover, we also allow that the number of internal nodes k changes during sampling of the population function from the posterior. Hence, k is technically a hyper-parameter that controls the roughness of the resulting spline. As will be clear from the outline of the MCMC algorithm below, note that the final point estimate obtained from posterior sampling will be a mixture of linear splines (i.e. a smooth and possibly nonlinear function) rather than a single spline. Likelihood function The likelihood L employed in our procedure is the product of the densities of the waiting times between subsequent coalescence events, i.e. . This function depends via Eq. 2 on the effective population size N e ( t ), and hence indirectly on the spline parameters a i , h i and k . Because N e ( t ) is represented by a linear spline, calculation of the likelihood can be done in a computationally efficient fashion. Prior distributions Number of change-points Following [ 18 ] we employ a truncated Poisson-distribution as the prior distribution for k , i.e. where c is a normalizing constant to ensure that P( k ) is a proper distribution. For the hard upper limit of the number of change-points we use k max = 30. The parameter λ acts as a smoothing parameter, set in a typical analysis to about λ = 0.1 - 1.0. As an alternative to using a fixed λ we also suggest a hierarchical Bayes approach where λ is drawn from a Gamma distribution with some shape parameter a and scale parameter b (for instance, a ≈ 0.5 and b ≈ 2 so that E( λ ) = ab ≈ 1 and Var( λ ) = ab 2 ≈ 2). Positions We assume that the internal nodes of the spline are a priori uniformly distributed in the interval [0, T ]. As a simple trick to avoid very small inter-node distance we generate 2k + 1 random variables, and set the change-points a j = z [2 j ] for j = 1,..., k . The corresponding joint density is with a 0 = 0 and a k +1 = T . Heights As prior distributions for the heights h i we assume a Gamma distribution Gamma( h i | α i , β i )     (9) which ensures that sampled heights are always positive. The parameters α i and β i determine the a priori mean and variance of height h i . More generally, one can also allow fully time-dependent prior parameters α ( t ) and β ( t ). This is particularly advisable if the population size is known in advance to be subject to large changes in time. In a strict Bayesian approach, the choice of the prior distribution for the heights is completely external to the observed data. One simple possibility would, e.g., be to assume an arbitrary constant for the mean and variance. However, we recommend to follow a more pragmatic "empirical Bayes" route and to use the data at hand (or some other related data set) to obtain an informed guess about the prior heights. For example, an assumed constant population size as prior mean could be estimated using the method by Felsenstein [ 13 ]. Another possibility is to employ the skyline plot as a prior mean estimate (this is the default in our program). However, note that in practice the actual choice of prior height distribution seems to matter only little for estimating the posterior demographic function (see Figure 2 and the section on simulated data below). Only when there are few coalescent events per unit of time will the posterior estimate of the demographic function be dominated by the prior. Construction of the Markov chain There are four different possibilities to change the state defined by the parameters c i , h i , and k of the spline describing the effective population size N e ( t ): 1. varying the position of a change-point (i.e. internal node), 2. changing the height at a certain change-point, 3. generating a new change-point ("birth" step), and 4. deleting an existent change-point ("death" step). Let η k , π k , b k , and d k the probabilities of the four moves given k , with η k + π k + b k + d k = 1. In order to satisfy the requirement of detailed balance in the corresponding Markov chain the probabilities of birth and death steps ( b k and d k ) need to be synchronized [ 18 ]. This can be achieved, e.g., by setting and where c is chosen so that b k + d k < 0.9 for all k . Next, we describe the individual procedures to propose and accept one of the above four moves as implemented in our program. Height change First, a height h j is selected out of the k + 2 existing heights with probability . Second, a new height is generated by = h j exp( z ), where z is a uniformly distributed random variable on . Third, the new height is accepted with probability where α and β are from the prior distribution and denotes the ratio of the likelihood of the new state (with modified height) and the likelihood of the current state x . Position move First, a change-point a j is chosen randomly with probability . Second, its new position within [ a j -1 , a j +1 ] is determined by drawing from the corresponding uniform distribution. Third, is accepted with probability Birth step First, the position a * of the new change-point is found by uniformly drawing from (0, L ), and let the neighboring nodes left and right of a * have positions a j and a j +1 . Second, the corresponding new height h * is generated by randomly disturbing the current height N e ( a *) on the position a * according to N e ( a *) + zN e ( a *) where z is a uniformly distributed random variable on the interval . Note that the birth step increases the dimension of the parameter vector from 2 k + 2 to 2 k + 4 as a new change-point and a new height are generated. The corresponding acceptance probability of the birth step is computed according to Eq. 5 with likelihood and prior ratios as above, and with proposal ratio and Jacobi determinant Death step This is the inversion of the birth step and consists of removing a change-point. First, a * chosen from a 1 ,..., a k with probability . Second, the corresponding height h * is also removed from the vector of spline parameters. The acceptance probability for the death step is where the proposal ratio and the Jacobi determinant is the same as for the birth step. Computation of estimated N e ( t ) and associated confidence intervals In order to obtain an estimate of the effective population size in time we now proceed as follows. First, the Markov chain is started with an initial state that corresponds to a completely flat demographic function, i.e. N e ( t ) = c , where c is some rough estimate of population size, and k = 0. Second, 100,000 repeats of the MCMC algorithm are performed, of which the first 5,000 are ignored to allow for a "burn-in" period. Third, the remaining samples are thinned out by a factor of 1:50 to remove auto-correlation. As a result, 1900 independent samples from the joint posterior of the spline parameters a i , h i and k are obtained. Subsequently, in order to obtain a point estimate and associated confidence bands we compute the distribution of the effective population size at a number of fixed equidistant time points t 1 , t 2 ,..., t 1000 ∈ [0, T ]. Finally, we report as summary statistics the corresponding median and the lower and upper 2.5% quantiles. Extension to multiple genealogies In this paper we have introduced non-parametric sampling of demographic histories assuming a fixed underlying genealogical tree (or equivalently, a fixed set of inter-node distances w n , w n -1 ,..., w 2 .) However, in our approach – unlike previous non-parametric methods such as the skyline plot – it is also conceptually straightforward to incorporate phylogenetic error. This can be done by joint sampling of trees and demographies according to the following simple algorithm: 1. Given sequence data D , sample a tree G * with clock-like branch lengths (see, e.g, refs. [ 8 , 9 , 11 , 12 , 26 ] for suitable methods). 2. Use the method described in this paper to sample the demographic function conditioned on the inter-node distances from G *. 3. Repeat steps 1 and 2 to obtain the posterior distribution for the population size function, now conditioned on D rather than on some given w n , w n -1 ,..., w 2 . Note that each sampled tree may have a different depth . This means that the interval [0, T ] for the prior (and posterior) height distribution has to be set in advance (and independent of the T *). For the case of 0 < t < T * sampling of heights then proceeds as described above, while for T * < t < T – the region with no data from a given sampled tree – the heights are simply drawn from the respective prior distribution. Discussion In order to test the potential of the proposed reversible jump MCMC algorithm we first applied it to synthetic data simulated according to various demographic scenarios. Subsequently, we reanalyzed two viral data sets from Central Africa and Egypt. Computer program The proposed framework has been implemented by us for the case of a single underlying genealogy. The program is written in the statistical computer language R [ 19 ] and is incorporated in recent versions of the R package APE [ 20 ]. To install the APE package, simply run the R program, and enter at the R prompt install.packages("ape") This downloads the APE package from the Internet. The proposed reversible jump MCMC approach is implemented in the function "mcmc.popsize" of which an extensive description along with examples can be obtained online by typing library("ape") help(mcmc.popsize) into the R command window. The APE package also includes routines for plotting the inferred population function (e.g., all figures in this paper were prepared with APE). Note that the use of this R program is only valid if the phylogenetic error is low – this is typically the case when the evolutionary rate is high and the available sequences are long (e.g. viral data). If the phylogenetic error is not negligible compared to the coalescent error, please use software such as BEAST [ 27 ]. Simulated data In the simulation setup we followed Pybus et al. [ 14 ] and Strimmer and Pybus [ 17 ]. Specifically, we performed simulations assuming constant population size ( N e ( t ) = 100) as well as exponential population growth ( N e ( t ) = l000 e - t ), using 25 and 100 sampled lineages, respectively. To estimate the population size function we employed the proposed MCMC algorithm and the classic and generalized skyline plot. In the former the smoothing parameter λ was drawn from the hierarchical model with default parameters ( a = 0.5 and b = 2). Figure 1 shows the results from a typical run of the simulations. The top row illustrates the case of constant population size, whereas the bottom row demonstrates exponential growth. On the left in Figure 1 , top row, the true underlying constant population size is shown (the thick dashed line), together with the estimate provided by the classic skyline plot. On the right, this is contrasted with the estimate obtained by using our reversible jump MCMC algorithm. Clearly, the median of the posterior distribution of N e ( t ) is a very good point estimator of the true demographic history. In addition, the 95% confidence band is also automatically obtained by the MCMC method. Interestingly, it can be immediately seen that the uncertainty in N e ( t ) increases with a growing distance from the present. This simply reflects the fact that near the root of the tree for constant population size there are only few coalescent events. Figure 1 Simulated data Top row : Example of a simulation with constant population size: (left) true demographic history (dashed line) and estimate obtained with the classic skyline plot; (right) point estimate obtained with rjMCMC and 95% confidence band. Bottom row : Example with exponential population growth: (left) true population growth and classic skyline plot; (right) results from rjMCMC approach. In Figure 1 , bottom row, an example for a simulation with an exponentially growing population is shown. As for the constant population, the rjMCMC algorithm is capable of recovering the original population size function (shown as thick dashed line) complete with confidence bands, whereas the skyline plot contains a large amount of stochastic noise, and only provides a rough exploratory picture of the population size changes. In Figure 2 the influence of the choice of prior demographic function on the final posterior estimate is investigated using further simulations of an exponentially growing population. The left column depicts the prior distributions (specifically the 2.5%, 50% and 97.5% quantiles for each time point) for two typical cases: a constant prior function (= constant population size with constant variance), and the "skyline plot" prior function (= time dependent piecewise- constant population size and variance). The right column of figure 2 presents the corresponding posterior distributions as obtained with the present rjMCMC approach. The results for both cases are very similar. This indicates that there is sufficient signal in the data to make the posterior demographic function (almost) independent from the choice of prior distribution. Note that only near the left and right end of the investigated time intervals there are some slight differences. These can be explained by the lack of data points near the borders. HIV-1 in Central Africa Next, we applied our method to infer the demographic history from a set of HIV-1 sequences from Central Africa. These data was originally used by Vidal et al. [ 28 ] who examined the genetic diversity of HIV-1 type M in this region. Further detailed analysis can be found in Rambaut et al. [ 29 ] and Yusim et al. [ 30 ]. Here we use the reconstructed phylogeny of Yusim et al. with which Strimmer and Pybus also estimated the demographic history by means of the generalized skyline plot [ 17 ]. Figure 3 shows the result of the analysis with the reversible jump MCMC algorithm compared with the predictions from the classic and generalized skyline plots. As in Yusim et al. [ 30 ] an evolutionary rate of 0.0023 substitutions per year was assumed to convert the time axis into units of years. The first row of Figure 3 displays the tree of Yusim et al. [ 30 ] and the corresponding classic skyline plot. The latter exhibits a large amount of noise, nevertheless the main demographic signal is clearly visible in the graph. In contrast, in Figure 3c (second row) the effective population size as estimated by the rjMCMC algorithm is displayed. The thick line shows the median and the thin lines the 95% confidence interval. Especially in the middle part of the figure, where most of the data is located, the confidence interval is very narrow, indicating a stable estimation of the demographic history. Also note that for this data the average number of change-points in the MCMC run was k = 9.25, i.e. the estimated effective degree of freedom is much less than that implicitly assumed in the classic skyline plot. Figure 3 HIV-1 in Central Africa Top row : a) underlying genealogy; b) classic skyline plot. Bottom row : c) population size function estimated with rjMCMC and corresponding 95% confidence band; d) comparison rjMCMC versus generalized skyline plot. A comparison with the generalized skyline plot [ 17 ] is shown in Figure 3d . This demonstrates that the generalized skyline plot, in contrast to its classic cousin, provides a very good noise-reduced approximation to the demographic history as estimated by the reversible jump MCMC approach. However, especially near the present the step function employed in the generalized skyline plot leads to unrealistic jumps in the population size that are not present in the smooth estimate provided by the proposed MCMC method. HCV in Egypt In Egypt 10%-20% of the general population are infected with the Hepatitis C virus (HCV) [ 31 ]. This endemicity seems mainly to be caused by percutaneous medical procedures such as needle injections that took place during a countrywide health campaign between 1964 and 1982 against schistosomiasis. In order to investigate this phenomenon blood samples were obtained from various regions of Egypt and used to study the epidemic history of Hepatitis C. For instance, Tanaka et al. [ 32 ] analyzed the molecular evolution of HCV genotype 4a. Specifically, they utilized 47 sequences (AF217800-AF217812 [ 31 ] and AB103424-AB103457 [ 32 ]) from the NS5B region of the HCV subtype 4a to reconstruct the respective phylogeny, and subsequently applied the skyline plot method to infer the demographic history. We repeated their analysis with the reversible jump MCMC approach developed in this paper. We downloaded the sequence data from the HCV sequence database [ 33 ] and inferred the corresponding maximum-likelihood genealogy using the TREEFINDER program [ 34 ]. This tree is depicted in Figure 4a , next to the demographic history estimated from it by the classic skyline plot (Figure 4b ). In the bottom of the figure we show the estimated population size function and its 95% confidence bands as obtained by our rjMCMC method (Figure 4c ) and we also compare our results with those of the generalized skyline plot (Figure 4d ). For the generating the time axis in these plots we assumed an evolutionary rate of 0.00045 substitutions per year. Figure 4 HCV in Egypt Top row : a) underlying reconstructed genealogy; b) classic skyline plot. Bottom row : c) population size function estimated with rjMCMC and corresponding 95% confidence band; d) comparison rjMCMC versus generalized skyline plot. Generally, the star-like shape of the inferred tree already is indicative of exponential growth. This is confirmed by both the skyline plot as well as by our analysis (Figure 4d ). Moreover, it can be seen that around 1940 the growth rate increased (i.e. the slope of N e ( t ) in the log-plot changes). Near the present, the rate decreased again. Also note the broadening of the confidence interval since 1940 which reflects the sparsity of available observations. This implies that the claim of Tanaka et al. [ 32 ] that the demographic history recently changed back to constant population size after an exponential growth is not firmly backed by the data. For further biological analysis of the HCV data we refer to Pybus et al. [ 35 ]. Conclusions We have presented a new approach to non-parametric inference of demographic history from an inferred genealogy. This method is based on reversible jump MCMC sampling of the population size function N e ( t ). Unlike its predecessors, the classic and generalized skyline plots, it returns a smooth and realistic estimate of the demographic history and thus overcomes the constraints due to assuming a step function. Moreover, it automatically provides confidence limits. Nevertheless, the procedure is still computationally fast and can be run on any standard PC hardware. In our examples we demonstrated the advantage of non-parametric estimation of demographic history. Parametric estimation always assumes a certain functional form of population growth which may lead to problematic statements (cf. the HCV data set), in particular if the confidence bands of the estimated function N e ( t ) are not taken into account. From the methodological point of view, model selection via rjMCMC has the advantage that the effective dimension, i.e. the degree of smoothing, is automatically chosen in a data-driven manner. There is only one parameter ( λ ) that controls the a priori degree of smoothing, and this is adjusted accordingly by the investigated data. In addition, a further advantage of our MCMC approach is that – in contrast to the skyline plot – at least in principle it is straightforward to incorporate it in more general MCMC sampling schemes that also take account of the uncertainty in the genealogy. During the referee process we have learned that the authors of the software package BEAST [ 27 ] have developed a similar non-parametric method to Bayesian coalescent inference of population history (A.J. Drummond et al., in preparation). We plan to work with Dr. Drummond to make available in BEAST joint sampling of sampling of demographic histories and of trees. This would combine the present rjMCMC approach and the method developed by Drummond and colleagues. Authors' contributions This paper summarizes the main results from a master's thesis of R.O. supervised by K.S. and L.F. Accordingly, K.S. and L.F. jointly devised the project and R.O. carried out all analyses and simulations. All authors participated in the development of methodology. R.O. and K.S. wrote the manuscript. All authors approved of the final version.

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509413

The Structural Basis of a Prostate Cancer Protein's Unique Selectivity

One of the major players in prostate cancer is a nuclear signaling protein called the androgen receptor. Prostate growth and development is regulated by androgen hormones (like testosterone) that activate the androgen receptor. When an androgen binds the receptor, the receptor binds other proteins, called coactivators, to activate genes controlling cell growth, survival, and differentiation. Unlike other receptors that function in the nucleus, the androgen receptor normally shuns coactivators with a leucine-rich binding domain in favor of those with “aromatic” domains. (Aromatic amino acids are defined by their ring structure.) But during prostate cancer, the receptor interacts with both coactivator types, to promote disease progression. The secret to a protein's binding preference rests in the underlying sequence of its amino acids, which determines the protein's structure and ultimate behavior. Robert Fletterick and colleagues set out to identify the “full repertoire” of amino acid sequences that might conceivably consort with the androgen receptor. Their findings help explain the unusual behavior of the androgen receptor during prostate cancer progression—a first step toward developing new anticancer therapies. Treatment for hormone-dependent prostate cancers focuses primarily on reducing androgen levels by using chemicals that compete for androgen receptor docking rights in the hormone-binding pocket of the ligand-binding domain, or LBD. (A ligand is a molecule, like the androgen hormone, that binds to a receptor.) But cancer cells eventually circumvent these chemical assaults through increased levels of either androgen receptors or their coactivators, or through mutations that make androgen receptors immune to chemotherapy. That's why Fletterick and colleagues turned their attentions to the receptor's consorts. Since targeting the hormone-binding pocket of the receptor offers limited benefits, a better strategy might involve disrupting associations with the receptor's coactivators. Dozens of proteins interact with different regions of the androgen receptor, but the details of these interactions were not known. When a hormone binds to the LBD of other nuclear receptors, it triggers a conformational change that creates a binding surface called AF-2 for the leucine-rich domains of the coactivator proteins. It was not clear, however, how the AF-2 region of the androgen receptor distinguishes between aromatic and leucine-rich domains. To characterize the receptor's binding selectivity, Fletterick and colleagues tested 20 billion peptides, or protein fragments, to see whether they interacted with the LBD region of a hormone-bound androgen receptor. As expected, most of the peptides that associated with the LBD domain were aromatic. And they interacted with the same region that naturally occurring coactivators bind to. Next, Fletterick and colleagues determined the three-dimensional structure of both the receptor bound to just the androgen hormone and the androgen–receptor pair bound to a subset of seven peptides. The different structures showed that the androgen receptor uses a single surface to bind both leucine-rich and aromatic peptides; when the aromatic peptides have bulky appendages, the receptor's AF-2 domain reorganizes to accommodate them. Surface complimentarity of hydrophobic motifs The various structures and binding affinities for the different receptor–peptide complexes described here show how the receptor can interact with a diverse array of proteins. The androgen receptor, unlike other nuclear receptors, has specific amino acid sequences that better support aromatic peptide binding. Interestingly, mutations in one of these amino acid sequences have been found in prostate cancer. Altogether, the authors conclude, the unique properties of the receptor's AF-2 surface make it “an attractive target for pharmaceutical design.” Drugs that directly interfere with coactivator binding, they explain, are likely to inhibit androgen receptor activity. Here, the authors recommend novel sites on the receptor as promising targets for androgen-receptor-specific inhibitors.

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526383

Multimorbidity and quality of life in primary care: a systematic review

Background Many patients with several concurrent medical conditions (multimorbidity) are seen in the primary care setting. A thorough understanding of outcomes associated with multimorbidity would benefit primary care workers of all disciplines. The purpose of this systematic review was to clarify the relationship between the presence of multimorbidity and the quality of life (QOL) or health-related quality of life (HRQOL) of patients seen, or likely to be seen, in the primary care setting. Methods Medline and Embase electronic databases were screened using the following search terms for the reference period 1990 to 2003: multimorbidity, comorbidity, chronic disease, and their spelling variations, along with quality of life and health-related quality of life. Only descriptive studies relevant to primary care were selected. Results Of 753 articles screened, 108 were critically assessed for compliance with study inclusion and exclusion criteria. Thirty of these studies were ultimately selected for this review, including 7 in which the relationship between multimorbidity or comorbidity and QOL or HRQOL was the main outcome measure. Major limitations of these studies include the lack of a uniform definition for multimorbidity or comorbidity and the absence of assessment of disease severity. The use of self-reported diagnoses may also be a weakness. The frequent exclusion of psychiatric diagnoses and presence of potential confounding variables are other limitations. Nonetheless, we did find an inverse relationship between the number of medical conditions and QOL related to physical domains. For social and psychological dimensions of QOL, some studies reveal a similar inverse relationship in patients with 4 or more diagnoses. Conclusions Our findings confirm the existence of an inverse relationship between multimorbidity or comorbidy and QOL. However, additional studies are needed to clarify this relationship, including the various dimensions of QOL affected. Those studies must employ a clear definition of multimorbidity or comorbidity and valid ways to measure these concepts in a primary care setting. Pursuit of this research will help to better understand the impact of chronic diseases on patients.

Background With technological advances and improvements in medical care and public health policy, an increasingly large number of patients survive medical conditions that used to be fatal. As a result of this phenomenon, and parallel to the aging of the population, a growing proportion of primary care patients presents with multiple coexisting medical conditions. From available data, it was estimated that 57 million Americans had multiple chronic conditions in 2000 and that this number will rise to 81 million by 2020 [ 1 ]. Epidemiological data from several countries support this estimate [ 2 - 8 ]. On average, patients aged 65 years and older present with 2.34 chronic medical conditions [ 7 ]. In fact, 50% of patients with a chronic disease have more than one condition [ 9 ]. The terms "comorbidity" and "multimorbidity" have been used to describe this phenomenon. Feinstein [ 10 ] originally described comorbidity as "any distinct additional entity that has existed or may occur during the clinical course of a patient who has the index disease under study." Kraemer [ 11 ] later referred to comorbidity in studying specific pairs of diseases. Van den Akker and colleagues [ 12 ] further refined both concepts, reserving the term "multimorbidity" to describe the co-occurrence of two or more chronic conditions; they also proposed some qualifiers to better classify the type of multimorbidity (simple, associative and causal). Unfortunately, much confusion still exists in the literature, where the 2 terms often seem to be used interchangeably. For the purpose of this paper, the term "multimorbidity" will be used according to Van den Akker and colleagues' definition and the focus will be solely on chronic diseases. Previous reports on multimorbidity or comorbidity have documented that this phenomenon influences outcomes in many areas of health care [ 13 - 19 ]. Outcome measures that have been related to multimorbidity include mortality, length of hospital stay, and readmission. An association between disability and multimorbidity in elderly patients has also been described [ 14 , 20 - 22 ]. Quality of life (QOL) is an outcome measure that is increasingly being used to evaluate outcomes in clinical studies of patients with chronic diseases [ 23 - 26 ]. QOL represents a subjective concept, with a multidimensional perspective encompassing physical, emotional, and social functioning [ 27 ]. It is important to address QOL as it has been associated with health and social outcomes [ 28 ] which may contribute to the worsening of the course of the diseases. In research and the medical literature, there is little distinction between health-related quality of life (HRQOL) and overall QOL (the latter encompasses not only health-related factors but also many non medical phenomena such as employment, family relationships, and spirituality) [ 29 ]. In practice, the terms are often used interchangeably. Different evaluation scales have been proposed to measure QOL or HRQOL. Some focus on a specific disease [ 30 , 31 ], while others have wider applications (i.e., generic measurements) [ 32 - 34 ]. Little is known about the impact of multimorbidity on QOL of primary care patients [ 35 ], although this is where most patients receive their care. Thus, the purpose of this systematic review is to clarify the association between the presence of several concurrent medical conditions and the QOL or HRQOL of patients seen or likely to be seen in a primary care setting. Methods Data sources For this review, we consulted Medline and Embase electronic databases for the reference period 1990 to 2003. Figure 1 illustrates the search strategy. Since the term "multimorbidity" does not have any equivalent in the thesaurus, databases were searched for the following terms: multimorbidity, comorbidity, and their spelling variations. The term "multimorbidity" was searched as a keyword, while "comorbidity" was searched as a Medical Subject Heading (MeSH). The term "chronic disease" was used to increase the sensitivity of the search. We also used the MeSH "quality of life" and the keyword "health-related quality of life" to help target pertinent literature. Figure 1 Selection of articles: Medline (Embase), years 1990–2003 To identify studies pertinent to the primary care setting, the following search terms were used: general practice, family practice, family medicine, family physician, and primary health care. A parallel strategy was used to identify all descriptive studies, regardless of the context of care, and the results were then combined. For the initial screening, the search was restricted to studies on human subjects, published in French or English. To be complete, we directly searched the Quality of Life Research and Health and Quality of Life Outcomes journals. We also screened references from key articles retrieved (hand searching). Study selection One researcher (LL) performed the initial screening. Any ambiguous findings were discussed with the lead investigator (MF) and a consensus was reached. Inclusion and exclusion criteria For the purpose of this systematic review, we selected original, cross-sectional, and longitudinal descriptive studies that had evaluated the relationship between multimorbidity or comorbidity and QOL or HRQOL as the main outcome of interest. As stated earlier, we focused on the population of patients seen, or likely to be seen, in the primary care setting including members of the general population and residents of nursing homes and home healthcare facilities. We also selected original descriptive studies that had examined the relationship between multimorbidity or comorbidity and QOL or HRQOL as a secondary outcome. Figure 1 shows our exclusion criteria. In keeping with our objectives, we did not include studies on specific diseases (e.g., acquired immunodeficiency disease) or populations unlikely to represent a large part of primary care practice. We also excluded any studies that did not address physical comorbidities, including those that exclusively examined mental disorders and associated mental comorbidities. Finally, we excluded studies in which the main outcome of interest was not QOL or HRQOL as well as those that used a nonstandard approach to measuring QOL or HRQOL. Assessment of study quality Before being included in the synthesis, the quality of each article selected was critically analyzed. For this assessment, we devised a scale in which points were assigned for study parameters indicative of good quality (e.g., well-defined populations, clear definitions, valid measures). Using this scale (Table 1 ), 2 researchers independently determined a global quality score for each article. The scores for each article were then compared and adjusted by consensus. To ensure adequate methodological quality, the cut-off score for an article to be included in the synthesis was 10 out of a maximum of 20 points. Table 1 Evaluation criteria Evaluation criteria for the studies identified in the literature search: 0, 1, or 2 points per criterion or subcriterion (maximum score = 20) Criterion1: Originality Original study (cross-sectional or longitudinal) with a clear objective Criterion 2: Population studied 2a) Primary care or general population 2b) Well-defined control group or good variability of the independent variable in a regression model 2c) Characteristics of the groups are described, including those of nonrespondents, and do not lead to bias Criterion 3: Definition Clear definition of multimorbidity and valid measure Criterion 4: Outcome 4a) Quality of life was the primary outcome measure 4b) Quality of life was evaluated with a validated scale 4c) Evaluation of quality of life was independent of the multimorbidity/comorbidity score (i.e., blind evaluation) 4d) Effects of the main confounding factors (e.g., age, gender) are presented and discussed Criterion 5: Limitations Authors comprehensively discussed the limitations of their study Synthesis or results Figure 1 shows the number of articles found at each stage of the selection process. Of the 753 articles screened, 108 were evaluated according to the study's inclusion and exclusion criteria. We also assessed the quality of each study before selecting 30 for inclusion in the synthesis: 7 that had evaluated the relationship between multimorbidity or comorbidity and QOL as the main outcome (Table 2 ) and 23, as a secondary outcome. Quality of life as the main outcome measure Of the 7 studies that featured QOL as a primary outcome [ 36 - 42 ], 5 had been conducted in European populations. We analyzed theses studies in detail. Quality scores for these studies ranged from 10 to 18 (out of a maximum of 20 points) and were highest in 2 studies from the Netherlands, one from the United States, and another study from Sweden. Table 2 presents a synthesis of the various studies. All studies came to the same conclusion, namely that there is an inverse relationship between the number of medical conditions and QOL or HRQOL. This association may be affected by the patient's age or gender. Whereas multimorbidity mostly affects physical dimensions of QOL or HRQOL [ 36 , 37 , 41 ], data from one study suggest that social and psychological dimensions may be affected in patients with 4 or more diagnoses [ 40 ]. In each study, investigators relied on simple count of chronic diseases from a limited list to measure multimorbidity. The chronic conditions included in this list varied among the studies, and no attempt was ever made to assess or account for the severity of each condition. Furthermore, 5 of the 7 studies did not consider psychiatric comorbidity, either because the illnesses considered did not include psychiatric diagnoses or because patients presenting with psychiatric diagnoses were excluded from the QOL evaluation. In most cases, the diagnostic information was obtained by a questionnaire that was completed by a nurse or a doctor or sometimes self-administered. One study assessed comorbidity via chart review. To measure QOL, a variety of scales were used. Most studies (5/7) used tools from the Medical Outcomes Study i.e., the Short-Form-36 Health Survey (SF-36) and Short-Form-20 Health Survey (SF-20). However, the Nottingham Health Profile (NHP) was used in one study and the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) was used in another. Although the number of domains explored varied from one study to the next, the measuring instruments used have excellent psychometric properties and validity. The 4 studies associated with the highest quality scores explored only a limited number of potential confounders, namely age [ 37 , 38 ], gender [ 36 , 41 ], and socio-demographic and economic factors [ 38 ]. Effects of these confounders are reported in Table 2 . The other 3 studies did not investigate potential confounders. Quality of life as a secondary outcome measure Of the 23 studies that evaluated the relationship between multimorbidity or comorbidity and QOL as a secondary outcome measure [ 43 - 65 ], most were done in Europe (9 studies) and the United States (12 studies). As with the main outcome studies, each used a simple count of a limited and varying number of chronic medical conditions to evaluate multimorbidity. While there was generally no attempt to assess or account for the severity of individual conditions, one study used a comorbidity index, the Duke Severity of Illness (DUSOI), for this purpose [ 48 ]. Diagnostic information was obtained from chart reviews and clinical evaluations (9 studies), from self-report questionnaires (13 studies), or both sources (1 study). Psychiatric comorbidity was evaluated in 13 studies. As with the results from the main outcome studies, we found an inverse relationship between the number of medical conditions and the QOL relating to physical domains in all studies. However, the relationship between multimorbidity and QOL relating to psychological or social domains was less clear. Some investigators reported an effect of multimorbidity on these domains in patients with 3 or more diagnoses [ 54 ], while others reported no effect [ 48 , 55 ]. As in the main outcome studies, tools from the Medical Outcomes Study, including the SF-36 (17 studies), SF-20 (3 studies), and Short-Form-12 Health Survey (SF-12) (1 study), were used to evaluate QOL in most of these studies. However, the NHP was used in one study and the Quality of Well-Being Scale (QWB), in another. In the majority of studies, all of the QOL domains were explored. Table 2 Synthesis of studies on multimorbidity with quality of life as the main outcome measure Author (Country) Design Score Population Multimorbidity QOL scale Limitations Conclusions Cheng 2003 [36] (United States) Cross-sectional design 17 Ambulatory, family medicine. n = 316 (55–64 years) 7 diagnoses of chronic conditions obtained by chart review. Medical Outcomes Study (SF-36). Administered by interviewer. Definition of multimorbidity was based on simple count of diseases. No assessment of disease severity or use of a healthy group for comparison. No mention of psychiatric comorbidity. Limited to low-income population. Small sample. Age of the sample was limited. For every SF-36 domain, scores obtained in pregeriatric patients are significantly lower than those obtained in the general population. Lower physical component summary scores (PCS) and mental component summary scores (MCS) are associated with a greater number of chronic diseases, but this association is much stronger for PCS than MCS. Wensing 2001 [37] (Netherlands) Cross-sectional design 18 Ambulatory, family medicine. n = 4,112 (18+ years) 25 diagnoses of chronic conditions, with the possibility of including other diagnoses reported spontaneously. Self-administered questionnaire. Medical Outcomes Study (SF-36); 8 domains. Self-administered. Definition of multimorbidity was based on simple count of diseases. Medical conditions were self-reported by patient, with no assessment of disease severity. Psychiatric comorbidity was not evaluated. Prevalences of chronic conditions were abnormally low, consistent with a selection or information bias. The QOL in each of the domains declines with the number of diagnoses (0, 1, 2 and over) but less so for the mental health domain. The QOL score declines with age, especially in physical domains. Michelson 2001 [38] (Sweden) Cross-sectional design 16 General adult population, stratified according to age. n = 3,069 (18–79 years) 13 diagnoses of chronic conditions, divided into 4 categories based on the number of problems: (0, 1–2, 3–4, 5+). Self-administered questionnaire. European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ); 5 domains. Self-administered. Too few diagnoses considered. Medical conditions were self-reported by patients, with no assessment of disease severity. Psychiatric comorbidity was not evaluated. Although adequate for use as a generic measure, the QOL questionnaire was developed for cancer patients. The presence of multiple chronic problems is associated with a lower QOL score. This association is present for each age group and tends to reduce the relationship between age and QOL. The impact of socio-demographic and economic factors varies with age. Cuijpers 1999 [39] (Nether-lands) Cross-sectional design at the beginning of a cohort study 10 Residents of homes for the elderly. n = 211 (Mean = 84.3 years) 7 diagnoses of chronic conditions, with the possibility of including other diagnoses reported spontaneously. Questionnaire administered by the nursing staff. Short-Form-20 Health Survey (SF-20); 5 domains. Administered by interviewer. Too few diagnoses considered. No assessment of disease severity. Psychiatric comorbidity was not evaluated. Data collection procedure was not standardized. Many refusals to participate (30%), including some for health reasons. Small sample. Aged patients. A lower QOL score is associated with a high number of chronic conditions. Grimby and Svanborg 1997 [40] (Sweden) Cross-sectional design in a cohort follow-up 14 General ambulatory. n = 565 (76 years) 16 diagnoses of chronic conditions present in > 5%. Medical questionnaire. Modified Nottingham Health Profile (NHP); part I: 6 dimensions; part II: 5 questions. Self-administered. Definition of multimorbidity was based on a simple count of diseases. No assessment of disease severity. Health of nonrespondents was not comparable (more ill). No age variation (76 years). The loss of QOL is proportional to the number of diagnoses for the dimensions of energy, pain, mobility, and sleep. For social and emotional dimensions, QOL is little influenced until health is significantly impaired (4 or more diagnoses). Kempen 1997 [41] (Nether-lands) Cross-sectional design at the beginning of a cohort study 17 Ambulatory, family medicine. n = 5,279 (57+ years) 18 diagnoses of chronic conditions. Questionnaire administered by interviewer. Short-Form-20 Health Survey (SF-20); 6 domains. Administered by interviewer or self-administered. Definition of multimorbidity was based on simple count of diseases reported by the patient. Use of a list of diagnoses in correlation and multiple regression analyses. No assessment of disease severity or psychiatric comorbidity. Age of the sample was limited. The presence of chronic medical conditions explains a high proportion of the variance (25%) in the QOL score in most domains, especially self-perceived health. Personality influences QOL scores, especially in the mental health domain. The association between the number of chronic conditions and the QOL score is slightly stronger for women than men. Fryback 1993 [42] (United States) Cross-sectional design 13 General ambulatory. n = 1,356 (45–89 years) 28 diagnoses of chronic conditions, with the possibility of including other diagnoses reported spontaneously. Questionnaire administered by interviewer. Medical Outcomes Study (SF-36) reduced to 2 domains. Quality of Well-Being scale (QWB). Administered by interviewer. Definition of multimorbidity was based on a simple count of diseases reported by patient. No assessment of disease severity. QOL questionnaire completed by the same interviewer immediately after the medical questionnaire. Characteristics of the healthy group were not described. Multimorbidity data were not adjusted for age. Questionnaire did not include all domains traditionally included in QOL assessment. The QOL score, as estimated with all of the measuring instruments, decreases with the number of chronic medical conditions. However, only limited domains of QOL were evaluated. QOL: Quality of life Discussion Although this systematic review confirms the inverse relationship between multimorbidity and QOL, it also raises some important questions. First, the relative lack of studies in primary care evaluating the association between multimorbidity and QOL or HRQOL is surprising given the number of patients who suffer from multiple concurrent chronic conditions. Although the existence of this association makes logical sense, it still has to be demonstrated and thoroughly studied to find ways of improving care for specially affected patients. Thus, the pressing question may not be whether there is an association but rather how strong is the association and what factors are responsible for it? Identifying these factors may contribute to better care for the affected patients. There is a clear need for further studies to address these issues. Ultimately, multimorbidity has the potential to affect all domains of QOL. However, the influence of multimorbidity on the social and psychological dimensions of QOL is much less clear than its influence on the physical domains. It is noteworthy that several studies showed a significant decline in social and psychological dimensions of QOL in patients with 3, 4, or more concurrent diagnoses. What does this finding mean? Is there any bias that can explain this difference, or is it related to a certain capacity for adaptation? Are there other factors associated with this finding? All of these questions have yet to be answered. All the studies examined were cross-sectional in nature. The effect of multimorbidity may vary over time. Some medical conditions may improve while others worsen resulting in various effects on QOL. Therefore, cross-sectional studies may not capture the real effect of multimobidity on QOL and predict the direction of change over time. Defining and measuring multimorbidity The absence of a uniform way of defining and measuring multimorbidity is of special concern and may explain some of the variability in our results. In most of the studies we evaluated, investigators had used only a simple list of diseases to identify concurrent medical conditions in patients, providing very incomplete information. Furthermore, the numbers and types of medical conditions in these lists varied among the studies, precluding comparisons. Given the urgent need for conceptual clarity, Van den Akker and colleagues' definition of multimorbidity should be refined and advanced to achieve a common understanding. A distinction must be made between simple and complex chronic diseases. Treated hypothyroidism (simple) and ischemic heart disease (complex) obviously do not have the same impact on QOL. Moreover, the influence of single-organ versus multi-organ diseases needs to be appropriately weighed. Additional factors to be considered when defining multimorbidity include the severity of the conditions and the presence or absence of associated pain. The use of self-reported diagnoses in many studies is another methodological limitation that may have introduced error. Patients may confuse symptoms and minor ailments with more significant disease states or may forget to report important diagnoses that are still active. Self-reporting may even be completely inaccurate in the presence of psychosomatic disorders. Conducting a chart review, clinical interview or using any specific standardized method may be a better way to obtain data related to diagnoses. Another methodological limitation of most of the studies evaluated was their failure to consider the influence of psychiatric comorbidity. This was either because psychiatric diagnoses were not included in the lists of disease states or because patients presenting with psychiatric diagnoses were excluded from QOL assessment. Given the importance of psychiatric conditions in primary care practice with a prevalence of more than 20% [ 66 ], this limitation is simply unacceptable. Confounders QOL tends to decrease with age [ 67 ], whereas the number of diagnoses increases with age. Thus, it is appropriate to consider age as a potential confounding variable. The effect of age was explored in some of the studies that used QOL as a main outcome measure [ 37 , 38 , 41 ]. Reference to established norms would have facilitated interpretation of these results. Only a few of the studies evaluated had explored the effect of gender. Furthermore, their results were contradictory, with gender being more detrimental to the QOL of women in some cases [ 41 , 58 ] and men, in others [ 51 ]. Little has been reported about the effects of other potential confounding variables (e.g., socio-demographic and economic data, health habits, social support, number of drugs prescribed), although these factors are recognized as having an impact on QOL [ 68 - 71 ]. A few of the studies that used QOL as a secondary outcome measure considered the influence of socio-economic variables; however, their results were ambiguous, showing an impact in only about half of the studies. Some studies also demonstrated that, although socio-economic variables and health habits were significant predictors of QOL, the number of comorbidities was the strongest independent predictor of QOL [ 41 , 56 ]. Only one study took into account social support, and this study revealed a relationship with the mental dimension of QOL [ 58 ]. Only one study took into account the number of drugs prescribed and found an impact on the physical domain of QOL [ 49 ]. This study looked specifically at comorbidities associated with arterial hypertension and their impact on QOL. Finally, other potential confounding variables such as marital status and living arrangements were considered in some studies, with demonstration of an impact on QOL in about half the studies. Many other factors should be explored in this regard. For example, the presence of coexisting acute conditions, the time since the diagnosis of important chronic conditions, and the duration and prognosis of health problems are among factors that may explain some of the variability in QOL or HRQOL. Research agenda In light of the findings of this systematic review, further research is needed to clarify the relationship between multimorbidity and QOL. The early work will certainly be conceptual and theoretical. The resultant conceptual clarity would benefit both researchers and practitioners. How do we define and how should we measure multimorbidity are among the first questions to be addressed. More descriptive studies, which take into account the influence of multiple potential confounders, can then be conducted. Multivariate analyses will help control for the effects of these confounding variables. The effects of age and gender also need to be further explored, with reference to established norms. Although there is still a need for cross-sectional studies, longitudinal studies are also needed to identify changes in the relationship between multimorbidity and QOL over time. Study limitations The main limitation of a systematic review is its inability to include all of the relevant literature. We realize that some articles may have been missed during the search stage. However, our review of a huge number of abstracts generated by different strategies improved the sensitivity of the search. Obviously, the absence of a keyword for multimorbidity is a limitation. However, we found that in the majority of cases in which the term "multimorbidity" was used to search, the term "comorbidity" also appeared in the list of keywords. Adding the term "chronic disease" also helped to circumvent the problem. Restricting the search to articles published in French or English is another limitation. Conclusion This systematic review focused on the relationship between the presence of several chronic coexisting medical conditions and QOL or HRQOL in a primary care setting. However, the studies evaluated had important limitations due to the lack of a uniform definition for multimorbidity or comorbidity, the absence of assessment of disease severity, the use of self-reported diagnoses, and the frequent exclusion of psychiatric diagnoses. The potential impact of important confounding variables was also neglected. In light of these observations, it seems clear that further studies are needed to clarify the impact of multimorbidity on QOL or HRQOL and its various dimensions (i.e., physical, social and psychological). A clear understanding of this relationship will ultimately help both researchers and primary health care professionals to deliver more comprehensive care. Author contributions MF was responsible for the conception and design of this systematic review and was also involved in the literature review. In addition, he was responsible for critically assessing the evaluated articles and drafting this manuscript. He takes responsibility for the integrity of the work as a whole and provided final approval of this version of the manuscript. LL provided a major contribution to the literature review and critical appraisal of the identified articles. She also participated in the drafting of this manuscript and gave final approval of this version. CH participated in both the conception and design of this review. She also contributed by critically revising this manuscript and gave final approval of this version. AV participated in the design of this review. He also made an important contribution in critically revising the manuscript and gave final approval of this version. ALN participated in the drafting of the manuscript and made an important contribution by critically revising it. He also gave final approval of this version. DM participated in the drafting of the manuscript and made an important contribution by critically revising it. She also gave final approval of this version.

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534793

Health-related quality of life among adolescents with allergy-like conditions – with emphasis on food hypersensitivity

Background It is known that there is an increase in the prevalence of allergy and that allergic diseases have a negative impact on individuals' health-related quality of life (HRQL). However, research in this field is mainly focused on individuals with verified allergy, i.e. leaving out those with self-reported allergy-like conditions but with no doctor-diagnosis. Furthermore, studies on food hypersensitivity and quality of life are scarce. In order to receive information about the extent to which adolescent females and males experience allergy-like conditions and the impact of these conditions on their everyday life, the present study aimed to investigate the magnitude of self-reported allergy-like conditions in adolescence and to evaluate their HRQL. Special focus was put on food hypersensitivity as a specific allergy-like condition and on gender differences. Methods In connection with lessons completed at the children's school, a study-specific questionnaire and the generic instrument SF-36 were distributed to 1488 adolescents, 13–21 years old (response rate 97%). Results Sixty-four per cent of the respondents reported some kind of allergy-like condition: 46% reported hypersensitivity to defined substances and 51% reported allergic diseases (i.e. asthma/wheezing, eczema/rash, rhino-conjunctivitis). A total of 19% reported food hypersensitivity. Females more often reported allergy-like conditions compared with males (p < 0.001). The adolescents with allergy-like conditions reported significantly lower HRQL (p < 0.001) in seven of the eight SF-36 health scales compared with adolescents without such conditions, regardless of whether the condition had been doctor-diagnosed or not. Most adolescents suffered from complex allergy-like conditions. Conclusions The results indicate a need to consider the psychosocial impact of allergy-like conditions during school age. Further research is needed to elucidate the gender differences in this area. A team approach addressing better understanding of how allergy-like conditions impair the HRQL may improve the management of the adolescent's health problems, both in health-care services and in schools.

Background An increase in the prevalence of asthma and atopy during the last two decades is documented for both children [ 1 ] and adults [ 2 ]. The International Study of Asthma and Allergies in Childhood (ISAAC) has demonstrated a large variation in the prevalence of asthma symptoms in children throughout the world [ 3 ]. An ISAAC-study on prevalence of childhood allergic diseases in Scandinavia and Eastern Europe has shown that the prevalence among Swedish children 13–14 years of age is 15% for asthma/wheezing, 17% for eczema and 26% for rhino-conjunctivitis [ 4 ]. It is well known that there are more individuals with perceived hypersensitivity than individuals with verified/doctor-diagnosed allergy. This is especially true when it comes to perceived food hypersensitivity with up to tenfold higher figures versus verified food allergy [ 5 , 6 ]. Prevalence figures for food hypersensitivity vary considerably (1–25%) with regard to study design, population of subjects [ 7 - 9 ] and country [ 7 , 8 ]. Research has demonstrated that allergic diseases have a negative impact on individuals' health-related quality of life (HRQL) and a number of studies describe HRQL-deteriorations in children and adults with asthma [ 10 - 12 ], eczema [ 13 - 15 ] and rhinitis [ 16 - 18 ]. Studies have also shown that allergy-associated physical and organ-related measures and tests do not always correlate with HRQL-scores [ 11 , 12 ]. Adverse reactions to food constitute an important part of allergy-associated problems, especially among children. Still, studies on food allergy and HRQL are scarce. However, parental perception of physical and psychosocial functioning, measured with the Children's Health Questionnaire (CHQ-PF50), has shown that childhood food allergy has a significant emotional impact on the parent and limits the family activities [ 19 ]. It has also been documented that, from a parental perspective, children with peanut allergy have significantly more disruption in their daily life compared with children with rheumatological disease, due to their children's risk of death [ 20 ]. Furthermore, peanut allergic children have been shown to report more anxiety about eating and more fear of an adverse event compared with children with diabetes mellitus [ 21 ]. Previous studies have shown that adolescent males have a higher prevalence of atopy than adolescent females [ 22 ] although there is a female dominance in self-reported allergic diseases [ 23 ]. Furthermore, the prevalence of asthma has been found to vary with age and sex, showing a male predominance before puberty that changes into a higher prevalence in females in adolescence [ 24 , 25 ]. Research in the allergy field is mainly focused on individuals with verified allergy and their suffering from these conditions, i.e. leaving out those with self-reported allergy-like conditions but with no doctor-diagnosis. Still, one can presume that perceived allergy could have an impact on the health-related quality of life (HRQL) and involve suffering, regardless of verifiable diagnosis. In order to obtain information about the extent to which adolescent females and males themselves experience allergy-like conditions and the impact of these conditions on their everyday life, the present study aimed to investigate the magnitude of self-reported allergy-like conditions in adolescence and to evaluate their HRQL. Special focus was put on food hypersensitivity as a specific allergy-like condition and on gender differences. Methods Subjects and procedure The present study involved adolescents at the senior level of the nine-year compulsory school and at the upper secondary school in a municipality in the south of Stockholm, Sweden. The socio-demographic distribution of the inhabitants in this municipality was slightly above in socio-economics and slightly below in number of immigrants compared with the country as a whole. A total of 2064 adolescents were registered in the schools at the relevant levels, all with the Swedish language as their school language. One week prior to starting the study (May 2003), an information letter outlining the purpose of the investigation, including an assurance of confidentiality and voluntary participation, was distributed to both the adolescents (n = 2064) and their parents. In connection with lessons at school, the teachers distributed questionnaires to the 1488 adolescents who were present at school. The instructions given by the teachers and the administration of the questionnaires were standardized. Two questionnaires were distributed together in one envelope, with the HRQL-questionnaire (se below) at the top. The adolescents themselves completed the questionnaires during that particular lesson. No other support was offered than the possibility to ask the teacher clarifying questions regarding the wording. After completion of the questionnaires, or in case of renouncing participation, each adolescent put the questionnaires into the envelope, sealed it, and handed it over to the teacher, who forwarded the envelopes to one of the authors (BM). The discrepancy between the number of registered adolescents (n = 2064) and the number, who were actually present when the data was collected (n = 1488), was partly due to the fact that it was close to the summer holiday and graduation and some adolescents attended activities outside school. The school records confirmed their absences. As 37 adolescents had not properly filled in the questionnaires, those were excluded from the study. In total 1451 questionnaires (97%) remained for data analysis. Age ranged between 13 and 21 years (mean 16.2 years), with 99% of the adolescents between 14 and 20 years. In total 696 females and 716 males had reported their gender. For 39 adolescents the gender was not reported. The terminology used in this study is according to ISAAC (The International Study of Asthma and Allergies in Childhood) [ 3 ] and EAACI (The European Academy of Allergology and Clinical Immunology) position paper [ 26 ] (Table 1 ). Table 1 Terminology and definitions 1 Allergy-like conditions Hypersensitivity Allergic diseases Asthma/wheezing Eczema/rash Rhino-conjunctivitis Self-reported hypersensitivity, allergy or intolerance to food or other defined environmental substances. Self-reported asthma, wheezing or whistling in the chest. Self-reported recurrent eczema or itchy rash for at least six months. Self-reported sneezing, runny nose, blocked nose or itchy-watery eyes without a cold. 1 Terminology according to ISAAC [3] and EAACI position paper [26]. Questionnaires A study-specific questionnaire was used to evaluate the magnitude of allergy-like conditions during the past twelve months and to evaluate the frequency of allergy testing. The questionnaire, devised by the authors, was based on relevant literature on similar subjects [ 3 ]. Prior to the data collection, a pilot test of the questionnaire was performed with fourteen adolescents, who were not included in the present study, and subsequently minor lexical adjustments were made. Some of the questions included were as follows: "Are you allergic or hypersensitive to any of the following?" (Possible answers: furred animal, pollen, dust/mite, food, nickel, other substances: Yes/No.) "If you are allergic or hypersensitive to any food items, what reactions or symptoms do you perceive? (Possible answers: not allergic or hypersensitive, eczema, rash, eye-nose-symptoms, itchy mouth, breathing difficulties, vomiting-diarrhoea-stomach ache, allergic chock, other)." "Have you had asthma, wheezing or whistling in the chest in the past 12 months ? (Yes/No)" " In the past 12 months , have you had recurrent eczema or itchy rash for at least 6 months? (Yes/No)" " In the past 12 months , have you had a problem with sneezing, or a runny, or a blocked nose when you did not have a cold? (Yes/No)" " In the past 12 months , have you had a problem with itchy-watery eyes when you did not have a cold? (Yes/No)" The questions concerning allergic diseases were taken verbatim from the ISAAC study [ 3 ]. The generic instrument Medical Outcome Trust Short Form 36 Health Survey (SF-36) was used to measure HRQL. SF-36 is a well-validated and reliable measure of HRQL in adults and adolescents from the age of 14, and normative data are available for the Swedish population [ 27 ]. The SF-36 consists of 36 items, which refer to eight health scales related to daily life activities. Four of these health scales represent the physical dimension and the remaining four health scales represent the mental dimension of the HRQL concept. The scale scores range from 0 to 100, with 100 representing the highest level of functioning and well being [ 27 , 28 ]. The footnote of Table 4 conveys a summary of the contents in the SF-36 health scales. Table 4 Comparison of SF-36 scores between adolescents with and without allergy-like conditions and between females and males with allergy-like conditions Allergy-like conditions No such conditions Females with allergy-like conditions Males with allergy-like conditions N = 931 N = 520 N = 501 N = 412 SF-36 health scales 1 Mean SD Mean SD p -value Mean SD Mean SD p -value Physical dimension Physical functioning (PF) 91.1 16.4 91.7 19.1 NS 91.1 13.8 91.2 18.8 NS Role functioning-physical (RP) 75.7 31.3 83.2 27.2 <0.001 73.6 31.5 78.4 30.4 <0.05 Bodily pain (BP) 71.3 23.6 81.2 20.3 <0.001 67.9 24.1 75.3 22.4 <0.001 General health (GH) 69.6 20.5 80.8 16.7 <0.001 66.3 21.1 73.5 19.2 <0.001 Mental dimension Vitality (VT) 53.0 21.0 62.2 21.0 <0.001 50.2 20.5 56.4 21.2 <0.001 Social functioning (SF) 81.3 21.6 86.9 18.9 <0.001 79.1 22.0 84.1 20.8 <0.001 Role functioning-emotional (RE) 65.4 40.3 75.4 36.8 <0.001 58.2 42.1 73.7 36.3 <0.001 Mental health (MH) 67.3 19.6 74.9 19.1 <0.001 62.7 20.2 72.8 17.4 <0.001 1 Summary of contents of SF-36 health scales: Physical dimension : PF = Ability to perform daily physical activities, e. g. walking, running, lifting, and other moderate physical efforts; RP = Extent to which physical health limits work/daily activities; BP = Intensity of pain and its interference with normal activities; GH = Personal evaluation of general health status, presently and in the future. Mental dimension : VT = Personal evaluation of energy, tiredness, etc; SF = Extent to which physical health or emotional problems interfere with normal social activities; RE = Extent to which emotional problems limit work/daily activities; MH = Personal evaluation of mental health, including anxiety, depression, and general positive and negative affects [27, 28]. Statistical analyses For statistical analyses the SPSS 11.0 program was used. SF-36 data was processed by means of an SPSS program provided by the HRQL-group at the University of Gothenburg, Sweden [ 27 ]. Internal consistency of the SF-36 health scales was tested by means of Cronbach's alpha and in this study ranged between 0.72 and 0.91, with the exception of the scale for social functioning (SF) showing 0.61. To test differences in proportions between groups, the Chi-square test was used. The Student's t-test and, when appropriate, the one-way analysis of variance (ANOVA) were used to assess differences in means between groups. A p-value <0.05 was considered to be statistically significant. Ethical approval This study was approved by the Director of School Administration in Tyresö municipality and by the research ethics committee at Huddinge University Hospital. Results Allergy-like conditions As shown in Table 2 , a total of 931 adolescents (64%) reported that they suffered from some kind of allergy-like condition, i.e. either hypersensitivity to defined substances (46%) or allergic diseases (51%) (definitions given in Table 1 ). In particular, 19% of the whole group (24% of the females and 14% of the males) reported that they reacted to some food (Table 2 ). Table 2 Self-reported allergy-like conditions among the 1451 adolescents Total Females Males N = 1451 1 N = 696 N = 716 p -values N (%) N (%) N (%) Allergy-like conditions, totals 931 (64) 501 (72) 412 (58) <0.001 Hypersensitivity to defined substances 663 (46) 364 (52) 282 (39) < 0.001 pollen 335 (23) 161 (23) 162 (23) NS food 271 (19) 165 (24) 98 (14) <0.001 furred animal 234 (16) 117 (17) 110 (15) NS dust/mite 194 (13) 114 (16) 75 (11) <0.001 nickel 169 (12) 132 (19) 32 (5) <0.001 other substances 2 94 (7) 62 (9) 31 (4) <0.001 Allergic diseases 739 (51) 408 (59) 319 (45) < 0.001 asthma/wheezing 231 (16) 156 (22) 72 (10) <0.001 eczema/rash 286 (20) 178 (26) 105 (15) <0.001 rhino-conjunctivitis 546 (38) 287 (41) 248 (35) <0.05 1 Gender unknown n = 39. 2 Offending substances reported: insects (n = 15), drugs (n = 14), detergents (n = 9), mildew (n = 8), perfume (n = 8) and smoke (n = 5). Substances reported for less than five persons each are not specified. The adolescents suffered to a large extent from complex allergy-like conditions, i.e. hypersensitivity to multiple offending substances and/or allergic diseases. Fifty per cent of those with hypersensitivity (n = 334/663) reported more than one kind of offending substance and 35% of those who reported allergic diseases (n = 260/739) reported more than one type of disease. Fifty-one per cent of those with allergy-like conditions (n = 471/931) reported both hypersensitivity and allergic disease. Significantly more females than males reported allergy-like conditions (Table 2 ). In addition, hypersensitivity to more than one type of offending substance was more frequently reported by females than by males (55% and 43%, respectively, p < 0.01). Females reported also to a greater extent more than one kind of allergic disease (40% and 29%, respectively, p < 0.001). Out of the 931 adolescents with allergy-like conditions, 404 (43%) reported that they had been tested for allergy by means of blood test or skin prick test (results not shown). For the majority (n = 324) of these adolescents with self-reported allergy testing, the tests had been performed during their school age years. Sixty-one per cent of those tested (n = 246/404) reported that the test results verified allergy. This figure corresponds to a 17% prevalence of self-reported verified allergy within the whole population of 1451 adolescents. Food hypersensitivity In the group of 271 adolescents reporting food hypersensitivity, 139 (51%) reported allergy test results that verified some kind of allergy, albeit not necessarily food allergy (results not shown). The most common food-induced symptoms were OAS (Oral Allergy Syndrome)-like symptoms (Table 3 ), i.e. itching and swelling of the lips and oral cavity, reported by 52% of the adolescents, similarly reported by females and males. Significantly more females than males reported food-induced symptoms from the skin (p < 0.001) and from the gastro-intestinal tract (p < 0.05). Table 3 Food-induced symptoms, hypersensitivity to other substances besides food and allergic diseases among adolescents with food hypersensitivity Adolescents with food hypersensitivity Total Females Males N = 271 1 N = 165 N = 98 p -values N (%) N (%) N (%) Food-induced symptoms 271 (100) 165 (100) 98 (100) OAS 2 -like symptoms 140 (52) 83 (50) 55 (56) NS skin symptoms 81 (30) 62 (38) 16 (16) <0.001 gastro-intestinal symptoms 76 (28) 55 (33) 20 (20) <0.05 breathing difficulties 67 (25) 38 (23) 29 (30) NS eye/nose symptoms 35 (13) 20 (12) 15 (15) NS anaphylaxis 32 (12) 21 (13) 11 (11) NS Hypersensitivity to defined substances 208 (77) 128 (78) 72 (74) NS pollen 141 (52) 79 (48) 56 (57) NS furred animals 125 (46) 67 (41) 53 (54) <0.05 dust/mite 90 (33) 56 (34) 33 (34) NS nickel 64 (24) 54 (33) 7 (7) <0.001 other substances 3 26 (10) 20 (12) 6 (6) NS Allergic diseases 210 (78) 135 (82) 70 (71) <0.05 asthma/wheezing 88 (33) 61 (37) 24 (25) <0.05 eczema/rash 93 (34) 66 (40) 25 (26) <0.05 rhino-conjunctivitis 167 (62) 103 (62) 58 (59) NS 1 Gender unknown n = 8. 2 OAS = Oral Allergy Syndrome 3 The substances reported for at least three persons each were: mildew (n = 4), drugs (n = 3), insects (n = 3) and perfume (n = 3). Offending food items reported were: nuts (39%), fruit and berries (35%), peanut (32%), almond (22%), tomato (19%), carrot (16%), lactose (12%), vegetables (10%), shellfish (9%), soy (7%), milk (7%), fish (5%) and egg (5%). Substances reported for less than five per cent of the 271 adolescents are not specified. For two food items there were significant gender differences. The offending food items fruit and berries were more commonly reported by females (44% and 24% respectively, p < 0.001) and peanut was more commonly reported by males (43% and 27% respectively, p < 0.01). A total of 63 adolescents reported food as the only offending substance. However, the majority of the 271 adolescents who reported food hypersensitivity suffered from complex allergy-like conditions that included additional offending substances besides food (77%) as well as allergic diseases (78%). In this group of food hypersensitive adolescents there were significantly more males than females who reported hypersensitivity to furred animals and as regards hypersensitivity to nickel the result was reverse (Table 3 ). Allergic diseases such as asthma/wheezing and eczema/rash were also significantly more often reported by the females (Table 3 ). Health-related quality of life Adolescents with allergy-like conditions scored significantly lower on seven of the eight SF-36 health scales compared with adolescents without such conditions (Table 4 ). The adolescents with allergy-like conditions scored similar on the health scales whether they had reported verified allergy or not (results not shown). Moreover, Table 4 also demonstrates gender differences among the adolescents with allergy-like conditions. Females reported significantly lower SF-36 scores in seven of the eight health scales. When comparing females with and females without allergy-like conditions, the former group scored significantly lower on all eight scales (Figure 1a ). For the males, statistically significant differences were seen for all health scales, except for physical functioning (PF) and role functioning-physical (RP) (Figure 1b ). Figure 1 Comparison of SF-36 scores between: a) females with allergy-like conditions and females with no such conditions, and b) males with allergy-like conditions and males with no such conditions. ( Physical dimension: PF, physical functioning; RP, role functioning-physical; BP, bodily pain; GH, general health. Mental dimension: VT, vitality; SF, social functioning; SE, role functioning-emotional; MH, mental health.) Figure 2 shows comparisons between food hypersensitive adolescents, females and males, with or without other allergy-like conditions. Females with food hypersensitivity scored significantly lower on three health scales (BP, GH and SF) compared with females with other allergy-like conditions (Figure 2a ). A corresponding comparison for the males showed no HRQL-deterioration for the food hypersensitive males (Figure 2b ). Figure 2 Comparison of SF-36 scores between: a) females with food hypersensitivity and females with other allergy-like conditions, b) males with food hypersensitivity and males with other allergy-like conditions, and c) adolescents with food hypersensitivity with or without allergic diseases. ( Physical dimension: PF, physical functioning; RP, role functioning-physical; BP, bodily pain; GH, general health. Mental dimension: VT, vitality; SF, social functioning; SE, role functioning-emotional; MH, mental health.) When comparing food hypersensitive adolescents who reported allergic diseases (i.e. asthma/wheezing, eczema/rash and rhino-conjunctivitis) (n = 210/271) to those food hypersensitive adolescents who did not report such conditions (n = 61/271), the groups showed a similar pattern as regards the mental dimension scales of the SF-36, i.e. no statistically significant differences were found. As regards the physical dimension scales, the food hypersensitive adolescents who also reported allergic diseases scored significantly lower on BP (bodily pain) and GH (general health) (Figure 2c ). A comparison within the whole group of adolescents with allergy-like conditions (n = 931), i.e. between those who reported only hypersensitivity to any defined environmental substances (A), those who reported only allergic diseases (B), and those who reported both (C), showed that the three groups scored similar on the four health scales representing the mental dimension of the SF-36. As regards the physical dimension, adolescents with allergic diseases only (B) or in combination with hypersensitivity (C) scored lower on the health scales for bodily pain (BP) and general health (GH) compared with those with only hypersensitivity to defined substances (A) (Figure 3 ). Figure 3 Comparison of SF-36 scores between adolescents with (A) only hypersensitivity to defined substances, (B) only allergic diseases and (C) both (p < 0.05: BP A > B and C; GH A > C). ( Physical dimension: PF, physical functioning; RP, role functioning-physical; BP, bodily pain; GH, general health. Mental dimension: VT, vitality; SF, social functioning; SE, role functioning-emotional; MH, mental health.) Discussion The present study focuses on self-reported allergy-like conditions among adolescents, in particular food hypersensitivity. The results show that as many as 64% of the adolescents reported allergy-like conditions, of which nearly one third reported food hypersensitivity. In most cases the allergy-like conditions were complex, i.e. included hypersensitivity to multiple offending substances and/or allergic diseases. Compared with the prevalence for Swedish children 13–14 years of age, shown in an ISAAC-study [ 4 ], the adolescents (13–21 years) in the present study reported about the same prevalence of asthma/wheezing (15% and 16%, respectively) and of eczema (17% and 20%, respectively), but a higher prevalence of rhino-conjunctivitis (26% and 38%, respectively). The differences in prevalence of rhino-conjunctivitis between these studies might to some extent be explained by the fact that different age groups were sampled. Furthermore, the referred ISAAC-study was performed at least six years earlier than the present one. During this time span the allergy problem has been a growing concern among both children and adults and the rates may have risen [ 1 , 2 ]. The adolescents with allergy-like conditions generally showed significantly lower HRQL than adolescents without such conditions. Previous studies have shown that doctor-diagnosed asthma, eczema, and rhinitis have negative impacts on HRQL [ 10 - 18 ]. In the present study we have shown that those who reported that they suffered from these allergic diseases scored low on SF-36, regardless whether the diseases were verified by medical expertise or not. Furthermore, also the adolescents who reported hypersensitivity without having such diseases, scored low on SF-36, especially on the scales concerning mental health and emotional-social functioning. This is in accordance with previous findings in children with doctor-diagnosed peanut allergy [ 20 , 21 ]. Living with constant vigilance, uncertainties and risks of adverse reactions, is likely to influence HRQL in adolescents in a negative way. The question of co-morbidity has been discussed [ 29 ], as it is not always possible to grasp what component(s) of a complex allergy-like condition affects the HRQL. Furthermore, one has to consider the possibility that the HRQL-deteriorations in these adolescents may not be a direct effect of their allergy-like conditions, but related to an overall poorer general state of health. The presence of poor social, mental or somatic health may increase the perception of allergy-like conditions. Still, irrespective of what the underlying causes are, it is evident that adolescents who experience allergy-like conditions also experience HRQL-deterioration. In most of the comparisons between different subgroups of adolescents with and without allergy-like conditions, the SF-36 health scale for physical functioning (PF) showed no significant difference. This is noteworthy, as the physical parameter often is in focus when health-care professionals assess an individual's state of health. However, it has been previously shown that in patients with asthma/wheezing, the link between lung function and HRQL is weak [ 11 , 12 ] and the results of the present study indicate that the link between physical parameters and the HRQL may be weak also in other kinds of allergy-like conditions. Hypersensitivity may perhaps be considered as a practical, emotional and psychosocial health problem – not primarily a physical. It has been shown, however, that HRQL-deterioration among peanut allergic children is related to anxiety and fear for adverse reactions [ 20 , 21 ]. Moreover, the adolescents with a non-severe chronic allergic disease may be well adapted to the disease, physiologically and/or psychologically, so that the disease as such has no significant impact on their physical quality of life. In the present study we show that in adolescence, significantly more females than males experienced not just asthma/wheezing but also eczema/rash, rhino-conjunctivitis, and hypersensitivity to food, dust/mite and nickel. The females presented more complex allergy-like conditions compared with the males. In addition, females with allergy-like conditions showed more severe HRQL-deterioration compared with the males. It is known that female gender among adults implies a larger report of burden of health problems in general [ 30 ] and SF-36 Swedish normative data show that females 15–19 years of age score lower compared with males in this age group [ 27 ]. Thus, the gender differences with respect to allergy-like conditions were in accordance with a known pattern within the health-and-gender-field. Biological, hormonal and socio-cultural explanations to gender differences in asthma and allergy have been discussed [ 24 , 31 , 32 ] as well as possible gender biased diagnostic practices [ 33 - 35 ] such as underdiagnosis of females due to gender differences in disease severity. Further research in this area is needed so that health-care professionals, school personnel, relatives and friends can improve their care and support given to both females and males suffering from allergy-like conditions. Seventeen per cent of the adolescents, of whom the most part were tested during school age, reported positive allergy test results. It can be assumed that there were some additional adolescents with doctor-diagnosed allergy but without verifying test results. Thus, the total of adolescents doctor-diagnosed as having allergy may well be more than 17%. However, in the present study the focus was on self-reported (perceived or verified) allergy-like conditions. The mean SF-36 scores did not differ whether the adolescents reported objectively verified allergy or not. The lack of difference in HRQL was not surprising as a diagnostic test that verifies allergy says nothing about the individuals experience or the severity of the allergic condition. Food hypersensitivity Most food allergies are something that children outgrow [ 36 ] and adverse reactions to food should consequently be a problem that decreases with age. The prevalence of food allergy is estimated to 5–8% in children and 1–2% in adults [ 37 ]. However, figures of perceived reactions to food may well be over 20% [ 6 ]. In the present study, 19% of the adolescents did report adverse reactions to food. This high figure may be explained by the fact that the reactions were self-perceived and not necessarily doctor-diagnosed and that the figure includes all kinds of food hypersensitivity regardless of the mechanisms behind the adverse reactions. The existing diagnostic methods for food hypersensitivity are not sufficient and the underlying mechanisms of perceived food hypersensitivity are not always known [ 38 ]. Nevertheless, it is noteworthy that almost every fifth adolescent perceive herself or himself as food hypersensitive and subsequently avoid certain food items. Food items constituted a considerable part of the offending substances reported in this study and up to 41% of all adolescents with hypersensitivity specified at least one food item as an offending substance. Professional counselling and diagnostic procedures may to some extent be able to help the adolescents to reduce their food avoidance. Yet, this kind of perceived allergy-like condition – regardless of what the underlying mechanisms were – was evidently associated with HRQL-deterioration and the adolescents' experiences deserve sincere attention. Previous research show that food allergy in a child implies disruption in daily life and HRQL-deterioration for both the child and the family [ 19 - 21 ]. A pattern emerged in this group of food hypersensitive adolescents, showing a great deal of hypersensitivity to pollen, rhino-conjunctivitis and OAS-like symptoms, which is in accordance with the well known cross-reactivity of pollen and food allergens [ 39 ]. Significantly more males than females reported additional hypersensitivity to furred animals. To our knowledge this has not been reported before but may be associated with the higher atopy prevalence among males [ 22 ]. The results also pointed to a possible gender difference in what offending food items females and males, respectively, experience. Further research is needed to elucidate such a phenomenon. More than half of the adolescents with food hypersensitivity reported positive allergy tests, but as a consequence of how the questions in the survey were asked, it is not known if they were verified as allergic specifically to food. However, a vast majority of the food hypersensitive adolescents did undoubtedly suffer from complex allergy or allergy-like conditions, which included multiple types of hypersensitivity and/or allergic diseases. This should require competence in health-care when trying to tackle the adolescents' multifaceted problems, including food hypersensitivity. Limitations The extensive number of adolescents who participated in the present survey, together with a very high answer rate, makes the results reliable. However, the sample of adolescents used in this study may limit the generalizability as the socio-demographic distribution in this particular municipality was slightly above in socio-economics and slightly below in number of immigrants compared with the country as a whole. Additional studies are warranted to confirm the results. The results of the present study emanate exclusively from adolescents' statements. There is always a risk that the respondents involved do not correctly remember things that were asked for in a questionnaire. However, our main interest was in adolescents' experiences of allergy-like conditions during the past twelve months and daily functioning during the past four weeks. Remembering correctly over a longer period of time was only of importance in questions about allergy testing. It seems likely that the adolescents would remember such events as skin prick tests or blood tests during their school age, although tests carried out in early childhood might have been unknown or forgotten. The magnitude of allergic diseases was measured by means of ISAAC-questions. The ISAAC questionnaire, which asks for events during the past 12 months, has been used in many countries all over the world and for many years. Its results constitute basis for international comparisons and it can be considered well validated. However, hypersensitivity items are not included in the ISAAC questionnaire. The questions in the present study about hypersensitivity were developed specifically for the present study and a pilot test was performed. Only lexical adjustments were needed. It could be discussed if the fact that the questionnaires asked for events during two distinct periods: 12 months (allergy-like conditions/ISAAC-questions) and 4 weeks (daily functioning/SF-36) might have biased the present results. It is also possible that an allergy-specific HRQL measure instrument would give another picture of the physical scale in relation to allergy-like conditions. Conclusions The prevalence of self-reported allergy-like conditions among adolescents was high – 64%. Significantly more females than males reported allergy-like conditions and females with allergy-like conditions showed more severe HRQL-deterioration compared with males with such conditions. The results indicate a need to consider not merely physical consequences but also the psychosocial quality of life impact of allergy-like conditions among both females and males. Further research is needed to elucidate the reasons behind the gender differences in this area. Most adolescents suffered from complex allergy-like conditions that included multiple types of hypersensitivity and/or allergic diseases. Food items constituted a considerable part of the offending substances reported. When attending to a young individual who suffers from an allergy-like condition, the whole syndrome should be in focus – not only one specific offending substance, or one specific hypersensitivity or allergic disease. A team approach accompanied by an understanding of how allergy-like conditions impair the quality of life may improve the management of the adolescent's health problems, both in health-care services and in schools. Authors' contributions BM and GN conceived of the study. All authors made substantial contributions to conception, planning and design. BM carried out the acquisition, analysis and interpretation of data. BM drafted the manuscript. GN and SA have been involved in revising it critically for important intellectual content. All authors read and approved the final manuscript.

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509406

Emerin Caps the Pointed End of Actin Filaments: Evidence for an Actin Cortical Network at the Nuclear Inner Membrane

X-linked Emery-Dreifuss muscular dystrophy is caused by loss of emerin, a LEM-domain protein of the nuclear inner membrane. To better understand emerin function, we used affinity chromatography to purify emerin-binding proteins from nuclear extracts of HeLa cells. Complexes that included actin, αII-spectrin and additional proteins, bound specifically to emerin. Actin polymerization assays in the presence or absence of gelsolin or capping protein showed that emerin binds and stabilizes the pointed end of actin filaments, increasing the actin polymerization rate 4- to 12-fold. We propose that emerin contributes to the formation of an actin-based cortical network at the nuclear inner membrane, conceptually analogous to the actin cortical network at the plasma membrane. Thus, in addition to disrupting transcription factors that bind emerin, loss of emerin may destabilize nuclear envelope architecture by weakening a nuclear actin network.

Introduction Emery-Dreifuss muscular dystrophy (EDMD) is inherited through mutations in either of two different genes: LMNA, encoding A-type lamins, and STA, which encodes a nuclear membrane protein named emerin ( Nagano et al. 1996 ; Emery 2000 ; Bengtsson and Wilson 2004 ). Lamin filaments and emerin interact at the nuclear inner membrane ( Burke and Stewart 2002 ; Holaska et al. 2002 ). Together, emerin and lamin A form stable tertiary complexes with other binding partners in vitro ( Holaska et al. 2003 ), suggesting that emerin and lamins together provide a structural foundation for oligomeric protein complexes. Mutations in emerin cause the X-linked recessive form of EDMD ( Bione et al. 1995 ; Bonne et al. 2003 ). Both emerin and lamin A are expressed in most cells, but EDMD disease strikes specific tissues: skeletal muscles, major tendons, and the cardiac conduction system. To explain the tissue specificity of EDMD, it was proposed that emerin might have tissue-specific binding partners such as transcription factors and signaling molecules that regulate gene expression ( Wilson 2000 ; Bonne et al. 2003 ; Östlund and Worman 2003 ). There is growing evidence to support “gene expression” models for emerin, as discussed further below. However, a second model, not mutually exclusive, proposes that emerin helps maintain the structural integrity of the nuclear envelope. According to structural models, loss of emerin selectively disrupts tissues under high mechanical stress, such as skeletal muscle and tendons ( Bonne et al. 2003 ; Östlund and Worman 2003 ). Although this model fails to explain the cardiac conduction phenotype of EDMD, it is consistent with structural defects (aberrant shape and nuclear envelope herniations) seen in nuclei from EDMD patients ( Fidzianska and Hausmanowa-Petrusewicz 2003 ) and in a subset of patients with other diseases linked to mutations in LMNA (“laminopathies”; Holaska et al. 2002 ; Östlund and Worman 2003 ). Whereas structural and mechanical roles are expected for lamins, which form nuclear intermediate filaments, mechanical roles for emerin have not been investigated. Emerin is detected in most human cells tested, except the nonmyocytes of the heart ( Manilal et al. 1996 ). In Caenorhabditis elegans emerin is expressed ubiquitously ( Lee et al. 2000 ; Gruenbaum et al. 2002 ). Emerin belongs to the LEM-domain family of proteins, which are defined by an approximately 40-residue folded domain known as the LEM domain. In vertebrates, other family members include LAP2β and MAN1 at the nuclear inner membrane ( Dechat et al. 2000 ; Lin et al. 2000 ; Cohen et al. 2001 ), LAP2α in the nuclear interior ( Dechat et al. 2000 ), and at least three additional uncharacterized LEM-domain proteins ( Lee and Wilson 2004 ). A major shared function of all characterized LEM-domain proteins is their binding (via the LEM domain) to a small protein named barrier-to-autointegration factor (BAF; reviewed by Segura-Totten and Wilson 2004 ). BAF is a highly conserved chromatin protein essential for cell viability ( Zheng et al. 2000 ), with direct roles in higher order chromatin structure and nuclear assembly ( Haraguchi et al. 2001 ; Segura-Totten et al. 2002 ), and gene regulation ( Wang et al. 2002 ; Holaska et al. 2003 ). Supporting gene regulation models for EDMD, emerin binds directly to BAF and two other transcription repressors, germ cell-less (GCL; Holaska et al. 2003 ) and Btf ( Haraguchi et al. 2004 ) as well as an mRNA-splicing factor named YT521-B ( Wilkinson et al. 2003 ). Interestingly, GCL and LAP2β, a LEM-domain protein closely related to emerin, comediate transcription repression in vivo ( Nili et al. 2001 ). On the other hand, emerin also has a growing number of structural or anchoring partners, including a spectrin-repeat (SR) membrane protein named nesprin-1α ( Mislow et al. 2002a , 2002b ), lamins A and C ( Clements et al. 2000 ; Lee et al. 2001 ; Sakaki et al. 2001 ), and lamin B ( Dreger et al. 2002 ). Lamins form type-V intermediate filaments that are critical for the integrity of the nucleus and confer unique elasticity and incompressibility properties to the nuclear envelope ( Dahl et al. 2004 ). Nuclear morphology and lamina architecture are disrupted in a fraction of cells that express disease-causing missense mutations in A-type lamins ( Östlund and Worman 2003 ). However, the line between gene expression and mechanical models for disease has become blurred. For example, the subnuclear localization of Rb, a transcription and cell-fate regulator, depends on both LAP2α and lamin A, since Rb is mislocalized in cells that either lack A-type lamins ( Johnson et al. 2004 ) or express disease-causing lamin-A mutations ( Markiewicz et al. 2002 ). A second putative anchoring partner for emerin is nesprin-1α, an integral nuclear inner-membrane protein with seven SR domains ( Zhang et al. 2001 ; Mislow et al. 2002b ). Each SR domain consists of approximately 100 residues and folds into a tightly packed triple α-helical structure ( Bennett and Baines 2001 ). Tandem SR domains, as seen in nesprin-1α, form a rigid, elongated tertiary structure ( Djinovic-Carugo et al. 2002 ). More important, SR domains provide binding sites for other proteins, the specificity of which is determined by exposed residues ( Bennett and Baines 2001 ). SR domains 1–7 (and particularly domains 1–5) of nesprin-1α mediate high-affinity binding to emerin ( Mislow et al. 2002a ). Interestingly, SR domains 5–7 of nesprin-1α bind directly to lamin A in vitro, suggesting that nesprin-1α, lamin A, and emerin might form stable tertiary complexes. Such complexes have the potential to stabilize lamin filaments at the nuclear envelope, in addition to anchoring and spacing emerin. Notably, both emerin and lamin A also bind G-actin in vitro ( Sasseville and Langelier 1998 ; Fairley et al. 1999 ). Actin binds two regions in the lamin-A tail ( Zastrow et al. 2004 ). Both α- and β-actin bind emerin in vitro, and emerin coimmunoprecipitates with actin from cell lysates ( Fairley et al. 1999 ; Lattanzi et al. 2003 ). The significance of these findings was unclear, in part because nuclear actin has been both documented and debated for over 35 y ( Pederson and Aebi 2002 ). However there is a growing consensus that nuclear actin is no artifact ( Pederson and Aebi 2002 ; Bettinger et al. 2004 ). Both α- and β-actin have been shown, definitively, to reside in the nucleus ( Scheer et al. 1984 ; Gonsior et al. 1999 ; Olave et al. 2002 ; Lattanzi et al. 2003 ) and to form short filaments in the nucleus ( Clark and Rosenbaum 1979 ). Actin and actin-related proteins (Arps) are required for chromatin remodeling and transcription ( Olave et al. 2002 ; Percipalle et al. 2003 ). Also interesting is that polymerase II–dependent mRNA transcription requires a nuclear-specific myosin I motor (nuclear myosin I; Nowak et al. 1997 ; Pestic-Dragovich et al. 2000 ). Thus, actin probably has a variety of roles in the nucleus. To test the hypothesis that emerin forms multiprotein complexes in vivo, we affinity-purified emerin-binding proteins from nuclear extracts of HeLa cells. We identified actin itself plus several actin-binding proteins as bona fide emerin-associated proteins, and we further discovered that emerin stimulates actin polymerization in vitro by binding and stabilizing the pointed end of growing filaments. These results suggest that emerin contributes to the formation of an actin cortical network at the nuclear inner membrane. Results We used affinity chromatography to purify emerin-binding complexes from HeLa nuclear extract; as the negative control, beads were conjugated to bovine serum albumin (BSA). Mass spectrometry (data not shown) and Western blotting identified β-actin as a major emerin-binding protein ( Figure 1 A). Six other proteins, including nuclear-enriched αII-spectrin, were also identified and will be reported in full elsewhere (J. M. H. and K. L. W., unpublished data). Consistent with previous reports ( Fairley et al. 1999 ; Lattanzi et al. 2003 ), antibodies specific for emerin coprecipitated actin from HeLa cell nuclear lysates, as shown by Western blotting with immune serum ( Figure 1 B, Im). Only background levels of actin were precipitated by preimmune sera ( Figure 1 B, PI). These findings led us to hypothesize that emerin might bind filamentous actin (F-actin). Figure 1 Affinity Purification of Emerin-Associated Proteins (A) Immunoblot of HeLa nuclear lysate proteins (L), or proteins affinity-purified using either BSA beads or emerin beads (see Materials and Methods ), probed with antibody against actin. (B) HeLa nuclear lysate proteins (L) were immunoprecipitated using either immune (Im) or preimmune (PI) serum 2999 against emerin, resolved by SDS-PAGE, and Western blotted using antibodies specific for actin (upper panel) or emerin (lower panel), in succession. (C) Cosedimentation assays using F-actin and purified, recombinant wild-type emerin (residues 1–222). G-actin (2 μM) was polymerized and then incubated in the absence or presence of 2 μM emerin. Emerin was incubated alone in polymerization buffer as a negative control. After 30 min samples were centrifuged 1 h at 100,000 g, resolved by SDS-PAGE, and stained with Coomassie blue. L, load (100%); S, supernatant (100%); P, pellet (100%). (D) F-actin column was used to determine the affinity of F-actin for emerin. The K d was 480 nM for the experiment shown; range was 300–500 nM, n = 8. (E) Binding of wild-type (WT) or mutant emerin protein to F-actin beads. Recombinant emerin proteins were incubated with F-actin beads, and bound emerins were eluted with SDS-PAGE sample buffer, resolved by SDS-PAGE, blotted, and probed with antibodies against emerin (“bound”; all emerin mutants are recognized by this antibody; Lee et al. 2001 ; Holaska et al. 2003 ). The input amounts (10%) of each emerin mutant (“load”) were visualized either by immunoblotting (top row, top panel) or Coomassie staining (top row, bottom panel). (F) Domains in emerin required for binding to BAF, lamin A, transcription repressor GCL, or actin ( Lee et al. 2001 ; Holaska et al. 2003 ; present study). Asterisks indicate EDMD disease-causing mutations. Emerin Binds F-Actin with High Affinity Emerin was first tested for binding to F-actin in a cosedimentation assay. Actin filaments were incubated 30 min in the presence or absence of recombinant emerin (4 μM) and then pelleted at 100,000 g. Approximately 75% of input emerin pelleted in the presence of F-actin, compared to 15% in the absence of F-actin ( Figure 1 C), demonstrating that emerin binds polymerized actin in vitro. The stoichiometry of this interaction was one emerin molecule per approximately 300 actin monomers, demonstrating that emerin binds actin filaments with an average length of 0.9 μm (data not shown). Emerin binds F-actin with high affinity, as determined by binding to an F-actin column (K d = 480 nM, range = 300–500 nM, n = 8; Figure 1 D). The F-actin columns were also used to screen selected emerin mutants for binding to F-actin. Wild-type emerin and EDMD disease-causing mutants S54F and P183H, and alanine substitution mutant m196 (Ser 196 Ser 197 to Ala 196 Ala 197 ; Holaska et al. 2003 ), bound efficiently to an F-actin column, whereas 12 other tested mutants, including EDMD disease-causing mutant Q133H, showed no significant binding to F-actin ( Figure 1 E). Similar results were seen in coimmunoprecipitation assays using antibodies against actin to immunoprecipitate F-actin in the presence of recombinant wild-type or mutant emerin proteins (data not shown). Fifteen additional emerin missense mutants, including LEM-domain mutants, were tested in blot overlay assays; mutants m11, m24, m30, m40, m207, m214, and m217 bound detectably to actin, whereas no significant binding was detected for mutants m45A, m45E, m61, m141, m145, m161, and m206 (data not shown; see Holaska et al. 2003 for details of mutations). Thus, three independent assays all showed that emerin binds F-actin. Furthermore, based on the positions of missense mutations that blocked binding to F-actin, this recognition involved almost the entire nucleoplasmic domain of emerin, with the notable exception of the LEM-domain ( Figure 1 F). The putative actin-binding domain in emerin overlaps with both the lamin- and repressor-binding (GCL) domains described previously ( Holaska et al. 2003 ). Emerin Regulates Actin Polymerization The above results suggested that in vivo emerin might (a) use actin filaments as anchors, (b) stabilize F-actin networks, or (c) actively influence actin dynamics. To test these models, we first used reactions containing 5% pyrene-labeled actin (final actin concentration, 2 μM) to determine if emerin influenced actin polymerization in vitro. Results were graphed as the rate of emerin-induced polymerization (R) divided by the control rate (cR; rate of actin polymerization in the absence of emerin). At concentrations ranging from 0.1 to 4.4 μM, emerin increased the rate of pyrene–actin polymerization 4-fold (mean = 6.2 ± 2.2, n = 32; one experiment is shown in Figure 2 A). These experiments also yielded an equilibrium affinity of 420 nM ( Figure 2 A), consistent with our previous results (480 nM; see Figure 1 D). Figure 2 Emerin Stimulates Actin Polymerization (A) Graph of a representative experiment ( n = 32) showing that emerin increases the rate of actin polymerization 4-fold. R, rate of polymerization in the presence of emerin; cR, control rate of polymerization (actin alone). These data also yielded an equilibrium binding affinity of emerin for actin of 420 nM. (B) Representative graph ( n = 17) in which each recombinant emerin mutant protein (1.0 μM) was added to 2.0 μM G-actin, and polymerization rates were calculated. R, rate of polymerization in the presence of emerin; cR, control rate of polymerization (actin alone). Stars indicate EDMD disease-causing mutations. (C) Critical concentration assays were performed in the presence or absence of 625 nM emerin. Actin was polymerized in the absence (barbed-end growth) or presence of 5 nM gelsolin–actin seeds (pointed-end growth) for 16 h at room temperature. Barbed-end growth with (□) or without (▪) emerin. Pointed-end growth with (○) or without (•) emerin. Actin monomers (Δ). We next tested eight emerin mutants (1 μM) in the pyrene–actin polymerization assay ( Figure 2 B). Five mutants (Q133H, m151, m164, m192, and m198) that failed to bind actin in vitro did not stimulate actin polymerization; instead, they reduced the rate of actin polymerization slightly, by 5%–40% ( Figure 2 B). Mutant 196, which had wild-type binding to F- and G-actin in coimmunoprecipitation assays, stimulated actin polymerization approximately 50% as well as wild-type emerin ( Figure 2 B). The two disease-causing mutants with apparently normal binding to F-actin, S54F and P183H, enhanced the rate of actin polymerization at least as well as wild-type emerin ( Figure 2 B). Critical concentration assays were done to determine if emerin acted on the barbed or pointed end of growing actin filaments. Pointed-end growth was examined by capping filaments with gelsolin. Emerin had no significant effect on the critical concentration of barbed-end growth ( Figure 2 C, + emr/no emr), but it increased the critical concentration for pointed-end growth by 2.3- to 2.7-fold ( Figure 2 C, + gelsolin no emr/+ gelsolin + emr). We therefore hypothesized that emerin, like tropomodulin ( Fowler et al. 2003 ), might stabilize growing filaments by capping the pointed end. Emerin Binds F-Actin at the Pointed End The vast majority of actin-binding proteins that influence subunit addition do so by binding the barbed end ( dos Remedios et al. 2003 ). However, because emerin failed to influence the critical concentration for barbed-end growth ( Figure 2 C), we used gelsolin–actin seeds to test the hypothesis that emerin binds the pointed end. Gelsolin binds and caps the barbed end of actin filaments ( Burtnick et al. 2001 ), thereby restricting subunit addition to the pointed end only. We measured the extension of gelsolin–actin dimers (10 nM) in the presence of 2 μM actin plus 0 to 2 μM wild-type emerin ( Figure 3 A). Emerin blocked actin polymerization in a concentration-dependent manner, supporting our model that emerin binds and caps the pointed end of actin filaments. Based on this assay, the affinity (K d ) of emerin for F-actin was 430 nM (range, 300–500 nM, n = 12; Figure 3 A). Interestingly, the affinity determined by either direct binding (see Figure 1 D) or activity measurements (see Figures 2 A and 3 A) differed by a maximum of 2-fold. We conclude that emerin binds F-actin with an affinity of 300–500 nM. Figure 3 Emerin Binds the Pointed End of Actin Filaments (A) Gelsolin–actin seeds were incubated with increasing concentrations of wild-type emerin residues 1–222. Emerin significantly reduced the rate of subunit addition at the pointed end, with an apparent K d of 430 nM (range, 300–500 nM, n = 12). R, rate of polymerization in the presence of emerin; cR, control rate of polymerization (actin alone). (B) Emerin inhibits depolymerization of actin filaments (2 μM) preformed from gelsolin–actin seeds, with an apparent K d of 380 nM (range, 350–450 nM, n = 6). R, rate of depolymerization in the presence of emerin; cR, control rate of depolymerization (actin alone). (C) Rhodamine–phalloidin-stabilized actin filaments were formed from 2 μM actin, then capped at the barbed end by the addition of 100 nM capping protein, and finally diluted 2-fold in the presence of buffer or 1 μM emerin, GST, or tropomodulin (Tmod). Samples were then incubated with actin (3.2 μM) and Alexa-488 phalloidin (3.2 μM) for 2 min, diluted 1:500, placed on polylysine-coated coverslips, and viewed by fluorescence microscopy. Bar is 1 μm and applies to all panels. (D) Actin (2 μM) was incubated with gelsolin–actin seeds (500 nM) in the presence of rhodamine–phalloidin (2 μM). These red filaments were diluted 10-fold and incubated with buffer alone or with 1 μM emerin or tropomodulin (Tmod) for 10 min, followed by incubation with actin (2 μM) and Alexa-488-labeled (green) phalloidin (2 μM) for 2 min. Samples were diluted 1:500, placed on polylysine-coated coverslips, and viewed by fluorescence microscopy. Bar is 1 μm and applies to all panels. (E–H) Alexa-488-labeled emerin (green) was incubated 30 min with actin filaments stabilized by Alexa-546 phalloidin (red) and centrifuged at 100,000 g to recover filaments, which were diluted 1:500 for viewing. To independently confirm that emerin binds the pointed end, we tested the effect of emerin on actin depolymerization in two separate assays. First, gelsolin–actin seeds were incubated with 2 μM actin and grown in the absence of emerin. The resulting filaments were then diluted to 0.2 μM actin in the presence of increasing concentrations of emerin (0–2 μM), and assayed immediately. Preformed actin filaments depolymerized rapidly in the absence of emerin ( Figure 3 B, arrow), as expected. Supporting our model, depolymerization was slowed up to 8-fold by emerin ( Figure 3 B). To independently confirm that emerin blocked subunit addition at the pointed end, preformed actin filaments were capped at the barbed end with capping protein (CapZ), a high-affinity barbed-end binding protein ( Cooper and Schafer 2000 ), then incubated in the presence or absence of emerin, and diluted into 0.2 μM actin; emerin slowed the rate of depolymerization by 10-fold (data not shown). Based on these three assays, we conclude that emerin binds and protects the pointed end of actin filaments in vitro, thereby stabilizing actin filaments. Fluorescent actin polymerization assays were done to demonstrate visually that emerin blocks pointed-end growth of single actin filaments. Rhodamine–phalloidin-stabilized actin filaments (red) were preformed from 2 μM actin, then capped on the barbed end with capping protein, and diluted 2-fold into a final concentration of 1 μM emerin. Pointed-end growth was then initiated by increasing actin to 3.2 μM in the presence of 3.2 μM Alexa-488 phalloidin (green) for 2 min. In the absence of emerin ( Figure 3 C, buffer or GST), actin filaments containing both red and green segments are seen ( Figure 3 C), demonstrating pointed-end growth. The average lengths of the growing filament segments (green) as measured for buffer and GST were 1.45 ± 0.3 μm and 1.47 ± 0.3 μm, respectively ( n = 30). However, in the presence of either emerin or tropomodulin, a pointed-end binding protein, most red filaments lacked green segments ( Figure 3 C), consistent with capped pointed ends. In the presence of emerin or tropomodulin, the lengths of the green segments were 0.05 ± 0.09 μm ( n = 60) and 0.09 ± 0.13 μm ( n = 50), respectively. Single filament assays were also done using small red filaments formed from gelsolin–actin seeds ( Figure 3 D). Here, actin (2 μM) was incubated with gelsolin–actin seeds (500 nM) and rhodamine–phalloidin (2 μM). The resulting red filaments were diluted 10-fold and incubated with 1 μM emerin for 10 min, then incubated 2 min with actin (2 μM) and Alexa-488-labeled (green) phalloidin (2 μM). In the absence of emerin, single filaments contained both short red (gelsolin–actin seeds) and longer green (pointed-end growth) segments ( Figure 3 D). The average length of these growing filament segments was 2.1 ± 0.6 μm ( n = 40). However, when emerin was present, the preformed filaments remained predominantly short and red, demonstrating that emerin blocks pointed-end growth ( Figure 3 D). Similar results were obtained in control reactions containing tropomodulin, the pointed-end binding protein ( Figure 3 D, Tmod). The average lengths of growing filaments incubated with emerin or tropomodulin were 0.1 ± 0.1 μm ( n = 40) and 0.1 ± 0.11 μm ( n = 40), respectively. These experiments also show that emerin does not stimulate branching ( Figure 3 D). To directly visualize emerin bound to actin filaments, green (Alexa-488-labeled) emerin was incubated with red (Alexa-546 phalloidin) actin filaments ( Figure 3 E– 3 H). Under these conditions 85% of labeled emerin molecules were bound to actin filaments; of these, 92% were localized at a filament end ( n = 306). Interestingly, 10% of actin-associated emerin proteins localized to “aster-like” structures ( Figure 3 G and 3 H), presumably due to the aggregation of emerin proteins on different actin filaments. Discussion This work shows for the first time that a nuclear membrane protein, emerin, is a pointed-end F-actin-binding protein. Similar to the activity of tropomodulin ( Fowler 1997 ; Cooper and Schafer 2000 ; Fowler et al. 2003 ), emerin caps the pointed end, thereby stabilizing the growing filament. Only three other pointed-end binding proteins have been reported: the Arp2/3 complex ( Mullins et al. 1998 ), tropomodulin, and mSWI/SNF, a component of a nuclear complex that remodels chromatin structure ( Rando et al. 2002 ). The Arp2/3 complex initiates filament branching at the cell surface ( Mullins et al. 1998 ; Mullins and Pollard 1999 ). We have no evidence that emerin initiates branching. Instead, emerin behaves most like tropomodulin, which binds the pointed end of F-actin with high affinity (K d = 110 nM) and stimulates actin polymerization by stabilizing the actin filament ( Fowler et al. 2003 ). Our analysis of 15 emerin missense mutants suggested that the actin-binding region in emerin overlaps with regions required for binding to lamin A ( Lee et al. 2001 ), transcription factors GCL and YT521-B ( Holaska et al. 2003 ; Wilkinson et al. 2003 ), and nesprin-1α (J. M. H. and K. L. W., unpublished data). However this overlap does not necessarily imply that actin competes with these other proteins. Indeed, despite similar overlap, GCL and lamin A can form stable ternary complexes with emerin in vitro ( Holaska et al. 2003 ). Further work is needed to determine if F-actin cobinds or competes with lamin A, nesprin-1α, or other emerin-binding proteins. A Proposed Actin Network at the Nuclear Envelope We propose that emerin stabilizes and promotes the formation of a nuclear actin cortical network, analogous to the actin cortical network at the plasma membrane ( Figure 4 ). Another LEM-domain protein, LAP2β, also an integral nuclear inner-membrane protein, was 20-fold less active than emerin in actin polymerization assays (data not shown), suggesting that LAP2β binds actin with an affinity 20-fold lower than that of emerin. Other LEM-domain proteins have not yet been tested for binding to actin. Whether emerin has specialized roles involving actin, or shares this function with other nuclear membrane proteins, are both interesting possibilities. An actin-based cortical network could help anchor emerin and possibly other nuclear membrane proteins and lamin filaments, contributing significantly to the structural integrity of the nuclear envelope and potentially reinforcing sites of chromatin attachment ( Figure 4 ). Figure 4 Model in Which Emerin Binding to the Pointed End of F-Actin Stabilizes an Actin Cortical Network at the Nuclear Inner Membrane Our model is based on the actin cortical network at the cell surface of erythrocytes, except that lamin filaments also anchor to emerin-based junctional complexes. Spectrin heterodimers bind short actin filaments at the erythrocyte membrane; we therefore speculate that nuclear isoforms of αII-spectrin (J. M. H. and K. L. W., unpublished data) act similarly. Direct binding of emerin and αII-spectrin has not yet been tested. Nuclear isoforms of protein 4.1, which are essential for nuclear assembly ( Krauss et al. 2002 ), have the potential to cross-link short actin filaments and spectrin filaments at the inner membrane (IM). Further work is necessary to test our model and identify other components of this proposed nuclear actin cortical network. OM, nuclear outer membrane. Since lamin A also binds G-actin in vitro ( Sasseville and Langelier 1998 ), we are currently testing the actin-binding properties of lamin A. Because emerin forms stable complexes with lamin A in vitro ( Clements et al. 2000 ; Lee et al. 2001 ), and because the nuclear envelope localization of emerin depends on lamins, we speculate that emerin might interlink multiple filament networks (actin, spectrin, and lamins) at the nuclear envelope. This model will be tested in future experiments by determining whether lamin A and actin compete for binding to emerin, or form trimeric complexes. Such complexes could significantly reinforce the mechanical properties of the nuclear envelope. Our nuclear actin cortical network model is further supported by the properties of the nesprin family of nuclear membrane proteins, which includes nesprin-1α (see Introduction ) and NUANCE. Nesprin-1α binds directly to both emerin (K d = 4 nM) and lamin A (affinity undetermined; Mislow et al. 2002a ). NUANCE is a large (796 kd), alternatively spliced isoform of nesprin that localizes to the nuclear envelope and nucleoplasm and binds F-actin ( Zhen et al. 2002 ). The organization of the membrane skeleton in erythrocytes (red blood cells) includes integral membrane proteins (e.g., Band 3), anchoring proteins (ankyrin), spectrin filaments, and “junctional complexes” (short actin filaments, protein 4.1, adducin, tropomodulin, and tropomyosin; Delaunay 2002 ). Tropomodulin and tropomyosin stabilize the junctional complex. Spectrin filaments (α/β-spectrin heterodimers) attach to junctional complexes through direct binding to protein 4.1, adducin, and actin. At the inner nuclear membrane, our working model is that emerin stabilizes junctional complexes ( Figure 4 ), consisting of short actin filaments, nuclear-specific αII-spectrin ( McMahon et al. 1999 ), and nuclear isoforms of protein 4.1 ( Krauss et al. 2002 ). This model is the first step toward understanding the structural function of nuclear actin. Materials and Methods Antibodies and proteins A pan-actin antibody (Sigma, St. Louis, Missouri, United States; catalog #A-5060) was used at 1:1,000 for immunoblotting. An antibody specific for β-actin (Sigma; catalog #A-5316) was used at 1:10,000 for immunoblotting and 1:1,000 for immunoprecipitation. Our rabbit polyclonal emerin antibody (serum 2999), described previously ( Lee et al. 2001 ), was used at 1:20,000 for immunoblotting and 1:2,000 for immunoprecipitation. Purified chicken actin was a kind gift of Doug Robinson (Johns Hopkins Medical School). Purified rabbit actin was purchased from Cytoskeleton. (Denver, Colorado, United States; catalog #AKL95 and #AKL99). Alexa-488 actin (#A12373), Alexa-594 actin (#A34050), Alexa-488 phalloidin (#A-12379), rhodamine–phalloidin (#R-415), and Alexa-546 phalloidin (#A-22283) were purchased from Molecular Probes (Eugene, Oregon, United States). Purified CapZ (capping protein) was a kind gift from John Cooper (Washington University, St. Louis). The full nucleoplasmic domain of wild-type emerin (residues 1–222) and corresponding mutants (detailed in Holaska et al. 2003 ) were expressed in bacteria and purified as described ( Lee et al. 2001 ; Holaska et al. 2003 ). Emerin protein was labeled with Alexa-488 (Molecular Probes, catalog #A20000) per manufacturer's instructions. Affinity purification using emerin-conjugated beads Wild-type emerin residues 1–222 (comprising the entire nucleoplasmic domain of emerin and lacking the transmembrane domain) or BSA (as a negative control) were coupled to Affigel-15 beads (Bio-Rad, Hercules, California, United States) per manufacturer's instructions. Nuclear extracts were prepared by hypotonic lysis ( Offterdinger et al. 2002 ) from 10 10 HeLa-S3 cells, obtained as frozen cell pellets from the National Cell Culture Center. For each affinity purification, we incubated 50 mg of nuclear lysate proteins with 2 ml of either emerin beads (0.5 mg/ml) or BSA beads in binding buffer (50 mM HEPES, 250 mM NaCl, 0.1% Triton X-100) for 4 h at 4 °C. Beads were collected by centrifugation at 500 g, washed five times with binding buffer, and eluted with SDS-PAGE sample buffer. Dr. Robert Cole at the Johns Hopkins Mass Spectrometry Facility performed MALDI-TOF. Actin and αII-spectrin were two of seven emerin-associated proteins identified unambiguously in this work, which will be reported separately (J. M. H. and K. L. W., unpublished data). F-actin-binding assays F-actin columns were assembled as described ( Forero and Wasserman 2000 ). Equal amounts of purified recombinant wild-type and mutant emerin proteins (residues 1–222) were incubated with each column in PBS containing 0.1% Triton X-100 (PBST) for 1 h at 22 °C. After washing beads five times with PBST, bound proteins were eluted and resolved by SDS-PAGE, and detected either by Coomassie blue staining, or by immunoblotting with rabbit serum 2999 against emerin. Coimmunoprecipitation assays were performed as described ( Lee et al. 2001 ). Briefly, equal masses (5 μg) of actin and either wild-type or mutant emerin were incubated 2 h, then incubated 4 h with protein-A Sepharose-coupled antibodies against emerin or actin. The beads were washed five times with buffer, and bound proteins were eluted with SDS-sample buffer, resolved by SDS-PAGE, then blotted and probed with antibodies specific for either actin or emerin. To measure emerin binding to single actin filaments, actin was polymerized by the addition of KMEI buffer (2 mM MgCl, 50 mM KCl, 10 mM imidazole [pH 7. 0], and 2 mM EGTA). After 30 min, the indicated form of emerin (4 μM, recombinant wild-type or mutant emerin residues 1–222, with or without conjugation to Alexa-488) was added to the filaments and incubated 30 min; we lastly added Alexa-546 phalloidin (final concentration, 0. 33 μM). These red F-actin polymers were then pelleted at 100,000 g for 60 min. For experiments with unlabeled emerin, corresponding load, supernatant, and pellet fractions were resolved by SDS-PAGE and stained with Coomassie blue. For experiments with phalloidin-546-labeled F-actin, filaments were viewed using a Zeiss Axiovert 200 fluorescent microscope (Zeiss, Oberkochen, Germany) and images captured using a Quantix CCD camera (Photometrics, Huntington Beach, California, United States) attached to an Apple G4 computer using IPLab (version 3.6; Scanalytics, Fairfax, Virginia, United States) software. Actin polymerization and depolymerization assays Actin polymerization assays were performed per manufacturer's instructions (Cytoskeleton). Rabbit actin (2 μM; Cytoskeleton, catalog #AKL95) plus pyrene–actin (0.1 μM; Cytoskeleton, catalog #AP05) were used in all assays, unless otherwise stated. Actin polymerization was measured in a fluorimeter (Fluoromax 2; SPEX, Edison, New Jersey, United States), with excitation wavelength 365 nm and emission wavelength 407 nm, and plotted using DataMax-Std (version 2.2; SPEX, Edison, New Jersey, United States). Graphs were refined using Cricketgraph III (version 1.0, Computer Associates, Smithfield, Rhode Island, United States) and Kaleidagraph (version 3.5.1, Synergy Software, Reading, Pennsylvania, United States). Pyrene–actin was always present at 5% of total actin. Increasing concentrations of recombinant emerin were added just prior to initiating actin polymerization. The actin depolymerization assays were performed exactly as described ( Mullins et al. 1998 ) with increasing amounts of recombinant emerin protein. Briefly, F-actin was polymerized by adding 2 μM G-actin to gelsolin–actin seeds (100 nM), then diluted 10-fold in the absence or presence of increasing concentrations of recombinant emerin (residues 1–222). Both gelsolin and actin were obtained from Cytoskeleton (catalog #HPG5 and #AKL95, respectively). Gelsolin–actin seeds were made exactly as described ( Blanchoin et al. 2000 ). Alternatively, 2 μM G-actin was polymerized in the absence of gelsolin for 2 h. Polymerized filaments were then incubated with or without 100 nM CapZ. Subsequent polymerization and depolymerization assays were assayed as described above. Actin polymerization in the presence or absence of emerin was monitored by fluorescent microscopy, as described ( Blanchoin et al. 2000 ; Amann and Pollard 2001 ). Samples were diluted 1:500–1:1000, viewed on a Nikon Eclipse E600W microscope (Nikon, Tokyo, Japan), and images were captured with a Q-imaging Retiga Exi CCD camera (Q Imaging, Burnaby, British Columbia, Canada) using IPLab (version 3.9.2) attached to an Apple G5 computer. Images were converted to TIFF images and lengths of filaments were measured in Photoshop version 7.0 (Adobe Systems, San Jose, California, United States).

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526382

Profiled support vector machines for antisense oligonucleotide efficacy prediction

Background This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises 315 AO molecules including 68 features each, inducing a problem well-suited to SVMs. The task of feature selection is crucial given the presence of noisy or redundant features, and the well-known problem of the curse of dimensionality . We propose a two-stage strategy to develop an optimal model: (1) feature selection using correlation analysis, mutual information, and SVM-based recursive feature elimination (SVM-RFE), and (2) AO prediction using standard and profiled SVM formulations. A profiled SVM gives different weights to different parts of the training data to focus the training on the most important regions. Results In the first stage, the SVM-RFE technique was most efficient and robust in the presence of low number of samples and high input space dimension. This method yielded an optimal subset of 14 representative features, which were all related to energy and sequence motifs. The second stage evaluated the performance of the predictors (overall correlation coefficient between observed and predicted efficacy, r ; mean error, ME; and root-mean-square-error, RMSE) using 8-fold and minus-one-RNA cross-validation methods. The profiled SVM produced the best results ( r = 0.44, ME = 0.022, and RMSE= 0.278) and predicted high (>75% inhibition of gene expression) and low efficacy (<25%) AOs with a success rate of 83.3% and 82.9%, respectively, which is better than by previous approaches. A web server for AO prediction is available online at . Conclusions The SVM approach is well suited to the AO prediction problem, and yields a prediction accuracy superior to previous methods. The profiled SVM was found to perform better than the standard SVM, suggesting that it could lead to improvements in other prediction problems as well.

Background The expression of a gene can be inhibited by antisense oligonucleotides (AOs) targeting the mRNA. However, if the target site in the mRNA is picked randomly, typically 20% or less of the AOs are effective inhibitors in vivo [ 1 ]. The sequence properties that make an AO effective are not well understood, thus many AOs need to be tested to find good inhibitors, which is time-consuming and costly. Antisense oligonucleotides contain 10–30 nucleotides complementary to a specific subsequence of an mRNA target, which are designed to bind to targets by standard Watson-Crick base pairing rules. The bound duplex can knockdown gene expression through a number of mechanisms. These are RNase-H mediated cleavage, inteference with translation or splicing and destabilization of the target mRNA [ 2 - 4 ]. The AO inhibits gene expression in a specific and reversible manner, a process termed 'Gene knock-down' and all mechanisms leave the AO intact to induce further knock-down. For a comprehensive review of the topic see [ 5 ]. There are many laboratory-based strategies for selecting AOs. A classical approach is the 'gene-walk' approach, in which 15 or more AOs are evaluated for a gene in order to find a sufficiently effective AO. Methods with higher reliability experimentally determine mRNA regions that are accessible to RNase-H clevage and therefore more likely to be an e'ective site for AOs [ 6 - 8 ]. In general, the experimental approaches are time consuming and expensive. There are many examples in the literature of experimental groups attempting to correlate AO sequence properties with efficacy. A correlation between binding energy (AO-RNA) and efficacy has been observed [ 6 , 9 ]. Particular target secondary structures have been shown to correlate with efficacy [ 10 ]. However, the correlations are not consistently detected across studies. This variation can be due to many factors including biases in the selection of the AOs, varying experimental conditions, or, in cases where computational RNA folding prediction was used, limitations in the structure prediction methods. In [ 11 ], published AOs were examined and recomended values for dimer, hairpin and ΔG to increase the proportion of higher efficacy AOs were given. AO selection can be based on either experimental or theoretical approaches (for a review, see [ 12 ]). Computational approaches to AO design have so far focused on prediction of the structure of the target mRNA and from this deriving the accessibility of target regions (e.g. [ 12 - 19 ]). Perhaps the most successful method is that of Ding and Lawrence [ 19 ], using a statistical sampling of secondary structures to predict accessible regions to find effective AOs for rabbit β -globin. In general, methods have not been evaluated on a broad range of gene targets. Another method is to look for motifs that occur more often in effective AOs. Ten sequence motifs have been identified with a correlation to AO efficacy in [ 20 ], and recently, motifs have been used as the input to neural network models [ 21 , 22 ] with reasonable success. In this context, the challenge is hence to discover general principles that hold across all AO studies. One approach to discover such principles is to explore a diverse range of sequence properties and incorporate the factors that affect AO efficacy into a computational model for AO design. This requires both a database of tested AOs, such as that produced by [ 21 , 23 ], and machine learning methods of model building. The database should be based on large AO screening experiments to ensure comparability. In this context, the use of advanced pattern recognition methods such as neural networks or Support Vector Machines (SVMs) is becoming very popular because of their good capabilities for classification, function approximation and knowledge discovery. In particular, the use of SVMs in bioinformatics has found a natural match because they work efficiently with high input dimension spaces and low number of labeled examples. As a consequence, many biological problems have been solved in this field. The interested reader can visit [ 24 ] for a collection of SVM applications in bioinformatics. However, the use of the SVM has been traditionally attached to the classification problem, and few efforts have been made to tackle the regression (or function approximation) problem. This paper proposes the use of SVMs for prediction and analysis of AO efficacy. The collected database comprises 315 AO molecules including 68 features each, which induces a priori a well-suited problem to SVMs, given the low number of samples and high input space dimension [ 25 ]. Nevertheless, the problem of feature selection becomes crucial because the number of examples in the database (AO molecules) is low compared to the number of features for each of them and, therefore, overfitting is likely to occur, reducing the performance of the model [ 26 , 27 ]. Additionally, being able to explain the obtained solution (in terms of the selected input features) can be as relevant as obtaining the best possible predictor. This is of particular interest in bioinformatics in general and for AO efficacy prediction in particular, as was previously illustrated in [ 21 , 22 ]. The issue of feature selection in the SVM framework has received attention in the recent years [ 28 - 32 ]. The fact that SVMs are not drastically affected by the input space dimensionality has sometimes led to the wrong idea that a feature selection is not necessary at all. The guiding principle of SVMs ensures certain robustness to outliers or abnormal samples in the distribution inherently, but the selection of the optimal subset of features is still an unsolved problem in the literature. We can state that in most applications, the success of machine learning is strongly affected by data quality (redundant, noisy or unreliable information) and thus a feature selection is not only recommendable but mandatory. In this paper, we propose a two-stage strategy to tackle the problem: 1. Feature selection. This task is carried out using three techniques: correlation analysis, the mutual information feature selection (MIFS) method, and the SVM-based recursive feature elimination (SVM-RFE). 2. AO efficacy prediction. We develop standard and profiled SVMs to accomplish this task. Several measures of accuracy of the estimations and two cross-validation methods are used in order to attain both significant and robust results. Methods Data collection In the present work, we have extended the database used in [ 21 ] by including 68 features for each AO. The so-called AO database (AOdb) was assembled from a selection of AO publications. Published data was incorporated for which: (a) at least 6 AOs were tested under the same experimental conditions, although more than one gene target were allowed; (b) efficacy of the AOs were presented as a percentage of the control level of the target gene expression, either as RNA or protein. No papers were reported matching these criteria before 1990, as is consistent with [ 23 ]. Accompanying this data is the full RNA sequence and accession number (where available) together with positional coordinates of the AOs and the position of the coding sequence. Publication details, cell line used and the chemistry of the AOs were also recorded in the database. The database consists of 315 oligonucleotides from 15 studies testing AO efficacy on 13 genes. The essential information in the database is AO sequence and efficacy expressed as (100% - [% of control expression])/100. For the cases where the same AO is tested in two different laboratories, or twice by the same laboratory the average efficacy is used. A set of a priori representative parameters was derived from the information contained in the AO sequence collection, including values for: (1) base composition (Number of A/C/G/T, % GC content): (2) RNA-AO binding properties (binding energy, enthalpy, entropy): (3) RNA-AO terminal properties (3' binding energy, 5' binding energy); (4) AO-AO binding properties (Hairpin energy and quality, Dimer energy); and (5) 9 of the 10 verified sequence motifs correlated with efficacy from [ 20 ]. Binding energy calculations were completed using thermodynamic parameters from [ 33 ]. The calculation of dimer energy was made using an ungapped alignment with stacking energies taken from [ 34 ] and a uniform penalty 0.5 for mismatches. Hairpin energy was calculated using both Mfold [ 35 ] and the Vienna package [ 36 ]. Parameters describing cellular uptake and protein interactions were not included, as we have no explicit way of modeling them. A number of additional features were included to complete the AOdb: motifs, AO position, predicted conformation of the target structure, single-strandedness, binding energies from [ 14 ]. For brevity, the complete list and more information on the database can be obtained at [ 37 ]. The database is available under request. The feature selection problem The Feature Selection Problem (FSP) in a "learning from samples" approach can be defined as choosing a subset of features that achieves the lowest error according to a certain loss functional [ 28 ]. Following a general taxonomy, the FSP can be tackled using filter [ 38 ] and wrapper [ 26 ] methods. Filter methods use an indirect measure of the quality of the selected features, e.g. evaluating the correlation function between each input feature and the observed output. A faster convergence of the algorithm is thus obtained. On the other hand, wrapper methods use as selection criteria the goodness-of-fit between the inputs and the output provided by the learning machine under consideration, e.g. a neural network. This approach guarantees that, in each step of the algorithm, the selected subset improves performance of the previous one. Filter methods might fail to select the right subset of features if the used criterium deviates from the one used for training the learning machine, whereas wrapper methods can be computationally intensive due to the learning machine has to be retrained for each new set of features. In this paper, we evaluate the performance of SVMs for different subsets of relevant features, which are selected using both filter and wrapper approaches. Correlation analysis and mutual information A common practice to evaluate the (linear) relationship between each of the n input features and output , or among pair-wise inputs ( and ) is the use of the correlation function. This is a good method to remove redundant features and to evaluate relationships, but fails when working with low number of samples, or when the assumed linear relationship is not present. When data is considered as the realization of random processes, it is possible to compute the relevance of variables with respect to each other by means of the mutual information (MI) function, which is defined as the difference between entropy of and the conditional entropy of given . The MI function is suitable for assessing the information content of features in tasks where methods like the correlation are prone to mistakes. In fact, the MI function measures a general dependence between features, instead of a linear dependence offered by the correlation function. In [ 39 ], an algorithm called Mutual Information Feature Selection (MIFS) was successfully presented. The method greedily constructs the set of features with high mutual information with the output while trying to minimize the mutual information among chosen features. Thus, the ith input feature included in the set, maximizes over all remaining features for some parameter β ∈ (0,1]. The feature selection procedure is performed iteratively until a desired number of features is reached. We will use the correlation function and the MIFS method as filter methods, i.e. a feature ranking will be provided and only the most important features will be accounted for modeling. Support vector regressor (SVR) Support Vector Machines are state-of-the-art tools for nonlinear input-output knowledge discovery [ 40 ]. The Support Vector Regressor (SVR) is its implementation for regression and function approximation, which has been used in time series prediction with good results [ 41 ]. Basically, the solution offered by the SVR takes the form , where x i is an input example, φ is a nonlinear mapping, w is a weight vector and b is the bias of the regression function. In the SVR, a fixed desired accuracy ε is specified a priori and thus one tries to fit a "tube" with radius ε to the training data. The standard SVR tries to minimize two factors: the norm of the squared weight vector, || w || 2 , and the sum of permitted errors. These two factors are traded-off by using a fixed penalization parameter, C . We can formally state the SVR method as follows: given a labeled training data set {( x i , y i ), i = 1,..., n }, where x i ∈ ℝ d and y i ∈ ℝ, and a nonlinear mapping to a higher dimensional space φ : ℝ d → ℝ H where d ≤ H , find the minimum of the following functional with respect to w , ξ i , and b : subject to: where and C are, respectively, positive slack variables to deal training samples with a prediction error larger than ε ( ε > 0) and the penalization applied to these ones. These two parameters are tuned by the user. The usual procedure for solving the SVR introduces the linear restrictions (2)-(4) into (1) by means of Lagrange multipliers α i and associated to each constraint. The dual functional obtained has to be minimized with respect to primal variables ( w , ξ i and ) and maximized with respect to dual variables ( α i ). The optimization of the obtained dual problem is usually solved through quadratic programming procedures [ 40 , 42 ], and the final solution provided by the SVR for a test example x can be expressed as where only the non-zero Lagrange multipliers account in the solution. The corresponding input examples are called support vectors and represent the most critical samples in the distribution. An important characteristic of the SVR training methodology is that one does not need to know explicitly the form of the mapping φ ( x ) but only a kernel function, which maps the samples into a high dimensional space. This kernel function appears in the form of dot products in (5), K ( x i , x j ) = φ ( x i )· φ ( x j ) and can be viewed as a measure of similarity between samples. Therefore, in order to train the SVR model, one only has to select a kernel function, its free parameters, the parameter C , and the size of the ε -insensitivity zone. In this paper, we have only used the Gaussian (or Radial Basis Function, RBF) kernel, given by: K ( x i , x j ) = exp (- γ || x i - x j || 2 ).     (6) There are some reasons to select the RBF kernel a priori . The RBF kernel maps samples into a higher dimensional space so, unlike the linear kernel, it can handle efficiently cases in which the relation between the dependent and independent variables is non-linear. The RBF kernel has less numerical difficulties than sigmoid or linear kernels. In fact, sigmoid kernels behave like RBF for certain parameters [ 43 , 44 ] but unfortunately, they are non-positive definite kernels in all situations, which precludes their practical application [ 25 ]. Finally, for using the RBF kernel, only the Gaussian width has to be tuned. For tutorials, publications, and software resources on SVM and kernel-based methods, the reader can visit [ 45 ]. Recursive feature elimination (SVM-RFE) The SVM-RFE algorithm has been recently proposed in [ 29 ] for selecting genes that are relevant for a cancer classification problem. The goal is to find a subset of size m among n features ( m < n ) that maximizes the performance of the predictor for a given measure of accuracy. This is a wrapper method and involves high computational cost. The method is based on a backward sequential selection. One starts with all the features and removes one feature at a time until m features are left. Basically, in each iteration, one focuses on the weight vector, which constitutes the solution provided by the SVR and therefore, its analysis is of fundamental relevance to understand the importance of each input feature. The removed feature is the one whose removal minimizes the variation of || W || 2 . Hence, the ranking criterion R c for a given feature i is: where K ( i ) is the kernel matrix of training data when feature i is removed and are the Lagrange multipliers corresponding to sample k when the input feature i is removed. The idea underlying this procedure is basically to evaluate at each iteration which feature affects less the weight vector norm and, consequently, to remove it. Results In this section, we present and discuss the results obtained both regarding feature selection and prediction accuracy. Filter and wrapper feature selection methods will provide different subsets of representative features. SVMs are trained for each subset and their performance is evaluated in terms of robustness and accuracy. Feature selection The first approach to the FSP consisted of performing a correlation analysis in order to identify redundant variables. We adopted a similar strategy followed in [ 21 ], i.e. to remove features correlated to each other at >0.9 ( p < 0.001), keeping the highest correlation to efficacy. This analysis discarded 12 redundant features out of the 68 original ones, and additionally provided a ranking of the most correlated features to efficacy. We finally selected the 14 top ranked features according to this criterion, ranging in correlation from -0.35 (ΔG) to -0.16 (# Adenine). We selected this number of features for the purpose of a fair comparison with the best subset in [ 21 ]. Table 1 shows selected features in both cases. Note that some di'erences are observed between the present work and [ 21 ] with regards the value of the correlation coefficient, (first and last columns, respectively). They are due to the facts that (1) we have included here very low efficacy oligos in the calculation, and that (2) because more features were added to the AO database, e.g. predicted secondary structure, oligos had to be discarded when the target RNA was unavailable. A feature ranking according to the correlation coefficient can be useful to analyze input-output linear dependencies, but it is not good practice to rely only on this decision to build a model. As a second approach, we ran the MIFS method and selected a desired subset of best 14 features. We selected β = 0.75, which yielded a balanced estimation of both the MI with the output (AO efficacy), and the already-selected features. The more important features match the ones selected using the correlation function, but MIFS also included hairpin measurements. This is due to the fact that MIFS is not based on correlatedness but on mutual dependence criteria. A third approach was the use of SVMs based on the RFE method. In this task, we trained an SVM to predict AO efficacy using all available features. It should be noted here that RFE is a wrapper method that involves a very high computational burden since the SVM must be retrained in each iteration with the selected features. The best model was selected by evaluating the RMSE (accuracy of the estimations) in the validation set through the 8-fold cross-validation method, which splits the data into eight parts, and uses seven parts for training and the eighth one for validation. The procedure is then repeated eight times. In our implementation, we included the possibility suggested in [ 29 ] by which it is possible to remove chunks of features at each iteration –a maximum value around 10 was a suitable option. In our application, only ten iterations were necessary to achieve the best 14 features (see Table 1 ). In [ 20 , 21 ], a surprising lack of correlation was observed between dimer energy and efficacy, which was attributed to some kind of bias in the databases. In the present work, nevertheless, SVM-RFE includes dimer energy as the 11th most relevant feature. In conclusion, SVM-RFE selects a combination of highly correlated but also mutually informative features. We can also conclude that noticeable differences are observed between the obtained rankings. A possible explanation for discrepancies of this sort is the non-linear mapping that SVR methods perform. Explaining those input-output relationships is often difficult and biased conclusions are usually obtained. Different families of methods (SVM, neurofuzzy, decision trees, or neural networks) perform different mappings due to their specific guiding principles (structural risk minimization, membership optimization, entropy-based criteria, or empirical risk minimization, respectively) and thus, the interpretation of these methods is quite diffcult. In addition, different models (topologies, structures, kernels, membership functions) in a family would surely yield different results. Model development A greedy search was carried out for the free parameters ( C , ε , γ ) As regards the penalization parameter, it is a common practice trying exponentially increase sequences of C ( C = 10 -2 , 10 -1 ,..., 10 3 ). In our case study, we achieved good results in the range of C ∈ [1,1000]. The insensitivity zone was varied linearly in the range [0.001, 0.3]. The γ parameter was exponentially varied in the range γ = 10 -7 ,...,10 -1 . For each free parameter combination, we evaluated the performance of the predictors through several measurements: the correlation coefficient between actual and predicted efficacies ( r ), the mean error (ME), and the root-mean-square-error (RMSE). Additionally, we computed the rate of observed efficacies above a defined predicted threshold of 0.75 (SR >0.75 ) and below 0.25 (SR <0.25 ). These prediction ranges are of particular interest, since they stand for high and low AO efficacies, respectively. In fact, it is not only important to identify high efficacy oligos but also factors causing AOs to be completely ineffective ([0,0.25]). However, care must be taken as more noise can be present in the low efficacy region. Model comparison At the first stage of the work, we trained SVMs using the 8-fold cross-validation method for RFE-based feature selection. However, this training methodology can lead to overoptimistic results because AOs on the same gene are not always independent data points. Hence, we also followed a different strategy, which entails removing all AOs targeting one gene for training, training the model, and then testing performance on predicting the efficacy of these oligos. This is a common method [ 22 ] and we refer to it as minus-one-RNA cross-validation (-RNA). It safely removes any overlap between training and test data, and thus ensures the generality of the model. In AO prediction, we are most interested in predicting good oligos (high efficacy, > 0.75), and those that are bad (low efficacy, < 0.25). This previous knowledge about the problem can be introduced in the SVM formulation by tailoring specific confidence functions for the adaptation of the penalization factor C , and the ε -insensitive zone of each sample. The so-called Profiled SVR (P-SVR) [ 46 ] obviously implies making some changes in the original SVR formulation since now C and ε become sample-dependent. In [ 46 , 47 ], we designed profiles for the variation of C and ε in complex pharmacokinetic problems. In this paper, our intention relaxing or tightening ε and C depending on the observed AO efficacy value. A proposal for this variation is illustrated in figure 1 . Note that we increase the penalization of errors committed in the high or low AO efficacy ranges since we are more interested in obtaining good results in these regions. Additionally, the ε -insensitivity zone is reduced in these regions thus forcing a reduced error there. Some other profiles could be introduced in the training methodology without loss of generality. Results for all approaches are shown in Table 2 for the validation set. We observe that RFE is the best method for selecting features. The choice of cross-validation method does not make much difference; the RMSE is the same while the goodness-of-fit ( r ) is almost unchanged. Using the P-SVR method (with features selected by the 8-fold crossvalidated RFE) we gained substantially in RMSE, and also obtained a better balance between the success rates of high and low predictions. This indicates that the P-SVR improves the performance of standard SVR even without a dedicated feature selection method, and suggests that even better results could be obtained if P-SVR were embedded in the RFE feature selection procedure. These outcomes are worth analyzing because one could expect worse results when using -RNA cross-validation since this method removes the possibility of cross-talk in the training phase between overlapping oligos. However, we have to stress here that, by training the SVR with -RNA cross-validation, one only improves the r indicator, which is a biased estimator of the accuracy. In fact, accuracy (RMSE) remains basically the same, and bias (ME) becomes positive and higher, which could induce some distrust for the model. When analyzing results from the P-SVR, we can observe a general improvement in all indicators, which is basically due to the fact that by tightening the "tube" around the interesting ranges, a higher number of support vectors is selected there (but lower in the overall domain), which induces a richer solution in the interesting zones. In addition, the profiled C parameter penalizes higher the committed errors in these zones, which is particularly interesting to deal with outlying samples in the distribution and to provide a smoother solution in these particular zones. The designed profile, nevertheless, could lead to an overfitted solution in the interesting zone if ε i and C i were not well-controlled. However, by using the-RNA cross-validation method, this threat is avoided and better results are finally obtained. Therefore, the combined strategy of P-SVR and -RNA cross-validation results in a balanced and robust predictor. Additional consequences can be extracted: (1) the correlation coefficient is relatively low for all methods but superior to the ones obtained in [ 21 ]; (2) differences among the models are neither numerically (see Table 2 ) nor statistically significant as tested with One Way Analysis-Of-Variance (ANOVA) in bias ( F = 0.01, p = 0.811) or accuracy ( F = 0.06, p = 0.567); (3) prediction is more accurate, in general terms, for the higher efficacy levels (SR >0.75 , > SR <0.25 ), as also noted in [ 22 ]; and (4) SVM-RFE can deal efficiently with high input spaces and produces robust results (compare results with those from the "All features" subset). Additionally, we can conclude that the P-SVR improved results in terms of accuracy of the predictions compared to the standard SVR. Conclusions In this paper, we have used standard and state-of-the-art methods for knowledge discovery in a relevant bioinformatics problem: the analysis and prediction of AO efficacy. We have engineered robust and accurate SVMs, and used filter and wrapper feature selection methods in order to build representative subsets of input features. Compared to [ 21 ], our results represent a significant improvement. In that work, SR >0.8 was reported to be 50%, and r = 0.30. The success of the P-SVR for the AO prediction problem suggests that it could be successfully applied to other prediction problems. A web server for AO prediction is available online at [ 48 ]. Our future work is concentrated to improving results with more careful design of profiles by the inclusion of fuzzy and rough sets. Additionally, we are exploring the possibility of providing confidence values for the predictions in the form of p -values from the Lagrange multipliers. This way, the user could get a set of best predictions back, then a second set that is more likely to be less accurate, and so on. This would allow the lab-user to choose the best ones first, but if they fail specificity controls they would have another set to work with. Authors' contributions GCV carried out the training of the feature selection and regression methods. AC participated in model development and testing process, and developed the web-server. AJSL collaborated in model development and assessment. JDMG engineered the profile function. ES conceived and coordinated the study. All authors contributed to the manuscript preparation, and approved the final manuscript.

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Prediction and identification of Arabidopsis thaliana microRNAs and their mRNA targets

Using bioinformatic methods, 83 novel Arabidopsis miRNAs have been predicted. Putative target mRNAs have been identified for most of the candidate genes.

Background MicroRNAs (miRNAs) are non-coding RNA molecules with important regulatory functions in eukaryotic gene expression. The majority of known mature miRNAs are about 21-23 nucleotides long and have been found in a wide range of eukaryotes, from Arabidopsis thaliana and Caenorhabditis elegans to mouse and human (reviewed in [ 1 ]). Over 300 miRNAs have been identified in different organisms to date, primarily through cloning and sequencing of short RNA molecules [ 2 - 16 ]. Experimental miRNA identification is technically challenging and incomplete for the following reasons: miRNAs tend to have highly constrained tissue- and time-specific expression patterns; degradation products from mRNAs and other endogenous non-coding RNAs coexist with miRNAs and are sometimes dominant in small RNA molecule samples extracted from cells. Several groups have attempted to screen for new Arabidopsis miRNAs by sequencing small RNA molecules, but only 19 unique Arabidopsis miRNAs have been found so far [ 12 , 13 , 15 - 17 ]. While intensive research has unmasked several aspects of miRNA function, less is known about the regulation of miRNA transcription and precursor processing. A recent study shows a 116 base-pair (bp) temporal regulatory element located approximately 1,200 bases upstream of C. elegans let-7 is sufficient for its specific expression at different developmental stages [ 18 ]. For some animal miRNAs, longer transcripts have been shown to exist in the nucleus before they are processed into shorter miRNA precursors [ 19 ]. Expressed sequence tag (EST) searches indicate that some human and mouse miRNAs are co-transcribed along with their upstream and downstream neighboring genes [ 20 ]. Most known animal miRNA precursors are approximately 70 nucleotides long, whereas the lengths of plant miRNA precursor vary widely, some extending up to 300 nucleotides [ 5 , 8 , 9 , 14 , 16 ]. As short mature miRNAs are generated from hairpin-structured precursors by an RNase III-like enzyme termed Dicer (reviewed in [ 21 , 22 ]), evidence for miRNA expression based on the presence of longer precursor RNAs is likely to be found in genome-wide expression databases. Most known miRNAs are conserved in related species [ 5 , 8 , 9 , 14 - 16 ]. Strong sequence conservation in the mature miRNA and long hairpin structures in miRNA precursors make genome-wide computational searches for miRNAs feasible. A variety of computational methods have been applied to several animal genomes, including Drosophila melanogaster , C. elegans and humans [ 4 , 10 , 11 , 23 ]. In each case, a subset of computationally predicted miRNA genes was validated by northern blot hybridizations or PCR. A known function of miRNAs is to downregulate the translation of target mRNAs through base-pairing to the target mRNA [ 21 , 24 , 25 ]. In animals, miRNAs tend to bind to the 3' untranslated region (3' UTR) of their target transcripts to repress translation. The pairing between miRNAs and their target mRNAs usually includes short bulges and/or mismatches [ 26 - 28 ]. In contrast, in all known cases, plant miRNAs bind to the protein-coding region of their target mRNAs with three or fewer mismatches and induce target mRNA degradation [ 12 , 15 , 17 , 29 ] or repress mRNA translation [ 30 , 31 ]. Several groups have developed computational methods to predict miRNA targets in Arabidopsis , Drosophila and humans [ 29 , 32 - 35 ]. In the work reported here, we defined and applied a computational method to predict A. thaliana miRNAs and their target mRNAs. Focusing on sequences that are conserved in both A. thaliana and Oryza sativa (rice), we predicted 95 Arabidopsis miRNAs, including 12 of 19 known miRNAs and 83 new candidates. Northern blot hybridizations specific for 18 randomly selected miRNA candidates detected the expression of 12 miRNAs. The sequences of another eight predicted miRNAs were found in the public Arabidopsis Small RNA Project (ASRP) database [ 36 ]. We also found massively parallel signature sequencing (MPSS) evidence for 14 known Arabidopsis miRNAs and 16 predicted ones. For 77 of the 83 predicted miRNAs we found putative target transcripts that were functionally conserved between Arabidopsis and O. sativa , with a signal-to-noise ratio of 4.1 to 1. Finally, we find supporting evidence for miRNA regulation of some mRNA targets using available genome-wide microarray data. The authentication of three predicted miRNA targets was validated by identification of the corresponding cleaved mRNA products. Results Prediction of Arabidopsis miRNAs To predict new miRNAs by computational methods, we defined sequence and structure properties that differentiate known Arabidopsis miRNA sequences from random genomic sequence, and used these properties as constraints to screen intergenic regions in the A. thaliana genome sequences for candidate miRNAs. Besides the well known hairpin secondary structure of miRNA precursors, the 19 unique known Arabidopsis miRNAs collected in Rfam [ 37 ] were evaluated for the following computable sequence properties: G+C content in mature miRNA sequences, hairpin-loop length in their precursor RNA structures, number and distribution of mismatches in the hairpin stem region containing the mature miRNA sequence, and phylogenetic conservation of mature miRNA sequences in the O. sativa genome. Sequences of all 19 known Arabidopsis miRNAs had a G+C content ranging from 38% to 70%. For 15 of the 19 miRNAs, the predicted secondary structure of their precursors, or at least one precursor if a miRNA has multiple genomic loci, had a hairpin-loop length ranging from 20 to 75 nucleotides. In the hairpin structures formed by miRNA precursors, all miRNAs were found in the stem region of the hairpin, and had at least 75% sequence complementarity to their counterparts. Fifteen of 19 miRNAs were conserved with at least 90% sequence identity in the O. sativa genome. Thus, constraints of G+C content between 38 and 70%, a loop length between 20 and 75 nucleotides, and a minimum of 90% sequence identity in O. sativa were used to predict Arabidopsis miRNA. The first step was to search for potential hairpin structures in the Arabidopsis intergenic sequences. As most known Arabidopsis miRNAs are around 21 nucleotides long, we used a 21-nucleotide query window to search each intergenic region for potential miRNA precursors as follows: for each successive 21-nucleotide query subsequence, if a 21-nucleotide pairing subsequence with more than 75% sequence complementarity was found downstream within a given distance (hairpin-loop length), the entire sequence from the beginning of the query subsequence to the end of the complement pairing subsequence with a 20-nucleotide extension at each side was extracted and marked as a possible hairpin sequence (see Materials and methods for details). The minimum and maximum hairpin-loop lengths used in this prediction were 20 and 75 nucleotides. Each 21-nucleotide query subsequence and its downstream complementary subsequence were considered as 'potential 21-mer miRNA candidates' (referred to as '21-mers'). If a series of overlapping forward query sequences and their corresponding downstream pairing sequences were all identified from the same hairpin structure, each of them was initially considered as an individual 21-mer. The second step was to parse miRNA candidates according to their nucleotide composition and sequence conservation. A filter of G+C content between 38 and 70% was applied to all 21-mers obtained from the above step, followed by a requirement for more than 90% sequence identity in the O. sativa genome. The secondary structures of the resulting candidates were evaluated by mfold [ 38 ]. Only 21-mers whose Arabidopsis precursor and corresponding rice ortholog precursor both had putative stem-loop structures as their lowest free energy form reported by mfold were retained. Because some non-coding RNA genes were not included in the current Arabidopsis gene annotation, orthologs of known non-coding RNA genes other than miRNAs were subsequently removed by aligning the 21-mers to non-coding RNAs collected in Rfam with BLASTN (version 2.2.6) [ 37 ]. The 21-mers that passed all sequence and structure filters above were considered as final miRNA candidates. A summary of the prediction algorithm is shown in Figure 1 . In cases where two or more overlapping 21-mer miRNA candidates from the same precursor were collected in the final miRNA candidate set, each miRNA candidate was scored using the following formula: miRNA score = number of mismatches + (2 × number of nucleotides in terminal mismatches) + (number of nucleotides in internal bulges/number of internal bulges) + 1 if the miRNA sequence does not start with U. The term 'terminal mismatches' in the formula above refers to consecutive mismatches among the beginning and/or ending nucleotides of a mature miRNA sequence. The term 'bulge' refers to a series of mismatched nucleotides. Because the sequences of most known miRNAs start with a U, a U-start preference was used in the formula above by penalizing non-U-start sequences. The sequence with the lowest miRNA score from a series of overlapping 21-mers was selected as the final miRNA candidate. In total, we predicted 95 miRNA candidates in the Arabidopsis genome, including 12 known Arabidopsis miRNAs and 83 new candidates. The former group corresponds to 63% of known Arabidopsis miRNAs to date (12 of 19). The remaining seven known miRNAs not included in the current prediction were filtered out as a result of their lower sequence conservation in the rice genome or longer loop length in their secondary structure, as outlined in Figure 1 . Because of the complementarity between the two DNA strands of a given genome region, theoretically there should be two sequence possibilities for a predicted miRNA: the predicted sequence itself or, alternatively, its reverse complementary sequence located on the opposite strand of the genome. In many cases, however, owing to G::U pairing in RNA structure prediction, the complementary sequence of a miRNA precursor did not always exhibit a hairpin structure as its lowest energy folding form because the complement of a G::U pair, that is, C::A, altered the secondary structure. Thus, we were able to identify the coding strand of most predicted miRNA candidates through secondary structure evaluation. Furthermore, as described in the following sections, the sequences/partial sequences of some miRNA candidates or their precursors could be found in the Arabidopsis MPSS data used. As most MPSS data probably represent the expression of their associated miRNAs, we were able to use them to predict the miRNA coding strand. The coding strand of miRNA candidates that were contained in the ASRP database was determined according to cloned RNA sequences (see below for details). The complete list of predicted miRNAs is shown in Additional data file 1. Experimental validation of predicted miRNAs To gain support for the expression of the predicted miRNAs, northern blot hybridizations were carried out using RNA samples from different tissues selected to cover a spectrum of potential miRNA expression patterns. Using strand-specific oligonucleotide probes, positive signals of expression were detected for 14 out of 18 miRNA candidates tested. The results for all newly identified miRNAs are shown in Figure 2a and 2b . Oligonucleotide probes against the antisense strand of different miRNA candidates were used as negative controls, and none produced any signal, as shown for miR417 in Figure 2b . Note that an extended exposure time was needed to detect expression of most miRNAs (indicated by a number in days in parentheses in Figure 2 ), suggesting that their abundance is significantly lower than that of other known miRNAs (that is, miR158 and miR159a in Figure 2c , and data not shown). In this analysis we also included 10 21-mers that were rejected by our miRNA prediction criteria as negative controls to evaluate the specificity of northern blot hybridization; as expected none of them produced a positive signal. The secondary structures of a few selected northern blot hybridization-positive miRNA candidates are shown in Figure 3 . A full list of the secondary structures of predicted precursors of Arabidopsis miRNA candidates and their rice orthologs is available in Additional data file 2. Among the 14 miRNAs that produced positive signals in the northern blot hybridizations, two are close paralogs of known miRNAs; miR169b is a paralog of miR169 and miR171b is a paralog of miR170. Because it is impossible to distinguish closely related sequences by northern blot hybridization, we were unable to rule out the possibility that signals detected by probes for miR169b and miR171b were contributed by their known miRNA paralogs. However, as miR169b was also identified in the ASRP database (see next section), we were able to conclude that miR169b was a real miRNA. Thus, 12 candidates validated by northern blot hybridization should be annotated as bona fide miRNAs (see Table 1 for a summary). Cloning evidence for predicted miRNAs An ASRP database has recently been made publicly available [ 36 ]. Sequences in the ASRP database were collected by cloning small RNA molecules with similar size to miRNAs and siRNAs [ 39 ]. To check whether any of our predicted miRNAs can be identified by a standard RNA cloning method, we compared the 83 predicted miRNA candidates with all sequences in the ASRP database. Eight newly predicted miRNA candidates were found in the ASRP database (Figure 4 ). Among them, five were identical to one or more cloned RNA molecules, indicating that we had correctly predicted the 5' and 3' ends and the actual length of these miRNA candidates. For the other three candidates, our predicted sequences were either shorter than, or a few nucleotides shifted from, their corresponding clones in the ASRP database. The exact sequences of these three miRNA candidates were then corrected according to the corresponding sequences in the ASRP database. The expression of miR169b and miR172b* was also detected by northern blot hybridization (Figure 2a ). Although miR169h was present in the ASRP database, it could not be detected by northern blot hybridization (see Additional data file 1). According to the current miRNA annotation criteria [ 22 ], these eight predicted miRNA candidates with corresponding cloned sequences in the ASRP database should be annotated as bona fide miRNAs. MPSS evidence for known and predicted Arabidopsis miRNAs To further validate the predicted miRNA molecules, we took advantage of available Arabidopsis massively parallel signature sequencing (MPSS) data. The MPSS sequencing technology identifies unique 17-nucleotide sequences present in cDNA molecules originated from polyadenylated RNA extracted from a cell sample. By inserting cDNA molecules into a cloning vector containing distinct 32-mer oligonucleotide tags, the MPSS technology ensures that each cDNA molecule is ligated to a unique tag and that more than 99% of the total cDNAs are represented after the cloning step. Tagged cDNAs are then amplified by PCR and hybridized to microbeads that have been precoated with multiple copies of unique anti-tags complementary to one type of 32-nucleotide tag. The expression level of a particular transcript is measured by counting the number of distinct microbeads that contain the same 17-nucleotide cDNA sequence. The MPSS technology does not require prior knowledge of a gene's sequence and thus can identify novel or rarely expressed genes. For a complete description, see [ 40 , 41 ]. To assess the degree to which MPSS data could be used to support predicted miRNAs, we inspected the 19 known Arabidopsis miRNAs for unique representation in public Arabidopsis MPSS datasets and in our own MPSS datasets derived from a variety of tissues and conditions (see Materials and methods for details) [ 42 - 44 ]. We compared the intergenic genomic sequence flanking the 19 known Arabidopsis miRNAs with the MPSS data. We found 30 MPSS signature sequences that were identical to subsequences within the flanking 500-bp sequences either upstream or downstream of 14 known miRNAs (see Additional data file 3). All 30 MPSS sequences were reported in both the public and private MPSS datasets. They occurred upstream, downstream or partially overlapping with known mature miRNAs. Despite the highly repetitive nature of the Arabidopsis genome, 28 of the 30 MPSS signatures mapped uniquely to only one miRNA locus, with no matches elsewhere in the genome. Two genomic loci were found for each of the two exceptional MPSS signatures MPSS78528 and MPSS28409. For MPSS78528, the associated miRNA mir162 appeared twice in the Arabidopsis genome (upstream of At5g08180 and upstream of At5g23060) and the MPSS sequence mapped exactly to those regions. For MPSS28409, its second genomic match was on the opposite strand of an intron in gene At3g04740, which was very unlikely to be a source for MPSS sequences because samples for MPSS were prepared from mRNA or other type of polyadenylated RNA molecules, in which introns should have been processed. Thus, the MPSS data accurately reflected the expression of 14 known Arabidopsis miRNAs from a total of 19, indicating that it can be used as a source of indirect experimental support for the expression of predicted miRNAs. We then assessed the presence of MPSS signature sequences for the 83 predicted miRNAs. Using the approach described above, 23 MPSS signature sequences corresponding to the flanking sequences of 16 predicted miRNAs were found (see Additional data file 1). All 23 MPSS signature sequences were present in both the public and our own MPSS datasets, and mapped uniquely to the miRNA flanking sequence. The expression of nine miRNA candidates supported by MPSS data was also tested by northern blot hybridization, with eight of them producing a positive signal. Another three miRNAs with MPSS data were found in the ASRP database (see previous section and Additional data file 1). These results indicate that MPSS data indeed represent the expression of predicted miRNAs. Comparison of predicted miRNAs to known Arabidopsis miRNAs To explore the relationship of predicted miRNAs to known Arabidopsis miRNAs, we compared the sequences of all 83 miRNA candidates from our prediction with sequences of the 19 known Arabidopsis miRNAs. Eight predicted Arabidopsis miRNAs exhibited high sequence similarity to one or more known Arabidopsis miRNAs and could be grouped into five clusters (Figure 5 ). We could not find convincing evidence that Arabidopsis and animal miRNAs are related, as clustering of these required the insertion of multiple gaps in the alignments (data not shown). Putative mRNA targets of predicted Arabidopsis miRNAs A previous study has predicted that most known plant miRNAs bind to the protein-coding region of their mRNA target with nearly perfect sequence complementarity, and degrade the target mRNA in a way similar to RNA interference (RNAi) [ 29 ]. Analysis of several targets has now confirmed this prediction, making it feasible to identify plant miRNA targets [ 12 , 15 , 16 ]. We developed a computational method based on the Smith-Waterman nucleotide-alignment algorithm to predict mRNA targets for the 83 newly identified miRNA candidates reported in this paper (see Materials and methods for details). Focusing on miRNA complementary sites that were conserved in both Arabidopsis and O. sativa , our method was able to identify 94% of previously confirmed or predicted mRNA targets for known conserved Arabidopsis miRNAs. Applying the method to the 83 predicted Arabidopsis miRNA candidates and their O. sativa orthologs, we predicted 371 conserved mRNA targets for 77 predicted Arabidopsis miRNAs, with an average of 4.8 targets per miRNA. The signal-to-noise ratio of the miRNA targets prediction was 4.1:1 when using randomly permuted sequences with the same nucleotide composition to miRNA sequences as negative controls that went through the same target prediction process. A complete list of these predicted target mRNAs and their pairings with miRNA sequences is available in Additional data file 4. Of the 371 predicted miRNA targets, 10 were potential targets of two independent miRNAs, one (At3g54460 mRNA) was a potential target of three different miRNAs (At1g60020_5_14, At3g27883_1009, At5g62160_613_rc), and the rest were targets of a single miRNA. We assessed the biological functions of all predicted miRNA targets using gene ontology (GO) [ 45 ]. GO terms for 254 targets were found in the molecular function class. Molecular functions of the putative miRNA targets included transcription regulator activity, catalytic activity, nucleic acid binding, and so on, as summarized in Table 2 . As some proteins were classified in more than one molecular function category, the total number of targets listed in different function categories in Table 2 exceeds the number of targets with GO function assignment. Consistent with previous reports [ 29 ], a large proportion of predicted targets encoded proteins with transcription regulatory activity, corresponding to 50% of total targets with GO annotation (129/254). One interesting phenomenon was that most transcription regulators in the miRNA target set were plant specific, such as MYB, AP2, NAC, GRAS, SBP and WRKY family transcription factors (Table 3 ). For example, the miRNA target set included 10 plant specific NAC-domain-containing transcription factors, corresponding to 9% of total NAC-domain-containing transcription factors encoded by the A. thaliana genome. In contrast, 139 genes encoding a general transcription factor bHLH were found in the A. thaliana genome, but only three were putative miRNA targets. We analyzed the expression patterns of potential targets to look for indications that they were under miRNA regulation. Twelve of the 14 miRNAs confirmed by northern blot hybridization showed an increased accumulation in flower tissue compared to the other tissues tested (Figure 2 ), suggesting a role for miRNAs in regulating flower-specific events. In a search of Arabidopsis microarray gene expression data available from The Arabidopsis Information Resource (TAIR) [ 46 ], we found the expression profile for 11 predicted mRNA targets that can base-pair nearly perfectly with five confirmed flower-abundant miRNAs. We hypothesized that expression levels of these targets in flower tissue could be decreased as compared to whole plant RNA samples as a result of mRNA cleavage induced by miRNA regulation. Accordingly, a reduced expression level (more than 1.25-fold decrement) was found for eight genes in total flower mRNA compared to total whole plant mRNA, with another three whose expression was almost unchanged (Table 4 ). A t -test on the possibility of decreased expression between transcripts listed in Table 4 and in the entire microarray data resulted in a p -value of 0.04, indicating that the decreased expression observed for predicted miRNA targets is significantly different from the general expression pattern of the entire microarray data. Target mRNA fragments resulting from miRNA-guided cleavage are characterized by having a 5' phosphate group, and cleavage occurs near the middle of the base-pairing interaction region with the miRNA molecule. Using a modified RNA ligase-mediated 5' rapid amplification of cDNA ends (5' RACE) protocol, we were able to detect and clone the At3g26810 mRNA fragment corresponding precisely to the predicted product of miRNA processing (Figure 6 ). Two other genes, At3g62980 (TIR1) and At1g12820, share extensive sequence homology with At3g26810 and were also predicted to be targets of miR393a. Consistent with this, we also identified the corresponding RNA fragments derived from miRNA cleavage by 5' RACE (data not shown). We were not able to identify other targets from flower RNA samples using a similar approach. The microarray data used in this tissue comparison experiment includes around 7,400 genes only (about a quarter of the entire Arabidopsis genome). Thus, we expect the expression profile of more mRNA targets to be determined as more whole-genome tissue comparison data is available. Discussion We have developed and applied a computational method to predict 95 Arabidopsis miRNAs, which include 12 known ones and 83 new sequences. All 83 new miRNAs are conserved with more than 90% identity across the Arabidopsis and rice genomes. The expression of 19 new miRNAs was confirmed by northern blot hybridization or found in a publicly available database of small RNA sequences. MPSS data support was also found for 14 known and 16 predicted Arabidopsis miRNAs. Of the 16 miRNAs, 10 were confirmed by northern blot hybridization or by their presence in the ASRP database, and six have MPSS data only. In total, we have found direct or indirect experimental evidence for 25 predicted miRNAs. We expect more evidence to be found for other predicted miRNAs as independent experimental data, such as small RNA sequencing and MPSS data, grow. Among the 83 predicted miRNAs, eight have strong sequence similarity with known plant miRNAs. The prediction results and supporting experimental evidence are summarized in Table 5 . Additional data file 1 summarizes the corresponding evidence for known miRNAs and contains additional detailed information for each new candidate. Potential functionally conserved mRNA targets were found for 77 predicted miRNAs. Assessment of miRNA prediction The prediction method developed in this study uses computable sequence and structure properties that characterize the majority of the known Arabidopsis miRNA genes to constrain the miRNA search space. Parameters used in the prediction were selected to minimize false positives while maximizing true positives. Thus, seven known miRNAs (37%) were missed using our selected parameters. However, relaxing the loop length range to include all known miRNAs increased the number of candidate hairpins from around 180,000 to around 337,000 (a 53% increase). As the method requires stringent miRNA sequence conservation between Arabidopsis and O. sativa , miRNAs with little or no sequence conservation in other genomes will be overlooked by this method. Given the current knowledge of miRNAs, it is difficult to develop computational methods to distinguish non-conserved miRNAs from noise. The prediction method developed here is not specific for Arabidopsis and can be applied to other pairs of related genomes as well. We attained a 67% success rate of northern blot hybridization on all tested miRNA candidates, demonstrating the expression of 12 miRNAs from a total of 18 tested candidates. Failure to detect miRNA candidates by northern blot hybridization could be due to the limited number of sample tissues tested, as specific miRNAs may be expressed only under particular conditions (stimuli and/or developmental stages) or in specific cell types. For instance, further analysis of miR169g* (shown in Figure 2a ) indicated a higher accumulation in mature siliques than in the seedling stage (J.L.R. and N-H.C., unpublished work). This can only be determined by detailed study of individual miRNAs, which is not possible in a general screening such as the one presented here. Alternatively, the expression level of certain miRNAs may fall below the detection limit of our assay conditions. Consistent with this idea, in all cases the confirmed miRNAs were detected only after an extended period of autoradiography (2-3 days), as compared with known miRNAs that were more easily detected (see Figure 2 and data not shown). The low abundance of the newly identified miRNAs is in agreement with the limited number of miRNAs identified to date using the established cloning strategies. MPSS support for miRNAs and possible polyadenylation of precursor transcripts We made an intriguing discovery by identifying known Arabidopsis miRNAs and their approximate precursor sequences in MPSS polyadenylated transcript datasets. All but two MPSS sequences reported here uniquely map to the mature miRNA sequence or to the flanking sequence 500 nucleotides upstream or downstream (see Results). The MPSS sequence locations and orientations indicate that they are not transcripts derived from surrounding annotated genes. All but one tested miRNA candidates with MPSS evidence produced positive signals in northern blot hybridizations. As MPSS cDNA libraries are generated using polyadenylated RNA molecules [ 40 , 41 , 43 , 44 ], the presence of 14 known Arabidopsis miRNAs from a total of 19 in these datasets strongly indicates that at least some, if not all, plant miRNAs have a polyadenylated precursor form at some stage of their biogenesis. Predicted miRNAs detected by both northern blot hybridization and MPSS have consistent tissue-specific expression profiles under both methods. This supports the notion that the MPSS data reflect miRNA expression patterns. The public MPSS datasets are accessible only through an online interface that allows direct query of 17-nucleotide MPSS sequences. Direct comparison of the public sequences and predicted miRNAs was not possible. Thus, we were limited in our analysis to inquire whether a private MPSS sequence was also in the public MPSS dataset. Consequently, only MPSS sequences that appeared in the private set alone or in both sets were available to support miRNA prediction. The public MPSS dataset has 120-fold more signature sequences (more than 12 million additional tags) than our private MPSS dataset (approximately 94,000 tags total). Thus, we expect far more MPSS evidence for expression of the predicted miRNAs to be found in the public MPSS datasets when the public MPSS data are available to be compared locally. Target mRNAs for predicted miRNAs We used phylogenetic conservation as a constraint on miRNA target mRNA prediction: only transcripts that had at least one O. sativa functional ortholog among the top 500 rice miRNA targets were considered as potential miRNA target genes. Because all miRNA candidates reported here are highly conserved in rice, it is expected that their mRNA targets should also be conserved. Transcripts encoding proteins with ambiguous annotations, such as those for hypothetical proteins, expressed proteins and putative proteins, are not included in the target prediction because of the difficulty in identifying their orthologs in the O. sativa genome. Thus, the absence of predicted mRNA targets for the minority of the miRNAs may be due to the unfinished annotation of the O. sativa genome or to the divergence of target mRNA sequences that may preclude its identification. Gaps and mismatches are commonly seen in known animal miRNA::mRNA base-pairing interactions and, as a result, miRNA binding represses the translation of their targets [ 1 ]. Although in most known cases plant miRNAs tend to pair nearly perfectly with their target mRNAs and induce mRNA cleavage [ 12 , 15 , 17 , 29 ], recent evidence has shown that plant miRNAs can also repress target mRNA translation in a way similar to that of animal miRNAs [ 1 , 30 , 31 ]. To further explore the function of Arabidopsis miRNAs in target mRNA translation repression, in this prediction we allowed gaps and mismatches in the putative Arabidopsis miRNA::mRNA pairs. The free energy of 90% of the predicted miRNA::mRNA pairs is lower than the average free energy of known animal miRNA::mRNA pairs (ΔG = -14 kcal/mol) [ 32 ], indicating that the predicted miRNA::mRNA pairs are potentially stable at the energy level if similar interactions are present in plants (see Additional data file 4). Our prediction of target mRNAs for the new 83 miRNA candidates reveals that a broad functional range of genes may be regulated by miRNAs (Table 4 and Additional data file 4). As in previous findings, the predicted miRNA targets were enriched for transcription factors [ 29 ]. Our prediction also included transcripts encoding proteins with transcription regulator activity, catalytic activity, signal transducer activity and translation regulator activity. This result is consistent with recent findings in animal miRNA targets, and suggests a broader role for miRNA regulation in plant gene expression [ 29 , 32 - 35 ]. We took advantage of available microarray data to assess the relative expression levels of potential mRNA targets in tissues in which their miRNAs were expressed. For mRNA targets of several newly identified miRNAs, we found reduced expression levels in RNA samples from flowers compared to the whole plant. Accordingly, we identified the cleavage product of At3g26810 mRNA, and those of another two homologous genes, At1g12820 and TIR1 (At3g62980), to confirm them as targets of the same miRNA (miR393a). These genes encode F-box proteins, and TIR1 in particular is involved in auxin-mediated protein degradation [ 47 ]. Interestingly, F-box proteins are another group over-represented among the target mRNAs (48 out of 254, or 19%), while there are around 700 F-box proteins encoded in the Arabidopsis genome (2.1%) [ 48 ]. Remarkably, these are the first confirmed plant miRNA targets that are not transcription factors, with the exception of DCL1 and AGO1. The identity and expression pattern of a target mRNA can help identify the specific expression profile of its corresponding miRNA. Tissues with low mRNA expression levels should be checked carefully for miRNA expression. Currently, this kind of search is limited by the availability of genome-wide and tissue-/time-specific microarray data. As such data accumulate, their analysis will enrich our understanding of the different biological processes regulated by microRNAs. Materials and methods Computational prediction of Arabidopsis miRNAs The Arabidopsis genome version 3 and the O. sativa genome released by The Institute for Genome Research (TIGR) on 22 July 2002 [ 49 ] and 24 January 2003 [ 50 ], respectively, were used for the present study. Intergenic regions of both the A. thaliana and the O. sativa genomes were extracted according to the annotations provided by TIGR. A scanning algorithm implemented in the Perl programming language was used to search for possible hairpin structures within each intergenic sequence in A. thaliana . The method inspects each successive 21-nucleotide query window in each intergenic region, with two nucleotide increments, and searches for downstream complementary sequences with up to 25% mismatches. We restricted the distance from the last base of the forward query sequence and the first base of the downstream complementary pairing sequence to a minimum of 10 nucleotides and a maximum of 150 nucleotides (loop length). For each 21-nucleotide query, the loop length was increased one nucleotide at a time, and all downstream 21-nucleotide pairing sequences with more than 75% identity to the complement of the query sequence were considered as possible 'pairing sequences'. For each query sequence, the downstream complementary sequence with the fewest mismatches was saved as the pair sequence for the query. Insertions and deletions were allowed in the alignment and were counted as mismatches. Sequences from the start of a qualified querying sequence to the end of its downstream complementary pairing sequence were considered as a potential miRNA precursor with putative hairpin structure. Twenty extra nucleotides were extracted from the genome at each end of a potential miRNA precursor for the purpose of structure check using mfold [ 38 ]. A G+C-content filter and a loop-length filter were applied to the 312,236 hairpin structures obtained. Only hairpins with a loop length between 20 and 75 nucleotides and 21-mer sequences with a G+C-content between 38 and 70% were analyzed further. The remaining 21-mer sequence pairs were aligned with rice intergenic regions using BLASTN (version 2.2.6) to identify homologous sequences in O. sativa intergenic regions with 90% or higher sequence identity. The secondary structure of Arabidopsis miRNA candidate precursors and their rice precursor orthologs was evaluated using mfold [ 38 ]. Only 21-mers whose Arabidopsis precursor and rice ortholog precursor both had a hairpin-like folding as their lowest energy states were considered as miRNA candidates. A sequence alignment search against non-coding RNAs collected in Rfam [ 51 ] using BLASTN (version 2.2.6) was applied to identify and remove homologs of non-coding RNAs other than miRNAs. The remaining 95 sequences were retained as our final miRNA dataset. Northern blot hybridizations Two-day-old seedlings, 4-week-old adult plants, root-regenerated calluses and mixed-stage flowers of A. thaliana (Col-0) were used to extract total RNA using the trizol reagent (Invitrogen). Samples of 20 μg total RNA were resolved in a 15% polyacrylamide/1x TBE/8 M urea gel and blotted to a zeta-probe membrane (BioRad). DNA oligonucleotides with the exact complementary sequence to candidate miRNAs were end-labeled with [γ- 32 P]ATP and T4 polynucleotide kinase (New England Biolabs) to generate high specific activity probes. Hybridization was carried out using the ULTRAHyb-Oligo solution according to the manufacturer's directions (Ambion), and signals were detected by autoradiography. Finding MPSS evidence for miRNA candidates To obtain genomic regions corresponding to miRNA precursors, we extracted 500 nucleotides upstream and downstream of every genomic locus of all known and predicted Arabidopsis miRNAs. If an intergenic region encoding a miRNA had fewer than 500 nucleotides on either side of the miRNA locus, sequences were extracted up to the neighboring gene. Two Arabidopsis MPSS datasets were used in this study: a MPSS database from abscisic acid (ABA)-treated plants, and plants with elevated levels of endogenous cytokinin [ 43 , 44 ] and a second public MPSS dataset produced by the Meyes laboratory at the University of Delaware, which covers gene-expression information for five Arabidopsis tissues at different developmental stages - around 10-week-old active growing calluses initiated from seedlings, mixed-stage buds and immature flowers, 14-day-old leaves, 14-day-old roots and 24- to 48-h post-fertilization siliques [ 42 ]. miRNA target gene prediction and 5' RACE miRNA target gene prediction was performed by aligning miRNA sequences with target mRNA sequences using the TimeLogic implementation of the Smith-Waterman nucleotide-alignment algorithm. Sequences of known and predicted Arabidopsis miRNAs and their O. sativa orthologs were used as query datasets. mRNA sequences of the Arabidopsis and O. sativa annotated genes were used as target datasets. Gaps were allowed in the pairing of miRNA and their target mRNAs. Mismatches were preferred over gaps by assigning higher penalties to gaps in the alignment algorithm. Consecutive gaps were preferred over scattered individual gaps by assigning higher penalties to gap opening than to gap extension. The top 500 putative hits from Arabidopsis miRNA target list and their O. sativa ortholog target list were compared. For each mRNA hit of an Arabidopsis miRNA, if a rice ortholog from the same gene family was also found among the top 500 rice miRNA hits, the Arabidopsis mRNA hit was selected as a putative miRNA target. Tissue comparison (reference vs flower) microarray data used for target gene validation were downloaded from TAIR [ 46 ]. mRNA samples from whole plants and flowers were used as reference and sample probes in the microarray hybridization. To identify the products of miRNA-directed cleavage we used the First Choice RLM-RACE Kit (Ambion) in 5' RACE experiments, except that we used total RNA (2 μg) for direct ligation to the RNA adaptor without further processing of the RNA sample. Subsequent steps were according to manufacturer's directions. Oligonucleotide sequences for PCR amplification of At3g26810, At1g12820 and TIR1 (At3g62980) are available upon request. miRNA clustering and alignment Predicted miRNAs were compared to known Arabidopsis miRNAs using the MEME motif-searching software and Smith-Waterman gapped local alignment to identify homologs of known miRNAs. Pairs of aligned sequences were grouped by transitive closure, and multiple alignments were generated with ClustalW [ 52 - 54 ]. The multiple alignment output was manually curated. Free energy calculation We used mfold program to calculate the free energy (ΔG) of predicted miRNA::mRNA pairs. For each miRNA::mRNA pair, the miRNA sequence was linked by 'LLL' to the target mRNA sequence. The 'LLL' linker sequence tells the mfold program to treat the miRNA and target sequence as two separate RNA sequences for energy calculation [ 38 ]. Note added in proof During revision of this manuscript, three groups [ 55 - 57 ] reported novel Arabidopsis miRNAs, some of which are included among the predicted miRNAs in this work, confirming the validity of our approach. Additional data files The following additional data are available with the online version of this paper: the complete list of predicted miRNAs (Additional data file 1 ); a full list of the secondary structures of predicted precursors of Arabidopsis miRNA candidates and their rice orthologs (Additional data file 2 ); MPSS evidence for known and predicted Arabidopsis miRNAs (Additional data file 3 ); a complete list of predicted target mRNAs and their pairing with miRNA sequences (Additional data file 4 ). Supplementary Material Additional data file 1 The complete list of predicted miRNAs Click here for additional data file Additional data file 2 A full list of the secondary structures of predicted precursors of Arabidopsis miRNA candidates and their rice orthologs Click here for additional data file Additional data file 3 MPSS evidence for known and predicted Arabidopsis miRNAs Click here for additional data file Additional data file 4 a complete list of predicted target mRNAs and their pairing with miRNA sequences Click here for additional data file

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Does the 12-item General Health Questionnaire contain multiple factors and do we need them?

Background The 12-item General Health Questionnaire (GHQ-12) is widely used as a unidimensional instrument, but factor analyses tended to suggest that it contains two or three factors. Not much is known about the usefulness of the GHQ-12 factors, if they exist, in revealing between-patient differences in clinical states and health-related quality of life. Methods We addressed this issue in a cross-sectional survey of out-patients with psychological disorders in Singapore. The participants (n = 120) completed the GHQ-12, the Beck Anxiety Inventory, and the Short-Form 36 Health Survey. Confirmatory factor analysis was used to compare six previously proposed factor structures for the GHQ-12. Factor scores of the best-fitting model, as well as the overall GHQ-12 score, were assessed in relation to clinical and health-related quality of life variables. Results The 3-factor model proposed by Graetz fitted the data better than a unidimensional model, two 2-factor models, and two other 3-factor models. However, the three factors were strongly correlated. Their values varied in a similar fashion in relation to clinical and health-related quality of life variables. Conclusions The 12-item General Health Questionnaire contains three factors, namely Anxiety and Depression, Social Dysfunction, and Loss of Confidence. Nevertheless, using them separately does not offer many practical advantages in differentiating clinical groups or identifying association with clinical or health-related quality of life variables.

Background Recent studies of disease burden have demonstrated the importance of psychological disorders. For instance, depression was the fourth leading cause of disease burden, accounting for 4.4% of total disability adjusted life years in the world in 2000 [ 1 ]. The 12-item General Health Questionnaire (GHQ-12) has been widely used in many countries for detecting psychological morbidity. Some major national studies such as the British Household Panel Survey (BHPS) also employ this instrument [ 2 ]. Calibration of this instrument may therefore contribute significantly to a large community of researchers. While the longer versions of the GHQ are normally considered multidimensional, the GHQ-12 is often regarded as measuring only a single dimension of psychological health. For example, Corti [ 3 ] analyzed the GHQ-12 data in the BHPS and maintained that the high Cronbach's alpha value indicated the unidimensionality of this instrument. However, several authors suggested that the GHQ-12 contained two or three clinically meaningful factors. Using principal component analysis, Politi et al. [ 4 ] identified two factors: general dysphoria and social dysfunction. Andrich and van Schoubroeck [ 5 ] suggested that the positively worded items formed one factor and the negatively worded items formed another. Graetz [ 6 ], Martin [ 7 ] and Worsely and Gribbin [ 8 ] proposed three different 3-factor models. In a multi-centre study, although considerable between-centre variation was found, the final solution tended to have either two or three factors [ 9 ]. Using confirmatory factor analysis (CFA) to analyze the BHPS data, Cheung [ 10 ] compared various models and found that the 3-factor model proposed by Graetz [ 6 ] gave the best fit. The factors are anxiety and depression (4 items), social dysfunction (6 items), and loss of confidence (2 items). In a study of employees in New Zealand, Kalliath et al [ 11 ] also employed CFA to compare various models. They also found that Graetz's 3-factor model gave better goodness-of-fit than the others. However, they maintained that none of the models they examined gave a sufficient level of goodness-of-fit. Hence they modified the instrument to propose a short (8-item) version of GHQ. In a study of college students and young adolescents in Australia, French and Tait [ 12 ] found that Graetz's model not only fitted the data better than other models, but also satisfactorily achieved some fit indices targets such as Comparative Fit Index > 0.95. In a study of a rural population in Australia [ 13 ], the model of Worsely and Gribbin fitted best and that of Graetz was second best. While the structure of the GHQ-12 has been studied using factor analysis methods, the construct validity and usefulness of those resulting factors are not often tested. The question is whether the additional information provided by the 2 or 3 factors, if they exist, is clinically useful. In other words, will multiple scores be more useful than a total single score in helping us to understand respondents' health status? The purpose of this study was therefore two-fold. First, we aimed to compare the previously proposed models of the GHQ-12 in an oriental population and identify the best-fitting one. It was not our objective to assess their absolute level of fit or to derive new model or version of the GHQ. Second, we aimed to assess whether the factors identified relate to clinical and health-related quality of life variables in different ways. Methods Subjects and study design A consecutive sample of outpatients with anxiety disorders and/or depressive disorders was recruited from a psychiatric clinic at a tertiary hospital in Singapore. Inclusion criteria were the presence of any anxiety disorder and/or major depressive disorder, literacy in English or Chinese, and completion of an informed consent form. Patients with organic brain syndrome or psychosis were excluded. During routine consultation visits, diagnoses of recruited patients were ascertained by a psychiatrist using DSM-IV criteria and the severity of their psychiatric disorders was assessed using a Clinical Global Impression (CGI) scale, which ranges from 1 (very mild) to 5 (very severe). Patients were then given a questionnaire containing the General Health Questionnaire (GHQ-12) [ 14 ], the Beck Anxiety Inventory (BAI) [ 15 ], and the Short Form-36 Health Survey (SF-36) [ 16 ] for self-completion. Identical English and Chinese questionnaires were prepared for subjects to select according to their preference. A research assistant checked returned questionnaires for completeness. Instruments The General Health Questionnaire (GHQ-12) consists of 12 items, each assessing the severity of a mental problem over the past few weeks using a 4-point scale (from 0 to 3). The score was used to generate a total score ranging from 0 to 36, with higher scores indicating worse conditions [ 14 ]. The Chinese version of GHQ-12 used in this study had been validated [ 17 , 18 ]. A previous study of the 60- and 30-item versions of English and Chinese GHQ yielded comparable scale scores, suggesting equivalence for the two language versions [ 19 ]. The Beck Anxiety Inventory (BAI) is a valid and reliable self-report checklist for anxiety symptoms [ 15 ]. This instrument consists of 21 items, each describing an anxiety symptom for a respondent to assess how much he or she has been bothered by the symptom over the past week on a 4-point scale. Responses to all items are summed up to a total score ranging from 0 to 63, with higher scores indicating more severe anxiety. A Chinese BAI was developed by the authors using forward- and back-translation procedures, and refined after a pilot study of subjects with anxiety disorders [ 20 ]. The Short Form 36 Health Survey (SF-36) [ 16 ] is a 36-item questionnaire assessing functional health-related quality of life (HRQoL) in 8 domains: physical functioning, role limitations due to physical problems, bodily pain, general health, vitality, social functioning, role limitations due to emotional problems, and mental health. The instrument yields each domain a score ranging from 0 to 100, with higher scores indicating better HRQoL. The validity and reliability of SF-36 have been extensively documented [ 21 ]. In Singapore, both the UK English [ 16 ] and Chinese (Hong Kong) [ 22 ] versions of SF-36 have been validated [ 23 , 24 ] and these two language versions appear to be equivalent [ 25 ]. Statistical analysis Various factor structures of the GHQ-12 were tested by confirmatory factor analysis. Model I was unidimensional. Model IIA contained 2 factors: General Dysphoria and Social Dysfunction [ 4 ]. Model IIB also contained 2 factors: positively worded items forming one factor and negatively worded items forming another [ 5 ]. Model IIIA contained 3 factors: Cope, Stress and Depress, identified by Martin [ 7 ]. Model IIIB was the 3-factor model proposed by Graetz [ 6 ]: Anxiety and Depression, Social dysfunction, and Loss of Confidence. Model IIIC was also a 3-factor model: Anhedonia-Sleep disturbance, Social Performance and Loss of Confidence [ 8 ]. In the confirmatory factor analysis the number of factors and the relationship between factors and observed GHQ-12 items were pre-specified according to the models. The loading of an item on a factor within a model was estimated using the maximum likelihood method. Methodologists have emphasized that it is desirable to use different indicators to examine a model's goodness-of-fit [ 26 ]. The fit of the six models was assessed by three measures. The Akaike's Information Criterion (AIC) penalizes the maximum log likelihood of a model according to its number of parameters. A model with a lower AIC is more plausible than one with a higher AIC. Instead of showing relative fitness, the Comparative Fit Index (CFI) assesses the fit of a model itself. The values range between 0 and 1. A CFI larger than 0.90 indicates an acceptable model. (Hu and Bentler [ 27 ] suggested that a CFI value above 0.95 indicates an acceptable model. In a later section we will discuss the more stringent cutoff.) The Root Mean Square of Approximation (RMSEA) assesses a model's amount of error. An RMSEA value larger than 0.08 indicates too much error. The best-fitting model was examined in detail. The Kruskal-Wallis test was used to compare the GHQ-12 overall and factor scores of patients with different diagnosis. Pearson's correlation coefficient (r) was used to assess the association between GHQ-12 scores and various variables, namely Beck Anxiety Inventory, Clinical Global Impression and SF-36 scores. The Fisher's Z transformation was used to produce 95% confidence interval. Results and Discussion A total of 120 participants (63 man and 57 women) were included in the analysis (Table 1 ). Most (90%) respondents were Chinese; the mean (SD) age was 43.1 (12.7). Sixty six percent of the participants chose to administer an English version of the questionnaire. The mean scores of clinical and HRQoL data reported by the respondents in both gender were shown in Table 1 . Men tended to have less anxiety, better clinical global impression, and higher SF-36 scores. Table 1 Mean (SD) clinical and SF-36 health-related quality of life values by gender Clinical or psychological data Men ( N = 63) Women ( N = 57) (a) Beck Anxiety Inventory 20.65 (13.48) 21.89 (13.59) Clinical Global Impression 2.76 (0.84) 3.02 (0.82) Physical Functioning 76.50 (17.88) 73.72 (17.97) Physical Problems 51.06 (43.57) 43.42 (42.13) Bodily Pain 62.06 (24.89) 53.46 (24.05) General Health 49.48 (21.14) 49.21 (20.07) Vitality 45.40 (18.15) 41.26 (19.94) Social Functioning 56.15 (23.75) 50.22 (26.88) Emotional Problems 39.15 (42.56) 26.32 (41.18) Mental Health 51.05 (17.65) 46.67 (19.11) (a) N = 56 for Clinical Global Impression scale due to a missing value. Table 2 shows goodness-of-fit statistics for the 1-, 2- and 3-factor models. The 3-factor model (IIIB) proposed by Graetz (1991) was the best in terms of all three fit statistics. It gave the lowest AIC and RMSEA and highest CFI. Its CFI was 0.935. All six models produced RMSEA's which exceeded 0.08. The one-dimensional model (Model I) had the highest AIC, highest RMSEA and lowest CFI. Table 2 Goodness-of-fit of six confirmatory factor analysis models (N = 120) (a),(b) Statistics Model I (1 factor) Model IIA (2 factors) Model IIB (2 factors) Model IIIA (3 factors) Model IIIB (3 factors) Model IIIC (3 factors) AIC 69.529 29.220 29.956 51.611 21.075 48.956 CFI 0.888 0.927 0.925 0.908 0.935 0.910 RMSEA 0.139 0.115 0.115 0.130 0.109 0.128 (a) AIC: Akaike's Information Criterion; CFI: Comparative Fit Index; RMSEA: Root Mean-Square Error of Approximation (b) See text for details about the models. Figure 1 displays the standardized factor loadings and between-factor correlation of model IIIB. The factor loadings ranged between 0.72 and 0.90. The three factors were strongly correlated. The correlation between factor 1 (Anxiety and Depression) and factor 2 (Social Dysfunction) was 0.89. The correlation between factor 2 and factor 3 (Loss of Confidence) was 0.83. That between factor 1 and 3 was 0.90. These strong correlations suggest that even if there were in fact three factors, in practice it may be very difficult to discern them. Figure 1 Standardised factor loadings and between-factor correlations of Graetz's model [6]. Boxes represent GHQ-12 items; ellipses represent factors. One-way and two-way arrows indicate factor loadings and between-factor correlations, respectively. Having established that Graetz's 3-factor model fitted the data better than the other models, we calculated the factor scores as unweighted sums of the items concerned. From figure 1 we could see that the loadings on each factor did not vary substantially. Hence we chose to use unweighted sums for simplicity. Table 3 shows the mean (SD) factor scores and the overall GHQ-12 score by clinical diagnosis. Some patients had multiple diagnoses; we categorized them into one of three major clinical diagnoses. The three factor scores and the overall GHQ-12 scores behaved in fairly similar ways. All four scores were significantly different between patients with and without depression; none was significantly different between patients with and without general anxiety disorder. Patients with panic disorder had lower scores on the factor Loss of Confidence (difference = 0.68; P = 0.043). The SD of the two diagnosis groups pooled was about 1.75; the between group difference was therefore approximately about 0.4 SD. Table 3 Comparison of mean (SD) values of GHQ-12 scores by clinical diagnosis. Diagnosis N Overall GHQ-12 score Anxiety and depression (Factor 1) Social dysfunction (Factor 2) Loss of confidence (Factor 3) Depression Yes 60 32.15 (9.18) 11.28 (3.10) 15.73 (4.74) 5.13 (1.83) No (Other diagnosis) 60 27.43 (6.74) 9.48 (2.86) 13.73 (3.06) 4.22 (1.62) P-value (a) 0.002 0.002 0.010 0.005 General anxiety disorder Yes 47 30.02 (8.10) 10.68 (2.99) 14.64 (3.96) 4.70 (1.82) No (Other diagnosis) 73 29.64 (8.58) 10.19 (3.18) 14.79 (4.20) 4.66 (1.77) P-value 0.712 0.410 0.987 0.993 Panic disorder Yes 54 28.48 (7.88) 9.96 (3.08) 14.22 (3.71) 4.30 (1.69) No (Other diagnosis) 66 30.86 (8.64) 10.73 (3.10) 15.15 (4.37) 4.98 (1.80) P-value 0.158 0.179 0.244 0.043 (a) Kruskal-Wallis test. Table 4 presents the results of the correlation of 3 factors of Graetz's model and BAI, Clinical Global Impression Score, and SF-36 scales. The 3 factors were correlated with the 10 clinical and HRQoL variables to very similar degree. Table 4 Pearson's correlation coefficients (95% confidence intervals) between GHQ-12 scores and clinical and health-related quality of life variables Clinical/HRQoL scales Overall GHQ-12 score Anxiety and depression (Factor I) Social dysfunction (Factor II) Loss of confidence (Factor III) Beck Anxiety Inventory 0.69 (0.58 to 0.77) 0.68 (0.57 to 0.77) 0.62 (0.50 to 0.72) 0.63 (0.50 to 0.72) Clinical Global Impression 0.49 (0.34 to 0.61) 0.45 (0.29 to 0.58) 0.47 (0.31 to 0.60) 0.43 (0.27 to 0.56) Physical functioning -0.17 (-0.34 to 0.01) -0.18 (-0.35 to 0.00) -0.16 (-0.33 to 0.02) -0.12 (-0.29 to 0.06) Role physical -0.63 (-0.73 to -0.51) -0.60 (-0.71 to -0.48) -0.61 (-0.71 to -0.48) -0.51 (-0.63 to -0.36) Bodily pain -0.52 (-0.68 to -0.44) -0.57 (-0.68 to -0.44) -0.43 (-0.56 to -0.27) -0.46 (-0.59 to -0.31) General health -0.57 (-0.68 to -0.44) -0.57 (-0.68 to -0.43) -0.52 (-0.64 to -0.38) -0.50 (-0.62 to -0.35) Vitality -0.71 (-0.79 to -0.61) -0.73 (-0.80 to -0.63) -0.63 (-0.73 to -0.51) -0.62 (-0.72 to -0.50) Social functioning -0.65 (-0.74 to -0.54) -0.62 (-0.72 to -0.50) -0.60 (-0.70 to -0.47) -0.59 (-0.70 to -0.46) Role emotional -0.62 (-0.72 to -0.50) -0.63 (-0.73 to -0.51) -0.55 (-0.66 to -0.41) -0.55 (-0.66 to -0.41) Mental health -0.67 (-0.76 to -0.56) -0.67 (-0.76 to -0.56) -0.60 (-0.70 to -0.47) -0.61 (-0.71 to -0.49) Several previous confirmatory factor analyses found that the 3-factor model of Graetz gave better fit to survey data from Australia [ 12 ], Britain [ 10 ] and New Zealand [ 11 ]. In this study we examined the issue in an Asian population in Singapore, whose members are mainly ethnic Chinese. All three goodness-of-fit indices employed, namely AIC, CFI and RMSEA, agreed that the 3-factor model of Graetz out-performed the other five models. The CFI value was 0.935. Conventionally, a CFI of 0.90 or larger is taken as evidence of sufficient fit. A more stringent criterion of CFI larger than 0.95 has recently been proposed and debated [ 27 , 28 ]. The RMSEA also indicated that even the best-fitting model did not fit well, using the cut-off of 0.08 as a criterion. However, our aim is to compare the models rather than to modify the instrument. So for our purpose it is the comparison of the goodness-of-fit of the six models that matters, not the absolute values of the fit indices. We consider the "correctness" and "usefulness" of a model two fairly separate issues. Although the goodness-of-fit of Graetz's model was limited, we proceeded to examine the factor scores in relation to external criteria in order to reach a conclusion about the usefulness of the model. The one-dimensional model was the worst according to all three goodness-of-fit indices. The three factors in the model proposed by Graetz were found to be strongly correlated with each other, with correlation coefficients in the neighborhood of 0.8 to 0.9. Such strong correlations suggest that even if there were indeed three different factors, in practice it is quite difficult to differentiate them. The study of French and Tait [ 12 ] also showed strong correlation between the factors, which led the authors to recommend that it may be prudent to use the overall score rather than overinterpret the factors within the GHQ-12. We examined the three factor scores and the overall GHQ-12 score in relation to clinical diagnoses. The four scores behaved in fairly similar ways. Although the Loss of Confidence scale was significantly different between patients with and without panic disorder while the other three scales did not show significant differences between the two groups of patients, the difference was only about 0.4 SD. This is smaller than a recommended threshold (0.5 SD) corresponding to minimal clinically important differences for health states questionnaires [ 29 ]. We also examined the association between the three GHQ scores and the Beck Anxiety Inventory, a clinical impression score, and the 8 scales of the SF-36. The three factors were associated with the clinical and HRQoL variables to similar degrees. Two limitations of the study should be noted. Firstly, the sample size was somewhat small for confirmatory factor analysis. Secondly, the participants were clinical cases. This homogeneity might have made it more difficult to detect variations in GHQ-12 scores. We believe that the question about the relative plausibility of various factor models have been sufficiently answered by this and several previous studies [ 10 - 12 ]. Nevertheless, future studies of non-clinical participants based on larger sample sizes will be helpful to further assess the practical usefulness of the factors of the GHQ-12. Conclusions Several studies, including the present one, have found that Graetz's 3-factor model of the GHQ-12 is more plausible than other models. However, the factors were strongly correlated and difficult to discern. Our analysis of the three GHQ scores in relation to clinical variables and aspects of health-related quality of life did not appear to be more informative than analysis of a single overall GHQ-12 score. As such, from a pragmatic point of view we consider it acceptable to use this instrument as a one-dimensional measure. Unless one has specific questions that are best answered by a subset of the three factors, there is no need to consider the multi-dimensionality. Authors' contribution FG carried out the confirmatory factor analysis, interpreted the findings, and drafted part of the manuscript. NL designed the study, participated in the development of the statistical framework and interpreted the findings. JT participated in the study design, discussion of the statistical framework, and the interpretation of findings. CF participated in the study design and carried out the data collection and clinical assessments. SCL participated in the study design and discussion and interpretation of findings. YBC conceived of the study, developed the statistical framework, carried out part of the statistical analysis, and drafted part of the manuscript. All authors read and approved the final manuscript.

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514495

Natural Biodiversity Breaks Plant Yield Barriers

The birth of agriculture, some 10,000 years ago in the Middle East's Fertile Crescent, revolutionized human culture and society. Refined farming techniques led to increased yields and freed humans from the demands of constant foraging. Along with that freedom came social complexity, division of labor, improved standards of living, and a measure of leisure time. Agriculture also led to overpopulation followed by starvation, conflict over fertile farming land, and environmental damage. For the Maya and other civilizations, such consequences proved fatal. Many consumer and environmental groups believe that modern industrial agricultural practices like factory farming of animals and genetic engineering of crops threaten to bring similar ruin. But with 6 billion people living on the planet—a figure that's expected to increase 50% in just 50 years—many plant scientists believe that feeding a burgeoning population will require the tools of biotechnology. Plant breeders face the daunting challenge of developing high-yielding, nutritious crops that will improve the global quality of life without harming the environment or appropriating dwindling natural habitats for agricultural production. A major roadblock to feeding the world is a continuing decline in the genetic diversity of agricultural crops, which has in turn limited their yield improvement. (Domestication often involves inbreeding, which by definition restricts the gene pool.) Now Amit Gur and Dani Zamir of Hebrew University report a way to lift these productivity barriers by tapping into the natural diversity of wild plants. Traditional plant breeders improve the quality and yield of crops by crossing plants with desired traits to create a new, hopefully improved, hybrid strain. But traditional breeding is limited by the available gene pool of a cultivated plant species and eventually hits a wall—reshuffling the same genetic variation can boost yield only so much. With the advent of biotechnology, plant scientists were buoyed by the prospect of improving plants through genetic modification. But aside from a few successes with introducing single-gene herbicide- and pest-resistant traits, most plant traits have proved too complex to repay the incorporation of a single transgene—that is, a gene taken from a different species—with the hoped-for response. Biotech-based investigations and applications in plant science have also been hampered by consumer reaction against genetically modified organisms. (For more on the techniques of modern plant breeding, see the essay “Diversifying Selection in Plant Breeding,” also in this issue.) Faced with these limitations, Gur and Zamir tried another approach—a back-to-nature approach. “Natural biodiversity is an unexploited sustainable resource that can enrich the genetic basis of cultivated plants,” they explain in the report. The distantly related wild cousins of cultivated plants can be seen as a “huge natural mutagenesis resource” with novel gene variants that can increase productivity, quality, and adaptability. Not only that, the genetic material of wild plants—every gene and regulatory element—has already been refined and tested by over a billion years of evolution and natural selection. To identify genomic regions in wild tomato species that affect yield, Gur and Zamir created a population of hybrid crosses of a wild tomato species and a cultivated tomato species; each line had a single genomic region from the wild tomato inserted into the cultivated plant. Rather than introducing a single wild tomato gene into the cultivated plants, the authors used a “pyramided” strategy that combined three independent yield-enhancing genomic regions from the wild species into the new plant line. Plants were grown over three seasons, during which they were exposed to different environments, including drought. By combining traditional phenotyping techniques—which characterize the plant's physical traits based on its genetic makeup—with genetic marker analysis, the authors identified a number of wild tomato genomic regions that increased yield. Their results demonstrate that an approach based on biodiversity—which takes advantage of the rich genetic variation inherent in wild relatives of cultivated crops—can produce varieties that outperform a commercially available hybrid tomato in both yield and drought resistance. Gur and Zamir attribute the improved performance to their unique pyramiding strategy. Their hybrid model—applying the tools of modern genomics to traditional plant breeding—offers plant breeders a powerful approach to improving the quality and yield of cultivated plants by taking advantage of the inherent biodiversity of the natural world. It's a strategy that may well apply to rice, wheat, and other vital staples of the world's food supply.

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522873

Discovery of estrogen receptor α target genes and response elements in breast tumor cells

Microarray analysis has identified 89 estrogen target genes. The cis -regulatory elements found upstream of those genes are not well conserved in mouse and human.

Background Estrogens are involved in a number of vertebrate developmental and physiological processes. Human and animal studies have revealed the roles of estrogen receptor (ER) in female and male sexual development and behavior, reproductive functions, and the regulation of the neuroendocrine and cardiovascular systems and bone metabolism [ 1 ]. Molecular characterizations of breast tumors and epidemiological studies have also shown important roles for estrogens and ERs in the genesis, progression, and treatment of breast cancers [ 2 , 3 ]. Two ER subtypes, ERα and ERβ, are known to mediate estrogen signaling; and they function as ligand-dependent transcription factors [ 4 ]. After traversing the cellular membrane, estrogens bind to the receptors, leading to receptor activation. ERs interact with cis -regulatory elements of target genes either directly by binding to previously described conserved estrogen response elements (EREs; 5'-GGTCANNNTGACC-3', where N is any nucleotide) or indirectly by associating with AP-1 and Sp1 transcription factor complexes and their respective binding sites [ 5 - 9 ]. Co-activators and co-repressors form complexes with ERs and are involved in regulating estrogen responses [ 10 ]. The cyclical turnover of ER and transcriptional complexes at the regulatory elements of target genes also presents an additional regulatory mechanism [ 11 - 13 ]. Tissue-specific distribution of co-regulators, associated transcription factor complexes, and receptor subtypes and splice variants are potential mechanisms for the observed pleiotropic effects of estrogens [ 14 ]. At the molecular level, the consequence of ER activation appears to be alterations in transcriptional activity and expression profiles of target genes. A number of genes, including those for trefoil factor 1/pS2, cathepsin D, cyclin D1, c-Myc and progesterone receptor, are positively regulated by ERα [ 15 - 20 ]. Transcriptional repression by ERs has been documented but is not as well studied or understood. Microarray experiments have been carried out, particularly in breast tumor cell lines, to study alterations in gene-expression profiles in response to estrogen treatment [ 21 - 27 ]. Many key issues remain to be addressed, however, using these initial inventories of responsive genes, including overall conservation of responses across cell lines, in vivo relevance in breast tumors, and cis -regulatory element mapping and molecular characterization and confirmation of the interaction between ER and putative target genes. In this study, we took a combinatorial approach to ERα target gene discovery and characterization by using high-density DNA microarrays to obtain a global gene-expression profile of hormone response in ERα-positive (EPα + ) breast tumor cells. This included drug treatments that interrogate ER-mediated and translation-independent regulation, integration of additional in vitro estrogen-response data and human breast tumor sample gene-expression data for candidate gene validation and identification of relevant in vivo targets, computational binding site modeling and promoter analysis to map putative ER-binding sites, and chromatin immunoprecipitation (ChIP) to characterize the interaction between ER and the regulatory elements of candidate target genes. Here we present our findings and discuss the insights they provide into the genome-wide architecture of the ER-mediated transcriptional regulatory network and its conservation in cell lines, breast tumors and through evolution. Results Global gene expression profile of estrogen response High-density DNA microarrays are powerful tools that simultaneously determine the transcriptional profiles of thousands of genes and are especially well suited for studies of transcription factor function. Previous efforts to determine changes in gene expression profiles following hormone treatment in MCF-7 [ 21 - 25 , 27 ] and ZR-75-1 [ 26 ] ER + breast carcinoma cell lines have yielded a number of novel estrogen-responsive genes and demonstrated the utility of such genome-scale technologies in studying estrogen biology. These earlier studies, however, only included anti-estrogen and cycloheximide (CHX) treatments either at a limited number of time points or only in validation assays for a handful of putative responsive genes. Therefore, to map more comprehensively the transcriptional regulatory network regulated by ER and to generate data in an additional ER + breast tumor cell context for cross-cell line analysis, we treated the estrogen-dependent T-47D ER + breast cancer cell line with 17β-estradiol (E2) and with E2 in combination with either the pure anti-estrogen ICI 182,780 (ICI) or the protein synthesis inhibitor CHX and performed high-resolution time-course gene-expression analyses (see Figure 1a for treatments and time points) using spotted oligonucleotide (60-mers) microarrays containing probes representing around 19,000 human genes. The concentrations of E2 (1 nM) and ICI (10 nm) used in this study were sufficient to respectively drive and inhibit hormone-responsive cell proliferation. T-47D cells differ in karyotypic abnormalities and nuclear receptor co-regulator expression levels from cell lines previously used - MCF-7 and ZR-75-1 - but have the advantage of expressing ER at more physiologic levels [ 28 , 29 ]. Samples were harvested on an hourly basis for the first 8 hours (0-8 hours) following hormone treatment and bi-hourly for the next 16 hours (10-24 hours) for a total of 16 time points surveyed (Figure 1a ). Estrogen-responsive genes were determined by statistical analysis of expression ratios in E2-treated samples versus the mock-treated controls using a two-tailed paired t -test with p -value cutoff. In addition, the genes were filtered for at least a 1.2-fold change in the same direction in three or more time points. Our choice of data-selection criteria was informed by the observed expression levels and profiles of known hormone-responsive and ER target genes such as the progesterone receptor, cathepsin D and stanniocalcin 2. Responsive genes were selected for E2 responsiveness ( p < 0.052) and filtered for ICI sensitivity ( p < 0.057) and CHX insensitivity ( p > 0.24) by comparing E2-treated samples with E2+ICI and E2+CHX samples to isolate putative ER downstream targets and direct targets, respectively. Figure 1b summarizes the statistics of the selection process. Expression profiles of estrogen-responsive genes were visualized by Eisen clustergrams and the genes were sorted by hierarchical clustering [ 30 ]. For estrogen-responsive genes (Figure 2a ), the expression profiles clustered into two groups: genes that are upregulated by hormone treatment (Figure 2a , red) and those that are downregulated (Figure 2a , green). Of the responsive genes, 58.5% (226/386) were upregulated following estrogen treatment. Figure 2b shows the expression profiles of the 137 genes specifically regulated by ER (defined by being responsive to estrogen and blocked by ICI treatment, Figure 2b , right panel). These genes cluster in a similar fashion as the estrogen-responsive genes. A notable finding is that ER-regulated genes, as determined by E2 response and ICI sensitivity, account for only 35.5% (137/386) of all estrogen-responsive genes, suggesting the possibility of ER-independent signal transduction mechanisms in mediating transcriptional responses to hormone exposure. Interestingly, ICI appears to have a greater effect on E2-upregulated than downregulated genes as these upregulated genes account for 71.5% (98/137) of the ICI-sensitive subset. Eighty-nine primary response genes constituted the putative ER direct targets - defined as responsive to hormone treatment, sensitive to ICI but not affected by CHX treatment (Figure 2c , right panel). From these observations the number of direct target genes involved in initiating hormone response in breast tumor cells might represent only 0.47% (89/18,912) of the genes in the human genome. The list of putative ER target genes is presented in Table 1 , and the complete listing of E2-responsive genes is given in Additional data file 4. Genes previously shown to be ER targets are shown in bold type (see Table 1 ). We note that five of the direct target genes on our list correspond to the results presented in the only other published microarray study to include anti-estrogen and CHX treatments as part of the experimental design [ 26 ]. The discrepancy between the two datasets is likely to be due to the differences in cell lines, experimental designs, array platform and the filtering parameters used for selecting target genes. For example, the Soulez and Parker study [ 26 ] utilized ZR-75-1 cells tested at only two time points (6 and 24 hours). Moreover, the Affymetrix HuGeneFL arrays used in that study contained probes for 5,600 genes as compared to the nearly 19,000 genes on our arrays, and represented early array technology with known limitations. Similarly, the absence of known target genes TFF1/pS2 and cyclin D1 in our list of direct targets is probably due to differences in the transcriptional cofactors and genomic abnormalities in the T-47D cells. The absence of the c- MYC proto-oncogene on our list is probably because the probe was not represented in the arrays used in our study. To control for the confounding direct effects of ICI and CHX, independent of E2, we also treated the cells with only ICI for 2, 8, 12 or 24 hours, or only CHX for 2 or 8 hours. CHX treatment partially obscured the responses in 4 of 89 genes (4.5%) that met the selection criteria for putative direct target genes by inducing a detectable E2-like effect following either CHX, E2, or E2+CHX treatments (see Additional data files 5 and 6). As this result does not rule out these genes as direct targets, we included them in the direct target list, but noted this caveat in Table 1 . CHX treatment alone had the opposite effect to E2 treatment in 32 (8.3%; 32/386) of the E2-responsive genes. However, in the presence of the hormone and the drug together (E2+CHX), CHX did not antagonize the E2 response of these genes and therefore did not affect the selection of putative direct targets. ICI treatment alone elicited an unexpected E2-like response (that is, identical response following either E2, ICI or E2+ICI treatments) in nine (2.3%; 9/386) E2 responsive genes. Because these nine genes did not meet the selection criteria for ICI antagonism, the putative direct target genes were also not affected. Thus, the independent effects of ICI and CHX did not substantially alter the final gene list or conclusions in our analysis. Comparison of T-47D and MCF-7 estrogen-response profiles A number of breast cancer cell lines have been used in in vitro studies of estrogen responses, but most of the data, including those from published microarray studies, have come from experiments using MCF-7 cells. Therefore, we were interested in comparing the expression profiles in response to hormone treatment between MCF-7 cells and the T-47D cells used in our studies. For our analysis, we obtained a publicly available MCF-7 hormone and tamoxifen response dataset [ 31 ] from the Stanford Microarray Database [ 32 ]. Using Unigene cluster IDs from build 166 as the common identifiers between the two datasets, we extracted expression data from 104 of 137 T-47D ER-regulated genes (Figure 3a ) that were also present in the MCF-7 dataset. For genes with multiple entries in the MCF-7 data, the entry with either the most complete data or with similar expression profiles to the T-47D results was selected for analysis. Overall, the results from the MCF-7 experiments correspond to the majority (64%; 66/103) of expression profiles of responsive genes obtained in the T-47D cells as defined by same direction changes in the available data points in MCF-7 cells following hormone treatment (see Figure 3a ). Using stringent selection criteria for the MCF-7 data for E2 response and sensitivity to tamoxifen treatment (see Materials and methods), we found 24 genes that can be defined as ER regulated in both MCF-7 and T-47D datasets. Remarkably, there was high concordance between the two studies with 23 out of 24 (96%) of the genes showing concordance in their expression response to estrogen (Figure 3b ). In contrast, there was little concordance in microarray datasets from unrelated stem-cell studies despite use of similar experimental systems and identical array platforms [ 33 ]. These findings were further validated by the many overlaps between the genes identified in this investigation and the estrogen-responsive genes reported by Frasor and colleagues (data not shown) [ 23 ]. The similarities we observe between the two ER studies with different experimental designs and array platforms suggest that the two ER + cell lines share common estrogen-response pathways. Differential expression of putative ER-regulated genes in breast tumors A key question we wished to address was whether the in vitro observations in cell lines reflected biological significance in vivo . To address this, we explored the association between the ER-regulated genes identified in our in vitro analysis and the ER status-associated expression profiles in breast tumor samples. We hypothesized that putative ER target genes should be differentially expressed in breast tumors in an ER status-dependent manner. For example, pS2/TFF1 and cyclin D1, both upregulated by estrogen treatment in MCF-7 cells, were shown to be expressed at higher levels in ER + tumors [ 34 , 35 ]. A number of breast cancer microarray studies have shown that ER status remains the most important prognostic marker and tumor classifier. Expression data from six breast cancer microarray studies (L.D.M., B.M.F. Mow, L.A.V., and E.T.L., unpublished work and [ 36 - 40 ]) were mined for genes that were differentially expressed ( p -value < 0.01 false discovery rate, ER + vs ER - ) in human breast tumor samples with respect to ER status. Of the 137 ER-regulated genes (E2 responsive, ICI sensitive) identified in the T-47D study, 44 genes were differentially expressed in at least one breast cancer study (Figure 4 ). The 44 ER-regulated genes represent only about 1% (44/3811) of the 3,812 ER-status-associated genes that met the selection criteria ( p < 0.01 in one or more studies), suggesting that the estrogen-responsive pathways represent only a minor part of the ER-status-associated transcriptome in breast tumors. This is similar to observations made previously by Meltzer and co-workers [ 22 , 39 ]. However, there appears to be a significant enrichment of ER-regulated genes within the ER-status-associated genes compared to the frequency of these ER-regulated genes represented in the microarray used in our study (1.15%, 44/3,811 vs 0.72%, 137/18,912, p = 0.006 by chi-square analysis). To compare the expression profiles of responsive and differentially expressed genes, we plotted the average relative expression ratios of each gene (ER + /ER - ) across all samples from the breast cancer studies (Figure 4 ). There was surprising concordance (70.5%; 31/44) between the estrogen-responsive genes identified in T-47D cells and genes differentially expressed in breast tumors. For example, genes upregulated by hormone treatment (Figure 4 , left panel, red) were also overexpressed in ER + breast tumors (Figure 4 , right panel, red). We noted a subset (29.5%; 13/44) of genes that exhibited opposite responses following estrogen treatment in vitro as compared to the ER-status-associated expression in tumors. These 13 genes that are discordant between cell line and tumor data were, however, consistent across the two cell lines (T47-D and MCF-7). This suggests context-dependent regulation of some downstream pathways, which is likely to be different between primary tumors and experimental cell lines. Taken together, we note that these in vitro validated estrogen-responsive genes are also differentially expressed in ER + primary tumors, and may therefore have direct biological and clinical significance. Computational modeling and predictions of ER-binding sites Previous studies have identified the consensus ERE and the AP-1- or Sp1-binding sites in DNA as possible target motifs for. This would suggest that the 89 direct responding genes should be enriched for these binding motifs within the transcriptional control regions. To further explore this, we computationally extracted sequences flanking (-3,000 to +500) the transcriptional start site (TSS, see Materials and methods section), defined as the most 5' nucleotide of the reference transcript in the NCBI RefSeq database, of candidate genes and queried them for potential ER-binding sites. The size and locations of the sequences flanking the start sites were selected because most of the characterized ER-binding sites have been mapped to these regions in known target genes [ 5 ]. For binding-site predictions we used our previously described ERE model [ 41 ] and AP-1 and Sp1 binding-site position weight matrices from the TRANSFAC database [ 42 ]. We also included the binding site for the GATA1 transcription factor as a negative control as it is not known to be involved in ER binding. Model sensitivities for all the sites surveyed were set at the established optimal setting for the ERE model of 83% sensitivity in detecting known binding sites in the training data for the models. Figure 5 shows the performance of the ERE (Figure 5a ), AP-1 (Figure 5b ), Sp1 (Figure 5c ), and GATA1 (Figure 5d ) binding-site models. The y -axis for each graph represents the relative frequency of binding-site prediction as determined by the fraction of genes with predicted binding sites over the total number of genes queried; the x -axis represents the number of most significant genes investigated, ordered by statistical significance, for each of the groups of genes (see Materials and methods). Since short binding site motifs are ubiquitous in the human genome, we asked whether there was enrichment of such response elements in the 3.5 kilobase (kb) upstream windows of responsive genes as compared to unresponsive genes. Enrichment for each motif is represented by a divergence of the relative frequencies of binding-site predictions for putative target genes (Figure 3 , solid lines) and non-responsive genes (Figure 3 , fragmented lines). For ERE predictions, we observed a threefold enrichment of putative sites in the 10 most significant primary response genes as compared to the most non-responsive controls (Figure 3a ), and twofold and approximately 70% enrichment for the 25 and 50 most significant genes, respectively. Overall, the enrichment of ERE sites in putative ER direct target genes is statistically significant ( p = 0.0027). The enrichment of putative Sp1 sites in the target genes was more modest but did not reach statistical significance (12.5% enrichment for the 10 most significant target genes; p = 0.085). This is expected as Sp1 sites are quite common in the human genome and additionally function in general transcriptional regulation. We did not observe any enrichment of AP-1 sites ( p = 0.66) or the negative control GATA1 sites ( p = 0.51). These findings suggest that the ERE is the major response element mediating the specific regulation of ER target genes on a whole-genome scale. We also surmised that although Sp1 and AP-1 binding sites are known to facilitate ER functions in some target genes they are not used as a common ER-targeted cis -regulatory element within the human genome, at least not sufficiently to distinguish target genes from non-responsive genes. To determine the conservation and potential functionality of the predicted EREs, we also examined the same 3.5 kb window in the 5' upstream regions of mouse orthologs of the 89 putative human ER target genes. Seventy-two human-mouse orthologous gene pairs were extracted from the Mouse Genome Database [ 43 ] and the regulatory regions demarcated and analyzed for potential EREs as described for the human sequences (see Materials and methods). We then compared the ERE predictions from the two organisms for the following features: conservation of the core ERE half-sites (GGTCANNNTGACC), excluding the flanking purine bases, between the two most similar sequences when multiple EREs are predicted in either organism; conservation of the 20 bases flanking the 5' and 3' ends (40 bases total) of the predicted EREs; and the distance between the binding-site sequences and the TSS. The statistics of our analysis is summarized in Figure 6a . Of the orthologous mouse-human pairs, 81% (58/72) have at least one ERE prediction and 22 (31%; 22/72) gene pairs have ERE predictions in both organisms. However, of the human direct target genes, 29% (21/72) have no EREs upstream of the mouse orthologs. Conversely, 21% (15/72) of the mouse genes with EREs have no ERE upstream of their human orthologs. Of the 22 gene pairs that have ERE predictions in both organisms (see Venn diagram in Figure 6b ), only four have perfect conservation of the core ERE sequences (Table 2 ). These four perfectly conserved ERE pairs also have the highest conservation in their flanking sequences (average identity = 74%) and the smallest difference in the relative positions of binding sites (average difference Δ d = 469 bases) between the human and the mouse sequences. In fact, the relative positions of the conserved EREs only differ by an average of 52 bases if the predicted EREs for GREB1 (human, NM_014668; mouse, NM_015764), which differed by 1.7 kb in their relative position, were excluded from the analysis. For the ERE mouse-human pairs with one or more base deviations in their core sequences, there is little conservation in the flanking sequences and in the relative positions of predicted EREs (see Table 2 ). These findings indicate that although the ERE motif is conserved through evolution, specific EREs found in the 5' regulatory regions of target genes are rarely conserved. They also suggest potential differences in the molecular mechanisms of ER function and in the repertoire of target genes between human and rodents. In light of this, our inference of ER function in humans from the results obtained from animal studies may warrant a re-evaluation and additional validation. Validation of direct ER target genes by chromatin immunoprecipitation The genomics and informatics approaches have enabled us to identify genes that meet the conventional definition for ER target genes (for example, responsive to E2, sensitive to ICI, and insensitive to CHX), are conserved in ER + breast cancer cell lines and tumor samples, and encode putative ER-binding sites in the promoter regions. Two genes emerged at the top of the list of direct target genes following these analyses. One was for nuclear receptor-interacting protein 1 (NRIP1), also known as receptor-interacting protein 140 (RIP140), first identified as an ER-binding protein and a co-regulator of receptor activity [ 44 , 45 ]. It was subsequently shown to bind and modulate transcriptional activities of other nuclear receptors [ 46 , 47 ]. Previous microarray experiments in MCF-7 and ZR75-1 cells showed that NRIP1 transcript levels were raised following estrogen treatment, and its expression dynamics in the presence of anti-estrogens and CHX were consistent with other primary response genes [ 23 , 24 , 26 ]. In this study, we have also identified NRIP1 as a putative ER target gene that is upregulated by E2, sensitive to ICI treatment and insensitive to CHX in T-47D cells. Furthermore, we detected a conserved perfect ERE at around 700 bases upstream of the TSS, indicating a potential ER-binding site and direct regulation by the activated receptor. The other direct target gene - gene regulated by estrogen in breast cancer 1 ( GREB1 ) - was identified in a subtractive hybridization screen for estrogen-responsive genes in MCF-7 cells. It has no known function and does not appear to share significant homology with any other gene in the sequence databases [ 48 ]. A perfect ERE was found at around 1.6 kb upstream of the TSS of GREB1 and the predicted ERE is also conserved in mouse. Given that both NRIP1 and GREB1 have been conserved during vertebrate evolution, we compared the 5' upstream regions from human, chimpanzee, mouse and rat genome sequences to see whether the predicted regulatory element has been conserved in additional murine and primate species. For all of the regions surveyed, we found that the core ERE has been perfectly conserved (Figure 7a ). In addition, sequences flanking the predicted ERE were also highly conserved, suggesting functionality for these regions. To determine the role of the predicted ERE as an ER-binding site, we performed chromatin immunoprecipitations (ChIPs) using anti-ER antibodies. In addition to the two conserved EREs, we also included two non-conserved EREs from TFF1/pS2 (positive control) and ATP-binding cassette, subfamily A, member 3 ( ABCA3 ), a gene related to other ABC transporters that are thought to be involved in cellular lipid transport and which is a putative ER direct target gene as determined in this and a previous study [ 26 ]. Forward and reverse primers (Figure 7b ) flanking the ERE were designed to specifically detect and quantify genomic DNA fragments that co-precipitate with ER in real-time PCR experiments. Following hormone treatments, we did not observe significant enrichment of the negative control actin exon 3 region in anti-ER precipitates as compared to the anti-GST antibody control or the input genomic DNA from the nuclear lysates for all primer pairs tested (Figure 7c ). In contrast, semi-quantitative PCR analysis (see Materials and methods) of the ChIP products using primers flanking the predicted EREs revealed ER binding to these sites in the absence of estrogen and after hormone treatment (see Figure 7c ). Furthermore, the binding appeared to be enhanced following estrogen treatment, suggesting a role for activated receptors in mediating the observed transcriptional regulation of these genes. The functionality of the conserved EREs in NRIP1 and GREB1 was also recently reported in a study of near-consensus EREs in the human and mouse genomes [ 49 ]. Discussion We have conducted a genome-wide analysis of E2-responsive genes. Through a strategy of iterative validation using genomics, informatics and experimental biology we have identified and characterized a core set of 89 ER direct target genes out of the 18,912 genes represented on our microarray (0.5%). This set of direct target genes derived from experiments in T-47D cells show very similar behavior in another cell line, MCF-7, and also overlap with genes that can distinguish ER status in human breast cancers. Taken together, these results suggest common underlying mechanisms for ER transcriptional control and define specific genetic components of the ER transcriptional network that are consistent across model experimental and clinical conditions. These results emboldened us to decipher the rules and informational framework underlying ER transcriptional control. The anti-estrogen treatment with the ICI drug and preincubation of the cells with CHX allowed us to identify genes likely to be ER direct targets. We extracted extended promoter regions (- 3,000 bp to +500 bp) and determined potential ER-binding sites by using ERE and AP-1 and Sp1 binding-site models [ 41 , 42 ]. Because transcription factor binding elements occur very frequently in the genome, finding an ERE, AP-1 or Sp1 site only in ER-responsive genes is highly unlikely. Instead, we asked whether the probability of finding an ER-associated response element was significantly higher than that seen in ER-unresponsive genes. Our results, depicted in Figure 5 , show distinctly that EREs are enriched in the putative direct estrogen-responsive genes ( p = 0.0027) but that binding sites for AP1, Sp1 or GATA1 (which we used as a negative control response element) are not. The ERE thus appears to be the predominant ER transcriptional control element. Moreover, despite definitive experiments showing the ability of AP-1 and Sp1 sites to mediate ER responses [ 7 - 9 , 47 , 50 - 54 ], our results suggest that their usage is not a common mechanism for specific ER transcriptional control on a genome-wide scale. Previous investigations have uncovered a functional ERE embedded within an Alu repetitive sequence that is frequent in the genome [ 55 ]. Inclusion of this Alu ERE into our analysis, however, dramatically degrades the enrichment of EREs found in direct ER-responsive genes ( p = 0.06). This suggests that though such EREs are experimentally functional, they have little impact on the specific ER transcriptional cassette, functioning as no more than 'noise' in the system. This has been confirmed by negative ChIP data for several Alu -ERE sites (data not shown). These observations highlight the potential confounding factors in genome-wide analysis of functionally relevant response elements. Our use of a 3.5 kb window around the TSS to search for relevant EREs captures the majority of known EREs [ 5 ] and represents a liberal survey of 5' regulatory regions. Despite this, we found that only about 50% of the target genes encode ERE-like sequences (including ERE half-sites) in their promoters. It is possible that ER-binding sites outside this window may be involved in regulating the specific activities of ERs. In support of this, Bourdeu and colleagues very recently described the identification and validation of EREs within DNA 10 kb upstream (relative to TSS) and 5 kb downstream in 5' regions of a number of human genes [ 49 ], indicating the presence of functional enhancer elements outside the region surveyed in our study. In addition, errors in annotating the TSS or additional 5' exons may account for up to an 8% error rate for TSS determination in known genes and 80% error rate in predicted genes (Y.J. Ruan, E.T.L. and C.L. Wei, unpublished work). Future studies will need to incorporate these information in the ERE analyses. Given that in silico identification of EREs does not assure their function in an ER response, we selected three new putative direct ER target genes identified by our stringent criteria for further validation. NRIP1 , GREB1 , and ABCA3 are all genes found to be ER responsive in at least two cell lines; they have a discernable ERE around the TSS, blocked by ICI and not inhibited by CHX, and their expression can discern ER status in breast cancers. Using ChIP we confirmed that the EREs in all three are directly targeted by ER following estrogen stimulation (Figure 7 ). Therefore, our process of ranking by consensus (that is, ranking by likelihood of being a direct target of ER by the number of criteria fulfilled) appears to be a reasonable approach to identify actual direct targets of ER. These target genes suggest potential roles for ER in regulating intracellular signaling pathways that may have an impact on processes in breast and tumor biology. NRIP1 was first identified as an ER-binding co-regulator protein and was subsequently found to interact with other nuclear receptors through the nuclear receptor binding motif LXXLL. Kerley and colleagues [ 56 ] showed that NRIP1 transcript and protein levels were also upregulated by all- trans retinoic acid treatment and suggested that NRIP1 may facilitate cross-talk between members of the nuclear receptor family. Thus, upregulation of NRIP1 by activated ER may not only modulate the estrogen response but also affect the transcriptional activities of other nuclear receptors and the cellular responses to their corresponding ligands. That NRIP1 transcript levels were elevated in ER + compared to ER - breast tumors suggests that the downstream function of other nuclear hormone receptor may be coordinately modulated by elements of the ER transcriptional cascade (see Figure 4 ). ABCA3 encodes a member of the ABC transporters that utilize ATP hydrolysis to drive the transport of substrates across the cell membrane; although its substrate is not known, ABCA3 appears to be related to other ABC transporters involved in lipid transport. Levels of ABCA3 protein are highest in lung tissue, and ABCA3 appears to localize to lamellar bodies of alveolar epithelial cells that are highly enriched in phosphatidylcholine [ 57 ]. These observations provide potential links between ER activation and alterations in phospholipid levels during breast epithelial cell differentiation and transformation. GREB1 , however, is a gene of unknown function and is unrelated to any other known gene. Its overexpression in ER + breast tumors and its evolutionary conservation suggest a central role for this gene in ER signaling and breast tumor biology. Of note, 21% (19/89) of the putative target genes identified in this study have no known biological functions (see Table 1 ). One strategy used in assessing cis -regulatory elements in the genome has been to map conserved segments in non-coding regions upstream of TSSs. Using the three genes above ( NRIP1 , ABCA3 and GREB1 ) as rigorously tested direct targets of ER regulation and a well-studied ER direct target, TFF1/pS2 , we assessed the evolutionary conservation of the validated upstream EREs between human and mouse homologs. Interestingly, we found highly conserved EREs (including flanking regions) only for NRIP1 and GREB1 . ABCA3 and TFF1/pS2 both have upstream functional EREs in the human genes but not in their mouse orthologs (Figure 7b ). We then extended this search for evolutionary conservation to the remaining 89 putative human ER direct target genes. Surprisingly, we found that in the majority of mouse-human orthologous pairs, the ERE core sequences, flanking regions and position relative to the TSS are not conserved: only 4 out of the testable 72 (6%) orthologous pairs examined showed conservation of ERE sequences between the human and mouse genes. This is remarkable given the 84.7% [ 58 ] identity between mouse and human sequences within coding regions. Taken together, our results suggest that the evolution of transcriptional control through cis -regulatory mechanisms must have different mutational rates or mechanisms, and may have undergone different selection pressures from those imposed on coding sequences. Moreover, the low level of conservation in the EREs of estrogen-responsive genes between mouse and human suggest two consequences: first, that the core physiologic estrogen effects such as sex differentiation/mammary gland development may be mediated by a small set of highly conserved and similarly regulated ER-responsive genes; and second, that there might be significant differences between downstream estrogen effects between mouse and human. We suggest the relevance of many of these estrogen-response genes to breast tumor biology by showing significant similarities between estrogen-induced expression profiles in MCF-7 cells and the behavior of these genes in ER + tumors from a database of six breast cancer microarray studies [ 36 - 40 ]. Not unexpectedly we observed that the number of direct estrogen-responsive genes was small in comparison to the overall number of genes that define the ER + breast tumors, suggesting that the estrogen-responsive pathways account for only a portion of the receptor-positive molecular signature, an observation also noted by others [ 22 ]. Nevertheless, taken together, it appears that the ER + status of primary breast cancers can be accounted for by concordant effects of an activated ER. Interestingly, a number of these differentially expressed genes (around 30%) were expressed in the opposite direction in the cell lines compared to the tumor consensus. We speculate that this may be due either to consistently different profiles of ER cofactors or to an intense expression signature in tumor-associated stromal cells that is opposite to that of the cancer cells. Nevertheless, those genes that are estrogen-responsive in cell lines and differentially expressed in ER + tumors represent the most promising candidates for further functional analysis. In summary, we have presented an integrated strategy for discovering and characterizing ER target genes, response elements and the transcriptional regulatory network downstream of ER activation. With this approach, we uncovered a universal set of genes that describe the most direct effects of ER and operate across multiple in vitro and in vivo systems. On examination, this core direct target gene list does not predict a unified biological process controlled by ER. Instead, the gene functions would predict a pleiotropic cellular response. By further in silico analysis of the promoter regions, we observed minimal conservation in the cis -regulatory region of the direct estrogen-response genes between humans and mice. This raises the intriguing possibility that the evolutionary processes governing the configuration of transcriptional regulation will be different from those affecting the functional domains of genes. Moreover, we predict that the estrogen response in the mouse will differ significantly from that in the human, but that a small set of ER direct target genes that are highly conserved in their cis -regulatory regions will act as the key effectors of evolutionarily important core ER functions such as sex differentiation. Conclusions Estrogen responses in human breast tumor cells appear to be mediated by a relatively small conserved core set of ER-regulated genes. Examination of the cis -regulatory regions of putative target genes within this core set revealed the enrichment of the ERE sequence motif but not other known ER-binding sites. Of all the predicted EREs in human direct target genes, only a handful (6%) appear to be conserved in mouse orthologs, although both conserved and non-conserved predicted EREs were shown to bind ER in human cell lines. Taken together, these findings suggest the potential for species-specific mechanisms and effects in response to hormone exposure. Materials and methods Cell culture, treatments and RNA extraction T-47D and MCF-7 cells were maintained in DMEM/F12 (1:1) medium (Invitrogen) supplemented with 10% fetal calf serum (FCS) (Hyclone) at 37°C and buffered with 5% CO 2 . For estrogen treatments, cells were washed with PBS and pre-cultured in phenol-red-free DMEM/F12 medium supplemented with 0.5% charcoal-filtered FCS (Hyclone) for 24 h. For time-course experiments, T-47D cells were treated with 1 nM 17β-estradiol (E2; Sigma-Aldrich) or 1 nM E2 + 10 nM ICI 182, 780 (Tocris Cookson) for the amount of time specified. To determine the primary response, cells were treated with 5 μg/ml cycloheximide (CHX; Sigma-Aldrich) for 30 min before the start of estrogen treatment. Control treatments with ICI (2, 8, 12 and 24 h) and CHX (2 and 8 h) alone were also carried out for the times specified and at the same concentrations as above. To extract RNA, cells were washed with PBS, lysed in Trizol (Invitrogen) and samples were harvested by additional phenol-chloroform extraction steps as prescribed by the manufacturer. Microarray analysis of gene-expression profiles Microarrays were generated by spotting the Compugen 19 K human oligo library, made by Sigma-Genosys, on poly-L-lysine-coated glass slides. Twenty-five micrograms of each sample total RNA and human universal reference RNA (Stratagene) were labeled with Cy5-conjugated dUTP and Cy3-conjugated dUTP (PerkinElmer), respectively, and hybridized to the arrays using protocols established by the Patrick O. Brown Laboratory [ 59 ]. Array images and data were obtained and processed using the GenePix4000B scanner and GenePix Pro software (Axon Instruments). Differentially expressed genes were determined using pairwise t -test between matching treated samples and mock-treated controls at each time point and fold-difference cutoff at multiple time points as described and clustered and visualized using the Eisen Cluster and TreeView programs [ 30 ]. Gene ontology of putative target genes was derived from annotations made by Compugen. Meta-analysis of breast cancer and cell line microarray data A database containing published and unpublished breast cancer expression data was queried for genes whose expression profiles differentiated ER + and ER - tumors. Each individual dataset was analyzed independently for differentially expressed genes by calculating the false discovery rate for each gene [ 60 ] and setting the p -value filter at less than or equal to 0.01. ER-status-associated genes were then cross-referenced with the in vitro estrogen-responsive genes via the UniGene cluster ID (build 166). The log-transformed average mean-centered expression values for each statistically significant study were used for visualization. Raw in vitro MCF-7 estrogen response data [ 31 ] were downloaded from the Stanford Microarray Database [ 32 ]. The data were compared directly with the T-47D results or selected for ER regulation by the following selection criteria: first, at least a 1.15-fold change in the same direction in two out of three time points and no conflicting (opposite direction) data in any of the time points; and second, changes in the opposite direction when co-treated with tamoxifen (Tam) for 48 h in one out of the two treatment conditions and no conflicting data in the two treatments. The 1.15-fold cutoff, which differs from the 1.2-fold change for the T-47D data, was selected to capture known E2-responsive genes in this dataset. Promoter sequence extraction and detection of ER-binding sites The LocusLink and RefSeq [ 61 ] databases at the National Center for Biotechnology Information (NCBI) were used to identify human and mouse genes and pinpoint their loci within the genome. These annotations were chosen for their comprehensiveness, in terms of number of annotated genes, and their consistency with the current state of NCBI contig databases. Using the TSS, defined as the most 5' nucleotide in the reference transcript, and the 3' terminus of the transcript as reference points, we extracted 3 kb upstream and 500 bases downstream of the start sites for binding-site analyses. NCBI human genome sequence build 33 and mouse genome sequence build 30 were used for transcript alignment and genomic sequence extraction. TSS locations annotated in LocusLink and RefSeq may only approximate true start sites because of incomplete information at the 5' ends of some reference sequences, but we believe that the relatively large (3.5 kb) regions used for our analysis allow for fluctuations in TSS position. Human-mouse ortholog determinations were based on annotations made in the Mouse Genome Database [ 43 ]. The four binding-site position weight matrix (PWM) models used were either derived in an earlier study [ 41 ] or downloaded from the TRANSFAC (version 6.0) database of transcription factor binding sites [ 42 ]. Detection parameters were set on the basis of optimized settings for the Dragon ERE Finder [ 41 ] at 83% sensitivity in detecting training data and corresponding settings were made for the other PWMs to have similar sensitivities. Statistical significance of binding-site enrichment between putative target genes and non-responsive genes was determined by Monte Carlo simulations between predictions in defined gene sets and randomly generated genes sets. A set of Monte Carlo simulations was performed to assess the significance of the apparent enrichment of putative EREs between the set of estrogen direct target genes and the non-responsive genes. In each simulation, we randomly generated two sets of genes (equivalent in sizes to the set of direct target and non-responsive genes), plotted the curves accordingly, and calculated the difference between the areas under the two curves. The simulations were performed 100,000,000 times and the fraction of times in the simulations that the random area-difference was at least as large as the observed area difference was reported as the empirical p -value. Most significant direct target genes used in the analysis were ranked by the lowest p -values from analysis of E2-treated and control samples, E2 and E2+ICI samples, and E2 and E2+CHX samples. Non-responsive genes were ranked by highest p -values from the same analysis. Chromatin immunoprecipitation assays MCF7 cells were estrogen deprived for 24 h and treated with 100 nM E2 for 45 min before 1% formaldehyde treatment to cross-link the transcription machinery and the chromatin. Immunoprecipitations were carried out overnight with ERα (HC-20) or GST antibodies (Santa-Cruz Biotechnology) and protein A-sepharose beads (Zymed). Washing and extraction protocols were modified from methods described previously [ 62 ] and PCR reactions were carried out in a LightCycler (Roche Diagnostics) real-time system. Forty cycles of PCR were carried out on precipitated DNA and control input DNA using the following primer sets: TFF1/pS2 ERE: forward CCATGTTGGCCAGGCTAGTC; reverse ACAACAGTGGCTCACGGGGT. NRIP1 ERE: forward, TGCTCCTGGGTCCTACGTCT; reverse TCCCCTTCACCCCACAACAC. GREB1 ERE: forward AGCAGTGAAAAAAAGTGTGGCAACTGGG; reverse CGACCCACAGAAATGAAAAGGCAGCAAACT. ABCA3 ERE: forward, CACCTTCCATCTGTCCAAAG; reverse, CAACCCTGAGGTTTGGGAAC. Actin exon 3 control: forward, AGACCTTCAACACCCCAGCC; reverse, GTCACGCACGATTTCCCGCT. Amplification products were also assayed for specificity by melting-curves analysis at the end of each run. Relative quantifications were carried out by building standard curves for each primer set and using genomic DNA, similar to the input, as the template. Enrichment of ER binding was determined by comparing the relative quantities of anti-ER and control anti-GST products. Additional data files The following additional data files are available with the online version of this article: the processed raw data for the time course microarray study (Additional data file 1 ) and replicate 1 (Additional data file 2 ) and replicate 2 (Additional data file 3 ) of the control microarray study with the ICI and CHX treatments alone, the complete list of all 387 estrogen-responsive genes described in the article with UniGene cluster numbers from build 166 (Additional data file 4 ), expression profiles of ICI and CHX responsive genes identified in the control experiments (Additional data file 5 ) and the corresponding figure legend (Additional data file 6 ). Supplementary Material Additional data file 1 The processed raw data for the time course microarray study Click here for additional data file Additional data file 2 Replicate 1 of the control microarray study with the ICI and CHX treatments alone Click here for additional data file Additional data file 3 Replicate 2 of the control microarray study with the ICI and CHX treatments alone Click here for additional data file Additional data file 4 The complete list of all 387 estrogen-responsive genes described in the article with UniGene cluster numbers from build 166 Click here for additional data file Additional data file 5 Expression profiles of ICI and CHX responsive genes identified in the control experiments Click here for additional data file Additional data file 6 The corresponding figure legend to expression profiles of ICI and CHX responsive genes identified in the control experiments Click here for additional data file

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Micronutrient Sprinkles to Control Childhood Anaemia

Over 750 million children have iron-deficiency anemia. A simple powdered sachet may be the key to addressing this global problem

Recent World Health Organization (WHO)/United Nations Children's Fund estimates suggest that the number of children with iron-deficiency anaemia (IDA) is greater than 750 million [1] . Iron deficiency is the most common preventable nutritional problem despite continued global goals for its control. Historically, the problem of IDA in children largely disappeared in North America when foods fortified with iron and other micronutrients became available for children. In this group, the prevalence of IDA has fallen from 21% in 1974 to 13% in 1994 [2] . Although pockets of infants and children remain at risk, generally, the eradication of iron deficiency in developed countries is recognized as a successful public health accomplishment. This solution has not worked in developing countries where commercially purchased fortified foods are not available or are not used. In the developing world, there are three major approaches available to address iron deficiency: dietary diversification so as to include foods rich in absorbable iron, fortification of staple food items (such as wheat flour), and the provision of iron supplements. When dietary or fortification strategies are not logistically or economically feasible, supplementation of individuals and groups at risk is an alternative strategy. For the past 150 years or more, oral ferrous sulphate syrups have been the primary strategy to control IDA in infants and young children [3] . However, adherence to the syrups is often limited owing to a combination of their unpleasant metallic aftertaste, the dark stain they leave on the child's teeth, and abdominal discomfort [4] . Thus, despite the ongoing work of the United Nations Standing SubCommittee on Nutrition and others to solve the problem of poor adherence in infants and young children, all interventions to date have been universally unsuccessful [ 1 , 5 ]. In this article, we describe our efforts, stage by stage, towards achieving the goal of controlling IDA. The Strategy Our research group at the Hospital for Sick Children in Toronto conceived the strategy of “home fortification” with “Sprinkles”—single-dose sachets containing micronutrients in a powdered form, which are easily sprinkled onto any foods prepared in the household. We hypothesized that this would be a successful method to deliver iron and other micronutrients to children at risk [6] . The idea of Sprinkles was formulated in 1996, when a group of consultants determined that the prevention of childhood IDA was a United Nations Children's Fund priority, yet available interventions (syrups and drops) were not effective [7] . In Sprinkles, the iron (ferrous fumarate) is encapsulated within a thin lipid layer to prevent the iron from interacting with food. This means that there are minimal changes to the taste, color, or texture of the food upon adding Sprinkles. Other micronutrients including zinc, iodine, vitamins C, D, and A, and folic acid may be added to Sprinkles sachets. Any homemade food can be fortified with the single-dose sachets, hence the term “home fortification”. Two formulations have been developed, a nutritional anaemia formulation ( Table 1 ) and a complete micronutrient formulation ( Table 2 ). Table 1 Daily Dose and Derivation of Sprinkles Nutritional Anaemia Formulation for Home Fortification of Complementary Foods Data for infants and young children, 6–24 months of age a Recommended nutrient intake as determined by the WHO [10] b Recommended dietary allowances as determined by the Institute of Medicine [9] c Based on DRI “Adequate Intake” estimates d Assuming medium bioavailability (10%) e Assuming moderate bioavailability (30%) DRI, Dietary Reference Intake Table 2 Daily Dose and Derivation of Sprinkles Complete Micronutrient Formulation for Home Fortification of Complementary Foods Data for infants and young children, 6–24 months of age a Recommended nutrient intake as determined by the WHO [10] b Recommended dietary allowances as determined by the Institute of Medicine [9] c Recommended nutrient composition of complementary foods (per 50 g of food as daily ration) is based on a total intake of one recommended nutrient intake dose for all children six to 23 months after accounting for the amounts already present in breast milk and complementary food [11] d Based on DRI Adequate Intake estimates e Assuming medium bioavailability (10%) f Assuming moderate bioavailability (30%) DRI, Dietary Reference Intake Clinical Trials Efficacy To investigate the bioavailability of the iron in Sprinkles, we used a dual stable isotope method and showed that anaemic infants absorbed iron from Sprinkles about twice as efficiently as nonanaemic infants when delivered in a maize-based diet in West Africa. The study was conducted in collaboration with the Kintampo Health Research Centre of the Ministry of Health in Accra, Ghana. The geometric mean iron absorption from two doses of iron (30 mg and 45 mg of elemental iron per sachet) was 8.3% (range, 2.9%–17.8%) in infants with anaemia and 4.5% (range, 1.1%–10.6%) in infants without anaemia [8] . Comparing these absorption values to the new American/Canadian Dietary Reference Intake standards for infants, we concluded that during infancy (i) iron absorption of Sprinkles from a maize-based porridge met and surpassed needs for absorbed iron, and (ii) iron absorption is up-regulated in infants with IDA [ 9 , 10 , 11 ]. Based on these results, we estimated through computer simulations that a 12.5-mg iron dose (as recommended by the WHO) from Sprinkles should be adequate for use in large-scale distribution programs for the prevention and treatment of mild to moderate anaemia. It has been suggested that zinc may compete with iron for the same receptor sites on intestinal mucosal cells in the proximal duodenum, thereby compromising the absorption of both minerals [12] . To address this important issue, we recently conducted a bioavailability study in rural Ghana using the same dual stable isotope method as previously used [8] . In order to determine the effect of two doses of zinc on the absorption of iron from Sprinkles (with 30 mg of elemental iron), 63 young children, 12–24 months of age with varying haemoglobin levels were studied. We found that 10 mg of zinc (in the form of zinc gluconate) added to Sprinkles significantly reduced the absorption of iron, whereas a 5-mg dose had no effect. Thus, we concluded that adding 5 mg of zinc to the formulation of Sprinkles was appropriate (unpublished data). Over the past five years, we have completed seven community-based trials in four different countries [ 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. The goal of these studies was to test the efficacy of Sprinkles in diverse settings. When we pooled data from two of our studies that compared Sprinkles to the reference standard, ferrous sulphate drops, we had a total of 518 anaemic infants (haemoglobin < 100 g/l) who were given one of two ferrous sulphate doses (15 mg or 40 mg of elemental iron as ferrous sulphate) and 318 similar infants who received one of four doses of iron from Sprinkles (12.5 mg, 20 mg, 30 mg, or 80 mg of elemental iron as microencapsulated ferrous fumarate) [ 13 , 18 ]. This gave us greater than 97% power (α = 0.05) to detect whether the mean difference in the end-of-study haemoglobin concentrations between ferrous sulphate and Sprinkles regimens was within ± 5 g/l (a range of equivalence). Using a random effects model (for study and dose) that adjusted for baseline haemoglobin, we found no significant difference between Sprinkles and drops. We further examined this through quantile-quantile plots of haemoglobin concentrations at the end of the studies for Sprinkles and ferrous sulphate drops ( Figure 1 ). The overlaid plots of haemoglobin concentrations of the Sprinkles and drops groups show that these two distributions overlap at all quantiles. These plots clearly indicate that the haemoglobin response to the two different forms of iron was equivalent. Thus, we have concluded that Sprinkles are as efficacious as the current reference standard for the treatment of anaemia. Overall, 55%–90% of the anaemic infants who were provided with Sprinkles were cured. Figure 1 Overlaid Quantile-Quantile Plots of Haemoglobin Concentrations at the End of Studies for Sprinkles and Ferrous Sulphate Drops The graph shows that the two distributions overlap at all quantiles, thus proving that there is an equivalent response to the two treatments for haemoglobin concentrations. Circles represent individuals who received iron drops; crosses represent individuals who received Sprinkles. Acceptability During our studies we also asked about the caregivers' perception of their infants' responses to Sprinkles as compared to drops, the Sprinkles' impact on the food to which they were added (change in taste, color, or consistency), the use of sachets as a delivery vehicle, and the perceived side effects of Sprinkles [ 13 , 18 , 19 ]. Invariably, the response to Sprinkles has been positive. No appreciable change in the food with Sprinkles has been reported, no one reported stains on the infants' teeth, and Sprinkles were reported to be easy to use. The only consistently reported side effect was a darkening of the infant's stool, which is expected since most of the iron is excreted in stool. In a recently conducted study in Bangladesh, using a four-point measurement scale, 60% of the mothers “extremely liked”, 30% “liked”, and the remaining 10% “somewhat liked” the Sprinkles intervention; no one disliked Sprinkles. Major reasons cited for liking Sprinkles included ease in mixing Sprinkles with complementary (i.e., weaning) foods and that their use promoted the appropriate introduction of complementary foods, since Sprinkles could be used only if complementary foods were used [19] . Ensuring a Sustainable Supply As the results of the first studies showing the efficacy of Sprinkles became available, the need for a reliable high-quality supply became apparent. In 2000, the H. J. Heinz Company of Pittsburgh, Pennsylvania, United States, expressed an interest in the Sprinkles program as a component of their corporate social responsibility program. Since 2001, the H. J. Heinz Company has provided support and expertise in the evaluation of consumer needs and a supply of Sprinkles for research, while the H. J. Heinz Company Foundation has provided financial support for research activities. Through a formal process of technology transfer, local overseas Sprinkles production has been encouraged. Currently, an independently licensed copacker is supporting local production for a national program in Guyana, and plans are in place for technology transfer to Bangladesh and Pakistan. Scaling Up for Countrywide Distribution The final stage, the scale-up process, is by far the most challenging. First, this process involves dialogue with the Ministries of Health, scientific community, civil society, and other private partners. Second, it is important to identify sustainable methods of distribution that are able to reach and provide Sprinkles to the most vulnerable populations in the developing world. From our experience in Mongolia, we have determined that it is feasible to distribute Sprinkles in partnership with a non-governmental organization called World Vision. Sprinkles sachets distributed in Mongolia over a two-year period included both iron and vitamin D. Sprinkles have been successfully distributed by World Vision field staff to over 15,000 children in seven districts. Coverage has been over 80%, at a cost of about US$0.03 per sachet. In the project area, the prevalence of anaemia (haemoglobin < 115 g/l) and rickets decreased from 42% to 24% and 48% to 33%, respectively [20] . Notwithstanding these positive results on anaemia control, without committed, long-term financial input from national governments, international agencies, or nongovernmental organizations, sustainability is not guaranteed. Clearly, sustainability over the long term can most likely be achieved if a program becomes self-financing. This may be achieved through public- and private-sector partnerships that use effective social marketing models or possibly through programs which include microcredit in order to reach poorer population groups. When strategizing how to scale up Sprinkles from small-scale research projects to large-scale programs, we quickly realized that our research group did not have the necessary funding, experience, or personnel needed to influence health policy, develop a social marketing strategy, or maintain a distribution network at a countrywide level. We have thus partnered with organizations that specialize in each of these areas to help achieve our goal of sustainable distribution. For example, the government of Pakistan is planning to distribute Sprinkles through their ongoing Lady Health Worker Program, which is the largest public-sector primary health-care program implemented by the Federal Ministry of Health. In Bangladesh, BRAC (formerly known as Bangladesh Rural Advancement Committee), the largest national non-governmental organization in the country, is planning to distribute Sprinkles through their ongoing Female Community Health Worker program (popularly known as Shastha Shebika ). In both of these countries, Sprinkles would be produced locally through public–private partnerships via a technology transfer agreement. The cost per sachet of locally produced Sprinkles should range from US$0.010 to US$0.015, depending on the volume of production, as compared to US$0.020 to US$0.025 if imported. Conclusion Each stage in the evolution of the Sprinkles intervention has been evaluated in a controlled manner. We determined that the use of encapsulated iron did not appreciably change the taste or color of the food to which it was added, we showed that the haemoglobin response in anaemic infants was equivalent to the current standard of practice, and we documented the acceptability of Sprinkles among caregivers who used Sprinkles in their homes. Finally, through various partnerships, we have developed a successful model to scale up the intervention for countrywide use. Our challenge for the future is to demonstrate the cost-effectiveness of this new intervention and to advocate for the adoption of Sprinkles in the nutrition policy of developing countries.

