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555947

Could flies explain the elusive epidemiology of campylobacteriosis?

Background Unlike salmonellosis with well-known routes of transmission, the epidemiology of campylobacteriosis is still largely unclear. Known risk factors such as ingestion of contaminated food and water, direct contact with infected animals and outdoor swimming could at most only explain half the recorded cases. Discussion We put forward the hypothesis that flies play a more important role in the transmission of the bacteria, than has previously been recognized. Factors supporting this hypothesis are: 1) the low infective dose of Campylobacter ; 2) the ability of flies to function as mechanical vectors; 3) a ubiquitous presence of the bacteria in the environment; 4) a seasonality of the disease with summer peaks in temperate regions and a more evenly distribution over the year in the tropics; 5) an age pattern for campylobacteriosis in western travellers to the tropics suggesting other routes of transmission than food or water; and finally 6) very few family clusters. Summary All the evidence in favour of the fly hypothesis is circumstantial and there may be alternative explanations to each of the findings supporting the hypothesis. However, in the absence of alternative explanations that could give better clues to the evasive epidemiology of Campylobacter infection, we believe it would be unwise to rule out flies as important mechanical vectors also of this disease.

Background Campylobacter infection is a zoonotic disease, observed in most parts of the world. The disease is caused by Campylobacter jejuni , or less commonly Campylobacter coli . It is estimated to cause 5–14% of diarrhoea, worldwide [ 1 ], and also in the Western world Campylobacter infection has emerged to be the most important bacterial cause of gastrointestinal infection. Animals (variety of fowl, swine, cattle, sheep, dogs, cats, and rodents) are the major reservoir for the bacteria. Campylobacter does not easily grow in food, but the critical infective dose is low [ 2 ]. Unlike salmonellosis with well-known routes of transmission, the epidemiology of campylobacteriosis is still largely unclear [ 3 ]. Known risk factors for the disease include ingestion of undercooked meat, contaminated food and water or raw milk, direct contact with pets, farm animals and small children, and swimming in lakes, but also travel abroad [ 2 , 4 - 6 ]. Direct person-to-person transmission between adults appears to be uncommon. In temperate regions, campylobacteriosis has a distinct seasonal pattern, with the peak incidence in the summer months [ 3 , 5 , 7 , 8 ]. Identified risk factors for Campylobacter infections, that may coincide with the summer peaks in the temperate regions include direct animal contact, eating barbecued meals, swimming in lakes, and drinking untreated water from streams and other natural sources [ 4 - 6 , 9 ]. However, all these factors could at most explain 50% of the sporadic cases [ 3 ]. Instead we put forward the hypothesis that flies play a more important role in the transmission of the bacteria, than has previously been recognized. Discussion The fly hypothesis The common houseflies ( Musca domestica ) and other muscid flies thrive in excreta and other filth. They could act as mechanical vectors, by carrying bacteria on the hairs and surface of their bodies or on the glandular hairs on their feet, but they could also act as biological vectors by passage through the alimentary tract, where pathogens have opportunity to multiply [ 10 ]. The houseflies are important mechanical vectors in the transmission of many infectious diseases with low infective dose, such as shigellosis, typhoid fever and E. coli infection [ 11 , 12 ]. Fly control has shown to be effective in preventing childhood diarrhoea in Pakistan and The Gambia [ 13 , 14 ], and shigellosis in Israeli Army personnel [ 15 ]. Already in 1983, Rosef and Kapperud postulated that flies might play a linking role by transmitting Campylobacter from animals to human food [ 16 ]. Since then several researchers have unravelled the role of flies in the epidemiology of avian campylobacteriosis [ 17 - 19 ], but the idea of flies as important vectors for human Campylobacter infection has been largely neglected [ 20 ]. Six factors speak in favour of our hypothesis. 1. Infective dose The infective dose of Campylobacter can be as low as 800 bacteria [ 21 ], which is in the same magnitude as that of Shigella spp, Salmonella Typhi, and E. coli , pathogens that are known to be transmitted by flies [ 11 , 12 , 15 ], and much lower than the infective dose of Vibrio cholerae (10 8 bacteria), and non typhoidal Salmonella species (10 5 -10 10 bacteria). Although less tolerant to desiccation than some other food-borne pathogens [ 22 ], Campylobacter can survive on dry surfaces for at least seven days [ 23 ], thus enabling the bacteria to survive for several days both on the body of the fly and in desiccated fly faeces. 2. Flies as a possible vector Studies have shown that Campylobacter could easily be transmitted from the environment to flies [ 17 , 24 ], and thus making flies a reservoir for the bacteria. Campylobacter could also be transmitted from flies to chickens [ 19 ]. In a recent study, Campylobacter could be isolated from 4 of 49 (8%) of flies caught outside a broiler house in Denmark. Furthermore, Wright showed that Campylobacter could be isolated from five of 210 (2.4%) living flies, isolated from three different locations [ 25 ]. From these results the author drew the conclusion that the health hazard from the transmission of Campylobacter from animals to human food is small. On the contrary, giving the numerous contacts between flies and human food, we find it highly likely that if one out of every 40 flies carries Campylobacter the health hazard would be significant. 3. Presence of the pathogen in the environment Shigella is a strict human pathogen, while the major source of Campylobacter is the faeces of both humans and animals such as chickens, cattle and pigs, which are often kept in close proximity of humans. Stanley and Jones have previously shown the importance of cattle and sheep farms as reservoirs of Campylobacter [ 26 ]. Campylobacter is also common in the droppings from wild birds [ 27 , 28 ], and ubiquitous in the environment. Campylobacter spp have been isolated from sewage contaminated water [ 29 ], contaminated soil [ 30 ] and aquatic sediments [ 31 ], and in sand from bathing beaches [ 32 ]. There are therefore likely considerably more Campylobacter than Shigella in the close vicinity of humans. Since flies have been shown to be an important mechanical vector of shigellosis, it would be surprising if they could not also be so for campylobacteriosis. Direct transmission from the soil could probably account for some of the cases in children, but less likely for adult cases. 4. Seasonality of the disease The distinct seasonality in the temperate regions [ 3 , 5 , 7 , 8 , 33 ] fits well with the fly hypothesis. The summer is the only season in temperate countries when people are in close contact with flies – often while having picnics or otherwise eating outdoor in close proximity of cattle and other environmental sources of Campylobacter . Some of the recorded association between barbeque and campylobacteriosis could very well be due to contamination of the food by flies, rather than undercooked meat or cross-contaminations, as has previously been postulated. A recent study from the UK has shown a close temporal association between the incidence of campylobacteriosis and fly density [ 34 ]. Although there is a seasonal pattern in the density of flies in the tropics, flies are present year round [ 13 , 14 ]. Therefore, if our hypothesis holds true, there should not be the same distinct seasonal peaks in the tropics. However seasonal data on campylobacteriosis from tropical regions are largely lacking. Instead we have recently compared Swedish notification data on travel-related campylobacteriosis with an extensive database on the travel patterns of Swedish residents (denominator for monthly risks per region). While a distinct seasonal pattern, as previously described, could be discerned in travellers from all temperate regions, the risk of campylobacteriosis in travellers from the tropics were more dispersed over the year [ 35 ]. Lack of detailed data on seasonal fly density and quite large geographical regions for our risk estimates of campylobacteriosis, prevented us from making any correlations between risk of campylobacteriosis and the presence of flies in the tropical regions. 5. Age profile Small children are less able to protect themselves from flies than older children and adults, and are more likely to have their hands on fly-soiled surfaces. In the tropics, the Campylobacter infection is largely confined to children below the age of two years, and the decreasing incidence thereafter has been attributed to a lasting immunity [ 20 ]. On the contrary, in Sweden and other Western countries, the highest incidence is seen in young adults, with a smaller peak in pre-school age children [ 20 , 36 ]. Then, how about western travellers going to the tropics? If the major transmission route of Campylobacter was ingestion of contaminated food, one would expect the infection to be relatively evenly distributed among the largely non-immune westerners coming to high prevalence countries. Again we turned to the risk estimates for campylobacteriosis in returning Swedish travellers. While, the incidence pattern in travellers returning from temperate countries closely mimicked the age pattern of indigenous Swedish cases, we noted that among travellers returning from tropical areas of Africa and Asia, the youngest children had twice as high risk as young adults, and more than four times the risk compared to older children [ 35 ]. This age pattern thus suggests other major routes of transmission than food or water, e.g. direct or indirect transmission from environmental sources. The flies would fit well in this concept. 6. Dominance of solitary cases If intake of chicken and undercooked meat (or cross-contamination from these food items) was a major route of transmission, clusters of cases within the same family should be common. Instead a striking feature of indigenous campylobacteriosis in Sweden is that the cases (except for in a few larger outbreaks) are solitary. A survey of notification data in one Swedish county over several years showed that it was exceptionally rare that cases shared the same address [ 37 ]. Information on the notification form indicating symptomatic cases around the notified patient was also very rare, even though this is specifically asked for. Solitary cases are instead more compatible with circumstance where an infected fly defecates on the plate of one family member, leaving the rest of the family unexposed. Testing the hypothesis The fly hypothesis needs to be backed by further experimental and epidemiological studies. The best evidence would be if controlled intervention studies could show an effect on the incidence of Campylobacter infection by fly control, as has previously been done for shigellosis and diarrhoea [ 13 - 15 ]. Such studies could only be done in high incidence areas, and would require good laboratory support. In temperate regions such intervention studies would be less feasible. Instead, questions focusing on the exposure to flies, and possible nearby environmental Campylobacter sources, e.g. cattle farms, sewage treatment or fowls, should be included in forthcoming case-control studies on campylobacteriosis. This has been a neglected line of questioning so far. More data on the carriage of Campylobacter by flies in different settings where people could be exposed are also needed. An alternative, and more innovative, approach would be to combine information on the likely place/s of infection with data on environmental sources, in analytic studies using geographical information systems (GIS) tools. Conclusion All the evidence in favour of the fly hypothesis is circumstantial and there may be alternative explanations to each of the findings supporting the hypothesis. However, in the absence of alternative explanations that could give better clues to the evasive epidemiology of Campylobacter infection, we believe it would be unwise to rule out flies as important mechanical vectors also of this disease. Summary We put forward the hypothesis that flies play a more important role in the transmission of the bacteria, than has previously been recognized. Factors supporting this hypothesis are: 1) the low infective dose of Campylobacter ; 2) the ability of flies to function as vectors; 3) a ubiquitous presence of the bacteria in the environment; 4) a seasonality of the disease with summer peaks in temperate regions and a more evenly distribution over the year in the tropics; 5) an age pattern for campylobacteriosis in western travellers to the tropics suggesting other routes of transmission than food or water; and finally 6) very few family clusters. The hypothesis should be further tested with experimental and epidemiological studies Competing interests The author(s) declare that they have no competing interests. Authors' contributions Bengt Normann raised the original idea and has studied the (lack of) family clustering. Yvonne Andersson contributed with in depth knowledge of campylobacteriosis. Karl Ekdahl did the literature search, looked into the seasonality and age distribution of the disease in domestic cases and returning travellers, and prepared the first draft of the manuscript. All authors have participated in revising the draft manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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529442

The Drosophila methyl-DNA binding protein MBD2/3 interacts with the NuRD complex via p55 and MI-2

Background Methyl-DNA binding proteins help to translate epigenetic information encoded by DNA methylation into covalent histone modifications. MBD2/3 is the only candidate gene in the Drosophila genome with extended homologies to mammalian MBD2 and MBD3 proteins, which represent a co-repressor and an integral component of the N ucleosome R emodelling and D eacetylase (NuRD) complex, respectively. An association of Drosophila MBD2/3 with the Drosophila NuRD complex has been suggested previously. We have now analyzed the molecular interactions between MBD2/3 and the NuRD complex in greater detail. Results The two MBD2/3 isoforms precisely cofractionated with NuRD proteins during gel filtration of extracts derived from early and late embryos. In addition, we demonstrate that MBD2/3 forms multimers, and engages in specific interactions with the p55 and MI-2 subunits of the Drosophila NuRD complex. Conclusion Our data provide novel insights into the association between Drosophila MBD2/3 and NuRD proteins. Additionally, this work provides a first analysis of the architecture of the Drosophila NuRD complex.

Background Methyl-DNA binding proteins are connecting DNA methylation to transcriptional silencing [ 1 - 4 ]. Up to now, six methyl-DNA binding proteins could be identified in vertebrates [ 5 ]. MeCP2, MBD2 and MBD3 can be found in large chromatin complexes containing histone deacetylase activity [ 1 , 6 , 4 , 3 ] whereas MBD4 is involved in DNA mismatch-repair [ 7 ]. MBD1 has been shown to repress transcription in cell culture [ 8 ] and recruits the histone H3-K9 methyltransferase SETDB1 to the chromatin assembly factor CAF-1 during S phase [ 9 ]. MBD2, which can bind methylated DNA [ 6 ], is a transcriptional repressor recruiting a Nu cleosome R emodelling and D eacetylase complex (NuRD) to methylated CpG dinucleotides [ 6 , 3 ], whereas mammalian MBD3, which is not able to bind methylated DNA [ 10 ] is an integral component of NuRD [ 3 ]. Kaiso, a transcriptional repressor protein, can bind directly to CpG methylated DNA even though it lacks a conserved methyl-DNA binding domain [ 11 ]. Kaiso is a component of a subpopulation of MeCP1 complexes that lack MBD2 [ 11 ]. The Drosophila gene MBD2/3 encodes a protein, which shares high homology to mammalian MBD2 and MBD3 [ 12 , 4 ]. Due to differential splicing, Drosophila MBD2/3 is expressed in two isoforms, the smaller one is lacking part of the putative methyl-DNA binding domain [ 12 - 15 ]. The large isoform is expressed during early development, whereas the small isoform can only be detected during late embryogenesis [ 14 , 15 ]. In insect cells expressing only the small MBD2/3 isoform, this protein was found to be associated with components of the Drosophila NuRD complex [ 12 - 14 ]. Moreover, this protein could repress transcription effectively in transfected Drosophila cells [ 13 , 14 ]. The NuRD complexes of vertebrates are a heterogeneous group of complexes containing both histone deacetylase and nucleosome remodelling activities [ 3 ]. NuRD complexes comprise at least seven proteins. The ATP- dependent nucleosome-remodelling activity is mediated by MI-2, which contains a SWI2/SNF2-type helicase/ATPase domain, two chromodomains and two PHD fingers [ 16 ]. The related MTA1, MTA2 and MTA3 proteins have been found in various complex preparations [ 17 , 4 , 3 , 18 ]. MTA1 was originally identified as being overexpressed in metastatic carcinomas [ 19 ]. The histone deacetylases HDAC1 and HDAC2 and the two histone binding proteins RbAp46 and RbAp48 form the histone deacetylase core of NuRD complexes. Finally, as mentioned above, mammalian MBD3 is an integral component of at least some NuRD complexes [ 3 ]. Strikingly, the Drosophila genome contains clear homologues for all verterbrate NuRD proteins. Recombinant Drosophila MI-2 was shown to have ATPase and nucleosome mobilization properties [ 20 ]. In Drosophila the HDAC gene Rpd3 is important for segmentation of the embryo [ 21 ]. Drosophila p55, a WD-40 protein, is homologous to the histone deacetylase-associated proteins RbAp46 and RbAp48 [ 22 ]. Finally, Drosophila MTA-like displays extensive homology to the vertebrate MTA proteins [ 23 ]. The strong conservation between vertebrate NuRD complexes and the Drosophila NuRD complex implies a conserved function during the animal development. In previous studies cell lines were analysed that express only the small isoform of MBD2/3, lacking part of the putative methyl-DNA binding domain and a Drosophila specific domain. In order to analyse isoform-specific differences of MBD2/3 and their ability to bind NuRD proteins, we now extend our analysis to both isoforms in Drosophila embryos. Results MBD2/3 is associated with Drosophila NuRD proteins An association of Drosophila MBD2/3 with the NuRD complex has been suggested previously [ 14 , 12 ]. However, these experiments were done in vitro or with protein extracts from tissue culture cells that express only the small isoform of MBD2/3. In addition, only a limited number of NuRD proteins were analysed. To confirm the association between MBD2/3 and NuRD in Drosophila embryos we size-fractionated nuclear protein extracts from 2–4 h or 0–12 h wild type embryos, respectively, by Superose 6 gel filtration chromatography. Proteins from individual fractions were then separated by standard SDS-PAGE and analysed by Western blotting using antibodies directed against known homologous subunits of the NuRD complex. MI-2 and MTA-like, which are homologues of subunits that are specific for vertebrate NuRD complexes [ 24 , 3 ] cofractionated with an apparent molecular weight of 1 MDa when extracts derived from early embryos (2–4 h) were applied (Fig. 1A , fractions 19 to 21). When extracts of late embryos (0–12 h) were analysed, MI-2 and MTA-like were detected in fractions 15 to 19, which correspond to an apparent molecular weight of approx. 2 MDa (Fig. 1B ). This result indicates that the formation of NuRD is developmentally regulated during embryogenesis. Additionally, we found a precise cofractionation of the large isoform of MBD2/3 (Fig. 1 , MBD2/3li) with MI-2 and MTA-like in both cases. The small MBD2/3 isoform (Fig. 1B , MBD2/3si) present in extracts derived from late embryos likewise cofractionated with MI-2 and MTA-like. This suggests a close association of both MBD2/3 isoforms with the Drosophila NuRD complex. The RPD3 and p55 proteins also cofractionated with MBD2/3 isoforms, but they were also found in fractions of lower molecular weight (Fig. 1 ). This is in agreement with the fact that both RPD3 and p55 are also components of other chromatin related complexes [ 25 , 26 ]. Figure 1 Cofractionation of Drosophila NuRD homologues in embryonic protein extracts Nuclear protein extracts were prepared from (A) 2–4 h and (B) 0–12 h old embryos, respectively and size-fractionated by FPLC using a Superose 6 column. Proteins from selected fractions were then separated by SDS gel electrophoresis and analysed by Western blotting. (A) During early embryogenesis the long isoform of MBD2/3 (MBD2/3li) cofractionated with MI-2 and MTA-like in fractions 19 to 21 (indicated in red), which correspond to a molecular weight of approx. 1 MDa. The small isoform of MBD2/3 is not expressed at this stage of embryogenesis. (B) During later stages of embryogenesis both isoforms of MBD2/3 cofractionated with MI-2 and MTA-like in fractions 15 to 19 (indicated in red), which correspond to a molecular weight of approx. 2 MDa. The size of marker proteins is shown left and on top, IN indicates input protein. Interactions between MBD2/3 and NuRD homologues To analyse the association between MBD2/3 and the NuRD complex in more detail and to identify direct NuRD interaction partner(s) of MBD2/3 we first used a GST-pulldown assay. In order to eliminate unspecific interactions with NuRD proteins, we established highly stringent assay conditions. This was achieved by assessing the interactions between radioactively labeled SV40 large T antigen (Fig. 2A , large T) and a number of control GST fusion proteins. When we used an incubation and washing buffer with high salt and detergent concentrations, significant amounts of SV40 large T were precipitated by p53 only (Fig. 2A ), which is known to be a strong interactor of the large T antigen [ 27 ]. Residual binding detected with some of the other proteins (Fig. 2A ) was considered background. Figure 2 Interactions between MBD2/3 and NuRD homologues in a GST-pulldown assay (A) Analysis of interactions between radioactively labelled SV40 large T antigen (large T) and a number of control GST fusion proteins under stringent buffer conditions. Significant amounts of SV40 large T were only precipitated by p53. The faint bands seen with some of the other proteins were considered background. (B) GST-MBD2/3 fusion proteins for long and small isoforms (MBD2/3li, MBD2/3si, respectively) efficiently precipitated radioactively labelled MBD2/3 long isoform and p55 (solid arrowhead). Similarly, MI-2 protein could be precipitated by the small GST-MBD2/3 isoform (solid arrowhead). No interaction could be observed between long MBD2/3 or small MBD2/3 isoforms and MTA-like or RPD3 (open arrowheads). (C) A MBD2/3-specific antibody immunoprecipitates p55, but not GAGA factor from embryonic nuclear extracts. No proteins were detectable in control immunoprecipitations with a myc-specific antibody. (D) Size-fractionation of baculovirus-expressed MBD2/3 long isoform and RPD3. Baculovirus-expressed MBD2/3li elutes in fractions that significantly exceed the calculated molecular weight of the protein (36 kDa), thus indicating that MBD2/3li efficiently multimerizes in solution. This effect appeared to be specific for MBD2/3 and was not observed with baculovirus-expressed RPD3 protein (58kDa). The size of marker proteins is shown left and on top, IN indicates input protein. We then performed the MBD2/3-NuRD interaction assay using these conditions and observed strong interactions only between the long and small MBD2/3 isoforms (Fig. 2B , MBD2/3li and MBD2/3si, respectively) and p55. To confirm the association between MBD2/3 and p55 in Drosophila embryos we immunoprecipitated nuclear extracts with MBD2/3-specific antibodies and with myc-specific control antibodies. Precipitates were analysed by Western blot for the presence of p55 and GAGA factor. This revealed a specific association of MBD2/3 with the Drosophila NuRD homologue p55, but not with the unrelated GAGA factor (Fig. 2C ). A weaker interaction could also be detected between the small MBD2/3 isoform and MI-2 (Fig. 2B ). Neither RPD3 nor MTA-like binding exceeded the background level defined by our pilot experiment with SV40 large T protein (Fig. 2B ). Our results thus identified p55 and MI-2 as the direct interaction partners of MBD2/3 in the NuRD complex. In addition, our results from the GST-pulldown assay indicate that Drosophila MBD2/3 forms dimers or multimers, similar to mammalian MBD2 and MBD3 [ 28 ]. To discriminate between the latter two possibilities we expressed a recombinant long MBD2/3 isoform and RPD3 in insect cells using a baculovirus expression system. Extracts from infected cells were subjected to Superdex 200 gel filtration and fractions were analysed by Western blot. The 58 kDa RPD3 protein eluted in fractions corresponding to molecular weights ranging from 66 kDa to 158 kDa, which suggested that RPD3 exists as monomers or dimers in solution (Fig. 2D ). In contrast, the 36 kDa MBD2/3 isoform showed a strikingly different elution profile (Fig. 2D ). The long MBD2/3 isoform eluted in a broad peak ranging from more than 158 kDa up to high molecular weight fractions (>400 kDa). No MBD2/3 was detected in fractions corresponding to the expected size of MBD2/3 monomers or dimers. This result is consistent with our earlier observation that MBD2/3 forms distinct aggregates in embryonic nuclei [ 15 ] and suggests that the protein efficiently oligomerises to form high-molecular weight complexes in solution. To confirm these interactions in an independent set of experiments we also analysed the association between MBD2/3 isoforms and the NuRD proteins in a yeast two-hybrid assay. In agreement with our previous results, growth on highly selective (Fig. 3A , panel H) plates was only observed upon co-expression of the MBD2/3 small isoform and either MI-2, MBD2/3 long isoform or p55, and upon co-expression of both MBD2/3 isoforms. These interactions were confirmed by X-Gal staining of filter-lifted yeast colonies (Fig. 3A , panel X). In these assays the two MBD2/3 isoforms differed only with regard to MI-2 binding (Fig. 3A ). However, differential binding could be eliminated by a slight reduction in the stringency of the assay (Fig. 3A , panel M), which suggested that both isoforms of MBD2/3 are capable of interacting with MI-2. Consistent with our GST-pulldown assays no interaction could be detected between the MBD2/3 long isoform and RPD3 or MTA-like (Fig. 3A ). Figure 3 Interactions between MBD2/3 and NuRD homologues in a yeast two-hybrid assay (A) An MBD2/3 long isoform bait efficiently transactivated reporter gene transcription in yeast expressing p55 or MBD2/3 small isoform prey constructs, respectively. A weaker transactivation could be seen upon expression of a MI-2 prey construct (panel M). An MBD2/3 small isoform bait transactivated reporter gene transcription co-expressing a MI-2 prey also under high-stringent conditions (panel H). No transactivation could be observed with MTA-like or RPD3 preys. N shows growth on non-selective plates, M on medium-stringency plates and H on high-stringency plates. X indicates X-gal staining of colonies grown on non-selective plates. (B and C) Delineation of interaction domains in a yeast two-hybrid assay. The methyl-DNA binding domain (MBD) is highlighted in red, the Drosophila specific domain (DSD) in green and the C-terminal coiled-coil domain (cc) in yellow. (B) The C-terminal region of MBD2/3 interacts with p55. The full-length p55 construct was used as a bait and various deletion mutants of MBD2/3 were used as preys. This identified the region between amino acids 178 and 305 of the MBD2/3 long isoform as the p55 interaction domain. (C) Deletion of the coiled-coil domain abolishes interactions between MBD2/3 small isoform and MI-2 under high stringent conditions. Next we sought to delineate the domains that mediate the association between the MBD2/3 isoforms and their interacting proteins. To this end, we generated several MBD2/3 deletion mutants and tested their interaction with other proteins in a yeast two-hybrid assay. In a first series of experiments we tested the MBD2/3 mutants for their ability to interact with p55. This identified the region between residues 178 and 305 of the MBD2/3 long isoform as the p55 interaction domain (Fig. 3B ). We also delineated the domain that mediates the interaction with MI-2. Our experiments revealed a strongly reduced interaction between a MBD2/3 small isoform derivative lacking the coiled-coil domain and MI-2 (Fig. 3C ). It has been shown previously that vertebrate MBD2 and MBD3 form homo- and heterodimers via their N-terminal MBD domain and their C-terminal coiled-coil like sequences [ 28 ]. Our findings might reflect a direct interaction between the coiled-coil domain and MI-2 or a requirement for efficient MBD2/3 multimerization for MI-2 interaction. In conclusion, our results identify distinct regions in the MBD2/3 protein that mediate protein-protein interactions with other NuRD proteins. In order to analyse the architecture of the NuRD complex, we performed a detailed yeast two-hybrid analysis including additional bait and prey constructs for NuRD proteins. Bait constructs for MI-2, RPD3, p55 and both MBD2/3 isoforms and prey constructs for MTA-like, RPD3, p55, and both MBD2/3 isoforms were co-transformed in all possible combinations and transformation was confirmed by growth on non-selective plates (Fig. 4A ). Colonies were then replicated onto highly selective plates that allow growth only upon interaction between the two expressed proteins (Fig. 4B ). Finally, we performed a filter lift assay followed by X-Gal staining to confirm the interactions (Fig. 4C ). In addition to the results presented above, we found strong interactions between p55 and all NuRD proteins. We also observed a homotypic interaction for p55 but no homotypic interaction for RPD3. To confirm the specificity of the interactions, we tested most of the constructs reciprocally by changing the bait and prey vectors for expression of NuRD proteins and MBD2/3 isoforms. This data allows the establishment of a more detailed model of the NuRD complex. Fig. 4D summarizes the data from all experiments. p55 interacted with MI-2, MTA-like, RPD3, and both MBD2/3 isoforms. The small isoform of MBD2/3 interacted with MI-2 as well as with the large MBD2/3 isoform. Homodimerization of p55 and MBD2/3 is not shown in the model. Figure 4 Analysis of the architecure of NuRD (A) Yeast colonies growing on non-selective plates carrying bait (left panel) and prey (top panel) NuRD and MBD2/3 constructs. (B) Replica plate with high-selective medium. Only yeast colonies with constructs encoding interacting proteins are able to grow. MBD2/3li Δ59-339 represents a truncated MBD2/3li construct that was used to confirm the specificity of the interaction between p55 and MBD2/3. (C) X-Gal staining of yeast colonies to confirm interactions. (D) Schematic illustration of protein-protein interactions in the NuRD complex. Homodimerization of p55 and MBD2/3 are not shown. Discussion It has been previously suggested that MBD2/3 is associated with the Drosophila NuRD complex [ 14 ]. This study determined that the small isoform MBD2/3 coelutes with some putative Drosophila NuRD subunits during fractionation of extracts derived from a Drosophila cell line. We have now extended this analysis to show that both isoforms of MBD2/3 coelute with NuRD homologues during fractionation of embryonic extracts. This data provides further evidence for a direct interaction between MBD2/3 and the NuRD complex. Using several independent assays, we have demonstrated that MBD2/3 engages in homotypic interactions to form multimers. This effect is consistent with the formation of foci in embryonic nuclei [ 15 ] and also reminiscent of the interactions described for vertebrate MBD2 and MBD3 [ 28 ]. In addition, our data provides new insights into the association between MBD2/3 and NuRD. For example, we have shown that p55 appears to be the primary interaction partner of MBD2/3. We also observed a strong interaction between the small isoform MBD2/3 and MI-2, but not between MBD2/3 small isoform and MTA-like or RPD3. Additionally, we found interactions between p55 and all NuRD proteins, as well as a p55 homotypic interaction. The last finding is consistent with the fact that in the vertebrate NuRD complex the two p55 homologues RbAp46 and RbAp48 were identified as integral components [ 3 ]. We note that the vertebrate NuRD complex also contains the two RPD3 homologues HDAC1 and HDAC2 [ 3 ]; unexpectedly, we were not able to detect any homotypic interaction of RPD3 in the yeast two-hybrid assay. One explanation could be that the dose of the two co-expressed RPD3 bait and prey proteins could interfere with the reporter gene activity due to their inherent histone deacetylation activity. However, the gel filtration assay revealed that the 58 kDa RPD3 protein eluted in fractions corresponding to molecular weights ranging from 66 kDa to 158 kDa, which suggested that RPD3 can interact homotypically (Fig. 3C ). It is possible that more complex interactions are involved in the assembly of the NuRD complex but they might not have been detectable under the stringent conditions of our assays. The interaction between MBD2/3 and MI-2 detected in our assays could also contribute to the specific association between MBD2/3 and the NuRD complex. The interaction between MBD2/3 and p55 could promote the assembly of specialized chromatin structures in the fly. p55 is a WD-40 repeat protein that is involved in many aspects of chromatin organization [ 29 ]. For example, p55 has been shown to be a component of the Drosophila CAF-1 complex that promotes nucleosome assembly [ 22 ]. In addition, p55 is also contained in the NURF chromatin remodelling complex [ 30 ] and in the E(Z) complex that regulates homeotic gene expression [ 25 , 26 ]. A mutant Drosophila allele for p55 is not available, but results obtained from Arabidopsis mutants with decreased levels of a p55 homologue indicate that the protein plays an important role in stabilizing epigenetic chromatin structures [ 31 ]. Conclusions The goal of this study was to identify the interacting partners of the Drosophila methyl-DNA binding protein MBD2/3 within the Drosophila NuRD complex. We identified p55 and MI-2 as the primary interacting partners. We also found homo- and heterotypic interactions of the MBD2/3 isoforms, similar to vertebrate MBD2 and MBD3. Additionally, yeast two-hybrid assays revealed that p55 is able to specifically interact with all other NuRD proteins and can form homotypic interactions. Our data provides for the first time information about the architecture of the Drosophila NuRD complex. This allows us to develop a structural model of the NuRD complex. Methods DNA constructs Constructs for the yeast two-hybrid assay were generated by PCR amplification from cDNA clones [ 32 ] using specific primers (Tab. 1) with an attached restriction endonuclease target site for cloning. The PCR products were subsequently cloned into pGBKT7 or pGADT7 (Clontech) using standard procedures. All constructs were sequenced and in vitro translated to confirm the expression of corresponding proteins. Additionally, the bait constructs were expressed in yeast and expression of the fusion proteins was confirmed by Western analysis. Antibodies The following antibodies have been described previously: rabbit anti-MI-2 [ 20 ], rabbit anti-MTA1 [ 19 , 4 ], rabbit anti-RPD3 [ 20 ], rabbit anti-p55 [ 22 ], rabbit anti-MBD2/3 [ 14 ] and rabbit anti-GAGA [ 33 ]. Immunoprecipitations Immunoprecipitations were caried out in 300 mM KCl supplemented with 0.2 % NP-40. Rabbit anti-MBD2/3 or mouse anti-myc (Clontech) antibodies were added to 75 μl of nuclear extracts prepared as mentioned below and incubated for 12 h at 4°C. Protein G beads (Amersham) were blocked in 3 mg/ml BSA for 20 min at room temperature, washed three times with 300 mM KCl, 0.2 % NP-40 and added to the samples. Incubation was carried out for an additional 1 h at 4°C. The beads were collected by centrifugation and washed four times in 1 ml 300 mM KCl, 0.2 % NP-40. The beads were resuspended in loading buffer for SDS-PAGE and vigorously vortexed for 15 sec. The immunoprecipitates were separated by SDS-PAGE, without futher boiling, transferred to a PVDF membrane and probed with antibodies against RPD3, p55 and GAGA factor, respectively. Preparation of protein extracts and gel filtration For baculovirus expression, the MBD2/3 cDNA [ 32 ] was subcloned into the pVL1392 baculovirus transfer vector. Transfer vector and linearised baculovirus DNA were cotransfected into Sf9 cells using the Bac'n'Blue transfection kit (Invitrogen) and recombinant virus was amplified according to the manufacturer's instructions. Whole cell extracts of infected Sf9 cells were generated by resuspending cell pellets in lysis buffer (20 mM Hepes pH 7.6, 200 mM KCl, 0.1 % NP40), incubation on ice for 10 min, three freeze/thaw cycles and sonication. Nuclear extracts from Drosophila embryos were prepared as described previously [ 20 ]. Extracts were cleared by centrifugation and passaged through a 0.2 μm filter. 200 μl of cleared extract was applied to Superdex 200 HR 10/30 or Superose 6 HR 10/30 gel filtration columns (Amersham Pharmacia) and resolved in 20 mM Hepes pH 7.6 and 300 mM KCl on an Äkta Purifier system (Amersham Pharmacia) according to the manufacturer's instructions. GST-pulldown assays 35 S-methionine-labelled proteins were generated by in vitro trancription/translation of pGADT7_T, pGADT7_Mi-2, pGADT7_MTA-like, pGADT7_Rpd3, pGADT7_p55, pGADT7_MBD2/3 long isoform and pGADT7_MBD2/3 small isoform using the TNT coupled reticulocyte lysate system (Promega) according to the manufacturer's protocol. GST-MBD2/3 long isoform and GST-MBD2/3 small isoform fusionproteins were obtained by cloning the coding region of the two isoforms in pGEX4T1 (Amersham) and subsequent expressing of the constructs in BL-21 bacteria according to the manufacturer's protocol. GST-MBD2a was obtained from Hidetoshi Fujita [ 34 ]. GST-pull downs were performed under the following conditions: As incubation and washing buffer we used 20 mM HEPES, pH 7.8, 300 mM NaCl, 0.1 % desoxycholate, 0.1 % IGEPAL, 10 % glycerol. The radioactively labelled proteins were incubated in incubation buffer for 3 h at room temperature with GST fusion proteins coupled to Sepharose 4B (Amersham) or with GST alone coupled to Sepharose 4B. Beads were then washed five times for 10 min at room temperature. After the last washing step, beads were boiled in SDS loading buffer for 10 min and loaded onto standard SDS-polyacrylamide gels. After separation by SDS-PAGE, proteins were blotted onto a PVDF membrane, which was stained with Ponceau S, dried and exposed on X-ray films. Yeast two-hybrid assays The Matchmaker Two-Hybrid system 3 (Clontech) was used for all experiments, according to the manufacturer's instructions. The AH109 strain was used as host and transformed with various constructs (see above) using standard procedures. Transformants were selected on SD/-Ade/-His/-Leu/-Trp plates. Authors' contributions KK and JM carried out the molecular interaction studies. AB carried out the gel filtration experiments. JM conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript. Table 1 PCR primers used for the cloning of recombinant plasmids MBD-BD-F: gga att cat gca aat gaa ccc gag cgt c MBD-BD-R: tcc ccc ggg tgt ctt gag tgc atc ctg cag Mi2-BD-F: cgc cat atg atg gca tcg gag gaa gag aat gac Mi2-BD-R: gcg gcc tcc atg gcc gac gcc gga att att cga tag c MTA-AD-F: ccg gaa ttc atg gcc aca aat atg tat cga gtc gg MTA-AD-R: tcc ggg ccc ggt gac act ata gaa ctc gag Rpd3-BD-F: atg gcc atg gat gca gtc tca aca gc Rpd3-BD-R: ggc cgc tgc aga atg ttg ttc tcc ttg gcg Rpd3-AD-F: cgc tca tat gat gca gtc tca cag c Rpd3-AD-R: gca gct cga gaa tgt tgt tct cct tgg cg p55-BD-R: ggc tca atc ttt ggt tat ggc gaa ttg gat ccg cg p55-AD-F: ccg gaa ttc atg gtg gat cgc agc g p55-AD-R: ggc gag ctc tta agc ggt att ggt ttc taa ctc gg MBD-AD-F: gga att cat gca aat gaa ccc gag cgt c MBD-AD-R: ccg ctc gag tgt ctt gag tgc atc ctg cag MBD-AD-Δ59-339: ccg ctc gag cca cct tgt tat tgt tgt tgt tgc BD designates primers used for the binding domain-constructs, AD designates primers used for the activation domain-constructs. F indicates forward primers, R indicates reverse primers.

/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529442.xml

555953

cAMP controls cytosolic Ca2+ levels in Dictyostelium discoideum

Background Differentiating Dictyostelium discoideum amoebae respond upon cAMP-stimulation with an increase in the cytosolic free Ca 2+ concentration ([Ca 2+ ] i ) that is composed of liberation of stored Ca 2+ and extracellular Ca 2+ -influx. In this study we investigated whether intracellular cAMP is involved in the control of [Ca 2+ ] i . Results We analyzed Ca 2+ -fluxes in a mutant that is devoid of the main cAMP-phosphodiesterase (PDE) RegA and displays an altered cAMP metabolism. In suspensions of developing cells cAMP-activated influx of extracellular Ca 2+ was reduced as compared to wild type. Yet, single cell [Ca 2+ ] i -imaging of regA - amoebae revealed a cAMP-induced [Ca 2+ ] i increase even in the absence of extracellular Ca 2+ . The cytosolic presence of the cAMP PDE inhibitor 3-isobutyl-1-methylxanthine (IBMX) induced elevated basal [Ca 2+ ] i in both, mutant and wild type cells. Under this condition wild type cells displayed cAMP-activated [Ca 2+ ] i -transients also in nominally Ca 2+ -free medium. In the mutant strain the amplitude of light scattering oscillations and of accompanying cAMP oscillations were strongly reduced to almost basal levels. In addition, chemotactic performance during challenge with a cAMP-filled glass capillary was altered by EGTA-incubation. Cells were more sensitive to EGTA treatment than wild type: already at 2 mM EGTA only small pseudopods were extended and chemotactic speed was reduced. Conclusion We conclude that there is a link between the second messengers cAMP and Ca 2+ . cAMP-dependent protein kinase (PKA) could provide for this link as a membrane-permeable PKA-activator also increased basal [Ca 2+ ] i of regA - cells. Intracellular cAMP levels control [Ca 2+ ] i by regulating Ca 2+ -fluxes of stores which in turn affect Ca 2+ -influx, light scattering oscillations and chemotactic performance.

Background Starving Dictyostelium discoideum amoebae form a multicellular organism by chemotactic aggregation. The signaling molecule that mediates aggregation and development is cAMP. Aggregation proceeds in a rhythmic fashion; cAMP is secreted periodically by cells in the center of the aggregate. Cells in the neighbourhood respond by an oriented inward movement and secrete cAMP themselves to relay the signal. In cell suspensions periodic synthesis and release of cAMP leads to rhythmic shape changes that cause alterations in light transmittance and spike-shaped and sinusoidal light scattering oscillations [ 1 ]. The marked rhythmic behaviour of the cell population is also apparent by oscillations of other parameters, e.g. extracellular concentrations of Ca 2+ , K + or H + (for review see [ 2 ]). Recently, changes in [Ca 2+ ] i were postulated to comprise the (or at least a part of the) master oscillator controlling oscillation patterns [ 3 , 4 ]. A short [Ca 2+ ] i -transient induced by addition of CaCl 2 or calmodulin antagonists alters light scattering oscillations and can even reset the oscillation phase [ 3 ]. The height of the [Ca 2+ ] i -increase determines whether light scattering and the accompanying cAMP oscillations are abolished or augmented: large [Ca 2+ ] i -transients inhibit cAMP and light scattering oscillations [ 3 ] whereas small [Ca 2+ ] i -elevations enhance oscillations of both parameters [ 4 ]. From these experiments it was concluded that Ca 2+ exerts a dual control over the production of the first messenger cAMP (for a detailed model see [ 4 ]). cAMP controls its own synthesis as binding of the agonist to cell surface receptors induces a transient [Ca 2+ ] i -elevation [ 5 - 7 ]. However, until now the question as to whether there is an interaction between cAMP acting intracellularly as second messenger and [Ca 2+ ] i in D. discoideum has not been resolved. In other cell systems such as nerve cells crosstalk between the cAMP and the Ca 2+ signaling pathway exists that is necessary to generate oscillations of both parameters [ 8 ]. In order to gain insight into a possible connection between intracellular cAMP and [Ca 2+ ] i we used a mutant defective in the phosphodiesterase RegA. RegA is one out of two cAMP-specific phosphodiesterases (for an overview of classes of PDEs in Dictyostelium see [ 9 ]) that is inhibited by IBMX and comprises part of an eukaryotic phospho-relay system [ 10 , 11 ]. RegA - mutants are rapid developers; their differentiation is shifted towards the stalk pathway [ 12 , 13 ]. Chemotactic migration is characterized by an increased frequency of lateral pseudopod extension as compared to wild type amoebae [ 14 ]. We found that the mutant displayed an altered [Ca 2+ ] i -response pattern upon stimulation with cAMP with an augmentation of Ca 2+ -release from stores and a concomitant decrease of extracellular Ca 2+ -entry. Light scattering oscillations and the underlying cAMP oscillations were drastically reduced in regA - cells. Chemotaxis was influenced by the extracellular presence of EGTA. We conclude that indeed, intracellular cAMP signaling and the regulation of [Ca 2+ ] i are linked at the level of Ca 2+ -storage compartments. Results Extracellular and intracellular [Ca 2+ ]-recordings To test whether the absence of the main cAMP-specific phosphodiesterase affects regulation of [Ca 2+ ] i we analyzed extracellular Ca 2+ -fluxes in cell suspensions and studied [Ca 2+ ] i in single amoebae. cAMP-induced Ca 2+ -influx in suspensions of regA - cells occurred with a similar time course as in wild type. Yet, influx was reduced by approximately 40% (Fig. 1 ). The loss of RegA should lead to an altered cAMP metabolism. Indeed, the basal total amount of cAMP was increased fourfold (13 ± 3 pmol/10 7 regA - cells; mean ± s.e.m. of 16 determinations in 7 independent experiments vs. 2.8 ± 0.3 pmol/10 7 wild type cells; mean ± s.e.m. of 11 determinations in 6 independent experiments). Addition of the PDE inhibitor IBMX (up to 200 μM) to wild type cells affected neither the amount nor the characteristics of cAMP-activated extracellular Ca 2+ -fluxes. Figure 1 Ca 2+ -influx after cAMP stimulation is reduced in regA - cells. The amount of influx (pmol/10 7 cells) after addition of 1 μM cAMP is plotted versus extracellular [Ca 2+ ]. Average influx was higher in wild type than in regA - amoebae (mean ± s.d. from at least 6 determinations in 3 independent experiments each). IBMX does not inhibit extracellular PDE [ 15 ] but affects cAMP hydrolysis intracellularly, so we compared basal [Ca 2+ ] i and cAMP-activated [Ca 2+ ] i -changes of regA - to wild type cells in the absence and intracellular presence of IBMX. The inhibitor should affect the activity of both cAMP phosphodiesterases, RegA and PDE-E [ 16 , 17 ]. Without IBMX, basal [Ca 2+ ] i was similar in both strains (Table 1 ). However, cAMP-addition induced a [Ca 2+ ] i -transient in regA - cells in nominally Ca 2+ -free medium (Fig. 2 , Table 1 ). In wild type, cAMP-activated [Ca 2+ ] i -changes were observed after preincubation with 1 mM Ca 2+ for 10–15 min only (see also [ 18 ]). After loading of IBMX into the cytosol both, basal [Ca 2+ ] i and cAMP-induced [Ca 2+ ] i -changes were altered. Basal [Ca 2+ ] i in the presence and absence of extracellular Ca 2+ was significantly increased in regA - ; the height of the [Ca 2+ ] i -transient after cAMP-stimulation was comparable to the control situation. In wild type, basal [Ca 2+ ] i was elevated and a [Ca 2+ ] i -change was also observed after cAMP addition in nominally Ca 2+ -free medium (Fig. 3 , Table 1 ). In summary, increasing cAMP levels augmented cAMP-induced [Ca 2+ ] i -transients at concomitantly reduced levels of Ca 2+ -influx; the increase in basal intracellular cAMP caused by the absence of RegA was sufficient. Alteration of basal [Ca 2+ ] i required an even higher concentration of cAMP. This was achieved by inhibition of RegA and of PDE-E via loading of IBMX into the cytosol. In wild type where both enzymes are present basal [Ca 2+ ] i was not elevated in the presence of external Ca 2+ which indicates that the amount of cAMP had just reached a threshold value and that basal [Ca 2+ ] i is more tightly controlled than agonist activated [Ca 2+ ] i -changes. Figure 2 Measurement of cAMP activated [Ca 2+ ] i -changes in wild type and mutant amoebae. Cells were stimulated with 1 μM cAMP in the presence or absence of 1 mM external CaCl 2 . In wild type amoebae a [Ca 2+ ] i -transient was observed in the presence of external Ca 2+ . The graph shows the average increase (mean ± s.e.m.). Figure 3 Measurement of cAMP activated [Ca 2+ ] i -transients in wild type and mutant amoebae in the cytosolic presence of IBMX. IBMX led to an elevation of basal [Ca 2+ ] i . Upon stimulation with 1 μM cAMP in the absence of external CaCl 2 a [Ca 2+ ] i -transient was observed in both, mutant and wild type amoebae (mean ± s.e.m.). Table 1 Basal [Ca 2+ ] i and the increase over basal [Ca 2+ ] i after cAMP-addition in wild type and regA - cells in the absence and presence of IBMX. 1 μM cAMP was added to wild type at t 7 –t 8 and to regA - at t 4 because the mutant develops more rapidly. [Ca 2+ ] i was determined by ratiometric imaging in single cells either in nominally Ca 2+ -free buffer (- Ca 2+ ) or in buffer containing 1 mM Ca 2+ . Values are mean ± s.e.m. and numbers in brackets indicate the numbers of cells tested in at least 3 determinations in at least 2 independent experiments each. Strain Condition Basal [Ca 2+ ] i cAMP-induced [Ca 2+ ] i -change - IBMX + IBMX - IBMX + IBMX regA - - Ca 2+ 55 ± 1 (131) 97 ± 1 (111) 71 ± 8 (30) 81 ± 9 (25) + 1 mM Ca 2+ 54 ± 1 (85) 96 ± 2 (66) 79 ± 6 (52) 85 ± 8 (35) Wild type - Ca 2+ 53 ± 1 (94) 98 ± 1 (148) no increase 132 ± 9 (58) + 1 mM Ca 2+ 50 ± 1 (185) 53 ± 1 (127) 125 ± 6 (83) 155 ± 10 (55) The effect of the increased basal cAMP concentration on the [Ca 2+ ] i -regulation in regA - amoebae might be caused by a change in the characteristics of Ca 2+ -fluxes of internal stores. A positive influence of cAMP via PKA-mediated phosphorylation of both, IP 3 -receptors and ryanodine receptors on release of stored Ca 2+ has been reported (for review see [ 19 ]). We therefore tested the response of regA - amoebae upon stimulation with cAMP in the presence of the chelator BAPTA. We found that even after the addition of 1 mM BAPTA cAMP activated a transient increase in [Ca 2+ ] i (Fig. 4 ). The elevation was smaller than that observed in nominally Ca 2+ -free medium and amounted to an average of 44 ± 3 nM above basal [Ca 2+ ] i (mean ± s.e.m. of 18 determinations in 2 independent experiments). In wild type amoebae a cAMP-stimulated [Ca 2+ ] i -increase is not detectable in the presence of BAPTA; the occurrence of a transient [Ca 2+ ] i -elevation in regA - cells indicates an augmented release of Ca 2+ from stores in the mutant. Support for an effect of cAMP via PKA came from experiments where we incubated cells with the membrane permeant activator of PKA, Sp-5,6-DCl-cBIMPS [ 20 , 21 ]. Basal [Ca 2+ ] i was increased in regA - cells upon treatment with 30 μM Sp-5,6-DCl-cBIMPS for 60 min (139 ± 2 nM; mean ± s.e.m. of 15 determinations in 3 independent experiments); agonist-induced [Ca 2+ ] i -transients in nominally free Ca 2+ -buffer were unaltered in height (87 ± 8 nM; mean ± s.e.m.) as compared to control cells. In addition, we found that preincubation of wild type amoebae with 30 μM Sp-5,6-DCl-cBIMPS reduced cAMP-activated Ca 2+ -influx in cell suspensions by 26 ± 8% (mean ± s.e.m. of 3 independent experiments). Figure 4 [Ca 2+ ] i -changes in regA - cells in the presence of a Ca 2+ -chelator. Amoebae in nominally Ca 2+ -free medium were challenged with 1 mM BAPTA (final concentration) and subsequently with 1 μM cAMP. Arrows indicate the time point of addition of agents. The graph shows the average increase (mean ± s.e.m.). Light scattering and extracellular Ca 2+ oscillations depend on internal cAMP levels We had shown previously that artificial changes of [Ca 2+ ] i , either by affecting Ca 2+ -stores or by activating Ca 2+ -influx alter light scattering oscillations [ 3 , 4 ]. When light scattering was analyzed in regA - suspensions two types of responses were observed. On one hand, regular oscillations with a phase length of 4.3 ± 1 min (mean ± s.d. of 61 determinations in 6 independent experiments) occurred (Fig. 5A ). The amplitude of these oscillations was reduced as compared to wild type (Fig. 5B ), i.e. by 78%. On the other hand, irregular light scattering changes were detected (Fig. 5C ). Determination of cAMP levels revealed that cAMP scarcely oscillated in regA - (Fig. 5D ) and increased on average by a factor of 2.9 ± 0.6 (mean ± s.e.m. of 5 independent experiments). The response upon addition of cAMP was also different: after an increased first light scattering peak and the occurrence of a second peak light scattering did not return to the baseline as in wild type suspensions but fell well below (Fig. 6 ). The alteration in light scattering responses in the mutant might be due to a shift in sensitivity to cAMP. As a control we tested the reaction upon stimulation with cAMP and found that regA - cells reacted when 3 nM cAMP was added (not shown) which indicates that the mutant strain is practically as sensitive as wild type. Measurement of [Ca 2+ ] e in regA - cell suspensions revealed irregular [Ca 2+ ] e oscillations, similar to the results obtained for light scattering (Fig. 7 ). Figure 5 Light scattering and [Ca 2+ ] e oscillations of regA - cells. Light scattering and [Ca 2+ ] e were recorded as outlined in Methods. (a, b) Regular light scattering oscillations with a phase length of roughly 4–5 min but with strongly reduced amplitude as compared to wild type oscillations (see also [3]). (c) Irregular light scattering changes. (d) Oscillations of cAMP levels in the regA - strain were less pronounced than in the wild type; the graph shows examples of one cAMP oscillation each, determined during one spike of light scattering oscillations. Figure 6 Light scattering response upon addition of 1 μM cAMP. (a) Wild type cells displayed two peaks of light scattering which subsequently returned to the baseline. (b) In regA - cells there was a strong decrease in light scattering after the second peak. One out of 7 independent experiments is shown. Figure 7 [Ca 2+ ] e oscillations in wild type and regA - cell suspensions. (a) Regular [Ca 2+ ] e oscillations were recorded in wild type cell suspensions (see also [2]). (b) Similar to light scattering oscillations the pattern of [Ca 2+ ] e oscillations in regA - was irregular. One out of 5 independent experiments is shown. Chemotaxis of regA - amoebae It had been reported previously that regA - cells have a reduced capacity to suppress lateral pseudopod formation [ 14 ]. In accordance with the data presented by Wessels et al. [ 14 ] we also observed augmented lateral pseudopod extension upon challenge of aggregation competent amoebae with a cAMP filled glass capillary (not shown). The reduction in chemotactic polarization was reflected by a decrease in the average chemotactic speed as compared to wild type amoebae (Fig. 8 ). Pretreatment with EGTA to empty Ca 2+ -storage compartments dose-dependently inhibited chemotaxis of regA - and wild type. The EGTA-incubated cells were rounded and extended only small pseudopods towards the capillary tip (not shown); in both strains chemotactic velocity was reduced. The effect was more pronounced in regA - : already in the presence of 2 mM EGTA cells chemotaxed more slowly than under control conditions (velocity of EGTA-treated amoebae was significantly lower at all concentrations of EGTA tested (P < 0.001) as compared to control cells; Mann Whitney rank sum test). Wild type cells were unaffected by preincubation with 5 mM EGTA for up to 1 hour whereas at 10 mM EGTA chemotaxis was reduced. Figure 8 Chemotactic speed of wild type and regA - amoebae. The effect of preincubation with EGTA for 30 min was assayed. Chemotactic velocity of amoebae was affected dose dependently by EGTA treatment; when compared to the wild type the speed of the regA - strain was significantly reduced at lower concentrations of EGTA. Velocity of wild type and regA - cells is shown (median of at least 2 independent experiments). Discussion The cytosolic concentration of Ca 2+ was demonstrated to control light scattering oscillations by affecting the synthesis of cAMP; depending on the height of an artificial [Ca 2+ ] i -transient the production of cAMP which in this case serves as first messenger was either augmented or blocked [ 3 , 4 ]. The results presented in this study provide evidence for a reciprocal influence of the second messengers cAMP and Ca 2+ in Dictyostelium cells. We observed altered agonist-induced Ca 2+ -fluxes and [Ca 2+ ] i -transients in the regA - mutant cell line where the absence of the main cAMP-hydrolyzing PDE led to a fourfold increased basal cAMP level. One could argue that the effect on [Ca 2+ ] i was not a consequence of the increased basal concentration of cAMP but rather due to a potentially altered pattern of gene expression in the mutant strain. Indeed, this is possible and could result in a different signal perception and/or processing. However, we consider an alteration in gene expression unlikely to be responsible for the augmented [Ca 2+ ] i -transients upon cAMP-stimulation since the same effect could be evoked in wild type amoebae by loading of the PDE inhibitor IBMX into the cytosol. In addition, IBMX evoked an increase in basal [Ca 2+ ] i in both, wild type and mutant cells. In regA - the inhibitor should act on the additional cAMP-PDE (PDE-E) [ 16 , 17 ] and therefore increase cAMP levels even further. In wild type amoebae hydrolysis of cAMP should be retarded as well. Yet, the threshold of the cAMP concentration required to increase basal [Ca 2+ ] i might not be achieved as consistently as in the mutant since IBMX must act on both PDEs. The sensitizing effect of the increased amount of cAMP on [Ca 2+ ] i could be caused by several factors. Ca 2+ -flux characteristics can be changed by influencing Ca 2+ -channels and/or Ca 2+ -ATPases located on both, the plasma membrane and membranes of internal stores. When we analyzed Ca 2+ -fluxes with a Ca 2+ -sensitive electrode influx was reduced in the mutant while the rates of influx and efflux were unchanged. If the activity of the plasma membrane Ca 2+ -ATPase (PMCA) was altered then flux rates should be affected. Moreover, the reduced amount of Ca 2+ -influx precludes activation of a plasma membrane Ca 2+ -channel. In other cell systems activation of the PMCA and of Ca 2+ -channels by an increase in cAMP levels was shown [ 22 - 24 ] but our data argue against a stimulating effect on plasma membrane Ca 2+ -channel or PMCA activity in Dictyostelium amoebae. The second target of action of cAMP are intracellular stores. Indeed, we showed for the first time that in Dictyostelium a cAMP-activated [Ca 2+ ] i -elevation occurred in the extracellular presence of the Ca 2+ -chelator BAPTA. This argues for an alteration of Ca 2+ -uptake into and/or Ca 2+ -release from stores. An as yet unknown negative regulation of Ca 2+ -sequestration could cause accumulation of Ca 2+ in the cytosol; until now, however, activation of SERCA-type Ca 2+ -ATPases was found only (for review see [ 19 ]). On the other hand, release of Ca 2+ could have been augmented by the high basal cAMP level in the mutant. cAMP-dependent phosphorylation of the IP 3 -receptor by PKA results in increased sensitivity for IP 3 in pancreatic acinar cells [ 25 ]; the same holds true for the ryanodine receptor [ 19 ]. Stimulation of PKA activity is plausible since pretreatment with the PKA-activator Sp-5,6-DCl-cBIMPS elevated basal [Ca 2+ ] i and reduced agonist-evoked Ca 2+ -entry. Membrane permeable Sp-5,6-DCl-cBIMPS was shown to be virtually ineffective in inducing gene expression and to be highly selective for PKA vs cAMP receptor activation at the concentration employed [ 21 ]. In summary, we propose the following model: in the mutant sensitivity of the Ca 2+ -release system is enhanced by an augmented PKA-mediated phosphorylation which is due to increased basal cAMP levels. This results in larger amounts of Ca 2+ being liberated upon stimulation. In Dictyostelium release of Ca 2+ from stores was also found after addition of calmidazolium [ 26 ] which was shown to inhibit calmodulin-dependent and independent activity of calcineurin [ 27 ]. Calcineurin in turn was proposed to be responsible for termination of Ca 2+ -release by dephosphorylating the IP 3 -receptor [ 28 ]. In regA - augmented release of Ca 2+ leads to a reduction of Ca 2+ -entry across the plasma membrane as a negative feedback. We suggest the alteration in [Ca 2+ ] i to be responsible for the irregular light scattering and extracellular [Ca 2+ ]-oscillations of regA - cells. Previously, Wessels et al. [ 14 ] have shown that the mutant cannot propagate a cAMP wave since wild type amoebae no longer aggregated correctly when mixed with mutant cells. Indeed, we found that peak cAMP levels during light scattering oscillations were very low in regA - as compared to wild type. This effect is plausible, as the increased sensitivity of the Ca 2+ second messenger system exerts a negative feedback on cAMP synthesis: large [Ca 2+ ] i -transients inhibit production of cAMP [ 3 ]. An interplay of cAMP and [Ca 2+ ] i -oscillations and their mutual dependence has also been shown in neurons: absence of either, cAMP or [Ca 2+ ] i -oscillations resulted in failure of the other component to oscillate [ 8 ]. In Dictyostelium the strong decrease in peak cAMP oscillation levels affected [Ca 2+ ] e -oscillations which were irregular. The basis is probably an influence on [Ca 2+ ] i -oscillations. Such oscillations were suggested to occur but have not been demonstrated in single cells until now, presumably due to the small size of the amoebae and the characteristics of the wave [ 29 ]. With respect to chemotaxis, reduced suppression of lateral pseudopod formation was shown in regA - cells and an essential role of RegA for a correct response in a natural cAMP wave and chemotactic migration was assigned [ 14 ]; subsequently, a similar result was found in a mutant expressing a constitutively active PKA [ 30 ]. When we analyzed chemotaxis towards a cAMP-filled glass capillary we observed the same behaviour as described by Wessels et al. [ 14 ]. In principle, it is possible that the reduced capacity of regA - cells to polarize was due to a difference in the developmental stage as compared to wild type cells. However, regA - develops much faster than wild type which suggests an even more efficient chemotaxis as this response increases during differentiation to aggregation competence. Alternatively, an altered or dampened signaling response caused by a lower number of cAMP receptors present on the cell surface could have caused the reduced chemotactic response. We consider this to be unlikely for the following reason. Aggregation-competent Dictyostelium amoebae possess roughly 50.000 cAMP receptors at the cell surface [ 31 ]. Yet, for chemotactic orientation and polarization in a cAMP gradient the difference in receptor occupancy between the front and the rear end of the amoebae is important rather than the absolute number of stimulated receptors [ 31 ]. So even if regA - expressed less receptors than wild type this should not influence the accuracy of the response. We propose the reduced polarization capacity of regA - amoebae to be caused by their altered [Ca 2+ ] i -regulation. In the mutant strain the threshold for generation of an agonist-induced [Ca 2+ ] i -increase is lower than in wild type. The [Ca 2+ ] i -elevation is not as tightly controlled and occurs even in the presence of BAPTA. The characteristics of a [Ca 2+ ] i -increase are important for the resulting cytoskeletal rearrangements and whether pseudopods are formed correctly. Indeed, artificial induction of a small global [Ca 2+ ] i -transient by incubation with calmidazolium caused overall pseudopod protrusion [ 26 ]. In migrating cells the establishment of a [Ca 2+ ] i -gradient at the rear end was shown [ 5 , 32 ] which indicates the presence of a highly organized spatial [Ca 2+ ] i -pattern during chemotaxis. By contrast, a role of the [Ca 2+ ] i -elevation for the chemotactic response was questioned by Traynor et al. [ 33 ] because a mutant disrupted in a gene bearing similarity to IP 3 -receptors of higher eukaryotes aggregated and differentiated almost normally but displayed no cAMP-activated global [Ca 2+ ] i -change; yet, the existence of localized, small [Ca 2+ ] i -transients in this particular mutant cell line that had escaped detection could not be excluded [ 33 ]. When we analyzed the influence of pretreatment with EGTA on chemotactic behaviour of wild type and regA - cells we found that the mutant was more sensitive. When compared to wild type, lower doses of EGTA were sufficient to reduce chemotactic speed. The effect of EGTA treatment is most probably due to emptying of the storage compartments [ 34 ]; the presence or absence of extracellular Ca 2+ affects the Ca 2+ -content of stores [ 35 , 36 ]. RegA - cells are more sensitive than wild type amoebae because of the lower threshold for Ca 2+ release and thus a more rapid depletion of Ca 2+ in the cells. Conclusion Abnormal basal levels of cAMP impair chemotactic performance by augmenting agonist-activated [Ca 2+ ] i -elevations which in turn lead to uncontrolled pseudopod extension. [Ca 2+ ] i regulates cAMP acting as first messenger in a negative feedback loop: when the [Ca 2+ ] i response is increased the amount of cAMP synthesized upon stimulation is low as observed in regA - cells devoid of the phosphodiesterase RegA. The low level of cAMP relay results in improper light scattering oscillations. We conclude that intracellular cAMP acts on [Ca 2+ ] i via PKA: phosphorylation of the system responsible for release of Ca 2+ from stores leads to a greater sensitivity facilitating Ca 2+ liberation. The cAMP activated [Ca 2+ ] i -increase is due to Ca 2+ -release from internal stores which triggers subsequent extracellular Ca 2+ -entry. The fraction of the [Ca 2+ ] i -elevation that is mediated by liberation of Ca 2+ is thus larger in the mutant. Methods Materials Fura2-dextran and BAPTA were from MoBiTec (Göttingen, FRG). IBMX was purchased from Sigma (Munich, FRG) and cAMP was from Boehringer (Mannheim, FRG). Sp-5,6-DCl-cBIMPS was from Biomol (Hamburg, FRG). Cell culture D. discoideum axenic wild type Ax2 was grown as described [ 4 ]; the mutant regA - (kindly provided by Dr. P. Thomason) was grown in the presence of blasticidinS. Cells were washed by repeated centrifugation and resuspension of the cell pellet in cold Sørensen phosphate buffer (17 mM Na + /K + -phosphate, pH 6.0; SP-buffer). Amoebae were shaken at 2 × 10 7 cells/ml, 150 rpm and 23°C until use. The time, in hours, after induction of development is designated t x . Recording of light scattering At t 2.5 –t 4 2 ml of cell suspension was pipetted into cuvettes and aerated. Light scattering oscillations were recorded at 500 nm with a photometer as described [ 4 ]. Determination of cAMP The total amount of cAMP was determined using the cAMP enzyme immuno assay (Biotrak, Amersham Pharmacia Biotech, Freiburg, FRG) according to the manufacturer's instructions. Samples were prepared as outlined previously [ 4 ]. Extracellular [Ca 2+ ]-measurements The extracellular Ca 2+ -concentration ([Ca 2+ ] e ) was measured in 2 ml of cell suspension (5 × 10 7 cells/ml in 5 mM Tricine, 5 mM KCl, pH 7.0) with a Ca 2+ -sensitive electrode (Möller, Zürich, Switzerland) as described [ 18 ]. [Ca 2+ ] e -oscillations were measured at a cell density of 1 × 10 8 cells/ml. Single cell [Ca 2+ ] i -imaging Cytosolic [Ca 2+ ]-imaging was done as outlined in [ 6 ]. Cells (5 × 10 7 cells/ml; 20 μl) were loaded at t 3 with the Ca 2+ -indicator fura2-dextran (concentration in the loading solution: 5 mg/ml SP-buffer + 1 mM CaCl 2 ) by electroporation (0°C, 850 V, 3 μF, 200 Ω). Immediately after electroporation, 80 μl of cold 5 mM MgCl 2 was added and cells were incubated for 10 min on ice. Then cells were washed 3× with 5 mM Hepes, pH 7.0 (H5-buffer). Washed cells (2–5 μl) were placed on glass coverslips and incubated in a humid chamber until use. When experiments were done in nominally Ca 2+ -free medium, 85–88 μl of H5-buffer was added 1 min before the [Ca 2+ ]-imaging experiment. To test the response of amoebae in the presence of BAPTA, 75–78 μl of H5-buffer was pipetted to the cells; 10 μl of 10 mM BAPTA was added during the [Ca 2+ ]-imaging experiment and 10–12 sec later cAMP was given. When the response of cells was to be analyzed in the presence of extracellular CaCl 2 , H5-buffer (85–88 μl) with 1 mM CaCl 2 was added to the cells 15 min before the [Ca 2+ ]-imaging experiment to load stores (see also [ 18 ]). cAMP-stimulation was done by adding 10 μl of 10 μM cAMP (± 1 mM CaCl 2 ) to the cells. To load cells with IBMX, they were electroporated with fura2-dextran in the presence of 250 μM of the inhibitor. The cytosolic concentration of IBMX is in the range of maximally 2–5% of the concentration present during electroporation [ 6 ]. Measurement of regA - was done at t 4 and wild type [Ca 2+ ]-imaging was done at t 7–8 . In another series of experiments we treated regA - cells with Sp-5,6-DCl-cBIMPS, a membrane permeant activator of PKA [ 20 ]. Incubation was done with 37 μM of the activator for 60 min prior to the [Ca 2+ ]-imaging experiment. Chemotaxis of regA - cells Chemotactic performance of the amoebae depends on the degree of differentiation, so their shape was checked prior to the chemotaxis assay. 200 μl of cells at 2 × 10 7 cells/ml were placed on a coverslip and allowed to settle for at least 30 min. The morphology of the cells was controlled microscopically: when elongated and thus aggregation competent cells were present, an aliquot of cells from the suspension was diluted for the chemotaxis assay. RegA - was tested at t 4 –t 5 , wild type was measured at t 7 –t 10 . 250 μl of cells in 5 mM Hepes, pH 7.0 (1 × 10 5 cells/ml) were placed on glass coverslips. After 30 min cells were challenged with a cAMP (100 μM) filled glass capillary and chemotaxis was recorded for 40–45 min either on vidoe tape or images were stored directly on a hard disk. In addition, experiments were done with cells incubated with 2–10 mM EGTA for 30 min to empty Ca 2+ -storage compartments. Analysis of chemotaxis was done as outlined previously [ 34 ]. List of abbreviations Cytosolic free Ca 2+ concentration: [Ca 2+ ] i Phosphodiesterase: PDE 3-isobutyl-1-methylxanthine: IBMX cAMP-dependent protein kinase: PKA Plasma membrane Ca 2+ -ATPase: PMCA Authors' contributions DFL performed extracellular [Ca 2+ ] recordings and light scattering experiments. He also determined cAMP levels and designed the study. KBR did chemotaxis experiments at different external conditions. KH carried out [Ca 2+ ] i -measurements. CS did [Ca 2+ ] i -imaging experiments, designed the study and wrote the manuscript. All authors read and approved the manuscript.

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526759

Second edition of 'The Bethesda System for reporting cervical cytology' – atlas, website, and Bethesda interobserver reproducibility project

A joint task force of the American Society of Cytopathology (ASC) and the National Cancer Institute (NCI) recently completed a 2-year effort to revise the Bethesda System "blue book" atlas and develop a complementary web-based collection of cervical cytology images. The web-based collection of images is housed on the ASC website, which went live on November 5 th , 2003; it can be directly accessed at .

The second edition of the Bethesda 'blue book' atlas maintains an easy to read format with bulleted morphologic criteria and half-page color illustrations. The content has been divided into chapters based on the major 2001 Bethesda System interpretive categories. Highlights of the new edition include: (1) incorporation of liquid based cytomorphologic criteria and images; (2) new sections addressing ancillary testing, educational notes and recommendations, computer assisted interpretation and anal-rectal cytology; and (3) inclusion of sample reports, references, and detailed legends for images. Overall, the second edition has tripled in size from the original version, with a total of 186 images of which 90% are new images and 40% are from liquid based specimens. Some are classic examples of an entity while others have been selected to illustrate interpretive dilemmas or "borderline" cytomorphologic features that may not be interpreted in the same way by all cytologists. In parallel with production of the Bethesda book atlas, the ASC-NCI task force has also developed a Bethesda web-based collection of images. Approximately 350 images, (40% of which are from liquid based specimens) along with linked explanatory notes, including all the images in the published atlas, can be viewed on this site. The website is user friendly and has several search modalities for viewing the images including searching by Bethesda terminology, atlas chapter headings, keyword(s), or preparation type. It also allows for individual self-assessment by participating in a "self test" in which viewers can compare their interpretation to other participants' responses. The image selection process for the book atlas and website involved a multistage review: Step 1 : individual Bethesda forum group members (32 participants) reviewed and selected images for their chapter from among those in the first edition of the atlas and new submissions; and Step 2 : the images selected from Step 1 were reviewed individually ("validated") by 13 task force members and scored on a scale of 1–5 for agreement with interpretation and quality of image. In all over 1000 images were reviewed of which 186 images were selected for the atlas and an additional 163 for the website. A subset (n = 77) of the book atlas images were posted as "unknowns" on the Internet from mid July to mid September 2003 as part of a study – the Bethesda Interobserver Reproducibility Project (BIRP). The site was open to the cytopathology community to view the images and provide their interpretations. Immediately after submitting their response, participants were able to view a histogram of the distribution of results submitted by all prior participants for that image. Over 600 cytologists from around the world participated in BIRP. Summary histograms for each of the 77 images can be viewed on the Bethesda atlas website (select BIRP images from the left menu). Preliminary BIRP results presented at the ASC annual meeting in Orlando in November 2003 showed that Negative for Intraepithelial Lesion or Malignancy (NILM) and Low Grade Squamous Intraepithelial Lesion (LSIL) reference images attained the highest concordance scores, while glandular abnormalities demonstrated the most splay in distribution of interpretations. BIRP analyses are ongoing and further results should be available in 2004. ASC-NCI Working Group for the Second Edition Bethesda Atlas and Website ASC Bethesda 2001 Task Force: Ritu Nayar (Chair), Diane Solomon (Co-Chair, NCI) George Birdsong (Adequacy), Jamie Covell (Glandular Lesions), Ann Moriarty (Endometrial cells), Dennis O'Connor (Educational notes and recommendations), Marianne Prey (Computer assisted interpretation), Steve Raab (Ancillary testing), Mark Sherman (Atypical squamous cells), Sana Tabbara (Other malignant neoplasms), Tom Wright (Squamous lesions), Nancy Young (Non-neoplastic findings). ASC Consultants : ASC 2002/2003 Presidents: Diane Davey and Dave Wilbur . Information Technology representatives : Mike Montgomery (NCI) and Brandon Winbush (Northwestern University), Aquilent (Laurel, MD) . The second edition of the 'blue book' atlas can be ordered through Springer-Verlag (1-800-SPRINGE) for $34.95.

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423153

Computation Approach Shows Robustness of the Striped Pattern of Fruitfly Embryos

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Since the days of ancient Greece, mathematics has been used to describe the world in the hopes of identifying underlying laws of nature. Physicists have long relied on mathematics to understand the behavior and interaction of particles too small to observe directly. Since it's not always possible to determine the behavioral properties of a single atom or electron, physicists characterize the behavior of these particles in terms of probability and the law of averages. Likewise, it's not always easy to tell how a single protein contributes to the behavior of a cell or organism. Faced with increasingly immense datasets—from genomes, proteomes, gene expression networks, cell signaling pathways, and more—biologists are turning to the tools of higher mathematics. High-throughput technologies like genome sequencers and microarrays generate a global picture of genomic or cellular activity, but such datasets have a high noise-to-signal ratio—the details are often subject to multiple interpretations. One way computational methods can help separate the signal from the noise is by determining the likelihood of a given set of interactions and presenting a range of possible network behaviors. When sufficient information about a biological pathway is available, experimental evidence can enhance modeling approaches to help refine the nature and role of putative network behaviors. (To learn more about computational biology, see the essay “A Calculus of Purpose,” by Arthur Lander, also in this issue of PLoS Biology .) Cell behaviors for segment polarity patterning One model system ripe for computational analysis is the fruitfly Drosophila melanogaster , genetically the best-understood multicellular organism. Drosophila development proceeds through a complex series of both sequential and simultaneous events. An elaborate network of genetic interactions transforms a single-cell Drosophila egg into a multicellular embryo with 14 discrete segments. These segments are the result of a series of hierarchical decisions, as one set of genes induces the characteristic expression pattern of another set: “gap” genes direct the striped expression pattern of “pair rule” genes, which induce expression of segment polarity genes, whose messenger RNA (mRNA) and protein products produce the characteristic 14-segment polarity pattern. While the molecules and pathways that generate the segment polarity pattern are well known, little is known about the quantitative nature of their interactions: in what concentrations do the components (for example, mRNAs and proteins) exist and what parameters (for example, binding constants, transcription rates, and gene product life spans) govern their interactions? Four years ago a group of researchers led by George von Dassow developed a model of the genetic interactions that define segment polarity, called the segment polarity network. The model used a parameter set of 48 numerical values for each computer simulation of the segment polarity pattern. Since quantitative information about the network was unavailable, the group used random values for each of the parameters, repeating the simulation for nearly 250,000 different random parameter sets. The model proved remarkably robust—the network output was largely insensitive to variation in parameter values, with a surprisingly large fraction of random parameter sets generating the desired segment polarity pattern. That so many random variables could produce the pattern means either that almost any set of parameter values can work or that only a few of the parameters are important. Now, Nicholas Ingolia reveals the mechanism accounting for this robustness and bolsters the model with recent experimental evidence. To investigate the reason for the original model's robustness, Ingolia asked whether the parameters of the model could be deconstructed into the properties of individual cells. It's known, for example, that the stable expression of two genes, called wingless (wg) and engrailed (en) , within specific cells of a “prepattern” laid down early in embryogenesis is converted into the segment polarity pattern by an intercellular signaling network. Wg and en operate through positive feedback loops that activate their own expression, a process that is destined to end up with individual cells in one of two stable states of gene expression (an outcome called bistability). Since each stable state is intrinsically robust—that is, resistant to changing parameters—Ingolia hypothesized that the parameters that generate the robustness of the segment polarity pattern in von Dassow's model are those that produce this bistability. Using computational methods to simulate the behavior of individual cells, Ingolia shows that individual cells in the original model adopt three different stable states of wg and en expression. The overall pattern of the model, as well as its insensitivity to parameter variation, Ingolia concludes, emerges from the stable expression states of single cells. Parameters that do not produce bistability within single cells, Ingolia found, almost never generate the correct pattern, while those that do produce bistability are much more likely than randomly chosen parameters to generate the striped segment pattern. When Ingolia added new experimental variables to the model—the signaling protein produced by the sloppy-paired gene and its interactions with en —he could reduce the fraction of parameter sets that satisfied the bistability requirement but nonetheless failed to produce the segment polarity pattern, refining the model to reflect the realities of the cell. Such computational approaches are allowing biologists to gain valuable insights into the real-world properties and behavior of staggeringly complex biological networks. It's been over 2,000 years since Pythagoras proposed that the laws of heaven and earth reflect a numerical harmony rooted in mathematical laws. Whether that notion holds for biology, bit by bit the tools of higher mathematics are peeling back the layers of complexity to identify underlying properties of living systems.

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526765

Genomic imprinting and assisted reproduction

Imprinted genes exhibit a parent-of-origin specific pattern of expression. Such genes have been shown to be targets of molecular defects in particular genetic syndromes such as Beckwith-Wiedemann and Angelman syndromes. Recent reports have raised concern about the possibility that assisted reproduction techniques, such as in vitro fertilization or intracytoplasmic sperm injection, might cause genomic imprinting disorders. The number of reported cases of those disorders is still too small to draw firm conclusions and the safety of these widely used assisted reproduction techniques needs to be further evaluated.

Introduction The first in vitro fertilization (IVF) baby was born in 1978 and intracytoplasmic sperm injection (ICSI) was introduced in 1992 for the treatment of male infertility. Both these techniques have been continually amended and access to them improved for infertile couples. Indeed, assisted reproduction now accounts for 1% to 3% of births in developed countries [ 1 ]. Until recently, these techniques were considered accurate substitutes for natural oocyte fertilization, and were therefore regarded as safe. However, reports of children conceived by assisted reproduction techniques (ART), and presenting with congenital anomalies have been published over the last 3 years. Even though the number of reported cases indicating a link between ART and congenital anomalies is still small, the safety of these techniques needs to be evaluated. In particular, the relationship between ART and the occurrence of imprinting defects needs to be clarified. Epigenetics and DNA methylation Epigenetic modifications are reversible changes of the DNA methylation pattern and chromatin structure that can affect gene expression. In many instances, epigenetic changes governing gene expression can be passed from cell to cell or from parent to offspring. Epigenetic modifications themselves might therefore explain how environmental factors modulate gene expression without affecting the genetic code. The most researched epigenetic phenomenon is DNA methylation [ 2 ]. DNA methylation is a covalent modification in which methyl groups are added to cytosine bases located 5' of guanosines (within cytosine-phospho-guanine (CpG) dinucleotides sequences). Methylation is catalyzed by the DNA cytosine-5-methyltransferase (DNA-MTase) enzyme family. Methylation induces changes in chromatin structure and is generally associated with silencing of gene expression, thus providing a way to control gene expression [ 3 ]. Indeed, methylation patterns are the result of complex interactions between de novo methylation, the maintenance of existing methylation and demethylation [ 4 ]. Imprinting Genomic imprinting is an epigenetic phenomenon by which the expression of a gene is determined by its parental origin. Only one allele of an imprinted gene is expressed. Imprinting is controlled by DNA methylation in such a way that a difference in methylation between the maternal and paternal alleles correlates with the different expression of the two parental alleles. It is estimated that the total number of imprinted genes in the human and mouse genomes ranges between 100 and 200 [ 5 ]. Imprinted genes are more often grouped into clusters than scattered throughout the genome and this organization most likely reflects a coordinated way of gene regulation in a chromosomal region [ 6 ]. Two features are characteristic, although not specific, to imprinted genes. The first one is the unusual richness in CpG islands onto which imprinted patterns of methylation are placed, and the second one is the presence of clustered direct repeats near or within the CpG islands [ 7 ]. Imprinting in development In order to ensure that every generation receives the appropriate sex-specific imprint, the genome undergoes reprogramming. Epigenetic reprogramming has been shown to occur during gametogenesis and during preimplantation development [ 6 ]. During the development of primordial germ cells (PGC), imprinted methylation patterns are removed by a mechanism of erasure [ 8 ]. Both, passive and active demethylation may occur, although no active demethylating enzymes have yet been identified. The timing of erasure in PGCs is thought to be crucial. Studies in mice showed that erasure occurred when primordial germ cells enter into the gonads [ 8 , 9 ]. Erasure is followed by the establishment of sex-specific patterns of methylation during gametogenesis. Imprint establishment during gametogenesis occurs at different times in the male and female germ lines. In males it is completed by the haploid (meiotic) phase of spermatogenesis whereas in females imprint acquisition occurs in oocytes around the time of completion of the first meiotic division [ 5 ]. Furthermore, it seems that at least in oocytes, methylation might be acquired at different times (asynchronous) for different genes [ 5 ]. Epigenetic reprogramming is important for accurate development, as it controls expression of early embryonic genes, cell cleavage and cell determination in the early embryo [ 10 ]. Further genome reprogramming occurs during the preimplantation embryonic stage with epigenetic changes taking place through demethylation in non-imprinted genes in maternal and paternal genomes. This is followed by a genome-wide methylation at the time of implantation. The different stages of imprint establishment, maintenance and manipulations possibly disturbing them are illustrated in Figure 1 . Genomic imprinting defects might indeed occur at any stage of the reprogramming process, such as during imprinting erasure, acquisition or maintenance. Figure 1 ART and possible imprinting defects. Possible interactions between different steps of assisted reproduction procedures and imprint establishment or maintenance through different stages of development. PGC: primordial germ cell. The main consequence of the sex-specific establishment and maintenance of imprinted methylation patterns is the creation of maternal- and paternal-allele methylation differences (differentially methylated domains or DMDs) in or around imprinted genes. A primary DMD is established during gametogenesis and secondary DMDs develop during embryogenesis, most likely due to a direct influence of a nearby primary DMD [ 11 ]. Imprinted genes are implicated in the regulation of embryonic and fetal growth, as well as many aspects of placental function, including placental growth and the activity of transplacental transport systems [ 12 ]. Indeed, in ruminants, such as sheep and cattle, a particular overgrowth syndrome known as "large offspring syndrome" (LOS) was reported after in vitro culture of embryos. LOS is caused by abnormal methylation of the IGF2R gene [ 13 ]. Imprinted genes are also involved in postnatal behavior development. Based on the functions of imprinted genes, disruption of normal imprinting can have predictable consequences such as embryonic death, excessive, defective or impaired fetal growth. Imprinting defect syndromes in human Several human syndromes are known to be associated with defects in gene imprinting, including Prader-Willi, Angelman, Beckwith-Wiedemann, Silver-Russell and Albright hereditary oseodystrophy syndromes [ 1 ]. Aberrant imprinting might also play a role in cancers and neuro-behavioral disorders such as autism. The Beckwith-Wiedemann syndrome (BWS), whose frequency in the general population is about 1/14,000, is characterized by somatic overgrowth, congenital malformations and a predisposition to embryonic neoplasia. The majority of cases occur sporadically. In up to 60% of sporadic cases, the epigenetic changes occur at differentially methylated regions within 11p15.5 in a region of approximately 1 Mb. This region contains an imprinted cluster of at least 12 genes, including the paternally expressed genes IGF2 and KCNQ1OT1 , and the maternally expressed genes H19 , CDKN1C and KCNQ1 [ 14 ]. Approximately 25 to 50% of BWS patients have biallelic expression of the IGF2 gene, and some of these cases exhibit loss of imprinting (LOI) of IGF2 which is dependent on hypermethylation changes of H19 [ 14 ]. Approximately 50% of sporadic BWS have a loss of methylation associated to a LOI at KCNQ1OT1 , an untranslated RNA within the KCNQ1 gene [ 15 ]. Some BWS cases exhibit LOI for KCNQ1OT1 as well as LOI for IGF2 [ 14 ]. It has been shown in BWS patients that aberrant methylation of KCNQ1OT1 is specifically associated with overgrowth and congenital defects, whereas aberrant methylation of H19 is specifically associated with an increased risk of developing tumors [ 16 ]. The Prader-Willi and Angelman syndromes (PWS/AS) are typical examples of imprinting dysregulations leading to severe neuro-behavioral disturbances. Their frequencies in the general population are approximately 1/10,000 and 1/15,000, respectively. The domain involved in these two pathologies is a 2 Mb domain on the 15q11–13 chromosomal region, including genes as SNRPN , UBE3A , ZNF127 , IPW and NDN . The small percentage of AS cases (<5%) associated with methylation defect involves loss of methylation within the SNRPN imprinting center (IC) and defective expression or silencing of maternally expressed genes within this region. However, the methylation defect associated with PWS involves methylation within the SNRPN IC and a defective expression or silencing of paternally expressed genes within the same region. The IC comprises 2 regulatory regions: the PWS-shortest region of overlap (SRO) and the AS-SRO [ 17 ]. PWS-SRO and AS-SRO seem to operate in a stepwise way to establish imprinting during the early developmental stages [ 18 ]. Indeed, imprinting at the AS-SRO might cause maternal allele-specific repression of the PWS-SRO, preventing activation of the corresponding genes [ 17 ]. In addition, imprinting may have a wider impact on neurological development and behavior. Some reports suggest parent-specific imprinting defect in common neuro-behavioral disorders. Autism, bipolar affective disorder, schizophrenia [ 19 ] and other complex neuro-behavioral phenotypes such as alcohol abuse and audiogenic seizures [ 20 ] may be linked to imprinting disturbances. The transmission of abnormalities has been shown to be dependent upon which parent transmits the disease susceptibility. Such parent-of-origin effects on disease manifestation may be explained by a number of genetic mechanisms, one of them being genomic imprinting [ 21 ]. For instance, a lower age of onset of symptoms following paternal inheritance of one subtype of schizophrenia and following maternal inheritance of Tourette's syndrome suggests that imprinted genes are involved in the pathophysiology of these syndromes. Similarly, parent-specific components for late-onset Alzheimer's disease (paternal-specific component) or familial neural tube defects (maternal-specific component) have been described [ 20 ]. Cases of defective imprinting in ART conceptions Prior to the establishment of sex-specific imprints in male and female germ cell lineages, imprints are erased. After erasure of the pre-existing imprints, the timing of acquisition of imprints is significantly different between the two germ lines [ 6 ]. In the female germ line, methylation occurs in the postnatal growth phase while oocytes are arrested at the diplotene stage of prophase I [ 22 ], whereas during spermatogenesis, methylation takes place before meiosis [ 23 ]. Maternal imprints are continually established as oocytes mature in females, and paternal imprints are established as long as spermatogonia proliferate in males. Thus, paternal imprints seem to be established earlier than maternal ones. It has been shown that this sex-specific methylation is intrinsic and cell-autonomous, and is not due to any influence of the genital ridge somatic cells, or gonadal environment on the primordial germ cells [ 24 ]. Imprinting defects in the course of assisted reproduction could theoretically occur during several stages of the methylation erasure/re-methylation process in male and female germ cells as well as during the early stages of in vitro embryonic development. The first baby conceived by IVF was born 26 years ago. Intracytoplasmic sperm injection (ICSI), developed approximately 10 years ago, was seen to be the reproductive solution for severe male infertility. Several studies have established the general safety of both IVF and ICSI [ 25 ]. Nevertheless, it was recently reported that IVF and ICSI may be associated with an increased risk of major birth defects. Schieve et al. [ 26 ] studied 42 463 infants conceived with assisted reproductive techniques and reported a higher occurrence of low (less-than-or-equal 2500 g) and very low (less-than 1500 g) birth weight in this group compared to the control population of children naturally conceived. Hansen et al. [ 27 ] in a study on 837 infants conceived by IVF and 301 infants conceived by ICSI, reported rates of major birth defects (musculoskeletal, cardiovascular, urogenital, gastrointestinal, central nervous system, metabolic and poorly defined ones), as high as 9.0% for IVF and 8.6% for ICSI conceptions, compared to 4.2% reported for natural conceptions. A possible link with imprinting disturbances was not considered by the authors. These results were in part due to the increase in multiple pregnancies, known to be associated with ART, but also due to a higher rate of low birth weight babies among singleton pregnancies. In addition to these associated defects, a higher incidence of sex-chromosome aneuploidy has also been reported in ART conceptions [ 27 ]. DeBaun et al. [ 28 ] recently reported 7 cases of BWS conceived by ART, 6 of those showing an imprinting defect at KCNQ1OT1 or H19. By comparing this rate of ART-conceived BWS to the rate of ART in the general population during the same time period, sporadic cases of BWS were approximately six times more likely to have been conceived by ART than by natural conception. The authors suggested that causative factors may include the in-vitro culture conditions or the exposure of the gametes or embryos to specific media or growth factors. Maher et al. reviewed a different set of sporadic BWS cases and looked for an association with ART [ 29 ]. Six out of the 149 BWS cases examined were conceived by ART, and 2 of these had a KCNQ1OT1 loss of imprinting as the causative molecular defect. Indeed, when compared to the incidence in the general population, ART had a four-fold greater likelihood of being associated with BWS than natural conception. The cases reported by DeBaun et al. [ 28 ] and Maher et al. [ 29 ] were recruited through registries of BWS patients. However, parents with BWS babies born after ART may be more likely to join BWS registries, which could introduce bias when using these registries. Recently, a case-control study analyzed the frequency of BWS in 1'316'500 live births and 14'894 babies born after an IVF procedure [ 30 ]. The risk of BWS was reported to be 9 times higher in the IVF population compared to the general population. Cox et al. [ 32 ] and Orstavik et al. [ 33 ] reported a total of 3 children with Angelman syndrome conceived by ICSI. In all 3 cases, AS was due to loss of imprinting within SNRPN gene at 15q11–13. Considering that the occurrence of AS in the general population is about 1/15,000 and that <5% of cases are due to epigenetic imprinting defects, these reports suggest that the predominant abnormalities seen in ART are epigenetic rather than genetic. However, no evidence of abnormal methylation patterns at 15q11–13, the locus linked to the pathogenesis of AS and PWS, was found in 92 children conceived by ICSI [ 31 ]. Why might ART be harmful for the imprints For assisted reproduction by intracytoplasmic sperm injection (ICSI), the injection of a spermatozoon into the ovum by micro-manipulation bypasses several of the steps involved in fertilization. However, in male germ cells, it seems that the paternal imprints are well established in the mature, meiotic stages of spermatogenesis. Furthermore, round spermatid microinjections have confirmed that paternal imprints are completely established in primary spermatocytes [ 34 ]. This point is relevant to the recent use of ICSI using round spermatids. Manning et al. [ 35 ] have analyzed the methylation pattern in immature testicular sperm cells at different developmental stages at the 15q11–13 imprinted region and reported that the ejaculated spermatozoa and elongated spermatids had completed the establishment of paternal methylation imprints. However, spermatozoa used for ICSI generally originate from men with abnormal semen parameters that may have had adversely affected the establishment of imprints. Moreover, immature spermatozoa for ICSI can also be directly collected from the testes of infertile males. It has been hypothesized that spermatozoa from men with fertility problems contain a higher number of gametes with chromosomal abnormalities [ 36 ]. A defect in gene imprinting can be considered as a possible sperm abnormality. Indeed, a recent report has analyzed the imprinting of two opposite imprinted genes ( MEST and H19 ) in spermatozoon DNA from normozoospermic and oligozoospermic patients. The data presented suggest an association between abnormal genomic imprinting and hypospermatogenesis [ 37 ]. Theoretically, it is possible that freezing of mature sperm or the cryoprotectants used might disturb the established male imprints in mature spermatozoa or round spermatids. Women with a variety of fertility problems, such as ovarian failure and/or hormonal disturbances, may be more prone to produce gametes with inherent imprinting defects because of the establishment of maternal imprints during the final phase of oocyte growth and meiotic maturation. Although biologically plausible, this is purely speculative at the moment. In addition to the theoretical possibility that there may be innate defects in oocytes used in ART, the in vitro treatment of oocytes and embryos during ART procedures might affect the establishment of imprints in female germ cells. For example, superovulation or in vitro maturation of oocytes might affect the establishment of the complete array of normal maternal imprints. Oocytes used for assisted reproduction usually originate from women who undergo hormonal hyperstimulation protocol followed by fertilization in vitro. It is not clear to date if the clinical use of high doses of gonadotrophins might alter imprint acquisition. Gonadotrophins might cause the premature release of immature oocytes that have not completed the establishment of their imprints, and establishment may not be completed during in vitro maturation. Shi and Haaf [ 38 ] determined the possible incidence of abnormal methylation patterns in mice embryos from superovulated compared to non-superovulated female mice. An immunostaining method was used to assess the overall extent of genomic cytosine methylation and reported abnormal methylation patterns in 2-cell embryos from superovulated females as compared to non-superovulated ones. Kerjean et al [ 39 ] explored in mice whether maternal imprinting progresses normally when oocytes are cultured in vitro. The authors analyzed the DMDs of 3 imprinted genes and reported that indeed in vitro culture affected imprint establishment and might lead to loss of methylation at certain imprinted loci, such as IGF2R and gain of methylation at other loci, such as H19 . However, to our knowledge, no data concerning the possible effects of ovarian hyperstimulation on imprinting in humans is available yet. Potential disruption of normal imprinting could result from the in vitro manipulation of early stage embryos. In vitro culture with the use of slightly different culture media led to decreased fetal viability and imprinting disturbances in mice. Doherty et al. [ 40 ] first reported the differential affects of culture media in preimplantation mouse embryos at the H19 imprinted gene. The loss of methylation at H19 gene was associated with culture in Whitten's media, resulting in LOI in the imprinting control domain upstream of the start of H19 transcription. Khosla et al. [ 41 ] examined mouse preimplantation mouse embryos cultured in different culture media and transferred into recipient mothers. Fetal development as well as the expression pattern of imprinted genes, including the IGF2 and H19 genes, was influenced by the addition of fetal calf serum (FCS) in the culture media. The mechanism by which culture media and other gamete or embryo handling might induce defects and lack of maintenance of methylation at imprinted loci is not clear. It may be due to the facilitation of removal of methyl groups on cytosine bases or the disturbance of the gamete development leading to incompleteness of imprint erasure and/or establishment [ 10 ]. Furthermore, cryopreservation of embryos could potentially affect the cytoskeleton, chromatin structure and the availability of methylating and/or demethylating enzymes during preimplantation development. However, it is not known at present if culture of human preimplantation embryos in different media or over longer periods – might lead to disturbances in genomic imprinting. Disturbances in imprinting could affect the germline cells of the embryo conceived by assisted reproduction and the problems of imprinting might occur in the offspring of the subsequent generation [ 10 ]. Follow-up of these individuals may give important information about the possible risks associated with ART. Imprinting and placenta A critical way of regulating intrauterine development is through placental function and growth. Most imprinted genes are expressed in fetal and placental tissues, and are involved in fetal growth [ 12 ]. In general, paternally expressed imprinted genes enhance fetal growth whereas maternally expressed imprinted ones suppress it [ 6 ]. Among the genes expressed in the placenta, the MASH2 gene was shown to regulate the development of spongiotrophoblast [ 42 ]. Igf2 transcripts are found specifically in the labyrinthine trophoblast [ 43 ], and ASCL2 is a transcription factor expressed in the spongiotrophoblast and labyrinthine layers [ 5 ]. Indeed, mice with deletions of IGF2 and ASCL2 genes showed fetal growth restriction and death during embryonic development [ 43 , 42 ]. In humans, several imprinting disorders are associated with intrauterine growth restriction (IUGR) [ 44 ]. Studies on human placental imprinted genes and on the different roles of the maternally and paternally expressed genes are certainly needed to understand the placenta's role in normal embryonic and fetal development. Furthermore, analyses of placental samples obtained after ART conceptions might provide answers to some important questions about the possible links between ART and genomic imprinting. Conclusion Concern has been raised about the possible increased incidence of genetic syndromes due to imprinting defects in children conceived by assisted reproduction. In particular, experimental reports in mice have raised the question that some of the steps involved in these techniques, such as ovarian hyperstimulation or certain culture media for in vitro culture of embryos might be detrimental to the formation of genomic imprints. In order to be able to adequately counsel infertile couples enquiring about ART, solid evidence from large, well-designed studies as well as cautious long-term evaluation of the safety of these techniques need to be available. Although the unraveling of the mechanisms underlying genomic imprinting is only at the beginning, there is a clear need to investigate and better understand the regulation of this process during fecundation and embryogenesis. Competing interests The authors declare that they have no competing interests. Authors' contributions Both authors contributed to the writing of this review and both read and approved the final manuscript.

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524172

Prediction of DtxR regulon: Identification of binding sites and operons controlled by Diphtheria toxin repressor in Corynebacterium diphtheriae

Background The diphtheria toxin repressor, DtxR, of Corynebacterium diphtheriae has been shown to be an iron-activated transcription regulator that controls not only the expression of diphtheria toxin but also of iron uptake genes. This study aims to identify putative binding sites and operons controlled by DtxR to understand the role of DtxR in patho-physiology of Corynebacterium diphtheriae . Result Positional Shannon relative entropy method was used to build the DtxR-binding site recognition profile and the later was used to identify putative regulatory sites of DtxR within C. diphtheriae genome. In addition, DtxR-regulated operons were also identified taking into account the predicted DtxR regulatory sites and genome annotation. Few of the predicted motifs were experimentally validated by electrophoretic mobility shift assay. The analysis identifies motifs upstream to the novel iron-regulated genes that code for Formamidopyrimidine-DNA glycosylase (FpG), an enzyme involved in DNA-repair and starvation inducible DNA-binding protein (Dps) which is involved in iron storage and oxidative stress defense. In addition, we have found the DtxR motifs upstream to the genes that code for sortase which catalyzes anchoring of host-interacting proteins to the cell wall of pathogenic bacteria and the proteins of secretory system which could be involved in translocation of various iron-regulated virulence factors including diphtheria toxin. Conclusions We have used an in silico approach to identify the putative binding sites and genes controlled by DtxR in Corynebacterium diphtheriae . Our analysis shows that DtxR could provide a molecular link between Fe +2 -induced Fenton's reaction and protection of DNA from oxidative damage. DtxR-regulated Dps prevents lethal combination of Fe +2 and H 2 O 2 and also protects DNA by nonspecific DNA-binding. In addition DtxR could play an important role in host interaction and virulence by regulating the levels of sortase, a potential vaccine candidate and proteins of secretory system.

Background Iron is an important inorganic component of a cell. Iron is required as co-factor for various essential enzymes and proteins some of which are involved in electron transport (Cytochromes), redox reactions (oxidoreductases) and regulation of gene expression (fumarate-nitrate reduction regulatory protein, iron-binding protein) [ 1 ]. However a higher level of intracellular iron can catalyze formation of hydroxyl radicals and reactive oxygen species through Fenton's reaction which could be lethal to the cell [ 2 ]. Hence, a careful regulation of iron-requiring enzymes/proteins and iron uptake proteins/enzymes is required for the survival of bacteria. Inorganic iron is also known to influence virulence in many pathogenic bacteria such as Corynebacterium diphtheriae , Escherichia coli , and Bordetella bronchiseptica [ 3 - 5 ]. The diphtheria toxin repressor DtxR is known as an iron-activated global transcription regulator that represses the transcription of various iron-dependent genes in C. diphtheriae [ 6 , 7 ]. Eight DtxR-binding sites in upstream sequences of operons/genes named as tox, hmuO, irp1, irp2, irp3, irp4, irp5 and irp6 have been identified by DNA footprinting methods [ 6 ]. The product of tox gene is diphtheria toxin which catalyzes the NAD-dependent ADP ribosylation of eukaryotic aminoacyl-transferase-II, thereby causing inhibition of protein synthesis and subsequent death of the host. The hmuO gene, which encodes a haem oxygenase, oxidizes the haem to release free iron. The operons irp1 and irp6 encode the products with homology to ABC-type ferric-siderophore transport systems. The gene irp3 encodes a homologue of AraC-type transcriptional activators. The products of irp2, irp4 and irp5 do not show any homology to the other known proteins. In addition, C. diphtheriae with inactive DtxR has been shown to be sensitive to killing by exposure to high iron conditions or hydrogen peroxide than the wild type [ 8 ]. This work uses an in silico method to identify additional DtxR-binding sites and target genes to understand the role of DtxR in virulence and patho-physiology of C. diphtheriae . Results In silico identification of putative DtxR-binding sites Experimentally characterized DtxR-binding motifs were collected from the literature (Table 1 ). These binding sites were used to identify additional putative DtxR-binding sites along with associated operons in C. diphtheriae NCTC13129 genome (see materials and methods). Table 2 shows the predicted DtxR-binding sites with score 3.7438 or more. We could identify five (tox, irp4, irp5, irp6 and hmuO) of the eight known DtxR-binding sites, in sequenced C. diphtheriae NCTC13129 genome. We could not find irp1 and irp2 motifs as the corresponding genes ( irp1, irp2 ) are not present in the sequenced strain NCTC13129 [ 9 ]. The regulator binding sites of irp3 , irp4 and irp6 genes in the strain NCTC13129 shows one base change from the binding sites reported in strain C7 [ 6 ]. Binding site of irp3 gene (TTAGGTGAGACGCACCCAT) although exists in strain NCTC13129, but not there in the predicted sites, because it is located within the coding region of irp3 ORF. The predicted ORF of irp3 in the sequenced strain NCTC13129 has different start position and is larger than what was previously reported in strain C7 [ 9 , 10 ]. In addition, we have identified binding sites in upstream sequences of eight genes recently reported to be regulated by DtxR [ 7 ]. However, our prediction differs from the previous report for five (secY, deoR, chtA, frgA, sidA) of the seven sites which were identified by BLAST search (Table 2 ). Our prediction agreed with the previous report that the genes such as recA (DIP1450) and ywjA (DIP1735) are not under a direct DtxR regulation as we could not detect any motif upstream to these gene with scores above the cutoff value [ 7 ]. Experimental validation of predicted binding sites Since our approach to identify DtxR-regulated genes is purely computational in nature, we decided to test the validity of our predictions. A sample of predicted regulator binding motifs (Table 2 ) (upstream to ORFs: DIP2161, DIP0699, DIP0586, DIP2304, DIP2272) were experimentally verified by EMSA using IdeR, an orthologue of DtxR from M. tuberculosis . DtxR and IdeR are iron-dependent regulators. A pair wise sequence comparison of the two proteins shows a high (58%) overall sequence identity (similarity 72%) which increases further to 92% identity and 100% similarity in DNA recognition domain. In addition, the structural comparison of two regulators also shows a very similar 3D organization, suggesting that the IdeR regulator would be able to recognize the DtxR motif [ 11 ]. Synthetic double stranded oligonucleotides corresponding to DNA-binding sites were labeled with 32 P and mixed with purified IdeR in presence of manganese ions and was assayed for the formation of DNA-protein complex using EMSA. Manganese was used as the divalent metal in the binding reactions on account of its redox stability compared with ferrous ion. Electrophoretic mobility of all five double stranded oligonucleotides tested was retarded by IdeR (Figure 1 ). However a synthetic motif (TTTTCATGACGTCTTCTAA) used as a negative control did not show any complex formation. These results indicate that the predicted DtxR-binding sites can indeed bind to DtxR. Identification and annotation of DtxR-regulated genes C. diphtheriae genome In addition to the binding site prediction, we have also identified co-regulated genes (operons) downstream to the predicted DtxR-binding site (Table 3 ). Function of the proteins encoded by the putative genes in Table 2 and Table 3 was predicted by RPS-BLAST search against conserved domain database [ 12 ]. Discussion Our analysis identified putative DtxR motifs upstream to various operons/genes which could be involved in siderophore biosynthesis, ABC-type transport systems, iron storage, oxidative stress defense and iron-sulfur cluster biosynthesis. In addition, we have also identified the motifs upstream of operons that could be involved in anchoring of host-interacting proteins to the cell wall and secretion of various virulence factors. Important functions of some of these DtxR-regulated genes and their role in C. diphtheriae physiology are discussed here. Regulation of siderophore biosynthesis and ABC-type transport systems Predicted member of the DtxR regulon, the gene DIP0586, codes for the IucA/IucC family of enzymes that catalyze discrete step in the biosynthesis of the aerobactin [ 13 ]. In addition to known DtxR-regulated siderophore transport genes (irp1, irp6), DtxR could also regulate other ABC-type transport systems similar to Manganese/Zinc, peptide/Nickel and multidrug subfamilies of ABC transporters. The peptide/nickel transport system (DIP2162-DIP2165) has been suggested to be recently acquired by pathogenic C. diphtheriae [ 9 ]. Regulation of iron storage and oxidative stress defense We predict that DtxR could regulate divergently transcribed genes DIP2303 and DIP2304 whose products are similar to starvation inducible DNA-binding protein (Dps) and Formamidopyrimidine-DNA glycosylase (Fpg), respectively. Dps in Escherichia coli is induced in response to oxidative or nutritional stress and protects DNA from oxidative stress damage by nonspecific binding [ 14 ]. Dps also catalyzes oxidation of ferrous iron to ferric iron by hydrogen peroxide (2Fe 2+ + H 2 O 2 + 2H 2 O → 2Fe +3 OOH (core) + 4H + ) which in turn prevents hydroxyl radical formation by Fenton's reaction (Fe 2+ + H 2 O 2 → Fe +3 + HO - + HO . ) and thereby prevents subsequent DNA damage [ 15 ]. The enzyme, formamidopyrimidine-DNA glycosylase is a primary participant in the repair of 8-oxoguanine, an abundant oxidative DNA lesion [ 16 ]. The gene DIP1510 which codes for the site-specific recombinase XerD could also be regulated by DtxR. The xerD gene in E. coli belongs to the oxidative stress regulon [ 17 ]. Regulation of proteins involved in iron-sulfur cluster biosynthesis and iron-sulfur cluster containing proteins We predict that the operon DIP1288-DIP1296, which is similar to the suf operon of E. coli , could be regulated by DtxR. The suf operon in bacteria encodes the genes for Fe-S cluster assembly machinery [ 18 ]. In addition, genes encoding the iron-sulfur containing proteins such as succinate dehydrogenase (Sdh), cytochrome oxidase (CtaD) and Ribonucleotide reductase (NrdF1) in C. diphtheriae also show DtxR motif in their upstream sequences. Regulation of sortases We predict that DtxR could regulate the recently acquired pathogenic island DIP2271-DIP2272, encoding the sortase srtA and hypothetical protein, respectively [ 9 ]. Sortases are membrane-bound trans-peptidases that catalyze the anchoring of surface proteins to the cell wall peptidoglycan [ 9 ]. Such systems are often used by gram-positive pathogens to anchor host-interacting proteins to the bacterial surface [ 19 ]. Regulation of protein translation and translocation system DtxR could regulate two operons that contain genes DIP0699 ( secA ) and DIP0540 ( secY ) that code for the protein translocation system. The sec Y-containing operon, which is similar to the streptomycine operon spc from B. subtilis and other bacteria, involves the genes required for protein translation and translocation [ 20 ]. The operon contains additional sialidase gene (DIP0543) in comparison to non pathogenic Corynebacterium species. Activity of sialidase has been linked to virulence in several other microbial pathogens and may enhance fimbriae mediated adhesion in Corynebacterium diphtheriae by unmasking receptors on mammalian cells [ 9 ]. The Sec system can both translocate proteins across the cytoplasmic membrane and insert integral membrane proteins into it. The former proteins but not the latter possess N-terminal, cleavable, targeting signal sequences that are required to direct the proteins to the Sec system. Some of the DtxR-regulated genes including diphtheria toxin (Table 4 ) show predicted signal sequences by SignalP 3.0 [ 21 ] and hence they may play an important role in host interaction and virulence of Corynebacterium diphtheriae [ 9 ]. Conclusions The bioinformatics method used to predict the targets of DtxR in C. diphtheriae NCTC13129 genome is promising, as some of the predicted targets were experimentally verified. The approach identified novel DtxR-regulated genes, which could play an important role in physiology of C. diphtheriae NCTC13129. DtxR, generally known as a repressor of diphtheriae toxin and iron siderophore/transport genes, can also regulate other metal ion transport genes, iron storage, oxidative stress, DNA-repair, biosynthesis of iron-sulfur cluster, Fe-S-cluster containing proteins, and even protein sortase and translocation systems. Methods Source of genome sequence The complete genome sequence of C. diphtheriae was downloaded from NCBI ftp site [ 22 ], and the DtxR-binding sites identified by experimental methods were collected from literature [ 6 , 10 , 25 - 27 ]. Prediction of DtxR-binding sites DtxR-binding site recognition profile was calculated by positional Shannon relative entropy method [ 23 , 24 ]. The positional relative entropy Q i at position i in a binding site is defined as where b refers to each of the possible base (A, T, G, C), f b,i is observed frequency of each base at position i and q b is the frequency of base b in the genome sequence. The contribution of each base to the positional Shannon's relative entropy is calculated by multiplying positional frequency of each base with positional relative entropy. The binding site profile thus generated was used to scan upstream sequences of all the genes of the Corynebacterium diphtheriae genome. The score of each site is calculated as the sum of the respective positional Shannon relative entropy of each of the four possible bases. A maximally scoring site is selected from the upstream sequence of each gene. The lowest score among the input binding sites is considered as cut-off score. The sites scoring higher than the cut-off value are reported as potential binding sites conforming to the consensus sequence. Prediction of operons Co-directionally transcribed genes, downstream to the predicted binding site were selected as potential co-regulated genes (operons) according to one of the following criteria (a) Co-directionally transcribed orthologous gene pairs, conserved in at least 4 genomes; (b) genes belong to the same cluster of orthologous gene function category and the intergenic distance is less than 200 base pairs; (c) the first three letters in gene names are identical (gene names for putative genes were assigned from COG database); (d) intergenic distance is less than 90 base pairs [ 24 ]. Functional assignment of genes The function of predicted genes was inferred using the RPS-BLAST search against conserved domain database [ 12 ]. These genes were further classified according to their function. Expression and purification of IdeR The iron-dependent regulator IdeR from M. tuberculosis was expressed from a recombinant pRSET vector containing the IdeR gene fused to a six His affinity tag (P. Chakhiyar unpublished). The expressed protein was first purified using Ni-NTA Metal Chelate Affinity chromatography; later it was desalted and concentrated using Centricon Ultra filtration device. The concentration of the recombinant protein was estimated using Bradford method. Electrophoretic mobility shift assay Double-stranded oligonucleotides containing the predicted binding motif (19 bp long) were end labeled with T4 polynucleotide kinase and [γ 32 P]-ATP and were incubated with the recombinant purified IdeR protein in a binding reaction mixture. The binding reaction mixture (20-μl total volume) contain the DNA-binding buffer (20 mM Tris-HCl [pH 8.0], 2 mM DTT, 50 mM NaCl, 5 mM MgCl 2 , 50% glycerol, 5 μg of bovine serum albumin per ml), 10 μg of poly(dI-dC) per ml (for nonspecific binding) and 200 μM MnCl 2 . The reaction mixture was incubated at room temperature for 30 min. Approximately 2 μl of the tracking dye (50% sucrose, 0.6% bromophenol blue) was added to the reaction mixture at the end of incubation and was loaded onto 7% polyacrylamide gel containing 150 μM MnCl 2 in 1 × Tris-borate-EDTA buffer. The gel was electrophoresed at 200 V for 2 hours. Subsequently the gel was dried and exposed to Fuji Storage Phosphor Image Plates for 16 hours. The image plates were subsequently scanned in Fuji Storage Phosphor Imaging workstation. List of abbreviations DtxR – Diphtheria toxin repressor; IdeR – Iron-dependent regulator; Dps – DNA-binding protein from starved cells; RPS-BLAST – Reversed Position Specific – Basic Local Alignment Search Tool; EMSA – Electrophoretic Mobility Shift Assay Authors' contributions SY: carried out the computation, data analysis, and manuscript preparation. SR: Carried out the EMSA and drafted the manuscript. PC: provided the cloned IdeR construct, drafted the manuscript. SH: Manuscript preparation and coordination. AR: Design of the study and coordination. All authors read and approved the final manuscript.

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423147

Scientists and Bioethics Councils

In response to the Blackburn and Rowley essay on the President's Council on Bioethics, several thought-provoking opinions on ethical challenges in biomedical research are expressed by prominent stakeholders

I read with interest the article in a recent issue of PLoS Biology by Elizabeth Blackburn and Janet Rowley, two of the scientific members of President Bush's Council on Bioethics. Invited by the President to serve on this Council, they say that it was ‘a difficult invitation to accept’. Maybe, but that they did accept the invitation is to be applauded. As the Council's report ‘Monitoring Stem Cell Research’ states, ‘fairness in ethical evaluation and judgment depends on … fair and accurate description of the relevant facts of the case at hand’. In other (fewer) words, sound ethics requires a solid base in sound science. It is crucial that any bioethics committee or council made up of ten to twenty members should include at least two or three scientists broadly acquainted with the field in general, and with recent published findings. I was only sorry to read that Elizabeth Blackburn (who works in California but is a Fellow of the Royal Society, the United Kingdom Academy of Sciences) had her Council term terminated by White House directive on February 27, 2004. Of course, any bioethics committee or council (and I have served on several such, both in the UK and elsewhere in Europe) is likely also to include philosophers, lawyers, theologians, sociologists, and probably ‘lay’ people of appropriate interests. The scientists may well find that other members of the group have ‘strong opposing views’ on ethical issues, as well as on the costs and benefits of technologies arising from biomedical research. Elizabeth Blackburn and Janet Rowley were assured, both by Leon Kass, the chairman of the Council, and by President Bush himself, that their voices would be heard and integrated into the Council statements. It is therefore disappointing to learn that, in the ‘Beyond Therapy’ report (which I have not yet read), their requests for revision of certain aspects was declined. Were they not offered the option of a brief minority report? It would be expected in such circumstances that dissenting opinions would be recorded (as was done, for example, in the 1984 UK report by the Committee on Human Fertilisation and Embryology chaired by Mary Warnock (1984) , and in some of the Opinions offered by the European Group of Ethics to the European Commission). This would be particularly appropriate, and indeed essential, when recommendations are put forward. The ‘Monitoring Stem Cells Research’ report (which I have read) contains no recommendations, but includes a rather comprehensive survey of the various ethical positions relating to human embryonic stem cell research, a historical account of the development up to the present time of federal law and policy, and a chapter on recent (almost entirely United States) developments in human stem cell research and therapy. The scientists must have contributed substantially to this section of the report. Emphasis is put on the need for research on both adult and embryonic stem cells, since at present there is no way to assess which approach has the more promising therapeutic potential for which diseases. Some funding figures are given: on human embryonic stem cell research the US National Institutes of Health spent $10.7 million in 2002 and $17 million in 2003, with an estimated total spent by US companies of $70 million, while in the same two years the National Institutes of Health spent $170 million in 2002 and $181.5 million in 2003 on adult stem cell research. However, it is not obvious that there are any US scientists wanting to work on human embryonic stem cells within the constraints of US federal funding who are prevented from doing so by lack of money. To my mind, the major deficiency in the ‘Monitoring Stem Cells Research’ report is the almost complete lack of reference to what Elizabeth Blackburn and Janet Rowley correctly call ‘years of rigorous and careful research in animal models’. Some mention is made of experiments with human embryonic stem cells in immunologically handicapped mice, but in any such model both the stem cells and the mice are difficult to work with. Much of the science-based optimism that human embryonic stem cells may eventually prove of therapeutic value springs from the results of experiments with mouse embryonic stem cells in intact mice. Curiously, only a single such experiment is cited: an impressive but somewhat recondite piece of work from Jaenisch's laboratory ( Rideout et al. 2002 ), using cloned and genetically modified mouse embryonic stem cells to treat a form of mouse hepatitis. A wider consideration of work on animal models, together with some emphasis on the potential use of human embryonic stem cells for toxicity testing and drug design by pharmaceutical companies, is in part what Elizabeth Blackburn and Janet Rowley believe ‘would help the public and scientists better assess the content of the report’. If they requested inclusion of such material, it is unfortunate that their requests were declined.

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529456

Acetylation of insulin receptor substrate-1 is permissive for tyrosine phosphorylation

Background Insulin receptor substrate (IRS) proteins are key moderators of insulin action. Their specific regulation determines downstream protein-protein interactions and confers specificity on growth factor signalling. Regulatory mechanisms that have been identified include phosphorylation of IRS proteins on tyrosine and serine residues and ubiquitination of lysine residues. This study investigated other potential molecular mechanisms of IRS-1 regulation. Results Using the sos recruitment yeast two-hybrid system we found that IRS-1 and histone deacetylase 2 (HDAC2) interact in the cytoplasmic compartment of yeast cells. The interaction mapped to the C-terminus of IRS-1 and was confirmed through co-immunoprecipitation in vitro of recombinant IRS-1 and HDAC2. HDAC2 bound to IRS-1 in mammalian cells treated with phorbol ester or after prolonged treatment with insulin/IGF-1 and also in the livers of ob/ob mice but not PTP1B knockout mice. Thus, the association occurs under conditions of compromised insulin signalling. We found that IRS-1 is an acetylated protein, of which the acetylation is increased by treatment of cells with Trichostatin A (TSA), an inhibitor of HDAC activity. TSA-induced increases in acetylation of IRS-1 were concomitant with increases in tyrosine phosphorylation in response to insulin. These effects were confirmed using RNA interference against HDAC2, indicating that HDAC2 specifically prevents phosphorylation of IRS-1 by the insulin receptor. Conclusions Our results show that IRS-1 is an acetylated protein, a post-translational modification that has not been previously described. Acetylation of IRS-1 is permissive for tyrosine phosphorylation and facilitates insulin-stimulated signal transduction. Specific inhibition of HDAC2 may increase insulin sensitivity in otherwise insulin resistant conditions.

Background The insulin receptor substrate (IRS) proteins represent key elements in insulin and insulin-like growth factor (IGF) actions, transducing pleiotropic effects on cellular function and regulating processes such as metabolism, growth, cell differentiation and survival [ 1 ]. At least four members (IRS 1–4) have been identified that differ with regard to tissue distribution, subcellular localization, developmental expression, binding to the insulin receptor, and interaction with Src homology 2 (SH2) domains. They are all structurally characterised by N-terminal pleckstrin-homology (PH) and phosphotyrosine-binding (PTB) domains, which are required for coupling to the activated insulin/IGF receptors, and a C-terminal region with multiple sites for tyrosine phosphorylation by the receptors. IRS proteins thus act as molecular adapters in recruiting, inter alia , a number of SH2-containing proteins binding to specific phosphorylated tyrosine residues. This leads to activation of different intracellular cascades [ 2 ], one of which is the PI 3-kinase signalling cascade implicated in mediating the metabolic effects of insulin [ 3 ]. The best-substantiated post-translational modification of IRS proteins, in addition to tyrosine phosphorylation, is phosphorylation of specific serine residues. Phosphorylation on these residues is associated both with inhibition of insulin-induced tyrosine phosphorylation of IRS proteins and with facilitation of the effects of insulin [ 4 ]. Phosphorylation catalysed by protein kinase C (PKC) isozymes [ 5 , 6 ], c-Jun N-terminal kinase (JNK) [ 7 ], inhibitor κB kinase (IKK) isozymes [ 8 ], mitogen activated protein kinases (MAPK) [ 9 ] and the mammalian target of rapamycin (mTOR) [ 10 ] are all associated with reducing the ability of insulin to stimulate tyrosine phosphorylation of IRS proteins and therefore may be part of the physiological and pathophysiological negative regulation of insulin signalling through the IRS pathway. Specific mechanisms explaining why serine phosphorylation leads to reduced tyrosine phosphorylation have not been completely identified, but candidates for this are reduced interaction of IRS proteins with the insulin receptor [ 11 ] and increased degradation of IRS [ 12 , 13 ]. Furthermore, phosphorylation of different residues can lead to different effects. Thus, phosphorylation of serine 307 in rat IRS-1 (serine 312 in human IRS-1) is associated with reduced insulin signalling [ 7 ] whilst phosphorylation of serine 302 has recently been suggested to facilitate insulin signalling [ 14 ], although this has been contested [ 15 ]. In addition to phosphorylation of different amino acid residues, insulin signalling through IRS proteins has been shown to be regulated by at least two other mechanisms. Prolonged signal transduction via phosphoinositide 3-kinase (PI3K), which generates the lipid second messenger phosphatidylinositol 3,4,5-trisphosphate, has been shown to induce a state of insulin resistance in cells [ 16 ], in part through degradation of IRS-1 [ 17 ]. Thus, insulin signalling can be negatively regulated through modulation of IRS concentrations in cells, via degradation of the proteins in the proteasomal pathway [ 18 - 20 ]. The mechanism by which IRS proteins are degraded by the proteasome is not completely understood, but the N-terminal PH and PTB domains are required [ 21 ]. In addition, the sub-cellular localisation of IRS proteins may be important for appropriate insulin signalling. The sub-cellular localisation is not absolutely defined, with various lines of evidence pointing to potential places in the cell where the proteins can be found. In addition to the plasma membrane, IRS proteins have been associated with high-density pellets [ 22 ] implicating association with the cytoskeleton and recently also with the nucleus [ 23 , 24 ]. Thus, IRS proteins may be located to different parts of the cell where they carry out different functions. Multiple histone acetyltransferases (HATs) and histone deacetylases (HDACs) control the state of histone acetylation and hence play a regulatory role in modulating the structure and function of chromatin [ 25 ]. About 20 HATs have been detected to date, grouped in three different classes on the basis of structural properties. They all have one structural motif in common, the so-called A-motif responsible for acetyl CoA recognition [ 25 ]. Several HATs also have non-histone substrates but it is not yet possible to identify putative acetylation sites within a protein simply by sequence analysis. Generally, acetylation affects DNA-binding, protein-protein interactions, protein stability, and protein localization [ 26 ]. The acetyl-mediated signals are reversed by HDACs that counteract the effects of HATs by deacetylating lysine residues on histone tails. In higher eukaryotes, HDACs can be subdivided into three distinct groups known as classes I, II, III, according to similarities of their sequences to those of yeast founding members [ 27 ]. To date, four enzymes, HDAC1, 2, 3 and 8, are the known members of class I deacetylases [ 28 , 29 ]. HDAC1 and 2 are the best characterised, and are chief constituents of the multiprotein transcriptional-repression complex Sin3/HDAC and the nucleosome remodelling deacetylase NuRD/Mi2/NRD complex [ 30 ]. Complexes that contain class I HDACs bind to numerous transcription factors, either directly, or indirectly through the nuclear-hormone corepressors NCOR and SMRT (silencing mediator for retinoid and thyroid hormone receptors). Although all class I and II HDACs can deacetylate histone tails, other cellular proteins can be specifically targeted by different HDACs as well, such as α-tubulin and importin-α [ 31 ]. Recent developments have shown that the class I enzymes are regulated by phosphorylation, by casein kinase II amongst others, which increases activity [ 32 - 34 ]. The fact that class II enzymes are phosphorylated has been known for longer, a reaction which is associated with re-localization of the enzymes to the cytoplasm through interactions with 14-3-3 proteins [ 35 ]. We now demonstrate that HDAC2 interacts with IRS-1 under conditions when the ability of cells to respond to insulin is compromised. As such, this interaction may constitute a new component of the negative regulation of IRS protein function. We also show that IRS-1 is acetylated, and that augmenting the acetylation level by treating cells with Trichostatin A (TSA, a non-specific inhibitor of HDACs) or with short inhibitory RNA oligonucleotides against HDAC2 partially restores normal responsiveness to insulin. Results and discussion Interaction between IRS-1 and HDAC2 In an attempt to elucidate the regulation of IRS-1, we investigated inter-molecular interactions between IRS-1 and potential binding partners using yeast two-hybrid screening through a human foetal brain plasmid cDNA library. The system we used was the sos recruitment system as described in the Methods section, which displays protein-protein interactions in the cytoplasm of yeast cells. In these experiments, full length human IRS-1 was used as bait. Two independent transformants from a screen of 4 × 10 5 cDNAs encoded the N-terminal portion of a 488 amino acid protein identified as histone deacetylase 2 (HDAC2, Figure 1A ). To map the interaction site of HDAC2 on IRS-1 we used a GAL4-based yeast two-hybrid system, where interactions take place in the nucleus of the yeast cell. Cells were transformed with vectors encoding full length HDAC2 and different truncation mutants of IRS-1. The truncations of IRS-1 that were used were the PH domain (residues 1–155), the PH-PTB domains (residues 1–578) and the PH-PTB-pre-C-terminal domains (residues 1–895). Using growth of yeast cells on selective medium as a readout for interaction between HDAC2 and IRS-1 showed that the interaction requires the C-terminal portion of the IRS-1 protein (Figure 1B ). In order to confirm the interaction further in vitro , we used a coupled in vitro transcription/translation system in which full length IRS-1 and the HDAC2 N-terminal portion from the initial yeast two-hybrid screen were transcribed and translated in the presence of S35 methionine. IRS-1 was subsequently immunoprecipitated from the mixture and the proteins were resolved by SDS-PAGE. Gels were then subjected to autoradiography. Results showed that two radioactive protein bands were visible in the IRS-1 immunoprecipitates (Figure 1C ) and their molecular weights corresponded to those of full length IRS-1 (approx 160 kD) and truncated HDAC2 (approx 35 kD). When the IRS-1 antibody was boiled prior to immunoprecipitation (Figure 1C lane 2) or omitted (Figure 1C lane 3), no radioactive proteins were observed, indicating that the interaction between the two proteins is specific and not due to non-specific interactions with immunoglobulins or beads. Thus, IRS-1 and HDAC2 proteins are able to interact with each other in cell-free systems. To validate the interaction between IRS-1 and HDAC2 further and to ascertain whether IRS-1 and HDAC2 are associated in mammalian systems, we chose to work with MCF-7 cells (a human breast adenocarcinoma cell line), with a high endogenous expression of IRS-1 [ 36 ]. The cells were stimulated with IGF-1 or PMA (phorbol myristic acid; a PKC activator known to inhibit growth factor signalling [ 37 ]) for different time periods. Immunoprecipitations with IRS-1 antibody revealed that HDAC2 was co-precipitated to a larger extent in PMA-treated cells (Figure 2A ). In addition, the interaction between IRS-1 and HDAC2 was more visible in cells under prolonged stimulation with IGF-1. Similar results were obtained during prolonged stimulation with insulin. Considering that the ability of cells to respond to insulin and IGF-1 is reduced after prolonged ligand stimulation or PMA treatment, these data indicate that IRS-1 and HDAC2 associate when responsiveness is low and intracellular serine phosphorylation is increased. Indeed, analysis of serine phosphorylation of IRS-1 after treatment of cells with insulin or phorbol ester showed that PMA treatment caused a significant increase in phosphorylation of IRS1 on serine 312 (equivalent to serine 307 in rat IRS-1), which has been associated with reduced phosphorylation on tyrosine residues by the insulin receptor (Figure 2B lanes 1,2 and 4), whereas insulin stimulation had no effect. In these experiments, cells were stimulated with insulin for 10 minutes and responsiveness was subsequently analysed by measuring tyrosine phosphorylation of IRS-1 (see Figure 4 and discussion below). Responsiveness of the cells to insulin was compromised after PMA treatment, thus confirming the apparent association of IRS-1 with HDAC2 under conditions of reduced cellular sensitivity to insulin. To assess whether the interaction measured between IRS-1 and HDAC2 in vitro as described above occurs in vivo , we prepared lysates of liver tissues prepared from different mouse lines. The ob/ob mouse, which lacks functional leptin, was chosen as an insulin resistant animal model, and C57/bl6 was used as its genotype control. A PTP1B knockout mouse [ 38 ] was used as an insulin-sensitised animal model and balb/cJJ was used as its genotype control. IRS-1 was immunoprecipitated from liver lysates and western blotted for co-immunoprecipitation of HDAC2. The data showed that whilst a clear interaction between IRS-1 and HDAC2 was seen in livers from ob/ob mice (Figure 2C ), no interaction was evident in the C57/bl6 control. In contrast, no interaction was evident in livers of PTP1B knockout animals, whilst the balb/cJJ genotype control demonstrated a measurable interaction. Taken together with the in vitro data, these results showed that IRS-1 and HDAC2 are able to interact with each other in the cytoplasmic compartment of cells and that the interaction occurs under conditions of reduced insulin sensitivity, both in mammalian cells and in animals. The cytoplasmic location of the interaction is interesting in view of the fact that HDAC2 is considered to be largely a nuclear protein. In our work with cells and tissues, we have utilised lysis methods that are designed to retain nuclei intact and thereby minimise cross-contamination of compartments [ 39 , 40 ]. Whilst we have not formally excluded the possibility of contamination of cytoplasmic extracts with nuclear lysate, thereby leading to the presence of HDAC2, we feel that the body of evidence indicates that cytoplasmic HDAC2 is interacting with cytoplasmic IRS-1 in our experiments. The yeast two hybid "Sos recruitment system" is built on the rescue of cell growth through the interaction of proteins in the cytoplasm, which is how we detected this interaction. Interestingly, it has recently been shown that histone deacetylase 1, another class I histone deacetylase, which was considered to be exclusively nuclear, is present in a cytoplasmic protein complex by virtue of interaction with a cellular phosphatase complex [ 41 ]. Lysine acetylation of IRS-1 and insulin signal transduction The finding that HDAC2 binds to IRS-1 indicated that IRS-1 might be an acetylated protein in which acetylation might be a regulated post-translational modification of the protein. Indeed, the acetyl transferase Tip60 has been reported to bind to the PH domain of IRS-1 [ 42 ], suggesting the IRS-1 could be acetylated and deacetylated under different conditions. The lysine-acetylation status of IRS-1 was assessed by western blotting of IRS1 immunoprecipitated from MCF-7 cells after different treatments, using an antibody specific for acetylated lysine. Trichostatin A (TSA), which is a non-selective inhibitor of both class I and class II HDACs [ 43 ], was used as a positive control. Basal acetylation of the IRS1 protein was evident in unstimulated cells (Figure 3 ). Stimulation of cells with IGF-1 did not alter the level of acetylation although the basal signal was low and small effects cannot therefore be ruled out. PMA was also ineffective in altering the basal degree of acetylation of IRS1 whereas treatment of cells with TSA caused a very large increase in signal (Fig. 3 ). Our data therefore show that IRS-1 protein is acetylated on lysine residues, and the acetylation increases when HDAC activity is generally inhibited. This represents a heretofore-undescribed post-translational modification of IRS1 in addition to tyrosine/serine phosphorylation and ubiquitination previously described. TSA treatment did not induce phosphorylation of IRS1 on serine 312 (Fig 2B lane 3), nor did it modify the increase in serine 312 phosphorylation in the presence of PMA (lanes 1 and 2). The regulation and function of proteins such as sterol regulatory element binding protein 1c (SREBP1c) [ 44 ] and p53 [ 45 ] has been shown to be altered by changes in acetylation. The alterations in lysine acetylation in IRS-1 induced by TSA raised the possibility that insulin signal transduction may be altered in cells after treatment with this compound. To assess the effects of changes in IRS-1 acetylation on insulin signalling, MCF-7 cells were treated with PMA, TSA and insulin in different combinations and immunoprecipitated IRS-1 protein was immunoblotted for the presence of phosphotyrosine. PMA alone and in combination with TSA did not increase tyrosine phosphorylation of IRS1 above basal, as expected (Fig 4 lanes 4–6). Furthermore, the ability of insulin to induce tyrosine phosphorylation of IRS-1 was reduced by 60% in cells pre-treated with PMA (Fig 4 lane 3) consistent with a state of insulin unresponsiveness. However, pre-treatment with TSA in the presence of PMA reduced this unresponsiveness, increasing insulin-stimulated tyrosine phosphorylation to 70% of control (Fig 4 lane 2). Thus, increases in IRS1 acetylation via TSA-mediated HDAC inhibition were able to restore insulin signalling significantly. This restoration occurred without reducing PMA-induced serine 312 phosphorylation of IRS-1 (Fig 2B lane 2), indicating that acetylation of IRS1 overcomes the inhibitory effects of phosphorylation of serine 312. To assess the relative roles of altered intracellular protein acetylation and binding of HDAC2 to IRS-1 on insulin signalling, we treated cells with the general HAT inhibitor, desulfo coenzyme A (DesCoA, [ 46 ]) and examined HDAC2-IRS-1 interactions and insulin-stimulated tyrosine phosphorylation of IRS-1. The data showed that treatment with DesCoA induced HDAC2 to bind to IRS-1 to a similar extent to phorbol ester, which was coincident with reduced insulin-stimulated tyrosine phosphorylation of IRS-1 (Figure 5 ). In these experiments, interactions between HDAC2 and IRS-1 were apparently weaker in cells treated in the presence of TSA. This is not a consistent phenomenon, and occurs to varying degrees in our experiments (unpublished data). However, TSA has been reported to break other cellular HDAC-phosphatase complexes [ 41 ], so the effect here on HDAC2 and IRS-1 is not unprecedented. Treatment of cells with PMA and DesCoA did not lead to significantly greater effects, indicating that the two compounds share a common mechanism of reducing insulin signalling. Thus, inhibition of intracellular lysine acetylation accompanied by interactions between IRS-1 and HDAC2 leads to compromised insulin signalling, which can be overcome by inhibition of HDAC activity. Casein kinase II is an enzyme that has been shown to regulate the ability of HDAC2 to form oligomeric complexes both positively and negatively [ 32 ]. Interestingly, treatment with an inhibitor of casein kinase II (5,6-dichloro-1-β -D-ribofuranosylbenzimidazole) did not induce binding between IRS-1 and HDAC2 (Kaiser & James, unpublished) and had no effect on insulin signalling. To ascertain if more distal insulin signalling was also enhanced, we examined the activation of protein kinase B (PKB) by western blotting, using an antibody against PKB phosphorylated on serine 474; this phosphorylation is induced in a PI3K-sensitive manner resulting in enhanced protein kinase activity. The data showed that PMA treatment reduced the activation of PKB by 50% (Figure 6 lane 3), whereas with pre-treatment with TSA, the response was 80% of control (Figure 6 lane 5). Thus, TSA-mediated increases in lysine acetylation of IRS-1 led to virtual restoration of PKB activation by insulin in PMA-treated cells. Interestingly, the PKB response in the presence of TSA and PMA (but no insulin, Figure 6 lane 4) showed significantly higher basal activation of PKB than in unstimulated cells. We speculate that this is due to the recently described ability of HDAC inhibitors, including TSA, to activate PKB through an unknown mechanism [ 47 ]. Thus, the increased response of cells to insulin in the presence of TSA (Figure 6 lane 5) may represent a summation of the effects of TSA alone and insulin. One candidate mechanism for the reported activation of PKB by HDAC inhibition is via increased acetylation of IRS-1 leading to enhanced basal PI3K activity and enhanced PKB activity. We could not, however, detect increases in basal tyrosine phosphorylation of IRS-1 in the presence of TSA without insulin (Figure 4 lane 4), suggesting that, if this is indeed part of the mechanism of activation of PKB by HDAC inhibition, it is beyond the limits of detection. Such a possibility is not without precedent. We have previously reported the ability of a non-specific protein tyrosine phosphatase inhibitor to increase PI3K-dependent glucose transport in muscle cells in culture without being able to detect changes in basal tyrosine phosphorylation of the insulin receptor or IRS-1 [ 48 ]. Thus, it remains possible that HDAC inhibition by TSA leads to enhanced PKB phosphorylation through small changes in IRS-1 phosphorylation. A major functional response downstream of the PI3K arm of insulin signal transduction is increased glucose transport mediated by the GLUT4 transporter. We sought to examine the effects of TSA on glucose transport in rat L6 myotubes to see if the enhanced insulin signalling mediated by TSA treatment of cells translated into increased glucose uptake. We found that treatment of L6 myotubes with PMA resulted in increased basal glucose transport and had no effect on insulin-stimulated glucose transport (Kaiser & James, unpublished). Such effects are in line with data presented for rat epitrochlearis muscle [ 49 ] and indicated that L6 cells do not exhibit a clear insulin-resistance phenotype after PMA treatment, at the level of glucose transport. We also have similar observations in the human neuroblastoma cell line SHSY-5Y, which demonstrates insulin-stimulated glucose uptake [ 50 ]. Phorbol ester treatment of these cells increased basal glucose transport but in contrast to data in L6 cells, also inhibited insulin-stimulated glucose transport (Kaiser and James, unpublished). We have therefore not been able to distinguish an effect of TSA on GLUT4-mediated glucose transport owing to the large PMA-stimulated increases in insulin-independent glucose transport (presumably mediated by GLUT1), and are at present analysing other cells for their response to phorbol ester treatment. Interestingly, Takigawa-Imamura et al. [ 51 ] recently showed that several HDAC inhibitors increase glucose transport in muscle cells in culture. Although the treatment regimens with these inhibitors in these experiments were chronic, the data show that inhibition of HDAC activity enhances glucose transport. Molecular mechanisms behind this effect could be several, including enhanced insulin signalling through increases in intracellular protein acetylation. TSA is an efficacious inhibitor of all class I and class II HDAC enzymes, with a potency in the low nanomolar range. To ascertain whether specific inhibition of HDAC2 activity is able to enhance insulin signalling in otherwise non-permissive conditions (PMA treatment), we used RNA interference to reduce HDAC2 activity specifically. MCF-7 cells were transiently transfected with a 21 base RNA duplex oligonucleotide against HDAC2 which reduced the HDAC2 protein content of the cells by approximately 70% (Figure 7 ). This was associated with a greater than three-fold increase in lysine acetylation of IRS-1. Furthermore, insulin-stimulated tyrosine phosphorylation of IRS-1 was increased 1.5-fold in RNAi-treated cells (Figure 7 ). A second RNAi oligonucleotide against HDAC2 was found to be much less efficient in silencing, exerting no effect on HDAC2 expression at 25 nM (corresponding to 80 pmol, see Methods section). Control experiments with this oligonucleotide at concentrations when HDAC2 expression was unaffected, showed that insulin-stimulated tyrosine phosphorylation of IRS-1 was not affected (data not shown), indicating that specific reductions in HDAC2 after RNAi treatment were the main cause of enhanced insulin signalling and IRS-1 acetylation. These data showed that specific reductions in HDAC2 activity in MCF-7 cells induced similar changes in IRS-1 regulation as treatment with TSA and that HDAC2 is an integral component of phorbol ester-induced insulin unresponsiveness in cells. The increase in lysine acetylation and tyrosine phosphorylation was arguably not as marked in RNAi-treated cells as in cells treated with TSA. An interpretation of these data could be that other members of the HDAC family are also involved in the processes leading to insulin resistance. We have found that HDAC1 does co-immunoprecipitate with IRS-1 from MCF-7 cells but its regulation is different, with no significant changes in the association by prolonged insulin stimulation or by PMA treatment of the cells (Kaiser & James, unpublished) suggesting that whatever the involvement of other HDACs, HDAC2 is central to the observed changes in insulin signalling. The data we present here imply that treatment of insulin-resistant or diabetic animals with inhibitors of HDAC2 should increase insulin responsiveness. We attempted to assess the effects of TSA on insulin sensitivity in ob / ob mice. The animals were divided into two groups: vehicle (DMSO) and TSA (0.1 mg/kg) and treated subcutaneously for three days. At the same time as drug injection, all food was withdrawn from the animals and 4 hours later, blood was collected from the tail vein for blood glucose and plasma insulin analysis. On the third day, an insulin tolerance test (ITT) was performed 4 hours after administration of the drug. After 24 hours, fasting blood glucose tended to be lower in treated animals than vehicle controls, but after three days no difference was evident. Furthermore, we were unable to detect a change in insulin sensitivity after drug treatment during the ITT on day 3 (Kaiser, Warpman & James, unpublished). In addition, no changes in lysine acetylation of IRS-1 were observed, indicating that the lack of effect on insulin sensitivity could be due to the inability of TSA to work through the molecular mechanism of increasing IRS-1 acetylation. TSA is rapidly metabolised by liver cells in culture in two stages, initially by reduction to the imide followed by demethylation, leading to inactive metabolites [ 52 ]. It is therefore probable that the compound was rapidly metabolised by hepatic phase I metabolic processes in these experiments so that it was unable to exert pharmacodynamic effects on the animals. The poor bioavailability of TSA [ 53 ] has led to its discontinuation as a clinical candidate for the treatment of human disease and the possibility of testing the insulin sensitizing effects of HDAC inhibition must await the availability of a drug with better pharmacokinetics. Furthermore, HDACs are not redundant, but have specific expression patterns and functions. Therefore, it is of great importance to develop specific HDAC-inhibitors to be able to assess their respective contributions to increases in insulin sensitivity in vivo. The mechanism whereby lysine acetylation of IRS-1 leads to increased tyrosine phosphorylation by the insulin receptor is not known. Time course experiments, in which cells were stimulated with insulin for one to ten minutes, showed that the kinetics of IRS-1 phosphorylation were the same, irrespective of pre-treatment of cells with TSA (Kaiser & James, unpublished). However, the IRS-1 tyrosine phosphorylation signal was greater at all times in cells treated with TSA, suggesting that lysine acetylation of IRS-1 simply increases the amount of phosphorylated IRS-1. It has recently been shown that lysine acetylation protects the transcription factor SREBP1C from ubiquitination and degradation via the proteasomal pathway by competing for the same lysine residues. IRS-1 has also been shown to be degraded via ubiquitination and subsequent proteasomal degradation [ 21 ]. We investigated the influence of lysine acetylation of IRS-1 on ubiquitination by blotting immunoprecipitates of IRS-1 from cells for the presence of ubiquitin (Fig 8 ). The data showed that in the absence of PMA, IRS-1 was only slightly ubiquitinated, whereas in cells treated with PMA, this was markedly increased. The molecular mass of both bands of the IRS-1 doublet increased after PMA treatment, spanning 132 kD to 145 kD, presumably due to the addition of ubiquitin molecules. TSA did not influence PMA-induced ubiquitination of IRS-1. These data therefore indicate that increases in IRS-1 phosphorylation after its lysine acetylation are not the result of increasing the concentration of the protein by preventing its degradation. Interestingly, a protein called PH domain interacting protein (PHIP) was recently described that selectively binds in vitro and constitutively associates in cells to the PH-domain of IRS-1 [ 54 ]. PHIP is not itself a substrate of the insulin receptor but rather a ligand of the IRS-1 PH-domain that serves to link IRS-1 to the insulin receptor and enhance its phosphorylation. PHIP contains two bromodomains located in tandem in the centre of the molecule [ 55 ]. Considering the fact that IRS-1 is acetylated and that bromodomains can interact specifically with acetylated lysine [ 56 ], the mode of interaction between PHIP and IRS-1 could be through the bromodomains, providing a molecular mechanism that explains why the increased acetylation of IRS-1, after TSA treatment, is accompanied by a higher level of tyrosine phosphorylation of IRS-1 despite the insulin resistant state. We have sought to test this hypothesis by blotting immunoprecipitates of IRS-1 for PHIP but have been unable to distinguish a specific band corresponding to PHIP using the antibodies that are available commercially. Conclusions In this study, we have identified a previously undescribed interaction between IRS-1 and HDAC2 in the cytosolic compartment of cells. The interaction is observed both in vitro and in vivo during conditions of compromised insulin signalling, as seen by reductions in insulin-stimulated IRS-1 tyrosine phosphorylation and PKB activation and increased phosphorylation of the negative regulatory phosphorylation site, serine 312. Our data indicate that it is the interaction with HDAC2 itself rather than its catalytic activity that is integral to the insulin unresponsiveness that ensues. Furthermore, our data show that IRS-1 is a lysine-acetylated protein, a previously unidentified post-translational modification of IRS-1, and that increases in the level lysine acetylation of IRS-1 result in improved insulin signal transduction. Increases in IRS-1 acetylation can be achieved pharmacologically (with TSA) or by ablation of HDAC2 specifically by use of RNAi. Out data therefore indicate that a new dimension to the physiology and pathophysiology of insulin sensitivity and insulin resistance involves changes in the degree of lysine acetylation of IRS-1 and that specific small molecule inhibitors of HDAC2 activity could represent novel therapeutics for the treatment of diseases that centre around insulin resistance, such as type 2 diabetes and obesity. Methods Yeast two hybrid screening The CytoTrap™ (Stratagene) yeast two-hybrid system was used to discover protein-protein interactions in the cytoplasm of yeast cells. Interactions were detected by recruitment to the cell membrane of the human Sos (hSos) gene product, which activates the Ras pathway. The yeast strain used (cdc25H) harbours a temperature sensitive mutation in the cdc25 gene, the yeast homologue for hSos, which means that the cells can grow at 25°C but not at 37°C unless rescued with a protein-protein interaction. A human foetal brain plasmid cDNA library (Stratagene), harboured in the pMyr vector (with a myristylation signal to direct and anchor proteins in the membrane), was used as "prey" and the sub-cloned full length IRS-1 gene in the pSos vector was used as "bait". When prey and bait proteins interact the hSos is brought into close proximity to Ras and subsequently the yeast survive and are selected by growth at 37°C. The IRS-1/HDAC2 interaction rescued growth at 37°C in this way. The corresponding pMyr yeast plasmid was isolated and co-transformed with the pSos bait construct to perform false positive tests. HDAC2 was full length cloned using RACE cDNA obtained from human heart tissue together with gene specific primers and the Advantage 2 polymerase mix (Clontech). With the purpose of mapping the interaction site of HDAC2 on IRS-1 we used the Matchmaker 3 yeast two-hybrid system (Clontech). This is a GAL4-based two-hybrid system that provides a transcriptional assay for detecting specific protein-protein interactions in yeast. Two nutritional markers and one enzymatic reporter gene were used to detect interactions. Different domains of IRS-1 (PH domain, residues 1–155, the PH-PTB domains, residues 1–578 and the PH-PTB-pre-C-terminal domains, residues 1–895, obtained by PCR) were sub-cloned into a "bait" vector (pGBKT7), fused to the DNA-binding domain of GAL4. Full length HDAC2 was sub-cloned into the "prey" vector (pGADT7), fused to the activation domain of GAL4. Cell growth on medium lacking the two nutritional markers was used as a readout of the interaction between the predator and prey. In vitro transcription-translation In order to confirm the IRS-1/HDAC2 interaction in vitro , we used a coupled transcription/translation system (Promega) comprising a rabbit reticulocyte lysate solution with RNA polymerase, nucleotides, salts, a ribonucleoside inhibitor, and [ 35 S]-methionine (Amersham Biosciences) to allow detection of translated proteins. Since the prey vector pMyr already contains a T7 promoter, this was used directly in the system. However, the bait vector pSos lacks a T7 promoter and thus the IRS-1 gene was subcloned into a T7-containing vector (pGBKT7; Clontech) to permit transcription. The individually transcribed and translated proteins were mixed and co-immunoprecipitated with anti-IRS-1 antibodies (Upstate Biotechnologies) and subsequently analysed by polyacrylamide gel electrophoresis (4–12%). The gel was dried analysed by phosphorimagery. Cell culture The human breast adenocarcinoma cell line MCF-7 was cultured in a mixed medium of Dulbecco's Modified Eagle Medium with nutrient mixture F12 (Invitrogen) lacking phenol red with 10% Foetal Bovine Serum (Gibco). At near confluency, cells were starved of serum for 16 h and subsequently treated with IGF-1, insulin, PMA (phorbol myristic acid; Sigma) or TSA (Trichostatin A; Sigma), or combinations thereof, for different lengths of time as indicated in individual figures. Cells were harvested in hypotonic cell lysis buffer comprising 20 mM Hepes, pH 7.6, 20% glycerol, 10 mM NaCl, 1.5 mM MgCl 2 , 0.2 mM EDTA, 0.1% NP40, 25 mM NaF, 25 mM β-glycerophosphate, 1 mM DTT, 1 mM Na-orthovanadate and protease inhibitors. Western blot assays Cell lysates were cleared by centrifugation at 16000 g for 10 min at 4°C, and protein content was determined using the Bradford method (BioRad). For immunoprecipitations, matched amounts of protein were incubated with primary antibody (amount used as recommended by the manufacturer or empirically determined) for 2 h at 4°C followed by addition of 20μl of protein A/G agarose suspension (Santa Cruz) for 1 h at 4°C with rotating tube. After washing (3 times with high salt (500 mM NaCl) and twice with isotonic buffer), beads were heated with SDS-PAGE sample buffer for 10 minutes at 70°C and proteins were resolved by 4–12% gradient SDS-PAGE. After blotting, membranes were blocked in 5% non-fat dried milk in Tris-buffered saline containing 0.1% Tween 20 for 1 h prior to addition of the primary antibody. After incubation with secondary horseradish peroxidase-conjugated antibody, protein bands were visualised using enhanced chemiluminescence (ECL-plus detection kit, Amersham Biosciences). Antibodies used were anti-IRS-1 (Upstate, cat. no 06–248); anti-HDAC2 (Santa Cruz, cat. no. sc-9959 and sc-6296); anti-phosphotyrosine (Santa Cruz, cat. no. sc-7020); anti-acetyl lysine (Cell Signalling, cat. no. 9681); anti-ubiquitin (Santa Cruz, cat. no. sc-6085 and sc-9133); anti-phospho-serine 307 IRS-1 (Upstate, cat. no. 07–247), HRP-conjugated anti-mouse IgG (Amersham Biosciences, cat. no. NA931V); HRP-conjugated anti-goat IgG (Dako cat. no. PO449) and HRP-conjugated anti-rabbit IgG (Upstate, cat. no. 12–348). RNA interference Double stranded RNA duplexes corresponding to amino acids from the C-terminal part of human HDAC2 (5'CAGCUCAGCAACCCCUGAAtt3') were annealed and transfected into human MCF-7 cells (Lipofectamine 2000 from Invitrogen was used as transfection agent): The effect of RNAi on HDAC2 expression and on insulin dependent IRS-1 tyrosine phosphorylation was measured after 48 hours. A second oligonucleotide (5'GGAGCAAAGAAAGCUAGAAtt3') was found to be non-silencing at a dose of 80 pmol, in contrast to the silencing oligonucleotide above, and was used in control experiments showing that no effect on IRS-1 phosphorylation or acetylation was observed (data not shown). Animal experiments Male 8-week old ob / ob mice were obtained from Bomhultsgard, Denmark and housed according to standard procedures. C57/bl6 genotype control mice were obtained from Scanbur BK AB (Sollentuna, Sweden). PTP1B knockout animals on a balb/cJJ background were purchased from McGill University, Montreal, Canada. Balb/cJJ genotype controls were obtained from Scanbur BK AB. In our hands, balb/cJJ mice are generally a healthy mouse strain that breeds well. In side-by-side experiments, the mice are more insulin sensitive than C57/bl6 mice whilst being less insulin sensitive than the PTP1B knockout animals on the same genetic background. The animals are somewhat smaller than C57/bl6 mice and have a relatively high body fat content. For compound treatment experiments and insulin tolerance tests, animals were divided into two groups: vehicle (1% DMSO sub-cutaneous injection (s.c.), n = 15 and TSA 0.1 mg/kg s.c., n = 15) and subsequently treated s.c. at 09.00 h for three days. At the same time as injection, all food was withdrawn from the animals. Four hours later, blood was collected from the tail vein for blood glucose and plasma insulin analysis. On the third day, an insulin tolerance test (ITT) was performed 4 h after administration of the drug. ITT: insulin (actrapid 0.5 U/kg) was administered i.p. Following insulin administration, blood samples were collected after 15, 30, 60, 120 and 180 min from the tail vein for glucose analysis. Animals were then sacrificed and livers were dissected and immediately frozen in liquid nitrogen and stored at -70°C. All experiments were performed in accordance with permission from the local Swedish ethics committee and the company Pharmacology ethics review team. For western blotting of liver proteins, frozen liver was powdered finely under liquid nitrogen using a pestle and mortar pre-cooled to -70°C. Powdered liver (1 g) was homogenized at 4°C using a Polytron in 3 ml of homogenisation buffer (4 mM EDTA, 50 mM NaF pH 8.0, 1 mM Na-orthovanadate, 1μM okadaic acid, 0.1% (v/v) 2-mercaptoethanol, with protease inhibitor cocktail). The homogenates were centrifuged at 13000 × g for 10 minutes at 4°C and the supernatant removed and used immediately for Western blot analysis or snap frozen in aliquots at -70°C until needed. List of abbreviations DesCoA: desulfo coenzyme A HAT: histone acetyl transferase HDAC: histone deacetylase IGF: insulin-like growth factor IRS: insulin receptor substrate PH: pleckstrin homology PKB: protein kinase B PI3K: phosphoinositide 3-kinase PMA: Phorbol myristic acid PTB: phosphotyrosine binding domain TSA: Trichostatin A Authors' contributions CK carried out all of the experimental procedures reported in this study and drafted the manuscript. SRJ conceived of the study, participated in the design of all the experiments and coordinated the study.

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Men's values-based factors on prostate cancer risk genetic testing: A telephone survey

Background While a definitive genetic test for Hereditary Prostate Cancer (HPC) is not yet available, future HPC risk testing may become available. Past survey data have shown high interest in HPC testing, but without an in-depth analysis of its underlying rationale to those considering it. Methods Telephone computer-assisted interviews of 400 men were conducted in a large metropolitan East-coast city, with subsequent development of psychometric scales and their correlation with intention to receive testing. Results Approximately 82% of men interviewed expressed that they "probably" or "definitely" would get genetic testing for prostate cancer risk if offered now. Factor analysis revealed four distinct, meaningful factors for intention to receive genetic testing for prostate cancer risk. These factors reflected attitudes toward testing and were labeled "motivation to get testing," "consequences and actions after knowing the test result," "psychological distress," and "beliefs of favorable outcomes if tested" (α = 0.89, 0.73, 0.73, and 0.60, respectively). These factors accounted for 70% of the total variability. The domains of motivation (directly), consequences (inversely), distress (inversely), and positive expectations (directly) all correlated with intention to receive genetic testing (p < 0.001). Conclusions Men have strong attitudes favoring genetic testing for prostate cancer risk. The factors most associated with testing intention include those noted in past cancer genetics studies, and also highlights the relevance in considering one's motivation and perception of positive outcomes in genetic decision-making.

Background There are several factors to consider in undergoing genetic testing for cancer risk: potential benefits, possible risks, psychological distress, and the uncertainty in subsequent decision-making about prophylactic interventions [ 1 - 9 ]. While the health professional's assessment of the potential benefits and harms frames the disclosure of informed consent, the patients' values and expectations are intrinsic on the decision-making process. Current understanding of these values and expectations has been primarily derived from patients considering genetic testing for breast and colorectal cancers [ 10 ]. It remains unclear how these same factors may influence men's decision making in testing for hereditary prostate cancer risk [ 2 ]. The question addressed in this article is what values and expectations influence the intention of men to undergo genetic testing for prostate cancer risk. A definitive genetic test for prostate cancer is not clinically available yet. Current genetic tests are only conducted in research studies. Several potential genetic loci have been identified as linked to hereditary prostate cancer, including HPC1 [ 11 ], MXI1, KAI1, [ 12 ] and 1q42.2-q43 on chromosome 1q. In the future, a test (or set of tests) for hereditary prostate cancer risk may become available. Such testing may become an important tool in preventing prostate cancer, or be useful once prostate cancer is diagnosed (e.g., for treatment decisions). Further, it is prudent for physicians to be prepared for patient requests for genetic testing, even when there are no strong clinical indications. Learning why men would accept or refuse prostate cancer genetic risk information is therefore relevant to the future of testing, and its informed consent. Informed consent for genetic testing for cancer risk is particularly controversial in cancers where knowledge of a positive test result does not provide opportunities for interventions for favorable outcomes, and a negative result does not provide reassurance [ 13 ]. High stated intention for genetic testing for prostate cancer risk (over 80%) has been reported in the past [ 14 ]. Identification of a man at genetic risk for prostate cancer presents an ambiguous dilemma: Should a positive result be followed by prophylactic surgery, medication, increased surveillance (via PSA testing or rectal examination), or standard screening recommendations? The knowledge gained through genetic screening may not necessarily lead to clear cut recommendations about what the patient should do next. This study examines men's beliefs and values toward interest in prostate cancer genetic testing. A survey instrument was developed for men between 40 and 70 years of age, exploring their beliefs, attitudes, and concerns in considering a hypothetical blood test. Exploratory factor analysis was applied to identify the underlying factor dimensions. The relative importance of these factors was then compared to testing intention. Methods Study population The Institutional Review Board (I.R.B.) of the University of Pennsylvania and US Department of Defense Human Subjects Review approved the study. Subjects for this study included healthy outpatient males, identified with the assistance of the institution's Office of Health Services Research for demographic characteristics of age, ethnicity, and absence of past or current history of prostate cancer. Subjects were sent a letter-invitation to participate with an opt-out telephone number to call. Inclusion criteria were that subjects must be English-speaking men in a large metropolitan East-coast city, between the ages of 40 and 70, with no current evident mental incapacity and no present or past personal history of prostate cancer. All others were excluded. Prostate cancer genetic screening survey questionnaire Survey development A 53-item attitude survey instrument was developed. The items were selected by the collaborators from a pool of more than 100 preliminary items from the data resulting from 12 focus groups of 90 lay men regarding their attitude, beliefs, and concerns about prostate cancer genetic screening [ 15 ]. The statements were answered on a 1–5 Likert-type scale ("Strongly Disagree" = 1, "Disagree" = 2, "Neutral" = 3, "Agree" = 4, and "Strongly Agree" = 5). Twenty-one items were reverse phrased to counter balance directionality in the response scale. Items 1, 51, 52, and 53 were intent items: "I would want the genetic test for prostate cancer risk when it becomes available," "I would want this test if it could tell me that prostate cancer is more likely to happen earlier in my life," "I would want this test if it could tell me that prostate cancer is more likely to be more life threatening because I have the prostate cancer risk gene," and "I would want this test even if it does not tell me new information about how early or aggressive prostate cancer may be in my future," respectively. Telephone interview The survey was conducted using Computer-Assisted Telephone Interviewing software (MacCATI, Senecio Software). The survey instrument was pilot tested in face-to-face interviews of randomly selected men, age 40–70, in a primary care office prior to data collection, to verify understandability of the survey's content and format. For the telephone survey, a recruitment packet that included an informed consent letter was first mailed to the prospective participants. Instructions explained the goals of the study and gave them an option to opt-out with a toll-free phone call prior to their interview. An oral informed consent was completed prior to the telephone interview. Missing data The number of missing observations ranged from 0 to 13, with an average of 2.38. Missing data were imputed based on an imputation model that predicts the missing values of factors as predicted by all of the other responses, including the outcome (desire to be tested). The algorithm uses Markov Chain Monte Carlo methods to select at random a value from the distribution of the possible values predicted by the missing value model. This method differs in several respects from other methods of filling in for missing data, in that with each imputation a different value will be imputed for the missing value, thus ensuring an added dimension of variability in the resulting analyses. The imputation was repeated multiple times. Each imputation generated an imputed data set. The same factor analysis was applied and no statistically reliable differences were found across the imputed data sets. Thus, only the results from the first imputed data are reported here. The imputation was carried out by SAS PROC MI. Factor analysis and reliability statistics A maximum-likelihood factor analysis with oblique rotation was applied to the 49 non-intent questions to classify men's non-intent beliefs and attitudes according to their underlying dimensions. The four questions that directly probed men's expressed intent were considered a priori as a separate factor. The factor analysis involved methodological criteria for data reduction, which included the rules summarized in Tabachnick [ 16 ]. Items with factor pattern loading lower than .40 were dropped (less than 16% overlapping variance between the item and the associated factor). The most salient dimensions were then retained, accounting for at least 70% of the total variability. The internal consistency reliability was assessed by Cronbach's alpha coefficient [ 17 ]. Items that showed the highest factor pattern loadings for a particular factor were considered items that measure the attitude associated with that dimension [ 18 ]. Factor scores, with estimated scores on each of the individual factors had they been measured directly, were also derived by summing the raw scores of the items [ 19 ]. Results Demographics Interviews were completed with 400 respondents with a cooperation rate of 47% (1675 were contacted, 431 refused to participate either by phone prior to the interview, or at the time of the interview, and 844 were excluded due to no answer, disconnected telephones, and death). Table 1 summarizes the respondents' characteristics. Of note, another study by the authors revealed that no demographic factor had a moderating impact on intention, except one – in which higher levels of education correlated with diminished testing intention [ 20 ]. IRB constraints precluded non-respondent data collection for comparison. Table 1 Respondent characteristics Characteristics N (N = 400) % Ethnicity White 288 72 Black 87 22 Hispanic 5 1 Asian 8 2 Other 6 2 No response 6 2 Age 40–49 133 33 50–59 143 36 60–69 124 31 Education < High school 86 22 High school graduate/some college 149 37 College graduate 141 35 Post-graduate degree 23 6 No response 1 0 Annual household income $15,000 or less 17 4 $15,001 – $45,000 74 19 $45,000 – 75,000 84 22 $75,000 – $105,000 90 23 More than $105,000 107 28 No response 28 7 Marital status Married 319 80 Steady relationship but not married 23 6 Separated or divorced 26 7 Single 25 6 Widowed 7 2 Testing intention About 82% of men interviewed expressed that they "probably" or "definitely" would take the test if one were offered now. This high interest increased to 88% if a positive test result indicates elevated risk in the early onset of cancer; 93% if it indicates graver prognosis of cancer; and the stated interest dropped to a still appreciable 68% if no new information on timing or severity of prostate cancer is to be learned from the prospective test. Subscales Exploratory factor analysis identified four underlying factors that accounted for 76% of the total variability among the 49 items probing men's beliefs and attitudes. The four factors were 1) Motivation , i.e., those values relating how strongly the respondent wanted the test, and how strongly the opinions of professionals, spouse, family, relatives, and friends could have influenced the respondent's own strength of intent; 2) Consequences , which measured beliefs with respect to follow-up decision-making and management; 3) Distress , which assessed fear of losing health and life insurance, anxiety, and worsening of quality of life if tested positive; and 4) Positive Expectations , which described beliefs in how the test results will confer useful information in family risk and favorable outcomes. The four intent items were added separately as the fifth subscale 5) Intention directly probing the respondent's stated intent. Table 2 summarizes the subscales, their respective internal consistency, and the factor loadings of their constituent items. Table 2 Subscales, internal consistency, and factor item loadings Factors / statements (internal consistency statistics) Factor pattern loading Motivation Subscale 1: Motivation (alpha = 0.89, 37% variability) Even if other relatives did not want me to, I would get genetic testing. 0.80 Even if my children did not want me to, I would get genetic testing. 0.77 I would get genetic testing if my friends wanted me to. 0.73 Even if my friends did not want me to, I would get genetic testing. 0.72 I would get testing if other relatives wanted me to. 0.68 Even if my wife or partner did not want me to, I would get genetic testing. 0.68 Even if a genetic testing specialist recommended against it, I would get genetic testing. 0.60 I would get testing if my children wanted me to. 0.59 Even if my doctor recommended against it, I would get genetic testing. 0.57 I would get testing if a genetic testing specialist recommended it. 0.46 I would get testing if my wife or partner wanted me to. 0.43 Consequences Subscale 2: Consequences and actions after knowing the test result (alpha = 0.73, 23% variability) I find that my concerns about getting prostate cancer interfere with my every day life. [R] 0.56 I don't want testing unless there is a prostate cancer cure. [R] 0.54 If I know I have the prostate cancer risk gene, it will make me feel guilty. [R] 0.53 I'll have to make a quick treatment decision if I know I have the prostate cancer risk gene. [R] 0.52 If I know I have the prostate cancer risk gene, I will make me want to end my life. [R] 0.51 If I don't have the prostate cancer risk gene, I will be able to put my mind at rest about prostate cancer. [R] 0.51 I don't want testing unless it can tell me whether I have prostate cancer now. [R] 0.49 I would not want to have children if I know I have the prostate cancer risk gene. [R] 0.44 I would want to put off testing as long as I can. 0.42 Distress Subscale 3: Psychological distress (alpha = 0.73, 10% variability) I am concerned I will lose or not be able to get LIFE insurance if I get the genetic testing for prostate cancer risk. [R] 0.64 If I know I have the prostate cancer risk gene, it will make me anxious. [R] 0.59 I am concerned I will lose or not be able to get HEALTH insurance if I get the genetic testing for prostate cancer risk. [R] 0.57 If I know I have the prostate cancer risk gene, I will feel worse about myself. [R] 0.46 My life will get worse if I know I have the prostate cancer risk gene. [R] 0.46 If I know I have the prostate cancer risk gene, it will change the way I think about the future. 0.45 Positive expectations Subscale 4: Beliefs in favorable outcomes if tested (alpha = 0.60, 7% variability) I believe this test could save my life. 0.52 The more I know about my risk for prostate cancer, the better I will feel about testing. 0.51 The test results might provide valuable information on prostate cancer risk to my family members. 0.45 If I know I have the prostate cancer risk gene, my doctor may want to do more tests. 0.42 Intent Subscale 5: Intention (alpha = 0.79) I would want the genetic test for prostate cancer risk when it becomes available. - I would want the test if it could tell me that prostate cancer is more likely to happen earlier in my life. - I would want this test if it could tell me that prostate cancer is more likely to be more life threatening because I have the prostate cancer risk gene. - I would want this test even if it does not tell me now information about how early or aggressive prostate cancer may be in my future. - [R] – Item reversed in coding for analysis N.B. – Intent items were not included in the factor analysis, thus there are no available data on pattern loadings and variance. The following factors did not load onto the four value-based factor domains, and were omitted from further analysis: I want to wait on testing until it is shown to be very accurate. I will not be able to keep my job, or get a promotion, if I know I have the prostate cancer risk gene. If I know I have the prostate cancer risk gene, my doctor might pressure me to receive treatment. Nothing can be done to prevent prostate cancer. Changes in my lifestyle can reduce my risk of cancer. I only want my family doctor to do this test for prostate cancer risk. I don't want testing unless I can do something to prevent prostate cancer. The government could use my test results in ways I do not want. I often worry about getting prostate cancer If I know I do not have the prostate cancer risk gene, I won't need rectal exams or PSA tests as often. No matter my results, I would want testing if it helps find a cure. I don't want the test if my health care coverage does not pay for it. I would want to get tested because I just want to know if I have the gene for prostate No one should give out my test results to anyone else without my permission. I would get testing if my doctor recommended it. Overall, the five subscales showed satisfactory internal consistency. The four items within Intention scale, although grouped together a priori for their content, showed a good internal consistency alpha coefficient at 0.79. Among the 49 items that probed men's beliefs, values, and attitudes, the 11 items that loaded high on Motivation accounted for most of the variability (37%) with a very high alpha coefficient (0.89). The nine items in Consequences accounted for the next largest amount of variability (23%) with an alpha coefficient of 0.73. The six items in Distress accounted for 10% of the variability with an alpha of 0.73. Finally, the four items in Positive Expectations accounted for 7% of the variability with an alpha of 0.60. The factor pattern loadings reflect the correlation between an individual item and its subscale. For example, Table 2 shows that Motivation is strongly associated with the item "even if other relatives did not want me to, I would get genetic testing." (Loading value = 0.80). Respondents with high motivation tended not to be influenced by other relatives. Importantly, the less one is influenced by a relative's opinion, the more likely he is to be motivated to get testing. Conversely, a man who was easily influenced by his spouse or children was somewhat less likely to be motivated toward testing. This latter set of values may reflect the desire for more information and counsel. The inter-correlations between the subscales are summarized in Table 3 , and reveal how these subscales were associated with one another and how they affected intent. The respondents' motivation (regarding the influence of others in their decision) was positively correlated with intention to test ( r = 0.69, p < 0.001). There was also a positive and statistically significant correlation between one's motivation and one's expectations that genetic screening may lead to favorable outcomes for the gene carrier and his family ( r = 0.39, p < 0.001). Concerns about the consequences of a positive result, including the uncertainties of test validity and accuracy, and the availability of subsequent interventions, were positively correlated with distress ( r = 0.34, p < 0.001) and diminished intention to test ( r = -0.16, p < 0.01). Distress-based values were associated with diminished intention to test ( r = -0.17, p < 0.001). Finally, respondents who expected favorable outcomes were associated with increased intention to test ( r = 0.48, p < 0.001). Table 3 Inter-correlations between subscales Motivation Consequences Distress Positive Expectations Motivation - Consequences -0.08 - Distress -0.19* 0.34* - Positive Expectations 0.39* -0.02 -0.003 - Intention 0.69* -0.16* -0.17* 0.48* * p < 0.001 Discussion These data demonstrate that men in the general public, aged 40 to 70 years without a personal history of prostate cancer, consider prostate cancer genetic testing related to four value-based factor domains, similar to past literature findings on genetic testing for hereditary cancer risk. The motivation factor, which measures values of influence by others, is the strongest decision factor in guiding their opting for the test. More than 80% of men interviewed would consider getting tested if the test was available now. Their stated intention, as measured by the four intent items, is highly correlated with how strongly they feel they are motivated toward the test and inversely related to family influences. Men with strong motivation to get tested also have significantly lower concerns about psychological distress and higher levels of positive expectations. The recommendations of physicians and geneticists are important to men's expressed motivation, although the professionals did not appear to be more influential than their kin. A respondent is more likely to want the test if he believes that the test may be informative of family risk and may lead to early identification and prevention of cancer (as part of the Positive Expectations domain). The influences of kin, along with beliefs in family risk, highlight the importance of reviewing family-related risk information as part of genetic consultation and informed consent. Men undergoing informed consent for hereditary prostate cancer risk in the future not only should be provided information on what genetic testing can and cannot do for them, but also what the test results could mean for others surrounding them (as evidenced by the influences of family, etc.). Prior hereditary breast cancer (BRCA) and colorectal cancer (CRC) literature has noted anecdotally that perception of benefit to one's family influences genetic test uptake. Eliciting patient perceptions of concerns regarding their family may be beneficial to consider in oncology genetic testing generally. Similar to this literature, intention was found to be influenced by the respondent's concerns about test validity, test accuracy, and by the availability of interventions that may lead to favorable outcomes. Not surprisingly, men who were concerned about potential psychological distress were less likely to want the test. One unanswered question is how men's anticipatory distress and expected adverse consequences may affect how family risk information is interpreted and discussed. Few men in our study anticipated high levels of distress. Although literature data clearly show elevated distress among patients and their family members [ 21 ]. More research is needed to better establish the family-risk construct and how it may be influenced by other beliefs and values. The present study has limitations. Given the exploratory nature of factor analysis, these data are aimed at identifying coherent subsets of variables for data reduction, not at identifying specific attitude statements that discriminate skeptics from supporters. Nevertheless, the reduced set of 34 items is the most important among the administered 57 items, and comprises a coherent and reliable assessment tool of eliciting values and intention toward testing. This item set can thereby serve as a foundation for a confirmatory health beliefs model, using Structural Equation Modeling techniques to better elucidate the interactions of these value-based domains [ 22 ]. Also, we noted that this population had somewhat higher income and education levels than the overall Philadelphia Consolidated Metropolitan Statistical Area (CMSA). 51% of men had over $75,000 income, compared with the 32% in the Philadelphia CMSA 2000 census year dataset, and 41% had completed a Bachelor's degree or higher, compared with 28% in the CMSA. These differences may be due to affluent subjects living in suburban counties in the metropolitan Philadelphia area, who then self-select to be seen by physicians in the University of Pennsylvania system. As noted above, our prior work demonstrated no demographic differences except education (with more education correlating with diminished intention). Thus, we do not foresee an adverse impact of these discrepancies on the overall outcomes of our analysis [ 20 ]. Future directions of this research may include exploring the relationship between stated intent in prostate cancer genetic screening and actual testing behavior when testing is available. Studies have shown that expressed intention does not necessarily translate to actual behavior in taking genetic tests for breast and colorectal cancers [ 10 , 23 - 29 ]. The same discrepancy between attitude and behavior may exist when a test for prostate cancer is available for the general public. Our data suggest that potential psychological distress, worries about test validity, insurance, confidentiality, and the uncertainties in subsequent intervention decisions may need to be balanced with family considerations when testing becomes available [ 30 ]. Conclusions Men in this survey voiced strong attitudes favoring future genetic testing for prostate cancer risk. In the past decade and a half, genetic testing for a variety of cancers concentrated on several key concepts: i.e., stigmatization, privacy, anxiety/stress, and the need to know. These notions of stigma and psychological impact were not as relevant in this population regarding prostate cancer risk genetic testing. For examples, the following statements did not show strong enough factor loadings to warrant their inclusion, such as "I will not be able to keep my job, or get a promotion, if I know I have the prostate cancer risk gene," "The government could use my test results in ways I do not want," "I often worry about getting prostate cancer," and "I would want to get tested because I just want to know if I have the gene for prostate cancer." The most relevant aspect of data reported herein is that they begin to shed new light on the relevance of "others." How men were concerned about the impact on and the effects upon one's family were reflected in the factor analysis. As a result, future informed consent may likely include considerations of 1) how the test results will affect their own future lives, and 2) how the test results will affect their family members. The latter consideration is seldom brought into the informed consent process in the genetic counseling but may be relevant to the patient. Competing interests The author(s) declare that they have no competing interests. Authors' contributions DD designed the overall project study, collaborated in the data analysis, and participated in its coordination. YL designed and carried out the factor analysis statistics. Both authors drafted, read, and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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Racial variations in processes of care for patients with community-acquired pneumonia

Background Patients hospitalized with community acquired pneumonia (CAP) have a substantial risk of death, but there is evidence that adherence to certain processes of care, including antibiotic administration within 8 hours, can decrease this risk. Although national mortality data shows blacks have a substantially increased odds of death due to pneumonia as compared to whites previous studies of short-term mortality have found decreased mortality for blacks. Therefore we examined pneumonia-related processes of care and short-term mortality in a population of patients hospitalized with CAP. Methods We reviewed the records of all identified Medicare beneficiaries hospitalized for pneumonia between 10/1/1998 and 9/30/1999 at one of 101 Pennsylvania hospitals, and randomly selected 60 patients at each hospital for inclusion. We reviewed the medical records to gather process measures of quality, pneumonia severity and demographics. We used Medicare administrative data to identify 30-day mortality. Because only a small proportion of the study population was black, we included all 240 black patients and randomly selected 720 white patients matched on age and gender. We performed a resampling of the white patients 10 times. Results Males were 43% of the cohort, and the median age was 76 years. After controlling for potential confounders, blacks were less likely to receive antibiotics within 8 hours (odds ratio with 95% confidence interval 0.6, 0.4–0.97), but were as likely as whites to have blood cultures obtained prior to receiving antibiotics (0.7, 0.3–1.5), to have oxygenation assessed within 24 hours of presentation (1.6, 0.9–3.0), and to receive guideline concordant antibiotics (OR 0.9, 0.6–1.7). Black patients had a trend towards decreased 30-day mortality (0.4, 0.2 to 1.0). Conclusion Although blacks were less likely to receive optimal care, our findings are consistent with other studies that suggest better risk-adjusted survival among blacks than among whites. Further study is needed to determine why this is the case.

Background Pneumonia (with influenza) is the leading infectious disease cause of death in the United States and the sixth leading cause of death overall [ 1 ] According to national mortality data from the CDC blacks suffer disproportionately from this disease, with blacks having a higher incidence of pneumonia and a 1.4 times higher age-adjusted odds of death from pneumonia as compared to non-Hispanic whites [ 1 - 4 ] In contrast several studies of racial variations in short-term mortality have demonstrated that black patients hospitalized with pneumonia are less likely to die in the hospital than whites. [ 5 , 6 ] As part of the Pneumonia Medical Quality Improvement Study (MQIS) a national expert panel established a set of process of care measures for patients hospitalized with CAP [ 7 ] Several studies have demonstrated that some of these processes of care, especially prompt antibiotic administration within 4 or 8 hours of presentation, is associated with decreased mortality for inpatients with CAP [ 7 - 9 ] Although several studies have demonstrated significant racial differences in pneumonia care no one has examined whether there are racial variations in all of these explicit processes of care for patients with CAP. [ 5 , 6 , 10 - 13 ] The aims of this paper are to 1) examine whether there are significant racial differences in the processes of care that have been associated with mortality for patients hospitalized with CAP, and 2) to examine the relative risks of death within 30-days for blacks versus whites. Methods Study patients KePRO, the Medicare Peer Review Organization for Pennsylvania, obtained these data as part of the Pneumonia MQIS project, whose goals is to assess and improve the quality of care for Medicare patients hospitalized with CAP. The study population was Medicare fee-for-service inpatients hospitalized at participating hospitals in Pennsylvania between 10/1/1998 and 9/30/1999. Inclusion criteria included having a primary ICD-9 diagnosis of pneumonia (480.0–483.99; 485–487.0), or a primary diagnosis of respiratory failure (518.81) or sepsis (038. XX) with a secondary diagnosis of pneumonia. Only the first qualifying discharge was considered for each patient. Among the 204 hospitals functioning in PA during the study period, 101 agreed to participate in this study. For each hospital, a random sample of up to 60 discharges with qualifying ICD-9 codes was selected. For hospitals with fewer than 60 qualifying discharges, all charts were selected. In most cases, chart review data was collected by trained record abstractors either on site from the original record, or from photocopies sent to the offices of the Quality Improvement Organization. In two cases, data were collected by the hospital's own staff using an approved QIO data collection instrument (n = 2). Patients were excluded if they had no working diagnosis of pneumonia on admission or received care limited to comfort measures, left the hospital "against medical advice", or were transferred from another acute care hospital. Patients whose race was not white or black were also excluded. Data abstraction Chart review data included demographics, comorbid conditions, physical exam findings, laboratory data, and chest radiograph information. In addition, data on important processes of care for patients hospitalized with CAP were obtained by chart abstraction. These processes of care included: first antibiotics within 8 hours of admission, collection of blood cultures prior to antibiotic administration, oxygen saturation measurement within 24 hours of presentation, and concordance of antibiotic therapy with national guidelines. [ 7 ] After initial training the abstractors performed data collection on charts were assessed using gold-standard cases that had been previously evaluated by multiple expert abstractors. If the abstractors did not achieve 95% accuracy, they underwent further training until they had an error rate of less than 5%. In addition, 10% of charts were reabstracted during the review process to monitor the accuracy of chart review. The error rate for these reabstracted charts remained less than 5%. Risk adjustment The pneumonia severity index (PSI) was used to assess severity of illness at presentation [ 14 ] The PSI is a validated prediction rule for 30-day mortality in patients with CAP. Patients are classified into one of five risk classes based on three demographic characteristics, five comorbid illnesses, five physical examination findings, and seven laboratory and radiographic findings at the time of presentation. The PSI was developed and validated using data from a large prospective cohort study, in which 30-day mortality ranged from 0.1% for Class I to 27% for Class V for patients. [ 14 ] Sampling Due to the relatively small number of black patients in the cohort (n = 240) we performed a modified resampling procedure of the white cohort with matching to the black patients on age and gender [ 15 ] We included all black patients in the study sample, and performed multiple resampling of three white patients matched for age (< 65, 65–74, 75–84, and ≥ 85) and gender to each black patient in the sample. Matching was used to filter out demographic imbalances between the populations. This resampling was performed 10 times and the results were pooled for analysis. Statistical analyses Univariate statistics were used to compare sociodemographic and clinical characteristics between white and blacks patients. Categorical variables were analyzed using the Chi-square test and continuous variables were analyzed using Student's t-test. Separate discrete conditional logistic regression models were estimated for each of the individual process of care measures, and for 30-day mortality [ 16 ] The PSI score and race were entered as independent variables into the models. In addition we assessed the significance of any clinical variables not included in the PSI and significant at P < 0.10 into regression models using a step-wise forward method. However none of these additional variables were significant so they were excluded from the models. Interactions terms were assessed for each of the models however none were statistically significant so they were not included in any of the models. Results Of 4889 charts requested, the complete medical record was available for 4823. Of these, 4034 patients, 240 of whom were black, were eligible for inclusion in the study. Patients were excluded because they were neither white or black (N = 231) or because they had no working diagnosis of pneumonia on admission (n = 413), their care was restricted to comfort measures (n = 173), they were transferred from another acute care facility (n = 37), or they left "against medical advice" (n = 14). For each of the ten resamplings 720 white patients were sampled and matched to the 240 black patients based upon the age and gender as previously discussed. The clinical and demographic characteristics of the study population are presented in Table 1 . For our analysis of racial differences in care, the age and gender distribution of the whites was similar to that of the blacks because of our matching strategy. However, blacks continued to have higher PSI scores, indicating greater severity of illness, as well as more commonly having each of the comorbid conditions (malignancy, chronic renal disease, liver disease, congestive heart failure and history of stroke) that contribute to the PSI. There were no other statistically significant differences between the two groups. In univariate analysis mortality at 30-days was 7.8% for whites and 5.8% for blacks (p = 0.3), and 82.1% of whites received antibiotics within 8 hours as compared to 75.7% of blacks (p = 0.04). Regarding blood culture performance, 96.4% of white and 97.1% of blacks had blood cultures obtained within 24 hours, and 84.8% of whites and 77.8% of blacks had blood cultures obtained prior to antibiotics (p = 0.03). Oxygenation saturation was assessed within 4 hours of 88.9% of whites and 93.9% of blacks (p = 0.03). Figures 1 through 5 are forest plots that demonstrate the effect of race on the dependent variables. These plots show each of the 10 samplings and the results of the pooled analysis. These figures demonstrate the significant variability between the random samples for the different dependent measures. In the regression models, after adjusting for severity of illness with the PSI, black patients were significantly less likely to receive antibiotics within 8 hours with an odds ratio (OR) of 0.63 and 95% confidence interval (CI) of 0.41 to 0.97. Black patients also had a trend towards decreased all-cause mortality at 30-day with an OR of 0.4 and 95% CI of 0.16 to 1.0. There were no significant differences between whites and blacks in regards to obtaining blood cultures prior to antibiotics (OR 0.69, 95% CI 0.32–1.47), oxygenation assessment within 24 hours (OR 1.61, 95% CI 0.85–3.04), or use of guideline concordant antibiotics (OR 0.86, 95% CI 0.62-1.71). Discussion This study found significant racial differences in an important process of care for patients with CAP, specifically time to antibiotic administration. Our results support the previous studies of racial variation in pneumonia care which demonstrated racial variations in care for patients hospitalized with community-acquired pneumonia. [ 10 - 13 ] Our study also suggests that these variations may have clinically important outcomes since the process measures used to assess quality of care in this study have been previously associated with increased 30-day mortality. [ 7 - 9 ] Our study is also consistent with previous studies which found that blacks hospitalized with CAP have lower short-term mortality rates as compared to do whites [ 5 , 6 ] It is unclear why this would be the case. Possible explanations include confounders that we were not able to control for, or other important factors, which were not examined that may significantly vary by race such as sociodemographic characteristics or differences in immune response. Racial variations in CAP are important to assess since unlike coronary artery bypass surgery, hemodialysis, and many other conditions that have been studied, the inpatient treatment of CAP is largely outside of the control of the patient. Although the patient has input into being admitted to the hospital, after that point the patient has little input into the processes of care such as choice and timing of antibiotics, diagnostic testing or location of care. This has several advantages in studies where researchers seek to determine if racial differences in care reflect patient preferences, provider decisions or some negotiation between them. There are several possible explanations for our findings of racial variations in these processes of care. Besides the obvious conclusion that there may be biases that affect care there are several other possible factors that may be responsible that we are not able to examine. One possible factor is that there are geographic or other factors that results in blacks presenting for admission at hospitals with overall lower quality of care for patients with CAP. Although we were not able to control for this factor other studies have suggested that the reverse is usually true. [ 11 , 13 ] That is, minorities are more likely than whites to receive their care at tertiary teaching hospitals, which on average provide superior care as compared to other hospitals. [ 12 , 17 ] To attempt to adjust for imbalances between black and white patients we used a modified resampling technique to generate 10 samples of white patients, which were matched to the black population. We then pooled these results over the 10 samples. This approach allowed us to obtain a more robust estimate of the effect racial variation may have on mortality and processes of care then would be obtained from a single random matched sample [ 15 ] Interestingly it also demonstrates the potential biases that may be present if only a single sampling is performed for a matched analysis. The forest plots (figures 1 , 2 , 3 , 4 , 5 ) demonstrate that for some individual samples obtained significantly different results than the pooled analysis. We feel that this technique strengthens our demonstrated results. There are several limitations that should be acknowledged. First we did not have information on the physicians, hospitals, or the geographic locations of the providers so we were not able to adjust for clustering. Second our study was limited to Medicare patients hospitalized in Pennsylvania. It will also be important to examine whether patients with other types of insurance, such as Medicaid and managed care, and from other states have similar outcomes. In addition we were also unable to assess the robustness of our analysis using traditional techniques such as model cross validation on a new independent sample, or by randomly subdividing our current sample into a training and test samples, due to our small sample size. However we do have quasi-replication, at least in the white sample, by the multiple sampling that we performed. Finally we were unable to adjust for potential bias in pulse oximetry since this is a retrospective study. However recent work [ 18 , 19 ] questions the idea that pulse oximetry does not perform as well in those with increase pigmentation as compared to those with lighter pigmentation. Therefore we feel that it is unlikely that this would systematically bias the results of our study. Conclusions Despite these limitations, we believe our results, and the results of other studies, allow us to conclude that blacks are less likely than whites to have processes of care that are considered to represent superior quality of CAP care. Despite this, blacks with CAP have similar, and perhaps lower mortality than whites. Further research should both investigate how to make sure all patients receive optimal CAP care, and identify the factors responsible for the paradoxical advantage in survival that is seen among blacks. Competing interests None declared. Authors' contributions EM and JW conceived the study. EM and JC were responsible for the analysis. EM was responsible for the initial draft of the manuscript. 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/PMC514714.xml

545598

Genomic neighborhoods for Arabidopsis retrotransposons: a role for targeted integration in the distribution of the Metaviridae

The full complement of Arabidopsis LTR retroelements was identified and relative ages of full-length elements estimated showing that Pseudoviridae are much younger than Metaviridae. The distribution of retroelement insertions across the genome was shown to be non-uniform.

Background Endogenous retroviruses and long terminal repeat (LTR) retrotransposons (collectively called retroelements) generally comprise a significant portion of higher eukaryotic genomes. Dismissed as parasitic or 'junk' DNA, these sequences have traditionally received less attention than sequences contributing to the functional capacity of the organism. This perspective has changed with the completion of several eukaryotic genome sequences. The contributions of retroelements to genome content range from 3% in baker's yeast to 80% in maize [ 1 , 2 ]. Retroelement abundance has resulted in increased appreciation of the important evolutionary role they play in shaping genomes, fueling processes such as mutation, recombination, sequence duplication and genome expansion [ 3 ]. The impact of retroelements on their hosts is not without constraint: the host imposes an environmental landscape (the genome) within which retroelements must develop strategies to persist. Retroelement cDNA insertion directly impacts on the host's genetic material, making this step a likely target for regulatory control. Transposable elements (TEs) in some systems utilize mechanisms that direct integration to specific chromosomal sites or safe havens [ 4 , 5 ]. For example, the LTR retrotransposons of yeast are associated with domains of heterochromatin or sites bound by particular transcriptional complexes such as RNA polymerase III [ 6 - 9 ]. These regions are typically gene poor and may enable yeast retrotransposons to replicate without causing their host undue damage [ 10 ]. Non-uniform chromosomal distributions are observed in other organisms as well. For example, many retroelements of Arabidopsis thaliana and Drosophila melanogaster are clustered in pericentromeric heterochromatin [ 11 , 12 ]. However, beyond the yeast model, it is not known whether retroelements generally seek safe havens for integration. The genome of A. thaliana is ideal for exploring processes that influence the chromosomal distribution of retroelements. A. thaliana retroelement diversity has been analyzed previously, preparing the way for this study [ 13 - 15 ]. In contrast to the genomes of Saccharomyces cerevisiae , Schizosaccharomyces pombe and Caenorhabditis elegans , which have relatively few retroelements, A. thaliana has a diverse mobile element population whose physical distribution can be described in detail. Another benefit of A. thaliana stems from the fact that in contrast to most other 'completely sequenced' eukaryotic genomes, the A. thaliana genome sequence better represents chromosomal DNA of all types, including sequences within heterochromatin [ 11 ]. Here we undertake a comprehensive characterization of the LTR retroelements in the well characterized genome of A. thaliana to better understand the factors contributing to their genomic distribution. Results Dataset All reverse transcriptases in the A. thaliana genome were identified by iterated BLAST searches (Figure 1 ). The query sequences were representative reverse transcriptases from the Metaviridae, Pseudoviridae and non-LTR retrotransposons (Table 1 ). LTRs (if present) were assigned to each reverse transcriptase using the software package RetroMap (Figure 1 , see also Materials and methods). Although the coding sequences of many elements with flanking LTRs were degenerate, they are referred to as full-length or complete elements (FLE) to indicate that two LTRs or LTR fragments could be identified. 5' LTRs from FLEs and published A. thaliana elements were used to identify solo LTRs in the genome by BLAST searches. The final data set consisted of three insertion subtypes: 376 FLEs, 535 reverse transcriptase (RT)-only hits, and 3,268 solo LTRs (Table 2 ). These sequences comprise 3,951,101 bases or 3.36% of the total 117,429,178 bases in The Institute of Genomic Research (TIGR) 7 January 2002 version of the genome. Overall, chromosomal retroelement content ranged from 2.64% (chromosome 1) to 4.31% (chromosome 3). Chromosome 4 contained the fewest FLEs (53) and solo LTRs (449), whereas chromosome 3 had the most (92 FLEs and 1,053 solo LTRs). Element subtypes (FLE, RT-only and solo LTRs) were sorted into taxonomic groupings using the formal taxonomic nomenclature assigned to retrotransposons [ 16 , 17 ]. Our analysis identified numerous insertions for both the Pseudoviridae (211 FLE/82 RT-only/483 solo LTRs) and Metaviridae (168 FLE/142 RT-only/2,803 solo LTRs). The non-LTR retrotransposons lack flanking direct repeats, and therefore only reverse transcriptase information is provided in this study; 311 non-LTR retrotransposon reverse transcriptases were identified. Unlike the Pseudoviridae, A. thaliana Metaviridae elements can easily be divided into sublineages, which are referred to as the Tat , Athila and Metavirus elements [ 14 , 18 ] (Figure 2 ). Our method identified 42 Tat FLEs, 38 Athila FLEs and numerous divergent Metavirus elements (82 FLE). No evidence was found for BEL or DIRS retroelements. The Metaviridae make up 2.34% of the A. thaliana genome, whereas the Pseudoviridae represent only 1.25% of the total genomic DNA. This difference is accounted for largely by the longer average size of Metaviridae FLEs (8,952 nucleotides) and solo LTRs (447 nucleotides) when contrasted with the Pseudoviridae FLEs (5,336 nucleotides) and solo LTRs (187 nucleotides) (data not shown). Among the subgroups of the Metaviridae, the average length of Metaviruses is closer to that of the Pseudoviridae than to the mean lengths of the Athila and Tat lineages. The Pseudoviridae are also more uniformly sized than the Metaviridae. A second factor contributing to the abundance of Metaviridae is that they have approximately six times more solo LTRs than the Pseudoviridae, even though numbers of complete elements are similar between families (Table 2 ). The ratios of solo LTRs to FLEs also clearly differ between the Metaviridae (16.7:1) and Pseudoviridae (2.3:1). Chromosomal distribution The distribution of retroelements was examined on a genome-wide basis. Upon mapping the retroelement families onto the A. thaliana chromosomes, the previously noted pericentromeric clustering of TEs was immediately evident (Figure 3 ) [ 11 ]. The Metaviridae appeared to cluster in the pericentromeric regions more tightly than the Pseudoviridae and non-LTR retrotransposons. Distributions of these latter two groups appeared similar, as did the distribution of solo LTRs relative to full-length elements (Figure 4 ). We assessed statistical support for the apparent clustering of elements by comparing the observed distribution of each lineage to a random uniform distribution model (Table 3 ). This model assumes that any location in the genome is expected to have a uniform probability of element insertion. This model was rejected by Kendall-Sherman tests of uniformity for every lineage and chromosome combination. All p -values were less than 0.05 and most were less than 0.0001. We next looked at distribution patterns between element families to determine whether they are similar. On the basis of the retroelement distribution maps (Figure 3 ), we hypothesized that this would not be the case for the Metaviridae because they appeared to be associated with centromeres to a greater degree than the other families. Each family's chromosomal distribution, inclusive of all subtypes (for example, FLE, RT-only and solo LTR), was tested for similarity to the distribution of the other families using a permutation test. With the exception of chromosome 3, the distribution of non-LTR retrotransposons was not significantly different from that of the Pseudoviridae. Comparisons of Metaviridae elements with Psedoviridae and/or non-LTR elements differed significantly ( p < 0.05) for all combinations. To assess whether the Metaviridae sublineages contributed equally to the observed distribution bias, we tested a model wherein the three sublineages ( Athila , Tat and Metavirus ) were expected to have similar distributions. This appears to be true, as significant differences were not detected on any chromosome for these sublineages. We then checked whether the FLEs, RT-only hits or solo LTRs displayed different distributions from one another within their respective families. No consistently significant trends were observed for the Pseudoviridae or the Metaviridae. Oddly, the Metaviridae solo LTR distribution displayed significant differences from the FLEs and RT-only hits for chromosome 3. A feature of pericentromeric regions in A. thaliana is that they are heterochromatic, a state required for targeted integration by the yeast Ty5 retroelement [ 19 ]. Because of the observed pericentromeric clustering of retrotransposons in A. thaliana , we assessed a simple model that assumes that all elements transpose to heterochromatin (Table 4 ). There are several genomic regions that are typically considered heterochromatic in A. thaliana - centromeres, knobs (on chromosomes 4 and 5), telomeres and rDNA [ 20 - 22 ]. We looked for differences between lineages with respect to whether retroelements were within a heterochromatic region, or, if outside, whether differences existed in distances to the nearest heterochromatic domain. All lineage combinations showed highly significant differences in heterochromatic distributions. In the Metaviridae, the Metavirus elements are less tightly associated with heterochromatin than are Tat and Athila , which did not differ significantly from each other. Element subtypes also differed in their distribution with respect to heterochromatin. The major source of differences was the distribution of solo LTRs in the Metaviridae. Age of insertions LTR retroelements have a built-in clock that can be used to estimate the age of given insertions. At the time an element inserts into the genome, the LTRs are typically 100% identical. As time passes, mutations occur within the LTRs at a rate approximating the host's mutation rate. LTR divergence, therefore, can be used to estimate relative ages between elements, assuming that all elements share the same probability of incurring a mutation. Although it is possible to estimate ages for non-LTR retrotransposons by generating a putative ancestral consensus sequence and calculating divergence from the consensus, this method is not directly equivalent to estimating ages by LTR comparisons. Therefore, age comparisons were performed only for the LTR retroelement families. Note that the ages depicted in Figure 5 are relative, and we do not claim that a particular element is a specific age in this study. Rather, we focus on whether elements are significantly older or younger than each other. Statistically significant age differences were observed among the Pseudoviridae and three Metaviridae sublineages ( F = 14.4, df = 3 and 368, p < 0.0001) (Table 5 , Figure 5 ). Overall, the Pseudoviridae are younger than the Metaviridae ( t = 5.72, df = 368, p < 0.0001). When the Metaviridae sublineages are considered, it is apparent that the Athila elements are responsible for much of the increased age of this family. The difference between Athila and the other two sublineages is significant, with p = 0.0003 being the highest value for sublineage comparisons. Elements within heterochromatic regions were significantly older than those found outside ( F = 17.19, df = 1 and 368, p < 0.0001). There was suggestive evidence that the mean element ages varied among chromosomes ( F = 2.73, df = 4 and 368, p = 0.0289). However, all pairwise comparisons between chromosomes failed to yield significant results at the 0.05 level using the Tukey-Kramer adjustment (data not shown). Discussion Completed genome sequences enable comprehensive analyses of retroelement diversity and the exploration of the impact of retroelements on genome organization. Although most large-scale sequencing projects use the shotgun sequencing method, this method makes it particularly difficult to assemble repetitive sequences and to correctly position sequence repeats on the genome scaffold. Consequently, regions of repetitive DNA such as nucleolar-organizing regions (NORs), telomeres and centromeres tend to be skipped, or are sometimes represented by consensus or sampled sequences. The difficulty of cloning repetitive sequences and the drawbacks noted above result in the under- or misrepresentation of the repetitive content of most genomes. Because retroelements frequently comprise a large proportion of the repetitive DNA, 'completed' genome sequences are typically not ideal for studies of retroelement diversity and distribution on a genomic scale. In contrast to these cases, the A. thaliana genome is reliably sequenced well into heterochromatic regions and work continues to further define these domains [ 11 , 23 ]. Another factor frustrating comprehensive analyses of eukaryotic mobile genetic elements is the inherent difficulty in annotating these sequences. Many mobile element insertions are structurally degenerate, rearranged through recombination or organized in complex arrays. Software tools and databases such as Reputer [ 24 ] and Repbase update [ 25 ] have been developed to identify and classify repeat sequences, and these tools have proved helpful in several genome-wide surveys of mobile elements. RECON [ 26 ] and LTR_STRUC [ 27 ] are software tools that go one step further and consider structural features of mobile elements that can assist in genome annotation. We developed an additional software tool, called RetroMap, to assist in characterizing the LTR retroelement content of genomes. RetroMap delimits LTR retroelement insertions by iterated identification of reverse transcriptases followed by a search for flanking LTRs. The software goes beyond existing platforms and carries out a number of analytic functions, including age assignment, solo LTR identification and visualization of the chromosomal locations of various groups of identified elements on a whole-genome scale. Data generated by RetroMap are subject to a few caveats. First, because element searches use reverse transcriptase sequences as queries, elements lacking reverse transcriptase motifs (for whatever reason) will not be identified. Second, when RetroMap encounters nested elements, tandem elements, and other complex arrangements, it does not attempt to delimit the element. Rather, the user is notified that a complex arrangement was encountered and the original reverse transcriptase match and any LTR(s) found are logged as separate entities. For the most part, RetroMap was quite effective in identifying LTR retrotransposon insertions. Our results closely agree with the findings of a parallel study conducted by Pereira [ 28 ]. For the Pseudoviridae and two of the three Metaviridae lineages ( Tat and Metavirus ), we identified 210 and 128 full-length elements, respectively, whereas Pereira recovered 215 and 130 insertions for these respective element groups. The two studies, however, differed significantly in the number of Athila elements identified. We found 38 insertions, whereas Pereira recovered 219. To reconcile these differences, we independently estimated Athila copy numbers by conducting iterative BLAST searches with a variety of Athila query sequences (data not shown). BLAST hits recovered with each query were then mapped onto the genome sequence. As a result of this analysis, we concluded that RetroMap missed many Athila insertions, either because they are highly degenerate or part of complex arrangements. In contrast to Pereira's approach, RetroMap requires that a reverse transcriptase reside between LTRs, and in many cases reverse transcriptases were absent or not detectable in Athila insertions. This can be resolved in future implementations of RetroMap that enable multiple query sequences to be tested. The Athila elements are large, and our underestimate of the number of Athila elements resulted in a corresponding underestimate of the total amount of retrotransposon DNA in the A. thaliana genome. We calculated 3.36% for this value, whereas Pereira calculated 5.60%. Pereira's estimate is likely to be the more accurate of the two. With the exception of the Athila elements, the observed frequency of insertions in complex arrangements was rare. For example, the Pseudoviridae had only eight nested and five unassignable elements. The small observed number of complex element arrangements in A. thaliana contrasts sharply with observations in grass genomes, where retroelements are usually found in complex nested arrays [ 29 , 30 ]. This may reflect a difference between species in factors contributing to chromosomal distribution of retroelements, or it may simply be a consequence of the difference in abundance of retroelements between A. thaliana (5.60% of the genome) and grasses (up to 80% of some genomes) [ 1 , 28 ]. Genomic distribution of A. thaliana retroelements Our data on the genomic distribution of retroelements can be considered in the light of theoretical work predicting the distribution of TE populations within genomes. These studies largely focus on the effects of selection and recombination on element insertions [ 31 , 32 ]. Particularly relevant is the recent study by Wright et al. [ 33 ], which considers the effects of recombination on the genomic distribution of major groups of mobile elements in A. thaliana (DNA transposons and retroelements). Our analysis extends this work by considering the genomic distribution of specific retroelement lineages. We investigate a model wherein selection and recombination affect element lineages uniformly, and hypothesize that observed deviations in the genomic distribution of specific element lineages reflect unique aspects of their evolutionary history or survival strategies such as targeted integration. Ectopic exchange model The ectopic exchange model assumes that inter-element recombination restricts growth of element populations [ 31 ]. Elements should be most numerous in regions of reduced recombination such as the centromeres, because of less frequent loss by homologous recombination. A corollary is that element abundance at a genomic location should inversely reflect the recombination rate for that region in the genome. Previous work suggests that this model is not the primary determinant of element abundance in A. thaliana . Wright et al. [ 33 ] examined recombination rate relative to element abundance in detail and found that the abundance of most A. thaliana TE families actually had a small but positive correlation with recombination rate, as was also observed in C. elegans [ 34 ]. Devos et al. [ 35 ] found ectopic recombination to be very infrequent relative to intra-element recombination, suggesting this process is unlikely to have a significant role in explaining the observed A. thaliana retrotransposable element distribution. The ectopic exchange hypothesis makes two unique predictions for retrotransposons: solo LTRs (a product of recombination) should be observed in higher proportions relative to full-length elements outside of heterochromatin; and heterochromatic elements will show a shift toward greater average age than elements elsewhere in the genome. Our consideration of age assumes that the chance of loss by recombination remains steady or increases with element age. However, old elements will have higher sequence divergence, thereby reducing the likelihood that they will recombine. In considering age, we also assume that all elements evolve at the same rates. This is unlikely to be the case, as local, chromosomal and compartmental locations are increasingly found to have different mutation rates [ 36 , 37 ]. With respect to the distribution of solo LTRs, our data show exactly the opposite bias predicted by the ectopic exchange model: the ratio of Metaviridae solo LTRs to FLEs in heterochromatin was nearly twice that found outside heterochromatin. The frequency of solo LTRs at the centromeres suggests that homologous recombination, at least over short distances (less than 20 kilobases (kb)), occurs frequently in pericentromeric regions. While we did observe the predicted shift toward older elements within heterochromatin, the data are not consistent with low rates of recombination as the determinant of retrotransposon accumulation at the centromeres. Within the Metaviridae, for example, the Metaviruses and Tat elements differ significantly in their association with heterochromatin. The ectopic exchange model would predict that the Tat elements should be older; however, these two lineages do not differ significantly in age. Although it is possible that recombinational forces could act differentially on different element sublineages, we view this as unlikely. Rather, forces other than ectopic recombination, such as targeted integration (see below), are responsible for the differential genomic distribution of certain element lineages. This is not to say that ectopic exchange has no role; however, it is unlikely to be the sole or prevailing influence. Deleterious insertion model The deleterious insertion model hypothesizes that element insertions are generally harmful to the host, and thus elements accumulate in regions of low gene density, where insertions are least likely to have negative effects on the host. According to this model, abundance of all classes of mobile elements should inversely reflect gene density within the genome. This is supported by the observation that elements are over-represented in gene-poor pericentromeric heterochromatin and are rare over much of the chromosome arms. However, we did not observe an increase in element abundance at other gene-poor heterochromatic regions (such as the telomeres and NORs), which would be predicted by the deleterious insertion hypothesis. This model would also predict that element insertions into gene-rich regions that are tolerated by the host should act as founders or safe havens for future element insertions. This could lead to an ever-expanding area of tightly clustered and frequently nested elements in euchromatin, assuming the overall random insertion rate is greater than the rate of sequence loss through recombination. Nested clusters of elements have been reported in cereals such as maize and barley [ 29 , 30 ]. In A. thaliana , although numerous potential 'seed' insertion sites are observed along the chromosome arms, we did not detect dense clusters of nested elements at these locations. In contrast to the deleterious insertion model, it is important to recognize that some element insertions may provide a selective advantage. Studies in C. elegans and rice indicate that many retrotranposons are associated with genes (63% and 20% in these species respectively) [ 38 , 39 ]. In D. melanogaster , some retrotransposon-gene associations are preserved in diverse natural populations, consistent with the hypothesis that they confer a positive selective advantage [ 40 ]. Furthermore, recent analyses in S. pombe suggest that the Tf1 retrotransposons may regulate expression of adjacent genes [ 41 ]. We cannot rule out a role for positive selection in the distribution of some A. thaliana mobile elements, but identifying such a role would require a more refined analysis of element distribution and gene associations. Impact of targeted integration The observation that many LTR retroelements have non-uniform genomic distributions suggested that targeted integration may be a driver of retroelement distribution patterns [ 42 ]. Neither the deleterious insertion nor ectopic recombination models address the situation where some or all elements have evolved the ability to bias their distributions through targeted integration. The LTR retroelements of S. cerevisiae insert preferentially into heterochromatin or sites occupied by RNA polymerase III, and in the evolutionarily distant S. pombe genome, retroelements are located preferentially upstream of genes transcribed by RNA polymerase II [ 6 - 9 ]. Retroviruses also insert preferentially into transcribed regions, with some retroviruses favoring insertions into promoter regions [ 4 , 43 ]. Targeted integration could contribute significantly to the chromosomal distribution of A. thaliana retroelements. As in other systems, targeting may occur because elements recognize a specific chromatin state and actively insert into regions with that type of chromatin. A chromatin-targeting model has the following predictions. First, very few elements will be found outside targeted chromatin domains. For example, all heterochromatic regions such as NORs, knobs and telomeres would be occupied by the same lineage of elements if these regions share a chromatin feature recognized by that lineage. Second, different retroelement lineages may be associated with different regions of the genome if they employ different targeting strategies. The targeting hypothesis is well supported for the Metaviridae, which on a genome-wide basis differ significantly in their chromosomal distribution from the Pseudoviridae and non-LTR retrotransposons. This is particularly true for the Athila and Tat lineages, both of which are tightly associated with pericentromeric regions. Athila and Tat elements are not found in heterochromatin regions around the telomeres, however, suggesting that telomeric and centromeric heterochromatin differ. Targeted integration to pericentromeric heterochromatin may be a general feature of the Metaviridae. Members of the Metaviridae are abundant in pericentromeric heterochromatin in many grass species [ 44 ]. Langdon et al. [ 45 ] suggested that an evolutionary ancient member of the Metaviridae in cereals targets to centromeric domains. Portions of a maize homolog of this element were found to co-precipitate with the centromere-specific histone CENH3, indicating an association of this element with a particular type of chromatin [ 46 ]. The Pseudoviridae and non-LTR retrotransposons differ in their genomic organization from the Metaviridae and are more loosely associated with pericentromeric regions. It may be that these element lineages do not target their integration, or they may recognize other chromosomal features, although we did not observe any association with other genome features or gene classes such as tRNA genes (data not shown). De novo integration events have been mapped on a chromosomal level for two tobacco Pseudoviridae elements in heterologous hosts - Tto1 in A. thaliana and Tnt1 in Medicago trunculata. In both cases these elements integrated throughout the genome, displaying some preference for genic regions [ 47 , 48 ]. Whether this observed distribution pattern reflects random integration or recognition of some other subtle chromosomal feature remains to be determined. Because we predict that the Metaviridae recognize pericentromeric heterochromatin, an important dataset for analysis will be maps of the various DNA methylation and histone-modification patterns for the full genome. In-depth characterization of the distribution of retroelements relative to chromatin modifications may reveal additional evidence for targeting and help to understand the impact of targeting on genome organization. Conclusions Our analysis of the genomic distribution of the A. thaliana LTR retroelements revealed that the distribution of the Pseudoviridae and the Metaviridae is non-uniform and that they tend to cluster at the centromeres. The pericentromeric association of three Metaviridae sublineages ( Metavirus , Tat and Athila ) was significantly more pronounced than for the Pseudoviridae. Several factors are likely to contribute to the centromeric association of these elements, including target-site bias, selection against euchromatin integration and pericentromeric accumulation of elements due to suppression of recombination. For the Tat and Athila lineages, however, target-site specificity appears to be the primary factor determining chromosomal distribution. We predict that, like retroelements in yeast, the Tat and Athila elements target integration to pericentromeric regions by recognizing a specific feature of pericentromeric heterochromatin. Materials and methods RetroMap and the A. thaliana retroelement dataset Reverse transcriptase amino-acid sequences (as defined by [ 49 ], see also Table 1 ), were used to query a database of A. thaliana chromosomes (TIGR version 7 January 2002) with the tblastn program (E = 1e -10 , XML output, filtering disabled) [ 50 ]. The resulting search report was imported into RetroMap. RetroMap (to be described in detail elsewhere) provides a graphical user interface (GUI) to interactively characterize LTR retrotransposons in targeted genomes or large genomic contigs (Figure 1a ). RetroMap generates a nonredundant set of database hits from BLAST results generated by a given query sequence set. Hits are merged if they directly overlap or if they align to different portions of the same query sequence. In this study, the nonredundant sequences were used to re-query the chromosome database twice more using tblastx (E = 1e -10 , XML output, filtering disabled) to identify increasingly divergent or degenerate elements. Unique hits identified in the final round of screening were taken to represent the entire complement of retroelements in A. thaliana . RetroMap assigns putative LTRs where possible for each reverse transcriptase by comparing 10 kb of DNA from each flank. This is accomplished using Blast2Sequences to identify flanking repeats [ 51 ] (Figure 1b ). Direct repeats found closest to the reverse transcriptase, larger than 50 bp and less than 5 kb, are considered to be LTRs. Hits with putative LTRs were considered to be full-length elements (FLE) or complete elements. Twenty-six reverse transcriptase hits were excluded from the FLEs owing to difficulty in automatic LTR assignment (13 each from the Pseudoviridae and Metaviridae). Among these were nested elements and tandem elements sharing a LTR. Reverse transcriptases were assigned to a retroelement lineage (Metaviridae, Pseudoviridae or non-LTR retrotransposon) on the basis of their similarity to the diagnostic reverse transcriptase query sequences. Full-length Metaviridae elements were further subdivided into the classic ( Metavirus ), Tat and Athila groups on the basis of the highest-scoring match in a BLAST database containing the Metaviridae reverse transcriptase sequences described in [ 18 ]. Putative complete elements with a predicted reverse transcriptase failing to significantly match any sequence in this database were removed from further consideration as false positives (two cases). Solo LTRs and solo LTR fragments were identified with blastn (E < 1e -5 ) using all predicted 5' LTRs of known A. thaliana elements and the FLEs. RetroMap assigns any putative LTR sequence that fails to match or overlap with a predicted FLE LTR as a solo LTR. Relative age calculation for full-length elements LTRs are identical at the time of retroelement integration, and so relative element ages were estimated from the percentage of identical residues shared between 5' and 3' LTRs for FLEs. The age formula used was T = d /2 k (time ( T ) = genetic distance ( d )/ [2 × substitution rate ( k )]), where genetic distance is 1 - (percent identity/100) and the substitution rate is 1.5 × 10 -8 [ 52 ]. Assignment of heterochromatin boundaries Chromosome coordinates relative to the left (north) end were used to calculate distances between retroelements and heterochromatic domains. Heterochromatin boundaries were derived from [ 20 - 22 ] and include the telomeres, heterochromatic knobs, NORs and centromeres. Chromosome end-coordinates were considered as the telomere boundaries. The A. thaliana NORs are located at the left (north) ends of chromosomes 2 and 4, and as these regions were only sample sequenced, their boundaries were assigned as the left ends of chromosomes 2 and 4. Heterochromatic knobs and pericentromeric regions were assigned as the outermost physical markers delimiting these regions, as determined by the studies listed above. Statistical tests A RetroMap-generated datafile was used as the data source for statistical testing. The data file contains chromosomal element coordinates, LTR identity, age and lineage information for all A. thaliana retroelement families by element category: reverse transcriptase only (R), full-length (F), and solo LTR (S). For each element type and each chromosome, a Kendall-Sherman test [ 53 - 55 ] was conducted to determine if the element positions were randomly distributed across chromosomes according to a uniform distribution. A permutation test [ 55 ] was used to assess the statistical significance of observed differences in the chromosomal position distributions for each chromosome across various element categories. The multi-response permutation procedures (MRPP) test is briefly described as follows. The average distance between a pair of elements within a category of interest is determined. A weighted sum of these averages over all categories of interest is computed, with each category weighted in proportion to the number of elements in the category. This weighted sum is the observed value of the test statistic. Next, the test statistic is re-computed for each of 10,000 random permutations of the category labels. For each permutation, the observed chromosomal positions of the elements are held constant while the category labels are randomly shuffled. The proportion of the 10,000 permutation-replicated test statistics that are less than or equal to the original observed test statistic serves as an approximate p -value for a test whose null hypothesis is that all element categories of interest have the same chromosomal position distribution. This permutation approach is useful for the chromosomal position data because first, no distributional assumptions are required, second, differences in chromosomal position distributions other than simple location shifts are detectable, and third, the method is not as sensitive to outliers as common parametric approaches. For FLEs, linear model analyses were used to assess the effects of the factors 'chromosome', 'lineage/sublineage', and 'location' relative to heterochromatin on the response variable 'element age'. F -tests were used to check for interaction between these three factors and to assess the statistical significance of observed differences among the five chromosomes, among the four lineage/sublineage categories (Pseudoviridae and the three Metaviridae sublineages: Athila , Tat or Metavirus ), and between elements inside and outside heterochromatin. The square root of age was used as the response variable in the age analysis so that the variance of the response would be roughly constant across categories defined by combinations of chromosome, lineage/sublineage, and location, as required for standard linear model analyses. Outlying observations were present, but the results of the analysis remained essentially the same with or without the outliers. Thus the reported results are based on the full dataset. Additional data files The following additional data are available with the online version of this article: a Microsoft Excel spreadsheet of data generated by RetroMap for each retrotransposon insertion identified; the data in this file was used for all statistical analyses (Additional data file 1 ). The Java application used to generate the LTR and retrotransposon coordinates and to estimate retrotransposon ages (Additional data file 2 ). To run RetroMap, version 1.3 or higher of the Java Runtime Environment (JRE ) must be present. To enable searches for LTRs, NCBI's BLAST 2 Sequences must be locally installed. Supplementary Material Additional data file 1 A Microsoft Excel spreadsheet of data generated by RetroMap for each retrotransposon insertion identified; the data in this file was used for all statistical analyses Click here for additional data file Additional data file 2 The Java application used to generate the LTR and retrotransposon coordinates and to estimate retrotransposon ages Click here for additional data file

/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545598.xml

338072

A Nuclear Function for Armadillo/β-Catenin

The Wnt signaling pathway provides key information during development of vertebrates and invertebrates, and mutations in this pathway lead to various forms of cancer. Wnt binding to its receptor causes the stabilization and nuclear localization of β-catenin. Nuclear β-catenin then functions to activate transcription in conjunction with the transcription factor TCF. A recent report has challenged this basic precept of the Wnt signaling field, arguing that the nuclear localization of β-catenin may be unrelated to its function and that β-catenin functions at the plasma membrane to activate this signaling pathway. Here we present evidence that the pathway in fact does depend on the nuclear localization of β-catenin. We reexamine the functionality of various truncations of β-catenin and find that only the most severe truncations are true signaling-null mutations. Further, we define a signaling-null condition and use it to show that membrane-tethered β-catenin is insufficient to activate transcription. We also define two novel loss-of-function mutations that are not truncations, but are missense point mutations that retain protein stability. These alleles allow us to show that the membrane-bound form of activated β-catenin does indeed depend on the endogenous protein. Further, this activity is dependent on the presence of the C-terminus-specific negative regulator Chibby. Our data clearly show that nuclear localization of β-catenin is in fact necessary for Wnt pathway activation.

Introduction The Wnt signal transduction pathway has been studied extensively in both vertebrate and invertebrate systems. The Drosophila ortholog wingless ( wg ) is a segment polarity gene that defines posterior cell fates in each of the larval segments (for a review of the various functions of Wg, see Wodarz and Nusse 1998 ). The pathway is activated when the extracellular ligand Wg binds to the transmembrane receptors Frizzled and Arrow. These in turn activate Disheveled (Dsh), which inactivates a complex composed of Axin, adenomatous polyposis coli (APC), and Zeste-white 3 (Zw3) (the Drosophila homolog of glycogen synthase kinase [GSK3β]). This complex is responsible for the retention of Armadillo (Arm) in the cytoplasm, for its phosphorylation, and thus for its targeting for ubiquitination and destruction. When the complex is inactivated by Dsh, the intracellular levels of Arm increase, and Arm enters the nucleus, where in combination with the transcription factor TCF/Pangolin, it activates the transcription of genes such as cyclin D and c- myc ( Wodarz and Nusse 1998 ). We have argued that Axin plays a key role in the Wnt signaling process, functioning both as an anchor for Arm and a scaffold for the degradation complex. Wnt signaling results in a visible reduction in Axin levels, and mutations in Axin cause a relocalization of Arm to the nucleus ( Tolwinski and Wieschaus 2001 ; Tolwinski et al. 2003 ). The nuclear import and export of Arm are not clearly understood (for a review, see Henderson and Fagotto 2002 ), but Arm can cross the nuclear membrane by interacting with the nuclear pore complex directly. Once in the nucleus, Arm interacts with a variety of nuclear factors, in particular the transcription factor TCF/LEF ( Behrens et al. 1996 ; Molenaar et al. 1996 ; Brunner et al. 1997 ; van de Wetering et al. 1997 ). The β-catenin–TCF complex releases repression and activates transcription ( Cavallo et al. 1998 ). A recent study has challenged this view and has questioned the importance of nuclear localization of Arm protein ( Chan and Struhl 2002 ). These authors' conclusions were based primarily on the observation that a membrane-tethered, stabilized form of Arm (Arm ΔArm ) causes activation of the Wnt pathway without entering the nucleus. However, this is not the first time that the controversy about the location of Arm/β-catenin function has arisen. Previously, a group working with amphibian embryos had found that membrane-tethered plakoglobin, a close relative of β-catenin, can activate Wnt signaling ( Merriam et al. 1997 ). Another group showed, however, that expression of membrane-tethered forms of β-catenin leads to the nuclear localization of endogenous β-catenin ( Miller and Moon 1997 ). When the endogenous Arm/β-catenin gene was mutated, the activity of membrane-tethered forms was lost ( Cox et al. 1999 b). These experiments illustrate the importance of following the activity of the endogenous allele in evaluating the activity of membrane-tethered forms. Previously, we had expressed the same membrane-tethered form used by Chan and Struhl (2002 ) in embryos with various endogenous arm mutations and had concluded that it functions by titrating Axin to the membrane, releasing the endogenous Arm protein and allowing it to move freely into the nucleus ( Tolwinski and Wieschaus 2001 ). These experiments are difficult, because none of the cell-viable alleles are absolute genetic nulls, as Arm plays essential roles in both Wnt signaling and cell adhesion. In this study, we reexamine Arm function using three classes of previously described arm alleles. We find that by manipulating their levels and localizations, many alleles believed to be signaling nulls can still activate transcription. When the cell-adhesive defects of the most severe class of alleles are rescued, however, the mutant protein still fails to signal, allowing us to assay the activity of membrane-tethered Arm in a true signaling-null background. We find that nuclear localization is necessary for pathway activation and that exclusively membrane-bound forms of Arm are insufficient for this. We use two novel missense mutations in arm to assess the nuclear activity of Arm and confirm that negative regulation by the transcriptional regulator Chibby (Cby) is required for patterning. Results Membrane-Tethered Arm Is Dependent upon the Endogenous arm Allele The original mutants in the arm gene were classified into three groups based upon their phenotypes and the position of stop codons that result in truncated proteins. The “weak” class has the smallest truncations and is represented by arm XM19 . In germline clones (where maternal and zygotic contribution of protein is removed; Chou and Perrimon 1992 ), its phenotype is identical to loss-of-function wg mutations ( Figure 1 B; Peifer and Wieschaus 1990 ). The “medium” class, represented here by arm O43A01 , shows defects in adhesion as well as transcription. Here germline clones give embryos that fail to differentiate an intact cuticle ( Figure 1 C; Tolwinski and Wieschaus 2001 ). The “strong” class ( arm XK22 ) does not allow proper progression through oogenesis and germline clones do not make eggs ( Figure 1 D; Peifer et al. 1993 ). Cox et al. (1999 b) showed that the junctional defects of the “medium” alleles can be circumvented by coexpression of a membrane-tethered full-length form of Arm (Arm S18 ) ( Figure 2 ). We have confirmed their findings and extended them to the “strong” allele during oogenesis. We show that uniform expression of Arm S18 allows arm XK22 germ cells to produce normal eggs and rescues the adhesive defects of both arm XK22 and arm O43A01 embryos. The membrane-tethered form does not, however, rescue the signaling defects associated with either of these alleles and the embryos show typical wg phenotypes (see Figure 1 G and 1 H). Figure 1 Arm ΔArm Requires Endogenous Arm Endogenous allele indicated at top; ectopically expressed transgenes indicated at left. (A) The wild-type cuticle of a Drosophila embryo. (B) The arm XM19 “weak” allele phenotype, similar to wg mutations in which the entire cuticle is covered with denticles. (C) The arm O43A01 “medium” allele phenotype shows disintegrated embryos in which cells delaminate owing to an inability to form adherens junctions. (D) arm XK22 “strong” allele does not produce embryos, owing to an oogenesis defect. (E) A wild-type embryo expressing Arm S18 shows a wild-type cuticle. (F) arm XM19 mutant expressing Arm S18 is rescued to a wild-type cuticle. (G) arm O43A01 mutant expressing Arm S18 shows rescued adhesion, but a wg mutant signaling phenotype. (H) arm XK22 mutant expressing Arm S18 also shows rescued adhesion, as well as a wg mutant signaling phenotype. (I) Coexpression of Arm ΔArm and Arm S18 in wild-type embryos leads to naked cuticle or the uniform Wg active phenotype. (J) Coexpression of Arm ΔArm and Arm S18 leads to naked cuticle or the uniform Wg active phenotype in an arm XM19 mutant background. (K) Coexpression of Arm ΔArm and Arm S18 in arm O43A01 mutant embryos leads to naked cuticle or the uniform Wg active phenotype. (L) However, coexpression of Arm ΔArm and Arm S18 in “strong” mutant arm XK22 background shifts embryos back to the wg mutant phenotype. Expression of the membrane-tethered, stabilized form of Arm (Arm ΔArm ) leads to uniform activation of signaling in all cells. This effect is independent of whether the cell is exposed to Wg signal or not, because Arm ΔArm functions independently of Wg ligand. The membrane-tethered, unstabilized form of Arm (Arm S18 ) leads to pathway activation only in cells that receive Wg signal, because this form of Arm is still subject to Wg-dependent phosphorylation and phosphorylation-dependent degradation. Figure 2 Structure of Arm Protein and Alleles Arm protein consists of three regions. The N-terminus is required for transactivation, for phosphorylation-based and proteasome-mediated degradation, and for α-catenin binding. The central repeats region is a superhelical structure that contains the binding sites for most of Arm's binding partners, including APC, TCF, Cadherin, and Axin. The C-terminus is required for Cby and Teashirt binding and transactivation. The arm F1a mutation causes an arginine-to-histidine change within repeat six. The arm LM134 mutation causes a serine-to-phenylalanine change in repeat five. The “weak” allele arm XM19 removes the entire C-terminus. The “medium” allele arm O43A01 causes early termination within repeat nine. The “strong” allele arm XK22 causes early termination within repeat six. The Arm ΔArm transgene consists of the entire repeats region and C-terminus fused to an HA tag and myristoylation sequence at the N-terminus under GAL4/UAS control. The Arm S10 transgene contains a small deletion in the N-terminus, which removes the four phosphorylation sites necessary for degradation and is under GAL4/UAS control. The Arm S8 transgene contains a deletion of approximately a third of the C-terminus and is under endogenous promoter control. The Arm S18 transgene contains the entire Arm sequence fused to the CAAX myristoylation sequence of Ras and is under endogenous promoter control. The UAS–Arm XM19 is the equivalent of the arm XM19 allele in deletion, but is fused to an N-terminal HA tag and is under GAL4/UAS control. Expression of Arm S18 has no effect on the cuticle of wild-type embryos (compare Figure 1 E to 1 A), but it does rescue the signaling defects of arm alleles, like arm XM19 , that have only short C-terminal truncations ( Cox et al. 1999 b; see Figure 1 F). These alleles normally show very low levels of protein ( Peifer and Wieschaus 1990 ), and Cox et al. (1999 b) postulated that expression of a membrane-tethered Arm might “free up” the endogenous mutant protein, allowing the “weak” allele to signal. The low levels of arm XM19 may reflect degradation of nonsense mRNAs triggered by the premature stop codon in this mutant (reviewed in Wagner and Lykke-Andersen 2002 ). To eliminate this degradation, we expressed a cDNA version of the arm XM19 allele under GAL4/UAS control ( Brand and Perrimon 1993 ) in embryos mutant for arm XM19 ( Figure 3 B). To avoid the possibility of overexpression artifacts, we also expressed a smaller C-terminal deletion from the endogenous promoter (Arm S8 ; Orsulic and Peifer 1996 ). In both experiments, the truncated protein from the transgene accumulated to levels approximating those observed in wild-type ( Figure 3 G and 3 H) and in the characteristic striped pattern indicative of response to the Wg signal ( Peifer and Wieschaus 1990 ). The truncated protein rescued the arm XM19 phenotype to a wild-type cuticle pattern and allowed hatching ( Figure 3 C). When combined with a mutation in the kinase zw3 , Arm S8 causes the cuticles of these embryos to appear uniformly naked (compare Figure 3 E to 3 D), as would be expected since the Arm S8 protein is expressed to high uniform levels throughout the epidermis when Zw3 is removed ( Figure 3 I). These experiments argue that the C-terminus is not essential for signaling or transcriptional activation of Wnt targets required for cuticle patterning. However, as we do not obtain adult flies containing exclusively the truncated alleles, it is very likely that the C-terminus is not entirely expendable and must have important functions later in development. Figure 3 C-Terminally Truncated Arm Can Signal If Its Levels Are Increased (A) arm XM19 shows a wg mutant phenotype. (B) Expression of GAL4/UAS-driven Arm XM19 protein in arm XM19 mutant background rescues this to a wild-type pattern. (C) The same is true of expression of an endogenous promoter-driven truncation Arm S8 . (D) Removal of Zw3 has no effect on arm XM19 cuticle pattern. (E) However, when Arm S8 is introduced into arm XM19 , zw3 mutants, the cuticle is naked. (F) Wild-type embryo is shown for comparison. (G–I) Arm stainings reveal that expression of UAS–Arm XM19 (stained for the HA tag [G]) and Arm S8 (stained for Arm [H]) is present in stripes corresponding to Wg striping, whereas removal of Zw3, along with Arm S8 expression, leads to uniform and high levels of Arm throughout the epidermis (I). Null Allele Background Proves That Arm ΔArm Cannot Signal on Its Own The fact that arm XM19 is able to signal when expressed at normal levels invalidates its use in tests for a direct activity of membrane-tethered Arm in Wnt signaling ( Chan and Struhl 2002 ). Therefore, expression of Arm ΔArm in a “weak” allele background cannot address whether membrane-tethered Arm activates transcription without ever entering the nucleus, since a membrane-untethered, signaling-competent form of Arm is also present. To directly address whether the Arm ΔArm transgene can transmit Wg signal on its own, we turned to the “strong” and “medium” alleles. Although Arm S18 is not sufficient to restore signaling to these alleles, it raises the possibility that stronger expression of stabilized, membrane-tethered Arm (Arm ΔArm ) might reveal some signaling capacity of those alleles as well. Experiments of this kind have been difficult with Arm ΔArm , given that it lacks the α-catenin-binding site and fails to rescue the junctional defect in “medium” and “strong” endogenous arm allele backgrounds. We have found that by expressing both Arm ΔArm and Arm S18 , we can recover intact embryos in all backgrounds tested. We find that “medium” and “weak” alleles can be induced to activate transcription, but the “strong” arm allele cannot (see Figure 1 J– 1 L), consistent with the position of the “medium” alleles in the hypomorphic allelic series. These findings demonstrate that Arm ΔArm is dependent upon the endogenous form of arm , as it cannot activate transcription in the “strong” allele background. Loss-of-Function Missense Mutations When Arm ΔArm is expressed in a wild-type embryo, it strongly activates Wg signaling ( Figure 4 C; Chan and Struhl 2002 ). Chan and Struhl (2002 ) suggest that this is because this membrane-tethered form of Arm can signal on its own. The results presented above argue, on the other hand, that it does so by stabilizing the endogenous protein. To further test this, we asked whether expression of Arm ΔArm can induce Wg signaling when endogenous Arm is replaced by signaling-deficient Arm. We turned to two novel missense mutations where the rest of the arm coding region remains intact. Because these alleles do not produce truncations through stop codons, they are immune to nonsense mRNA degradation ( Wagner and Lykke-Andersen 2002 ). Both mutations result in amino acid substitutions close to repeat seven, a key hinge region postulated to be important in binding of TCF ( Huber et al. 1997 ; Graham et al. 2000 ). Both mutants retain the phosphorylation sites required for degradation and therefore accumulate in stripes in response to Wg signal ( Figure 5 I and 5 J). They supply apparent wild-type junctional activity and accumulate to high levels in all cells when the kinase responsible for the degradation signal (Zw3) is removed ( Figure 5 K and 5 L). The primary phenotype of these alleles is a loss or reduction of Wnt transcriptional responses ( Figure 5 A and 5 B). The arm F1a allele produced a partial loss-of-function phenotype, and germline clone embryos show some residual naked cuticle. arm LM134 produces a stronger phenotype comparable to a loss of wg function, although it may not be a signaling null (see below). Figure 4 Expression of Arm ΔArm Leads to the Nuclear Localization of Endogenous Arm Protein (A) Wild-type Arm protein appears in stripes that correspond to cells responding to Wg signaling. (B) Expression of Arm ΔArm in an arm F1a background leads to the nuclear localization of endogenous Arm. (C and D) Dark-field images reveal that expression of both Arm ΔArm and Arm S10 leads to similar naked cuticle phenotypes. (E) An anti-Arm Western blot showing a faster-migrating band, which correlates with endogenous Arm's being active, and a slower-migrating band, which correlates with Arm's being inactive. Figure 5 ΔArm Functions through Endogenous Arm (A) Embryonic cuticle of arm F1a mutant showing a weak loss-of-function phenotype. (B) Cuticle of arm LM134 mutant embryo showing a strong loss-of-signaling phenotype. (C) Embryo mutant for arm F1a expressing Arm ΔArm showing relatively normal segment polarity. (D) arm LM134 mutant expressing Arm ΔArm also shows segment polarity. (E and F) Both alleles in combination with a null zw3 allele and expressing Arm ΔArm show a complete lack of denticles. (G and H) Both alleles expressing the activated but nontethered form of stabilized Arm, Arm S10 , show the naked cuticle phenotype. (I–L) In both missense alleles, the mutant protein is expressed in stripes (I and J), corresponding with Wg expression (data not shown), which is abolished when the key degradation kinase Zw3 is removed (K and L). We asked whether these signaling-deficient alleles could block the cell fate transformation and Wnt target activation observed when Arm ΔArm is expressed in wild-type epidermis. If Arm ΔArm functions independently of the endogenous protein, then all cells should assume the naked cell fate. However, this does not occur ( Figure 5 C and 5 D). Instead, both point mutants produce a cuticle pattern with periodic denticle belts and regions of intervening naked cuticle. This periodicity may reflect the fact that arm F1a and arm LM134 can still be controlled by Wg even when Arm ΔArm is expressed. This periodicity is, in fact, abolished when Zw3 activity is removed from such embryos (i.e., in triply mutant zw3, arm F1a ; Arm ΔArm embryos). Under these conditions, all cells in the cuticle take on the naked cell fate ( Figure 5 E and 5 F). Since Arm ΔArm lacks the N-terminal sites that respond to Zw3, the sensitivity of the double-mutant phenotype confirms that the pattern of the double mutant is dependent on the endogenous Arm protein. The behavior of membrane-tethered Arm ΔArm contrasts with that of other stabilized forms of Arm that would be predicted to move more freely between the cytoplasm and the nucleus. Arm S10 , for example, contains a small N-terminal deletion that blocks Zw3 phosphorylation, but preserves binding sites for various nuclear proteins (see Figure 2 ; Pai et al. 1997 ). Arm S10 is not membrane-tethered, but the cell fate transformations it produces are identical to those produced by Arm ΔArm (compare Figure 4 C and 4 D). They do not, however, depend on the endogenous allele and are still observed in an arm F1a or arm LM134 germline clone background ( Figure 5 G and 5 H). Arm ΔArm Causes Nuclear Localization and Mobility Shift of Endogenous Arm All of our experiments argue that Arm ΔArm produces its effect on transcription by activating the endogenous alleles. To investigate the mechanism that underlies this effect, we looked at the in situ localization of the endogenous Arm protein and its migration pattern on Western blots. Expression of Arm ΔArm is sufficient to drive both wild-type and the point mutant forms of Arm into nuclei (see Figure 4 A and 4 B; Miller and Moon 1997 ; Tolwinski and Wieschaus 2001 ). Generally, the most obvious feature observed upon removal of any of the negative factors of the Wg pathway is the rapid accumulation of Arm in cells. However, another feature is the phosphorylation state of the Arm protein. Peifer et al. (1994 a) found that a fast-migrating band of Arm corresponds with active Wg signaling and that a slower-migrating band corresponds with Wg's being off. Therefore, it is the unphosphorylated band that corresponds with signaling. Here we show that, on Western blots, endogenous Arm protein responds to Arm ΔArm expression in much the same way that it does to the removal of negative components of the pathway such as Axin and APC1 and APC2 (see Figure 4 E). We see a downshift of the protein, which is directly opposite to what is seen when a positive component of the pathway is removed (Dsh or Wg; see Figure 4 E). Wild-type embryos show the expected intermediate phenotype, as they have both active and inactive forms of Arm protein (see Figure 4 E). The observed shift is most likely the result of phosphorylation ( Peifer et al. 1994 a), though we do not address this directly in this study. The C-Terminus of Arm Is Necessary for Cby-Mediated Repression Although the missense mutations we have used in our studies produce (on average) weaker phenotypes, they are more effective at blocking the cell-fate transformation induced by Arm ΔArm than the “medium” C-terminal truncation mutants (compare Figure 1 K with Figure 5 C and 5 D). The comparison is somewhat indirect, owing to the necessity of expressing Arm S18 in the “medium” arm allele background in order to get intact embryos. However, we find that expression of Arm S18 in an arm F1a background has no visible effect on the cuticle (data not shown). Therefore, the activity of C-terminally truncated arm alleles in response to ΔArm expression suggests that, under certain conditions, removal of the C-terminus may actually enhance the transcriptional activity of Arm. One possibility is suggested by the recent discovery of Cby ( Takemaru et al. 2003 ), a nuclear negative regulator of the Wg pathway that binds to the C-terminus of Arm. To test whether nuclear Cby affected the transformation produced by Arm ΔArm , we used RNA interference (RNAi) to reduce Cby levels in arm F1a embryos with and without Arm ΔArm . In the absence of Arm ΔArm , i.e., in embryos where most Arm F1a protein is cytoplasmic, Cby RNAi has no effect ( Figure 6 D). However, when Arm ΔArm is present, lowering Cby levels leads to increased naked cuticle characteristic of Wnt pathway activation (compare Figure 6 B to 6 C). We propose that Cby's effect on arm F1a protein is dependent on Arm ΔArm relocalizing Arm to the nucleus. Figure 6 Relief of C-Terminal Repression through the Elimination of Cby Leads to Uniform Activation of Signaling (A) A wild-type cuticle shown for comparison. (B) Expression of Arm ΔArm in the arm F1a background. (C) Expression of a Cby RNAi construct along with Arm ΔArm in the arm F1a background. (D) Expression of a Cby RNAi construct in an arm F1a background. Discussion In this study we offer genetic proof that the nuclear localization of Arm is important for the activation of the pathway. The dissenting view ( Chan and Struhl 2002 ) relied on C-terminal truncations that we have shown retain their ability to signal if their levels are increased. These alleles also appear to bypass the normal nuclear regulation by Cby. We show that full-length loss-of-function forms of Arm provide a novel way of assessing the activity of the pathway. Finally, we show that in an approximate signaling-null condition, Arm ΔArm cannot activate transcription on its own. Based on these findings, we propose that membrane-tethered Arm, whether wild-type or activated, cannot activate transcription on its own. It does, however, have a profound effect on the endogenous form, forcing both “weak” and “medium” alleles to translocate to the nucleus and activate transcription. Our findings extend and build upon the original nuclear localization of Arm model ( Miller and Moon 1997 ; Cox et al. 1999 b). Further support for the nuclear localization of Arm model has recently been provided by the publication of a study that uses tissue culture experiments to show that nuclear localization of Arm is required ( Cong et al. 2003 ). Our results also point to an unexpected feature of Arm, namely that the C-terminus, although it has been shown to supply transcriptional activation ( Hsu et al. 1998 ), does not appear to be required for Wnt activation. Cox et al. (1999 a) studied this aspect of Arm function and found that a C-terminally truncated form of Arm can significantly rescue the signaling defects of arm mutants, but is not as good as the wild-type form at transcriptional activation. Further, given that arm mutant flies expressing the transgene that lacks the C-terminus do not survive to adulthood, the C-terminus may not be entirely expendable. This may point to the requirement for Cby-based repression or Teashirt-mediated activation at a later stage of development, as both these proteins function by binding the C-terminus of Arm ( Gallet et al. 1999 ; Takemaru et al. 2003 ). However, taken together with the finding that an N-terminally truncated Arm sent to the nucleus fails to activate transcription ( Chan and Struhl 2002 ), it appears that it is the N-terminus that is most important for the nuclear transactivation and chromatin remodeling functions ascribed to β-catenin ( Hsu et al. 1998 ; Hecht and Kemler 2000 ; Takemaru and Moon 2000 ; Barker et al. 2001 ; Tutter et al. 2001 ; Bienz and Clevers 2003 ). We have previously shown that the “medium” arm mutant ( arm O43A01 , which creates a stop codon eliminating repeats 10 through 12 and the entire C-terminus) does not signal in the presence of uniform Arm ΔArm ( Tolwinski and Wieschaus 2001 ). Chan and Struhl (2002 ) found that arm O43A01 embryos expressing high levels of Arm ΔArm from the paired GAL4 driver were able to activate Wnt targets. But since neither Arm ΔArm nor arm O43A01 can provide junctional Arm activity, the abnormalities of these embryos make these experiments difficult to interpret. As an alternative, we used a membrane-tethered but otherwise wild-type form of Arm (Arm S18 ), which we expressed in arm O43A01 mutant embryos (see Figure 1 G). The Arm S18 allele rescues the junctional defects, but does not allow signaling. Similar results have been obtained with another “medium” allele, arm XP33 ( Cox et al. 1999 b). However, when combined with Arm ΔArm and Arm S18 , arm O43A01 can now be clearly seen to activate naked cell fates. It thus appears that even the “medium” alleles of arm actually do retain some ability to function when Arm ΔArm is present. This is not observed in the larger truncations (“strong” alleles), consistent with the “medium” alleles retaining the TCF-binding region ( Graham et al. 2000 ). The question now becomes what is Arm ΔArm doing at the membrane that causes such drastic change in the signaling kinetics of the pathway. We have previously argued that Arm ΔArm may function by titrating the cytoplasmic anchoring activity of Axin and by therefore allowing rapid enrichment of Arm in the nucleus. We have in fact observed such an enrichment and have shown that it is counteracted by increasing the level of Axin ( Tolwinski and Wieschaus 2001 ). Further work has pointed to the importance of controlling Axin stability in pathway activation ( Salic et al. 2000 ; Mao et al. 2001 ; Lee et al. 2003 ; Tolwinski et al. 2003 ). Expression of large quantities of a stabilized, membrane-tethered form of Arm might also remove additional cytoplasmic inhibitory factors, preventing them from interacting with nontethered Arm. In turn, even lower-level or lower-activity alleles will now be able to activate transcription, simply owing to the complete lack of inhibiting factors. The missense mutations described here provide a glimpse of the in vivo activity of Arm protein. Structural studies of β-catenin found that although the central repeat region forms a uniformly repeating super helix, one α-helix was missing from repeat seven. The missing helix might allow a local flexibility in the structure and led the authors to define this region as a potential hinge ( Huber et al. 1997 ). Further crystallographic analysis concluded that this region was important for TCF binding ( Graham et al. 2000 ). Both our point mutations cluster around this repeat and would probably lead to structural consequences for this hinge. The apparent specificity of these alleles for the transcriptional response to Wnt signaling provides in vivo evidence that the postulated hinge may be very important for that aspect of Arm protein function. Note As the final version of this paper was being prepared, the paper by Chan and Struhl (2002 ) was retracted. Materials and Methods Fly Strains The wild-type strain used was Oregon R. See Flybase ( http://flybase.bio.indiana.edu ) for details on mutants used. Hypomorphic mutants of arm are as follows: arm LM134 TCC to TTC at nucleotide 2776, arm F1a CGC to CAC at nucleotide 2990, arm XM19 stop codon at nucleotide 3850, arm O43A01 stop codon at nucleotide 3404, arm XP33 stop codon at nucleotide 3466, arm XK22 stop codon at nucleotide 3013. Other alleles used were axin S044230 , zw3 M11–1 , dsh V26 , apc1 Q8 , apc2 d40 , and wg IG22 . Crosses and Expression of UAS Constructs arm mutants As Arm and many other Drosophila proteins are contributed maternally, to fully evaluate the function of a mutant protein, one needs to make embryos maternally and zygotically mutant. Therefore, maternally mutant eggs were generated by the dominant female sterile technique ( Chou and Perrimon 1992 ). For all expression experiments, the Arm–GAL4 driver was used. All X-chromosome mutants use FRT 101. The arm mutants used were as follows: arm F1a zw3 M11–1 (maternal)/Y (zygotic) arm LM134 zw3 M11–1 (maternal)/Y (zygotic) arm F1a (maternal)/Y (zygotic) arm LM134 (maternal)/Y (zygotic) arm F1a (maternal)/Y (zygotic); Arm–GAL4/UAS–ΔArm (zygotic) arm F1a zw3 M11–1 (maternal)/Y (zygotic); Arm–GAL4/UAS–ΔArm (zygotic) arm LM134 (maternal)/Y (zygotic); Arm–GAL4/UAS–ΔArm (zygotic) arm LM134 zw3 M11–1 (maternal)/Y (zygotic); Arm–GAL4/UAS–ΔArm (zygotic) arm O43A01 (maternal)/Y (zygotic) arm O43A01 (maternal)/Y (zygotic); Arm S18 (zygotic) arm F1a (maternal)/Y (zygotic); Arm–GAL4/UAS–WIZ–Cby, UAS–ΔArm (zygotic) arm F1a (maternal)/Y (zygotic); Arm–GAL4/UAS–WIZ–Cby (zygotic) arm XK22 (maternal)/Y (zygotic); Arm S18 (maternal) arm XK22 (maternal)/Y (zygotic); MAT–GAL4/UAS–ΔArm (zygotic); Arm S18 (maternal) UAS transgenes and GAL4 driver lines Previously published transgenes used were UAS–Arm*[S10], a small deletion of the phosphorylation sites ( Pai et al. 1996 ); the Arm–GAL4 driver ( Sanson et al. 1996 ); Arm S18 , a mirystoylated, membrane-tethered full-length Arm ( Cox et al. 1999 b); and UAS–WIZ–Cby for RNAi ( Takemaru et al. 2003 ). ΔArm is a pUAST transgene that deletes the first 128 amino acids, including the GSK3β and CKII phosphorylation sites, the CBP acetylation site, the α-catenin-binding domain, and a transactivation domain ( Zecca et al. 1996 ). Antibodies and Immunofluorescence Embryos were treated and stained as described previously ( Tolwinski and Wieschaus 2001 ), except that they were fixed with heptane/4% formaldehyde in phosphate buffer (0.1 M NaPO 4 [pH 7.4]). The antibodies used were anti-Arm (monoclonal antibody [mAb] N2 7A1; Developmental Studies Hybridoma Bank, University of Iowa, Iowa City, Iowa, United States), rabbit anti-Arm ( Peifer et al. 1994 b), rabbit anti-c-Myc (Santa Cruz Biotechnology, Santa Cruz, California, United States), and anti-Sexlethal (mAb M-14; Developmental Studies Hybridoma Bank). Staining, detection, and image processing were as described previously ( Tolwinski and Wieschaus 2001 ). Though not shown, the Sexlethal antibody was used to sex embryos. This allows for the identification of male embryos laid by germline clone mothers, which are hemizygous and therefore maternally and zygotically mutant for X-chromosome genes. Western Blotting Embryos were lysed in extract buffer (50 mM Tris [pH 7.5], 150 mM NaCl, 1% NP-40, 1 mM EDTA, 10% glycerol; Complete Mini Protease, Sigma, St. Louis, Missouri, United States), and the extracts were separated by 7.5% SDS-PAGE and were blotted as described elsewhere ( Peifer et al. 1994 a). Maternally and zygotically mutant embryos were hand-selected using standard GFP balancers ( http://flybase.bio.indiana.edu ). Supporting Information Accession Numbers The GenBank ( http://www.ncbi.nlm.nih.gov/Genbank/ ) accession numbers for the genes and alleles discussed in this paper are apc1 Q8 (U77947), apc2 d40 (AF091430), arm (X54468), axin S044230 (AF086811), dsh V26 (U02491), wg IG22 (NM 164746), and zw3 M11–1 (X54005).

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Cyclin A and cyclin D1 as significant prognostic markers in colorectal cancer patients

Background Colorectal cancer is a common cancer all over the world. Aberrations in the cell cycle checkpoints have been shown to be of prognostic significance in colorectal cancer. Methods The expression of cyclin D1 , cyclin A , histone H3 and Ki-67 was examined in 60 colorectal cancer cases for co-regulation and impact on overall survival using immunohistochemistry, southern blot and in situ hybridization techniques. Immunoreactivity was evaluated semi quantitatively by determining the staining index of the studied proteins. Results There was a significant correlation between cyclin D1 gene amplification and protein overexpression (concordance = 63.6%) and between Ki-67 and the other studied proteins. The staining index for Ki-67, cyclin A and D1 was higher in large, poorly differentiated tumors. The staining index of cyclin D1 was significantly higher in cases with deeply invasive tumors and nodal metastasis. Overexpression of cyclin A and D1 and amplification of cyclin D1 were associated with reduced overall survival. Multivariate analysis shows that cyclin D1 and A are two independent prognostic factors in colorectal cancer patients. Conclusions Loss of cell cycle checkpoints control is common in colorectal cancer. Cyclin A and D1 are superior independent indicators of poor prognosis in colorectal cancer patients. Therefore, they may help in predicting the clinical outcome of those patients on an individual basis and could be considered important therapeutic targets.