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Investigation of hydrophobic moment and hydrophobicity properties for transmembrane α-helices

Integral membrane proteins are the primary targets of novel drugs but are largely without solved structures. As a consequence, hydrophobic moment plot methodology is often used to identify putative transmembrane α -helices of integral membrane proteins, based on their local maximum mean hydrophobic moment (< μH >) and the corresponding mean hydrophobicity (< H >). To calculate these properties, the methodology identifies an optimal eleven residue window ( L = 11), assuming an amino acid angular frequency, θ , fixed at 100°. Using a data set of 403 transmembrane α -helix forming sequences, the relationship between < μH > and < H >, and the effect of varying of L and / or θ on this relationship, was investigated. Confidence intervals for correlations between < μH > and < H > are established. It is shown, using bootstrapping procedures that the strongest statistically significant correlations exist for small windows where 7 ≤ L ≤ 16. Monte Carlo analysis suggests that this correlation is dependent upon amino acid residue primary structure, implying biological function and indicating that smaller values of L give better characterisation of transmembrane sequences using < μH >. However, varying window size can also lead to different regions within a given sequence being identified as the optimal window for structure / function predictions. Furthermore, it is shown that optimal periodicity varies with window size; the optimum, based on < μH > over the range of window sizes, (7 ≤ L ≤ 16), was at θ = 102° for the transmembrane α -helix data set.

Background Integral membrane proteins are the primary choice as targets when developing new drugs and although clearly of medical relevance, forming 20% – 30% of the gene products of most genomes, these proteins have been structurally determined in only about thirty cases [ 1 , 2 ]. Where high levels of sequence homology exist, an unknown protein's structure and hence, the location of its membrane interactive segments, can sometimes be deduced by direct comparison to known protein structures. However, where sequence information alone is available, the identification of transmembrane α -helical structure requires a bioinformatics approach to understanding the structure / function relationships of these α -helices. A number of α -helical properties have been used as models to study transmembrane α -helices and their structure / function relationships but the most commonly used are those based on the amphiphilicity of protein α -helices with the hydrophobic moment used as a measure of amphiphilicity [ 3 ]. To quantify the amphiphilicity of protein secondary structures, Eisenberg and co-workers [ 4 ] introduced the hydrophobic moment, μ ( θ ), which provides a measure of the structured partitioning of hydrophilic and hydrophobic residues in a regular repeat structure of period θ . For a structure comprising L consecutive residues, the general form of μ ( θ ) is given by: where H j is the hydrophobicity of the j th residue within the sequence, and θ is the angular frequency of the amino acid residues forming the structure. Eisenberg et al ., [ 4 ] assumed that for an α -helix, θ is fixed at 100°, and that a segment of eleven consecutive residues, equivalent to three turns of an α -helix, could be used to represent amphiphilic α -helices. These assumptions led to the more generally used measure of α -helix amphiphilicity, the mean hydrophobic moment < μH >, where < μH > = μ(100°)/11 As a major extension to the use of the hydrophobic moment, Eisenberg et al ., [ 5 ] introduced hydrophobic moment plot methodology, which provides a graphical technique for the general classification of protein α -helices. Using this methodology, a putative protein α -helix is characterised according to its maximum < μH > and corresponding mean hydrophobicity, < H >, where this is defined by: The parameters < μH > and < H > are then plotted on the hydrophobic moment plot diagram (figure 1 ) and the location of the resulting data point used to classify the putative α -helix. Figure 1 Conventional hydrophobic moment plot analysis of the transmembrane protein data set. Figure 1a shows the hydrophobic moment plot diagram [5] with protein classification boundaries. Figure 1b shows the results of hydrophobic moment plot analysis of the 403 transmembrane sequences of our data set using the conventional values of L = 11 and θ = 100° [4]. The mean hydrophobic moment is widely used and generally regarded as a good predictor of α -helix amphiphilicity but the results of statistical analyses have shown the efficacy of hydrophobic moment plot methodology as a predictor of α -helical class to be less certain [ 6 ]. A number of authors have observed that the methodology can erroneously classify α -helices in cases where the hydrophobic moment for a particular amino acid sequence is greatly affected by the spatial arrangement of a few extreme amino acids, thus masking the overall nature of an α -helix [ 3 ]. However, a more fundamental source of erroneous classification could come from the questionable assumption made by hydrophobic moment methodology with respect to angular periodicity. It is known that in naturally occurring α -helices, θ can vary over the range (95° ≤ θ ≤ 105°) and between consecutive residues [ 7 ]. Clearly, assuming a fixed value of θ = 100° for all α -helices is an approximation and could lead to classification difficulties for the methodology. Furthermore, classification difficulties could arise from the arbitrary choice of window length made by the methodology as window length is known to have a profound effect on the relationship between < μH > and < H >[ 7 ]. It would seem that the optimisation of θ and window length are crucial to the classification of amphiphilic α -helices yet the values chosen for these parameters by hydrophobic moment plot analysis are not optimal for the classification of any single subclass. A number of studies have considered the significance of < μH > in relation to structure / function relationships of the α -helical classes described by hydrophobic moment plot methodology with common examples including: surface active α -helices, transmembrane α -helices and oblique orientated α -helices [ 8 - 10 ]. However, if different α -helical classes have differing optima for θ and window length, not only does this question the validity of results obtained in these studies but also questions the validity of α -helix classification according to hydrophobic moment plot methodology. In this paper we examine the criteria upon which the methodology is based and, in view of their medical relevance, we use transmembrane α -helices as a test data set. These α -helices possess central regions, which are predominantly formed by hydrophobic residues and interact with the membrane lipid core, and end regions, which are primarily formed by hydrophilic residues and reside in the membrane surface regions [ 8 ]. For the α -helices of our data set, we analyse the relationships for the mean hydrophobic moment and window size, angular frequency and the robustness to varying angular frequency. Correlations between the mean hydrophobic moment and mean hydrophobicity of transmembrane α -helices are established, verified and analysed to appraise biological function using resampling Bootstrap and Monte Carlo techniques [ 11 , 12 ]. Results A data set of 84 transmembrane proteins were identified within Swiss-Prot and used to generate a set of 403 transmembrane sequences (see Additional file 1 ). All sequences within the data were of 21 residues in length and showed less than 5% homology (data not shown). For the sequences of this data set, the maximum mean hydrophobic moment, < μH >, and its corresponding mean hydrophobicity, < H >, were determined and used to generate the hydrophobic moment plot shown in figure 1 , based on the generally used 11 residue window ( L = 11) introduced by Eisenberg et al ., [ 4 ]. It can be seen that data points representing the sequences of our data set cluster around the transmembrane region identified by Eisenberg et al ., [ 5 ] but as previously noted [ 6 ] there are a significant number that fall outside the boundaries of this region. In particular, many of this number possess < H > values less than 0.5 and would not be classified as transmembrane α -helices according to the hydrophobic moment plot taxonomy of Eisenberg et al ., [ 5 ]. Even allowing for the diffuse nature of these boundaries on the hydrophobic moment plot diagram [ 5 ], these results clearly question the efficacy of hydrophobic moment methodology for the prediction of transmembrane α -helices. The above analysis was repeated except that window sizes varying in the range (7 ≤ L ≤ 20) were employed. The values for < μH > and corresponding < H > were plotted as above and the results for window sizes of 7, 9, 16 and 20 are shown in figure 2 . It can be seen that a weak negative correlation exists between < μH > and < H > for smaller window sizes but that the level of correlation appears to reduce as window size increases. The sample correlation coefficients for the various window sizes are given in table 1 . To conduct standard statistical tests to determine whether the population correlation coefficients do differ from zero, it is necessary to establish if these data are bivariate Normal. The P-values obtained from Anderson-Darling and Kolmogorov-Smirnov tests for Normality for the various window sizes with θ = 100° are shown in table 2 . These results present clear evidence that the populations for the variates for each window size are not bivariate Normal. These findings prompted the use of the bootstrap procedures to estimate the confidence intervals for the population correlation coefficient values for the window sizes in the range (7 ≤ L ≤ 20). Figure 2 Hydrophobic moment plot analysis of the transmembrane protein data set with varying window size. Figure 2 shows the 403 transmembrane sequences of our data set, which were analysed according to hydrophobic moment plot methodology but with varying window size (L). In comparison to L = 1 (figure 1b), here in figure 2a, L = 7; in figure 2b, L = 9; in figure 2c, L = 16; and in figure 2d, L = 20. In each case, θ = 100°. Table 1 Sample correlation coefficients between < μH > and < H > for window sizes (7 ≤ L ≤ 20). Window size ( L ) Sample correlation coefficient (r) Window size ( L ) Sample correlation coefficient (r) 7 -0.57648 14 -0.34654 8 -0.45020 15 -0.31280 9 -0.30316 16 -0.17998 10 -0.40110 17 -0.15074 11 -0.47663 18 -0.21843 12 -0.33693 19 -0.20038 13 -0.30354 20 -0.15653 Table 2 Confidence Intervals for regression coefficient from bivariate Normality goodness-of-fit for window size L . * 93% Confidence Interval Window size ( L ) 95% Confidence Interval 99% Confidence Interval 7 (1.077, 1.112) (1.072, 1.176) 8 (1.051, 1.084) (1.046, 1.089) 9 (1.067, 1.091) (1.061, 1.095) 10 (1.091, 1.171) (1.078, 1.184) 11 (1.078, 1.134) (1.068, 1.149) 12 (1.046, 1.075) (1.042, 1.080) 13 (1.054, 1.110) (1.047, 1.167) 14 (1.055, 1.124) (1.044, 1.135) 15 (1.050, 1.087) (1.044, 1.093) 16 (1.036, 1.045) (1.030, 1.051) 17 (0.976, 1.001) (0.977, 0.999)* 18 (0.959, 0.980) (0.956, 0.983) 19 (0.957, 0.967) (0.955, 0.968) 20 (0.950, 0.960) (0.948, 0.962) The results of this investigation for θ = 100° are presented in figure 3 . It would appear that the smaller window sizes do show correlations between < μH > and < H > and if this reflects a biological property of transmembrane sequences, it could be of use in the analysis and prediction of these motifs. It is known that angular frequency for a transmembrane α -helix varies between 95° and 107° [ 16 ], rather than being fixed at 100° as proposed by the methodology of Eisenberg et al ., [ 4 ]. For each window size in the range (7 ≤ L ≤ 21) residues, to accommodate the findings of Cornette et al ., [ 16 ], the fixed value of θ was therefore varied from 95° to 108° in increments of 1°. Once the optimal window had been obtained, to observe the discriminating effect of θ on < μH >, the < μH > values, denoted by Σ< μH >, were summed for the 403 sequences for each θ . Figure 4 shows the optimal θ , based on the maximum values of Σ< μH > for each window length. It can be seen that as the window size increases the total < μH > reduces approximately linearly until the intermediate size of eleven residues in length. For subsequent larger window sizes, we observe a further near linear reduction trend but at a reduced rate. The optimal angular frequency corresponding to each window size (7 ≤ L ≤ 21) is also given in figure 5 . The overall relationship between Σ< μH >, the window size, L , and the angular frequency, θ , is finally depicted in figure 6 as a response surface diagram. Figure 3 Confidence intervals for the Correlation Coefficient. Figure 3a shows the 99% BCa confidence intervals for the correlation coefficients estimated from 4000 bootstrap replicates. Figure 3b shows the 99% ABC confidence intervals for the correlation coefficients. Figure 3c shows the 99% Delta Method confidence intervals for the correlation coefficients. Figure 4 Σ< μH > for the transmembrane protein data set for variable window sizes with optimised angular frequency. Figure 4 shows the variation of Σ< μH > for the 403 transmembrane sequences of our data set with window size (7 ≤ L ≤ 20) for optimised θ (95° ≤ θ ≤ 108°). Figure 5 The variation of optimal angular frequency with window size for the transmembrane protein data set. Figure 5 shows the variation of optimal angular frequency, θ , (95° ≤ θ ≤ 108°) with window size (7 ≤ L ≤ 20) for the 403 transmembrane sequences ofour data set Figure 6 Response surface diagram for the transmembrane protein data set. Figure 6. Response surface diagram for the Σ< μ H > for window sizes (7 ≤ L ≤ 20) and angular frequency (95° ≤ θ ≤ 108°). To assess the robustness of < μH > to this fixed angular frequency assumption, and thus, the accuracy of the hydrophobic moment plot analysis for candidate transmembrane sequences, Monte Carlo simulation studies were conducted. Initially, the angular frequency, θ , was assumed to have a mean value, E( θ ), fixed at 100° and the angle for each successive residue varied about E( θ ). The random variation, X, followed a Normal distribution and six separate simulations were undertaken with X~N(100, σ 2 ), where the standard deviation, σ , was set at 0.1°, 0.3°, 0.5°, 0.7°, 0.9° and 1.1° respectively for each. The process was repeated with the mean value being set at the identified optimal angular frequency for the window size, again, for each of the window sizes in the range (7 ≤ L ≤ 20). Hydrophobic moment plots for variable angular frequency were obtained for E( θ ) = 100° for each window size in the range (7 ≤ L ≤ 21) residues and for the separate standard deviation values, σ = 0.1°, 0.3°, 0.5°, 0.7°, 0.9°, 1.1°. These were compared visually with the original plots obtained under the fixed angular frequency assumption ( θ = 100°). In all cases, the bulk properties of the plots were similar irrespective of the level of dispersion introduced by the different values of the standard deviation. The hydrophobic moment plot for L = 15; θ = 100° is provided in figure 7 . This is to be contrasted with the plots for L = 15; E( θ ) = 100°, σ = 0.1°, σ = 0.7° and σ = 1.1°, also present in figure 7 . Similar results were obtained for all other values, confirming, at least visually, that < μH > is robust to slight random perturbations about a fixed value. These properties were also observed for the simulation study with the fixed angular frequency assumption being violated about the optimum frequency for each of the window sizes in the range (7 ≤ L ≤ 20) and for each corresponding level of dispersion. Figure 7 Hydrophobic moment plot analysis of the transmembrane protein data set with varying standard deviation of θ about θ = 100°. Figure 7 shows hydrophobic moment plot analysis of the 403 transmembrane sequences of our data set using L = 15 and: In figure 7a, θ = 100°; in figure 7b, θ is from a Normal Distribution with E( θ ) = 100° and standard deviation of 0.1° ; In figure 7c, θ is from a Normal Distribution with E( θ ) = 100° and standard deviation of 0.7° and in figure 7d, θ is from a Normal Distribution with E( θ ) = 100° and standard deviation of 1.1°. A more rigorous assessment of the variation was provided by analysis of the sample correlations. These were calculated in each case and compared to the empirically derived 99% confidence intervals established for window sizes in the range (7 ≤ L ≤ 20) under the fixed angular frequency assumption of θ = 100°. The calculated sample correlation coefficients were also compared to the point estimates for the original data. In all cases, the values were within the appropriate confidence intervals and were always close to the original sample correlation coefficient values, again providing evidence that < μH > is robust to random variation in angular frequency. The results of this investigation are given in table 3 . Table 3 Sample correlation coefficients for optimum < μH > for θ = 100°, θ ~N(100, σ 2 ) and window sizes, L = 7, 11, 15, 16, 20. Window size ( L ) θ = 100; σ = 0 σ = 0.1 σ = 0.3 σ = 0.5 σ = 0.7 σ = 0.9 σ = 1.1 7 -0.576465 -0.576557 -0.576118 -0.574907 -0.577803 -0.575951 -0.577435 11 -0.476666 -0.476109 -0.475923 -0.476820 -0.476131 -0.475736 -0.475371 15 -0.312882 -0.312924 -0.312973 -0.313221 -0.313488 -0.312796 -0.311120 16 -0.180014 -0.180160 -0.180679 -0.180656 -0.179292 -0.178218 -0.180065 20 -0.156516 -0.156837 -0.156606 -0.156546 -0.158868 -0.158272 -0.155921 To test whether these correlations are artefactual, hydrophobic moment plots were obtained for the < μH > and < H > derived from the 403 artificial randomisation sequences generated by random re-ordering or randomisation [ 20 ] of each of the original optimum window sequences. The plot for a window size of L = 11 is given in figure 8 . These analyses were undertaken for all those window sizes with previously identified statistically significant correlation coefficients between < μH > and < H > and were designed to test the importance of the spatial arrangement of the amino acids within the optimum sequences. Figure 8 Hydrophobic moment plot analysis of the transmembrane data set using randomised sequence arrangements. Figure 8 Hydrophobic moment plot analysis of our data set was performed using sequences generated by a) random rearrangement of sequences for the optimal windows, b) random sequences formed with amino acid relative frequencies the same as those of the optimal windows. In all cases, L = 11 and θ = 100°. Similar plots were obtained from Monte Carlo simulated data derived from the 403 sequences that had been generated by random sampling using the relative abundancies of residues found in the set of optimal windows. These analyses were therefore designed to look at the importance of relative amino acid composition for the correlations between < μH > and < H > and the results can be seen for a window size of L = 11 in figure 8 . Again, analyses were performed for all window sizes with associated statistically significant correlations (data not shown). It is worth noting that since the effect of varying window size had a significant effect on the correlation between < μH > and < H >, varying L was observed to vary the optimal sequence identified within the transmembrane domain. Clearly this was not unexpected. Conclusions It can be seen from figure 5 that the most discriminating angular frequency for a fixed window size varies within the range, (95° ≤ θ ≤ 104°) for window sizes (7 ≤ L ≤ 20). There is an obvious damped oscillation present, which can be seen to correspond to the assumed intrinsic periodicity of α -helical secondary structure i.e. 3.6 residues per turn. Figure 5 clearly demonstrates that the fixed 100° angular frequency, assumed when modelling α -helices in general, is no more than a representative average with a value nearer 102° providing a maximum for an optimum L = 11 residue window in a transmembrane α -helical sequence. From figure 4 , it is also evident that the degree of discrimination possible using < μH > declines in a near linear fashion with increasing window size with the optimum L = 11 residue window appearing to provide approximately average discrimination for transmembrane α -helices. The bootstrap derived 99% confidence intervals for the correlation coefficients between < μH > and < H > for window sizes in the range (7 ≤ L ≤ 20) showed that there are highly significant linear associations for the smaller window sizes in the range (7 ≤ L ≤ 16). As the magnitude of each of the corresponding sample coefficients is small (table 1 ), this should be interpreted as evidence of a strong (negative) association but with high variability being present. These correlations become weaker, on average, with increasing window size until they are not statistically significant at the 1% level and we have no compelling evidence that the variates are not independent. The choice of window size therefore, becomes paramount if < H > and < μH > are to be used to classify transmembrane α -helices. More importantly, the variation in correlation between these parameters and the effect of varying window size on the location of the sequence identified as optimal for α -helix classification brings into question the relevance of using the mean hydrophobic moment for comparison between varying window sizes. However, < μH > has been shown to be robust to departures from the fixed angular frequency assumption for a large range of window sizes appropriate for transmembrane proteins and for a range for levels of dispersion. There were no substantial differences between the plots for relative abundance sample data and those for the randomisation sequences (figure 8 ) except for a few chance negative < H > observations from the former. This suggests that there are no serial correlations between residue types, where presence in the identified section of the penetrating transmembrane stretch is determined predominantly by relative abundance. This is to be contrasted with the distribution of observations for the original transmembrane sequences for a window size of 11 residues (figure 1 ). Most noticeable is the difference in < μH > over the range of < H > values. There appears to be a lower bound for < μH > for the original sequence, which is clearly not present for the randomisation data. Furthermore, whilst the negative correlation would appear to be an artefact, as it is exhibited in all cases, the dispersion around any optimal fitted line through the data such as a least squares fit also is clearly different. It appears similar and quite spread out for the two randomised sequence data but considerably less so for the transmembrane sequences. This provides evidence that within the optimum window, whilst residue composition is not influential, order is. It would appear that this ordering is leading to both organisation and biological function for at least segments of the interacting portions of transmembrane proteins. This is consistent with the belief that the hydrophobic moment is a good predictor of amphiphilicity [ 8 ] although it can be unduly influenced by relatively few amino acid residues within a sequence [ 21 ]. In summary, our analyses confirm previous studies, which have shown limitations to the ability of hydrophobic moment plot methodology to assign function to membrane interactive α -helices [ 6 ]. More importantly, our investigation leads to a questioning of the logic of comparing mean hydrophobic moments, in general, for transmembrane proteins. This is due to the effect of window size on both, the correlation of mean hydrophobic moment with mean hydrophobicity and the identified sensitivity of the optimum window. Comparisons of the hydrophobic moment are seemingly only meaningful for separate transmembrane proteins with identical window sizes. Despite these limitations, < μH > has been shown to be robust to departures from the fixed angular frequency assumption for transmembrane proteins. Given the severe lack of structural information for transmembrane proteins, the identification of transmembrane α -helices using hydrophobic moment based analyses, and other bioinformatic approaches, seems likely to continue for the foreseeable future. Nonetheless, the results of such analyses should only be taken as a guide, and where possible, obtaining corroborative experimental data is essential. On the positive side, our results have demonstrated the importance of amino acid residue sequence order in establishing organisation and biological function for the transmembrane α -helices of proteins. With the ongoing development of predictive techniques, these results should be useful in furthering this development and helping to improve drug target identification. Methods The selection of transmembrane, α -helix forming segments The primary structures of 96 transmembrane proteins were selected from the Swiss-Prot data bank ( ; accessed 25.05.04) and confirmed as transmembrane by extensive analysis of the literature. The sequences were analysed for homology using the sequence alignment program BLAST (Basic local alignment search tool) [ 13 ] and twelve homologous sequences were rejected. From the remaining 84 primary structures, a data set comprising 403 putative transmembrane α -helical sequences, each of 21 residues, was established using the algorithm, Top Pred2 ([ 14 ]; ; accessed 25.05.04). Hydrophobic moment plot analysis of transmembrane, α -helix forming segments In the present study, all hydrophobic moment plot analyses were performed using the consensus hydrophobic scale of Eisenberg [ 4 , 5 ]. To identify putative transmembrane α -helix forming segments using hydrophobic moment plot methodology, hydropathy plot analysis [ 15 ] is initially undertaken to identify the primary amphiphilicity of candidate sequences. These sequences are selected using a 21 residue window as this is sufficiently long for an α -helix to span the bilayer. Once a putative transmembrane domain has been identified, an eleven residue window is considered to progress along the amino acid sequence and for each window, the hydrophobic moment at 100° is calculated. Based on the assumption that a protein sequence will adopt its most amphiphilic arrangement, the window with the maximum mean hydrophobic moment, < μH >, is taken as the most likely to form an amphiphilic α -helix [ 5 ]. The location of the optimum window was observed accordingly for window sizes of seven through to twenty consecutive residues. Optimal angular frequency and window length for < μH > For window sizes ranging from 7 to 20 amino acid residues < μ H > were computed for the range of angular frequency values (95° ≤ θ ≤ 108°). In each case, the value of θ , which maximises < μ H >, i.e. the value of θ which produces < μH >, was determined and is referred to as the optimal angular frequency for that window size. These procedures were based on previously published work, which identified variations in θ for α -helices [ 16 ]. Hydrophobic Correlation For window sizes ranging from 7 to 20 amino acid residues, scatterplots of < μH > versus < H > (hydrophobic moment plots) with θ = 100° were obtained. The corresponding sample correlation coefficients were calculated to identify the effect of window size on the relationship between these variates and hence on their ability to act as discriminators in the prediction of transmembrane α -helices. In addition, for each window size in the range (7 ≤ L ≤ 20) residues and for θ in the range (95° ≤ θ ≤ 108°), the response surface diagram for < μH > was constructed. Confidence intervals for the Correlation Coefficient Statistical confidence intervals were established for the Pearson (Product-Moment) Correlation Coefficient between < μH > and < H > for both cases where window size was varied for a fixed value of the angular frequency, and the angular frequency was varied for a fixed window size. The resulting mean hydrophobicity measures were checked for bivariate Normality and non-parametric bootstrap procedures [ 11 ] were used to estimate confidence intervals for the Correlation Coefficients [ 17 ]. To provide evidence of the statistical significance of any linear association, the bootstrap bias-corrected and accelerated technique (BCa) [ 18 ] and an analytical extension of this, the ABC [ 19 ]. In addition, the bootstrap Delta method was employed, which although another bootstrap based method, was developed specifically for estimating the variance of a function of sample means. As the sample Correlation Coefficient can be readily expressed as such a statistic, it is also well suited to the estimation of confidence intervals for these Correlation Coefficients [ 12 ]. As both main approaches differ substantially, a more informed assessment of statistical significance could therefore be made. Variable angular frequencies To assess the robustness of < μH > to the fix angular frequency assumption, e.g., θ = 100°, θ was varied randomly about 100° and < μH > was calculated for each of the optimal windows for window sizes (7 ≤ L ≤ 20) for the 403 transmembrane proteins. These calculations were also obtained for similar random variations about the observed optimum angular frequencies, again, for the various window sizes (7 ≤ L ≤ 20). In all cases, it is assumed that the variation follows a Normal distribution with the mean value set at the desired value for θ and with the standard deviation, σ , set at: 0.1°, 0.3°, 0.5°, 0.7°, 0.9° and 1.1° respectively for six separate Monte Carlo simulation studies. The sample correlation coefficients for each simulation were calculated and compared to the empirically derived 99% confidence intervals for the corresponding population values and, in particular, with the point estimates for the original sequences. Causality and biological function Given that these data are from an observational study, it is necessary to assess whether any linear associations between < μH > and < H > for the α -helix forming sequences of our data set are likely to be causal or merely an artefact of amino acid composition. To investigate these possibilities, two additional simulation studies were undertaken. The first looked at spatial arrangements of residues within the primary sequences and the second focused on the effect of amino acid composition on correlations between < μH > and < H >. To assess if positional or sequential correlational properties existed for the amino acids within the sequences, the sequence of residues for each of the optimum windows was re-ordered randomly. Artificial sequences were thus generated by random rearrangement or randomisation [ 20 ] of the primary sequences within the 403 optimal windows. Hence, each window associated with < μH > was used to generate a random arrangement. To further investigate whether correlations between < μH > and < H > were dependent on sequence composition and not on spatial or sequential correlation, an additional parametric bootstrap simulation study was conducted. Here 403 artificial sequences were created. Each was randomly generated where, for each position, selection was based on the relative abundance of all the residues for the complete 403 optimum windows. In both cases the corresponding < μH > and < H > from these newly created sequences were calculated, the associated hydrophobic moment plots obtained and sample correlations calculated. These were inspected to assess whether any linear associations for the original transmembrane data were thus likely to be causal or merely artefactual and whether, from inspection of variation, there was evidence of increased organisation, which could be interpreted as an indication of biological function. Supplementary Material Additional File 1 Transmembrane sequence data set Click here for file

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509407

Interdependency of Brassinosteroid and Auxin Signaling in Arabidopsis

How growth regulators provoke context-specific signals is a fundamental question in developmental biology. In plants, both auxin and brassinosteroids (BRs) promote cell expansion, and it was thought that they activated this process through independent mechanisms. In this work, we describe a shared auxin:BR pathway required for seedling growth. Genetic, physiological, and genomic analyses demonstrate that response from one pathway requires the function of the other, and that this interdependence does not act at the level of hormone biosynthetic control. Increased auxin levels saturate the BR-stimulated growth response and greatly reduce BR effects on gene expression. Integration of these two pathways is downstream from BES1 and Aux/IAA proteins, the last known regulatory factors acting downstream of each hormone, and is likely to occur directly on the promoters of auxin:BR target genes. We have developed a new approach to identify potential regulatory elements acting in each hormone pathway, as well as in the shared auxin:BR pathway. We show that one element highly overrepresented in the promoters of auxin- and BR-induced genes is responsive to both hormones and requires BR biosynthesis for normal expression. This work fundamentally alters our view of BR and auxin signaling and describes a powerful new approach to identify regulatory elements required for response to specific stimuli.

Introduction The continuous shaping of plant form is a marvel of signal integration. In early seedling development this is particularly clear, as environmental cues, such as light, profoundly alter the innate morphogenetic program. How diverse pathways merge to determine a discrete cellular growth response is largely unknown. Auxin, the first plant hormone identified, has been implicated in patterning or growth of virtually every plant tissue from earliest embryo to developing fruit ( Liscum and Reed 2002 ). Brassinosteroids (BRs), the polyhydroxylated steroid hormones of plants, have been linked to many of these same processes, including photomorphogenesis ( Clouse 2002 ). The nature of the relationship between these hormones has remained largely undefined. Many factors in the signal transduction pathways operating downstream from BRs and auxin have been identified. Brassinosteroid Insensitive-1 (BRI1), a plasma-membrane-localized receptor serine/threonine kinase, is essential for BR perception and accounts for most BR-binding activity in Arabidopsis ( Wang et al. 2001 ). A Shaggy/GSK3-type kinase, Brassinosteroid Insensitive-2 (BIN2), acts as a negative regulator of the pathway downstream of BRI1 action ( Li and Nam 2002 ). When BR levels are low, proteins in the BES1/BZR1 family are hyperphosphorylated by BIN2 and targeted for degradation by the proteasome ( He et al. 2002 ; Yin et al. 2002a ). Upon BR perception, BIN2 is inactivated by an unknown mechanism which allows hypophosphorylated BES1/BZR1 proteins to accumulate in the nucleus, where they presumably provoke changes in gene expression ( He et al. 2002 ; Yin et al. 2002a ). In contrast to BRs, no auxin receptor has been identified. However, exposure to auxin is known to promote rapid turnover of nuclear Aux/IAA proteins by ubiquitin-mediated targeting to the 26S proteasome ( Gray et al. 2001 ). Aux/IAAs are direct negative regulators of the Auxin Response Factor (ARF) family of transcription factors and contain four highly conserved domains numbered I to IV ( Abel et al. 1995 ). Domains III and IV are also found in most ARFs and facilitate dimerization within and between members of both families ( Kim et al. 1997 ; Ulmasov et al. 1997b ). ARF proteins bind to a conserved auxin-responsive element (AuxRE) found upstream of many auxin-regulated genes ( Ulmasov et al. 1999 ). Previous studies have suggested that auxin and BRs may have a particularly close relationship among plant hormones. In a variety of bioassays representing diverse species, BRs have been shown to synergistically promote cell elongation when supplied with auxin ( Mandava 1988 ). Clouse and colleagues examined the effect of the two hormones on gene transcription more than a decade ago, and found that while BRs could activate the expression of some auxin-responsive genes, others appeared to be auxin specific ( Clouse et al. 1992 ; Zurek et al. 1994 ). They also noted that detectable BR effects required much longer treatments compared with the extremely rapid effects of auxin, and concluded that BR-mediated cell elongation effects were likely independent from the auxin signal transduction pathway. Microarray experiments, assaying approximately one-third of the Arabidopsis genome, rekindled interest in the interaction between auxin and BRs, as it was found that a significant percentage of the BR genomic response comprised genes annotated as auxin responsive ( Goda et al. 2002 ; Mussig et al. 2002 ; Yin et al. 2002a ). Recent work from Nakamura and colleagues has shown that three genes— IAA5, IAA19, and SAUR-AC1 —are induced by both auxin and BRs and that induction requires BR biosynthesis ( Nakamura et al. 2003a , 2003b ). In this work, genetic, physiological, and genomic approaches were used to dissect the relationship between auxin and BRs in seedling growth. Together these techniques demonstrated that the relationship between these hormones is far more deeply intertwined than previously suspected. Auxin and BR effects on cell elongation were found to be interdependent, and this physiological interdependency was mirrored at the transcriptional level. In addition, growth and transcriptional effects of exogenous BR treatment could be largely superceded by overstimulation of the auxin pathway. Several lines of evidence suggested that auxin:BR synergism did not depend upon biosynthetic regulation of hormone levels; rather, the two response pathways are likely to converge at the promoters of shared target genes. New computational approaches detected a number of known transcription factor–binding motifs enriched in promoters induced by both hormones, as well as motifs which are overrepresented in promoters activated specifically by auxin or BRs. This multifaceted approach elucidates the mechanism of action of both auxin and BRs in cell expansion, and serves as a model for interrogating complex signaling networks. Results Auxin and BRs Interact Synergistically to Promote Hypocotyl Elongation Early studies of BR effects in a variety of bioassays suggested that there was a synergistic interaction between auxin and BRs ( Mandava 1988 ). We confirmed and extended these studies to the reference plant Arabidopsis thaliana, using hypocotyl (primary stem) length as a quantitative measure of growth. Both hormones are known to induce cell elongation, and exogenous BR treatment has been shown to increase hypocotyl length ( Nemhauser et al. 2003 ). In contrast, addition of auxin to media has only modest effects on seedling hypocotyl elongation, likely as a result of inefficient acropetal transport from root to shoot ( Gray et al. 1998 ). However, increased temperature has been demonstrated previously to be an effective method of altering auxin levels in the shoot and leads to robust increases in hypocotyl length ( Gray et al. 1998 ; Zhao et al. 2002 ). In our conditions, hypocotyls of plants grown at 29 °C were approximately 1.8 times longer than those of plants grown at 22 °C, consistent with what has been observed by others ( Gray et al. 1998 ; Zhao et al. 2002 ). When exogenous brassinolide (BL), the most biologically active BR, was applied, hypocotyls of plants grown at elevated temperature exhibited a “kinked” morphology and agravitropic growth, typical of saturating BL conditions (data not shown). In order to examine the relationship between auxin and BRs, it was necessary to find conditions where auxin levels were increased but at subsaturating levels for the hypocotyl growth-promoting response. Plants grown at 26 °C versus 22 °C showed measurable increases in both hypocotyl elongation and levels of auxin intermediates ( Zhao et al. 2002 ). Using these conditions, it was possible to observe that plants grown at higher temperatures were more sensitive to exogenous BR treatment, both in threshold levels for response as well as in terms of absolute growth ( Figure 1 A). Figure 1 BR and Auxin Pathways Are Interdependent, as Measured by Hypocotyl Elongation (A) Mild temperature elevation causes elongation of the hypocotyl and BR hypersensitivity in WT plants. Columbia ecotype is shown but results are similar for Wassilewskija. Hypocotyls of 3-d-old plants grown at either 26 °C (diamonds, dashed line) or 22 °C (circles, solid line) were measured. (B) det2-1 plants are defective in BR biosynthesis and are also insensitive to the temperature increase. As the det2 deficiency is rescued by exogenous BL, temperature sensitivity is restored. (C) Plants with the weak bri1-5 mutation are insensitive both to temperature and exogenous BR. (D–H) BR response depends upon auxin response. WT is shown in circles with a solid thin line and mutants are shown in squares with a thick dashed line. Known auxin response mutants axr2-1 (D), axr1-12 (E), tir1-1 (F), and axr3-1 (G) have decreased BR response. (F) tir1 has no hypocotyl elongation phenotype in the absence of exogenous hormone treatment and only very modest effects on BR sensitivity. Response is significantly reduced in tir1 mutants at 100 nM BL, as measured by Student's t-test ( p = 0.03, using Bonferroni adjustment for multiple tests; Hochberg 1988 ). (H) yucca plants, which overproduce auxin, also show reduced BR response. Error bars represent standard error. Data in (F) and (G) were collected in a separate experiment from other panels, resulting in small differences in the values for WT hypocotyl length. BR- and auxin-mediated growth promotion required both pathways to be intact. As has been shown previously, hypocotyls of det2 mutants defective in BR biosynthesis ( Li et al. 1996 ) fail to elongate with increased temperature ( Gray et al. 1998 ; Zhao et al. 2002 ). Importantly, the hypersensitivity of det2 plants to exogenous BR was enhanced by increased temperature, suggesting that these two responses are tightly linked ( Figure 1 B). Weak bri1 mutants were also unresponsive to temperature, suggesting that auxin response was dependent on a functional BR signal transduction pathway ( Figure 1 C). The dramatic growth enhancement caused by overproduction of auxin in the yucca mutant ( Zhao et al. 2001 ) requires functional BRI1, as yucca bri1 mutants are dwarfs ( Figure 2 ). Conversely, BR response was dependent on a functional auxin signal transduction pathway as axr1 ( Lincoln et al. 1990 ) and axr2 ( Timpte et al. 1994 ) mutants with reduced auxin response showed significantly reduced sensitivity to BR treatment (see Figure 1 D and 1 E). The degree of BR insensitivity is correlated with the level of reduced auxin responsiveness, as tir1 mutants, which show only subtle phenotypes in the absence of exogenous auxin ( Ruegger et al. 1998 ), exhibited only a modest reduction in BR response (see Figure 1 F). axr3 mutants, which in many assays display a constitutive auxin response ( Leyser et al. 1996 ), were insensitive to BRs (see Figure 1 G). This suggests that the BR insensitivity observed in axr1 and axr2 mutants is not simply a block in cell elongation, and that regulated turnover of Aux/IAA proteins, such as those encoded by AXR2 and AXR3, is required for normal BR response. yucca mutants were also largely insensitive to exogenous BR and appeared saturated for the BR response (see Figure 1 H). Figure 2 Enhanced Hypocotyl Elongation of yucca Mutants Requires Functional BRI1 (A) Average hypocotyl lengths of 3-d-old plants. Error bars represent standard error. (B) Ten-day-old WT, yucca, yucca bri1-116, and bri-116 seedlings. Auxin and BR Transcriptional Responses Substantially Overlap Previous studies have identified several auxin-responsive genes that are also regulated by BRs ( Goda et al. 2002 ; Mussig et al. 2002 ; Yin et al. 2002a ; Nakamura et al. 2003a , 2003b ). To comprehensively compare the genomic effects of treatment with each hormone, Affymetrix oligonucleotide microarrays, representing approximately 22,000 genes, were hybridized with probes from two biological replicates following mock or BR treatment. Linear models were used to identify 342 transcripts whose levels were increased following BR treatment ( Figure 3 A; Tables S1 and S3 ). The levels of 296 transcripts were decreased in the same treatment ( Figure 3 A; Tables S2 and S4 ). Comparison with newly analyzed data from a similar experiment using auxin-treated seedlings ( Zhao et al. 2003 ) showed that nearly a quarter of genes upregulated by either auxin or BR treatment were regulated by both hormones ( Figure 3 A and 3 C; Tables S1–S6 ). This is a much larger overlap than that reported in the recent study by Goda and colleagues (2004) , likely reflecting substantial differences in experimental design and analysis methods, including the use of different microarrays. In addition, at least 75% of the genes identified as BR inducible were late responders (only observed after 12 or 24 h of BR treatment) and therefore were not included in the analysis described here. Figure 3 BR and Auxin Have Shared Genomic Effects (A) Venn diagram showing relative proportion of BR- and auxin-responsive genes and the degree of overlap. (B) Functional categories of BR–auxin shared genes reveal a potential growth signature. (C and D) Effects of auxin on BR-regulated gene expression. Transcripts which show elevated levels are shown in orange, those with decreased levels are shown in blue, and those transcripts whose levels are not changed are shown in yellow. (C) Relative ratios were derived from the following comparisons (from left to right): BR versus mock treatment (WT plants; B), auxin versus mock treatment (WT plants; A), and yucca versus WT (Y). The three columns to the left are BR-upregulated genes and the three columns to the right are BR-downregulated genes. Among the BR-upregulated genes, there are a large number that are also induced by auxin treatment or in a yucca background. Few BR-repressed genes are repressed by auxin. nc, no change. (D) Effect of BR treatment in yucca background. Relative ratios represent BR versus mock treatment in WT plants (WT) or in yucca mutants (YB). Approximately two-thirds of BR-regulated genes were not affected by BR treatment of yucca plants. (E) Quantitative PCR shows that shared target genes are synergistically induced when treated with both auxin and BRs. At5g64770 encodes a protein with unknown function. At1g18400 encodes BEE1, a bHLH-containing protein known to be required for the BR response ( Friedrichsen et al. 2002 ). At1g10550 and At4g30290 are putative endoxyloglucan transferases. Asterisks indicate response under an additive model. As much of the auxin response is transient, yucca plants which continuously experience high levels of auxin have a different profile of altered transcript levels than plants exposed to exogenous auxin for a short time period ( Zhao et al. 2002 ). To produce a more complete list of auxin-responsive genes, RNA from yucca seedlings was isolated and used to probe additional microarrays. More than 20% of all BR-upregulated genes were also differentially regulated in a yucca background ( Figure 3 C; Tables S1 and S2 ). In combination, 40% of the BR-upregulated genes were altered either by auxin treatment or in yucca mutants (see Table S1 ). Members of all known auxin-responsive gene families were identified, as has been seen in previous microarray experiments representing a smaller fraction of the genome ( Goda et al. 2002 , 2004 ; Mussig et al. 2002 ; Yin et al. 2002a ). While auxin treatment had no effect on ARF gene expression, transcripts of ARF4 (At4g30080) and ARF8 (At5g37020) were negatively regulated by BR treatment (see Tables S2 and S4 ). This is the first evidence of transcriptional regulation of ARF genes. In addition, BRs repressed the expression of several auxin transport–related transcripts, including PIN3 (At1g70940), PIN4 (At2g01420), PIN7 (At1g23080), and an AUX1 -like gene (At1g77690). Auxin induced the expression of BRI1 and a close paralog, BRL3 (At3g13380), and repressed the expression of another BRI1 -like gene, VH1/ BRL2 (At2g01950) ( Clay and Nelson 2002 ; Yin et al. 2002b ). It is possible that the genes identified here as auxin and BR responsive may represent a common growth signature regulated by many factors during seedling development. The majority of these genes do not have known functions; however, many of the rest are known or predicted to be involved in cell expansion, metabolism, and signal transduction ( Figure 3 B). Integration between Auxin and BR Signals Occurs in the Nucleus Many plant hormones directly regulate the levels of other hormones ( Alonso and Ecker 2001 ). This complicates analysis of cross-talk, which is defined by shared signal transduction components. The interdependency between auxin and BRs does not function primarily through regulation of hormone levels. Auxin does not induce BR biosynthesis. det2 plants, which are hypersensitive to exogenous BR treatment, were insensitive to growth at elevated temperature (see Figure 1 B). Auxin treatment does not affect the subcellular localization of BES1 ( Yin et al. 2002a ), and growth at elevated temperature does not alter BES1 levels or phosphorylation state (unpublished data). Conversely, BRs do not regulate auxin biosynthesis. Nakamura and colleagues (2003a) reported that det2 mutants make at least normal amounts of auxin and that BR treatments do not alter auxin levels. It was recently reported that the stability of an IAA1:luciferase fusion protein was unchanged following BR treatment, though the data were not shown ( Zenser et al. 2003 ). Here, we used a heat shock–inducible β-glucuronidase (GUS) reporter fused to the N-terminal portion of AXR3 described by Gray and colleagues (2001) . This construct was rapidly turned over in the presence of auxin but showed no change in stability following BR treatment ( Figure 4 D). Figure 4 Endogenous BR Levels Affect Expression of an Auxin-Responsive Reporter but Do Not Induce Aux/IAA Protein Turnover (A) WT, (B) det2 , and (C) DW4FOX plants carrying the DR5::GUS transgene. (A) GUS staining is particularly strong in young leaves (yellow arrow). (B) det2 plants show no GUS staining in aerial tissues. (C) DWF4OX plants show increased intensity of staining, particularly at the tips of emerging leaves (yellow arrow) and in the hypocotyl (orange arrows). Inset shows hypocotyl-root junction. (D) Aux/IAA stability does not appear to be affected by treatment with BRs. Plants carrying a heat shock–inducible fusion of the N-terminal portion of AXR3 and GUS reporter were subjected to 2 h at 37 °C and then treated with mock or hormone treatments for the time periods listed. Together, these results suggested that the interaction between the auxin and BR pathways was likely at the promoters of shared target genes. To test whether the auxin:BR synergism was detectable at the level of gene transcription, transcript levels from four genes identified in the microarray studies were quantified in plants exposed to exogenous treatment of either hormone or both in combination (see Figure 3 E). In all cases, levels of these transcripts were regulated nonadditively in the presence of both hormones. If, as suggested by these results, BR and auxin response pathways converge at the level of gene activation, we reasoned that yucca plants, which are largely insensitive to BR for growth promotion, might also show a reduced BR genomic response. RNA was isolated from yucca plants treated with BR and used to probe additional microarrays. Approximately two-thirds of genes showing BR responsiveness in wild-type (WT) plants were no longer affected by BR treatment in a yucca background (see Figure 3 D; Tables S1 and S2 ). This result strongly suggests that auxin and BR treatment affect transcription of these target genes by a common mechanism. Promoters of Coordinately Regulated Genes Share Regulatory Motifs Computational analysis of coordinately regulated genes is an emerging tool for dissecting regulatory networks (e.g., DeRisi et al. 1997 ; Harmer et al. 2000 ; Tullai et al. 2004 ). To identify potential regulatory elements acting in these pathways, a list of all genes regulated by either auxin or BR was generated, and 500 bp upstream of each gene were identified. These promoters were split into three groups: those with increased transcript levels following treatment with BR only (B group; n = 258), those with increased transcript levels following auxin treatment only (A group; n = 254), and those genes whose transcripts were induced following treatment with either hormone (AB group; n = 82). Known plant promoter elements and their annotations were downloaded from PLACE ( Higo et al. 1999 ) and used to screen each promoter list. The expected number of occurrences of each PLACE motif was estimated using 1,000 sets of n promoters randomly sampled from the genome, where n is equal to the number of promoters in each group (A, B, or AB). This approach offers a significant advantage over other background models used to assess enrichment. Permuted distributions reflect real expected frequencies and do not rely on assumptions about genome architecture. In addition, the normal distribution of site frequencies observed with large numbers of permutations allows for the use of powerful parametric statistical methods. Moreover, the ease of filtering based on relative probabilities makes this approach ideally suited to comparisons of promoters regulated in different conditions. In this study, matches were considered significant if a motif was overrepresented in a given set ( p < 0.1) and present in at least 10% of group promoters. This analysis identified several motifs specifically enriched in a given group ( Table 1 ), as well as several motifs found to be enriched in multiple groups ( Table 2 ). Table 1 PLACE Motifs Enriched Specifically in AB, A, or B Promoters Motifs with related patterns are grouped together by color a Total number of sites identified b Expected number of sites based on 1,000 randomly sampled groups of promoters c Percentage of promoters containing at least one site d Transcription factor family known to bind this element <, value is less than 0.001; SA, salicylic acid DOI:10.1371/journal.pbio.0020258.t001 Table 2 PLACE Motifs Enriched in Promoters of Multiple Groups See text and Table 1 caption for abbreviations DOI:10.1371/journal.pbio.0020258.t002 One of the sequences enriched in the B group was TGTCTC, previously identified as an auxin-responsive element ( Ulmasov et al. 1995 ) termed ARFAT in the PLACE database. Surprisingly, this sequence was not significantly enriched in the A set ( p = 0.78). However, the A, B, and AB groups showed significant enrichment of the core ARF-binding element TGTC in their promoters, perhaps reflecting some sequence divergence between Arabidopsis and soybean, where the element was first identified. A well-characterized synthetic element containing the ARFAT called DR5 ( Ulmasov et al. 1997a ) could be used to test the BR responsiveness of this element and was therefore introduced into plants with altered BR levels. In det2 plants with lower endogenous levels of BRs ( Li et al. 1996 ), DR5 expression was greatly reduced, particularly in the shoot ( Figure 4 A versus 4 C). Conversely, in plants with increased levels of BRs caused by overexpressing a BR biosynthetic gene, DWF4 ( Wang et al. 2001 ), DR5 expression was increased ( Figure 4 A versus 4 B). DR5 expression was also increased following transient BR treatment of WT plants carrying the DR5 reporter (unpublished data). Nakamura and colleagues (2003a) also recently demonstrated the BR inducibility of DR5::GUS and found no change in endogenous IAA levels following BR treatment, providing further evidence that BR transcriptional effects are direct. These data strongly suggest that the ARF-binding element requires both hormones for proper expression and should be considered a Brassinosteroid-Auxin Response Element. This finding raises questions about the utility of the DR5 element as a reporter of auxin response, as it likely reflects regions of regulatory overlap between the two pathways. Consensus binding sites for several families of transcription factors were identified as enriched in the AB set (see Table 1 ). The presence of a MYC consensus site in more than 80% of AB promoters was quite striking, especially in light of the BR and auxin inducibility of the bHLH-containing Brassinosteroid Enhanced Expression 1 ( BEE1; At1g18400) gene, which is known to function in BR response ( Friedrichsen et al. 2002 ). Many of the other AB consensus motif matches were implicated in regulation by light or abscisic acid (ABA), both of which have been linked previously to BR-mediated growth response by physiology and genetics ( Nemhauser and Chory 2002 ). For the B set, there was widespread occurrence of a GT-1 consensus binding motif, as well as evidence for a MYB-binding site distinct from that found in the A set. Identification of several elements specific for the A set, including those known to bind WRKY-family members, suggests attractive targets for designing new reporters which may not be BR dependent. Several instances of light-regulated motifs are intriguing given the strong evidence for a close relationship between auxin and light responses ( Tian and Reed 2001 ). Several of the promoter elements identified in the A, B, and AB promoters were found as multiple copies within promoters, including the core ARF-binding element TGTC. Recent studies have suggested that ARF dimerization is not required for activation of ARFAT-mediated transcription ( Tiwari et al. 2003 ). Interestingly, a scan of AB promoters revealed that nearly half of all AB promoters contain at least one instance of multiple copies of the core TGTC element within a 50-bp window. Clustering of TGTC sites was also seen in the A set (42% of promoters contain at least one pair of sites within 50 bp) and somewhat less frequently in the B set (33%). This finding suggests that interactions between ARFs may be important for hormone responsiveness of natural promoters, in addition to enhancing auxin inducibility of synthetic multimerized ARFATs. As specific binding factors are not known for most of the other elements identified, exact nucleotides required for factor binding are not known. Therefore, this analysis is likely a conservative estimate for the number of true transcription factor–binding sites present in each promoter. Discussion With the notable exception of auxin, most plant hormones are produced and perceived throughout the plant body. Modulation of hormone response stems from regulation of hormone levels and/or signal transduction components, as well as from interactions with other signaling pathways. There are many examples of cross-talk between hormones in plant biology. In addition to auxin and BRs, gibberellins (GAs), ethylene, ABA, and cytokinin have all been shown to affect hypocotyl elongation (reviewed in Nemhauser and Chory 2002 ). As mentioned previously, some of these hormones interact through biosynthetic regulation. For example, auxin, ABA, and cytokinin stimulate ethylene biosynthesis, particularly when supplied at high levels ( Yang and Hoffman 1984 ; Vogel et al. 1998 ; Ghassemian et al. 2000 ). Physiological and genetic evidence suggests that auxin, GAs, and ethylene promote hypocotyl growth by largely independent means ( Gray et al. 1998 ; Collett et al. 2000 ). Similarly, BRs and GAs interact additively in most cell elongation bioassays ( Mandava et al. 1981 ), and analysis of bri1 mutants suggests that the two hormones independently and antagonistically regulate transcription of some target genes ( Bouquin et al. 2001 ). In contrast, auxin and BRs interact synergistically and interdependently to promote hypocotyl cell elongation, making their relationship unique among plant growth regulators. The nature of hormone interactions may be tissue specific. A recent study demonstrated that auxin acts primarily through GAs to promote root elongation, and proposed that the DELLA family of negative regulators was a point of convergence between the two pathways ( Fu and Harberd 2003 ). One possible complication for this interpretation is that auxin is required for normal GA biosynthesis in pea ( Ross et al. 2000 ) and thus, the effects of auxin on DELLA protein stability may be indirect. We have preliminary evidence that interactions between auxin and BRs may be different in aerial tissues than in roots. While auxin and BRs promote hypocotyl elongation, the hormones have opposite effects on root hair growth (J. L. Nemhauser and J. Chory, unpublished data). In addition, reduced BR levels or response may actually increase auxin effects on root pericycle proliferation (J. L. Nemhauser, N. Geldner, and J. Chory, unpublished data). While auxin and BRs stimulate elongation of the hypocotyl, light antagonizes this effect. The AB genes induced by auxin and BRs may be targets for repression by the light response. Plants with reduced BR levels or response show a light-grown phenotype even when grown in the dark, including a short hypocotyl, expansion of cotyledons, and production of leaves. Many mutants with stabilized Aux/IAA proteins also show this deetiolated phenotype ( Tian and Reed 2001 ). Levels of BRs may be light regulated ( Kang et al. 2001 ), and response to BRs is affected by light quality and intensity ( Nemhauser et al. 2003 ). Interestingly, two photoreceptors, PHOT1 (At3g45780) and Phytochrome E (At4g18130), are both downregulated by BRs. Two potential negative regulators of the light response, PKS1-like (At5g04190) and DRT100 (At3g12610), are upregulated by both auxin and BRs. Differential regulation of target genes by auxin, BRs, and light may allow fine-tuning of the photomorphogenetic response. Bioinformatic Analysis of Signaling Networks The regulation of gene expression in eukaryotes is complex and is largely mediated by multiple transcription factors that bind within regulatory regions upstream of the coding sequence. In the simplest model, coexpressed genes exhibit similar expression characteristics because they are regulated by the same transcription factors. A number of algorithms have been developed to identify potential regulatory motifs overrepresented in the promoter sequences of coregulated genes (reviewed in Rombauts et al. 2003 ). Each algorithm requires a background model to calculate the expected frequency for each motif. The simplest background model estimates the expected frequency for a given motif based on the single nucleotide composition of the analyzed sequences ( Bailey and Elkan 1995 ; Roth et al. 1998 ). Improvements on these methods use so-called higher-order models based on Markov chain statistics ( Thijs et al. 2001 , 2002 ; Marchal et al. 2003 ), building the background model by estimating the probability at each nucleotide position based on the previous bases in the sequence. Other approaches include enumerative methods that generate background models based on whole-genome motif counts from noncoding intergenic ( van Helden et al. 1998 ) or randomly sampled ( Marino-Ramirez et al. 2004 ) genomic sequences. Because biological sequences are inherently nonrandom, we chose another approach to build our background model. For each motif under consideration, we modeled the expected frequency distribution by randomly sampling sets of promoter sequences from among all the genes represented on the microarrays used in our study. Therefore, we could directly estimate the statistical significance for each motif from its Z score, which is the number of standard deviations by which the observed frequency exceeds the expected frequency based on the distribution observed in the permutation sampling. In contrast to other methods, our approach uses a background model based on a real distribution of motif counts derived from annotated promoter sequences, rather than estimating expected word frequencies from simulated or randomly selected genomic sequences or from models based on distribution functions. Thus, given any set of Arabidopsis genes clustered on the basis of similar expression, we could easily identify overrepresented known transcription factor–binding motifs or overrepresented novel presumptive promoter elements. For example, new experiments assaying genomic effects of different hormone treatments or environmental conditions could be used to define finer groupings of coregulated genes and could be readily integrated into our current analysis. A Model for Auxin:BR Synergy Auxin:BR synergism results from convergence of the two response pathways on a common mechanism for promoting cell elongation. The integration of these hormone signals occurs very late in signal transduction, likely at the promoters of more than 80 genes whose expression is induced by short treatments with either hormone. Several known regulatory elements have been identified in these common target genes. The well-characterized auxin-response element ARFAT is one crucial node of intersection between the BR and auxin pathways, as it is BR responsive and requires BR synthesis for normal expression. More than 20 ARFs have been identified in the Arabidopsis genome ( Liscum and Reed 2002 ). Many have been shown to bind the ARFAT motif and promote auxin-inducible gene expression ( Ulmasov et al. 1997b ; Tiwari et al. 2003 ). Stabilization of Aux/IAA proteins, such as AXR2 and AXR3, completely blocks BR growth responses. We propose a model where auxin and BR pathways converge on regulation of ARF transcription factors ( Figure 5 ). Figure 5 A Model of BR–Auxin Interaction Auxin and BR signals are likely integrated on promoters of shared target genes. The node(s) of intersection between auxin and BR pathways must be downstream of BES1 and Aux/IAAs and upstream of gene expression. One likely mechanism is via regulation of transcriptional complexes, such as those containing the ARFs. Cross-talk is a common feature of animal growth regulator pathways. For example, glucocorticoids synergistically enhance the effects of retinoic acid in mouse cells ( Subramaniam et al. 2003 ). Upon ligand binding, the glucocorticoid receptor directly interacts with the homeodomain protein Pbx1 and activates transcription of Hoxb-1. In Xenopus, transcriptional activation of several genes, including twin, siamois, and nodal-related-3, requires stimulation of both TGFβ and WNT pathways. Similarly, two transcription factors, SOX10 and KROX20, have been recently reported to interdependently regulate expression of a neural crest–specific enhancer conserved among mouse, human, and chicken ( Ghislain et al. 2003 ). This type of coregulation is also seen in plants. One example is the synergistic interaction between osmotic stress and ABA response, which is likely mediated by interaction between DREB and AREB transcription factors ( Narusaka et al. 2003 ). In all of these cases, signal integration is achieved by formation of a complex containing transcription factors independently regulated by each pathway, often binding to composite regulatory elements. By integrating the inputs of multiple pathways, these mechanisms provide cellular or regional specificity for a given response. ARFAT was originally identified as part of a composite element ( Ulmasov et al. 1995 ). However, DR5 has been characterized as a multimerized simple response element ( Ulmasov et al. 1997b ) and can be activated by either auxin or BRs. So, unlike in the systems described above, auxin and BR signals likely converge on the same family of transcription factors. Such a relationship has recently been described for ethylene and jasmonate in plant defense responses ( Lorenzo et al. 2003 ). Both ethylene and jasmonate pathways are required to induce expression of the transcription factor ERF1, which in turn regulates the expression of a number of defense-related genes. Neither auxin nor BRs have large effects on ARF transcription, and several AB targets are early-response genes not requiring de novo protein synthesis for activation ( Friedrichsen et al. 2002 ; Liscum and Reed 2002 ). Auxin and BRs likely regulate ARF complex activity posttranslationally rather than through transcriptional regulation. Auxin is already known to modulate ARF activity by regulating the stability of the interacting Aux/IAA repressor proteins ( Gray et al. 2001 ; Tiwari et al. 2003 ). BR perception could increase ARF activity by leading to modification of the ARFs themselves or through interactions with a BR-regulated transcriptional coactivator. The additional transcriptional regulation of some ARFs by BRs, together with auxin and BR effects on a number of Aux/IAA genes, could favor formation of particular transcriptional complexes promoting growth. Five genes encoding proteins with DNA-binding motifs were induced by both hormones, including members of the MYC, EREBP, and leucine zipper families. Higher-order interactions among several transcription factor complexes, perhaps directly involving members of the BES1/BZR1 family, could provide additional control of the shared auxin:BR response pathway. A longstanding question in plant biology has been how a small number of hormones with overlapping functions can provoke a wide range of responses. Combinatorial control has long been suggested as one possible explanation (e.g., Singh 1998 ). The detailed analysis of BR and auxin pathways in this work suggests that hormone response is determined by the cellular milieu. Additional factors, including other hormones and environmental stimuli, can be incorporated into this model, leading ultimately to a detailed map of plant growth processes. Materials and Methods Hypocotyl measurements Seeds were sterilized for 15 min in 70% ethanol, 0.01% Triton X-100, followed by 10 min of 95% ethanol. After sterilization, seeds were suspended in 0.1% low-melting-point agarose and spotted on plates containing 0.5× Murashige Minimal Organics Medium (Gibco-BRL, San Diego, California, United States), 0.8% phytagar (Gibco-BRL), and one of five concentrations of BL (0, 1, 10, 100, or 1,000 nM). Seeds on plates were then stratified in the dark at 4 °C for 2 d. Plants were grown in approximately 35 μmol m −2 s −1 white light with a red:far-red light ratio near 1. Plate position was changed every 24 h to minimize position effect. Hypocotyl lengths were measured from 10 to 14 3-d-old seedlings. Seedlings were removed from one plate at a time and scanned between two transparencies on a flatbed scanner. NIH Image 1.62 was used to perform length measurements. All dose-response experiments were performed in duplicate. bri1-5 is a weak allele in a Wassilewskija background. All other mutants used in this work are in a Columbia background. GUS staining GUS staining protocol was as described in Sessions et al. (1999) . Induction of AXR3-NT-GUS lines was as described in Gray et al. (2001) . Microarray studies Nine-day-old, light-grown Arabidopsis seedlings were immersed in 1 μM BL in 0.5× Murashige Minimal Organics Medium (Invitrogen, Carlsbad, California, United States) or medium alone for 2.5 h before they were harvested for total RNA preparation. Total RNA from the treated seedlings was used for preparing probes for the microarray experiments, which were carried out according to the protocols provided by the gene chip manufacturer Affymetrix (Santa Clara, California, United States). All experiments used two independent biological replicates. Details of the auxin experiment have been described previously ( Zhao et al. 2003 ). Data analysis was performed in R ( Ihaka and Gentleman 1996 ). Genes were normalized using rma in the Bioconductor affy package ( http://www.bioconductor.org ; Irizarry et al. 2003 ) and subsequently analyzed using linear models and Empirical Bayes analysis (limma package; Smyth 2004 ). To be considered differentially expressed, genes were required to have a false discovery rate adjusted p value of less than 10% and an empirical Bayes log odds of differential expression (B) greater than 0. Data are available at Gene Expression Omnibus; see Supporting Information for accession numbers. Quantitative PCR Plants were treated with hormones as above using treatments of either 1 μM BL, 1 μM indole-3-acetic-acid (auxin), both hormones, or a mock treatment. Total RNA was extracted using a Qiagen (Valencia, California, United States) RNAeasy kit and first-strand cDNA was synthesized using an Invitrogen Superscript First-Strand cDNA Synthesis kit. cDNAs were diluted 20-fold and combined with SYBR master mix (PE Biosystems, Wellesley, California, United States) for PCR. Primers were as follows: At5g64770 (5′-CTTCTCATACTCTTCATTTCCTCTCCTACT-3′, 5′-TTCTCGTAAGCTTCGTGCTTGA-3′), At1g18400 (5′-CTAGCGGCGTCTCCGATAAT-3′, 5′-AAGAACCTGTTTCAGTGGCAATAAC-3′), At1g10550 (5′-AAGCTTCCCGCTGGATTTG-3′, 5′-TTGATAAATAGAAAGCAACCACAACAC-3′), and At4g30290 (5′-TCCCTGGTAACTCTGCTGGAA-3′, 5′-CCGGAGATTTAAGATAGAATGTTGTGA-3′). At5g15400 (ubiquitin) was used to normalize all values (5′-TGCGCTGCCAGATAATACACTATT-3′, 5′-TGCTGCCCAACATCAGGTT-3′). PCR reactions were performed in triplicate and analyzed using an ABI PRISMA 7700. A standard curve was constructed for each primer using an equal mixture of all cDNAs. Sequences for promoter analysis We used a Perl script to extract the 500 bp of sequence preceding the 5′ end of each annotated transcription unit in the AGI pseudomolecules annotation (14-May-2003) downloaded from NCBI. These putative promoter sequences begin immediately upstream of the 5′ UTR for transcription units with an annotated 5′ UTR, and upstream of the annotated translational start for the remainder. Promoter analysis and significance calculations We analyzed putative promoter regions upstream of auxin- and BR-regulated genes to identify overrepresented promoter elements. One thousand surrogates of each promoter set were created by randomly shuffling the list of genes represented on the Affymetrix ATH1 arrays and then sampling n genes and extracting 500-bp promoter sequences for the sampled set of genes. Known plant promoter elements and their annotation were downloaded from PLACE ( Higo et al. 1999 ). For each set of n promoters, the null distribution for each PLACE motif was modeled by counting the number of occurrences for each word within each of the 1,000 surrogate sets of n promoters. Using this approach we could then ask how well the observed frequency of a certain motif in a set of n promoters matched the frequency that would be expected for a random set of n promoters. We estimated the one-tailed p value for each motif based on the Z score of the difference of the actual word count of the promoter set (C true ) minus the mean count from the 1,000 surrogates (C surr ) relative to the SD from the 1,000 surrogates (SD surr ) [i.e., Z = (C true − C surr )/SD surr ]. Thus for each motif the p value we calculated was the probability to the right of the observed count calculated on the null distribution derived from sampling promoters randomly from the genome. We considered a motif to be significantly overrepresented if this probability was less than 0.1. These calculations were implemented using Perl scripts and a relational database (MySQL). Supporting Information Table S1 Fold Change of BL-Upregulated Genes following Exposure to BL or IAA (Auxin) Treatment Effects of increased auxin levels in the yucca mutant are shown as compared to WT and following BL treatments. The comparisons from left to right are WT BL- versus mock-treated, WT IAA- versus mock-treated, yucca mock-treated versus WT mock-treated, and yucca BL- versus mock-treated. nc, no change. (160 KB XLS). Click here for additional data file. Table S2 Fold Change of BL-Downregulated Genes following Exposure to BL or IAA (Auxin) Treatment Effects of increased auxin levels in the yucca mutant are shown as compared to WT and following BL treatments. The comparisons from left to right are WT BL- versus mock-treated, WT IAA- versus mock-treated, yucca mock-treated versus WT mock-treated, and yucca BL- versus mock-treated. nc, no change. (169 KB XLS). Click here for additional data file. Table S3 Normalized Values of BL-Upregulated Genes ave, average; se, standard error. (64 KB XLS). Click here for additional data file. Table S4 Normalized Values of BL-Downregulated Genes ave, average; se, standard error. (64 KB XLS). Click here for additional data file. Table S5 Values of IAA-Upregulated Genes ave, average; se, standard error. (63 KB XLS). Click here for additional data file. Table S6 Normalized Values of IAA-Downregulated Genes ave, average; se, standard error. (26 KB XLS). Click here for additional data file. Accession Numbers The Gene Expression Omnibus ( http://www.ncbi.nlm.nih.gov/geo/ ) accession numbers for the genes and gene products discussed in this paper are WTBR1 (GSM13423), WTBR2 (GSM13424), WTmock1 (GSM13420), WTmock2 (GSM13421), wtzm1 (GSM13430), wtzm2 (GSM13432), wtzmIAA1 (GSM13433), wtzmIAA2 (GSM13434) and, yucca BR1 (GSM13428), yucca BR2 (GSM13429), yucca mock1 (GSM13426), and yucca mock2 (GSM13427).The associated experimental descriptions are available at accession numbers GSE862 (BR effects on WT and yucca seedlings) and GSE863 (auxin effects on seedlings).

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539249

Identification of a panel of tumor-associated antigens from breast carcinoma cell lines, solid tumors and testis cDNA libraries displayed on lambda phage

Background Tumor-associated antigens recognized by humoral effectors of the immune system are a very attractive target for human cancer diagnostics and therapy. Recent advances in molecular techniques have led to molecular definition of immunogenic tumor proteins based on their reactivity with autologous patient sera (SEREX). Methods Several high complexity phage-displayed cDNA libraries from breast carcinomas, human testis and breast carcinoma cell lines MCF-7, MDA-MB-468 were constructed. The cDNAs were expressed in the libraries as fusion to bacteriophage lambda protein D. Lambda-displayed libraries were efficiently screened with sera from patients with breast cancer. Results A panel of 21 clones representing 18 different antigens, including eight proteins of unknown function, was identified. Three of these antigens (T7-1, T11-3 and T11-9) were found to be overexpressed in tumors as compared to normal breast. A serological analysis of the 21 different antigens revealed a strong cancer-related profile for at least five clones (T6-2, T6-7, T7-1, T9-21 and T9-27). Conclusions Preliminary results indicate that patient serum reactivity against five of the antigens is associated with tumor disease. The novel T7-1 antigen, which is overexpressed in breast tumors and recognized specifically by breast cancer patient sera, is potentially useful in cancer diagnosis.

Background A recent development in tumor immunology is based on the idea that the immune system can distinguish between normal and tumor tissues. Various studies suggest that both the cellular and humoral components of the immune system are able to recognize tumors (see review of Lake et al.) [ 1 ]. The presence of natural antibodies against cancer cells in peripheral blood of tumor patients probably plays a protective role against tumor development. The latest advances in molecular techniques further support the existence of natural antibodies against cancer antigens. The SEREX approach, based on the serological screening of cDNA expression libraries generated from tumor tissues of various origin, led to the molecular definition of immunogenic tumor proteins (tumor-associated antigens, TAAs) based on their reactivity with autologous patient sera [ 2 ]. This type of screening of a cDNA expression library is quite a laborious procedure requiring the preparation of a large number of membrane filters blotted with bacteriophage plaques, which are then screened with sera from cancer patients, usually available in limited quantity. In contrast to SEREX, phage display strategy is based on the selection and enrichment of antigens displayed on the phage surface. A physical link between a displayed fusion protein and the DNA encoding for it makes this phage target selectable through affinity purification. Phage display technology has been successfully applied to the screening of cDNA libraries from different tumors using the antibody repertoire of cancer patients [ 3 - 6 ]. In these experiments different phage display systems were used. Some of the authors used the C-terminus of a filamentous phage minor protein pVI for expression of cDNA libraries from breast cancer cell lines T47D and MCF-7 [ 3 ] and from colorectal cancer cell line HT-29 [ 5 ]. However, the filamentous phage display system imposes some biological bias for the expression and display of fusion proteins, since a filamentous phage-based library displays only those recombinant proteins able to pass through the inner bacterial membrane during filamentous phage assembly. To overcome this potential problem the lytic bacteriophages T7 [ 4 ] and λ [ 6 ] were used. By using these latter systems, the phage capsid is assembled in the cytoplasm of bacteria and mature phage particles are released by cell lysis. For example, Hansen and co-workers in their studies screened a commercially available (Novagen) human breast cancer cDNA library cloned in T7 vector [ 4 ], identifying positive clones. Usually cDNA libraries are generated as C-terminal fusions. When such a library is panned on a serum, the presence of a complex antibody repertoire gives to out-of-frame or antisense-derived cross-reactive short peptide sequences a good chance of being enriched. In our previous work [ 6 ] we designed a new-concept lambda vector for the display of cDNA-encoded protein fragments as fusion to the N-terminus of bacteriophage gpD, allowing us to overcome this obstacle. In this vector, phage clones display a given protein fragment on the phage surface only when the insert's correct reading frame matches that of gpD. The size of the cloned DNA fragments in our libraries was adjusted to an average of 200–300 base pairs, which is of a size reasonably sufficient to potentially encode for a protein domain. The vast majority of out-of-frame sequences of the above-mentioned length most probably contains at least one in-frame stop codon. Thus, these inserts are not expressed as D fusion, are consequently not displayed on the phage surface and cannot be selected. In such cases, phage capsid contains only wt gpD encoded by lambda genome D gene. The N-terminal display system greatly reduces the selection of artifactual peptides, in comparison with a C-terminal fusion library displayed on lambda ([ 7 ] and our unpublished data). By employing the SEREX approach numerous tumor antigens from different human neoplasms were identified [ 8 , 9 ]. Analysis of TAA expression in tumor samples and normal tissue led to the identification of a group, called cancer/testis antigens. Members belonging to this family are aberrantly expressed in human cancers and only in normal testis, but not in other normal tissue. For this reason, in addition to tumor samples and tumor cell lines, testicular cDNA libraries are also a convenient source of antigens which can be identified by screening with sera derived from tumor patients [ 10 , 11 ]. In the present work we report the construction of lambda-displayed cDNA libraries from breast cancer cell lines MCF-7, MDA-MB-468, from human breast carcinomas and from human testis, generated according to an improved protocol. These libraries were screened by using sera from breast cancer patients. The list of 21 identified antigens contains eight proteins with still unknown functions. Three of the genes (T7-1, T11-3 and T11-9) were found to be overexpressed in tumors as compared to normal breast. Recognition by human sera of five of the selected antigens (T6-2, T6-7, T7-1, T9-21 and T9-27) was associated with cancer diagnosis. Methods Tissue and serum samples Specimens of breast carcinoma and autologous sera from breast cancer patients (B81-B96) were obtained from M. G. Vannini Hospital, Rome. A panel of human sera from breast cancer patients B1-B20, B36-B80 was provided by the Division of Medical Oncology, Federico II University of Naples. All the human biological samples were obtained through informed consent. Construction of λKM8, λKM10 vectors λKM8 was constructed by cloning the oligonucleotide duplex KM46 5’-CTAGTCTCCTCAGCGGCCGCGGTTCCGGTTCTGGTTCCGGTTCTGGTTCCGGTTCTGGT-3’ and KM47 5’-GGCCACCAGAACCGGAACCAGAACCGGAACCAGAACCGGAACCGCGGCCGCTGAGGAGA-3’ into Spe I, Not I sites at the 5'-end of the D gene in λKM4 vector [ 6 ]. The resulting vector λKM8 maintains the unique Spe I and Not I sites and encodes for a GS linker between the fusion site and gpD, Figure 1 . The plasmid pKM7 is a derivative of pKM3 [ 6 ], which was obtained by cloning of the oligonucleotide duplex K52 5’-GACCGCGTTTGCCGGAACGGCAATCAGCATCGTTACTAGTTTATTAAGCGGCCGCTAAGTGAGTG-3’ K53 5’-AATTCACTCACTTAGCGGCCGCTTAATAAACTAGTAACGATGCTGATTGCCGTTCCGGCAAACGCG-3’ into pKM3 previously digested with Rsr II and EcoR I restriction enzymes. pKM7 was digested with Spe I and Not I to obtain pKM9, by direct cloning of the oligonucleotide duplex KM48 5’-CTAGCGGTTCCGGTTCTGGTTCCGGTTCTGGTTCCGGTTCTGGCACTAGTCTCCTCAGC-3’ and KM49 5’-GGCCGCTGAGGAGACTAGTGCCAGAACCGGAACCAGAACCGGAACCAGAACCGGAACCG-3’. λKM10 was constructed by cloning pKM9, which was linearized by digestion with Xba I restriction enzyme, into the Xba I site of λ Dam15imm21nin5 [ 12 ]. The resulting vector λKM10 bears unique Spe I, Not I sites at the 3'-end of the D gene and encodes for a flexible GS linker between gpD and the cloned protein fragment, Figure 1 . RNA extraction mRNA from breast carcinoma cell lines MCF-7 and MDA-MB-468 was isolated in a single step by QuickPrep Micro mRNA Purification Kit (Amersham Pharmacia Biotech, UK) according to manufacturer's instructions. Tumor samples from breast carcinoma patients were obtained as surgical specimens and immediately frozen in liquid nitrogen. Total RNA was prepared by Total RNA Isolation System (Promega, Madison, WI) and purified to Poly A+ RNA using PolyATract mRNA Isolation Systems (Promega). Total RNA from normal testis was purchased from Genpak, UK (# 061023). Total RNA from normal breast (pool of 3) was purchased from Stratagene, La Jolla, CA (# 735044). cDNA library construction From 1 to 5 μg of the purified poly(A) + RNA from cell lines or human tissues were used to synthesize cDNA by random priming, using TimeSaver cDNA Synthesis Kit (Amersham Pharmacia Biotech, Piscataway, NJ, USA). RNasin Ribonuclease Inhibitor (Promega) was added to first-strand synthesis reaction. A mixture of the following oligonucleotides (130 pmol): K64 (5'- GCGGCCGC TGGNNNNNNNNN-3'), K79 (5'- GCGGCCGC TGGCNNNNNNNNN-3'), and K81 (5'- GCGGCCGC TGGCANNNNNNNNN-3') was used for priming. They all carry a Not I site (underlined) at their 5' end, and a random sequence of nine nucleotides at their 3' end, positioned in the three possible reading frames. The second strand was synthesized by nick translation according to the manufacturer's instructions. One hundred ng of ds cDNA were randomly primed with 25 pmol of oligonucleotide K56 (5'-GGCCGGCCAACNNNNNNNNN-3'), constituted by a constant sequence at the 5' end, and a random 3'sequence. The reaction mixture was purified by QIAgen QIAquick columns. Approximately 0,2 ng of the above randomly primed ds cDNA was amplified by PCR with biotinylated primers: K59 (bio-5'-GC ACTAGT GGCCGGCCAAC-3'), K60 (bio-5'-GC ACTAGT CGGCCGGCCAAC-3'), K61 (bio-5'-GC ACTAGT CGGGCCGGCCAAC-3') and K65 (bio-5'-GGAGGCTCGA GCGGCCGC TGG-3'). K59, K60 and K61 carry the same constant sequence of K56 positioned in the three possible frames with respect to a Spe I site (underlined) allowing directional cloning. K65 carries a Not I site (underlined), that anneals to the 5' end of the reverse strand of cDNA. PCR product was purified with QIAquick PCR purification kit (QIAGEN, Germany), filtered by Microcon-100 columns (Millipore, Bedford, MA) to reduce the number of small fragments and additionally fractionated by 6% PAGE. DNA smear, corresponding to 300–1000 base-pair fragments, was cut and eluted from gel according to standard procedure [ 13 ]. After digestion with Spe I and Not I enzymes, in order to remove the biotinylated extremities and uncut fragments, a 20-minute incubation with streptavidin M-280 Dynabeads (DYNAL, Norway) was performed. After additional filtration on Microcon-100 the insert was cloned in λKM8 or λKM10 vectors. The vector was digested with Spe I, Not I enzymes and dephosphorylated. For each library 5 ligation mixtures, each one containing 0.5 μg of vector and about 3 ng of insert, were performed. After overnight incubation at 4°C the ligation mixtures were packaged in vitro by lambda packaging extract (Stratagene, La Jolla, CA). BB4 cells were infected by lambda and plated in top-agar on 100 (15 cm) NZY plates. After overnight incubation phages were eluted from the plates with SM buffer, purified, PEG/NaCl precipitated [ 13 ] and stored at -80°C in SM buffer, 7% DMSO. Affinity selection Two μl of human serum were preincubated with 10 μl of BB4 bacterial extract and 10 μl of UV-killed lambda phage in 1 ml of blocking buffer (3% BSA, 1X PBS, 10 mM MgSO 4 , 1% Triton) for 30 minutes at 37°C under gentle agitation. 10 10 pfu of lambda library were then added to the preincubated mixture for a further incubation of 1 hr. Magnetic beads (100 μl), linked to Protein A (Dynabeads Protein-A, Dynal, Norway) were washed twice with the blocking solution. Mixture of library with serum was incubated with the beads for 10 min at RT under agitation. The beads were washed 10 times with 1 ml of washing solution (1X PBS, 1% Triton, 10 mM MgSO 4 ). The bound phages were recovered by infection of 600 μl BB4 cells added directly to the beads. After a 20-minute incubation 10 ml of molten NZY-top agar (48°C) was added to the mixture of beads with infected cells and immediately poured onto NZY plates (15 cm). Next day the phage particles were harvested by incubation of the plates under agitation with 15 ml of SM buffer for 4 hours at 4°C. The phage particles were purified by PEG/NaCl precipitation and stored in 1/10 of initial volume of SM with 0.05% NaN 3 at 4°C. Analysis of gene expression by PCR Five hundred ng of poly(A) + RNA from breast carcinomas or normal tissue were used to synthesize full-length cDNA by SMART cDNA library construction kit (Clontech, Palo Alto, CA). For maximum sensitivity specific primers for the different genes were designed to amplify sequences located near the 3' end of gene's transcript. Twenty-five cycles of PCR were performed from 1 μl of each cDNA template, normalized through PCR amplification of the β-actin gene. Results Construction of the libraries Lambda libraries were constructed by directional cloning of randomly primed cDNA from human breast carcinoma cell lines MCF-7 and MDA-MB-468, from human breast carcinomas or from human testis into the phage display vector λKM8 to generate fusions with the N-terminus of gpD (see list of libraries in Table 1 ). Only library T6 was built like C-terminal fusions with protein D by cloning cDNA into λKM10 vector. λKM8 and λKM10 are derivatives of λKM4 vector [ 6 ] obtained by introducing a flexible GS-linker between the displayed protein and gpD (Fig. 1 ). The insert size in the majority of the clones in the libraries ranged from 100 to 400 bp (Fig. 2 ). Only a tiny fraction of out-of-frame clones of this length do not contain stop codons, and are therefore displayed in the libraries constructed as N-terminus fusions, thus greatly reducing the probability of the selection of mimotopes. Selection of tumor-associated antigens The scheme of TAA identification is shown in Figure 3 . Typically, one or two rounds of biopanning, performed according to the selection protocol described in Materials and Methods, were sufficient to obtain 2–50% of positive clones in the following immunoscreening procedure. Then, the identified phage clones were tested with a panel of positive and negative human sera by picking the clones in arrayed order on the bacterial lawn, blotting onto nitrocellulose membrane and probing with a number of different sera as previously described [ 6 ]. The nucleotide sequences of 21 clones that exhibited specific or preferential reactivity with sera from breast tumor patients as compared to sera from healthy donors were identified, and their nucleotide sequences were determined (Table 2 [see Additional file 1 ]). Serological analysis of tumor antigens Phage lysates were prepared from all the selected clones as previously described [ 6 ] and tested in ELISA first with a collection of negative, and subsequently, with positive sera (Table 2 [see Additional file 1 ]). All the antigens tested reacted exclusively or preferentially with sera from breast cancer patients. Eight of the antigens reacted only with the patient serum used in the corresponding selection. Five antigens had cancer-related profile of reactivity, P < 0.05 (T6-2, T6-7, T7-1, T9-21 and T9-27). The other antigens either reacted with a low percentage of cancer sera, or the total panel of the tested sera was too small to offer any clear conclusion. Sequence analysis of selected cDNA clones Twenty-one positive clones were found to encode fragments from 18 different gene products, such as 4 clones (T5-9, T9-21, T9-27, T11-7) showing homology to different regions of the same reverse transcriptase gene (Figure 4 ). Most of the clones correspond to known gene products in the correct orientation and reading frame, with the exception of clone T5-18 encoding myc oncogen in an alternative frame. Several of these known gene products, such as reverse transcriptase homolog (clones T5-9, T9-21, T9-27, T11-7), protein kinase C-binding protein (T6-1), trap ankyrin repeat (T11-3), heat shock protein apg-2 (T11-13), have been previously identified by SEREX [ 9 , 14 - 17 ]. Eight of the sequences listed in Table 2 [see Additional file 1 ] encode for proteins with unknown functions. Cancer-specific expression of selected tumor antigens Expression patterns for several of the selected genes were analyzed by semi-quantitative PCR from SMART cDNA template. It has been previously shown [ 18 ], by comparing the expression level of target genes in SMART PCR-amplified cDNAs and their corresponding total RNAs, that SMART cDNA accurately reflects gene expression patterns found in total RNA. We normalized the panel of cDNAs from ten different breast carcinomas, one metastasized lymph node, normal breast, normal testis and peripheral blood lymphocytes from healthy donors, by PCR amplification of a housekeeping gene, β-actin (Figure 5 ). Three of the identified antigens, fucosyltransferase (T6-7), Zinc finger protein 258 (T11-6), and p53-binding protein (T1-52) [ 6 ], were ubiquitously expressed in all the tumor and normal tissue samples tested (Figure 5A ). Some of the antigens, T5-15 (KIAA1735), T5-13 (Sos1), T11-5 (hypothetical protein MGC4170) were found to be downregulated in many tumors (Figure 5B ). T11-9 (hypothetical protein AF225417) was overexpressed in 50% of the primary tumors and the unique metastasized lymph node tested. T11-3 (trap ankyrin repeat) was overexpressed in most of the tumors tested in comparison with normal breast, although it was also transcribed in testis and normal lymphocytes (Figure 5C ). T7-1 (KIAA1288) was found to be overexpressed in 50% of the primary breast carcinomas and in the metastasis specimen tested. In order to obtain an evaluation of the accuracy of the method used for the analysis of gene expression, we performed PCR amplification of neu/HER2, a known tumor marker overexpressed in breast cancer. We observed that neu/HER2 is overexpressed in 2 primary tumors among the 7 tested (≈29%) in accordance with the literature on breast carcinoma [ 19 , 20 ]. Discussion In the present study we report the construction of MCF-7 and MDA-MB-468 cell lines, breast carcinoma and testis cDNA phage-displayed libraries expressed as fusions to bacteriophage lambda gpD. The new phage vectors bear a flexible GS linker between the cloned protein domain and protein D, so as to facilitate lambda head assembly. Moreover, a new efficient protocol to synthesize cDNA was applied. We primed cDNA synthesis on mRNA template with random oligonucleotides containing a constant 5' end. After complete synthesis of double-stranded cDNA, a second round of random priming was applied to generate oriented fragments of cDNA suitable for library construction. This protocol, in comparison with previous version, increases the presence of authentic protein domains in the library twofold, because of correct cDNA orientation. Moreover, some of the clones isolated from our previous libraries were results of chimerical fusion of two or more different genes, generated through double random priming on ds cDNA template. The new protocol has reduced this problem significantly. We also confirmed the advantage of N-terminal fusion for domain library construction in phage display vectors for screening with sera, because a significant amount of false positive cross-reactive clones, containing stop codons downstream of the fusion site giving rise to short mimotope sequences, were selected from the C-terminal fusion library (T6). Only 4 clones with specific tumor-related reactivity were isolated from the T6 library. However, C-terminal fusion might allow efficient display and selection for some antigenic C-terminal protein domains. In fact, the C-terminal fragment of fucosyltransferase (clone T6-7) was isolated from the T6 library. The panel of selected TAAs in Table 2 [see Additional file 1 ] contains several functionally defined gene products, previously unknown as tumor antigens. AKAP450 and Sos1 proteins, corresponding to clones T5-8 and T5-13, are intracellular components of the signal transduction pathway. Sos1 is a well-known guanine nucleotide exchange factor for Ras oncogene [ 21 ]. Transgenic mice expressing a dominant form of Sos in basal keratinocytes develop skin papillomas with 100% penetrance [ 22 ]. Moreover, a Sos1 mutant, lacking four functionally important proline-rich (SH3 binding) regions was reported to be responsible for gingival fibromatosis [ 23 ]. AKAP450 is a member of the A-kinase anchor proteins family. It is located in the centrosome [ 24 ], and acts as a microtubule nucleation site [ 25 ] and as a scaffold for proteins involved in mitotic process [ 26 ]. Other selected antigens with known or predicted intracellular location are alpha-6-fucosyltransferase (clone T6-7) and zinc finger protein 258 (ZNF258, clone T11-6). Alpha-fucosyltransferase catalyzes the transfer of GDP-fucose to oligosaccharide chains linked to proteins, lipids and sugars [ 27 ] and resides in the luminal compartment of trans-Golgi vesicles [ 28 ]. The predicted protein product ZNF258 contains zinc-binding motif repeats [ 29 ]. If ZNF258, together with structural homology, also shares biological properties with zinc finger proteins, thus recognizing and interacting with DNA, it should have a nuclear localization. The presence on our antigen list of proteins with predicted intracellular residence is in agreement with findings from the other groups [ 30 , 5 ] and is related to possible tissue necrosis and cell lysis associated with tumor growth. The human myc oncogene is transcribed from four alternative promoters giving rise to mRNAs for Myc1, Myc2, MYCHEX1 and 5'ORF [ 31 ]. Clone T5-18 is the result of the translation of an alternative frame to Myc1, Myc2 and does not correspond to any known protein product of myc oncogene transcription. It is not clear whether selection of this clone is an artifact of the experiment, or the result of an aberrant genome rearrangement in the tumor cells used for library construction. Among isolated antigens, there are 4 clones (T5-9, T9-21, T9-27 and T11-7) having between 55–91% sequence identity with that of a reverse transcriptase homolog (Figure 4 ). Viral antigens corresponding to human endogenous retrovirus were previously isolated from renal cancers and melanomas by SEREX [ 9 ]. It is interesting to note that all these clones, isolated with sera from breast cancer patients, derive from libraries constructed with cDNA from every different origin utilized: i.e. cell lines (T5), solid tumor (T9), testis (T11). We have no explanation for the transcription of reverse transcriptase gene in normal testis tissue. Eight proteins in the tumor antigen panel are unknown, or hypothetical proteins with unknown functions (T5-2, T5-15 , T5-19, T6-2, T6-6, T7-1 , T11-5 , T11-9 ). The four underlined gene products from the list in parenthesis were analyzed for mRNA expression in tumors and normal breast tissue. The mRNA expression levels were analyzed by PCR from SMART-cDNA template in 7–10 breast cancer specimens, one metastasized lymph node, normal breast, testis and peripheral lymphocytes from healthy donors. Two of these 4 unknown antigens and T11-3 were found to be frequently overexpressed in breast cancer. In particular clone T7-1, which was classified as encoding for an unknown protein since it has 100% identity only with KIAA1288 from EST database, was found to be overexpressed in breast carcinomas. This finding, together with the good reactivity of T7-1 protein with sera from tumor patients, identifies this antigen among the most promising targets for diagnosis of the disease. In contrast to the other antigens, which are overexpressed in breast cancer, mRNAs of T5-13, T5-15 and T11-5 appear to be underexpressed in 50–90% of breast cancer specimens, in comparison with normal breast tissue. How the immune system succeeds in responding to such antigens is still not clear. However, this finding is common to several SEREX-defined antigens, such as LU-12 [ 32 ], REN-9, REN-10 [ 33 ] and BR-41 [ 15 ], representing a group of TAAs deleted or downregulated in tumors. Lu-12, REN-9, Ren-10 map within cancer tumor suppressor gene locus at chromosome 3p21.3, a region often deleted in small cell lung cancer as well as in renal cancer. Downregulated antigen BR-41 was identified as SNT-1, a membrane-associated adaptor protein interacting with Sos1 [ 15 ]. In the present work we show that Sos1 (T5-13) is also downregulated in 50% of breast cancer samples. The downregulated antigens T11-5, T5-13 (Sos1), and T5-15 do not react with sera from patients B82-B96 analyzed for tumor mRNA expression. Furthermore, tumor biopsies from patients with good response for these antigens were not available for expression analysis. Thus, at present, it is not possible to determine whether T11-5, T5-13 (Sos1), and T5-15 are normally expressed, or downregulated, in patients showing an immune response for the corresponding antigen. Sequence comparison of T11-5 and T5-15 clones with the EST database revealed identity with the hypothetical proteins MGC4170 and KIAA1735. We have derived the aa sequence of the corresponding ORFs and predicted the whole sequence architecture by computer analysis using the SMART program [ 34 , 35 ]). MGC4170 encodes for two NL domains, while KIAA1335 encodes for a 389 aa protein bearing a DIX domain at the carboxy-terminus. The presence of such structural domains indicates that both of these still unknown proteins (corresponding to clones T11-5 and T5-15), which we found downregulated in several tumor specimens, may be involved in the signal transduction machinery. In spite of the fact that several promising antigens were identified from cDNA library constructed from testis mRNA, none of the antigens derived from testis or other libraries could be classified as specific testis/cancer (CT) antigen, because of their low expression in testis (T11-9, T7-1) or expression in other tissues as well. In this work we analyzed the frequency of the immune response to the 21 identified antigens by using a panel of sera from tumor patients and healthy donors. In general, we observed a low frequency of serum reactivity with the antigens, which was expected and is similar to that of the vast majority of SEREX-identified clones [ 36 ]. A significant number of sera from tumor patients, in comparison with healthy individuals, efficiently recognized five of the identified antigens (T6-2, T6-7, T7-1, T9-21, T9-27). Clones T9-21 and T9-27, isolated from breast carcinoma library, respectively show 70% homology (55% identity) and 62% homology (68% identity) to reverse transcriptase homolog (PO8547). T7-1 is a protein having an unknown function, which was found to be overexpressed in breast carcinoma. Taken together, these results lead us to believe that analysis of a complex panel of serologically-defined TAAs, with very large panels of sera from patients classified according to clinical parameters, i.e., age of patient, stage, extent and outcome of disease, etc. could lead to a much clearer understanding of the role, specificity and significance of the immune response versus disease in cancer patients. Conclusions We demonstrated that a lambda display-based approach permits the efficient identification of tumor antigens, potential immunological targets in breast cancer. The list of 21 antigens identified in this work contains eight proteins of still unknown function. Three of the genes (T7-1, T11-3, T11-9) were found to be overexpressed in tumors as compared to normal breast. Five of the selected antigens (T6-2, T6-7, T7-1, T9-21, T9-27) were recognized specifically by breast cancer patient sera. List of abbreviations aa, amino acids; Ag, antigen; EST, expressed sequence tags; ds cDNA, double-stranded cDNA; SEREX, serological identification of antigens by recombinant expression cloning; PAGE, polyacrylamide gel electrophoresis; PEG, polyethylene glycol; pfu, plaque-forming units; Sos1, son of sevenless homolog 1; TAA, tumor-associated antigen. Competing interests EP, PV, AP, GM, EB, FF and OM are salaried by an organization holding two patents relating to the content of the manuscript. Authors' contributions EP and PV contributed equally to the work. EP, PV and AP carried out cDNA library experiments, recombinant protein production, immunoassays and database search. GM and EB performed selection experiments. SB, MLD and MC contributed to immunological analysis of tumor antigens. ADPC and AL performed clinical studies. EC coordinated all medical aspects of the work. OM planned and performed molecular biology experiments, and teamed with FF in design and coordination of the entire project. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Supplementary Material Additional File 1 Table 2. List of identified TAAs. The File is given in Microsoft Word format. The table contains information about selected antigens. Click here for file

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539261

Differences in access to coronary care unit among patients with acute myocardial infarction in Rome: old, ill, and poor people hold the burden of inefficiency

Background Direct admission to Coronary Care Unit (CCU) on hospital arrival can be considered as a good proxy for adequate management in patients with acute myocardial infarction (AMI), as it has been associated with better prognosis. We analyzed a cohort of patients with AMI hospitalized in Rome (Italy) in 1997–2000 to assess the proportion directly admitted to CCU and to investigate the effect of patient characteristics such as gender, age, illness severity on admission, and socio-economic status (SES) on CCU admission practices. Methods Using discharge data, we analyzed a cohort of 9127 AMI patients. Illness severity on admission was determined using the Deyo's adaptation of the Charlson's comorbidity index, and each patient was assigned to one to four SES groups (level I referring to the highest SES) defined by a socioeconomic index, derived by the characteristics of the census tract of residence. The effect of gender, age, illness severity and SES, on risk of non-admission to CCU was investigated using a logistic regression model (OR, CI 95%). Results Only 53.9% of patients were directly admitted to CCU, and access to optimal care was more frequently offered to younger patients (OR = 0.35; 95%CI = 0.25–0.48 when comparing 85+ to >=50 years), those with less severe illness (OR = 0.48; 95%CI = 0.37–0.61 when comparing Charlson index 3+ to 0) and the socially advantaged (OR = 0.81; 95%CI = 0.66–0.99 when comparing low to high SES). Conclusion In Rome, Italy, standard optimal coronary care is underprovided. It seems to be granted preferentially to the better off, even after controversial clinical criteria, such as age and severity of illness, are taken into account.

Background The Italian National Health Service is supposed to provide universal coverage of standard care to all citizens, no social or economic selection bias should limit access to high technology resources as far as they are available. Direct admission to Coronary Care Unit (CCU) on hospital arrival can be considered as a good proxy for adequate management in patients with acute myocardial infarction (AMI) because it has been associated with better prognosis and shorter hospital stay [ 1 , 2 ]. Timely access to advanced diagnostic and therapeutic options, thorough cardiovascular monitoring, provision of primary angioplasty or thrombolytic therapy when indicated, and prompt defibrillation when necessary all contribute to favorable outcomes. With regard to reperfusion therapies, they have been shown to be effective in reducing short and mid-term mortality in patients with ST-segment elevation AMI [ 3 - 8 ]. The treatment is beneficial regardless of gender, and although relative mortality reduction is greater in younger than in older patients, absolute mortality reduction progressively increases in patients up to 75 years of age. After age 75, the benefits of treatment are less certain [ 9 - 11 ]. Intensive coronary care should be administered without delay, ideally within 60 minutes of the onset of symptoms [ 12 - 14 ]. Previous studies have investigated the role of demographic characteristics (such as age, gender and ethnicity), clinical characteristics (such as time from symptoms, presence of ST elevation and Killip class at presentation), and hospital characteristics (such as location, teaching status and level of invasive capability) on the probability of being admitted to CCU and the probability of receiving initial thrombolysis [ 11 , 15 - 18 ], but no information is available on factors affecting direct admission to CCU in Italy in an ordinary clinical setting. We analyzed a cohort of patients with AMI hospitalized in Rome (Italy) in 1997–2000 to assess the proportion directly admitted to CCU and to investigate the effect of patient characteristics such as gender, age, illness severity on admission, and socio-economic status on CCU admission practices. Methods Cohort selection criteria We used discharge abstract data, routinely collected by the regional Hospital Information System (HIS), to identify a cohort of patients with AMI (ICD-9 code of principal diagnosis at discharge = 410), aged 18 years of age or more, residing in Rome, admitted to one of the 11 city hospitals equipped with an emergency department and a CCU, and surviving the Emergency Room, from 1 July 1997 to 31 December 2000. From the above defined cohort, we then excluded: • patients who had been hospitalized for AMI in the previous six months, identified through record linkage within the HIS file, • patients transferred from other acute care facilities, • ruled-out AMI (those discharged alive or discharged against medical advice with a length of stay less than five days), • episodes of care with a diagnosis of trauma, with an important surgical operation, or with DRG non compatible with an AMI diagnosis. Exposure and outcome We categorized patients into five age-intervals: (less than 50, 50–64, 65–74, 75–84 and over 85 years). The Deyo's adaptation of the Charlson's comorbidity index [ 19 ] was calculated in order to describe illness severity on admission: based on ICD-9 codes we identified four severity groups (Charlson's adapted index 0, 1, 2, 3+). A socio-economic status (SES) index had been derived for each of the 5736 census tracts (CT) in Rome (average population = 480 inhabitants) using selected census variables including level of education, occupation, dwelling ownership, family size, and people/room density [ 20 ]. Based on CT of residence, AMI patients in the cohort were classified into four levels of SES (level I referring to the highest SES). For each patient, vital status 30 days after hospital admission was obtained through an automatic record linkage with the Municipal Registry of Rome. The main outcome measure was the indication of CCU as admission ward in the discharge abstract. For the purposes of this study we considered admission to Intensive Care Unit (ICU) in hospitals equipped with CCU equivalent to direct admission to CCU, because both represent an intensive care for AMI patients. Statistical analysis As a first step, a logistic regression analysis was performed in order to confirm the association between direct admission to CCU and 30 days mortality. after adjusting for patient characteristics (gender, age, SES, Charlson's index) and admitting hospital (ORs and 95% CI). Moreover, we compared the average length of stay among patients admitted to CCU and among those admitted to other wards, after excluding deceased and transferred patients, using the Student's t test. We then assessed the extent of differences among Rome hospitals with respect to the number of AMI patients admitted, the size of CCU, and the proportion of AMI patients directly admitted to CCU. For each hospital the ratio between AMI patients admitted and number of CCU beds was calculated as a proxy of the pressure on CCU resources. The effect of personal characteristics, i.e. gender, age, illness severity and socio-economic status, on risk of non-admission to CCU was then investigated using a logistic regression model. Since important differences among hospital rates of CCU admission had been found, and we wanted to take into account the possible effect of patients clustering by hospital, we used a random effect model with admitting hospital as clustering variable. The area under the receiver operator characteristics (ROC) curve was estimate as a measure of the overall predictive ability of each model, while the Hosmer and Lemenshow (H-L) statistics was used to assess models' calibration. The possible effect modification of gender on the other variables was tested by forcing interaction terms in the multivariate models. All statistical analyses were performed using STATA version 7.0 [ 21 ]. Results Of 9127 patients hospitalized with an incident AMI diagnosis (32% females, mean age 68.5 years, SD 12.6 years), 53.9% were directly admitted to CCU. The crude 30-day mortality was 13.2% in patients admitted to CCU and 25.0% in those admitted to other wards. The protective effect of CCU admission on 30-day mortality remained strong after adjusting for potential confounders (OR 0.53, I.C. 95% 0.47–0.60; area under the ROC = 0.729; H-L = 7.86, p = 0.448). Moreover, among 3765 AMI patients admitted to CCU or ICU, and discharged to home, the length of stay was significantly shorter than among those admitted to other wards (12.2 versus 14.4 days, p < 0.0001). The CCU admission proportion varied widely among hospitals (Table 1 ), from 27.7% in hospital a (a large, public, teaching hospital which admitted 962 AMI patients during the study period) to 87.5% in hospitals l (a medium sized, no-profit, catholic hospital which admitted 393 AMI patients during the study period). The ratio between AMI patients admitted and number of CCU beds varied from 37 to 166. This two indicators were not slightly correlated (r = 0.52). Patients characteristics with respect to CCU admission status are presented in table 2 . In the bivariate analysis it emerged that lower odds of being directly admitted to CCU were associated to female gender, older age, and higher Charlson's index, while we found no difference with respect to SES level (Table 3 , first three columns). In multiple logistic regression analysis (Table 3 , last two columns), when the potential confounding was adjusted for and the clustering by hospital was taken into account, the independent roles of gender (OR = 0.72; 95%CI = 0.64-0.84 when comparing females to males), age (a strong trend over the whole age range, with OR = 0.35; 95%CI = 0.25-0.48 when comparing 85+ to up to 50 yrs.) and illness severity (OR = 0.48; 95%CI = 0.37-0.61 when comparing Charlson index 3+ to 0) were confirmed, while low SES level emerged as an independent determinant of non-admission to CCU (OR = 0.79; 95%CI = 0.65-0.95 and OR = 0.81; 95%CI = 0.66-0.99 when comparing levels III and IV, respectively, to level I, area under the ROC = 0.704; H-L = 15.1, p = 0.06). No effect modification by gender was observed. Discussion Coronary care units have now been in use for 40 years, and it is generally acknowledged that they have helped to improve prognosis and reduce hospital stay among patients with acute myocardial infarction. This was confirmed in our AMI cohort where we observed a strong protective effect of CCU admission on 30 days mortality and a significantly shorter hospital stay for patient admitted to CCU. We observed that in most Rome hospitals the proportion of AMI patients directly admitted to CCU is lower than it should be according to international recommendations, [ 12 ] and lower than that observed in other developed countries [ 22 , 23 ]. Moreover, we found wide differences in rates of CCU admission among hospitals. It is beyond the scope of this paper to investigate which structural and organizational characteristics at the hospital level are associated to high proportion of non-admission to CCU, however admission rates do not increase in hospitals where the number of AMI patients is low in comparison to available CCU beds. While available data, and the results of a previous study [ 24 ] suggest a less than optimal use of CCU resources. In fact, we found that, among the 11243 patients who passed through the 112 CCU beds available in the 11 Rome hospitals in the year 2000, for an overall length of stay of 62622 days, only 40% had a diagnosis of AMI, while 46% had principal diagnosis of other acute cardiac disease and 14% had other diagnoses. In summary, variable, and incongruous admission and discharge policies as well as actual shortage of beds could have affected the CCU admission rate of AMI patients, whatever the reasons CCU is apparently a scarce resource in Lazio hospital which should be used unbiasedly. On the contrary, our results showed that age, severity of illness, and SES are important determinants of the probability that a patient with AMI who reaches qualified Rome hospital is directly admitted to CCU. Previous studies have documented restricted access to CCU and invasive procedures, and under use of well-established therapies such as aspirin, reperfusion and beta-blockers among elderly [ 25 ], female [ 17 ], and poorer AMI patients [ 26 ]. A recent systematic review suggests that patients who are perceived not to benefit from critical care are more often refused intensive care unit admission [ 27 ]. The age-related admission policy to CCU we observed has been documented previously [ 27 , 28 ], as well as the lower probability of being accepted in CCU for patients with higher severity [ 30 ]. The factors influencing admission decisions are likely to exclude large numbers of patients who could benefit from advanced diagnostic and therapeutic options [ 31 ]. We used discharge abstract data, coded according to the International Classification of Diseases IX revision, so it was impossible for us to distinguish between ST-segment elevation and non ST-segment elevation MI. Even though ST-elevation may (and should) influence the physician referral decision, we think that, if the percentages of non-ST segment MI in the groups under study are the same, our results should not strongly be biased. We used a small area-based SES index, because direct individual data on social class were not available. This index has been shown to be a strong predictor of differences in mortality, [ 20 ] and associated to inequalities in access to important health interventions [ 32 , 33 ] and medical management [ 34 ] in Rome. Small-area data have been widely used to impute individual socio-economic status, and despite some criticism [ 35 ] inferences based on this method appear to be valid [ 36 , 37 ]. Age and admitting hospitals were the variables responsible for a negative confounding effect on the association of socio-economic status with direct CCU admission. Patients with low SES levels are younger than patients with high SES levels and tend to be admitted to hospital with higher provision of CCU care. Conclusions In Rome, where high-technology resources are available, they do not seem to be efficiently and fairly used. Our results suggest that access to optimal care is offered selectively to the socially advantaged, as well as to younger patients (even well under the 75 years threshold) and to those with less severe illness. The National Health Service, its policy of unrestricted access notwithstanding, falls short of providing equal opportunities to all citizens. Delivery of effective services to the underprivileged should be actively promoted. Competing interests The author(s) declare that they have no competing interests. Authors' contributions CA conceived of the study, participated in its design, planned the statistical analysis, drafted the manuscript MA participated in the study design and coordination, drafted the manuscript CS participated in the study design, drafted the manuscript NA participated in the study design DF performed the statistical analysis VT assisted in data management CAP conceived of the study Pre-publication history The pre-publication history for this paper can be accessed here:

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545802

Model-independent fluxome profiling from 2H and 13C experiments for metabolic variant discrimination

A novel method for intracellular fluxome profiling that does not require a priori knowledge of the metabolic system allowed the identification of characteristic flux fingerprints in 10 Bacillus mutants from 132 2 H and 13 C tracers experiments.

Background Genome-wide analyses of cellular mRNA, protein or metabolite complements have become workhorses in biological research that produce unprecedented amounts of data on cellular network composition. In contrast to such compositional information, molecular fluxes through intact metabolic networks link genes and proteins to higher-level functions that result from biochemical and regulatory interactions between the components [ 1 ]. As such, quantitative knowledge of in vivo molecular fluxes is highly relevant to functional genomics, metabolic engineering and systems biology [ 2 , 3 ]. Intracellular fluxes, or in vivo reaction rates, can be assessed by methods of metabolic flux analysis that are based on stable isotopic tracer experiments [ 4 , 5 ], which have successfully unraveled novel biochemical pathways [ 6 , 7 ] and gene functions [ 8 , 9 ]. The presently tedious and limited methodologies, however, hamper broader application to a large range of environmental conditions, isotopic tracers and higher biological systems [ 4 ]. We set out to overcome a principal bottleneck in metabolism-wide flux (fluxome [ 10 ]) analysis: the requirement for mathematical frameworks to interpret the isotopic tracer data from nuclear magnetic resonance (NMR) or mass spectrometric (MS) analyses within a detailed metabolic model [ 4 , 5 ]. Constructing such models requires a priori knowledge on possible distributions of the tracer used within the network, and, more importantly, extensive labeling and physiological data to resolve all fluxes within a given model. The lack of such structural knowledge on metabolic pathways and the technical difficulty of acquiring sufficient data hamper studies of metabolism, in particular in higher cells with complex nutrient requirements and for exotic tracer molecules. Hence, fluxome analysis is largely restricted to few 13 C-labeled carbon sources in microbes or plants cultivated in minimal medium [ 7 , 11 - 16 ]. Here we discriminate mutants/conditions and assess their metabolic impact directly from 'raw' mass-isotope data by unsupervised multivariate statistics without a priori knowledge of the biochemical reaction network. To illustrate the applicability of this conceptually novel profiling method, we focused on the reactions of central metabolism in the model bacterium Bacillus subtilis , for which detailed flux data were available to validate the results [ 9 , 11 , 14 ]. Results 2 H and 13 C tracer experiments Environmental and genetic modifications were used to perturb intracellular metabolic activities in B. subtilis . In particular, we chose 10 knockout mutants [ 17 ] that were affected in metabolic genes or transcriptional regulators linked to central metabolism (Table 1 and Figure 1 ). These mutants were grown in 1-ml batch cultures [ 18 ] with six combinations of the carbon sources [U- 13 C] or [U- 2 H]glucose, [U- 13 C]sorbitol or [3- 13 C]pyruvate and the nitrogen sources ammonium or casein amino acids (CAA). As a proof of concept, we detected the isotopic labeling patterns in proteinogenic amino acids by gas chromatography MS (GC-MS), which provides direct access to several metabolic nodes in the network [ 6 , 7 , 19 ] (Figure 1 ). The raw mass isotope data of all mutants under each of the six experimental conditions are given in Additional data file 2. In media supplemented with amino acids, cell protein was only partly synthesized from the isotopically labeled substrate. In such cases, current flux-analysis methods such as isotopomer balancing or flux ratio analysis are not applicable [ 4 , 5 ] because they do not account for variations in the labeling patterns due to amino-acid uptake and catabolism. Practically, we tackled here a worst-case scenario: growth in a medium enriched with unlabeled amino acids and profiling of the labeling pattern from tracers in the proteinogenic amino acids, which may potentially originate entirely from the medium. Nevertheless, a sufficiently high fraction of all analyzed amino acids was synthesized de novo from the labeled substrates to obtain relevant MS signals, indicating that information on pathway activities was recorded in the labeling patterns (Figure 2 ). To capture the impact of genetic or environmental modifications, we analyzed the 260-330 raw mass isotope data points for each mutant and condition. This is essentially a table of mass-distribution vectors for all detected amino-acid fragments upon correction for naturally occurring stable isotopes, that is, the list of the relative frequencies of all possible isotope isomers for each detected analyte. Identification of metabolic determinants for altered flux profiles For the visualization of metabolic effects, the corrected MS signals of the wild type were subtracted from those of the mutants (Figures 3 and 4 ). Some mutations, such as pps , were silent under the conditions tested and exhibited only noise in the wild-type-normalized data. In other mutants, characteristic profiles of strongly affected amino acids were readily apparent. One example was the almost identical signature of serine (S) fragments in the profiles of the glcP and cggR mutants during growth on sorbitol with CAA; that is, high fractions of masses m 0 and m 3 and low fractions of m 1 and m 2 (where the subscripts denote the number of 13 C atoms in each amino-acid fragment). While the S signature of the mdh mutant on sorbitol with CAA was also distinct, it was different from that in the above two mutants with low m 1, m 2, and m 3 fractions (Figure 3 ). These characteristic labeling profiles are biochemically very informative and may be linked to precise metabolic causes. For the above examples, the high fraction of uncleaved serine molecules with intact C 3 backbones (that is, m 0 and m 3 ) in glcP and cggR is evidence of a lower exchange with the glycine pool, when compared with the wild type [ 19 , 20 ]. In the mdh mutant, the high fraction of uncleaved but unlabeled S ( m 0 ) reveals high incorporation of unlabeled serine from the CAA supplement, and thus low de novo biosynthesis from 13 C-labeled sorbitol. As well as consistency with the data in the literature, the analysis also revealed new information on pathway activity and regulation that was not previously accessible. One example is the pronounced signatures of the sdhC mutant on glucose and sorbitol. Because the sdhC mutation disrupts the tricarboxylic acid (TCA) cycle, the wild-type flux through the cycle must be similar on these substrates, both with and without CAA (Figure 3 ). The sdhC signatures of the TCA cycle-derived amino acids aspartate (D) and glutamate (E) were also present in the CAA profiles of the other TCA cycle mutant mdh . Their absence on ammonium indicates activity of the malic enzyme-based pyruvate bypass [ 11 ] in the mdh mutant. While such a level of detailed biochemical insight is possible, it requires considerable expertise and time to retrieve. Alternatively, metabolic impacts in new mutants can be identified by comparison of the mass fingerprints in mutants with known metabolic lesions. During growth on sorbitol and pyruvate in minimal media but not with CAA, the CggR repressor of the glycolytic gapA operon, for example, appears to affect TCA cycle fluxes because the mutant profile matches those of the TCA cycle mutants sdhC and mdh (Figure 3 ). In contrast to glucose, sorbitol does not elicit catabolite repression; hence, comparison of sorbitol and glucose profiles can identify repression-dependent effects. Examples are the signatures of the oxaloacetate-derived amino acids isoleucine (I), threonine (T) and aspartate in the cggR profile that reveal, by the similarity to the sdhC and mdh mutants, a TCA cycle flux-promoting effect of CggR on sorbitol but not on glucose. This is consistent with the repression of cggR on glucose [ 21 ], and the TCA cycle effect is probably indirect, through the repression of glycolytic genes [ 22 ]. A significant extension beyond the canonical 13 C-tracer methods is the applicability to any isotope, which broadens the observable metabolic processes. Here we used fully deuterated [U- 2 H]glucose that allows us to monitor dehydrogenase activities and water release. The 2 H-label was present exclusively in the variable side chains, because the α-carbon hydrogen was lost in the transaminase reaction. Thus, glycine contains no label and the acidic aspartate and glutamate lose the label proximal to the carboxyl group as a result of exchange with water at the low pH during hydrolysis. The remaining amino acids provided a stable and informative 2 H-pattern (see Additional data file 1). An illustrative example is the cggR mutant signatures for the pyruvate-derived amino acids valine (V), leucine (L) and, partially, alanine (A) (Figure 3 ) In all three cases, reduced m 2 and increased m 0 fractions revealed a double loss of 2 H-label in their common precursor pyruvate at position C-3. This loss of 2 H indicates increased exchange of 2 H with water at the C-3 position of pyruvate (or any upstream triose), which is fully consistent with increased transcription of the glycolytic enolase in the cggR mutant on glucose [ 23 ] that could catalyze this exchange. As the enolase activity does not affect the carbon backbone, the corresponding patterns cannot be identified in 13 C experiments Independent component analysis (ICA) For large-scale profiling studies, automated mutant classification based on metabolic function without user supervision would be desirable. Initially, we used principal component analysis (PCA), which is often used for graphical representation of multidimensional variables from profiling experiments [ 24 , 25 ], as was recently described for pretreated (summed fractional labels) mass isotope data [ 26 ]. From the raw mass isotope data, the first two PCs discriminated, under most conditions, mutants with extreme labeling patterns (see Additional data file 1). The differences become smaller with increasing PCs, and only the initial three to four PCs allowed reliable discrimination. In the present data, PCA tended to discriminate extreme singular labeling patterns in few fragments or, more frequently, combinations of altered patterns in the fragments of many amino acids, as was expected from the variance maximization of PCA. Unfortunately, the resulting complex PCs are difficult to interpret metabolically, and thus are of limited biochemical relevance. Consequently we used independent component analysis (ICA) for unsupervised, automatic recognition of conserved labeling patterns that are biochemically relevant. The underlying assumption is that these patterns result from the superposition of independent metabolic activities. Each activity causes a specific shift in the mass distributions of one or more intermediates. ICA seeks to separate the observed variables into non-gaussian components that are statistically as independent as possible [ 27 ]. Generally, ICA clearly discriminated mutants and conditions from the corrected (non-normalized) MS data (see Additional data file 1). While the weights in PCs were more broadly distributed among the input variables, ICs were dominated by fewer, sharper peaks (Figure 4 ). For the particular example of the [U- 13 C]sorbitol with ammonium experiment, we explored the ICA results in more detail (Figure 5 ). The first, striking, observation was that the second IC contains the biochemically redundant signals of m 2 T, m 2 D, and m 1 and m 3 E (highlighted in red in Figure 5a ) that arise from acetyl-CoA units in the TCA cycle [ 19 ]. This shows that ICA automatically provides insights into the biosynthetic linkage between amino acids with a resolution that eclipses visual comparison of the normalized signatures. For amino acids, this information was of course previously available, but statistical identification of biochemical relations could potentially also be obtained for less well-characterized compounds. Second, ICA often clustered biosynthetically related signals in the same component (Figure 5 ): IC7 grouped the similar signatures of phenylalanine (F) and tyrosine (Y) together; IC1 reports labeling shifts in glycine (G) and partially serine; and IC4 concentrated high weights in signals of the pyruvate derivatives alanine, valine and leucine (highlighted in blue in Figure 5 ). While isoleucine is also synthesized from pyruvate, it had only a marginal weight in IC4 because of interference from its second precursor oxaloacetate. Third, specific signatures of proline (P), leucine and serine are clearly recognized in IC3, IC8 (highlighted in green in Figure 5a ), and IC10, respectively. These signatures reflect those previously identified in the normalized profiles (Figures 3 and 5c ). Among the remaining components, IC5 and IC6 emphasize outliers in the cggR and ytsJ MS data, respectively, whereas the noisy IC9 profile indicates that the identified ICs in our small dataset approach a limit. Akin to PCA, ICA allowed us to discriminate mutants from the corrected MS data (Figure 5b and Additional data file 1). On sorbitol, mutants such as pgi , yqjI , pps, glcP and glcR were mostly silent, and typically projected in proximity to the parent strain. In contrast to PCA, ICs classified the mutants on the basis of specific metabolic effects. In some cases (IC2 or IC4 in Figure 5b ), the IC defined well-separated clusters of mutants, usually two groups, reflecting a binary (on-off) effect. In the majority of the components, however, the even distribution between the extremes reveals progressive metabolic responses (for example, IC3, IC7 or IC10). Overall, the ICs correlated favorably with the signatures of wild-type-normalized profiles (Figure 5 and Additional data file 1). Thus, ICA clearly outperformed PCA by its capacity for unsupervised recognition of metabolic responses and its ability to correlate biochemically redundant information in the data. Comparison of PCA and ICA with analytically determined flux ratios For most experimental conditions tested, mathematical frameworks for numerical flux analysis such as isotopomer balancing or flux-ratio analysis [ 4 , 5 ] were not available. Only the [U- 13 C]glucose minimal medium experiments allowed a direct comparison of fluxome profiles with flux ratios. Therefore, we examined whether any of the statistically identified PCs and ICs was linearly correlated with eight analytically determined flux ratios [ 9 , 19 ] that were obtained from the same MS data (Figure 6 ). For PCs, the correlation coefficients decreased with increasing component number, and singular correlations could not be detected between individual PC-flux ratio pairs. Generally, the ICs were much better correlated with the flux ratios, for particular pairs with coefficients close to 0.90. This indicates that the identified ICs define signatures in the mass distribution of the analytes that bear high metabolic relevance, similarly to analytically derived flux ratios. Notably, IC6 was almost perfectly correlated with the flux ratio of oxaloacetate derived through the TCA cycle (Figure 6 ). This IC contained high weights in TCA-cycle-derived amino acids signals that are linked to the incorporation of C 2 units from acetyl-CoA (Figure 4 ). As shown above, the projection of a data point on the axis defined by a component reflects the presence of the fluxome signature in its labeling patterns, and hence directly quantifies the occurrence of a particular metabolic activity. When plotting the projection versus the numerical values, the IC6-derived data exhibited a highly linear correlation, while the correlation coefficient was almost halved for PC3, the closest relative to IC6 (Figure 7 ). This confirms numerically the enhanced capacity of ICA to capture essential and independent information for a complex metabolic trait such as the TCA cycle activity. The extraordinarily high correlation coefficient of 0.99 demonstrates that IC6 represents very closely the analytically deduced TCA-cycle flux ratio. This is surprising because IC6 was statistically identified from 265 masses, whereas the flux ratio was calculated on the basis of a large body of biochemical background information [ 19 , 20 ]. Discussion For the example of central and amino-acid metabolism in B. subtilis , we show that fluxome profiling by multivariate statistics from mass isotopomer distribution analysis is meaningful for the discrimination of mutants or conditions on the basis of their metabolic behavior, and applicable to conditions that are inaccessible to previous flux analysis. In sharp contrast to metabolome concentration data [ 24 , 25 ], fluxome profiles contain functional information on the operation of fully assembled networks [ 1 , 4 ]. As shown here by ICA, this approach enables us to distill the essential signatures of independent metabolic activities, and supports the identification of the underlying biochemical causality. Because no model or a priori knowledge on the investigated system is required, the metabolic imprints of any tracer atom and molecule can be followed in virtually any biological system, including multicellular organisms in complex multisubstrate media. Similarly, a priori knowledge of the number of ICs to be computed is not a prerequisite. As a matter of fact, the optimal number depends primarily on the labeling patterns and can hardly be estimated from the dataset dimensions. An underestimate will generally leave some relevant signatures unrecognized, whereas an overestimate will lead to an increased fraction of components reflecting measurement or biological noise. Although statistical significance can be assessed with duplicates, this becomes prohibitive with large datasets (that is, hundreds of mutants or analytes) or reduced availability of replicas. The bottleneck resides in the stochastic approach of most ICA algorithms, for which independent runs result in different ICs or ordering thereof. Instead, algorithmic and statistical reliability of the ICs can be evaluated by repeating the estimation several times either with randomly chosen initial guesses or by slightly varying the dataset (bootstrapping [ 28 ]), respectively, and then clustering all results to identify robust ICs [ 29 ]. Two factors directly affect the results that can be obtained by comparative fluxome profiling: the detected analytes and the choice of isotopic tracer. As well as polymer-based analytes such as the proteinogenic amino acids monitored here, fluxome profiles can be detected in any set of intra- or extracellular metabolites, thereby widening the observable metabolic processes The choice of tracer depends, to some extent, on the metabolic subsystem of interest. Uniformly labeled substrates provide a more global perspective because they allow assessment of the scrambling of any carbon backbone and, in the case of experiments performed in rich media, also allow quantification of the fraction of de novo biosynthesis from the tracer relative to the uptake of a medium component. Similarly, uniformly deuterated substrates or 2 H 2 O are valuable for simultaneously capturing a wide number of ICs that are affected by the release, binding and exchange of water or protons. Substrates that are labeled at specific positions, in contrast, enable deeper interrogation of particular sub-networks, for example, [1- 13 C]hexoses for the initial catabolic reactions [ 8 , 19 ] or [1- 13 C]aspartate to assess urea cycle activity. The results also revealed new biological information on pathway activity, function or regulation. First, both glycolysis and the pentose phosphate pathway actively catabolized glucose in the presence of CAA, because the pgi and yqjI mutant signatures were different from the wild type and from each other. On sorbitol, in contrast, the same mutants were very similar to the wild type, suggesting that both reactions are only marginally involved in catabolism of this sugar. Second, the Krebs cycle flux was similar on glucose and sorbitol (with and without CAA), as deduced from the similarly pronounced signatures of the sdhC mutant. Third, absence of the sdhC signatures in the Krebs cycle-derived amino acids aspartate and glutamate of the mdh mutant when grown with ammonium (but not CAA) indicates activity of the malic enzyme-based pyruvate bypass [ 30 ]. Fourth, activity of the NADP-dependent malic enzyme appears to be independent of catabolite repression because pronounced signatures of the ytsJ mutant were seen on all substrates. The gluconeogenic phosphoenolpyruvate synthetase Pps, in contrast, was inactive in the presence of the repressing glucose but active on pyruvate or sorbitol. Fifth, as discussed above the data reveal a Krebs cycle-promoting effect of the repressor CggR on sorbitol but not on glucose, most likely through the repression of glycolytic genes [ 22 ]. The comparative fluxome profiling presented here complements traditional flux analysis because it enables potentially rapid and automated identification of relevant mutants or conditions from large-scale datasets, for example from entire mutant libraries. The approach is quantitative in terms of the relative difference between variants, but qualitative with respect to the in vivo flux. Interesting variants are then subjected to deeper interrogation of the specific metabolic phenomenon identified. Besides mere data mining, fluxome profiling also has the potential to identify complex functional traits in higher cells where current flux methods fail, and possibly even identify the underlying biochemical mechanism of discriminant mass isotope signatures. Materials and methods Strains and growth conditions Wild-type B. subtilis 168 ( trpC2 ) [ 31 ] and knockout mutants containing an antibiotic marker in single genes [ 17 ] were grown in M9 minimal medium [ 9 ] at pH 7.0 with 50 mg tryptophan. Six different combinations of 2 H- or 13 C-labeled isotopic tracers (3 g/l) and nitrogen sources were used: (i + ii) uniformly 13 C-labeled [U- 13 C]glucose with either 0.5 g/l CAA (Sigma) or 1 g/l NH 4 Cl; (iii + iv) [U- 13 C]sorbitol with either 0.5 g/l CAA or 1 g/l NH 4 Cl; (v) [U- 2 H]glucose ([1,2,3,4,5,6,6- 2 H]glucose) with 1 g/l NH 4 Cl; and (vi) [3- 13 C]pyruvate with 1 g/l NH 4 Cl and twofold higher concentrations of phosphate to ensure pH buffering. [U- 13 C]glucose (Martek Biosciences), [U- 13 C]sorbitol (Omicron Biochemicals), and [1,2,3,4,5,6,6- 2 H]glucose (Euriso-Top) were supplemented as 50:50 mixtures of labeled and unlabeled isotopomers. Pyruvate was supplied entirely as the [3- 13 C] isotopomer (Euriso-Top). Aerobic batch cultures were grown in silicone-covered, deep-well microtiter plates at 37°C and 300 rpm in a 5-cm orbital shaker [ 18 ]. Frozen stocks were used to inoculate 1 ml LB medium with selective antibiotics. After 10 h of incubation, 10 μl were used to inoculate 1 ml M9 medium with 5 g/l glucose and selective antibiotics, incubated for 12 h, and 10 μl of these precultures were used to inoculate 1.2 ml of M9 medium with isotopic tracers. Cultures were harvested upon entry into stationary phase (assessed by visual evaluation). Because the length of batch growth varied, cultures with CAA, with NH 4 Cl, and with pyruvate were harvested after 10, 14 and 24 h, respectively. Labeling patterns in the analyzed proteinogenic amino acids are rather stable [ 10 , 19 ]; hence differences of a few hours in growth phase at harvest were irrelevant. This was also confirmed in separate (data not shown) and duplicate experiments for each combination of strain and medium that was independently started from culture stocks. GC-MS analysis and data preprocessing Cell harvest, protein hydrolysis and GC-MS analysis of amino acids were done exactly as described before [ 19 , 32 ]. Amino-acid mass distributions were derived from the spectra after correction for the natural abundance of stable isotopes [ 19 ]. Since amino acids are fragmented during electron impact ionization in the MS, we obtained three to five fragments with partially redundant information for each amino acid. For each fragment, a normalized vector m 0 , m 1 , ..., m n , expresses the fraction of molecules that are labeled at 0,1, ..., n positions, depending on the total number n of carbon or hydrogen atoms present. Considering all corrected fragment vectors obtained per sample, a complete dataset typically consisted of about 260 and 330 single mass values from 13 C and 2 H experiments, respectively, depending on the quality of the MS measurement. Multivariate data analysis To obtain a new representation of the multivariate MS data and to make their essential structure accessible, we applied PCA to the corrected fragment vectors. This approach projects the input variables in an orthogonal space that is spanned by the PCs. Among the infinite number of possibilities, each successive PC is selected to maximize the variance of the projected data and to be orthonormal to the previous ones [ 33 ]. Consequently, PCA concentrates the maximum and nonredundant information of the entire dataset in the minimal number of dimensions, and thus is best suited for data compression [ 27 ]. The computation was performed with Matlab (The Mathworks) using the princomp function of the Statistics toolbox 4.0. No input vectors were eliminated from the dataset to filter outliers in PCA, because this operation affected only PCs with higher order but only marginally PC1 and PC2. To reveal hidden information in the labeling patterns, the corrected MS vectors were subjected to ICA [ 27 ], which is frequently used in the neurosciences [ 34 , 35 ] and in gene-expression studies [ 36 , 37 ]. For ICA, we assume that independent metabolic processes such as reactions or pathways produce characteristic fingerprints in the labeling pattern. These metabolic fingerprints are defined by m fundamental components S = ( s 1 , ..., s m ) T , each of which is represented by a vector of p MS-signals. We assumed that the experimental data X = ( x 1 , ..., x n ) T , with n vectors of p corrected MS signals for each mutant/condition, result from a linear combination of the m fundamental processes, given by x i = a i 1 s 1 +...+ a i m s m . In matrix notation, this leads to X p × n = A p × m S m × n , with A as the mixing or loading matrix. ICA seeks to estimate the unknown terms A and S from the observed values X but has different objectives from PCA. Briefly, ICA identifies statistically ICs by selecting those with maximum non-gaussianity [ 27 ]. Hence, ICs are nonlinearly decorrelated and assumed to have non-gaussian distributions. Because of the central limit theorem, which states that the sum of non-gaussian random variables is closer to gaussianity than the original ones, ICs are identified by selecting the linear combinations of the observed variables that have maximum non-gaussianity [ 27 ]. In particular, we used the publicly available FastICA 2.1 algorithm [ 38 ] to estimate the number of components that were equal to the number of strains in the dataset, excluding duplicates. The data dimension was not reduced (by PCA) before IC computation. Additional data files The following additional data is available with the online version of this paper. Additional data file 1 contains three figures (Additional Figure 1 shows the mass distribution in the 2 H experiment; Additional Figure 2 shows mutant discrimination by PCA (less relevant than by ICA); Additional Figure 3 is a complete representation of the 660 ICs (10 ICs in 6 experiments for 11 strains). All the raw data is contained in six Excel tables in Additional data file 2 . Supplementary Material Additional data file 1 Three additional figures (Additional Figure 1 shows the mass distribution in the 2 H experiment; Additional Figure 2 shows mutant discrimination by PCA (less relevant than by ICA); Additional Figure 3 is a complete representation of the 660 ICs (10 ICs in 6 experiments for 11 strains) Click here for additional data file Additional data file 2 All the raw data contained in six Excel tables Click here for additional data file

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548671

The loss of NKX3.1 expression in testicular – and prostate – cancers is not caused by promoter hypermethylation

Background Recent studies have demonstrated that the NKX3.1 protein is commonly down-regulated in testicular germ cell tumors (TGCTs) and prostate carcinomas. The homeobox gene NKX3.1 maps to chromosome band 8p21, which is a region frequently lost in prostate cancer, but not in TGCT. Mutations have not been reported in the NKX3.1 sequence, and the gene is hypothesized to be epigenetically inactivated. In the present study we examined the methylation status of the NKX3.1 promoter in relevant primary tumors and cell lines: primary TGCTs (n = 55), intratubular germ cell neoplasias (n = 7), germ cell tumor cell lines (n = 3), primary prostate adenocarcinomas (n = 20), and prostate cancer cell lines (n = 3) by methylation-specific PCR and bisulphite sequencing. Results and Conclusions Down-regulation of NKX3.1 expression was generally not caused by promoter hypermethylation, which was only found in one TGCT. However, other epigenetic mechanisms, such as modulation of chromatin structure or modifications of histones, may explain the lack of NKX3.1 expression, which is seen in most TGCTs and prostate cancer specimens.

Background The protein expression of the homeobox gene NK3 transcription factor related locus 1 (NKX3.1) is highly specific for the prostate and the testis [ 1 - 3 ], and is frequently lost in cancers of these two tissue types [ 1 , 4 , 5 ]. NKX3.1 is located in chromosome band 8p21 [ 2 , 6 , 7 ], a region that undergoes frequent allelic imbalance in prostatic intraepithelial neoplasia (PIN) and prostate carcinomas [ 8 , 9 ]. In mice, targeted disruption of Nkx3.1 leads to prostatic epithelial hyperplasia and dysplasia [ 10 , 11 ], and over-expression of exogenous NKX3.1 suppresses growth and tumorigenicity in human prostate carcinoma cell lines [ 12 ]. However, the expression levels and possible role for NKX3.1 during prostate cancer progression in humans is still being debated [ 13 - 15 ]. No gene mutations of NKX3.1 have been found [ 6 ], and NXK3.1 is therefore believed to be epigenetically inactivated in the cases with loss of protein expression [ 1 , 5 , 16 ]. Only one study has reported NKX3.1 protein expression in testicular germ cell tumors (TGCTs), however the series analyzed was large, including a total of more than 500 samples, and NKX3.1 was found absent in all embryonal carcinomas and present in only 15–20% of the seminomas as well as among the differentiated histological subtypes of germ cell tumors [ 5 ]. During the last decade, epigenetic changes in cancer have been frequently reported and are now recognized to be at least as common as genetic changes [ 17 ]. The best characterized epigenetic mechanism is DNA hypermethylation, in which cytosines located within selected CpG sites in the gene promoters become methylated, thereby inactivating gene expression. Several tumor suppressor genes are inactivated by such promoter hypermethylation in various cancer types [ 18 , 19 ]. In the present study we have performed methylation-specific PCR (MSP) and bisulphite sequencing of the NKX3.1 promoter in TGCTs and prostate adenocarcinomas to examine whether this mechanism may explain the commonly observed loss of NKX3.1 protein. Results Only one out of 54 TGCTs and none of the prostate adenocarcinomas (n = 20), intratubular germ cell neoplasias (n = 7), normal testis tissues (n = 4), or the cell lines (n = 6) displayed methylation when analyzed with MSP (Figure 1a ). Bisulphite genomic sequencing of the tumors and cell lines showed that all cytosines at non-CpG sites were converted to thymine (Figure 1b ). Only one sample demonstrated overall methylation in the NKX3.1 sequence, and this was the same sample that was positive for methylation from the MSP analysis. Interestingly, all the samples that were sequenced, including the normal blood, unmethylated cell lines, and primary tumors, displayed some extent of methylation (the majority below 25%) at the cytosine in CpG number 21 (base 1914762, +1 bp from transcription start). We detected a possible polymorphism in base 1914730 (+33 bp from transcription start and 15 bp upstream of the coding sequence). In previous sequences this site has been described as a guanine (Gene bank accession number NT_023666, and AF24770). In the cell lines, 5/6 contained adenosine in this position, but all except the germ cell tumor cell lines NCCIT and TERA2 were heterozygotes. In contrast, all 5 primary tumors sequenced were homozygous for the adenosine allele. Figure 1 Representative results of the methylation analyses of the NKX3.1 promoter. (A) Methylation-specific PCR. A visible PCR product in Lanes U indicates the presence of unmethylated alleles whereas a PCR product in Lanes M indicates the presence of methylated alleles. The left panel illustrates the methylation status of selected TGCTs and the testicular cancer cell lines. Note the methylation of sample # 2110. The right panel shows the unmethylated status of primary prostate cancers and prostate cancer cell lines. Abbreviations: NB , normal blood (positive control for unmethylated samples); IVD , in vitro methylated DNA (positive control for methylated samples); neg , negative control (containing water as template); U , lane for unmethylated MSP product; M , lane for methylated MSP product. (B) Bisulphite sequencing. The bisulphite sequence allows a positive display of 5-methyl cytosines in the gene promoter as unmethylated cytosines appear as thymines, while 5-methylcytosines appear as cytosines in the final sequence. The left chromatogram represents a part of the unmethylated NKX3.1 promoter in the germ cell tumor cell line TERA2, including 11 CpG sites marked by underlined letters. The right chromatogram represents the unmethylated prostate cancer cell line DU145. Both sequences have been generated by reversing the respective anti-sense sequences by use of the software "Chromas". Discussion We have previously reported that the protein expression of NKX3.1 is virtually ubiquitously lost in TGCTs [ 5 ]. This was done using a tissue microarray containing 510 testicular tissue samples. NKX3.1 expression is known for 25 of the TGCTs now analyzed for promoter hypermethylation and 22 showed complete absence of protein. The down regulation of NKX3.1 in TGCT has also been detected at the mRNA level, both by quantitative RT-PCR [ 5 ] and from an oligonucleotide microarray study including 20 of the present TGCTs (Skotheim et al ., submitted). This simultaneous down regulation of both protein and mRNA levels of NKX3.1 is consistent with epigenetic regulation, which is further supported by the fact that mutations have not been detected in the NKX3.1 gene [ 6 ]. DNA promoter hypermethylation is the best-characterized epigenetic change in cancer, and can be associated with gene silencing. It was therefore of interest to analyze the methylation status of the NKX3.1 promoter in TGCT and prostate cancer samples. However, with the exception of a single TGCT, the NKX3.1 promoter was unmethylated in the samples analyzed. The methylated TGCT was classified as a yolk sac tumor, and has also been demonstrated to have promoter hypermethylation of several other genes that are generally unmethylated in TGCTs (Lind et al ., unpublished). We therefore consider this sample not to be representative for the general TGCT epigenotype, nor for the general epigenetic profile of yolk sac tumors. Thus, we do not regard promoter hypermethylation as the general mechanism of NKX3.1 down-regulation neither in TGCT nor in prostate carcinomas. We also studied cell lines since it can be argued that presence of normal cells as well as tumor heterogeneity may mask cancer specific methylation in primary tumors. LNCaP cells have previously been demonstrated to express NKX3.1 , in contrast to PC-3 and DU-145, which do not express NKX3.1 since they lack a functional androgen receptor [ 2 ]. The lack of NKX3.1 expression in PC-3 and DU-145 cells is not due to methylation. This was also the case with the germ cell tumor cell lines. From Western analysis, the cell line NCCIT had strong expression of NKX3.1 whereas both TERA1 and TERA2 had no expression (data not shown). The polymorphism in NKX3.1 that we detected 15 bases upstream of the coding sequence has to our knowledge not been described previously. It was identified by bisulphite sequencing of the cell lines and a subgroup of primary tumors, thus caution should be taken when concluding from these results, since regular sequencing analysis is the recommended approach for describing sequence changes. As the polymorphism is located in the promoter region of NKX3.1 , it has no influence on the protein structure. However, it can still have a potential role in the transcriptional regulation of NKX3.1 . A polymorphism in the coding sequence is also reported for NKX3.1 [ 6 ]. All samples analyzed with bisulphite sequencing, including cell lines expressing NKX3.1, as well as non-expressing cell lines, demonstrated some degree of methylation in the cytosine in CpG number 21. As this site-specific methylation included only one CpG site, it is unlikely that it will have any regulating effect on gene expression. However, considering its intriguing location immediate upstream of the transcription start point, this possibility should not be excluded. There is also the possibility that the apparent methylation could be due to a less efficient bisulphite conversion for this site. In general, the bisulphite sequencing results showed that all cytosines at non-CpG sites were converted to thymine (Figure 1b ), but sequence-specific partial resistance to this conversion may lead to methylation artifacts, but only in rare cases, as has been reported previously [ 20 ]. Conclusions In summary, these data show that the previously reported down-regulation of NKX3.1 in TGCTs and prostate carcinomas is not caused by promoter hypermethylation. Even though the NKX3.1 promoter is unmethylated, the simultaneous down-regulation of mRNA and protein levels in TGCTs and the absence of mutations still make other epigenetic mechanisms, such as modulation of chromatin structure or modifications of histones, possible explanations for loss of NKX3.1 expression in testicular- and prostate cancers. Materials and Methods Primary tumors and cell lines Included in the present study are primary TGCTs (n = 55), intratubular germ cell neoplasias (also called carcinoma in situ ; n = 7), normal testis tissue (n = 4), germ cell tumor cell lines (TERA1, TERA2, and NCCIT), prostate adenocarcinomas (n = 20), and prostate cancer cell lines (LNCaP, PC-3, and DU-145). The primary TGCTs include all histological subtypes: seminomas, embryonal carcinomas, teratomas, yolk sac tumors, and one choriocarcinoma, classified according to the WHO's recommendations [ 21 ] by a germ cell tumor reference pathologist using light microscopic examination of hematoxylin and eosin stained tissue sections. From our previous comparative genome hybridization analysis, about half of the TGCTs had a low-level copy number gain at chromosome 8, but only rarely 8p deletions [ 22 ]. Primary prostate adenocarcinomas obtained from radical prostatectomy specimens were graded according to the Gleason grading system [ 23 ] using routinely stained tissue sections. The median Gleason score of prostate adenocarcinomas was 7 (range: 4 – 8). The prostate carcinomas were all of pTNM stage 2 and 3, and included 10 samples with 8p deletions (among other cytogenetic aberrations), 3 samples with copy number changes not involving the 8p region, and 7 samples with no copy number changes (Ribeiro et al ., submitted). Methylation-specific PCR The DNA samples were initially bisulphite modified [ 24 , 25 ], which converts unmethylated but not methylated cytosines to uracil. All samples were subsequently submitted to MSP analysis [ 26 ] using PCR primers specific to methylated and unmethylated sequences: NKX3.1 unmethylated sequence, sense: 5'GGAAAGTGAAAGTGGTGTGGGTT3', antisense: 5'CTACACACCATCCCACAAAATATC3', methylated sequence, sense: 5'AAAGTGAAAGCGGTGCGGGTC3', antisense: 5'ACGCGCCGTCCCGCAAAATAT3' (MedProbe AS, Oslo, Norway). The two fragments were amplified by the Fast Star DNA polymerase (Roche Ltd, Basel, Switzerland) in a reaction containing 1.5 mM Mg 2+ . We used a 58°C annealing temperature for both primer sets. Bisulphite treated DNA from normal blood (NB) and Sss1 methyltransferase (New England Biolabs Inc., Beverly, MA, USA) in vitro treated placenta DNA (IVD; Sigma Chemical Co., St. Louis, MO, USA) represented the unmethylated positive control and the methylated positive control, respectively. Water, replacing bisulphite treated template, was the negative control in both reactions. Bisulphite sequencing Bisulphite sequencing allows a positive display of 5-methyl cytosines in the gene promoter after bisulphite modification as unmethylated cytosines appear as thymines, while 5-methylcytosines appear as cytosines in the final sequence [ 27 ]. A subset of the samples (n = 11) were bisulphite sequenced, including all 6 cell lines, 3 TGCTs, and 2 prostate adenocarcinomas. Additionally, NB and IVD were bisulphite sequenced as positive controls for unmethylated and methylated sequence, respectively. The NKX3.1 bisulphite sequence fragment (Gene bank accession number NT_023666 (minus strand), bases 1914526 to 1914961) was 436 bp long and covered 52 CpG sites in the promoter and first exon of the gene. We designed bisulphite sequencing primers (MedProbe) with the following sequences; sense: 5'ATTGGGGAAGGAGAGGGAATTG3', antisense: 5'CCTCTAACTCTAACTCTAACTCC3'. The Mg 2+ content of the reaction was 1.3 mM, the enzyme used was HotStarTaq™ DNA polymerase (QIAGEN Inc., Valencia, CA, USA), and the annealing temperature 52°C. The PCR fragments were eluted from a 2% agarose gel (BioRad Laboratories Inc, CA, USA) containing ethidium bromide, by the MinElute™Gel Extraction kit (QIAGEN), and sequenced with the dGTP BigDye Terminator Cycle Sequencing Ready Reaction kit (Applied Biosystems, Foster City, CA) in an ABI Prism 377 Sequencer (Applied Biosystems). The bisulphite sequencing results were scored according to Melki et al . where the amount of methylcytosine of each CpG dinucleotide is quantified by comparing the peak height of the cytosine signal with the sum of the cytosine and thymine peak height signals [ 28 ]. Authors' contributions GEL performed the experimental analyses and statistics, interpreted the results, and drafted the manuscript. RIS did an independent scoring of the results, and contributed to manuscript preparation. MFF designed the primers used for the MSP and bisulphite treatment and contributed to manuscript preparation. VMA and RH were reference pathologists for the testicular cancer tissues and prostate tissues, respectively. FS was responsible for the Western Blot studies of the cell lines and participated in the writing of the manuscript. Parts of this work were done in the lab of ME who also contributed with scientific discussions. MRT provided the relevant selected series of primary prostate carcinomas with known genetic profiles, and contributed to manuscript preparation. RAL conceived the study, was responsible for its design and coordination, and contributed in the evaluation of the results and in preparation of the manuscript.

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548665

Increased polyclonal immunoglobulin reactivity toward human and bacterial proteins is associated with clinical protection in human Plasmodium infection

Background Polyclonal B-cell activation is well known to occur in Plasmodium infections, but its role in pathogenesis or protection remains unclear. However, protective properties of natural antibodies have previously been demonstrated in other contexts. Methods Sera from asymptomatic and symptomatic Plasmodium -infected subjects locally detected in a survey study in the Brazilian Amazon, and from unexposed and exposed but presently uninfected control subjects, were assayed by a standardized quantitative immunoblot method allowing simultaneous detection of IgG or IgM reactivity to a large number of parasite-unrelated proteins. Results In subjects free of coinfection with hepatitis B virus, IgG reactivity to human brain antigens and Escherichia coli proteins was strikingly enhanced in asymptomatic Plasmodium -infected individuals when compared to such with clinical malaria symptoms, or to uninfected control subjects. This difference was most characteristic for limited exposure times (less than ten years locally, or 20 years in endemic areas). It was more significant than a similar trend found for IgG to Plasmodium falciparum antigens, and unrelated to parasitaemia levels. Asymptomatic subjects with comparatively short exposure characteristically showed relatively elevated IgG versus IgM reactivity. Polyclonal IgG reactivity appears triggered by previous P. falciparum but not Plasmodium vivax malaria. Conclusion The observed difference in polyclonal antibody production seems related to intrinsic activation states of infected individuals, rather than to parasite-antigen specific immune responses. However, it appears influenced by preceding stimuli. This supports the idea that acquired clinical immunity may not exclusively depend on antigen-specific responses, but also on the individual polyclonal reaction.

Background Malaria remains an important health problem in sub-Saharan Africa and in some parts of Asia and South America. Resistance to therapeutic drugs and to insecticides, as well as social and environmental changes, are important factors in this situation. Increasing importance is currently given to antibodies in protection against human malaria, especially directed at erythrocytic stages of Plasmodium falciparum [ 1 ]. However, this protection is relatively unstable, and the precise role of specificities remains unclear regarding the antigenic variability of parasite proteins. Although parasite-specific antibodies clearly contribute to protection, it is not evident to which extent protective antibodies in general originate from specific immune responses to parasite antigens. They may also include components of innate immunity and be in part derived from natural antibody repertoires of the host. The remarkable protective properties of natural antibodies have previously been demonstrated in viral and bacterial [ 2 - 4 ] as well as in Leishmania [ 5 ] infection, and it appears conceivable that analogous properties exist toward Plasmodium parasites, either naturally or selected during the long co-evolution of the human species with these parasites. An example may be autoantibodies to 'band 3', a host-encoded target on cell membranes, involved in protection against malaria [ 6 , 7 ] as well as physiologic cellular life span regulation [ 8 ]. Natural antibodies, immunoglobulins circulating in the absence of particular immunogenic stimuli, emerge from continuous autonomous activity of the immune system which appears largely independent of any external priming, as demonstrated e. g. in germ-free and antigen-free mice [ 9 , 10 ]. They are often multireactive, and a large proportion interacts with endogenous targets and may play roles in internal homeostasis [ 11 ]. Reactivity patterns of IgM and IgG natural antibodies to autologous tissue proteins appear established early in life and remain remarkably stable throughout healthy living [ 12 ], but are capable of characteristic changes in autoimmune [ 13 , 14 ] and other [ 15 , 16 ] human diseases. Thus, such patterns are likely to reflect stabilized states of physiologic activation, shaped by polymorphic genes relevant for the immune system [ 17 ] which can be selected in evolution. The aim of this study was to investigate whether likely natural antibody reactivity patterns measured toward targets not related to parasites, but rather derived from autologous tissue or intestinal flora, could differentiate between asymptomatic and symptomatic forms of malarial infection. Asymptomatic infection is frequent in the Brazilian Amazon [ 18 ], even without very long exposure times, although malaria is only hypo- to mesoendemic and transmission is unstable with seasonal fluctuations [ 19 ]. Nevertheless, the situation appears analogous to hyperendemic regions, where parasite loads are known to gradually diminish with exposure time, resulting in a state of premunition, in which the still chronically infected subjects nevertheless remain asymptomatic for long periods [ 20 , 21 ]. Asymptomatic infection can also be maintained after clinical cure by antimalarial drugs [ 22 ], showing that protection from disease can be very distinct from parasite clearance, which may paradoxically even enhance the risk of clinical relapses [ 23 ]. Asymptomatic and symptomatic subjects who are studied here were occasionally detected in a survey study of endemic Brazilian populations. They mainly consisted of migrants who lived in endemic areas for individually different time periods, and may have experienced sequential infections by P. falciparum or Plasmodium vivax , with clinical symptoms of variable degrees of intensity but low reported mortality [ 24 ]. Results showed that asymptomatic and symptomatic states could be remarkably well distinguished by multi-specific antibody reactivity, particularly when exposure times were limited, and that the distinction consisted more in a difference in nonspecific polyclonal activation than in a specific immunization effect. Materials and Methods Study areas and subjects 78 sera analysed here originated from subjects exposed to transmission in the Brazilian Amazon endemic area, who had variable numbers of reported previous episodes of P. vivax or P. falciparum clinical malaria. The malaria-exposed subjects comprised three distinct groups [see Additional file 1]. The principal study group was derived from a screening of 531 miners living in gold-mining areas in the municipality of Apiacás (AP), Mato Grosso, among whom 99 had been found parasitaemic, presenting with positive Giemsa-stained thick-blood smears [ 25 ]. Out of these 99 subjects, only 46 had shown classical malaria symptoms within 72 hours after parasite detection, while the other 53 had remained asymptomatic. Symptoms were mainly headache, anorexia and fever. Included in the present study are 48 of these miners, 24 symptomatic and 24 asymptomatic, who had lived for up to 17 years in Apiacás. There was no significant difference between symptomatic and asymptomatic individuals in their time of residence. According to anamnestic reports, numbers of previous malaria episodes were highly variable, but neither significantly different between the groups. The time elapsed since the respective last episode, however, was significantly longer among the asymptomatics (see Table 1 ). Within these parasitaemic subgroups, subjects were further distinguished whether or not they were positive for hepatitis B surface antigen (HbSAg) and therefore hepatitis B virus (HBV) carriers. Two further groups included exposed, but aparasitaemic control subjects. The first group (20 subjects) had resided for 10 or more years in Terra Nova Norte (TNN), a small rural community within the endemic region, continuously exposed to malaria. These parasitologically negative, convalescent individuals had been treated for malaria only until two months before the blood collection (Aparasitaemic/Previous malaria). The second group (10 subjects) also lived in TNN, but had no record of previous malarial episodes (Aparasitaemic/No previous malaria). All subjects responded to a questionnaire including information on past malaria and previous treatments. Consent to draw blood was obtained from each individual according to the Fundação Oswaldo Cruz Ethics Committee (MH, November 26 th , 1994) and to the Universidade Federal de Minas Gerais Ethics Committee (April 15 th , 1998). Venous blood samples (20 ml per subject) were drawn in Vacutainer™ (Becton Dickinson, Oxnard, CA) heparinized tubes. Giemsa-stained thick-blood smears were examined at this point for blood parasitaemia. Finally, a third control group consisted of 10 healthy adult volunteers from Belo Horizonte (Minas Gerais) who had never been exposed to malaria transmission or visited endemic regions (Aparasitaemic/Not exposed). IgG and IgM to human brain proteins were assessed in the subjects described above. When measuring IgG reactivity to E. coli proteins, two of the Terra Nova and seven of the Apiacas subjects were not included, but replaced by one Terra Nova and eight Apiacas subjects not assayed for reactivity to brain proteins. Table 1 Composition of the sample studied Group Origin Nb Age 1 Residence 1 Previous malaria 2 Time elapsed since last episode 1 Aparasitaemic Not Exposed B. Horizonte 10 27–55 [31] 0 Aparasitaemic – No Previous Malaria Terra Nova 10 16–39 [27] 0 Aparasitaemic – Previous Malaria Terra Nova 20 14–35 [27.5] 4 1–11 [3] 3 Parasitaemic – HBV-negative Asymptomatic Apiacas 19 20–47 [30] 2–13 [8] 4 2–70 [15] 0–13 [2 years] 3 Parasitaemic – HBV-negative Symptomatic Apiacas 13 6–66 [27] 2–17 [7] 3 2–50 [15] 0–17 [1 month] Parasitaemic – HBV-positive Asymptomatic Apiacas 5 20–50 [27] 2–11 [6] 7–50 [15] 0–4 [1 year] Parasitaemic – HBV-positive Symptomatic Apiacas 11 24–46 [30] 5–11 [10] 4 5–50 [35] 0–2 [2 months] 1 In years; range [median] 2 Number of malaria episodes anamnestically reported; range [median] 3 Unknown for one subject 4 Unknown for two subjects Parasitaemia and anti-P. falciparum reactivities The parasite density was quantified after examination of 200 microscopic fields at 1.000× magnification under oil-immersion. All slides were examined by three well-trained microscopists. Blood parasitaemia was expressed as the number of parasites per 200 leukocytes. Parasitaemia and reactivity to P. falciparum and MSP1-19 in these populations have been analysed and described previously [ 25 ]. Immunoblot Assay The assay was done as described [ 26 ]. Briefly, protein extracts from human brain and cultured E. coli were run in a discontinuous SDS-PAGE 10% gel (Mighty Small electrophoresis apparatus, Hoefer Scientific Instruments, San Francisco, CA). After eletrophoresis, proteins were transferred onto a nitrocellulose membrane (Schleicher & Schuell, Germany) in a semi-dry system for one hour at 0.8 mA/cm 2 . After overnight blocking of free binding sites in PBS-Tween 0.2%, membranes were incubated for four hours with sera, diluted 1/20, in incubation units fixing membranes in cassettes with 28 independent channels (Miniblot System C-Shell, Immunetics Inc., Cambridge, MA). Whole membranes were then washed and incubated for 90 minutes at room temperature with secondary anti-human IgM or IgG conjugated with alkaline phosphatase (Southern Biotech, Birmingham, AL). Reactivies were revealed with NBT/BCIP (nitroblue-tetrazolium/bromo-chloro-indolyl-phosphate) substrate (Promega, Madison, WI) for three to five minutes, and membranes scanned in 8-bit grayscale and with 600 dpi resolution in a domestic scanner (Apple Color OneScanner). Thereafter, membranes were stained overnight with colloidal gold (Biorad, Hercules, CA) to reveal total protein and again scanned as described. Data processing and statistical analysis The method of data processing has been described [ 26 ]. Briefly, reactivity profiles from the scanned immunoblot image were adjusted for migration irregularities during electrophoresis, using the scan of the same membrane stained for total protein. Special procedures programmed with the software IgorPro (Wavemetrics, Lake Oswego, OR) on a Macintosh computer (Apple computers, Cupertino, CA) were applied in order to represent each serum sample as a profile on a standardized migration scale, with the optical density (OD) as a function of migration distance. After this rescaling, sections were defined by intervals on the standardized migration scale around reactivity peaks, and, after baseline subtraction, reactivity for each section and serum was quantified as the average OD within a respective section. In this way, each serum can be represented by a vector with a dimension equal to the number of sections, containing the respective reactivity quantitation. In order to make these data commensurate across membranes, they were further normalized by the membrane-wise average reactivity of a unique standard (pool of human IgM or IgG), assayed twice on each membrane. These vectors were then analysed by Principal Component Analysis (PCA). PCA is a classic method of multivariate analysis designed to describe multidimensional data with high dimensionality through projection onto characteristic subspaces with lower dimensionality. Principal components are defined in a mathematically strict manner as orthogonal axes fitting maximal information in terms of total variance with decreasing proportion and uncorrelated among each other. This includes no information on experimental groups or other particularities, but provides a completely neutral and unbiased description of the data set as such. The number of bands detected on a respective extract was quantified as the number of sections showing reactivity values two-fold above the average reactivity of the standard used for adjustment. Total reactivity for a given extract was assessed as the average OD over the entire migration scale, from the first to the last section. Only distribution-independent statistics were used: Mann-Whitney rank sum test and Spearman rank correlation. P-values below 0.05 were considered significant. Results IgG reactivity to human brain proteins As an example, Fig. 1 shows one representative out of four total immunoblot membranes on which IgG reactivities to brain proteins were assayed. Most of the reactivity bands appear in samples derived from asymptomatic parasitaemic subjects, with the exception of one symptomatic coinfected with HBV. In Fig. 2 , three different (however, correlated) ways to evaluate the reactivity quantitatively are shown : (1) by the number of detected bands; (2) by the summation of total reactivity in terms of averaged optical density over the whole migration scale; (3) by the score of the first principal component calculated from standardized optical densities of all reactivity bands. By any of these criteria, asymptomatic parasite carriers from Apiacas showed more reactivity than parasite-free subjects in all groups with high significance (p < 0.00001). Parasite carriers with symptoms, however, also had less reactivity and, provided that they were not coinfected with HBV, did not significantly differ from parasite-free subjects. Among symptomatics, only HBV-positives showed reactivity levels comparable to the asymptomatics. In the absence of HBV-coinfection, asymptomatic and symptomatic subjects differed with high significance in terms of all three reactivity measures (p = 0.0003, 0.0002 and 0.0001, respectively). Even disregarding the presence of HBV coinfection, this difference was still significant (p = 0.017, 0.008 and 0.005, respectively). Assays of specific anti-parasite reactivity in the same subjects (reported in [ 25 ]) are shown in Fig. 2 for comparison. Although showing the same tendency, these specific assays were less discriminatory, considering either only HBV-negative (IgG anti- P. falciparum : p = 0.034; IgG anti-MSP1-19: nonsignificant) or all parasitaemic individuals (p = 0.017 and p = 0.014, respectively). Figure 1 IgG reactivity patterns to brain proteins on one of four membranes. Open circles indicate asymptomatic malaria, closed circles symptomatic malaria in HBV-free parasite carriers, open and closed rhombi analogously in HBV-coinfected subjects. N indicates unexposed (Belo Horizonte), X and + exposed aparasitemic subjects from Terra Nova without and with previous malaria, respectively. Unmarked intermediate lanes contain the standard used for adjustment. Figure 2 Comparison of properties of anti-brain IgG immunoblot reactivity andantiplasmodial IgG. A. Immunoblot of IgG to human brain proteins: number of bands, total reactivity and PCA factor-1 scores for IgG reactivities for each patient group. B. Antiplasmodial IgG: equivalent displays of data from the same patients for IgG reactivity to anti- P. falciparum and anti-PfMSP1-19. In both panels, medians for each group are indicated by vertical bars. C. factor loads for PCA factor-1 shown in panel A. The first principal component (PCA factor 1) is, by definition, the linear combination of single reactivity measurements which represents a maximum of information about a multivariate dataset in terms of total variance, here 34%. Since this is the most systematic quantitative representation, the analysis will be continued based on principal components. In PCA, factor loads, i. e., coefficients indicating the relative contribution of measured parameters to the respective factor score, can be interpreted according to whether this factor represents a general level difference or a pattern-related property. Here, the factor-1 score contained only positive loads and, thus, represents a modified measure of total reactivity. Factor-1 scores indeed showed similar groupwise distributions as band number or total reactivity and were most discriminating. Among the first few principal components, factor 1 was the only one with interpretable properties. Further properties of factor-1 scores derived from IgG anti-brain reactivities are shown in Fig. 3 , 4 , 5 . Parasitaemic subjects had provided information on the time they had spent in Apiacas and in malaria-endemic areas in general. When plotted against these exposure times (Fig. 3 ), factor-1 scores discriminated best between asymptomatic and symptomatic subjects without HBV coinfection who had been exposed for relatively shorter periods. Hence, HBV-free subjects living less than 10 years in Apiacas or less than 20 years in malaria-endemic areas were almost completely separated according to their clinical status by factor-1 scores, but not those with long-term exposure. HBV-coinfected subjects, however, all displayed enhanced scores with no evident relationship to malaria exposure. For instance, both exposure parameters did not differ significamtly between symptomatic and asymptomatic subjects, regardless whether HBV infection is taken into account or not. Figure 3 Polyclonal reactivity and exposure. Scores of PCA factor-1, derived from IgG reactivity to brain proteins, in relation to the time spent in Apiacas and in malaria-endemic zones, for HBV-negative (left) and HBV-positive subjects (right). Open symbols indicate asymptomatic, closed symbols symptomatic subjects. Figure 4 Polyclonal reactivity, parasitemia and anti-PF antibodies. Relations of anti-brain IgG-derived PCA factor-1 scores are shown to parasitemia levels and anti- P. falciparum reactivity (ELISA absorbance, according to ref. 27). X and + indicate exposed aparasitemic subjects without and with previous malaria, respectively. The parameters were not always available from all subjects. Open symbols represent asymptomatic and closed symbols symptomatic subjects, all HBV-free. Figure 5 Polyclonal IgG to brain proteins and Plasmodium species in previous and present infections. Association of anti-brain IgG derived PCA factor-1 scores and Plasmodium species detected in the previous clinical Malaria episode (A), or presently (B). Medians calculated for all indicated subjects are shown by vertical bars. Subjects in which both species were detected at the same time were not considered. Crosses indicate exposed aparasitemic subjects with previous malaria, circles HBV-, and rhombi HBV+ parasite carriers. Open symbols represent asymptomatic and closed symbols symptomatic subjects. Fig. 4 shows the relationship between factor-1 scores and (a) individual parasitaemia and (b) anti-parasite IgG. Within HBV-negative asymptomatic subjects, scores were highest when parasitaemia levels were relatively low, although this association was quantitatively insignificant. A significant correlation was found between factor-1 scores and IgG reactivity to P. falciparum (Spearman rank correlation: +0.57 [p < 0.00001] including parasitaemics and exposed aparasitaemics; +0.37 [p = 0.011] within parasitaemics only), or to PfMSP1-19 (Spearman R, considering parasitaemics and exposed aparasitaemics: +0.42 [p = 0.0002]; not shown). Nevertheless, as can be seen in Fig. 4 for IgG anti- P. falciparum , these correlations are mainly due to the fact that all parameters were relatively enhanced in asymptomatic subjects. Considering asymptomatic and symptomatic individuals separately, correlations are no longer evident. Namely, some HBV-free symptomatics had elevated IgG anti- P. falciparum , but without a parallel increase in factor-1 scores. Medical records of previous episodes of clinical malaria were available for both parasitaemic and exposed aparasitaemic subjects. Considering subjects of all groups together, factor-1 scores of individuals with evidence for P. falciparum infection in their last clinically diagnosed episode were higher than for those who had had P. vivax malaria (Mann-Whitney test: p < 0.01). Qualitatively, this appeared to be the case for parasite carriers as for aparasitaemic subjects with reported previous malaria (Fig. 5 ), although a valid statistical evaluation taking subject groups into account is impossible due to the small sample size. Nevertheless, it is interesting that the Plasmodium species presently detected in the parasitaemic subjects, often not identical with the one ascribed to the previous malaria period, was not associated with a similar difference in respect to factor-1 scores. IgG reactivity to E. coli extract Patterns of IgG reactivity were also assayed toward an extract of E. coli whole cultures, which provided an independent and completely different set of target antigens, and, consequently, a different set of reactivity bands. Surprisingly, multivariate analysis of these bands yielded a result very similar to that described above for IgG reactivity to human brain proteins (Fig. 6 ). Although less significantly, the E. coli -derived score shared several properties described above. Analogously, asymptomatic parasitaemics had higher scores for reactivity to E. coli than symptomatics in the absence (p = 0.041), but not in the presence of HBV coinfection. Also similarly to IgG anti-brain, this significance increased when only subjects living less than 10 years in Apiacas were considered (p = 0.002, not shown). As can be seen in Fig. 7 , factor-1 scores calculated from anti- E. coli IgG reactivities indeed correlated highly with anti-brain-IgG-derived factor-1 scores (Spearman rank correlation: +0.70; p < 1E-9). Finally, IgG anti- E. coli -derived factor-1 scores were higher in subjects reporting previous infection with P. falciparum , compared to P. vivax infection (p < 0.05; Fig. 8 ). Figure 6 IgG reactivity to E. coli proteins. Distributions of PCA factor-1 scores derived from IgG reactivities to E. coli proteins per group. Group medians are indicated by vertical bars. Figure 7 IgG reactivity to different antigenic sources is highly correlated. IgG anti-brain and anti- E. coli derived PCA factor-1 scores, respectively, are displayed in two dimensions. N indicates non-exposed, X and + exposed aparasitemic subjects without and with previous malaria, respectively (B,C). Circles indicate HBV-, rhombi HBV+ parasitemics, open symbols asymptomatic and closed symbols symptomatic subjects. Figure 8 Polyclonal IgG to E. coli proteins and Plasmodium species in previous infection. IgG anti- E. coli derived PCA factor-1 scores are displayed against the parasite species detected in the previous malaria episode, in analogy to Fig. 5. Medians indicated by vertical bars include all subjects in the figure. Crosses represent exposed aparasitemic subjects with previous malaria, circles HBV-, and rhombi HBV+ parasite carriers. Open symbols represent asymptomatic and closed symbols symptomatic subjects. When principal components were calculated from IgG reactivities to both brain and E. coli proteins together, the properties described for both respective factor-1 scores fell together in the resulting first principal component (Fig. 9 ), indicating again that they were highly coincident. The difference between HBV-free asymptomatic and symptomatic parasitaemic subjects reached a higher significance level (p = 0.00005) than for factor-1 scores derived from either extract alone. Figure 9 IgG reactivity to E. coli proteins. Distributions per group of PCA factor-1 scores derived from IgG reactivities to human brain and E. coli proteins joined together. Group medians are indicated by vertical bars. IgM reactivity to human brain proteins IgM reactivities to brain proteins were measured using the same extract as described for IgG (data not shown). Generally, a smaller number of bands was detected. The IgM-derived factor-1 included only positive loads like the IgG-derived one. The scores of both were correlated (Spearman rank correlation: +0.55; p < 1E-6), and, as for IgG, IgM-derived factor-1 scores were higher in asymptomatic than in symptomatic parasitaemic individuals free of HBV. However, IgM-derived factor-1 did not significantly discriminate between them, except when only individuals living less than 10 years in Apiacas were considered (p = 0.013). No significant difference was found either in respect to previously or presently detected Plasmodium species. In contrast to IgG anti-brain or anti- E. coli , within parasitaemics, a remarkable positive correlation existed between IgM-derived factor-1 scores and individual age (Spearman rank correlation: +0.41; p = 0.005), and also with times spent in Apiacas (+0.34; p = 0.03), but not within aparasitaemic subjects. As for IgG anti-brain, there was no significant correlation with blood parasitaemia levels, but with specific IgG anti- P. falciparum (+0.55; p < 1E-5). Joint analysis of IgG and IgM reactive to brain proteins reveals distinct components Finally, principal components were calculated for IgG and IgM reactivities to human brain proteins together (Fig. 10 ). Surprisingly, the properties of the respective first factors calculated for each isotype alone did not coincide in a single principal component, as it had occurred in the co-calculation of IgG anti-brain and anti- E. coli reactivities. Instead, the first two principal components (factor-1 and factor-2) of the co-calculation both significantly distinguished between HBV-free asymptomatic and symptomatic parasite carriers (Factor 1: p = 0.013; Factor 2: p = 0.004), and, as above, not between those infected with HBV. Scores of both factors were enhanced in asymptomatic subjects. Since principal components in the same set are by definition uncorrelated, these two factors appear to represent separate effects associated with clinical states. Figure 10 Principal components derived from IgG and IgM reactivities to human brain taken together. A. Coefficients of factor 1 and 2, representing weight and direction of section reactivities contributing to the respective factor scores. B. Distributions of factor 1 and 2 scores according to subject groups. Vertical bars represent medians within each group. C. Distribution of factor 1 and 2 scores in respect to Malaria exposure (HBV-free parasite carriers only). Different subject groups are represented by the indicated symbols. Factor-1, characterized by positive loads as the above described, was however positively influenced primarily by IgM reactivity, and properties of factor-1 scores were similar to those of the IgM-derived factor-1. Within parasitaemic subjects, scores increased with age (Spearman R: +0.39; p = 0.007), with exposure times in Apiacas and in endemic areas (+0.29 and +0.26, but not significant), and were correlated with anti- P. falciparum IgG (+0.32; p < 0.05). However, like IgG-derived factor 1, scores were also elevated in respect to P. falciparum but not P. vivax pre-exposure (p = 0.01; not shown). In contrast, factor-2 scores were positively influenced mainly by IgG reactivity, while a number of IgM bands had a negative impact. Thus, factor 2 can be said to represent a certain IgG/IgM relationship. Remarkably, among HBV-free parasite carriers, the highest scores were characteristically found in asymptomatics who had only been exposed to malaria in endemic areas for a limited time. Factor-2 scores showed no significant association with IgG anti- P. falciparum or with pre-exposure to Plasmodium species. Instead, scores were slightly higher in subjects presently infected with P. vivax , but not P. falciparum (p = 0.04; not shown). Neither factor correlated significantly with parasitaemia. Association with reactivity to MSP1-19 Global IgG reactivity and subtype-specific reactivity have been previously assayed including some subjects examined here [ 25 ]. Among parasitaemic subjects, IgG1, IgG2, IgG3 and IgG4 anti-MSP1-19 all correlated significantly with IgM-anti-brain-derived as well as with IgG/IgM-anti-brain-derived factor-1, in particular IgG3 (Spearman R: +0.68 [p < 0.001] and +0.62 [p < 0.01], respectively). These values, however, did not corrrelate significantly with any IgG-derived factor, nor with IgG/IgM-anti-brain-derived factor-2. Only IgG anti-MSP1-19, measured in a larger number of subjects, correlated positively with IgG-anti-brain and IgG-anti-brain/ E. coli -derived factor-1 (not shown). Discussion Autoantibodies detected in the context of malaria infection are an old observation, reviewed in [ 27 , 28 ]. Typically, they were found elevated in long-term exposed subjects and in acute symptomatic infection, while asymptomatic infection has rarely been studied. However, phospholipid-related specificities were found more elevated in asymptomatics than in patients with malaria symptoms [ 29 , 30 ]. All these previous studies focused on antibody specificities otherwise known from autoimmune disease conditions, particularly systemic lupus erythematosus. The findings were often interpreted as results of specific crossreactivity or auto-immunization, and analogies were regularly made to 'autoimmunity'. This appears confusing, since malaria infection and pathological autoimmunity have little obviously in common and, in fact, the respective pathologies appear to mutually inhibit rather than to facilitate each other [ 27 ]. The simultaneous standardized detection of multiple immunoglobulin reactivities on immunoblots, as utilized in the present study, is most likely to represent natural antibody repertoires and, therefore, a way to approach the problem of repertoire description in an unbiased way, avoiding a potentially misleading disease- or otherwise antigen- or specificity-oriented vision. Extracts of human tissue (brain) or whole bacterial cultures were used as ligands for antibodies with the aim of relating eventual changes in binding patterns to clinical status, and comparing whole reactivity patterns by multivariate analysis. The same semiquantitative immunoblot technique has previously demonstrated characteristics of natural IgM and IgG reactivity patterns [ 17 , 31 , 32 ], among which stability [ 12 , 33 , 34 ] and independence of physiologic antigenic exposures [ 35 ] are most remarkable. IgG patterns, however, change with age [ 36 ], during human [ 13 , 14 ] and experimental [ 37 ] autoimmune diseases and in murine parasite infection [ 38 ]. The present results show that reactivity patterns to human brain and E. coli proteins, unrelated to parasites, could differentiate strikingly between asymptomatic and mild symptomatic malaria infection. Asymptomatic subjects generally showed elevated reactivity, which was concordant but far more characteristic when compared with anti-plasmodial IgG measures in the same sample. Thus, Plasmodium infection is able to alter reactivity patterns to target proteins without relation to the parasite particularly in asymptomatic subjects. Only co-infection with HBV, known to be frequent in our study population [ 39 ], heightened reactivity regardless of malaria symptoms and obscured this discrimination when disregarded. This effect is most probably unrelated to malaria, since chronic HBV infection itself is known for its association with a variety of autoantibodies [ 40 ]. Remarkably similar results were obtained by analyses of IgG immunoblot reactivity against extracts of human brain and of E. coli . In both cases, the same major properties were represented by a single respective principal component, characterized by positive loads. Both were highly correlated and when reactivity to both extracts was analysed together, they coincided in a single PCA factor with maximal discriminatory power, allowing to separate 13/15 (87%) of the HBV-free asymptomatics from symptomatic patients. Thus, IgG reactivity patterns to brain and to E. coli proteins behaved somewhat like fragments of a hologram which, added together, show the same image with increased resolution. Other than previous data on malaria-associated autoantibodies, these observations cannot easily be attributed to specific immune responses, despite a positive correlation with anti-parasite reactivity. Instead, they probably reflect another phenomenon well known for malaria and other parasite infections, that of polyclonal lymphocyte activation. Polyclonal activation, however, is often discussed as an immune evasion mechanism, beneficial primarily for parasites. Our results show in contrast that the production of polyclonal IgG was associated with protection in asymptomatic parasite carriers, and that polyclonal reactions appeared to have at least short-term protective effects. A reason for this discrepancy may be that earlier studies of polyclonal activation [ 41 ] assessed peripheral plaque-forming cells, which may not contribute much to circulating antibody repertoires, and not the recruitment of resident plasma cells with a relevant lifespan from which circulating natural antibodies likely originate. When such natural antibodies as they are addressed by us have pre-existent protective properties, their polyclonal recruitment can well be efficient and protective, as it has been demonstrated for other infections [ 2 , 3 , 5 ]. This could be due to preceding evolutionary selection. Our observation of an effect of the parasite species present in previous clinical episodes further suggests that previous antigenic experience can trigger not only classical recall responses, but also this capacity to react polyclonally. With increasing exposure time, this nonspecific recruitment of natural repertoires could be stepwise complemented by induced parasite-specific antibodies, leading to an increasingly adapted protection as it is observed in long-term exposed subjects. Remarkably, in our study, asymptomatic and symptomatic infections were indeed best discriminated in subjects with relatively short exposure times. In contrast to previous data on autoantibodies, this indicates that the reactivity shift in asymptomatic subjects described here does not result from long-term adaptation to the parasite, but is representative of an intermediate state of adaptation. This interpretation is most clearly supported by the result of joint analysis of IgM and IgG reactivity to brain proteins, where two distinct principal components appeared. Factor-1, representing a general elevation of all reactivities with dominant IgM impact, shows an evident overall time dependency in parasite carriers and may, thus, reflect long-term adaptation. However, factor-2 discriminated asymptomatic from symptomatic infections best and, most characteristically, those asymptomatic subjects who had been least exposed. Factor-2 represented a relative dominance of IgG reactivity against some IgM. Thus, in order to remain asymptomatic, particularly infected subjects without long-term adaptation to the parasite may require a pattern of natural antibody production dominated by IgG but not IgM. This is in principal agreement with known protective effects of antibodies. Classically, passive transfer of hyperimmune IgG to patients infected with P. falciparum has shown that antibodies play a crucial role in controlling blood stage parasitaemia [ 42 , 43 ]. The gradual acquisition of clinical immunity to malaria after repeated infection is positively correlated with the development of a diverse IgG repertoire, most clearly including IgG reactive to parasitized red blood cells [ 1 ]. Such cytophilic antibodies are predominant in clinically immune individuals living in hyperendemic areas [ 21 ]. In contrast to IgG, IgM with the same cytophilic properties is associated with rosetting and enhanced pathogenicity [ 44 - 47 ]. The targets of cytophilic antibodies include diverse and highly variable parasite-encoded proteins, but also host proteins such as 'band 3' [ 6 ], which is involved in parasite entry into red blood cells [ 7 ]. Nevertheless, anti-band 3 antibodies may just exemplify the possible relevance of natural repertoires, since they are originally known as physiologic autoantibodies involved in the general clearance of senescent and damaged (including infected) erythrocytes [ 8 ]. Intrinsic tuning of the production rate of such pre-existing antibodies may, therefore, contribute as much to the control of parasitaemia that occurs in clinically immune individuals, as do cytophilic antibodies originating from parasite-specific responses. Other natural antibody-mediated effects could act analogously, and an appropriate individual reshaping of the natural repertoire toward such components could well lead to a capability to regulate parasitaemia, triggered by parasite-mediated polyclonal lymphocyte activation. Such reshaping, associated with a shift in internal self-recognition, could also explain the appearance of lupus-like autoantibodies in chronically exposed subjects [ 28 ] without, however, indicating autoimmunity. In general, protective natural repertoire components appear to deserve further investigation, since vaccines and other malaria control strategies could possibly be designed to make use of them. Conclusions This study shows that simultaneous detection of IgM and IgG reactivities to a broad range of targets can reveal remarkable properties which are not easily accessible by the usual specificity-focussed approaches. Thus, clinical states in Plasmodium infection appear to depend on internal activation states which can be distinguished by different patterns of polyclonal antibody production. Particularly, asymptomatic but not symptomatic infection of HBV-free subjects without extensive pre-exposure to malaria was characterized by elevated polyclonal IgG reactivity in absolute terms and in relation to IgM, furthermore appearing to be triggered by previous P. falciparum but not P. vivax infections. Authors' contributions CJFF and EMB did the field work and collected the samples. NMV designed and supervised the study. AC performed preliminary experiments. CF, LFG and ASN did the immunoblots and analysed the results. CF prepared software, performed statistics and wrote the manuscript.

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549037

Functional evolution of ADAMTS genes: Evidence from analyses of phylogeny and gene organization

Background The ADAMTS (A Disintegrin-like and Metalloprotease with Thrombospondin motifs) proteins are a family of metalloproteases with sequence similarity to the ADAM proteases, that contain the thrombospondin type 1 sequence repeat motifs (TSRs) common to extracellular matrix proteins. ADAMTS proteins have recently gained attention with the discovery of their role in a variety of diseases, including tissue and blood disorders, cancer, osteoarthritis, Alzheimer's and the genetic syndromes Weill-Marchesani syndrome (ADAMTS10), thrombotic thrombocytopenic purpura (ADAMTS13), and Ehlers-Danlos syndrome type VIIC (ADAMTS2) in humans and belted white-spotting mutation in mice ( ADAMTS20 ). Results Phylogenetic analysis and comparison of the exon/intron organization of vertebrate ( Homo , Mus , Fugu ), chordate ( Ciona ) and invertebrate ( Drosophila and Caenorhabditis ) ADAMTS homologs has elucidated the evolutionary relationships of this important gene family, which comprises 19 members in humans. Conclusions The evolutionary history of ADAMTS genes in vertebrate genomes has been marked by rampant gene duplication, including a retrotransposition that gave rise to a distinct ADAMTS subfamily ( ADAMTS1 , -4 , -5 , -8 , -15 ) that may have distinct aggrecanase and angiogenesis functions.

Background ADAMTS (A Disintegrin-like and Metalloprotease with Thrombospondin motifs) proteins have homology with the metalloprotease region of the ADAM proteases, but also have at least one of the Thrombospondin type 1 Sequence Repeat (TSR) motifs that are common in extracellular matrix proteins. Since the discovery of a gene encoding ADAMTS1 in 1997 [ 1 ], a total of 19 similar genes have been found in the human genome [ 2 ], numbered ADAMTS1-20 ; there is no ADAMTS11 because early reports of an ADAMTS11 [ 3 ] were later found to describe ADAMTS5 . Many of these genes have been implicated in a variety of diseases, including connective tissue disorders [ 4 ], cancer [ 5 - 7 ], osteoarthritis [ 3 , 8 ], and possibly Alzheimer's disease [ 6 , 9 ]. Recently, an autosomal recessive form of Weill-Marchesani syndrome (WMS) has been attributed to null mutations of the ADAMTS10 gene [ 10 ]. The symptoms characteristic of this syndrome (short stature, brachydactyly, joint stiffness, and anomalies of the eye lenses), together with its expression patterns, suggest a role for the gene encoded by this protein in normal growth and in skin, eye, and heart development. ADAMTS proteins are characterized by a pro-domain, a metalloprotease domain, the so-called disintegrin-like and spacer domains, and a tail of TSR repeats. The pro-domain of ADAMTS1 and -4 is cleaved at the RX(K/R)R furin cleavage site [ 11 ] in the Golgi [ 12 , 13 ], releasing an active protein [ 14 ]. There are clearly conserved furin cleavage sites for most human ADAMTS proteins (positions 578–581 of the alignment) [ Additional File 2 ]. While this site was less well conserved in ADAMTS10 and ADAMTS12, the pro-domain of ADAMTS12 was also shown to be removed by a furin-mediated process [ 7 ]. On the basis of this combined evidence, it is commonly believed that furin cleavage of the pro-domain might occur for all ADAMTS proteins. The metalloprotease domain of ADAMTS proteins is shared with the related ADAM proteins, and the catalytic Zn2+-binding motif HEXGHXXXXXHD [ 15 ] is well conserved, shown at amino acid positions 761–772 [ Additional File 2 ]. While the metalloprotease domain of ADAM proteins is followed by a disintegrin domain which binds integrins at a conserved X(D/E)ECD site [ 16 , 17 ], the corresponding amino acids in the disintegrin-like domain of ADAMTS proteins are not well conserved. We also note that the so-called spacer domain following this disintegrin-like domain (amino acids 1060–1400) [ Additional File 2 ] in fact has many highly conserved residues, despite its comparatively reduced overall conservation of amino acid sequence. There are four matrix metalloprotease (MMP) cleavage sites in the spacer domain of ADAMTS1 [ 14 , 18 ], including the highly conserved IPAGA site at amino acid positions 1229–1233 [ Additional File 2 ] ( L. Iruela-Arispe , personal communication ). Further proteolytic processing within this domain has been demonstrated for ADAMTS1, -2, -5, and -12 [ 3 , 6 , 7 , 19 ]. For ADAMTS1, this second proteolytic step is mediated by several MMPs, and results in removal of the C-terminal TSRs that interact with the extracellular matrix (ECM). This leads to release of the protein from the endothelial cell membrane, reducing its ability to inhibit endothelial cell proliferation and probably reducing its anti-angiogenic potential [ 14 ]. Release of ECM-bound proteins via proteolytic removal of their TSR domains may be a common theme, as we see similar proteolytic removal of the C-terminal TSRs of the unrelated neuronal guidance protein F-spondin by plasmin, releasing it from ECM binding [ 20 ]. While the exact mechanism of the proteolytic processing of ADAMTS proteins remains somewhat controversial, there is an intriguing possibility that regulation of the ratio of ECM-bound vs . free ADAMTS protein could be mediated by MMPs. The region containing these sites is conserved to varying degrees in the newly discovered ADAMTS proteins, suggesting variable (perhaps tissue-specific) MMP processing of these proteins. ADAMTS4, which lacks a TSR tail, may not have an ECM-bound form. The region between the metalloprotease domain and the TSR repeat tail was demonstrated to be necessary for gon-1 , a Caenorhabditis ADAMTS homolog, to mediate cell migration during gonadogenesis [ 21 ]. A variant of this region that lacks the conserved amino acids upstream of the classic TSR but maintains the highly conserved spacer residues is found in papilin, where it has been implicated in influencing cell rearrangements during organogenesis [ 22 ] and in the Manduca sexta lacunin protein which plays a role in basal lamina remodeling during morphogenesis [ 23 ]. It will be interesting to investigate whether there is to be a common theme of organogenesis function among proteins that contain this configuration of domains. There is evidence that several mammalian ADAMTS proteins are expressed organogenesis. For example, mutations in the mouse ADAMTS20 gene have been found to cause the belted white-spotting mutation, resulting from a defect in melanocyte development or migration during embryogenesis [ 29 ], the ADAMTS1 protein is necessary for mouse gonadogenesis [ 30 ], ADAMTS12 is specifically expressed in fetal lung [ 7 ], and several of the newly described ADAMTS proteins [ 28 ] are expressed solely or primarily in fetal tissue. ADAMTS proteins contain a single "classic" TSR motif (WXXWXXW) in the disintegrin-like domain, and a variable number of variant TSRs within the C-terminal tail of the protein, which contain 4 amino acids between tryptophan residues (W4XW) rather than two. TSRs can be divided in several structural groups, based on the presence and spacing of cysteines [ 24 ]. The precise function of each type of TSR has not yet been determined, although it is known that the sequence CSVTCG in one of the thrombospondin-1 TSR's mediates endothelial cell apoptosis through binding to CD36 [ 25 , 26 ]. About 70 proteins in the human genome contain TSRs [ 27 ] and many of them are matrix binding proteins. ADAMTS1 and -8 inhibit angiogenesis [ 31 ], and gene expression profiling suggests that ADAMTS4 also has a role in angiogenesis [ 32 ]. Several of these proteins (ADAMTS1, -4, and -5) have also been shown to cleave aggrecan, the proteoglycan that makes cartilage elastic and compressible [ 19 , 33 , 34 ], and ADAMTS4 was recently shown to cleave cartilage oligomeric matrix protein (TSP5) [ 35 ]. The ADAMTS2, -3, and -14 proteins appear functionally related. ADAMTS3 is a procollagen II N-propeptidase, and ADAMTS14 appears also to be an aminoprocollagen peptidase [ 36 ]. ADAMTS2 is an aminoprocollagen peptidase of procollagen I and II, and deficiency of this protein causes Ehlers-Danlos syndrome type VIIC [ 4 ]. ADAMTS13 is a von Willebrand factor-cleaving protease. Mutations in the ADAMTS13 gene result in inappropriate platelet activation, leading to the blood disorder thrombotic thrombocytopenic purpura (TTP) [ 37 - 40 ]. Recently, an intriguing link has been discovered between ADAMTS metalloproteases. The proinflammatory cytokines IL17 [ 41 ], IL1β [ 42 ] and TGFβ [ 43 ] induce expression of ADAMTS4 . TGFβ also induces ADAMTS2 [ 44 ] and TNFα was found to up-regulate ADAMTS1 , ADAMTS6 , and ADAMTS9 in ocular cells [ 45 ], suggesting a role for these proteases in inflammatory eye disease. Similarly, TNFα produced a marked induction of ADAMTS1 in endothelial cells [ 46 ]. As several ADAMTS proteins, ADAMTS4 in particular, are implicated in rheumatoid arthritis, and TNFα inhibitors have been recently been used with great success in its treatment [ 47 ], we speculate that part of the effect of the TNFα inhibitors is an indirect downregulation of the ADAMTS proteins that break down connective tissues. As TNFα inhibitors are not without inherent risks [ 48 , 49 ], transcriptional inhibition of specific ADAMTS genes may ultimately provide similar benefits with fewer risks. To better understand the multiple functions of the ADAMTS proteins, we carried out the most detailed and comprehensive analysis to date of the phylogenetic relatedness and intron/exon organization of all human ADAMTS genes, including their comparison with invertebrate and chordate ADAMTS homologs. Prior analyses included fewer species and did not address the sequence of genomic events that resulted in the current ADAMTS genomic structure [ 2 , 28 , 50 ]. Our analysis reveals distinct sub-families with unique functions and reveals a history of gene duplications, retrotransposition, and the loss and gain of introns during animal evolution. For example, ADAMTS1 , -4 , -5 , -8 , and -15 genes all derive from a retrotransposition event that occurred prior to the divergence of vertebrates and the urochordate Ciona intestinalis , and from subsequent gene duplications that occurred prior to the divergence of mammals and the pufferfish, Fugu rubripes . This ADAMTS protein subfamily encompasses proteins that share aggrecanase and angiogenesis-related activities. Results & Discussion Gene discovery To perform a phylogenetic analysis of the ADAMTS gene family we first examined several genome databases to have a comprehensive survey of all ADAMTS genes in humans and other species. When we started this analysis in 2002 only 12 ADAMTS proteins were known. We predicted coding sequences of the human ADAMTS genes based on several sequence databases (see Material and Methods) and found them to be identical to those subsequently published by Cal, et al [ 28 ] based on cloned cDNAs. This work confirmed that a total of 19 ADAMTS genes exist in the human genome, with various isoforms. Since there were several cases in which alternative splicing or different exon predictions resulted in ADAMTS proteins of varying lengths, the most complete (longest) translations were considered in our analyses, and their Genbank accession numbers are indicated [ Additional File 2 ]. ADAMTS9 has three known splice variants, of which the long variant that we used for analysis was NM_182920. ADAMTS20 has two known splice variants, of which we used NM_025003. ADAMTS18 has two known variants, of which we used NM_199355, minus the final exon. ADAMTS13 has four known variants, of which we used NM_139025. ADAMTS10 and ADAMTS6 each have a single known coding sequence, and we found evidence of others. The variant of ADAMTS6 that is published (NM_014273) is a short form, and contains a non-consensus exon immediately following the metalloprotease catalytic site, while the variant of ADAMTS10 that is published (NM_030957) has a consensus exon at this location, and is in the long form. We predict a long form of ADAMTS6 , as well as a consensus exon for ADAMTS6 and a non-consensus exon for ADAMTS10 . We used the consensus exons of both genes in our analyses. Phylogenetic analyses We compared the 19 known human ADAMTS protein sequences with ADAMTS homologs from invertebrates ( Drosophila and Caenorhabditis ) from which entire genome sequences were recently determined, to elucidate their evolutionary relationships (Figure 1A and 1B ) [ Additional File 1 ]. This revealed a series of gene duplications among human ADAMTS genes, of uncertain affinity to these invertebrate relatives. With the goal to further elucidate this gene duplication history, the human and invertebrate ADAMTS orthologs were compared with ADAMTS orthologs from Mus , Fugu and Ciona , which diverged between humans and invertebrates, and with an additional invertebrate, the honeybee, Apis mellifera (Figure 2 ) [ Additional File 2 ]. Figure 1 Phylogenetic analysis of human ADAMTS proteins and invertebrate homologs . Unambiguously aligned amino acids were analyzed by distance (Protdist+NJ), maximum parsimony (MP) and maximum likelihood (ML) methods. The trees shown are the ML distance topologies. Numbers at the nodes represent the percent of bootstrap replicates of distance (NJ) and parsimony (MP), and the percent of quartet puzzling steps (QP) in support of each group. (A) Phylogenetic tree of human and distantly related invertebrate ADAMTS homologs inferred from a 359-amino acid alignment, with α = 1.42 and proportion of invariable sites (pI) = 0.09. (B) Phylogeny of human and invertebrate ADAMTS homologs with long branches removed, inferred from 543 aligned amino acids, with α = 1.48 and proportion of invariable sites (pI) = 0.10. For reference, Genbank GI numbers for the sequences are provided [ Additional File 2 ]. Figure 2 Phylogenetic analysis of animal ADAMTS homologs. This is the consensus maximum likelihood tree topology determined from 900 trees with the highest posterior probabilities inferred by Bayesian analysis of protein sequences. 571 aligned amino-acid sites were analyzed, with mean α = 1.59 (1.38 < α < 1.83), pI = 0.10 (0.07 < pI < 0.13) and lnL = -37875.26. Numbers at nodes represent Bayesian posterior probabilities for that relationship, with the best-supported posterior probabilities (1.00) represented by bullets (•). The percent of 1000 bootstrap replicates in support of the nodes, as found by distance and parsimony analyses, are also reported. Accession numbers and scaffold numbers for sequences are provided [ Additional File 2 ]. To perform this analysis we inferred the coding sequence of sixteen ADAMTS proteins in the Fugu rubripes genome [ 52 ], and drew from Genbank nine representative mouse orthologs, three orthologs from the Drosophila genome and four from Caenorhabditis (see Figures 1A and 2 ). Other Mus (and Rattus ) ADAMTS orthologs that were unannotated at the time of our initial work have since been identified by others [ 51 , 53 ], and some are annotated in the MEROPS database[ 82 ]. However, they were not included for our final analyses presented here since they are so similar to the human sequences (69–99% identical, [ 53 ]) that they offered no help in elucidating the gene duplication history. The invertebrate genomes were surveyed extensively for additional ADAMTS genes, and those most closely related to the vertebrate ADAMTS orthologs were retained in the analyses presented herein. The most divergent Drosophila and Caenorhabditis ADAMTS homologs represented in Figure 1A were removed from further analyses in attempt to avoid systematic bias known as "long branch attraction" where divergent but putatively unrelated sequences group together because of their divergence rather than due to shared characters [ 54 ]. All ADAMTS proteins introduced here contain the same basic domain structure as previously described ADAMTS proteins. A complete alignment of all human and invertebrate ADAMTS protein sequences, and representative Ciona , Fugu and Mus orthologs, annotated with intron positions and phases, is available [ Additional File 2 ]. Intron position and phase We compared the positions of introns and their phases between Homo , Fugu , Ciona , Drosophila and Caenorhabditis homologs of ADAMTS genes, in attempt to corroborate and further elucidate their evolutionary relationships, as shown in Figure 3 . The term intron phase refers to the position of the splice site with respect to the codon, where phase 0 describes a splice site 5' of the codon, phase 1 describes a splice site between the first and second base of a codon, and phase 2 describes a splice site between the second and third base of a codon. Introns at the same position that have the same phase in homologous genes are considered to be shared characters that were conserved during evolution. The lack of an intron at a conserved position may either suggest that the gene lost an intron at that position during its evolution, or that it never had that intron, and the intron conserved in the other homologs was gained after those homologs diverged from the intron-lacking homolog. In combination with the phylogenetic analysis of the ADAMTS protein sequences, a parsimonious interpretation of the data summarized in Figure 3 that invokes the fewest changes should help to distinguish between older and more recent gene duplication events in this gene family. Three of our most striking observations of the intron distribution are that (i) some intron positions are shared between worm, fly, chordate and vertebrates, (ii) recently duplicated genes share similar patterns of introns, and that (iii) the complete absence of ancient introns and the presence of introns at new positions in ADAMTS1, 4, 5, 8 and 15 of vertebrates and Ciona reveals that this subgroup of genes evolved by retrotransposition early during chordate evolution, was repopulated by new introns (in some cases, separately in vertebrates and Ciona ), and subsequently underwent gene duplication during the evolution of vertebrates. Figure 3 The phase and position of introns in ADAMTS genes support the phylogeny of ADAMTS proteins. Intron positions 16 – 87, found in the conserved region of the multiple alignment, are numbered consecutively from the 5'>3' locations in the ADAMTS-coding regions of genes. The presence of an intron is indicated according to its phase (0, 1, 2), absence of an intron indicated by "-" and missing data is blank. Unambiguously aligned intron positions are highlighted in bold, and conserved intron positions shared between chordates and Drosophila CG4096 or CG6107 or chordates and Caenorhabditis are indicated by $, # or * symbols respectively. The phases and positions of introns summarized here are also individually highlighted in the multiple sequence alignment [ Additional File 2 ]. The phylogenetic analysis of animal ADAMTS homologs reveals that proteins that are known to have similar biological activities are closely related, and that they have evolved by a series of gene duplication events (Figure 2 ). Since the functions of only some ADAMTS proteins have been empirically tested, estimates of evolutionary relatedness amongst the entire family may imply closer functional relatedness, and thus guide the future design of more specific empirical tests of protein functions. An interesting property of the vertebrate ADAMTS proteins are the extensive sequence similarity between many pairs of sequences, as indicated in Figures 1 , 2 , 3 , 4 [and Additional file 2 ]. Although in many cases little is known about the functions of these proteins, we can speculate that the two proteins in each pair may share similar biological activities due to their shared primary sequence. It is also possible that these ADAMTS proteins act as heterodimers, in a manner similar to the ADAM proteins fertilin α and β [ 55 ]. Figure 4 Proposed scenario for the evolutionary history of ADAMTS proteins. During chordate evolution a series of gene duplications resulted in six ADAMTS proteins present in the Ciona genome, while an early retrotransposition event gave rise to the "angiogenesis clade" of ADAMTS proteins. This proliferation of ADAMTS proteins did not occur in invertebrates, and there is evidence of the loss of one ADAMTS ortholog from Caenorhabditis . More recent duplications that occurred early during vertebrate evolution resulted in the paired sets of ADAMTS proteins present in the human genome. The chromosomal locations of the human ADAMTS genes are indicated in parentheses and the exon structure of each human gene is diagrammed to the right of its position in the schematic phylogenetic tree, and shown in more detail in the Additional Files. As shown in Figures 1 and 2 and summarized in Figure 4 , animal ADAMTS homologs have undergone several gene duplications. Assuming that the Ecdysozoa hypothesis is true and arthropods and nematodes are united as a group [ 56 - 62 ], our results indicate that a single ADAMTS gene duplication preceded the divergences of Ecdysozoa and chordates. At least 3–4 ADAMTS gene duplications occurred in chordates prior to the divergence of Ciona and vertebrates, followed by additional gene duplications in vertebrates prior to the divergence of Fugu and mammals (Figures 2 and 4 ). Ciona intestinalis , the urochordate sea squirt, was found to have at least six ADAMTS genes (Figure 2 ), which correspond to six of the seven major groups of vertebrate ADAMTS homologs. Ciona ADAMTS6 is the sister of the group comprised of vertebrate ADAMTS6 and -10, indicating that ADAMTS6 and -10 evolved by gene duplication early during vertebrate evolution, preceding the divergence of pufferfish and mammals, but after their divergence from urochordates. Similarly, Ciona ADAMTS16 is a sister to the group comprised of vertebrate ADAMTS16 and -18, Ciona ADAMTS7 is a sister to the group comprised of vertebrate ADAMTS7 and -12, Ciona ADAMTS3 is a sister to the group comprised of vertebrate ADAMTS2, -3 and -14, Ciona ADAMTS9 is a sister to the group comprised of vertebrate ADAMTS9 and -20 and Ciona ADAMTS15 is the sister to the group comprised of vertebrate ADAMTS1, -4, -5, -8 and -15. This reveals that both gene duplications early in chordate evolution as well as subsequent gene duplications early during vertebrate evolution have contributed to the proliferation of ADAMTS genes studied in growing depth in mammalian model systems. ADAMTS2 , -3 , and -14 have been recognized as evolutionarily closely related genes, encoding proteins with a common functionality as procollagen aminopeptidases. They are as a group most closely related to a single gene in Ciona , and appear to have evolved by gene duplications that occurred prior to the divergence of pufferfish and mammals but after the divergence of urochordates and vertebrates. They are most closely related to ADAMTS13 , suggesting a gene duplication from a common ancestor (Figures 1 and 2 ). ADAMTS13 appears to have originated early in vertebrate evolution as it has a closely related homolog in the pufferfish Fugu rubripes but is apparently absent in Ciona , fly and worm genomes. The pufferfish ADAMTS13 homolog is not only closely related at the amino acid sequence level, but also has the same ADAMTS13 -specific intron/exon structure in its tail, which is unique among the ADAMTS gene family. This is in agreement with a unique function for ADAMTS13 as a protease cleaving von Willebrand factor, leading to abnormal blood clotting. Although the mouse ADAMTS13 gene was not included in this analysis, it has been identified (Genbank accession number NM_001001322). A second evolutionarily related group is comprised of ADAMTS1 , -4 , -5 , -8 and -15 and their single sister in Ciona . Vertebrate members of this group share unique intron positions and lack all of the intron positions held by other ADAMTS genes and their invertebrate homologs (Figure 3 ). Three members of this group ( ADAMTS1 , -4 , and -8 ) encode proteins with aggrecanase and angiogenesis-related functions, which suggests the examination of ADAMTS5 and -15 for similar biological activities. This putative "angiogenesis/aggrecanase group" appears most closely related to ADAMTS20 and -9 . Further, the unique intron positions shared by ADAMTS1 , -4 , -5 , -8 , and -15 , and lack of invertebrate orthologs in this putative "angiogenesis/aggrecanase group" suggest that this group's progenitor arose within chordates via a retrotransposition event from the common ancestor of the group comprised by ADAMTS20 and -9 (Figures 2 and 4 ). The intron/exon structures of ADAMTS1 , -4 , -5 , -8 , and -15 are similar to that of the mouse ADAMTS1 gene [ 63 ], and our analysis shows four ADAMTS genes with this characteristic gene structure in the genome of F. rubripes . Therefore, retrotransposition of an ancestor of the angiogenesis/aggrecanase subfamily of genes, its acquisition of new introns, and subsequent gene duplications that produced five related genes occurred prior to the divergence of human, mouse and pufferfish lineages. In at least one case (intron 17 in ADAMTS8 ) we see evidence of acquisition of a new intron following the process of duplication, but prior to the divergence of mammals and pufferfish. ADAMTS20 and -9 are most closely related and, along with the members of the angiogenesis/aggrecanase clade, are most closely related to invertebrate gon-1 ( Caenorhabditis ) and CG6107 ( Drosophila ). The finding that ADAMTS9 and -20 together as a group have a single sister gene in Ciona indicates that they evolved by gene duplication in the vertebrate lineage, after their divergence from urochordates. However, the results of our phylogenetic analyses demonstrate that neither ADAMTS9 nor ADAMTS20 can alone be rightfully dubbed as being orthologous to gon-1 , as has been recently proposed [ 64 , 65 ]. In fact, our analyses suggest that while gon-1 and CG6107 are likely orthologs, the chordate ortholog of these genes was the common ancestor of Ciona ADAMTS9 and -15 , i.e. also the common ancestor of the later-duplicated vertebrate ADAMTS genes ADAMTS9 , -20 , -15 , -5 , -8 , -4 , and -1 (Figures 1 and 2 ). Only one invertebrate sequence ( Drosophila CG4096) was found that grouped with the remainder of the human ADAMTS homologs. The placement of this gene with or within a group of these remaining ADAMTS genes would suggest the number of gene duplication events in this gene family that occurred prior to the divergence of vertebrates and invertebrates from a common ancestor. The Kishino-Hasegawa test revealed that the likelihood of Drosophila CG4096 being most closely related to an ancestor of the group of all remaining mammalian ADAMTS proteins, or of the various groups nested within it, was not significantly different from the likelihood that Drosophila CG4096 is most closely related to ADAMTS 7 and -12 (data not shown). The most parsimonious explanation of this result is that a single gene duplication of an ancient ADAMTS homolog occurred early during the evolution of animals, prior to the divergence of chordates from invertebrates, followed by lineage-specific gene loss and gene duplications (Figure 4 ). If this scenario is correct, the Caenorhabditis ortholog of Drosophila CG4096 has been subsequently lost, but the vertebrate ortholog has been retained and underwent several gene duplications within and among chromosomes in the vertebrate lineage ( ADAMTS2 , -3 , -6 , -7 , -10 , 12–14 , 16–19 ). The exons comprising the TSR tail each contain a single variant TSR, with the C(S/T)XCG motif 5' and the W4XW motif at the 3' end. This exon structure may facilitate the formation of alternately spliced isoforms, such as we describe here, but it would also lend itself to duplication or loss of individual repeats. However, the number of variant TSRs in the tails of these proteins has been conserved for the gene pairs ADAMTS17 and -19 , ADAMTS6 and -10 , and ADAMTS18 and -16 (Figure 4 ). While this may suggest a series of relatively recent gene duplications, a more likely explanation is that each TSR has an important and non-redundant role, or that the presence of a specific number of TSRs is critical for each protein's function. The apparent absence of any ortholog of ADAMTS17 or -19 in the pufferfish genome (Figure 2 ), but their presence in Mus and Rattus [ 51 ] suggests that this gene duplication either occurred in mammals after they diverged from fish, or that ADAMTS17 or -19 evolved earlier than the mammal/fish divergence but were lost in Fugu . Gene duplication is a common way by which new genes with similar functions may evolve. In fact, duplication of large segments of chromosomes has been a common occurrence during animal evolution [ 66 , 67 ]. Both the phylogenetic trees and the intron/exon structures of ADAMTS genes show a history of such duplications. In addition to the similarity in intron positions of ADAMTS-1 , -4 , -5 , -8 , and -15 in both mouse and pufferfish, human ADAMTS1 and -5 are located in tandem on chromosome 21, and human ADAMTS8 and -15 , on chromosome 11 (Figure 3 ). The remaining genes have additional introns at conserved locations, and both proteins in each set of pairs have the same intron/exon structure. Thus, by combining the phylogenetic analysis and intron/exon structure determinations, we are able to propose the following series of events leading to the ADAMTS protein family (Figure 4 ): (i) The ancestral ADAMTS gene duplicated prior to the divergence of the ecdysozoan and chordate lineages, approximately 673 million years ago [ 68 ]. (ii) In the following approximately 250 million years prior to divergence of fish and mammals [ 69 ], multiple gene duplications occurred. (iii) A retrotransposition of the common ancestor of the ADAMTS9 and -20 gene pair resulted in an intronless gene that proceeded to gain multiple introns, giving rise to the angiogenesis/aggrecanase clade. (iv) This gene was involved in a duplicative chromosomal inversion, and later a duplication of the chromosomal segment containing both ADAMTS genes. (v) Another intron was gained, in ADAMTS8 , prior to the divergence of the pufferfish and mammalian lineages. In the other branch of the ADAMTS family, we see a remarkable frequency of genes located on chromosome 5, suggesting it as the location of the ancestor of these genes. We can speculate that a similar scenario of within-chromosome duplication followed by duplication of chromosomal segments took place, although none are in as close physical proximity as the ADAMTS1 -subfamily genes. Conclusions This comprehensive bioinformatic survey of the human genome affirms the widely held belief, derived from experimental work, that the nineteen known human ADAMTS proteins constitute the complete gene family. By examining both the amino acid sequences using rigorous phylogenetic methods and comparing the exon structure of these proteins, we were able to draw conclusions about the evolutionary history of this family of proteins which, in turn, provides a framework for further analysis of the functions of these clinically-relevant genes. Methods Gene discovery Sequences of ADAMTS homolog sequences presented here were identified from 2001 to 2004 using genomic sequences cataloged in the NCBI, JGI ( Fugu and Ciona [ 52 , 70 ]) and Celera genome databases using BLASTp, BLASTn, BLASTx, tBLASTn and tBLASTx searches [ 71 ]. We searched databases of Expressed Sequence Tags (ESTs) for all human genes and, with the exception of ADAMTS15 , found ESTs that corresponded to those genes, confirming their transcription. Splice site predictions were made by neural network via the Berkeley Drosophila Genome Project and also by eye using Sequencher 4.2 (Genecodes), with reference to protein multiple sequence alignments. We used the same method to identify Caenorhabditis elegans , Drosophila melanogaster , and Fugu rubripes homologs of ADAMTS genes, and their genomic structure. Multiple sequence alignments of the inferred amino acid sequences were prepared using Multalin [ 72 ] and ClustalX1.81 [ 73 ] and manually refined and annotated within BioEdit [ 74 ] and MacClade4.06 [ 75 ]. Phylogenetic analysis Initial phylogenetic analyses were conducted including all of the human ADAMTS proteins along with seven invertebrate homologs, three from Drosophila melanogaster and four from Caenorhabditis elegans (Figure 1A ), and then these analyses were repeated with the most divergent invertebrate sequences removed (Figure 1B ). The datasets for these analyses were comprised of 359 and 543 unambiguously aligned amino acid sites, respectively. The alignments were analyzed using parsimony and distance methods. Parsimony analyses used a heuristic search with random stepwise addition of data and tree-bisection-reconnection in PAUP*4.0b10 for 1000 bootstrap replicates [ 76 ]. Distance matrices were inferred using the Jones, Taylor, Thornton (JTT) substitution model with PROTDIST in PHYLIP 3.6a3 [ 77 , 78 ]. Neighbor-joining trees were constructed with the input order jumbled for 1000 bootstrap replicates using NEIGHBOR, SEQBOOT and CONSENSE in PHYLIP. Using Tree-Puzzle 5.0 [ 79 ] we generated maximum-likelihood distance matrices in which among-site substitution rate heterogeneity was corrected using an invariable and eight gamma-distributed substitution rate categories and the JTT model. 10,000 quartet-puzzling steps were also used (Tree-Puzzle) to assess branch support. To better resolve the evolutionary relationships of the vertebrate ADAMTS subfamily members and to provide information on their presence in other chordate lineages, sequences from Mus , Fugu and Ciona were identified and added to the alignment and phylogenetic analysis. An annotated ADAMTS homolog from the honeybee Apis mellifera was also included in the analysis as another representative invertebrate. 571 unambiguously aligned amino acid sites of ADAMTS -homologous sequences encoded by Homo , Mus , Fugu , Ciona , Apis , Drosophila and Caenorhabditis were analyzed (Figure 2 ). MrBayes3.0 [ 80 ] was used to construct a maximum likelihood (ML) phylogenetic tree from this protein alignment. MrBayes was run for 1000000 generations, with four incrementally heated Markov chains, and a sampling frequency of 1000 generations. The temperature setting was increased to 0.5. Among-site substitution rate heterogeneity was corrected using an invariable and eight gamma-distributed substitution rate categories and the WAG model for amino acid substitutions [ 81 ], abbreviated herein as WAG+I+8Γ. The consensus ML tree topology, the arithmetic mean log-likelihood (lnL) for this topology, and branch support were estimated from the set of sampled trees with the best posterior probabilities. Means and 95% confidence intervals for the gamma distribution shape parameter α and the proportion of invariable sites (pI) were also estimated. List of abbreviations ADAMTS ( A D isintegrin-like and M etalloprotease with T hrombo s pondin motifs) ADAM ( A D isintegrin-like and M etalloprotease) TSR ( T hrombospondin type 1 S equence R epeat) MMP ( m atrix m etallo p rotease) ECM ( e xtra c ellular m atrix) SAGE ( s erial a nalysis of g ene e xpression) TTP ( t hrombotic t hrombocytopenic purpura ) IL ( i nter l eukin) TGF ( t ransforming g rowth f actor) TNF ( t umor n ecrosis f actor) BLAST ( B asic l ocal a lignment s earch t ool) Authors' contributions ACN and EGVM initiated the project and all authors were involved in the design phases. ACN, SBM and JML inferred sequences of previously un-annotated ADAMTS genes from Genbank, Celera, and JGI, and determined intron positions. SBM performed the phylogenetic analyses. ACN and SBM drafted the manuscript and JML and EGVM contributed to writing the paper and advised throughout. Supplementary Material Additional File 2 Alignment used for phylogenetic analyses of animal ADAMTS homologs. Unambiguously aligned amino acid sites, indicated by the "mask" line in the alignment, were used for phylogenetic analyses (Figure 2 ). Accession (GI) numbers for sequences are provided. Intron positions in the corresponding genomic sequence are indicated, with color-coding for intron phases (Figure 3 ). Click here for file Additional File 1 Alignment used for phylogenetic analyses of human ADAMTS proteins and invertebrate homologs. Unambiguously aligned amino acid sites, indicated by the "mask" line in the alignment, were used for phylogenetic analyses (figure 1 ). Intron positions in the corresponding genomic sequence are indicated, with color-coding for intron phases (Figures 3 and 4 ). Click here for file

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Who Pays for Open Access?

Publication fees are not borne purely by authors, but are shared by the many organizations whose missions depend on the broadest possible dissemination and communication of scientific discoveries

In the wake of declarations supporting open access to research literature from international bodies including the Organization for Economic Cooperation and Development (OECD) and the United Nations' World Summit on the Information Society (WSIS), advocates and critics of the movement appear to have agreed that the issue warrants a robust, ongoing dialogue—a development undoubtedly in the interest of the scientific community, regardless of its ultimate outcome. To the extent that listserv messages, editorials, and conference presentations are representative of more widespread reactions to the debate, there appear to be a number of common misconceptions about what open access is and what problems it can or cannot solve. Over the next few months in PLoS Biology , we plan to explore the more pervasive of these misunderstandings, in an effort to expose the real challenges that need to be overcome and to identify some possible solutions. Here we address the first of these—the perception that the publication-charge model puts an unfair burden on authors. Subsequently, we will address concerns about the long-term economic viability of the open-access model, the integrity and quality of work published in open-access journals, and the effect that open access will have on scholarly societies. Publication Charges—Nothing New By charging authors a fee to have their work published in lieu of charging readers to access articles, open-access publishers such as the Public Library of Science (PLoS) and BioMed Central (BMC) have transformed the traditional publishing system. This reliance on a seemingly untested revenue stream has generated skepticism that authors will be both willing and able to pay publication charges. Publication fees are not a phenomenon born of the open-access movement. Many authors regularly pay several thousands of dollars in page charges, color charges, correction costs, reprint costs, and other fees to their publisher, even when such costs are entirely voluntary. In the EMBO Journal , for example, authors are allowed six pages of text free, but are then charged $200 per page beyond that. A review of recent issues shows that almost all authors exceed six pages, voluntarily paying on average over $800 to publish their articles. Furthermore, in addition to paying other publication charges, authors may be willing to pay extra for their articles to be made open access, as several publishers have recently recognized. A recent survey of authors in the Proceedings of National Academy of Science ( PNAS ) found that although PNAS already makes its content freely available after six months, nearly 50% of PNAS authors expressed a willingness to pay an “open-access surcharge” of $500 or more to make their papers available for free online immediately upon publication—this above and beyond the $1,700 in page charges that the average PNAS author already pays ( Cozzarelli et al. 2004 ). Although we recognize that authors who submit to PLoS Biology may well be a self-selected group of enthusiastic open-access supporters, we have found that nearly 90% of those who submit manuscripts do not request a fee waiver, and the few who do still offer to pay some portion of the fee. The concern about authors' ability to pay publication charges will become less pressing as governments, funding organizations, and institutions increasingly support open-access publication on their researchers' behalf. More funding agencies are joining the Howard Hughes Medical Institute, the Wellcome Trust, and others who have already designated funds for open-access publication. (For more information about these funders' announcements and other international policy statements relevant to open access, see http://www.plos.org/openaccess .) Universities, too, are supporting open access directly by setting aside funds for open-access publication through institutional memberships with BMC and PLoS or through discretionary funds that faculty can tap into to pay publication charges. Such approaches reduce authors' reliance on individual grants to support charges directly and ensure equal access to publishing options that require such payments. The Disenfranchised Even with the steady increase in sources to pay publication fees, detractors claim that open-access publishing may lead to a situation in which some authors are simply unable to publish their work due to lack of funds. The response to this concern is that the ability of authors to pay publication charges must never be a consideration in the decision to publish their papers. To ensure that this happens, PLoS has a firewall in place such that neither the editors nor the reviewers know which authors have indicated whether or not they can pay. Because all work judged worthy of publication by peer review should be published, any open-access business model should be designed to account for fee waivers, just as publishers have always absorbed some authors' inability to pay page and color charges. PLoS grants full or partial publication-charge waivers to any author who requests them, no questions asked. In part, the savings to institutions, hospitals, nongovernmental organizations, and universities provided by open-access publications could help to establish funds for researchers who are less well supported. In the developing world, as free online access to scientific literature is increasingly seen as a political imperative, organizations such as the World Health Organization, the Oxford-based International Network for the Availability of Scientific Publications, and Brazil's SciELO are likely to become more willing to pay open-access publication charges for authors who cannot afford them. The Open Society Institute (OSI) already pays such costs for universities and other organizations in a number of countries in which the foundation is active by way of a PLoS Institutional Membership that grants waived publication charges to authors while providing compensatory revenue for PLoS. Perhaps the real misconception about the unfair burden that open access places on authors resides in the terminology—the term “author charge” is itself misleading. Publication fees are not borne purely by authors, but are shared by the many organizations whose missions depend on the broadest possible dissemination and communication of scientific discoveries. Some of those may provide funding for open-access publication as intermediaries between authors and journals, as OSI does. Others—including many government-financed funding agencies—do so directly through their research grants to scientists. In both cases, funding open access is an effective way to fulfill mandates for public access to and accountability over scientific research and to ensure that all worthy research is published.

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549547

Recent Hits Acquired by BLAST (ReHAB): A tool to identify new hits in sequence similarity searches

Background Sequence similarity searching is a powerful tool to help develop hypotheses in the quest to assign functional, structural and evolutionary information to DNA and protein sequences. As sequence databases continue to grow exponentially, it becomes increasingly important to repeat searches at frequent intervals, and similarity searches retrieve larger and larger sets of results. New and potentially significant results may be buried in a long list of previously obtained sequence hits from past searches. Results ReHAB (Recent Hits Acquired from BLAST) is a tool for finding new protein hits in repeated PSI-BLAST searches. ReHAB compares results from PSI-BLAST searches performed with two versions of a protein sequence database and highlights hits that are present only in the updated database. Results are presented in an easily comprehended table, or in a BLAST-like report, using colors to highlight the new hits. ReHAB is designed to handle large numbers of query sequences, such as whole genomes or sets of genomes. Advanced computer skills are not needed to use ReHAB; the graphics interface is simple to use and was designed with the bench biologist in mind. Conclusions This software greatly simplifies the problem of evaluating the output of large numbers of protein database searches.

Background Advances in technology have increased the speed and reduced the cost of DNA sequencing. This has resulted in a dramatic increase in the number of sequences contributed by both large sequencing centres and individual laboratories to sequence databases. Public biological sequence databases are growing at an ever-increasing rate, with 9 million new sequences being added to GenBank from August 2002 to August 2003 alone [ 1 ]. Currently, the GenBank database has almost 42 billion nucleotides from over 32 million sequences. The number of whole genome sequences of eukaryotes, prokaryotes and viruses is also increasing rapidly. Accordingly, tools like NCBI BLAST, which search those databases for sequences similar to a given query sequence, return larger and larger sets of results. Sequence similarity searching is a powerful tool to help develop testable hypotheses in the quest to characterize genes and other DNA sequences and infer structural, functional or evolutionary relationships. Researchers interested in identifying new matches to query sequences, which may be a few genes or even whole genomes, must search through massive amounts of alignment data to retrieve new and interesting matches. In order to keep up with the growing databases, the researcher must submit the same queries periodically. However, the new results, no matter how significant, are often buried in a long list of results that were previously obtained on past searches. ReHAB (Recent Hits Acquired from BLAST) is a new software package that was developed to address these problems. ReHAB performs PSI-BLAST [ 2 ] searches of a protein sequence database and keeps a database of all significant alignments (" hits ") obtained; these searches are performed on a regular schedule against updated versions of the sequence database. It then compares the sequences in the new PSI-BLAST result with the ReHAB hits database to identify new matches resulting from recently deposited sequences. The complete ReHAB hits database can then be queried by date using a simple GUI to allow the researcher to easily identify new hits ; these are highlighted, and pairwise or multiple alignments can be performed to assess the quality of the match. As well as filtering out results that have been found previously, the ReHAB browser can filter out hits against sequences that are identical to the sequences being submitted as queries (such as orthologs of the query sequence). ReHAB is designed to be a practical tool for searching NCBI database updates with large numbers of query sequences. For example, our laboratory uses it with all open reading frames (ORFs) from fully sequenced poxvirus genomes (over 7000 query sequences). As the number of sequenced virus genomes continues to increase, the number of hypothetical ORFs of unknown function also expands. This is particularly true for large viruses like poxviruses, baculoviruses, and herpesviruses that possess many virulence genes that are not part of the core set of genes that define a virus family [ 3 ]. There are also numerous core genes for which no known function has yet been identified; for example, of 49 completely conserved protein families in poxviruses, there are 11 with completely unknown function and at least 5 others with only poorly defined function. Other programs have been previously created to deal with this particular issue, including DBWatcher [ 4 ], SEALS [ 5 ], Swiss-Shop [ 6 ], Sequence Alerting System [ 7 ] and BLAST Search Updater [ 8 ]. However, WWW-based programs are not well suited to searching with large numbers of query sequences, and there may be concerns with a shut-down of service (as occurred with Sequence Alerting System) or allowing proprietary data out of a secure network. Other programs may be complicated to use, or require users to directly interact with UNIX operating systems. ReHAB is specifically designed for searching with large numbers of query sequences and can support a number of research groups; it also provides a user-friendly graphical interface. The client will run on most major operating systems including Mac OS X, Windows, Linux and Solaris. Implementation Design rationale ReHAB was implemented for the Java platform to simplify the support of multiple operating systems including Linux, Microsoft Windows, Solaris, and Mac OS X. Users initially access and launch the application (client) from a web page using Java Web Start, which also automatically downloads updated versions as they become available. This ensures users are taking advantage of improvements or added features in the latest software version. Furthermore, coding in Java allows interoperability with existing applications developed in our laboratory, including Base-By-Base [ 9 ]. Our choice was reinforced by past successes with the Java platform and Java Web Start for implementation and distribution of programs such as VOCs [ 10 ], VGO [ 11 ], and Base-By-Base [ 9 ]. Components ReHAB consists of four main components (Figure 1 ): (1) a MySQL relational database that stores information about hits , including biological sequences, alignments between them, and other categorization and annotation data; (2) a Java server that provides access to programs which cannot be run locally by the client on arbitrary user workstations, such as NCBI BLAST and EMBOSS [ 12 ] utilities; (3) a Java Swing graphical client, downloaded and launched on client machines using Java Web Start; (4) and a back-end Java program which runs alignment programs and compiles results in the database. Each of these components is described in more detail below. Although all components can be run on a single machine, it is envisioned that a single server will support a variety of users dispersed on an intranet or the Internet; if required, it is simple to offload the batch database searching to a more powerful cluster or grid system. Hits database There are four types of information stored in the ReHAB database: (1) biological sequences and their annotations, both those used as queries in BLAST searches and those which have been returned as hit subjects; (2) information on each query/subject pair ( hit ), gathered from individual search results and alignment programs (including bit-score, date entered, and percent identity); (3) organizing information, such as which query sequences belong to which organisms; and (4) other caching information, used to speed performance of server-side program functions. To reduce the amount of required storage space, actual alignments are not stored, but are regenerated for presentation when the user selects the specific query sequence or query-target pair to be viewed. Query sequences, which are entered using a simple FASTA-like format that includes additional annotation information in the identifying line, need only be submitted once to ReHAB since they are stored for future search cycles. Back-end processing The work of running PSI-BLAST searches is done in batch mode by the NCBI blastpgp program against a local copy of the NCBI non-redundant (NR) protein database. PSI-BLAST is performed for three iterations without filtering procedures (such as for low-complexity regions). Hits with an E-value less than 0.001 are used to generate the scoring matrix for the subsequent cycle. To increase speed, searches with query sequences that result in no new hits are terminated after the first cycle. Those with new hits scoring below the threshold continue to the third cycle. PSI-BLAST was chosen because it is a more sensitive search method than BLASTP. The searches do not need to be performed on the same machine on which the database or server components are installed. XML output from blastpgp is parsed and relevant information about each hit is stored in the ReHAB database. In addition to scores and identifying information, target sequences are copied into the ReHAB database to ensure that they are available for analysis in the future, even if they are no longer available from NCBI. This is important because, although NCBI does not actually remove sequences from its database, it may change the identifier of a sequence if it is corrected, updated, or merged with another identical entry. Any changes to a pre-existing entry are added to the database, but it is not registered as a new hit. Server The server component consists of Java RMI classes that provide remote access to local facilities, and a loading program that registers those classes with an RMI Registry installed on the server from which the client will be downloaded. Requirement for the server is a system that can support Java 1.4.1 and MySQL 4.0. Client GUI The Java Swing client component allows a user to browse the information collected in the database by the back-end program. When the client is downloaded and launched from a website, it connects to the server and database specified in its configuration file. The client program visually presents summary information about hits added to the database, and allows the user to quickly locate new, relevant hits and the sequences involved. There are five main views available in the client: (1) The management console lists the available databases, and has options for creating new databases or adding files to existing databases, (2) The Hits Browser window lists the organisms for which query sequences have been added in the database, and allows users to select filtering and highlighting options, (3) a Hits Summary, which displays the results in a table with highlighting to mark new hits, and (4) an HTML output or (5) a Hits Manager that displays detailed information about retrieved sequences and alignments. Results and discussion Finding new hits ReHAB is a tool that works with BLAST to identify new hits in updated versions of sequence databases. It allows the researcher to ask the question: " what new sequences match my sequences since the last time I searched?" In the example of our work, the query sequences are all the ORFs of the fully sequenced poxvirus genomes (36 genomes, 7075 query sequences). These sequences are used to query the NR NCBI protein database and a MySQL database of all hits is generated and stored (Figure 2 ). Databases of hits for other virus families maintained by The Virus Bioinformatics Resource (TVBR; herpesviruses, baculoviruses, coronaviruses, and adenoviruses) will also be available in the near future. The hits database can then be accessed by double-clicking on the database name or by selecting " browse by organism " in the Action menu. This opens a new window to present browsing, sorting, and highlighting options (Figure 3 ). The user can browse by organism name, such as " Variola Virus strain Bangladesh-1975 ". To highlight recent hits , the " date option " is chosen to define the date after which the hits are considered new. The available dates are those on which the query sequences were searched against a then current NR NCBI database. The output can be sorted based on three criteria (name, new hit date, or maximum new hit bit-score) by selecting the appropriate radio button. The results are presented in a new window, using colors to indicate new hits (Figure 4 ). Since all new hits are not necessarily significant, results are highlighted in different colors depending on the bit-score. The user can change the default threshold of the minimum bit-score, to show new hits scoring above this cut-off in red and new hits scoring below it in yellow. Since all query sequences that have new hits are highlighted, any that remain unhighlighted do not have new hits . However, unhighlighted queries may have significant hits from previous searches. The " Latest Hit " column indicates this fact: query sequences showing hits only from previous searches show an older hit date, and a bit-score of "0" in the " New Hit Score " column. Unhighlighted sequences with no information in the " Latest Hit " column do not have any hits in the database or they have been filtered out (see below). Information about the hits can be viewed in two ways. Selecting " HTML Report " launches the user's default web browser and displays the " hit-list " in familiar BLAST-style (Figure 5a ). Hits are displayed in descending order of bit-score, however, a key feature of this program is that new hits are highlighted in red or yellow. The pairwise alignment can be displayed rapidly by clicking on the score (a hyperlink). In contrast to the usual BLAST output, which presents the local alignment found by BLAST, a global alignment produced by Needle [ 12 , 13 ] is shown. More information can be obtained about the target sequence by clicking on the link to the NCBI file for that entry. Alternatively, a full list of hits can be viewed in the " Hits Manager" window (Figure 5b ). Here, sequences can be sorted by highlight, and pairwise or multiple alignments can be performed. Pairwise alignments are displayed by selecting a single target sequence and clicking the " Global " button for global alignments produced by the EMBOSS program Needle or the " Local " button for local alignments generated by the EMBOSS program Water [ 12 , 14 ]. Multiple alignments are generated by selecting more than one target sequence and clicking the " Base-By-Base " button; the software automatically retrieves the appropriate sequences from the ReHAB hits database, performs a ClustalW alignment and passes the resulting multiple alignment to Base-By-Base, which functions as an alignment viewer and editor [ 9 ]. Finally, sequences in the Hits Manager can be viewed in FASTA format by clicking the " Show " button and can be copied from this window using standard keystrokes. Filtering out identical sequences Unless a sequence has not been deposited in the public database, a sequence similarity search will return results including the query sequence itself, as well as nearly identical sequences that are orthologs of the query. ReHAB can block the highlighting of hit sequences that are also present in the query database when the " Don't Show My Own Sequences " option is selected; such sequences will not be shown or highlighted in the Hits Results window. However, these sequences and their alignments with the query can still be visualized in the HTML Report and Hits Manager windows, thus allowing the user to access all the available information. This feature becomes essential when new poxvirus genomes are added to the public database, since a large fraction of the queries will hit proteins in the new genome and signal a " new hit " report when there may be no other new hits in the database. Although these are clearly high scoring matches, they are expected and therefore must be masked in the analysis if the full value of ReHAB is to be realized. Browsing by other criteria In the browser window (Figure 3 ), the user can chose to browse by the annotation included in each sequence's information line. In the case of our poxvirus sequences, useful annotations are organism name and protein family (as determined in POCs [ 10 ]). Selecting an item from the " Group by Annotation " list loads the new category in the list on the left side of the window. This sorting allows the user to quickly find query sequences of particular interest. For example, one may be interested in looking at only sequences from the Ankyrin family. Results can then be viewed and analyzed as described above. Setting up ReHAB with user selected sequences Researchers can use ReHAB to search databases with their own set of query sequences. In the example of our research, it is most practical to organize the query sequences by organism and protein family. Other researchers, however, may find other naming schemes to be more useful; no changes to the program or database are required. For example, a research group could organize query sequences and the hits results databases by laboratory name, and browsing of results could be by the researcher's name (Figure 6 ). Individual laboratory members would add query sequences to the database including their name in the identifying information line. In this example, the laboratory name would replace virus family , and user names would replace organism names . All query sequences would be searched in the same batch process, and each individual could then browse their sequences of interest. Users interested in establishing their own ReHAB database should contact the authors for assistance. Conclusions The goal of this project was to build a software package to aid in the identification of new results returned from sequence similarity searches. To this end, we developed ReHAB, a tool that highlights new hits by comparing results from previously run searches to those with a recently updated database. ReHAB allows researchers to query the NR protein database with large numbers of sequences and can highlight, sort, and analyze results in a user-friendly graphical interface. It can also be used to rapidly create multiple alignments with any set of sequences returned by a BLAST search. This enables researchers to recognize new significant sequence matches in the mass of results generated by high throughput database search protocols. Availability and requirements Project name: ReHAB Project home page: Operating systems: All platforms supporting Sun's JRE version 1.4.1 or compatible Programming languages: Java, SQL Other requirements: Java 1.4 or higher License: GNU General Public License Restrictions for non-academic use: Contact corresponding Author Authors' contributions CU described and specified the features of and problems to be solved by ReHAB, tested the program and provided usage examples. JW implemented the software, both the Java components and the database schemata used to store alignment results. DJE tested the program and provided usage examples. All authors contributed to writing of the manuscript.

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539275

Performance of a genetic algorithm for mass spectrometry proteomics

Background Recently, mass spectrometry data have been mined using a genetic algorithm to produce discriminatory models that distinguish healthy individuals from those with cancer. This algorithm is the basis for claims of 100% sensitivity and specificity in two related publicly available datasets. To date, no detailed attempts have been made to explore the properties of this genetic algorithm within proteomic applications. Here the algorithm's performance on these datasets is evaluated relative to other methods. Results In reproducing the method, some modifications of the algorithm as it is described are necessary to get good performance. After modification, a cross-validation approach to model selection is used. The overall classification accuracy is comparable though not superior to other approaches considered. Also, some aspects of the process rely upon random sampling and thus for a fixed dataset the algorithm can produce many different models. This raises questions about how to choose among competing models. How this choice is made is important for interpreting sensitivity and specificity results as merely choosing the model with lowest test set error rate leads to overestimates of model performance. Conclusions The algorithm needs to be modified to reduce variability and care must be taken in how to choose among competing models. Results derived from this algorithm must be accompanied by a full description of model selection procedures to give confidence that the reported accuracy is not overstated.

Background When Petricoin et al. [ 1 ] published their analysis using serum to distinguish individuals with ovarian cancer from individuals with benign conditions, it suggested great promise in using high throughput mass spectrometry to improve upon existing biomarkers for patient groups that could greatly benefit from accurate and early diagnosis. Results from the analyses using this algorithm have, along with early findings from other groups (e.g. [ 2 , 3 ]), fueled an explosion of interest in using mass spectrometry techniques for quick and accurate diagnosis. Many other investigators have since used classification techniques to achieve impressive results in correctly categorizing unlabeled mass spectrometry samples as either diseased or healthy. Among the more common classification methods used are classification trees [ 2 ], boosting [ 4 ], stepwise discrimination methods [ 5 ], and wavelet discrimination [ 6 ], though few have used a genetic algorithm. Baggerly et al. [ 7 ] do use a genetic algorithm though its properties are substantially different than that used in the earlier studies and is generally not subject to the conclusions drawn below. Here we evaluate the performance of a genetic algorithm described in the original Lancet paper and subsequent studies [ 8 , 9 ]. Description of the algorithm The specifics of the genetic algorithm used here are based on webpages at the NCI-FDA website housing the data [ 10 ] and [ 1 , 9 ]. As the descriptions are limited, this attempt to reproduce the algorithm may differ from the implementation supporting the published results. • As described, the genetic algorithm (GA) seeks to find a collection of markers that separate cases and controls. Here the markers correspond to a biological sample's measurements at a given set of m / z values. In the GA framework such a collection of markers is called a chromosome. Each chromosome is evaluated by a fitness function in the following way. Suppose a given chromosome is composed of N "genes" (i.e. N m/z values in this case). Each sample's intensity values at the N genes are linearly scaled to lie between 0 and 1; the smallest of the N intensities is assigned 0, the largest assigned 1, and intermediate values interpolated in a linear way. The first sample is assigned its own cluster with centroid (i.e. mean values) given by its N values. The next sample is compared to the first and if the Euclidean distance between the two samples exceeds .1· then the second sample is assigned a new cluster with centroid given by its values. If the distance is less than this limit the second sample is assigned to the first cluster and the centroid values recalculated as the mean of both cases. Subsequent cases are handled similarly – if a sample's representation as an N dimensional point lies within the .1· limit of a cluster the case is assigned to the closest cluster and centroid values are recalculated. If the smallest distance to any cluster centroid exceeds the limit then the case is assigned a new cluster. When all the cases are clustered a cluster's type is designated by majority vote – those clusters composed mostly of cancer cases are deemed cancer clusters and those composed mostly of nondiseased are likewise defined. The fitness function then computes the chromosome's fitness as its classification accuracy, i.e. the proportion of cases assigned to a cluster of the appropriate type. • The selection process starts with 1500 randomly chosen chromosomes, i.e. sets of markers. The documentation indicates that chromosomes with length between 5 and 20 markers are used. In this implementation, different chromosomes may have different lengths – the 1500 are chosen to have a length between 5 and 20 with a uniform probability of 1/16 governing the choice. It is not clear how the original GA treated chromosomes of different length. Each of the 1500 chromosomes is evaluated by the fitness function as described above. Chromosome pairs are then produced with the likelihood of being selected for a pair related to the fitness function. The available documentation does not make clear how this probability is explicitly related to the fitness. Here the choice was made by ranking the fitness scores and setting parameters α and β such that Prob [ selecting k th ranked chromosome ] = α + β k where α and β were chosen such that This approach is described in section 2.1 of [ 11 ] – ranking is preferred to absolute fitness values as it avoids some potential problems with scaling. An alternative method based on absolute fitness values produced qualitatively similar findings (results not shown). • A new generation of chromosomes is produced by first creating 750 parent pairs from the set of 1500 chromosomes. A parent pair is created by choosing two of the 1500 chromosomes using the above probabilities. A given chromosome can be chosen to be in more than one pair. For a given pair each chromosome is broken to produce two sub-chromosomes. The location of the break is random with uniform probabilities. The two sets of sub-chromosomes are then crossed-over to produce two new chromosomes. As an example suppose chromosome 1 has genes = (3001, 5500, 7800, 11011, 13059) and chromosome 2 is composed of m / z locations = (2500, 4200, 909, 15002) and the first chromosome breaks between its second and third elements while the second chromosome breaks after its third. Then the resulting new chromosomes are (3001, 5500, 15002) and (2500, 4200, 909, 7800, 11011, 13059). In this way the 750 pairs of chosen chromosomes produce a next generation of 1500 chromosomes. At this point each gene in each new chromosome may be randomly changed to any other gene in the entire spectrum range with probability .0002 (this corresponds to genetic mutation). In our implementation it is possible to match sub-chromosomes that would merge to be longer than 20 units. In this event the chromosome is truncated to 20. Further, here it is allowed to have chromosomes composed of as few as 2 markers as there seemed no compelling reason to impose a lower limit of 5 m / z values as described in the documentation. It is unclear if the original GA allowed chromosomes of different lengths to reproduce or instead restricted cross-overs to pairs with the same length. • After mutation this new generation of 1500 chromosomes is then evaluated by the fitness test and then another round of selection, cross-over, and mutation processes produce the next generation. Typically, the average fitness of generations increases over time. According to the documentation, the process stops 1) after 250 generations, or 2) when a perfectly discriminating chromosome is found. In the first instance, that model that has produced the highest fitness score is chosen. • Given a chosen model derived from a training set, an unlabeled spectrum (e.g. test set spectrum) is classified by determining that cluster with the centroid that lies closest to the unlabeled case and assigning the label of the cluster. The documentation describes a second, related approach that is to make this assignment only if the nearest centroid is with .1· ; otherwise assign the case as of a third, unknown/new type. In this current work, classification errors for a test set correspond to the first criteria of nearest centroid, without the .1· requirement. Empirically, this led to greater classification accuracy. Some concerns about this algorithm have been raised by others [ 7 ]; a few issues will be examined below in more detail. • Each chromosome is evaluated by a fitness function that measures how well the chromosome classifies the training set. However it is clear that the order in which the cases are considered may make a difference in what cluster a case is assigned as well as the clusters' centroid values. Consequently, different results may arise in attempts to replicate findings. • The GA algorithm starts with a random selection of 1500 chromosomes and then letting these evolve through a random mating process. As the initial selection and evolutionary process is random it is again the case that different ultimate models may be chosen, depending on the seed of a random number generator. • In this application, each chromosome partitions the samples of the training set into clusters defined as groups of cases with centroids that are at least .1· apart from one another. It is not uncommon to find chromosomes that partition perfectly, but rely upon a large number of clusters (e.g. > 30). This suggests overfitting of data. As described, this algorithm does not penalize or otherwise take into account the number of clusters or length of chromosomes. Largely because of insufficient information, this implementation of the algorithm likely differs from that supporting the published results. However, some elements should be the same. In particular, the evaluation of the fitness function should yield the same results except for the issue of how the order of the cases can change the clusters' attributes. Therefore, we should be able to match or come close to verifying the published results for a given model. However, our results are likely to be different as far as generating best models. This is in part due to the inherent randomness the process employs as well as possible differences in how the fitness function scores generate members of the next generation. Datasets Two publicly available datasets were used to evaluate the algorithm; information regarding them is available from an NCI-FDA website [ 10 ]. Both datasets consist of ovarian cancer patients and healthy controls. The first dataset, hereafter referred to as DS1, contains "low resolution" mass spectrometry data from a Ciphergen instrument and is identified on the NCI-FDA website as the 8-7-02 data. The data consist of 162 ovarian cancer samples and 91 control samples. The second dataset, DS2, contains "high resolution" data from a hybrid quadrupole time-of-flight spectrometer. Description and analysis of these data are available in [ 12 ]. The dataset contains spectra from 121 cancer samples and 95 controls. For both datasets GA-produced models are presented on the NCI-FDA website that were developed from a training set and perfectly discriminate a test set. There is no designation as to which individuals were used for training and which for testing. Results The NCI-FDA website shows the chromosome consisting of m / z values {435.46, 465.57, 2760.67, 3497.55, 6631.70, 14051.98, 19643.41} was able to perfectly discriminate a test set drawn from the low resolution dataset, DSl. The 253 samples were randomly split into a training set of 81 cancer and 46 control individuals with the remainder forming a test set. Here we illustrate how the test set looks for these seven markers. Figure 1 shows the ratio of the second marker (molecular weight of 465.6) to the first (weight of 435.5) does an excellent job in separating the two types of samples in the test dataset. In the training set only two clusters were determined – one composed completely of cancer cases and the other solely of controls. In the test dataset one sample is misclassified (essentially because of its values on the remaining 5 markers) though it should be again pointed out that the number of misclassifications does vary by the order in which samples are processed and how the cases are split into test and training sets. Ten consecutive trials in which different test/training splits and ordering decisions were randomly made produced 1, 0, 0, 0, 0, 0, 0, 0, 5, and 1 errors (all misclassifications of normal as cancer) for this 7 marker model. This exercise verifies that the model does quite well though it establishes that results do change with ordering and test/training set splits. Also, it confirms that results of 100% accuracy should be understood to depend upon the particular split and ordering. This may be of great importance when the goal is to develop tests with sensitivity and specificity exceeding 99% [ 12 ]. Next, the GA developed for this paper was then applied to these data with the expectation it should produce something like the 7 marker chromosome given above. After 7 generations, a chromosome was found that perfectly split the training set, but 7 clusters were required and 10 markers were used. The graph of test set classification, Figure 2 , shows a less compelling picture of discrimination; the third marker is perhaps best (based on t-test p-values) at distinguishing samples. This marker corresponds to a molecular weight of 831.1 Daltons. To examine robustness the algorithm was run 9 more instances using different initial sets of 1500 chromosomes to try to get a sense of the variation in the algorithm's chosen models. The same ordering, test samples, and training samples were maintained. In each case a perfectly discriminating (i.e. training set error of 0%) chromosome was found within a few generations. Table 1 shows that there is considerable variation in the test set accuracies given they were all produced by the same data. Further, the best discriminating single marker within the chosen chromosome shows little consistency. Also, the set of 10 generally shows a large number of clusters and markers – nothing very similar to the published model that contained only two clusters. The results in Table 1 suggest there are many markers that are different in these data and it is easy to find classifiers that performs well – at least in the training set. However, it is also clear this creates a kind of algorithmic instability in that considerable variation in results can arise from the same training set data. Even if one uses a fixed training/test set division there is now a question of how does one decide which results to use? One could run the algorithm just once, but run the risk of choosing a not very good model (e.g. the model with 24 clusters and 16 markers). However, if the algorithm is run many times in the search for a good model, the reported sensitivity and specificity in the test set are likely to be biased. This question will be pursued further in the Discussion section below. Table 1 and the preceding discussion of variation suggest this implementation of the algorithm might be improved by changing the procedure to favor models with fewer clusters/markers. In this way, those models that may overfit the training data are penalized and the number of perfect discriminators of the training set consequently reduced. A simple way of doing this is to alter the fitness function to penalize large numbers of clusters and/or markers. In the analysis above the fitness function was given as Fitness = Accuracy = % Correctly classified cases. This could now be modified to Fitness = % Correctly classified cases - p 1 ·# of clusters - p 2 ·# of markers where p 1 and p 2 are non-negative penalization weights. A resampling method was used to determine the performance of different parameter combinations of p 1 among {0, .002, .005, .008} and p 2 in {0, .001, .002}. Specifically, random training samples (chosen without replacement) were selected from the entire set of samples so the original training sample size of 127 was maintained with 81 cancer and 46 control spectra. Then, for a given pair of p 1 and p 2 values the GA was trained on this pseudo-random training set and a model chosen. The remaining cases that were omitted from the training set (81 cancer and 45 control) were then treated as a test set. We repeat this procedure for 50 randomly chosen training sets and examine the distribution of the test set classification accuracy for the different parameter combinations. The same 50 training and test sets were used for each set of p 1 and p 2 combinations. In addition to illustrating the test set accuracy, the number of clusters, the number of markers associated with the different GA models, and the proportion of times (out of 50) a perfectly discriminating chromosome was found (for the training set) are also indicated. This procedure gives a sense for the performance of the algorithm for different parameter combinations. Another question concerns performance if model selection were incorporated into the procedure. This was assessed in the following way. For each of the 50 training sets, an additional 5-fold cross-validation determined which of the 12 p 1 and p 2 combinations performed best in terms of predicting the omitted cases (in the event of ties the model associated with the most restrictive p 1 and p 2 was chosen with p 1 the first tie-breaker). The chosen parameters were then used with the entire training set to develop a model that was evaluated on the associated test set. As before, this procedure was performed on the same 50 training and test sets. In the tables that follow, the results for this model are labeled as "Best GA". These results are perhaps most representative of overall performance for the algorithm developed here. As a means of comparison two other classification schemes were applied to the same bootstrap samples. Boosting is a general method of combining a weighted set of classifiers that each "vote" on the class of a sample in question with majority vote dictating the set's aggregate classification. It has been successfully used in classification of mass spectrometry data [ 4 , 13 ]. Here, the base classifier is a simple threshold classifier, e.g. if intensity at mass 245.8 ≤ 47.5 then classify as cancer, otherwise classify as normal. The general process by which the set of base classifiers is chosen is discussed at length in [ 4 ] and [ 14 ]. Here 150 was chosen as the number of base classifiers for the aggregate classifier and the algorithm generally followed that outlined in section 10.1 of [ 14 ]. The second algorithm used was PAM (Predictive Analysis for Microarrays), a shrunken centroid method of classification [ 15 ]. This method has been used for high dimensional microarray studies and is relatively easy to implement. Both methods require little operator assisted tuning to obtain a small feature set – an important consideration when conducting so many resamplings. For these methods the data were normalized (test and training sets normalized separately for each resampling) so each spectra had the same average intensity. Also, attention was restricted to those m / z values showing Bonferroni-corrected differential expression (calculated anew for each resampling). Computer code and information regarding the parameters and details of these methods are available on a webpage [ 16 ] with supporting documentation. Table 2 shows the 25 th and 75 th percentiles for test set accuracy among 50 samples as described above. The two penalty parameters have the desired effect in reducing the number of clusters/markers but there is relatively small variation over the different parameter combinations. The GA models apparently perform a bit better than PAM and a little worse than the boosting method though all models have high accuracy. Some reviewers of these data [ 5 , 17 ], have questioned why the groups are so easy to classify and whether the entire m / z range should be used. The criticism centers around the strong signals that are present in very low m / z values (e.g. 2.79 and 245.54 Daltons) that are speculated to be products of experimental procedures rather than reflective of biological differences. Other investigators [ 2 ] routinely exclude the lower end of the spectrum (less than 1500 or 2000 Daltons) as they feel it too contaminated by matrix and other effects to be clearly interpretable. As a result of these concerns the experiment was rerun with the m / z range restricted to be greater than 1500 Daltons. Table 3 is based upon the m / z restricted dataset and shows evidence of greater spread among the different GA models – those with p 1 = 0 or .008 do not appear to do as well as p 1 = .002 or .005. With no penalty on the number of clusters one sees very high dimensional models (median number of clusters > 90), perfect training set performance every time, and relatively poor test set performance indicating some type of penalization is necessary. Increasing the value of p 2 has the desired effect of yielding more parsimonious models without an obvious decline in performance. As before, the GA models seem to perform better than PAM but less well relative to the boosting model. Next, results from the high resolution dataset are presented. The data require preprocessing. Some samples contain raw data from approximately 370,000 m / z values in the 700 – 12,000 Dalton range while other samples have about 330,000 data points. This discrepancy is particularly worrisome as the cancer samples appear more likely to have fewer datapoints. The information presented at the NCI-FDA website and in [ 12 ] includes some discussion of how the data were aggregated. The implementation in this work is similar to that described at the NCI-FDA website – details are available at a webpage containing supporting material [ 16 ]. After aggregation, the resulting spectra containing 7106 points were normalized to have the same average intensity. We note (data not presented) that while the models for the high resolution dataset on the NCI-FDA website have relatively good test set performance (accuracy of about 95%) they entail a large number of clusters – typically between 30 and 50. This is in contrast to the model reported for the low resolution DS1 Ciphergen data that had two clusters. The results in Table 4 are quite similar to those reported for DS1 in the m / z > 1500 range in that poorly performing high dimensional models are associated with p 1 = 0 and the GA appears to again perform at an intermediate level. Discussion As implemented here, the genetic algorithm without penalties produces a large number of chromosomes that can perfectly discriminate a training set of the type considered here. For the last two analyses (DS1 with m / z > 1500 and DS2) those models produced with p 1 = 0 are associated with a large number of clusters (median ≥ 90), indicating that many clusters have only 1 or 2 individuals. As demonstrated above, a resampling approach shows that models with large numbers of clusters will generally not perform as well as more parsimonious chromosomes and the use of penalization parameters greatly improves performance. While this modification results in better models it does not address the other fundamental question of how to choose a final model. Because of their reliance on random choices GA models can and, for these data, will present very different solutions from a given dataset. Therefore, even if one uses a supplemental cross-validation process to choose some ideal set of penalization parameters many different models can be chosen by running the GA repeatedly. This is in contrast to many other means (e.g. boosting, discrimination methods) that have no such reliance on random processes and will produce the same answer given a fixed dataset and parameters. Some methods such as decision trees and PAM employ cross-validation as part of their fitting process and therefore do have a random component, but the results are not nearly so variable, at least for the data considered here. Next we explore some consequences when the GA is repeatedly applied to a fixed training and test set with the goal of finding "best" or superior models. Such repeated examination of test set performance violates the principal of evaluating the test set only after the model has been selected [ 14 ]. Consequences of repeated model fitting Given a model developed on a training set, the performance of such a model on an independent test set is an unbiased estimate of its performance when exposed to a subsequent group of unlabeled cases that are generated by the same process. However, the situation becomes more complicated when a collection of models is considered. It is generally not true that the best performing model (judged by which model attains highest test set accuracy) will reproduce similar results on a yet another group of cases. Essentially, while every model has a true error rate, its performance on a particular test set is a function of both the true error and random variation. The best performing model is likely the beneficiary of positive random variation that is unlikely to be repeated in application to yet another set of data. In this sense the best performing model has an underestimated error rate when the selection of the best model is performed via repeated examination of a test set. We present a final set of bootstrap based analyses to illustrate the degree of bias. For DS1, 50 runs of the following type of experiment were performed. First, a bootstrap sample of size 253 with 162 cancer and 91 controls is drawn (the cancer and control individuals were bootstrapped separately from their respective cohorts). This is denoted as X b while the original cohort is X . This bootstrap sample is then split into training (81 cancer, 46 control) and test sets (81 cancer, 45 control). On the training part of the bootstrap sample the GA is run with p 1 = .005 and p 2 = .001. These parameters were chosen as they seemed to perform relatively well in Tables 2 , 3 , and 4 and they generally employed a smaller number of clusters and markers. The GA produced a model associated with this particular bootstrap sample, denoted . The performance of that model was then evaluated by the error rate in the test set portion of the bootstrap sample, denoted . Because the GA process produces different estimates when run on the same data due to randomness as described above, the model-fitting process is then repeated 19 more times on the same bootstrap sample to obtain 20 different models and 20 different measures of performance . The order of the training set and random sampling decisions made by the GA were allowed to vary though the composition of the test and training set were fixed for a given bootstrap sample. The best model, denoted , was chosen as that among the 20 with lowest classification error, . In the event of a tie, the number of clusters served as a tie-breaker (smaller is better). This procedure is meant to mimic the idea of applying 20 models to the test set and settling upon the best one. To get an idea of the bias in estimation error we then examine how the chosen, best model performs for the original cohort of 253 cases – this error rate is denoted as and the bias estimated by . This procedure was performed 50 times and one obtains an estimate of the distribution of the bias from in 1) DS1 using the whole m / z range, 2) DS1 restricting the range to m / z > 1500, and 3) DS2 with 700 < m / z < 12000 (using different corresponding sample sizes). The use of the bootstrap to assess bias in this way conforms to the notion of treating the full sample distribution like a population distribution and the bootstrap sample distribution like the full sample distribution – see chapter 10 of [ 18 ]. The results in Table 5 show the degree of bias is relatively modest in the first dataset – on the order of 2% and somewhat higher (median of 4–5%) in the other data under consideration. This may not be of great practical import unless one is particularly concerned that the specificity be near 100% to justify using such tests on the basis of widespread diagnostic testing [ 12 ]. The degree of bias is influenced by, among other things, the number of times the test set is interrogated – here the figure used was 20 and it may be that greater bias is associated with increased searching. This analysis could also have been performed by splitting the data into 3 datasets (training, test, and bias assessment groups) though these datasets are small enough that the bootstrap approach was preferred in that it makes more efficient use of the data. Generalizing results There is considerable controversy regarding these ovarian cancer datasets – particularly with respect to whether the multitude of models with high or perfect sensitivity and specificity are more the result of rich complexity reflecting true biological variation [ 19 , 20 ] or flaws in experimental design [ 5 , 17 ]. While it is of paramount importance to know if true biological difference or flaws in experimental design are primarily responsible for the ease with which classification algorithms can separate the cancer and normal spectra (especially the low resolution dataset with 0 < m / z < 20000 Daltons), the algorithms' performances will not change regardless of the answer to this question. Therefore, in the limited context of algorithmic performance considered here this critical issue is of secondary importance and not addressed. This observation indicates that these algorithmic analyses may still be valuable even if one believes the datasets to be flawed. It is interesting to note how the GA performed on these three different datasets and speculate on its performance in other circumstances. The results in Table 5 regarding bias arising from multiple applications of the GA do vary somewhat among the three datasets under consideration. Because the spectra in the full, low resolution dataset (0 < m / z < 20000 Daltons) are easiest to correctly classify (as seen in Table 2 ) this dataset shows the smallest degree of bias arising from multiple applications of the GA – the median bias is about 2% in Table 5 . Essentially the bias is low because the normal and cancer samples are so distinct and many models do very well. This is the case even though the multiple models may look very different from one another and use different primary m / z values to discriminate; in this case the bias is low because virtually all the dissimilar models do quite well. The truncated, low resolution dataset ( m / z > 1500 Daltons) was used to exclude the lower mass values that some [ 21 ] believe are difficult to interpret. Exclusion of these masses made the spectra harder to classify (see Table 3 ) and the associated bias in Table 5 was greater. The GA's performance in the high resolution dataset showed perhaps an intermediate level of difficulty in correctly classifying spectra (Table 4 ) and a corresponding intermediate degree of bias. The results suggest that as the spectra become easier to classify, the degree of bias due to repeated model fitting declines. This generalization is speculative in that it is based solely on these three related datasets and should be investigated in other datasets. Also, it should be pointed out that bias may be quite low in situations where there are only a few m / z values that can distinguish spectra. In this case one could speculate that repeated model fittings may identify primarily the same chromosome and therefore lead to very little bias. Conclusions This paper presents a genetic algorithm based on descriptions in earlier work. It was difficult to exactly reproduce performance of the original algorithm because important aspects were not well described and questions directed to the associated website were unacknowledged. Consequently, the GA's implementation described here is likely different than that made to produce the published findings. In particular, there are ambiguities concerning the manner in which more "fit" chromosomes are chosen to produce the subsequent generation, how chromosomes of different lengths may be produced and combined, and the possible use of penalization or other means to obtain parsimonious models. Despite these potential differences some aspects of the original algorithm's performance are likely shared with those of the model developed here. Some modification of the algorithm to guard against overfitting seems necessary to obtain good performance. In particular, defining the fitness function simply as training set classification accuracy produces models with too many clusters. Here, a penalization based on the number of clusters and markers was imposed that improved algorithmic performance. A cross-validation procedure was incorporated to choose the penalization parameters – this resulted in algorithmic performance similar to other classification schemes. Results based on this type of algorithm should be accompanied by a clear description of how individual models are generated, e.g. what penalization parameters or other means of reducing the number of clusters are included and how they were chosen. There is randomness and lack of reproducibility in model performance that depends on order of cases, random choice of initial chromosomes, and how the fitness function determines the subsequent chromosomes. Consequently, for a fixed training dataset, the algorithm can produce many chromosomes that perform well simply by repeatedly running the algorithm. There may be a temptation to use the algorithm repeatedly and evaluate test set performance to select the final model(s). While this can be a problem for classification algorithms in general, the random characteristics of this procedure may make it especially hard to resist. Here we saw some sense of the bias resulting from, such an approach. As the discussion regarding bias demonstrates, the reported sensitivities and specificities cannot be adequately assessed without very detailed description of the models' discovery. In this sense, those who employ such a scheme must supply complete information regarding the entire process used to choose the given models and users of algorithms that have this property of producing multiple models from a fixed dataset must be aware of this potential bias. Overall, once modifications have been incorporated to address the overfitting concerns, the algorithm's performance seems comparable to other methods. It should be noted that the final models produced by this GA are of a simple to interpret form that may be based on a small number of markers and clusters. This simplicity is not necessarily present for other algorithms (e.g. boosting, neural nets, support vector machines). This algorithm seems a reasonable option for creating discrimination models though it does have disadvantages that might guide analysts to choose a different approach. Methods Data sources The low resolution dataset, DS1, was obtained from a ProteinChip Biomarker System-II (PBS-II) surface-enhanced laser desorption ionization time-of-flight (SELDI-TOF) instrument produced by Ciphergen Biosystems, Inc. of Fremont, CA, USA using a WCX2 ProteinChip array, also produced by Ciphergen. Further details regarding sample handling and preparation are not readily available from the NCI-FDA website. While data from earlier low resolution datasets were available from the NCI-FDA website, these data (labeled 8-7-02) were chosen because the baseline does not appear to have been subtracted. As discussed by others [ 17 ] it does not appear possible to reproduce the original results of the genetic algorithm after baseline subtraction has been performed. The high resolution dataset, DS2, was obtained from a hybrid quadrupole time-of-flight mass spectrometer (QSTAR pulsar I , Applied Biosystems, Inc. Framingham, MA, USA) modified to read the WCX2 ProteinChip. Additional information regarding handling and preparation of samples is available in [ 12 ]. Normalization of the two datasets was performed differently. For the low resolution data the spectra were rescaled linearly so the smallest value was 0 and the largest was 1. This was described in an earlier document on the NCI-FDA website (since removed) and was the approach described in [ 17 ]. This transformation has no effect on the genetic algorithm since additional rescaling is done within each individual spectrum on a chromosome by chromosome basis. This may have some effect (relative to performing no normalization) on the boosting and PAM algorithms but it is likely to be quite small as the maximum value for each spectrum was 100 (except one which reported a max value of 99.75) and the minima lay between 3.75 and 3.95 – so the effect was nearly one of applying the same transformation to each spectrum. The PAM and boosting algorithms were implemented after an additional normalization step that equalized the average intensity for each spectrum. For the DS2 data, once the raw values were aggregated into 7106 bins the spectra were normalized to have the same average intensity. Here it seemed necessary to try to address the fact that the intensities for samples processed later were generally less than those processed earlier – see the QC document on the NCI-FDA website and [ 12 ]. Again, the normalization has no effect for the genetic algorithm. For the other algorithms it seemed important to try to address this temporal effect. Data processing Computing for all the classification algorithms (GA, boosting, and PAM) was done using the R programming language. Results for the PAM algorithm were obtained using the pamr package available from the R website [ 22 ]. On the website housing supporting information for this paper [ 16 ], full details are available showing the code and steps necessary to reproduce the findings presented in this paper.

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Textpresso: An Ontology-Based Information Retrieval and Extraction System for Biological Literature

We have developed Textpresso, a new text-mining system for scientific literature whose capabilities go far beyond those of a simple keyword search engine. Textpresso's two major elements are a collection of the full text of scientific articles split into individual sentences, and the implementation of categories of terms for which a database of articles and individual sentences can be searched. The categories are classes of biological concepts (e.g., gene, allele, cell or cell group, phenotype, etc.) and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., biological process, etc.). Together they form a catalog of types of objects and concepts called an ontology. After this ontology is populated with terms, the whole corpus of articles and abstracts is marked up to identify terms of these categories. The current ontology comprises 33 categories of terms. A search engine enables the user to search for one or a combination of these tags and/or keywords within a sentence or document, and as the ontology allows word meaning to be queried, it is possible to formulate semantic queries. Full text access increases recall of biological data types from 45% to 95%. Extraction of particular biological facts, such as gene-gene interactions, can be accelerated significantly by ontologies, with Textpresso automatically performing nearly as well as expert curators to identify sentences; in searches for two uniquely named genes and an interaction term, the ontology confers a 3-fold increase of search efficiency. Textpresso currently focuses on Caenorhabditis elegans literature, with 3,800 full text articles and 16,000 abstracts. The lexicon of the ontology contains 14,500 entries, each of which includes all versions of a specific word or phrase, and it includes all categories of the Gene Ontology database. Textpresso is a useful curation tool, as well as search engine for researchers, and can readily be extended to other organism-specific corpora of text. Textpresso can be accessed at http://www.textpresso.org or via WormBase at http://www.wormbase.org .

Introduction Text-mining tools have become indispensable for the biomedical sciences. The increasing wealth of literature in biology and medicine makes it difficult for the researcher to keep up to date with ongoing research. This problem is worsened by the fact that researchers in the biomedical sciences are turning their attention from small-scale projects involving only a few genes or proteins to large-scale projects including genome-wide analyses, making it necessary to capture extended biological networks from literature. Most information of biological discovery is stored in descriptive, full text. Distilling this information from scientific papers manually is expensive and slow, if the full text is available to the researcher at all. We therefore wanted to develop a useful text-mining tool for full-text articles that allows an individual biologist to locate efficiently information of interest. The natural language processing field distinguishes information retrieval from information extraction. Information retrieval recovers a pertinent subset of documents. Most such retrieval systems use searches for keywords. Many Internet search engines are of this type, such as PubMed ( http://www.ncbi.nlm.nih.gov/entrez/query.fcgi ). Information extraction is the process of obtaining pertinent information (facts) from documents. The facts can concern any type of biological object (entity), events, or relationships among entities. Useful measures of the performance of retrieval and extraction systems are recall and precision. In the case of retrieval, recall is the number of pertinent documents returned compared to all pertinent documents in the corpus of text. Precision is the number of pertinent documents compared to the total number of documents returned. A fully attentive reader would have complete recall, but low precision, because he has to read the whole body of text to find information. The emphasis for most applications is on recall, and we thus sought a system with high recall and as high precision as possible. Attempts to annotate gene function automatically include statistical approaches, such as cooccurrence of biological entities with a keyword or Medical Subject Heading term ( Stapley and Benoit 2000 ; Jenssen et al. 2001 ). These methods have high recall and low precision, as no effort is being made to identify the kind of relationship as it occurs in the literature. Another approach has involved semantic and/or syntactic text-pattern recognition methods with a keyword representing an interaction ( Sekimizu et al. 1998 ; Thomas et al. 2000 ; Friedman et al. 2001 ; Ono et al. 2001 ). They have high precision but low recall, because recognition patterns are usually too specific. Other machine learning approaches have classified abstracts and sentences for relevant interactions, but have not extracted information ( Marcotte et al. 2001 ; Donaldson et al. 2003 ). For a more detailed report of these and related projects, see reviews by Andrade and Bork (2000) , de Bruijn and Martin (2002) , and Staab (2002) . The precision of a keyword search can be increased by searching for combinations of keywords. For example, a researcher might construct a search for “anchor cell” and the gene name “lin-12” because he is interested in learning whether lin-12 plays a role in the anchor cell. However, there are many potential ways to describe the same concept or biological entity. Also, one often wants to search for a category of terms such as any gene or any body part. In this case, the intended search might be of a more general nature: If the researcher asks which genes are of interest in the anchor cell at all, he might have a hard time typing in all the known gene names (either one by one or concatenated with the Boolean operator “or”) in combination with the cell name. We therefore sought to develop a system that uses categories of terms such as “gene,” “cell,” or “biological process.” We established these categories of terms and organized them as an ontology, a catalog of types of objects and concepts and their relationships. The categories impart a semantic quality to searches, because the categories are based on the meaning of the entries. In many cases literature databases only contain bibliographic information and abstracts. The latter suffer from the constraint of information compression and convolution imposed by a word limit. Access to the full text of articles is critical for sufficient coverage of facts and knowledge in the literature and for their retrieval ( Blaschke and Valencia 2001 ); our results confirm these findings. We wanted to use the Caenorhabditis elegans literature as a test case for developing a useful information extraction system. C. elegans has a relatively small literature, so in principle we could use it to test a complete, well-defined corpus. We also wanted to support a new database curation effort involving manual literature curation ( Stein et al. 2001 ). Literature curation consists of identifying scientific data in literature and depositing them in an appropriate manner in a database. One extreme curation method is to read through the whole corpus of literature, identifying and extracting all significant information. This approach has the advantage that quality control of the data is done to the highest degree, based on human expertise. However, the volume and growth of biological literature makes it hard to keep the biological database up to date. In addition, data in literature may be missed by oversight, an inevitable flaw of purely human curation. The other extreme curation method is to extract data automatically. We therefore wanted a system that uses the computer to assist the curators. Our system is defined by two key components: the introduction of an ontology and the searchability of full text. The ontology is organized into categories that facilitate broader searches of biological entities as illustrated above. To be useful, it should also contain other categories that are not composed of biological entities, but describe relationships between entities. We sought to offer the user an opportunity to query the literature in the framework of the ontology such that it returns sentences for inspection by the user. We hypothesized that searching the corpus of text with a combination of categories of an ontology could facilitate a query that contains the meaning of a question in a much better way than with keywords alone. For example, if there is a “gene” category containing all gene names and a “regulation” category that includes all terms (nouns, verbs, adjectives, etc.) describing regulation, searching for (at least) two instances of the category gene and one instance of the category regulation in a sentence increases the chance that the search engine will return a sentence describing a gene-gene regulation. The search could then be limited by using a particular gene name as a keyword to get a list of genes that regulate or are regulated by that particular gene. Results We have developed a text processing system, Textpresso, that splits papers into sentences, and sentences into words or phrases. Each word or phrase is then labeled using the e X tensible M arkup L anguage (XML) according to the lexicon of our ontology (described below). We then index all sentences with respect to labels and words to allow a rapid search for sentences that have a desired label and/or keyword. The labels fall into 33 categories that comprise the Textpresso ontology. We built a database of 3,800 C. elegans papers, bibliographic information from WormBase, abstracts of C. elegans meetings and the Worm Breeder's Gazette, and some additional links and WormBase entities. See Materials and Methods for details on the database preparation. Textpresso Ontology Abstracts, titles, and full texts in the Textpresso system are processed for the purpose of marking them up semantically by the ontology we constructed. An ontology is a catalog of types of objects and (abstract) concepts devised for the purpose of discussing a domain of interest. An ontology helps to clarify a domain's semantics for everyday use, as is nicely demonstrated by Gene Ontology (GO; The Gene Ontology Consortium 2000 ). Although GO terms are not intended as a representation of natural language prose, they are a rich source of biologically meaningful terms and synonyms. They are the foundations for three corresponding categories in Textpresso, which are added to its 30 other categories. GO terms comprise approximately 80% of the lexicon. The first group of categories in the Textpresso ontology consists of biological entities: It contains the categories gene, transgene, allele, cell and cell group, cellular component, nucleic acid, organism, entity feature, life stage, phenotype, strain, sex, drugs and small molecules, molecular function, mutant, and clone. We have incorporated the GO molecular function category and proteins in the Textpresso molecular function category. A more detailed list with definitions can be found on the Textpresso Web site, and the most important ones are provided in Table 1 . Many of these categories have subcategories. For example, the molecular function category has the subcategories “source = (Go|Textpresso)” and “protein = (yes|no).” As we have imported all terms from GO, the first subcategory makes it possible to search specifically for GO terms. Terms added by us have the attribute “Textpresso.” Similarly, not all molecular function terms are classified as protein. The word “co-transporter,” for example, conveys more of a function and would be used more in this context in the literature, even though its physical realization may in fact be a protein. A list of all subcategories can be found in Table 2 . Table 1 The 18 Biologically Most Relevant of the 33 Categories of the Textpresso Ontology a HSN, hermaphrodite-specific neuron Table 2 The Subcategories of the Ontology Categories without any subcategories are omitted The second group of categories comprises terms that characterize a biological entity or establish a relation between two of them. It includes physical association (in the sense of binding) and consort (abstract association), effect, purpose, pathway, regulation, comparison, spatial and time relation, localization in time and space, involvement, characterization (terms that express the characterization of something), method, biological process, action, and descriptor (words that describe the state or condition of an entity). These categories, while well defined, have somewhat delicate boundaries, and the common-sense aspects of our ontology apply more to this group. It is likely that its categories are going to be changed as we continue to develop the system. In some instances terms are attributed to one category, even though they might as well fit into another. As an example, the term “coexpress” is put in the “consort” category to emphasize the concurrent aspect of the process, while it could as well be classified as a biological process. However, we believe that in most cases the first sense of the word is used in the literature. The last group (auxiliary) contains categories that can be used for more involved semantic analysis of sentences. These categories are auxiliary (forms of the verbs “be” and “have”), bracket, determiner, conjunction (and, or, because, since, although, etc.), conjecture (could, might, should, suggests), negation, pronoun, preposition, and punctuation. Some of them overlap with the syntactic categories that the part-of-speech tagger (used in the preprocessing steps; see Materials and Methods ) assigns to terms, but are repeated here as they also contain some semantic component. The category “conjecture” is introduced to distinguish statements that convey hypotheses, speculations, or theoretical considerations from sentences that are expressed with confidence, thus representing more of a fact. The words of this category indicate the certainty of a statement. The Textpresso ontology is organized into a shallow hierarchy with 33 parent categories. The parent categories may have one or more subcategories, which are specializations of the parent category. For example, all of the terms in the parent category “biological process” will belong to one of its subcategories, “transcription,” “translation,” “expression,” “replication,” “other,” or “no biosynthesis.” This is user friendly and certainly serves the current implementation of the user interface well, which is oriented more towards information retrieval. The ontology is populated with 14,500 Practical Extraction and Report Language (PERL) regular expressions, each of which covers terms with a length from one to eight words. These expressions are contained in a lexicon. Table 3 shows examples of regular expressions for each category and examples of text strings matching them. Each regular expression can match multiple variable patterns. The multiple forms of regular verbs, for example, can be conveniently expressed as “[Ii]nteract(s|ed|ing)?” which stands for the eight cases “interact,” “interacts,” “interacted,” “interacting,” “Interact,” “Interacts,” “Interacted,” and “Interacting.” All regularly named C. elegans genes are matched with the expression “[A–Za–z][a–z][a–z]–\d+” matching three letters ([A–Za–z][a–z][a–z]), a dash (–), and a sequence of digits (\d+). As this example illustrates, the expressions can be made case sensitive. This is important as biological nomenclature becomes more elaborate, and the ability to distinguish subtle differences is pivotal for separating terms into the correct categories. Many of the regular expressions are generated automatically via scripts, taking a list of plain words as input and transforming them as shown in this example, to account for regular forms of verbs and nouns. The text-to-XML converter (see Materials and Methods ) marks up the whole corpus of abstracts, full texts, and titles and produces XML documents. Figure 1 illustrates this process with an example. The computer identifies terms by matching them against regular expressions (such as the one shown above) and encloses them with XML tags. The tag <text> serves as a containment of terms not semantically marked up. These tags will be used for a repeated reevaluation of the lexicon, as these terms can be easily pulled out and analyzed. A list of the most frequently missed terms is then produced and included in the lexicon for the next markup. Figure 1 The Process of Marking up a Sentence The process of marking up the sentence “In par-1, par-4 and par-3 mutant four-cell embryos, MEX-3 is present at high levels in all cells, indicating that activity of these par genes is required to restrict MEX-3 to the anterior.” This sentence is taken from Huang et al. (2002) . (A) The computer identifies terms that are stored in a lexicon according to categories of the ontology. A text-to-XML converter marks up the terms by enclosing them in XML brackets. (B) The fully marked-up sentence. Some categories have subcategories (for example, the category “regulation” is subdivided into “positive,” “negative,” and “unknown”). Grammar attributes have been omitted here for the sake of clarity, because they are not used in the current version of the system. Some white spaces have been inserted in the graphics for clarity enhancement. Table 3 Categories of the Ontology with Examples of Regular Expressions and Matching Text Strings This table also contains the distribution of 24,542,376 tags in the 1,035,402 sentences of the corpus Applications of Textpresso The marked-up text is stored in a database and can be queried. We built a user interface for general queries and another one for a specific type of query for WormBase curators (gene-gene interactions; see below). Textpresso is used in several related ways. Individual biologists use it to find specific information. Database curators, whose job is to extract information from papers or abstracts and to add this to a database, use it repeatedly to find all information of a particular type, in addition to using it for individual queries. The current Textpresso user interface ( http://www.textpresso.org/ ) includes a query interface, a side menu with links to informative pages about the ontology, a document type definition, a user guide, and example searches, as well as the two retrieval and customization interfaces. The Web site offers two different types of retrieval, simple and advanced. Options for the retrieval queries are offered: searching a combination of categories, subcategories, and keywords in a Boolean fashion, specifying the frequency of occurrences of particular items, and choosing where in the article to search (title, abstract, body). The user can also determine whether a query is to be met in the whole publication or in a sentence. These options make the search engine powerful; for example, if a query is met in the whole article, the search has the function of text categorization, while meeting it in a sentence aims at extracting facts, which can be viewed in the context of a paragraph. The specification of cooccurrence determines the character of a search. If a combination of keywords and categories is found in a sentence, the likelihood that a sentence contains a fact involving the chosen categories and keywords is quite high. If the user chooses cooccurrence within a document, he is more interested in finding a relevant document. The scope of a search can be confined to full text, abstract, title, author, year, or any combination thereof, for document searches as well as sentence searches. A typical result page shows a list of documents with all bibliographical information and the abstract as displayed in Figure 2 . A simplified version of the Textpresso interface is incorporated within WormBase ( http://www.wormbase.org ). Figure 2 A Typical Result Page Returned from a Simple Retrieval Query (Keyword) A simple retrieval was performed with “let-23” as keyword and “regulation,” “cell or cell group,” and “molecular function” as categories. A total of 245 matches were found in 113 publications. The result list retrieved by a query can be customized in such a way that the user can choose how to display the information. This list is sorted according to the number of occurrences of matches in the document, so the most relevant document will be on the top of the list. A series of buttons for the whole list as well as for each document is available, allowing the user to view matching sentences or prepare search results in various formats. The individual result entries have up to six links: One can view matches for each paper only, go to the Web site of the journal to read the online text of the article (this only works if the user is subscribed to the journal), view a list of related articles that is provided by PubMed, export the bibliographical information into Endnote (two different links), or, if the user is accessing Textpresso internally (currently at Caltech), one can download the PDF of the paper. The power of Textpresso's search engine unfolds when category searches are used. By searching for a category, the researcher is targeting all keywords that populate that category. For example, the researcher might be interested in facts about genetic regulation of cells. Assuming that many facts are expressed in one sentence, he would search for the categories “gene,” “regulation,” and “cell or cell group” in a sentence. He can then view the matches (and surrounding sentences) of the search return and decide which facts are relevant. If one is not interested in all genetic regulation instances mentioned in the literature, it might be more useful to combine keywords with categories. For example, the question “What entities interact with ‘daf-16' (a C. elegans gerontogene)?” can be answered by typing in the keyword “daf-16” and choosing the category “association.” Advanced Retrieval and Subcategories An extension (the advanced retrieval interface) allows the use of the subcategories of the ontology and the specification of Boolean operators, thereby concatenating categories and keywords with “or” or “not” to permit alternatives or exclude certain items. One special subdivision of terms is the distinction between named and unnamed entities: Categories can include both general terms and specific names of entities. For example, the word “gene” would be an unnamed term of the gene category, while “lin-11” is a named entity. The general terms will likely be used for fact extraction across several neighboring sentences, but they might also be useful for retrieval purposes, even though the rate of false positives might be much higher in the latter case. Lastly, the user can determine how a keyword or category term has to be matched numerically. The options “greater than,” “less than,” and “equal to” are available together with a drop-down menu for the number of occurrences. With these additional tools, document categorization can be made more effective. A detailed profile of which categories and keywords should occur a minimum, maximum, or exact number of times for triggering a match can be established. Similarly, searches on the sentence level acquire a semantic quality, i.e., they at least partially encompass a meaning. In many cases, the answers to questions, phrased in the form of a sophisticated query, can immediately be read off the result screen. If, for example, one were to ask in which cells lin-11 is expressed, one would search sentences for a combination of the category “biological process” (subcategory “biosynthesis: expression”), the category “cell or cell group” (subcategory “type: name”) and the exact keyword “lin-11.” The subcategory “expression” filters out all words that relate to expression, the subcategory “name” limits the search to specific cells which have a name, such as “anchor cell,” “HO neurons,” “IL sensillum,” etc. Other subcategory options would be “group” (for example, “head,” “vulva,” “tail”) and “lineage” (“AB lineage,” “EMS lineage,” etc.). To better understand the following results, note that the term “cell(s)” has the type “name,” to gain the correct meaning of phrases such as “AB lineage cells.” The first two words of this phrase are marked as lineage, but the last word makes the whole phrase named cells. The system returns sentences of different quality. Some of them answer the question posed immediately (returned sentences are taken from Gupta and Sternberg 2002 ; that paper produced the most hits). The underlined words mark the matched items: “An analysis of the expression pattern of lin-11 in vulva and uterine lineage cells earlier suggested that cellular defects arise due to a failure in the differentiation process”; “Our analysis of the expression of lin-11 in VPC granddaughters (Pn.pxx stage) has revealed the following pattern in P5.p and P7.p lineage cells (from anterior to posterior; L, low; H, high), LLHH and HHLL , respectively.” Other sentences meet the truth more by accident, as the terms are matched within a sentence, but the statement does not really express the fact sought. The cells where lin-11 is expressed might be inferred by the knowledgeable reader, and not stated explicitly: “Our results demonstrate that the tissue-specific expression of lin-11 is controlled by two distinct regulatory elements that function as independent modules and together specify a wild-type egg -laying system”; “Using a temporally controlled overexpression system, we show that lin-11 is initially required in vulval cells for establishing the correct invagination pattern.” Finally, some sentences just do not give any clue about the posed question: “ lin-11 cDNA- expressing vectors under the control of lin-11- AB (pYK452F7-3) and lin-11-C (pYK452F7-2) elements were designed as follows.” Here, “AB” is marked up as a named cell, but this is not the semantically correct tag in this context. This false positive might have been prevented if specific sections of a paper could be searched, as this statement comes from the method section. Evaluation of the Textpresso System An automatic method for retrieving or extracting information from text is only useful if it is as accurate and reliable as human curation. We devised two tests based on two common tasks performed by human experts who extract biological data from journal articles. The first task was the automatic categorization of papers according to the types of biological data they contain. Our study used a large test set of papers scanned by a curator to examine the effectiveness of automatically searching for information in the full text of a journal article compared to its abstract. The second task focused on retrieving sentences containing a specific type of biological data from text. Sentences from eight journal articles were manually inspected on a sentence-by-sentence basis and compared to the return from a Textpresso query on the same articles. From this study we present a detailed error analysis outlining the strengths and weaknesses of the current Textpresso system as an automatic method for information retrieval. We evaluated the performance of Textpresso using the information extraction performance metrics of precision, which is a measure of the amount of true returned data compared to the amount of false returned data, and recall, which is a measure of the true data returned compared to the total amount of true data in the corpus. These values are formulated as recall = number of true returns / total number of true data items and precision = number of true returns / total number of returns. Classification of Journal Articles: Full Text Versus Abstract We examined the effectiveness of automatically identifying journal articles that contain particular types of data. A test set of 965 journal articles pertaining to C. elegans biology was assessed by a human expert and categorized into groups according to six different types of data (antibody data, ablation data, expression data, mapping data, RNAi data, and transgenes). Note that there can be more than one data type per article. We first measured the value of searching for keywords in the full text of an article as opposed to searching its abstracts ( Table 4 ). The overall information recall when searching abstracts is low (∼44.6%) compared to the information recall when searching full text (∼94.7%). Furthermore, keywords for some specific types of data (e.g., antibody data, mapping data, transgene data) are very unlikely to appear in abstracts (∼10% recall) but can be found in full text (∼70% recall). However, precision of the keyword search is reduced by almost 40% when searching full text compared to abstracts (30.4% and 52.3%, respectively). Single keyword searches of full text return a large number of irrelevant documents for most searches. This higher false positive rate might reflect the writing style found in full text, where facts can be expressed within complex sentence structures (as compared to abstracts, where authors are forced to compress information), combined with the inability of a keyword search to capture context. Table 4 Comparison of a Keyword Search on Abstracts versus Full Text Automatic classification of journal articles based on the biological information they contain (i) searching abstracts with keywords and (ii) searching full text with keywords. The keywords used as search terms are indicated by k ( keyword ). A, the number of true articles returned; B, the total number of articles returned Small-Scale Information Retrieval Study We tested the accuracy of a search combining word categories and keywords to retrieve sentences containing genetic interaction data. For this experiment we broadly defined genetic interaction as the effect of one or more genes on the function of another gene or genes (and thus it includes genetic interaction, regulation, and interaction of gene products). To directly assess how Textpresso performs, a human expert manually evaluated the text sentence by sentence ( Figure 3 ). Figure 3 Schema of Small-Scale Information Retrieval Study Sentences from eight journal articles were both queried by Textpresso and evaluated by a human expert for sentences that described genetic interaction (information retrieval task). In the information extraction task, a human expert inspected the sentences returned by each method to determine the amount of distinct gene-gene interactions that could be extracted in order to analyze the output of the first task. We formulated a Textpresso query that searched for the presence of at least two genes mentioned by name and at least one term belonging to the “regulation” or “association” word categories (see Materials and Methods ). A total of 178 sentences were matched for this query in the eight journal articles, and the results are shown in Table 5 . A human expert assessed the returned sentences and determined that 63 sentences contained gene-gene interaction data according to our criterion. The same set of journal articles had been independently manually evaluated for their description of genetic interactions, and 73 true sentences were identified. In both cases, information from the article title, abstract, contents of tables, and reference section was excluded. Sentences that described genetic interaction using the gene product name rather than the gene were also excluded from this study. To measure recall, we first determined the total number of sentences that contained genetic interaction data. Table 5 Retrieval of Sentences Containing Gene-Gene Interaction Data from a Set of Journal Articles Retrieval was performed manually or automatically using Textpresso For this analysis we took the union of true sentences manually identified in the journal articles and the true sentences returned by Textpresso. The total number of true sentences identified by the two methods was 102. The recall of sentences containing genetic interaction was ∼62% using Textpresso compared to ∼71% for those sentences manually identified in journal articles. One-third of the sentences returned by Textpresso were true positives (35%). Although the numbers of true sentences retrieved by the automatic and manual methods were similar (63 and 73, respectively), only 34 of these sentences overlapped. To investigate this discrepancy, we manually extracted the genetic interactions described in both sets of sentences and determined the number of distinct genetic interactions found by each method ( Table 6 ). The sentences manually identified from the journal articles yielded 23 more distinct genetic interactions than those which were extracted from true sentences retrieved by Textpresso. However, 43 interactions derived from the Textpresso output overlapped with the manually identified set, and Textpresso located sentences describing seven genetic interactions that the human expert missed. The average redundancy (how many times the same gene-gene interaction occurred) of a distinct genetic interaction extracted from both the manual and automatic methods was 3-fold. Table 6 Distinct Gene-Gene Interactions Retrieved from Journal Articles Interaction data were either manually retrieved from journal articles or manually retrieved from sentences retrieved by Textpresso We analyzed the gene-gene interaction sentences missed by Textpresso. In many cases (65%) the word or phrase used to describe the genetic interaction belonged to neither the “association” nor the “regulation” word category and so the sentence was not returned. In some cases, the term or phrase that determined “genetic interaction” belonged to some other Textpresso word category (e.g., some terms that implied genetic interaction and were not matched by the query were “epistatic,” which belongs to the “consort” word category, and “alters,” which belongs to the “effect” word category). This type of analysis is useful for revising and updating the ontology. In other cases, due to the intricacies of natural language prose, it was difficult to isolate an interaction term in the sentence (e.g., “Thus ref-2 alone is insufficient to keep P(3–6).p unfused when lin-39 is absent.”). Approximately 8% of true sentences were missed because the genetic interaction information was discussed over a number of sentences. This is a limitation of the current Textpresso system, as search queries are matched per sentence (or per entire article). Our analysis of the false positive sentences returned by Textpresso revealed that approximately 10% discussed gene-gene interactions that did not occur (e.g., “Neither pdk-1(gf) nor akt-1(gf) suppressed the Hyp phenotype of age-1(mg44) .”). While we do have a “negation” category in our Textpresso ontology, we chose not to exclude negation terms from the posed query, to avoid missing true positives (in case the negation does not apply to the interaction term in a sentence, but to some other portion of it). Twenty-one percent of the false positive sentences were determined by inspection to suggest genetic interaction, but were too weakly phrased to extract the information in confidence without the context of the sentence. However, the majority of false positives (70%) were due to the lack of context of the search terms in the sentence, where they matched the query terms (underlined) but in a context that did not mention genetic interaction: “ lin-35 and lin-53 , two genes that antagonize a C. elegans pathway, encode proteins similar to Rb and its binding protein RbAp48.” This example strongly supports the idea that an information extraction method that considers semantic context of a search query would dramatically increase the precision of the return. Large-Scale Information Retrieval to Expedite Information Extraction We performed extraction of genetic interaction information from a corpus of 3,307 journal articles. A Textpresso query searched for the presence of at least two uniquely named genes and at least one term belonging to the “regulation” or “association” word categories (see Materials and Methods for more details). A total of 17,851 sentences were returned by this query. Due to the lack of context of some sentences, true sentences were determined by a more stringent definition of genetic interaction, i.e., where one or more named genes were described as modifying the phenotype of another named gene or genes by suppression, enhancement, epistasis, or some other genetic method. To determine the frequency of true sentences, a random sample of 200 of the sentences returned by Textpresso was evaluated by a human expert according to this more stringent criterion ( Table 7 , column C). This sample was compared to 200 sentences chosen from the whole corpus at random ( Table 7 , column A) and 200 sentences randomly chosen from the whole corpus that contained two or more named genes ( Table 7 , column B). Table 7 The Frequency of Genetic Interaction Data Contained in Full Text A, 200 random sentences; B, 200 sentences containing at least two genes; C, 200 sentences returned from a Textpresso query for at least two uniquely named genes and at least one “regulation” or “association” word. See Materials and Methods for details A typical sentence that was determined to be true for genetic interaction data is “Interestingly, at lower temperatures, the akt-2(+) transgene can supply sufficient Akt/PKB activity to weakly suppress the dauer arrest caused by age-1(mg44) .” Some of the sentences strongly suggested genetic interaction but did not quite meet the genetic interaction criterion. These were grouped as “possible genetic interaction,” for example, if a phenotype was not mentioned: “For example, lin-15(lf) animals display a 54% penetrance of P11 to P12 fate transformation, while all egl-5(lf) ; lin-15(lf) double mutants show a P12 to P11 fate transformation.” Sometimes it is unclear exactly which genes are participating in the genetic interaction: “Evidently the effect of the sir-2.1 transgene alone is too subtle to trigger dauer formation without the sensitizing daf-1 or daf-4 mutations.” Another group was highlighted as discussing interaction, but fell outside the criterion set for genetic interaction. These were classified “non-genetic interaction.” Some examples of this are sentences that specify gene regulation: “These studies have shown that smg-3(Upf2) and smg-4(Upf3) are required for SMG-2 to become phosphorylated.” Finally, sentences that describe physical interaction were also put into the category “possible genetic interaction”: “For example, GLD-1 represses translation of tra-2 , one of the sex-determination genes, by binding to the 3′-UTR or the tra-2 mRNA (Jan et al. 1999).” This analysis shows that there is a 1 in 200 chance of a sentence discussing genetic interaction (as defined above) randomly occurring in the full text of the journal articles analyzed. The odds increase to 7 in 100 if one looks at sentences containing at least two named genes. The returned matches from the Textpresso search are enriched 39-fold for genetic interaction compared to random chance, and there is a significant 3-fold enrichment when compared to sentences containing at least two named genes. There is a 1 in 5 chance that a returned Textpresso match is true. To date, 2,015 of the 17,851 returned sentences have been evaluated. Of these, 370 discuss genetic interaction, yielding 160 distinct gene-gene interactions mined from the literature. There are 213 sentences that mention nongenetic interactions, and 419 sentences are classified as possible genetic interactions. Large-Scale Simple Fact Extraction We have extracted gene-allele reference associations from the corpus of papers to populate the WormBase database by searching for the pattern <gene><bracket><allele> <bracket>. Of the 10,286 gene-allele associations extracted, 9,230 were already known by WormBase, while 1,056 associations were new and could be added to the database. In addition, 1,464 references could be added to the 2,504 allele reference associations in WormBase. Ninety-eight percent of the data extracted went into the database without any manual correction, and the last 2% were compromised because of typographical errors in the original paper or the inherent character of the data (i.e., gene name synonyms and changes). Discussion Accomplishments We have developed a system to retrieve information from the full text of biological papers and applied it to the C. elegans literature. As of March 2004, the database contains full texts of 60% of all papers listed by the Caenorhabditis Genetics Center (CGC; http://www.cbs.umn.edu/CGC/CGChomepage.htm ) and almost all abstracts that are information rich for C. elegans research. The introduction of semantic categories and subsequent marking up of the corpus of texts introduce powerful new ways of querying the literature, leading towards the formulation of meaningful questions that can be answered by the computer. We have demonstrated such queries with one example and have successfully tried many others. A more thorough evaluation of the system revealed that the availability of full text is crucial for building a retrieval system that covers many biological data types with a satisfying recall rate, and thus is truly useful for curators and researchers. For biologists, an automated system with high recall and even moderate precision (like the current Textpresso) confers a great advantage over skimming text by eye. Textpresso is already a useful system, and thus serves not only as proof of principle for ontology-based, full-text information retrieval, but also as motivation for further development of this and related systems to achieve higher precision and hence even greater time savings. It is apparent that the number of articles available in the C. elegans literature (currently about 6,000) can be curated with the assistance of Textpresso, as it is much more efficient than when done by human readers alone. The larger the corpus of papers, the more useful Textpresso will become. We have shown this by calculating the frequencies of genetic interaction data in sentences in three different cases: random sentences, sentences that contain at least two genes, and sentences returned from a Textpresso advanced query. The efficiency was shown to increase dramatically (39-fold in the best case). We have outlined the first steps of how Textpresso helps the curation effort by extracting gene-gene interactions. Overall, we have shown that Textpresso has several uses for researchers and curators: It helps to identify relevant papers and facts and focuses information retrieval efforts. Indeed, Textpresso is used daily by C. elegans researchers and WormBase curators: The server sends 530 files to requests daily via the Web, a quarter of which are to WormBase curators. Areas for Improvement Textpresso is limited in two ways: the lack of complete coverage of the C. elegans literature and the fact that the ontology and its corresponding lexicon are still in their infancy. The preparation of full texts has to be better and more efficient. The conversion of PDF to plain texts was problematic because of the different layouts of each journal. Even with the software we developed, a layout template for each journal needs to be written to specify where different components of text can be found. Prior to the use of this software, we had to forgo the use of figure and table captions. Acquisition of processable text is a general problem for biologists. A new release of XPDF (a PDF viewer for X; http://www.foolabs.com/xpdf/ ) eases this problem considerably (see Materials and Methods ). One of our studies on the effectiveness of the extraction of a specific type of biological fact, in this case gene-gene interaction, showed that the machine still cannot replace the human expert, although it increases efficiency greatly. We anticipate that the computer does better with a larger number of articles because of redundancy. While roughly 9% of distinct gene-gene interactions from a corpus of eight journal articles were missed by the human but revealed by Textpresso, 29% of the interactions were missed by Textpresso, primarily due to flaws in the ontology. Advancing the Textpresso ontology will help to increase the specificity of the retrieval system. A deeper, meaningful structure is likely to make extraction easier and more stable. Possible improvements are to include other biological ontologies and language systems, such as UMLS ( http://www.nlm.nih.gov/research/umls/ ) and SNOMED ( http://www.snomed.org/ , and to establish a more sophisticated tree structure. Our core lexicon recognizes 5.5 tags per sentence (out of an average of 23.7 tags per sentence) that are of scientific interest. This density results in a term coverage of 23.2%, while the maximum that could theoretically be added is 36.5%, assuming that all terms currently not marked up belong to relevant categories. An average of 9.5 tags per sentence are apparently of no interest for information retrieval; however, this is due to the nature of human language (and will be nonetheless useful for information extraction purposes). Reevaluation of the corpus of text for terms and their meanings that have been missed is necessary. This process will result in an expansion of our ontology, thus continually expanding the resulting lexicon, or revising the structure of the ontology. Ontology and lexicon revision is most efficiently done by a human, and a feasible automated approach seems out of reach. However, we have illustrated semiautomatic methods to help make this task easier in the future: The containment of words that are not covered in our lexicon with <text> tags serves several purposes. First, we are able to extract all words (or n-grams, which are represented as a consecutive sequence of words embedded in <text> tags), assemble a histogram of the most frequent terms, and add important ones to our lexicon. Second, having identified frequently occurring semantic patterns in the corpus, we are able to infer likely candidates of words for specific categories. For example, one popular pattern that indicates a gene-allele association is <gene><bracket><allele><bracket>. If one now searches for patterns such as <gene><bracket> <text><bracket> and extracts the word enveloped by the <text> tags, then a frequency-sorted list of words that are likely to be alleles can be assembled, presented to a curator for approval, and deposited into the lexicon. The alternative, <text><bracket><allele><bracket>, would give a list of possible gene names. Many other patterns, identified by statistical means and similarity measures, could be obtained and used in such a fashion. These two methods will help us to systematically and significantly reduce the number of terms not marked up in the corpus, making it more complete. The procedure can be repeated with every build of the Textpresso database and has the advantage that the list of words added to the lexicon is tailored to the literature for which it is used. In addition, shortcomings in the general structure of the ontology can be detected and corrected, if those issues have not been caught in the research and development of the information extraction aspects of the system. If the strategy outlined above is applied continually, we will be able to close this gap and reach saturation, even with the addition of new papers and abstracts. About 89% of current users take advantage primarily of the full text and multiple keywords. Some (11%) proceed to keyword plus category. Only 0.3% of users use the advanced retrieval search. It is clear that the implementation of a user test interface improvement/education cycle will greatly help the development of Textpresso and subsequently help users take full advantage of this system. More generally, biologists will become increasingly familiar with ontology-based search engines. Prospects Future development of Textpresso can be undertaken at many different levels. A synonym search could be enabled for keyword searches: After having compiled lists of them, an option could be given to automatically include synonyms for a given term (e.g., genes, cells, cellular component) in a search. Similarly, GO annotations could be used to search for and display sentences involving genes associated with gene ontology terms, after the latter ones have been queried first. As already mentioned, search targeting could be made more flexible: Papers could be subdivided into more sections (such as introduction, methods, results, conclusion, etc.), and a query could then be applied only to the specified sections. In addition, the limitation of searching criteria to just one sentence can be relaxed to a set number of neighboring sentences. Finally, one could improve on links to other databases of relevance besides WormBase and PubMed and increase the wealth of links to the latter ones. An important issue is the portability of the system to other model organism databases. This undertaking is part of the Generic Model Organism Database (GMOD) project ( http://www.gmod.org , and a downloadable package with software will be made available on their Web site. For a different model organism, parts of the lexicon, and maybe also parts of the ontology, need to be modified. Language and jargon in each community differ, and terms need to be systematically collected to accommodate their specific usage in the respective communities. However, this is not too laborious, as we have been able to generate a yeast version in a few weeks (E. E. Kenny, Q. Dong, R. S. Nash, and J. M. Cherry, unpublished data). We believe that Textpresso can be extended to achieve information extraction. The wealth of information buried in semantic tag sequences of 1 million sentences asks to be massively exploited by pattern-matching, statistical, and machine learning algorithms. Having the whole corpus semantically marked up provides bioinformaticians with the opportunity to develop fact extraction algorithms that might be quite similar to sequence alignment and gene-finding methods, or, more generally, algorithms that have similarity measures at their core, because sentences can now be represented as sequences of semantic tags. Furthermore, semantic sequences of related sentences show similar properties as related genomic sequences, such as recurring motifs, insertions, and deletions. The relatively rigid structure of the English language (subject-verb-object) and the comparatively low degree of inflections and transformations certainly help. In addition, some scientific information is stored in a structured manner. We have already started to run simple pattern-matching scripts to populate gene-allele associations from the literature for WormBase, as many of them are written in the form “gene name(allele name),” such as “lin-3(n1058).” Materials and Methods Sources. Textpresso builds its C. elegans database from four sources. A collection of articles in PDF format is compiled according to the canonical C. elegans bibliography maintained at the CGC ( http://www.cbs.umn.edu/CGC/CGChomepage.htm ). As of March 2004 we had around 3,800 (60%) CGC papers in our database. Software developed by us (see below) converts the PDFs to plain text. We import additional bibliographical information from WormBase: titles of documents and author and citation information. WormBase data comprise additional C. elegans- related documents such as C. elegans meeting abstracts and Worm Breeder's Gazette articles. We also curate certain types of data ourselves. Some C. elegans- related papers are not found in the CGC bibliography or WormBase. We compile lists of URLs of journal Web sites and their articles, and links to related articles (provided by PubMed). Citations are prepared in Endnote format for download. Finally, as Textpresso returns scientific text to the user, we construct links to report pages of WormBase that display detailed information about biological entities, such as genes, cells, phenotypes, clones, and proteins. All data and links produced by us are referred as “Textpresso” data in Figure 4 . Figure 4 Schema of Textpresso Database Preparation The regular hexagons indicate the sources from which Textpresso is built. The rounded rectangles are either intermediate or final processed parts of the corpus. The dashed-dotted rectangles signify automatic processing units or actions. Ontology. The objective of an ontology is to make the concepts of a domain and the relationships and constraints between these concepts computable. For an ontology to be utilized in a search engine for biological literature, it has to include the language of everyday use and common sense. We have therefore assigned the most commonly used meaning to a word even though it has several meanings in different contexts. We have consequently adopted a strategy of devising an ontology drawing from our own knowledge. Our ontology includes all terms of the three major ontologies of GO, namely “cellular component,” “biological process,” and “molecular function.” The current ontology is unstructured for the sake of straightforward usability, our first priority. A variety of approaches were utilized to construct and populate the 33 categories of the Textpresso ontology. We first designed individual categories for well-defined biological units or concepts such as strain, phenotype, clone, or gene. The terms in some of these categories (such as clone, allele, and gene) were represented by a PERL regular expression designed to match any text that looked like that particular biological unit. This was possible where a conserved and unique nomenclature for that biological concept had been established in the literature. Any exceptions to the established nomenclature recorded in WormBase were also added to these categories. For other biological concepts (e.g., “method,” “phenotype,” “cellular component,” and “drugs and small molecules”), we extracted information from publicly accessible biological databases, such as WormBase, GO, and PubMed/NCBI to construct lists of terms. We supplemented these lists through primary literature and textbook surveys. Next, we conceived categories of terms that would describe the relationship between the biological categories. To structure these “relationship” categories, we listed words of the text of 400 C. elegans journal articles for analysis. From this list we flagged natural prose words that we felt had at least some defined meaning within the context of biological literature (for example, “expressed,” “lineage,” “bound,” “required for”). From this list we constructed 14 new categories designed to encapsulate the natural language used by biologists to describe biological events and the relationship between them (action, characterization, comparison, consort, descriptor, effect, involvement, localization in time and space, pathway, purpose, physical association, regulation, spatial relation, and time relation). We made a second pass through the subset of flagged words from the list and assigned them to one of these categories according to what the sense of the word was in the biological literature for the majority of the time. Finally, a number of categories were designed to account for syntax and grammatical construction of text, such as “preposition,” “conjunction,” and “bracket.” Names. We have manually curated a lexicon of names because it has proved difficult in the past to automatically recognize names of biologically relevant entities ( Fukuda et al. 1998 ; Proux et al. 1998 ; Rindflesch et al. 2000 ; Blaschke and Valencia 2002 ; Hanisch et al. 2003 ). We therefore chose to curate and maintain a lexicon with names of interest by hand. In this C. elegans- specific implementation of Textpresso, the effort was helped by the fact that the C. elegans community is somewhat disciplined in choosing names and WormBase includes names of interest. Of course, there is the danger that entities not listed in WormBase (and therefore in our lexicon) will be missed in our system, and those cases are of special interest to curators (of WormBase) and researchers, such as newly defined genes or newly isolated alleles. Dictionaries tend to be incomplete and turn stale rapidly, because of the issues of synonyms, lack of naming conventions, and the rapid pace of scientific discovery. Thus, we do not rely only on WormBase, but maintain an independent, Textpresso-specific part of the lexicon. Technical aspects of the system. Figure 4 shows the details of database preparation. The regular hexagons indicate the sources from which Textpresso is built. The PDF collection was converted to plain text by a software package written by Robert Li at Caltech. The development of such a software tool had become necessary, as current PDF-to-text converters do not comply with the typesetting of each journal, i.e., footnotes, headers, figure captions, and two-column texts in general are dispersed and mixed up senselessly in the converted text. The application works with templates that specify the structure and fonts used in a particular journal and uses this information to convert the articles correctly. A high-fidelity conversion is crucial for any information retrieval and extraction application. The software will be made available at the GMOD Web site ( http://www.gmod.org ). While this manuscript was being written, a new version (2.0.2) of XPDF ( http://www.foolabs.com/xpdf/ ) was released. This version, unlike its predecessors, does a superb job in converting PDF into a congruent stream of plain text. Additional bibliographic data of references for which PDFs are not available are imported from WormBase (symbolized as “WormBase data” in Figure 4 ). These are mainly abstracts from various meetings. The data collected from our primary sources are treated in two different ways. Author, year, and citation information are deposited “as is” into the database, while abstracts, titles, and full texts are further processed. First, the texts are tokenized. Our tokenizer script reads the ASCII text derived from the conversion from PDF and splits the text into individual sentences based on the end-of-sentence period, where words hyphenated at the end of a line are concatenated and instances of periods within sentences (which are used mainly in technical terms and entity names) are ignored. The script also adds an extra space preceding any instance of punctuation within a sentence, which is a requirement for the Brill tagger ( Brill 1992 ), a publicly available part-of-speech tagger, to attach 36 different grammatical tags to each tokenized word. The tagger has been trained specifically to handle the C. elegans literature, and additional tagging rules are applied. For example, gene names are forced to be tagged as nouns. The grammatical tags are not further used in the current Textpresso system. After this preprocessing step, the corpus of titles, abstracts, and full texts is marked up using the lexicon of the ontology (PERL expressions), as explained in Results and exemplified in Figure 1 . The tags contain the name of the category as well as all attributes that apply to a matched term. Terms that are not matched by any of the 14,500 PERL expressions are given the tag <text>, one token at a time. The corpus of searchable full texts, abstracts, and titles has 1,035,000 sentences. A total of 351,000 keywords have been indexed, covering 19,180,000 words in the texts. The semantic mark-up yields a total of 24,542,000 tags. Table 3 shows the distribution of tags. The number of meaningful tags (the ones that are not just <text>) is only 15,577,368, or 15.04 tags per sentence. An average of 5.5 tags per sentence are of scientific interest, i.e., are either biological entities or words that describe a relationship or characterize an entity. When displaying sentences and paragraphs, Textpresso provides links to report pages of several biological entities, such as proteins, transgenes, alleles, cells, phenotypes, strains, clones, and loci. There are a total of 165,000 different entities in WormBase to which Textpresso links, including links to journal articles and PubMed. All these links are produced statically and again deposited on disk for fast retrieval, and these data are referred to as “Textpresso data” in Figure 4 . In this way the actual link is not made on the fly from generic URLs, and the response time for queries remains short. We generated an exhaustive keyword and category index for the whole corpus. This index makes the search extremely fast, using rapid file access algorithms. All keywords and tags in the corpus are indexed. Also, all terms in the corpus that have a report page in WormBase are indexed. For 2,700 full-text articles and 16,300 abstracts, the index takes up 1.7 Gb. The interfaces for submitting queries and customizing display options are written as CGI scripts. They are supported by simple HTML pages that contain documentation. The Web site runs with a RedHat Linux operating system and an Apache http server. No special changes to the standard configuration are required. The Web interface accesses the custom-made Textpresso database; no commercial-grade database systems have been used. It takes 2–3 d to build the complete 6.9-Gb database. Methodology of evaluation. For the preliminary study, a query was formulated using three category rows of the Textpresso “advanced retrieval” interface to identify sentences containing gene-gene interaction data from a test set of eight full-text journal articles (see Table 5 ): the PMID:11994313 ( Norman and Moerman 2002 ), PMID:12091304 ( Alper and Kenyon 2002 ), PMID:12051826 ( Maduzia et al. 2002 ), PMID:12110170 ( Francis et al. 2002 ), PMID:12110172 ( Bei et al. 2002 ), PMID:12065745 ( Scott et al. 2002 ), PMID:12006612 ( Piekny and Mains 2002 ), and PMID:12062054 ( Boxem and van den Heuvel 2002 ). In the top row of the advanced retrieval tool the “association” ontology was selected in the “category or keyword” column. No other changes in the first row were made, which implies that no subcategory or specification was selected, and the occurrences of association terms in one sentence were “greater than 0.” In the second row, the Boolean operator “or” and the category “regulation” were selected, with no further specification, again asking the machine to return sentences with at least one regulation term. Finally, in the third row, the category “gene” was chosen, with a specification of “named” and an occurrence of “greater than 1.” The Boolean operator to connect this row with the former ones is “and.” All other values remained as default, resulting in no further query specification. As the “advanced retrieval” search engine processes queries sequentially from the top row to the bottom row, this query asks to return sentences with at least one association or regulation term in conjunction with at least two genes mentioned by name. For the semiautomatic information extraction from text, the same query was utilized as above. In addition, sentences that did not mention at least two uniquely named genes were eliminated.

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An interactional network of genes involved in chitin synthesis in Saccharomyces cerevisiae

Background In S. cerevisiae the β-1,4-linked N-acetylglucosamine polymer, chitin, is synthesized by a family of 3 specialized but interacting chitin synthases encoded by CHS1 , CHS2 and CHS3 . Chs2p makes chitin in the primary septum, while Chs3p makes chitin in the lateral cell wall and in the bud neck, and can partially compensate for the lack of Chs2p. Chs3p requires a pathway of Bni4p, Chs4p, Chs5p, Chs6p and Chs7p for its localization and activity. Chs1p is thought to have a septum repair function after cell separation. To further explore interactions in the chitin synthase family and to find processes buffering chitin synthesis, we compiled a genetic interaction network of genes showing synthetic interactions with CHS1 , CHS3 and genes involved in Chs3p localization and function and made a phenotypic analysis of their mutants. Results Using deletion mutants in CHS1 , CHS3 , CHS4 , CHS5 , CHS6 , CHS7 and BNI4 in a synthetic genetic array analysis we assembled a network of 316 interactions among 163 genes. The interaction network with CHS3 , CHS4 , CHS5 , CHS6 , CHS7 or BNI4 forms a dense neighborhood, with many genes functioning in cell wall assembly or polarized secretion. Chitin levels were altered in 54 of the mutants in individually deleted genes, indicating a functional relationship between them and chitin synthesis. 32 of these mutants triggered the chitin stress response, with elevated chitin levels and a dependence on CHS3 . A large fraction of the CHS1 -interaction set was distinct from that of the CHS3 network, indicating broad roles for Chs1p in buffering both Chs2p function and more global cell wall robustness. Conclusion Based on their interaction patterns and chitin levels we group interacting mutants into functional categories. Genes interacting with CHS3 are involved in the amelioration of cell wall defects and in septum or bud neck chitin synthesis, and we newly assign a number of genes to these functions. Our genetic analysis of genes not interacting with CHS3 indicate expanded roles for Chs4p, Chs5p and Chs6p in secretory protein trafficking and of Bni4p in bud neck organization.

Background In vegetatively growing cells of Saccharomyces cerevisiae , chitin, a linear polymer of β-1,4-linked N-acetylglucosamine (GlcNAc) residues, is selectively concentrated at the bud neck and is also found as a minor component of the mature lateral cell wall. Chitin is also the main constituent of the primary septum, a structure that separates mother and daughter cells (for reviews, see [ 1 - 3 ]). Polymerization of UDP-GlcNAc to chitin is catalyzed by a family of three membrane-associated chitin synthases (CS) with specialized activities. CSIII, encoded by CHS3 , is responsible for synthesis of the chitin ring at the bud neck and for chitin in the lateral wall. CSII synthesizes the chitin of the primary septum, and is encoded by CHS2 , a gene that is essential in many strain backgrounds [ 4 ]. CSI, encoded by CHS1 , is localized to the plasma membrane and to chitosome vesicles [ 5 ] and mutants are hypersensitive to the chitin synthase inhibitor, polyoxyin D, and under acid conditions can form small aberrant buds that are prone to lysis [ 6 ]. Disruption of the chitinase gene CTS1 required for cell separation suppresses the chs1 lysis phenotype, leading to the suggestion that Chs1p is involved in chitin repair at cytokinesis [ 7 ]. The precise deposition of chitin is achieved through spatial and temporal controls on each chitin synthase which determine their localization and activity. CSII is expressed in a cell cycle-dependent manner, and is transported to the bud neck through the secretory pathway, and subsequently degraded in the vacuole [ 8 , 9 ]. CSI and III are transported to a specialized endosome-derived compartment, the chitosome, from which they are mobilized by regulated secretion to the plasma membrane [ 5 , 8 , 10 ]. The localization and trafficking of Chs3p require BNI4 , CHS4/SKT5 , CHS5 , CHS6 and CHS7 . Chs7p is required for exit of Chs3p from the endoplasmic reticulum [ 11 ], while Chs5p and Chs6p are involved in transport of Chs3p from the chitosome to the plasma membrane [ 12 , 13 ]. Chs3p forms a complex with Chs4p/Skt5p, a protein required for Chs3p activity during vegetative growth, and Bni4p localizes this complex to the septin ring at the bud neck [ 14 ]. Although accounting for only 1–2% of the wild type cell wall under vegetative growth, chitin can contribute up to 20% of the cell wall under the conditions of cell wall stress found in cell wall mutants or on drug exposure [ 3 ]. Indeed, in response to cell wall stress Chs3p activity is up-regulated leading to an increased synthesis of chitin, which can be essential for survival. For instance, CHS3 is essential for maintaining the cell integrity of several cell wall mutants, such as fks1 or gas1 [ 15 - 17 ]. Similarly, defective primary septum synthesis can be compensated for by Chs3p-dependent formation of a remedial septum, resulting in a synthetic lethal interaction between CHS2 and CHS3 [ 4 ]. To further explore the relationship between chitin synthesis and other pathways, we assemble a network of 316 synthetic interactions of 163 genes with genes involved in the regulation of chitin synthesis. The relationship of these genes with chitin synthesis was analyzed by measuring the chitin content of the 156 viable deletion mutants and by testing for Calcofluor white sensitivity phenotypes of the 116 deletion mutants in non-essential genes of the CSIII network. Results A network of genetic interactions with genes involved in chitin synthase function To identify genes buffering defects in chitin synthesis, we searched for genes engaged in synthetic interactions with BNI4 , CHS1 , CHS3 , CHS4 , CHS5 , CHS6 or CHS7 using the SGA methodology [ 18 , 19 ]. Our results identified 163 genes involved in 316 synthetic interactions that form a network in which BNI4 , CHS1 , CHS3 , CHS4 , CHS5 , CHS6 and CHS7 are connected to 22, 57, 63, 47, 71, 25 and 31 genes, respectively (Table 2 ). Genes interacting with BNI4, CHS3, CHS4, CHS5, CHS6 or CHS7 tend to be multiply connected, while those interacting with CHS1 form a more distinct subnetwork (Figure 1A ). Indeed, just 17 of the 57 CHS1 interacting genes show an additional interaction with at least another query gene (Figure 1B ). In contrast, 67/123 genes interacting with BNI4 or CHS3-7 are multiply connected (Figure 1B , green oval), and 55 of those show an interaction with either BNI4 or CHS3-7 (Figure 1B , red oval) resulting in a densely connected CSIII network. Table 2 Synthetic interactions with BNI4 , CHS1 , CHS3 , CHS4 , CHS5 , CHS6 and CHS7 . Functional category Gene Interacting partners Cell wall maintenance BCK1 BNI4, CHS1, CHS3, CHS4, CHS5, CHS7 FKS1, SLT2, SMI1 BNI4, CHS3, CHS4, CHS5, CHS6, CHS7 YPL261C CHS1 ECM21 CHS1, CHS5 CHS2 CHS3 SWI4 CHS3, CHS4, CHS5 CCW12, GAS1, YLR111W CHS3, CHS4, CHS5, CHS7 TUS1 CHS4, CHS5, CHS7 DAN3, PAT1 CHS5 Cell polarity & vesicular transport NBP2, RGD1, SHS1, SPA2 BNI4 EDE1, MYO2, RVS167, VRP1 BNI4, CHS3, CHS4, CHS5, CHS7 ARC40, ARP2 BNI4, CHS3, CHS4, CHS5, CHS6, CHS7 BNI1 BNI4, CHS3, CHS4, CHS7 RVS161 BNI4, CHS5 CYK3 BNI4, CHS7 BUD20, VPS5, VPS17, VPS29, VPS35 CHS1 HBT1 CHS1, CHS3 ARC18 CHS1, CHS3, CHS4, CHS5, CHS6 EMP24 CHS1, CHS3 BEM4, PEA2 CHS1, CHS5 CDC3, CDC11, IES6, SRV2, VAM7 CHS3 CDC12 CHS3, CHS4 FAB1 CHS3, CHS4, CHS5 CLA4 CHS3, CHS4, CHS5, CHS6, CHS7 SAC6, SLA1, TPM1 CHS3, CHS4, CHS5, CHS7 YLR338W CHS3, CHS4, CHS6 SHE4, SMY1 CHS3, CHS4, CHS7 VPS24, VPS67 CHS3, CHS5 AST1, LST4, YPK1 CHS4 SEC22 CHS4, CHS5 AOR1, HSE1, VPS21 CHS5 Suspected role in cell polarity & vesicular transport YPL066W BNI4 ILM1 BNI4, CHS3, CHS4, CHS6 SPF1 CHS1, CHS4 YGL081W CHS1, CHS5 YBR077C CHS3 GUP1 CHS3, CHS4, CHS5, CHS6 OPI3 CHS3, CHS4, CHS7 LSM6 CHS5 IST3 CHS6 Protein modification VAN1 BNI4, CHS3, CHS4, CHS5, CHS6, CHS7 YGL110C CHS1 ANP1, BTS1, MNN2, MNN9 CHS3 MNN10 CHS3, CHS4, CHS5, CHS6, CHS7 UBI4 CHS3, CHS5, CHS6 UBP13 CHS4 BRE1 CHS5 UFD4 CHS5 MNN11 CHS5, CHS6 LAS21 CHS6 Ribosomal function/cell size LGE1 CHS1, CHS3, CHS5 RPL20B CHS3 RPS8A CHS3, CHS4, CHS5 ASC1 CHS3, CHS5 RSA1 CHS4 RPL14A CHS5 Cell cycle CLN2 CHS1 CDC26, DOC1 CHS3 YNL171C CHS3, CHS5 CLB3, CTK2 CHS5 Mitochondrial function MDM38, NUC1, UTH1, YME1 CHS1 YFR045W CHS1, CHS5 MST1, TOM37 CHS3 YTA12 CHS3, CHS4 ATP17 CHS4 RPO41 CHS4, CHS6, CHS7 COQ2, COX11, LAT1, MDM12, PET8, SHE9 CHS5 Carbohydrate and lipid metabolism DEP1, ELO1, HXT8, IPK1, PDA1, PDC1, PFK2, PHO5, PKR1, RPE1, TYR1, YDR248C CHS1 Other functions BRE5 BNI4, CHS3, CHS4 IXR1 BNI4, CHS5 CNB1, HAP2, HIT1, PEX22, PMP3, PRM3, SKI2, WHI2 CHS1 RPA34 CHS1, CHS3, CHS4, CHS5, CHS7 FPS1 CHS1, CHS4, CHS5 GRS1, LEA1, MRE11 CHS1, CHS5 CSF1 CHS3, CHS4, CHS5 PRE9 CHS3, CHS5, CHS7 MUM2 CHS3, CHS6 UME6 CHS4, CHS6 DOT1, PDE2, PEX14, SWI3 CHS5 IRA2 CHS5, CHS6 NUP133 CHS5, CHS6, CHS7 MSN5 CHS6 PEX6 CHS7 Unknown function YBR209W, YDR314C, YEL033W, YIL110W, YMR003W, YNL179C, YOR322C, YPR053C CHS1 YDL206W CHS1, CHS5 YDL032W CHS3 YDL033C CHS3, CHS5 YGL152C CHS5 YNL235C CHS6 YIL121W CHS7 Figure 1 A network of genetic interactions with BNI4 , CHS1 , CHS3 , CHS4 , CHS5 , CHS6 and CHS7 . (A) Global view of the network. Synthetic interactions with any query gene (diamonds) are depicted as edges joining these to nodes (circles). Nodes whose deletion mutant have a decreased, wild type and increased chitin content are colored in green, gray and red, respectively. For the decreased (green) and increased (red) chitin contents, color intensity is proportional to the magnitude of the change. (B) Venn diagram of the CHS1 interaction set with the CSIII network. The number of genes interacting with CHS1 or with any of the CSIII query genes is indicated. The numbers in parentheses indicate the number of interactions for multiply connected genes. Genes showing 2 or more interactions are grouped in green or red ovals, respectively. The CSIII network The 123 genes engaged in the 259 interactions of the CSIII network were grouped by function (Figure 2A , outer pie). Some genes show multiple connections, with 55 of these accounting for almost 75% of the interactions. Among this group, 44 genes (Figure 2B ) interact with CHS3 and at least one other query gene, reflecting the central role of CHS3 in the network. These 44 genes, involved in 166 interactions, are significantly more connected to the query genes than the remaining 11 multiply connected genes, which have 25 interactions ( p < 0.01). Thus, this set of 44 genes defines a core group of multiply interacting genes. In addition, the "core" genes account for 57 of 74 synthetic lethal interactions of the CSIII network [ 19 ], highlighting their importance for survival when the CSIII pathway is defective. Grouping "core" genes by functional categories (Figure 2A , inner pie) revealed enrichment for certain functions relative to the overall CSIII network. For example, cell wall assembly and secretory pathway polarization/vesicular transport contain 18% and 43% of "core" genes, respectively, whereas these functional categories represent 10% and 33% of genes in the CSIII network, respectively. In contrast, the category "mitochondrial function" is under-represented in the "core" group when compared to the CSIII network (Figure 2A ). Thus, analysis of the "core" of highly connected genes indicates that cell wall assembly and polarization of the secretory apparatus are central processes buffering defects in the CSIII pathway. Figure 2 Analysis of the CSIII network. (A) Grouping genes of the CSIII network in functional categories. Genes belonging to the "core" group ( CHS3 plus at least one other) are underlined. The proportions of the functional categories in the CSIII network and in the "core" group are represented in the outer and the inner pies, respectively. (B) Interactions among the "core" group. Color coding for nodes is as in (A). CHS1 interaction set Some 57 genes show synthetic interactions with CHS1 (Figure 1A and Table 2 ), and while a number of these are embedded in the CSIII network, most interact only with CHS1 , indicative of a distinct functional role for Chs1p that is analyzed further in the Discussion. Chitin content in mutants of interacting genes To investigate the relationship between the interacting genes and chitin synthesis, the chitin content of the 156 deletion mutants in non-essential genes of the CSIII network and the CHS1 interacting genes was measured (see Additional file 2 ). To focus on the biologically meaningful changes in chitin level, a set of mutants with marginally altered chitin content were excluded from our analysis despite their having statistical significance. Thus, 51 and 3 mutants with levels above 20 and below 12 nmole GlcNAc/mg dry weight, respectively are discussed below as having altered chitin content. To integrate synthetic interaction and chitin determination data, each node of the interaction network was colored according to the chitin level of its deletion mutant (Figure 1A ). Four groups of genes emerged from this analysis. Group 1 has 33 mutants with an altered chitin level and a requirement for Chs3p function for optimal growth (Figure 3A ). All but one of the group 1 mutants have elevated chitin levels, indicating that they trigger the chitin stress response. Nine of these genes are involved in the synthesis of cell wall components such as β-glucan and mannoprotein. Half of the group 1 genes (17/33) are required for polarization of the actin cytoskeleton or have a function in vesicular transport through retrograde transport in the endosomal pathway. The majority of the group 1 genes belong to the CSIII network "core", with just 7 genes interacting uniquely with CHS3 ( ANP1 , BTS1 , DOC1 , MNN2 , MNN9 , RPL20B and YBR077C ). Thus, the deletion mutants of group 1 genes are highly sensitive to CSIII pathway perturbation. Figure 3 Grouping deletion mutants with an altered chitin content according to their interaction pattern. (A) Chitin levels, expressed in nmole GlcNAc/mg dry weight, in wild type, group 1 and query mutants. (B) Chitin levels in wild type and group 2 mutants. Note the different scales in (A) and (B). Hypersensitivity, resistance, wild type and not determined sensitivity to Calcofluor are indicated by black, open, gray and hatched bars, respectively. Group 2 is composed of 19 and 2 mutants with an increased and a decreased chitin level, respectively, but whose optimal growth does not require CHS3 (Figure 3B ). A large fraction of group 2 genes (16/21, 76%) interact with CHS5 and/or CHS6 (Table 2 ). Group 2 mutants are affected in secretion or mitochondrial functions and in the regulation of transcription and translation. The elevated synthesis of chitin in 19 of the group 2 mutants is probably triggered as a non-specific stress response to the mutation, but unlike group 1, it does not serve to buffer against the deleterious effects of the mutation. For example, a set of 14 group 2 mutants interacting with CHS5 or CHS6 have elevated chitin levels. In these cases, the stress activated chitin response reflects a broader Chs5p- and/or Chs6p-dependent activation that is required for cell wall buffering in these mutants (see Discussion). The third group of 16 mutants have a wild type chitin content and a synthetic interaction with CHS3 (Figure 4A ). These mutants are defective in ubiquitin processing/cell cycle progression, membrane biogenesis and polarized secretion. Figure 4 Grouping deletion mutants with wild type chitin content according to their interaction pattern. (A) and (B) group 3 and 4 mutants, respectively. Hypersensitivity, resistance, wild type and not determined sensitivity to Calcofluor are indicated by bold, open, gray and underlined characters, respectively. Finally, group 4 contains deletion mutants in 57 genes with a wild type chitin level and a synthetic interaction with any CHS gene other than CHS3 (Figure 4B ). Sixteen of these genes are connected to CHS5 , suggesting a broad, and Chs3p-independent, role for Chs5p in their buffering. Calcofluor white phenotypes of the CSIII network mutants Calcofluor white is a toxic compound which binds primarily to chitin in yeast, and mutants with cell surface defects frequently show altered sensitivity to it [ 20 - 23 ]. For example, a chs3 null mutant and mutants with a defective CSIII pathway show Calcofluor resistance because they make low levels of cell wall chitin [ 23 ]. We thus searched for synergistic interactions between Calcofluor white and the deletion of each gene found in the CSIII network. Mutant strains were spotted on solid medium containing 10 μg/ml or 50 μg/ml Calcofluor white, and scored for sensitivity relative to the wild type. In all, 59% of mutants exhibited an altered Calcofluor sensitivity, with 65 and 4 mutants showing hypersensitivity and resistance, respectively (Figure 3 and 4 , and see Additional file 2 ). As seen in Figure 3 , a high fraction of mutants with an altered chitin content also showed an altered sensitivity to Calcofluor. Indeed, 80% (39/49) and 67% (2/3) of mutants with increased and decreased chitin levels, respectively, were hypersensitive and resistant to Calcofluor, respectively. More specifically, 97% of group 1 mutants had a Calcofluor phenotype, revealing the critical role of Chs3p-synthesized chitin in Calcofluor sensitivity. However, Calcofluor toxicity does not correlate strictly with the chitin level or the requirement for Chs3p function. Indeed, 10 mutants with wild type Calcofluor sensitivity have an altered chitin content (Figure 3 , gray bars). This set is almost entirely composed of group 2 mutants (Figure 3B ), with the optimal growth of 9 of these mutants not requiring CHS3 . In addition, 17 mutants with an altered Calcofluor sensitivity have a wild type chitin level (Figure 4 , bold and open characters): 8 and 9 of those mutants fall in groups 3 and 4, respectively. The 8 group 3 mutants require Chs3p function but do not trigger the chitin stress response, indicative of a requirement for an additional Chs3p function distinct from lateral wall chitin synthesis, such as remedial septum or bud neck chitin synthesis (see Discussion). The 9 group 4 mutants require integrity of the CSIII pathway but not an increase of chitin level through Chs3p. This subgroup indicates that components of the CSIII pathway function in other cellular processes. Finally, a set of 26 mutants are wild type for both Calcofluor sensitivity and chitin level. Nineteen of them are not connected to CHS3 , reflecting chitin-independent functional requirements for CHS4 , CHS5 , CHS6 , CHS7 and BNI4 . Synthetic interactions with SHC1 The SHC1 gene product is 43% identical to Chs4p. While Chs4p functions in Chs3p activation during vegetative growth, the known role of Shc1p is restricted to sporulation [ 24 ]. However, overexpression of Shc1p during vegetative growth can compensate for the lack of Chs4p, and reciprocally, overexpression of Chs4p during sporulation partially complements the shc1 Δ mutant phenotype [ 24 ]. Although Chs4p and Shc1p show structural and functional relatedness they are not an essential redundant pair since the chs4 shc1 double mutant has no synthetic growth defect. We searched for genes required for the optimal vegetative growth of the shc1 Δ mutant and found 6 synthetic interactions. In addition, we added the previously reported synthetic interaction between PHO85 and SHC1 [ 25 ] to this list. FAB1 and DEP1 are part of the CSIII network and CHS1 -interacting set, respectively. The remaining 5 genes ( BUD16 , DBF2 , HOP2 , PHO85 and SPT8 ) interact uniquely with SHC1 . The pho85 null mutant was not further analyzed due to its very poor growth. The amount of chitin produced in the 4 remaining mutants was measured and found to be similar to the wild type (see Additional file 2 ). Genes compensating for a SHC1 deletion form a distinct group from those buffering a CHS4 deletion (Figure 5 ), and their genetic interactions with SHC1 appear to be independent of a chitin defect. Thus, our synthetic interaction data indicate that SHC1 has evolved new functions that are not shared with CHS4 and which extend the role of Shc1p beyond sporulation to mitotic growth. Figure 5 Comparative synthetic interaction patterns of CHS4 and SHC1 . Synthetic interactions with CHS4 or SHC1 are depicted as connections between these nodes and their respective partners (black and gray nodes, respectively). Discussion We globally analyzed a network of 259 interactions among 123 genes required for optimal growth of BNI4 , CHS3 , CHS4 , CHS5 , CHS6 or CHS7 deletion mutants. The query genes are highly interconnected, reflecting common requirements in the bni4 and chs3-7 null mutants. This network centers on CHS3 function, with CHS3 sharing most of its interactions with the other query genes. Grouping CHS3 -interacting genes by functional requirement for Chs3p The genetic interactions observed with CHS3 can be sorted by Chs3p function, which includes synthesis of chitin in the lateral wall, in the remedial septum and at the bud neck. Lateral wall chitin, the chitin stress response The Chs3p-dependent synthesis of wall chitin is dramatically stimulated upon cell wall stress, through a stress response pathway involving activation of the chitosome and stimulation of the cell integrity pathway [ 10 , 15 - 17 ]. Mutants with cell wall defects activate this stress pathway and our synthetic analysis indicates that many of them require Chs3p function (Figure 6 ). Our work indicates that the extent of this stress response is far greater than previously realized: just 6 of the 26 mutants in this group were previously known to have an altered chitin content. Among such new mutants involved in triggering the chitin stress response are the cell wall protein encoding gene CCW12 , and the actin-based polarity genes BNI1 , CLA4 , SAC6 , SHE4 , SLA1 and VRP1 . Actin patches are crucial for the proper targeting of cell wall synthesis components [ 26 ], and their perturbation activates a chitin stress response. Other mutants include CSF1 , GUP1 and ILM1 that have growth defects on non-fermentable carbon sources and the putative vacuolar protein encoding YBR077C . Figure 6 Functional integration of CHS1 - and CHS3 -interaction sets. CHS1 - and CHS3 -interacting genes were grouped according to their effects on chitin synthesis. The Venn diagram shows the distinct and overlapping sets for each functional category. Glucosamine-driven chitin synthesis Chs3p has an additional role in the synthesis of chitin upon glucosamine addition [ 27 ]. The basis for this process is uncertain, but probably relies on metabolic flux changes and appears to be independent of the classic chitin stress response [ 27 ]. Deletion of genes compensating for defects in this glucosamine-response pathway may interact synthetically with CHS3 and genes of the CSIII pathway (Figure 6 ). Candidate genes are MST1 , TOM37 and YTA12 , involved in mitochondrial function, a process known to be down-regulated by glucosamine exposure: their deletion may lead to metabolic imbalance compensated for by an increased chitin synthesis. Insight into Chs2p function Chs2p is responsible for synthesis of the primary septum but a detailed understanding of how this is achieved remains incomplete. Analysis of CHS3 synthetic interactions can give insight into Chs2p function as, in its absence, Chs3p can partially compensate by forming a "remedial septum" [ 28 ]. We reasoned that a set of synthetic interactions with CHS3 could occur through perturbation of CHS2 function, leading to the need for CHS3 . A group of genes affecting cell cycle progression likely have an impact on septation in this way. For example, mutants in CDC26 , DOC1 or YNL171C (which is an apc1 allele) show a delay in exit from mitosis and mutants in ASC1 , IES6, LGE1, RPL20B, RPS8A or VAM7 exhibit altered cell size, a phenotype frequently reflecting defects in cell-cycle checkpoints [ 29 , 30 ]. Deletion of any of these genes can uncouple cell-cycle progression and septation, resulting in defective synthesis of the primary septum by Chs2p. The synthetic interactions between these genes and CHS3 likely result from a failure to fully synthesize both the primary septum (as a consequence of a defect in cell-cycle progression) and a remedial septum (Figure 6 ). Pertinently and consistent with our data, Ufano et al . [ 31 ] show that deletion of SWM1 , encoding a subunit of the anaphase promoting complex, also leads to an increase of Chs3p-catalyzed chitin deposition. Chs2p has a cryptic in vitro activity that can be detected only after treatment of a cell extract with trypsin. This suggests that Chs2p may also be produced as a zymogen in vivo and be activated by posttranslational modification [ 32 ]. Although proteomic analysis reveals the existence of ubiquitinated and phosphorylated forms of Chs2p [ 33 , 34 ], the effect of these modifications on Chs2p activity is unknown. Mutants with defects in Chs2p activation or turnover may exhibit a low Chs2p activity and depend on a compensatory Chs3p activity. Of the CHS3 interacting genes, the serine/threonine protein kinases Bck1p and Slt2p are candidates for Chs2p activation, while the polyubiquitin gene UBI4 , the ubiquitin protease Bre5p and the proteasome subunit Pre9p may be required for Chs2p turnover (Figure 6 ). Chitin at the bud neck Chs3p synthesizes a chitin ring that marks the incipient bud site. Defects in secretion or polarization of the secretory apparatus may lead to abnormal bud neck assembly and/or septation. For example, the genes EDE1 , EMP24 , FAB1 , HBT1 , OPI3 , RVS167 , SMY1 , TPM1 , VPS24 , VPS67 or YBR077C are required for polarization of the secretory pathway, indicating that transport and proper localization of protein(s) to the bud neck are essential for growth of mutants with low CSIII activity. Thus, we identify these genes as candidates for involvement in Chs2p localization and in bud neck integrity (Figure 6 ). Functions of Bni4p, Chs4p and Chs5p beyond chitin synthesis The existence of synthetic interactions with BNI4 , CHS4 , CHS5 or CHS6 not shared with CHS3 uncovers functions of these genes that are unrelated to Chs3p transport or activity. Bni4p Five genes interact uniquely with BNI4 , indicating that Bni4p has functions distinct from anchoring Chs3p to the septin ring. Among these, NBP2 , RGD1 , SHS1 and SPA2 are required for regulation of cytoskeleton organization at the bud neck by the cell integrity pathway. Further, BNI4 shows a unique interaction with YPL066W , which together with the bud neck localization of Ypl066p [ 35 ] implicates this gene in bud development. Our data and the finding that localization of Crh2p at the bud neck requires Bni4p [ 36 ] indicate that Bni4p has a broad role in bud neck organization. Chs4p Of the 7 unique CHS4 interacting genes, 4 are required for trafficking of membrane proteins. Ast1p and Lst4p are required for Golgi to plasma membrane transport of the H + -ATPase Pma1p and the amino-acid permease Gap1p, respectively [ 37 , 38 ]. Spf1p, a putative calcium pump of the endoplasmic reticulum, may also play a role in the translocation of transmembrane proteins [ 39 ]. Ypk1p, a serine/threonine protein kinase required for full induction of the PKC1-SLT2 cell integrity pathway under stress condition, is also required for endocytosis [ 40 ]. Absence of these genes combined with a CHS4 deletion likely leads to defects in targeting membrane proteins to the septin ring, with resultant synthetic growth phenotypes. Chs5p and Chs6p Chs5p and Chs6p are late-Golgi localized proteins involved in targeting Chs3p to sites of polarized growth [ 12 ] and to the plasma membrane [ 13 ]. Our results for CHS5 and CHS6 , showing a strong web of synthetic interactions with CSIII network "core" genes, reflect these roles. Whereas little is known about a Chs6p function besides Chs3p trafficking, Chs5p is also involved in the selective polarization of other surface proteins, such as Fus1p [ 41 ] and, at least partially, Crh2p [ 36 ]. CHS5 and CHS6 show a large number of CHS3 -independent interactions (39/71 and 9/25, respectively), suggesting multiple additional roles for Chs5p and Chs6p in protein targeting. Interestingly, a number of these interacting mutants have elevated chitin levels and fall into group 2. For example, the mutants ira2 and pde2 are synthetic with CHS5 and CHS6 and CHS5 , respectively and make 76% and 35% more chitin than the wild type, respectively (Figure 3B ). These mutants constitutively elevate the Ras/cAMP pathway and pde2 mutants are known to affect cell wall integrity and to cause slight changes in glucan and chitin levels [ 42 , 43 ]. Our work suggests that the chitin elevation involves increased activity of the Chs5p and Chs6p chitosome pathway. However, the key buffering component in this cAMP response is not chitin, but must be some other component of the activated chitosome pathway, since neither ira2 nor pde2 show a synthetic interaction with CHS3 . Thus here, the stress activated chitin response is a gratuitous consequence of a broader Chs5p- and/or Chs6p-dependent activation that is required for cell wall buffering in these mutants. Regarding the known role of Chs5p in specialized late-Golgi trafficking; several of the CHS5 -interacting genes have products that likely work in conjunction or in parallel with Chs5p. These include AOR1 , BEM4 , HSE1 , LSM6 , PEA2 , RVS161 , SEC22 and VPS21 . A new candidate is YGL081W that interacts with CHS5 , and whose product has been found in a complex containing Cop1p, required for Golgi retrograde transport [ 44 ]. CHS5 interacts uniquely with 6 genes involved in mitochondrial function ( COQ2 , COX11 , LAT1 , MDM12 , PET8 and SHE9 ) some of which show elevated chitin levels. These mitochondrial proteins may play indirect roles in late-Golgi trafficking; for example, the secretory apparatus and mitochondria exchange lipids [ 45 ], and a defect in mitochondrial function may impact on secretory function. Alternatively, in the absence of CHS5 , mitochondria may be poorly transferred to daughter cell with their efficient functioning being essential for optimal growth. Finally, some 9 genes show an interaction with both CHS5 and CHS1 (Figure 1A ), indicating some common requirement for these genes. One provocative possibility for this interactional signature is that Chs5p is involved in the targeting of Chs1p. Analysis of synthetic interactions with CHS1 Although it was the first fungal chitin gene identified, the role of Chs1p has remained unclear. Cell lysis phenotypes of chs1 mutants have led to the view that Chs1p is an "auxiliary" enzyme implicated in the repair of chitinase-mediated cell wall damage associated with cell separation [ 7 ]. How such damage is sensed or how the repair process is activated remains unclear. The line between repair and redundant synthesis with Chs2p may be an arbitrary one, and a direct role for Chs1p involvement in septal chitin synthesis on growth in acidic minimal media where cell lysis is more pronounced, also explains the phenotype (see [ 46 ] for a discussion). The lysis phenotypes associated with CHS1 deletion also show strain variability. For example, a strain with a recessive suppressor in an uncharacterized gene SCS1 shows no lysis phenotype, indicating the involvement of other genes [ 7 ]. Our synthetic approach allows a broad survey of possible CHS1 function. However, CHS1 is part of a family and a synthetic analysis of a gene family can be complicated [ 47 ]. Specialized roles for CHS1 , CHS2 and CHS3 are likely ancient, predating the genome duplication of S. cerevisiae [ 48 , 49 ], since all three genes are present in Ashbya gossypii , a related fungus that did not undergo the S. cerevisiae duplication event. Our finding that the majority of the CHS1 interactions are both distinct from the CSIII network and do not trigger the chitin stress response (Figure 1A ) indicates distinct function. CHS1 and CHS3 mutants do not synthetically interact under our test conditions, so the synthetic effects of CHS1 mutants are not caused by a buffering of CHS3 function. Consistent with this, the CHS1 deletion does not activate the chitin stress response, as chitin levels in the chs1 Δ mutant are close to wild type [ 6 ], see Figure 3A ). One possible cause of synthetic effects of CHS1 mutants is through genes that buffer Chs2p function. A number of unique interactors with CHS1 are involved in bud morphogenesis ( BEM4 , BUD20 , PEA2 ), and in protein recycling through the endocytic pathway ( VPS5 , VPS17 , VPS29 and VPS35 ), all could be required for Chs2p function (Figure 6 ). This hypothesis, supported by the genetic evidence presented here, will require further testing. In our data we also find interactions with mutants in a number of genes that are singly prone to lysis or show phenotypes consistent with osmotic imbalance ( ARC18 , BCK1 , CNB1 , FPS1 , and WHI2 ). CHS1 also shows synthetic interactions with YEL033W and YNL179C , that overlap with and are alleles of YEL034W/HYP2 and YNL180C/RHO5 , genes that play a role in balancing cell integrity [ 50 , 51 ], and with YOR322C which has a role in signaling through the cell integrity pathway [ 52 ]. In addition the absence of Chs1p is buffered by the presence of 16 genes ( BCK1 , BEM4 , CNB1 , ECM21 , FPS1 , GRS1 , HBT1 , HIT1 , NUC1 , PDA1 , PFK2 , SPF1 , TYR1 , YGL081C , YGL110C and YPL261C ) that show synthetic interactions with the FKS1 , GAS1 or SMI1 genes involved in β-1, 3-glucan synthesis [ 19 ]. These results provide strong independent support for a function of Chs1p in buffering cell wall robustness through regulated chitin synthesis, and identify many candidates that may participate in the modulation of Chs2p function. As mentioned above, yeast cells are more dependent on Chs1p to prevent lysis and allow growth on synthetic minimal media [ 6 , 53 ]. The basis for this increased dependence is unknown, though there are data indicating that the partitioning of Chs1p activity between the plasma membrane and the chitosome is somewhat more pronounced toward the plasma membrane in minimal medium [ 54 ]. Interestingly, a number of unique CHS1 interactors are involved in metabolism and nutrient utilization (Figure 6 ), providing functional clues to this aspect of Chs1p function. Conclusions Our synthetic network analysis reveals a deep interactional complexity underlying chitin biology. The CHS3 -core network is informative in identifying components involved in all aspects of regulated chitin deposition. The chitin stress response that adds chitin to lateral cell walls is now shown to be triggered very broadly by cell wall and actin-based polarity defects and to play a key role in cell wall buffering. The CHS3 core-network also offers insight into Chs2p function by identifying proteins implicated in bud neck localization, and in the cell cycle coordination of septum formation with mitotic exit. Genes involved in secretory trafficking of Chs3p ( CHS4 , CHS5 , CHS6 and BNI4 ) show many CHS3 -independent interactions and these greatly expand the range of trafficking functions for these genes, especially for the heavily interacting CHS5 . In contrast to its currently assigned minor auxiliary role, CHS1 shows an extensive web of genetic interactions, most of which are distinct from the CSIII network and which do not trigger the chitin stress response. One set of these identifies components of endocytosis, budding and cell morphology, which may be required for Chs2p function. A second set of 25 interacting genes show that Chs1p is intimately involved in buffering yeast cell wall robustness during vegetative growth. Methods Strains, media and drugs Haploid deletion mutants (Table 1 ) are available from the deletion project consortium. These strains were arrayed on sixteen 768-format plates using a colony picker [ 18 ]. Starting strains for the SGA analysis (Table 1 ) were constructed as described in Tong et al. [ 19 ]. Arrays were propagated at 30°C on standard YEPD (10 g/l yeast extract, 20 g/l bacto-peptone, 20 g/l glucose) or YEPD supplemented with 200 μg/ml G-418 (Invitrogen, Carlsbad, CA). When required, strains were grown on standard SD medium (6.7 g/l yeast nitrogen base, 20 g/l glucose) supplemented with appropriate amino acids [ 55 ]. Nourseothricin (ClonNat) was purchased from Werner Bioagent (Jena, Germany). Table 1 Strains used in this study. Strain Genotype Reference BY4741 MATa his3 Δ leu2 Δ met15 Δ ura3 Δ [60] BY4742 MATα his3 Δ leu2 Δ lys2 Δ ura3 Δ [60] BY4743 MATa/α his3 Δ /his3 Δ leu2 Δ /leu2 Δ met15 Δ /MET15 lys2 Δ /LYS2 ura3 Δ /ura3 Δ [60] ΔarrayORF MATa orf Δ ::KanMX4 his3 Δ leu2 Δ met15 Δ ura3 Δ [61] HAB1122 As Y3656 chs3 Δ ::NatMX4 [19] SBY4 As Y3084 chs1 Δ :: NatMX4 [19] SBY5 As Y3084 chs5 Δ :: NatMX4 [19] SBY6 As Y3084 chs7 Δ :: NatMX4 [19] SBY30 As Y3084 chs4 Δ :: NatMX4 [19] SBY70 As Y3084 shc1 Δ ::NatMX4 This work SBY105 As Y3656 chs6 Δ :: NatMX4 [19] Y3084 MATα mfα1 Δ ::MFα 1pr-LEU2 can1 Δ ::MFA1pr-HIS3 his3 Δ leu2 Δ lys2 Δ ura3 Δ [18] Y3638 As Y3084 bni4 Δ :: NatMX4 [19] Y3656 MATα can1 Δ ::MFA1pr-HIS3-MFα 1pr-LEU2 his3 Δ leu2 Δ lys2 Δ ura3 Δ [19] Screening for synthetic lethal/sick interactions and data refinement Synthetic genetic array analysis (SGA) was used to identify genes required for the optimal growth of strains deleted for BNI4 , CHS1 , CHS3-7 or SHC1 , as described [ 18 , 19 ]. From three SGA screens for each "query" gene, ~1,800 potential interactions were identified and 333 synthetic interactions confirmed by random spore or tetrad analysis as described previously [ 19 ]. Briefly, spores were germinated into liquid haploid selection medium [SD-His/Arg + canavanine] in a 96-well format. The germinated MATa spore progeny were serially diluted in sterile water and 2 μl for each dilution was spotted onto medium selecting for the query-gene mutation [SD-His/Arg + canavanine/Nourseothricin], the interacting gene mutation [SD-His/Arg + canavanine/G-418], and both the query-gene and interacting gene mutations [SD-His/Arg + canavanine/Nourseothricin/G-418] then incubated at 30°C for ~2 days. Cell growth under the three conditions was compared and double mutants were scored as synthetic sick (SS), synthetic lethal (SL) or no interaction (No) [ 19 ]. For tetrad analysis, dissections were performed on solid complete SD medium and growth of individual spores was scored after 4 days incubation at 30°C. Plates were then replicated on YEPD + G-418 or Nourseothricin to identify tetrad type. Growth of double mutants was compared to that of single mutants from tetratype tetrads and then scored as "SS", "SL "or "No". Ten of the 22 previously reported synthetic lethal interactions with CHS3-7 or SHC1 [ 4 , 15 , 25 , 56 , 57 ] were found by the SGA procedure. Of the remaining, 9 engaged genes whose mutant is absent from our deletion collection ( CDC3 , CDC11 , CDC12 and CHS2 ) or genes whose deletion leads to systematic growth defects in our conditions ( ANP1 , MNN9 , PHO85 and SRV2 ) and these genes were used in our network analysis. No synthetic interaction between GAS1 and CHS4 or CHS7 was found by the SGA. These discrepancies with other's data [ 56 ] reflect differences in strain background. These two synthetic interactions were included in our analysis. An additional set of 57 interactions were analyzed further by random spore or tetrad analysis [ 19 ]. Of these, 30 synthetic interactions were confirmed, with the 27 remainder discarded (see Additional file 1 ). It is important to note that this additional set of tested interactions was not random and was strongly biased toward dubious interactions: for example, a group of 11 interactions with genes closely linked to CHS1 or a set of 16 non-reciprocal interactions (that is gene A found in screen for genes interacting with gene B and gene B not found in the set of genes interacting with gene A). Chitin assay Stationary phase cultures were diluted 1:100 into 3 ml of YEPD and grown again for 22-24 h at 30°C. Cells from 1.5 ml culture were colleted by centrifugation (20,000 × g, 2 min). Pellets were then frozen at -20°C until used for alkali-extraction. Dry weights were determined after a 2 day incubation at 37°C. Cell pellets were resuspended in 1 ml 6% KOH and heated at 80°C for 90 min with occasional mixing. Alkaline insoluble material was pelletted (20,000 × g, 20 min), neutralized with phosphate-buffered saline for 10–20 min with occasional mixing. After centrifugation (20,000 × g, 20 min), 200 μl of McIlvaine's Buffer (0.2 M Na 2 HPO 4 /0.1 M citric acid, pH 6.0) was added to pellets. Extracts were then stored at -20°C until processed for chitin measurements. Samples were thawed and subjected to two digestions with 4 μl of purified Streptomyces plicatus chitinase-63 (4 μg/ul in PBS) at 37°C for 36–40 h and then for 20–24 h. The amounts of chitin were then determined by using the modified Morgan-Elson procedure as described previously [ 27 ]. The levels of chitin, expressed as GlcNAc concentration, were then normalized to the dry weight of the sample. Of the 84 mutants whose chitin levels differed significantly from wild type ( p < 0.01 in a Student's t-test, see Additional file 2 ), 54 with larger changes were further considered (see text). Calcofluor white sensitivity/resistance Sensitivity to Calcofluor white was assessed using a modified version of the method described by Ram et al. [ 21 ]. Cells were grown overnight, and then diluted to an optical density of OD 600 nm = 0.5. Five μl of this suspension, as well as 1:10, 1:100, and 1:1000 dilutions of this suspension, were spotted on SD plates (buffered to pH 6.2 with 10 mM MES) containing 10 μg/ml or 50 μg/ml Calcofluor white (Fluorescent Brightener 28, Sigma), and control plates. Plates were incubated at 30°C for 48 hours, photographed, and then rechecked after 72 hours. A literature search indicated that the phenotype we found agreed with that previously reported for 29 mutants (22 interacting mutants + 7 query mutants). In 4 cases however ( ARC18 , PDE2 , PEX6 and SPF1 ), we found a wild type sensitivity for mutants that had previously shown altered Calcofluor white sensitivity [ 22 , 42 , 58 , 59 ]. These discrepancies may be due to differences in Calcofluor white concentration or to allelic or strain variation. Authors' contributions GL participated in the design of the study and its coordination, collected and analyzed data, and drafted the manuscript. JS carried out confirmations of SGA screens and Calcofluor white sensitivity assays. CAS carried out chitin determinations and data analysis. AMS, PM, SH and AHYT carried out SGA screens. HB and CB conceived the study, and oversaw its design and coordination. HB participated in data analysis and manuscript writing. All authors read and approved the final manuscript. Supplementary Material Additional File 1 Title: Interactions reported previously and not included in our global analysis. Click here for file Additional File 2 Title: Sensitivity to Calcofluor white and chitin levels of mutants. Click here for file

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Protein kinases of the human malaria parasite Plasmodium falciparum: the kinome of a divergent eukaryote

Background Malaria, caused by the parasitic protist Plasmodium falciparum , represents a major public health problem in the developing world. The P. falciparum genome has been sequenced, which provides new opportunities for the identification of novel drug targets. Eukaryotic protein kinases (ePKs) form a large family of enzymes with crucial roles in most cellular processes; hence malarial ePKS represent potential drug targets. We report an exhaustive analysis of the P. falciparum genomic database (PlasmoDB) aimed at identifying and classifying all ePKs in this organism. Results Using a variety of bioinformatics tools, we identified 65 malarial ePK sequences and constructed a phylogenetic tree to position these sequences relative to the seven established ePK groups. Predominant features of the tree were: (i) that several malarial sequences did not cluster within any of the known ePK groups; (ii) that the CMGC group, whose members are usually involved in the control of cell proliferation, had the highest number of malarial ePKs; and (iii) that no malarial ePK clustered with the tyrosine kinase (TyrK) or STE groups, pointing to the absence of three-component MAPK modules in the parasite. A novel family of 20 ePK-related sequences was identified and called FIKK, on the basis of a conserved amino acid motif. The FIKK family seems restricted to Apicomplexa, with 20 members in P. falciparum and just one member in some other Apicomplexan species. Conclusion The considerable phylogenetic distance between Apicomplexa and other Eukaryotes is reflected by profound divergences between the kinome of malaria parasites and that of yeast or mammalian cells.

Background Modulation of protein phosphorylation through the antagonistic effects of protein kinases and protein phosphatases is a major regulatory mechanism of most cellular processes. Dysregulation of protein phosphorylation in human cells plays a major role in many diseases such as cancers and neurodegenerative disorders [ 1 ]. This has prompted the search for drugs targeting protein kinases, an endeavour which led in 2002 to the commercialisation of Gleevec, the first protein kinase inhibitor used as a drug for human disease [ 2 ]. Additional molecules targeting protein kinases are in clinical trial [ 3 , 4 ], and significant developments in this field are expected in the next few years. Some of the most devastating infectious diseases are caused by protists such as malaria parasites and trypanosomatids: hence, about half the global population lives in malarious areas, with 10% of the world population contracting the disease each year, which results in 1–3 million annual deaths. The essential role played by eukaryotic protein kinases (ePKs) in crucial cellular functions makes them attractive potential targets for drugs against such eukaryotic infectious agents [ 5 ]. Malaria parasites have a complex life cycle. Infection of human beings by Plasmodium falciparum , the species responsible for the lethal form of human malaria, begins with the bite of an infected Anopheles mosquito, which delivers sporozoites into the bloodstream. These cells establish an infection inside hepatocytes, where they undergo an intense multiplication generating several thousand merozoites, a process called exo-erythrocytic schizogony. The merozoites invade erythrocytes, where they also undergo schizogony, the process that is responsible for malaria pathogenesis. Some merozoites, however, arrest the cell cycle and differentiate into male or female gametocytes, which are infective to the mosquito. Once ingested by the insect, the gametocytes develop into gametes (which for the male cells involves three rapid rounds of cell division) and fuse into a zygote. Further development in the mosquito involves a process of sporogony, producing sporozoites that accumulate in the salivary glands and are now ready to infect a new human host (see for information on malaria). The observation that many parasitic ePKs display profound structural and functional divergences from their counterparts in their vertebrate hosts [ 5 - 7 ] suggests that specific inhibition is an attainable goal. The availability of PlasmoDB, a genomic database for Plasmodium falciparum [ 8 ], now permits a systematic analysis of the entire complement of ePKs encoded in the genome (the "kinome") of this pathogen, an important milestone both in our understanding of Plasmodium biology and in the definition of potential novel drug targets. Prior to the genomic era, the initial classification system of Hanks and Quinn [ 9 ] distributed ePKs into four major groups: • the cyclic-nucleotide- and calcium/phospholipid-dependent kinases (the AGC group); • the CMGC group, constituted of the cyclin-dependent- (CDK), mitogen-activated- (MAPK), glycogen-synthase- (GSK) and CDK-like kinases; • the calmodulin-dependent kinases (CaMK), and • the tyrosine kinases (TyrK). ePKs that did not clearly fit into any of these groups were placed into the OPK ("other protein kinases") group. The primary structure of all enzymes in these groups conform to the model described by Hanks, in which the catalytic domain is subdivided into eleven subdomains, which can be aligned across all groups. In addition to the "typical" ePKs, several enzymes possessing protein kinase activity, but which are unrelated (or only distantly related) to ePKs at the primary structure level, have been identified and termed "atypical protein kinases" (aPKs). These include phosphatidyl-inositol 3' kinase (PI3K), DNA-dependent protein kinase, and members of pyruvate dehydrogenase kinase family. Exhaustive analyses of the kinome of some model organisms have now been published. The kinome of S. cerevisiae contains 115 ePKs [ 10 ], and the genomes of D. melanogaster , C. elegans and H. sapiens comprise 239, 454 and 510–520 ePK-coding genes, respectively [ 11 - 14 ]. On the basis of this wealth of new data, three additional major ePK groups were recognized (reviewed in [ 15 ]: • the casein kinase 1 (CK1) group; • the STE group, which includes many enzymes functioning in MAPK pathways, although the MAPKs themselves belong to the CMGC group (STE stands for "sterile", referring to the fact that enzymes belonging to this group were first identified in genetic analysis of yeast sterile mutants); • the tyrosine kinase-like (TKL) group, which, as its name indicates, includes enzymes that are related to those in the TyrK group, although they are serine-threonine protein kinases. Furthermore, a description of the 369 non-receptor serine/threonine protein kinases of the plant Arabidopsis thaliana has recently been published [ 16 ]. Comparative examination of this and previously available kinomes has demonstrated that members of all major ePK groups can be found in yeast, worms, insects, mammals and plants, with the exception of TyrKs, which are not found in yeast. That most TyrKs function in hormone-response receptor-linked pathways suggests that this family arose as an adaptation to the needs for intercellular communication in multicellular organisms. It has however been reported recently that a few unicellular eukaryotes (Chlamydomonoas, Entamoeba and Phytophtora) possess putative TyrK family members [ 17 ]. Despite the fact that most serine-threonine ePKs groups are found in all eukaryotes, indicating that their appearance occurred early in evolution, each of the kinomes has nevertheless its specificities. A striking feature in this respect is the considerable extension of some ePK families in some organisms but not in others. For example, yeast and Drosophila have 4 and 10 members of the casein kinase 1 (CK1) group respectively, whereas the C. elegans genome encodes 85 CK1-related genes. With the exception of the plant A. thaliana , all eukaryotes whose kinome has been characterised, from yeast to man, belong to the Opisthokonta phylogenetic group. As depicted in Fig. 1 , this lineage represents only one small branch of the eukaryotic tree. Several eukaryotes of high medical importance, such as malaria parasites (Alveolates) or trypanosomes (Discicristates), belong to phylogenetic groups that are vastly distant from both the Opisthokonta and Planta branches [ 18 ]. This is reflected by many profound peculiarities in their basic biology (see [ 5 ] for a review). Divergences from model eukaryotes can also be expected not only at the level of individual protein kinases of these organisms (as has been previously documented in a number of instances – see [ 5 , 6 ] for reviews), but at the level of their kinome as well. As is documented below, our analysis of the P. falciparum kinome confirms this prediction. Figure 1 Phylogenetic distance between malaria parasites and the organisms used as model Eukaryotes. With the exception of the plant Arabidopsis , the organisms whose kinome has been characterised (yeast, worms, Drosophila and human), all belong to the Opisthokonta lineage, which is vastly distant from the Alveolata branch which include the Apicomplexa . Adapted from Badlauf, S (2003), with permission (Copyright 2003 AAAS). Results and discussion Overview of the tree 65 sequences related to ePKs were retrieved from PlasmoDB and used to construct a phylogenetic tree as described in the Methods section (see Additional file 1 for the alignment). The tree of the P. falciparum kinome (Fig. 2 ) indicates that although the parasite possesses enzymes belonging to most of the major serine/threonine kinase groups, as described in the following paragraphs, several enzymes do not cluster with any of these groups. Figure 2 The P. falciparum kinome. Phylogenetic tree of ePKs from P. falciparum . The tree was compiled using conserved portions of aligned sequences using a protein distance matrix method (see Additional file 1 for the alignment). All major groupings discussed were observed in the 100 replicate bootstrap tree (not shown). Branches with bootstrap values >70 are shown in red and >40 in blue. The scale bar represents 0.1 mutational changes per residue (10 PAM units). 65 sequences from P. falciparum are shown (in red characters), together with representative members of major subgroups of human kinases (in black characters). The P. falciparum sequences are labelled with their identifier in the PlasmoDB database and, where applicable, with the published name of the enzymes. The human sequences are labeled with HUGO gene names. CK1 group Only one malarial kinase, the previously described PfCK1 [PF11_0377] [ 19 ], clearly falls within this group, which is vastly expanded in some other kinomes (e.g. 85 genes in C. elegans , see above). AGC group Five malarial kinases cluster within this group, three of which have been characterized: the cAMP-dependent PfPKA [PFI1685w] [ 20 ], the cGMP-dependent PfPKG [PF14_0346] [ 21 ], and PfPKB [PFL2250c] [ 22 ], an enzyme displaying maximal similarity to AKT/PKB. In other eukaryotes, PKB functions in the PI3K-dependent pathway; a PI3K kinase homologue is present in the P. falciparum genome (see below). Two additional sequences [PFC0385c and PF11_0464] form a separate cluster attached to the base of the AGC branch. There appears to be no clear member of the PKC subfamily. CamK group The main branch of the tree that contains the human CamKs also contains 13 PfePKs, which underlines the importance of calcium signalling in the parasite [ 23 ]. A tight cluster is formed by five of these enzymes, which share the overall structure of the calcium-dependent protein kinases (CDPKs) found in plants and ciliates but not in Metazoans. CDPKs are characterised by the presence of a kinase catalytic domain located on the same polypeptide as four EF-hand calcium-binding domains. Four of these enzymes have been described previously: PfCDPK1 [PFB0815w] [ 24 ], PfCDPK2 [MAL6P1.108] [ 25 ], PfCDKP3 [PFC0420w] [ 26 ] and more recently PfCDPK4 [PF07_0072]. The latter enzyme is expressed in sexual stages and was shown to be essential for development of the parasite in the mosquito, through mediating cell cycle resumption during male gametocyte exflagellation [ 27 ]. A fifth CDPK [PF13_0211], which like the four cited above possesses four EF-hand motifs, has been discovered in the present study. PF11_0242 appears to be related to CDPKs, but contains only one EF-hand motif. PfPK2 [Pfl1885c] constitutes a sister branch to the CDPK group. This enzyme was previously characterized as being related to the CamK family [ 28 ], and has no EF-hand domain. No malarial kinase clusters closely with the mammalian CamKs used to anchor the tree. Six other sequences, however, form a sister branch to the cluster that contains the CDPKs; only one of these six sequences (PF11_0239) possesses an EF-hand domain. The CamK activity described [ 29 ] as crucial for ookinete development in the mosquito vector (see below) is likely to be associated with one of the enzymes in this group. CMGC group Eighteen malarial kinases cluster within this group, which makes it the most prominent group in the Plasmodium kinome. Interestingly, in other eukaryotic systems a majority of CMGC kinases are involved in the control of cell proliferation and development, and their relative abundance in the P. falciparum kinome may reflect the variety of successive proliferative and non-proliferative stages which constitute the life cycle of malaria parasites. Six enzymes are related to the cyclin-dependent kinase family, 5 of which were identified previously (reviewed in [ 30 ]), the last one (Pfcrk-5, [MAL6P1.271]) having been discovered during the present analysis. Two previously characterised mitogen-activated protein kinases (MAPKs), Pfmap-1 [PF14_0294] [ 31 - 33 ] and Pfmap-2 [PF11_0147] [ 34 ], cluster together with a member of the MAPK family, as expected. Two enzymes, PfPK6 [PF13_0206] [ 35 ] and Pfcrk-4 [PFC0755c] (Equinet, Le Roch and Doerig, unpublished), display features of both CDKs and MAPKs according to BLASTP analysis. Their position either in a cluster (composed of PfPK6 and Pfcrk-5) that is intermediate between the CDK and the MAPK groups, or in a cluster (composed of Pfcrk-4 and uncharacterized MAL13P1.196) at the base of the CDK/MAPK/GSK3 branch, is consistent with these early observations. Three GSK3-related kinases, two of which [PF08_0044 and PFC0525c] have been characterised previously [ 36 , 37 ], form a cluster within the CMGC group. Four additional enzymes form another cluster that includes human Clk1, one of which is a previously described LAMMER-related kinase [PF14_0431] [ 38 ]. The complexity of the CMGC group, its relative importance in the P. falciparum kinome, and our long-standing interest in the control of cell proliferation and differentiation in the parasite, prompted us to produce a three-species comparative tree of this group (see below and Fig. 3 ). Figure 3 A three-species tree of the CMGC group. Phylogenetic tree showing members of the CMGC group of protein kinases from P. falciparum , yeast and human. The tree was compiled using conserved portions of aligned sequences using a protein distance matrix method; the tree shown is a consensus tree built from 100 bootstrap replicates. Branches with bootstrap values >70 are shown in red and >40 in blue. The scale bar represents 0.1 mutational changes per residue (10 PAM units). The P. falciparum sequences are identified by with their identifier in the PlasmoDB database and, where applicable, with the published name of the enzymes. The human sequences are labeled (black) with HUGO gene names (except for sk466, which is a numerical designation taken from Manning et al. (2002), and the yeast sequences (blue) identified according to the catalogue in Hunter and Plowman (1997). TKL group Five malarial enzymes appear in the vicinity of the TyrK-like group, including two [MAL6P1.191 and PFB0520w] that display maximal homology to MAPKKK-related or MLK (mixed-lineage kinases) enzymes upon BLASTP analysis. PFB0520w clusters with the TGFβ receptor (TGFβ1). The malarial sequence is much more similar to TGFβ receptors than to mammalian Raf, and furthermore, in common with TGFβ receptors, the malarial enzyme has a predicted transmembrane sequence N-terminal to the kinase domain. Mammalian TGFβ receptors assemble as heterodimers, and it remains to be seen whether the malarial enzyme forms a homodimer or has the capacity to coassemble with a mammalian subunit. Absence of members of the STE and TyrK groups No malarial protein kinase clusters with the STE7/11/20 group, which is consistent with the lack of success of earlier in vitro and in silico attempts at identifying MAPKK malarial homologues [ 39 , 40 ] and points to a divergent organisation of the MAPK pathways in malaria parasites (see below). It is relevant to mention here that one of the P. falciparum NIMA-related enzymes (see below) possesses an activation site that closely mimics that of MEK1/2. This enzyme, Pfnek-1 [PFL1370w], is able to specifically phosphorylate Pfmap-2 (but neither Pfmap-1 nor mammalian ERK2) in vitro , and to act in synergy with Pfmap-2 towards the phosphorylation of exogenous substrates [ 39 ]. This suggests that Pfmap-2 activity may be regulated by Pfnek-1. However, the physiological relevance of these finding remains to be demonstrated. Our tree indicates that members of the TyrK family are absent, as is the case in yeast and most (but not all) unicellular eukaryotes [ 17 ]. Other clusters and "orphan" kinases Five Plasmodium genes form a cluster of NIMA-related sequences that includes the NIMA-related kinase Nek1. Of these five, four are recognised by BLASTP analysis as being related to the NIMA/Nek family [ 41 ], including the well characterised Pfnek-1 enzyme [ 39 ]. The fifth enzyme, MAL6P1.56, does not cluster with the NIMA-like kinases in other analyses (not shown). Several protein kinases appear not to cluster clearly with any defined group, or to constitute small "satellite" clusters. Examples of such "orphan" kinases are (i) the cluster formed by PfKIN [PF140516], an enzyme previously described as related to the SNF1 family [ 42 ], with two uncharacterised PfPKs [PF14_0476 and PF13_0085]. This cluster is located at the base of the CamK and AGC branches, and does not strongly associate with any established ePK group (when mammalian NIM1/SNF1-like kinases were included in the phylogenetic tree no malarial kinases clustered with them (not shown)). (ii) A group of three malarial enzymes, including PfPK4 [MAL6P1.146], a previously characterised HRI kinase homologue [ 43 ], that are similar to mammalian elongation factor kinases, and form a distinct cluster associated to the NIMA group. (iii) Several sequences that are isolated at the base of major branches of the tree, indicating an absence of relatedness to established ePK groups. These include the " P. falciparum exported protein kinase" (PfEST, MAL7P1.91) [ 44 ], which forms an isolated branch at the base of the part of the tree containing the CMGC, CamK and AGC groups, PFL2280w, which is in a similar situation, and a group of two sequences at forming a sister cluster to the branch containing the AGC and CamK groups. One of these two sequences, PfPK7 [PFB0605w], displays relatedness to AGC and STE kinases in BLAST analysis (see below). So far, four PfePKs have been described as appearing as "composite" enzymes displaying features from more than one established ePK family. As mentioned above, PfPK6 [PF130206] and Pfcrk-4 [PFC0755c] both display relatedness to CDKs and MAPKs, and this is confirmed by their position on the tree. The MAPKK-like activation site of Pfnek-1 [PFL1370w] has been discussed above. The fourth example is that of PfPK7 [PFB0605w], an enzyme whose C-terminal region carries a sequence which is conserved in MAPKKs but whose N-terminal region is more closely related to that of PKAs [ 40 ]. This sequence does not cluster with any well-defined group in the tree, although it associates with uncharacterized PFI1415w in a sister cluster to the major branch containing the AGC and CamK groups. Whether such "dual" enzymes represent common ancestors to subsequently divergent families which have been conserved in the evolution of the Apicomplexan lineage, or whether they arose from domain shuffling between existing kinase genes, remains to be elucidated. It is possible that additional such "composite" enzymes will be identified, particularly among the PfPKs which do not associate with well defined PK groups. A three-species comparison of CMGC kinases Because of the large number of CMGC-group kinases found in the P. falciparum genome, we carried out a more thorough analysis in which the 18 malarial kinases belonging to this group were compared with comprehensive sets of related kinases from the yeast and human genomes (Fig. 3 ). The phylogenetic tree was constructed in a similar way to that in Figure 2 . 152 amino acid positions from the alignment were used in the construction of the tree. Evidence for absence of typical 3-component MAPK pathways In this analysis, both P. falciparum kinases (Pfmap-1 and Pfmap-2) previously reported as belonging to the ERK family clustered, as expected, with the MAP kinases. However, in contrast to previous suggestions brought forward before the full complement of mammalian ERKs had been characterised [ 33 , 45 ], they do not specifically cluster with ERK1/2. Rather, they lie outside the cluster of typical MAP kinases comprising the p38, JNK and ERK1/2 classes from human and yeast. Pfmap-2 lies at a basal position relative to the MAPK family, indicating no preferential relatedness to any of its subfamilies. Pfmap-1, in contrast, clearly associates with ERK8, a recently described member of the ERK family which, like Pfmap-1, has a large extension at the C-terminus [ 46 ]. In the orthologous rat enzyme ERK7, a similar extension has been shown to be involved in regulation of enzymatic activity [ 47 , 48 ]. It has hence been proposed that ERK8/7 may not be part of typical three-component (MEKK-MEK-MAPK) modules which are the hallmark of the ERK1/2, p38 and JNK pathways. Formal demonstration that ERK8/7 is not regulated by classical MEKs in mammalian cells is difficult because of the numerous MEK homologues present in the genome. The situation in P. falciparum therefore provides a first clear example that in vivo regulation of a kinase related to ERK8/7 does not require a typical MEK, since no member of the latter family is present in the parasite's genome (see above). It is perhaps unsurprising that P. falciparum lacks MAP kinases of the ERK1/ERK2, p38 of JNK subfamilies, given the absence of MAPKKs and STE-like MAPKKKs in the genome. In summary, our data indicate that although the malaria parasite uses MAPK homologues, these are not part of three-component modules – to our knowledge, P. falciparum is the first eukaryote demonstrated to lack such modules. Cell cycle control kinases Three P. falciparum kinases cluster with the cell division kinase group that includes the human cell cycle CDKs. PfPK5 [MAL13P1.279] appears orthologous to yeast cdc28 and to human CDK1-3. PfPK5 displays similar levels (60% identity) of overall homology to both mammalian CDK1 and CDK5; however, in our analysis this enzyme clearly clusters with the former, lending support to the idea that this enzyme is a functional homologue of the major cell cycle control kinases, as previously suggested [ 49 , 50 ]. The other two malarial enzymes that clearly cluster within the CDK group, Pfcrk-3 [PFD0740w] and Pfcrk-1 [PFD0865c], cannot be assigned an orthology with any yeast kinase. However, Pfcrk-1 appears to be related to human CDKs such as CDK10 and CDK11 that are involved in transcriptional control, consistent with earlier reports [ 51 ] that this enzyme shares primary structure features with the human PITSLRE (CDK11) kinases. Pfmrk [PFL00141] was initially described [ 52 ] as a putative homologue of the CDK-activating kinases (CAKs) such as mammalian CDK7, and subsequently shown to be able to undergo some activation by human cyclin H (the cognate cyclin activator of mammalian CDK7) and by Pfcyc-1, a P. falciparum protein with maximal homology to cyclin H [ 50 , 53 ]. However, in our tree Pfmrk appears not to be included in the CDK7 cluster, but instead lies at an intermediate position between the MAPK and the CDK groups. It is relevant to mention here that sequence-based prediction of kinase-cyclin pairs is difficult: for example, PfPK5, a clear CDK1-3 orthologue, is unexpectedly activated very efficiently in vitro by human cyclin H (a CDK7 activator) and p25 (a highly specific CDK5 activator), among other cyclin-related proteins [ 50 ]. This may be explained by structural properties making this enzyme very prone to adopt the active conformation [ 54 ]. Extreme caution must therefore be exercised in predicting precise functions for the four cyclin-related proteins which have been identified so far [ 55 ]. The positions of the clusters containing (i) PfPK6 [PF130206] [ 35 ] and Pfcrk-5 [MAL6P1.271], and (ii) Pfcrk-4 and uncharacterized MAL13P1.196, are consistent with the data in the general tree, and confirm the previously detected relatedness of two of these enzymes to both CDKs and MAPKs. Overall, the number of clear orthologues of cell division kinases in the P. falciparum genome is smaller than that in the yeast or human genomes, and may represent a minimum complement of such kinases that are necessary for the completion of a eukaryotic cell cycle. Alternatively, some cell cycle control functions assured by CDKs in human cells may be taken over, in Plasmodium , by some of the CMGC kinases with no clear relatedness to established families. Other CMGC kinases A number of CMGC group kinases interact with factors involved in mRNA splicing. PF11_0156 clearly is an orthologue of human PRP4, a kinase that is associated with mRNA splicing and histone deacetylation and that is conserved in most eukaryotic genomes (including Schizosaccharomyces pombe , but not Saccharomyces cerevisiae ) [ 56 , 57 ]. Human SRPK1 phosphorylates the "Serine-Arginine-rich pre-mRNA splicing factors" called SR proteins, and homologues are conserved in all eukaryotic genomes [ 58 , 59 ]. Two P. falciparum kinases (PFC0105w and PFl4_0408) cluster with SPRK. Both these kinases have an insertion between domains VIb and VII that is a distinctive feature of SRPKs. Previously described PfLAMMER [PF14_0431] [ 38 ] associates with yeast kns1 [ 60 ] and the related human LAMMER kinases CLK1-4 that also phosphorylate SR proteins [ 61 ]. Other kinases clustering within the CMGC group include a single orthologue of casein kinase 2α [PF11_0096]. Other eukaryotes have at least 2 alpha subunit-encoding genes, emphasizing the relative simplicity of the P. falciparum kinome. As detected on the general tree (Fig. 2 ), three malarial enzyme cluster with the GSK3 family, the most closely related to human GSK3α/β being the recently characterised PfGSK3 [PFC0525c], which appears to be exported into the host erythrocyte [ 37 ]. In several instances our phylogenetic classification of individual kinases differs from the previously reported classification based on BLAST searches. There are at least two reasons for this discrepancy. Firstly, our analysis is based on a comprehensive catalogue of protein kinases from P. falciparum , and we have access to comprehensive catalogues from several other organisms. In contrast, several malarial ePKs were classified at the time of their initial identification several years ago, when the sequences could be compared only to non-comprehensive sets. As an example, both P. falciparum MAPKs were identified before the mammalian ERK8/7 enzymes were discovered, and the closest sequences available at the time were those of the ERK1/2 family. Secondly, it has been reported that BLAST performs poorly in assigning orthology between human and C. elegans genes [ 62 ]. This is because of extensive independent gene duplication on the lineages leading to the two organisms. Humans and P. falciparum are much more distantly related and there has been extensive gene duplication on the human side. Our data support the view that reliable assignments of orthology between genes in distantly related species might only be assigned through the construction of phylogenetic trees and suggest that comparisons based on BLAST must be interpreted cautiously. FIKK, a novel, Apicomplexa -specific group of ePK-related proteins That only 65 typical ePKs were identified in this search is somewhat surprising, as Saccharomyces cerevisiae , whose genome (12 megabases) is half the size of the P. falciparum genome (24.8 megabases), encodes approximately twice as many enzymes of this family. In preliminary analyses, 21 sequences identified in the HMM search appeared to form a tight cluster that is relatively distantly related to the more typical ePK groups discussed above. Based on an amino acid motif corresponding to subdomain II of the ePK catalytic domain, and which is well conserved in members of this novel family, we called this group "FIKK". In addition to the ePK catalytic domain-like region, the FIKK sequences all have a highly variable N-terminal extension, and in some cases the catalytic domain itself is interrupted by large insertions (as is the case for several of the 65 "typical" malarial ePKs, see below). An alignment of the FIKK kinase-like domain with the 65 typical ePKs in the P. falciparum genome showed that they share most of the residues that are conserved in the ePK catalytic domain. Indeed, with the exception of the Glycine triad in subdomain I, all residues which are crucial for phosphotransfer or structural stability of protein kinases, and therefore well conserved throughout the family, are present in all members of this family (see Table 1 and Fig. 4 ). In contrast, no FIKK sequence possesses a full Glycine triad (GxGxxG) in subdomain I. This triad is present in a majority of ePKs and is involved in positioning the ATP molecule in the catalytic cleft [ 63 ]. However, one, and sometimes two glycine residues are present in subdomain I of the FIKK sequences. This is also the case in a number of enzymes with demonstrated protein kinase activity from many organisms (including P. falciparum ) [ 40 ], and it is clearly established that ATP binding and phosphotransfer ability is not dependent on the presence of a Glycine triad. Although lacking the Glycine triad, all FIKK sequences possess an N-terminal extension, with a conserved tryptophan residue in the region that corresponds to subdomain I. One of the FIKK sequences is represented in PlasmoDB as two contiguous ORFs (PF14_0733 and PF14_0734) separated by a gap. This is presumably due to erroneous prediction: alignment with other FIKKs clearly shows these sequences represent two parts of a single member of the FIKK family rather than two separate genes. Furthermore, RT-PCR across the two predicted ORFs demonstrates that both sections are present on the same mRNA molecule. Interestingly, sequencing of the RT-PCR product showed that the open reading frame in the cDNA is interrupted by an in-frame stop codon, which is presumably the cause of the misprediction of the gene structure. That this sequence is cDNA than genomic is ascertained by the presence of an intron near the 3'end (see Additional file 2 ). Whether PF14_0733/4 is a transcribed pseudogene, or whether a protein can be produced by readthrough of the internal stop codon as has been documented for another P. falciparum gene [ 64 ], remains to be determined. In any case, it appears there are only 20 FIKK sequences in the genome, instead of the 21 that were counted originally (see above). Table 1 Variability in key residues of the protein kinase catalytic domain. The residues indicated at the top are: G1, G2, G3, the three residues constituting the glycine triad (corresponding to G51, 53 and G56 in human PKAα), and which form a hairpin enclosing part of the ATP molecule; the lysine in subdomain II (K73), which contacts the α- and β-phosphate of ATP, anchoring and orienting the ATP; the glutamate of subdomain III (E92), which forms a salt bridge with the former residue; the aspartate and asparagine within the HRDXXXXN signature motif of ePKs in subdomain VIB (D167, N172), the former of which is thought to be the catalytic residue acting as a base acceptor; the aspartate in the DFG motif of subdomain VII (D185), which binds to the Mg 2+ (or Mn 2+ ) ion associated with the β-and γ-phosphates of ATP; the glutamate in subdomain VIII (E209), which forms a salt bond with the arginine in subdomain XI and provides structural stability of the C-terminal lobe; and the aspartate in subdomain IX (D221), which is involved in structural stability of the catalytic loop of subdomain VI through hydrogen bonding with the backbone. The conservation status of these residues in the 65 malarial typical ePKs is summarized at the top of the Table, and that of the 20 FIKK family members is presented at the bottom. It is immediately apparent that with the exception of the Glycine triad in subdomain I, all important residues are extremely well conserved in the FIKK sequences Residue G1 G2 G3 K E D N D(FG) E D R subdomain I I I II III VIB VIB VII VIII IX XI "Typical" ePKs (65) Number not conserved 16 10 27 0 4 0 0 1 5 2 2 % conserved 75 85 58 100 94 100 100 98 92 97 97 Amino-acid substitution 11S 3A I MAL7P1_18 N PF14_0408 N PFA0380A K PFB0665w K PFB0665w Q MAL6P1_108 Y PF11_0060 Y PF11_0220 N PF11_0377 Q PFC0420w E PF11_0220 L PFI1415w N MAL7P1-18 N PF10_0160 Lacking all three Gs in subdomain I MAL7P1-18 MAL7P1_73 MAL7P1_91 PF11_0060 PF14_0408 PFA0380w PFI1415w PFL0080c FIKK Number not conserved 13 12 17 0(a) 0 0 0 0 0 1 0 All 20 FIKK have a conserved W in a [ILV][YF]W[NTS]XX[GC] motif approx 100 residues upstream of the FIKK motif E PF14_0733 % conserved 28 33 5 100 100 100 100 100 100 95 100 Note: a. This residue corresponds to the first K in the FIKK motif. Figure 4 Comparative primary structure of FIKKs and typical ePKs. The eleven subdomains of the protein kinase catalytic domain are indicated in the central bar. The residues which are conserved in most ePKs (see legend to Table 1 for details) are indicated at the top. The corresponding residues in FIKKs are indicated under the bar, together with some of the motifs with which they are associated and which are conserved in all FIKK family members. In addition to the residues conserved in typical ePKs, several amino-acid motifs are fully conserved in all members of the FIKK family (Fig. 4 and 5 ). These can be used to define signature motifs, which allowed us to perform a number of motif searches in various databases, to determine whether members of this ePK-like family are present in other organisms. Interestingly, sequences containing such motifs could be retrieved only from Apicomplexan species: 20 sequences in the P. falciparum genome, one in P. berghei (Pb75h08p1c-3-1074-4583), one in P. yoelii (chrPy1 00951-1-3319-5523), one in P. knowlesi (Pk2145b11q1c-4-8079-3688) and one in P. vivax (Pv402596-4-9942-5746). In contrast, no FIKK family member was found in the (yet incompletely sequenced) genomes of P. chabaudi or P. reichenowi . Searches of the NRprot database, which contained sequences representing all eukaryotic and prokaryotic phyla, yielded only the Plasmodium sequences mentioned above (20 in P. falciparum , and one each in P. berghei , yoelii , knowlesi and vivax ). In agreement with the motif searches, BLAST analysis of the NRprot database with PF10_0160 finds 20 Plasmodium falciparum and one yoelii sequences among the top hits (E < 10 -37 ). Weaker hits (E > 10 -5 ) are mostly MAPKs from a variety of organisms. Further investigations using Apicomplexan genome project databases (Sanger and TIGR) allowed us to identify one such sequence in Toxoplasma gondii and one in Cryptosporidium parvum . Taken together, these data strongly suggest that the FIKK group is specific to Apicomplexa, and has undergone a dramatic expansion in P. falciparum . Interestingly, of the 20 FIKK sequences in the P. falciparum genome, 7 are located on chromosome 9, where they are arranged in a contiguous subtelomeric tandem array, a common location for genes involved in antigenic variation such as those of the var /PfEMP1 [ 65 ] or Rifin [ 66 ] families (Fig. 6 ). On the tree depicted in Fig. 6 , these sequences (PFI0095c to PFI0125c) tend to cluster together. The structure of the tree (no major subgroups, with most of the branch points very close to each other and a fairly uniform branch length) suggests a rapid and presumably recent expansion of the family. This hypothesis is supported by the presence of the tandem array, an indicator of gene duplication. Furthermore, the presence of only one FIKK gene in several other apicomplexan species is consistent with the expansion in P. falciparum being a recent event. Obviously, a definite conclusion about the species distribution of this gene family will have to await the completion of additional genome sequencing projects, especially with respect to other Plasmodium species and other Apicomplexan genera. Figure 5 Alignment of four representative sequences of the FIKK family with a typical ePK (PfPK5 [MAL13P1.279], a CDK homologue). Asterisks indicate those residues that are invariant in all 20 FIKK sequences. Figure 6 A tree of the FIKK family. Phylogenetic tree of FIKKs from P. falciparum . The tree was compiled using conserved portions of aligned sequences (see Additional file 3) using a protein distance matrix method. The scale bar represents 0.1 mutational changes per residues (10 PAM units). Bootstrap values over 75 are shown. The bottom panel shows a map of one of the telomeric and subtelomeric regions of chromosome 9 obtained from the PlasmoDB website. The location of genes encoding proteins of the var/PfEMP1 (Duffy et al., 2003), rifin (Kyes et al., 1999) and FIKK (this study) families is indicated. Although no experimental evidence is available that associates PK activity with any of the FIKK sequences, the fact that all residues required for phosphotransfer and ePK folding are present strongly suggests that these proteins are indeed protein kinases. Some FIKKs have a predicted signal peptide (PFD1165w, PFE0045c, MAL13P1.109, PFI0095c, PFI0105c, PFI0110c) and/or transmembrane helix (PFD1165w, PFD1175w, PF10_0160, PFI0110c, PFI0125c, PFI0100c has two) at the N-terminus. Otherwise, aside from their similarity to the kinase domain, no recognised Pfam domains are found in these proteins. Two of the FIKK sequences have been identified as P. falciparum antigens in the context of immunological studies: the R45 trophozoite antigen (PFD1175w) [ 67 ] and the 3.8 protein (PF10_0160). No function has previously been attributed to either of these proteins. R45 has a large insertion of 570 residues, comprising mostly His, Lys, Asn, Ser and Asp residues, relative to the other members of the FIKK family. The belonging of R45 to a 20-sequence family in the P. falciparum genome has been discovered independently in the context of research into the R45 antigen (Schneider and Puijalon, personal communication, to be published elsewhere). Features of gene structure Table 1 presents the degree of conservation, in malarial ePKs, of residues that play a crucial role in ePK enzyme function (see legend to Table 1 for details). As is the case in ePKs from other eukaryotes, the Glycine triad is not complete in many PfPKs and in all FIKKs, and none of the three glycine residues are present in 8 of the 65 "typical" ePfPKs. Other important residues are better conserved in the malarial PKs. The observation that some sequences (e.g. PF11_0060, PF14_0733 and MAL7P1.18) lack more than one of these conserved residues raises the question of their ability to function as protein kinases. These may represent kinase-dead scaffold proteins similar to those found in other eukaryotes, such as KSR [ 68 ]. In contrast, all 20 FIKKs possess essentially all these residues, despite a conservative D > E substitution in subdomain IX of PF14_0733. Like in many other plasmodial proteins, large extensions rich in charged and/or polar residues, and in some cases repeated amino acid motifs, are found adjacent to the catalytic domain of several PfPKs. Several enzymes also carry such sequences as insertions within the catalytic domain. The function of these elements is as yet undetermined, although there is evidence in some cases [e.g. Pfmap-1, [ 32 ]] that extensions are absent from the enzymes in parasite protein extracts, presumably as a result from proteolytic cleavage. In some sequences (e.g. PFD0740w [Pfcrk-3] and PFC0755c [Pfcrk-4]), large insertions have been mapped to the hinge region between adjacent β-sheets in the N-terminal lobe; hence, it can be argued that such insertions may not interfere with proper folding of the catalytic domain (Equinet and Doerig, unpublished). Organelle targeting Malaria parasites possess two organelles with extra-chromosomal DNA: the apicoplast and the mitochondrion. The apicoplast is a four-membrane organelle carrying a circular 35 kb DNA whose structure is very similar to that of plastid genomes. It is specific to the Apicomplexa (hence its name), and thought to originate from secondary endosymbiosis [ 69 ]. As is the case for chloroplasts in plants [ 70 ], it appears that many genes whose products are essential for apicoplast function and survival have been transferred to the "host cell" nucleus; products of these genes must be addressed back to the organelle. A bipartite peptide has been identified and shown to be necessary and sufficient for targeting a protein to the apicoplast [ 71 ]. The 35 kb genome of the apicoplast does not encode any PK, but it is to be expected that protein phosphorylation is necessary for function and maintenance of the organelle. We used an algorithm available on PlasmoDB to determine that 5/65 typical ePfPKs (including 2 NIMA-related kinases) and 6/18 FIKKs are predicted to be addressed to the apicoplast (see Fig. 7 ). Likewise, four kinases (none of them of the FIKK family) possess a potential mitochondrion-targeting signal sequence, as defined by the algorithm available on PlasmoDB [ 72 ]. It is important to emphasise that presence or absence of targeting signals relies on gene structure prediction algorithms, which have been demonstrated to be erroneous in some instances (see ref. [ 55 ] for an example); therefore this must be considered with caution until the 5'end of the cDNAs has been sequenced, and targeting to the organelle has been verified experimentally by the transfection of constructs expressing GFP-tagged proteins. Figure 7 P. falciparum ePKs and related proteins, and stage-specificity of their expression. PlasmoDB gene identifiers are indicated in the left column, followed by the published names where applicable. Identifiers of enzymes belonging to defined ePK groups appear in color (see the inset for color codes). Microarray data from the Le Roch et al. and Bozdech et al. studies available on PlasmoDB, were compiled to produce the third column. Genes were arranged in function of the timing of their expression according to Bozdech et al., to illustrate the fact essentially all of them are expressed in a regulated way during erythrocytic schizogony, and that this process involves sequential but overlapping expression of most kinases in the genome. The phaseogram (data generated by Bozdech et al. and available on the PlasmoDB website) represent the relative abundance of mRNAs throughout the erythrocytic asexual cycle, measured by two-colour competitive hybridisation between total RNA from each time point and a reference pool of total RNA from all time points (48 time points, i.e. one per hour during the 48 hours of the asexual cycle, starting one hour post invasion). The phaseogram shows the red/green colorimetric representation of the gene expression ratio for each oligonucleotide. Green: negative ratio (no expression), red: positive ratio (expression); grey or white: no data. See Bozdech et al. (2003) and PlasmoDB for details. To the right of the phaseogram, the presence or absence of mRNA in samples from merozoites (M), gametocytes (G) and sporozoites (S) is indicated by red boxes (data generated by Le Roch et al.). Where only one of the two synchronised merozoite population gave a signal, the M box is colored in orange (see Le Roch et al. 2003 for details). Columns to the right indicate those molecules which, according to the gene prediction algorithm used in PlasmoDB, possess a putative apicoplast or mitochondrion targeting sequence (see text for details). Regulatory subunits Proteins devoid of kinase activity but which are known to associate with, and regulate the activity of, ePKs have been identified in PlasmoDB. These include four previously characterised cyclins [PF14_0605, PF13_0022, PFL1330c and PFE0920c] which have been demonstrated to associate with histone H1 kinase activities in parasite extracts [ 50 , 55 ], a PKA regulatory subunit [PFL1110c], which as expected is able to down-regulate PKA in parasite extracts (Merckx and Doerig, unpublished), and two putative CK2 regulatory subunits [PF11_0048 and PF13_0232]. Genes encoding aPKs BLASTP searches of PlasmoDB were performed using atypical protein kinases (aPKs) from Homo sapiens as queries. GeneDB was also used to look for relevant Pfam domains (ABC1, FAT, FATC, Bromodomain, RIO). Two members of the RIO kinase family were found: PFL1490w (RIOK1-like) and PFD0975w (RIOK2-like). Enzymes of this family are involved in rRNA processing in S. cerevisiae [ 73 ]. We also identified two putative members of the ABC1 family of atypical protein kinases [PF08_0098 and PF14_0143]. Some P. falciparum genes (e.g. PFD0685c and PF14_0326) display regions with low-level similarity to the histidine kinase domain (scores between 4 and 5 with Pfam entries PF00512 and PF06580), but the significance of this observation remains to be established. No significant hits were obtained with A6 kinases, Alpha kinase, pyruvate dehydrogenase kinase, aminoglycoside phosphotransferases or DNA-dependent kinases. In contrast, we identified a malarial phosphatidyl-inositol-3 kinase homologue [PFE0765w], in agreement with experimental studies [ 74 ] and the presence of a PKB homologue (see above) demonstrating the presence of a phosphatidyl-inositol pathway in the parasite. However, the PI3K homologue, like two other sequences (PFE0485w and PFD0965w) related to PI4K, appears not to contain the FAT and FATC domains which are present in PIKs from other organism and have been associated with protein kinase activity [ 75 ]. Hence, it may be that these three enzymes function solely as phosphatidylinositol kinases, a proposition that requires experimental testing. Overall, these results on malarial aPKs contrast with those obtained from the recently-sequenced L. major , T. brucei and T. cruzi genomes, where ABC1 and RIO kinases were found, as were PIKK (with the FAT and FATC domains), PDHK and Alpha kinase family members (Parsons and Ward, unpublished). Expression pattern of PfPKs during the P. falciparum life cycle Data from two studies [ 76 , 77 ] of the P. falciparum transcriptome during development are available on the PlasmoDB database. We compiled these data to obtain a general picture of PfePK gene expression during erythrocytic development (Fig. 7 ). It is clear that the steady-state level of mRNA is developmentally regulated for all the PfPK genes, in accordance with the unique gene expression pattern described in this organism by Bozdech et al. [ 76 ]. Most of the PfePKs are expressed in trophozoites and schizonts, but some PK mRNAs are clearly predominantly detected in rings, the younger form following erythrocyte invasion. Data from Le Roch et al. [ 77 ] included a transcriptome analysis of additional development stages: free merozoites, gametocytes and sporozoites. Compilation of data from this study indicated that a small number of PfePKs are specific to gametocytes, including two of the NIMA-related kinases (one of which is potentially targeted to the apicoplast), one of the MAPKs (Pfmap-2), and PfKIN, an enzyme previously described as related to the SNF1 family (see above). Gametocyte-specific expression had been described in the literature for the latter two enzymes [ 42 , 45 ]. Overall, and despite some discrepancies, there is good agreement between the two studies with respect to PfePK genes, as illustrated by the observation that PfePKs whose expression is detected in late schizonts and segmenters by Bozdech et al. are also detected in free merozoites by Le Roch et al. At least some of these enzymes are likely to play a role in invasion of the erythrocyte by the merozoite. As expected, the PK genes that are gametocyte-specific according to Le Roch et al. (and hence likely to play a role during sexual development of the parasite) give low intensity signals in the dataset from Bozdech et al. (see for example Pfmap-2 or Pfnek-4 to illustrate this point). Conclusion This study has allowed us to classify the 65 typical ePKs encoded by the P. falciparum genome, and to establish the presence of a novel group of ePK-related genes, the FIKK family, which, from analysis of currently available databases, appears to be specific to Apicomplexa and considerably extended in P. falciparum . The number of genes encoding protein kinases is somewhat smaller than expected from analogy with other organisms. We cannot exclude that our study, which is based on sequence similarity with ePKs, may have missed genes encoding proteins with protein kinase activity, but with a primary structure that would be too divergent from that of known ePKs to be identified. Nevertheless, it is hoped that the present study will facilitate investigations into the regulation of many pathways and processes operating during growth and development of the parasite. In addition to the FIKKs, several malarial ePKs belong to "orphan" groups, as they do not cluster clearly with established ePK groups as defined in model organisms. Furthermore, our analysis provides evidence that elements which are usually found in eukaryotes are absent or dramatically modified in malaria parasites. Such elements include MAPK pathway components and PKC, for example. These important divergences between the malarial and human kinomes reflects the vast phylogenetic distance between Apicomplexans and Opisthokonta, and strengthen our expectations that specific interference with essential functions of the parasite can be achieved through the use of protein kinase inhibitors. Methods Identification of ePK genes in the P. falciparum genome The set of predicted peptides of the Plasmodium falciparum genome 3D7 [ 78 ] was downloaded from PlasmoDB [ 8 ]. A Hidden Markov Model search [ 79 ] of the predicted proteins encoded by the genome was carried out using a eukaryotic protein kinase profile downloaded from the Pfam database [ 80 ]. In addition, PlasmoDB was searched for proteins carrying a Gene Ontology molecular function assignment [ 81 ] of 'protein kinase activity' (GO:0004672). This allowed us to constitute an initial list of 108 sequences. After inspection, 15 were removed that had high e-value (>0.01), low HMM scores (<-110) and visibly lacked a protein kinase domain. The remaining 93 sequences were aligned using our own Hidden Markov Model, trained on a complete set of human protein kinases, to check for the presence of the key kinase motifs. In addition, the genomic context of each putative kinase gene was examined to check for missing exons using GeneDB and Artemis [ 82 ]. Eight proteins, the first four of which have a PlasmoDB enzyme assignment to EC2.7.1 (phosphotransferases), lacked sufficient similarity to typical eukaryotic protein kinases to be aligned meaningfully across the kinase domain. These sequences were: PF13_0166, PFC0945w, PFE0170c, PFI1275w, MAL7P1.127, MAL7P1.132, PF11_0079 and PF14_0264; they were removed from further analysis. A further 20 sequences constituted the FIKK family (see below). This set of closely related, but atypical, sequences was analysed separately. The remaining 65 sequences represent the complement of typical protein kinases in P. falciparum . Although the Hidden Markov Model used for the alignment is based on an extensive training set, the alignment did require some manual optimisation. This is partly because of the extreme diversity of the gene family and partly because many predicted proteins from P. falciparum contain large repetitive insertions (Hidden Markov Model-based alignment protocols would be expected to cope better in these circumstances than other common methods). A full alignment of the kinase domains is shown in Additional file 1 . Once a definitive set of the 65 sequences representing typical ePKs had been assembled, a phylogenetic tree was produced using Phylip [83], with the Protdist and Fitch algorithms. Human protein kinases were added to the alignment in order to improve the visualization of the main groups of protein kinases among the P. falciparum sequences. Only gap-free conserved regions of the alignment were used for the construction of the tree (164 amino acid positions). Bootstrap values supporting the branches of the tree are rather low; this is to be expected given the diversity of the protein kinase family. Authors' contributions PW performed most of the database searches for ePK-related sequences and constructed the FIKK phylogenetic tree; LE contributed to the searches for aPKs, compiled expression data and performed the in silico and in vitro analyses of the FIKK family. JP generated the HMM-derived alignments, constructed the ePK phylogenetic trees and contributed significantly to their description in the text. CD coordinated the study and wrote the larger part of the manuscript. All authors read and approved the manuscript. Supplementary Material Additional File 1 Alignment of the 65 "typical" P. falciparum ePKs used for constructing the tree in Fig. 2. Please see the Methods section for details on how the alignment was generated. Click here for file Additional File 2 partial sequence of the cDNA for the gene PF14_0733/PF14_0734. Click here for file Additional File 3 Alignement of the 20 FIKK sequences used to construct the tree in Fig. 6. Click here for file

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Methodological considerations in the design of trials for safety assessment of new drugs and chemical entities

Introduction Assessment of the QT interval started to receive increased regulatory attention in the late 1980s. The heightened safety concern was precipitated by repeated reports on torsade de pointes (TdP) and other arrhythmias occurring in patients treated with an antihistamine drug (terfenadine) [ 1 ]. ECG measurements performed during the clinical development process by cardiologists (allegedly using "eyeball/calliper" techniques), have failed to identify drug-related QT prolongation. The false-negative conclusions consequently provided have resulted in a number of serious adverse events and, ultimately in the removal of terfenadine from the US market [ 2 ]. Similarly, in early 1990s, attempts to decrease sudden cardiac death by novel antiarrhythmic drugs (Cardiac Arrhythmia Suppression Trial – CAST), have demonstrated that a certain degree of arrhythmia suppression was paralleled by a proarrhythmic effect, translated in 3-fold increase in mortality rate among patients treated with encainide or flecainide [ 3 ]. Awareness about the potential risk of drug-induced QT prolongation and subsequent risk of malignant arrhythmias has increased gradually since then and, particularly during the past years, regulatory requirements for short- and long-term safety of any new chemical entities have become more stringent. For example, after CAST, the FDA changed its advice regarding antiarrhythmic drugs and required evidence showing minimally, that a new antiarrhythmic agent did not cause death in patients. The first regulatory guidelines regarding clinical evaluation of the QT/QTc interval prolongation in the context of new drug development were issued in 1997 by the Committee for Proprietary Medicinal Products (CPMP) [ 4 ]. Most recently, the FDA has issued its 4 th draft document on the matter, clarifying the specific safety issues related to QT/QTc prolongation [ 5 ]. Congenital Long QT Syndrome The frequency of congenital long QT syndrome (LQTS) is unknown, but appears to be a common cause of sudden and unexplained death in children and young adults. It is much more common than previously thought – possibly as frequent as 1 in 5,000, and may cause 3,000 – 4,000 sudden deaths in children and young adults each year in US [ 6 ]. It is present in all races and all ethnic groups, but it is not certain if the frequency is the same in all races. Clinically, the diagnosis of LQTS is suggested by the occurrence of syncope, cardiac arrest or sudden death [ 7 ]. The diagnosis is established on the basis of prolonged QT interval on the ECG. A clearly prolonged QT interval is present in 60% to 70% of affected persons, but the QT is normal or only borderline prolonged in 30–40% of those affected. Overall, about 12% of LQTS patients have a normal QT interval on their baseline, resting ECG. Torsade de pointes (TdP) tends to appear during exercise (especially swimming) or psychological stress in LQT1, during stress or startle (particularly auditory stimuli) in LQT2 and during rest in LQT3 [ 8 ]. Studies on transmural dispersion of repolarization (TDR) in experimental models have shown it to be linked to the genesis of TdP. TDR has different features in the three different forms of LQT referenced as LQT1, LQT2 and LQT3 [ 9 ]. Diurnal and sex-related pattern of QT interval The maximal QT interval over 24 hours in normal subjects is longer than thought so far (440 ms). Both QT and QTc intervals are longer during sleep. The QT interval and QTc variability reach peak shortly after awakening, which may reflect increased autonomic instability during early waking hours. The time of the peak value corresponds to the period of reported increased vulnerability to ventricular tachycardia and sudden cardiac death. These findings have implications regarding the definition of QT prolongation and its use in predicting arrhythmias and sudden death [ 10 ]. At rest, the surface ECG in women displays longer QT interval [ 11 ], lower T wave amplitude [ 12 ] and less QT dispersion [ 13 ]. The QT interval displays greater shortening during exercise as compared to men, as a consequence [ 14 ]. Women are also known to have a greater propensity towards developing TdP when treated with agents belonging to class III antiarrhythmic drugs [ 15 , 16 ]. Besides, women are more susceptible to development of malignant arrhythmias in various settings of QT prolongation [ 12 ]. The basis for sex differences in repolarization appear to be, at least in part, influenced by sex hormones [ 17 ]. However, most recent data derived from a novel, automated QT-analysis algorithm, indicate that there are also sex differences in the dynamics of the QT interval during exercise and recovery in healthy subjects [ 18 ]. Women exhibited greater QT-interval shortening during accelerating heart rates and greater QT-interval prolongation during decelerating heart rates than in men. These results suggest that women might have a greater QT interval-rate adaptation, contributing to the greater prevalence of drug-induced TdP episodes in women as compared to men. In this context, the currently 20 ms sex difference in the rate-adjusted QT interval, recommended by the regulatory agencies, might need to be revised. Acquired forms of Long QT interval in diseased patients It is estimated that more than 50 marketed agents and an equivalent number of drugs under development have been found to block potassium channels, to prolong the QT interval and induce, in some individuals, malignant arrhythmias. TdP is, however, a relatively rare event with a rate of 2–3% for some drugs [ 19 ]. Drugs which prolong the QT interval exist in every therapeutic class [ 20 ]. An international registry for cases of drug-induced arrhythmias associated with QT prolongation can be found on the web [ 21 ]. The pathophysiology of the TdP Prolongation of the QT interval on the ECG is caused by increased duration of the action potential (AP) of the ventricular myocytes. Inhibition or activation of the potassium channels in the cells belonging to the different myocardial layers (Purkinje cells, subendocardial myocytes, mid-myocardial M cells and subepicardial myocytes) [ 22 ], interferes with the normal repolarization process and triggers different patterns of AP duration. The M cells for example, are characterised by prolonged repolarization in comparison with the epicardial or the endocardial layers. The potassium channels are of particular importance in drug-related QT changes, most notably the rapid component of the delayed rectifier potassium current (I Kr ) channel. Blockage of the channel caused by the human ether-a-go-go-related gene (HERG) protein, the gene encoding for the I Kr , has been implicated in many of the drug-induced changes. The model used to explain the increased propensity toward malignant arrhythmias secondary to prolonged QT interval is based on extraneously induced, altered depolarization process with occurrence of "early after-depolarization" action potentials (EADs), which register on the surface ECG as prolonged QT interval [ 23 ]. In the drug-induced model, any drug, normally used for therapeutic purposes, but which interferes with the inward/outward ion currents across the cell membrane is leading to a prolongation of the action potential duration (APD) and thereby delayed repolarization. Certain drugs have the property to block the potassium channels (I Kr ) in order to achieve a desired antiarrhythmic effect. These types of changes facilitate additional inward Ca ++ currents that further prolong the action potential. Consequently, the AP not only fails to repolarize but also depolarizes again, creating characteristics "humps" which, actually are EADs (Fig. 1A ) [ 24 ]. Figure 1A "Humps" on the terminal part of the T-wave reflecting early ADPs. Figure 1b EAD degenerating in tachycardia. Genetic defects of the Na + or of the K + channels lead to lengthening of QT interval and EADs which may trigger ventricular extrasystoles (VES). Occurrence of burst-like, repetitive EADs may degenerate in a tachycardia (see Fig. 1B ) with particular features, termed torsade de pointes [ 25 ]. The French term torsade de pointes, suggests a rapid polymorphic tachycardia in which the QRS axis rotates 360 degrees over a sequence of 5 to 20 complexes [ 15 ]. Such early EADs also occur in a multitude of cases such as: bradycardia, diuretic-induced hypokalemia or hypomagnesemia, treatment with natrium or calcium channel blockers. Preferential prolongation of the action potential duration in the M cells is thought to underlie QT prolongation, the phenotypic appearance of abnormal T-waves, the pathologic U-wave, and the development of TdP. It is generally accepted that a focal activity initiates the onset of TdP, whereas functional re-entry is responsible for its maintenance [ 26 ]. Results from more recent research (27) suggest that changes in a new variable termed "T-wave peak to T-wave end" interval (TPE) would predict increased risk in subjects with LQT1 and LQT2. These changes would reflect the dynamicity of the transmural dispersion of repolarization (TDR) in clinical setting, in LQTS patients. Increased TPE interval may show to be the electrophysiological substrate for TdP. Modulation of the TPE interval magnitude seems to be a property of the Iks and Ikr (rapidly respectively slowly activating delayed rectifier potassium current) defects. The TPE interval, as an index of TDR, has been proved to be clinically useful in assessing arrhythmic risk [ 28 - 31 ]. Current regulatory recommendations. Objectives and Scope Drugs with significant effects on repolarization must be identified and their risk quantified in preclinical and clinical development. Risk-benefit assessment of drugs under development, with particular emphasis to their propensity to prolong repolarization should be individualized to their pharmacokinetic and pharmacodynamic profile as well as to their safety characteristics. The following major aspects need to be addressed: • Rigorous assessment of the agent's effects on the QT/QTc interval. • Assessment of the QT/QTc prolongation-related safety risks of the particular drug against its potential benefits. The above-mentioned issues should be taken into account in any of the following circumstances: • Development of a novel agent (with non-antiarrhythmic properties). • A marketed agent for which new dose or route is being developed (with consequent potential increases in pharmacokinetic parameters – Cmax, AUC values). • A marketed agent for which a new indication or new target patient population is pursued. • A marketed agent belonging to a chemical or pharmacological class in which any other drug may have been associated with any of the following events: QT/QTc prolongation, TdP or sudden death during postmarketing surveillance. The "thorough QT/QTc study" – General Considerations The "thorough QT/QTc study" is about to emerge as the comprehensive "clinical data set" fully complying with current regulatory requirements, as opposed to "non-clinical" testing that may, or may not generate sufficient information considered to preclude risk of QT/QTc prolongation. Judgement is required on a case-to-case basis on whether the "clinical data set" following completed non-clinical testing [ 32 , 33 ] is still necessary or not, with correspondent adjustment of study design variables. Being considered a biomarker of proarrhythmic risk, the QT/QTc interval is the pharmacodynamic (PD) parameter which is explored to assess drug induced changes in heart rate (HR) and ECG parameters as correlated to plasma drug concentrations (PK). The PK/PD analysis implies a standardized collection of blood samples for determination of PK parameters (Cmax, Tmax, AUC) and recording of 12-lead ECGs for measurement and computation of specific ECG parameters (PR, QRS, QT/QTc). All of these measurements can be expected to show exposure-response relationships that enhance comparison of the investigated drug with its comparator (placebo or active), primarily with respect to its safety. In early phase I studies, when the PK profile of the drug is eventually still unknown, a traditional PK study should be performed with the aim to determine the plasma concentration-time profiles (see Fig. 2B ). This allows not only calculation of AUC but also determination of concentration versus time profiles over a dosing interval for each individual, as well as for the population. This approach yields relatively detailed exposure information that can be correlated to the observed responses in individuals. The exposure-response relationship based on concentration-time profiles can provide time-dependent information that cannot be derived from AUC or Cmin. Figure 2A 12-lead ECG sampling pattern in the run-in period (baseline). Minimum number of recordings are highlighted at 8, 14 and 20 hours. Figure 2B Plasma concentration-time profiles (PK/PD analysis). Within the bounds of maintained safety and tolerability, the QT/QTc evaluation should also be performed on ECGs recorded at substantial multiples of the maximum therapeutic exposure (multiples of Tmax – see Fig. 2B – samplings at 8, 12, 16, 20 and 24 hours from Tmax). Knowledge of "concentration increases" that might occur due to drug-drug or drug-food interactions require specifically adjusted study designs. Likewise, in instances where increased plasma concentrations and ensuing QT/QTc prolongation effects may occur due to a metabolite with different pharmacokinetic profile from that of the parent drug (see Fig. 3A and 3B ), a tailored study design will be needed. Figure 3A Plasma concentration-time profile of parent drug. Figure 3B Plasma concentration-time profile of metabolite. When the "through QT/QTc study" assessment is intended to be performed in drugs with well known pharmacokinetic profile (known optimal dose and therapeutic window), the sampling plan for both blood collection and ECG recordings will be spaced to match the known peak plasma concentration (Cmax – for single doses of the formulations) or the attained "steady state" after multiple dosing. Importantly, there can be large interindividual variability in the time to peak concentration with differences in the PK profile (e.g., Tmax, time to Cmax) due to demographics, disease states, etc., compelling to closely spaced samplings to account for these differences. Study design – Methodological Considerations The study design needs to be adjusted to the individual drug's pharmacokinetics and safety characteristics. Both the crossover and the parallel designs have specific advantages and relative disadvantages that need to be taken into account in the particular case at hand (see Additional file 1 ). However, as a rule, regardless of the design alternative chosen, the study should be randomised , double-blind and controlled . Primary objectives To quantify the dose-, concentration-, and time-relationships of the drug on the QT/QTc interval in the target population at therapeutic and supra-therapeutic plasma concentrations. Secondary objectives Collection of (serious) adverse events such as: • Absolute QT/QTc prolongation: - QTc > 500 ms and/or - QTc > 60 ms increase as compared to baseline • Events suggestive of arrhythmia:- TdP - Cardiac arrest/Sudden death - VT/VF - Syncope - Dizziness - Seizures - Palpitations Selection of control Selecting a control for the purpose of demonstrating safety of a product in terms of "no risk for QT/QTc prolongation effect" is inevitably facing the question of whether an active control or a placebo should be used. The basic assumption is however, that the largest time-matched mean (baseline subtracted) difference between the drug and control (placebo or active control) for the QT interval is ≤ 5 ms, with a one-sided 95% CI that excludes an effect at <8 ms. Placebo-controlled trials are still used to demonstrate effectiveness of new drugs and, for circumstance in which no increased risk for patients is foreseen, use of placebo seems appropriate and ethical, provided that the patients are fully informed and that they give written, informed consent [ 34 - 36 ]. At closer scrutiny, use of placebo in the particular case of demonstrating safety of a drug is not, by far, so much ethically charged as usually, as the subjects supposed to receive it are, in fact, exposed to a lesser degree of risk by QT prolongation. On the other hand, the "placebo-induced changes" are a reflection of underlying variability of the QT/QTc, an otherwise a well-known phenomenon. With other words, use of placebo-control in these cases is fully justifiable. Use of an active control, while extensively advocated currently, due to its considerable credibility as compared with placebo, may raise troublesome methodological issues, typical for equivalence trials, such as the rigorous choice of control agent with special emphasis to essay sensitivity, etc.[ 34 ]. Commonly, the primary objective of an equivalence/noninferiority trial is to demonstrate that the efficacy of a new treatment matches that of the control treatment while, in the "thorough QT/QTc study", the goal is to demonstrate that the safety of the new drug is equal or at least not worse than that of the control agent. This translates into the need to demonstrate that the new agent doest not prolong the QT/QTc by more than 5 ms on average, as compared to the control. That is to say that the "equivalence margin" is set to 5 ms, although, a definite prolongation effect will be stated if the upper bound of the one-sided 95% CI would exceed 8 ms [ 5 ]. The 5 ms value, as an average threshold for demonstrating non-inferiority of the tested drug versus a comparator, might be a too ambitious cut-off point (i.e., too low). With the technique currently available, this level of accuracy may possibly be attained by some highly skilled analysts, but it might be difficult to be maintained as an average level for an entire group of analysts. A more reasonable and practically attainable average value would be 10 ms. Individual subjects displaying prolongation in excess of 10 ms would, however, need to be given careful scrutiny. Target patient population These studies are generally performed in normal, healthy, adult volunteers. The subject population should be selected carefully to minimize inter-subjects variations. Restrictive eligibility criteria are recommended in early phase studies (I and II) of compounds known to have APD or QT prolonging effects, with subsequent widening of criteria in later phase studies (II and III). It is estimated that ECGs should be generated in at least 100 volunteers (including females and males), for NCE with no pre-clinical evidence of QT prolongation [ 37 ], and in at least 200 volunteers (including females and males) for NCE with pre-clinical evidence of prolonged action potential duration or prolonged QT/QTc [ 37 ]. The test and the reference products are usually administered to the subjects in the fasting state (overnight fast for at least 10 hours). These subjects should not take any other medication for one week prior to the study or during the study. Identical test conditions must be used for the two group subjects with respect to: foods, fluid intake, physical activity, posture, etc. and, the physical characteristics of the subjects should be standardized (age, height, weight, and health) [ 38 ]. Clinical studies in later phases of development (phase III) and after market approval (phase IV) are supposed to have enlarged inclusion criteria to encompass female and elderly patients, patients with associated comorbidities and with concomitant treatment. Exposure to the relative new treatment of a heterogeneous population, to mimic the real population anticipated to be the end-user of the drug in the future, is meant to create a "worst case scenario" for drugs that in the pre-clinical and clinical development stages have shown effects on the QT/QTc interval. Establishing with confidence the behaviour of the QT/QTc interval in these patients, while exposed to the peak effect (Cmax/steady state) of the drug, is not only an effective risk management tool but also a highly ethical issue. Timing of ECG recordings Baseline ECG sampling For NCE with suspected, or known from previous clinical studies, effects on the HR and/or APD, 10 to 20 baseline ECGs are required (see Fig. 2A ). For agents administered intermittently, repeated baseline ECG assessments may be needed prior to each new treatment period. Carry-over effects should be carefully taken into consideration when cross-over design is employed. During the run-in period of later phase trials (II-III), at least three baseline ECGs should be recorded [ 39 ]. "On-treatment" ECG sampling The pattern of ECG sampling should match the planned blood sample collections for PK assessment (see Fig. 2B ). There will be a few or up to 20 ECGs recorded during 24 hours period, depending on how the PK/PD analysis has been planned to be performed, on the amount of knowledge regarding the agent's pharmacokinetics as well as on the information generated by previous pre-clinical studies. However, regardless of the study design, whenever possible, ECGs should be recorded at the same time of the day during both baseline period and after randomisation (during "on-treatment") to minimize the confounding effects of diurnal variations and postprandial effects [ 37 ]. For drugs with known metabolite(s), the ECG recordings should cover the prolonged blood sampling for the plasma concentration-time profile of the metabolite (see Fig. 3B ). Whenever ethically justifiable, for the case of inadvertent over-dosage or metabolic inhibition, it is recommendable that ECGs should be recorded at substantial multiples of the maximum therapeutic exposure, even in excess of the upper bound of the anticipated therapeutic range (see Fig. 2B – sampling at 28 hours). Measurement of QT interval Quality of ECG recordings is of paramount importance for the reliability of the data generated. Poor quality traces due to artefacts or lead misplacement should be avoided through appropriate training of the staff in charge with acquisition of ECGs. Whether these people are professionals or temporary research staff, all are supposed to have a high level of expertise in ECG acquisition technique and be able to validate tracings that are analysable or not. Standard 12-lead ECGs should be taken in supine, after at least 5 minutes rest with default calibration of the recording device at 1 mV, speed at 50 mm/s. Currently, standard lead II is chosen for measurement of RR and PR interval, QRS complex and the QT interval, on at least three cardiac cycles. Two additional precordial leads may be used for performance of the same measurements (e.g., V3-V4). Means are computed consequently, from one or three leads. Manual measurement of different ECG parameters is charged with problems of accuracy and reproducibility due to the inter- and intra-observer variability inherent in such highly demanding tasks while, interpretation of ECG tracings is known to vary from one clinician to another [ 40 ]. However, ICH-GCP-compliant quality control and quality assurance SOPs, as well as systematic performance analyses applied to the individual analysts/technicians and their output data, employed nowadays in certain core laboratories, ensure the prospective clients of minimized inter- and intra-observer variability regarding the measurements performed and of high level of accuracy of the output results in the range of ± 10 ms, around a selected/agreed "gold standard" [ 41 ]. In order to ensure an overall high level of performance within a group of technicians/analysts who perform the factual measurements on ECG tracings, performance analysis applied to the group and each individual member of the group, should be run at six months interval. Deviation in the measurements performed of more than ± 10 ms should be addressed speedily and corrective measures implemented. Such quality-assurance performance analyses may maintain a high level of measurements' homogeneity and ensure a high quality of the data provided. Likewise, ECG tracings as well as summary data are subject to interpretation and reporting by qualified cardiologist(s) [ 4 ]. Fig. 4 depicts a normal ECG with the most common parameters measured in the process of exploring any new NCE's effects on the QT/QTc interval. Apparently, measuring the QT interval should be a quite straightforward task, however, in practice there are a number of pitfalls and difficulties [ 30 , 31 ]. Figure 4 Normal ECG highlighting the common parameters measured when assessing the QT/QTc interval. The beginning of the QRS complex is best determined in a lead with an initial "q" wave – commonly standard lead I or II, and leads aVL, V5 and V6. Sometimes, the "q" wave may be missing (the initial part of the QRS complex is isoelectric) due to its incorporation within the PR interval. Determining the precise end of the T wave may be simple, when a tangent line to the steepest part of the descending portion of the T wave is drawn and the intercept between the tangent and the isoelectric line is indicating the end of T wave. At times, however, the T wave may be obscured by a superimposed U wave or, in the case of sinus tachycardia, by the ensuing P wave, making the positioning of the fiducial point difficult. The U wave deflection is usually minimal or isoelectic in lead aVL. The aVL lead is therefore a useful for QT measurement since the end of the T wave is least likely to be obscured by a U wave. TU morphology assessment Different repolarization properties among the epicardium, M cells, and endocardium, as well as their interplay, are responsible for various morphologies of the T-wave and the pathologic U-waves. The T-wave is a symbol of the transmural dispersion of repolarization. Several hypotheses have been proposed to explain the genesis of the U-wave, which represents the last repolarization component of the ventricules [ 42 ] however, the hypothesis that the Purkinje network is responsible for the physiologic U-wave seems most plausible. Morphology changes of the T and U-wave should be interpreted as warning signs of TdP. Sometimes, a clear demarcation between the two waves is very difficult, exposing to the risk of underestimating the QT interval and, ultimately, to missing the clinical significance of the changes per se . Clearly, both qualitative and quantitative assessments of the repolarization changes occurring with different degrees of merger between the T and the U-wave are subject to a certain degree of subjectivity of the assessor. Therefore, it is recommendable that TU-wave morphology assessment to be made by qualified cardiologist(s) according to a standardised methodology. Additional file 2 captures the possible changes that may be encountered in the T-waves, U-waves and different forms of TU mergers in a particular individual. Additional file 3 summarizes the frequency distribution of TU morphology changes across two groups compared. Given the high level of subjectivity inherent in this type of assessments, with considerable discrepancies between two assessors, even when identical data are assessed, an overall, reasonable conclusion on the TU morphology changes can be provided by use of a visual analogue scale (see Fig. 5 ). The degree of normality/abnormality in a particular case is estimated on a scale from 1 to 10, on which: "1" – is definite abnormal and "10" – is unquestionably normal. As an example, the flat-to-small negative T-waves in V5/V6 in the early phase of hypertension could be scaled as "7", whereas the large negative T-waves in the same leads, in the case of severe aortic stenosis, would be scaled as "1". A classical "borderline" change would be given a "5". Figure 5 Visual Anlogues Scale to assist in reconciliating the inter-observer assessment of TU morphology. QT dispersion (QTD) Increased dispersion on the QT interval of the electrocardiogram has been proposed as a marker for increased risk of arrhythmias in patients with hypertrophic cardiomyopathy [ 48 ], long QT intervals [ 44 ], and sustained ventricular arrhythmias [ 45 ]. Most of the studies exploring QT dispersion were small and, thereby could not provide accurate data for the sensitivity and specificity of the method to be derived. One study has assessed different cut-off values for QT dispersion by employing ROC analysis, however, the QT dispersion analysed was essentially developed on the basis of a training set [ 46 ]. The average normal value of QT dispersion in normal subjects was ≤ 40 ms in 13 studies and ≥ 40 ms in eight studies [ 47 ]. The Rotterdam study reported QTc dispersion > 60 ms in apparently healthy subjects aged ≥ 55 years in whom a two-fold increase in sudden death was registered subsequently [ 48 ]. Despite sophisticated methods of computerised measurements of QT dispersion [ 49 , 50 ], the reliability of both manual and automatic measurement of QT dispersion is low and the method is considered a crude measure of the abnormalities during the whole course of repolarization [ 51 ]. However, more recent studies [ 52 , 53 ] indicated that dispersion in repolarization may arise from differences in the action potential durations between cells situated in difference myocardial layers and that heterogeneity in repolarization might be linked to induction of ventricular fibrillation [ 42 ]. The analysis of repolarization variability is commonly based on methods that evaluate spatial and temporal QT dispersion. Recent experimental studies [ 54 ] in arterially perfused canine left ventricular wedge preparations, suggest that the second part of the T wave represents the arrhythmogenic substrate and that the peak-to-end interval of the T wave is the trasmural dispersion of the repolarization. The TPE interval of the T wave is postulated to reflect the transmural dispersion in humans (as measured in V5) and might become a parameter to be routinely measured in the future. It is claimed that TPE correlates better than the QT-dispersion with TdP and that a TPE > 280 msec may be useful in predicting risk of TdP in acquired LQTS. Heart rate correction of QT interval The length of the QT interval varies inversely with heart rate and therefore shortens as the heart rate increases. Due to the known substantial inter-subject variability of the QT/RR interval relation, there is no mathematical formula to fit every individual. A formula that performs well in one healthy individual may not do so in another, resulting in over- or undercorrection of the QT interval. Several correction formulas exist. The Bazett formula (square root – QTcB = QT/RR 1/2 ) [ 55 , 56 ], most commonly used, is known to overcorrect at high heart rates and undercorrect at low heart rates [ 57 , 58 ]. The Fridericia formula (cubic root – QTcF = QT/RR 1/3 ) [ 59 ] is considered to reflect a more accurate correction factor in subjects with tachycardia. A more recent formula is the Framingham linear correction (QTcL = QT + 0.154 × [1 - RR]) known to be derived from a large patient population and thereby to be considered the most rigorous from an epidemiological perspective [ 60 , 61 ]. The main limitation in the aforementioned formulas is that each of them attempts to correct for heart rate only, while leaving into play a number of other known confounders (diurnal variability, effect of physical exercise, etc.). Disappointingly, analysis done on ECGs sampled from periods of stable heart rate provided no better results [ 62 ]. According to Malik et al., the relation between QT interval and heart rate is highly individual [ 63 ]. Using a parabolic heart rate correction formula (QTc = QT/RR α ) they demonstrated a large variability of the α exponent (range: 0.233 – 0.485) in 50 healthy subjects. The same parameter in Fridericia's and Bazett's formulas is 0.33 and 0.50 respectively. Malik and colleagues concluded that correction of QT interval by heart rate may be misleading, regardless of the method used. QT/RR regression models [ 64 , 65 ] can be used for computing the "right formula for the right data" in experimental situation, however, for practical purposes the Bazett and Fridericia as well as the linear corrections are preferred at present (from regulatory point of view). Reporting of measurement results Reporting of results becomes mostly informative if tabular frequency distribution and frequency histograms are used to display PR, QRS and QTc data (QTcB, QTcF, QTcL) for individuals and/or groups. For the hypothetic example captured in Fig. 2B , tabular representation of the data might be used to illustrate the frequency distribution of a number of parameters (PR, QRS, QTcB, QTcF, QTcL) matching the PK sampling (see Additional file 4 ). Summary data for the same parameters (Min, Max, Mean) as compared to baseline can be displayed for individual subjects and/or group of subjects (see Additional file 5 ). The relevant normal ranges for all parameters are given in Additional file 6 . Additional file 7 captures the baseline , mean and mean maximum values for all parameters measured/computed for one group (PR, QRS, QT, QTcB, QTcF and QTcL) and displays the difference (D1) between the mean value of each parameter "on-treatment" and the corresponding mean value at baseline. Given that a D2 value is to be computed for the second group (comparator), their difference (D2 – D1), for all parameters and the resulting p value (Bomferoni adjusted) could be displayed in Additional file 8 . Risk assessment as related to prolonged QT/QTc interval Risk-benefit assessment with respect to a drug's propensity to prolong the QT/QTc interval entails a careful judgement of the frequency and magnitude of QT changes encountered in the preclinical and/or clinical program and balancing the potential risks against the drug's benefit. The large variability in the prolonged QT/QTc behaviour as to the potential risk for a TdP ensuing, makes this task difficult and requires individual characterisation of a specific drug's effects on repolarization. Amiodarone, for example, is known to prolong repolarization but to cause rarely TdP. Sotalol which prolongs repolarization through the same mechanism of action as Amiodarone (blockade of the IKr channel) causes a more frequent occurrence of TdP [ 66 ]. Some agents may cause slight QTc prolongation but when combined with other drugs that inhibit the metabolism of the suspected drug (e.g., terfenadine and cisapride), marked prolongation can occur [ 67 ]. A typical example is dofetilide, a potent QT-prolonging class III antiarrhythmic agent indicated for atrial fibrillation. Concomitant administration of cimetidine with dofetilide was shown to enhance the QT-prolonging effect resulting in a dose-dependent, baseline-related QTc increase of 22% and 33% with 100 mg and 400 mg of cimetidine respectively [ 68 ]. It is estimated that about 40–50% of the cases of drug-induced QT interval prolongation and/or TdP, result from drug-drug interactions with metabolic inhibitors (as in the example of dofetilide-cimetidine) and that only 10% are associated with electrolyte imbalance, some 10% with concurrent use of other QT-prolonging drugs and approximately 10–20% of cases have no obvious risk factors [ 69 ]. As a general rule, it is recommended that any prolongation should be considered as a potential toxicity [ 36 ]. In this context, it has become a widespread consensus that outliers with QTc > 500 ms or a baseline-related increase of QTc > 60 ms are better predictors than the mean QTc values [ 44 ]. In such instances, a careful screening for associated underlying risk factors or concomitant drugs is recommended, in order to determine the best course of action. Small QT prolongations (<10 ms) are acceptable as long as there are no associated risk factors. Longer QTc, however, requires individual monitoring and withdrawal from study should be considered, while further elective investigation should be scheduled on a case-to-case basis (see Additional file 9 ). Risk management for marketed products Ideally, therapy should be individualized on the basis of patient's genotype/phenotype determined through pharmacogenetic studies performed in the early stages of a drug's development and through application of that information while exploring the drug's pharmacokinetic and pharmacodynamic properties, its drug interaction potential as well as when ethnical-based bridging data is generated. While genotyping of individual cases, where prior informed consent is obtained, based on strong suspicion of genetic substrate having caused substantial QT/QTc prolongation is highly recommendable (such as, outliers in phase I-III studies, patients withdrawn from study due to lack of efficacy or due to type A adverse events), large-scale genotyping in early stages of drug development or pre-prescription genotyping are still controversial. Consequently, the clinical and scientific community is facing the need to apply classical "individualizing therapy" approaches [ 70 ] in reducing the clinical risk of QT/QTc-related adverse events (TdP, VT/VF, sudden death, etc.). Obviously, the most elementary requirement in this respect is that prescribing physicians should fully comply with contraindications regarding co-prescription of interacting drugs and with the recommendation on appropriate monitoring of targeted patients. More specifically, attention should be given to pharmacokinetic and pharmacodynamic factors that constitute important risk factors [ 4 ]. Liver and/or renal diseases act as risk factors at pharmacokinetic level. Likewise, a multitude of metabolic inhibitors (see Additional file 10 ), when temporarily co-administered, develop high plasma concentration of the parent drugs, exposing them to high-dose pharmacology of the drugs concerned [ 4 ]. Pharmacodynamic risk factors include diseases that are associated with QT interval prolongation (see Additional file 11 ). Obviously, appropriate monitoring is a sine qua non condition for preventing SAE in patients known to be treated with QT-prolonging drugs. QT interval should be monitored in these patients: (i) at baseline; (ii) at steady-state post-dose and at each incremental dose; (iii) when there is an inter-current change in level of risk, and (iv) if the patient develops symptoms of tachycardia or impaired cerebral circulation [ 4 ]. Treatment should be discontinued if QTc ≥ 500 ms and appropriate measures instituted based on the clinical picture at hand. Occurrence of typical AE suggestive of eventual QT-prolongation, should prompt careful investigation of this possibility even in cases where initial QT/QTc assessment has shown to be negative. In such instances, it is recommended that screening for risk factors shall be employed and genotyping performed after receipt of informed consent. Furthermore, consideration should be give to "re-challenge" with the investigational drug under appropriate monitoring conditions, with the aim of obtaining an accurate assessment of the situation at hand as well as for getting useful information on dose- and concentration-response relationship. Conclusions Compelling evidence has accrued during the past years on the potential of several cardiac and non-cardiac drugs to prolong cardiac repolarization (reflected as prolonged QT on surface ECG) and to predispose to life-threatening arrhythmias. This evidence has a major impact on the risk-benefit ratio of any drug, currently carefully considered from early stages of clinical drug development by pharmaceutical companies, by ethics committees as well as by regulatory agencies. The broad spectrum of risk factors that may interplay in the increased propensity toward malignant arrhythmias of any new chemical entity is just increasing (congenital LQTS, genetic substrate, comorbidities, concomitant treatment) and adding to the complexity of the problem. This calls for standardized methodologies to deal with the multifaceted aspects that the QT/QTc prolongation poses in practice, meant to ensure that drugs awarded market approval have undergone appropriate quality assurance scrutiny and, where necessary, further post-marketing surveillance is systematically planned and reported on, in a timely manner. Competing interests The author(s) declare that they have no competing interests. Supplementary Material Additional File 1 Frequency distribution of TU morphology changes across two groups. Click here for file Additional File 2 TU morphology changes in individual subjects. Click here for file Additional File 3 Frequency distribution of TU morphology changes across two groups. Click here for file Additional File 4 Frequency distribution of the PR/QRS/QTc(B/F/L) data matching PK sampling (for individuals and/or groups). Click here for file Additional File 5 Summary of PR/QRS/QTc(B/F/L) data (for individuals and/or groups). Click here for file Additional File 6 Normal ranges for the PR/QRS/QTc(B/F/L) data and for the QTc(B/F/L) relative changes to baseline. Click here for file Additional File 7 Frequency distribution of the baseline and on-treatment values pertaining the PR, QRS, QT, QTcB, QTcF and QTcL parameters as well as the D1 difference. Click here for file Additional File 8 Summary of outcome differences between the two groups regarding key ECG parameters. Click here for file Additional File 9 Alert criteria based on ECG findings (measurements) and rational for subject withdrawal from study. Click here for file Additional File 10 Characteristics of the cross-over and parallel study designs. Click here for file Additional File 11 Disease associated with prolonged QT/QTc interval. Click here for file Additional File 12 Abbreviations (Not mentioned in the text!) Click here for file

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514898

Electroconvulsive therapy and determination of cerebral dominance

Electroconvulsive therapy (ECT) often results in a number of short- and long-time side effects including memory impairment for past and current events, which can last for several months after ECT treatment. It has been suggested that unilateral ECT (uECT) with electrodes placed over the non-dominant (typically right) hemisphere significantly reduces side effects, especially memory disturbances. It is important to note that cerebral dominance equates to speech dominance and avoiding this area of the brain also reduces speech dysfunction after ECT. Traditionally, the routine clinical determination of cerebral dominance has been through the assessment of hand, foot and eye dominance, which is an easy and inexpensive approach that, however, does not ensure accuracy. This review of literature on different methods and techniques for determination of cerebral dominance and provides evidence that functional transcranial Doppler sonography (fTCD) represents a valid and safe alternative to invasive techniques for identifying speech lateralisation. It can be concluded that fTCD, notwithstanding its costs, could be used as a standard procedure prior to uECT treatment to determine cerebral dominance, thereby further reducing cognitive side-effects of ECT and possibly making it more acceptable to both patients and clinicians.