Background Colorectal cancer (CRC) is the third most common cancer in Western countries [ 1 ]. In Egypt, CRC has unique characteristics that differ from that reported in other countries of the western society. It was estimated that 35.6% of the Egyptian CRC cases are below 40 years of age and patients usually present with advanced stage, high grade tumors that carry more mutations [ 2 ]. This uniquely high proportion of early-onset CRC, the early and continuous exposure to hazardous environmental agents, the different mutational spectrum and the prevalent consanguinity in Egypt justify further studies [ 3 ]. It was proved that most cancers result from accumulation of genetic alterations involving certain groups of genes, the majority of which are cell cycle regulators that either stimulate or inhibit cell cycle progression [ 1 ]. Cell proliferation allows orderly progression through the cell cycle, which is governed by a number of proteins including cyclin s and cyclin dependent kinases [ 4 , 5 ]. The cyclin s belong to a superfamily of genes whose products complex with various cyclin -dependent kinases ( cdks ) to regulate transitions through key checkpoints of the cell cycle [ 6 ]. Abnormalities of several cyclins have been reported in different tumor types, implicating, in particular, cyclin A, cyclin E and cyclin D [ 6 , 7 ]. Cyclin D1 is a G1 cyclin that regulates the transition from G1 to S phase since its peak level and maximum activity are reached during the G1 phase of the cell cycle. Whereas cyclin A is regarded a regulator of the transition to mitosis since it reaches its maximum level during the S and G2 phases [ 8 ]. The mechanisms likely to activate the oncogenic properties of the cyclins include chromosomal translocations, gene amplification and aberrant protein overexpression [ 7 , 9 ]. Several studies have shown that, histone H3 mRNA expression can be used to identify the S phase fraction (SPF) through the in situ hybridization (ISH) technique [ 10 , 11 ]. The level of histone H3 mRNA reaches its peak during the S phase and then drops rapidly at the G2 phase [ 12 ]. In face of the increasing incidence of CRC and its peculiar pattern in the Egyptian population, the present study was conducted to assess the role of Ki-67 (pan-cell cycle marker), cyclin D1 (G1 phase marker), histone H3 mRNA (S phase marker), cyclin A (S to G2 phase marker) in CRC. The expression level of these markers was correlated to the clinicopathologic features and the overall survival of patients. Methods Tissue samples Paraffin-embedded tumor tissues were obtained from 60 CRC patients (47 colon and 13 rectal carcinomas) that were diagnosed and treated at the National Cancer Institute, Cairo, Egypt during the period from January, 1997 to June, 2002. Clinicopathological data of the studied cases are illustrated in table 1 . None of the patients received any chemotherapy or irradiation prior to surgery. Histological diagnosis of all cases was done by 2 independent pathologists according to the WHO Histological Classification. Tumors were staged according to the TNM staging system [ 13 ]. The depth of tumor invasion was classified as invasion of the mucosa including muscularis mucosa (m), invasion of the submucosa (sm), or invasion beyond the submucosa [ 8 ]. Normal colonic tissues were obtained from autopsy specimens (n = 20) and were used as a control. The actual survival rate of the patients was calculated from the date of resection to the date of death. Table 1 Clinicopathological features of patients in relation to the staining index (SI) of Ki-67 , cyclin D1 , cyclin A , histone H3 SI (mean + SD) Variables No. of cases Ki-67 Cyclin DI Cyclin A Histone H3 Sex Male 36 18.0 ± 6.4 6.7 ± 4.3 12.7 ± 5.7 10.7 ± 5.3 Female 24 20.1 ± 5.8 8.8 ± 8.4 10.0 ± 6.0 10.7 ± 5.4 Age (years) ≥50 41 11.7 ± 6.0* 5.6 ± 5.2 10.0 ± 5.3 6.0 ± 5.0* <50 19 23.8 ± 5.6 7.7 ± 6.8 13.6 ± 5.7 22.0 ± 5.2 Tumor size (cm) <5.0 33 12.2 ± 6.3* 5.3 ± 3.8* 11.5 ± 6.1* 10.3 ± 4.9* ≥5.0 27 30.1 ± 6.2 22.8 ± 7.2 28.6 ± 5.6 24.0 ± 5.6 Histology Normal 20 3.5 ± 2.0* 0.6 ± 0.2* 2.3 ± 1.1* 2.2 ± 0.9 Carcinoma 60 30.3 ± 6.2 24.9 ± 6.3 27.2 ± 5.8 10.7 ± 5.3 GI 15 11.7 ± 6.2 6.6 ± 4.0 10.0 ± 5.4 11.4 ± 4.9 GII 21 11.8 ± 5.6 8.9 ± 3.6 12.3 ± 6.5 7.8 ± 5.4 GIII 24 30.0 ± 4.3 22.0 ± 8.1 27.0 ± 4.9 11.5 ± 5.4 Lymph node Negative 33 19.5 ± 7.0 5.4 ± 5.3* 11.9 ± 6.5 12.3 ± 5.5 Positive 27 21.3 ± 4.9 20.6 ± 6.9 12.5 ± 5.0 14.2 ± 5.0 Depth of invasion m, sm 17 20.7 ± 6.7 3.1 ± 3.1* 11.9 ± 7.2 10.4 ± 5.1 beyond sm 43 21.9 ± 6.2 12.4 ± 6.5 12.2 ± 5.6 10.7 ± 5.4 Stage I 6 20.6 ± 6.7 5.7 ± 6.9 24.2 ± 6.9 11.1 ± 5.3 II 27 20.8 ± 6.9 5.3 ± 4.3 24.6 ± 6.0 10.4 ± 5.7 III 12 22.0 ± 5.4 7.7 ± 6.0 27.1 ± 5.2 10.4 ± 4.9 IV 15 24.7 ± 6.1 11.3 ± 9.6 27.5 ± 5.5 12.3 ± 6.2 * p. value < 0.05 (significant) Immunohistochemistry Four micron sections of each normal and tumor specimen were cut onto positive-charged slides; air dried overnight, de-paraffinized in xylene, hydrated through a series of graded alcohol and washed in distilled water and 0.01 PBS (pH 7.4). Slides were then processed for IHC as described by Handa et al. [ 8 ]. using the following antibodies: Ki-67 (MIB-1, Dako), cyclin A (6E6; Novocastra, Newcastle-Upon-Tyne, UK) and cyclin D1 (DCS-6, Dako). A case of invasive breast cancer was used as a positive control for Ki-67 and cyclin A whereas a case of mantle cell lymphoma was used as a control for cyclin D1 . Negative controls were obtained by replacing the primary antibody by non-immunized rabbit or mouse serum. Brown nuclear staining was regarded as a positive result for all studied markers. The proportion of positively-stained cells and the intensity of staining were scored in tumor and normal colorectal mucosal sections at medium power (×200). The degree of positive tumor staining (percentage of positive tumor cells in the examined section) was scored from 1–6 and the staining intensity was scored from 0–6 according to the pattern of staining in the examined section. Staining index (SI) was calculated by multiplying the cellularity and staining scores as described by King et al. [ 14 ]. In situ hybridization All tumor samples and 5 normal controls were assessed for histone H3 mRNA by ISH using the commercially available 550 base fluorescein-labeled DNA probe (Dako, Carpinteria, CA) as described by Nagao et al., 1996. This probe hybridizes to the whole mRNA transcript of the human histoneH3 gene including the5' and 3' un-translated regions. Scoring of histone H3 mRNA was performed as for immunohistochemistry, however, hybridization signals were detected in the cytoplasm. Molecular detection of cyclin D1 gene amplification High molecular weight DNA was extracted from paraffin-embedded tissues of the tumor and normal colorectal mucosal samples as previously described [ 15 ]. The proportion of neoplastic and normal cells was determined in each tumor sample by examining hematoxylin and eosin-stained slides obtained from the edge of the specimen used for DNA extraction. Tumor samples were evaluated for amplification of cyclin D1 if more than 75% of the examined sections were formed of neoplastic cells. Accordingly, 50 cases were eligible for the analysis. Ten micrograms of the extracted DNA was digested with Eco R1. DNA from selected cases was also digested with Bgl II and Hind III. Samples were separated on 0.8% agarose gels and transferred to Hybond-N membranes (Amersham Int., Amersham, UK). The membranes were hybridized with 50% formamide, 5 × SSC, 5 × Denhardt's, 500 μg/ml denatured salmon sperm DNA, 10% dextran sulphate and 10 6 cpm/ml of 32 P-labeled PRAD-1 probe for 24 h. Membranes were washed with 2 × SSC, 0.1% SDS at room temperature for 30 min followed by 2 × SSC, 0.1% SDS at 60°C for 30 min and 0.1 × SSC, 0.1% SDS at 60°C for 1 h. Filters were autoradiographed using an intensifying screen at -70°C for 24–72 h. After being stripped free of the PRAD-1 probe, the same blots were hybridized with 32 P-labeled B-actin probe to normalize against possible variations in the loading or transfer of DNA. The autoradiograms were analyzed using a densitometer. Intensities of PRAD-1/cyclin D1 were normalized to the β-actin control bands. The degree of amplification was calculated from these normalized values. Amplification was considered when the signal of the tumor band was ≥2-fold the value of the matched normal mucosa [ 16 ]. Statistical analysis The Mann-Whitney non-parametric test was used to compare the SIs of pairs of subjects whereas the Kruskal-wallis was used for categorial data. Correlation between indices was performed using a simple linear regression test. The Kaplan-Meier method was used to create survival curves which were analyzed by the log-rank test. The impact of different variables on survival was determined using the Cox proportional hazards model. p . values less than 0.05 were considered significant. Results The results of IHC are illustrated in figures 1 and 2 . In general, the staining index (SIs) of all studied markers was higher in carcinomas than in normal colonic mucosal samples ( p = 0.0001). Normal colorectal mucosa revealed positive imunostaining for Ki-67 in the lower half of the crypts only. A heterogeneous staining pattern was detected in the neoplastic cells of well and moderately-differentiated adenocarcinomas whereas a diffuse homogeneous staining pattern was detected in poorly-differentiated carcinomas. The SI ranged from 10–40.2 (mean: 24.6 ± 6.5). Figure 1 Normal colonic mucosa showing positive nuclear immunostaining for: (a) cyclin D1 , (b) ISH of histone H3 mRNA, (c) Ki-67 and (d) cyclin A Figure 2 A case of well differentiated adenocarcinoma with positive immunostaining for: (a) cyclin D1 , (b) histone H3 mRNA, (c) Ki-67 , and (d) cyclin A . Another case of moderately differentiated denocarcinoma with positive immunostaining for: (e) c yclin D1, (f) histone H3 mRNA, (g) Ki-67 , and (h) cyclin A . A case of poorly differentiated adenocarcinoma with diffuse staining for: (i) cyclin D1 , (j) ISH of histone H3 mRNA, (k) Ki-67 and (l) cyclin A . Immunostaining for cyclin D1 was predominantly nuclear but cytoplasmic staining was detected in some cases. However, unless a nuclear staining was also detected, cases with cytoplasmic staining were considered negative. Normal colorectal mucosal samples were almost negative for cyclin D1 whereas 41 out of the 60 (68.3%) CRC cases were positive. Marked heterogeneity was observed in well- and moderately-differentiated adenocarcinomas even within the same tumor. Poorly-differentiated carcinomas revealed a diffuse staining pattern with more darkly-stained nuclei. The SI ranged from 0.5–28.6 (mean: 9.3 ± 4.2). Positive nuclear staining for cyclin A was detected in 80% (48/60) of CRC cases and in all non-neoplastic control samples. Positively-stained nuclei were confined to the lower half of the crypts in normal colonic mucosa and diffusely-dispersed in carcinomas. The SI ranged from 3.3–30.2 (mean: 15.1 ± 6.6). Histone H3 mRNA was intensely expressed in the cytoplasm of all examined samples either neoplastic or non-neoplastic. The distribution of histone H3 mRNA was similar to that of cyclin A and Ki-67 however, the proportion of histone H3 mRNA positive cells was less than that of Ki-67 . The SI ranged from 1.8–24.2 (mean: 12.4 ± 5.3). The PRAD-1 probe detected 3 Eco RI fragments of 4.0, 2.2 and 2.0 and 1 Bgl II fragment of 15 Kb. PRAD-1/cyclin D1 gene amplification was detected in 22/50 (44%) cases analyzed. The degree of amplification was heterogeneous with 2–10 fold increase when compared to normal mucosal samples (Figure 3 ). Amplification was confirmed by other restriction enzymes. Figure 3 A: Southern blot analysis of normal mucosa (N) and their seven corresponding cases of colonic adenocarcinomas (T1–T7), cases No. 1, 2, 4, and 5 are poorly differentiated whereas cases No. 3, 6, and 7 are moderately differentiated. Genomic DNA was digested with Bgl II, fractionated by electrophoresis in agarose gel, transferred onto membranes and hybridized with PRAD1 and β-actin . Tumors number 1–6 (Lanes 1–6) show different degrees of PRAD1/cyclin D1 amplification, tumor number 7 (lane 7) was not amplified. B : Southern blot analysis of 3 cases of adenocarcinomas (T) and matched normal colonic mucosa (N). Genomic DNA was digested with Eco RI, fractionated by electrophoresis in agarose gel, transferred onto membranes and hybridized with PRAD1 and β-actin probes for loading control. The identification of the 3 tumors is the same as in Fig. 3A with amplification of PRAD1/cyclin D1 in tumors number 4, 5 (Lanes 1, 2) but not 7 (Lane 3). Correlations There was a significant correlation between cyclin D1 gene amplification and protein overexpression. Out of the 22 cases that showed amplification 14 showed protein overexpression (concordance = 63.6%). Linear regression analysis of SIs revealed a significant correlation between Ki-67 and cyclin D1, cyclin A, histone H3 as well as between the SIs of cyclin A and histone H3 ( p = 0.008, 0.0001, and 0.0001 respectively) (Figure 4 ). There was a significant relationship between the SI of both Ki-67 and cyclin A and the degree of differentiation of tumors as well as the size of the tumor ( p < 0.001 and p < 0.01 respectively). In addition, SI of Ki-67 and histone H3 were higher in patients <50 years than in those ≥50 years ( p < 0.05) (table 1 ). Figure 4 Correlation between the staining intensity of (a) Ki-67 vs. cyclin D1 , (b) Ki-67 vs. histone H3 , (c) Ki-67 vs. cyclin A and (d) cyclin A vs. histone H3 mRNA expression. In addition table 2 shows a significant relationship between high cyclin D1 SI and large, poorly-differentiated tumors, carcinomas with positive lymph node metastasis and deeply-invasive carcinomas ( p < 0.05, p < 0.001, p < 0.05 and p < 0.05 respectively). Whereas cyclin D1 gene amplification was significantly associated with an advanced disease stage since amplification was detected in 10/15 (66.7%) of stage IV tumors compared to 12/45 (26.7%) of stage I-III tumors ( p = 0.002). Similarly, DNA amplification was detected in 60.5% (26/43) of the carcinomas with extensive local invasion (beyond sm) but only in 23.5% (4/17) of the carcinomas with limited invasion (m, sm) ( p = 0.001). A significant correlation was also present between cyclin D1 gene amplification and the presence of lymph node metastasis ( p = 0.008) as well as between the SI of histone H3 , the size of the tumor and the patient's age ( p < 0.05, p < 0.001 respectively). The SI was higher in tumors >5 cm in diameter and in patients <50 years. Table 2 The relation between cyclin D1 overexpression vs cyclin D1 amplification and clinicopathological prognostic markers. Variables No. of cases Cyclin DI overexpression Cyclin D1 Amplification Tumor size (cm) <5.0 33 5.3 ± 3.8* 13/33 ≥5.0 27 22.8 ± 7.2 p < 0.05 9/27 p < 0.236 Histology GI 15 6.6 ± 4.0 7/15 GII 21 8.9 ± 3.6 8/21 GIII 24 22.0 ± 8.1 p < 0.001 7/24 p < 0.075 Lymph node Negative 33 5.4 ± 5.3* 6/33 (18.2%) Positive 27 20.6 ± 6.9 p < 0.05 16/27 (59.3%) p < 0.008 Depth of invasion m, sm 17 3.1 ± 3.1* 4/17 (23.5%) beyond sm 43 12.4 ± 6.5 p < 0.05 26/43 (60.5%) p < 0.001 Stage early 45 5.5 ± 10.1 12/45 (26.7%) late 15 11.3 ± 9.6 P = 0.175 10/15 (66.7%) p < 0.002 Survival analysis The mean follow-up period for all patients was 30 months (range: 1–66 months). Eighteen of 60 patients had already died by the time the study was completed. We defined the cutoff level for overexpression of each cell cycle marker at the point that showed the maximum difference of survival rate between the 2 groups separated by that point. Cox regression analysis revealed that cyclin A overexpression (our definition: SI ≥ 10.5), cyclin D1 overexpression (our definition: SI ≥ 6.1), poorly differentiated histology, lymph node metastasis, TNM stage, tumor size and depth of invasion were all significant prognostic variables for survival (Table 3 ). The Kaplan-Meier survival curves for the subgroups of patients who are subdivided according to each marker's status are shown in Figure 5 . Patient with tumors that showed Ki-67 overexpression (our definition: SI ≥ 11.5) and histone H3 overexpression (our definition: SI ≥ 8.2) tended to have poor prognosis but this did not reach a statistically significant level, however the overall survival was significantly lower in patient with cyclin A and cyclin D1 overexpression. Cox multivariate regression analysis revealed that lymph node metastasis, cyclin A and cyclin D1 overexpression were independent negative prognostic factors after adjustment for the depth of tumor invasion, age and sex of the patient (Table 4 ). Table 3 Uunivariate analysis of the relationship between survival and the tested markers PredictiveVariables Median Survival HR CI P Ki-67 <11.5 36 ≥11.5 32 1.826 0.636 – 5.243 0.26 Cyclin D1 <6.1 35 ≥6.1 18 7.246 1.007 – 45.150 0.03* Histone H3 <8.2 35 ≥8.2 29 4.639 0.854 – 25.196 0.07 Cyclin A <10.5 35 ≥10.5 15 7.820 1.017 – 60.122 0.02* Histological grade Low 38 High 10 7.331 2.696 – 19.940 0.0001* Lymph node Negative 38 Positive 15 6.826 1.973 – 23.621 0.002* Stage I, II, III 38 IV 12 6.378 1.842 – 22.083 0.001* Tumor size (cm) <5.0 35 ≥5.0 13 4.835 1.386 – 16.868 0.01* Depth of invasion T1, T2 36 T3, T4 20 7.759 1.024 – 58.789 0.04* Age (years) <50 38 ≥50 28 2.802 0.988 – 7.943 0.0526 Sex Male 38 Female 36 0.696 00.274 – 1.766 0.4449 * p. value < 0.05 (significant) HR: Hazard Ratio CI: 95% confidence Interval Figure 5 Kaplan-Meier survival curves for colorectal carcinoma. Overall survival is significantly lower in patients with (a) cyclin A and (b) cyclin D1 overexpression. Patients with high SI for histone H3 mRNA have poorer prognosis but this was not statistically significant (c). No significant difference was present between patients with high Ki-67 SI and those with low Ki-67 SI (d). Table 4 Multivariate analysis ofthe relationship between survival and thetested markers PredictiveVariables HR CI P Cyclin D1 10.864 1.055 – 86.250 0.03* (baseline < 6.1) - - - Cyclin A 13.886 1.012 – 190.579 0.0490* (baseline < 10.5) - - - Positive Lymph node metastasis 3.921 1.057 – 14.472 0.0410* Stage IV 3.411 1.048 – 12.083 0.03* Depth of invasion T3, T4 5.408 0.449 – 65.080 0.1836 Age (years) ≥50 1.996 0.678 – 5.878 0.2310 Sex 0.910 0.315 – 2.358 0.8453 p. value < 0.05 (significant) HR: Hazard Ratio CI: 95% confidence Interval Discussion The proliferative activity of CRC cells has been investigated in several studies either by immunohistochemical determination of cell proliferation index using antibodies to some types of cyclins or by flowcytometric determination of the SPF of the cell cycle [ 8 ]. Although Leach et al. [ 17 ] did not find cyclin D1 gene amplification in a panel of 47 CRC cell lines; its protein was overexpressed in about 30% of CRC cases that were included in the studies of Bartakova et al. [ 6 ] and Arber et al. [ 18 ]. In the former study [ 6 ] cyclin D1 was aberrantly accumulated in a significant subset of human CRC cases and the cell lines derived from these cases were dependent on cyclin in their cell cycle progression. In the second study [ 18 ], overexpression of cyclin D1 was detected in 30% of adenomatous polyps indicating that overexpression is a relatively early event in colon carcinogenesis which is possibly responsible for the pathological changes in the mucosa preceding neoplastic transformation. More recently, Holland et al. [ 19 ], Pasz-Walczak et al. [ 20 ] and Utsunomiya et al. [ 21 ] reported up-regulation of cyclin D1 in 58.7%, 100% and 43% of their studied cases respectively. In the present study, up-regulation of cyclin D1 was detected in 68.3% of the cases. The SI was significantly higher in carcinomas than in normal colorectal mucosa and in poorly-differentiated adenocarcinomas it was approximately twice that of other histological types. Amplification and/or overexpression of cyclin D1 significantly correlated with deeply invasive tumors and positive lymph node metastasis. Our results in this regards are consistent with previous studies [ 8 , 22 ]. In 2001, Holland et al. [ 19 ]. demonstrated that deregulation of cyclin D1 and p21 waf proteins are important in colorectal tumorigenesis and have implications for patient prognosis. Similarly McKay et al. [ 23 ] found that cyclin D1 was the only protein in their panel ( cyclin D1, p53, p16, Rb-1, PCNA and p27 ) that correlated with improved outcome in CRC patients. However, few studies failed to detect any correlation between cyclin D1 overexpression and the clinicopathological factors in CRC [ 6 , 18 ]. This controversy in results could partially be explained by the difference in the sampling of studied cases. The present study included 24 cases of poorly differentiated adenocarcinoma, which is not common in other studies of CRC in western countries. This was possible because the majority of CRC cases diagnosed in Egypt are of high histological grade [ 3 ]. The correlation between cyclin D1 overexpression and the high histological grade was also reported in other tumor types including non-small cell lung carcinomas [ 24 ] and squamous cell carcinomas of the larynx [ 16 ]. Another possible explanation for the observed controversy in the results of different studies is the detection method used. In the present work, overexpression of cyclin D1 was more common than gene amplification of the PRAD-1/cyclin D1 gene with a 63.6% concordance. This was similarly reported by Bartakova et al. [ 6 ] who mentioned that there is a subset of CRC cases in which cyclin D1 is overexpressed without PRAD-1/cyclin D1 gene amplification. Consistent with this hypothesis are reports of elevated cyclin D1 mRNA levels and immunohistochemically detectable accumulation of the protein in over one third of breast cancer cases at a frequency significantly higher than that deduced from DNA amplification studies [ 9 , 25 ]. These data imply that mechanisms other than gene amplification can also lead to deregulation and accumulation of cyclin D1 in solid tumors. So far, several studies were done to reveal the prognostic significance of cyclin D1 overexpression in various carcinomas, including CRC [ 22 ]. However, these studies yielded conflicting results which could be attributed to organ heterogeneity. In our study, patients with tumors that exhibited cyclin D1 overexpression tended to have poor prognosis. It was reported that, patients with cyclin A positive carcinomas had significantly shorter median survival times. Handa et al. [ 8 ] were able to detect cyclin A overexpression in 77% of their CRC cases. They also demonstrated that, cylcin A could be used as a prognostic factor of CRC. More recently, Habermann et al. [ 26 ] studied cases of ulcerative colitis with and without an associated adenocarcinoma for the presence of cyclin A overexpression. They found that, cyclin A overexpression was higher in cases of ulcerative colitis with adenocarcinomas than in those without adenocarcinomas. Consequently, they concluded that, cyclin A could be used for monitoring ulcerative colitis patients and for the early detection of an emerging carcinoma in this high risk group of patients. In our study, cyclin A was detected in 80% of the patients and Cox regression analysis showed that it could be used as a prognostic marker in CRC in addition to cyclin D1 . It would have been useful if we assessed the expression level of cyclin A by another technique (DNA amplification). This would have added more information regarding the gene status on one hand and confirmed the results of IHC on the other hand. Unfortunately, this was not possible because in most of the cases included in the present work, the extracted DNA was not sufficient to study cyclin amplification after the assessment of cyclin D1 . In 1996, Nagao et al. [ 11 ] reported that histone H3 labeling index significantly correlated with ki-67 immunostaining and was high in poorly differentiated human hepatocellular carcinoma. This was similarly reported in the present work since we found a significant correlation between the SI of histone H3 and Ki-67 . However, no statistically significant correlation was found between histone H3 SI and any of the studied clinicopathological factors. Although Ki-67 immunostaining reflects the proliferative activity of CRC, it has not been recognized as a significant prognostic factor in this type of tumors [ 27 , 28 ]. However, Suzuki at al. [ 29 ] found a significant correlation between Ki-67 labeling index and local invasion of CRC. In the present study there was a significant relationship between the SI of Ki-67 , tumor size and grade. However, Kaplan-Meier survival curves showed no significant difference in survival rates between patients with- and without overexpression of Ki-67 . Conclusions Our results demonstrate that cyclin D1, cyclin A, histone H3 and Ki-67 are overexpressed in a subset of CRC, however only cyclin D1 and cyclin A overexpression correlates with poor differentiation and tumor progression. This indicates the superiority of cyclin A and cyclin D1 as indicators of poor prognosis compared to Ki-67 and histone H3 mRNA in CRC. Cyclin A and D1 could therefore be considered significant, independent prognostic factors in CRC patients. These findings are especially important in stage II patients since 25–30% of those patients have poor prognosis in spite of being node-negative. However, the standard clinicopathologic prognostic factors can not identify this subset accurately and therefore; there is a great demand for more accurate, individually-based, biological prognostic parameters that help in detecting this high risk group of patients who can benefit from an adjuvant therapy. If the findings of the present study are confirmed in a larger study, evaluation of cyclin A and D1 may be applicable to clinical management of CRC, allowing the identification of patients with poor prognosis. Competing interests The author(s) declare that they have no competing interests. List of abbreviations CRC – Colorectal cancer OS – overall survival SI – staining index SPF – S phase fraction ISH – in situ hybridization m – muscularis mucosa sm – invasion of the sub mucosa Authors' contributions BA and ZA-R carried out the molecular genetic studies, designed, coordinated the study and drafted the manuscript. BA and El-HS carried out all the histopathological and immunohistochemical studies. El-SA participated in molecular genetic studies and drafted the manuscript. MM coordinated the study. El-SM carried out all the patient clinical data. 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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Trade and Health: Is the Health Community Ready for Action?

There are greater tensions than ever before between promoting trade and protecting health. Human health could lose out to trade liberalization unless the health community fights its case

Trade is the lifeblood of all commerce. The exchange of goods and services has played a defining role in human history, creating vast empires, encouraging mass migration, and sometimes tipping the balance between peace and conflict. It is thus unsurprising that protecting and encouraging international trade has remained a top priority for governments, businesses and international organisations. Historically, the protection of health has been a permitted reason for restricting trade. Trade brought plague to Athens in 430 BC, killing as much as one third of the population, as well as to fourteenth century Europe after which quarantine practices were introduced. During the nineteenth century, flourishing trade also facilitated the spread of diseases such as cholera. This prompted a series of International Sanitary Conferences among leading trading nations, and the adoption of International Sanitary Conventions (forerunners of the present day International Health Regulations). While protecting health was a clear aim, in reality the primary task was to minimise interference by health matters on trade. Today, there are greater tensions than ever before between promoting trade and protecting health because of globalisation. Successive rounds of trade negotiations held since the Second World War, under the General Agreement on Trade and Tariffs and, since 1995, the World Trade Organization (WTO), have substantially reduced tariff levels and standardised trading practices across countries. This process of trade liberalisation has significantly increased trade volumes, bringing more and more countries into the world trading system. For the public health community, trade has raced ahead of corresponding measures to protect health. Efforts to ensure that there is an appropriate balance between the two policy areas has become a difficult challenge. Tensions between Trade and Health The right to restrict trade to protect the health of humans, animals, and plants is recognised by the General Agreement on Trade and Tariffs (Article XX) under two conditions: (1) the restriction is applied in a nondiscriminatory way; and (2) the restriction is based on recognised scientific evidence. Countries are allowed to restrict trade, for example, of certain goods such as radioactive waste or infected food products. Disputes can arise if the restriction is believed to be discriminatory or there is disagreement about the scientific evidence supporting it (see sidebar). The ban introduced by the European Community in 1989 on hormone-treated beef imported from the US. led to two rulings by the Dispute Settlement Body of the WTO in favour of the American government. The assessment of the evidence primarily by trade experts, rather than public health experts, is a clear problem of the existing dispute settlement process. The process also makes it difficult to regulate inappropriate production methods which do not lead to problems in the end product but may be of public health concern. For example, the practice of using hormones to boost meat production may prove problematic in future research, even if residues in the meat are not judged high enough at present to warrant sufficient proof of health concerns. Moreover, tight regulations on trade that are intended to protect health can come under fire from the trade lobby. Two World Bank studies argue, for instance, that European Union (EU) regulations on pesticides in bananas, as well as aflatoxins, could be interpreted as barriers to trade and market access [ 1 , 2 ]. The short shrift given to precautionary measures to protect health, where existing scientific evidence is deemed insufficient, reflects a further inbuilt priority given to trade. Growing concerns over the development and use of genetically modified organisms (GMOs), for example, have been dismissed by major companies such as Monsanto and Cargill on the basis of a lack of existing scientific evidence of harm to health. Consumer groups and public health advocates, however, argue that the subject is still in its scientific infancy. Where new causal pathways or systemic impacts of environmental exposures are of concern, such as with GMOs, at best one can say that the jury is still “out”. Hence, allowing GMOs to be spread widely, rather than taking precautionary measures, could prove to have irreversible consequences. There is a fine balance between protecting patents and ensuring access to essential drugs in the developing world (Illustration: Margaret Shear) The classification of certain goods as a risk to health, and thus subject to trade restrictions, is also a source of dispute. The best example is tobacco products which manufacturers argue should be treated like other traded goods. Public health advocates, however, argue that because tobacco is harmful to health, it should be subject to special restrictions. A battle over tobacco is currently being played out in regional trade negotiations and will be raised at forthcoming multilateral negotiations over agricultural trade. Whether the public health community will be able to argue successfully to protect health, when pitted against the vast resources of a multi-billion dollar industry, remains to be seen. The TRIPs Agreement Two new sources of tension have arisen in recent years—intellectual property rights (IPRs) and trade in services. The protection of IPRs is a new feature of international trade law, coming into force under the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS) adopted in 1994. The agreement sets out minimum standards for protecting and enforcing patents, trademarks, and copyrights. Since the mid-1990s there has been increasing concern over access to drugs in the developing world, and especially drugs for treating HIV/AIDS. This issue gained international attention when the South African government sought to access cheaper versions of patent protected drugs, but was faced with strong opposition by the pharmaceutical industry. The importance of public health priorities, and the existence of flexibility within TRIPS, was eventually confirmed in the Doha Declaration on the TRIPS Agreement and Public Health signed in 2001 [3] . The agreement allows for “compulsory licensing”, which means that local manufacturers in poor countries are allowed to make cheap versions of patented drugs during public health emergencies, provided that they give a royalty payment to the patent holder. Nonetheless, IPRs protection has remained a problem given continued disagreement by the US over which diseases and countries are covered under the declaration. The capacity to protect IPRs has also been enhanced by the shift towards bilateral trade negotiations as a result of the breakdown in multilateral negotiations under the WTO. While international debates over TRIPS have so far focused on the developing world, it is clear that there are issues relevant to the public health community as a whole concerning open access to a wide range of health-related knowledge and information. The possible benefits and costs of the TRIPS agreement had not been openly discussed beforehand. Rather, its measures were heavily influenced by industries seeking to exert ownership over intellectual goods such as research, information, and other data sources. Within an increasingly competitive world market, companies are driven to recoup their investment in such resources through IPRs. For the public health community, however, there is a vital need for affordable and open access by all to such resources. Leaving the commercial market to drive research and development (R&D) can lead not only to problems of access in developing countries but it can also lead to the neglect of research and public health priorities in all countries, such as research on antibiotics, which has been deemed insufficiently profitable [4] . Concern over the impact of intellectual property rights and marketing monopolies on overall pharmaceutical policies, pricing and R&D of pharmaceuticals has also led to proposals for a new trade framework for global health care R&D efforts [5] . Trade in Health Services The General Agreement on Trade in Services (GATS) is another expanded area of trade law. Services are the fastest-growing segment of the world economy, providing more than sixty percent of global output and employment. In the past, most services were not considered to be tradable across borders. Advances in communications technology, including the rise of e-commerce, and regulatory changes have made it easier to deliver services across borders. For trade in health services, the implications are not yet clear. It is generally expected that GATS would not apply to public services due to a general exemption on the matter. However, this exclusion is very narrowly worded, and based on a model of public services which may no longer hold. Health sector reforms have changed the ways in which publicly financed services are provided in many countries, including the extensive use of contracting out and managed competition. In most countries, this includes both medical care and related services such as laboratory or ambulance services. Health services, which are contracted out to the non-profit or for-profit sector, are likely to be no longer considered purely “public” and thus protected by the exclusion. Recent legal reviews of the GATS [ 6 , 7 ] confirm this concern, describing how the agreement would apply to any health-related service supplied on a “commercial” basis. Whether paid for directly by the patient or through a social security fund, the expectation that GATS negotiations will not apply to public services may no longer hold. Given this, the two reviews warn that there are valid grounds to suggest that negotiations on trade in services, and full commitments in health services in GATS, will have important implications for the ways in which national health systems and policies are implemented. While GATS may not directly limit the aims of national health policies, commitments under GATS can influence the ability of governments to implement health policies and regulate commercial service providers. This could apply especially to efforts to introduce new regulations that restrict market forces. The current GATS negotiations on domestic regulation include requirements of least trade restrictiveness and necessity tests for introducing regulatory measures in committed sectors. These requirements could pose difficulties if a government sought, for example, to oblige hospitals to operate on a non-profit basis. This might be interpreted under the GATS as restricting market forces. In this way, GATS could effectively influence the scope of national health policy, even challenging the capacity of governments to pursue health policies that prioritise universal access, cost containment, and quality control. Challenges to the Health Community As world trade continues to expand in scale and scope, the health community faces a number of key challenges. We must be armed with a better understanding of the world trading system, notably the legal framework for international trade. Comprehending the potential health implications of various bilateral, regional, and multilateral agreements regulating trade today is a daunting task. Although the public health community has fewer resources at its disposal than the proponents of trade liberalisation, it is clear that health priorities do have strong support by citizens all over the world. It is critically important for the health community to challenge the value-based assumption that trade liberalisation, rather than human welfare, should be given automatic priority. Indeed, ignoring health can lead to problems in the trade sphere. The outbreaks of bovine spongiform encephalopathy in Europe and North America and severe acute respiratory syndrome in Asia emphasised that trade can be severely disrupted by insufficient measures to protect health. The health community has to press for a much louder voice in the setting of trade policy at the national and international levels. A balance between trade and health policies can only be achieved if the health community is prepared to be far more vocal, and the trade policy community is prepared to listen. Recent Disputes between Trade and Health Growth-Promoting Hormones In 1998 WTO ruled that a European Community ban of the use of certain growth-promoting hormones was not based on an appropriate risk assessment. Rather than lift the ban, the EU sought new evidence of the risk to human health of hormone residues in meat products. In 1999 Canada and the US imposed trade sanctions worth US$116.8 million and Cdn$11.3 million. In 2003 the EU announced that, based on new scientific evidence, the ban will remain in place and asked the US and Canada to lift sanctions. Chrysotile Asbestos In 2001 WTO ruled that the European Community was permitted to ban the import of chrysotile asbestos on the grounds of protecting public health, and rejected the Canadian government's claim that the ban was discriminatory and an unnecessary barrier to trade. While the decision shows that WTO panel decisions can prioritise health, the process and grounds of the decision indicates that, even with such a well-established carcinogen, the dispute settlement process required extensive argument by the public health community.

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544876

The exceptionally high rate of spontaneous mutations in the polymerase delta proofreading exonuclease-deficient Saccharomyces cerevisiae strain starved for adenine

Background Mutagenesis induced in the yeast Saccharomyces cerevisiae by starvation for nutrilites is a well-documented phenomenon of an unknown mechanism. We have previously shown that the polymerase delta proofreading activity controls spontaneous mutagenesis in cells starved for histidine. To obtain further information, we compared the effect of adenine starvation on mutagenesis in wild-type cells and, in cells lacking the proofreading activity of polymerase delta (phenotype Exo - , mutation pol3-01 ). Results Ade + revertants accumulated at a very high rate on adenine-free plates so that their frequency on day 16 after plating was 1.5 × 10 -4 for wild-type and 1.0 × 10 -2 for the Exo - strain. In the Exo - strain, all revertants arising under adenine starvation are suppressors of the original mutation, most possessed additional nutritional requirements, and 50% of them were temperature sensitive. Conclusions Adenine starvation is highly mutagenic in yeast. The deficiency in the polymerase delta proofreading activity in strains with the pol3-01 mutation leads to a further 66-fold increase of the rate of mutations. Our data suggest that adenine starvation induces genome-wide hyper-mutagenesis in the Exo - strain.

Background Mutagenesis in stationary-phase cells has attracted much attention recently. Historically, most studies on spontaneous mutation rates in bacteria and unicellular eukaryotes were conducted in exponentially growing cells, even though it was well known that bacteria and yeast, in their natural habitat, spend most of the time in the stationary phase [ 1 , 2 ]. There were relatively few papers about the accumulation of spontaneous mutations in non-dividing or poorly dividing cells [ 3 ] until the publication of the Cairns' paper "The Origin of Mutants" [ 4 ]. The paper showed that mutations can arise in a non-growing bacterial population and also suggested their adaptive nature. Since then, the parameters of spontaneous mutagenesis in unicellular organisms under conditions of limited growth have been examined in numerous studies [ 5 , 6 ]. Starvation for amino acids and bases has been used largely because of the relative ease of studying reversions of nutritional markers in both bacteria and yeast [ 4 , 7 - 9 ]. We previously reported that the replicative DNA polymerases δ and ε are involved in the control of mutability in non-dividing yeast cells. We have shown that strains with the mutational inactivation of proofreading exonucleases ( pol3-01 and pol2-4 mutations, correspondingly) retained their mutator phenotypes, compared to each other and to the wild-type strains, upon histidine starvation [ 10 ]. This result was consistent with the earlier studies of the effect of the cdc2-1 mutation, allele of the POL3 [ 11 ]. We studied the effect of adenine starvation on the reversion of an auxotrophic strain carrying the ade5-1 allele. We show that adenine starvation induced a high level of reversion. The effect was further elevated 66 fold in the pol3-01 mutator strain, de3-01-CG. In addition to reversions, additional mutations throughout the genome were induced. The latter was suggested by the fact that most Ade + revertants were also auxotrophic for additional nutritional requirements and 50% of them were temperature-sensitive. These data suggested that reversions to prototrophy in the strain de3-01-CG, under adenine deprivation, are not adaptive, as was observed for histidine starvation [ 12 ]. We propose that adenine starvation of strains auxotrophic for this nutrient leads to perturbations of replication and/or DNA repair synthesis (for example, nucleotide pool deprivation or imbalances, which results in high rates of mutagenesis). The proofreading exonuclease activity of polymerase δ is an important factor that protects resting cells from this mutagenesis. Results Ade + revertants rates in the strains CG379-3-29(LR) and in de3-01-CG First, we tested the effect of adenine starvation on reversion rates in a Hall's experiment [ 8 ], as we did in a previous study on histidine starvation [ 10 , 12 ]. The rate of accumulation of Ade + revertants on SD medium with limited amount of adenine was high: all colonies of the wild-type strain CG379-3-29(LR) on day 11, and its pol3-01 derivative with defect in proofreading by polymerase δ (strain de3-01-CG) on day 7, had one or more papillae, thus making it impossible to estimate the reversion rate. Therefore, we used the medium without any adenine (see "Methods"). High reversion rates were observed again, but an estimation of the mutation rate was now possible. Ade + revertants begun to appear on SDNA-ade plates on day 9 and on day 6 for the strains CG379-3-29(LR) and de3-01-CG, respectively, and continued to accumulate up to the end of the experiment (Figure 1 ). The cumulative reversion rate on day 16 was 1.5 × 10 -4 for CG379-3-29(LR) and 1.0 × 10 -2 for de3-01-CG. The presented reversion frequencies are the total number of Ade + revertants at the end of the experiment per cells plated (not per survived cells). There are several reasons why we did the calculations in this way. We do not know exactly when the mutational event occurred since the Ade + revertants growth rates were somewhat different (see below); we did not know the exact number of viable cells, due to ongoing residual divisions and cell death. In the latter respect, the strains CG379-3-29(LR) and de3-01-CG behaved very differently. The de3-01-CG cells stopped dividing on day 3 after plating and began to die. The strain CG379-3-29(LR) continued to multiply slowly and its survival was higher than survival of the de3-01-CG strain. These two parameters are documented in Figure 2 (dependence of number of cells on days of incubation) and in Figure 3 (cell viability versus time of incubation). Figure 1 Accumulation of Ade + revertants in the strains CG379-3-29 (LR) and de3-01-CG during starvation on SDNA-ade plates The revertant rate for the strains CG379-3-29 (LR) (squares ■) and de3-01-CG (triangles ▲) is given as the total number of revertant colonies per plated cell. The mean values from 3 independent experiments are reported on a logarithmic scale (Y axis). Vertical bars represent the standard errors of the mean. Figure 2 Number of cells/unit on SDNA-ade in the strains CG379-3-29(LR) and de3-01-CG The number of cells per unit was counted at the microscope (400×) in order to estimate the post-plating cellular divisions on SDNA-ade in the strains CG379-3-29 (LR) (squares ■) and de3-01-CG (triangles ▲). Figure 3 Cell viability in the strains CG379-3-29 (LR) and de3-01-CG during starvation on adenine-free plates The squares (■) represent values for CG379-3-29 (LR), while the triangles (▲) are values for de3-01-CG. The mean values from three independent experiments are reported. The vertical bars correspond to the standard errors of the mean. The differences in the growth rate among Ade + revertants made the estimation of the exact reversion rates in the logarithmic growth phase almost impossible. In one fluctuation test where 50 independent cultures of the de3-01-CG strain were analysed, we observed that the variability coefficient (σ × 100/X; where σ is the deviance and X is the mean) drastically dropped on day three. This suggests that the majority of Ade + revertants that arose during the logarithmic growth phase were able to give visible colonies by day 2. Therefore, we decided to calculate an approximate reversion rate on day 2 by the P 0 method and obtained a reversion rate of 2.0 × 10 -7 , 4.5 orders of magnitude lower than the rate calculated on day 16 (see Figure 1 ). It was more difficult to determine the exact reversion rate in the logarithmic phase of growth for the CG379-3-29(LR) strain. Since the strain is not a spontaneous mutator, a very high number of cells had to be plated on SDNA-ade dishes to get reliable estimates. In a fluctuation experiment with 10 7 cells/dish, we did not observe any Ade + revertant colonies out of 50 independent cultures after two days of incubation at 28°C, implying a reversion rate lower than 2.0 × 10 -9 . Therefore, in this wild-type strain, starvation for adenine likely induced an accumulation of Ade + revertants at a level that is several orders of magnitude higher than in standard growth conditions. Molecular and growth characteristics of Ade + revertants We compared the ade5-1 sequence from the CG379-3-29(LR) strain with the sequence of the ADE5,7 gene in SGD and found complete identity except for a C to A transversion at position 1158 (amino acid position 386). This transversion introduced the TAA ochre codon instead of the TAC tyrosine codon, generating a nonsense mutation. DNA sequencing of the ade5-1 allele in 19 Ade + revertants of the de3-01-CG strain isolated on day 14 showed that they were all suppressors. Among 17 independent Ade + clones isolated on day 2 of a fluctuation experiment with the de3-01-CG (logarithmic cultures) strain, 6 were locus revertants and the rest were suppressors. The revertants obtained after starvation for adenine differed from each other in growth characteristics. Most of them gave visible colonies 6 to 8 days after plating on SDNA-ade. All of them had lower growth rates on both YEPD and SDNA+ade, than the parent de3-01-CG strain. The colonies were visible on YEPD at the stereomicroscope for even the best growing revertants 1 day later than colonies of the parent strain, de3-01-CG. These initial observations prompted a more detailed examination of the growth characteristics in different conditions. Are Ade + revertants adaptive? The extremely high rate of Ade + revertants observed during prolonged incubation on selective medium could be the consequence of either "adaptive" or genome-wide mutagenesis in a strain with the pol3-01 mutation. To discriminate between the two possibilities, we tested the occurrence of temperature-sensitive (ts) and nutritional mutants among revertants and among Ade - survivors. The results are described below. a) ts mutants The frequency of ts mutants in independent experiments was estimated using a random sample of de3-01-CG Ade + revertants, Ade - survivors isolated on day 14 and Ade + revertants obtained from exponentially growing cells. The data are reported in Table 1 . Fifty-one percent of Ade + revertants and thirty-nine percent of Ade - survivors (i.e. non-mutated cells from aged and starved colonies) were ts mutants, whereas the number of ts mutants among exponentially growing cells was negligible. We also tested 100 Ade + revertants of the strain CG379-3-29(LR) starved for adenine and we did not find a single ts mutant. Table 1 Ts mutant frequency among: Ade + revertants, Ade - survivors and colonies from the log phase. The frequency of ts mutants in three independent experiments was estimated using a random sample of de3-01-CG Ade + revertants, Ade - survivors isolated on day 14 and Ade + revertants obtained from exponentially growing cells. A hundred Ade + revertants of the strain CG379-3-29(LR) starved for adenine were used as controls. The percentage of ts mutants with respect to the number of tested colonies is reported in parentheses. Revertants/Survivors No. of tested colonies No. of ts mutants Starvation condition day 14 de3-01-CG Ade + 489 249 (51%) de3-01-CG Ade - 151 59 (39%) CG379-3-29(LR) Ade + 100 0 Log phase cells de3-01-CG Ade + 1070 7 a a The percentage has not been calculated since the ts mutants are likely to be a single clone. b) Nutritional mutants To detect nutritional mutants we first used the replica plating technique ("Methods"), as we did for ts mutants. By this method, the fraction of nutritional mutants among de3-01-CG Ade + revertants was fifty-nine percent (20 out of 34 revertants tested); all were leaky nutritional mutants. We did not systematically test the ts phenotype in these experiments, but we noticed that the two phenotypes, ts and the nutritional requirement , did not necessarily correlate. To get a quantitative estimation of the severity of nutritional defects in Ade + revertants and Ade - survivors, we compared their fitness ratios (number of cells per colony on SDNA+ade/number of cells per colony on YEPD; see "Methods") with the control strain, de3-01-CG. We presented the growth rate estimations for strain de3-01-CG and for two Ade + revertants in Figure 4 . For all strains there was always less vigorous growth on SDNA+ade than on YEPD, however, the difference for Ade + revertants is much more distinct than the rate in the parent strain; the exponential growth phase ended on day 4. For this reason, we compared the fitness ratios for all strains on day 4. The data are reported in Tables 2 (Ade + revertants) and 3 (Ade - survivors). Sixteen out of 17 Ade + revertants (94%) and 7 out of 12 Ade - survivors had a two times lower fitness ratio than the control strain. It is important to note that all of the strains were respiratory competent, as determined by the 2,3,5-triphenyltetrazolium chloride (TTC) test. We concluded that Ade + revertants acquired one or more nutritional requirements. Figure 4 Growth curves of the strains de3-01-CG and of two Ade + revertants on YEPD and SDNA+ade plates The number of cells/colony (fitness) on SDNA+ade (dotted lines) and on YEPD (continuous lines) is plotted against days in culture. We compared the strain de3-01-CG (triangles ▲) with two Ade + revertants (strain 10, open circles ○; strain 15, closed circles ●). Table 2 Number of cells/colony (fitness) of de3-01-CG Ade + revertants (1–17). We estimated the colonies' fitness as the number of cells per colony 30 on SDNA+ade as well as on YEPD after four days of incubation at 28°C. The strain de3-01-CG was used as control; see "Methods" for details. Strain/Revertant No. of cells /colony (×10 7 ) on: Fitness ratio SDNA+ade/YEPD YEPD SDNA+ade de3-01-CG 4.380 1.700 0.388 1 1.700 - a - a 2 0.070 - a - a 3 - b - b - b 4 2.300 0.040 0.017 5 3.300 0.079 0.024 6 0.200 0.026 0.130 7 0.870 0.026 0.030 8 0.730 0.200 0.274 9 0.260 - a - 10 3.900 0.200 0.051 11 1.700 0.300 0.176 12 1.700 0.210 0.124 13 2.600 0.100 0.038 14 1.600 0.200 0.125 15 0.700 0.080 0.114 16 0.500 0.080 0.160 17 1.700 0.210 0.124 a Hardly visible at the stereomicroscope after 4 days of incubation at 28°C, diameter not estimable. b Not yet visible at the stereomicroscope after 4 days of incubation at 28°C. Visible colonies developed by day 8. Table 3 Number of cells/colony (fitness) of Ade - survivors isolated on day 14 from SDNA-ade dishes. see Table 2. Strain/Survivor No. of cells/colony (×10 7 ) on: Fitness ratio SDNA+ade/YEPD YEPD SDNA+ade de3-01-CG 4.380 1.700 0.388 101 3.320 - a - a 102 1.700 0.100 0.059 103 1.120 0.400 0.357 104 0.750 - a - a 105 1.200 0.120 0.100 106 1.140 0.710 0.623 107 0.080 0.006 0.075 108 0.040 0.013 0.325 109 0.040 0.013 0.325 110 0.002 - b - b 111 3.320 - b - b 112 0.420 0.420 1.000 a Hardly visible at the stereomicroscope after 4 days of incubation at 28°C, diameter not estimable. b Not yet visible at the stereomicroscope after 4 days of incubation at 28°C. Visible colonies developed by day eight. With the replica-plating technique we estimated that the proportion of leaky nutritional mutants among revertants was 59% (see above). When the fitness ratios were determined, we concluded that 16 out of 17 Ade + revertants tested (94%) were nutritional mutants. We suggest that the differences in the estimates may be due to the inaccuracy of the replica plating technique. We did not find a single nutritional mutant among 12 log-phase revertants (data not shown). In the next experiment, cells of the de3-01-CG strain were plated on SDNA without ade and containing four additional amino acids: val, ile, met, arg. We tested the proportion of clones requiring at least one of these amino acids by replica-plating and found that 10.9% of Ade + revertants and 7.9% of Ade - survivors were auxotrophs for the selected four amino acids (Table 4 ; see "Methods" for more details). Table 4 Frequency of auxotrophic mutants among de3-01-CG Ade + revertants and Ade - survivors. Auxotrophic mutants were detected by replica plating de3-01-CG Ade + revertants and de3-01-CG Ade - survivors on SDNA+ade and on SDNA+ade + (val, ile, met, arg). The percentage of auxotrophic mutants with respect to the number of tested colonies is reported in parentheses. No. of replicated colonies No. of auxotrophic mutants de3-01-CG Ade + revertants 375 41 (10.9%) de3-01-CG Ade - survivors 128 10 (7.8%) Does hypermutagenesis in the de3-01-CG strain under adenine starvation occur under starvation for other nutrilites? To answer this question we evaluated the rates of reversion to prototrophy from histidine and tryptophan auxotrophy, respectively (the his7-2 , frameshift allele; trp1-289 , nonsense allele), by the same method that we used to evaluate the rates of accumulation of the Ade + revertants. We have previously shown that the reversion rate of the his7-2 allele in non-growing de3-01-CG cells was about 1.6 × 10 -7 on day 9 [ 10 ], therefore, we plated 1.0 × 10 6 cells/plate for our determinations. This density was optimized to avoid errors in rate estimation arising at higher densities due to cannibalism. The data reported in Table 5 suggest that histidine and tryptophan starvation was much less mutagenic than adenine starvation. Table 5 Accumulation of de3-01-CG revertants under different selective conditions. The mean values of three experiments as well as the standard errors of the mean are reported; for each experiment, 15–20 dishes were done. The reversion rates are given as the total number of revertant colonies per plated cell. Selective Condition Days after plating 6 8 9 10 12 16 SDNA-trp 0.20 × 10 -6 ± 1.00 0.26 × 10 -6 ± 0.58 0.26 × 10 -6 ± 0.58 0.73 × 10 -6 ± 1.30 0.73 × 10 -6 ± 1.30 0.73 × 10 -6 ± 1.30 SDNA-ade a 2.50 × 10 -4 ± 1.00 5.00 × 10 -4 ± 0.60 - b 7.80 × 10 -4 ± 0.90 1.70 × 10 -3 ± 0.50 1.00 × 10 -2 ± 0.30 SDNA- his 0.06 × 10 -6 ± 0.58 0.12 × 10 -6 ± 0.58 0.18 × 10 -6 ± 1.17 0.18 × 10 -6 ± 1.17 0.18 × 10 -6 ± 1.17 0.18 × 10 -6 ± 1.17 a These values are from Figure 1. b Not determined. Discussion In our previous studies we observed that the 3'→5' exonuclease activity of the polymerases δ and ε are both involved in correcting errors in yeast cells starved for histidine [ 10 ]. Here we investigated the effects of adenine starvation and the role of polymerase δ poofreading activity in resting cells starved for adenine. At first we used the Hall's test [ 8 ], the same experimental approach as the previous paper [ 10 ], which allows us to detect revertants as papillae. As mentioned in the "Results" section, with the de3-01-CG strain, every colony had one or more papillae, making an estimation of the reversion rates by this method impossible. Therefore, we studied the rate of accumulation of revertants on SDNA-ade plates, a medium completely devoid of adenine. We have shown that the reversion rate rate in the wild-type strain CG379-3-29(LR) on day 16 was almost 5 orders of magnitude higher than the mutation rate estimated in a fluctuation test (where only the data of the first two days were considered). The high rate of mutations during adenine starvation was further elevated in the de3-01-CG strain, reaching 1% of the plated cells, which means an increase of 66 times with respect to the CG379-3-29(LR) strain. This implied that the proofreading activity of polymerase δ prevented a majority of mutations in resting cells, as in growing cells [ 13 ]. One possible explanation for the extremely high reversion frequency observed is that starvation of strains auxotrophic for adenine leads to perturbations of DNA replication and repair (for example, due to nucleotide pool deprivation or imbalances which are known to be mutagenic in yeast [ 14 , 15 ]). In the yeast S. cerevisiae the consequences of adenine starvation on mutagenesis were previously studied by Korogodin et al. [ 16 ]. The authors investigated the reversion rates of the ade2-192 allele (a missense mutation) in different strains and found that the lowest adenine concentration tested resulted in a 150-fold increase in locus revertants rate, while the suppressors rate was almost constant. When ade2-192 cells entered the stationary phase, their color shifted from white to red, a color which is due to a pigment that accumulates in ade2 mutants when the adenine biosynthetic pathway is in operation. Korogodin et al. [ 16 ] suggested, therefore, that the ade2-192 allele is derepressed under the condition of adenine deprivation and proposed that mutagenesis resulted from some process associated with transcription. Indeed, it is now well known that transcription-coupled mutagenesis occurs in yeast [ 17 ]. The data presented in this paper allow us to conclude that the high frequency of reversion to adenine prototrophy cannot be explained by transcription-coupled mutagenesis at the specific location of the ade5-1 allele in our experimental conditions. Instead, genome-wide mutagenesis occurred in the de3-01-CG strain under adenine deprivation. This is suggested by the high rate of ts and nutritional mutants among de3-01-CG Ade + revertants as well as Ade - survivors. It is possible that genome-wide mutagensis occured in CG379-3-29(LR) as well but its lower mutability could have made difficult to detect ts and nutritional mutants even under adenine starvation. The observed mutation rates in the de3-01-CG strain were so high that we can characterize adenine deprivation as one of the most powerful mutagens for adenine auxotrophic strains. We can also conclude that under adenine starvation the 3'→5' exonuclease activity of polymerase δ prevented errors leading to the reversion of the ade5-1 strain to prototrophy along with the prevention of numerous genome-wide errors. Indeed, the rate of the ade5-1 reversion, under the conditions of adenine starvation was increased 66-fold in the pol3-01 strain. Apparently, the high rate of reversion was a sign of mutational catastrophe, since most of the revertants were ts or auxotrophs due to additonal mutations that occurred elsewhere in the genome. High mutation rates, similar to what is described in the present paper, were reported by Bresler et al. [ 18 ]. The authors showed that bacterial cells grown on thymine-limited medium were often auxotrophs for more than one nutritional requirement, and that most mutants selected for other markers (such as streptomycin resistance) had additional mutations leading to auxotrophy. They observed, for example, that in an E. coli strain the percentage of streptomycin-resistant mutants with a nutritional requirement was 97.8%. This proportion is similar to the 94% of nutritional mutants obtained for de3-01-CG Ade + revertant clones in our study; however, Bresler et al. [ 18 ] performed experiments with replicating cells. To the best of our knowledge, the high spontaneous frequency of ts mutations observed in the present work have never been reported. Hartwell [ 19 ], in a study of cells heavily treated with N-methyl-N'-nitro-N-nitrosoguanidine, found that 1% were ts mutants, which is fifty times lower than the proportion of ts mutants among the Ade + revertants reported here. We can give a rough estimation of mutation rate per gene in the de3-01-CG auxotrophic strain under adenine starvation from the proportion of ts mutants (51%) among Ade + revertants. The ts phenotype is supposed to be the consequence of mutations in essential genes. According to Winzeler et al. [ 20 ], the number of essential genes in S. cerevisiae is about 1,000. If one Ade + revertant cell has a probability of 0.51 to be a ts mutant, then the probability for any one essential gene to mutate to a ts phenotype is 0.51/1000, i.e. 5.1 × 10 -4 . Harris and Pringle [ 21 ] observed that only a fraction of essential genes could be identified by ts mutations in S. cerevisiae . Since ts mutations are only a portion of total mutations, it is likely that each mutation rate in an essential gene was higher than the rate of ts mutations. This high mutation rate might be one of the reasons for a decrease in the viability of the pol3-01 strain under adenine starvation (see "Results"). We previously calculated that overall a 0.01 level of mutability leads to a drop of viability to 5% [ 22 ]. Finally, we wish to address a further important issue. In the present paper, we show that yeast haploid cells may sustain a very high genetic load even if their viability and fitness were reduced. Indeed, it is likely that the much lower survival of the mutator strain de3-01-CG, with respect to CG379-3-29 (LR) on adenine-free plates, was due to a high rate of mutations in the essential genes. One may wonder how some haploid cells can survive with such a high genetic load. One possibility is that under adenine starvation most mutations are base changes which could not have an appreciable lethal effect; actually, we found high rates of ts mutants which should be due to base changes. In natural conditions, yeast cells are diploids and, therefore, they could accumulate more variability, given that, according to Hartwell [ 19 ], 99% of ts mutations are recessive. Therefore, yeast diploids can afford much higher rates of mutagenesis [ 23 - 25 ]. The same holds true for other eukaryotic organisms. Pimpinelli et al. [ 26 ] showed that Aspergillus nidulans diploid conidia subjected to several cycles of 6-N-hydroxylaminopurine-induced mutagenesis (a base analog that induces only base substitutions) differ from each other for about ten lethals and, therefore, for a large number of mutations, perhaps several hundreds, without any viability reduction. Conclusions In conclusion, we have demonstrated that: i) adenine starvation strongly induces reversion to Ade + phenotype in the wild-type strain; ii) a defect in the proofreading exonuclease activity of DNA polymerase δ due to the pol3-01 mutation leads to a further 66-fold elevation of the Ade + mutagenesis; and iii) under adenine starvation, the mutagenesis in the de3-01-CG strain is genome-wide, therefore, Ade + reversions in this strain are not adaptive. Methods Strains The S. cerevisiae strains used were: CG379-3-29(LR) [ MATα ade5-1 leu2-3 , 112 Δ ura3 bik1::ura3 29 (LR) his7-2 trp1-289 CAN1 lys2- Tn 5-13 ]; and de3-01-CG [same as CG379-3-29(LR) but pol3-01 ] [ 27 ]. Media YEPD medium (1% Yeast Extract, 2% Pepton, 2% glucose) and the synthetic SD medium (6.7% Yeast Nitrogen Base, 2% glucose) were used throughout the work. In some experiments, SD was solidified with 1.5% Noble Agar (Sigma, SDNA) (see below). We named the SDNA medium containing all the nutrilites required by the strain SDNA+ade. When adenine was not included we named it SDNA-ade. Reversion rates and isolation of revertants The accumulation of revertants under the starvation condition was investigated on SD with a limited amount of adenine (20 μg/l, SD.lim), as well as on SDNA-ade. On SD.lim we counted the number of colonies with Ade + papillae throughout the experiment [ 8 ]. On SDNA-ade plates, the number of Ade + revertants was evaluated as follows: 10,000 and 1,000 cells/plate were plated for the strains GC379-3-29(LR) and de3-01-CG, respectively, and incubated at 28°C; the revertant colonies were scored at the stereomicroscope (20×). For each experiment, 15–20 plates were set up. Noble agar was used to limit unwanted cellular divisions. The reversion rate is given as the total number of revertant colonies per plated cell. As explained in the "Results" section, we did not correct for the residual divisions or for the surviving fraction. We estimated the total number of post-plating cellular divisions on SDNA-ade plates by comparing the number of cells immediately after plating and in the following days. The dishes were observed at the microscope (400×) and the number of cells per unit was counted. Here we considered a unit any single cell as well as more cells clustered together. For each experimental point, at least 200 units were counted and the mean values calculated. To estimate the surviving fraction of cells and to characterise Ade - survivors, we plated an adequate number of cells on SDNA-ade. We needed to rescue Ade - survivors colonies from SDNA-ade dishes to determine viable cells and to isolate Ade - clones for further characterisation. In order to do this, we have cut off two small pieces of agar in some dishes. This procedure created wells where we put adenine, which spread across plates without washing away the colonies. The procedure allows a correct estimation of surviving cells. The reversion rate during the logarithmic growth phase was estimated by the fluctuation test using the P 0 method [ 28 , 29 ]. To obtain Ade + revertants for further characterization we transferred Ade + colonies to YEPD medium. We were careful to pick up cells from the revertant colony by touching only the colony's surface with a needle at the stereomicroscope. Control experiments have shown that this procedure is reliable in our hands (data not shown). The phenotypic as well as the molecular analysis of Ade + revertants that arose in the logarithmic phase of growth was done on revertants isolated on day 2 in a fluctuation experiment. Only 1 colony per dish was picked up and isolated on YEPD. The analysis of Ade + revertants arisen in starved cells was done on a random sample of revertants isolated on day 14, since we were sure that the great majority of them derived from mutational events that occurred in cells starved for adenine (see "Results"). Determination of growth of revertants on SDNA-ade To determine the time of appearance of Ade + revertant colonies as well as their growth rate on SDNA-ade, we either plated 100 cells per dish or streaked suspensions (10 5 cells/0.1 ml), incubated at 28°C and scored at the stereomicroscope (20×). Detection of mutants with nutritional requirements To detect leaky nutritional mutants among Ade + revertants and Ade - survivors, we estimated the colonies' fitness as the number of cells per colony [ 30 ] on SDNA+ade as well as on YEPD on fourth day after plating. Fifty cells of each strain were plated on Petri dishes containing 25 ml of YEPD and SDNA+ade, respectively. The plates were then incubated at 28°C and scored at the stereomicroscope for the appearance of colonies. Most colonies appeared by 4 days (see "Results") but the plates were incubated for longer to score slowly growing colonies. The diameters of 50 randomly chosen colonies were measured, and the mean value estimated. The mean value was used to calculate the approximate colony volumes, assuming their hemispheric shape as was done previously by Wloch et al. [ 30 ]. To obtain the number of cells per colony, we divided the colony volume by 1.1 × 10 -7 μl (by the volume of a haploid yeast cell) [ 31 ]. We then calculated the ratio of the revertant colonies' fitness on SDNA+ade to that on YEPD (SDNA+ade/YEPD) and compared it to that of the control strain. We arbitrarily considered those strains whose SDNA+ade/YEPD fitness ratio was at least twice lower than that of the strain de3-01-CG to be nutritional mutants. The comparison of SDNA+ade/YEPD ratios allowed us to detect nutritional mutants quantitatively but this approach was rather cumbersome. Alternatively, to screen more revertants, we used a qualitative test. The cells were point-inoculated by a needle on YEPD plates, which were then incubated for several days at 28°C. Thereafter, they were replica-plated on YEPD and SDNA+ade. After 2 days, the growth spots on both media were compared with those of the control strain. A revertant was considered a nutritional mutant when its SDNA+ade/YEPD growth ratio was reduced drastically (judged from visual inspection) with respect to that of the control strain. The detection of respiration-deficient strains ( petite ) was done by the 2,3,5-triphenyltetrazolium chloride (TTC) test as in Ogur et al. [ 32 ]. Detection of nutritional mutants auxotrophic for valine, isoleucine, methione, arginine Strain de3-01-CG cells were plated on SDNA-ade plus other randomly chosen aminoacids [SDNA-ade + (val, ile, met, arg)]. On the day 14, the Ade + colonies were marked and adenine was added in two wells in agar as described above. The plates were incubated for further 6 days to allow Ade - survivors to form colonies. Then they were replica plated on SDNA+ade and on SDNA+ade + (val, ile, met, arg) to detect auxotrophic mutants. Detection of temperature-sensitive (ts) mutants Ade + revertants as well as Ade - survivors isolated on SDNA-ade on day 14 were tested for the presence of ts mutations. To obtain Ade - survivors, Ade + colonies were marked and then adenine was added to two wells of SDNA-ade plates seeded with 1,000 cells/plate on day 14. Dishes were incubated for 6 days more and previously non-marked colonies were isolated on YEPD. Colonies were then tested for their Ade - phenotype on SDNA-ade. To detect ts mutants, cells from a fresh culture were point inoculated by a needle on YEPD plates, which were incubated for several days at 28°C. Colonies were then replica plated on two YEPD dishes: one of them was incubated at 28°C while the other one at 37°C for two days. The first replica was always incubated at 37°C. A strain was considered to be a ts mutant if in two days it was able to grow at 28°C but not at 37°C. The strains CG379-3-29(LR) and de3-01-CG were included as controls. Determination of the nucleotide sequence of the ADE5,7 locus in CG379-3-29(LR) and Ade + revertants strains Genomic DNA from S. cerevisiae was purified using the NucleoSpin ® Tissue kit (Macherey-Nagel). The ADE5,7 locus (from 490 bp upstream of the start codon to 473 bp downstream of the stop codon) was amplified from genomic DNA of the CG379-3-29(LR) strain using primers ADE5-F1 (5'-CAAAAGTAGAAGACCCCC-3') and ADE5-R1 (5'-CCATTCATCAATTACGG-3'). The PCR reaction was performed according to standard protocol, using the proofreading-proficient Pfx DNA polymerase (Invitrogen). The PCR produced a DNA fragment of 3383 bp, which was purified from an agarose gel by the High Pure PCR Product Purification Kit (Roche). The nucleotide sequence of both strands of the purified DNA fragment was determined by the Sanger method [ 33 ], with fourteen different synthetic primers, using the BigDye Terminator Cycle Sequencing Kit (Applied Biosystem). The sequence of the amplified fragment from the CG379-3-29(LR) strain was compared with the sequence of the ADE5,7 gene in the Saccharomyces Genome Database [ 34 ] by the BLAST algorithm [ 35 ]. DNA fragments of the ADE5,7 alleles in Ade + revertant strains were obtained by PCR amplification, using purified genomic DNA as template and the primers ADE5-F4 (5'-CCG TAA ACA TAG GAA TCG-3') and ADE5-R4 (5'-TTG TAC GAG ATT GTT ACC-3'). PCR, performed as previously described, generated a 398 bp long DNA fragment, encompassing the ade5,7 mutation in the CG379-3-29 strain. The purified DNA products were sequenced using the same primers, ADE-F4 and/or ADE5-R4. Authors' contributions AA performed molecular analysis of Ade + revertants and AA, AL, NB and GM studied mutagenesis during starvation. YIP constructed the pol3-01 strain, participated in the design of the study and writing the manuscript. EC performed sequencing of the ade5-1 allele and molecular analysis of Ade + revertants. NB, GM and YIP coordinated the study. AA, AL, EC participated in the design of the study. All authors read and approved the final manuscript.

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545215

Three More Learning Points

After reading the Learning Forum by Fleming and Lynn [1] , I would like to suggest three learning points that, in my opinion, should receive more attention. (1) Morphology: the essential point of dermatological diagnosis is morphology, a low tech, but hard to master, skill. Dermatological diagnosis, as any other medical diagnosis, starts by collecting adequate information from the patient, and follows by its elaboration. Many doctors consider that dermatological diagnosis can be made on a quick recognition basis, but an ordered and syndromic approach is essential to get to an adequate diagnosis. I think that most dermatologists would agree that a good description of a patient by an experienced colleague is a better starting point for diagnosis than many pictures. I would describe the lesions seen in Figure 1 of [1] not simply as shallow ulcers, but as clearly polycyclic erosions (a finding highly suggestive of herpetic infection). (2) Indicated investigations: Tzanck test is the microscopic evaluation of cell morphology on a cutaneous smear. It can be done in about 15 minutes, requiring a microscope and a trained doctor. Access to this test is probably much easier than to viral cultures or polymerase chain reaction tests. In this setting, a positive Tzanck test would be enough to confirm the clinical diagnosis at a minimum cost. Considering the widespread audience of PLoS Medicine , with many readers in less developed countries, this test should not be forgotten. (3) This case, and the suspicion about systemic manifestations of skin disease, is a wonderful opportunity to disseminate an old concept, very frequently forgotten in medical literature: the skin is an organ, in fact, the biggest one in the body. Its main functions are to act as a barrier, to control temperature, to serve immunological and hormonal roles, and, physiologically less important but very important for patient well-being, to participate in personal relationships. When these functions are not adequately performed, skin failure appears, exactly as is the case with heart or renal failure. Skin failure can have many manifestations, including noninfectious fever, bacteremia, or sepsis. As is the case with renal or cardiac failure, it is easier and more practical to learn about this syndrome than to discuss the systemic manifestations of the many diseases that can cause it. I would highly recommend the following references for doctors interested in the subject: [ 2 , 3] .

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539057

Correction: Nevirapine and Efavirenz Elicit Different Changes in Lipid Profiles in Antiretroviral-Therapy-Naive Patients Infected with HIV-1

Published October 19, 2004 In PLoS Medicine, volume 1, issue 1: Nevirapine and Efavirenz Elicit Different Changes in Lipid Profiles in Antiretroviral-Therapy-Naive Patients Infected with HIV-1 Frank van Leth, Prahpan Phanuphak, Erik Stroes, Brian Gazzard, Pedro Cahn, et al. DOI: 10.1371/journal.pmed.0010019 The following information was missing from the legend for Figure 1 : closed squares, NVP; open squares, EFV; error bars denote standard errors. Oliver Flint at Bristol-Myers Squibb alerted PLoS Medicine to this omission. Figure 1 Change in Plasma Concentrations of Lipids and Lipoproteins Adjusted for sex, region, pVL decrease, and CD4 + -cell increase. Closed squares, NVP; open squares, EFV; error bars denote standard errors. There was also a line with open circles in Figure 1F that should not have been included.

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374244

A Protein Complex Containing the Conserved Swi2/Snf2-Related ATPase Swr1p Deposits Histone Variant H2A.Z into Euchromatin

The conserved histone variant H2A.Z functions in euchromatin to antagonize the spread of heterochromatin. The mechanism by which histone H2A is replaced by H2A.Z in the nucleosome is unknown. We identified a complex containing 13 different polypeptides associated with a soluble pool of H2A.Z in Saccharomyces cerevisiae . This complex was designated SWR1-Com in reference to the Swr1p subunit, a Swi2/Snf2-paralog. Swr1p and six other subunits were found only in SWR1-Com, whereas six other subunits were also found in the NuA4 histone acetyltransferase and/or the Ino80 chromatin remodeling complex. H2A.Z and SWR1 were essential for viability of cells lacking the EAF1 component of NuA4, pointing to a close functional connection between these two complexes. Strikingly, chromatin immunoprecipitation analysis of cells lacking Swr1p, the presumed ATPase of the complex, revealed a profound defect in the deposition of H2A.Z at euchromatic regions that flank the silent mating type cassette HMR and at 12 other chromosomal sites tested. Consistent with a specialized role for Swr1p in H2A.Z deposition, the majority of the genome-wide transcriptional defects seen in swr1 Δ cells were also found in htz1 Δ cells. These studies revealed a novel role for a member of the ATP-dependent chromatin remodeling enzyme family in determining the region-specific histone subunit composition of chromatin in vivo and controlling the epigenetic state of chromatin. Metazoan orthologs of Swr1p ( Drosophila Domino; human SRCAP and p400) may have analogous functions.

Introduction Histones are the major constituent of chromatin and exert a profound influence on most if not all aspects of chromosome behavior. The functional state of chromatin is regulated, in part, by histone modifying enzymes and ATP-dependent chromatin remodeling enzymes. Members of the latter enzyme class alter the structure of nucleosomes or slide them along DNA in vitro (reviewed in Becker and Horz 2002 ; Peterson 2002 ). These enzymes have a catalytic DNA-dependent ATPase subunit, which is similar in sequence to those of the DEAD/DEAH-box class of RNA-dependent ATPases. The prototype for this family is the Saccharomyces cerevisiae Swi2/Snf2 protein, originally identified for its role in promoting transcription. In addition to histone modification and nucleosome remodeling/sliding, there is a third form of chromatin regulation that involves the replacement of canonical histones with histone variants. For example, replacement of histone H3 by a conserved H3 variant (called Cse4p in S. cerevisiae, Cid in Drosophila, or CENP-A in humans) is essential for the assembly of the kinetochore (reviewed in Smith 2002 ). The other histone variant that is conserved between yeast and humans is H2A.Z, which replaces H2A in about one in ten nucleosomes. By convention, the gene encoding H2A.Z in Saccharomyces is referred to as HTZ1 and mutant forms of the gene are referred to as htz1. We have shown previously that an important function of H2A.Z in S. cerevisiae is to prevent the spreading of silent chromatin, also termed heterochromatin, into adjacent euchromatic regions ( Meneghini et al. 2003 ). Silencing in S. cerevisiae occurs at the HMR and HML silent mating type cassettes, near telomeres, and in the rDNA (reviewed in Rusche et al. 2003 ). All three types of silencing require the NAD-dependent histone deacetylase Sir2p. Telomeric and HM silencing also require the histone H3/H4 tail binding proteins, Sir3p and Sir4p. In yeast cells lacking H2A.Z, the Sir complex spreads beyond its normal boundaries at HMR and into neighboring euchromatin, resulting in the repression of gene expression ( Meneghini et al. 2003 ). This repression is reversed by a deletion of SIR2 or a deletion of the nucleation sites for silencing at HMR . Likewise, the silencing of genes near telomeres in htz1 Δ cells is reversed by a deletion of SIR2 . In yeast, H2A.Z itself is enriched in the euchromatic region flanking HMR and is depleted in silent regions. Genetic analysis indicates that H2A.Z acts independently of a characterized chromatin boundary element that occurs on the right border of the HMR silent cassette. Thus, H2A.Z is a euchromatin-specific factor that antagonizes the spread of silencing through a mechanism that is independent of at least one characterized boundary element ( Meneghini et al. 2003 ). However, the creation of a boundary for the spread of silenced chromatin likely involves additional protein factors, such as the double bromodomain protein, Bdf1p, whose function is similar to that of H2A.Z and which binds preferably to acetylated histones that are found in euchromatin outside of silenced regions ( Ladurner et al. 2003 ; Matangkasombut and Buratowski 2003 ). Despite its critical role in preventing the spread of heterochromatin, the mechanism by which H2A.Z is deposited in euchromatin is unknown. The canonical histones can be deposited by both replication-coupled and replication-independent deposition mechanisms (reviewed in Haushalter and Kadonaga 2003 ). In human cells, the replication-coupled deposition pathway is essential for progression through S-phase and for cell viability ( Hoek and Stillman 2003 ; Ye et al. 2003 ). In contrast, in budding yeast, no single deposition pathway is essential for viability ( Kaufman et al. 1998 ; Formosa et al. 2002 ). For example, the histone H3/H4 chaperones CAF-I and Asf1p function synergistically during replication-coupled histone deposition in vitro and cooperate to form heterochromatin in vivo. However, neither CAF-I nor Asf1p is essential for cell viability in S. cerevisiae, and mutants lacking both proteins are also viable ( Tyler et al. 1999 ). Nap1p, a yeast homolog of a mammalian histone chaperone purified on the basis of a replication-independent assembly assay, is also dispensable for viability in S. cerevisiae ( Ishimi and Kikuchi 1991 ; Kellogg and Murray 1995 ). Thus, other mechanisms must operate to deposit chromatin in living cells. One candidate is the Drosophila factor ACF and the orthologous human complex RSF, which each contain a ISWI-type Swi2/Snf2 ATPase subunit (reviewed in Haushalter and Kadonaga 2003 ). These factors promote the ATP-dependent assembly of ordered nucleosome arrays in vitro, but their precise in vivo roles have not been firmly established. Even less is known about the mechanisms of deposition of variant histones. Understanding the mechanism by which euchromatin that contains H2A.Z is formed requires the identification of the machinery that catalyzes its deposition. The results of this study identify a multisubunit protein complex, SWR1-Complex (SWR1-Com), which contains a Swi2/Snf2 paralog and is required for H2A.Z deposition and function in S. cerevisiae . We link this complex structurally and genetically to the NuA4 histone acetyltransferase (HAT) and the Ino80-C chromatin remodeling complex. Results A Protein Complex (SWR1-Com) Associated with the Histone Variant H2A.Z H2A.Z is important for specifying euchromatic regions in the genome of S. cerevisiae ( Meneghini et al. 2003 ). To determine which other proteins contribute to directing H2A.Z to its chromosomal locations, we purified proteins associated with a soluble pool of H2A.Z from whole cell extracts of a yeast strain harboring an allele of HTZ1 that encodes a carboxyl-terminal fusion to the tandem affinity purification (TAP) tag (see Materials and Methods ) ( Rigaut et al. 1999 ). These initial purifications were performed under low salt conditions and with limited wash steps to maximize protein complex recovery, with more stringent conditions used subsequently to distinguish strong from weak and potentially artifactual interactions (see below). The protein compositions of the samples were determined using Direct Analysis of Large Protein Complexes methodology, which consists of tryptic digestion of the mixture, multidimensional microcapillary chromatography, tandem mass spectrometry, and genome-assisted analysis of the acquired spectral data ( Link et al. 1999 ; Sanders et al. 2002 ). A protein was judged to be associated with H2A.Z if the number of corresponding peptides in the H2A.Z-TAP purified material was higher than in the material purified from strains lacking a tagged H2A.Z protein and if the protein passed additional criteria described below. Proteins established to nonspecifically copurify with TAP-tagged proteins were excluded from the analysis ( Shevchenko et al. 2002 ). Using these criteria and additional purifications (described below), we identified 15 proteins associated with H2A.Z ( Table 1 ), of which 13 form a complex designated SWR1-Com ( Figure 1 and see below). The largest subunit corresponded to Swr1p (Swi2/Snf2-related), an uncharacterized member of the Swi2/Snf2 family of ATP-dependent chromatin remodeling enzymes ( Pollard and Peterson 1998 ). Figure 1 Subunit Architecture of SWR1-Com and Overlap with NuA4 and Ino80-C Complexes Venn diagram showing proposed subunit compositions of the SWR1, NuA4, Ino80p-C, and Nap1p/Kap114p complexes. Assignments were based on the data shown in Table 1 and Figure 2 and Figure 3 . Proteins used in TAP purifications are indicated by “*” and proteins encoded by essential genes are underlined. Table 1 Peptides in TAP Purifications ND, not determined. We named SWR1-Com by convention used for similar complexes. Shown is the number of peptides corresponding to the protein indicated in the left column that were found in the mass spectrometry analysis of purifications from strains with H2A.Z-TAP, Swr1-TAP, Yaf9-TAP, and Swc4-TAP. Previously undescribed subunits of SWR1-Com are referred to as SwcNp (for SWR1-complex) and the corresponding genes as SWCN, where N is an integer assigned in order of decreasing molecular weight. However, an important point of this work is that SWR1-Com shared subunits with other protein complexes. We have retained all the previously published names assigned to these proteins. Protein abundance and subcellular localization data are adapted from recently published data ( Ghaemmaghami et al. 2003 ; Huh et al. 2003 ) SWR1-Com Shared Subunits with the Essential HAT NuA4 and the Ino80-C Chromatin Remodeling Complex Four SWR1-Com subunits that are also found in the Ino80-C chromatin remodeling complex are Rvb1p, Rvb2p, Arp4, and actin ( Shen et al. 2000 ). Similarly, Yaf9p, as shown below and by others ( Le Masson et al. 2003 ), as well as Arp4p and actin, are also components of the NuA4 HAT ( Galarneau et al. 2000 ). To determine whether the proteins that associated with H2A.Z formed one discrete complex, multiple complexes, or were copurifying contaminants, three of these proteins were themselves tagged with the TAP domain. Complexes from the soluble fraction of whole cell extracts were purified in conditions similar to those used for the H2A.Z-TAP purification, and the composition of the purified material was evaluated by the same procedure used for the H2A.Z-TAP (summarized in Table 1 and Figure 1 ). With the exception of the histone chaperone Nap1p and the import protein Kap114p, the proteins that copurified with TAP-tagged Swr1p were similar to the set found with H2A.Z, except that two additional proteins, designated here as Swc3p and Swc7p, were identified. Similarly, purifications from strains with TAP-tagged Swc4p and Yaf9p yielded nearly all the proteins associated with Swr1p and H2A.Z and lacked Nap1p and Kap114p. Like the Swr1-TAP material, the Swc4-TAP-associated material contained Swc3p and Swc7p, supporting the assignment of these two proteins to SWR1-Com. TAP-tagged Swc4p and Yaf9p also associated with most of the subunits of the NuA4 complex (including Tra1p, Epl1p, Eaf3p, Yng2p, and the catalytic subunit Esa1p). These data suggested that SWR1-Com and NuA4 shared the Yaf9p, Swc4p, Arp4, and actin subunits. Representative complex purifications under high stringency conditions (see Materials and Methods ) from strains with either the Swr1-TAP, Yaf9-TAP, or an untagged control strain are shown in Figure 2 A. Proteins that copurified with both Swr1-TAP and Yaf9-TAP represented subunits of SWR1-Com ( Figure 2 A, arrows), whereas proteins that only copurified with Yaf9-TAP represented specific NuA4 subunits ( Figure 2 A, stars). A schematic representation of the domain structures of SWR1-Com subunits is presented in Figure 2 B. Several of the proteins in the complex contained motifs (SANT, Bromo, YEATS, and HIT) found in proteins associated with chromatin, suggesting that SWR1-Com acts directly on chromatin. Figure 2 SWR1-Com Shared Subunits with NuA4 and Contained Proteins with Motifs Involved in Chromatin Biology (A) Protein complex overlap. Purifications were performed under high stringency conditions (see Materials and Methods ) from Swr1-TAP, Yaf9-TAP, and untagged control strains, resolved by SDS-PAGE and stained with silver. Due to the relatively low efficiency of the Swr1-TAP purification, the wt and Swr1-TAP purifications were performed from twice the amount of starting material compared to Yaf9-TAP. Not all proteins identified by mass spectrometry were clearly visible on the gel. Arrows point to proteins that were common to the Swr1-TAP and Yaf9-TAP purifications, whereas stars point to proteins that were found only in the Yaf9-TAP purifications as judged by visual inspection and comparison of protein sizes with the data deduced from mass spectrometry. The vertical bar indicates that proteins in that area of the gel could not be clearly resolved. (B) Domain structure of SWR1-Com. Shown are SMART domain representations of individual proteins assigned to the SWR1-Com taken from the SMART database ( http://smart.embl-heidelberg.de/ ). Domain names are included, green bars indicate coil-coiled regions, and magenta bars indicate regions of low complexity. The amino-terminal part of Swr1p is not to scale. Since the histone chaperone Nap1p and the import factor Kap114p copurified with H2A.Z but not other members of the complex, they were likely to be part of an H2A.Z-containing protein complex distinct from SWR1-Com. Affinity purification of TAP-tagged Rvb2p, an established component of the Ino80-C chromatin remodeling complex, yielded peptides corresponding to the other known subunits of the Ino80-C complex as well as six members of SWR1-Com, three of which (Swc4p, Arp4p, and actin) are also subunits of NuA4 ( Table S1 ). Consistent with the assignment of SWR1-Com subunits, a percentage of the cellular pool of these proteins cosedimented with each other upon glycerol gradient centrifugations of whole cell extracts ( Figure S1 ). The initial purifications suggested that Swc4p and Bdf1p, both of which have domains that are involved in recognition of histone tails, copurified with H2A.Z-TAP and might be part of SWR1-Com. Independent assessment of the composition of the complexes deduced by mass spectrometry was obtained by analytical-scale affinity purifications of Yaf9-TAP, Esa1-TAP, Rvb2-TAP, Swr1-TAP, and Ino80-TAP from cells containing a version of Swc4p that was fused at its carboxyl-terminus to a triple hemagglutinin (HA) tag. These analytical-scale affinity purifications were more stringent than the initial TAP purifications and therefore served to eliminate false-positive results and to provide independent tests of interactions. Anti-HA epitope antibodies and antibodies against Tra1p, the largest subunit of NuA4, were used to analyze the copurified material. Both Yaf9-TAP and Esa1-TAP associated with comparable amounts of Tra1p and Swc4p, supporting the assignment of Yaf9p and Swc4p as new subunits of NuA4. Likewise, Rvb2-TAP and Swr1-TAP copurified with a substantial amount of Swc4-HA, but Ino80-TAP did not. Rvb2-TAP, Swr1-TAP, and Ino80-TAP were not associated with Tra1p ( Figure 3 A). These data were consistent with Swr1p and Rvb2p being components of SWR1-Com and not of NuA4. Further supporting the assignment of Swc4p as a subunit of NuA4, significant amounts of the NuA4 subunits Tra1p and Esa1p were present in material from Swc4-TAP analytical-scale purifications ( Figure 3 B). Figure 3 Swc4p and Bdf1p Were Components of SWR1-Com This figure shows immunoblots of analytical-scale TAP purifications. The captured TAP-tagged protein is indicated above the gels, and the protein that was tested for association is indicated at the right side. (A) Association of Swc4p and Tra1p. Swc4-HA was present in purifications from Yaf9-TAP, Esa1-TAP, Rvb2-TAP, and Swr1-TAP but not Ino80-TAP. NuA4 was only present in the Yaf9-TAP and Esa1-TAP material. (B) Reciprocal confirmation of Swc4p being part of NuA4. Swc4-TAP and Yaf9-TAP purified material contained NuA4 components Esa1p and Tra1p. (C) Association of Bdf1p. Bdf1p was present in purifications from Swr1-TAP, Yaf9-TAP, and Swc4-TAP but not Esa1-TAP. The number of peptides corresponding to Bdf1p in the TAP purifications was low, and Bdf1p was found only in the H2A.Z-TAP and the Yaf9-TAP ( Table 1 ). Bdf1p's potential presence was tested further by additional analytical-scale affinity purifications from strains carrying Yaf9-TAP, Swr1-TAP, Swc4-TAP, and Esa1-TAP and immunoblotting with an antibody against Bdf1p. Bdf1p associated with Swr1-TAP, Yaf9-TAP, and Swc4-TAP but not with Esa1-TAP or untagged control material, supporting the assignment of Bdf1p as a subunit of SWR1-Com ( Figure 3 C). SWR1-Com Selectively Associated with Histone H2A.Z Versus H2A To determine whether subunits of SWR1-com associated specifically with H2A.Z or both H2A.Z and H2A, TAP-tagged versions of H2A.Z and H2A were purified from cells containing HA-tagged versions of the five different SWR1-Com components Swr1p, Swc2p, Swc3p, Swc4p, and Swc7p, and the nuclear import factor Kap114p. The composition of the copurifying material was then evaluated by immunoblotting with antibodies against the HA tag, Bdf1p, and Tra1p. Yaf9-TAP served as a positive control for recovery of SWR1-Com and NuA4. H2A.Z associated with a substantial fraction of the SWR1-Com as judged by the comparable intensity of the signal for SWR1-Com subunits in the material copurified with H2A.Z-TAP and Yaf9-TAP, whereas no NuA4 copurified with H2A.Z-TAP based upon the absence of Tra1p in the H2A.Z-TAP sample ( Figure 4 A). In contrast, histone H2A copurified with only trace amounts of Swc2-HA, Swc3-HA, Swc4-HA, Swc7-HA, and Bdf1p and with virtually no Swr1-HA (see Figure 3 ). Kap114-HA associated with both H2A.Z-TAP and H2A-TAP but not Yaf9-TAP, suggesting that it did not discriminate canonical and variant H2A. Hence, based on the apparent relative strength of the interactions, SWR1-Com (in contrast to Kap114-HA) associated primarily with H2A.Z, although weak affinity of SWR1-Com to H2A was possible. Furthermore, these experiments also supported the assignment of Swc3p and Swc7p to SWR1-Com despite peptides for these two proteins being present only in the initial Swr1-TAP and Swc4-TAP purifications. Figure 4 SWR1-Com Associated Selectively with H2A.Z and Contained H2B (A) Analytical-scale TAP purifications from H2A.Z-TAP, Yaf9-TAP, and H2A-TAP were analyzed by immunoblotting for the components indicated on the right. SWR1-Com preferentially associated with H2A.Z-TAP, whereas Kap114-HA associated equally with H2A.Z-TAP and H2A-TAP but not Yaf9-TAP. (B) SWR1-Com was purified from strains with HA-tagged versions of either H2A.Z or H2B and analyzed by immunoblotting for the presence of these histones as well as the SWR1-Com subunit Act1p. Canonical H2A that is not bound to chromatin is usually found in a H2A/H2B dimer ( Jackson 1987 ). The presence of H2B in the SWR1-Com was investigated by purifying SWR1-Com from strains containing H2A.Z-HA and H2B-HA. SWR1-Com contained H2A.Z-HA and also H2B-HA ( Figure 4 B). These data raised the possibility that this complex used H2A.Z/H2B dimers as a substrate. Similar Gene Expression Profiles of htz1 Δ and swr1 Δ Cells To determine the extent to which the role of H2A.Z depends upon SWR1-Com function, genome-wide transcription profiles of swr1 Δ cells were compared to the profiles of htz1 Δ cells ( Meneghini et al. 2003 ). To permit an optimal comparison, experiments were performed under the conditions used previously to analyze htz1 Δ cells (see Materials and Methods ). Due to the role of H2A.Z in anti-silencing, H2A.Z-dependent genes tend to be located near silenced domains such as telomeres. This theme was echoed in the results from the swr1 Δ mutant. Specifically, 42 of the 94 (45%) Swr1p-dependent genes were within 20 kb of a chromosome end, which is less than 3% of the genome ( Figure 5 A). This enrichment is highly significant, as judged by p -values estimated from the hypergeometric distribution ( Figure 5 B). Swr1p-dependent genes were underrepresented from regions more than 40 kb from a telomere, suggesting that, as seen earlier for H2A.Z, the telomere-proximal genes were most sensitive to loss of Swr1p function. Figure 5 Chromosomal Distribution of Swr1p-Activated Genes (A) Histogram showing the number of Swr1p-activated genes as a function of their distance to the nearest chromosome end. (B) The statistical significance of the enrichment of Swr1p-activated genes as a function of distance to the nearest telomere, and the significance of the depletion of Swr1p-activated genes in regions greater than 40 kb from a telomere, were determined using the hypergeometric function ( Tavazoie et al. 1999 ). Comparison of the transcript profile across the genome of swr1Δ cells to that of htz1 Δ cells also revealed a marked overlap ( Figure 6 A). Ninety-four genes displayed reduced expression in the swr1 Δ mutant compared to wild type. Of these 94 Swr1p-dependent genes, 64 were also reduced in expression in htz1 Δ ( Figure 6 A). This remarkably large overlap is highly significant ( p = 2.9 × 10 −80 , calculated using the hypergeometric distribution) and even more impressive for telomere-proximal genes. These data suggested that Swr1p and H2A.Z shared a common function in regulating gene expression. Figure 6 Relationship of Genes Activated by Swr1p or H2A.Z (A) The Venn diagram of number of genes that exhibited a significant decrease in expression in swr1 Δ cells (this work) or htz1 Δ cells ( Meneghini et al. 2003 ), revealing a large overlap. Shown on the top is the relationship for the genome overall and on the bottom for genes within 20 kB of a telomere. H2A.Z-dependent genes whose expression could not be determined in swr1 Δ cells were omitted. (B) A color representation of all genes that were significantly reduced in expression in swr1 Δ cells only, htz1 Δ cells only, or both, grouped according to (A). Each column represents data from an independent microarray experiment that compared genome-wide expression in mutant cells of the indicated genotype to wt cells. Each row represents the changes in expression of a single gene across the eight experiments. Change in expression measured as the log 2 of the mutant/wt expression ratio is indicated according to the color scale shown. Red cells refer to genes found to have increased expression in either swr1 Δ cells or htz1 Δ cells that decreased in expression in the other mutant. Excluded from representation are genes that increased expression in both mutants. A substantial number of H2A.Z-dependent genes (116) did not appear to require Swr1p for expression. A color representation of the swr1 Δ and htz1 Δ datasets grouping the genes described in Figure 6 A ( Figure 6 B) revealed that a subset of these appeared to have mildly reduced expression levels in swr1 Δ cells but were not reduced enough to meet the stringent significance cutoff. However, there also were clear examples of genes that required H2A.Z for expression but not Swr1p. Likewise, there were clear examples among the 94 genes that required Swr1p for expression but did not require H2A.Z ( Figure 6 ). Swr1p Was Required for H2A.Z Deposition In Vivo The evidence linking H2A.Z and Swr1p function and the association of both H2A.Z and H2B with SWR1-Com suggested that SWR1-Com was responsible for depositing H2A.Z onto chromatin in vivo, perhaps in the form of an H2A.Z/H2B dimer. (The Swr1p relatives in the ACF and RSF complexes perform related roles in assembling chromatin in vitro (reviewed in Haushalter and Kadonaga 2003 ). If so, then cells lacking Swr1p should display reduced levels of H2A.Z in chromatin. To test this prediction, we performed chromatin immunoprecipitation (ChIP) experiments comparing wild type to swr1 Δ strains expressing a functional amino-terminal triple-HA-tagged version of H2A.Z expressed from the HTZ1 promoter at the normal chromosomal locus (HA3-H2A.Z). Consistent with H2A.Z being in a stable complex with Swr1p that protected it from protein degradation, the level of HA3-H2A.Z in swr1 Δ strains was reduced approximately 2- to 3-fold ( Figure S2 ). To normalize the signals from each experimental locus assayed, we measured the levels of DNA derived from a control locus whose expression is H2A.Z independent (the middle of the PRP8 open reading frame [ORF]) in samples derived from each whole cell extract and precipitate (see Materials and Methods ). We first examined HA3-H2A.Z levels at two chromosomal regions where H2A.Z prevents the spread of Sir-dependent silencing: one flanking the silent mating locus HMR and another near the telomere on the right arm of chromosome XIV ( Figure 7 A). In wild type, H2A.Z was present at levels similar to those described previously ( Figure 7 B); HA3-H2A.Z was depleted from the silenced HMR locus and enriched in the flanking euchromatic regions ( Figure 7 B). In addition, HA3-H2A.Z was depleted from the most telomere-proximal locus tested, AAD3, presumably because of telomeric silencing of this gene. Likewise, HA3-H2A.Z was highly enriched at the YNR074C gene, a telomere-proximal gene on chromosome XIV strongly protected from silencing by H2A.Z. Figure 7 ChIP Analysis of HA3-H2A.Z Deposition in the HMR Region and Near the Right Telomere of Chromosome XIV (A) Location of PCR primers. (B) ChIP results in wild type (bars indicate relative enrichment versus a probe in the PRP8 ORF; standard errors are shown). The ChIP enrichment signal at HMR relative to PRP8 being less than 1.0 indicated some H2A.Z deposition occurred at the PRP8 control region. (C) ChIP results in swr1 Δ cells. In striking contrast, in swr1 Δ cells, the enrichment (relative to the PRP8 locus) of HA3-H2A.Z at every locus tested approached a ratio of one ( Figure 7 C). These data were consistent with Swr1p being essential for the deposition of H2A.Z in the HMR region and near the right telomere of chromosome XIV. However, because the ChIP measurements were normalized to the PRP8 locus, we considered the possibility that a uniform amount of HA3-H2A.Z remained at all chromosomal loci examined in the mutant, for instance if there was a specific increase in the association of HA3-H2A.Z with the PRP8 locus rather than a decrease at all other loci. This possibility was discounted by the approximately 13-fold mean decrease in the ratio of DNA obtained from the pellet versus whole cell fractions in swr1 Δ cells relative to wild type, indicating a substantial defect in the absolute chromatin association of HA3-H2A.Z in cells lacking Swr1p. H2A.Z is also deposited at several loci that are not near silenced regions ( Meneghini et al. 2003 ). The function of H2A.Z at these regions is unknown. To determine if Swr1p was also required for H2A.Z deposition at such loci, we examined H2A.Z levels at 12 euchromatic regions on chromosome III that each displayed some level of deposition of HA3-H2A.Z ( Figure 8 A). These loci were identified in a comprehensive study of H2A.Z deposition on chromosome III (M.D.M., M. Bao, H.D.M., unpublished data). As with the regions examined above, the relative ChIP enrichment of HA3-H2A.Z approached one at each of these loci in the absence of Swr1p ( Figure 8 B), and the absolute amount of DNA precipitated from these loci showed a large decrease in the swr1 Δ mutant (data not shown). Thus, Swr1p was broadly required for the deposition of HA3-H2A.Z, even in regions distant from silenced domains. It is worth noting that for several of the loci examined in the swr1 Δ mutant, the ChIP enrichment was significantly less than one, suggesting that there may exist some residual deposition of HA3-H2A.Z at the PRP8 locus in these cells. Figure 8 ChIP Analysis of H2A.Z Deposition at Nontelomeric Euchromatic Sites (A) ChIP results in wild type. (B) ChIP results in swr1 Δ cells. We detected a reduced enrichment of H2A.Z at all these loci when we estimated the absolute H2A.Z abundance by dividing the amount of immunoprecipitated DNA by the amount of total input DNA for each locus. NuA4 Function Was Required for SWR1-Com to Support Cell Growth The sharing of four proteins between the SWR1-Com and NuA4 (see Figure 1 ) raised the possibility that SWR1-Com was functionally linked to NuA4, which is the major HAT for histones H4 and H2A. Initial purifications from Yaf9-TAP and Swc4-TAP strains suggested that the protein encoded by the nonessential gene YDR359C was a subunit of NuA4, consistent with some earlier results from high-throughput studies ( Gavin et al. 2002 ). Initial efforts to fuse a triple HA-tag to the carboxy-terminus of YDR359C were unsuccessful, but we noticed that all proteins encoded by YDR359C orthologs from the Saccharomyces sensu strictu strains had a carboxy-terminal extension of approximately 22 amino acids, suggesting a possible error in the S. cerevisiae sequence. Therefore, we chose to integrate a triple HA-tag at the chromosomal location that corresponded to the second-to-last codon of the sensu strictu strains and found that this version was now successfully tagged. Recently, a revised copy of YDR359C with the stop codon at the location we chose was deposited in GenBank and named EAF1 . Therefore, we used this name here rather than a previously assigned name for the shorter version of YDR359C. Eaf1p contained a SANT domain as well as an HSA domain that is associated with SANT domains and found in helicases ( Letunic et al. 2002 ). Analytical-scale affinity purifications showed that Eaf1-HA, similar to Tra1p, copurified with Yaf9-TAP, Swc4-Tap, and Esa1-TAP but not with H2A.Z-TAP and Swr1-TAP ( Figure 9 A). In addition, global H4 acetylation defects were evident in eaf1 Δ but not in htz1 Δ, yaf9 Δ, or swr1 Δ cells ( Figure 9 B). This was based on the reduced signal in immunoblot experiments obtained with an antibody directed against tetra-acetylated H4. Similar experiments with antibodies directed against individual acetylated residues revealed that the H4 acetylation defect of strains lacking EAF1 was most profound on K8 and K12 of H4, whereas K5 and K16 of H4 were less affected ( Figure 9 B). Similarly, K9 of H2A did not have a strong acetylation defect in any of the mutants ( Figure 9 B). The physical association and the H4 acetylation defects provided independent evidence that Eaf1p was a subunit of NuA4. Figure 9 Eaf1p Was a Subunit of the NuA4 HAT (A) Eaf1-HA associated with NuA4 subunits. Immunoblots of analytical-scale TAP purifications are shown. The captured TAP-tagged protein is indicated above the gels, and the protein that was tested for association is indicated at the right. (B) Strains lacking EAF1 have defects in histone H4 acetylation. Whole cell extracts from mutant strains indicated on the top were tested for global histone acetylation using antibodies directed against different forms of acetylated H4 and H2A as indicated on the right. To explore genetic links between SWR1-Com and NuA4, phenotypic and double mutant analyses were performed. SWR1-Com mutants and the strain lacking EAF1 shared sensitivities to genotoxic and stress conditions ( Figure 10 A). The eaf1 Δ strains were also slow growing whereas the other strains were not. All mutant strains tested were sensitive to the DNA replication inhibitor hydroxyurea (HU) and the microtubule poison benomyl and to caffeine and formamide, reagents that elicit a number of cellular responses ( Figure 10 A). Strains lacking HTZ1 and YAF9 were comparably sensitive to HU and formamide, but htz1 Δ strains were more sensitive to benomyl and caffeine. Strains lacking SWR1 were less sensitive than the other strains to HU and formamide, but the sensitivity to caffeine and benomyl was comparable to that of yaf9 Δ strains ( Figure 10 A). Cells lacking the NuA4 subunit Eaf1p were most sensitive to HU and caffeine, and their sensitivity to benomyl and formamide was comparable to that of htz1 Δ mutants ( Figure 10 A). While the severity of the defects varied, the similar phenotypes of mutants in SWR1-Com and NuA4 suggested that the two complexes were broadly required for resistance to DNA damage and genotoxic stress. Figure 10 NuA4 and SWR1-Com Shared Similar Phenotypes and Interacted Genetically (A) SWR1-Com and Eaf1p were required for resistance to DNA damage and genotoxic stress. Ten-fold serial dilutions of strains from a stationary overnight culture with the indicated deletions of SWR1-Com subunits and of EAF1 were plated and incubated at 30 °C for 2–3 d. YPD plates with the following concentrations of chemicals were used: 100 mM HU, 10 μg/ml of benomyl, 2% formamide, or 3 mM caffeine. (B) SWR1-Com and NuA4 interacted genetically. Double mutants, deduced from genetic analysis of the viable spore clones, are circled, with the two mutations of interest in each cross indicated at the side. All double mutants were inviable. To test whether the sensitivity to DNA damage and genotoxic stress was a shared function of SWR1-Com and NuA4, or whether these sensitivities were caused by independent functions, double mutant analysis was performed using the EAF1 gene as an exemplary NuA4 subunit. No viable spores were obtained that had deletions of EAF1 and HTZ1 , SWR1, or YAF9 ( Figure 10 B). Thus, SWR1-Com and NuA4 interacted genetically, and the two complexes shared at least one essential function. Discussion Protein complexes that can substitute canonical histones with variant histones represent a fundamental mechanism for regulating the functional state of chromatin. Previous work has identified large protein complexes that assemble, remodel, and modify chromatin (reviewed in Becker and Horz 2002 ; Peterson 2002 ). In contrast, the studies described here identified a novel complex, referred to as SWR1-Com, whose putative ATPase, Swr1p, promoted the deposition of the histone H2A variant, H2A.Z, into chromatin in vivo. SWR1-Com, a Multisubunit Complex, Associated Specifically with H2A.Z SWR1-Com was identified by its specific association with H2A.Z. SWR1-Com consisted of 13 subunits: six were only found in SWR1-Com, four were shared between SWR1-Com and NuA4, and four were shared between SWR1-Com and the Ino80 complex. Two subunits, Arp4 and actin, were in all three complexes (see Figure 1 ). Several of the subunits of SWR1-Com contained motifs highly suggestive of a role for this complex in affecting chromatin structure. Chief among these was Swr1p, a relative of the ATPase-containing subunit of the Swi2/Snf2 ATP-dependent chromatin remodeling enzyme complex ( Pollard and Peterson 1998 ). The Swc4p subunit contained a SANT domain, suggested in other contexts to mediate association of proteins with histone tails ( Boyer et al. 2002 ; Sterner et al. 2002 ). Similarly, Bdf1p contained two bromodomains that preferentially bind to acetylated tails of histones H3 and H4 ( Ladurner et al. 2003 ; Matangkasombut and Buratowski 2003 ). The Swc6p subunit contained a HIT domain found in a human protein that binds to steroid receptors ( Lee et al. 1995 ), and the Yaf9p subunit contained a YEATS domain found in several proteins involved in chromatin modification, such as the SAS-I HAT complex, and several proteins implicated in human leukemias ( Xu et al. 1999 ; Le Masson et al. 2003 ). The weak interactions between SWR1-Com subunits and H2A relative to those between SWR1-Com subunits and H2A.Z suggested that the role of SWR1-Com was dedicated to those chromatin structures enriched for H2A.Z. This was further supported by the association of H2B-HA along with H2A.Z-HA with highly purified SWR1-Com, suggesting that this histone dimer was the physiological substrate for activity of SWR1-Com. Genome-Wide Expression Profiles and Phenotypic Analysis Identified Functional Links between H2A.Z and SWR1-Com Similarities between the consequences of disruptions of SWR1-Com function and loss of H2A.Z protein implied that SWR1-Com was required for H2A.Z function. These similarities included the striking sensitivities of cells lacking SWR1-Com function or H2A.Z to a variety of cellular and genotoxic stresses. Comparison of the genome-wide expression profiles of swr1 Δ and htz1 Δ strains also revealed similar responses to loss of either function at many loci. These included silencing of genes near telomeres and the HMR silent mating type locus, which is antagonized by H2A.Z ( Meneghini et al. 2003 ). In addition, there were genes distal to silenced domains that required both H2A.Z and Swr1p for their expression. Because the majority of gene expression defects seen in swr1 Δ cells also occurred in htz1 Δ cells, the role of Swr1p, and presumably SWR1-Com, was predominantly in promoting the function of H2A.Z. H2A.Z Deposition into Chromatin was Promoted by SWR1-Com SWR1-Com promoted the deposition of H2A.Z into chromatin. At 20 sites flanking the silent HMR locus that were previously identified as enriched or depleted for H2A.Z, the ratio of H2A.Z at these loci relative to the PRP8 ORF as determined by ChIP converged to unity in swr1 Δ cells. In addition, a dramatic 13-fold decrease in the absolute enrichment of HA-H2A.Z-associated DNA was observed in swr1 Δ cells. A similar picture emerged from the analysis of 12 sites of H2A.Z deposition across chromosome III. Therefore, Swr1p was required for enrichment of H2A.Z at a wide variety of loci, including those distal to silent regions. Several lines of evidence suggested that Swr1p and presumably SWR1-Com play direct roles in H2A.Z deposition into chromatin. Foremost in favor of this view is the tight physical association of H2A.Z with SWR1-Com in whole cell extracts. Additionally, Swr1p, and other members of SWR1-Com, had sequence motifs found in proteins acting in chromatin and were localized in the nucleus. In particular, the Bdf1 protein via its bromodomains might be responsible for the recruitment of SWR1-Com to deposit H2A.Z to euchromatic regions, which are generally characterized by acetylation of the H4 tail. Lastly, the profound defect of swr1 Δ cells in H2A.Z deposition, and the established actions of the Swi2/Snf2 family members directly on nucleosomes, provided further support for a direct role of Swr1p and SWR1-Com in H2A.Z deposition. Several observations were consistent with a small amount of H2A.Z deposition in chromatin in cells lacking Swr1p function. First, some genes affected by htz1 Δ were not affected by swr1 Δ. Second, the enrichment of H2A.Z at some loci relative to the PRP8 ORF was less than unity in the swr1 Δ mutant, suggesting residual H2A.Z present at PRP8 . Perhaps in the absence of SWR1-Com, some H2A.Z is deposited by the same mechanisms responsible for the bulk deposition of H2A. Nevertheless, the key observation was a pronounced deficiency in H2A.Z deposition in the absence of Swr1p function. The conservation of Swr1p orthologs raises the possibility of SWR1-Com-like complexes dedicated to the deposition of variant histones in other organisms. The Drosophila Domino protein, human SRCAP, and human p400 are orthologs of SWR1 , and serve as candidates for the founding members of such complexes. Mutations in Domino affect silencing by Polycomb proteins, although the directness of these effects is unknown ( Ruhf et al. 2001 ). The SRCAP protein is associated with CREB-binding protein, and p400 is recruited by the Adenovirus E1A oncoprotein ( Johnston et al. 1999 ; Fuchs et al. 2001 ). Although SRCAP and p400 are known primarily as transcription factors, our results suggest possible roles for these proteins in deposition of variant histones. While this work was under review, two groups independently reported on the SWR1-Com and described its role in H2A.Z deposition ( Krogan et al. 2003 ; Mizuguchi et al. 2004 ). Consistent with our data, purified SWR1-Com has a Swr1p-dependent histone exchange activity ( Mizuguchi et al. 2004 ) and hence presents a third mechanism of chromatin remodeling. SWR1-Com and NuA4 Function Were Linked The SANT-domain-containing proteins Swc4p and Eaf1p were subunits of NuA4, newly described here. Both proteins associated with other NuA4 subunits, and cells lacking EAF1 had defects in global histone H4 acetylation. Similar defects were found in a strain carrying a conditional allele of the essential SWC4 gene (M.S.K., H.Xu, C. Boone, and J.R., unpublished data). Whereas Swc4p was shared with SWR1-Com, Eaf1p was not. However, cells lacking EAF1 were sensitive to DNA-damaging drugs and genotoxic stress conditions, as were cells lacking subunits of SWR1-Com and H2A.Z. While NuA4's involvement in DNA damage survival was known ( Bird et al. 2002 ; Choy and Kron 2002 ; Boudreault et al. 2003 ), the data presented here extended this view, suggesting that it might be more broadly required in the maintenance of genomic integrity in concert with SWR1-Com. Genetic interactions between EAF1 and three SWR1-Com subunits uncover a deeper connection. Specifically, the synthetic lethality of eafl Δ in combination with null alleles of SWR1-Com indicated that these complexes were likely to share an essential function. That is, genes encoding subunits of SWR1-Com became essential when NuA4 activity was compromised by deletion of EAF1, and vice versa. While understanding the mechanisms will require further work, these data suggested important functional links between the H2A.Z deposition machinery and the NuA4 HAT. Why Do SWR1, NuA4, and Ino80 Complexes Share Subunits? As discussed above, a third of the subunits of SWR1-Com are shared with the Ino80 complex, the NuA4 HAT, or both. While the sharing of subunits between different protein complexes is not unprecedented, it may reflect highly related functions, rather than vagaries of chance and circumstance in evolution. This was supported by the functional overlap and genetic interactions between SWR1-Com and NuA4. The shared subunits may act as a core scaffold, upon which the unique subunits can be assembled and exchanged during a cycle of chromatin modification. This notion finds some support in the existence of a mini-NuA4 complex, known as piccolo NuA4, which contains only some of those subunits that are unique to NuA4 ( Boudreault et al. 2003 ). Shared subunits of SWR1-Com could coordinate the recruitment of an analogous mini-SWR1-Com to achieve histone subunit replacement, with the replacement of mini-SWR1-Com by piccolo NuA4 to achieve the acetylation of the newly reconstituted nucleosome. This model could explain why two subunits of NuA4 (Tra1 and Epl1p) were detected in the H2A.Z-associated material under low stringency conditions (see Table 1 ). Alternatively, the acetylation of H2A by NuA4 may facilitate its replacement by H2A.Z. Other orders of action involving the SWR1-Com, NuA4, and Ino80-C complex are also possible, such as acetylation of H2A.Z by NuA4 being a prerequisite for its exchange by SWR1-Com. Other potential roles for the sharing of subunits include targeting complexes to common locations or promoting their biogenesis or assembly. Our data may resolve an interesting paradox concerning the localization of Bdf1p on chromatin. Earlier work showed that Bdf1p is a subunit of TFIID, yet Bdf1p was found in regions where TATA box binding protein, the core subunit of TFIID, was not ( Matangkasombut and Buratowski 2003 ). The discovery that Bdf1p is part of two distinct complexes, SWR1-Com and TFIID, explains the lack of a perfect correspondence between Bdf1p and TATA box binding protein localization. Materials and Methods Yeast techniques Strains are listed in Table S2 . Sequences encoding the TAP-tag ( Rigaut et al. 1999 ) or a triple HA-tag ( Longtine et al. 1998 ) were integrated in frame at the 3′ end of genes using homologous recombination and one-step gene integration of PCR-amplified modules. Similarly, complete deletion of genes was achieved by a similar strategy as described before ( Longtine et al. 1998 ). Large-scale affinity purifications Purifications of native protein complexes were performed using extracts from strains with a segment encoding the TAP tag fused in-frame to the 3′ end of the chromosomal gene of interest ( Rigaut et al. 1999 ). In general, purifications were performed from extracts obtained from 2 l cultures that were harvested in late logarithmic phase. Our protocol for the initial purifications presented in Table 1 was modified from published protocols in a way to maximize recovery of intact protein complexes. Briefly, cells were disrupted with a coffee grinder in the presence of dry ice pellets and resuspended in 0.8 volumes/weight of TAP-B1 (50 mM Tris-Cl [pH 7.8], 200 mM NaCl, 1.5 mM MgAc, 1 mM DTT, 10 mM NaPPi, 5 mM EGTA, 5 mM EDTA, 0.1 mM Na 3 VO 4 , 5 mM NaF, Complete Protease inhibitor cocktail [Roche, Basel, Switzerland]). Crude extracts were prepared by centrifugation in a SS34 rotor for 20 min at 14,000 rpm. These were then further clarified by ultracentrifugation (Ti70 rotor, 33,500 rpm for 60 min). NP-40 was added to a final concentration of 0.15%, and the extract was incubated with 200 μl of IgG Sepharose beads (Amersham Biosciences, Little Chalfont, United Kingdom) for 90 min at 4 °C. The beads were then washed with 800 μl of TAP-B2 (50 mM Tris-Cl [pH 7.8], 200 mM NaCl, 1.5 mM MgAc, 1 mM DTT, 0.15% NP-40). After washing, the TAP tag was cleaved by adding 10 μl of TEV protease (GIBCO, San Diego, California, United States) in 200 μl of TAP-B2 to the beads and incubating at 16 °C for 90 min. Cleaved protein complexes were eluted with an additional 200 μl of TAP-B3 (50 mM Tris-Cl [pH 7.5], 200 mM NaCl, 1.5 mM MgAc, 1 mM DTT, 4 mM CaCl 2 , 0.15% NP-40) The material eluted by the TEV protease cleavage from the first affinity matrix was incubated with 200 μl of Calmodulin beads (Stratagene, La Jolla, California, United States) for 60 min at 4 °C. Beads were washed with 400 μl of TAP-B4 (50 mM Tris-Cl [pH 7.8], 200 mM NaCl, 1.5 mM MgAc, 1 mM DTT, 2 mM CaCl 2 , 0.15% NP-40) followed by 200 μl of TAP-B5 (50 mM Tris-Cl [pH 7.5], 200 mM NaCl, 1.5 mM MgAc, 0.5mM CaCl 2 ). Finally, the proteins were eluted by adding 600 μl of TAP-EB (20 mM Tris-Cl [pH 7.9], 5 mM EGTA) to the beads and incubating for 30 min at room temperature, and were then precipitated with trichloroacetic acid. A similar, but more stringent, procedure was used to purify the complexes shown in Figures 2 A and 4 B. The main differences were an increase in salt concentration to 350 mM NaCl during extraction, column binding, and washing and the amount of washes applied to the columns, which were increased to 40 column volumes at each step. In addition, 10% glycerol was present in all buffers. Protein identification The protein composition of the final fraction resulting from the TAP procedure was determined using Direct Analysis of Large Protein Complexes technology as described previously ( Sanders et al. 2002 ). Briefly, proteins were precipitated and proteolyzed by trypsin. The peptides resulting from the digestion were separated by multidimensional capillary chromatography and subjected to mass spectrometry. Analytical-scale affinity purifications For coprecipitation assays, we prepared extracts from 150 ml yeast cultures harvested at an OD 600 of 1.0. Cells were pelleted, washed with PBS, and resuspended in 0.6 ml of TAP-IPB (50 mM Tris [pH 7.8], 150 mM NaCl, 1.5 mM MgAc, 0.15% NP-40, 1 mM DTT, 10 mM NaPPi, 5 mM EGTA, 5 mM EDTA, 0.1 mM Na 3 VO 4 , 5 mM NaF, Complete TM Protease inhibitor cocktail). Acid-washed glass beads were added, and the cells were disrupted mechanically using a bead beater (BioSpec Products, Bartlesville, Oklahoma, United States) for 5 min. Insoluble material after cell disruption was removed by centrifugation in a microfuge at 14,000 rpm for 20 min. The supernatant was incubated with 25 μl of IgG sepharose beads (Amersham Biosciences) for 90 min at 4 °C. Beads were then pelleted and washed three times with 0.6 ml of TAP-IPB. After washing, the beads were resuspended in SDS sample buffer and subjected to SDS PAGE and immunoblotting with anti-HA-Peroxidase antibody (#2 013 819; Roche) and antibodies against Tra1p (a generous gift from J. Workman), Bdf1p (a generous gift from A. Ladurner), and Act1p (a generous gift from D. Drubin). Microarray expression analysis The strains used for expression analysis were derived from S288c: YM1823 MATα swr1 Δ ::kanMX4 his3 Δ 1 leu2 Δ 0 ura3 Δ 0 lys2 Δ 0 (obtained from the MATα yeast deletion collection; Research Genetics, Huntsville, Alabama, United States) and YM1769 MATα his3 Δ 1 leu2 Δ 0 ura3 Δ 0 lys2 Δ 0. Exponentially growing cultures were diluted to OD 600 0.1 in yeast extract-peptone-dextrose medium (YPD) (Qbiogene, Carlsbad, California, United States) supplemented with tryptophan and adenine. Each mutant culture was paired with a wild-type (wt) culture placed in an adjacent slot in a shaker. Four such pairs of cultures were grown at 30 °C to OD 600 0.8. Cultures were harvested at identical optical densities by vacuum filtration onto nitrocellulose filters (0.45 μm; Millipore, Billerica, Massachuesetts, United States), and snap-frozen in 15 ml conical tubes in liquid nitrogen. Total RNA was extracted as described ( http://www.microarrays.org ), and mRNA was prepared using oligo-dT coupled to latex beads, using the manufacturer's protocol (Oligotex mRNA Mini Kit; Qiagen, Valencia, California, United States). mRNA was then reverse-transcribed into cDNA. Microarrays were fabricated as described by DeRisi et al. (1997 ). Yeast ORFs were amplified using a commercially available primer set (Research Genetics), with yeast genomic DNA as a template. PCR products were verified by gel electrophoresis, precipitated and resuspended in 3X SSC and robotically spotted onto poly-L-lysine-coated glass slides. The exposed poly-L-lysine was then blocked using the succinic anhydride method. Detailed protocols are available at http://www.microarrays.org . After chemical coupling to Cy5 and Cy3 fluorescent dyes, mutant and wt cDNA samples were mixed and hybridized to microarrays at 63 °C for 12–16 h. Two of the four hybridizations were performed with fluor-reversed samples to avoid artifacts arising from differences in coupling efficiency of the two dyes. After washing and drying, the arrays were scanned on a Genepix 4000B scanner (Axon Instruments, Union City, California, United States) and the images analyzed using Genepix 3.0 software to determine the ratio of median fluorescence intensity (above background) for each spot. After flagging poor quality spots, the ratios were normalized for total signal in the two samples. After filtering the data for dim and uneven spots, genes with at least three good measurements were retained for statistical analysis. The swr1 Δ/wt mRNA ratios were analyzed using the SAM (Significance Analysis of Microarrays) statistical package ( Tusher et al. 2001 ) to determine significantly induced or repressed genes. Missing values were estimated using the KNN algorithm with ten nearest neighbors. The analysis was performed with a delta value corresponding to a median false-positive rate less than 1% ( Tibshirani et al. 2002 ). The full dataset is available at http://madhanilab.ucsf.edu/public/swr1 . Chromatin immunoprecipitation ChIP assays were performed and analyzed exactly as described by Meneghini et al. (2003 ) with the following modifications. DNA derived from the whole cell and pellet fractions was analyzed by real-time PCR and Syber Green fluorescence on an MJ Research (Waltham, Massachusetts, United States) Opticon instrument using DNA derived from whole cell extracts as a standard. Oligonucleotides used correspond to those described by Meneghini et al. (2003 ) and those in Table S3 . Histone acetylation assays Yeast whole cell extracts were prepared from cells growing in logarithmic phase by glass bead lysis in the presence of trichloroacetic acid. Equal amounts of whole cell extract were subjected to SDS-PAGE and immunoblotting. The antibodies used were directed against tetraacetylated H4 (#05-698; Upstate Biotechnology, Lake Placid, New York, United States), acetylated K5 of H4 (#AHP414; Serotec, Raleigh, North Carolina, United States), acetylated K8 of H4 (Serotec # AHP415), acetylated K12 of H4 (Serotec #AHP416), acetylated K16 of H4 (Serotec #AHP417), and acetylated K9 of H2A (Upstate Biotechnology #07-289). Supporting Information Figure S1 A Fraction of SWR1-Com Subunits Cosedimented Fractions collected from glycerol gradient centrifugations of whole cell extracts containing HA-tagged SWR1-Com subunits (shown on the right) were analyzed by immunoblot with an anti-HA antibody. The gradients were from 10% to 40 % glycerol and 22 0.1-ml fractions were collected in each case, starting at the top (Fraction 1). A percentage of the total cellular pool of all six SWR1-Com subunits that were tested was present in the same fractions, consistent with their association in one complex. (263 KB PDF). Click here for additional data file. Figure S2 H2A.Z Was Protected from Degradation by SWR1-Com Three different dilutions of whole cell extracts from wt or swr1 Δ strains were tested for levels of 3HA-H2A.Z using an anti-HA antibody. Equal amounts of total protein extract were present at each dilution, as seen by the immunoblot with the antibody against Vma1p. The level of H2A.Z in the swr1 Δ mutant was reduced approximately 2- to 3-fold. This suggested that the SWR1-Com contributed to the stability of H2A.Z, likely by protecting it from protein degradation. (54 KB PDF). Click here for additional data file. Table S1 Peptides in the Rvb2-TAP Purification (54 KB PDF). Click here for additional data file. Table S2 Yeast Strains Used in This Study (95 KB PDF). Click here for additional data file. Table S3 ChIP Oligo Sequences (60 KB PDF). Click here for additional data file. Accession Numbers The Saccharomyces genome database ( http://www.yeastgenome.org ) accession numbers of the proteins discussed in this paper are actin (SGDID S0001855), Arp4 (SGDID S0003617), Asf1p (SGDID S0003651), Bdf1p (SGDID S0004391), CAF-I (SGDID S0006222), Cse4p (SGDID S0001532), Eaf3p (SGDID S0006227), Epl1p (SGDID S0001870), Esa1p (SGDID S0005770), H2A (SGDID S0002633), H2B (SGDID S0002632), Kap114p (SGDID S0003210), Nap1p (SGDID S0001756), Rvb1p (SGDID S0002598), Rvb2p (SGDID S0003118), Rvb2p (SGDID S0006156), SAS-I HAT (SGDID S0005739), Sir2p (SGDID S0002200), Sir3p (SGDID S0004434), Sir4p (SGDID S0002635), Swc2p (SGDID S0002893), Swc3p (SGDID S0000009), Swc4p (SGDID S0003234), Swc6p (SGDID S0004505), Swc7p (SGDID S0004377), Swi2/Snf2 (SGDID S0005816), Swr1p (SGDID S0002742), Tra1p (SGDID S0001141), Yaf9p (SGDID S0005051), and Yng2p (SGDID S0001132). The Saccharomyces genome database accession numbers of the genes discussed in this paper are AAD3 (SGDID S0000704), HML (SGDID S0029214), HMR (SGDID S0029655), HTZ1 (SGDID S0005372) , PRP8 ORF (SGDID S0001208), YDR359C (SGDID S0002767), and YNR074C (SGDID S0005357). The GenBank ( http://www.ncbi.nih.gov/Genbank/index.html ) accession number of EAF1 is AY464183.

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535902

Rhodobacter capsulatus porphobilinogen synthase, a high activity metal ion independent hexamer

Background The enzyme porphobilinogen synthase (PBGS), which is central to the biosynthesis of heme, chlorophyll and cobalamins, has long been known to use a variety of metal ions and has recently been shown able to exist in two very different quaternary forms that are related to metal ion usage. This paper reports new information on the metal ion independence and quaternary structure of PBGS from the photosynthetic bacterium Rhodobacter capsulatus . Results The gene for R. capsulatus PBGS was amplified from genomic DNA and sequencing revealed errors in the sequence database. R. capsulatus PBGS was heterologously expressed in E. coli and purified to homogeneity. Analysis of an unusual phylogenetic variation in metal ion usage by PBGS enzymes predicts that R. capsulatus PBGS does not utilize metal ions such as Zn 2+ , or Mg 2+ , which have been shown to act in other PBGS at either catalytic or allosteric sites. Studies with these ions and chelators confirm the predictions. A broad pH optimum was determined to be independent of monovalent cations, approximately 8.5, and the K m value shows an acidic pK a of ~6. Because the metal ions of other PBGS affect the quaternary structure, gel permeation chromatography and analytical ultracentrifugation experiments were performed to examine the quaternary structure of metal ion independent R. capsulatus PBGS. The enzyme was found to be predominantly hexameric, in contrast with most other PBGS, which are octameric. A protein concentration dependence to the specific activity suggests that the hexameric R. capsulatus PBGS is very active and can dissociate to smaller, less active, species. A homology model of hexameric R. capsulatus PBGS is presented and discussed. Conclusion The evidence presented in this paper supports the unusual position of the R. capsulatus PBGS as not requiring any metal ions for function. Unlike other wild-type PBGS, the R. capsulatus protein is a hexamer with an unusually high specific activity when compared to other octameric PBGS proteins.