Introduction Electroconvulsive therapy (ECT) is often regarded by the general public as a controversial procedure for the treatment of mental disorders. This is despite evidence of its safety and efficacy [ 1 ], and its benefit over anti-depressants in patients resistant to conventional medications and those with life threatening conditions such as catatonia and depressive stupor. The evidence suggests that in unipolar depression ECT has better efficacy when compared with older tricyclic antidepressants and monoamine oxidase inhibitors, as well as newer drugs such as paroxetine [ 2 ]. Notwithstanding the efficacy of ECT, its use is declining in some countries [ 3 ], while in a few others, including Italy – where ECT was first introduced in 1938 by Cerletti and Bini – it is prohibited. Aside from political reasons and public pressure, the declining trend in ECT use could be the result of the introduction of more effective antidepressants. A further possible explanation for the reduction in ECT use may relate to the concern over adverse effects of the procedure. There are a number of short-term side effects including headache, nausea and, sometimes, brief confusion. However, the main side effect of concern is memory impairment for past events (retrograde amnesia) and for current events (anterograde amnesia) that can last for several months after a course of ECT treatment. Some of these side effects are substantially reduced by advances in safety and the introduction of controlled-current ECT machines. The utilisation of muscle relaxants, anaesthetics and resuscitation equipment, and electroencephalographic monitoring during the application of ECT are considered now considered routine. In addition, ECT guidelines issued by the UK National Institute for Clinical Excellence [ 4 ] restrict the use of ECT only to patients with severe symptoms to which "an adequate trial of other treatment options has proven ineffective" (p. 5). The risk associated with ECT has also been reduced with the introduction of refined ECT procedures, such as "maintenance ECT" or "unilateral ECT" (uECT) [ 5 ]. It has been suggested that unilateral treatment significantly reduces side effects, especially memory disturbances [ 6 , 7 ]. Despite the well-documented efficacy of unilateral over bilateral ECT, current practice still favours bilateral treatments [ 8 , 9 ]. Unilateral treatment, for the majority of patients, entails that electrodes are placed over the non-dominant, right hemisphere. Given that memory impairment could be reduced by unilateral electrode placement and the fact that placement of electrodes to the dominant hemisphere may cause a greater disturbance in memory compared to non-dominant uECT, determination of cerebral dominance appears to be critical [ 10 ]. It is important to note that cerebral dominance here equates to speech dominance, including a lateralised capacity of the cortex to be the locus of language-specific memory traces [ 11 ]. Avoiding the stimulation of the speech area will therefore reduce speech dysfunction after ECT. Traditionally, the routine clinical determination of cerebral dominance has been through the assessment of hand, foot and eye dominance. It certainly is an easy and inexpensive approach, but it does not ensure accuracy. Unilateral ECT and cerebral dominance The practice of determining cerebral dominance from handedness appears to mirror Broca's view that a person's handedness is opposite to hemispheric language specialisation. This, however, is incorrect, since there is no "mirror-image" cortical language organisation in left-handers. Several attempts to improve cerebral dominance assessment by introducing additional clues such as handwriting posture (i.e. inverted or hooked style versus non-inverted) and familial sinistrality have not substantially improved the prediction as to determination of cerebral dominance [ 12 , 13 ]. For example, the use of hand writing posture to determine speech dominance has been shown to be completely invalid [ 14 - 16 ]. A great majority of left-handers have also an ipsilateral functional specialisation for language (i.e. left hemispheric, as in the majority of right-handers). Although right-handers are more clearly lateralised than left-handers in this regard, a certain proportion of right-handers have language localised in the right-hemisphere. This has been confirmed by various techniques, ranging from the old and invasive procedures such as the intracarotid sodium amytal test and ECT, to the new and more sophisticated techniques such as functional magnetic resonance imaging (fMRI) and functional transcranial Doppler sonography (fTCD). The pooling of empirical data from a number of studies [ 17 - 27 ] which used both old and new, non-invasive techniques to determine cerebral dominance for language is shown in Table 1 . Table 1 Percentages of right- and left-handers with speech localised predominantly in the left, right hemisphere, or bilaterally, according to different studies and techniques Study Right-handers Left-handers Left Bilateral Right Left Bilateral Right Milner, 1975* 96 0 4 70 15 15 Rossi & Rosadini, 1967* 99 1 0 40 10 50 Pratt & Warrington, 1972 # 99 0 1 - - - Warrington & Pratt, 1973 # - - - 70 7 23 Geffen et al., 1978 # 92 0 8 67 0 33 Geffen & Traub, 1979 ‡ 84 9 7 61 15 24 Springer et al. 1999 & 94 6 0 - - - Pujol et al. 1999 & 96 4 0 76 14 10 Szaflarski et al. 2002 & - - - 78 14 8 Hund-Georgiadis et al. 2002 & 94 0 6 47 12 41 Knecht et al. 2000 † - - 4 - - 27 * intracarotid sodium amytal test # ECT ‡ dichotic listening test & fMRI † fTCD From Table 1 one can see that if the hemisphere for uECT treatment were solely ascertained from handedness assessment, then a small proportion of right-handers and a much larger proportion of left-handers would have treatment administered to the dominant hemisphere. One could also see from it that about 3% of right-handers and 25% of left-handers have speech localised in the right hemisphere. This represents the error rate percentage in both groups if uECT was administered to all patients on the right side of the cranium. However, the overall error rate is lower since the incidence of left-handedness is low, and is likely to be in the range of 6.4% to 12.5% [ 28 ]. A strict application of the "mirror-image" cortical organisation (i.e. considering left-handers as right-hemisphere dominant and therefore performing left-sided uECT) is even more destructive, illogical, and would increase the error rate. For example, in the survey of the use of ECT by psychiatrists in New Zealand [ 9 ], 20% of respondents reported using uECT depending on handedness. Adverse effects caused by determining speech dominance on the basis of handedness would be lower if right-sided ECT was always administered, thus making handedness assessment unnecessary. Given the additional risk of uECT treatment on the dominant hemisphere, which is even more disruptive than bilateral ECT [ 29 ], correct identification of cerebral dominance appears to be crucial. The importance of identification of cerebral dominance prior to electrode placement has been highlighted by a number of authors [ 6 , 10 , 28 ], but routine ECT practice has remained unchanged. From intracarotid injection to transcranial sonography Until recently, an accurate determination of speech dominance prior to a course of ECT treatment was possible only through invasive procedures such as intracarotid sodium amytal test [ 30 ], also known as the Wada tests, and through the administration of ECT itself – the ECT Test [ 10 ]. Lateralisation of language capacity using the Wada test is based on the temporary anaesthesia of one half of the brain. The subject in the study receives sodium amytal – a short-acting anaesthetic – into (usually) the left carotid artery. This causes the left hemisphere to be temporarily rendered dysfunctional. As a result, if this were the patient's dominant hemisphere, the subject's language capacity – primarily speech production – is affected. Conversely, injecting sodium amytal into the right carotid artery leaves this language capacity intact. By using this technique it is possible to identify precisely which hemisphere hosts language, which is considered necessary for patients who are to go through neurosurgical procedures. Although accurate, the use of Wada procedure in a normal healthy population is generally considered as unsuitable. Using ECT for the determination of cerebral dominance is, as mentioned previously, associated with adverse effects and therefore may not be entirely appropriate, although Weiner [ 31 ] suggests giving left and right side ECT alternately followed by the administration of a simple verbal performance test and then continuing treatment with the side associated with the better result. The advent of sophisticated and non-invasive technologies during the 1980s and 1990s has enabled a non-invasive approach to the assessment of speech dominance. One of the most elegant, mobile, and cost effective methods for determining cerebral dominance for speech is functional transcranial Doppler sonography (fTCD). fTCD is increasingly used in both clinical and research settings and is a new and robust technique based on the same principles as fMRI. Subjects in studies using this method are asked to generate as many possible words within 5-second periods after a letter presented on the computer screen cues for word generation. Basically, fTCD measures cerebral blood flow velocity which corresponds to brain activity. The physical foundation for this technique is quite old and is based on the work of the Austrian mathematician and physicist, Christian Doppler (1803–1853), who discovered that the change in pitch results from a shift in the frequency of the sound waves. This means that the speed of a physical object (i.e. blood) can be estimated by measuring the rate of change of pitch. To complete the fTCD procedure, the additional sound produced through the arteries is required. Recently, it has been argued that fTCD can reliably replace the Wada procedure in patients undergoing brain surgery [ 32 ]. The validity of fTCD has been established by comparing fTCD with the Wada test, which is considered as the ultimate (gold standard) test of cerebral lateralisation for speech. Several independent studies [ 33 - 35 ] have found highly significant correlations between these two methods. A high agreement between fTCD and fMRI has also been identified [ 36 ] for the assessment of cerebral speech lateralisation. Conclusion This review of the literature on ECT and cerebral dominance provides evidence that fTCD represents a valid and safe alternative to invasive techniques for identifying speech lateralisation. It seems therefore, that fTCD, notwithstanding costs, could be used as a standard procedure prior to uECT treatment to determine cerebral dominance, thereby further reducing cognitive side-effects of ECT and possibly making it more acceptable to both patients and clinicians. Competing interests none declared.

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526194

Electroesophagogram in gastroesophageal reflux disease with a new theory on the pathogenesis of its electric changes

Background In view of the disturbed esophageal peristaltic activity and abnormal esophageal motility in gastroesophageal reflux disease, (GERD), we investigated the hypothesis that these changes result from a disordered myoelectric activity of the esophagus. Methods The electric activity of the esophagus (electroesophagogram, EEG) was studied in 27 patients with GERD (16 men, 11 women, mean age 42.6 ± 5.2 years) and 10 healthy volunteers as controls (6 men, 4 women, mean age 41.4 ± 4.9 years). According to the Feussner scoring system, 7 patients had a mild (score 1), 10 a moderate (score 2) and 10 a severe (score 3) stage of the disease. One electrode was applied to the upper third and a second to the lower third of the esophagus, and the electric activity was recorded. The test was repeated after the upper electrode had been moved to the mid-esophagus. Results The EEG of the healthy volunteers showed slow waves and exhibited the same frequency, amplitude and conduction velocity from the 2 electrodes of the individual subject, regardless of their location in the upper, middle or lower esophagus. Action potentials occurred randomly. In GERD patients, score 1 exhibited electric waves' variables similar to those of the healthy volunteers. In score 2, the waves recorded irregular rhythm and lower variables than the controls. Score 3 showed a "silent" EEG without waves. Conclusion The electric activity in GERD exhibited 3 different patterns depending on the stages of GERD. Score 1 exhibited a normal EEG which apparently denotes normal esophageal motility. Score 2 recorded irregular electric waves variables which are presumably indicative of decreased esophageal motility and reflux clearance. In score 3, a "silent" EEG was recorded with probably no acid clearance. It is postulated that the interstitial cells of Cajal which are the electric activity generators, are involved in the inflammatory process of GERD. Destruction of these cells appears to occur in grades that are in accordance with GERD scores. The EEG seems to have the potential to act as an investigative tool in the diagnosis of GERD stages.

Background Reflux esophagitis is a multifactorial disease that entails the reflux of gastric contents into the esophageal lumen [ 1 ]. Esophagitis develops when noxious substances in the refluxate have sufficient time to get in contact with the esophageal mucosa and then prevail over structural and functional defenses [ 2 ] The mechanisms involved in the defense of the esophagus against the gastric acid pepsin comprise the antireflux barriers, luminal clearance and epithelial resistance [ 3 - 6 ]. The antireflux barriers and the luminal clearance mechanism by peristalsis represent motor components of the reflux disease. The non-motility elements include salivary and esophageal submucosal glands. Abnormal esophageal motility results in an increased exposure of the esophageal mucosa to gastric contents. Progressing severity of the reflux disease is associated with failing primary peristalsis [ 7 - 9 ]. The failure rate in patients with mild and severe GERD is 25% and 36%, respectively [ 7 ]. The amplitude of peristaltic contractions in the esophagus is significantly lower in the esophagitis patients than in the controls [ 6 - 9 ], and is inversely related to esophagitis severity [ 7 , 10 ]. The duration of contractions was variable but the propagation velocity was unequivocally slower in esophagitis patients than in controls [ 7 , 8 , 11 ]. Previous studies have shown that the esophagus possesses electric activity presenting as slow waves (SWs) followed or superimposed by fast activity spikes or action potentials (APs) [ 12 , 13 ]. Action potentials were associated with a rise in the intraesophageal pressure. Balloon distension of the esophagus effected an increase in the electric activity proximally to the balloon and a decrease distally [ 12 ]. The caudad direction of the SWs and APs was evidenced when after esophageal myotomy the potentials appeared proximally but not distally to the cut in the experimental animal [ 12 ]. This suggested also the presence of a pacemaker in the cervical esophagus which might initiate the electric waves[ 12 ].In achalasia of the esophagus, three electroesophagographic patterns were identified: bradyesophagia, esophagoarrhythmia and "silent" electroesophagogram [ 13 ]. The three patterns seem to represent different stages in one pathologic process. In view of the disturbed esophageal peristaltic activity and abnormal esophageal motility in GERD, we hypothesized that these findings result from a disordered myoelectric activity of the esophagus. This hypothesis was investigated in the current study. Methods Subjects Twenty seven patients with GERD (16 men, 11 women, mean age 42.6 ± 5.2 SD years, range 36–48) were enrolled in the study. The diagnosis was confirmed by 24-hour pH monitoring, endoscopy and esophageal motility test. According to Feussner's scoring system [ 14 ], seven patients had a mild (score1), 10 a moderate (score 2) and 10 a severe (score 3) stage of the disease. Score 1 had mild heartburn with mild chest pain but no regurgitation, dysphagia, hiatus hernia or mucosal changes. Exposure time to pH was <4.4–8%. Score 2 had moderate heartburn, moderate chest pain, regurgitation after large meals, small hiatus hernia, and isolated erosive mucosal lesions. Score 3 had severe heartburn, severe chest pain, regurgitation, occasional dysphagia, hiatus hernia, and esophageal ulcers. The study also included 10 healthy volunteers (6 men, 4 women, mean age 41.4 ± 4.9 SD years, range 35–50) who had no reflux esophagitis. They had no gastrointestinal complaints in the past or at the time of enrollment in the study. Physical examination of both the patients and healthy volunteers had normal findings. The results of laboratory work comprising blood count, renal and hepatic function tests as well as electrocardiogram were unremarkable. The studied subjects gave an informed consent after having been fully informed about the nature of the study, the tests to be done and their role in the study. The study was approved by the Review Board and Ethics Committee of the Cairo University Faculty of Medicine. Methods The electric activity of the esophagus was recorded in the patients with GERD and the healthy volunteers. We used a monopolar silver-silver chloride electrodes of 0.8 mm diameter (Smith-Kline Beecham, Los Angeles, CA, USA) introduced through a 6F catheter (Rubber Industries Ltd., London, UK) with the electrode protruding by 1 cm from the catheter tip. The catheter was attached to the esophageal mucosa by negative pressure suction of 50 to 100 mmHg which was maintained during the test. Two electrodes were introduced into the esophagus by means of an endoscope and fixed to the esophageal mucosa by suction; one electrode was applied to the upper third, and the second to the lower third of the esophagus, and the electric activity was recorded. The upper electrode was then transferred to the middle third of the esophagus and recordings of the electric activity from the middle and lower third electrodes were performed. Signals from the electrodes were fed into an AC amplifier with a frequency response within ± 3 dB from 0.016 Hz to 1 kHz; they were displayed on a recorder at a sensitivity of 1 mV/cm. A metal disc applied to the abdominal skin served as the indifferent electrode. A strain gauge respiration transducer was attached to the thoracic wall for respiratory artefacts. We allowed the esophagus a 30 minute period to adapt to the electrodes applied to its wall, before we started a 120-min recording session for each subject. The results were analyzed statistically using the Student's t test. Differences assumed significance at p < 0.05 and values were given as the mean ± standard deviation (SD). Results No adverse side effects were encountered during or after the performance of the tests and all the subjects were evaluated. There was no difficulty in applying the electrodes to the esophageal mucosa. We found that a suction pressure of 50–60 mmHg was sufficient to keep the electrode fixed to the esophageal mucosa during the testing period in most of the subjects; in few cases we had to increase the suction pressure to 100 mm to keep the electrodes in position. Applying the aforementioned pressures, we encountered neither migration nor detachment of the electrodes during the entire test. We met no mucosal bleeding, tears or ulcers during application or after removal of the electrodes either. Electroesophagogram in healthy subjects Monophasic negatively deflected SWs were recorded from the 2 electrodes of each subject of all the studied individuals (fig. 1 ). They had an unvariable shape in all recordings from the same site. The frequency, amplitude and conduction velocity were constant in the individual subject. The SWs in each individual exhibited the same frequency, amplitude and regular rhythm from both electrodes (fig. 1 ), regardless of their location in the upper, middle or lower third of the esophagus. The mean and range of frequency, amplitude and conduction velocity of the 10 healthy volunteers are displayed in table 1 . These values were reproducible from the electrodes in the upper, middle or lower third of the esophagus. Bursts of APs representing fast activity spikes were recorded (fig. 1 ). They followed or were superimposed over the SWs; they occurred randomly and their frequency was inconsistent in each subject. Figure 1 Electroesophagogram of a healthy volunteer showing slow waves with regular rhythm and random action potentials. Table 1 The frequency, amplitude and conduction velocity of the slow waves of the healthy volunteers and patients with gastroesophageal reflux disease (GERD) + Slow waves Frequency c/m Amplitude (mV) Velocity (cm/s) Mean Range Mean Range Mean Range Volunteers 5.2 ± 1.3 4 – 7 0.52 ± 0.1 0.4 – 0.6 4.8 ± 0.7 3.5 – 6.1 Score 1 GERD 4.8 ± 1.2 4 – 6 • 0.49 ± 0.1 • 0.35 – 0.6 4.6 ± 0.7 • 4.1 – 5.9 Score 2 GERD Irregular Score 3 GERD Absent waves + values were given as the mean ± SD • p > 0.05 p values of the patients were compared to those of the healthy volunteers Electroesophagogram in GERD patients In score 1 GERD, the electric waves' variables were similar to those of the healthy volunteers in all the subjects (p > 0.05, fig 2 ). The SWs were monophasic and negatively deflected and had a regular rhythm (fig 2 ). The frequency, amplitude and conduction velocity are shown in table 1 . Action potentials were randomly recorded following or superimposed over the SWs. This electromyographic pattern was similar from the 2 recording electrodes of the individual subject and was reproducible during the recording period. Figure 2 Electroesophagogram of a patient with score 1 gastroesophageal reflux disease showing slow waves with regular rhythm and random action potentials. Score 2 GERD patients exhibited a different electromyographic pattern. The SWs had an irregular rhythm with varying but lower frequency, amplitude and conduction velocity compared to the normal controls (fig. 3 ). The APs occurred randomly and were less frequent than in the normal recordings (fig. 3 ). The SWs and APs differed from one electrode to the other of the same subject and were variable during the recording period. In 8 score 3 GERD patients, the electrodes did not register electric waves; neither SWs nor APs were recorded. A "silent" electromyographic pattern was registered (fig. 4 ); this picture was reproducible during the recording period. In the remaining 2 patients; occasional SWs were recorded that were inconsistent and different from the 2 electrodes of the same patient (fig. 5 ); no APs were recorded at any time during the recording period (fig. 5 ). Figure 3 Electroesophagogram of a patient with score 2 gastroesophageal reflux disease exhibiting slow waves with irregular rhythm and varying frequency, amplitude and conduction velocity from the same electrode and between the 2 electrodes of the same subject. Figure 4 Electroesophagogram of a patient with score 3 gastroesophageal reflux disease recording no electric activity: a "silent" electroesophagogram. Figure 5 Electroesophagogram of a patient with score 3 gastroesophageal reflux disease recording occasional slow waves with no action potentials. Discussion The current study has demonstrated that the esophagus possesses an electric activity in the form of regular SWs and APs. The waves in the healthy volunteers were reproducible with identical frequency, amplitude and conduction velocity in the same subject. Previous studies have shown that the APs were coupled with increased esophageal pressure, while the SWs were not [ 12 , 13 ], these findings presumably denote that the APs have a contractile activity [ 12 , 13 ]. Effective esophageal motility is a critical determinant for esophageal clearance of refluxed gastric contents [ 15 ]. A single normal peristaltic wave completely clears the entire barium bolus from the esophagus. If a peristaltic wave fails due to motile dysfunction, there is little or no volume clearance [ 16 ]. Increased exposure of the esophageal mucosa to gastric contents may result from abnormal esophageal motility. Thus, while a defective gastroesophageal barrier accounts for an increased number of gastroesophageal reflux episodes, abnormal esophageal peristalsis results in impaired esophageal acid clearance [ 17 , 18 ]. The relationship between esophageal peristalsis and gastroesophageal reflux has been studied using stationary and ambulatory prolonged esophageal manometry. Various motor-disorders have been detected in GERD including a significantly high rate of incomplete primary peristalsis, changes in esophageal motility and an increased number of non-transmitted contractions [ 6 , 19 ]. Contractions had a shorter duration and a slower propagation velocity [ 20 ]. Patients with abnormal GER but mild esophagitis, or none, had normal amplitude of contractions with increased prevalence of simultaneous contractions [ 16 , 21 ]. Meanwhile patients with severe esophagitis had reduced amplitude of contractions, slow propagation velocities and an increased rate of failed primary peristalsis [ 21 ]. The current study may shed some light on the mechanism of these motor changes in GERD. The electric activity in GERD exhibited different patterns depending on the stage of the GERD. In score 1 GERD, an electroesophagram similar to that of healthy volunteers was recorded. This apparently denotes that the motile activity of the esophagus in score 1 is normal and that the esophageal peristaltic activity can probably clear the esophagus of the refluxed gastric contents. The irregular and diminished esophageal electric wave variables displayed in score 2 GERD are presumably indicative of diminished motile activity and peristalsis of the esophagus with a resulting inhibited reflux clearance rate. The failure of adequate esophageal clearance is probably responsible for the clinical manifestations and investigative results encountered in score 2 GERD. With progress of the condition to score 3, there is probably no motor or peristaltic esophageal activity as evidenced by the absence of the esophageal electric waves. In such case, we presume that there is no esophageal clearance. We do not know the cause of the diminished esophageal electric activity in GERD. Is it due to the refluxed acid material or to the resulting esophageal inflammation? It may be argued that the refluxed acid content into the esophagus inhibits its motile and peristaltic activity. However, the current and earlier studies have demonstrated normal peristalsis in score 1 GERD in which acid reflux was manifest [ 16 ]. Furthermore, the current study showed normal EMG activity in this condition. Probably these findings negate the role of acid reflux as inhibitor of the peristaltic and electric activity in GERD. What then could be the cause of the deranged electric activity and peristaltic movement in the more advanced stages of GERD? A new theory of the pathogenesis of diminished electric activity in GERD The electric waves seem to be generated from the interstitial cells of Cajal that are located at the level of the myenteric plexus and in the circular muscle layer of the esophageal wall [ 22 - 24 ]. They are considered as the generators of the spontaneous pacemaker activity in the smooth muscle layers of the gut [ 22 - 24 ] and are also involved in neurotransmission [ 25 - 27 ]. They mediate or transduce inputs from enteric motor nerves to the smooth muscle syncytium. In the advanced stages of GERD it may be assumed that the inflammatory changes in the esophageal wall have involved the interstitial cells of Cajal. Destruction of these cells appears to occur in grades that are in accordance with the GERD socres. It seems that in score 1 GERD, the mucosal inflammatory changes of the esophagus, if present, have not involved the Cajal cells yet. With the more advanced stages of the disease as in scores 2 and 3, the Cajal cells are presumingly being gradually destroyed by the advancing esophageal inflammatory process. The diminished SW variables encountered in score 2 GERD seem to be due to partial involvement of Cajal cells in the inflammatory process; the cells are not yet completely destroyed and are still mediating electric and peristaltic activity. However the Cajal cells in score 3 GERD are believed to be extremely injured so that they cannot generate electric activity. Diagnostic role of electroesophagogram in GERD There are various methods for the diagnosis of GERD. They include pressure measurements using water-perfused manometry catheters, external transducers or intraluminal transducers, pH-metry and others [ 28 , 29 ]. However they might have disadvantages [ 30 ]. In view of the results of our above study, the introduction of the electroesophagogram as an investigative tool may be a valuable addition to the armamentarium of esophageal investigations of GERD. Conclusion The electric activity in GERD expressed 3 different patterns depending on the stage of GERD. In score 1 GERD, a normal electroesophagogram was recorded which would denote normal esophageal motile activity and acid clearance. Score 2 GERD exhibited irregular and diminished esophageal electric waves' variables which are presumably indicative of decreased esophageal motility and reflux clearance. In score 3, a "silent" electroesophagogram was recorded with probably no acid clearance. A new theory of the pathogenesis of diminished electric activity in GERD is put forward. It is postulated that the interstitial cells of Cajal which are considered as the generators of the pacemaker activity and electric waves, are involved in the inflammatory process of GERD. Destruction of these cells appears to occur in grades that are in accordance with GERD scores. The electroesophagogram may serve as an investigative tool in diagnosing the various GERD stages, especially if they can be recorded percutaneously. List of abbreviations gastroesophageal reflux disease = GERD (electroesophagogram = EEG slow waves = SWs action potentials = APs standard deviation = SD Authors contributions AS: Study design/ planning OES: Data collection/entry, Data analysis/statistics, Literature analysis/search IS: Data collection/entry, Data analysis/statistics, Literature analysis/search AS: Data collection/entry, Preparation manuscript Pre-publication history The pre-publication history for this paper can be accessed here:

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524032

Virology on the Internet: the time is right for a new journal

Virology Journal is an exclusively on-line, Open Access journal devoted to the presentation of high-quality original research concerning human, animal, plant, insect bacterial, and fungal viruses. Virology Journal will establish a strategic alternative to the traditional virology communication process.

The outbreaks of SARS coronavirus and West Nile virus (WNV), and the troubling increase of poliovirus infections in Africa, are but a few recent examples of the unpredictable and ever-changing topography of the field of virology. Previously unknown viruses, such as the SARS coronavirus, may emerge at anytime, anywhere in the world. Viruses previously thought to be geographically restricted, such as WNV, may appear in new regions and spread rapidly. Poliovirus, once thought to be on the brink of elimination, has surged with a widespread distribution in nearly a dozen African nations that now poses a serious risk to the polio eradication initiative. Governments and individuals are increasingly aware of the threats posed by viruses, including established viruses, emerging viruses and the many viruses that are potential agents of bioterrorism. However, lack of information or misinformation regarding viruses can further exacerbate their impact on public health. There is an urgent need for a rapid forum for communications among virologists. Virology Journal will present high-quality original research concerning human, animal, plant, insect bacterial, and fungal viruses, while establishing a strategic alternative to the traditional virology communication process. Links to an extensive database of virology information on the Internet will be provided through our "All the Virology" (ATV) web site . Open Access Virology Journal 's Open Access policy changes the way in which articles in virology can be published [ 1 ]. First, all articles are freely and universally accessible online as soon as they are published, so an author's work can be read by anyone at no cost. Second, the authors hold copyright for their work and grant anyone the right to reproduce and disseminate the article, provided that it is correctly cited and no errors are introduced. Third, a copy of the full text of each Open Access article is permanently archived in an online repository separate from the journal. Virology Journal 's articles are archived in PubMed Central [ 2 ], the US National Library of Medicine's full-text repository of life science literature, and also in repositories at the University of Potsdam [ 3 ] in Germany, at INIST [ 4 ] in France and in e-Depot [ 5 ], the National Library of the Netherlands' digital archive of all electronic publications. Open Access has four broad benefits for science and the general public. First, authors are assured that their work is disseminated to the widest possible audience, given that there are no barriers to access their work. This is accentuated by the authors being free to reproduce and distribute their work, for example by placing it on their institution's website. It has been suggested that free online articles are more highly cited because of their easier availability [ 6 ]. Second, the information available to researchers will not be limited by their library's budget, and the widespread availability of articles will enhance literature searching [ 7 ]. Third, the results of publicly funded research will be accessible to all taxpayers and not just those with access to a library with a subscription. As such, Open Access could help to increase public interest in, and support of, research. Note that this public accessibility may become a legal requirement in the USA if the proposed Public Access to Science Act is made law [ 8 ]. Similar calls for a move to Open Access of all scientific research have been made recently by the UK government [ 9 ]. Fourth, a country's economy will not influence its scientists' ability to access articles because resource-poor countries (and institutions) will be able to read the same material as wealthier ones (although creating access to the Internet is another matter [ 10 ]). This is particularly relevant in virology as many viruses have regional, rather than global, distributions. Peer Review policy Virology Journal will consider: research, book reports, case reports, commentaries, debate articles, hypotheses, methodology articles, reviews, short reports and short protocols. An editorial board of 30 members has been established [ 11 ]. In addition to these outstanding individuals, nine other distinguished virologists constitute an advisory board that will provide general oversight of the journal [ 11 ]. While initially all manuscripts will be submitted to my office, as Editor-in-Chief, as the volume of manuscripts increases, submissions in specific areas of virology (ie. large DNA viruses, plant viruses etc) will go directly to a Section Editor chosen by the author. The Editor-in-Chief or Section Editor will assign each research manuscript submitted to the journal to a member of the Editorial Board who will be known as the "monitoring editor". The monitoring editor will then appoint at least two ad hoc reviewers from experts in the field. Once the reviewers have provided their feedback, the monitoring editor makes the final recommendation. Managing Editor, David Sander will be available to assist authors with content and formatting issues not resolved during the review process. He will also assist the authors of review articles with integration of content with the ATV website (where appropriate). Articles will be published online immediately upon acceptance and soon after listed in PubMed. Competing interests Critics of Open Access often suggest that Editors have a financial incentive to accept articles as more articles means more revenue. However, BioMed Central insists that decisions about a manuscript must be based on the quality of the work, not on whether the article-processing charge can be paid. This policy will certainly apply for Virology Journal whose authors and readers will benefit from learning about viruses in regions of the world with limited financial resources. No member of the editorial or advisory boards of Virology Journal or their Institutions will receive any portion of the article-processing charge. It is also a BioMed Central policy that Editors should declare their competing interests. Several years ago, I suggested that it would be a useful policy for the Editors of scientific and medical journals to declare their competing interests on a yearly basis [ 12 ]. Few editors have accepted this suggestion, but by way of example I shall declare my own here: "I declare that my institution holds or has applied for several United Stated and International patents based on technology developed in my laboratory. These patents or patent applications cover a range of technologies including diagnostic assays, human A-type retroviruses and a B-type retrovirus (betaretrovirus), and peptides that inhibit viral infectivity. Tulane University has licensed some of these technologies to private companies for commercial development (list available on request), and I receive royalties from these licenses. I have also served on several study sections for the National Institutes of Health and currently served as the Chair of a biodefense study section (SSS-Z). I receive a per diem and reimbursement from the NIH for service on the study sections. Except for mutual funds in a retirement account managed through Tulane University, I own no stocks or other commercial instruments." Conclusion There are several outstanding virology journals covering all aspects of this dynamic field, but none of the general virology journals are exclusively published on-line or are Open Access. With the launch of Virology Journal , we hope to catalyse a fuller utilization of the Internet for scientific communication in virology drawing on our long experience with the ATV website. We welcome any advice and input.

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539063

Structure of a Conserved RNA Element in the SARS Virus Genome Determined

In February 2003, the first (and so far only) epidemic of severe acute respiratory syndrome (SARS) started in Guangdong Province, China. A respiratory illness that begins with a high temperature and can develop into life-threatening pneumonia, SARS is spread by close person-to-person contact. Before the end of the month, a Guangdong doctor had inadvertently taken the infection to Hong Kong. A woman staying in the same Hong Kong hotel as the doctor then carried the disease to Toronto. In March, the World Health Organization issued a global alert and warned against unnecessary travel to affected areas. Because of these and other containment efforts, 8,098 people became ill with SARS, rather than the predicted millions; 774 people died. The last case of the epidemic was reported in Taiwan in June 2003, and since then there have been only two cases in Singapore and nine in China. By May 2003, a coronavirus had been identified as the cause of SARS, and the full genome sequence of this new human pathogen, which may have jumped from civet cats to people, had been published. From the viral genome, researchers have deduced the sequences and structures of the viral proteins, hoping to use this information to develop treatments and vaccines for SARS. But could the structure of the RNA genome itself also be a target for antiviral drugs? Structure of a conserved RNA element within the SARS virus genome The genome of the SARS virus is a single strand of RNA that folds into regular repeating patterns to form secondary structures such as helices. These then fold and bend in three dimensions to form complex tertiary structures. William Scott and colleagues have used X-ray crystallography to measure the exact positions of individual ribonucleotides and the interactions between them in a small segment of the SARS virus genome called the s2m element. This element sits at one end of the viral genome, and, as the researchers show, its sequence is highly conserved in related coronaviruses. Furthermore, unlike the rest of the SARS genome, which changes rapidly, the s2m element is absolutely conserved in SARS variants obtained from patients during the SARS epidemic. This strong sequence conservation indicates that the tertiary structure of s2m could be important for viral function, and when the researchers solved the three-dimensional crystal structure of the element, they found that it had a unique tertiary structure. In particular, there was a right-angle kink in its helical axis and a tunnel with a net negative charge. The biological role of a new protein can often be deduced by comparing its shape with that of proteins with known functions. Scott and colleagues used this approach to hypothesize that the function of the s2m element involves interaction with a conserved host factor during the SARS life cycle. Finding a similar 90° kink in a region of ribosomal RNA that binds factors necessary for the initiation of protein synthesis, the researchers speculate that the SARS virus may use the s2m element to hijack its host cell's protein synthesis machinery. This and other putative roles need to be tested experimentally, but given that the s2m element is absent in the human genome, its unusual structural features could be an attractive target for the design of antiviral therapeutic agents.

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529258

HLA haplotypes associated with hemochromatosis mutations in the Spanish population

Background The present study is an analysis of the frequencies of HLA-A and -B antigens and HLA haplotypes in two groups of individuals homozygous for the two main HFE mutations (C282Y and H63D) and a group heterozygous for the S65C mutation. Methods The study population includes: 1123 healthy individuals, 100 homozygous for the C282Y mutation, 138 homozygous for the H63D mutation and 17 heterozygous for the S65C mutation. HFE and HLA alleles were detected using DNA-based and microlymphocytotoxicity techniques respectively. Results An expected significant association between C282Y and the HLA-A3/B7 haplotype was found, but other HLA haplotypes carrying the -A3 antigen were found: HLA-A3/B62 and HLA-A3/B44. Also, a significant association between H63D mutation and HLA-A29/B44 haplotype was found, and again other HLA haplotypes carrying the HLA-A29 antigen were also found: HLA-A29/B14 and HLA-A29/B62. In addition, the S65C mutation seems to be associated with a HLA haplotype carrying the HLA-A26 antigen. Conclusion These findings clearly suggest that HLA-A3/B7 and HLA-A29/B44 are the ancestral haplotypes from which the C282Y and H63D mutations originated, respectively. The frequencies of these mutations in different populations, their geographical distribution, and the degree of the statistical association to the ancestral haplotypes, suggest that the H63D mutation must have occurred earlier than the C282Y mutation.

Background Hereditary hemochromatosis (HH) is an autosomal recessive disease common in northern European populations. HH is characterized by increased iron absorption and deposition in the liver, pancreas, heart, joints and pituitary gland. Without treatment, death may occur from cirrhosis, primary liver cancer, diabetes or cardiomyopathy. In 1996, the HH gene ( HFE ) was cloned and located on the short arm of chromosome 6 (6p21.3) [ 1 ], 4 megabases (Mb) telomeric to the major histocompatibility complex (MHC). A single point mutation 845 G>A (exon 4), changing cysteine at position 282 to tyrosine (C282Y) is identified in 85 to 100% of patients with HH in populations of northern European descent, but it is found in only 60% of cases from Mediterranean populations [ 2 ]. Two other mutations, 187 C>G (exon 2), a histidine to aspartate change at amino acid 63 (H63D) and 193 A>T (exon 2), a serine to cysteine change at amino acid 65 (S65C) appear to be associated with milder forms of HH and may increase risk of disease in persons heterozygous for C282Y mutation [ 3 , 4 ]. C282Y lies within a Celtic ancestral haplotype which includes the human MHC (HLA) haplotype HLA-A3/B7 [ 5 ]. The HLA-A3/B7 haplotype was reported in HH patients in many European and populations of European descent [ 5 - 8 ] but HLA-A3/B14, HLA-A3/B35 and others were also reported [ 9 - 11 ]. The predominance of the HLA-A3 associated haplotypes on hemochromatosis chromosomes, and the pattern of their distribution in the world, led Simon et al [ 5 ] to propose the founder hypothesis, postulating that the hemochromatosis mutation was a rare event that occurred once on a particular chromosome which was subsequently modified by recombinations involving both HLA-B and HLA-A alleles and population migrations, producing the varied haplotype associations that were described. In contrast, the H63D substitution is not restricted to European populations: allele frequencies greater than 5% are found in countries bordering the Mediterranean, in the Middle East, and in the Indian subcontinent. H63D seems to be associated with HLA-A29 and HLA-B44 [ 3 , 12 ]. A few studies have been performed on the distribution of the S65C mutation in Europe and other countries. In 1999, Barton et al [ 13 ] identified the S65C mutation in Alabama hemochromatosis probands and found that this mutation was linked to a haplotype characterized by HLA-A32; and recently, Couto et al [ 14 ] found that this mutation is in linkage disequilibrium with the HLA-A29/B44 haplotype. The aim of this study is to find the HLA antigens and haplotypes associated with the three main mutations in the HFE gene in a sample of the Spanish population. Methods Individuals A total of 100 unrelated individuals homozygous for the C282Y mutation, 138 unrelated individuals homozygous for the H63D mutation and 17 individuals heterozygous for the S65C mutation were selected for this study. These were subjects in whom HFE genotyping has been previously performed on a medical care basis because of a presumptive diagnosis of hemochromatosis. In addition, 1113 unrelated, apparently healthy subjects were used as controls for the study. In addition, HLA typing was performed in 230 individuals whom HFE genotyping was negative for the three mutations. HLA-A and -B typing HLA-class I typing was performed on freshly collected venous blood samples by the standard complement-dependent microlymphocytotoxicity assay using commercially available alloantisera. DNA extraction and HFE amplification Genomic DNA from whole blood samples was extracted by standard protocols. Polymerase chain reaction (PCR) with the pair of primers HEMEx2-5' (5'-CTT TGG GCT ACG TGG ATG ACC) and HEMEx2-3' (5'-CTG GCT TGA AAT TCT ACT GGA AAC C) was used to amplify exon 2 of the HFE gene. To amplify exon 4, a second set of oligonucleotides was used: HEMEx4-5' (5'-GGT GTC GGG CCT TGA ACT ACT ACC) and HEMEx4-3' (5'-A CAT ACC CCA GAT CAC AAT GAG G). The following conditions were used for the PCR reactions: five minutes denaturation at 94°C, 40 cycles of 15 seconds denaturation at 95°C, 15 seconds annealing at 57°C and 30 seconds extension at 72°C. PCR products coming from exons 2 and 4 were 101 and 228 base pairs (bp), respectively. Digestion with mutation-specific restriction endonuclease Following the PCR amplifications, aliquots (17 μl) of the reaction mixture were digested with the restriction endonucleases Bcl I (exon 2), Hinf I (exon 2) and Rsa I (exon 4) for 3 hours following the protocol recommended by the manufacturer (Promega, Madison, WI). The H63D mutation destroys the Bcl I site in the 101 bp PCR product, so while normal DNA is cut into two fragments of 38 and 63 bp, the mutated DNA is not cut. The S65C mutation destroys the Hinf I site in the 101 bp PCR product, so while normal DNA is cut into two fragments of 47 and 54 bp, the mutated DNA is not cut. The C282Y mutation creates a new Rsa I site, the 228 bp DNA product digested with this enzyme is cut into two fragments of 145 and 83 bp in the normal allele, while in the mutated DNA three fragments of 145, 29 and 54 bp are generated after digestion. The digested products were size resolved in 10% acrylamide gel and detected by staining with ethidium bromide. Statistical analysis Allele and haplotype frequencies were estimated using Arlequin V2.0 software [ 15 ]. The haplotype frequencies were computed using the Expectation-Maximization algorithm [ 16 ]; this procedure is an interactive process aimed at obtaining maximum-likelihood estimates of haplotype frequencies from multi-locus genotype data when the gametic phase is unknown. The existence of association between HFE mutations and HLA-A and -B alleles and haplotypes was calculated by 2 × 2 comparison tables and p values were corrected according to the number of alleles or haplotypes compared [ 17 ] and using Yates corrected Chi 2 and Fisher's tests. Odds ratios were calculated as previously described [ 18 ]. Results The allele frequencies of the HLA-A and -B antigens found in the C282Y carriers group, in comparison with the frequencies in the control population are listed in Table 1 . As expected, significant associations were found for HLA-A3 and -B7, but HLA-B62 also shows significant association. The association of HLA-A3 is stronger than that of HLA-B7 or -B62. The frequencies of the HLA-A/B haplotypes in the homozygous group in comparison with the haplotype frequencies in the control population are listed in Table 2 . Three haplotypes are significantly associated with the C282Y mutation: HLA-A3/B7, HLA-A3/B62 and HLA-A3/B44. Table 1 Allele frequencies of HLA-A and HLA-B antigens in the C282Y homozygous group in comparison with the control group. C282Y HOMOZYGOTES CONTROLS C282Y HOMOZYGOTES CONTROLS HLA Freq (n = 200) OR p Freq (n = 2226) HLA Freq (n = 200) OR p Freq (n = 2226) A1 0.070 0.69 N.S. 0.097 B8 0.035 0.81 N.S. 0.044 A3 0.425 6.23 <10 -7 0.106 B7 0.260 3.67 <10 -7 0.089 B62 0.075 2.74 0.030 0.028 A29 0.035 0.54 N.S. 0.062 B44 0.170 1.19 N.S. 0.146 A30 0.010 0.16 0.093 0.060 B18 0.015 0.27 0.120 0.088 A2 0.195 0.67 N.S. 0.264 B35 0.095 0.77 N.S. 0.119 A11 0.060 0.75 N.S. 0.078 B51 0.055 0.60 N.S. 0.088 A26 0.020 0.42 N.S. 0.046 B49 0.025 0.67 N.S. 0.036 A28 0.025 0.59 N.S. 0.041 B60 0.015 0.42 N.S. 0.035 A32 0.020 0.57 N.S. 0.034 B14 0.010 0.28 N.S. 0.035 A23 0.030 0.95 N.S. 0.031 B38 0.010 0.33 N.S. 0.029 A33 0.010 0.36 N.S. 0.027 B27 0.025 0.88 N.S. 0.028 A25 0.020 0.97 N.S. 0.020 B50 0.005 0.21 N.S. 0.023 A31 0.025 1.56 N.S. 0.016 B65 0.015 0.64 N.S. 0.023 Freq: Frequency n: Total number of alleles in each group OR: Odds ratio p: Significance level N.S.: Not significant Table 2 Frequencies of HLA-A/B haplotypes in the two groups homozygous for H63D and C282Y in comparison with the control group. HAPLOTYPE H63D HAPLOTYPES Freq (n = 276) p OR C282Y HAPLOTYPES Freq (n = 200) p OR CONTROLS Freq (n = 2226) A1/B8 0.02513 N.S. 0.01500 N.S. 0.0246 A2/B7 0.03612 N.S. 0.02859 N.S. 0.0239 A2/B44 0.08254 N.S. 0.04037 N.S. 0.0443 A2/B51 0.04839 N.S. 0.00000 0.0404 A2/B35 0.01545 N.S. 0.03543 N.S. 0.0258 A3/B14 0.00000 0.00000 0.0005 A3/B7 0.00725 N.S. 0.20275 <10 -7 7.29 0.0343 A3/B62 0.00000 0.03379 10 -5 16.11 0.0024 A3/B44 0.00409 N.S. 0.08989 <10 - 12.13 0.0079 A11/B27 0.01812 N.S. 0.00000 0.0064 A11/B35 0.00362 N.S. 0.00862 N.S. 0.0204 A24/B35 0.00794 N.S. 0.01478 N.S. 0.0233 A29/B44 0.13261 <10 -7 3.93 0.02999 N.S. 0.0378 A29/B14 0.01449 <0.01 32.7 0.00000 0.0005 A29/B62 0.01591 <0.01 32.7 0.00000 0.0005 A30/B18 0.01087 N.S. 0.00000 0.0278 A33/B14 0.00000 0.00500 N.S. 0.0121 Freq: Frequency n: Total number of haplotypes in each group OR: Odds ratio p: Significance level N.S.: Not significant The allele frequencies of the HLA-A and -B antigens in the H63D homozygous group in comparison with the frequencies in the control population are listed in Table 3 . Significant associations were found for HLA-A29 and -B44. Again, the association of the HLA-A antigen (HLA-A29) is stronger than HLA-B44. The frequencies of the HLA-A/B haplotypes are also listed in Table 2 , and three HLA-A/B haplotypes (with the same HLA-A antigen, HLA-A29) are significantly associated with the H63D mutation: HLA-A29/B44, HLA-A29/B14 and HLA-A29/B62. Table 3 Allele frequencies of HLA-A and HLA-B antigens in the H63D homozygous group in comparison with the control group. H63D HOMOZYGOTES CONTROLS H63D HOMOZYGOTES CONTROLS HLA Freq (n = 276) OR p Freq (n = 2226) HLA Freq (n = 276) OR p Freq (n = 2226) A1 0.061 0.60 N.S. 0.097 B8 0.050 1.14 N.S. 0.044 A3 0.086 0.80 N.S. 0.106 B7 0.068 0.75 N.S. 0.089 B62 0.028 1.00 N.S. 0.028 A29 0.199 3.65 <10 -7 0.062 B44 0.264 2.10 2.10 -5 0.146 A30 0.036 0.58 N.S. 0.060 B18 0.086 0.98 N.S. 0.088 A2 0.286 1.12 N.S. 0.264 B35 0.076 0.60 N.S. 0.119 A11 0.036 0.44 N.S. 0.078 B51 0.097 1.12 N.S. 0.088 A26 0.029 0.61 N.S. 0.046 B49 0.032 0.89 N.S. 0.036 A28 0.021 0.52 N.S. 0.041 B60 0.011 0.30 N.S. 0.035 A32 0.039 1.16 N.S. 0.034 B14 0.014 0.40 N.S. 0.035 A23 0.047 1.52 N.S. 0.031 B38 0.032 1.10 N.S. 0.029 A33 0.007 0.26 N.S. 0.027 B27 0.036 1.29 N.S. 0.028 A25 0.032 1.60 N.S. 0.020 B50 0.018 0.76 N.S. 0.023 A31 0.011 0.67 N.S. 0.016 B65 0.039 1.74 N.S. 0.023 Freq: Frequency n: Total number of alleles in each group OR: Odds ratio p: Significance level N.S.: Not significant From the 17 individuals heterozygous for the S65C mutation, 7 (20%) were HLA-A26 versus 4.6% found in the control population (p = 0.02, OR = 5.29). No association with HLA-B has been found. The significant associations did not change if we used a control group of 230 individuals without HFE mutations. Discussion Populations of homozygous individuals for C282Y and H63D are optimal groups to study the HLA haplotypes in which these mutations preferentially appear. To our knowledge, Barton [ 19 ] and the present work are the only studies of associations between HFE mutations and HLA antigens and haplotypes in homozygous probands. The paper by Barton and Acton [ 19 ] presents haplotype frequencies assessed by family studies where phase could be set; in our paper, the haplotype frequences are estimated because the probands and controls are unrelated individuals. The low frequency of the S65C mutation makes the sampling of homozygous probands difficult and imposes the use of heterozygous individuals for the analysis. C282Y and HLA The strong association between the HLA-A3/B7 haplotype and the C282Y mutation indicates that this haplotype is the main one associated with this mutation in the Spanish population. However, other haplotypes are also associated: HLA-A3/B62 and HLA-A3/B44. This finding supports the founder hypothesis of Simon et al [ 5 ]: the ancestral haplotype where the C282Y mutation occurred on the ancestral haplotype HLA-A3/B7 and subsequent recombinations involving both HLA-B and HLA-A alleles produced the varied haplotype associations that have been found. Thus, we found many HLA-A/B haplotypes in our C282Y group, but only three HLA-A3 bearing haplotypes are statistically associated with this mutation. The two less frequent haplotypes (HLA-A3/B44 and HLA-A3/B62) have been observed in other populations in association with HH [ 20 , 21 ]. In addition, the high frequency of the HLA-A3/B7 haplotype makes other HLA antigens and haplotypes have reduced frequencies in respect to the controls. It is interesting to see that haplotypes with high-frequency in the Spanish population, such as HLA-A30/B18 and HLA-A2/B51 are absent in the C282Y homozygous group (Table 2 ). These HLA haplotypes are not contaminated by the C282Y mutation, and up until now, these haplotypes may be considered as protector haplotypes. H63D and HLA Porto et al [ 3 ] and Cardoso et al [ 22 ] found individual associations between HLA-A29 and non-classical forms of iron overload in linkage disequilibrium with H63D, and a strong linkage disequilibrium between H63D and all A29 containing haplotypes assigned in a large population of normal portuguese families. In the present work we found a strong association between the HLA-A29/B44 haplotype and the H63D mutation. Our finding agrees with the association of HLA-A29/B12(44) and hemochromatosis described in the Danish population [ 21 ]. H63D and HLA-A29-bearing haplotypes follow a pattern of associations similar to that described for C282Y and HLA-A3-bearing haplotypes. This promotes speculation that HLA-A29/B44 is the ancestral haplotype from which the H63D mutation emerged, since other HLA-A29 carrying haplotypes are also statistically associated with the mutation (HLA-A29/B14 and HLA-A29/B62, see Table 2 ), confirming the results reported by Cardoso et al [ 22 ] in the normal Portuguese population. Studies in other populations might lend support to whether HLA-A29/B44 is the ancestral haplotype of the H63D mutation, and HLA-A29/B14 and HLA-A29/B62 are specific Spanish haplotypes associated with H63D mutation. C282Y and H63D mutations: which one is older? In an attempt to establish the relative age of C282Y and H63D mutations, we have analysed the geographical distribution, allele frequencies and HLA haplotype associations for each mutation, assuming that the mutations ocurred once and that its age is directly proportional to its geographical spread, its frequency in the population, and the number of HLA haplotypes to which they are linked. On the other hand, a strong association of a particular HFE mutation to a particular HLA haplotype could mean that the mutation arose more recently, since the lower number of ruptures and recombinations of the original haplotype would reflect that a shorter time has passed. Merryweather-Clarke et al [ 23 ] analysed 2978 samples from probands distributed world-wide and showed that the C282Y mutation was most prevalent in northern European populations and absent from samples of non-European subjects (Africans, Asians, Australasians and Americans). In contrast, the H63D mutation is not restricted to European populations, being found in countries bordering the Mediterranean, in the Middle East and in the Indian subcontinent, and its allele frequency is higher than that of the C282Y mutation [ 23 ]. Our analysis of C282Y and H63D homozygous groups yielded a higher number of HLA haplotypes in association with the H63D mutation; and the frequency of HLA-A3/B7 in the C282Y homozygous group is 20%, while the frequency of HLA-A29/B44 in the H63D homozygous group is 13% (see table 2 ), reflecting that the HLA-A29/B44/H63D haplotype has suffered more recombinations than HLA-A3/B7/C282Y, and therefore, that HLA-A29/B44/H63D is older [ 24 ]. Altogether, these features suggest that the H63D mutation may have occurred earlier than the C282Y mutation, as has been previously proposed in studies from Italian populations [ 25 , 26 ]. S65C and HLA Few studies have been performed on the distribution, frequency and HLA association of the S65C mutation in Europe and other continents. Barton et al [ 13 ] described the linkage of the S65C mutation to a HLA-A32 haplotype in hemochromatosis probands from Alabama. Surprisingly, Couto et al [ 14 ] found the linkage of S65C (and not H63D) to the HLA-A29/B44 haplotype in a population from the Azores, although only 5 H63D homozygous and 9 S65C heterozygous individuals were studied in that work. In the present work we find that the S65C mutation seems to be linked to HLA-A26 in the Spanish population. Further studies in other populations and with more S65C-bearing haplotypes are necessary to shed light on the generation of the S65C mutation. Conclusions We have found that, in the Spanish population, the three main HFE mutations: C282Y, H63D and S65C, are in linkage disequilibrium with HLA haplotypes carrying the HLA-A3, -A29 and -A26 alleles, respectively. In addition, the ancestral HLA haplotypes from which C282Y and H63D mutations were originated are HLA-A3/B7 and HLA-A29/B44, respectively, and H63D is older than C282Y. Further studies in other populations using homozygous individuals for HFE mutations will help to identify the associated ancestral and specific haplotypes. Competing interests The author(s) declare that they have no competing interests. Authors' contributions Authors AP and PM conceived the study, contributed to proband characterisation, performed statistical comparisons and edited the manuscript. Authors EM, MJR, MJC, DO, MGB and LG contributed at different times to the characterisation of probands and HLA typing. Pre-publication history The pre-publication history for this paper can be accessed here:

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529270

Efficient activation of gene expression using a heat-shock inducible Gal4/Vp16-UAS system in medaka

Background Genetic interference by DNA, mRNA or morpholino injection is a widely used approach to study gene function in developmental biology. However, the lack of temporal control over the activity of interfering molecules often hampers investigation of gene function required during later stages of embryogenesis. To elucidate the roles of genes during embryogenesis a precise temporal control of transgene expression levels in the developing organism is on demand. Results We have generated a transgenic Gal4/Vp16 activator line that is heat-shock inducible, thereby providing a tool to drive the expression of specific effector genes via Gal4/Vp16. Merging the Gal4/Vp16-UAS system with the I-SceI meganuclease and the Sleeping Beauty transposon system allows inducible gene expression in an entirely uniform manner without the need to generate transgenic effector lines. Combination of this system with fluorescent protein reporters furthermore facilitates the direct visualization of transgene expressing cells in live embryos. Conclusion The combinatorial properties of this expression system provide a powerful tool for the analysis of gene function during embryonic and larval development in fish by ectopic expression of gene products.

Background The most widely used strategies to investigate the function of genes in medaka ( Oryzias latipes ) are the analyses of mutants, miss-expression of wild type genes or their variants by mRNA injection and gene specific translational inhibition by morpholino injections [ 1 - 3 ]. However, the phenotype of a given mutation mainly reflects the first temporal function of the affected gene in embryonic development, obscuring possible later functions. Similarly, mRNA and morpholinos exert their functions immediately following injection, providing information only on the early role of the gene of interest. A detailed analysis of gene function in a given process can thus be a difficult task. The Gal4/UAS system provides an alternative and more specific strategy to analyze specific functions of a gene [ 4 , 5 ]. The direct application of the Drosophila Gal4-UAS approach, by the generation of transgenic lines, has been established successfully in zebrafish [ 6 , 7 ]. However, the generation of different transgenic activator and effector lines may be a time- and space-consuming task, and expression levels in these transgenic lines are weak, probably due to a limited transactivation potential of Gal4 in fish. Gal4/Vp16, a fusion of the yeast Gal4 DNA-binding domain with the strong Vp16 transactivation domain of the herpes simplex virus [ 8 ] can be used to enhance transactivation efficacy. Yet, strong transcriptional activators can cause unspecific promoter squelching [ 9 ] resulting in retardation of embryogenesis [ 10 ]. Nonetheless, the Gal4/Vp16-UAS system has been used in zebrafish in transient approaches resulting in mosaic, but easily detectable transgene expression [ 11 ]. We have applied the Gal4/Vp16-UAS system for transient transactivation in a heat-shock inducible transgenic Gal4/Vp16 activator line. Generation of transgenic medaka lines, which allow the induction of the Gal4/Vp16 activator to 'physiological' (i.e. non-toxic) levels was achieved by using a 5' truncated version of the zebrafish heat-shock promoter HSP70 [ 12 ]. Using a heat-shock promoter to drive expression of the Gal4/Vp16 activator allows tight temporal control of activator and effector (reporter) gene expression. To trace transgene expression in cells of living embryos we have used the cyan fluorescent and yellow fluorescent proteins (CFP, YFP). Combination with the meganuclease (MN) transgenesis system [ 13 ] and the direct-inverted repeats (IR/DR) of the Sleeping Beauty (SB) transposon system [ 14 ] yielded high numbers of transgene expressing cells. Thus, in contrast to the entirely mosaic nature of a transient approach reported thus far, the combined use of a transgenic activator line with systems enhancing even DNA distribution or early integration allows uniform expression of injected effector genes upon induction by heat-shock treatment without an immediate need to generate transgenic UAS lines. Results and discussion Generation of a heat-shock inducible transgenic Gal4/Vp16 activator line (pCG6.0WCS/T) DNA injection leading to mosaic expression in G0 allows in vivo tracing of transgene-expressing cells and observation of effects exerted by the transgene through application of fluorescent markers [ 11 ]. However, elucidation of biological questions sometimes requires ubiquitous expression of transgenes in a temporally controlled manner. While the MN protocol strongly reduces mosaicism, it does so only in a fraction of injected embryos ([ 13 ], Fig. 1F,1G,1H,1I,1J,1K and Table 1 ). This can be improved by the use of transgenic animals providing inducible and sufficient expression in all cells. The idea is to combine stable heat-shock inducible expression of the Gal4/Vp16 activator with transient expression of effector genes upon microinjection. The effector constructs are uniformly distributed in the entire embryo due to the presence of the SB direct-inverted repeats [ 15 ]. We have designed two activator/reporter vectors containing Gal4/Vp16 under control of a 1.5 kb fragment of the zebrafish (zf) HSP70 promoter (pCG5.0WCS) or a 0.6 kb 5' truncated fragment of zfHSP70, respectively (pCG6.0WCS). Both vectors contain CFP downstream of several UAS elements as an internal reporter. The IR/DRs of SB and two I-SceI meganuclease sites flank this entire expression cassette (Fig. 1A ). The internal reporter provides a direct read-out for activator expression. A third vector (pCG3.0Y), containing YFP downstream of several UAS elements and flanked by IR/DRs, was designed as an independent reporter (Fig. 1A ). It has been shown that the Gal4/Vp16 activator can interfere with general transcription by titrating the basal transcription machinery [ 16 ]. We observed developmental retardation and malformation in all embryos injected with Gal4/Vp16 driven by ubiquitous promoters. Similarly, co-injection of high concentrations of Gal4/Vp16 mRNA (50 ng/μl) with pCG5.0WCS always resulted in developmental malformations (not shown). However, DNA co-injections did not affect embryonic development in transient experiments when the HSP70 promoter was used to control Gal4/Vp16 expression (Fig. 1B,1B',1F,1G,1H,1I,1J,1K ). Moreover, co-injections of low concentrations of Gal4/Vp16 mRNA (3.5 ng/μl) with the activator/reporter construct pCG5.0WCS also showed no effects on embryogenesis (Fig. 1C,1C' ), suggesting that the toxicity of the activator depends on the expression level. The truncated version of the zfHSP70 promoter fragment used in the activator/reporter construct pCG6.0WCS showed a moderate activation upon heat-shock treatment. This allowed adjusting the induction levels by varying the heat-shock duration. A transgenic medaka line was established (by co-injection of circular vector pCG6.0WCS with MN) in which expression levels directly correlated with the heat-shock duration. Extended heat-shocks resulted in very high expression levels, but also caused retardation phenotypes due to the strong transactivation potential of the Gal4/Vp16 fusion protein. Comparable phenotypes were not observed in heat-shock treated wild type embryos. Depending on the developmental stage at the time of induction, the duration of heat-shock treatment was adjusted to induce Gal4/Vp16 and reporter expression without interfering with embryonic development. Induction periods ranged from one minute of heat-shock at 37°C at early stages (~st16/21hpf) to 10 minutes at later stages (~st22/38hpf). On top of uniform CFP expression in the entire embryo and yolk upon heat-shock, some regions of the embryo showed additional responsiveness of the reporter (Fig. 1E,1E' ). Microinjection experiments and RT-PCR revealed that reporter gene (CFP) expression in transgenic fish is mediated by Gal4/Vp16. Offspring of pCG6.0-WCS/T transgenic fish was injected with Gal4/Vp16 mRNA (3.5 ng/μl) at the one-cell stage without heat-shock treatment. Injected embryos exhibited uniform expression of CFP shortly after the onset of zygotic transcription at the mid-blastula transition [ 17 ], indicating that CFP expression was induced in response to Gal4/Vp16 (Fig. 1D,1D' ). We applied RT-PCR for the dose/response analysis of activator and reporter mRNA (Fig. 2A ). Transcripts of Gal4/Vp16 were detectable already 10 minutes after a heat-shock of 90 seconds at 37°C. Following a steady increase until about three hours after induction, Gal4/Vp16 messages were degraded between five and ten hours to undetectable levels after twenty hours. CFP mRNA was first detected after two hours and transcript levels were still increasing after 25 h. This indicates that the transcription of the reporter CFP is controlled by Gal4/Vp16 protein and that active Gal4/Vp16 is still present when the amount of its transcripts already dropped below detectable levels (Fig. 2A ). Activation of an independent reporter upon injection into the transgenic activator line pCG6.0WCS/T We tested the Gal4/Vp16 activator line pCG6.0WCS/T as a tool to induce expression of an independent reporter upon injection of plasmid DNA (pCG3.0Y). Transgenic embryos were injected with different concentrations of the reporter pCG3.0Y (5–150 ng/μl). Injected embryos were subjected to heat-shock treatment at different developmental stages for various periods of time, kept at 28°C thereafter and monitored for activator and effector expression during the following days. Due to the SB IR/DRs flanking the expression cassette, the independent reporter was distributed equally in the entire embryo resulting in ubiquitous expression of YFP, entirely co-localizing with the internal reporter (CFP). Additional mosaic clones of cells expressing YFP at higher levels presumably reflect higher plasmid concentrations in these cells (Fig. 2B,2C,2D,2E,2F,2G,2H,2I,2J and Table 1 ). However, YFP expression levels appeared relatively independent from the DNA concentration, but were directly correlated to the expression levels of the activator or internal reporter, respectively. Conclusions Here we show that the Gal4/Vp16-UAS transactivation system can be efficiently used in medaka. By using fluorescent proteins as internal or independent reporter, cells co-expressing the activator and the gene of interest can be visualized directly. Transparency of these fish embryos allows the evaluation of the cellular fate and response to ectopically expressed genes by time-lapse analyses. The combination with inducible promoters permits temporal control of effector gene expression and enables the modulation of the response intensity by adjusting the duration of the heat-shock treatment. This inducible system can be used in transient experiments to study the behavior of transgene expressing cells in an otherwise wild type environment. The combination with the MN and SB system offers to tailor a range of different levels of mosaicism (Fig. 1F,1G,1H,1I,1J,1K ). A transgenic Gal4/Vp16 activator line was generated, which provides a powerful tool to induce activator and effector gene expression in a ubiquitous manner at a given time-point (Fig. 1E,1E' ). When used in microinjection approaches of reporter vectors containing IR/DRs, our transgenic activator line allows ubiquitous and uniform expression of the reporter gene without the need to generate transgenic effector (UAS) lines (Fig. 2B,2C,2D,2E,2F,2G,2H,2I,2J ). In addition to temporal control mediated by the heat-shock promoter, induction using a focused laser-beam [ 12 ] could provide precise spatial control of the effector gene expression. Methods Plasmids pCG3.0Y A YFP/SV40pA cassette was cloned downstream of a 4xUAS/dHSP70 element (non responsive to heat-shock; kind gift of M. Gonzalez-Gaitan). This entire cassette was cloned into pCG1.1 containing the IR/DR sequences of the SB transposable element [ 14 ] resulting in a 5.1 kb plasmid containing the reporter cassette (4xUAS/dHSP70/YFP/SV40pA) and the pBSII backbone flanked by a left and right IR/DR of SB (Fig. 1 ). pCG5.0WCS A 1.5 kb zebrafish HSP70 promoter fragment [ 12 ] was subcloned upstream of Gal4/Vp16/SV40pA. The entire cassette was further subcloned into pCG3.0C (containing CFP instead of YFP, see above) resulting in a 8.7 kb plasmid (pCG5.0C) containing the expression cassettes zfHSP70/Gal4/Vp16/SV40pA followed by 4xUAS/CFP/SV40pA flanked by the IR/DRs of SB. Finally, the expression cassettes including the inverted repeats were cloned into a I-SceI backbone vector [ 13 ] and verified by sequencing (Fig. 1 ). pCG6.0WCS The 1.5 kb zfHSP70 promoter fragment in pCG5.0WCS was replaced by a truncated zfHSP70 promoter fragment lacking 900 bp 5' to the internal BamHI site resulting in a 7.8 kb plasmid that was verified by sequencing (Fig. 1 ). Further structural details of the activator and reporter vectors are available upon request. pCGGal4/Vp16 A Gal4/Vp16 fusion construct (Gal4 DNA binding domain: amino acids (aa) 1–147 and Vp16 transactivation domain: aa 411–491) was designed from Clontech vectors pM (Gal4) and pM3-VP16 (Vp16) and cloned into pCS2+ [ 18 ]. Gal4/Vp16 mRNA was transcribed in vitro from pCGGal4/Vp16 using the mMessage mMachine kit (Ambion Inc.). Microinjection and heat-shock treatment of medaka embryos For microinjections, one-cell stage embryos of the Cab inbred strain were used. Microinjection capillaries were backfilled with the injection solution [DNA (5–150 ng/μl); Yamamoto buffer (1×) or DNA (5 ng/μl); Yamamoto buffer (0.5×); I-SceI buffer (0.5×, New England Biolabs); I-SceI meganuclease (0.35 u/μl, New England Biolabs) with or without Gal4/Vp16 mRNA (3.5–50 ng/μl)]. DNA was prepared using a Qiagen Maxiprep kit (Qiagen, USA) and dialyzed using nitrocellulose filters (#VSW01300; Millipore, USA). DNA was injected through the chorion into the cytoplasm of one-cell stage embryos. Heat-shock treatment was performed in small volumes (100–200 μl) using a waterbath at 37°C. Animals used in the study were kept according to national and international ethical provisions for animal husbandry as implemented at EMBL. Microscopy Embryos were observed and scored using a MZFLIII dissecting microscope with a 436/20 nm (EF); 480/40 nm (BF) filter set for CFP, a 510/20 nm (EF); 560/40 nm (BF) filter set for YFP and a 360/40 nm (EF); 420 nm (BF) filter set for UV/Brightfield. The stereomicroscope was equipped with a DC500 digital camera for imaging (Leica Microsystems, Germany). RNA isolation and RT-PCR Transgenic embryos were heat-shocked and subsequently kept at 28°C to recover for different periods of time. Total RNA was isolated from individual embryos as described [ 19 ]. Total RNA was subjected to reverse transcription (SuperscriptII, Gibco-BRL) using a mixture of random hexamer primers (25 μM, Amersham) and gene specific oligomeres for Gal4/Vp16 (25 μM; 5'-CCACGTCCAAAGCCCCATAC-3') and CFP (25 μM; 5'-GTTCATCCATGCCATGTGTAATCCC-3') in a 20 μl reaction. 2 μl of each RT reaction was used for PCR in a 50 μl reaction. The primer pairs used were Gal4/Vp16up2 (5'-GATAATGTGAATAAAGATGCCGTCA-3') and Gal4/Vp16low2 (5'-CCACGTCCAAAGCCCCATAC-3') to amplify a 420 bp fragment, and CFPup2 (5'-TCAAGGAGGACGGCAACATC-3') and CFPlow2 (5'-GTTCATCCATGCCATGTGTAATCCC-3') to amplify a 320 bp fragment. Amplification of a 580 bp fragment of c-actin was used as an internal control using the intron-spanning primer pair c-actinup2 (5'-GCCGCGACCTTACAGACTACCT-3') and c-actinlow2 (5'-CTGTTTAGAAGCATTTGCGGTGGAC-3'). An initial 1 min. denaturation step at 95°C was followed by an additional denaturation step for 30 sec. at 95°C, annealing for 30 sec. at 60°C and elongation at 72°C for 30 sec. The program was repeated for 30 cycles followed by a final extension step for 5 min. at 72°C. Authors' contributions CG designed and performed all experiments and drafted the manuscript. JW conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.

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549584

Can Blood Gene Expression Predict Which Patients with Multiple Sclerosis Will Respond to Interferon?

Gene expression patterns from peripheral blood cells may be useful as biomarkers for monitoring MS progression and response to therapy, argue Kaminski and Achiron

Despite the significant progress in increasing our understanding of the immune mechanisms of multiple sclerosis (MS), in improving clinical classification and brain imaging, and in developing new treatments, the factors that determine the course of the disease are mostly unknown [ 1 ]. Currently, it is nearly impossible to predict the course of MS, its severity in terms of disability progression, or when a relapse will happen. The most commonly used disease-modifying therapies are interferon β (IFNβ) [ 2 ] and glatiramer acetate [ 2 , 3 ]. Despite initial excitement, these therapies have beneficial effects in some, but not all, patients [ 2 , 3 ]. Because of the potential favorable effects of these therapies, it has been suggested that they should be initiated as early as possible to maximize neuroprotection [ 4 ]. Additionally, it has been recommended that patients should be monitored closely to determine whether and when it is necessary to modify treatment in order to maximize the benefit [ 5 ]. The recommended monitoring is based on annual rate of relapses, neurological deterioration, and evidence of disease activity on brain magnetic resonance imaging scans. However, given the destructive nature of the disease, if we rely solely on clinical or radiological manifestations (such as a relapse or a new lesion on a scan) to determine a patient's response to therapy, we will probably be responding too late. Gene Expression Patterns in Affected Organs The diagnosis and management of disease could be transformed thanks to the completion of the human genome project, the availability of sequence information for nearly every gene, and the advent of novel high throughput technologies (microarrays—see Glossary ) that allow parallel profiling of thousands of genes. By definition, nearly every aspect of a disease phenotype should be represented in gene expression signatures of multiple genes in the affected organ. Indeed, studies that analyze affected tissues (mostly in cancer) clearly show that it is possible to predict prognosis, to identify new classes of diseases, and potentially to determine response to therapy [ 6 , 7 , 8 ]. Glossary cDNA arrays: Microarrays in which the gene detectors are pieces of cDNA. Cross-validation: A method by which an available sample is split into learning and testing sets to test classifiers. Gene expression signature: Statistically significant changes in the expression of multiple genes that characterize (classify) a biological state. Glatiramer acetate: A synthetic protein made of four amino acids found in myelin. It is used as an immunomodulator drug in treating MS. IFNβ: A cytokine that is secreted from fibroblasts in response to stimulation by a live or inactivated virus or by double-stranded RNA. It is used as an immunomodulator drug in treating MS. Microarray: A technology that allows the simultaneous profiling of the expression of thousands of genes (even whole genomes). Multiple gene detectors (oligonucleotides or cDNAs) are deposited on a slide that is hybridized with fluorescently labeled samples. PCR (polymerase chain reaction): The exponential amplification of a DNA fragment using repeated activation of a heat-stable DNA polymerase. Real-time PCR (also called one-step kinetic RT-PCR): A method in which the quantitation of the products of PCR is made by measuring fluorescent emission. It is used for accurate quantitation of mRNA. RT-PCR (reverse transcription–polymerase chain reaction): PCR that is performed on cDNA generated from RNA. It is used for mRNA detection and quantitation. Supervised classification: A process in which classifiers are learned from user-defined groups (classes). Unsupervised classification: A process in which classifiers are learned without user-defined groups (classes), i.e., without a predefined training set. In diseases that do not require tissue resection for diagnosis or therapy, it is rare to obtain tissues for analysis. This problem is even more pronounced in diseases like MS, in which the target organ is the very inaccessible brain and spinal cord. Despite these limitations, several groups used microarrays to analyze brain tissues obtained posthumously from patients who had MS and identified genes that characterized either acute or chronic lesions [ 9 , 10 , 11 ]. However, although these studies identified some potential genes that may be involved in the local pathogenesis of the disease, they did not produce any information that could be used for identifying biomarkers associated with disease activity. Diagnostic Peripheral Blood Mononuclear Cell Gene Expression Signatures In MS, looking for markers of disease activity in the much more accessible peripheral blood does not require a significant leap of faith. MS is an autoimmune disease, and it is possible that some of the cells involved in the pathogenesis of the disease will be found in the bloodstream. Abnormal T cell populations have repeatedly been observed in the peripheral blood of patients with MS [ 12 , 13 , 14 ]. While these results supported looking at the easily accessible peripheral blood mononuclear cells (PBMCs) for potential markers that reflect the disease, some doubts persisted. These revolved around two very strong arguments. The first argument was that if the signal comes from a minority of the cells within the bloodstream it will be too low to be detected. The second was that interpersonal variability, added to the inherent noisy nature of gene expression data, will make the data impossible to reproduce. Fortunately, recent observations suggest that these doubts are unfounded. Bomprezzi et al. [ 15 ] determined that gene expression patterns can distinguish patients with MS from controls and suggested that at least some of the differences identified were derived from activated T cells. Achiron et al. [ 16 ] analyzed the expression of 12,000 genes in patients with relapsing–remitting MS. Gene expression patterns clearly distinguished patients with MS from controls as well as relapse from remission. Mandel et al. [ 17 ] compared patients with systemic lupus erythematosus and MS, and identified a common autoimmunity signature as well as disease-specific gene expression signatures. Interestingly, similar findings were recently described for pulmonary arterial hypertension [ 18 ]. Could PBMC Gene Expression Signatures Be Used for Predicting Response to Therapy? Weinstock-Guttman et al. [ 19 ] analyzed the acute transcriptional response of 4,000 genes in peripheral blood lymphocytes to IFNβ. They identified increases in known interferon-inducible genes, and in genes involved in antiviral activity and interferon signaling. Using complementary DNA (cDNA) arrays, Sturzebecher et al. [ 20 ] identified gene expression signatures that distinguished IFNβ responders from nonresponders. And now, in a new study published in last month's PLoS Biology , Baranzini et al. [ 21 ] provide compelling evidence that these PBMC gene expression signatures can be used to predict response to therapy ( Figure 1 ). They studied the expression of 70 genes selected for their presumed biological function in 52 patients with MS, followed up for at least two years after initiation of IFNβ therapy. Instead of using microarrays that carry probes for thousands of genes, they chose to use real-time PCR. This method is highly sensitive, specific, and reproducible across different laboratories. It is often used to verify microarray findings. Baranzini et al. identified MX1 (interferon-inducible protein p78), a known interferon-inducible gene, as the marker of treatment with IFNβ. They did not find overall differences between responders and nonresponders, but they did, using supervised classification methods, identify triplets of genes that distinguish IFNβ responders and nonresponders. Figure 1 Expression Levels of Three Genes in Patients Who Responded (Red) and Who Did Not Respond (Blue) to IFNβ (Source: [ 21 ]) Interestingly, individual and pairs of genes did not perform that well, and all three genes in a triplet were required for the highest accuracy (about 80%–90%). The minimal combinatorial number of genes that contains the most predictive information is not available since combinations of more than three genes were not performed. Although the results were not tested on an independent dataset, as is frequently requested [ 22 ], the authors applied an array of cross-validation strategies that convincingly suggested that the identified predictive signal was robust. Implications of the Study What could Baranzini and colleagues' findings mean? Clearly, the most obvious conclusion is that the lack of response did not result from the deactivation of IFNβ. The effect of IFNβ on MX1, IFNAr1, and STAT2 was observed for two years in all patients, suggesting that the response did not depend on IFNβ bioavailability. Considering that PBMCs represent an admixture of multiple cell types, the most plausible explanation is a simple lack of shift in subcellular populations. However, the importance of Baranzini and colleagues' study lies not in its mechanistic insights, but in its clinical relevance. The careful design of the experiment, the use of reproducible real-time PCR instead of microarrays, the meticulous analysis, and the previous observations [ 15 , 16 , 17 , 19 , 20 ] support the notion that PBMCs express clinically relevant gene expression signatures in MS and probably in other organ-confined diseases. To further prove this notion will require a significant investment in large studies that prospectively test the utility of these signatures in guiding the management of MS. Only when direct evidence shows that therapy guided by markers expressed in PBMCs improves patient outcome will PBMC gene expression patterns take their place as biomarkers at the center stage of monitoring MS progression and response to therapy.

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Calcium Dynamics of Cortical Astrocytic Networks In Vivo

Large and long-lasting cytosolic calcium surges in astrocytes have been described in cultured cells and acute slice preparations. The mechanisms that give rise to these calcium events have been extensively studied in vitro. However, their existence and functions in the intact brain are unknown. We have topically applied Fluo-4 AM on the cerebral cortex of anesthetized rats, and imaged cytosolic calcium fluctuation in astrocyte populations of superficial cortical layers in vivo, using two-photon laser scanning microscopy. Spontaneous [Ca 2+ ] i events in individual astrocytes were similar to those observed in vitro. Coordination of [Ca 2+ ] i events among astrocytes was indicated by the broad cross-correlograms. Increased neuronal discharge was associated with increased astrocytic [Ca 2+ ] i activity in individual cells and a robust coordination of [Ca 2+ ] i signals in neighboring astrocytes. These findings indicate potential neuron–glia communication in the intact brain.

Introduction Astrocytes are nonneuronal cells of the brain with some known and hypothesized functions (Kettenmann and Ransom 1995; Fields and Stevens-Graham 2002 ). Traditionally, astrocytes have been considered to mediate supportive and protective functions in the central nervous system because of their strategic placement relative to the vasculature, and because they lack fast sodium action potentials. It is only recently that this family of glial cells has been implicated in controlling the dynamics of the neuronal networks in the central nervous system ( Nedergaard 1994 ; Parpura et al. 1994 ; Kang et al. 1998 ; Parri et al. 2001 ). Although the membrane potential of unidentified glial cells shows correlated changes with neuronal activity in vivo ( Amzica and Steriade 2000 ; Amzica and Massimini 2002 ), most of our knowledge on neuron–glia and glia–glia communication comes from studies in vitro. In cultured and acutely prepared astrocytes, free calcium concentration ([Ca 2+ ] i ) in the cytosol undergoes large changes spontaneously or in response to various physiological and pharmacological manipulations, such as mechanical stimulation, membrane potential depolarization, and activation of metabotropic glutamate receptors ( Cornell-Bell et al. 1990a ; Pasti et al. 1997 ). These slow events are mediated by release of Ca 2+ from intracellular stores ( Charles et al. 1993 ; Venance et al. 1997 ). The [Ca 2+ ] i surges can be evoked by strong neuronal activity ( Dani et al. 1992 ; Porter and McCarthy 1996 ), suggesting a potential homeostatic role of astrocytes in the regulation of extracellularly accumulating neurotransmitters ( Verkhratsky et al. 1998 ). Conversely, spontaneous [Ca 2+ ] i changes in astrocytes have been shown to influence neuronal excitability ( Parpura et al. 1994 ; Kang et al. 1998 ; Pasti et al. 2001 ). The mechanism of activity propagation among astrocytes is controversial. In tissue cultures, [Ca 2+ ] i events can propagate among a network of astrocytes via gap junction or by elevation of adenosine triphosphate level ( Cornell-Bell et al. 1990b ; Charles et al. 1991 ; Nedergaard 1994 ; Reetz et al. 1997 ; Newman 2001 ). In the in vitro slice preparation, coordination of [Ca 2+ ] i activity appears independent of gap junctions but may require transmitter activation of N-methyl-D-aspartic acid (NMDA) and/or metabotropic glutamate receptors ( Parri et al. 2001 ; Aguado et al. 2002 ; Nett et al. 2002; Tashiro et al. 2002 ). Moreover, the extent and magnitude of these network effects vary as a function of the preparation used, and can involve correlated [Ca 2+ ] i changes in no, or only a few, neighboring astrocytes, or the whole population ( Porter and McCarthy 1996 ; Verkhratsky et al. 1998 ). Whether and how the observations in the various in vitro situations apply to the intact brain have yet to be determined. We have used two-photon laser scanning microscopy (2-PLSM) to monitor cytosolic Ca 2+ concentration in astrocytes labeled with Fluo-4 acetoxymethyl (AM) ester in juvenile rats in vivo. We find that [Ca 2+ ] i dynamics in astrocytes is rather quiescent during baseline anesthesia. However, increased population bursting, brought about by attenuating γ-aminobutyric acid (GABA A ) receptor-mediated neurotransmission, leads to increased magnitude [Ca 2+ ] i surges, and the [Ca 2+ ] i changes become more strongly coordinated in neighboring astrocytes. Results Loading of Calcium-Sensitive Dye To examine the depth of penetration of the Fluo-4 AM, coronal brain slices (300 μm thick) were acutely prepared after the residual dye was washed off from the craniotomy. A large number of cells below the craniotomy showed fluorescence labeling ( Figure 1 ). On the basis of morphological appearance (see also Videos S1-S4 ), most brightly labeled cells were astrocytes, in accordance with recent observations using a pressure application of the indicator ( Stosiek et al. 2003 ). The large overlap between Fluo-4 AM-loaded cells and astrocytes identified by S100B immunoreactivity provided confidence that most of the loaded cells were astrocytes ( Video S5 ). In addition to astrocytes, capillary endothelial cells and pericytes, outlining microvessels, were also observed, albeit less regularly. Some processes of astrocytes contacted local vessels. To quantify the dye penetration, mean bulk fluorescence intensity was plotted for different depths from the pial surface. Most intensive labeling occurred between 50–150 μm below the surface (i.e., layers I/II), but labeled cells could be visualized at greater than 300 μm as well ( Figure 1 C). The decreased fluorescence on the surface is likely due to the diluting effect of the washout procedure in the superficial tissue. Like the histological appearance, in vivo imaging revealed numerous astrocytes ( Figure 1 E). Although the labeling was dense, the somata and several associated processes, including vessel-contacting end feet, of single astrocytes could be clearly revealed ( Figure 2 ). Figure 1 In Vivo Loading and Imaging of Astrocytes Using Fluo-4 AM (A) Acute slice prepared 1 h after dye loading. Scale bar, 200 μm. (B) Higher magnification reveals cells with typical astrocyte morphology. Scale bar, 20 μm. (C) Average bulk fluorescence as a function of the depth from the pial surface. (D) Schematic drawing of the experimental arrangement. Abbreviations: EKG, electrocardiogram. PMT, photomultiplier. LFP, glass micropipe for local field potential and multiple unit recording. The same pipette was used to deliver bicuculline. (E) Image taken 50–150 μm below pial surface in vivo. Flattened xyz stack. (F) Fluo-4 AM loaded cells (left) were stained for S100B immunoreactivity (right), and the images were merged (center). See Video S3 for large-scale staining. Scale bar, 20 μm. Figure 2 Time-Lapse Imaging of Astrocytes In Vivo Four astrocytes, from which fluorometric Ca 2+ imaging (0.5 Hz) was made, are outlined. A blood vessel, outlined by the astrocyte end feet, runs diagonally across the viewed area. White arrows show the end foot connected to the imaged astrocyte. Spontaneous Calcium Events in Astrocytes In our initial experiments, we made a large number of line scans (sampling rate ∼200 Hz) of dye-loaded cells to examine whether some of them were neurons. We never observed short-lasting [Ca 2+ ] i transients (less than 200 ms; Svoboda et al. 1997 ; Garaschuk et al. 2000 ), suggesting that the brightly loaded cells were likely to be non-neuronal ( Parri et al. 2001 ; Stosiek et al. 2003 ). In subsequent experiments ( n = 8 rats), cells with astrocytic appearance ( n = 185) were selected for long-term (10–20 min) monitoring. For quantitative studies, three states of [Ca 2+ ] i activity were distinguished: (a) quiescent state with very slow (less than 0.025 Hz) oscillations of baseline fluorescence level, (b) [Ca 2+ ] i spikes (greater than or equal to 20% increase in ΔF/F 0 between 5–50 s), and (c) [Ca 2+ ] i plateau potentials (greater than or equal to 20% increase in ΔF/F 0 for greater than 50 s). [Ca 2+ ] i spikes and [Ca 2+ ] i plateau potentials were automatically detected. In the control (baseline) condition, 11% of astrocytes had at least one spike event, and 52% had at least one plateau event in 10 min. The mean frequency of [Ca 2+ ] i spikes among the cells that had at least one [Ca 2+ ] i spike was 0.121 ± 0.098 per minute (mean width at greater than or equal to 20% ΔF/F 0 : 25.1 ± 10.31 s) and the mean frequency of [Ca 2+ ] i plateau was 0.118 ± 0.058 per minute (mean duration: 160.4 ± 114.9 s). To investigate whether the baseline values of [Ca 2+ ] i dynamics were affected by increasing neuronal activity, we induced regularly occurring population bursts by local application of bicuculline ( Schwartz and Bonhoeffer 2001 ; n = 7 rats). Large amplitude (0.69 ± 0.26 mV) synchronous field events (approximately 100 ms) occurred at relatively regular frequency (0.15 ± 0.06 Hz), associated with multiple unit discharges. No significant difference was observed in average heartbeat frequency between the control sessions and bicuculline sessions (4.51 ± 0.54 Hz and 4.36 ± 0.74 Hz, respectively; paired t-test, p = 0.13). We used two methods to evaluate the effect of neuronal activity on [Ca 2+ ] i in astrocytes ( n = 214 cells). First, the incidence of [Ca 2+ ] i spikes and plateau events was counted in the absence and presence of bicuculline-induced population bursts. Under bicuculline condition significantly more astrocytes had [Ca 2+ ] i spikes (11% versus 24%; p < 0.001; Fisher's exact test), whereas the probability (52% versus 54%) of plateau potentials did not differ significantly. The mean duration of plateau potentials, however, was significantly longer (160.4 ± 114.9 s versus 211.12 ± 152.175 s; t-test, p < 0.001) after bicuculline treatment. Among the cells that exhibited at least one spike or plateau event, there was not a significant difference in frequency of the event occurrences (spike: 0.121 ± 0.098/min versus 0.098 ± 0.068/min; t-test, p = 0.24; plateau 0.118 ± 0.058/min versus 0.112 ± 0.049/min; t-test, p = 0.46). Thus, the major difference between control and bicuculline conditions was the higher proportion of active astrocytes under bicuculline. The second method examined [Ca 2+ ] i changes in the frequency domain. The ΔF/F 0 trace was considered as a continuous process, and the power spectrum estimate was calculated with a multi-taper method for each astrocyte and averaged across cells. There was a general increase of power at all frequencies in bicuculline-treated animal. The most consistent significant increase ( p < 0.05) of power appeared in the frequency range of 0.10–0.24Hz, reflecting the increased incidence of [Ca 2+ ] i spikes. Short-term cross-correlation of neuronal field bursts and [Ca 2+ ] i signals (± 10 s) did not show a significant time-locked relationship ( Figure 3 ). Figure 3 Frequency Domain Analysis of Population Dynamics of Fluorescence in Astrocytes in Control State and during Bicuculline-Induced Neuronal Hyperactivity Insets show local field potentials in a control animal and regular spiking in a bicuculline treated mouse (scale bar: 2.0 s, 500 μV). Asterisks show significant differences ( p < 0.05) between groups at various frequencies. Spatio-Temporal Dynamics of [Ca 2+ ] i Events In individual experiments, propagation of synchronous activity could be observed visually ( Figure 4 A; Video S6 ) but the spatio-temporal relationship of [Ca 2+ ] i dynamics among astrocytes varied across experiments. To quantify the magnitude and spatial extent of this population effect, pair-wise cross-correlograms of ΔF/F 0 intensity were calculated separately for nearby cell pairs (local: less than or equal to 50 μm) and distant cell pairs (greater than 50 μm). In control conditions, the temporal correlation of [Ca 2+ ] i signals in neighboring pairs was somewhat larger than in distant pairs, but this difference was not significant ( n = 374 neighbor pairs and n = 1,138 distant pairs). Nevertheless, [Ca 2+ ] i signals in astrocytes were not completely random, since the cross-correlograms had wide central peaks at the 10–100 s scale ( Figure 4 B). In contrast to the baseline condition, the temporal correlation of [Ca 2+ ] i changes in local and distant pairs were significantly different after large population bursts were brought about by bicuculline ( Figure 4 C). Correlation of distant pairs under bicuculline ( n = 433 pairs) was similar to those in the control condition. However, synchrony between local pairs ( n = 1,282) increased several-fold relative to both distant pairs under the same condition ( t -test, p < 0.0001) and to local pairs in the baseline condition ( t -test, p < 0.0001). Figure 4 Spatio-Temporal Dynamics of Astrocyte Ca 2+ Activity (A) Definition of nearby (less than 50 μm) and distant (greater than 50 μm) cell pairs. (B) Fluorescence changes in two nearby astrocytes. (C) Cross-correlogram of fluorescent intensity. (D) Mean cross-correlation of ΔF/F 0 in all nearby (thick line) and distant (thin line) cell pairs in control condition (left) and in the presence of bicuculline (right). Note large increase of ΔF/F 0 correlation in nearby cell pairs in the bicuculline condition (error bar: standard error of the mean). (E) Relationship between distance of the two cells and the magnitude of correlation at zero timelag. Note lack of a reliable relationship in the control condition (left). Note also the significant negative correlation between the distance and correlated ΔF/F 0 changes in cell pairs in the bicuculline-treated cortex (right). Using a different approach, the magnitude of the zero-timelag correlation coefficient for each cell pair was plotted against distance between the cell pairs. Under control condition, no notable relationship was observed between these variables ( Figure 5 ; n = 1,512 cell pairs, r = 0.019, p = 0.46). In contrast, a significant negative correlation was found between the synchrony of [Ca 2+ ] i signals in the bicuculline condition ( n = 1,715; r = −0.281; p < 0.0001). Discussion Astrocytes in superficial cortical layers were successfully loaded using Fluo-4 AM by surface application up to 350 μm from the pial surface in juvenile rats. In agreement with previous literature ( Parri et al. 2001 ; Dallwig and Deitmer 2002 ; Simard et al. 2003 ), the majority of the Fluo-4-loaded cells exhibited astrocytic morphology with multipolar branching and bushy microprocesses impinging on local vasculature. 2-PLSM imaging revealed spontaneous [Ca 2+ ] i events in individual astrocytes in vivo. Some coordination of these events was indicated by the broad cross-correlograms in the baseline condition. Increased neuronal discharge was associated with increased astrocytic activity and a robust coordination of [Ca 2+ ] i signals in neighboring astrocytes, providing evidence for neuron–glia communication in the intact brain. The magnitude, frequency and pattern of [Ca 2+ ] i events observed here are qualitatively similar to those described in tissue cultures ( Dani et al. 1992 ; Charles 1998 ) and acute hippocampal, neocortical, and thalamic slice preparations ( Parri et al. 2001 ; Aguado et al. 2002 ; Nett et al. 2002; Tashiro et al. 2002 ). It has been reported that the percentage of active astrocytes in brain slices showed a 2- to 3-fold decrease from early postnatal days to juvenile age ( Parri et al. 2001 ; Aguado et al. 2002 ). In our experiments, a large portion of the imaged astrocytes were active, showing either [Ca 2+ ] i or plateau potentials. It is unlikely that the elevated activity in vivo is due to anesthesia because urethane is known to suppress transmitter release from presynaptic vesicles and attenuate both α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) and NMDA receptors ( Hara and Harris 2002 ). Since blockade of these receptors decreases astrocytic [Ca 2+ ] i activity in vitro ( Parri et al. 2001 ; Aguado et al. 2002 ), it is expected that in the drug-free animal the percentage of active cells will be even higher. A different explanation for the lower percentage of active astrocytes in the slice, relative to the in vivo situation and tissue culture preparation, is that the trauma of brain slicing attenuates spontaneous [Ca 2+ ] i activity. Reactive astrocytes in a stab wound area show very limited [Ca 2+ ] i activity ( Aguado et al. 2002 ). In addition, the temperature at which the cells are kept may be playing an important role. In the absence of provoking conditions, spontaneous [Ca 2+ ] i activity in individual astrocytes does not spread among astrocytes as an intercellular Ca 2+ wave ( Nett et al. 2002). In baseline condition, the magnitude of correlated activity in nearby and distant astrocytes was quite similar. Nevertheless, the presence of zero-timelag correlation suggests that activity in the astrocytic syncytium in vivo is not random, but is under some coordinated control. Widespread but limited coordination of glial cells can be brought about by common synchronizing inputs in the intact brain, such as vascular and vegetative nervous system control or large-scale slow changes of neuronal excitability. The latter possibility is supported by the observation that ionotropic glutamate receptor antagonists and tetrodotoxin effectively decorrelated the astrocytic network without altering the number of active astrocytes ( Aguado et al. 2002 ). Furthermore, the intact corticothalamic system displays substantial excitability fluctuation at the time scale of the astrocytic [Ca 2+ ] i events ( Jando et al. 1995 ). Although neuronal activity is not needed to generate [Ca 2+ ] i surges in astrocytes ( Aguado et al. 2002 ; Nett et al. 2002), neurotransmitters can enhance the frequency of such events. The impact of neuronal activity on the glial network is illustrated by the increased activity and enhanced local correlation of [Ca 2+ ] i signal in astrocytes after regular population bursting of neurons was brought about by the GABA A -receptor blocker bicuculline. These changes shared similarities to those observed in hippocampal and neocortical slices ( Aguado et al. 2002 ; Tashiro et al. 2002 ). In contrast to the slice situation, we did not find a time-locked triggering of astrocytic events to the neuronal bursts (see also Nett et al. 2002). This discrepancy may be explained by the magnitude of the evoked neuronal bursts. Bicuculline in vitro evoked rare (greater than 30 s intervals), but very large bursts or afterdischarges ( Tashiro et al. 2002 ; Aguado et al. 2002 ). In vivo, synchronous events of moderate size occurred frequently (approximately 0.3 Hz). The enhanced bursts, associated with large field potentials, can be regarded as interictal epileptic spikes ( Schwartz and Bonhoeffer 2001 ), but seizures were never observed. Although the exact mechanisms of neuron–astrocyte signaling remain to be disclosed, our findings indicate that neuronal and glial networks are coupled in the intact brain. Many of the imaged astrocytes had processes (end feet) in close contact with small brain vessels ( Peters et al. 1970 ). It has been shown that surges of [Ca 2+ ] i in astrocytes trigger the release of vasoactive compounds ( Bezzi et al. 1998 ). Furthermore, stimulation of single astrocytes in cortical slices led to delayed (greater than 30 s) and protracted dilation of the contacted arteriole ( Zonta et al. 2003 ). These findings support the view that a cardinal function of astrocytes in the intact brain is to regulate local circulation according to the metabolic needs of neurons. Overall, the approach introduced in this paper will be a potent tool to investigate these issues in vivo. Materials and Methods Subjects and surgery Male and female rats, 12–16 d postnatal (P12– P16), of the Sprague–Dawley strain were used in these experiments. Animals were deeply anesthetized with 1.7 g/kg urethane. An outline of the craniotomy above the primary somatosensory (barrel) cortex was marked with a dental drill. A metal frame, similar to what has been described in Kleinfeld and Denk (2000 ), was attached to the skull with cyanoacrylic. A craniotomy (3–4 mm diameter), centered at 1.5 mm posterior to bregma and 2.5 mm from midline, was performed and the dura mater was surgically removed. Care was taken to avoid any damage to pial vessels or the cortex. Dye loading Fluo-4 AM (F-14201, 50 μg; Molecular Probes, Eugene, Oregon, United States) was mixed with 2 μl of Pluronic (P-3000, Molecular Probes) and 5 μl of dymethyl sulfoxide (D-8779; Sigma, St. Louis, Missouri, United States) for 15 min. The solution was then diluted in 18 μl of artificial cerebrospinal fluid (ACSF) (125 mM NaCl, 3 mM KCl, 10 mM glucose, 26 mM NaHCO 3 , 1.1 mM NaH 2 PO 4 , 2 mM CaCl 2 , 1 mM MgSO 4 ; pH adjusted to 7.4) and mixed for a further 15 min. A small volume (up to 12 μl) of the dye-containing solution was applied to the cortical surface by a micropipette. The solution was retained in place by a small piece gelfoam. The unbound dye was removed 45–60 min after the surface application of Fluo-4 AM by irrigating the exposed surface with ACSF for at least 10 min. The craniotomy was then covered with 1% agar dissolved in phosphate-buffered saline (pH 7.4), and a glass coverslip was placed on a metal frame. This arrangement allowed access for a glass recording electrode from the side. Juvenile rats (P13–P15) were used because we found in preliminary experiments that in adult animals, mostly vascular cells were loaded with the current protocol. Electrophysiological recording During the recording session, a heating blanket was placed under the rat to maintain body temperature at approximately 37°C. The electrocardiogram (EKG) was monitored continuously. The R wave of EKG was used to monitor brain pulsation-derived movement of artifacts during imaging. Population bursts of cortical neurons (“interictal” spikes; Schwartz and Bonhoeffer 2001 ) were induced by inserting a large-tip (20–50 μm tip diameter) glass pipette, containing 2 mM bicuculline in 0.9% (w/v) NaCl, into the deep layers of the somatosensory cortex. This electrode also served to record local field potential and multiple unit activity. Large population bursts were reliably induced 10–30 min after the insertion of the pipette. Imaging A custom-made 2-PLSM was constructed as described earlier ( Majewska et al. 2000 ). In brief, a Ti:S laser (Mira 800F; Coherent, Santa Clara, California, United States) was pumped by a solid state CW laser (Verdi 8; Coherent) to produce a mode-locked beam (840 nm; approximately 100 fs pulse width at 76 MHz repetition rate). The beam was directed to a modified confocal scanhead (Fluoview 300; Olympus, Tokyo, Japan). The fluorescent signal was first filtered with an emission filter (HQ525, passband 525 ± 25 nm; Chroma, Rockingham, Vermont, United States) and detected by an external photo-multiplier tube (R-3896, Hamamatsu Photonics, Hamamatsu City, Japan) with a built-in preamplifier board (F-5 PSU-B; Olympus). Data analysis Fluorescence signal was quantified by measuring the mean pixel value of a manually selected somatic area for each frame of the image stack using ImageJ software. The values were exported to MatLab and the fluorescence change ΔF/F 0 was computed, where F 0 is the mean of the lowest 20% of the somatic fluorescence signals. Sessions that had visible drifts when image sequences were replayed as animation (the majority of the cells showed correlated activity [ |r| > 0.6], or greater than 10% fluorescence change due to the heartbeat when the cell was imaged in line scan [approximately 200 Hz]) were excluded from the analysis. For display purposes, the signal was convolved with a Hanning window of order three to smooth the signal trace. Power spectra of fluorescent signals were computed using the multi-taper method (NW = 4) . For the calcium event detection, ΔF/F 0 signal was convolved with a Hanning window of order 15. “Spike” events were defined as transient increase of ΔF/F 0 signal exceeding 20%, lasting 5–50 s. “Plateau” events were defined as sustained increase of ΔF/F 0 (greater than 20%) signal longer than 50 s. Peak amplitudes of both spike and plateau events required an increase of at least 50% ΔF/F 0 from the onset of events. Calcium events were automatically detected with the above detection. Cross-correlation between cell pairs was computed by normalizing the ΔF/F 0 signals to unity (zero mean, unity standard deviation) so that the computed values represent the correlation coefficient between the two signals at a given timelag. All numbers are indicated as mean ± standard deviation, unless otherwise noted. Immunocytochemisty Since Fluo-4 AM loading was best visible in the somatic region of the putative astrocytes, we chose S100B antibody (A5110; DakoCytomation, Glostrup, Denmark) because this antibody stains the somatic region of astrocytes as well as its processes ( Ren et al. 1992 ). Following Fluo-4 AM loading, acute brain slices (300 μm thickness) were cut coronally around the dye-loaded area using standard procedures. Fluo-4 in cells of the acute brain slices were fixed by incubating the acute brain slices in freshly made saline containing 40 mg/ml 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide hydrochloride (EDAC, E7750; Sigma) for 30 min. Next, the slices were incubated in formalin-based fixative (4% formaldehyde, 0.1 M phosphate buffer, [pH ∼7.1]) for 30 min. Once the fixation procedures were completed, the sections were mounted on a glass slide and imaged with 2-PLSM (z-stack; wavelength, 840 nm). After imaging of calcium-loaded cells, and three subsequent washes in phosphate-buffered saline (PBS) (1.06 mM KH 2 PO 4 , 155.17 mM NaCl, 2.96 mM NaHPO 4 , pH approximately 7.4), the slices were treated with S100B antibody (made in rabbit, 1:50 dilution) in Triton X-PBS (0.5% Triton X in PBS) overnight. The sections were subsequently washed three times in PBS, followed by incubation with the secondary fluorescent antibody (1:1000 dilution, 711-166-152, CY3 Anti-Rabbit IgG [H + L]; Jackson ImmunoResearch Laboratories, West Grove, Pennsylvania, United States) in Triton X-PBS solution for 2 h. Simultaneous viewing of the two image stacks allowed a systematic comparison of the extent of overlap between Fluo-4 loading and S100B immunoreactivity ( Video S5 ). Supporting Information Video S1 Visualization of Loaded Astrocytes (Low Magnification) The primary somatosensory cortex (P15) was stained with Fluo-4 AM in vivo and subsequently imaged in vitro. Acute slices (approximately 300 μm thickness) were cut in cold ACSF after the cells were loaded in vivo. (Z step = 1 μm; scale bar = 50 μm). (49 MB AVI). Click here for additional data file. Video S2 Visualization of Loaded Astrocytes (High Magnification, Layer I) Same slice as shown in Videos S1 , but with higher magnification. Z step = 1 μm; scale bar = 20 μm. (48 MB AVI). Click here for additional data file. Video S3 Visualization of Loaded Astrocytes (High Magnification, Layers II/III) Detailed imaging of in vivo-loaded acute slice preparation of the primary somatosensory cortex (P15; approximately 270 μm below the pial surface). Z step = 1 μm; scale bar = 20 μm. (39 MB AVI). Click here for additional data file. Video S4 High-Contrast Image Upper Layers (I to II/III) of the Fluo-4 AM-Loaded Somatosensory Cortex (P15) Empty circles in layers II/III, presumed unloaded neurons (note their absence in layer I). The loaded cells have typical glial morphological appearance. Z step = 1 μm; scale bar = 50 μm. (50 MB AVI). Click here for additional data file. Video S5 Double-Labeling of Fluo-4 AM-Loaded Astrocytes with S100B Antibody Acute slices (300 μm thickness) were prepared from the in vivo Fluo-4 AM-loaded somatosensory cortex. The slices were subsequently incubated in EDAC containing saline followed by formalin fixation. The loaded astrocytes were identified by examination at various depths and numbered (left). Next, the slices were processed for immunocytochemistry with astrocyte marker S100B. Depth scans (1 μm between the frames) were taken again to determine immunoreactivity of cells with S100B (right movie). An overlapping set of the cells was identified to be S100B-immunoreactive, indicating that nearly all Fluo-4 AM-loaded cells were astrocytes. (5 MB AVI). Click here for additional data file. Video S6 Imaging of Fluo-4 AM Fluorescence Activity in Astrocytes In Vivo Movie taken from a P14 rat. Image was taken with 2 Hz sampling rate for 10 min and compressed to 36 s for display purposes. Note spatial- and light-emission-stability of the recorded cells. Note also that at frames approximately 9 s and 15 s, two of the astrocytes in the middle display transient increased fluorescence. Scale bar 50 micro μ. (55 MB AVI). Click here for additional data file.

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521176

Endemic Infection of the Amphibian Chytrid Fungus in a Frog Community Post-Decline

The chytrid fungus Batrachochytrium dendrobatidis has been implicated in the decline and extinction of numerous frog species worldwide. In Queensland, Australia, it has been proposed as the cause of the decline or apparent extinction of at least 14 high-elevation rainforest frog species. One of these, Taudactylus eungellensis, disappeared from rainforest streams in Eungella National Park in 1985–1986, but a few remnant populations were subsequently discovered. Here, we report the analysis of B. dendrobatidis infections in toe tips of T. eungellensis and sympatric species collected in a mark-recapture study between 1994 and 1998. This longitudinal study of the fungus in individually marked frogs sheds new light on the effect of this threatening infectious process in field, as distinct from laboratory, conditions. We found a seasonal peak of infection in the cooler months, with no evidence of interannual variation. The overall prevalence of infection was 18% in T. eungellensis and 28% in Litoria wilcoxii/jungguy, a sympatric frog that appeared not to decline in 1985–1986. No infection was found in any of the other sympatric species. Most importantly, we found no consistent evidence of lower survival in T. eungellensis that were infected at the time of first capture, compared with uninfected individuals. These results refute the hypothesis that remnant populations of T. eungellensis recovered after a B. dendrobatidis epidemic because the pathogen had disappeared. They show that populations of T. eungellensis now persist with stable, endemic infections of B. dendrobatidis .

Introduction Increasingly, the amphibian chytrid fungus (Batrachochytrium dendrobatidis) has been implicated as a major contributor to global catastrophic declines in frog populations ( Berger et al. 1998 ; Daszak et al. 1999 , 2003 ). It has been found on frogs in areas where catastrophic declines were reported, it has been shown in the laboratory to be highly pathogenic to some species, and there is pathological evidence to link this fungal parasite to host mortality ( Berger et al. 1998 ). The pathogen may therefore be capable of producing the extremely high mortality observed during declines. However, little information is available on the impact of the fungus on individuals in the field, rather than the laboratory. Furthermore, little has been published on the prevalence of infection among frog populations as a whole, as distinct from the prevalence among morbid frogs only. In addition to data on the prevalence of the pathogen among morbid animals, information on the prevalence of a putative pathogen in the population in general is important to determine the potential effect of the pathogen on the host population ( McCallum and Dobson 1995 ). In Queensland, Australia, there have been extinctions or major declines of at least 14 frog species in undisturbed, high-elevation rainforest streams, commencing in 1979–1981 in the Conondale and Blackall Ranges (26°50′ S, 152°41′ E), followed in 1985–1986 in the Eungella region of the Clarke Range (21°07′ S, 148°29′ E), and, in 1990–1995, in the Wet Tropics bioregion (17°22′ S, 145°49′ E) ( Laurance et al. 1996 ; McDonald and Alford 1999 ). Laurance et al. (1996 , 1997 ) suggested that an epidemic disease was responsible for all these declines, without proposing an agent. Despite the presence of B. dendrobatidis in ill and dead frogs collected from the Big Tableland in the Wet Tropics in 1993, it was not recognised as a pathogenic organism until 1998 ( Berger et al. 1998 ) and was described as a new species of fungus in 1999 ( Longcore et al., 1999 ). B. dendrobatidis has been suggested as the causative agent of many of the east coast Australian declines ( Berger et al. 1999a ), although only the decline at Big Tableland ( McDonald and Alford 1999 ) had direct evidence of an association with the presence of B. dendrobatidis . In this paper, we report the retrospective analysis of B. dendrobatidis infection on toe tips collected between 1994 and 1998 from six species of frogs at Eungella National Park in east-central Queensland, Australia ( Figure 1 ). Declines at this location were particularly catastrophic. Between 1985 and 1986, the Eungella Gastric-Brooding Frog (Rheobatrachus vitellinus) disappeared suddenly from relatively undisturbed rainforest streams, and it is now considered to be extinct ( McDonald 1990 ; Campbell 1999 ; Department of Environment and Heritage 2003). During the same period, the Eungella Torrent Frog (Taudactylus eungellensis) also disappeared, but it was later found to have persisted in a few small populations ( McDonald 1990 ; Couper 1992 ; McNellie and Hero 1994 ; Retallick et al. 1997 ), which are the subject of this paper. A suite of other species that coexisted with R. vitellinus and T. eungellensis showed no evidence of decline. Unfortunately, the extent of infection with B. dendrobatidis in the frog community at Eungella during the period of decline is unknown. The first record of B. dendrobatidis at Eungella was from a moribund frog collected in 1995 ( Berger et al. 1999a ). Figure 1 Location of Study Sites 1, Mount David Creek; 2, Mount William Creek; 3, Dooloomai Falls; 4, Rawson Creek; 5, Picnic Ground Creek; and 6, Tree Fern Creek. Results We detected B. dendrobatidis on 71 (15.0%) of the 474 toes assessed. Four species showed no sign of infection, while we detected infections on 58 (18.4%) of 316 toes of T. eungellensis and 13 (34%) of 47 toes of frogs identified at the time as Litoria lesueuri ( Table 1 ). Recently, the taxonomy of L. lesueuri has been revised ( Donellan and Mahoney, 2004 ), with North Queensland members of the complex being either L. jungguy or L. wilcoxii. From the reported distributions of these species, our “L. lesueuri” may have been either one of the species or even hybrids ( Donnellan and Mahoney, 2004 ; Michael Mahoney, personal communication) These species can be distinguished only with genetic information. We therefore describe them as L. wilcoxii/jungguy for the remainder of this paper. Table 1 Prevalence of Infection of B. dendrobatidis in All Frog Toes Examined Sample sizes are in parentheses. A small number of cases with uncertain diagnoses have been omitted Using a logistic model with season (summer, autumn, winter, and spring), species, and site as predictor variables, we found significant effects of each variable on infection, corrected for the effects of the other variables (for season, the change in deviance [Δdev] = 15.25, df = 3, p = 0.0061; for site, Δdev = 13.56, df = 5, p = 0.02; for species, Δdev = 17.32, df = 5, p = 0.004). The most parsimonious model (i.e., one that minimizes the Akaike Information Criterion [AIC]) included each of these predictors but no interaction terms. Further analysis was concentrated on the two species on which B. dendrobatidis was detected, namely T. eungellensis and L. wilcoxii/jungguy. Infection in T. eungellensis The proportions of frogs that were infected in the three largest populations (at Rawson Creek, Dooloomai Falls, and Tree Fern Creek [ Figure 1 ]) differed significantly among those sites (Δdev = 12.84, df = 2, p = 0.001). A significantly smaller proportion was infected at Rawson Creek (10.5%) than at Dooloomai Falls (26.7%) or Tree Fern Creek (25.0%). There was a marginally significant difference overall in the infection levels among males, females, and subadults (Δdev = 5.9, df = 2, p = 0.052). However, when site was included in the model, any suggestion of a difference in infection level between males, females, or subadults disappeared. When we separated the main T. eungellensis populations, it was apparent that the difference in prevalence between those categories was influenced by the population at Tree Fern Creek, where 46% of males ( n = 13) and no females or subadults were infected ( Table 2 ). When we grouped all sites and times, the estimated overall prevalence of infection was 18.1%. Table 2 Prevalence of Infection of B. dendrobatidis in T. eungellensis by Age/Sex Class and Site, Pooled over Sampling Times Sample sizes are shown in parentheses. A small number of metamorphlings and adult frogs, the sex of which was not recorded, have been excluded At these three sites, levels of infection among T. eungellensis varied significantly among seasons (Δdev = 14.605, df = 3, p = 0.002), but not among years (Δdev = 3.433, df = 3, p = 0.26). Further, there was no evidence that the pattern of seasonal variation in infection changed among years (Δdev = 5.561, df = 6, p = 0.49). Infection was most prevalent (37.8%) during the winter months (1 June to 31 August) and least prevalent (11.3%) during the summer months (1 December to 28/29 February). Comparing the two sites with the largest sample sizes, Dooloomai Falls and Rawson Creek, there was no evidence that they had differing seasonal patterns of infection (Δdev = 5.32, df = 3, p = 0.150), although the level of infection overall was much higher at Dooloomai Falls (log odds ratio = 1.1612, standard error [se] = 0.3586, p = 0.0012). Infection levels were much higher in winter and spring combined than in summer and autumn (log odds ratio = 1.360, se = 0.3589, p = 0.00015), and there was no evidence of infection levels differing between winter and spring or between summer and autumn (Δdev = 1.107, df = 2, p = 0.5). The seasonal changes in infection at the two sites are shown in Figure 2 . Figure 2 Seasonal Patterns of Prevalence of B. dendrobatidis in T. eungellensis Solid circles show the observed prevalence, with binomial 95% confidence limits, in frogs pooled over years and age/sex class. The dashed line shows the prevalence predicted from the best-fitting logistic model. Numbers in brackets above each error bar are the sample sizes. Infection in L. wilcoxii/jungguy B. dendrobatidis was detected in 13 of the 47 L. wilcoxii/jungguy examined, giving an estimated prevalence of 27.7%, with a 95% confidence interval ranging from 15.6% to 42.6%. There was no evidence that prevalence of infection differed among males, females, and subadults (Δdev = 2.32, df = 2, p = 0.31); among sites (Δdev = 0.175, df = 2, p = 0.91); or among seasons (Δdev = 1.44, df = 1, p = 0.7) (each of the above Δdev terms is corrected for the other terms in the model). Comparing the prevalence of infection between L. wilcoxii/jungguy and T. eungellensis was hampered by the fact that prevalence of infection on T. eungellensis differed between sites, and that the sampled populations of the two frog species had largely disjunct distributions. When the data were pooled over all sites, there was insufficient evidence to reject a null hypothesis of equal prevalence in the two species, whether the effects of season were allowed for (Δdev = 0.15, df = 1, p = 0.7) or not (Δdev = 2.09, df = 1, p = 0.15). Influence of Infection on Recapture and Survival Table 3 shows the numbers of L. wilcoxii/jungguy and T. eungellensis recaptured at any stage later in the study, grouped by their infection status at first capture. A logistic model with recapture as the response and species and infection status as predictors produced no evidence that the effect of B. dendrobatidis infection on recapture probability differed between the species (Δdev = 0.002, df = 1, p = 0.96). In both species, the probability of recapture was significantly lower for infected frogs than for uninfected frogs (Δdev = 5.34, df = 1, p = 0.02; log odds ratio = –0.6464, se = 0.2856), correcting for the substantially higher overall recapture rate of T. eungellensis relative to L. wilcoxii/jungguy . Table 3 Recapture and Survival of Infected and Uninfected Frogs Shown are numbers of marked L. wilcoxii/jungguy and T. eungellensis frogs that were infected (+ve) and uninfected (-ve) and recaptured during the 4-y monitoring study, and maximum periods of time over which those frogs were known to survive after being toe-clipped This simple analysis suggests that B. dendrobatidis may affect survival, but confounds the probability of recapturing a frog that is present at a site with the probability that a frog is still present at the site. The more sophisticated analysis that follows separates these two components, although it cannot distinguish between death and permanent emigration from the site. For brevity, we refer to continued presence at the site as “survival.” Investigating mark–recapture data for both Rawson Creek and Dooloomai Falls, we found that the best model (on the basis of minimizing the AIC) for which there were sufficient data to estimate almost all parameters had the probability of recapture varying with time but not group (i.e., infected and uninfected males, females, and subadults), and the survival probability differing between the groups but constant through time. However, further analysis in both cases showed that there was no evidence that survival differed between infected and uninfected frogs: At both sites, the group effect was due to survival being highest in females, intermediate in males, and lowest in subadults ( Figure 3 ; Table 4 ). In the case of Tree Fern Creek, which had a smaller total sample size than the other two sites, and in which only males were infected, the best model had recapture probabilities constant with both time and group, and survival varying with group. At this site, there was some evidence that infected males had lower survival than uninfected males ( Figure 3 ; Table 4 ). Figure 3 Estimated Quarterly Survival of Age/Sex Classes of Taudactylus eungellensis at Three Sites Survival for uninfected frogs is shown with circles, and survival for infected frogs is shown with squares; 95% confidence limits around each point are also shown. Where there is no survival estimate for infected frogs, there were insufficient data to estimate the parameter. Sample sizes are given in Table 2 . Table 4 Summary of Results of Mark-Recapture Modelling on T. eungellensis “AICc” is the corrected Akaike Information Criterion; “ΔAICc” is the change in AICc from the “best” model; and “Model Likelihood” is the likelihood of the model relative to the best model. A parametric bootstrap analysis using the most complex model that could be parameterised from the capture histories (a model with additive effects of group and time on both recapture and survival) indicated that in each case the goodness of fit was adequate Discussion Our results show unequivocally that remnant populations of T. eungellensis, a rainforest frog that almost disappeared as a result of major die-offs in the Eungella area in the mid 1980s, now persist with stable infections of B. dendrobatidis. This does not imply that this pathogen cannot have been responsible for the decline. One hypothesis that can be discarded, however, is that B. dendrobatidis drove frog populations to low levels, consequently became locally extinct itself, and that frog populations subsequently recovered or stabilised in the absence of the pathogen. Two other hypotheses are consistent with our observed results. It may be that B. dendrobatidis was not responsible for the initial decline of T. eungellensis populations. These populations declined more than a decade before this chytrid was formally identified, and the declines occurred over a very short period ( McDonald 1990 ). Because of the rapidity of the declines, no samples were collected during the period of declines, so it is not possible to examine for the presence of B. dendrobatidis. Although it is not possible to eliminate all environmental factors as being responsible for the decline of T. eungellensis and the disappearance of R. vitellinus from Eungella in 1985, the failure to detect substantial climatic anomalies in the area at that time ( McDonald 1990 ) means that this explanation is unlikely to account for the sudden declines. Another possibility consistent with our results is that B. dendrobatidis was a pathogen novel to the ecosystem in 1985, and that it was indeed responsible for the declines. Available molecular evidence ( Morehouse et al. 2003 ), although not conclusive, is consistent with the hypothesis that B. dendrobatidis is a recently emerged disease agent. Populations of T. eungellensis may have recovered or stabilised following evolution of resistance to the pathogen in the frogs, or evolution of less-pathogenic strains of the fungus. Rapid coevolutionary changes in both host and pathogen following the introduction of a novel pathogen are to be expected, with the best-known example being the coevolution of myxomatosis and its rabbit hosts within a few years of the introduction of the virus to Australia in 1953 ( May and Anderson 1983 ; Fenner and Fantini 1999 ). Our study provides no direct evidence for such coevolution in frogs and B. dendrobatidis, but it identifies this as an important area for future research. If it could be shown that susceptible frog populations were able to develop resistance to the amphibian chytrid, then captive breeding and artificial selection for resistance would provide an avenue for management of this threat to critically endangered species. It is intriguing that we found similar seasonal fluctuations in infection levels within each year, but no evidence of variation among the 4 y of the study. This suggests strongly that B. dendrobatidis has become endemic and relatively stable in prevalence in these populations. Given that frog numbers and diversity remained broadly similar over this period, it suggests that some form of host–pathogen equilibrium has become established, in contrast to the epizootic that may have occurred 10 y previously. There are some obvious methodological limitations in our study that we must acknowledge. Infection status was determined by histological examination of toe tips at the time of first capture. Toe tips are often examined for B. dendrobatidis because the feet of frogs are a particularly favoured body location for infection by the fungus ( Berger 2001 ). However, in light infections, B. dendrobatidis can occur in microscopic clusters, which can potentially be missed in histological sections. Hence, a proportion of frogs found to be negative for B. dendrobatidis using histology at first capture may actually have been infected. This possibility of false negatives ( Berger 2001 ; Berger et al. 2002 ) suggests that the infection prevalences found in this study may underestimate the true prevalence of B. dendrobatidis within these frog populations. For individuals classed as infected at the time of first capture, and that subsequently survived for extended periods, it is not known whether their infection persisted or was cleared after first capture. There is evidence that some frog species can clear B. dendrobatidis infection: 50% of experimentally infected Mixophyes fasciolatus held at 27 °C with confirmed infection subsequently cleared the infection ( Berger 2001 ; Berger et al. 2004 ). The prevalences we report are therefore estimated from the prevalence of infection in frogs captured for the first time in the period under consideration. In this study, infection levels of B. dendrobatidis were significantly higher during winter and spring than during summer and autumn. A survey of ill and dead frogs from eastern Australia from 1995 to 1999 showed a similar seasonal prevalence of chytridiomycosis ( Berger et al. 2004 ). In the laboratory, the growth of B. dendrobatidis has been shown to peak at about 23 °C, with death or arrested growth occurring in vitro at temperatures above 30 °C ( Longcore et al. 1999 ; Johnson et al. 2003 ; Piotrowski et al. 2004 ). Further, infection in some frog species can be cleared in the laboratory by exposing them to temperatures in excess of 37 °C ( Woodhams et al. 2003 ). At Eungella, 23 °C is a typical daytime maximum temperature for winter, with water and air temperatures along streams generally remaining at or below 23 °C for the entire 24-h daylength period. In summer, however, daytime air temperatures along Eungella's streams regularly exceed 23 °C, and at sites such as Rawson Creek can reach as high as 37 °C (R. Retallick, unpublished data). The different infection levels among sites for T. eungellensis reported in Table 2 may be correlated with the degree of sunlight and warmth that reaches the streams. The streams at Dooloomai Falls and Tree Fern Creek are well shaded and remain relatively cool and damp for much of the year. At those sites, the average canopy gap above the centre of the streams (a coarse measure of how much sunlight reaches the stream) are 0.35 m and 1.90 m respectively (R. Retallick, unpublished data). Rawson Creek is considerably wider (average canopy gap = 5.10 m) and thus receives more sunlight. With access to sunny microhabitats, where surface temperatures can exceed ambient air temperatures, frogs at “warmer” streams such as Rawson Creek may be less subject to infection at any time of the year, or may be able to reduce infection through thermoregulation. The idea that frogs may avoid, control, or eliminate infection by differential use of their environment warrants considerable and immediate attention. Such a process may prove to be critical to the relationship between B. dendrobatidis and frog populations in the wild. Our mark–recapture analysis did not find consistent evidence that T. eungellensis infected with B. dendrobatidis at the time of first capture had a lower survival rate than uninfected T. eungellensis. Failure to reject the null hypothesis of no effect of infection on survival cannot, of course, be used as evidence in favor of the null hypothesis, and it is worth noting that the point estimate of survival for infected males was lower than that for uninfected males at each site. Only at Tree Fern Creek, however, did the best-supported model include an infection term. There was also evidence that infection influenced the proportion of frogs that were recaptured ( Table 3 ). Together with the observation that some infected T. eungellensis survived for extended periods (a maximum of 1,089 d), our results show that infection with B. dendrobatidis did not inevitably lead to rapid death in T. eungellensis. Both epidemiological theory and observations suggest that where a pathogen drives a host species to extinction, there is likely to be a reservoir host within which the pathogen has a reduced effect and is therefore maintained at a higher prevalence ( McCallum and Dobson 1995 , 2002 ). L. wilcoxii/jungguy appears not to have declined at the same time as T. eungellensis and R. vitellinus and, in our data, it has a high prevalence of infection. It therefore is a candidate reservoir host. Whether the prevalence of B. dendrobatidis differs between the sibling species L. wilcoxii and L. jungguy at sites where they are sympatric would be an interesting question, but cannot be answered from our study. The L. lesueuri complex has a widespread distribution throughout streams on the east coast of Australia ( Barker et al. 1995 ; Donellan and Mahony 2004 ) and could therefore play a substantial role in the maintenance and spread of chytrid infection throughout that region. If a species is acting as a reservoir, the prevalence of infection in that species should be higher than in species that are declining as a result of infection ( McCallum and Dobson 1995 ). The prevalence of infection we observed in L. wilcoxii/jungguy exceeded that observed in T. eungellensis, but we do not have clear evidence that this represents a higher prevalence in the populations as a whole. It is also possible that B. dendrobatidis exists as a saprophyte in the environment independent of amphibians ( Longcore et al. 1999 ; Johnson and Speare 2003 ), or may use tadpoles (which seem relatively little affected by the pathogen) as a reservoir ( Daszak et al. 1999 ). We did not detect infection in any of the 50 individuals of Litoria revelata or the 42 individuals of L. chloris we examined, which demonstrates that those species had a lower prevalence of chytridiomycosis than T. eungellensis and L. wilcoxii/jungguy . We did not record any infected frogs of any species from the two sites at which L. revelata was collected. Litoria chloris, however, has been shown to carry infection in other areas ( Speare and Berger 2004 ) and in laboratory experiments ( Woodhams et al. 2003 ). Sample sizes in our study for these other frog species may be too small to draw any reliable conclusions about whether they become infected with B. dendrobatidis in the wild. Materials and Methods Between 1994 and 1998, 36 excursions to Eungella National Park were made as part of a mark–recapture study of populations of frogs associated with streams. Frogs were captured from six study sites (see Figure 1 ), which were visited monthly from March 1994 to June 1996, in February and September 1997, and in February and May 1998. When caught for the first time, frogs were toe-clipped using the numbering system devised by Hero (1989) and then released alive. Amputated toe tips were preserved and individually stored in vials filled with 70% ethanol or 10% formalin. To minimize effects on the animals, no further toes were taken from subsequent recaptures of marked frogs; recaptured frogs were identified and released alive. All frog species encountered were monitored, with a special focus on T. eungellensis because of its precarious conservation status and history of decline. In 1997, toes from six species (278 individual frogs) were histologically prepared in transverse sections stained with Ehrlich's haematoxylin for skeletochronological assessment (see Castanet et al. [1996] for a description of the technique). We subsequently reexamined these sections for B. dendrobatidis ( Berger et al. 1999b ; Pessier et al. 1999 ). On average, 160 sections per individual were examined. Despite the sections not being stained with eosin, which highlights the keratinised layer of the epidermis where B. dendrobatidis occurs ( Berger et al. 1999b ; Pessier et al. 1999 ), most diagnoses were unambiguous. A small number, however, were not, and those samples were excluded from the analysis. For this assessment, samples were labelled “positive” only when the examiners were convinced that the sample was infected with B. dendrobatidis . Samples in which no infection was found were labelled “negative.” For this study, a further 196 archived toes of T. eungellensis were analysed by the Australian Animal Health Laboratory in Geelong, Australia, for B. dendrobatidis infection using histopathology with immunoperoxidase staining ( Berger et al. 2002 ). The immunoperoxidase stain improves the sensitivity of diagnosis by highlighting structures that are equivocal with haematoxylin and eosin, and that would otherwise be diagnosed as negative. With the software MARK ( Cooch and White 2002 ), we used mark–recapture modelling to investigate the survival of T. eungellensis at different sites. Frogs were grouped into six categories on the basis of their status at first capture (infected and uninfected males, females, and subadults). For both mark–recapture and analysis of prevalence, we grouped the data into 3-mo austral seasons (in Australia, summer runs from 1 December to the end of February, etc.). Mark–recapture modelling of survival requires that several assumptions be satisfied. Most critically, every marked individual present in the population at a given time has the same probability of recapture as all other members of its group, and the same probability of surviving to the next time interval. We used a parametric bootstrap ( Cooch and White 2002 ) to test the goodness of fit of our capture history sets to these assumptions. We analysed prevalence data using logistic models implemented in R (Version 1.6.2) ( R Development Core Team 2003 ). Since the mark–recapture study was performed with no knowledge of the infection status of individual animals, and the examination of histology was carried out with no knowledge of details of the fate of individual animals in the field, the study was double-blinded in design.

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549590

Communicating with Patients about Harms and Risks

Health professionals, says Herxheimer, must share their understanding of the benefits and harms of any treatment with patients and their families

Everything that doctors and other health workers do involves communication about the benefits and harms to be expected from interventions—whether they are therapeutic, diagnostic, or prophylactic. As health-care professionals, we need to share our understanding and perceptions of benefits and harms with patients and their families as fully as we can. We also have to share them with other professionals. When we do so we have to remember that how we personally value particular benefits and harms may well differ from how another person values them. A clinician who recommends an intervention does so in the belief that its benefits outweigh the harms that it can cause. In most consultations there is little time in which to explain in detail what these benefits and harms are, or to find out what the patient thinks about them. Moreover, most clinicians are not trained or practised at describing and explaining benefits and harms clearly to patients, and much of the time they also lack important information about these aspects. “Risk” Versus “Harm” The problems begin with the word “risk”. Very often people use it when they mean “harm”, and this causes ambiguities and confusion. The widely used expression “benefit/risk ratio” is meaningless—no such ratio exists. Before a decision is made to use an intervention, its benefits and harms must be weighed, ideally by the clinician and the patient together. Other advantages and disadvantages, such as convenience and cost, may also be relevant. This analysis requires use of the same dimensions for considering both benefits and harms. These dimensions have not been generally recognised or taught, though they seem obvious enough. Health professionals need to share their understanding of harms and benefits with patients and their families (Illustration: Margaret Shear, Public Library of Science) In this context any benefit or harm has four dimensions (see sidebar). The clinician is expected to know or find out about the nature and probability of each benefit and harm, and how to maximise benefits and minimise harms. A great many clinicians do not meet this expectation, and often that is not their fault. But only patients can say how they regard the hoped for benefits and the possible harms, though they may need help to think clearly about them. Clinicians should identify how much the benefits matter to their patient—for example, are the benefits of taking a medicine or having an operation “worth the trouble”?—and whether a specific harm is particularly threatening or would be intolerable to that particular patient. People's fears, wishes, and priorities differ greatly and unpredictably. The deepening of the voice that occurs with long-term use of tamoxifen for breast cancer, and that is usually irreversible, is an example of a side effect that prescribers, manufacturers, and drug regulators have considered trivial and have largely ignored. While this side effect does not bother most women, for professional or keen amateur singers it is a disaster—it can rob them of what they enjoy most. A patient who is offered a treatment with serious implications needs time and encouragement to think, and to talk to other people, before making a decision. Three major issues are important in helping patients with decision-making: obtaining reliable information about benefits and harms, effectively communicating probabilities to the patient, and determining what to do to reverse or mitigate harmful effects when they occur. Explaining Uncertainties and Probabilities Innumeracy is very widespread. Many people cannot handle percentages, and most are unclear about the meaning of “relative risk”, “absolute risk”, “odds ratio”, and “number needed to treat”, including many clinicians who want to tell their patients about the likelihood of benefits or harms [ 1 ]. Gigerenzer has shown that information on outcomes presented as natural frequencies (for example, “a one in five chance”) is much easier to understand than information expressed in probabilities (for example, “a 20% chance”) [ 2 ]. The reason, he suggests, is that “natural frequencies result from natural sampling, the process by which humans and animals have encountered information about risks during most of their evolution” ([ 1 ], p. 48–49). So, to put it in its simplest form, it is most effective to say to a patient “this treatment is effective in eight patients out of ten”, or “this drug causes nausea or vomiting in three people out of every ten who use it”. The Four Dimensions of Any Benefit or Harm Its nature , described by its quality, its intensity, and its time course (onset, duration, and reversibility). The probability that it will occur. Its importance to the person experiencing it. How the benefit can be maximised , or the harm prevented or minimised. Obtaining Reliable Information The effectiveness of an intervention (the extent to which a treatment produces a beneficial effect when implemented under the usual conditions of clinical care for a particular group of patients) is most readily estimated from controlled clinical trials. With the rise of evidence-based medicine, there are now many more critical analyses, systematic reviews, and meta-analyses of the best evidence, as in the rapidly growing Cochrane Database of Systematic Reviews ( www.cochrane.org ). Nevertheless, there are huge gaps—we still lack reliable evidence about many important interventions. Even in the case of common conditions for which many high-quality trials have been published, trial reports have not addressed some elementary questions, for example, on optimal drug dosage and duration of treatment. Almost all drug effects are related to dose [ 3 ], but we rarely learn what the lowest effective dosage is in different circumstances, and how far it is worth increasing the dosage if the effect is insufficient. Details of dose–response relationships are hardly ever published. They are usually studied early in the development of a drug in a relatively small number of volunteers, and are used to decide on the dosages to be used in the major clinical trials that will support the licensing application. They are regarded as internal working data of the company, which is not interested in publishing them. Regulatory agencies do not appear to ask for them or examine them critically. Everybody now habitually uses means and group differences to judge effectiveness, although individuals commonly differ greatly in their sensitivity to both beneficial and harmful effects of drugs. This thoughtless reliance on means and group differences, which ignores an important dimension of evidence, is now embedded in “evidence-based practice”. Marketing departments prefer a “one size fits all” approach: it is hard to sell a drug whose dose may need to be titrated. Another important unanswered question is the variation in response between individuals. Because controlled trials compare treatments they usually report only group means and test their significance. This gives clinicians no help in treating people who are more or less sensitive to the drug than average. Reliable information on harms is for several reasons even harder to get [ 4 ]. Far less research is done to investigate them. Companies do not want to do more work than regulators require, and once they have marketed a drug they hesitate to pay for more research, especially if the results might be inconvenient. Independent public funding hardly exists. Many kinds of harm—often unforeseen and uncommon—need to be first detected and then diligently investigated and analysed. And the available research designs yield less robust evidence than can be obtained for predefined therapeutic effects. Here, too, dose–response data are almost completely lacking. We still lack reliable evidence about many important interventions. Thus, much of the time prescribers and patients are poorly informed, and have to rely on cautious exploration, common sense, and personal experience. Nevertheless, as Yoon Kong Loke has pointed out, there are certainly some situations at the bedside when it is particularly important to base treatment decisions on as precise an estimate as possible of the balance of benefits and harms [ 5 ]. An example is when there is a narrow margin between benefit and harm, such as giving aspirin to a patient with a stroke who has a past history of gastrointestinal haemorrhage. Another example is when there are several efficacious treatments with differing safety profiles, such as warfarin versus aspirin in a healthy, middle-aged patient with lone atrial fibrillation. Checking Effectiveness and Detecting and Dealing with Harms Doctor and patient need to work together to check that the treatment is as effective as intended, and to detect possible harm promptly. Monitoring can be left to patients if they (or the family) can understand what to watch for and what to do if a problem arises. If not, or if examination or lab tests are necessary, then monitoring and follow-up by a nurse or doctor will need to be arranged. Here is a checklist of points for clinicians—and of course also drug regulators—to consider. (1) When an adverse effect occurs, should the dose be reduced, or the drug changed? (2) If reduced, by how much? (3) Is reducing the dose possible and practicable with the available preparations? (4) How and over what time should the effect of the change be observed and assessed? (5) Should the patient, as well as the clinician, keep the records of adverse effect(s) and their intensity and timing? Such notes can help both the patient and current and future doctors. Medication experiences can remain relevant for life. (6) Should an adverse effect be reported to a local or national adverse drug reaction register? (If in doubt, the answer is yes). Conclusion Effective communication about harms and risks is an essential component of care, and it requires learning, preparation, and rehearsal. The onus lies with professionals to persuade and to teach patients to play their part in coming to an informed decision about treatments.

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524026

What is Nutrition & Metabolism?

A new Open Access journal, Nutrition & Metabolism ( N&M ) will publish articles that integrate nutrition with biochemistry and molecular biology. The open access process is chosen to provide rapid and accessible dissemination of new results and perspectives in a field that is of great current interest. Manuscripts in all areas of nutritional biochemistry will be considered but three areas of particular interest are lipoprotein metabolism, amino acids as metabolic signals, and the effect of macronutrient composition of diet on health. The need for the journal is identified in the epidemic of obesity, diabetes, dyslipidemias and related diseases, and a sudden increase in popular diets, as well as renewed interest in intermediary metabolism.

Editorial Recent events that provide the rationale for a new Open Access journal, Nutrition & Metabolism ( N&M ) include 1) an awareness of an epidemic of obesity, diabetes, dyslipidemias and related diseases, 2) a sudden increase in the popularity of diets, such as low carbohydrate diets, to achieve weight loss and combat diabetes, and 3) a renewed interest in intermediary metabolism accompanied by the development of new tools and techniques for genomic and metabolic analysis. With the considerable activity shown in these areas, rapid and easily accessible dissemination of new information is clearly valuable. Whereas articles in existing journals do discuss intermediary metabolism in a nutritional context, there is a need for a unique and explicit focus for this discipline. In addition, it is precisely because publications in nutritional biochemistry are spread over such a large number of existing journals, few libraries and almost no individual can subscribe to all. It is in areas like this that free, open access becomes important. There is a large published debate on open access (see, e.g. [ 1 ]). Most recently, the UK House of commons issued a report encouraging open access publishing of government-funded research (available with comments through ) and similar motions exist in the US congress [ 2 , 3 ]. The editors of N&M feel that, at this point, the burden of proof is on proponents of perpetuating the current system. We are, however, not doctrinaire on this point and believe one should pay for a service if it is valuable. Beyond information, printed collections provide convenience and we intend to offer bound copies of articles on individual topics as the journal proceeds. Nutrition and metabolism is a broad field and we welcome submissions from all areas of nutrition and related biochemistry. Like any journal, however, N&M has its own strengths and interests as indicated by the board of editors . Three areas of particular interest are lipoprotein metabolism, amino acids as metabolic signals, and the effect of macronutrient composition of diet on health. This is reflected in our opening research articles by Darimont, et al . on the control of obesity and lipid structure by adrenergic systems, and by Volek, et al . on the effectiveness of low carbohydrate diets, and differential effects on fat and lean mass. The sudden popularity of low carbohydrate diets is one of the most remarkable phenomena in nutrition today. A recent editorial by Walter Willett points out how important it is that we understand them [ 4 ]. Similarly, the recent conference on Nutritional and Metabolic Aspects of Low Carbohydrate Diets , while not recommending any particular diet, highlighted many of the relevant issues in macronutrient control of metabolism. In our initial publications, contributors to the conference will provide reviews of the various topics covered. In the first posting, Klaas Westerterp summarizes the importance of macronutrient composition in thermogenesis, and Stephen Phinney discusses the impact of ketogenic diets on physical performance. Kimball and Jefferson review the regulation of mRNA translation in general. The article provides a nice overview of various mechanisms involved in the control of protein synthesis when amino acids become limiting. Perhaps the most important from a practical standpoint, Nuttall and Gannon summarize potential benefits of higher protein diets in diabetes. Nutrition & Metabolism welcomes contributions in all areas of research in which nutrition interacts with biochemistry and molecular biology. Emphasis will be on the molecular, biochemical, and physiologic understanding of various metabolic pathways. The journal will publish Original Research, Reviews, Commentaries and Perspectives, Brief Communications, Methods and Book Reviews. Access to all articles in N&M is free. Articles are included in PubMed and archived in PubMed Central. Online submissions can be made at .

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535895

The hazards of lack of co-registration of ictal brain SPECT with MRI: A case report of sinusitis mimicking a brainstem seizure focus

Background Single photon emission computed tomography (SPECT) following injection of radiotracer during a seizure is known as ictal SPECT. Comparison of an ictal SPECT study to a baseline or interictal study can aid identification of a seizure focus. Case presentation A young woman with encephalitis and refractory seizures underwent brain SPECT during a period of frequent seizure-like episodes, and during a seizure-free period. A focal area of increased radiotracer uptake present only when she was experiencing frequent seizure-like episodes was originally localized to the brainstem, but with later computerized co-registration of SPECT to MRI, was found to lie outside the brain, in the region of the sphenoid sinus. Conclusion Low-resolution SPECT images present difficulties in interpretation, which can be overcome through co-registration to higher-resolution structural images.

Background Radiotracers used for brain single photon emitted computed tomography (SPECT) pass the blood-brain barrier and bind intracellularly on their first pass through the circulation, providing a "snapshot" of cerebral perfusion at a particular timepoint. When injected during a focal epileptic seizure, an area of significantly increased radiotracer uptake typically corresponds to the region of maximal abnormal activity, often the seizure focus. This ictal pattern of cerebral blood flow can be compared to an interictal/baseline pattern obtained when the patient is not having a seizure, to provide unique information about the nature and location of a patient's epileptic focus, which can be used to guide therapy [See [ 1 ] for a review of the use of SPECT in epilepsy]. Case presentation A previously-healthy young woman developed behavioral changes followed by seizures and refractory status epilepticus. She was diagnosed with encephalitis and treated with antiviral and multiple antiepileptic agents. She required nasotracheal intubation and mechanical ventilation for respiratory support. She experienced persistent episodes of facial twitching resembling seizures. These episodes were not however associated with an ictal EEG pattern on continuous video/EEG monitoring. To clarify the nature of these episodes, 99mTc-HMPAO was injected during a period of frequent twitching. Brain SPECT showed a prominent focus of increased uptake interpreted by the radiologists and clinical team as arising in the upper brainstem (Figure 1A .) A repeat study (using 99mTc-ECD) two weeks later, when twitching was no longer occurring, showed resolution of this increased uptake (Figure 1B ). These findings were considered to support a diagnosis of seizures/repetitive myoclonus originating from the brainstem. Although brainstem seizures in humans remain a controversial entity, there are reports in the medical literature of seizures and seizure-like movements related to brainstem lesions [ 2 - 4 ] making this a plausible diagnosis in this case, based on clinical, EEG and SPECT findings. Antiepileptic and supportive treatment were continued, but the patient's disease proved fatal. No autopsy was performed. Figure 1 A: Axial, coronal and sagittal 99mTc-HMPAO SPECT images of the brain obtained during a facial twitching episode show moderate to severe heterogeneous cerebral hypoperfusion with an apparent focus of increased radiotracer uptake near the midbrain. B: 99mTc-ECD SPECT image of the brain obtained two weeks after (A) during a period free from twitching shows resolution of the area of increased uptake. C: Computer-generated depiction of A-B overlayed onto a co-registered MRI shows the area of increased uptake to lie outside the brain. See [5] or for image analysis and alignment methodology. With later co-registration of SPECT data to the patient's MRI using a computerized medical image registration and visualization program, [ 5 ] the area of increased radiotracer uptake was seen to be anterior to the brain, likely in the sphenoid sinus, consistent with sinusitis (Figure 1C ). MRI showed prominent maxillary and sphenoidal sinus mucosal thickening also consistent with sinusitis. Chronic nasotracheal intubation is commonly accompanied by sinusitis, [ 6 ] which may resolve with removal of the offending tube, as was performed in this case when the patient underwent tracheotomy during the interval between the first and second SPECT scans. Conclusions The nature of this patient's twitching episodes remains uncertain, though they were likely due to epileptic activity involving too small a volume of brain to be detectable by either EEG or SPECT. Her case is described here to illustrate a previously-unreported pitfall in the interpretation of brain SPECT studies, with the goal of emphasizing the importance of image co-registration in nuclear medicine. Diagnostic limitations inherent to low-resolution images can be overcome through use of computer software to accurately co-register brain images of different modalities acquired separately (as described here) or hybrid medical devices such as PET-CT scanners to automatically fuse simultaneously-acquired images. Both methods have been shown to be superior to visual inspection and mental integration of information by experienced radiologists [ 7 , 8 ]. List of abbreviations SPECT: single photon emitted computed tomography; MRI: magnetic resonance imaging; EEG: electroencephalography Competing interests The author(s) declare that they have no competing interests. Authors' contributions TB performed image analysis and co-registration and drafted the manuscript. LJH identified the patient, conceived of the study, and drafted a preliminary version of the manuscript. JC participated in data collection and analysis. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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529264

Parents' reported preference scores for childhood atopic dermatitis disease states

Background We sought to elicit preference weights from parents for health states corresponding to children with various levels of severity of atopic dermatitis. We also evaluated the hypothesis that parents with children who had been diagnosed with atopic dermatitis would assign different preferences to the health state scenarios compared with parents who did not have a child with atopic dermatitis. Methods Subjects were parents of children aged 3 months to 18 years. The sample was derived from the General Panel, Mommies Sub-Panel, and Chronic Illness Sub-Panel of Harris Interactive. Participants rated health scenarios for atopic dermatitis, asthma, and eyeglasses on a visual analog scale, imagining a child was experiencing the described state. Results A total of 3539 parents completed the survey. Twenty-nine percent had a child with a history of atopic dermatitis. Mean preference scores for atopic dermatitis were as follows: mild, 91 (95% confidence interval [CI], 90.7 to 91.5); mild/moderate, 84 (95%CI, 83.5 to 84.4); moderate, 73 (95%CI, 72.5 to 73.6); moderate/severe, 61 (95%CI, 60.6 to 61.8); severe, 49 (95% CI, 48.7 to 50.1); asthma, 58 (95%CI, 57.4 to 58.8); and eyeglasses, 87(95%CI, 86.3 to 87.4). Conclusions Parents perceive that atopic dermatitis has a negative effect on quality of life that increases with disease severity. Estimates of parents' preferences can provide physicians with insight into the value that parents place on their children's treatment and can be used to evaluate new medical therapies for atopic dermatitis.

Background Atopic dermatitis is the most common of childhood skin diseases, with a lifetime prevalence in children of 10% to 20% [ 1 ]. The disease is most common in industrialized countries and among Caucasians and Asians [ 2 ]. Annual total costs of treatment are estimated to range from $0.9 to 3.8 billion in the United States [ 3 ]. Atopic dermatitis can have a negative impact on quality of life by affecting psychosocial adjustment in children. Lapidus and Kerr [ 4 ] report that atopic dermatitis can cause embarrassment, disrupt sporting activities in older children, and interfere with employment opportunities among adults. The disease can also have a negative impact on families. Parents report feelings of guilt, exhaustion, frustration, and helplessness [ 4 - 7 ]. Atopic dermatitis can disrupt sleep in patients and their family members, and parents can miss work or avoid outside work altogether to care for a child with the disease [ 4 , 8 ]. Fivenson et al [ 9 ] found that 50% of the total burden of illness of atopic dermatitis is associated with lost productivity. Specifically, they found that days lost from work and nights of sleep lost were high among parents of young children with atopic dermatitis [ 9 ]. These stresses take additional tolls on familial relationships and are confounded in low-income families, who often have minimal access to social support mechanisms [ 4 ]. As the need to control increasing medical expenditures continues to mount, formal economic evaluations are taking on a prominent role in assessing the value of new medical therapies. To properly evaluate the impact of new therapies for atopic dermatitis, patients' health-related quality of life (HRQOL) must be considered. Although a number of quality-of-life evaluations have been conducted for adults and children affected with atopic dermatitis [ 4 , 7 , 9 - 12 ], quality-of-life adjustments in cost-utility analyses must be performed using preference weights. Preference weights represent summary measures of HRQOL associated with individual health states and are necessary to calculate quality-adjusted life-years (QALYs) for use in cost-utility analyses. Although the prevalence of atopic dermatitis is highest in children, the existing literature on patient preferences for atopic dermatitis is limited to the adult population [ 13 , 14 ]. However, eliciting preferences from children may not be possible, because they lack the necessary language skills and cognitive abilities to interpret and respond to questions used to evaluate preferences. Evidence suggests that proxy reports by parents may provide valid estimates of HRQOL in children [ 15 ]. Therefore, our primary objective was to elicit preference weights from parents for health states corresponding to children with various levels of severity of atopic dermatitis. In addition, we evaluated the hypothesis that parents with children who had been diagnosed with atopic dermatitis would assign different preferences to the health state scenarios compared with parents who did not have a child with atopic dermatitis. Methods Preference assessment instrument Patient preferences can be elicited using standard gamble or time-tradeoff or direct rating methods such as a visual analog scale. Because both the standard gamble and the time-tradeoff exercises involve choices between two alternatives that involve a chance of death or longevity, we believed it was unethical to ask parents to participate in such exercises when children were the subjects. Therefore, our choice for eliciting preferences was the rating scale. We developed case scenarios for 5 levels of atopic dermatitis severity – mild, mild/moderate, moderate, moderate/severe, and severe. These severity levels were created by combining the characteristics of an Investigator Global Assessment (IGA) and the Eczema Area and Severity Index (EASI) score [ 16 ]. Each scenario included descriptions of erythema, infiltration and/or papulation, excoriation, and lichenification, as well as location of body area affected (Table 1 ). Efforts were made to ensure that the scenarios were descriptive, explicit, nonjudgmental, and targeted to an eighth-grade reading level. A medical artist developed images to depict the descriptions of atopic dermatitis. We also included 2 additional scenarios – one that described wearing glasses and another that described suffering from asthma – to compare the preferences for atopic dermatitis health states to nondermatological health states. A pediatrician and a pediatric dermatologist reviewed the descriptions and illustrations to ensure their validity and realism. The scenarios were revised based on their comments. Table 1 Scenario descriptions Severity Scenario Mild • The area looks like a light pink or white, dusty rash. • It is affecting the cheeks. • It is rarely itchy and your child scratches it only a few (about 3) times a day. • There are only a few (about 3) slightly bumpy areas. • There is no oozing or crusting. • The skin is not dry or leathery. • Sleep is rarely disrupted by itching. Mild/Moderate • The area looks like a light pink or white, dusty rash. • It is affecting the cheeks and the chin. • It is somewhat itchy and your child scratches it about 5 times a day. • There are about 5 slightly bumpy areas. • There is no oozing or crusting. • The skin is not dry or leathery. • Sleep is somewhat disrupted by itching. Your child loses about 15 minutes of sleep each night because of scratching. Moderate • The area looks like a dark pink rash. • It is affecting the cheeks, the chin and the inside of the elbows. • It is moderately itchy and your child scratches it often (about 15 times) during the day. • There are about 7 moderately bumpy areas. • There is no oozing or crusting. • The skin is not dry or leathery. • Sleep is disrupted by itching. Your child loses about 1 hour of sleep each night because of scratching. Moderate/Severe • The area looks like a dark pink rash. • It is affecting the cheeks, the chin and the inside of the elbows, and the back of the knees. • It is itchy and your child scratches it often (about 30 times) during the day. • There are about 10 moderately bumpy areas. • There is some light oozing or crusting in one area. • The skin is not dry or leathery. • Sleep is disrupted by itching. Your child loses about 2 hours of sleep each night because of scratching. Severe • The area looks like a red rash. • It is affecting the cheeks, the chin and the inside of the elbows, and the back of the knees, and the trunk of the body. • It is very itchy and your child scratches it scratching continuously throughout the day. • There are numerous bumpy areas. • There is oozing or crusting in some areas. • The skin is dry and leathery in some areas. • Sleep is disrupted by itching. Your child loses about 3 hours of sleep each night because of scratching. Using cognitive interview techniques, we pilot-tested the preference assessment instrument in a convenience sample of 20 parents of children who were being evaluated at a local children's primary care clinic to assess patients' understanding of the instrument and its instructions. The instrument was further revised based on the results of the pilot test. Survey administration A health state preference assessment asks subjects to make judgments regarding the value of particular health states [ 9 ]. Preferences for health states can be elicited from patients with disease (or their family members), from patients at risk for disease, or from the general public [ 17 , 18 ]. We elected to develop preferences from family members of children who currently had atopic dermatitis or were at risk for the disease. To obtain responses from a broad range of respondents in an efficient manner, we recruited participants over the Internet. The sample was derived from the General Panel, the Mommies Sub-Panel, and the Chronic Illness Sub-Panel of Harris Interactive (Rochester, NY), an international market research and consulting firm. The General Panel is a multimillion-member panel of respondents who register to participate in The Harris Poll online panel. The Mommies Sub-Panel is a subpanel of respondents with children aged up to 2 years. The Chronic Illness Sub-Panel identifies respondents (or household members) who have been diagnosed with at least 1 of more than 44 chronic medical conditions, including skin conditions. (The Mommies and Chronic Illness Sub-Panels are part of The Harris Poll online panel. Aside from parental and health status, their members do not differ systematically from members of the General Panel.). Subjects were invited to participate in the survey from February 12 through 14, 2002, and were asked to register at a specific survey site. After consent was obtained online, subjects completed the survey. Respondents were offered the incentive of a chance to win one of five $100 prizes. Respondents had to be adults with children aged 3 months to 18 years in order to be included in the study. The study was approved by the institutional review board of Duke University Medical Center. Clinical data were based on self-report and included information on diagnosis history and severity level. Specifically, respondents were asked if they had a child between the ages of 3 months and 18 years who had ever been diagnosed by a medical professional with atopic dermatitis. If they responded "yes," they were then asked to describe the child's atopic dermatitis at its worst point by selecting from the following response options: mild, mild/moderate, moderate, moderate/severe, severe. For the preference assessment, each respondent was given the scenarios in the same order – mild through severe atopic dermatitis, asthma, and glasses. Subjects were instructed to indicate on a scale ranging from 100 (perfect health) to 0 (death) how good or bad they believed it would be to be a child experiencing the scenario depicted. Respondents recorded their values using a movable pointer on the scale. Respondents whose Internet browser software did not support the movable pointer entered their numerical responses manually into a required field. All 7 values were summarized at the end of the survey to allow respondents to review and, if desired, revise their ratings. Data analysis Descriptive statistics were used to describe the sample. Because subjects provided responses across severity levels, a repeated-measures analysis of variance was conducted using polynomial contrasts for the within-subjects (severity) effect. A P value of ≤ .05 was used as the criterion for statistical significance. Results Of the 28105 subjects contacted, 6131 (22%) responded. Of the 6131 respondents, 3539 (57.7%) met the inclusion criteria, consented to participate in the study, and completed the survey (Table 2 ). The mean age was 41 years; 93% of the subjects were women; and 90% were white. Nonresponders were similar to responders with respect to age, sex, and race/ethnicity. More than 98% of the sample had at least a high school education, with 83% of respondents completing at least some college courses. Overall, the sample reflected moderate- to high-income families, with 74% having an annual household income of at least $35000. Thirty percent of the parents had a child with atopic dermatitis, 55% had a child with asthma, and 46% had a child who wore glasses. Table 2 Subject characteristics Characteristic Responders (n = 3539) Nonresponders (n = 21974) Age Mean (SD) 40.6 (6.2) 41.0 (6.4) Range 18–64 19–76 Female sex 3298 (93.2) 20263 (92.2) Race/ethnicity* White 3045 (89.7) 18507 (84.2) Black/African-American 136 (4.0) 1098 (5.0) Hispanic 79 (2.3) 703 (3.2) Asian/Pacific Islander 21 (0.6) 171 (0.8) Native American 38 (1.1) 316 (1.4) Mixed/other 77 (2.3) 520 (2.4) Unknown 0 559 (2.5) Declined to answer 0 100 (0.5) Education level† Did not complete high school 55 (1.6) 706 (3.2) High school degree 555 (15.7) 4366 (19.9) Some college 1391 (39.3) 9074 (41.3) College degree 991 (28.0) 5179 (23.6) Some graduate school or degree 543 (15.4) 2568 (11.7) Unknown 0 81 (0.4) Annual household income‡ <$15000 107 (3.5) 868 (3.9) $15000$24999 262 (8.6) 1983 (9.0) $25000–$34999 410 (13.4) 2945 (13.4) $35000–$49999 665 (21.7) 4177 (19.0) $50000–$74999 806 (26.3) 5065 (23.0) $75000–$99999 406 (13.3) 2003 (9.1) $100000–$149999 220 (7.2) 1442 (6.6) $150000–$199999 85 (2.8) 273 (1.2) $200000–$249999 61 (2.0) 117 (0.5) ≥ $250000 16 (0.5) 103 (0.5) Declined to answer 24 (0.8) 1 (0.0) Unknown 0 2997 (13.6) Employment status § Employed full-time 1766 (80.0) 9070 (42.2) Employed part-time 554 (15.7) 2355 (11.0) Self-employed 281 (7.9) 1588 (7.4) Not employed but looking for work 119 (3.4) 852 (4.0) Not employed and not looking for work 70 (2.0) 588 (2.7) Retired 40 (1.1) 258 (1.2) Student 149 (4.2) 3071 (14.3) Homemaker 974 (27.5) 3566 (16.6) Disabled 0 138 (0.6) Not sure 4 (0.1) 0 Declined to answer 4 (0.1) 0 Not applicable 0 0 Number of children in household Mean (SD) 1.9 (1.0) 1.9 (1.2) Range 0–9 0–15 Country of residence Australia 2 (0.1) -- Canada 2 (0.1) -- United States 3535 (99.9) -- Values are reported as number (percentage) unless otherwise indicated. *There were 143 missing responses for this variable. † There were 4 missing responses for this variable. ‡ There were 477 missing responses for this variable. § Responses sum to more than 100% because respondents could select more than one answer. Nonresponders did not have this option. There were 488 missing responses for this variable. Table 3 displays the characteristics of the children's atopic dermatitis (n = 1017). Seventy-eight percent (n = 806) of children were diagnosed more than a year ago. Sixteen percent (n = 160) of the sample described their child's atopic dermatitis as mild and 8% (n = 78) described their child's atopic dermatitis as severe. Thirty-five percent (n = 357) of the sample reported their child's atopic dermatitis under limited control or uncontrolled. Table 3 Disease characteristics for children with atopic dermatitis Characteristic Subjects (n = 1017) Time of diagnosis ≤ 1 month ago 119 (11.7) 7 months to <12 months ago 95 (9.3) 1 year to 5 years ago 467 (45.9) > 5 years ago 336 (33.0) Disease severity Mild 160 (15.7) Mild to Moderate 236 (23.2) Moderate 277 (27.2) Moderate to Severe 266 (26.2) Severe 78 (7.7) How well controlled? Complete 206 (20.3) Good control 409 (40.2) Limited control 330 (32.4) Uncontrolled 27 (2.6) No treatment 45 (4.4) Values are reported as number (percentage) unless otherwise indicated. The mean values for all participants are presented in Table 4 . Among the atopic dermatitis health states, there was a progressive decline in respondents' preferences, with the mildest state receiving the highest mean preference score and the severe state receiving the lowest mean preference score. On average, preferences for asthma were higher than for severe atopic dermatitis but lower than moderate/severe atopic dermatitis. Not surprisingly, wearing glasses received a higher preference value than suffering from asthma. Average preference values for the glasses health state were ranked between the mild and mild/moderate atopic dermatitis health states. Table 4 Average health state preference values Health State Mean Median 95% Confidence Interval Mild atopic dermatitis 91.1 95.0 90.7–91.5 Mild/moderate atopic dermatitis 83.9 88.0 83.5–84.4 Moderate atopic dermatitis 73.1 76.0 72.5–73.6 Moderate/severe atopic dermatitis 61.2 63.0 60.6–61.8 Severe atopic dermatitis 49.4 50.0 48.7–50.1 Asthma 58.1 60.0 57.4–58.8 Wearing eyeglasses 86.8 94.0 86.3–87.4 There was a significant effect of severity (F 4,3391 = 3065.66; P = .0001). The linear effect of severity (F 1,3394 = 11454.90; P < .0001) indicated that preference ratings significantly decreased as the severity of the health states increased (Figure 1 ). Furthermore, there was a significant main effect for preferences reported by parents of children with atopic dermatitis as compared to parents of children without atopic dermatitis (F 1,3394 = 8.10; P = .0045). Across all health states, parents of children with atopic dermatitis gave a slightly higher mean preference (72.85 [SD, 13.50]) compared to parents whose children did not have atopic dermatitis (71.34 [SD, 14.19]) (Figure 1 ). Figure 1 Comparison of overall ratings, stratified by children with atopic dermatitis and children without atopic dermatitis There was no significant severity by parent group interaction (F 4,3391 = 1.21; P = .31), indicating that the differences across health states were the same for both parent groups. Discussion Our study evaluated preferences for 5 health states for atopic dermatitis. The aggregate values for each health state may be used for computing QALYs for new therapies that treat atopic dermatitis or can be used to help physicians make more informed decisions by considering parents' perceptions of atopic dermatitis measured on a continuum from perfect health to death. The differences in average values across the 5 health states were generally consistent, with mild at 91, mild/moderate at 84, moderate at 73, moderate/severe at 61, and severe at 49. Lundberg and colleagues [ 13 ] found that the mean health-state utility using a rating scale for patients with atopic dermatitis was 77, a value only slightly higher than our average health-state utility of 73. This small discrepancy could be explained by several factors. First, Lundberg et al [ 13 ] asked adult patients to provide ratings for themselves, whereas our study asked parents to provide ratings for children. Parents might feel that a given health state is worse for their children than it would be for themselves. Second, Lundberg et al [ 13 ] asked patients to provide a rating for their current health state, whereas our study asked parents to assign utilities to 5 varying levels of severity of atopic dermatitis. The average severity level of Lundberg et al's [ 13 ] sample might have been slightly lower than the average severity among our 5 health states, making the mean preference value slightly higher. By obtaining preferences for varying levels of severity, our results have greater applicability in various types of models for decision making. Although preference ratings were systematically higher among parents of children with atopic dermatitis than among parents whose children did not have atopic dermatitis, the magnitude of the difference was small (difference = 1.5). Research on adults who rate the health states of other adults has suggested that people who have experienced a particular health state are more likely to assign a higher value to it than others who are asked to imagine the health state [ 19 - 21 ]. The lack of a larger difference between the parent groups in our study could indicate that parents evaluate health states of children the same, regardless of whose children they are, because of a general concern for all children. Regardless of the reason, these results have important implications for the use of community-based preference weights, as opposed to patient-based (or parent-based) weights, in preference-weighted decision analyses. For this limited therapeutic domain, our study shows that parents in the general community would supply approximately the same preferences as parents whose children suffer the condition under study. Future research should consider whether this consistency holds for other serious childhood diseases, such as pediatric cancer. Our study has several limitations. First, by using the Internet, respondents did not have an opportunity to ask questions if they did not understand what they were being asked to do. However, we feel that this limitation was negligible, because the instrument was pilot-tested using in-person interviews, and the very large majority of responses were ranked appropriately (eg, mild ranked higher than severe). Secondly, there may be a sample bias in using the Harris Interactive database. Our sample reflected a predominately white, female cohort from a high socioeconomic class and may present generalizability issues. However, we received responses from 351 (14%) nonwhite respondents and 779 (22%) responses from participants with an annual household income of less than $35000, providing a sufficient number of responses to test for differences by race/ethnicity and income level. Further research will be needed to corroborate our findings using a population-based sample. Third, since these data are self-reported, some parents may have misclassified their children as having or not having atopic dermatitis, potentially biasing our results. Fourth, it is unclear whether physician assessment of severity would correspond with the severity levels that we assigned to the health states. However, physicians could evaluate the descriptions provided to judge whether their assessments are consistent. Finally, people enrolled in the Harris Interactive database are computer users who may be more motivated to participate in a survey than the general population. It is unclear how or in what direction these sample biases might affect the results of our analyses. We had an apparent response rate of 22%. Harris Interactive generally achieves a 15% to 20% response rate when using the Chronic Illness Sub-Panel. While our response rate was higher than Harris' average response rate, possible reasons for why the response was low could be attributed to the nature of the study design. First, because subjects were contacted by e-mail, it is possible that some subjects did not open the e-mail message until after the survey deadline. Second, Harris Interactive panel members agree to be notified about survey opportunities, but do not agree to participate in each survey. Since the characteristics of responders and nonresponders did not differ, we have no reason to believe that nonresponse bias is exerting a substantial influence on our results. Conclusions The results of this analysis clarify the values that parents of children with atopic dermatitis assign to different atopic dermatitis health states. These assigned values, relative to the comparison states, clearly demonstrate the perceived burden of atopic dermatitis by parents of children suffering from the disease. Understanding the preferences for atopic dermatitis can provide physicians insight into the value that parents place on treatments for their child's disease and in evaluating the cost-effectiveness of therapies for atopic dermatitis. Competing interests This study was supported by a research agreement between Duke University Medical Center and the Novartis Pharmaceuticals Corporation, East Hanover, NJ, which manufactures a cytokine inhibitor for the treatment of atopic dermatitis. KPW and KAS have received monetary compensation for consultancies, and EBW and KAS have received research grants, from Novartis. KHK is an employee of Novartis. Authors' contributions JYF conceived of and designed the study, performed the statistical analysis, interpreted the data, and drafted the manuscript. SDR conceived of and designed the study and assisted in interpretation of the data and drafting of the manuscript. KPW assisted in interpretation of the data and drafting of the manuscript. EBW and KHK conceived of and designed the study and assisted in drafting of the manuscript. KAS conceived of and designed the study, assisted in drafting of the manuscript, and obtained funding. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529264.xml

516043

Bistability and hysteresis of the 'Secteur' differentiation are controlled by a two-gene locus in Nectria haematococca

Background Bistability and hysteresis are increasingly recognized as major properties of regulatory networks governing numerous biological phenomena, such as differentiation and cell cycle progression. The full scope of the underlying molecular mechanisms leading to bistability and hysteresis remains elusive. Nectria haemaotcocca , a saprophytic or pathogenic fungus with sexual reproduction, exhibits a bistable morphological modification characterized by a reduced growth rate and an intense pigmentation. Bistability is triggered by the presence or absence of σ, a cytoplasmic determinant. This determinant spreads in an infectious manner in the hyphae of the growing margin, insuring hysteresis of the differentiation. Results Seven mutants specifically affected in the generation of σ were selected through two different screening strategies. The s 1 and s 2 mutations completely abolish the generation of σ and of its morphological expression, the Secteur. The remaining five mutations promote its constitutive generation, which determines an intense pigmentation but not growth alteration. The seven mutations map at the same locus, Ses (for 'Secteur-specific'). The s 2 mutant was obtained by an insertional mutagenesis strategy, which permitted the cloning of the Ses locus. Sequence and transcription analysis reveals that Ses is composed of two closely linked genes, SesA , mutated in the s 1 and s 2 mutant strains, and SesB , mutated in the s * mutant strains. SesB shares sequence similarity with animal and fungal putative proteins, with potential esterase/lipase/thioesterase activity, whereas SesA is similar to proteins of unknown function present only in the filamentous fungi Fusarium graminearum and Podospora anserina . Conclusions The cloning of Ses provides evidence that a system encoded by two linked genes directs a bistable and hysteretic switch in a eukaryote. Atypical regulatory relations between the two proteins may account for the hysteresis of Secteur differentiation.

Background Although it has long been known that cellular memory, or epigenetic states, can be created by emergent properties of regulatory or metabolic networks (see Delbrück in the discussion of [ 1 ], and [ 2 , 3 ]), the full implications of this type of inheritance have only recently been understood. To date, pertinent studies focused mainly on phenomena related to chromatin structure and DNA methylation, RNAi and other post-transcriptional gene silencing processes, and prions. However, virtually any physiological process can adopt a bistable (or multistable) behavior, as defined by the ability to adopt two (or more) stable states rather than a range of intermediate states, provided that a positive feedback loop exists (or its related counterpart, the mutually inhibitory double negative feedback loop) within the system [ 1 , 3 , 4 ]. The bistability may sometimes be associated with hysteresis, i.e., the ability of the system to maintain, in a sustained manner, a particular state despite the fact that the stimulus initiating this state is no longer present or is below the level that initially activated the system [ 5 , 6 ]. In some cases, the hysteresis is sufficiently dominant to permit faithful transmission of the different states during mitosis and even meiosis, thus appearing as an epigenetic phenomenon [ 4 , 7 ]. In the light of these concepts, alternative inheritable regulatory states were designated (reviewed in [ 8 ]) based on previous descriptions of regulatory or metabolic networks, permitting the definition of new types of inheritance units, the 'toggle switch' and the 'positive feedback switch'. More recently, mathematical models defined the conditions in which a system endowed with positive autoregulation can present bistability [ 9 , 10 ]. However, most studies on bistable regulatory states are presently performed with a few well-known systems [ 7 , 8 ], including the lactose operon, the lambda lysogenic/lytic decision switch, and the Xenopus mos MAP kinase cascade. Other relevant models are necessary for the comprehension of these phenomena. Fungi are an excellent source of well-defined bistable and multistable processes associated with hysteresis (reviewed in [ 4 , 11 ]; see also [ 12 ]). In yeasts, such phenomena are quite common and are called phenotypic switches [ 11 , 13 ] or prions [ 14 ]. In filamentous fungi, bistable phenomena seem to be particularly prevalent, as one-third of the species show at least one example of these [ 4 ]. In most cases investigated in filamentous fungi, bistability results from the appearance and subsequent spread of cytoplasmic and infectious factors. Apart from the HET-s and the Crippled Growth determinants of Podospora anserina , their molecular nature and their roles remain unknown. HET-s is a prion [ 15 ] and the Crippled Growth determinant seems to result from a positive autoregulation of a signal transduction cascade [ 16 ]. The widespread recognition of these infectious factors in fungi is probably due to the ease with which they are detected. The syncytial structure of the mycelium facilitates the propagation of factors from cell to cell. Usually, the presence of the infectious element results in a modification of thallic characteristics, such as fertility or morphology, and is thus easily scored visually as sectors in which the mycelium displays different properties. In the filamentous ascomycete Nectria haematoccoca , two bistable phenomena have been described [ 17 ]. N. haematoccoca is the teleomorph of Fusarium solani , a fungus encountered throughout the world as both saprophyte and pathogen. N. haematoccoca produces naphthoquinones exhibiting biological activities. Production of naphthoquinones is regulated by genetic and environmental but also epigenetic factors. The thallus of this species, observed just after ascospore germination, is a dense, grayish aerial mycelium, called Normal. Two kinds of morphological modification (the Anneau and the Secteur) frequently and randomly appear in the growth margin of the thallus as small brown areas in which hyphal elongation is reduced and secretion of pigments is drastically increased (see Figure 1A for the development of the Secteur). Once initiated, the modifications spread and progressively invade the margin of the culture, with a speed that dictates their form (20 times the hyphal elongation speed for the Anneau and twice for the Secteur). The new growth forms can be perpetuated with large pieces of mycelium excised from the growing margin of affected mycelia. The resulting modified subcultures, called ZiS (from a Secteur) and ZiA (from an Anneau), grow slowly and are pigmented in brown. However, fragmentation of a modified culture permits the restoration of the Normal morphology in a variable proportion of subcultures [ 18 ], showing that ZiS and ZiA cultures are probably mosaics of infected and uninfected hyphae. Each modification can be specifically transmitted to Normal cultures by contamination experiments, as shown in Figure 1C for Secteurs. The tangential propagation of the new growth forms is thus due to the transmission through hyphal fusion (anastomoses) of specific infectious cytoplasmic determinants, called σ for the Secteur and α for the Anneau. Mutagenesis experiments of wild-type conidiospores demonstrated that both the Secteur and the Anneau are under the control of nuclear genes [ 19 ]. In these early mutageneses, several kinds of mutation were detected. Five mutations prevent the expression of both the Secteur and Anneau, either spontaneously or after inoculation. They differed from wild type in producing more aerial mycelium, lacking pigmentation, and suppressing the sexual stage through self-fertilization. They mapped to at least four loci. Since this type of mutation prevents the generation of both infectious factors, they are now designated nas mutants (for 'no Anneau or Secteur'). Several mutations that specifically prevent the formation of Anneaux were also selected [ 19 ]. The two different types of mutations recovered, a and a *, suggested that the Anneau is under the control of a unique but complex locus. All a and a * mutations map to the same locus, Ans (for 'Anneau-specific'). Mutants carrying the a mutations are unable to generate the α factor, since they never present Anneau morphology and cannot be infected by that factor. Mutants carrying the a * mutations never show Anneaux, spontaneously or after contamination, but display a red color. Surprisingly, when used as donor in contamination with the wild type as recipient, these mutants are able to trigger Anneaux in 100% of attempts, showing that these a * mutants carry the α factor constitutively. It is noteworthy that the phenotype of a * mutants suggests that the mere presence of this factor is sufficient to promote a red color but is insufficient to alter growth. To date, only one mutation that specifically prevents Secteur formation has been described [ 18 , 19 ]. This s * 789 (formerly 789) mutant acts similarly to a * mutation in that it entails a red pigmentation (Figure 1B ) and specifically prevents the expression of the Secteur, although it possesses the σ determinant throughout the thallus. This property is shown in Figure 1C , by the ability of small inocula harvested in the red s * thallus to induce Secteurs on growing recipient mycelia lacking the σ determinant. Because of the similar properties of Anneaux and Secteurs, we decided to screen for more mutations that specifically prevent Secteur formation, to determine if s mutations (i.e., a mutation that specifically prevents the generation of σ) could be obtained. To this end, we developed novel mutagenesis procedures permitting the recovery of mutations that specifically prevent Secteur development. Most were nas mutations. However, a few s * alleles and two s alleles ( s 1 and s 2 ) were obtained. Genetic analysis suggested that the σ factor, like the α factor, is under the specific control of a single complex genetic locus. Molecular analysis of the s 2 allele, obtained by insertional mutagenesis, permitted the cloning and characterization of the Ses locus. As expected from the genetic data, the locus is complex and encompasses two linked genes, one of which has similarity with putative esterase/lipase/thioesterase enzymes. These data provide evidence that two linked genes could generate a bistable differentiation. Results Selection and genetic characterization of mutants affected in the expression of the Secteur phenomenon To increase the number of mutants affected in Secteur expression, we decided to use a strategy based on the recovery of fast-growing sectors after mutagenesis of the slow-growing ZiS cultures (see Methods; Figure 2 ). We recovered 354 independent mutants (Table 1 ), with a large majority of nas mutants (97%). Eleven mutants were specifically affected in Secteur expression. Ten exhibited an s * phenotype identical to that of the s * 789 strain. One mutant, s 1 , had a wild-type phenotype, except that it was unable to express the Secteur, spontaneously or after contamination tests (Figure 1D ). Genetic analysis of the mutants defines a complex locus involved in Secteur expression The s 1 mutant and five s * mutants were initially crossed with the I 4 mod reference strain. All behaved as single mutants, with about 50% wild type and 50% mutant type in the progeny (data not shown). In some progeny, the s * and s 1 mutations were recombined with the I 4 mod markers. These strains were kept for further crosses. Crossing s 1 with s * 789 or crossing the new s * mutants with s 1 and with s * 789 yielded progeny that were mostly segregants, with the parental phenotypes in a ratio 1:1 and few segregants with the wild-type phenotype. Their frequency ranged from 0.1 to 0.6% of the progeny (Table 2 ), indicating that mutations affecting the Secteur were closely linked. In order to determine dominance/recessivity relationships of the mutated and wild-type alleles, forced heterokaryons were produced by pairing some mutants and wild-type strains marked with auxotrophic mutations (see Methods; Table 3 ). The s 1 /+, s * 789 /+, and s * 84 /+ prototrophic mycelia were grayish and able to differentiate Secteurs, as did the control heterokaryon, which carried only the auxotrophic markers. Thus, the wild-type allele was dominant over its mutated counterparts. Combinations of s * mutants with s 1 gave rise to heterokaryotic wild-type mycelia, indicating that complementation occurred. In contrast, no complementation was observed in pairings involving two different s * alleles. The simplest interpretation of these results is that s 1 and s * mutations could affect two different linked genes or two separate domains of a multifunctional protein encoded by a large gene. However, due to the low representation of heterokaryotic cells (about 10%) determined in previous studies [ 20 ], one must carefully interpret these data, deduced from the characteristics of the prototrophic heterokaryotic mycelium. Insertional mutagenesis identified the Ses locus Since the s 1 mutant allele appears recessive to the wild type in balanced heterokaryons, we tried to clone the Ses locus by complementation using the sib selection strategy [ 21 ]. Although two different cosmid banks, XSG and XN (see Methods), were used, none of the tested transformants exhibited Secteurs. As an alternative strategy, we therefore used insertional mutagenesis, which can rapidly lead to the cloning of the relevant gene. Transformation with a plasmid that carries a hygromycin B resistance marker was performed to identify new mutants affected in Ses . However, because the contamination tests necessary for this screen were labor-intensive and time-consuming, we preferred the 61a 1 strain as a recipient for transformation, since it expressed Secteurs very early, and at high frequency, and never expressed Anneaux [ 22 ]. As illustrated in Figure 3A , the majority of transformants grown for 15 days at 18°C differentiated Secteurs, so that few transformants had to be tested by contamination experiments for their Secteur expression. During the course of these experiments, we also screened transformants harboring a variation in colony morphology or pigmentation (Figure 3B ). These phenotypes could be maintained from conidia isolation, showing that the transformation procedure was an effective approach in the creation of mutants. Ten transformants among the 5000 recovered failed to express the Secteur. Nine exhibited a nas phenotype. One was probably affected in the Ses locus, as it was unable to differentiate Secteurs, either spontaneously or after contamination tests. This transformant, called s 2 , had a wild-type morphology and behaved as did the s 1 mutant previously isolated. The s2 transformant carries a DNA fragment integrated in the Ses locus In order to prove that s 2 carries integration in the Ses locus, we crossed it with the wild-type (wt) and s 1 strains. When crossed with wt, the 100 tested ascospores segregated 1:1 for ability:inability to differentiate Secteurs. As expected, hygromycin B resistance always cosegregated with the inability to differentiate Secteurs. When s 2 was crossed with the s 1 strain, only seven ascospores among 1657 were unable to express the Secteur (Table 2 ), indicating that s 2 also mapped at the Ses locus. Overall, the data strongly suggested that s 2 resulted from a single insertion at the Ses locus. To establish the integration pattern in s 2 , Southern blotting analysis was performed after digestion by Cla I, which did not cut the plasmid, and by Bam HI, which cut once in the vector. The probe was the pAN7-1 vector used for insertional mutagenesis. As shown in Figure 4A , the number and intensity of hybridizing bands in Cla I digest reflected a complex integration event, with at least two integrated copies. Southern blot analysis of 10 s progeny from an s 2 × wild-type cross did not show segregation of the two integration sites (data not shown), suggesting that the two integrated copies were linked. The size of the larger Cla I-fragment, LI, was compatible with an entire copy of the vector, whereas the smaller, SI, could be interpreted as a truncated copy. Further analyses with other restriction enzymes and probes (data not shown) established the restriction map of this region (Figure 4B ). The sequence of a region flanking SI revealed that both LI and SI occurred at the same genomic site and were separated by a DNA fragment of unknown origin (Figure 4B ). Molecular cloning of the Ses locus The restriction enzyme Bam HI was used to recover the genomic sequence flanking LI (Flank1 in Figure 4B ) along with part of the integrated pAN7-1 vector. A part of Flank1 was then used as a probe to screen the XN cosmid library. One hybridizing cosmid, XN31E6, was identified and used to transform the s * 789 , s * 18 , s * 27 , and s * 4 mutants. Most of the transformants recovered the ability to express the Secteur, showing that the s * mutations are probably recessive. However, different phenotypes were observed (Figure 5 ). The 'mild S' exhibited the Secteur altered in its propagation and maintenance, and the 'S → s*' showed an s* phenotype beyond the Secteur. The mild S was interpreted as having a reduced amount of σ in the modified areas because of insufficient expression of the transgene, and the S → s* type was probably due to transgene sorting. Indeed, wild-type and s * nuclei could be recovered through the isolation of microconidia in such transformants, before expression of a Secteur, indicating that the S → s* thalli had a heterokaryotic structure. After the development of a Secteur, only the s * cells that were not affected in their growth in the presence of σ could grow, as previously observed for balanced heterokaryons [ 20 ]. Interestingly, we also observed several transformants displaying an s phenotype (Figure 5 ). These might have resulted from an abnormal integration inactivating the Ses locus. Molecular analysis of five hygromycin-resistant (Hyg R ) transformants (four with a wild-type phenotype, and one with a mild-S phenotype) revealed two patterns of integration (Figure 6 ). The pattern exhibited by the four wild-type transformants was wild type, except for an additional band corresponding to the pMoCosX vector. These transformants were thus interpreted as having integrated one copy of XN31E6 at the resident Ses locus. The mild-S transformant pattern was more complex, showing additional bands and a difference in fragment stoichiometry, suggesting a complex integration. This is consistent with a reduced amount of σ hypothesized for mild-S transformants. It is noteworthy that despite several attempts, transformation experiments done with the s 1 mutant as a recipient did not yield any transformants able to express the Secteur. This suggests that, contrary to the observations in balanced heterokaryons, s 1 is dominant in partial diploids. Dominance of s 1 was indeed established through transformation (see below). This dominance in diploids explains the failure to clone Ses by complementation. In order to further define the DNA fragment complementing the recessive s * mutation, cosmid XN31E6 was subcloned into pBluescript and the plasmids were assayed for complementation. This yielded psecX5, a plasmid carrying a 5.5-kb Xho I fragment sufficient to confer Secteur expression (Figure 7 ) with the same efficiency as did XN31E6. Gene organization of the Ses locus A 9-kb-long region surrounding the integration site in the s 2 strain was sequenced (GenBank Accession no. AY572411). One interesting feature of the sequenced region concerned the presence of several inverted repeats ranging from 32 to 290 bp and organized in a symmetrical fashion (Figure 7 ). Inspection of the sequences revealed four open reading frames (ORFs) that were either larger than 200 amino acids or showed significant similarity with proteins in the databases (Figure 7 ). To begin with, we found an ORF encoding a putative large protein of unknown function that is also detected in the complete genome sequences available for the other filamentous ascomycetes (those of Neurospora crassa , Magnaporthe grisea , F. graminearum , Aspergillus nidulans , Aspergillus fumigatus , and P. anserina ). This protein, NhHET-E-like, has a weak similarity (23% identity and 39% similarity over 455 amino acids) to the HET-E protein of P. anserina, which has been shown to be involved in heterokaryon incompatibility [ 23 ]. On the other side of the insertion site, a partial ORF of 165 amino acids carrying a PROSITE (PS00061), short-chain alcohol dehydrogenases/reductases family signature, was detected and designated ADHS. Two additional ORFs, SesA and SesB , were also identified. Functional analysis revealed that only these two ORFs were part of Ses, each having a different role. SesA is a 210-codon ORF (Figure 7 ) with no homologue in the genomes of N. crassa , M. grisea , A. nidulans , or A. fumigatus . However, it is significantly similar (30% identity and 42% similarity) to the N terminus of a large putative protein of P. anserina of unknown function but with 46% identity and 60% similarity with the Het-E protein in its C terminus (Figure 8A ). It is also similar to two ORFs, of 214 and 201 codons, present in the genome of F. graminearum , with 41% identity and 54% similarity over 197 amino acids and 32% identity and 49% similarity over 199 amino acids, respectively (Figure 8A ). SesA is interrupted by pAN7-1 in the s 2 transformant, and sequence analysis of SesA in the s 1 mutant showed a mutation at the end of the coding sequence, which changes a glycine into a glutamic acid (Figures 6 , 7 , 8A ). SesA was expressed because a 480-bp-long RT-PCR product was obtained by using the 3' RACE (rapid amplification of cDNA ends) procedure. The sequence of this product revealed that a polyadenylation signal existed 141 bp downstream from the SesA stop codon. SesB , a 386-codon ORF (Figure 7 ), is located on the opposite strand from SesA . SesB shows significant similarity with several putative proteins from filamentous ascomycetes (at least three in A. fumigatus and A. nidulans , six in F. graminearum, two in N. crassa , and four in M. grisea and P. anserina ) and animals ( Caenorhabditis elegans , Drosophila melanogaster , or mammals). It does not show similarity with hemiascomycetous yeast ORFs ( Saccharomyces cerevisiae and 12 other partially sequenced yeasts), basidiomycete ORFs ( Coprinus cinereus , Ustilago maydis , and Phanerochaete chrysosporium ), or Arabidopsis thaliana ORFs. All the proteins similar to SesB show a significant PROSITE (PS50187) esterase/lipase/thioesterase active site serine domain. The sequence of SesB in s 1 , s * 789 , s * 4 , s * 27 , and s * 18 revealed that in the four s * mutant alleles, SesB contains a single point mutation (Figures 7 and 8B ), but no mutation in the s 1 mutant. In s * 789 , s * 18 , and s * 4 , the mutations are missense mutations, and in s * 27 , the mutation corresponds to a one-base addition resulting in a frameshift 120 bp upstream of the stop codon. None affected highly conserved residues of the esterase/lipase/thioesterase domain, suggesting that a functional protein was expressed in the mutants. The expression of SesB was also investigated with the 3'-RACE procedure. A 370-bp-long RT-PCR product was obtained, confirming that SesB is expressed. Sequencing showed that a polyadenylation signal is used 81 bp downstream from the SesB stop codon. Downstream of SesB is another potential short ORF (ORF-C), encoding a putative peptide of 157 amino acids with no homologue in the databanks. To show that ORF-C is not an exon of SesB , we cloned into pBluescript the 2.4-kb-long Sma I fragment carrying only SesB , i.e., without ORF-C or SesA . This yielded plasmid psecSm24 (Figure 7 ). Its transformation in four different s * mutants showed that the insert restored the expression of the Secteur. The molecular analysis of transformants showed that the integration was ectopic (data not shown), supporting the hypothesis that SesB alone is per se a functional gene involved in Secteur development. Since homologues of both SesA and SesB are present in the genomes of F. graminearum and P. anserina , we investigated whether the gene arrangement was conserved in these two species. In P. anserina, for which a single SesA homologue is found, the gene arrangement is not conserved, since SesA and SesB homologues are on two different contigs. In F. graminearum , the putative 201-amino-acid homologue of SesA that displays the lowest percentage of identity is not associated with any of the SesB homologues. On the contrary, the 214-amino-acid homologue of SesA that displays the highest identity is associated with a SesB homologue in the same order (Figure 8C ). This homologue is highly conserved between N. haematococca and F. graminearum (79% identity and 85% similarity over 387 amino acids) whereas the other F. graminearum homologues are less conserved (40% identity and 63% similarity over 273 amino acids for the next-best homologue). In F. graminearum , the inverted repeats 1, 2, and 3 are absent but the inverted repeat 4 is present. Overall, these data suggest an evolutionary conservation of Ses between N. haematococca and F. graminearum , both of which are in the genus Fusarium , but with a lack of conservation of the gene organization in more distant species, including the loss of SesA . There are no data concerning the potential development of Secteur in the F. graminearum strain used by the Fungal Genome Initiative for sequencing. s1 is dominant in diploids To investigate the dominance of s 1 , we co-transformed the wild-type strain with pSec3-s 1 and pBC-Hygro. pSec3-s 1 was obtained by cloning into 'pGEM-T easy' (Promega, Charbonnières, France), a PCR amplification product constructed with oligonucleotides im317 and ip2393c (see Figure 7 ) using the s 1 mutant genomic DNA as template. Thus, pSec3- s 1 contained the entire Ses locus present in the s 1 mutant strain. Among 17 tested Hyg R transformants, seven could not differentiate Secteurs. Stu I-restricted DNA from five of these transformants was analyzed by Southern blotting. Two integration patterns were observed (Figure 9 ). For three transformants, the expected wild-type Stu I fragment was absent, suggesting that integration altered the Ses locus, thus accounting for the lack of Secteur formation. For the two other transformants, the wild-type Stu I fragment was present, as was an additional band larger than 15 kb. As this band hybridized with psec3-s 1 and the hph hygromycin resistance marker (data not shown), these transformants could be interpreted as bearing a co-integration of pBC-Hygro and pSecs 1 at an ectopic position. Sequencing of the Ses locus in these two transformants that do not display Secteurs confirmed the presence of both alleles, i.e., the wild-type allele at the resident locus and the mutated allele s 1 at an ectopic position. This clearly demonstrated the dominance of the s 1 mutation, in contrast to the s * mutations, which are recessive. Discussion Although the Secteur and Anneau phenomena were described about 30 years ago [ 17 ], the molecular mechanisms able to generate these fascinating bistable differentiations are still mysterious. Early studies suggested peculiar epigenetic mechanisms [ 24 ]. In this study, we have initiated the molecular characterization of Ses , the primary locus controlling the development of Secteurs. The impact of mutagenesis procedures The experimental design, based on the differences in the growth rate between modified and normal cells, was very efficient in finding mutations that block the propagation of Secteurs after the action of both UV and NG ( N -methyl- N '-nitro- N -nitrosoguanidine). A vast collection of mutants affected in the Secteur expression was easily obtained. One mutant with an s phenotype was isolated, along with 11 s * mutants. Apparently, NG ( N -methyl- N '-nitro- N -nitrosoguanidine) mutagenesis was more efficient than UV mutagenesis in recovering these specific mutants (9/105 and 3/250, respectively). Genetic analysis showed that the structure of the Ses locus mirrors the structure of the Ans locus, indicating that α and σ could be generated through similar mechanisms, in agreement with the fact that both factors require the same set of nas genes for propagation. Relationships between s1 and wt alleles: recessivity in heterokaryons versus dominance in partial diploids Dominance/recessivity tests using balanced heterokaryons showed that s 1 /wt heterokaryons were able to differentiate Secteurs as wild type. The recessivity of s 1 , deduced from the heterokaryon tests was the initial point of our cloning strategy, i.e., the use of cosmid libraries from wild type to restore the ability to express the Secteur in an s 1 recipient strain. The screening of two representative cosmid libraries failed, and we examined various hypotheses to explain this failure, especially the possibility of the dominance of s 1 . In order to easily clone the Ses locus, we used an insertional mutagenesis strategy, a powerful method for gene isolation in filamentous fungi [ 25 ]. With the pAN7-1 vector, 5000 Hyg R transformants were screened for defects in mycelium pigmentation, colony morphology, and the expression of the Secteur and around 4% of mutant phenotypes were detected. This frequency is similar to the 0.4 to 1.4% reported for loss of pathogenicity in different fungal species [ 25 ]. Among them, 9 nas mutants and 1 s mutant were obtained. Given the proportion observed for classical mutagenesis (12 s * or s mutants among 355 nas ), the recovery of the s 2 mutant was an unexpected outcome. Although we may have been lucky, the recovery of this transformant may reflect a preference for plasmid integration in the region of the Ses locus, which is compatible with the high recombination frequency observed at Ses . Cloning of Ses permitted the construction by transformation of a partial diploid containing both the wild-type and s 1 mutant alleles. The fact that this partial diploid has a s phenotype indicates that s 1 allele is indeed dominant over the wild-type allele in partial diploids. Similar contradictions have been observed in A. nidulans by comparing diploids and heterokaryons for complementation between mutations in the regulatory and the cognate structural genes. These data were interpreted as being due to a limitation of regulatory gene products to the nucleus or by a stringent dose effect when combined with a nonrandom distribution of nuclei in heterokaryons [ 26 , 27 ]. In our study, a dose effect is also probable. In N. haematococca , as reported earlier [ 20 ], only 1–10% of hyphal fragments containing 3–4 cells are heterokaryotic, the others corresponding to both homokaryons in similar proportions. In addition, phase-contrast microscopic observation of the prototrophic mycelia revealed the presence of rows of uninucleate cells disrupting the heterokaryotic association. This structure does not prevent the stability of balanced heterokaryons with regard to metabolic requirements (hence the complementation of the auxotrophic mutations), but might severely affect the dosage of the SesA products expressed from the wild-type and s 1 nuclei in different portions of the thallus. Because s 1 is dominant and corresponds to a missense mutation, it is likely that the product expressed from SesA in s 1 is a dominant negative. If its concentration is insufficient, especially in hyphae homokaryotic for wild-type SesA nuclei, the propagation of σ and Secteur formation is favored. In contrast, in diploids an even ratio of the two products is always achieved, preventing propagation of σ and Secteur formation. Integrated model of functional elements at the Ses locus The molecular characterization of Ses shows that it is composed of two linked and expressed genes, SesA and SesB , both of which are necessary for Secteur expression. Each has a different role. The s 1 and s 2 mutants map to SesA . Because s 2 is an integration of a large segment of DNA at the beginning of SesA, the phenotype of the s 2 mutant probably results from a complete loss of function of SesA . The s 1 mutant carries a dominant missense mutation and therefore synthesizes the SesA mRNA, and probably a dominant negative protein. The SesAp protein has no evident homologue in the databanks yielding a clue to its function. As s 2 does not produce the σ determinant, cannot be contaminated by mycelia carrying σ, and never differentiates the Secteur morphology, SesA is probably necessary for the production and transmission of σ. All s * mutations map to SesB and determine a red-pigmented phenotype associated with the generation of the σ determinant throughout the thallus, but without any growth alteration. It is noteworthy that all the s * mutations are probably not simply preventing the production of a functional mRNA, but are also not preventing the production of an active protein, as they map outside the evolutionarily conserved region of the protein. The function of SesB and its homologue remains unknown in fungi; however the inactivation by RNA interference of the most similar gene in C. elegans is lethal during embryogenesis, suggesting that the protein produced by SesB could be essential (accession NP_510177; [ 28 ]). Based on the analysis of the mutant phenotype triggered by s * mutation, the wild-type SesB product is involved in the repression of pigmentation and σ generation. To date, this situation has not been described for any of the previously reported systems responsible for bistable or multistable switches in fungi. Previous systems implicated prions [ 23 , 29 ], chromatin silencing [ 12 ], hysteresis in a MAP kinase cascade [ 16 ], and possible membrane inheritance [ 30 , 31 ]. At present, it is premature to propose a molecular model to explain the Secteur, because SesA and SesB display weak similarity only with proteins of unknown function. However, from our data we can infer that SesA most likely encodes a regulatory factor for SesB and that the regulation probably takes place at the protein level and probably not at the RNA level, since s 1 and all s * mutation are point mutations that are not likely to affect RNA transcription and stability. Two formal models could explain how the regulation might work. Firstly, the product of SesA (SesAp) could exist in two states: one, A N , characterizing the Normal morphology and the other, A S , determining the Secteur morphology (Figure 10A ). The transition A N to A S may be initiated by a rare event in cells of the growing margin of the thallus. Once formed, the A S state becomes predominant by directing other A N molecules to adopt the same state. This positive feedback loop allows A S propagation from hyphae to hyphae through anastomoses. A S alone would induce the hyperproduction of pigments (hence the absence of both σ and pigmentation in the s mutants, as they are mutated in SesA ). In addition, the product of SesB (SesBp) can adopt the normal B N state, which can be transformed into a B S state in the presence of A S . B S would be responsible for the growth alterations observed in the Secteur and would follow the propagation of A S (hence the lack of growth impairment presented in the s * mutants, as they are mutated in SesB ). In the second model, SesAp may negatively regulate SesBp but also be negatively regulated by SesBp (Figure 10B ). In the normal mycelium, SesBp, which probably has a catalytic activity, would be active in promoting healthy growth. The appearance in some cells from the growing margin of a sufficient amount of SesAp would displace the equilibrium, resulting in the inhibition of SesBp. In order for this to happen, the equilibrium constants must be in favor of SesAp. This would result in growth impairment (because SesBp would not be present) and in a red pigmentation (because SesAp would be present). In the s mutants, SesAp would never be present, thus making the presence of SesBp constitutive (hence the absence of Secteurs and the healthy growth). In the s * mutant, the interactions between the two proteins would be abolished, permitting the activity of both SesAp and SesBp (hence the presence of a constitutive σ, the red pigment, and healthy growth). This model could explain the dynamic equilibrium found in the ZiS area, as well as the dose effect for SesAp, explaining the difference of heterokaryons and partial diploids. Conclusions Secteur, one of the two bistable and hysteretic differentiations exhibited by the filamentous fungus N. haematococca , is controlled by a complex, two-gene locus. Each gene has a distinct role in defining bistability, and atypical regulatory relations between the two proteins coded by the two genes may account for the hysteresis of Secteur differentiation. The data exemplify the diversity of mechanisms that generate differentiation in fungi, and, more generally, in eukaryotes. Methods Fungal strains and growth conditions The homothallic N. haematococca strain wt (Centraal Bureau voor Schimmelcultures, Baarn, The Netherlands) was used as the standard wild-type strain in this study. The origin and relevant characteristics of all strains used in this study are listed in Table 4 . The a 1 s 1 I 4 mod and 61a 1 strains used as recipients in transformation experiments were constructed by crossing the s 1 I 4 mod strain with a 1 mutant and the 61 mutant with a 1 I 4 mod strain, respectively (unpublished data). The marker segregation was recorded after three weeks. This included (1) mycelium and perithecium pigmentation, (2) fertility, and (3) the ability to express the Secteur and the Anneau as tested by transferring the progeny onto potato dextrose agar (PDA) and by inoculating 3-day cultures with s* 789 (for Secteurs) and a* 58 (for Anneaux). General culture conditions and manipulations were as described by Daboussi-Bareyre [ 20 ]. Strains were purified through microconidia and maintained on PDA at 26°C. Long-term stocks were stored as plugs under mineral oil at 12°C. The medium selective for transgenes was PH8, i.e., PDA containing 8 μg/ ml of hygromycin B from Sigma-Aldrich (Saint Quentin Fallavier, France). Mating and ascospore recovery The general methods for crossing the homothallic N. haematococca have been described elsewhere [ 19 , 32 ]. Since the strains used in this study were homothallic, detection of hybrid perithecia in crosses were performed using as a partner in crosses the double mutant strain I 4 mod. This strain developed white, self-sterile perithecia whereas wild-type and fertile mutants developed self-fertile, red perithecia [ 32 ]. Thus, all the white, fertile perithecia, which appeared on the crossing plates, were hybrid. The progeny of crosses was analyzed in accordance with the following procedure: two to nine white, fertile perithecia from each cross were freed from mycelium and conidia. Each was opened to spread the ascospores on one Petri dish containing water plus 3% agar. To control viability, 35 ascospores from each perithecium were transferred to PDA and incubated for 4 days at 26°C, while the water-agar stock dishes were kept at 2°C to prevent ascospores from germinating. Then, the water-agar dishes containing many viable ascospores (usually those with more than 70% of germination were selected) were returned to 26°C to allow germination overnight. A sample of about 400 germinating ascospores from each dish was transferred to PDA. The phenotypes were recorded after a week at 26°C in the dark, except for the perithecium color, which was evaluated after an additional period of two weeks. Heterokaryon test Heterokaryons were constructed as described in [ 20 ]. Initially, strains s 1 , s* 84 , and s* 18 were crossed with the two strains carrying either of the markers, arg 154 and lys 255 , that promote auxotrophy for arginine and lysine, respectively. Auxotrophic marked strains, which were recovered in the progeny, were paired on a cellophane membrane in the combinations appropriate to restore prototrophy. After 48 hours of growth on complete medium, the membrane was transferred to minimal medium. Widely inclusive inocula from prototrophic mycelia observed at the junction of the two partners were transferred to minimal medium and examined for their pigmentation and their ability to express the two modifications, either spontaneously or after inoculation. Standard mutagenesis Plugs taken from the growing margin of a culture modified by the Secteur were inoculated on cellophane discs on PDA and grown for 4 days at 26°C. The modified slow-growing cultures (ZiS) were submitted to mutagenesis by UV or NG. For UV mutagenesis, cultures were exposed at 450 J/m 2 , with a UV light source (254 nm), and then kept in the dark for 72 hours. For NG mutagenesis, 0.1 ml of a 200γ/ml solution of NG was deposited under the cellophane disc. After 1 hour, the treated cultures were exposed to light for NG degradation. Fast-growing sectors were clearly visible a week after mutagenesis. For the estimation of the number of sectors recovered from each treated thallus, only sectors harboring different phenotypes were considered. A plug of these independent sectors was inoculated on PDA and the resulting cultures were examined for pigmentation and ability to express the Secteur and/or the Anneau at 26°C. The majority of the recovered mutants corresponded to nas mutants, defined by (1) the inability to differentiate both Anneaux and Secteurs, (2) an exuberant white mycelium, and (3) the inability to differentiate perithecia. Some of these mutants could express the modifications at other temperatures, as was previously observed for mutants 727 and 100 [ 33 , 34 ]. s * mutants were recovered as red, fast-growing sectors. They displayed the same properties as the s * 789 mutant described previously [ 19 ], i.e., red thallus and inability to express the Secteur spontaneously or after inoculation. A unique s mutant was selected as a wild-type-growing sector. This mutant displayed a wild-type phenotype, except for the inability to express the Secteur spontaneously or after inoculation. Both s * and s mutants could differentiate Anneaux. Insertional mutagenesis Plasmids pAN7-1 (GenBank accession number Z32698) or pBC-Hygro [ 35 ], which had no sequence similarity with the N. haematococca genome, were used to transform the double mutant strain 61a 1 . Both vectors carried a hygromycin resistance gene. Transformation occurred at a frequency of about 10 transformants/μg plasmid. Southern analysis on 10 independent hygromycin-resistant transformants (Hyg R ) indicated that the transforming DNA inserted generally at one or two genomic sites, in some cases in a tandem fashion (data not shown). This pattern of integration was suitable for recovery of tagged genes. To screen for mutant phenotypes, 5000 Hyg R independent transformants were transferred to PH8 (12 per Petri dish) and grown for 15 days at 18°C, a temperature that increased the frequency of spontaneous Secteur formation. Thalli with mutant phenotypes were frequently recovered (Figure 3 ). These most likely resulted from the plasmid integrations, since a sample of regenerating protoplasts treated in the same way but without the transforming DNA did not show any phenotypic variation. As control, a sample of transformants with an altered morphology was purified through single conidial isolation. Data showed that the mutant phenotype was stable. Potential candidates affected in the expression of the Secteur were recovered as thalli that did not form spontaneous Secteurs. Inoculation experiments were used to confirm the mutant phenotypes. Transformation procedure Protoplasts were prepared as described in [ 36 ], with the following modifications. Petri dishes containing 25 ml of a solid PDA medium covered with a cellophane disk were inoculated with 5×10 6 spores and incubated for 20 hours at 26°C. Mycelia were collected (0.2 g/10 ml) in a lysis buffer (1.2 M MgSO 4 , 10 mM sodium phosphate, pH 5.8, 10 mg/ml Glucanex (Novozymes, Bagsvaerd, Denmark), 10 mg/ml mutanase (Interspex Products, San Mateo, CA, USA), and incubated for 2–3 hours at 26°C with gentle agitation. Protoplasts were separated from cell debris by addition of 5 ml of ST buffer (0.8 M Sorbitol, 100 mM Tris-HCl pH = 7.5) and centrifugation at 2000 g for 10 min. The protoplasts collected at the interface of the two solutions were harvested by centrifugation at 750 g for 5 min, washed twice in ice-cold buffers, once in ST and then in STC (0.8 M Sorbitol, 50 mM CaCl 2 , 100 mM Tris-HCl pH = 7.5; [ 36 ]). They were resuspended in 4/5 STC, 1/5 50% PTC buffer (50% PEG 3350 [Sigma-Aldrich], 100 mM CaCl 2 , 100 mM Tris-HCl, pH 7.5) at a final concentration of 5–10 × 10 7 protoplasts/ml and kept on ice. For transformation, 5 μg or 10 μg of DNA suspended in a maximum of 50 μl TE buffer (10 mM Tris-HCl, pH 7.5, 1 mM EDTA) were mixed gently with 100 μl protoplasts and placed on ice. After 30 min, 900 μl of PTCS buffer (50% PTC containing 0.8 M sorbitol) was added and incubation continued at room temperature for 30 min. Aliquots of the protoplasts were mixed with 2.5 ml molten (37°C) top PDAS (PDA with 0.8 M sucrose and 0.3% w/v agar), and overlaid onto 30 ml of selective medium (PDAS containing 8 μg/ ml of hygromycin B. Plates were incubated at 26°C and colonies appeared within 2–4 days. Numerous small colonies stopped growing after 2–3 days. These were interpreted as abortive transformants. Only the colonies that grew after this delay were considered resistant to hygromycin. When co-transformation experiments were performed, 5 μg of the transforming plasmid was mixed with 5 μg of pBC-Hygro. DNA manipulation All the nucleic acid manipulations were performed using standard methods [ 37 ]. For Southern blot analysis, genomic DNA was extracted as described in [ 38 ]. The cosmid libraries were made in the pMoCosX vector as recommended by Orbach [ 39 ]. The library XSG was obtained with Xho I partially digested wt genomic DNA. Determination of gene representation in the XSG library was performed by estimating the number of clones containing conserved genes ( NhNia encoding the nitrate reductase, NhHsp70 and NhHsp90 encoding molecular chaperones, NhTUB1 encoding β-tubulin, NhTEF1 encoding the translation initiation factor eEF1A) by PCR, Southern blot hybridization, or direct cloning using a complementation screen. Each tested gene was represented by 2 to 5 independent clones, indicating that the library contained at least four N. haematococca genome equivalents. Library XN was made with Sal I partially digested wt genomic DNA following the same protocol as for the XSG library. The sequence of the mutant alleles was performed on two independent PCR amplification products, obtained with oligonucleotides im317 (5'-TGATCAACCTCCACGCACAT-3') and ip2393c (5'-AAGGAGATATCGCGCAGGCT-3'). Identification of the 3' end of the SesA and SesB genes was done by 3'-RACE using the 5'/3' RACE kit (Roche Diagnostics, Meylan, France) on polyA + mRNA extracted from 2-day-old mycelium, using for SesA oligonucleotide ip238 (5'-AAGAGGCCGTGAGACAAGAG-3'), and for SesB ip974c (5'-CCAAGACGACCGATAGAAGA-3'). GenBank accession The genBank accession no. for cosmid XN31E6 sequences is AY572411. Authors' contributions SG performed all the experimental work and contributed to the interpretation of the data. PS and MJD performed part of the phylogenetic analysis, contributed to the interpretation of the data, and supervised the work. The writing of the manuscript was done in teamwork. All authors read and approved the final manuscript.

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555740

High-Temperature unfolding of a trp-Cage mini-protein: a molecular dynamics simulation study

Background Trp cage is a recently-constructed fast-folding miniprotein. It consists of a short helix, a 3,10 helix and a C-terminal poly-proline that packs against a Trp in the alpha helix. It is known to fold within 4 ns. Results High-temperature unfolding molecular dynamics simulations of the Trp cage miniprotein have been carried out in explicit water using the OPLS-AA force-field incorporated in the program GROMACS. The radius of gyration (Rg) and Root Mean Square Deviation (RMSD) have been used as order parameters to follow the unfolding process. Distributions of Rg were used to identify ensembles. Conclusion Three ensembles could be identified. While the native-state ensemble shows an Rg distribution that is slightly skewed, the second ensemble, which is presumably the Transition State Ensemble (TSE), shows an excellent fit. The denatured ensemble shows large fluctuations, but a Gaussian curve could be fitted. This means that the unfolding process is two-state. Representative structures from each of these ensembles are presented here.