Background The enzyme porphobilinogen synthase (PBGS, EC 4.2.1.24) catalyzes the first common step in the biosynthesis of the tetrapyrrole pigments such as heme, chlorophyll, and cobalamin [ 1 ]. PBGS is very highly conserved in sequence and structure but contains a remarkable phylogenetic variation in metal ion usage for catalytic and allosteric functions [ 2 , 3 ]. As of 2003, approximately one-half of the ~130 PBGS sequences available contained the binding determinants for a catalytic zinc ion, and about one-half did not [ 2 ]. On the other hand, approximately 90% of the known PBGS sequences contain the binding determinants for an allosteric magnesium. The only known PBGS sequences that lack the binding determinants for both the catalytic zinc and the allosteric magnesium are in the bacterial genus Rhodobacter [ 2 ]. These atypical PBGS expressed by Rhodobacter sphaeroides and Rhodobacter capsulatus were two of the earliest PBGS enzymes to be characterized in the pioneering work of Shemin and coworkers and were erroneously chosen as representative of PBGS from all photosynthetic organisms [ 4 , 5 ]. However, one distinct difference between the ∝-proteobacteria, of which R. capsulatus is an example, and other photosynthetic organisms is the biosynthetic pathway used to produce the PBGS substrate, 5-aminolevulinic acid (ALA). The ∝-proteobacteria synthesize ALA from succinyl-CoA and glycine while other photosynthetic organisms use glutamic acid to make ALA [ 6 ]. In light of the vast information now available on phylogenetic variations in tetrapyrrole biosynthesis and on the PBGS that require a catalytic zinc and/or that utilize an allosteric magnesium, the current study revisits the PBGS of Rhodobacter capsulatus with emphasis on understanding the enzyme's unique characteristics. Since other PBGS have been shown to absolutely require divalent cations for catalytic activity, and in light of the enhanced purity of modern reagents, it is important to revisit the metal ion requirements of R. capsulatus PBGS to test the predictions of the sequence analysis that suggests the absence of any metal binding determinants. Herein we present evidence that there is absolutely no effect of Zn 2+ or Mg 2+ on the activity of the enzyme and no other metal ions appear to be required for enzyme function. Prior studies have also shown that some PBGS enzymes exhibit a pH rate profile whose pKa value is altered by the presence of monovalent cations [ 7 , 8 ]. Hence, we include an analysis of enzyme activity in relation to pH and monovalent cations. The native holoenzyme quaternary structure for PBGS from most species is a homo-octamer as supported by 18 deposited PBGS crystal structures from yeast, human, E. coli , and Pseudomonas aeruginosa , and noncrystallographic cross-linking data on PBGS from the green plant pea [ 9 - 14 ]. However, an alternative hexameric structural variant was revealed by the crystal structure of a rare allele of human PBGS [ 15 ]. The hexameric structure suggests a functional relationship between binding of the allosteric magnesium of most PBGS and a putative hexamer-octamer distribution that serves as the structural basis for allosteric regulation of enzyme function [ 15 ]. In the absence of the binding sites for either catalytic or allosteric metal ions we investigated the oligomeric structure of R. capsulatus PBGS, and results suggest that the protein is a homo-hexamer. We present a homology model of the hexameric R. capsulatus PBGS structure. Results Cloning and sequencing The cloning of the hemB gene (which encodes PBGS) from R. capsulatus was accomplished by PCR using primers based upon the sequence of Indest and Biel [[ 16 ], GenBank accession U14593]. The sequence of the cloned gene differed from that published previously. Figure 1 presents an alignment of the predicted polypeptides based on the published R. capsulatus and R. sphaeroides sequences (GenBank accession number AAL 26883) as well as the sequence determined from our PCR product (GenBank accession number AY618996). The changes in the predicted polypeptides are due to three differences that we observe when comparing the nucleotide sequence determined herein with the published sequence: a deletion of G at position 425, an insertion of an A at position 468, and reversal of the AC at positions 643–644 to CA. The first two sequence differences result in alteration of the predicted amino acid sequence from amino acids 72 to 86. The third sequence difference alters the amino acid at position 145 from leucine to isoleucine. Based on the aligned polypeptide sequence, the newly determined sequence appears more homologous to R. sphaeroides PBGS, and hence is deduced to be the correct sequence. Figure 1 PBGS Protein Sequence Alignment. Amino acid sequences as predicted from published DNA sequences for R. capsulatus PBGS and R. sphaeroides PBGS as well as the PCR product sequences from our genomic R. capsulatus DNA (labeled as revised sequence). Sequence identity between all three sequences is boxed. The regions where the published R. capsulatus sequence and the sequence we determined differ are indicated with an asterisk below those amino acid positions. In these regions, a black background indicates where sequence matches occur between the revised sequence for R. capsulatus PBGS and R. sphaeroides PBGS, but not for the previously published R. capsulatus PBGS sequence. Expression and purification As demonstrated in Figure 2 , we were able to express and achieve substantial purification of R. capsulatus PBGS. The specific activities of the ultracentrifuge supernatant, redissolved ammonium sulfate pellet, phenyl-sepharose pool, DEAE pool, and concentrated S-300 pool were 130, 250, 212, 176, and 364, μmol h -1 mg -1 respectively. We suspect that some of this variation is due to a protein concentration dependence to the specific activity (see below). The enzyme has an apparent molecular weight that is in agreement with the predicted mass of 35.8 kDa (Figure 2 ). Based on SDS-PAGE and silver staining, the protein appears to have been purified to homogeneity. Figure 2 SDS-PAGE (4–20%) of PBGS Purification Steps. Lane M is marker; lane 1 is Crude Extract; lane 2 is Ultracentrifuge supernatant; lane 3 is 25% ammonium sulfate pellet; lane 4 is pooled Phenyl-Sepharose fractions; lane 5 is pooled DEAE fractions; and lane 6 is pooled S-300 fractions. Protein concentration dependence of the specific activity Other PBGS that lack the catalytic zinc ion binding site have been shown to exhibit a protein concentration dependence to the specific activity [ 7 - 9 ] This unusual phenomenon indicates that a maximally active oligomer can dissociate into less active smaller units. A protein concentration dependent specific activity is illustrated for R. capsulatus PBGS in Figure 3 . The maximal R. capsulatus PBGS activity, ~450 μmol h -1 mg -1 , is the highest ever seen for a purified PBGS, and the lowest R. capsulatus PBGS activity, ~150 μmol h -1 mg -1 , shows that the smallest oligomeric structure retains significant activity. As shown in Figure 3 , the activity of the smaller unit is significantly different from what is documented for PBGS that lack the catalytic zinc but contain the allosteric magnesium binding site; in those instances, the smallest oligomers are inactive [ 7 , 9 ]. Kinetic characteristics described below use protein concentrations varying from 0.15–15 μg ml -1 and this variation does not appear to effect the pK a values apparent from the pH rate profiles, the K m values, or the effects of metal ions or metal ion chelators, which suggest that these properties are more or less the same for the largest and smallest oligomer. Figure 3 Protein Concentration Dependence to R. capsulatus PBGS Specific Activity. Protein was varied from 0.01 μg ml -1 to 40 μg ml -1 and assay times used were 5 min (○) and 1 h (□) with the purified R. capsulatus enzyme. The solid line represents a hyperbolic fit to the activity data presented for the combined 5 min and 1 h assays. The final pH for the R. capsulatus assays was 8.3 in BTP-HCI. For comparison, protein concentration curves are presented from previous experiments for B. japonicum PBGS (+) [7] and P. sativum PBGS (Δ,) [9] and the hyperbolic fits are presented as dotted and dashed lines respectively. Kinetic characteristics Metal ion requirements of purified R. capsulatus PBGS were determined and the results confirm that the Rhodobacter enzyme is different in its response to a variety of cations compared to most known PBGS enzymes. At a protein concentration of ~1 μg ml -1 there is no significant stimulation or inhibition of R. capsulatus PBGS by the addition of Zn 2+ or Mg 2+ ions. The presence of Zn 2+ , up to 100 μM, caused no change in activity and inclusion of 10 mM Mg 2+ resulted in 86% activity. There is also no apparent inhibition by the addition of 10 mM EDTA or by pretreatment with Chelex resin. Inclusion of 1,10-phenanthroline from concentrations of 10 μM – 10 mM had no effect on R. capsulatus PBGS activity. The purified enzyme was tested for the presence of zinc and magnesium by atomic absorption spectroscopy; under conditions where it would have been possible to detect as little as 0.05 metal ion per subunit, none were detected. Previous experiments with a wide variety of PBGS enzymes suggest that monovalent cations can affect the activity of the enzyme. Such cations were clearly shown to shift the pH rate profile for some PBGS [ 7 , 8 ]. Results presented in Table I (data obtained at ~1 μg protein ml -1 ) suggest that there is little if any effect of the monovalent cations K + , Na + or NH 4 + over a wide range of concentrations (0–100 mM). Figure 4 shows that inclusion of 0.1 M KCl has no significant effect on the pH rate profile at 15 μg ml -1 protein concentration. Table 1 Monovalent cation effects. Samples were pre-incubated with various concentrations of chloride salts of the monovalent cations and then assayed using the standard procedure. Reported values and standard errors are triplicate absorbances at 555 nm. Concentration of Salt (mM) 0 1 5 10 50 100 KCl 0.270 ± 0.019 0.268 ± 0.006 0.271 ± 0.002 0.261 ± 0.007 0.269 ± 0.003 0.310 ± 0.014 NaCl 0.302 ± 0.006 0.294 ± 0.017 0.292 ± 0.002 0.276 ± 0.012 0.262 ± 0.003 0.268 ± 0.003 NH 4 Cl 0.297 ± 0.022 0.278 ± 0.004 0.279 ± 0.009 0.225 ± 0.001 0.224 ± 0.009 0.220 ± 0.005 Figure 4 pH Rate Profile. The pH rate profile is presented at 10 mM ALA in BTP-HCl in the presence (○) and absence (□) of 0.1 M KCl. Protein was 15 μg ml -1 . The K m (filled tringle) and V max (filled circle) values as a function of pH at (0.15 μg ml -1 ) are given in units of mM and A 555 , respectively. To determine the optimal pH for the enzyme we determined the V max and K m values at ~1 μg ml -1 protein at a variety of pH values as presented in Figure 4 . The results demonstrate that maximal activity was observed around pH 8.0, but the enzyme is still very active over a wide range of pH values. It is also clear that the K m value drastically increases at lower pH values, which is similar to what has been observed for other PBGS enzymes e.g. , human PBGS [ 17 ], E. coli PBGS [ 18 ], or B. japonicum PBGS [ 7 ]. Based on the references cited, the rise in K m at low pH appears to be independent of the metal ion requirements for PBGS. Quaternary structure A recent paper described an alternative quaternary structure for a rare allele of human PBGS. The unprecedented structural change was shown to have significant effects on the enzyme activity [ 15 ]. In contrast to the active octameric human PBGS, a hexameric form observed with the rare human allele was relatively inactive. The interconversion of these two oligomeric structures was related to the allosteric regulation of some non-human PBGS by magnesium. To assess the different oligomerization states possible for R. capsulatus PBGS, a native gel analysis was performed and the gel was stained for enzyme activity followed by Coomassie staining for protein (see Figure 5 ). Previous studies have shown that native gel electrophoresis can give good separation of the quaternary structure forms of PBGS (see also ref [ 19 ]). Four different sized complexes are observed whose mobility fit well to an mixture of dimer, tetramer, hexamer, and octamer (note constant charge/mass ratio). As had been seen before for E. coli PBGS [ 19 ], the distribution of these oligomeric forms is altered by substrate. By comparing samples preincubated without substrate (Figure 5A , lanes 1 and 4) with samples preincubated in the presence of substrate (Figure 5A , lanes 2 and 3) it can be observed that the complex that runs as the smallest form (putative dimer) becomes less prominent and the largest molecular weight complex (putative octamer) becomes visible. It is also interesting to note that no activity is observed for the two smallest complexes (Figure 5B ). Figure 5 Native gel electrophoresis. Part A presents the Coomassie stained gel, part B presents the same gel stained with an activity stain based on the pink color formed by complex of porphobilinogen with Ehrlich's reagent. Lanes 2 and 3 contain enzyme preincubated with ALA, Lanes 1 and 4 do not include ALA in the preincubation buffer. Each lane was loaded with 2.25 μg of protein. Based upon a combination of size-exclusion chromatography and analytical ultracentrifugation, the size of the major complex was determined. The major component in size exclusion chromatography ran at an approximate molecular weight of 220,000 Daltons. The predicted molecular weight for a monomer is 35,856 Daltons so it would appear that R. capsulatus PBGS is predominantly a hexamer. Ultracentrifugation data for samples collected at several speeds were fit well using a single species model and show that the R. capsulatus PBGS is largely a hexamer (Table II ). The molecular weight obtained from a global fit to data collected at 8,000, 10,000, 12,000 and 14,000 rpm is 215,700 ± 9,700 and was largely independent of speed, indicating strong evidence for ideal single species behaviour. Since we do observe a slight trend in decreasing molecular weight with increasing speed, we further analyzed the data by considering more complex two state models (Table III ). The lowest apparent molecular weight from Table II was no smaller than that expected for a hexamer so we mainly considered models with the hexamer and some larger second state. A lack of lower molecular weight species is not surprising since the protein concentration dependence of the activity plateaus at about 1 μM and the loading concentration in the AU is greater than ten-fold higher. As judged by the square roots of variance for the fits of the various models to the data, collected either in dithiothreitol (DTT) or 2-mercaptoethanol (βME), we saw no appreciable improvement in the fits relative to the pure hexamer model. In the one instance where a slight improvement was noted (the hexamer-octamer model for the βME sample), less than 5% of the total absorbance could be ascribed to the octamer, suggesting very little higher order self-association. Prolonged dialysis results in some non-specific aggregation, presumably due to a build-up of oxidized DTT or βME, and may provide an explanation for problems with unwanted aggregation. Finally, we also tested the possibility that the apparent molecular weight from single species analysis might instead reflect a proportionation between an octamer and some smaller species. We were able to rule this out as such models resulted in poorer fits to the data (e.g. a fit to a tetramer-octamer model is shown in Table III ). Table 2 Molecular weight analysis of R. capsulatus PBGS as measured by equilibrium sedimentation. Data were collected at 4°C. The column headings refer to RPM values. All results are in Da. The monomer molecular weight is 35,857 Da. Sample 8000 10000 12000 14000 Overall 12.3 μM (.1 mM DTT) 221,698 222,291 213,584 206,743 215,700 ± 9,700 12.3 μM (1 mM βME) 227,785 230,906 224,189 205,239 220,200 ± 9,100 Table 3 Sedimentation equilibrium model analysis of R. capsulatus PBGS. All numbers reported are the square root of variance (×10 -3 ) from the fits of the various models to the data. The data for all speeds were fit globally to individual models Model (.1 mM DTT) (1 mM BME) single species 10.50 8.20 hexamer 10.49 8.38 6----->8 10.51 8.27 6----->10 10.52 8.32 6----->12 10.54 8.36 4----->8 12.98 9.82 R. capsulatus PBGS hexamer homology model Figure 6 is an illustration of the homology model of hexameric R. capsulatus PBGS based on a model of hexameric P. aeruginosa PBGS (see below). Regions of highest uncertainty are places where alignment of R. capsulatus PBGS and P. aeruginosa PBGS contain insertions and deletions. These regions are illustrated in the Figure; they are all on the solvent exposed surface of the oligomer and thus unlikely to affect subunit interactions. In an attempt to understand why, unlike other PBGS, R. capsulatus PBGS does not predominate as an octamer, we analyzed points of subunit contact in the octamer of the highly homologous P. aeruginosa PBGS. Each P. aeruginosa PBGS monomer contains thirty-six residues that are within 3.2 Å of an adjacent subunit of the octamer. Twenty-five of these residues are identical in R. capsulatus PBGS; eleven are different. The majority of these differences result in a reduced ability in R capsulatus PBGS to form an ion pair or hydrogen bonding interaction at the subunit interface. The differences are tyrosine to phenylalanine or isoleucine, arginine to glutamine or glycine, valine to isoleucine, aspartic acid to asparagine or alanine, histidine to arginine or leucine, and glutamic acid to alanine or asparagine. This analysis is consistent with the observation that the interactions between PBGS subunits are largely hydrophilic in character with ordered water molecules at the subunit interfaces (see Discussion). Figure 6 A homology model for hexameric R. capsulatus PBGS. A) The R. capsulatus PBGS detached dimer model, shown in stereo view, looking down the αβ-barrel domain of subunit A (red), directly into the active site. The two active site lysine residues, implicated in covalent catalysis [13], are shown ball-and-stick. The N and C termini are labeled for subunits B and A respectively. B) The hexamer is composed of three detached dimers, which are shown as ribbon representations and colored shades of red, blue, and green. For the dimer view only, side chains in regions where the model must accommodate deletions and/or insertions are shown as sticks colored as the subunit; amino acids homologous to, but different from those at the hugging dimer interface of P. aeruginosa PBGS are shown in space fill representation. In this representation, the N and C termini are visible for subunits A and B and are labeled in the dimer representation. Discussion Prior to the current work, it appeared that there was a considerable sequence diversion in a 13 amino acid segment between R. capsulatus and R. sphaeroides PBGS. The revised sequence for R. capsulatus PBGS presented shows close homology between the PBGS of the two Rhodobacter species. This is interesting in light of the apparent differences between these enzymes regarding monovalent cation usage. The R. sphaeroides enzyme is reported to be stimulated by monovalent cations [ 5 ], while the R. capsulatus is not affected by monovalent cations. While it was previously tempting to ascribe the difference in response between the enzymes to this region, clearly this is not the case. To further analyze the enzymatic characteristics of the R. capsulatus PBGS, the enzyme was purified after being heterologously expressed in E. coli . The purification has allowed us to carry out definitive experiments on the requirements for R. capsulatus PBGS function. Based on sequence comparisons and known crystal structures for some PBGS, the Rhodobacter PBGS appear to constitute a unique form of the enzyme that does not require metal ions for structure, activity, or allosteric regulation [ 2 ]. Although the original description of the Rhodobacter PBGS enzymes [ 4 , 5 ] did not demonstrate a requirement for metal ions, the reagents of that time period are now known to be contaminated with metal ions, particularly zinc. The current reagents are of better quality, thus allowing us to confirm the metal requirements for R. capsulatus PBGS. R. capsulatus PBGS activity is independent of all metal ions tested. It has been proposed that chloroplast containing photosynthetic organisms use the allosteric regulation of PBGS by magnesium as part of a complex control of the biosynthesis of chlorophyll [ 15 ]. Although Rhodobacter capsulatus makes a similar pigment, bacteriochlorophyll, the PBGS enzyme from this organism does not exhibit any regulation by divalent cations. In the absence of the allosteric magnesium, Rhodobacter must use alternative mechanisms to prevent the accumulation of photoreactive intermediates in the biosynthesis of its physiologically relevant tetrapyrroles. The preferred pH for enzyme function was determined by measuring V max and K m in a systematic fashion. Based upon these analyses, the apparent pH optimum is approximately pH 8.0, but the enzyme demonstrates significant activity from pH 7–9. The K m value at optimal pH is still high (0.5 mM) relative to other PBGS at their optimal pH in the presence of their required metal ions (~150 μM). This suggests that an unknown factor may be required in vivo . Because there have been reports for stimulation of PBGS enzymes from other organisms by the addition of monovalent cations, several monovalent cations were tested for their ability to stimulate enzyme function at the pH optimum. At the pH optimum no stimulation by monovalent cations was observed (see Figure 4 ). The rare human allele for PBGS encoding F12L revealed the possibility for alternative quaternary structures of PBGS that have been proposed to form the basis for allosteric regulation of PBGS that contain an allosteric magnesium binding site [ 15 ]. These types of PBGS are found in all plants, all archaea, and all bacteria except those of the genus Rhodobacter [ 2 ]. Evidence for alternate quaternary forms of PBGS is particularly apparent for those PBGS that contain the allosteric magnesium but do not contain the catalytic zinc, because these forms exhibit a protein concentration dependence to their specific activity as illustrated in Figure 3 [ 7 , 9 , 15 ]. The protein concentration dependence has been proposed to be due to an equilibrium between a fully active octamer and an inactive hexamer [ 15 ], which is consistent with the data for pea and B japonicum PBGS presented in Figure 3 . The data for R. capsulatus PBGS suggests however that the active form of this protein is a hexamer of specific activity ~400 μmol h -1 mg -1 , and that this active hexamer can dissociate into a smaller form that is less active, but not inactive, with a specific activity of ~150 μmol h -1 mg -1 . These observations lead to three interrelated questions. Why does R. capsulatus PBGS associate into a hexamer rather than an octamer; why is the R. capsulatus PBGS hexamer of high activity rather than of low activity; and what is the less active quaternary structure that is in equilibrium with the R. capsulatus PBGS hexamer? To answer these questions, we need to address the factors that govern the interconversion of PBGS quaternary forms and the structural basis for the different activities associated with these different quaternary forms. Crystal structures reveal that those PBGS that readily interconvert between quaternary forms contain subunit-subunit interfaces that are hydrophilic in character. For instance, in the P. aeruginosa PBGS structure, the interaction of the barrel of subunit A and the N-terminal arm of subunit B, which form a hugging interaction, is dominated by hydrogen bonds and buried water molecules. One could argue that this type of subunit-subunit interface can readily dissociate because the protein-protein interactions are similar in energy to aqueous solvation of the protein surfaces [ 20 , 21 ]. A sequence comparison between P. aeruginosa PBGS and R. capsulatus PBGS shows that the amino acids that lie at the hugging dimer interface of the former are of lower hydrogen bonding and ion pairing capacity in the latter, which might explain why R. capsulatus PBGS is not an octamer. As for the functional difference between human octameric and hexameric PBGS, this has been ascribed to the mobility/stability of an active site lid that serves to gate access to solvent [ 15 ]. In that case, destabilization of the lid causes the pH rate optimum for the reaction to shift dramatically toward basic pH and causes a dramatic decrease in affinity for the K m determining substrate molecule since the lid residues form part of the binding site for this substrate [ 15 ]. Consistent with the fact that R. capsulatus PBGS appears to be a hexamer, the pH optimum is basic and the K m is 2 – 3 fold higher than most other PBGS species under their optimal assay conditions. Crystallization trials for R. capsulatus PBGS are currently underway to provide insight into these fascinating questions. Finally, based on the native gel analysis, we propose that the active R. capsulatus PBGS hexamer can dissociate into a less active dimer. Preliminary unpublished results suggest that one can produce an active dimeric species of human PBGS by destabilizing the dimer-dimer interactions that are essential for oligomerization of PBGS into either the hexamer or the octamer. Conclusions The evidence presented in this paper supports the unusual position of the R. capsulatus PBGS as not requiring any metal ions for catalytic function, which may be characteristic of the Rhodobacter genus. Unlike other wild-type PBGS, the R. capsulatus protein is a hexamer. What remains to be determined is how the reaction mechanism for this enzyme might differ from those PBGS that show both an absolute requirement for metal ions and an octameric quaternary structure. Methods Materials Chemicals and buffers were obtained from Fisher or Sigma, in the purest possible form, except where noted below. Ultrafiltration devices used for concentrating protein were obtained from Fisher as were Slide-A-Lyzer dialysis cassettes. Construction of the expression plasmid The DNA encoding PBGS was amplified from R. capsulatus genomic DNA by PCR using oligonucleotide primers (Integrated DNA Technologies) directed to the 5' and 3' ends of the coding region based on published sequence [ 16 ]. The forward primer PBGS 5' (5'-G CATATG ACCCTGATCACCCCCCCC-3') introduced an Nde I site and the reverse primer PBGS 3' (5'-C GGATCC GCGGTCAGGCGCCGATCAGC-3') introduced a Bam HI site. The PCR reaction was performed using a thermocycler from MWG Scientific and Pfu polymerase (Stratagene) with the following program: 45 sec at 95°C, 45 sec at 48°C, 1 minute at 72°C. The resulting PCR fragment was cloned into vector pPCRScript Amp (Stratagene) creating plasmid pPBGS1. The PCR fragment was removed from the vector by digestion with Nde I and Bam HI and ligated into the vector pET11a (Novagen) digested with the same restriction enzymes. The resultant plasmid pPBGS4 was sequenced in the FCCC DNA Sequencing Facility using external and internal primers to confirm the sequence in both directions. For expression, the recombinant plasmid pPBGS4 was transformed into strain BLR (DE3). Enzyme expression and purification A 1 L culture of LB broth with 0.4% glucose was inoculated with a single colony from a fresh transformation and grown for 16 hours at 37°C. The cells were harvested by centrifugation (10 min at 10,800 × g ) and resuspended in fresh LB medium containing no glucose, but with 100 μM isopropyl-1-thio-β-D-galactopyranoside (Research Organics) and grown for 45 hr at 15°C. From this point all steps were performed on ice or at 4°C. Cells were harvested by centrifugation for 10 min at 10,800 × g with a yield of 5.74 g wet weight. The cells were washed with 0.1 M BisTris Propane (BTP, Research Organics) pH 8.5 and then resuspended in 15 ml of 0.1 M BTP pH 8.5 and lysed by two passes through a French Press in the presence of Benzonase™ (Novagen) nuclease and 1 mM AEBSF (Calbiochem). Unbroken cells, inclusion bodies, and debris were removed by centrifugation for 15 min at 21,500 × g . The sample was then ultracentrifuged for 1 hour at 141,000 × g to remove membranes. The enzyme was precipitated from solution by treatment with 25% ammonium sulfate and collected by centrifugation for 20 min at 31,000 × g . The pellet was resuspended in 0.1 M BTP pH 7.0 and loaded onto a 100 ml Phenyl-Sepharose (Amersham Biosciences) column pre-equilibrated in 20% ammonium sulfate, 0.1 M BTP pH 7.0 buffer. The enzyme was eluted from the column with a two column volume gradient running from 20% to 0% ammonium sulfate in 30 mM BTP pH 7.0. The PBGS eluted from the column very close to the end of the gradient. Fractions with specific activity greater than 100 μmol h -1 mg -1 were then pooled and loaded to a 100 mL DEAE-Sepharose column equilibrated in 30 mM BTP pH 7.5 and eluted with a two column volume gradient from 0 to 0.4 M KCl in 30 mM BTP pH 7.0. The fractions with a specific activity greater than 300 μmol h -1 mg -1 eluted near the end of the gradient and were pooled and concentrated using centrifugal concentrators. The concentrated DEAE fraction (0.9 mg ml -1 ) was then loaded on to a 300 mL S-300 column (2.6 cm × 60 cm) (Amersham Biosciences) pre-equilibrated with 0.1 M BTP pH 7.0, and eluted with the same buffer. The fractions with specific activity greater than 185 μmol h -1 mg -1 were pooled and concentrated. The enzyme appeared to be greater than 95% pure based on SDS-PAGE analysis. Enzyme activity assays Enzyme was pre-incubated in 0.1 M BTP pH 8.6 in the presence or absence of various metal ions and other reagents for 10 min at 37°C. Assays were initiated by the addition of ALA-HCl (Aldrich) to a final concentration of 10 mM and were allowed to run for 5 minutes in a final volume of 1 ml. Assays were terminated by the addition of 0.5 ml of 20% TCA. The product was then quantified by reaction of the stopped assay mixture with an equal volume of modified Ehrlich's reagent and measurement of absorbance at 555 nm approximately 8–10 minutes later. All assays were performed in duplicate or triplicate. If the amount of product resulted in an absorbance above 1.0 OD, the stopped assay mixture was diluted prior to the addition of Ehrlich's reagent. Inhibition by 1,10-phenanthroline was carried out as described previously [ 22 ]. Inhibition by Chelex 100 resin (BioRad) was assayed by incubating PBGS in 0.1 M BTP pH 8.5 at 0.05 g resin per mg enzyme, on ice for 4 hours with occasional stirring, followed by centrifugation at 13,000 × g for 5 min to pellet the resin. The resultant enzyme was then assayed. For determination of monovalent cation effects at pH 8.3, the enzyme was first dialyzed against 100 mM BTP pH 8.6. Monovalent cations were added as the chloride salts. Effect of pH For assays performed as a function of pH, the buffer was 0.1 M BTP (initial pH 6–9). For determination of K m and V max as a function of pH, the enzyme was at 0.13 μg ml -1 . Since the substrate is an acid, the actual pH values for assays were determined by running a mock assay without enzyme and measuring the actual pH of the combined reaction. When ALA concentration was varied for determination of V max , the pH of the assay mixture was adjusted with 0.5 M HCl to control the final pH. For determination of the pH rate profile with and without 0.1 M KC1, the enzyme was at 15 μg ml -1 . Gel electrophoresis SDS-PAGE was performed using the Laemmli system and precast 4–20% gradient gels from Cambrex (Rockland, ME). Gels were stained using a silver stain kit from Pierce Chemical (Rockford, IL). Native gels were performed using the same gel system but omitting SDS from all buffers. Activity staining of the gel was performed as described previously [ 19 ]. Following a wash with 20% TCA, the activity stained gel was then stained with Coomassie blue to visualize protein bands. Samples for the native gels were preincubated at a final concentration of 0.15 mg ml -1 for 10 minutes in 0.3 M Tris pH 6.8 with additions of 100 μM Zn, 13 mM ALA or both prior to loading. 15 μl of the preincubated sample was then loaded to each well. Holoenzyme size determination The size of the enzyme was determined both by size exclusion chromatography and by analytical ultracentrifugation (AU). Size exclusion chromatography was performed using a Waters 600 system equipped with a Waters 996 photodiode array for detection of protein elution at 280 nm. The column used was a Superose 6 (10 × 300 mm, Amersham Pharmacia) and was run at 0.5 ml/min with 100 mM BTP pH 8.6 with 100 μL of a 200 μg ml -1 solution. The column was calibrated with standards obtained from the manufacturer. For AU experiments, protein samples were dialyzed against 10 mM Tris-HCl pH 7.7 with either 0.1 mM DTT or 1 mM βME as reducing agent. Although TCEP (Tri(2-carboxyethyl)phosphine) is the preferred reducing agent for such biophysical experiments, we discovered that the oligomeric state was destabilized in the presence of this reagent with other PBGS; weak chelation of divalent cations has been observed for this reagent suggesting a mechanism for this destabilization. Protein loading concentrations were 12.3 μM in monomer (440 μg ml -1 ). Concentrations were determined by UV absorption at 280 nm. The extinction coefficient used for the protein was 29,870 L mol -1 cm -1 and represents the sum of individual tyrosine and tryptophan absorbance coefficients. Sedimentation equilibrium (SE) experiments were carried out at 4°C using a Beckman Optima XL-A analytical ultracentrifuge equipped with an An60 Ti four-hole rotor. Samples were loaded into six-channel charcoal-filled Epon centerpieces. Temperature-corrected partial specific volumes and solution densities were calculated using the Sednterp program [ 23 ]; the solution density was 1.00028 g ml -1 and partial specific volume was 0.7304 ml g -1 . Data analysis was performed using the WinNonlin V.1.060 nonlinear least squares fitting program obtained from the National Analytical Ultracentrifugation Facility at the University of Connecticut. Homology Model Building The only existing crystal structure on which one can base a model of hexameric R capsulatus PBGS is that of hexameric human PBGS clinical variant F12L, PDB code 1PV8 [ 15 ]. Unfortunately, the crystal structure of F12L shows significant disorder, which limits its use as the sole foundation for homology model building. However, comparison of human PBGS octameric and hexameric structures (PDB codes 1E51 and 1PV8) show near identity for the amino acids that comprise a TIM-like αβ-barrel domain. The differences between the octamer and the hexamer are in the 24 N-terminal amino acids and in the disordered regions [ 15 ]. Hence, one can use a higher quality crystal structure of a PBGS octamer for homology model building the αβ-barrel domain of R. capsulatus PBGS. The chosen structure is PDB code 1GZG [ 13 ], which is a highly ordered, high resolution crystal structure of Pseudomonas aeruginosa PBGS, and 56% sequence identical to R. capsulatus PBGS. The model building procedure was a two step process. The first step was construction of a model of a hexameric form of P. aeruginosa PBGS; the second step was to use that hexamer to build the R. capsulatus PBGS hexamer. P. aeruginosa PBGS hexamer preparation used various capacities of the program Swiss-PDB Viewer [ 24 ] and some in-house programs. First, the N-terminal arms (amino acid numbers <32) were removed from the structure file for the 1GZG dimer. The resulting αβ-barrel domains were successively overlaid upon the three dimers of hexameric 1PV8 to create a hexameric assembly of P. aeruginosa PBGS αβ-barrels. There is no significant sequence identity between the N-terminal arms of human and P. aeruginosa PBGS, hence there is an alignment ambiguity when trying to build the outstretched arms of the P. aeruginosa PBGS hexamer. However, there is a region of the arm that is α-helical in both the human octamer and the human hexamer. Hence, a structure alignment of octameric forms of human PBGS and P. aeruginosa PBGS was used to determine the proper sequence alignment for this α-helical segment. This information was used to spatially position the amino acids 22 – 29 of P. aeruginosa PBGS in the hexamer according to the position of this helix in the hexamer of human PBGS. Loop and side-chain prediction was performed in a graphical user environment, developed in the FCCC Molecular Modeling Facility, that integrates the functions of the programs Loopy [ 25 ], and SCWRL [ 26 ]. Within this environment, the program Loopy [ 25 ] was used to model the backbone of amino acids 29 – 32, so as to connect the N-terminal α-helix to the αβ-barrel domain of each subunit. The most N-terminal amino acids were built onto the structure within the Swiss-PDB viewer software using phi, psi, and omega angle information for the corresponding amino acids of hexameric human PBGS. Finally, the program SCWRL [ 26 ] was used to position the side chains for the N-terminal arm segments resulting in a model for hexameric P. aeruginosa PBGS, which could then be used for preparing hexameric models of other PBGS as we have done before for the octameric forms of pea and D. melanogaster PBGS [ 7 , 9 ]. The model for hexameric R. capsulatus PBGS was built using the same integrated graphical environment developed in house. This software integrates sequence alignment, threading, loop model building to accommodate insertions and deletions, and side chain optimization similar to that used for our previously published models [ 7 , 9 ]. Authors' contributions DWB was responsible for the initial cloning by PCR, purification of the enzyme, initial assays of the enzyme, and preparation of Figs. 1 , 2 , and 5 . CC created the expression vector and helped with initial purification and assays. RL was involved in determining the pH dependence of the enzyme. SF performed the native gel electrophoresis experiments and biochemical characterizations. BK and RF performed the analytical ultracentrifugation experiments. LK and EKJ were involved in creating the homology model. EKJ performed much of the writing, supervised some of the biochemical characterization and prepared Figs. 3 , 4 , and 6 .

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529318

The Genetics of Speciation by Reinforcement

Reinforcement occurs when natural selection strengthens behavioral discrimination to prevent costly interspecies matings, such as when matings produce sterile hybrids. This evolutionary process can complete speciation, thereby providing a direct link between Darwin's theory of natural selection and the origin of new species. Here, by examining a case of speciation by reinforcement in Drosophila, we present the first high-resolution genetic study of variation within species for female mating discrimination that is enhanced by natural selection. We show that reinforced mating discrimination is inherited as a dominant trait, exhibits variability within species, and may be influenced by a known set of candidate genes involved in olfaction. Our results show that the genetics of reinforced mating discrimination is different from the genetics of mating discrimination between species, suggesting that overall mating discrimination might be a composite phenomenon, which in Drosophila could involve both auditory and olfactory cues. Examining the genetics of reinforcement provides a unique opportunity for both understanding the origin of new species in the face of gene flow and identifying the genetic basis of adaptive female species preferences, two major gaps in our understanding of speciation.

Introduction During reinforcement, mating discrimination is strengthened by natural selection in response to maladaptive hybridization between closely related taxa ( Dobzhansky 1940 ; Fisher 1958 ). Although reinforcement was a contentious issue in the past ( Butlin 1989 ; Howard 1993 ; Noor 1999 ), recent theoretical work has identified the most favorable conditions for its existence ( Liou and Price 1994 ; Kelly and Noor 1996 ; Servedio and Kirkpatrick 1997 ; Kirkpatrick and Servedio 1999 ; Servedio 2000 ), and empirical data have provided potential examples of its occurrence in nature ( Noor 1995 ; Sæaetre et al. 1997 ; Rundle and Schluter 1998 ; Nosil et al. 2003 ). Theoretical work on reinforcement shows that reproductive isolation may be strengthened when either the same (one) or different (two) alleles conferring mating discrimination spread in the emerging species (Felsenstein 1981). In two - allele models, alleles conferring mating discrimination spread if they become genetically correlated with alleles reducing hybrid fitness. However, the evolution of such a correlation is opposed by recombination because alleles conferring discrimination in a given species do not confer discrimination in the other species. Consequently, two - allele models require either very strong selection, or tight linkage (e.g., physical or via chromosomal rearrangements) between alleles conferring mating discrimination and alleles reducing hybrid fitness ( Kirkpatrick and Ravigné 2002 ). In contrast, one-allele models are not opposed by recombination because alleles conferring mating discrimination reduce hybridization in the genetic background of both species ( Kelly and Noor 1996 ; Servedio 2000 ) and so may be more conducive to reinforcement. Unfortunately, empirical data concerning these two models of speciation are lacking (see Ortíz-Barrientos et al. 2002 ; Servedio and Noor 2003 ). In addition to providing fundamental information for theoretical models, discerning the genetics of reinforcement will also develop our understanding of both the physiological basis of and forces governing changes in female preference. Furthermore, because the strengthening of female preference is driven by natural selection, the genetics of reinforcement will provide unique insights into the genetics of adaptation, another unsettled issue in evolutionary biology. Finally, high-resolution genetic studies of reinforcement can identify candidate speciation genes with effects on mating discrimination, information almost nonexistent in speciation studies (but see, Ritchie and Noor 2004 ). Here, we address these many fundamental issues in speciation by examining a case of reinforcement in Drosophila and present for the first time a high-resolution genetic study of variation within species in female mating discrimination, including a set of candidate reinforcement genes and a discussion of the evolutionary implications of our findings. The North American fruitflies Drosophila pseudoobscura and D. persimilis hybridize in nature and produce sterile male hybrids. While D. pseudoobscura occurs alone in non-coastal western United States and Central America, the two species co-occur in California and the Pacific Northwest. Males court females from both species indiscriminately ( Noor 1996 ), but females mate preferentially with individuals from the same species. The strength of this discrimination is not homogeneous across the species' geographic range: in a previous study, Noor (1995) showed that D. pseudoobscura females derived from populations where D. persimilis was absent exhibited weak mating discrimination (hereafter, “basal mating discrimination”) while females derived from populations where D. persimilis is present exhibited strong mating discrimination (hereafter “reinforced mating discrimination”). This difference in mating discrimination is likely the evolutionary consequence of maladaptive hybridization where the two species coexist: reinforcement has strengthened mating discrimination in the D. pseudoobscura populations co-occurring with D. persimilis . These observations and the recent completion of the genome sequence of D. pseudoobscura (BCM-HGSC 2004) make these species an ideal system to genetically dissect the enhancement of mating discrimination in sympatry. Although the genetics of reinforcement has not been studied in D. pseudoobscura, or in any system, the genetic basis of other traits contributing to the species' reproductive isolation (i.e., hybrid sterility and basal mating discrimination) is known in detail. All traits contributing to reproductive isolation between D. pseudoobscura and D. persimilis, including traits for basal discrimination, map primarily or exclusively to regions bearing fixed chromosomal inversion differences between the species ( Noor et al. 2001a , 2001b ). This result is consistent with a two - allele model of speciation in which the reduction in recombination between alleles for hybrid unfitness (i.e., hybrid sterility) and mating discrimination creates the necessary genetic correlations to advance divergence in the presence of gene flow. However, we do not know whether the genetic basis of reinforced mating discrimination corresponds to this picture, and specifically, whether chromosomal inversions are fundamental to this process. Comparing these genetic architectures will provide the most comprehensive view yet on the genetics of mating discrimination contributing to the formation of new species in the face of interspecies gene flow. Results Female Discrimination Is Dominant and Reinforced in Sympatry Table 1 shows that D. pseudoobscura females derived from sympatry (with D. persimilis ) exhibited stronger mating discrimination against D. persimilis males than did D. pseudoobscura females derived from allopatry. This pattern holds for both inbred and outbred lines. Also, our data show that both sympatric-derived lines and allopatric-derived lines vary considerably in their degree of discrimination ( p < 0.001 for sympatric inbred lines, and p = 0.0006 for allopatric inbred lines), suggesting some within-population variation in female mating discrimination, both basal and reinforced. Table 1 Matings of D. persimilis Males to D. pseudoobscura Females Derived Sympatry or Allopatry Each comparison involves either a sympatric versus an allopatric line of D. pseudoobscura, or F 1 females (allopatric × sympatric) versus sympatric lines. Probability values were derived from Fisher's exact tests using geography (allopatric versus sympatric) and copulation occurrence (yes versus no) as variables O, outbred lines; I, inbred lines; F 1 , first generation offspring from crossing the D. pseudoobscura sympatric and allopatric line 10.1371/journal.pbio.0020416.t001 Apparent reinforced mating discrimination could result from behavioral differences in D. persimilis males when exposed to sympatric or allopatric D. pseudoobscura females. To exclude this possibility, we measured the copulation latency and number of attempted copulations by D. persimilis males towards D. pseudoobscura females derived from sympatry or allopatry, and found no significant differences between groups (copulation latency, p = 0. 736, n = 138; attempted copulations, p = 0. 937, n = 110). Finally, we investigated the mode of inheritance of the phenotype and observed that F 1 females from crosses between sympatric and allopatric flies discriminated as strongly as their sympatric parent, suggesting that reinforced female mating discrimination is inherited as a dominant trait in both inbred and outbred lines (see Table 1 ). This F 1 female mating discrimination is restricted to pairings with D. persimilis males, as F 1 females mate readily with conspecifics (data not shown). Taken together, these results suggest that reinforced mating discrimination in D. pseudoobscura is exclusive to females derived from areas of sympatry with D. persimilis , is inherited as a dominant trait, and is not markedly affected by inbreeding. Within-Species Variation in Reinforced Female Mating Discrimination We investigated within-species variability in reinforced discrimination by estimating the chromosomal contributions to mating discrimination between two pairs of D. pseudoobscura populations. In each case, we performed a male-parent backcross in which a mixture of whole chromosomes from sympatry and allopatry (F 1 genome) was substituted into an allopatric background (F 2 backcross genome) (see Figure 1 , left panel). Each male-parent backcross was also replicated with the reciprocal F 1 cross between parental strains, thus ruling out any maternal effects and providing insight into the effect of the X chromosome on mating discrimination. Figure 1 Experimental Design to Substitute Chromosomes or Chromosomal Regions Derived from Sympatry into an Allopatric Background and Measure Their Effect on Mating Discrimination F 1 male-parent backcrosses (A) allow measurements of whole chromosome effects, while F 1 female-parent backcrosses (B) measure specific chromosomal region effects. Curved arrow represents the reciprocal backcross of the one shown. Our two backcrosses identified different chromosomes as affecting reinforced mating discrimination (binomial test of proportions for effects of all chromosomes, p < 0.01). For example, sympatric X and fourth chromosomes derived from Mather, California (male-parent backcross 1), contribute significantly to reinforced mating discrimination ( p < 0.0001 for X chromosome, p < 0.005 for fourth chromosome, n of approximately 1,000 for all markers), while the same chromosomes show no detectable effect on reinforced mating discrimination when derived from Mt. St. Helena, California (male-parent backcross 2, p = 0.2297, n = 600 for all markers) (see Figure 2 A and 2 B). In contrast, the second chromosome shows the opposite relationship between the two backcrosses. The third chromosome shows marked effects on reinforced mating discrimination in both backcrosses, although at this level of resolution, it is impossible to tell whether this chromosome carries the same alleles in both sympatric populations. Figure 2 C shows the genome composition of backcross females between Flagstaff, Arizona (allopatric), and Mather, California (sympatric), and their respective frequency of matings with D. persimilis males. The strongest effect is observed when both sympatric X and fourth chromosomes are substituted in an allopatric background, and no significant epistatic interactions were detected between chromosomes. Figure 2 Mean Square Chromosomal Effects on Mating Discrimination (A) Male-parent backcross 1 shows the effects of substituting chromosomes derived from Mather, California (sympatry), into a background derived from Flagstaff, Arizona (allopatry). (B) Male-parent backcross 2 shows the effects of substituting chromosomes derived from Mt. St. Helena, California (sympatry), into a background derived from Mesa Verde, Colorado (allopatry). *, p < 0.005; **, p < 0.001; ***, p < 0.0001. (C) Combined chromosomal contributions to female mating discrimination. Small bars on the left represent chromosomes (X, 2, 3, and 4), while long bars on the right show the frequency of matings of backcross females with D. persimilis . These results suggest that different alleles for reinforced mating discrimination are segregating within sympatric populations of D. pseudoobscura despite extensive gene flow within and between populations ( Schaeffer and Miller 1992 ; Noor et al. 2000 ). Fine-Mapping the Genes Causing Reinforcement We measured female mating discrimination against D. persimilis males in 1,500 F 2 individuals derived from a female-parent backcross between a line derived from Mather, California (sympatric line), and a line derived from Flagstaff, Arizona (allopatric line), and genotyped 275 to 1,500 individuals for 70 markers dispersed along the four major chromosomes in D. pseudoobscura . Our initial single-marker analyses revealed significant associations between reinforced mating discrimination and three regions defined by markers located on the right and left arms of the X chromosome (XR and XL, respectively) (XR marker X021, p < 0.0001, n = 1,129; XL marker X002, p = 0.02, n = 1,293) and the fourth chromosome (4034 marker, p < 0.0001, n = 1,434). We were not able to detect an effect of any single region on the third chromosome even though nine markers were surveyed. Effects identified on XR and Chromosome 4 reinforced mating discrimination when the sympatric allele was present (positive), while the effect from XL was negative. After our initial scan, we used composite interval mapping (CIM) to account for any inflated estimates in the absence of background correction. In addition, several markers were genotyped around the X021 and 4034 regions with the goal of refining the segments containing the quantitative trait loci (QTLs). Figure 3 shows the major results from CIM, and confirms our previous observations: one major QTL was identified on XR around X021, and a suggestive one close to the telomere of XL. In addition, one major QTL was found on the fourth chromosome. These results validate our previous findings using male-parent backcross females and provide a high-resolution definition of regions contributing to reinforced mating discrimination. Figure 3 QTLs and Candidate Genes for Reinforced Mating Discrimination Each panel shows CIM estimations of chromosomal region effects on mating discrimination. Arrows point to major QTL locations and are named after their candidate genes. The direction of the chromosomal region effect on mating discrimination is shown in parentheses. The y-axis, LR, is the ratio of the likelihood value under the null hypothesis of no QTL to the likelihood value under the hypothesis that there is a QTL in a given interval of adjacent markers. The likelihood ratio significance threshold reflecting a Type I error of 0.05 is 11.5 s. The indicated inversion is a fixed chromosomal inversion differentiating D. pseudoobscura and D. persimilis. X chromosome: Candidate genes Coy-1 and Coy-3 A more careful examination of the X021 region showed that the QTL location (CIM LOD score = 5. 16), hereafter referred to as Coy-1, is estimated to lie between two additional markers, X021-A1 and X021-A4 (these markers are physically separated by 390 kb and by a recombination fraction of 4.5 centi-Morgans [cM]). According to the recently obtained genome sequence of D. pseudoobscura, there are seven genes between these two markers, one of which, bru-3, accounts for one-third of the sequence length of this region. In addition, CIM also identified another QTL, hereafter referred to as Coy-3, located between markers X021 and X021-B2, although with a weaker effect (CIM LOD score = 2. 84). There are approximately 200 kb and 30 genes between these markers and a recombination fraction of 3.5 cM. Finally, a third QTL was found near the XL telomere and, in contrast to the X021 region, showed a negative and weak additive effect (CIM LOD score = 2. 45). We tested this model for the X chromosome using multiple interval mapping and found that the strongest support is for Coy-1, followed by Coy-3. We were unable to recover any support for the QTL on XL. No epistatic interactions were detected among any QTLs. Chromosome 4: Candidate genes Coy-2 and Coy4 Dissection of the 4034 region using CIM split the effect into two QTLs for reinforced mating discrimination; we refer to them as Coy-2 and Coy-4, respectively. These QTLs show the strongest effects (CIM LOD scores of 7.7 and 7, respectively). As with Coy-1 and Coy-3, these QTL are additive and contribute positively to the degree of mating discrimination of F 2 females. Coy-2 is located next to marker 4034-A8. This marker is within a 300-kb region homologous to a D. melanogaster region containing a p-element insertion disrupting normal olfactory behavior (see Discussion for details) ( Anholt et al. 2001 , 2003 ). The D. melanogaster region contains 30 genes of which at least ten have known or predicted olfactory functions. The primary candidate gene for the disrupted olfactory behavior in the p-element mutant is CG13982 . Interestingly, the D. melanogaster p-element mutation up-regulates expression of bru-3, suggesting a possible functional link between the candidate genes Coy-1 and Coy-2. The second QTL in this region, Coy-4, is defined by two markers, 4003 and 4032, on each side of 4034. CIM places the QTL between 4003 and 4034, an approximately 200-kb region containing only nine genes. Five of these nine genes are a conglomerate of UDP-glycosyltransferases, genes preferentially expressed in the Drosophila antenna and coding for biotransformation enzymes involved in detoxification and olfaction (Wang et al. 2003). However, a more careful examination of the genes shows that their sequence overlap results from the inability of BLAST homology searches to distinguish the members of this gene family, suggesting that there may be only one or few UDP-glycosyltransferase genes here. Consequently, the number of candidate genes in the region may be reduced from nine to five genes, at least one of which is involved in olfaction. As before, we tested this model using multiple interval mapping and recovered significant support for Coy-2 under stringent conditions and no evidence of significant epistasis among previously identified QTLs. Based on these results and those for the X chromosome, we suggest that the strongest evidence for QTLs contributing to reinforced discrimination in sympatry lies with Coy-1 and Coy-2, and that Coy-3 and Coy-4 are suggestive QTLs. Discussion We have provided the first genetic dissection of an adaptive female preference involved in speciation by developing a QTL map for discrimination variation in Drosophila pseudoobscura . The resolution of our approach is novel to genetic studies of behavioral discrimination in that we have surveyed the genome with 70 microsatellite markers for chromosomal regions contributing to increased mating discrimination and have narrowed some of these regions to intervals containing as few as five genes. The role of these genes in reinforcing mating discrimination is supported by indirect evidence from D. melanogaster mutants: two of the major QTLs identified in our mapping experiments bear genes identified in smell impairment screenings of p-element mutants ( Anholt et al. 2003 ). A gene in one of these intervals, CG13982 ( D. melanogaster Chromosome 2L), appears to up-regulate a second gene located in the other interval, bru-3 ( D. melanogaster X chromosome). Furthermore, we have shown that the chromosomal contributions to reinforced mating discrimination vary among strains of D. pseudoobscura . Finally, the chromosomal effects on mating discrimination are inherited in a dominant fashion, consistent with general theories on the evolution of adaptive characters ( Haldane 1924 ). Below, we discuss these results in the context of several evolutionary hypotheses of reinforcement and speciation. The Genetics of “Basal” Versus “Reinforced” Female Mating Discrimination Most genetic studies of female preference and sexual isolation have utilized between-species genetic crosses or non-hybridizing allopatric populations. Some of these studies suggest that female preference is a polygenic character (e.g., Moehring et al. 2004 ; Ting et al. 2001 ), while other researchers have found a very simple genetic basis for female discrimination ( Doi et al. 2001 ). A study of another behavioral trait, response to odorants, showed that many genes contribute to olfaction, and epistasis plays a fundamental role in determining the specificity of odor identification ( Anholt et al. 2001 , 2003 ). We expect the genetics of reinforced female mating discrimination to bear some similarities to the genetics of overall female species preferences and/or traits involved in response to olfactory cues. Available genetic data on “basal” female mating discrimination in D. pseudoobscura (between-species crosses using a D. pseudoobscura line derived from areas allopatric to D. persimilis ) show that all QTLs for this trait map unequivocally to two inverted chromosomal regions separating it from D. persimilis ( Noor et al. 2001a ), one on XL and one on Chromosome 2. This result suggests that the regions we localized as contributing to reinforced mating discrimination (on XR and Chromosome 4) are distinct from those previously identified as contributing to basal discrimination. Hence, chromosomal inversions may have been crucial in allowing these species to persist in sympatry ( Noor et al. 2001a ), but the rearranged regions might not have contributed directly to the subsequent reinforcement of mating discrimination. This idea is consistent with data showing that a region (DPS4003) just 400 kb away from the QTL identified on the fourth chromosome seems to have introgressed recently between D. pseudoobscura and D. persimilis ( Machado et al. 2002 ). This result supports either a one-allele mechanism, perhaps controlling the genetics of variation within species for female mating discrimination if there was not strong assortative mating before sympatry, or possibly a two-allele mechanism, if reinforcement took place after sympatry and strong assortment had already evolved. The definitive test will be to determine whether introgressing the different D. pseudoobscura alleles into D. persimilis affects female discrimination in the same manner. Female Mating Discrimination Is a Composite Trait These “layers” of female discrimination (see Figure 4 ) are intimately related to the genetic differences being evaluated. Genes localized within fixed chromosomal regions inverted between D. pseudoobscura and D. persimilis are responsible for the first layer, basal discrimination. In contrast, the second layer, reinforced mating discrimination, is caused by genes localized outside those inverted regions. Basal discrimination appears to stem mostly from female responses to acoustic “courtship song” signal differences between D. pseudoobscura and D. persimilis . This is suggested by both a strong correlation in mating success of backcross hybrids with song parameters ( Williams et al. 2001 ) and in playback experiments with wingless flies (M. Lineham, M. A. F. Noor, and M. Ritchie, unpublished data). Even though we cannot discard fine-tuning of the acoustic receiver signaling system in sympatric females, the nature of the candidate genes we identified suggests that olfactory responses might play a major role in the second layer of female preference. Non-auditory cues conferring reinforced discrimination are also suggested by behavioral data collected by Mark Lineham and Michael Ritchie (personal communication) showing that the rejection exercised by D. pseudoobscura females towards D. persimilis male song is the same in lines derived from sympatry and allopatry, even though females from the two regions clearly show differences in mating discrimination ( Noor 1995 ; this study). Finding different genetic architectures for traits involved in speciation is expected under models based on selection on many traits ( Rice and Hostert 1993 ). These traits may be a composite response of behavioral traits, as exemplified in this study, or ecology and behavior, as evidenced by Timema walking sticks, in which traits conferring ecological adaptation and traits contributing to mating discrimination act in conjunction to increase the overall level of sexual isolation between hybridizing populations ( Nosil et al. 2003 ). Figure 4 Genomic Distribution of Genetic Factors Preventing Gene Flow between D. pseudoobscura and D. persimilis Gray boxes denote fixed chromosomal inversions separating D. pseudoobscura and D. persimilis . Black boxes denote the genomic locations of QTLs for reinforced mating discrimination. Note that the third chromosome also conferrs high discrimination in sympatry, but no particular QTLs have been identified for this chromosome. Our results suggest, albeit not conclusively, that reinforced mating discrimination is related to differences in response to olfactory cues. We have shown here that candidate regions on the fourth chromosome bear an unusual excess of olfactory genes, and some of these have been associated with specific olfactory responses in other Drosophila . Further, the fact that we mapped reinforced discrimination to two interacting gene regions involved in olfaction (bearing bru- 3 and CG13982 ) was striking in this regard, supporting a potential role of olfactory response in reinforcement in these species. We also observed differences among strains in the genetic architecture of reinforced mating discrimination. Such variation in genetic control may be common when populations exchanging genes differ in phenotype because of selection. Multiple alleles from different loci may have increased in frequency because of selection for discrimination, and these alleles sometimes spread into allopatry or are replaced by the allopatric alleles in sympatry. When sampling from single lines, we capture only a fraction of the genetic variation in mating discrimination, and sometimes a high-discrimination allele is even sampled from allopatry (as we observed in the QTL on XL). This observation should be typical in many QTL mapping studies that utilize strains within species with extensive gene flow among populations, as in the many studies of D. melanogaster variation. In brief, these results show that basal and reinforced discrimination are different, species discrimination in D. pseudoobscura is a composite trait, and there is genetic variation within species in reinforced mating discrimination. Reinforced Mating Discrimination Is Inherited As a Dominant Trait Recessive adaptive mutations are often lost before selection can screen their effects on the phenotype. Conversely, adaptive mutations that are visible to selection in a heterozygous state will be available for selection even at very low frequencies. Therefore, we expect that most adaptive mutations reaching high frequencies in a population are dominant ( Haldane 1924 , but see Orr and Betancourt 2001 ). This process is commonly referred to as Haldane's sieve and predicts that alleles for mating discrimination that increase in frequency in response to selection should be dominant ( Orr and Betancourt 2001 ). Our study shows that F 1 female offspring of crosses between allopatric and sympatric populations of D. pseudoobscura are as reluctant to mate with D. persimilis males as are D. pseudoobscura females from sympatric populations. This result implies that high discrimination can be expressed in heterozygous individuals, suggesting a dominant basis for the phenotype. In contrast, “basal” female mating discrimination seems to be a recessive trait (F 1 female hybrids from crosses between allopatric D. pseudoobscura individuals and D. persimilis do not discriminate against D. persimilis males [ Noor et al. 2001a ]). Taken together, these results are consistent with genetic differences between basal and reinforced female mating discrimination and with general predictions from Haldane's sieve theory. Conclusions This is the first study to provide a detailed description of the genetic basis of speciation by reinforcement. We conclude that, in D. pseudoobscura, (1) high discrimination in sympatry is inherited in a dominant fashion, (2) there is within-species variability for high female mating discrimination as evidenced by the different genetic architectures recovered in the male-parent backcross experiments, (3) there are multiple genes, possibly involved in olfaction, contributing to enhanced female mating discrimination, (4) some candidate genes for reinforcement identified here have been previously identified in p-element mutant screenings for smell impairment in D. melanogaster, (5) the genetic architecture of basal female mating discrimination is different from that of reinforced mating discrimination, and (6) inversions seem to play no direct role in creating or maintaining the genetic differences directly responsible for increased female mating discrimination in sympatry. However, these inversions seem to play a crucial role, as evidenced by previous studies ( Noor et al. 2001a ), in maintaining the identity of hybridizing species and thus providing time for selection to reinforce their sexual isolation. These results have broad evolutionary implications, as discussed above, and open exciting new avenues of research to understand the genetics of an adaptive behavioral trait involved in speciation. Materials and Methods Our approach is based on measuring in one species the effects of substituting chromosomal segments from a highly discriminant genome into a less discriminant genome. In particular, we (1) test for within-species variation in the genetic architecture of female mating discrimination (F 1 male-parent backcrosses), (2) identify chromosomal regions contributing to reinforced mating discrimination (F 1 female-parent backcross) and compare them to regions conferring basal mating discrimination, and (3) provide a set of candidate genes for increased mating discrimination. Fly rearing and lines D. persimilis flies were collected in 1993 from Mt. St. Helena, California. D. pseudoobscura flies were collected from Mather, California (1997), Mt. St. Helena, California (1997), Flagstaff, Arizona (1993 and 1997), and Mesa Verde National Park, Colorado (2001). Isofemale lines were established by rearing the offspring of individual females previously mated in the wild. All lines were maintained under a constant regime of temperature (20 °C) and humidity (85%) in diurnal/nocturnal cycles of 12 h and reared on a mixture of agar, dextrose, and yeast. Reinforced mating discrimination in sympatry Pairs of D. pseudoobscura isofemale lines from each of two populations were crossed: Mather (1997) 52 × 10 (California, sympatric with D. persimilis ) and Flagstaff (1997) 16 × 17 (Arizona, allopatric to D. persimilis ), respectively. Virgin F 1 females from these crosses as well as D. persimilis males were routinely collected during afternoons and confined for 8 d. On the morning of the eighth day, individual females were confined with individual D. persimilis males. The rationale of this no-choice design is based on behavioral observations suggesting that females tend to copulate more often in the presence of single males than when multiple males approach them (Noor, unpublished data). Therefore, no-choice experiments should provide a more conducive setting for mating. The flies were observed for 10 min. If the male attempted fewer than three copulations, the pair was not scored, and the data were discarded. Otherwise, the pair was scored for successful copulation versus not (the male must have been on the back of the female for at least 1 min—the average copulation duration in D. pseudoobscura is 3 min). These protocols are the same used in Noor et al. (2001a) . We performed Fisher exact tests to evaluate differences among D. pseudoobscura lines sympatric versus allopatric to D. persimilis . Comparisons between allopatric and sympatric populations were performed both for outbred lines and inbred lines and only between lines that were tested for the phenotype at the same time, thus controlling for environmental error. Our comparisons between the two allopatric lines and between the two sympatric lines were not temporally controlled, and therefore may have been subject to some environmental heterogeneity. We used pairs of D. pseudoobscura inbred lines that significantly differed in their degree of female mating discrimination against D. persimilis in our mapping experiments (see below). The heritable basis of increased mating discrimination in sympatry We measured the frequency of matings with D. persimilis males of F 1 females resulting from crosses between sympatric and allopatric D. pseudoobscura lines. If F 1 females discriminated as strongly as the parent derived from sympatry, then we concluded that higher (reinforced) mating discrimination was inherited as a dominant trait. Fisher exact tests where performed to evaluate this hypothesis (see Table 1 ). Testing for male discrimination D. persimilis males were tested against D. pseudoobscura females from the Mather 17 and Flagstaff 1993 strains. We measured the time to first attempted copulation, the number of attempted copulations, and the time between the first attempt to copulate and copulation itself. Analysis of variance was conducted to test for a difference between treatments. Mapping approach Microsatellite markers include those reported previously ( Noor et al. 2000 ) and 100 more that were developed by scanning contig sequences produced by the D. pseudoobscura genome project ( Richards et al. 2004 ). Microsatellites were tested for fixed allelic differences between D. pseudoobscura lines Mather 17 and Flagstaff 1993. All primer information, both for informative and non-informative markers, will be published elsewhere and is available upon request. A recombinational map with an average distance of 15 cM between markers was produced using the female-parent backcross (see below) and the multipoint-linkage approach implemented in MapMaker version 3.0 ( Lander et al. 1987 ). Male-parent backcross Two male-parent backcrosses ( n 1 = 900 and n 2 = 600 flies) were used to determine the chromosomal basis of reinforced mating discrimination and its natural within-species variation. Crossing over does not occur in male Drosophila, and they thus transfer whole chromosomes to their offspring (see Figure 1 ). Each F 1 backcross female was scored for mating (as above), and its DNA was subsequently extracted. Lines used in each backcross were: for backcross 1, Mather (California) 17 and Flagstaff (Arizona) 1993, and for backcross 2, Mt. St. Helena (California) 7 and Mesa Verde (Colorado) 17. We consider strains derived from California as sympatric and strains derived from Arizona or Colorado as allopatric to D. persimilis . We used microsatellite markers to score the origin of each chromosomal segment in backcross hybrid females. To determine the chromosomal contributions from each chromosome, we performed analyses of variance in which the dependent variable was mating discrimination and the independent variables the origin of each chromosome. Female-parent backcross Once we determined the chromosomal effects and their variation for mating discrimination, we scored an additional 1,500 females derived by backcrossing Mather 17 × Flagstaff 1993 F 1 females to Flagstaff 1993 males (see Figure 1 ) for mating discrimination against D. persimilis . A total of 288 females were genotyped for all markers, and both single-marker analyses and CIM ( Zeng et al. 1999 ) were used to identify QTLs contributing to reinforced mating discrimination. Both approaches consistently identified the same regions. An additional 1,200 females were genotyped for markers showing significant effects on mating discrimination. When implementing CIM, forward-backward stepwise regressions were used to search for target QTLs over 2-cM intervals while simultaneously fitting partial regression coefficients for background markers with a window size of 15 cM. We tested for epistatic interactions between significant QTLs using multiple interval mapping ( Zeng et al. 1999 ). In all cases, procedures were carried out as implemented in QTL Cartographer ( Basten et al. 1999 ). Significance threshold values were obtained by permutation analysis as described by Doerge and Churchill (Basten et al. 1996) . Supporting Information Accession Numbers The Flybase ( flybase.bio.indiana.edu ) accession numbers for the genes discussed in this paper are bru-3 (FBgn0036379) and CG13982 (FBgn0031811).

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387284

Chronic Wasting Disease—Prion Disease in the Wild

Chronic wasting disease in deer is the only prion disease that infects both free-ranging and captive animals -- a situation that greatly complicates efforts to control it

In 1967, mule deer in a research facility near Fort Collins, Colorado, in the United States apparently began to react badly to their captivity. At least, that was the guess of researchers working on the natural history and nutrition of the deer, which became listless and showed signs of depressed mood, hanging their heads and lowering their ears. They lost appetite and weight. Then they died—of emaciation, pneumonia, and other complications—or were euthanized. The scientists dubbed it chronic wasting disease (CWD), and for years they thought it might be caused by stress, nutritional deficiencies, or poisoning. A decade later, CWD was identified as one of the neurodegenerative diseases called spongiform encephalopathies, the most notorious example of which is bovine spongiform encephalopathy (BSE), more commonly known as mad cow disease. Nowadays, CWD is epidemic in the United States. Although no proof has yet emerged that it's transmissible to humans, scientific authorities haven't ruled out the possibility of a public health threat. The media have concentrated on this concern, and politicians have responded with escalated funding over the past two years for fundamental research into the many questions surrounding this mysterious disease. Quite apart from how little is yet known about CWD, media interest is reason enough to step up investigation of it, says Mo Salman, a veterinary epidemiologist at Colorado State University in Fort Collins. He's been scientifically involved with BSE, since it was first discovered among cattle in the United Kingdom in 1986. He recalls predicting that lay interest in BSE would wane after five years. Instead, the disease was found in the mid-1990s to be capable of killing humans who ate tainted beef. “I was wrong, and it really changed my way of thinking, to differentiate between scientific evidence and the public perception,” Salman admits. “Because CWD is similar to BSE, the public perception is that we need to address this disease, to see if it has any link to human health.” CWD is the only spongiform encephalopathy known to naturally infect both free-ranging and captive animals, a situation that greatly complicates efforts to monitor, control, or eradicate it. Increasing Attention In 2001, the United States' Department of Agriculture (USDA) declared an emergency after CWD was first diagnosed in deer east of the Mississippi River, indicating a potential nationwide problem. This year, the USDA is developing a herd certification program to help prevent the movement of infected animals in the game farming industry. This will bolster monitoring already underway in virtually every state, including postmortem examinations of game killed by hunters and by sharpshooters in mass culling operations. By June 2003, brain tissue from more than 111,000 animals had been sampled in North America, and 629 were found to have tested positive for CWD. That's a small epidemic compared to the thousands of BSE cases detected in cattle in the United Kingdom, but CWD is thought to be slow-spreading and perhaps lurking undiscovered elsewhere. So far, the United States and Canada are the only countries in which it has been identified, apart from a few imported cases in the Republic of Korea, but surveillance has not been thorough in North America and is virtually nonexistent in the rest of the world. Considered 100% fatal once clinical signs develop, CWD has struck three species of the cervid family—mule deer, white-tailed deer, and Rocky Mountain elk—which roam wild and are raised on farms for meat and hunting. It's the only spongiform encephalopathy known to naturally infect both free-ranging and captive animals, a situation that greatly complicates efforts to monitor, control, or eradicate it. The economic costs are hard to quantify, but a 2001 survey by the United States Department of Commerce's Bureau of Census shows that big-game hunters nationwide spend more than US$10 billion annually for trips and equipment. By far, their main target is deer. Wildlife watching of large land mammals, principally deer, drew 12.2 million participants in 2001. The North American Deer Farmers Association represents owners of 75,000 cervid livestock raised for their meat and for velvet antler, a health-food supplement made from antlers. These animals are valued at more than US$111 million. Over the past two years, the federal government's emphasis on CWD has been “quite high” compared to other wildlife diseases, says USDA staff veterinarian Dan Goeldner. “In no small part, that's because the disease has cropped up in new places, and those are states that have political clout.” It has now been found in ten more states beyond what became known as the endemic region of Colorado and neighboring Wyoming ( Figure 1 ). Last year, the USDA received US$14.8 million to monitor and manage the disease, and Goeldner says the department expects to get about US$16 million this year. Figure 1 CWD in North America CWD has been detected in both free-ranging and captive animals in Wyoming, Colorado, South Dakota, Wisconsin, and Saskatchewan; only in captive herds in Montana, Nebraska, Kansas, Oklahoma, Minnesota, and Alberta; and only in wild animals in New Mexico, Utah, and Illinois. (Figure courtesy of Gary Wolfe and the CWD Alliance.) The Prion Diseases Those figures don't include scientific research funded by other organizations, such as the US$42.5 million received by the United States' Department of Defense in 2002 to start up a National Prion Research Program. The prion is the protein-like agent that causes transmissible spongiform encephalopathies (TSEs). Its normal function is uncertain, but when it misfolds into an abnormal or “infectious” form, it causes the microscopic holes and globs of toxic, misshapen protein found in the brains of TSE victims. Unlike viruses, prions don't contain nucleic acids—only protein. Without DNA or RNA to issue biochemical commands, abnormal prions shouldn't be able to convert normal prions to the infectious state, but that's exactly what they do ( Box 1 ). Prion diseases occur in many species. In domestic sheep and goats, prion diseases occur as scrapie, which has a virtually worldwide distribution. North America and Europe have also reported rare cases of TSE in ranched mink. Humans get kuru, Creutzfeldt-Jacob disease (CJD), and Gerstmann-Sträussler-Scheinker syndrome—all rare—and BSE itself manifests in people as a variant form of CJD. Since the United Kingdom outbreak, BSE has been discovered in more than 20 countries, most recently in North America. As public fear rose of possible CWD transmission to humans who eat infected venison, the United States' Centers for Disease Control and Prevention (CDC) released a report last year of its investigation into several deaths among venison eaters who might have had a TSE. The report concluded that none of the deaths could be attributed to venison, but it nevertheless cautioned that animals showing evidence of CWD should be excluded from the human and animal feed chains ( Box 2 ). CWD is the least understood of all the prion diseases. Its origins are unknown and may well never be discovered. The question is largely academic, unless one hypothesis is proven true, that it derives from scrapie. In that case, the knowledge might help in efforts to control the two diseases through herd and flock management. Researchers are working to determine the minimum incubation time of CWD before clinical signs appear, now roughly estimated at 15 months in deer and 12—34 months in elk. They're trying to discover whether CWD strains exist that can affect the length of the disease process and different regions of the brain or that can infect different species, including humans. They are also investigating the period during which the prion is passed on, as well as its modes of transmission. They want to know whether disease reservoirs exist in the bodily fluids of hosts, in the environment, or both. They're racing to develop a diagnostic test that can be performed on live animals, enabling identification of the disease before clinical signs appear, which would eliminate the need to kill thousands of apparently healthy animals in areas where CWD is detected. But among the first things they need to clarify are CWD's distribution across North America and its prevalence. “…the disease has cropped up in new places, and those are states that have political clout.” An Initial Step: Improved Surveillance “Before you can start to control CWD, you need to understand where it is and how much of it you have,” says veterinary pathologist Beth Williams of the University of Wyoming in Laramie. “So I think you really need surveillance.” Research on its pathogenesis and transmission will help to develop better diagnostic tools, which will improve surveillance, adds Williams, who first identified the disease as a TSE more than a quarter-century ago. Colorado State's Salman argues that current surveillance is primarily a series of reactions to reported cases, rather than a systematic strategy designed to determine where and at what prevalence the disease exists and where it's absent. The estimated prevalence is about 1% in elk and 2.5% in deer. But Salman says, “We don't have a good idea of areas in which we are saying we haven't found the disease because these areas are not yet, in my estimation, negative for the disease. Scrapie is a wonderful example of systematic surveillance but, to be fair to the decision-makers and technical people involved with CWD, surveillance on wildlife species is very difficult.” The USDA's Goeldner declares, “We have the goal and the hope to eradicate the disease from the farm population.” But Colorado Department of Wildlife veterinarian and CWD expert Mike Miller warns, “Given existing tools, it seems unlikely that CWD can be eradicated from free-ranging populations once established.” The gold standard of diagnosis is based on examination of the brain for spongiform lesions and abnormal prion aggregation. Suspect animals are decapitated and their bodies incinerated. “This is an approach that nobody wants, including the people who have to implement it,” says wildlife ecologist Michael Samuel, principal investigator in the United States Geological Survey–Wisconsin Cooperative Wildlife Research Unit at the University of Wisconsin in Madison. Nevertheless, when three white-tailed deer shot by hunters in the south-central part of that state during the fall of 2001 were diagnosed with CWD, the state government took swift action. By the spring of 2003, almost 40,000 deer had been sacrificed and sampled for the disease, both within and without a 411 square-mile (1065 square-kilometer) region dubbed the eradication zone. There the goal was to remove as many deer as possible, whereas the plan in contiguous outlying areas was to reduce density to about ten deer per square mile. CWD is thought to spread more efficiently in high-density populations, and normal densities in Wisconsin are 50–100 deer per square mile, about five times that of Colorado and Wyoming. The main objectives of the Wisconsin culling were to discover where the disease existed and its prevalence in affected areas. In the eradication zone, it was 6%–7%, although in the outlying region it was only 1%–2%. Samples elsewhere in the state tested negative. In Search of a Live Assay A key to combating the spread of CWD is to put into widespread use a preclinical diagnostic test on live animals. Miller and colleagues recently developed and validated the first such assay, based on a biopsy of lymphoid tissue, where the infectious agent is known to incubate. They showed that tonsillar biopsies taken from live animals can confirm disease at least 20 months prior to death and up to 14 months before the onset of clinical signs. Although the method is a useful screening tool, it requires much time and training. Each deer must be anaesthetized and blindfolded, placed in a restraint, its mouth held open with a gag, the tonsil visualized with a laryngoscope, and the biopsy taken with endoscopic forceps. Lymphoid tissue sampling was first used as a preclinical test in sheep scrapie. “Many attempts have been made to develop and evaluate tests for live animals, but it is fraught with difficulties,” declares TSE specialist Danny Matthews of the United Kingdom Government's Veterinary Laboratories Agency in Weybridge. He says that a live test for BSE in cattle is likely to be evaluated shortly by the European Food Safety Authority, but warns of a major problem: test samples are collected early in the incubation, whereas brain pathology only arises two to three years later. This creates long delays in determining whether a positive preclinical test result is, in fact, accurate: “How can one do an appropriate evaluation?” Matthews notes that blood appears to be a useful medium for testing scrapie in sheep, but current technology cannot deliver a tool applicable across a range of different scrapie genotypes. “Like sheep, elk and mule deer do have a peripheral pathogenesis, which suggests that the blood test route may have some potential, especially if the genotype variability is more restricted than in sheep.” Transmission Mysteries Scrapie can be vertically transmitted from mother to offspring, either in the womb or from the transfer of infected germ plasm. It also can be transmitted horizontally, from any one animal to another. CWD, the only other known contagious TSE, is thought to be transmitted solely by as-yet-undetermined direct or indirect horizontal contact. It probably is not transmitted through infected feed, as is the case for BSE. A number of scientists are currently on the trail of suspected CWD disease reservoirs. Saliva is a leading candidate, because clinical signs of CWD include excessive thirst, drinking, and drooling. Work with lab animals suggests that the infectious agent might be produced in salivary glands and, if so, it could be transmitted through social interactions. Feces is also a possible reservoir because animals nose in the ground for feed, and urine is yet another candidate, because it is involved in the scenting activities of cervids. Soil could be an environmental reservoir, because cervids ingest dirt to supplement their diets with minerals. Bucks also lick soil on which does have urinated to ascertain their mating status. University of Wisconsin soil science professor Joel Pedersen has discovered that abnormally folded prions stick to the surface of some soil types, such as clay, resisting environmental and chemical damage. “Captive elk contracted CWD when introduced into paddocks occupied by infected elk more than 12 months earlier, despite fairly extensive efforts to disinfect the enclosures,” Pedersen notes. He has begun a five-year project to characterize interactions between infectious prions and soil particles and determine the extent to which infectivity is retained. No matter how CWD is transmitted between cervids, the likelihood of human susceptibility seems low. Laboratory evidence has demonstrated a molecular barrier against such cross-species infection, based on the failure of abnormal cervid prions to efficiently convert normal human prions to the infectious state. Likewise, abnormal cervid prions don't easily convert normal cattle prions, suggesting that cattle won't get CWD and pass it on to humans who eat tainted beef. While cattle can contract CWD if inoculated with the infectious agent, long-term studies placing cattle in close proximity to diseased cervids have resulted in no cases of natural transmission. Williams summarizes what all this suggests: “Never say never, but based on the [molecular] work, the CDC's findings, and the epidemiology, we certainly don't have evidence that humans have gotten CWD.” Figure 2 Identifying Animals at Risk from CWD A raccoon family feeds on a deer carcass staked out by researchers at the University of Wisconsin, in a study aimed at determining which species could be at risk of contracting CWD. (Photo courtesy of the Wisconsin Cooperative Wildlife Research Unit, University of Wisconsin-Madison.) Box 1. How Prions Confound Research The relative newness to science of CWD and mad cow disease is one reason they aren't well understood, but sheep scrapie was first identified in Great Britain in 1732—and it still isn't well-characterized. The main problem is the numerous roadblocks to researchers posed by prions, the disease agents of such TSEs. Because normal and abnormal prions have identical amino acid sequences, the immune system neither recognizes an infection nor mounts a prion-specific response. Accordingly, an antibody specific to prions has not yet been identified. Without nucleic acid, prions can't be detected or analyzed using conventional techniques such as polymerase chain reaction. They also are extraordinarily resistant to a range of treatments that typically kill or inactivate infectious agents, such as ultraviolet and ionizing radiation, heating, and most chemical disinfectants. The infectious form is largely resistant to degradation by protease enzymes, and in laboratory animals it can incubate for months to years before clinical disease signs appear. Finally, prion diseases must compete for space in expensive, biohazard-safe labs. It's therefore unsurprising that knowledge of these diseases has not sped forward. Still, scientists hope that the recent upsurge of research into BSE, CWD, and scrapie in the United States and Europe will produce synergistic results for preventing and controlling all TSEs. Box 2. Who Else Might Get CWD? When mad cow disease broke out in the United Kingdom in the 1980s, cattle and humans were far from the only species found to be affected. Among other bovids in zoo and research colonies that contracted spongiform encephalopathy from tainted beef were nyala, gemsbok, eland, Arabian and scimitar-horned oryx, greater kudu, and North American bison. A feline version of the disease was found in domestic cats, cougars, cheetahs, ocelots, and tigers. Among primates, rhesus macaques and lemurs were also infected. Unlike BSE, CWD is not thought to be transmitted through feed. But three species of cervids are naturally susceptible, and the question arises of how many other species might be in danger. To help answer that question, Michael Samuel and colleagues at the University of Wisconsin are staking out deer carcasses to see which scavengers come to feed. With flashlit photography, they've discovered “an amazing cast of characters,” including hawks, owls, crows, dogs, cats, coyotes, raccoons, skunks, mink, foxes, and opossums ( Figure 2 ). Mammalian scavengers in the state's CWD-affected region will later be examined for disease.

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549598

Mass Spectometry–Based SARS Genotyping

To quickly control infectious disease outbreaks, extensive information is required to identify the source and transmission routes, and to evaluate the effect of containment policies. Traditionally, scientists have used travel- and contact-tracing methods, but the recent SARS epidemic showed that sequence-based techniques for pathogen detection can also be important tools to help understand outbreaks. Jianjun Liu and colleagues adapted mass spectrometry (MS)–based genotyping, already used as a high-throughput way of detecting single nucleotide polymorphisms in human DNA, to the analysis of the SARS virus from clinical samples. The major breakthroughs against SARS were the discovery of the SARS coronavirus (SARS-CoV) as the etiological agent and the sequencing of the SARS genome. Liu's colleagues at the Genome Institute of Singapore had previously shown that common genetic variants in the SARS-CoV genome could be used as molecular fingerprints to help trace the route of infection. However, as “sequence analysis of large numbers of clinical samples is challenging, cumbersome, and expensive,” they felt that “what is needed is a rapid, sensitive, high throughput, and cost-effective screening method.” Towards this goal, Liu and colleagues now demonstrate that an MS-based technique can quickly yield accurate information on clinical isolates (in this case from the 2003 SARS outbreak in Singapore). Two transmission routes for the Singapore SARS outbreak The scientists demonstrate the sensitivity of the assay in detecting SARS-CoV variations and test it further in cultured viral isolates and uncultured lung tissue samples of SARS-CoV. They analyzed isolates taken from 13 patients with SARS at different stages of the Singapore outbreak, identified nine sequence variations, and discovered a new primary route of introduction of the virus into the Singapore population. They also found a Singaporean origin for a German case of SARS, a result that could not be derived from standard sequencing methods. The analysis of the uncultured lung tissue also found different sequences in a single patient, which suggested the presence of multiple viral sequence variants in one host. The study suggests that MS-based genotyping can be used for large-scale genetic characterization of viral DNA from clinical samples. The researchers found that the method was accurate and sensitive, with a 95% success rat e for detecting sequence variations at low virus concentrations. The MS-based assay allows high-throughput analysis and complements the “gold standard” direct sequence analysis method, which is used to identify new sequence variations. As such, it is particularly useful for investigating agents for which extensive sequence information exists. Liu and colleagues propose that the most efficient method for a large-scale population investigation would be initial characterization of a genome sequence by direct sequence analysis in a subset of samples, followed by MS-based analysis of informative genetic variations. Altogether, their results suggest that MS-based genetic analysis can help real-time investigations in disease outbreaks.

/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC549598.xml

555748

Are decisions using cost-utility analyses robust to choice of SF-36/SF-12 preference-based algorithm?

Background Cost utility analysis (CUA) using SF-36/SF-12 data has been facilitated by the development of several preference-based algorithms. The purpose of this study was to illustrate how decision-making could be affected by the choice of preference-based algorithms for the SF-36 and SF-12, and provide some guidance on selecting an appropriate algorithm. Methods Two sets of data were used: (1) a clinical trial of adult asthma patients; and (2) a longitudinal study of post-stroke patients. Incremental costs were assumed to be $2000 per year over standard treatment, and QALY gains realized over a 1-year period. Ten published algorithms were identified, denoted by first author: Brazier (SF-36), Brazier (SF-12), Shmueli, Fryback, Lundberg, Nichol, Franks (3 algorithms), and Lawrence. Incremental cost-utility ratios (ICURs) for each algorithm, stated in dollars per quality-adjusted life year ($/QALY), were ranked and compared between datasets. Results In the asthma patients, estimated ICURs ranged from Lawrence's SF-12 algorithm at $30,769/QALY (95% CI: 26,316 to 36,697) to Brazier's SF-36 algorithm at $63,492/QALY (95% CI: 48,780 to 83,333). ICURs for the stroke cohort varied slightly more dramatically. The MEPS-based algorithm by Franks et al. provided the lowest ICUR at $27,972/QALY (95% CI: 20,942 to 41,667). The Fryback and Shmueli algorithms provided ICURs that were greater than $50,000/QALY and did not have confidence intervals that overlapped with most of the other algorithms. The ICUR-based ranking of algorithms was strongly correlated between the asthma and stroke datasets (r = 0.60). Conclusion SF-36/SF-12 preference-based algorithms produced a wide range of ICURs that could potentially lead to different reimbursement decisions. Brazier's SF-36 and SF-12 algorithms have a strong methodological and theoretical basis and tended to generate relatively higher ICUR estimates, considerations that support a preference for these algorithms over the alternatives. The "second-generation" algorithms developed from scores mapped from other indirect preference-based measures tended to generate lower ICURs that would promote greater adoption of new technology. There remains a need for an SF-36/SF-12 preference-based algorithm based on the US general population that has strong theoretical and methodological foundations.

Background Health-related quality of life (HRQL) measures have many applications, including the measurement of population health status and outcomes of medical interventions that subsequently can be applied to economic evaluations of health care interventions. One such method of economic evaluation, cost utility analysis (CUA), is a special form of cost effectiveness analysis that evaluates incremental costs and effects of an intervention by assessing health effects using quality-adjusted life years (QALYs) [ 1 ]. QALYs incorporate both length of life and quality of life into a single metric, and are calculated by summing the time periods individuals spend in different health states, weighted by the qualities of the health states [ 2 ]. Because new therapies are typically more expensive than standard therapies, CUA has gained prominence as a method to inform decision makers who seek to compare the tradeoff in incremental costs and gains in health conferred by new treatment choices within and across disease states. Optimally, CUA is used to guide the allocation of resources on a societal level. The Panel on Cost Effectiveness in Health and Medicine recommended that community preferences for health states collected from a representative sample of the US general population should be "the most appropriate ones for use in a Reference Case analysis" for US decision makers [ 2 ]. Such an approach is facilitated by indirect preference-based generic measures of health-related quality of life (HRQL) such as the Quality of Well-Being Scale [ 3 ], Health Utilities Index [ 4 , 5 ], and EQ-5D [ 6 , 7 ], as opposed to elicitation of preferences directly from patients using techniques such as the standard gamble, rating scale, and the time trade-off. Indirect preference-based HRQL measures typically generate index-based single summary scores for health states described by the instrument's classification system using an algorithm based on preferences of the community or general population. An important development in health services research has been the emergence of algorithms that generate single preference-based summary scores based on items, domain scores, or summary scores from the Short Form 36 (SF-36) [ 8 ] and SF-12, a 12-item subset of the SF-36 [ 9 ]. While many SF-12 and SF-36 datasets are available due to the widespread use of this family of health assessment measures in clinical trials and population health surveys, their value for application to economic evaluations has been previously limited due to an absence of a scoring algorithm that could generate QALYs from SF-12 and SF-36 response sets. The preference-based algorithms provide an opportunity to use SF-36 and SF-12 data in CUA. As of 2004, 10 published algorithms were identified in the literature that were based on SF-36 or SF-12 items, subscale scores, or summary scores [ 10 - 18 ]. Each preference-based algorithm is unique, derived from different modeling approaches, items/domains, data and/or sources of preferences. Several of these algorithms have been compared in studies, and found to differ from one another and from valuations directly elicited from patients [ 19 - 22 ]. Studies have used some of the algorithms to conduct CUA [ 23 - 27 ], which may be used to inform health care resource allocation. Although the algorithms are known to produce different results, their impact on incremental cost-utility ratios (ICURs) and related decision-making in health care have not been clearly demonstrated. The purpose of this study was to examine how choice of algorithm for the SF-36/SF-12 might affect decision-making. The specific objectives for the study were to calculate ICURs by applying each algorithm to data from 2 different studies that included longitudinal assessments of the SF-36, to compare the ranking of each algorithm-based ICUR across conditions, and finally to interpret whether differences in ICURs generated by each algorithm had the potential to affect decision making. There were two specific hypotheses. First, ICURs calculated from different algorithms were expected to differ because preferences derived from those algorithms had been found to be different [ 19 ]. Second, the rank ordering of ICURs was expected to be similar between the conditions, stroke and asthma, examined in the CUA simulations. Methods Data sources To illustrate the outcomes of CUA using the different SF-36 algorithms, data with empiric responses to the SF-36 from patients were used from two different sources and conditions: (1) a clinical trial of adults with asthma [ 19 ]; and (2) a longitudinal study of health-related quality of life (HRQL) after stroke [ 28 ]. The study of asthma patients was a 12-month randomized controlled trial conducted in inhaled corticosteroid naïve adult patients with mild persistent to moderate persistent asthma that compared two inhaled corticosteroid treatments, triamcinolone acetonide hydrofluoroalkane and fluticasone propionate. Patient included in this trial were ≥ 18 years old, had had a forced expiratory volume in 1 second ≥ 60% of their predicted value after withholding inhaled β-agonists, and had had airway reversibility of ≥ 15% following the administration of an inhaled β-agonist. For the purpose of this analysis, responses to the SF-36 at baseline and 12 months were used. The second source of data was a natural history of HRQL after stroke. Stroke patients who were hospitalized with a confirmed ischemic stroke and consented to participate were included. Patients were excluded if they were ≤ 18 years old, could not comprehend English-based questionnaire, lived > 150 kilometers from Edmonton, Alberta, had hemorrhagic or lower brain stem stroke, coma, global or Wernicke's aphasia, or life expectancy was less than 6 months for any medical reason. Patients were enrolled in the study within two weeks of stroke and no later than 3 weeks after stroke. Health status measures, including the SF-36, were self-assessed by patients. For this analysis, responses to the SF-36 at baseline and 6 months were used. Both the stroke and asthma studies used version 1 of the SF-36. Measures The SF-36 has been traditionally described as a psychometrically-derived generic health status profile, with 8 subscales and two summary scores, the physical component summary (PCS-36) score and the mental component summary (MCS-36) score. The eight domains include physical functioning (PF), role limitations-physical (RP), bodily pain (BP), general health (GH), mental health (MH), role limitations-emotional (RE), vitality (VT), and social functioning (SF). The SF-12 is a shorter, 12-item version of the SF-36 that does not generate domain scores but provides summary scores, the PCS-12 and MCS-12, that are highly predictive of the PCS-36 and MCS-36 [ 9 ]. Scores of the 8 subscales range from 0 to 100. The summary scores (i.e. PCS-36, MCS-36) have a mean score of 50 and a standard deviation of 10. Similarly, the PCS-12 and MCS-12 summary scores have a mean of 50 and a standard deviation of 10. Preference-Based Algorithms for SF-36 and SF-12 Nine publications that derived 10 unique preference-based algorithms for the SF-36 or SF-12 were identified (Table 1 ) [ 10 - 18 ]. Four algorithms were identified that mapped scores for the SF-36, and 6 algorithms mapped scores for the SF-12. The mapping approach was described as 1 st generation if the algorithm was derived from directly elicited preferences, and denoted as 2 nd generation mapping if the SF-12/SF-36 algorithm was based upon scores from an indirect preference-based HRQL measure, such as the EQ-5D. Note that these algorithms relate to the most recently advocated algorithms, as several authors published earlier algorithms and subsequently published updates (e.g. Shmueli) [ 16 ]. For brevity, each published algorithm is identified by the name of the first author. Table 1 Summary of SF-12/SF-36 preference-based algorithms Theoretical Range* Algorithm Minimum Maximum Original source of Preferences Source of value (country) Source of sample (country) Sample Size Brazier (SF-12) 0.35 1.00 1 st generation – SG UK UK 836 Lundberg (SF-12) 0.27 0.97 1 st generation – VAS Sweden Sweden 4,180 Franks (SF-12) -0.24 0.92 2 nd generation – EQ-5D UK US 240 Franks (SF-12) -0.09 0.96 2 nd generation – HUI3 Canada US 240 Franks (SF-12) -0.07 0.98 2 nd generation – EQ-5D UK US 12,998 Lawrence (SF-12) 0.15 1.01 2 nd generation – EQ-5D UK US 14,580 Shmueli (SF-36) 0.23 1.00 1 st generation – VAS Israel Israel 2,505 Brazier (SF-36) 0.30 1.00 1 st generation – SG UK UK 836 Fryback (SF-36) 0.59 0.84 2 nd generation – QWB US US 1,356 Nichol (SF-36) 0.24 1.05 2 nd generation – HUI2 Canada US 6,921 *Maximum and minimum scores are based on best and worst responses to all items on the SF-36 and SF-12. For the Lundberg algorithm, minimum obtained is based on male, ≥ 80 years of age, while maximum is based on female, <30 years of age. For the Nichol algorithm, the minimum is based on 100 years of age, while maximum is based on 0 years of age. Brazier and colleagues constructed an econometric model for predicting health state valuations by first revising the SF-36 into a health status measure with 6 domains called the SF-6D [ 10 ]. Using a variant on the standard gamble, 249 health states defined by the SF-6D were valued by a representative sample of the UK general population. Ordinary least squares (OLS) models were estimated to predict all 18,000 SF-6D health states. The Brazier (SF-36) algorithm used for the present study was based on the parsimonious consistent model, the preferred specification for model 10. The same data and a similar approach was used to estimate an algorithm based on the SF-12 [ 17 ]. Fryback and colleagues predicted Quality of Well-being Index (QWB) scores from SF-36 domain scores using data collected from the Beaver Dam Health Outcomes Study [ 12 ]. A six-variable regression model with three main effects (PF, MH, and BP) and three interaction terms (GH*RP, PF*BP, and MH*BP) is used to estimate preferences. Nichol and colleagues mapped the SF-36 to the preference-based Health Utility Index Mark 2 (HUI2). They estimated HUI2 scores from SF-36 domain scores and sociodemographic variables from a sample of Southern California Kaiser Permanente members [ 15 ]. The Nichol method used OLS models, retaining statistically significant parameter estimates that included all eight domains of the SF-36 and age of the respondent. Shmueli updated an examination of the relationship between Visual Analog Scale (VAS) ratings and SF-36 domains provided in a population health survey in Israel by predicting VAS values from SF-36 domains using linear and non-linear regression models [ 16 ]. The model was anchored such that scores of 100 on all 8 SF-36 domains would result in a VAS score of 100. The present study used the anchored algorithm that included statistically significant coefficients for PF, MH, VT, and GH. Franks and colleagues mapped the SF-12 to the EQ-5D Index and HUI3 using a convenience sample of 240 low-income, predominantly Latino and black patients visiting a community health center in New York [ 11 ]. Two equations were separately developed that mapped the PCS-12 and MCS-12 onto EQ-5D and HUI3 scores using OLS models. Described as a pilot, the authors observed that the level of explained variance was consistent with the Fryback and Nichol studies (between 50–60%). Franks led a second investigation, again mapping the SF-12 to EQ-5D scores, using data from the Medical Expenditure Panel Survey (MEPS) [ 18 ]. The algorithm based upon SF-12 responses that did not include demographic variables was utilized for the present study. In a similar analysis, Lawrence and colleagues predicted the EQ-5D scores from the SF-12 using MEPS data [ 13 ]. A series of 2-variable, 3-variable, and 6-variable models, based on functional variations on, and interactions between, the PCS-12 and MCS-12 were developed. The 2-variable model was advocated for its simplicity and predictive ability across a diverse set of subgroups in the validation set. Finally, Lundberg and colleagues investigated the relationship of preference-based measures and the SF-12 based on self-assessed HRQL from a random sample of residents in Uppsala County of Sweden [ 14 ]. Linear regression models were used to predict valuations from 11 of the 12 items on the SF-12 (excluding the global health item), age, and gender. When using proportion explained variance as a criterion, the reduced VAS-based model that retained only significant coefficients was recommended, with 50% of variance explained by the model. Data analysis Empiric data for stroke and asthma were used to ensure that actual health state changes were represented. The present analysis was based on patients who completed both pre- and post- assessments and had no missing items. After the scoring algorithms were applied to SF-36 responses using the 10 algorithms [ 10 - 18 ], the change in utility was transformed into QALYs, with the assumption that the incremental gain/lose in health state utility was realized for a 1-year period. QALYs were calculated using the area under the curve (AUC) approach. We assumed incremental costs associated with the intervention were $2000 per year greater than standard treatment in both the stroke and asthma patients. Such costs over standard treatment were considered reasonable approximations for the costs of an innovative treatment in asthma and stroke, and although distributions of costs could have been used to further simulate a "realistic CUA", but would further complicate the paper without contributing to the main purpose of this study. The incremental cost utility ratio (ICUR) between the intervention and control groups was calculated by dividing incremental costs by gain in QALYs. The algorithms were ranked based on ICURs for each condition. The pre/post domain and preference-based scores were described for both study groups visit using means and standard deviations. The 95% confidence intervals (CIs) for ICURs were based on the CIs for the preference scores. The pre/post change scores were evaluated with paired t -tests. The rank order of the ICURs was compared between the asthma and stroke groups using Spearman's correlation coefficient (r s ). P-values < 0.05 were considered statistically significant. Results Of the 304 patients enrolled in the asthma study, 220 (72.4%) completed both the baseline and final SF-36 assessment. The stroke study had 81 of 124 initial respondents (65.3%) complete the SF-36 at baseline and final follow-up. In comparison to the patients in the asthma study, patients in the stroke study were older (mean age 67.4 years vs. 39.1 years) and had much lower mean average PF, RP, SF, and PCS scores (Table 2 ). Positive change was observed on all 8 domains of the SF-36 in the asthma patients from the baseline to the end of the study (all p-values < 0.01). Stroke patients showed trend towards improvement on all 8 domains, with significant improvement on all domains (p-values < 0.01) with the exception of GH and BP (p-values > 0.05). Table 2 Demographics Characteristics and SF-36 Scores Asthma Patients (n = 220) Stroke Patients (n = 81) Baseline Assessment Final Assessment Baseline Assessment Final Assessment Mean (SD) Mean (SD) Mean (SD) Mean (SD) Age 39.1 (12.6) 67.4 (14.4) Female (%) 55 49 GH 59.4 (18.8) 69.4 ‡ (19.0) 54.4 (18.4) 56.8 (22.2) BP 66.4 (23.2) 75.5 ‡ (21.8) 62.3 (27.4) 68.8 (30.8) PF 63.1 (21.9) 81.3 ‡ (21.4) 17.8 (25.9) 41.6 ‡ (33.0) RE 63.3 (41.4) 79.6 ‡ (34.5) 47.3 (44.7) 68.3 † (44.1) RP 38.1 (40.0) 73.3 ‡ (37.4) 8.3 (23.7) 32.1 ‡ (40.2) MH 71.2 (17.9) 75.9 ‡ (16.6) 67.2 (19.2) 77.9 ‡ (17.2) SF 72.6 (22.0) 83.1 ‡ (19.8) 42.7 (26.4) 60.8 ‡ (31.8) VT 48.8 (20.7) 60.0 ‡ (21.6) 41.5 (17.8) 50.5 † (22.8) PCS 40.1 (9.0) 48.2 ‡ (9.1) 28.9 (8.52) 34.5 ‡ (12.8) MCS 48.1 (11.1) 50.5 † (10.3) 46.4 (11.2) 51.7 † (10.8) † p-value < 0.01; ‡ p-value < 0.001, based on t -test for dependent samples According to the preference-based summary scores, all patients in both studies demonstrated statistically significant improvement from baseline to the end of the study (p-value < 0.001) (Table 3 ). In the asthma study, the mean (SD) change in preference scores ranged from 0.063 (0.117) to 0.130 (0.159). In the stroke study, change scores ranged between 0.055 (0.124) and 0.143 (0.215). Table 3 Preference-Based Scores for Asthma and Stroke Samples using SF-36 Algorithms Baseline Assessment (T i ) Final Assessment (T f ) Difference (T f -T i ) 95% CI Asthma (n = 220) Mean (SD) Mean (SD) Mean (SD) Lower Upper Brazier (SF-36, SG) 0.694 (0.101) 0.757 (0.113) 0.063 ‡ (0.117) 0.048 0.082 Brazier (SF-12, SG) 0.724 (0.116) 0.789 (0.119) 0.065 ‡ (0.125) 0.047 0.078 Fryback (SF-36, QWB) 0.655 (0.063) 0.721 (0.072) 0.066 ‡ (0.070) 0.057 0.075 Nichol (SF-36, HUI2) 0.765 (0.123) 0.840 (0.118) 0.075 ‡ (0.114) 0.060 0.090 Shmueli (SF-36, VAS) 0.683 (0.124) 0.766 (0.130) 0.084 ‡ (0.111) 0.069 0.098 Lundberg (SF-12, VAS) 0.667 (0.113) 0.759 (0.119) 0.091 ‡ (0.117) 0.076 0.107 Franks (SF-12, EQ-5D) 0.699 (0.181) 0.814 (0.152) 0.115 ‡ (0.169) 0.093 0.138 Franks (SF-12, HUI3) 0.643 (0.170) 0.764 (0.173) 0.121 ‡ (0.176) 0.098 0.144 Franks (SF-12, EQ-5D, MEPS) 0.667 (0.174) 0.797 (0.163) 0.129 ‡ (0.167) 0.107 0.151 Lawrence (SF-12, EQ-5D) 0.667 (0.158) 0.798 (0.159) 0.130 ‡ (0.159) 0.109 0.152 Stroke (n = 81) Shmueli (SF-36, VAS) 0.602 (0.115) 0.656 (0.155) 0.055 ‡ (0.124) 0.027 0.082 Fryback (SF-36, QWB) 0.548 (0.060) 0.616 (0.100) 0.069 ‡ (0.094) 0.048 0.089 Lundberg (SF-12, VAS) 0.512 (0.108) 0.592 (0.155) 0.080 ‡ (0.156) 0.045 0.114 Brazier (SF-12, SG) 0.609 (0.099) 0.696 (0.145) 0.087 ‡ (0.152) 0.054 0.121 Nichol (SF-36, HUI2) 0.656 (0.110) 0.745 (0.147) 0.089 ‡ (0.143) 0.058 0.121 Brazier (SF-36, SG) 0.552 (0.087) 0.669 (0.139) 0.116 ‡ (0.137) 0.086 0.147 Franks (SF-12, HUI3) 0.482 (0.150) 0.615 (0.200) 0.133 ‡ (0.200) 0.089 0.177 Lawrence (SF-12, EQ-5D) 0.491 (0.132) 0.626 (0.204) 0.134 ‡ (0.194) 0.091 0.177 Franks (SF-12, EQ-5D) 0.478 (0.199) 0.618 (0.232) 0.139 ‡ (0.233) 0.088 0.191 Franks (SF-12, EQ-5D, MEPS) 0.472 (0.165) 0.615 (0.219) 0.143 ‡ (0.215) 0.096 0.191 ‡ p-value < 0.001, based on t -test for dependent samples NB: algorithms are ordered from smallest to largest difference score for each condition Table 4 shows the results from the two sets of CUA simulations, and the rank order of the algorithms. As the incremental cost of $2000 is held constant across the algorithms, the differences in QALYs are mirrored by the differences in ICURs. In the asthma patients, estimated ICURs ranged from Lawrence's SF-12 algorithm at $30,769/QALY (95% CI: 26,316 to 36,697) to Brazier's SF-36 algorithm at $63,492 (95% CI: 48,780 to 83,333). ICURs for the stroke cohort varied slightly more dramatically. The MEPS-based algorithm by Franks et al. provided the lowest ICUR at $27,972/QALY (95% CI: 20,942 to 41,667). The Fryback and Shmueli algorithms provided ICURs that were greater $50,000/QALY and did not have confidence intervals that overlapped with most of the other algorithms. The rank order of algorithms based on ICUR was similar across the two conditions, with r s = 0.60 (p-value < 0.10). Table 4 Ranking of SF-36/SF-12 Algorithm by Estimated Incremental Cost Utility Ratio Incremental Cost 1 year QALYs Gained ICUR ($/QALY) [95% CI] Rank Asthma Lawrence (SF-12, EQ-5D) $2000 0.065 30 769 [26 316, 36 697] 1 Franks (SF-12, EQ-5D, MEPS) $2000 0.065 31 008 [26 490, 37 383] 2 Franks (SF-12, HUI3) $2000 0.061 33 058 [27 778, 40 816] 3 Franks (SF-12, EQ-5D) $2000 0.058 34 783 [28 986, 43 011] 4 Lundberg (SF-12, VAS) $2000 0.046 43 956 [37 383, 52 632] 5 Shmueli (SF-36, VAS) $2000 0.042 47 619 [40 816, 57 971] 6 Nichol (SF-36, HUI2) $2000 0.038 53 333 [44 444, 66 667] 7 Fryback (SF-36, QWB) $2000 0.033 60 606 [53 333, 70 175] 8 Brazier (SF-12, SG) $2000 0.033 61 538 [51 282, 85 106] 9 Brazier (SF-36, SG) $2000 0.032 63 492 [48 780, 83 333] 10 Stroke Lawrence (SF-12, EQ-5D) $2000 0.067 29 851 [22 599, 43 956] 3 Franks (SF-12, EQ-5D, MEPS) $2000 0.072 27 972 [20 942, 41 667] 1 Franks (SF-12, HUI3) $2000 0.067 30 075 [22 599, 44 944] 4 Franks (SF-12, EQ-5D) $2000 0.070 28 777 [20 942, 45 455] 2 Lundberg (SF-12, VAS) $2000 0.040 50 000 [35 088, 88 889] 8 Shmueli (SF-36, VAS) $2000 0.028 72 727 [48 780, 148 148] 10 Nichol (SF-36, HUI2) $2000 0.045 44 944 [33 058, 68 966] 6 Fryback (SF-36, QWB) $2000 0.035 57 971 [44 944, 83 333] 9 Brazier (SF-12, SG) $2000 0.044 45 977 [33 058, 74 074] 7 Brazier (SF-36, SG) $2000 0.058 34 483 [27 211, 46 512] 5 NB: algorithms are ordered from lowest to highest ICUR in the asthma patients Discussion The development of preference-based algorithms for the SF-36 and SF-12 to facilitate CUA has fostered studies that recognized these preference-based scores can differ from each other and from directly elicited valuations in patients with asthma, hypertension, lung transplantation, and osteoporosis [ 19 , 20 , 29 , 30 ]. However, the extent to which the differences might lead to different decisions on implementing or reimbursing for a new technology has been unclear. Using actual health states self-assessed by patients and imputing what might be considered conservative costs for an innovative treatment, our analysis demonstrated that ICURs based on the derivation algorithms can vary dramatically. The 10 algorithms produced a wide range of ICURs that varied more than 2-fold in magnitude for the asthma cohort and almost 3-fold in the stroke study. Although guidelines or thresholds for decision making based on cost per QALY are contentious, cost-effectiveness thresholds that health care decision makers are willing to accept in health care reimbursement decisions exist, if not explicitly, then implicitly. Some guidance has been published. The National Institute of Clinical Effectiveness (NICE) in the UK has indicated they do not have an explicit threshold [ 31 ], while a threshold of around £20,000 to £30,000 per QALY gained (about $37,000 to $55,000 in 2004 US dollars) [ 32 , 33 ] or slightly higher [ 34 ] has been cited as the value used in making decisions. Laupacis et al (1992) suggested that a treatment costing less than $20,000/QALY could be considered very cost-effective, a treatment costing between $20,000/QALY and $100,000/QALY was judged acceptable, while a treatment costing more than $100,000/QALY was deemed not likely to be cost-effective [ 35 ]. Other studies have suggested that $50,000/QALY provides a threshold for judging cost effectiveness [ 36 , 37 ]. Although arbitrary criteria, the application of any of the cited guidelines to the CUAs illustrated in the present study convey that the choice of algorithm can dictate whether the intervention is considered cost-effective or unacceptable. The choice of algorithm could determine whether a drug is considered for formulary listing, particularly if an emphasis is placed on cost-effectiveness as a criterion by the decision-making committee, as is often done by publicly funded health care systems. The CUA simulations illustrated how selection of a specific algorithm could lead to a different interpretation of the cost-effectiveness of an intervention. In the asthma cohort, algorithms by Lawrence [ 13 ], and the three equations by Franks [ 11 , 18 ] generated relatively smaller ICURs close to a level that may be considered very cost-effective, i.e. $20,000, with 95% confidence intervals that did not bound the $50,000/QALY threshold. In contrast, the Nichol, Fryback, and both Brazier methods produced ICUR point estimates above $50,000/QALYs that would be unacceptable by most guidelines. In stroke, the Lawrence and Franks methods again generated ICURs that would indicate the technology of interest was relatively cost-effective, at $30,000/QALY or less, while the algorithms by Shmueli [ 16 ] and Fryback [ 12 ] produced ICURs over $50,000/QALY. In examining the robustness of the results, all algorithms produced ICURs below $20,000/QALY when incremental costs for the hypothetical intervention are reduced to less than $500, but algorithm selection becomes critical as incremental costs increase and thresholds such as $20,000/QALYs or $50,000/QALY are crossed. Changes in the rank order of algorithms between conditions can be explained, not only by differences in the preference-based weighting assigned to each of the domain/summary scores, but several additional factors. There are differences in the SF-36 items or subscales retained by some of the methods. For instance, Brazier's SF-6D based on the SF-36 does not include GH, while the score generated by the Shmueli algorithm is largely influenced by the GH domain. The responsiveness/sensitivity of algorithms appears to be somewhat related to the scale range. It was not surprising that Fryback's method produced relatively larger ICURs that implied the intervention was less cost effective, as Fryback's method had a much smaller range of scale relative to the other algorithms (Table 1 ). Algorithms that incorporate demographic characteristics, such as the Nichol and Lundberg methods, provide estimates that are influenced by age of the cohort and could contribute to changes in their rank order. In order to provide some guidance in the selection of preference-based algorithms for the SF-36 and SF-12 the algorithms were appraised in the context of their theoretical and methodological foundations, source of community-based preferences, and their relative potential to enhance or deter the uptake of new technology. The study results clearly illustrated that choice of algorithm can affect the estimated ICUR, and that there was a tendency for the Fryback and Shmueli methods to generate higher estimates of ICURs relative to the other algorithms. From a third-party payer perspective, algorithms generating higher ICURs would appeal to third-party reimbursement decision makers with short-term budget constraints, as algorithms that generate higher ICURs provide less encouraging evidence in the adoption of new technology when considered in the context of the $/QALY benchmarks previously discussed. The Panel on Cost Effectiveness of Health and Medicine [ 2 ] recommended that preference-based measures have a theoretical basis and represent community-based preferences. The Brazier algorithms are arguably most favorable on a theoretical basis. Only the Brazier, Lundberg, and Shmueli algorithms were based on preferences directly elicited from the general populace, i.e. first generation. The Lawrence, Franks, Nichol, and Fryback methods mapped the SF-12/SF-36 onto scores obtained from indirect utility-based measures, e.g. EQ-5D, HUI2, to derive what we termed "second generation" preference-based algorithms. Such an approach is limited by differences in the descriptive systems [ 17 ]. Interestingly, algorithms derived from directly elicited valuations of health states (i.e. first-generation mapping) tended to generate smaller magnitudes of change compared to the algorithms that mapped the SF-36/12 using other indirect utility measures (i.e. second-generation mapping). One explanation for the second-generation algorithms producing larger change scores is that several of them were derived from the utility scores of the HUI3 and EQ-5D, which have broader scale ranges compared to the SF-6D [ 38 ]. A further consideration is the theoretical foundation for the elicitation technique used in the valuation study. Only Brazier employed methodology using the SG technique for first-generation mapping. The SG has the most appeal in economic theory due to its foundations in Expected Utility Theory (EUT), although it has been suggested that the axioms of EUT are empirically flawed [ 39 ], and requires the respondent possess a rudimentary understanding of probabilities. Scores generated by Lundberg, Shmueli, and Fryback methods were based on first or second generation mapping of the SF-12/SF-36 onto scores from rating scales. Rating scales have been criticized for lack of theoretical basis in economics [ 39 , 40 ], as a rating scale is not a choice-based technique and its ability to represent preferences on a cardinal scale is debatable. In contrast, the TTO and SG are choice-based techniques that generate utilities [ 2 ]. Lundberg utilized a variant of the TTO in addition to the VAS, but the complexity of the TTO task does not lend itself to a mail survey design. Lundberg observed that the TTO models did not perform as well as the VAS. Most of the algorithms were developed using self-assessed preferences for health status from a general population where severe states are rare, rather increasing the representation of more severe health states by statistical design, as done by Brazier [ 10 , 17 ] and by other developers of preference-based measures [ 4 , 7 ]. Given that HRQL may be valued differently between countries [ 41 ], an algorithm based on the preferences of a representative sample of the general population for the country of interest would be most desirable for resource allocation decision-making on the societal level, e.g. when the payer is the national ministry of health. The algorithms for the SF-36 find their preference-based origins from a diverse range of national sources. The algorithm by Shmueli was based on valuations obtained from representative samples of the Israeli Jewish population [ 16 ], while Lundberg's algorithm was based on valuations from the Sweden populace [ 14 ]. Brazier's utilities for health states were elicited from respondents in the United Kingdom [ 10 ]. The preferences for algorithms derived by Franks (EQ-5D) [ 11 ] and Lawrence [ 13 ] were mapped from the EQ-5D scoring function derived from the general population in the United Kingdom [ 7 ]. Fryback [ 12 ] mapped scores from the QWB that were based on community-based preferences from San Diego, California, USA [ 3 ]. The Nichol [ 11 , 15 ] and Franks [ 11 ] algorithms were mapped from the utility-based scores of the HUI2 and HUI3 systems, respectively, that were originally elicited from respondents in Ontario, Canada [ 4 , 5 ]. Nichol and Lundberg algorithms may not be considered as representing general population values because they include demographic variables such as age and/or gender. At present, only the Fryback algorithm has preferences originating from a community in the US, albeit a second generation mapping of those preferences. Among the algorithms presently available, Brazier's algorithms for the SF-12 and SF-36 appear to be most favorable because of their methodological and theoretical basis. From the perspective of the third party reimbursement decision maker, the Brazier algorithms are not among those that tend to encourage adoption of new technology, tending to provide relatively higher estimates of ICUR. For those decision-makers, those algorithms would appear to be more fiscally conservative in the sense that they would not promote the adoption new technology any more than the other methods according to the results of this study. Although similar estimates are obtained using the Brazier SF-36 and SF-12 algorithms [ 17 ], it would be preferable to utilize the Brazier SF-36 algorithm rather than the SF-12-based algorithm if responses to the SF-36 are available because of the richer information afforded by the descriptive system. If alternative algorithms are used for CUA, it may be suggested to test robustness of conclusions by sensitivity analysis using Brazier's SF-36 or SF-12-based algorithms. At present, no SF-36/SF-12 algorithm has been published based on the first generation preferences of the US general population. As there is evidence to support health states valuations by the general US population differ from other countries[ 41 ], this represents an opportunity for future research leading to the development of an algorithm specific to the US as well as for other countries. Note that there are several limitations and assumptions to the CUAs simulated in this paper. The primary purpose was to determine whether choice of preference-based algorithm applied to SF-36/SF-12 data has the potential to change the conclusion of a CUA; hence, aspects of the CUA not central to the purpose were simplified. For example, incremental costs were assumed to be constant, whereas in reality, considerable cost variance would be observed across patients. CUAs were performed in two patient populations, i.e., asthma patients and stroke patients, rather than using a single data set, to enhance the generalizability of the results. The rank order of the algorithms is limited to the datasets examined in this study, however, and comparisons of the algorithms across more diseases/conditions and persons with different demographic characteristics may provide stronger evidence of the rank order "stability". Change scores and thus ICUR estimates depend on baseline health status and the impact of an intervention on the various domains of health as captured by changes in responses to the SF-12/SF-36 items. Note that baseline domain scores for asthma and stroke cohorts were lower than US-based population norms. Several algorithm developers provide caveats for the application of their algorithm, including concerns about profiles severely limited by ceiling or floor effects [ 12 ], and inconsistent estimates and overprediction of poorest health states [ 10 ]. For instance, the descriptive system of the SF-6D is more concentrated at the milder end of health problems relative to the EQ-5D [ 42 ]. These concerns may be particularly relevant to the stroke cohort, where floor effects were observed. Conclusion In summary, SF-36/SF-12 preference-based algorithms tend to generate a wide range of ICURs that can potentially lead to different reimbursement decisions. Brazier's algorithms for the SF-36 and SF-12 had an arguably stronger methodological and theoretical basis, and tended to produce higher ICURs. For decision-makers who consider cost-effectiveness in the decision to reimburse for a new medical technology, selection of an algorithm that generates relatively higher ICURs would provide less convincing evidence of the cost-effectiveness of a new technology and consequently, its uptake. The "second-generation" algorithms mapped from other indirect preference-based measures tended to produce lower ICURs. When an alternative algorithm is selected, sensitivity analysis is recommended using the Brazier SF-12/SF-36 algorithm in order to examine the robustness of CUA. There remains a need for an SF-36/SF-12 algorithm developed from U.S.-based general population preferences with strong methodological and theoretical foundations. Authors' contributions Drs. Pickard and Lee were responsible for the conception of the study and acquisition of data. Mr. Wang analyzed the data. Dr. Pickard and Mr. Wang were involved in the drafting of the article. All authors contributed to the interpretation of results and revising the article for important intellectual content.

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539043

Strengthening the Role of Genomics in Global Health

How genomics and related health biotechnologies can improve the health of the poor and contribute towards meeting the Millenium Development Goals

Development experts and policy makers agree that investment in science and technology is important for economic growth and development. The 2001 United Nations (UN) Development Programme report, Making New Technologies Work for Human Development , identified technical progress as the largest factor in reducing mortality rates and improving life expectancy from 1960 to 1990 [1] . A May 2004 report to UN Secretary-General Kofi Annan from the InterAcademy Council on Science and Technology Capacity supports the view that mobilization of sound scientific knowledge and evidence-based principles is needed to address critical world issues such as poverty, disease, and the effects of globalization and economic transformation [2] . Annan himself has drawn attention to the importance of science capacity for global development, observing that “no nation can afford to be without its own [science and technology] capacity” [3] . This capacity is essential if the world is to achieve the UN Millennium Development Goals (MDGs), which were adopted by all UN members in 2000 in a commitment to promote sustainable development and eliminate poverty in the world. As part of the Millennium Project, the UN established task forces to come up with strategies to help developing countries achieve the MDGs. One of these is the Task Force on Science, Technology, and Innovation (Task Force 10), created in recognition of the fact that many of the goals, especially those related to health and the environment, cannot be realized without a strong contribution from science and technology [4] . In a report titled Genomics and Global Health , presented recently to Task Force 10, we addressed how genomics and related health biotechnologies can improve global health and contribute towards meeting the MDGs [5] . The report shows how the world can unite in a global approach to meet these objectives and what steps developing countries themselves are taking to harness these technologies. The main findings of the report are summarized in our conclusions below. Genomics Can Contribute to the MDGs Genomics refers to the powerful new wave of health-related life sciences energized by the human genome project and the knowledge and tools it is spawning. It is a relatively new science that has tremendous potential to address health problems in developing countries. The role of genomics in global health has been highlighted previously in the World Health Organization's 2002 report [6] , and explored further in a technology foresight exercise by the University of Toronto Joint Centre for Bioethics [7] . Genomics-related technologies, including DNA sequencing and bioinformatics, were once considered expensive, exotic, and applicable only to wealthy nations, but this perception has been changing over the past few years. Through the efforts of companies and institutions worldwide, certain applications have become simpler and cheaper to the point that they can start replacing older technologies that are currently used for health care in poorer nations. Such simple and easy-to-use tests are being developed for tuberculosis, hepatitis C, HIV, malaria, and other diseases (e.g., the OptiMAL rapid malaria test [ http://www.malariatest.com/ ]). Recombinant vaccines, a result of genetic engineering, promise to be safer, cheaper, and possibly easier to store and transport than traditional vaccines [7] . Microorganisms with remarkable biochemical properties show promise of being able to reduce pollution, making water safer to drink [8] . Table 1 provides a snapshot of how genomics and related biotechnologies can support some important MDGs [9] ; a more complete discussion can be found in our report [5] . Table 1 Genomics and Related Biotechnologies Can Support the MDGs a Source: Global Fund to Fight AIDS, Tuberculosis, and Malaria ( http://www.theglobalfund.org ) GM, genetically modified; STD, sexually transmitted disease What the International Community Can Do In Genomics and Global Health [5] , we argue that genomics knowledge should be considered a global public good [10] . We need to establish a governance mechanism that fosters a balance between genomics knowledge as a public good and the application of this knowledge to foster private-sector interests. We propose the creation of a global partnership, the Global Genomics Initiative (GGI), to promote genomics for health. We see this as a network of industry leaders, academics, concerned citizens, non-governmental organizations, and government officials, with strong representation from the developing world. The proposed GGI would highlight broad actions that should be taken at the global level to apply genomics to development issues in this new era of globalization. Participation in the GGI would strengthen capacity in biotechnology worldwide by increasing international and inter-sectoral exchange of knowhow, and encouraging partnerships between countries. The GGI could also facilitate the sharing of good practices. For example, the Canadian Prime Minister, Paul Martin, in his February 2004 reply to the Speech from the Throne, set a long-term target for Canada to devote 5% of its research and development spending to the challenges of developing countries. If successfully implemented and replicated by other industrialized countries, this target could make a real difference to global health. What Developing Countries Can Do Our report concludes that the key actors are developing countries themselves. We explore how to put genomics and related technologies to work in developing countries within the next 5–10 years. Developing countries with the scientific capacity and institutional arrangements that allow creation, utilization, adaptation, and diffusion of genomics are well positioned to harness this new science for development ( Figure 1 ). Learning is important for building genomics capacity, and is central to the creation of national systems of innovation (NSIs) in biotechnology in developing countries. Figure 1 A Rapid Test for HIV Used in Jaipur, India Biotechnology has a vital role to play in developing better diagnostic tools for diseases such as HIV, tuberculosis, and malaria. (Photo: World Health Organization/P. Virot) Today there are examples of strategies that some developing countries, including China, Cuba, Brazil, India, and South Africa, have followed to institute learning processes that are helping them to build NSIs in biotechnology. China seized the opportunity to take part in the Human Genome Project and quickly set up major institutions in genomics, such as the Beijing Genomics Institute, equipped with state-of-the-art sequencing facilities and computers. It has also followed a strategy of private-sector development in line with the NSI framework. Because of a government policy encouraging their return, Chinese expatriates are increasingly active in setting up small health biotechnology firms, bringing to the country knowledge from the world's major centers for genomics and related technologies. The government in Cuba became interested in biotechnology in the early 1980s when the field was still in its infancy and created an interdisciplinary group, the Biological Front, to explore the possibilities of the technology for Cuba. It has continued to support biotechnology even during periods of economic hardship, set up institutions with research, development, and manufacturing facilities, and encouraged linkages between these institutions by setting up a biotechnology cluster, the West Havana Scientific Pole. Encouraging linkages has been a core policy of the government in Cuba, and its health biotechnology development has benefited from the ties with a strong public health system. Brazil has a relatively long history of supporting science and technology, and the country is increasingly focusing on genomics and related technologies. The lack of commercialization of its cutting edge science and technology has been a weakness of the system in Brazil, but the country is now trying to overcome this weakness by proposing an “Innovation Law” that encourages cooperation between universities and the private sector. Since its independence in 1947, India has followed a vision to improve the quality of life of its people by emphasizing science and technology. Limited resources and a patenting system that did not allow patenting of pharmaceutical products but only patenting of processes encouraged firms to come up with low-cost process innovation. This has resulted in health products such as the Shanvac-B hepatitis B vaccine, which is produced in India for a fraction of the cost in developed countries. The South African government's Biotechnology Advisory Committee recognizes that successful commercialization of public-sector-supported research and development requires strong linkages within the NSI. The committee has recommended the creation of several Regional Innovation Centres to act as nuclei for the development of biotechnology platforms that can effectively launch new products and services. These strategies will provide important lessons for many other developing nations as they begin participating in the genomics revolution. Six Conclusions to Our Report First, the development gap between developing countries and the industrialized world continues to grow. The international community is beginning to promote science and technology to reduce this gap. The genomics revolution holds tremendous potential to improve health in developing countries and, if harnessed appropriately, could help to reduce the development divide. Second, genomics and related biotechnologies can help to achieve the UN MDGs. Fast, accurate molecular diagnostic devices, safer recombinant vaccines, female-controlled vaginal microbicides, and low-cost bioremediation tools are some examples of biotechnologies that can have an impact. Third, genomics knowledge has the characteristics of a global public good. In order to harness the benefits of genomics for development, the developing world needs, above all, access to genomics knowledge. Fourth, the promotion of the science of genomics as a global public good and the encouragement of global knowledge flows could best be achieved through international partnerships. A GGI involving an international partnership of public and private entities from both developed and developing countries could catalyze genomics knowledge and learning worldwide. Fifth, countries that have genomics capacity are best positioned to take advantage of the genomics revolution to meet their health needs. For the transfer of technologies to be effective and sustainable, it must be accompanied by transfer of science and knowledge. As well, receiving countries must have the capacity to absorb and use the technology. And sixth, learning is important for building genomics capacity, and is central to the creation of NSIs in biotechnology in developing countries. These countries can strengthen the building blocks of the NSI framework by doing the following: re-energizing academic institutions and public-sector research to strengthen their science base; training people and building human capital to use, adapt, and innovate biotechnologies; encouraging regional and international cooperation to create new channels for knowledge exchange and trade; improving the policy environment (including intellectual property laws and regulation) to encourage the building of capacity; and fostering the growth of the private sector, encouraging it to address local health needs, and strengthening linkages between public and private sectors to create new biotechnology goods and services.

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549201

GeneNotes – A novel information management software for biologists

Background Collecting and managing information is a challenging task in a genome-wide profiling research project. Most databases and online computational tools require a direct human involvement. Information and computational results are presented in various multimedia formats (e.g., text, image, PDF, word files, etc.), many of which cannot be automatically processed by computers in biologically meaningful ways. In addition, the quality of computational results is far from perfect and requires nontrivial manual examination. The timely selection, integration and interpretation of heterogeneous biological information still heavily rely on the sensibility of biologists. Biologists often feel overwhelmed by the huge amount of and the great diversity of distributed heterogeneous biological information. Description We developed an information management application called GeneNotes. GeneNotes is the first application that allows users to collect and manage multimedia biological information about genes/ESTs. GeneNotes provides an integrated environment for users to surf the Internet, collect notes for genes/ESTs, and retrieve notes. GeneNotes is supported by a server that integrates gene annotations from many major databases (e.g., HGNC, MGI, etc.). GeneNotes uses the integrated gene annotations to (a) identify genes given various types of gene IDs (e.g., RefSeq ID, GenBank ID, etc.), and (b) provide quick views of genes. GeneNotes is free for academic usage. The program and the tutorials are available at: . Conclusions GeneNotes provides a novel human-computer interface to assist researchers to collect and manage biological information. It also provides a platform for studying how users behave when they manipulate biological information. The results of such study can lead to innovation of more intelligent human-computer interfaces that greatly shorten the cycle of biology research.

Background In a genome-wide profiling project, researchers usually select many sets of genes (or ESTs) for further investigation based on the computational analyses of the experimental data. For example, a set of genes is selected because they are clustered together based on their mRNA levels. To generate or support biologically meaningful hypotheses, researchers need to selectively and systematically collect information about the genes/ESTs from various sources. For example, huge amount of gene annotations have been accumulated over decades in distributed databases. In addition, there are plenty of online computational tools (e.g., BLAST [ 1 ], TMHMM [ 2 ], MEME [ 3 ], etc.) that can be customized to generate invaluable information complementary to the local computational analyses of researchers. Most databases and online computational tools require a direct human involvement. Sometimes, it is extremely difficult, if not impossible, to perform further computational analyses on the collected information. For example, a cellular image often contains large amount of important information that can be easily understood by human but is beyond the capability of existing computational tools. Therefore, the timely integration and interpretation of the collected information still relies heavily on the sensibility of biologists. However, it is a challenging task to effectively collect and manage various types of information of interest. Researchers often feel overwhelmed by not only vast amount of information but also the great diversity of information types. To facilitate this task, we developed GeneNotes that provides an integrated environment for surfing the Internet, recording information, annotating genes, and retrieving information in the form of text, HTML, image, PDF, word file, and so on. Implementation Architecture We maintain a server (Figure 1 ) that integrates gene annotations from many major databases (e.g., HGNC [ 4 ], MGI [ 5 ], RGD [ 6 ], FlyBase [ 7 ], WormBase [ 8 ], PlasmoDB [ 9 ], SGD [ 10 ], KEGG pathway DB [ 11 ], etc.). The integrated gene annotations are stored as XML files, which are updated every two weeks. GeneNotes runs locally on users' computers and uses the integrated gene annotations to identify genes given various types of IDs (e.g., RefSeq ID, GenBank ID, UniGene ID, LocusLink ID, etc.). There is one menu in GeneNotes that allows the user to update the annotation files from the server. Once a gene is identified, GeneNotes can visualize Gene Ontology annotation of the gene, list its other annotations (e.g., name/symbol/synonyms/products, RefSeq ID, GenBank ID, UniGene ID, LocusLink ID, Model Organism database ID, protein information, etc.), and generate hyperlinks to major databases (e.g., Swiss-Prot [ 12 ], UCSC Genome DB [ 13 ], KEGG pathway DB [ 11 ], etc.) for the user to jump around those databases easily. GeneNotes also supports Affymetrix probe sets given the corresponding GeneChip ® annotation files, which can be downloaded from the web site of Affymetrix. GeneNotes manages information by projects (Figure 2 ). Each project contains a note database and several lists of genes/ESTs. The gene/EST lists are selected by users and can be edited anytime via the GUI of GeneNotes. Each gene/EST can have many notes that contain multimedia information. For example, a note could be a segment of text, an image, a PDF file, a word file, a local copy of a web page, and so on. Create, collect, and manage notes GeneNotes offers many useful functions. The most attractive feature to biologists is the function for creating, collecting, and managing notes for genes/ESTs. Basically, there are three ways for creating/collecting notes. First, GeneNotes has an embedded Web browser, which allows the user to surf the Internet. The user can selectively record useful information segments shown in the Web browser or save a web page as a note. Saving a web page as a note is especially useful when the web page contains the non-text results (e.g., images, logos, etc.) generated by a remote computational server. GeneNotes automatically stores the sources of notes and allows users to trace back to the sources of notes later. Second, users can create text notes to summarize their thoughts/comments about genes/ESTs. Finally, users can create notes linked to local files (e.g., images, PDF files, word files, etc.). The user can directly modify a text note and add annotations to non-text notes. Each note has an editable title. A meaningful title helps the user recall what information the note contains. When the number of notes is large, it may become difficult for users to browse and locate notes. GeneNotes allows users to organize notes into directories, which can be defined by categories. Note database Currently, GeneNotes runs on Microsoft Windows 2000/XP and uses Microsoft Data Access Components (MDAC) 2.7 to manipulate the note database. MDAC 2.7 provides the same Data Access core components as Windows XP SP1. Windows 2000 users need to download and install MDAC 2.7 or the latest version of MDAC, which are free at the web site of Microsoft. We are considering developing a platform independent version of GeneNotes and using other free database software such as MySQL [ 14 ]. GUI The GUI of GeneNotes is flexible and user friendly. It contains the following main windows: project explorer, gene list window, note window, gene property window, Gene Ontology visualization window, and web browser window. The project explorer displays the content of a project, e.g., gene lists, the note database file, Affymetrix GeneChip ® annotation files, etc. It allows users to edit the project, e.g., add/delete gene lists, create/change the note database, add/delete Affymetrix GeneChip ® annotation files, etc. The user can select a gene list in the project explorer. The selected gene list will be displayed in the gene list window. When a gene is selected in the gene list window, its properties (e.g., name/symbol/synonyms, RefSeq IDs, GenBank IDs, UniGene ID, etc.) will be displayed in the gene property window and its Gene Ontology annotation will be visualized in the Gene Ontology visualization window. The gene property window also displays a set of hyperlinks that are linked to the records of the selected gene in remote biological databases (e.g., HGNC [ 4 ], MGI [ 5 ], RGD [ 6 ], FlyBase [ 7 ], WormBase [ 8 ], PlasmoDB [ 9 ], SGD [ 10 ], Swiss-Prot [ 12 ], UCSC Genome DB [ 13 ], KEGG pathway DB [ 11 ], etc.). Once a hyperlink is clicked, GeneNotes will display the corresponding URL in the web browser window. The web browser window allows user to surf the Internet freely. All windows are dockable. Users can configure of the interface by dragging and dropping the window to virtually wherever they want. If a window is set as auto-hide, it will hide itself when it is inactive so that the computer screen can be used to display other windows. Discussion and conclusions GeneNotes provides a novel human-computer interface for researchers to effectively and efficiently manage multimedia biological knowledge. There are many online databases (e.g., Entrez Gene [ 15 ], GeneCards [ 16 ], etc.) providing pre-compiled information about genes/ESTs. GeneNotes has different purposes. It gives users freedom to selectively collect information and create their own databases to store heterogeneous biological information. At the same time, GeneNotes allows users to make full usage of those online databases. GeneNotes stores notes locally so that the notes are accessible when computers are offline. GeneNotes organizes information in the order of project, gene/EST list, and notes. This not only makes it easier for researchers to switch from one gene/EST to another one but also helps researchers obtain global view about the ongoing status of the project. We are currently pursuing the direction to innovate more intelligent human-computer interface to help biologists collect and manage information by observing how biologists using GeneNotes. Availability and requirements Project name: GeneNotes Project home page: . Operating system(s): Windows 2000/XP Programming language: C# License: Free for non-commercial usage. Authors' contributions PH was responsible for the conception, design, implementation, and testing of the GeneNotes program. WHW was responsible for its conception, design, and testing and provided overall project coordination. Both authors have read and approved the final manuscript.

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548692

Effectiveness of different databases in identifying studies for systematic reviews: experience from the WHO systematic review of maternal morbidity and mortality

Background Failure to be comprehensive can distort the results of a systematic review. Conversely, extensive searches may yield unmanageable number of citations of which only few may be relevant. Knowledge of usefulness of each source of information may help to tailor search strategies in systematic reviews. Methods We conducted a systematic review of prevalence/incidence of maternal mortality and morbidities from 1997 to 2002. The search strategy included electronic databases, hand searching, screening of reference lists, congress abstract books, contacting experts active in the field and web sites from less developed countries. We evaluated the effectiveness of each source of data and discuss limitations and implications for future research on this topic. Results Electronic databases identified 64098 different citations of which 2093 were included. Additionally 487 citations were included from other sources. MEDLINE had the highest yield identifying about 62% of the included citations. BIOSIS was the most precise with 13.2% of screened citations included. Considering electronic citations alone (2093), almost 20% were identified uniquely by MEDLINE (400), 7.4% uniquely by EMBASE (154), and 5.6% uniquely by LILACS (117). About 60% of the electronic citations included were identified by two or more databases. Conclusions This analysis confirms the need for extending the search to other sources beyond well-known electronic databases in systematic reviews of maternal mortality and morbidity prevalence/incidence. These include regional databases such as LILACS and other topic specific sources such as hand searching of relevant journals not indexed in electronic databases. Guidelines for search strategies for prevalence/incidence studies need to be developed.

Background The importance of comprehensive search strategies to identify 'all relevant articles' when conducting systematic reviews has been long documented [ 1 ]. Comprehensive strategies include systematic searching of multiple databases as well as hand searching and contacting relevant experts. These strategies, however, may yield thousands of citations from which only a small number is eventually included in the review. Knowing which sources yield a reasonable number of relevant studies on a health topic may help those planning and conducting systematic reviews in that particular area. At the World Health Organization (WHO), we have conducted a systematic review of prevalence/incidence of maternal mortality and morbidities from 1997 to 2002. The primary objective of this review is to assist in mapping the burden of reproductive ill-health by providing a comprehensive, standardized and reliable tabulation of data on the prevalence/incidence of maternal morbidity and mortality [ 2 ]. This article evaluates the usefulness of different sources in identifying data for the systematic review. We also discuss limitations of the databases and implications for future systematic reviews of observational studies. Methods The methodology of the systematic review and the search strategy have been described elsewhere [ 3 ]. In brief, we searched for reports of maternal mortality and morbidity across various study designs (cross-sectional, cohort, census, RCTs, etc.). The search included multiple electronic databases: MEDLINE, Popline, EMBASE, CINAHL, CAB Abstracts, Econlit, Sociofile, LILACS, BIOSIS and PAIS International. Specialist librarians together with the reviewers developed database-specific search strategies according to the particular subject headings and searching structure of the databases (See Additional file 1 ). Given the importance of retrieving data from developing countries, we also identified and searched databases in developing countries such as Index Medicus of the Eastern Mediterranean Region (IMEMR) [ 4 ]; African Index Medicus (AIM) [ 5 ]; IndMED [ 6 ], a bibliographic database of Indian biomedical journals; and HELLIS.ORG [ 7 ], a network of health science libraries across Asia. However, the search for some of these databases did not yield complete results due to limited functionality of these systems (e.g. lack of essential information from the citation, inconsistencies) and their results, except for IMEMR, are not presented independently but under 'other' in Table 1 . The search also included hand searching of journals not indexed in major databases and available at WHO's library, government reports, screening of reference lists of retrieved articles, congress abstract books, and contacting experts active in the field for unpublished datasets. Table 1 Results of the various types of searches Source Number identified Number included Number unique included* Sensitivity (%) Precision (%) MEDLINE 38986 1590 400 61.6 4.1 Popline 3255 297 91 11.5 9.1 EMBASE 23133 1135 154 43.9 4.9 CINAHL 9090 263 9 10.2 2.9 CAB Abstracts 4317 190 19 7.4 4.4 Econlit 188 4 1 0.2 2.1 SocioFile 1618 32 8 1.2 2.0 LILACS 1456 137 117 5.3 9.4 BIOSIS 3313 436 21 16.9 13.2 PAIS International 705 21 3 0.8 3.0 IMEMR 109 11 5 0.4 10.1 All Electronic databases** 64098 2093 NA 81.1 3.3 Other § 487 487 487 18.9 NA TOTAL ± 64585 2580 2580 NA 4.0 * Refers to the number of citations that were exclusively identified by each database. ** Refers to all citations identified through the electronic databases above after duplicate entries are removed. § Includes hand searching, contacting experts, conference proceedings, reference lists, library collections of journals, and databases in developing countries. ± Refers to all citations identified through all methods after duplicate entries are removed. NA: Non-applicable We downloaded all citations identified by electronic databases into Reference Manager ® software. Selection of eligible studies involved two stages; the first stage consisted of screening of title and/or abstracts from the citations downloaded. Citations were excluded if any of the following applied: (i) data collection dates were not reported, (ii) data were collected only before 1990, (iii) part of the data were collected before 1980 and disaggregation by year was not possible (in order to exclude data before 1990), (iv) number of study participants was less than 200, (v) the study design was case-control and incidence/prevalence estimates from the defined population cannot be calculated, (vi) the methodology was not described. The second stage consisted of full-text evaluation of those citations that were not excluded in the first step applying the same criteria. For practical reasons, studies identified by other sources were only entered in Reference Manager ® if they were eventually included in the review. We recorded the source or sources of each citation. For each source, we calculated number of citations identified, included, and number included that were unique to the source. The sensitivity of each source was defined as the number of included citations identified by the source over the total number included. The precision was defined as the number of included citations identified by a source over the number of both included and excluded citations identified by that source. This review had no language restrictions and we recorded the language in which the report was written. Detailed results regarding languages will be reported separately. Two reviewers performed the screening for all citations. In order to estimate the level of disagreement between the two reviewers within 2.5% of the true value, they independently screened title/abstracts for a sample of citations (560). This sample size assumes a 95% confidence interval and that the level of disagreement between the two reviewers will not exceed 10% [ 8 ]. The percentage of agreement was 88.9% (95% CI 86.0% to 91.4%). The inter-observer agreement beyond chance was calculated using the Kappa statistics and found to be 0.60 (95% CI 0.52 to 0.69). This value corresponds to moderate to substantial agreement between the reviewers. Results For the time period from 1997 to 2002, 64098 different citations from electronic databases were identified of which 2093 were included. Additionally, 487 citations were included from other sources. There were 92 citations for which we could not obtain full text and, therefore, they could not be assessed (2% of those that required full-text evaluation). Table 1 shows a breakdown of the results by source including, for each source of data, number of citations identified, number included, number included unique to each source, sensitivity and precision. Overall, electronic databases identified four fifths (81.1%) of the included citations. MEDLINE and EMBASE which identified about 62% and 44% of the included citations respectively were most sensitive. Considering electronic citations alone (2093), almost 20% were identified uniquely by MEDLINE (400), 7.4% uniquely by EMBASE (154), and 5.6% uniquely by LILACS (117). About 60% of the electronic citations included were identified by 2 or more databases. Overall, in terms of precision, we included 1 in 25 screened citations (4%). The most precise database was BIOSIS where 13.2% of the screened citations were included; IMEMR, LILACS and Popline followed this with 10.1%, 9.4% and 9.1%, respectively (see Table 1 ). MEDLINE and EMBASE were similarly precise, 4.1% and 4.9%, respectively. Preliminary analysis regarding languages revealed that about 20% of the included studies were published in other languages than English. Spanish and French were, after English, the most used languages for reporting. Discussion Failure to identify relevant information in systematic reviews can result in bias [ 9 ]. The importance of including other sources of data in addition to electronic databases in general and MEDLINE in particular has been documented, especially for clinical or randomised controlled trials [ 1 , 9 - 11 ]. On the other hand, search strategies for systematic reviews of observational data on morbidities are less precise, more difficult to narrow the focus and have been studied to a lesser extent [ 12 ]. This led us to perform for our systematic review an extensive search strategy that is highly sensitive but barely precise. From 64098 citations identified only 2580 were included which represents 4% of the scrutinized articles. Although MEDLINE identified about 62% of all citations and 76% of electronic citations relevant for this review, sources of data other than the major electronic databases are confirmed to be crucial. Some 487 (one fifth) citations were identified by reference lists of articles, expert contacts, congress proceedings, abstract books, hand searching of journals available in libraries that are not indexed in electronic databases, and other emerging databases in developing countries. As expected, there has been a large overlap between databases: 60% were identified by two or more databases and about 44% were identified by MEDLINE and EMBASE together. These two databases also provided the largest number of unique citations and both are considered necessary. PAIS International and Econlit only identified 3 and 1 citations, respectively, that were not identified by any other database and they could probably be disregarded in future reviews. The nature of this systematic review with its focus on settings where burden of disease is highest necessitates extensive searching of developing country sources. However, literature from developing countries is difficult to access and it is not well represented in MEDLINE or other well-known electronic databases [ 13 , 14 ]. An editorial by Zielinksi in 1995 stated that only 2% of the journals indexed in MEDLINE or the Science Citation Index were from developing countries [ 15 ]. In 2004, the situation was similar. We calculated the number of journals published in developing countries and also indexed in MEDLINE to be about 6%. In 1996, the whole Latin American continent accounted for 0.39% of the total number of articles included in MEDLINE, down from a high of 2.03% in 1966 [ 16 ]. One of the reasons for this is the indexing of journals on a priority system where the impact factor of a journal influences its chances of being indexed. This results in country bias since western journals have in general higher impact factors, and they are therefore more likely to be indexed than those from developing countries. The value of LILACS database to improve the quality of systematic reviews has been previously reported [ 17 ]. Our analysis confirms LILACS as a unique source of information for the Latin America and the Caribbean region that is not covered in other databases (117 unique citations included). Unfortunately, specific databases for other less developed regions like Asia and Africa, are just emerging or their access and functioning limited (e.g. AIM, IMEMR, IndMED, HELLIS.ORG). Although these regional databases are included in the review, the results are not presented individually but under 'other' in Table 1 . With these databases, we experienced language barriers, difficulty in obtaining abstracts and full-text reports, inconsistencies, lack of essential information from the citation (e.g. year or title missing) and other technical problems. We believe that the low number of citations identified by IMEMR (see Table 1 ) is due more to the limitations mentioned above than to lack of data. These regional databases provide unique relevant citations and incomplete access limits their usefulness. Strengthening the functionality and improving the search facility of these databases could provide substantial relevant information. A limiting factor for identifying citations is related to late indexing of journals in electronic databases. Search strategies for this review were conducted in early 2003 to identify articles published in 2002 or earlier. While only few articles published in 2002 could be expected not to be in the databases by 2003, some articles published in 1997 were only appearing in the databases as late as 2003. Traditionally, EMBASE has been found to index faster than MEDLINE, thus supporting the argument to search multiple databases [ 18 ]. Furthermore, each database producer has a particular schedule that the searcher needs to be aware of. For example, MEDLINE available through OVID, due to the updating of the MeSH terms by the National Library of Medicine, will cease entry of new citations in November and only update the database in January of the following year. These factors need to be considered in assessing the yield from different databases. It is necessary to determine how to capture these 'late indexed' citations whether by delaying the running of the search or building into follow-up studies the need to capture these citations. The electronic search for this review would have probably captured more citations had it been run in 2004. This systematic review involved significant financial and human resources over a 3-year period [ 3 ]. Screening of a large number of citations and retrieving the full text of about 5000 articles have resource implications that need to be balanced with the benefits of the results. For this type of reviews, decisions on the extent of the comprehensiveness of the search strategy should take the resource implications into account. A careful selection of databases to be used and tailored search strategies for each database would help to maximise the benefits compared to costs. Conclusions 1. In contrast with RCTs, guidelines for search strategy of systematic reviews of observational studies in general, and incidence/prevalence studies in particular, need to be developed. 2. Searching beyond the major electronic databases such as MEDLINE or EMBASE is necessary to identify studies in journals from less developed countries. 3. Regional databases indexing citations from local journals not reaching MEDLINE are especially relevant for this type of systematic review. They need to be fully functioning and made worldwide accessible. A network for accessing the full text of these articles would be helpful. Competing interests The author(s) declare that they have no competing interests. Authors' contributions APB, LS, AMG, TA and LH developed the search strategy for the systematic review. APB and LS analysed the data and wrote the manuscript. AMG, TA and LH participated in the interpretation of results and provided key comments on the manuscript. 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 Detailed search strategy for electronic databases used for the systematic review. Click here for file

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IdentiCS – Identification of coding sequence and in silico reconstruction of the metabolic network directly from unannotated low-coverage bacterial genome sequence

Background A necessary step for a genome level analysis of the cellular metabolism is the in silico reconstruction of the metabolic network from genome sequences. The available methods are mainly based on the annotation of genome sequences including two successive steps, the prediction of coding sequences (CDS) and their function assignment. The annotation process takes time. The available methods often encounter difficulties when dealing with unfinished error-containing genomic sequence. Results In this work a fast method is proposed to use unannotated genome sequence for predicting CDSs and for an in silico reconstruction of metabolic networks. Instead of using predicted genes or CDSs to query public databases, entries from public DNA or protein databases are used as queries to search a local database of the unannotated genome sequence to predict CDSs. Functions are assigned to the predicted CDSs simultaneously. The well-annotated genome of Salmonella typhimurium LT2 is used as an example to demonstrate the applicability of the method. 97.7% of the CDSs in the original annotation are correctly identified. The use of SWISS-PROT-TrEMBL databases resulted in an identification of 98.9% of CDSs that have EC-numbers in the published annotation. Furthermore, two versions of sequences of the bacterium Klebsiella pneumoniae with different genome coverage (3.9 and 7.9 fold, respectively) are examined. The results suggest that a 3.9-fold coverage of the bacterial genome could be sufficiently used for the in silico reconstruction of the metabolic network. Compared to other gene finding methods such as CRITICA our method is more suitable for exploiting sequences of low genome coverage. Based on the new method, a program called IdentiCS ( Identi fication of C oding S equences from Unfinished Genome Sequences) is delivered that combines the identification of CDSs with the reconstruction, comparison and visualization of metabolic networks (free to download at ). Conclusions The reversed querying process and the program IdentiCS allow a fast and adequate prediction protein coding sequences and reconstruction of the potential metabolic network from low coverage genome sequences of bacteria. The new method can accelerate the use of genomic data for studying cellular metabolism.

Background Knowledge about the metabolic network of an organism is essential for understanding its physiology and phenotypic behavior. A comprehensive understanding of the metabolic network at the system level is particularly important for both biotechnological and biomedical research and is now made possible by rapid advances in genome sequencing and functional genomics. In silico reconstruction of metabolic networks from genome sequences of organisms represents a starting point for a systematic analysis of metabolism [ 1 - 3 ]. The functionality of the potential metabolic network of a given organism can then be further experimentally studied by system perturbations at both physiological and genetic levels [ 4 ]. Several methods and tools have been recently developed for the reconstruction, visualization and analysis of metabolic networks. These include general static metabolic network tools such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) [ 5 ], the Boehringer Mannheim metabolic charts [ 6 , 7 ] and dynamic or potentially dynamic tools such as WIT [ 3 ], MPW [ 8 ], EcoCyc [ 9 , 10 ] and PathFinder [ 11 ]. Metabolic network reconstruction is generally based on the identification of metabolic enzymes and the corresponding biochemical reactions in a specific organism. For this purpose the EC numbers of all possible enzymes need to be determined. The set of EC numbers of an organism may be obtained from the genome annotation. This conventional approach of metabolic network reconstruction is briefly summarized in Fig. 1A . It covers three successive steps: (1) gene finding, (2) database searching and function assignment and (3) metabolic reconstruction. In the first step, genes or coding sequences (CDSs) are predicted from the genome data using programs such as Glimmer [ 12 ], GeneMarkS [ 13 ], ZCURVE [ 14 ] or CRITICA [ 15 ]. Then, coding sequences are used as queries and compared to sequence databases such as GenBank, GenPept and SWISS-PROT or to databases of protein domains and functional sites such as InterPro [ 16 ], PROSITE [ 17 ], Pfam [ 18 ] etc. Based on the similarity, the function of the database entry may be assigned to a CDS as its annotation. From these function assignments the metabolic network can be constructed. This three-step approach is used for example in the WIT system [ 3 ]. Efforts were also made in some bioinformatic systems such as WIT to reconstruct metabolic networks from incomplete genome data [ 3 ]. The program suite ERGO™, a commercial version of WIT, integrates over 400 finished and unfinished genomes into a comprehensive network of metabolic and non-metabolic pathways [ 19 ]. No details about the WIT approach have been published and merely some information about 55 annotated genomes (Status: March 2004) is publicly available on the website of WIT [ 20 ]. The three-step method starting from gene finding has several drawbacks for the reconstruction of the metabolic network from incomplete or unfinished genome sequences. In unfinished sequences of a genome, especially in sequences with a low genome coverage (e.g. less than 4 fold), there may be many sequencing errors that do not warrant an accurate prediction of genes [ 21 ]. For example, the start or stop positions of CDSs may not be accurately predicted. Protein sequences translated from these CDSs may be completely wrong because of coding frame shifts. Fusion CDSs may be predicted, to which the function assignment is difficult. Moreover, a CDS that normally appears as one CDS in other organisms may be predicted as several smaller fragmented CDSs. On the other hand, existing CDSs may not be found at all, either because of sequencing errors or because of limitations of the gene finding software. For eukaryotes, the prediction of CDSs is even more difficult because of the existence of introns. To avoid these problems, alternative methods are required for directly reconstructing metabolic networks from unfinished genome data. Sequencing and annotation are still time and resource consuming. An as early as possible exploitation of the genome data is of importance for functional genome research. In this work, we propose a method to identify coding sequences for proteins (particularly for metabolic enzymes) directly from unannotated low-coverage genomic data for in silico reconstruction of the metabolic network. The method is demonstrated with genome data from two organisms. A program combining automatic prediction and function assignment of CDSs with a visualization and comparison of metabolic networks of different organisms is also delivered. Principle of the new method The principle of the new method is schematically shown in Fig. 1B . In comparison to the conventional three-step method (Fig. 1A ) our method can be called a two-step approach. To avoid the separate step of gene finding in the conventional methods, we propose to reverse the searching relationship between public databases and the query sequence: gene or protein sequences from public databases are taken as queries, while the sequences in the unannotated genome of a given organism are treated as a local database that can be searched using a standalone algorithm of BLAST [ 22 ]. This results in the prediction of possible CDSs in the genome and simultaneously their functions. Functional information about these CDSs is then used to reconstruct the metabolic network. Thus, our method can significantly simplify the process of CDS prediction and metabolic network reconstruction. By skipping over the separated steps of gene-finding and function assignment, our method can avoid or relax some of the problems of the traditional methods mentioned above. Results and Discussion Evaluation of IdentiCS for identifying protein coding sequences from genome sequences of S. typhimurium LT2 To examine the applicability of the method proposed, the well-annotated genome sequences of S. typhimurium LT2 [ 23 ] are used as "standard of truth" for statistic evaluation. According to the annotation given in the KEGG database, S. typhimurium LT2 has 4449 CDSs, out of which 1218 have been annotated with enzyme EC numbers. These CDSs encompass 656 different unique EC numbers. The reliability of CDS prediction by the program IdentiCS is evaluated by using a nucleotide database (KEGG genome) and a combined protein database (SWISS-PROT + TrEMBL + TrEMBL update) separately. The annotated coding sequences or proteins of S. typhimurium were filtered out of these databases before sequence alignment. All CDSs having an E-value less than 10 -10 were accepted and submitted for comparison with the KEGG annotation of S. typhimurium . The results are summarized in Table 1 . 92.6% and 97.7% (sensitivity) of the CDSs in the original annotation of S. typhimurium are identified by using the KEGG genome database and the whole protein database SWISS-PROT and TrEMBL, respectively. The sensitivity on the nucleotide level (91.1% and 98.2% for the two databases respectively) is similar as on the CDS level. These results suggest that the SWISS-PROT-TrEMBL based approach is more preferable than the KEGG genome based approach for our method. It is understood that the combined protein database SWISS-PROT and TrEMBL contains almost all of the known protein sequences available in public databases (including proteins in silico translated from nucleotide sequences) while the KEGG database contains only a limited number of sequenced and annotated genomes. The difference becomes more significant if the organism studied is evolutionarily far from any organism whose genome is completely sequenced and annotated. The specificity of the method is about 81–82% on the CDS level and 87.2–94.9% on the nucleotide level for the KEGG genome database and the whole protein database SWISS-PROT and TrEMBL. The moderate specificity on CDS level is due to the relatively high amount of additionally predicted CDSs (false positive). It should be mentioned that all the additionally predicted CDSs have quite strong statistic significance (most of them with an E-value 1E-20 – 1E-40). These additional CDSs may be missed in the original annotation and could in fact represent good candidates for an improved annotation of the genome. The inconsistence rate by IdentiCS is as low as 0.35% for the KEGG genome database and 0.64% for the SWISS-PROT and TrEMBL protein database, indicating the reliability of our method. In the above mentioned evaluation of the method, the cut-off E-value is less than 1E-10 for the CDS prediction. Further the effects of different scoring parameters (i.e. bits score, E-value and identities) and their cut-off values on the CDS prediction by using the database SWISS-PROT and TrEMBL are examined. (Fig. 2A,2B,2C) show the distribution of the true positive CDSs, false positive CDSs, sensitivity and specificity as function of bits score, E-value and identities respectively. The major part of the false positive CDSs is found in the regions of bits score less than ca. 80 and E-value larger than 1E-15. The specificity increases with the bits score and E-value in a form of a saturation curve while the sensitivity decreases almost linearly. This indicates that the prediction performance can be further optimized by choosing appropriate cut-off parameters. If the CDSs with bits score less than 75 (their corresponding E-values are higher than 1E-15 in most cases) are rejected, the false positive will decrease by 40% (from 987 to 602) while the false negative will increase from 110 to 144 (Table 2 ). The prediction specificity increases from 81.5% to 87.7% at the expense of a slight decrease in the sensitivity from 97.5% to 96.8%. The specificity of IdentiCS can be further improved by combining a third criterion, i.e. Identities > = 25% (Table 2 ). Thus, the sensitivity and specificity of IdentiCS for CDS prediction are satisfactory and can be balanced to certain extent by choosing proper scoring parameters. Identification of enzyme-coding sequences in S. typhimurium LT2 For the reconstruction of metabolic network it is desired to know the enzyme-coding sequences, and especially the EC-number containing enzymes in an organism. The possibility to use the EC number-containing subset of the combined protein database SWISS-PROT + TrEMBL to identify enzyme-coding sequences in S. typhimurium LT2 and thus to further reduce the computation time for constructing the metabolic network is examined (Table 3 ). 1894 of EC-number containing CDSs (EC-CDSs) are identified. Of the 1218 originally annotated EC-CDSs, 98.9% of them are identified with an annotation inconsistence rate of as low as 0.08%. The specificity appears to be relatively low due to the large number of false positives. However, if the prediction of EC-CDSs is compared to all the originally annotated CDSs, the number of true positive EC-CDSs is increased from 1204 to 1813 and the number of false positive EC-CDSs is decreased from 690 to 55, resulting in a specificity of 97.1%. The inconsistence rate still remains at a low level, indicating the prediction and function assignment for the additionally predicted EC-CDSs is correct and their EC numbers are missed in the original annotation. This can helps in reconstructing a more complete metabolic network. The KEGG genomes based prediction is also evaluated for its ability to predict the enzyme-coding sequences. 95.4% of the CDSs originally annotated to have an EC-number are correctly predicted and assigned with EC numbers. This value is slightly lower than the one based on the SWISS-PROT+TrEMBL database. The more complete protein databases are therefore more suitable for EC-CDS identification as well. Identification of enzyme coding sequences with different coverage of genome sequences of K. pneumoniae Both the KEGG genomes and SWISS-PROT-TrEMBL databases are used to identify enzyme-coding sequences from the 3.9-fold and 7.9-fold coverage genome sequences of K. pneumoniae . From the 3.9-fold coverage genome, IdentiCS identified 1169 and 1342 EC-CDSs by applying the KEGG genome database and SWISS-PROT-TrEMBL databases, respectively, whereas from the 7.9-fold genome sequences 1158 and 1495 EC-CDSs, respectively. As in the case of S. typhimurium, IdentiCS identified 15% to 30% more EC-CDSs with queries from SWISS-PROT-TrEMBL than with queries from KEGG for the two versions of K. pneumoniae genome sequences respectively. The number of EC-CDSs identified for K. pneumoniae is comparable to that identified for S. typhimurium with the respective databases. They are also comparable to the number (1156) of annotated EC-CDSs of E. coli based on the KEGG genome database. With the method proposed by Ma and Zeng [ 24 ], the structure and evolution distance of the metabolic networks of these three organisms and other 47 bacteria are compared. The metabolic network of K. pneumoniae is found to be most similar to those of E. coli and S. typhimurium (data not shown). Thus, the predicted number of enzyme-encoding sequences for K. pneumoniae appears to be reasonable. With the same 3.9-fold coverage genome sequences of K. pneumoniae , the method of WIT predicted 2650 EC-CDSs which are twice the number of EC-CDSs in E. coli and S. typhimurium . The EC-CDSs predicted by WIT are significantly smaller and fragmented, possibly because of the presence of too many errors in the unfinished genome sequences. The fragmentation problem was overcome in our method that leads to a significant reduction in the number of identified EC-CDSs. The less false positive EC-CDSs will further simplify experimental design such as for microarray to examine the metabolic network. A comparison of the unique EC numbers of EC-CDSs identified from the two different versions of genome sequences and by the different approaches reveals that the results of these different combinations share over 80% of common EC numbers (Table 4 ). The WIT version contains more EC numbers than other versions, obviously because the criteria used in our approaches allow a region to have only one function or an EC number whereas the method used by WIT allows more. With the 3.9-fold genome sequences both KEGG and SWISS-PROT based methods identified a certain number of EC numbers (44 and 81, respectively) that are not identified by WIT. Interestingly, the two different versions of genome sequences result in very close EC numbers. The KEGG based approach identified only 11 (1.68%) more and the SWISS-PROT-TrEMBL based approach identified merely 57 (7.76%) more by using the 7.9-fold genome sequences than by using the 3.9-fold genome sequences (Table 4 ). This indicates that the 3.9-fold coverage genome sequences result in a fairly good estimation of enzyme-coding sequences for the purpose of an in silico reconstruction of the metabolic network of K. pneumoniae . It would be of interest to examine if this also applies to other organisms or even lower genome coverage. The use of lower genome coverage sequences for studying cellular metabolism will greatly accelerate the exploitation of genome sequencing projects. The EC numbers of K. pneumoniae as identified by the combination of 7.9-fold genome sequences and SWISS-PROT and TrEMBL databases are summarized in Table 5 in terms of different functional categories. More than half of the enzymes are involved in the metabolism of carbohydrates, amino acids, cofactors and vitamins. 22.2% – 47.6% of the enzymes in the different KEGG metabolism categories can be found in K. pneumoniae (Table 5 ). These values are comparable to the values of several evolutionarily closely related strains such as Escherichia coli, S. typhimurium , S. typhi , Pseudomonas aeruginosa and Yersinia pestis . Comparison of IdentiCS and CRITICA for identifying coding sequence from low coverage genome sequences CRITICA is a well-developed program for the prediction of coding sequences [ 15 ]. It combines the comparative analysis of DNA sequences with noncomparative methods (i.e. dicodon bias). We compared CRITICA and IdentiCS for predicting CDSs from the two different versions of K. pneumoniae genomic sequences. The comparison is done on the basis of all the CDSs including non-enzyme coding sequences. The results are summarized in Table 6 . From the 3.9-fold coverage genome data, CRITICA predicts 6734 CDSs with a cut-off p-value = -4 suggested by Badger and Olsen [ 15 ], while IdentiCS predicted 5650 CDSs (with a cut-off E-value = 1E-10). 94.0% of the CDSs predicted by CRITICA are covered by the prediction of IdentiCS. O, In many cases two or more smaller CDSs predicted by CRITICA are covered by a CDS predicted by IdentiCS, obviously because of the relatively high sequencing errors in the 3.9-fold coverage genome data. CRITICA predicts 29 fusion coding sequences. Since they have similarities to two different functions, function assignment to this kind of fusion CDSs is uncertain. Half of the CRITICA-specific CDSs have p-values between 1E-4 and 1E-10. In comparison, of the 1348 CDSs merely predicted by IdentiCS, all have E-values less than 1E-10, 27% have E-values less than 1E-40; all the CDSs have an identity greater than 20% and 60% have an identity greater than 50%, indicating that the predictions by IdentiCS have a high confidence. From the 7.9-fold coverage genome data, CRITICA predicts 5135 CDSs. This number is much less than the CDS number predicted from the 3.9-fold coverage. This may be explained by the significant decrease of sequence errors in the 7.9-fold genome data. In contrast, CDSs predicted by IdentiCS are only 389 less than that predicted from the 3.9-fold genome data. 93.9% of the CRITICA predictions are covered by the 4512 CDSs predicted by IdentiCS. Only 8 CDSs predicted by CRITICA span two or more CDSs. This shows that the increase of sequence quality increases the precision of the prediction of CRITICA. Again, the IdentiCS-specific predictions have a high confidence: all with E-values less than 1E-10 and amino acid sequence identities greater than 20%, more than 50% with E-values less than 1E-20 and identities greater than 50%. The fact that in some cases fusion CDSs are predicted by CRITICA and in other cases many highly potential coding regions are not predicted as CDSs indicates a shortcoming in this algorithm for low quality contigs. When CRITICA finds a coding region with a high score, it tries to find the start and stop codons by extending this region to both upstream and downstream with the conditions of not decreasing the total score after extension. Sequencing errors, especially translation shifts, make it difficult for CRITICA to calculate the extension score correctly. In such cases, the algorithm used by IdentiCS does not need to locate the start and stop codons. Transcription frame shifts also have less interference to IdentiCS because it does not use predicted coding sequence as queries but uses entries from public database to search for coding sequences in the raw genome sequences of an organism. These features make IdentiCS more suitable for identifying possible protein-coding regions from low-coverage error-containing raw genome sequences than other available approaches. Reconstruction and visualization of metabolic networks for comparison With the identified enzyme-encoding sequences discussed above the potential metabolic networks of S. typhimurium and K. pneumoniae can be reconstructed and compared to other organisms. The reconstruction of metabolic networks can be done in a similar way as based on CDSs from annotated genome sequences as recently described by Ma and Zeng [ 1 ]. Briefly, from the identified EC numbers of CDSs, the set of biochemical reactions involved in the organism can be established with the help of a reaction database (i.e. a revised version of LIGAND [ 5 ] or BRENDA [ 25 ]). From the reaction set, a connection matrix is obtained that can be used to represent the metabolic network as a directed graph for computational analysis. For a straightforward visualization of the biochemical reactions related to a specific organism and especially for comparing the metabolisms of different organisms, the KEGG metabolic maps act as a blueprint for visualization of metabolic networks in this work. Reconstruction, comparison and visualization of the metabolic network have been integrated in the program IdentiCS as a built-in component. It can work directly with the coding sequences and their functions predicted by IdentiCS or with existing annotation files such as the those in Microsoft Excel format or in GenBank flat file format. To use the KEGG maps for metabolic reconstruction, comparison and visualization information from the KEGG metabolic pathways is reformed into an Excel template. Metabolic network reconstruction is realized by mapping the identified enzymes (EC numbers) to the KEGG metabolic maps. Different similarity levels of the identified enzymes can be displayed in different colors. All identified enzymes in the map are marked and linked to their annotations. Web links to other Internet databases such as IUBMB [ 26 ], BRENDA [ 25 ], WIT [ 3 ], KEGG [ 5 ], Ecocyc [ 9 , 10 ] and SWISS-PROT [ 27 ] are also integrated to offer the user a fast tool to access the relevant information. For metabolic network comparison, strain-specific colored boxes are drawn on the lower part of the EC number rectangle if that strain possesses this enzyme as demonstrated in Fig. 3 for the glycolysis pathways. This box is linked to the original annotation of the enzyme in that strain. The background of the enzyme box becomes green if this enzyme is found in all the compared organisms. In such a way an informative metabolic network is generated which can serve as a starting point for functional and comparative analysis of the metabolism of organisms under study. Conclusions The use of genome sequences from S. typhimurium and K. pneumoniae demonstrated the applicability and reliability of the new method proposed for in silico identification of protein coding sequences from unannotated genome sequences. The use of protein sequence databases SWISS-PROT and TrEMBL is more favorable than the use of KEGG genome database for identifying coding sequences and thus for metabolic network reconstruction. Furthermore, the method allows an adequate reconstruction of the potential metabolic network from sequence data with low coverage (e.g. < 4 fold) of the bacterial genome as shown for K. pneumoniae . Together with the algorithms for the automatic annotation of sequences, the visualization and comparison of metabolic networks, the method and program developed in this work can accelerate the use of genomic data for studying cellular metabolism. Methods Database preparation The applicability of the method proposed above was examined with the genome sequences of two organisms, namely Salmonella typhimurium LT2 and Klebsiella pneumoniae . The genome of S. typhimurium LT2 has been completely sequenced and well annotated [ 23 ]. Thus, the annotated genome sequences of S. typhimurium LT2 serve as a reference to evaluate the accuracy of the proposed method. The sequences and annotation for S. typhimurium LT2 were downloaded from KEGG [ 28 ](version of Dec. 18. 2003). The genome of K. pneumoniae has been recently sequenced and the annotation is still in progress. Two different versions of the raw genome data of K. pneumoniae (3.9-fold whole genome shotgun coverage in 920 contigs and 7.9-fold coverage in 341 contigs) obtained from the Genome Sequencing Center of Washington University [ 29 ] were examined in this study. Each version of the raw genome data was formatted as a local database for BLAST [ 22 ]. Two types of databases are used in this work for the prediction and function assignment of CDSs for a given organism, namely the nucleic acid database from KEGG and the non-redundant protein sequence databases from SWISS-PROT, TrEMBL and TrEMBL updates. The reason to choose the genome database from KEGG as query but not from other nucleic acid databases such as GenBank or EMBL is that KEGG contains the most extensive EC numbers for enzymes that are needed for reconstructing metabolic networks. Therefore, the genome database of KEGG version can serve as an EC number source and be used for the purpose of comparative analysis of genome-based metabolism. In contrast, the flat data files from GenBank and EMBL do not contain the necessary enzyme index information in many cases. SWISS-PROT is human-curated and therefore more preferred. SWISS-PROT and its sister database TrEMBL (SWISS-PROT Release 42.7, TrEMBL Release 25.7, released on 15 Dec. 2003) were obtained from the Swiss Institute of Bioinformatics [ 30 ]. Not "fasta" format files but SWISS-PROT flat files were used because the enzyme EC numbers may not be included in the fasta format files available on the FTP site. Entries in the databases that do not contain EC numbers can be filtered out before the sequence alignment step to shorten the computational time if the purpose is merely to identify metabolic enzymes and to reconstruct the metabolic network. For identifying all possible CDSs, the complete SWISS-PROT and TrEMBL databases are used. Automatic prediction and annotation of protein-coding sequences The annotation process is based on similarity comparison as normally used in other annotation processes. The difference is that in our approach the gene or protein sequences from public databases are used as queries to search and locate similar ones in the raw genome sequences. When proteins from public database are used as queries, the tblastn algorithm in the BLAST program is applied that compares the query to all six translation frames of the unannotated DNA sequences. The dynamic translation of a small genomic database takes much less system resource than the translation of a large public database as in the conventional methods. Our method can thus be realized on a common PC system, especially when merely a subset of the public database is considered, for example for the purpose of identifying metabolic enzymes for metabolic network reconstruction. Because of sequence errors (especially the translation shift and abnormal stop codon) and the local alignment nature of the BLAST algorithm, the BLAST research may report several small alignments between different parts of the query protein or gene and different parts of a genomic contig even if there should be only one alignment in the reality. In this situation, the tfasty34 program in the FASTA3 suite [ 31 ] should give a better alignment since the translation shift is considered. But the tfasty34 program runs very slowly in our test and is therefore not used here for large-scale genomic alignment. In this work, fragment(s) of a genomic contig are joined to the genomic fragment that has the highest alignment score, resulting in a larger CDS fragment if: 1. they are coded on the same strand of the same genomic contig as the highest score fragment. In other words, all of these fragments must be translated either in positive or in negative frames. 2. the alignments have an identity level not lower than 80% of the identity level of the highest score alignment. 3. the generated larger sequence region has alignment gaps or extensions not more than 20% of its length. Since many queries can be similar to the same region on a genomic contig and sometimes they may have different function annotations, the program must judge and choose one annotation for this region. The decision is made by applying the following criteria: 1. Each region normally has only one function. Here the region represents a piece of nucleotides either on the positive strand or on the negative strand of a DNA molecule. The same physical position on different strands of a DNA molecule can belong to different regions, and can therefore have a different function assignment. Although there are examples in some viruses that a region can code different proteins depending on the transcription frame, it happens very rarely in other organisms. The user can assign a tolerance value (e.g. 60 bp) to allow two successive regions to overlap each other to some extent. 2. Highest similarity principle. If a query gene or protein has a similarity to a CDS higher than other queries, then the function of this query gene or protein is assigned as the annotation of the CDS. Bits score is used as a measure for similarity first. If two queries have the same bits score, then the identity level in percentage is taken as a second measure for similarity. If both bits score and identity are the same and these two entries have different function annotation (rarely occurred) then both of their functions are assigned to that region. 3. Closest evolutionary relationship. If two or more query genes or proteins are comparably similar (e.g. the difference between their identity levels is lower than 5%) to a CDS but have different function, the evolutionary relationship between these organisms is further considered. The annotation of the organism that is mostly related to the studied organism from the viewpoint of metabolic evolution is transferred to the unknown CDS. The evolutionary relationship between different organisms and the one studied is established with the method of Ma and Zeng [ 24 ] after the initial function assignment for the CDSs with the highest similarity criteria. In this way, the coding sequences of a genome are identified and annotated at the same time. No second large-scale sequence alignment is needed. Once all the software and databases are prepared, our program which is called IdentiCS ( Identi fication of C oding S equences from Raw Genome Sequences) can reconstruct the metabolic network of an organism with about 5 million base pairs of raw genome data. The computing time is less than 8 hours on a PC with 2.8 GHz Pentium 4 CPU and 512 MB memory. This program works together with Microsoft Excel under Windows environment. Statistic evaluation For a more detailed examination of our method, the results are evaluated separately for the prediction of CDSs and their function assignment, although our method integrates these two aspects into one step. The terms true positive (TP), false negative (FN) and false positive (FP) are used to calculate the sensitivity and specificity of CDS prediction in comparison with CDSs in the original annotation. The terms "sensitivity" and "specificity" are defined according to Burset and Guigo [ 32 ]: We also evaluated the terms TP, FN and FP on nucleotide level according to Burset and Guigo [ 32 ] and calculated the corresponding sensitivity and specificity as above. It should be mentioned that a true positive CDS does not necessarily mean that its function assignment is also correct. The terms consistence and inconsistence are used to describe whether a true positive CDS has the same function assignment as in the original annotation or not. Correspondingly, an "inconsistence rate" is used and defined as: Authors' contributions JS is the developer of the method and the program. APZ supervised the study. Both authors read and approved the final manuscript.

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176548

Monitoring Malaria: Genomic Activity of the Parasite in Human Blood Cells

Every year, malaria kills as many as 2.5 million people. Of these deaths, 90% occur in sub-Saharan Africa, and most are children. While four species of the single-celled organism Plasmodium cause malaria, Plasmodium falciparum is the deadliest. Harbored in mosquito saliva, the parasite infects its human host as the mosquito feeds on the victim's blood. Efforts to control the disease have taken on an increased sense of urgency, as more P. falciparum strains show resistance to antimalarial drugs. To develop new drugs and vaccines that disable the parasite, researchers need a better understanding of the regulatory mechanisms that drive the malarial life cycle. Joseph DeRisi and colleagues now report significant progress toward this goal by providing the first comprehensive molecular analysis of a key phase of the parasite's life cycle. While P. falciparum is a single-celled eukaryotic (nucleated) organism, it leads a fairly complicated life, assuming one form in the mosquito, another when it invades the human liver, and still another in human red blood cells (erythrocytes). The intraerythrocytic developmental cycle (IDC) is the stage of the P. falciparum lifecycle associated with the clinical symptoms of malaria. Using data from the recently sequenced P. falciparum genome, the researchers have tracked the expression of all of the parasite's genes during the IDC. The pattern of gene expression (which can be thought of as the internal operating system of the cell) during the IDC is strikingly simple. Its continuous and clock-like progression of gene activation is reminiscent of much simple life forms—such as a virus or phage—while unprecedented for a free living organism. Virus and phage behave like a “just-in-time” assembly line: components are made only as needed, and only in the amount that is needed. In this respect, malaria resembles a glorified virus. Given the remarkable coupling of the timing of gene activation with gene function, as shown in this paper, this understanding could help identify the biological function of the 60% of genes in P. falciparum that encode proteins of unknown function. P. falciparum appears to be ultra-streamlined and exquisitely tuned to perform a single job: consume, replicate, and invade. The simple program regulating the life of P. falciparum may hold the key to its downfall as any perturbation of the regulatory program will likely have dire consequences for the parasite. This offers renewed hope for the design of inhibitory drugs targeted at the regulatory machinery that would irreparably foul the parasite's regulatory program, ultimately resulting in its death. Gene expression profile of P. falciparum

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212704

Mathematical Modeling Predicts How Proteins Affect Cellular Communication

From the moment its life begins, the fate of a multicellular organism depends on how well its cells communicate. Proteins act as molecular switchboard operators to keep the lines of communication open and the flow of cellular messages on track. But charting the protein interactions, signaling pathways, and other elements that regulate these networks is no small feat. Previous efforts have been hampered by the lack of quantitative data—measurements of signal duration, amplitude, and fluctuation—on these regulatory pathways. Hoping to fill in some of the quantitative gaps, Marc Kirschner of Harvard Medical School, Reinhart Heinrich of Humboldt University Berlin, and colleagues developed a mathematical model as a framework for understanding the quantitative relationships among signaling proteins. To do this, they focused on a well-studied signaling pathway, the Wnt pathway, which plays a role both in various stages of embryonic development and in carcinogenesis. The researchers chose the Wnt pathway in part because a lot is known about it and in part because they could collect enough of the additional measurements they needed to build a solid model from experiments. And like most signaling pathways, Wnt is highly conserved. Consequently, developing tools that elucidate the Wnt pathway will not only provide insights into this important pathway, but have implications for understanding other communication pathways in animals from jellyfish to humans. To get the additional measurements needed to build their model, the researchers reproduced aspects of the Wnt pathway in the cytoplasm of unfertilized frog eggs. Among the new data collected from these experiments were measurements of the concentrations of scaffold proteins, which bring other components in a pathway together by providing an interaction surface. Strikingly, they found that the principal scaffold proteins involved in the pathway, axin and adenomatous polyposis coli (APC), occur in dramatically different concentrations and perform their jobs in different ways. After a series of refinements based on additional experiments, the model could not only simulate the behavior of the main players in the pathway—both in the absence and presence of a Wnt signal—it also suggested why the two scaffold proteins are present in different concentrations. Axin occurs at very low concentrations relative to the other proteins in the pathway and is likely to bind with them randomly, while APC occurs in similar concentrations and probably binds with the other components in an ordered manner. Because the proteins axin interacts with are also involved in other signaling pathways, the authors propose that the low level of axin here may help the pathways retain their modularity, preventing the Wnt pathway from interfering with the other pathways. These findings demonstrate that modeling can offer powerful new insights into the workings of complex signaling systems, cutting through the static to pick up important signals even in those pathways that are well understood. The results have important implications for developmental biology and human disease: The Wnt pathway is often activated during carcinogenesis—and mutations in several of these signaling proteins have been linked to colon cancer—suggesting that cancer can develop when signals in the Wnt circuitry somehow get crossed. By predicting how quantitative factors may influence the behavior of signaling networks, mathematical models such as this could shed light on the role that breakdowns in cellular communication play in carcinogenesis. The researchers argue that future attempts to characterize these complex networks must incorporate quantification measurements, and their modeling efforts suggest ways to do that. Understanding Wnt signaling through molecular modeling

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555760

Reliability of videotaped observational gait analysis in patients with orthopedic impairments

Background In clinical practice, visual gait observation is often used to determine gait disorders and to evaluate treatment. Several reliability studies on observational gait analysis have been described in the literature and generally showed moderate reliability. However, patients with orthopedic disorders have received little attention. The objective of this study is to determine the reliability levels of visual observation of gait in patients with orthopedic disorders. Methods The gait of thirty patients referred to a physical therapist for gait treatment was videotaped. Ten raters, 4 experienced, 4 inexperienced and 2 experts, individually evaluated these videotaped gait patterns of the patients twice, by using a structured gait analysis form. Reliability levels were established by calculating the Intraclass Correlation Coefficient (ICC), using a two-way random design and based on absolute agreement. Results The inter-rater reliability among experienced raters (ICC = 0.42; 95%CI: 0.38–0.46) was comparable to that of the inexperienced raters (ICC = 0.40; 95%CI: 0.36–0.44). The expert raters reached a higher inter-rater reliability level (ICC = 0.54; 95%CI: 0.48–0.60). The average intra-rater reliability of the experienced raters was 0.63 (ICCs ranging from 0.57 to 0.70). The inexperienced raters reached an average intra-rater reliability of 0.57 (ICCs ranging from 0.52 to 0.62). The two expert raters attained ICC values of 0.70 and 0.74 respectively. Conclusion Structured visual gait observation by use of a gait analysis form as described in this study was found to be moderately reliable. Clinical experience appears to increase the reliability of visual gait analysis.

Background Patients exhibiting gait deviations caused by orthopedic impairments are often referred to a physical therapist for treatment. In order to determine treatment goals or to evaluate the effect of a therapeutic intervention, physical therapists visually observe the patient's gait [ 1 - 3 ]. This type of gait assessment is cost efficient, quick, and easy to use in comparison to computer-assisted gait analysis [ 1 , 3 , 4 ]. Several reliability studies on observational gait analysis have been described in the literature. These studies included patients with hemiplegia [ 5 - 7 ], amputation [ 8 ], neurological diseases [ 9 ], cerebral palsy [ 10 ], rheumatoid arthritis [ 11 ] and spinal cord injuries [ 12 ]. The outcomes of these studies are diverse. The inter-rater reliability score for 'live' observational gait analysis (OGA), varies from reasonable [ 9 ] to moderate – good [ 12 ]. The inter-rater reliability scores for videotaped observational gait analysis (VOGA) varies from moderate [ 11 , 13 ] to moderate – good [ 12 ], while others show that the intra-rater reliability of VOGA is poor [ 10 ], moderate [ 13 ] or good [ 12 ]. The results of the validity of 'live' and videotaped observation varies from reasonably good [ 5 ], to not valid [ 8 ] as well as valid and accurate [ 9 , 12 ]. Two other studies used VOGA, in which raters had the opportunity to look at a video in slow motion or freeze-frame. One of these studies, by Eastlack et al . [ 11 ], found only slight to moderate inter-rater reliability levels. The other study, by Hughes et al . [ 7 ], showed that only some parts of a hemiplegic gait analysis form show sufficient inter- and intra-rater reliability levels. All the above mentioned differences stem from a large variety in design, (amount and type of patients and raters, types of gait analysis forms, rating scales and types of statistical methods). Despite the numerous studies on observational gait analysis, patients with orthopedic impairments have received little attention. In the Netherlands a gait analysis form has been developed which focuses mainly on orthopedic disorders [ 14 ]. Visual gait analysis with use of this gait analysis form is used by many physical therapists who practice gait training in patients with lower extremity orthopedic disorders. In addition, the use of this form is recommended by the Royal Dutch College of Physical Therapy for patients with chronic ankle sprain [ 14 ]. It is questionable, however, whether results from above described research concerning the reliability and validity of visual gait analysis in patients with neurological or other conditions can be extrapolated to patients with orthopedic problems. For example, gait deviations in patients with orthopedic impairments may result in less obvious gait deviations compared to patients with neurological disorders and may therefore be harder to identify visually. The purpose of this present study is to determine the inter- and intra-rater reliability of videotaped observational gait analysis with use of an orthopedic gait analysis form when applied to a cohort of patients suffering from orthopedic impairments. In addition, this study determines how well the raters perform observational gait analysis by comparing their assessments with a criterion, based on the experts' opinion. In order to gain insight into how the results may give guidance to physical therapy treatment, this study also investigates which items on the gait analysis form, that have been considered to be disturbed by visual observation, receive high priority in the physical therapy treatment program according to the physical therapist who performs the visual gait analysis. Methods Patients Thirty videotapes of patients' gait were selected from the archives of the department of Physical Therapy of the University Medical Center Nijmegen, the Netherlands. These videotapes involved patients who had been referred to a physical therapist for gait treatment. It is common practice at this department that prior to gait training therapy the gait of each patient is videotaped according to a standardized protocol. The criteria for inclusion of the videotapes were: (1) the presence of mild to severe gait deviations due to an orthopedic impairment; (2) patient was wearing shorts or underwear to allow for a more accurate observation of the joint movement; (3) ability of a patient to walk 15 meters at least four times, twice in a semi-circle and twice in a straight line on a gymnasium floor; (4) and patient's written informed consent. The first thirty patients who complied with these criteria were included. The group consisted of 15 male and 15 female patients with a mean age of 37.8 years (range: 15 to 62 years). The type of orthopedic impairments varied from status post hip, knee, ankle surgery (n = 8), status post hip or knee prosthesis (n = 6), status post femur, tibia or ankle fracture (n = 3) and traumatic or non-traumatic non-specific hip, knee or ankle pain (n = 13) (see Table 1 ). Table 1 Patient characteristics (N = 30) Affected side Subject Age (years) Gender Type of orthopedic impairment Left side Right side 1 25 F Status post hip surgery Hip 2 56 F Status post hip prosthesis Hip 3 48 M Status post knee surgery Knee 4 19 F Trauma induced non-specific knee pain Knee 5 41 M Status post hip surgery and prosthesis Hip 6 62 F Status post hip prosthesis Hip 7 37 M Status post femur fracture Hip/ Knee 8 49 M Status post hip surgery and prosthesis Hip 9 15 F Non-specific knee pain Knee 10 33 M Status post hip and knee prosthesis Hip Hip/ Knee 11 21 M Status post ankle fracture Ankle Ankle 12 37 M Status post ankle surgery Ankle 13 34 F Non-specific knee pain Knee 14 32 F Status post knee surgery Knee 15 19 F Non-specific ankle pain Ankle Ankle 16 46 M Non-specific knee pain Knee 17 51 F Non-specific knee pain Knee 18 62 F Status post hip surgery Hip 19 44 M Status post hip surgery Hip 20 21 M Status post tibia fracture Knee 21 33 F Non-specific knee pain Knee 22 28 F Status post hip surgery Hip 23 31 M Status post ankle surgery Ankle 24 60 F Trauma induced non-specific knee pain Knee 25 52 M Trauma induced non-specific knee pain Knee 26 50 F Status post hip surgery and prosthesis Hip 27 21 F Trauma induced non-specific ankle pain Ankle 28 41 M Non- specific knee pain Knee Knee 29 49 M Non- specific knee pain Knee 30 16 M Trauma induced non-specific knee pain Knee Raters Ten raters participated in this study, 4 inexperienced, 4 experienced and 2 experts. The inexperienced raters were two physical therapy students and two human movement science students. These inexperienced raters had no clinical experience in the analysis of gait deviations in orthopedic patients and never analyzed gait deviations by means of an observational gait analysis form. The group of experienced raters consisted of four senior physical therapists who had all taken part and successfully completed a gait training course. All experienced raters had worked more than ten years as a physical therapist and had at least five years of experience in treating and analyzing gait deviations by means of an observational gait analysis form. The two expert raters were two senior physical therapists, who were selected based on their exceptional skills and knowledge in the observation of gait deviations due to orthopedic impairments. They have considerable experience with treating patients with orthopedic gait disorders. In addition, these two physical therapists cooperatively developed the orthopedic gait analysis form used in this study and are instructors in a course in which participants are taught to treat and observe orthopedic gait deviations with a functional approach. All four experienced raters had taken part in this course. Design of the gait analysis form The 12 items contained in the gait analysis form used in this study describe the trunk, arm, pelvis, hip, knee and ankle during the gait cycle (Table 2 ). In daily practice, the results of the visual gait analysis are used as a guide for treatment or to evaluate the effect of a therapeutic intervention. Table 2 Orthopedic gait analysis form STANCE PHASE SWING PHASE Item Question Early Mid Late Early Late General 1 Is a shortened stance phase present? Left Yes / No NA Right Yes / No NA Trunk 2 Is the trunk anterior to the hips? Yes / No 3 Is the trunk posterior to the hips? Yes / No 4 Is lateral flexion present? Left Yes / No NA Right Yes / No NA 5 Is arm-swing reduced? Left Yes / No Right Yes / No Pelvis 6 Is the posterior rotation excessive? Left NA Yes / No NA Right NA Yes / No NA Hip 7 Is the extension reduced? Left NA Yes / No NA Right NA Yes / No NA Knee 8 Is the extension reduced? Left NA NA Yes / No Right NA NA Yes / No 9 Is the flexion movement absent ? Left Yes / No NA NA Right Yes / No NA NA 10 Is the flexion reduced? Left Yes / No NA NA Right Yes / No NA NA 11 Is the extension absent? Left NA Yes / No NA NA Right NA Yes / No NA Ankle 12 Is the plantar flexion reduced? Left NA Yes / No NA Right NA Yes / No NA NA = not applicable Visual gait analysis The gait pattern was analyzed from a lateral (both sides), anterior and posterior view at each of the three sub-phases of stance and the two sub-phases of swing. Early stance was defined as the combined phases of initial contact and loading response. In this phase, the ankle moves from heel contact to foot contact, while the knee is flexed to absorb the shock of limb loading. Mid-stance was defined as the phase of foot contact to heel rise, during this phase the trunk progresses over a single stable limb. Late stance was defined as the combined phases of terminal stance and pre-swing, in which heel-rise and toe-off occurs. Early swing was defined as toe-off until to the swing leg reaches the stationary leg. Late swing was defined as the combined phases of mid swing and terminal swing. In this phase, the moving leg passes the stationary leg and the knee extends as the limb prepares to take the load at initial contact. Videotape recording All patients were recorded from a lateral view (both sides) while walking 15 meters in a semi-circle (radius approximately 10 m) at a comfortable self-selected walking speed. We used a semi-circle in order to be able to observe the patient's gait in the sagittal plane from one position. The anterior and posterior views were videotaped while the patient walked five meters toward and away from the camera. The collected videos were edited with use of the computer program adobe premiere 6.0 (Adobe systems ® ). Manufactured videos were reduced into a one-minute film-clip in which the patient's gait could be viewed in the lateral and frontal plane. Subsequently, these videos were converted to analog format again, so that they could be played by a regular video player. Sampling frequency was 24 Hz. Rater instructions To ensure visual assessment of gait based on comparable criteria, all raters received standardized information about normal gait kinematics prior to the rating sessions (Table 3 ). Raters were required to use this information during the rating sessions. Before each session, raters viewed a videotaped gait sequence of a non-participating patient and a healthy subject. All raters started rating after they felt completely comfortable with rating the videos. Table 3 Normal joint-angles during stance and swing phase. Range of motion summary in the sagittal plane measured in degrees. Phase of the gait cycle STANCE PHASE SWING PHASE Early 0 – 10% GC. Mid 10 – 30% GC. Late 30 – 60% GC. Early 60 – 70% GC. Late 70 – 100% GC. Trunk Positioned above the hip Positioned above the hip Pelvis 5° forward rotation 0° 5° backward rotation 5° backward rotation 5° forward rotation Hip 25° flexion 0° 30–50% GC: 10° extension 50–60% GC: 0° 15° flexion 25° flexion Knee 20° flexion 0° 40° flexion 60° flexion 0° Ankle 10° PF 10° DF 20° PF 10° PF 0° GC = Gait Cycle, PF = Plantar Flexion, DF = Dorsal Flexion [1] Rating procedure The rating session took place in an isolated room in which each rater individually assessed the videotaped gait-patterns of 30 patients twice, with a minimum interval between the two rating sessions of 3 weeks, in order to reduce the effect of recognition. Raters had to rate each item of the form as present or absent. Both legs were assessed and were dealt with in the statistical analysis as independent ratings. Each rater was permitted to view the videotape in slow motion or freeze-frame, allowing the raters to more closely inspect the patient's gait. Each rater was able to rate the patient's gait as many times as necessary until they were satisfied with their rating. The rating of the 30 patients was spread out over two days and a single session lasted for a maximum of two hours. All videos were put in a randomized order to prevent the raters from recognizing the patient and recalling their scores from the last session. The randomization was done through the use of dice and was concealed from all raters. Raters were also asked to assign priority levels (high or low priority) to the items they scored as disturbed, with respect to a physical therapy treatment program. In other words, which items would receive important attention in the physical therapy intervention if the rater was going to treat this patient for his or her gait disorder. Level of performance In order to determine the level of performance of observational gait analysis of all experienced and inexperienced raters, we compared their ratings with a criterion. This gives us an indication about how well the raters were capable in performing visual gait analysis. The criterion was attained during a consensus session of the two expert raters: After individually assessing the 30 patients for the second time, the two expert raters jointly observed the videotaped gait of all 30 patients for the third time. Data analysis Inter- and intra-rater reliability levels were assessed by using Intraclass Correlation Coefficients (ICCs), validated for use with multiple raters and calculated in a two-way random model based on absolute agreement. We used ICCs because it has been shown that with data that are rated as a dichotomy, the ICC is equivalent to measures of nominal agreement, simplifying computation in cases where more than two raters are involved [ 15 ]. In addition, the ICC computation also provides us with an estimate of accuracy (95% CI) of the reliability levels. The level of performance (quality of assessment) was obtained by comparing the joint assessment of the expert raters to each individual, also using reliability analyses with use of ICCs. Agreement strengths for ICC values have been classified as follows: <0 = poor; 0 – 0.20 = slight, 0.21 – 0.40 = fair; 0.41 – 0.60 = moderate; 0.61 – 0.80 = substantial and 0.81 – 1.00 = almost perfect [ 16 ]. All analyses were performed with use of SPSS 11.0.1. Results Inter-rater reliability The inter-rater reliability among experienced raters was 0.42 (95%CI: 0.38–0.46). This level of reliability is comparable to the inter-rater reliability of in-experienced raters, which reached an ICC value of 0.40 (95%CI: 0.36–0.44). The expert raters reached the highest inter-rater reliability (ICC: 0.54 (95%CI: 0.48–0.60)). There were no differences in inter-rater reliability between the first and second rating session of all three groups separately, based on the overlap of 95% confidence intervals. Intra-rater reliability The average intra-rater reliability of the experienced raters was 0.63 (ranging from 0.57 to 0.70). The inexperienced raters reached an average intra-rater reliability of 0.57(ranging from 0.52 to 0.62). The two expert raters attained ICC values of 0.70 and 0.74 respectively. Level of performance The agreement between the outcome of the joint assessment of the expert raters (criterion) and those of the individual experienced raters ranged from 0.43 to 0.55 with an average ICC value of 0.48. The inexperienced raterrs attained agreement levels ranging from 0.41 to 0.55, with an average of 0.49. There is no difference in the level of performance of visual gait assessments of experienced or inexperienced raters, when compared to the experts' opinion. Reliability levels for each item separately The inter-rater reliability per item on the gait analysis form between the two experts is generally moderate to substantial (see Table 4 ). However, two items in particular, showed low agreement levels. These are flexion of the knee during early stance (item 9) and posture of the trunk during walking (item 2) (for both: ICC = 0.33). With respect to the experienced and inexperienced raters, the visual observation of the lateral flexion of the trunk (item 4), the arm swing (item 5) and the knee extension in the late swing phase (item 8) showed the highest inter-rater reliability levels (all ICC-values > 0.50). Table 4 Reliability of the gait analysis list per item Inter-rater reliability 1 Intra-rater reliability 2 Item Expert (n = 2) Experienced (n = 4) Inexperienced (n = 4) Expert (n = 2) Experienced (n = 4) Inexperienced (n = 4) ICC (95% CI) ICC (95% CI) ICC (95% CI) Mean ICC (range) Mean ICC (range) Mean ICC (range) General 1 0.62 (0.43 – 0.76) 0.25 (0.12 – 0.39) 0.26 (0.14 – 0.40) 0.86 (0.82 – 0.89) 0.54 (0.32 – 0.83) 0.50 (0.36 – 0.65) Trunk 2 0.33 (0.01 – 0.61) 0.25 (0.12 – 0.39) 0.41 (0.22 – 0.61) 0.87 (0.74 – 1.00) 0.81 (0.64 – 1.00) 0.53 (0.37 – 0.64) 3 - - - - - - 4 0.66 (0.50 – 0.78) 0.58 (0.46 – 0.70) 0.52 (0.39 – 0.65) 0.82 (0.69 – 0.95) 0.68 (0.49 – 0.86) 0.74 (0.66 – 0.84) 5 0.48 (0.17 – 0.68) 0.53 (0.40 – 0.66) 0.55 (0.40 – 0.69) 0.75 (0.70 – 0.79) 0.75 (0.61 – 0.82) 0.81 (0.74 – 0.88) Pelvis 6 0.58 (0.38 – 0.73) 0.19 (0.08 – 0.34) 0.33 (0.20 – 0.47) 0.65 (0.53 – 0.76) 0.13 (-0.07 – 0.61) 0.45 (0.27 – 0.61) Hip 7 0.52 (0.23 – 0.71) 0.43 (0.28 – 0.57) 0.24 (0.11 – 0.39) 0.63 (0.59 – 0.67) 0.59 (0.35 – 0.72) 0.47 (0.14 – 0.67) Knee 8 0.58 (0.34 – 0.73) 0.58 (0.45 – 0.70) 0.60 (0.48 – 0.71) 0.66 (0.62 – 0.69) 0.65 (0.49 – 0.82) 0.63 (0.48 – 0.76) 9 0.33 (0.07 – 0.54) 0.45 (0.32 – 0.59) 0.16 (0.05 – 0.30) 0.82 (0.76 – 0.88) 0.58 (0.44 – 0.72) 0.36 (0.10 – 0.55) 10 0.51 (0.30 – 0.68) 0.23 (0.10 – 0.38) 0.41 (0.28 – 0.55) 0.82 (0.70 – 0.94) 0.42 (0.02 – 0.65) 0.54 (0.50 – 0.64) 11 0.40 (0.16 – 0.59) 0.29 (0.15 – 0.44) 0.36 (0.23 – 0.50) 0.52 (0.42 – 0.61) 0.58 (0.47 – 0.63) 0.22 (0.00 – 0.54) Ankle 12 0.52 (0.27 – 0.70) 0.30 (0.17 – 0.45) 0.20 (0.09 – 0.35) 0.66 (0.62 – 0.70) 0.30 (0.16 – 0.46) 0.37 (0.17 – 0.67) The intra-rater reliability levels with respect to the visual gait assessments by expert raters were generally higher compared to the experienced and inexperienced raters. With regard to five items intra-rater reliability was good (>0.80). Only one item, extension movement of the knee during mid stance, had an ICC value for intra-rater reliability of less than 0.6. The experienced raters were able to attain good intra-rater reliability for item 2, posture of the trunk during walking (ICC = 0.81). Three items reached substantial intra-rater reliability (item 4, 5, and 8). Two items of the gait analysis form, pelvis rotation and ankle movement during late stance, were not intra-rater reliable (ICC < 0.40). The inexperienced raters reached the highest intra-rater reliability for the assessment of arm swing during walking (ICC = 0.81). Three items had inadequate intra-rater reliability levels; flexion of the knee in early stance (ICC = 0.36), extension of the knee in mid stance (ICC = 0.22), and ankle movement during the late stance phase (ICC = 0.37). No reliability score was obtained from item 3, which describes a trunk position behind the hips, because this item was observed only once. Priority level with respect to physical therapy treatment On average, with respect to all items, in about a quarter of the cases items were judged to be disturbed by the expert and experienced raters (see Table 5 ). Except for item three which was considered disturbed only once in the group of experienced raters. Both expert and experienced raters would give hip, knee and ankle movements, which were judged as being disturbed, generally high priority if they were to treat the patient. Expert raters also gave a shortened stance phase of either one of the legs, and an excessive lateral flexion of the trunk high priority, in contrast to the experienced raters for whom these items received generally a low priority. The other items such as movement of the pelvis, arm swing, and position of the trunk (flexed or extended) received generally low priorities in a potential physical therapy intervention. Table 5 Treatment priority per item when scored as disturbed. Expert raters Experienced raters Treatment priority b Treatment priority b Item Times scored as disturbed a High Low Times scored as disturbed a High Low General 1 15,0% 72,2% 27,8% 13,8% 21,2% 78,8% Trunk 2 16,7% 20,0% 80,0% 15,8% 47,4% 52,6% 3 0,0% - - 0,8% 100,0% 0,0% 4 26,7% 71,9% 28,1% 26,3% 54,0% 46,0% 5 50,8% 55,7% 44,3% 40,4% 24,7% 75,3% Pelvis 6 22,5% 44,4% 55,6% 7,9% 26,3% 73,7% Hip 7 42,5% 82,4% 17,6% 26,7% 82,8% 17,2% Knee 8 26,7% 59,4% 40,6% 25,4% 75,4% 24,6% 9 20,0% 95,8% 4,2% 41,7% 98,0% 2,0% 10 24,2% 100,0% 0,0% 52,9% 99,2% 0,8% 11 45,8% 67,3% 32,7% 26,3% 92,1% 7,9% Ankle 12 54,2% 83,1% 16,9% 35,8% 96,5% 3,5% a This number indicates how many times raters scored this item as being disturbed. b When raters scored an item as being disturbed they were asked to indicate whether this item would receive high or low priority in their physical therapy treatment program with respect to the patients gait disorder. Discussion The results of this study indicate a moderate reliability of observational gait analysis in patients with orthopedic gait disorders while using a structured gait analysis form. In addition, the observation of only three items of the gait analysis form reached substantial levels of inter-rater reliability. These were related to lateral movements of the trunk, arm swing, and the movement of the knee just before heel strike. This study shows comparable results with similar studies on observational gait analysis in different patient categories. Studies on visual gait analysis that show high reliability levels, generally focused on patients exhibiting severe neurological pathology. Severe neurological pathology causes grossly larger gait deviations, which makes potential gait deviations easier to recognize. Furthermore, most of the gait analysis forms being used contain easy observable items. With respect to the present study, the highest agreement levels are reached on items that are considered easy observable: the lateral flexion of the trunk, the arm swing and the knee extension in the late swing phase. Items that are considered more difficult to observe, like the pelvis rotation and the plantar flexion of the ankle in the late stance phase, scored lower agreement levels. Minute gait deviations displayed by the patients in this study lead to difficult observable items, explaining the moderate reliability level found in this present study. Another explanation for the moderate results may be that some of the patients in this study displayed an inconsistent gait pattern. This means that, despite the accuracy with which the videos were collected in this study, still some participants performed a slight variability in their gait pattern. This results in small gait deviations present during a few steps and absent a couple of steps later, so when raters do not observe the same gait cycles, differences occur. This might explain relatively low inter- and intra-rater reliability levels, even when raters were 'right' in their assessment. To correct for this disturbance we believe that a gait deviation should only be defined as abnormal when the patient repeats the deviation in a series of gait cycles. This will increase reliability levels of the videotaped observational gait analysis. On the other hand, inconsistent gait patterns are of minor importance during 'live' observation or videotaped gait observation without the opportunity for freeze-frame or slow-motion. In that case more gait cycles are observed, leading to a situation in which an average of the inconsistencies is scored. This consideration is supported by the fact the reliability of gait analysis without the opportunity for freeze-frame or slow-motion is not always found to be worse [ 12 , 13 ]. A weakness of this study is that we have not included an objective standard to assess the validity of raters' visual observations. Nevertheless, we tried to gain insight in raters' performance by using a criterion, which was accomplished during a joint rating session by the two expert physical therapists. According to this study, experience in gait observation does not improve the reliability of this observation. Inexperienced raters achieve a comparable reliability level to experienced raters. However, expert raters accomplish significant better reliability levels of visual gait observation compared to experienced and inexperienced raters. In other words, some experience does not improve observation skills, but a lot more does. We have shown that not all movements of body segments during gait can be observed with similar reliability levels. The visual observation of only three items proved to be substantially reliable. This indicates that one should bear in mind when using this 12-item gait analysis form that nine of these items are at the best moderately reliable. However, the results of this study indicate that for at least four items the intra-rater reliability levels are substantial to good (items 2, 4, 5 and 8). Expert raters showed the least variability between the first and second session; five items showed to have a mean intra-rater reliability level that is considered good (ICC > 0.80). The results of this study suggest that a brief introduction in normal gait kinematics in inexperienced raters gives comparable reliability levels of observational gait analysis in patients with orthopedic impairments compared to experienced physical therapists, who have worked for several years with patients with gait disorders. However, expert raters – those that work significantly more intensive with patients with gait disorders – accomplish higher reliability levels. As mentioned in the methods section, the gait analysis form used in this study is also used in daily practice to guide the treatment of the patient's gait disorder. In the physical therapist's treatment program, some items on the form will obviously receive higher priority than others. The results of this study show that physical therapists mainly focus their intervention on movement disorders of the lower extremity. However, the expert raters also report to give priority to asymmetry of the stance phase and excessive lateral flexion of the trunk during gait. Of the three items in this study that achieved the highest reliability levels, only the movement of the knee received generally a high priority in the treatment program of experienced raters. This implies that experienced raters will mainly focus their treatment on items that have generally a low inter- and intrarater reliability. Conclusion Structured visual observation of a patient's gait by use of a gait analysis form as described in this study is found to be only moderately reliable, but may be a useful guide to the physical therapist in setting up a gait training or exercise therapy program. Intra-rater levels have shown that visual gait analysis will supply the observer with a fair indication of changes in a person's gait. However, to evaluate the effect of an intervention on a patient's gait we recommend more objective instrumentation which has been proven reliable and valid. Competing interests The author(s) declare that they have no competing interests. Authors' contributions JB carried out the data analysis, participated in the design of the study and drafted the manuscript. CvU participated in the design and coordination of the study, assisted with statistical analysis, and helped to draft the manuscript. SvM participated in the design of the study and supplied the videotapes. JK 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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Prognostic meta-signature of breast cancer developed by two-stage mixture modeling of microarray data

Background An increasing number of studies have profiled tumor specimens using distinct microarray platforms and analysis techniques. With the accumulating amount of microarray data, one of the most intriguing yet challenging tasks is to develop robust statistical models to integrate the findings. Results By applying a two-stage Bayesian mixture modeling strategy, we were able to assimilate and analyze four independent microarray studies to derive an inter-study validated "meta-signature" associated with breast cancer prognosis. Combining multiple studies ( n = 305 samples) on a common probability scale, we developed a 90-gene meta-signature, which strongly associated with survival in breast cancer patients. Given the set of independent studies using different microarray platforms which included spotted cDNAs, Affymetrix GeneChip, and inkjet oligonucleotides, the individually identified classifiers yielded gene sets predictive of survival in each study cohort. The study-specific gene signatures, however, had minimal overlap with each other, and performed poorly in pairwise cross-validation. The meta-signature, on the other hand, accommodated such heterogeneity and achieved comparable or better prognostic performance when compared with the individual signatures. Further by comparing to a global standardization method, the mixture model based data transformation demonstrated superior properties for data integration and provided solid basis for building classifiers at the second stage. Functional annotation revealed that genes involved in cell cycle and signal transduction activities were over-represented in the meta-signature. Conclusion The mixture modeling approach unifies disparate gene expression data on a common probability scale allowing for robust, inter-study validated prognostic signatures to be obtained. With the emerging utility of microarrays for cancer prognosis, it will be important to establish paradigms to meta-analyze disparate gene expression data for prognostic signatures of potential clinical use.

Introduction DNA microarray analysis has been shown to be a powerful tool in various aspects of cancer research [ 1 ]. With the increasing availability of published microarray data sets, there is a tremendous need to develop approaches for validating and integrating results across multiple studies. A major concern in the meta-analysis of DNA microarrays is the lack of a single standard experimental platform for data generation. Expression profiling data based on different technologies can vary significantly in measurement scale and variation structure. It poses a great challenge to compare and integrate results across independent microarray studies. In a recent study of diffuse large B cell lymphoma (DLBCL), Wright et al. [ 2 ] sought to bridge two different microarray platforms by validating findings from a cDNA lymphochip microarray using an independent dataset generated using Affymetrix oligonucleotide arrays. Although the idea of training and testing classifiers is frequently used for discriminant analysis, this application to distinct expression array platforms is less common. More systematic approaches have been proposed for integration of findings from multiple studies using different array technologies. Rhodes et al. [ 3 ] have proposed methods to summarize significance levels of a gene in discriminating cancer versus normal samples across multiple gene profiling studies. By ranking the q-values [ 4 ] from sets of combinations, a cohort of genes from the four studies was identified to be abnormally expressed in prostate cancer. Choi et al. [ 5 ] suggested combining effect size using a hierarchical model, where the estimated effect size in individual studies follows a normal distribution with mean zero and between study variance τ 2 . The effect size was defined to be the difference between the tumor and normal sample means divided by pooled standard deviation. From a Bayesian perspective, Wang et al. [ 6 ] used data from one study to generate a prior distribution of the differences in logarithm of gene expression between diseased and normal groups, and subsequent microarray studies updated the parameter values of the prior. Assuming a normal error distribution, the differences were then combined to form a posterior mean. Although phrased using different model frameworks, these methods are similar in the spirit of combining the standardized differences between two sample means across multiple studies. It has been shown, however, that the overlap between significant gene detection on different array platforms is only moderate due to low comparability of independent data sets [ 7 ]. The large variability brought in by microarray datasets using different platforms is expected to affect the sensitivity and specificity of summary statistics constructed in various ways across studies. Given the inherent differences of the microarray techniques, heterogeneity of the sample populations, and low comparability of the independently generated data sets, meta-analysis of microarrays remains a difficult task. A recent study proposed a Bayesian mixture model based transformation of DNA mi-croarray data with potential features applicable to meta-analysis of microarray studies [ 8 ]. The basic idea is to estimate the probability of over-, under- or baseline expression for gene sample combinations given the observed expression measurements. With data-driven estimation of these quantities, one can translate the raw expression measurement into a probability of differential expression. As a result, poe (i.e., probability of expression) was introduced as a new scale and used in the context of molecular classification [ 8 ]. The platform-free property of this scale, however, motivated us to incorporate poe in a framework to meta-analyze microarray data. Several desirable features of using poe as a new expression scale include the following: 1. poe provides a scaleless measure and thereby facilitates data integration across microarray platforms; 2. poe is a model-based transformation with direct biological implications in the context of gene expression data, as it is estimated based on a method that adopts an underlying mixture distribution that accommodates over-, under-, and unchanged expression categories; 3. poe unmasks differential expression patterns in microarray data by offsetting the influence of extreme expression values [ 9 ]; 4. Data integration based on poe allows merging of samples on the unified scale rather than using gene-specific summaries. In recent publications of breast cancer microarray studies, several groups have explored the hypothesis that the capacity to metastasize is intrinsic to the tumor and therefore can be revealed by gene expression pattern. Four independent studies have correlated gene expression profiles generated from distinct DNA microarray platforms to breast cancer prognosis [ 10 - 13 ]. Among the four, Sorlie et al. [ 10 ] and Sotiriou et al. [ 12 ], both cDNA microarray studies, applied unsupervised clustering and identified several breast cancer subtypes characterized by differential expression of a cohort of genes. Further, they correlated the tumor subtypes derived from the expression profile with survival outcome and in both cases found that, as expected, the ERBB2+ subtype correlated with shorter survival times. On the other hand, van't Veer et al. [ 11 ], an inkjet oligonucleotide array study, and Huang et al. [ 13 ], an Affymetrix GeneChip study, have built classification models based on gene expression profiles to predict 5-year or 3-year recurrence status. In all four studies, however, the authors explored a common hypothesis that molecular profiles were able to provide a more accurate prediction of patient survival compared with clinical/pathological parameters. These studies therefore provided an excellent basis for developing a meta-analysis of microarrays with regard to disease prognosis. In this proof-of-concept study, we propose a two-stage meta-analysis of microarrays based on poe . We applied our method to the aforementioned breast cancer DNA microarray data sets. With the strength of the poe transformation and data integration, our goal was to develop an inter-study validated meta-signature that predicts relapse-free survival in breast cancer patients with improved statistical power and reliability. Results Development of the two-stage Bayesian mixture modeling approach for the meta-analysis of microarray data Figure 1 outlines the two-stage Bayesian mixture modeling strategy. The idea is to build a scale that can be combined across different microarray platforms, and therefore allows simultaneous examination of independent data sets. The stage 1 of the analysis involves data-driven estimation of posterior probability of differential expression, namely poe . The Bayesian hierarchical model employed for estimation borrows strength across genes by assuming further distributions for the gene-specific parameters (see Methods). For data integration purposes, we focused on a common set of 2,555 genes that were profiled in each of the four studies. Although the cost for compiling common genes is a loss of potential predictive features, it is not unreasonable to assume, given the analogous hypothesis explored in each study, that the common set represents the most relevant genes of interest for breast cancer prognosis. The resulting values of poe represent signed probability of differential expression for gene j in sample i , and thus provide a unified measure across studies. Further, the transformation improves contrast in each data set by removing the influence of extreme expression values. In stage 2, the expression profile of tumor samples from multiple studies were combined on the poe scale to generate a meta-cohort. The benefit of data integration using poe is twofold. First, it improves power of statistical analysis by increasing the sample size. Such integration of independent data sets renders sensitivity to those small yet consistent expression changes for certain genes. Second, it reduces the chance of false positive features due to artifacts from a single study, and allows reliable findings across studies. In this paper, we integrated four breast cancer microarray data sets of distinct platforms (Table 1 ), and developed a prognostic meta-signature for disease recurrence. Figure 1 Meta-analysis of microarray data using a two-stage mixture model approach. Table 1 Breast cancer gene expression data sets used in the prognostic meta-analysis. Bad outcome (Y = 1) is defined as recurrence during follow-up, and good outcome (Y = 0) is defined as remaining recurrence-free for at least three years. Authors Array platform Number of array elements Sample size (n) Good outcome (n 0 ) Bad outcome (n 1 ) Sorlie et al. Spotted cDNA 8102 58 23 35 van't Veer et al. Inkjet oligonucleotide 25000 78 44 34 Sotiriou et al. Spotted cDNA 7650 98 53 45 Huang et al. Affymetrix chip 12625 71 36 35 Building a gene expression meta-signature for breast cancer prognosis In the second stage of the analysis, We assessed the performance of the genes found using the meta-analysis methods based on classification accuracy. A complication is that while most methods of classification deal with data from two populations, the response with which we wish to build classifiers to predict is time to breast cancer recurrence. While the ideal data would have information on time to recurrence on all subjects (potentially censored), not all studies have the time to recurrence information available and instead provide data on recurrence within a certain time interval (e.g., recurrence within five years versus no recurrence within five years). To deal with this issue, we utilized a dichotomization where a bad outcome is recurrence during followup and a good outcome is remaining recurrence-free for at least three years. The additional constraint for the good outcome group is to reduce potential bias introduced by short censoring due to insufficient length of follow-up. This is particularly relevant in cross-study analysis, given the heterogeneity in patient recruitment criteria and study designs. Accordingly, of the combined meta-cohort (n = 305) of breast cancer patients, 48.9% were in the poor outcome group, whereas 51.1% in the good outcome group. The sample sizes for each study are shown in Table 1 . Each gene was then associated with the recurrence status by a logistic regression within a leave-one-out cross validation scheme, and rank-ordered by the significance level of the coefficient. As a result, 23 genes held up as significant predictor of recurrence ( P ≤ 0.001) in all cross-validation steps, representing a cohort of essential genes strongly associated with breast cancer recurrence. By random chance, there would be on average 2.5 genes to be found significant at P ≤ 0.001 in a set of 2,555. By finding 23 genes with a P ≤ 0.001, it is clear that there are much more predictive features than would be expected by random chance. To identify a prognostic meta-signature, we define a risk index (RI) as a linear combination of the poe profile and the coefficient estimates from the univariate logistic regression for each gene j . Large positive values of RI indicate high risk of failure, whereas large negative values of RI indicate low risk of failure. Classification of sample i to the risk groups is then based on the i th leave-one-out risk index. The classifier is = I { RI i > c }, with c being the empirical quantiles of the risk indices. The number of genes in a classifier is treated as a parameter and optimized to minimize the prediction error rates. More details on building a classifier at the second stage are described in the Methods section. The 90-gene expression meta-signature predicts clinical outcome in breast cancer patients By minimizing the misclassification error, we obtained a 90 gene meta-signature that reliably predicts outcome in the meta-cohort. This meta-signature classified 122 patients into a high risk group, where 84 (69%) of them had a recurrence. On the other hand, the signature classified 183 patients into a low risk group, where 118 (64%) of them did not recur by the end of the followup. By cross-tabulating the risk groups predicted by the meta-signature and the actual recurrence status, we obtained an estimated odds ratio of 4.0 (95% CI: 2.5–6.5, P < 0.0001). In spite of the heterogeneity of the combined patient population, the meta-signature predicted the odds of recurrence for a patient showing a high risk signature as four times of the odds of recurrence for a patient showing a low risk signature. Several studies have implicated that the lymph node status is one of the principal clinical factors to classify patients in relation to the risk of relapse of breast cancer [ 14 - 16 ]. Although there have been controversial findings with regard to its predictive values in breast cancer survival outcome, we have shown in the meta-cohort that the nodal status is a significant risk factor of recurrence. The estimated odds of recurrence for node-positive patients is two times higher than the odds of recurrence for node-negative patients (95% CI:1.3–3.2, P = 0.002) in the combined samples. Kaplan-Meier analysis provides further evidence that the meta-signature was a significant prognostic index of breast cancer recurrence in the meta-cohort (Figure 2 ). The estimated three-year survival rate was 76.0%(± 3.2%) for low risk signature and 45.9%(± 4.5%) for high risk signature. Nodal status, on the other hand, was less discriminative at the three-year time point with an estimated survival rate of 71.7%(± 3.7%) for lymph node negative patients and 56.2%(± 4.0) for lymph node positive patients. Node-negative patients, although generally considered to be at low risk of recurrence, are heterogeneous in disease progression. About one third of node-negative patients develop local recurrence [ 17 ]. Many studies have therefore explored the potential of using molecular biomarkers to further differentiate patient survival outcome in nodal negative cohort [ 18 - 21 ]. As shown in Figure 2C and 2D , the meta-signature further differentiated 48 (31.6%) of the LN- patients to be at higher risk of recurrence during followup ( P < 0.0001). Similarly for nodal positive patients, a cohort thought to be at high risk of recurrence, the meta-signature identified 79 (51.6%) of the LN+ patients to have, in fact, lower recurrence risk over time ( P < 0.0001, Figure 2D ). In contrast, nodal status failed to maintain its predictive power after controlling for the meta-signature risk groups ( P = 0.05 and 0.12 in low risk signature and high risk signature group respectively). A multivariate logistic regression model suggested that the meta-signature is an independent predictor of the recurrent status with respect to nodal status in the meta-cohort (OR = 3.7(2.3–6.1), P < 0.0001). Figure 2 The 90-gene meta-signature displayed greater performance than nodal status in predicting relapse-free survival in breast cancer, and it further predicts survival outcome in nodal status sub-cohorts. (A) Lymph node status correlates with survival outcome ( P = 0.0004). (B) The meta-signature correlates with survival outcome ( P = 2 × 10 -10 ). (C) The meta-signature differentiates risk groups in nodal negative patients ( P = 2.6 × 10 -5 ). (D) The meta-signature predicts risk groups in nodal positive patients ( P = 7.0 × 10 -5 ). Comparison of the meta-signature to the study-specific signatures To comprehend the potential gains of such two-stage meta analysis over individual analysis in each single study cohort, we constructed study-wise gene expression signatures using the same method. By minimizing the misclassification errors, we obtained a signature consisting 10, 60, 100, and 130 genes for Sorlie, van't Veer, Sotiriou, and Huang study cohort respectively ( Additional file 5 ). The results of the classifiers are summarized in Table 2 . In fact, not only did the size of the study-specific signatures vary significantly, but the elements of the signatures had very little overlap. At most two genes appeared in more than one signature among the four. In addition, signature identified in one study tended to have poor performance in other studies. Table 3 lists the estimated odds ratios for disease outcome and risk groups predicted by a gene expression signature. An individual signature identified in one study cohort demonstrated considerable shrinkage in the odds ratio estimates and non-significant 95% confidence intervals in the validation studies, indicating significantly reduced discriminative power in the testing cohorts. Kaplan-Meier analysis provided further evidence that the study-specific signatures performed poorly in pairwise cross-validations ( Additional file 6 ). Table 2 Comparisons of the number of genes (Size), the number of elements overlap with the meta-signature (overlap), and the prediction error rates for the signatures identified in individual study cohort and in the meta-cohort. Sorlie van't Veer Sotiriou Huang Meta-cohort Size 10 60 90 140 90 Overlap 4 14 19 6 -- Prediction error rate 0.28 0.29 0.35 0.18 0.33 Table 3 Comparison of the performances of the individual signatures and the meta-signature in each single study cohort. Table lists odds ratios (95% confidence interval) comparing the odds of actual recurrence for those being classified as high risk to the odds of recurrence for those being classified as low risk of recurrence by each signature. Cohort Signature Sorlie (n = 58) van't Veer (n = 78) Sotiriou (n = 98) Huang (n = 71) Sorlie (D = 10) 18.6 (5.0, 69.5) 2.1 (0.8, 5.4) 2.3 (1.0, 5.3) 10.87 (3.5, 33.8) van't Veer (D = 60) 3.1 (1.1, 9.2) 10.6 (3.3, 33.9) 4.1 (1.7, 9.7) 1.3 (0.5, 3.4) Sotiriou (D = 100) 1.7 (0.6, 5.0) 3.5 (1.4, 8.9) 7.8 (3.0, 20.1) 1.5 (0.6, 3.7) Huang (D = 130) 5.1 (1.6, 15.7) 2.3 (0.9, 5.6) 0.9 (0.4, 2.0) 184.9 (30.1, 1137.2) Meta (D = 90) 25.0 (4.2, 149.0) 4.1 (1.6, 10.6) 6.0 (2.5, 14.5) 5.8 (2.1, 16.5) D is the number of genes in a signature. n is the sample size for each cohort. Meta-analysis accounts for such heterogeneity of the individual signatures in two ways. First its overlap with the study-specific signatures ranged from 3–40%. The excluded genes are likely to be cohort-specific findings that can not be replicated. Second, the meta-signature recruited 41 genes not previously picked by any of the single cohort signature, likely representing predictive features with small but consistent effects previously masked in single studies. When examining the performances of the gene signatures, the meta-signature showed a comparable or better performance compared with the individually optimized signatures both in the odds ratio estimates (Bottom row of Table 3 ) and in Kaplan-Meier analysis (Figure 3 ). This shows that the meta-signature can serve as a common breast cancer recurrence index that is able to predict patient survival in heterogeneous sample populations. When a gene signature built in one study cohort performs differently in another, such meta analysis provides a solution to identify a cross-study validated expression signature that holds across independent samples. Figure 3 The 90-gene meta-signature achieves similar or better performance than the individually optimized signatures. A and E compare the Kaplan-Meier curves stratified by high versus low risk group predicted by the study-specific signature and by the meta-signature respectively in the Sorlie study cohort; B and F show similar comparison in the van't Veer study cohort; C and G show similar comparison in the Sotiriou study cohort; and D and H show comparison in the Huang study cohort. Comparison of data integration based on poe transformation and simple linear rescaling An alternative approach to integrating data across multiple datasets is to perform a study-wise global normalization. For one study, let be the globally scaled expression value for gene j in sample i . Each study dataset is then standardized to have zero mean and unit standard deviation. The linearly rescaled values can also be used for data integration purposes in that expression values generated from different array platforms are standardized to a common scale. Such an approach is less computationally challenging compared to the mixture model-based rescaling described in the previous sections. However, there are several advantages to the mixture model-based transformation. First, the method incorporates biological information into estimating the posterior probabilities of expression. The transformed values carry meaningful interpretations as signed probabilities of differential expression of a gene in a particular sample. Second, the underlying normal and uniform mixture distributions give equal density in the tails and is effective in reducing the influence of extreme expression values. And third, the Bayesian hierarchical modeling approach borrows strength across genes resulting in shrinkage-type estimators for a large correlated gene-specific parameter vector. This is a method in which the high dimensional gene expression data are denoised. To study the benefit of data integration based on poe compared to that based on the linearly rescaled values, we compared the model performances based on data integration by these two methods. Figure 4A shows that with the poe transformation, misclassification rates steadily decreases as more genes are used in the classifier. Performance based on linearly rescaled data (Figure 4B ), however, is unpredictable. Figure 4C and 4D uses a 90-gene meta-signature based on poe and based on the global standardization respectively in predicting survival. The signature based on poe is noticeably better than the signature based on global standardization in differentiating patients at low risk of recurrence from those at high risk of recurrence. Taken together, the poe transformation outperforms the linear rescaling method in combining multiple microarray data sets. The meta-signature identified based on poe values therefore offers more reliable prediction of recurrence-free survival in the meta-cohort. Figure 4 Comparison of model performances based on data integrated by poe transformation (A and C) and global standardization (B and D). A set of top 10 to 200 genes were used in a classifier to construct risk index and 40 th to 70 th percentiles of the cross-validated RIs were then used to dichotomize samples into a high risk or a low risk group. A. Misclassification rates based on poe transformation and B. based on global standardization. C. Performance of the 90-gene signature built on poe and D. built on global standardized data in differentiating patients at low risk of recurrence from those at high risk of recurrence. The meta-signature displays two distinct expression patterns A heat map representation of the poe profile for the 90 gene meta-signature revealed two distinct patterns of differential expression (Figure 5A ). Genes in the top half of the matrix displayed consistently high probability of over-expression (yellow) in the recurrent samples (R). On the other hand, genes in the bottom half displayed great probability of under-expression (blue) in the recurrent group. Individually generated heat maps of the raw data confirmed such distinct patterns at raw measurement levels (Figure 5B ). Functional annotation revealed genes involved in many important biological processes such as cell cycle regulation (e.g., CDC28 protein kinase regulator subunit 2), cell adhesion (e.g., chemokine C-X3-C motif receptor 1), and apoptosis (e.g., secreted frizzled-related protein 4). A complete list of the meta-signature genes can be found in the Additional file 7 . Some of the genes in the meta-signature were previously shown to correlated with breast cancer survival outcome. For example, Keyomarsi et al. [ 22 ] demonstrated the association of the cell cycle regulator cyclin E and death due to breast cancer. Figure 5 The 90 gene meta-signature displayed two distinct patterns of expression in breast cancer groups. (A) Heat map representation of differential expression probabilities for the 90 gene meta-signature across the combined samples. The top set of genes showed consistently high probability of over-expression (yellow) in the poor outcome group, and the bottom set of genes showed consistently high probability of down-regulation (blue) in the poor outcome group. (B) Heat map of log-transformed raw data. Individually generated heat maps of the raw measurements of gene expression confirmed the distinct expression patterns of the meta-signature from independent studies. Red represents up-regulation while green represents down-regulation. R (recurred) – poor outcome group; RF (recurrence-free) – good outcome group. Enriched functional classes in the meta-signature To gain a better understanding of the processes related to disease recurrence, we examined whether a particular functionally defined biological process is enriched in the recurrence signature. Each of the ninety genes were mapped to Gene ontology (GO) terms and then grouped by functional classes. Based on the hypergeometric distribution, we calculated the significance of over-representation of a particular process in the signature. Figure 6 demonstrated the top seven enriched functional groups in the meta-signature, comparing the total proportion (out of 2310 annotated) and the signature proportion (out of 85 annotated) of genes in each group. Cell cycle regulation is the most highly over-represented category (P = 0.001). All genes under this category except BCL2 displayed increased expression level, reflecting elevated cell cycle activities. Signal transduction represents the largest functional class over-represented in the meta-signature. Genes involved in signalling pathways that regulate cell growth (VEGF, PPP2R5C), immune response (TRAF3), apoptosis (SFRP4), and other processes are found to constitute 15.7% of the meta-signature compared to the 9.7% in the entire gene set (the common set). Figure 6 Top seven over-represented functional classes in the meta-signature. Black bars represent proportion of genes associated with each of the GO terms among the meta-signature, and white bars represent the corresponding proportion among the total study population of 2555 genes. P-value represents the significance of over-representation based on a hypergeometric distribution, and is calculated as the probability of observing larger proportion of a particular functional group genes in the meta-signature than in the entire gene set. The meta-signature genes are listed under each functional class. Discussion Several important issues to consider when integrating microarray studies include use of different gene expression measurement scales, varying analytical power and reliability of the results for individual studies. To account for these issues, we proposed a two-stage mixture modeling strategy, the strength of which was built on the mixture model based transformation and the subsequent data integration on the poe scale. In particular, poe provides a unified platform-free scale, and simultaneously enhances the intrinsic contrast in the expression data. Furthermore, combining sample pools on the poe scale mitigates the influence of potential artifacts from a single study. The benefit of such data integration is reflected on two counts. One, integrated sample cohorts improve the reliability of the findings by guarding against false positive results from a single study. Two, it increases the statistical power to detect small consistent effects that can be otherwise masked by inadequacy of the sample size of an individual data set. By implementing this modeling approach, we were able to combine information from four microarray studies to build an inter-study validated meta-signature for predicting survival in breast cancer patients. As described earlier, a common set of 2555 genes was used in this meta-analysis, as it is important to provide the same context for data-driven estimation of the posterior probabilities. Although we assume the common set comprises the most biologically relevant genes, the loss of potential predictive genes, however, may offset the statistical power of the analysis. For example, one of our recent studies has established the polycomb protein EZH2 to be an independent predictor of breast cancer survival outcome[ 23 ]. This gene was filtered out of the meta-analysis as one of the studies [ 12 ] did not profile EZH2. However, in each of the other three studies where EZH2 was profiled on the array, its expression level was found to correlate with survival (data not shown), which confirmed its role as a prognostic marker. Alternative approaches to allow genes profiled in some studies but not others is a topic for future research. Functional annotation of the meta-signature revealed genes such as Cyclin E and BCL2, which were previously shown to be correlated with survival outcome in breast cancer [ 22 , 24 ]. A strength of the inter-study validated signature is the capability of recruiting genes which may not be significant in one study due to limiting sample size or artifacts of the experiments. In this sense, the meta-signature will be more stable and less subjective to variations in subsets of the samples. As a result, the predictive genes in a meta-signature may carry more reliable information about tumor progression and patient survival. In conclusion, a distinction of the analysis presented here relative to those by other authors [ 3 , 6 ] is that we sought to find genes that were predictive of recurrence rather than predictive of diseased versus nondiseased status. Given the heterogeneity of the tumors with respect to treatment response and survival outcome, a prognostic prediction analysis is generally more difficult because it is a more complicated phenotype. Further, a prognostic signature (classifier) of failure risk trained in one cohort is often times difficult to validate in independent cohorts. The meta-analysis method presented here may potentially provide more powerful gene signatures that are predictive of prognosis because they are validated across multiple studies. Methods Data collection and preparation The breast cancer microarray data sets were obtained at the author's websites from four recently published studies [ 10 - 13 ]. Each data were preprocessed, either by a lowess normalization for two-channel microarray data [ 25 ] or a robust analysis for Affymetrix data [ 26 ]. We filtered for a common set of 2,555 genes from these four studies by Unigene Cluster IDs. Each data matrix of the 2,555 genes was then normalized by median centering and dividing by the standard deviation for each gene. Missing data were imputed by the k-nearest neighbors imputation algorithm [ 27 ]. Mixture modeling of microarray data Each of the four raw data sets was treated as an expression matrix X with elements x ij , where i = 1, ..., m k , j = 1, ..., n ( k = 1, .., 4 and n = 2,555). The expression measurement x ij can be the ratio of the two fluorescent dye hybridization intensities for the spotted cDNA arrays[ 10 , 12 ] and the Intjek oligonucleotide array [ 11 ], or averaged difference between the perfect match and mismatch probe hybridizations for the Affymetrix gene chip [ 13 ]. Let E be a latent class variable, and e ij indicates over-, under- or normal expression for each entry of the R matrices. We have: The values of e ij are latent and not directly observed from the data. We were interested in estimating the probabilities of e ij being 1 or -1 given the observed raw expression x ij , which were denoted as and . Estimates of these latent quantities were obtained under a Bayesian mixture model setting. In particular, we assume the raw expression x ij falls into one of the three expression categories. For each gene j , the expression then arises from a mixture of three distributions: ( x ij | e ij = 1) ~ f 1, j (·), ( x ij | e ij = 0) ~ f 0, j (·), and ( x ij | e ij = -1) ~ f -1, j (·). In the mixture, f 1, j , f 0, j and f -1, j are the density functions of the following distributions: respectively. Here, U refers to a uniform distribution and N refers to a normal distribution. α i + μ j is both the mean of the normal distribution and the threshold point in the uniform distribution. μ j is the gene effect and α i is the sample effect. The and provide limits to the uniform distribution in the mixture, and are set to be at least 3 σ j . = P ( e ij = 1) and = P e ij = -1) are the multinomial probabilities for e ij . With the specifications of models, we can calculate the latent quantities by Bayes' rule: By noting that the supports for the two uniform distributions are disjoint, the probabilities of differential expression are mutually exclusive with the forms: A one dimension measure can thus be constructed as poe = p + - p - . As a result, poe ranges from -1 to 1, and can be interpreted as the signed conditional probability of differential expression. To borrow strength across genes, the estimation of the gene-specific parameters was formulated under a Bayesian hierarchical model setting. Given the large amount of parameters, prior distributions were specified to model the variation of the gene-specific parameter estimates, in particular, We followed the recommendations of Parmigiani et al. [ 8 ] in terms of the prior choices. A Metropolis-Hastings MCMC sampling algorithm was then implemented to approximate the posterior distributions of the parameters. Data augmentation started at a set of data-driven initiating parameter values. For example, trimmed means and variances across samples were used as the initial values for the parameters in the normal distribution of the mixture. Further details of the Bayesian hierarchical mixture model used here can be found in Parmigiani et al. [ 8 ]. Matrices of were obtained for each of the five data sets (Additional files 1 , 2 , 3 , 4 ). Leave-one-out cross validation and risk index computation For the combined sample pool of the breast cancer patients (the meta-cohort), we defined outcome groups as recurred during followup and remained relapse-free for at least 3 years. In particular, Let T i be the event time for subject i , C i be the censoring time for subject i , and δ i = 1{ T i < C i } be the censoring indicator. Define a new outcome variable, where t * can be specified with clinical knowledge. We chose t * = 3 years in this study. We then consider constructing classifiers using y ; note that y = 1 corresponds to the poor outcome group and y = 0 to the good outcome group. The sample sizes for each study are shown in Table 1 . Logistic regression was used to build a classifier for prognosis. For each gene j , we fit the following univariate logistic regression model using data from all studies: where x * is the rescaled value that allows data integration across multiple studies. The esti-mated values of β j , , are then used to form a risk score using a variation of the compound covariate predictor method [ 28 , 29 ]; for a given set of covariate values x 1 , ..., x D , the risk index is given as . If we want to assess the performance of the classifier, we must deal with the issue of training and testing the model using the same data. An "honest" estimate of the prediction error rate is obtained using leave-one-out cross-validation. Define a risk index , where , and is the effect estimate for gene j in the combined meta-cohort without the i th sample. The risk index for sample i is a weighted linear combination of the expression profiles of the top D genes, where the ranking of the genes is based on their corresponding significance in the univariate logistic model fit. Classification of sample i to the risk groups is then based on the i th leave-one-out risk index, i.e., = I { RI i > c } with c being the empirical quantiles (40 th - 70 th ) of the RI's . The number of genes D in a classifier is treated as a parameter and optimized to minimize the prediction error rates. The list of the top cumulative genes in the meta-signature was obtained by ranking all 2,555 genes by the number of times in the leave-one-out cross-validation steps that each one had a P-value from the univariate logistic regression less than 0.001. Heat map display We used the treeview software [ 30 ] to generate a heat map representation of the poe pro-files of the meta-signature. Yellow represents high probability of over-expression and blue represents high probability of under-expression. For heat maps of raw data matrices, we preprocessed the data by mean centering and then dividing by the standard deviation for each row. The means and the standard deviations used in the normalization were the relapse-free (RF) sample means and variances for each study data. The values for the recurrence (R) samples after standardizing then represented the number of standard deviations over or under the mean RF sample expression. Authors' contributions RS, DG, and AC designed the study. RS carried out the statistical analysis and prepared the manuscript. DG and AC supervised the analysis and participated in the manuscript preparation. All authors read and approved the final manuscript. Supplementary Material Additional File 5 Plots of misclassification rates. The PDF file lists plots of misclassification error rates for classifiers identified in each individual study cohort and the meta-cohort. Click here for file Additional File 6 Plots of Kaplan-Meier curves. The PDF file lists Kaplan-Meier plots for study-wise cross-validation of the individually identified signatures. A gene signature was trained in one study cohort and used to validate in each of the other study cohorts as testing sets. Click here for file Additional File 7 Meta-signature gene list. The excel file contains a list of Unigene ID, gene symbol, and full name of the 90 genes in the meta-signature. Click here for file Additional File 1 POE imputation of the Sorlie data. The excel file contains a table of imputed signed probability matrix transformed from the Sorlie et al. study data (2,555 times 58 in dimension). Click here for file Additional File 2 POE imputation of the van't Veer data. The excel file contains a table of imputed signed probability matrix transformed from the van't Veer et al. study data (2,555 times 78 in dimension). Click here for file Additional File 3 POE imputation of the Sotiriou data. The excel file contains a table of imputed signed probability matrix transformed from the Sotiriou et al. study data (2,555 times 98 in dimension). Click here for file Additional File 4 POE imputation of the Huang data. The excel file contains a table of imputed signed probability matrix transformed from the Huang et al. study data (2,555 times 71 in dimension). Click here for file

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548679

Survey of general practitioners' knowledge about Helicobacter pylori infection

Background Helicobacter pylori , occurring throughout the world and causing gastroduodenal diseases, is one of the most common chronic bacterial agents in humans. The purpose of this study was to measure the general practitioners' (GPs) knowledge and practices pertaining to H. pylori infection. Methods A cross-sectional type questionnaire survey was conducted in all of 19 primary health care centres (PHCC) in Samsun, Turkey, between November 1 and December 31, 2003. The questionnaire was sent to 124 GPs and 109 (87.9 %) of those filled in. They were requested to answer the questions on the knowledge, sources of medical information, diagnostic tests and treatment to H. pylori . Results Medical journals were the most frequently used source of information on H. pylori , being cited by 86 (78.9%) of GPs. Ninety-two (84.4%) of the GPs reported having used one or more tests and 17 (15.6%) never used any test for the diagnosis of H. pylori infection. Only 9.8% had used stool antigen test for diagnosis. GPs reported that they would prescribe symptomatic treatment without ordering diagnostic tests for 29 (26.6%). 54.1% of the GPs explain that they sent patients with H. pylori infection to a specialist, and most used a triple drug regimen containing a PPI. Treatment duration varies between 7 to 28 days. 80.7 of the GPs treat patients for 14 days. Conclusion GPs may not have enough knowledge about the importance of stool antigen test or possibility of usage of this test. GPs have not sufficient knowledge about the difference between symptomatic and asymptomatic individuals. It is thought that GPs preferred to treat the patients with suspected ulcer empirically or to send them to a specialist because of the limited diagnostic conditions. The efforts to educate the GPs about the algorithms regarding the management of H. pylori infection during post-graduation period should be improved in PHCCs.

Background Helicobacter pylori , occurring throughout the world and causing gastroduodenal diseases, is one of the most common chronic bacterial agents in humans [ 1 ]. Although the number of peptic ulcers unrelated to H. pylori is increasing, most ulcers are related to H. pylori infection [ 2 , 3 ]. For most of the patients with gastrointestinal symptoms apply to general practitioners (GPs), non-invasive "test and treat" policies for H. pylori infection have been promoted in order to improve early detection and treatment of ulcers in dyspeptic patients [ 4 , 5 ]. The successful isolation of H. pylori infection in patients with chronic gastritis and peptic ulcer disease in 1983 has fundamentally changed concept of the etiologic, pathogenesis and management of upper gastrointestinal (UGI) diseases [ 6 ]. This has led to an explosion of H. pylori related information and the development and publication of international, regional and national guidelines [ 7 ]. Subsequently, numerous educational initiatives have been undertaken to educate health care professionals regarding the appropriate diagnosis and management of this infection. However, results from several recent surveys conducted in different countries have revealed that significant confusion exists and discrepancies are present in the thinking among GPs with respect to the understanding of the relationship between H. pylori infection and the pathogenesis, diagnosis and treatment of UGI diseases [ 6 ]. The major uncertainties surround the management of patients with dyspepsia where the GPs needs to make a decision whether to test for H. pylori infection and treat if positive, and when to refer patients to a specialist [ 8 , 9 ]. It is thought that too many patients with dyspeptic symptoms apply to GPs in Turkey. This study was performed a survey of GPs' to assess their knowledge and practices pertaining to H. pylori infection. Methods A cross-sectional study was conducted in all of 19 primary health care centres (PHCC) in Samsun, Turkey, between November 1 and December 31, 2003. The questionnaire was sent to all GPs (n = 124). 109 of 124 (87.9 %) GPs from different PHCCs completed the survey. The material used was adapted from the questionnaire devised by Sharma et al. [ 10 ] and translated into Turkish. The questionnaire was designed in a self-administered format with closed answers being provided to questions. Demographic variables such as gender, age and working year were assessed. The survey questionnaire includes a multiple-choice question relevant to sources of medical information. The H. pylori knowledge section contained 6 questions. The items assessed respondents' knowledge of diagnosis of infection, case selection for treatment and treatment options in H. pylori . Participating GPs were asked to offer the type(s) of diagnostic tests such as ELISA, histology, biopsy urease test (BUT), urea breath test (UBT) or culture of biopsy specimen. A list of 7 different clinical presentations was given. It was asked whether the respondents would offer testing for H. pylori and also treat the infection when the test results were positive for H. pylori . The respondents were asked to select a regimen for the management of H. pylori infection among the list of four drug combination regimens included proton pump inhibitor (PPI)-based triple therapies. [ 7 , 11 , 12 ]. GPs were also asked about their choice of treatment duration. The authors did not make any educational program focusing on H. pylori infection before or after the survey in this study period. Data were given as mean ± standard deviation (SD) and percentage. Results Sociodemographic characteristics The mean age and working year of the GPs was 31.7 ± 5.4 and 7.2 ± 5.0 years, respectively; 59 (54.1%) of the GPs were women. Sources of information Medical journals were the most frequently used source of information on H. pylori , being cited by 86 (78.9%) of GPs. Pharmaceutical company-sponsored symposia (70.6%), textbooks (64.2%), conferences (20.2%) and on-line sites (6.4%) were the other major source of information used by the GPs. These numbers add up to more than 100% because the GPs had been checked more than one item. Diagnostic tests for H. pylori Ninety-two (84.4%) of the GPs reported having used one or more tests and 17 (15.6%) never used any test for the diagnosis of H. pylori infection. Of those, 44.1% had used UBT, 34.5% had used BUT, 23.8 % had used ELISA and 9.8% had used the stool antigen test. The practitioners included in the survey had not equally access to all diagnostic tests mentioned in the study. Testing and treatment choices for H. pylori infection The proportions of GPs who would test patients for H. pylori infection in the 9 different clinical situations and the proportions of those who would offer treatment based on a positive test result, were summarized in Table- 1 . 92 (84.4%) of the GPs answered this section. GPs reported that they would prescribe symptomatic treatment without ordering diagnostic tests for 29 (26.6%). 54.1% of the GPs explain that they send patients with H. pylori infection to a specialist. Treatment of H. pylori infection in patients with confirmed H. pylori -positive Treatment regimens of choice are listed in Table- 2 . Most used a triple drug regimen containing a PPI. Of the GPs 3.7% would treat patients for 7 days, 4.6% for 10 days, 80.7% for 14 days, 3.7% for 21 days, 5.5% for 28 days and 1.8% for more than 28 days. Discussion UGI symptoms are common reasons for patients to visit GPs. In recent years, the development of non-invasive H. pylori detection methods, including ELISA and the UBT, has enabled GPs to diagnose and treat H. pylori infection. The inadequate treatment of peptic ulcer disease results in therapy failures, high recurrence rates, the emergence of resistant bacterial strains, and increased health care costs, therefore clinical application of current knowledge is crucial [ 13 , 14 ]. There are several tests used for diagnosis of H. pylori infection [ 12 , 13 , 15 , 16 ]. 84.4% the GPs surveyed used one or more tests for H. pylori infection same as Huang J et al.'s study [ 6 ]. However this was higher than reported in a recently preliminary survey of GPs, of whom 48% used one or more tests [ 17 ]. UBT is the most (44.1%) used tests in this study. On the other hand, stool antigen test, a useful test for diagnosis, was the least ordered test. It is thought that GPs may not have enough knowledge about the importance of stool antigen test or possibility of usage of this test. Diagnosis of infection should be done by using UBT or stool antigen test. It is always recommended to test by UBT, or endoscopy-based test if endoscopy is clinically indicated, for successful eradication. On the other hand stool antigen test is the alternative if UBT is not available [ 14 ]. It is worrisome that considerably fewer perceived a need for testing and subsequent treatment in patients with a new diagnosis and past history of duodenal ulcer (Table 1 ). Both the recent America College of Gastroenterology (ACG) publications [ 8 ] and Centers for Disease Control and Prevention (CDC) [ 7 ] clearly state that a new diagnosis and past history of duodenal ulcer disease is a definite indication for testing and, if positive, for treatment. Testing and treatment of H. pylori infection are recommended following resection of early gastric cancer and for low-grade gastric MALT lymphoma. Retesting after treatment may be prudent for patients with bleeding or otherwise complicated peptic ulcer disease [ 7 ]. Although it is not recommended to test the asymptomatic individuals for H. pylori infection, 64.1% of GPs reported that they would offer testing for H. pylori infection and 31.5% of them reported that they would treat H. pylori infection based on a positive test result in asymptomatic individuals. These findings suggest that GPs have not sufficient knowledge about the difference between symptomatic and asymptomatic individuals. On the other hand, in any person testing positive for the infection, treatment may be offered after a full discussion about its potential risks and benefits [ 4 , 18 ]. Anti- H. pylori therapy was almost never recommended for suspected ulcer disease without the prior use of diagnostic tests [ 13 , 18 ]. In this study it was found that 26.6% of GPs treat the initial onset of a suspected ulcer empirically without ordering diagnostic tests for H. pylori infection. 54.1% of the GPs, whether ordering diagnostic tests or not, explain that they send patients with suspected or diagnosed H. pylori infection to a specialist. In the light of these findings, it is thought that GPs preferred to treat the patients with suspected ulcer, empirically or to send them to a specialist because of the limited diagnostic conditions, the lack of rapidly diagnostic tests at PHCCs, or they thought that they should be treated by a specialist. H. pylori peptic ulcers are treated with drugs that kill the bacteria, reduce stomach acid, and protect the stomach lining. Antibiotics are used to kill the bacteria. Two types of acid-suppressing drugs might be used: H 2 blockers and PPI. H 2 blockers and PPI have been prescribed alone for years as a treatment for ulcers. When used alone, these drugs do not eradicate H. pylori and, therefore, do not cure H. pylori -related ulcers. Bismuth subsalicylate, a component of Pepto-Bismol, is used to protect the stomach lining from acid. It also kills H. pylori [ 4 , 7 , 12 , 19 ]. The highest eradication rates are achieved with the following regimens: a PPI, clarithromycin, and either amoxicillin or metronidazole for 2 week; ranitidine bismuth citrate, clarithromycin, and either amoxicillin, metronidazole, or tetracycline for 2 week; a PPI, bismuth, metronidazole, and tetracycline for 1 to 2 week [ 7 , 11 , 12 , 20 ]. There is good evidence for the efficacy of 14-day triple regimens including a PPI or RBC. Possibility of shortening the duration of PPI-based triple therapies between 7 and 10 days will depend on further results from US-based studies. Seven-day duration may be too short. Some trials have failed to show a statistically significant difference in eradication rates between 7-day and 14-day duration [ 20 ]. 84.4% GPs test for H. pylori infection but 15.6% never test. Urea breath test is a commonly used investigative tool for H. pylori infection. Triple therapy consisting of a proton pump inhibitor, clarithromycin and amoxicillin is the most commonly used treatment combination for H. pylori infection. It was found that most of the information was being obtained in traditional teaching formats such as medical journals, pharmaceutical company-sponsored symposia, textbooks and conferences. Other studies ([ 10 , 13 , 17 ]) confirmed our finding that medical journals were the most important source of information on H. pylori infection among GPs. Our data suggested that pharmaceutical company-sponsored symposia were used very frequently among GPs. Patients with dyspeptic complaints are mostly managed in primary care. The most prescriptions for dyspepsia are empirical without testing due to limitations of diagnostic facilities around the world [ 21 ]. Similar results were reported that there were significant gaps related to testing and treating H. pylori infection [ 13 , 17 ]. Conclusions The diagnosis of and treatment of peptic ulcer disease related to H. pylori is not adequate. The choice of optimal therapeutic decision depends on the appropriate definition of the disease. In order to provide accurate diagnosis and treatment of H. pylori infection, it's suggested that efforts to educate the GPs about the algorithms regarding the management of H. pylori infection during post-graduation period should be improved in PHCCs. Competing interests The author(s) declare that they have no competing interests. Authors' contributions SC participated in the design and coordination of the study; ATS provided drafted the manuscript and performed the statistical analysis. YP drafted the questionnaire and participated in study design and coordination. HL conceived the study, participated in its design and drafted the manuscript. 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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521181

Did We or Didn't We? Louse Genetic Analysis Says Yes

If you're an evolutionary biologist, the tired old saw, “You can tell a lot about a person by the company they keep,” represents a fresh new approach to a longstanding problem. Especially if the company in question is a parasite—say, for example, lice—and the problem is tracing the path of human evolution. One of the hottest debates in the study of human origins centers around whether modern Homo sapiens interbred with archaic humans. While genetic data have provided insight into recent human evolution, fossils remain the only available evidence for many archaic human species—and the fossil record is notoriously spotty, leaving the data open to multiple interpretations. Two prominent models and a subset of variants have emerged, differing mainly on the question of gene flow: one asserts that modern humans emerged from an archaic ancestor in Africa about 130,000 years ago and then replaced archaic forms in Africa, Asia, and Europe with no gene flow between them; the other proposes gene flow between modern human populations as well as interbreeding between modern and archaic forms in different parts of the world. Both models find support in the available data, but neither can claim a perfect fit with all the data, leaving the possibility of interbreeding an open question. Faced with a relative paucity of human fossil and genetic data, scientists have been forced to rely on other data sources. Mounting evidence suggests that parasites with an established coevolutionary history with their hosts can serve as a proxy for host evolutionary history, an especially handy tool in the event of insufficient host data. Following this approach in a new study, David Reed and colleagues circumvent the lack of human data by analyzing the next best thing: head lice. As host-specific, obligate parasites—that is, occurring on a single species and not able to survive off that host—lice require direct physical contact between hosts for transmission. As human parasites, lice harbor in their genetic sequence hints of the slings and arrows of evolutionary fortune (and touches of grace, for that matter) that strike their host. Recent studies of the evolutionary history of other human parasites (tapeworms, malarial parasites, and human papillomaviruses), for example, fall in line with fossil and genetic data that place our origins in Africa. Ancient nit combs (above) resemble modern ones (below). (Egyptian wooden comb courtesy of Te Papa, Wellington, New Zealand, negative number F.003884/5. Modern louse comb and head louse images by Vincent S. Smith) Two louse species parasitize humans, head/body ( Pediculus humanus ) and pubic (Pthirus pubis) . Head and body lice obviously occupy different habitats, but are not genetically distinct. Interestingly, P. humanus contains two ancient lineages, offering the opportunity to shed light on this murky period in human evolution. To do this, Reed and colleagues had to reconstruct the evolutionary history of P. humanus , which they did using morphological and genetic analyses of this and other species of lice. They confirmed that P. humanus comprises two lineages—one contains both head and body forms and has worldwide distribution; the other contains only the head louse and is restricted to the New World—but discovered that P. humanus originated long before its H. sapiens host. Humans went through a population bottleneck around 100,000 years ago, followed by an expansion; one would expect to see the same thing in lice. Population genetics studies revealed, however, that only the worldwide lineage went through a bottleneck and subsequent expansion. The New World lineage not only maintained a relatively stable population size but followed an evolutionary path distinct from the worldwide lineage for the past 1.18 million years. It is unlikely, the authors argue, that two ancient louse lineages could embark on such different evolutionary histories on the back (or head) of a single host. More likely, the New World louse evolved on an archaic form of humans and then cast its lot with a modern version. While the split between H. sapiens and H. neanderthalensis was too recent (about 700,000 years ago) to support a concurrent split between the worldwide and New World lice lineages, the split between H. sapiens and H. erectus (about 1.8 million years ago) could. Reed and colleagues propose a scenario in which H. sapiens and H. erectus carried distinct types of lice owing to a million years or so of isolation. As the first waves of modern humans left Africa about 100,000 years ago and modern humans replaced archaic forms, the two forms engaged in enough contact—whether in the form of fighting, swapping clothes, or interbreeding—for archaic lice to make the switch to modern human hosts. Tackling the question of interbreeding, the authors suggest, might best be pursued by studying P. pubis , which requires sexual contact for transmission.

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548686

Population dynamics of the Teak defoliator (Hyblaea puera Cramer) in Nilambur teak plantations using Randomly Amplified Gene Encoding Primers (RAGEP)

Background The Teak defoliator ( Hyblaea puera ) is a pest moth of teak woodlands in India and other tropical regions (e.g. Thailand) and is of major economic significance. This pest is of major concern as it is involved in complete defoliation of trees during the early part of the growing season. Defoliation does not kill teak trees, but it results in huge amount of timber loss. Teak defoliator outbreaks are a regular annual feature in most teak plantations in India and it is extremely difficult to predict the exact time and place of occurrence of these outbreaks. Evidence from the study of the population dynamics of H. puera indicated habitual, short range movements of emerging moth populations, suggesting that these populations have spread to larger areas, generation after generation, affecting the entire teak plantations. We were therefore interested in investigating the temporal and spatial relationship among various population groups in Nilambur, Kerala (India) and address the cause of outbreak at the landscape level. Results The populations were classified into 'endemic', 'epicenter' and 'epidemic' populations based on the time of occurrence and size of infestation. We devised a novel method of screening nuclear and mitochondrial DNA polymorphisms using Randomly Amplified Gene Encoding Primers (RAGEP). We have used this method extensively to evaluate the species specificity, reproducibility and to discriminate among the three different characterised populations of teak defoliator. Conclusions This method also allowed us to comment with some certainty that the endemic teak defoliator, H. puera do not play a major role in contributing to large-scale infestations. With respect to the hypotheses put forward regarding the origin of outbreaks of the moth, this study confirms the role of migration in outbreak causation, while negating the belief that endemic populations aggregate to cause an epidemic.