Background Understanding the mechanisms behind protein folding, which is one of the most fundamental biochemical processes, is proving to be a challenging task for biochemists and biophysicists. Recent developments in instrumentation and methodology have enabled us to take major steps forward in comprehending the dynamics of proteins and peptides at the molecular level. Protein engineering methods such as Phi-value analysis [ 1 ] and various spectroscopic techniques such as NMR have made the task more practicable. Proteins are composed of two major secondary structural elements, helices and sheets, which, along with loops, pack together to form super-secondary and tertiary structures. Trp cage is a novel, and a highly stable, mini-protein fold. A 20-residue Trp-cage miniprotein has been designed [ 2 ]. It has the sequence NLYIQWLKDGGPSSGRPPPS. While residues 1–9 form an alpha helix, residues 10–15 form a 3,10 helix. W6 is caged by the C-terminal poly-proline stretch. D9 and R16 are involved in a stabilizing salt-bridge interaction. Molecular dynamics simulations, which make use of classical Newton mechanics to generate trajectories, are playing an ever-expanding role in biochemistry and biophysics due to substantial increases in computational power and concomitant improvements in force fields. In particular, the contribution of such studies to protein folding is immense [ 1 ]. As pointed out by Fersht and Dagget, molecular dynamics simulations are capable of unraveling whole protein folding / unfolding pathways [ 1 ]. Indeed, simulation techniques have been widely used for studying helices and sheets. Today, folding simulations of more-than-model peptides are being carried out on high-power computers. Despite being a new mini-protein construct, the Trp cage motif has attracted considerable computational analysis. Folding simulations of this protein in explicit water have been carried out using what is known as the Replica Exchange Method. A two-state folding mechanism has been proposed and free energy surfaces have been determined [ 3 ]. Moreover, a few folding simulations of have been carried out using implicit solvation models [ 4 - 6 ]. In this article, the results of a high-temperature unfolding simulation of the Trp-cage mini-construct are presented. Three separate structural clusters are identified: the close-to-native-state cluster, the intermediate cluster and the denatured ensemble. These clusters, considered in terms of their radii of gyration, are shown to be Gaussian ensembles. Structural features representing each of these ensembles are also illustrated. Results and Discussion Molecular dynamics simulations of the Trp-cage mini-protein construct (PDB ID: 1L2Y) were carried out using the OPLS-AA force-field incorporated in the freely available program, GROMACS. The simulations were carried out at 498 K, at which temperature the unfolding process is favored. This temperature provides a good description of the unfolding process, at least in respect of CI2 and the homeodomain of engrailed [ 7 ]. It is also much higher than the melting temperature determined by experiment (315 K) or through replica-exchange simulations (400 K) [ 3 ]. It can be seen that the RMSD (figure 1 ) of the evolving structure with reference to the starting structure increases rapidly in the first 40 ps, during which time the only structural change observed is denaturation of the 3,10 helix. This is followed by rapid unwinding of the second and third turns of the helix. While the third turn unwinds within 200 ps, the second turn remains intact for a little longer and remains visible until 250 ps. The first helical turn remains stable until about 800 ps after which it also denatures. During this time period W6 begins to move out of the cage that is formed by the prolines. The above listed processes are not adequately reflected by the time-evolution of the Rg (figure 2 ) and are all categorized as close-to-native-state ensemble. Representatives from this ensemble are shown in figure 3a and 3b . Figure 1 Time evolution of the root mean square deviation (nm) with reference to the starting structure. Figure 2 Time evolution of the radius of gyration (nm) After 800 ps, there is a jump in the values of both RMSD and Rg. The new value remains constant until about 3200 ps. This state is characterized by complete annihilation of the cage. The W6 is released from the Pro cage and becomes completely "solvent-exposed". It must be noted that the use of the term "solvent exposed" is not entirely appropriate in this context as there is no real change in the solvent-accessible surface area of the W side-chain. However, the point is that, this W is no longer protected by the proline cage. Native contacts are retained in the form of a salt-bridge between D9 and R16. Representatives of this ensemble are shown in figure 3c, d . In fact, the folding simulations carried out by Ruhong Zhou [ 3 ] point to an intermediate state characterized by the single salt-bridge interaction. This state, which is the only intermediate state observable, may be the transition state ensemble (TSE). This would mean that the unfolding process is two-stage and is the reversal of the folding process. In order to assess whether this state is indeed the TSE, lower temperature simulations at 293 K were performed. Eight structures were randomly obtained from this ensemble and the simulations were carried out for 5 ns on each of these structures. The progress of each simulation was monitored using Rg. The idea is that, at temperatures favoring the folding process, structures from the TSE roll down towards the native state with a probability of approximately 0.5, assuming a two-state process [ 1 ]. Of the eight simulations, three simulations showed a drastic fall in the Rg, indicating a collapse towards the native state. In a fourth simulation, there was a slight decrease in the Rg, which was not drastic, but still implying a fall towards the native state. In the other four simulations, a significant jump in the Rg was observed, indicating a tendency towards the unfolded conformation. These observations show that this ensemble is, most probably, the TSE. Figure 3 Representative structures from the folding pathway obtained after (A) 0 ps (B) 700 ps (C) 1000 ps (D) 2500 ps (E) 4000 ps (F) 5000 ps. Structures A and B belong to the first ensemble; C and D to the second and E and F to the third. Color code: Pro: Red; Trp: Blue; Asp: Green; Arg: Yellow After 3200 ps, a further jump in RMSD and Rg is observed leading to a state where these values fluctuate markedly. This highly disordered state, showing a measure of heterogeneity, is the denatured ensemble, in which the salt-bridge interaction that characterized the intermediate state is also lost. There is a significant jump in the distance between the Asp9 and Arg 16 sidechains after this time. As a result, there are no native contacts in this state. This is represented by structures in figures 3e and 3f . In this manuscript, I also discuss a new method for identifying sufficiently populated states during the course of an MD simulation. The idea is that each state is to a large extent topologically different from any other state and can be characterized by an approximately Gaussian distribution of the radius of gyration. This is to be expected because each state lies at a defined height in the free-energy well. In this simulation it can be observed that transitions from one state to another are characterized by a significant jump in the radius of gyration. The distribution of the radius of gyration was determined for each of the three states and for the entire time-evolving system. For each of the three ensembles and for the entire time duration, the distribution was calculated over the ranges of values shown in table 1 . It was found that Gaussian-like curves could be fitted for the three ensembles taken separately, while the distribution for the entire system was highly skewed (figure 4 ). The slight skew in the curve for the close-to-native state ensemble might be due to the inability to sufficiently demarcate the helix unwinding stages in the plot. Table 1 Rg range and time corresponding to each state seen in the simulation Ensemble Time (ps) Rg range (nm) Native 0–800 0.7 – 0.8 TSE 800–3200 0.72 – 1 Unfolded 3200–5000 0.8 – 1.4 Entire range 0–5000 0.7 – 1.4 Figure 4 Distributions of Radius of gyration for (A) Ensemble 1 (B) Ensemble 2 (C) Ensemble 3 (D) Entire range of structures. Conclusion High-temperature unfolding molecular dynamics simulations of a Trp cage miniprotein construct have been carried out. This has shown that the process is two-stage, akin to the folding process results [ 3 ]. The three ensembles, including the TSE, are shown to be Gaussian with respect to their Rg values. Methods The starting structures for the simulations were obtained from PDB 1L2Y [ 3 ]. The first three models were used to carry out the 5 ns simulations and similar results were obtained with each. Results presented here correspond to model 1. All simulations were carried out using GROMACS 3.2 [ 8 , 9 ], running on a single Fedora Linux system. The OPLS-AA force field was used. The peptide was solvated in a box containing approx. 500 water molecules [ 10 ]. Periodic boundary conditions were employed to eliminate surface effects. Energy minimization with a tolerance of 2000 kJ/mol/nm was carried out using the Steepest Descent method. All bonds were constrained using LINCS [ 11 ]. The system was loosely coupled to a temperature bath (at 498 K or 293 K) using Berendsen's method [ 12 ]. Berendsen's pressure coupling was used. Long-range electrostatics was handled using the PME method [ 13 ]. All potential cut-offs were set at 1 nm. The final MD simulations were carried out with a time-step of 2 fs and without any position restraints. All analyses were conducted using programs built within GROMACS. The RMSD values were obtained from a least square fit of the respective non-hydrogen atoms (main-chain and side-chain). The radius of gyration was also calculated for the whole protein minus hydrogens as an indicator of the compactness of the overall structure. The compiled DSSP [ 14 ], which was downloaded separately and run from GROMACS, was used to calculate secondary structure formation. Competing Interests The author(s) declare that they have no competing interests.

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549553

Deciphering structure and topology of conserved COG2042 orphan proteins

Background The cluster of orthologous group COG2042 has members in all sequenced Eukaryota as well as in many Archaea. The cellular function of these proteins of ancient origin remains unknown. PSI-BLAST analysis does not indicate a possible link with even remotely-related proteins that have been functionally or structurally characterized. As a prototype among COG2042 orthologs, SSO0551 protein from the hyperthermophilic archaeon Sulfolobus solfataricus was purified to homogeneity for biophysical characterization. Results The untagged protein is thermostable and behaves as a monomeric protein in gel filtration experiment. Several mass spectrometry-based strategies were combined to obtain a set of low resolution structural information. Kinetic data from limited proteolysis with various endoproteases are concordant in pointing out that region Glu 73 -Arg 78 is hyper-sensitive, and thus accessible and flexible. Lysine labeling with NHS-biotin and cross-linking with DTSSP revealed that the 35 amino acid RLI motif at the N terminus is solvent exposed. Cross-links between Lys 10 -Lys 14 and Lys 23 -Lys 25 indicate that these residues are spatially close and in adequate conformation to be cross-linked. These experimental data have been used to rank multiple three-dimensional models generated by a de novo procedure. Conclusion Our data indicate that COG2042 proteins may share a novel fold. Combining biophysical, mass-spectrometry data and molecular model is a useful strategy to obtain structural information and to help in prioritizing targets in structural genomics programs.

Background Genomic comparative studies on entirely sequenced genomes from the three domains of life, i.e. Bacteria, Archaea and Eukaryota [ 1 ], evidenced that proteins involved in the organization or processing of genetic information (structures of ribosome and chromatin, translation, transcription, replication and DNA repair) display a closer relationship between Archaea and Eukaryota than between Bacteria and Eukaryota [ 2 - 4 ]. To identify new proteins involved in such important cellular mechanisms, an exhaustive inventory of proteins of unknown function common to only Eukaryota and Archaea but not in Bacteria has been devised [ 5 - 7 ]. Among such proteins, the Cluster of Orthologous Group COG2042 comprises proteins ubiquitously present in Eukaryota and present in many, but not all, Archaea; a hallmark of their ancient origin. The corresponding ancestral protein should have been present in the common ancestor of these two domains of life. Some partial experimental data are known from the Saccharomyces cerevisiae COG2042 homolog. Deletion of the Yor006c gene was shown to result in a viable phenotype but some apparent moderate growth defects were noticed on a fermentable carbon source [ 8 , 9 ]. Two putative protein partners for Yor006c were identified through a high-throughput two-hybrid study [ 10 ]: Ydl017w, a serine/threonine kinase also known as the cell division control protein 7 (Cdc7), and Yil025c, a hypothetical ORF. However, the cellular function of COG2042 proteins remains unknown. A polar region, named RLI, is conserved at the N terminus of COG2042 proteins as well as at the N terminus of another cluster of orthologous proteins, namely COG1245. The latter, exemplified by SSO0287 in Sulfolobus solfataricus [ 11 ], are large proteins (about 600 residues) that encompass four different domains: a RLI domain, a [4Fe-4S] ferredoxin domain, and two ATPase domains, usually found in ABC transporter. Their putative function is currently subjected to discussion [ 12 , 13 ] but could be related to rRNA metabolism. Indeed, four of the eleven proteins shown to interact with the yeast COG1245 homolog (Ydr091c) were identified as involved in rRNA metabolism (Ymr047c, Ydl213c, Ylr340w, Ylr192c). Experimental data on the human homolog of Ydr091c indicated that this protein reversibly associates with RnaseL, and thus COG1245 proteins were named RNase L inhibitor [ 14 ]. Because knowledge of protein structure is of high importance to understand protein function, huge efforts have been recently invested in high-throughput protein structure determination programs [ 15 ]. Recent reports indicate that only a relatively small percentage of expressed and purified proteins are amenable to full 3D structure by NMR or crystallography and X-ray diffraction [ 16 , 17 ]. In silico modeling (homology modeling, fold recognition, ab initio and de novo modeling) is the alternative to quickly gain the fold of a protein. However, such approach sometimes remains ambiguous in reliably identifying correct structures for protein sequences remotely-related to those found in PDB database. A promising strategy is the use of experimental data (if possible easily obtained) for model discrimination or refinement [ 18 - 20 ]. For example, the tertiary structure of the bovine basic fibroblast growth factor (FGF)-2 was probed with a lysine-specific cross-linking agent and subjected to tryptic peptide mapping by mass spectrometry to identify the sites of cross-linking [ 21 ]. The low resolution interatomic distance information obtained experimentally allowed the authors to distinguish among threading models in spite of a relatively low sequence similarity (13 % of identical residues). Interestingly, the constant development of novel cross-linking reagents suitable for mass spectrometry [ 22 ] enables enrichment of cross-linked peptides facilitating such strategy. A chemical modification approach [ 23 - 26 ], in combination with limited proteolysis procedures [ 27 , 28 ], can also provide useful structural constraints [ 29 ] for model refinement. A step further is to attempt such approaches with proteins having no detectable homologs. In order to get insight into the topology of COG2042 members and if possible to use these experimental data to discriminate among structural protein templates, we combined limited proteolysis, lysine labeling and cross-linking strategies. The protein SSO0551 from the hyperthermophilic archaea Sulfolobus solfataricus was chosen as a prototype because of its thermostability and the probable absence of post-translational modifications when produced as a recombinant form in Escherichia coli . The SSO0551 protein is monomeric with a low molecular mass (19 kDa). This size is easily amenable to characterization by mass spectrometry. Our results reveal that the polar RLI motif at the N terminus is probably structured and solvent exposed, pointing at a common trait between COG2042 and COG1245 proteins, this latter group being also conserved in Eukaryota and Archaea but absent in Bacteria. The accessible and flexible regions defined by limited proteolysis combined with lysine accessibility assessed by NHS-biotin labeling and DTSSP cross-linking allowed us to discriminate among ten top ranking de novo three-dimensional (3D) models. Results COG2042 comprises members exclusively from Eukaryota and Archaea The sequence of SSO0551 from S. solfataricus was used as query in a PSI-BLAST database search to identify homologous proteins. A constant cutoff expectation value of 10 -15 resulted after three iterations in selection of 40 sequences (15 from Archaea and 25 from Eukaryota) that were all aligned over their full length. No close homologs (E-value below 10 -10 in the third iteration) with full-length sequence matching to SSO0551 were found among Bacteria. Remarkably, all completely sequenced Eukaryal organisms were found to have one SSO0551 homolog. Fig. 1 shows an unrooted phylogram of the updated COG2042 family (Fig. 1A ) and an alignment of a selection of six representative sequences (Fig. 1B ), selected on the basis of their phylogenetic distribution. When experimental evidences concerning the protein are unfortunately lacking for ORF description genome annotators usually take into consideration the most upstream initiation codon. For this reason, the most probable start codons of several open reading frames should be reconsidered after exhaustive alignment (Fig. 1 ). For example, atg codon starting at nucleotide 484790 on the Crick strand for SSO0551 from S. solfataricus (NC_002754) should be a more appropriate start codon than atg starting at nucleotide 484916 and mentioned erroneously in current database. From the unrooted phylogram (Fig. 1A ), two main lineages (archaeal and eukaryal) can be defined based on organism origin. This suggests that occurrence of these proteins is at least as ancient as divergence of these two phyla. No paralogs, sign of a possible evolution of a new derived function, have been evidenced in entirely sequenced organisms currently available. Although these proteins are of ancient origin, the core sequence appears well conserved as observed in Fig. 1B . Thirty-three residues (38%) are found identical in the core central segment (out of 88 amino acids) between the most distant COG2042 orthologs, namely gi48852409 from Ferroplasma acidarmanus and gi6324579 from Saccharomyces cerevisiae (Fig. 1B ). From the alignment, several conserved motifs that may be functionally crucial (cofactor or substrate binding, catalysis, or partner interactions) were detected. A conserved hexapeptide sequence, Val-Val/Ile/Leu-Asp/Glu-Cys-Ser-Trp (motif I in Fig. 1B ), is found distant of 14–17 amino acids from another conserved motif of 25 amino acids containing 4 polar, 18 hydrophobic and 3 aromatic residues (motif II). Database searches with these motifs as queries did not allow identification of remotely-related proteins. All sequences from COG2042 encompass a stretch of 35 conserved amino acids upstream of the core common sequence. This motif, called RLI, is extremely polar (11 basic and 4 acidic residues) and is also found at the N terminus of another group of orthologous sequences, namely COG1245. Expression in E. coli of two engineered SSO0551 constructs From multiple sequence alignments, SSO0551 should encode a 166 amino acid polypeptide. An N-terminal 6His tagged recombinant construct (pSBTN-AB31) was engineered. As we could not exclude that the 42 amino acids extension at the N terminus was not an annotation artifact, we intended to check experimentally whether this putative extension could have some influence on SSO0551. A second construct (pSBTN-AB30) was simultaneously engineered supposedly allowing production of a 26 kDa N-terminal 6His variant. Unexpectedly, no major difference in expression was detected between the two cellular extracts when they were resolved on SDS-PAGE. Two overexpressed products with both an apparent molecular weight of approximately 20 kDa were obtained upon addition of IPTG (data not shown). Fingerprint identification of these two products was carried out by trypsin proteolysis and mass spectrometry. Table 1 shows the MALDI-TOF mass measurements recorded for the two samples. The tryptic peptides that were detected revealed that both products correspond to native SSO0551 sequence. From the 6His-SSO0551 product (pSBTN-AB31 construct), thirteen peptides map with the theoretical sequence (57 % sequence coverage). Noteworthy, a peptide (1590.64 amu) was attributed to part of the 6His-modified N terminus (Table 1 ). The twelve peptides recorded from the 6His-SSO0551 extended version (pSBTN-AB30 construct) fit only to the C terminus of the theoretical construct (43 % sequence coverage). These results along with low molecular weight observation on SDS-PAGE indicate that probably a truncated protein was obtained during expression of the ORF comprising the 126 nt 5'-extension (42 additional amino acids at the N-terminus). This product, corresponding in fact to untagged SSO0551 as confirmed hereafter with purified product, showed no binding on Ni-NTA chromatography. This observation is in agreement with absence of 6His tag at the N terminus. Recombinant SSO0551 is structured, thermostable and monomeric Crude extract containing native untagged SSO0551 polypeptide from E. coli Rosetta(DE3)(pLysS)(pSBTN-AB30) cells was heated at different temperatures. Proteins that remained soluble were analyzed on SDS-PAGE. Most of E. coli contaminants were removed by such treatment. SSO0551 polypeptide remained soluble even when cell extract was heated to 80°C and therefore this protein was considered as thermostable. This protein was purified to homogeneity by a three-step purification protocol. A 20 min heat treatment at 70°C (Fig. 2A , lane 3), followed by a Resource-S ion exchange chromatography (Fig. 2A , lane 4) and a Superdex75 gel filtration (Fig. 2A , lane 5), yielded approximately 1.6 mg of pure protein per L of culture. Purified protein was subjected to MALDI-TOF mass analysis. Fig. 2B shows the spectrum recorded. The experimental m/z of 19,198 measured for the monocharged polypeptide matches perfectly with theoretical average mass of native untagged SSO0551 protein (average mass of 19,197 Da). This measurement unequivocally confirmed that a truncated protein is produced using E. coli Rosetta(DE3)pLysS transformed with pSBTN-AB30. Both SDS-PAGE (Fig. 2A , lane 5) and MALDI-TOF spectrum (Fig. 2B ) testify for homogeneity of the sample. Content of secondary structure elements in SSO0551 was estimated by far-UV circular dichroïsm. Fig. 3 shows the spectrum recorded at 20°C. Purified protein presents negative ellipticity in the near-UV with minima at 208 (-14.7 10 3 deg cm 2 dmol -1 ) and 222 nm (-12.7 10 3 deg cm 2 dmol -1 ). Deconvolution of the CD spectrum leads to an estimation of secondary structural element content of about 28–29 % of α-helices and 14–16 % of β-sheets using K2D neural-software. Predictions of SSO0551 secondary structures by PSIPRED and Jpred web servers gave values of 10–11 % of β-sheets in relative agreement with the circular dichroïsm data, but overestimated the α-helix average content (54 %). PSIPRED and Jpred predictions are based on neural networks trained on known folds. The overestimation of the α-helix content may be due to the novel fold of these COG2042 proteins as discussed here below. Native molecular mass of SSO0551 was determined by size-exclusion chromatography on a Superdex 200 HR10/30 calibrated column. Pure protein eluted as a peak centered at 39.1 mL in the assay conditions corresponding to an apparent molecular mass lower than 20 kDa. This elution profile indicates that this structured protein behaves as a compact monomer. Limited proteolysis defines Glu 73 -Arg 78 as a hyper-sensitive region Purified SSO0551 protein was subjected to limited proteolysis with various endopeptidases (trypsin, chymotrypsin, ArgC and GluC). MALDI-TOF mass spectrometry was used to determine cleavage sites by following the time course generation of peptides. Several protease/substrate ratios were assessed to confirm which preferential sites on entire protein were first attacked (earliest cleavage), thus corresponding to a native state of the protein. The two fragments generated by such cleavage may be more vulnerable to subsequent attacks than native protein and therefore late proteolytic sites are considered less informative. Both small and large peptides generated during proteolysis were evaluated. Partial proteolyzed products obtained with trypsin were first resolved by reverse-phase chromatography and analyzed by MALDI-TOF mass spectrometry. Results recorded from direct analysis of the digestions without prior separation were almost similar to those obtained with separation. Therefore, the latter cost-effective strategy was used for analyzing the numerous conditions tested. Figure 4 shows the MALDI mass spectrum of the main large products obtained from a tryptic digest of SSO0551 (enzyme/protein ratio of 1:20) after 60 sec of reaction. In these conditions, the signal of intact protein was still visible at m/z 19198.4, but mixed with signals corresponding to 8 different large fragments. Among these, 7 peptides arose from an N-terminal proteolysis: [32–166], [35–166], [56–166], [57–166], [76–166], [79–166], [101–166] (Fig. 4 ). Such peptidic profile indicates that SSO0551 N terminus is rather solvent exposed in comparison to C terminus. During the earliest events of the trypsin proteolysis analyzed in various conditions for detection of large products but also smaller peptides, monocharged cations with following m/z : 8614.6 amu, 10603.4 amu, 6489.8 amu, and 12724.1 amu, were attributed to fragments [1–75] (Δmass: -178 ppm), [76–166] (+89 ppm), [1–56] (+145 ppm), [57–166] (+200 ppm), respectively (data not shown). These data clearly indicate that Lys 75 and Arg 56 are two sites of early cleavage by trypsin. Identification of peptides Val 32 -Lys 166 (15478.7 amu, -53 ppm) and Gly 35 -Lys 166 (15191.2 amu, +153 ppm) also indicates that Arg 31 and Lys 34 could be two other initial nick-sites. Similar experiments with endoproteinase Arg-C resulted in observation of two pairs of complementary peptides with m/z of 1920.9 amu ([1-15] +70 ppm) and 17296.8 amu ([16–166], -95 ppm) on one hand, 8998.1 amu ([1–78], -176 ppm) and 10217.5 amu ([79–166], +332 ppm) on the other hand. These data indicated that Arg 78 and Arg 15 are the main proteolyzed sites when ArgC enzyme was used. Chymotrypsin attacks SSO0551 native protein mainly at Phe 74 because two complementary peptides with m/z of 8487.0 amu ([1–74], -249 ppm) and 10734.2 amu ([75–166], -157 ppm) were clearly evidenced. Glu 73 is the main proteolyzed site when GluC protease was used, as peptides with m/z of 8338.7 amu ([1–73], -118 ppm) and 10880.0 amu ([74–166], +28 ppm) were detected. For all these analysis, smaller peptidic fragments that accumulated over time could be attributed from further proteolysis of the products arising from initial attacks (data not shown). All these results are concordant in pointing out that Glu 73 -Arg 78 and Glu 28 -Arg 31 are two accessible solvent-exposed regions of the protein as they can be proteolyzed by several endopeptidases, the first cited being definitively hyper-sensitive. Local unfolding not just surface exposure is necessary for efficient in vitro proteolysis because the polypeptide segment being cleaved must form a specific structure with the associated protease [ 30 ]. For this reason, Glu 73 -Arg 78 region should also correspond to a flexible region, i.e. a protruding loop. Lysine labeling with NHS-biotin and DTSSP cross-linking confirm that the N terminus is rather solvent-exposed The SSO0551 protein contains 21 lysine residues (12 %) distributed along the whole polypeptide sequence. Under mild conditions that should keep the native conformation of the protein, specific labeling of these residues with NHS-biotin may give further details about their respective surface accessibility and/or their interactions with other residues [ 31 ]. After reaction with various amount of chemical reagent (molar ratio NHS-Biotin/total lysines of 1:40, 1:20, 1:10, 1:2, 1:1, 2:1), protein labeling was monitored by determining the mass of undigested samples. Figure 5 shows the signals measured by MALDI-TOF mass spectrometry for four of these ratios. The fact that some unmodified protein is still present at ratio below 1:20 testifies for mild conditions that should allow modification of protein still in a native state. As expected with NHS-biotin, each peak exhibits the predictable mass increment (average mass of 226.3 amu per label). Figure 5 shows that at molar ratio of 1:40 a simple modification is obtained, while a more heterogeneous population was detected for higher ratio. For examples, 1 to 3 modifications are detected at ratio 1:20, 2 to 5 modifications at ratio 1:2. However, a limited number of modifications (8–10) are recorded for higher ratio, indicating that among the 21 lysine residues only a fraction is accessible to the chemical. To localize all labeled residues, NHS-biotin treated samples were subsequently subjected to proteolysis with various endoproteases (trypsin, Arg-C, or Glu-C) and compared to untreated samples. SSO0551 sequence coverage was estimated to be 92 % with all 21 lysine residues included in this coverage. Peptides (Δmass below 120 ppm) detected with NHS-biotin treated samples but not detected with untreated samples are listed in Table 2 . Using limiting amount of NHS-biotin (molar ratios of 1:10, 1:20 or 1:40), nine reactive residues are unequivocally identified: Lys 10 , Lys 14 , Lys 20 , Lys 23 , Lys 25 , Lys 51 , Lys 75 , Lys 128 , and Lys 154 , assuming that proteases do not cleave after a modified residue. Other residues, such as Lys 34 and Lys 49 might be also labeled (Table 2 ). The number of labeled lysines is in agreement with the limited number of modifications recorded at higher ratio. Remarkably, spectra of whole peptide mixture were informative enough to give assignment of all modified peptides without the need of a purification step. Therefore, other amine reactive reagent that creates a mass shift could have been used. Using a lysine cross-linking reagent, DTSSP, it is possible to assess intra- or inter-molecular protein contacts [ 21 , 32 ]. DTSSP enables cross-linking of amino groups up to 12 Å apart. As SSO0551 was shown to be monomeric and its concentration used in the assays was low (2.5 pM), intramolecular cross-links should be favored over intermolecular cross-links. In addition, the low reagent concentration used should avoid unwanted conformational changes that may be induced by multiple intramolecular cross-linking. After reaction with DTSSP, products were subjected to trypsin proteolysis and peptides were identified by MALDI-TOF. As the protein is relatively small, mass signals could be attributed with a good confidence (tolerance < 120 ppm). In addition, peak attribution was always confirmed upon reduction of products and sometimes through redundancy due to miss-cleavage. SSO0551 sequence coverage was 89%. The monoisotopic cations at m/z 1169.55, 2077.04, 2715.11 and 2871.14, detected for SSO0551 treated by DTSSP (ratio DTSSP/total polypeptide of 20:1) correspond in mass to addition of a DTSSP moiety on peptides [24-31] (Δmass tolerance: +16 ppm), [123–138] (-7 ppm), [57–78] (+61 ppm) and [56–78] (+82 ppm). Since trypsin does not cleave after a modified lysine, we conclude that Lys 25 , Lys 75 and Lys 128 were modified. After DTT treatment, peaks corresponding to the expected products (-103.993 amu theoretically) were detected at m/z 1065.46 (-109 ppm), 1973.03 (0 ppm), 2611.21 (-28 ppm) and 2767.26 (-45 ppm), respectively. Fig. 6 shows two monoisotopic [MH] + ions at m/z 1491.76 and 1835.84 corresponding to intrapeptide cross-linked peptides: [21-31] (+31 ppm) and [3-15] (+3 ppm), respectively. These peptides contain two proximal lysine residues (Lys 23 -Lys 25 and Lys 10 -Lys 14 ). As shown in Fig. 6 , these two peaks were absent in mass spectrum following DTT reduction but new peaks at m/z 1493.69 and 1837.81 appears at the expected increment (+2.016 amu theoretically). An additional peak at m/z 2502.22 could be attributed to peptide [35–55] (+37 ppm) with an intrapeptide cross-link between Lys 49 and Lys 51 . However, the corresponding reduced peak was not detected. Strikingly, every lysines that were reactive with DTSSP were also detected by NHS-biotin labeling. Most modifications are located at the N terminus of the protein where five modified residues belong to the RLI motif. Discussion Although COG2042 proteins are distributed among a large number of organisms, no experimental evidences have yet been reported concerning their biochemical characterization and function. As they are not related, even remotely, to any other family of proteins, COG2042 members can be phylogenetically considered as orphans. Figure 7 (Panel A) summarizes the structural information obtained with chemical modification approach, in combination with limited proteolysis procedures. Using MALDI-TOF mass spectrometry to identify protease-accessible sites, we have shown that the most exposed regions are located at the first half of the protein, the Glu 73 -Arg 78 region being revealed hyper-sensitive to various proteases (Fig. 7A ). It probably indicates a protruding loop out of the globular protein. This charged region is relatively conserved among COG2042 orthologs and lies between two highly conserved segments of COG2042 (motif I and II as shown on Fig. 7 ). Chemical modification agrees with limited proteolysis in that the RLI motif is solvent exposed while the C terminus appeared rather inaccessible (Fig. 7A ). The length of the RLI motif, first defined by conserved domain search [ 33 ], matches perfectly with two sensitive proteolytic sites (Arg 31 and Lys 34 ). The RLI domain is also present at the N terminus of another group of orthologous proteins, namely COG1245. Remarkably, COG1245 proteins only occur in two domains of life (Archaea and Eukarya) similarly to COG2042 proteins. Although co-occurrence of protein members is not strictly identical (for example, pyrococci encompass the information for COG1245 but not for COG2042 polypeptides), such occurrence pattern may reflect a functional link between the two protein families. Our initial objective was to obtain about SSO0551 as much low-resolution structural information as possible in order to discriminate among putative three-dimensional models representing COG2042 protein structure. However, currently available threading tools applied on SSO0551 failed to detect any structurally related-proteins. Alternatively, we obtained ten different ab initio models of SSO0551 using the fully-automated ROBETTA server based on ROSETTA procedures [ 34 ]. On these ten models, we applied all the low-resolution structural information gathered in this work. We predicted for every model location of preferential proteolytic sites using the NickPred software [ 35 ]. Models M1, M2 and M6 on one hand, and M9 and M10 on the other, show hypersensitive regions in the RLI motif or C terminus, respectively. These features do not correspond to our experimental data. Only models M4, M7 and M8 predict that the loop Glu 73 -Arg 78 is solvent exposed (data not shown). Among these three models, M4 and M8 respect the ranking of preferential nick-sites for trypsin, chymotrypsin, ArgC and GluC proteases. Solvent accessibility for lysine side chain was evaluated for models M4, M7 and M8 and compared with experimental data (data not shown). All the lysine residues labeled with NHS-biotin are found solvent-exposed in model M8. Manual inspection of cross-linked lysines (Lys 10 -Lys 14 and Lys 23 -Lys 25 ) revealed that model M4 is not valid because of the opposite orientation of Lys 10 and Lys 14 . Figure 7 (Panels B & C) shows cartoon views of the M8 model that fulfills all our experimental constraints. For this model, the distance between the two reactive amine groups of Lys 10 -Lys 14 and Lys 23 -Lys 25 pairs are 12.7 Å and 13.3 Å, respectively. Search with DALI for structural homologs using model M8 did not result in significant scores with any known PDB structures. This is consistent with the PSI-BLAST results and may indicate that COG2042 proteins share a novel fold. COG2042 proteins are thus a target of choice for genomic structural studies. In conclusion, we have presented a strategy consisting in obtaining low-resolution structural information (determination of nick-sites, solvent exposed residues, and residue-residue distances) that can be used to distinguish among a large set of theoretical molecular models. Lack of remotely-related structural templates or lack of adequacy between experimental data and most theoretical models indicates that such family of proteins should become a priority in structural genomic projects. Methods Chemical and biological reagents Most chemicals used in this study were obtained from Sigma and were of analytical grade. Oligonucleotide primers were purchased from Genset. N-hydroxysuccinimide-biotin (NHS-biotin) and 3,3'-dithio-bis [sulfosuccinimidyl-propionate] (DTSSP) were obtained from Pierce. Matrices for Matrix-assisted Laser Desorption Ionization-Time of Flight (MALDI-TOF) mass spectrometry and calibration standards were purchased from Bruker Daltonics. Sequencing grade proteolytic enzymes were from Roche Applied Science. Cloning and overexpression of SSO0551 Two constructs were designed in order to get overexpression of the SSO0551 ORF (starting with an ATG codon at nucleotide 484790 on the Crick strand of S. solfataricus P2 genome (NC_002754)) and an N-terminal extended version of SSO0551 (starting with an ATG codon at nucleotide 484916). For both proteins, an N-terminal 6His tag was added to render the purification of the recombinant products easier. For this purpose, synthetic oligonucleotide primers were oAB22 (5'- gctagc ATGAAGCCCAAACCC-3') and oAB49 (5'- gctagc ATGAAGGTATATATTATAGAC-3') that both contain an engineered Nhe I site, oAC34 (5'- cggatcct acTCATTTTTCAAGTATTTTC-3') and oAE62 (5'- ggatcc tcaTCATTTTTCA AGTATTTTCTC-3') that both contain an engineered Bam HI site (restriction sites underlined in the primer sequences and nucleotides not present in the original sequence shown by lower case). Oligonucleotide pairs oAB22/oAC34 and oAB49/oAC34 were used for two distinct PCR amplifications of SSO0551 with S. sulfolobus total DNA as template. A 643-bp fragment (N-ter 6His-tag extended version of SSO0551) and a 517-bp fragment (N-ter 6His-tag SSO0551) were obtained, respectively. They were cloned into pCRScript-cam (Stratagene), resulting in plasmids pSBTN-AB36 and pSBTN-AB37, respectively. The two inserts were removed by digestion with Nhe I and Bam HI and ligated with T4 DNA ligase into plasmid pSBTN-AB23 (Armengaud J. & Chaumont V., unpublished data), a derivative of pCR T7/NT-topo (Invitrogen) containing a T7 promoter and 6 His-tag, previously digested with the same endonucleases. The resulting plasmids pSBTN-AB30 and pSBTN-AB31, respectively, were verified by DNA sequencing in order to ascertain the integrity of the nucleotide sequence. Hyperexpression of the recombinant SSO0551 constructs was achieved with E. coli Rosetta(DE3)pLysS strain (Novagen), freshly transformed with the plasmids described above. Cultures were carried out at 30°C as described earlier [ 6 ]. Purification of recombinant SSO0551 protein The purification of recombinant SSO0551 was performed from 44 g (wet material) packed cells. Buffer A consisted of 50 mM K 2 HPO 4 /KH 2 PO 4 buffer (pH 7.2) containing 400 mM K-glutamate. The pellet was thawed on ice and resuspended in 120 mL of buffer A. The cells were disrupted by sonication with a total energy delivered of 71 kJ. The cell-extract was then centrifuged at 30,000 g for 20 min at 4°C to remove cellular debris and aggregated proteins. The supernatant was subjected to a 20 min heat treatment using a water bath maintained at 70°C, and immediately centrifuged a second time at 30,000 g for 20 min at 4°C. Chromatographic steps were performed at room temperature using an Äkta Purifier FPLC system (Amersham Biosciences). The 135 mL supernatant was applied at a flow rate of 2.8 mL/min onto a XK 26 × 20 column (Amersham Biosciences) containing 50 mL of Chelating Sepharose Fast Flow (Amersham Biosciences) and previously loaded with 200 mM NiSO 4 , washed with milliQ water and equilibrated with Buffer A containing 50 mM imidazole. The fraction collected during the IMAC loading was shown to contain the SSO0551 protein. This 222 mL fraction was concentrated to a volume of 56 mL by means of Centricon Plus-20 filtration units (Millipore) and then dialyzed overnight at 4°C against 20 mM K 2 HPO 4 /KH 2 PO 4 buffer (pH 7.2) containing 20 mM NaCl (buffer B). The 78 mL supernatant obtained after centrifugation at 30,000 g for 10 min at 4°C was divided and applied in two separate runs onto a 6 mLResource-S ion-exchange column (30 mm × 16 mm, 15 μm) from Amersham Biosciences, previously equilibrated with buffer B and operated at a flow rate of 3 mL/min. After a 10 column volume wash with buffer B, proteins were resolved with a 25 column volume linear gradient from 20 to 500 mM NaCl in buffer B. Recombinant SSO0551 was eluted at approximately 250 mM NaCl and desalted by overnight dialysis against Buffer B. The resulting 20 mL protein solution was concentrated to a volume of 8 mL by means of Centricon Plus-20 filtration units (Millipore). The sample was again divided and applied in two separate runs onto a superdex75 gel filtration packed into a HR 16/50 column at a flow rate of 1.5 mL/min in 20 mM K 2 HPO 4 /KH 2 PO 4 buffer (pH 7.2) containing 100 mM NaCl. The fractions obtained with the two runs were pooled and dialyzed overnight at 4°C against 10 mM HEPES buffer (pH 7.2). After dialysis, the fraction was centrifuged at 26,000 g for 20 min at 4°C and the protein concentration was measured by spectrophotometry using a molar absorption coefficient of 19060 M -1 cm -1 at 280 nm. The purified protein was flash frozen in liquid nitrogen and stored at -80°C at a concentration of 0.48 mg/mL. Circular dichroïsm Far- and near-UV circular dichroism spectra were recorded at 20°C between 200 and 300 nm on a J-810 Jasco spectropolarimeter equipped with a PTC-424S Jasco Peltier, using a quartz cuvette of 1 mm path length, with a 20 nm/min scanning speed and a band-width of 1 nm. Three spectra of purified SSO0551 at 1.92 μM in 10 mM HEPES buffer (pH 7.2) were averaged and corrected from the baseline for buffer solvent contribution. Experimental data were analyzed using the program K2D [ 36 ] described by Andrade et al. [ 37 ]. Determination of native molecular mass by gel filtration The native molecular mass of SSO0551 was estimated by gel filtration chromatography on a Superdex 200 gel packed into a HR10/30 column (Amersham Biosciences) with a final bed volume of 24 mL. The column was equilibrated at room temperature at a flow rate of 0.5 mL/min with 50 mM Tris/HCl buffer, pH 8.3, containing 50 mM NaCl and eluted with the same buffer. Protein standards used to calibrate the column were ribonuclease A (15.8 kDa), chymotrypsinogen A (21.2 kDa), ovalbumin (49.4 kDa), albumin (69.8 kDa), aldolase (191 kDa) and catalase (215 kDa), all from Amersham Biosciences. Exclusion limit was evaluated with dextran blue 2000 (Amersham Biosciences). A sample consisting of 90 μL of SSO0551 at 25.2 μM was injected and specific absorptions at 280 and 266 nm were followed. Mass spectrometry Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight (MALDI-TOF) mass measurements were performed using a Biflex IV instrument (Bruker Daltonics) in positive ionization mode. Protein samples and large peptidic fragments (>3500 Da) were applied to the target using sinapinic acid prepared as saturated solution in 30 % acetonitrile, 70 % milli-Q water and 0.1 % TFA as matrix. Samples were prepared using the dried droplet method and measured in linear mode. Small peptide samples were measured in reflectron mode using α-cyano-4-hydroxycinnamic acid in 30% acetonitrile containing 0.1% trifluoroacetic acid as matrix. Mass spectra were obtained by summation of 100–210 laser shots. The instrument was calibrated for determination of entire protein masses using either a mixture of chymotrypsin and bovine serum albumine, or apomyoglobin and aldolase. For peptides, the instrument was calibrated using a pepmix calibration kit (Bruker Daltonics). When necessary, the mass spectrometer was also internally calibrated using some of the theoretical peptide masses. Limited protease digestion For in-solution partial digestion, 0.2 nmol of pure SSO0551 were diluted into buffer D1 (20 mM TRIS/HCl, pH 7.8), buffer D2 (20 mM NH 4 HCO 3 , pH 7.8) or buffer D3 (20 mM TRIS/HCl, pH 7.8, containing 10 mM CaCl 2 and 5 mM DTT). Trypsin or chymotrypsin was added to SSO0551 diluted into buffer D1, whereas Glu-C or Arg-C was added to the protein diluted into buffer D2 or D3, respectively. Several enzyme/protein ratios (1:50 (w/w), 1:20 (w/w) and 1:2 (w/w)) were tested for each endoprotease. The digestions were performed at room temperature and aliquots were analyzed from 30 sec to 10–240 min. Digested samples were desalted using ZipTip C18 or ZipTip C4 pipette tips (Millipore) according to the protocol specified by the manufacturer and their mass directly evaluated by MALDI-TOF. Eventually, partially proteolyzed mixtures of larger quantities (10 nmol of SSO0551) were fractionated by reverse-phase HPLC using an Aquapore RP-300 column (PerkinElmer; 100 × 1.0 mm, 7 μm, 300 Å pore size) developed at 200 μL/min with a linear gradient from 5 to 90 % of acetonitrile in TFA 0.1 % over 45 min. The elution was monitored at 220 nm with an Agilent 1100 Series HPLC system equipped with a G1315 diode array detector. Individual fractions were concentrated by evaporation in a SpeedVac (Savant) and directly analyzed by MALDI-TOF. Lysine labeling by NHS-biotin N-hydroxysuccinimide-biotin (NHS-biotin) was used to label ε-amino groups of SSO0551 lysines. After reaction the biotin labels resulted coupled to the lysines through a stable amide bond. The increase in mass for each label (C 10 H 14 N 2 O 2 S 1 ) should be 226.293 amu if average mass is considered or 226.078 amu in monoisotopic mode. Modification of lysine residues was carried out by incubating 1.25 nmol of SSO0551 in 20 mM HEPES, pH 7.2, with various amount of freshly prepared NHS-biotin reagent dissolved in anhydrous dimethylsulfoxide. After 30 min of incubation at room temperature, the reagent in excess was removed by a 30 min micro-dialysis against 20 mM HEPES, pH 7.2. Samples were directly desalted by using ZipTip C4 (Millipore) prior MALDI-TOF analysis. They were eventually digested overnight with an endoprotease (trypsin, GluC or ArgC) and desalted by using ZipTip C18 pipette tips (Millipore) prior mass analysis. Lysine cross-linking with DTSSP 3,3'-Dithio-bis [sulfosuccinimidyl-propionate] (DTSSP) was used to cross-link two ε-amino groups of SSO0551 lysines, essentially as described in [ 32 ]. The mass increase (in monoisotopic mode) for each label should be 191.991 amu (C 6 H 8 O 3 S 2 ) or 87.998 amu (C 3 H 4 O 1 S 1 ) when DTT treated. The increase in mass for an intramolecular cross-link between two lysines should be 173.981 amu (C 6 H 6 O 2 S 2 ) or 175.997 amu (2 × C 3 H 4 O 1 S 1 ) when DTT treated. Therefore after reduction of the disulfide bridge by DTT, an additional increase of 2.016 amu should be measured. Reaction was carried out by incubating 0.25 nmol of SSO0551 in 20 mM NaH 2 PO 4 /Na 2 HPO 4 , pH 7.5 containing 150 mM NaCl, with various amount of DTSSP reagent (molar ratio of 20, 35, and 50 mol of DTSSP per mol of polypeptide). After 30 min of incubation at room temperature, the reagent in excess was removed by a 30 min micro-dialysis against 20 mM NaH 2 PO 4 /Na 2 HPO 4 , pH 7.5 containing 150 mM NaCl. Prior overnight trypsin proteolysis, urea (330 mM final concentration) was added to each sample. Before being desalted by using ZipTip C18 pipette tips (Millipore), the digested peptide mixture was eventually reduced with 50 mM DTT for 30 minutes at 37°C to reduce the thiol linker. In silico analysis Sequence searching was performed using PSI-BLAST with default parameters. Multiple sequence alignments were performed using VectorNTI software package (Informax Inc). Secondary structure predictions were obtained through the PSIPRED v2.4 web-interfaced facilities [ 38 ] described by McGuffin et al. [ 39 ]. The molar absorption coefficient at 280 nm for SSO0551 was obtained from calculation of the amino acid composition of the recombinant protein [ 40 , 41 ]. Isotopic and average mass of both DTSSP cross-linker and NHS-biotin were calculated using a web-interfaced molecular weight calculator [ 42 ]. The peptide assignment and the first attempt for identifying the labeled products and cross-linking products were performed using the FindMod package at ExPaSy [ 43 ]. If no match was found, a more detailed search for multiple labels or combinatorial cross-linkable peptide pairs was carried out. Partially proteolyzed products were assigned using the FindPept tool [ 44 ]. Tertiary structure predictions were carried out using publicly available online services, including 3D-PSSM [ 45 ], FUGUE [ 46 ] and PSIPRED [ 39 ]. Ab initio modeling was performed using the ROBETTA server [ 34 , 47 ]. Each model was analyzed in terms of proteolytic sensitivity using the NICKPRED software [ 35 , 48 , 49 ]. Residues accessibility have been calculated using a modified version of Connolly's MS program ([ 50 ]; Pellequer JL, unpublished results). Structural homologs were searched using DALI web server from the European Bioinformatics Institute [ 51 ]. Model views were obtained with the MOLSCRIPT program [ 52 ] and rendered using RASTER3D [ 53 ]. List of abbreviations amu , atomic mass unit; COG , Cluster of Orthologous Group; DTSSP , 3,3'-dithio-bis [sulfosuccinimidyl-propionate]; IPTG , isopropyl-γ-D-thiogalactopyranoside; HPLC , high performance liquid chromatography; EDTA , Ethylenediaminetetraacetic acid; HEPES , 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid; HEPPS , N-(2-hydroxyethyl)piperazine-N'-(3-propanesulfonic acid); IMAC , immobilized metal ion adsorption chromatography; MALDI-TOF , Matrix-assisted Laser Desorption/Ionization Time-of-Flight; NHS-biotin , N-hydroxysuccinimide-biotin; PSI-BLAST , Position-Specific Iterated Blast; Tris , 2-[bis(2-hydroxyethyl)amino]-2-(hydroxymethyl)-propane-1,3-diol. Authors' contributions JA conceived, coordinated the study and participated in all its experimental aspects. He analyzed the genomic distribution of this family of proteins, designed and engineered the recombinant SSO0551 molecule, conceived the mass spectrometry strategies and interpreted the data. He proposed ab initio modeling of SSO0551 and drafted the original manuscript. AD actively participated in conception of the mass spectrometry strategies, advised OS on execution and interpretation of mass spectrometry experiments and assisted in figure design. OS performed and interpreted all mass spectrometry experiments. JLP contributed its experience for the modeling aspects of the project. EQ contributed its experience in mass spectrometry-based topology. All authors participated in manuscript preparation, read and approved the final manuscript.

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Design, implementation and evaluation of a practical pseudoknot folding algorithm based on thermodynamics

Background The general problem of RNA secondary structure prediction under the widely used thermodynamic model is known to be NP-complete when the structures considered include arbitrary pseudoknots. For restricted classes of pseudoknots, several polynomial time algorithms have been designed, where the O ( n 6 )time and O ( n 4 ) space algorithm by Rivas and Eddy is currently the best available program. Results We introduce the class of canonical simple recursive pseudoknots and present an algorithm that requires O ( n 4 ) time and O ( n 2 ) space to predict the energetically optimal structure of an RNA sequence, possible containing such pseudoknots. Evaluation against a large collection of known pseudoknotted structures shows the adequacy of the canonization approach and our algorithm. Conclusions RNA pseudoknots of medium size can now be predicted reliably as well as efficiently by the new algorithm.

Background Biological relevance Pseudoknots have been shown to be functionally relevant in many RNA mediated processes. Examples are the self-splicing group I introns [ 1 ], ribosomal RNAs, or RNaseP. Recently, pseudoknots were located in prion proteins of humans, and confirmed for many other species [ 2 ]. With the current increased interest in the universe of RNA functions [ 3 ], algorithmic support for analysing structures that include pseudoknots is much in demand. Previous algorithmic work Well established algorithms for the prediction of RNA secondary structures (MFOLD [ 4 ], RNAfold [ 5 ]) are commonly based on a thermodynamic model [ 6 ], returning a structure of minimal free energy, called MFE-structure for short. In spite of their importance, pseudoknots are excluded from consideration by these programs for reasons of computational complexity: While folding a sequence of length n into unknotted structures requires O ( n 3 ) time and O ( n 2 ) space, finding the best structure including arbitrary pseudoknots has been proved to be NP-complete [ 7 , 8 ]. In fact, the proof given in [ 8 ] uses a scoring scheme based on adjacent base pairs only, simpler than the MFE model because it neglects entropic energies from loops. These complexity results leave two routes to achieve practical algorithms. The first route is to consider pseudoknots in full generality, but resort to an even more simplistic energy model. An O ( n 4 ) time and O ( n 3 ) space algorithm for base pair maximization has been given in [ 7 ], and an O ( n 3 ) time algorithm based on maximum weight matching in [ 9 ] and [ 10 ]. The second route is the one followed here: We retain the established thermodynamic model, but restrict to a more tractable subclass of pseudoknots. For some quite general classes of pseudoknots, polynomial time algorithms have been designed: Rivas and Eddy achieve O ( n 6 ) time and O ( n 4 ) space [ 11 ]. This algorithm is available, and, in spite of the high computational cost, it is actually used in practice. We build upon this work and shall call it pknotsRE for later reference. Further improvements have been shown to be possible for yet more restricted classes, e.g. the non-recursive simple pseudoknots considered by Lyngsø and Pedersen [ 12 ] with O ( n 5 ) time and O ( n 4 ) space, but to our knowledge, no implementations are available. Recently, an O ( n 4 ) time and O ( n 3 ) space algorithm based on the technique of [ 7 ], that uses a thermodynamic model has been reported in [ 13 ]. While it handles simple pseudoknots consisting of more than two helices, it is restricted to non-recursive pseudoknots. Thus, this class of pseudoknots and the class presented here have a nonempty intersection, but neither of them contains the other. Our contributions The new contributions reported here are the following: • We present an algorithm pknotsRG for folding RNA secondary structures including pseudoknots under the MFE model which requires O ( n 4 ) time and O ( n 2 ) space. • The algorithm considers the class of simple recursive pseudoknots, further restricted by three rules of canonization. Each simple recursive pseudoknot has a canonical representative that is recognized by pknotsRG . • While this class is more restricted than the one of the Rivas/Eddy algorithm, practical evaluation shows that our algorithm finds the same pseudoknots, while the length range of tractable sequences is increased significantly. • We provide an evaluation of the class of pseudoknots introduced here against known examples from the literature. • We perform a rigorous evaluation of our algorithm on 212 sequences from PseudoBase [ 14 ] plus 7 other structures and compare our results with those obtained with RNAfold and, where feasible, with pknotsRE . Results It is not easy to relate the classes of pseudoknots recognized by the different algorithms mentioned above. We refer the reader to the review by Lyngsø and Pedersen [ 8 ], which compares these classes by means of examples. The starting point of our work is the algorithm pknotsRE by Rivas and Eddy. It recognizes pseudoknots that can be nested and can have unlimited chains of helices involved in crosswise interactions. The drawback of this powerful, but computationally expensive algorithm is the following paradox: Pseudoknots with complex helix interactions naturally require longer primary sequence than simpler ones. The high runtime complexity of O ( n 6 ), however, as well as the space consumption of O ( n 4 ) restricts the use of this algorithm to a maximal sequence length of around 150 nucleotides. Most of the pseudoknots predicted belong to a much simpler structural class and do not exhibit chains of crosswise interactions. The algorithm developed here achieves time complexity O ( n 4 ) and space complexity O ( n 2 ). The runtime improvement, compared to pknotsRE , results from an idea of canonization, while the space improvement results from disallowing chained pseudoknots. These improvements extend the range of tractable sequences to a length up to 800 nucleotides, and we can locate pseudoknots up to this size in even longer sequences. Simple recursive pseudoknots Following the terminology of [ 7 ], a simple pseudoknot is a crosswise interaction of two helices, as shown in Figure 1 . In simple recursive pseudoknots, we allow the unpaired strands u, v, w in a simple pseudoknot to fold internally in an arbitrary way, including simple recursive pseudoknots. Let us call this class sr-PK. More complex knotted structures like triple crossing helices or kissing hairpins, as shown in Figure 4 , are excluded from sr-PK. We will show later how they can be integrated in our approach and outline the increased computational cost of doing so. For the main part of this paper, we concentrate on the class sr-PK. Anticipating the complexity of a DP algorithm Thermodynamic RNA folding is implemented via dynamic programming (DP). We start with a semi-formal discussion of how to estimate the efficiency of a DP algorithm for folding (or any kind of motif search) before it is written in detail. We consider elements of RNA structure as sequence motifs of different types: hairpins, bulges, multiloops, etc. The following notation is taken from the algebraic dynamic programming approach [ 15 ]. By an equation m = f <<< a ~~~ b ~~~ c | | | g <<< c ~~~ a we specify that the sequence motif m can be composed in two alternative ways: The first case, labelled by f , requires adjacent occurrences of motifs a , b and c . The second case, labelled by g , requires adjacent occurrences of motifs c and a . When motif m is to be scored, f and g are seen as the scoring functions that combine the local score contribution of each case with the scores of sub-motifs a , b , and c . What is the computational effort of locating motif m in an input sequence x of length n , say at sequence positions i through j? First we assume that all motifs can have arbitrary size between 0 and n . The algorithm must consider all boundary positions ( i, j ) for motif m , which requires O ( n 2 ) steps at least. In case g , it must consider all boundary positions k where motifs c meets a , such that the runtime for case g is in O ( n 3 ). In case f , there are two such moving boundaries k and l between the three sub-motifs, so we obtain O ( n 4 ) overall for motif m . This can be improved if there is an upper bound on the size of some motif involved. If motif a is a single base, for example, the exponent of n decreases by 1 in both cases. Furthermore, if motif b is (say) a loop of maximal size 40, then one factor of n is reduced to a constant factor and overall asymptotic runtime is now O ( n 2 ). Sometimes a motif description can be restructured to improve efficiency by reducing the number of moving boundaries. Whether or not this is possible does not depend on the motif structure, but on the scoring scheme! This is a somewhat surprising observation from [ 15 ], where such optimizations are studied, and where also the line of reasoning exercised here is given a mathematical basis. In the sequel, we shall exploit another source of efficiency improvement. If the lengths of two sub-motifs are coupled somehow, say a and c have the same length, then the boundaries k and l in case f are related by k - i = j - l . When iterating over k , we can use l := j - k + i (rather than k ≤ l ≤ j )and save another factor of n . Canonization When the search space of a combinatorial problem seems to be too complex to be evaluated efficiently, heuristics are employed. Canonization restricts the search space in a well-defined way, arguing that all the relevant solutions in the full search space have a representative that is canonical, and hence, nothing relevant is overlooked. One such technique is the purging of structures that have isolated basepairs. Here the plausibility argument refers to the underlying energy model, where base pairings without stacking have little or no stabilizing effect. This canonization does not affect efficiency, but it achieves a significant reduction of the search space (figures in [ 16 ]), which renders the enumeration of near-optimal solutions [ 17 ] much more meaningful. We shall introduce three canonization rules that reduce class sr-PK to the class of canonized simple recursive pseudoknots , csr-PK. Using the notation introduced above, the motif definition of a simple recursive pseudoknot is given by knot = knt <<< a ~~~ u ~~~ b ~~~ v ~~~ a' ~~~ w ~~~ b' with boundaries at sequence positions i, e, k, g, f, l, h, j as shown in Figure 2 . Segment a forms a helix with a ', and b with b' . Segments u , v , and w can have arbitrary structures, including pseudoknots. Naively implemented, we can expect a DP algorithm of time complexity O ( n 8 ) according to our efficiency estimation technique introduced above. We now apply canonization. Note that it only applies to helices forming pseudoknots; other helices are unaffected. We first present the technical aspects; the discussion of these restrictions is deferred to the next section. Canonization rule 1 (a) Both strands in a helix must have the same length, i.e. | a | = | a '| and | b | = | b '|. (b) Both helices must not have bulges. Note that (b) is a stronger restriction and trivially implies (a). Under the regime of Rule 1 we may conclude: f = l - ( e - i ) h = j - ( g - k ) We are left with 6 out of 8 boundaries that vary independently, and runtime is down to O ( n 6 ). Canonization rule 2 The helices a , a' and b , b' facing each other must have maximal extent, or in other words, compartment v must be as short as possible under the rules of base pairing. We observe that the maximal length of a and a' is fixed once i and l are chosen. The maximal helix length stacklen ( i, l ) can be precomputed and stored in an O ( n 2 ) table. The same observation holds with respect to the other helix, and we fix e = i + stacklen ( i, l ) g = k + stacklen ( k, j ). Thus, we are left with only four independently moving boundaries – i, k, l, j –, and can hope to obtain an algorithm with runtime O( n 4 ). Scores of pseudoknots found between i and j are stored in table knot ( i, j ), and hence the space requirements are O( n 2 ), which is the same asymptotic space efficiency as in the folding of unknotted structures. A subtlety arises when both helices, chosen maximally, compete for the same bases of v , or in other words, the length of v would become negative. This case is addressed by Canonization rule 3 If two maximal helices would overlap, their boundary is fixed at an arbitrary point between them. Let m and m' be the helix lengths so determined. We finally obtain e = i + m g = k + m' The language of pseudoknots in class csr-PK can be defined by a simple context free grammar over an infinite terminal alphabet. Let a k denote a terminal symbol of k times the letter a . The grammar uses a single nonterminal symbol S and its productions are for arbitrary k, l ≥ 1. For example, the simple pseudoknot of Figure 1 is represented as the string .. [[[......{{..]]]]..........}}. This grammar is useful to judge how different an experimentally determined structure is from class csr-PK. It is not useful for programming, since it is ambiguous and does not distinguish the fine grained level of detail required in the energy model. Canonical representatives A careful discussion is required to show that each simple recursive pseudoknot, if not canonical by itself, has (a) a canonical representative of (b) similar free energy. Rule 1 (b) affects the length of helices that are considered in forming the pseudoknot. Let there be a pseudoknot between i' and j' . It is not canonical if one of the two helices contains bulges. However, there must be at least one pair of shorter helices without bulges at i, j with i' ≤ i and j ≤ j' , which serves as a canonical representative, albeit with somewhat higher free energy. Rule 2 is justified by the fact that the energy model strongly favours helix extension. Clearly, for each family of pseudoknots delineated by i, k , l , j there is a canonical one with maximal helices, whose free energy is at least as low – except for the following case: The maximal helices compete with the internal structure of u , v and w . It may be possible to contrive a structure where shortening (say) helix a – a' by one base pair allows to create two pairs with new partner bases in u and v , resulting in a structure which has slightly lower energy. Still, the free energy of the canonical pseudoknot must be very similar. Finally, Rule 3 requires a decision where to draw the border between two helices facing each other and competing for the same bases. An arbitrary decision here can only slightly affect free energy, as the same base pairs are stacked either on the a – a' or the b – b' helix. Let E ( s ) denote the free energy computed for structure s . Summing up, we have shown that for each simple recursive pseudoknot K , there is a canonical one C in the search space. While we cannot prove that E ( C ) ≤ E ( K ), we have argued that this is likely, and if not, the energies will at least be close. Still, there might be another, energetically optimal canonical structure S (knotted or not) such that E ( K ) < E ( S ) < E ( C ). In this case, if only the "best" structure S is reported, neither K nor its canonical representative C is observed. (A remedy to this is the computation of near-optimal structures.) Finally, let us add that the implementation described below is actually slightly more general that the "pure" csr-PK model described above: We do allow a single nucleotide bulge in either helix of a pseudoknot, which complicates the program, but does not affect asymptotic efficiency. Evaluation of the class csr-PK To evaluate how well the class csr-PK covers known pseudoknots, we considered 212 pseudoknot structures from PseudoBase. The observations are shown in Table 1 . We find 172 simple recursive pseudoknots, and 40 of more general shapes. We find that 135 out of the 172 pseudoknots lie in csr-PK, i.e. they are their own canonical representatives. 11 more fall into the relaxed csr-PK, where we allow a single nucleotide bulge in Canonization Rule 1. Thus, we cover 146 out of 212 (68%). 26 simple recursive pseudoknot do not fall in class csr-PK, since they contain isolated basepairs, non canonical basepairs or one of the helices has not maximal extent. Considering the remaining 20% complex pseudoknots, note that often pseudoknots in more general classes also have a good representative in csr-PK. For example, the pseudoknot of Hepatitis delta virus (Figure 3 ) consists of four interacting helices of shape a – b – c – d – c' – a' – d' – b ', where helix d – d' is very short – only two base pairs. Deleting it, helix c – c' is no longer interacting with other helices, and the pseudoknot falls within class csr-PK. Better than optimal There are many reasons why "the" MFE structure may only be part of what we want to know about a molecule's foldings. To deal with the problem when the optimal (knotted) structure is non-canonical, and its canonical representative is dominated by an unrelated structure, we provide two means: First of all, our algorithm is non-ambiguous, the prerequisite for a non-redundant enumeration of near-optimal structures [ 16 ]. We can let the program to report the k best structures. Secondly, we shall provide three variants of our program: pknotsRG-mfe computes the mfe structure (or the k best), pseudoknotted or not. pknotsRG-enf picks out from the folding space the energetically best structure that contains at least one pseudoknot. pknotsRG-loc computes the energetically best pseudoknot that can be formed locally, i. e. somewhere in the sequence. "Best" is defined here as minimal free energy per base, to avoid a built-in bias towards large pseudoknots. The best local pseudoknot motif is included by adding two cases: bestPK = skipleft <<< base ~~~ bestPK ||| bestPKl bestPKl = skipright<<< bestPKl ~~~ base ||| knot These clauses have time complexity O ( n 2 ) and preserve the non-ambiguity of the algorithm. If desired, an enumeration of near-optimal "local" pseudoknots is also feasible. Predictive accuracy We first consider the predictive accuracy achieved by our approach. We have already evaluated the class csr-PK against the known pseudoknots, and we know that our algorithm correctly implements this class in its search space. What is really tested in the following is the adequacy of the current thermodynamic model (which our algorithm shares with RNAfold and in an older version with pknotsRE ), and the results in this section may improve if this model is further improved in the future. We test our algorithm on the set of sequences listed in Table 2 , including 212 sequences from PseudoBase. Although there is some redundancy on the sequence level, there is a good reason why we found it important to use all available sequences for testing: Even near identical sequences can have different MFE structures, or a small change may prevent successful pseudoknot prediction. In contrast to [ 13 ] we did not restrict the evaluation to the class of pseudoknots recognized by our program. It is also instructive to retain the difficult cases, and see whether the predictions catch at least some aspect of a more general pseudoknot. We compare our results to the output of RNAfold , as a representative for RNA folding tools without pseudoknot folding capability, and to pknotsRE where computationally feasible. For each predicted structure we count the number of correctly and falsely predicted base pairs (TP and FP). Let BP be the number of basepairs in the reference structure from the database or literature. We define the sensitivity as (TP/BP), selectivity as (TP/TP+FP). In Table 3 we list the prediction accuracy for our sequence set. For all sequences we enhance the prediction accuracy with respect to RNAfold . Both, the sensitivity and the selectivity increase. Compared to pknotsRE our results are slightly better, probably because we are using the newer and subtler energy model. For example, for the sequence of hepatitis delta virus, our algorithm predicts all helices except for the very short helix 5 (see Figure 3 ), while the other programs miss more than 50% of the basepairs. We also folded 14 randomly selected human tRNAs (third line in Table 3 ) and found only one false positive pseudoknot. Interestingly, the pseudoknotted structure has two helices (9 bp) in common with the true clover-leaf structure, while the structure computed by RNAfold has only one helix (4 bp). For all programs the overall prediction accuracy for tRNAs is not very high. tRNAs are a known hard case for structure prediction because they contain many modified bases. Since we use the same energy model as RNAfold and our algorithm does not introduce spurious pseudoknots, predictions of RNAfold and pknotsRG for unknotted structures are identical. Of course, if there is more than one optimal structure, each of the optimal alternatives may be reported and thus the same folding can not be guaranteed. Computational performance Clearly, we are able to fold sequences that are longer than pknotsRE's limit of 150 nucleotides. Short sequences up to 100 nucleotides are folded within a minute. Long sequences (400 bp) take about 2 hours (see Table 4 ). If we restrict the maximal pseudoknot size to a reasonable constant, say 150 nucleotides, we can further increase the running time. The algorithm runs now in O ( cn 3 ) with a rather large constant c . This enables us to fold sequence of length 1000 in approximately 12 hours. We can further observe that the space requirements scale quadratically with the input size, as expected. For a fair comparison, the reader should keep in mind that the extra time spent by pknotsRE is not strictly wasted: It is spent on assuring that the optimal folding of the input RNA sequence does not contain pseudoknots with chained interacting helices of lower free energy than the reported structure. pknotsRG does not consider such structures and hence cannot make this assertion. Discussion In the following, we discuss extensions of the implemented model and their expected computational cost Bulges, triple crossing and kissing hairpins Canonization Rule 1 can be relaxed further to allow larger bulges inside the helices forming a pseudoknot. As long as their number (and hence the length difference of the two arms of a helix) is bounded by a constant, asymptotic efficiency is not affected. Two examples of non-simple pseudoknots are shown in Figure 4 . We can incorporate them into our algorithm adding the definitions kiss = kss <<< a~~~u~~~b~~~v~~~a'~~~w~~~c~~~x~~~b'~~~y~~~c' triple = trp <<< a~~~u~~~b~~~v~~~c~~~w~~~a'~~~x~~~b'~~~y~~~c' Canonization can be applied as above, with Rule 3 becoming more sophisticated for the triple interaction case. This would yield an algorithm of runtime O ( n 6 ), bringing runtime back to the efficiency class of the Rivas/Eddy algorithm. But note that the space requirements remain O ( n 2 ). This is due to the fact that we now consider three interacting helices, but not arbitrary chains. Folding long sequences RNA folding in vivo as in vitro must be understood as a hierarchical process, where small structures in close vicinity form first, and then combine to larger ones [ 18 ]. The folding path becomes relevant, and the longer a sequence, the more unlikely it is that its folding path leads to a global energy minimum. In other words, the longer the sequence, the less reliable are the results of minimum free energy folding. pknotsRG gives us the possibility to test this using a fairly large structure containing pseudoknots that have been proved experimentally. We considered the sequence of the group I intron from Tetrahymena thermophila (419 NT) (V01416). The MFE-structure found was quite different from the "true" structure taken from the literature. We hand-coded the experimental structure and evaluated its stability in our energy model. The result was striking: the experimental structure (-132.26 kcal/mole) was significantly far from the possible minimum of free energy (-155.64 kcal/mole). So far in fact that it seems infeasible to detect the structure by scanning the space of near-optimal structures. This could be interpreted as the energy model being incorrect, but since it works well for short sequences, we suggest that this is an indication that the kinetics of folding already have a strong influence with this size of sequence, at least when pseudoknots are involved. While we have achieved a considerable speedup for predicting small pseudoknotted structures, it seems that minimum free energy approach is not meaningful with the largest structures which it now can handle algorithmically. However, the situation changes when we are looking for particular structural motifs (see below). Conclusion We presented an algorithm pknotsRG-mfe , based on the MFE-model, for finding the best RNA structure including the pseudoknot class csr-PK. This requires O ( n 4 ) time and O ( n 2 ) space. The algorithm variant pknotsRG-enf returns the energetically best structure that contains a pseudoknot (interesting when the MFE structure is unknotted), while pknotsRG-loc reports the best pseudoknot (under a length-normalized energy score) somewhere in a sequence. We achieve a high prediction accuracy for moderate length sequences, whereas long sequences, at least when pseudoknots are involved, seem to have a folding scheme that cannot be modelled with minimum free energy folding. Algorithm pknotsRG is based on a simpler grammar model than the crossed interaction grammars [ 19 ] underlying pknotsRE , as well as the communicating grammars underlying the recent approach by Cai [ 20 ]. It requires only a minor extension over the ADP tree grammars that are applicable to a wide range of sequence analysis problems [ 21 ]. Furthermore, the grammar is not only a theoretical backup, explaining the underlying model. With minor annotation for the sake of efficiency, the grammar actually constitutes executable code. This means that pknotsRG can serve as a template for a new class of programs we call thermodynamic matchers. Many functionally important RNAs like RNase P or group-I-introns have known structures that include pseudoknots. The search for such motifs using combinatorial matchers like RNAmotif [ 22 ] is hampered by the problem that a motif description is either too specific and misses relevant instances, or else it is too vague and produces a large number of different matches to the same sequence. We suggest to develop thermodynamic matchers , which are RNA folding programs, based on the established MFE model, but specialized to the particular structural motif at hand. Such a matcher returns the optimal way to fold a sequence into the motif structure, together with the free energy of this folding. Comparing this energy to the MFE of an unrestricted folding can give us a hint with respect to the significance of such a match. Methods Choice of implementation method Using the ideas presented so far, our folding algorithm can be implemented in any language suitable for dynamic programming, say FORTRAN or C. However, we are interested in a reusable implementation that can be integrated without change in specialized folding programs called thermodynamic matchers. Therefore pknotsRG was implemented using the method of algebraic dynamic programming (ADP) [ 15 , 23 ]. RNA folding in ADP In ADP, the search space of a DP problem is defined on a declarative level, specified by clauses like the ones we have already seen above. Together they form a tree grammar, defining a tree language whose elements are all the candidates in the search space. In our case, the candidates are RNA structures represented as trees. The typical DP recurrences are implicit in this description. Scoring is achieved by interpreting the operators (e.g., knt, skipleft, skipright ) that build the trees as scoring functions. The grammar needs to be annotated with respect to tabulation and the application of the objective function (in our case, minimization). The advantage of this method is its high level of abstraction. No subscripts, no errors. The perfect separation of search space definition and evaluation allows the same grammar to be used for different kinds of analyses, e. g. folding space statistics. Relevant algorithmic properties such as non-ambiguity and efficiency can be studied on this level of abstraction. Last not least, an ADP program can be executed as is, avoiding the explicit formulation of DP recurrences (and a whole universe of programming errors). A significant, but constant factor of speedup can be gained by explicitly formulating the recurrences and implementing them in a lower level language. Automating this process is part of our current work. We start from an ADP algorithm for folding RNA secondary structures (excluding pseudoknots) provided by Dirk Evers [ 24 ]. We show ADP clauses defining the closed substructures: stacks, hairpins, bulges, and multiloops, adding an alternative for pseudoknots. region denotes an arbitrary sequence of (unpaired) bases. The shown code abstracts from efficiency annotation and the treatment of dangling bases. The complete algorithm is found on the ADP WWW pages [ 25 ]. It is based on the standard MFE model with dangling bases, is non-ambiguous and requires O ( n 3 ) time and O ( n 2 ) space. A size constraint of 30 is used to bound loop length in internal loops. Closed substructures are defined such as to avoid lonely base pairs. While all this is easily expressed within the standard ADP framework, our new algorithm requires extensions which are now explained. Adding pseudoknots The implementation strictly follows the outline given in the methods section, except that a considerable amount of detail related to the energy model has to be taken care of. While ADP bans the use of subscripts, our canonization ideas require to explicitly manipulate subscripts. We show the concrete pseudoknot code, but explain only the essential points. A subscript pair ( i, j ) denotes input sequence positions inp i +1 .. . inp j . [...] denotes lists, and <- denotes enumerating a list of alternative values. knot (i, j) = [pk energy a u b v a' w b' | k <-[i+2 .. j-1], l<-[k+1 .. j-2], These line chooses k and l from the interval ( i, j ), and put together the results from a , u , b , v, a' , w, b' under the scoring function pk . Each helix must have a minimum length of two bases. Due to stereochemical reasons one base in the front part and two bases in the back part are left explicitly unpaired; these bases should bridge the stacks. This consideration is taken over from pknotsRE . The next definitions implement canonization rules 1, 2 and 3. They determine the helix lengths, finally computed into the variables m and m' . If either of them is smaller than 2, a pseudoknot is not possible at this particular location. The function cut shortens the helix b – b' as much as necessary in case of overlapping helices. The next lines define the pseudoknot components a through b ', plus the local energy contribution. To avoid an extra factor of n in time complexity, the energies of maximal length helices are also precomputed in table stackenergy . If the helix b – b' must be chosen shorter than maximal to avoid overlap, a correction term has to be subtracted. This explains the negative term in the energy computation. Left to be defined are the interior structures front, middle, and back. For reasons of space, we only show the definition of front . For a full implementation of the algorithm see additional file 1 . This case takes care of a potentially dangling base from the b -helix, and if the remaining region is not empty, an arbitrary list of substructures ( comps ) is recognized. idd, frd and pul are the corresponding functions from the energy model. Overall, the energy of a pseudoknot consists of stabilizing and destabilizing terms. Where possible, we use the values from the current thermodynamic energy model [ 6 ]. As stabilizing terms we count the nearest neighbour stacking energies of the pseudoknot helices and contributions of dangling bases at both ends of each helix. If the length of the middle part v is smaller or equal to 1, the pseudoknot helices stack coaxially on each other and we further add the appropriate stacking energy. In [ 11 ] a pseudoknot initiation parameter of 7 kcal/mole is proposed. However, we found out, that setting this value to 9 kcal/mole performs better with the new energy model. Our observation supports the similar choice made by Dirks and Pierce [ 26 ]. Finally, we penalize each unpaired nucleotide inside a pseudoknot loop with 0.3 kcal/mole. This seems to be the best approximation of the values given in [ 27 ]. Of course, if the pseudoknot is recursive the energy of the subcomponent is taken into account as well. The first clause (knot) chooses k, l inside ( i, j ), computes m and m' using the precomputed maximal helix information, and passes these boundaries to the pseudoknot compartments. Methodically, this is a use of inherited attributes with the underlying tree grammar, and appears to be a novel technique in dynamic programming, at least in its grammar oriented tradition [ 19 , 28 - 30 ]. The relative effort of implementing the three variants of pknotsRG can be judged from the sizes of the tree grammars required, which are summarized in Table 5 . Availability The three variants of the algorithm pknotsRG-mfe, pknotsRG-enf , and pknotsRG-loc are available as executables and source code on the Bielefeld Bioinformatics Server [ 31 ]. Authors' contribution RG had the initial idea for the algorithm. JR developed and evaluated the software. All authors read and approved the final manuscript. Supplementary Material Additional File 1 Source code of pknotsRG-mfe Click here for file

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The structure of biodiversity – insights from molecular phylogeography

DNA techniques, analytical methods and palaeoclimatic studies are greatly advancing our knowledge of the global distribution of genetic diversity, and how it evolved. Such phylogeographic studies are reviewed from Arctic, Temperate and Tropical regions, seeking commonalities of cause in the resulting genetic patterns. The genetic diversity is differently patterned within and among regions and biomes, and is related to their histories of climatic changes. This has major implications for conservation science.

Introduction Phylogeography, named by Avise et al in 1987 [ 1 ], is a recent and rapidly developing field that concerns the geographical distribution of genealogical lineages. It grew from the newly acquired technical ability to obtain DNA sequence variation from individuals across a species range, and from this to reconstruct phylogenies. These are then plotted geographically to display their spatial relationships and deduce the evolutionary origins and history of populations, subspecies and species [ 2 , 3 ]. Genetic relationships between species based on polytene chromosome banding patterns had been used earlier to deduce the geographic history of colonization and speciation by Drosophila of the Hawaiian Islands [ 4 ], and allozyme variation may still complement DNA information, but the ready access to mitochondrial (mt) DNA sequences opened the door to most animal species and generated this new field [ 5 ]. DNA methods Whilst mtDNA has lead the way in animal phylogeography, other DNA sequences are used, most commonly chloroplast (cp) in plants and non-coding nuclear (nc) regions in both animals and plants. MtDNA has a relatively fast rate of nucleotide divergence, well suited to examining events over the last few million years, but those of cpDNA and ncDNA are an order of magnitude lower and consequently less useful for such young divergences. More slowly evolving sequences are required for deeper phylogenetic history. For more recent events, like the last 10 thousand years, highly variable markers are needed, such as microsatellites and AFLPs, but whilst useful for population studies they suffer from homoplasy and produce equivocal genealogies [ 3 ]. Techniques for obtaining DNA sequence information are still advancing rapidly, with whole genome sequences being produced in a growing number of organisms. This allows sequences and markers to be identified and developed for many types of investigation, and some will be useful for phylogeographic studies. In particular, it is clear that genealogical data is required from several independent nuclear loci to provide a fuller and more reliable history of the species [ 6 ]. Single nucleotide polymorphisms (SNPs) are also becoming available across the genome, which will produce comprehensive measures of genetic diversity and allow the construction of better population histories [ 7 ]. Analytical approaches The advance in DNA technology is producing a wealth of data for individuals, populations and species, and there are concomitant developments in analytical methods to divine demographic history and evolutionary relationships, and to test their significance. This progress in analysis is facilitated by access to increasingly powerful desktop computers on which the increasingly sophisticated software can be used. Haplotype sequences of a particular DNA region can be ordered into a genealogical tree or network, and hence produce their phylogeny. When combined with their population frequency and geographic distribution, this provides a strong basis for inferences on the evolutionary history of the populations and species. The usual phylogeographic approach is to build a phylogeny from haplotype sequences using distance, parsimony and maximum likelihood methods and then represent the lineages geographically. There are several approaches that are regularly used, such as DNA Distance Phylogeography, Nested Clade Analysis, Haplotype Networks, Sequence Mismatch Distribution and Genetic and Demographic Simulation, e.g. PAUP and GeoDis [ 8 - 10 ]. This last approach uses computers to explore broadly how DNA markers evolve in specified molecular, spatial and demographic conditions over history, and is being used increasingly [ 11 ]. Recent developments seek to use the genetic data to estimate the demographic history of a population, the dates of historical bottlenecks or expansions, the size of ancestral populations, the location of refugial areas, the dates of divergence, the extent of migration and gene flow, the extent of fragmentation, and the sequence of such events to produce the present geographic distribution of genotypes, e.g. [ 12 - 15 ]. We can expect further developments to provide even more discriminating analyses. Each DNA sequence has its own genealogy and they may evolve at different rates. Furthermore, the various methods of analysis probe different aspects of the molecular and spatial history. Consequently, to reconstruct a species phylogeographic history one would ideally like to use a range of sequences (including nuclear, cytoplasmic, sex-linked, autosomal, conserved, neutral, high and low mutation rate) and apply a suite of pertinent analyses. This is not easy and often not possible with resources available. However, technological advances for molecules and computers have been explosive in the past decade, making much more detailed analysis possible today than only a few years ago, and this looks set to continue. Paleoclimate and Paleobiology The very different field of paleoclimatology is also experiencing great advances. The results of these are most pertinent to phylogeographic explanations, since they reveal the past environmental conditions and changes that have molded the evolutionary processes producing the present genetic structure. They provide a framework in which the phylogeny may be reconstructed. Past conditions can be deduced from carbon and oxygen isotopes, radiolarian skeletons, pollen grains and other residues from the sea bed, lake bottoms and ice sheets [ 16 ]. Novel information sources like insect exoskeletons, coral terraces and stalagmites are adding to this [ 17 - 20 ]. Such records show that earth's climate has been cooling for some 60 my with periodic (21, 41 and 100 kyr) global oscillations producing increasingly severe ice ages through the Quaternary (2.4 my). These involved greatly enlarged ice sheets and surrounding permafrost, and the lower temperatures and reduced water availability caused great changes in the distribution of species as demonstrated by the fossil record [ 16 , 21 ]. Nested within the major 100 kyr cycles are millennial scale oscillations, which can occur rapidly and are often severe [ 22 , 23 ]. Changes of 7–15°C may occur in decades and persist for centuries, as happened most recently in the Younger Dryas (11 kya), where fossils record shifts in the distributions of species. These major changes in distributions of species occurred latitudinally as the ice sheets advanced and retreated, altitudinally in major mountain regions, and also longitudinally where new dispersal routes became available, as for example the Bering land bridge produced by the lowered sea level. The demographic fluctuations and adaptive challenges produced by such range changes would have had both stochastic and selective effects on the genetic variation and architecture, and the consequences of these can be studied by genetic and phylogeographic approaches. Thus the once distinct fields of paleobiology and phylogeography are now being combined, and have much to tell us about how present biodiversity was structured. Fossil and Genetic Signals of Range Changes With some effort it is now possible to obtain DNA data from specimens across the present range of a species, but fossil data is often more limited or absent. The most useful fossil data are for Europe and North America, which have extensive networks of pollen cores; a few span 3 ice ages (400 kyr), several reach the last interglacial (125 kyr), and a larger number cover back to the last glacial maximum (LGM 23-18 kyr) [ 21 ]. There are also some helpful detailed series of beetle exoskeletons [ 24 ]; animal bones and plant macrofossils tend to be localized and discontinuous, but are nonetheless useful markers of time and place. Reconstructions of paleovegetation have been made, e.g. [ 25 ], which are quite detailed from the LGM to the present, and when coupled with other fossil evidence indicate the extent and rapidity of changes in species distributions. During the LGM the ice sheets and permafrost extended towards lower latitudes, so that generally species distributions were compressed toward the equator. Boreal species survived south of the ice in North America and Europe, but large areas of the north eastern Palearctic and Beringia remained ice free and some cold-hardy species appear to have survived here. Temperate species survived further south where habitats occurred to which they were each adapted. In Europe the disjunct southern peninsulas of Iberia, Italy and Balkans were particularly important, while in North America many temperate locations occurred around 40°N between the East and West coasts. Nearer the equator the pollen record is not extensive, but conditions were generally drier in the LGM and Tropical habitats were reduced while desert and savanna increased. As a consequence, the habitats of many Boreal, Temperate and Tropical species were reduced and fragmented and they survived in refugia; but for some their habitats expanded, like those in the tundra and savanna. As the climate warmed after the LGM and the ice retreated, many Boreal and Temperate species were able to expand their ranges, as were some Tropical species. In some cases the refugial populations died out, but particularly in mountainous regions they could survive by ascending with the climate and their niche, as for example in the Alps, Andes, Appalachians and Arusha mountains. Such refugial regions allow the survival of species through several ice age cycles by ascending and descending to track their habitat, e.g. [ 26 ]. Such events modify the genetic content and structure of populations within species, and leave some traces for which we may search. Populations, races and subspecies that have been effectively separated for several glacial cycles will show divergence through the accumulation of neutral and possibly selected DNA changes. The extent of this divergence will be proportional to the time of separation. The haplotype tree or network of an evolving DNA sequence will reflect population expansions and contractions. Increasingly these effects can be analyzed, e.g. [ 27 ] and placed in some order of occurrence. When the geographic positions of haplotypes are included, a further range of deductions is possible. For example, recently derived populations will contain a sample of the same haplotypes as the parent populations, which combined with paleo-information allows colonization routes to be deduced [ 28 , 29 ]. The extent of distribution of younger haplotypes compared with that of older ones in the tree provides information on the past fragmentation of populations and processes involved in colonization [ 30 ]; this can also be combined with paleo-information to deduce the intraspecific phylogeographic history. Higher Latitudes – the Arctic Most phylogeography has concerned Temperate biota [ 2 , 26 ], but recently a number of species from higher latitudes have been analysed in sufficient detail across their range to provide some first genetic insights into their biogeographic history. These include mammals, birds, fish, crustaceans and plants adapted to such cold conditions [ 31 , 32 ]. Table 1 contains some major studies of Holarctic animal species complexes. During the LGM the greatly extended Arctic ice sheets forced such species south, as evidenced by fossil records in Europe and North America. At the same time, large areas of Northeast Asia and the NW corner of North America were covered in permafrost but not glaciated. Fossil evidence suggests that these also contained refugia, particularly Beringia [ 18 , 33 , 34 ] which with lowered sea level joined Asia and America across the Bering Straits. The different range changes involved would be expected to have various effects on the genetic diversity that may have left marks of their occurrence and extent. Table 1 Animal species with Holarctic ranges showing distinct phylogeographic pattern, with some indication of their possible divergence times, glacial refugia and genetic signals of population history. CA = Circumarctic, HA = High Arctic. PA = Palearctic, NA = Nearctic, BE = Beringia, GL = Greenland, NT = North Temperate. Species Range Phylogenetic Divergence (Myr) Likely Refugia (fossil evidence *) Genetic signals of range changes Authors & Reference Larus argentatus spp Herring gull complex CA HA (+EurAsia Lakes) 9 clades <0.5% (0.1–0.3) Atlantic Aralo-Caspian Allopatric fragmentation Bimodal mismatch Recent expansions Hybridizations Liebers et al [96] Rangifer tarandus tundra reindeer CA HA 7 clades 1–2% (0.1–0.3) Beringia-Asia * W EurAsia* N America 150 kyr expand 15 kyr expand Ragged mismatch Gravlund et al [97] Flagstad & Roed [98] Lemmus ssp true lemmings HA PA NA 4 clades 3.8–7.9% (0.5–1.0) Beringia E Asia Siberia* N America* Expand Few haplotypes Few haplotypes Expand Fedorov et al [99] Dichrostonyx ssp collared lemmings HA PA NA GL 6 clades 1–7% (0.1–1.0) Beringia* Arctic Islands E Asia C&W Siberia* Not to east Expand Low diversity Low diversity Fedorov & Stenseth [100] Microtus oeconomus root/tundra vole HA PA BE 4 clades 2.0–3.5% (0.2–0.6) Beringia S Urals* Caucasus C Europe* Not far Few haplotypes N expansion N expansion Brunhoff et al [101] Microtus agrestis field vole not HA, PA 3 clades 0.5–5.2% (0.1–0.6) S Urals* Carpathians* Iberia Across Asia N&W expansion Not far Jaarola & Searle [102] Lagopus mutus rock ptarmigan CA HA 7 clades 0.21–1.12% (0.05–0.1) Multiple, eg Greenland – Beringia/Aleuts Siberia Several recent Expansions Only 4% diversity within lineages Holder et al [103, 104] Calidris alpina Dunlin (migrant) CA 5 clades 1.1–3.3% (0.1–0.3) W Africa Arabia SE Asia C America W EurAsia Siberia Beringia Canada Wennerberg [105] Wenink et al [106] Daphnia pulex Waterflea (clonal) CA HA 7 clades 0.5–3% (0.2–1.5) Periglacial Some more local clones Mixing, but some N Amer/Eurasian difference Weider et al [107] Troglodytes troglodytes Winter wren NT not HA EurAsia BE N Amer 6 clades 3.0–8.9% (0.5–1.6) NW Amer NE Amer NE Asia C Asia, S Europe Series of glacial vicariances Recent expansions Drovetski et al [38] Cleithrionomys rutilus/glareolus/gapperi red-backed voles HA PA NA BE 12 clades 1–10% (0.1–1.8) C Europe* E Asia* Beringia N Amer* Several colonizations of N Amer across Beringia from Asia Cook et al [37] Distinct Parapatric Clades, Refugia and Range Changes The phylogeographic structure, in terms of distinct regional DNA clades, is very marked in some species like the lemmings, voles and wren, moderate in the ptarmigan and dunlin, and less in the more mobile waterflea, reindeer and herring gull. The extent of DNA divergence between major clades in small mammals would suggest effective separation of up to 1 Myr, some 5–10 full glacial cycles, with further subdivision for shallower clades in more recent ice ages. In the gull, ptarmigan and reindeer the divergence among clades is low, indicating events occurring in the last or penultimate glacial cycles. Such recent structure would suggest that these species came from or were reduced to a small ancestral population in the late Pleistocene. The deeper clades of the true and collared lemmings, the root and field voles, and to some extent the shallow ones of the ptarmigan and dunlin, are remarkably parapatric and many contacts between them coincide around major features like the Urals, Lena, Kolyma and MacKenzie Rivers (Fig 1 ) [ 32 ]. Regions where several subspecific and sister-specific boundaries coincide, called suture zones [ 35 ] have been recorded in North America and Europe, and are probably due to species having similar range changes and refugial areas [ 29 ]. Thus these regional parapatric genomes seem to have been diverging separately over a number of ice ages, with distinct refugia from which they colonized to fill their individual interglacial distributions. The pattern of range changes may not be exactly the same through each cycle, but there is no sign of genetic mixing among mtDNA clades, and the major boundary features and refugia are likely to have been similar over the last few ice ages. Other taxon contacts occur in these regions in groups like birds and butterflies, and it will be informative to investigate their phylogeographies to look for commonalties and causes. Figure 1 A polar projection showing the general regions of contact between diverged DNA clades of six Holarctic species (see text and references for details and Latin binomials). Note the clustering near features like mountain ranges and major rivers. The Scandinavian cluster, which includes a number of other species, forms where the last remnants of the ice cap melted. Last glacial ice caps and sheets are in white, and tundra is darker grey (I am grateful to Richard Abbott for the basic map). Each distinct regional clade would have had its own refugium, but the location of these remains to be determined. There are late glacial fossils of small mammals in Central Europe and also near the southern Urals, which were both parts of the extensive tundra and could have been refugia for European and west Asian clades. An additional refugium in east Asia would account for the clades meeting in the regions of the Lena and Kolyma Rivers, while fossils for a number of species in Beringia indicate that it was probably a significant refugium [ 32 ]. A recent detailed examination of the phylogeography of the tundra vole in Beringia [ 36 ] pinpoints the contact between the Central Asian and Beringian clades on the Omolon River in the Kolyma uplands, which formed a partially glaciated barrier during the last ice age. This would obviously affect other species and provide the western boundary to many Beringian distributions. The equivalent boundary of Beringia in the east was formed by the North American ice sheets which fringed Alaska from the MacKenzie River to the Aleutian Ranges. The contractions, expansions and distant colonizations involved in these late Quaternary range changes would have influenced the genetic diversity, and should have left some signs. Low haplotype diversity and shallow clades are expected when populations have been severely contracted, and the age of the subsequent expansion may be gauged by mismatch analysis. The structure of haplotype networks and nested clades also provide indications of such events. Many of the populations and clades reported show these features (Table 1 and references). For example, tundra reindeer, herring gulls and rock ptarmigans have shallow clades diverging in the recent ice ages and populations with mismatch analyses indicating postglacial expansion and colonization of high Arctic regions. In those species like the lemmings and voles where DNA lineage divergence goes back several ice ages to perhaps the onset of more severe glaciations some 0.9 My, most clades are shallow with low diversity, particularly those for Central Asia, suggesting extensive colonization from a much reduced refugial source. This is an emerging feature of some significance. It does seem that even for cold adapted species life was hard in Central Asia during the ice age and it provided few refugia. Beringia – an Arctic Refugium Beringia, which spans Eastern Siberia and Alaska, was united and disjoined each Quaternary ice age by changes in the sea level of some 120 m. It was only partly glaciated and fossil evidence shows it supported a mixture of tundra habitats, which allowed it to act as a causeway for continental migration between Asia and America for various species, including humans. The history of Beringia is currently of interest and some of the lower parts now under the Bering Sea probably had conditions suitable for mesic tundra species even in colder times [ 18 ]. Several species have a distinct genetic clade across Beringia and some of these show higher diversity here than where previously glaciated regions were colonized, supporting its role as a glacial refugium [ 32 ]. A careful analysis of genetic diversity in the tundra, or root vole, Microtus oeconomus through Beringia indicates that the Beringian voles probably expanded from a population with low genetic diversity, which had colonized from Central Asia in the penultimate glacial cycle [ 36 ]. A broader phylogeographic study on related taxa of red-backed voles, Clethrionomys , demonstrated that North America has been colonized successfully from Asia at least twice, possibly three times in the mid-Pleistocene, and C. rutilus reached Alaska quite recently with the first Nearctic fossils in the Holocene [ 37 ]. The phylogenies of a number of other species, including Homo sapiens also indicate Beringia as a colonization corridor. Analysis of the DNA differences among these Clethrionomys species reveals that they have been diverging from the Early Pleistocene, whilst the divergence within the other listed species is much younger (Table 1 ). An exception is the winter wren, where there are six clades that appear to have begun diverging some 1.6 Mya, suggesting possible cryptic species [ 38 ]. These distinct clades contain low diversity and signs of contraction and expansion. The species does not inhabit truly high Arctic habitats, reaching down to more Temperate latitudes. It would seem that its Holarctic range was progressively broken up by the increasingly severe Pleistocene glaciations, with connection across the oceans, Beringia and the centres of the continents becoming more difficult or impossible as its more Temperate range was forced south. Mid Latitudes – Temperate Regions So called Temperate species span a wide range of latitudes, since the climate determinants like insolation, oceans and altitude may produce suitable habitats between 20° and 60°. In Eurasia and North America those more cold hardy species generally have more northerly distributions than those better adapted to more southerly warmer climes, and this will also be reflected in altitudinal range differences. This would also be true of distributions in glacial periods, so that refugia for north Temperate species were nearer to the ice and permafrost than those of more southerly ones. Fossil evidence is very important in properly determining such Pleistocene range changes [ 39 ]. In the Arctic species considered (Table 1 ), the winter wren and field vole provide examples of low Arctic/north Temperate species in what is a progression of adaptations, niches and ranges on the cold to warm axis from pole to equator. Refugia and Colonization in Europe and North America Paleoclimate and phylogeography have been most researched in Temperate Europe and North America, generating many particular examples and several more general conclusions [ 2 , 26 ]. In particular, the similarity among DNA haplotypes across a species range allows the deduction of which northern populations came from which southern populations, and their likely postglacial colonization routes. The fossil record underpins these deductions, particularly for refugial areas and times of colonization [ 26 , 28 ]. Thus many species survived the LGM in southern Europe, the centre and north being covered in tundra and ice. Fossil and DNA evidence show that the peninsulas of Iberia, Italy, Greece and the Balkans were major refugia and contributed variously to the postglacial recolonization of the north. Whilst a few mobile species crossed from North Africa, the Mediterranean Sea appears to have been a major barrier throughout the Quaternary. For many species these southern refugial areas currently contain much genetic diversity for haplotypes, lineages and subspecific taxa. These southern parts of Europe are also mountainous, so that species may survive by ascending and descending with climate changes. The extent of genetic divergence among these peninsular populations clearly indicates that for many species they have been effectively separate for several to many ice ages. Importantly, this separate refugial survival is seen as a causative factor in divergence and speciation [ 3 , 29 ]. It is possible to deduce pathways of genetic divergence in a geographical framework that has produced the continent's diversity of populations, subspecies and species. The fossil record, in particular that of pollen and beetles, shows that postglacial colonization was to a large extent a property of the individual species niche and the distribution of its habitat. Nonetheless, the patterns of DNA divergence within species have some common features, which argue for common colonization processes and routes [ 29 ]. Temperate species often show reduced haplotype diversity in the north, which is considered to be the result of rapid colonization with repeated founder events. This is seen in many species in Europe and North America, e.g. [ 28 , 40 - 46 ]. Furthermore the recolonized areas are often a broad patchwork of distinct genomes that have emanated from the different refugia, and which usually form hybrid zones where they make contact. These hybrid zones in different species often appear to be clustered together and so may be considered to belong to suture zones [ 29 , 35 ]. In Europe the Balkan haplotypes and genomes provided the main source for postglacial colonization for many species, while less came from Iberia and few came from Italy, probably hindered by the ice-capped Pyrenees and Alps. Species that exemplify these different patterns of colonization are the grasshopper, Chorthippus parallelus , the bear, Ursus arctos , and the hedgehog, Erinaceus europaeus/concolor [ 29 ]. Freshwater fishes like the chubb, Leuciscus cephalus , often show colonization by different haplotypes up the Danube and Dneiper Rivers from the Black Sea (Fig 2 ) [ 32 ]. Many European species phylogeographies are emerging and a considerable number broadly show these distribution patterns and probably followed similar colonization routes despite differences in their niche, mobility and life history. This apparent and remarkable commonality would seem to be a result of colonization following postglacial climate change in Europe's particular geography of southern peninsulas, transverse mountain ranges and northern plains. It demonstrates the explanatory power of combined phylogeography and paleoclimatology. Figure 2 Likely postglacial colonization routes from refugial areas in Europe and North America for a distinctive sample of species that have been deduced from DNA haplotype relationships. Note that regions like central Scandinavia, Britain, the Pacific North West and central Canada contain a mixture of species whose genomes have come from different refugia (see text for discussion). A particularly interesting consequence of these various colonization routes is that northern regions like Scandinavia and the Pacific NW of America have biotas that are mixtures of species whose genomes came from different refugia [ 26 ]. Thus in Central Scandinavia the grasshopper genome came from the Balkans, the bear from Iberia and Russia, the hedgehog from Italy and the chubb from the Black Sea. For the NW corner of America, where Alaska, the Yukon and British Columbia meet, DNA evidence suggests that it has been colonized sequentially from four directions; (1) initially from the south along the coast by the long-tailed vole, dusky shrew, ermine and marten, (2) then from the south by an inland route by all but the marten, (3) from Beringia by the ermine, and (4) from the Appalachians by the marten, and possibly bears and chickadees (Fig 2 ). Several plant species also colonized probably along the two southern routes [ 32 ]. Such mixed biotas carry a number of important implications. They mean that the component species from different refugia have not been evolving together during the previous glacial periods, so any close coadaptation must be either postglacial, or possibly survive from when their distant ancestors were sympatric. More general species-wide coadaptations may be maintained if the different species survive together in refugia. Where genomes from two or more refugia come together, genetic diversity will be increased by the presence of diverged lineages, as seen in hybrid and suture zones. Two populations in the same region living in similar habitats, but from different colonizing refugia will possess very different alleles and genomes, while conversely two very distant populations in distinct habitats may have the same refugial genome. This points to the importance of population history in the process of post glacial adaptation, and our understanding of it. Mediterranean Latitudes – 30–40°N The Mediterranean Sea, with Europe's refugial peninsulas and mountains in the north and North Africa to the south lies between roughly 30°N and 40°N, where at these latitudes in North America there are the Southern States across the Appalachians and Rockies to California. While in Europe the Scandinavian ice sheet came down to Warsaw about 52°N with extensive tundra to the south, the Laurentide ice sheet reached near 40°N. below the Great Lakes, with very little tundra and steppe. Such contrasts in geography have produced differences in the phylogeography of species, but there are also similarities. Species in these southern regions generally contain greater diversity for alleles, populations and subspecies, which in several form distinct geographic genomic patches. The divergence among southern lineages and patches is often deeper than further north, indicating a longer survival and probably in the same region. This southern divergence is often estimated to be over many ice age cycles from the Early Pleistocene or even the Pliocene for some species [ 26 ]. The best-studied regions in these latitudes are Iberia [ 47 ], South Eastern USA [ 2 ] and West Coast USA [ 48 - 51 ]. Molecular phylogeography began in the SE USA [ 1 ] and many terrestrial and aquatic species there have marked genetic substructure with concordant genomic boundaries [ 52 ]. A number of recent studies in Iberia, covering a range of organisms, e.g. beetles [ 53 ], lizards [ 54 ], salamanders [ 55 ], woodmice [ 45 ], rotifers [ 47 ], and several plants, also show this intraspecific diversity and substructure, with lineages from as early as the Pliocene and often in mountain regions. Likewise West Coast phylogeography for salamanders [ 56 ], woodrats [ 51 ], shrews [ 50 ], frogs [ 57 ] and other species from California and the Cascades [ 49 ] reveals geographically structured lineages diverging from the Pliocene and Pleistocene. This pattern and divergence would seem to be a product of the geological and climate changes that have occurred, involving major mountain building and Quaternary ice ages. Lineages and populations from the northern parts of such southern regions, like the southern Appalachians, west and central Iberia and the northern Cascades, appear to have provided the main source for northward postglacial colonization, while genomes to the south survived with altitudinal shifts in broadly the same regions [ 32 ]. Species with distributions north and south of the Mediterranean Sea must have managed to cross this now major barrier to terrestrial organisms at some stage before or since the opening of the Gibraltar Straits some 5.3 Mya after the Messinian crisis [ 58 ]. If this was before 5.3 My, they are likely to have diverged to sister species if there has been little gene flow. There are now phylogeographic studies on a few species both terrestrial and volant. In terrestrial species of salamanders Salamandra spp and scorpions Buthus spp [ 59 , 60 ] the DNA data shows that the N African/European divergence is old, before the opening of the Gibraltar Straits. While in the woodmouse Apodemus sylvaticus [ 45 ] the N African haplotypes appear recently derived from southern Iberia, possibly transferred by humans. Interestingly an old divergence in holm oak, Quercus ilex , may also perhaps be due to humans [ 61 ]. Five flying species have been examined, of which the chaffinch, bearded vulture and barbastelle bat [ 62 - 64 ] have DNA phylogenies that indicate the Gibraltar Strait has not been a major barrier. In dragonflies Calopteryx spp [ 65 ] the North African genotypes are related to the Italian ones, and in honey bees [ 66 ] some African mtDNA haplotypes are found in south Iberia and Sicily, but nuclear markers indicate little migration. These latter two species and the bearded vulture appear to have crossed the Sicilian Channel, which was also narrow during the lowered sea level of the pleniglacials. Lower Latitudes – Tropics and Savannah Much of Africa, South America, South East Asia and North Australia lie in the Tropics. They are rich in species diversity, but with a few notable exceptions little is known of their phylogeography or their paleobiology [ 26 ]. During the recent ice ages the climate was colder and drier in the Tropics, with increased deserts and savannah and reduced rain forests. The pollen record is unfortunately poor, but it seems that forest species descended the mountains (~6°C lower LGM), while lowland forest species may have survived in many local wet places and gullies [ 16 , 67 , 68 ]. It would seem clear that even tropical biotas have undergone repeated changes as a result of climatic oscillations through the Quaternary [ 26 , 69 ]. Wet Tropics Several phylogeographic studies from American and Australian rainforests and a few from Africa and Asia indicate that there is great genetic diversity produced by a complex history often diverging in the Pliocene [ 26 , 70 ]. A nice example of this has been studied in the montane forests of the central Divide of Costa Rica, where a North American salamander Bolitoglossa has radiated into tropical Middle America [ 71 ]. There are strong allozyme and mtDNA differences between several populations only a few kilometres apart (Dnei 0.18, cytb 4%), and 2 putative species within 10 km (Dnei 0.45, cytb 9%). Such genetic distances indicate divergence from the late Pliocene through the Pleistocene. This has involved several adaptations to elevation zones that would have been amplified by local topographic isolation and climatic oscillations. These amphibians may have peculiar attributes, but phylogeographies of birds and freshwater fish in Middle America are also complex with many lineages [ 72 ]. There are few studies yet, but it may be that the phylogeographic status of Bolitoglossa is not so unusual. Recently over 100 species of rhacophorine tree frog were described in Sri Lanka using mtDNA in combination with exophenotypic measures, when only 18 were previously known, and despite recent extinctions by Man's activities [ 73 ]. This suggests that tropical biotas are not only amazingly diverse but highly structured genetically, both above and below the species level. Genetic studies in tropical rainforests of SW Amazonia and NE Australia show phylogeographic divergence that is geographically concordant across a number of taxa and also originating in the Pliocene. The first set concern some 35 species of small mammals sampled along the Jurua River, and where for the majority there is a deep phylogenetic divide coincident with the Iquitos Arch. This formed as a bulge in front of the uplifting Andes in the Pliocene creating two basins that filled with sediment. The depth of mtDNA divergence between clades in these two basins places their separation at this time [ 74 ]. The Iquitos Arch is also implicated in the phylogeographic structure of the dart-poison frog Epipedobates femoralis , which was also sampled along the Jurua River traversing this ancient ridge, and which also has coincident mtDNA divergence (cytb 12%) dating to the Pliocene [ 75 ]. Interestingly, the collection sites differed markedly for their haplotypes, particularly in the headwaters region, again suggesting considerable local genetic structure. There has been a multitude of hypotheses proffered to explain the structure of Amazonian diversity, and such molecular phylogeographic approaches are beginning to distinguish amongst them. The second set of phylogeographic studies involves several birds, reptiles and frogs from the remnant strip of tropical forest in NE Queensland [ 76 ]. This wet forest has undergone contraction and fragmentation during the drier colder stages and expanded in the interglacials. These show concordant mtDNA divergence that possibly dates back to the Late Pliocene. This is coincident with the Black Mountain Corridor, a narrow region from which rainforest disappeared in the Pleistocene ice ages producing main north and south refugia. The north and south clusters of haplotypes have various structures, some of which show low diversity probably due to population contractions during the ice age, while others have retained more haplotype diversity possibly by survival in local patches of forest. The rainforest snail Gnarosophia bellendenkerensis also shows these main phylogeographic features, and with some finer subdivisions. Its distribution from the LGM to the present has been modeled using current climate envelopes for this snail species mapped onto reconstructed paleoclimate distributions [ 77 ]. There is good agreement between the changes in the modeled snail distribution from the LGM to the Holocene and the signals from mtDNA data of refugial locations and expansions. Such an approach provides support for the deductions of both paleoclimatic modeling and phylogeography. Furthermore, the relationship between particular paleoclimatic changes and genetic structure is sharpened by studies on other species from this region that are not adapted to rainforest, like grasshoppers and frogs [ 78 , 79 ]. These species show genetic subdivision that is coincident with other physical features that would provide refugia and barriers commensurate with their lifestyle and climatic history, such as the coastal humidity transition or Burdekin Gap. The phylogeographic pattern demonstrated by amphibians, reptiles and small mammals, is also found in bird species from tropical Africa and South America, which show old Pliocene lineages in the lowland forest and mixed old and recently diverged clusters in the mountains. This has lead to the proposal that such mountains provided a relatively stable environment through the ice ages and rising mountains, in which older lineages survived and new ones were created [ 80 ]. DNA divergence in spinetails from the Andes [ 81 ] and greenbuls from East Africa [ 82 ] provide evidence of montane speciation through the Pleistocene. Such mountain ranges appear to act as generators and reservoirs of lineages and species, and this probably is a function of their low latitude and topographic variety, which provide warm wet habitats through climatic and altitudinal range changes. The repeated small shifts in distribution driven by climate, along with continued uplifting of these mountains would provide conditions for contraction, selection, expansion and speciation. Dry Tropics There have been a number of recent DNA studies of several larger mammals from Africa that provide some interesting insights into how Pleistocene climatic changes modified their ranges and hence their genetic structure and divergence (Table 2 ). Whilst sampling such species across Africa is a major task, the threat posed by reductions in their numbers means that considerable efforts are being made to assess their genetic makeup for management and conservation, and many have a useful fossil record. They are not inhabitants of the wet forests, which were reduced during the colder drier glacial periods, but are found largely in the savannah grasslands and woodlands that had a different pattern of contraction and expansion. These habitats increased with the onset of the Pleistocene and its increasing glacial activity (3-2 Mya), with periods of dominance recorded around 1.7 and 1.2 Mya. They show increasing prevalence from 0.6 Mya through the Late Pleistocene, and fossils record the emergence of the associated mammal species and their subspecies since then (see references in Table 2 ). The DNA data, although not an accurate measure over this time scale, also indicates that these are recent events with most divergences in the last 0.4 My. Table 2 Larger mammal species from across African savannah grasslands and woodlands showing phylogeographic pattern, with some indication of their phylogenetic structure and possible divergence times, refugia in west W, east E, and south S, and genetic signals of colonization and population history. LP = Late Pleistocene, MP = Mid Pleistocene, EP = Early Pleistocene, → = colonization/expansion. MS = mismatch expansion. All studies used d-loop mtDNA; also elephant used cytb and microsats, impala cytb, warthog and dog microsats, and buffalo Y. Species Phylogenetic structure Likely Refugia (fossil evidence *) Genetic signals of range changes Reference Hartebeest Alcelaphus buselaphus 3 step clades W→S→E, W, E subdiv, S, *0.7 My> S→, E→, some shallow clades Arctander et al [83] Topi Damaliscus lunatus 3 clades S→E (+ S) (W), E, S, *0.7 My> S→, 2 clades, MS E→, shallow clade, MS Arctander et al [83] Wildebeest Connochaetes taurinus 2 clades, S→E, S structured E, S, *1.5 My> S→E, MS in E LP Arctander et al [83] Kob (& Puku) Kobus kobus sl 3 clades, W→E + S W, E, S * EP> W↔E several times, lineage mixing, MP LP Birungi & Arctander [108] Greater Kudu Tragelaphus strepsiceros 3 clades, E, SW→S→E E, S, SW isolate *widespread S→E LP shallow clades diversity S>E Nersting & Arctander [84] Impala Aepyceros melampus 2 clades, SW, S→E (E), S SW isolate *widespread S→E LP network cluster E diversity S>E Nersting & Arctander [84] Wild dog Lycaon pictus 2 shallow clades, E, S, few haplotypes (W), E, S W→E&S?, 340 ky> each clade 70 ky> mobile – mixing Girman et al [89] Buffalo Syncerus caffer 2 shallow clusters W→E+S S nested in E W, E, S, * LP W→E <180 ky E→S twice <130 ky MS LP Van Hooft et al [85] Elephant Loxodonta africana 3–5 clades W→E+S→W W, E, S, *EP *LP→ W→S&E, EP W→S&E, MP E→W, LP Nyakaana et al [109] Eggert et al [88] Warthog Phacochoerus africanus 3 distinct clades W→S→E W, E, S, *0.78 My> *0.4 My→ 3 clades isolated MP by dry climate contract/expand LP Muwanika et al [87] Most phylogeographies show some 3 major clades that are associated with 3 main areas of Tropical Africa, the west, east and south, indicating that these have been major refugial areas for the development of this divergence through climatic cycles in the Late Pleistocene (Fig 3 ). Many have shallow clades, mismatch analyses and star-like networks that are the expected result of contractions and expansions of these populations, and their phylogeographies indicate various colonizations between these major regions. In three species, the wildebeest Connochaetes taurinus , greater kudu Tragelaphus strepsiceros and the impala Aepyceros melampus , the data support colonization northwards to the east from refugia in the south of Africa [ 83 , 84 ]. The greater kudu and impala have distinct SW clades, which suggests isolation and survival there, as well as central South Africa, where many species appear to have had a refugium. Interestingly the first wildebeest fossils are from east Africa, so that the species seems to have disappeared from this region and been recolonized recently from the south. Figure 3 Africa with major vegetation and mountain areas. Reduced Tropical rainforest at the LGM is shown. The Savannah species often show West, East and South clades (see Table 2 for details) and the general areas of these are indicated. The genetic data also indicates colonisations between these possibly refugial areas in the middle and late Quaternary Period. On the other hand, the Cape buffalo Synercus caffer caffer has younger haplotypes in the south, which along with mismatch analyses suggest one or two recent colonizations from populations in eastern Africa. The DNA divergence of these from central African buffalo subspecies is perhaps only 180-130 kyr, and roughly coincident with the Cape buffalo's genetic expansion and evidence from fossils [ 85 ]. The hartebeest Alcelaphus buselaphus and the topi Damaliscus lunatus probably survived in a few places in southern and eastern Africa from which they expanded with better conditions [ 83 , 86 ]. The warthog Phacochoerus africanus is now relatively widespread, but has 3 distinct clades equivalent to subspecies, and with low divergence within each one [ 87 ]. This points to strong isolation through the last few ice ages with considerable recent population reduction followed by population expansion. The mtDNA phylogeny of the African elephant is more complexly structured, with haplotypes of the putative species of forest Loxodonta cyclotis and savannah L. africanus elephants mixed together in several clades [ 88 ]. It suggests successive production of clades from the early Pleistocene, which involved colonization from the centre to the south and east with increasing savannah habitats, loss of competitors and punctuated by climatic cycles. Such admixture of clades in regions and taxa is probably a reflection of several such colonizations, and a recent invasion of western Africa from central regions is also indicated by the haplotype distribution. The African wild dog is very mobile and populations over the middle part of its current eastern through southern range show a mixture of haplotypes. There are 2 shallow but distinct mtDNA clades that would have diverged perhaps 340 kya, with each coalescing about 70 kya [ 89 ]. The cause of this divergence is not clear, but restriction in habitat by climatic oscillations, and separate colonization of east and south from western Africa are possible. Whilst there are common features within and distinguishing ones between the wet and dry examples reviewed from the Tropics, there are individualities to each species phylogeography; these reflect differences in biology and history that have produced differences in genetic structure. The richness and diversity seen at the species level is multiplied by that within species, and more studies are needed on biotas from such habitats to properly describe and understand them. Little is known from the species rich Tropics of SE Asia, or from the plains of S America and the large areas of Temperate Asia. There are a number of individual studies on a range of species, but one needs several representatives from each community to look for generalities. Given the species diversity in these areas, such genetic and phylogeographic knowledge is particularly important to inform sensible decisions on management and conservation of these resources. Lessons for Conservation from Phylogeography Man is in the unique position to know and predict the consequences for the environment and its biota of his innate will to survive and reproduce. Our actions are greatly modifying both of these, so we face the challenge of managing this sensibly. But we must also think of these natural and induced biotic changes in the light of future major changes in the climate. It is clear that global oscillations, producing great climatic changes, have occurred and will continue; in particular the increasingly severe Quaternary ice ages, which are now well researched and clearly demonstrated. Biotas have changed greatly due to these, and will do so again. We are currently well into an interglacial, the Holocene, and there is debate about how soon it will end and how quick this will be. If the North Atlantic conveyor is turned off, and Man may assist in this, colder conditions may return very quickly. On the other hand, in the shorter term global warming may continue, and Man may assist this! What should we do about biodiversity, and how does phylogeography inform us for this? The distribution of biodiversity across the world is largely measured as species diversity – their numbers, proportions and distinctness. But within a species there are often several geographic subspecies, and genetic studies have added greatly to knowledge of subspecific diversity, with some regions possessing more lineages and older divergence. Mountain ranges in warm Temperate and Tropical regions are seen to be important because they harbour much diversity at species, lineage and allelic levels. Phylogeographic studies reveal that this is likely a product of species surviving through climatic oscillations by tracking their habitat altitudinally and locally in a varied topography in regions not so affected by the extremes of climate change, e.g. [ 26 ]. The southern mountains of Europe, the southern Appalachians and western mountains of USA have clearly been important as refugia and provided most colonists for the vast north Temperate regions today. DNA divergence argues that this has happened repeatedly and so will probably happen again. To date there is little information on the patterns from Asia or S America, and it is needed. Such regions of Temperate refugial genetic diversity have accumulated lineages and alleles through several ice ages and deserve particular research and conservation. The mountain regions in the wet Tropics of Africa and South America are very rich in species; while phylogeographic studies reveal that these contain divergences often into the Pliocene with subsequent diversification through the Pleistocene. This retention of older diversity through millions of years along with younger lineages argues that they are both generators and reservoirs of divergence and species [ 26 , 80 ]. Less is known about the Tropical regions than Temperate ones, but the phylogeographic evidence does suggest that they can contain greater diversity and divergence in an area, as for example in the wet forests of Costa Rica or Queensland [ 71 , 90 ]. One wonders just what genetic diversity the species in the mountains of China and SE Asia contain. However, tropical Asia is even less studied than Africa and Central America, and with the rapid anthropogenic changes there studies on their phylogeography is urgent. With such information the genetic value of particular regions will be clearer, however their conservation and management involve complex and difficult political matters. Besides these more general issues, there are a number of more particular lessons and questions. For example, it has recently been noted in several butterflies that the lower genetic diversity produced by postglacial colonization of northern Europe is correlated with their recent decline, as evidenced in national records. Moreover, different deduced postglacial colonization patterns show the same correlation of low genetic diversity and population decline [ 91 ]. This suggests that the phylogeography of a species may be used as a predictor of demographic threat and loss. Clearly similar evidence from more species and groups is required to substantiate this. Another particular example is the genetic diversity created by the formation of a hybrid zone as two genomes meet with postglacial colonization, which is multiplied when several species zones coincide as a suture zone, e.g. [ 26 ]. It has been argued that such regions are important because of their genetic diversity [ 92 ]. They may well allow the generation of occasional hybrid species [ 93 , 94 ] and possibly reinforcement [ 95 ], but except perhaps for climatically very stable locations in the wet Tropics they are transient, and will disappear with each major climatic reversal. They may reform in roughly the same place each cycle, but fossil evidence suggests that this is not necessarily the case [ 29 ]. Furthermore, for most zones the diversity they contain is accumulated in their refugia over several cycles, and hence these regions have greater long term value. The demonstration that the extent of divergence among lineages within and between sister species generally increases from the High Arctic to the wet Tropics reflects their evolutionary age. It can be argued that the richer Tropical biotas are more valuable than the poorer temperate ones, both in terms of their present allelic, lineage and species diversity, and their long term survival. However, this overlooks the particular adaptations of Temperate species and the vast highly productive biotas they produce. The agriculture of the Temperate regions also supports much of the world's population. The consideration of regional diversity and adaptation raises a number of related questions. How well coadapted are recently assembled Temperate ecosystems? Are north Temperate and Arctic species particularly selected for colonization by repeated range change? Are genetically richer genomes more able to adapt to change? Do putative refugial regions contain genetic variation that may be useful in agriculture? And there are many more such considerations. Conclusion The frequent major climatic oscillations in the last 2 My caused repeated changes in the ranges of surviving taxa, with extensive extinction and recolonization in higher latitudes and altitudinal shifts and complex refugia nearer the tropics. As a result of these past dynamics, the genetic diversity within species is highly structured spatially, with a patchwork of genomes divided by often coincident hybrid zones. The extent of divergence among lineages within and between sister species generally increases from the High Arctic to the wet Tropics and reflects their evolutionary age. Holarctic animal species show shallow but clear phylogeographic structure from the last or recent glaciations. Clades of several species are parapatric near major geographic features like rivers and mountains, suggesting they had similar range changes and refugial areas. In Temperate regions like Europe and North America there is much more diversity in the south, where it has accumulated in refugia over many ice ages, and much less in the north, where it was lost during postglacial colonization. These northern places have been colonized by species from different southern refugia, and have had little time to become closely coadapted. Furthermore, this loss of diversity in the north is implicated in the present reduction of population abundance in some species. Mammals from the Dry Tropics of Africa often show major clades in the west, east and south indicating major refugial areas for recent divergence through climatic cycles in the Late Pleistocene. Mountain ranges in warm Temperate and Tropical regions would seem to be important for the survival of lineages through climatic changes, and hence for genome divergence and speciation. Such understanding of the distribution of biodiversity carries serious implications for the theory and practice of conservation.

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Steps on the Critical Path: Arresting HIV/AIDS in Developing Countries

The director of the United States Centers for Disease Control and Prevention gives a personal view of how the world should tackle the HIV pandemic

As an intern, I took care of the first patients with HIV/AIDS at San Francisco General Hospital, and so I grew up with AIDS in the early days of my medical career. We struggled through the confusion about what was making people so sick, and each new day brought a new discovery about the disease and its consequences. I went through that evolutionary process along with everybody else, and it shaped me in many profound ways. Before long, I recognized that this wasn't a disease of “those people over there.” This was a disease that could strike anyone, anytime. And as physicians, we had to adjust our thinking about our own vulnerability to occupational risk, and to emphasize prevention, because there wasn't going to be a cure for a long, long while. And not only physicians had to rethink things—AIDS has reshaped society's very notions of the most basic human behaviors. I was in Uganda in 1985, early in the AIDS epidemic there. We knew then where that epidemic was going to go, absent an effective vaccine or cure, but few of us could have imagined that it would evolve so quickly without an end in sight. While the people of Africa have achieved a huge amount in tackling HIV/AIDS, particularly in Uganda, the epidemic is far from being under control on that continent and is spreading through other parts of the world with alarming speed. The Crisis of Human Resources The theme of this year's International AIDS Conference in Bangkok was “Access for All.” Over the past few years, it has become increasingly apparent that a critical component of assuring access to care and treatment is human capital. Like fiscal capital, human resources are essential to ending the AIDS pandemic. I visited Africa with US Health and Human Services Secretary Tommy Thompson and many AIDS experts last December, and we saw evidence of this critical need in every country we visited. The miracles of modern science are meaningless without systems and people to deliver them to those in need. Figure 1 Estimated Percentage of Adults in Need of Antiretroviral Treatment Who Are Receiving It, as of March of 2004 (This graphic is based on an image by the World Health Organization, available at http://www.who.int/3by5/en/coverage_march2004.jpg ) The World Health Organization estimates that of the 40 million people worldwide infected with HIV, 6 million need immediate, life-sustaining antiretroviral therapy. Fewer than 400,000 people in developing countries have access to such treatment ( Figure 1 ) [ 1 , 2 ]. There are too few skilled health care workers to provide reliable delivery and administration of these life-saving therapies. According to a recent Institute of Medicine report, and a study sponsored by the US Agency for International Development, the number of health care workers in many African countries is actually shrinking as they are lured to developed countries by better pay and professional opportunities ( Box 1 ) [ 2 , 3 ]. Reversing this brain drain is essential over the long-term, as HIV treatment and care will be required for decades. In the short-term, the Institute of Medicine called for expanded efforts “to bring qualified volunteer initiative medical professionals into both urban and rural areas to support prevention, care, and training programs” [ 2 ]. I could not agree more that addressing the human resource needs will be essential as we move forward—and not just for HIV/AIDS programs, but for all aspects of public health and health care. Box 1. The Brain Drain: Facts and Figures [ 2 , 3 ] Only 360 of the 1,200 doctors trained in Zimbabwe during the 1990s continue to practice within the country. Two-thirds of University of Zimbabwe medical students intend to leave the country after graduating, and one of the country's major 1,000-bed teaching hospitals lacks a single qualified pharmacist. In Zambia, only 50 of the 600 doctors trained locally since independence have remained in the country. In Ghana, 320 nurses are recorded to have been lost in 1999, roughly equivalent to that country's annual output of nurses; losses for the year 2000 totaled 600. It has now been shown, beyond any doubt, that even in resource-poor countries with the most basic health infrastructure, people get the same benefit from treatment and prevention interventions as those in the rich world [ 4 ]. In fact, surveys in Cape Town, Kampala, Khayelitsha, and Senegal found rates of adherence to antiretroviral therapy of 90%–94%, compared with estimates of 70% in developed countries [ 5 , 6 , 7 ]. When You Have Seen the Faces We hear the numbers—the millions upon millions infected—and we grow numb. That is why we must go to the front lines—the households and communities—and start focusing on each individual living with HIV. I was at the dedication of an AIDS clinic in Kenya. It was raining, and we were waiting outside with our umbrellas. A 12-year-old girl in front of me turned around and leaned her head against my belly and said, “Could you take me to America? I need drugs.” If you take that girl's face and multiply it a thousand times—that is the memory I bring home from Africa: the faces of the children and their asking, “Why are so many of our parents dying? Why are we dying?” We visited a US Centers for Disease Control and Prevention (CDC) program in the very remote areas of Uganda where there are no roads and it is impossible for people to come into population centers to receive HIV testing and other services. Young staff from the CDC are working with Ugandans and community organizations in that area to deliver antiretroviral therapy. Some may think that the difficulties of delivering antiretroviral therapy into such a remote area are overwhelming—and some may question whether this is a sustainable intervention. But once you see firsthand what miracles are possible, your world view changes almost overnight. What we saw was the success of a wonderful home-based treatment and care program for people who don't have access through other means. And when I say “home-based care,” picture a hut without running water or electricity, where only motorcycles are available to deliver medications. The first step of the program is to provide clean water. Coliforms and other pathogens in the water supply for the household are removed through an inexpensive water vessel fitted with a filter and through a chlorination process. In addition, a cotrimoxazole tablet is given every day, which, in one patient's words, changed his life because he began to feel well almost immediately. Not only do the cotrimoxazole prophylaxis and the water treatment improve diarrheal illness, but malarial parasitemia also drops. So that is a very positive, unexpected consequence of just two very simple and inexpensive interventions. Many patients with HIV/AIDS in Africa also have tuberculosis and are put on tuberculosis therapy in addition to cotrimoxazole. As a result, they begin to feel better even before they begin antiretroviral therapy. Behavior change club at a technical school in Entebbe, Uganda (Photo: Arjen van de Merwe/World Population Foundation) We spent time with one of the patients in the home-based care program. As she began to participate in these programs, tests became available to measure her CD4 count. She explained to me what her CD4 count was, what it meant, and how it improved when she started the cotrimoxazole and tuberculosis therapy. She had begun taking three antiretroviral drugs and held up her pill box to explain her regimen in detail. Every week a Ugandan health aide delivered her supply of pills on a CDC motorcycle and monitored her adherence to the treatment. Not only was she extremely reliable in taking her medications, but she also knew more about them and their side effects than most of the patients I treated at San Francisco General. She was also an expert in HIV prevention. I asked her, “What do you do to protect your three young sons from this infection?” She replied, “Every day I take them by the hand, and I go out of the house and I say, ‘Do you see that mound of dirt? That is your father’s grave. Your father acquired this fatal infection through sex. Be careful.'” And then she talks to them about the “ABCs” (“A” for abstinence, “B” for being faithful, “C” for condoms). So when you see a story like that unfold in the middle of Africa, it's impossible not to be hopeful. And yet, it's also very sobering because we are reminded of our responsibility. The question is not what the international health community is accomplishing in these countries now, but what we could accomplish if we joined together to really fight this war on AIDS. Such a story also inspires hope because you can see the multiplier effect that comes from taking on one problem and can see the way that effort can expand to encompass and address a much greater set of problems. Beyond ABCs—Diagnosis and Responsibility When we think about successful prevention models in Uganda, “ABC” certainly stands out [ 8 ]. However, at this point in the epidemic curve, other letters must also be considered. Most HIV transmission is accounted for by infected people having risky sex with uninfected people. Both in the US and in Africa, studies show that most infected people engaging in risky sex are unaware of their infection status, and that when their infection is diagnosed, they usually take steps to protect the others with whom they are having contact [ 9 , 10 , 11 , 12 ]. So let's add the letter “D” for diagnosis. In fact, improving efforts to help people choose risk avoidance and to diagnose those who are already infected is the cornerstone of the CDC's new domestic HIV prevention strategy. Diagnosis is extremely important in many African communities, especially where the number of discordant couples—where one individual is infected and the other is not—is high. Sadly, many couples “being faithful” now do not realize that one partner is already infected and are not being reached with diagnostic testing programs. So “ABCD” is a concept that I would like to put out on the table as food for thought. Of course, there is another letter that we need to stress: the letter “R,” for responsibility: personal sexual responsibility is a critical component of HIV prevention. Many women and girls become infected after being raped by men or because their social circumstances rob them of the power to refuse sex. Men must be held accountable for greater sexual responsibility and for ending sexual violence and degradation of women and girls. HIV prevention programs need to emphasize responsibility, but not lose sight of the fact that responsibility can be practiced only with personal autonomy, which many women and girls simply do not have. Expanding the Team to Meet the Needs The innovative programs and ideas emerging in Africa can change the picture of the AIDS epidemic. The purchase of antiretroviral drugs for Africans is not the big challenge. Access to drugs will improve in Africa. The real challenges are delivering drugs in a safe and effective way, monitoring therapy, and sustaining the pipeline of drugs so that ongoing treatment can be guaranteed. In the example of the home-based program in Uganda, we have seen that these challenges can be overcome. Expanding access to prevention, care, and treatment services isn't going to be easy, but it is certainly possible. It will take unprecedented commitment by people in the public sector, the private sector, faith communities, and community organizations, and perhaps most importantly, individual volunteers who make up their minds to contribute in any way they can. Last fall, the US Peace Corps announced that it was activating programs in some countries that allow volunteers to help communities fight the AIDS epidemic, but this is just one of many steps that are being taken. The US president's Emergency Plan for AIDS Relief will provide $15 billion, including almost $10 billion in new funds, over five years for international AIDS assistance [ 13 ], and I am part of the team that is charged with making this plan happen. I look forward to learning from others in the global health community how we can best expand our impact and collectively find a way to support the delivery of prevention messages and life-saving medications to everyone in Africa—and especially to that little girl at the Kenyan clinic who touched my heart.

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514708

Association study of polymorphisms in the excitatory amino acid transporter 2 gene (SLC1A2) with schizophrenia

Background The glutamatergic dysfunction hypothesis of schizophrenia suggests that genes involved in glutametergic transmission are candidates for schizophrenic susceptibility genes. We have been performing systematic association studies of schizophrenia with the glutamate receptor and transporter genes. In this study we report an association study of the excitatory amino acid transporter 2 gene, SLC1A2 with schizophrenia. Methods We genotyped 100 Japanese schizophrenics and 100 controls recruited from the Kyushu area for 11 single nucleotide polymorphism (SNP) markers distributed in the SLC1A2 region using the direct sequencing and pyrosequencing methods, and examined allele, genotype and haplotype association with schizophrenia.The positive finding observed in the Kyushu samples was re-examined using 100 Japanese schizophrenics and 100 controls recruited from the Aichi area. Results We found significant differences in genotype and allele frequencies of SNP2 between cases and controls ( P = 0.013 and 0.008, respectively). After Bonferroni corrections, the two significant differences disappeared. We tested haplotype associations for all possible combinations of SNP pairs. SNP2 showed significant haplotype associations with the disease ( P = 9.4 × 10 -5 , P = 0.0052 with Bonferroni correction, at the lowest) in 8 combinations. Moreover, the significant haplotype association of SNP2-SNP7 was replicated in the cumulative analysis of our two sample sets. Conclusion We concluded that at least one susceptibility locus for schizophrenia is probably located within or nearby SLC1A2 in the Japanese population.

Background Schizophrenia is a severe mental disorder characterized by hallucinations, delusions, disorganized thoughts, and various cognitive impairments. The life-time prevalence is about 1%, and genetic factors were known to play a critical role in its pathogenesis [ 1 ]. Based on the fact that phencyclidine (PCP) induces schizophreniform psychosis, a glutamatergic dysfunction hypothesis has been proposed for the pathogenesis of schizophrenia [ 2 - 4 ]. This hypothesis has been supported by recent multiple reports of association of schizophrenia with glutamate receptor genes and with the genes related to glutamatergic transmission, such as G72 and NRG1 [ 5 - 10 ]. In addition, other synaptic elements related to glutamate, such as excitatory amino acid transporters (EAATs), also potentially affect glutamatergic neurotransmission. EAATs maintain extracellular glutamate concentrations within physiological levels by reuptaking the synaptically released glutamate. A deficient uptake has been implicated in the pathogenesis of ischemic brain damage [ 11 ] and may be involved in neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) [ 12 ]. Recently significant increases of mRNA expression of EAAT1 and EAAT2 have been reported in the thalamus of schizophrenics, suggesting the possibility that an excessive glutamate uptake is involved in schizophrenia [ 13 ]. On the other hand, a significant decrease of EAAT2 mRNA expression was observed in the parahippocampal gyrus of schizophrenics [ 14 ]. Therefore the EAAT genes are reasonable candidates for schizophrenia, as well as glutamate receptor genes. The EAATs family consists of five members (EAAT1-EAAT5). Their cellular localizations are different: EAAT1 and EAAT2 are astroglial, whereas EAAT3 EAAT4 and EAAT5 are neuronal [ 25 ]. Since EAAT2 accounts for approximately 90% of glutamate reuptake in the rodent forebrain [ 16 , 17 ], we focused on the EAAT2 gene ( SLC1A2 ) in association studies of schizophrenia. SLC1A2 has been mapped to 11p13-p12 [ 18 ] and consists of 11 exons spanning over 165 kb. In this study we tested associations of schizophrenia with 11 SNPs distributed in SLC1A2 with an average interval of 15.9 kb. To enhance the detection power of the study, we also examined the haplotype associations of the SNPs with the disease. Methods Human subjects Blood samples were obtained from unrelated Japanese individuals who had provided written informed consent. We used two Japanese sample sets in this study. In the first one, Kyushu samples, 100 schizophrenia patients (mean age 49.5; 44.0% female) were recruited from hospital in the Fukuoka and Oita areas and 100 healthy unrelated controls (mean age 51.2; 44.0% female) were recruited from the Fukuoka area. In the initial SNP selection process, we used another 16 Japanese samples which are recruited in the Fukuoka area and informed in the same way. In the second one, Aichi samples, 100 schizophrenia patients (mean age 34.4; 44% female) and 100 healthy unrelated controls (mean age 39.9; 45% female) were collected in the Aichi area about 600 km east of Fukuoka. All patients fulfilled the DSM-IV criteria for schizophrenia [ 19 ]. All of the case and control samples are ethnically Japanese. DNA samples were purified from whole peripheral blood by the method previously described [ 20 ]. This study was approved by the Ethics Committee of Kyushu University, Faculty of Medicine and the Fujita Health University Ethics Committee. SNP selection in the SLC1A2 region We retrieved the primary SNP information from the dbSNP database . Assuming the same size of the half length of linkage disequilibrium (LD) (60 kb) as reported in Caucasians [ 21 ], we initially intended to select common SNPs every 50 kb in SLC1A2 . We tested 22 candidate SNPs including all of the exonic SNPs, in the 16 healthy Japanese samples by the direct sequencing method. Out of the 22 SNPs we selected the following 7 common SNPs with minor allele frequencies over 10% for further analyses: SNP1, rs1923295; SNP3, rs4534557; SNP6, rs1885343; SNP8, rs752949; SNP9, rs1042113; SNP10, rs3838796; SNP11, rs1570216. We also identified a novel SNP, SNP7, in intron 1 (conting location: 34105026). After the LD analyses described below, we noticed LD gaps ( D ' < 0.3) of the initial SNP set and examined additional 20 candidate SNPs. Out of the 20 SNPs, we selected the following 3 SNPs to fill the LD gaps: SNP2, rs4755404; SNP4, rs4756224; SNP5, rs1923298. The locations of the total 11 SNPs are shown in Figure 1 . Figure 1 Genomic organization of SLC1A2 and locations of the SNPs. Exons are shown as vertical bars with exon numbers. Eleven SNPs are indicated by circles. Distances between the SNPs are indicated above with kb. Genotyping Eleven SNPs were amplified as 11 individual fragments by PCR using the primers shown in Table 1 - additional file 1 . The reaction mixture for PCR was prepared in a total volume 10 μl with 5 ng of genomic DNA, 10 pmol of each primer (4 pmol of SNP3), 2.5 mM of MgCl 2 , 0.2 mM of each dNTP and 0.25 U of Taq DNA polymerase. An initial denaturing step of 1 min at 94°C was followed by 30, 35 or 40 cycles of 94°C for 30 sec, appropriate annealing temperature for 30 sec and 72°C for 30 sec. A final extension step was carried out at 72°C for 7 min. The nucleotide sequences of each primer, PCR conditions and genotyping methods for each SNP are shown in Table 1 - additional file 1 . We genotyped SNP3 by pyrosequencing analysis on a PSQ™96MA Pyrosequencer according to the manufacturer's specifications with a biotinylated reverse primer (5'-CGCCTACTCCTGGTGACTTC-3'), and the sequencing primer (5'-CGCCCCCATGTGT-3'). The other 10 SNPs were genotyped by direct sequencing, as previously described [ 7 ]. The raw data of direct sequencing were compiled on PolyPhred [ 22 ]. Statistical analyses To control genotyping errors, Hardy-Weinberg equilibrium (HWE) was checked in the control samples by the χ 2 -test (d.f. = 1). We evaluated the statistical differences in genotype and allele frequencies between cases and controls by the χ 2 -test (d.f. = 2) and the Fisher's exact probability test (d.f. = 1), respectively. The magnitude of LD was evaluated in D ' and r 2 using the haplotype frequencies estimated by the EH program, version 1.14 [ 23 ]. Statistical analysis of the haplotype association was carried out as previously described [ 24 ]. The significance level for all statistical tests was 0.05. Results Genotyping and SNP association analysis We selected 11 SNPs at average interval of 15.9 kb to cover the entire SLC1A2 region with LD as described in Materials and Methods. Table 2 - additional file 2 . shows the results of genotype and allele frequencies of SNPs in case and control samples. No significant deviation from HWE in control samples was observed (data not shown). SNP2 showed significant differences in genotype ( P = 0.013) and allele ( P = 0.008) frequencies between cases and controls. After Bonferroni corrections, these two P values became non-significance levels ( P corr = 0.143, P corr = 0.088, respectively). Pairwise linkage disequilibrium and haplotype association analyses We compared the magnitude of LD for all possible pairs of the 11 SNPs in controls by calculating D ' and r 2 (Table 3 - additional file 3 . , upper diagonal), because LD around common alleles can be measured with a modest sample size of 40–50 individuals to a precision equal to 10–20% of the asymptotic limit [ 19 ]. We observed relatively strong LD ( D ' > 0.8) in the seven combinations: SNP4-SNP5 ( D ' = 0.800), SNP7-SNP8 ( D ' = 0.877), SNP8-SNP9 ( D ' = 0.925), SNP4-SNP11 ( D ' = 0.838), SNP5-SNP11( D ' = 0.999), SNP7-SNP11 ( D ' = 0.816), SNP9-SNP11 ( D ' = 0.819). Modest LD ( D ' > 0.4) was observed in the combinations of adjacent SNPs except for SNP5-SNP6 ( D ' = 0.286) in the control samples. However, modest LD was detected in cases in the SNP5-SNP6 combination ( D ' = 0.497). We constructed pairwise haplotypes for all of the 55 possible SNP pairs (Table 3 - additional file 3 . , lower diagonal). We observed significant associations with schizophrenia in eight combinations: SNP2-SNP3 ( P = 0.0021), SNP2-SNP4 ( P = 0.0274), SNP2-SNP5 ( P = 0.0054), SNP2-SNP6 ( P = 0.0178), SNP2-SNP7 ( P = 9.4 × 10 -5 ), SNP2-SNP9 ( P = 0.0354), SNP2-SNP10 ( P = 0.0089) and SNP2-SNP11 ( P = 0.0216). The combination of SNP2-SNP7 was the only one remained significant after Bonferroni correction ( P corr = 0.0052). Cumulative analysis using the second sample set In this study, we detected significant associations of one haplotype in the SLC1A2 region with schizophrenia in the Kyushu samples. To confirm the positive finding, we investigated the second Japanese sample set recruited from the Aichi area. Although significant association of the disease was observed with neither genotype, allele frequencies of SNP2 ( P = 0.195, P = 0.178, respectively), nor haplotypes of SNP2-SNP7 ( P = 0.084) in the second sample set, the significant haplotype association of SNP2-SNP7 was replicated in the cumulative analysis including the two sample sets ( P = 5.0 × 10 -4 ) (Table 4 - additional file 4 . ). Discussion SLC1A2 is located on the chromosomal region of 11p13-p12, to which no evidence has been reported for linkage of schizophrenia, [ 25 , 26 ]. However, there is still a possibility that SLC1A2 is a candidate for schizophrenia susceptibility genes, because linkage studies could only detect genes with the large genotype relative risk [ 27 ]. We carried out the genotyping of 100 cases and 100 controls for 11 SNPs, which were selected to cover the entire SLC1A2 region with LD. Since minor allele frequencies of each SNP we tested ranges from 0.220 to 0.485, the expected detection power of our case-control study is from 0.89 to 0.94 for the susceptibility gene assuming 2 for genotype relative risk [ 28 ]. Modest LD ( D ' = 0.925 ~ 0.409) was observed in the combinations of neighboring SNPs except for SNP5-SNP6 ( D ' = 0.286) in the control samples, suggesting that there may be a recombination hot spot present in the small region (7.8 kb) between the two SNPs (Table 3 - additional file 3 . ). We plotted the magnitude of LD with the physical distance for each pair of the SNPs, and estimated the average half-length of LD to be 31.8 kb by assuming a linear regression (Fig. 2 ). This is approximately half of the previously estimated size 60 kb in a United States population of north-European descent [ 21 ]. Figure 2 A plot of pairwise linkage disequilibrium (LD) vs. physical distance between the SNPs in the SLC1A2 region. D ' were plotted with filled diamonds, and r 2 with open diamonds. From the regression line, the half-length of LD was estimated to be 31.8 kb in the SLC1A2 region. Significant associations of schizophrenia with genotype ( P = 0.013) and allele ( P = 0.008) frequencies of SNP2 (rs4755404) were detected (Table 2 - additional file 2 . ). However, none of these "single-marker" associations survived after Bonferroni corrections. An A-G transition in codon 206, causing a substitution of serine for asparagine, was identified in the exon 5 of SLC1A2 in a heterozygous sporadic ALS patient [ 29 ]. Since located in a putative glycosylation site, the nonsynonymous SNP is potentially involved in the pathophysiology of schizophrenia through affecting the glycosylation status and the transport activity of SLC1A2 [ 30 ]. No occurrence of the G allele of the SNP in 124 Italian schizophrenic and 50 control subjects has been reported [ 30 ]. We found also only A allele of the SNP in the 100 controls and 100 cases of the Kyushu samples (data not shown). In pairwise haplotype association analyses, SNP2 consistently showed significant haplotype associations. The P value of the combination SNP2-SNP7 was still significant even after Bonferroni correction ( P = 9.4 × 10 -5 , P corr = 0.0052). In our second sample set, the Aichi sample, no significant association of SNP2 was observed in any of the analyses of genotypes, alleles and haplotypes. Cumulative analyses of the two sample sets, however, provide the replication of the significant haplotype association of SNP2-SNP7 with schizophrenia ( P = 5.0 × 10 -4 ). The frequency of the G-C haplotype in schizophrenics (26.6%) was notably higher than in controls (5.6%), suggesting that the G-C haplotype may be a risk haplotype for schizophrenia. We observed that the G-C haplotype frequency of schizophrenics (20.0%) was only slightly higher than controls (14.2%) in the Aichi sample, suggesting a less contribution of this locus on schizophrenia pathogenesis in the Aichi sample, although no apparent difference in clinical subtypes between both sample sets studied in this paper. The positive association reported here needs to be validated in larger sample sets, and it would also be worthwhile to search for functional SNPs in the region spanning SNP2-SNP7. Conclusion We concluded that at least one susceptibility locus for schizophrenia is probably located within or nearby SLC1A2 in the Japanese population. Competing interests None declared. List of abbreviations used SNP; single nucleotide polymorphism DSM-IV; dianostic and statistical manual of mental disorders, 4 th edn PCR; polymerase chain reaction HWE; Hardy-Weinberg equilibrium LD; linkage disequilibrium EAAT; excitatory amino acid transporter Authors' contributions XD carried out genotyping, statistical analyses and drafted the manuscript: HS participated in design of this study and statistical analyses: HN, NT, NI and NO participated in collecting specimens and clinical data: YF conceived of the study and participated in its design and coordination. Pre-publication history The pre-publication history for this paper can be accessed here: Supplementary Material Additional file 1 PCR primers for genotyping of SNPs in SLC1A2. Click here for file Additional file 2 Genotype and allele frequencies of SNPs in SLC1A2 in Kyushu samples. Click here for file Additional file 3 Pairwise linkage disequilibrium and haplotype association in SLC1A2. Click here for file Additional file 4 Association analysis of the SNP2-SNP7 haplotype using two sample sets. Click here for file

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545209

Rethinking Immunity against Pneumococcal Disease

Streptococcus pneumoniae is a common bacterium that is present in the nasopharynx of many children and some adults, where it causes no harm to its carrier but can be transmitted to others. If it moves beyond the nasopharynx, however, it can cause ear infections or invasive disease, such as pneumonia or meningitis. Invasive disease from this organism occurs especially in children, the elderly, and individuals with weakened immune systems. The protective effect of antibodies against bacterial pneumonia has been appreciated since the 1930s, when it was shown that serum therapy—the transfer of serum from an immunized animal to a patient with acute disease caused by the same bacterial strain—could reduce mortality from pneumococcal pneumonia by half. Subsequent development of vaccines based on the bacterium's polysaccharide capsule, which could protect against infection, confirmed that an endogenous antibody response can provide protection against invasive disease. Parallel age-incidence curves for pneumococcal serotypes suggest a common mechanism of protection One challenge for vaccine development has been the existence of many different serotypes (the same species of bacteria but with different composition of the polysaccharide capsule). As protection usually doesn't extend to different serotypes, vaccination with capsule components from different serotypes is necessary to ensure broad protection. Such vaccines have been shown to be efficient and safe. They are now recommended in many countries for infants and toddlers, and for people over 65—the two age groups in which invasive disease is most common—and for others who are at increased risk of pneumococcal disease (e.g., patients with heart, kidney, liver, or lung disease, or who have had a splenectomy). Even without vaccination, however, most exposed individuals will never get invasive disease. Instead, they develop natural immunity against the different serotypes, though this immunity gradually declines with old age. Marc Lipsitch and colleagues wanted to understand the immunological basis of this natural immunity, and specifically whether it was due to anticapsular antibodies. If protection from invasive disease is due to acquiring anticapsular antibodies against each of the pneumococcal serotypes, they argued, this would lead to two predictions about the age distribution of disease caused by the different serotypes in the non-vaccinated population. First, for serotypes that are more common and therefore encountered earlier in life, children should develop immunity more quickly, causing disease from these types to drop off earlier in life than disease from the less common types. Second, protection against invasive disease from a particular serotype should coincide with the acquisition of antibodies against that serotype, on both the individual and population level. Neither prediction was borne out by the actual data the researchers analyzed, suggesting that there is more to natural immunity against pneumococcal disease than just anticapsular antibodies. The study doesn't demonstrate what the additional components are, but additional research might not just teach us about our immune system but also provide clues for further vaccine development. As the authors say, “A better understanding of the mechanisms that underlie natural immunity to pneumococcus could pave the way for the development of more effective, species-specific pneumococcal vaccines.”

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555754

Subjective impact of osteoarthritis flare-ups on patients' quality of life

Background Clinical trials on osteoarthritis (OA) flare-ups treatment usually focus only on objective measures of health status, albeit recent literature suggestions on the importance of patients' subjectivity. Aim of the study was to evaluate the effects of OA and of its different types of medical treatment(s) on Health Related Quality of Life (HRQoL) in terms of both subjective satisfaction and functional status. Methods An observational study on prospective data collected from the Evaluation of Quality of life in OA (EQuO) clinical trial (April 1999-November 2000) was conducted; outpatients from 70 participating centers (Orthopedy or Rheumatology Departments in Italy) with a diagnosis of OA of the hip or knee were consecutively enrolled. Patients were observed at OA flare-ups (baseline) and at follow up 4 weeks after treatment. Patients' objective and subjective HRQoL were assessed by means of the SF-36 and the Satisfaction Profile (SAT-P, which focuses on subjective satisfaction); Present Pain at baseline and Pain Relief at follow up were also evaluated. Results Among the 1323 patients, 1138 (86%) were prescribed one drug/treatment of osteoarthritis, 169 (13%) 2 drugs/treatments, and 16 (1%) 3 drugs/treatments; most of treatments involved the prescription of NSAIDs; non-coxib, COX2 selective NSAIDs were prescribed in about 50% of patients. Follow-up visits were performed after 29.0 days on average (± 7.69 SD). For all SF-36 domains, all SAT-P items and factors, the differences between baseline and follow up scores resulted statistically significant (p < 0.001), enlighting an improvement both in health status and in subjective HRQoL. Conclusion Besides the classic health status measures, the assessment of patients' subjective satisfaction provides important clues on treatments efficacy of OA within the patient-centered medicine model. In clinical practice this could lead to a better doctor-patient communication and to higher levels of treatment adherence.

Background The impact of osteoarthritis (OA) on patient's functional levels is well known [ 1 - 3 ]. Pain and physical limitations constitute difficulties patients have to deal with [ 4 , 5 ] and require long term pharmacological treatment and physical therapies. Usually OA affects elderly people, and is one of the main causes of physical disability. In OA patients, Health Related Quality of Life (HRQoL) and activities of daily living are negatively affected. Significant work disability, reduced ability to deal with household duties and sleep disorders are reported in patients with symptoms of OA flare-ups, together with dysfunctions in the areas of ambulation, body-care and movement (in terms of perceived health status), and emotional behaviour (in terms of perceived psychological functioning) [ 1 , 2 , 4 - 8 ]. As a chronic condition, the impact of OA has been studied mainly focusing on its consequences on health status. Similarly, treatment efficacy is assessed within the context of health status and/or symptomatology in many clinical trials [ 6 , 7 , 9 - 12 ]. However, health status and symptomatology can be considered only two components of HRQoL [ 13 ] and little is known about the impact of OA and its treatments on patient's subjective perspective, in spite of increasing attention on this topic [ 14 - 19 ]. In literature, HRQoL refers to patients' appraisals of their current levels of functioning and satisfaction, compared to what they perceive to be ideal [ 20 ]. HRQoL assessment allows a subject to express his or her ability to perform daily activities across many domains which include physical, social and cognitive functioning, role activities and emotional wellbeing. Besides, "...how a subject feels about the performace of each of those activities may be assessed separately by measuring satisfaction for each domain." [ 21 ]. The subjective implications of HRQoL, within the context of patient centred medicine, have been already stressed by suggestions from recent reliable scientific literature [ 15 , 17 - 24 ]. The aim of the present study is to evaluate the effects of OA and of its different types of medical treatment(s) on HRQoL in terms of both subjective satisfaction and functional status. Methods Patient population and procedure Data from collaborating, educated outpatients aged 50–80 years with a diagnosis of OA of the hip or knee according to the criteria of the American College of Rheumatology [ 25 ] were collected in this observational, prospective study. Outpatients (n = 1340) were consecutively enrolled in 70 Italian participating centers (Orthopedy or Rheumatology Departments, listed in Appendix A [see additional file]) from April 1999 to November 2000. 147 patients withdrawn OA treatment before follow-up visit. All patients signed an informed consent in which the purposes of the study (HRQoL assessment and treatment efficacy, as primary and secondary outcomes respectively) were clearly stated. Approval for this research was obtained by the ethics committee, patients did not receive any remuneration for their participation. Patients with concomitant osteoarticular disorders, impairment of motor function not due to OA of the hip or knee, concomitant systemic disease(s) affecting HRQoL or requiring NSAIDs/steroids use on a regular basis were not included into the study, in order to avoid biases in the results due to treatments other than OA treatments. Patients were observed at OA flare-ups, when attending for a visit (baseline) and at follow up 4 weeks after treatment. According to the observational design of this trial, no "study treatments" were assigned to patients, but any drug(s)/medical treatment(s) considered by the physician as adequate to the patient's clinical condition was freely prescribed; therefore patients were not previously randomized to treatment. During both visits, patients were administered the following: the Visual Analogue Scale (VAS) [ 26 ] on Present Pain (baseline) or on Pain Relief (follow up); the Medical Outcomes Study Short-Form 36 Health Status Survey (SF-36) [ 27 ] in its validated Italian version [ 28 , 29 ] and the Satisfaction Profile (SAT-P) [ 30 ]. Moreover, at follow up, the global assessments of efficacy and tolerability of the medical treatment(s) prescribed for OA flare ups (expressed by the patient and by the physician according to a 4 point semi-quantitative rating scale: excellent – good – moderate – poor) were collected. Side effects to this/these treatment(s), if any, were registered as well. The assessment procedure was standardized for all the participating centres. During the visit patients were invited to compile alone all the questionnaires and rating scales, only if required patients were assisted by a trained health professional. Self-reporting bias in HRQoL improvements was kept under control by the assessment procedure and by the adoption of valid and reliable questionnaires. Measures Visual Analogue Scale The VAS is perhaps the most widely used instrument for the measurement of pain intensity. The classic version of the VAS was administered: 10 centimeter line, horizontal. "It is a simple, robust, sensitive, and reproducible instrument that enables a patient to express the severity of his pain in such a way that it can be given a numerical value." [ 26 ] Its psychometric properties and its utility in clinical trials have been confirmed [ 2 , 8 , 31 , 32 ]. VAS on Present Pain ranged from "no pain" to "the worst pain possible"; VAS on Pain Relief ranged from "no pain relief" to "the maximum pain relief". Scores ranged from 0 to 100. SF-36 The SF-36 is a well known self-administered and generic health status measure which encompasses 8 domains related to daily life activities: physical functioning, role limitations due to physical problems, role limitations due to emotional problems, vitality, bodily pain, social functioning, mental health and general health perception [ 33 - 35 ]. Each domain scores from 0 (lowest level of functioning) to 100 (highest level of functioning). The instrument has been extensively validated within the Medical Outcome Study [ 33 ] and in other settings [ 34 ]. Satisfaction Profile The SAT-P is a self-administered, generic questionnaire which provides a satisfaction profile in daily life and can be considered as an indicator of subjective QoL. Satisfaction can be defined as the cognitive product of the comparison between ideal life and reality, and can therefore be quantitatively measured. The subject is asked to evaluate his/her satisfaction about 32 life aspects with reference to the last month (on 32 10 cm horizontal VAS) independently of his/her objective health status (for example: "How satisfied have you been in the last month with your Resistance to physical fatigue?"; "How satisfied...with your Mood?"; "How satisfied...with your Emotional stability?"). It provides 32 individual scores and 5 factor scores, all ranging from 0 (lowest level of satisfaction) to 100 (highest level of satisfaction). Together with its ability to detect patient's subjective satisfaction, the SAT-P addresses some aspects of daily life which are not included in SF-36 items (i.e. sleep, sexual life, quality of couple relationship, eating, self-confidence, resistance to stress, etc.). Its psychometric properties and clinical utility have been confirmed [ 30 , 36 , 37 ]. Statistical analyses Sociodemographic data and clinical values were analysed by means of descriptive statistics. Since the incidence of withdrawals resulted low, analyses were performed on complete cases and no solutions for handling missing data was adopted. Baseline and follow-up of SF-36 and SAT-P item and factor scores were compared by means of Analusis of Covariance (ANCOVA). Moreover, ANCOVAs were adopted in order to evaluate the impact of clinical variables on SF-36 and SAT-P factor delta scores (calculated subtracting the follow-up scores from baseline scores). The variables included into the models were: age, gender, body weight, OA localization (hip, knee, or both), VAS Present Pain, presence of concomitant disease(s), type of treatment (COX2 selective NSAIDs vs. other treatments). Results were summarized using mean ± SE for continuous variables and frequency (absolute and percent) for categorical variables. All p values are two-tailed and p < .05 was considered statistically significant. All computations were carried-out by resorting to SAS 8.0 procedures. Results Patients demographic and clinical characteristics (OA localization (hip/knee/both), VAS Present Pain, type of medical treatment(s) of OA flare-ups, concomitant diseases and treatments are shown in Table 1 . Patients' baseline VAS Present Pain resulted consistent with a clinical condition of moderate to severe rheumatic disease. Table 1 Patients' characteristics Gender (F/M) 795/528 Age (years, mean ± SD) 64.4 ± 10.3 Marital status: Single, n (%) 72 (5.4) Married, n (%) 922 (69.7) Widowed, n (%) 220 (16.6) Separated/divorced, n (%) 13 (1.0) Missing, n(%) 96 (7.3) Educational level: Primary school, n (%) 548 (41.4) Junior high school, n (%) 325 (24.6) Senior high school, n (%) 280 (21.2) Degree/Master/PhD, n (%) 103 (7.7) Missing, n(%) 67 (5.1) Employment status: Employed, n (%) 434 (32.8) Retired, n (%) 550 (41.6) Housewife, n (%) 288 (21.8) Missing, n (%) 51 (3.8) Body weight (kg, mean ± SD) 73.4 ± 11.0 OA localization: Knee, n (%) 658 (49.7) Hip, n (%) 463 (35.1) Knee + hip, n (%) 202 (15.2) VAS Present Pain (mm, mean ± SD) 67.7 ± 17.0 Concomitant diseases, n (%) 632 (47.8) Concomitant treatments, n (%) 444 (33.6) The most frequent concomitant diseases were: hypertension (19.1%), metabolic and nutritional disorders (9.2%), muscoloskeletal, connective tissue and bone disorders (8.2%) and gastrointestinal system disorders (4.3%). The most frequently prescribed concomitant treatments were: cardiologic drugs (9.7%) and antihypertensive (9.4%), antidiabetic drugs (8.4%), antithrombotic agents (4.5%), antiacids (6.7%), sedatives (4.8%). 1138 patients (86%) were prescribed one drug/treatment of OA, 169 patients (13%) 2 drugs/treatments, and 16 patients (1%) received 3 drugs/treatments. Most of treatments involved the prescription of NSAIDs; non-coxib, COX2 selective NSAIDs (nimesulide betadex and nimesulide, the only two COX2 selective NSAIDs available in Italy at the time of this study) were prescribed in about 50% of patients (Table 2 ). Table 2 Treatments prescribed for osteoarthritis flare-ups n % patients COX2 NON-SELECTIVE NSAIDs Arylacetic acid derivatives (diclofenac, indomethacin, sulindac, etc.) 221 16.7 Arylpropionic acid derivatives (ibuprofen, naproxen, ketoprofen, etc.) 165 12.5 Oxycams (piroxicam, tenoxicam, etc.) 181 13.7 Others (nabumetone, glucosamine, diacerein, etc.) 107 8.1 COX2 SELECTIVE NSAIDs Nimesulide betadex (or nimesulide) 689 52.1 OTHER DRUGS/TREATMENTS Various, systemic (ASA, paracetamol, corticosteroids, centrally acting myorelaxants) 46 3.5 Various, topical (transcutaneous or intraarticular) 44 3.3 Physical treatment (mobilization, iontophoresis, etc.) 60 4.5 Follow-up visits were performed after 29.0 days on average (± 7.69 SD). Only a small number of patients (17; 1.2%) did not attend follow-up visit. HRQoL assessment: SF-36 For all SF-36 domains, the difference between baseline and follow up scores resulted statistically significant (p < 0.001) (Table 3 ). Table 3 SF 36 scores (Mean ± SE). Baseline vs Follow-up scores. At the ANCOVAs: p < 0.001 for all domains SF-36 domains Baseline Follow up p Physical Functioning 47.9 ± 0.7 59.3 ± 0.7 <.001 Role Physical 27.8 ± 1.0 48.0 ± 1.1 <.001 Bodily Pain 31.7 ± 0.4 50.5 ± 0.5 <.001 General Health 45.8 ± 0.5 50.0 ± 0.5 <.001 Vitality 46.5 ± 0.5 53.2 ± 0.5 <.001 Social Functioning 44.1 ± 0.6 65.4 ± 0.6 <.001 Role Emotional 46.9 ± 1.2 65.7 ± 1.1 <.001 Mental Health 59.2 ± 0.5 65.4 ± 0.5 <.001 Baseline Present Pain was associated with almost all the SF-36 domains (Table 4 ). The presence of concomitant disease(s) resulted in a statistically significant association with 4 domains: Role Physical, Bodily Pain, General Health, Social Functioning. The type of OA treatment was associated with Physical Functioning and Bodily Pain. OA localization and age was associated with only one domain: Physical Functioning and Role Physical respectively. Gender and body weight did not correlate with any SF-36 domain. Table 4 Detected statistical significances on SF-36 delta scores. The p values resulted from the ANCOVAs are indicated. SF-36 domains Covariates Age Gender Body weight OA localization Present Pain Concomitant diseases Treatment Physical Functioning 0.021 0.0001 0.020 Role Physical 0.022 0.007 Bodily Pain 0.0001 0.0001 0.006 General Health 0.0001 0.003 Vitality 0.0001 Social Functioning 0.0001 0.003 Role Emotional 0.007 Mental Health 0.0001 HRQoL assessment: SAT-P factors All the differences between baseline and follow up SAT-P factor scores were statistically significant (p < 0.001) (Table 5 ). Table 5 SAT-P factor scores (M ± SE). Baseline vs Follow-up scores. At the ANCOVAs: p < 0.001 for all Factors. SAT-P Factors Baseline Follow up p Psychological functioning 59.3 ± 0.6 65.5 ± 0.5 p <.001 Physical functioning 41.3 ± 0.5 51.9 ± 0.5 p <.001 Work 53.3 ± 0.7 57.8 ± 0.7 p <.001 Sleep/Eating/Leisure 55.4 ± 0.5 60.9 ± 0.5 p <.001 Social functioning 66.0 ± 0.6 70.8 ± 0.5 p <.001 Baseline pain was significantly associated with all SAT-P factors (Table 6 ). The presence of concomitant disease(s) was in a statistically significant association with 3 out of 5 factors: Psychological functioning, Sleep-Eating-Leisure, Social functioning. OA treatment was associated with the factor Sleep-Eating-Leisure. Table 6 Detected statistical significances on SAT-P factors. The p values resulted from the ANCOVAs are indicated SAT-P Factors Covariates Age Gender Body weight OA localization Present Pain Concomitant diseases Treatment Psychological functioning 0.0001 0.022 Physical functioning 0.0001 Work 0.007 Sleep/Eating/Leisure 0.0001 0.007 0.026 Social functioning 0.0001 0.018 HRQoL assessment: SAT-P items Figure 1 shows the graphic representation of baseline and follow up SAT-P item scores. All the differences were statistically significant (p < 0.001). Figure 1 SAT-P items: mean scores at baseline and at follow-up. For all the differences (ANCOVAs) p < 0.001. Clinical outcome of OA treatment: Efficacy and Tolerability At follow-up, mean VAS Pain Relief was 61.1 mm (± 24.3 SD). In 65% of cases treatment efficacy was evaluated as good or excellent by patients themselves, in 67% of cases it was evaluated as good or excellent by physicians. In 81% of cases treatment tolerability was evaluated as good or excellent by patients themselves, in 84% of cases it was evaluated as good or excellent by physicians. It was evaluated as poor in 7% and 6% of cases respectively (Table 7 ). Table 7 OA treatments' evaluations (efficacy and tolerability) Poor Moderate Good Excellent Missing data n (%) n (%) n (%) n (%) n (%) Efficacy – patients 163 (12.3) 288 (21.8) 634 (47.9) 227 (17.2) 11 (0.8) Efficacy – physicians 129 (9.8) 292 (22.1) 634 (47.9) 257 (19.4) 11 (0.8) Tolerability – patients 93 (7.1) 147 (11.1) 712 (53.8) 359 (27.1) 12 (0.9) Tolerability – physicians 79 (6.0) 122 (9.2) 703 (53.1) 407 (30.8) 12 (0.9) 11.1% of patients reported side effects to medical treatment of OA; most of these reactions involved the gastrointestinal system. Poor tolerability led to treatment withdrawal in 6.2% of patients. Discussion Our study represents, to our knowledge, the largest observational prospective clinical trial carried out in OA patients' subjective HRQoL. The sample size and the very small number of drop-outs could be considered the strenghts of the study. A limit of the study could be considered the adoption of the SAT-P which is a new questionnaire, validated on the Italian population [ 30 ], but not previously used in clinical trials or in OA patients. Nevertheless, its psychometric properties have been previously confirmed, and moreover it is the only Italian questionnaire specifically aimed at assessing subjective satisfaction in daily life, independently of the presence of a disease. Its user friendly structure and its easily comprehensible graphical representation could be considered substantial methodological facilities both in research and in clinical practice. Finally, the coherence between the data provided by the two HRQoL instruments could confirm that health status and subjective satisfaction partially overlap, and allows us to study the same phenomenon from two different points of view: the objective and the subjective. This could therefore be considered the added value of the study. Considering the whole sample, SF-36 results confirm what previous studies have already enlightened in clinical trials: the SF-36 is, according to Kosinski et al. [ 35 ], a suitable instrument for assessing health status in OA, and medical treatment improves functionality levels in daily life aspects. The same conclusions could be drawn for the SAT-P: on the whole sample a general improvement of satisfaction levels can be observed in all the 32 items considered. In other words, pharmacological treatment has a significant positive impact on patients' both objective functioning and subjective well-being [ 16 ]. Thanks to the sinergic utility of the two instruments it has been possible to enlight results otherwise left unperceived and whose positive value on patients' life is unquestionable. Further investigations are needed in order to better clarify the relationships between perceived pain and pain relief and patients' HRQoL. Mastery, self-efficacy and coping abilities could be significant mediators between these two constructs [ 38 , 39 ]. Conclusion From both an objective and a subjective point of view, OA flare-ups' treatment has proved to have positive effects on HRQoL. The sinergic use of a health status measure (SF-36) and of a tool addressing subjective satisfaction (SAT-P) allows to wider the focus on patients' life. This methodological approach could help clinicians and researchers in transferring into practice the ICF model issues [ 40 ], with special attention on Activity and Participation and on Environmental Factors. List of abbreviations ANCOVA Analysis of Covariance HRQoL Health Related Quality of Life NSAID Non Steroid Anti Inflammatory Drugs OA Osteoarthritis SAT -P Satisfaction Profile SF-36 Medical Outcome Study Short-Form 36 Health Status Survey VAS Visual Analogue Scale Competing interests The author AS is employee of the company that partially funded the study. Authors' contributions GM: responsible for the design of the study, contributed to the statistical evaluation, contributed to the writing of the paper. AG: responsible for the statistical evaluation, contributed to the writing of the paper. AS: contributed to the design of the study and data collection, contributed to the statistical evaluation, contributed to revise the manuscript. Supplementary Material Additional File 1 Appendix A – Participating Centers Click here for file

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544895

Molecular characterization and functional expression of flavonol 6-hydroxylase

Background Flavonoids, one of the major groups of secondary metabolites, play important roles in the physiology, ecology and defence of plants. Their wide range of activities is the result of their structural diversity that encompasses a variety of functional group substitutions including hydroxylations. The aromatic hydroxylation at position 6 of flavonols is of particular interest, since it is catalyzed by a 2-oxoglutarate-dependent dioxygenase (ODD), rather than a cytochrome P450-dependent monooxygenase. ODDs catalyze a variety of enzymatic reactions implicated in secondary metabolite biosynthesis. Results A cDNA fragment encoding an ODD involved in the 6-hydroxylation of partially methylated flavonols, flavonol 6-hydroxylase (F6H), was isolated and characterized from Chrysosplenium americanum using internal peptide sequence information obtained from the native plant protein. This novel clone was functionally expressed in both prokaryotic and eukaryotic expression systems and exhibited ODD activity. The cofactor and cosubstrate requirements of the recombinant proteins are typical for ODDs, and the recombinant enzymes utilize 3,7,4'-trimethylquercetin as the preferred substrate. The genomic region encoding this enzyme possesses two introns at conserved locations for this class of enzymes and is present as a single copy in the C. americanum genome. Conclusions Recombinant F6H has been functionally expressed and characterized at the molecular level. The results demonstrate that its cofactor dependence, physicochemical characteristics and substrate preference compare well with the native enzyme. The N-terminal region of this protein is believed to play a significant role in catalysis and may explain the difference in the position specificity of the 6-hydroxylation reaction.

Background Flavonoid compounds constitute one of the major groups of secondary metabolites and play important roles in plant development, reproduction and defence. This diverse spectrum of activities results from their structural diversity and a variety of functional group substitutions [ 1 ]. Chrysosplenium americanum (Saxifragaceae), a semi-aquatic weed, accumulates a variety of tetra- and penta methylated flavonol glucosides substituted at various positions of the flavonol ring [ 2 ]. Their biosynthesis from the parent aglycone, quercetin, is catalyzed by a number of stepwise, substrate-specific, position-oriented O -methyltransferases and two distinct O -glucosyltransferases in a highly ordained sequence (Figure 1 ) [ 2 ]. During the course of their biosynthesis, the partially methylated intermediate, 3,7,4'-trimethylquercetin (TMQ) is hydroxylated at position 6 to 3,7,4'-trimethylquercetagetin (TMQg) by a 2-oxoglutarate-dependent dioxygenase (ODD), flavonol 6-hydroxylase [ 3 ]. Plant ODDs (EC 1.14.11.-) constitute a class of non-heme, iron-containing cytosolic enzymes that utilize an oxoacid as a cosubstrate and a reducing agent for the reactive iron moiety, typically ascorbate. This widespread class of enzymes has been implicated in a variety of plant metabolic pathways, including the biosynthesis of some amino acids, hormones, signalling molecules and a variety of secondary metabolites [ 4 ]. Hydroxylation at position 6 of partially methylated flavonols is of particular interest, since it is catalyzed by a 2-oxoglutarate-dependent dioxygenase rather than a cytochrome P450-dependent monooxygenase. Using the peptide sequence information obtained from the purified plant protein [ 3 ], degenerate primers were designed for the screening a C. americanum cDNA library and the isolation of a F6H clone. The identity of this clone was confirmed after identifying internal peptide sequences in the translated amino acid sequence of the isolated cDNA clone, as well as by functional expression of F6H in both prokaryotic and eukaryotic systems. The molecular characterization of this gene, with respect to its genomic organization and phylogenetic relationship to other ODDs involved in plant secondary metabolism, contributes to the growing pool of information on this class of enzymes. Results and discussion Isolation and cloning of F6H Several peptides were obtained from tryptic digestion of the native protein, one in particular, Micro1 – DNGWILLHIGDSNGHR, exhibited significant similarity to other known flavonoid ODDs such as the flavanone 3-hydroxylase (F3H) [ 5 ], flavonol synthase (FLS) [ 6 ] and anthocyanidin synthase (ANS) [ 7 ]. Two other peptide sequences, Micro2 – KIVEACEDWG and Micro3 – TLMAGLACKLLGVL, exhibited limited homology to this class of enzymes. Of the different approaches used, two methods allowed the isolation of putatively positive cDNA fragments from a C. americanum bacteriophage expression library [ 8 ]. The PCR-based strategy utilized several primer combinations and resulted in the isolation of a fragment termed, F6H·1, that exhibited a significant degree of homology to flavonoid ODD genes. In addition, a portion of the deduced amino acid sequence of F6H·1 matched another fragment obtained from microsequencing. Subsequently, the PCR-based screening approach resulted in the amplification of a 1,245 bp-long cDNA fragment, termed cF6H , that contained the 3'-end of this putative cDNA clone, including an in-frame stop codon (TAA), a putative polyadenylation signal (ATATAA) and a short polyA tail (Accession # AY605048), although it lacked the translation start site. The same cDNA library was also screened with an oligonucleotide probe derived from the F6H·1 sequence. Putatively positive clones were isolated and characterized, but none yielded a full-length F6H cDNA clone, although several clones were isolated with homology to related sequences, particularly F3H and aminocyclopropanecarboxylate oxidase (ACCO) . Further attempts to isolate a complete F6H ORF were unsuccessful, including the use of inverse PCR and the GenomeWalker technique (ClonTech). The truncated DNA fragment, cF6H , translates into a 376 amino acid-long sequence with a predicted molecular mass of 40.9 kDa and a pI of 5.1. The fact that the native protein exhibits a molecular mass of 43 to 45 kDa following gel filtration or SDS-PAGE analysis respectively [ 3 ], suggests that the cDNA fragment lacks ~10 to 15 N-terminal amino acid residues. However, the conserved regions and catalytically important residues located in the C-terminal of ODDs [ 9 ] are present in the translated cF6H sequence. The amino acid residues involved in iron (His222, His285, Asp224) and α-KG-binding (Arg295, Ser297), as well as other conserved residues are present within the cF6H sequence (Figure 2 ). The near-full length cF6H , although truncated at the N-terminal, was confirmed to be an authentic fragment of the gene encoding the F6H, since the internal peptide sequences obtained from the native protein were present in the deduced amino acid sequence of the cDNA clone (Figure 2 ). Sequence analyses of ODD genes including cF6H demonstrate that the conserved regions and catalytically important amino acids are located primarily within the C-terminal half of these proteins, whereas the less conserved N-terminal region may be involved in substrate binding or maintaining the protein's tertiary conformation. Given the inherent variability of the N-terminal, that in certain cases it does not contribute significantly to ODD enzyme activity as was the case with the desacetoxyvindoline 4-hydroxylase of Catharanthus roseus [ 10 ], and that all possibilities for the isolation of the remaining fragment were exhausted, the cF6H fragment was cloned into prokaryotic and eukaryotic expression vectors to assess its enzyme activity. Expression of recombinant F6H The induction and solubility of the bacterial expressed F6H (rF6Hb) fusion protein were assessed over a 4-h period and recombinant F6H enzyme activity was assayed. The level of expression of the fusion protein was monitored by Western bolt analysis of cell lysates using anti-(His) 6 antibodies. The antibody reacted with a 45 kDa protein band in cell lysates carrying the pTrc-His-cF6H construct after induction (Figure 3 ). This corresponds to the correct mass of the recombinant protein since the (His) 6 -tag and extraneous amino acids resulting from the cloning process account for an additional ~3.5 kDa in the fusion construct. The Ni-NTA-purified recombinant protein (Figure 3 ) exhibited a F6H activity of 0.103 pkat/mg following size exclusion chromatography (Table 1 ). The level of enzyme activity did not vary significantly regardless of the time or temperature of induction. In order to test for any inhibitory effect resulting from the (His) 6 -tag, the fusion protein was cleaved by incubation with enterokinase (EK). The enzyme activity of the cleaved protein was significantly reduced compared to the Ni-NTA-purified rF6Hb (Table 1 ). The loss of activity was attributed to destabilization of the protein resulting from dialysis to remove inhibitors of the EK reaction, followed by incubation at room temperature with EK. Control experiments indicated that the (His) 6 -tag did not stimulate overall recombinant enzyme activity, since the intact rF6Hb treated in parallel with the preparation undergoing cleavage exhibited a similar reduction in enzyme activity. The translated cF6H sequence possesses two potential glycosylation sites at Ser139 and Ser305 that may contribute to catalytic activity, perhaps by stabilizing a favorable tertiary conformation or through the modulation of interactions with other proteins. The effects of such post-translational modifications and protein folding were taken into account by expression of the recombinant protein in the eukaryotic expression system Pichia pastoris . This system is relatively easy to manipulate and exhibits many of the advantages of eukaryotic expression, including protein processing, folding and modification. Recombinant protein expression was both intracellular (rF6Hy) and secreted (rF6Hys). The chosen culture media (BMGY/BMMY) contained protein stabilizing factors, such as peptone and yeast extract, shown to reduce proteolysis, particularly of secreted proteins [ 11 ]. Protein expression, monitored by Western blot analysis using anti-(His) 6 antibodies, was maximal at 3 to 4 days post-induction in both intracellular and secreted systems (Figure 4 ), and the protein eluted at a volume corresponding to ~40 kDa from a Superose 12 column. The Ni-affinity-purified preparations exhibited a specific activity of 0.21 and 0.11 pkat/mg for the intracellular (rF6Hy) and the secreted (rF6Hys) constructs, respectively. Their specific activities could not be further improved by size exclusion chromatography instead of or in addition to, Ni-NTA purification (Table 1 ). In both prokaryote and eukaryote expression systems rF6H was soluble, exhibited similar physicochemical properties to the native protein and was no more susceptible to proteolytic degradation. Interestingly, as with the native plant protein [ 3 ], the recombinant F6H was functional as a monomer, but was also shown by gel filtration to associate in vitro (Figure 3C ). In the case of the native F6H, this may result from the disruption during isolation of any weak interactions with other proteins, particularly those involved in polymethylated flavonol biosynthesis. A hydrophobic prediction plot of the translated cF6H (data not shown) indicates the presence of a nonpolar region at the very end of the protein sequence, which may participate in dimerization or aggregation processes. The substrate specificity of recombinant F6H was tested using the Ni-NTA-purified enzyme with different flavonol substrates (Table 2 ). The results indicate that, although the overall specific activity of both recombinant proteins is reduced as compared to the native protein, 3,7,4'-TMQ is the preferred substrate for both rF6Hb and rF6Hy, which accepted neither quercetin nor 3-methylquercetin to any significant extent. On the other hand, 3,7-dimethylquercetin was accepted at 56% and 63% of the control activity by rF6Hb and rF6Hy, respectively. Given the fact that neither of the recombinant proteins utilized naringenin as a substrate, it seems unlikely that F6H catalyzes a side reaction of F3H or a bifunctional activity as F3H-FLS, as has been demonstrated with the Citrus unshiu bifunctional dioxygenase [ 12 ]. Therefore, this enzyme may putatively be classified as a narrow-specificity ODD [ 12 ]. Taken together, these results suggest that Chrysosplenium F6H exhibits a specificity for partially methylated flavonoids involved in polymethylated flavonol biosynthesis characteristic of the species. The cofactor requirements for the bacterially expressed recombinant protein were similar to those of the native plant protein [ 3 ]. Ferrous ions had the greatest effect on enzyme activity and enzyme reactivation in affinity-purified samples, as demonstrated by abolition of enzyme activity upon incubation with 5 mM EDTA. A preliminary assessment of the apparent K m values of rF6Hb for the flavonol substrate (63 μM) suggests that the binding affinity has been reduced 17-fold compared to the native protein (0.27 μM) [ 3 ]. In contrast, that for α-KG was only slightly affected (78 μM instead of 60 μM), indicating that the binding site for the cosubstrate has not been substantially altered. Nevertheless, a detailed kinetic analysis of the recombinant protein was not conducted given the truncation of the N-terminal and reduced enzyme activity. The hydroxylation of an aromatic carbon may be the result of substrate positioning in relation to the oxidizing moiety within the active site. Mehn and colleagues [ 13 ] in attempting to elucidate the role of the cosubstrate in oxygen activation by ODDs through the use of synthetic iron complexes have also demonstrated the hydroxylation of phenolic substrates. In addition, the nature of the substituents on the phenolic moiety, dramatically affects the reaction rate. These results suggest that the structure of the substrate and its positioning within the active site play a crucial role in aromatic hydroxylations by ODDs as opposed to more fundamental differences in reaction mechanisms. This may explain the importance of the N-terminal to F6H enzyme activity, particularly if it is involved in substrate binding either by directly contributing to the flavonol binding site, or by maintaining the appropriate conformation for substrate recognition. This hypothesis is reinforced by the fact that rF6H exhibited a reduced specific activity in comparison to the native F6H, regardless of the expression system, degree of purification or the location of the polyhistidine tag. 3.2 Molecular characterization In order to isolate the genomic region coding for F6H, genomic C. americanum DNA was used as a template for amplification reactions with primers designed to the outermost regions of the cF6H sequence. This produced a fragment of ~3.1 kbp ( gF6H ) that contained two potential intronic sequences (Figure 5 ). The first intron, 421 bp long is centrally located at position 684 of cF6H , whereas the second intron is significantly longer, 964 bp and is located towards the 3'-end of the gene at position 943. Southern analysis of genomic DNA, probed with the cF6H partial ORF, gave rise to single bands in Bam HI- and Eco RI-digested genomic DNA (Figure 6 ). The internal sequence of gF6H does not contain any recognition sites for the above enzymes; however, one recognition site is located within the known sequence for Kpn I, Nco I, Xho I. Two major bands were detected in these lanes at estimated sizes ranging from ~4.3 to 10.0 kbp. These results indicate that F6H is present as a single copy gene in C . americanum , particularly since potential tandem F6H repeats would have resulted in the observation of fragments larger than 6.2 kbp, which were not present in lane 1. Under conditions of reduced stringency, certain lanes exhibited more than the two expected bands (data not shown), indicating the existence of related sequences within the genome. The ORFs of the clones isolated using different approaches were identical in sequence, indicating that they represent the same protein. This is in agreement with the results obtained from Southern analysis suggesting that F6H is present as a single copy in the C. americanum genome. The deduced amino acid sequence of cF6H exhibits homology to other ODDs, particularly at the C-terminal, and this conservation can be extended to the organization of the gene as a whole. The fact that gF6H possesses two introns at conserved locations for ODDs [ 14 ], suggests that ODD sequences arose through divergence from a common ancestor. The single copy nature of this enzyme also suggest a regulatory role in polymethylated flavonol biosynthesis and may be significant, in relation to a second hydroxylation that occurs at the 2'-position of the TMQ intermediate (Figure 1 ). A comparable reaction was recently reported to be catalyzed by a cytochrome P450-dependent monooxygenase involving the 2'-hydroxylation of isoflavones in Medicago truncatula [ 15 ]. It has been proposed that the cytosolic enzymes involved in the sequential methylation of Chrysosplenium flavonoids are organized on the surface of a multienzyme aggregate, thus allowing for a more efficient regulation of the pathway as a whole [ 16 ]. It is likely that the F6H is a component of this enzyme complement, as it introduces a hydroxyl group at position 6 of 3,7,4'-trimethylquercetin for subsequent O -methylation at this position by a flavonol 6- O -methyltransferase (F6OMT). Immunolocalization of both enzymes, F6H and F6OMT, should provide further evidence in support of this view. cF6H from C. americanum exhibits highest similarity, at the amino acid level, to various F3H homologs. Phylogenetically, it is evident that homologous genes encoding biochemically related proteins in single pathways are clustered into related subgroups (Figure 7 ), perhaps as a result of gene duplication and divergence. Genes encoding proteins in the same pathway of a given species, although not within the same subgroup, exhibit expectedly higher identity than unrelated genes. cF6H clusters with the F3H group of genes, although at a position distal to those homologs from other species, thus suggesting an evolutionary relationship with this particular subgroup of biosynthetically related enzymes. It is evident from Figure 7 that flavonol ODDs cluster into 2 distinct clades; the first consisting of enzymes with a narrow substrate specificity including F3H, FSI and F6H, whereas the second is comprised of FLS and ANS, both possessing broad substrate specificity as has been previously described [ 12 , 17 , 18 ]. It seems that based on biochemical and phylogenetic considerations, Chrysosplenium F6H exhibits high substrate and position specificity. At the phylogenetic level, ODDs comprise a superfamily with numerous subgroups whose subsets are defined by shared motifs in the encoded proteins, such as those involved in flavonoid biosynthesis. These motifs often comprise the active site of the enzyme and/or the binding domains for substrates and cofactors. In addition, the degree of similarity between genes encoding dioxygenases with different substrate preferences suggests a common reaction mechanism. The molecular characterization of F6H and related ODDs could identify potential commonalities in structure or reaction mechanisms, as well as reveal motifs or residues that may determine reaction type and/or substrate preference. When aligned with related sequences, cF6H exhibits a high degree of conservation of the motifs required for iron and cosubstrate binding, whereas other regions show little or no identity and are presumed, most likely, to contribute to differences in substrate specificity and/or reaction type. This applies particularly to the variable N-terminal and a region where a gap insertion within an ODD sequence motif is required for proper alignment with other flavonoid biosynthetic enzymes. Further evidence of such distinctness is the fact that, although F6H clusters with the F3H group of flavonoid dioxygenases (Figure 7 ), it appears to have evolved paraphyletically from a common ancestor with respect to this group of genes. Conclusions A novel ODD cDNA involved in the 6-hydroxylation of partially methylated flavonols was isolated and characterized from C. americanum . The substrate specificity observed with the recombinant F6H compares well with the native enzyme [ 3 ]; displaying a specificity for position 6 of partially methylated flavonols, with 3,7,4'-trimethylquercetin being the preferred substrate. The fact that it hydroxylates position 6 of the aromatic ring A of a partially methylated flavonol contrasts with other aromatic hydroxylations which are commonly catalyzed by cytochrome P450 monooxygenases, such as the flavonol 8-hydroxylase of Tagetes patula [ 19 ] and the flavonoid 6-hydroxylase of soybean involved in isoflavone biosynthesis [ 20 ]. Given that both the native and recombinant F6H exhibit a preference for relatively hydrophobic substrates further distinguishes this protein from other dioxygenases characterized to date, that are known to accept relatively polar flavonoid aglycones [ 21 - 24 ]. Further evidence of such distinctness is the fact that, although cF6H clusters with the F3H group of flavonoid dioxygenases (Figure 7 ), it appears to have evolved in a paraphyletic fashion with respect to this group of genes. General flavonoid biosynthesis may have arisen from a multifunctional dioxygenase, since F3H and F6H seem to share a common ancestor, but significant divergence has since occurred resulting in the evolution of this novel activity. A clone with full enzyme activity, which can be isolated based on the cF6H sequence provided fresh tissue is available, can be used to assess the versatility of this enzyme with respect to substrate preference through site-directed mutagenesis, as well as to assess its potential applications in metabolic engineering. Methods Materials Chrysosplenium americanum (Schwein x Hooker; Saxifragaceae), was collected from St. Anicet, Québec, and was maintained in the greenhouse under conditions simulating its natural habitat regarding light intensity, temperature and humidity. Flavonol substrates were from our laboratory collection. All other chemicals were of analytical reagent grade. Buffers: Assay buffer, 50 mM Tris-HCl (pH 7.3), 10 mM DTT, 150 mM NaCl, 10% glycerol (v/v); Wash solution I, 2 × SSC, 0.1% SDS (w/v); Wash solution II, 0.1 × SSC, 0.1% SDS (w/v); Blocking solution, 5% SDS (w/v), 125 mM NaCl, 25 mM sodium phosphate (pH 7.2); Blot washing solution, 0.5% SDS (w/v), 12.5 mM NaCl, 2.5 mM sodium phosphate (pH 7.2). FPLC buffers were filtered, degassed and stored at 4°C. Isolation of an F6H clone The ligand-affinity purified F6H protein [ 3 ] was subjected to digestion and sequencing at the Harvard Microchemistry Facility using microcapillary, reverse-phase HPLC nano-electrospray tandem mass spectrometry (MS/MS) on a Finnigan LCQ quadrupole ion trap mass spectrometer. The MS/MS spectra obtained were correlated with known sequences using the Sequest algorithm developed at the University of Washington [ 25 , 26 ]. A C. americanum cDNA Lambda UniZap XR library was screened by PCR as described in [ 27 ] with 5 μL of the cDNA library (representing 1 × 10 6 pfu) per reaction. The following degenerate oligonucleotide primers were derived from two internal peptide sequences obtained from the native protein, Micro1 and Micro2; Micro1For-5'-GCTGGATCCTCCTTCATATA-3'; Micro1Rev-5'-(GC)GATAC(AT)GG(TC)AA(TC)(CG)TTAG(ATGG(CT)TATAC-3'; Micro2For-5'-AATTGTTGAAGCATGTGAAG-3'; Micro2Rev-5'-(TC)GGGGTTAG(AG)AG(TC)GT(AC)CG(AG)AA-3'; T3 + 6 - 5'-GCT CGA AAT TAA CCC TCA CTA AAG GG-3' T7 + 6 - 5'-GAA TGG TAA TAC GAC TCA CTA TAG GGC G-3' Primer combinations: i) Micro1Rev and Micro2For; ii) Micro1For and T3; iii) Micro1Rev and T7; iv) Micro2For and T3; v) Micro2Rev and T7. PCR products were subjected to DNA sequencing for characterization after cloning into the pGEM-T vector (Promega). DNA sequencing was carried out using the dideoxy-mediated chain termination method [ 28 ]. Fragment F6H·1 was amplified using a mixed primer set, T7 and Micro1Rev, and contained the peptide sequence to which the primer was designed, as well as certain conserved ODD motifs and a second peptide sequence. In order to isolate full-length putative F6H clones, new sets of primers were designed specifically to the ends of the F6H·1 sequence and the screening procedure was repeated with vector primers under stringent conditions. Alternatively, the bacteriophage cDNA library was screened as described in [ 29 ], using the F6H·1 fragment (602 bp) as an oligonucleotide probe. The near-full-length cDNA fragment isolated that putatively encoded the F6H was termed cF6H . Given the lack of fresh C. americanum tissue and its disappearance from its natural habitat, for use in 5'-rapid amplification of cDNA ends (RACE) experiments or primer extension, genomic DNA-based techniques such as inverse PCR and GenomeWalker (ClonTech) were employed in attempts to isolate the remaining 5'-end of the putative F6H sequence. Nevertheless, neither of these approached proved successful. To isolate the genomic region coding for the cF6H , C. americanum genomic DNA (0.1 to 1.0 μg) was employed as a template for PCR using primers designed to the ends of the cF6H sequence. Putatively positive fragments were subsequently cloned into the pGEM-T vector for DNA sequencing. To determine the copy number of F6H , genomic DNA (15 μg) was digested overnight and subjected to Southern analysis according to [ 30 ]. The probe, cF6H , was labeled using the BioPrime Kit (Amersham) designed for the preparation of biotinylated nucleotide probes for blotting with the IRDye800-conjugated Streptavidin (Rockland Immunochemicals) as the detection system. The membrane was pre-hybridized using UltraHyb-OS (Ambion) at 42°C for 2–3 h. Hybridization was carried out with denatured, biotinylated probe solubilized in a fresh aliquot of UltraHyb-OS overnight at 42°C. The membrane was washed according to manufacturer's instructions using wash solutions I and II. The membrane was blocked with blocking solution for one hour at room temperature, prior to probing with IRDye800-labelled streptavidin (1:10,000) in blocking solution for 1 h at room temperature. The membrane was washed with blot washing solution three times, 15 min each, prior to detection. Cloning and expression strategies The cDNA fragment encoding the near-full length F6H, cF6H was cloned into an E. coli expression system (pTrc-His; Invitrogen) The fragment was amplified by PCR using gene-specific primers, containing Bam HI and Hin dIII recognition sites, respectively. The DNA insert is positioned downstream and in-frame with a sequence encoding the (His) 6 -tag and an enterokinase cleavage recognition site. The pTrc-His-F6H construct was transformed into Top 10 cells by heat shock, and selected on ampicillin (50 μg/mL) containing media. Recombinant protein production in E. coli strain Top 10 was induced by the addition of 1 mM isopropyl-β-D-thiogalactopyranoside (IPTG) for 4 h at 37°C. After sonication of the cell pellet and centrifugation, the supernatant was assayed for F6H enzyme activity or purified on Ni-NTA resin (Qiagen). The affinity-purified protein was eluted in presence of 250 mM imidazole and subjected to buffer exchange on a PD-10 column against the assay buffer. Enzyme assays and analysis of reaction products were carried out as previously described [ 3 ]. Heterologous expression in the Pichia pastoris expression system (EasySelect pPicZ-His; Invitrogen) can be either intracellular (pPicZ) or secreted (pPicZα), depending on the presence of an in-frame signal peptide. The cF6H fragment was amplified by PCR using gene-specific primers, containing Kpn I and Sac II recognition sites, respectively. For the pPicZ construct, the initiation ATG was part of the yeast consensus sequence (AATA ATG TCT) included in the 5' gene-specific cloning primer. For the pPicZα construct, the insert was cloned in-frame with the N-terminal signal sequence and C-terminal His-tag. The pPicZ-cF6H and pPicZα-cF6H constructs were transformed into Pichia cells by electroporation and putative multi-copy recombinants were selected on Zeocin-containing media according to manufacturer's instructions (Invitrogen). Recombinant F6H production was induced by the addition of 0.5% methanol (in the absence of glucose) every 24 h for 3 to 4 days. A buffered culture medium (BMGY/BMMY; containing 100 mM potassium phosphate, pH 8.0) was used for cell growth and protein induction in order to enhance protein stability and limit enzyme inactivation. In the case of intracellular recombinant protein production, cells were lysed using glass beads and extracts were prepared according to manufacturer's instructions (Invitrogen). Secreted proteins were collected and concentrated by ammonium sulfate precipitation (35 to 70% saturation), and used for activity assays after desalting or for subsequent affinity purification. Recombinant proteins obtained from both prokaryotic and eukaryotic expression systems were subjected to SDS-PAGE [ 31 ] and Western blot [ 32 ] analysis using chemiluminescent (HRP; Amersham) or IRDye800 (Li-Cor) detection. Phylogenetic analyses Fifteen ODD genes involved in secondary metabolism where biochemical information was available, belonging to different plant species, were selected from the PubMed and GenBank searches. The amino acid sequences were aligned using CLUSTAL-W [ 33 ] and PHYLIP output format. The data was transferred into MacClade 4.03 [ 34 ] for visual inspection and manual editing prior to analysis by a phylogenetic tree building and analysis program, PAUP 4.0, beta 4 [ 35 ]. The optimality criterion employed for the distance method was Neighbor-Joining [ 36 ]. The aligned amino acid sequences were analyzed using a heuristic search algorithm with 1000 random addition sequences. Bootstrapping analysis was carried with heuristic search based on 1000 replicates and the distance measure was set to be equal to mean character difference. List of abbreviations cF6H F6H cDNA F6H flavonol 6-hydroxylase gF6H genomic F6H ODD 2-oxoglutarate-dependent dioxygenase α-KG α-ketoglutarate ORF open reading frame rF6H recombinant F6H rF6Hb recombinant F6H expressed in bacteria ( E. coli ) rF6Hy recombinant F6H expressed in yeast ( P. pastoris ) – intracellular rF6Hys recombinant F6H expressed in yeast ( P. pastoris ) – secreted TMQ 3,7,4'-trimethylquercetin TMQg 3,7,4'-trimethylquercetagetin Authors' contributions DA carried out experiments in the project, participated in the design and coordination of the project, as well as the writing of the manuscript. RKI conceived of the project and contributed to the writing of the manuscript. All authors read and approved the final manuscript.

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544881

Potential of essential fatty acid deficiency with extremely low fat diet in lipoprotein lipase deficiency during pregnancy: A case report

Background Pregnancy in patients with lipoprotein lipase deficiency is associated with high risk of maternal pancreatitis and fetal death. A very low fat diet (< 10% of calories) is the primary treatment modality for the prevention of acute pancreatitis, a rare but potentially serious complication of severe hypertriglyceridemia. Since pregnancy can exacerbate hypertriglyceridemia in the genetic absence of lipoprotein lipase, a further reduction of dietary fat intake to < 1–2% of total caloric intake may be required during the pregnancy, along with the administration of a fibrate. It is uncertain if essential fatty acid deficiency will develop in the mother and fetus with this extremely low fat diet, or whether fibrates will cross the placenta and concentrate in the fetus. Case presentation A 23 year-old gravida 1 woman with primary lipoprotein lipase deficiency was seen at 7 weeks of gestation in the Lipid Clinic for management of severe hypertriglyceridemia that had worsened with pregnancy. While on her habitual fat intake of 10% of total calories, her pregnancy resulted in an exacerbation of the hypertriglyceridemia, which prompted further restriction of fat intake to < 2% of total calories, as well as administration of gemfibrozil at a lower than average dose. The level of gemfibrozil, as the active metabolite, in the venous and arterial fetal cord blood was within the expected therapeutic range for adults. The clinical signs and a biomarker of essential fatty acid deficiency, namely the ratio of 20:3 [n-9] to 20:4 [n-6] fatty acids, were closely monitored throughout her pregnancy. Despite her extremely low fat diet, the levels of essential fatty acids measured in the mother and in the fetal blood immediately postpartum were normal. Normal essential fatty acid levels may have been achieved by the topical application of sunflower oil. Conclusions An extremely low fat diet in combination with topical sunflower oil and gemfibrozil administration was safely implemented in pregnancy associated with the severe hypertriglyceridemia of lipoprotein lipase deficiency.

Background Primary lipoprotein lipase (LPL) deficiency is a rare autosomal recessive disorder characterized by severe hypertriglyceridemia, due to the accumulation in plasma of chylomicrons and very low density lipoproteins (VLDL) that result from the absence of LPL activity [ 1 ]. The estimated frequency of this disorder is <1 per million with the carrier frequency at about 1 in 500. Clinically significant hypertriglyceridemia usually manifests early in childhood with dietary fat intolerance, including recurrent episodes of abdominal pain and acute pancreatitis, failure to thrive, eruptive xanthoma and hepatosplenomegaly. Very severe hypertriglyceridemia during pregnancy can occur and is associated with significant maternal morbidity and fetal mortality [ 2 - 6 ]. Overproduction of hepatic VLDL in the presence of decreased LPL activity contributes to the marked increase in plasma triglyceride (TG) levels during pregnancy [ 7 , 8 ]. The management of severe hypertriglyceridemia in a pregnant patient with LPL deficiency is directed toward preventing pancreatitis in the mother and delivery of a healthy infant. Lowering of plasma TG in the prevention of pancreatitis is managed primarily by dietary fat restriction, but additional TG lowering may be required and has been reported with use of fibrates, such as gemfibrozil [ 6 , 9 , 10 ]. Two major questions arose during the treatment aimed at lowering the severe hypertriglyceridemia in this pregnant LPL-deficient patient. First, would essential fatty acid (EFA) deficiency develop in the mother and fetus as a result of severe maternal dietary fat restriction? Second, would gemfibrozil cross the placenta and concentrate in the fetus? The strategies utilized to prevent EFA deficiency and the fetal nutritional information obtained from studies at birth will address these questions and concerns. Case presentation Clinical history The proband presented to her pediatrician at age 3 month with failure to thrive. She was evaluated at the Children's Hospital Medical Center in Seattle, where an elevated TG level of 14,000 mg/dl (158 mmol/L) suggested hyperchylomicronemia with LPL deficiency. Plasma post-heparin LPL activity was absent, consistent with defective catabolism of TG rich particles. Further study at the University of Washington of her post-heparin plasma at age 19 revealed absent LPL activity due to a defective LPL protein, while her hepatic lipase activity was normal [ 11 ]. She was a compound heterozygote with two missense mutations in the LPL gene (Trp86-Arg/His136-Arg) [ 12 ]. On a self-selected low fat diet (< 20% of dietary calories) she was able to maintain her TG < 1000 mg/dl (11.3 mmol/L) throughout a healthy and normal childhood and adulthood. Because of her excellent compliance with low dietary fat intake and active physical lifestyle, she had never developed clinical pancreatitis. Throughout the years, there were few episodes of mid epigastric abdominal discomfort that subsided with short periods of fasting. She had developed eruptive xanthoma briefly when oral contraceptives were used. Pregnancy course At the age of 23, the proband presented at week 7 of gestation for management of anticipated worsening of hypertriglyceridemia in pregnancy. She had been in excellent physical condition and had continued her routine 10–20% fat diet during the first trimester (Figure 1 ). Her TG was 396 mg/dl (4.5 mmol/L) at week 7 of gestation. When she retuned to the University of Washington Medical Center (UWMC) 5 weeks later, her TG levels had started to rise and despite further restriction of dietary fat to < 10% of calories, the level had risen to 3705 mg/dl (41.9 mmol/L) by week 16. At week 28, she developed her first episode of mid epigastric abdominal pain without elevated serum amylase or pancreatic lipase levels, consistent with subclinical pancreatitis. Remission of the symptoms occurred within 2–3 days of a near zero dietary fat intake as an outpatient. Subsequent reduction to less than 2% of dietary fat was implemented with a liquid formula by the following week, to decrease the risk of recurrent abdominal pain in the setting of extremely elevated TG levels (3000–6000 mg/dl [33.9–67.8 mmol/L]). Gemfibrozil at a low dose of 300 milligram (mg) twice a day was also initiated at week 29 to prevent a further upward trend in TG in the third trimester. The dosage was increased to 300 mg three times a day a week later. This appeared to stabilize her TG in the 5000–6000 mg/dl (56.5 – 67.8 mmol/L) range until week 34 when she developed severe abdominal pain. Initial evaluation at her local hospital revealed a TG level of 6,050 mg/dl (68.4 mmol/L) and elevated pancreatic lipase (680 IU/dl) and amylase (1336 IU/L). She was transferred and admitted to the UWMC and placed on intravenous fluids. Two days later, her pancreatitis subsided and she was placed back on the <2% fat diet and 900 mg/day of gemfibrozil. A second episode of pancreatitis a few days later prompted re-admission to UWMC for labor induction at the 35 th week of gestation. A 5 lb 3 oz baby girl with a 5-minute Apgar score of 9 was delivered vaginally. A short time after the delivery, the baby was briefly intubated for about 48 hours due to respiratory distress but did well subsequently. The patient's plasma TG rapidly decreased to 2015 mg/dl (22.8 mmol/L) within the first postpartum 24 hours, accompanied by improved abdominal symptoms. Resumption of low fat solid food brought back the symptoms of pancreatitis and she was placed back on the IV fluids followed by a more gradual incremental introduction of oral intake. Along with 1,200 mg/day of gemfibrozil, she had complete resolution of abdominal symptoms by postpartum day-8 and eventual resolution two weeks after discharge of peri-pancreatic fluid accumulation demonstrated by CT imaging studies. Now, 11 years later, the proband and her daughter are both healthy and doing well. The proband's TG levels are back to baseline and stable on 10–20% fat diet. Her daughter has had normal TG and cholesterol levels on regular diet. Figure 1 Serum triglyceride level and corresponding dietary fat intake and gemfibrozil administration during pregnancy *Dietary fat was expressed as % of total caloric intake. Eruptive xanthomas, which are associated with hypertriglyceridemia, developed on the proband's buttocks at week 20 and subsequently spread to the upper arms and medial aspects of thighs as her TG levels rose. Peculiarly, palmar xanthoma, typical of remnant removal disease (type III hyperlipidemia), also developed at week 27. A concomitant ex vivo investigation of the mechanisms contributing to palmar xanthoma in the proband, who has an apo E 4/E3 phenotype, revealed an enhanced macrophages uptake of the TG rich lipoproteins as a result of an unusual enrichment of these lipoproteins with apo E during pregnancy [ 13 ]. Gestational EFA profiles Because of concern for unfavorable fetal neurological development due to EFA deficiency, EFA profile was monitored in the mother at each visit starting at gestational week 23. The initial analyses were performed at the Clinical Nutrition Research Unit (CNRU), Harborview Medical Center campus of the University of Washington. After separation from cells, the fatty acids from the phospholipid fraction of the plasma were extracted and subsequently measured by capillary gas chromatography. In addition to the total amount and % of each FA, the ratio of eicosatrienoic acid (ETA, 20:3(n-9)) to arachidonic acid (AA, 20:4(n-6)) was calculated (Figure 2 ). This ratio was used as an index to the patient's EFA status. By week 26, the ratio had risen from 0.032 to 0.052 (Fig 2 ), suggesting a trend to a less EFA abundant state [ 14 ]. Topical application of sunflower oil containing large amounts of polyunsaturated fatty acids (PUFA) was initiated as a non-oral route for supplementing EFA because of its reported success in EFA deficient subjects [ 15 ]. With 460 mg per day of sunflower seed oil (approximately 240 mg of linoleic acid) applied to her arms and trunk, her EFA profile appeared to improve with the ratio stabilizing at 0.08 at 31 weeks. A peak to a ratio of 0.09 occurred at week 34 possibly due to irregular uses of topical PUFA (Figure 2 ). Figure 2 Essential fatty acid profile in maternal blood EFA: essential fatty acids, from sunflower seed oil. Measurement was made in the phospholipid fractions. 20:3(n-9): eicosatrienoic acid (ETA). 20:4(n-6): arachidonic acid (AA). Immediately postpartum, placental fetal blood and maternal plasma was obtained for total fatty acid analysis (Figure 3 ). These FA were measured by capillary gas/liquid chromatography at the Oregon Health Sciences University and expressed as % of total FA. In spite of low levels of n-6 and n-3 fatty acids in maternal blood and similarly decreased levels of PUFA precursors (linoleic [LA] and α-linolenic acid [ALA]) in cord blood samples compared to the reported normal reference range [ 16 ], there were abundant long chain PUFA (such as arachidonic acid [AA]) in the fetal circulation. This suggested that either the topical application of sunflower seed oil during the late stage of pregnancy prevented EFA deficiency or that the fetus had increased capacity for obtaining EFA from the mother. Figure 3 Fatty acid composition in maternal and cord plasma LA: linoleic acid. ALA: α-linolenic acid. ETA: eicosatrienoic acid. AA: arachidonic acid. Gemfibrozil in fetal circulation To examine whether there might be excessive accumulation of gemfibrozil in the newborn baby, fetal cord blood was obtained at the time of delivery and gemfibrozil levels and its active compound, metabolite III, were measured. The analysis was performed as a courtesy of the Research Lab at the Parke-Davis Pharmaceutical (Ann Arbor, Michigan) by high performance liquid chromatography (HPLC) and revealed similar concentrations of the drug and its active metabolites in both umbilical vein and artery, which were within the normal reference range for adults (Figure 4 ). Figure 4 Gemfibrozil metabolite III levels in the fetal cord blood *Ref. range: 0.5 – 40 μg/ml Conclusions Children with primary LPL deficiency can be effectively managed on fat-restricted diets and grow normally into adulthood. However, they can present with extreme elevation of TG levels with serious acute pancreatitis. This LPL-deficient subject developed severe hypertriglyceridemia in early pregnancy, with eruptive xanthomas and pancreatitis. With the diligent efforts from the patient, her family, and a team of specialists in lipid metabolism, dietetics, high-risk obstetrics and gastroenterology, a successful outcome was achieved. Outcome goals were clearly set at the onset of her pregnancy care, including nutritional management of the expected rise in triglyceride levels associated with the estrogen surge of pregnancy to prevent acute pancreatitis, and avoidance of clinical EFA deficiency in both the mother and the fetus. Pregnancy and hypertriglyceridemia Pregnancy-induced hypertriglyceridemia is estimated to be the cause in 4–6% of all pancreatitis cases during pregnancy, while most cases result from cholelithiasis [ 4 ]. Hypertriglyceridemia-related pancreatitis in pregnancy also has been reported due to other causes of severe hypertriglyceridemia [ 17 ]. Successful management requires early detection of signs and symptoms of acute pancreatitis often accompanied by increases in serum lipase and amylase levels and characteristic findings in imaging studies. Once the pancreatitis is suspected, these individuals should be admitted for aggressive medical management including intravenous hydration concurrent with no oral intake of solids or liquids. Obstructive processes in the biliary system need to be ruled out specifically since treatment modalities are quite different. Pregnancy and LPL deficiency Pregnancy is a well known situation in which the physiologic estrogen surge profoundly alters the TG-rich lipoprotein metabolism, resulting in a gradual rise in TG levels over the course of non-complicated pregnancy, peaking at the level of 200–300 mg/dl (2.26 – 3.39 mmol/L) at term [ 17 ]. During the first two trimesters of pregnancy, adipose fat storage, as maternal fuels, occurs in preparation for an active transfer of maternal glucose, amino acids, and free fatty acids (FFA) across the placenta for accelerate fetal growth in late phase of gestation [ 18 ]. In late gestation, adipose tissue lipolysis is greatly augmented generating FFA and glycerol, for further hepatic VLDL production, contributing to the flux of circulating TG-fatty acids in pregnancy [ 18 , 19 ]. Greater concentration of chylomicrons from dietary fat as a result of maternal hyperphagia in late pregnancy also contributes to the circulating TG-rich lipoprotein pool [ 18 , 19 ], and provides alimentary substrates for VLDL production [ 20 , 21 ]. LPL activities in the liver, heart, and particularly adipose tissue are, however, reduced by an estimated total of 85% [ 19 , 22 ] in late gestation. Concomitantly, clearance of circulating TG-rich lipoproteins is reduced in late pregnancy. Hepatic lipase activity is decreased as well and could explain the observation of parallel TG-enrichment of LDL and high-density lipoproteins (HDL) particles during normal gestation. All these changes take place to ensure a stable supply of fuel substrates across the placenta for normal fetal development while preserving maternal metabolic homeostasis [ 18 , 19 ]. Very low fat diet and EFA deficiency Arachidonic acid [AA, 20:4(n-6)], an important precursor of the prostaglandin compounds, cannot be synthesized de novo from FFA in mammals and must be derived from another EFA in the diet, namely linoleic acid [LA, 18:2(n-6)]. In the case of life long low oral fat intake, as in our patient, clinical EFA deficiency might occur with depletion of n-3 and n-6 FA stored in adipose tissue. Therefore, her source of EFA would be entirely from recent dietary intake and deficiency might occur sooner than in individuals with normal LPL and abundant EFA storage [ 23 ]. Eicosatrienoic acid [ETA, 20:3(n-9)], on the other hand, is not an EFA because it can be synthesized in mammals from palmitic acid [16:1(n-9)]. In the event of diminishing pool of both n-3 and n-6 fatty acids due to absence or deficiency in the diet, more ETA are produced and the amount parallels the degree of deficiency [ 24 - 26 ]. EFA deficiency syndrome commonly results from a combined deficiency in both n-3 and n-6 fatty acids. A ratio of ETA to AA > 0.2, is suggestive of EFA deficiency [ 24 - 26 ]. Clinical manifestations in EFA deficiency are unusual on a diet containing > 2% of the calories as linoleic acid [ 27 ]. While the clinical symptoms of dryness and desquamation of the skin are annoying at best, a more serious consequence could be impaired fetal brain and visual development. The proband did not develop signs of clinical EFA deficiency, nor did the ratio of 20:3(n-9) to 20:4(n-6) exceed 0.2 at any stage of her pregnancy, although an upward trend did occur. Additionally, the report that infants fed a formula low in EFA grew poorly and developed multiple medical complications was a concern [ 28 ]. Several reports have documented a reversal of biochemical and clinical manifestations of EFA deficiency in infants and adults by cutaneous administration of EFA-rich oil, such as sunflower oil [ 29 - 35 ]. Therefore, application of sunflower oil to the proband's skin was initiated at week 25 and may have had prevented progression of EFA deficiency in mother, as suggested by the stabilization of the 20:3(n-9) to 20:4(n-6) ratio. Surprisingly, we found low levels of n-3, n-6, and PUFA precursor levels in the cord blood taken during the delivery, and yet there was abundant long chain PUFA in the infant circulation. This would suggest that other adaptive mechanisms were involved in maintaining the critical levels of long chain EFA in fetal circulation in the face of inadequate maternal supply. Use of gemfibrozil in LPL deficiency Use of TG lowering drugs, such as gemfibrozil (a fibrate), can be used to directly lower the triglyceride level in the prevention of acute pancreatitis. Pregnancy induces hepatic production of TG-rich VLDL and may respond to fibrates through inhibition of hepatic production of VLDL. Gemfibrozil, which is an FDA category C drug, has not been observed to be associated with adverse drug effects in reports of pregnancy-related severe hypertriglyceridemia [ 6 , 10 , 36 , 37 ]. During the last few weeks of her gestation low dose gemfibrozil in our subject seemed to have stabilized her TG level (Fig 1 ), which might otherwise have continued to rise due to the estrogen effect on hepatic VLDL production in the third trimester. A lower than usual dose of gemfibrozil was used due to the concern for excess placental transfer of its metabolites that has been reported in pregnant cats [ 38 ]. Analysis of the parent compound and metabolites did not detect excessive accumulation in the fetal cord circulation in contrast to the reports in animal models. While this observation needs to be independently confirmed, adverse drug effects in the infants born to mothers on gemfibrozil or other fibrates have not been reported. Moreover, gemfibrozil has been used and appears to be free of short-term side effects in pediatric populations [ 39 - 42 ]. Therefore, low dose gemfibrozil may be safe for use during the last trimester in hyperlipidemic patients at high risks for acute pancreatitis. In conclusion, a successful pregnancy outcome was achieved in our LPL deficient patient, confirming previous reports [ 6 , 43 ] that aggressive lipid lowering strategies under the supervision of experienced health care providers works in this high risk setting. Although the patient developed pancreatitis during her pregnancy, the use of an extremely low fat diet together with a fibrate helped limit the increase in the triglycerides, and her pancreatitis was neither life threatening nor adversely affected fetal survival. Sunflower oil applied topically may have helped prevent EFA deficiency in both the mother and fetus. Use of gemfibrozil did not appear to have any adverse effect on the child. Thus, the use of these two therapeutic approaches appears safe and appropriate in the medical management of pregnancy-associated severe hypertriglyceridemia, where EFA deficiency and recurrent pancreatitis are major concerns. Competing interests The author(s) declare that they have no competing interests. Authors' contributions ECT was a senior fellow in Metabolism, Endocrinology and Nutrition and drafted the manuscript. JAB was the dietitian. Both MSV and GJA contributed to the measurement of fatty acids. GJA was also a consulting scientist in fatty acid metabolism. AC and JDB were the faculty associated with the case at the UW GCRC. JDB conceived of the research, supervised the fellow, and coordinated the manuscript revisions. Pre-publication history The pre-publication history for this paper can be accessed here:

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524185

Intravascular ultrasound to guide the management of intracoronary thrombus: a Case Report

Percutaneous coronary intervention can be associated with distal embolization of thrombotic material causing myocardial necrosis and infarction. We discuss the role of intravascular imaging to guide the use of a distal protection device by describing the outcome of a young woman presenting with non-ST elevation myocardial infarction. Coronary angiography demonstrated an isolated minor stenosis in the proximal left anterior descending coronary artery with slight haziness beyond the lesion. Intravascular ultrasound confirmed an extensive thrombus overlying a bulky atherosclerotic plaque. A distal filter wire was therefore successfully used to reduce the risk of distal embolization. The use of intravascular ultrasound in patients presenting with acute coronary syndrome may reveal large thrombi that are difficult to image using conventional angiographic techniques. Intravascular ultrasound can therefore be used as a tool to select lesions requiring distal protection.

Background Patients with acute coronary syndromes (ACS) are increasingly treated with an early invasive strategy. During percutaneous coronary interventions (PCI) interventionalists have often to deal with thrombus-laden lesions in native coronary vessels. This poses the serious problem of preventing macroscopic and microscopic distal embolization [ 1 ]. There have been many recent advances in this field, and new tools are available for shielding the distal microvasculature, including occlusive systems and basket filters. In the very emboli-prone saphenous vein grafts interventions, for example, both techniques have been associated with favourable results [ 2 , 3 ]. In native vessels cost and efficacy [ 4 ] considerations prompt a careful use of these devices, and a sensible approach could be selecting lesion and patients at high risk of distal embolization. For example, preventing distal embolization is particularly important in young patients presenting with their first coronary event with a large thrombotic burden [ 5 , 6 ]. Angiography alone is known to underestimate the risk of distal embolization: for example, only overt signs of massive thrombus burden are predictive of no-reflow in myocardial infarction patients treated with primary PCI [ 7 ]. Intravascular ultrasound (IVUS) has the potential to overcome many of the limitations of angiography, including lesion characterization and assessment of plaque rupture and thrombus [ 8 - 11 ], but its use is still restricted. We present a case of successful prevention of macroscopic distal embolism in a young patient with ACS obtained combining IVUS and distal filter protection. Case presentation A 41-year-old lady presented with a short history of cardiac sounding chest pain. She was a smoker, had hypertension and had a strong family history of premature ischaemic heart disease. The ECG showed widespread anterior T wave inversion. Conventional treatment was started immediately for ACS including intravenous nitrates, low molecular weight heparin, aspirin and clopidogrel. The patient remained pain-free following admission and serial biochemistry demonstrated a rise in cardiac troponin I to 24 mmol/l at 24 hours. There was no evidence of Q waves on the ECG and left ventricular function was normal on echocardiography. Coronary angiography was undertaken four days after admission. This demonstrated mural thickening of the proximal left anterior descending (LAD) coronary artery with a possible filling defect at the distal end of the lesion but no evidence of coronary atherosclerosis elsewhere (Fig. 1B ). Interrogation of the proximal LAD stenosis with IVUS (Galaxy II system; Atlantis 40 MHz Catheter, Boston Scientific/Scimed, Inc., Maple Grove, Minnesota) showed a large intracoronary thrombus (Fig. 1C ) adherent to a mural atheromatous plaque starting at the ostium of LAD (Fig. 1A ). The thrombus had a lobulated appearance with no evidence of internal blood flow or speckling. It contained echolucent areas indicating cavitation and consistent with ongoing thrombus organization. No evidence of complete plaque rupture (intraplaque cavity communicating with the lumen) was seen. Figure 1 Composite image showing an angiographic right anterior oblique projection of the left coronary system (Panel B) and two intravascular ultrasound images (Panels A&C) before the intervention. Dotted line shows the approximate location of the IVUS slices. An eccentric plaque is visible in the proximal left anterior descending artery (Panel B), with some haziness at the distal end. IVUS confirms the presence of the plaque (Panel A) and shows a bulky, partially organized, thrombus (Panel C) loosely attached to the distal end of the plaque. No signs of plaque rupture are visible. Percutaneous coronary intervention was performed using distal filter protection with the EZ Filterwire (Boston Scientific, Natick, MA, USA). The GpIIb/IIIa antagonist Abciximab was administered. A 4.0 × 15 mm stent was placed directly with good final angiographic result (Fig. 2B ) and no evidence of macroscopic distal embolisation. Repeat IVUS confirmed good apposition of the stent and the absence of residual thrombus (Fig. 2A & 2C ). At retrieval, the Filterwire contained a small but significant amount of pink thrombotic material and yellowish plaque debris. Equivalent chest x-ray radiation dose (assuming a single posteroanterior projection chest x-ray is eight centi-Gray/cm2) was 380. Figure 2 Composite image showing an angiographic right anterior oblique projection of the left coronary system (Panel B) and two intravascular ultrasound images (Panels A&C) after the intervention. Dotted line shows the approximate location of the IVUS slices. An excellent angiographic result is visible on the left anterior descending (Panel A). IVUS confirms good apposition of the stent (Panel A&B), with no residual or prolapsed thrombus. No further Troponin I elevation occurred; the patient was discharged home the next day, and remains asymptomatic at two months. Discussion Acute coronary syndromes with extensive thrombosis in the absence of widespread coronary atheroma are detected most frequently in young smokers [ 5 , 6 ]. The necessity of preventing distal embolic during PCI is becoming increasing recognised, as traditional angioplasty may be associated with distal myocardial necrosis [ 1 ]. In our case, angiographic appearance was not suggestive of either obstructive coronary disease or a high embolic risk: none of the criteria set up by Yip et al [ 7 ] (cutoff pattern of occlusion, accumulated thrombus > 5 mm proximal to the occlusion, presence of floating thrombus, persistent dye stasis distal to the obstruction, reference lumen diameter of the culprit artery > or = 4 mm, and incomplete obstruction with presence of accumulated thrombus more than three times the reference lumen diameter of culprit artery) was met, and the patient had already received prolonged antiplatelet and anticoagulant therapy. However, we suspected the presence of a significant thrombotic mass, mainly on the clinical grounds of widespread ECG change and Troponin I elevation, and performed IVUS examination. The importance of the IVUS results is clear: the visualization of a lobulated thrombus, loosely attached to an eroded, non-ruptured plaque, prompted us to use distal protection, which in turn may have prevented significant embolism. IVUS proved also useful in ensuring full coverage of the lesion, resolving the relation of the lesion with the LAD ostium, correctly sizing the stent, and ruling out thrombus or plaque prolapse through stent struts. Conclusion We present a case of successful management of an intracoronary thrombus, which was accomplished combining IVUS data and a distal protection device. IVUS proved invaluable in the diagnosis and treatment of this challenging case. We believe IVUS guidance should be considered for assessing thrombotic burden and embolism potential particularly in young patients with ACS when angiographic data are inconclusive. Competing interests The authors declare that they have no competing interests. Authors' contributions IP and AM have written the first draft of the manuscript. AB and IP have performed the coronary intervention. IP, AM, VA and AB participated in the design and coordination of the final manuscript. All authors have read and approved the final manuscript.