Background Teak ( Tectona grandis L.) is a very valuable timber species, and is a member of the moist deciduous and dry deciduous forest types. Teak plantations are threatened by two major pests: the Teak Defoliator ( Hyblaea puera Cramer) Lepidoptera: Hyblaeidae and the Teak Skeletonizer ( Eutectona machaeralis (Walker) syn.). H. puera is less widely distributed in the tropics: in Oriental and Australian regions (India, Sri Lanka, Burma, Java, Papua New-Guinea, Northern Queensland in Australia, Solomon Islands); in the West Indies; and in South and parts of East Africa [ 1 ]. The Teak defoliator is of major concern since it is involved in complete defoliation of trees during the early part of the growing season. Defoliation does not kill the trees, but does lead to huge timber loss. Recent studies have shown that the defoliation leads to an average loss of 44% of the potential volume increment in four to nine year-old teak plantations. It has been estimated that in the Nilambur teak plantation during the study period, protected trees increased by an annual increment of 6.7 m 3 /ha compared with 3.7 m 3 /ha for unprotected trees, a gain of 3 m 3 /ha per annum [ 2 ]. Teak defoliator outbreaks are a regular annual feature in teak plantations in Kerala, India. It is difficult to predict the exact time and place of these outbreaks. Evidence gathered from the past decade on the population dynamics of H. puera indicates habitual, short range movements of emerging moth populations, suggesting that these spread to larger areas, generation after generation, affecting entire teak plantations [ 3 ]. Earlier studies also indicated that the outbreaks begin as small epicenters during the pre-monsoon season [ 4 ]. Populations were classified as 'endemic', 'epicenter' and 'epidemic', based on their time of occurrence and the density of the population as represented by the area it infests. Endemics are insects belonging to the low-density population level; epicenters are patchy, medium density outbreaks that occur during the pre-monsoon season, whilst epidemic represents large area, high-density outbreak populations. An understanding of the origin and spread of the epidemic of this pest, which erupt suddenly following the pre-monsoon rain each year, is an important prerequisite for developing appropriate control strategies. If progenies of the epicenter populations cause the larger epidemics, control of these could prevent major outbreaks. On the other hand, if immigrant moths were involved, it would be difficult to control major outbreaks. Thus, understanding the cause and effect relationship between initial small outbreaks and large outbreaks that occur later in the year is crucial for the control of the pest. Recently, molecular markers have been used to enhance understanding of insect displacements, especially including estimates of movement of particular genotypes and/ or biotypes, reproductive strategy and success. Such approaches have also been used to study founder events [ 5 ], geographical invasions [ 6 ], small and large scale displacements [ 7 , 8 ], including movement of entire population demes [ 9 ], and even altitudinal movements related to habitat patchiness and persistence [ 10 ]. Molecular data can yield valuable information when integrated with information from ethology, field ecology, comparative morphology, systematics and palaeontology [ 11 ]. Use of direct and indirect methods of tracking insects along with description of the role and utility of various molecular markers – protein and DNA – in monitoring insect dispersal, has been extensively reviewed [ 12 ]. Arbitrarily-primed DNA markers, and involving the polymerase chain reaction (PCR), have proved very useful for genetic fingerprinting and for facilitating positional cloning of genes. This class of markers are particularly important for less studied species, for which genome sequence information is generally not known. These technologies include randomly amplified polymorphic DNA (RAPDs) [ 13 , 14 ], DNA amplification fingerprinting (DAF)[ 15 ], and amplified fragment length polymorphisms (AFLPs) [ 16 ]. In this study, we used a variant of the RAPD approach involving various nuclear and mitochondrial gene specific primers to trace the origin of teak defoliator outbreaks. It is expected that the molecular data would provide the necessary information to elucidate the origin of the epidemic population. Such information should prove valuable in planning and implementing measures to control these pests. Therefore, the aim of the present study was to identify the relationship among the three apparent populations – endemic, epicenter and epidemic. Results The nuclear and mitochondrial gene specific primers chosen did not produce any amplification product when used in combination with the corresponding primers as described in the UBC primer set kit [ 17 ]. This resulted in our devising a novel PCR, which we have named RAGEP-PCR. In RAGEP-PCR, we used single nuclear and mitochondrial gene encoding primers at low stringency annealing temperatures. Unlike RAPDs, in RAGEP longer nuclear (21–26 nucleotide) and mitochondrial (19–26 nucleotide) gene encoding primers were utilised, and which we have here extensively employed to evaluate the species taxonomic specificity/reproducibility and to discriminate the endemic, epicenter and epidemic populations of teak defoliator from one another. RAGEP markers were first tested for polymorphisms, species-specificity and repeatability. Similar fingerprinting pattern were observed in subsequent PCRs for the same individual using the same primers (Fig 1 ), which displayed overall robustness and repeatability with RAGEP-PCR. It was also possible to discriminate various moth species based on their species-specific DNA fingerprint pattern (Fig 2 ). The bands scored for each nuclear RAGEP used in the present study were of a size range 200 bp to 1500 bp. With nuclear RAGEP markers, an average of 2–3 monomorphic bands were observed, except for primer CK6-5'. In each marker, the average number of bands scored varied from 7–16. The maximum number of bands was detected using primer cytC-B-3', while the maximum number of monomorphic bands were detected using primer EFS599. Figure 1 Reproducibility of RAGEP fingerprints. mt1-3, nu1-3 depicts reproducibility of RAGEPs using mitochondrial and nuclear primers respectively Figure 2 Species specificity of RAGEP fingerprints. M1-4 depicts variability in Lepidopteran species. M1-Eutectona machaeralis , M2-Sylepta derogata , M3-Cnaphalocrocis medinalis , M4-Bombyx mori Each individual RAGEP marker gel was screened and a similarity matrix was generated. Subsequently similarity matrixes of all experimental patterns were combined to generate a UPGMA (Unweighted pair-group mathematical average) tree. While evaluating the similarity matrix based on the Dice coefficient for all nuclear specific RAGEP markers and whilst constructing a UPGMA tree, it was observed that the various population groups of H. puera fall in two clusters, which are further divided into two major sub clusters. Average similarity between the two major clusters was 20%, while that between the two sub clusters was 34%. In one of the major clusters, we observed all the endemic insects clustering together with some of the populations from the epicenter insects; however, both populations fall in two distinct sub-clusters (Fig 3 ). Similarly in the second major cluster, the remaining populations from the epicenter and entire epidemic insect populations were likewise seen to fall into two distinct sub-clusters. Figure 3 RAGEP fingerprint patterns generated by nuclear gene specific DNA markers in individuals of three populations (Panel B) and UPGMA dendrogram showing clustering of different insect populations of Hyblaea puera (Panel A) Using the mitochondrial RAGEP markers, the average numbers of bands scored for each primer ranged from 6–15. All bands scored were of size range 300 bp to 1600 kb. The maximum numbers of bands detected was found using primer SR-J-14233, the minimum numbers using marker N4-N-8924. Among mitochondrial markers, an average of 1–2 monomorphic bands were observed. The maximum number of monomorphic bands was observed using marker CB-N-10920. Two distinct clusters were observed in the UPGMA dendrogram for mitochondrial markers. Similarity between the two clusters was only 20%. One of these clusters comprised the majority of the endemic samples with a few samples from epicenter insects, whilst the other cluster was comparatively larger and had the two major sub clusters. Both these sub-clusters have insects from epicenter and epidemic populations (Fig 4 ). From this dendrogram, it may be deduced that all the seven epidemic population samples tested in the study shared the same gene pool with sets of epicenter populations. In contrast, the endemic populations are genetically distant from the epicenter populations. Figure 4 RAGEP fingerprint patterns generated by mitochondrial gene specific DNA markers in individuals of three populations (Panel B) and UPGMA dendrogram showing clustering of different insect populations of Hyblaea puera (Panel A) Discussion The first teak plantation in India was started as early as 1842 in Nilambur, Kerala State, India. Preliminary information on the life history of H. puera and the nature of its damage was published in 1898 [ 18 ]. H. puera outbreaks have been reported to begin in small epicenters and later spread to larger areas. It was then suspected that population build-up in the early outbreak epicenters might account for the subsequent widespread epidemic. However, a study using the time lapse (developmental time) between two epidemics to determine whether an earlier epidemic was responsible for causing the subsequent outbreak showed that all subsequent outbreaks could not be attributed to previous outbreaks, thereby indicating the possibility of migrant populations being involved [ 19 ]. Several technical advancements on the DNA fingerprinting methodologies have been established to resolve the taxonomic uncertainties and address the issue on species variability and migration [ 13 - 16 , 20 , 21 ]. The RAGEP-PCR method described here uses gene-specific primers and randomly amplifies the nuclear and mitochondrial-like gene products. Longer mitochondrial (19–26 nucleotide) gene encoding primers are likely to increase the reproducibility and specificity when compared to RAPD technique. This method was found to be efficient, simple and highly reproducible. Here it has been effectively used to discriminate the various population groups of H. puera infesting teak plantations in South India. It can also be used to discriminate taxonomically various closely – related moths to the species level. Mitochondrial RAGEP fingerprints are derived from the randomness of RAGEP-PCR. It is difficult to predict with certainty that the bands are diagnostic feature of the mitochondrial genome, but since RAGEP PCR uses gene specific primers, the PCR products could therefore be a result of amplification of homologous genes or pseudogenes which could represent nuclear mitochondrial DNA (NUMTs). Mitochondrial DNA sequences are frequently transferred to the nucleus-giving rise to NUMTs, which are considered to be common in eukaryotes [ 22 ]. Very high rate of horizontal transfer between organellar and nuclear genomes has been reported in the brown mountain grasshopper, Podisma pedestris (L.)[ 23 ]. Age groups, sexes, life history variants, etc. and the processes including birth, death, immigration and emigration as different phenotypic classes have been very well defined [ 24 ]. While studying the differentiation process of grain aphid, Sitobion avenae (F.) populations across agricultural ecosystems using DNA fingerprinting [(GATA) 4 ] and RAPDs, it was possible to discriminate the micro- and macro geographical heterogeneity [ 25 ]. Highly diagnostic banding patterns in individuals of S. avenae on wheat and cocksfoot grass, Dactylis glomerata (L.) were observed during the early months of infestation, which declined as the season progressed, largely as a result of genetic drift and local movement between adjacent host species [ 26 ]. Monophyly and a strong biogeographic pattern of each biotype have been reported in whitefly, Bemisia tabaci (Gennadius) populations studied throughout the world [ 27 ]. While evaluating the genetic structure in introduced population of the fire ant, Solenopsis invicta (Buren) using different classes of markers, it was confirmed that both mitochondrial and nuclear markers display the same hierarchical structure [ 28 ]. Distinct mitochondrial and nuclear DNA sequence divergence patterns for phylogenetic inference has been established among nymphalid butterflies [ 29 ]. The present study using RAGEP-PCR provides a tool for a logical continuation of the earlier work to trace the relationship of endemic, epicenter and epidemic populations of the teak defoliator. The dendrogram produced from nuclear RAGEP clearly indicates that the endemic insects are not involved in causing the epidemic; however, they are apparently involved in the localized spread by building up small epicenter populations. Similarly, while evaluating the observation based on mitochondrial RAGEP's, it is further apparent that endemic populations were not involved in causing the epidemic. This suggests that all the epidemic insects, which are spatially distinct, but temporally co-occurring, share the same gene pool. Randomness of genome amplification methods have been efficiently used in constructing the phylogenetic history in the weevil, Aubeonymus mariafranciscae (Roudier), which had diverged recently [ 5 ], whilst the origin of the Argentine stem weevil, Listronotus bonariensis (Kuschel) in New Zealand, was traced to the eastern coast of South America [ 30 ]. Use of RAPDs to examine, for example, population subdivision of the saw toothed grain beetle, Oryzaephilus surinamensis (L.) [ 31 ], characterization and identification of Asian and North American gypsy moth, Lymantria dispar (L.) [ 32 ], host based genotype variation in S. avenae [ 33 ], and genotypic variation among different phenotypes of asexual adult winged and wingless of some clones of cereal aphid species [ 34 ], has been well documented. Earlier reports involving molecular DNA markers mention the use of these markers in the detection of sibling species of black flies, Simulium spp. [ 35 ], whilst the dynamics of colonization of Drosophila subobscura (Collin) [ 36 ] in the west coast of North America and its impact in the sibling species Drosophila athabasca Sturtevant and Dobzhansky, and Drosophila azteca Sturtevant and Dobzhansky has been extensively studied by allozymes, mitochondrial DNA (mtDNA) and RAPD markers. With the Teak defoliator, earlier studies based on temporal and spatial distribution of the larvae indicated that the epicenters were not constant over the years and did not represent highly favourable local environments [ 3 ]. The present study found little evidence to show that the aggregation of moths belonging to the endemic populations cause the epicenter populations. On the other hand, the findings do suggest the alternate hypothesis, i.e., that immigration of moths from distant teak plantations cause the epidemic, and that there is a continuous inflow of moths during the infestation period. This suggests that under a single demographic structure, two phenotypic classes of H. puera coexist during the outbreak season. The degree of variability observed for RAGEPs also argues that this technique could be useful for a variety of questions, including individual identification, strain identification and phylogenetic analysis. Conclusions The present results appear to validate the hypothesis, that control of H. puera epicenter populations would help prevent large-scale outbreaks of the teak defoliator in teak plantations. Therefore, appropriate strategies should be adopted to control the epicenter populations, which occurs in a smaller area. This appears to be a more practical and economical approach for teak defoliator management when compared with management of the pest in the total plantation area covering thousands of hectares. Thus the molecular markers detected using RAGEP-PCR can enhance the understanding of insect population dynamics and aid in tracing the spread and cause of epidemics. Methods Sample collection Based on the spatial pattern of infestation in the past, the area was divided into convenient observation units of approximately 50 ha, based on natural boundaries of streams, roads and footpaths. The canopy of teak is continuous within in the observation area. Each area was monitored every 15 days, which was precisely based on the life cycle of H. puera . Larval samples were collected from the infestation sites. Whenever fifth instar larvae were available, ten larvae were preserved in 70 % alcohol and stored deep frozen at -20°C. If only lower stages were available, i.e., third or fourth instar, they were reared up to 5th instar in the laboratory. Ten 5th instar larvae were preserved for DNA isolation from each sample site, whilst the remaining larvae were reared into the next generation. Each sample was assigned a code number containing the details of Year / Month / Date / Block / Grid / Generation for further reference. Using the duration of each instar (egg – one day; 1 st and 2 nd instars – two days each, 3 rd to 5 th instars – three days each; pre-pupa – one day and pupa – four days), the temporal data on outbreaks were examined to see whether each subsequent epidemic could be explained on the basis of a previous outbreak. The details of location of pest incidence and extent of infestation were later transferred to the field map in order to understand the spatial pattern of infestation (Fig 5 ). Figure 5 Landscape of Nilambur teak plantation showing distribution of the endemic, epicenter and epidemic populations of Hyblaea puera Populations were classified as 'endemic', 'epicenter' and 'epidemic', based on their time of occurrence and the density of the population as represented by the area it infests. Five endemic populations, twenty six epicenter populations and seven epidemic populations for the year 2002 were included in the study. Earlier studies had indicated that outbreak begin as small epicenters in February during the pre-monsoon season and end by June. Endemic samples were collected throughout that year based on their stray occurrences in various life stages, whilst epicenter samples from each aggregated patch were collected only from the insects that attained the same stage of its life cycle at the time of collection in that patch. Similarly the epidemic samples were also collected from insects representing the same life stages at the time of collection from each aggressive patch. The temporal relationship between the endemic population and the epicenter populations and that of the epicenter populations with the large-scale epidemics were first worked out. The larval samples that were geographically close and had a difference of one complete life cycle stage between the population groups were subjected to molecular studies to evaluate their relatedness. DNA isolation DNA extraction was performed with a minor modification of isolation and purification protocol as described earlier [ 37 ] being extracted from whole larvae and quantified spectrophotometrically using a spectrophotometer at 260 nm (Shimadzu). The quality of the DNA was checked spectrophotometrically by taking the absorbance ratios of 260/280 nm. Polymerase chain reaction Both nuclear and mitochondrial DNA RAGEP amplifications were performed in a total volume of 30 μl. Each reaction consisted of 1x Taq buffer with 1.5mM MgCl 2 , 1.2 U of Taq polymerase (BG), 0.25 mM of dNTPs (Amersham) and 12 pM of primer per reaction. Primers were initially screened for polymorphism and repeatability. Amplifications were performed in similar cycling conditions in a Thermocycler (Biorad) programmed as follows: initial denaturation at 95°C for 5 min., followed by 45 cycles of cycle denaturation at 94°C for 1 min., annealing at 36°C for 1 min., extension at 72°C for 2 min. and final extension at 72°C for 5 mins. The amplification products were separated using 1.2% agarose gel in 0.5 × TBE buffer with ethidium bromide staining to visualize the product separation using a Bio-Rad's Fluor S imager. The molecular weight of each band was estimated by comparing with a co-migrating 100-bp ladder (Amersham). RAGEP fingerprints of each sample from different regions were then interpreted using Fingerprint type module of Bionumerics software (Applied Maths Kortrijk Belgium, ver.2.0). A preliminary screening with 50 nuclear RAGEPs and 37 mitochondrial RAGEP primers were evaluated for polymorphism and repeatability. Only 11 nuclear (Table- 1 ) and mitochondrial RAGEPs (Table- 2 ) from each group was selected for the study, as they showed constant repeatability of highly polymorphic patterns. Species specificity was evaluated by comparing the banding patterns in H. puera with those from the Teak skeletonizer, E. machaeralis (Walk.), Leaf roller, Sylepta derogata (F.), Leaf folder, Cnaphalocrocis medinalis (Guenée), and the Silkworm, Bombyx mori (L.). Table 1 Insect nuclear gene specific primer sequences used in nuclear RAGEP-PCR S.No Primer name Sequence 1 EFS599 ATC TCC GGA TGG CAC GG(CT) GAC AA 2 22.5drc GAA CCA (AG)TT (AG)AC (AG)TG (AG)AA GAT C 3 LEPWG1 GA(AG)TG(CT)AA(AG)TG(CT)CA(CT)GG(CT)ATGTCT GG 4 CK6-5' GAC CAC CTC CGA GTC ATC TC(CG) ATG 5 CK7-3' CAG GTG CTC GTT CCA CAT GAA 6 CytC-B-3' CAT CTT GGT GCC GGG GAT GTA TTT CTT 7 EF1-5' GAC AAC GTT GGC TTC AAC GTG AAG AAC G 8 Tub3-5' GAT TTG GAG CC(AGCT) GG(AGCT) ACC ATG GA 9 18S-A1984 TCC CTG GTT GAT CCT GCC AGT A 10 S1124 AGC GTA TGG C(AC)T C(AG)A AGAACT G 11 rcM4 ACA GC(CGA) AC(GT) GT(TC) TG(CT) CTC AT(AG) TC Table 2 Insect mitochondrial gene specific primer sequences used in mitochondrial RAGEP-PCR S.No Primer name Sequence 1 C1-J-2183 CAA CAT TTA TTT TGA TTT TTT GG 2 TL2-J-3034 AAT ATG GCA GAT TAG TGC A 3 C2-N-3661 CCA CAA ATT TCT GAA CAT TGA CCA 4 TK-N-3785 GTT TAA GAG ACC AGT ACT TG 5 N4-N-8924 AAA GCT CAT GTT GAA GCT CC 6 CB-J-10612 CCA TCC AAC ATC TCA GCA TGA TGA AA 7 LR-J-12887 CCG GTC TGA ACT CAG ATC ACG T 8 LR-J-13417 ATG TTT TTG TTA AAC AGG CG 9 LR-N-13398 CGC CTG TTT AAC AAA AAC AT 10 SR-J-14233 AAG AGC GAC GGG CGA TGT GT 11 CB-N-10920 CCC TCA GAA TGA TAT TTG TCC TCA Analysis The polymorphic content for nuclear and mitochondrial primers were analyzed using Bionumerics software [ 38 ]. Band search parameters were kept constant as 5% minimum profiling for all the gels. The position tolerance for selection of bands in constructing a dendrogram was kept constant at 1% through out the interpretations. Only bands showing clear and reproducible patterns were included in the final analysis and these were scored. Real-time normalization of gel electrophoresis patterns and band position for all the gels was based on the reference system for the species-specific bands. Normalization helped us to control the brightness and streakiness of bands without altering the lighter bands and also control the inter-gel mobility shifts. Subsequently a data matrix of similarity values was produced for each individual for each marker. The Dice coefficient was used to analyze the similarities of the banding patterns. Consensus similarity matrix and dendrogram based upon individual matrices from different markers were used for pair wise clustering based on unweighted pair group method (UPGMA) with average linkages (11). The UPGMA dendrogram prevails on the assumption that nucleotide substitution rates are same across all branches. It employs a sequential clustering algorithm, in which local topological relationships are identified in order of similarity, and the phylogenetic tree is built in a stepwise manner. All analysis was done using Bionumerics software V-2. Authors' contributions CN and MB performed the molecular studies and are responsible for the interpretation of molecular data whilst TV and VVS performed the field data collection and are responsible for spatial and temporal data interpretation. All authors read and approved the final manuscript. MB and VVS conceived and designed the study.

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Multivariate search for differentially expressed gene combinations

Background To identify differentially expressed genes, it is standard practice to test a two-sample hypothesis for each gene with a proper adjustment for multiple testing. Such tests are essentially univariate and disregard the multidimensional structure of microarray data. A more general two-sample hypothesis is formulated in terms of the joint distribution of any sub-vector of expression signals. Results By building on an earlier proposed multivariate test statistic, we propose a new algorithm for identifying differentially expressed gene combinations. The algorithm includes an improved random search procedure designed to generate candidate gene combinations of a given size. Cross-validation is used to provide replication stability of the search procedure. A permutation two-sample test is used for significance testing. We design a multiple testing procedure to control the family-wise error rate (FWER) when selecting significant combinations of genes that result from a successive selection procedure. A target set of genes is composed of all significant combinations selected via random search. Conclusions A new algorithm has been developed to identify differentially expressed gene combinations. The performance of the proposed search-and-testing procedure has been evaluated by computer simulations and analysis of replicated Affymetrix gene array data on age-related changes in gene expression in the inner ear of CBA mice.

Background The set of microarray expression data on p distinct genes is represented by a random vector X = X 1 ,..., X p with stochastically dependent components. The dimension of X is typically very high relative to the number of observations (replicates of experiment). The standard practice is to test the hypothesis of no differential expression for each gene. Formulated in terms of the marginal distributions of all components of X , this hypothesis means that the expression levels of a particular gene are identically distributed under two (or more) experimental conditions. It is commonly believed that the only challenging problem here is that of multiple statistical tests, because the corresponding test statistics computed for different genes are stochastically dependent. This problem is discussed in [ 2 ] in the context of microarray data analysis. Resampling techniques [ 3 , 4 ] provide a universal approach to the problem of multiple dependent tests inherent in the most typical study designs. However, there is another aspect of the standard approach that warrants special attention. Any test constructed solely in terms of marginal distributions of gene expression levels disregards the multidimensional (dependence) information hidden in gene interactions, which is its most obvious deficiency. In a recent paper, Szabo et al. [ 5 ] proposed to build a target set of interesting genes from non-overlapping subsets of genes of a given size (≥1) that have been declared differentially expressed in accordance with a pertinent statistical test. The size of each sought-for subset is naturally constrained by the available sample size. This approach strives to preserve the dependence structure at least within each of such building blocks, which is already a major step toward a more general methodology of microarray gene expression data analysis. No matter what specific statistical techniques are chosen to approach the problem of identifying differentially expressed gene combinations rather than individual genes, the hypothesis that the expression levels of a given set of genes are identically distributed across the conditions under study is the most meaningful hypothesis to be tested. However, this hypothesis is now formulated in terms of the joint distribution of expression levels. The issue of multiple testing is dramatically magnified with multivariate methodology, because the total number of tests to be carried out at all steps of multivariate selection may be many orders of magnitude larger than with univariate methods. A constructive idea is to design a random search procedure for identifying differentially expressed sets of genes followed by testing significance of a final set. Szabo et al. [ 5 , 6 ] proposed a search procedure based on maximization of a new distance between multivariate distributions of gene expression signals. They used permutation techniques for hypotheses testing. To adjust for multiple testing, the null-distribution was estimated from the test statistics generated by each optimal (in terms of the adopted distance) set of genes found in each permutation sample. The authors provided an illustrative example of clear advantages of multivariate methodology over univariate approaches. In the present paper, we improve the cross-validation and multiple testing components of the earlier proposed algorithm. This new combination of the search-and-testing procedures furnishes a sound statistical methodology for multivariate analysis of microarray data. Results Mathematical framework: measure of differential expression To compare gene expression signals in two different experimental conditions (states) one needs a pertinent distance between two random vectors. Such a distance is expected to satisfy the following requirements: (1) it should have a clear probabilistic meaning; (2) it should accommodate both continuous and categorical data; (3) its estimate should be stable to random fluctuations and numerical errors; (4) its computation should not be too time consuming. A distance that meets all the above requirements was proposed in [ 6 ]. Let X = X 1 ,..., X d and Y = Y 1 ,..., Y d , d ≤ p , be two random sub-vectors with probability measures μ and ν , respectively, defined on the Euclidean space R d . Let K ( x , y ) be a strictly negative definite kernel, that is for any x 1 ,..., x s from R d and any real numbers h 1 ,..., h s , , with equality if and only if all h i = 0. Introduce the following expression The quantity N ( μ , ν ) can be shown [ 7 ] to be a metric in the space of all probability measures R d , so that the null hypothesis in two-sample comparisons can be formulated as H 0 : N ( μ , ν ) = 0. A normalized version of N can be derived as , where If K ( x , y ) = Ψ( x - y ) and Ψ(·) is homogeneous of any order, then N norm is both location and scale invariant. Consider two independent samples, consisting of n 1 and n 2 observations respectively, represented by the d -dimensional vectors and , and introduce an empirical counterpart (nonparametric estimate) of N ( μ , ν ) as follows A very important advantage of the empirical counterpart of the distance N is that it does not involve numerically unstable high-dimensional components (such as covariance matrix or its inverse), thus it is expected to be numerically stable even for small sample sizes. This was corroborated by a computer simulation study [ 5 ], in which this distance demonstrated a much higher stability than the Mahalanobis distance and the nearest neighbor classifier. Another distinct advantage of the approach based on is a wide selection of negative definite kernels that are sensitive to various departures from the hypothesis: μ = ν . Let x and y denote observations in two samples on a particular set of variables. We consider either of these observations to be points in Euclidean space R d . One natural choice is the Euclidean distance between points representing experimental measurements: When this kernel is applied to logarithms of gene expression signals the corresponding distance is scale invariant. Another possible choice is a bounded kernel exemplified by Yet another kernel based on the correlation coefficient tends to pick up sets of genes with separated means and differences in correlation in the two samples under comparison [ 6 ]. One can also use a convex combination of the above mentioned kernels with the weights chosen in such a way as to make the distance more sensitive to particular types of the alternative hypothesis. The search-and-testing algorithm Once a multivariate distance between expression signals has been selected, it can be employed in a search for differentially expressed genes with the target subset of genes being defined as a subset for which the distance between the two groups under comparison attains its maximum. Unlike univariate testing, an exhaustive multivariate search is computationally prohibitive because the number of possible subsets increases as the d -th power of the total number of genes. The issue of computational complexity can be resolved by applying random search methodology. Random search can be designed in a number of various ways. One simple algorithm was described in [ 6 , 8 ]. We used this algorithm, hereafter designated as Simple Random Search (SRS), with multiple random starts and long sequences of search steps in the application reported in the present paper. We also compared its performance with that of simulated annealing [ 1 ]. To reduce the selection bias associated with choosing a small number of variables from a large set [ 9 ], Szabo et al. [ 5 , 6 ] suggested to use cross-validation techniques with the search for a target subset of genes running in each cross-validation cycle. The basic structure of our cross-validation algorithm is as follows: Algorithm A1: Cross-validated search for differentially expressed genes 1. Randomly draw (without replacement) u 1 samples from one group of arrays and u 2 samples from the other group. 2. Leave out the selected arrays and find the optimal (in accordance with the chosen criterion) subset of genes using only the data from the remaining arrays. 3. Repeat steps 1 and 2 in succession v times to obtain v "optimal" sets of genes. The main problem here is that the algorithm results in many overlapping sub-optimal sets, and one needs to somehow combine them to report a single final set. Szabo et al. resorted to a somewhat unnatural way of forming a final set by selecting single genes with the highest frequencies of occurrence in sub-optimal sets. In our new algorithm, this is accomplished through designing a second-stage cross-validated search limited to the union of the previously selected sets. In the second-stage search procedure, cross-validation is carried out at each step of random search with the distance averaged over all cross-validation samples. With this approach, the correlation structure is better preserved when combining the results of cross-validation. The foregoing description of the second-stage search may be summarized in the following algorithm: Algorithm A2: The second-stage cross-validated random search 1. Form the union of all sets resulted from Algorithm A1 to represent an initial target set. Drop the data on all other genes from the data set. 2. Initiate a random search algorithm. 3. At each step of the search algorithm, randomly draw (without replacement) l 1 samples from one group of arrays and l 2 samples from the other group. Leave out the selected arrays and compute the N -statistic using only the data from the remaining arrays. Perform this computation r times. 4. Compute the average (arithmetic mean) of the N -statistics resulted from step 3. Denote this average by . 5. Move to the next step of random search using the statistic as a pertinent objective function to be maximized. In the application discussed in the present paper, we used Algorithm A2 with 200 cross-validated samples in the second stage of the search algorithm. The two-stage search algorithm runs with multiple random starts and returns the most differentially expressed (in terms of the distance ) gene combination of a given size. Once an optimal set has been found, all genes pertaining to this set are discarded and a search for the next set of differentially expressed genes is initiated. Szabo et al. [ 5 ] proposed a stopping rule based on a permutation significance test. In the improved version of our algorithm, instead of testing significance at each step of the successive selection of subsets of genes, the selection procedure runs (without testing) for a preset number of steps, thereby forming a reasonably long sequence of non-overlapping "maximal" subsets. The same cross-validated random search procedure is applied to each permutation sample, generated to model the complete null hypothesis for disjoint subsets of genes, and finally the step-down multiple testing resampling algorithm by Westfall and Young [ 4 ] is applied to the subsets thus selected. If all the null hypotheses happen to be rejected, the selection procedure goes on eliminating subsets of genes resulting from the search algorithm, otherwise the procedure stops. The heuristic procedure thus designed mimics its univariate multiple testing (marginal hypotheses testing) counterpart with known properties [ 4 ], thereby ensuring an approximate control of the family-wise error rate (FWER). Suppose that all tests are two-tailed and utilize the same test statistic , then the following resampling algorithm can be proposed: Algorithm A3: Successive selection of differentially expressed gene combinations 1. Form m permutation samples of sizes n 1 and n 2 , respectively, from n 1 + n 2 replicated observations (arrays). For each of the m permutation samples, run (without testing) the successive selection algorithm to find a preset number I of disjoint sets. At each step of successive selection, an optimal k -element set is identified by the two-stage cross-validated search algorithm and the corresponding m sequences of -values are stored. 2. Returning to the original two-sample setting, find a sequence of I optimal sets of the same size k and compute the respective test statistics for the selected sets. 3. Apply the step-down multiple testing resampling algorithm by Westfall and Young [ 4 ] to the N -statistics resulting from Steps 1 and 2. If the number of rejected hypotheses is less than I then stop and declare all the rejected sets of genes differentially expressed, otherwise return to Step 1 and continue successively selecting sets of genes. A faster version of Step 3 uses the single-step resampling adjustment [ 4 ]. The above algorithm can be reformulated in terms of p -values. The algorithm is computationally more expensive than its prototype presented in [ 5 ]. We used a SunFire V480 station to implement the algorithm. This "brute force" approach is needed to extract more information from multivariate gene expression profiles. With the above approach, no distributional assumptions are needed although the test statistic is not distribution free. For this statistic, however, it can be proven that permutations produce samples from a distribution that is, in some sense, the least favorable for rejecting an underlying composite null hypothesis. In other words, permutations provide an optimal choice of a null distribution. More precisely, this theoretical result is valid for the resampling (with replacement) analog of permutations, but regular (without replacement) permutations may be a good approximation to this resampling procedure if both samples under comparison are not too small. This concept and its mathematical framework is discussed at length in our previous report [ 10 ]. For efficient nonparametric estimation of adjusted p -values associated with sets of genes resulting from random search, it is also desirable that the test statistic be scale invariant for any sample size. A statistic that meets this requirement is an empirical counterpart of the normalized distance N norm with a properly chosen kernel function, see formula (2) and the succeeding explanation. Yet another possibility is to use the kernel K 1 with log-intensities of gene expressions. We employed the latter pivoting structure of the N -statistic in the analysis of simulated and biological data presented in the subsequent sections. Simulation studies We first tested our methodology by computer simulations. To this end, we designed a simulation study as follows. Two sets of data on 1,000 genes were simulated. For convenience we will label them as "control" and "treatment" samples, respectively. The size of each sample was equal to 10. In the treatment group, the first 12 genes were set to be differentially expressed. To simulate these genes, logarithms of gene expression signals were generated from a multivariate normal distribution with an exchangeable correlation structure. The algorithm designed to simulate such data is presented in the Appendix. The correlation coefficient for all pairs of gene log-intensities was set equal to 0.6, while the standard deviation was chosen to be either σ = 0.5 or σ = 1 for all individual genes. The mean log-expression values τ for the genes assigned to the target set of genes were specified as follows: τ = 5 for the first 4 genes (Subset 1), τ = 4 for the second group of 4 genes (Subset 2), τ = 3 for the third group of 4 genes (Subset 3). The remainder of the genes (not differentially expressed) were simulated as log-normally distributed random variables with τ = 1 and the same standard deviation (either σ = 0.5 or σ = 1) and correlation coefficient. The 1,000 genes in the control group were simulated just like those that were not differentially expressed in the treatment group. Our search-and-testing procedure was applied to the data sets thus generated in order to see whether (and how frequently) it can find all subsets, as well as all individual genes, included in the target set of differentially expressed genes. In each experiment, the SRS algorithm was run with multiple random starts. At each step of the successive selection of genes, the algorithm sought for a subset of 4 genes. The parameter I in Algorithm A3 was set equal to 5. Since the sole purpose of our simulations was to check how well a given algorithm finds a maximum of the N -statistic over gene sets, no recourse to cross-validation was made in this study. The number of permutations was set at 200. Because such simulations are very time consuming the experiment was repeated only 100 times. Two samples (control and treatment) were generated in each of the 100 experiments. First we tested the SRS algorithm with 8 random starts and 2,500 search steps. When σ = 0.5 for the treatment group the algorithm was able to correctly recover Subset 1 in 82%, Subset 2 in 72%, and Subset 3 in 76% of simulation runs. The proportion of cases where all 12 genes were correctly recovered (irrespective of the order they entered the selected subsets) was 61%. The false discovery rate, defined as the mean proportion of falsely discovered genes among the true differentially expressed genes, was equal to 0.02. When σ = 1 the SRS algorithm recovers Subset 1 in 76%, Subset 2 in 56%, and Subset 3 in 39% of the simulation runs. The proportion of cases where all 12 genes were correctly recovered was 53%. The false discovery rate was equal to 0.04. As one would expect, the SRS algorithm performed better with 16 random starts and 3,600 search steps. For σ = 0.5, the rate of correct discovery becomes 100% for all three sets. For σ = 1 the algorithm correctly recovers Subset 1 in 81%, Subset 2 in 65%, and Subset 3 in 48% of simulation runs. The proportion of cases where all 12 genes are correctly recovered is 62%. However, the false discovery rate remains essentially the same as when running the SRS algorithm with 8 starts and 2,500 search steps. The results on individual simulated genes are presented in Table 1 . By way of comparison, we ran the Westfall and Young algorithm with a univariate counterpart of the test statistic N at the same level of FWER. While the results for σ = 0.5 were identical (100% correct recovery), the univariate method recovered less genes (45%) in the target set when we set σ = 1. In the latter case, the univariate algorithm had a uniformly lower correct discovery rate for genes #9 through #12 (69%, 71%, 70%, 71%, respectively) in comparison to the multivariate method (Table 1 ). One should not expect much discrepancy between the univariate and multivariate methods in these simulations because the alternative hypotheses were modeled in a univariate way. In another experiment we studied the simulated annealing optimization (SAO) with one random start and the same parameters of the simulation model. Although computationally expensive, the SAO algorithm is easier to handle when tuning its parameters in simulation experiments. Proceeding from the less favorable case of σ = 1, we determined parameters of the SAO algorithm that provide correct selection of all three sets of differentially expressed genes in all simulation runs. Another way of testing the two algorithms is to apply them in a situation where the true global maximum of the N -distance is known. We randomly selected 2000 genes from the data set discussed in the next section. All possible pairs were formed from the 2000 genes and the corresponding N -statistic between the two samples (young versus old mice) was computed for each pair. The data were normalized before the analysis (see Section "Results and Discussion"). Having determined a maximum value of the N -statistic over all pairs, we ran the SRS and SAO algorithms (with parameters suggested by our simulation experiments) to see whether they could find the actual maximum. Both algorithms hit the target. Results The biological purpose of our experimental study was to better understand age-related changes in gene expression that occur in mouse inner ear (including the organ of Corti and stria vascularis). Since we do not expect numerous genes to be involved in the process of aging of the auditory system, this experimental system seems to be especially promising for the use of multivariate methods. Hearing loss or deafness affects about 10% of the U.S. population, or about 30 million people, most of them over age 60. Presbycusis – age-related hearing loss – is a primary sensory problem in the elderly population, the number one communicative disorder, and one of the top three chronic medical conditions affecting the aged. It is often described as difficulty in understanding speech, especially in conditions of high ambient background noise. Most elderly persons have a reduction in hearing acuity. For example, cross-sectional and longitudinal studies have consistently demonstrated gradually decreasing pure tone thresholds by cohort groups of elderly [ 13 , 14 ]. The composite audiometric pattern is one of better hearing for low- and mid-speech frequencies than higher speech frequencies. The consequence of this pattern is difficulty in hearing and understanding, not only conversational speech, but in particular, speech that is softly spoken. In fact, a similar gradual reduction in speech recognition for words and phonemes in quiet has been shown to accompany the pure tone threshold decrease in cohort groups of the elderly [ 14 - 16 ]. Much progress had been made in the field of auditory aging research regarding sensitivity deficits and metabolic problems of the cochlea. As humans and animals age, they lose sensory hair cells, 8th cranial nerve (i.e., vestibulocochlear) fibers, and develop stria vascularis/potassium recycling metabolic problems that degrade audibility and spectral tuning [ 17 - 21 ]. In addition, the differing roles of the ear and brain in presbycusis, and aging deficits in speech understanding in background noise, and their respective neural bases are beginning to be understood. Age effects in these areas are distinguishable and age-related problems in the brain can be influenced by the peripheral etiologies of presbycusis [ 22 - 24 ]. Considering studies completed to date, presbycusis in humans, and corresponding age-related hearing loss in animal models such as the CBA mouse, have two major facets: 1) A peripheral hearing loss of cochlear origin, starting with sensitivity losses in the high pitches (high frequencies), involving loss of sensory hair cells, spiral ganglion neurons (8th nerve fibers) and metabolic malfunctions of the highly vascularized stria vascularis organ system that produces the potassium rich endolymph of the inner ear [ 25 , 26 ]; and 2) An inability to comprehend speech in background noise, that results from deficits in the inner ear and the central auditory nervous system [ 23 , 24 ]. For the animal model studies of presbycusis, the CBA mouse strain has been quite useful to date. The goal of the present study is to explore the underlying cochlear gene expression changes that may predispose or cause presbycusis. Common neurodegenerative diseases such as presbycusis are likely to be caused by several fundamental problems that interact with each other and with environmental factors, including genetic pre-dispositions to environmental insults, noise and ototoxic medications [ 27 ]. Although over a hundred genes have been identified that cause congenital deafness (e.g. [ 28 - 30 ]), no candidate genes have yet been identified that are involved in human presbycusis. The present report attempts to gain some initial insights into gene expression changes related to inner ear problems that may predispose or cause age-related neurosensory disorders, such as age-related hearing loss – presbycusis, utilizing the CBA mouse strain. The two groups of arrays under comparison included 9 and 12 arrays, respectively (see the next section). The data were normalized using the quantile normalization method [ 11 , 12 ] carried out at the probe feature level. Compared to our simulations, the number of permutations was increased to 400. Each search cycle in the SRS algorithm proceeded in 45,000 steps with 100 random starts. The algorithm was tuned to search for a set of 5 genes at each step of the successive selection procedure. We also changed parameters that control the efficiency of the SAO algorithm to account for an increased dimensionality of the problem. The latter algorithm also sought for sets consisting of 5 genes. We used the following parameter values in the combined two-stage cross-validated search algorithm: I = 5, u 1 = 4 (out of 9 arrays), u 2 = 6 (out of 12 arrays), v = 10, l 1 = 4 (out of 9 arrays), l 2 = 6 (out of 12 arrays), r = 200. Although the lists of genes produced by both algorithms are quite similar, there are still some discrepancies between them which may be attributed to the choice of parameters for each method. Since the SAO algorithm is less sensitive to the choice of the initial gene combination, we present only the results obtained with this algorithm. In the "young" versus "old" comparison, the procedure selected two sets of 5 genes with an adjusted p -value of less than 0.05. For comparison, we applied the Wesfall and Young step-down multiple testing procedure with a univariate counterpart of as the test statistic. This method selects only 6 genes at the same FWER; all of them appear among those genes that have been selected by the multivariate search-and-testing procedure. The final list of 10 genes was evaluated further for consistency with the existing biological knowledge. Discussion Of the 10 identified genes (from 2 sets) exhibiting major expression changes with age, there are 6 differentially expressed genes having to do with immune system function. This is important from an aging point of view for two reasons. First, immunoprecipitations or immunoproducts can be damaging to nerve cells, and have been implicated as being responsible for age-related neurodegeneration in the brain in general, and in Alzheimer's disease specifically, but this is a new finding for the cochlea and age-related hearing loss – presbycusis. Second, autoimmune problems, where the immune system starts attacking its own nerve cells, is another leading candidate for a causative factor in neurodegenerative aging conditions. These immune products are likely to come from the vascular supply to the cochlea, yet may be a causative component for age-related hearing loss due to the resultant damage to the cochlea sensory cells. There are 3 genes having to do with post-translational protein changes, including protein binding properties, with two of these genes involved in carbohydrate metabolism (sugar/glucose binding in mitochondria for cellular respiration). These genes are related to the production of reactive oxygen species (ROS), which damage nerve cells, and have been implicated in age-related neurodegenerative disorders, and in cases of cochlear sensorineural hearing loss. For example, problems in cellular respiration can lead to accumulation of toxic intracellular substances, causing damage to sensory cell structures and abnormal metabolic processing along with increased levels of ROS [ 31 - 33 ]. The last gene, involved in mammary gland functioning, showed a significant increase with age. A closer inspection of the expression levels for this gene have shown that the observed effect cannot be attributed to the presence of outliers in the data. Although not directly involved in sensory functioning, this gene may change its espression as part of general degenerative processes in inner ear. An error in this gene annotation cannot be ruled out as well. This observation is definitely worth another look. The above-described initial observations are quite provocative, in that we have several groupings of genes that have important functional significance for aging and hearing, including important aspects of cochlear, inner ear functioning. These animal-model gene-array investigations are quite useful for guiding human genetics experiments aimed at identifying candidate genes involved in the susceptibility and progression of human age-related hearing loss and other age-dependent neurosensory disorders. Regarding methodological aspects of this paper, we would like to note that a pertinent multivariate method for selection of differentially expressed genes should include two components: finding subsets of candidate genes that jointly separate the classes (states) under comparison and testing statistical significance of this separation; the latter does not necessarily refer to characteristics of a classification (allocation) rule such as classification error rates. We also would like to stress that the problem of significance testing in the multivariate formulation is not equivalent to the problem of statistical classification (supervised learning). While closely related, these problems are fundamentally different. For example, the use of the classification error rate as a criterion for selection of important variables is appropriate where the aim is to form a discriminant rule for the subsequent outright allocation of unclassified samples to one of the known classes. A very good separation between classes can sometimes be provided by looking at a single feature variable (gene) so that the classification error rate is difficult to reduce further by including other (probably quite significant) variables in the rule. However, one would like to keep the chance of missing other interesting variables to a minimum. The problem dealt with in this paper is not that of classification or prediction. Our method is designed to find gene combinations that change in concert (as a set) their expression due to some biological factors. The problem thus formulated reduces to that of significance testing. It must be emphasized that our method is designed not only to identify sets of genes whose interrelationships differ but also those genes with marginal effects. More importantly, the method seeks to provide an alternative way of making a specific FWER-based multiple testing procedure less conservative and, to some extent, less dependent on the subset pivotality requirement (see [ 4 ] for definition), by extracting more information from the data. In addition, this approach can be used for ranking and clustering those genes that have been declared differentially expressed by univariate methods. Conclusions A new algorithm for identifying differentially expressed gene combinations has been developed. This algorithm is built on the earlier proposed multivariate test statistic [ 6 ] and successive selection of differentially expressed sets of genes [ 5 ]. The algorithm includes an improved random search procedure designed to generate candidate gene combinations of a given size. Cross-validation is used to provide replication stability of the search procedure. A permutation two-sample test is used for significance testing. We design a multiple testing procedure to control the family-wise error rate when selecting significant combinations of genes that result from a successive selection procedure. A target set of genes is composed of all significant combinations selected via random search. The performance of the proposed search-and-testing procedure has been evaluated by computer simulations and analysis of replicated Affymetrix gene array data on age-related changes in gene expression in the inner ear of CBA mice. Methods Subjects CBA mice from the University of Rochester vivarium served as subjects for this study who had similar environmental, non-ototoxic life histories. Subjects were mice of the following age groups: Young adult (N = 9, 3–4 months) and old (N = 12, 24–33 months). All animal procedures were approved the University of Rochester Committee on Animal Resources. Cochlear dissections Subject groups of the present report had extensive behavioral and neurophysiological hearing testing prior to sacrifice, verifying that the old mice had age-related hearing loss. Mice were sacrificed by cervical dislocation. Then both cochleae for each mouse were immediately dissected using a Zeiss stereomicroscope. The cochleae were placed in cold saline for micro dissection of the cochlear partition (basilar membrane, organ of Corti and spiral ligament), and were then placed in cold Trizol. A detailed protocol for Trizol can be found at . All samples were stored at -80°C for microarray gene expression processing. Gene expression microarrays The RNA quality was assessed by electrophoresis using the Agilent Bioanalyzer 2100. Between 200 ng and 2 ug of total RNA from each sample was used to generate a high fidelity cDNA, which was modified at the 3' end to contain an initiation site for T7 RNA polymerase, while 1 ug of cDNA was used in an in vitro transcription (IVT). 20 ug of full-length cRNA, from each mouse (age groups as described above), was fragmented. After fragmentation, the cDNA, full-length cRNA, and fragmented cRNA were analyzed by electrophoresis using the Agilent Bioanalyzer 2100 to assess the appropriate size distribution prior to microarray hybridization. Detailed protocols for sample preparation using the Ambion MessageAmp protocol can be found at . Affymetrix M430A High density oligonucleotide array set (A) which queried 20,000 murine probe sets was used. Each gene on the subarray is represented by 11 pairs of 25 mer oligonucleotides that span the coding region for the 20,000 genes and ESTs represented (clear overlapping of genes is evident). Each probe pair consists of a perfect match (PM) sequence that is complementary to the cDNA target, and a miss-match (MM) sequence that has a single base pair mutation in a region critical for target hybridization; this sequence serves as a control for non-specific hybridization. Staining and washing of all arrays was performed in the Affymetrix fluidics module per manufacturer's protocol. Streptavidin phycroerythrin stain (SAPE, Molecular Probes) was the fluorescent conjugate used to detect hybridized target sequences. All arrays in this study were assessed for "array performance" prior to data analysis. Methods for data analysis and computer simulations The methodology of data analysis and design of computer simulations have been described at length in the preceding sections. The relevant software for data analysis and simulations is included in the Additional Material Files [see the folder "MultivariateSearch"]. Here we supplement this information with a description of the generator of multivariate exchangeable normal random vectors which we used in our simulations. Suppose we want to generate a normal random vector X in R d with mean vector M ∈ R d and covariance matrix Σ whose entries are σ 2 and ρσ 2 on and off diagonal, respectively. It is well-known that X can be represented in the form X = M + CZ , where Z is the standard normal vector with mean 0 in R d and C is a d × d matrix with CC T = Σ. (Here C T denotes the transpose of C .) The matrix C may be chosen symmetric and can be computed using well-known algebraic procedures. However, our matrix Σ has a special structure: Σ = (1 - ρ ) σ 2 I d + ρσ 2 1 d × d , where I d is a unit matrix of size d and 1 d × d is a square matrix with all the d 2 entries being equal to 1. Using this we look for C of the same form: C = α I d + β 1 d × d . From the relations C 2 = Σ and we have α 2 = σ 2 (1 - ρ ), 2 αβ = ρσ 2 , so that Authors' contributions YX is responsible for the computational component of this study. He also participated in the methodology development. LK, AG, and AY have equally contributed to various methodological aspects of the proposed multivariate analysis. RF provided experimental data and biological interpretation of the net results of data analysis. Supplementary Material Additional File 1 The additional folder "MultivariateSearch" includes the following three sub-folders: 1. SAO _Simulation 2. SRS_Simulation 3. TSSearch Each subfolder contains a Unix executable file. The executable file "SASearch" implements the algorithm based on simulated annealing optimization. The executable file "SRSearch" implement the version based on simple random search. The exectuable file "TSSearch" for the two-stage search is is located in the sub-folder "TSSearch". Each sub-folder also contains two input files. The file "simulation04_UI.txt" is an input file for data analysis. Suppose the data file is named xxxx.marr, then the input file should be named as xxxx_UI.txt. To analyze the data from the file xxxx.marr, type: [Executable file] xxxx or [Executable file] 0 xxxx. The input file "simulation04_ui.txt" is designed for simulation experiments. To conduct simulations, one has to prepare an input file with the name: XXX_simu_ui.txt, where XXX is a string that follows the naming convention of computer files. An input file for data analysis with the name XXX_ui.txt is also needed. To run simulations, type: [executable file] 1 xxxx. Click here for file

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Association of house spraying with suppressed levels of drug resistance in Zimbabwe

Background Public health strategies are needed to curb antimalarial drug resistance. Theoretical argument points to an association between malaria transmission and drug resistance although field evidence remains limited. Field observations, made in Zimbabwe, on the relationship between transmission and multigenic drug resistance, typified by chloroquine, are reported here. Methods Periodic assessments of the therapeutic response of uncomplicated falciparum malaria to chloroquine in two selectively sprayed or unsprayed health centre catchments, from 1995 – 2003. Cross-sectional analysis of in vivo chloroquine failure events for five sites in relation to natural endemicity and spraying history. Results During selective house spraying, the chloroquine failure rate for the sprayed catchment decreased, such that, after four years, the odds of chloroquine failure were 4× lower than before start of spraying in the area (OR 0.2, 95% CI 0.07 – 0.75, p = 0.010, n = 100). Chloroquine failure odds for the sprayed area became 4× lower than contemporaneous failure odds for the unsprayed area (OR 0.2 95% CI 0.08 – 0.65, p = 0.003, n = 156), although the likelihood of failure was not significantly different for the two catchments before selective spraying started (OR 0.5, 95% CI 0.21 – 1.32; p = 0.170, n = 88). When spraying ended, in 1999, the drug failure odds for the former sprayed area increased back 4 fold by 2003 (OR 4.2, 95%CI 1.49 – 11.78, p = 0.004, n = 146). High altitude areas with naturally lower transmission exhibited a 6× lower likelihood of drug failure than low-lying areas (OR 0.16 95% CI 0.068 – 0.353, -2 log likelihood change 23.239, p < 0.001, n = 465). Compared to sites under ongoing annual spraying, areas that were last sprayed 3–7 years ago experienced a 4-fold higher probability of chloroquine failure (OR 4.1, 95%CI 1.84 – 9.14, -2 log likelihood change 13.956, p < 0.001). Conclusion Reduced transmission is associated with suppressed levels of resistance to chloroquine and presumably other regimens with multigenic drug resistance. It seems the adoption of transmission control alongside combination chemotherapy is a potent strategy for the future containment of drug-resistant malaria.

Background The escalation of parasite drug resistance has persisted as a major obstacle to malaria control for decades [ 1 - 3 ]. Owing to dwindling options for affordable, safe and effective drugs, rising clinical failure rates exact a substantial public health toll, especially in Africa [ 4 , 5 ]. In countries that recently replaced chloroquine with sulfadoxine/pyrimethamine as first line treatment, there are signs of increasing resistance to the antifolate combination [ 1 , 2 , 6 - 9 ]. Partly because of the spectre of drug resistance, pharmaceutical companies reduced investment in new antimalarial drug research. Fortunately, official calls in the mid 1990's led to renewed public-private sector initiatives for the development of new compounds, as well as the improvement of existing ones [ 10 , 11 ]. However, Plasmodium falciparum has repeatedly demonstrated the ability to develop resistance to practically any drug upon wider introduction, as illustrated by multi-drug resistance, especially in South East Asia [ 12 - 15 ]. Thus, public health strategies that delay or minimize the escalation of drug resistance are urgently required. To date, the only approach that has been widely evaluated and is currently being introduced is the use of combination chemotherapy [ 11 , 16 , 17 ] which protects constituent drugs from resistance through a multigenic mechanism of resistance and strategic pharmacological properties such as short half-life. In poor countries the effectiveness of this method is hampered by increased cost of medication. Furthermore, even the new combinations are not totally protected from the development of resistance, as illustrated by the recent confirmations of clinical failure and in vitro resistance to proguanil/atovaquone [ 18 - 22 ]. Additional strategies are, therefore, needed to ensure the successful containment of drug-resistant malaria. Mathematical models have been proposed suggesting a relationship between malaria transmission and the evolution of drug resistance, though some workers suggest a positive association [ 23 , 24 ] while others propose a negative one [ 25 , 26 ]. Major implications for control pertain to this question. It may mean that vector control programmes are counterproductive by aggravating drug resistance, or, it could be that they complement chemotherapy by alleviating resistance. Although this interaction between transmission and drug resistance is further addressed in a review [ 27 ], the exact answer still remains uncertain against a background of limited field evidence. The present paper presents observations on the field relationship between transmission variations (both natural and vector control induced) and the levels of in vivo multigenic drug resistance, typified by chloroquine. Methods Study areas and population Zimbabwe, on the southern fringes of malaria in Africa, experiences seasonal and potentially epidemic transmission characterized by a non-immune population with high probability of drug treatment [ 28 - 30 ]. The country has sustained a national malaria vector control programme for decades, based on intradomicilliary application of residual insecticide. From the early 1990s selective vector control was introduced, in which areas with moderate transmission are of less priority and spraying is focused in zones of high transmission/high malarial incidence. Chloroquine has remained the first line treatment for uncomplicated malaria, although a combination of chloroquine and sulfadoxine/pyrimethmanine is currently being introduced in some areas. A tiered drug distribution policy has been implemented in the country, so that, until 1997, chloroquine was the only antimalarial available at the peripheral level. Thereafter, policy revisions allowed wider distribution of sulfadoxine/pyrimethamine to treat chloroquine failure cases. The study was based at five health centres located in the low-lying (<600 m above sea level) hyperendemic transmission zone as well as those in the higher altitude (600 – 1200 m asl) mesoendemic transmission zone bordering the malaria-free central watershed (Table 1 , Fig 1 ). All the study locations experience seasonal, single peak (February-May) malaria transmission typical for Zimbabwe. Acute symptoms and complications occur across all ages in this non-immune population, where asymptomatic carriage of asexual parasitaemia is rare [ 28 , 29 ]. The study was conducted on uncomplicated falciparum malaria cases of all age groups presenting at the health centres for treatment. Table 1 Study area characteristics Site Elevation Endemicity *Population Estimate Villages of patient origin Spraying status Treatment drug Burma Valley 683 m mesoendemic 11764 25 Last sprayed 1999 CQ+S/P since 2001 Chitakatira 1211 m mesoendemic 13245 28 Last sprayed 1998 CQ+S/P since 2003 Sahumani 784 m mesoendemic 5950 24 Last sprayed 1992 CQ+S/P since 2003 Madhuku 471 m hyperendemic 11583 39 Ongoing CQ+S/P since 2001 Mola ≈500 m hyperendemic 13000 28 Ongoing CQ+SP since 2001 *2002–2003 population census. Figure 1 Location of study sites, shown in relation to altitudinal zones that govern malaria endemicity. Central watershed (elevation > 1200 m above sea level) experiences nil – hypoendemic malaria transmission, and endemicity increases with falling altitude towards the north and south of the country. Study design The study was a prospective assessment of the therapeutic response of P. falciparum malaria to chloroquine from 1995–2003. Consecutive assessments of therapeutic response were conducted in two mesoendemic sites during the presence or absence of selective indoor residual insecticide spraying (house spraying). Transverse assays for Pfmdr1 and Pfcrt mutations associated with chloroquine resistance were carried out in these two sites during the 1998–99 transmission season. Further assessments of in vivo chloroquine therapeutic response were carried out cross-sectionally in another three sites where treatment change to chloroquine (CQ) + sulfadoxine/pyrimethamine (SP) was not yet being implemented due to temporary unavailability of SP. Malarial incidence was determined retrospectively for all sites using available health centre records. In vivo antimalarial therapeutic efficacy assessments The in vivo therapeutic efficacy of chloroquine was assessed using the standard WHO (1996) protocol [ 31 ]. Since this protocol was primarily targeted for regions of intense malaria transmission, two modifications were adopted to suit the seasonal/epidemic conditions of Zimbabwe. These were (i) inclusion of febrile patients of all age groups and (ii) adoption of radical asexual parasite elimination as a criterion for adequate response to treatment. Inclusion of all age groups was on the rationale that there is no premunition in the population. Recruited patients were thus a representative sample of the symptomatic population which presents for treatment with chloroquine in the primary health care system. The radical asexual parasite elimination criterion was adopted because persistent asexual parasitaemia poses a risk of complications in non-immunes. Molecular detection of Pfmdr1 and Pfcrt polymorphisms Amino acid polymorphisms at codons 86 and 1246 of the P. falciparum Pfmdr 1 gene and at codon 76 of the P. falciparum chloroquine resistance transporter gene ( Pfcrt ), which are associated with chloroquine resistance [ 32 , 33 ], were detected by PCR and codon-specific restriction enzyme digestion [ 34 , 35 ]. Appropriate positive and negative control strains were used in interpretation and, except for the Pfcrt codon, additional restriction sites were included in the target PCR product to serve as internal controls for complete digestion. Ethics The study was approved by respective provincial medical health authorities and by the Medical Research Council of Zimbabwe. Patient participation was by the informed consent of the patients themselves or guardians, in the case of children. Results Association of house-spraying with reduced levels of chloroquine resistance (i) Burma Valley and Sahumani follow-up study On the grounds of low malarial incidence, the catchments of Sahumani clinic, in Mutasa district and Burma Valley clinic, in Mutare district (Fig 1 ), were removed from the spraying programme in 1992, with the advent of selective control to save on inseciticide. However, the Burma catchment, which is situated on commercial farms, was re-allocated to annual spraying from 1995 – 1999 when, for economic reasons, local farmers agreed to supply the malaria control authorities with insecticide. The Burma catchment subsequently reverted to no spraying after the 1999 spraying operation, due to disagreements between commercial farmers and the government. In contrast, the Sahumani catchment, which is located in villages, remained unsprayed from 1992. There were no malaria statistics for the two health centres prior to 1998, (1997 for Sahumani). However, during the selective annual spraying, the risk of contracting malaria in the sprayed Burma Valley catchment was at least 2.6 fold lower than for Sahumani (Fig 2 ) from 1998 – 2000. After the selective spraying operation ended in 1999, the malarial incidence became uniform for the two catchments by 2001 (Fig 2 ). Figure 2 Monthly malarial incidence in Burma valley (BV) and Sahumani (SH) catchments during and after selective spraying (boxed terms, Risk Ratios (95% CI) for peak malaria transmission period (February – May)). The therapeutic failure rate of Burma Valley decreased during selective spraying (Table 2 ) such that by 1999, the odds of chloroquine failure were 4× lower than they were before spraying resumed in this area (OR (95% CI) 0.233 (0.072 – 0.747), for 1999 compared to 1995; 0.482 (0.270 – 0.861), for each year of spraying: -2 log likelihood ratio change 6.432, df = 1, p = 0.011). Therapeutic failure rates were not significantly different in the Burma Valley and Sahumani catchments (1995 season) prior to selective spraying of Burma Valley (Table 2 ). However, by 1999 the odds of drug failure had become 4× lower in the annually sprayed Burma catchment (Table 2 ). The failure rate in Sahumani did not significantly change during the 4-year period (OR (95%CI): 0.62 (0.25 – 1.57), for 1998 compared to 1995; 0.53 (0.26 – 1.08) for 1999 compared to 1995; 0.85 (0.71 – 1.02) for each successive year, -2 × log likelihood ratio change, 3.080, df, 1, p = 0.0793). Table 2 Chloroquine therapeutic failure (TF) rates in Sahumani and Burma Valley from 1995–2003. Therapeutic failure rate (n) 1995 1997/98* 1999 2003 Burma Valley 27.0% (37) 15.2% (33) 7.9% (93) 26.5% (83) Sahumani 41.2% (51) 30.3% (33) 26.9% (65) - Odds ratio (95% CI) 1.89 (0.76 – 4.72) 2.4 (0.73 – 8.14) 4.3 (1.54 – 11.85) - P 0.170 0.142 0.003 - *Burma Valley 1997 compared to Sahumani 1998. After selective spraying ceased in 1999, the odds of drug failure in Burma valley increased back 4-fold by 2003 (OR (95%): 4.18 (1.485 – 11.782), p = 0.004, n = 146) Chloroquine efficacy assessments for 2003 were not conducted in Sahumani as the treatment was changed that year to chloroquine plus sulfadoxine/pyrimethamine. (ii) In vivo prevalence of mutations in Pfmdr1 and Pfcrt genes Amino acid polymorphisms on Pfmdr 1 and Pfcrt codons associated with chloroquine resistance were examined in pre-treatment patient samples from 1998 and 1999 in Burma Valley and Sahumani (i.e. 3–4 years after re-start of spraying in Burma Valley). Resistance-associated mutations at amino acid codons 86 and 1246 of Pfmdr 1, and codon 76 of Pfcrt , were more prevalent in the Sahumani area (Table 3 , Fig 3 ). Interestingly, mixed infections containing both mutant and wild type variants tended to be more frequent in the Burma Valley area (Fig 3 ), despite lower transmission in this catchment. The same distribution pattern observed with individual codons was mirrored in mutated haplotypes comprising two or more amino acid codons (Table 3 ). Three-codon haplotypes from the sprayed area exhibited significantly more mixed mutant and wild variants at one or more codons than corresponding haplotypes from the unsprayed area (odds ratio 5.4, 95 % CI: 1.89 – 15.54, p = 0.001, n = 131). Table 3 Relative abundance of mutated P. falciparum genotypes in Sahumani and Burma Valley (1998 and 1999 transmission seasons). Mutant genotype OR (95%CI) of mutants (Sahumani : Burma Valley) P N Pfmdr1 Tyr-86 2.4 (1.2 – 4.7) 0.013 137 Pfmdr1 Tyr-1246 4.2 (1.7 – 10.7) 0.001 135 Pfcrt Thr-76 2.2 (1.1 – 4.6) 0.028 144 Pfmdr1 Tyr-86 + Pfmdr1 Tyr-1246 3.9 (1.5 – 10.1) 0.003 132 Pfmdr1 Tyr-86 + Pfmdr1 Tyr-1246 + Pfcrt Thr-76 4.0 (1.6 – 10.3) 0.002 131 Figure 3 Distribution of mutated (m) and wild (w) P. falciparum variants in Burma Valley (BV) and Sahumani (SH), at Pfmdr1 codons 86 (Pfmdr-86) and 1246 (Pfmdr-1246), and Pfcrt codon 76 (Pfcrt-76). Drug failure as a function of transmission A scatterplot of chloroquine therapeutic failure rate with malarial incidence suggested a positive association (Fig 4 ). In stead of using parametric tests on arcsine transformed data (perhaps better done with more data points), the probability of chloroquine failure was examined as a function of transmission zone, and spraying history, using a logistic model. The health centre catchments naturally falling in the mesoendemic zone according to altitudinal classifications [ 28 ], did exhibit significantly lower malarial incidence, for at least the previous 10 years, than those in the hyperendemic zone (Fig 5 , Table 4 ). In the logistic regression, the probability of therapeutic failure was 6.4-fold lower in these mesoendemic catchments than in hyperendemic ones (Table 5 , 6 , 7 ). At any time point, catchments that were under ongoing annual spraying experienced 4-fold lower likelihood of drug failure than those that were last sprayed 3–7 years ago (Table 5 ). Figure 4 Scatter plot of therapeutic failure prevalence with malarial incidence. Figure 5 Monthly malarial incidence per thousand population in hyperendemic (hyper) and mesoendemic (meso) catchments. Table 4 Risk of clinically diagnosed malaria in hyperendemic and mesoendemic catchments during the peak malaria season (February – May). Year 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 Hyperendemic population (elev. <600 m) 21306 21925 22643 34298 35733 27647 25578 22651 27174 27989 Mesoendemic population (elev. ≥600 m) 65664 66497 69788 75761 88181 90910 93721 48244 96057 61625 Malarial RR (95% CI) 1.9 (1.72 – 1.99) 1.7 (1.57 – 1.81) 5.3 (5.09 – 5.55) 2.8 (2.67 – 2.88) 1.1 (1.09 – 1.17) 5.0 (4.82 – 5.12) 2.0 (1.89 – 2.04) 2.7 (2.56 – 2.75) 1.6 (1.55 – 1.69) 3.3 (3.06 – 3.48) P <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Table 5 The probability of chloroquine therapeutic failure as a function of transmission level and spraying history : Independent variable coding Parameter coding (1) (2) (3) (4) Study year 2003 1.000 .000 .000 .000 1999 .000 1.000 .000 .000 1998 .000 .000 1.000 .000 1997 .000 .000 .000 1.000 1995 .000 .000 .000 .000 Last annual spraying 3+ yrs ago 1.000 0 yrs/ongoing .000 Transmission level mesoendemic 1.000 hyperendemic .000 Table 6 The probability of chloroquine therapeutic failiure as a function of transmission level and spraying history: variables in the equation B S.E. Wald df Sig. *Exp(B) 95.0% C.I. for EXP(B) Lower Upper Step 1(a) Transmission level (1) -1.863 0.419 19.780 1 0.000 0.155 0.068 0.353 Last annual spraying (1) 1.411 0.409 11.879 1 0.001 4.099 1.838 9.142 Study year 13.037 4 0.011 Study year (1) -0.728 0.290 6.317 1 0.012 0.483 0.274 0.852 Study year (2) -0.400 0.317 1.589 1 0.207 0.671 0.360 1.248 Study year (3) -0.224 0.440 0.259 1 0.611 0.799 0.338 1.892 Study year (4) 0.262 0.445 0.346 1 0.556 1.299 0.543 3.109 Constant -0.157 0.407 0.149 1 0.700 0.855 a Variable(s) entered on step 1: Transmission, Last annual spraying, Study year. * corresponds to odds ratio for therapeutic failure Table 7 The probability of chloroquine therapeutic failiure as a function of transmission level and spraying history: Model if term removed Variable Model Log Likelihood Change in -2 Log Likelihood df Sig. of the Change Step 1 Transmission level -331.110 23.239 1 .000 Last annual spraying -326.469 13.956 1 .000 Study year -326.142 13.303 4 .010 Discussion The build up of drug-resistant P. falciparum malaria calls for public health strategies to maximize the useful life of antimalarials. According to the findings of the present study, reduced transmission, due to vector control or high altitude, was associated with suppressed levels of in vivo therapeutic failure and genotypic resistance to chloroquine. Assuming that chloroquine resistance has a multigenic mechanism, as is the general consensus [ 12 , 36 , 37 ], this association between transmission and drug resistance presumably governs other drugs or drug combinations that have polygenically encoded resistance. From the Burma Valley and Sahumani cross-sectional assays, there was, in the sprayed catchment, a higher likelihood of infections carrying mixed mutated and wild type codons, for both Pfcrt and Pfmdr1 , despite the lower transmission. This paradoxical result suggests that the sprayed area probably favoured more genetic out-crossing, resulting in recombination break down of drug-resistant haplotypes. The genetic out-crossing may partly explain the association of low drug resistance with the house spraying. Further studies are needed to verify this relationship in more areas. In Burma Valley, despite drug pressure, the proportion of resistant parasites decreased during spraying, and subsequently resurged after the spraying stopped. This is reminiscent of the decrease in proportion of chloroquine-resistant parasites reported in China [ 38 ], and more recently in Malawi [ 39 , 40 ], following suspension of chloroquine use. From these observations it would seem that chloroquine-resistant parasites bear a fitness cost as drug selection advantage is removed or counteracted. What is distinct about the current results is that the fitness cost for resistance appeared to occur in the sporogonic phase, as distinguished from an in vivo fitness burden that is thought to ensue following cessation of drug use. In the present results, drug selection advantage for the resistant parasites appeared to be directly counteracted by independent survival limiting factors, such as vector control and high altitude. This has important implications for control as it means that drug-resistant P. falciparum can be contained during drug use. Furthermore, costly acquisition of immunity in the resident population is, presumably, not the only prerequisite for curbing drug resistance. The present results afford field evidence supporting the continuation of sustainable malaria vector control programmes. Similar findings were reported for Uganda [ 41 ], although the same workers found a difference between chloroquine (multigenic resistance) and sulfadoxine/pyrimethamine (monogenic resistance) below a critical threshold of transmission [ 37 ]. These papers may further support the findings of the present study. It has been cautioned that resistance might exacerbate as eradication is approached [ 42 ]. However, in the current study, the low transmission levels associated with high altitude and spraying showed no signs of this counterproductive effect. Moreover, in poor countries, which are the de facto stronghold for malaria, eradication so far remains only an academic prospect, as the malaria burden continues to increase [ 43 ]. It seems that the adoption of sustainable transmission control with combination chemotherapy is a potent approach for the future containment of drug-resistant malaria. Conclusions Reduced transmission due to house spraying or high altitude is associated with suppressed levels of phenotypic and genotypic resistance to chloroquine and presumably other multigenically encoded drug regimens. Transmission control implemented with combination chemotherapy seems a potent approach for the future containment of drug-resistant malaria. Authors' contributions SM was the principal investigator responsible for the study design, data collection, analysis and drafting of the manuscript. SLM carried out essential co-ordination of project activities. RM and TC afforded technical input on the manuscript and facilitated field data collection. SKC made vital contributions in original proposal development, seeking of funding, and edited the manuscript. KPD provided crucial inputs in the study design, genetic analysis, general direction and co-ordination of the study and the writing up of the manuscript.

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539241

Review of "System approach to engineering design" by P.H. Sydenham

Based on a semester-long seminar on the topic, this book aims to fill a gap in the current engineering curricula by taking a wide-angle view at the process of engineering design rather than focusing on a more narrow and in-depth approach. As part of Artech House Publishers' technology management and professional development library, this is an excellent introduction to the topic and may serve for later reference. The author, Peter. H. Sydenham is the inaugural professor and head of the University of South Australia's School of Electronic Engineering, co-founder of the Australian Centre for Test and Evaluation, and a director of Global Systems Engineering Consulting Pty Ltd. This brief biographical sketch explains his qualification to write a book of such practical value and dimension, and why the book is pedagogically sound. The book, according to the preface, aims at those readers who are engineers "who have, or aspire to team leadership or want to take on increased team interfacing responsibilities". As such it builds on and expands what the author perceives to be too little taught in the regular university courses, and covers what is lacking: "breadth of the knowledge now needed to be an effective engineering designer." Twelve chapters offer a step-by-step introduction to the topic. The first chapter, "Systems Thinking and Systems Engineering", gives an overview and the "philosophical" background, while the last looks at "Change and Future Trends". The remaining ten chapters cover the practical aspects of the whole process of systems engineering design with a more hands-on approach, including basics of supporting knowledge such as staff management from planning over recruitment through training to promotion or termination of contract (chapter 3) or information technology support. As such, chapters 2–4 cover the more general aspects, while chapters 5–9 cover the design process from idea to evaluation. Chapter 10 intersperses legal issues, while chapter 11 covers the prototype build, i.e. the step from abstract design to material product. This is an introductory textbook, and as such, it does a very good job of the task at hand. The language is clear, the case examples are well chosen, and the message is conveyed without fail. Some issues are discussed somewhat at length; for example, the basic IT issues are explained in a very detailed way, but one might assume that the basics would be self-evident for today's user: the target audience will have grown up in the age of the personal computer and the internet and as such, will neither question the computer's usefulness nor be overly naïve with regards to the many IT bugs one has to deal with. The illustrations are about as clear as can be-some, in fact, are not clear at all but as they are meant to demonstrate the complexity of the issue at hand, the message gets conveyed the way it should be. How does this general book relate to the specialist field of biomedical engineering? To quote from p. 12: "Researchers in the life sciences were driven by a need to better understand how nature works and controls itself. Out of this pioneering work emerged general systems theory cybernetics, self-organizing systems, automation, automaton systems, organizational science, operations research, systems science, and more-topics with which engineers are not usually that familiar". This lack of familiarity becomes very evident when young engineers join research teams with a focus on applications for the life sciences, such as biomechanical engineering, but also within the broad field of bioinformatics, and they usually take more time to acquire and apply that holistic view of their work than life scientists need to acquire and implement detailed and circumscript engineering knowledge to accomplish their tasks. As such, this book can be recommended to engineers working in biomedicine even at the outset of their careers as it may draw their attention to the importance of this view of things in the new field they enter. Competing recent titles include works by Blanchard [ 1 ], Hitchins [ 2 ] and Sheridan [ 3 ]. A more general outlook on the importance of systems thinking in many areas of life, and far beyond engineering design, is Gharajedaghi's [ 4 ] modern classic. One point that a next edition seriously needs to address is the text editing. Using a word processor does not guarantee a perfect text: this one has a lot of extra words, and as many words missing. As faulty as the text editing is the punctuation check. These errors occur as often as once per page, and force the reader to repeat the study of entire paragraphs several times because, more often than not, it is the missing preposition or punctuation that poses a serious threat to understanding. The publishing house would do well in employing an old-fashioned human text editor to spare the reader such nuisance. In summary, this is a basic textbook to project design management for aspiring team leaders, not only in engineering but for any scientific and some business projects as well. Well written, this is a recommended introduction to the matter and may serve as a reference book and reminder even to the experienced team leader. Adrian Mondry is at Bioinformatics Institute, Singapore Mondry@hotmail.com .

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549215

Pathophysiologic consequences following inhibition of a CFTR-dependent developmental cascade in the lung

Background Examination of late gestation developmental genes in vivo may be limited by early embryonic lethality and compensatory mechanisms. This problem is particularly apparent in evaluating the developmental role of the cystic fibrosis transmembrane conductance regulator (CFTR) gene in the cystic fibrosis (CF) phenotype. A previously described transient in utero knockout (TIUKO) technology was used to address the developmental role of CFTR in the rat lung. Results Rat fetuses transiently treated with antisense cftr in utero developed pathology that replicated aspects of the human CF phenotype. The TIUKO CF rat developed lung fibrosis, chronic inflammation, reactive airway disease, and the CF Antigen (MRP8/14), a marker for CF in human patients, was expressed. Conclusions The transient in utero antisense technology can be used to evaluate genes that exhibit either early lethality or compensating gene phenotypes. In the lung CFTR is part of a developmental cascade for normal secretory cell differentiation. Absence of CFTR results in a constitutive inflammatory process that is involved in some aspects of CF pathophysiology.

Background The in utero gene transfer technology devised in this laboratory [ 1 ] was originally developed to circumvent the inflammatory response seen after birth with adenoviral-mediated gene transfer. During the course of these experiments it was discovered that the in utero transfer of the gene for cystic fibrosis transmembrane conductance regulator ( cftr ) to normal rat fetuses resulted in phenotypic changes in the neonatal lungs [ 2 ]. At the time of gene transfer the targeted epithelial cells were undifferentiated multipotential cells [ 3 ]. Administration of cftr to this epithelium using an adenovirus vector system resulted in persistent phenotypic changes in cells although the expression of the transgene was transient. These data provided the first insight that CFTR expression during the fetal period could permanently alter the differentiation of lung epithelial cells. The permanent functional changes in the in utero cftr -treated rats included an enhanced resistance to pulmonary bacterial infection three months after birth [ 2 ]. At the same time, other laboratories were examining the temporal and tissue-specific expression of CFTR. CFTR lung expression is greatest during the fetal period where it is localized to airway epithelial undifferentiated multipotential cells [ 4 - 9 ]. As these multipotential cells differentiate, the expression of CFTR dissipates and the adult lung expresses only a fraction of that expressed during the fetal period. Thus, CFTR resembles other developmentally important genes in its expression at specific times during organogenesis [ 10 - 12 ]. In addition to its role as a chloride channel in the mature lung, CFTR's expression in undifferentiated epithelial cells suggested another role (or roles) during development. Moreover, this raised the question of how much of CF disease pathology could be attributed specifically to the lack of CFTR expression during differentiation and how much could be attributed to lack of a chloride channel in the mature lung. These questions prompted further experiments by this laboratory in the CF knockout mouse. Reversal of the lethal phenotype of the CF ( cftr -/-) mouse following transient in utero expression of cftr [ 13 ] confirmed the role of this gene in gut development. Because of the rapid cell turnover, the human CFTR transgene was detected in the fetal gut for up to 72 hours post-treatment but not after birth. The in utero gene therapy did not permanently replace the CFTR-encoded cAMP-dependent chloride channel but rescued the mice from the disease phenotype and reversed biochemical markers specific to the knockout phenotype [ 14 ]. These data established that extra uterine expression of CFTR was not required for the correction of the intestinal obstruction in cftr -/- mice. Additional insight into the role of CFTR in secretory cell development was obtained when we began to examine the effects of CFTR following in utero over expression in homozygous normal mouse pups and discovered that over expression resulted in a lethal phenotype due to epithelial cell hyperplasia [ 11 ]. Characterization of the secretory epithelium following CFTR over expression during fetal development has now demonstrated accelerated lung epithelial cell differentiation in the rat, mouse and nonhuman primate [ 2 , 14 - 16 ]. Experiments examining the developmental role of CFTR relied on either a knockout mouse model that poorly mimicked human lung disease or over expression studies in normal animals. At this point it seemed that only two research approaches were available to determine which aspects of CF pathology were due to the lack of CFTR expression during development. Reversal of human CF by transient in utero gene therapy is currently under consideration by our laboratory, but is many years from practical therapeutic consideration. Alternately, one could attempt to transiently inhibit in animals models CFTR production in utero to induce aspects of the adult CF disease phenotype in the presence of normal adult levels of CFTR. The in utero gene transfer method developed by this laboratory uses small quantities of recombinant adenovirus at times during gestation when the lung and intestine epithelium is largely composed of undifferentiated multipotential cells [ 1 ]. Recombinant adenoviruses at 10 8 pfu/ml of amniotic fluid have been transferred to mice, rats, and rhesus monkeys [ 2 , 14 - 16 ]. The high transfer efficiency and absent immune response suggested that it was possible to use recombinant adenoviruses to transfer antisense genes to the lung and intestinal epithelium and transiently inhibit gene expression. Because undifferentiated multipotential cells were targeted, transfer of the antisense analog of a developmentally active gene would have the potential to significantly affect the developmental cascades in the lung and intestines. Recently, we developed a transient in utero knockout (TIUKO) technology to inhibit expression of specific genes in the fetal lung and intestine [ 17 ]. In this paper the TIUKO technology is applied to the question of the developmental role of CFTR in the cystic fibrosis phenotype. Results Inhibition of CFTR expression using TIUKO An adenovirus was constructed from a ATCC plasmid containing exons 1–6 of cftr included in the [ 18 ] cloned into a recombinant adenovirus in the 3'-5', antisense direction (AdCMVAScftr). This virus was used for in utero gene transfer into fetal rats at 16 days gestation. Sprague-Dawley rats were used in these experiments. There were 75 rats from 7 litters in the control group and 114 rats from 11 litters in the TIUKO group. The rats were treated with AdCMVAScftr at 16 days gestation and were evaluated daily from 18–22 days gestation and up to 1 year following birth. The choice of controls for these experiments was a primary consideration. We showed in several publications that over expression of CFTR in normal mice and rats results in altered lung morphology. Thus, neither cftr constructs nor any sense portion of this gene could be used as a control. An adenovirus with exons 1–6 in the sense direction would not express a truncated product and thus its expression could not be detected as a control. The adenovirus constructs with beta-galactosidase (AdCMVlacZ) and green fluorescent protein (AdCMVgfp) were used in previous experiments in several hundred individual fetuses with no effect on the viability, structure, or function of the lung [ 1 , 15 , 16 ]. Thus, these two adenoviruses with reporter genes were used as negative controls for normal organogenesis. The effects of AdCMVAScftr on CFTR expression in rat tissues was compared to control (AdCMVlacZ-treated) lungs at 24 and 72 hours post antisense therapy by fluorescent immunohistochemistry. As shown in Fig. 1A , deconvolution microscopic analysis readily detected CFTR in the normal embryonic lungs. The specificity of the immunohistochemistry was shown by the blocking of all fluorescence using specific blocking peptides (Fig. 1C ). Comparison of control (Fig. 1B ) and antisense CFTR treated (Fig. 1D ) revealed decreased expression of CFTR in antisense treated lungs. Figure 1 Inhibition of CFTR expression in rats treated in utero with antisense c ftr . Sprague-Dawley rats at 16 days of age were treated with either AdCMVlacZ (Panel A, B, C) or AdCMVAScftr (Panel D). At 19 days gestation lungs were harvested and CFTR expressing cells visualized by fluorescent microscopy with an Alexa 568 (RED) secondary and a goat anti-CFTR primary antibody. Nuclei were stained with DAPI (BLUE). Original Magnification Panels A & C 100×; Panels B & D 400×. Reduction of the antisense transgene expression is difficult to measure, because at a maximum only 10 8 cells would be affected if one achieved 100% infection efficiency. Transfection efficiency via the amniotic fluid is less than 10% so only between 10 6–7 cells are affected in the tissue. Thus, real time PCR, northern blots, and western blots lack the sensitivity to detect these changes as shown in our previous publication on the TIUKO c-myc mouse [ 17 ]. Thus, the only method available to quantitate reduction in target gene expression in the TIUKO method is image analysis of random sections from multiple, independently treated lungs. As shown in Fig. 2 , image analyses of the relative levels of CFTR expressed per cell in the AdCMVAScftr-treated tissues were performed. Figure 2 Quantitation of CFTR expression following infection with AdCMVAScftr . Fetuses were treated at 16 days gestation with either AdCMVlacZ (control) or AdCMVAScftr and lungs harvest at 24 and 72 hours post-gene transfer. Lungs from 5 animals were cryo-sectioned and CFTR visualized by immunohistochemistry. Image analysis on the deconvoluting microscope was performed and the results standardized for the number of cells by nuclear staining with DAPI Statistically significant reduction in CFTR levels was observed at 24 (p = 0.014) and 72 hours (p = 0.005) post-TIUKO cftr therapy. Thus, as in our previously published TIUKO c-myc model, the TIUKO cftr therapy decreases expression of the target gene at a critical time in lung development. Airway and parenchymal changes in the CF TIUKO rat Focal areas of fibrosis are seen in the lungs of congenic CF mice as well as humans at autopsy [ 19 ]. Rats were followed sequentially for lung histological examination to determine if they would develop any chronic lung changes that mimicked CF lung pathology. Both the airways and parenchyma were examined. Comparison of the histology of lungs from control and AdCMVAScftr-treated animals during the neonatal period revealed little or no gross structural pathology (data not shown). Development of pulmonary histopathology became apparent in adult rats by 100 days of age following the in utero antisense cftr treatment. The most notable histologic change was in the airways, which appeared thickened and fibrosis. Morphometric analysis was used to quantitate airway wall dimensions on lung sections from 100 day old rats following staining with hematoxylin and eosin [ 20 , 21 ]. The wall area was determined by digitizing the area excluding airway epithelium and cartilage. The corresponding segment of sub epithelial basement membrane was digitized and used as a reference length to normalize airway wall area[ 21 ]. As shown in Table 1 , there was a significant increase in airway wall thickness in the in utero antisense cftr treated animals as compared to their aged-matched controls. The average internal airway circumference was not statistically different between the treated and control group. These measurements insured that similar sized airways were compared between the two groups. Table 1 Morphometric analysis of fibrosis and airway thickness in control and AdCMVAScftr treated lungs at 100 days of age Sample Average Internal Circumference (I) N = 20/group Average area (A) Average A/I Average airway Protein (V) N = 24/group average collagen (C) average C/V AdCMVgfp-treated 101.8 452.1 4.49 6595 ± 1829 2921 ± 810 0.5251 AdCMVAScftr-treated 114.7 833.9 7.27* 6965 ± 911 11665 ± 1829 1.6648** * p = .023 ** p < 0.001 Masson's Trichrome was used to differentiate collagen from smooth muscle and elastin surrounding the airways to better visualize and quantitate the extent of airway fibrosis. Collagen following this stain was visualized as a dense bluish-tinged material as shown surrounding the membranous airways in Figure 3 . There was increased collagen in both the small (Fig. 3C ) and large airways (Fig. 3D ) of the AdCMVAScftr-treated rats when compared to control airways of the same size (Fig. 3A & 3B ). Morphometric quantitation of airway collagen was performed using image analysis [ 20 ]. Airway collagen was increased significantly (p < 0.001) in the antisense treated animals as determined by an increased collagen/protein ratio (Table 1 ). Total lung collagen was also quantitated using image analysis [ 22 ]. As shown in Figure 4 , statistically significant (p = 0.0029) increase in total collagen was confirmed. Figure 3 Airway fibrosis following in utero AdCMVAScftr therapy . Lung sections were stained with Masson's Trichrome to visualize collagen (blue) in 100 day old rats. There was increased collagen in both the small (Panel C) and large airways (Panel D) of the AdCMVAScftr-treated rats when compared to control airways of the same size (Panels A and B). The morphometric quantitation of this fibrosis (Table 1) confirmed that these changes were consistent throughout the lung fields examined. Original magnifications 100×. Figure 4 Collagen in rat lungs following in utero antisense cftr gene transfer . Rat fetuses at 16 days gestation were treated with either AdCMVlacZ (control; black) or AdCMVAScftr (ASCFTR; red). At 120 days of age 5 animals in each group were harvested and 5 random sections were analyzed for total collagen following Mason trichome staining using image analysis as described in Methods Chronic inflammation is another feature of CF lung pathology in humans [ 23 ]. At 100 days of age, prominent inflammatory cell infiltrate was present in the lung parenchyma of the AdCMVAScftr treated rats (Fig. 5B & 5D ) that was not present in the AdCMVgfp-treated control animals (Fig. 5A & 5C ). We have previously demonstrated that in utero adenoviral-mediated transgene expression decreases rapidly in the 30 days post-transfer [ 2 ]. Thus, the adult rat lung pathology progressed in the absence of significant antisense cftr expression. In addition, although these animals were not kept in a germ free environment, repeated bacterial challenge was not required for the induction of either lung inflammation or fibrosis. All animals greater than 60 days of age thus far examined (n = 12) have had significant pulmonary inflammatory infiltrate. Figure 5 Chronic inflammation following in utero AdCMVAScftr therapy . Lung fields from rats at 100 days were examined for inflammation following hematoxylin and eosin staining (Panels A & B). Prominent areas of inflammatory cell infiltrate surrounding membranous airways were demonstrated in AdCMVAScftr treated rats (Panel B) and were not found in AdCMVgfp control animals (Panel A). Staining of the areas of inflammatory cell infiltrate with Masson's Trichrome demonstrated interstitial fibrosis associated with the inflammation (Panels C and D). Original magnification Panels A, B and C-100×; Panel D-400×. Expression of CF-specific proteins following TIUKO cftr MRP8 and 14 are proteins previously used as clinical markers of cystic fibrosis. These proteins are calcium binding proteins that form a heterodimer, are produced in neutrophils, and are associated with wound healing. Importantly, MRP8 was originally called "CF antigen" because it was found to be elevated in the serum of CF patients. The protein was subsequently found to be a heterodimer of MRP8 and MRP14. It was used to identify CF affected individuals as well as heterozygous carriers prior to the discovery of the cftr gene. Because of their significance the expression levels of these proteins were confirmed by western blot analysis in both mice and rats following AdCMVAScftr gene therapy. To determine if MRP8/14 expression was directly associated with the inhibition of CFTR expression, and not induced by post-natal events, western blot analysis of expression was followed sequentially over the first 96 hours post antisense cftr therapy in utero . Minimally detected levels of MRP 8 were expressed in control fetuses (Fig. 6 ; AdCMVgfp-treated animals). In the AdCMVAS cftr -treated rats, a gradual increase in MRP 8 expression was documented over 96 hours post-therapy. Similar results were obtained with MRP 14 (data not shown). Thus, increased CF Antigen expression was correlated with the decreased expression of CFTR following antisense cftr gene therapy. Figure 6 Western analysis of MRP 8 (CF Antigen) expressions in rat lungs following in utero antisense cftr therapy . Western blots were performed on protein (20 μg) from lungs using MRP8 or actin specific antibodies. Protein was extracted from either AdCMVgfp (control) or fetuses (n = 6) treated at 16 days gestation with AdCMVAScftr (n = 6) and fetal rat lungs harvested at 18–20 days gestation Altered airway reactivity in antisense cftr -treated rats In cystic fibrosis patients, alteration in airway reactivity was previously documented [ 24 , 25 ]. To evaluate the effect of in utero antisense cftr on the airway development rats treated at 16 days gestation with AdCMVAScftr or AdCMVlacZ were maintained in filtered cages and analyzed for airway reactivity to acetylcholine at 6–13 months of age. As shown in Fig. 7 , control animals challenged with nebulized acetylcholine showed only small changes in airway resistance ( Raw ) at 3.125 and 12.5 mg/ml concentrations. In contrast, age-matched, antisense cftr treated animals were highly reactive to the low concentrations of acetylcholine. In addition, maximal stimulation at 50 mg/ml in the TIUKO CF rats was over twice that observed in control animals. The differences between control and TIUKO CF rats was highly significant (p < 0.0001) Figure 7 Airway reactivity in AdCMVAScftr-treated rats . Fetuses at 16 days gestation were treated with either AdCMVlacZ (black; n = 5) or AdCMVAScftr (red; n = 5). Animals were maintained in filtered cages to minimize exposure to environmental pathogens. At 6–12 months of age, changes in airway resistance ( Raw ) were determined in response to nebulized saline and acetylmethylcholine at concentrations of 3.125, 12.5, and 50 mg/ml. Discussion The development of the TIUKO procedure permits the examination of mid-gestation developmentally required genes in the absence of both early lethality and compensatory mechanisms that ameliorate the final disease phenotype. Previously, transient expression of the antisense to a known growth factor c-myc [ 17 ] demonstrated its requirement for normal cell expansion in both the lungs and intestines. The key element in the TIUKO method is the targeting of multi-potential, undifferentiated cells. Because the lung is developing rapidly at the time, organogenesis can be dramatically affected by inhibition of genes involved in a developmental cascade. Thus, inhibition of c-myc gave rise to severely hypoplastic lungs and stunted villi formation in the intestines, even though fewer than 10 7 cells were affected by the antisense transgene. This method can be used to dissect the developmental pathway of different epithelial cell types in these organs. One caveat with the TIUKO method, however, is the difficulty in measuring the decrease in expression of the target gene. Because the population of affected multipotential, undifferentiated cells represent a small proportion of the total, rapidly expanding lung population, it is impossible to detect the changes in gene expression via real time PCR, northern blots, or western blots. However, as shown previously two independent methods, antisense and ubiquitin targeted, down regulation of C-MYC [ 17 ] yielded identical phenotypes and immunofluorescent quantitated decrease of the target transgene,. In this paper, all conclusions are based only immunofluorescent quantitation of target gene down regulation following transient antisense CFTR in utero . Cystic fibrosis is a pleiotropic disease. The seemingly unrelated phenotypic effects of CFTR are largely unexplained by the hypothesis that CF pathology results from the lack of continuous chloride channel expression. Beginning with the reversal of the CF knockout mouse phenotype with transient in utero cftr gene therapy using a recombinant adenovirus [ 9 ], this laboratory proposed that CF was also a disease of secretory cell differentiation and that the protein's many functions, including that of a chloride channel, were required for multipotential cell differentiation. Results supporting this hypothesis were obtained in mice, rats and non-human primates. Thus, some of the altered functions observed in CF tissues are due to incomplete development and malfunctioning secretory cells. As shown recently [ 5 ], CFTR is highly expressed in the lung during the pseudoglandular phase of development and begins to decline during the cannalicular phase of development where it remains low at birth. This early phase of lung development correlates with that used for in utero gene therapy and reversal of the knockout mouse phenotype [ 5 , 13 ]. These data also suggested that the transient, selective, inhibition of CFTR expression should recapitulate the human CF phenotype without species-specific compensatory mechanisms interference. The development of the TIUKO method permitted such experiments. The selective, transient CFTR expression inhibition in a small number (<10 7 ) of undifferentiated multipotential cells was performed in using a recombinant adenovirus with a cftr fragment cloned in the 3'-5', antisense, direction. As shown in immunohistochemical examinations of lung tissues (Figure 1 , 2 ), specific inhibition of CFTR expression occurred to the extent of that obtained previously with antisense c-myc [ 17 ]. In the lungs of TIUKO CF rats, significant changes in lung structure were not readily apparent at birth. As the animals aged, however, airway thickening and fibrosis were found morphologically. Changes in the airways were confirmed with morphometric analysis (Fig. 3 , 4 ; Table 1 ) and pulmonary function tests (Fig 7 ). Thus, the TIUKO CF rats reproduced many aspects seen in lung disease of human. Elevated serum levels of MRP8 were used to identify CF affected individuals and heterozygous carriers prior to the cloning of the cftr gene. The gene for the cystic fibrosis antigen (MRP8) was cloned in 1987 by Dorin et al. [ 20 ]. Because intermediate levels of the protein were expressed in clinically unaffected heterozygotes it was hypothesized at that time that its expression was closely related to the basic defect of cystic fibrosis. Work on this protein lost momentum when the cftr gene was cloned and confirmed to be a chloride channel and also when MRP 8 expression was not found in the preliminary survey of adult and fetal CF lung [ 26 ]. Because MRP8/14 is highly expressed in polymorphonuclear leukocytes, the high levels of MRP8/14 in CF patients were explained as a result of inflammation rather than a potential source of it. In addition to elevated levels of MRP8/14 protein in human CF serum, mRNA expression has been found in tracheal gland cells obtained from normal and cystic fibrosis patients. A significant increase in these mRNAs was shown in the cells of CF origin [ 27 ]. The increased expression of this protein in the fetal lung following antisense cftr gene transfer (Fig. 6 ) is consistent with human CF and the knockout mouse. Reversal of the CF phenotype by in utero gene therapy and the developmental changes following CFTR over expression studies in mice, rats, and non-human primates are consistent with a developmental paradigm for this disease. As summarized in Table 2 , the TIUKO CF rats demonstrate that faulty differentiation of secretory cell may be associated with many of the features of the CF lung disease phenotype [ 28 ]. Table 2 Comparison of cystic fibrosis disease phenotypes between human and animal models HUMAN DISEASE PHENOTYPE CFTR KNOCKOUT MOUSE MODEL PHENOTYPE TIUKO CF RAT PHENOTYPE LUNG FIBROSIS FIBROSIS AND INFLAMMATION PRESENT BY 100 DAYS OF AGE MRP8/14 ELEVATED DETECTED IN G551D MOUSE INCREASED PRENATALLY AIRWAY REACTIVITY NOT DETECTED INCREASED WITH AGE CHRONIC INFLAMMATION DETECTED IN CONGENIC MICE PRESENT BY 100 DAYS OF AGE Several recent papers illustrate the potential role of the developmental requirement of CFTR in CF pathophysiology and lung growth Groman and co-workers [ 29 ] found a subset of patients with the CF phenotype and no mutation in the cftr coding sequence. This finding is consistent with the role in CF of other genes in a common secretory cell pathway that includes cftr as only one of many components. In addition, transplant of human fetal CF lung tissues into SCID mice resulted in lung inflammation [ 30 ]. These data are consistent with our prenatal elevation of the MRP8/14 (Figure 6 ) and suggest that developmental interference with secretory cell differentiation results in a constitutive inflammatory response. Until recently, no distinctive changes in lung structure and function were found in the CFTR knockout mouse. However, recent evaluation by our laboratory of lung function in cftr+/+ , cftr+/- , and cftr-/- mice, showed distinct phenotypes for each genotype [ 31 ]. Thus, normal lung development in mouse is affected in a dose response manner by CFTR. The TIUKO rat is distinct genetically from a heterozygous animal. In heterozygous animals, one maintains a single functional copy of the transgene in all multipotential, undifferentiated cells of the developing fetal lung. So in the mature, heterozygous lung altered pulmonary function but normal structure is observed. In contrast, in the TIUKO CF fetal lung, multipotential, undifferentiated cells infected with the antisense gene have a total deficiency of CFTR (Fig 1 ). The developing TIUKO CF rat lung is a mosaic of normal ( cftr+/+ ) and CFTR deficient (essentially cftr-/- ). Thus, as shown in this paper, the TUIKO CF rat exhibited a CF-related phenotype while a CFTR heterozygous does not show any CF features. We propose that CFTR is part of a developmental cascade for secretory cells in the lung, intestines, pancreas and other secretory organs (Fig. 8A ). Disruption of this pathway could occur by either a cftr mutation, or as suggested by Groman et al's [ 29 ] work, other mutations of genes in this cascade. This would lead to incomplete differentiation of secretory cells and loss of function (Fig. 8B ). In addition, the failure of secretory cell differentiation leads to a constitutive expression of cytokines that function in development as agents of differentiation. Once the immune system matures postnatally, however, these same cytokines assume a proinflammatory role, leading to chronic inflammation and fibrosis. The TIUKO CF rats may be used to identify these other genes involved in human lung epithelial cell differentiation and diseases resulting from their dysfunction. Finally, the TIUKO CF rat provides an animal model for the development of pharmacologic agents to disrupt the constitutional inflammatory processes in the CF affected tissues. Figure 8 Developmental Paradigm for Cystic Fibrosis Lung Fibrosis Based on TIUKO CF Rat and Developmental Studies in Mice, Rats, and Non-human Primates . In Panel A CFTR is shown as one member of a developmental cascade required for normal secretory epithelium development. Included in this pathway are other cytokines, possibly MRP8/14. In normal development in the presence of CFTR feedback mechanisms either completely inhibit or at least decrease the expression of these developmentally active cytokines. In the absence of CFTR, Panel B, the secretory epithelium fails to differentiate properly. Failed development leads to an immature epithelium that does not exhibit the feedback function necessary for inhibition of developmentally required cytokines. Expression of these cytokines in the permanent, developmental immature, CF lung leads to activation of inflammatory cells once the immune system matures post-natal. Constitutive, chronic inflammation would explain the lung fibrosis and inflammatory disease seen in CF patients Conclusions Transient inhibition of CFTR expression in the lungs results in many features of cystic fibrosis in the mature animal. Increased fibrosis, chronic inflammation, increased airway reactivity, and elevation of CF antigen were observed. These data are consistent with a CFTR requirement for normal lung development. Methods Recombinant adenoviruses A 920 bp human CFTR cDNA that included exons 1–6 (ATCC 61123; [ 18 ]) was gel-purified and subsequently subcloned into the plasmid pShuttle-CMV (Quantum Biotechnologies, Montreal, Canada). Recombinant adenoviruses were generated by homologous recombination in the E. coli strain BJ5183, according to the protocol of He et al [ 32 ]. Recombinants were confirmed for overall size by restriction endonuclease digestion and propagated in DH5a. Linear recombinant adenoviral DNA was used to transfect 911 packaging cells by Ca2PO4 precipitation to produce the virus AdCMVAScftr. Recombinant adenoviruses with the lacZ (AdCMVlacZ) and green fluorescent protein (GFP; AdCMVgfp) were provided by Dr. J. Kolls (LSHHSC, New Orleans, LA). All viruses were CsCl or HPLC purified. In utero gene transfer Timed pregnant Sprague-Dawley Rats were induced (5%) and sedated (2%) with inhaled Isoflurane. A laparotomy was performed exposing the uterine horns. The individual amniotic sacs of the fetuses were visualized and injected with fine gauge needle containing adenoviral particles in 10% of the amniotic fluid volume. The recombinant adenoviruses in Dulbecco's Minimal Essential Medium delivered final concentrations of 10 8 pfu/ml to the amniotic fluid. Histochemistry and morphometry At the time of sacrifice all animals received a number. This code was used for identification of all histologic and biochemical studies. All tissues were fixed in methanol-free, 4% buffered paraformaldehyde and either mounted in paraffin or OCT for sectioning. Fluorescent immunohistochemistry was performed with goat polyclonal IgG (Santa Cruz) specific for CFTR carboxy (sc-8911) and amino terminal (sc-8909) sequences. Secondary donkey anti-goat ALEXA (Molecular Probes) antibodies were used. All tissues were visualized on a deconvoluting, Lieca, light microscope. Hematoxylin and eosin stain and Masson's Trichrome stain were performed with kits (Sigma Chemical Co) and tissues examined by standard light microscopy. Morphometry was performed with the identification numbers and treatment groups unidentified by two blinded investigators. Airway thickness was determined following staining with hematoxylin and eosin in 100 day old rats. The area of the wall between the sub epithelial basement membrane and parenchymal epithelium was digitized excluding airway epithelium and cartilage. The corresponding segment of sub epithelial basement membrane was digitized and used as a reference length to normalize airway wall area [ 21 ]. Quantitation was performed using Scion Image [ 13 , 14 ]. Image analysis based morphometry was performed with the identification numbers and treatment groups unidentified. Morphometric analysis was performed by two blinded investigators. Digitalized images were analyzed for airway thickness using Scion Image [ 13 , 14 ] or for collagen using PHOTOSHOP imaging software [ 22 , 33 ]. Deconvoluting microscopy and image analysis was performed on a Lieca inverted microscope with Xenon light source and SLIDEBOOK imaging software. Western blots Polyacrylamide gel electrophoresis was performed on 18% Tris-HCl gels (Biorad) and transferred to PVDF membranes (Amersham) [ 34 , 35 ]. Polyclonal antibodies to MRP8, MRP14, and actin (Santa Cruz) were used in the concentrations of 1:1000 (all antibodies). The secondary HRP-labeled anti-goat antibody (Santa Cruz) was incubated at a concentration of 1:8000. Detection was performed using ECL-plus (Amersham). Pulmonary function tests Rats at 12–14 months of age were anesthetized with intra-peritoneal pentobarbital (90 mg/kg), and the trachea was dissected free of surrounding tissue and cannulated with a 20-gauge cannula. The rat was then connected to a small animal ventilator ( flexiVent , SCIREQ Inc. Montreal, PQ, Canada) and ventilated with a tidal volume (V t ) of 10 ml/kg; inspiratory:expiratory ratio (I:E) of 66.67%, respiratory rate of 150 breaths/minute, and maximum pressure of 30 cmH 2 0. Positive end-expiratory pressure (PEEP) was controlled by submerging the expiratory limb from the ventilator into a water trap. Each animal was paralyzed with pancuronium bromide (0.5 mg/kg) and allowed to equilibrate on the ventilator until spontaneous breathing ceased (5 minutes). Zrs measurements at a PEEP level of 3. Data were statistically evaluated using paired t-test. Respiratory mechanics To measure the input impedance of the respiratory system ( Zrs ), mechanical ventilation was interrupted and the animal was allowed to expire against the set level of PEEP for 1 s. We then applied an 8 second broad-band volume perturbation signal was then applied to the lungs with the flexiVent , after which ventilated was resumed. A PEEP of 3 cmH 2 O was used. The volume perturbation signal consisted of the superposition of 18 sine waves having frequency spaced roughly evenly over the range 0.25 Hz to 19.625 Hz. Zrs was calculated from the displacement of the ventilator's piston and the pressure in its cylinder as described previously [ 36 , 37 ]. Correction for gas compressibility as well as resistive and accelerative losses in the flexiVent , connecting tubing and the tracheal cannula were performed as described previously [ 38 ]using dynamic calibration data obtained by applying volume perturbations through the tubing and tracheal cannula first when it was completely closed and then when it was open to the atmosphere. We interpreted the measurement of Zrs in terms of the constant phase model [ 39 ] where Raw is a frequency independent Newtonian resistance reflecting that of the conducting airways [ 40 ], Iaw is airway gas inertance, G characterizes tissue damping, H characterizes tissue stiffness (elastance), i is the imaginary unit, α links G and H , and f is frequency. We also calculated a quantity known as hysteresivity ( η = G/H ), which is believed to increase when regional heterogeneities develop in the lung [ 41 ]. Acetylmethylcholine challenge After rats were equilibrated on the respiratory, sequential 30 second challenges with nebulized physiologic saline, 3.125, 12.5 and 50 mg/ml acetylmethylcholine dissolved in physiologic saline were performed. Between each challenge, 18 broad-band volume perturbations were produced by the ventilator at 10 second intervals between each perturbation. Raw was calculated for each perturbation. Abbreviations CFTR – Cystic fibrosis transmembrane conductance regulator; CF – cystic fibrosis Author contributions Both authors were equally responsible for both the laboratory work and design of experiments

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555600

Angiogenesis in cancer of unknown primary: clinicopathological study of CD34, VEGF and TSP-1

Background Cancer of unknown primary remains a mallignancy of elusive biology and grim prognosis that lacks effective therapeutic options. We investigated angiogenesis in cancer of unknown primary to expand our knowledge on the biology of these tumors and identify potential therapeutic targets. Methods Paraffin embedded archival material from 81 patients diagnosed with CUP was used. Tumor histology was adenocarcinoma (77%), undifferentiated carcinoma (18%) and squamous cell carcinoma (5%). The tissue expression of CD34, VEGF and TSP-1 was assessed immunohistochemically by use of specific monoclonal antibodies and was analyzed against clinicopathological data. Results VEGF expression was detected in all cases and was strong in 83%. Stromal expression of TSP-1 was seen in 80% of cases and was strong in 20%. The expression of both proteins was not associated with any clinical or pathological parameters. Tumor MVD was higher in tumors classified as unfavorable compared to more favorable and was positively associated with VEGF and negatively with TSP-1. Conclusion Angiogenesis is very active and expression of VEGF is almost universal in cancers of unknown primary. These findings support the clinical investigation of VEGF targeted therapy in this clinical setting.

Background Cancer of unknown primary (CUP) is a unique clinical entity that accounts for an approximately 3% of human cancers[ 1 ]. Patients with CUP present with metastases for which the site of origin cannot be identified at initial workup. Early dissemination, unpredictability of metastatic pattern and aggressiveness constitute fundamental characteristics of these tumors. Although the clinical characteristics of CUP have been established, little is known about the underlying biology of these tumors [ 2 , 3 ]. Angiogenesis, the formation of new vessels, is essential for tumor growth and the development of metastases. It evolves though a complex multifactor process that involves interaction of pro-angiogenic and anti-angiogenic signals from tumor, endothelial and stromal cells. The angiogenic activity is reflected in the development of novel microvessels in tumor tissue that is quantified by the intratumoral microvessel density (MVD). Among several molecules implicated, Vascular Endothelial Growth Factor (VEGF) and Thrombospondin-1 (TSP-1) appear to be most relevant. Much evidence indicates that VEGF is a key activator of angiogenesis[ 4 , 5 ] and TSP-1 a primary endogenous inhibitor of angiogenesis[ 6 ] Up to now, no useful prognostic factors have been established other than the classic pathologic and laboratory ones and immunohistochemical detection of various factors did not add prognostic value in CUP.[ 7 , 8 ] Moreover, investigation of the expression of crucial angiogenesis factors that can be therapeutically targeted is today of great interest for the oncologists who deal with CUP clinical research.[ 9 ] We were prompted to investigate angiogenesis in unknown primary cancer in an attempt to enrich our understanding of the biology of these tumors. We studied by immunohistochemistry the tissue expression of VEGF and TSP-1 in CUP and correlated with MVD and clinicopathological parameters. In a recently published study vascular endothelial growth factor, and CD34, factors were not found to be of prognostic value in adenocarcinoma of unknown primary.[ 8 ] Methods A total of 81 patients diagnosed with CUP and treated in three University Medical Oncology Settings (Ioannina, Patras and AHEPA, Thessaloniki, Greece) between January 1997 and December 2002 were selected on the basis of availability of archival tumor tissues and accessibility to medical notes. Pathology diagnosis was reviewed by two pathologists blinded to written pathology report and representative paraffin blocks were selected for immunohistochemistry. Subgroup definition Eligible cases categorized into unfavorable and more favorable subgroups (tables 1 and 2 ). Patients with poorly differentiated carcinoma with midline distribution, papillary adenocarcinoma of peritoneal cavity and adenocarcinoma involving only axillary lymph nodes in women, squamous cell carcinoma involving cervical lymph nodes and poorly differentiated neuroendocrine carcinomas were assigned to favorable CUP subsets. Patients with adenocarcinoma metastatic to the liver, multiple visceral involvement and extensive metastatic bone disease were considered as unfavorable. Systemic chemotherapy was given in 64 patients (78%); four patients with cerebral metastases received whole brain irradiation. Chemotherapy was consisted of a platinum based combination. Objective response to chemotherapy was observed in 34 patients (53%) while one patient with brain metastases responded to radiotherapy. Median survival for all patients was 10.5 months (Figure 1 ). Patients belonging to favorable subsets had a significantly higher response rate to treatment (Fisher's t-test, p = 0.04) and a longer survival, 11.5 vs 8.5 months ( p = 0.01). Immunohistochemistry Immunostaining was performed on formalin-fixed, paraffin-embedded tissue sections by the labeled streptavidin avidin biotin (LSAB) method. In brief, tissue sections were deparaffinised in xylene and dehydrated. They were immersed in citrate buffer (0,1 m, pH 0,6) and subjected to microwave twice for 15 min. Subsequently, all sections were treated for 30 min with 0,3% hydrogen peroxide in methanol to quench endogenous peroxidase activity. Mouse monoclonal antibodies directed against human CD34 antigen (M 7165, Dako) in dilution 1/50 β) VEGF Ab-3 (isoform 121, clone Jh121, Neomarkers) in dilution 1/50 and c) thrombospondin (Mob 315, DBS) in dilution1/50 were used. Positive control slides were included in all cases. All dilutions were made in TBS-1% BSA solution and were followed by overnight incubation. The assessment of immunostaining was made by two experienced pathologists using light microscope. Tumor specimens too small to provide sufficient sections for all the immunoassaying procedures were disregarded from the study. Immunostaining evaluation Staining of endothelial cells for CD34 was used to evaluate the MVD. Any CD34 positive endothelial cell clusters clearly separated from each other were considered as single countable microvessels. A lumen was not required to identify a vessel. Larger vessels with muscular walls were excluded from counting. In each sample three areas of most prominent vascular density (hot spots) were identified at ×40 power field and microvessel counting was done under ×400 magnification. Counting was performed by two independent observers blinded to clinical information. The median count was used to make distinction between low and high MVD. Immunoreactivity for VEGF was observed in stromal and epithelial cells. Only staining of tumor cells was considered for analysis. To evaluate the expression of VEGF protein, we devised a combined score that corresponds to the sum of staining intensity (0 = negative, 1 = weak, 2 = intermediate, 3 = strong staining) and percentile quadrants of positive cells (0 = 0%, 1 = 1–25%, 2 = 26–50%, 3 = >50%). The maximum score was 6. Score 2 was regarded to represent weak expression, score 3 intermediate and score 4–6 strong expression. Staining for TSP-1 was only considered in regard to extracellular matrix. The expression of TSP-1 was characterized according to the extent and the intensity of staining classified as negative, +1: mild, focal, +2: intermediate, multifocal, +3: strong, diffuse reactivity. Statistics Staining results were analyzed against clinical subgroup, histological differentiation, response to treatment and survival. The association between MVD and clinical subgroup, histological differentiation and response to treatment was assessed by an unpaired t test. A Fisher's exact test was used to determine associations between VEGF and TSP-1 and the clinical subgroup, histological differentiation and response to treatment. Spearman non parametric correlation test was used for associations between MVD, VEGF and TSP-1. Survival was calculated by Kaplan-Meier method and comparison of survival curves was performed by the log-rank test. For statistical significance a two-tailed p value was considered. The Graphpad Instat version 3.05 (Graphpad Software, Inc, San Diego, CA) and Prism version 4 (Graphpad Software, Inc, San Diego, CA) software programs were used for statistical analysis and graphing. Results Demographics of studied cases are depicted in Tables 1 and 2 . Overall survival of patients included in this study is shown in Figure 1 . (Median survival 10 months). Immunohistochemistry Microvessel density Widespread staining for CD34 was seen in all tumor specimens. Within the most prominent vascular areas of the tumors the recorded mean MVD was 59 microvessels/mm 2 (range, 16 to 300 microvessels/mm2) (Table 3 , figure 2 ). A positive association was observed between VEGF expression and MVD (Spearman r = 0.36, p = 0.0016) and negative with TSP-1. VEGF expression Positive staining of tumor cells for VEGF, both membranic and cytoplasmic was observed in all cases. This was strong in 83% of the cases and moderate in 17%. VEGF staining was heterogeneous within tumors comprising of areas of intense and also weak staining and demonstrated a characteristic granular cytoplasmic staining pattern. (Figure 3 ) A weak and focal positive reaction of intervening stromal cells (fibroblasts or/and macrophage) and endothelial cells was also seen in some cases. This staining was excluded from VEGF analysis. (Table 3 ) TSP-1 expression Stromal TSP-1 staining was detected in 80% of the cases, while in 20% it was absent (figure 4 ). Strong (score = 3)and intermediate (score = 2) TSP-1 staining was observed in 50% of cases and weak (score = 1) in 30% (Table 3 ). A negative association was observed between TSP-1 expression and MVD, (Spearman r = -0.3426, p = 0.003) while there was no association between TSP-1 and VEGF expression. Association between immunostaining and clinicopathological variables MVD was found statistically higher in unfavorable CUP cases compared to more favorable ones (70 vs 46 microvessels/mm2, t test, p = 0.034) (table 4 ). This was the only correlation detected between angiogenesis related tissue markers studied and clinicopathological variables. No association was detected between VEGF and TSP-1 and tumor differentiation, response to treatment, clinical subgroups and survival (Table 4 ). Discussion The investigation of the biological profile of CUP and the understanding of molecular pathways underlining these tumors has been limited. We have worked on these issues and found several oncoproteins overexpressed, but failed to establish any clinically relevant correlations[ 10 , 11 ]. We now investigated neo-angiogenesis by assessing MVD and the tissue expression of two representative molecules involved in angiogenesis; the major stimulator of angiogenesis VEGF (A), and the intrinsic angiogenic inhibitor TSP-1. Overall, we demonstrated that a high angiogenetic activity occurs in CUP tumors, which is higher in unfavorable when compared with more favorable subsets. VEGF is known to play a key role and MVD is considered to reflect the final result of the tumor angiogenesis cascade. In the present study, all cases were found to be VEGF-positive and in the majority VEGF was overexpressed. Tumor VEGF and MVD were strongly correlated that is in line with findings in solid tumors[ 12 , 13 ]. We failed to demonstrate any significant correlations of angiogenic activity with regard to clinical outcome, but this was obviously due to universal expression of both CD34 and VEGF in our cases. We also demonstrated that in our series TSP-1 was overexpressed in 50% and was absent or weak in approximately half of the cases. TSP-1 correlated inversely with microvessel counts. The role of TSP-1 in epithelial tumor growth and metastases remains controversial. In vitro studies suggest that TSP-1 may promote tumor cell adhesion and invasion by up-regulating urokinase plasminogen activator and its receptor[ 14 ] but in clinical studies overexpression has been associated with a lower MVD score and a better clinical outcome in several carcinomas[ 15 ]. Moreover, other studies suggest that TSP-1 inhibits tumor progression and may serve as an indicator of less aggressive potential and of favorable prognosis in solid tumors.[ 16 ] We consider that low TSP-1 in our material reflects a suppression of anti-angiogenic mechanism of TSP-1 that possibly contributes to the aggressiveness of these tumors. CUP patients have in general a brief life expectancy with a median survival approximately of 3–9 months.[ 17 , 18 ] It must be emphasized that CUP diagnosis applies to a heterogeneous group of patients who are usually grouped together in biological and therapeutic studies to obtain statistically meaningful results. However several patients fare better and enjoy longer survival and within this more favorable prognostic subgroup, unique subsets, such us young patients with midline tumors and women with peritoneal carcinomatosis or isolated axillary adenocarcinoma, have a distinct clinical biology compared to others also classified as unknown primary cancer. [ 19 - 23 ]. In our study MVD score were found low in the group of more favorable tumors compared to unfavorable, but neither MVD nor VEGF or TSP-1 were associated with known prognostic factors.[ 24 ] Similarly, Hillen et al, in a small study, evaluated MVD as a prognostic factor for patients with liver metastases of unknown primary and found that MVD score correlated with marginally shorter survival.[ 25 ] Conclusion In conclusion, we found that angiogenesis is very active and VEGF expression is universal in cancer of unknown primary, which supports the clinical investigation of VEGF targeted therapy in this clinical setting.[ 9 ] To identify additional druggable molecular targets in cancer of unknown primary we need to advance our knowledge on the biology of these tumors and validate novel molecular therapeutics. Competing interests The author(s) declare that they have no competing interests. Authors' contributions NP conceived, coordinated and designed the study, interpreted the data and drafted the manuscript; VK, EB, designed and carried out the study, performed the statistical analysis, interpreted the data and drafted the manuscript; VMM carried out the pathological and immunohistochemical study, interpreted data and drafted the manuscript; ET, EK carried out the pathological and immunohistochemical study, interpreted data and drafted the manuscript; HK, GF, TF participated in designing the study, acquisition and interpretation of data and revising critically the manuscript. All of the authors have read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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554091

Assessment of obesity management in medical examination

Obesity is a growing international health problem that has already reached epidemic proportions, particularly within the United States where a majority of the population is overweight or obese. Effective methods of treatment are needed, and should be taught to physicians by efficient means. There exists a disconnect between the rising obesity prevalence with its high toll on medical resources, and the lack of obesity education provided to practitioners in the course of their training. One particular shortfall is the lack of representation of obesity on standardized medical examinations. Physician attitudes toward obesity are influenced by their lack of familiarity with the management of the disease. This may include dietary restriction, increasing physical activity, behavior modification, pharmacotherapy, and surgical interventions. Thus, curricular changes in the medical education of obesity could help reduce morbidity and mortality associated with this disease.

Wegeners's granulomatosis, errlichiosis, and tetrology of Fallot are examples of some of the rare diseases that I have learned to identify and look for in patients for over seven years as a medical student and resident in Internal Medicine. As a physician in training, I was frequently challenged to consider broad differentials and to watch out for the zebra that masquerades as a common disease throughout my clinical encounters. I have had my antennas up in search of these diseases for quite a while now. I have not, however, encountered any patients with these diseases so far. What I have usually encountered instead are common diseases, like type 2 diabetes, hypertension, and arthritis. More than anything, I have been struck by the incidence of obesity in our population. I find it alarming that many clinicians fail to actively address this growing epidemic in a formal manner with their patients, but rather regard obesity as a lifestyle choice that is the patient's sole responsibility. My personal experience with obesity, having trained at a quaternary referral center in the relatively thin state of California, is that over one third of the patients I cared for were obese (not just overweight). Consistent with national trends, patients in my region have been becoming more obese and accordingly have been suffering increasingly from the complications of the disease, such as hypertension, insulin resistance, fatty liver disease, dyslipidemia, coronary heart disease, osteoarthritis, obesity-related cancer, and premature death [ 1 ]. I have been reassured that national policy makers at agencies such as the NIH and Medicare have taken administrative steps to address this epidemic [ 2 ]. What has perplexed me is that medical educators have been slow to prioritize obesity as an important challenge in the medical education of new physicians. Many physicians cite their unfamiliarity with obesity as an impediment to their ability to adequately address the problem with their patients [ 3 ]. In one study by Jelalian et al., the authors found that when addressing obesity, one fourth of physicians thought that they were not at all or only slightly competent, while 20% reported feeling not at all or only slightly comfortable [ 3 ]. My impression is that obesity is not well represented in examinations of medical knowledge. As the latest confirmation of this hypothesis, I found it alarming that there were no questions addressing management of obesity on the American Board of Internal Medicine training examination in August 2004. This is my based on my immediate recollection of the exam, and confirmed by an informal same-day survey of five co-examinees. I later wrote to the ABIM to confirm my suspicion of this omission. In their response, they could not deny that the topic of obesity management had been left out [ 4 ]. I pose to you that our medical education is based largely upon that which we are tested. If this is true, it is not surprising that many physicians do not feel comfortable managing obesity. I recalled at least five examination questions addressing Wegener's granulomatosis, but none directly on obesity. The differences in prevalence are remarkable. In the United States, approximately 61% (110 million) of adults (age 20–74 years) are overweight or obese. [ 5 ]. Educators must realize that if we are to aggressively arrest this epidemic, we must be armed with the knowledge to do so. Awareness, in part comes from exposure. By that, I mean, that which we study is that which we will be questioned on. If we all agree that obesity education is a priority, it follows that examinations should reflect that prioritization. Diabetes, coronary heart disease, dyslipidemias, hypertension, and cancer were appropriately well represented in this ABIM exam and previous standardized examinations I have taken. Obesity should be right up there with these "big players". There is a lot to understand within this field. It is a lot more complex than "eat less, make better nutritional choices, and exercise more". The complexities of nutritional decision making are very important to the patient, and they want to discuss these choices with physicians as well as dieticians. Pharmacotherapy, although limited in terms of number of options, does have a role. Bariatric surgery is an evolving field and there are complexities associated with the use of the procedure that surgeons and internists alike must understand. Also, such psychosocial aspects of obesity as diminished quality-of-life, self-esteem, and work performance must be stressed and understood. Fogelman reported that in one survey of family practitioners, 72% believed that they had limited efficacy in treating obesity and considered themselves not well prepared by medical school to treat overweight patients [ 6 ]. Some 60% reported feeling that they have insufficient knowledge regarding nutritional issues. Regarding pharmacotherapy for treating obesity, only 66% knew the drugs' prescription indications. [ 6 ]. Primary prevention is the way to go in obesity research expenditure. In my opinion, the greatest healthcare cost-savings' "bang-for-the-buck" comes from preventive care and education. Consider how many fewer cases of diabetes, hypertension, CHD, fatty liver disease, dyslipidemia, thromboembolic disease, obesity-hypoventilation, obstructive sleep apnea, gout, osteoarthritis, cancer, GERD, reproductive and urinary tract abnormalities, cataracts, psychosocial abnormalities we would have to battle if the inciting factor (obesity) was aggressively treated at the onset. Is this not one prudent management step toward curtailing an overtaxed health care system? The war on obesity seems winnable. We just need the tools and awareness to address the disease. Obesity is not a silent disease to be tolerated: it is an aggressive yet insidious disease (much like type 2 diabetes) that must be arrested before its negative health consequences become irreversible. The first step is to teach practitioners what to look out for, and in turn, to teach patients what to look out for. Meanwhile, I will have my antennas up in search of Wegener's granulomatosis. Competing interests I hereby declare that I do not have a financial association or other conflict of interest with the subjects mentioned in this manuscript.

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526188

Reconstruction of putative DNA virus from endogenous rice tungro bacilliform virus-like sequences in the rice genome: implications for integration and evolution

Background Plant genomes contain various kinds of repetitive sequences such as transposable elements, microsatellites, tandem repeats and virus-like sequences. Most of them, with the exception of virus-like sequences, do not allow us to trace their origins nor to follow the process of their integration into the host genome. Recent discoveries of virus-like sequences in plant genomes led us to set the objective of elucidating the origin of the repetitive sequences. Endogenous rice tungro bacilliform virus (RTBV)-like sequences (ERTBVs) have been found throughout the rice genome. Here, we reconstructed putative virus structures from RTBV-like sequences in the rice genome and characterized to understand evolutionary implication, integration manner and involvements of endogenous virus segments in the corresponding disease response. Results We have collected ERTBVs from the rice genomes. They contain rearranged structures and no intact ORFs. The identified ERTBV segments were shown to be phylogenetically divided into three clusters. For each phylogenetic cluster, we were able to make a consensus alignment for a circular virus-like structure carrying two complete ORFs. Comparisons of DNA and amino acid sequences suggested the closely relationship between ERTBV and RTBV. The Oryza AA-genome species vary in the ERTBV copy number. The species carrying low-copy-number of ERTBV segments have been reported to be extremely susceptible to RTBV. The DNA methylation state of the ERTBV sequences was correlated with their copy number in the genome. Conclusions These ERTBV segments are unlikely to have functional potential as a virus. However, these sequences facilitate to establish putative virus that provided information underlying virus integration and evolutionary relationship with existing virus. Comparison of ERTBV among the Oryza AA-genome species allowed us to speculate a possible role of endogenous virus segments against its related disease.

Background The virus-like sequences that have been found in plant genomes are divided into two groups of plant viruses, single-stranded DNA geminivirus and double-stranded DNA pararetroviruses. The geminivirus segments, including the viral replication origin and the adjacent AL1 gene, have been found in the genomes of tobacco and its related species [ 1 , 2 ]. Pararetrovirus-like sequences have been reported in the petunia [ 3 , 4 ] banana [ 5 - 7 ] and tobacco genomes [ 8 - 10 ]. Compared to the intact virus sequences, most of the endogenous virus-like sequences were rearranged in the host genomes. Their rearranged structures suggested that illegitimate recombination may have occurred when putative virus progenitors integrated [ 11 ]. The endogenous viruses for banana streak virus (BSV) [ 6 ], tobacco vein-clearing virus (TVCV) [ 9 ] and petunia vein clearing-virus (PVCV) [ 4 ] could be activated as episomal viruses under certain conditions in the host plant, and appeared to have pathogenic potential. The integrations of these viruses were shown to have been relatively recent events and the copy numbers of the endogenous virus sequences were found to be very low. On the other hand, for tobacco endogenous pararetroviruses (TEPRVs), it was estimated that there are about 1000 segments in the tobacco genome [ 8 ], but the intact virus has not been identified so far, suggesting that the integration of TEPRVs was not a recent event. The finding of such endogenous virus sequences raises questions concerning 1) the integration process giving rise to endogenous virus sequences, 2) possible differences in the evolutionary rate between the virus and endogenous virus and 3) resistance potential as a result of endogenous virus integration. In the rice genome, pararetrovirus-like sequences that are similar to rice tungro bacilliform virus (RTBV) have also been found [ 12 - 14 ]. In South and Southeast Asia, rice tungro bacilliform virus, which is transmitted by green leafhoppers, causes one of the most serious diseases of rice with the assistance of rice tungro spherical virus (RTSV) [ 15 ]. Kobayashi and Ikeda [ 16 ] reported that African rice species, Oryza glaberrima and O. barthii , showed much severer systemic necrosis compared to the other rice species present in South and Southeast Asia after inoculation of both RTBV and RTSV. Here, we have characterized RTBV-like sequences in the Japonica (cv. Nipponbare) genome. These sequences, denoted endogenous RTBV-like sequences (ERTBVs), were highly rearranged and dispersed throughout the rice genome. Sequences of the putative viruses for ERTBV were reconstructed from the dispersed segment in the genome. Copy numbers of ERTBV segments are shown to vary among AA-genome Oryza species. Asian species have more ERTBV segments than the species originated from the other regions where RTBV is not distributed. The results obtained advance our understanding of the manner of integration of authentic pararetrovirus into the host genome, evolutionary implication of the integrated virus and possible involvement of endogenous virus segments in the corresponding disease resistance. Results Identification of RTBV-like sequences in the rice genomes Previously, we found a repetitive sequence near the rice waxy gene, which is partially homologous to the rice tungro bacilliform virus (RTBV) genome [ 12 , 17 ]. A probe of this segment hybridized to about 30 bands in Eco RI-digested fragments from both Japonica and Indica genomic DNAs [ 12 ]. In the present study, we collected 29 RTBV-like sequences from the rice genome databases for Japonica (cv. Nipponbare). The segments collected here had ample length for further analyses. The segments of ERTBV were distributed throughout the rice genome. Structural differences among the collected ERTBV segments appeared to be due to rearrangements of the segments including deletions, insertions, inversions and duplications. None of the segments had the same structure as the virus or seemed likely to be active as virus. However, the similarities among the ERTBV segments were scored as more than 80% (described in detail in below), so that each homologous part in the ERTBV segments was easily recognized. Most of the ERTBV segments are flanked by AT-repeated sequences (Table 1 ), which might be involved in the integration mechanism. Table 1 Summary of the ERTBV structures in the rice genomes 1 . Chr. 2 Accession Number ERTBV position (length) 3 Cluster 4 alignment of gene 5 AT-repeated sequence 6 Intergenic region Region x ORF y (MP/CP/PR) ORF y (RT/RH) ORF z 5'-end 3'-end [Japonica] 1 AP003338 31237-38745 (7509) C 32277-31237 38711-38217 38259-34814 34534-33094 33127-32278 34 (2) 153 (0) 38745-38712 2 AP006160 a 128189-135399 a C 128189-128420 a 128421-128915 a 128873-129447 a 134248-132808 a 132841-131989 a 97 (0) a 12 (0) b AP004842 b 1-7610 b (11686) 131988-131526 a 7379-6885 b 130212-131451 a 135399-134914 a 134913-134534 a 7610-7380 b 5595-3136 b 6927-6352 b 4 AL606628 47001-48868 (1868) B - - 47001-47054 47334-48768 48756-48868 16 (0) 45 (391) AL606618 82165-88112 (5948) B - 88112-87631 87673-84239 83959-82532 82544-82165 13 (678) 156 (48) AL606592 36282-40413 (4132) B 39437-40413 - 36282-36894 37174-38614 38602-39436 65 (0) 101 (17) AL662971 104278-111739 (7462) C 105283-104278 111720-111226 111268-107823 107543-106102 106135-105284 65 (727) - 111739-111721 AL607003 63290-71598 (8309) A 63406-64469 64470-64882 64846-68248 68532-69972 63290-63405 52 (68) 151 (265) 70794-71598 69939-70793 5 AC107085 22244-29756 (7513) B 22436-22244 28859-28374 28416-24971 24691-23258 23270-22437 25 (0) 55 (64) 29756-28860 6 AP002542 33961-41438 (7478) B 39087-38121 38120-37636 37678-34233 39121-40541 40529-41362 216 (2) 252 (1) 41363-41438 AP006056 28996-33700 (4705) C 29562-28996 - 33700-32101 31821-30381 30414-29563 93 (10) 337 (87) AP004750 97242-104472 (7231) A 98061-97242 104472-103986 104022-100607 100323-98883 98916-98062 39 (178) 52 (694) 7 AP006163 118513-126010 (7498) C 118513-118518 118519-119013 118971-122416 122696-124136 124103-124954 82 (502) 224 (129) 124955-126010 AP005719 363-7932 (7570) C 3278-2211 2210-1716 1758-363 5526-4096 4129-3279 65 (100) 33 (2) 7932-5806 AP004348 17568-24897 (7330) A 18513-17568 24897-24437 24473-21059 20775-19335 19368-18514 96 (100) 37 (20) 8 AP005164 171654-179236 (7583) C 173775-174838 174839-175333 175291-178760 171654-172956 172923-173774 52 (284) 274 (11) 179071-179236 AP003883 117668-125143 (7476) C 117668-117743 117744-118238 118196-121641 121921-123361 123328-124179 54 (612) 41 (16) 124180-125143 AP003914 22973-25201 (2229) A - - - 23074-24514 24481-25201 373 (14) 1136 (0) AP005301 34330-41566 (7237) A 34330-34741 34742-35228 35192-38611 38895-40314 40281-41135 153 (14) 34 (23) 41136-41566 AP005159 88879-97300 (8422) B 88879-89828 89829-90315 90273-93716 93996-95435 95423-96256 179 (0) 34 (19) 96257-97300 9 AP005424 11998-18576 (6579) C 18576-17867 11998-12492 12450-15849 16129-17569 17536-17833 57 (10) 95 (225) AP005860 50709-58281 (7573) A 50709-50806 50807-51295 51259-54579 54863-56304 56271-57124 218 (0) 8 (3) 57125-58281 10 AC119147 89355-102382 (13028) B 90235-89355 101319-100834 99260-96143 95863-94424 94436-93603 71 (0) 183 (68) 93602-93432 100876-100548 102382-101320 AC027660 24299-31769 (7471) A 29370-28257 28256-27768 27804-24390 31632-30192 30225-29371 - 28 (520) AC069300 89901-96619 (6719) A 90209-89901 96619-96133 96169-92755 92471-91031 91064-90210 21 (162) 21 (688) 11 AC135957 69527-81251 (11725) A 73392-74286 81251-80765 69527-70846 71130-72570 72537-73391 368 (619) - 75398-74475 80801-77387 75444-75410 12 AL713945 45991-49426 (3436) B 47029-45991 - - 49291-47851 47863-47030 55 (1) 261 (9) AL731743 14231-18608 (4378) B 17596-18608 14768-14283 14325-14231 15333-16774 16762-17595 - 44 (40) 14791-15053 AL928780 103187-110757 (7571) A 103187-103406 103407-103893 103857-107273 107665-109105 109072-109926 44 (25) 25 (32) 109927-110757 AL928749 6275-11538 (5264) A 7149-6275 - 11538-9695 9411-7971 8004-7150 479 (127) 624 (0) [Indica] 4 AB124591 554-4677(4124) B 3709-4677 - 554-1166 1446-2886 2874-3708 43(0) 105(26) ND AB124592 8867-14510(5644) C 10990-12051 12052-12546 12504-14510 8867-10171 10138-10989 64(273) unknown ND AB124593 158-5914(5757) C 4214-5914 - 158-1677 1957-3397 3364-4213 157(0) 62(2) 1 The sequences were mined from Japonica database or investigated from phage clones isolated from Indica (IR36) genomic library. 2 Chromosome no. on which the ERTBV segment resides. 3 Nucleotide positions of ERTBV in the registered genomic clone. Parenthesis indicates a length of ERTBV sequence. 4 Clusters into which the individual ERTBV sequences were phylogenetically grouped. 5 The region belongs to the part of ERTBV, and their nucleotide positions in the clone registered in the database. 6 The numbers indicate repetition times of AT at both the ends of ERTBV, and parenthesis indicates distance (bp) from the ERTBV. a and b These clones contain the identical ERTBV, but both the clones ended within the ERTBV sequence. Assembling ERTBV segments We sorted out the 29 ERTBV segments using the sequences homologous to the RT gene, which is encoded in the end of ORF 3. Similarity analyses based on the RT gene grouped them into three clusters (Figure 1 and Table 1 ), suggesting the presence of three independent ERTBV sequence families. The discontinuity of the three clusters allows us to predict independent integration events for each of the ERTBVs into certain rice species genome(s). We then attempted reconstruction of the complete ERTBVs from the three clusters present in the phylogenetic tree. Approximately 7.5-kb circular virus-like structures could be reconstituted by assembling common parts in individual ERTBVs. The assembled virus-like sequences, which are designated as ERTBV-A, -B and -C, encode potentially functional ORFs. The nucleotide similarities among ERTBVs range from 82% to 93%, and therefore the segments are clearly distinguished in any of the clusters. Of the four ORFs in RTBV, ORF 3 and 4 correspond to ORF y and z of ERTBVs, but ORF 2 is absent from ERTBVs (Figure 2A ). Nucleotide sequence of ORF 1 showed a 49% of homology to Region x of ERTBVs, while we failed to find ORF from the Region x sequences (Figure 2A ). Pararetroviruses form a circular double-stranded DNA genome (Figure 2B ), therefore, it is reasonable to believe that the authentic ERTBV viruses had a similar structure. It seems that the integration of ERTBVs did not occur randomly since more than a half of the ERTBV ends connected with rice genomic DNA were in the putative intergenic region (IGR) (Figure 2B ). In addition, the other common junctions are found in the middle of ORF y (Figure. 2B ), which corresponds to the location of the discontinuities in the open circular form of RTBV [ 18 ]. These structures may indicate that the integration process occurred after the reverse transcription of the virus genome. Figure 1 The phylogenetic tree based on reverse transcriptase (RT) gene of 29 ERTBV segments and RTBV. These ERTBV were collected from the rice genome database (Table 1). The nucleotide sequences were aligned using the CLUSTAL W program [35] from the DNA Data Bank Japan (DDBJ). The method detailed of construction of the tree was described in the text. These sequences were fallen into three clusters, ERTBV-A, -B and -C. Numbers above the nodes are bootstrap support based on 100 bootstrap replicates for all branches were resolved on the strict consensus tree. Figure 2 Deduced virus form of ERTBV that was assembled from the rice genomic sequences. A: Comparison of the assembled ERTBV and RTBV. Percentages indicate the nucleotide similarity of each of the corresponding segments or ORFs between ERTBV and RTBV. ERTBV lacks ORF 1 and 2. The assembled sequences designated as ERTBV-A, -B and -C have 7526 bp, 7496 bp and 7499 bp in length, respectively. Their assembled sequences consist of intergenic region (IGR) (A: 1–1114; 1114 bp, B: 1–1066; 1066 bp: C: 1–1063; 1063 bp), Region x (A: 1115–1600; 486 bp, B: 1067–1552; 486 bp, C: 1064–1558; 495 bp), ORF y (A: 1570–6702; 5133 bp, B: 1519–6672; 5154 bp; C: 1525–6678; 5154 bp) and ORF z (A: 6702–7523; 822 bp, B: 6672–7493; 822 bp, C: 6678–7496; 819 bp). Identical organizations of ORFs and their orders were observed in their structures. The nucleotide sequence for Region x corresponds with ORF 1, but ATGs for initiation codon were not present. ORF 3 contains movement protein (MP), coat protein (CP), asparatic protease (PR) and RNase H (RT/RH) [19]. B: Schematic representation of the junction sites of the ERTBV segments adjoining the rice genomic sequence. The junctions are indicated by vertical bars on the circular virus form of ERTBV. The figure shows the number of junctions of all the examined segments referred to Table 1. The different colors in the circle correspond to the above-mentioned segments. The junctions are concentrated in the IGR, which contains the transcriptional initiation and terminal overhanging segments. The longest ORF in RTBV, ORF 3 encodes the movement protein (MP), coat protein (CP), asparatic protease (PR), RT and RNase H (RH) in the single polycistronic mRNA [ 19 ]. ORF 3 mostly parallels ORF y in ERTBV-A, -B and -C. Similarities within these nucleotide sequences between the RTBV and ERTBVs were around 50%. The amino acid identity of the genes in ORF 3 ranged from 63% for RT/RH to 40% for PR genes. With respect to RT and RH genes in ORF 3, all characteristic motifs and invariant amino acids for individual genes were preserved in the corresponding ORF in each consensus ERTBV (Figure 3 ). Therefore, the putative genes in consensus ERTBVs potentially encode proteins comparable to those in RTBV. Figure 3 Amino acids sequence alignments for RT and RH domains of RTBV and the assembled ERTBVs. The alignments were performed with the CLUSTAL W program and the conserved motifs are shown encompassed by yellow. The numbers after each motif indicate the numbers of the amino acids, which are not conserved. Conserved amino acid residues are marked with an asterisk. Invariant amino acids are highlighted in red above the sequences. To evaluate the genetic relationship of ERTBVs and RTBV, RT amino acid sequences from the viruses belonging to Caulimoviridae, were compared. Using the PHYLIP package program [ 20 ], the phylogenetic tree was constructed for 14 kinds of viruses in Caulimoviridae (Figure 4 ). RTBV and ERTBV-A -B and -C were found to be most closely located in the RT peptides dendrogram among the Caulimoviridae viruses. These results strongly suggest that ERTBVs are virus in origin and are closely related with RTBV. Figure 4 Neighbor-joining dendrogram of putative RT amino acid sequence relationships among species of the different genera of the Caulimoviridae family. The dendrogram was bootstrapped 100 times (percent scores shown at nodes) and rooted on a random sequence. No sequences exactly matching RTBV per se were found in the databases for Japonica cv. Nipponbare. We conducted Southern hybridization analysis to see whether RTBV-homologous sequences are present in 14 lines from Oryza AA-genome species (Table 1 ). The hybridization patterns probed with RTBV sequence resulted in faint and indistinct bands (data not shown). Periods of integration of ERTBV segments into the rice genome To investigate the periods of integration of ERTBV, we attempted to obtain ERTBV sequences from an Indica variety (cv. IR36) using the RTBV-like sequence near the waxy locus as a probe. We thereby isolated three clones carrying ERTBV-homologous sequences (Table 1 ). Indica clone, AB124591, was found to have the same ERTBV sequence as that found in Nipponbare accession AL606592 (Table 1 ), indicating that the ERTBV integration events occurred before the Japonica-Indica differentiation. The other two Indica clones do not correspond with any ERTBV segments from Nipponbare. Except for the sequences examined here, we could not find any other RTBV-like sequences in database searches using RTBV nor each of ERTBVs sequences as queries. Therefore, a fourth cluster of the RTBV-like sequences is unlikely to be present. The integration of ERTBV or its derived segments after the differentiation of Japonica and Indica cultivars thus seems to have not occurred. Distribution of ERTBVs in the Oryza AA-genome species To test whether other Oryza species contain ERTBV in their genomes, Southern blotting experiments were performed with 14 lines of the Oryza AA-genome species. A PCR fragment of the 7.4-kb ERTBV sequence from chromosome 10 was prepared as a probe, and Figure 5 shows the discrete bands and varying copy numbers revealed by the hybridization patterns. Each accession or cultivar of O. sativa and O. rufipogon (lanes 1–8) has about 50 bands, some of which showed common sizes among the lines. An Australian rice ( O. meridionalis ) and two O. longistaminata accessions showed middle-copy numbers (approximately 10–20) of the ERTBV segments. In O. glaberrima , O. barthii and O. glumaepatula accessions, only a few bands hybridized to ERTBV; this may also be caused by divergence of the ERTBV sequence and not only due to lower copy numbers of the sequence. Especially in These three species derived from Africa and Latin America were genetically distinct from Asian rice species, but another African rice species, O. longistaminata, was considered to have undergone introgression with Asian species [ 21 ]. Africa and Latin America are regionally isolated from rice tungro disease. Figure 5 Southern blotting patterns for the genomic DNAs from 14 Oryza lines probed with 7.4-kb ERTBV fragment. The numbers above the blots correspond to the numbers of the materials (Table 2). The regions are the origins of the materials. Some accessions/lines of O. sativa , O. rufipogon and O. longistaminata are being used as the sources of resistance against tungro disease.. Methylation of ERTBV in Oryza AA-genome species Since high-copy-number sequences generally tend to have a heavier methylation state than low-copy-number sequences, we investigated the methylation state of ERTBVs in several Oryza species with various copy numbers. The methylation states were analyzed by Southern blotting method using a methylation-sensitive enzyme, Hpa II, and a partially methylation-sensitive isoschizomer, Msp I. The 7.4-kb probe was employed to examine the methylation states of the ERTBV in the Oryza AA-genome species. The blotting patterns of O. sativa (Shimokita), O. rufipogon (W1954), O. longistaminata (W1034), O. meridionalis (W1625), O. barthii (W1592), O. glumaepatula (W1185) showed differences of methylation state depending on the ERTBV copy number (Figure 6 ). In the high-copy-number species, O. sativa and O. rufipogon , the Msp I and Hpa II digests of DNA clearly showed different digestion patterns, and in particular, most of the small bands in the Msp I digests were not observed in the Hpa II digests, indicating that these ERTBV sequences were considerably methylated. Although the results of blotting for the middle-copy-number species, O. longistaminata and O. meridionalis , also showed the presence of methylcytosine within their ERTBV sequences, some bands in the Msp I digests were shared with the Hpa II digests. Preferential digestion of DNA from the low-copy-number species, O. barthii and O. glumaepatula , compared to DNA from the other species was observed. The above results indicate that the copy number of the ERTBV sequences in the Oryza genomes is correlated with the methylation level. A chloroplast DNA fragment [ 22 ] was used as a control probe to confirm the completeness of digestions (data not shown). Figure 6 Methylation state of ERTBV in the genomic DNAs from the Oryza AA-genome species. Each genomic DNA was digested with Msp I (M) or Hpa II (H) as described in Materials and Methods. Differential hybridization patterns between the Msp I and Hpa II digests observed in O. sativa and O. rufipogon show heavier methylation compared to the others, and O. longistaminata indicates possession of methylated ERTBV segments in the genome. Discussion Completion of ERTBV via integration of the virus Our data suggest that the putative virus for ERTBVs has been integrated into the Oryza genomes at least three times. These putative viruses are thought to be closely related to RTBV and to form circular double-stranded DNA. Cleavage of circular DNA molecules or open circular forms should be required for integration of the infecting virus. One of the preferential cleavage sites of ERTBV was mapped within a putative promoter segment of the authentic ERTBV sequence. Integrated sequences of TPVL in tobacco [ 8 ] and hepatitis B (hepadna) virus in human liver [ 23 ] were also found to have preferred junctions with their host genomes at a similar region to that seen in ERTBV. Jakowitsch et al . [ 8 ] proposed that the open circular form of the virus during the process of replication was involved in integration, and the free ends of the virus DNA molecule might contribute to integration or recombination. The ends of the ERTBV segments likely correspond with IGR and the putative discontinuities of RTBV (Figure 2B ), which possibly functions in transcription and replication initiation or in the priming of DNA strand synthesis [ 18 ]. This fact accords with Jakowitschs' idea that the preferential integration occurred while the virus was in the process of replication (Figure 7 ). In addition to the preferred sites for integration within the virus DNA, we found that 93% of the ERTBV ends were flanked by AT-repeated sequences. This high probability of the presence of AT-repeated sequences adjoining ERTBV led us to postulate that the AT tracks have facilitated or are associated with integration of the virus DNA into the host genome (Figure 7 ). Transgenes introduced by particle bombardment into the Arabidopsis genome were preferentially delivered to AT-rich scaffold/matrix-attached region (S/MAR)-like sequences [ 24 , 25 ]. SINE integration sites in the Brassica genome show strong affinity for S/MAR-like sequences [ 26 ]. Similar processes accounting for these two instances might also function in the case of integration of the virus for ERTBV. Our data alone, however, are unable to distinguish between whether ERTBV integrated into the AT-repeat sequences or whether ERTBV accompanied the AT-repeat sequences in their integration (Figure 7 ). Figure 7 Two hypothetical processes for the integration of the putative virus for ERTBV into the rice genome. DNA strands after the reverse transcription step of the virus were targeted to AT-repeat sequences (left), or AT-repeat sequences became attached to the virus segments during the process of the reverse transcription and the complex was integrated into the rice genome (right). Relationship between ERTBV and RTBV Although the genomes of ERTBV and RTBV are structurally similar, particularly in the longest ORF, some regions are markedly different. Phylogenetically, both are apparently closely related viruses. One important question is whether or not ERTBV is a cognate of RTBV. ERTBVs existed in the Oryza AA-genome species before differentiation of Japonica and Indica. Considering this evolutionary period, two possible relationships of RTBV and ERTBV might be predicted: one is that the virus that was to become ERTBV was a direct progenitor of RTBV, and the other is that both were differentially branched from a common ancestral virus. Because the evolution of virus genomes is generally much faster than that of plant genomes, we cannot compare them equivalently. In fact, rapid evolution of RTBV was inferred from high level of genetic diversity of RTBV field isolates [ 27 ]. Even in a single field in the Philippines, more than one RTBV isolate could be observed, and the genotype changes year by year. Comparison of the sequences of several different isolates revealed evidence for incidences of nucleotide substitution, insertion/deletion and recombination occurred during differentiation of RTBV isolates [ 28 ]. Particularly, it was suggested that recombination had played a role in the evolution of RTBV [ 29 ]. If ERTBV is a direct progenitor of RTBV, recombination events might have contributed as a driving force to establish the present RTBV form. The longest ORF (ORF 3) of RTBV is functionally essential [ 30 ] and is thought to have been conserved since ERTBVs were present as viruses, but the other less homologous segments might have gradually undergone substitution by recombination. If RTBV was derived from the virus that became ERTBV, estimation of the nucleotide substitution rate of the genes common to RTBV and ERTBV would allow us to compare the evolutionary rates of a plant genome and a plant virus. By such a comparison, we estimated the virus evolution ranged from 30 to140 times faster than that of the host genome. The faster evolution of a virus was thus substantiated for the first time in plants if the virus for ERTBV was in fact the progenitor of RTBV. The different evolutionary rates are dependent on the virus genes; that is, the slow evolution might reflect the functional conservation of the gene. In the other case, in which RTBV and the virus for ERTBV are phylogenetically located on different branches, the progeny of the virus corresponding to ERTBV might have vanished or may be hidden in a small population. Even though RTBV is not in the case a direct progeny of the virus corresponding to ERTBV, their structural similarity and parallel distribution lead us to consider their common ancestral origin. Correlation between rice tungro disease and ERTBV Plant virus-like sequences have been found in several plant genomes such as banana, tobacco and petunia [ 11 , 31 ]. So far, no association between virus disease and endogenous virus sequences has been reported [ 32 ]. Kobayashi and Ikeda [ 16 ] reported that O. glaberrima and O. barthii showed severe systemic necrosis within 4 weeks after infection of RTBV and rice tungro spherical virus (RTSV). O. longistaminata , which possesses ERTBV fragments in its genome, showed disease symptoms like those of the Asian species, and some of the accessions were utilized for obtaining the resistance gene [ 29 ]. Interestingly, this species originated from Africa where RTBV is not distributed. The fact led us to suppose that there is a correlation between presence or absence of ERTBV in the genome and the degree of RTBV susceptibility. The species, which have a low-copy-number of ERTBV tend to be vulnerable to the rice tungro disease caused by both RTBV and RTSV. The methylation of ERTBV appeared to be positively related in the copy number in the genome. Based on a study on the endogenous virus sequences (EPRV) in tobacco, Mette et al . [ 33 ] proposed a model in which methylation dependent on the copy number of endogenous virus sequences may induce episomal viral methylation through a homology-dependent process involving DNA-DNA or RNA-DNA interaction. The phenomenon observed here fits their model. The copy number of EPRV in the tobacco genome is 10 times as high as that of ERTBV in the rice genome. Our results demonstrated that about 50 copies of endogenous elements are sufficient to induce methylation in the genome. If we ever find the rice germ lines that have incorporated sequences more similar to those of RTBV, as well as ERTBV in germ lines, those would be exploited as valuable sources of stronger resistance against the rice tungro disease. Conclusions The rice genome contains more than 30 of RTBV-like sequence (ERTBVs) which were unlikely to have functional potential as a virus, while we were able to assemble putative virus forms from these sequences. The phylogenetic analysis showed that at least three times integrations of authentic ERTBVs occurred during Oryza speciation. ERTBV integrations likely occurred when the virus was in the replication process, and were preferentially targeted to AT-repeat sequences. The closely relationship between ERTBV and RTBV were proven by comparisons of the DNA and amino acid sequences. The Oryza AA-genome species originated from RTBV-distributed regions appeared to contain higher copy numbers of ERTBV segments. The methylation state of the ERTBV sequences was correlated with their copy number in the genome. The results obtained allowed us to speculate a possible relationship between RTBV disease resistance and the copy number and/or DNA methylation of ERTBV in the Oryza AA-genome species. Methods ERTBV sequences from Japonica Sequences of ERTBV in Japonica (cv. Nipponbare) were mined with rice blast search queries [ 34 ] against the rice genome sequences that had been registered as of June 2003. Twenty-nine ERTBV sequences were found in the following Japonica genomic database (Table 1 ). ERTBV sequences from Indica We attempted to search for ERTBV sequences in the Indica (cv. 93–11) genome database, however, the homologous sequences found through the search had insufficient length for designation as ERTBV segments. Indica ERTBV sequences were isolated from the EMBL 3 genomic library constructed with IR36 strain (FL1041j), which was purchased from Clontech (Palo Alto, California). For screening, a 3.5-kb ERTBV fragment about 50-kb upstream of the waxy locus was used as probe [ 17 ]. Three clones carrying an ERTBV-containing segment of more than 4 kb were selected. Nucleotide analysis was performed with using a d-Rhodamine Terminator Cycle Sequencing Ready Reaction-Sequencing Kit (Applied Biosystems) and an ABI377 Automated DNA Sequencer (Applied Biosystems). Construction of phylogenetic trees The nucleotide sequences and amino acids sequences inferred from the reverse transcriptase (RT) gene were aligned using the CLUSTAL W program [ 35 ] from the DNA Data Bank Japan (DDBJ). We calculated the pairwise nucleotide divergence (K) between 30 independent ERTBV sequences (including RTBV) based on Kimura's two-parameter method [ 36 ] without taking synonymous and nonsynonymous changes into account. We constructed a neighbor-joining (NJ) tree based on these estimates [ 37 ]. The tree was drawn using PAUP*4.0 [ 38 ]. The consensus maximum parsimony and NJ trees based on amino acid sequences for RT in 14 viruses including ERTBV-A, -B and -C were calculated using programs from the PHYLIP package [ 20 ]. The minimum evolution tree was calculated by the implementation of PAUP software in the GCG package. Southern hybridization Total genomic DNA was isolated from 7 Oryza AA-genome species including 14 strains (Table 2 ). Eco RI-digested DNA was separated by 0.7% agarose gel electrophoresis. The resultant DNA was transferred to nylon membranes (Pall: Biodyne B), and hybridized using the Alk Phos Direct Southern hybridization kit (Amersham Life Science). For the probe, nearly the full length of the 7.4-kb ERTBV fragment (located on chromosome 10, BAC clone accession no. AC069300) was amplified by PCR with the primer combination of 5'GAACTACAACTAGATATGAACGGGGATA3'+5'CACAACTATTCTTAGTGCTGAATTCACTT3'. The membranes were washed twice under the standard Alk Phos conditions with 0.5 M NaCl at 42°C for 20 minutes. To test the methylation state of ERTBV, Southern blotting analysis was carried out using the C-methylation-sensitive enzyme Hpa II and the partially sensitive enzyme Msp I (isoschizomer of Hpa II). The same probe mentioned above was prepared using a PCR-based labeling system with the PCR DIG labeling mix (Roche). To verify that complete digestion was achieved by the enzymes, a chloroplast DNA fragment, the 5.2-kb Sma-8 fragment of buckwheat [ 22 ], was used as a control probe. Table 2 Plant materials used. Sample Species Cultivar or accession Remarks 1 O. sativa Shimokita Japonica from Japan 2 O. sativa T65wx Near-isogenic line of Taichung 65 with wx from Kinoshitamochi (BC12) 3 O. sativa 221 Javanica type from Indonesia 4 O. sativa PTB10 Indica type from India 5 O. rufipogon W107 Annual type from India 6 O. rufipogon W120 Perennial type from India 7 O. rufipogon W1717 Perennial type from China (through IRRI) 8 O. rufipogon W1718 Perennial type from China (through IRRI) 9 O. glaberrima W025 From Guinea 10 O. barthii W1592 From Cameroon 11 O. glumaepatula W1185 From Surinam 12 O. meridionalis W1625 From Australia 13 O. longistaminata W1034 From Nigeria 14 O. longistaminata W1572 From Nigeria Sequence data The sequences containing Indica ERTBV have been deposited in DDBJ: accession nos. AB124591, AB124592 and AB124593. The reconstructed sequences for the authentic ERTBV viruses, ERTBV-A, -B and -C were deposited in DDBJ: accession nos. BR000029, BR000030 and BR000031, respectively. Authors' contributions MoKu and MaKa carried out the molecular genetic studies and participated in the sequence alignments. HN participated in the sequence alignment and performed the phylogenetic analysis. IU participated in the design of the study. YK conceived of the study and drafted the manuscript. YK and YS participated in its design and coordination. All authors read and approved the final manuscript.

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523231

Reconstructing Neural Circuits in 3D, Nanometer by Nanometer

Understanding how the brain processes and stores information depends in large part on knowing which neurons are involved in a particular process and how they're organized into functional networks. Each of the 10 billion or so neurons in the brain has thousands of connections to other neurons, sending (via axons) or receiving (via dendrites) the signals that allow us to think. Each neuron can transmit signals to both local and distant neurons, and it is by mapping these networks that neuroscientists can discern correlations between neural connectivity and physiological responses and ultimately unveil the computational algorithms underlying brain function. Since the beginning of cellular neuroscience at the end of the 19th century, neuronal connections have been explored by tracing axons and dendrites under the light microscope. But even with the resolution of state-of-the-art light microscopy, this approach works only if a small subset of neurons is stained and thus leaves most of the network hidden. Electron microscopy, on the other hand, can provide the spatial resolution necessary both to resolve processes in densely packed neural “wire bundles” and to identify synapses faithfully, but individual electron microscopic images are restricted to two dimensions. Transmission electron microscopy provides cross-sectional images through tissue, while scanning electron microscopy typically provides the appearance of 3D but in reality maps only the specimen surface and is thus blind to the connections within. It's possible to wrest 3D information from the transmission electron microscope by using tilt-series tomography, but sections can't be much thicker than 1 micron (a millionth of a meter). Data from thicker volumes can be obtained, but the process so far has been so painstaking and time-intensive—it involves, among other labor-intensive tasks, manually reconstructing serial sections—that few undertake it. It should, however, be possible to get similar data with “serial block-face imaging,” which involves repeatedly cutting section after section from a plastic-embedded block of tissue and photographing what's left. Scanning electron microscopy is needed for this task, but sample preparation methods are like those used for transmission electron microscopy, albeit with a few additional steps to enhance contrast. Neurite Reconstruction Manual reconstruction of selected processes in cortical tissue This is exactly what Winfried Denk and Heinz Horstmann have done to obtain “truly 3D datasets” using a method they call “serial block-face scanning electron microscopy” (SBFSEM), for which they constructed a “microtome” that goes inside the scanning electron microscope chamber. The resolution achieved is sufficient to reveal “even the thinnest of axons” and identify synapses. The SBFSEM method can generate stacks of thousands of ultra-thin sections, 50–70 nanometers (a nanometer is a billionth of a meter) thick, generating 3D datasets to reconstruct the topology and circuitry of neurons in brain tissue. The authors' custom-designed microtome holds the tissue block in a way that ensures image alignment and maintains focus; all the while the specimen surface is positioned close enough to the objective lens to allow high-resolution imaging. Denk and Horstmann expect that with this method they might ultimately be able to cut sections thinner than the 50 nanometers that their current setup manages. This then would allow them to cut sections even thinner than what is routinely possible in conventional transmission electron microscopy. While the authors doubt that the lateral resolution will ever reach that of transmission electron microscopy, they also argue that such high resolution may not actually be needed to trace neuronal connectivity. On the other hand, the method accelerates 3D electron microscopic data collection “by several orders of magnitude” by obviating the need for the labor-intensive adjustments to correct alignment and distortion required by other methods, an advance that is crucial for large-volume neuroanatomy and might, in addition, open up many hitherto inaccessible problems to ultra-structural investigations.

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554085

Human neuroglobin protein in cerebrospinal fluid

Background Neuroglobin is a hexacoordinated member of the globin family of proteins. It is predominantly localized to various brain regions and retina where it may play a role in protection against ischemia and nitric oxide-induced neural injury. Cerebrospinal fluid was collected from 12 chronic regional or systemic pain and 5 control subjects. Proteins were precipitated by addition of 50% 0.2 N acetic acid, 50% ethanol, 0.02% sodium bisulfite. The pellet was extensively digested with trypsin. Peptides were separated by capillary liquid chromatography using a gradient from 95% water to 95% acetonitrile in 0.2% formic acid, and eluted through a nanoelectrospray ionization interface into a quadrapole – time-of-flight dual mass spectrometer (QToF2, Waters, Milford, MA). Peptides were sequenced (PepSeq, MassLynx v3.5) and proteins identified using MASCOT ® . Results Six different neuroglobin peptides were identified in various combinations in 3 of 9 female pain subjects, but none in male pain, or female or male control subjects. Conclusion This is the first description of neuroglobin in cerebrospinal fluid. The mechanism(s) leading to its release in chronic pain states remain to be defined.

Background The protein constituents (proteome) of cerebrospinal fluid (CSF) are altered in disease states such as meningitis, but may also be more subtly altered in many other neural conditions. CSF has been difficult to investigate because of the need for invasive lumbar punctures and the small volumes of CSF available for analysis. This situation is now rapidly changing as methods requiring microliter volumes and sophisticated analysis tools such as proteomics become available [ 1 , 2 ]. Proteomics has made it possible to identify scores of proteins that have not been previously discovered in this fluid. One such protein is neuroglobin. Neuroglobin is a recently identified member of the globin family. It binds oxygen with an affinity between that of myoglobin and hemoglobin [ 3 , 4 ]. Neuroglobin is 151 amino-acids long with a molecular mass of ≈ 17 kDa. The mouse and human genes are 94% identical. Neuroglobin is an ancient protein (estimated < 550 Myr old) that is more related to the annelid Aphrodite aculeate intracellular globin (30% identify) [ 5 ] than to vertebrate myoglobin (<21% identity) and hemoglobin (<25% identity) [ 3 ]. Human neuroglobin mRNA is predominantly expressed in brain with high signal in the frontal lobe, subthalamic nucleus and thalamus. The concentration is estimated to be less of 0.01% of the total brain protein content [ 3 ]. Neuroglobin protein has not been previously detected in cerebrospinal fluids. Results Neuroglobin Peptides Five peptides derived from neuroglobin (NCBInr ID accession 10864065) were identified using both the MASCOT software with NCBInr database and ProteinLynx Global Server with SwissProt database (Table 1 ). Two precursor ions with mass/charge (M/Z) ratios of 423.97 and 435.82 were identified in CSF sample #3 with the SwissProt, but not NCBInr, searches. Table 1 shows the mass-over-charge (m/z), charge state, elution time, position, sequence, molecular weight (M r ) for each peptide. The numbers of matching peptides were 5 in sample #1, 2 in sample #2, and 3 in sample #3. The peptides mapped 31.1%, 13.9% and 17.2%, respectively, of the total neuroglobin protein sequence. They matched amino acids 1–10 and 15–30 of the N-terminal and 131–151 of the C-terminal. Trypsin digestion missed cleavage sites at amino acids 18 and 146. Reproducibility was demonstrated by the consistent retention times for the same peptides from different subjects. No low abundance neuroglobin peptides were found in other samples. BLAST sequence analysis of all six peptides identified only one protein: hypothetical 16.9 kDa protein (neuroglobin: NREF and iProClass NF00135839; SwissProt/TrEMBL Q9NPG2). Table 1 Amino acid sequence of neuroglobin peptides identified from human CSF using CapLC nanoESI Q-TOF tandem mass spectrometry. # a Amino Acids M/z b Z c Molecular Weight Δ d Amino Acid Sequences Time e (min) Calc. Exp. 1 1–10 423.98 3 1268.65 1268.91 0.25 (-)MERPEPELIR(Q) 37.02 1 15–30 580.73 3 1738.95 1739.18 0.23 (R)AVSRSPLEHGTVLFAR(L) 42.94 1 19–30 442.99 3 1325.71 1325.95 0.25 (R)SPLEHGTVLFAR(L) 42.68 1 131–146 580.04 3 1736.87 1737.10 0.24 (R)AAWSQLYGAVVQAMSR(G) 68.23 1 131–151 761.42 3 2281.06 2281.23 0.17 (R)AAWSQLYGAVVQAMSRGWDGE(-) 74.49 2 131–146 580.02 3 1736.87 1737.03 0.16 (R)AAWSQLYGAVVQAMSR(G) 68.24 2 131–151 761.37 3 2281.06 2281.09 0.03 (R)AAWSQLYGAVVQAMSRGWDGE(-) 74.54 3 1–10 423.97 f 3 1268.65 1268.88 0.23 (-)MERPEPELIR(Q) 37.31 3 15–30 435.82 f 4 1738.95 1739.27 0.32 (R)AVSRSPLEHGTVLFAR(L) 43.27 3 19–30 442.99 3 1325.71 1325.96 0.25 (R)SPLEHGTVLFAR(L) 43.01 a. Subject Number b. Mass / charge ratio c. Charge d. Difference (error) between the experimental (Exp.) and calculated (Calc.) molecular weights e. Elution time expressed in minutes. f. Peptides in Subject 3 identified only with ProteinLynx Global Server using the SwissProt database. Mass Spectrometry Figures 1 through 5 show the tandem MS data for the 5 [M+H + ] precursor ions. The mass of each b- and y-fragment is listed. The amino acid sequence is shown at the top of each spectrum using the Roepstorff nomenclature [ 11 ]. The amino acid sequences were determined from both the N- and C-terminal directions. Figures 1 and 4 show two spectra from subject #1. Figures 3 and 5 show two spectra from subject #2. Figure 2 shows one spectrum from subject #3. Neuroglobin peptides were detected in 2 of the 3 CapLC runs for subjects #1 and #2, but only in 1 run for subject #3. Figure 1 The tandem mass spectrum is shown for the neuroglobin amino acid 1 to 10 peptide. In this and the following figures, the top line represents the b-series, and the 2 nd line the y-series. The x-axis presents M/z and the y-axis signal intensity. The numbers are the M/z values for each daughter ion (vertical lines). Figure 2 The tandem mass spectrum is shown for the neuroglobin amino acid 15 to 30 peptide. Figure 3 The tandem mass spectrum is shown for the neuroglobin amino acid 19 to 30 peptide. Figure 4 The tandem mass spectrum is shown for the neuroglobin amino acid 131 to 146 peptide. Figure 5 The tandem mass spectrum is shown for the neuroglobin amino acid 131 to 151 peptide. The peptides with M/z of 580 and 761 (Table 1 ) overlapped with the 761 ion having a missed tryptic cleavage point at Arg 146 . Additional peptides were not identified, perhaps because we did not reduce disulfide bridges to reveal additional trypsin digestion sites. However, all the identified peptides were specific for neuroglobin, and so were appropriate markers for fast identification of this protein. Neuroglobin and Pain Subjects Neuroglobin-derived peptides were found in 3 of 9 female pain subjects, but none of the 3 male pain subjects; it was not detected in the 3 female or 2 male control subjects. Within the chronic pain group there was no association between the presence of neuroglobin and clinical factors such as age, extent or duration of pain, or tenderness to pressure. No hemoglobin or cytoglobin [ 12 , 13 ] were detected. Discussion This is the first description of neuroglobin protein in the CSF of any species. Neuroglobin joins cytoglobin (histoglobin) in a new globin subfamily that forms hexacoordinated heme iron complexes [ 12 , 13 ]. These are distinct from the pentacoordinated hemoglobin and myoglobin. The source of neuroglobin in the CSF is likely to be brain regions such as the subthalamic nuclei (60% of total brain neuroglobin mRNA expression), frontal lobe, thalamus, occipital pole, pituitary gland, and medulla oblongata [ 3 , 14 ]. Immunohistochemistry confirmed this distribution with strong staining in the hippocampus, thalamus, hypothalamus (especially the paraventricular nucleus) and brainstem nuclei of cranial nerves [ 15 ]. Expression was often patchy within these regions indicating that only select neurons expressed neuroglobin. Regions with high sensitivity to hypoxia such as the cerebral cortex had constitutive expression [ 15 ]. Spinal cord was a less likely source since its neuroglobin mRNA expression was less than 10% of that from the subthalamic nuclei. Neuroglobin mRNA was expressed in the retina [ 16 ] and in peripheral nerves suggesting that the mRNA was axonally transported and translated to distal neurons [ 17 ]. The protein has a cytoplasmic distribution [ 18 ]. Neuroglobin could provide oxygen for high energy consuming processes such as synaptic activity, neural plasticity, or efferent transmitter release as in nociceptive nerve axon responses. Neuroglobin mRNA was also present in adrenal cells and the β cells of the pancreatic islets of Langerhans [ 14 ]. Roles in diabetes or hypoxia-induced insulin secretion are unstudied. These studies of mRNA expression should not be extrapolated into relative levels of protein expression or neuroglobin turnover since concordance between microarray and proteomic studies can be as low at 13% [ 19 ]. Neuroglobin is likely to serve as an intracellular oxygen depot to facilitate oxygen diffusion to the mitochondria. A role in oxygen supply was supported by the very high expression of neuroglobin mRNA in retinal neurons but not the supporting ocular epithelium and other structures [ 16 ]. Retinal neuroglobin concentrations were estimated at > 100 μM, compared to > 1 μM for the whole brain. The retinal and muscle oxygen tensions, oxygen affinities and tissue concentrations of neuroglobin and myoglobin were comparable suggesting that the two play homologous roles in their respective tissues. Neuroglobin might act in certain circumstances to limit neural cellular damage during hypoxia. Neuroglobin expression was inversely correlated to the sensitivity of the brain regions to ischemia [ 3 ]. For example, neuroglobin expression was 4 times higher in the cerebral cortex than the hippocampus, corresponding to the time for ischemia to cause half-maximal damage (19.1 and 12.7 min, respectively) in these tissues [ 20 ]. Neuroglobin-immunoreactive material was upregulated in the cytoplasm of neurons that were destined to survive acute cerebral ischemia, and was reduced in apoptotic neurons [ 21 ]. Hypoxic induction of neuroglobin was blocked by the mitogen-activated protein kinase/extracellular signal-regulated kinase kinase inhibitor PD98059 [ 22 ]. Like hemoglobin and myoglobin, hemin increased neuroglobin 4-fold through a separate signalling process mediated by protein kinase G and soluble guanylate cyclase. Hypoxia-inducible neuroprotective factor (HIF-1) that can induce β-globin production may play a role in neuroglobin induction. It is not clear if there are differential responses to intermittent, recurrent, or chronic cerebral ischemia. Neuroglobin was also colocalized with nitric oxide synthase in the lateral tegmental nuclei, stria terminalis, habencule, nucleus of the tractus solitarius, periaqueductal grey matter, amygdala and subfornic organ [ 23 ]. The protein may act as a nitric oxide scavenger, a role that has also recently been proposed for myoglobin [ 24 ]. This function would protect against nitric oxide – induced damage that is part of hypoxia – ischemia related neuron injury. Nitric oxide appears to bind to the hexacoordinated deoxy ferrous form (F8His-Fe 2+ -E7His) and displace the protein from the globin [ 25 ]. This affinity may be a double-edged sword, since neuroglobin, hemoglobin and myoglobin may protect Plasmodium and Trypanosoma from the antiparasitic effects of nitric oxide [ 26 ]. Neuroglobin may also play a protective role in carbon monoxide poisoning [ 27 ]. In this study, neuroglobin was qualitatively identified in CSF from 3 female subjects with chronic pain conditions. Females have greater pain sensitivity to pressure and other stimuli (lower pain thresholds) [ 28 ], but pain is not thought to induce neural hypoxia or any of the known triggers of neuroglobin expression [ 21 ]. It is tempting to speculate that the source of neuroglobin in our samples was from nuclei involved in pain transmission or regulation such as the thalamus, prefrontal cortex, amygdala, or spinal cord dorsal horn somatic pain synaptic regions (e.g. layers 1 and 2 of Rexed). The fact that neuroglobin was not detected in any of the control females in our study makes it unlikely that the expression was related to gender. Examination of additional normal and chronic pain subjects is underway to determine the factors that may be responsible for neuroglobin expression. It is also possible that the proteomic detection of neuroglobin varies depending upon sample preparation, signal-to-noise ratio for relatively low abundance proteins compared to albumin and immunoglobulins that are present in high abundance, duration of storage, factors related to trypsin digestion, capillary liquid chromatography, mass spectrometry or bioinformatic neuroglobin peptide detection. These technical factors are unlikely to be significant since our samples were treated identically and were stored for approximately equal amounts of time. In contrast to neuroglobin's localization, cytoglobin-immunoreactive material was localized to the cellular nucleus in all tissues examined [ 14 ]. Mammalian cytoglobin genes display an unique exon-intron pattern with an additional exon resulting in a C-terminal extension of the protein that is not present in lower species such as zebra fish [ 29 , 30 ]. Again, it is not clear if cytoglobin acts as an oxygen depot or sink, free radical scavenger, oxygen-sensor or transcription factor. No evidence for cytoglobin was found in cerebrospinal fluid suggesting that nuclear degeneration was not present in any of our subjects. Conclusion This is the first description of neuroglobin in cerebrospinal fluid and in humans. Neuroglobin was identified in 3 of 9 female pain subjects. The role(s) for this ancient oxygen and nitric oxide binding protein in humans, and potential links to pain, remain to be fully determined. Methods After obtaining informed consent, lumbar punctures were performed on 17 subjects as part of an evaluation of pain mechanisms. Twelve patients had musculoskeletal pain and five were healthy control subjects. Cerebrospinal fluid samples were aliquoted and frozen at -70°C. Lipids and peptides were extracted from 200 μl of thawed CSF by adding an equal volume of 50% ethanol, 50% 0.2 N acetic acid 0.02% sodium bisulfite ("acid-ethanol") [ 6 ]. Centrifuged pellets were reconstituted in 50 μl of 0.1 M ammonium bicarbonate buffer (pH 7.8) and digested with trypsin (protein-enzyme ratios of 20:1) at 37°C overnight. Digested peptides were separated by capillary liquid chromatography (CapLC, Waters, Milford, MA) over a Zorbax 18WSB reverse phase column (100 mm × 0.15 mm inner diameter) (Micro-Tech Scientific, Sunnyvale, CA) at room temperature for 100 min using a gradient starting at 95% solvent A (aqueous solution of 0.2% formic acid) and ending with 95% solvent B (acetonitrile with 0.2% formic acid). The elution was performed at a flow-rate of 1 μl/min. The column eluate was pumped through a nanoelectrospray interface into a quadrapole – time of flight (Q-TOF-2, Waters, Milford, MA) mass spectrometer. MASSLYNX version 3.5 software was used to control the CapLC and Q-ToF-2, data acquisition, processing, and determination of peptide sequences. The protein identification was performed with the MASCOT MS/MS ion search software and NCBInr protein database [ 7 , 8 ], and with ProteinLynx Global Server Web (Waters) with SwissProt database. The BLAST algorithm was used to compare protein queries to database sequences (e.g. Protein Information Resource, PIR, ) [ 9 , 10 ], proteins derived from GenBank coding sequences, and PDB atomic coordinates. Samples were assessed by CapLC-Q-ToF-2 in triplicate. At least 2 separate peptides from neuroglobin had to identify in each individual sample to ensure that this protein, and not a related protein, was present. In an attempt to detect low abundance expression of neuroglobin peptide ions that were not selected by MS-MS (false negative results), all MS data from the appropriate CapLC retention times were reassessed at high resolution. Positive results (MS data) were checked to see if ions in MS were present but not in MS-MS for other pieces. All putative neuroglobin peptide spectra were sequenced using PepSeq (Waters) and confirmed by visual inspection. Competing interests The author(s) declare that they have no competing interests. Authors' contributions Casado B 1,4 , Sample preparation, chromatography, mass spectrometry and manuscript preparation Pannell LK 2 , Supervision and assistance with chromatography and mass spectrometry and manuscript preparation Whalen G 1 , Sample preparation Clauw DJ 3 , Clinical investigation of subjects Baraniuk JN 1, *, Organization of study and selection of samples, preparation of manuscript

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493280

Color Doppler imaging of cervicocephalic fibromuscular dysplasia

Background Fibromuscular dysplasia (FMD) is a possible cause of stroke, especially in middle-aged women. However, only few reports are available on ultrasonographic detection and monitoring. Methods Among the 15,000 patients who underwent color Doppler imaging (CDI) of the cervicocephalic arteries during the study period, all cases fulfilling ultrasound criteria of FMD were included into the case series. Criteria of FMD were: 1. Segmental string-of-beads pattern, 2. Localization in the distal extracranial part of internal carotid artery (ICA) or vertebral artery (VA), and 3. (optional): Direct and/or indirect criteria of stenosis. Results CDI detected FMD in 39 vessels (37 ICA and 2 VA segments) of 21 patients. 16 patients had bilateral manifestation on ICA, one of those also on VA, bilaterally. CDI disclosed 4 symptomatic high-grade ICA stenoses, 3 of them underwent endovascular treatment. 5 patients with moderate symptomatic ICA stenoses got medical treatment. In 6 patients FMD was the most likely cause of headache and in one patient FMD was diagnosed as a cause of vertigo. Conclusions CDI may be used for detection of cervicocephalic FMD. Due to the unfavourable localisation of FMD for CDI, the sensitivity of CDI is lower in comparison to angiography. However, high-grade FMD stenoses that require invasive treatment can be recognized on the basis of indirect hemodynamic criteria.

Background Fibromuscular dysplasia (FMD) is a non-atheromatous, non-inflammatory arteriopathy of unknown etiology with segmental manifestation on medium-sized arteries in various regions of the body [ 1 ]. Manifestation on the renal arteries with the possible consequence of renovascular hypertension is remarkably frequent [ 2 ]. The cervico-cephalic arteries, especially the internal carotid artery (ICA) are attacked with an incidence of about 0.6 – 1%, often bilaterally [ 3 ]; manifestation also occurs on the vertebral artery (VA) [ 4 ]. The disease can occur at any age but is usually diagnosed in middle-aged, predominately female individuals [ 4 ]. Angiography reveals in most cases the typical string-of-beads pattern (fig. 1 ) with alternating regions of lumen narrowing and vessel dilatation over a length of 3 – 5 cm [ 3 ]; the proximal section of the ICA is generally not affected, except in a rare FMD subtype characterised by proximal involvement with a web-like membrane [ 5 ]. Figure 1 The string-of-beads sign with alternating regions of lumen narrowing and vessel dilatation on angiogram of the ICA (arrows) in a 52-year-old woman sufferning from recurrent transient ischemic attacks. Clinical manifestations of FMD on the ICA are transitoric ischemic attacks or cerebral infarctions [ 6 ] as well as unspecific symptoms such as headache and vertigo. In cases of cerebrovascular events, endovascular or surgical treatment is recommended [ 7 - 9 ], therefore detection of FMD is of considerable importance. Patients and methods Among the 15,000 patients who attended the neurosonography department of our clinic during the study period, 21 cases were identified fulfilling ultrasound criteria of FMD (Table 1 ). The presenting symptoms of the patients are listed in table 2 . Table 1 Color Doppler ultrasound criteria of FMD 1. Morphological criteria: Segmental string-of-beads pattern with alternating regions of lumen narrowing and vessel dilatation 2. Localization: Distal extracranial part of ICA (VA). 3. Hemodynamics (optional): Direct and/or indirect criteria of stenosis (in distal extracranial part of ICA / VA). Table 2 Patients and symptoms No. Age Male/female Symptoms 1 52 f Transient ischemic attack 2 55 f Bruit 3 55 f Headache 4 75 f Bruit 5 61 f Vertigo 6 53 f Pulsatile tinnitus 7 63 f Vertigo 8 65 f Amaurosis fugax 9 47 f Amaurosis fugax, vertigo 10 41 f Minor stroke 11 54 f Minor stroke 12 52 f Headache, vertigo 13 57 f Minor stroke 14 46 f Vertigo, bruit 15 73 f Bruit, headache, vertigo 16 55 f Headache 17 51 f Headache 18 62 f Headache 19 42 M Transient ischemic attack 20 62 f Transient ischemic attack 21 40 f Headache The color Doppler examinations were performed as described by Arning [ 10 ] and included the common carotid, external carotid, and internal carotid arteries as well as the vertebral arteries. CDI was performed with 5 MHz and 7 MHz linear array transducers using one of the following systems: Acuson Sequoia (Siemens AG, Erlangen, Germany), Toshiba Powervision 6000 or Toshiba Aplio (Toshiba Medical Systems Europe, Zoetermeer, Netherlands), or ATL HDI 5000 (Philips Medical Systems, Andover, MA). Results Using the criteria of table 1 , FMD was diagnosed in 21 patients (1 male, 20 female). In total, CDI detected FMD in 39 vessels (37 ICA and 2 VA segments). 16 patients had bilateral manifestation on ICA, one of those also on VA, bilaterally. 5 patients had unilateral manifestation on ICA. The degree of stenosis was low in 2 patients (Fig. 2 ) and moderate in the majority of cases (Fig. 3 , 4 , 5 ). 5 patients with moderate symptomatic ICA stenoses got medical treatment. 4 symptomatic high-grade ICA stenoses (Fig. 6 , 7 , 8 ) were detected, 3 of them underwent endovascular treatment (Fig. 9 ). In 6 patients FMD was the most likely cause of headache and in one patient FMD was diagnosed as the cause of vertigo, involving vertebral artery (fig. 10 ). Figure 2 The string-of-beads sign in the color Doppler image in a 51-year-old patient with low-grade stenosing FMD of the ICA. The patient suffered from migraine-like headache. Figure 3 FMD of the ICA in a 53-year-old woman suffering from headache. Power Doppler image of the left ICA shows the string-of-beads pattern. Figure 4 The same case as in fig. 3: Color Doppler and spectral Doppler examination of the left ICA revealing stenoses of about 70%. Figure 5 The same case as in fig. 3: Power Doppler image of the right ICA. Figure 6 High-grade stenosis of the ICA caused by FMD in a 52-year-old woman sufferning from recurrent transient ischemic attacks. CDI shows the string-of-beads pattern distally to a longer section of normal vessel. Figure 7 The same case as in fig. 6 (enlarged), showing the string-of-beads pattern distally to a longer section of normal vessel. Figure 8 The same case as in fig. 6: Spectral Doppler examinations reveal a high-grade stenosis. Figure 9 The same case as in fig. 6: Findings after endovascular treatment (stenting). Figure 10 The string-of-beads sign on the VA (C2-C1) in a in a 55-year-old woman with bilateral manifestation of FMD on ICA and VA. The patient suffered from vertigo. Discussion FMD is an uncommon angiopathy with an incidence on the ICA of about 0.6 – 1% [ 3 ]. However, the frequency of FMD detection by ultrasound imaging is considerably lower: 0,14% in our case series. Only few reports are available on the detection and monitoring of cervicocephal FMD with ultrasonography [ 11 - 14 ]. Ultrasound criteria of FMD correspond to those of angiography (Fig. 1 ). CDI reveals the segmental string-of-beads pattern with alternating regions of lumen narrowing and vessel dilatation (Fig. 2 , 3 ), distally to a completely normal segment of the vessel (Fig. 6 ). Dependent on the degree of stenosis, direct (Fig. 8 ) or indirect hemodynamic criteria may be recognized [ 14 ]. In comparison to angiography, the sensitivity of CDI is low: The vascular lesion can only be visualized sonographically when it is located not too far cranially on the ICA [ 15 ]. However, high-grade FMD stenoses will be detected on the basis of indirect hemodynamic criteria. To overlook asymptomatic cases of low grade or medium grade stenosing lesions will not have a negative consequence since they do not require any treatment [ 16 ]. Conclusions CDI allows diagnosis of FMD in numerous cases. Due to the unfavourable localisation of FMD for CDI, the sensitivity of CDI is low in comparison to angiography. However, high-grade FMD stenoses that require invasive treatment can be recognized on the basis of indirect hemodynamic criteria. Competing interests None declared. List of abbreviations CDI Color Doppler Imaging FMD Fibromuscular Dysplasia ICA Internal Carotid Artery VA Vertebral Artery

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548137

Alteration of the hypothalamic-pituitary-gonadal axis in estrogen- and androgen-treated adult male leopard frog, Rana pipiens

Background Gonadal steroids, in particular 5 alpha-dihydrotestosterone (DHT) and 17 beta-estradiol (E2), have been shown to feed back on the hypothalamic-pituitary-gonadal (HPG) axis of the ranid frog. However, questions still remain on how DHT and E2 impact two of the less-studied components of the ranid HPG axis, the hypothalamus and the gonad, and if the feedback effects are consistently negative. Thus, the goal of the study was to examine the effects of DHT and E2 upon the HPG axis of the gonadally-intact, sexually mature male leopard frogs, Rana pipiens. Methods R. pipiens were implanted with silastic capsules containing either cholesterol (Ch, a control), DHT, or E2 for 10 or 30 days. At each time point, steroid-induced changes in hypothalamic GnRH and pituitary LH concentrations, circulating luteinizing hormone (LH), and testicular histology were examined. Results Frogs implanted with DHT or E2 for 10 days did not show significant alterations in the HPG axis. In contrast, frogs implanted with hormones for 30 days had significantly lower circulating LH (for both DHT and E2), decreased pituitary LH concentration (for E2 only), and disrupted spermatogenesis (for both DHT and E2). The disruption of spermatogenesis was qualitatively similar between DHT and E2, although the effects of E2 were consistently more potent. In both DHT and E2-treated animals, a marked loss of all pre-meiotic germ cells was observed, although the loss of secondary spermatogonia appeared to be the primary cause of disrupted spermatogenesis. Unexpectedly, the presence of post-meiotic germ cells was either unaffected or enhanced by DHT or E2 treatment. Conclusions Overall, these results showed that both DHT and E2 inhibited circulating LH and disrupted spermatogenesis progressively in a time-dependent manner, with the longer duration of treatment producing the more pronounced effects. Further, the feedback effects exerted by both steroid hormones upon the HPG axis were largely negative, although the possibility exists for a stimulatory effect upon the post-meiotic germ cells.

Background It is well established in mammals that gonadal steroid hormones are potent negative feedback regulators of the hypothalamic-pituitary-gonadal (HPG) axis. In ranid frogs, the first evidence supporting this notion came from a study on the bullfrog, Rana catesbeiana , in which gonadectomy elevated circulating gonadotropins, and estrogen and androgen replacement suppressed this elevation [ 1 ]. It was later shown that two gonadal steroids, 17β-estradiol (E 2 ) and 5α-dihydrotestosterone (DHT), could directly target the pituitary to modulate the release of luteinizing hormone (LH) and follicle-stimulating hormone (FSH) in these frogs [ 2 - 4 ]. Despite the established role of DHT and E 2 as feedback regulators of gonadotropin secretion in ranid frogs, there is still some confusion regarding the exact nature of these feedback effects. For example, in female and juvenile R. catesbeiana , DHT suppressed the post-gonadectomy rise in circulating gonadotropins [ 1 ], yet it enhanced the responsiveness of the pituitary to gonadotropin-releasing hormone (GnRH) [ 1 , 5 ], suggesting DHT is involved in both negative and positive feedback. On the other hand, in the leopard frog ( R. pipiens ), DHT had no effect on the post-castration rise in gonadotropin in males [ 2 ] but modestly stimulated pituitary responsiveness to GnRH, suggesting a role in only positive feedback. Although the effects of E 2 were less variable, some conflicting data also exist. In both R. catesbeiana and R. pipiens , E 2 consistently inhibited LH and FSH secretion both in vivo and in vitro , demonstrating a direct and powerful negative feedback effect of E 2 at the level of the pituitary [ 1 - 3 ]. However, recent studies reported E 2 treatment significantly stimulated the proliferation of primary spermatogonia (I SPG) in the green frogs, R. esculenta [ 6 , 7 ], suggesting an additional role of E 2 in the positive feedback of the HPG axis. Results from the previous studies revealed the complex nature in which estrogen and androgen feed back on the reproductive axis, and suggest that the nature of the feedback effects might vary depending on the species, sex, reproductive stage of the frogs used, and the duration of steroid hormones administered. Further, there are still significant gaps in our knowledge regarding how these two steroid hormones feed back on the other two components of the HPG axis, the hypothalamus and the gonad. Therefore, the goal of the present study is to understand how E 2 and DHT impact the HPG axis in gonadally-intact male R. pipiens . We will do so by measuring parameters that reflect the function of the HPG axis, including hypothalamic GnRH, pituitary and circulating LH, and spermatogenic activity. Moreover, steroid treatments were administered over two periods, 10 days and 30 days, to examine if the nature of steroidal feedback effects remains consistent over time. These results should allow us to determine if DHT and E 2 act consistently as negative feedback regulators at different levels of the HPG axis. Methods Animals All experimental procedures were conducted in compliance with the animal protocol approved by the Institutional Animal Care and Use Committee at the University of Colorado. Mature male northern leopard frogs, Rana pipiens , were obtained from Carolina Biologicals (Burlington, NC) from April to July of 2004. Since the life histories of these animals were not entirely clear, all experiments were conducted within the three-month period to minimize the possible confounding effects of seasonality. As a control, we performed histological analysis on testes of representative frogs from every batch. When testicular histology was compared, little differences were observed among batches of frogs arriving at different times (data not shown). Frogs were kept under a 12L:12D photoperiod and fed live crickets every other day. All frogs were allowed to acclimate to the laboratory environment for at least one week before surgical implant. Surgical Implant One-cm silastic capsules containing crystalline cholesterol (Ch: control), DHT, or E 2 were prepared as previously described [ 8 ], with some minor modifications. Briefly, silastic tubing (outer diameter = 1.96 mm; inner diameter = 1.47 mm) was filled with 1 cm length of crystalline Ch, DHT, or E 2 (Sigma, St Louis, MO) and sealed on both ends with silicon glue. Ch implant was widely used as a negative control for the experimental treatment of cholesterol-based compounds such as steroid hormones [ 8 - 11 ]. In a preliminary observation (data not shown), we noted no difference in the testicular morphology in animals that have lost Ch capsules compared to animals that have retained capsules throughout the 30-day period, indicating Ch had minimal effects on the reproduction of R. pipiens . Filled capsules were equilibrated in 0.6% saline for at least 48 hours before implant. For implant, frogs were anesthetized by immersion in 0.03% benzocaine. A small incision was made at the base of the left leg and a silastic capsule inserted subcutaneously. The incision was then closed with silk thread. Frogs were monitored for recovery from anesthesia and then returned to their respective holding tanks. Tissue Preparation Ten or 30 days after implant, frogs were weighed and sacrificed by quick decapitation using a guillotine. Trunk blood was collected into heparinized tubes, centrifuged, and plasma stored at -70°C until the measurement of LH and steroid hormones by radioimmunoassays (RIAs). Testes were removed, their masses recorded, and immersion-fixed in Bouin's fixative overnight. Hypothalami were excised from the brain by four cuts: a coronal cut 1 mm rostral to the optic chiasm, a coronal cut on the caudal border of the optic tectum, and two sagittal cuts along the lateral margins of the median eminence. Hypothalami were flash-frozen on dry ice and stored at -70°C until extraction and the measurement of GnRH by RIA. Pituitary glands were removed, sonicated in 500 μl phosphate-buffered saline (PBS), and stored at -70°C until the measurement of LH by RIA. All carcasses were later inspected for the presence of the silastic capsule in the legs. Animals whose capsules were lost were excluded from data analysis. LH RIA Plasma and pituitary LH levels were measured by a LH RIA developed for the bullfrog ( R. catesbeiana ) [ 12 ] and validated for R. pipiens [ 13 ]. The iodination stock, standard, and antiserum for the RIA were a generous gift of Dr. Paul Licht (University of California at Berkeley). The limit of detection was 0.1 ng/ml. The intra- and inter-assay coefficients of variation were 4.8% and 13.3%, respectively. Pituitary LH levels were normalized for protein content assessed by the Bradford protein assay (Bio-Rad Laboratories, Inc., Hercules, CA). Extraction of Hypothalami and GnRH RIA Hypothalamic GnRH was extracted with 1 N HCl from the frozen tissues as previously described [ 11 ]. The recovery for hypothalamic extractions, assessed by the post-extraction counting of a known amount of [ 125 I]GnRH added to representative homogenates prior to extraction, was 86%. GnRH RIA was carried out with an antiserum specific for the mammalian form of GnRH (R1245, provided by Dr. Terry Nett at the Colorado State University) using a protocol described in detail elsewhere [ 11 , 14 , 15 ]. The intra- and inter-assay coefficients of variation were 7.3% and 5.0%, respectively. Hypothalamic GnRH levels were normalized for protein content determined by the Bradford protein assay. Steroid Hormone RIAs E 2 and DHT RIAs were performed using the RIA kits from Diagnostic Systems Laboratories (Webster, TX). These RIA kits have been validated previously for the measurement E 2 and DHT in R. pipiens [ 11 ]. The limits of detection were 6.5 pg/ml for the E 2 RIA and 4 pg/ml for the DHT RIA. The intra- and inter-assay coefficients of variation were 5.3% and 4.9%, respectively, for the E 2 RIA, and 3.1% and 8.4%, respectively, for the DHT RIA. Both RIAs are highly specific and cross-react minimally with other steroid hormones. Histology After fixation, testes were dehydrated through ascending concentrations of ethanol, defatted in Histoclear, and embedded in paraffin. Thirteen-μm sections were cut on a rotary microtome, mounted on poly-L-lysine-coated slides, and stained with hematoxylin and eosin. Immunocytochemistry (ICC) of Proliferating Cell Nuclear Antigen (PCNA) Testes were processed for ICC of PCNA, a cell cycle S phase marker, to identify I SPG and secondary spermatogonia (II SPG) undergoing cell proliferation [ 16 ]. Testicular sections, prepared as described above for histological staining, were deparaffinized in Histoclear, rehydrated through descending concentrations of ethanol, and immersed in Antigen Unmasking Solution (Vector Laboratories, Burlingame, CA) for 10 minutes at 90°C. After antigen retrieval, sections were washed with 1% hydrogen peroxide in 0.1 M PBS containing 0.4% Triton × 100 (PBST) for 10 minutes to quench the endogenous peroxidase activity, rinsed 5 times with PBST, and incubated for 48 hours at 4°C in PBST containing a monoclonal anti-PCNA antibody (Santa Cruz Biotechnology, Santa Cruz, CA; 1:500) and 4% normal sheep serum. After incubation, sections were washed with PBST and incubated with a biotinylated sheep-anti-mouse IgG (Jackson Laboratory, West Grove, PA; 1:400), washed, and incubated with the Vectastain ABC reagent (Vector Laboratories) for 1 hour. Sections were washed and the immunoreactivity visualized using diaminobenzidine as the chromagen. After the color reaction, sections were washed, counterstained with hematoxylin, dehydrated through ascending concentrations of ethanol, cleared in Histoclear, and coverslipped. Controls for ICC included the preadsorption of the primary antiserum with 20 μg/ml of recombinant human PCNA (Spring Bioscience, Fremont, CA) and the omission of the primary antiserum. Histological Analysis Five to eight testes (each from a different animal) per treatment group were assessed for the following histological parameters: seminiferous tubule diameter, the number of I SPG per tubule, and the number of cysts within each tubule containing II SPG, primary spermatocytes (I SPC), or secondary spermatocytes (II SPC). These germ cells were defined according to Rastogi et al . [ 17 ]. To score the number of cysts containing II SPG, I SPC, and II SPC, sections stained with hematoxylin and eosin were used. To score the number of I SPG, which were scattered and more difficult to locate, sections processed for PCNA ICC were used. Specifically, PCNA-positive cells that were large, isolated, and located at the periphery of the cysts were scored as proliferating I SPG. This method allowed us to identify more I SPG than if morphological criteria were used alone. Since most spermatids and mature spermatozoa were not confined within the cysts and were therefore difficult to measure, these two germ cell types were not quantified. For each testis, five randomly selected tubules were sampled on a slide that had been coded to conceal the identity of the animal. Histological parameters from five tubules were averaged to give a mean for a single animal. Tubular diameters were measured using a calibrated ocular micrometer. All histological parameters were assessed by one individual blind to the identity of the slides. Statistical Analysis Differences among groups were analyzed by the one-way analysis of variance (ANOVA) on log 10 -transformed data followed by the Tukey's post-hoc test. Differences were considered significant when P < 0.05. Results Steroid hormone RIAs were performed to monitor circulating steroid hormone levels in Ch- and hormone-implanted animals. For animals implanted for 10 days, circulating E 2 levels were 540 ± 110.5 (Ch group; n = 5) and 1966 ± 13.2 pg/ml (E 2 group; n = 5), and circulating DHT levels were 0.9 ± 0.3 (Ch group; n = 4) and 37.5 ± 4 ng/ml (DHT group; n = 5). For animals implanted for 30 days, circulating E 2 levels were 488 ± 370 (Ch group; n = 5) and 2255 ± 650 pg/ml (E 2 group; n = 9), and circulating DHT levels were 2.1 ± 1.4 (Ch group; n = 4) and 24.6 ± 2.7 ng/ml (DHT group; n = 8). To assess the overall accumulation of GnRH in the hypothalami of control and steroid hormone-treated animals, hypothalami were removed, extracted, and measured for the concentration of GnRH. No significant differences in hypothalamic GnRH concentration were observed among Ch, DHT, and E 2 groups implanted for 10 or 30 days (Fig. 1 ). In animals implanted for 10 days, plasma LH levels were not different among the treatment groups (Fig. 2A ). However, in animals implanted for 30 days, both DHT and E 2 significantly suppressed circulating LH (Fig. 2B ). The suppressive effect of E 2 was significantly more potent than DHT, with all E 2 -treated animals having undetectable levels of circulating LH (Fig. 2B ). In 10-day-implanted frogs, no differences in pituitary LH concentration were observed among the treatment groups (Fig. 3A ). In 30-day-implanted frogs, E 2 , but not DHT, significantly decreased the accumulation of LH in the pituitary (Fig. 3B ). Figure 1 Hypothalamic GnRH concentrations in implanted frogs. Hypothalamic GnRH concentrations in frogs implanted for (A) 10 days or (B) 30 days with either Ch, DHT, or E 2 . No significant differences were observed among treatment groups in either 10- or 30-day-implanted animals. Each bar represents mean ± SEM. N = 6–11.+ Figure 2 Plasma LH levels in implanted frogs. Plasma LH levels in frogs implanted for (A) 10 days or (B) 30 days with either Ch, DHT, or E 2 . Each bar represents mean ± SEM. Dissimilar letters indicate significant difference between groups. ND = not detectable. N = 7–10. Figure 3 Pituitary LH concentrations in implanted frogs. Pituitary LH concentrations in frogs implanted for (A) 10 days or (B) 30 days with either Ch, DHT, or E 2 . Each bar represents mean ± SEM. Dissimilar letters indicate significant difference between groups. N = 7–10. Testicular function was assessed by six parameters: the gonadosomatic index (GSI; [g testes mass/g body mass] × 100), the diameter of the seminiferous tubules, and the presence of four germ cell types (I SPG, II SPG, I SPC, II SPC) in the testes. Overall, no differences were observed in any of the six parameters among treatment groups in the 10-day-implanted animals (Fig. 4 ). However, in the 30-day-implanted animals, significant steroid-induced changes in the testes were seen. E 2 significantly depleted the presence of I SPG, II SPG, I SPC, and reduced the GSI (Fig. 5 ), whereas DHT significantly reduced only the presence of II SPG and I SPC (Fig. 5 ). Neither steroid hormone affected the diameter of the seminiferous tubules or II SPC (Figs. 5B, F ). Representative photomicrographs of testicular histology (Fig. 6 ) showed morphological changes parallel to the quantitative measurements in Figs. 4 and 5 . In animals implanted for 10 days, no visible differences in germ cell types were seen among treatment groups; I SPG, II SPG, and I SPC were present equally in the testes of all groups (Figs. 6A, B, C ). In contrast, 30-day implant with DHT or E 2 resulted in highly pronounced and visible changes in the histology of the testes (Figs. 6D, E, F ). Whereas Ch-treated tubules contained germ cells of all types (Fig. 6D ), DHT- and E 2 -treated tubules showed a conspicuous absence of II SPG and I SPC (Figs. 6E, F ). The loss of I SPG with DHT and E 2 treatments was less visible than the loss of other two germ cell types (Figs. 6E, F ), a result consistent with the quantitative data (Fig. 5 ). Interestingly, the formation of spermatozoa appeared to be stimulated by DHT and E 2 ; in fact, the most prominent germ cells in tubules of DHT and E 2 -treated were the large bundles of mature spermatozoa, which occupied most of the tubular lumen (Figs. 6E, F ). Figure 4 Testicular function in frogs implanted for 10 days. Measurements of testicular function in frogs implanted for 10 days with either Ch, DHT, or E 2 . (A) Average GSI, (B) average diameter of seminiferous tubules, (C) number of I SPG, and number of cysts containing (D) II SPG, (E) I SPC, and (F) II SPC were measured from 5–8 animals per treatment group. Each bar represents mean ± SEM. ND = not detectable. No significant differences were observed among treatment groups in any of the parameters measured. Figure 5 Testicular function in frogs implanted for 30 days. Measurements of testicular function in frogs implanted for 30 days with either Ch, DHT, or E 2 . A) Average GSI, (B) average diameter of seminiferous tubules, (C) number of I SPG, and number of cysts containing (D) II SPG, (E) I SPC, and (F) II SPC were measured from 5–6 animals per treatment group. Each bar represents mean ± SEM. Dissimilar letters indicate significant difference between groups. Figure 6 Testicular histology of implanted frogs. Representative testicular histology of frogs implanted with (A, D) Ch, (B, E) DHT, or (C, F) E 2 . (A, B, C) Testes from animals implanted for 10 days. (D, E, F) Testes from animals implanted for 30 days. Red arrow = I SPG; dark blue arrow = II SPG; light blue arrow = I SPC; yellow arrow = II SPC; green arrow = spermatozoa. Note DHT and E 2 had no visible effects on testes of animals implanted for 10 days (A, B, C) . In contrast, DHT and E 2 visibly altered the germ cell composition in animals implanted for 30 days (D, E, F) . Note the prominent spermatozoa and the absence of I SPC and II SPG in both DHT- and E 2 -treated testes (E, F) . Scale bar = 100 μm. PCNA ICC was conducted to determine the effects of gonadal steroids on the number of proliferating germ cells and to allow for the more consistent identification of I SPG. In animals implanted with Ch, intense PCNA immuoreactivity was observed in both I SPG and II SPG. In addition, the cytoplasm of I SPC was lightly stained (Figs. 7A, D ), since PCNA was also shown to be expressed during the pre-meiotic S phase and meiotic prophase [ 18 ]. All spermatogonia (I SPG and II SPG) identifiable by the hematoxylin counterstain were positive for PCNA. Treatment with DHT (Fig. 7B ) or E 2 (Fig. 7C ) did not visibly alter the appearance of cells positive for PCNA in frogs implanted for 10 days compared to the Ch control (Fig. 7A ). In contrast, in animals implanted for 30 days, a visible reduction in the number of PCNA-positive germ cells was observed in DHT- and E 2 -treated animals (Figs. 7E, F ) compared to the Ch control (Fig. 7D ). This reduction was primarily due to the decreased presence of I SPG, II SPG, and I SPC in the testes treated with steroid hormones. In control sections incubated with preadsorbed primary antiserum or no primary antiserum, only background staining was present (data not shown). Figure 7 PCNA ICC on testes of implanted frogs. Representative photomicrographs of PCNA ICC performed on testicular sections of frogs implanted with (A, D) Ch, (B, E) DHT, or (C, F) E 2 . (A, B, C) Testes from animals implanted for 10 days. (D, E, F) Testes from animals implanted for 30 days. Brown stain = PCNA immunoreactivity. Blue stain = hematoxylin counterstain. Red arrow = I SPG; dark blue arrow = II SPG; light blue arrow = I SPC. Note DHT and E 2 had no visible effects on testes of animals implanted for 10 days (A, B, C) . In contrast, DHT and E 2 visibly reduced the presence of PCNA-positive germ cells in animals implanted for 30 days (D, E, F) . Σχαλεβαρ = 100 μm. Discussion Under our experimental paradigm, both E 2 and DHT exerted negative feedback effects upon the reproductive axis of the sexually mature male leopard frogs. The manifestation of these inhibitory effects was time-dependent and required treatment duration for longer than 10 days. In frogs implanted for 30 days, E 2 decreased circulating LH to undetectable levels and significantly reduced the presence of I SPG, II SPG, and I SPC. The effects of DHT were less potent, reducing only circulating LH, II SPG, and I SPC. Unexpectedly, the presence of post-meiotic germ cells was either unaffected or stimulated with the DHT or E 2 treatment. These results suggest that along the reproductive axis, the most significant negative feedback effects were upon the pituitary and testes, although a stimulatory effect upon the testes might also exist. All hormone implants elevated circulating steroid hormones to levels above the Ch controls without exceeding the physiological range reported for male ranid frogs. For instance, depending on the reproductive status, the range of circulating E 2 reported for sexually mature male ranid frogs was approximately 100 to 3500 pg/ml, and the range of circulating DHT was approximately 1 to 30 ng/ml [ 6 , 19 ]. Another study [ 20 ] reported circulating levels of approximately 10 ng/ml for DHT and 2 ng/ml for E 2 in captive male R. pipiens . Thus, circulating E 2 and DHT in the hormone-implanted animals were largely within the high end of the physiological range. DHT and E 2 did not significantly alter hypothalamic GnRH concentration in animals treated for 10 or 30 days. These results were consistent with our previous finding on frogs implanted for 20 days with DHT and E 2 , and speak to the highly stable nature of GnRH peptide accumulation. One should note that this study focused on the mammalian form (Type I) of GnRH because this is the predominant hypophysiotropic form of GnRH in the diencephalon of ranid frogs [ 21 ] and the form more sensitive to changes in reproductive status [ 22 ]. However, the chicken II (Type II) form of GnRH may also be hypophysiotropic since it binds to pituitary GnRH receptor with high affinity [ 23 ], and its presence is detected in the hypothalamic-pituitary portal blood [ 21 ]. The ability of steroid hormones to feed back upon the Type II GnRH system in R. pipiens is at present unclear and awaits further investigation. Only E 2 treatment for the longer duration (30 days) significantly reduced pituitary LH concentration, although a substantial amount of LH still remained in the pituitary glands of these E 2 -treated animals. Thus, the potent suppression of circulating LH in animals treated with E 2 for 30 days was most likely attributable to the low secretory activity of the pituitary gonadotropes rather than the depletion of LH stores. Somewhat surprising was the inability of E 2 treatment for 10 days to suppress circulating LH. The pituitaries of ranid frogs were shown to be extremely sensitive to the inhibitory actions of E 2 . In R. pipiens , in vitro exposure of the pituitary to E 2 concentrations as low as 100 pg/ml for only 48 hours significantly suppressed both basal and GnRH-stimulated gonadotropin secretion [ 2 ]. Extrapolating from this time course and from our current observation that E 2 implants could elevate circulating E 2 to about 2000 pg/ml, one might expect a substantial decline in circulating LH of these animals after only 10 days of implant, but this was not the case. It is possible that additional in vivo mechanisms exist in these frogs to buffer against short-term estrogenic inhibition. Some of these might include changes in the clearance rate of circulating LH [ 24 ] and the levels of sex steroid binding proteins [ 25 ]. The former could prolong the half-life of LH in circulation; the latter could dampen the inhibitory effects of E 2 by binding to E 2 and decreasing the availability of the bioactive hormone. Another unexpected observation was that DHT treatment for 30 days also suppressed circulating LH. Our results differ from a previous study demonstrating the inability of DHT to suppress post-gonadectomy rise in LH [ 2 ] and showed, for the first time, that DHT participates in the negative feedback regulation of gonadotropin secretion in R. pipiens . It is at present unclear if reduced circulating LH is a direct consequence of suppressed secretory activity of the gonadotropes or reduced output from the GnRH system. Based on the previous report that DHT had no direct inhibitory effect on pituitary gonadotropin secretion [ 2 ], it seems likely that DHT may achieve negative feedback primarily by targeting the GnRH system to suppress GnRH release. This possibility does not conflict with our current observation that DHT lacks an effect on GnRH content. Since GnRH content is a measure of GnRH peptide accumulation which is a result of transcription, translation, mRNA stability, peptide turnover, or release, it is a poor indicator of GnRH release alone. One of the most pronounced negative feedback effects of DHT and E 2 was observed at the level of the testes. In animals implanted for 30 days with these two steroids, a marked loss of several germ cell types (I SPG, II SPG, and I SPC) was observed. Interestingly, although E 2 exerted a greater disruptive effect on spermatogenesis, similar trends of reduction with virtually no qualitative difference were also observed in DHT-treated testes, suggesting similar outcome might be attained with longer DHT exposure. That DHT- and E 2 -induced disruption of spermatogenesis differed only in the degree of severity suggests the disruption occurred primarily via a common pathway, possibly through the inhibition of gonadotropins. In this study, we could not measure circulating FSH because we lack a homologous FSH RIA. However, previous studies have reported that FSH secretion in R. pipiens was under the negative control of E 2 [ 2 , 3 ] and possibly DHT [ 2 ], since gonadectomy significantly elevated the levels of circulating FSH. The observation that spermatogenic disruption occurred only when circulating gonadotropin was reduced (30 day-implants) further lends support to this hypothesis. Although the roles of FSH and LH in anuran spermatogenesis are not entirely clear, data from other amphibians suggest FSH is essential for supporting the proliferation and survival of spermatogonia [ 26 , 27 ]. Importantly, FSH is required for the completion of the last spermatogonial mitosis, thus the entrance into meiosis and the generation of spermatocytes [ 27 ]. On the other hand, LH is specifically required for the stimulation of androgen production in ranid frogs [ 28 ] and could be responsible for maintaining high levels of intratesticular androgen required for androgen-dependent stimulation of germ cell formation [ 29 ]. Thus, low circulating levels of gonadotropins could be the common pathway leading to defective spermatogenesis in both DHT- and E 2 -treated animals. Although the significant reduction of I SPG in E 2 -treated testes could partially account for the loss of germ cell types that arose from I SPG, this cannot be the sole cause. For example, substantial PCNA-positive I SPG still remained in the testes of frogs implanted with E 2 for 30 days, yet virtually no II SPG remained in the testes of these animals. Similarly, in 30-day-DHT-treated testes, there was no significant decline in I SPG, but II SPG were markedly reduced. These observations indicate a disproportionate loss of II SPG that may have resulted from their failure to survive. These data were consistent with a previous report in the newt that the mitotic penultimate SPG failed to survive when circulating FSH was suppressed [ 26 ]. Taken together, we believe that II SPG was the germ cell type most severely affected by steroid treatments, and the loss of II SPG was the most important underlying cause for disrupted spermatogenesis. An interesting observation is that although pre-meiotic germ cells (I SPG, II SPG, and I SPC) were adversely affected by steroid hormone implants at 30 days, meiotic or post-meiotic germ cells (II SPC, spermatids and spermatozoa) appeared unaffected or stimulated. In fact, the most conspicuous germ cells in the seminiferous tubules of 30-day E 2 - or DHT-implanted frogs were mature spermatozoa, which occupied the largest bulk of the tubular lumen. It is possible that low circulating FSH had little influence on the germ cells once they entered meiotic division. Under low circulating LH, spermiation was inhibited, and mature spermatozoa continued to accumulate in the tubule. Another possibility is that E 2 and DHT, while suppressing the presence of pre-meiotic germ cells, actually stimulated the entrance of existing I SPC into meiosis and promoted the survival of post-meiotic germ cells. This possibility was partially supported by the previous observation that testes of frogs treated with DHT for 20 days had fewer II SPG, but significantly more I SPC in the midst of meiotic division [ 11 ]. Along the same line of reasoning, it is also possible that DHT and E 2 facilitated the progression of spermatogenesis to the extent that the intermediate germ cell types could no longer be adequately replenished, leaving tubules filled with post-meiotic cells (primarily spermatozoa) and very little else. Regardless, the trend towards reduced GSI in steroid hormone-treated animals, along with the reduced presence of pre-meiotic germ cells, indicate an overall negative effect of these hormones upon the testes. The abundance of spermatozoa in DHT- and E 2 -treated animals nevertheless raised an interesting possibility for the existence of a positive steroidal effect on spermatogenesis. Worth mentioning is the possibility that DHT and E 2 , in addition to affecting spermatogenesis by lowering circulating gonadotropins, have also been shown to act directly upon the amphibian testes. Both androgen and estrogen binding sites were found in the amphibian testes [ 30 - 33 ]. A number of physiological responses were presumably mediated through these testicular steroid hormone receptors. For instance, E 2 acted directly upon the amphibian testes to suppress androgen secretion [ 34 - 36 ], stimulate nuclear translocation of c-Fos [ 37 , 38 ], and enhance proliferation of I SPG [ 6 , 37 ]. Similarly, DHT has also been found to directly modulate androgen secretion [ 34 ]. Of interest to the present study is the demonstration that E 2 directly stimulated SPG I proliferation in R. esculenta [ 6 , 7 , 37 ]. Under our experimental paradigm, however, such a stimulatory effect was not seen in R. pipiens . Whether or not this discrepancy was due to the differences in experimental paradigms or species used is at present unclear. We previously showed that spermatogenesis in the ranid frogs was altered in mature male frogs implanted with DHT and E 2 for 20 days [ 11 ]. Specifically, E 2 reduced the presence of II SPG and I SPC, whereas DHT reduced only the presence of the former. However, the study represented only a snapshot in time, so no information was available regarding the progression of events that led to the altered formation of germ cells. Moreover, it was unclear if the treatment with these two steroid hormones for shorter or longer periods could impact the testes differently. Our current results showed that both steroids inhibited circulating gonadotropin and disrupted spermatogenesis progressively in a time-dependent manner, with the longer duration of treatment producing the more pronounced effects. Further, the changes in the testes were qualitatively similar between DHT and E 2 treatments, suggesting declining gonadotropin levels might be the common underlying cause for the disrupted spermatogenesis. These results reflect the highly sensitive nature of the anuran reproductive axis to estrogenic and androgenic modulation. We showed that the continuous exposure of mature frogs to high physiological levels of steroid hormones for a relatively short period could profoundly alter their pituitary and testicular function. In particular, the potency of estrogen hormones raises concerns regarding the potential reproductive disruption that can occur when mature frogs are exposed to short-term and low-level environmental estrogen mimics. Authors' contributions PST designed the experiments, analyzed the data, and prepared the manuscript. AEK and JTJ prepared the silastic capsules, implanted the animals, removed the tissues, and performed all the hormone measurements. KBW implanted some animals, prepared all histological samples, counted the germ cells, and performed the PCNA ICC. All authors read and approved the final manuscript.

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514884

Single Nucleotide Polymorphism–Based Validation of Exonic Splicing Enhancers

Because deleterious alleles arising from mutation are filtered by natural selection, mutations that create such alleles will be underrepresented in the set of common genetic variation existing in a population at any given time. Here, we describe an approach based on this idea called VERIFY (variant elimination reinforces functionality), which can be used to assess the extent of natural selection acting on an oligonucleotide motif or set of motifs predicted to have biological activity. As an application of this approach, we analyzed a set of 238 hexanucleotides previously predicted to have exonic splicing enhancer (ESE) activity in human exons using the relative enhancer and silencer classification by unanimous enrichment (RESCUE)-ESE method. Aligning the single nucleotide polymorphisms (SNPs) from the public human SNP database to the chimpanzee genome allowed inference of the direction of the mutations that created present-day SNPs. Analyzing the set of SNPs that overlap RESCUE-ESE hexamers, we conclude that nearly one-fifth of the mutations that disrupt predicted ESEs have been eliminated by natural selection (odds ratio = 0.82 ± 0.05). This selection is strongest for the predicted ESEs that are located near splice sites. Our results demonstrate a novel approach for quantifying the extent of natural selection acting on candidate functional motifs and also suggest certain features of mutations/SNPs, such as proximity to the splice site and disruption or alteration of predicted ESEs, that should be useful in identifying variants that might cause a biological phenotype.

Introduction Exonic splicing enhancers (ESEs) were identified about a decade ago as short oligonucleotide sequences that enhance exon recognition by the splicing machinery (reviewed in Blencowe 2000 and Cartegni et al. 2002 ). Sequences with ESE activity have been identified in both plants and animals and have been found to occur frequently in constitutively spliced exons as well as alternatively spliced exons ( Tian and Kole 1995 ; Coulter et al. 1997 ; Liu et al. 1998 ; Schaal and Maniatis 1999 ; Fairbrother et al. 2002 ). ESEs often mediate their effects on splicing through the action of proteins of the SR protein family, which bind to ESEs and recruit components of the core splicing machinery to nearby splice sites ( Graveley 2000 ). Previously, we reported a computational method called relative enhancer and silencer classification by unanimous enrichment (RESCUE)-ESE which identifies ESEs in human genomic sequences using statistical properties of the oligonucleotide composition and splice site strengths of large datasets of exons and introns ( Fairbrother et al. 2002 ). This method identified a set of 238 hexamers (of the 4,096 possible hexamers) which were predicted to possess ESE activity on the basis that (1) they are significantly enriched in human exons relative to introns and (2) they are significantly more frequent in exons with weak (nonconsensus) splice sites than in exons with strong (consensus) splice sites. Tests of splicing enhancer activity using an in vivo splicing reporter system confirmed ESE activity for a representative sequence from each of ten clusters of RESCUE-ESE hexamers ( Fairbrother et al. 2002 ). The function of this set of hexamers was further confirmed by the observation that ESE activity was reduced significantly in nine out of ten point mutants chosen to eliminate RESCUE-ESE hexamers and the observation that the set of RESCUE-ESE hexamers was also predictive in analyzing a list of published mutations that cause exon skipping in the human hypoxanthine phosphoribosyl transferase gene ( Fairbrother et al. 2002 ). A variety of other selection-based methods have been used to identify sets of sequences that are capable of functioning as ESEs. These SELEX methods isolate ESEs from a complex pool of random sequence by iteratively selecting and amplifying the fraction of molecules that can function as ESEs in a reporter assay ( Tian and Kole 1995 ; Coulter et al. 1997 ; Liu et al. 1998 ; Schaal and Maniatis 1999 ). These methods have yielded a variety of sequence motifs, and ESE activity of representative sequences has been demonstrated in reporter systems. Often, these motifs have not been refined to a degree where it is possible to reliably design single point mutations that disrupt ESE function ( Tian and Kole 1995 ; Coulter et al. 1997 ; Liu et al. 1998 ; Schaal and Maniatis 1999 ). Despite this, a few previous studies have identified several disease alleles where the disruption of a conserved splicing enhancer corresponds to observed splicing defects, a noteworthy example being splicing mutations in the breast cancer gene BRCA1 ( Liu et al. 2001 ; Orban and Olah 2001 ). To date, this type of analysis has been limited to only a few genes. While mutational studies on model splicing substrates have proven an effective means of characterizing individual ESEs, the ability to draw general conclusions about ESE function has been complicated by additional features that vary between substrates. Features such as transcript secondary structure, adjacent negative elements, and the possible contribution of splicing factors associated with the transcription machinery could all modulate ESE activity on a given substrate and prevent any single substrate from serving as a paradigm for all aspects of exon recognition problems. To dilute the contribution of sequence context and to develop general rules for splicing, we have used genomic data to survey the strength of selection on RESCUE-ESE hexamers 2 across several thousand exons. Here we test the hypothesis that, in addition to protein-coding requirements, human exon sequences are also significantly constrained by the requirement to encode ESEs. We have developed a population genetic approach (variant elimination reinforces functionality [VERIFY]) which exploits the simple principle that, because they are selected against, deleterious alleles will tend to be underrepresented in the pool of sequence variants that are common in a population ( Graur and Li 2000 ). Taking advantage of the huge repository of genetic information represented by the human single nucleotide polymorphism (SNP) database, we determined the ancestral allele for exonic SNPs by comparison to the chimpanzee genome. This information makes it possible to distinguish between SNPs derived from mutations that disrupt predicted ESEs and those derived from mutations that create predicted ESEs, allowing an assessment of the degree of selection to conserve ESEs in human exons. While we have tested a small subset of RESCUE predictions in a functional assay, many sequences proposed to possess ESE activity have not been validated. This work provides additional evidence that RESCUE-ESE hexamers are physiologically important when they occur in human exons and suggests a way to use SNP data to validate oligonucleotide motifs proposed to have biological activity. Results/Discussion To assess the relationship between the locations of common genetic variation in human genes and ESEs, we screened the public SNP database (dbSNP; build 112) for SNPs that mapped to human exons. A set of biallelic reference SNPs was used, excluding entries that (1) mapped to multiple regions in the human genome, (2) mapped to repetitive elements, or (3) were derived from transcript sequence data, e.g., through comparison of expressed sequence tags (ESTs) (see Materials and Methods for details). The remaining SNPs were searched against a large database of human genes containing approximately 121,000 internal exons annotated by aligning available human cDNAs to the assembled genome using the GENOA genome annotation system (see Materials and Methods ). This search identified 9,862 SNPs that were localized to an internal exon (aligned perfectly to the genomic sequence over a 33-base segment centered on the polymorphic position). ESE Density Is Highest and SNP Density Lowest near Splice Sites Recording the position of each SNP within the corresponding exon revealed that SNP density is not uniform along exons ( Figure 1 ). Consistent with previous observations ( Majewski and Ott 2002 ), SNP density was approximately 20–30% lower near both the 3′ splice site (3′ss) and the 5′ splice site (5′ss) of human exons than in the interior of exons, and reached a plateau at about 25–30 bases from the splice sites. The distribution of RESCUE-predicted ESE hexamers along exons had roughly an inverse relationship to the SNP density, with the highest density of ESEs observed near the 5′ and 3′ splice junctions and a lower density in the interior of exons ( Figure 1 ). Previously, ESE activity has been observed to vary as a function of the distance between the ESE and the adjacent splice sites, with the highest activity in vitro and in vivo for ESEs positioned closest to splice sites ( Nelson and Green 1988 ; Lavigueur et al. 1993 ; Graveley et al. 1998 ). Thus, selective pressure is likely to be higher on ESEs located near splice junctions relative to ESEs in the interior of exons, which could explain the trend in ESE density shown in Figure 1 . As a consequence of the increased density of ESEs near splice sites, mutations that occur in exons near splice sites should have a higher likelihood of disrupting ESEs and therefore be more likely to be eliminated by purifying selection. Thus, selection on ESEs could potentially explain the trend in SNP density seen in Figure 1 . In order to more directly test the hypothesis that ESE disruption mutations are subject to negative selection, we conducted a large-scale analysis of sequence variation in human exons. Figure 1 Density of Predicted ESEs and SNPs along Human Exons RESCUE-ESE hexamers were searched against a database of 121,000 internal human exons. ESE density (blue curve) was determined as the fraction of hexamers beginning at the given exon position in this dataset that were contained in the RESCUE-ESE set. SNP density (red curve) was determined analogously using SNPs from dbSNP mapped to the exon database. Both curves were smoothed by averaging the densities over a leading (3′ss) or lagging (5′ss) window of ten nucleotides. Estimating the Frequency of ESE Disruption in Human SNPs The frequency of ESE disruption for simulated (randomly generated, unselected) mutations was compared to the frequency of ESE disruption observed in SNPs, which represent mutations that have survived selection to become reasonably frequent in the human population. SNPs are shaped by the interplay between the mutation process and the process of natural selection. Comparing simulated mutations to natural variations is an effective way to decouple these processes, and this approach has been used by others to study selective pressure in protein-coding genes ( Gojobori 1983 ; Nei and Gojobori 1986 ; Kowalczuk et al. 2001 ). Here, we describe the analysis of simulated and natural mutations using a variation of the McDonald–Kreitman test, a widely used statistical test for detecting selection in genes, that we have adapted to measure the strength of selection acting on ESEs using data from several thousand exons ( McDonald and Kreitman 1991 ; Jenkins et al. 1995 ). When considering SNPs, in order to distinguish mutations that disrupt predicted ESEs from those that create predicted ESEs, the identity of the ancestral allele must be established. Since the mutations that created most human polymorphisms occurred less than 1 million years ago ( Slatkin and Rannala 2000 ; Miller and Kwok 2001 ), long after the human–chimpanzee divergence of 5 million years ago ( Stauffer et al. 2001 ), the orthologous chimpanzee exon will almost always represent the sequence of the ancestral allele. Each of the 9,862 mapped human SNPs described previously was aligned (using a 33-nucleotide sequence window centered around the polymorphic position) to unassembled reads from the genome of the chimpanzee Pan troglodytes, accessed through the NCBI trace archives ( ftp://ftp.ncbi.nih.gov/pub/TraceDB/pan_troglodytes/ ). As the trace archives represented several-fold coverage of the chimp genomic sequence, most SNPs matched to several sequence reads. Whenever one allele of a human SNP consistently matched the chimpanzee sequence in all high-quality alignments, that allele was designated as the ancestral allele, and the other allele at that position was designated as a variant allele. The 8,408 SNPs that satisfied this criterion were then annotated for predicted ESEs in both the ancestral and variant sequence, simply by comparing the six overlapping hexanucleotides that differed between the two alleles to the set of RESCUE-ESE hexamers and recording the number of matching hexamers. It is well known that current SNP databases contain a certain rate of error. The SNP consortium estimated that about five percent of their submissions were false positives attributed to base calling errors ( Altshuler et al. 2000 ). Incorrect mapping can also result in the misclassification of nearly identical paralogous regions as SNPs ( Bailey et al. 2002 ; Cheung et al. 2003 ). The rate of false positives in dbSNP can be conservatively estimated by resequencing DNA that has been collected from many individuals. SNPs that cannot be validated in such a manner are either rare SNPs that were not present in the sample or are false positives of the SNP discovery method. Recent resequencing studies validate 60–86% of the entries in dbSNP ( Carlson et al. 2003 ; Reich et al. 2003 ). We anticipated a lower rate of false positives in the 8,408 SNPs that were used in this analysis because we removed error-prone categories of SNPs (such as those derived from ESTs or duplicated regions) from our data set. Despite this expected improvement, our initial analysis focused on the subset of 2,561 SNPs that had been validated by resequencing and were thus assumed to be free of errors (see Materials and Methods ). This precaution was taken because the measurement of ESE disruption is particularly sensitive to artifacts (unpublished data). The annotation of RESCUE-ESE hexamers in a biallelic SNP results in one of four possible outcomes: no ESE hexamers in either allele (ESE neutrality, − −), one or more ESE hexamers only in the ancestral allele (ESE disruption, + −), one or more ESE hexamers only in the variant allele (ESE creation, − +), or one or more ESE hexamers in both alleles (ESE alteration, + +). The latter category is referred to as ESE alteration because the sets of RESCUE-ESE hexamers in the ancestral and variant alleles are, of course, different, and therefore may not necessarily be recognized with the same affinity by the same trans -factor(s). The relative frequencies of these four outcomes are listed in Figure 2 A in the row labeled “Selected (SNP).” Since the 238 RESCUE-ESE hexamers represent only a small fraction (approximately 6%) of the 4,096 possible hexanucleotides, it was not surprising that a large majority of SNPs fell into the ESE-neutral category. To determine whether the rate of ESE disruption in SNPs was higher or lower than what would be expected from unselected mutations, we performed a Monte Carlo (random) simulation of point mutations in human exons. Figure 2 Analysis of the Effects of SNPs and Unselected Mutations on Predicted ESEs (A) The percentages of the four prediction outcomes. ESE disruption (+ −), ESE alteration (+ +), ESE neutrality (− −), and ESE creation (− +) changes are listed for the set of 2,561 validated SNPs (selected) and for the set of 100,000 simulated (unselected) mutations. (B) Synonymous and nonsynonymous mutations were analyzed separately and then compared using the MH test for homogeneity. All outcomes passed the MH test for homogeneity (H 0 :Outcome synon ≈ Outcome nonsynon ; p < 0.05) and could, therefore, be combined into a summary OR (weighted combination of the ORs measured in the synonymous and nonsynonymous sets). The height of each bar can be interpreted as the odds that the listed outcome will occur in the evolutionarily selected set of mutations (SNPs) relative to the odds that the same outcome will occur in the unselected (simulated mutation) set. Error bars extend one standard deviation on either side of the calculated value. Reduced Frequency of ESE Disruption in SNPs versus Unselected Changes Mutations were simulated at random in human exons using nucleotide substitution frequencies that reflect the mutational biases observed in unselected regions of the genome with similar nucleotide composition. In vertebrates, the greatest biases in nucleotide-to-nucleotide substitution frequencies are related to the hypermutability of C residues ( Duncan and Miller 1980 ) and the higher rate of transitions (C ↔ T, A ↔ G) relative to transversions (purine ↔ pyrimidine). Rates for different base changes have been estimated from analysis of aligned sequences which are assumed to be under no selective pressure. For example, transitions make up 67–70% of all substitutions in human pseudogenes and 65.5% of all substitutions in genomic repeat sequences ( Graur and Li 2000 ; Hardison et al. 2003 ; Zhang and Gerstein 2003 ). Using the substitution frequencies derived from a recent large-scale study of nucleotide substitution patterns in processed pseudogenes ( Zhang and Gerstein 2003 ), mutations were simulated in the set of approximately 121,000 GENOA-annotated internal human exons and the effects on predicted ESEs were analyzed as described above for SNPs. The simulation captured the influence of nearest-neighbor bases on the pattern and rate of nucleotide substitution. These nearest-neighbor effects are particularly pronounced for CpG dinucleotides, where an elevated C-to-T mutation rate is observed as an indirect consequence of cytosine hypermethylation. Comparing the results of this simulation to those observed for SNPs (listed as “Selected (SNPs)” in Figure 2 A), the most striking difference was observed for the category of ESE disruption: 13.6% of simulated (unselected) mutations caused ESE disruption compared to only 10.9% of SNP mutations. This difference implies a significant selective disadvantage for mutations that disrupt RESCUE-ESE hexamers. To assess the degree of selection on ESEs, one standard measure is the relative risk (RR), defined in this instance as the ratio of the frequency of ESE disruption in SNPs to the frequency of ESE disruption for unselected mutations (e.g., RR = 10.9%/13.6% = 0.80, using the pooled data from Figure 2 A). In this instance, we preferred to use the slightly more complex odds ratio (OR) measure to quantify this effect (defined in Materials and Methods ) because of its better statistical properties ( Pagano and Gauvreau 2000 ). As expected, the SNP dataset was greatly enriched for synonymous variation relative to the simulated mutation dataset. There is a 1.3:1 ratio of synonymous:nonsynonymous changes in the SNP dataset compared to a 0.5:1 ratio of synonymous:nonsynonymous changes in the simulated dataset. This difference, which has been observed many times, suggests that more than 60% of mutations that change the amino acid sequence are eliminated by natural selection ( Graur and Li 2000 ). In order to account for the potentially confounding effect of selection occurring at the protein level, SNPs and simulated mutations were divided into synonymous and nonsynonymous groups and analyzed separately. After controlling for the higher frequency of synonymous mutations in dbSNP, the selective pressure to avoid disrupting ESEs was approximately equal for the synonymous and nonsynonymous classes of mutations (the Mantel–Haenzel [MH] test of homogeneity indicated no significant differences in the magnitude of the effect across all comparisons; χ 2 < 0.5). This observation confirms our previous result and alleviates the concern that the analysis might have been confounded by the effects of selection acting at the protein level. The summary OR (the weighted combination of the separate synonymous and nonsynonymous analysis) for ESE disruption was 0.82 ± 0.05 ( Figure 2 B), which implies that natural selection has eliminated approximately 18% of arising point mutations that disrupt RESCUE-ESE hexamers ( p < 0.001). Base changes that alter one or more predicted ESE hexamers but result in creation of other RESCUE-ESE hexamers (ESE alteration) are also selected against, but to a somewhat lesser degree ( Figure 2 B, “+ +” category). This observation is not surprising given that these changes may alter the specific combination of SR proteins which interact with the exon and consequently alter ESE activity. In our previous study, we found that ESE alteration mutations would often cause an increase or decrease in enhancer activity, as determined in vivo using a splicing reporter construct ( Fairbrother et al. 2002 ). SR proteins generally have distinct, though sometimes overlapping, RNA binding specificities and vary in their ability to activate splicing ( Graveley et al. 1998 ; Liu et al. 1998 ). Therefore, some ESE alteration mutations that result in one SR protein replacing another SR protein may weaken the ESE and disrupt splicing. In addition, there are situations where the simultaneous binding of multiple activator proteins on a substrate is critical for correct processing of that pre-mRNA ( Tian and Maniatis 1993 ). In such a case, it is unlikely that one ESE could be exchanged for another without deleterious consequences. At first glance, the overrepresentation of some categories in this analysis may seem surprising. However, this is simply a consequence of the underrepresentation of disruption and alteration mutations in the SNP pool causing the remaining two categories of variation, ESE neutrality and ESE creation, to appear slightly overrepresented in SNPs relative to unselected mutations ( Figure 2 B). As mutations that result in a selective disadvantage are rapidly eliminated from the population, an increasing fraction of the mutations that persist as SNPs will be selectively neutral ( Graur and Li 2000 ). In other words a neutral variant will, on average, be eliminated less rapidly than a disadvantageous variant and so the set of neutral variations will come to represent an increasing fraction of the total (diminishing) pool of variants. The analysis presented here divides SNPs into four categories based on ESE annotation. As variations from two of these categories (ESE disruption and ESE alteration) are shown to be preferentially eliminated by natural selection, the remaining two categories (ESE neutrality and ESE creation) will represent a larger fraction of a diminished total pool and, therefore, appear enriched ( Figure 2 B). Selective Pressure Is Strongest for ESEs Located near Splice Sites Experiments measuring the splicing activity of substrates with variations in the distance between a well-characterized ESE and the 3′ss have demonstrated a strong proximity effect, with ESE activity decreasing as the distance from the splice site increases ( Lavigueur et al. 1993 ; Graveley et al. 1998 ). Although the closest ESEs tested in the distance studies were 70 nucleotides away from the splice sites, other studies have demonstrated that ESEs can function at much closer distances to splice sites ( Nelson and Green 1988 ; Coulter et al. 1997 ). In order to test the generality of this distance effect, we quantitated the selective pressure on ESEs in distal and proximal windows at both the 3′ss and the 5′ss ( Figure 3 ). Validated SNPs that fell within a particular exon region (e.g., the first 20 nucleotides of the 3′ss proximal window is defined as region A in Figure 3 ) were compared to unselected (simulated) mutations that fell in the same region, and summary ORs for ESE disruption were calculated for the four exon regions shown. Consistent with higher ESE activity for ESEs located near splice sites, we observed a pronounced increase in the conservation of RESCUE-ESE hexamers located within 20 bases of either the 5′ss or 3′ss ( p < 0.05) relative to predicted ESEs located further from splice sites ( Figure 3 ). Figure 3 Selection against Disruption of Predicted ESEs in Different Exon Regions Summary ORs were calculated for mutations that disrupt RESCUE-ESEs as in Figure 2 , for each of four regions spanning the length of a typical human internal exon. The heights of the blue bars represent the odds that an ESE will be disrupted by a mutation in the set of 2,561 validated SNPs (selected mutations) relative to the odds of disruption in the set of 100,000 simulated (unselected) mutations. Error bars extend one standard deviation on either side of the calculated value. SNP Analysis Identifies Conserved ESEs Our observations that SNPs tend to avoid disrupting RESCUE-ESE hexamers (see Figure 2 ) and that the magnitude of this selection increases near splice sites ( Figure 3 ) indicate that this set of hexamers represents a physiologically important collection of sequences across many human exons and genes. Although all RESCUE-ESE hexamers tested to date have ESE activity in cell culture assays, we have tested only a small fraction of the 238 individual hexamers, and presumably some members of this set may be false positives of the RESCUE-ESE method. In order to better define functional hexamers in the RESCUE-ESE set, we repeated the selected versus unselected comparisons for each hexamer individually using the larger set of 8,408 exonic SNPs described previously. For each RESCUE-ESE hexamer, we counted cases where a hexamer was interrupted by a mutation that has survived selection (SNP mutations) and compared this frequency to the value we would expect in the absence of selection (simulated mutations). For this analysis we used a simple RR measure, defined as the frequency with which a hexamer overlaps with SNPs relative to the frequency with which the same hexamer overlaps with simulated mutations. This ratio (frequency SNP /frequency simulated ) was calculated for each hexamer and provided a means of assessing the selective pressure on each hexamer. The RR for a hexamer that was under no additional selective pressure would therefore be equal to 1.0, and a hexamer under increased selection would have an RR of less than 1. Consistent with our previous analysis (see Figure 2 ), the majority of RESCUE-ESE hexamers (162 hexamers) had an RR of less than 1 ( Figure 4 A), suggesting that many RESCUE-ESE hexamers are subject to purifying selection. Figure 4 Measuring Selective Pressure on Each RESCUE-ESE Hexamer Any point mutation alters six overlapping hexamers, and so a database of 8,408 SNP mutations alters a total of approximately 50,000 hexamers in the wild-type (ancestral) allele. In considering all 238 RESCUE-ESE hexamers, the frequency of each ESE hexamer in the total set of ancestral alleles was recorded for the database of SNPs and simulated mutations (8,408 SNP mutations and 100,000 simulated mutations). The ESE frequency in the SNP set was divided by the ESE frequency in the simulated set to calculate the RR for each of the 238 hexamers. (A) The distribution of RR for all 238 ESE hexamers is plotted on a logarithmic scale. A resampling strategy was used to identify 57 ESE hexamers that were significantly conserved (pink bars have an RR less than 1; p < 0.05) and also six ESE hexamers that were not conserved (blue bars have an RR greater than 1; p < 0.05). (B) The output of RESCUE-ESE was compared for several vertebrate genomes (human, mouse, pufferfish, and zebrafish). The set of 238 human RESCUE-ESE hexamers was divided into nonoverlapping subsets based on their conservation in the RESCUE-ESE output generated from other vertebrates. The proportion of ESEs that were significantly conserved in the SNP analysis (as described above in [A]) were recorded for each subset of RESCUE-ESE hexamers and are represented as pink sectors in the pie chart. While the somewhat limited size of the currently available SNP databases limits our power to detect selection acting on individual hexamers, it was possible to detect a subset of hexamers that displayed a statistically significant level of conservation. A bootstrap sampling strategy identified a total of 57 hexamers with RRs of significantly less than 1 ( Figure 4 A, pink bars) compared to only six hexamers with RRs significantly greater than 1 ( Figure 4 A, blue bars). By comparison, testing a set of 238 arbitrary hexamers would be expected to yield approximately 12 significant hexamers in each of these categories at a p value cutoff of 0.05. Included within the set of 57 conserved ESEs are hexamers corresponding to the well-characterized “GAR” and AC-rich ESE classes ( Coulter et al. 1997 ) and several other types of ESEs (see Supporting Information ). A comparison of RESCUE-ESE predictions for four different vertebrates (G. Yeo, S. Hoon, B. Venketesh, and C. B. B., unpublished data) revealed a strong correspondence between within-species conservation (SNP analysis) and cross-species conservation ( Figure 4 B). In other words, the ESE hexamers that appeared to be under the greatest selective pressure within the time frame of the SNP analysis (the last hundreds of thousands of years) were more likely to retain the characteristics used by the RESCUE approach to identify ESEs over the time frame of vertebrate speciation (the last tens to hundreds of millions of years). While only a minor fraction (11%) of the hexamers that appear exclusively in the human lineage were significantly conserved in the SNP analysis (RR < 1; p < 0.05), about half of the hexamers predicted to be ESEs in all four vertebrates examined (human, mouse, zebrafish, and pufferfish) were significantly conserved in the SNP analysis. In the future, with a larger SNP database and more genomes available, it should be possible to use these methods to analyze more individual hexamers for evidence of selective pressure. As mentioned previously, the public SNP database used in this study contains a significant fraction of entries that could not be validated by resequencing. If these unvalidated entries in dbSNP were errors, they would not be expected to specifically avoid ESEs, or particular exon positions. Therefore, SNP artifacts are likely to reduce, rather than increase, the apparent significance of the biases in the nature and distribution of SNPs that we have observed. Here we have shown, using polymorphism data, that RESCUE-ESE hexamers have been preferentially conserved in the recent evolutionary history of the human lineage and that the strength of this conservation increases with increasing proximity to the splice sites. These results imply that splicing imposes important constraints on the evolution of human exons. As the size and quality of the SNP database is rapidly increasing, measures of selection deriving from SNP data are likely to become increasingly useful for evaluating the function of short, degenerate sequence elements like ESEs. For example, it should be possible to use the VERIFY method to analyze selection on motifs that are postulated to control transcription, polyadenylation, messenger RNA (mRNA) stability, or translation. The current build of dbSNP contains 360,000 SNPs that are located in a “locus region” within 2 kb upstream of the transcript start site or 500 bp downstream of the polyadenylation site ( Sherry et al. 2001 ). There are also more than 500,000 SNPs localized to the untranslated regions of mRNAs where elements that modulate translation, polyadenylation, and mRNA stability are thought to be located. The analysis presented here used 8,400 SNPs to study selection on ESE hexamers. Making the simplifying assumptions that ESE hexamer frequencies are both uniform and slightly elevated in exons and are mutated without bias, we can roughly estimate the statistical power of the VERIFY method to detect selection (see Materials and Methods ). For example, the set of ESE hexamers, as a whole, is under selective pressure (OR = 0.82), but this selective pressure will vary according to hexamer, with some hexamers being highly conserved and others less so ( Figure 4 ). Our ability to detect conservation at the level of the individual hexamers depends upon (1) the degree of hexamer conservation (large differences are easier to detect than small differences) and (2) the number of times a SNP interrupts an ESE hexamer (larger data size increases our confidence in individual measurements and, therefore, increases our ability to measure differences). The VERIFY method could detect about 70% of strongly conserved hexamers (OR > 0.5) in the set of 238 ESE hexamers using 8,400 SNPs. A similar type of analysis performed with 500,000 SNPs would not only detect almost all the strongly conserved motifs but would be able to detect motifs under a weaker degree of selection (OR > 0.77) with a similar power (approximately 70%). As an alternative to using polymorphisms within a species, VERIFY could also utilize variations between closely related species to study selection on gene control elements. In addition, this work identifies two new categories of mutations that are under selective pressure: mutations that disrupt or alter RESCUE-ESE hexamers. This increased selective pressure presumably reflects the increased likelihood that such variations will alter splicing and, therefore, gene activity. Several cases of polymorphisms which result in allele-specific differences in splicing have been reported ( Betticher et al. 1995 ; Stallings-Mann et al. 1996 ; Stanton et al. 2003 ). Here, we identify features such as proximity to splice sites and ESE disruption and alteration that should prove useful in discovering additional polymorphisms that affect splicing. As splicing mutations constitute at least 14% of disease-causing mutations ( Stenson et al. 2003 ), polymorphisms that affect splicing would be good candidates for association studies intended to identify genetic contributors to quantitative traits or diseases. An additional benefit of using variations that are predicted to result in altered splicing relates to the feasibility of validating an RNA phenotype. While variations predicted to alter protein activity may require gene-specific activity assays or antibodies, RNA phenotypes such as exon skipping can be readily screened by RT-PCR, thus enabling large scale phenotyping of genotyped cell lines. Materials and Methods SNP data Build 112 of dbSNP was downloaded from the NCBI ftp server ( ftp.ncbi.nih.gov ) and parsed from the XML format, which integrates data (e.g., annotation, sequence, transcript) from several sources ( Sherry et al. 2001 ). A current description of the database structure is available online ( http://ncbi.nih.gov/ ). To limit the contribution of erroneous SNPs, several filters were applied to produce the set of SNPs used in this analysis. First, SNPs located within a coding region in the assembly annotation were required to align to an internal exon in the GENOA exon dataset. GENOA is a genome annotation script that annotates exons by spliced alignment of mRNA/cDNA sequence to an assembled genome, applying a number of checks on the quality of the resulting alignments (see below). SNPs that mapped to multiple genomic regions, to known repetitive elements, to regions where the reading frame differed in the genomic/transcript alignment, or to an entry that had been contributed in the context of spliced transcripts (e.g., through comparison of ESTs) were excluded. We also removed entries where both versions of a SNP contained a match to either the human exon database or the chimpanzee (Pan troglodytes) genome ( ftp://ftp.ncbi.nih.gov/pub/TraceDB/pan_troglodytes/ ). From the resulting pool of reference SNPs, entries associated with genotype data (population frequency) were used to build a validated SNP set. Unless otherwise indicated, SNPs were aligned to other sequences only when a perfect (33/33) base match was obtained using BLAST ( Altschul et al. 1997 ) with one or the other of the polymorphic alleles. Exon data Datasets of internal human exons were generated by spliced alignment of cDNA sequences from GenBank (release no. 134) to the assembled, masked human genome sequence (GoldenPath assembly HG13, http://genome.ucsc.edu ) using the genome annotation script GENOA (D. H., Lee P. Lim, R.-F. Yeh, U. Ohler, and CBB, unpublished data). The exon/intron structures were inferred from at least two cDNA/genomic alignments, and the reading frame was determined from the CDS annotation of the GenBank cDNAs. As RESCUE-ESE hexamers were identified in constitutively spliced exons and alternative splicing sometimes results in ambiguous splice site positions, we confined our analysis to exons which showed no (cDNA) evidence of alternative splicing. Therefore, exons present in some, but not all, cDNA alignments overlapping a genomic region were excluded. In addition, it was required that each exon (1) be flanked by introns whose ends matched the consensus terminal dinucleotides of U2-type or U12-type introns (GT-AG, GC-AG, or AT-AC) and (2) be in an open reading frame that spanned at least three exons (the exon being considered and at least one flanking exon on either side). Simulation of exon mutations A Monte Carlo simulation was used to estimate background frequencies, in humans, of ESE-disrupting, ESE-creating, ESE-neutral, and ESE-altering mutations in internal exons. A PERL script simulated point mutations in sequences during multiple passes through the GENOA exon dataset. For each exon considered, the script utilized a set of randomly generated numbers to dictate the following sequence of decisions: (1) whether a mutation would occur in an exon, (2) the position where a mutation would occur, and (3) the identity of the variant allele. Mutations were simulated in present-day internal coding exons with a probability of occurrence proportional to the length of the exon and no a priori strand or position bias. The output mutations were stored in reference SNP format and annotated with predicted ESEs as described in the text. The mutation probabilities and the pattern of substitution are functions of the input sequence (i.e., the base to be mutated and the 3′ neighboring base). The values of all 12 nucleotide-to-nucleotide substitution probabilities used here were considered for all four possible 3′ neighboring-base contexts. The distribution of dinucleotide substitution probabilities (48 possible) used in this work was derived from a large study of mutation in ribosomal protein pseudogenes (all substitution probabilities were extracted from Figure 2 except those for CpG, which were obtained from Figure 1 using the assumption that both transversion values, i.e., CpG to ApG and CpG to GpG, were of equal probability [ Zhang and Gerstein 2003 ]). These probabilities reflect the context effect of the nucleotide 3′ of the substituted base averaged over all four possible 5′ contexts. If neighboring-nucleotide effects are not independent and the relevant context encompasses more sequence than is being considered in the simulation, this may result in a slight effect on the substitution pattern generated by the simulation. The dominant well-known contextual influences, such as those seen in the CpG dinucleotide, are captured in the simulation. Total genomic sequence was used to derive the substitution rates and simulate mutations. Features that could potentially influence the mutation process, such as the extent of CpG methylation, regional GC content, or recombination rates, could not be explicitly incorporated into the simulation. However, the analysis and simulation excluded first exons (reducing the contribution of unmethylated CpG in CpG islands), and these other variables affected the result of this analysis only to the degree that they altered the substitution pattern, as distinct from the overall mutation rate. Analysis Mutations were annotated in terms of their effect on overlapping RESCUE-ESE hexamers as ESE disruption (+ −), ESE creation (− +), ESE alteration (+ +), or ESE neutrality (− −). In the annotations, the first position refers to the wild-type or ancestral allele, where “+” indicates one or more ESE hexamers and “−” indicates no ESE hexamers. The ESE alteration category can include mutations in which a net gain or a net loss of ESE hexamers is annotated. All annotations used the set of 238 RESCUE-ESE hexamers described previously ( Fairbrother et al. 2002 ). ORs (rather than RRs) were used to quantify the difference between the set of experimentally validated SNPs and simulated mutations in Figures 2 and 3 . Briefly, the relative OR is defined here as where P(outcome|selection) represents the probability that SNP (a mutation under selection) will have a particular ESE annotation outcome (+ +, + −, − −, or − +). The extent of selection was measured separately for synonymous and nonsynonymous mutations and standard methods were used to calculate 95% confidence intervals ( Pagano and Gauvreau 2000 ). The MH test was used to determine whether the degree of selection was independent of synonymy. Experimentally validated SNPs that were located in the first or last 70 nucleotides of an exon were evaluated for ESE disruption as a function of position. As no restrictions were placed on exon size, it was possible for SNPs in small exons to be placed in multiple categories (as was the case for approximately 20% of all SNPs). ORs were used to measure the extent of selection, and significance was assessed at an α level of 0.05 (one-tailed) for ESE disruption mutations in the four different regions of an exon. Bootstrap sampling was used to determine hexamers that were significantly avoided by SNPs. RR was used to compare the selection on individual hexamers over the course of 5,000 trials. For each trial, 8,408 SNPs were sampled with replacement from the set of 8,408 SNPs described in the text. The frequency of cases where an ESE coincided with an SNP was calculated for each of the 238 RESCUE-ESE hexamers and divided by the expected frequency for that hexamer (determined through simulation). This ratio of frequencies was used to estimate RR for each hexamer. Dividing the instances where RR was greater than 1 by the number of trials (5,000) provided a bootstrap p value for each of the 238 hexamers. The interspecies comparisons considered the output of RESCUE-ESE on four vertebrate genomes: human, mouse, zebrafish, and pufferfish. The set of human hexamers was divided into subsets according to the degree of conservation across vertebrates in the following manner: Hexamers that were only present in humans defined set 1; hexamers present in human and mouse, set 2; hexamers present in human, mouse, and one of the fish species, set 3; hexamers present in human, mouse, zebrafish, and pufferfish, set 4. The degree of overlap between these hexamer sets and the RESCUE-ESE hexamers with an RR of significantly less than 1 was recorded and displayed in Figure 4 B. Power calculations for single hexamer analysis were performed as described previously ( Pagano and Gauvreau 2000 ; method, pages 243–246; estimation of standard error as a function of sample size, page 355). For the purposes of the power calculation the mutations were assumed to be unbiased and the ESE hexamers were assumed to have a slightly elevated frequency (1.5/4,096 = 3.7 × 10 −4 rather than 2.4 × 10 −4 ), and so a particular ESE would be expected to be interrupted by a SNP at any one of six positions with a frequency of 6 × 3.7 × 10 −4 = 2.2 × 10 −3 . This probability was used to estimate the number of variations that would interrupt (disrupt or alter) an ESE hexamer with and without selection for the different SNP database sizes and degrees of selection (ORs) described in the text. Supporting Information URLs http://genes.mit.edu/burgelab/rescue-ese/ . An online tool to annotate RESCUE-ESE hexamers in exons. http://genes.mit.edu/burgelab/Supplementary/fairbrother04/ . Contains exon, SNP, RR, and ancestral allele databases used and/or generated in this study.

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521195

HIV-1 Vif and APOBEC3G: Multiple roads to one goal

The viral infectivity factor, Vif, of human immunodeficiency virus type 1, HIV-1, has long been shown to promote viral replication in vivo and to serve a critical function for productive infection of non-permissive cells, like peripheral blood mononuclear cells (PBMC). Vif functions to counteract an anti-retroviral cellular factor in non-permissive cells named APOBEC3G. The current mechanism proposed for protection of the virus by HIV-1 Vif is to induce APOBEC3G degradation through a ubiquitination-dependent proteasomal pathway. However, a new study published in Retrovirology by Strebel and colleagues suggests that Vif-induced APOBEC3G destruction may not be required for Vif's virus-protective effect. Strebel and co-workers show that Vif and APOBEC3G can stably co-exist, and yet viruses produced under such conditions are fully infectious. This new result highlights the notion that depletion of APOBEC3G is not the sole protective mechanism of Vif and that additional mechanisms exerted by this protein can be envisioned which counteract APOBEC3G and enhance HIV infectivity.

In contrast to most animal viruses, infection with the human and simian immunodeficiency viruses results in prolonged, continuous viral replication in the infected host. Remarkably, viral persistence is not thwarted by the presence of apparently vigorous, virus-specific immune responses. Several factors, including the evasion of an innate cellular anti-viral defense by HIV-1 as discussed in a recent Retrovirology article [ 1 ], are thought to contribute to persistent viral replication. Most notably during its course of engendering the development of acquired immunodeficiency syndrome (AIDS), HIV-1 mutates with high frequency and thus avoids immune response and intracellular defense mechanisms [ 2 ]. Interestingly, it has been observed for several years that the genomes of HIV-1, other retroviruses, and hepatitis B viruses show under certain conditions a very high rate of G-to-A hypermutation [ 2 - 5 ]. Earlier, this mutagenic phenomenon was attributed to the error-prone retroviral reverse transcriptase together with imbalances in the available deoxynucleotide pools in the cell. However, more recently a new player has been discovered, and new studies implicate the host cell cytidine deaminase APOBEC3G as responsible for G-to-A hypermutation in viral genomes [ 4 , 6 ]. APOBEC3G is a virion-encapsidated cellular protein that deaminates dC to dU in minus-strand viral cDNA during reverse transcription [ 7 - 10 ]. The uracil-containing cDNA may then activate a cellular uracil-DNA-glycosidase causing the failure of reverse transcription. This failure is characteristic of Vif-defective virus and results in the impairment of proviral integration into the host genome [ 10 , 11 ]. Furthermore, even if the reverse transcription is completed at low efficiency and the resulting proviral double stranded cDNA is integrated into the cellular genome, the massive C-U conversion in the minus strand leads to pervasive G to A hypermutation of the proviral plus-strand cDNA [[ 5 , 7 , 8 ], and [ 10 ]]. Thus, APOBEC3G is a member of a group of innate cellular antiviral response factors that limit the damage inflicted by viruses to their hosts (Figure 1 ). Figure 1 Schematic representation of Vif and APOBEC3G interactions during the HIV-1 replication cycle. Red arrows represent Vif action during the HIV-1 viral replication in non-permissive cells. Green arrows represent APOBEC3G/3F action in viral HIV-1 Vif defective virus. Broken arrows represent inhibition of APOBEC3G activity by Vif. Question marks (?) represent unresolved questions about Vif and APOBEC interactions. Box1: Schematic representation of minus-strand DNA and/or viral RNA deamination by APOBEC3G/3F [48]. Box2: Degradation model of APOBEC3G induced by Vif; Vif interacts with APOBEC3G as part of a Vif-Cul5-SCF complex resulting in the polyubiquitination and proteasomal degradation of APOBEC3G. Vif may have been derived from a cellular SOCS box protein that targets APOBEC 3G to the ECS ubiquitin ligase [49]. Two possible pathways of APOBEC3G regulation by Vif are represented. The effects of APOBEC3G and its G-to-A deaminase activity on the survival of wild type HIV-1 vif + virus are not known; but, current observations are that APOBEC3G confers a major deleterious effect to the HIV-1 genome when the Vif protein is absent. Historically, Vif has been known to play a dramatically important role in HIV-1 infectivity [ 12 , 13 ]. Vif is a basic protein of 23 kDa which is packaged into virions and which is required in virus producing cells during the late stages of infection to enhance viral infectivity by 10-to-1000 folds [ 14 - 17 ]. HIV-1 vif -defective virus can replicate in some permissive cells such as Jurkat and SupT1 cells, but cannot replicate in other non-permissive cells such as macrophages, primary human T cells, and some restrictive T cell lines [ 18 - 20 ]. For a very long time, it was not known what determined the difference between a permissive versus a non-permissive cell. The answer to this long-standing puzzle came when Michael Malim's laboratory found that non-permissive cells contain the anti-viral cellular factor APOBEC3G, and that the anti-viral action of APOBEC3G is thwarted by Vif [ 4 ]. Following on the heels of that initial observation, an enormous amount of effort emerged from several laboratories directed at elucidating how Vif mechanistically counteracts APOBEC3G in order to protect HIV-1 (Figure 1 ). Subsequent results showed remarkably that APOBEC3G binds Gag nucleocapsid NC protein, and in the absence of Vif, it is incorporated into the viral particle in close proximity to the reverse transcription complex [ 21 ]. Whether this interaction explains previous results on viral core stability or downstream effects during reverse transcription remains unclear [ 22 ]. Additionally, it was shown that Vif inhibited translation of APOBEC3G and/or its intracellular half-life [ 23 - 29 ]. In this regard, elegant biochemical studies showed that Vif interacted with APOBEC3G as part of a Vif-Cul5-SCF complex which led to the polyubiquitination and proteasomal degradation of APOBEC3G [ 30 ]. These latter results provided the mechanistic basis for the current accepted paradigm whereby increased degradation and/or reduced ambient level of APOBEC3G caused by Vif hinders the incorporation of APOBEC3G into virions. This consequently leads to an absence of APOBEC3G during reverse transcription in the virion-infected target cell, thereby permitting HIV-1 to replicate more robustly (Figure 1 ). Now the report by Kao et al . adds a new wrinkle to this model by demonstrating that production of infectious human immunodeficiency virus type 1 does not require physical depletion of APOBEC3G in the presence of Vif from virus-producing cells [ 1 ]. Kao's study is remarkable for the fact that it raises the possibility of an alternative mechanism of viral protection from APOBEC3G by Vif. Indeed, some previous studies have shown drastic effects of Vif on steady-state amounts of APOBEC3G while others have found only modest effects [ 4 , 25 - 29 ]. Using confocal microscopy, Strebel and co-workers directly compared different methods of immunofluorescence to evaluate the expression of APOBEC3G at the single-cell level in absence or presence of Vif. Strikingly, depending on the fixation method and antibodies used, the results obtained showed variations in the number of cells which express APOBEC3G and Vif concomitantly. Thus, it is conceivable that direct binding of Vif to APOBEC3G may have alterred the deaminase's conformation, covering epitopes recognized by some of the antibodies used to detect APOBEC3G. Notably, most published studies have used APOBEC3G tagged at its N-terminus or C-terminus. Nevertheless, it should be kept in mind that a possible conformational change in APOBEC3G triggered by Vif-binding may also expose hydrophobic domains that are recognized by the ubiquitination and/or degradation machinery [ 31 , 32 ]. Thus, ubiquitination of APOBEC3G may still occur under the conditions used by Kao et al , but as demonstrated by these authors no degradation of APOBEC3G ensued. In this respect, protein ubiquitination could be not only a signal for protein turnover, but also a signal for cellular localization. An illustrative example of this concept is the putative ubiquitination of p6 protein in which findings by Strack et al . suggested that the engagement of the ubiquitin conjugation machinery by L domains plays a crucial role in the release of enveloped virus [ 33 ]. Many examples of allosteric alteration by protein-protein interaction are reported in the literature, and further work is necessary to evaluate possible conformational switches induced by Vif [ 34 - 36 ]. Bearing this in mind, it is noteworthy that a single amino acid substitution from D (aspartate)128 to K (lysine) in APOBEC3G can render this protein resistant to depletion by HIV-1 Vif [ 37 - 40 ]. It is possible that this amino acid represents a direct contact point for Vif, or that a change at this position influences the global conformation of the enzyme. Previous studies support the notion that this amino acid is positioned in a protein loop and is suitable for protein contact [ 38 ]. Thus, it is possible to speculate that Vif interaction with APOBEC3G at this position might alter protein conformation changing its biochemical and biophysical properties in ways that are larger than that normally expected from altering just one amino acid position in a protein. Elegant studies on the involvement of D128 in species specificity of Vif to counteract APOBEC3G function are, in part, consistent with this hypothesis [ 37 - 40 ]. Additionally, the D to K amino acid change at position 128 of APOBEC3G may alter the negative electrostatic interaction of aspartate to a positively charged amino acid which may inhibit Vif-induced allosteric changes. Conversely, if APOBEC3G from African green monkey, AGM, cells is considered, the positively charged lysine 128 found in this protein cannot interact with HIV-1 Vif but may instead do so with SIVAGM Vif, probably by using a negatively charged protein pocket. Thus, one idea is that conformational changes can result only from species-specific interaction between Vif and its cognate APOBEC3G. Although this model may be attractive, further refinements should be investigated since the isoelectric points of HIV-1 Vif and SIVAGM Vif are similar. Indeed, this assumption could be tested by studies similar to those of Kao et al using APOBEC3G with SIVAGM Vif or HIV-2 Vif, together with the role of these proteins in the context of APOBEC3F [ 41 , 42 ]. In the work of Kao et al ., the authors explored the possibility that the different expression systems used by them and others could explain the discrepant results obtained on Vif-induced APOBEC3G depletion. For this hypothesis to hold several factors may be envisioned to interfere with the APOBEC3G-depletion mechanism of Vif. For example, one way to stabilize and activate p53 in cells is by interfering either with the interaction of MDM2 and p53 or with the ability of MDM2 to target its bound p53 for degradation [ 34 , 35 ]. Making a parallel between MDM2-p53 and Vif-APOBEC3G, two mechanisms can be hypothesized: one through changes in both proteins due to covalent modifications, and the other through non-covalent regulation of Vif-APOBEC3G association. In the case of MDM2-p53, it is apparent that both mechanisms are observed under different experimental conditions: induced phosphorylation of p53 can attenuate the p53-MDM2 interaction, and alternatively the human protein p14 ARF can bind to MDM2 and prevent its destruction of p53. Interestingly, these two mechanisms of p53 regulation appear to be entirely independent of each other, and emanated through distinct signal pathways. Using this parallel, one cautions that the findings of Kao et al . of a lack of APOBEC3G depletion do not rule out the possibility that Vif, under different conditions, can mediate proteasome dependent degradation of this deaminase [ 1 ]. Further research directions can be designed to evaluate additional putative regulatory mechanisms of APOBEC3G activity. For example, exposure of cells to a variety of extracellular stimuli leads to the rapid phosphorylation, ubiquitination, and ultimately proteolytic degradation of cellular proteins like IkappaB, which frees NF-kappaB to translocate to the nucleus where it regulates gene transcription [ 36 ]. NF-kappaB activation represents a paradigm for controlling the function of a regulatory protein via ubiquitination-dependent proteolysis, as an integral part of a phosphorylation based signaling cascade. After phosphorylation, the IKK phosphoacceptor sites on IkappaB serve as an essential part of a specific recognition site for E3RS (IkappaB/beta-TrCP), a SCF-type E3 ubiquitin ligase, thereby explaining how IKK controls IkappaB ubiquitination and degradation. A parallel may be envisaged for the regulation of Vif-induced APOBEC3G ubiquitination and the consequent depletion. It was reported recently that Vif is monoubiquitinated in the absence of APOBEC3G [ 28 ]. In addition, when Vif is co-expressed with APOBEC3G it is polyubiquitinated and rapidly degraded, suggesting that co-expression accelerates the degradation of both proteins [ 28 , 43 ]. Furthermore, mutations of conserved phosphorylation sites in Vif impair viral replication but do not affect APOBEC3G degradation, suggesting that Vif is important for other functions in addition to inducing proteasomal degradation of APOBEC3G. Whether or not phosphorylation regulates polyubiquitination or monoubiquitination is another open question. Kao et al . interestingly also reported that expression of Vif from a codon-optimized vector had a more pronounced effect on APOBEC3G steady-state levels than wild-type Vif from pNL-A1 [ 1 , 44 ]. Even though the expression level of Vif-optimized construct is lower than wild-type, it is conceivable that its intracellular half-life may be increased affecting the quality and constancy of Vif-APOBEC3G association. Supporting this hypothesis are results where the authors showed a partial co-localization of Vif and APOBEC3G which may be indicative of higher k off , typically resulting from a lower protein affinity. This type of finding will not be observable by physical interaction assays which employ Western blotting since only stronger bindings are detected by such technique. Kao et al . remarkably demonstrated that infectious viruses are obtained in the presence of various ratios of APOBEC3G and Vif. Nevertheless, the question of whether under their conditions APOBEC3G and/or Vif are incorporated into viral particles remains pertinent. If the deaminase is not incorporated into the viral particle, then Vif may directly or indirectly inhibit the interaction of APOBEC3G with Gag polyproteins in the cytoplasm [ 45 , 46 ]. If APOBEC3G is included in the virion, then a direct blocking of its cytidine deaminase activity by Vif can be hypothesized. To date, a direct blocking of cytidine deaminase activity in the cytoplasm that consequently inhibits APOBEC3G interaction cannot be excluded. In fact, our own studies with a bacterial deaminase system where Vif and APOBEC3G are co-expressed show that Vif-mediated interaction with APOBEC3G can inhibit its cytidine deaminase activity (Santa-Marta et al ; manuscript submitted). These results strongly support a new mechanistic function of HIV-1 Vif protein, complementing the model where Vif counteracts the inhibitory effects of APOBEC3G by enhancing its degradation via ubiquitin-proteasome pathway (Figure 1 ). The findings reported by Kao et al . together with the direct effects of Vif on the activity of cytidine deaminase (our work) may indicate an alternative protective mechanism used by HIV-1 to eliminate innate cellular immunity. Nevertheless, we cannot exclude that HIV-1 uses Vif to exert multiple mechanisms to synergistically and more effectively inhibit the anti-viral activity of APOBEC3G. In conclusion, the existence of two different mechanisms may represent two faces of the same coin, with the common goal of inhibiting APOBEC3G's anti-viral activity. As is often the case with new findings, new questions are posed. The link between APOBEC3G's enzymatic function, its degradation pathway, and its incorporation into virions in the presence of Vif is certainly to require additional attention. Answers to these questions are likely to keep many of us busy for the foreseeable future. Competing Interests None declared. Abbreviations The abbreviations used are: HIV-1, human immunodeficiency virus, type 1; Vif, Viral Infectivity Factor; SIV, simian immunodeficiency virus; NC, nucleocapsid protein; APOBEC3G, apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3G; APOBEC3F, apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3F PBMC, peripheral blood mononuclear cells; Cul5, Cullin type 5; SCF, skp1-cullin-F-box protein ligase.