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523826

The Global Health Watch

Why three non-governmental organizations are launching an alternative to the World Health Report

At the World Health Assembly in May 2003, three civil society groups—the People's Health Movement, the Global Equity Gauge Alliance, and Medact—discussed the need for civil society to produce its own alternative to the World Health Organisation's World Health Report. We felt strongly that we needed to produce a global health report that had equity and the right to health at its heart. We also needed a way to monitor the performance of global health institutions themselves. The idea of an alternative to the World Health Report has developed into an initiative called the Global Health Watch, which we are launching next year. The Three Key Players Medact ( http://www.medact.org ) is a United Kingdom–based global health charity, undertaking education, research, and advocacy on conflict, poverty, and the environment. The Global Equity Gauge Alliance ( http://www.gega.org.za ) was created to participate in and support an active approach to monitoring health inequalities and promoting equity within and between societies. The Alliance currently includes 11 member-teams, called Equity Gauges, located in ten countries in the Americas, Africa, and Asia. The People's Health Movement ( http://www.phmovement.org ) is a global network of activists, organisations, and social movements. Its goal is to re-establish health and equitable development as top priorities in local, national, and international policy-making, with comprehensive primary health care as the strategy to achieve these priorities. Why an Alternative Is Needed Concerted action by civil society has had tremendous success in the field of international health—global grassroots campaigns on infant feeding, smoking, and drug prices have changed policies and people's lives. The Watch: Examining the world's health from an alternative perspective (Illustration: Giovanni Maki, Public Library of Science) But over the last two decades—at the same time as these campaigns have scored victories—there has, in some parts of the world, been a stagnation and even reversal of the dramatic gains in life expectancy witnessed by many others for much of the 20th century. These reversals, unprecedented outside times of war and famine since the early 1800s and a scandal in a world of enormous wealth and technological prowess, have once more thrown the spotlight on how underlying social and economic problems affect health and health services. The setbacks have also underlined appalling failures of health development policy. Ambitious targets to achieve ‘Health for All’ agreed to at the end of the 1970s by health ministers from around the world have failed miserably; a similar fate seems likely for the targets set out in the Millennium Development Goals for 2015. As a result, there are large question marks hanging over the effectiveness of international health policy. These are the reasons why we have decided to produce Global Health Watch, which we hope will become a regular report on international health issues ( Box 1 ). We believe that civil society campaigners need to look at the broader health agenda—beyond single-issue advocacy. Major concerns about health systems such as poor pay and working conditions for health professionals, creeping commercialisation, and plummeting public investment have not had the attention they deserve. Likewise, broader determinants of health—such as education, water, food, and the environment—are often insufficiently regarded when health policies are formulated. The Watch attempts to focus minds on the need for more integrated planning across sectors and on the creation of health systems that promote social justice rather undermine it. Box 1. Global Health Watch—2005 Report Contents Section A: The Politics and Economics of Health in the 21st Century Section B: The Health Care Sector Health systems that promote social justice Responding to the commercialisation of health care The pharmaceutical industry, access to medicines, and intellectual property rights Human resources: the lifeblood of health systems Responding to HIV/AIDS Gene technology and the attainment of health for all Sexual and reproductive health Section C: Beyond Health Care Environmental challenges Militarism and conflict Water The right to food: land, agriculture, and household food security Education Section D: Marginalised Groups Indigenous peoples People with disabilities Section E: Monitoring of Institutions and Resource Flows World Health Organisation World Bank World Trade Organisation and trade agreements Global Fund and Pepfar (United States President's Emergency Plan for AIDS Relief) Monitoring of international promises on aid and debt relief Section F: Summary and Strategies for Action How Will the Watch Be Different? This is how the Watch will be alternative: it will present options for health policy-makers that question the dominant reform agenda that emphasises market-driven and diseased-based approaches to health care. A policy bias against government action and a lack of creative thinking about how governments can shape health care markets to work in favour of equity and social inclusion are unfortunate features of global health debates. More recently, the emphasis has been placed once again on campaigns against specific diseases such as HIV/AIDS and tuberculosis, despite the universally acknowledged importance of building and maintaining health systems that can respond to the broader needs of patients. We hope the Watch will present some alternative and imaginative thinking about how health services can respond creatively to the many challenges they face, with a strong focus on basic principles of equity and universality and avoiding top-down disease-focussed programmes that neglect the broader determinants of health. We have invited some of the most interesting and innovative thinkers in health policy—from both developing and developed countries and from academia and civil society—to help us achieve these objectives. The Watch will also be ‘alternative’ in another sense—it will act as a regular monitor of the policies, governance, and funding of the institutions affecting global health, including the World Health Organisation and World Bank, something no other health report undertakes. We hope to offer proposals for reform, as well as to stimulate further action by civil society to make these institutions more accountable and responsive to the needs of the poor and vulnerable. Linking Civil Society Groups It is important to say that the three networks and organisations that have convened the Watch are really just its initiators. In the end we hope the Watch will be backed by as many individuals, organisations, and social movements as possible, strengthening the links between civil society organisations across countries and across health-related sectors, and increasing the power and influence of the report itself. Already, many have expressed their interest in the project, and their willingness to contribute: through writing chapters, contributing case studies, and launching the Watch and promoting it in their country when it is finished. Groups from India and Brazil are planning parallel national Watches. We plan to launch the Watch at the second People's Health Assembly, which will be held in Ecuador in July 2005. We don't want this report to be addressed just to health activists or health policy-makers or academics. If we are going to create change we need to capture the imagination of the broader health professional community and the public at large. That is why we encourage readers to get involved and tell others about the Watch and to use it to throw down a challenge to those who call the shots at national and international levels.

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212693

Heterochromatin Dynamics

Heterochromatin is usually thought of as a stable and inactive region of the genome. Not so, according to a study published earlier this year

In 1928 the German botanist Emil Heitz visualised in moss nuclei chromosomal regions that do not undergo postmitotic decondensation ( Heitz 1928 ). He termed these parts of the chromosomes heterochromatin, whereas fractions of the chromosome that decondense and spread out diffusely in the interphase nucleus are referred to as euchromatin. Further studies revealed that heterochromatin can be found in all higher eukaryotes, mainly covering regions with a low frequency of genes, such as pericentromeric regions and telomeres. Heitz proposed that heterochromatin reflects a functionally inactive state of the genome, and we now know that DNA in heterochromatic regions is less accessible to nucleases and less susceptible to recombination events. All these findings contributed to the current view that heterochromatin is a rigid nuclear compartment in which transcriptionally inactive regions of chromatin are densely packed and inaccessible to the transcription machinery ( Grewal and Elgin 2002 ). This view was challenged earlier this year in two papers published back-to-back in Science ( Cheutin et al. 2003 ; Festenstein et al. 2003 ). Certain proteins are specifically associated with heterochromatin— notably, the family of heterochromatin protein 1 (HP1) ( Eissenberg and Elgin 2000 ; Singh and Georgatos 2002 ). HP1 is thought to play a central role in creating a stable and inaccessible heterochromatic network by interacting with several other proteins, including histones, the major protein constituent of all chromatin. In particular, HP1 binds to the tail of the histone H3 when it has been modified by methylation of lysine 9. This histone modification is an important landmark of inactive chromatin regions. In the two articles in Science , both groups generated cell lines stably expressing HP1 fused to green fluorescent protein (GFP) so that they could watch the behaviour of HP1 in living cells. Specifically, they used photobleaching techniques to study the in vivo mobility of HP1. In a defined region of a cell, fluorescently tagged proteins are bleached by a laser pulse. Recovery of fluorescence in the bleached area can then only occur if bleached molecules are replaced with unbleached molecules from regions outside the bleached area. The technique is called fluorescence recovery after photobleaching (FRAP) and provides information about the mobility and stability of the cellular structures and proteins. For HP1–GFP, the speed at which fluorescence recovers depends on how tightly it is bound within heterochromatic regions. Heitz (and many others) might have expected that heterochromatin-bound HP1 shows little turnover and therefore recovery should take place very slowly. Cheutin et al. (2003) first demonstrated that the heterochromatic regions visualised with HP1–GFP are stable in shape for at least 2 h. By contrast, subsequent FRAP experiments revealed that HP1 proteins have a surprisingly high turnover rate in heterochromatic clusters as well as in regions the authors define as euchromatic ( Figure 1 ). Recovery of 50% was reached after 2.5 s in heterochromatin and after 0.6 s in euchromatin. In contrast, for histone proteins, the structural protein components of chromatin, 50% recovery took more than 2 h ( Kimura and Cook 2001 ). Cheutin et al. found that complete recovery of bleached HP1 took 5 s in euchromatin and 60 s in heterochromatin. Festenstein et al. (2003) report, however, that recovery only reaches 90% in euchromatin and 70% in heterochromatin. Incomplete recovery would point to an immobile population of HP1 that does not exchange rapidly. In fact, such a stable fraction could be indicative of a stable structural network made of a minor fraction of HP1 that could serve as a nucleation site for a more mobile fraction of HP1. In my opinion, this should be kept in mind, even if 100% recovery is observed. It might well be that a few stably associated HP1 molecules that remain undetected in FRAP studies exert an important structural function in heterochromatin formation. Consequently, this can be regarded as an important discrepancy between the two studies. Both studies also reported a number of other experiments in which the condensation state of chromatin was modified and was found to alter the mobility of HP1, such that relaxed condensation was associated with increased HP1 mobility. Figure 1 FRAP of HP1–GFP Reveals a Dynamic Association with Heterochromatin A fraction of a heterochromatic cluster (arrowhead) was bleached by a laser pulse, and recovery of fluorescence was monitored by time-lapse imaging. Images were kindly provided by Thierry Cheutin and Tom Misteli. As discussed by the authors of both studies, several important conclusions can be drawn. In striking contrast to previous models, HP1 appears to be a very mobile molecule. The formation of heterochromatin appears not to be based on a stable oligomeric network of HP1 molecules. Furthermore, heterochromatin is accessible. There is no obvious constraint shielding these transcriptionally inactive compartments from factors residing outside. Given the rapid exchange of HP1 in heterochromatic clusters, any other soluble nuclear protein, such as a transcription factor, should be able to gain access, compete with silencing factors, and potentially activate genes located within heterochromatin. Taken together, heterochromatin appears to be a surprisingly dynamic compartment even though it forms morphologically stable entities. This dynamic situation could imply that heterochromatic silencing is not just a switch, but rather a continuous and active process. Although the new work suggests that heterochromatin is more dynamic than was thought, some caveats remain. It is still possible that a stable “mark” of heterochromatin does exist. As I discussed above, this mark might be an undetected fraction of immobile HP1 molecules. In addition, one cannot exclude that HP1 is a downstream factor that is dynamically tethered to a stable binding site, the most likely candidate being the methylated histone tail. Perhaps the role of HP1 in heterochromatic silencing has simply been overinterpreted. The formation of facultative heterochromatin by X inactivation in mammals, for example, does not involve HP1 even though appropriate histone methylation marks are set. This indicates that heterochromatin formation does not always follow the same rules and suggests that our definitions of heterochromatin must be refined. In any case, it could well be that a silent state is marked by signals that have a slow turnover. In fact, histone methylation is believed to generate a quite stable “code” ( Jenuwein and Allis 2001 ). Until this hypothesis has been tested in vivo, we should keep an open mind about the stability and dynamics of nuclear structure. Several other nuclear compartments (spliceosomes, nucleoli) have also been proposed to consist of dynamic collections of components ( Misteli 2001 ). Personally, I am intrigued by the fact that heterochromatin also might function as a steady-state association of molecules. Is the entire nucleus, the genome organization—irrespective of its functional state—in constant flux? Of course, such a situation would provide an appealing explanation for the plasticity of gene expression. On the other hand, dynamic control of gene expression complicates explanations of how established expression patterns are stably inherited. So far, genetic knockout experiments have been the most powerful tools to unravel the mechanisms of epigenetic regulation. Unfortunately, many of those investigations can only provide insight into the establishment of expression profiles. What happens if regulatory factors are knocked down after expression patterns are set up? Which signals will be erased and which ones will persist? I am working on the mechanism of dosage compensation in Drosophila ( Lucchesi 1998 ). This process involves stable changes of chromatin structure, which leads to lasting effects on X-chromosomal gene expression. To examine the generality of the new results on heterochromatin, it will be important to find out whether the proteins involved in defining the X chromosome as an epigenetic compartment have the same dynamic behaviour as HP1. In addition, systematic knockdown of these factors after establishment of dosage compensation might disclose a hierarchy in epigenetic maintenance that is different from the one affecting establishment.

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535936

A randomized trial comparing digital and live lecture formats [ISRCTN40455708

Background Medical education is increasingly being conducted in community-based teaching sites at diverse locations, making it difficult to provide a consistent curriculum. We conducted a randomized trial to assess whether students who viewed digital lectures would perform as well on a measure of cognitive knowledge as students who viewed live lectures. Students' perceptions of the digital lecture format and their opinion as whether a digital lecture format could serve as an adequate replacement for live lectures was also assessed. Methods Students were randomized to either attend a lecture series at our main campus or view digital versions of the same lectures at community-based teaching sites. Both groups completed the same examination based on the lectures, and the group viewing the digital lectures completed a feedback form on the digital format. Results There were no differences in performance as measured by means or average rank. Despite technical problems, the students who viewed the digital lectures overwhelmingly felt the digital lectures could replace live lectures. Conclusions This study provides preliminary evidence digital lectures can be a viable alternative to live lectures as a means of delivering didactic presentations in a community-based setting.

Background Medical education is increasingly being conducted in community-based teaching sites outside of the traditional academic medical setting [ 1 ], At the same time, the economics of health care are requiring academic physicians to be more productive[ 2 ]. These trends in academic medicine are making it more difficult to provide students and residents with consistent, high quality instruction. Our institution has a community integrated structure where medical students spend the clinical portion of their training in one of six community campuses spread throughout the State of Michigan. Although this structure has many advantages, it is difficult to provide a consistent educational experience for the students. To help address this challenge, we implemented an all-day lecture series held at one of the community campuses two weeks before the end of the internal medicine clerkship. The students and faculty presenters from other campuses traveled from their home campus to the campus hosting the lecture series. End-of-clerkship feedback from the students has indicated the lecture series is both valuable and well received. Traveling to the host community, however, was inconvenient and time consuming for both students and faculty presenters. In addition, it is not practical for students at our rural medicine campus to attend due to the distance (approximately 400 miles) from the other communities. There is evidence that delivering the audio from a lecture in combination with the presenter's slides can be an effective means of delivering lectures at remote sites, and may even be as effective as traditional lectures[ 3 , 4 ]. We saw this as a potential solution for providing a consistent didactic curriculum in our clerkship. With the availability of inexpensive, high quality digital camcorders and software for merging audiovisual material with presentation slides, we felt including video of the presenter as well as audio from a live lecture in combination with the presenter's slides might result in a more engaging and hence more effective presentation than audio alone. During the 2003–2004 academic year, we conducted a randomized trial comparing attending the lecture series with viewing a CD-ROM-based multimedia version of the same lecture series. If the digital lectures could help students master the material at the same or similar level of understanding as live lectures, they could potentially replace the live lectures and thereby save the time lost to travel for both the students and faculty presenters. Additionally, the digital lectures would provide the same instructional opportunities for students in our rural medicine program as students in our other campuses and provide all our students the opportunity to view the presentations at their convenience. Methods Students taking the third-year required internal medicine clerkship during the 2003–2004 academic year at our institution were offered the opportunity to participate in the study. Those agreeing to participate were randomized into to one of two arms of the study. The random assignment of students to the two arms of the study was done within each community to control for the potential of community differences. The control group traveled to the host community campus and attended the live lectures with their colleagues who chose not to participate in the study. The experimental group stayed at their home campus on the same day and completed a parallel set of CD-ROM-based multimedia modules made from digital recordings of the previous year's lectures. They completed these digital lectures in computer laboratories in either the community campus office or within one of the teaching hospitals. The series included six lectures covering asthma, coronary artery disease (CAD), acute renal failure, liver disease, thyroid disease, and antibiotic pharmacology. The Clerkship Education Committee chose these topics based on their perceived importance and consistency with the Society for General Internal Medicine/Clerkship Directors of Internal Medicine (SGIM/CDIM) Curriculum Guide[ 5 ]. Between the 2002–2003 academic year when the lectures were taped and the 2003–2004 academic year when the study was conducted, the clerkship faculty decided to revise the lecture series to be more case-based though the topics were kept the same. Two of the lectures, CAD and renal failure, were not modified and kept as consistent as possible with the previous year in order to conduct the study. Though there might have been minor inconsistencies between the digital and live versions of these two lectures, the same faculty member presented each lecture during both the 2002–2003 academic year when the lectures were taped and the 2003–2004 academic year when presented live. The two lecturers also attempted to keep the live lectures as consistent as possible with the digital lectures and used the same slides that they had used the previous year. While the format of the other four lectures changed, the material covered and instructional objectives remained consistent. At the end of the live lecture series, students were asked to complete a short examination that included four to five questions based on each of the six lectures. These questions were written by the presenters of the lectures and designed to assess student mastery of the lectures' key objectives. The students were informed that the purpose of the examination was to provide them with feedback on the mastery of the material and the presenters with feedback on the effectiveness of the lectures, and would not impact on their clerkship grade. After the students completed the exam, they were given a copy that included the correct answers and a short explanation for the correct answer. The exam forms contained no student identifiers, but students in the control group were asked to indicate on the examination form that they had agreed to participate in the study so they could be differentiated from the students who had chosen not to participate in the study. Students in the experimental arm of the study completed the same examination in their home community after they had completed the digital lectures. They were also asked to complete a short feedback form asking whether they had any technical problems using the modules, to rate their agreement with what the researchers felt to be three potential advantages and three potential disadvantages of the modules, and whether they felt the modules could serve as a suitable replacement for live lectures. The specific questions are listed below. Advantages of the Modules • Convenience of viewing the presentations when you choose. • Avoiding having to travel to another community for an all day lecture series. • Ability to keep copies of these presentations for use in the future. Disadvantages of these modules • Inability to ask questions of the presenter • Lack of group interaction/discussion of a topic • Just not like being in the room with the presenter The CD-ROM modules were created using a technique developed by the first author. A manual outlining how to develop these modules is available from . They included digitized video and audio from the taped presentation inserted as a window in the PowerPoint ® slides from the presentation. As students displayed each of the slides, they were able to observe the presenter in the multimedia window discussing the slide that was being viewed. Nine of the items on the exam focused on the material in the CAD and acute renal failure lectures, where the lecturers presented the lectures in the same format as they had used in the previous year when the lectures were taped. The remaining 20 examination items covered material in the other four lectures. Group differences were tested for statistical significance by both an independent sample t-test for means and a Mann-Whitney test for ranks. A Levene's test for equality of variance between the two groups was also performed. These analyses were conducted separately for the subset of items covering the material in the CAD/acute renal failure lectures and the other four lectures. A power analysis was conducted to assess the magnitude of the difference between the groups that would likely be detectable given the number of students participating in the study. The coefficient alpha reliability of the exam was also estimated. The data were presented descriptively using means, standard deviations and mean ranks within the control and experimental groups. All analyses were conducted using the Statistical Package for the Social Sciences version 11. Approval for the project was obtained from the University Committee for Research Involving Human Subjects within our institution. Results A total of 96 students completed the internal medicine clerkship during the 2003–2004 academic year. As described below 56 of the students were eligible to participate in the study. A total of 29 students or 52% of the eligible students agreed to participate in the study. Complete data were available for 12 students who attended the live lectures and 17 students who completed the digital lectures. During the first rotation, there were some technical problems in a demonstration of the digital lectures. The net result was that very few students chose to participate during that rotation. During the second and third rotations, approximately two-thirds of the students agreed to participate. There were also 20 students who were ineligible to participate. These included six students from the rural medicine program at Marquette who do not participate in the live lecture series due to the distance from the other communities. Additionally, some of the communities conducted a fourth rotation of the internal medicine clerkship due to space limitations in the three regular rotations and a live version of the lecture series was not given for the students in the fourth rotation. These 20 students all completed the CD-ROM modules but because they could not be randomized between the live and digital formats, they were not able to participate in the study. Differences in the sample sizes for the two groups were due to some of the students in the live lecture group failing to mark that they were participating the study. During the second clerkship rotation, the proctor inadvertently failed to remind the students participating in the study to mark this information on their examinations when the exams were handed out. A power analysis indicated that with the number of subjects in the study, it would be possible to detect differences of nine tenths of a standard deviation with a power of 80%, p < 0.05 for a one-tailed t-test. Table 1 displays the mean, standard deviation, and average rank of the exam score for the control and experimental groups for the two sets of items. The differences between the groups for both sets of items were not statistically significant for means (t-test) or medians (Mann-Whitney) at the p < 0.05 level. Table 1 Performance on the examination: CD-ROM versus live lecture format Mean SD No. p-value Items from CAD and renal failure (lecture format the same for each group) Live lecture 4.42 1.08 12 CD-ROM 4.88 2.00 17 t-test † 0.22 (one-tailed) Mann Whitney U 0.56 (exact test) Levene's Test for equality of variances 0.026 Items from other four lectures (lecture format differed for control & treatment groups) Live lecture 9.25 3.11 12 CD-ROM 9.00 2.72 17 t-test † 0.41 (one-tailed) Mann Whitney U 0.91 (exact test) Levene's Test for equality of variances 0.96 † The t-test was calculated based on unequal variances. Differences in variances were tested via a Levine test and found to be statistically different in the two groups. ‡ The t-test was calculated based on equal variances. Differences in variances were tested via a Levine test and found not to be statistically different in the two groups. The Levene's test for equality of variance between the control and experimental groups was statistically significant (p = 0.03) for the CAD and renal failure items. The variation among the scores of students who observed the CD-ROMs was almost twice as large as for students who observed the live lectures. There was no statistically significant difference among the groups for the variance of the items from the other four lectures. The coefficient alpha reliability for the items covering CAD/renal failure and the items covering the other four lectures were 0.33 and 0.66 for the 9 and 20 item scales respectively and was 0.70 for the combined 29-item exam. The 17 students who completed the digital lectures also completed a short feedback form on their experiences and impressions of the digital lecture format. These data are presented in Table 2 . Table 2 Feedback on the CD-ROM Based Lectures Yes No Did you have any technical difficulties viewing the modules? 16 (94.1%) 1 (5.9%) Advantages of the Modules Very Important Important Slightly Important Not Important Convenience of viewing the presentations when you choose. 12 (70.6%) 5 (29.4%) 0 (0.0%) 0 (0.0%) Avoiding having to travel to another community for an all day lecture series. 15 (88.2%) 2 (11.8%) 0 (0.0%) 0 (0.0%) Ability to keep copies of these presentations for use in the future. 9 (52.9%) 3 (17.6%) 5 (29.4%) 0 (0.0%) Disadvantages of these modules Inability to ask questions of the presenter 3 (17.6% 6 (35.3%) 6 (35.3%) 2 (11.8%) Lack of group interaction/discussion of a topic 3 (17.6% 5 (29.4%) 1 (5.9%) 8 (47.1%) Just not like being in the room with the presenter 0 (0.0%) 1 (5.9%) 5 (29.4%) 11 (64.7%) Strongly Agree Agree Disagree Strongly Disagree These modules can serve as an adequate replacement for the all day Crush the Boards lecture series. 10 (58.8%) 6 (35.3%) 0 (0.0%) 0 (0.0%) Discussion There were no statistically significant differences found between students who viewed the live and CD-ROM based lectures. The observed mean scores in the two groups were in fact almost identical. Unfortunately, the small sample size limits the power of the study and confidence in which we can assert that digital lectures can be as effective as live lectures in increasing students' knowledge. The study does suggest that it is unlikely that there are large differences in the performance of students who view CD-ROM based lectures as opposed to live lectures and adds to the growing body of literature concerning the effectiveness of technology for implementing distance learning in medical education. There was a statistically significant difference in variances among the two groups for the items covering the CAD/renal failure lectures. The standard deviation in the scores was twice as large for the students who completed the digital modules. The differences in the dispersion are also evident in the range of values in each group. It is not clear why there was more variation in the scores among the students who completed the digital modules. It may be related to the technical problems encountered by many of the students in accessing the modules, though one would expect this would have resulting in extending the lower tail of the distribution but not the upper tail. It may have also in part reflected the impact of discussions that occurred during the live lectures that may have reduced the variability among the students in their responses to the examination. Despite the fact that almost all of the students experienced some technical difficulties using the modules, they all agreed and most strongly agreed the modules could serve as an adequate replacement for live lectures. They were particularly appreciative of not having to travel to another community to attend didactic presentations and having the flexibility of viewing the modules at their convenience. Of the three potential disadvantages of the format that were listed on the feedback form, they felt their inability to ask a question of the presenter was the most important. In the future we are considering using a web-based bulletin board system as a means of allowing students to ask questions of the presenter. The number of students with technical difficulties viewing the modules was surprising. We had tested the modules on a variety of different computers with very few problems. In a few cases, the CD-ROMs we distributed apparently had not been copied correctly. Additionally, we switched the video formats from MPEG to Windows media files. We assumed there would be less compatibility problems with the Windows media files given that this is a format developed by Microsoft. Unfortunately, we later found out the Windows media files require software that was not shipped with earlier versions of Windows. We expect this was a significant cause of the technical problems the students experienced. We are now using a commercial software package which greatly simplifies the process of creating the digital lectures and allows them to be distributed over the Web as well as via CD-ROM requires no special software minimizing the compatibility issues. Students who completed the fourth rotation of the clerkship and did not participate in the study were provided with the new version of the modules. Only one of the 12 students indicated they had technical problems accessing the lectures off the CD-ROM disks on which the modules were distributed and that student was able to access the modules via the Web. Such combined Web and CD-ROM distance learning formats have been shown to be effective in a number of educational settings [ 6 , 7 ]. Limitations There were several important limitations in the study. First is the very small sample size which limited the power of the study for detecting differences in the performance of the students completing the live and CD-ROM based lectures. It also increased the likelihood the two groups of students were not equivalent. Since there were no student identifiers on the exams, it was not possible to compare the characteristics of the two groups. The outcome measure was a locally developed test. While the items were written by the presenters and based on the major objectives in their lectures, there was no assessment of validity other than content validity. It is also not clear the extent the findings of this study can be generalized to other digital lecture formats. Conclusions Although the data collected in this study were limited, it provides some evidence that digital lectures are both well received by students and can provide a satisfactory substitute for live lectures from a performance standpoint. Competing interests The author(s) declare that they have no competing interests. Authors' contributions DJS designed the study, developed the feedback instrument on for the digital modules conducted the statistical analyses and wrote the first draft of the paper. GSF, HSF and KK developed and gave presentations, wrote questions for the knowledge examination and edited and helped revise the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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544842

FNAC of Bacillus- Calmette- Guerin lymphadenitis masquerading as Langerhans cell histiocytosis.

Bacillus Calmette Guerin (BCG) lymphadenitis is a well known entity. Disseminated BCG infection usually presents as generalized lymphadenopathy, skin rash and hepatosplenomegaly and at times, can pose a diagnostic challenge to clinicians. There are only a few published studies on the cytological findings of BCG lymphadenitis. In this letter we report the fine needle aspiration cytology (FNAC) of BCG lymphadenitis clinically masquerading as Langerhans cell histiocytosis (LCH). FNA smears showed sheets of foamy macrophages and many polymorphs in a dirty necrotic background with many macrophages as well as polymorphs showing negatively stained rod like structures within their cytoplasm. Zeihl Neelson stain revealed that these cells were heavily loaded with acid fast bacilli (AFB). In the index case, AFB were also seen within the cytoplasm of polymorphs, which has not been documented earlier in the literature.

To the Editor Bacillus Calmette Guerin (BCG) vaccine has been included in the immunization programmes of the developing countries including India. Immunization with BCG is done on the first day of life. The most common response to BCG vaccine is sub clinical. However, some infants may develop regional lymphadenitis or a subcutaneous abscess at the vaccination site [ 1 ]. Disseminated BCG infection usually presents as generalized lymphadenopathy, skin rash and hepatosplenomegaly [ 2 ]. There are only a few published studies on the cytological findings of BCG lymphadenitis [ 3 - 5 ]. In this letter we report the Fine needle aspiration cytology (FNAC) of BCG lymphadenitis clinically masquerading as Langerhans cell histiocytosis (LCH). This index case is from a two and a half month old male child, who presented with generalized lymphadenitis, skin rash and delay in developmental milestones. On examination, moderate hepatosplenomegaly was noted. The patient had been immunized properly for his age. The clinical possibility of LCH was strongly considered. On hematological examination, the counts were within normal limits. Fine needle aspiration was performed on a 3 cm, soft, left axillary lymph node. Thick pus was aspirated and the swelling reduced in size after aspiration. A part of the aspirated material was sent for mycobacterial (AFB) culture. May- Grunwald Geimsa (MGG), Hematoxylin and Eosin and Ziehl Neelson (ZN) stains were performed on the smears. Microscopically, sheets of foamy macrophages lying singly and in clusters were noted along with many polymorphs and nuclear debris in a dirty necrotic background. No epithelioid cell granulomas were seen. Many of the macrophages showed negatively stained (unstained) rod like structures within their cytoplasm (pseudo Gaucher cells). Similar structures were identified extracellularly, as well as within the polymorphs (Figure 1 ). Streaked cytoplasm was also noted. On Z-N staining, sheets of AFB positive bacilli were seen both intracellularly (in macrophages as well as polymorphs) as well as extracellularly. They corresponded with the negative shadows seen with MGG staining (Figure 2 ). The culture for mycobacteria was negative. The diagnosis of BCG lymphadenitis was offered and it was advised to further investigate the patient for immunodeficiency states. Later, a 1 cm right axillary lymph node was also aspirated. It revealed reactive hyperplasia microscopically but showed strong AFB positivity. Figure 1 Microphotograph showing many macrophages with negative shadows and polymorphs in a necrotic background (MGG X 1375). Figure 2 Microphotograph showing extensive load of acid fast bacilli both intracellularly (in macrophages as well as polymorphs) and extracellularly (Z-N Stain X 1375). Enlargement of regional lymph nodes is a well-known complication of BCG vaccination and occurs within 6 months of vaccination [ 3 ]. It may be suppurative or non-suppurative and smears show a combination of necrosis and epithelioid cell granulomas [ 3 - 5 ]. Acid-fast bacilli are demonstrable in nearly all the cases. Disseminated BCG infection can however, pose a diagnostic challenge to clinicians (as happened in the index case). The occurrence of systemic manifestations like skin rash and hepatosplenomegaly can closely mimics those of hematological malignancies. Smears from these cases show predominantly histiocytes in a background of polymorphs, and debris heavily loaded with AFB. In the index case, AFB were also seen within the cytoplasm of polymorphs, which has not been documented earlier in the literature. However, this observation could also be due to overlap of polymorphs by numerous extracellular organisms present in the background. This can definitely be commented upon only by electron microscopic examination, which was not carried out in this case. This might also be related to the type and extent of immunological deficiency in the patient. Moreover, the case was also deceptive from the clinical view point, as it closely mimicked LCH. As such, this case further reinforces the role of FNAC as a diagnostic modality.

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526779

International Network for the Availability of Scientific Publications: Facilitating Scientific Publishing in Developing Countries

The International Network for the Availability of Scientific Publications (INASP) was established in 1992 to bridge the information divide between the developed and developing world

‘The most important element that restricts our researchers is access to information.’—Subbiah Arunachalam, India, 2003 The International Network for the Availability of Scientific Publications (INASP) was established by the International Council for Science in 1992 to provide support for networking between information providers and users, particularly to bridge the information divide between the developed and developing world. Since 1992 INASP has worked, in response to requests, to develop its activities for capacity building in information production, access, and use, with an overarching vision that all people are able to access and contribute information, ideas, and knowledge necessary for sustainable and equitable development. To ensure that INASP activities are appropriate for the communities and cultures of the countries in which INASP works, local partners are used to build networks and to provide advice and support. Enhancing capacities is central to all activities, and local ownership and sensitivity to local conditions and opinions are of paramount importance. Here I highlight two aspects of our work: increasing access to information and supporting the visibility of regional journals within the global research community. Programme for the Enhancement of Research Information The growth and acceptability of the internet during the 1990s opened up tremendous possibilities for the dissemination of research information, providing many nations with access to information that had previously been out of their reach. Although internet connectivity remains problematic in many countries, it still offers great potential for bridging the information gap. Arising from discussions with librarians and researchers in 1999 and 2000, the Programme for the Enhancement of Research Information was formally launched in 2002 after a two-year pilot programme. The Programme for the Enhancement of Research Information works in a two-phase manner: (1) providing and supporting access to international research information and (2) supporting and promoting access to nationally published research. To support access to international information, INASP negotiates for heavily discounted or free access to online information from publishers and information providers in developed countries. Enabling access, however, does not guarantee that resources are used; both training and promotion are needed so that researchers and downstream information providers know how to make the best use of what is available. With this in mind, INASP has set up four series of training workshops, which have trained over 1,000 people from over 200 institutions in over 17 countries during the last two years. Although some of the training is undertaken by INASP staff, most is facilitated by in-country trainers. Planning for long-term sustainability, INASP aims to hand over the tasks of negotiation, purchasing, and training to local consortia, associations, or networks. African Journals OnLine Although much needed, access to international resources can discriminate against nationally published scholarly information. This may be due to one of the following: a perception that local publications are lower quality, distribution problems and irregular publishing, or lack of online visibility. However, national publications provide vital access to potential collaborators and information about research on topics of local relevance—since 1998, INASP has provided support to indigenous research publications to enable them to survive and coexist with international information. One specific project that exemplifies these aims is known as African Journals OnLine (AJOL). AJOL launched in 1998 in response to requests from African journals. Starting with only ten titles, it now includes 189 from 21 African countries. Access to the site, which includes tables of contents, article abstracts, and a homepage for each journal with information about editorial boards, guidelines for authors, and more, is entirely free. Participating journals report increased international submissions and increasing contact with international researchers. Researchers make wide use of this service, and over 8,000 people have registered to use AJOL since it launched. Registration is optional and until March this year did not provide the user any benefit—it simply provided an indication of the number of people visiting and from which countries. However, since March 2004 anyone who registers can sign up to receive a free E-mail table of contents alert. Over 500 people have chosen to receive E-mail alerts from an average of four journals each, and the effect of these alerts is felt through the increase in document delivery requests. AJOL does not currently host full text, but can provide full-text articles through a document delivery service (there are plans to load full-text articles on AJOL in the future). This service is provided to researchers from developing countries for free and to researchers elsewhere at a minimal charge (to cover costs, plus a small payment to the journal). In the first six months of 2004, over 700 articles were ordered and sent out. Most journals publishing out of Africa are not run by commercial publishers, and most of them operate at a loss, subsidised by universities, associations, funding agencies, or a mixture of all three. Paid subscriptions to print journals are frequently a vital part of their economics, and the financial viability of many journals is constantly under threat. Originally, it was hoped that AJOL would increase subscriptions, thereby providing greater financial security to the journals. This has not been achieved and is unlikely to occur in the future. However, with increasing visibility, the value of the journals increases along with, hopefully, their importance to the supporting agencies and long-term sustainability. Since AJOL is set up to provide support for the participating journals, the journals' opinions are constantly sought before any developments are undertaken, meaning AJOL is effectively “owned” by them. Although the service is not actively run by the journals themselves, all participating journals are considered to be part of a community, receiving regular E-mail contact and skills support. Many journal editors (who frequently undertake all the publishing activities) feel isolated and unskilled, and even though AJOL does not operate as an association for the journals, it encourages communication between the editors, and a sharing of experience. The AJOL website was relaunched in March 2004 using open-source software called Open Journal System, originally developed in Canada by the Public Knowledge Project at the University of British Columbia and further developed for AJOL at Bristol University, United Kingdom. This software was written to enable a single journal to manage the entire publishing process online from submission to publishing. Being open source, the software can also easily be adapted and modified. The Public Knowledge Project set up the system with the developing world in mind: it operates efficiently at low bandwidths and is easy to use, with many guides and help functions built in. For the users, this software offers sophisticated searching, E-mail alerts, and a space for each journal within AJOL for journal-specific information. It also now provides a range of management tools, which makes the service more efficient and enables it to grow. Another important consideration for choosing this system was that individual journals can take over the responsibility for maintaining their own journal areas within AJOL via the Internet. Over 50 journals have expressed an interest in taking this on, and one publisher is already successfully maintaining its material. To support this, training workshops are currently in preparation. This development will assist the long-term sustainability of AJOL and also give the participating journals experience in managing and publishing content online. In the near future, INASP will be including full text on AJOL and hopes to move the management of AJOL to an African organisation so that it will truly become an African gateway for published research. In addition, INASP continues to work with journals to strengthen their quality and sustainability, providing advice, training workshops, study tours, and a coordinating point for discussion and collaboration. Outside Africa, INASP is working on similar developments in Nepal and the Caribbean and has received expressions of interest from Bangladesh, Sri Lanka, and Vietnam. The Future of Journal Access It is vital that researchers everywhere in the world have access to reliable, relevant information. At the same time, providing access to international literature needs to be balanced with supporting local publications to ensure that indigenous knowledge is not lost, but can take its place in the research community and contribute to the continuing development of science. Worldwide access to information is central to all INASP activities, and INASP supports policies and activities that work towards this. Where to Find Out More INASP: http://www.inasp.info AJOL: http://www.ajol.info Public Knowledge Project: http://pkp.ubc.ca

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515370

Preserving Genome Integrity: The DdrA Protein of Deinococcus radiodurans R1

The bacterium Deinococcus radiodurans can withstand extraordinary levels of ionizing radiation, reflecting an equally extraordinary capacity for DNA repair. The hypothetical gene product DR0423 has been implicated in the recovery of this organism from DNA damage, indicating that this protein is a novel component of the D. radiodurans DNA repair system. DR0423 is a homologue of the eukaryotic Rad52 protein. Following exposure to ionizing radiation, DR0423 expression is induced relative to an untreated control, and strains carrying a deletion of the DR0423 gene exhibit increased sensitivity to ionizing radiation. When recovering from ionizing-radiation-induced DNA damage in the absence of nutrients, wild-type D. radiodurans reassembles its genome while the mutant lacking DR0423 function does not. In vitro, the purified DR0423 protein binds to single-stranded DNA with an apparent affinity for 3′ ends, and protects those ends from nuclease degradation. We propose that DR0423 is part of a DNA end-protection system that helps to preserve genome integrity following exposure to ionizing radiation. We designate the DR0423 protein as DNA damage response A protein.

Introduction Deinococcus radiodurans is a non-spore-forming bacterium notable for its capacity to tolerate exposure to ionizing radiation ( Battista and Rainey 2001 ). The D 37 dose for D. radiodurans R1 is approximately 6,500 Gy, at least 200-fold higher than the D 37 dose of Escherichia coli cultures irradiated under the same conditions. The energy deposited by 6,500-Gy γ radiation should introduce thousands of DNA lesions, including hundreds of double-stranded breaks ( Smith et al. 1992 ). The mechanisms responsible for this species' resilience are poorly described, and recent analyses of DNA-damage-induced changes in the proteome ( Lipton et al. 2002 ) and transcriptome ( Liu et al. 2003 ) of D. radiodurans cultures have done little to improve our understanding of D. radiodurans' radioresistance ( Edwards and Battista 2003 ; Narumi 2003 ). For most species, the intracellular generation of strand breaks has lethal consequences; exposed free ends serve as substrates for intracellular exonucleases that degrade the genome. However, in D. radiodurans the presence of strand breaks does not result in a catastrophic loss of genetic information ( Dean et al. 1966 ; Lett et al. 1967 ; Vukovic-Nagy et al. 1974 ). Instead, this species appears to have the ability to control DNA degradation postirradiation by synthesizing proteins that prevent extensive digestion of the genome, and it has been suggested that the DNA degradation observed in this species is an integral part of the process of DNA repair, generating single-stranded DNA that promotes homologous recombination and restitution of the damaged genome ( Battista et al. 1999 ). When D. radiodurans is exposed to a high dose of ionizing radiation, a number of genes are induced that lack readily identifiable homologues among known prokaryotic proteins ( Liu et al. 2003 ; Tanaka et al. 2004 ). Among these is the gene designated DR0423. This locus is one of the most highly induced genes in Deinococcus following γ-irradiation, with expression increasing 20- to 30-fold relative to an untreated control. Although originally annotated as a “hypothetical” protein ( White et al. 1999 ), a more detailed analysis ( Iyer et al. 2002 ) has identified an evolutionary relationship between DR0423p and the important eukaryotic recombination protein Rad52. Rad52 is part of a larger family of proteins exhibiting structural similarity but little sequence homology, including the prokaryotic Redβ, RecT, and Erf proteins ( Passy et al. 1999 ; Iyer et al. 2002 ). In this report, we provide evidence for a DNA end-protection system in D. radiodurans and characterize the DR0423 protein as a component of that system. Our studies suggest that DNA end protection might be particularly important to this species in the context of long-term survival during desiccation and recovery in a nutrient-poor environment. Results Transcripts Corresponding to the Coding Sequence Designated DR0423 Increase in Response to Sublethal Doses of Ionizing Radiation During the course of microarray studies intended to establish which R1 loci respond to ionizing radiation, it was noted that transcripts of DR0423 were among the mostly highly induced ( Tanaka et al. 2004 ). As an independent confirmation of these microarray results, the expression of this gene was monitored using quantitative real-time PCR. Total RNA was isolated from exponential-phase cultures of R1 immediately after and at 30 and 60 min following exposure to 3,000-Gy ionizing radiation. Changes in transcript abundance for the recA (DR2340), gap (DR1343), and DR0423 genes were determined as previously described ( Earl et al. 2002a ). The results of these analyses are listed in Table 1 . Consistent with previous results, levels of recA transcript increased postirradiation ( Narumi et al. 2001 ; Bonacossa de Almeida et al. 2002 ; Satoh et al. 2002 ), whereas gap induction remained unchanged ( Earl et al. 2002a ). The gap gene encodes glyceraldehyde 3-phosphate dehydrogenase and does not respond to DNA damage. Within one-half hour postirradiation, levels of DR0423 transcript increased 20- to 30-fold, suggesting that DR0423p may be a previously unrecognized component of the cell's defense against ionizing-radiation-induced damage. Table 1 Relative Expression of the ddrA , recA, and gap Genes of D. radiodurans R1 following Exposure to 3,000-Gy Ionizing Radiation Relative expression was determined before and after irradiation by calculating transcript abundance using quantitative RT-PCR. The numbers in this table are the ratio of transcript present postirradiation to that present preirradiation. Values are the means of ratios calculated from three independent experiments ( n = 6). The ranges of values obtained are included in parentheses adjacent to each mean. A value greater than one indicates an increase in expression in response to ionizing radiation Deletion of DR0423 Sensitizes D. radiodurans R1 to Ionizing Radiation and Mitomycin C The DR0423 gene was inactivated by deletion in D. radiodurans R1, as described elsewhere ( Funayama et al. 1999 ), and the resulting strain designated TNK104. Confirmation of the gene deletion is provided in Figure 1 . Deletion of DR0423 does not alter the growth rate of the culture (approximately 1.5-h doubling time), or decrease the efficiency of natural transformation (approximately 5 × 10 −5 rifampicin-resistant transformants per colony-forming unit ) relative to R1, indicating that DR0423p is not essential for the processes of DNA replication or homologous recombination. To establish whether DR0423p was necessary for DNA damage tolerance, TNK104 was evaluated for its ability to survive ionizing radiation and mitomycin C. Aliquots of exponential-phase cultures were exposed to these DNA-damaging agents. TNK104 exhibits increased sensitivity to both agents relative to the wild-type R1 strain ( Figure 2 ), but cultures only displayed significant ionizing radiation sensitivity at doses in excess of 5,000 Gy. Since expression of DR0423 increases in response to ionizing radiation, and its gene product contributes to the DNA damage resistance of this species, we have chosen to designate this gene as DNA damage response A (ddrA) . Figure 1 Verification of Gene Deletions (A) Verification of ddrA and recA gene deletions by PCR analysis. Purified PCR fragments were amplified from the genomic DNA of strains R1, TNK104, TNK106, and TNK110 using primers that flank the coding sequences for ddrA and recA. Products were separated on a 0.8% agarose gel to establish whether the fragment size corresponded to the gene-replacement cassette. The left panel depicts the replacement of ddrA in TNK104 and TNK110. The right panel depicts the replacement of recA in TNK106 and TNK110. Expected sizes of the wild-type and mutant sequences are given in the figure above each image of the agarose gel. (B) Verification of the ddrA gene deletion by restriction analysis of purified PCR products. Purified PCR fragments were amplified from the genomic DNA of strains R1, TNK104, and TNK110, using primers that flank the coding sequences for ddrA. Products were restricted with EcoR1 (left panel) and EcoRV (right panel) to verify their identity. Products were separated on a 0.8% agarose gel to establish whether the restriction fragment corresponded with the expected sizes as illustrated in the figure above each image of the agarose gel. (C) Verification of the recA gene deletion by restriction analysis of purified PCR products. Purified PCR fragments were amplified from the genomic DNA of strains R1, TNK106, and TNK110, using primers that flank the coding sequences for recA. Products were restricted with PvuII (left panel) and BglII (right panel) to verify their identity. Products were separated on a 0.8% agarose gel to establish whether the restriction fragment corresponded with expected sizes as illustrated in the figure above each gel. Figure 2 DNA Damage Sensitivity of D. radiodurans Cells Lacking DdrA Function (A) Representative survival curves for D. radiodurans strain TNK104 ΔddrA (squares) and D. radiodurans R1 (circles) following exposure to γ radiation. Survival of strains; values are the mean ± standard deviation of three independent experiments; n = 9. (B) Representative survival curves for D. radiodurans strain TNK104 ΔddrA (squares) and D. radiodurans R1 (circles) following exposure to mitomycin C. Values are the mean ± standard deviation of three independent experiments; n = 9. A ddrA recA Double Mutant Is More Sensitive to Ionizing Radiation Than Either Single Mutant The recA gene was deleted from R1 and TNK104 (see Figure 1 B and 1 C), resulting in strains TNK106 (ΔrecA) and TNK110 (ΔrecA, ΔddrA), respectively. Deinococcal strains lacking recA function are considered the most ionizing-radiation-sensitive strains described for this species ( Moseley and Copland 1975 ; Gutman et al. 1994 ). However, as indicated in Figure 3 , TNK110 is 3- to 5-fold more sensitive to ionizing radiation than the ΔrecA strain, indicating that DNA damage response A protein (DdrA), at least in part, contributes to D. radiodurans' survival by a mechanism that is independent of RecA function. Figure 3 DdrA Functions in a RecA-Independent DNA Repair Process Representative survival curves for D. radiodurans strains TNK106 ΔrecA (closed circles) and TNK110 ΔddrA ΔrecA (open triangles) following exposure to lower levels of γ radiation. All values are the mean ± standard deviation of three independent experiments; n = 9. Evidence That the DdrA Protein Contributes to Genome Restitution To determine if loss of DdrA affected genome restitution and stability postirradiation, we followed the recovery of cultures of R1 and TNK104 following a 5,000-Gy dose of γ radiation. Initially, exponential-phase cultures were harvested, suspended in 10 mM MgSO 4 , and irradiated. No carbon source was added. Restoration of the genome was monitored by pulsed-field gel electrophoresis, and aliquots retrieved from the recovering cultures were used to determine viability. Cultures were left in this medium and sampled at 24-h intervals over a 120-h time course. The gel depicted in Figure 4 illustrates the reassembly of the genomes of irradiated R1 cells. There are 11 NotI sites in the D. radiodurans genome, and when restricted, most of the resulting fragments can be separated by pulsed-field gel electrophoresis as seen in the lane (C) corresponding to the unirradiated control. Immediately after irradiation, the introduction of DNA double-stranded breaks results in the disappearance of the higher molecular weight NotI fragments, but the pattern of fragments is restored in 24–48 h, indicating that R1 is repairing double-stranded breaks under these conditions, in spite of the absence of nutrients. This pattern persists throughout the rest of the time course, indicating that once reformed the genome is stable. Despite genome restitution, R1 cultures held in MgSO 4 are not as proficient at recovering from ionizing-radiation-induced damage as cultures that are allowed to recover in rich medium ( Figure 4 ; data not shown). Even if plated immediately after exposure, R1 cultures suspended in MgSO 4 exhibit a modest 2-fold reduction in viability when exposed to 5,000-Gy γ radiation relative to R1 cultures irradiated in rich medium (see Figure 2 ). The longer the culture is held in MgSO 4 ( Figure 5 ), the greater the reduction in viability. After 120 h, approximately 10% of the irradiated R1 population remains viable. In comparison, 80% of an unirradiated exponential-phase population of R1 is viable when kept in 10 mM MgSO 4 for 5 d (data not shown). Figure 4 Genome Recovery in the Absence of Nutrients Depends on DdrA (A) Pulsed-field gel electrophoresis analyses of D. radiodurans strain RI recovery over a 120 h time course in 10 mM MgSO 4 following 5,000-Gy γ radiation. (B) Pulsed-field gel electrophoresis analyses of D. radiodurans strain TNK104 ( ΔddrA ) recovery following 5,000-Gy γ radiation. Figure 5 DdrA Protein Effects on In Vivo Survival and Genome Preservation following Exposure to Ionizing Radiation in the Absence of Nutrients (A) Survival of D. radiodurans R1 and TNK104 cultures held in 10 mM MgSO 4 for 120 h following exposure to 5,000-Gy γ radiation. Samples were obtained at 24-h intervals. All values are the mean ± standard deviation of three independent experiments; n = 9 (B) Changes in DNA content in cultures of R1 and TNK104 recovering from exposure to 5,000-Gy γ radiation in MgSO 4 . The DNA concentration at each time point is expressed as a percentage of that present in each strain prior to irradiation. Irradiated TNK104 cultures are significantly more vulnerable to ionizing radiation during a prolonged incubation in MgSO 4 ( Figure 5 A). TNK104 cultures exhibit only 0.1% survival after 120 h, a 100-fold reduction relative to identically treated R1 cultures. Also, in sharp contrast to the R1 cultures (see Figure 4 A), there is no evidence of genome reassembly in the TNK104 cells over this time course (see Figure 4 B), suggesting that failure to reassemble the genome contributes to the lower viability observed in TNK104 cultures. We directly examined the influence of DdrA on the fate of genomic DNA (see Figure 5 B) by monitoring changes in DNA content as the cultures of R1 and TNK104 recovered from exposure to 5,000 Gy in MgSO 4 . An aliquot of each unirradiated culture was isolated and total DNA concentration for 10 6 cfu calculated. Following irradiation, the DNA content of a volume corresponding to the original 10 6 cfu of each culture was determined. The DNA concentration at each time point in Figure 5 B is expressed as a percentage of that present in each strain prior to irradiation. Immediately after irradiation, the genomic DNA in the R1 culture was reduced by approximately 18%, a value consistent with previous findings ( Dean et al. 1966 ; Lett et al. 1967 ; Vukovic-Nagy et al. 1974 ) that indicate that 20%–25% of the genomic DNA of D. radiodurans will be degraded and expelled from the cell following exposure to 5,000-Gy γ radiation. In contrast, genomic DNA degradation in the strain lacking DdrA approached 55%. Thus, the presence of DdrA has a greater than 3-fold effect on the preservation of genomic DNA during early times after irradiation. In the succeeding 120 h, the R1 genomic DNA was reduced by a total of 31%, while the loss of genomic DNA increased to 64% in TNK104. These results suggest that DdrA has a direct effect on the preservation of genomic DNA following extreme insults. We also examined genome restitution in a rich medium (TGY broth). Consistent with the survival curve depicted in Figure 2 , we found that when TNK104 cells are exposed to 5,000 Gy their genomes reassemble with kinetics identical to those of the wild-type R1 culture ( Grimsley et al. 1991 ; Mattimore and Battista 1996 ); the genome reforms in less than 6 h (data not shown). Thus, DdrA appears to contribute to genome reconstruction in D. radiodurans following irradiation, but this role was only obvious in cultures suspended in MgSO 4 . There could be at least two explanations for this observation. First, the action of DdrA may overlap with the activity of at least one other protein, and while each redundant activity is functional in rich medium, only DdrA is functional in cultures held in MgSO 4 . Alternatively, the primary role of DdrA could be the passive protection of exposed 3′ DNA ends at the sites of DNA strand breaks. Under conditions with limiting nutrient availability, DdrA could contribute to genome restitution simply by preventing the massive genomic degradation evident in Figure 5 B. In a rich medium, active DNA repair may render DdrA-mediated DNA protection less important. The Purified DdrA Protein Binds the 3′ Ends of Single-Stranded DNA and Protects Them from Digestion by an Exonuclease The ddrA gene was cloned and expressed in E. coli, and the protein was purified to homogeneity ( Figure 6 ). The identity of the purified protein was confirmed by N-terminal sequencing and mass spectrometry. The deduced N-terminal sequence was MKLSDV, matching the predicted sequence of the first six amino acids perfectly (with the initiating methionine retained). The measured mass of the protein was 23,012.8 ± 3.46 Da, in good agreement with the 23,003.38 Da predicted. In two gel-filtration experiments using a Sephacryl S300 column calibrated with molecular weight standards, DdrA eluted as a sharp peak with an apparent mass in the two different trials of 218 and 190 kDa (data not shown). These results suggest that DdrA is an oligomer in solution with 8–10 subunits. Whereas these results are preliminary, Rad52 protein and other members of this family function as large oligomeric rings ( Passy et al. 1999 ; Iyer et al. 2002 ; Singleton et al. 2002 ) Figure 6 Purification of the DdrA Protein The first lane contains molecular weight markers. The second and third lanes contain crude extracts from E. coli strain pEAW298 (DdrA overproducer) in which the ddrA gene is uninduced or induced, respectively. The final lane contains purified DdrA protein. DdrA exhibited no ATPase, helicase, recombinase, or nuclease activity (data not shown). However, it bound to single-stranded DNA as determined by an electrophoretic mobility-shift assay (EMSA) ( Figure 7 ). Binding to duplex DNA depended on the presence of a 3′ single-stranded extension at one end ( Figure 7 ), indicating that the protein has some affinity for a free 3′ end in single-stranded DNA. This binding was not disrupted by a challenge with a 1,000- to 2,000-fold excess of a duplex oligonucleotide with a 5′ single-stranded extension ( Figure 7 ). Figure 7 DdrA Protein Binds to Single-Stranded DNA with Free 3′ Ends Four sets of EMSAs are presented, with the gels and electrophoresis conditions carefully matched. DNA substrate concentrations are 0.7 nM in each case, reported as total molecules. In each set, the first three lanes show the effects of the indicated concentration of DdrA protein. The fourth and fifth lanes are identical to the second and third lanes, respectively, except that they are treated with proteinase K to demonstrate that the DNA has not been altered. In set D, the sixth and seventh lanes are identical to the third lane (with 4 μM DdrA protein), except that they have been challenged with a 1,000-fold or 2,000-fold excess of unlabeled oligo with a 5′ extension, respectively. The unlabeled challenge oligo is the same as that used in reaction set C. (A) Single-stranded oligonucleotides (51 nt in length), labeled on the 5′ end. (B) 5′ end–labeled duplex DNA fragments (51 bp). (C) 5′ end–labeled oligonucleotide, with a self-complementary sequence leading to the formation of an 18-bp hairpin and a 15-nt 5′ single-stranded extension. (D) 3′ end–labeled oligonucleotide, with a self-complementary sequence leading to the formation of an 18-bp hairpin and a 16-nt 3′ single-stranded extension. The sequences of the single-stranded extensions in the oligos used in sets C and D are matched, except that an extra adenosine residue has been added to the oligo used in set D during the labeling process. Note that in set B, only the lower substrate band (unannealed oligonucleotides) is bound by DdrA, and the migration of the resulting complexes is identical to that shown in set A. DdrA also protected the single-stranded DNA from degradation by exonuclease I from E. coli, which digests single-stranded DNA from the 3′ end ( Figure 8 ). The DNA binding trials shown in Figure 8 A were scaled up, and the bound species was cut out of a preparative gel. The extracted protein comigrated with DdrA protein on a sodium dodecyl sulfate (SDS)-polyacrylamide gel ( Figure 8 B), providing further confidence that the binding is due to DdrA and not a minor contaminant in the DdrA protein preparation. These results suggest that D. radiodurans possesses a novel DNA end-protection system and that DdrA is a component of that system. Figure 8 DdrA Protein Protects 3′ Ends from Degradation by Exonuclease I (A) This set of reactions uses the labeled duplex DNA illustrated. The oligos annealed to form this DNA are 51 and 37 nt in length and pair so as to leave a 14-nt 3′ extension. The shorter DNA is 5′ end–labeled. The first lane contains unreacted DNA, showing both the annealed duplex and the unannealed single-stranded DNA. The second lane shows the DNA after treatment with 3 units of exonuclease I for 7 min in a 15-μl reaction mixture. Note that the duplex DNA in the upper band has been shortened by removal of the single-stranded extension. In lanes 3 and 4, the DdrA protein (4 μM) has been incubated with the DNA, without and with the 3 units of exonuclease I, respectively. The DNA is bound by DdrA and shifted to the top of the gel. The reactions shown in lanes 5 and 6 are identical to those in lanes 3 and 4, but with SDS and proteinase K added to disrupt the DdrA–DNA complexes and reveal that the DNA has been minimally affected by exonuclease I. The final lane shows another reaction of the DNA with 3 units of exonuclease I, in the presence of 4 μM bovine serum albumin. Exonuclease I degrades single-stranded DNA in the 3′ to 5′ direction. (B) The protein bound to the duplex DNA is DdrA. The reaction of lane 3 in (A) was scaled up and the protein–DNA complex excised from the gel as described in Materials and Methods . The protein in this complex was subjected to electrophoresis on an SDS-polyacrylamide gel, shown here (lane 3). The control lanes contained prestained protein standards (lane 1) and purified DdrA protein (lane 2). The gel-extracted protein comigrated with DdrA. The eukaryotic Rad52 protein has a single-stranded annealing activity that may be important to its in vivo function ( Mortensen et al. 1996 ; Sugiyama et al. 1998 ). We carried out several tests to determine if the DdrA protein had a similar annealing activity. In multiple trials using oligonucleotides of 30 and 51 nucleotides (nt) in length, no DNA strand annealing activity was detected over a range of DdrA concentrations and conditions (data not shown). Discussion The extraordinary resistance of D. radiodurans to DNA damage arose not as an adaptation to high levels of radiation, but rather as a response to desiccation ( Mattimore and Battista 1996 ). In an arid environment, dormant D. radiodurans cells would gradually accumulate DNA lesions of all kinds, including strand breaks. Since DNA repair is highly reliant on metabolic energy, and appropriate nutrients cannot be assured upon rehydration, it is not unreasonable to expect that this species possesses a means to efficiently repair accumulated damage that minimizes energy use. In this context, mechanisms must have evolved to maintain the genome and protect it from unnecessary degradation by nucleases and other agents. In this study we have identified functions associated with a “hypothetical” protein encoded by D. radiodurans R1 that contributes to this species' capacity to tolerate exposure to ionizing radiation and mitomycin C. We propose that the DR0423 protein, which we have designated DdrA, is part of a DNA end-protection system. Induced in response to the appearance of strand breaks generated by ionizing radiation (or subsequent to desiccation), DdrA would cap the strand breaks and help stabilize the genome until such time as conditions were more amenable to systematic DNA repair. The results we have obtained both in vivo and in vitro are consistent with this hypothesis. When the ddrA gene is deleted from R1, an otherwise wild-type cell becomes more sensitive to DNA-damaging agents (see Figure 2 ). We show that DdrA has at least two activities: DdrA contributes to genome restitution following irradiation (see Figure 4 ), and purified DdrA binds the 3′ ends of single-stranded DNA and protects those ends from digestion by exonucleases (see Figures 7 and 8 ). Notably, the effects of a ddrA deletion are amplified if nutrients are not provided after exposure to ionizing radiation, and cells held this way for 5 d display a 100-fold reduction in viability relative to the wild-type cells (see Figure 5 ). In these nutrient-poor conditions, cells lacking DdrA protein do not restore their chromosomes. Instead, the chromosomes are degraded extensively. Even though the R1 strain was able to restore its genome following irradiation and incubation in 10 mM MgSO 4 , there was no evidence of genome reassembly in similarly treated cultures of TNK104, the ΔddrA derivative of R1 (see Figure 4 ). This result indicates that DdrA plays a qualified role in genome restitution. Clearly the protein is necessary for this process in cells held in MgSO 4 , and we suggest that TNK104's inability to reconstitute its genome under these conditions is likely to be related to the DNA degradation that is observed in this strain following irradiation (see Figure 5 B). DdrA is not needed if cells are allowed to recover in a nutrient-rich medium (see Figure 2 ). This suggests that the function that DdrA mediates in genome restitution is either redundant or unnecessary when other repair processes are robust. If there is a protein with a redundant activity, it is evident only in rich medium. We do not know the identity of the redundant component, or understand why it is not functional in MgSO 4 . Since DdrA binds the 3′ ends of single-stranded DNA, we presume that this protein either has the same activity or is rendered unnecessary by a compensating activity possible only in a nutrient-rich environment (such as DNA synthesis to counter exonucleolytic degradation). If, instead, DdrA is part of a passive DNA protection system, this system may be critical under conditions in which active (energy-requiring) DNA repair is not possible, such as when cells are desiccated or held in a nutrient-free medium. DdrA may not be as important in a nutrient-rich environment, where active DNA synthesis and other DNA repair processes may compensate for the loss of DNA end protection. The increased sensitivity observed in TNK110 (ΔrecA ΔddrA) relative to TNK106 (ΔrecA) indicates that DdrA participates in a process that complements RecA-mediated survival mechanisms (see Figure 3 ), rescuing some irradiated cells even in the absence of RecA function. Since DdrA is distantly but specifically related to the Rad52 family of eukaryotic proteins, as well as a family of phage-associated proteins that mediate single-stranded annealing ( Iyer et al. 2002 ), we speculate that DdrA could be a component of a single-stranded annealing system that functions simultaneously with RecA-dependent homologous recombination. This possibility is consistent with an earlier report by Daly and Minton (1996) who documented RecA-independent genome restitution postirradiation. They reported that approximately 30% of the R1 genome is assembled in a recA background during the first 1.5 h after exposure, and they suggested that this process was single-stranded annealing. The DdrA protein could act directly or indirectly in any single-stranded annealing process that might occur in Deinococcus. Although the related Rad52 protein possesses a single-stranded annealing activity ( Mortensen et al. 1996 ; Sugiyama et al. 1998 ), we have thus far failed to detect such an activity with DdrA protein. One of three explanations seems likely: (i) we have not yet identified suitable conditions for the assay of DdrA-dependent DNA strand annealing; (ii) DdrA is part of a complex, and other proteins are needed to observe activity; or (iii) DdrA does not possess such an activity. DdrA's capacity to protect the 3′ ends of single-stranded DNA from digestion should help maintain the integrity of DNA fragments generated following DNA damage, whether those fragments are a result of the direct action of the damaging agent or arise as a consequence of a repair process that cleaves the phosphodiester backbone. By limiting degradation, proteins that protect DNA ends should enhance DNA damage tolerance and cell survival; the stabilized fragments serve as a long-lived substrate for homologous recombination or single-stranded annealing. In other words, we suspect that the ability to preserve genetic information is one key to understanding DdrA function and, in a larger context, the DNA damage tolerance of this species. DNA binding proteins, such as DdrA, may be particularly important for surviving desiccation. Like ionizing radiation, the process of desiccation is inherently DNA damaging, introducing large numbers of DNA double-stranded breaks. Following an extended period of desiccation, broken DNA ends would presumably need to be protected to minimize loss of genetic information. We know of no precedent for an activity of this sort in bacteria, although its existence has been predicted at least once ( Clark 1991 ). Bacteriophage are known to encode proteins (e.g., the gene 2 protein of T4 [ Wang et al. 2000 ]) that prevent exonucleolytic digestion of their genomes during infection, and given its sequence similarity to other phage proteins, it is possible that D. radiodurans acquired DdrA from a phage during its evolution. Since inactivation of DdrA reduces, but does not eliminate, the DNA damage resistance of Deinococcus, we suggest that other proteins with complementary functions, possibly designed to bind DNA ends with different structures, are also encoded by this species, and the protection provided by these proteins contributes significantly to DNA damage tolerance. By itself, DdrA protein does not enhance the radiation resistance of E. coli strains in which it has been expressed (L. Alice Simmons and J. Battista, unpublished data). It seems likely that D. radiodurans, and other bacteria with similar capacities to survive high DNA damage loads, employs multiple systems to repair its DNA. The DNA end-protection system we have begun to explore may be supplemented by special genome architectures ( Levin-Zaidman et al. 2003 ), traditional DNA repair systems (some with unusual properties [ Kim and Cox 2002 ]), and perhaps novel enzymatic systems not previously examined. Although we have detected no apparent enzymatic activities in DdrA to augment its DNA binding function, further work is needed to determine if DdrA contributes to single-stranded annealing or other potential DNA repair pathways. Bound to 3′ DNA ends, DdrA would be at a focus of DNA repair activity once genome restitution was initiated. The evolutionary relationship of DdrA to Rad52 may also telegraph a facilitating role in other DNA repair processes. Materials and Methods Strains, growth conditions, and treatment Strains and plasmids used in this study are described in Table 2 . All genes are identified as described in the published genome sequence ( http://www.tigr.org/tigr-scripts/CMR2/GenomePage3.spl?database=gdr ). All strains derived from D. radiodurans were grown at 30 °C in TGY broth (0.5% tryptone, 0.3% yeast extract, and 0.1% glucose) or on TGY agar (1.5% agar). E. coli strains were grown in Luria-Bertani (LB) broth or on LB plates at 37 °C. Plasmids were routinely propagated in E. coli strain DH5αMCR. D. radiodurans cultures were evaluated for their ability to survive exposure to DNA-damaging agents in exponential growth (OD600 = 0.08 − 0.15, 5 × 10 6 − 1 × 10 7 cfu/ml). All cultures were treated at 25 °C. Gamma irradiation was conducted using a model 484R 60 Co irradiator (J. L. Shepherd and Associates, San Fernando, California, United States) at a rate of 30 Gy/min. Resistance to mitomycin C was determined by adding 1 mg of mitomycin C (Sigma, St. Louis, Missouri, United States) to 1-ml broth cultures of the D. radiodurans strain. Aliquots of the treated culture were removed at one-half-hour intervals over the next 2 h, washed in 10 mM MgSO4, and plated on TGY agar to determine viability. Table 2 Strains and Plasmids Construction of TNK104, TNK106, and TNK110 The genes ddrA and recA were disrupted by targeted mutagenesis using techniques described previously ( Funayama et al. 1999 ). A deletion cassette was created for each locus and transformed into an exponential-phase D. radiodurans R1 culture. Recombinants were selected on TGY plates containing an appropriate antibiotic. Since D. radiodurans is multigenomic, individual colonies were screened to determine if they were homozygous for the disruption by isolating genomic DNA from putative recombinants and using a PCR-based analysis to determine whether the gene of interest had been deleted. Details for how each strain was generated are given below. The construction of TNK104 began with the creation of a drug cassette capable of conferring hygromycin resistance on D. radiodurans. The hygromycin B phosphotransferase gene (hyg) from pHP45omega-hyg ( Blondelet-Rouault et al. 1997 ) was spliced to the 120 bp of sequence immediately upstream of the initiation codon of the D. radiodurans katA gene (DR1998) ( Funayama et al. 1999 ), using primers whose sequences overlapped. Subsequently, the katA–hyg fusion product was joined to PCR fragments ( Horton et al. 1989 ) derived from the sequence 1.0 kbp immediately upstream and 0.9 kbp immediately downstream of ddrA . This hybrid fragment was cloned into pGEM-T (Promega, Madison, Wisconsin, United States), creating pTNK205. pTNK205 was propagated in E. coli DH5α-MCR. The deletion of ddrA was accomplished by transforming ( Earl et al. 2002b ) an exponential-phase R1 culture with linear pTNK205. Hygromycin-resistant recombinants were selected on TGY plates containing 37.5 μg/ml hygromycin. To confirm gene replacement, primers, which anneal outside the coding sequence of ddrA, were used to generate PCR fragments from genomic DNA from hygromycin-resistant colonies and R1. The purified PCR products were restricted with EcoRI and EcoRV. The hyg gene contains an EcoRI site, but ddrA does not. ddrA contains an EcoRV site, but hyg does not. In the recombinant, designated TNK104, a single 1.3-kbp fragment, corresponding to the katA–hyg cassette was amplified, whereas there was no trace of the 0.85-kbp fragment, indicative of ddrA amplification (see Figure 1 A). EcoRI cleaved the product amplified from TNK104 into 0.2-kbp and 1.1-kbp fragments, while the R1-derived product remained intact ( Figure 1 B). EcoRV digested the amplicon from R1 into fragments of 0.4 kbp and 0.45 kbp, but it did not affect the TNK104-derived product ( Figure 1 C). We conclude that TNK104 carries a deletion of the ddrA coding sequence marked by the katA–hyg cassette and that the strain is homozygous for the deletion. The recA deletion strain TNK106 was constructed in a manner similar to that of TNK104. Initially, the katA promoter of D. radiodurans was fused to the chloramphenicol acetyltransferase gene (cat) from pBC (Stratagene, La Jolla, California, United States). This drug cassette was then spliced to PCR products corresponding to genomic DNA sequences 1.6 kbp upstream and 1.2 kbp downstream of recA by overlap extension, before being cloned into pGEM-T. The resulting plasmid was designated pTNK210. An exponential-phase R1 culture was transformed with the replacement cassette from pTNK210, and chloramphenicol-resistant recombinants were selected on TGY plates containing 3 μg/ml chloramphenicol. Genomic DNA of each recombinant was amplified to determine if the recA coding region was deleted. Purified PCR products amplified using primers that anneal to sequences flanking recA were treated with PvuII and BglII. The cat gene carries a PvuII site, but recA does not. recA contains a BglII site, but cat does not. A 1.3-kbp fragment, corresponding to the katA–cat cassette, was obtained from a recombinant designated TNK106, but DNA from this recombinant did not generate the 1.5-kbp fragment corresponding to recA ( Figure 1 A). Amplifications of genomic DNA from R1 only produced the 1.5-kbp fragments ( Figure 1 A). The 1.3-kbp PCR product from TNK106 was cleaved by PvuII to 0.5-kbp and 0.8-kbp fragments, whereas the 1.5 kbp from R1 remained intact ( Figure 1 C). BglII cut the R1-derived 1.5 kbp to fragments of 0.45 kbp and 1.05 kbp, but not the product from TNK106 ( Figure 1 C). We conclude that recA has been replaced by katA–cat in TNK106 and that the strain is homozygous for this allele. TNK110 is a double mutant in which recA and ddrA are deleted. This strain was constructed by deleting recA from TNK104 using the protocol described for the creation of TNK106. The construct was verified by the scheme used to identify ddrA deletion in TNK104 and recA deletion in TNK106 (see Figures 1 A and 1 C). Pulsed-field gel electrophoresis After irradiation at 5.0 kGy, cells were collected by centrifugation (6,000 g, 15 min, 4 °C) and resuspended in either TGY broth or 10 mM MgSO4 solution, before being placed in a shaking incubator at 30 °C for 24 h. Aliquots of these cultures were removed at various time points, and cells were washed in 0.9% NaCl and suspended in 0.125 M EDTA (pH 8.0) at a density of 5 × 10 8 cells/ml. The suspensions were mixed with low-melting-point agarose (Sigma) to obtain a final concentration of 0.8% agarose. Agarose blocks containing the cell suspension were incubated overnight at 37 °C in 0.05 M EDTA (pH 7.5) containing 1 mg/ml of lysozyme. After lysozyme treatment, agarose plugs were placed in ESP buffer (EDTA 0.5 M [pH 9–9.5], 1% lauroyl sarcosine, 1 mg/ml proteinase K) at 50 °C for 6 h, followed by a 2-d incubation at 37 °C. Prior to digestion with restriction enzymes, agarose plugs were washed once with TE buffer (pH 7.5) containing 1 mM phenylmethylsulfonyl fluoride and then four times with TE buffer (pH 7.5). DNA contained within the agarose plugs was digested with 10 U of NotI restriction enzyme (New England Biolabs, Beverly, Massachusetts, United States) overnight at 37 °C. Restriction digests were analyzed on 1% agarose gels in 0.5X TBE, using a CHEF-MAPPER electrophoresis system (Bio-Rad, Hercules, California, United States) at 6 V/cm for 22 h at 12 °C, with a linear pulse ramp of 10–60 s and a switching angle of 120°. Gels were stained with water containing 0.5 μg/ml ethidium bromide for 20 min and destained for 10 min in water. Quantitative real-time PCR The protocol followed was the same as that described previously ( Earl et al. 2002a ). Total RNA was extracted from 1-l cultures of irradiated and nonirradiated exponential-phase D. radiodurans cultures using TRI Reagent (Molecular Research Center, Cincinnati, Ohio, United States) following manufacturer's instructions. Cell disruption was accomplished by adding 100 μ1 of 0.1-mm zirconia/silica beads (Biospec Products, Bartlesville, Oklahoma, United States) and TRI Reagent to the cell paste from 1 l of cells and vigorously agitating this mixture for 6 min with a vortex mixer. Two micrograms of each DNase I–treated, purified RNA sample was converted to cDNA using SUPERSCRIPT II RNase H − Reverse Transcriptase (Invitrogen, Carlsbad, California, United States) combined with 25 pmol of random hexamers to initiate synthesis. Conditions for this reaction followed the manufacturer's instructions. Approximately 100 bp of unique sequence from the genes encoding DdrA (DR0423), RecA (DR2340), and glyceraldehyde 3-phosphate dehydrogenase (DR1343) were amplified using the following primer sets: DR0423up (5′-GGTGCAGGACCGACTCGACGCCGTTTGCC-3′), DR0423down (5′-CCTCGCGGGTCACGCCGAGCACGGTCAGG-3′), DR2340up (5′-GTCAGCACCGGCAGCCTCAGCCTTGACCTC-3′), DR2340down (5′-GATGGCGAGGGCCAGGGTGGTCTTGC-3′), and DR1343up (5′-CTTCACCAGCCGCGAAGGGGCCTCCAAGC-3′), DR1343down (5′-GCCCAGCACGATGGAGAAGTCCTCGCC-3′). The PCR reaction (50 μ1) for amplifying these genes contained the appropriate primers at a final concentration of 0.2 μM, 1 μ1 of the cDNA template, and SYBR Green PCR Core Reagents (Applied Biosystems, Foster City, California, United States). Amplifications were carried out by incubating reactions at 95 °C for 3 min prior to 40 cycles of 30 s at 95 °C, followed by 30 s at 65 °C and 30 s at 72 °C. Data were collected and analyzed at each 72-°C interval. Each 96-well plate consisted of standard curves for each primer set run in duplicate. Standard curves were constructed using cDNA obtained from the unirradiated wild-type organism. A dilution series (1 to 1 × 10 −4 ) of each experimental sample was generated and run in duplicate. Negative controls without a cDNA template were run on every plate analyzed. All assays were performed using the iCycler iQ Real-Time Detection System (Bio-Rad). All data were PCR-baseline subtracted before threshold cycle values were designated and before standard curves were constructed. Mean concentrations of the transcripts in each sample were calculated from the standard curves generated using the recA primer set. Induction levels were determined by dividing the calculated concentration of transcript from the irradiated sample by the concentration of transcript from the unirradiated sample for each strain. The mean concentration of the gap transcript, a housekeeping gene whose expression is unaffected by ionizing radiation, was also determined before and after irradiation for each strain. DNA content measurement in TNK104 and R1 cells Overnight cultures growing in TGY medium were harvested at room temperature. Control culture aliquots were fixed with 1% toluene (final vol/vol), shaken vigorously, and stored at 4 °C. The fixed bacteria were diluted (1/10, 1/100, and 1/1,000) in 3 ml (final volume) of dilution buffer: 10 mM NaCl, 6.6 mM Na 2 SO 4 , 5 mM N′-2-hydroxyethylpiperazine-N′-2-ethanesulfonic acid (HEPES; pH 7.0). The remaining cultures were centrifuged for 20 min at 4 °C at 7,000 rpm. Bacterial pellets were washed twice and resuspended in 10 mM MgSO 4 for γ irradiation. Cell suspensions were irradiated at 5,000 Gy and incubated at 30 °C for 120 h. Aliquots were removed immediately following irradiation, at 48 h, and at 120 h postirradiation. Cells were toluene-fixed as described above; 100 μ1 of DAPI (stock solution 3 μg/ml) was added to each dilution tube and mixed. The fluorescence intensity was determined after excitation at 350 nm by measuring emission at 450 nm. Cloning, overexpression, and purification of DdrA The ddrA gene was amplified using the genomic DNA from D. radiodurans strain R1. PCR primers were designed according to the ddrA gene sequence annotated in the genomic bank ( http://www.ncbi.nlm.nih.gov ). The gene was cloned in E. coli overexpressing plasmid pEAW298. DdrA-overproducing cells were lysed with lysozyme, and the protein was precipitated from the supernatant by adding ammonium sulfate to 30% saturation. The protein was purified with DEAE and hydroxyapatite chromatography to greater than 99% purity. The identity of the purified protein was confirmed by N-terminal sequencing (Protein and Nucleic Acid Chemistry Laboratory, Washington University School of Medicine, St. Louis, Missouri, United States) and accurate mass determination (Biotech Center, University of Wisconsin, Madison, Wisconsin, United States). The protein was transferred into the storage buffer (20 mM Tris-acetate, 80% cation [pH 7.5]/50% glycerol [w/v], 0.5 M NaCl, 0.1 mM EDTA, and 1 mM DTT) and stored at −80 °C. Determination of the extinction coefficient for pure DdrA protein The extinction coefficient for DdrA protein was determined using a modification of a published procedure ( Marrione and Cox 1995 ). UV absorbance spectra were measured with a Cary 300 dual-beam spectrophotometer (Varian, Palo Alto, California, United States). The temperature was maintained using a circulating water bath. Cell-path length and bandwidth were 1 cm and 0.5 nm, respectively. The extinction coefficient for native DdrA protein was determined in the storage buffer, by comparing the absorbance spectra of the native protein to the absorbance spectra of the protein denatured in 6 M guanidine hydrochloride (Gnd–HCl) in storage buffer. The extinction coefficients at 280 nm of glycyl- L -tyrosylglycine and N -acetyl- L -tryptophanamide in 6 M GND–HCl are 1,280 M −1 cm −1 and 5,690 M −1 cm −1 , respectively ( Edelhoch 1948 ). In the DdrA protein there are five tyrosine, five tryptophan, and two cysteine residues in a protein with a total molecular mass of 23 kDa. Even if all cysteine residues were involved in disulfide bonds, the contribution of cystine to the absorbance of DdrA protein is predicted to be less than 1% and was neglected from our calculations. The extinction coefficient at 280 nm for denatured DdrA protein in ɛ denat, 280 nm = 5 × 5,690 + 5 × 1,280 = 3.485 × 10 4 M −1 cm −1 . Absorbance spectra of native and denatured (6 M GND–HCl) DdrA protein were scanned at 25 °C, from 320 to 240 nm, for five different dilutions and with two different protein preparations. DdrA protein was diluted in storage buffer or storage buffer plus 6 M GND–HCl (final concentration) in a total volume of 80 μ1 and was preincubated at 25 °C for 5 min before scanning. Each dilution was carried out in triplicate, and the absorbance values at 280 nm were averaged. The concentrations of native and denatured protein were equal to each other in each scan at each dilution. The extinction coefficient of native DdrA protein at 280 nm was determined according to the expression ( Gill and von Hippel 1989 ): ɛ nat, 280 nm = ɛ denat, 280 nm × Abs nat, 280 nm /Abs denat, 280 nm . We used five determinations with two different protein preparations, yielding an average extinction coefficient of ɛ nat, 280 nm = 2.8728 ± 0.1999 × 10 4 M −1 cm −1 in storage buffer at 25 °C. The A 280 /A 260 ratio for the native DdrA protein is 1.575 ± 0.00091. The error in both cases is 1 s.d. DNA binding assay The duplex oligonucleotide with a 3′ single-stranded extension was hairpin-forming oligonucleotide A (5′-TTA ACG ACC GTC GAC CTG CAG GTC GAC GGT CGT TAA CGT CTC TCA GAT TGT-3′), which was labeled at the 3′ terminus with [α- 32 P]ddATP, using terminal transferase. After labeling, hairpin formation generated an 18-bp duplex hairpin with a 16-nt 3′ extension. The duplex oligonucleotide with a 5′ single-stranded extension was hairpin-forming oligonucleotide B (5′-CGT CTC TCA GAT TGT TTA ACG ACC GTC GAC CTG CAG GTC GAC GGT CGT TAA-3′). The oligo was labeled at the 5′ end using [γ- 32 P] ATP and polynucleotide kinase. After labeling, hairpin formation generated a DNA with 18 bp in the hairpin duplex and a 15-nt 5′ extension. A blunt-ended duplex DNA fragment was prepared by annealing oligonucleotide C (5′-GGT CTT TCA AAT TGT TTA AGG AAG AAA CTA ATG CTA GCC ACG GTC CGA GCC-3′) 32 P-labeled at its 5′ end, with unlabeled oligonucleotide D (5′-GGC TCG GAC CGT GGC TAG CAT TAG TTT CTT CCT TAA ACA ATT TGA AAG ACC-3′). The single-stranded oligonucleotide was the end-labeled oligo C. EMSAs for DNA binding were carried out in 15-μl reaction mixtures containing the reaction buffer (40 mM Tris-acetate [pH 7.5],10% glycerol [w/v], 0.1 M NaCl, 0.1 mM EDTA, 1 mM DTT) and 0.7 nM (60 nM nt) 32 P-labeled duplex DNA. The reaction was initiated by adding the DdrA protein to the required concentration. The reaction mixture was incubated at 30 °C for 30 min and loaded onto a 10% native polyacrylamide gel. The electrophoresis was performed in 1X TBE (89 mM Tris-borate [pH8.3], 2 mM EDTA) at room temperature. After the electrophoresis was completed, the gel was dried and exposed with a Phosphoimager (Molecular Dynamics, Sunnyvale, California, United States). Identification of DdrA protein in DNA–protein complex The general strategy of this experiment was to incubate a DNA duplex with a 3′ extension with DdrA protein, resolve the protein complex in native PAGE, excise the complex from the gel, extract the protein from the slice, and analyze the protein in SDS-PAGE. If the protein is DdrA, it will comigrate with DdrA protein in SDS-PAGE. A 32 P-labeled oligonucleotide (30 nt; 5′-GTG CGC TCC GAG CTC AGC TAC CGC GAG GCC-3′) was annealed with a longer unlabeled oligonucleotide (50 nt; 5′-GGC CTC GCG GTA GCT GAG CTC GGA GCG CAC GAT TCG CAC TGC TGA TGT TC-3′). Annealing was carried out in a 40-μ1 solution containing 0.5 μM of each oligonucleotide in 25 mM Tris HCl (pH 8), 50 mM NaCl, and 12.5 mM MgC1 2 . The solution was heated briefly at 100 °C, by transferring the closed tube to a beaker of boiling water, and allowed to cool slowly overnight. The tube was refrigerated for several hours and then stored at −20 °C until use. The resulting labeled duplex DNA with a 3′ extension (0.7 nM) was incubated with 4 μM DdrA protein under the DNA binding conditions described above. The mixture was loaded onto a 10% native polyacrylamide gel. Electrophoresis was performed as described above. The gel was exposed with X-ray film to map the position of the protein–duplex complex. The complex was cut out of the gel. The gel slice was frozen in liquid nitrogen and crushed into a slurry with a plastic stick. The slurry was mixed with an equal volume of SDS-PAGE loading buffer and boiled for 3 min. The mixture was loaded onto a 12% SDS-PAGE gel and the protein present compared to molecular weight standards and purified DdrA protein. Exonuclease assay The duplex with a 3′ extension was prepared by annealing oligonucleotide A (5′-CTA GCA TTA GTT TCT TCC TTA AAC AAT TTG AAA GAC C-3′), which was labeled at the 5′ terminus with [γ- 32 P]ATP, and cold oligonucleotide B (5′-GGT CTT TCA AAT TGT TTA AGG AAG AAA CTA ATG CTA GCC ACG GTC CGA GCC-3′). The annealing generated a 14-nt 3′ extension at one end of the short duplex. Before adding the exonuclease, the 32 P-labeled duplex (60 nM nt) was preincubated with the DdrA protein at the indicated concentration in 15 μl of the exonuclease reaction buffer (40 mM Tris-acetate [pH 7.5], 0.1 M NaCl, 10 mM MgC12, 0.1 mM EDTA, 1 mM DTT, 10% glycerol) at room temperature for 10 min. In the control experiment, the DdrA protein was replaced with bovine serum albumin. Exonuclease I was added to 200 U/ml and the reaction mixture was incubated at 37 °C for 30 min. After the incubation was complete, the reactions 5 and 6 were deproteinized with 0.2% SDS and 0.2 mg/ml proteinase K at 37 °C for 15 min. The DNA–protein complexes were resolved in the native polyacrylamide gel as above. Supporting Information Accession Numbers The GenBank ( http://www.ncbi.nlm.nih.gov/Genbank/index.html ) accession numbers for the genes and gene products discussed in this paper are ddrA /DR0423 (NP_294146), Erf (P04892), gap/ DR1343 (NP_295066), Rad52 (P06778), recA/ DR2340 (NP_296061), RecT (P33228), and Redβ (P03698).

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340937

Immune Activation and CD8+ T-Cell Differentiation towards Senescence in HIV-1 Infection

Progress in the fight against the HIV/AIDS epidemic is hindered by our failure to elucidate the precise reasons for the onset of immunodeficiency in HIV-1 infection. Increasing evidence suggests that elevated immune activation is associated with poor outcome in HIV-1 pathogenesis. However, the basis of this association remains unclear. Through ex vivo analysis of virus-specific CD8 + T-cells and the use of an in vitro model of naïve CD8 + T-cell priming, we show that the activation level and the differentiation state of T-cells are closely related. Acute HIV-1 infection induces massive activation of CD8 + T-cells, affecting many cell populations, not only those specific for HIV-1, which results in further differentiation of these cells. HIV disease progression correlates with increased proportions of highly differentiated CD8 + T-cells, which exhibit characteristics of replicative senescence and probably indicate a decline in T-cell competence of the infected person. The differentiation of CD8 + and CD4 + T-cells towards a state of replicative senescence is a natural process. It can be driven by excessive levels of immune stimulation. This may be part of the mechanism through which HIV-1-mediated immune activation exhausts the capacity of the immune system.

Introduction During primary human immunodeficiency virus 1 (HIV-1) infection, the immune system appears to respond appropriately in order to prevent viral spread, with the mounting of a strong HIV-specific CD8 + T-cell response and a corresponding reduction in viraemia ( Koup et al. 1994 ). In common with the majority of persistent viruses, HIV has developed a number of strategies to evade host immunity ( Alcami and Koszinowski 2000 ). Continuous adaptive mutation ( Borrow et al. 1997 ) and destruction or impairment of elements necessary for an optimal immune response (e.g., CD4 + T-cells and antigen-presenting cells) ( Kalams and Walker 1998 ) may explain the failure of antiviral immunity to eradicate the virus. However, unlike most other persistent viruses, HIV-1 progressively destroys the immune system, resulting in acquired immunodeficiency syndrome (AIDS) and death. The precise mechanisms by which immune function is lost remain the subject of considerable controversy. In addition to elevated T-cell turnover and an increase in the proportion of highly differentiated antigen-experienced CD8 + and CD4 + T-cells during HIV infection ( Wolthers et al. 1996b ; Appay et al. 2002c ), HIV-infected individuals are characterised by decreased thymic output ( Douek et al. 1998 ) and reduced naïve T-cell numbers ( Roederer et al. 1995 ; Hellerstein et al. 1999 , Hellerstein et al. 2003 ), which reflect a diminished capacity to renew the pool of T-cells. Increasing evidence suggests an association between high levels of immune activation and poor outcome in HIV-infected individuals ( Giorgi et al. 1993 ; Hazenberg et al. 2000a , Hazenberg et al. 2003 ; Grossman et al. 2002 ; Sousa et al. 2002 ), although the underlying mechanism remains unclear. This is supported by studies of sooty mangabeys and African green monkeys, the natural hosts of simian immunodeficiency virus (SIV), which survive SIV infection and are characterised by low immune activation, in striking contrast to rhesus macaques, for which SIV infection is fatal ( Kaur et al. 1998 ; Broussard et al. 2001 ; Silvestri et al. 2003 ). To gain further insights into the mechanisms involved, we have studied the potential interplay among immune activation, CD8 + T-cell differentiation, and outcome in the context of HIV-1 pathogenesis. We report here that T-cell activation and differentiation are closely related, and that HIV-1 induces immune activation directly and indirectly, which results in differentiation of CD8 + T-cells towards replicative senescence. Results HIV-Infected Subjects Our study involved the analysis of two distinct groups of HIV-1-infected individuals. On one hand, we performed a longitudinal analysis of T-cell subsets during acute HIV-1 infection and its resolution. To examine the effect on T-cells of elevated immune activation associated with an episode of vigourous HIV replication (particularly evident at time of high HIV-1 viraemia, such as the acute infection phase), T-cells were studied in individuals during HIV acute infection and later on—postacute—when viral replication was suppressed following the start of antiretroviral therapy (ART) ( Table 1 ). These donors were diagnosed at an early stage of primary infection: before or at the time of HIV-1 seroconversion. On the other hand, we carried out a cross-sectional study of HIV-infected untreated individuals at different stages of infection, to draw a correlation between their T-cell characteristics and clinical status. For this purpose, untreated HIV-infected donors were classified into three different groups: acute infection, chronic infection with no sign of progression (infected for more than 10 y with a CD4 + count above 500 per milliliter and mean viral load of 10 4 copies/ml), and chronic infection with signs of disease progression (with decreasing CD4 + count, 500 < x < 130 per milliliter, and mean viral load of 7 × 10 4 copies/ml). In addition to analysing whole CD8 + T-cell populations in these individuals, we have used a panel of tetramers to study the phenotypic evolution of CD8 + T-cells specific for HIV, cytomegalovirus (CMV), Epstein–Barr virus (EBV), and influenza. Although this approach focuses on a limited number of viral epitopes (restricted by the number of tetramers available), it remains the only way to avoid stimulation of the cells in order to detect them (e.g., by interferon-γ [IFN-γ] secretion), which may alter cellular phenotype and does not enable the detection of all cells. Table 1 Clinical Characteristics and Percentages of Activated HIV-Nonspecific CD8 + T-Cells in Donors Studied during Both Acute and Postacute HIV-1 Infection Stages a Sampled during the influenza season and low-positive titers for complement fixation antibody assays to both influenza A and influenza B (although these titers did not vary significantly after the first timepoint) Direct and Indirect T-Cell Activation during Acute HIV-1 Infection CD38 was used as a marker of activation; cells expressing high levels of CD38 ( Appay et al. 2002b ) were considered as being activated. During acute HIV-1 infection, HIV-specific CD8 + T-cells were strongly activated, and, intriguingly, activation of the CD8 + T-cell compartment as a whole was particularly high, reaching to levels of 80%–90%, in contrast to CD4 + T-cells, which show much less activation ( Figure 1 A). In order to shed light on the elevated level of activation experienced by the CD8 + T-cell population, we examined which CD8 + T-cell subsets were activated and whether all activated cells were HIV-specific. Naïve cells exhibited a slight increase in Ki67 (proliferation marker) expression during acute infection ( p = 0.03), in keeping with activation-related proliferation of this subset, as previously described ( Hazenberg et al. 2000b ). However, little or no difference in activation levels CD38 + between acute and postacute infection stages was observed within the naïve CD8 + T-cell subset (CD62L + /CD45RA + ) and antigen-experienced CD45RA + (quiescent [ Dunne et al. 2002 ; van Leeuwen et al. 2002 ]) CD8 + T-cells, in contrast to the rest of antigen-experienced CD8 + T-cells ( Figure 1 B). This indicates that most activated CD8 + T-cells are or have become antigen-experienced. According to the expression of the costimulatory receptors CD28 and CD27, antigen-experienced CD8 + T-cells can be positioned along a putative linear model of differentiation or post-thymic development: early (CD28 + /CD27 + ), intermediate (CD28 − /CD27 + ), and late (CD28 − /CD27 − ) differentiated subsets ( Appay et al. 2002a ). While both CD28 + /CD27 + and CD28 − /CD27 + T-cell subsets expressed high levels of CD38 and Ki67 during acute infection, CD28 − /CD27 − T-cells exhibited little activation and proliferation despite increased proportions of these cells following acute infection ( Figure 1 C), suggesting the differentiation into this subset of earlier differentiated cells following activation. Figure 1 CD8 + T-Cell Activation during Acute HIV-1 Infection (A) Percentages of activated CD38 + cells (gated on whole CD8 + T-cells, HIV tetramer-positive CD8 + T-cells, or whole CD4 + T-cells) in donors during acute HIV-1 infection and later postacute on ART ( n = 12); healthy donors ( n = 11) and untreated donors with nonprogressing chronic infection ( n = 12) are also shown. (B and C) CD38 and Ki67 expression on CD8 + T-cell subsets defined by CD45RA/CD62L (B) or CD28/CD27 (C) expression, shown in one single donor from acute to postacute (on ART) HIV-1 infection. Percentages of positive cells are shown. Means (± SEM) of CD38 + and Ki67 + CD8 + T-cells for ten patients are also shown; statistics concern CD38 expression. (D) Staining for the activation marker CD38 on CMV-, EBV-, or influenza A virus-specific CD8 + T-cells during acute and postacute (on ART) HIV-1 infection in a single donor. Percentages of CD38 + tetramer-positive CD8 + T-cells are shown. Data on all donors (see Table 1 ) are also shown. (E) Activation (CD38 and Ki67 staining) of CMV-specific CD8 + T-cells or whole CD8 + T-cell population during acute and postacute (on ART) HIV-1 infection in a single donor. Percentages of cells present in quadrants are shown. Statistics: * p < 0.002, ** p < 0.01, NS = nonsignificant, with the nonparametric Mann–Whitney test. Surprisingly, from the analysis of CD8 + T-cells specific for non-HIV viral antigens in donors with suitable human leukocyte antigen (HLA) type (HLA-A*0201 for CMV, EBV, and influenza A virus; HLA-B*0701 for CMV; and HLA-B*0801 for EBV), both CMV- and EBV-specific CD8 + T-cells displayed significant levels of activation exclusively during acute HIV infection, compared to chronic infection ( p < 0.002) ( Figure 1 D; see Table 1 ). Activated cells specific for non-HIV viral antigens also participated in the expansion of the CD8 + T-cell population observed in HIV primary infection, as shown by expression of the proliferation marker Ki67 ( Figure 1 E). Plasma DNA levels of CMV and EBV in these study subjects were below detection limits of the assays and thus did not provide evidence of high levels (greater than 400 genomes per milliliter) of systemic reactivation (data not shown). However, the observation of nonactivated influenza A virus-specific CD8 + T-cells ( Figure 1 D), in contrast to CMV- or EBV-specific CD8 + T-cells ( p < 0.01), strongly suggests that the stimulation of these cells associated with HIV-1 infection is due to reactivation of pathogens such as CMV and EBV, rather than as a result of bystander activation. Overall, these data show that HIV-1 infection leads to activation of antigen-experienced CD8 + T-cells at early stages of differentiation, both in direct (HIV-specific) and indirect (HIV-nonspecific) manners. Activation-Induced T-Cell Differentiation The potential relationship between T-cell activation and differentiation was first studied using a system of in vitro priming of naïve CD8 + T-cells by dendritic cells (DCs), which represents a useful model to analyse the generation of antigen-experienced CD8 + T-cells. This system is based on the existence in normal human donors of a significant number of naive CD8 + T-cells (reactive for the HLA-A2-restricted melan-A antigen [ Dutoit et al. 2002 ; Zippelius et al. 2002 ]), which can be primed by autologous matured DCs loaded with specific peptides to become antigen-experienced cells ( Salio et al. 2001 ). Although we cannot with certainty extend our interpretation of data from this assay system beyond the in vitro conditions (i.e., signals involved in T-cell differentiation, apoptosis, or both, as well as homeostatic signals, may be absent or differ from the in vivo situation), this system represents a unique opportunity to study the priming of naïve CD8 + T-cells using human material. We used a range of concentrations of the melan-A antigen loaded onto professional antigen-presenting cells to generate different levels of stimulation. Mature DCs do not persist very long in culture (2–3 d); moreover, the half-life of class I MHC–peptide complexes on mature DCs is rather short ( Cella et al. 1999 ); therefore, the results reflect increasing antigen doses from a single round of antigen exposure. We observed a close relationship between the level of stimulation induced and the size of the resulting antigen-specific CD8 + T-cell population ( Figure 2 A). This relationship was steady, as maintained over time, following priming of naïve cells and following a second round of stimulation of the antigen-experienced cells with antigen-loaded matured DCs ( Figure 2 B). The priming of naïve cells (granzyme A-negative) was successfully initiated at all antigen concentrations, as shown by the expression of the cytotoxic factor granzyme A in all melan-A-specific CD8 + T cells ( Figure 2 C). Increasing concentrations of antigen were associated with increasing activation levels and proliferation, indicated by increased expression of Ki67 and declining expression of CD62L ( Figure 2 C). The analysis of the differentiation phenotype (based on CD28 and CD27 expression) throughout the priming of the cells provided in vitro confirmation of the hypothetical model of CD8 + T-cell differentiation observed ex vivo ( Hamann et al. 1999 ; Appay et al. 2002a ): starting from a population with naïve characteristics (CD28 + /CD27 + /CD62L + /CD45RA + /granzyme A − ) at day 0 (data not shown), antigen-primed cells lost sequentially expression of CD28 and CD27 ( Figure 2 D). Following priming, the differentiation phenotype of the melan-A-specific CD8 + T-cells varied according to the level of stimulation induced, with high antigen load resulting in further differentiation of the cells ( Figure 2 E). These data show that there is a close correlation among the level of activation, size, and differentiation of the antigen-specific CD8 + T-cells. Figure 2 In Vitro Priming of Antigen-Specific CD8 + T-Cells (A) Representative stainings for melan-A-specific CD8 + T-cells following priming of naïve cells from healthy donor PBMCs by autologous mature DCs loaded with various concentrations of antigen. Cells are gated on lymphocytes 47 d after priming. Percentages of melan-A tetramer-positive CD8 + T-cells are shown. (B) Percentages of melan-A-specific CD8 + T-cells over time following priming at day 0 with mature DCs loaded with various concentrations of antigen, with no restimulation or with restimulation using mature DCs at day 25. The legend indicates the concentration of melan-A–peptide used in microgram per milliliter; populations generated with 0 or 10 −3 μg/ml of antigen are plotted on the right-hand side Y axis. (C) Percentages of melan-A tetramer-positive CD8 + T-cells expressing granzyme A, Ki67, CD62L, or CD57 according to antigen concentration used, at day 30 following priming. Ki67 and CD57 expressions are plotted on the right-hand side Y axis. (D) CD28 and CD27 expression on melan-A tetramer-positive CD8 + T-cells in PBMC (day 0), and over time following priming with 1 μg/ml of antigen. Percentages of cells present in quadrants are shown. The model of CD8 + T-cell differentiation based on CD28 and CD27 expression is illustrated (top left panel). (E) Distribution of the melan-A-specific CD8 + T-cells into the distinct differentiated subsets according to antigen concentration used, at day 47 following priming. Similar observations were made whether the cells were subjected to a second round of stimulation or not. Data are representative of three independent experiments. This relationship was confirmed by ex vivo analysis of antigen-experienced CD8 + T-cells. Despite that the majority of HIV-specific CD8 + T-cells are usually found at an intermediate stage of differentiation ( Appay et al. 2002a ), certain of these populations exhibit a significant percentage of late-differentiated CD8 + T-cells, as exemplified by the analysis of three HIV-1-specific CD8 + T-cell populations in a single individual ( Figure 3 A). The examination of the differentiation state (percentage of CD27 − in the tetramer-positive cells) and the size (percentage of tetramer-positive cells in the whole CD8 population) of a variety of HIV-specific CD8 + T-cell populations in several donors revealed a correlation between these two parameters ( Figure 3 B). A similar correlation was also found in the case of CMV-specific populations (although these cells are usually more differentiated, as previously described [ Appay et al. 2002a ]), as well as in EBV- and influenza-specific CD8 + T-cells. The correlation between differentiation and population size becomes highly significant when data on all specificities are combined. Following acute HIV infection and related strong activation, HIV-specific CD8 + T-cells displayed increased percentages of CD28 − /CD27 − cells (especially with larger populations) ( Figure 3 C; Figure 4 B). The differentiation phenotype of non-HIV-specific CD8 + T-cells could also vary from acute to postacute HIV infection stages in relation to activation: while the differentiation phenotype of influenza A virus-specific cells remained unchanged, CMV- and (although less frequently) EBV-specific CD8 + T-cells became further differentiated ( Figure 3 D; Figure 4 B). This is in keeping with a recent report, which shows increased differentiation of EBV-specific CD8 + T-cells during HIV-1 infection ( van Baarle et al. 2002a ). Taken together, these data indicate that the immune activation induced in the context of HIV-1 infection can result in the differentiation of T-cells specific for HIV-1 as well as other pathogens such as CMV and EBV, which may explain the increase in the proportions of highly differentiated cells observed during HIV-1 infection. Figure 3 Activation and Differentiation of Antigen-Specific CD8 + T-Cells during HIV-1 Infection (A) Representative staining for the differentiation marker CD27 on three HIV-specific (HLA-B8 nef, HLA-A2 p17, and HLA-B8 p24) populations in a single HIV-1-infected donor. Numbers show percentages of tetramer-positive CD8 + T-cells (outside the quadrants) and percentages of CD27 − tetramer-positive cells (inside the quadrants). (B) Correlation between size (percentage of tetramer-positive CD8 + T-cells) and differentiation (percentages of CD27 − tetramer-positive cells) of CD8 + T-cells specific for HIV antigens (including HLA-A2 p17, pol, HLA-B7 nef, gp41, HLA-B8 nef, p24, and HLA-B57 p24) (open circles), CMV antigens (including HLA-A2, B7, and B35 pp65) (filled circles), EBV (HLA-A2 BMLF1, HLA-B8 BZLF1, EBNA3A) (filled squares), and influenza (HLA-A2 matrix) (open squares) antigens or all antigens together. These populations were studied in individuals with chronic infection for HIV, CMV, or EBV (independently from clinical status). P values were obtained using the nonparametric Spearman rank correlation test. (C) CD28 and CD27 expression on whole, HIV nef-, or p24-specific CD8 + T-cells during acute and postacute (on ART) HIV-1 infection in a single donor. (D) CD28 and CD27 expression on CMV-, EBV-, or influenza-specific CD8 + T-cells during acute and postacute (on ART) HIV-1 infection in a single donor. Percentages of cells present in quadrants are shown. Figure 4 CD8 + T-Cell Differentiation and HIV-1 Disease Progression (A) Distribution of the CD8 + T-cell population in differentiated subsets (CD28 + /CD27 + early, CD28 − /CD27 + intermediate, and CD28 − /CD27 − late) through the course of HIV-1 infection. Abbreviations: H, healthy ( n = 15); A, acute HIV infection ( n = 11); C, chronic HIV infection nonprogressor (no ART; n = 14); P, chronic HIV infection with signs of disease progression (no ART; n = 10). Statistics: * p < 0.0001 with the ANOVA test and p < 0.005 between each group. (B) Percentages of CD27 − CD8 + T-cells that are specific for HLA-B8 HIV (nef) or HLA-A2 CMV in HIV-1-infected individuals at different stages of infection. Statistics: ** p < 0.005 with the nonparametric Mann–Whitney test. (C) Inverse correlation between CD4 + T-cell counts and percentage of highly differentiated CD27 − cells in the whole CD8 + T-cell population of HIV-1-infected donors during chronic infection (untreated nonprogressors and progressors). The p value was obtained using the nonparametric Spearman rank correlation test. Increased T-Cell Differentiation with Progression to AIDS Persistent and continuous replication is a hallmark of HIV-1 infection, along with chronic activation and constant turnover of T-cells, and these factors are now thought of as playing a critical role in HIV pathogenesis and disease progression ( Giorgi et al. 1993 ; Hazenberg et al. 2000a ; Grossman et al. 2002 ; Hellerstein et al. 2003 ). The detailed distribution of the CD8 + T-cell population along the pathway of differentiation during HIV-1 infection was analysed in a cross-sectional study of individuals at different stages of infection. It revealed an increase in the proportion of highly differentiated CD8 + T-cells associated with HIV disease progression ( Figure 4 A). Increased proportions of CD28 − /CD27 + CD8 + T-cells during acute HIV-1 infection are likely to reflect expansion of HIV-specific CD8 + T-cells. The enrichment in highly differentiated CD8 + T-cells from acute infection onwards included virus-specific cells, as exemplified by the analysis of populations specific for one HIV epitope or one CMV epitope ( Figure 4 B). The study of individuals during chronic infection (including nonprogressors and donors with evidence of disease progression, both untreated) revealed an inverse correlation between the overall percentage of highly differentiated cells and CD4 + T-cell count, as an indicator of disease progression ( Figure 4 C). No significant correlation emerged between the differentiation state of virus-specific CD8 + T-cell populations and CD4 + T-cell count; a larger number of virus-specific CD8 + T-cell populations studied may be required. A problem with the interpretation of increased numbers of highly differentiated T-cells relates to the controversy around the significance of these cells. Some investigators regard these cells as the effector-type population, conferring optimum protective immunity ( van Baarle et al. 2002b ; Zhang et al. 2003 ), but for others, these cells have lost their capacity to proliferate and their incidence may reflect ageing of the lymphocyte population ( Effros et al. 1996 ; Globerson and Effros 2000 ; Appay and Rowland-Jones 2002b ). Replicative Senescence and Increased T-Cell Differentiation As CD8 + T-cells differentiate further, they express increasing levels of CD57 ( Figure 5 A), a marker that has recently been associated with a state of replicative senescence ( Brenchley et al. 2003 ). This is in line with the observation of increased CD57 expression on CD8 + T cells following acute HIV infection, including cells specific for HIV, as well as other specificities, such as CMV- and EBV-specific cells ( Figure 5 B). Increased CD57 expression in association with further T-cell differentiation was also seen following priming of T-cells in vitro (see Figure 2 C), although this remained relatively modest (below 10%), possibly due to the high susceptibility to activation induced cells death of CD57 + T-cells ( Brenchley et al. 2003 ; unpublished data) in the interleukin-2 (IL-2)-supplemented assay conditions. In keeping with the finding by Brenchley et al. (2003 ), we observed that highly differentiated CD27 − /CD57 + CD8 + T-cells exhibited a reduced capacity to proliferate despite being activated following stimulation with anti-CD3 antibodies (−/+ addition of IL-2) ( Figure 5 C). In addition, we measured telomere length in CD8 + T-cell subsets at different stages of differentiation. The telomere length reflects the mitotic history of cells: in lymphocytes, every cell division shortens the telomeres by approximately 30–60 basespairs ( Rufer et al. 1998 ), until the cells lose their capacity to proliferate any longer. The induction of human telomerase expression (necessary for the maintenance of telomere length) has recently been shown to decrease in T-cells that have expanded in vivo upon antigen encounter ( Roth et al. 2003 ). Shortening of the telomeres appears to occur progressively along T-cell differentiation ( Figure 5 D) so that highly differentiated CD27 − /CD57 + cells display the shortest telomeres, with lengths (4–5 kb) equivalent to those observed in antigen-experienced CD8 + T-cells from the elderly ( Rufer et al. 1999 ). All together, these data support the view that T-cells exhibit increasing characteristics of replicative senescence as they differentiate further. The assumption that CD28 − /CD27 − T-cells are protective effector cells is mainly based on the fact that these cells possess strong cytotoxic potential, expressing high levels of perforin, as seen ex vivo ( Hamann et al. 1997 ). However, a recent report suggests that ex vivo Cr51 release assay, and therefore perforin levels, may not be a true reflection of in vivo cytotoxic capacities and, accordingly, this could be misleading in the interpretation of what constitutes a protective “effector cell” ( Barber et al. 2003 ). Figure 5 CD8 + T-Cell Differentiation and Senescence (A) Expression of the replicative senescence-associated marker CD57 on antigen-experienced CD8 + T-cell subsets. The percentage and mean fluorescence intensity for the CD57 + cells are shown for one single donor. Data on several donors (HIV-1-infected or healthy) are also shown ( n = 24). (B) Expression of CD57 on CD8 + T-cells (whole population or antigen-specific) from acute to postacute (on ART) HIV-1 infection. (C) CD69 expression and CFSE proliferation profile for CD8 + T-cell subsets gated on the basis of CD57 and CD27 expression following stimulation with anti-CD3 antibodies. PBMCs were analysed for CD69 expression after 18 h and CFSE labeling after 6 d. Percentages of proliferating cells (with background subtracted) are indicated. Representative results from three experiments (one HIV-infected and two healthy donors) are shown. (D) Telomere length measurement by flow FISH on naïve and antigen-experienced CD8 + T-cell subsets FACS-sorted on the basis of CD57, CD27, CCR7, and CD45RA expression. The average length of telomeres was obtained by substracting the mean fluorescence of the background control (no probe; open histogram) from the mean fluorescence obtained from cells hybridised with the FITC-labeled telomere probe (gray histogram). Representative results from two experiments (on healthy donors) are shown. (E) CD57 and perforin expression in the CD8 + T-cell population dissected into naïve (CD27 +high , perforin-negative), antigen-experienced CD27 + (perforin low ), and antigen-experienced CD27 − perforin low or perforin high subsets. The percentage and mean fluorescence intensity for the CD57 + cells are indicated. (F) Representative staining for perforin and CD57 in CD8 + T-cells from a HIV-1-infected or a healthy donor. Percentages of cells present in the top quadrants are shown. (G) Representative staining for perforin and CD57 in CD4 + T-cells from an HIV-1-infected or a healthy donor. Percentages of cells present in the top quadrants are shown. It was previously reported that antigen-specific CD27 − CD8 + T-cells do proliferate ( van Leeuwen et al. 2002 ). We show here that only a proportion of highly differentiated CD27 − CD8 + T-cells express CD57, therefore exhibiting reduced proliferative capacities, while the rest of the CD27 − CD8 + T-cells should indeed be able to expand. Nonetheless, the vast majority of highly differentiated cells with high levels of perforin are CD57 + ( Figure 5 E). The association between high levels of perforin and characteristics of replicative senescence is not a particular characteristic of HIV infection, but holds true in both HIV-infected and HIV-noninfected individuals ( Figure 5 F). Increase in the intracellular perforin content seems to be the normal consequence of the process of post-thymic development, and it is also valid in the case of CD4 + T-cell differentiation, since cytotoxic CD4 + T-cells, whose proportions are increased during HIV-1 infection ( Appay et al. 2002c ), are CD57 + ( Figure 5 G). Overall, as HIV-1-infected individuals are progressing, they display increasing proportions of late-differentiated T-cells with characteristics of replicative senescence, with an average of 40% of CD57 + CD8 + T-cells in progressor/AIDS individuals (data not shown). Overall, the accumulation of highly differentiated CD8 + T-cells in HIV infection goes along with reports of reduced proliferative capacities and shorter telomere length characterising the T-cells of the HIV-infected individual ( Wolthers et al. 1996a ; Bestilny et al. 2000 ; Effros 2000 ). Discussion Here we have studied the interplay between CD8 + T-cell activation and differentiation and its implications for HIV pathogenesis. HIV-1 induces a strong immune activation, which is particularly evident within the CD8 + T-cell compartment. Our data indicate that HIV-1 infection results in immune activation not only directly, but also indirectly, with the activation of cells specific for non-HIV antigens. In recent years, the role of potential bystander activation has been reevaluated and is now considered less important ( Murali-Krishna et al. 1998 ), suggesting that most of the stimulation observed may be antigen-driven. During acute HIV-1 infection, immunosuppression may develop that favours the replication of host flora like CMV and EBV, as occurs in other immunocompromised individuals ( Yao et al. 1996 ; Gerna et al. 1998 ). Recently, the help provided by CD4 + T-cells to control viral replication has been emphasised in the context of CMV infection ( Gamadia et al. 2002 ). The drop in the CD4 + T-cell counts during HIV acute infection may result in suboptimal immune control of CMV and EBV and thus permits the replication of these viruses. Data have indicated that frequent reactivation of CMV likely occurs in the human host, as evidenced by the presence of a large population of CD69 + CMV-specific cells, indicative of recent in vivo activation ( Dunn et al. 2002 ). Hence, HIV infection may serve to increase both the frequency and magnitude of CMV reactivation. In addition, inflammatory conditions occurring during HIV acute infection (e.g., release of proinflammatory cytokines) may participate in the reactivation of latent forms of CMV and EBV. We have shown here that T-cell activation and increasing differentiation are closely related. One could speculate that the association between different stages of CD8 + T-cell differentiation and viral specificity of these cells, as previously described ( Appay et al. 2002a ; Tussey et al. 2003 ), may be related to the stimulation intensity received by the cells from priming onwards. CMV may therefore be a particularly potent stimulus for CD8 + T-cells, thus promoting a strong differentiation of these cells. Interestingly, a similar phenomenon seems to happen in the context of CD4 + T-cells, as CMV-specific CD4 + T-cells show further differentiation, in comparison with EBV-specific CD4 + T-cells ( Amyes et al. 2003 ). In the context of HIV infection, elevated and chronic immune activation is the most plausible cause for the general shift of the CD8 + T-cell population towards the highly differentiated cells that accompanies progression towards AIDS, as we have shown that elevated cellular activation drives further differentiation of CD8 + T-cells (including HIV-, CMV-, or EBV-specific cells). Converging evidence suggests that a reduction of replicative potential occurs with extensive T-cell division and differentiation. Differentiation towards late stages (CD28 − /CD27 − /CD57 + ) is strongly associated with the display of characteristics of replicative senescence, which may have an impact on viral control. The relevance of perforin high late-differentiated T-cells in conferring protective immunity is controversial. For instance, van Baarle et al. (2002a ) reported a correlation between high numbers of late-differentiated HIV-specific CD8 + T-cells and years of AIDS-free survival. However, it remains to be determined whether late-differentiated CD8 + T-cells would simply accumulate in these individuals with chronic infection over time, whilst playing no role in delaying disease progression. Overall, there is confusion regarding the ideal functional and phenotypic profile of a “protective effector cell.” Protective immunity has recently been associated with the proliferative capacity of virus-specific CD8 T-cells in the mouse model ( Wherry et al. 2003 ). This is supported by Migueles et al. (2002 ), who showed that HIV-1-infected long-term nonprogressors are characterised by HIV-1-specific CD8 + T-cells that maintain a strong proliferative capacity following in vitro stimulation (cells defined mainly as CD45RO + /CD28 + /CD27 + early-differentiated cells). In this study, the proliferative potential of these cells was coupled to strong perforin expression, suggesting that early-differentiated cells (which express low perforin levels in a resting state [ Appay et al. 2002a ]) are able to express high perforin levels after certain conditions of stimulation. In contrast, the high perforin levels observed in resting late-differentiated T-cells seem to correlate with characteristics of replicative senescence. These findings challenge the view that highly differentiated T-cells are beneficial effector cells that should be the goal of vaccine or immunotherapeutic strategies ( Speiser et al. 2002 ). In keeping with this position, the fraction of perforin high HIV-specific CD8 + T-cells has been proposed to be a marker for disease progression ( Heintel et al. 2002 ). One may speculate that this high perforin expression may reflect an alteration of gene expression related to replicative senescence. This may not be dissimilar to the changes in gene expression that occur during replicative senescence in fibroblasts ( Smith and Pereira-Smith 1996 ). More investigations on this matter will be necessary to clarify the cause and consequence of high perforin levels in late-differentiated T-cells. The elevated and chronic stimulation induced by HIV-1 may result in the exhaustion of the capacity to generate new T-cells ( Hazenberg et al. 2003 ), while the pool of antigen-experienced cells is driven to differentiate into aged oligoclonal populations. Interestingly, these characteristics are not unique to HIV infection, but they are also common to other conditions that result in some degree of immunodeficiency, like ataxia telangiectasia ( Giovannetti et al. 2002 ), and normal human ageing ( Nociari et al. 1999 ; Rufer et al. 1999 ). They may reflect a premature decline of the immune resources necessary for viral control and therefore contribute to the onset of disease progression ( Effros 2000 ; Hazenberg et al. 2000a ; Appay and Rowland-Jones 2002b ; Grossman et al. 2002 ). This hypothesis is also strongly supported by a recent study performed in a mouse model in which persistent immune activation was shown to exhaust the T-cell pool and be sufficient to induce lethal immunodeficiency ( Tesselaar et al. 2003 ). In addition to a direct effect of HIV on the thymus, decreased thymic output and T-cell renewal may originate from thymus involution ( Kalayjian et al. 2003 ) as well as the failure of the bone marrow and the reduction of primitive hemaopoietic stem cell subsets ( Marandin et al. 1996 ; Moses et al. 1998 ), as observed in HIV-1-infected individuals. Increased proportions of highly differentiated T-cells may relate to the maintenance of homeostasis and “immunological space” in the absence of T-cell renewal. Our study also emphasises the importance of considering the influence of HIV-1 infection on other pathogens as well as the influence of these pathogens on HIV pathogenesis. For instance, CMV is known to drive substantial differentiation of T-cells towards CD57 + cells ( Wang et al. 1995 ). CMV may therefore play an important role in the decline of the immune resources, as recently proposed in the HIV-noninfected elderly ( Khan et al. 2002 ; Wikby et al. 2002 ). CMV infection was recently associated with a higher rate of disease progression in HIV-1-infected infants ( Kovacs et al. 1999 ) and with reduced survival in patients with advanced HIV disease ( Erice et al. 2003 ); it has also been shown to be a cofactor for HIV disease progression and death in some longitudinal studies of HIV-infected haemophiliacs ( Webster et al. 1989 ). The impact of elevated activation and differentiation on immune function appears to have considerable importance in the onset of immunodeficiency and needs to be addressed in the development of current and future anti-HIV strategies. Materials and Methods Study subjects. Samples were taken from HIV-1-infected patients attending clinics in London or Oxford (United Kingdom) and San Diego (United States) who were known to have either acute or chronic HIV-1 infection. The relevant local Institutional Review Boards and Ethics Committees approved the study. Subject ages ranged from 23 to 65 y old. Eleven patients with HIV-1 acute infection were selected from a well-characterised cohort in San Diego on the basis of their having an HLA type (HLA-A*0201, HLA-B*0701, or HLA-B*0801) for which we could detect virus-specific CD8 + T-cell populations using tetramers. The donors were diagnosed before or at the time of HIV-1 seroconversion, defined by symptomatic disease, recent high-risk exposure, high-plasma HIV-1 RNA (ranging from 3 × 10 5 to 3 × 10 6 copies/ml [mean, 8.3 × 10 5 copies/ml]), and either a negative HIV-1 ELISA or a negative/indeterminate HIV-1 Western blot. A second sample was analysed at a later timepoint after the start of successful ART (see Table 1 ). The study also involved untreated HIV chronically infected individuals: either with indications of viral control ( n = 14, drug naïve, infected for more than 10 y with a CD4 + count above 500 per milliliter and viral load ranging from undetectable to 2 × 10 4 copies/ml) or with evidence of progressive HIV disease ( n = 10, with decreasing CD4 + count, 500 < x < 130 per milliliter, and viral load ranging from 5 × 10 3 to 3 × 10 5 copies/ml). Blood samples were also obtained from healthy adult volunteers. Peripheral blood mononuclear cells (PBMCs) were separated from heparinised blood and cryopreserved for subsequent studies. HLA typing was carried out by amplification refractory mutation system–polymerase chain reaction (ARMS–PCR) using sequence-specific primers as previously described ( Bunce et al. 1995 ). HLA-typed patients were generally screened first for virus-specific CD8 + T-cell responses by means of Elispot assays using known HLA class I-restricted viral epitope peptides. Reagents and flow cytometry. HLA–peptide tetrameric complexes (“tetramers”) were produced as previously described ( Altman et al. 1996 ) and included the following specificity: A2 HIV p17-SLYNTVATL and pol-ILKEPVHGV, A2 CMV pp65-NLVPMVATV, A2 EBV BMLF1-GLCTLVAML, A2 influenza matrix-GILGFVFTL, A2 melan-A-ELAGIGILTV, B7 HIV nef-TPGPGVRYPL and gp41-IPRRIRQGL, B7 CMV pp65-TPRVTGGGAM, B8 HIV nef-FLKEKGGL and p24-DIYKRWII, B8 EBV BZLF1-RAKFKQLL, B35 CMV pp65-VFPTKDVAL and B57 HIV p24-KAFSPEVIPMF. Anti-CD8–PerCP (peridinin chlorophyll protein) or APC CY7 (allophycocyanin cyanine 7), anti-CD27–PE (phycoerythrin) or APC, anti-CD28–FITC (fluorescein isothiocyanate), anti-CD38–APC, anti-CD45RA–FITC or ECD (PE–Texas red), anti-CD62L–APC, anti-Ki67–FITC, anti-CD69–FITC, anti-CCR7-purified, anti-granzyme A–FITC, and anti-perforin–PE antibodies were purchased from Becton-Dickinson PharMingen (San Diego, California, United States); anti-CD57–FITC or PE antibodies were from Beckman Coulter (San Diego, California, United States). FACS stainings were performed as previously described ( Appay and Rowland-Jones 2002a ). In brief, titrated tetramers (PE-conjugated) were added to 150 μl of heparinised blood or PBMCs, followed by addition of a panel of titrated antibodies (FITC-, PerCP-, or APC-conjugated). The lymphocytes were then fixed and the red blood cells lysed using FACS TM lysis solution (Becton-Dickinson). Cells were washed, fixed, and permeabilised in FACS TM permeabilisation buffer (Becton-Dickinson). After washing, intracellular perforin staining was performed using titrated antibodies. Cells were then washed and stored in Cell Fix TM buffer (Becton-Dickinson) at 4°C until analysis. Samples were analysed on a Becton-Dickinson FACSCalibur after compensation was checked using freshly stained PBMCs. Carboxyfluorescein diacetate succinimidyl ester (CFSE) labeling was performed by incubating PBMCs with 5 μM CFSE (Molecular Probes, Leiden, The Netherlands) in RPMI 1640 for 10 min at 37°C, before quenching with ice-cold RPMI 1640–10% foetal calf serum (FCS) and washing. The cells were then incubated with immobilised OKT3 (10 μg/ml) for 6 d (with or without 20U/ml of IL-2) before staining. Flow fluorescence in situ hybridisation. Naïve and antigen-experienced CD8 + T-cell subsets were sorted ex vivo from freshly isolated PBMCs, on the basis of CD27, CD57, CCR7, and CD45RA expression using a five-color FACS vantage SE (with 98%– 99% purity). For each subset, 0.5 × 10 5 to 2 × 10 5 cells were used to measure the average length of telomere repeats at chromosome ends in individual cells by quantitative flow fluorescence in situ hybridisation (FISH), as previously described ( Rufer et al. 1998 , 1999). FITC-labeled fluorescent calibration beads (Quantum TM-24 Premixed; Bangs Laboratories Inc., Fishers, Indiana, United States) were used to convert telomere fluorescence data to molecules of equivalent soluble fluorescence (MESF) units. The following equation was performed to estimate the telomere length in basepairs from telomere fluorescence in MESF units: basepair = MESF × 0.495 ( Rufer et al. 1998 ). In vitro priming of CD8 + T-cells with DCs. DCs were generated as previously described ( Salio et al. 2001 ). Monocytes were purified from healthy donors' PBMCs (screened for HLA-A2 expression) by positive sorting using anti-CD14-conjugated magnetic microbeads (Miltenyi Biotec, Bergisch-Gladbach, Germany). The recovered cells were greater than 99% CD14 + . DCs were generated by culturing monocytes in RPMI 1640–10% FCS supplemented with 50 ng/ml GM–CSF (Leucomax, Basel, Switzerland) and 500 U/ml IL-4 (Peprotech, London, United Kingdom) for 5 d. Cells (3 × 10 5 /ml) were stimulated by addition of 1 μg/ml LPS (Sigma, St. Louis, Missouri, United States). Antigen-presenting cells were pulsed for 3 h with various concentrations of melan-A–peptide in serum-free medium before incubation with autologous PBMCs at a 1:5 ratio in RPMI 1640–10% FCS. Human rIL-2 (R&D Systems, Minneapolis, Minnesota, United States) was added from day 4 at 10 U/ml, then at 500 U/ml IL-2 when cells expanded. Melan-A-specific CD8 + T-cells were then analysed by flow cytometry over time for up to 50 d. Statistics. Group medians and distributions were compared by the nonparametric Mann–Whitney test. Associations between variables were determined by the nonparametric Spearman rank correlation test. Associations between variables in different patient groups were determined by simple linear regression or ANOVA test. P values above 0.05 were considered not significant.

/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC340937.xml

551532

Identifying genetic networks underlying myometrial transition to labor

A time course of gene expression at the onset of labor reveals transcriptional networks associated with activation of the uterine muscle and identifies targets for drugs to prevent premature labor.

Background The initiation of mammalian labor is a complex physiological process that requires the expression and secretion of many factors, both maternal and fetal [ 1 , 2 ]. The majority of these factors exert their effect on the myometrium, the smooth muscle responsible for expelling the fetus from the uterus. While species differences in labor regulation have been observed, several common signaling pathways and factors have been implicated as key regulators across species. During mid to late gestation, myometrial quiescence is maintained by several contractile inhibitors, such as relaxin, adrenomedullin, nitric oxide, prostacyclin and progesterone [ 1 , 2 ]. A number of these regulators stimulate cyclic AMP (cAMP)- and cGMP-mediated signaling pathways. Smooth muscle contraction is inhibited by the phosphorylation of myosin light-chain kinase by the cAMP-dependent protein kinase. This inhibition is believed to promote quiescence. In addition, the myometrium undergoes major structural changes throughout pregnancy that are required to generate the necessary contractile force for labor, including hypertrophy and hyperplasia of smooth muscle, connective tissue, focal adhesion, and cytoskeletal remodeling [ 3 ]. The transition to labor results in synchronous contractions of high amplitude and high frequency by the myometrium. Factors previously associated with the regulation of myometrial activation include the oxytocin receptor, gap junction protein connexin-43, voltage-gated calcium channels, prostaglandin receptor subtypes, estrogen, cortisol and transcription factors c-Jun and c-Fos. Most of these proteins participate in pathways that stimulate calcium release (for example, calcium-calmodulin G protein signaling) and the formation of intracellular junctions, leading to stimulation of contractions. Although several important components that regulate the initiation of labor have been identified, the mechanisms that guide this transition are poorly understood. A difficult challenge in identifying the regulatory events that control the switch from myometrial quiescence to activation has been developing tools for examining whole-genome expression profiles in the context of known biology. Recent efforts to identify transcriptional changes from laboring and non-laboring human myometrium have proved valuable in identifying putative physiological regulators [ 4 - 8 ]; however, the lack of gestational time points examined has limited these approaches to interrogating only those genes with large fold-changes at term activation without exploring the global patterns of gene expression over the time-course of myometrial transformation. While gene profiling of the rodent uterus during gestation has proved fruitful in revealing some of the large-scale patterns of gene expression throughput pregnancy [ 5 , 9 ], there is still a critical need to improve the global view of myometrial gene expression with greater temporal resolution using newly developed bioinformatic tools. To identify molecular mechanisms involved in the transition from myometrial quiescence to labor, we analyzed gene-expression changes in mouse myometrium at mid-gestation, throughout late gestation, and during the postpartum period. Our results reveal several novel patterns of expression occurring along the phases of myometrial quiescence to term activation and postpartum involution. Analysis of putative quiescence and term activation regulators in the context of well defined biological pathways revealed new putative functional roles for several previously unassociated genes in the suppression of contraction throughout gestation and activation of phase-dependent contractions at labor. This analysis further implicates the regulation of several novel pathways, including smooth muscle-extracellular matrix interactions throughout late gestation and cell junction-cytoskeletal interactions immediately before the onset of labor. Results Clustering of expression changes in gestational myometrium Messenger RNA transcript levels were measured from isolated myometrium of 35 time-mated mice at four time-points of late gestation (14.5-18.5 days), at postpartum (6 and 24 hours after labor), and from a non-pregnant control group. In all, approximately 13,000 probe sets corresponding to around 9,000 unique cDNAs and expressed sequence tags (ESTs) were probed with oligonucleotide microarrays. About 35% of these transcripts were regulated throughout gestation and postpartum (14.5 days through 24 hours postpartum) using the criteria of p < 0.05 and a change in level of expression of more than 20% (fold-change 0.2). Analysis of these probe sets with HOPACH [ 10 - 12 ] revealed eight primary cluster groups and 133 subclusters. The majority of these clusters showed a clear association with known physiological phases of uterine gestation: quiescence (clusters 2, 3, 7 and 8), term activation (cluster 6), and postpartum involution (clusters 3, 4 and 7). In addition to these clusters, we observed two cluster groups with genes downregulated or upregulated throughout the analyzed time-course (clusters 1 and 5) (Figure 1 ). MAPPFinder analysis To characterize the major biological processes, molecular functions, and cellular components associated with the HOPACH pattern groups, we used MAPPFinder (a component of GenMAPP version 2.0) [ 13 - 16 ]. MAPPFinder produced a statistically ranked list (based on p -value) of Gene Ontology (GO) biological categories associated with each cluster, from which the most significant nonsynonymous groups are listed (Figure 1 , GO categories). In each cluster, several highly significant biological associations were identified (adjusted permutation p < 0.05). Association of expression clusters with previously associated uterine quiescence and activation genes Gene expression groups associated with the maintenance of pregnancy (quiescence) or induction of labor (activation) were confirmed by mapping lists of previously associated regulators of uterine quiescence and activation onto our HOPACH cluster map. Extensive literature searches for such regulators identified 66 genes, of which 23 were regulated in our dataset (Figure 1 , previously associated regulators). Genes hypothesized to regulate quiescence by transcriptional upregulation or secretion were largely associated with clusters 7 and 8 ('increased quiescence'), while putative activators of uterine activation were largely associated with cluster 6 ('increased term activation'). Although only three downregulated quiescence regulators were associated with HOPACH clusters, two of them mapped to cluster 2 ('decreased quiescence'), as predicted. Functional analysis of quiescence and term activation pattern groups To further elucidate specific genes and pathways linked to the regulation of uterine quiescence and the initiation of labor, we examined pattern groups linked to quiescence and term activation, in the context of GO categories, GenMAPP pathway maps and literature associations. While low-magnitude fold-changes have been included within these functional analyses to broaden our survey of biological groups, we have largely restricted our discussion to transcripts with fold-changes greater than two. Upregulation of pathways of relaxation and remodeling during quiescence Analysis of genes upregulated throughout gestation (increased quiescence) revealed a number of biological categories associated with uterine quiescence. These categories contain a large number of highly regulated genes coupled to the inhibition of prostaglandin and cortisol synthesis, stimulation of cAMP and cGMP signaling pathways, extracellular matrix remodeling, cytolysis and regulation of cell growth (Figure 2 , Table 1 ). To explore the potential relationships between the products of these transcriptionally regulated genes, we mapped the data onto respective metabolic and signaling pathways (Figure 3a,b ). Besides well established quiescence regulators ( Adm , Cgrp , Hsd11b2 , Gnas , Cnn1 and Utg ; see Tables 1 , 2 , 3 for full gene names), several genes previously unassociated with the maintenance of quiescence were identified along the same or related biological pathways. The most highly regulated of these genes were those implicated in the induction of cGMP and cAMP signaling pathways ( Guca2b and Cmkor1 ), genes for calcium-dependent phospholipid binding proteins ( Anxa1 , Anxa2 , Anxa3 and Anxa8 ), and for the Anxa2 dimerization partner S100A10 (Figure 3a ). Other changes in expression from this pattern group were observed among cytolysis-inducing proteases (granzymes B-G), regulators of cell growth ( Igfbp2 and Il1r2 ), and transcriptional regulation ( Sfrp4 and Klf4 ). Several of these and other genes were found to have highly reproducible patterns of expression using quantitative real-time PCR (TaqMan), with typically larger fold-changes produced by TaqMan than by GeneChip (consistent with the more conservative fold-changes typically produced after robust multi-array average (RMA) normalization) (see Additional data file 1). Several genes for cAMP-response element transcription factors were also found within the increased quiescence group ( Atf4 , Crebl1 , and Creb3 , see Figure 3b ). These are all members of a larger group of basic leucine zipper (bZip) transcription factors not previously associated with quiescence, which also includes the CCAAT/enhancer binding protein Cebpd, the Maf protein Mafk, the nuclear factor, interleukin-3, regulated Nfil3, and the X-box binding protein Xbp1, also upregulated with quiescence. Downregulation of mRNA processing and contraction-associated signaling during quiescence MAPPFinder analysis of genes in the decreased quiescence group identified a wide variety of cell maintenance, transcription, and cell-signaling biological processes. Many of these GO categories were associated with the onset of labor (calcium-ion transport and protein tyrosine phosphatase activity) or myometrial postpartum involution (programmed cell death, collagen catabolism and ubiquitin-conjugating enzyme activity). These results are in accordance with the inhibition of contraction and suppression of cell death in late gestation. Unlike term-related biological processes, categories shared between the decreased quiescence and 'increased postpartum involution' group appear to be largely the result of a common transcript expression profile (Figure 1 , cluster 3; Figure 2 ). Although similar numbers of genes were downregulated or upregulated with quiescence (approximately 480-520 genes), very few genes were downregulated more than twofold at 14.5 days of gestation (Table 2 ). One of the most downregulated transcripts was the myosin light-chain gene Myl4 ; the Myl4 protein is the primary target for oxytocin-induced phosphorylation leading to uterine contraction at term. Several additional putative components of the oxytocin contractile signaling pathway (calcium-calmodulin signaling pathway) were also present in this expression group (Iptr1, Ryr3, Plcg1, and Atp2a2) (Figure 3b ). Another large set of coordinately downregulated genes includes factors involved in RNA processing. Alternative splicing of putative quiescence and term activation regulators has been proposed to be a critical mechanism of the physiological switch to labor [ 17 , 18 ]. Transition from remodeling and relaxation to cell-cell signaling and transcriptional regulation with activation of the myometrium at term A large percentage of genes regulated with quiescence continued to be highly regulated at term. This result emphasizes the importance of expression changes immediately before labor to counteract the effects of quiescence. Consistent with the number of upregulated genes, MAPPFinder analysis of the increased term activation group identified a smaller set of GO terms and pathways. Prominent among these were genes associated with the formation of cell junctions, kinesin complexes and endopeptidase inhibitors. In addition, functionally related transcription factors (members of the basic helix-loop-helix (bHLH) family), ion transport proteins and ion transport regulators were coordinately upregulated at term. Within these biological categories, several contractile regulators, both associated and unassociated with parturition, were highly upregulated. These genes include those for cell junction proteins (Cx43, Cx26, Ocln, and Dsp), the pulmonary smooth muscle contractile regulator and complement component C3, the estrogen signaling regulator Hsp70, the chloride conductance regulator Fxyd3 and the ryanodine receptor regulator Gsto1 (Table 3 ). These changes occurred in concert with the upregulation of signaling molecules, such as growth factors (Inhba, Inhbb), G-protein signaling components (Edg2, Gng12) (Figure 3b ) and collagen catabolism proteins (Pep4, Mmp7). On the whole, however, this pattern group was dominated by the upregulation of genes encoding proteins that are largely epithelial-cell specific. Most prominent among these are the genes for the cytokeratin intermediate filament proteins, Krt2-7, Krt2-8, Krt1-18, and Krt1-19, and for the cytokeratin transcriptional regulator Elf3, which are among the most highly upregulated genes at term. Downregulation of pathways of calcium mobilization and G-protein signaling in term myometrium HOPACH analysis with a metric that disregarded the direction of fold-change (see Additional data file 2) revealed a small number of downregulated genes at term that mirror the increased term activation group. Among these, we observed two highly downregulated genes: regulator of G-protein signaling 2 ( Rgs2 ), a potent inactivator of Gαq-GTP bound activity, and inhibitor of DNA binding 2 ( Idb2 ), a bHLH factor that heterodimerizes with other HLH proteins to inhibit their function. Rgs2 is one of the most downregulated genes throughout the gestation-postpartum time-course, in addition to being highly expressed in non-pregnant myometrium and throughout gestation. Additional term-downregulated G-protein signaling proteins that act to antagonize calcium-calmodulin signaling are illustrated in Figure 3b . Global mechanisms of transcriptional regulation One of the most prominent observations in this dataset is the highly significant correlation in the expression and genomic position of genes for eight serine-type endopeptidases ( Gzmb through Gzmg , Mcpt8 and Ctsg ) during the phase of quiescence. Genes within this multigene cluster undergo tight coordinate regulation in response to cell stimulation [ 19 , 20 ]. Examination of this expression cluster group in the context of genomic position reveals a novel pattern of positional gene regulation, where relative fold-change in expression increases from the peripheral members in the cluster to the center of the gene cluster (Figure 4a ). To determine whether other gene clusters exhibit a similar form of positional co-regulation, we developed a program to identify genomic intervals containing several coexpressed genes. Searching for regions with three or more members in a broad genomic interval (500 kilobases (kb)), we identified 11 clusters of genes that are co-localized and co-regulated (the same HOPACH cluster) [ 21 ]. Among these, we were able to identify at least one other gene cluster that possessed a genomic pattern of gene expression similar to that of the granzyme cluster, with genes maximally upregulated postpartum (Figure 4b ). These genes, which encode several of the collagen catabolism matrix metalloproteinases, Mmp3, Mmp10, Mmp12 and Mmp13, are among the most highly upregulated genes postpartum. Because we do not have data from full genome arrays, it is difficult to determine if these co-regulated clusters of genes occur more frequently. However, these co-regulated gene clusters suggest coordinated gene regulation by an unknown mechanism. Discussion This time-course analysis provides the first global view of gene-expression changes in mouse myometrium from uterine quiescence through the activation of the myometrium before labor and to its postpartum involution. Examination of multiple time points, the use of replicates, robust array normalization and powerful clustering tools enabled us to delineate and characterize unique patterns of gene expression throughout this physiological process. In addition to partitioning clusters of genes, analysis with the program HOPACH also provides us with a continuum of expression changes that reveals an overall transition in the expression of genes from one cluster group to another (Figure 1 ). Annotation of these clusters with GO terms provides a bird's eye view of the major processes regulating each of these pattern groups. These results support the hypothesis that mid-to-late gestation is dominated by changes in the expression of genes related to cell growth and extracellular-matrix remodeling (cluster 7), term gestation by changes in the content of cell junctions (cluster 6), and postpartum by targeted protein degradation, collagen digestion and apoptosis (clusters 3 and 4). Furthermore, results from genes upregulated throughout gestation and through postpartum suggest a continual local uterine immune response throughout this process (cluster 5). To help visualize the large-scale gene-expression changes in the context of myometrial physiology, we have depicted the data in an animation (see Additional data file 3) that summarizes our major findings. A number of studies emphasize the importance of fetal regulation of the switch from quiescence to term activation, particularly increased cortisol and estrogen output from the fetal adrenal gland [ 1 , 2 ]. Interestingly, our studies provide evidence of a dynamic interplay between the myometrium and the fetus, particularly at the level of cortisol and progesterone synthesis (Figure 3a ). Genes highly upregulated with quiescence include Hsd11b , which encodes an enzyme that converts cortisol to the inactive cortisone, and Cyp11a1 , encoding an enzyme that promotes the synthesis of progesterone. Conversely, Hsd11a , coding for an enzyme that catalyzes the synthesis of cortisol, increased expression from 11- to 18-fold throughout gestation, suggesting that local regulation of cortisol levels are important for myometrial activation. While we observed the upregulation of the estrogen signaling regulator Hsp70, with term activation, downstream markers of estrogen action are among the most highly upregulated genes with term activation, supporting the role of the fetus in myometrial activation. Examination of highly upregulated putative quiescence and term activation genes revealed several novel changes within important associated pathways for quiescence and activation (cAMP and cGMP signaling, calcium and calmodulin signaling and prostaglandin synthesis). Proteins encoded by these genes include Guca2b (uroguanylin), Anxa3, and Anxa8 with quiescence, and C3, Edg2, Gsto1 and Fxyd3 during activation (see Figure 3 ). These factors may represent novel targets for controlling the length of gestation. This is evidenced by the parallel observed upregulation of Guca2b from a recent microarray analysis of rat uterine gestation, where this factor has also been proposed to be a crucial regulator of cGMP-mediated smooth muscle relaxation throughout late pregnancy [ 9 , 22 ]. We have validated the expression patterns of a number of these genes using quantitative real-time PCR (see Additional data file 1). In addition to the candidates mentioned here, a number of other highly upregulated genes, whose functions have not been elucidated are also found in these two expression groups (see Additional data file 6). Although a number of genes upregulated with quiescence or with term activation can be clearly implicated in the regulation of contractile pathways or uterine growth, several more groups of genes with little known functional connection to these processes were coordinately expressed. Highlighted among these groups are serine endopeptidases (granzymes) and bZip transcription factors, upregulated during quiescence, and endopeptidase inhibitors and bHLH factors, upregulated with term activation. In addition to its role in cytolysis, granzyme expression and secretion by T lymphocytes has been associated with the breakdown of extracellular matrix proteins in the uterus during pregnancy [ 18 , 23 , 24 ]. Interestingly, the upregulation of serine endopeptidases appears to be antagonized before the onset of labor by the upregulation of several serine endopeptidase inhibitors with term activation. A similar antagonistic relationship may also exist for bHLH factors upregulated at term with inhibitors of HLH function that are upregulated with quiescence and become downregulated at term. Although the myometrium is considered to be relatively homogeneous, many of the largest changes in gene expression at term occurred in genes that are not normally associated with muscle, such as the keratins, tight junction and desmosome junction proteins. Indeed, altered gene expression due to changes in cell-type distribution or the invasion of the myometrium by the decidua and endometrium would not be distinguished if those changes occur consistently between gestational myometrium preparations. Further inspection of the literature reveals that the cytokeratins, which compose the bulk of this group, are expressed within smooth muscle and probably function as components of intermediate filaments of the cytoskeleton [ 25 - 28 ]. Furthermore, several components of desmosome spot junctions and hemidesmosomes, which interact with keratin intermediate filaments and the extracellular matrix to impart tensile strength between cells, are also upregulated with term activation (see Additional data file 3). These data suggest that an increase in rigidity-imparting cell junctions and remodeling of the cytoskeleton immediately before labor may promote coordinate contractions. However, further studies are needed to determine if cytokeratin expression at term occurs within resident or infiltrating cells. In addition to the capability to group and annotate clusters of genes, pattern analysis with HOPACH can be used to interrogate gene clusters in the context of genomic location. For this analysis, we developed a program to isolate gene clusters that are likely to be co-regulated on the basis of genomic location, similar to other reported methods [ 29 - 32 ]. Using this program, we identified genomic regions that undergo correlated changes in gene expression associated with specific phases of the myometrial time-course. These groups highlight novel forms of gene regulation during quiescence and postpartum to coordinate cell responses (serine-protease activation and collagen catabolism). The prominent co-regulation among members of these two gene clusters further suggests that immune-cell trafficking and activation also play important roles in the progression towards labor and recovery from pregnancy. Conclusions We have identified several highly regulated genes not previously associated with myometrial quiescence or activation, in addition to families of genes co-regulated at different phases of the myometrial time-course. In addition to providing new hypotheses about how the switch from quiescence to term activation may be facilitated (Figure 5 ), these data highlight several proteins that may serve as new candidate pharmacological targets for regulating myometrial contraction and thus the onset of labor. Such analyses will also be useful in predicting and correlating gene-expression changes in human pregnancy, where several time-points are often difficult to obtain [ 4 - 8 ]. Similar studies in other species using complementary methods of transcript measurement will also be necessary to validate these changes and understand the species-specific and regional myometrium transcriptional differences that probably occur. A detailed examination of the precise physiological roles of these regulators and mechanisms of regulation will be essential for developing a more detailed view of the regulation of labor. Materials and methods Tissue harvesting FVB/N mice (Jackson Laboratory) were sacrificed in the morning (10 to noon) at 14.5 ( n = 3), 16.5 ( n = 4), 17.5 ( n = 5), or 18.5 days ( n = 7) after timed mating, and 6 ( n = 4) or 24 h ( n = 4) after delivery. Control myometrium was harvested from non-pregnant littermate females ( n = 8) 1 day after timed mating with a vasectomized male. After dissection of both uterine horns, the tissue closest to the cervix was removed. Each horn was washed with PBS and opened longitudinally. Pups and placenta were discarded, and the decidua was removed by blunt dissection. The myometrium from each horn was then immediately frozen in liquid nitrogen and stored at -80°C. Sample preparation and microarray data normalization For each sample, labeled cRNA was prepared from 20 μg purified total RNA and hybridized to Affymetrix Mu11k A and B arrays according to the manufacturer's instructions. Tissue from each mouse was hybridized individually to one array set. Microarrays were scanned at a photomultiplier tube (PMT) setting of 100%. Resulting .cel files were generated with Affymetrix Microarray Suite 5.0 and analyzed with RMA [ 33 ]. Statistical analysis To identify transcripts differing in mean expression across the seven experimental groups, p -values were calculated from a permutation test with the F-statistic function from the multtest package of Bioconductor [ 12 , 34 ]. Fold-changes in transcript levels were calculated from the mean log 2 expression values of each time-point group versus the mean of non-pregnant controls. For cluster analysis, the dataset was filtered for probe sets with a p < 0.05 across the full expression time-course and a greater than 20% change in level of expression (positive or negative) for at least one time-point group versus non-pregnant controls. Additional filters were used downstream of clustering for genes related to uterine quiescence and term activation. For clusters related to quiescence and term activation, a change of more than 20% was required for the midgestation (14.5 days) and term (18.5 days) time points, respectively, versus non-pregnant controls. Clustering and pattern analysis Gene expression clustering for 4,510 significant probe sets was performed using the program HOPACH (hierarchical ordered partitioning and collapsing hybrid), with uncentered correlation distance [ 10 - 12 ]. HOPACH produced a tree with six levels of clusters (eight primary level clusters and 133 main clusters). To examine expression patterns independently of the direction of the fold change, HOPACH was re-run with absolute uncentered correlation distance. Associations with GO biological process, molecular function, cellular component groups, and GenMAPP biological pathways were obtained with MAPPFinder 2.0, a part of the GenMAPP 2.0 application package [ 13 - 16 ]. A permuted p -value was calculated by MAPPFinder 2.0 to adjust for multiple hypothesis testing (see Additional data file 7). Because of the highly redundant nature of the oligonucleotide arrays used, redundant probe sets corresponding to a single gene were identified from the Affymetrix NetAFFX website [ 35 ]. Real-time PCR validation of microarray data Real-time reverse transcription PCR (RT-PCR) was used to validate the expression patterns of several highly regulated genes associated with specific phases of myometrium gestation. Gene-specific primers for multiplex real-time RT-PCR were designed for each gene of interest ( n = 18) using Primer Express software (Perkin Elmer) and based on sequencing data from the National Center for Biotechnology Information (NCBI) databases and purchased from Biosearch Technologies. Sequence data for all oligos are available online [ 36 ]. Total RNA concentration and quality was assessed using the Agilent Bioanalyzer 2001. First-strand cDNA synthesis was performed using total cellular RNA (BD Biosciences Clontech), Powerscript reverse transcriptase (BD Biosciences Clontech), and random hexamer primers. Finally, an equivalent of 10 ng of total RNA from the first-strand cDNA synthesis reaction was used in 10 μl of each TaqMan gene quantification in 384-well format. Universal Master Mix for real-time PCR was purchased from Invitrogen Life Technologies. Raw data from an ABI Prism 7900 (Applied Biosystems) were processed into Excel spreadsheets and conversion of raw Ct values to relative gene copy numbers (GCN) was done as described previously [ 37 ]. Gene-expression analysis requires proper internal control genes for normalization. By using an endogenous control as an active reference, quantification of an mRNA target can be normalized for differences in the amount of total RNA added to each reaction. For this purpose, we used four mouse housekeeping genes - PPIA , GAPDH , PGK1 and S9 . Moreover, using GeNorm [ 38 ], we selected PGK1 and GAPDH as the two most stable housekeeping genes across all 12 specimens and used their geometric means for normalization. Normalized data were graphed and compared to the data generated on similar specimens via microarrays. Genes could be broken down into the following groups: 13 genes with concordant microarray-TaqMan patterns; one false-negative result by microarray ( Acta2 ); three genes with high TaqMan variability ( Mmp9 , Krt19 , Id1 ); and one gene with evidence of alternative splicing ( Csb ) (see Additional data file 1). It should be noted that Acta2 baseline expression was relatively high for both microarray and TaqMan results. As both of these techniques probed different regions of the Acta2 gene, we cannot exclude the possibility of alternative splicing. Chromosomal localization analysis We constructed a program to link HOPACH expression data to chromosome transcription start-site location and strand orientation, obtained from the Ensembl database [ 39 ]. Co-localized clusters of genes were identified as those genes clustered within a 500-kb genomic interval, belonging to the same HOPACH cluster, with a z -score >1.96, and an average pairwise Pearson correlation among cluster members of r >0.65 (see Additional data file 7 for calculation details and [ 21 ] for the full supplemental chromosome cluster lists). Additional data files The following additional data are available with the online version of this article. Additional data file 1 is a figure showing the TaqMan vs GeneChip gene expression patterns. Relative fold changes (log base 2) are shown for 18 genes identified by these GeneChip studies to be differentially regulated throughout the myometrium gestation time-course. Combined standard errors are shown for each gestational time-point as compared to the non-pregnant control group. Additional data file 2 is a figure showing the HOPACH Absolute Value Pearson Correlation of Myometrial Expression Data. Gene expression data used for Pearson correlation HOPACH was used to generate a new set of clusters with a metric that disregards the direction of fold-change. Genes downregulated with term are identified based on association with genes upregulated at term from the non-absolute HOPACH analysis. Additional data file 3 is an animation of the summary and results, with a cartoon representation of myometrial transformation, general experimental design, results and conclusions. Additional data files 4 and 5 are Excel tables listing the MAPPFinder results. Nonsynonymous MAPPFinder GO categories for each expression pattern group are provided. Reanalysis with GenMAPP version 2.0 is required to visualize the genes that associate with each GO term. To download GenMAPP version 2.0, go to [ 16 ]. Additional data file 6 is a set of tables of cluster groups with annotations. Expression data, statistics, and biological groupings based on Gene Ontology annotations (via MAPPFinder analysis) and the literature are provided for 'Quiescence', 'Activation', and Postpartum 'Involution' gene lists. Additional data file 7 contains additional details of methods. Additional data file 8 contains the full expression dataset as an Excel file and Additional data file 9 is a GenMAPP format GEX file for use with GenMAPP format pathway maps (MAPP files). MAPP files can be downloaded from [ 16 ]. Supplementary Material Additional data file 1 A figure showing the TaqMan vs GeneChip gene expression patterns Click here for additional data file Additional data file 2 A figure showing the HOPACH Absolute Value Pearson Correlation of Myometrial Expression Data Click here for additional data file Additional data file 3 An animation of the summary and results, with a cartoon representation of myometrial transformation, general experimental design, results and conclusions Click here for additional data file Additional data file 4 Excel tables listing the MAPPFinder results: HOPACH unique GO Click here for additional data file Additional data file 5 Excel tables listing the MAPPFinder results: MAPPFinder quiescence, activation and postpartum Click here for additional data file Additional data file 6 A set of tables of cluster groups with annotations Click here for additional data file Additional data file 7 Additional details of methods Click here for additional data file Additional data file 8 The full expression dataset as an Excel file Click here for additional data file Additional data file 9 A GenMAPP format GEX file for use with GenMAPP format pathway maps (MAPP files) Click here for additional data file

/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC551532.xml

514720

Identification of proteases employed by dendritic cells in the processing of protein purified derivative (PPD)

Dendritic cells (DC) are known to present exogenous protein Ag effectively to T cells. In this study we sought to identify the proteases that DC employ during antigen processing. The murine epidermal-derived DC line Xs52, when pulsed with PPD, optimally activated the PPD-reactive Th1 clone LNC.2F1 as well as the Th2 clone LNC.4k1, and this activation was completely blocked by chloroquine pretreatment. These results validate the capacity of XS52 DC to digest PPD into immunogenic peptides inducing antigen specific T cell immune responses. XS52 DC, as well as splenic DC and DCs derived from bone marrow degraded standard substrates for cathepsins B, C, D/E, H, J, and L, tryptase, and chymases, indicating that DC express a variety of protease activities. Treatment of XS52 DC with pepstatin A, an inhibitor of aspartic acid proteases, completely abrogated their capacity to present native PPD, but not trypsin-digested PPD fragments to Th1 and Th2 cell clones. Pepstatin A also inhibited cathepsin D/E activity selectively among the XS52 DC-associated protease activities. On the other hand, inhibitors of serine proteases (dichloroisocoumarin, DCI) or of cystein proteases (E-64) did not impair XS52 DC presentation of PPD, nor did they inhibit cathepsin D/E activity. Finally, all tested DC populations (XS52 DC, splenic DC, and bone marrow-derived DC) constitutively expressed cathepsin D mRNA. These results suggest that DC primarily employ cathepsin D (and perhaps E) to digest PPD into antigenic peptides.

Review Dendritic cells (DC) are professional antigen presenting cells that induce primary antigen specific T cell responses [ 1 ] and exhibit all functional properties required to present exogenous antigen (Ag) to immunologically naïve T cells. These properties include: a) uptake of exogenous Ag via receptor-mediated endocytoses, b) processing of complex proteins into antigenic peptides, c) assembly of these peptides with MHC molecules, d) surface expression of MHC molecules as well as costimulatory molecules, including CD80, CD86, and CD40, e) secretion of T cell stimulatory cytokines, including IL-1β, IL-6, IL-8, TNF-α, and macrophage inflammatory protein (MIP)-1α and f) migration into draining lymph nodes [ 2 ]. In the present study, we sought to characterize the Ag processing capacity of DC, as well as the enzymes previously involved in this process. In this regard, several groups have previously reported that epidermal LC and splenic DC, both of which contain small numbers of non-DC contaminants, exhibit significant Ag processing capacities [ 3 - 12 ]. LC freshly obtained from skin are quite potent in their Ag processing capacity, but the majority of these LC lose this capacity as they "mature" during subsequent culture [ 3 - 6 , 12 ]. On the other hand, other reports have shown that DC are less efficient than macrophages in Ag processing, with each employing different pathways for Ag processing [ 10 , 13 - 16 ]. These differences suggest the possibility of unique pathways and requirements for Ag presentation by DC. With respect to the mechanisms by which DC process complex protein Ags, chloroquine has been shown to inhibit this process; this suggests that Ag processing primarily occurs within acidic compartments [ 6 - 8 ], [ 10 - 12 ]. Macrophages and B cells have been reported to employ cathepsins B, D, and/or E for digesting protein Ag, including ovalbumin (OVA), hen egg white lysozyme (HEL), myoglobin, exogenous IgG, and Staphylococcus aureus nuclease [ 17 - 35 ]. These proteases may each exhibit differential pathways for activity; for example, macrophages appear to employ cathepsin D for the initial cleavage of myoglobin and cathepsin B for C-terminal trimming of resulting fragments [ 17 ]. Little information, however, has been available with respect to proteases that are employed by DC for Ag processing. Thus, in the present study we sought to define the protease profiles produced by DC and then to identify which protease(s) would primarily mediate Ag processing in DC. Materials and Methods Cells The XS52 DC cell line (a gift of Dr. Takashima, Dallas, Texas), a long-term DC line established from the epidermis of newborn BALB/c mice [ 23 ], were expanded in complete RPMI in the presence of 1 ng/ml murine rGM-CSF and 10% culture supernatants collected from the NS stromal cell line as described previously [ 23 ]. Other phenotypic and functional features of this line are descibed elsewhere [ 23 - 25 ]. As responding T cells, we used the protein purified derivative (PPD)-reactive Th1 clone LNC.2F1 and the Th2 clone LNC.4K1 [ 26 ], both of which were kindly provided by Dr. E. Schmitt (Institute for Immunology, Mainz, Germany). As control cells, we also employed Pam 212 keratinocytes [ 27 ], 7–17 dendritic epidermal T cells (DETC) [ 28 ], J774 macrophages (ATCC, Rockville, MD), and BW5147 thymoma cells (ATCC). Splenic DC were purified from BALB/c mice (Jackson Laboratories, Bar Harbor, ME) by a series of magnetic bead separations as before [ 24 , 25 ]. Briefly, spleen cell suspensions were first depleted of B cells using Dynabeads conjugated with anti-mouse IgG. Subsequently, T cells were removed using beads coated with anti-CD4 (GK1.5) and anti-CD8 mAbs (3.155), and then macrophages were depleted using beads conjugated with F4/80 mAb. Finally, DC were positively sorted using beads coated with anti-DC mAb 4F7 [ 29 ]. The resulting preparations routinely contained > 95% DC, as assessed by flow cytometry. DCs were propagated from bone marrow as described by Inaba et al. [ 30 ]. Using magnetic beads, bone marrow cell suspensions were first depleted of B cells (with anti-mouse IgG), I-A + cells (with 2G9 mAb, Pharmingen, San Diego, CA), and T cells (with GK1.5 and 3.155 mAbs). The remaining I-A - cells were then cultured in the presence of GM-CSF (10 ng/ml). The purity of bone marrow derived DC was more than 95% as determined by flow cytometry using anti-CD11c and anti-I-A antibody (not shown). Determination of protease activities Cells were lysed in 0.1% Triton X-100 in 0.9% NaCl; extracts were then examined for protease activities using the following substrates: a) Z-Arg-Arg-βNA (for cathepsin B, at pH 6.0), b) denatured hemoglobin (cathepsin D/E, pH 3.0), c) Arg-βNA (cathepsin H, pH 6.8), d) Z-Phe-Arg-MCA (cathepsin J, pH 7.5), e) Z-Phe-Arg-MCA (cathepsin L, pH 5.5), f) Gly-Phe-βNA (DPPI or cathepsin C, pH 5.5), g) BLT ester (BLT esterase, pH 7.5), and h) Suc-Ala-Ala-Pro-Phe-SBz and Suc-Phe-Leu-Phe-SBz (chymotrypsin-like proteases, pH 7.5). Samples were incubated at the indicated pH and enzymatic activities were assessed by colorimetric or fluorogenic changes [ 31 ]. Enzymatic activities were expressed as nmol/min/mg soluble protein, in which protein concentrations were measured by the bicinchoninic acid method using bovine serum albumin as a standard [ 32 ]. Ag presentation and T cell stimulation assays XS52 DC were γ-irradiated (2000 rad) and then pulsed for 8 hr with 100 μg/ml of PPD (kindly provided by Dr. E. Schmitt, Mainz, Germany) in the presence of each of the following inhibitors (or vehicle controls): a) pepstatin A (100 μg/ml, Sigma, St. Louis, MO), b) DCI 100 μM, Sigma), c) E-64 (100 μM, Sigma), d) DMSO (1%), and e) NH 4 CL (15 mM). Subsequently, the XS52 cells were washed 3 times with PBS to remove unbound PPD and then cultured in 96 round-bottom well-plates (10 4 cells/well) with either the PPD-reactive Th1 or Th2 clone (10 5 cells/well) in the presence of the same inhibitor at the above concentration. In some experiments, XS52 DC were pulsed overnight with PPD in the presence of an inhibitor and then fixed with 0.05% glutaraldehyde in PBS for 30 seconds at 4°C; the fixation reaction was stopped by adding 0.1 M L-lysine. These XS52 cells were then washed with PBS and examined for their ability to activate Th1 or Th2 clones in the absence of protease inhibitors. In order to determine the mechanism of action for pepstatin A, XS52 cells were pulsed in its presence with PPD either in a native form or following digestion with trypsin-conjugated sepharose beads (Pierce, Rockford, IL) for 15 minutes at 37°C. We also examined the effect of added pepstatin A on the capacity of XS52 cells to activated allogeneic T cells isolated from CBA mice (Jackson Laboratories). Samples were pulsed for 18 hr with 1 μCi of 3 H-thymidine and then harvested using an automated cell harvestor. RT-PCR Analysis mRNA expression for cathepsin D was examined by RT-PCR. RNA isolation, reverse-transcription, and cDNA amplification were carried out as previously described [ 33 ]. The following primers were designed based on the published sequence of murine cathepsin D [ 34 ]: 5'-GGTCAGAGCAGGTTTCTGGG-3' and 5'-GCTTTAAGCTTTGCTCTCTTCGGG-3'. After 25 cycles of amplification, PCR products were analyzed in 1% agarose gel electrophoresis containing 2 μg/ml ethidium bromide. Other experimental conditions, including primer sequences for the β-actin control, are described elsewhere [ 33 ]. Results DC exhibit several different protease activities and they process the complex protein Ag PPD into antigenic peptides In the first set of experiments we sought to identify which protease activities were expressed by DC. A panel of synthetic peptide and protein substrates was incubated with extracts prepared from three DC populations: the XS52 DC line, 4F7 + splenic DC, and GM-CSF-propagated bone marrow DC. As noted in Table 1 , each DC population exhibited all tested protease activities, including cathepsins B, C, D/E, H, J, and L, BLT esterase, and chymotrypsin-like proteases. Each protease activity in DC was substantially higher (up to 20 fold) than that detected in the BW5147 thymoma cell line, a line that expresses relatively low levels of protease activities. Moreover, cathepsin D/E activity was undetectable (<1 nmol/min/mg) in Pam 212 keratinocytes and 7–17 DETC (data not shown), indicating further cell type-specificity. These results demonstrate that DC produce a variety of protease activities and at relatively high levels. Table 1 Protease Profiles Expressed by Several DC Populations Protease XS52 DC Splenic DC Bone Marrow DC BW5147 Thymoma Cells Cathepsin B 1 133 ± 39 2 123 ± 3.3 121 ± 3.3 1.5 ± 0.08 Cathepsin C 34 ± 7 16 ± 4 0.4 ± 0.1 <0.01 Cathepsin D/E 34 ± 6 30 ± 14 22 ± 2 1.6 ± 0.1 Cathepsin H 2.8 ± 0.8 3.5 ± 0.7 1 ± 0.2 0.9 ± 0.2 Cathepsin J 26 ± 0.3 0.7 ± 0.3 3.0 ± 0.1 0.2 ± 0.09 Cathepsin L 14 ± 0.6 26 ± 11 19 ± 0.6 0.6 ± 0.08 BLT esterase 25,000 ± 400 58,000 ± 4,000 21,300 ± 100 <100 Suc-FLF-SBz esterase 1,900,000 ± 61,000 310,000 ± 10,800 1,150,000 ± 10,200 12,000 ± 100 Suc-AAPFSBZ esterase 433,000 ± 2,900 134,000 ± 7,300 360,000 ± 6,100 3,400 ± 600 1 Extracts prepared from the indicated cell types were examined for protease activities using a panel of standard substrates. 2 Enzymatic activities are expressed as nmol/min/mg soluble protein. Data shown represent the mean ± SD from three independent preparations. We next asked whether DC are capable of digesting a complex protein Ag into antigenic products. In this regard, it has been reported previously that the original XS52 DC, as well as clones derived from this line, are capable of presenting KLH to the KLH-specific Th1 clone HDK-1 [ 23 ]. These results, however, did not fully test the processing capacity because it remained uncertain whether the conventional KLH preparation, which also contained many small molecular weight species, was indeed "processed" before effective presentation. For this reason, we developed a new experimental system using two PPD reactive T cell clones, a Th1 clone LNC.2F1 and a Th2 clone LNC.4K1. The advantage of PPD lies in the relative certainty of its purity. When pulsed with native PPD for 8 hr, XS52 DC were capable of stimulating both T Cell clones effectively. In dose-response experiments (Fig 1A ), XS52 DC induced maximal activation of both T cell clones at 25–100 μg/ml of PPD, whereas no significant activation was observed, even at higher concentrations, in the absence of XS52 DC (data not shown). Importantly, chloroquine (100 μM) inhibited completely the capacity of XS52 cells to activate both Th1 and Th2, T cell clones (Fig. 1B ), indicating the requirement for processing of PPD in an acidic environment. These observations indicate that XS52 DC do possess the capacity to digest a complex protein Ag into an immunogenic Ag. Figure 1 XS52 DC are capable of presenting native PPD effectively to T cells: (A) XS52 DC were γ-irradiated and then pulsed for 8 hr with the indicated concentrations of PPD. The PPD-reactive Th1 clone (diamonds) or Th2 clone (squares) (10 5 cells/well) was cultured for 2 days with PPD-pulsed XS52 cells (10 4 cells/well). (B) Following a 3 hr incubation with or without chloroquine (100 μM), XS52 DC were pulsed with PPD (100 μg/ml) in the presence or absence of chloroquine (100 μM) and then examined for their capacity to activate the PPD-specific Th1 and Th2 clones. Data shown are the mean ± SD (n = 3) of 3 H-thymidine uptake. Baseline proliferation of γ-irradiated XS52 DC alone was <300 cpm. Pepstatin A inhibits the capacity of XS52 DC to present native PPD to T cells To identify the proteases responsible for processing PPD, we employed three inhibitors: pepstatin A (aspartic acid protease inhibitor), DCI (serine protease inhibitor), and E-64 (cysteine protease inhibitor). XS52 DC were pulsed for 8 hr with native PPD in the presence of each inhibitor and then examined for the capacity to activate PPD-reactive Th1 and Th2 clones. To ensure a maximal effect, inhibitors were also added to cocultures of XS52 DC and T cells. As noted in Figure 2A , pepstatin A (100 μg/ml) almost completely blocked the capacity of XS52 cells to stimulate both T cell clones. When XS52 DC were pretreated with pepstatin A only during the 8 hr of Ag pulsing (but not during the subsequent coculture with T cells), we also observed significant, albeit less effective, inhibition (data not shown). By contrast, neither DCI nor E-64 caused any significant inhibition (Figure 2A ). No inhibition was observed after treatment with 1% DMSO or 15 mM ammonium chloride alone, which was used to dissolve the above inhibitors. With respect to the mechanism of pepstatin A inhibition, the XS52 DC remained fully viable after 8 hr pre-incubation with pepstatin A (Figure 2B ), thus excluding the possibility that pepstatin A had simply killed the XS52 DC. When pepstatin A was added to XS52 DC that had been pulsed with PPD and then fixed with paraformaldehyde, no inhibition was observed (Figure 3A ). Moreover, pepstatin A failed to affect the capacity of XS52 DC to stimulate allogeneic T cells in a primary mixed lymphocyte reaction (Figure 3B ); making it unlikely that pepstatin A had impaired the T cell-stimulatory capacity of XS52 DC. Finally, pepstatin A treatment was only effective when the native form of PPD was used as complex Ag, whereas it caused no inhibition when trysin-digested PPD fragments were employed (Figure 3C ). Based on these observations, we concluded that pepstatin A had primarily inhibited the processing events. Figure 2 Pepstatin A inhibits the capacity of XS52 DC to present native PPD: (A) γ-irradiated XS52 DC were pulsed with PPD (100 μg/ml) in the presence or absence of each protease inhibitor (100 μg/ml pepstatin A, 100 μM DCI, or 100 μM E-64) or vehicle alone (1% DMSO or 15 mM NH 4 Cl). XS52 DC were then cultured for 2 days with the PPD-reactive Th1 or Th2 clone in the continuous presence of the same inhibitor or vehicle alone. Data shown are the mean ± SD (n = 3) of 3 H-thymidine uptake in three representative experiments. (B) XS52 DC were incubated with each of protease inhibitor (100 μg/ml pepstatin A, 100 μM DCI, or 100 μM E-64) or vehicle alone (1% DMSO or 15 mM NH 4 Cl) for 16 hrs. Subsequently, cells were harvested and their viability was measured by trypan blue. Figure 3 Failure of pepstatin A to inhibit the Ag presenting capacity of PPD-pulsed and fixed XS52 DC: (A) γ-irradiated XS52 DC were pulsed with PPD and then fixed with paraformaldehyde (left panels). Alternatively, XS52 DC were first fixed and then pulsed with PPD. Subsequently, the XS52 DC were cultured with the PPD-specific Th1 or Th2 clone in the presence or absence of pepstatin A. Data shown are the mean ± SD (n = 3) of 3 H-thymidine uptake. (B): Allogeneic splenic T cells isolated from CBA mice (5 × 10 5 cells/well) were cultured for 4 days with the indicated numbers of γ-irradiated XS52 DC in the presence or absence of pepstatin A. Data shown are the mean ± SD (n = 3) of 3 H-thymidine uptake. (C): γ-irradiated XS52 DC were pulsed for 8 hr with either native PPD or trypsin-digested PPD in the presence or absence of pepstatin A. XS52 DC were then cocultured for 4 days with PPD-reactive Th1 or Th2 clones in the presence or absence of pepstatin A. Cocultures were then pulsed for 18 hr with 3 H-thymidine and then harvested using a β-counter. Functional role of cathepsin D/E in the processing of PPD by XS52 DC To identify the protease(s) inhibited by pepstatin A, XS52 DC were pretreated for 1 hr with pepstatin A (100 μg/ml), and extracts prepared from these cells were then examined for enzymatic activities. As noted in Figure 4 , 1 hr pretreatment with pepstatin A was sufficient to block cathepsin D/E activity significantly (>70%). Pepstatin A also inhibited, albeit less effectively, cathepsin J activity and it had no significant effect on other tested protease activities. On the other hand, DCI and E64 were highly inhibitory of the chymotrypsin-like activities as well as cathepsin B, J, and/or L activities, but they did not inhibit cathepsin D/E. These results corroborate previous reports that pepstatin A inhibits cathepsin D/E activity relatively selectively [ 35 ]. Thus, it appears that cathepsin D/E is the primary target of pepstatin A, with the implication that these proteases play important roles in processing PPD by XS52 DC. Figure 4 Pepstatin A Inhibits selectively the cathepsins D/E. XS52 DC were pretreated for 60 min with each of protease inhibitors or vehicles. After extensive washing, the cells were extracted and subsequently examined for protease activities. Data shown are % inhibition compared with untreated control cells. Cathepsins D and E are prototypic aspartic acid proteases, which exhibit maximal enzymatic activities at acidic pH. Because both digest denatured hemoglobin effectively, the substrate used to measure cathepsin D/E activity, and because both are equally susceptible to pepstatin A treatment, it remained uncertain where processing of PPD in XS52 DC was mediated by cathepsin D, or cathepsin E, or both. As a first step to answer this question, we detected cathepsin D mRNA by RT-PCR in the XS52 DC line, as well as in 4F7 + splenic DC and a bone marrow derived DC line, indicating that DC do possess the capacity to produce cathepsin D (Figure 5 ). Figure 5 DC constitutively express cathepsin D mRNA. Total RNA isolated from the indicated cell types were subjected to RT-PCR analysis for cathepsin D and β-actin. Data are shown, including bone marrow DC and macrophages, as well as 4F7 + splenic DC (splDC), products after 25 cycles of amplification. Conclusion The experiments reported in this study provide new information with respect to complex Ag processing by DC. First, the long-term DC line, XS52 DC, was capable of processing PPD into immunogenic peptides, in the complete absence of other cell types. Although previous studies using several different DC preparations have documented similar results (3–12), this is the first report validating the Ag processing capacity of DC, in the absence of contaminating cells. Second, we have characterized the protease profiles expressed by DC. XS52 DC, 4F7 + splenic DC, and bone marrow-derived DC, all exhibited significant protease activities for cathepsins B, C, D/E, H, J, and L, BLT esterase, and chymotrypsin. Thus, DC possess the capacity to produce a family of protease activities. Finally, pepstatin A, but not other protease inhibitors, abrogated almost completely the ability of XS52 DC to digest native PPD into an antigenic product, suggesting an important role for pepstatin A-sensitive proteases (most likely cathepsin D and/or E) during Ag processing by DC. Taken together, these results reinforce the concept that DC are fully capable of processing complex protein Ag into antigenic peptides. As described before, macrophages and B cells have been reported to employ cathepsins B, D, and E primarily to digest complex protein Ag, such as ovalbumin (OVA), hen egg white lysozyme (HEL), myoglobin, exogenous IgG, and Staphylococcus aureus nuclease (17–22). Here we report that DC also employ cathepsin D and/or E to digest PPD into an immunogenic Ag-product. This conclusion is supported by several lines of evidence: a) pepstatin A, but not other protease inhibitors, completely blocked the presentation of intact PPD by XS52 DC to PPD-reactive Th1 and Th2 clones, whereas it did not affect the presentation of PPD fragments; b) pepstatin A pretreatment inhibited cathepsin D/E activity selectively among the DC-associated protease activities; and c) all tested DC preparations expressed cathepsin D mRNA constitutively. In this regard, DC isolated from the mouse thoracic duct have been reported to produce neglible, if any, cathespin D immunoreactivity (assessed by immunofluorescence staining), whereas peritoneal macrophages produced relatively large amounts [ 14 ]. Also comparable levels of cathepsin D/E activity were detected in extracts from bone marrow-derived DC and from bone marrow-derived macrophages (data not shown). This discordance may reflect differences in the DC preparations tested and/or in the assays employed to detect cathepsin D. Nevertheless, our observations indicate that DC employ cathepsin D/E to degrade some protein Ag, with the implication that pepstatin A and other cathepsin D/E inhibitors [ 36 ] may be useful to prevent and even to treat unwanted hypersensitivity reactions against such protein Ag. It is important to emphasize that different protein Ag may be degraded by different proteases in DC. Moreover, DC isolated from different tissues or in different maturational states may employ different proteases. For example, murine DC isolated from the thoracic are unable to digest human serum albumin effectively [ 14 ], and murine splenic DC purified following overnight culture have failed to degrade KLH significantly into a TCA-soluble form [ 13 ]. Moreover, several reports document that LC lose their Ag processing capacity as they mature in culture [ 3 - 6 , 12 ]. Thus, it will be interesting to compare DC from different tissues and in different states of maturation for their protease profiles and susceptibilities to pepstatin A treatment. We believe that the experimental system described in this report will provide unique opportunities to study the function of proteases and the regulation of their production in DC. Competing Interests None declared. Author's Contributions Dr. Mohamadzadeh is the major contributor (15%) of the experimental data and a rough draft of the paper. The next three intermediate authors' contributed remaining data and advice. Dr. Luftig was the overall individual who directed the several drafts and contributed to providing a new set of references to the manuscript.

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544856

Xenon prevents cellular damage in differentiated PC-12 cells exposed to hypoxia

Background The neuroprotective effect of xenon has been demonstrated for glutamatergic neurons. In the present study it is investigated if dopaminergic neurons, i.e. nerve-growth-factor differentiated PC-12 cells, are protected as well against hypoxia-induced cell damage in the presence of xenon. Results Pheochromocytoma cells differentiated by addition of nerve growth factor were placed in a N 2 -saturated atmosphere, a treatment that induced release of dopamine, reaching a maximum after 30 min. By determining extracellular lactate dehydrogenase concentration as marker for concomitant cellular damage, a substantial increase of enzymatic activity was found for N 2 -treated cells. Replacement of N 2 by xenon in such a hypoxic atmosphere resulted in complete protection against cellular damage and prevention of hypoxia-induced dopamine release. Intracellular buffering of Ca 2+ using the Ca-chelator 1, 2- bis (2-Aminophenoxy)ethane-N,N,N',N'-tetraacetic acid tetrakis (acetoxymethyl) ester (BAPTA) reduced the neuroprotective effect of xenon indicating the essential participation of intracellular Ca 2+ -ions in the process of xenon-induced neuroprotection. Conclusions The results presented demonstrate the outstanding property of xenon to protect neuron-like cells in a hypoxic situation.

Background Originally, hypoxia/ischemia-induced alterations in neuronal function have been attributed to be an over-release of neurotransmitters, including dopamine and glutamate. Many studies have been performed on the mechanisms of glutamate-induced neuronal damage [ 1 , 2 ] but relatively few have investigated the hypoxia-induced damage in dopaminergic neurons [ 3 - 6 ]. In recent years several lines of evidence have suggested that effects other than excitotoxic mechanisms may also participate in hypoxia-induced cell damage such as cortical spreading depression [ 7 , 8 ]. Rat pheochromocytoma (PC-12) cells are catecholaminergic, excitable cells that have been widely used as an in vitro model for neuronal cells [ 9 ] possessing both D1- and D2-dopamine receptors [ 10 ]. In these cells hypoxia causes a transient release of dopamine resulting from a complex cellular response consisting of increased dopamine release and reduced uptake rate. Such increased dopamine concentration has been shown to be associated with cellular damage indicated by an elevated release of lactate dehydrogenase (LDH) from the cells [ 6 , 11 ]. Numerous approaches have been undertaken to reduce hypoxia-induced neurotoxicity [ 2 , 12 ]. The pathological increase of extracellular neurotransmitter concentration presents probably one of the first indicators for such damage although it is not clear to what extent it contributes directly. Thus, a reduction or even complete suppression of such an increase of neurotransmitter concentration after the primary neuronal damage would suggest a high probability for protection from the hypoxic insult. Recently, we have shown that the noble gas xenon prevents in hypoxic cortical neurons hypoxia-induced cell damage and glutamate release [ 13 , 14 ]. Such neuroprotective potential has been confirmed by Ma et al. [ 15 ] and Wilhelm et al.[ 16 ], and related to its property of being an NMDA-receptor antagonist. In the present paper, however, we show that also in the dopaminergic PC-12-system xenon exhibits profound neuroprotective properties for hypoxic cells thus underlining its usefulness as a general neuroprotectant. Results Release of dopamine under hypoxic conditions Cells kept under normoxic conditions did not release dopamine during the time period studied. If, however, they were kept in an atmosphere consisting of 100% nitrogene, considerable amounts of dopamine were found in the extracellular space reaching a maximum at 30 min of incubation, followed by a subsequent decrease. If under the same conditions nitrogen was replaced by xenon, no such increase in dopamine concentration was found (Fig. 1a ). The level of extracellular dopamine remained as low as in cells kept under normoxic conditions. Hypoxia-induced cellular damage In order to test if such hypoxia damaged the cells, extracellular LDH was determined after a two-hour period of treatment. A low level of LDH was found in cells kept under normoxic conditions whereas cells kept under nitrogen showed a significant release of LDH indicating severe cellular damage (Fig. 1b ). If instead of nitrogen xenon was used to create such hypoxic condition, the LDH level remained at the same low level as in controls. Effect of the dopamine reuptake inhibitor GBR 1209 Hypoxia-induced extracellular increase of dopamine could be caused either by elevated release of dopamine or by a reduced, or even inhibited, dopamine uptake. If hypoxia caused faster release but did not interfere with uptake, uptake-inhibitors would cause a higher concentration of dopamine in the extracellular space. On the other hand, if the release was constant but the re-uptake inhibited by hypoxia, additional inhibition of uptake by inhibitors would have no or little effect. In the presence of 5 nM of the dopamine reuptake inhibitor GBR 1209 the extracellular dopamine concentration did not change in a normoxic or xenon environment. However, in nitrogen the extracellular dopamine concentration did not reach exactly the same value as in pure nitrogen, the dopamine level was slightly but significantly reduced, thus supporting the view that hypoxia-induced extracellular dopamine increase was caused by an enhanced release of dopamine and – to a lesser extent – an interference with the uptake mechanism (Fig. 2 ). Effects of the dopamine receptor antagonists SCH 23390 and sulpiride To test if indeed the hypoxia-induced increase of extracellular dopamine itself caused the cell damage measured by the increase in extracellular LDH, dopamine receptor antagonists were used. Since they prevent dopamine binding they should provide protection of dopamine-induced damage. If the D1 receptor antagonist SCH 23390 was used during the incubation period, then at the highest dose of 10 nM, a reduction of nitrogen-induced external LDH-increase could be seen. However, even at this highest applied dose of SCH 23390, there was still only a less than 50% reduction in extracellular LDH (Fig. 3a ). If, on the other hand, the D2 receptor antagonist sulpiride was used, no reduction in the nitrogen-induced LDH-release was found (Fig. 3b ). Both compounds did not change the xenon-induced suppression of cellular damage. Cellular damage induced by external addition of dopamine To analyze if indeed the increased external dopamine was detrimental to cells, they were incubated in the presence of 100 nM dopamine, either for 30 min followed by 120 min in normal medium, or continuously for 150 min. As shown in fig. 4 , column (c), even the 30 min incubation with 100 nm dopamine (the lesser of the two dopamine challenges) was sufficient to cause considerable cell damage. Such damage was further increased if dopamine was present for the whole period of time of 150 min (column (e). We asked then if xenon not only prevented the release of dopamine in a hypoxic situation but could even reduce the damage caused by external dopamine. Cells were incubated for 30 min in normal buffer containing 100 nM dopamine followed by 120 min in xenon-saturated buffer, without dopamine. As shown in column (d), the dopamine-induced damage to the cells as seen in column (c) was significantly reduced. If the cells were incubated for 150 min in xenon-saturated buffer containing dopamine, even under those conditions the damage was low compared to cells exposed to dopamine in normal buffer (column (f)). Buffering of intracellular Ca 2+ -ions using BAPTA In order to test if changes in intracellular Ca 2+ were required for the neuroprotective effect of xenon, cells were incubated with the cell-permeant Ca-chelator BAPTA-AM. As shown in fig. 5 , chelating intracellular Ca 2+ does not damage the cells per se (control + 10 μM BAPTA). Surprisingly, such chelation reduces significantly the neuroprotective effect of xenon, indicating an essential role for intracellular Ca 2+ for this effect to occur. A slight but significant reduction in cellular damage is observed when BAPTA-treated cells are incubated in nitrogen-saturated buffer. Comparison with another dopaminergic cell system To exclude that the results obtained were limited to the PC-12-system itself, hypoxia-induced dopamine release and cell damage was investigated in rat embryonic primary mesencephalic cell cultures that are known to contain 0.5 – 1.5% of dopaminergic cells [ 26 ]. As shown in fig. 6 , in an hypoxic atmosphere a very similar pattern of dopamine and LDH release is obtained compared to PC-12 cells. Xenon prevents also in these primary cells the hypoxia-induced neurotransmitter and LDH release. Discussion In hypoxia/ischemia a key feature of secondary damage after the primary neuron-damaging event is the over-release of neurotransmitters [ 17 ]. Consequently, an interference with the hypoxia-induced release mechanism with respect to its control systems may be extremely useful to reduce cellular damage. The results presented here show that xenon has such properties, namely to prevent cellular damage and neurotransmitter release in a hypoxic situation thus qualifying it as an almost ideal early neuroprotectant. Concerning possible cellular targets for xenon, a first indication for the participation of Ca 2+ -regulated events was obtained when it was shown that xenon blocked cells in metaphase and that the block could be lifted by artificial small intracellular Ca 2+ - increases [ 18 ]. Since the CaM KII complex is known to play a decisive role in the metaphase/anaphase transition, it was tested if the CaMKII-inhibitor KN-93 had likewise metaphase-blocking properties. Such effects were obtained [ 19 ]. It is well known that in dopaminergic differentiated PC-12 cells, the CaMKII complex is involved in the regulation of neurotransmitter release [ 20 - 22 ] as well as its participation in a multitude of other Ca 2+ -dependent regulatory events [ 23 ]. Thus, it appears to be plausible that one of the targets for xenon might be the CaMKII complex, either directly or via interference with other Ca 2+ -dependent systems. One of those may be the Ca 2+ /calmodulin-activated calcineurin system that has been implicated in the regulation of monoamine release [ 24 ]. Alternatively, xenon might interact upstream of these regulatory systems with other Ca 2+ -dependent events required to occur in hypoxia-induced cell damage. Such a scenario is suggested by our demonstration that the neuroprotective effect of xenon is strongly reduced if PC-12 cells are loaded with BAPTA. Thus, at present all evidence obtained by us [ 13 , 14 , 18 , 19 ] and others [ 15 , 16 ] establish a complex and composite picture of targets susceptible to xenon including NMDA receptors, Ca 2+ -regulating and -regulated systems up to the activaton of transcription factors whereby such targets are probably not essentially and sequentially linked to each other. To summarize briefly our main findings: (1) The presence of xenon blocks hypoxia-induced dopamine release in dopaminergic cells. (2) Hypoxia-induced dopamine increase is caused by an enhanced release of dopamine rather than a reduced uptake of dopamine. (3) When measuring LDH release as a marker of cellular damage, xenon was found to block such release, which suggests that xenon reduces hypoxia-induced cellular damage. (4) Increased extracellular dopamine can damage dopaminergic cells directly. This is mainly mediated by D1 receptor agonism rather than D2. (5) Such direct extracellular dopamine-induced damage can be reduced by the presence of xenon, even when the increase in extracellular dopamine has not been caused by an episode of cellular hypoxia. (6) The above described protective effects of xenon depend on the presence of calcium ions. Further studies will show if indeed in the hypoxic cell multiple intracellular targets exist for xenon and how they are orchestrated together to result in cellular protection. Conclusions Based on the present results obtained with NGF-differentiated PC-12 cells and on the literature cited in this paper, xenon appears to be a neuroprotectant for a broad spectrum of neuronal cells; given its proven non-toxicity based on its long clinical use, it may come close to fulfilling the requirements for an ideal or "gold standard" neuroprotectant. Methods Cells Rat pheochromocytoma cells (PC-12) were maintained in RPMI 1640 medium containing 5% fetal calf serum, 10% horse serum, at 37°C, 5% CO 2 . For experiments, cells were seeded in 24-well plates at a density of 1 × 10 5 cells/well and nerve-growth-factor (Promega, Heidelberg, Germany) was added (0.4 μg/ml) whereupon cells entered differentiation. They were used on day five after the addition of growth factor [ 25 ]. Primary dopaminergic cells from rat embryonic brain were prepared as described (26) and used on day 14. Determination of dopamine and LDH Hypoxia-treatment was performed as described [ 13 ]. Samples from individual wells were taken at the intervals indicated and deproteinated using 5% perchloric acid (1:1 = vol/vol). Supernatants were transferred to Eppendorff tubes and the same volume (0.5 ml) of 0.4 M perchloric acid was added, mixed on vortex and centrifuged (6000 rpm, 3 min) to remove cell debris. Dopamine concentration was determined by high-pressure liquid chromatography (Bio-Tek, Neufahrn, Germany) using an electrochemical detector (Biometra, Göttingen, Germany). Cellular damage after the experiment was assessed by measuring spectrophotometrically the concentration of LDH in the original supernatant, before the addition of perchloric acid (Roche Diagnostics, Mannheim, Germany). Chemicals Gases were supplied by AGA-Linde (Berlin, Germany). 1,2- bis (2-Aminophenoxy)ethane-N,N,N',N'-tetraacetic acid tetrakis (acetoxymethyl) ester (BAPTA-AM) was purchased from Molecular Probes, (Leiden, The Netherlands), and all standard chemical products were obtained from Merck (Berlin, Germany). Statistical analysis All experiments were repeated at least five times, i.e. in five different plates on five different days. The data were presented as means ± SEM. The results of multiple groups were analyzed using one-way ANOVA with Dunnett's multiple comparison post test or two-way ANOVA with Bonferroni posttests using GraphPad Prism version 3.00 for Windows, GraphPad Software, San Diego California USA. Differences with p values less than 0.05 were considered statistically significant. Authors' contributions CP conceived the study, participated in its design and coordination, carried out the cellular studies involving the various gas treatments, participated in the preparation of the cells, and drafted the manuscript. PB and WS participated in the design of the experiments and the gas applications, JM performed neurotransmitter analysis and LDH determinations, and WK participated in the design of the study and performed the statistical analysis. All authors read and approved the final manuscript.

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529304

Killing Bugs at the Bedside: A prospective hospital survey of how frequently personal digital assistants provide expert recommendations in the treatment of infectious diseases

Background Personal Digital Assistants (PDAS) are rapidly becoming popular tools in the assistance of managing hospitalized patients, but little is known about how often expert recommendations are available for the treatment of infectious diseases in hospitalized patients. Objective To determine how often PDAs could provide expert recommendations for the management of infectious diseases in patients admitted to a general medicine teaching service. Design Prospective observational cohort study Setting Internal medicine resident teaching service at an urban hospital in Dayton, Ohio Patients 212 patients (out of 883 patients screened) were identified with possible infectious etiologies as the cause for admission to the hospital. Measurements Patients were screened prospectively from July 2002 until October 2002 for infectious conditions as the cause of their admissions. 5 PDA programs were assessed in October 2002 to see if treatment recommendations were available for managing these patients. The programs were then reassessed in January 2004 to evaluate how the latest editions of the software would perform under the same context as the previous year. Results PDAs provided treatment recommendations in at least one of the programs for 100% of the patients admitted over the 4 month period in the 2004 evaluation. Each of the programs reviewed improved from 2002 to 2004, with five of the six programs offering treatment recommendations for over 90% of patients in the study. Conclusion Current PDA software provides expert recommendations for a great majority of general internal medicine patients presenting to the hospital with infectious conditions.

PDAs (Personal Digital Assistants) are becoming widely used in medicine. A survey done by the America College of Physician predicted that 67% of physicians would be using PDAs by the end of 2002 [ 1 ]. These devices are used not only by the new generation of residents and physicians, but by all ages and all specialties [ 2 , 3 ]. PDA's are used not only as personal planners and contact lists but also for medical purposes such as patient billing and bedside medical references [ 4 , 5 ]. Physicians who have rapid and easy access to information are increasingly using that data when treating patients. This should ensure appropriate therapy and also reduce medical errors by ensuring proper dosing and treatment choices [ 6 ]. One medical specialty which has focused on PDA's application in medicine is infectious diseases [ 7 ]. There are numerous infectious disease programs which provide both expert recommendations regarding antibiotic choice as well as background information (epidemiology, diagnostic studies, source of pathogens, etc). We sought to determine the how often expert recommendations were available from the PDA infectious disease resources for the infectious conditions seen on our general internal medicine teaching service over a 4 month period of time. A secondary goal was to determine the change in the software over a 15 month period to provide expert recommendations. Methods Clinical Setting Miami Valley Hospital is an 827 bed secondary and tertiary referral center, in Dayton, Ohio. It is an urban hospital that averages over three-thousand patient admissions per month. The internal medicine resident teaching service consists of two teams, each team with 2 senior residents and 2 interns who are supervised by an attending physician. There is a senior resident and intern on call in the hospital at all times. Patients were eligible to be admitted to resident's service if they were established within the Medical-Surgical Health Center of Miami Valley Hospital, if they were uninsured or if they had insurance but were without a local physician (a.k.a. private unattached patients). The general medicine teaching service averages approximately eight admissions per twenty-four hour period. Patients and Problems The patients were screened prospectively over a four month period (July 2002 through October 2002). The admitting senior resident prospectively recorded the chief complaint and initial differential diagnosis for each patient. One of us (SDB), as the chief resident during these months, gathered the data during morning report. Patients were considered appropriate for the study if they had a leading diagnosis or active alternatives that suggested an infectious disease at the time of admission. Cases selected were then assigned categories based on the "major clinical syndromes" from Mandell, Douglass and Bennett's Principles and Practice of Infectious Disease (PPID) (8) (Table 1 ). Syndromes were categorized by organ system and were considered only if they would commonly require hospitalization (for example, sinusitis was not evaluated). Table 1 Appropriate inpatient clinical syndromes according to PPID (8) and the distribution of patients admitted to the general medicine teaching service from July through October of 2002. Major Clinical Syndromes Patients Fever Fever of Unknown Origin (Neutropenia) 6 (2) Upper Respiratory Pharyngitis 2 Infections of head and neck 1 Pleuropulmonary Acute Bronchitis 16 Chronic Bronchitis 20 Acute Pneumonia 31 Empyema 2 Chronic Pneumonia 1 Cystic Fibrosis 1 Urinary Tract 22 Sepsis Syndrome 3 Peritonitis and Other Intra-abdominal Infections 3 Cardiovascular Endocarditis 2 Central Nervous System Acute Meningitis 6 Encephalitis 1 Brain Abscess 1 Soft Tissue Cellulitis and subcutaneous Tissue Infections 40 Lymphadenitis and Lymphangitis 2 Gastrointestinal Inflammatory Enteritides 20 Abdominal Symptoms and Fever 7 Bone and Joint Infectious Arthritis 1 Osteomyelitis 8 STD Prostatitis, Epididymitis and Orchitis 1 Eye Peri-ocular Infections 2 HIV Pulmonary Manifestations in HIV 5 CNS Manifestations in HIV 1 Searching the PDA A Sony Clie T615C (Palm OS) was the device used to access the software, but all programs evaluated were also available in the Pocket PC format (thus applicable to nearly 100% of PDAs in clinical use). Five PDA programs were initially searched to determine if expert recommendations were available. Software was chosen based on its availability to both the Palm OS and the Pocket PC and at the time of the initial software evaluation were the primary infectious disease programs available (since 2002 numerous other titles have been released to address infectious diseases). The PDA programs included: Sanford's Guide to Antimicrobial Therapy (SG) [ 9 ], John's Hopkins Antibiotic Guide (JHABx) [ 10 ], 5-Minute Infectious Diseases Consult ) (5MID) [ 11 ], 5-Minute Clinical Consult ) (5MCC) [ 12 ], and Pocket Medicine-Infectious Disease ) (PMID) [ 13 ]. The initial evaluation was performed with the most current software in October 2002 and reassessed in January 2004 with the latest versions of the available software. In addition, ePocrates ID ) (QID) [ 14 ] was also evaluated in January 2004 (but was not included in the October 2002 assessment as it was only available for the Palm OS at this junction). A minimum of three attempts were used to locate conditions within each program. Searching was done using either the disease name or clinical problem that had led to the patient's admission. Synonyms were used when appropriate to increase the possibility of locating a condition within each program (for example: "urinary tract infection" was the first term searched and if no results available, then "pyelonephritis" was searched next and if still no results then "kidney infection" was entered into the database). Programs that were organized according to organ system (JHABx, QID only) were searched within the appropriate organ system, while programs that listed diagnoses alphabetically were searched accordingly. Expert recommendations were considered to be present and thus counted as a positive if the software had treatment recommendations present, whether related to antibiotic decision or "supportive care." In order to determine the change in software capabilities over a 14 month period, the same patient data set was used to assess software programs in January of 2004. A comparison of the programs was then performed comparing the availability of expert recommendations. Statistical Analysis The data was collected by a single physician (SDB) and then validated independently by a second physician (TEH). The data was analyzed using descriptive statistics with simple frequencies and the confidence intervals were calculated according to standard formulas. Results Over the four month period, from July through October of 2002, there were 883 patients admitted to the resident service, of whom 212 had syndromes that were suspected on admission to be infectious in etiology (202 of which could be assigned to the pre-defined categories) (See Figure 1 and Table 1 ). Figure 1 Results of patient screened for infectious etiologies over a 4 month period. As shown in Table 2 , treatment recommendations were available in the PDA in at least one program for one-hundred percent of the patients admitted during the software evaluation in January 2004. Expert recommendations were available in all six of the programs for 52% of the patients admitted. The Sanford Guide and ePocrates ID each offered expert recommendations regarding treatment for 100% of the patients, while John's Hopkins Antibiotic Guide, 5 Minute Clinical Consultant and 5 Minute Infectious Diseases both offered expert recommendations in over 95% of the patients. Pocket Medicine-Infectious Disease offered expert recommendations for the fewest number of patients. Table 2 Number and percent of patients with infection- related clinical syndromes covered by the studied PDA programs as of January 2004. Major Clinical Syndromes Patients SG QID JHABx 5MCC 5MID PMID Total % Rec Fever 6 6 6 6 4 4 4 100 Upper Respiratory 3 3 3 3 3 3 3 100 Pleuropulmonary 71 71 71 71 71 69 31 100 Urinary Tract 22 22 22 22 22 22 0 100 Sepsis 3 3 3 3 3 3 0 100 Peritonitis 3 3 3 3 3 3 2 100 Cardiovascular 2 2 2 2 2 2 2 100 Central Nervous System 8 8 8 8 8 8 7 100 Soft Tissue 42 42 42 42 42 42 40 100 Gastrointestinal 27 27 27 27 27 27 7 100 Bone and Joint 9 9 9 9 9 9 8 100 STD 1 1 1 0 0 1 0 100 Eye 2 2 2 2 2 0 2 100 HIV 6 6 6 6 0 0 0 100 TOTALS 202 202 202 201 195 192 106 202 TOTAL % 100 100 99 97 95 52 100 95% Confidence Intervals 100% 100% 97.5% to 100% 94.5% to 99.5% 92% to 98% 45% to 59% In regards to software changes between October 2002 and January 2004, each of the programs evaluated increased the number of patients for whom expert recommendations were available Table 3 . The recommendations were not evaluated for changes in treatment over this time period, only the number of patients for whom recommendations were available was evaluated. The Sanford Guide had minimal improvements to make (initially offering expert recommendations for 96% of patients) while others improved significantly (JHABx improved from approximately 50% to over 96%). PMID, while offering treatment recommendations for the fewest number of patients, did show an improvement of 28% of the 14 month time period assessed. QID was assessed for the first time in 2004 when it was made available for both the Palm OS and Pocket PC and therefore no comparison data is available. Table 3 Improvement in expert recommendations available in October 2002 as compared with January 2004. Programs 2002 2004 Difference SG 94% 100% +6% QID NA 100% NA JHABx 61% 99% +38% 5MCC 64% 97% +33% 5MID 58% 95% +37% PMID 24% 52% +28% Discussion We were able to find expert recommendations regarding initial treatment of suspected infectious diseases on the PDA for 100% of patients admitted to the general medicine teaching service at Miami Valley Hospital over a 4 month period from July until October of 2002. As far as we know, this is the first ever prospective study of the breadth of coverage provided by PDA software for recommendations in infectious disease. Miller et al provide an excellent review and buyer's guide of many of the PDA software evaluated in this project and did sample the recommendations available for six selected infectious conditions [ 7 ]. This study should be interpreted in light of its potential limitations. First, we may have erred in our selection of which patients had infectious syndromes as the cause for admission. Patients' initial diagnoses might have been mistaken and the cause for admission was non-infectious. We have no information about how often such errors occurred. However, we attempted to assess the frequency of recommendations available for the initial diagnosis by the admitting physician rather than the discharge diagnosis. A second potential limitation to our study is that searching errors occurred. Multiple steps were taken to limit the possibility that recommendations were credited that did not correctly match with the conditions sited or that recommendations were not found that did exist. Explicit criteria were used by an evaluator (SDB) familiar with both the PDA and the aforementioned software looking for management recommendations. This usually included antibiotic recommendations and occasionally recommendations regarding further evaluation. The possibility that we did not find recommendations which were indeed available seems unlikely because of the previously mentioned points as well as a systematic approach using multiple synonyms. Furthermore, the data was independently reviewed by a second physician and no inconsistencies were identified. A third potential limitation is that of reproducibility. Since searching was done by an experienced user, searching errors would be more likely with less experienced user(s). Many of the programs require persistent use to learn the nuances and style of the programs and how to best access information. Therefore, in order for others to duplicate our results, users will need to develop some profiency with the software and be willing to perform searches using multiple synonyms. Lastly, our study may have limits to its applicability. Our patients were admitted to an inpatient general internal medicine teaching service at an urban hospital in the United States. These data probably apply to similar inpatient services elsewhere within North America, but may not apply to either other specialty services (Pediatrics, Surgery, etc) or hospitals in other parts of the world. While the limitations mentioned above apply to this study, they can also be expanded to include limitations in the software. No physician can access a software program for the first time and be expected to take full advantage of the recommendations available. It takes time and effort to maximize the clinical utility that is available on the PDA, which unfortunately, many clinicians do not accomplish. This paper was focused on treatment recommendations and did not evaluate the ability of the individual programs to assist with diagnosis. The diagnostic data and information other than treatment recommendations varies from program to program. This could be a topic for future research or may be available in other formats such as software reviews in PDA magazines. This study demonstrates that these infectious disease programs have improved over time (table 3 ). The reasons for this are several. Many of the programs were newly released in 2002 and where advertised as a "works in progress." As time passed, they had time and resources to add more clinical data to their software (JHABx being the prime example) or they have released a more recent edition of the software (5MCC, 5MID, PMID). Secondly, the researcher (SB) had more time to become familiar with each program and therefore it is possible that part of the increased available recommendations is in part a "false positive" in that it was present in 2002 but not easily located (SG for example claims to have everything in the paperback version available in the PDA version, but accessing the data may be a challenge). This, as discussed previously, is an issue with software (often due to format or search engine) and increased experience with software definitely leads to increased clinical utility (both in regards to time and amount of information located). Table 3 also demonstrates the benefit of the "auto-update" feature that many of these programs possess. As new data is added to database, the device is able to access the central database and import these changes, thus making the software more dynamic rather than static. This allows the user the ability to use the latest recommendations, rather than material which may out of date. These features, allow with the compact size, mobility of the devices and the fact that multiple references may be available on a single device are just several examples of the benefit of using a PDA's in medicine. Despite these potential limitations, our data suggests that PDAs provide expert recommendations for the majority of infectious clinical conditions encountered in practice by non-infectious disease general physicians. Since a majority of patients admitted to the hospital receive care from clinicians who are not specialists in infectious diseases, PDA's have the potential to have an impact on the quality of initial care by guiding not only the choice of antibiotics but also diagnostic testing and when to involve infectious disease specialists. Further research is needed to examine the efficiency of use; evidence supporting the recommendations, and the clinical impact of the use of these resources.

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526180

Conservation and Evolution of Cis-Regulatory Systems in Ascomycete Fungi

Relatively little is known about the mechanisms through which gene expression regulation evolves. To investigate this, we systematically explored the conservation of regulatory networks in fungi by examining the cis -regulatory elements that govern the expression of coregulated genes. We first identified groups of coregulated Saccharomyces cerevisiae genes enriched for genes with known upstream or downstream cis -regulatory sequences. Reasoning that many of these gene groups are coregulated in related species as well, we performed similar analyses on orthologs of coregulated S. cerevisiae genes in 13 other ascomycete species. We find that many species-specific gene groups are enriched for the same flanking regulatory sequences as those found in the orthologous gene groups from S. cerevisiae , indicating that those regulatory systems have been conserved in multiple ascomycete species. In addition to these clear cases of regulatory conservation, we find examples of cis -element evolution that suggest multiple modes of regulatory diversification, including alterations in transcription factor-binding specificity, incorporation of new gene targets into an existing regulatory system, and cooption of regulatory systems to control a different set of genes. We investigated one example in greater detail by measuring the in vitro activity of the S. cerevisiae transcription factor Rpn4p and its orthologs from Candida albicans and Neurospora crassa . Our results suggest that the DNA binding specificity of these proteins has coevolved with the sequences found upstream of the Rpn4p target genes and suggest that Rpn4p has a different function in N. crassa .

Introduction The diversity of modern organisms reflects and arises from an underlying molecular diversity that is only beginning to be understood. In recent years, much focus has been given to the evolution of protein coding regions, under the assumption that diversification of protein function has driven the evolution of organismal form and function. Nevertheless, the relative dearth of species-specific genes, and the seeming abundance of functionally homologous proteins in many different genomes, suggest additional mechanisms of diversification. One mechanism likely to play a significant role is variation in gene expression ( Monod and Jacob 1961 ; Wilson et al. 1974 ). Subtle alterations in the timing, location, and levels of protein synthesis can have considerable consequences at both the molecular and organismal level ( Averof and Patel 1997 ; Gompel and Carroll 2003 ; Lee et al. 2003 ). Despite the likely importance of variation in gene expression, relatively little is known about the evolution of gene-expression regulation or how this evolution contributes to organismal diversification. Much of a gene's expression pattern is dictated by flanking noncoding sequences that contain, among other things, binding sites recognized by sequence-specific nucleotide-binding proteins that modulate transcript abundance. A number of recent studies have examined the evolution of cis -regulatory elements in alignments of orthologous regulatory regions, consistently showing that these elements evolve at a slower rate than the nonfunctional DNA that surrounds them ( Hardison et al. 1997 ; Loots et al. 2000 ; McGuire et al. 2000 ; Bergman and Kreitman 2001 ; Dermitzakis and Clark 2002 ; Rajewsky et al. 2002 ; Moses et al. 2003 ). Most of these studies have been limited to closely related species whose orthologous noncoding sequences can be aligned, such that the putative cis -regulatory elements can be identified and compared. Cis -regulatory elements can be conserved in more distantly related species, even when the orthologous regulatory regions are too divergent to be accurately aligned ( Piano et al. 1999 ; Cliften et al. 2003 ; Romano and Wray 2003 ). However, without the guidance of multiple alignments, little has been gleaned about the patterns of evolution or the functional constraints that act on cis -regulatory elements over longer evolutionary timescales. Recently, several methods have been developed to dissect the regulatory networks that function within an individual species. Myriad studies have shown that functional regulatory sequences can be identified in a set of coregulated genes on the basis of the enriched fraction of those genes that contain the sequence within their flanking regions ( van Helden et al. 1998 ; Tavazoie et al. 1999 ; McGuire et al. 2000 ; Bussemaker et al. 2001 ; Sinha and Tompa 2002 ). Gene coregulation can be conserved in related species, and this conservation has been exploited for the computational prediction of cis -regulatory elements that are highly conserved ( Gelfand et al. 2000 ; Qin et al. 2003 ; Wang and Stormo, 2003 ; Pritsker et al. 2004 ; Yu et al. 2004 ). We reasoned that we could extend this approach to examine the evolution of cis -regulatory networks across species, by analyzing the orthologs of genes coregulated in S. cerevisiae . As a first step toward this goal, we have examined the simplest model of regulatory networks: the connection between groups of coregulated genes and the flanking cis -regulatory sequences that coordinate their expression. We characterized groups of coregulated S. cerevisiae genes and their orthologs in 13 additional ascomycete fungi ( Figure 1 ) and assessed the enriched fraction of those genes that contain known and novel cis -regulatory sequences. Our results strongly suggest that many of the known cis -regulatory systems from S. cerevisiae have been conserved over hundreds of millions of years of evolution ( Berbee and Taylor 1993 ; Heckman et al. 2001 ). Based on these observations, we present a number of models for the mechanisms of cis -regulatory evolution. Figure 1 Fungal Phylogeny The phylogenetic tree shows the 14 different fungi analyzed in this study. The topology of the tree was based on Kurtzman and Robnett (2003) , and the branch lengths represent the average of maximum-likelihood estimates of synonymous amino acid substitutions (obtained using the PAML package [ Yang 1997 ]) for the 303 proteins that had orthologs assigned in all 14 of these genomes. The closely related saccharomycete species for which the orthologous upstream regions can be aligned are labeled in orange. The source of each genome sequence is also indicated to the right of each species. Results We began by systematically characterizing known cis -regulatory elements and their gene targets in the well-studied yeast S. cerevisiae . We compiled a catalog of known and predicted S. cerevisiae cis -regulatory elements ( Dataset S1 ) in two ways. First, we retrieved 80 known consensus transcription factor-binding sites from the literature, based in part on information summarized on the Yeast Proteasome Database ( Costanzo et al. 2001 ) and the Saccharomyces Genome Database ( Weng et al. 2003 ). The majority of these sequences have been experimentally defined. Six others were identified by virtue of their conservation in the 3′ untranslated regions of closely related Saccharomyces species ( Kellis et al. 2003 ), and five downstream elements were computationally predicted from mRNA immunoprecipitation experiments ( Gerber et al. 2004 ). In addition to these known consensus sequences, we used the program MEME ( Bailey and Elkan 1994 ) to identify 597 upstream sequence motifs common to groups of predicted coregulated genes (see below). Genes that contained one or more instance of each of these sequences in the 1,000-bp upstream or 500-bp downstream regions were identified as described in Materials and Methods . We next identified and manually annotated 264 partially redundant groups of genes that are predicted to be coregulated in S. cerevisiae , based on the genes' similarity in expression, physical association with the same transcription factor, or functional relationships ( Dataset S2 ; see Materials and Methods for details). For each gene group, we systematically scored the enrichment of genes that contained each of the putative regulatory elements identified above, compared to all genes in the S. cerevisiae genome that contained that flanking sequence. Of the 80 consensus sequences, 41 were identified as significant by this criterion. Of these significant sequences, 34 were identified in the gene group known to be regulated by that element ( Dataset S3 ), suggesting an upper limit of 17% false-positive identifications. Of the 597 MEME matrices we identified, only 43 were significantly enriched in the gene group that they were identified in (see matrices in Dataset S4 ). All but four of these matrices were very similar to the consensus element known to regulate those genes (see Materials and Methods for details). Therefore, out of 19,239 motif-gene group comparisons, we recovered 34 consensus sequences and four additional MEME matrices representing known cis -regulatory elements (thus 38 of 80 known elements) and four unannotated MEME matrices that may represent novel S. cerevisiae regulatory sequences, for a total of 42 S. cerevisiae cis -elements in 35 unique gene groups. Many of these S. cerevisiae regulatory elements were shown to be conserved in orthologous regulatory regions from four closely related saccharomyces species ( Figure 1 , orange species) ( Cliften et al. 2003 ; Kellis et al. 2003 ). However, it was not known whether these elements are conserved in more distantly related species for which the intergenic regions cannot be aligned. To explore this possibility, we reasoned that many genes that are coregulated in S. cerevisiae should also be coregulated in other fungal species, and that functional cis -regulatory elements could be identified with the same methods applied to coregulated S. cerevisiae genes. Therefore, for each group of coregulated S. cerevisiae genes, we identified orthologs in each of 13 other fungal genomes using the method of Wall et al. (2003) . This method identifies reciprocal BLAST hits between two genomes that span more than 80% of the protein lengths, thereby providing a more conservative list of putative orthologs than a simple BLAST method. The complete set of orthologs is available in Datasets S5–S13 . For each species-specific gene group, we scored the enrichment of genes that contain each of the 80 consensus sequences or examples of the MEME matrices discovered in the orthologous S. cerevisiae genes, as described above. This procedure was performed separately on each species, so that the identification of an enriched sequence in one species was independent of its identification in the other species. Therefore, when a given sequence was enriched in the orthologous gene groups from multiple genomes, we interpreted this to reflect the conservation of the cis -regulatory system represented by that element in the corresponding species. It is important to note that we have characterized this conservation at the level of regulatory networks, which does not necessarily imply that the individual elements upstream of each gene have been perfectly conserved ( see Discussion ). Many S. cerevisiae Cis -Regulatory Systems Are Conserved in Other Fungi The patterns of cis -sequence enrichment in gene groups from each species strongly suggest that many of the genes coregulated in S. cerevisiae are also coregulated in the other fungal species. Furthermore, these patterns suggest that the expression of those genes is likely to be governed by the same cis -regulatory systems. Figure 2 shows the enrichment measured for each S. cerevisiae cis -regulatory element in the gene group it is proposed to regulate (represented by each row of the figure) in the 14 fungal species (shown in each column in the figure). (All p -values are available in Datasets S14–S46 .) All of the 42 elements were identified in the same gene groups from at least three of the four closely related saccharomycete species. The majority of these elements were identified in the orthologous genes from other hemiascomycete species as well: 31 (74%) were identified in S. castellii, 23 (56%) and 27 (64%) were found in the related species S. kluyveri and Kluyveromyces waltii, respectively, and 21 (50%) and 14 (33%) were found in Ashbya gossypii and Candida albicans, respectively. Outside of the hemiascomycete group, we identified three to four (7%–10%) of these elements in the euascomycete fungi and two (5%) in Schizosaccharomyces pombe . Notably, when an identical procedure was performed using randomized consensus sequences, zero sequences were enriched with p < 0.0002 in their respective gene group from any species (Figures S1 and S2 ). Figure 2 Conservation of Cis -Sequence Enrichment in Specific Gene Groups Gene groups from each of the 14 species that are enriched for genes whose flanking regions contain known or novel cis -sequences are represented by orange boxes. Each row represents a group of coexpressed S. cerevisiae genes and a single cis -regulatory element known or predicted to control the genes' expression, as indicated to the left of the figure. Each column in the figure represents the orthologous gene groups in 14 different fungal species. An orange box indicates that the S. cerevisiae cis -regulatory sequence listed to the left of the diagram is enriched in the denoted S. cerevisiae genes or their orthologs in each fungal genome, according to the key at the bottom of the figure. The p -values for each group are available in Datasets S14–S46 , and the number of orthologs in each gene group is available in Dataset S49 . Some cis -regulatory elements did not meet our significance cutoff for enrichment but had been previously identified as conserved in related gene groups from the closely related saccharomycete species ( Kellis et al. 2003 ), and these are denoted with a yellow box. A gray box indicates that the denoted sequence was not significantly enriched in that gene group, while a white box indicates that fewer than four orthologs were identified in the species. The rows are organized in decreasing order of the number of species in which the element was enriched. The number of regulatory systems that could be found in each species roughly correlates with the species tree, in that more cis -regulatory elements were identified in species closely related to S. cerevisiae compared to the more distantly related fungi. This result could arise from the decreased accuracy of ortholog assignment in the distantly related species, which would hinder the identification of conserved regulatory systems. However, control experiments indicate that our ability to identify each regulatory element by enrichment is largely insensitive to noise in each gene group and to the ortholog assignment parameters ( Figure S3 and unpublished data). These results therefore suggest that the number of regulatory systems conserved across species correlates with their divergence times. A handful of these cis -regulatory systems are conserved in all or nearly all of the fungal genomes. For example, the group of G1-phase cell-cycle genes from all species was significantly enriched for genes containing the upstream Mlu1-cell cycle box (MCB) ( McIntosh 1993 ). This sequence regulates the expression of the G1-phase genes from S. cerevisiae ( Moll et al. 1992 ) as well as its distant relative Sch. pombe ( Lowndes et al. 1992 ; Malhotra et al. 1993 ), strongly suggesting that the element has a similar role in the other fungi. Likewise, the Gcn4p binding site was identified in the amino acid-biosynthesis genes from all but Sch. pombe, consistent with the known involvement of Gcn4p-like transcription factors in the amino acid-starvation responses of S. cerevisiae, C. albicans, Neurospora crassa, and Aspergillus nidulans ( Hinnebusch 1986 ; Ebbole et al. 1991 ; Tazebay et al. 1997 ; Tripathi et al. 2002 ). The expression of nitrogen-catabolism genes in C. albicans, N. crassa, and As. nidulans is thought to be governed by GATA-like factors ( Kudla et al. 1990 ; Chiang et al. 1994 ; Marzluf 1997 ; Limjindaporn et al. 2003 ), as it is in S. cerevisiae ( Magasanik and Kaiser 2002 ), consistent with our ability to detect upstream GATA-binding elements in the group of nitrogen catabolism genes from these species. In the majority of cases (approximately 80%) in which a given cis -regulatory element was identified by enrichment, we could also identify in that species an ortholog of its binding protein from S. cerevisiae . Therefore, the most parsimonious model is that gene-expression regulation through the identified cis -regulatory sequence is governed by the orthologous transcription factor in each species. Novel Sequences Are Enriched in Coregulated Gene Groups from Other Fungi In many cases, we were unable to detect significant enrichment of the S. cerevisiae upstream elements in the orthologous gene groups from other species, particularly in the more distantly related fungi. One possible explanation for this observation is that, although the genes are still coregulated in these species, the cis -regulatory mechanisms that control their expression have evolved. We therefore searched the upstream regions from each group of orthologous genes for novel sequence motifs, using the program MEME ( Bailey and Elkan 1994 ) and selected matrices that were significantly enriched in the gene group in which they were identified (see Materials and Methods for details). As has been previously noted for this type of motif discovery ( Tavazoie et al. 1999 ; McGuire et al. 2000 ), the majority of the identified motifs were not significantly enriched in the appropriate gene group and may represent background sequences that are not functional. Thus, a total of 53 matrices were identified as significant in at least one species based on this criterion (the complete list of matrices and enrichment p values are available in Datasets S47 and S48 ). Over half of these were similar to known S. cerevisiae elements shown in Figure 2 and were enriched in the orthologous S. cerevisiae genes. Of the remaining motifs, two recognizably similar matrices were identified in the same gene group from multiple species, suggesting that they represent conserved regulatory systems not present in S. cerevisiae . To further examine this possibility, we scored the enrichment of genes containing examples of the 53 matrices in the orthologous gene groups from all species. This procedure identified 19 unique MEME matrices that were not identified in the S. cerevisiae genes and therefore may represent novel cis -regulatory elements in these fungi ( Figure 3 ). More than a third of these elements were also enriched in the same gene group from other species, providing additional support for their functional relevance. For example, a number of upstream sequences identified in ribosomal-protein genes were enriched in the same gene group from four or five other species, but not from S. cerevisiae . Similarly, sequences identified upstream of tRNA synthetase genes and upstream of the proteasome genes were identified in the same genes from all of the euascomycete fungi (N. crassa, Magnaporthe grisea, and As. nidulans). In the case of the proteasome genes, MEME identified the same motif upstream of orthologous genes from the related euascomycete Histoplasma capsulatum, for which partial genome sequence is available ( http://www.genome.wustl.edu/projects/hcapsulatum/ ) (unpublished data). That these sequences were identified in the same gene groups from multiple euascomycetes (but not the other species) implies that they are clade-specific. Although future experiments will be required to elucidate the exact roles of these sequences, our observations suggest that the identified cis -sequences are functionally relevant and conserved across species. Figure 3 Enrichment of Novel Sequences in Coregulated Genes from Other Species Gene groups from each of the 14 species that are enriched for genes containing novel upstream sequences identified by MEME (see Materials and Methods for details) are shown, as described in Figure 2 . Enrichment of genes that contain the cis -sequence listed to the left of the diagram is indicated by a purple box, according to the key at the bottom of the figure. Cis -Regulatory Element Positions and Spacing Are Also Conserved across Species The physical locations of many characterized S. cerevisiae cis -regulatory elements are restricted to a narrow region upstream of their target genes ( Mannhaupt et al. 1999 ; Tavazoie et al. 1999 ; McGuire et al. 2000 ; Lieb et al. 2001 ; Natarajan et al. 2001 ). This suggests that these elements must be positioned in the appropriate window of the upstream sequences, perhaps to promote proper interactions between the element's binding protein and other factors (such as nucleosomes or RNA polymerase subunits) ( Workman and Kingston 1992 ; Vashee and Kodadek 1995 ; Fry et al. 1997 ; Fry and Farnham 1999 ; GuhaThakurta and Stormo 2001 ). To characterize the upstream positions of cis -regulatory elements in S. cerevisiae, we compared the fraction of elements in 50-bp windows upstream of their target genes to the fraction of elements in the same 50-bp window upstream of all genes in the S. cerevisiae genome. (This model is required to overcome the nonrandom nucleotide distribution immediately upstream of genes in this and other species, as described in Materials and Methods .) We found that many of the S. cerevisiae cis -regulatory elements are nonrandomly distributed upstream of their target genes ( Figure 4 , blue boxes). Each element shows a different window of peak enrichment in S. cerevisiae . This likely reflects mechanistic differences between the regulatory systems that control the expression of each set of genes. Figure 4 Distribution of Cis -Regulatory Elements Upstream of Coregulated Genes The distribution of nine different sequences motifs (represented to the left of the figure by the consensus sequences and their known binding proteins) was measured in 50-bp windows within 1,000 bp upstream of the putative target genes (denoted to the right of the figure). Each colored box represents the frequency of an element in a 50-bp window upstream of the target genes compared to the element's frequency in the corresponding window of all upstream regions in each genome. Blue boxes represent sequences that matched the S. cerevisiae MEME matrices, while purple boxes represent sequences that matched the designated species-specific MEME matrices. Distributions that were significantly different from background in at least one 50-bp window ( p < 0.01) were identified using the hypergeometric distribution (as described in Materials and Methods ) and are denoted by an asterisk. In the majority of cases, when a cis -regulatory system was conserved in another species, the corresponding element had a similar upstream distribution to that seen in S. cerevisiae, in that the distributions had the same window of peak enrichment ( Figure 4 ). This is significant, as the underlying genomic distribution of many of these sequences is substantially different in each species, due in part to the different GC content of some of the genomes (unpublished data). For many regulatory systems, there was no correlation between the positions of individual elements in orthologous upstream regions from multiple species (although there were some exceptions; Figures S4 and S5 ). This indicates that the distributions of these elements have been conserved, even though the precise positions of individual elements have not ( see Discussion ). In addition to the conserved S. cerevisiae elements, many of the novel cis -sequences presented in Figure 3 also showed nonrandom distributions in the species in which they were identified ( Figure 4 , purple boxes). Thus, the positional distribution of cis -regulatory elements appears to be a general feature of cis -regulation in multiple ascomycete species. In one case, the close spacing between two cis -regulatory elements was conserved across species. Chiang et al. (2003) previously reported that the distance between the Cbf1p- and Met31/32p-binding sites upstream of the methionine biosynthesis genes is closer than expected by chance. We found this feature to be conserved in other species as well. The Cbf1p and Met31/32p elements were independently identified upstream of the methionine genes from almost all of the hemiascomycetes (see Figure 2 ). In addition, the closer-than-expected spacing between these sequences was also conserved in these species ( Figure 5 ). The spacing between elements was independent of the exact positions of the Cbf1p or Met31/32p sites in the saccharomycete species, indicated by permutation tests performed as previously described ( p < 0.05; Chiang et al. 2003 ). Thus, the close spacing between these sites is not simply due to the conserved positioning of the individual elements in each orthologous upstream region, but likely resulted from an evolutionary constraint on the distance between these sequences ( see Discussion ). Figure 5 Spatial Relationships between Cis -Regulatory Elements The mean spacing between the Cbf1p- and Met31/32p- binding sites within 500 bp upstream of the methionine biosynthesis genes (m) and of all of the genes in each genome (g) was calculated for the species indicated. The error bars represent twice the standard error, indicating the range of the estimated means with 95% confidence. The values below each plot indicate the number of binding-site pairs used in each calculation. Evolution of the Proteasome Cis -Regulatory Element in S. cerevisiae and C. albicans We were particularly interested in exploring patterns of cis -element evolution across fungi. One interesting example is the case of Rpn4p, a nonclassical Cys2-His2 zinc-finger protein known to regulate proteasome gene expression in S. cerevisiae ( Mannhaupt et al. 1999 ; Xie and Varshavsky 2001 ). For the group of S. cerevisiae proteasome genes, the enrichment of genes containing the known Rpn4p binding site was highly significant (GGTGGCAA; p < 6 × 10 –41 ). The same consensus sequence was also enriched in the orthologous upstream regions of all of the hemiascomycete fungi, but not in the upstream regions retrieved from fungi outside of the hemiascomycete group. We noticed that, in addition to the Rpn4p consensus site, a number of related hexameric sequences were also highly enriched in the orthologous upstream regions from C. albicans (unpublished data). This hinted at the possibility that a slightly different set of regulatory sequences governs the expression of the C. albicans proteasome genes. To further explore this possibility, we compared sequences found upstream of the proteasome genes from S. cerevisiae and C. albicans . To identify these sequences in an unbiased way, we first generated a species-independent “meta-matrix” based on a limited subset of the proteasome upstream regions from both species (see Materials and Methods for details). We then identified all examples of the meta-matrix upstream of the proteasome genes from S. cerevisiae and C. albicans, partitioned the sequences according to their species, and calculated two species-specific position-weight matrices ( Figure 6 ). These matrices were statistically different at the second, third, and ninth positions ( p < 0.01; see Materials and Methods for details) and indicated that the C. albicans matrix had less basepair specificity at these positions. Figure 6 Position-Weight Matrices Representing Proteasome C is -Regulatory Elements Sequences within 500 bp upstream of the S. cerevisiae or C. albicans proteasome genes that matched the species-independent meta-matrix were identified as described. The identified sequences were used to generate sequence logos ( Crooks et al. 2004 ) to represent the set of cis -sequences from S. cerevisiae (left) or from C. albicans (right). The height of each letter represents the frequency of that base in that position of the matrix. Positions in the matrices that are statistically different (see Materials and Methods for details) are indicated with an asterisk. The matrices are useful because they summarize the set of related sequences that are common to the upstream regions in each group, but a more direct assessment of these elements is to inspect the sequences directly. Sequences upstream of the S. cerevisiae and C. albicans proteasome genes that matched the “meta-matrix” described above were combined and organized by sequence similarity, using a hierarchical clustering method described in Materials and Methods . The sequences could be classified into three general categories ( Figure S6 ). The first category consisted of related sequences that were found in both S. cerevisiae and C. albicans proteasome upstream regions, the second was composed of sequences found almost exclusively upstream of S. cerevisiae genes, and the third was composed of elements found only upstream of the C. albicans proteasome genes. Manual inspection of the proteasome-gene upstream regions supported these classifications: There were zero instances of the S. cerevisiae -specific 10-mer GGTGGCAAAW upstream of any C. albicans proteasome genes, although nearly 75% of the S. cerevisiae proteasome genes contained this upstream sequence. Similarly, zero instances of the C. albicans -specific 10-mer GRAGGCAAAA were found upstream of S. cerevisiae proteasome genes, whereas 25% of the C. albicans genes contained the element. These observations suggest that S. cerevisiae and C. albicans use different sequences to govern the expression of the proteasome genes. Sc_Rpn4p and Ca_Rpn4p Have Different In Vitro Binding Specificities Two mutually exclusive possibilities could explain the differences in the upstream sequences found in S. cerevisiae and C. albicans proteasome genes. One model is that the species-specific differences in these cis -sequences reflect differences in the binding specificity of S. cerevisiae Rpn4p and its ortholog in C. albicans . Alternatively, the two transcription factors may bind with the same specificity, indicating that some other feature(s) contributed to the differences in these sets of sequences. Examination of the nucleotide frequencies in each genome ruled out the possibility that the differences in cis -sequences arose simply by drift in the underlying genomic base composition (unpublished data). To further distinguish between the above models, we cloned and purified S. cerevisiae Rpn4p (Sc_Rpn4p) and the orthologous protein from C. albicans (Ca_Rpn4p) and measured their binding properties in vitro. The interaction of each protein with three different DNA sequences (each representing one of the three classes of upstream sequences described above) was measured using the Biacore 3000 affinity system, which measures biomolecular interactions between proteins and DNA (see Materials and Methods for details). Briefly, double-stranded DNA fragments containing the relevant sequences were immobilized onto a solid surface, and real-time protein-DNA interactions were measured as each protein was passed over the immobilized DNAs and allowed to bind (reviewed in Malmqvist 1999 ). The results of these in vitro binding experiments revealed that Sc_Rpn4p and its ortholog Ca_Rpn4p have different DNA-binding specificities. Figure 7 shows the binding of Sc_Rpn4p and Ca_Rpn4p to the S. cerevisiae -specific Sequence A (GGTGGCAAAA), the C. albicans -specific Sequence B (GAAGGCAAAA), and Sequence C (AGTGGCAACA), which represents sequences found in both species. Sc_ Rpn4p bound preferentially to Sequence A and, to a lesser extent, to Sequence C; however, the binding of Sc_Rpn4p to Sequence B was barely detectable ( Figure 7 A). Ca_Rpn4p also bound preferentially to Sequence A, but in contrast to Sc_Rpn4p, this protein bound nearly indistinguishably to Sequence B and Sequence C in vitro ( Figure 7 B). Figure 7 In Vitro DNA-Binding Profiles of Rpn4p Proteins Profiles of 50 nM Sc_Rpn4p (A), Ca_Rpn4p (B), Hybrid_Rpn4p (C), and Nc_Rpn4p (D) binding to Sequence A ( S. cerevisiae -specific; red curve), Sequence B ( C. albicans -specific; blue curve), and Sequence C (hybrid; black curve) are shown. Protein was injected into the Biacore system at time = 0 for a duration of 90 sec, after which time buffer was injected and the protein dissociated from the Biacore chip. The scale of each binding profile was adjusted such that the binding levels to Sequence A are comparable for all species. In all cases, the DNA binding was specific, as competitor fragments that were similar to the Sc_Rpn4p consensus sequence, but not a dissimilar control fragment, were effective inhibitors of binding when preincubated with the protein ( Figure 8 ). This was true even for Sc_Rpn4p binding to Sequence B, despite the low levels of binding to this sequence. A fragment identical to the immobilized Sequence A was the best competitor for both Sc_Rpn4p and Ca_Rpn4p binding to all immobilized sequences, compared to competitor fragments with single basepair differences in either the first or ninth position of the element. This was surprising in the case of Ca_Rpn4p, since the lower basepair specificity in the ninth position of the C. albicans proteasome matrix (see Figure 6 ) predicted that sequence variation at this position would not significantly affect binding. Figure 8 In Vitro Competition for DNA Binding The maximum response units of binding were measured for Sc_Rpn4p (A), Ca_Rpn4p (B), or the hybrid protein (C) binding to Sequence A (left graphs), Sequence B (center graphs), and Sequence C (right graphs) in the absence (“mock”) or presence of a 1× or 5× molar excess of competitor fragments: Sequence G (with a core sequence of CTGCATTTGG), Sequence D (GGTGGCAAAA), Sequence E (AGTGGCAAAA), and Sequence F (GGTGGCAACA). Each histogram shows the maximum response units of binding, relative to the maximum response units measured for that protein binding to the Sequence A in the absence of competitor. Replicate experiments were performed for each mock reaction and the 5:1 competition experiments for Sc_Rpn4p protein. The range of replicate measurements was very narrow and is indicated by the error bars. A reasonable expectation is that amino acid differences in the DNA-binding domains of each protein account for the differences in their specificity, perhaps by promoting subtly different contacts between each protein and its DNA substrate. While this is not an obligate explanation, we found it to be the case: A hybrid protein that consisted of the amino-terminal portion of Sc_Rpn4p fused to the carboxyl-terminal DNA-binding domain of Ca_Rpn4p (see Materials and Methods for details) was able to bind Sequence B indistinguishably from Sequence C, as did the native Ca_Rpn4p (see Figure 7 C). Again, the binding was specific, since the expected sequences, but not the negative control, were able to compete for binding ( Figure 8 ). These results reveal that amino acid differences between the Sc_Rpn4p and Ca_Rpn4p DNA-binding domains account for the altered specificity of these proteins. Nc_Rpn4p Has the Same In Vitro Specificity as Ca_Rpn4p Although we could not identify Rpn4p-like elements upstream of the majority of proteasome genes from the other fungi, we did identify a different sequence, GGAGCT, upstream of the proteasome genes from the euascomycete fungi. Because each of these fungi has an ortholog of Rpn4p, we cloned Nc_Rpn4p as a representative and characterized its binding to the novel sequence and to Sequence A, B, and C described above (see Materials and Methods for details). Nc_Rpn4p did not bind detectably to the GGAGCT sequence in vitro, similar to its orthologs Sc_Rpn4p and Ca_Rpn4p that did not bind this sequence (unpublished data). In contrast, Nc_Rpn4p bound to the Rpn4p-like elements with a binding profile similar to Ca_Rpn4p: Nc_Rpn4p bound maximally to Sequence A and bound nearly identically to Sequence B and Sequence C on the Biacore chip (see Figure 7 D). Since the majority of proteasome genes from the euascomycete fungi do not contain these sequences, these results suggest that Nc_Rpn4p does not regulate proteasome gene expression. Discussion The ascomycete fungi represent nearly 75% of all fungal species, and their diversity is evident by their unique morphologies, life styles, environmental interactions, and niches ( Ainsworth et al. 2001 ). This diversity has been shaped by over a billion years of evolution ( Berbee and Taylor 1993 ; Heckman et al. 2001 ) and has almost certainly been affected by variation in gene expression. To explore the evolution of gene-expression regulation in these fungi, we have examined the cis -regulatory networks of 14 ascomycete species whose genomes have been sequenced, using a framework that is not dependent on multiple alignments of orthologous regulatory regions. We have identified probable cis -acting sequences in each of these species by applying motif search and discovery methods to the flanking regions of orthologs of coregulated S. cerevisiae genes. Our ability to identify such sequences in the same gene groups from multiple species strongly suggests that the coregulation of those genes has been conserved. Examples from our analysis indicate that in many cases the genes' coregulation is governed by a conserved regulatory system, while other examples suggest that some regulatory networks have evolved. These examples provide insights into the functional constraints that underlie the evolution of gene-expression regulation, as summarized below. Conservation of Cis -Regulatory Systems Our results indicate that a large number of cis -regulatory networks that function in S. cerevisiae are conserved in other ascomycete species. This is expected for the closely related species, since conserved regulatory elements can be readily identified in alignments of orthologous regulatory regions ( Cliften et al. 2003 ; Kellis et al. 2003 ). However, we show here that many of the cis -regulatory systems represented by these elements are conserved over much longer evolutionary time frames, beyond those for which orthologous noncoding regions can be aligned. For example, 50%–75% of the regulatory systems identified in S. cerevisiae are also found in S. kluyveri and S. castellii, which are diverged enough from S. cerevisiae that much of the gene synteny is lost and most orthologous intergenic regions cannot be aligned ( Cliften et al. 2003 ). Over a third of these regulatory systems were identified in C. albicans, which is estimated to have diverged from S. cerevisiae over 200 million years ago, and a small number of regulatory networks have been conserved since the origin of the Ascomycetes some 500 million to a billion years ago ( Berbee and Taylor 1993 ; Heckman et al. 2001 ). It is likely that we have underestimated the number of conserved regulatory networks, partly because of statistical limitations of our method. Nonetheless, these data indicate that regulatory networks can be conserved over very long periods of evolution. Despite the widespread conservation of cis -regulatory networks, it is important to note that this does not necessarily imply that the individual cis -elements have remained perfectly conserved. For example, while we could identify the same cis -sequences in orthologous gene groups, the positions of the individual elements in orthologous upstream regions in many cases appear to have changed (see Figure S4 ). Evolution of cis -element position has been observed in closely related drosophilids, mammals, and other species ( Ludwig and Kreitman 1995 ; Ludwig et al. 1998 ; Piano et al. 1999 ; Dermitzakis and Clark 2002 ; Scemama et al. 2002 ; Dermitzakis et al. 2003 ) and is proposed to occur by two general mechanisms (reviewed in Wray et al. 2003 ). The first is binding-site turnover, whereby the appearance of a new cis -element elsewhere in a promoter can compensate for the loss of a functional element in the same regulatory region. Simulation studies show that cis -element turnover occurs frequently over short evolutionary time scales and is likely to play an important role in gene-expression regulation ( Stone and Wray 2001 ; Dermitzakis et al. 2003 ). Alternatively, small insertions and deletions in a regulatory region can permute the cis -element's position without changing the element's sequence ( Ludwig and Kreitman 1995 ; Piano et al. 1999 ; Ruvinsky and Ruvkun 2003 ). Thus, regulatory regions appear to be relatively plastic in their organization. Despite this plasticity, however, a gene's expression pattern and the regulatory system governing its expression can remain intact even though the gene's flanking regulatory region has undergone reorganization ( Piano et al. 1999 ; Ludwig et al. 2000 ; Scemama et al. 2002 ; Hinman et al. 2003 ; Romano and Wray 2003 ; Ruvinsky and Ruvkun 2003 ). This indicates that some combination of purifying selection and drift ( Ludwig et al. 2000 ) can act to maintain the appropriate regulatory connections to conserve the gene's expression pattern. Although the positions of many of the individual cis -elements have evolved in these species, we found that the distribution of elements upstream of their gene targets was often similar across species. This suggests that there has been constraint on the region in which the elements are positioned, without pressure to maintain the exact positions of individual elements. One explanation for this model is that mechanistic features of these regulatory systems are also conserved across species ( Wray et al. 2003 ). For example, the restricted location of cis -regulatory elements may promote interactions between the cognate binding protein and other regulatory proteins. Therefore, selective pressure may act to maintain these interactions through the relative positions of the underlying binding sites. This model may also explain the conserved close spacing between Cbf1p and Met31/32p elements in methionine biosynthesis genes from the hemiascomycete fungi. These transcription factors are proposed to act cooperatively in S. cerevisiae to recruit additional transcriptional regulators ( Blaiseau and Thomas 1998 ). That the spacing between the Cbf1p and Met31/32p elements is closer than expected in other species as well suggests that the cooperative interaction between the factors has been conserved across the Hemiascomycetes. Evolution of Cis -Regulatory Networks In addition to the clear cases of network conservation discussed above, we also found evidence for the evolution of cis -regulatory systems. Our ability to identify novel sequences enriched in orthologs of coregulated S. cerevisiae genes implies that, although the genes are still coregulated in those species, the systems governing their expression have changed. This indicates that the regulatory regions of those genes coevolved to contain the same cis -sequences. We were interested in identifying global predictors of the relative rates of cis -regulatory network evolution, but these factors remain enigmatic. Unlike the evolutionary rates of protein coding regions, for which essential proteins typically evolve at a slower rate ( Wilson et al. 1977 ; Hirsh and Fraser 2001 ; Krylov et al. 2003 ; H. B. F., personal communication), we found no evidence for a retarded rate of evolution/loss of the cis -regulatory systems of essential genes (unpublished data). For example, the proteasome subunits and the ribosomal proteins are among the most highly conserved proteins, and the genes that encode them are expressed with similar patterns in S. cerevisiae, C. albicans, and Sch. pombe ( Gasch et al. 2000 ; Chen et al. 2003 ; Enjalbert et al. 2003 ). Nonetheless, we identified different upstream sequences for these groups in the different species we analyzed, suggesting that the regulation of the genes' expression has evolved even though their expression patterns have not. This is consistent with previous observations of developmentally regulated genes in higher organisms, whose temporal and spatial expression can be conserved across taxa despite divergence in their regulation ( Takahashi et al. 1999 ; True and Haag 2001 ; Scemama et al. 2002 ; Hinman et al. 2003 ; Romano and Wray 2003 ; Ruvinsky and Ruvkun 2003 ; Wang et al. 2004 ). In contrast, we observed that proteins involved in mating have a high rate of evolution, yet we could identify the Ste12p binding site ( Fields and Herskowitz 1985 ) upstream of mating genes in nearly all of the hemiascomycetes. Consistently, orthologs of Ste12p are known to be required for mating in distantly related fungi that mate through significantly different processes ( Lengeler et al. 2000 ; Vallim et al. 2000 ; Young et al. 2000 ; Chang et al. 2001 ). Since mating may be triggered by similar environmental cues ( Lengeler et al. 2000 ), evolutionary pressure may have conserved the regulatory system that mediates this process (to the extent of our observations), even though the mating proteins have evolved. Although we could not find global correlates with the patterns of cis -regulatory network evolution, a number of individual examples from our analysis are consistent with specific models of network evolution. These examples are discussed below. Addition of Gene Targets into an Existing Regulatory Network Sequences that match cis -regulatory elements can readily appear in noncoding DNA through drift. In the same way that this process can promote binding site turnover within a given regulatory region, it can create de novo elements in the regulatory regions of random genes, giving rise to novel targets of that regulatory system ( Stone and Wray 2001 ; Rockman and Wray 2002 ). The addition of novel targets into cis -regulatory systems may have occurred in the case of E2F-like transcription factors. In S. cerevisiae , the related MCB (ACGCG) and Swi4-Swi6 cell-cycle box, or SCB (CGCGAAA) regulatory elements are found upstream of G1-phase cell-cycle genes, similar to the E2F element found in these genes in worms, flies, humans, and plants ( Lowndes et al. 1992 ; Malhotra et al. 1993 ; DeGregori 2002 ; Ren et al. 2002 ; De Veylder et al. 2003 ; Rustici et al. 2004 ). What is striking about the conservation of this network is that cell-cycle progression is markedly different in these organisms: The hemiascomycete fungi replicate by budding, unlike the filamentous fungi in the euascomycete group, the fission yeast Sch. pombe , and the other higher eukaryotes. While some of the genes regulated by these elements are well conserved across organisms (namely, the DNA replication proteins), genes whose products are involved in budding are also expressed in G1 phase and regulated by these elements in S. cerevisiae ( Spellman et al. 1998 ; Iyer et al. 2001 ) and likely in its budding cousins as well. Because these genes are not conserved outside the hemiascomycete clade, and since it is unlikely that budding represents the ancestral mode of replication, this suggests that genes involved in budding were assumed into an existing cis -regulatory network in these yeasts. Coevolution of an Existing Regulatory Network Mutation of a cis -regulatory element can be compensated by the stabilizing effects of binding site turnover ( Ludwig et al. 2000 ), as discussed above, but it could also be overcome by corresponding changes in its DNA-binding protein, such that the interaction between the two is maintained. Parallel changes in DNA element and protein sequence can occur to conserve the overall regulatory network (i.e., the same binding protein regulating the same set of genes), despite evolution of their molecular interaction. We found slightly different sets of sequences enriched upstream of the proteasome genes from S. cerevisiae versus C. albicans, and these differences corresponded with the different binding specificities of Sc_Rpn4p and Ca_Rpn4p in vitro. This result is consistent with the model that the binding specificity of Sc_Rpn4p and Ca_Rpn4p coevolved with the elements found upstream of the proteasome genes in each species. Neither Ca_Rpn4p nor the hybrid protein functioned in an in vivo reporter system (unpublished data); however, Sc_Rpn4p could transcribe a reporter gene to higher levels if Sequence A was present in its promoter compared to when Sequence B or a minimal promoter was placed upstream of the reporter gene (see Figure S7 ). These results are consistent with the hypothesis that Sc_Rpn4p ineffectively initiates transcription from the C. albicans -specific element. Since Ca_Rpn4p and Nc_Rpn4p both bind significantly to Sequence B, it is likely that this was also true of the proteins' common ancestor and that Sc_Rpn4p largely lost the ability to bind productively to this sequence. The altered specificity of Sc_Rpn4p is due to amino acid differences in its DNA-binding domain, since the hybrid Rpn4p (containing the Ca_Rpn4p DNA binding domain) bound to Sequence B as well as it did to Sequence C (see Figure 7 C). Determining which residues are responsible for the altered activity is a difficult task, however, since all of the residues known to participate in zinc coordination and DNA contact ( Rhodes et al. 1996 ; Wolfe et al. 1999 ; Wolfe et al. 2000 ; Pabo et al. 2001 ; Benos et al. 2002 ) are perfectly conserved between these orthologs ( Figure 9 ). One obvious difference in the orthologous proteins is the spacing between the cysteine and histidine pair in the second zinc finger, which is proposed to contact the first half of the DNA-binding site ( Wolfe et al. 2000 ; Pabo et al. 2001 ) wherein the base-specificity differences reside. Sc_Rpn4p, Ca_Rpn4p, and the euascomycete Rpn4p orthologs all vary in amino acid length and identity in this region, which implicated the region as relevant to the specificity differences. However, a mutant Sc_Rpn4p that contained the Nc_Rpn4p sequence in this region (see Figure 9 ) had the same binding specificity as the wild-type Sc_Rpn4p (albeit with less activity; unpublished data), indicating that this region alone is not sufficient to explain the differences in binding profiles. Figure 9 Sequence Alignment of the DNA-Binding Domain of Rpn4p and Its Orthologs Clustal W was used to identify a multiple alignment between S. cerevisiae Rpn4p and its orthologs in the other fungi; the alignment over the DNA binding domain is shown. No ortholog was identified by our method in S. kluyveri, apparently due to poor sequence coverage in that region (unpublished data). The conserved cysteine and histidine residues of the two C2H2 zinc-finger domains are highlighted in yellow, and the domain in each finger that is predicted to contact the DNA is indicated with a gray bar. The region of sequence variation between the hemiascomycete and euascomycete Rpn4p proteins is indicated with a box. Cooption of a Regulatory System to Govern a Different Set of Genes An extreme example of the previously discussed modes of evolution is the complete alteration of a regulatory system's target genes ( True and Carroll 2002 ). This may have occurred for the Rpn4p regulatory system sometime after the divergence of the euascomycete and hemiascomycete fungi. Our data suggest that, while Sc_Rpn4p and Ca_Rpn4p control proteasome-gene expression in these species, the euascomycete orthologs of this transcription factor probably do not. Nc_Rpn4p did not bind the novel sequence we identified upstream of euascomycete proteasome genes, and reciprocally the majority of these genes did not contain examples of the Rpn4p binding site. One possibility is that Nc_Rpn4p and its orthologs regulate a different set of genes in the euascomycete clade. Preliminary investigation of orthologous euascomycete genes that contain examples of the Ca_Rpn4p matrix (used as a surrogate for the Nc_Rpn4p binding matrix) did not reveal any obvious relationships in the genes' functional annotations or striking similarities in their patterns of expression (T. Kasuga, personal communication). Interestingly, however, the orthologs of RPN4 in all three euascomycete species contained upstream Rpn4p elements, raising the possibility that this gene is autoregulated at the level of expression in these fungi. Future experiments will test the function of this factor in N. crassa as well as the role of the novel sequence in mediating proteasome gene expression. The converse of this situation is that the regulatory regions of coregulated genes must coevolve, such that they all contain the same regulatory elements recognized by the new system. This apparently occurs despite strong constraint on the genes' expression patterns. For example, most proteasome subunits are essential and required in proper stoichiometric amounts ( Russell et al. 1999 ; Kruger et al. 2001 ). Nonetheless, we found different cis -sequences upstream of the proteasome genes from the hemiascomycete and euascomycete fungi. Another example can been seen in the ribosomal protein genes, which must also be expressed to the same relative levels ( Warner 1999 ; Zhao et al. 2003 ). In all species, we could find elements upstream of the ribosomal proteins, but different cis -sequences were identified in subsets of these species (see Figures 2 and 3). How the regulatory systems that control the genes' expression evolve is unclear. This process may involve an intermediate stage in which the genes' expression is controlled by two distinct, but partially redundant, regulatory systems ( True and Haag 2001 ; True and Carroll 2002 ). Differential loss of one system in two diverged species would render the orthologous genes coregulated by different regulatory systems. This model for regulatory system “turnover” is in direct analogy to the case of binding site turnover, in which partially redundant cis -elements that are created by drift coexist in a regulatory region before they are differentially lost in the diverged species ( Ludwig et al. 2000 ; Stone and Wray 2001 ). Conclusions and Future Directions We have provided a framework for studying cis -regulatory evolution without relying on alignments of intergenic regions. The evolutionary dynamics of transcriptional regulation is evident from the examples we have presented. We expect that as more complete fungal genomes emerge, particularly for fungi with intermediate evolutionary relationships, important gaps in the existing phylogeny will be filled. These key species may provide a window into intermediate stages of cis -element evolution, allowing us to further delineate the patterns of and constraints on the evolution of cis -regulation. Materials and Methods Genome sequences Genome sequence and open reading frame (ORF) annotations for the saccharomycete species were obtained from P. Cliften, M. Kellis, and the Saccharomyces Genome Database ( Goffeau et al. 1996 ; Cliften et al. 2003 ; Kellis et al. 2003 ). Sequences for other genomes were downloaded from the published or listed Web sites as follows. K. waltii ( Kellis et al. 2004 ), A. gossypii ( Dietrich et al. 2004 ), C. albicans (Assembly 6; http://www-sequence.stanford.edu/group/candida/ ) ( Jones et al. 2004 ), N. crassa (Release 3; Galagan et al. 2003 ), M. grisea (Release 2; http://www-genome.wi.mit.edu/annotation/fungi/magnaporthe/ ) , As. nidulans (Release 3.1; http://www.broad.mit.edu/annotation/fungi/aspergillus/ ) , and Sch. pombe ( Wood et al. 2002 ). A conservative list of putative ORFs from S. kudriavzevii, S. castellii, and S. kluyveri was generated, taking all ORFs of more than 100 amino acids as putative genes. ORFs orthologous to S. cerevisiae genes were identified as described below; some intron-containing S. cerevisiae genes that may also contain introns in these species (namely ribosomal protein genes) were identified by tBLASTn and manually added to the list of orthologs for these species. Orthologs between S. cerevisiae and S. paradoxus, S. mikatae, and S. bayanus ( Kellis et al. 2003 ) were downloaded from the Saccharomyces Genome Database ( http://www.yeastgenome.org/ ) . All other orthologs to S. cerevisiae genes were assigned using the method of Wall et al. ( Wall et al. 2003 ) using a BLAST e-value cutoff of 10 -5 and the requirement for fewer than 20% gapped positions in the Clustal W alignments. The number of orthologs assigned in each species is listed in Table 1 , and the complete results are available in Datasets S5–S12 . Table 1 Orthologs Assigned to S. cerevisiae Genes a Gene numbers reported in genome sequence publication or on the source website; see Materials and Methods for references b Orthologs for S. paradoxus, S. mikatae, and S. bayanus were identified by Kellis et al. (2003) All other orthologs were identified as described in Materials and Methods nd, not determined S. cerevisiae gene clusters Groups of known or putatively coregulated genes were identified in three ways. First, we used hierarchical ( Eisen et al. 1998 ) and fuzzy k -means ( Gasch and Eisen 2002 ) clustering to organize publicly available yeast gene expression data ( DeRisi et al. 1997 ; Spellman et al. 1998 ; Gasch et al. 2000 ; Lyons et al. 2000 ; Ogawa et al. 2000 ; Primig et al. 2000 ; Gasch et al. 2001 ; Yoshimoto et al. 2002 ), taking gene clusters that were correlated by more than about 0.7 or with a membership of 0.08 or greater ( Gasch and Eisen 2002 ). Second, we identified genes or transcripts whose flanking regions are physically bound by the same DNA or RNA binding proteins, as indicated by immunoprecipitation experiments ( Simon et al. 1993 ; Iyer et al. 2001 ; Lieb et al. 2001 ; Simon et al. 2001 ; Lee et al. 2002 ; Gerber et al. 2004 ): For the DNA immunoprecipitation experiments, genes were ranked according to the published binding p values, and a sliding p value (between 10 -2 and 10 -4 ) was applied such that at least 20 genes were selected in each group. Transcripts that are bound by RNA binding proteins were taken from ( Gerber et al. 2004 ). Finally, genes with the same functional annotations ( Weng et al. 2003 ), and genes known to be coregulated by various transcription factors ( Gasch et al. 2000 ; Lyons et al. 2000 ; Ogawa et al. 2000 ; Shakoury-Elizeh et al. 2004 ), were grouped together. In all, we identified 264 partially redundant groups of S. cerevisiae genes that are likely to be coregulated. These gene groups ranged in size from four to 570 genes, with a median size of 17 genes per group. The complete gene groups are available in Dataset S2 . Motif identification and enrichment We compiled from the literature a list of 80 known transcription factor-binding sites, represented by IUPAC consensus sequences ( Dataset S1 ) ( Costanzo et al. 2001 ; Weng et al. 2003 ). Unless otherwise noted, we searched 1,000 bp upstream or 500 bp downstream of the genes from each group in each fungal genome for sequences that matched the consensus binding sites, by doing string comparisons on both strands using PERL scripts. For each group of genes identified above, we scored the enrichment of genes whose flanking regions (either 500 bp upstream, 1,000 bp upstream, or 500 bp downstream) contain one or more example of each cis -regulatory element, using the hypergeometric distribution where M is the number of genes that contain the motif in a group of i selected genes, relative to N genes that contain the motif in a genome of l genes. A p ≤ 0.0002 (approximately 0.01/80 tests) was deemed statistically significant for the consensus sequences, although if the sequence was enriched in the known group of target genes, we relaxed the cutoff to p = 0.01. A cutoff of p ≤ 2 × 10 –5 was applied to sequences that matched the MEME matrices. For the Mig1p and GATA binding sequences, which are sufficiently short and occur frequently in each genome, we also scored the enrichment of genes whose upstream region contained two or more examples of the known binding sites. For each group of genes, we also ran the motif-finding algorithm MEME ( Bailey and Elkan 1994 ) on the upstream regions of S. cerevisiae genes or their orthologs in each species, using a two-component mixture model both with and without a motif-width specification of 8 bp. Unless otherwise noted, we used 500 bp upstream (for the hemiascomycetes) or 1,000 bp upstream (for the euascomycetes and Sch. pombe ) of the genes in each group. Thus, for each group of coregulated genes, we performed 14 MEME analyses (each identifying three matrices) on the upstream regions of the genes from a given species. Matrices that matched known S. cerevisiae regulatory elements were identified by manual and automated comparisons, similar to that previous described ( Hughes et al. 2000 ). A position-weight matrix was calculated for each motif on the basis of n motif examples MEME identified by counting the number of occurrences of each base at each position in n motifs, adding one pseudocount, and dividing by n + 4. A log-likelihood score S was calculated for each motif example as follows. In this formula, p is each position in the motif, b is the base {GACT} and X is a matrix of indicator variables representing the sequence, where X pb = 1 if the sequence has base b at position p , and zero otherwise. The probabilities of bases in the motif according to the position-weight matrix are represented by f motif , and the probabilities of bases in the genomic background are represented by f background (see below). The score S ′ was assigned to each matrix, equal to 0.75× the average S of the motif examples, using the base frequency from each genome as the background model (G/C = 0.2 and A/T = 0.3 for all species except N. crassa , where G/C/A/T = 0.25). This score was used as a cutoff to identify genomic examples of the matrix. To identify genes whose upstream regions contained examples of each motif, we calculated the log-likelihood S of each 8-bp sequence within the 1,000 bp upstream region of each gene. The background model was based on the genomic nucleotide frequency in the 50 bp upstream window corresponding to the position of the sequence being assessed. We used this model to overcome the species-specific positional nucleotide biases immediately upstream of coding sequences (A. M. M., A. P. G., D. Y. C., and M. B. E., unpublished data). A sequence was considered a match to the matrix if S > S ′. The enrichment of genes that contained each motif was scored using the hypergeometric distribution, as described above. A p ≤ 1 × 10 –5 (0.01 divided by the number of matrices tested in each species) was considered statistically significant. Out of the MEME matrices trained on the non- S. cerevisiae species, 53 were enriched in the gene group in which they were identified. Of these elements, 28 were similar to S. cerevisiae elements shown in Figure 2 and were enriched in the S. cerevisiae genes. An additional six matrices were redundantly identified in nearly identical gene groups (namely, Fhl1p targets and ribosomal protein genes) from the same species, and two elements were very similar and identified in the same gene group from As. nidulans and M. grisea . Thus, in all, 19 novel elements were identified. The complete list of matrices is available in Dataset S47 . Positional distribution and spacing of cis -sequences Genes that contained sequences that matched the S. cerevisiae position-weight matrices were identified as described above. We then calculated the frequency of each sequence in 50-bp windows upstream of the potential target genes and compared it to the frequency of that element in the corresponding upstream window for all of the genes in that genome. To identify distributions that were statistically different from the background, we identified 50-bp windows that contained a disproportionate number of the cis -sequences in the target upstream regions compared to the background, using the hypergeometric distribution presented above, where i was the total number of elements identified upstream of the genes in each group, M was the number of those elements that fell within a given 50-bp window, l was the total number of elements upstream of all of the genes in that genome and N was the number of those elements that fell within the same 50-bp window. We considered an element's distribution to be significant if there was at least one 50-bp window with p ≤ 0.01; only 5%–10% of the elements had distributions that met this criterion in gene groups other than their putative target genes. We calculated the correlation between element positions in S. cerevisiae and each of the other species by taking all possible pairwise combinations of a cis -element's positions in a given S. cerevisiae upstream region and in the orthologous region from other species and plotting these values for each group of coregulated genes (example scatter plots shown in Figures S4 and S5 ). Genes that contained sequences that matched the S. cerevisiae Cbf1p and Met31/32p position-weight matrices were identified in each species as described above. The average spacing between Cbf1p and Met31/32p binding sites within the 500 bp-upstream regions of the methionine biosynthesis genes and of all of the genes in each genome was measured by calculating the distance between all pair-wise combinations of the two motifs in each upstream region and taking the average spacing for the respective group of genes. Rpn4p matrix comparisons To compare the upstream sequences identified in proteasome genes from S. cerevisiae and C. albicans, and to ensure that the identified sequences were not obtained by sampling bias, we performed the following permutation analysis. We ran MEME on the entire set of upstream regions of 26 proteasome genes with orthologs in both species, using the conservative one-per-sequence model. This produced a “meta-matrix” that identified exactly one putative binding site from each gene, leaving us with a set of exactly 52. We calculated the likelihood-ratio statistic, testing the hypothesis that the sequences were drawn from a single multinomial, or from multinomials estimated separately for each species. In order to test the significance of this statistic, we randomly divided the data into two equal-sized groups 10,000 times, recalculated the statistic, and found that matrix positions 2, 3, and 9 had values of p < 0.001. The results were similar when the test was performed on all cis -sequences that matched the meta-matrix: These sequences were identified in both species using the S. cerevisiae background model (which identified a list of sequences that was nearly identical to that generated when the C. albicans background model was used to identify motifs from each species). This set of elements was organized by sequence similarity as follows. Each basepair was represented by a four-dimensional binary vector of indicator variables: G = 1,0,0,0; A = 0,1,0,0; C = 0,0,1,0; T = 0,0,0,1. Each basepair in each 10-mer sequence was replaced by the corresponding vector of indicator variables, translating the 10-mer sequence into a 40-dimensional binary vector. The sequences were organized by hierarchically clustering the binary vectors that represented them, using the program Cluster ( Eisen et al. 1998 ). The organized sequences were visualized using the program TreeView ( available at http://rana.lbl.gov ) as shown in Figure S6 . Cloning and culture growth The S. cerevisiae RPN4 ORF and its orthologs in C. albicans (orf6.4920) and N. crassa (NCU01640.1) were cloned by PCR from genomic DNA ( S. cerevisiae strain S288C, C. albicans strain NIH 3147 [#10231D; American Type Culture Collection, Manassas, Virginia, United States], and N. crassa Mauriceville strain) using Bio-X-act DNA polymerase (BioLine, Boston, Massachusetts, United States). Primers that exactly spanned each ORF (excluding the first ATG) and introduced XmaI and NcoI sites at the 5′ and 3′ ends, respectively, of each PCR product, were used to amplify each ORF. The digested products were cloned into pCAL-n (Stratagene, La Jolla, California, United States) to add an amino-terminal calmodulin-binding protein tag to each protein. In addition, a hybrid protein was generated from the amino-terminal portion of Sc_ RPN4 (corresponding to nucleotide position 4–1,247) and the DNA binding-domain from C. albicans orf6.4920 (position 1,235–1,611), guided by Clustal W ( Thompson et al. 1994 ; Chenna et al. 2003 ) alignments of the proteins. The orf6.4920 fragment was amplified by PCR, generating an EcoRI site in the amino end of the fragment. The digested fragment was ligated to a natural EcoRI site in Sc_RPN4 (present in a region of high sequence conservation between the proteins), and the hybrid was cloned into pCAL-n as described above. The wild-type amino acid sequences of Sc_Rpn4p, Ca_Rpn4p, and the hybrid clones were verified by DNA sequencing. (The Mauriceville Rpn4p ortholog had five amino acid differences compared to the published sequence from strain 74A. Because we recovered the identical sequence from multiple independent PCRs, we take this to be the wild-type Nc_Rpn4p for this strain.) Each plasmid was used to transform BL21DE3-RIL E. coli cells (Stratagene). Yeast overexpression plasmids were constructed by PCR amplification of Sc_RPN4, Ca_RPN4, or Hybrid_RPN from the above plasmids and cloned into the GAL-inducible expression plasmid pRS-TAP (provided by D. Nix) by homologous recombination and gapped plasmid repair. Reporter constructs were generated by cloning 40-bp fragments that contained either one or five copies of Sequence A or Sequence B upstream of the HIS3 minimal promoter in pDC204 (provided by D. Y. C.). Yeast strain BY4741 (MAT a his3Δ1 leu2Δ0 met15Δ0 ura3Δ0, provided by M. Kobor) was transformed with each overexpression construct and each reporter construct. Liquid cultures were grown to mid-log phase and washed three times with synthetic-dropout medium lacking histidine and glucose. Serial culture dilutions were spotted onto solid SC medium lacking uracil, leucine, and histidine, with 2% galactose, and containing 0–15 mM 3-amino triazole (Sigma, St. Louis, Missouri, United States). Photos were taken after growth for 3 d at 30 °C. Protein purification and Biacore measurements The proteins were purified from bacteria by affinity purification. 250 ml of LB medium containing 50 ng/ml carbenicillin (Sigma) was inoculated with 8 ml of saturated cultures and grown at 37 °C to OD 600 of approximately 1.0. The cells were induced with 0.3 mM IPTG (Sigma) at 30 °C for 1 h, collected by centrifugation at 4 °C, and flash-frozen in liquid nitrogen. The cells were resuspended in ice-cold 8V calcium binding buffer (50 mM Tris-Cl [pH 7.5], 150 mM NaCl, 1 mM magnesium acetate, 1 mM imidazole, 2 mM calcium chloride, and 1 mM PMSF) and lysed on ice by sonication. The lysate was cleared by centrifugation, and the soluble extract was loaded onto 0.5 ml of calmodulin resin (Stratagene) in a 2-ml column (BioRad, Hercules, California, United States) at 4 °C. The column was washed with 8V calcium binding buffer followed by 8V binding buffer adjusted to 0.5 M NaCl. The resin was eluted with elution buffer (50 mM Tris-Cl [pH 7.5], 0.5 M NaCl, and 2 mM EGTA), and the eluates were flash-frozen and stored at –80 °C. The interaction of each purified protein with three predicted Rpn4p binding sites was measured using a Biacore 3000 system (Biacore, Piscataway, New Jersey, United States). Complementary 40-nucleotide oligonucleotides were designed, with one oligonucleotide containing a 5′ biotinylated group (Qiagen, Valencia, California, United States). Each of the three sequences contained a different 10-bp core flanked by the same 15 bp that flanked a natural Rpn4p site from the C. albicans orf6.8078 gene: Sequence A ( GCGTGCCAGATAATC GGTGGCAAAA CGGAAGAAAAAGTGA); Sequence B ( GCGTGCCAGATAATC GAAGGCAAAA CGGAAGAAAAAGTGA); and Sequence C ( GCGTGCCAGATAATC AGTGGCAACA CGGAAGAAAAAGTGA). (The flanking sequence did not noticeably contribute to the binding properties, as a 40-bp fragment consisting of the natural Rpn4p site and flanking sequence from the S. cerevisiae gene PUP2 performed nearly indistinguishably from Sequence A in competition experiments [unpublished data].) The HPLC-purified oligonucleotides were combined at a ratio of 2:1 unbiotinylated:biotinylated oligonucleotides in 10 mM Tris-Cl (pH 7.4), 1 mM EDTA, and 50 mM NaCl, heated to 95 °C for 10 min, and incubated at room temperature overnight. Each double-stranded, biotinylated sequence was bound to one flow cell of an SA sensor chip (Biacore) in HBS buffer (10 mM HEPES [pH 7.4], 150 mM NaCl, 3 mM EDTA, and 0.005% P20) at a flow rate of 10 μl/min. Each cell was coated with roughly the same DNA (approximately 46–56 response units) according to the manufacturer's instructions. The fourth flow cell was not coated with DNA and served as a control. A single cell on a second SA chip was coated in the same way with double-stranded, biotinylated Sequence I ( ACTTGTTCCCGCTCGCT GGAGCT CCTCCAACGACACGGGC), representing an instance of the GGAGCT site and flanking sequence from the N. crassa proteasome gene NCU06712.1 . Protein was diluted to 10–100 nM in ice-cold HBS buffer and maintained on ice until injection into the Biacore system. Proteins were passed through four flow cells at a flow rate of 10 μl/min for 90 s at room temperature, then HBS buffer was flowed over the chip at 10 μl/min for 180 s. The protein was desorbed by flowing 0.5% SDS over the chip for 30 s followed by HBS. The kinetics of binding were examined using the Biacore software, and the fit of each calculation was acceptable according to the manufacturer's instructions. Double-stranded competitor DNA was generated by mixing equimolar amounts of complementary 30-nucleotide fragments, heating to 95 °C for 10 min, and allowing the mixture to cool to room temperature overnight. The DNAs were quantified before and after annealing by replicate absorbance measurements. Four different competitor fragments were used: Sequence D ( CCAGATAATC GGTGGCAAAA CGGAAGAAAA), Sequence E ( CCAGATAATC AGTGGCAAAA CGGAAGAAAA), and Sequence F ( CCAGATAATC GGTGGCAACA CGGAAGAAAA); the fourth sequence, Sequence G, ( CCAGATAATC CTGCATTTGG CGGAAGAAAA) was chosen as the worst-scoring sequence to the Sc_Rpn4p position-weight matrix and served as a negative control. Each fragment was mixed with 50 nM protein at a 1:1 or 5:1 molar ratio (or buffer was added for mock experiments), incubated for 50 min on ice, then injected into the Biacore system, as described above. The maximum response units of each protein binding to the three sequences on the chip were measured using the Biacore software. Supporting Information Dataset S1 List of S. cerevisiae Consensus Transcription Factor Binding Sites (2 KB TXT). Click here for additional data file. Dataset S2 List of S. cerevisiae Genes in the 264 Gene Groups Identified (339 KB XLS). Click here for additional data file. Dataset S3 Transcription Factor/Motif vs. Gene Group Relationships Used to Score Enrichment in Figure 2 (22 KB XLS). Click here for additional data file. Dataset S4 S. cerevisiae Matrices Identified by MEME That Matched Known S. cerevisiae Binding Sites (47 KB XLS). Click here for additional data file. Dataset S5 S. cerevisiae–S. castellii Orthologs (90 KB TXT). Click here for additional data file. Dataset S6 S. cerevisiae–S. kluyveri Orthologs (64 KB TXT). Click here for additional data file. Dataset S7 S. cerevisiae–K. waltii Orthologs (69 KB TXT). Click here for additional data file. Dataset S8 S. cerevisiae–A. gossypii Orthologs (53 KB TXT). Click here for additional data file. Dataset S9 S. cerevisiae–C. albicans Orthologs (74 KB TXT). Click here for additional data file. Dataset S10 S. cerevisiae–N. crassa Orthologs (70 KB TXT). Click here for additional data file. Dataset S11 S. cerevisiae–M. grisea Orthologs (63 KB TXT). Click here for additional data file. Dataset S12 S. cerevisiae–As. nidulans Orthologs (64 KB TXT). Click here for additional data file. Dataset S13 S. cerevisiae–Sch. pombe Orthologs (54 KB TXT). Click here for additional data file. Dataset S14 Probability of Enrichment of Genes Containing Two or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of S. paradoxus Genes (433 KB XLS). Click here for additional data file. Dataset S15 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of S. paradoxus Genes (433 KB XLS). Click here for additional data file. Dataset S16 Probability of Enrichment of Genes Containing Two or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of S. mikatae Genes (433 KB XLS). Click here for additional data file. Dataset S17 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of S. mikatae Genes (433 KB XLS). Click here for additional data file. Dataset S18 Probability of Enrichment of Genes Containing Two or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of S. bayanus Genes (433 KB XLS). Click here for additional data file. Dataset S19 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of S. bayanus Genes (433 KB XLS). Click here for additional data file. Dataset S20 Probability of Enrichment of Genes Containing Two or More copies of S. cerevisiae Consensus Elements within 500 bp Upstream of S. castellii Genes (416 KB XLS). Click here for additional data file. Dataset S21 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of S. castellii Genes (359 KB XLS). Click here for additional data file. Dataset S22 Probability of Enrichment of Genes Containing Two or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of S. kluyveri Genes (411 KB XLS). Click here for additional data file. Dataset S23 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of S. kluyveri Genes (414 KB XLS). Click here for additional data file. Dataset S24 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 1,000 bp Upstream of K. waltii Genes (411 KB XLS). Click here for additional data file. Dataset S25 Probability of Enrichment of Genes Containing Two or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of K. waltii Genes (411 KB XLS). Click here for additional data file. Dataset S26 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of K. waltii Genes (416 KB XLS). Click here for additional data file. Dataset S27 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 1,000 bp Upstream of A. gossypii Genes (398 KB XLS). Click here for additional data file. Dataset S28 Probability of Enrichment of Genes Containing Two or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of A. gossypii Genes (406 KB XLS). Click here for additional data file. Dataset S29 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of A. gossypii Genes (405 KB XLS). Click here for additional data file. Dataset S30 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 1,000 bp Upstream of C. albicans Genes (404 KB XLS). Click here for additional data file. Dataset S31 Probability of Enrichment of Genes Containing Two or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of C. albicans Genes (404 KB XLS). Click here for additional data file. Dataset S32 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of C. albicans Genes (389 KB XLS). Click here for additional data file. Dataset S33 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 2,000 bp Upstream of N. crassa Genes (399 KB XLS). Click here for additional data file. Dataset S34 Probability of Enrichment of Genes Containing Two or More Copies of S. cerevisiae Consensus Elements within 1,000 bp Upstream of N. crassa Genes (410 KB XLS). Click here for additional data file. Dataset S35 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 1,000 bp Upstream of N. crassa Genes (383 KB XLS). Click here for additional data file. Dataset S36 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of N. crassa Genes (384 KB XLS). Click here for additional data file. Dataset S37 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 1,000 bp Upstream of M. grisea Genes (381 KB XLS). Click here for additional data file. Dataset S38 Probability of Enrichment of Genes Containing Two or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of M. grisea Genes (405 KB XLS). Click here for additional data file. Dataset S39 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of M. grisea Genes (378 KB XLS). Click here for additional data file. Dataset S40 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 1,000 bp Upstream of As. nidulans Genes (403 KB XLS). Click here for additional data file. Dataset S41 Probability of Enrichment of Genes Containing Two or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of As. nidulans Genes (408 KB XLS). Click here for additional data file. Dataset S42 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of As. nidulans Genes (402 KB XLS). Click here for additional data file. Dataset S43 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 2,000 bp Upstream of Sch. pombe Genes (382 KB XLS). Click here for additional data file. Dataset S44 Probability of Enrichment of Genes Containing Two or More Copies of S. cerevisiae Consensus Elements within 1,000 bp Upstream of Sch. pombe Genes (399 KB XLS). Click here for additional data file. Dataset S45 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 1,000 bp Upstream of Sch. pombe Genes (372 KB XLS). Click here for additional data file. Dataset S46 Probability of Enrichment of Genes Containing One or More Copies of S. cerevisiae Consensus Elements within 500 bp Upstream of Sch. pombe Genes (379 KB XLS). Click here for additional data file. Dataset S47 Significant MEME Matrices Trained on 500-bp or 1,000-bp Upstream Regions of Genes from Non- S. cerevisiae Species (42 KB TXT). Click here for additional data file. Dataset S48 The p -Values of Enrichment Measured for Species-Specific MEME Matrices (11 KB TXT). Click here for additional data file. Dataset S49 The Number of Orthologs Identified in Each Species in Each Gene Group (19 KB XLS). Click here for additional data file. Figure S1 The Enrichment Measured for Randomized Consensus Sequences in Target Gene Group Is Not Statistically Significant Consensus sequences identified by enrichment in Figure 2 were randomized, and the enrichment of the randomized sequence in the denoted gene group was scored. An orange box indicates that the corresponding gene group was enriched for genes containing the randomized sequence, according to the key at the bottom of the figure. Notably, none of the randomized sequences was enriched with p < 2 × 10 –4 in the denoted gene group from any species. (1.1 MB TIF). Click here for additional data file. Figure S2 Significant Enrichment Measured for Randomized Upstream Sequences in Random Gene Groups Is Not Consistent across Species Fifteen of the randomized sequences shown in Figure S1 were enriched below the cutoff of p < 2 × 10 –4 in any gene group. However, the enrichment was not consistent across species. Only two randomized sequences were enriched in the same gene group from two species, although the enrichment pattern did not correlate with the species tree. Thus, randomized sequences are enriched with different characteristics than the functional consensus sequences shown in Figure 2 (898 KB TIF). Click here for additional data file. Figure S3 The Enrichment Measured for S. cerevisiae Consensus Sequences Is Tolerant of Noise in Each Gene Group Our ability to detect conserved cis -regulatory elements in other species requires identification of orthologs of the coregulated S. cerevisiae genes. We wondered how our enrichment-based method would be affected if incorrect orthologs were assigned to individual S. cerevisiae genes, thereby producing “noise” in the gene groups. To test the sensitivity of our method to this type of noise, we performed the following gene replacement control: For each group of S. cerevisiae genes, we performed 100 trials in which 0%–100% of the genes in each group were randomly selected and replaced with random S. cerevisiae genes. The number of trials in which the p of enrichment was below our cutoff of p < 2 × 10 –4 was scored with an orange box, according to the key shown at the bottom of the figure. Nearly all of the cis -elements could be identified in their respective gene groups despite some amount of “noise” in the gene group. (864 KB TIF). Click here for additional data file. Figure S4 Correlation between Rpn4 Element Positions in S. cerevisiae Upstream Regions and Orthologous Regions from Other Species Positions of Rpn4p elements upstream of each S. cerevisiae proteasome gene (x axis) were plotted against the positions of Rpn4p elements upstream of the orthologous proteasome gene from each of the other species (y axis). The linear fit is shown in the upper right corner of each plot. (685 KB TIF). Click here for additional data file. Figure S5 Correlation between MCB Element Positions in S. cerevisiae Upstream Regions and Orthologous Regions from Other Species Positions of MCB elements upstream of S. cerevisiae G1-phase genes (x axis) were plotted against the positions of MCB elements upstream of the orthologous G1-phase gene from each of the other species (y axis). The linear fit is shown in the upper right corner of each plot. (767 KB TIF). Click here for additional data file. Figure S6 Position-Weight Matrices and C is -Sequences Found Upstream of Proteasome Genes Sequences within 500 bp upstream of the S. cerevisiae or C. albicans proteasome genes that matched the species-independent meta-matrix were identified as described. (A) The identified sequences were used to generate sequence logos ( Crooks et al. 2004 ) to represent the set of cis -sequences from S. cerevisiae (top) or from C. albicans (bottom). The height of each letter represents the frequency of that base in that position of the matrix. Positions in the matrices that are statistically different (see Materials and Methods for details) are indicated with an asterisk. (B) Examples of the species-independent meta-matrix found upstream of S. cerevisiae proteasome genes (shown in red) and C. albicans proteasome genes (shown in blue) were pooled and organized by a hierarchical clustering method, as described in Materials and Methods . The sequences found upstream of S. cerevisiae genes only (red bar), C. albicans genes only (blue bar), or both the S. cerevisiae and C. albicans proteasome genes (black bar) are indicated, along with the consensus sequence representing each denoted group. (1.1 KB TIF). Click here for additional data file. Figure S7 3-Amino-Triazole Resistance Due to Sc_Rpn4p Activity S. cerevisiae cells harboring a HIS3 reporter gene with either a minimal promoter (left), minimal promoter + Sequence A (middle), or minimal promoter + Sequence B (right), and overexpressing Sc_Rpn4p from a galactose-inducible promoter, were grown on 0 mM, 1 mM, 5 mM, or 15 mM His3p inhibitor 3-amino-triazole. Two serial dilutions of each strain were plated for each drug concentration. The level of drug resistance is indicative of the level of HIS3 expression ( Guthrie and Fink 2002 ). (631 KB TIF). Click here for additional data file.

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529462

Visualization and exploratory analysis of epidemiologic data using a novel space time information system

Background Recent years have seen an expansion in the use of Geographic Information Systems (GIS) in environmental health research. In this field GIS can be used to detect disease clustering, to analyze access to hospital emergency care, to predict environmental outbreaks, and to estimate exposure to toxic compounds. Despite these advances the inability of GIS to properly handle temporal information is increasingly recognised as a significant constraint. The effective representation and visualization of both spatial and temporal dimensions therefore is expected to significantly enhance our ability to undertake environmental health research using time-referenced geospatial data. Especially for diseases with long latency periods (such as cancer) the ability to represent, quantify and model individual exposure through time is a critical component of risk estimation. In response to this need a STIS – a Space Time Information System has been developed to visualize and analyze objects simultaneously through space and time. Results In this paper we present a "first use" of a STIS in a case-control study of the relationship between arsenic exposure and bladder cancer in south eastern Michigan. Individual arsenic exposure is reconstructed by incorporating spatiotemporal data including residential mobility and drinking water habits. The unique contribution of the STIS is its ability to visualize and analyze residential histories over different temporal scales. Participant information is viewed and statistically analyzed using dynamic views in which values of an attribute change through time. These views include tables, graphs (such as histograms and scatterplots), and maps. In addition, these views can be linked and synchronized for complex data exploration using cartographic brushing, statistical brushing, and animation. Conclusion The STIS provides new and powerful ways to visualize and analyze how individual exposure and associated environmental variables change through time. We expect to see innovative space-time methods being utilized in future environmental health research now that the successful "first use" of a STIS in exposure reconstruction has been accomplished.

Background Geographic Information Systems are beneficial tools in modelling static representations of reality; however they fall short in their ability to handle time. The ability to store, visualize, and analyze both the temporal and spatial dimension of data continues to be a challenging task. Over the past decade, there have been several attempts to include time enabled capabilities into GIS. [ 1 ] and [ 2 ] proposed amendment vectors to extend the vector data model to the time dimension, while others enhanced the grid data model to represent snap-shots of raster data at different time intervals [ 3 ]. Although temporal extensions exist, e.g. [ 2 ] commercial GIS packages do not properly support temporal aspects of spatial data [ 4 ]. The importance of GIS for medical research and epidemiology has long been recognized [ 5 - 7 ], and GIS is frequently used for retrospective exposure reconstruction [ 8 - 10 ]. However the application of GIS to risk and exposure assessment has historically focused on the hazard as the object of interest – such as the locations of contaminated industrial sites with high concentrations of carcinogens – instead of the individual [ 3 ]. More recently exposure assessment using GIS has targeted individuals in their present homes, but relatively little attention has been placed on individual exposure reconstruction involving residential histories and past activities. This in large part is due to the poor ability of current GISs to handle multitemporal geographic information and the movement of individuals within the context of putative exposure sources whose locations and output change through time. Consequently, there have been few attempts to expand on the 'static map' to provide a more accurate view of exposure. The ability to effectively represent, query, and model the temporal dimension is expected to significantly enhance researchers' abilities to undertake environmental health research with georeferenced data. Studying an individual's exposure over time is a key factor in determining risk, particularly for diseases with long latency periods such as cancer [ 3 ], because individual exposure to environmental contaminants (eg carcinogens) can change as people move through space over time. Exposure assessment characterizes the concentration of potential toxins, as well as the frequency and duration of contacts between individuals and those toxins. Therefore, accurate exposure assessment requires estimation of variation in contaminant concentration as well as changes in geographic proximity to contaminant sources over time. This requires models that can account for residential histories and how residential location influences ambient contaminant concentrations as well as exposure opportunities. In this research we applied a STIS to visualize and analyze data from a bladder cancer case-control study. The objective of the epidemiologic research project is to identify a range of factors that have contributed to bladder cancer incidence in Michigan, with the focus on spatial and spatiotemporal patterns of exposure to naturally occurring arsenic in drinking water. Cases are recruited from the Michigan State Cancer Registry and diagnosed in the years 2000–2003. Controls are frequency matched to cases by age (± 5 years), race, and gender, and recruited using a random digit dialing procedure from an age-weighted list. To be eligible for inclusion in the study, participants must have lived in the eleven county study area for at least the past five years and had no prior history of cancer (with the exception of non-melanoma skin cancer). The goal is to enroll 1400 participants in total. This is an ongoing five year project and only some preliminary spatiotemporal datasets, visualization tools, and results are shown here. Conclusive results will not be available for a few more years, until data has been collected and analyzed for all 1400 participants. The STIS is being developed at BioMedware, in Ann Arbor Michigan with funding from the National Institutes of Environmental Health Sciences and the National Cancer Institute. In this paper STIS is used to visualize and analyze data from a bladder cancer case-control study but it can also be used for health/environment interactions or marketplace sales trends. More information about the STIS and a free 30 day download can be evaluated at . Results and discussion Data from a case-control study of bladder cancer in south eastern Michigan was used to evaluate the efficacy of the STIS for documenting and visualizing space-time relationships between cases, controls and putative risk factors. Lifetime exposure to arsenic in drinking water (an element that has been associated with bladder cancer at high levels [ 12 , 13 ]) was reconstructed for each individual by incorporating spatiotemporal information about residential mobility (every address inhabited since birth), occupational history (every full time job since the age of 16), drinking water patterns, and concentration of arsenic in drinking water. Space time information system The motivation for this system comes from the idea that the 'what and where' of conventional GIS needs to be extended to the 'what, where, and when' of reality and spatiotemporal modelling. Based on similar spatiotemporal approaches (e.g. [ 4 ], [ 18 ], [ 19 ]), objects are implemented using the space time model: { object, space-time coordinate, attributes } where object identifies the modelled entity (e.g. person X); space-time coordinate is a spatiotemporal location which may be a space-time point (e.g. latitude, longitude, altitude, date, movement model) or a space-time polygon (e.g. polygon centroid, polygon boundary, date, movement model); and attributes are observations on objects (e.g. income). Within the space time coordinate , in addition to the well known descriptors (e.g. latitude, longitude), we also specify a movement model that defines how the object moves through space as a function of time. Among the simplest of movement models is an instantaneous displacement such that the object ceases to exist at one location and immediately reappears at another location. We use this simple model to describe residential histories. Morphing describes how the shape of geographic features (such as lines and polygons) changes through time. Here an object is comprised of multiple vertices changing shape through time by the addition, deletion and movement of vertices. This is called network morphing (for lines) and polygon morphing (for polygons). Morphing can be gradual, in which case the change in the object's shape occurs over a defined time interval; or it can be abrupt. In our research we utilize this approach to model cadastral systems and the realignment of administrative and political boundaries. This allows us to track, for example, how municipal water districts change through time, and to then estimate arsenic exposure from drinking water for individuals on municipal water supplies. Attributes are observations on variables describing the modelled entity and its environment (e.g. case/control identifier, population size, ethnicity, etc.) Our data model assumes observations occur at discrete times at which the attributes of an object are quantified. Attribute change models describe how the values of attributes change between observation times. The simplest attribute change model is a step function that updates an attribute's value when a new observation is made on that attribute. More complex change functions that obtain values from nearby locations are used to interpolate values through space and time for both categorical and continuous data [ 14 ]. These include techniques from the field of geostatistics that provide a probabilistic framework for space-time interpolation by building on the joint spatial and temporal dependence between observations [ 15 ]. In this research we use the step function approach to model, for example, change in arsenic concentration in potable water when an individual's water supply source is switched from one source of supply to another. We also use geostatistics to model how arsenic concentration in ground water changes spatially and as a function of geology (described in [ 16 ]). Study data We reconstructed individual exposures by incorporating spatiotemporal data on residential mobility (where people have lived throughout their lives), water supplies (private well, city well water, or city surface water), and drinking water habits. Only locations in which the participants have lived or worked for longer than one year were collected and geocoded. Data about diet, smoking, and medical history were also collected by a phone interview or written questionnaire. A point file (where each point represents a participant) was then imported into the STIS along with associated database files containing attribute information such as address and primary source of drinking water. Table 1 is an example of the drinking water and residential mobility database. Even though information for only three participants is shown, seven different addresses and nine different sources of drinking water are represented. (Street addresses are not shown to protect participant's identity). Therefore, a change in address or primary source of water warrants a new row in the database. Table 1 Part of database of participant addresses and water source information Information for four participants is shown. For each change in address or primary source of water a new row is entered in the database. Therefore there are 16 rows in this sample database. Year moved in Year moved out Sample ID City Primary Source of Water 9/12/1935 1/1/1953 1 Swartz Creek Private well 1/1/1956 1/1/1958 1 Swartz Creek Private well, softener 1/1/1958 1/1/1963 1 Swartz Creek Private well 1/1/1963 1/1/1974 1 Swartz Creek Private well, reverse osmosis 1/1/1974 1/1/1990 1 Swartz Creek new private well 1/1/1990 1/1/2002 1 Swartz Creek Community Supply 1/1/2002 1/1/2004 1 Swartz Creek Community Supply, softener 1/1/1976 1/1/1990 2 Livonia Community Supply 1/1/1990 1/1/2004 2 Brighton CS (township well and treatment plant) 1/1/1953 1/1/1961 3 Jackson Community Supply 1/1/1961 1/1/1971 3 Jackson Well (30 ft) 1/1/1971 1/1/1984 3 Michigan Centre Private well 1/1/1984 1/1/1993 3 Vandercook Lake Private well 1/1/1993 1/1/2004 3 Horton Well (280 feet) 1/1/1943 1/1/1958 4 Ferndale Community Supply 1/1/1982 1/1/2004 4 Waterford Community Supply Other point files were imported including present and historical data on industries and contaminated sites in the study area. A township map and water supply boundary map were imported as polygons. In addition to temporal changes in attributes such as township population, source of community's water supply, and number of people served, town boundaries and water supply boundaries changed with time. New towns were incorporated, community systems expanded their borders, and occasionally, communities were combined and town boundaries dissolved. All of these temporal changes were handled using attribute change models and morphing. Importing spatiotemporal datasets We imported shapefiles describing the above data using the STIS data import facility that allows the variables to be time stamped. The user is prompted to import vector information into a new geography or an existing geography (if new information is to be added to an already existing geographic layer the latter will be chosen). The user must tell the system whether the data is (1) a time slice (similar to a collection of GIS static maps) where changes take place at specified times for all objects in the dataset, or (2) a time series where data varies asynchronously and objects move or change attributes at different times. For example Census data are time slice data – attributes remain constant for a decade (1980–1990) and then all attributes are updated with the next decade's census information (1990–2000). On the other hand, data associated with tracking residential histories are time series data, with household moves occurring at different times for each individual. The system imports data at temporal granularities varying from seconds to years; and the data may then be analyzed at these different time scales. Visualization procedures Being able to visualize changes in boundaries and attribute values over time is an effective approach to better understanding and exploring data. Because time is a dimension of the data rather than an attribute all views of the data are easily animated. Analogous to a static GIS, attributes of data are visualized by specifying colour, shape, and size of graphical elements (e.g. symbols). However, in contrast to a GIS, the STIS easily facilitates visualization of changing polygon shapes and attribute values over time by animating maps, histograms, and tables simultaneously. Valuable information that might be lost in an atemporal GIS is captured and can become the focus of analysis in the STIS. There are four major visualization views – maps, graphs (histograms, scatter plots, box plots), tables, and time plots. (1) The map view displays spatial data and the user interacts with the maps by zooming, panning, selecting, and querying. The added feature of the STIS is the animation toolbar. It is employed to show individuals changing place of residence through time; arsenic-emitting industries being founded, operating, and going out of business; municipal water supply districts growing and coalescing; and attribute values, such as arsenic concentrations, changing through time. (2) In the STIS histograms , scatter plots , and box plots are also animated over time. An individual or group of individuals (e.g. cases vs. controls) may be selected at one point in time and the user can explore how that selection's values change through time. For example, we used this feature to explore how individual arsenic exposure changed over a participant's lifetime. We also used it to compare estimated arsenic burdens for the cases to those of the control population. (3) Table views also are animated, as the given value of a variable (such as the arsenic concentration in a municipal water supply) will change through time. Tables thus show how data values change over time by updating a given objects value when it increases or decreases. (4) The time plot graphs time on the x-axis and the value of a variable, such as estimated arsenic exposure, on the y-axis. Objects of interest, such as cases and controls, then map into this bivariate time plot to explore time dependencies in arsenic exposure. Unlike the other views, the time plot is not animated because it already shows the entire time range of the data on the x-axis. A novel feature of the STIS is the ability to time-link visualization windows. Maps, statistical graphics, and tables may be time-linked so that all of the views are synchronized to the same point in time. Animating the time-linked windows then displays the views simultaneously changing through time. We use this feature to display the changing residential locations of the cases and controls along with the locations and emission volumes of arsenic-producing industries. All of this is done within the context of municipal water districts whose boundaries morph and whose arsenic concentrations are dynamic. While this map visualization is occurring we observe how the frequency distributions of modelled arsenic exposure are changing for the cases relative to that of the controls. Participants (cases or controls) are thus easily evaluated and compared to other participants in terms of their residential histories, and population-level characteristics, such as the mean and dispersion for arsenic exposure estimates, may be compared statistically as they evolve over time. Statistical and Cartographic Brushing is employed to link together the views associated with a given dataset. This is made possible by using unique identifiers (such as the participant ID's of the cases and controls, or the names of the municipal water districts) to link together corresponding values on the maps and statistical graphics. Statistical brushing is used to select objects (such as the points on a scatter plot) and to then highlight the corresponding objects on maps and other statistical graphics. Cartographic brushing occurs when objects are selected on a map, and their corresponding values on the statistical graphics are highlighted. We used statistical brushing to select participants with high arsenic exposures, and to then identify their locations on maps of their residential histories. We use cartographic brushing to explore possible associations between proximity to arsenic emitting industries and the local densities of cases relative to the controls. Application of visualization procedures We first investigate changes in the water supply systems (Figure 1 ). It is clear that over a 50 year interval (from 1935–1995) private well owners and some community ground water systems replaced their private wells or ground water systems with a purchased surface water system (hooking up to a larger system such as the Detroit Sewer and Water System). Visualizing this information over time is valuable as it shows areas that historically might have been associated with high arsenic levels. It also is used to help assign arsenic concentrations to previous residences. For some public ground or surface water systems historic arsenic concentrations have been recorded. For participants on such water supply systems we therefore can directly assign water source arsenic concentrations. Historic arsenic concentrations for well water supplies often are not available, and for these we interpolate arsenic concentration values using geostatistical procedures that account for values in nearby wells, spatial covariance in these values, and their dependency on predictors such as groundwater geology [ 16 ]. Figure 1 Change in water supply systems over 50 years (1935, 1965, 1995) Over the years many towns in Oakland County and Genesee County begin to purchase surface water (from Detroit). Visualizing the movement of bladder cancer cases and controls through time is crucial in our analysis of arsenic exposure and how it relates to the incidence of bladder cancer. Figure 2 presents participants at three different time points (1960, 1982, 2001). A case is represented by a circle and a control by a square. In 1960 there were two cases and one control. By 1982 four more cases and two more controls moved into the study area and in 2001 the same number of cases and controls remain in the area. Note that one case and one control have moved residences. The animated map thus informs us regarding the residential mobility of the cases and controls. Spatial and temporal subsets of these populations can then be selected and statistically analyzed and summarized using other visualization windows and statistical methods. Figure 2 Participant movement over 20 years Cases (circles) and controls (squares) continue to move in, out, and around the study area. In 1960 there were two cases and one control. By 1982 four more cases and two more controls moved into the study area and in 2001 the same number of cases and controls remain in the area however one case and one control have moved addresses. Analysis of arsenic exposure In this analysis we are interested in the temporal variability in arsenic exposure in cases versus controls as well as clusters of high arsenic values. Arsenic exposure was calculated by multiplying arsenic concentration (μg/L) by home consumption of water and beverages made with water (L/day) at each residence and for each change in water consumption. Data regarding water and beverage consumption was obtained via survey [ 17 ]. We utilize the box plot to look at means and interquartile ranges through time (Figure 3 for 1988). The windows are time linked and show cases (on the left) and controls (on the right). A more evenly distributed exposure to arsenic in the case subset is indicated by the large interquartile, and 1.5X interquartile range. Figure 3 Box plot of arsenic exposure in 1988 for cases (left) and controls (right) The median is the black line that bisects the box. The upper and lower quartiles, the medians of the upper and lower halves of the data, are the edges of the black box. The "whiskers" on the box, the bars at the top and bottom, are 1.5X the interquartile range. The time plot is another visualization method and provides information over the entire time range (Figure 4 x-axis equals time, y-axis represents arsenic exposure). This graph shows general trends in this preliminary dataset. In the early 1960's arsenic exposure was actually greater for controls (bottom graph) than for cases (upper graph). We also notice that the highest arsenic value (51 μg/L) occurred for a control in 1964 and lasted until the end of the study period. The highest value for a case (38 μg/L) occurred later in the study period (1990). All records are linked to the map view and an investigation of geographical clustering can occur in tandem with the temporal analysis of the time plot. Figure 4 Time graph of arsenic exposure in cases (top) and controls (bottom) Notice the increase in arsenic for both sets after 1951. The increase in arsenic is much larger for controls and remains high for at least two individuals. In addition to the graphical analysis we employed statistical clustering methods to identify spatial clusters of homes with high arsenic concentrations in their water supplies. The Univariate Local Moran is a statistical method used to detect local spatial autocorrelation by decomposing Moran's I into contributions for each location. Here, each location refers to an arsenic value sampled at the home of each participant. Moran's I is a weighted correlation coefficient that is used to determine whether neighbouring areas are more similar than would be expected under the null hypothesis. In this study the local Moran statistic is used to detect where there are statistically significant clusters of high (or low) arsenic values in participants' drinking water. Data regarding arsenic in drinking water was collected at the kitchen tap of each participant from their present residence. Water samples were stored on ice, acidified with 0.2% trace metal grade nitric acid, and refrigerated until analysis. Water samples were subsequently analyzed for arsenic using an inductively coupled plasma mass spectrometer (ICP-MS, Argilent Technologies Model 7500 c) [ 17 ]. A map of arsenic values from participants' drinking water is shown in Figure 5 . The Local Moran analysis was performed on this arsenic dataset resulting in a map of significant clusters (identifying areas as high-high clusters, low-low clusters, low-high outliers, high-low outliers, and areas not significant from background), and a local moran scatterplot. Figure 6 is the result of the local Moran analysis using spatial weights of five (left) and ten (right) nearest neighbours, with 999 randomizations, at the alpha level of 0.05. Generally the two maps look similar, and this is corroborated by similar Global Moran's I values of 0.126279 for five nearest neighbours and 0.129596 for ten nearest neighbours. However, there are differences that arise from analysing spatial pattern at two different local spatial scales. For example, in the northern region of the ten nearest neighbour map we find high-high values indicating high arsenic values surrounded by other high arsenic values. We also see an area of low-low values in the western part of the map, around Lansing. Households in these low-low locations are generally on community water supplies where arsenic values are kept below 50 μg/L to comply with Environmental Protection Agency standards. Conducting the Local Moran analysis at different neighbourhood sizes allows one to evaluate the sensitivity of clustering to different spatial scales. Figure 5 Arsenic in drinking water (2003/2004) Each point represents an arsenic value taken from the kitchen tap at the present residence of each participant. Figure 6 Local Moran analysis at two spatial scales Local Moran analysis with five nearest neighbours is on the left, and with ten nearest neighbours is on the right. Notice the appearance of the high-high cluster to the north, and the increase in size of the low-low cluster to the west as the size of the local neighbourhood is increased Conclusions In this paper we presented a novel application of a space time information system to analyze some preliminary data in an ongoing case-control bladder cancer study. This approach is significant in that it not only visualizes the movement and attribute changes of spatial objects (including cases, controls, arsenic producing industries, and municipal water supplies) but also allows the user to compare values of these objects over time by time-linking windows. This ability to handle high temporal resolution data is enabling new approaches to exposure assessment. In the near future the STIS will be able to integrate exposure assessment models using an Application Programmers Interface (API). Users will have the flexibility to program specific models outside the software and then visualize their outcome in the STIS using the API. For less technically sophisticated users, a methods toolbar will be included, where common modelling algorithms will be made available using a simple calculator-type interface. Other plans for the software include importing and supporting raster files, exporting animated maps as movies (for presentations), visualizing geospatial lifelines [ 18 , 19 ] in a separate window once objects are selected, and adding spatiotemporal clustering statistics to the methods toolbar. Competing interests Some authors are also affiliated with BioMedware a research company that also develops software for the exploratory spatial and temporal analysis of health and environmental data. With funding from the National Cancer Institute, GMJ, AMK, and GAA developed STIS, which is a commercial product of Terraseer.

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529310

The effect of chemotherapy combined with recombination mutant human tumor necrosis factor on advanced cancer

Background Past studies suggested that tumor necrosis factor (TNF) assisted anti-tumor treatment and intensified the sensitivity of chemotherapy. However its clinical application has been curbed because of its low purity, high dosage, and strong toxicity. This research, through perspective random clinical control experiment, observed the therapeutic effect of the treatment of late malignant tumor through the injection of recombinant mutant human tumor necrosis factor (rmhTNF) combined with general chemotherapy and its adverse reactions. Methods 105 patients with advanced malignant tumor were randomly divided into trial group, 69 patients, and control group, 36 patients. Injection of rmhTNF 4 × 10 6 u/m 2 was given to the trial group, from the 1 st to 7 th days, the 11 th to 17 th days combined with chemotherapy course. The chemotherapy plan was as follows: CAP for patients with the NSCLC; FAM for patients with gastric cancer; FC for patients with colorectal cancer. One treatment cycle lasted for 21 days and two cycles were scheduled. The control group was given only the same chemotherapy as the trial group. Results In the trial group there was 1 CR case and 12 PR cases, and the response rate is 13/69 (18.84%); in the control group 1 PR case, the response rate 1/36 (2.78%). The response rate of the trial group was significantly higher than that of the control group ( P = 0.022). The response rate for NSCLC in the trial group was 8/17 (47.06%), and 1/6 (16.67%) in the control group. The response rates for gastric cancer and colorectal cancer in the trial groups also were higher than those of the control groups. After the treatment the KPS is 89.00 ± 9.92 in the trial group, and 84.17 ± 8.84 in the control group, with a significant difference between the two groups ( P = 0.028). The adverse reactions of rmhTNF injection included: pain in the injection area, chill, hardening and swelling and redness in the injection area, fever, ostealgia and myosalgia, and cold-like symptoms. All these adverse reactions were mild and bearable. Conclusions The administration of rmhTNF injection in combination with general chemotherapy is an effective and secure means in treating advanced malignant tumor.

Tumor necrosis factor (TNF) is a polypeptide produced by monocytic macrophages and T-lymphocytes stimulated by endotoxin[ 1 ]. It has been well shown in vivo or in vitro that TNF assists anti-tumor treatment and intensified the sensitivity of chemotherapy to many different kinds of tumor cells [ 2 - 5 ]. However its clinical application has been curbed because of its low purity, high dosage, and strong toxicity. Via the cooperation between the Forth Military Medical University and Shanghai Celstar Bio-pharmaceutical Holding Co. Ltd, an injection of recombinant mutant human tumor necrosis factor (rmhTNF) which is a genetic engineering TNF of a high activity and low toxicity, has been produced by rebuilding natural TNF with protein engineering technics. Phase I clinical trial (tolerance test) showed that the patients had good tolerance. and the toxicity of rmhTNF was slight As a participant of the Phase II and Phase III clinical study of rmhTNF, we observed the therapeutic effect of the treatment of late malignant tumor through the injection of recombinant mutant human tumor necrosis factor combined with general chemotherapy and its toxicity in a multi-center, random clinical control Phase II and Phase III clinical study of rmhTNF during October 2000 ~ May 2002. The results are reported as below. 1. Materials and Methods 1.1 Patients 105 patients from our department with advanced malignant tumors diagnosed via pathologic or cytological examinations were randomly collected, of which 23 were non-small cell lung cancer, 50 gastric cancers and 32 were colorectal cancers. Moreover, 79 of them were males and 26 of them were females. The range of their ages was 25~70, with the median age 52 years old. All of them were during their later phases of either recrudescent or metastatic cancers, had no sugary indexes and were taking conservative medicine treatment. KPS scoring for them before treatment were ≥ 60, neutrophil ≥ 2.0 × 109/L, PLT ≥ 100 × 109/L and Hb ≥ 90 g/L. They had almost normal functions of the heart, liver and kidney and at least had one evaluable tumor focus. They had not taken any other anti-tumor treatment one month before the experiment and they had a prospective survival time > 3 months. All of the patients were well informed and written consents were signed. Then they were randomly divided into two groups, i.e. the trial group of 69 patients and the control group of 36 patients, the conditions of the two groups were comparable ( P >0.05, see Table 1 ). In the individual group of three tumors, the stage of the disease is of no significant difference ( P >0.05, see Table 1 ). Table 1 The General Data of the Trial and Control Group Item Trial group (n = 69) Control group (n = 36) P Sex 0.362 Male 50 29 Female 19 7 Median age (year) 52 51 0.437 Type of tumors 0.638* NSCLC 17 6 Gastric cancer 32 18 Colorectal cancer 20 12 KPS ( ) 85.31 ± 6.07 86.69 ± 7.81 0.334 Clinical stage 0.630 III 11 8 IV 58 28 NSCLC III 5 3 0.621* IV 12 3 Gastric cancer III 4 3 0.684 IV 28 15 Colorectal cancer III 2 2 0.620* IV 18 10 *The p value is calculated by Fisher exact chi-square because n < 30 or some cells have expected count less than 1. 1.2 Source of drugs Injection of rmhTNF which was in powder form of 500 × 10 5 u/tube (number 00061) was made and provided by the Forth Military Medical University and was stored at 4°C in refrigerator. 1.3 Treatment protocol For the trial group, injection of rmhTNF 4 × 10 6 u/m 2 was given from the 1 st to 7 th days, the 11 th to 17 th days combined with chemotherapy course. The chemotherapy plan was as follows: CAP (CTX 750 mg/m 2 , d 1 , ADM 40 mg m 2 , d 1 , DDP 30 mg m 2 , d 1 -d 3 ) for patients with the non-small cell lung cancer; FAM (5-FU500 mg/ m 2 , d 1 -d 5 , ADM 40 mg/ m 2 , d 1 , MMC 6 mg/ m 2 , d 1 ) for patients with gastric cancer; FC (5-FU 500 mg/ m 2 , d 1 -d 5 , CF 100 mg/ m 2 , d 1 -d 5 ) for patients with colorectal cancer. One treatment cycle lasted for 21 days and two cycles were scheduled. For the control group, only the same chemotherapy as the trial group was given. Signs, symptoms and adverse reactions were carefully observed during the treatment. Weekly examinations of blood routine were performed before and after treatment, while liver and kidney functions, urine routine, EEG, liver ultrasonic and chest X-ray examinations were performed before and after every treatment cycle. CT examinations of the evaluable tumor focuses were performed one time before treatment, when treatments were finished and after 4 weeks of the finish. 1.4 Evaluation of response and toxicity 1.4.1 Evaluation of response Complete response (CR) is that, the disappearance of all lesions and no appearance of new disease for at least 4 weeks. Partial response (PR) is defined as a reduction by at least 50% in the sum of the products of the two longest diameters of all lesions maintained for at least 4 weeks with no appearance of new disease. Minimal response (MR) is different from PR with a reduction by at least 25%, but not more than 50%. Stable disease (SD) is a less than 25% reduction or less than 25% increase in the sum of the products of the two perpendicular diameters of all measured lesion with no appearance of new disease. Progression disease (PD) is that, an increase greater than 25% over the size present at entry into the study or, for patients who respond, the size at time of maximum regression, or the appearance of new areas of malignant disease. CR+PR were rated as response rate. 1.4.2 Toxicity The toxicity was followed the WHO acute and sub-acute toxic rating 2. Results 2.1 Response to treatment After two treatment cycles, the trial group had 1 CR case, 12 PR cases, 11 SD cases and 18 PD cases, and the response rate was 13/69(18.84%). The control group, on the other hand, had 1 PR case, 4 MR cases, 19 SD cases and 12 PD cases, and had a response rate 1/36 (2.78%). The response rate of the trial group was significantly higher than that of the control group ( P = 0.022, see Table 2 ). Table 2 The Response Rate in the Trial and Control Group after Two Treatment Cycles Group n CR PR MR SD PD Response rate P Trial 69 1 12 11 27 18 13/69 (18.84%) 0.022 Control 36 0 1 4 19 12 1/36 (2.78%) The response rate for NSCLC of the trial group was 8/17 (47.06%), higher than that of the control group 1/6 (16.67%) but without statistic significance ( P = 0.208). The response rates for gastric cancer was 12.50% (4/32), while for the controls were 0.00% (0/18) without statistic significance ( P = 0.283). The response rates for colorectal cancer was 5.00% (1/20), while no response case in the controls group (0/12), but there was still no statistic significance ( P = 1.000, see Table 3 ). Table 3 The Response Rate in the Trial and Control Group for Different Type of Tumors Group n CR PR MR SD PD Response rate p * NSCLC Trial 17 1 7 3 4 2 47.06% (8/17) 0.208 Control 6 0 1 1 3 1 16.67% (1/6) Gastric cancer Trial 32 0 4 6 13 9 12.50% (4/32) 0.283 Control 18 0 0 2 9 7 0.00 (0/18) Colorectal cancer Trial 20 0 1 2 10 7 5.00% (1/20) 1.000 Control 12 0 0 1 7 4 0.00 (0/12) *The p value is calculated by Fisher exact chi-square because n < 30 or some cells have expected count less than 1. 2.2 Life quality Before the treatment there was no significant difference of the general status (KPS) between the two groups ( P > 0.05). After the treatment the KPS was 89.00 ± 9.92 in the trial group, and 84.17 ± 8.84 in the control group, with a statistic significant difference (p = 0.028, see Table 4 ). Table 4 Before and after Treatment, KPS Value in the Trial and Control Group Group Trial (n = 69) Control (n = 36) P Before treatment ( ) 85.31 ± 6.07 86.69 ± 7.81 0.334 After treatment ( ) 89.00 ± 9.92 84.17 ± 8.84 0.028 2.3 Toxicity Fever, cold-like symptoms, ostealgia and myosalgia, chill, pain in the injection area, hardening and swelling and redness in the injection area were much more happened in the trail group compared with the control group (P < 0.01 = , while there were no significant differences between the two groups on the frequencies of anemia, leukopenia, thrombocytopia and nausea / vomiting (P > 0.05). No abnormalities correlated with drugs were found in liver or kidney functions, urine routine, EEG and blood pressure (see Table 5 ). Table 5 Toxicity in the Trial and Control Group Toxicity Trial (n = 69) Control (n = 36) P * 0 I II III IV 0 I II III IV Anemia 37 16 8 7 1 21 9 4 1 1 0.665 Leukopenia 28 23 9 9 0 17 13 4 2 0 0.570 Thrombocytopia 59 5 2 2 1 31 3 1 1 0 0.557 Nausea / Vomiting 32 16 19 2 0 18 4 11 2 1 0.476 Fever 52 12 5 0 0 36 0 0 0 0 0.000 Eruption 67 2 0 0 0 36 0 0 0 0 0.274 Cold-like symptoms 47 19 3 0 0 36 0 0 0 0 0.000 Ostealgia / Myosalgia 46 21 2 0 0 36 0 0 0 0 0.000 Chill 38 31 0 0 0 36 0 0 0 0 0.000 Pain in injection area 13 41 15 0 0 36 0 0 0 0 0.000 Hardening, swelling and redness in injection area 42 17 10 0 0 36 0 0 0 0 0.000 *The p value is calculated by Fisher exact chi-square because n<30 or some cells have expected count less than 1. 3. Case report A 54-year-old man hospitalized at August 27, 2001 with complains of "left chest pain accompanied by cough and hard breath for half a month". Physical examination after hospitalization showed: enlarged lymph node of 3 × 3 cm above the right clavicle, hard and immobile. Chest CT on September 27, 2001 (see Figure 1 ) showed: conglomeration of a size of 5.5 × 4.2 cm at the left lower hilus pulmonis, large amount of accumulation of fluid in the left thoracic cavity, enlarged lymph nodes in the mediastinum. Biopsy of the lymph node above the right clavicle showed: transferred adenocarcinoma. Cancer cells were found in the fluid in the thoracic cavity after centrifugation. The diagnosis was "Adenocarcinoma on the left lower lung, stage T 4 N 3 M 0 IIIb". Chemotherapy of protocol CAP + rmhT NF injection (i.m.) was given from October 4 to November 14, 2001. Two weeks later, a clear relief of hard breath and cough was found. After two periods of therapy (November 16, 2001), physical examination showed shrinkage of lymph node of 0.5 × 0.5 cm above the right clavicle, and Chest CT (see Figure 2 ) showed: clear shrinkage of conglomeration of 3.0 × 2.5 cm at the left lower hilus pulmonis, small amount of accumulation of fluid in the left thoracic cavity. A callback of CT one month later showed: conglomeration was of the size of 4.0 × 2.8 cm. The curative effect was confirmed as "PR". Figure 1 Chest CT before treatment (27-Sep-2001) show that conglomeration of a size of 5.5 × 4.2 cm at the left lower hilus pulmonis, large amount of accumulation of fluid in the left thoracic cavity, enlarged lymph nodes in the mediastinum. Figure 2 Chest CT after treatment (16-Nov-2001) show that clear shrinkage of conglomeration of 3.0 × 2.5 cm at the left lower hilus pulmonis, small amount of accumulation of fluid in the left thoracic cavity. 4. Discussion Tumor necrosis factor (TNF) is a polypeptide produced by monocytic macrophages and T-lymphocytes stimulated by endotoxin. It can act as modulator to immunity and induces anti-tumor effects in hosts. It also has direct cytotoxic effects and inhibitory effects on cellular growth. It can kill the tumor cell without notable toxic effect on the normal cells [ 1 ]. Studies have shown that the anti-tumor mechanism of the tumor necrosis factor includes 1) killing the tumor cell directly [ 3 ]; 2 inducing the apoptosis of tumor cells [ 3 ]; 3) reversing more drug resistance of tumor cell and improving the sensitiveness of chemotherapy [ 3 ]; 4) destroying the blood supply of tumor tissue [ 4 ]; 5) increasing the killing effects of immune-effect cells on the tumor cells [ 3 ]. However, its clinical application has been curbed because of its low purity, high dosage, and strong toxicity. Studies have also shown that, a higher anti-tumor effect and lower toxicity were got by modified some structure of TNF. Nakamura [ 6 ] prepared a novel recombinant tumor necrosis factor-α (TNF) mutant (mutant 471), in which 7 N-terminal amino-acids were deleted and Pro 8 Ser 9 Asp 10 was replaced by Arg-Lys-Arg, and compared its biological activity with that of wild-type recombinant TNF. Mutant 471 had a 7-fold higher anti-tumor activity against murine L-M cells in vitro, and a higher binding activity to TNF receptors on L-M cells, than wild-type TNF. Kamijo[ 7 ] reported that TNF(C-Phe), in which the C-terminal leucine of TNF molecule was replaced by phenylalanine, was 20-times as potent in induction of differentiation of human myelogenous leukemia cells (U-937 cells) as the parent TNF(N-Met). The rmhTNF has been obtained successfully from hTNF-α by gene engineering technology which was mutated by deleting 7 amino acids at the N-terminus, replacing Pro 8 Ser 9 Asp 10 by Arg-Lys-Arg, and substituting Leu157 with Phe [ 8 ]. Phrase I clinical trial indicated that, all of 32 patients who were randomly grouped into six groups were treated with different dose: 2.5 × 10 5 u/m 2 , 5 × 10 5 u/m 2 , 1 × 10 6 u/m 2 , 2 × 10 6 u/m 2 , 3 × 10 6 u/m 2 , 4 × 10 6 u/m 2 , were well tolerable. The present study has shown that shortly after the combined chemotherapy with rmhTNF, 24/69 (34.78%) of the focuses were more or less absorbed or subsidized, of which there were 1 CR case and 12 PR cases, with the response rate was 13/69 (18.84%), while in the control group only 5/36 (13.89%) cases had reduced focuses with only 1 PR case and the response rate 1/36 (2.78%). The response rate of the trial group was significantly higher than that of the control group ( P = 0.022). Analysis of the therapeutic effects in different kind of diseases showed that the response rate for NSCLC of the trial group was 8/17 (47.06%), higher than that of the control group 1/6 (16.67%), which also means that TNFα has suppressive effects on lung adenocarcinoma[ 9 ]. The reason why there was no statistic significance ( P > 0.05) between the two groups may be due to too small samples in this investigation. The response rates for gastric cancer and the colorectal cancer were both quite low, i.e. 4/32 (12.50%) and 1/20 (5.00%), respectively, while for the controls were 0/18 and 0/12, respectively (0.00%) and without statistic significance ( P > 0.05). Such a result may be mainly due to the fact that most of the patients had taken combined chemotherapy before and that samples in both groups were quite small. It was thought [ 2 ] that the anti-tumor activity of TNF may co-activate some chemotherapy drugs. Results of the present study showed that the combined therapy of TNF and chemotherapy may be still effective on previously chemotherapy drug resistant tumors, which also means that TNF has co-activating effects on chemotherapy drugs. Moreover, after two treatment cycles, scoring for the general status (KPS) was 89.00 ± 9.92 in the trial group and 84.17 ± 8.84 in the control group, with a statistic significant difference ( P = 0.028). It shows that the combined rmhTNF chemotherapy may benefit the quality of the patients' life. It has already been reported[ 2 - 5 , 10 , 11 ] that the toxicity of TNF in phase I or II clinical trials are mainly chill, fever, local redness, swelling and pain, hypotension, nausea, vomiting, myalgia, fatigue and diarrhea, while pulmonary hemorrhage and severe hepatic dysfunction also have been observed[ 12 ]. But there are no reports on the toxicity of rmhTNF. The present study showed that some of the patients had pain in the injection area, chill and hardening, swelling and redness in the injection area of which the incidences were 81.2%(56/69), 44.9%(31/69) and 39.1% (27/69), respectively, but of a low degree and the patients had good tolerance. The symptoms of fever, ostealgia and myosalgia and cold-like symptoms were more in the trail group than that in the control group, all of which were of grade I or II. They mainly happened when the drugs were given at the 3 rd or 5 th times, and can be relieved after taking 25 mg metacen, and can disappear automatically after the finish of the therapy. There were no significant differences between the two groups on the number of cases which showed marrow suppression or nausea / vomiting, and on the degree of those symptoms. There were no cases which showed rmhTNF-correlated abnormal liver or kidney functions, urine routine, EEG and blood pressure. In summary, combined therapy of rmhTNF and chemotherapy has co-activating and sensitivity improving effects on the treatment of advanced malignant tumors, and may increase the recent responsive effectiveness with an improvement of the general status and quality of patients' lives. The main adverse reactions of the local injection of rmhTNF are pain in the local injection area, chill, hardening and swelling and redness in the injection area, fever, ostealgia and myosalgia and cold-like symptoms, all of which were of light to moderate degree and are tolerable.

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543446

HTLV-1 p30II: selective repressor of gene expression

Human T-lymphotropic virus type-1 (HTLV-1) is a complex retrovirus that causes adult T-cell leukemia/lymphoma (ATL) and is implicated in a variety of lymphocyte-mediated disorders. HTLV-1 pX ORF II encodes two proteins, p13 II and p30 II whose roles are beginning to be defined in the virus life cycle. Previous studies indicate the importance of these viral proteins in the ability of the virus to maintain viral loads and persist in an animal model of HTLV-1 infection. Intriguing new studies indicate that p30 II is a multifunctional regulator that differentially modulates CREB and Tax-responsive element-mediated transcription through its interaction with CREB-binding protein (CBP)/p300 and specifically binds and represses tax/rex mRNA nuclear export. A new study characterized the role of p30 II in regulation of cellular gene expression using comprehensive human gene arrays. Interestingly, p30 II is an overall repressor of cellular gene expression, while selectively favoring the expression of regulatory gene pathways important to T lymphocytes. These new findings suggest that HTLV-1, which is associated with lymphoproliferative diseases, uses p30 II to selectively repress cellular and viral gene expression to favor the survival of cellular targets ultimately resulting in leukemogenesis.

The complex sequence of events set in motion by human T-lymphotropic virus type 1 (HTLV-1) to cause proliferation and ultimately transformation of T lymphocytes is beginning to be unraveled. Only recently has it become clear that viral encoded proteins, the so-called "accessory" gene products of this complex retrovirus, play an integral role in the pathogenic process. In addition to the structural and enzymatic gene products, HTLV-1 encodes regulatory and accessory proteins from four open reading frames (ORF) in the pX region between env and the 3' long terminal repeat (LTR) of the provirus [ 1 , 2 ]. The well studied Rex and Tax positive regulators are encoded in the ORF III and IV, respectively. Rex plays a critical role in nuclear export of unspliced or singly spliced viral mRNA [ 3 , 4 ]. Tax orchestrates multiple interactions with cellular transcription factors and activates transcription from the viral promoter and modulates the transcription or activity of numerous cellular genes involved in cell growth and differentiation, cell cycle control, and DNA repair [ 5 , 6 ]. Recent studies have indicated novel roles for pX ORF I and II gene products in the replication of HTLV-1 [ 7 - 9 ]. Although the study of these gene products were largely by-passed by virologists until the mid 1990's, they intensified when infectious molecular clones provided the tools to better understand their role in vivo . Both HTLV-1 pX ORF I and II mRNAs have been detected in infected cell lines and blood leukocytes from HTLV-1-infected subjects including ATL and HAM/TSP patients [ 10 , 11 ]. Also, immune responses of HTLV-1 infected patients and asymptomatic carriers indicate that these proteins are expressed in vivo [ 12 - 14 ]. Molecular clones of HTLV-1 with selective mutations of ORF I and II have revealed the requirement of p12 I and p13 II /p30 II in the establishment of infection and maintenance of viral loads in a rabbit model of infection [ 15 - 17 ]. The nuclear and nucleolar localizing p30 II has minimal homology to transcription factors Oct-1 and -2, Pit-1, and POU-M1 [ 18 - 21 ]. In addition, the protein co-localizes with p300 in the nucleus and physically interacts with CREB binding protein (CBP)/p300 and differentially modulates cAMP responsive element (CRE) and Tax response element-mediated transcription [ 21 , 22 ]. Intriguing recent reports also indicate a post-transcriptional role of HTLV-1 p30 II and HTLV-2 p28 II (homologous protein encoded in the HTLV-2 pX ORF II region), in repressing the export of tax/rex mRNA from the nucleus [ 23 , 24 ]. Thus, it appears that HTLV-1 has yet another multifunctional protein with transcriptional and post-transcriptional roles in regulating viral gene expression. Microarrays are important tools to gain insight into changes in gene expression profiles of virus-infected cells. This approach has been primarily used to investigate gene expression in HTLV-1-immortalized/transformed cell lines or in cells from ATL patients [ 25 - 29 ]. In the report by Michael et al. [ 30 ] the authors used the Affymetrix U133A human gene chip to test the role of HTLV-1 p30 II as a regulator of gene expression in Jurkat T cells. They identified alterations in gene expression profiles unique to cell cycle regulation, apoptosis, and T lymphocyte signaling/activation. Although p30 II expression, as might be expected from earlier reports, resulted in a general repressive pattern of gene expression, their data indicated that the viral protein selectively spared or enhanced NFAT, NFκB, and AP-1 mediated transcription in T cells undergoing co-stimulation. Signaling pathways primarily affected by p30 II as measured by luciferase reporters included both NFAT and NFκB, which increased from approximately 3 to 11 fold, depending on co-stimulatory treatment. Overall, this study supports earlier reports on the repressive role of HTLV-1 p30 II in gene expression [ 21 - 24 ] and reveals new potential mechanisms by which p30 II may play a role in HTLV-1 replication (figure 1 ). The effects of p30 II appear to overlap or counteract the influence of other HTLV-1 regulatory proteins like Tax or other accessory proteins such as p12 I . Further studies to test if these proteins act coordinately or synergistically will undoubtedly shed light on this issue. It is possible that HTLV-1 employs selective use of these viral proteins during various stages of the infection to promote cell proliferation, a hallmark of the diseases associated with the deltaretrovirus family. Whatever the outcome of these studies, it is clear that "accessory" proteins, like p30 II , may have "essential" roles in the life cycle of HTLV-1. Abbreviations HTLV-1, human T cell lymphotropic virus type-1 ATL, adult T cell leukemia HAM/TSP, HTLV associated myelopathy/tropical spastic paraparesis ORF II, open reading frame II LTR, long terminal repeat CRE, cAMP responsive element CREB, cAMP response element binding protein NFAT, nuclear factor of activated T cells NFκB, nuclear factor kappa B AP-1, activator protein 1 Competing Interests The author(s) declare that they have no competing interests. Figure 1 Model for HTLV-1 p30 II transcriptional and posttranscriptional gene regulation. The cell nucleus surrounded by the nuclear membrane and key components are shown. p30 II can directly interact with CBP/p300 and modulate transcription of viral and/or cellular genes. At low concentration p30 II may stabilize the transcription complex and potentiate transcription, whereas a high concentration it may compete for limited amounts of CBP/p300 and repress gene expression. p30 II (as well as the homologous p28 II of HTLV-2) specifically binds tax/rex mRNA and block its export, reducing Tax and Rex and ultimately repressing viral gene expression. This interaction may be directly linked to splicing factors and splicing and/or the juxtaposition of specific exon/exon junction sequences. Thus, p30 II is a multifunctional protein with transcriptional and post-transcriptional roles in regulating viral and/or cellular gene expression.

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548513

An interactive course to enhance self-efficacy of family practitioners to treat obesity

Background Physicians' awareness of their important role in defusing the obesity epidemic has increased. However, the number of family practitioners who treat obesity problems continues to be low. Self-efficacy refers to the belief in one's ability to organize and execute the courses of action required to produce given attainments. Thus, practitioners who judge themselves incapable of managing obesity do not even try. We hypothesized that practitioners' self-efficacy and motivation would be enhanced as a result of participating in an interactive course designed to enrich their knowledge of obesity management. Methods Twenty-nine family practitioners participated in the course, which was accompanied by qualitative interviews. The difference between the physicians' pre-course and post-course appraisals was tested by paired t -test. The interviews were analyzed by qualitative methods. Results Post-course efficacy appraisals were significantly higher than pre-course appraisals ( p < 0.0005). A deeper insight on the practitioners' self-efficacy processes was gained through reflection of the practitioners on their self-efficacy during the interviews. Conclusions Up-to-date information and workshops where skills, attitudes and social support were addressed were important in making the program effective.

Background Obesity is becoming increasingly common and is recognized as a major public health problem worldwide [ 1 - 3 ]. In the UK, the overweight and obese population increased by almost 15% between 1980 and 1992. Similar increases have been noted in many countries, including the USA [ 4 ], Sweden [ 5 ] and the Netherlands [ 6 ]. In Israel, 55% of females and 58% of males aged 25–64 were reported to be overweight or obese (Body Mass Index >25 kg/m 2 ) in a Mabat survey [ 7 ] in 2000. Guidelines published in 1996 for the management of obesity recommended setting a modest weight loss and weight maintenance, rather than a targeted ideal weight, as goals [ 8 ]. Lately, pharmacological therapies have been proposed as adjuncts to diet and lifestyle changes to improve long-term weight loss [ 9 ]. The World Health Organization declared obesity an epidemic in developed countries. Awareness of physicians of their important role in defusing the obesity epidemic has increased. Yet, the number of family practitioners (FP) treating obesity problems continues to be low [ 10 ]. Many chronic health problems are exacerbated by unhealthy behaviors and harmful environmental conditions. From the psychological perspective, healthful lifestyles and environmental conditions may yield large health benefits. The widespread adoption of a healthier lifestyle rather than medical technologies has resulted in a substantial decline in premature mortality and morbidity [ 11 ]. The media plays a major role in informing the public about health risks. Efforts to convince people to adopt health practices that prevent disease have relied heavily on persuasive communications in health education campaigns [ 11 ]. Health benefits are accelerated by community-wide efforts to reduce habits that impair health [ 12 ]. Self-efficacy refers to the belief in one's ability to organize and execute the courses of action required to produce a given attainment [ 11 ]. Such beliefs influence the courses of action people choose to pursue, how much effort they put into a given endeavor and how long they will persevere in the face of obstacles and failure. If people believe they have no power to produce results, they will not attempt to effect changes. Self-efficacy is not a fixed ability that one has or lacks in one's behavioral repertoire. Rather, it is a thinking process, a generative capability in which cognitive, social, emotional and behavioral sub-skills are organized and effectively orchestrated to serve innumerable purposes. Self-efficacy is concerned not with the number of skills one has, but with what one believes one can do with the skills under a variety of circumstances. Efficacy beliefs operate as a key factor in a generative system of human competence [ 11 , 13 - 15 ]. Self-efficacy is an important contributor to performance accomplishments, whatever the underlying skills might be [ 11 ]. The greater a person's efficacy beliefs, the greater the academic challenges one sets for oneself and the greater their intrinsic interest [ 16 ]. Personal efficacy beliefs influence the level of interest in occupational pursuits even when the influence of ability is removed [ 17 , 18 ]. A sense of personal efficacy is constructed through a complex process of self-persuasion. Efficacy beliefs are the product of cognitive processing of diverse sources of information conveyed inactively, vicariously, socially and physiologically. Once formed, efficacy beliefs contribute to the quality of human functioning [ 11 ]. Self-efficacy is measured by the strength of a subject's beliefs in the ability to execute requisite activities. Social cognitive theory distinguishes among three basic processes of personal change: the adoption, general usage and maintenance over time of new behavioral patterns [ 19 ]. Efficacy beliefs affect each of these phases [ 11 ]. Self-efficacy conceptualizes a person's perceived ability to perform on a task as a mediator of performance on future tasks [ 11 , 13 ]. A change in the level of self-efficacy can predict a lasting change in patients' behavior if there are adequate incentives and skills [ 13 - 15 ]. People's beliefs that they can motivate themselves and regulate their own behavior play a crucial role in whether they even consider acting. Thus, practitioners who judge themselves incapable of treating obesity do not even try. Obesity has not been considered a disease till recent years. Physicians did not treat obesity unless they were asked to do so by patients. To our knowledge and after a literature search, no intervention studies have yet been conducted to change the self-efficacy of FPs in Israel towards treating obese people. Among other courses for which physicians usually receive credits towards their annual professional training, a course was offered by the Israeli Academic Medical Council. The course was initiated by the Israeli Association of FPs and recommended by the Medical Professional Journal of FPs in Israel. Registration in the course was open to all FPs. The present research was a preliminary study. This being the case, the first group of FPs who attended the new course participated in it. Though that group contained a small number of subjects, the importance of investigating a new program contribution to FPs self-efficacy for future research was evident. The objectives of the course were to enrich the knowledge of FPs with up-to-date information on obesity and to raise their motivation to treat it. The study objective was to determine if an interactive course would raise the self-efficacy of FPs to treat obesity. It was hypothesized that the self-efficacy of FPs would be enhanced as a result of participating in an interactive obesity-treatment course. Methods Subjects Twenty-nine FPs (62% female) chose to participate in the course along with other Continuing Medical Education (CME) courses. All participants work as FPs in public health care clinics throughout the country. Design This study was based on a one group, pre-course – post-course test design, without a control group. It was accompanied by qualitative interviews to validate the results of the data analysis. Research tools The strength of the efficacy beliefs of the FPs to treat obesity was estimated by using a five point scale Likert type questionnaire containing nine items (Table 1 ). The subjects were asked how confident they were in the ability to treat obesity across problem situations. The levels of confidence were as follows: 1. not at all confident, 2. somewhat confident, 3. moderately confident, 4. very confident, 5. completely confident. The questionnaire was filled out before and after the course. The items were generated from the criteria on the domain map that was constructed on the basis of theoretic analyses of knowledge accumulated in the domains of self-efficacy and health behavior change [ 11 , 13 - 15 ] and consultation with experts. The researchers used the analytic induction method for the theoretic analysis of knowledge. The map's main criteria were: obesity – a serious disease; up-to-date clinical and behavioral knowledge; processes of change, e.g: decision making, planning, monitoring and behavior controlling; resilience; lack of time and social involvement. Table 1 Original domain map criteria and the sequence of criteria in the questionnaire regarding the self-efficacy beliefs of family practitioners to manage obesity Original sequence of criteria Sequence in the questionnaire Efficacy to treat a problem of high priority 1 Efficacy to give up-to-date and correct information 7 Efficacy to persuade, support and help patients make decisions 3 Efficacy to make patient plan behaviors and situations 6 Efficacy to make patient monitor his behavior 4 Efficacy to make patient control behaviors and situations 9 Efficacy to treat obesity regardless of previous failure or unsuccessful experiences 2 Efficacy to treat obesity regardless of lack of time 5 Efficacy to bring about involvement of other people in the patient's behavior change process 8 The Alpha Cronbach for the reliability of the tests was α = 0.88 for the pre-course test and α = 0.90 for the post-course test (Table 2 ). Table 2 Pre-course (α = 0.88) and post-course (α = 0.90) scale mean, SD, item total correlation, and α if item deleted (n = 29) Item no. Mean SD Item total correlation α, if item deleted Pre-course 1 0.77 0.13 44.03 0.88 2 0.61 0.15 43.62 0.87 3 0.53 0.16 43.40 0.86 4 0.59 0.16 42.83 0.86 5 0.74 0.15 39.85 0.87 6 0.84 0.15 41.39 0.87 7 0.44 0.13 46.61 0.88 8 0.77 0.16 39.89 0.86 9 0.72 0.14 39.36 0.85 Post-course 1 0.67 0.16 20.10 0.88 2 0.75 0.16 20.67 0.88 3 0.67 0.16 20.11 0.88 4 0.46 0.14 21.17 0.90 5 0.59 0.15 19.82 0.90 6 0.72 0.15 20.29 0.88 7 0.68 0.15 21.50 0.89 8 0.71 0.16 19.21 0.88 9 0.81 0.16 19.99 0.88 The following aspects of structure validity were examined: (a) for the content aspect, the items matched the domain concept map. Final version was rewritten on the basis of experts' and researchers' comments. The items were finally presented in an nonsequential order to make subjects think while reading the questions and not relate to earlier answers; and (b) for the substantive aspect, FPs were interviewed regarding their self-efficacy to assure that the questions were clear and did not require rewording. The interview was a 30 min. open interview. A physician was given open questions such as: "Describe your feelings and thoughts of efficacy to treat obesity" or "How the self-control lectured help your efficacy perceptions". The subject was free to speak openly on the issue. The interview was actually a verbal reflection of thoughts and feelings of the subjects. It was recorded and later on transcribed by the researchers. The interview was analyzed by the constant comparative qualitative method of analysis [ 20 , 21 ]. Every sentence said by the subject in the interview was considered a unit to be taken into account for the content analysis. The present study design used paired t -test in order to compare pre and post strength of efficacy beliefs for treating obesity. Procedure Participants answered the questionnaire before the start of the course and at the end of the last session, and a few days later participated in an open interview. The course was interactive and contained 12 clinical and psychological lectures given by experts in all subjects relating to obesity (Table 3 ). Every lecture was followed by a workshop. The program consisted of six monthly sessions. Each session (from 17:00 to 21:00) started with two medical lectures followed by a 90 min workshop, and ended with a panel discussion. In the first workshop FPs said they did not address the problem of obesity unless they were asked to do so by patients. Even if they wanted to relate to it they would feel uncomfortable with it, as if that was none of their business. They reported between 1–3 obesity treatments a day. Table 3 Table of contents of the interactive course: "Monitoring and treating obesity by the family practitioner" 1 Obesity – the epidemiological perspective 2 The pathogenesis and metabolic factors of obesity 3 The clinical approach of the family physician to the obese patient 4 Nutrition, diet and treatment of overweight 5 Self-control and behavior modification – diagnosing and managing the stages of change: the trans-theoretical model, the self-regulation model 6 Physical activity and exercise, lifestyle and energy expenditure 7 Drug treatment of obesity 8 Surgical treatment of obesity 9 The metabolic syndrome 10 The mechanism of hypertension in obesity 11 The diabetic obese patient 12 Infertility of obese women FPs filled in clinical report forms and presented the cases they treated and tools they used. The cases were discussed during the course and feedback was given by colleagues and experts. The course supplied the FPs with knowledge, skills and psychological tools such as: food and physical activity diaries, decision making tools, self-evaluation tools, self-report tools, self-monitoring tools, persuading tools, stimulus control tools and counter-conditioning tools, to treat obesity. Medical knowledge and skills were not examined. The course attempted to raise the self-efficacy of FPs by creating a supportive atmosphere, providing feedback, recalling successful experiences, learning from models, bringing patients into the workshops, discussing sociological and psychological problems and allowing reflection of thoughts and emotions. Studies have shown that reflection enhances metacognitive processes such as: self-monitoring, self-evaluation, self-reaction and attribution [ 11 , 22 - 25 ]. Since self-appraisal of efficacy is a form of metacognition and efficacy beliefs are structured by experience and reflective thoughts, we viewed reflection on obesity issues and on FPs self-efficacy as a forethought process so that the mental process the FPs went through had an effect on the processing of their efficacy appraisals. We expected their appraisals to go through a change [ 13 - 15 ]. Results The differences between FP pre and post course efficacy appraisals was tested by paired t -test (Table 4 ) and significant differences were found (Effect size .317). Table 4 Difference between pre and post course efficacy beliefs to treat obesity Item no. Mean pre-course Mean post-course t df N 1 3.93 4.48 2 3.86 4.48 3 4.21 4.41 4 3.48 4.17 5 3.00 3.79 6 3.34 4.07 7 4.17 4.55 8 3.31 4.31 9 3.41 4.10 -3.606* 28 29 *(significant 1-tailed) p < 0.0005 All subjects reported enhanced efficacy beliefs to treat obesity. Negative feelings towards the course were not said or written. Yet, efficacy belief enhancement of the group differed among the items (see Table 4 ). Three FPs left the course right after the first meeting claiming a lack of time in learning and dealing with new perceptions and no time to treat the family holistically. They also said that the time slot of the course was inconvenient. Some FPs presented cases which had failed to bring about a change in the patient's behavior. Those cases were discussed and the FPs were given strategies and tips for further treatment. In addition, the interviews resulted in reflection by the FPs on the process of their self-efficacy. Coded sentence units of the interviews were constantly compared while evidence accumulated. Nine main criteria were generated through that systematic analysis. These criteria matched the questionnaire items. The four criteria that received the most evidence formed four core constructs. The first was the contribution of the course to the FPs. FPs appreciated the importance of up-to-date information, the various treatment perspectives, and the skills they acquired. Knowledge was a precondition for change. FPs talked about the practical tools and tips they acquired. This is illustrated in the example: "It is his will and actions and our help" . The second criterion was the efficacy to persuade patients to treat obesity. FPs described how they could persuade patients to treat obesity in a variety of ways. The third criterion was the FP performance reports. FPs presented their clinical report forms and described how they successfully used the new knowledge, skills, tools and tips they acquired in the course to manage obesity in their clinics. The fourth criterion was efficient time management. Time management scored the lowest on the pre-course questionnaire. Whenever the issue was raised during the course, FPs claimed that time was the main obstacle in treating obesity. By the end of the course, a significant change in their perception of time was noted. Prior to the beginning of the course, only 1–3 clinical report forms on obesity treatment were reported by the FPs; at the end of the course, that number increased to 8–37. After having taken the course, obesity problems were not ignored anymore. Table 5 shows the criteria listed in the questionnaire, and the criteria generated from coded sentence units mentioned during interviews. The criteria derived from the interviews are illustrated by characteristic examples. Table 5 Questionnaire criteria, criteria coming out of interviews, and examples Questionnaire criteria Criteria coming out of interviews Examples from interviews 1. Efficacy to treat a problem of high priority a. Course contribution: motivation to learn, and to work harder - "I used to treat obesity as something that needed cosmetics now I know it's a disease that needs a cure...and it is my job" - "I've a lot more to learn...I wish I had more courses like this one...It's very important...I'm ready to work hard...to do a lot more..." 2. Efficacy to give up to date precise information b. Course contribution: enriched important knowledge, treatment perspectives, skills, practical tools and tips - "Now I have the tools, a lot of information...now I have the right perspective...I shouldn't be angry with him but supportive...with the tools it's much easier...It's his will and actions and our help. I feel I know how to help him...the course was helpful" 3. Efficacy to persuade, support and help patients make decisions c. Efficacy to persuade patients to treat obesity - "Today I'm more patient...I know when it's the right moment to bring up the issue...and I know how to do it" - "I can use emotions to persuade him" - "Before taking the course, I wasn't self-confident enough to do it, now I feel free to talk about this...I can show him statistics on obesity..." 4. Efficacy to make patients plan behavior and situations d. Efficacy to make patients plan, monitor and control health behavior - "Since he is aware of his expectations I can make him plan or act..." - "under my guidance he can see what's right and what's wrong... and he can change things..." - "when he understands the process he can initiate behavior" 5. Efficacy to make patients monitor behavior 6. Efficacy to make patients control behavior and situations 7. Efficacy to treat obesity regardless of previous failures or unsuccessful experiences e. FP performance reports - "What you taught in the course works!" - "Now that I know that taking small steps is better than expecting a dramatic weight loss – it is easier...and the patient is happier. I now treat 10 obese people..." - "I now treat 8 people, before taking the course, I did not treat any" - "I have 9, I was given feedback by a patient... she said: I lost two pounds, thank you !...you are great..." 8. Efficacy to treat obesity regardless of lack of time. f. Efficient time management - "I'll tell you my secret, everybody starts work at 8.00, I com at 7.00. I'm ready to do it, I want to succeed, after all, it is my job" - "I make a double appointment for an obese patient..." - "If I treat obesity now, I save time, I won't have to treat other diseases in the future" - "I keep thinking about how to be more efficient, I have to do something about the time!" - "I know that when I want something I find the time" 9. Efficacy to bring about other people's involvement in the patient's behavior change process g. Better done with someone's help - "I tell her, doing it alone is too difficult. You should bring your husband or a friend to the next visit" h. FP weight loss - "I lost weight as a result of the course" i. Enhancing efficacy beliefs by reflection, feedback and supportive climate - "Did you hear the FPs' reaction to my presentation?...Wow!... that was great...I understood I had great success" - "I was given feedback by patients, now I know I can!" - "The best thing that happened to me in this course is that it made me think" - "I could open myself to talk about things that I hadn't done before...I think it's because of the warm climate" Discussion The purpose of the study was to discover whether participation in an interactive course would result in a change in the efficacy beliefs of FPs to treat obesity. Results show a significant difference between pre and post course beliefs. The increase was satisfactory (>4 in a scale of 1–5) and the results of the qualitative analysis indicate that the criteria derived from the interviews matched those of the questionnaire. When speaking openly, FPs addressed the same issues that made up the domain theoretical concept map. Several researchers have suggested that quantitative efforts in the study of self-efficacy should be complemented by qualitative studies aimed at gaining a deeper understanding of attitudes and emotions [ 22 - 24 ]. The criteria obtained from the interviews not only matched the criteria in the questionnaire but also enriched our knowledge with a deeper understanding of the attitudes and thoughts of the FPs about the course and the way they looked at obesity management after the course. All sentence units of the interviews were taken into account for content analysis. The study showed that acquisition of knowledge and skills enable a person to meet personal standards of merit that tend to heighten beliefs of personal efficacy [ 11 ]. In judging their efficacy, individuals necessarily unite personal agency with means. They act on beliefs of how well they can use prescribed means [ 10 ]. The FPs felt the course equipped them with appropriate knowledge and means for treating obese patients. This was expressed in many sentence units. Another important psychological role in all phases of behavior change was the efficacy to persuade patients to treat obesity. The FPs' presentations of clinical report forms and descriptions of success to manage obesity in their clinics support research findings that efficacy beliefs predict both intentions and behavior [ 10 ]. The FPs challenged time management as efficiently as they could, which is another important change in the perception of their role as FPs. The impact of the questions analyzed in this study extends beyond the issues asked by the questionnaire. New insights were gained through qualitative analysis: FPs analyzed the process they experienced during the course. They described how their efficacy beliefs were enhanced through reflection, feedback and the supportive climate of the course. Studies have shown that reflection enhances self-efficacy processes since self-appraisal of efficacy is structured by experience and reflective thought [ 25 ]. FPs reported that reflection on thoughts and emotions helped them construct their beliefs. Feedback regarding the quality of one's work progressively raises perceived efficacy, which, in turn, predicts subsequent performance. This is illustrated in studies of self-regulated productivity [ 26 ]. The feedback the FPs received from their colleagues and the experts on the quality of their reported experiences enhanced their efficacy beliefs. The FPs feedback on the course showed that the workshops contributed most to their self-efficacy. FPs explained that they had got the chance to "bring the clinic into the workshop", to discuss their performance, to get feedback on it, and to be stimulated to reflect on the treatment and on themselves as physicians. Incentives for mastering activities contribute to the growth of interest and perceived efficacy[ 10 ]. The credit points FPs received for their professional training served as an incentive that fostered performance accomplishments. The FPs reported on an increased number of obesity treatments which was an important gain of this educational program. There were no other absences except for the 3 who had left after the first session. At the end of the course FPs requested that the course be continued. In summary, an effective program of widespread change in health practices includes four major components. The first is informational and intended to increase the physician's awareness and knowledge of the subject. The second involves development of skills needed to translate informed concerns into effective action. The third is aimed at building a robust sense of self-efficacy to support the exercise of control in the face of difficulties that inevitably arise. This is achieved by providing repeated opportunities for guided practice and corrective feedback in applying the skills in simulated situations that people are likely to encounter. The final component involves creating social support for desired changes. The present program contained all these components. The limitations of the study were the small number of participants and the reliance on one motivated group of FPs. These limitations result from the fact that this was the first course organized by the Israeli Association of Family Physicians on the subject of obesity. It was important to study the effect of the program on FPs self-efficacy for future continuing education and research. We recommend studying the effect of interactive courses on the lifestyle and weight loss of FPs. Future research should consider randomized samples from larger courses and analyses of the correlation between course success and actual FPs performance, FPs' self-efficacy and treatment outcomes e.g: BMI change, Lipids and BP. We also recommend studying the differences in obesity treatment outcomes and in general health feelings between patients whose FPs attended obesity courses and patients whose FPs did not. Practical recommendations for Continuing Medical Education planners would be to focus on workshops rather than on lectures, to enhance those processes the FPs felt less efficacious to go through and to have guidance of Endocrinology experts' as well as Psychology and Education specialists to improve communication with patients and their families in an effort to enhance motivation to loose weight. It is also recommended to bring patients to the workshops to reflect on the treatment they have received. Competing interests The author(s} declare that they have no competing interests. Authors' contributions SK and AF conceived and designed the study, participated in the collection, analysis and interpretation of data and drafted the manuscript. SV Participated in the statistical analysis, interpretation of data and draft of the manuscript. SP participated in the design of the study, data collection and interpretation. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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A mathematical model for LH release in response to continuous and pulsatile exposure of gonadotrophs to GnRH

In a previous study, a model was developed to investigate the release of luteinizing hormone (LH) from pituitary cells in response to a short pulse of gonadotropin-releasing hormone (GnRH). The model included: binding of GnRH to its receptor (R), dimerization and internalization of the hormone receptor complex, interaction with a G protein, production of inositol 1,4,5-trisphosphate (IP 3 ), release of calcium from the endoplasmic reticulum (ER), entrance of calcium into the cytosol via voltage gated membrane channels, pumping of calcium out of the cytosol via membrane and ER pumps, and release of LH. The extended model, presented in this paper, also includes the following physiologically important phenomena: desensitization of calcium channels; internalization of the dimerized receptors and recycling of some of the internalized receptors; an increase in G q concentration near the plasma membrane in response to receptor dimerization; and basal rates of synthesis and degradation of the receptors. With suitable choices of the parameters, good agreement with a variety of experimental data of the LH release pattern in response to pulses of various durations, repetition rates, and concentrations of GnRH were obtained. The mathematical model allows us to assess the effects of internalization and desensitization on the shapes and time courses of LH response curves.

Background Gonadotropin-releasing hormone (GnRH) is released by the hypothalamus in a pulsatile fashion and stimulates luteinizing hormone (LH) and follicle stimulating hormone (FSH) release by pituitary cells by a complex series of signaling processes. Although there is substantial information about various individual steps in the signaling system, there is less understanding of how these components interact to give rise to the overall behavior of the system. The frequency of pulses varies throughout the menstrual cycle increasing markedly just prior to ovulation. And, it has been observed in in vitro experiments on perifused pituitary cells that pulse frequency and concentration have marked (nonlinear) influences on the release of LH and FSH. The purpose of our work is to use mathematics and machine computation to understand the dynamics of this important and interesting physiological system. In a prior study, [ 1 ], a mathematical model was developed to investigate the rate of release of luteinizing hormone from pituitary gonadotrophs in response to short pulses of gonadotropin-releasing hormone. The model included binding of the hormone to its receptor, dimerization, interaction with a G-protein, production of inositoltrisphosphate ( IP 3 ), release of calcium from the endoplasmic reticulum (ER), entrance of calcium into the cytosol via voltage gated membrane channels, pumping of calcium out of the cytosol via membrane and ER pumps, and the release of luteinizing hormone (LH). Cytosolic calcium dynamics were simplified and it was assumed that there is only one pool of releasable LH. Despite these and other simplifications, the model results matched experimental curves and enabled us to understand the reasons for the qualitative features of the LH release curves in response to GnRH pulses of short durations and different concentrations both in the presence and absence of external calcium. We note that Heinze et al, [ 2 ], created a mathematical model for LH release that reproduces some data for pulsatile administration of GnRH. Their model, however, does not include most of the important intracellular mechanisms known to play important roles; thus, they match data but do not study mechanisms. We also note that mathematical models for other aspects of the reproductive hormone system have been created: Keenan et al, [ 3 ], developed a stochastic systems model for the interactions between GnRH, LH, and testosterone; Gordan et al, [ 4 ] modelled the pulsatile release of GnRH by hypothalamic neurons. There are four important medium-term effects that were not included in the previous study. Desensitization of the response to GnRH occurs because after GnRH binds to its receptors, some of the bound complexes are internalized and partially degraded [ 5 ]. Secondly, prolonged exposure to GnRH desensitizes the outer membrane calcium ion channels, as described in detail by Stojilkovic et al [ 6 ]. Thirdly, there exist basal rates of receptor synthesis and degradation. Finally, in response to GnRH, there also occurs an increase in the number of G q /11 proteins closely associated with the plasma membrane [ 7 ]. Incorporation of these four phenomena into the previous model allows us to analyze the contrasting effects of desensitization and signal amplification during medium-term continuous and pulsatile exposures to GnRH. We then show that the LH response curves of the enlarged model capture most of the essential features of a large number of experimental studies. It should be noted that in the present model we ignore the long-term effects that result in changes in DNA, messenger RNA, and protein concentrations (e.g., receptor number) that are known to occur several hours after exposure to GnRH [ 8 - 11 ]. Thus, in the present study, we limit the time of exposure to three hours. We also ignore the long term effects of diacylglycerol which is known to cause an increase in the synthesis of LH α , the α subunit of the LH dimer [ 12 ]. Model Development Let H ( t ) represent the GnRH concentration (nM) in the surrounding medium t minutes after the initiation of the experiment. Initially, the hormone is bound by the receptor, R. The bound complex HR reacts with itself to form dimers [ 13 ], denoted by HRRH. A G q /11 protein, denoted GQ, reacts with the dimer to produce an effector, E (e.g., phospholipase C, [ 13 ]). The values of the rate constants, k 1 , k 2 , k 3 , k -1 , k -2 , k -3 , are the same as in our earlier model [ 1 ]. The abbreviations for the physiological components of the model are listed in Table 1 and all the rate constants for the current model are listed in Table 2 . Table 1 Glossary of Variables H GnRH concentration (nM) R Free GnRH receptor concentration (nM) HR Hormone-receptor complex concentration (nM) HRRH Hormone-receptor dimer concentration (nM) GQ G q /11 protein concentration (nM) E Effector concentration (nM) IP 3 Inositol 1,4,5-trisphosphate concentration (nM) CAC Cytosolic Ca 2+ concentration ( μ M) CAER ER Ca 2 + concentration ( μ M) CHO Fraction of open ER Ca 2+ channels LH LH concentration (ng) Table 2 Constants R 0 Total receptor concentration (nM) GQ 0 Total G q /11 protein concentration (nM) ERUL Resting Ca 2+ concentration in ER (normally 40 μ M) CAE External Ca 2+ concentration (normally 1000 μ M) α = 2 nM -1 , see equation (17) β = 4 min -1 , see equation (17) v 1 = 0.02 min -1 , see equation (12) v 2 = 0.002 min -1 , see equation (12) r 0 = 0.6, fraction internalized receptors returned P 0 = 8.3 × 10 -6 nM·min -1 , basal rate of receptor synthesis γ = 8.3 × 10 -4 min -1 , basal rate of receptor degradation k 1 = 2.5 nM -1 ·min -1 k -1 = 5 min -1 k 2 = 2500 nM -1 ·min- 1 k -2 = 5 min -1 k 3 = 4000 nM -1 ·min -1 k -3 = 200 min -1 k 5 = 2 × 10 7 min -1 k -5 = 10 min -1 k 6 = 1 nM -1 ·min -1 k 66 = 10 nM -1 ·min -1 k 666 = 0 k -6 = 5 min -1 k 7 = 2.2 μ M·min -1 k 8 = 0.4 nM -1 ·min -1 k 88 = 0 k 888 = 0 k 9 = 0.0002 min -1 k 10 = 5 ng·min -1 k 11 = 0.0008 nM- 1 ·min -1 k 33 = 2.7 min -1 The monomers, HR, can also interact with each other to form larger aggregates [ 14 ]. Macroaggregation and internalization occur at least 20 minutes after exposure to GnRH [ 14 ]. All of the internalized hormone and some of the receptors are then degraded, and the receptors that are not degraded are returned to the membrane [ 15 , 16 ]. We assume that a fraction of receptors, r 0 , can be returned intact to the membrane after a time delay of 20 minutes. Consistent with the data of [ 14 ], we assume that r 0 = 0.6. Since we are not concerned with the details of the internalization or return processes, we adopt simple first order reactions for these processes. We assume that n monomers, HR , are internalized at a rate k 11 and that r 0 n monomers that have been internalized are available to be returned to the membrane at rate k 11 . There is evidence that the macroaggregates consist of an average of n = 100 monomers [ 14 ]. In our model, we will choose k 11 = 0.08/ n = 0.0008 nM -1 ·min -1 . With this choice, 7% of the receptors are internalized after a 5 minute pulse of 1 nM GnRH, and 60 minutes after the initial exposure, approximately half of the internalized receptors have returned. It should be noted that it is only the combination k 11 n that occurs in the equations. We make the following simple assumption about the recyling of receptors (consistent with the data of Maya-Nunez et al. [ 17 ] and Table 2 of Conn et al. [ 18 ]). i.e. that the formation of macroaggregates begins 20 minutes after exposure to GnRH and that the internalization and recycling process takes 20 minutes after the formation of the macroaggregates. Let χ ( t ) be the function that equals 1 for t ≥ 0 and equals 0 for t < 0. Then, at time t, the rate of internalization of receptors is k 11 n [ HR ]( t ) and the rate of return of receptors to the membrane is k 11 n [ HR ]( t - 40) χ ( t - 40). To simplify notation, we write [ HR ] 40 = [ HR ]( t - 40) χ ( t - 40). Since only 60% percent of the internalized receptors are returned to the membrane after exposure to GnRH, there would not be a full recovery of receptors in the membrane. In the model we therefore include a low basal rate of receptor synthesis, P 0 = 8.3 × 10 -6 nM·min -1 , and degradation, γ = 8.3 × 10 -4 min -1 . The ratio is chosen so that the resting (in the absence of hormone) receptor concentration is R 0 = 10 -2 nM, and the magnitude of P 0 is chosen so that approximately of the resting amount of receptor is produced per hour, thus ensuring a slow recovery to the steady state receptor concentration in the absence of GnRH. The number of membrane associated GQ proteins increases in response to a GnRH agonist as described by Cornea et al [ 7 ]. For simplicity we assume that the increase of GQ proteins near the membrane depends on the concentration of HRRH in the membrane. The kinetic coefficient k 33 is the parameter that determines the rate of increased concentration of GQ at the membrane in response to the formation of HRRH. We are assuming a finite pool of GQ that can be transported from the cytoplasm to the immediate vicinity of the plasma membrane. This pool is assumed to be regulated by the amount of HRRH for only the first 20 minutes, and after this time the rate of increase is negligible [ 7 ]. To fit the experimental data, we choose k 33 = 2.7 min -1 and multiply the kinetic coefficient k 33 by e - t /20 . With these parameters, 60 minutes after a constant exposure to 1 nM GnRH, there is a 40% increase of GQ concentration near the membrane and 120 minutes after exposure to the hormone, there is only a 43% increase. The following differential equations reflect the physiological assumptions that we have so far discussed. We further assume that the production of IP 3 is proportional to the concentration of E and that it is converted to inactive metabolites at a rate proportional to its concentration. As in [ 1 ], the fraction of open channels in the ER, denoted by CHO, depends on IP 3 concentration. CHO reaches its maximum 0.25 min after exposure to GnRH and the maximum value of CHO is 0.6. To incorporate multiple pulses, we modify the function CHO from the previous model so that it reaches its maximum 0.25 min after the start of each pulse. Thus we have where t p is the time after the start of each individual pulse and, as in [ 1 ],, α = 2 nM -1 and β = 4 min -1 . In response to GnRH, calcium is released from the ER into the cytoplasm with a rate constant ERR and is pumped back into the ER. As discussed in the previous model, the rate constant ERR increases proportionally to cytosolic calcium concentration, CAC, with a rate constant k 66 and is inhibited at high CAC at a rate that is proportional to the square of CAC, with a rate constant k 666 . Just as in, [ 1 ], k 6 = 1, k 66 = 10, and k 666 = 0, i.e., we ignore the inhibitory effects of calcium on reuptake of calcium into the ER. ERR = k 6 + k 66 [CAC] - k 666 [CAC] 2 (8) The change in cytosolic calcium concentration, CAER, is then determined by the rate constant ERR, which is the rate of extrusion, multiplied by the fraction of open channels, CHO, and the difference in concentration between the calcium concentration in the cytoplasm and the endoplasmic reticulum. As in Blum et al. [ 1 ], calcium is actively transported back into the ER by pumps with the rate constant k -6 = 5 min -1 . As in the previous model, the volume of the ER is assumed to be 1/20 of the volume of the cytosol. CAC is determined by the rate of calcium efflux through ion channels in the ER membrane minus the rate at which calcium is being pumped back into the ER, plus the rate of calcium entry from the plasma membrane. The function VSR denotes the rate of calcium influx from extracellular calcium into the cytosol and depends on E with rate constant k 8 [ 19 ] and on CAC with rate constants k 88 for the influx at low CAC and k 888 for the inhibitory effects at high CAC. There is considerable evidence that desensitization occurs, i.e., the fraction of open calcium channels in the cell membrane decreases soon after exposure to GnRH [ 18 ]. Since the precise mechanism of desensitization in unknown, we assume that VSR depends on E and CAC, and that channels slowly become inactive in response to exposure to GnRH, consistent with the experimental data [ 18 ]. We further assume that the fraction of open calcium channels in the outer membrane, denoted by VSRO( t ), decreases at a linear rate of v 1 = 0.02 min -1 when the hormone is applied and has a minimum value of 0. In the absence of hormone, the fraction of open channels increases at a linear rate of v 2 = 0.002 min -1 and has a maximum value of 1. Thus, immediately a five minute pulse of 5 nM GnRH, 10% of the channels are in the refractory state and 50 minutes after the removal of the GnRH, all of the channels have recovered, consistent with experimental data; see [ 18 ] for more details. Incorporating calcium influx, pumps and leakage into the cytoplasm from the medium (the term k 9 [CAE], we have where VSR( t ) = ( k 8 E( t ) + k 88 [CAC]( t ) - k 888 ([CAC])( t )) 2 ) × VSRO( t )     (11) and VSRO satisfies the following. 0 ≤ VSRO( t ) ≤ 1     (13) Finally, the rate of release of LH depends on cytosolic calcium concentration (see Blum et al. [ 1 ] for details). Although there is evidence that there are three pools of LH in gonadotrophs, one pool, comprising of only 2% of the total LH, is released within one minute after exposure to GnRH, and the third pool is not released during continuous exposure to GnRH (Naor et al.,[ 20 ]). Therefore, as in the previous model [ 1 ], we treat LH as being released from a single pool. The mathematical model consists of equations (1) – (14). These non-linear equations cannot be solved analytically but solutions can be obtained by machine computation. To do this, we used the solver ODE45 in Matlab. The values of the rate constants are given in Table 2 . The values for many of them are discussed in detail, with references, in our original paper, [ 1 ]. The values of the rate constants for the signalling mechanisms introduced in this paper were discussed (above) as the mechanisms were introduced. In some cases the rate constants were taken from experimental data (references given) and in other cases, where direct experimental data does not yet exist, we explained the rationale for our choices. Since the resulting model captures and explains many experimental studies (see below), these choices provide useful predictions for future experimental studies. Results In Figure 1 , we compare the amounts of LH released in 5 minute intervals in the original model and the present model in response to continuous administration of 5 nM GnRH. In both models there is an initial large pulse of LH released. However, in the original model (open circles in Panel A) the long-term release plateaus at a high level, while in the present model (solid circles) the long term release declines to a low level. Panel A in Figure 4 contains experimental results of Hawes et al. [ 21 ], that clearly show show a decline in LH release to a low level after approximately 1.5 to 2 hours. Similar experimental results were obtained by Baird et al, [[ 22 ], Figure 4 ] and by Janovick and Conn, [[ 5 ], Figure 1 , Panel A]. Figure 1 Amount of LH released in five minute intervals in response to constant exposure to 5 nM GnRH. The solid circles show the results of the present model while the open circles show the results of the original model [1]. The decay of LH release to zero is in accord with experimental results (see discussion in text); thus, new mechanisms included in the present model allow one to match this data (and other data, see other figures) from several laboratories for medium-term GnRH exposure experiments. Figure 4 Experimental data of Hawes et al.[21]. Gonadotrophs were treated continuously with lO nM GnRH (Panel A), with 5 minute pulses every 30 minutes (Panel B), or every 15 minutes (Panel C). Figures 2 and 3 show in detail the changes that occur in all components of the system during the model experiments described above. Fig. 2A shows the total amount of the LH released as a function of time while Fig. 2B shows the LH release rate (LHRR), which peaks within one minute after exposure to GnRH and then declines slowly for the next 50 minutes to a very low value in the present model. Note that LHRR is the instantaneous rate of LH release (in ng/min) while LH release in Figure 1A is in ng released in each five minute interval. In the previous model(dashed lines), LHRR plateaus at a high level (Figure 2B ), so the total LH released increases linearly (Figure 2A ). In the present model (solid lines), LHRR declines to a low level. In both the previous and present models, there is a rapid extrusion of calcium from the ER (Fig. 2D ) and an initial rapid increase in CAC (Fig. 2C ), which correlate well with the time course of the rate of change of LHRR (Figure 2B ). However, the long-term behavior is different in the two models because in the present model CAC declines to a low plateau. This explains the similar drop in LH release since the rate of LH release depends on CAC (see equation (14)). The drop in CAC is caused by the desensitization of the outer membrane channels; Figure 2E shows that the fraction of open channels declines linearly to zero in 50 minutes. In the ER membrane, there is an almost instantaneous increase of open calcium channels followed by a rapid decrease and then a slight further decline (Fig. 2F ). Figure 2 Panel A shows the total amount of LH released as a function of time during continuous exposure to 5 nM GnRH, while Panel B shows the instantaneous rate of LH release at each moment of time. Panels C and D show the calcium concentration in the cytosol and the endoplasmic reticulum, respectively. Panels E and F show the fraction of open calcium channels in the outer membrane and the endoplasmic reticulum, respectively. The solid lines show the results of the present model while the dashed lines show the results of the earlier model [1]. Figure 3 Panels A, C, and D show the concentrations of free, bound, and dimerized receptors, respectively, while Panel B shows the total amount of receptors in the membrane. Panel E shows the concentration of IP3. Panel F shows the GQ concentration at the membrane as a function of time during the continuous exposure to 5 nM GnRH. The solid lines show the results of the current model and the dashed lines show the results of the earlier model in [1]. Figures 3A and 3C show the concentrations of free receptors and receptors bound to the hormone. It can be seen that, initially in both the present and previous models, there is a very rapid decline in free receptors, R, and a very rapid increase of receptors to which GnRH has bound (HR) but have not yet dimerized. This is immediately followed, as shown in Figure 3D , by the formation of the dimers (HRRH). After this initial reaction, the concentrations of HR and HRRH remain constant in the previous model, but decline in the present model due to internalization and degradation. The recycling of receptors was assumed to start at 40 minutes (see equation (1)), which is why the rates of decrease of HR and HRRH decline at that time. Because of degradation, only a fraction ( r 0 = 0.6) of the internalized receptors are returned to the membrane. Thus, in the presence of continuous exposure to GnRH, the total number of receptors in the membrane continues to decline as shown in Figure 3B . The rate of change of IP3 (Fig. 3E ) is closely related to the rate of change of HRRH as shown in Fig. 3D . Finally, Fig. 3F shows that there is a slow increase of approximately 43% of the concentration GQ associated with the membrane during the exposure. Figures 6 , 7 , and 8 show model results for gonadotrophs exposed to 5 minute pulses of 5 nM GnRH administered every 15 minutes for a total duration of 3 hours. In the previous model (Figure 6A , open circles), there was a drop in LH release between the first and second pulse, but the same amount of LH was released in response to all subsequent pulses, contrary to experimental observations. The initial drop occurs because there is insufficient time for the calcium in the ER to refill completely (data not shown). In the present model, in response to the first pulse there is a large release of LH. In response to the second pulse considerably less LH is released, and in subsequent pulses there is a steady decline in the amount of LH released. This continual decline in LH release has been observed in a large number of experiments. Panels B and C of Figure 4 show the results of Hawes et al [ 21 ] obtained from female weanling rats. Figure 5 shows the results of experiments by Baird et al. [ 22 ] in which LH release was measured in response to similar GnRH pulse patterns in pubertal female rats (Panel A) and hamsters (Panel B). See also Janovick & Conn, [[ 5 ], Figure 1B ]. This decline in the amount of LH release results both from desensitization of the calcium channels in the outer membrane and internalization of the receptors into the lysosomes, as we will see below. Figure 5 Experimental data of Baird et al.[22]. Panels A and B show the response of pubertal rat and hamster anterior pituitary cells, respectively, to six minute pulses of 10 nM GnRH. Figure 6 Amount of LH released as a function of time during a series of 5 minute pulses of 5 nM GnRH every 15 minutes. Open circles are the original model results and solid circles are the current model results. Figure 7 Model responses to a series of 5 minute pulses of 5 nM GnRH every 15 minutes. Figure 8 Model responses to a series of 5 minute pulses of 5 nM GnRH every 15 minutes. The previous model (Blum et al, [ 1 ]) was intended to explain the short term response of gonadotrophs to GnRH. The success of the previous model in the first few minutes is not visible in Figures 1 , 2 , 3 , and 6 because the long time scale compresses the first five minutes. The present model, which includes the four important medium-term processes discussed in the Introduction, now enables us to study the effects of these intracellular processes on medium-term responses, including the responses to pulses of GnRH. From now on, when we refer to the "model", we mean the present expanded model. As shown in Figure 7B , the LH release rate decreases appreciably after the first pulse, and then continues to decrease slowly with each subsequent pulse. This arises (see equation (14)) because of the decline in the size of the cytosolic calcium pulse after each GnRH pulse as shown in Figure 7C . The ER is able to refill its calcium store to almost the same level as the preceding pulse, although the amount remaining in the ER after each pulse decreases appreciably (Figure 7D ). Notice that the fraction of open channels in the outer membrane (Figure 7F ) declines dramatically, while the fraction of open ER channels declines only slightly with each pulse (Figure 7E ). This suggests that the primary cause of decline in the amount LH release with each GnRH pulse is the desensitization of the outer membrane. We examine this hypothesis further below. To understand why the number of open ER channels does not decrease markedly from pulse to pulse, we refer to Figure 8 . Note that the total number of receptors (Figure 8B ) declines steadily by approximately 1/3 in the course of the experiment as does the number of free receptors (Figure 8A ). The decline in the HRRH peaks is much greater (approximtely 40%, Figure 8D ) because the formation of these dimers depends on the square of [HR]. However, the decline in the effector, E, which leads to the formation of IP3 (see equation (6)) is only 25% (data not shown) because of the substantial, rapid rise in GQ (Figure 8F ) in response to the first pulse of GnRH. Thus, the IP3 peaks decline only about 25% (Figure 8E ). Because of the Michaelis-Menten kinetics of the interaction between IP3 and the ER channels, there is an even smaller change in the fraction of open ER channels (CHO) in response to each GnRH pulse. This explains why the internalization and degradation of receptors does not have a more profound effect. We now investigate how the desensitization depends on pulse frequency and GnRH concentration. In Figure 4 , we examined the response of the cells to pulsatile administration of a intermediate concentration of GnRH. We now examine the LH release pattern in response to pulsatile exposure to lower (0.1 nM) and higher (10 nM) concentrations of GnRH. Panels A, B, and C of Figure 9 show the model results for five minute pulses of GnRH administered every 15, 30, and 60 minutes, respectively. On each panel, the three curves correspond to pulse concentrations of 10(stars), 1 (crosses), and 0.1 (open circles) nM of GnRH, respectively. At the lowest concentration in each case there is little or no desensitization throughtout the three hour time period. At the high concentration, there is a large release of LH in response to the first pulse. For pulse period of 15 minutes, there is a large decline in the amount of LH released with each subsequent pulse (Panel A). Figure 9 Dependence of desensitization on GnRH concentration and pulse frequency. Panels A, B, and C show model LH outputs in response to 5 minutes pulses of GnRH at pulse periods of 15 (Panel A), 30 (Panel B), and 60(Panel C) minutes. Each panel shows responses to 10 nM(*), 1 nM(+), and O.1 nM(○) GnRH. The decline is much smaller for pulse period of 30 minutes (Panel B). For a pulse period of 1 hour, the same amount of LH is released in response to each pulse for each GnRH concentration (Panel C). In vivo, one would not expect desensitization, so this result is consistent with experimental observations that LH pulses of the same magnitude occur approximately once an hour except just prior to ovulation (Kaiser et al,[ 23 ]). Note also that at the medium concentration of 1nM there is less desensitization at both period 15 and period 30 minutes than at the high concentration. These results are consistent with the experimental results seen by Hawes et al, [ 21 ] (our Figure 4 ) and Baird et al., [ 22 ] (our Figure 5 ), and Janovick & Conn, [[ 5 ], see their Figures 1 , 2 , 3 , 4 ]. Experiments have been performed to examine LH release in response to different concentrations of GnRH. King et. al. [ 24 ] performed an experiment in which they exposed pituitary cells to increasing concentrations of GnRH for 2 minutes at 30 minute intervals for a total time of three hours. Fig. 10 shows the model results for such an experiment. The pattern of LH release by the model closely coincides with the experimental results except that at 150 minutes the model predicts a somewhat larger LH release than observed experimentally. In Figure 11 we show the total amount of LH released in the model during a one hour and a two hour exposure to increasing concentrations of GnRH. The saturating shape of each curve is sigmoidal at medium and high GnRH concentrations, as observed experimentally (see: Keri et al. [[ 25 ], Figure 1 ]; King et al., [[ 24 ], Figure 4 ]; Conn et al, [[ 18 ], Figure 6 ]; and Stoljikovic et al. [[ 26 ], Figure 7 ]). Note that, because of desensitization, the amount of LH released in 2 hours is much less than twice the amount released in one hour. Figure 10 LH released during 2 minute pulses of GnRH administered every 30 minutes at the indicated increasing concentrations of GnRH. Figure 11 Total LH released after a 1 hour (open circles) and 2 hour (closed circles) continuous exposure to the concentrations of GnRH shown on the abscissa. King et al. [ 24 ] also performed an experiment in which the cells were exposed to 20-minute pulses of 100 nM GnRH at 1-hour intervals. The model results (Figure 12 ) show a peak followed by a rapid decline to approximately half of the peak value and then a slower decrease to a lower level of LH release. The pattern is repeated at a reduced peak level with subsequent pulses. This pattern resembles Fig. 9 in King et al. [ 24 ] except that the experimental results show a flattening of the LH release curve late in the pulse, while the model results show a continual slow decline. Notice that both the model and experimental results show that even at one hour intervals pulses can cause desensitization if the pulse length is long enough or the frequency is high enough. Figure 12 LH released in the model in response to 20 minute pulses of 100 nM GnRH administered every hour. To investigate which of the two desensitization mechanisms, receptor interalization or outer membrane calcium channel desensitization, plays the major role in LH release densensitization, we set either the receptor internalization to zero (i.e k 11 = 0) or calcium channel densensitization to zero ( v 0 = 0 = v 1 ) and compared the results to the full model for continuous and pulsatile exposures. In the full model, in response to continuous exposure there is initial rapid increase in LH release followed by a decrease to basal levels at about 40 minutes (Figure 13 , Panel A, open squares), comparable to the results observed by Janovick & Conn [ 5 ]. An almost identical response occurs if k 11 = 0, except that the rate of decline after the initial spike is somewhat slower(Figure 13 , Panel A, solid circles). If, however, v 0 = 0 and v 1 = 0, while k 11 retains its normal value, then the amount of LH released declines much more slowly and does not reach basal levels (Figure 13 , Panel A, open circles). In response to 5 minute pulses every 15 minutes (Figure 13 , Panel B), again there is a relatively small effect of setting the internalization of the receptors to zero and a much larger effect of ignoring the desensitization of the calcium channels. Thus, for continuous and pulsatile exposures up to 3 hours, internalization of the receptors plays a relatively small role in the desensitization of gonadotrophs, whereas calcium channel desensitization has a much larger effect. Figure 13 LH released during constant exposure (Panel A) and to 5 minute pulses every 15 minutes (Panel B) to 5 nM GnRH. Open circles indicate the model with no desensiti-zation of calcium channels in outer membrane ( v 1 = 0 and v 2 = 0); solid circles indicate the model with calcium channel desensitization but with no internalization of receptors ( k 11 = 0); open squares indicate the full model. In all of our previous simulations, except those in Figure 13 where we compared the two mechanisms for desensitization of LH release, the parameters in the model were never varied. We now discuss two situations where the modification of parameters gives good fits to the data and possibly new insights. Stojilkovic et al. [ 6 ] exposed gonadotrophs from two week old ovariectomized female rats to two 30 minute pulses of 100 nM GnRH at one hour intervals or to two 30 minute pulses of 100 nM endothelin (ET), a hormone with LH releasing activity comparable to GnRH. In response to GnRH, the peak of the response to the second pulse was actually slightly larger than the response of the first pulse (Figure 14 , Panel A). However, the response to the second pulse using the present model without any change in parameters was appreciably smaller than the response to the first pulse (Figure 14 , Panel B). A closer approximation to the experimental results from ovariectomized rats was obtained simply by increasing the rate of recovery of the outer membrane calcium channels from v 2 = 0.002 min -1 to v 2 = 0.02 min -1 (data not shown). If, in addition, the rate of internalization of receptors is decreased from k 11 = 0.08/ n nM -1 ·min -1 to k 11 = 0.04/ n nM -1 ·min -1 , the response to the second pulse of GnRH was very similar to that observed experimentally, as shown in Figure 14 , Panel C. Figure 14 Panel A shows the results of an experiment of Stojilkovic et al.[19] in which rat pituitary cells were exposed to two 30 minute pulses of 100 nM GnRH at one hour intervals. Panel B shows the response of the present model to the same pulses. If, how-ever, the rate of recovery of the calcium channels in the outer membrane is increased from v 2 = 0.002 min -1 to v 2 = 0.02 min -1 and the rate internalization of receptors is decreased from k 11 = 0.08/ n nM -1 ·min -1 to k 11 = 0.04/ n nM -1 ·min -1 , then the present model gives responses (Panel C) similar to the exerperimental results in Panel A. The ordinate units for Panels B and C are ng. In the experiments of Stojilkovic et al. [ 6 ], the first 30 minute pulse of ET provokes a high peak in LH release, as for GnRH. This peak, however, is followed by a rapid decline to basal levels. Furthermore, only a very small amount of LH was released in response to the second pulse of ET (see our Figure 15 , Panel A). They attributed this rapid desensitization in part to rapid internalization of the ET receptors (see also Stojilkovic et al. [ 27 ]). To test this hypothesis, we increased the rate of internalization of these receptors from k 11 = 0.08/ n to k 11 = 0.8/ n . Although this decreased the amount LH released appreciably on the second pulse, the amount of LH released was not reduced to a comparably low level as observed experimentally. We therefore also decreased the amount of return of internalized ET receptors to the membrane, r 0 , from 60% to 10%. As shown in Fig. 15 , Panel B, the model now produces a good match to the experimental data. We also note that as in the experimental data, the LH released in response to ET with the receptor internalization modification returns to basal level much faster than in the case of GnRH. Figure 15 Panel A shows the results of an experiment of Stojilkovic et al. [6] in which rat pituitary cells were exposed to two 30 minute pulses of 100 nM endothelin at one hour intervals. Note that the response to Endothelin is markedly different than the response to GnRH in Panel A of Figure 14. If we change the present model by increasing in internalization of receptors ( k 11 = 0.8/ n nM -1 ·min -1 ) and a decreasing the return of internalized receptors (from 60% to 10%), then the model (Panel B) closely approximates the experimental results. The ordinate units for Panels B are ng. A similar result can be acheived by introducing desensitization of both the outer membrane and ER calcium channels instead of changing the internalization and recycling of the receptors. The parameters for the desensitization of the calcium channels in the outer membrane were increased from 0.02 min -1 to 0.4 min -1 . This resulted in approximately 70% decrease in the magnitude of response to the second pulse of ET, but further increase in v 1 did not cause any further reduction in magnitude. Since there is evidence suggesting that the calcium channels in the ER desensitize in response to GnRH (Conn et al [ 18 ]), we introduced this desensitization into the model to see if ER desensitization might also be occuring in response to ET. For simplicity, the rates of desensitization and of recovery of the ER calcium channels were chosen to be identical to that of the desensitization of the outer calcium channels. By including desensitization of both the outer membrane and ER calcium channels, the amount of LH released in response to the second pulse of ET was as small as was observed experimentally (data not shown). Thus, our current model, with few parameter changes, appears capable of explaining the responses to endothelin. However, in the absence of more detailed experimental data (for example responses to pulses of different durations and frequencies, etc.) we cannot at present distinguish between the two above proposed mechanisms. Discussion We have extended our previous model to include receptor internalization and partial degradation, outer membrane calcium channel desensitization, basal levels of receptor synthesis and destruction, and an increase in the number of G q /11 proteins closely associated with the plasma membrane. With these additions we are now able to examine the behavior of the model system over medium term (up to three hours) exposures to GnRH and to a variety of pulsatile exposures. We have compared the model behavior to many such different experiments and found that it shows the essential response properties of the gonadotrophs. Furthermore, since the model includes many of the intracellualar physiological processes, we have used the model to investigate and understand the mechanisms that give rise to the various experimental results. We note that the response of gonadotrophs to GnRH depends on the method of cell preparation, the stage of the estrous cycle, and the particular animals and species used. Thus, the real physiological parameters will vary in these different situations. Therefore, one would not expect that our model with the fixed set of "standard" parameters (used for the simulations in Figures 1 , 2 , 3 and 6 , 7 , 8 , 9 , 10 , 11 , 12 ) would match perfectly any particular set of experimental data. Of course, one can tune the model by adjusting parameters. For example, notice that the degree of desensitization to six minute pulses of 10 nM GnRH is differs markedly for the pubertal female rats and hamsters in the experiments of Baird et al. [ 22 ] as shown in Figure 5 . The model behavior with standard parameters gives less desensitization than the hamster and more than the rat (see open circles in Figure 16 ). By changing the model parameter v 1 (the rate of desensitization of the outer membrane calcium channels) from 0.02/min to 0.005/min we obtain a good match to the rat data (closed circles in Figure 16 ), and by changing v 1 from 0.02/min to 0.05/min we obtain a good match to the hamster data (stars in Figure 16 ). This does not prove, of course, that it is only physiological variation in this parameter that gives the different experimental results, but it does suggest the specific experiments that could be performed to test this hypothesis. Figure 16 Model responses to six minutes pulses of 10 nM GnRH every 30 minutes with the standard parameters (crosses), with v 1 changed from 0.02/min to 0.005/min (stars) or to 0.05/min (open circles). The weak desensitization (stars) is similar to that of the rat in the experiments of Baird et al.[22](our Figure 5A) and the strong desensitization (open circles) is similar to that seen in the hamster (our Figure 5B). We used parameter variation to investigate whether receptor internalization or outer membrane calcium channel desensitization plays the major role in LH release desensitization and concluded that outer membrane calcium channel desensitization is more important, at least in the experiments of Janovick and Conn [ 5 ]. We also used parameter variation to show that changing two parameters (the rate of recovery of the outer membrane channels and the rate of receptor internalization) the model gives good matches to the data of Stoljilkovic et al [ 19 ], on LH responses to pulses of endothelin. This strongly suggests that the same intracellular mechanisms are primarily responsible for the LH responses to GnRH and endothelin. It is important to note that the model ignores a number of processes that play a role in the long-term response to GnRH. In gonadotrophs, depending on the frequency and duration of exposure to pulses of GnRH, there may be an increase or decrease in the number of receptors in the cell membrane due to changes in gene expression and/or mRNA translation [ 28 , 9 , 8 , 30 ]. These long-term effects are not important for the current study but will be included in future work. It is also known that there is activation of protein kinase C in gonadotrophs exposed to GnRH [ 20 ], but while PKC may not be involved in GnRH-mediated LH release [ 31 ], PKC may have other roles in the pituitary, such as to modulate gonadotroph responsiveness to GnRH [ 32 ]. Another aspect that our model ignores is the rapid calcium concentration oscillations in the cytosol. As shown by Stojilkovic and Tomic [ 33 ], the frequency of the oscillations affect the LH release. In the present model, as in the previous model [ 1 ], for simplicity we have assumed that the average cytosolic calcium concentration is an adequate approximation to the rapid oscillatory responses. Finally, we note (Stanislaus et al, [ 34 ]) that there is evidence that the GnRH receptor interacts with more than one G protein and Stanislaus et al,[ 13 ], have proposed that this underlies the differential regulation of the release of luteinizing hormone and follicle stimulating hormone. We plan to address these questions in future work. Authors' Contributions Washington and Reed contributed mostly to the mathematical development, Conn contributed to the physiological analysis, and Blum contributed to both. Competing Interests The authors declare that they have no competing interests.

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519006

Developmental Milieu Influences a Gene's Role in Tumor Formation

Whether a person inherits a defective gene or acquires genetic damage by chance, two types of genes typically play a role in transforming a healthy cell into a cancer cell. Oncogenes and tumor suppressor genes are normally involved in cell growth, development, and cell differentiation. Both functions can be appropriated to ill effect by mutations. Single mutations in these genes rarely cause cancer on their own, but they predispose cells to additional insults that precipitate malignant transformation. Susceptibility to cancer depends, among other things, on age. Though cancer in children is rare, the most common childhood cancers strike the hematopoietic system (leukemia), nervous system, and skeletal muscle system, while solid tumors of the lung, breast, prostate, and colon are more common in adults. This age differential suggests that an oncogene's ability to cause cancer in a particular cell type might depend on that cell's developmental stage. (A cell's gene expression profile differs with type and age; breast cells express different genes than liver cells, and immature cells express different genes than fully differentiated cells.) In a new study, Dean Felsher and colleagues show that age matters: activating oncogenes at different developmental time points in mouse liver cells produces different results. Typically, once a cell is transformed, it stays in its “differentiative” state, that is, it stays in whatever developmental stage it was in when it became a tumor cell. But in a previous study, Felsher and colleagues found that turning off oncogenes in tumor cells allowed them to differentiate; these mature cells did not resume tumorigenesis after the oncogenes were reactivated. In this study, Felsher and colleagues show that the ability of the MYC oncogene to initiate liver cancer (hepatocellular carcinoma) in a transgenic mouse model varies with the age of the mouse. Developmental consequences of MYC overexpression To study the consequences of MYC overexpression in the liver cells of embryonic, neonatal, and adult mice, the authors used a biotech trick (called the Tet system) that controls gene expression dose and timing with a drug. The system relies on the interplay of two elements: a gene (in this case, MYC ) fused to a regulatory enhancer, and a transcription factor that binds to the enhancer and activates the gene. Administering a tetracycline-like drug (in this case, doxycycline) prevents the transcriptional activation of the gene. Overexpressing the MYC oncogene in mice during embryonic development or at birth occasioned their demise fairly quickly (ten days and eight weeks after birth, respectively). In contrast, overexpression of MYC in adult mice resulted in tumorigenesis only after a long latency period. When the authors evaluated the cellular effects of MYC overexpression, they found that hepatocytes from neonatal transgenic mice showed evidence of increased proliferation (replicated DNA content) compared to normal hepatocytes, while transgenic adult hepatocytes showed increased cell and nuclear growth (some nuclei had as many as twelve genome copies instead of two) without dividing. Since these adult cells eventually developed into tumors, some clearly acquired the ability to divide, which the authors show is facilitated, among other events, by the loss of the p53 tumor suppressor. Altogether these results suggest that whether oncogene activation can support tumor growth depends on the age of the host, which in turn suggests the role of genetically distinct pathways in young and adult mice. The consequences of MYC activation, Felsher and colleagues conclude, depend on the cell's developmental program, which determines whether a cell can grow and divide, or simply grow. In adult hepatocytes—which are normally quiescent— MYC requires additional genetic events to induce cell division and tumorigenesis; in immature hepatocytes—which are already committed to a program of cellular proliferation— MYC activation alone is sufficient. The next step will be to identify the epigenetic developmental factors, both internal and external, that lead to tumor formation, and how to prevent it.

/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC519006.xml

555556

Discordance in diagnosis of osteoporosis using spine and hip bone densitometry

Background Diagnostic discordance for osteoporosis is the observation that the T-score of an individual patient varies from one key measurement site to another, falling into two different diagnostic categories identified by the World Health Organization (WHO) classification system. This study was conducted to evaluate the presence and risk factors for this phenomenon in a large sample of Iranian population. Methods Demographic data, anthropometric measurements, and risk factors for osteoporosis were derived from a database on 4229 patients referred to a community-based outpatient osteoporosis testing center from 2000 to 2003. Dual-energy X-ray absorptiometry (DXA) was performed on L1–L4 lumbar spine and total hip for all cases. Minor discordance was defined as present when the difference between two sites was no more than one WHO diagnostic class. Major discordance was present when one site is osteoporotic and the other is normal. Subjects with incomplete data were excluded. Results In 4188 participants (3848 female, mean age 53.4 ± 11.8 years), major discordance, minor discordance, and concordance of T-scores were seen in 2.7%, 38.9% and 58.3%, respectively. In multivariate logistic regression analysis, older age, menopause, obesity, and belated menopause were recognized as risk factors and hormone replacement therapy as a protective factor against T-score discordance. Conclusion The high prevalence of T-score discordance may lead to problems in interpretation of the densitometry results for some patients. This phenomenon should be regarded as a real and prevalent finding and physicians should develop a particular strategy approaching to these patients.

Background Osteoporosis is defined as a systemic skeletal disease characterized by low bone mass and micro-architectural deterioration of bone tissue, with a consequent increase in bone fragility and susceptibility to fracture [ 1 , 2 ]. This definition indicates that measurement of bone mineral density (BMD) is a central component to diagnosis of the disease [ 3 ]. 'T score' is a statistical definition which indicates the difference between patient's BMD and mean bone density of normal population in the age of 20 – 30 (reference population) [ 3 ]. This value shows the difference in terms of standard deviations. According to the World Health Organization (WHO) classification system, T scores under the value of -2.5 are considered as osteoporosis and between -1 and -2.5 as osteopenia. These figures are usually calculated separately for two different sites of lumbar spine and total hip. Discordance in diagnosis of osteoporosis is defined as presence of different categories of T scores (osteoporosis, osteopenia, and normal) in two skeletal sites of an individual patient [ 4 ]. This phenomenon has been divided into two groups: major and minor [ 5 ]. Minor discordance happens when the different diagnostic classes are adjacent; i.e., patient is diagnosed as osteoporotic in one site and osteopenic in the other site, or, osteopenic in one site and normal in the other site. If the diagnosis is osteoporosis in one site and the other site is in the normal range, the discordance falls into the major class. Actually, one of the reasons for measuring BMD in several sites is the presence of discordance, which can affect the diagnosis and therapeutic plan in an individual person. Various studies have analyzed the prevalence and impact of T-score discordance on different aspects of management of osteoporosis [ 5 - 9 ]. However, most of these studies did not evaluate risk factors for this phenomenon. Given this background and concerning the need for the estimation of the impact of this phenomenon in our country, we aimed to evaluate the presence and risk factors for T-score discordance in a large sample of Iranian population. Methods Participants in this study were 4229 persons who underwent bone densitometry in outpatient clinic of Endocrinology & Metabolism Research Center in Tehran from 2000 to 2003. A considerable proportion of these cases were healthy post-menopausal women referred by clinicians for densitometric evaluations. All study participants signed the informed consent for any scientific approach to their medical registered data. Our Institutional Review Board approved this study. A standardized questionnaire was filled before densitometry for all participants. Demographic data (including age and sex) as well as other known or suspicious risk factors for osteoporosis (including menopause, age at menopause, age at menarche, history of osteoporotic fractures, drugs, and smoking) were collected. All participants had their standing height measured using a stadiometer to the nearest 0.5 cm. Weight was measured on a standard weighting scale with a precision of 0.5 kg. Body mass index (BMI) was calculated as weight (kg) divided by height (m) squared. All the BMD measurements were done for diagnostic purposes and none of the participants were on the treatment with bone active agents (hormone replacement therapy was not considered a bone active agent). BMD was measured at the lumbar spine and total hip with dual X-ray absorptiometry (DXA) using a Lunar DPXMD densitometer (Lunar 7164, GE, Madison, WI) by a trained operator according to the manufacturer's instruction. The instrument was calibrated weekly by using appropriate phantoms. Precision error for BMD measurements was 1–1.5% in the lumbar and 2–3% in the femoral regions. The device normative data of US population for spine BMD and NHANES III study for femur BMD were used as reference values. All the data gained from densitometry and questionnaires were entered into a comprehensive relational database. The participants with incomplete data were excluded from the study. To compare presence of various risk factors in participants with and without T-score discordance, chi-square test and independent sample t-test were used firstly. Potential risk factors were entered to a multivariate binary logistic regression analysis and the resulted odds ratios with 95% confidence intervals were reported. P values less than 0.05 were taken to indicate statistical significance. Statistical analyses were performed using Stata Statistical Package, version 8.0 (Stata Corporation, College Station, Tx). Results In sum, 4188 persons were enrolled in the study. Characteristics of all participants are summarized in Table 1 . The main reasons of referral for BMD measurement were menopause in 49%, old age in 16%, glucocorticoid use in 9%, history of low energy fractures in 1.5%, and other reasons (such as metabolic disorders, rheumatoid arthritis, positive family history, leanness, and transplantation) in 4.5% of participants. In 20% of participants, no major risk factor was identified as the referral reason. Table 1 Characteristics of the study population* Male participants (n = 340) Female participants (n = 3848) Age (years) 49.7 (16.3) 53.8 (11.2) Weight (kilograms) 68.5 (13.1) 67.1 (11.9) Height (centimeters) 168.5 (7.7) 156.1 (6.1) Body Mass Index (kg/cm 2 ) 24.1 (4.2) 27.6 (4.7) History of osteoporotic fracture 8 (2.4) 47(1.2) Smoking 35 (10.3) 94 (2.4) Corticosteroid use 89 (26.2) 298 (7.7) Hormone Replacement Therapy 231 (6.0) Age at menarche (years) 13.6 (1.5) Menopause 2137 (55.5) Age at menopause (years) 47.2 (5.8) Femoral T score -0.93 (1.24) -1.43 (1.18) Lumbar T score -1.40 (1.48) -1.45 (1.54) * Numbers are presented as mean (standard deviation in parenthesis) for numerical variables and frequency (percentage in parenthesis) for categorical variables. Totally, 518 participants were diagnosed in osteoporotic range in hip area and 1036 participants in the lumbar area. T-score classifications are presented in Table 2 . Major discordance was observed in BMD results of 115 (2.7%) participants. Minor discordance was observed in 1631 (38.9%) participants and T-score categories of two measurement sites in other 2442 (58.3%) participants were not different. Distribution and pattern of this variable in different genders is depicted in Table 3 . Table 2 Classification of T scores according to WHO criteria in different sites* Lumbar spine Total hip No. % 95% Confidence Intervals No. % 95% Confidence Intervals Osteoporosis (T = -2.5) 1036 24.7 23.4–26.0 518 12.4 11.4–13.4 Osteopenia (-2.5 < T = -1) 1605 38.3 36.8–39.8 1592 38.0 36.5–39.5 Normal (T > -1) 1547 36.9 35.5–38.4 2078 49.6 48.1–51.1 Table 3 Distribution of diagnostic discordances according to WHO criteria in different genders* Male participants (n = 340) Female participants (n = 3848) Total (n = 4188) Major T-score Discordance 7 (2.1) 108 (2.8) 115 (2.7) Hip Osteoporosis, Normal Lumbar 5 16 21 Hip Normal, Lumbar Osteoporosis 2 92 94 Minor T-score Discordance 117 (34.4) 1514 (39.3) 1631 (38.9) Hip Osteoporosis, Lumbar Osteopenia 10 99 109 Hip Osteopenia, Lumbar Osteoporosis 39 515 554 Hip Osteopenia, Normal Lumbar 35 220 255 Hip Normal, Lumbar Osteopenia 33 680 713 T-score Concordance 216 (63.5) 2226 (57.8) 2442 (58.3) Hip and Lumbar Osteoporosis 50 338 388 Hip and Lumbar Osteopenia 93 690 783 Hip and Lumbar Normal 73 1198 1271 * Numbers are presented as frequency (percentage in parenthesis). T-score discordance was more prevalent in women than men (42.2% versus 36.5%, P = 0.042). The mean age of participants with discordance (54.8 years) was higher than the other group (52.5 years, P < 0.001). In 3848 female participants, the number of post-menopausal women with diagnostic discordances (951 of 2027) was significantly higher than pre-menopausal participants with discordance (671 of 1821; P < 0.001). In multivariate analysis (Table 4 ), two genders lost their difference in occurrence of discordance. Effects of age and menopause were established with their significant odds ratios. Participants with late menopause (age at menopause > 50) were more likely to show T-score discordances. Obesity defined as BMI over 30 was recognized as a risk factor for major discordance and smoking as a protective factor against minor discordance. Hormone replacement therapy was a significant protector against both. Table 4 Results of multivariate logistic regression analysis for risk factors of major and minor discordance getting T-score concordance at lumbar and femoral sites as the reference Variables Minor Discordance Major Discordance Gender (female) 1.09 (0.85 – 1.4) 1.02 (0.45 – 2.3) Age decade 1.2 (1.1 – 1.3)* 1.5 (1.2 – 1.9)* Age group (>65 years) 1.2 (1.01 – 1.6)* 1.4 (0.70 – 2.7) Corticosteroid use 0.89 (0.73 – 1.1) 0.71 (0.37 – 1.3) Body Mass Index (>30 kg/cm 2 ) 1.01 (0.87 – 1.2) 1.7 (1.2 – 2.6)* History of osteoporotic fracture 1.1 (0.59 – 2.0) 1.3 (0.29 – 5.5) Smoking 0.66 (0.45 – 0.97)* 0.49 (0.12 – 2.1) Menopause 1.3 (1.1 – 1.5)* 1.7 (1.01 – 2.7)* Hormone Replacement Therapy 0.37 (0.16 – 0.82)* 0.54 (0.36 – 0.82)* Age at menarche (> 13 years) 1.1 (0.90 – 1.3) 0.82 (0.50 – 1.3) Age at menopause (> 50 years) 1.4 (1.1 – 1.7)* 2.0 (1.2 – 3.4)* * indicates significant odds ratio. Numbers are presented as odds ratio (95% confidence intervals in parentheses). Discussion This study reveals that, using WHO criteria for definition of osteoporosis and osteopenia, a significant fraction of patients (41.7% in this study) would show T-score discordance between hip and spine sites. Most of these discordances (38.9%) are from minor category, presenting difference on only one class, and could be due to minor variation in BMD techniques or some minor physiologic dissimilarity. Minor discordance generally does not influence the overall prognosis of patients; however, in the case of patients with one site normal and the other osteopenic, follow up of patients with hip osteopenia seems reasonable [ 7 ]. The multivariate analysis we have implemented to the data could aid clinicians and diagnosticians to approach patients with different characteristics. According to our results, BMD measurement in both sites is necessary at least for older patients and post-menopausal women especially those with delay in menopause. Hormone replacement therapy, however, could decrease the diagnostic discordance and patients receiving estrogen and progesterone are more likely to have similar results in DXA scans of lumbar and femoral areas. This could be the result of drug effects on the BMD of lumber area [ 10 ]. Generally, five different causes have been proposed for occurrence of discordance [ 5 ]. Physiologic discordance is related to the skeleton's natural adaptive reaction to normal external and internal factors and forces. An example of this type of discordance is the difference observed between the dominant and non-dominant total hip. Pathophysiologic discordance is seen secondary to a disease. Common examples include vertebral osteophytosis, vertebral end plate and facet sclerosis, osteochondrosis, and aortic calcification. Anatomic discordance is owing to differences in the composition of bone envelopes tested. An example is the difference in T-scores found for the PA lumbar spine and the supine lateral lumbar spine in the same patient. Artifactual discordance occurs when dense synthetic substances (such as metal from zipper, coin, clip, etc) are within the field of region of interest of the test. And finally, technical discordance occurs when the technician improperly positions the patient for the test or the hardware or software used to acquire the test data is out of order. Major discordance was observed in 2.7% of our participants, which is in agreement with the results of similar studies. In both major and minor discordances, lower BMD for lumbar spine was more prevalent. This could be due to several reasons. The difference between velocities of bone loss in different parts of human body could be the main reason [ 11 ]. Trabecular bones (typical of lumbar area) are known to have a more rapid rate of deprivation in early post-menopausal state in comparison to cortical bone (typical of proximal femur) [ 12 ]. Moreover, most of the etiologies of the secondary osteoporosis (such as glucocorticoid excess, hyperthyroidism, malabsorption, liver disease, rheumatoid arthritis, and medications) first affect spinal column [ 13 ]. This will lead to higher prevalence of lumbar osteoporosis. In addition, weight bearing is a known cause of physiologic dissimilarity, which can cause rise in bone density especially in the hip and femur regions [ 14 ]. This mechanism could be the reason of more major T-score discordances observed by increment of BMI in this study. In 30% of our participants, the lumbar T-score was higher than hip T-score and this culminated in poorer hip diagnoses in 9.2% of participants. This phenomenon could be regarded as 'inverse discordance' and several factors may be involved in its occurrence. One of these reasons is the prevalent vitamin D deficiency in our participants. A recent nationwide study with random sampling from five major cities in Iran reported a high prevalence (about 80%) for vitamin D deficiency in Iranian population [ 15 ]. Other studies have confirmed this finding [ 16 , 17 ]. Basic studies have revealed that decrease in serum concentrations of vitamin D by means of raising serum parathyroid hormone (PTH) would induce reduction in density of cortical bones and may have a supportive role for density of trabecular bones [ 18 ]. The other reason for 'inverse discordance' could be due to other diseases such as minor compression fractures in lumbar area, joint sclerosis, and aortic calcification [ 19 , 20 ]. These ailments can induce errors in the estimation of lumbar BMD and falsely higher values. The observation of 'inverse discordance' could not be regarded as a direct influence of more significant bone loss in femoral region. A known phenomenon named 'birth cohort effect' can play a role [ 21 ]. This indicates that, in the particular section the data have been gathered, a specific observed finding could not be interpreted for the effects of age and time passing. In this study, the reason for lower femoral BMD can be insufficient bone gain during puberty in this area. Latest findings indicates that peak bone mass of Iranian population are about 5% lower than that of western population [ 22 , 23 ]. Decreased bone density in hip region could lead to start of bone loss from lower amounts in older ages and post-menopausal states. This can lead to femoral osteoporosis without significant decrease in lumbar BMD. This study, as every other cross-sectional study, has a number of limitations. We could not rule out the possibility of referral bias for this study. As the study was performed in a referral center affiliated to a teaching hospital, the assumption of similarity of study population to exact community is not reasonable and we could not generalize the results to the Iranian population. The other limitation is the choice of multivariate analysis used in this study. With the current analysis, prediction of the presence or absence of T-score discordances is possible. However, prediction of the situation of one site according to results of the other site or choosing one site to measure BMD need further evaluations and analyses which was behind the scope of this study. Future studies using more powerful statistical analyses with larger sample sizes are needed to establish these imperative questions. The importance of existing discordance on the prognosis and fracture risk of patients needs further prognostic studies with long follow-up designs. The high prevalence of T-score discordance could induce some problems for the physicians in decision-making regarding these patients. In general, high prevalence of discordance in this study and similar studies suggests some defects in the cut-off values for definition of osteoporosis and osteopenia proposed with the WHO [ 5 ]. To eliminate this problem, further studies to re-calculate ranges for definition of these diagnoses (considering diagnostic and therapeutic necessities) seem to be needed. Conclusion In summary, this study indicates that about 40% of participants evaluated for bone density changes in a referral center may show diagnostic discordance, majority of them from minor class. This phenomenon should be regarded as a real and prevalent finding and physicians should become familiar with this topic. Clinicians should look for possible cause or causes of this occurrence and develop a particular strategy approaching to these patients. Competing interests This study was supported by a grant from Endocrinology & Metabolism Research Center of Tehran University of Medical Sciences. Authors' contributions In advance, suggestion of the design of the study was from AS. Data extraction and initial analysis were done by NKT and AH. AM performed additional analyses and wrote the first draft of the paper. AS and BL both had helpful and valuable comments in revising the paper. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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Factors influencing emergency medical readmission risk in a UK district general hospital: A prospective study

Background Over recent years increased emphasis has been given to performance monitoring of NHS hospitals, including overall number of hospital readmissions, which however are often sub-optimally adjusted for case-mix. We therefore conducted a study to examine the effect of various patient and disease factors on the risk of emergency medical readmission. Methods The study setting was a District General Hospital in Greater Manchester and the study period was 4.5-years. All index emergency medical admission during the study period leading to a live discharge were included in the study (n = 20,209). A multivariable proportional hazards modelling was used, based on Hospital Episodes Statistics data, to examine the influence of various baseline factors on readmission risk. Deprivation status was measured with the Townsend deprivation index score. Hazard ratios (HR) and associated 95% confidence intervals (CI) of unplanned emergency medical admission by sex, age group, admission method, diagnostic group, number of coded co-morbidities, length of stay and patient's deprivation status quartile, were calculated. Results Significant independent predictors of readmission risk at 12 months were male sex (HR 1.13, CI: 1.07–1.2), age (age >75 (HR 1.57, CI 1.45–1.7), number of coded co-morbidities (HR for >4 coded co-morbidities: 1.49 CI: 1.26–1.76), admission via GP referral (HR 0.93, CI 0.88–0.99) and primary diagnosis of heart failure (HR 1.33, CI: 1.16–1.53) and chronic obstructive pulmonary disease/asthma (HR 1.34, CI: 1.21–1.48). Higher level of deprivation was also significantly and independently associated and with increased emergency medical readmission risk at three (HR for the most deprived quartile 1.21, CI: 1.08–1.35), six (HR 1.21, CI: 1.1–1.33) and twelve months (HR 1.25, CI: 1.16–1.36). Conclusions There is a potential for improving health and reducing demand for emergency medical admissions with more effective management of patients with heart failure and chronic obstructive airways disease/asthma. There is also a potential for improving health and reducing demand if reasons for increased readmission risk in more deprived patients are understood. The potential influence of deprivation status on readmission risk should be acknowledged, and NHS performance indicators adjustment for deprivation case-mix would be prudent.

Background Over recent years increased emphasis has been given to performance monitoring of NHS hospitals and various quality indicators based on analysis of routine administrative data have been devised[ 1 ]. The 2003 dataset of the Commission of Health Improvement indicators includes 28-day hospital readmission rates following any hospital admission, and also readmission rates following admission for stroke and hip fracture[ 2 ]. Although indicators are currently standardised for age and sex 1 , they are not adjusted for potential case-mix differentials in disease severity, co-morbidity and patient deprivation status. Unplanned hospital re-admissions may represent adverse events and could therefore indicate poor quality of care[ 3 , 4 ]. The interpretation of variation in readmission rates between healthcare organisations is nevertheless complicated[ 5 , 6 ]. Broadly a readmission could be due to healthcare factors (e.g. sub-optimal health and social care, either at hospital or within primary/social care structures), patient factors (e.g. poor treatment adherence), disease factors (e.g. natural disease progression), or a combination of all the above. Readmissions due to healthcare and patient factors could be assumed to be potentially avoidable. There is insufficient evidence about the proportion of hospital readmissions that could be judged to be due to healthcare factors, as estimates of the proportion of medical readmissions that are due to healthcare factors vary widely between 9 and 48%[ 4 ]. Although current NHS performance indicators use readmission rates at 28-days[ 1 , 2 ], there is lack of consensus in the literature about the choice of optimal time interval, with different studies choosing different intervals, ranging from one week to one year[ 4 ]. Intuitively shorter time intervals are more likely to represent "avoidable" readmissions due to poor quality care, nevertheless this may be more applicable in the case of elective surgical admissions rather than emergency medical ones. Moreover, for chronic medical conditions (such as diabetes, chronic obstructive pulmonary disease and heart failure), even a "delayed" readmission may represent a failure of disease management due to deficiencies in healthcare quality[ 4 ]. It can be hypothesised that factors such as patient sex, length of stay, number of coded co-morbidities, method of admission (e.g. presentation to the Accidents and Emergency department or GP referral), as well as patient deprivation, independently influence the probability of hospital readmission. Lower socioeconomic status in particular is independently associated with increased risk for many adverse health outcomes[ 7 ], including hospital readmission due to conditions such as heart failure[ 8 ]. The increasing demand for emergency medical admissions[ 9 ] makes epidemiological studies of medical readmissions a priority. Additionally, emergency medical admissions constitute a sizeable proportion of all hospital admissions, and can therefore play an important role in the overall performance of NHS hospitals under the current set of indicators[ 1 , 2 ]. We therefore conducted a study to examine the effect of several patient and disease factors on the risk of emergency medical readmission at various time intervals following an index emergency medical admission. Methods Context This work was carried out as part of the routine function of Stockport NHS Trust Clinical Effectiveness Unit, and in relation to work commissioned by the then "Emergency Demand Management Group" of the Stockport Primary Care Trust. The objective was to accurately describe the epidemiology of emergency medical readmissions so that demand management strategies (e.g. appropriate targeting of resources to patients with certain conditions, or certain types of presentation) could be informed. Setting Stockport NHS Trust is a district general hospital in Greater Manchester, serving a reference population of about 300,000. About 85% of all patients emergency medical admissions are from Stockport, a population with a slightly lower, compared to the England and Wales average, Standardised Mortality Ratio from all causes (all ages) of 96 (95% CI 94–98)[ 10 ]. Data source, population and follow-up period Hospital Episodes Statistics Data from April 1997 to September 2001 for Stockport NHS Trust were analysed and all emergency medical admissions in Stockport residents leading to live discharge were identified. An emergency medical admission was defined as an emergency hospital admission to any medical specialty in person over 18 years of age. Some persons had more than one emergency medical admission during the study period, and emergency medical admissions other than the index admission (defined as the chronologically first admission during the 4.5-year study period) were excluded. This was because not restricting analysis to index admissions would have meant that any deprivation gradients in readmission rates would have been confounded by deprivation gradients in index admissions, as previously described[ 11 ]. This is an important difference of the methodology used in this study in relation to the way the relevant performance indicators are presently calculated, including "all" (as opposed to index/first only) admissions in the denominator[ 12 ]. An emergency medical re-admission was defined as the first subsequent emergency medical admission during a follow-up period of either 28-days, or 3, 6 and 12 months respectively, following a first (index) emergency medical admission that led to a live discharge, and through the use of a single patient identifier. Observations were censored at the end of the chosen follow-up periods (as above) or at the time of intervening death unrelated to readmission to the study hospital. The latter was ascertained by data-linking to the Stockport Health Authority Public Health Mortality File produced by the Office for National Statistics. Measurement and definitions Index admission data were originally available on: sex; age; length of stay of index admission; International Classification of Diseases (ICD)-10 coded primary diagnosis; number (up to four) of coded co-morbidities; patient post code and admission method (referral by Accidents and Emergency Department, General Practitioner or other). Information on primary diagnosis was aggregated into five categorical groups comprising chronic obstructive pulmonary disease / asthma (ICD codes J44.0–45.9 respectively), heart failure (I50.0–50.9), acute coronary syndrome (I20.0 [unstable angina] and I21.0–9 [acute MI]), stroke (I60.0–I67.0) and all other conditions (all other codes). Length of stay was divided into quartiles (<2, 2–5, 6–11 and >11 days). Deprivation status was subsequently ascribed with an area-based measure, using the 1991 Census enumeration district (ED) of patient's post-code, and by the use of Townsend multiple deprivation index score. Four deprivation groups were defined, using quartiles of the range of the Townsend scores between Stockport EDs. Analysis Kaplan-Meier readmission-free curves at 28 days, and 3, 6 and 12 months were constructed for each of the following variables: sex , age group , diagnostic group (defined as above), admission method , number of coded co-morbidities (0–4), length of stay group (quartile) and deprivation group (quartile). Statistical significance for each of the above variables was assessed by the log rank test. A series of proportional hazards models with follow-up at 28 days, 3, 6 and 12 months were subsequently constructed to examine the adjusted hazard (risk) ratio of emergency medical readmission. Each model included all variables found to be significant in the uni-variable analysis at the 0.05 probability level. The proportional hazards assumption was tested using the Schoenfeld residuals as per the stphtest command in STATA. This showed that a time varying co-variate should be included in all four models, in relation to the length of stay variable (i.e. that an interaction term between length of stay and time of follow-up should be included), and this was hence included in the models. Additionally, for the number of coded co-morbidities and deprivation group variables, a test for trend was performed, entering the actual values as continuous variables. In this context, the test for trend value indicates the proportional change in the risk of readmission associated with one unit change in the exposure variable (i.e. number of coded co-morbidities, Townsend deprivation score). Results There were 21,118 index emergency medical admissions corresponding to an equal number of patients leading to a live discharge during the study period, but primary diagnosis information was only available for 20,209 index emergency medical admissions (Table 1 ). Cases without diagnostic information were excluded from further analysis. Table 1 Basic characteristics of index admissions in study participants (n = 20,209) Variable Category n % Sex Male 9397 46.5 Female 10812 53.5 Age group <60 8094 40.1 60–74 5526 27.3 75+ 6589 32.6 Diagnostic group Acute coronary syndrome 4283 21.2 COPD/asthma 1594 7.9 Heart failure 587 2.9 Stroke 575 2.8 All other diagnoses 13170 65.2 Length of Stay <2 5666 28.0 2–5 5184 25.7 6–11 5174 25.6 >11 4185 20.7 Deprivation Group Affluent 5057 25.0 2 5003 24.8 3 5113 25.3 Deprived 5015 24.8 Unknown 21 0.1 Admission method A&E 12604 62.4 GP referral 7113 35.2 Other 492 2.4 No of co-morbidities 0 2963 14.7 1 3796 18.8 2 3790 18.8 3 8801 43.5 4 859 4.3 Uni-variable analysis The proportion of patients readmitted at 28 days and 3, 6, 12 months progressively increased from 7.2% at 28-days to 23.3% at 12 months respectively (Table 2 ). Male sex, older age group, length of stay, higher number of coded co-morbidities and any primary diagnosis other than the "all other diagnoses" category were significantly associated with higher readmission rates independently of duration of follow-up (Table 2 ). Higher deprivation status was significantly associated with increased readmission rates in follow-up periods longer than three months, but not at 28 days (Table 2 and Figure 1 ). Admission method was not significantly associated with deprivation risk. Table 2 Proportion of patients readmitted (%) by patient subgroup and different periods of follow-up (log rank test p values from relevant Kaplan-Meier readmission-free curves) 28 days p* 3 months p* 6 months p* 12 months p* Sex Men 7.7 0.017 13.5 0.009 18.3 0.003 24.1 0.01 Women 6.8 12.4 16.8 22.7 Age group <60 5.4 <0.001 8.8 <0.001 11.8 <0.001 15.8 <0.001 60–74 8.2 15.1 19.7 26.4 >75 8.5 15.8 22.3 29.6 Admission method A&E 6.9 0.07 12.7 0.2 17.4 0.79 23.3 0.93 GP referral 7.7 13.4 17.7 23.4 Other 7.8 11.6 17.6 23.9 Length of Stay <2 5.9 <0.001 8.6 <0.001 11.2 <0.001 14.7 <0.001 2–5 6.5 10.9 15.5 21.4 6–11 8.0 15.6 21.2 28.0 >11 8.8 17.4 22.3 31.0 Number of coded co-morbidities None 6.1 <0.001 9.6 <0.001 13.2 <0.001 17.3 <0.001 1 6.0 9.8 13.3 17.5 2 7.0 12.3 16.4 22.2 3 8.3 15.8 21.6 28.9 4 7.3 14.3 18.7 24.4 Diagnosis ACS 7.2 <0.001 13.0 <0.001 17.2 <0.001 22.3 <0.001 COPD/Asthma 8.7 15.7 22.1 30.1 Heart Failure 11.1 22.7 31.3 37.5 Stroke 4.5 9.6 14.6 23.0 All other 7.0 12.3 16.6 22.3 Deprivation Affluent 7.1 0.44 11.8 0.002 15.8 <0.001 21.0 <0.001 2 7.2 12.5 17.0 22.2 3 6.9 13.0 18.1 24.2 Deprived 7.7 14.3 19.2 25.9 Total 7.2 12.9 17.5 23.3 *Log Rank test A&E: Accident and Emergency, GP: General Practitioner, ACS: Acute Coronary Syndrome, COPD: Chronic Obstructive Pulmonary Disease Figure 1 Kaplan-Meier readmission-free curves by deprivation group. Multi-variable analysis Male sex, older age group, and primary diagnosis of heart failure and chronic obstructive pulmonary disease/asthma were significantly associated with increased readmission risk, independently of length of follow-up (Table 3 ). With the "all other diagnoses" as the reference category, primary diagnosis of acute coronary syndrome was associated with a significantly increased risk of readmission at 3 and 6 months, but not at 28 days or 12 months. Independently of length of follow-up and all other variables, primary diagnosis of stroke was significantly associated with reduced readmissions risk compared with the "all other diagnoses" category as reference. Table 3 Hazard ratios (HR) by variable and follow-up length, with associated 95% confidence intervals Variables in the Equation 28 days HR (95% CI) 3 months HR (95% CI) 6 months HR (95% CI) 12 months HR (95% CI) Female - - - - Male 1.17** (1.06 – 1.30) 1.14*** (1.06 – 1.23) 1.15*** (1.08 – 1.23) 1.13*** (1.07 – 1.20) Age <60 - - - - Age 60–74 1.41*** (1.23 – 1.62) 1.47*** (1.33 – 1.64) 1.44*** (1.32 – 1.58) 1.46*** (1.35 – 1.58) Age >75 1.45*** (1.26 – 1.67) 1.45*** (1.30 – 1.62) 1.56*** (1.42 – 1.71) 1.57*** (1.45 – 1.70) Affluent - - - - 2 1.01 (0.87 – 1.17) 1.05 (0.94 – 1.17) 1.07 (0.97 – 1.18) 1.07 (0.98 – 1.16) 3 0.98 (0.84 – 1.13) 1.09 (0.98 – 1.22) 1.15** (1.05 – 1.27) 1.17*** (1.08 – 1.27) Deprived 1.09 (0.94 – 1.26) 1.21** (1.08 – 1.35) 1.21*** (1.10 – 1.33) 1.25*** (1.16 – 1.36) Test for trend (Deprivation Index) ^ 1.02 (0.98 – 1.07) 1.06*** (1.03 – 1.10) 1.07*** (1.04 – 1.10) 1.08*** (1.05 – 1.11) All other diagnoses - - - - Heart Failure 1.32* (1.02 – 1.70) 1.43*** (1.19 – 1.71) 1.47*** (1.26 – 1.71) 1.33*** (1.16 – 1.53) COPD/asthma 1.25* (1.04 – 1.50) 1.23** (1.08 – 1.41) 1.29*** (1.15 – 1.45) 1.34*** (1.21 – 1.48) ACS 1.12 (0.97 – 1.28) 1.15** (1.04 – 1.27) 1.12* (1.02 – 1.22) 1.07 (0.99 – 1.15) Stroke 0.54** (0.37 – 0.81) 0.57*** (0.44 – 0.75) 0.65*** (0.52 – 0.81) 0.76** (0.63 – 0.90) Without co-morbidity - - - - 1 co-morbidity 1.02 (0.83 – 1.25) 1.04 (0.89 – 1.23) 1.05 (0.91 – 1.20) 1.10 (0.97 – 1.24) 2 co-morbidities 1.13 (0.93 – 1.38) 1.21* (1.03 – 1.41) 1.19* (1.04 – 1.36) 1.29*** (1.15 – 1.45) 3 co-morbidities 1.25* (1.04 – 1.49) 1.39*** (1.21 – 1.60) 1.41*** (1.25 – 1.59) 1.54*** (1.38 – 1.71) 4 co-morbidities 1.26 (0.93 – 1.69) 1.46** (1.17 – 1.82) 1.42*** (1.18 – 1.73) 1.49*** (1.26 – 1.76) Test for trend (number of com.) ^ 1.08** (1.03 – 1.14) 1.11*** (1.08 – 1.17) 1.13*** (1.09 – 1.17) 1.15*** (1.12 – 1.18) A&E referral - - - - GP referral 1.09 (0.98 – 1.22) 1.00 (0.92 – 1.09) 0.96 (0.89 – 1.03) 0.93* (0.88 – 0.99) Other referral 1.17 (0.85 – 1.60) 0.84 (0.64 – 1.09) 0.91 (0.74 – 1.13) 0.94 (0.78 – 1.13) <2 days LoS - - - - 2–5 days LoS 0.54*** (0.42 – 0.69) 0.82* (0.69 – 0.99) 0.92 (0.79 – 1.08) 1.06 (0.93 – 1.21) 6–11 days LoS 0.52*** (0.41 – 0.66) 0.89 (0.74 – 1.05) 1.14 (0.98 – 1.32) 1.31*** (1.15 – 1.49) >11 days LoS 0.54*** (0.41 – 0.70) 0.95 (0.79 – 1.14) 1.23** (1.06 – 1.44) 1.42*** (1.25 – 1.62) <2 days LoS * Time^^ - - - - 2–5 days LoS * Time^^ 1.07*** (1.05 – 1.09 1.01*** (1.01 – 1.02) 1.01*** (1.00 – 1.01) 1.002*** (1.001 – 1.003) 6–11 days LoS * Time^^ 1.08*** (1.06 – 1.11 1.02*** (1.01 – 1.02) 1.01*** (1.00 – 1.01) 1.002*** (1.001 – 1.003) >11 days LoS * Time^^ 1.09*** (1.06 – 1.11 1.02*** (1.02 – 1.02) 1.01*** (1.00 – 1.01) 1.002** (1.001 – 1.002) *: p < 0.05, **: p < 0.01, ***: p < 0.001 ^ : Denotes the proportion change in probability of outcome associated with one unit change in continuous variable (e.g. Townsend deprivation score index, number of co-morbidities) ^^ In days HR: Hazard Ratio, COPD: Chronic obstructive airways disease, ACS: Acute coronary syndrome, LoS: Length of stay, A&E: Accident and Emergency, GP: General Practitioner. More than two coded co-morbidities were associated with higher readmission risk only in follow-up periods of more than three months duration. However test for trend indicated a strong and significant positive effect of the number of coded co-morbidities independently of follow-up length. Higher deprivation status was independently associated with higher readmission risk at 3, 6 and 12 months, but did not significantly influence readmission risk short term (at 28 days). Test for trend confirmed the strong and statistically significant effect of deprivation at 3–12 months but there was no effect at 28 days. Admission method via a GP referral was significantly associated with a lower readmission risk at one year, but not at any other time intervals. Length of stay of the index admission influences readmission risk differently, depending on the length of follow-up as there was a highly significant interaction between length of stay group and time of follow-up (see Additional file 1 ). Taking into account the relevant time varying co-variate, shorter length of stay is associated with higher readmission risk at discharge and immediately afterwards, but with lower readmission risk thereafter. Discussion The findings indicate that in the study hospital about a quarter of patients with an index emergency medical admission will be readmitted in the same hospital during the subsequent year. Male sex and older age were strongly and independently associated with higher readmission risk, along with diagnosis of heart failure and chronic obstructive pulmonary disease or asthma. Effective measures to reduce readmission rates for patients suffering from these two conditions in particular are available[ 13 , 14 ] but not always used[ 13 , 15 , 16 ]. Improving the availability of effective treatments for these two conditions could contribute greatly to the management of demand for emergency care in general. The present study, at the local health economy level, has helped support the decision making process that allocated increased resources to the management of these two conditions by the expansion or creation of relevant specialist services. As originally hypothesised, patient deprivation status exerted a significant independent effect on the risk of emergency medical readmission at 3–12 months of follow-up, with more deprived patients having had a higher readmission risk. There are several theoretical reasons why deprived patients may be at higher readmission risk, including: disease factors, such as greater disease severity in deprived patients[ 17 ]; patient factors, such as poor adherence to treatment and advice because of educational or behavioural reasons; and health and social care factors, such as differentials in the type and quality of primary care in particular, in a way analogous to the "inverse care law", originally describing differentials in access, rather than quality, of care[ 18 ]. A clearer understanding of the exact mechanisms responsible for deprivation group gradients through further research is necessary for future policy measures aiming at reducing such gradients. Although this is a single-centre study, the results may also have implications for the way current and future NHS performance indicators relating to readmission rates are both constructed and interpreted. NHS hospitals serving pre-dominantly deprived populations might in principle be disadvantaged if indicators are not adjusted for the impact of deprivation on case-mix. Although this study showed no significant effect of deprivation status on readmission risk at 28-days, which is the follow-up period currently used by the performance indicators[ 1 , 2 ], care should be taken when interpreting this "negative" finding. Firstly, this analysis included in the denominator only index (as opposed to "all") admissions, in contrast to the technical specification of the performance indicators[ 12 ]. Because more deprived patients have higher rates of index emergency medical admissions[ 11 ], including all index admission in the calculation will accentuate any deprivation differences in readmission risk, and the performance indicators as they are currently calculated may for this reason be misleading. Previous analysis of the same dataset including "all" admissions provides empirical evidence that this is true[ 19 ]. Secondly, it is possible that a true effect of deprivation status on index readmission rates at 28-days also exists but it was not detected by our study due to its single-centre nature, or insufficient sample size. A larger study, ideally using data from more than one hospital may be warranted. The Department of Health includes performance indicators in the calculations of award of "three-star" status, which in turn is the "gateway" to "Foundation" status"[ 20 ]. Standardising, or otherwise adjusting, for patient deprivation is feasible using the HES data, as this study indicates. Standardisation of readmission indicators for patient deprivation status would be prudent. This would ensure that NHS organisations serving deprived communities would not be unfairly "punished" for poor performance because of factors outside their control. It will also increase the perception of validity of the indicators. Unlike information on disease severity, which is difficult to measure accurately for most medical conditions, information about patient socioeconomic status using area-based (ecological) deprivation measures is relatively easy to obtain, using patient postcodes, routinely included in the Hospital Episodes Statistics dataset. All studies using administrative data are sensitive to the quality of routine data collection. The validity of HES data in relation to age, sex, length of stay, admission method, and area of residence is generally good, but misclassification errors may occur in relation to diagnostic codes and the extent to which co-morbidities are recorded and coded[ 21 ]. Currently the degree of miscoding in our data is uncertain, but an audit of 200 cases in the study hospital has shown diagnostic inaccuracy to be in the order of 7.5%, comparable with levels quoted in the published literature[ 22 ]. Misclassification of primary diagnosis might be assumed to have occurred non-differentially between patients of different deprivation groups, and is so it would have diminished rather than exaggerated any association observed in this study, including the observed effect of deprivation. Misclassification error may have also resulted by the use of ecological measures of socioeconomic status (ecological fallacy). Again, this would reduce the effect size, if one exists. Therefore the effect of deprivation status on readmissions risk reported in our study may be an under-estimate of a true association. A limitation of the study is that, besides the very large sample size, the findings are based on one single hospital in an urban English setting, and in principle the results are not generalisable. Similarly, the study was not population-based, so readmissions that may have occurred to other hospitals (either because of where patients happened to be taken if fallen acutely ill, or due to migration) were not ascertained. In theory such readmissions may have occurred at a differential rate between different deprivation groups. However this factor is unlikely to have biased the results in any considerable way for two reasons. First, the emergency (as opposed to elective) nature of the studied condition (emergency medical admission) makes it unlikely that either patients or doctors exercise an important degree of choice on which hospital a patient is admitted or readmitted, independently of patient deprivation status. Second, due to local geography and service configuration, 85% of the total medical admissions in Stockport residents occur at Stockport NHS (unpublished data). Similarly, by the nature of the hospital-centred nature of the study, admissions to private hospitals could not have been accounted. However, most admissions to private hospitals are for elective surgical procedures (rather than emergency medical reasons) for which we believe this is unlikely to have introduced considerable degree of bias. Lastly it is worth remembering that current NHS performance indicators for hospital Trusts are not population-based. Conclusions Our study suggests that there is an important potential for both managing emergency demand and improving individual patient experience by focusing on the effective management of heart failure and chronic obstructive pulmonary disease. Although there is a similar potential by reducing differentials in readmission risk between deprivation groups, more research is required in order to understand reasons for such differentials in order to inform relevant policy measures. In the mean time, standardisation or other adjustment of hospital readmission indicators for patient socio-economic status in the future would be prudent. Failure to do so may disadvantage hospitals serving primarily deprived communities. Competing interests The author(s) declare that they have no competing interests. Authors' contributions The study was conceived and designed by GL and GC. GL, DH and IG analysed data. All authors contributed in the interpretation of findings and in the writing of the paper. GL and GC are guarantors. Pre-publication history The pre-publication history for this paper can be accessed here: Supplementary Material Additional File 1 Length of stay group and readmission free Kaplan-Meier curves (0–28 days). This file demonstrates that during follow-up of 0–28 days, length of stay is not proportional to readmission risk, reason for which a time varying co-variate was included in the Cox regression model (see main article Text). Click here for file

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543452

Unusual metabolic characteristics in skeletal muscles of transgenic rabbits for human lipoprotein lipase

Background The lipoprotein lipase (LPL) hydrolyses circulating triacylglycerol-rich lipoproteins. Thereby, LPL acts as a metabolic gate-keeper for fatty acids partitioning between adipose tissue for storage and skeletal muscle primarily for energy use. Transgenic mice that markedly over-express LPL exclusively in muscle, show increases not only in LPL activity, but also in oxidative enzyme activities and in number of mitochondria, together with an impaired glucose tolerance. However, the role of LPL in intracellular nutrient pathways remains uncertain. To examine differences in muscle nutrient uptake and fatty acid oxidative pattern, transgenic rabbits harboring a DNA fragment of the human LPL gene (hLPL) and their wild-type littermates were compared for two muscles of different metabolic type, and for perirenal fat. Results Analyses of skeletal muscles and adipose tissue showed the expression of the hLPL DNA fragment in tissues of the hLPL group only. Unexpectedly, the activity level of LPL in both tissues was similar in the two groups. Nevertheless, mitochondrial fatty acid oxidation rate, measured ex vivo using [1- 14 C]oleate as substrate, was lower in hLPL rabbits than in wild-type rabbits for the two muscles under study. Both insulin-sensitive glucose transporter GLUT4 and muscle fatty acid binding protein (H-FABP) contents were higher in hLPL rabbits than in wild-type littermates for the pure oxidative semimembranosus proprius muscle, but differences between groups did not reach significance when considering the fast-twitch glycolytic longissimus muscle. Variations in both glucose uptake potential, intra-cytoplasmic binding of fatty acids, and lipid oxidation rate observed in hLPL rabbits compared with their wild-type littermates, were not followed by any modifications in tissue lipid content, body fat, and plasma levels in energy-yielding metabolites. Conclusions Expression of intracellular binding proteins for both fatty acids and glucose, and their following oxidation rates in skeletal muscles of hLPL rabbits were not fully consistent with the physiology rules. The modifications observed in muscle metabolic properties might not be directly associated with any LPL-linked pathways, but resulted likely of transgene random insertion into rabbit organism close to any regulatory genes. Our findings enlighten the risks for undesirable phenotypic modifications in micro-injected animals and difficulties of biotechnology in mammals larger than mice.

Background The endothelial cell-associated lipoprotein lipase (LPL) works to break down triacylglycerol-rich dietary fats absorbed after a meal, thus generating free fatty acids transported in the blood. Earlier works suggested that LPL acts as a metabolic gate-keeper for fatty acid partitioning between adipose tissue for storage and muscle primarily for energy use [ 1 ]. Then, variation of LPL activity among fat depots as well as ratio of adipose tissue to skeletal muscle LPL activity, have been proposed to be linked to the development of regional obesity under certain genetic predisposition [ 2 ]. Transgenic mouse lines that highly over-express LPL exclusively in muscles, further evidence a role of LPL in the intracellular fate of nutrients into skeletal muscles. Indeed, induced mutant mice over-expressing human LPL (hLPL) exclusively in muscles have, proportional to the level of LPL transgene expression, increases in LPL activity and free FA concentration in muscle [ 3 ], a higher number of metabolic organelles (mitochondria, peroxisomes) in muscles [ 4 ], and elevated muscle oxidative enzymes activities [ 3 , 4 ]. Thus, a greater use of lipids for energy production during fasting has been suggested in transgenic hLPL mice [ 5 ]. In agreement with the inverse relative rates of fatty acid oxidation and glucose utilization in muscle first proposed by Randle and coworkers [ 6 ], mice with over-expression of hLPL specifically in muscles show alterations in muscle glucose metabolism, such as elevated blood glucose levels [ 7 ], increased glycogen stores [ 3 ] or glucose-6-phosphate content [ 5 ], and(or) impaired glucose tolerance [ 5 , 8 ]. Finally, as shown in mice over-expressing a mutant defective hLPL, enhanced lipoprotein uptake into cells may also occur via pathways independent of LPL catalytic activity, resulting in a mitochondriopathy as well as in muscle glycogen accumulation similar to the pattern observed in mice expressing active hLPL [ 9 ]. However, another point not studied so far in hLPL transgenic animals is that uptake of nutrients and(or) intra-myocellular trafficking to target organelles are facilitated to a great extent by specific transporters and(or) binding proteins. Convincing data are available for the involvement of both membrane-associated and cytoplasmic fatty acid-binding proteins in fatty acid uptake by skeletal muscles [ 10 , 11 ]. Especially, a permissive action of heart-type fatty acid binding protein (H-FABP), also known as muscle FABP or FABP3, in delivering fatty acids to mitochondrial β-oxidation systems has been shown [ 12 , 13 ]. Facilitated glucose transport across membranes of muscle cells mediated by GLUT4 is usually considered as rate-limiting for glucose utilization by skeletal muscles in laboratory rodents [ 14 ]. However, it remains to determine whether LPL effects on muscle oxidative pathways involve modifications in the intracellular binding of nutrients. Altogether, metabolic studies in muscles of transgenic animals help to understand the biological links between fatty acid uptake, intracellular lipid metabolism, and some metabolic disorders such as diabetes in human beings. However, most data have been established in mice. Potential advantages of rabbit compared with mouse as human disease model [ 15 , 16 ] relate in part to its lipoprotein profile which more closely mimics that of humans. Therefore, this study aimed to characterize the oxidative phenotype of two skeletal muscles in transgenic rabbits harboring a DNA fragment of the human LPL gene. The study revealed that despite lack of differences in tissue LPL activity when compared with their wild-type littermates, transgenic hLPL rabbits displayed modest increases in both H-FABP and GLUT4 contents in a pure oxidative muscle and significant lower mitochondrial fatty acid oxidation rates in two skeletal muscles differing in their fiber type composition. This suggested that a random insertion of hLPL DNA into the rabbit genome resulted into unexpected disruption of target nutrient pathways. Results Tissue LPL level An amplification product corresponding to hLPL fragment was evidenced in adipose tissue, semimembranosus proprius and longissimus muscles of hLPL group, proving the expression of the transgene in tissues of the rabbit organism. On the contrary, no signal was detected in the same tissues of wild-type animals (figure 1 ). Surprisingly, hLPL rabbits and their wild-type littermates exhibited similar LPL activity for adipose tissue and muscles (table 1 ). Figure 1 Expression of human lipoprotein lipase (hLPL) mRNA in transgenic rabbits. The cDNA obtained by reverse transcription (RT) of total RNA extracted from skeletal muscles or perirenal fat and primed by random primers followed by 35 cycles of PCR with hLPL-specific primers, was loaded on 2% agarose gel. Reaction was performed in parallel in the absence of reverse transcriptase (RT-), to ensure for lack of genomic DNA contamination. Typical RT-PCR results are shown for semimembranosus proprius muscle. Lanes 1–4: RT-PCR product in hLPL rabbit; Lane 5: RT- in hLPL rabbit; Lane 6: 100 bp DNA ladder; Lane 7–10: RT-PCR product in wild-type rabbit; Lane 11: RT- in wild-type rabbit. A band at the expected size of 137 bp was detected in hLPL rabbits only. Table 1 Lipoprotein lipase activity 1 in tissues of wild-type and hLPL transgenic rabbits Tissues Wild-type rabbits hLPL rabbits Perirenal fat 1305 ± 336 1420 ± 500 SMP muscle 2036 ± 583 1546 ± 397 LL muscle 493 ± 111 396 ± 58 1 Activities are presented as mean ± SEM in perirenal fat, semimembranosus proprius (SMP) and longissimus (LL) muscles (nmol free fatty acids released. min -1 per g of tissue). There were no differences among groups ( P > 0.10). Plasma metabolites and tissue lipids Plasma concentrations in triglycerides, free fatty acids, and glucose, were similar in the two genetic groups (table 2 ). Moreover, there were no differences between the two groups for lipid contents in muscles and perirenal adipose tissue (table 3 ), as well as for fat proportion relative to body weight (18.8 ± 1.0 g/kg and 20.6 ± 0.9 g/kg in wild-type and hLPL rabbits, respectively). Table 2 Plasma triglycerides, free fatty acids and glucose levels 1 in wild-type and hLPL transgenic rabbits Plasma metabolites Wild-type rabbits hLPL rabbits Triglycerides 0.69 ± 0.13 0.81 ± 0.14 Free fatty acids 0.41 ± 0.10 0.41 ± 0.11 Glucose 9.21 ± 0.60 8.60 ± 0.27 1 Concentrations are presented as mean + SEM (mmol/L). There were no differences among groups ( P > 0.10). Table 3 Lipids and intracellular nutrient trafficking 1 in perirenal fat and skeletal muscles in wild-type and hLPL rabbits Wild-type rabbits hLPL rabbits Perirenal fat Lipids 677 ± 25 691 ± 31 GLUT4 198 ± 18 248 ± 30 Semimembranosus proprius muscle Lipids 46.5 ± 4.8 42.9 ± 6.5 H-FABP 222 ± 19 *289 ± 20 GLUT4 96.8 ± 14.9 †131.4 ± 8.5 Longissimus muscle Lipids 13.1 ± 2.3 11.8 ± 1.3 H-FABP 20.4 ± 4.6 32.0 ± 6.0 GLUT4 76.3 ± 11.8 94.4 ± 12.2 1 Data are presented as mean + SEM in perirenal fat, semimembranosus proprius (SMP) and longissimus (LL) muscles. Abbreviation used: au (arbitrary units). *Difference in heart-fatty acid bind protein content (H-FABP) in hLPL rabbits as compared with wild-type littermates ( P < 0.05). †Difference in insulin-sensitive glucose transporter GLUT4 in hLPL rabbits as compared with wild-type littermates ( P < 0.10). Nutrient oxidative pathways Muscle content in H-FABP (responsible for cytoplasmic binding of fatty acids in muscle cells), was 30% higher in semimembranosus proprius samples of hLPL rabbits compared with wild-type littermates (table 3 ). The difference between the two groups (+56%) did not reach significance level in the longissimus muscle. This was probably related to a high intra-assay variability, due to the low expression of H-FABP in low-fat glycolytic muscles. The content in insulin-sensitive glucose transporter GLUT4 (the first step in glucose utilization by tissues) was 36% higher ( P = 0.07) in hLPL rabbits than in wild-type animals for semimembranosus proprius muscle, but it did not vary in other sites under study (table 3 ). The mitochondrial oxidation rates of oleate were reduced by 45% and 41% ( P < 0.05) in semimembranosus proprius and longissimus muscles, respectively (figure 2 ), in hLPL rabbits compared with wild-type littermates. By contrast, oxidation rate in peroxisomes did not vary between groups. Figure 2 Mitochondrial and peroxisomal oxidation rates of oleate. Oxidation rates were measured in freshly excised samples of semimembranosus proprius and longissimus muscles, using [1- 14 C]oleate as substrate in the presence (peroxisomal oxidation) or absence (total oxidation) of mitochondrial inhibitors. Mitochondrial oxidation rates were calculated by difference between total and peroxisomal oxidation rates. Values shown are mean ± SEM of oleate oxidation (nmole/min -1 per g of muscle wet weight). The * indicates a significant difference ( P < 0.05) in mitochondrial oxidation rate in hLPL rabbits in comparison with their wild-type (WT) littermates. Discussion Despite a clear evidence for expression of the hLPL transgene in the tissues under study in the hLPL rabbits only, total LPL (human +native) activity in skeletal muscles or perirenal adipose tissue was similar in hLPL rabbits and in their wild-type littermates. This situation contrasts with the moderately enhanced LPL activity in post-heparin plasma reported in another line of hLPL transgenic rabbits [ 17 ], and with the marked elevation of LPL activity observed in adipose tissue [ 18 ] or skeletal muscle [ 3 , 4 , 7 ] of hLPL mice. A preliminary study in the heart of our hLPL trangenic rabbits and their wild-type littermates using polyclonal [ 19 ] and monoclonal [ 20 ] antibodies which recognize different epitopes of the LPL molecule, did not evidence any significant differences in total LPL protein content between groups with both antibodies (data not shown). Furthermore, plasma triglyceride concentration was currently found similar in hLPL transgenic rabbits and wild-type animals, which is again in favor to a similar content in LPL protein among groups rather than to a catalytically defective hLPL enzyme in transgenic rabbits. Indeed, triglyceridemia is consistently found lower in transgenic animals over-expressing a catalytic active hLPL [ 7 , 17 ] and mutant catalytic defective enzyme [ 9 ], although this effect may be less pronounced on some genetic backgrounds [ 9 ]. Then, a possible explanation is that failure in hLPL mRNA traduction currently resulted in no hLPL protein, due to lack of regulatory essential elements in the transgene sequence [ 21 ]. A second explanation may be that expression of hLPL in transgenic animals led to a down regulation of native LPL. Surprisingly, despite the lack of difference in LPL activity, many metabolic differences were found between hLPL rabbits and their wild-type littermates in semimembranosus proprius (a muscle composed exclusively of slow-twitch type I fibers), and to a lesser extent in the fast-twitch glycoytic longissimus muscle. However, unlike results in mice, our findings reported a lower muscle fatty acid oxidation rates in hLPL rabbits. Others have observed that over-expression of hLPL gene specifically in skeletal muscle of transgenic mice rather led to a dose-dependent increase in oxidative enzymes and to a proliferation of the oxidative specialized organelles [ 3 , 4 ]. According to the well-known fatty acid-glucose cycle in skeletal muscles [ 6 ], decreased fat oxidation is generally associated with increased glucose utilization. In accordance with this rule, the muscle content in insulin-sensitive glucose transporter GLUT4, i.e., the first step of glucose utilization in skeletal muscle [ 14 ], was currently found higher in the pure oxidative muscle of hLPL rabbits compared with their wild-type littermates. However, possibly enhanced utilization of glucose was not followed by any variations in blood glucose level. Either elevated blood level [ 7 ] or similar plasma concentration in glucose [ 3 ] have been observed in hLPL mice compared with wild-type animals. Finally, the reason for a higher content of intra-cytoplasmic fatty acid binding proteins (H-FABP) in semimembranosus proprius muscle of our hLPL rabbits compared with wild-type animals remains largely unknown. Indeed, a preferential involvement of H-FABP in delivering intracellular fatty acids to sites of oxidation has been widely suggested [ 22 ]. Here, fatty acid oxidation rate was decreased in hLPL rabbits compared with wild-type littermates, but muscle lipid content and body fat did not vary among groups. One hypothesis may be that fatty acids bound to H-FABP within cell cytoplasm would by-pass any muscle metabolic pathways. If true, fatty acids would be immediately re-exported into the blood circulation and subsequently oxidized in the liver, presumably to prevent muscle from toxicity due to increased fatty acids entry. In vitro and ex vivo findings indeed recently suggest that non-adipose tissue, such as cardiomyocytes, can re-export fatty acids when influx exceeds oxidation rate [ 23 ]. However, there is no clear evidence for such a mechanism in our hLPL rabbits, since plasma concentration of free fatty acids was found similar in the two genetic groups. Various results are reported in the literature data on free fatty acids concentration in serum of hLPL transgenic mammals, with either similar, increased, or decreased levels [ 3 , 4 ] depending of mice strain and level of hLPL over-expression. Altogether, the various metabolic disruptions in skeletal muscles of hLPL rabbits are in favor to a random integration of the micro-injected hLPL DNA within or close to endogenous genes. In transgenic mice, estimates of the frequency of these insertional mutations range from 7 to 20% [ 24 ]. This may have resulted in a loss of function of neighboring genes, aberrant expression patterns, and therefore in unexpected phenotypes. However, genes coding for LPL, H-FABP, GLUT4, and oxidative pathway (e.g. carnitine palmitoyl-transferase I) are not clustered on the same chromosome in the human genome [ 25 ] and likely, although not available, in the rabbit map. Therefore, if any, the integration site of the foreign DNA must have conflicted with regulatory elements of any molecular factors able to modify whole nutrient metabolic cascade. Conclusions During the last 15 years, transgenesis has been extended from mice to larger mammals, with the aim of benefiting human health. Transgenic rabbits for LPL gene may offer useful models to test the relationships between uptake of nutrients, intracellular trafficking and subsequent metabolic fate in a species sharing a lipoprotein profile closely similar to that in Human. However, we currently reported alterations of nutrient bindings and oxidative metabolism in skeletal muscles of hLPL rabbits, despite the lack of difference in tissue LPL activity between transgenic rabbits and their wild-type littermates. It is thus suggested that hLPL phenotype emerged from insertional mutation of hLPL DNA within or close to endogenous genes. This study underlined the risk of unpredictable phenotypic properties in micro-injected transgenic rabbits, and thereby the difficulty of animal biotechnology in mammals larger than mice. Nevertheless, transgenic rabbits remain useful tools for understanding the relative importance of the various metabolic pathways involved in the control of tissue lipid content, especially when the genetic map now under progress will be available in the rabbit. Methods Rabbits The Genetic Committee of the French Ministry of Agriculture approved the experiment. Rabbits were reared and killed in accordance with the French regulations for humane care and use of animals in research. New-Zealand White rabbit does were super-ovulated by injections of porcine-follicle-stimulating hormone, as previously described [ 26 ], and were mated to males of the same genetic background. Embryos were collected 17 hours later. The human LPL (hLPL) fragment of genomic DNA, inserted into a 90-kilobase P1 phagemid together with regulatory elements, was kindly provided by N. Duverger (Aventis, Evry, France). The expression of hLPL fragment in the host organism was governed by the P1 phagemid promoter. DNA solution was injected into the male pronuclei, and the injected embryos were transferred to the pseudo-pregnant females (INRA, Laboratoire de Biologie Cellulaire, Jouy-en-Josas, France). Genomic DNA was extracted from ear biopsy in the offspring [ 27 ]. Presence or absence of hLPL DNA was screened by PCR using 5'-CCCTTTTTCCTGTCTTTTT-3' as sense and 5'-AGTGCTTGAGACTGTC-TCCTAA-3' as anti-sense primers. These primers framed a fragment of 201 bp of the human LPL gene spanning intron 9 and exon 10. Two transgenic littermate male founders were cross-bred with 20 females of a standard New-Zealand White line (A-1067, INRA, France) at the INRA experimental unit (Le Magneraud, Surgères, France), to provide F1 animals for analysis. Pup genotypes were determined at the hLPL locus by PCR from tail tip DNA at the age of 4 weeks, using the primers described above. Control PCR amplification of the actin gene was performed in parallel to ensure DNA quality. After weaning (5 weeks), young rabbits were housed collectively by genotype (8 animals per cage), under a controlled light/dark cycle (16/8 h). They were offered free access to water and to a standard rabbit pelleted diet (16.5% crude protein, 16.4% cellulose, 2.8% fat, 8.3% ash, and 3790 kcal/kg gross energy). At 10 weeks of age, pairs of hLPL rabbits and wild-type littermates of similar body weight (2400 g ± 53, n = 6 in each genotype) were selected within litters, and bled in the fed state. Analysis of plasma metabolites Enzymatic methods adapted to a Cobas Mira multi-analyzer apparatus (ABX, Montpellier, France), were used to determine levels of triglycerides (kit PAP 150, BioMérieux, Marcy l'Etoile, France), free fatty acids (kit Wako NEFA-C kit, Richmond, VA, USA) and glucose (kit PAP 1200, BioMérieux, Marcy l'Etoile, France) in rabbit plasma collected at the time of the death. Tissue preparation Portions of perirenal fat, semimembranosus proprius (SMP) as a muscle composed solely of slow-twitch oxidative fibers, and longissimus (LL) muscle representing predominantly fast-twitch glycolytic fibers, were stored at -70°C until RNA analysis and biochemical measurements. About 300 mg of each muscle was homogenized immediately after sacrifice in an appropriated buffer for measurements of ex vivo oxidation rates, as described previously [ 28 , 29 ]. RNA analysis for expression of the transgene Total RNA from 600 mg of tissues was extracted by acid guanidium thiocyanate-phenol chloroform method [ 30 ], and was reverse transcribed into cDNA using pd(N)6 random primers (Amersham Biosciences, Orsay, France). Nested PCR (Quiagen, Courtaboeuf, France) was carried out (35 cycles) using hLPL cDNA specific primers, as follows. 5'-TTCTGTGAAGAATGAAGTGG-3' as sense and 5'-AGTGCTTGACA-CTGTCTCCTAA-3' as anti-sense primers framed a 137 bp fragment in the exon 10 of hLPL gene. PCR products were loaded on 2% agarose gel. The amplified fragment was picked up and sequenced (ESGS Cybergene, Evry, France). In each sample, the absence of genomic DNA contamination was checked by performing RT-PCR reaction without reverse transcriptase. Lipoprotein lipase activity Lipoprotein lipase (LPL) activity was assessed after homogenization of the tissues in a buffer composed of ammonia-HCl (25 mM) pH 8.2, containing EDTA (5 mM), Triton-X-100 (8 g/l), sodium dodecyl sulfate (0.10 g/l), heparin (5000 IU/l) and peptidase inhibitors. Insoluble material was discarded by centrifugation at 20000 × g for 20 min at 4°C. As previously described [ 31 ], rat serum was used as activator, and Intralipid ® (Pharmacia, Stockholm, Sweden), into which [ 3 H] triolein has been incorporated, was used as the substrate. Liberated [ 3 H]-free fatty acids were quantified by liquid scintillation. Biochemical analyses Tissue lipid content was determined after chloroform/methanol extraction [ 32 ]. Muscle content in H-FABP was determined by ELISA analysis on cytosolic protein preparations [ 33 ] using a rat polyclonal antibody [ 34 ]. Taken into account yields of proteins in cytosolic fractions, results were converted into arbitrary densitometric (DO) units per g tissue wet weight. Insulin-sensitive glucose transporter GLUT4 content was investigated by Western-blot analysis [ 35 ] using a polyclonal antibody raised against a synthetic peptide of the C-terminal part of GLUT4, on tissue preparations obtained for LPL activity determination. Results were converted into arbitrary densitometric (DO) per g tissue wet weight, after taking into account yields of proteins in tissue preparations. Rates of fatty acid oxidation Oxidation rate of oleic acid was determined in freshly excised muscles as described earlier for rat and bovine muscles [ 28 ], with minor modifications to take into account rabbit specificity [ 29 ]. Briefly, samples were minced with scissors and homogenized at a tissue concentration of 60 mg/mL in 0.25 M sucrose, 2 mM EDTA, and 10 mM Tris-HCl ice-cold buffer (pH = 7.4), using a glass-glass homogenizer. A tracer amount of [1- 14 C]oleic acid bound to defatted albumin in a 5:1 molar ratio was used as substrate. Oleate oxidation was measured using L-carnitine and other cofactors, in the absence (total oxidation rate) or presence (peroxisomal oxidation) of mitochondrial inhibitors of the respiratory chain (i.e., 75.6 μM antimycin A, and 10 μM rotenone, SIGMA, St-Louis, MO). The difference between total oxidation and peroxisomal oxidation was considered to be mitochondrial oxidation. All assays were performed in triplicates. Statistics The Kruskal-Wallis non-parametric test was used to analyze differences between groups (SAS Inst, Cary NC, NY, USA). All data are presented as mean ± SEM. Authors' contributions FG, JFH and PH conceived of the study, participated in its design and co-ordination. FG, SBJ and JFH carried out biochemical analyses. MD carried out pup genotyping. CV and LMH carried out micro-injection and provide transgenic breeder animals. FG, JFH and MD drafted the manuscript. All authors read and approved the final manuscript.

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534802

Zygapophysial joint blocks in chronic low back pain: a test of Revel's model as a screening test

Background Only controlled blocks are capable of confirming the zygapophysial joints (ZJ) as the pain generator in LBP patients. However, previous workers have found that a cluster of clinical signs ("Revel's criteria"), may be valuable in predicting the results of an initial screening ZJ block. It was suggested that these clinical findings are unsuitable for diagnosis, but may be of value in selecting patients for diagnostic blocks of the lumbar ZJ's. To constitute evidence in favour of a clinical management strategy, these results need confirmation. This study evaluates the utility of 'Revel's criteria' as a screening tool for selection of chronic low back pain patients for controlled ZJ diagnostic blocks. Methods This study utilized a prospective blinded concurrent reference standard related validity design. Consecutive chronic LBP patients completed pain drawings, psychosocial distress and disability questionnaires, received a clinical examination and lumbar zygapophysial blocks. Two reference standards were evaluated simultaneously: 1. 75% reduction of pain on a visual analogue scale (replication of previous work), and 2. abolition of the dominant or primary pain. Using "Revel's criteria" as predictors, logistic regression analyses were used to test the model. Estimates of sensitivity, specificity, predictive values and likelihood ratios for selected variables were calculated for the two proposed clinical strategies. Results Earlier results were not replicated. Sensitivity of "Revel's criteria" was low sensitivity (<17%), and specificity high (approximately 90%). Absence of pain with cough or sneeze just reached significance (p = 0.05) within one model. Conclusions "Revel's criteria" are unsuitable as a clinical screening test to select chronic LBP patients for initial ZJ blocks. However, the criteria may have use in identifying a small subset (11%) of patients likely to respond to the initial block (specificity 93%).

Background It is estimated that 15 – 40% of chronic low back pain patients have pain arising from the lumbar zygapophysial joints (ZJ)[ 1 , 2 ]. Previous studies have indicated that historical and physical examination findings cannot predict results from diagnostic ZJ blocks [ 1 - 6 ]. A specific sequence of injections of local anesthetic under fluoroscopic guidance into the joint space or targeting the medial branches of the dorsal rami, are reference standards for diagnosis. For the ZJ to be considered the sole source of pain, there must be a total or near total pain ablation for a time consistent with the known properties of the anesthetic agent[ 7 , 8 ]. In a recent study by Revel M et al (1998), the authors found that a cluster of seven items, (hereinafter called Revel's criteria) were shown to be of value in predicting a 75% reduction of pain following a single intra-articular anesthetic injection into the ZJs. The items in the cluster are: age over 65 years, pain well relieved by recumbency, no exacerbation of pain with: coughing and sneezing, forward flexion, extension, rising from flexion and the extension-rotation test[ 9 ]. These authors suggested two clinical strategies: Strategy 1 consists of five or more items being true. Strategy 2 is the same except that one of the true statements must be 'pain well relieved by recumbency'. Estimated sensitivities and specificities for strategies 1 and 2 were 100/92%, and 66/80% respectively. A subsequent study of 200 consecutive patients using double blocks failed to confirm these findings[ 6 ]. Because prognosis for acute low back is good, invasive and expensive and invasive diagnostic testing cannot be justified. However, persistent disabling pain needs more intensive investigation in order to determine appropriate management strategies. Back pain of ZJ origin may be treated using intra-articular steroid injection[ 7 , 10 ]., or radio frequency neurotomy [ 11 - 14 ]. However, the low prevalence of the condition dictates that a clinical selection process capable of identifying patients unlikely to respond to the initial screening diagnostic block is desirable. Patients with a low probability of a positive anesthetic response need not be subjected to the screening block and the tissue origin of pain should be sought elsewhere. Revel's criteria are currently the only documented clinical means by which response to an initial screening block may be predicted, but it remains a provisional finding only, until further research confirms the previous findings. The current study objectives were to estimate the predictive value of the two clinical strategies of Revel et al (1998), using similar measurement parameters (75% reduction in pain VAS after ZJ block), and apply alternative analytic methods to explore any potential utility of the variables used. Methods Design This study utilized a prospective, blinded, concurrent, reference standard-related validity design with intra-articular ZJ or medial branch blocks as the reference standard against which clinical variables were compared. Local Institutional Review Board approval was granted at the beginning of the study. A 75% or more reduction in pain following ZJ block on pain VAS was designated as reference standard A, the same standard used by Revel et al (1998). Based on pain drawings and patient self-report, complete abolition of the patient's primary or dominant pain was designated as reference standard B. Dominant pain location was acquired by pain drawing and direct questioning, and documented prior to clinical examination and diagnostic injection in a prospective manner. Post injection dominant pain location was acquired by reference to pain drawings and direct questioning also. Patients Patients with low back pain with or without lower extremity symptoms, referred to a private radiology practice in New Orleans, USA specializing in the diagnosis of spinal pain, were invited to participate in the study. Patients receiving ZJ blocks were either referred specifically for that procedure or had the procedure included in their radiology examination based on pre-injection clinical evaluation by the injectionist (CA). Between May 2001 and October 2002, physical therapists attended the clinic in blocks that ranged from 4 to 8 weeks (ML) and examined patients. Normal scheduling was not affected by the presence of the visiting therapists, so patients were consecutive during these periods. All patients had undergone imaging studies prior to referral from a variety of medical and paramedical practitioners. Some were self-referred. Patients were excluded from the study if they were unwilling to participate, were too frail to tolerate a physical examination, or were deemed by any member of the clinic team to be unable to comprehend the study procedure. Prior to the formal clinical examination, clinic staff recorded basic demographic and medical data. Measurements Pain 100 mm visual analog scales (VAS) scales for current, best and worst pain. A current pain VAS was repeated after the clinical examination and following ZJ blocks. The 23-point Roland-Morris Disability Questionnaire [ 15 ] was completed to evaluate disability, and psychosocial distress estimated using the Zung Depression Index[ 16 ], the Modified Somatic Perception Questionnaire[ 17 ] and the Distress Risk Assessment Method (DRAM) [ 18 ]. The physical examination History taking and a structured physical examination were carried out by a physical therapist with 30 years of clinical experience as a manipulative therapist (ML). Some patients were examined by a physical therapist with 17 years experience (SBY). The clinical examination occupied 30 to 60 minutes and included many tests besides those necessary for the current analysis, as part of a larger project. Inconclusive findings or incomplete examinations were documented. The physical examination included a visual assessment of range of motion, recording anatomical location of dominant pain, nerve tension tests, key muscle strength tests, tendon reflex tests, light touch sensitivity, a McKenzie[ 19 ] styled examination and where possible, Waddell's tests for signs of inappropriate pain behaviour[ 20 ]. The data for Revel's criteria[ 9 ]were obtained in a prospective and systematic manner using standardized language and terminology. The four physical tests that form part of the criteria are depicted in Figure 1 . (see file Figure 1 Revels criteria.png) Radiology examination Prior to ZJ blocks, the radiologist reviewed case notes and imaging studies, and conducted a physical examination that guided the type of diagnostic procedure to be employed and the target structures. Intra-articular ZJ joint injection or MBB using standard technique[ 5 ] was carried out by an interventional radiologist (CA) with 20 years experience, or by an injectionist under his guidance. Patient pain responses to injections were recorded as 0.5 cc Lidocaine 2% was slowly injected into the target joint or at medial branch targets. Pain intensity 100 mm VAS's were recorded 30 to 45 minutes post procedure, then hourly in a pain journal for eight hours post-injection. Reference standards A and B were evaluated. A positive anesthetic response was recorded if reduction or abolition of pain lasted the known duration of lidocaine, about one and a half hours. Where appropriate and possible, positive responders were rescheduled for confirmatory blocks using bupivacaine 0.75%. A ZJ source of pain was confirmed if a confirmatory block was positive and relief of pain lasted for at least four hours. Some patients received ZJ blocks and sacroiliac joint injections during the same session. If the combined block was positive, the patient was scheduled to return for confirmatory blocks to identify which structure was responsible for the effect. If the combined block produced less than 75% reduction in pain, a negative ZJ block was recorded. Blinding Physical therapists conducting the clinical examination were blinded to the results of previous imaging studies and diagnostic injections, the Roland, Zung and MSPQ questionnaires. The injectionist was blinded to the results of the physical therapy examination and diagnostic conclusions. Data analysis Basic statistical values for demographic variables and regression analyses were calculated using statistics software (Minitab version 13.31 © Minitab Inc 2000). Differences between included and excluded patients were evaluated with the student's t, chi square, and Kruskal-Wallis tests where appropriate. Significance for differences was set at p < 0.05. Calculations of sensitivity, specificity, predictive values and likelihood ratios with 95% confidence intervals were performed using Confidence Interval Analysis software © Bryant T.N. 2000[ 21 ]. Results Initial ZJ blocks were carried out on 151 chronic low back pain patients. Thirty-four patients were excluded from analysis as they received another intervention in the same procedure session and did not return for differentiating and confirmatory blocks. One case was excluded through incomplete data on Revel's criteria. Following ZJ block, 27 of 116 patients satisfied reference standard A. Data required for determination of Reference standard B were missing for five of the 116 cases. Eighteen of these 111 patients satisfied reference standard B. Table 1 contains demographic and other descriptive characteristics with comparisons between included and excluded patients. Included patients had longer time off work than excluded patients (mean 55 versus 99 weeks) but otherwise had similar characteristics. In specifically evaluating Revel's criteria against reference standard A, logistic regression failed to achieve significance as a model (n = 108, p = 0.46). Two variables; "absence of pain with coughing and sneezing" and "no exacerbation of pain rising from flexion", showed a trend towards significance as predictors within the model (p = 0.07). Using Revel's criteria within a logistic regression with reference standard B as the response variable, a strong trend towards significance was reached (n = 100, p = 0.06). One component variable (age over 65) individually reached significance within the model: (p = 0.004, odds ratio 16.1 with 95% confidence intervals of 2.4 and 107.8). In the whole sample 12.5% were aged over 65 years whereas of the 19 positive responders six were over 65 years (31.6%). The same patients satisfied both strategies of Revel et al. Estimated sensitivity, specificity, predictive values and positive likelihood ratios for both strategies of Revel et al are presented in Table 2 . With respect to reference standards A & B, sensitivities are low at 11 and 17%, specificities are high at 91 and 93% and likelihood ratios are 1.2 and 2.5 respectively. Of the 27 patients satisfying reference standard A, 13 (48%) returned for confirmatory ZJ blocks. Three of these reported 75% or more reduction in pain following the confirmatory block. None of the three patients with confirmed ZJ pain satisfied Revel's criteria. Discussion The current data produces results that are in stark contrast to those of Revel et al (1998) with sensitivity low and specificity high. However, 'no pain with cough and sneeze' and 'no exacerbation of pain rising from flexion' approached statistical significance in relation to a 75% reduction pain after ZJ block (reference standard A). These variables are in line with Revel's results. Age over 65 is associated with reference standard B (abolition of primary pain). Likelihood ratios for the criteria are lower in the current data also. Some of the differences in results may be explained by a number of factors: 1. Revel et al's study was a placebo controlled design whereas we did not routinely utilize a similar or equivalent control. 2. The patients in Revel et al's sample were older (mean 58 versus 43 years), and had a shorter duration of symptoms (mean 78 versus 160 weeks). 3. It is also possible that the high level of standardization when acquiring the criteria data in the current study, and the prospective methodology might have contributed to the differences in results. Following anaesthetic blocks, patients frequently state that the pain prompting consultation is abolished, yet a post-procedure pain VAS still registers more than 0/100. In this study reference standard B was evaluated as an alternative to the usual standard, so that pain in areas above the lumbar spine or pain directly attributable to the needle insertion site do not result in inappropriate post procedure VAS scores. In the interests of developing more precise instruments documenting results of diagnostic blocks, we propose that in future studies, the VAS scale should specifically refer to the primary pain complaint for which the diagnostic block is undertaken. Based on the current data, Revel's criteria are not suitable as a screening test to select patients suitable or unsuitable for an initial screening ZJ block. Such a screening device should have high sensitivity to ensure that most patients likely to respond are included in the initial diagnostic block. Our study suggests that, at best, Revel's criteria, might identify a small subset (11%) of patients likely to respond to a screening block (specificity 93%). Conclusions Neither strategy utilizing Revel's criteria is suitable as a clinical screening device for selection of chronic LBP patients for initial diagnostic ZJ blocks. In contrast to Revel's findings, the current data demonstrated low sensitivity and high specificity for these clinical criteria. The high specificity of the criteria reported in this study relates to a single uncontrolled screening block. Consequently these criteria can not considered diagnostic of painful lumbar ZJ. Only placebo controlled or double ZJ blocks are able to diagnose this source of low back pain. Competing Interests The author(s) declare that they have no competing interests. Authors' contributions ML conceived the design of the study, examined all but 10 patients, carried out data analysis and prepared the manuscript BÖ assisted in project design and manuscript preparation CNA assisted in project design, provided facilities and conducted fluoroscopically guided injections BMcD carried out data analysis and assisted in manuscript preparation. All authors have read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC534802.xml

212687

A Functional Analysis of the Spacer of V(D)J Recombination Signal Sequences

During lymphocyte development, V(D)J recombination assembles antigen receptor genes from component V, D, and J gene segments. These gene segments are flanked by a recombination signal sequence (RSS), which serves as the binding site for the recombination machinery. The murine Jβ2.6 gene segment is a recombinationally inactive pseudogene, but examination of its RSS reveals no obvious reason for its failure to recombine. Mutagenesis of the Jβ2.6 RSS demonstrates that the sequences of the heptamer, nonamer, and spacer are all important. Strikingly, changes solely in the spacer sequence can result in dramatic differences in the level of recombination. The subsequent analysis of a library of more than 4,000 spacer variants revealed that spacer residues of particular functional importance are correlated with their degree of conservation. Biochemical assays indicate distinct cooperation between the spacer and heptamer/nonamer along each step of the reaction pathway. The results suggest that the spacer serves not only to ensure the appropriate distance between the heptamer and nonamer but also regulates RSS activity by providing additional RAG:RSS interaction surfaces. We conclude that while RSSs are defined by a “digital” requirement for absolutely conserved nucleotides, the quality of RSS function is determined in an “analog” manner by numerous complex interactions between the RAG proteins and the less-well conserved nucleotides in the heptamer, the nonamer, and, importantly, the spacer. Those modulatory effects are accurately predicted by a new computational algorithm for “RSS information content.” The interplay between such binary and multiplicative modes of interactions provides a general model for analyzing protein–DNA interactions in various biological systems.

Introduction During B- and T-lymphocyte development, the immunoglobulin (Ig) and T-cell receptor (TCR) genes are assembled from discrete V, D, and J gene elements via a process of genomic rearrangements known as V(D)J recombination ( Fugmann et al. 2000a ; Hesslein and Schatz 2001 ). V(D)J recombination occurs in two steps: a cleavage phase, in which DNA double-strand breaks are created, followed by a joining phase ( Fugmann et al. 2000a ). During cleavage, the lymphoid-specific recombinase proteins, RAG1 and RAG2, presumably together with the accessory DNA-binding factor HMG-1/2, bind recombination signal sequences (RSSs) located adjacent to each rearranging gene element. A complex consisting of RAG and HMG proteins bound to a single RSS is then thought to capture a second RSS ( Jones and Gellert 2002 ; Mundy et al. 2002 ); within this synaptic complex, the RAG proteins introduce double-strand breaks at the junctions between each RSS and its associated gene element ( Hiom and Gellert 1998 ). In the joining phase, ubiquitous DNA repair factors involved in nonhomologous end joining, in the presence of the RAG proteins, ligate the cleaved ends, generating two types of recombinant junctions: precise signal joints (SJs) and imprecise coding joints (CJs) ( Bassing et al. 2002 ). RSSs are an essential part of V(D)J recombination, as their presence is both necessary and sufficient to direct RAG-mediated recombination on artificial substrates. Sequence alignments of RSSs suggested that each signal can be dissected into three components: a conserved heptamer (consensus: 5′-CACAGTG) and a conserved nonamer (consensus: 5′-ACAAAAACC), separated by a poorly conserved spacer of either 12 ± 1 or 23 ± 1 bp ( Tonegawa 1983 ; Akira et al. 1987 ; Ramsden et al. 1994 ). The heptamer is the site of DNA cleavage ( Roth et al. 1992 ), while the nonamer provides a major binding surface for RAG1 ( Difilippantonio et al. 1996 ; Spanopoulou et al. 1996 ; Nagawa et al. 1998 ; Swanson and Desiderio 1998 ). Spacer length restricts recombination according to the “12/23 rule”; efficient recombination occurs between two gene elements only when one element is flanked by an RSS with a 12 bp spacer (12-RSS) and the other by an RSS with a 23 bp spacer (23-RSS) ( Tonegawa 1983 ). Despite the enormous specificity that RSSs confer on the recombination process, the recombination signals themselves demonstrate a remarkable degree of sequence heterogeneity. Only the first three nucleotides of the heptamer and the fifth and sixth positions of the nonamer show almost perfect conservation ( Ramsden et al. 1994 ) and are therefore thought to be the major determinants of RSS specificity and function. Mutations in any of these five “critical” nucleotides, alone or in combination, essentially abolish recombination ( Tonegawa 1983 ; Akira et al. 1987 ; Hesse et al. 1989 ). The roles of the remaining “noncritical” heptamer and nonamer nucleotides are less understood. Some studies observed that mutations in these lesser-conserved residues have comparatively milder phenotypes unless present in combination ( Tonegawa 1983 ; Hesse et al. 1989 ). Others, however, reported that nonconsensus deviations of noncritical residues lead to vastly different recombination efficiencies, resulting in significant differences in gene element usage in the unselected antigen receptor repertoire ( Ramsden and Wu 1991 ; Suzuki and Shiku 1992 ; Connor et al. 1995 ; Larijani et al. 1999 ). Our current knowledge about the functional role of the spacer is that its length is crucial in directing V(D)J recombination ( Tonegawa 1983 ; Hesse et al. 1989 ). Comprehensive sequence alignments show that the spacer possesses some degree of sequence conservation, albeit at a level much lower than that of the heptamer or nonamer ( Ramsden et al. 1994 ). This suggests that there is little or no selective pressure for spacers to adopt a given sequence. Studies examining the effects of different spacer sequences on recombination activity have yielded seemingly conflicting results. An early report found up to a 15-fold effect of different spacer sequences ( Akira et al. 1987 ), while follow-up studies observed either no effect ( Wei and Lieber 1993 ; Akamatsu and Oettinger 1998 ) or up to 6-fold effects ( Fanning et al. 1996 ; Nadel et al. 1998 ; Larijani et al. 1999 ). This suggests that spacer sequence may affect recombination activity, but a comprehensive picture of the rules that govern how it does so is lacking. One limitation inherent in many prior RSS studies is that they have often been performed in the context of RSSs with a preponderance of consensus nucleotides. While such analyses have been useful in characterizing the most conserved or critical determinants of RSS function, the contributions of other nucleotides are potentially masked in RSSs with high consensus nucleotide representation. That most endogenous RSSs do not contain consensus heptamer and/or nonamer motifs further suggests the need for a careful study of individual RSS nucleotides in the context of physiologically relevant RSSs. We have performed an extensive analysis of the functional properties of RSS elements in the context of endogenous recombination signals. To explore the nature of the complex relationships that might exist among different elements and positions in the RSS, we started with the nonfunctional RSS associated with the murine Jβ2.6 pseudogene element of the TCRβ locus (Jβ2.6 RSS). While most such pseudogene elements are flanked by RSSs with crippling mutations ( Akira et al. 1987 ), Jβ2.6 is unique in that the sequence of its flanking RSS suggests no obvious explanation for its complete lack of activity ( Figure 1 ). All of the critical residues are conserved, and each nonconsensus nucleotide in the heptamer and nonamer is represented in at least one other functional RSS in the TCRβ locus ( Figure 1 ). A systematic analysis of Jβ2.6/consensus hybrid RSSs revealed that the nonamer, by itself, is the biggest determinant of Jβ2.6 RSS activity and that the lack of Jβ2.6 RSS function is due to the concerted action of nonconsensus nucleotides throughout the entire RSS, including the spacer. Surprisingly, we found that in combination with other consensus elements, an artificial consensus spacer can markedly boost recombination activity, while an anticonsensus spacer strongly impairs activity. Furthermore, in a genetic screen for functional spacer sequences, we observe a selective pressure for substrates with an increased representation of consensus nucleotides. Our results provide strong support for the model that RSS activity is a summation of numerous complex interactions between the RAG proteins and the RSS, involving not only the heptamer and nonamer but also most (if not all) basepairs of the spacer. Figure 1 Recombination Signal Sequences Heptamer, spacer, and nonamer elements of 12-RSSs referred to in this study are shown. “Cons.” and “Anti-Cons.” denote the consensus and anticonsensus 12-RSSs, respectively. VκL8, Jβ2.6, and Jβ2.2 are murine 12-RSSs. “Jβ Cons.” denotes the consensus RSS compiled for all functional 12-RSSs in the murine Jβ1 and Jβ2 clusters. Where more than one nucleotide is listed at any given position, this indicates a shared preponderance of those nucleotides. For consensus RSSs, nucleotides in bold indicate almost absolute conservation; for the anticonsensus RSS, bold nucleotides are almost completely absent. Nucleotides in lowercase italics appear at slightly reduced frequencies compared to the other nucleotides listed. “Jβ-G/-A/-T/-C” and the corresponding numbers indicate the number of functional RSSs in the murine Jβ1/Jβ2 clusters at which the respective nucleotide appears at the designated position. At the top of the figure, the position of each nucleotide is labeled with respect to the first position of the respective element. Results In Vivo Assay for Recombination We generated a series of recombination substrates to measure the ability of various hybrid Jβ2.6/consensus 12-RSSs to rearrange to a “standard” 23-RSS (consisting of consensus heptamer and nonamer elements flanking a spacer from the functional Ig Jκ1 RSS). This standard 23-RSS was used instead of the natural Jβ2.6 RSS partner (the 23-RSS flanking Dβ2), since the substrates containing the Dβ2 23-RSS showed much lower levels of recombination in our hands (data not shown). The 12-RSS coding flank was the same for all constructs, namely that of Jβ2.6. For our study, a polymerase chain reaction (PCR)-based assay ( Figure 2 , top) was employed, which allowed us to visualize recombination efficiencies across a >1,000-fold range. The recombination substrates were transfected into the human embryonic kidney cell line 293T along with constructs expressing full-length RAG1 and RAG2 proteins, and recombination frequencies were measured by PCR using primers that amplify SJs. To confirm that the amplified products in our PCR assay were bona fide SJs, we demonstrated that they could be cleaved efficiently with Apa LI restriction endonuclease, which cuts precise RSS–RSS junctions (data not shown). The amount of recombination substrate recovered from each transfection was measured by PCR and used to normalize the recombination activity. Although we assayed primarily for SJ formation, analyses of CJ formation yielded parallel results (data not shown). As a reference, we used a substrate containing the 12-RSS from the TCR Jβ2.2 gene element (see Figure 1 ), which recombines at low but detectable levels, as measured both in our system and during T-lymphocyte development ( Figure 2 , lanes 1–4) ( Livàk et al. 2000 ). Figure 2 Recombination Activities on Hybrid Jβ2.6/Consensus RSSs A diagram of the recombination assay (SJ formation) is shown (top). Activities were measured on substrates containing the indicated hybrid 12-RSS and a standard 23-RSS. H, Sk, Sc, or N denotes the consensus heptamer, VκL8 spacer, consensus spacer, or consensus nonamer, respectively; each 12-RSS bears the indicated combination of consensus/VκL8 elements, with the remaining elements belonging to Jβ2.6 RSS. To determine relative recombination efficiencies, the amount of SJs was first corrected for DNA recovery, then normalized to the values obtained for the substrate containing the Jβ2.2 RSS. Relative recombination efficiencies for each of three experiments are shown as bar graphs; the average value is shown below each sample. The gels shown here correspond to Experiment 3 and represent products of PCRs on 10-fold dilutions of recovered plasmid DNA. Consensus Heptamer, Spacer, and Nonamer Replacements Recombination of Jβ2.6 RSS is below the level of detection of our assay ( Figure 2 ). Substitution of a consensus heptamer (H) into the Jβ2.6 RSS elevates the recombination frequency to levels just above background ( Figure 2 , lanes 13–16). Similarly, substitution of a spacer from a standard, functional 12-RSS (recombination signal sequence spacer [Sk], from Ig VκL8; see Figure 1 ) or of an artificial consensus spacer (Sc) only marginally restores recombination ( Figure 2 , lanes 17–24). By contrast, substitution of a consensus nonamer (N) boosts recombination activity to the level of Jβ2.2 RSS ( Figure 2 ; compare lanes 1–4 to 25–28), approximately 20-fold higher than substitution of H, Sk, or Sc alone and at least two orders of magnitude above Jβ2.6 RSS. Therefore, the nonamer, by itself, is the biggest single determinant of Jβ2.6 RSS activity. The combination of a consensus heptamer and nonamer (H–N) further increases activity approximately 10-fold above N alone ( Figure 2 , lanes 45–48). Hence, the cumulative effects of nonconsensus mutations in the heptamer and nonamer elements of Jβ2.6 RSS are quite large. In combination with a consensus heptamer and/or a consensus nonamer, the presence of either the VκL8 or the consensus spacer markedly enhances recombination activities above those observed with the Jβ2.6 RSS spacer ( Figure 2 , lanes 29–44). Although there is some fluctuation between experiments, in each replicate the greatest enhancement by the Sk or Sc spacer is seen in combination with a consensus heptamer: on average, H–Sk and H–Sc are 30- to 50-fold higher than H alone. By comparison, Sk–N and Sc–N are 3- to 8-fold higher than N, while H–Sk–N and H–Sc–N are 3- to 9-fold higher than H–N. Thus, a functional spacer can, in most cases, “rescue” the effects of a nonconsensus nonamer more fully than the effects of a nonconsensus heptamer, suggesting that the spacer has greater functional overlap with the nonamer than with the heptamer. Single-Nucleotide Consensus Replacements The heptamer and nonamer of Jβ2.6 RSS differ from the consensus in only five positions (see Figure 1 ): the last three nucleotides of the heptamer and the second and fourth nucleotides of the nonamer. To determine which of these nucleotides make the greatest contributions to Jβ2.6 RSS activity, we introduced the respective consensus nucleotides individually at each of these positions. Since substitution of a consensus heptamer alone yields very low recombination levels ( Figure 2 ), we assayed single-nucleotide heptamer replacements (H[5], H[6], and H[7]) in combination with a consensus spacer. We also assayed substrates containing H(5) combined with a consensus nonamer or with both consensus spacer and nonamer elements. All single-nucleotide heptamer replacements result in significant partial restoration of activity, to levels at least 50% of those obtained with the full consensus heptamer (data not shown). This suggests that the low activity of the Jβ2.6 RSS heptamer is due to contributions of all three nonconsensus nucleotides. Substitution of a consensus nucleotide at either the second or fourth position of the nonamer (N[2] or N[4], respectively), alone or in combination with a consensus heptamer and/or spacer, partially reproduces the effects of the full consensus nonamer ( Figure 3 A). Interestingly, in each set of constructs, N(2) confers a greater restoration of activity than N(4): on average, constructs containing N(2) recombine at 50% the level of N, while constructs containing N(4) recombine at roughly 10% of N. This suggests that the recombination process has a greater preference for preserving a consensus C at the second position of the nonamer than a consensus A at the fourth position. Figure 3 In Vivo Recombination Activities on Hybrid 12-RSSs with Nonamer Point Mutations or with the Anticonsensus Spacer The plots, error bars, and values listed below each sample represent the averages of three experiments. Note that all recombination efficiencies presented in this figure were obtained from transfections/PCRs that were completely independent from those shown in Figure 2 . Abbreviations are identical to those used in Figure 2 . (A) N(2) or N(4) denotes point substitution of the consensus nucleotide at the second or fourth position of the nonamer, respectively. (B) Sac indicates substrates that contain an anticonsensus 12-RSS spacer. Anticonsensus Spacer Replacements In the presence of a consensus heptamer and/or nonamer, a consensus spacer markedly enhances recombination levels over the Jβ2.6 RSS spacer. We therefore wondered whether the presence of an artificial anticonsensus spacer (Sac) (see Figure 1 ), containing the least-conserved nucleotide at each position ( Ramsden et al. 1994 ), would impair recombination. In all cases, Sac reduced recombination levels 10- to 20-fold compared to the already inefficient Jβ2.6 RSS spacer ( Figure 3 B; compare N to Sac–N, and H–N to H–Sac–N). In our experimental system, the consensus and anticonsensus spacer sequences are therefore capable of specifying a surprisingly large range of recombination efficiencies of up to two orders of magnitude. Coupled Cleavage In Vitro Two important questions arise from the results of these in vivo assays. First, do the differences in the RSS nucleotide sequences affect the cleavage or the joining phase of the reaction? Second, are the RAG proteins by themselves the only proteins that mediate the discrimination between various RSSs? To address these questions, we performed standard 12–23 coupled cleavage reactions using purified, truncated (core) RAG proteins ( Figure 4 A). The linear substrates for these reactions were amplified by PCR from the plasmids used in the transient recombination assay. The amount of coupled cleavage products from three independent sets of reactions was quantified ( Figure 4 C). While the consensus RSS (H–Sc–N) promotes efficient cleavage of up to 23% of the input substrate, the Jβ2.6 RSS is cleaved at extremely low levels, at or below the limit of detection ( Figure 4 A, lane 2). As expected from the in vivo experiments, Jβ2.2 is sufficient for low but clearly detectable cleavage ( Figure 4 A, lane 26). In agreement with the SJ formation data, the consensus nonamer substitution (N) boosts the level of cleavage significantly ( Figure 4 A, lane 6), while the introduction of Sk or Sc has less effect ( Figure 4 A, lanes 8 and 10). In contrast to our findings on SJ formation, the substrate containing a consensus heptamer (H) is as efficiently cleaved as that containing N ( Figure 4 A; compare lanes 4 and 6). Interestingly, all substrates containing a consensus nonamer (and to a lesser extent those harboring a consensus spacer) show a high level of single-site cleavage at the 12-RSS ( Figure 4 A, lanes 6, 10, 12, 18, and 20); such products, which are only rarely generated on extrachromosomal substrates in vivo ( Steen et al. 1997 ), could account for a reduced level of coupled cleavage compared to the recombination efficiencies obtained for the respective constructs in our SJ assays. The underlying mechanism of this phenomenon is the topic of ongoing studies. Figure 4 In Vitro Cleavage Reaction (A and B) Coupled cleavage was performed using body-labeled DNA substrates containing a standard 23-RSS (filled triangle) and different 12-RSSs (open triangle) as indicated above the lanes. Reaction products were separated on 4% polyacrylamide gels. The identity of the bands is indicated by symbols located between the gels; an arrow indicates the double cleavage product, while an asterisk marks single-site cleavage products. The gels shown here correspond to Experiment 2. (C and D) The intensity of the bands from three individual experiments (see legend) was quantified and the average cleavage efficiency calculated for each individual substrate (indicated below the chart). The efficiencies are displayed as relative to those obtained for Jβ2.2, which were arbitrarily set to 1. Interestingly, a favorable spacer sequence (Sk or Sc), when paired with H or N, boosts cleavage over the Jβ2.6 RSS spacer ( Figure 4 A, lanes 12, 14, 16, and 18). The levels of cleavage for H–Sk or H–Sc are reproducibly higher than those for Sk–N or Sc–N; although the effect is less striking than for SJ formation, the limits of detection in the coupled cleavage assay dictate that this assay spans a much narrower range of activities than the SJ formation assay. To further address the role of spacer sequences in our coupled cleavage system, we performed another set of experiments using the substrates containing the anticonsensus spacer (Sac) ( Figure 4 B and 4D). In conjunction with either consensus heptamer (H–Sac) or consensus nonamer (Sac–N), the anticonsensus spacer reduces cleavage 5- to 10-fold compared to the consensus spacer (H–Sc or Sc–N) ( Figure 4 C and 4D) and 3-fold compared to the Jβ2.6 RSS spacer (H or N) ( Figure 4 B; compare lanes 4 and 8 to lanes 6 and 10, respectively). This suggests that the Jβ2.6 RSS spacer, although “poor” compared to Sk or Sc, is still more proficient for cleavage than Sac. RSS Binding It is likely that differences in the nucleotide sequences of the RSS lead to variations in the stability of RAG–RSS complexes ( Hiom and Gellert 1997 ; Akamatsu and Oettinger 1998 ; Swanson and Desiderio 1998 ). This idea provides one obvious explanation for the observed differences in SJ formation and cleavage efficiency among the various analyzed 12-RSSs. To address this possibility, we analyzed binding of the RAG proteins to individual isolated 12-RSSs, since the 23-RSS remained identical in all experiments described above. Binding was assessed in standard gel-shift assays using oligonucleotide substrates containing the respective 12-RSSs ( Figure 5 A). All binding assays were performed three times; the quantitation of binding for each RSS relative to Jβ2.2 is displayed in Figure 5 B. (Note that the amount of shifted complex has been normalized for the amount of free probe, which contributes to the fact that, between some samples, visual assessment of relative binding activities are less striking than quantitative measurements.) As expected, the consensus 12-RSS (H–Sc–N) shows the highest binding efficiency, while binding to the endogenous Jβ2.6 RSS is weak, about 2-fold reduced compared to our standard, the functional Jβ2.2 12-RSS. Given that, as with the coupled cleavage assay, the range of activities in the binding assay is much narrower than in the SJ formation assay, these results correlate well with those obtained in the other assays. Substitution of the individual consensus elements H, Sc, and N, however, led to surprising results. While the consensus nonamer (N) sequence, as expected, increases the level of binding (up to that of Jβ2.2), the consensus spacer (Sc) alone has no effect on binding at all, and the consensus heptamer (H) consistently reduces the level of binding. The consensus spacer boosts binding only in the context of a consensus nonamer (the ratios of Sc–N:N and H–Sc–N:H–N are greater than H–Sc:H), and the consensus heptamer contributes significantly to RAG–RSS interactions in this assay only when both spacer and nonamer are consensus sequences (H–Sc–N:Sc–N > H–N:N or H:Jβ2.6 RSS). This indicates that the nonamer is the predominant element determining the stability of the initial RAG–HMG–RSS complex while the heptamer makes additional important contributions to cleavage and recombination not reflected in this binding assay. Figure 5 In Vitro Binding (A) Binding assays were performed using the 5′-end-labeled 12-RSS substrates indicated above the lanes. Each reaction contained identical amounts of DNA substrate. Owing to differences in the end-labeling efficiencies, the quantitation (shown in [B]) is required to make quantitative comparisons. The gels shown here correspond to Experiment 3. (B) The relative amount of substrate in the shifted complex was determined. The binding efficiencies from three independent experiments were calculated relative to the binding seen for Jβ2.2 oligonucleotides (which were arbitrarily set to 1). The average value is displayed below the chart. In the context of a consensus nonamer, the consensus spacer reproducibly enhances binding more than a consensus heptamer (Sc–N > H–N). In contrast, the anticonsensus spacer (H–Sac–N) reduces binding about 3-fold compared to H–Sc–N ( Figure 5 A and 5B). The effects of Sc–N compared to Sac–N are also clearly visible. Interestingly, the levels of binding in the presence of Sac are very similar to those obtained for the respective RSSs containing the original Jβ2.6 RSS spacer, in contrast to the comparative effects of the two spacers on cleavage (see Figure 4 ). Taken together, the results of our binding studies underline clearly that the reduced ability of the Jβ2.6 RSS to participate in the initial interaction with the RAG complex, and hence the subsequent steps of V(D)J recombination, is caused not solely by the Jβ2.6 RSS nonamer but also by the “inefficient” spacer sequence. This indicates that the spacer helps the nonamer to efficiently lock the RAG proteins onto the RSS. The heptamer can contribute to this only when interactions with the other two elements are favorable. Genetic Screen for Functional Spacer Sequences Although the RSS spacer is poorly conserved and no naturally occurring RSS has yet been identified that bears the published consensus spacer sequence, our results show that the presence of the most- or least-conserved nucleotides at all positions of the spacer dramatically alters recombination activities of RSSs that contain a consensus heptamer and/or nonamer. This suggests that a functional preference exists for certain spacer sequences over others. We therefore established a genetic screen for functional spacer sequences in which each position of the spacer was randomized to contain either a consensus or an anticonsensus nucleotide (Sc/Sac). Because the greatest effect of the consensus spacer in our experiments is seen in combination with a consensus heptamer (H–Sc), the randomized spacer was analyzed in the context of 12-RSSs containing a consensus heptamer and the Jβ2.6 RSS nonamer (H–Sc/Sac). The H–Sc/Sac library contained roughly 80,000 clones, sufficient to represent each of the 4,096 possible spacer sequences multiple times (data not shown). We transfected the H–Sc/Sac library into 293T cells together with vectors expressing full-length RAG1 and RAG2 , and we cloned and sequenced PCR-amplified SJs. As a control, we analyzed PCR products corresponding to unrearranged substrates from library pools transfected in the absence of RAG1 and RAG2 ( Figure 6 ). This control pool shows a bias toward the presence of C nucleotides (the consensus nucleotide at positions 4 and 7–9 of the spacer, and the anticonsensus nucleotide at positions 1 and 6), such that the overall bias of the unselected library is slightly toward the consensus spacer (total consensus/total anticonsensus nucleotides = 1.19), consistent with sequence analysis of untransfected library clones (data not shown). Sequence analysis of amplified SJs reveals an overall enrichment for consensus spacer nucleotides over the unrearranged control (total consensus/total anticonsensus nucleotides = 1.73 for SJs, versus 1.19 for control). Spacer positions 1–5 (adjacent to the heptamer) and 8–11 all show a preference for the consensus nucleotide; the remaining positions show little or no preference for the consensus or in one case (position 7) even an enrichment for the anticonsensus nucleotide ( Figure 6 , white bars). The strongest preference for consensus is seen at position 5, which shows almost a 3-fold enrichment over the unrearranged control; interestingly, previous mutation analyses have implicated this spacer position as having a role in affecting recombination levels ( Fanning et al. 1996 ; Larijani et al. 1999 ). In general, the degree of enrichment at any given position reflects the degree to which the consensus nucleotide is represented among the endogenous RSS repertoire ( Figure 6 ) ( Ramsden et al. 1994 ). Figure 6 Genetic Screen for Preferred Spacer Sequences A plasmid library containing 12-RSSs with a consensus heptamer and either consensus or anticonsensus nucleotides at each position of the spacer was screened for spacers with higher activity using either in vivo recombination or in vitro coupled cleavage assays (see text for details). The number of library clones screened was >10 5 . In total, 240 sequences from two independent in vivo experiments and 205 sequences from two in vitro screens were analyzed. The relative enrichment for a consensus over an anticonsensus nucleotide at each position was calculated (taking the bias in the starting library into account). The average from two experiments is displayed in the bar graph and the values are displayed above or below the bars. The log 2 of the ratio of the frequency of consensus and anticonsensus nucleotides at each position is displayed; hence, a value of one indicates that the respective nucleotide occurs two times more frequently in the selected population than in the starting library. In addition, the degree of conservation of each nucleotide is indicated ( Ramsden et al. 1994 ). To determine whether the preferred spacer sequences for SJ formation and cleavage differ, the library screen was also performed in vitro. To obtain artificial SJs from our biochemical cleavage assays, T4 ligase was added to the deproteinized cleavage products, which circularized the cleavage product containing two signal ends. The sequence analysis of such artificial SJs from two independent cleavage reactions showed that positions 2–5 as well as positions 8–11 of the spacer are enriched for consensus over anticonsensus sequences ( Figure 6 , black bars). While these observations mirror the SJ formation data, the nucleotide located at position 1 (and to some extent position 3) seems less important for coupled cleavage than for recombination in vivo. Similar to the in vivo experiment, position 5 shows the highest magnitude of enrichment for the consensus (about 4-fold). The differences between the results of the two experimental systems (SJ formation in vivo and cleavage in vitro) could be a reflection of the number of sequences obtained in each type of analysis (200–250) or could represent differences in the nucleotide requirements of spacer participation in cleavage versus SJ formation. Overall, our experiments indicate that spacer effects are largely mediated by the RAG proteins and occur, at least in part, in the first phase of V(D)J recombination: the recognition of the RSSs, their synapsis, and the cleavage step. Correlation with a Computational Model for RSS Function The observation that an RSS spacer can act in concert with the noncritical residues of the heptamer and nonamer to drastically modulate RSS activity suggests the need for models of RSS function that take into account complex functional relationships among the different nucleotides. A predictive algorithm for quantitatively assessing the potential of a given DNA sequence to undergo V(D)J recombination has recently been developed ( Cowell et al. 2002 , 2003 ). This algorithm calculates the theoretical recombination potential, or RSS information content (RIC) score, by examining internucleotide relationships within a given DNA sequence. We calculated RIC scores for the hybrid Jβ2.6/consensus RSSs used in this study, and we compared them to the experimental binding, cleavage, and recombination values ( Figure 7 A and 7B; data not shown). The correlation between RIC scores and our experimental data is striking. The RIC score for Jβ2.6 RSS is below the threshold (−40) for sequences that would be expected to recombine. The addition of consensus heptamer and/or nonamer elements boosts RIC scores, mirroring the increases in binding, cleavage, and SJ formation. Of particular interest is the fact that effects of consensus and anticonsensus spacers on binding/cleavage/recombination are prominently reflected in the RIC scores as well. Intriguingly, RIC scores appear to be more strongly correlated with cleavage ( r S = 0.90) than with binding ( r S = 0.86) and most correlated with SJ formation ( r S = 0.96). The correlations between our experimental data and RIC scores suggest that the failure of Jβ2.6 RSS to recombine and the ability of consensus heptamer, spacer, and nonamer elements to rescue Jβ2.6 RSS activity are functions of how well RSS structure corresponds to that of a preferred sequence. In this case, the selective advantage of the consensus RSS is not limited to a few critical nucleotides in the heptamer or nonamer but, rather, extends throughout the length of the RSS, even in regions (e.g., the spacer) that were previously thought to be unimportant. Figure 7 Theoretical Predictions of RSS Qualities The average recombination/cleavage efficiencies obtained in the in vivo experiments (A) and in vitro assays (B) are plotted against the RIC scores for the 12-RSS in the respective recombination substrates. Note that the values obtained from the in vitro cleavage assays were normalized to account for differences in the detection range of individual experiments. Further support for the potential of the RIC score as a theoretical measure for RSS activity arises from our genetic screen. For both the in vivo and the in vitro screens, the mean RIC score of the 12-RSSs in the enriched population is higher than that of the starting pool (data not shown), and those differences are statistically significant (Student's t test and the Mann–Whitney test, p<0.0002 for all tests). This indicates that the RIC score is able to predict the quality of RSSs and that this ability is not limited to the well-conserved heptamer and nonamer but also applies to the far more diverse spacer. Discussion RSSs are the DNA elements that direct and control the V(D)J recombination reaction. In the TCR loci, differences in the abilities of individual RSSs to recombine with each other are a significant determinant of variations in the frequencies with which gene elements appear in the mature TCR population ( Livàk and Petrie 2002 and references therein). The molecular basis of such differences in intrinsic recombination activities lies in the remarkable sequence diversity of endogenous RSSs. Previous studies using consensus or nearly consensus RSSs suggested that only a handful of absolutely conserved nucleotides in the heptamer and nonamer serve as the major determinants of RSS specificity and function. These studies, however, did not take into account the fact that the vast majority of endogenous RSSs do not contain fully consensus elements; hence, the physiologic roles of lesser-conserved RSS nucleotides are likely of much greater significance than previously estimated. Contributions of Individual Elements Starting from the nonfunctional Jβ2.6 RSS, we asked the following question: what effects do a perfect heptamer, nonamer, or spacer and combinations thereof have in an inactive or poorly active RSS? We show that a number of mutations in noncritical RSS positions are required to convert Jβ2.6 RSS into a highly active 12-RSS or to convert a highly active RSS (H–Sk–N or H–Sc–N) into a completely nonfunctional, pseudogene-type RSS. Our experiments demonstrate that all RSS nucleotides, including the spacer element and the noncritical positions of the heptamer and nonamer, have some sequence-directive roles. In general, we observe that the magnitude of the effects of unfavorable nucleotides in noncritical RSS positions is dependent on the presence of other unfavorable nucleotides. This explains why, in previous studies using largely consensus RSSs, the effects of nonconsensus nucleotides at the noncritical positions were concluded to be less significant ( Tonegawa 1983 ; Hesse et al. 1989 ). Contributions of Individual Nucleotides in Jβ2.6 RSS The Jβ2.6 RSS heptamer differs from the consensus in the fifth, sixth, and seventh positions; none of these is drastically more important than any other in specifying overall heptamer function (data not shown). The Jβ2.6 RSS nonamer differs from the consensus in the second and fourth positions (see Figure 1 ), and the G at the fourth position disrupts the poly(A) tract present in the consensus nonamer. Previous footprint analyses and studies on the homologous DNA-binding domain of the bacterial Hin recombinase ( Feng et al. 1994 ) suggest that RAG1 may bind the nonamer in the minor groove of this poly(A) tract ( Spanopoulou et al. 1996 ; Akamatsu and Oettinger 1998 ; Nagawa et al. 1998 ). Hence, we expected that restoration of the poly(A) tract of the nonamer would have a greater boosting effect on recombination levels than a consensus substitution at the second position. Instead, the opposite is true, regardless of the sequences in the remainder of the RSS (see Figure 3 ). Having the consensus cytidine at position 2 creates a CA step within the nonamer. Such CA steps have been implicated in alternative DNA structures ( Gorin et al. 1995 ); while previous discussion has focused on the CA steps present at the site of cleavage in the heptamer, it is possible that a single CA step in the nonamer is important for the RAG complex to identify the subsequent downstream poly(A) tract. Defects in RAG Binding to Jβ2.6 RSS Previous binding studies have shown that the nonamer is the key element for initial RAG–RSS interactions and that mutations within the nonamer can strongly reduce or even completely abolish formation of the 12-SC (signal complex) ( Hiom and Gellert 1997 ; Akamatsu and Oettinger 1998 ). In contrast, mutating the entire heptamer leads only to a partial decrease in 12-SC formation, and, importantly, the absolutely conserved “CAC” triplet contributes only as much to binding as the last four nucleotides of the heptamer ( Akamatsu and Oettinger 1998 ). Our gel-shift studies recapitulate these observations with the Jβ2.6 RSS heptamer and nonamer (see Figure 5 ). Moreover, a hybrid Jβ2.6/consensus RSS containing a consensus nonamer can promote 12-SC formation as efficiently as the functional Jβ2.2 RSS (see Figure 5 ). This explains why replacement of the Jβ2.6 RSS nonamer with a consensus nonamer can restore recombination to low but physiologically relevant levels (see Figure 2 ). The effect of a consensus spacer on 12-SC formation exhibits striking plasticity (see Figures 2–5 ). Additionally, in our in vitro screen, the areas of the 12-RSS spacer most highly enriched for consensus nucleotides (see Figure 6 ) correlate with sites of spacer contacts identified in previous footprinting studies (spacer positions 2–5 and 9–11) ( Akamatsu and Oettinger 1998 ; Nagawa et al. 1998 ; Swanson and Desiderio 1998 ; Swanson 2002 ). Given that the nonamer provides the most important contact surfaces, if strong interactions with the nonamer can form, then the presence of a consensus spacer may allow additional favorable contacts to be established, not only in the spacer itself, but even farther away, in the heptamer. By contrast, an unfavorable spacer (e.g., the Jβ2.6 RSS spacer or Sac) may structurally “insulate” protein–DNA contacts seen in the nonamer, such that potential heptamer contact surfaces that could otherwise contribute to overall 12-SC stability remain hidden. This may explain why a consensus heptamer, in the absence of a good nonamer, is unable to promote formation of a stable 12-SC complex. Our in vitro cleavage assay integrates the effects of RSS binding, pairing, and actual DNA cleavage. Hence, the differences between the results of binding and cleavage assays suggest that the steps following initial binding (paired complex [PC] formation and DNA cleavage) are also regulated by spacer sequences. PC formation requires the recognition of the partner RSS with respect to its spacer length, and thus it is plausible that the sequence of spacers influences the protein–DNA contacts required for this compatibility test. Since it is within the PC that coordinated, synchronous DNA cleavage takes place ( Hiom and Gellert 1998 ; West and Lieber 1998 ), it is conceivable that RSSs “communicate” with each other and that their spacer sequences therefore may affect the alignment of the cleavage site with respect to the recombinase active site. Such structural changes may underlie the phenomenon of the “beyond 12/23 rule” that restricts V(D)J recombination of the TCRβ locus, preventing recombination of certain 12–23 RSS pairs and favoring recombination of others ( Jung et al. 2003 ). The 23 bp spacer of the Vβ RSSs is the critical element in dictating the strong preference of Vβ RSSs for the 12-RSS flanking the D segments as compared to the 12-RSS flanking the J segments, and this preference is regulated before or at the cleavage step ( Jung et al. 2003 ). These intriguing findings, however, did not provide experimental insight into how a DNA motif whose sequence had previously been deemed unimportant could paradoxically play such an important role. Our findings provide a framework with which to understand how such an unexpected phenomenon might occur. Finally, the differences between the in vitro cleavage and in vivo recombination assays indicate an additional role of the spacer sequence in the joining phase of the reaction. This seems plausible, since joining is thought to start with the controlled disassembly of the postcleavage complex in which the four DNA ends, including the RSSs, are held in intimate contact with each other, presumably by the RAG proteins ( Hiom and Gellert 1998 ; Tsai et al. 2002 ). Spacer sequences might thus be involved in controlling the structure and stability of such complexes. Relationship between Spacer Sequence Conservation and Recombination Activity Based on comprehensive sequence alignments showing a small but significant degree of spacer sequence conservation ( Ramsden et al. 1994 ), a few studies demonstrated reproducible effects of up to 6-fold of naturally occurring spacers on recombination levels ( Fanning et al. 1996 ; Nadel et al. 1998 ). In transient transfection assays, we infer a much wider range of recombination efficiencies solely due to differences in spacer sequence. Strikingly, we observe that spacer sequence variably affects RSS activity depending on the extent to which each nucleotide of the spacer matches either the most- or the least-conserved nucleotide. This observation resolves some of the apparent discrepancies observed among previously published studies. For example, a poly(G) spacer, which reduces recombination 15-fold compared to a highly active control ( Akira et al. 1987 ), contains one consensus and five anticonsensus residues; by contrast, a spacer containing intermixed G and C residues, which has no effect on recombination activity ( Wei and Lieber 1993 ), contains five consensus and four anticonsensus residues. A Structural Basis for the Ability of RAG Proteins to Recombine Highly Diverse RSSs We find that progressive accumulation of nonconsensus nucleotides within an RSS progressively impairs recombination activity and that, at the less-conserved positions of an RSS, a multitude of nonconsensus nucleotides acting in concert can render the RSS completely inactive. This suggests that the RAG–RSS complex can tolerate or correct for a considerable amount of sequence and/or structural diversity. UV–cross-linking studies previously demonstrated RAG1 and RAG2 cross-linking to the heptamer, particularly near the site of cleavage ( Eastman et al. 1999 ; Mo et al. 1999 ; Swanson and Desiderio 1999 ). Footprint analyses of the 12-SC show that complex formation is at least partly blocked by base or phosphate group modification on the spacer side of the heptamer, on both the heptamer- and nonamer-proximal sides of the spacer, and throughout the nonamer ( Akamatsu and Oettinger 1998 ; Nagawa et al. 1998 ; Swanson and Desiderio 1998 ; Swanson 2002 ). The identified contact sites in the spacer coincide with the areas of the spacer that were preferentially found to be consensus type in our genetic screen (see Figure 6 ). Moreover, the observed recombination efficiencies of our hybrid substrates correlate well with the predicted recombination efficiencies from RIC analyses (see Figure 7 A and 7B). Together, these findings support a unifying model in which the RAG proteins establish multiple contacts throughout the length of an RSS (including the spacer) that allow for fine-tuning of activity. Such an extensive network of RAG–RSS contacts within the recombinase complex would create a “structural buffer,” in which unfavorable nucleotides at only a few noncritical positions might be compensated for by favorable protein–DNA interactions at other positions. Conceptually similar models exist for the I- Ppo I and I- Cre I homing endonucleases, which cleave at recognition sites approximately 20 bp in length ( Argast et al. 1998 ; Jurica et al. 1998 ), and which can tolerate sequence heterogeneity in cleavage sites. Both I- Ppo I and I- Cre I form direct sidechain interactions with most of the nucleotides in their recognition sites, and it is believed that the extensive protein–DNA contacts contribute to tolerance of sequence diversity. Based on our in vivo, in vitro, and in silico analyses, we propose that the RAG–RSS complex contains two distinct types of protein–DNA interactions: “digital” (or binary) interactions of a strictly sequence-specific nature, and “analog” (or multiplicative) contacts that fine-tune the strength of the digital contacts ( Travers 1993 ). Digital interactions are established with those nucleotides for which proper sequence is absolutely critical for activity (e.g., the first three nucleotides of the heptamer and positions 5 and 6 of the nonamer). Analog interactions describe local structural variations brought about by different sequences along the rest of the RSS. Disruption of digital interactions completely precludes complex formation (e.g., a single mutation of a critical residue in the consensus RSS can render it entirely inactive), yet digital interactions alone are not sufficient to establish complex formation (e.g., the critical residues by themselves cannot confer activity to the Jβ2.6 RSS). This duality in the nature of protein–DNA contacts present within the RAG–RSS recombinase may be applicable to other biological systems, including other transposases, transcription factors, and DNA-binding proteins. In most protein–DNA interaction systems, the target sequence to which a protein binds contains some nucleotides that are absolutely critical, and others that are noncritical. Digital interactions are established with the absolutely conserved nucleotides in the form of sequence-specific binding, conferring a binary specificity; the digital contacts therefore determine whether a protein will bind (+1) or not (0). Analog contacts are then established with the lesser-conserved nucleotides; the analog interactions act as functional multipliers that determine the efficiency of complex stability, yielding a spectrum of binding efficiencies ranging from full activity (1 × A max , where A = effect on binding efficiency due to analog interactions) to no activity (0 × A min ). Hence, the noncritical residues are crucial for determining how well a protein complex can exert its biological function. By including so many nucleotides as requirements for RSS function, the V(D)J recombination system may have evolved to avoid random cleavage of DNA and translocation errors. If only the critical heptamer and nonamer nucleotides were required for activity, the frequency of cleavage at inappropriate or “cryptic” sites in the genome would be expected to be quite high. By contrast, the required participation of noncritical nucleotides in complex stability safeguards the reaction against uncontrolled cleavage. Hence, from the standpoint of controlled diversification of reaction specificity, it is beneficial for the recombinase to have evolved a spacer with a high degree of sequence heterogeneity, while maintaining intimate contact with the spacer nucleotides via analog interactions. The complex multiplier effect of analog contacts throughout the length of the RSS, superimposed onto specific digital contacts in the heptamer and nonamer, therefore confers upon the recombinase the critical ability to distinguish between inappropriate sites that happen to contain the requisite absolutely conserved nucleotides (e.g., the Jβ2.6 RSS) versus true binding sites whose sequences diverge markedly from the consensus (e.g., most endogenous RSSs). Theoretical Predictions of RSS Quality RIC scores provide a powerful tool for the prediction of RSS quality based on nucleotide sequence. This method generates statistical predictions of RSS function based on the physiologic 12- and 23-RSSs in the mouse antigen receptor gene loci. In our study, RIC scores accurately predicted the relative efficiencies with which RSSs were bound, cleaved, and rearranged (see Figure 7 ; data not shown). Interestingly, the capacity of RIC models to predict RSS quality is not restricted to sequence variability in the conserved RSS heptamer and nonamer; RIC scores also predict the effects of the RSS spacer sequence on RSS function with considerable accuracy. It is striking that RIC scores correlate so well with SJ formation, less well with cleavage, and less well still with RSS binding. This supports the idea that individual nucleotides (and groups thereof) make distinct contributions to the different steps of the V(D)J recombination reaction. This concept is consistent with previous findings showing that the nonamer is a major determinant of binding while the influence of the heptamer becomes most apparent at the level of cleavage. Hence, the efficiency with which an RSS recombines represents an integration of its protein–DNA interactions throughout all steps of the reaction, and RIC scores provide a remarkably accurate prediction of this. RIC models should be useful not only in guiding RSS mutation studies, but also in identifying potential cryptic RSSs in the genome, whose usage could lead to genomic alterations as an initial event leading to chromosomal translocations and cancer ( Cowell et al. 2002 , 2003 ). Furthermore, an identical mathematical approach could be useful for predicting binding sites for DNA-binding complexes (e.g., transcription factors) in general, since the algorithm incorporates the combination of both the digital and the analog DNA–protein interactions that determine the biological function of a given protein complex on a potential DNA target. Materials and Methods Oligonucleotides and plasmids. The sequence of oligonucleotides used for cloning of recombination substrates and libraries are presented in Table S1 . The oligonucleotides used in the gel-shift experiments are listed in Table S2 , and the sequences of oligonucleotides used for PCR ( INNE1 , CIT4A , TL1 , TL2 , TL3 , TL4 , TL5 , and TL6 ) have been described previously ( Eastman et al. 1996 ; Leu et al. 1997 ). The pSJΔ series of substrates for the in vivo recombination and in vitro cleavage assays was created as follows: pSF299 ( Fugmann and Schatz 2001 ) was modified to create p299-Jβ2.6 by replacing the original 12-RSS with a Jβ2.6 12-RSS such that the 12/23-RSS pair is in deletional orientation; for all other substrates, the 12-RSS of p299-Jβ2.6, flanked by Hind III and Sal I sites, was replaced with the respective annealed oligonucleotides (see Table S1 ). To generate the library for the genetic screen, the oligonucleotide HSCSAC1 was synthesized that contained a 1:1 molar ratio of consensus:anticonsensus nucleotides at each position of the spacer and an additional randomized trinucleotide sequence downstream of the nonamer. The oligonucleotide SJLIBREV was annealed, the overhang was filled in using Klenow fragment (New England Biolabs, Beverly, Massachusetts), and the double-stranded fragment was digested with Hind III and Sal I and ligated into the linearized p299-Jβ2.6 vector. Ligation reactions were transformed into DH5α, colonies were harvested into 120 ml of Luria broth (containing 100 μg/ml ampicillin), and plasmid DNA was prepared after an additional incubation at 37°C at 250 rpm for 15 min. pEBB, pEBB-RAG1, and pEBB-RAG2 expression constructs have been described elsewhere ( Roman et al. 1997 ). Recombination assays. Human embryonic kidney 293T cells were transfected with 6 μg of recombination substrate and 3 μg each of pEBB-RAG1 and pEBB-RAG2 using calcium phosphate as described previously ( Fugmann and Schatz 2001 ); for control samples without RAG expression constructs, 6 μg of pEBB was substituted. After 48 h, DNA was recovered by rapid alkaline lysis preparation (RAP) ( Hesse et al. 1987 ). PCR was performed on 10-fold serial dilutions in 20 μl reaction volumes containing 1× Taq buffer (Invitrogen, Carlsbad, California), 2 mM MgCl 2 , 0.1 mM each dNTP, 0.5 μM each oligo, and 0.2 U Taq (Invitrogen). To quantify DNA recovery, the oligonucleotide pair TL5/TL6 was used for the PCR (94°C for 15 s, 60°C for 15 s, 72°C for 30 s, for 18 cycles). To detect SJs, DNA samples were treated with Dpn I, Mlu I, and Xho I to remove unreplicated and unrecombined plasmids. Oligonucleotides INNE1 and CIT4A were used to amplify SJs (94°C for 15 s, 60°C for 15 s, 72°C for 30 s, for 28 cycles). To detect CJs, RAP samples were treated with Dpn I and CJs were amplified using primers TL2 and TL3 . All PCR products were electrophoresed on native 4.5% polyacrylamide gels, stained with SYBR green, visualized using a Fluoroimager 595 (Molecular Dynamics, Sunnyvale, California), and quantified using ImageQuant software (Molecular Dynamics). Genetic screen for functional spacer sequences. 293T cells were transfected with the plasmid library and RAG or pEBB constructs as described in the Results. Extrachromosomal DNA was extracted and samples were digested with either Dpn I/ Mlu I/ Xho I (for cloning of SJs) or Dpn I only (for cloning of unrearranged bands in no-RAG controls). PCR was performed using INNE1 and CIT4A primers, and samples were electrophoresed and stained as indicated above. The products corresponding to the appropriate SJ or unrearranged bands were excised, purified, and cloned into pCR2.1 using a TOPO-T/A cloning kit (Invitrogen). DNA was prepared from individual transformed colonies and sequenced. The in vitro screen was performed using the plasmid library as the substrate in a standard coupled cleavage reaction. After proteinase K digestion, the products were precipitated and dissolved in 100 μl of 1× ligase buffer. T4 DNA ligase (1 μl) (New England Biolabs) was added and the mixture incubated at 16 °C for 4 h to create artificial SJs. The resulting plasmids were treated identically to the plasmids recovered after transfection in the in vivo screen. Protein expression. Recombinant GST-RAG2, MBP-RAG1, and HMG2 were expressed and purified as described previously ( Spanopoulou et al. 1996 ; Eastman et al. 1999 ; Rodgers et al. 1999 ). DNA-binding and cleavage assays. The body-labeled DNA substrates for the cleavage assay were generated by PCR using the oligonucleotides TL1 , TL4 , and the respective recombination substrate as a template. The 12-RSS oligonucleotide substrates used in EMSA were generated by annealing the 5′-end-labeled top strand with an equimolar amount of the unlabeled respective bottom strand (see Table S2 ). Binding and cleavage reactions were performed as reported previously ( Fugmann et al. 2000b ), and gels were quantified using a Storm 820 PhosphorImager and ImageQuant software (Molecular Dynamics). RIC score calculation and other computational analysis. Statistical models of RSS correlation structure have been previously reported ( Cowell et al. 2002 ) ( Data S1 ). Supporting Information Data S1 RIC Score Calculation and Other Computational Analysis (23 KB DOC). Click here for additional data file. Table S1 Oligonucleotides for Cloning of Recombination Substrates (31 KB DOC). Click here for additional data file. Table S2 Oligonucleotides for Gel Shift Experiments (23 KB DOC). Click here for additional data file.

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549631

Isometric force production parameters during normal and experimental low back pain conditions

Background The control of force and its between-trial variability are often taken as critical determinants of motor performance. Subjects performed isometric trunk flexion and extension forces without and with experiment pain to examine if pain yields changes in the control of trunk forces. The objective of this study is to determine if experimental low back pain modifies trunk isometric force production. Methods Ten control subjects participated in this study. They were required to exert 50 and 75% of their isometric maximal trunk flexion and extension torque. In a learning phase preceding the non painful and painful trials, visual and verbal feedbacks were provided. Then, subjects were asked to perform 10 trials without any feedback. Time to peak torque, time to peak torque variability, peak torque variability as well as constant and absolute error in peak torque were calculated. Time to peak and peak dF/dt were computed to determine if the first peak of dF/dt could predict the peak torque achieved. Results Absolute and constant errors were higher in the presence of a painful electrical stimulation. Furthermore, peak torque variability for the higher level of force was increased with in the presence of experimental pain. The linear regressions between peak dF/dt, time to peak dF/dt and peak torque were similar for both conditions. Experimental low back pain yielded increased absolute and constant errors as well as a greater peak torque variability for the higher levels of force. The control strategy, however, remained the same between the non painful and painful condition. Cutaneous pain affects some isometric force production parameters but modifications of motor control strategies are not implemented spontaneously. Conclusions It is hypothesized that adaptation of motor strategies to low back pain is implemented gradually over time. This would enable LBP patients to perform their daily tasks with presumably less pain and more accuracy.

Background There are many possible explanations for the origin and consequences of acute and chronic low back pain but the transition from acute to chronic low back conditions needs to be clarified [ 1 , 2 ]. There is a number of recent evidences suggesting that chronic LBP patients exhibit deficits in proprioception and trunk motor control. For example, changes in postural control[ 3 ], delayed muscle responses to sudden trunk loading[ 4 ], increased trunk movement detection threshold[ 5 ] and increased repositioning errors in patients with LBP have all been reported[ 6 , 7 ]. For example, Oddsson et al.[ 8 ] used spectral parameters of the surface electromyographic (EMG) signal from lumbar back muscles assessed during a fatiguing isometric contraction to classify LBP and healthy subjects. They observed more activation imbalances in chronic LBP subjects and proposed that these changes would eventually become «normal» behavior for the chronic LBP individuals[ 8 , 9 ]. They suggested that changes in the trunk muscular activity could result from subtle postural adjustments that were developed during the acute phase to avoid pain. These observed changes imply a certain level of adaptation to the initial acute pain. Motor control in chronic subjects can be influenced by the presence of chronic pain but also by other phenomenon like type II fiber atrophy, degenerative changes and decreased trunk muscle force and endurance[ 10 ]. Clinical studies of chronic LBP patients involve heterogeneous populations and the effect of chronic pain cannot be differentiated from other degenerative and functional changes occurring in the lumbar spine. Experimentally induced LBP eliminates some of these uncertainties and could allow an examination of the effect of pain per se[ 11 ]. To examine the effect of experimental pain on the sensori-motor control of the lumbar spine, two different protocols have been used in the past: (1) lumbar cutaneous pain induced by electrical or mechanical stimulation[ 11 ] and (2) deep lumbar pain induced by saline injection of lumbar muscles[ 11 , 12 ]. Zedka et al.[ 11 ] noted increased stretch reflex responses in the presence of cutaneous electrical and mechanical stimulations. They also noted an increase in EMG amplitude (during extension) as well as several changes in the motor patterns (trunk velocity and range of motion) in presence of muscle pain induced by a saline injection. Hodges and is colleagues recently demonstrated that feedforward recruitment of trunk muscles is altered in presence of experimental and clinical LBP[ 13 , 14 ]. In a postural task where the subjects were asked to rapidly flex the upper limb, they noted delayed transversus abdominis muscles activation in the presence of experimental pain[ 14 ] or chronic low back pain[ 13 ]. They concluded that some changes in motor control that occur in LBP patients (experimental or chronic) may be caused by pain. These modifications do not resolve spontaneously with alleviation of symptoms since the effect was still observed after a 10-min delay. In a previous study, we have observed that two different control strategies were used by chronic LBP subjects to produce accurate trunk isometric forces[ 15 ]. One subgroup of LBP subjects used an open-loop control strategy similar to that used by healthy control subjects whereas a second subgroup of subjects used a less open-loop control strategy characterized in part by a longer time to peak force. Both LBP subgroups, however, were able to produce isometric trunk forces as accurately as the healthy subjects. The aim of the present study was to evaluate if a painful stimulation, induced by cutaneous electrical stimulation, would spontaneously yield a change in the control strategy or the variability of trunk isometric force production. To explore whether isometric trunk forces are similarly programmed with and without experimental pain, we used the model proposed by Gordon and Ghez[ 16 ]. If motor planning is affected by lumbar cutaneous pain, a more closed-loop mode of control characterized by an increased time-to-peak force and a lack of relationship between the peak of dF/dt and the peak force should be observed. On the other hand, the absence of such a change in the mode of control could yield a more variable force production resulting from sensory and motor effects of pain on the motor response. Methods Force production parameters were measured in 10 healthy subjects with no history of chronic or recurrent LBP (10 men, age: 25.9 years). Each subject gave their written inform consent and the study was approved by the local ethics committee. All subjects were university students. Force data (torque) were obtained from an isometric testing apparatus (Loredan Biomedical, West Sacramento, USA) and recorded at a sampling rate of 500 Hz. Torque data were digitally filtered with a seventh-order dual pass Butterworth filter (7 Hz low pass cut-off frequency). The first time derivative of torque was calculated using a finite difference algorithm (window 25 ms). Superficial pain was elicited by electrical stimulation of the skin over the spinous process of L3 using bipolar surface Ag-AgCl electrodes (Beckman electrodes, 1 cm diameter). This site of stimulation was chosen to ensure that no direct muscular activation could result from the electrical stimulus. The range of voltage used during our experiment was 135–140 Volts. This stimulation created a focal cutaneous painful stimulus with very limited current spread. The technique for inducing the pain stimulation was inspired from the work of Arendt-Nielsen et al.[ 17 ]. Each stimulus consisted of a standard 3-second constant-voltage pulse train of 1-ms pulses delivered at 10 Hz (ISI = 100 ms; S88 Grass stimulator with SIU8T constant voltage isolation unit, USA). The amplitude used for the stimulation was determined when the subjects quoted the pain intensity of the stimulation between 7.5 and 8.5 on a 0–10 scale. The intensity of pain was monitored throughout the experiment and adjusted accordingly to ensure a constant pain level. Testing was done in a neutral standing posture (no trunk flexion or extension). First, maximal isometric flexion and extension torques of trunk muscles were collected. The higher torque value obtained in three consecutive 4-second trials was used as the reference for maximal voluntary contraction. Then, four experimental conditions of trunk torque production were evaluated without and with experimental pain: 50 and 75% of the maximal isometric torque in both extension and flexion. Conditions were presented by block with the order of presentation being randomized across subjects. For each condition, trials without pain were presented first followed by the trials with pain. For each trial, subjects were instructed to produce a trunk isometric force as quickly as possible following an auditory signal. They were encouraged to produce a single impulse ("shoot and release") and to make no attempt at correcting the force once the contraction was initiated. For each condition, a learning phase was provided. During this phase, after each trial, subjects were given visual accuracy feedback through an oscilloscope located in front of them. Subjects were specifically asked to produce peak torques that were within 10% of the goal target. This learning phase stopped when five consecutive contractions were within the 10% margin. Following these learning trials, subjects performed 10 consecutive trials without any visual feedback. The pain condition followed. A second learning sequence with feedbacks and without pain was given to the subjects. This procedure was used to insure that no differences between the control and pain conditions would reflect a pain effect and not a loss of calibration after a block of trials without pain. Hence, if any differences between the control and pain conditions were found, these would reflect a pain effect and not a learning effect. For the pain trials, the stimulation was initiated 0.5 sec before an auditory tone indicating the subjects to initiate the contraction. All dependent variables were derived from the behavior observed for the 10 trials without feedback without and with the experimental pain. For each experimental trial, the onset of torque and peak torque were determined. Using this information, time to peak torque, time to peak torque variability, peak torque variability as well as the constant and absolute error in peak torque were calculated for each condition. Constant error represents the positive or negative difference between the peak torque reached and the target torque. Absolute error in peak torque represents the positive difference between the reached peak torque and the goal peak torque whereas time to peak represents the period of time between the beginning of rising torque and the maximal torque obtained in the trial. Peak dF/dt was also computed to examine if the first peak of dF/dt could predict the peak torque achieved. Linear regressions were calculated for each subject and a high r 2 , indicating that the first peak of dF/dt could predict the peak torque, was taken as an indication of a preprogrammed or open-loop mode of control[ 16 ]. Results On average, the maximal voluntary contraction in flexion and extension were 236.2 Nm and 346.5 Nm, respectively. Table 1 presents a summary of the statistical analyses for all dependant variables. The ANOVA for absolute errors yielded a main effect of Pain. Absolute errors were higher in the painful condition than in the normal condition (30.7 Nm vs 23.9 Nm respectively; F1-9 = 8.29, p = 0.018). The main effects of Direction, Force level and all interactions were not significant (ps > 0.05). Similar observations were made for the constant errors as the ANOVA yielded a main effect of Pain (F1-9 = 6.22, p = 0.035). The main effects of Direction, Force level and all interactions also were not significant (ps > 0.05). The painful stimulus yielded increased constant and absolute errors indicating that subjects, on average, overshot the target by 25.9 Nm (13.9 Nm for the normal condition). Table 1 Statistical analyses for all dependant variables. Pain (P) Direction (D) Force Level (F) P × D D × F P × F Time to peak force F = 0.017 p = 0.901 F = 1.094 p = 0.323 F = 0.541 p = 0.481 F = 1.011 p = 0.341 F = 2.009 p = 0.190 F = 2.628 p = 0.139 Time to peak force variability F = 8.763 p = 0.016* F = 0.083 p = 0.779 F = 0.005 p = 0.943 F = 0.115 p = 0.742 F = 3.904 p = 0.080 F = 0.028 p = 0.870 Peak force variability F = 7.756 p = 0.021* F = 1.183 p = 0.209 F = 0.487 p = 0.503 F = 0.032 p = 0.861 F = 0.096 p = 0.764 F = 8.047 p = 0.020* Constant error F = 6.222 p = 0.034* F = 0.530 p = 0.485 F = 5.02 p = 0.052 F = 5.018 p = 0.053 F = 0.273 p = 0.614 F = 0.027 p = 0.873 Absolute error F = 8.289 p = 0.018* F = 1.1 p = 0.482 F = 0.537 p = 0.482 F = 0.909 p = 0.365 F = 2.222 p = 0.170 F = 1.158 p = 0.310 *p < 0.05 Figure 1 illustrates, for one subject, the mean and variability of ten consecutive flexion trials (50% of maximal flexion torque) without and with pain. With pain, the torque-time curves exhibit greater variability around the peak. Figure 1 Typical torque-time curves illustrating the mean (SD is represented by the dashed line) of ten consecutive flexion trials (without feedback) in the control condition. (b) Typical torque-time curves illustrating the mean (SD is represented by the dashed line) of ten consecutive flexion trials (without feedback) in the experimental pain condition. Figure 2 illustrates peak torque variability with and without experimental pain for both levels of force. The ANOVA for peak torque variability showed a significant main effect of Pain (F 1,9 = 7.76, p = 0.021) and an interaction of Pain × Force (F 1,9 = 8.05, p = 0.020) but no main effect of Force (ps > 0.05). A decomposition of the interaction showed that peak torque variability increased with the painful stimulation only for the higher level of force. For the higher level of force, the variability was 12.6 Nm in the control condition and 18.6 Nm in the presence of electrical stimulation (Tukey: p = 0.027). For the lower level of force, peak torque variability was similar for both conditions (15.0 Nm; p > 0.05). Figure 2 Mean (SD) peak torque variability with and without electrical stimulation for both levels of force. The average time to peak torque was not affected by the lumbar electrical stimulation. On average, the time to peak torque was 240 ms. The main effects of Pain, Direction, Force level and all interactions were not significant ( p s > 0.05). The time to peak torque variability, however, was increased in the painful condition than in the normal condition (81 ms vs 58 ms respectively; F1-9 = 8.76, p = 0.016). Again, the main effects of Direction, Force level and all interactions were not significant (ps > 0.05). The dF/dt curves for both conditions are characterized by a single peak in the first phase of isometric force production. On average, peak dF/dt explained 73.5 and 74.3 percent of the variance observed in peak torque for the normal and the painful conditions, respectively (p > 0.05). This suggests a similar control strategy for both the normal and the painful conditions. Discussion The presence of an experimental cutaneous lumbar pain altered the production of isometric trunk forces in various ways. Specifically, when exposed to the painful cutaneous electrical stimulation, subjects showed greater absolute and constant errors in isometric trunk torque production. The effects of a lumbar cutaneous painful stimulation on the isometric trunk force production yielded an overestimation of the learned level of force to be performed in both flexion and extension. This observation argues against a specific modification of the trunk flexor or extensor motoneuronal pool following the painful stimulation. Rather it appears that, independently of the direction of the force production required, the pain stimulation yielded an increased excitability of the agonist motor pathways. Our results, however, cannot discriminate if these modifications occurred at the programming stage or at the execution stage (upper and lower motorneurons). All of these mechanisms have previously been suggested to explain the modifications induced by experimental pain[ 11 , 14 , 18 ]. Across the painful trials, subjects also showed greater torque variability for the higher level of forces. Time to peak torque variability was also greater with than without pain. Linear regressions between peak dF/dt and peak torque however, were similar in both conditions indicating that the subjects used a similar strategy force control strategy without and with pain. In a previous study, chronic low back pain patients demonstrated longer time to peak values suggesting a shift from an open loop strategy of control to a more close loop strategy of control[ 15 ]. Results of the present experiment suggest that, in the presence of experimental cutaneous pain, subjects maintained an open loop control strategy to perform the task. Such an absence of modification in the control strategy could be specifically related to the task used in the present experiment. Subjects were explicitly told to perform the isometric force production as quickly and accurately as possible. Numerous authors have showed that chronic LBP patients exhibit deficits in proprioception and trunk motor control [ 3 - 7 ]. The link between persistent pain and subsequent adaptations to low back symptoms remains unclear although some hypotheses have been formulated. Lund et al. first proposed a pain adaptation model that could occur in the presence of persistent pain[ 19 ]. This adaptation is characterized by an increased motoneuron output when the muscle is acting as an antagonist and by a decreased motoneuron output when the muscle is acting as an agonist. Luoto et al., throughout a series of study, have shown that motor control deficits observed in chronic LBP subjects can be, at least in part, due to impairment in central processing. According to the authors, pain would consist of an irrelevant sensory input that cannot be ignored but that is hampering central processing[ 20 , 21 ]. Even though pain probably causes peripheral adaptations, central impairment must also be considered. Oddsson and his colleagues[ 9 ] suggested that chronic low back patients, for whom acute pain reactions are no longer present, could develop a new strategy (postural adjustments) to avoid the sensation of pain. Although experimentally induced pain is different from clinical pain, some authors reported motor changes similar to those observed in LBP patients when inducing experimental pain in control subjects[ 14 ]. Hodges et al. observed that experimental and recurrent low back pain induced similar delays in transversus abdominis activation[ 4 , 13 , 14 ]. Zedka et al[ 11 ] observed a decrease in velocity and range of trunk motion after saline injection of lumbar muscles similar to those observed in patients with low back pain. They also demonstrated an increased excitability in the long latency lumbar response after a painful cutaneous electrical stimulation. These changes were attributed to the interactions between nociceptives afferents and motor neuron pool excitability[ 17 ]. Overall, it appears that both clinical and experimental low back pain can influence trunk muscle activations suggesting that the sole presence of pain is detrimental to motor performance. The painful stimulus used in the present experiment consisted of trains of 1 ms electrical pulses applied to the spinous process of the third lumbar vertebra. Although the experimenter could not observe nor palpate any muscular contractions and the subjects did not report any involuntary muscular contractions, the possibility exists that spreading of the current over the surrounding tissues activated the neuromuscular junction of the nearby lumbar paraspinal muscles. Consequently, imperceptible muscular contractions could have occurred, particularly at the high level of Voltage used to elicit the perception of pain in our subjects. Muscular activation of the paraspinal muscles due to the current spreading while performing an isometric force reproduction task could certainly lead to a deterioration of the subjects' performance (both the accuracy and variability) under the experimental pain condition. However, the overestimation of the learned level of force was observed in both flexion and extension – whereas the painful stimulation was always applied to the spinous process (presumably biasing only the paraspinal muscles) – argues against this factor playing a critical role in the findings reported in the present manuscript. Further work, however, is needed to quantify the performance of healthy subjects performing an isometric force reproduction task using a different experimental pain protocol (e.g. muscle saline injection). In a previous study, we observed that some chronic LBP patients, compared to healthy control subjects, adopted a more close loop control strategy of trunk isometric force production to maintain a particular level of performance[ 15 ]. Both experiments used a similar protocol of isometric force production but the present results failed to reveal any changes in the control strategy adopted by the subjects. On the other hand, in the presence of experimental cutaneous pain, a less accurate isometric force production was observed. Therefore our results suggest that, even if some modifications occurred directly in the presence of pain[ 11 , 14 ], adaptation to low back pain and modifications of motor control strategies are not implemented spontaneously. It seems that the modification in control strategy observed for chronic LBP subjects could be an adaptation to limit the variability of force production. For control subjects, the "rise time regulation" strategy or variations thereof have been suggested to help in reducing response variability[ 16 , 22 , 23 ]. Also, it has been suggested that, in the presence of persistent experimental or chronic low back pain, subjects need to adapt their motor control strategies in order to limit exacerbation of pain symptoms[ 9 , 19 ]. Whether chronic LBP subjects adopt a new control strategy to limit their pain symptoms or to minimize their force production errors remains to be determined. Conclusion The present data indicate that trunk isometric force production can be affected by experimental cutaneous low back pain. While the motor control strategy remained the same between the non painful and painful condition, subjects showed less accuracy and more variability in the painful condition. Experimental cutaneous low back pain is different from deep tissue pain and the observed changes. This precludes any generalization to acute low back pain. It is hypothesized, however, that adaptation of motor strategies to low back pain is implemented gradually over time. This would enable LBP patients to perform their daily tasks with presumably less pain and more accuracy. Competing interests The author(s) declare that they have no competing interests. Authors' contributions MD and JS performed all the testing and data analyses. NT acted as the thesis director of MD and JS and participated in the design and coordination of the study. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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555581

Discovery of adult T-cell leukemia

Adult T-cell leukemia (ATL) was first reported as a distinct clinical entity in 1977 in Japan. The predominant physical findings are skin lesions, lymphadenopathy and hepatosplenomegaly. The ATL cells are of mature T-helper phenotype and have a characteristic appearance with indented nuclei. There is striking frequent hypercalcemia with increased numbers of osteoclasts. Central to the identification of the disease is a striking geographic clustering in southwestern Japan and the isolation of human T-cell lymphotropic virus type-1 (HTLV-1) from the cell lines of patients. Worldwide epidemiological studies have been made through international collaborations. Several diseases were found to be related to HTLV-1 infection. Moreover, it was noted that an immunodeficiency state may be induced by HTLV-1 infection. In Japan, HTLV-1 carriers have been estimated to be 1.2 million, and more than 700 cases of ATL have been diagnosed each year.

Adult T-cell leukemia (ATL) was described as a distinct clinical entity in 1977 in Kyoto, Japan [ 1 , 2 ]. The illness is manifested by presentation in adult life: frequent skin lesions, lymphadenopathy, hepatosplenomegaly, and elevated white blood cell count with abnormal lymphoid cells. The abnormal ATL cells are of mature T-helper phenotype and have a characteristic appearance with especially indented or lobulated nuclei. There is strikingly frequent hypercalcemia with increased numbers of osteoclasts. Central to the identification of the syndrome is the striking geographic clustering in southwestern Japan and the isolation of the human T-cell lymphotropic virus type-1 (HTLV-1) from the cell lines of patients with ATL. Background of our ATL study It was around the 1973 that we came to recognize the existence of ATL, previously an unknown disease. I would like to give a retrospective view concerning the background of our studies on ATL. Many clinicians in Japan probably feel that the descriptions of diseases in the literature from abroad differ from the features of the diseases observed in their practices in Japan. We can mention many examples in the field of hematology. One of these is that the incidence of chronic lymphocytic leukemia is quite low, being only 2% of all hematological malignancies. What differs is not only the incidence but also the detailed symptoms and signs of diseases. This vague feeling that an autochthonous pathology exists in Japan may be considered as key factor in the background of our study of ATL. The second major factor is the recent progress made in basic immunology. Having an interest in immunoglobulin abnormalities, I studied multiple myeloma and related diseases in the days when even the word 'immunoglobulin' was not yet in use. The central theme of immunology at that time was to identify the structure of antibodies. Immunology has advanced rapidly, and myeloma was defined as a B-cell malignancy. Therefore, it was quite natural to enlarge the objectives of our clinical studies to all lymphoproliferative diseases. At this stage of our research in Kyoto, joint studies with young researchers were initiated. This was the third and most important element of the background of our ATL study. I became acquainted with Drs. Takashi Uchiyama and Junji Yodoi, who are currently both working in Kyoto, during their postgraduate training. Dr. Yodoi prepared an antiserum against human thymocytes and invited us to direct our attention to T-cells. In the course of examining patients with various lymphoproliferative disorders, we arrived at the conclusion that ATL was a disease which had not been described anywhere before. It was recognized that T-cell malignancy had a relatively high incidence among Japanese adults and that most of the patients with this disease were from Kyushu. This discovery was made from our bedside observations rather than from laboratory work. Thereafter, Dr. Uchiyama went to the National Cancer Institute, Bethesda to work with Dr. Thomas A. Waldmann and raised a monoclonal antibody, called 'Tac' antibody, which later played an important role in our ATL studies. Dr. Yodoi has developed a new field of research by identifying a novel cytokine, ATL-derived factor (ADF), which has proved to be important in redox regulation. At the end of 1981, I moved from Kyoto to Kumamoto, which is located in the middle of Kyushu. Our studies advanced remarkably there, due mainly to the efforts of excellent young co-workers including Drs. Kazunari Yamaguchi, Toshio Hattori, and Masao Matsuoka, who are now independently working in Tokyo, Sendai and Kyoto, respectively. Development of virology This discovery of ATL ushered in some dramatic developments in oncology, virology and, unexpectedly, neurology and other fields of medicine. When we reported a series of 13 patients with ATL in 1976 on the occasion of the 16 th International Congress of Hematology in Kyoto, it was stated that 'attempt to elucidate leukemogenesis in this disease should be directed towards exploring the genetic background and a possible viral involvement'. HTLV (human T-cell leukemia virus), the pathogen of ATL, was first reported by Dr. Robert C. Gallo and his co-workers in Bethesda in 1980 and 1981. They isolated HTLV from cultured cells taken from a patient with an aggressive variant of mycosis fungoides and another with Sezary syndrome. Although both patients were said to have cutaneous T-cell lymphoma, they had some unusual features which, in retrospect, linked them to the clinical entity now called ATL. In Japan, co-culturing of ATL cells with umbilical cord lymphocytes was first done successfully by Dr. Isao Miyoshi's group in Okayama, who obtained the cell line MT-1. Dr. Yorio Hinuma and his co-workers in Kyoto demonstrated that ATL patients have antibodies against presumed viral antigens on MT-1 cells by indirect immunofluorescence method. Subsequently, a retrovirus was isolated and called ATLV (adult T-cell leukemia virus). Since Dr. Mitsuaki Yoshida and his group in Tokyo showed that HTLV and ATLV are, in fact, identical, the term HTLV-1 (human T-cell lymphotropic virus type 1) has been commonly used. Furthermore, the following observations have been successively reported to support the etiologic association of HTLV-1. 1. All patients with ATL have antibodies against HTLV-1. 2. The areas of high incidence of ATL patients correspond closely with those of high incidence of HTLV-1 carriers. 3. HTLV-1 immortalizes human T cells in vitro . 4. Monoclonal integration of HTLV-1 proviral DNA was demonstrated in ATL cells. Thus, HTLV-1 is the first retrovirus directly associated with human malignancy. Diagnosis and classification of ATL The diagnostic criteria for HTLV-1 associated ATL have been defined as follows: 1. Presence of morphologically proven lymphoid malignancy with T-cell surface antigens (These abnormal T lymphocytes include typical ATL cells and the small and mature T lymphocytes with incised or lobulated nuclei that are characteristic of chronic or smoldering type). 2. Presence of antibodies to HTLV-1 in the sera. 3. Demonstration of monoclonal integration of HTLV-1 provirus by Southern blot method. Virological study led us to classify the patients with ATL into four clinical subtypes according to the clinical features: acute, chronic, smoldering, and lymphoma. The acute type is the prototypic ATL in which patients exhibit increased number of ATL cells, frequent skin lesions, systemic lymphadenopathy, and hepatosplenomegaly. Most of these patients are resistant to chemotherapy and have a poor prognosis. In chronic ATL, white blood cell count is mildly increased, and skin lesions, lymphadenopathy, and hepatosplenomegaly are sometimes exhibited. In the past, chronic ATL was thought to be 'chronic T-lymphocytic leukemia'. Smoldering ATL is characterized by the presence of a few ATL cells in the peripheral blood over a period of years. Frequent symptoms are skin or pulmonary lesions. Chronic and smoldering ATL often progress to acute ATL after a long period (crisis). Lymphoma-type ATL is characterized by prominent systemic lymphadenopathy, with few abnormal cells in the peripheral blood. This type has been diagnosed as nonleukemic malignant lymphoma. Later, the Lymphoma Study Group in Japan proposed a practical diagnostic criteria for classifying ATL into these four subtypes. Epidemiology of ATL and HTLV-1 HTLV-1 is endemic in southwestern Japan, especially Kyushu and Okinawa, in the Caribbean Islands, and in Central Africa. It has been revealed that there are HTLV-1 carriers in South America, Papua New Guinea, the Solomon Islands, South China, and other isolated populations in the world, including Ainus in Hokkaido and Aborigines in Australia. These epidemiological studies have been promoted by international collaborations, to which Drs. William A. Blattner in Bethesda, Guy de The in Paris, Kazuo Tajima in Nagoya, Shunro Sonoda in Kagoshima, and many other epidemiologists have made important contributions. Dr. Daniel Catovsky and his colleagues in London delineated the clinical features of ATL patients originating in the Caribbean islands. HTLV-1 related diseases On the other hand, several diseases have been found to be related to HTLV-1 infection. Drs. Antoinne Gessain and Guy de The first reported the association of tropical spastic paraparesis (TSP) and HTLV-1, and Dr. Mitsuhiro Osame and his co-workers in Kagoshima studied features of HTLV-1-associated myelopathy (HAM/TSP) in detail. HTLV-1 uveitis was subsequently described by a study group of ophthalmologists in Kyushu. HTLV-1 may also be associated with bronchopneumonitis, arthritis, polymyositis and other inflammatory conditions. Moreover, it was noted that an immunodeficiency state may be induced by HTLV-1 infection. Prevention and treatment In Japan, HTLV-1 carriers have been estimated to be 1.2 million, and more than 700 cases of ATL have been diagnosed each year. Majority of HTLV-1 transmission occurs via one of three routes, all of which require the passage of virus-infected cells. HTLV-1 carrier mothers transmit the virus to newborns mainly through breast milk. Dr. Shigeo Hino and his group in Nagasaki conducted intensive fieldwork regarding the mother-to-infant infection. Carrier mothers in Japan have been instructed to refrain from breastfeeding or modify the feeding procedures to prevent HTLV-1 infection. There is convincing evidence that HTLV-1 can be transmitted from individual to individual by sexual contact, especially males to females, and also through blood transfusions. All blood donated at the Red Cross Blood Centers in Japan has been subjected to HTLV-1 antibody testing beginning in November 1986. Treatment of ATL is the most difficult task. Dr. Masanori Shimoyama in Tokyo has organized a multicenter study group for the chemotherapy of ATL. Many other trials have been reported: deoxycoformycin, α-interferon combined with azidothymidine, and so on. The use of humanized monoclonal antibodies against the interleukin-2 receptor has been championed by Dr. Waldmann's group. More recently, successful allogeneic bone marrow transplantation for patients with ATL has been reported from many institutions. Addendum Before my retirement from Kumamoto University in 1996, I edited a book titled "Adult T-cell Leukaemia" [ 3 ]. Many of the above-mentioned investigators contributed chapters to this book. I also would like to add that Dr. Matsuoka and I wrote a chapter on ATL in a textbook of leukemia [ 4 ]. It may be pertinent here to commemorate the establishment of the International Retrovirology Association, which was announced on the occasion of the 5 th International Conference of Human Retrovirology held in Kumamoto on May 11–13, 1992. A companion article by Robert C. Gallo recollects the events surrounding the discovery of the first human retrovirus, HTLV-I [ 5 ].

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548507

Host genotype by parasite genotype interactions underlying the resistance of anopheline mosquitoes to Plasmodium falciparum

Background Most studies on the resistance of mosquitoes to their malaria parasites focus on the response of a mosquito line or colony against a single parasite genotype. In natural situations, however, it may be expected that mosquito-malaria relationships are based, as are many other host-parasite systems, on host genotype by parasite genotype interactions. In such systems, certain hosts are resistant to one subset of the parasite's genotypes, while other hosts are resistant to a different subset. Methods To test for genotype by genotype interactions between malaria parasites and their anopheline vectors, different genetic backgrounds (families consisting of the F1 offspring of individual females) of the major African vector Anopheles gambiae were challenged with several isolates of the human malaria parasite Plasmodium falciparum (obtained from naturally infected children in Kenya). Results Averaged across all parasites, the proportion of infected mosquitoes and the number of oocysts found in their midguts were similar in all mosquito families. Both indices of resistance, however, differed considerably among isolates of the parasite. In particular, no mosquito family was most resistant to all parasites, and no parasite isolate was most infectious to all mosquitoes. Conclusions These results suggest that the level of mosquito resistance depends on the interaction between its own and the parasite's genotype. This finding thus emphasizes the need to take into account the range of genetic diversity exhibited by mosquito and malaria field populations in ideas and studies concerning the control of malaria.

Background In the last few years, exciting advances in the biology and molecular genetics of the development of Plasmodium parasites in their mosquito vectors [ 1 , 2 ] have led to the creation of transgenic mosquitoes that are partially resistant to malaria infection [ 3 ], bringing the efforts to control malaria with the techniques of transgenesis a major step forward [ 4 , 5 ]. A crucial aspect of these advances is, of course, the fact that the mosquito's genetic make-up determines, at least partly, its resistance to malaria infection [ 6 , 7 ], giving hope for the possibility that key genes controlling resistance may be identified. This hope has been reinforced by the recent identification, in a rodent model of malaria, of several mosquito immune genes that affect parasite development [ 8 , 9 ]. Unfortunately, several aspects of the current knowledge make it difficult to estimate the relevance of such laboratory-based studies to control malaria in natural conditions [ 10 ]. One of the crucial aspects is that most studies on the genetics of resistance have considered the response of a mosquito line or colony to a single malaria genotype, while any malaria control programme based on the release of resistant mosquitoes in highly endemic areas can be effective only if mosquitoes are resistant to all the genotypes of the parasite [ 11 ]. Because of the limited genetic variation in laboratory colonies compared to natural populations of mosquitoes [ 12 ] and the large diversity of natural populations of malaria parasites [ 13 ], it is currently far from clear whether this will be possible. One potential problem of the genetic diversity in natural populations could be that, as in many other host-parasite systems (e.g. plant-fungus [ 14 ], snail-schistosome [ 15 ], bumble-bee-trypanosome [ 16 ], Daphnia -bacterium [ 17 ]), the outcome of the interaction is determined by an interaction between host and parasite genotypes. In systems governed by such genotype by genotype interactions, individual hosts are resistant to only a portion of the parasite genotypes and, reciprocally, individual parasites can infect only particular host genotypes [ 18 ]. In other words, no parasite is best at infecting all hosts, and no host is best at resisting all parasites, so that the success of infection depends on the specific combination of the two opponents. Despite its potentially important role for malaria epidemiology and control, such a genetic specificity of host-parasite compatibility between malaria parasites and their insect vectors have never been investigated. This study examines the potential for genotype by genotype interactions in the combination that is most important for the epidemiology of malaria – Plasmodium falciparum and Anopheles gambiae . Malaria genotype by mosquito genotype interactions were tested with a standard procedure of quantitative genetics from measurements of the resistance of different genetic backgrounds of the mosquito A. gambiae , a major malaria vector in sub-Saharan Africa, to different isolates of the human malaria parasite P. falciparum . The parasite isolates were obtained from naturally infected children in western Kenya that harboured gametocytes, the infective stage of the parasite. The genetic backgrounds of mosquitoes were 'mosquito families' generated as the F1 offspring of single egg-laying females. Each mosquito family was challenged with each parasite isolate, and all mosquitoes were simultaneously fed on the blood of the gametocyte carriers via membrane-feeding. This basic design was repeated three times throughout three successive experimental blocks that involved different families and isolates, giving a total of 18 mosquito families, 11 parasite isolates, and 62 specific interactions. As in previous studies [ 7 ], the resistance of mosquitoes was quantified with the proportion of blood-fed females that developed oocysts and with the number of oocysts. The genotype by genotype interaction on mosquito resistance was estimated according to standard quantitative genetic methods as the interaction effect in a statistical analysis between the parasite isolate and the mosquito family [ 17 , 19 ]. These methods are based on the idea that sibs are genetically more similar that non-sibs. Therefore, partitioning the variance of any trait (e.g. number of oocysts) among families (individuals sharing a mother) and within groups of sibs give an indication of the extent to which the trait has a genetic basis [ 20 ]. Methods Mosquitoes The mosquitoes used in this study came from a colony that had been established in 2001 from A. gambiae s.s . caught in the area surrounding Mbita, a small village on the shore of Lake Victoria in Suba District (western Kenya). These mosquitoes had been initially adapted to feed on a Parafilm ® membrane, and then maintained in standard insectary conditions using a rabbit as a blood source for routine maintenance. Females of the colony were blood-fed on a rabbit and allowed to lay eggs in individual vials. Immediately after hatching, each larva was individually placed in one well of a 12-well plate with three mL of filtered lake water. They were fed daily on a standard diet of Tetramin ® fish food (0.06 mg per larva on day 0; 0.12 mg on day 1; 0.24 mg on day 2; 0.36 mg on day 3; 0.48 mg on day 4; 0.6 mg on the following days). Adults were kept in an insectary and supplied with a 6% glucose solution and cotton soaked with distilled water. The temperature and humidity in the insectary followed the daily environmental fluctuations. So that mosquito age at pupation did not affect the success of infection, only females that pupated seven days after hatching were used. The wing length of the mosquitoes, measured from the tip (excluding the fringe) to the distal end of the allula with a precision of 0.02 mm, was used as an indication of body size [ 21 ]. Where both wings could be measured, the mean of the two lengths was used. Gametocyte carriers P. falciparum carriers were recruited from the two- to 10-year old children in the rural area around Mbita, from December 2003 to January 2004. Finger-prick blood samples were collected and thick blood smears were air-dried, stained with 8% Giemsa during 15 minutes, and examined microscopically for the presence of P. falciparum . Children with asexual parasitemia (>1,000 parasites/μL) were immediately treated with sulfadoxine-pyrimethamine according to national guidelines. Asymptomatic gametocyte-positive children were recruited for the study after their parents or guardians had signed an informed consent form. The Kenyan and the United States National Institute of Health ethical review committees approved this recruitment procedure. Experimental infections For logistic reasons, the experiment was repeated three times, and within each experimental block infections were done simultaneously. For each of the three blocks, P. falciparum isolates were collected from gametocyte carriers that had been identified one or two days before, and used to feed the mosquitoes on the same single day (block 1: December 14, 2003; block 2: January 23, 2004; block 3: January 28, 2004). The gametocyte densities were assessed just before blood withdrawal on a blood smear (as described above) by counting against 500 leukocytes, and converted to numbers of parasites per μL by assuming a standard leukocyte count of 8,000/μL. Although gametocyte densities in the venous blood and the peripheral finger-prick blood might differ, potential differences were assumed to be proportional among the isolates. A sample of five mL of venous blood was collected from each gametocyte carrier in a heparinized tube, 400 μL of which were stored at -20°C for further parasite genotyping. So that the importance of human factors such as transmission-blocking immunity [ 22 ] was reduced, the blood was centrifuged at 37°C for three minutes at 2,000 g and the autologous serum was replaced with the same volume of a pool of AB serum from two French blood donors without any malaria exposure (the same pool of AB serum was used for all experimental blocks). The mixture was used to feed mosquitoes, which had been starved for 12–16 h before blood feeding, with a standard membrane-feeding system [ 23 ]. For each mosquito family, i.e. each group of mosquitoes that was derived from the eggs of a single female, equal groups of three-day old females were randomly chosen and fed separately with each isolate. Depending on the size of the family, each feeding cage contained between four and 15 females. Mosquitoes were allowed to take a blood meal for 40 minutes, after which unfed and partially fed mosquitoes were discarded. Seven or eight days after the infective blood meal, mosquitoes were dissected and their midguts were stained with 2% mercurochrome in distilled water in order to detect the presence and number of oocysts by light microscopy. Microsatellite genotyping P. falciparum DNA was extracted from the blood samples using the QIAamp DNA blood kit following the manufacturer's instructions (Qiagen, CA). The isolates were typed using the semi-nested PCR method slightly modified from a previous study [ 24 ] (details are available upon request to PD) and the markers used [ 25 ] and their GenBank accession number in parenthesis are as follows: PJ2 (G37826), UIDG (G37823), Polyα (L18785), TA60 (AF010556), ARA2 (G37848), Pfg377 (L04161), PfPK2 (X63648), TA87 (AF010571), TA109 (AF010508). The microsatellite PCR products were size-genotyped using a standard size Genescan 500 LIZ on an ABI Prism 310 Genetic Analyser (PE Applied Biosystems, CA). Data analysis Only those mosquito families in which at least four individuals had been fully fed and had survived infection with each isolate were included in the analyses. The likelihood that a mosquito had been infected was analysed with a nominal logistic analysis. The intensity of infection was analysed with an analysis of variance (ANOVA). In this analysis, the square root of the number of oocysts was used, so that the assumptions of the statistical tests (in particular, normality of the residuals) were satisified. As the study was run in three successive experimental blocks, both analyses included the effect of block, and the effects of family, isolate and their interaction. The effect of wing length was also included as a potential confounder [ 26 ]. As different families and isolates were used in each experimental block, the factors family, isolate and their interaction were nested within block. Block, family and isolate were considered as random factors. Results The three successive experimental blocks involved three, five and three parasite isolates, and nine, four and five mosquito families, respectively. A third (151) of the 455 mosquitoes of the study were infected by P. falciparum oocysts, and the number of oocysts in infected mosquitoes ranged from one to 97 (mean 11.0, median 3). The prevalence and the number of oocysts differed among blocks (block effect, Table 1 ), and were lower in larger mosquitoes (wing length effect, Table 1 ). Table 1 Statistical analysis of the effects of mosquito family and parasite isolate on the success of infection. The proportion of infected mosquitoes (a, nominal logistic analysis) and the square root of the number of oocysts (b, ANOVA) were analysed as a function of the mosquito family, the parasite isolate, and their interaction. In both analyses, the mosquito's wing length was included as a confounder. As the study was run in three experimental blocks using different families and isolates, the factors family, isolate and their interaction were nested within block. Block, family and isolate were considered as random factors. (a) Proportion infected (b) Intensity of infection Source d.f. χ 2 P Sum of Squares F P Experimental Block 2 85.5 <0.001 265.2 2.40 0.155 Wing Length 1 3.1 0.029 6.4 7.14 0.008 Family (within Block) 14 3.8 0.927 29.5 0.66 0.800 Isolate (within Block) 8 15.5 0.482 462.5 19.40 <0.001 Family*Isolate (within Block) 34 127.2 <0.001 110.2 3.59 <0.001 Error (for analysis b) 395 356.8 Family by isolate interaction While the crude variation among families (averaged across all parasite isolates) was substantial (mean infection rate ranging from four to 83%; mean number of oocysts ranging from 0.1 to 16.4), most of this variation was due to differences among blocks (Fig. 1 ), so that there was no evidence that families differed in the overall proportion of infected individuals or in the intensity of infection (family effect, Table 1 ). Similarly, most of the crude differences among isolates (averaged across mosquito families) were due to differences among blocks. Thus, isolates did not vary in the proportion of mosquitoes they infected (ranging from four to 94%), although they did vary in the number of oocysts they produced (median ranging from zero to 35) (isolate effect, Table 1 ). More importantly in the context of our study, while neither the families of mosquitoes nor the parasites differed in their average responses to all of their partners, the interaction between mosquito family and parasite isolate (an estimation of the genotype by genotype interaction) had a highly significant effect on the likelihood and the intensity of infection (family by isolate effect, Table 1 ). Thus, no parasite isolate was most infectious to every host genotype. Rather, isolates that were most infectious on one host tended to be less infectious than the other isolates on other hosts (Fig. 1 ). Similarly no host genotype was most resistant to every parasite isolate (Fig. 1 ). Figure 1 Graphic representation of the mosquito family by parasite isolate interactions underlying (a) the probability and (b) the intensity of infection . Each point represents the proportion of infected mosquitoes (in a) or the mean of the square root of the number of oocysts (in b) for a given combination of family and isolate. The families are indicated on the x-axes, and are separated into the three experimental blocks of the study with vertical lines. Different colours represent different isolates (squares: isolates containing two clones; circles: isolates containing three clones), and the lines connect points representing the same isolate. Crossing lines give an indication of family by isolate interactions. Genetic characterization of P. falciparum isolates While the quantitative genetic analysis of the data gives an adequate representation of the genetic basis of the mosquito's resistance [ 20 ], the use of natural isolates may complicate the interpretation, as (i) they do not necessarily consist of different malaria clones and (ii) isolates often contain several clones in areas where transmission is high [ 27 , 28 ]. However, genotyping the blood samples at nine microsatellite markers showed that the isolates differed. The overall genetic diversity was high, ranging from four to 15 allelic variants per locus. Each isolate had an allelic pattern that differed from all other isolates at, at least, one locus (data not shown), showing that the isolates were genetically distinct. Using the maximum number of alleles at a single locus as a conservative estimate of the number of clones, each isolate was found to contain either two or three distinct clones of P. falciparum (Table 2 ). Table 2 Description of P. falciparum isolates. The number of gametocytes per 500 leukocytes, converted to numbers of parasites per μL (assuming a standard leukocyte count of 8,000/μL) and the maximum number of alleles at a single locus found for 9 microsatellite markers (a conservative estimate of the number of clones) are given for each isolate. Experimental block Isolate Gametocyte density (parasites/μL) Number of clones 1 A 176 3 1 B 32 3 1 C 32 2 2 D 32 3 2 E 16 2 2 F 16 3 2 G 32 3 2 H 32 2 3 I 48 2 3 J 16 2 3 K 16 3 Potential confounding effects Separate analyses of the data for the two numbers of clones (two or three) ensured that the number of clones contained in each isolate did not confound the interpretation. The effect of the mosquito family by parasite isolate interaction on the likelihood of infection was significant in both cases (two clones: P = 0.050; three clones: P = 0.003) and the effect of the interaction on the number of oocysts was significant in one of the cases and showed a tendency in the other case (two clones: P = 0.219; three clones: P = 0.008). In addition, differences in gametocyte density between isolates (Table 2 ) may be expected to bias infection success [ 23 ]. There were sufficient data to analyse the effects of the mosquito family by parasite isolate interaction separately for the isolates with 16 or 32 gametocytes/μL (i.e. one or two gametocytes per 500 leukocytes). At both gametocyte densities, the interaction significantly influenced the probability of infection (16 gametocytes/μL: P < 0.001; 32 gametocytes/μL: P < 0.001) and the number of oocysts (16 gametocytes/μL: P < 0.001; 32 gametocytes/μL: P < 0.001). In conclusion, the two potential confounders – number of clones per isolate and gametocyte density – had no qualitative influence on the results of the analysis. Discussion While the specificity of mosquito-malaria interactions at the species level is well documented [ 29 ], the present results are the first experimental evidence of the genetic specificity of mosquito infection by malaria parasites at the intraspecific level. This finding corroborates an earlier study, where a mosquito line selected for resistance to malaria infection varied considerably in its response against different Plasmodium species and strains [ 6 ]. The present study goes one step further by suggesting that mosquito resistance to malaria is at least partly determined by the specific interaction between its own and the parasite's genotype. This idea is supported by two other studies showing that, in a strain of mosquitoes selected to resist infection by a wide variety of malaria species, different genetic loci are involved in the responses against different Plasmodium parasites [ 30 , 31 ]. The present study suggests, moreover, that the genes conferring resistance to a particular parasite depend on the genetic background of the mosquito. The specificity of host-parasite interactions is often postulated to occur at the level of parasite recognition. While the molecular mechanisms of Plasmodium recognition by mosquitoes are still largely unknown, a group of thioester-containing proteins (TEPs) represents a promising family of candidate recognition molecules. One of them, the complement-like protein TEP1, has recently been shown to bind to and mediate the killing of the rodent malaria parasite P. berghei by the mosquito A. gambiae [ 9 ]. Moreover, two allelic variants of the TEP1 gene are associated to susceptible and refractory strains of A. gambiae [ 9 ]. It is therefore tempting to speculate that this protein may be involved in the specific recognition of particular malaria genotypes by the insect's immune system. The mosquito genotype by parasite genotype interactions shown in this paper may help to understand some puzzling aspects of the epidemiology of malaria. Thus, even in areas with intense transmission, the probability that a mosquito becomes infected is generally low [ 26 , 32 ]. Furthermore, the probability of infection is generally low even when, as in our study, mosquitoes fed on a blood-meal known to contain infectious gametocytes [ 33 , 34 ]. This could have several explanations: mosquitoes fail to pick up infective gametocytes, transmission-blocking immunity in the human hosts prevents the parasite's development within the mosquito [ 22 , 35 ], or parasites are cleared by mosquitoes that mount a sufficiently effective immune response [ 2 ]. The present results indicate an additional reason: that many parasites are incompatible with many of the mosquitoes in a natural population. The epidemiological consequences of mosquito genotype by malaria genotype interactions are perhaps most obvious in the context of malaria control with mosquitoes transformed to be resistant against malaria. The strong genetic specificity of compatibility between parasite isolates and individual insect vectors suggests that most studies on the mechanisms underlying the resistance of mosquitoes against Plasmodium might be misleading for the development of malaria control strategies. Indeed, most of these laboratory-based studies focus on the response of one mosquito line or colony against a single parasite strain and thus do not represent the genetic diversity of mosquitoes and parasites in natural populations [ 12 , 13 ]. However, any malaria control programme based on the release of mosquitoes harbouring 'resistance genes' is unlikely to be effective if resistance is expressed against only a subset of the parasite genotypes of the local population. Indeed, as parasites facing resistant mosquitoes will be under strong selective pressure to avoid mosquito defence mechanisms, genotypes that are eliminated by the resistance genes might be replaced rapidly by genotypes that cannot be controlled. Thus, before a possible release of transgenic mosquitoes, it will be crucial to ensure that the transformed mosquitoes are resistant to all of the parasite genotypes in the local population. This reinforces the idea that any release of genetically modified mosquitoes for reducing transmission of mosquito-borne diseases must be preceded by studies that have moved from the laboratory to the field [ 10 ]. Conclusions This study demonstrated that the resistance of an anopheline mosquito to P. falciparum development, a major component of its vector competence, varies considerably between different combinations of parasite isolates and individual, genetically variable, vectors. Optimal transmission may thus require some specific compatibility between the insect's and the parasite's genotypes. This result has important consequences for the epidemiology of malaria. Overall, it suggests that conclusions from a particular subset of mosquito and malaria genotypes will not necessarily hold for other combinations of genotypes. Therefore, field studies taking into account the full diversity of mosquito and parasite populations are necessary to reach valid conclusions concerning the technologies developed in laboratories for the control of malaria. Authors' contributions LL participated in the design and the coordination of the study, carried out the fieldwork, participated in the molecular analysis, performed the statistical analysis, and wrote the manuscript. JH participated in the fieldwork. PD carried out the molecular analyses and helped to draft the manuscript. LCG supervised and coordinated the fieldwork. JCK conceived and designed the study, performed the statistical analysis, and wrote the manuscript.

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What is important in evaluating health care quality? An international comparison of user views

Background Quality of care from the perspective of users is increasingly used in evaluating health care performance. Going beyond satisfaction studies, quality of care from the users' perspective is conceptualised in two dimensions: the importance users attach to aspects of care and their actual experience with these aspects. It is well established that health care systems differ in performance. The question in this article is whether there are also differences in what people in different health care systems view as important aspects of health care quality. The aim is to describe and explain international differences in the importance that health care users attach to different aspects of health care. Methods Data were used from different studies that all used a version of the QUOTE-questionnaire that measures user views of health care quality in two dimensions: the importance that users attach to aspects of care and their actual experience. Data from 12 European countries and 5133 individuals were used. They were analysed using multi-level analysis. Results Although most of the variations in importance people attach to aspects of health care is located at the individual level, there are also differences between countries. The ranking of aspects shows similarities. 'My GP should always take me seriously' was in nearly all countries ranked first, while an item about waiting time in the GP's office was always ranked lowest. Conclusion Differences between countries in how health care users value different aspects of care are difficult to explain. Further theorising should take into account that importance and performance ratings are positively related, that people compare their experiences with those of others, and that general and instrumental values might be related through the institutions of the health care system.

Background Large differences between countries exist in the use, costs, quality, and accessibility of health services [ 1 ]. Also large differences exist between countries in health care performance and in people's evaluations of their health care system [ 2 - 7 ]. But do these differences also exist in what people from different countries view as important in evaluating health care quality? The World Health Report 2000 has been criticized on its assumption of a universal value base to all health care systems; values such as responsiveness may be valued differently in different countries [ 8 ]. In this article we address this issue by comparing what people find important in general practice care in different countries. Grol et al studied patients' priorities in general practice [ 9 ]. They found both many similarities and differences between countries. Particularly, doctor-patient communication and accessibility of services were common priorities among general practice visitors in different countries. Service aspects, such as waiting times, were considered less important. In this study we did a secondary analysis on surveys of patient views on quality of health care. Patients' views were measured using the QUOTE-questionnaire – with the acronym QUOTE standing for QU ality O f care T hrough the patients' E yes – that distinguishes two quality of care dimensions: performance and importance [ 10 ]. Performance relates to the actual experience of the use of health care services (rather than a patient satisfaction judgement), which is in line with recent developments within health services research. Importance refers to the fact that people see some features of health services as more significant than others. They reflect what people see as desired qualities in health care. This approach avoids problems with conceptualising people's evaluations of health care in terms of satisfaction (usually high levels of satisfaction, not specific enough to be used in quality improvement) and expectations (ambiguous relations between expectations and actual experiences). To select relevant quality of care aspects, a general and a disease-specific approach was followed, using focus group discussions [ 10 ]. With this procedure a series of QUOTE-questionnaires has been tailored to the needs of various patient groups. In these QUOTE-questionnaires the expectations of people are reflected in the statements included in the instruments. These questionnaires have been used in several studies in different countries. Research questions In this article we first compare the importance dimension of QUOTE across several European countries and Israel to gain insight in the similarities and differences in people's views on quality of care. Secondly, we will look at the relationship between importance and performance ratings as part of an explorative analysis to explain differences in importance ratings between patients and/or countries. The general research question is: Do patients in different European countries think differently about the relative importance of various aspects of quality of care, and if so, how can these differences be explained? This general question is divided into the following separate questions: a. To what extent do the importance judgements of patients cluster within countries when individual characteristics of patients are taken into account? b. Does the ranking of importance judgements vary between countries? c. What is the relationship between the average performance of health care systems, as judged by patients, and the individual importance judgements? When we compare the importance judgements of patients between countries, we will take into account individual characteristics of respondents to rule out differences in the composition of the groups of respondents. With respect to the relationship between importance and performances scores it might be anticipated that in general people attach more importance to those aspects that they actually experience less often. Analogous to the economic mechanism of decreasing marginal utility, e.g. quick service without waiting time in the doctor's office might be valued as less important, if in general services are quick and people don't have to wait long. However, at the same time it can be hypothesized that it's no use aspiring to something that nobody has. If quality of care ratings, as seen through the eyes of the patient, are low on the average and if there is small variation in these performance ratings between individuals, people will probably not find these aspects important. This idea is based on a mechanism of social comparison [ 11 ]. Methods Material The First Dutch QUOTE-questionnaires (for disabled persons, COPD, arthritis and frail elderly people) served as a starting point for our database [ 10 , 12 ]. These questionnaires contain 16 general importance and performance items. In the SCOPE-project (Supporting Clinical Outcomes in Primary Care for the Elderly) the QUOTE-elderly was used in Finland, Ireland and the Netherlands [ 13 ]. A large contribution to the database comes from an international study of patients with inflammatory bowel disease (IBD) in eight countries [ 14 ]. This study used ten generic questions (of the original 16) relating to GPs. Additional material was obtained from the UK (QUOTE-disabled) and from Belarus and the Ukraine [ 15 , 16 ]. The QUOTE-questionnaires have been translated in the context of different projects. In all but two cases backward-forward translations have been used. Answering formats of importance items were: Not important (1); Fairly important (2); Important (3); and Extremely important (4). The answering formats for the performance items were: No (1); Not really (2); On the whole, yes (3); and Yes (4). The equivalence of the answering formats in different languages has not been assessed. The wording of the importance items that were used in the QUOTE-questionnaires are presented in tables 2 and 5 and throughout the result section of the article. The performance items ask for the actual experience of respondents. One of the importance items is, e.g., 'my GP should always take me seriously'. The corresponding performance item is: my GP always takes me seriously'. QUOTE-items included in the analysis refer to the organisation of health care services and the care giving process. Table 1 Number of respondents in health care user groups and countries Country User group Selection of users N per user group N per country Belarus GP patients GP office 500 500 Denmark IBD a hospital files 102 102 Finland Elderly PHC files 143 143 Greece IBD hospital files 96 96 Ireland IBD hospital files 57 73 Elderly Homecare Organisation files 16 Israel IBD hospital files 46 46 Italy IBD hospital files 201 201 Netherlands Migrants Snowball method 152 2873 IBD hospital files 192 Elderly GP files 338 Disabled GP files/patient organisation 334 Diabetes GP files/patient organisation 681 COPD GP files/patient organisation 604 Arthritis GP files/patient organisation 572 Norway IBD hospital files 93 93 Portugal IBD hospital files 36 36 UK Disabled GP files 480 480 Ukraine GP patients GP office 490 490 Total 5133 5133 a IBD inflammatory bowel disease Table 2 Descriptive statistics for importance items: mean, variance at user level, variance at country level, intra-class correlation coefficient, uncorrected (ICCu) and corrected for age and sex (ICCc) Item My GP should Mean Var Users Var Country ICCu ICCc 3 always take me seriously 3.45 .377 .044 .105 .092 6 inform me, in understandable language, about the medicines that are prescribed for me 3.35 .532 .059 .100 .107 1 have a good understanding of my problems 3.24 .615 .147 .193 .087 9 make sure that I can see a specialist within 2 weeks after being referred to him/her 3.13 .591 .198 .251 .256 4 always keep appointments punctually 3.10 .545 .074 .120 .113 2 allow me to have an input into the decisions regarding the treatment or help I receive 3.07 .648 .071 .099 .063 7 prescribe medicines which are fully covered by the National Health System or social services 3.05 .896 .100 .100 .113 8 always be easy to reach by telephone 3.02 .509 .060 .092 .111 10 always communicate with other health and social care providers about the services I require 2.90 .650 .084 .114 .116 5 not keep me in the waiting room for more than 15 minutes 2.54 1.016 .062 .058 .087 Table 3 Mean scores of ten importance items per country 1* 2* 3* 4* 5* 6* 7* 8* 9* 10* Belarus** 2.42 2.61 3.21 3.34 2.59 3.04 2.98 2.68 Denmark 3.23 3.22 3.47 2.75 2.37 3.57 2.43 2.62 3.10 2.57 Finland** 2.91 3.03 2.84 2.87 2.86 3.00 Greece 3.46 3.10 3.51 3.25 2.64 3.34 3.09 3.23 3.03 2.93 Ireland 3.47 3.15 3.60 2.90 2.42 3.55 3.02 3.01 3.21 2.96 Israel 3.71 3.70 3.84 3.52 3.07 3.75 3.40 3.14 3.51 3.12 Italy 3.10 2.89 3.23 2.63 1.95 3.12 2.79 2.70 2.03 2.39 Netherlands 3.21 3.28 3.59 3.24 2.50 3.42 3.01 3.33 3.27 3.29 Norway 3.42 3.14 3.60 3.08 2.46 3.57 3.00 2.81 3.17 2.56 Portugal 3.61 2.94 3.61 3.19 2.78 3.42 3.64 3.42 3.44 3.28 UK 3.37 3.20 3.44 3.02 2.57 3.40 3.21 3.27 3.46 3.20 Ukraine** 2.68 2.77 3.37 3.46 2.71 3.21 2.88 2.92 Overall 3.24 3.07 3.45 3.10 2.54 3.35 3.05 3.02 3.13 2.90 * See table 2 for the wording of the items. ** Not all ten items were used in these countries. Table 4 Ranking of items by mean importance within each country; r1-r10 is the ranking, cell entries contain the item number corresponding to that rank. Country r1 r2 r3 r4 r5 r6 r7 r8 r9 r10 Denmark 6 3 1 2 9 4 8 10 7 5 Greece 3 1 6 4 8 2 7 9 10 5 Ireland 3 6 1 9 2 7 8 10 4 5 Israel 3 6 1 2 4 9 7 8 10 5 Italy 3 6 1 2 7 8 4 10 9 5 Netherlands 3 6 8 10 2 9 4 1 7 5 Norway 3 6 1 9 2 4 7 8 10 5 Portugal 7 1 3 9 6 8 10 4 2 5 UK 9 3 6 1 8 7 10 2 4 5 Table 5 Pearson correlation coefficients between importance- and performance items on individual level and between average performance items in each country and the individual importance scores (mixed level) Importance/performance items Individual level Mixed level have a good understanding of my problems .346 ** .322 allow me to have an input into the decisions regarding the treatment or help I receive .277 ** .263 always take me seriously .126 ** .167 always keep appointments punctually .140 ** .081 not keep me in the waiting room for more than 15 minutes .150 ** .054 inform me, in understandable language, about the medicines that are prescribed for me .179 ** .170 prescribe medicines which are fully covered by the National Health System or social services .080 ** -.057 always be easy to reach by telephone .163 ** .184 make sure that I can see a specialist within 2 weeks after being referred to him/her .135 ** .119 always communicate with other health and social care providers about the services I require .281 ** .287 ** p < .01 Table 1 gives the number of respondents in each user group and country and the selection of respondents. In the case of Belarus and Ukraine respondents were selected by distributing questionnaires to people who visited general practices. Response rates are not available for these two countries. In all other countries but one addresses were randomly selected from the files of health care (and in one case home care) institutions and (in The Netherlands) from membership lists of voluntary patient organisations, irrespective of actual visits to a GP. In the case of the QUOTE-Migrants, respondents from ethnic groups in the Netherlands were selected using a snowball sampling method; data for these respondents were collected through oral interviews in the respondents' mother language. In all other cases postal questionnaires were used, followed by one or two reminders. Response rates vary between 35% (elderly in the Netherlands) and 78% (the average of the IBD samples). Statistical analysis All 5133 health care users reported for each of (maximum) ten items their importance and performance ratings. The importance ratings are dependent variables in a series of statistical analyses with patients hierarchically nested in countries. In contrast to traditional forms of analysis of variance in which factors have 'fixed' effects, countries are considered to have 'random' effects. Such a variance component model is preferred over traditional analysis if the number of categories exceeds ten [ 17 , 18 ]. The degree of resemblance between patients belonging to the same country can be expressed by the intraclass correlation coefficient (ICC). If there is no resemblance between patients within countries, the ICC is zero or near zero. An ICC of .15 is considered quite high [ 19 ]. Most commonly ICCs are lower. For instance, the median ICC calculated for more that 1000 primary care variables, was .01 [ 20 ]. The ICC is statistically defined as the variance between countries divided by the total variance. An ICC of zero therefore implies no variance between countries, indicating the absence of differences between countries in patients' importance ratings. Age and sex were included as covariates to take into account differences in the composition of responder groups in the different countries, because of their association with importance scores [ 9 , 10 , 21 - 23 ]. Correction for different user groups turned out to be impossible due to the small number of countries for some user groups. Differences in number of cases between countries were taken into account in the statistical analysis. The estimates of country parameters are more precise with larger numbers per country. In order to explore the relationship between importance and performance ratings Pearson correlations were calculated between the performance items, both at the individual level and aggregated to country level, and the importance rating on user level. In the introduction we have put forward two hypothetical relations between variation of performance within the countries and the importance ratings. To look at the relation between variation of performance and importance ratings, a distinction was made between countries with large variation in experienced health care quality and countries with smaller variation. Based on the mean standard deviation (SD) of all ten performance items, the countries were equally split into: Denmark, Italy, Belarus, Ireland, Ukraine and Portugal (mean SDs ranging from 1.17 to 1.40) indicating countries with high variation and Greece, Finland, Israel, Norway, Netherlands and UK (mean SDs ranging from .82 to 1.08) indicating countries with low variation. Furthermore, explore the relationship between variation in performance at country level, individual respondents performance experience and their importance ratings, we have divided the individual respondents into those who experienced high performance and those who experienced low performance. To keep these distinctions conveniently arranged in one table, we recoded the individual performance scores from the four point scale to a two point scale, with the combination of 'No' and 'No, not really', indicating poor quality, versus 'On the whole, yes' and 'Yes'. Results We start the presentation of the results with a description of the overall importance that respondents in all twelve countries attached to the different aspects and the clustering of their answers within countries. We then move to the differences in the ranking of aspects between countries. Finally, we will present results for the relationship between the actual experiences of respondents, both individually and aggregated to an average for each country, and the importance they attach to the different aspects. Importance judgements and clustering As shown in table 2 , 'The GP should always take me seriously' is seen as most important, halfway between 'important' and 'extremely important' on the Likert scale. Less than 1% of users rated this item as 'not important' (not in table). The differences between users as well as countries for this aspect are the smallest of all aspects (smallest variance, both on user- and country level). 'The GP should not keep me in the waiting room for more than 15 minutes' is seen as least important, halfway between 'important' and 'fairly important'. About 20% of users rated this aspect as 'not important' (not in table). The differences between users for this aspect are largest (highest variance on user level). The importance of 'The GP should make sure that I can see a specialist within 2 weeks' shows the biggest differences between countries. The uncorrected ICCs vary from low (.058 aspect 5) to high (.251 aspect 9). The sex-age adjusted ICCs are a little (7%) lower on average, but still range to high. In order to explore differences between user groups, we have computed intra-class correlation coefficients for user groups within the Netherlands only. These coefficients are on average higher than those regarding countries. We also analysed the differences between countries within the IBD patient groups. These differences are much like the figures of table 2 . So the estimated intra-class coefficients of table 2 seem to refer more to differences between countries than differences between user groups. Differences between countries and ranking The variation between the countries for each aspect is illustrated in table 3 by mean importance scores for all aspects. For instance, 'The GP should always take me seriously' is seen as most important in Israel and as least important in Finland. 'The GP should not keep me in the waiting room for more than 15 minutes' also is seen as most important in Israel but as least important in Italy. In order to look at the consistency of user views across the different countries, the ten importance aspects were ranked according to their mean value within each country. Table 4 gives the ranks for countries where all ten aspects are available. Some rankings differ between countries. For instance in Denmark 'My GP should inform me, in understandable language, about the medicines that are prescribed for me' is ranked first. In Portugal it is 'My GP should prescribe medicines which are fully covered by the National Health System or social services'. But there is also a general pattern. The service aspect 'My GP should not keep me in the waiting room for more than 15 minutes' is ranked last in all countries, while 'My GP should always take me seriously' is ranked high in all countries. Importance and performance Looking at the relationship between importance and performance ratings by means of correlation coefficients, table 5 shows that the correlation coefficients on individual level are all positive and range from small (.080) to moderate (.346). Because of the large number of respondents, even the small correlations are statistically significant. The correlation between the average performance in each country and the individual importance vary also from small (.054) to moderate (.322). Because of the small number of countries these correlation coefficients are not significantly different from zero. Except for one aspect 'My GP should prescribe medicines which are fully covered by the National Health System or social services' all correlations are positive, while we anticipated negative correlations. If we take into account the variation in performance ratings within countries, the positive relationship between importance and performance ratings is somewhat stronger in the 'high variation' mode compared to the 'low variation' mode. This can be seen by comparing the difference between the first two columns of table 6 and those between the last two columns. We had specifically expected to find a difference between the last two columns of table 6 , i.e. within countries with low variation in aggregate performance. However, for only half of the items the difference is statistically significant. Table 6 Mean scores of ten importance items according to variation in performance items per country and individual scores on corresponding performance items (Low vs High performance) Country level: High variation in performance Low variation in performance Individual level: Low performance High performance Low performance High performance 1 should have a good understanding of my problems 2.06 2.92 3.04 3.28 2 should allow me to have an input into the decisions regarding the treatment or help I receive 2.27 3.03 3.11 3.30 3 should always take me seriously 2.99 3.35 3.66 3.55 4 should always keep appointments punctually 3.01 3.32 3.08 3.22 5 should not keep me in the waiting room for more than 15 minutes 2.26 2.82 2.42 2.60 6 should inform me, in understandable language, about the medicines that are prescribed for me 2.80 3.24 3.28 3.43 7 should prescribe medicines which are fully covered by the National Health System or social services 2.74 2.95 2.98 3.09 8 should always be easy to reach by telephone 2.63 3.04 3.29 3.34 9 should make sure that I can see a specialist within 2 weeks after being referred to him/her 2.29 2.67 3.26 3.34 10 should always communicate with other health and social care providers about the services I require 2.42 2.98 3.12 3.30 Italic means in column Low variation at country level/Low performance at individual level differ statistically significant from means in column Low variation at country level/High performance at individual level (Scheffé contrasts). Overall, importance scores are somewhat lower in countries with high variation in performance ratings as compared to countries with low variation in performance scores. Discussion The objective of our study was to gain insight into similarities and differences in the value users of health care in different countries attach to aspects of care. As an indicator of these values, importance scores of the QUOTE-questionnaires were used. These scores reflect what is important in evaluating health care quality according to users. Our results show that health care users in different countries to some extent think differently about the relative importance of various aspects of quality of care. Intra-class correlation coefficients were calculated to measure the difference between countries. They range from low to high. Sex-age adjusted intra-class correlation coefficients were only slightly lower. This means that demographic differences between the groups that filled in the questionnaires in different countries cannot explain the differences in average importance between the countries. Although there are differences between countries, the importance rankings of the aspects also show consensus. 'My GP should always take me seriously' is nearly always ranked highest, while the item about waiting time is always ranked as least important. Since we only analysed a small sample of countries, it is difficult to generalise this result. However, it might say something about a hierarchy of these instrumental health care values, suggesting that values concerning respectfulness are seen as more important than service aspects, such as waiting time. This is in line with the findings of Grol et al. [ 9 ]. There are no accepted explanations for these value differences between countries. General theories about dimensions of culture see culture as the independent variable, explaining differences between countries in institutions and organisations [ 24 , 25 ]. A more specific application in the health care field is Payer's book Medicine and Culture that relates differences in culture to variations in the practice of medicine [ 26 ]. In this article, however, differences in values is what we want to explain. In general, there is a positive relation between what people find important and their experiences, both on an individual level and related to the average experience in a country. The positive relation between importance and experience could probably be explained by a general tendency of cognitive consistency [ 27 ] or alternatively by processes of selection where people try to find those health care providers that do what they value most. This alternative hypothesis would mean that the correlation between importance and experience is stronger the more freedom of choice of health care provider people have. One of the assumptions behind the QUOTE-questionnaires is that importance and experience are two different aspects, together constituting quality judgements. The correlation at the individual level is not so high as to invalidate this assumption. By looking at the variation in the performance scores, we have tried to include social comparison mechanisms into the analysis. It can be argued that if people's individual experience indicates low performance for certain aspects in countries, they will value these aspects as more important. However, such a hypothesis has to be rejected on the basis of the results presented in this article. A contrasting hypothesis, that in countries with low variation in actual experiences, people who experience low performance themselves, will not aspire to something that is apparently (from their own and others' experience) out of reach is only partly supported by our findings. Although people in this low variation condition have significantly lower importance scores for half of the items, still the differences in the high variation condition are higher. Looking at the individual aspects, it can be argued that people don't find issues important if they are more or less guaranteed by the health care system. An example for this is the issue of prescribing pharmaceuticals that are fully covered by the health care insurance plans of patients. On the basis of the material presented in this article this hypothesis too has to be rejected. People in countries with low levels of cost sharing in this field, found this item more important than people in countries with higher levels of cost sharing. However, an alternative explanation for this finding could be that structural aspects of the health care system, e.g. on the dimension public – private, reflect general values [ 28 , 29 ]. If these general values also relate to instrumental values, than the relationship we found is understandable: the people in countries that took the pain to organise their health care system in a way that financial access is very good, might find this issue more important. In this explanation the mechanism between general and instrumental values is the institutional make-up of health care systems. The importance items in our study reflect instrumental values in the sense that they are low in a hierarchy of values where lower values contribute to the realisation of higher values. Solidarity and equity are examples of general values; prescribing pharmaceuticals that are covered by health care insurance could be seen as contributing to equity, and is thus an instrumental value. In general, we believe that further theorising about differences between health care systems in what people find important, might start from the positive relation between importance and experience, from the idea that people compare their experiences with those of others, and from the idea that general and instrumental values might be related trough the institutions of the health care system. Hofstede [ 24 ] has identified a number of general dimensions of culture that might also be related to instrumental health care values through different types of welfare states [ 30 ]. The analysis presented in this article has its shortcomings. The number of countries is small. The analysis of differences between countries is based on only twelve countries, even though large numbers of respondents were involved. The number respondents increase our confidence in the averages per country, but this does not solve the problem of small numbers at the country level. Differences between user groups could not be taken into account because of the small number of groups for all countries except the Netherlands, although one might expect these differences to exist [ 29 ]. The multilevel model now contained two levels, respondents and countries. However, as table 1 indicated, the selection of respondents was through health care institutions. Hence, a level between respondents and countries should ideally have been specified. However, the data did not allow this. Differences between user groups are relatively large. However, the estimated intraclass correlations of table 2 seem to refer more to variation between countries than between user groups. Future research with larger numbers of user groups would be helpful to be able to take case mix differences into account. We used existing data, collected in different studies with different aims and methods. The response rates differed across studies. The user groups in the surveys refer to are very different, ranging from GP-patients in Belarus to disabled people in the UK and IBD patients in Israel. Apart from the apparent differences between user groups, there are also differences between countries in the position and tasks of GPs. The situation in Ukraine and Belarus was transitional, even ten years after the fall of the Iron Curtain [ 31 ]. This may have reduced comparability and create variations in respondents and services to be evaluated. The QUOTE-questionnaires provide a general framework, and researchers have adapted them to their own aims. Against the advantage of flexible adaptation to different research aims and populations stands the disadvantage of reduced (international) comparability. For (international) comparisons more standardisation is very important. Apart from that, the ten QUOTE-aspects we used in our analyses cover different dimensions of the Quality of care concept and can be understood as being comprehensive enough for this explorative type of research. In conclusion, we believe it is important to continue to do research into health care related values because of the increasing importance of user views, both in the health policies of European countries separately and in the international debate about the performance of health care systems. There is not much ground for strong cultural relativism, saying that what is important in the eyes of health care users is so different that it is not possible to develop performance measures that can be used in a wide range of countries. Conclusion There are differences between countries in the importance people attach to aspects of health care. Most of this variation is related to individual differences, but there is also significant variation between countries. The ranking of aspects shows similarities between countries. In nearly all countries, people ranked the item that their GP should take them seriously as most important, while an item about waiting time was always ranked lowest. It is difficult to explain the variation between countries. Further theorising should take into account that importance and performance ratings are positively related, that people compare their experiences with those of others, and that general and instrumental values might be related through the institutions of the health care system. Competing interests The author(s) declare that they have no competing interests. Authors' contributions PG conceived the study and wrote the first drafts of the article; JK performed the statistical analysis; HS provided data and wrote the final draft of the article; WB provided data; IvdE provided data. Pre-publication history The pre-publication history for this paper can be accessed here:

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524378

Malaria Vaccine Trial Results Are Negative, but Important

A malaria vaccine called ME-TRAP, which targets the pre-erythrocytic stage of the disease, was not effective at reducing natural infection rates in semi-immune African adults, according to the report of a randomized controlled trial published this month in PLoS Medicine . “This first field efficacy trial was an important milestone in the progression of new recombinant vectored vaccines to deployable products,” says Adrian Hill (University of Oxford, United Kingdom), the lead investigator of the study. “The safety profile was excellent and the efficacy data provide a first indication of the levels of cellular immunogenicity that will be required for preventing infection,” he says. Hill and his co-workers used a heterologous prime–boost vaccination technique. They gave the volunteers two vaccines—a DNA priming vaccine followed by a modified vaccinia virus Ankara (MVA) that acted as a booster. The DNA and MVA vaccines both had the same insert coding for thrombospondin-related adhesion protein (TRAP; a pre-erythrocytic antigen) and a string of T cell epitopes (called ME for “multiple epitopes”). Hill's team had previously shown that ME-TRAP vaccines given in prime–boost sequence could induce large T cell responses in healthy volunteers from the UK and could delay parasitemia in a sporozoite challenge test (Nat Med 9: 729–735). The next step was to do a randomized controlled trial in Gambia to determine whether this vaccination strategy could provide protection against natural Plasmodium falciparum infection. The researchers recruited volunteers from 13 Gambian villages that were close to the alluvial flood plain and so were at high risk of developing malaria. They randomly assigned the 372 volunteers to receive either two doses of the DNA ME-TRAP vaccine followed by a single dose of MVA ME-TRAP, or three doses of rabies vaccine. This three-dose schedule is similar to the one used by the World Health Organization/United Nations Children's Fund Expanded Program on Immunization. Two weeks before the third dose was given, all the volunteers received antimalarial drugs to clear blood-stage P. falciparum infections. The time to first infection, the primary end point of the study, was similar in the two groups, with an estimated vaccine efficacy of only 10%. However, the effector T cell response to the TRAP antigen T9/96, measured one week after the third vaccination, was 80 times higher in the DNA/MVA vaccine group than in the rabies vaccine group. “It is absolutely crucial that results like these are published, since the failures, as well as the successes, need to be documented if we are to move towards rational strategies for optimizing malaria vaccines,” says Tom Smith from the Swiss Tropical Institute, who was not involved in the study. “At the same time, it makes sense to move on quickly without shedding too many tears, in a field that is moving much faster than it was before the recent injections of money from the Gates Foundation, but where it is still impossible to second-guess the results of field trials. This is partly because we do not have any good proxy measures of effective immunity in P. falciparum , and partly because this is a fertile area for trying out new techniques, such as DNA vaccines, where there is still a lot to learn.” Hill is planning to do further trials that address the important question of whether this type of vaccine can prevent the symptoms of malaria. “The next step,” says Hill, “is to assess newer vaccine regimes that employ two viral vectors rather than DNA and to study prevention of malaria rather than infection.”

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526209

Student evaluation of an OSCE in paediatrics at the University of the West Indies, Jamaica

Background The Faculty of Medical Sciences, University of the West Indies first implemented the Objective Structured Clinical Examination (OSCE) in the final MB Examination in Medicine and Therapeutics during the 2000–2001 academic year. Simultaneously, the Child Health Department initiated faculty and student training, and instituted the OSCE as an assessment instrument during the Child Health (Paediatric) clerkship in year 5. The study set out to explore student acceptance of the OSCE as part of an evaluation of the Child Health clerkship. Methods A self-administered questionnaire was completed by successive groups of students immediately after the OSCE at the end of each clerkship rotation. Main outcome measures were student perception of examination attributes, which included the quality of instructions and organisation, the quality of performance, authenticity and transparency of the process, and usefulness of the OSCE as an assessment instrument compared to other formats. Results There was overwhelming acceptance of the OSCE in Child Health with respect to the comprehensiveness (90%), transparency (87%), fairness (70%) and authenticity of the required tasks (58–78%). However, students felt that it was a strong anxiety-producing experience. And concerns were expressed regarding the ambiguity of some questions and inadequacy of time for expected tasks. Conclusion Student feedback was invaluable in influencing faculty teaching, curriculum direction and appreciation of student opinion. Further psychometric evaluation will strengthen the development of the OSCE.

Background The assessment of student's clinical competence is of paramount importance, and there are several means of evaluating student performance in medical examinations [ 1 , 2 ]. The Objective Structured Clinical Examination (OSCE) is an approach to student assessment in which aspects of clinical competence are evaluated in a comprehensive, consistent and structured manner, with close attention to the objectivity of the process [ 3 ]. The OSCE was introduced by Harden in 1975 [ 4 ], and first described as an assessment format in Paediatrics (Child Health) by Waterson and colleagues [ 5 ]. Since its inception, the OSCE has been increasingly used to provide formative and summative assessment in various medical disciplines worldwide [ 6 ], including non-clinical disciplines [ 7 ]. The University of the West Indies was established in 1948 as a medical college of the University of London, which granted external degrees to those who successfully completed the course [ 8 ]. The Faculty of Medical Sciences located on four campuses, on the islands of Jamaica, Bahamas, Barbados and Trinidad and Tobago, conducts bi-annual final examinations at the end of year 5. The 'traditional' format of examination that included long case, short cases and oral examination, was preserved until recent changes in the curriculum. In response to recommendations to improve the validity and fairness of the examination through adoption of proven methods and approaches in assessment and evaluation in medical education, the Faculty of Medical Sciences (FMS), University of the West Indies (UWI) initiated the OSCE as a formal method of assessment for the final examination in Medicine and Therapeutics, Child Health, Community Health and Psychiatry, in November 2000. Students and faculty were exposed for the first time to a relatively new assessment instrument in which aspects of competence (communication, history-taking and technical skills) were assessed in a structured, formal manner. The Section of Child Health, Mona, Jamaica, implemented the OSCE examination as an end-of clerkship assessment for students in their 5 th year, during the 1999–2000 academic year. It was felt timely in order to (a) direct and motivate student learning in areas not previously assessed in the 'traditional' curriculum, (b) verify students' competence in fundamental paediatric clinical skills, and (c) provide a forum for feedback to students on their strengths and weaknesses in clinical skills. It was thought that it would enhance faculty and student acceptance of this new assessment tool and promote faculty training for the newly introduced final OSCE examination. In the absence of any previous information from this institution, the study was designed to evaluate student overall perception of the end-of-clerkship OSCE, determine student acceptability of the process and provide feedback to enhance further development of the assessment. Methods The OSCE comprised a circuit of thirteen stations, which involved completion of a number of tasks such as examination of a system, eliciting a focussed history, counselling or communicating a problem, performing a procedure and problem-solving oriented around patient and laboratory data, and photographic material (Figure 1 ). The areas assessed included cardiovascular, respiratory, abdomen, neurological, developmental, dysmorphism and nutrition. This assessment format allowed the controlled exposure of students to a wide variety of paediatric clinical skills within a relatively short time period. Each station was 7 minutes duration with the exception of the 14-minute history-taking station. One minute was given between stations to facilitate change and the reading of instructions. With the inclusion of strategically placed rest stations, to reduce student and patient fatigue, all students completed the circuit over a 2-hour period. Figure 1 Plan of OSCE circuit A standardised technique of marking was used and student performance was assessed by criterion reference for each station. Criterion-based scoring was used, with each checklist item scored as 0 (omitted, incorrect or inadequate), or 1–2 (correct or adequate). Face and content validity of each checklist was established by review and consensus by a core group of senior paediatricians. Stations were first selected to represent the curricular goals and objectives and to reflect authentic clinical situations. Checklists were designed to include the features thought to be most important by the development committee. Through discussions, consensus was achieved on the checklist items and structure. The study was conducted during the period July 2001 to December 2002. Five groups of students participated in the process, during their respective clerkship rotations. Student groups had at least two briefing sessions before the OSCE, and included an orientation about the examination process (both end-of-clerkship and final MB) and a review of commonly assessed competences. They were also apprised of the valuable contribution they could make towards improving the assessment and encouraged to participate in the evaluation. A cross-sectional survey using a 32-item self-administered questionnaire was completed at the end of each OSCE [ 9 ]. Students were asked to evaluate the content, structure, and organization of the OSCE, rate the quality of performance and objectivity of the OSCE process, and to give their opinion about the usefulness of the OSCE as an assessment instrument compared to other forms which they had experienced (essays, multiple choice questions, long and short cases, general clerkship rating). Participation was on a voluntary basis and students were assured that those who declined involvement in the survey would not be penalised. The Curricular Affairs Section handled the administration and analysis of the questionnaires. Ethical approval was received from the University Hospital of the West Indies/University of the West Indies Faculty of Medical Sciences Ethics Committee. Following completion of the questionnaire, an OSCE review session was conducted with the students for feedback and teaching purposes, at the end of the clerkship. Students were given the opportunity to review their individual performances at the respective stations. Examiner evaluations were also used in the feedback process. Data were collated and descriptive and non-parametric tests applied using Stata version7 [ 10 ]. Basic statistical analysis of the Likert items was conducted by calculating frequencies, means and standard deviations. Qualitative analysis was done through a form of content analysis by identifying themes in student responses and grouping responses according to thematic content. Two of the authors individually conducted this content analysis and identified themes and final grouping of responses were developed by consensus. Results OSCE evaluation Eighty-one students responded to the questionnaire, representing 92 % (81/88) of those who completed the Clerkship. The majority of students agreed that the OSCE was comprehensive and covered a wide range of knowledge (95%) and clinical competencies (86%) in Child Health. Three quarters (78%) also agreed that the assessment process helped to identify weaknesses and gaps in their competencies (Table 1 ). Table 1 OSCE evaluation Question Agree % Neutral % Disagree % No comment % Exam was fair 68 19 12 1 Wide knowledge area covered 95 5 Needed more time at stations 70 22.5 7.5 Exams well administered 73 16 11 Exams very stressful 67 20 13 Exams well structured & sequenced 81.5 17 2.5 Exam minimized chance of failing 28 40.5 30 1.5 OSCE less stressful than other exams 15 40 35 10 Allowed student to compensate in some areas 67 21 12 Highlighted areas of weakness 78 13 9 Exam intimidating 48 32 20 Student aware of level of information needed 53 26 21 Wide range of clinical skills covered 86 6 8 Most (73–82%) felt that the exam was well administered, and that the stations were arranged in an organised and well-sequenced order. Students believed that the assessment was fair (68%). Fifty-three percent were aware of the level of information required at each station, yet 28% felt that the examination process minimized their chances of failing. Students found the OSCE to be intimidating (48%) and more stressful (35%) than other assessment formats to which they were previously exposed. And most (70%) felt that they needed more time to complete the stations. Performance testing The majority of students felt they were well oriented about the exam and that the required tasks were consistent with the actual curriculum that they were taught. They also felt that the process was fair but were not as satisfied with the time allocation for each station (Table 2 ). Table 2 Quality of performance testing Question Not at all % Neutral % To great extent % Fully aware of nature of exam 4 9 87 Tasks reflected those taught 4 23 73 Time at each station was adequate 44 35 21 Setting and context at each station felt authentic 18 24 58 Instructions were clear and unambiguous 15 27 58 Tasks asked to perform were fair 3 27 70 Sequence of stations logical and appropriate 13 30 57 Exam provided opportunities to learn 11 21 69 Most saw the OSCE as a useful learning experience and that the content reflected real life situations in Child Health. More than half of the students were satisfied with the conduct, organisation and administration of the OSCE. Perception of validity and reliability Although half of the students believed that the scores were standardised, they were unsure whether their scores were an actual reflection of their paediatric clinical skills (Table 3 ). Student responses to the question about bias due to gender, personality or ethnicity, were not interpretable. Table 3 Student perception of validity and reliability Question Not at all % Neutral % To great extent % OSCE exam scores provide true measure of essential clinical skills in paediatrics 14 43 43 OSCE scores are standardized 8 37 55 OSCE practical and useful experience 4 23 73 Personality, ethnicity and gender will not affect OSCE scores 18 19 63 Comparing assessment formats Students were asked to rate the following assessment instruments to which they had been exposed (multiple choice questions, essays / short answer questions, general clerkship ratings, OSCE). A likert scale was used to assess each according to the evaluative labels (Table 4 ). Table 4 Student rating of assessment formats Question: Difficult % Undecided % Easy % Which of the following formats is easiest? MCQ 48 26 26 Essay/SAQ 38 44 18 OSCE 43 45 12 Clerkship ratings 21 47 32 Question: Unfair % Undecided % Fair % Which of the following formats is fairest? MCQ 29 28 43 Essay/SAQ 7 25 68 OSCE 4 16 80 Clerkship ratings 16 26 58 Question: Learn very little % Undecided % Learn a lot % From which of the following formats do you learn most? MCQ 28 37 35 Essay/SAQ 12 37 51 OSCE 15 25 60 Clerkship ratings 20 18 62 Question: Used much less % Undecided % Used much more % Which of the following formats should be used more often in the clinical years of the programme? MCQ 31 59 10 Essay/SAQ 9 52 39 OSCE 5 43 52 Clerkship ratings 12 56 32 MCQ – multiple choice question; SAQ – short answer question; OSCE -objective structured clinical examination Thirty-two percent of students felt that the clerkship rating was the easiest, while 48% rated MCQ as a more difficult form of assessment. The OSCE was overwhelmingly considered the fairest assessment format (80%), and essays (68%) to a lesser extent. OSCE (60%) and clerkship ratings (62%) were considered the most useful learning experiences. Compared to the other assessment formats, 52% considered that the OSCE should be used most in the clinical years. Qualitative data Students were asked follow-up questions related to positive and negative aspects of the OSCE and suggestions for improvement. The open-ended responses were grouped by thematic content. Among the positive attributes of the OSCE, students re-affirmed that the assessment was comprehensive (44 comments) and that it was an objective and fair process (43 comments). Some indicated that the opportunity for feedback helped to motivate them and drive the learning process (21 comments). Students felt that the time allocated to perform expected tasks was insufficient (36 comments), and that the procedure was stressful (18 comments) and tiring (13 comments). Technical problems (28 comments) included unclear instructions, inadequate time provision and instructions between stations and detention of some candidates at stations by examiners. Suggestions for improvement included increasing the duration of stations (29 comments), ensuring clear instructions (8 comments) and having more realistic expectations of students for the expected tasks. A few students wished to have more training with the OSCE and suggested that the examination should be videotaped to increase objectivity and permit review. Discussion Students overwhelmingly perceived that the OSCE in Child Health had good construct validity. This was demonstrated by the favourable responses concerning transparency and fairness of the examination process, and the authenticity of the required tasks per station. Excellent levels of acceptance of the OSCE by students have been previously described in the literature [ 11 - 14 ]. They however expressed concerns and uncertainty about whether the process would minimize their chances of failing or that the results were a true reflection of their clinical skills. This was understandable, since it was their first encounter with this type of assessment. Several felt that the examination was stressful and intimidating, yet paradoxically some students perceived it as an enjoyable, practical experience. Studies surveying student attitudes during the OSCE have documented that the OSCE can be a strong anxiety-producing experience, and that the level of anxiety changes little as students progress through the examination [ 15 ]. It is well recognised that assessment is a catalyst for both curriculum change and student learning. The students recognised the value of the instrument for formative evaluation. In addition, as many medical schools have adopted a student-centred approach to medical education, greater student participation in quality assurance exercises must be encouraged. Students perceived the OSCE to be fairer than any other assessment format to which they were exposed. The findings were somewhat similar to the views of students at Newcastle medical school [ 16 ]. Although student views on fairness may not be consistent with published literature, the impact and influence on acceptability of the instrument should be noted. They offered constructive criticism of the structure and organisation of the process. At some stations they felt that the instructions were ambiguous and that the time allocation was inadequate for the expected tasks. The feedback was invaluable and facilitated a critical review and modification of the station content and conduct of the examination over time. Faculty perceived that the concerns about time allocation per station and the degree of stress expressed by the students were due to inadequate preparation for the examination, particularly in competences not previously assessed in the 'traditional' examination. The high student response rate has helped to ensure that the findings presented are a valid representation of student opinion. Students have traditionally viewed the end-of-clerkship assessment as a 'high-stake' examination and also perceive it as predictive of their performance at their final MB examination. Student perception of the OSCE however, may have been influenced by anxiety and lack of confidence associated with a new assessment. The responses may also have been affected by the timing of the inquiry (immediately after the examination); hence student stress and fatigue should be taken into consideration. Whereas the high response rate ensured that the views were reasonable representative of the students, differences in assessors could have influenced the interpretation of the results of open-ended responses. Implementing the OSCE in Child Health at the University of the West Indies, Jamaica has been challenging, however student participation in the evaluation and their overall acceptance of the instrument have been encouraging. Feedback from students and faculty has been useful in effecting improvements to the process and greater emphasis has been placed on the teaching and evaluation of history taking, communication and technical competencies. It is also sending a clear message to students that the achievement of overall competence is imperative to clinical practice in the current environment. Ultimately, these provide the loop necessary to drive the continuum of curriculum development. This has been timely considering that the Faculty of Medical Sciences, Jamaica is undergoing significant reform [ 17 ]. Further developments involving psychometric evaluation will strengthen the process. Conclusions In summary, the findings highlight the need for student participation in the development of new assessment tools in medical curricula. Student acceptance will be more favourable for assessment formats that they perceive to be transparent, authentic and valid. 'Traditional' medical curricula must be responsive to global paradigm shifts in undergraduate medical education. Competing interests The authors declare that they have no competing interests. Authors' contributions RP conceptualised the study; developed the proposal, coordinated the conduct of the project, completed initial data entry and analysis, and wrote the report. AW participated in the design of the study, coordinated the conduct of the project, performed the statistical analysis, and assisted in writing the report. MB was the main organizer of the clerkship OSCE, and assisted in editing the final report. MBr and CC participated in overall supervision of project and revision of report. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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538751

Tongue lesions in psoriasis: a controlled study

Background Our objective was to study tongue lesions and their significance in psoriatic patients. Methods The oral mucosa was examined in 200 psoriatic patients presenting to Razi Hospital in Tehran, Iran, and 200 matched controls. Results Fissured tongue (FT) and benign migratory glossitis (BMG) were the two most frequent findings. FT was seen more frequently in psoriatic patients (n = 66, 33%) than the control group (n = 19, 9.5%) [odds ratio (OR): 4.69; 95% confidence interval (CI): 2.61–8.52] (p-value < 0.0001). BMG, too, was significantly more frequent in psoriatic patients (28 cases, 14%) than the control group (12 cases, 6%) (OR: 2.55; 95% CI: 1.20–5.50) (p-value < 0.012). In 11 patients (5.5%), FT and BMG coexisted. FT was more frequent in pustular psoriasis (7 cases, 53.8%) than erythemato-squamous types (56 cases, 30.4%). On the other hand, the frequency of BMG increased with the severity of psoriasis in plaque-type psoriasis assessed by psoriasis area and severity index (PASI) score. Conclusions Nonspecific tongue lesions are frequently observed in psoriasis. Further studies are recommended to substantiate the clinical significance of these seemingly nonspecific findings in suspected psoriatic cases.

Background The occurrence of psoriatic lesions on oral mucous membranes was a subject of controversy [ 1 , 2 ]. Some investigators stated that they do not occur [ 3 ]; others, have claimed that they are uncommon. Still others say that they occur only in generalized pustular psoriasis (GPP) [ 4 , 5 ]. Nowadays, there is sufficient evidence that a subset of patients have oral lesions in association with skin disease [ 2 ]. Oppenheim, in 1903, was the first to substantiate oral psoriasis with biopsy [ 6 ]. Since then, various lesions have been described, including grey, yellowish, white or translucent plaques or annular forms, diffuse areas of erythema, geographic tongue and fissured tongue [ 7 - 16 ]. In all the cases reported in the literature, a positive biopsy showing a psoriasiform pattern has been the crucial component of the diagnosis [ 5 , 17 - 20 ]. Thus hyperkeratosis, parakeratosis, and an inflammatory infiltrate consisting of lymphocytes, polymorphonuclear leukocytes and histiocytes have been noted as well as Munro's microabscesses and spongiform pustules of Kogoj. In addition, many investigators believe that the presence of cutaneous lesions with a course parallel to that of oral lesions is necessary for establishing the diagnosis of oral psoriasis [ 2 , 5 , 20 ]. However, it is impossible to perform an oral biopsy in psoriatic cases in everyday clinical practice. On the other hand, some of the lesions seen more frequently in psoriatic patients are not specific histologically. In fact, similar changes are seen in otherwise healthy people (although with a lower frequency) leading to an underestimation of the value of these findings in psoriatic patients. In order to substantiate further the relationship between these oral disorders and psoriasis, we compared 200 patients with psoriasis to a matched control group. Methods Two hundred psoriatic patients (70 women and 130 men) attending the dermatology clinics of Razi Hospital, a major referral center in Tehran, from September 2000 till February 2001, were enrolled in this study using simple nonrandom (sequential) sampling. The diagnosis was made mainly on clinical data. The control group included 200 healthy subjects among the visitors of Surgery wards in a general hospital, matched one by one for age and sex. The skin and oral mucosa were examined in the two groups and, in addition to demographic and clinical data, PASI score [ 21 ] was recorded in plaque-type psoriasis. The data were analyzed by Epi-Info (version 6) software, and frequency, mean, standard deviation, OR and p-value were calculated. Results The mean age of the patient group was 33.8+/- 18.2 years (4–79 years). The mean age of onset of disease was 26+/-17.7 years (0–74 years), 23 +/-18.8 years in women and 27.6 +/- 17.0 years in men. Age and sex were matched between patients and control subjects. Family history of psoriasis was positive in 34 patients. Different clinical types of psoriasis were as follows: Chronic plaque-type psoriasis (n = 140); generalized pustular psoriasis (n = 10); flexural psoriasis (n = 10); erythrodermic psoriasis (n = 9); localized pustular psoriasis (n = 3); guttate psoriasis (n = 9); palmoplantar psoriasis (n = 15); scalp (n = 95); nail alone (n = 3). Oral findings were detected in 87 (43.5%) and 39 (19.5%) cases in the psoriatic and control groups, respectively. They are presented in table 1 . FT was seen more frequently in psoriatic patients (66 patients, 33%) than the control group (19, 9.5%) (OR: 4.69; 95% CI: 2.61–8.52) (p-value < 0.0001). BMG, too, was significantly more frequent in psoriatic patients (28 cases, 14%) than the control group (12, 6%) (OR: 2.55; 95% CI: 1.20–5.50) (p-value < 0.012). BMG was seen in 18.2% of patients with FT, and 42.9% of patients with BMG suffered from FT. In other words, in 12 patients (6%) FT and BMG coexisted. In the control group, FT and BMG coexisted in 2 cases (1%). Table 1 The frequency of oral findings in psoriasis patients and control group Psoriasis Control Fissured tongue 66 19 Benign migratory glossitis 28 12 Diffuse oral and tongue erythema 11 3 Hairy tongue 2 4 Rhomboid glossitis 2 3 Depapillated tongue 2 3 One hundred eighty-four patients (92%) suffered from erythemato-squamous lesions and 13 cases (6.5%) from pustular lesions. The frequency of FT in the erythemato-squamous and pustular groups was 30.4% (56 cases) and 53.8% (7 cases), respectively. On the other hand, the frequency of BMG in the erythemato-squamous and pustular groups was 14.1% (26 cases) and 15.4% (2 cases), respectively. The severity of chronic plaque-type psoriasis cases assessed by PASI score was as follows: mild, 53 cases (37.9%); moderate, 60 cases (42.9%); and severe 27 cases (19.3%). The corresponding frequency of FT and BMG in the three severity groups is presented in table 2 . The frequency of BMG increased with the severity of skin lesions (p-value < 0.001). Table 2 Frequency of fissured tongue and benign migratory glossitis according to severity in plaque-type psoriasis Fissured tongue Benign migratory glossitis Mild 14 (26.4%) 3 (5.7%) Moderate 23 (38.3%) 10 (16.7%) Severe 7 (25%) 9 (32.1%) Discussion In general oral lesions in psoriasis can be divided into two major categories. The first one includes authentic psoriatic lesions proved by biopsy and with a parallel clinical course with skin lesions. It's not known whether these lesions are truly rare, or they remain undetected, as mucosal biopsy is seldom done in known psoriatic cases. The second group comprises the majority of oral findings in psoriasis and includes nonspecific lesions such as FT and psoriasiform lesions such as BMG [ 22 ]. These lesions are underestimated in the literature, but deserve more attention due to their high frequency. We will discuss the main oral findings observed in our study as well as those reported in the literature. Fissured tongue, also termed lingua fissurata, lingua plicata, scrotal tongue, and grooved tongue is recognized clinically by an antero-posteriorly oriented fissure, often with branch fissures extending laterally. It's believed by most authors to be an inherited trait. The frequency of FT increases with age and has been associated with Down's syndrome and the Melkerson-Rosenthal syndrome [ 5 , 20 ]. According to our study, FT was the most common oral finding in the psoriasis group: Nearly one-third of patients suffered from FT. It was significantly more frequent in psoriasis patients than the control group (9.5%) (p-value < 0.0001). The previously reported figures of the frequency of FT in the general population vary markedly in the literature depending on the study design and the target study. Axell reported a figure of 6.5% [ 10 ] and Morris found FT in 20.3% of its target study [ 17 ]. Aboyans et al reported a frequency of 2.56% in Iran [ 23 ]. On the other hand, FT was reported in 6–16.7% of psoriatic patients in different studies [ 3 , 10 , 14 , 15 , 20 ]. BMG or geographic tongue presents clinically as one or more erythematous patches with a raised white or yellow serpiginous border. Lesions may migrate across the tongue by healing on one edge while extending on another. BMG has no known cause, but it has been associated with atopic conditions, diabetes mellitus, reactive bronchitis, anemia, stress [ 20 ], hormonal disturbances, Down's syndrome and lithium therapy [ 24 ]. Lesions identical to BMG have been described in patients with Reiter's syndrome and psoriasis. The association of both psoriasis and BMG with HLA-CW6 provides further evidence that the two disorders are related [ 25 ]. In our study, BMG was significantly more frequent in psoriatic patients (14%) than the control group (6%) (p-value < 0.012). According to the literature, the estimated frequency of BMG in the general population is from 1–5% [ 1 , 10 , 20 , 26 ] and varies from 1–10.3% in psoriatic patients [ 3 , 10 , 13 - 15 , 20 , 26 ]. Only Hietanen found a figure of 1% in psoriasis [ 10 ]. FT was more frequent in patients with pustular lesions compared with the erythemato-squamous types. Contrary to previous studies, this finding was not seen for BMG, a disease generally considered accompanied with GPP [ 27 , 28 ]. This may be due to the low frequency of GPP in our study group. On the other hand, the frequency of BMG increased with the severity of psoriasis in plaque-type disease, a finding not seen in Morris's study [ 20 ], perhaps due to different definition for the severity of the disease. According to our study, the frequency of FT didn't increase by increasing severity of psoriasis. SAM was first described by Cooke in 1955 as an idiopathic inflammatory condition of the nonlingual oral mucosa [ 10 , 15 ]. It is also denoted using different terms: Geographic stomatitis, ectopic geographic tongue, erythema circinate migrans, and migratory stomatitis. These lesions are similar in appearance to BMG, but occur on the oral mucosal surfaces as well as the dorsum of the tongue [ 1 , 29 , 30 ]. As seen in Van der Wal's study, [ 14 ] we didn't find SAM in psoriatic patients. The reported frequency of this oral finding in psoriatic patients in the literature is between 0–19% [ 15 , 20 ]. Furthermore, this lesion seems to be very rare in the general population, too: Bouquot found no patients with SAM in 231616 white American dental patients [ 20 ]. Diffuse oral and tongue erythema was another positive finding in the psoriasis group with a frequency of 5.5%. This lesion, too, was reported previously in the literature, although with a lower frequency (1%) [ 10 ]. An association between FT and BMG is well established in the literature [ 31 , 32 ]. In our study, BMG was seen in 18.2% of patients with FT (results consistent with Pindorf's) [ 14 , 16 ]. Conclusions Overall, although oral lesions might not be considered authentic oral psoriasis unless proven histologically and with a parallel clinical course, nonspecific tongue lesions are significantly more frequent in psoriatic cases. Further studies are recommended to evaluate the clinical significance of these seemingly nonspecific lesions in a suspected psoriatic case. Furthermore, more thorough studies are recommended regarding the relationship of oral psoriasis and disease severity in plaque-type psoriasis. Competing interests The author(s) declare that they have no competing interests. Authors' contributions All authors contributed equally in the study design, literature search, data analysis and manuscript preparation. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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Angiogenesis in male breast cancer

Background Male breast cancer is a rare but aggressive and devastating disease. This disease presents at a later stage and in a more advanced fashion than its female counterpart. The immunophenotype also appears to be distinct when compared to female breast cancer. Angiogenesis plays a permissive role in the development of a solid tumor and provides an avenue for nutrient exchange and waste removal. Recent scrutiny of angiogenesis in female breast cancer has shown it to be of significant prognostic value. It was hypothesized that this holds true in invasive ductal carcinoma of the male breast. In the context of male breast cancer, we investigated the relationship of survival and other clinico-pathological variables to the microvascular density of the tumor tissue. Methods Seventy-five cases of primary male breast cancer were identified using the records of the Saskatchewan Cancer Agency over a period of 26 years. Forty-seven cases of invasive ductal carcinoma of the male breast had formalin-fixed paraffin-embedded tissue blocks that were suitable for this study. All cases were reviewed. Immunohistochemical staining was performed for the angiogenic markers (cluster designations 31 (CD31), 34 (CD34) and 105 (CD105), von Willebrand factor (VWF), and vascular endothelial growth factor (VEGF)). Microvascular density (MVD) was determined using average, centre, and highest microvessel counts (AMC, CMC, and HMC, respectively). Statistical analyses compared differences in the distribution of survival times and times to relapse between levels of MVD, tumor size, node status and age at diagnosis. In addition, MVD values were compared within each marker, between each marker, and were also compared to clinico-pathological data. Results Advanced age and tumor size were related to shorter survival times. There were no statistically significant differences in distributions of survival times and times to relapse between levels of MVD variables. There was no significant difference in MVD between levels of the different clinico-pathological variables. MVD was strongly and significantly correlated between AMC, CMC and HMC for CD31, CD34, and CD105 (p < 0.01) and remained moderate to weak for VWF and VEGF. Conclusion Microvascular density does not appear to be an independent prognostic factor in male breast cancer. However, the likelihood of death for men with breast cancer is increased in the presence of increased age at diagnosis and advanced tumor size. This is perhaps linked to inherent tumor vasculature, which is strongly related throughout a tumor section.

Background Invasive ductal carcinoma of the male breast comprises approximately 1% of all breast cancers. Invasive ductal carcinoma of the male breast is distinct from invasive ductal carcinoma of the female breast in both presentation and immunophenotype. Male breast cancer generally presents in older patients and at a more advanced stage than its female counterpart [ 1 - 3 ]. In contrast to female breast cancers, ductal carcinoma in situ is quite rare in men [ 4 , 5 ]. Male breast cancers are also predominantly of the invasive ductal adenocarcinoma, not otherwise specified (NOS) type. Invasive ductal carcinoma of the male breast, despite being a high-grade tumor is more likely to express estrogen receptor and/or progesterone receptor and is less likely to over-express P53 or Erb-B2 when compared to invasive ductal carcinoma in the female breast [ 6 , 7 ]. The combination of a unique male hormonal environment, in addition to the unique immunophenotype, points to a distinct, non-p53-dependant, pathway of tumor progression in the male. Yet, despite these differences, it appears that the overall prognosis for male and female breast invasive ductal carcinomas are similar in age and stage-matched studies [ 1 , 8 - 10 ]. Angiogenesis is the growth and proliferation of blood vessels from existing vasculature. This process is quiescent in normal tissues and becomes active in rapidly growing tissues – including solid tumors. It has been shown that, in order to overcome tissue death by hypoxia, tumor growth beyond 1–2 mm 3 is dependant upon the formation of new vasculature [ 11 ]. Angiogenesis is, thus, an established step in solid tumor progression. This has been studied in many cancers including colorectal cancer [ 12 ] non-small cell lung cancer [ 13 , 14 ], hepatocelullar cancer [ 15 ], melanoma [ 16 ] prostate cancer [ 17 ], breast cancer [ 18 - 24 ] and bladder carcinoma [ 25 ]. Most assessments of angiogenesis in female breast carcinoma have shown it to be of significant prognostic value [ 18 - 22 ]. However, not all studies in this field have observed such important clinical correlations to MVD [ 23 , 24 ]. There are a variety of techniques used to evaluate angiogenesis and the variability between studies is probably related to the varying techniques employed in this process. Invasive ductal carcinoma of the male breast appears to be a unique and biologically different carcinoma [ 1 ]; it is not simply the appearance of female invasive ductal carcinoma in a male breast. Due to the rarity of the disease large cohorts are not readily available, and there is only a limited pool of published data exploring various facets of this important disease. In one study of 26 men with breast cancer, elevated MVD was associated with advanced stage of disease and poor outcome [ 26 ]. Another Japanese study confirms that angiogenesis is part of tumor progression in male breast cancer [ 27 ]. In an attempt to further characterize this rare tumor, the aim of the current study was to evaluate angiogenesis in invasive ductal carcinoma of the male breast by the assessment of microvascular density in tumor samples. Specifically, we investigated three questions: (1) do survival times and times to relapse differ between levels of MVD, demographic, and clinico-pathological variables; (2) do MVD measures differ between levels of demographic and clinico-pathological variables, and finally; (3) are different measures of MVD correlated within a section of tumor tissue? This study is an extension of our established work on immunophenotypic characterization of male breast carcinoma in Saskatchewan [ 6 ]. Patients and methods Patients After obtaining appropriate ethics approval from the University of Saskatchewan Advisory Committee on Human Experimentation, all cases (n = 75) of invasive ductal male breast cancer diagnosed between 1975 and 1997 were selected from the records of the Saskatchewan Cancer Agency. Detailed chart review was performed for cases where paraffin-embedded tissue samples were available (n = 59). After the removal of all cases with inadequate tissue sample, tissue staining and chart data, there remained 47 cases. Clinical and pathological studies Sections were cut from paraffin-embedded tissue samples. The sections were stained with hematoxylin and eosin (H & E). A detailed histopathological assessment was performed. Clinical features were recorded including age at diagnosis, date of birth, node status, tumor size, treatment method, date of relapse, and date of death. Age at diagnosis, tumor size, node status, disease-free survival and overall survival were the clinical variables of interest in this study. Age at diagnosis was determined from the patient chart. Tumor size and node status were determined from the pathology report. Overall survival (number of years patient survived since the diagnosis of invasive breast carcinoma) and disease-free survival (number of consecutive years the patient was alive without breast cancer or other cancer relapse related to the breast carcinoma since the date of diagnosis) were calculated from the information gathered in the chart review. In cases where multiple tissue blocks were available, all H & E sections were examined in order to select a representative tissue block with a large area of invasive tumor and satisfactory tissue integrity. Microvessel density determination MVD determination was modeled after the method described by Kato et al ., [ 18 ] and Weidner et al ., [ 28 ]. Immunohistochemical staining was performed for CD31, CD34, CD105, VWF and VEGF. Staining was carried out on a representative section by the avidin-biotin-peroxidase (ABC) technique after antigen retrieval using appropriate positive and negative controls in all cases. The source and dilution for each antibody are presented in table 1 . Table 1 Source and dilution of antibodies used in this study Antibody Clone Dilution Source Positive Control Negative CD31 JC70A 1/20 Dako Human Tonsil All markers used patient tissue stained in the absence of primary antibody as negative control. CD34 QBEnd10 1/20 Dako Human Tonsil CD105 4G11 1/25 Novacastra Human Tonsil VWF F8/36 1/40 Signet Human Tonsil VEGF Polyclonal 1/20 Zymed Human Colon Cancer CEA Brown-staining areas, whether single endothelial cells or clusters of endothelial cells, regardless of the absence/presence of a lumen were counted as individual microvessels. Vessels that had a thick muscular layer were excluded from the count. Cases were evaluated in a random order. Two observers using a double-headed light microscope simultaneously performed all counts for CD31, CD34, VWF and VEGF. A single experienced observer assessed CD105. Observers were blinded to all clinical and pathological data. Average, central and highest microvessel counts (AMC, CMC, and HMC, respectively) were performed. Ten high power (200×) fields along the border between cancer nests and the stroma were evaluated for each section (figure 1 ). The average number of microvessels per high power field was determined and reported as AMC. Figure 1 Average microvessel count – VEGF. Ten high power (200×) fields along the border between cancer nests and the stroma were evaluated for each section. The average number of microvessels (arrows) per high power field was determined and reported as AMC. After scanning at low power (40×), the central area of the tumor was estimated. From this area, six high power (200×) fields were evaluated for each section (figure 2 ). The average number of microvessels per high power field was determined and reported as CMC. For tumors with a central necrotic area, determination was completed using areas near the centre of the tumor that were viable (non-necrotic). Figure 2 Central microvessel count – VEGF. After scanning at low power (40×), the central area of the tumor was estimated. From this area, six high power (200×) fields were evaluated for each section. The average number of microvessels per high power field was determined and reported as CMC. After scanning at low power (40×), three areas with the highest concentration of microvessels (vascular hot spots) were selected. Each area was evaluated with one high power (200×) field in such a way as to include the maximum number of microvessels (figure 3 ). The highest value obtained among the three fields was reported as HMC. Figure 3 Highest microvessel count – VEGF. After scanning at low power (40×), three areas with the highest concentration of microvessels (vascular hot spots) were selected. Each area was evaluated with one high power (200×) field in such a way as to include the maximum number of microvessels. The highest value obtained among the three fields was reported as HMC. Statistical analysis Analysis was completed using the Statistical Package for the Social Sciences (SPSS) version 11.0 on an IBM PC 300PL computer. All tests were two tailed with the level of statistical significance set at p < 0.05. The demographic and clinico-pathological variables of interest included age at diagnosis (<65 and ≥ 65 years), tumor size (T1 is ≤ 2 cm, T2 is >2 cm but ≤ 5 cm, and T3 is >5 cm) and node status (positive and negative). To compare the distribution of survival times and disease free survival times (time to relapse) we produced Kaplan-Meier curves and made statistical comparisons using the log-rank test between levels of demographic and clinico-pathological variables. In addition to this we dichotomized the MVD variables based on the median and repeated the Kaplan Meier with log-rank analysis to compare survival times and times to relapse between levels of MVD. For comparison of survival times, the outcome of interest was death while the remaining subjects (those surviving to the end of the study period) were censored. For comparison of time to relapse, the outcome of interest was relapse while the remaining subjects (those surviving to the end of the study or those who died before relapse) were censored. Levels of MVD were also compared with levels of demographic and clinico-pathological variables using the Mann Whitney test or Kruskal Wallis test when MVD was considered as a continuous variable and chi squared or Fisher's Exact test when MVD was considered as dichotomous variable. Finally, for each vascular marker (CD31, CD34, CD 105, VWF, and VEGF), correlation between the different measures of MVD (i.e. AMC with CMC, AMC with HMC, and CMC with HMC) was assessed using the Spearman's correlation coefficient. Correlations with a coefficient (ρ) of ≥ 0.80 were considered strong, moderate-strong correlations had coefficients that were <0.80 but ≥ 0.50, moderate-weak correlations had coefficients that were <0.50 but ≥ 0.30, weak correlations had coefficients that were <0.30. Results Age at diagnosis and clinicopathological characteristics In this study of 47 cases of male breast cancer, the median age of diagnosis was 65.9 years with the youngest being 32 years and the oldest being 94 years. The frequency of male breast cancer cases by age is illustrated in figure 4 . As seen in Table 2 , most of the patients had a tumor size of T1 to T2 and were node status negative. Figure 4 Frequency of male breast cancer cases by age. This illustrates the age distribution of male breast cancer patients in this study. This is expressed as a percentage of the total number of patients. Note the predilection for older men. Table 2 Clinico-pathological characteristics and survival of the study population. The adjacent table is a summary of clinico-pathological data of interest in this study. Characteristics No. of cases % Number of patients 47 100 Tumor size, T T1 (≤ 2 cm) 20 43 T2 (>2 cm, ≤ 5 cm) 22 47 T3 (>5 cm) 5 11 Node status N(-) 26 55 N(+) 21 45 Overall survival, years <10 27 64 ≥ 10 15 36 Total evaluated 42 100 Relapse-free survival, years <10 29 69 ≥ 10 13 31 Total evaluated 42 100 Treatment regimens All patients underwent some form of surgical resection – most frequently a modified radical mastectomy. In 31 out of 47 cases, surgical resection was followed by some form of adjuvant therapy (radiotherapy, chemotherapy, hormonal therapy (tamoxifen), or some combination of the aforementioned). Specifically, 6 patients received only radiotherapy, 7 patients received only hormonal therapy and 2 patients received only chemotherapy. For combined therapies, 6 patients received radiotherapy with hormonal therapy, 3 patients received radiotherapy with chemotherapy, 4 patients received hormonal therapy with chemotherapy and 3 patients received all three methods of adjuvant therapy. Patient outcome All cases reviewed in this study came from the records of the Saskatchewan Cancer Agency between 1975 and 1997. Thirty-three of 47 patients (70%) died in the time period considered. Of the remaining 14 patients (30%), 9 (64%) had been followed for 10 years or more and 5 (36%) patients had been followed for under 10 years. Seventeen patients (36%) had documented relapse. The average age at death for patients with relapse was 72 years while the average age at death for relapse-free patients was 78 years. Although 70% of patients did die in this study, thirty-two patients (68%) survived at least 5-years after the diagnosis of breast cancer. The Kaplan-Meier curves relating prognostic variables to death and relapse are illustrated in figure 5 . There were significantly shorter survival times when the age of diagnosis was ≥ 65 years (p < 0.001) and when tumor size was larger (p < 0.01). However, there were no significant differences in the times to relapse by any of the clinical variables. In addition to this, there were no significant differences in survival times or times to relapse for any of the MVD markers when categorized by the median score (Table 3 ). Figure 5 Kaplan Meier curves for clinical variables with time to death (left column) and time to relapse (right column). This figure illustrates the percentage of patients with relapse-free survival across clinical groupings of age, node status and tumor size. Table 3 Results from log rank test based on Kaplan Meier curves for microvascular density variables categorized at their median. The adjacent table reports the test statistic and p-value from the log rank test comparing differences in survival time and time to relapse between different levels of clinico-pathological variables. Death Relapse Log rank test statistic p-value Log rank test statistic p-value VWF AMC 0.04 0.83 0.46 0.50 CMC 0.70 0.40 0.02 0.88 HMC 0.01 0.93 0.45 0.50 CD31 AMC 1.79 0.18 0.05 0.83 CMC 0.36 0.55 0.00 0.98 HMC 0.15 0.70 0.60 0.44 CD34 AMC 0.19 0.67 0.91 0.34 CMC 0.19 0.66 0.37 0.54 HMC 0.08 0.78 0.30 0.59 CD105 AMC 0.59 0.44 0.01 0.93 CMC 0.10 0.75 0.70 0.40 HMC 0.23 0.63 0.06 0.80 VEGF AMC 0.21 0.65 0.32 0.57 CMC 1.70 0.19 0.44 0.51 HMC 0.47 0.49 0.25 0.61 Microvascular density and clinical variables Regardless of whether MVD was considered as a continuous variable or as a categorical variable, there were no significant differences in MVD by demographic (age group) or clinico-pathological features (tumour size or node status) although some of the differences may be clinically important. Table 4 provides median values of MVD markers at different levels of clinico-pathological variables. Table 4 Microvascular density levels at various levels of clinico-pathological variables. The adjacent table reports median MVD levels at different levels of clinico-pathological variables. None of the comparisons are statistically significant Age group Tumor size Node status <65 years <65 years T1 T2 T3 Negative Positive VWF AMC 15.6 (5.7) 15.0 (5.8) 15.8 (5.5) 13.5 (5.3) 17.5 (27.9) 14.2 (5.2) 15.6 (5.2) CMC 53.7 (24.7) 47.2 (50.2) 44.8 (30.5) 50.3 (43.7) 67.5 (40.3) 48.5 (39.8) 50.0 (35.6) HMC 84.0 (50.3) 70.0 (48.5) 86.5 (48.6) 69.0 (58.5) 70.0 (41.8) 84.0 (53.5) 69.3 (44.0) CD31 AMC 5.9 (20.9) 14.5 (28.8) 6.8 (28.6) 11.4 (30.5) 15.4 (61.7) 7.2 (17.9) 10.4 (32.6) CMC 18.8 (41.4) 26.2 (28.6) 15.7 (38.0) 29.3 (28.9) 20.7 (81.0) 17.9 (33.7) 32.5 (36.5) HMC 36.5 (44.8) 38.0 (27.0) 28.0 (40.0) 43.6 (22.3) 30.0 (107.4) 35.9 (40.0) 43.0 (42.6) CD34 AMC 19.7 (9.6) 19.8 (10.5) 21.0 (9.0) 17.3 (11.5) 20.0 (81.8) 18.8 (8.3) 19.9 (11.4) CMC 52.0 (21.8) 41.3 (35.0) 43.3 (29.4) 52.0 (34.2) 48.5 (46.5) 47.2 (35.0) 50.7 (29.0) HMC 89.0 (50.5) 70.0 (77.0) 79.0 (54.3) 86.0 (83.1) 88.0 (79.2) 90.0 (63.3) 70.0 (60.9) CD105 AMC 2.7 (4.4) 4.4 (4.3) 2.7 (3.8) 4.4 (5.4) 5.4 (10.0) 3.0 (4.7) 4.0 (3.6) CMC 8.8 (14.3) 10.7 (13.2) 7.0 (13.8) 10.9 (14.9) 14.3 (31.7) 9.2 (14.5) 10.2 (10.6) HMC 29.0 (24.5) 32.0 (34.5) 28.5 (30.3) 30.5 (49.3) 39.0 (156.0) 26.5 (33.0) 31.0 (20.0) VEGF AMC 7.5 (20.0) 17.9 (25.1) 11.9 (25.5) 15.4 (26.8) 5.8 (64.9) 13.4 (21.8) 13.2 (29.2) CMC 42.5 (47.0) 39.4 (33.6) 47.5 (72.9) 40.8 (39.5) 36.3 (45.6) 41.1 (45.1) 42.3 (58.8) HMC 58.8 (103.1) 80.0 (87.6) 70.3 (113.6) 66.0 (79.1) 80.0 (55.9) 69.8 (86.2) 79.0 (92.8) None of the differences between levels of age or clinico-pathological variables are statistically significant Microvascular density within individual markers Measures of MVD (AMC, CMC and HMC) were compared within each marker. These correlations are illustrated in figure 6 . Figure 6 Microvascular density correlations within each marker. This figure illustrates all the relationships between the different methods of MVD measurement for each marker. CD31 Significant correlations (p < 0.01) were observed between all methods of measure (AMC correlates with CMC, CMC correlates with HMC, and HMC correlates with AMC) for CD31. The correlations between AMC and CMC, and AMC and HMC were moderate-strong (ρ = 0.76 and ρ = 0.60 respectively); the correlation between CMC and HMC was strong (ρ = 0.88). CD34 Significant correlations (p < 0.01) were observed between all methods of measure (AMC correlates with CMC, CMC correlates with HMC, and HMC correlates with AMC) for CD34. All correlations were moderately-weak or moderate-strong (ρ = 0.45 for AMC and CMC, ρ = 0.41 for AMC and HMC, and ρ = 0.77 for CMC and HMC). CD105 Significant correlations (p < 0.01) were observed between all methods of measure (AMC correlates with CMC, CMC correlates with HMC, and HMC correlates with AMC) for CD105. The correlations between AMC and CMC, and AMC and HMC were moderate-strong and moderate-weak (ρ = 0.62 and ρ = 0.49 respectively); the correlation between CMC and HMC was strong (ρ = 0.82). VWF A significant correlation (p < 0.01) was observed between CMC and HMC for VWF. A trend correlation (p < 0.10) was observed between AMC and HMC. Correlations were moderate-weak and weak (ρ = 0.47 and ρ = 0.25 respectively). There was no significant relationship between AMC and CMC for this marker. VEGF Significant correlations (p < 0.01) were observed between AMC and CMC, and between CMC and HMC for VEGF. Correlations were moderate-weak and moderate-strong (ρ = 0.43 and ρ = 0.68 respectively). There was no significant relationship between AMC and HMC for this marker. Discussion The markers VEGF also called vascular permeability factor (VPF) is an important angiogenic activator, for both physiological and pathological angiogenesis [ 29 , 30 ], and it may be associated with inflammation. VEGF plays an essential role in embryonic vasculogenesis and angiogenesis [ 31 , 32 ]. It has also been implicated in postnatal development of the glomerulus [ 33 , 34 ] and endochondral bone [ 35 , 36 ]. VEGF mRNA has been shown to be up-regulated in the majority of human tumors investigated [ 37 ], and carcinoma of the human breast is one of these. [ 38 , 39 ]. In addition, VEGF has been implicated in psoriasis [ 40 ], brain edema [ 41 ], polycystic ovary syndrome [ 29 ], age-related macular degeneration (AMD) and other intraocular neovascular syndromes [ 42 - 44 ] The expression of VEGF is triggered by hypoxia. That is to say, low oxygen tension provokes VEGF mRNA expression [ 45 ]. An excellent review of CD105 and its involvement in angiogenesis has been written by Duff et al ., [ 46 ]. CD105 (endoglin) is commonly expressed by angiogenic endothelial cells [ 46 - 48 ]. CD105 is an important pro-angiogenic factor. Transforming growth factor β exerts an inhibitory influence on cell proliferation, migration and microvessel formation. The suppressive effect of CD105 on transforming growth factor β, thus, contributes to angiogenesis [ 49 ]. It is, therefore, no surprise to observe elevated CD105 expression in various tumor endothelia [ 50 - 52 ], including breast cancer [ 53 ]. CD105 may be shed into the blood stream. The measure of serum endoglin appears to provide important prognostic information in cancer patients [ 54 , 55 ]. CD31 is an important part of the endothelial intercellular junction [ 56 ] and it plays a crucial role in leukocyte migration through vascular endothelial intracellular junctions [ 57 - 59 ]. This molecule is at least partially responsible for the adhesion between leucocytes/endothelial cells, leucocytes/platelets, and endothelial cells/endothelial cells [ 57 , 60 - 65 ]. This adhesion is likely the result of CD31-CD31 [ 66 ] interactions (homophilic interactions) although adhesion between CD31 and other components of the cell membrane has been demonstrated (heterophilic interactions) [ 61 , 67 - 70 ]. CD31 also exhibits signal transduction; its dimerization appears to upregulate integrin function [ 71 ]. This molecule appears to be involved in thrombosis, angiogenesis, wound healing, and inflammation [ 61 ]. CD31 is known to be a co-signal transducer for macrophages, inducing respiratory burst. CD34 is a glycosylated type I transmembrane protein [ 72 ] which is expressed on hematopoietic stem cells, committed hematological progenitor cells [ 73 - 75 ], small vessel endothelial cells [ 76 , 77 ], tumors of epithelial origin [ 78 , 79 ] and a limited number of other cell populations including some haematological malignancies [ 72 ]. As specific ligands are still undefined, the precise role CD34 plays in early hematopoiesis remains uncertain. It is thought that differential splicing of sugar residues on CD34 may permit it to host a variety of ligands under different conditions [ 80 ]. Despite our meager understanding of this complex molecule there is evidence indicating that hematopoietic CD34 plays a role in modulating adhesion (this has been reviewed previously [ 72 ]). Factor VIII related antigen, or von Willebrand factor (VWF), is a plasma protein produced by endothelial cells [ 81 , 82 ]. VWF is also present in platelets, as it is produced by their megakaryocytic precursor [ 83 ]. VWF is a multifunctional protein. It is known to mediate adhesion/aggregation of platelets in clot formation (reviewed in [ 84 ]). In addition to this, VWF acts as a chaperone for circulating factor VIII. About 1 – 2% of VWF is bound by factor VIII [ 85 ]. This non-covalent bond prolongs the survival of factor VIII in the plasma. When the coagulation cascade is triggered, thrombin cleaves the complex, thereby freeing factor VIII to participate coagulation [ 86 ] (reviewed in [ 87 ]). Age at diagnosis Male breast cancer is a disease of older men. The likelihood of this occurring in older men that is illustrated in this study is not surprising as this is the case for most studies of e breast cancer in males [ 88 , 89 ]. As mortality from common conditions (e.g. cardiovascular disease) within this group improves due to advances in treatment/intervention and a larger proportion of the population enters this age group, it seems that the relative incidence of male breast cancer is likely to rise. Such is the finding in a recent meta-analysis of male breast carcinoma [ 1 ]. Survival In this study, 70% of the reviewed patients died. Though this number may seem high, only half of those who died had documented relapse prior to the time of death. There is, however, an interesting difference between average age at death for relapsed and relapse-free patients, 72 years versus 78 years respectively. It appears that male breast cancer is contributing to mortality, but this study did not examine the effects of co-morbid conditions. The expected life remaining for a 65 year old male in Saskatchewan between 1995 and 1997 was 16.7 years (expected age approximately 82 years) [ 90 ]. Increased tumor size increases the likelihood of death for male breast cancer patients in this study (figure 5 ). One possible explanation for this relationship is as follows: a tumor's size may be a function of its rate of growth and time of growth; these characteristics seem likely to increase the opportunity for relapse and metastasis. Thus, we might expect large tumors to relapse more frequently than small ones, and therefore, also contribute to death. It appears that younger patients had a significantly better chance of not experiencing death (figures 5 ). This phenomenon is possibly related to improved response to treatment in younger patients; alternatively, this relationship may be demonstrating that younger patients are diagnosed with less advanced disease and vice versa. Evidence supports advanced age [ 88 , 89 ] and tumor size [ 91 ] as important negative prognostic factors. This study was not able to clearly demonstrate statistically significant differences in survival for node status. In the available literature axillary node status is an important prognostic factor [ 91 - 94 ]. Microvascular density, though it was the primary focus of this study, did not demonstrate statistically significant association with survival, demographic or clinico-pathological features. However, we cannot discount the importance of angiogenesis in tumor progression. The lack of correlation in this study may have been influenced by the lack of statistical power, the methods used, the age of the tissue, advanced stage of disease at presentation and method of analysis. In most tumors studied, MVD has been identified as a prognostic factor and has had important correlations to clinical variables [ 12 - 16 ]. In most studies where angiogenesis has been evaluated in cancer of the female breast, MVD is an important prognostic factor [ 19 - 22 ]. In one study of male breast cancer using CD34 to highlight vessels, it was concluded that MVD was an important prognostic tool [ 26 ]. In an angiogenesis methodology study of 109 women with breast cancer by Kato et al ., [ 18 ] it was found that CMC and HMC did not correlate to clinico-pathological variables other than peritumor vascular invasion. AMC was found to have prognostic value. The methods used to report microvessel density were modeled after this work by Kato et al , [ 18 ]. Despite a lack of strong evidence, in our study, to support angiogenesis as an independent prognostic factor, there is no evidence to disprove angiogenesis plays a critical role in tumor development. As angiogenesis remains a likely step in tumor progression, we must continue to recognize this process as a potential target for anti-tumor therapy. Microvascular density within each marker There were some important correlations between the different methods of measure for MVD (AMC, CMC and HMC) within the various markers. CD31, CD34 and CD105 were the strongest in this regard with correlations that were very significant (p < 0.01) and correlations that were usually moderate to strong. The correlations within VWF and VEGF were not all significant, and the relationship was moderate to weak. It could also be that VWF and VEGF are differentially expressed in male breast cancer tissue. This seems to be the case for VEGF. In fact, it was observed that VEGF had a propensity to be over-expressed in regions where there were invading lymphocytes. This may produce a patchy pattern of expression, which could have an important effect on microvessel counts. For the most part, this study saw strong correlations between the various microvessel count methods within the markers. Critics may suggest that evaluation of microvascular density for prognosis in tumors is flawed because, within a tumor, microvascular density is heterogeneous [ 24 , 95 ]. However, the correlations observed in this study support the notion that tumor vasculature is predictable (but not ubiquitous or necessarily homogeneous) from the centre, periphery and vascular hotspot of a tumor. Notably, similar research in female invasive ductal carcinoma of the breast using VWF MVD assessment techniques also demonstrated correlation between central, peripheral and highest microvessel densities [ 18 ]. Microvessel determination, by the methods used in this study, is dependant on a predictable pattern of vasculature within a tumor. Such predictability allows for practical (in terms of time, money and ease of use) application of important clinical prognostic features of the markers. Further research to examine the relationship between these markers in cancer is wanting. Such information may prove important in improving the prognostic value of MVD determination. Conclusion From this evaluation of angiogenesis in male breast cancer, we can draw the following conclusions: Microvascular density does not appear to be an independent prognostic factor in male breast cancer. Tumor vasculature (as measured by microvessel determination using antibodies to endothelial markers such as CD31, CD34, CD105) is strongly related throughout a tumor section (p < 0.01). Other endothelial markers such as VWF and VEGF appear to have a moderate to weak relationship. Advanced age at diagnosis and increased tumor size increases the likelihood of death for men with breast cancer. Abbreviations AMC Average microvessel count CD# Cluster designation or cluster of differentiation (CD31, CD34, CD105) CMC Central microvessel count HMC Highest microvessel count MVD Microvessel density TNM Tumour nodes metastasis VEGF Vascular endothelial growth factor VWF Von Willebrand factor Competing interests The authors declare that they have no competing interests. Authors' contributions EF wrote this manuscript, aided in collection and analysis of data and is the first author. JL provided statistical analysis of the collected data. RK conceived the design of this study, aided in data collection and remains the corresponding and senior author. All authors have read and approved this manuscript.

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517942

Phenotypic plasticity of fine root growth increases plant productivity in pine seedlings

Background The plastic response of fine roots to a changing environment is suggested to affect the growth and form of a plant. Here we show that the plasticity of fine root growth may increase plant productivity based on an experiment using young seedlings (14-week old) of loblolly pine. We use two contrasting pine ecotypes, "mesic" and "xeric", to investigate the adaptive significance of such a plastic response. Results The partitioning of biomass to fine roots is observed to reduce with increased nutrient availability. For the "mesic" ecotype, increased stem biomass as a consequence of more nutrients may be primarily due to reduced fine-root biomass partitioning. For the "xeric" ecotype, the favorable influence of the plasticity of fine root growth on stem growth results from increased allocation of biomass to foliage and decreased allocation to fine roots. An evolutionary genetic analysis indicates that the plasticity of fine root growth is inducible, whereas the plasticity of foliage is constitutive. Conclusions Results promise to enhance a fundamental understanding of evolutionary changes of tree architecture under domestication and to design sound silvicultural and breeding measures for improving plant productivity.

Background The use of chemical fertilizers has been responsible for dramatic increase in the stem wood production of forest trees [ 1 - 4 ]. In an 8-year-old stand of loblolly pine growing on an infertile site in Scotland County, North Carolina, for example, stem volume increment increased 152% after the fourth year of fertilization treatment [ 4 ]. However, little is known about the mechanistic basis for such favorable effects of fertilization. One hypothesis is that improved nutrient availability leads to increases in leaf area growth and photosynthetic capacity, thus producing more photosynthate that can be allocated to the stem wood. This hypothesis has been supported by a number of physiological studies [ 5 - 7 ] and used as a conceptual model for plant nitrogen acquisition and cycling [ 8 ]. However, forest trees can consume as much as 60–80% of annual net primary productivity in the turnover of fine roots [ 3 ]. Fine roots are a tissue with high maintenance respiration tissue whose primary function is to absorb and metabolize water and nutrients from the soil [ 9 - 12 ]. A number of previous studies have shown that the production of fine roots is sensitive to the availability and distribution of nutrients within the soil [ 1 , 4 , 13 , 14 ]. In this study, we test a second hypothesis that the capacity of fine roots to respond to nutrient availability, referred to as phenotypic plasticity , can potentially increase forest-tree productivity. Phenotypic plasticity is the potential of an organism to alter its phenotype in changing environments [ 15 - 19 ]. Phenotypic plasticity may play an important role in plant adaptation and evolution by combining a physiological buffering to poor environmental conditions with an improved response to favorable conditions [ 20 ]. The understanding of how phenotypic diversity is generated by the coherent change of other integrated traits is a key challenge in evolutionary biology. In much plant literature, studies of adaptive phenotypic plasticity have focused mainly on morphological and fitness traits above ground [ 16 ]. It is unclear how phenotypic plasticity exerts a significant effect on plant growth and production through the alteration of root systems below ground. Studies strongly suggest that plant root systems are adapted to different environments [ 14 ], and their diversity represents one important form of morphological evolution [ 12 ]. Fine roots are unique organs with great environmental and developmental plasticity which are subject to strong natural selection and are amenable to genetic and developmental study [ 10 ]. Loblolly pine is the most important tree species for fiber production in the southern US [ 21 ]. Because of its wide natural distribution from the moist Atlantic Coastal Plain to the dry "Lost Pines" region of Texas, this species displays strong adaptability to a range of environmental conditions. However, detailed ecophysiological and developmental mechanisms for the adaptive response of loblolly pine from a perspective of fine roots remain unknown. In the study, we integrate the conceptual theory of phenotypic plasticity into the test of the hypothesis that the reduced production of fine roots under high fertilization can increase stem productivity in loblolly pine. Results and Discussion After 4 weeks of treatment, trees receiving the high nutrient treatment displayed 22% ("xeric") and 47% ("mesic") greater stem biomass than those under the low fertilizer treatment ( P < 0.001). These values increased to 102% and 199% for these two ecotypes, respectively, when the trees were treated for 14 weeks ( P < 0.001). Allometric analysis was used to evaluate the influences of foliage and fine-root biomass partitioning on stem growth which arise from differences in nutrient supply. On both harvesting dates, the proportion of foliage biomass to total plant biomass increased markedly, whereas the proportion of fine root biomass decreased significantly, with better nutrient supplies. As an illustration, we use Figure 1 to demonstrate the phenotypic plasticity of stem growth (Fig. 1A ) and biomass partitioning between two treatments (Fig. 1B ) on the second harvesting date. However, the degree of plasticity, defined as the absolute difference between the two treatments [ 16 ], was strikingly greater for the fine-root proportion than foliage proportion, especially for the "xeric" ecotype. The significance levels for the treatment effect on stem biomass decreased when the proportion of foliage or fine-root biomass was held constant ( P < 0.01), as compared to the significance level when the proportion was not held constant ( P < 0.0001). These dependent relationships suggest that increased stem biomass due to better nutrient supplies was attributable to both increased foliage investment and decreased energetic costs of fine root construction. Figure 1 Different plant performance under the low and high nutrient treatments measured at 14 weeks of treatment. ( A ) Stem biomass. ( B ) The proportions of foliage (open bars) and fine-root (solid bars) biomass to total plant biomass. We analyzed genetic differences in how foliage and fine-root biomass partitioning affect stem biomass through changes in nutrient level. We used correlations of family means in the two treatments to calculate path coefficients of the nutrient-induced plasticity of foliage and fine-root biomass partitioning to the plasticity of stem biomass. For "mesic" families, the plasticity of foliage biomass partitioning did not give rise to a change in stem biomass ( p y ←1 = -0.09), whereas the plasticity of fine-root biomass partitioning, i.e ., decreased partitioning of biomass to fine roots under higher fertilization, had a significant impact on the corresponding increase of stem biomass ( p y ←2 = - 0.99, Fig. 2A ). For "xeric" families, both increased biomass partitioning to foliage and decreased partitioning to fine roots as a consequence of more nutrients favorably affected stem biomass. The path coefficients derived from foliage and fine-root biomass partitioning accounted for most of the variation in stem biomass as indicated by a small residual effect (0.09–0.12), suggesting that no additional traits are required to explain stem biomass. Results from path analysis suggest that the two ecotypes have different physiological mechanisms that determine the nutrient-dependent influences of foliage and fine-root biomass partitioning on stem growth. Figure 2 Path diagrams representing the cause-and-effect relationship between the two predictor variables, foliage biomass and fine-root biomass proportions, and the response variable, stem biomass, that results from differences in nutrient supply. The variable residual is the undetermined portion. p and r denote path coefficients and correlation coefficients, respectively. Foliage and fine roots have complementary roles in uptake of resources; the former in energy and carbon uptake and the latter in water and nutrient uptake [ 12 , 22 ]. Mechanistic modeling of resource uptake suggests that the most efficient deployment of plant biomass is to form minimal fine roots that supply water and nutrients for the production of maximum leaf area [ 11 ]. However, there are important trade-offs in generating few fine roots. We used the ratio of foliage biomass to fine-root biomass (RFF) as an architectural trait to describe the allocation of biomass within ephemeral tissues. This ratio reflects the degree to which plants display a balance of resource investment vs. resource acquisition. It was highly plastic to nutritional levels and tree development. The ratio was larger in the high nutrient treatment (RFF = 6.0–7.0) than in the low treatment (RFF = 3.0–3.5). Under the higher nutrient treatment, trees tended to invest increased energy on foliage with their growth. All these trends differed between the two ecotypes, as shown by significant interaction effects between ecotypes, treatments and harvesting dates ( P < 0.001). Plasticity between different growth stages indicates the dependence of plastic responses on the timing and sequences of developmental events. Ecotypic variation in developmental plasticity represents different genetic bases involved in relevant developmental events [ 23 ]. Ecotypic differentiation of loblolly pine could be explained by limits of plasticity. Quantitative evolutionary genetic models predict that the phenotypic plasticity of a trait is costly or physiologically limiting when the trait is forced to respond to environmental variation ("passive" response). DeWitt et al. [ 24 ] delineated five costs (maintenance costs, production costs, information acquisition costs, developmental stability costs and genetic costs) and three limits (information reliability limits, lag-time limits and developmental range limits) of plasticity. A limit of plasticity occurs when facultative development cannot produce a trait mean as near the optimum as can fixed development. A negative relationship between the degree of plasticity and the fitness residuals (calculated from the regression of fitness on mean phenotype) identifies a limit of plasticity. Our analysis suggests that the plasticity of fine-root biomass proportion is physiologically limiting, whereas the plasticity of foliage biomass proportion is not. The relationship of the shoot biomass residuals was positive with the degree of plasticity of foliage biomass proportion (Fig. 3A ), but negative with the degree of plasticity of fine-root biomass proportion (Fig. 3B ). Thus, when nutrient supply changes, foliage and fine roots will respond in different ways, with the former in a constitutive (active) way and the latter in an inducible (passive) way [ 24 ]. For both "xeric" and "mesic" ecotypes, the families that reduced fine root biomass the least had the highest stem biomass on the high nutrient treatment. Larger limits of fine-root plasticity for "xeric" than "mesic" (Fig. 3B ) could explain why the stronger plasticity of fine root growth for the former ecotype did not result in more stem growth as expected (see Fig. 1A ). Perhaps, for these "Lost Pines" from infertile sites, under improved nutritional conditions there is strong conflict between energetic savings due to reduced fine root production and energetic costs associated with higher efficiency of absorbing and metabolizing nutrients with fewer fine roots. Figure 3 The relationships of shoot biomass residuals with the degree of the plasticity of biomass partitioning to foliage ( A ) and fine roots ( B ). In this study, shoot biomass is used as a surrogate of fitness, because great capacity of vegetative growth at early stages is advantageous for competing for growth resources and is suggested to be favored by natural selection [15]. The residuals of shoot biomass were calculated by differences between its observations and predictions estimated from foliage and fine-root biomass proportions using polynomial equations (see ref. 24 for a detailed description of this calculation approach). The degree of plasticity was represented as family difference between the nutrient treatments. Forest tree form (biomass partitioning) is highly plastic in response to changes in nutrient levels. The carbon budgets for forest trees show a surprisingly large role of roots. Under low nutrient conditions that predominate in natural forests, 60–80% of photosynthate is allocated below ground, compared with 30% for high nutrient levels [ 3 ]. Our path analysis for loblolly pine seedlings showed that phenotypic plasticity of roots had a major influence on the plasticity of stem biomass, supporting the hypothesis that roots play a crucial role in forest productivity. Current selections when grown on high nutrient sites could have relative proportions of roots and stems and foliage that are unfavorable for high yield. Progress towards domestication in trees will be slowed by long generation times, but is likely to be based on the exploitation of interactions between genotypes and yield associated with various types of agronomic methods (e.g., fertilizer levels), as have been shown for herbaceous crop plants. However, the environmental uncertainties during the long life span of trees have caused some breeders to consider the value of plasticity as a trait itself. And plasticity could obscure the relationship between phenotype and genotype, making selection less efficient. Efforts to domesticate forest trees will be enhanced by a deeper knowledge of phenotypic plasticity [ 20 ]. Conclusions Our study of biomass partitioning in relation to varying nutritional levels in loblolly pine supports the previous hypothesis, proposed by Linder and Axelson [ 1 ], that the reduced production of fine roots under fertilization results in the increase of stem production through the optimal use of energy. Yet, supporting this hypothesis does not imply that we should reject a more commonly accepted hypothesis that greater plant production due to fertilization stems from increased foliage and photosynthetic capacity. We explained the discrepancy of these two hypotheses from an ecophysiological perspective using a well-established conceptual model of phenotypic plasticity. The pattern of biomass partitioning is under environmental control and exhibits considerable ecotypic differentiation for the best utilization of available resources. In this study, we observed that biomass partitioning in loblolly pine is also under ontogenetic control, as well documented in other species [ 25 , 26 ]. Although our study of fine roots was performed using young loblolly pine seedlings in controlled conditions, results promise to enhance a fundamental understanding of evolutionary changes of tree architecture under domestication and to design sound silvicultural and breeding measures for improving plant productivity. Methods Plant material Phenotypic plasticity was evaluated for fine roots and biomass partitioning of a commercially important forest tree species, loblolly pine ( Pinus taeda L.). We used two contrasting loblolly pine ecotypes from regions that differ in soil resource availability. One of the ecotypes, known as the "Lost Pines" of Texas, is adapted to droughty conditions and low soil fertility and is denoted by "xeric", whereas the other, Atlantic Coastal Plain, is adapted to more moderate conditions and is denoted by "mesic". Adaptive differentiation between the contrasting "xeric" and "mesic" ecotypes has been previously characterized [ 21 ]. In May 1997, the seeds from the two ecotypes of loblolly pine were germinated in vermiculite, the seedlings were transplanted to 40 cm deep by 20 cm diameter plastic pots filled with pure sand, and placed in an open site at the Horticulture Field Laboratory at North Carolina State University, Raleigh. Pine seedlings from each ecotype were assigned to two different treatments: low nutrients and high nutrients [ 4 ]. The experiment was laid out in a complete randomized design with two different nutritional treatments and with five half-sib families from each ecotype in each level (8 seedlings were included per family per ecotype in each treatment). The seedlings in the high nutrient regime were fertilized at 50 ppm N solution (Peters 15-16-17) every morning, and those in the low nutrient level at 10 ppm N every other morning. The two treatments received the same amount of water. Half of the trees were harvested after 4 weeks of treatment, whereas the other half, after 14 weeks of treatment. Plants were separated into foliage, branches, stem, tap root, coarse roots and fine roots. Fine roots are defined as those of diameter ≤ 2 mm. Data analysis The differences of stem biomass between the two nutritional levels were statistically analyzed using an allometric model that characterizes allometric relationships between plant parts and wholes. The model is based on an exponential function, y = ax b , where x and y are total plant biomass and stem biomass, respectively, and a and b represent the coefficient and exponent of the allometric equation, respectively [ 27 ]. Path analysis was used to identify the cause-effect relationships in a complex system [ 28 ]. Path analysis partitions the correlation of component traits with a yield trait into two parts, direct and indirect. We performed path analysis to detect the direct and indirect effects of the plasticity of foliage biomass and fine root biomass on the plasticity of stem biomass. The path coefficients for foliage biomass ( p 1← y ) and fine root biomass ( p 2← y ) to stem biomass through the change of nutritional levels were estimated by solving the following regular equations: p 1← y + r 12 p 2← y = r 1 y r 12 p 1← y + p 2← y = r 2 y where r 1 y and r 2 y are the family correlation coefficients of the plasticity of foliage biomass and fine-root biomass with the plasticity of stem biomass, respectively, and r 12 is the family correlation coefficient between the plasticity of foliage biomass and fine-root biomass. Residuals were estimated to evaluate the degree of determination for the path analysis [ 28 ]. All data analyses were performed using software SAS (SAS Institute 1988). Authors' Contributions RW designed the study, carried out the experiment, analyzed the data and drafted the manuscript. JEG participated in the experiment. SEM participated in the design of the study. DMO participated in the design and coordination. All authors read and approved the final manuscript.

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