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539255

Over expression of the selectable marker blasticidin S deaminase gene is toxic to human keratinocytes and murine BALB/MK cells

Background The blasticidin S resistance gene ( bsr ) is a selectable marker used for gene transfer experiments. The bsr gene encodes for blasticidin S (BS) deaminase, which has a specific activity upon BS. Therefore, its expression is supposed to be harmless in cells. The work reported on herein consisted of experiments to verify a possible toxicity of bsr on mammalian cells, which include several cell lines and primary cultures. Results Murine keratinocyte BALB/MK and human primary keratinocyte cells transduced with the retroviral vector LBmSN, which has an improved expression system of bsr , namely bsrm , died in five days after the transduction. Meanwhile the control vector LBSN, which expresses bsr , did not provoke cell death. The lethal activity of bsrm was observed only in human keratinocytes and BALB/MK cells among the cell types tested here. Death appears to be mediated by a factor, which is secreted by the BALB/MK transduced cells. Conclusion By our study we demonstrated that the expression of bsrm gene is toxic to human keratinocytes and BALB/MK cells. It is likely over expression of BS deaminase gene is responsible for the death.

Background Blasticidin S (BS) is a nucleoside antibiotic isolated from Streptomyces griseochromogenes , and has been used as a fungicide against rice blast disease [ 1 ]. BS inhibits protein synthesis in both prokaryotes and eukaryotes [ 1 ]. Later, a gene that provides resistance against BS ( bsr ) was isolated from Bacillus cereus K55-S1 strain [ 2 , 3 ]. The bsr gene possesses only 420 bp [ 4 ] and codes for an enzyme of 15 kDa, which is usually present in its dimer form [ 5 ]. The enzyme acts upon BS converting it into a deaminohydroxy derivative [ 5 , 6 ], thus it is named BS deaminase. BS antibiotic is highly toxic to mammalian cells; even 2 μg/ml is enough to kill HeLa cells in a few days. However, the cells transfected with bsr could resist against BS at several fold higher concentrations [ 7 ]. Hence, the BS/ bsr pair has been used as an efficient selection system for gene transfer experiments in many different cell types. Recently, we reported that some modifications introduced into the non-coding regions of the bsr gene ( bsrm ) resulted in an increase (several fold) of bsr gene expression, and consequently, NIH3T3 cells transduced by retroviral vectors could be selected with higher concentrations of BS in just a few days [ 8 ]. Even with such extensive use of the bsr /BS selection system, no side effects in response to bsr gene expression have been observed. Using the murine keratinocyte cell line BALB/MK [ 9 ] and human primary keratinocytes, we report here a surprising death of the keratinocytes provoked by the expression of bsrm . A detailed investigation about the death of keratinocytes, which was mediated by an unknown molecule and secreted by the BALB/MK cells transduced with LBmSN, is discussed below. Results Sensitivity of BALB/MK cells to BS To determine the range of BS concentrations and the time required for BALB/MK cell death to occur, 1 × 10 4 cells/well were incubated in a 24 well plate and 2 days later the media were replaced with a fresh one containing various concentrations of BS for 9 days. A BS concentration of at least 2 μg/ml was necessary to kill the cells in 5 days. At concentrations of BS greater than 8 μg/ml the majority of cells died within 3 days. Effect of bsrm gene and BS on BALB/MK cells To verify the effect of bsrm gene in BALB/MK cells, the cells were transduced with the LBmSN retroviral vector, which expresses the bsrm and neo R genes, and then incubated with BS. The bsrm gene was obtained by modifying the bsr gene at a non-coding region and, consequently, there was no alteration of the amino acid sequence [ 8 ]. The addition of BS at concentrations of ≤ 4 μg/ml or 500 μg/ml of G418 to cell media resulted in the death of all transduced BALB/MK (Figure 1G,1H,1I,1J,1K,1L,1M,1N,1O ). In contrast, the transduced cells incubated with BS at concentrations of ≥ 8 μg/ml reached confluence within 12 days of culture (Figs. 1P,1Q,1R ). As an experimental control, BALB/MK cells transduced with the LXSN vector (which expresses only the neo R gene) [ 10 ] were incubated in the presence or absence of 500 μg/ml of G418. As expected, the cells reached partial or complete confluence within 12 days (Figs. 1D and 1E ), as also observed with the non-transduced BALB/MK cells (Figure 1A ). BALB/MK cells not expressing the bsrm gene died in the presence of 8 μg/ml of BS (Figs. 1C and 1F ) as expected. However, the aspect of the BALB/MK cells which died after the expression of bsrm (Figs. 1G,1H,1I,1J,1K,1L,1M,1N,1O ) was different from the aspect of the non-transduced cells (Figs. 1B and 1C ) or cells transduced with LXSN (Figure 1F ) which were killed by antibiotics alone. BALB/MK cells which died after expressing the bsrm gene had a reduced cell volume when compared with normal BALB/MK or transduced BALB/MK incubated with 8 μg/ml BS (Figure 2 ). Additionally, the cells, which died after bsrm expression, remained on the plate after washing with PBS, whilst the cells killed by the antibiotics, BS or G418, were easily removed after washing with PBS (Figure 1 ). The death of BALB/MK cells was confirmed by staining with Trypane blue (Figure 1S ). Removal of BS from the medium of the cells selected with 8 μg/ml BS resulted in cell death within a week (not shown). Thus, the BS antibiotic counteracted the death effect of bsrm and therefore has a vital role to BALB/MK cells transduced with LBmSN. Effects of cell density and virus concentration upon induction of BALB/MK cell death Based on the above observations two variables were analyzed to assess their influences on the cell death: virus concentration and cell density. The total BALB/MK cells, transduced and non-transduced ones, were seeded at 1 × 10 3 to 4 × 10 4 cells in 25 cm 2 flasks and the cell death was monitored by optical microscope. The flasks containing a higher number of cells had faster cell death, even if the ratio of virus per cell was maintained constant in all flasks (Table 1 ). However, the absolute number of bsrm -transduced BALB/MK cells was higher in the flasks with higher number of seeded cells; consequently cell death was directly related to the presence of the number of bsrm -transduced cells. The virus concentration used to transduce BALB/MK cells was evaluated by infecting the cells with 1 × 10 2 to 1 × 10 5 cfu (colony forming units) of LBmSN vector. The transduced cells incubated with 8 μg/ml of BS produced resistant colonies proportionally to the used virus concentration (Figure 3 ). LBmSN-transduced BALB/MK cells that did not undergo selection died at all virus concentrations (Figs. 3G,3H,3I,3J ), although the cells transduced with 1 × 10 5 cfu died 2 days earlier than the cells transduced with 1 × 10 2 to 1 × 10 3 cfu. This is an extremely important observation since even in those wells containing less virus than cells (Figs. 3G and 3H ) cell death occurred simultaneously in each cell. This result suggests the existence of intercellular signaling of death. To confirm this hypothesis, we seeded the LBmSN transduced and non-transduced BALB/MK cells together with or without BS (Table 2 ). A clear induction of death in BALB/MK cells by the BALB/MK cells transduced with LBmSN was observed. Changes of cell morphology in each colony occurred within 5 days, as was seen in all experiments. To investigate whether the death signaling is mediated by a secreted factor, we tested the supernatant of the BALB/MK cells transduced with LBmSN on BALB/MK cells (Figure 4 ). A just two-day old medium was sufficient to induce death of normal BALB/MK cells. This result indicates that cell death was mediated by a soluble factor, secreted by the LBmSN-transduced cells, acting on both transduced and non-transduced BALB/MK cells. This factor we denominated DOKEB (Death factor Obtained from Keratinocytes Expressing Bsrm) to ease our discussion. DOKEB appears to be secreted only by LBmSN-transduced BALB/MK cells, because the 5 day old-medium from the LBmSN-transduced NIH3T3 cells had no death activity upon BALB/MK or NIH3T3 cells (data not shown). Effect of bsrm on mammalian cell lines The lethal effect provoked by bsrm was firstly observed in the murine keratinocyte cell line BALB/MK as described above. To verify this lethal effect in other cell types, we chose the cells originated from the skin or epithelium (NIH3T3, HeLa, LISP-A10, LISP-E11, HCT-8 and B16F10), because of the origin of the BALB/MK cells [ 11 ]. In addition, the rat vascular smooth muscle cells, which are useful for gene therapy experiments [ 12 ], were also tested. Until 7 days post-infection none of the above cells, which were transduced with LBmSN retroviral vector, did not die, whereas the control cell line BALB/MK died 5 days after the transduction (not shown). As the viral transduction rate is essential to analyze the possible death effect by the expression of bsrm , the cells were transduced with a ten-fold higher number of viruses than cells. Even in such conditions no cell types suffered with the expression of bsrm . To ensure the transduction and expression of bsrm in the cells, those transduced cells were selected with 8 μg/ml of BS from the non-transduced ones that die in 4 days. The selected cells were distributed to two plates, and in one plate the initial concentration of BS was maintained and in from the other plate the BS was removed. During the 7 days of observation no death was observed in both plates (not shown), which confirm the previous result that the bsrm gene is not lethal to those cell types. We also compared death activity of LBmSN and LBSN, which express bsrm and bsr respectively, on BALB/MK and NIH3T3 cells. Transduction of LBSN vector on BALB/MK or NIH3T3 cells did not cause cell death; meanwhile LBmSN caused cell death as expected (Table 3 ). In the presence of BS both cell lines transduced with LBmSN or LBSN did not die, which is a demonstration of BS deaminase gene expression, and also protection of the LBmSN transduced BLAB/MK cells against death as seen before. These results infer that over expression of BS deaminase gene could be responsible for the death of BALB/MK cells expressing bsrm . Effect of the BS analogs on BALB/MK cells The analogs of BS, cytidine, 5'-deoxycytidine, uridine and 5'-deoxyuridine, were tested in the culture of the BALB/MK cells transduced with LBmSN at 1 μM to 10 mM concentrations (Figure 4 ). Interestingly all analogs with 10 mM protected the transduced cells during 5 days of observation. Changing the medium with a fresh one containing 10 mM of each analog at every five days, the cells could be maintained alive for several passages (not shown). Effect of the bsrm gene and BS upon human keratinocytes The transduced human keratinocytes, which were modified with the virus producing cell clone PA317/LBmSN as a feeder-layer, did not grow during 8 days of culture in the absence of BS (Figure 6 ). Incubating the transduced keratinocytes with BS at 0.05 to 2 μg/ml, which are tolerant concentrations by the cells, also resulted in the absence of cell growth (not shown). However, the presence of 8 μg/ml of antibiotic, in the medium, which is a lethal concentration for the cells, resulted in the formation of many keratinocyte colonies. The number of these BS resistant colonies decreased as the BS concentration increased (Figure 6 ). The BS selected cells could be maintained alive even with the expression of bsrm if the medium is replaced every two days with a fresh one containing the initial concentration of BS. Nevertheless, if those cells were seeded on a new plate without BS they died in few days (Figure 7 ). This result confirms the vital role of BS in bsrm expressing keratinocytes, as was observed with murine keratinocyte BALB/MK cells. The vector LBmSN also expresses neo R , which provides resistance against geneticin. However, the transduced keratinocytes died after the incubation with 500 μg/ml of geneticin (Figure 6 ) even if the antibiotic was neutralized by aminoglycoside phosphotransferase. This result corroborates previous data that in keratinocytes the expression of bsrm gene leads to cell death. The keratinocytes transduced with the LXSN vector [ 10 ], which was used to construct the LBmSN vector, presented normal growth reaching complete confluence within 8 days (not shown). Discussion Here we report a surprising death caused by the transduction of the murine keratinocyte cell line BALB/MK cells with the retroviral vector LBmSN. This vector expresses bsrm which is a modified form of bsr only in the non-coding region; consequently both genes express the same BS deaminase. As the vector LBSN, which expresses bsr much lower than LBmSN [ 8 ], did not kill the cells an over expression of bsr could be responsible for the death. However, we can not discard other possibilities caused by interactions of the bsrm gene product (mRNA or protein) with intracellular molecules. In some cases the Moloney murine retrovirus can cause cell death [ 13 ]. However in our case the control retroviral vector LXSN, which was used to construct LBmSN and LBSN does not carry any viral genes [ 8 ], did not induce cell death in the same culture conditions (Figure 1 ). Additionally the wide range of viral concentrations and cell densities tested here (Table 1 and Figure 3 ) did not affect cell death. These last results corroborate the above conclusion that the death of BALB/MK cells was caused by the expression of bsrm . An interesting phenomenon of the death of BALB/MK cells expressing bsrm was that those cells can be rescued if a lethal concentration of BS (8 μg/ml to 32 μg/ml of BS were tested) is added in the medium before three days after transduction. It was a paradox, since the toxic antibiotic, BS, was able to rescue the murine keratinocyte BALB/MK induced to die by the apparently inoffensive bacterial bsrm gene. BS-rescuing process of the bsrm -transduced keratinocytes could be understood as a consequence of inhibition of the death factor (DOKEB) production by BS. Because those transduced keratinocytes could be maintained for long period (at least two months) simply by changing the medium every two days for a fresh one containing 8 μg/ml of BS (not shown). However, we do not know if the inhibition of DOKEB production is caused by the inhibition of protein synthesis by BS or just occupation of the active site of the BS deaminase by BS, and consequently inhibiting the binding of the first target molecule which is a responsible for the induction of the death process. We believe more in the last explanation, because if the analogs of BS were added to the medium at concentrations higher than 1 mM, cell death can be avoided (Figure 4 ). The requirement of higher concentration of the analogs of BS than BS, which requires only 19 μM to protect the bsrm expressing BALB/MK cells, is likely due to the low affinity of analogs for BS deaminase as expected [ 5 ]. Even though we have demonstrated that the expression of the bsrm gene in BALB/MK is lethal, the bsrm/BS selection system can still be used in keratinocytes. During the selection of LBmSN-transduced keratinocytes, the initial concentration of BS in the medium should determine a strict range of LBmSN transduced keratinocytes, which express not more and not less than certain levels of bsrm gene (Figure 6 ). Thus, for survival of those transduced cells AND selected with 8 μg/ml BS, the medium should be changed every 2 days to maintain active BS concentration in the medium; otherwise, the low BS concentration will allow the synthesis of DOKEB and in turn trigger the death mechanism. The BALB/MK cells transduced with LBmSN and selected with 8 μg/ml of BS should not be challenged with concentrations much higher than those used, since the cells expressing higher levels of bsrm gene should have died during the previous selection. Thus, the selected BALB/MK cells exist in a precarious situation where either apoptosis or necrosis can be easily activated at any unfavorable moment. We evaluated if the lethal effect provoked by bsrm occurs exclusively in BALB/MK cells or if this phenomenon is general for all cell types. In this study we included normal human primary keratinocytes and several cell lines. The human keratinocytes are resistant to BS at concentrations lower than 2 μg/ml and at concentrations higher than 8 μg/ml the cells die within 5 days (not shown). However, the keratinocytes transduced with LBmSN behaved in an opposite way. In the absence or presence of BS at low concentrations (lower than 2 μg/ml) the transduced cells died, as it was observed with the BALB/MK cells transduced with LBmSN. Additionally, the protection against the death of the BALB/MK cells expressing bsrm by the addition of a lethal concentration of BS was also observed with the human keratinocytes expressing bsrm (Figs. 6 , 7 ). These results indicate that the death process triggered by the expression of bsrm in keratinocytes should follow the same way. Interestingly the lethal effect provoked by bsrm appears to be specific to keratinocytes, because none of the cell types tested here died in our experimental conditions, except for the human and murine keratinocytes. As the gene transfer and expression of bsrm are an essential step to access the lethal effect of bsrm , an alternative strategy used to verify the gene expression and its effect was selecting the transduced cells with 8 μg/ml BS and exposing the cells to a fresh medium without BS. Even in such conditions the bsrm gene did not cause any morphological alterations to those cell types, whereas the BALB/MK cells and the human primary keratinocytes transduced with LBmSN and selected with BS died in a few days after removal of the antibiotic (Figure 7 ). Therefore, we conclude that the lethal activity of bsrm is specific to those keratinocytes. The analysis of DOKEB through exclusion molecular chromatography showed that the factor has a molecular weight equivalent of two amino acids (not shown). Therefore, DOKEB should not be BS deaminase, or even any protein. Further purification and molecular analysis are in progress. In this study we demonstrated only in vitro that the expression of the reporter gene bsrm has a lethal effect on keratinocytes. However as most of the gene therapy experiments using keratinocytes are carried out ex vivo with retroviral vectors, our finding has a very important meaning. Because the cells transduced with retroviral vector carrying bsrm and selected with BS can survive until the antibiotic is maintained in the medium, but when those cells are returned to the own organism, which has no BS in it, DOKEB will be produced and can provoke serious lesion in the body. By this study we also point out the danger of using heterologous genes, in particular those isolated from the microorganisms, in gene transfer and gene therapy experiments without proper controls. Conclusions We demonstrated in this study that the expression of the reporter gene bsrm has a lethal effect on the murine BALB/MK cell line and human primary keratinocytes. It is likely over expression of the BS deaminase gene is responsible for the death. The death appears to be mediated by a factor, which is secreted by the BALB/MK transduced cells. By this study we point out the danger of using heterologous genes, in particular those isolated from the microorganisms, in gene transfer experiments without proper controls. Methods Retroviral vectors The retroviral vectors used in the present study are based on the Moloney murine leukemia virus: LXSN [ 10 ], LBSN [ 8 ] and LBmSN [ 8 ]. The letters L, X, S, N, B, Bm of those vectors represent retroviral LTR promoter, cloning site, promoter of simian virus SV40, neomycine resistance gene (neo R ), bsr and bsrm, respectively. The LBSN and LBmSN vectors were constructed inserting the bsr and bsrm genes into the Hpa I site of LXSN, which is located in the cloning site [ 8 ]. Cell line culture The amphotropic retrovirus producing cell clones PA317/LBmSN, PA317/LBSN and PA317/LXSN [ 8 ], the murine fibroblast NIH3T3, HeLa, the human colorectal carcinoma cell lines LISP-A10 and LISP-E11 [ 14 ] were cultured in Dulbecco's modified Eagle medium (DMEM) with high glucose (4.5 g/ml), supplemented with 2 mM glutamine, 200 U/ml penicillin, 200 μg/ml streptomycin and 10 % fetal bovine serum (FBS) (InVitrogen, São Paulo, Brazil) at 37°C in a humidified atmosphere with 5 % CO 2 . The mouse fibroblast CCL-92 (ATCC) was cultured as above, except that the FBS was replaced with the bovine calf serum (InVitrogen, São Paulo, Brazil). For the culture of the murine keratinocyte BALB/MK cells (kindly provided by Dr Stuart A. Aaronson, The Derald H. Ruttenberg Cancer Center, New York, NY), EMEM (Biofluids, Rockville, MD) containing 0.05 mM CaCl 2 , 10 ng/ml of EGF and 10 % FBS was used. The human colorectal carcinoma cell line HCT-8 and the murine melanoma cell line B16F10 [ 15 ] were cultured in RPMI 1640 (InVitrogen, São Paulo, Brazil) supplemented with 0.2 % NaHCO 3 , HEPES 10 mM, pH 7.3, 40 μg/ml garamicine and 10 % FBS at 37°C in a humidified atmosphere with 5 % CO 2 . Rat primary smooth muscle cell culture and viral transduction A primary culture of rat smooth muscle cells was prepared as previously described [ 12 ], digesting the Wistar isogenic rat aortas enzymatically. These cells were characterized immunocytochemically using antibodies against α-actin (Boehringer Mannheim, São Paulo, Brazil) for SMC positive staining and von Willebrand factor (Boehringer Mannheim, São Paulo, Brazil) for SMC negative and endothelial cell positive staining [ 12 ]. Only early-passage smooth muscle cells were exposed for 24 h to virus harvested from PA317/LBmSN cells for a period of 24 h in the presence of Polybrene (8 μg/ml, Sigma) Transduction of mammalian cell lines with retroviral vectors The target cells were seeded on a 24 well plate at 1 × 10 4 cells per well with an appropriate medium as mentioned above. In parallel, 1 × 10 6 of virus producing cells (PA317/LBmSN, PA317/LBSN or PA317/LXSN) were seeded in a 25 cm 2 flask. After 24 h, the media from the target cells and the virus producing cells were replaced with a fresh one used for target cells. On the next day, the media of the target cells were replaced with 500 μl of the virus solution collected from the supernatant of the PA317/LBmSN cell culture and filtered in 0.45 μm syringe filter. Polybrene was added to the virus solution at the final concentration of 8 μg/ml. One day after the infection, the media were replaced with a fresh one, maintained in the CO 2 incubator and the cells were observed using a microscope everyday. In parallel, after two days of the infection, a new set of the transduced cells was split and only 1/10 part of the cells was maintained in the same well. The BS antibiotic was added to the wells at concentrations between 0 to 32 μg/ml. When the cells reached confluence they were split and transferred to two wells of a 12-well plate. To one well, BS was added at the concentration used for selection, and another well was maintained without BS. The cells were observed under the microscope everyday. Human primary keratinocytes culture and viral transduction Normal human keratinocytes from healthy adult volunteers were obtained by biopsy, cut in small pieces and incubated in a trypsin solution (0.05 %) containing 0.01 % EDTA at 37°C for 3 h under constant agitation. Every 30 min the detached cells were transferred to a new 75 cm 2 flask containing 2 × 10 6 cells of the irradiated CCL-92 cells (60 Gy) as a feeder-layer. The medium used for the culture of the keratinocytes was composed of DMEM and Ham's F12 (2:1) containing 10 % FBS, 4 mM glutamine, 50 IU/ml streptomycin- penicillin, 0.18 mM adenine, 5 μg/ml insulin, 5 μg/ml transferrin, 0.4 μg/ml hydrocortisone, 0.1 nM choleric toxin and 20 pM triiodotyronin [ 11 ]. The medium was replaced every 2 to 3 days with a fresh one containing 10 ng/ml EGF. The cells were maintained in a humidified atmosphere with 5 % CO 2 . For retroviral transduction, the packaging clones PA317/LBmSN and PA317/LXSN were irradiated with 30 Gy and used as a feeder-layer for the prepared previously keratinocyte cultures. Author's contribution FMB performed experiments with NIH3T3, keratinocytes and smooth muscle cells, and CBS with HCT-8, B16F10 and BALB/MK cells. DT and AKC performed purification and characterization of DOKEB. TRM tested analogs of BS in BALB/MK and BALB/MK/LBmSN cells. MBM participated in the preparation of the human primary keratinocytes. SWH drafted the manuscript and conducted all experiments.

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526375

Cdc42 Effector Protein 2 (XCEP2) is required for normal gastrulation and contributes to cellular adhesion in Xenopus laevis

Background Rho GTPases and their downstream effector proteins regulate a diverse array of cellular processes during embryonic development, including reorganization of cytoskeletal architecture, cell adhesion, and transcription. Changes in the activation state of Rho GTPases are converted into changes in cellular behavior by a diversity of effector proteins, which are activated in response to changes in the GTP binding state of Rho GTPases. In this study we characterize the expression and function of one such effector, XCEP2, that is present during gastrulation stages in Xenopus laevis . Results In a search for genes whose expression is regulated during early stages of embryonic development in Xenopus laevis , a gene encoding a Rho GTPase effector protein (Xenopus Cdc42 effector protein 2, or XCEP2) was isolated, and found to be highly homologous, but not identical, to a Xenopus sequence previously submitted to the Genbank database. These two gene sequences are likely pseudoalleles. XCEP2 mRNA is expressed at constant levels until mid- to late- gastrula stages, and then strongly down-regulated at late gastrula/early neurula stages. Injection of antisense morpholino oligonucleotides directed at one or both pseudoalleles resulted in a significant delay in blastopore closure and interfered with normal embryonic elongation, suggesting a role for XCEP2 in regulating gastrulation movements. The morpholino antisense effect could be rescued by co-injection with a morpholino-insensitive version of the XCEP2 mRNA. Antisense morpholino oligonucleotides were found to have no effect on mesodermal induction, suggesting that the observed effects were due to changes in the behavior of involuting cells, rather than alterations in their identity. XCEP2 antisense morpholino oligonucleotides were also observed to cause complete disaggregation of cells composing animal cap explants, suggesting a specific role of XCEP2 in maintenance or regulation of cell-cell adhesion in early embryos. This loss of cell adhesion could be rescued by co-injection with a morpholino-insensitive version of the XCEP2 mRNA. Conclusions XCEP2 appears to be an essential component in the early developmental program in Xenopus laevis . XCEP2 is involved in maintenance of cell-cell adhesion, and as such may constitute a regulatory component that could help to balance the need for tissue integrity and plasticity during the dynamic cellular rearrangements of gastrulation.

Background Vertebrate gastrulation depends upon exquisite regulation of diverse morphogenetic processes including changes in cell shape, cellular adhesion and migration. For example, in Xenopus laevis coordinated changes in cell shape and motility guide the initial formation of the dorsal lip, the initial site of mesodermal involution [ 1 , 2 ]. Later, the completion of involution of prospective mesodermal cells is strongly influenced by biomechanical forces generated by convergent extension of dorsal mesodermal cells [ 3 ]. Convergent extension involves mediolateral elongation of trunk mesoderm cells, followed by medially-converging intercalation. While convergent extension of dorsal mesoderm is a major driving force for the extension and completion of involution movements, epiboly of the non-involuting ectoderm (driven by radial intercalation of cells of the blastocoel roof) is also necessary for efficient gastrulation [ 4 ]. The coordinated changes in cell shape and cell migration associated with gastrulation are influenced by diverse processes, including large-scale remodeling of cytoskeletal architecture and precise modulation of cell-cell and cell-matrix associations. The molecular basis for initiating and regulating the complex cellular movements of vertebrate gastrulation is only beginning to be discerned. Recent work has shown Wnt proteins as key upstream regulators in gastrulation movements. In Xenopus laevis and zebrafish, non-canonical Wnt signaling on the dorsal side of developing embryos directly initiates the cellular rearrangements and migration that contribute to convergent extension of involuting mesoderm [ 5 , 6 ]. Other Wnt-mediated signals activate a distinct protein kinase C-dependent signaling pathway, which appears to affect Cdc42 signaling and to provide cues that maintain tissue separation during gastrulation [ 7 , 8 ]. Inactivation of this PKC-dependent pathway causes ineffective separation of involuting mesoderm from overlying ectoderm in Xenopus , resulting in severe gastrulation defects [ 8 ]. As with the planar cell polarity (PCP) pathway in Drosophila [ 9 ], vertebrate Wnt signals during gastrulation can involve signaling through the strabismus and JNK (JUN N-terminal Kinase) proteins [ 10 , 11 ], and affect cellular morphology and migratory behaviors through the activities of a diversity of Rho family GTPases [ 10 , 12 - 14 ]. Experiments perturbing the activity of Rho GTPases have suggested important regulatory roles for these proteins during gastrulation in Xenopus [ 7 , 10 , 12 , 14 ]. Upon activation, Rho GTPases are known to interact with a variety of downstream effector proteins which in turn mediate changes in actin and microtubule cytoskeletal architecture [ 15 ], cell adhesion [ 16 ], cell migratory behaviours [ 17 ], vesicular transport [ 18 ] and signalling [ 19 - 21 ]. Regulation of the coordinated cellular and tissue level processes involved in gastrulation appears to involve multiple Rho GTPases (including Rho, Rac and Cdc42) and multiple downstream effector proteins. However, we are only currently beginning to discern the identities and functions of the repertoire of effector proteins that specifically relay Rho GTPase signals involved in the initiation and coordination of gastrulation movements. Regulation of cell-cell adhesion is thought to be of particular importance during gastrulation movements in Xenopus , when the integrity of the elongating mesodermal sheet must be maintained at the same time that major cellular rearrangements are occuring. Downregulation of C-cadherin-mediated cellular adhesion has been observed to correlate with convergent extension movements of mesodermal cells [ 22 ]. This change in C-cadherin mediated adhesion between blastomeres occurs with no detectable change in cell surface expression of the C-cadherin protein. While the precise mechanism of regulation in this developmental context remains unclear, it is known that lateral clustering of cadherins (mediated through interactions between cytoplasmic tails of cadherin proteins) is capable of strengthening adhesive function [ 23 ]. In addition, it is also known that Rho GTPases can act through the IQGAP protein to regulate cadherin-mediated adhesion [ 24 - 27 ]. Recent chararacterization of the developmental pattern of IQGAP expression in Xenopus embryos suggests that analogous upstream regulatory mechanisms may operate during Xenopus gastrulation [ 28 ]. In this study, the embryonic expression pattern and function of a Xenopus gene encoding a member of the recently characterized CEP/BORG family of RhoGTPase effector proteins [ 29 , 30 ] is explored. These proteins have been shown to have distinct effects on cytoskeletal architecture, cellular morphology, adhesion and migratory behaviours [ 29 , 30 ], and have also been shown to regulate septin function during cytokinesis [ 31 , 32 ]. Xenopus Cdc42 Effector Protein 2, hereafter referred to as XCEP2, is shown here to be developmentally regulated during early embryonic stages, with diffuse expression of mRNA in the animal region that diminishes during late gastrula to neurula stages. Experiments employing morpholino-mediated inhibition of translation suggest that expression of this protein is essential for normal gastrulation movements, and that its activity is required for maintenance of cell-cell adhesion between blastomeres of animal cap explants. Results Xenopus laevis cdc42 effector protein 2 (XCEP2) is present in two allelic forms, and its expression is developmentally regulated during early embryogenesis A differential display approach was employed to reveal genes that are developmentally regulated during the transition from blastula to neurula. This screen allowed for the isolation of numerous cDNA fragments corresponding to differentially regulated mRNAs present in the Xenopus embryo. The sequence of one of these fragments was found to be highly homologous to the translational start site region of database cDNA sequences encoding Cdc42 effector protein 2. A full length cDNA corresponding to our isolated fragment was amplified using 3' RACE PCR, cloned and sequenced. An alignment of the predicted amino acid sequence for our isolated full length cDNA sequence with human [ 29 ] and Xenopus (accession number BC045241) CEP2/BORG1 genes from Genbank revealed significant homology (see Figure 1 ), particularly within and immediately surrounding the conserved CRIB, CI and CII domains [ 29 , 30 , 33 ]. When comparing the two Xenopus sequences, there were a significant number of positions where the amino acid sequence derived from our isolated cDNA sequence differed from that found in the Genbank sequence (15% of the amino acids were non-identical). These differences were found to occur almost exclusively in regions of the protein outside the three conserved domains (CRIB, CI and CII) that define the CEP family of effector proteins. Given the allotetraploid genetic ancestry of Xenopus laevis , and the degree of similarity between the sequences, it is likely that these two sequences constitute pseudoalleles of the same gene. We choose to refer to our isolated pseudoallele as XCEP2A and the database allele as XCEP2B. Figure 1 XCEP2 Nucleic Acid and Amino Acid Sequences. (A) The nucleic acid sequence of the XCEP2A cDNA is shown. Sequences encoding the start methionine (green), the stop codon (red) are indicated. The protein coding region is shown in blue. (B) Amino acid sequences of the two Xenopus pseudoalleles of CEP2, along with the mammalian (human) sequence, are shown. Asterisks indicate highly conserved residues within the CRIB domain (black asterisks, lines), the CI domain (red asterisks, lines) and the CII domain (blue asterisks, lines) in the CEP-2 protein. Dark gray shading indicate residues conserved in all three species; light gray areas indicate residues that are conserved between two of the three species listed. Vertically oriented pairs of dots (:) indicate positions where amino acid identity is conserved in all three sequences. Semi-quantitative RT-PCR was conducted on staged RNA samples using primers specific to the 5' untranslated sequence of the isolated XCEP2A cDNA. This analysis revealed the presence of maternally-derived XCEP2A mRNA prior to the onset of zygotic transcription (embryonic stage 7.5), maintenance of this expression level through mid-gastrula stages, with a downregulation of mRNA expression starting at stage 10.5 and becoming more marked by stage 12.5 (see Figure 2 ). RT-PCR analysis of the expression of the other pseudoallele (XCEP2B) revealed an expression pattern similar to XCEP2A (see Figure 2 , lower panel), with an almost complete loss of detectable expression by stage 12.5. Both patterns correspond to that observed for the amplified fragments originally isolated from the original differential display gels (data not shown). In situ hybridization revealed that XCEP2A mRNA (corresponding to our isolated pseudoallele) is distributed uniformly over the animal hemisphere of the embryo at blastula and early gastrula stages (see Figure 3A and 3B ), with an animal to vegetal gradient in staining evident (Figures 3B and 3C ). Over time, there is a diminution of the intensity but no change in the general expression pattern as the embryo transitions from blastula to gastrula stages (data not shown). Figure 2 Temporal regulation of XCEP2 during pre-neurula stages of embryonic development. Semi-quantitative RT-PCR was conducted on equivalent amounts of RNA derived from the indicated developmental stages. XCEP2A was amplified using XCEP2A forward and reverse primers (see Methods ). Ornithine Decarboxylase (ODC) serves as a loading control (middle panel). RT-PCR amplification to reveal expression of the alternative pseudoallele (XCEP2B), using XCEP2B forward and reverse primers, is shown in the lower panel. Figure 3 Spatial Localization of XCEP2 mRNA. (A) Animal pole view in situ hybridization of embryos fixed at late blastula stage with digoxygenin-labeled antisense XCEP2A antisense probe exhibit diffuse staining across the animal region of the embryo (right). An XCEP2A sense probe served as a negative control, and showed minimal background staining (left). (B) A blastula stage embryo, cut to reveal a cross-section, reveals the animal/vegetal gradient of antisense XCEP2 probe. The blastocoel cavity is visible in the upper portion of this embryo. (C) A side view of an antisense XCEP2A probed embryo, revealing an animal (top) to vegetal (bottom) gradient of staining. Morpholino oligonucleotides directed against XCEP2 cause gastrulation defects In order to assess the functional role of XCEP2 in early embryogenesis, microinjections were conducted with antisense morpholino oligonucleotides, MO1 and MO2 directed to the translational start site region of one or both of the two XCEP2 pseudoalleles. MO1 is targetted to XCEP2A, and MO2 is targetted to the XCEP2B sequence found in the Genbank database. For this experiment, a total of 100 ng of morpholino oligonucleotide was injected into the animal region of one-cell embryos. At time points just prior to blastopore closure (~embryonic stage 12), MO1 antisense oligonucleotides pseudoalleles elicited significant gastrulation delay as compared to an identical dose of control morpholino oligonucleotide (See Figure 4A ). A comparison of the effects of each morpholino, and the combined effects of co-injection of both morpholinos is shown in Figure 4B . The severity of gastrulation delay was quantified at late gastrulation by comparing the ratio of blastopore diameter to embryo diameter in antisense-injected, control injected and non-injected embryos. The mean ratio, and the distribution of ratios differed significantly between control injected and antisense morpholino injected groups (See Figure 4B and 4C ). MO2 was slightly less effective than MO1 in producing gastrulation delay. Small differences between the effects of the various injection conditions suggest that either the MO2 morpholino is less efficient at translational inhibition, or that the pseudoallele targeted by MO2 may be expressed at comparatively lower levels. The combined MO1+MO2 condition did not produce more severe defects than the individual morpholino injections, perhaps because the dose of each morpholino in the combined condition was half that in either of the single morpholino conditions (all injections were 100 ng, the combined condition included 50 ng of each morpholino). Many of the more severely affected embryos at this dose did not complete blastopore closure, and showed lethal defects that precluded normal neurulation. Embryos that survived treatments of between 75 and 115 ng of antisense morpholino (MO1) were found to have phenotypes consistent with gastrulation defects, including significant shortening of the AP axis and multiple instances of spina bifida (see Figure 4D ). The phenotypes we observe share significant similarity to defects caused by specific inhibition of convergent extension in mesoderm [ 34 ]. At a higher dose (100 ng injected into each blastomere of 2-cell stage embryos, 200 ng total injection), embryonic lethality was observed consistently in practically all treated embryos prior to neurulation (see Figure 8A , lower panel). Figure 4 Effects of antisense XCEP2 morpholino oligonucleotide on gastrulation. (A) Injected embryos received 100 ng of morpholino, delivered to the animal region of 1-cell embryos. Typical gastrula stage embryos for each of three experimental conditions (non-injected, control morpholino and MO1 antisense injected) are shown. (B) The distribution of blastopore-to-embryo diameter ratios for each experimental condition. 18–20 embryos were assessed for each condition. In the combined "MO1+MO2" condition, 50 ng of each morpholino were co-injected. (C) Average blastopore to embryo diameter ratios for each of the control and experimental conditions, +/- 1SEM, are shown. (D) Effects of antisense morpholinos on post-neurulation embryonic development are shown. Antisense XCEP2-injected embryos exhibit dose-dependent abnormalities suggestive of gastrulation and/or convergence extension defects. Representative viable embryos, at Stage 26–27, from each control and experimental condition are shown. Several embryos in the MO1 treated groups exhibited varying degrees of spina bifida. Embryonic viability for the water, control morpholino, and the three doses of antisense XCEP2 morpholino (75 ng, 95 ng and 115 ng) were 90%, 90%, 81%, 63%, and 26%, respectively (20–30 embryos injected for each condition). The antisense morpholino oligonucleotides used in these studies were found to elicit specific translational inhibition of XCEP2. Injection of antisense morpholino against our isolated pseudoallele resulted in largescale inhibition of translation of a myc-tagged fusion protein from co-injected mRNA (see Figure 5B ). A modified mRNA (XCEP2A*-myc) encoding a C-terminal myc tagged XCEP2A fusion protein, with seven point mutations in the 5' untranslated region and at the 3 rd base of selected codons in the translated region (see Figure 5A ), was found to be insensitive to inhibition by antisense morpholino oligonucleotide MO1 (See Figure 5B ), demonstrating sequence specificity of the translational inhibition effect. XCEP2A* myc migrates as a doublet, which probably arises due to inefficient translational initiation at the true start codon of the mutated mRNA and some initiation at the second AUG codon, encoding methionine at position 29 (see Figure 1B ). While MO1 does not inhibit translation from the multiply mutated XCEP2A* myc mRNA, we did find that MO2, which is designed to be complementary to the database pseudoallele, was capable of significantly reducing translation from mRNA corresponding to our isolated pseudoallele (XCEP2A-myc). This suggests that under these conditions, the two-nucleotide mismatch between MO2 and our XCEP2A-myc mRNA does not preclude translational inhibition (to compare sequences, see Methods , "Morpholino Oligonucleotides"). Given this observation, it is possible that injection of either antisense XCEP2 morpholino significantly reduces the endogenous expression of both pseudoalleles. In addition to the dosage issue in the combined condition (noted above), cross-inhibition of this type could contribute to the observed lack of additive effects in the combined MO1 + MO2 condition. Figure 5 Antisense XCEP2 morpholino oligonucleotides specifically inhibit translation from XCEP2 mRNA . (A) Schematic diagram indicating mutations (designated by asterisks) in the morpholino target site of XCEP2*-myc mRNA that would be expected to inhibit strong interactions with the antisense XCEP2 morpholino (MO1). (B) 0.7 ng of mRNA encoding myc-tagged XCEP2 (either the normal XCEP2-myc or the mutated XCEP2*-myc) was injected alone or in combination with 80 ng of antisense XCEP2 morpholino oligonucleotide (MO1) into the animal pole of 1-cell embryos. XCEP2 protein was detected in embryo extracts (prepared at stage 8.5–9) by Western Blotting using anti-myc monoclonal antibody 9E10 (upper panels). Equivalency in protein loads in the Western Blot lanes are indicated by the similarity in staining intensity of protein bands in the corresponding SYPRO Ruby-stained gels in the lower panels. The blastopore closure delay phenotype observed in antisense morpholino injected embryos could be completely rescued by co-injection with 0.7 ng of the XCEP2A*mRNA, which is insensitive to translational inhibition (see Figure 6 ). This result suggests that the observed effects of antisense morpholino oligonucleotides on gastrulation are not due to inhibition of a non-XCEP2 gene product, or to non-specific toxicity of the antisense oligonucleotides. This observation strongly suggests that the observed effects of the antisense oligonucleotides on embryogenesis are attributable to a specific knockdown of translation of the endogenous XCEP2 mRNA, and a concomitant reduction in XCEP2 protein. Figure 6 Rescue of the antisense XCEP2 morpholino phenotype by XCEP2 mRNA co-injection. Injected embryos received 100 ng of morpholino oligonuceotide in the animal region of both blastomeres in two-cell stage embryos. MO1 and MO2 oligonucleotides were mixed at a molar ratio of 3:1, respectively. 20–30 embryos were assessed for each condition. (A) The distributions of blastopore to embryo diameters for the indicated experimental conditions are shown. The rescuing XCEP2 mRNA (XCEP*-myc) sequence was altered such that antisense morpholino oligonucleotides would be expected to bind inefficiently. (B) Average blastopore to embryo diameter ratios, +/- 2 SEM, are indicated for each experimental condition. In contrast to the morpholino knockdown effects, overexpression of XCEP2 in embryos by injection of up to 1 ng XCEP2 mRNA was found to result in no detectable abnormalities in embryonic development (data not shown). The absence of effects may not be unexpected, given current models of RhoGTPase effector protein activation. RhoGTPase effector proteins are activated by direct binding to GTP-bound RhoGTPases. As such, the number of activated RhoGTPase molecules may constrain the number of effector proteins bound and activated, regardless of the heightened expression levels of the effector protein. XCEP2 morpholinos do not interfere with mesoderm induction The observed effects of antisense XCEP2 morpholinos in Xenopus embryos suggests that XCEP2 may play a direct role in directing the morphogenetic movements of gastrulation. This interpretation would be consistent with the limited characterization that have thus far been conducted on functional properties of this class of proteins [ 29 , 30 ]. However, it is also conceivable that XCEP2 antisense morpholinos may indirectly inhibit gastrulation by interfering with mesodermal induction. In order to assess this possibility, the level of expression of the pan-mesodermal marker, brachyury, and the dorsal mesodermal marker, goosecoid, was assessed in control and antisense morpholino injected embryos at gastrula stage using semi-quantitative RT-PCR (see Figure 7 ). Expression of mesodermal markers was similar in non-injected, control morpholino injected and antisense XCEP2 injected embryos, suggesting that it is the behavior of mesodermal cells during gastrulation (rather then the presence or absence of mesodermal cells) that is affected by XCEP2 antisense morpholino oligonucleotides. Figure 7 Antisense XCEP2 morpholino oligonucleotides do not inhibit mesodermal induction. Semiquantitative RT-PCR analysis was conducted on duplicate RNA samples using primers for Brachyury (a pan-mesodermal marker), goosecoid (a dorsal mesodermal marker) and ornithine decarboxylase ("ODC", used as loading control). For control and morpholino-injected conditions, 100 ng of morpholino oligonucleotide was injected into the animal region of 1-cell stage embryos. Figure 8 Effects of antisense XCEP2 Morpholino oligonucleotides on animal cap explant cell adhesion. (A) 100 ng morpholino oligonucleotide MO1 was injected into the animal region of each blastomere of 2-cell stage embryos. Animal cap explants from antisense MO1-injected embryos exhibited a marked loss of integrity (upper right panel) 24 hours after explantation, as compared to animal caps from non-injected or control morpholino injected embryos (upper left panels). Effects of these treatments on whole sibling embryos at Stage 22–23 are shown in the lower panels. In (B), embryos were injected with 75 ng of MO1 antisense morpholino in each blastomere at the 2-cell stage. Animal explants derived from non-injected embryos (left panel), MO1-injected embryos (middle panel), or embryos co-injected with 0.7 ng XCEP2*myc mRNA (right panel) are shown 24 hours after explantation. XCEP2 morpholinos Interfere with cell-cell adhesion in animal cap explants In order to assess the mechanism by which XCEP2 influences gastrulation, the effects of XCEP2 morpholinos on cultured animal cap explants were evaluated. While the initial intent of these experiments was to discern whether XCEP2 morpholinos prevented normal activin-induced convergent extension of animal caps, it soon became clear that morpholino-treated explants had a more fundamental deficiency. Within a 24 hour period, animal cap explants derived from XCEP2 antisense morpholino (MO1) -injected embryos were found to completely lose their integrity (see Figure 8A , upper right panel), collapsing into piles of dissociated cells. This contrasts with control injected and non-injected caps, which remained tightly associated at 24 hours (see Figure 8A , upper left panels). This result was evident with or without activin treatment (data for activin treated caps is not shown). The observed defect in XCEP2 MO1 treated caps suggested a loss of cell-cell adhesion, as cells of disintegrated explants appeared to be completely dissociated, with few if any adherent clusters of cells. The observed loss of integrity followed a reproducible pattern. At approximately 18 hours after explantation, dissociated cells from the interior of the explant could often be observed discharging from the healed wound site (or, in some cases, at other localized sites), causing the explants to become progressively reduced in size. The cells of the outer pigmented epithelium of the explant remained adherent until the latest stages of the 24 hour time course, by which time they often also dissociated. The animal cap dissociation caused by the MO1 morpholino could be largely rescued by co-injection with a XCEP2*myc mRNA (see Figure 8B ), which has modifications that make it insensitive to translational inhibition by our morpholinos (see Figure 5B ). This suggests that the dissociation observed is not a non-specific toxicity or cross-inhibition effect. XCEP2*myc mRNA rescued explants showed little difference from non-injected controls at and beyond the 24 hour time point. Discussion The Rho GTPases and their associated effector proteins are known to play diverse roles in the regulation of cytoskeletal remodelling, cellular adhesion and cell motility. The complex morphogenetic movements associated with gastrulation in Xenopus , including changes in the morphology and polarity of mesodermal cells, and their later mesolateral intercalation of these cells during convergent extension, are now known to be dependent upon RhoGTPase functions [ 5 , 12 , 14 ] (for review, see [ 35 , 36 ]). Currently, however, there is little known regarding the identity or role of specific effector proteins that are utilized to convert changes in the GTP binding state of RhoGTPases into gastrulation-associated changes in cytoskeletal architecture, cell morphology, and cellular adhesion and migration. The data presented here indicate a role for the Xenopus Cdc42 effector protein 2 (XCEP2) in gastrulation movements. XCEP2 is a member of the recently characterized CEP family of Rho GTPase effector proteins [ 29 , 30 ], which include the previously characterized mouse protein, MSE55 [ 33 ]. Effector proteins of the CEP family share a conserved expanded CRIB domain, which binds Rho GTPases, and two other highly conserved protein domains (CI and CII) [ 29 , 30 ]. By analogy to other Rho GTPase effector proteins, it has been proposed that Cdc42 binding to the CRIB domain of CEP proteins leads to a conformational change that exposes the previously inaccessible CI or CII domains (reviewed in [ 37 ]). The exposed domains of the effector protein would then be free to interact with downstream components of the signaling/regulatory pathway. When overexpressed in cultured cells, members of this family of effector protein induce marked pseudopodial/ lamellipodial extensions, membrane ruffling, alterations in actin and vinculin organization, and a reduction of E-cadherin staining at adherens junctions [ 29 , 30 ]. Consistent with a potential role for this class of proteins in embryonic morphogenesis, we have shown that XCEP2 expression is temporally regulated at gastrulation stages, when major modulations of cellular morphology, cytoskeletal organization, and cellular adhesion are occurring. mRNA for XCEP2 is present prior to mid-blastula transition, persists through mid gastrulation, and is strongly down-regulated by the time the blastopore closes and neurulation begins. This pattern would suggest that XCEP2 protein would be present through the period when active gastrulation movements are occurring. The diffuse spatial pattern of mRNA and, presumably, protein expression of XCEP2 may suggest that XCEP2 functions broadly in cells of the animal and equatorial regions. However, the observed broad spatial distribution of XCEP2 mRNA does not preclude the possibility that the XCEP2 protein may be functionally activated or inactivated at discreet times and locations during early embryonic development. Furthermore, we show that antisense morpholino oligonucleotides capable of blocking translation of the XCEP2 message interfere with Xenopus gastrulation, delay the closure of the blastopore and inhibit embryonic elongation. The observed rescue with XCEP2 mRNA is strong evidence for the specificity of the antisense morpholino effect. These effects are not due to a loss of mesodermal induction, as brachyury and goosecoid expression do not change in response to antisense XCEP2 morpholinos. This is particularly relevant given recent reports demonstrating a direct link between brachyury expression and control of cellular migration [ 38 ]. The effects we report require relatively high, although not unprecedented, doses of morpholino antisense oligonucleotide. This dosage requirement may reflect the difficulty inherent in morpholino-mediated translational knockdown of maternally expressed genes. XCEP2 mRNA and (presumably) XCEP2 protein are present prior to midblastula transition. Given this situation, the timing morpholino induced protein downregulation is dependent both upon the effectiveness of translational blockade, and the half life of the protein in the cytoplasm. In this context, it may be essential to impose close to complete translational inhibition in order to reduce protein levels rapidly enough to affect early embryonic events, such as gastrulation. Clearly, specific probes to assess endogenous XCEP2 protein expression will be necessary for fuller characterization of the role of this protein during gastrulation. For this reason, antibodies are currently being raised against the XCEP2 protein. These antibodies will be important in the characterization of the developmental time course of endogenous XCEP2 protein expression, assessment of the subcellular localization of the XCEP2 protein, isolation of potential XCEP2 binding partners, and in assessing and further optimizing the extent of protein down-regulation in morpholino injected embryos. Currently, the specific mechanism by which XCEP2 exerts its role in gastrulation is unknown. However, our preliminary data suggest that XCEP2 may either contribute to a required "ground state" of cellular adhesion or play a role in modulations in the strength of cadherin-mediated cell-cell adhesion that are known to occur during gastrulation [ 22 , 39 , 40 ]. More detailed work will be necessary to clearly distinguish between these possibilities. In embryos Wnt-mediated signals have been shown to activate Cdc42, a process that is required for normal gastrulation movements [ 7 , 12 ]. In future work, it will be important to discern whether XCEP2 plays an important role in transducing these upstream signals into changes in cellular behaviour during gastrulation. The known functional properties of the CEP class of effector proteins, and the characteristics of CRIB domain effector proteins in general, suggest some interesting possibilities relating to the control of cell adhesion during gastrulation. Consistent with the observed functions of the XCEP2 homologs in cultured cells, XCEP2 in embryos may impinge on regulatory circuits downstream of Cdc42 that control actin filament assembly, which in turn may affect diverse cellular processes, including assembly of adherens junctions. Alternatively, XCEP2 may more directly impinge upon cadherin functional activity, perhaps by influencing the association of IQGAP or other molecules with cadherin complexes. In future studies, it will also be important to establish whether embryonic activation of whether there are links between Wnt-mediated activation of Cdc42 and functional activation of XCEP2 and to characterize the mechanism(s) by which XCEP2 contributes to cell adhesion between cells of gastrulating embryos. Conclusions It has become clear in recent years that an integrated network of signals involving Rho GTPase proteins and their effector proteins help to control and regulate the diverse and intricate morphogenetic processes that occur during embryonic development. Less clear are the specific modes of functional interaction between the multiple Rho GTPases and the diversity of potential effector proteins. We have shown that XCEP2 is one component in the complex regulatory puzzle contributing to morphogenetic processes during Xenopus gastrulation. For this reason it will be interesting and important to discern further the role of XCEP2, with regard both to its relationship to intracellular signalling pathways and its effects on cellular behavior during gastrulation. Methods Restriction fragment differential display primer and adaptor sequences Adaptor 1- 5'-ATGAGTCCTGAC-3' (upper strand) 5'-PO 4 -CGGTCAGGACTCAT-3'(lower strand). Adaptor 2 (the 3' phosphate group of the lower strand inhibits DNA polymerase extension)- 5'-ACTGGTCTCGTAGACTGCGTACC-3'(upper strand) 5'-PO 4 -CGGGTACGCAGTC-PO 4 3' (lower strand). "Universal" RFDD-PCR primer (complementary to Adaptor 2)- 5'-ACTGGTCTCGTAGACTGC-3' "Selection" Primer 4 (complementary to Adaptor 1, with a 3-nucleotide 3' extension) 5'-ATGAGTCCTGACCGA AAG -3' (3-nucleotide extension is underlined) Primers used for construction of full-length XCEP2 cDNAs (sequences encoding start codon shown in bold, PCR-induced mutation sites are underlined) XCEP2 cDNA forward- 5'-ATTGCAAAG ATG TCCGCCAAG-3' XCEP2* cDNA forward- 5'- CGGGAT C CT AG ATG TC G GC G AAAGCGCCGATATACCTAAAGAG AAG-3' XCEP2 cDNA reverse- 5'-AACGTATCCCCTTCCCCA-3' RT-PCR primer sequences XCEP2A forward (complementary to 5' untranslated region of the cDNA sequence) 5'-AACGTATCCCCTTCCCCA-3' XCEP2A reverse (complementary to 5' untranslated region of the cDNA sequence) 5'-AAAGAGAAGTAGCCGTAAAGGA-3' XCEP2B forward 5'-GCCAAGGCCCCGATATAC-3' XCEP2B reverse 5'-CCAATAGCAGGTAGGGAA-3' Brachyury forward 5'-GGATCGTTATCACCTCTG-3' Brachyury reverse 5'-GTGTAGTCTGTAGCAGCA-3' Goosecoid forward 5'-ACAACTGGAAGCACTGGA-3' Goosecoid reverse 5'-TCTTATTCCAGAGGAACC-3' ODC forward- 5'-GTCAATGATGGAGTGTATG-3' ODC reverse 5'-TCCATTCCGCTCTCCTGA-3' Morpholino oligonucleotides Antisense morpholino oligonucleotides, which specifically block translation of targeted mRNAs [ 41 ] were synthesized by GeneTools, LLC (Philomath, OR) and were designed to interact with both characterized pseudoalleles of the XCEP2 gene. Antisense oligos were targeted to the region upstream and downstream of the translational start site of the XCEP2 mRNA. The target sequences that were chosen were compared to the Genbank database to confirm that the XCEP2 antisense oligonucleotides would not be expected to interfere with the expression of other known gene products. The morpholino sequences utilized in these studies were as follows, with morpholino sequence complementary to the start codon of the cognate mRNA shown in bold: Antisense XCEP2 MO1 (specific to the XCEP2A, characterized in this study)- 5'-GGGCCTTGGCGGA CAT CTTTGCA-3' Antisense XCEP2 MO2 (specific to XCEP2B, Xenopus Genbank sequence accession # BC045241)- 5'-GGGCCTTGGCTGA CAT CTTTCCA-3' Control Morpholino oligonucleotide 5'-CCTCTTACCTCAGTTACAATTTATA-3' Restriction fragment differential display PCR, gene identification and isolation Restriction Fragment Differential Display PCR (RFDD-PCR) procedures were patterned closely after the commercially available DisplayProfile kit from QBiogene (Carlsbad, CA), with minor modifications. In this differential display procedure, Adaptors 1 and 2 (see RFDD-PCR primer and adaptor sequences , above) are ligated to restriction digested, double stranded cDNA. Amplification of this cDNA is conducted with the "universal primer", complementary to one of the adaptor sequences, and one of 64 "selection" primers that bind largely to the to the second adaptor sequence but have a 3-nucleotide 3' extension that is complementary only to a subset of cDNA inserts. An extension-inhibiting chemical modification of the lower strand Adaptor 1, consisting of a 3' phosphate group in our modified procedure, and the 3-nucleotide extension of the selection primer largely restricts amplification to cDNA fragments that have different adaptor sequences ligated on opposite ends. Furthermore, any particular selection primer will selectively amplify only a subset of cDNA fragments (in theory, approximately 1/64 th of the total). Total RNA from staged, duplicate batches of Xenopus laevis embryos was purified using Trizol reagent (Invitrogen, Carlsbad, CA). RNA from Xenopus laevis embryonic stages 7, 8.5, 9.5, 10.5 and 12.5 were prepared. First strand cDNA was synthesized using oligo dT primer and Superscript III reverse transcriptase (Invitrogen), followed by second strand synthesis catalyzed by DNA polymerase I (Roche, Indianapolis, IN). Double stranded cDNA was purified using GeneClean silica resin (Qbiogene, Carlsbad, CA), and then digested with TaqI restriction enzyme (Roche, Indianapolis, IN). An annealed mix of RFDD-PCR of Adaptor 1/Adaptor 2 oligonucleotides was added, and ligated to the TaqI digested cDNA ends using T4 DNA Ligase (Roche). Touchdown PCR using the universal RFDD-PCR primer, 35 S-labelled dCTP, and "Selection" Primer 4 was conducted using Accuprime PCR mix (Invitrogen), with the following cycling parameters: Pre-dwell : 94°C 4 minutes 10 cycle touchdown PCR , with a 0.5 temperature decrement each cycle: 94°C 30 seconds 60°C→ 55°C 30 seconds 72°C 1 minute 30 cycle standard amplification : 94°C 30 seconds 55°C 30 seconds 72°C 30 seconds Post dwell : 72°C, 5 minutes Samples were run on a standard 6% denaturing DNA sequencing gel, and the gel was dried and subjected to autoradiography. Bands showing differential expression were excised from the gel and eluted by heating at 95°C for 15 minutes. Eluted fragments were re-amplified with 30 cycles of standard PCR, using the original primers (above). Direct cycle sequencing of isolated product (Thermosequenase; United States Biochemical, Cleveland, OH) revealed that one of the fragments corresponded to the 5' end (overlapping the translational start site) of a Xenopus homologue of the Cdc42 Effector Protein 2, which we refer to as "XCEP2". The full length cDNA was amplified using gene-specific primers and poly-dT primers using standard 3' RACE procedures [ 42 ]. The sequence of the full-length cDNA was determined by commercial automated sequencing (MWG Biotech, High Point, NC). Plasmid construction and RNA preparation The RACE amplified full-length fragment isolated from the RFDD-PCR procedure (see above) was cloned into the pCR2.1 vector, using the pCR2.1 TA cloning kit (Invitrogen), and commercially sequenced (MWG Biotech). To construct a vector encoding XCEP2A fused to a C-terminal 6xmyc tag, PCR was conducted using primers directed to the 5' and 3' end of the XCEP2A cDNA sequence (XCEP2A cDNA forward and XCEP2A cDNA reverse) with the cloned, full length XCEP2A as template. The primers used in this PCR mutated the normal stop codon and introduced a BamHI and ClaI site at the 5' and 3' ends of the amplified product, respectively. BamHI/ClaI digested full length cDNA was directionally cloned in the sense orientation into the corresponding into BamHI/ClaI digested pCS2-myc vector, producing the plasmid pCS2-XCEP-myc. In this context, the full length X-CEP2A cDNA encodes a fusion protein with a C-terminal 6x myc tag. A second construct, containing introduced mutations in the XCEP2A antisense morpholino target region, was also derived by PCR. To construct this vector, PCR was conducted using XCEP2* forward and XCEP2 reverse primers with the full-length XCEP2 DNA as template. XCEP2* forward introduced multiple changes in the sequence of the cDNA encoding the translational start site region (see Figure 5A ). These changes do not change the predicted amino acid sequence of the encoded protein, but would be expected to significantly reduce or eliminate binding of the antisense morpholino oligonucleotides used in this study. For transcription of antisense probe for in situ hybridization, the full length X-CEP2A cDNA was subcloned into the pCS2+ plasmid in an antisense orientation (relative to the SP6 promoter), producing the plasmid pCS2-XCEP2-anti. In a similar fashion, an RNA expression vector containing the XCEP2 insert in the sense orientation in pCS2+ was also constructed. Capped mRNAs were synthesized in vitro using the mMessage mMachine kit (SP6) from Ambion (Austin, TX), and were dissolved in distilled water prior to injection. Semi-quantitative RT-PCR Total RNA was isolated from embryos using Trizol (Invitrogen) according to manufacturer's instructions. Reverse transcription was carried out using SuperscriptIII (Invitrogen). Assessment of relative levels of gene expression over developmental time, or under different experimental conditions, was carried out using standard semi-quantitative RT-PCR methods [ 43 ], with the primers previously described (see RT-PCR Primers , above). 25 cycles of PCR were carried out using Accuprime PCR mix (Invitrogen) in 25 ul reactions containing 2 ul of 200 ug/ml reverse transcribed cDNA, 0.3μM of each primer, and a trace of radiolabelled nucleotide to allow for autoradiographic visualization. Parallel reactions containing primers specific to the metabolic gene, ornithine decarboxylase (ODC), were used as a loading control in all semi-quantitative RT-PCR experiments. RT-PCR products were separated electrophoretically on 5% acrylamide gels, which were dried and subsequently subjected to autoradiography. RT-PCR of the XCEP2A allele resulted in stronger amplification than with the XCEP2B primer set. XCEP2B bands required correspondingly longer exposure times (2–4 fold) for detection. Embryo manipulations Adult Xenopus laevis were purchased from Nasco (Fort Atkinson, WI). Eggs were obtained and fertilized according to standard methods. Staging was determined according to Nieuwkoop and Faber [ 44 ]. Antisense morpholino oligonucleotides and in vitro transcribed mRNA's were injected into two-cell stage embryos, with injected volumes of approximately 13 nl in doses as described. All injections were carried out using the Nanoject positive displacement microinjector (Drummond Scientific, Broomall, PA). Measurement of blastopore to embryo diameter ratios was accomplished by dividing the measured blastopore diameter (the distance between dorsal and ventral poles of the blastopore) by the embryo diameter. Diameter measurements were obtained using digital images of individual embryos, and the "Ruler" tool of the Adobe Photoshop software. To assess the effects of morpholino antisense oligonucleotides on animal cap explants, morpholino injected and control embryos were allowed to develop until stage 8.5. At stage 8.5 animal caps were dissected, and then cultured in 1xMMR for 24 hours. Non-dissected sibling embryos were allowed to develop until post-neurula stages in order to asses the effectiveness of the morpholino treatment. Detection of myc-tagged protein expression Proteins from embryos were extracted in 10 volumes of isotonic buffered saline containing 1% NP40. Extracts were cleared by a brief centrifugation, and supernatants were denatured by a 5-minute incubation at 95°C after diluting samples with SDS-PAGE sample buffer. Proteins were separated on 8–16% gradient polyacrylamide gels, and transferred to nitrocellulose. After blocking, blots were probed with monoclonal antibody 9E10 [ 45 ], which recognizes the myc epitope, and AP-conjugated goat-anti-mouse IgG (Biorad, Hercules, CA). Antibody binding was detected using Enhanced Chemiluminescence (ECL) reagents (Amersham-Pharmacia, Piscataway, NJ). Equivalency of protein loads was confirmed by running equivalent volumes of protein extracts on SDS-PAGE, and staining overnight with SYPRO Ruby (BioRad), with detection and documentation of protein bands conducted using UV transillumination. Wholemount in situ hybridization Digoxygenin-labelled antisense RNA probe was transcribed in vitro from linearized pCS2-XCEP2anti plasmid using a digoxygenin nucleotide labeling mix (Roche) and the mMessage mMachine in vitro transcription kit (SP6) from Ambion. In situ hybridization was carried out essentially as described [ 46 ], using non-hydrolyzed X-CEP2 digoxygenin-labeled probe. Embryos were subjected to a hybridization temperature of 62°C. AP-conjugated anti-digoxygenin FAb fragments (Roche) and BM Purple substrate (Roche) were used to detect hybridized probe. Authors' contributions KKN played a critical role in establishing in situ hybridization methodology in the laboratory, and conducted in situ hybridizations. RWN conceived of the study, designed and conducted molecular biological, embryological and biochemical experiments, and wrote the manuscript. Both authors read and approved of the final manuscript.

/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC526375.xml

539269

Randomised, controlled trial of N-acetylcysteine for treatment of acute exacerbations of chronic obstructive pulmonary disease [ISRCTN21676344]

Background Prophylactic treatment with N-acetylcysteine (NAC) for 3 months or more is associated with a reduction in the frequency of exacerbations of chronic obstructive pulmonary disease (COPD). This raises the question of whether treatment with NAC during an acute exacerbation will hasten recovery from the exacerbation. Methods We have examined this in a randomised, double-blind, placebo controlled trial. Subjects, admitted to hospital with an acute exacerbation of COPD, were randomised within 24 h of admission to treatment with NAC 600 mg b.d. (n = 25) or matching placebo (n = 25). Treatment continued for 7 days or until discharge (whichever occurred first). To be eligible subjects had to be ≥ 50 years, have an FEV 1 ≤ 60% predicted, FEV 1 /VC ≤ 70% and ≥ 10 pack year smoking history. Subjects with asthma, heart failure, pneumonia and other respiratory diseases were excluded. All subjects received concurrent treatment with prednisone 40 mg/day, nebulised salbutamol 5 mg q.i.d and where appropriate antibiotics. FEV 1 , VC, SaO 2 and breathlessness were measured 2 hours after a dose of nebulised salbutamol, at the same time each day. Breathlessness was measured on a seven point Likert scale. Results At baseline FEV 1 (% predicted) was 22% in the NAC group and 24% in the control group. There was no difference between the groups in the rate of change of FEV 1 , VC, SaO 2 or breathlessness. Nor did the groups differ in the median length of stay in hospital (6 days for both groups). Conclusions Addition of NAC to treatment with corticosteroids and bronchodilators does not modify the outcome in acute exacerbations of COPD.

Background Exacerbations are an important cause of morbidity in Chronic Obstructive Pulmonary Disease. Seemungal et al found that exacerbations were an important determinant of quality of life in COPD [ 1 ]. In addition hospital admissions with exacerbations account for a large proportion of the expenditure on the treatment of COPD [ 2 ]. This has led to a search for strategies to prevention exacerbations and to hasten their resolution when they do occur. A systematic review found that treatment with mucolytics for 2 months or more reduced the frequency of exacerbations by 29% [ 3 ]. The majority of the studies included in the review were with N-acetylcysteine. These findings are supported by a recent pharmacoepidemiologic study [ 4 ]. Aside from its action as a mucolytic, N-acetylcysteine is an antioxidant [ 5 , 6 ] and has anti-inflammatory actions [ 7 ] and this could contribute to its actions in preventing exacerbations of COPD. Exacerbations of COPD are characterized by increased infiltration of the airways with neutrophils and eosinophils [ 8 ] and by increased production of reactive oxygen species [ 9 ]. Reactive oxygen species can activate the epidermal growth factor receptor to promote mucus secretion [ 10 ] and this is one of the potential mechanisms by which an increase in reactive oxygen species could lead to a worsening of an acute exacerbation. In view of this we wondered whether N-acetylcysteine might also be useful in the treatment of patients presenting with an acute exacerbation of COPD. We undertook a randomised, double-blind, placebo-controlled, parallel group study of oral N-acetylcysteine 600 mg b.d. in addition to standard treatment in patients admitted to hospital with an acute exacerbation of COPD. Methods Patients were eligible for inclusion in the study if they had a physician diagnosis of COPD, were ≥ 50 years of age, had a smoking history ≥ 10 pack years and had been admitted to hospital with an acute exacerbation of their COPD in the previous 24 hours. In addition they were required to have FEV 1 ≤ 60% predicted and FEV 1 /VC ≤ 0.7 at time of inclusion. Patients were excluded if they had any of the following conditions: asthma (as the primary diagnosis), heart failure, bronchiectasis, bronchial carcinoma, interstitial lung disease, pneumonia. They were also excluded if they were unable to comply with the study procedures because they did not speak English or were demented or if they had any other medical problems that in the opinion of the investigator would interfere with the conduct of the study. Subjects were treated with N-acetylcysteine 600 mg twice daily (b.d.) or matching placebo. Treatment was continued for 7 days or until discharge whichever occurred first. Effervescent N-acetylcysteine tablets were purchased from Zambon pharmaceuticals (Milan, Italy) and were repackaged in size 0 gelatine capsules. Each capsule contained 300 mg of N-acetylcysteine. Placebo capsules were prepared containing lactose as a filler. A randomisation schedule was drawn up by the hospital pharmacy and patients were allocated sequential randomisation numbers as they entered the study. In addition to N-acetylcysteine the patients received standard treatment for their exacerbation as specified by the hospital guidelines. This was oxygen therapy, prednisone 40 mg o.d. for one week and nebulised bronchodilators i.e. salbutamol 5 mg four times daily (q.i.d.) and ipratropium 0.5 mg q.i.d. Antibiotics were prescribed if the patients had increased volume and/or purulence of sputum. Mucolytics were not permitted during the trial except as study medicine. The primary endpoint was breathlessness measured on a seven point Likert scale (Table 1 ). Secondary endpoints were FEV 1 , oxygen saturation and length of hospital stay. The study assessments were performed at the same time each day and two hours after the last dose of nebulised bronchodilator. Breathlessness was assessed prior to spirometry. Spirometry was performed according to American Thoracic Society criteria using a Vitalograph spirometer. Oxygen saturation was measured using a Nelcor N-20 pulse oximeter. Supplemental oxygen was stopped for 10 minutes before any of the measurements were performed. In addition the subjects were interrogated on each occasion about any possible adverse effects. Table 1 Likert Scale for Breathlessness 1 Extremely short of breath 2 Very short of breath 3 Quite a bit short of breath 4 Moderate shortness of breath 5 Some shortness of breath 6 A little shortness of breath 7 Not at all short of breath The study was conducted at Auckland Hospital between June 2001 and October 2001. The study was approved by the Auckland Ethics Committee and all participants provided written informed consent. Power calculation The power calculation was based on a previous study where we treated subjects for acute exacerbations of COPD with theophylline for up to seven days [ 11 ]. In that study the average improvement in Likert score from baseline to the end of the study was 1.95 with theophylline and 1.05 with placebo. We assumed the subjects in this study would have a similar distribution of Likert scores for breathlessness. On this basis, 50 participants gave us 88% power to detect a similar difference between the groups as in the previous study, at a 5% level of significance. Statistical analysis The two treatment groups were compared at baseline using Student's t-test for normally distributed variables, Wilcoxon test for non-parametric data and Fisher's exact test for categorical data. The effect of N-acetylcysteine on breathlessness, lung function and oxygen saturation was analysed by fitting the patient data to a random coefficient model using a mixed linear model approach (least squares regression). The baseline (Day 1) measurements were used as co-variates in the analysis. This allowed individual slopes and intercepts to be formed for each patient and their random variation incorporated in the model. This model adjusted for the varying number of observations available on the different patients. Non-normal dependent variables were rendered normal by transformation. Significant and main interaction effects were investigated by the method of Tukey. All tests were two-tailed and a 5% significance level was maintained throughout these analyses. The analyses were carried out using SAS Version 8.0 (SAS Institute Inc, Cary, NC, USA.) The life test procedure of SAS was used to compute nonparametric estimates of the length of stay function by the Kaplan-Meier method. Comparison between these functions was made using the Wilcoxon and log rank tests. Results Two hundred and ten patients who had been admitted to hospital with an exacerbation of COPD were screened for the study. Fifty subjects were randomised to treatment with 25 subjects receiving N-acetylcysteine and 25 subjects receiving placebo. The commonest reasons for exclusion were concomitant heart failure (n = 41) or pneumonia (n = 35). The two groups were similar at baseline in terms of age, smoking history, lung function, oxygen saturation and breathlessness (Table 2 ). There were more men in the placebo group but the difference was not statistically significant (p = 0.23). There was no difference between the groups in the use of inhaled bronchodilators prior to admission (Table 3 ). More subjects in the N-acetylcysteine group had been on treatment with inhaled corticosteroids prior to admission but this difference was not statistically significant (p = 0.16). Although we did not document the amount of sputum produced by the subjects most subjects presented both with an increased volume of sputum as well as breathlessness. Table 2 Baseline characteristics of the subjects N-Acetylcysteine (n = 25) Placebo (n = 25) Gender Male/Female 11/14 19/6 Age Years (SD) 73.6 (7.8) 73.0 (8.2) Smoking History Pack Years (SD) 44.4 (36.2) 53.7 (36.8) FEV 1 % predicted (SD) 22 (10) 24 (12) VC % predicted (SD) 56 (18) 64 (22) SaO 2 % (SD) 90.2 (4.0) 90.4 (2.7) Breathlessness Likert Score (IQ range) 4 (3–6) 4 (3–5) Values are shown as mean and standard deviation except for Likert scores that are shown as median and interquartile range. There were no statistically significant differences between the two groups for any of the measures. Table 3 Concurrent medications N-acetylcysteine (n = 25) Placebo (n = 25) Inhaled steroids 15 9 Oral prednisone 9 6 Short acting inhaled beta-agonists 20 19 Ipratropium bromide 14 14 Long acting inhaled beta-agonists 7 7 Theophylline 4 1 The patients on treatment with oral prednisone included patients on long term treatment with oral steroids and those who were prescribed prednisone for this exacerbation prior to admission. There was no significant difference between the N-acetylcysteine and placebo groups for any of the concomitant medicines. All of the subjects completed the study with none being withdrawn early. The rate of change in the Likert scores, lung function and oxygen saturation is shown in Table 4 . For the Likert score, FEV 1 , and SaO 2 the rate of change was greater with placebo than with N-acetylcysteine but none of these differences were statistically significant. Table 5 shows the absolute changes in Likert score, FEV 1 and SaO 2 from the beginning to end of the study. Table 4 Slope of least squares regression line N-acetylcysteine (n = 25) Placebo (n = 25) Likert Score 0.16 (0.42) 0.35 (0.45) FEV 1 % predicted 0.001 (0.015) 0.019 (0.019) Sa0 2 0.40 (0.89) 0.88 (1.43) Mean and standard deviations for slopes of the least square regression lines for the effects of NAC and placebo on Likert scores for breathlessness, FEV 1 % predicted and SaO 2 . There were no significant differences between NAC and placebo. Table 5 Change in outcome measures from beginning to end of study N-acetylcysteine (n = 25) Placebo (n = 25) Likert Score 0.7 0.8 FEV 1 (litres) 0.03 0.15 Sa0 2 (%) 1.2 1.8 The average change in Likert score, FEV 1 , VC and SaO 2 from entry into the study to end of study (discharge or Day 7) are shown. The Kaplan-Meier analysis showed a similar time course until discharge for the treatment and placebo arms (Figure 1 ). Neither the log-rank statistic (p = 0.33), which places more weight on longer lengths of stay in hospital, nor the Wilcoxon test (p = 0.30) which places more weight on shorter stays in hospital were significant. The median length of stay was 6.0 in the NAC group and 5.5 in the placebo arm. Figure 1 The percentage of patients remaining in the study (i.e. who had not been discharged from hospital) on each day. N-acetylcysteine is shown by a dotted blue line and placebo by a solid red line. The life test procedure of SAS was used to compute nonparametric estimates of the length of stay function by the Kaplan-Meier method. Comparison between these functions was made using the Wilcoxon and log rank tests. Neither the log-rank statistic (p = 0.33) nor the Wilcoxon test (p = 0.30) were significant. The median length of stay was 6.0 days in the NAC group and 5.5 days in the placebo arm. Three subjects reported adverse events in each group. One of the subjects treated with N-acetylcysteine reported nausea compared with two of the subjects treated with placebo. There were no serious adverse events. Discussion N-acetylcysteine has been consistently shown to reduce the number of exacerbations of COPD when it is taken for 3 months or more. In contrast we failed to show any benefit when N-acetylcysteine was administered as a treatment for acute exacerbations of COPD. There are a number of possible explanations for the failure to see any benefit. We cannot exclude the possibility that there was a Type II error and that there is indeed a beneficial effect of N-acetylcysteine in the treatment of acute exacerbations. A larger study would be needed to rule out this possibility but there was less improvement in breathlessness, lung function and oxygen saturation with N-acetylcysteine than with placebo that argues against this explanation. Another possibility that needs to be considered is that we used too low a dose of N-acetylcysteine and that the concentrations of N-acetylcysteine in the lung were not high enough to exert adequate antioxidant or anti-inflammatory effects. N-acetylcysteine is metabolized to cysteine and this in turn acts as a precursor of reduced glutathione which is an antioxidant [ 12 ]. Bridgeman and colleagues studied the effects of administering either 600 mg once daily or 600 mg three times daily [ 13 ]. After a single dose of 600 mg, N-acetylcysteine was detected in plasma for 1.5 hours. Plasma cysteine concentrations were also elevated but had returned to baseline by four hours. Glutathione concentrations were variably increased following a single dose of N-acetylcysteine but when N-acetylcysteine was given as 600 mg three times daily (t.i.d) for 5 days the glutathione concentrations were consistently and significantly elevated 12 hours post dose. In this study there was no increase in cysteine or reduced glutathione in either bronchoalveolar lavage fluid or lung tissue (from subjects undergoing pneumonectomy) when the samples were obtained 16–20 hours after the last dose of N-acetylcysteine. In an earlier study, however, reduced glutathione had been shown to be increased in bronchoalveolar lavage fluid 1 to 3 hours after a single dose of 600 mg of N-acetylcysteine [ 14 ]. It is likely that the dosing regimen that we used would lead to increases in cysteine and glutathione in both plasma and in the lungs but this may well not have been sustained over the whole of 24 hours. This leaves unanswered the question of whether the changes that did occur in N-acetylcysteine, cysteine and glutathione would have been sufficient to alter the course of the exacerbation. The results of studies where N-acetylcysteine was used as a prophylactic agent to prevent exacerbations of chronic bronchitis and/or COPD would argue that we did use an adequate dose. In these studies doses of N-acetylcysteine between 300 mg b.d. to 600 mg b.d. were effective and the dose that we used in this study is at the upper end of this range. N-acetylcysteine has also been shown to be effective for other indications when it has been used in this dose. Several studies have shown that N-acetylcysteine 600 mg b.d. protects against contrast nephropathy [ 15 , 16 ]. Whether or not a higher dose of N-acetylcysteine would have been any more effective in the treatment of acute exacerbations of COPD can only be answered by conducting additional studies. In contrast to N-acetylcysteine, prednisone and prednisolone are effective treatments for acute exacerbations of COPD. Davies et al studied 56 patients admitted to hospital with an exacerbation of COPD and found that prednisolone led to a greater improvement in lung function and shortened the hospital stay [ 17 ]. Other studies have confirmed the efficacy of corticosteroids in severe exacerbations of COPD [ 18 ]. There is evidence of increased numbers of eosinophils in the airways during exacerbations of COPD. Corticosteroids are very effective at suppressing eosinophilic inflammation in the airways and this may account for the benefit seen in exacerbations of COPD. When children with an exacerbation of asthma are treated with prednisone, there is a marked reduction in the concentration of 8-isoprostane in exhaled breath condensate [ 19 ]. 8-isoprostane is a marker of oxidative stress. If N-acetylcysteine prevents exacerbations of COPD because it is an anti-inflammatory agent and/or antioxidant, it may be difficult to see additional benefit in established exacerbations of COPD when the patients are also treated with prednisone, which has anti-inflammatory actions and the potential to reduce formation of reactive oxygen species from inflammatory cells. There have been a number of other studies looking at the effect of mucolytics in acute exacerbations of chronic bronchitis although none of these studies used N-acetylcysteine. Each of these studies has limitations. Langlands treated 27 patients, who had been admitted to hospital with an exacerbation of chronic bronchitis, with bromhexine 8 mg t.i.d. for two weeks (13 patients received bromhexine and 14 received placebo) [ 20 ]. In this study lung function was only measured twice a week during the study but the difference between treatments was not statistically significant. Maesen and his colleagues studied 22 patients admitted to hospital with an exacerbation of chronic bronchitis and purulent sputum [ 21 ]. All subjects received erythromycin and half were treated with bromhexine. Lung function was not measured but treatment with bromhexine did not influence the bacteriological response to erythromycin. Fimiguerra et al randomized 40 patients who had been admitted to hospital with an exacerbation of chronic bronchitis to treatment with amoxicillin alone (20 patients) or a combination of amoxicillin and domiodol (20 patients) for 10 days [ 22 ]. There was a three day washout period before treatment was initiated but it is not clear if this means that patients were in hospital for three days before treatment was started. Lung function was only measured at the beginning and end of treatment but there was no difference between the groups in changes in FEV 1 and VC. Sputum volumes, however, were greater with the combination of the mucolytic and antibiotic. Ricevuti et al treated 24 patients with an exacerbation of chronic bronchitis [ 23 ]. Half of the patients were randomised to a combination of erdosteine and amoxicillin for seven days and the other received amoxicillin alone for the same period of time. Sputum viscosity and temperature resolved significantly more quickly with the combination but lung function was not measured in this study. None of these studies measured lung function on a daily basis and none assessed changes in breathlessness. This makes it difficult to know if treatment with these mucolytics influenced the rate of resolution of the exacerbations. On balance however these studies do not strongly suggest that mucolytics influence the resolution of acute exacerbations of COPD. Conclusions Our study does not suggest that 600 mg b.d. of N-acetylcysteine is effective in the treatment of patients who are admitted to hospital with an acute exacerbation of COPD and who receive concurrent treatment with corticosteroids. In future studies it may be appropriate to use a higher dose of N-acetylcysteine and to compare N-acetylcysteine with placebo in patients with mild exacerbations who do not require treatment with corticosteroids. Consideration could also be given to comparing the effects of N-acetylcysteine with prednisone or prednisolone in patients who would usually be treated with oral corticosteroids. Abbreviations NAC N-acetylcysteine COPD chronic obstructive pulmonary disease FEV 1 forced expiratory volume in one second VC vital capacity SaO 2 oxygen saturation Competing interests The author(s) declare that they have no competing interests. Authors' contributions PNB conceived the idea for the study and was responsible for the study design and writing the manuscript. He was also was involved in the conduct of the study and the analysis of the data. AM-D was involved in the conduct of the study, in the analysis of the data and with writing the manuscript. PJP was involved with the design and conduct of the study. TEM and RPY were involved with the conduct of the study. All of the 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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539296

ABC: software for interactive browsing of genomic multiple sequence alignment data

Background Alignment and comparison of related genome sequences is a powerful method to identify regions likely to contain functional elements. Such analyses are data intensive, requiring the inclusion of genomic multiple sequence alignments, sequence annotations, and scores describing regional attributes of columns in the alignment. Visualization and browsing of results can be difficult, and there are currently limited software options for performing this task. Results The Application for Browsing Constraints (ABC) is interactive Java software for intuitive and efficient exploration of multiple sequence alignments and data typically associated with alignments. It is used to move quickly from a summary view of the entire alignment via arbitrary levels of resolution to individual alignment columns. It allows for the simultaneous display of quantitative data, (e.g., sequence similarity or evolutionary rates) and annotation data (e.g. the locations of genes, repeats, and constrained elements). It can be used to facilitate basic comparative sequence tasks, such as export of data in plain-text formats, visualization of phylogenetic trees, and generation of alignment summary graphics. Conclusions The ABC is a lightweight, stand-alone, and flexible graphical user interface for browsing genomic multiple sequence alignments of specific loci, up to hundreds of kilobases or a few megabases in length. It is coded in Java for cross-platform use and the program and source code are freely available under the General Public License. Documentation and a sample data set are also available .

Background Functional elements in a genome accumulate inter-specific substitutions more slowly than neutral DNA throughout evolution [ 1 ]. Therefore, comparing orthologous genomic sequences from related species is useful for the identification of elements that play important roles in the biology of an organism [ 2 - 7 ]. While the statistical and computational methods for extracting comparative information are variable, the types of data involved are generally quite similar. First, a multiple sequence alignment is necessary. Second, a vector of quantitative scores is produced that describes the similarity of the nucleotides observed in small windows, or individual columns, of the alignment; percent identity is the metric used by the popular program VISTA [ 8 ], while a variety of other scoring methods also exist [ 9 - 12 ]. Third, annotations are generated that highlight regions of the alignment that are under constraint or meet some other quantitative threshold. Fourth, annotations of features like transcripts, promoters, coding exons, and repeats provide functional context. Finally, the phylogenetic tree that relates the aligned sequences is important for both performing comparative analyses and for interpreting their results. Simultaneous visualization of complex data such as these is of utmost importance both for experimentalists and for computational biologists. Several options currently exist for such visualization, but there are a variety of characteristics that distinguish the ABC from them. VISTA, for example, generates a static image that is not interactive [ 8 ]. Other popular browsers such as phylo-VISTA [ 13 ] and PipMaker [ 14 , 15 ] require the use of a particular alignment program and scoring scheme. Also, the ABC is not suited for genome-wide visualization. Other tools exist for this and are quite useful for the browsing of very large genomic intervals and major evolutionary events such as genomic rearrangements [ 16 - 19 ]. However, these programs are generally part of larger, more complex interfaces that are not necessarily ideal for targeted analysis of an individual alignment or genomic locus. Finally, we note that the ABC allows many annotation types and colors, is not web-based and can be used on a local machine as intensively as necessary, and the source code is open and freely available allowing users to modify and add features if desired. Implementation The ABC requires Java 1.4 or later and has been successfully tested on Windows, Linux, and OS X. There is no specific upper limit in the size of potential data sets, but system memory usage can be high on large alignments. The ABC can efficiently handle a 2 Mb alignment of 29 sequences on a machine with a 1 GHz processor and 1 Gb of RAM. Details about file formats and instructions for use are available in the documentation that is available along with the source code . The file formats used by the ABC are quite similar, with only minor modifications, to other standard formats, such as fasta-formatted sequence files and standard parenthesis notation for phylogenetic tree descriptions. A sample data set is available, and is the source of the screenshot depicted in Figure 1 . The sequence data are derived from a previously published analysis [ 20 ]; it includes ~300 kb of sequence from 9 mammals, centered around the ST7 gene in the human genome, near the CFTR gene. Repeats were identified in the human sequence using RepeatMasker [ 21 ] and genes identified using RefSeq annotations from the UCSC genome browser [ 17 ]. The alignment was generated using MLAGAN [ 22 ], and has been compressed so that the human sequence is ungapped; annotation of human sequence features is thus identical to the alignment annotations shown in Figure 1 . A description of the method used to score the alignment columns and identify constrained elements, along with Perl scripts that facilitate this method, including export of results in ABC-ready formats, will be described elsewhere (in preparation). Please note that the ABC will not translate coordinates from alignment to sequence coordinates (or vice versa); the annotations that the user supplies must be appropriate to the alignment being analyzed. Results and discussion By default, the ABC displays graphical summaries of the quantitative information associated with the alignment. Scores are summarized regionally in consecutive non-overlapping windows. The size of these windows depends on the resolution, defined as the number of alignment columns summarized per pixel. The ABC has three distinct display modes, chosen automatically depending on the density of the information. At very low resolution, a histogram is displayed that plots the number of data points in each window that are at or below a specified value; note that regions containing many low scores will stand out as peaks in the histogram, as demonstrated by the clear association of peaks and the location of exons (Figure 1 , top panel). At intermediate resolutions, a 'wiggly plot' is displayed, in which the average score for each regional window is plotted; in this case, regions containing many low scores will appear as valleys in the plot (Figure 1 ; middle panels). Finally, at very high resolution, the user may view the sequence data directly, along with the sequence names and a tree relating the sequences (Figure 1 ; lower panel). A mobile and scalable zoom window allows for exploration of the summary views (Figure 1 ; upper panels). The user may drag and resize this rectangle, and when a desired region is selected a more detailed view can be obtained. This region will be expanded immediately below the parent display, with the resolution, score plot, and annotation adjusted accordingly (Figure 1 ; compare the start and stop coordinates of the black rectangle in the top panel to the start and stop coordinates of the entire panel immediately below). At all resolutions, annotation tracks are displayed immediately above the score/sequence display (Figure 1 ; all panels). An arbitrary number of tracks may be displayed, but the bottom two tracks are reserved for displaying information about transcripts with exons and introns. Colors for features can be specified individually using standard RGB notation. Other key features of the ABC include: • Mouse-over highlighting to reveal annotations, scores, coordinates, etc • Exporting of sequence, score, and annotation data • Searching sequence data for particular nucleotide strings • GoTo feature to quickly bring up a desired region The ABC is flexible in that is has the ability to visualize diverse quantitative information and it has the capacity to display an arbitrary number of annotation types. It does not have a built-in scoring function; all data needs to be generated and formatted prior to being displayed in the ABC. While this may seem to be a drawback, it is in fact the intended function for an interface that has no preconceptions about the methodology that generated the data. Finally, the ABC is interactive, allowing the user to zoom in quickly from summary views of the comparative data to individual alignment columns. Zoom levels remain in the display, allowing the user to keep a birds-eye view of a large genomic region while focusing at much higher resolution on a small section within it. Conclusions The ABC is stand-alone alignment browsing software that is relatively easy to use and customize. While it was not designed as a genome-wide browser, it is well-suited for tasks associated with comparative sequence analysis: exploration of alignments of individual genomic loci; analyzing the relationship between known biological features and quantitative comparative data; visualizing results for researchers who develop and test methods for comparative sequence analysis; isolating sequence elements in a genomic locus for downstream applications like motif-discovery or primer design; generating graphics that characterize a multiple sequence alignment or region of an alignment; and potentially more applications that we have not yet considered. In our own research, for example, we have used it to display SNPs between different mouse strains in the context of a comparative alignment (not shown). This flexibility should be beneficial to researchers whose primary interest is comparative sequence analysis, but should also be valuable to those who use comparative analyses in support of other types of projects, such as experimental characterization of constrained elements. We also note that this flexibility distinguishes the ABC from other browsers that require built-in or specific types of score data and/or the use of a particular alignment program. The software is written in Java for cross-platform support, and the source code is freely available under the General Public License (GPL). Availability and requirements Project name: Application for Browsing Constraints (ABC) Project home page: Operating system: Platform independent Programming language: Java Other requirements: Java 1.4 or later License: GPL Abbrevations ABC: Application for Browsing Constraints GUI: Graphical User Interface GPL: General Public License SNP: Single Nucleotide Polymorphism UCSC: University of California, Santa Cruz RGB: Red-Green-Blue Authors' contributions GMC and AS conceived of the project, organized the feel and design of the browser, generated the underlying data, and wrote the manuscript. SAGS wrote the Java code and provided comments on the manuscript. All authors read and approved the final manuscript.

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539282

Expression of pS2 in prostate cancer correlates with grade and Chromogranin A expression but not with stage

Background The biological potential of prostate cancer is extremely variable. Particular interest is focused on markers not expressed in normal prostatic tissues. pS2 protein expression has been demonstrated in a range of malignant tissues in an oestrogen-independent pathway. Recently, it has been demonstrated that pS2, in prostate cancer, is closely associated with neuro-endocrine differentiation. In the present study, we have analyzed, the potential of Neuro-endocrine and pS2 (TFF1) expression in human prostate cancer determined by immunohistochemistry, in primary adenocarcinoma of the prostate and attempted to correlate this with the clinico-pathologic features of the patient and neuroendocrine expression. Methods Ninety-five malignant prostatic specimens from primary adenocarcinoma, obtained from either transurethral resection of prostate or radical retropubic prostatectomy, from 84 patients between January 1991 and December 1998 were evaluated by immuno-histochemical staining using selected neuroendocrine tumor markers i.e. chromogranin A (CgA) and estrogen inducible pS2 protein. The relationship between the expressions of pS2 was studied with CgA expression, clinical stage (TNM) and tumour grade (Gleason system). Fischer exact test was used for statistical analysis. Results The mean age of the patients was 70 + /- 9.2 years. The pS2 expression was seen in 10% of primary prostate cancers. Worsening histological grade was associated with greater expression of pS2 (p < 0.001). The expression of CgA was noted in 31% of malignant prostatic tissue. In pS2, positive cases 2/3rd of patients were also CgA +ve. However, there was no significant correlation between pS2 expression and the stage of disease. Conclusion pS2 expression in prostate cancer significantly correlates with histological grade and the neuroendocrine differentiation, as demonstrated by Chromogranin A expression but not with the clinical stage of the disease. However, the overall expression was low consequently; no definitive conclusions can be drawn. We feel further work is required in a larger series, both in primary and metastatic cancer.

Background The biological potential of prostate cancer is extremely variable [ 1 ]. It is perhaps the only cancer, which could be managed by, deferred treatment in its early course for selected cancers [ 2 ]. To define the biological potential of prostate cancer, prognostic markers are employed. There are numerous markers for assessing the biological aggressiveness of the prostate cancer [ 3 ]. However, large studies have shown that they lack sensitivity and specificity due primarily to their expression in normal prostatic epithelium as well. This justifies a recent surge in interest in markers specific to malignant prostatic tissue [ 4 ]. Recent studies have shown the potential of neuro-endocrine differentiation in adenocarcinoma of the prostate and its role in ascertaining the biological aggressiveness of the tumor [ 3 ]. Wang et al [ 5 ] has recently noted that the expression of the pS2 protein is implicated in the pathogenesis and progression of some neuro-endocrine tumors. Maisakowski et al. first described the pS2 gene in the MCF-7 human breast cancer cell line [ 6 ]. The pS2 is a cysteine rich secretory protein, containing 84 amino acids and a molecular weight of 6.45 k-Da. The pS2 gene is highly expressed in estrogen-receptor positive breast cancer, and high levels of pS2 protein correlate with responsiveness to primary endocrine therapy and better patient survival in breast cancer. However, in prostate cancer it is linked with NE differentiation and poorer outcome [ 7 ]. In the present study, we have investigated the expression of pS2 in malignant primary prostatic tissue in specimens obtained from transurethral, open prostatectomy, and correlated this with neuro-endocrine differentiation and clinical stage and grade. This is a preliminary report on pS2 expression in prostate cancer, a larger study will better define the correlation between stage, grade of cancer with pS2 and CgA expression. Methods Demographic profile Ninety-five malignant consecutive primary prostatic specimens were obtained from 84 patients by either trans-urethral resection of prostate (n = 69 patients) for urinary obstruction or from radical retro-pubic prostatectomy (n = 15 patients) between January 1991 and December 1998. These tissue specimens were taken from the archived records of the department of pathology. The age ranged from 52–93 years (mean 70 + 9.2 years). Immuno-histochemical staining for pS2 and Chromogranin A Sections were stained for H & E as well as for pS2 (Novocastra, UK Cat. # NCL-pS2) and Chromogranin A (DAKO, Glostrup, Denmark Cat # A0430) by immunohistochemistry using indirect immunoperoxidase technique. Briefly, 3 μm thick tissue sections were cut and mounted on poly-L-lysine (sigma) coated slides. Sections were deparaffinized in xylene and re-hydrated through graded alcohol series followed by water. Antigen retrieval was done in case of pS2 with 10 mM citrate buffer, 6.0 in a microwave oven 3 × 5 seconds at 450 W, then gradually cooled down to room temperature. Sections were washed with water followed by Phosphate buffer saline (PBS) rinse. Endogenous peroxidase in the sections was blocked for 30 minutes with 0.3% H2 02 in methanol. Sections were washed with PBS. All sections were treated with Normal Swine serum (NSS) prediluted 1:10 in PBS for 5 minutes. The sections were then incubated with the primary antibody to pS2 diluted with NSS (1:100) and Chromogranin A (1:20) for 90 minutes at room temperature. Slides were washed with PBS and incubated with peroxidase-conjugated swine anti rabbit secondary antibody (DAKO) at a dilution of 1:150 for 45 minutes at room temperature. 3, 3'-diaminobenzidine (DAB) was used as a final Chromogen. Harris Haemtoxylin was used as a counter nuclear stain. Positive and negative controls were used with all batches of IHC staining. A prostatic adenocarcinoma specimen section expressing pS2 was used as a positive control. Same case exhibiting the primary antibody was used a negative control with each staining procedure. The extent of pS2 reactivity was semi quantitatively assessed by estimating the percentage of positive acini present in the whole mounted sessions. Expression was graded ++ if more than 50% of the tissue showed expression, + if between 5 and 49% showed expression and focal if <5% showed expression. Histological grading The Gleason system was used for grading of the cancer specimens; a senior histopathologist (SP) blinded of previous Gleason grading and clinical course did this. Based upon the Gleason score patients were divided into three groups i.e. well differentiated (Gleason sum 2–4), moderately differentiated (Gleason sum 5–7) and poorly differentiated (Gleason sum 8–10). To study correlation and determine the p value Student t test was applied. Results The cancerous lesion composed of 35% (n = 29) stage T1, 32% (n = 27) stage T2, 25% (n = 21) stage T3 and 6% (n = 5) stage T4 disease according to the TNM classification. Based upon the stage of the disease patients were divided into three groups i.e. organ confined (T1-2), locally invasive (T3-4 and N1) and metastatic (M1) cancer. In 95-cancer specimen from transurethral resection (n = 69) for urinary obstruction and radical retropubic prostatectomy for organ-confined cancers (n = 15), pS2 reactivity was detected in the adjoining normal or hyperplastic acini in only 4.2%. The pS2 expression in cancer was found in 10% (figure 1 ). The immuno-histochemical reactivity of pS2 in malignant epithelial cells was confined to the cytoplasm of with a tendency to a perinuclear accentuation. Expression of pS2 was correlated with the stage of disease in Figure 1 . Staining for NE marker (CgA) was seen in 31% (figure 1 ); correlation between the pS2 and CgA expression is summarized in table 1 , it showed that 2/3rd of pS2 also showed CgA expression. Worsening histological grade was associated with greater expression of pS2. In Gleason sum groups 2–4 and 5–6, expression of pS2 was noted in 6 and 8% respectively whereas in Gleason sum group 8–10 the expression was observed in 30% (p < 0.001). The expression of pS2 [figure 4(a) and 4(b) ] in various prognostically and therapeutically distinct groups based upon the grade of cancer is described in figure 2 . Discussion In the present study, we investigated the expression of pS2 protein in the adenocarcinoma of prostate and in the surrounding normal prostate tissue. We used a standard immunohistochemical method to assess pS2 expression in tissue sections of adenocarcinoma prostate instead of instead of biochemical or immuno-radiometric assay. The immuno-histochemical method for detection of pS2 expression has drawbacks in comparison to biochemical and immunoradiometric assay on tissue extracts. Both of the later methods allow precise quantification of levels of expression for a better correlation with other parameters studied. However, as we are interested in the clinical utility of pS2 expression in our prostate cancer population, we used immunohistochemistry, which allows appreciation of intra-tumoral heterogeneity of expression and of both cancerous and non-cancerous cells. pS2 protein expression has been demonstrated in a range of malignant and benign pathologies. It is highly expressed in receptor positive human breast cancer [ 5 ] but expression in other cancers like ovarian [ 7 ], cervical [ 8 ], gastrointestinal [ 9 ], thyroid [ 10 ] and bladder [ 11 ] is variable. A significant implication of pS2 in prostate cancer is the close association of this marker with Neuroendocrine (NE) differentiation. There is increasing evidence that focal NE differentiation frequently occurs in prostatic adenocarcinoma and it may have significant prognostic implications [ 12 - 14 ]. NE differentiation is also described in hormone refractory prostate cancer; Krijnen et al [ 14 ] noted that androgen receptors are not present in prostatic adenocarcinoma staining positive for CgA. While Higashiyama noted 17% expression of pS2 in all pulmonary cancers, Wang et al [ 5 ] noted 45% expression in small cell cancers of the lung (a neuroendocrine carcinoma). Recent evidence has suggested that expression of pS2 is closely associated with neuroendocrine differentiation in prostate cancer [ 15 ]. Colombel et al from in an RT-PCR study found a high expression of pS2 in prostate cancer; however, they found no correlation between with tumour stage or Gleason grade. Our present work [ 15 ] indicates that NE differentiation not only correlates with other prognostic markers like grade of the cancer but also has independent prognostic value. Bonkhoff et al [ 15 ] noted that pS2 expression was consistently confined to NE differentiation in untreated tumors and in carcinomas that relapsed after hormonal therapy. Our results have similarly shown that 6 out of 9 cancers that have expressed pS2 were also positive for CgA. Conclusions Our results demonstrate that although the expression of pS2 protein was noted in only 1/10th of prostate cancers, it significantly correlates with the histological grade and NE differentiation; both have independent and interdependent prognostic value. There is dearth of data exploring the correlation of pS2 expression and aggressiveness of prostate cancer cell behavior. Limited literature available at present show significant association of pS2 expression with prognosis in prostate cancer, however more work is required to explore the utility of this marker in defining the biological potential of prostate cancer. Competing interest The author(s) declare that they have no competing interests. Authors' contributions MHA, conceived of the idea, wrote the manuscript and conducted clinical part of the study. FA, helped in designing the study and reviewed the draft of the manuscript NF, helped in conducting study, helped in data collection and analysis. MI, conducted the pathological part of the study. SP, conducted and supervised the pathological aspects of the study and reviewed the manuscript and wrote methods and results related to the pathology. All authors' have read and approve of the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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509427

Microglia and neuroinflammation: a pathological perspective

Microglia make up the innate immune system of the central nervous system and are key cellular mediators of neuroinflammatory processes. Their role in central nervous system diseases, including infections, is discussed in terms of a participation in both acute and chronic neuroinflammatory responses. Specific reference is made also to their involvement in Alzheimer's disease where microglial cell activation is thought to be critically important in the neurodegenerative process.

Background A role for immune responses, involving antigen presentation and immune-response-generating cytokines, in neurodegenerative diseases such as Alzheimer's disease was recognized for a decade before the term neuroinflammation came into widespread use [ 1 , 2 ]. A PubMed search using "neuroinflammation" as the only key word yields some 300 papers, none before 1995 [ 3 ]. While some chronic/remitting neurological diseases, such as multiple sclerosis, have long been recognized as inflammatory, the term neuroinflammation has come to denote chronic, CNS-specific, inflammation-like glial responses that do not reproduce the classic characteristics of inflammation in the periphery but that may engender neurodegenerative events; including plaque formation, dystrophic neurite growth, and excessive tau phosphorylation. In this way, neuroinflammation has been implicated in chronic unremitting neurodegenerative diseases such as Alzheimer's disease – diseases that historically have not been thought of as inflammatory diseases. This new understanding has come from rapid advances in the field of microglial and astrocytic neurobiology over the past fifteen to twenty years. These advances have led to the recognition that glia, particularly microglia, respond to tissue insult with a complex array of inflammatory cytokines and actions, and that these actions transcend the historical vision of phagocytosis and structural support that has long been enshrined in the term "reactive gliosis." Microglia are now recognized as the prime components of an intrinsic brain immune system [ 4 ], and as such they have become a main focus in cellular neuroimmunology and therefore in neuroinflammation. This is not the inflammation of the adaptive mammalian immune response, with its array of specialized T-cells and the made-to-order antibodies produced through complex gene rearrangements. This is, instead, the innate immune system, upon which adaptive immunity is built [ 5 ]. Many researchers now consider this innate immune response in the brain to be a potentially pathogenic factor in a number of CNS diseases that lack the prominent leukocytic infiltrates of adaptive immune responses, but that do have activated microglia and astrocytes, i.e., neuroinflammation. The idea that neuroinflammation is detrimental implies that glial cell activation precedes and causes neuronal degeneration [ 2 ], a sequence of events that appears to be at odds with experimental models of neurodegeneration in which glial cell activation occurs secondary to neuronal damage. What is missing from this simple linear model is the understanding that chronic neurological diseases are just that – chronic, and that this chronicity introduces complex interactions and feedback loops between neurons and glia that render attempts to construct simple, linear cascades of cause and effect inelegant. In the following, we provide some basic definitions and discussion to more precisely define the idea of neuroinflammation as a CNS tissue response to injury, and the notion of neuroinflammation as a pathogenic factor in neurodegenerative diseases. Some basic definitions Inflammation is a reaction of living tissues to injury [ 6 ]. The discipline of pathology makes a fundamental distinction between acute and chronic inflammation. Acute inflammation comprises the immediate and early response to an injurious agent and is basically a defensive response that paves the way for repair of the damaged site. Chronic inflammation results from stimuli that are persistent. In the periphery, inflammation consists of leukocytic infiltrates characterized by polymorphonuclear cells (neutrophils) in acute inflammation and mononuclear cells (macrophages, lymphocytes, plasma cells) in chronic inflammation. In order to validate these principles of general pathology within the context of neuroinflammation, one must obviously consider both acute and chronic neuroinflammation and, therefore, these are addressed separately in the following sections. Acute neuroinflammation Before "neuroinflammation" became a commonly used term, neuroscientists spoke of "reactive gliosis" in describing endogenous CNS tissue responses to injury. Reactive gliosis specifically referred to the accumulation of enlarged glial cells, notably microglia and astrocytes, appearing immediately after CNS injury has occurred. In contrast to glial reactivity, which suggests a largely passive response to injury; glial activation implies a more aggressive role in responding to activating stimuli: activated glial cells release factors that act on and engender responses in target cells analogous to the responses of activated immune cells in the periphery. Activation of immune cells in the periphery leads to leukocyte infiltration of tissues, but this is notably absent in the brain unless there has been destruction or compromise of the blood brain barrier [ 7 , 8 ]. In the presence of such destruction or compromise, peripheral leukocytes do enter the brain producing a scenario similar to that seen in inflammatory responses in the periphery. In limited, acute reactions to injury, in the absence of blood-brain barrier breakdown, there is the subtler response of the brain's own immune system, composed largely of rapid activation of glial cells. These responses represent the other end of the spectrum of CNS injury, where limited neuronal insults trigger glial cell activation without breakdown of the blood brain barrier and without concomitant leukocytic infiltration. This form of "pure" glial response occurs in neuronal injury caused by either loss of afferents [ 9 ] or loss of efferents [ 10 ]. Axotomy, for instance, results in neuronal chromatolysis, the classic example of potentially reversible neuronal injury [ 9 ]. It is in these situations that microglial and astrocytic responses (like their peripheral counterparts) fulfill their evolutionarily programmed functions of a reparative response to the benefit of the organism as a whole. Although such specific responses might, in a strict sense, be included in the term "neuroinflammation," neuroinflammation as generally used and understood applies to more chronic, sustained cycles of injury and response, in which the cumulative ill effects of immunological microglial and astrocytic activation contribute to and expand the initial neurodestructive effects, thus maintaining and worsening the disease process through their actions. Chronic neuroinflammation The concept of chronic inflammation (as opposed to acute inflammation) is more relevant in the context of understanding CNS disease (as opposed to CNS injury), as the very term "disease" implies chronicity. Chronic multiple sclerosis is, of course, an unequivocal and long-recognized example of an inflammatory brain disease. Although the underlying cause(s) of multiple sclerosis have not been elucidated, it is probably safe to say that the persistent injurious stimulus that accounts for neuroinflammation in multiple sclerosis is a myelin-related protein that has escaped self-tolerance and become an autoimmunogen. Consistent with the chronic persistence of this autoimmunogen is a persistent accumulation of blood-derived mononuclear leukocytes in the CNS parenchyma, a phenomenon that is similar to what is found in other autoimmune diseases such as rheumatoid arthritis or polymyositis. Infections are another group of diseases that are classically recognized as inflammatory in nature, with meningeal, perivascular, or even parenchymal infiltrates of peripheral leukocytes. There are, however, exceptions. Rabies is a disease in which the peripheral immune response is slow and inadequate, and in which classic inflammatory changes are less striking than those found in other viral encephalidites. Babes, in 1897 [ 11 ], described microglial activation in rabies infection, although he did not recognize the nodules he found as clusters of activated microglia. Similar small collections of activated microglia were subsequently found to occur in a wide variety of viral brain infections. Today, the most important example of a chronic brain infection is human immunodeficiency virus (HIV). Chronic HIV encephalitis is characterized by the same nodules of activated microglia that Babes described in rabies. HIV enters and persists in the CNS via myelomonocytic cells: monocytes, perivascular cells, and microglia [ 12 ]. HIV infection is uniquely different from most other infectious diseases affecting the CNS in that the virus targets and disables precisely those cells that are key players in neuroinflammation; microglia in the brain and T lymphocytes in the periphery. It therefore comes as no surprise that prominent T cell infiltrates do not occur in HIV encephalopathy. Prion diseases represent another chronic infectious CNS disease that is not accompanied by leukocytic infiltrates. Microglial activation, again, appears to be the most prominent inflammatory component of prion diseases [ 13 , 14 ], although there are a few reports describing T cell infiltration as well [ 15 , 16 ]. Prion diseases share interesting parallels to rabies infection in that infected cells are unrecognized by peripheral immune responses. This may explain in part the unusual patterns of neuroinflammation in prion diseases – manifest not only in atypical cellular infiltrates but also in unusual cytokine profiles [ 17 ]. Both HIV and prion infections probably produce an altered microglial physiology that is likely to translate into cycles of neurodegeneration, which could be a contributing factor in the development of dementia that occurs in these conditions. Chronic microglial neuroinflammation in neurodegenerative diseases Neurodegenerative diseases – particularly Alzheimer's disease, but also amyotrophic lateral sclerosis, Parkinson's disease, and Huntington's disease – lack the prominent infiltrates of blood-derived mononuclear cells that characterize autoimmune diseases. On the other hand, there is abundant evidence that many substances involved in the promotion of inflammatory processes are present in the CNS of patients with such neurodegenerative diseases. By far the bulk of this body of evidence is related to studies in Alzheimer's disease [ 18 ]. What distinguishes Alzheimer's disease from other neurodegenerative diseases is the conspicuous presence of extracellular deposits of amyloid in senile plaques. Senile plaques in Alzheimer brain are present in different stages of maturity, ranging from diffuse to neuritic to dense core, but they all contain the amyloid beta protein (Aβ). Aβ is a peptide that forms insoluble and pathological extracellular aggregates that seem to attract microglial cells, as suggested by the clustering of microglia at sites of Aβ deposition (see [ 19 ] for a review). There is evidence from experimental studies in animals to support the idea that microglia can phagocytose and degrade amyloid [ 20 , 21 ], but such phagocytosis is apparently either ineffective or inadequate in Alzheimer's disease. A key question within the current context is: "Does the amyloid in Alzheimer brain by itself represent a persistent injurious stimulus that causes neuronal injury, or are additional factors involved in eliciting this outcome?" Direct injection of Aβ into the brain produces activation of microglia and loss of specific populations of neurons [ 21 ]. Furthermore, transgenic mice that overexpress human, mutant β-amyloid precursor protein (βAPP) do develop Aβ deposits with associated evidence of neuritic injury (although they do not develop Alzheimer-type neurofibrillary tangles unless they are also transgenic for human tau protein) [ 22 ]. These Aβ deposits, born of transgenic overexpression of mutant human amyloid precursor protein, invariably contain activated microglia [ 22 , 23 ]. β-Amyloid precursor protein βAPP functions as a neuronal acute-phase, injury-response protein. For instance, there is excessive expression of βAPP, accompanied by microglial activation and cytokine expression, after traumatic head injury [ 24 ]. With head injury, there is also Aβ deposition, both in experimental animals [ 25 ] and in humans – particularly in individuals genetically susceptible for AD (i.e. ApoE ε4-positive) [ 26 ]. These observations emphasize the complex interactions that underlie neurodegeneration in Alzheimer's disease. Conclusions Chronic microglial activation is an important component of neurodegenerative diseases, and this chronic neuroinflammatory component likely contributes to neuronal dysfunction, injury, and loss (and hence to disease progression) in these diseases. The recognition of microglia as the brain's intrinsic immune system, and the understanding that chronic activation of this system leads to pathologic sequelae, has led to the modern concept of neuroinflammation. This vision of microglia-driven neuroinflammatory responses, with neuropathological consequences, has extended the older vision of passive glial responses that are inherent in the concept of "reactive gliosis." Abbreviations Aβ: β-amyloid peptide βAPP: Aβ precursor protein CNS: central nervous system HIV: human immunodeficiency virus MS: multiple sclerosis Competing interests None declared Authors' contributions WJS conceived this review, wrote the initial draft, modified this with the comments of REM and WSTG, and wrote the final draft. REM and WSTG contributed particularly to the sections on infections and on Alzheimer's disease. All authors read and approved the final version.

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514488

Unused Natural Variation Can Lift Yield Barriers in Plant Breeding

Natural biodiversity is an underexploited sustainable resource that can enrich the genetic basis of cultivated plants with novel alleles that improve productivity and adaptation. We evaluated the progress in breeding for increased tomato (Solanum lycopersicum) yield using genotypes carrying a pyramid of three independent yield-promoting genomic regions introduced from the drought-tolerant green-fruited wild species Solanum pennellii. Yield of hybrids parented by the pyramided genotypes was more than 50% higher than that of a control market leader variety under both wet and dry field conditions that received 10% of the irrigation water. This demonstration of the breaking of agricultural yield barriers provides the rationale for implementing similar strategies for other agricultural organisms that are important for global food security.

Introduction Plant evolution under domestication has led to increased productivity, but at the same time it has narrowed the genetic basis of crop species ( Ladizinsky 1998 ). A major objective in modern breeding is to return to the wild ancestors of crop plants and employ some of the diversity that was lost during domestication for the improvement of agricultural yields under optimal as well as stress field conditions ( Bessey 1906 ; Tanksley and McCouch 1997 ; Lee 1998 ; Zamir 2001 ). Most of the genetic variation present in wild species has a negative effect on the adaptation of plants to agricultural environments; hence, the challenge is to identify and utilize the advantageous traits in a breeding program. DNA markers have facilitated quantitative trait loci (QTL) mapping studies in segregating populations, showing that certain genomic regions derived from wild germplasm have the potential to improve yield, e.g. for rice ( Septiningshi et al. 2003 ), wheat ( Huang et al. 2003 ), barley ( Pillen et al. 2003 ), soybean ( Concibido et al. 2003 ), chickpea ( Singh and Ocampo 1997 ), tomato ( Bernacchi et al. 1998 ), and pepper ( Rao et al. 2003 ). In the above studies, and many others that are not cited, plants in the segregating populations generally contained a number of wild-species chromosome segments which masked the magnitude of some of the favorable effects that were clearly identified for certain introgressed alleles. As a result, the yield-promoting QTL did not have a substantial contribution to the phenotype and the best lines were inferior to intensively bred varieties that are in wide commercial cultivation. A major advantage for the above populations is that they can easily lead to the development of introgression lines that are discussed below. The main question addressed in the present study is whether it is possible to incorporate favorable wild-species QTL into genetic backgrounds that will consistently out-perform the leading varieties in the market. To enhance the rate of progress of breeding based on wild-species resources, we developed a population of tomato segmental introgression lines (ILs). The ILs comprised marker-defined genomic regions taken from the drought-tolerant wild species Solanum pennellii and introduced (through genetic crosses) onto the genetic background of the elite inbred variety M82 ( Eshed and Zamir 1995 ; see Knapp et al. 2004 for the new taxonomic classification of tomato species in the genus Solanum ). The ILs constitute an “exotic library” where the entire wild-species genome was partitioned among 76 lines each carrying a single homozygous introgressed segment. Implementation of this resource for QTL mapping is based on the nearly isogenic nature of the lines such that any phenotypic difference between M82 and an IL, or the hybrid of M82 with an IL (ILH), is attributable to the S. pennellii genomic segments ( Figure 1 ). Similar population structures were recently shown to greatly facilitate the detection of naturally occurring variation in inbred mice ( Singer et al. 2004 ). Figure 1 Genetic Sources of BY Variation (Exotic variation) Since M82, the multiple-introgression line (IL789), and their hybrid IL789 × M82 (ILH789) differ only in three S. pennellii segments (green chromosomes), any BY difference between them is associated with the exotic allelic variation. (Cultivated variation) Yield differences between M82 (red chromosomes), the four tomato tester inbreds (pink chromosomes), and their hybrids (M82 × Testers) result from allelic variation present in the cultivated tomato gene pool. (Cultivated + Exotic) The yield of the hybrids of IL789 with the four testers (IL789 × Testers) results from both cultivated and exotic variation. Phenotyping is the rate-limiting component in the utilization of such an exotic genetic resource. This is particularly true for quantitative traits where the reproducibility of the phenotype has to be evaluated in different seasons, environments, and genetic backgrounds. Over the past ten years the ILs and their hybrids have been assayed for yield-associated traits, and the data are presented, in silico, in a search engine that displays a range of statistical and graphical outputs that describe the components of the genetic variation ( http://zamir.sgn.cornell.edu/ ; Gur et al. 2004 ). A review of the tomato QTL data and results of the QTL mapping studies from other species indicate that it is unlikely that a single introgression will induce a striking improvement in a yield-associated phenotype. However, pyramiding a number of independent introgressions in a single genotype, each with a positive effect on the desired trait, could be a strategy to greatly improve performance. The nearly isogenic nature of the ILs provides a relative advantage over other segregating populations in the rapid implementation of a pyramiding approach through crosses and marker analysis. We demonstrate here that the ILs make an efficient reagent for the discovery and utilization of genes that underlie traits of agricultural value and constitute a resource to explore the interactions among independent yield-associated QTL. We show that the pyramiding of independent yield-promoting segments can lead to novel varieties that reproducibly increase productivity relative to leading commercial genotypes both under normal cultivation conditions and in the stress environment of drought. Results/Discussion Exotic Variation In “ketchup tomatoes,” which are used to produce various concentrated products, agricultural yield is made up of the total weight of the fruits harvested per unit area (yield [Y], measured in kg/m 2 ) and their soluble-solids content (mainly the sugars glucose and fructose), which is measured in refractometer brix (B) units (expressed as a percentage). Therefore, agricultural yield of processing tomatoes is the total sugar output per unit area (brix × yield [BY], measured in g/m 2 ); the industry is searching for varieties that excel in BY. Our experiments were conducted in wet and dry fields, where the BY of the control variety M82 in the dry conditions was only 50% of that produced in the wet treatment, which received 10-fold greater irrigation (184 g/m 2 and 353 g/m 2 , respectively; average BY from 3 y). In this study we focused on three independent introgressions from Chromosome 7 (IL7-5-5), Chromosome 8 (IL8-3), and Chromosome 9 (IL9-2-5) that affect the components of BY. Figure 2 summarizes the data of the yield components from three growing seasons in wet and dry fields. The data from the different years were pooled, as we detected no significant year x genotype interactions. IL7-5-5 was dominant in its effect on Y, as both the homozygous IL and heterozygous ILH increased Y in the wet fields by 30% compared to M82 and by 12% to 22% (nonsignificant) in the dry fields. IL7-5-5 did not affect B, while for BY it was dominant. IL8-3 was greatly inferior to M82 for Y (−55% and −34% for the wet and dry treatments, respectively), but the ILH increased Y by 45% and 25% (wet and dry, respectively). This result indicates a strong overdominant effect for the introgression ( d/[a] = 2.5; see “Statistical analyses” for definitions). The homozygous IL had double the effect on B relative to the ILH; this resulted in a strong overdominant effect on BY in both environments (70% and 40% increases relative to M82 in the wet and dry fields, respectively; d/[a] = 5). The reduced Y of IL8-3 was caused by a pleiotropic effect of a leaf necrosis gene that was observed in all lines that were homozygous for this introgression; the necrosis was particularly severe in the dry treatment. IL9-2-5 significantly increased Y only in the homozygous condition in the wet treatment. For B and BY, ILH9-2-5 was intermediate between M82 and the homozygous IL, showing an additive mode of inheritance. The nature of the genes that improve BY in the above introgressions is unknown, with the exception of IL9-2-5, which harbors at least two QTL that affect the components of BY ( Fridman et al. 2002 ). One of the QTL is Brix9-2-5, which resides in a 484-bp interval within the apoplastic invertase (LIN5) that increases sugar content of the fruit as a result of a modification of enzyme functions ( Fridman et al. 2000 and unpublished data). LIN5 and three other invertase family members reside on segmental duplications in the near-collinear genomes of tomato and potato. These chromosomal segments are syntenically duplicated in the model plant Arabidopsis and in rice, thus facilitating the research of synteny-based orthologs and their relationship to yield components ( Fridman and Zamir 2003 ). Figure 2 Pyramiding of S. pennellii Introgressions That Increase Agricultural Yield Components Introgression lines IL7-5-5, IL8-3, IL9-2-5, and IL789, which combines all three segments, were compared to M82 (percent difference from M82) in a homozygous (IL) and heterozygous (ILH) condition in wet and dry fields (1 plant/m 2 ). The bars represent total yield (Y), brix (B), and brix × yield (BY) means (± standard error) from three growing seasons; these data were pooled, since no season × genotype interactions were found. The base line represents M82, where the mean BY values of M82 from the three seasons were 353 g/m 2 in the irrigated treatment (455 g/m 2 in 2001, 285 g/m 2 in 2002, and 320 g/m 2 in 2003) and 184 g/m 2 in the dry treatment (244 g/m 2 in 2001, 186 g/m 2 in 2002, and 122 g/m 2 in 2003). The additive effect (a) is half of the difference between each IL and M82. The dominance deviation (d) is the difference between ILH and the mid-value of its parents. Values marked by an asterisk are significant ( p < 0.05). The bars in the gray background and their corresponding a and d values represent the expected values of IL789 and ILH789 assuming complete additivity of the introgression effects. Asterisks above the expected-value bars represent significant deviations from the observed means for IL789 or ILH789 as determined by a t test at a confidence level of 95%. All experiments were transplanted in a randomized block design with the following number of replications for each genotype under each irrigation regime: 2001, 10 replications; 2002, 15 replications; 2003, 15 replications. The three S. pennellii segments were pooled, using marker-assisted selection, into a single M82 line designated IL789 (homozygous for IL7-5-5, IL8-3, and IL9-2-5). IL789 showed a strong interaction with the environment: In the wet treatment it produced a Y similar to that produced by M82, while in the dry fields Y was reduced by 36% as a result of the pleiotropic effect of the recessive leaf necrosis gene on IL8-3. In the heterozygous condition IL789 dramatically increased Y in both field environments, and combined with the increases in B, ILH789 improved BY by 109% in the wet field and 58% in the dry fields. As described in earlier studies ( Eshed and Zamir 1995 ) and demonstrated here for IL789, the positive effects of the wild introgressed segments on yield-associated traits were often more pronounced in the heterozygous condition due to linked deleterious recessive genes originating from S. pennellii . In a previous study based on the ILs, Eshed and Zamir (1996) showed less-than-additive epistatic interactions for yield QTL. For a large number of lines carrying pairs of different introgressed segments, they detected a trend of lower BY values than were expected based on the sum of the effects of the individual ILs. This phenomenon was more pronounced for combinations of ILs that affected the same component of BY (either B or Y). The less-than-additive mode of interaction was suggested as an underlying genetic model to explain canalized characters, where the phenotype is kept within narrow boundaries despite genetic and environmental disturbances. For quantitative traits affected by a large number of QTL, the less-than-additive interaction ensures that a “loss” of an allele will have a minimal effect on the canalized phenotype. In the present study we compared the observed phenotypic values of IL789 and ILH789 with the expected value based on the assumption of additivity of the effects of the three introgressions that were pyramided into these lines. In the wet treatment all the observed values for IL789 were lower than expected; however, this trend was statistically significant only for B. In the dry fields the recessive leaf necrosis gene on IL8-3 exerted a strong epistatic effect which nullified the contribution of the other introgressions. Thus in all cases the observed values for IL789 were lower than expected and very similar to those for IL8-3 ( Figure 2 ). From the plant breeding point of view, it is noteworthy that by pyramiding three heterozygous introgressions that affect the different components of BY, we achieved in ILH789 81% and 70% additivity (wet and dry, respectively) of the effects of the individual ILHs. Thus the heterozygous wild-species introgression pyramid improved BY in the genetic background of M82 by 109% in the wet fields and 58% in the dry fields. Cultivated Variation Our breeding program within the Solanum lycopersicum gene pool over the past several years has generated tester inbreds of different origins that give a sampling of the genetic diversity of processing tomatoes. Four testers, whose hybrids with M82 exhibited the highest BY, were selected for this experiment, which was aimed at exploring the breeding potential of the genetic variation within the processing tomato germplasm ( Figure 3 A). The BY values of the inbred testers in the wet and dry treatments were not significantly different from that of M82, whereas the four hybrid combinations with M82 had higher mean BY in both environments (71% in the wet treatment and 51% in the dry treatment; Figure 3 B). This improvement over the parents reflects the genetic variation present in the cultivated tomato gene pool, which was expressed as hybrid vigour originating from crossing of the preselected diverse inbreds (see Figure 1 ). As a reference outgroup for the entire experiment we selected the commerical hybrid BOS3155, which has been a processing tomato market leader in California for the past five years ( http://www.ptab.org/ ). BY of BOS3155 was in a range similar to that of our experimental hybrids, indicating that the experiment was conducted in elite genetic backgrounds. Figure 3 Contribution of Cultivated and Exotic Variation to BY (A) The contribution of cultivated and exotic variation to BY in five genetic backgrounds. BY phenotypes in the Akko wide-spacing wet and dry experiments that involved four independent tester inbreds and their hybrids with M82 and IL789 are shown. Included are mean values for a control background of M82 and BOS3155. The four inbreds are represented as horizontal lines with circles in the gray bars. Experiments were transplanted in a randomized block design with 20 replications for each genotype under each irrigation regime. In all cases BY of the hybrids containing the exotic introgressions (IL789 × Testers) was significantly higher than that of their nearly isogenic cultivated tomato hybrids (M82 × Testers; t test, p < 0.01). The exotic effect, which represents the BY differences between the IL789 × Testers hybrids and the M82 × Testers hybrids, was consistent for all genetic backgrounds in each of the irrigation regimes. This was determined by genetic background × exotic effect two-way ANOVA ( p for the interaction is 0.75 for the wet treatment and 0.88 for the dry field). (B) The mean contribution of cultivated and exotic variation to BY in wet and dry fields. BOS3155 is a leading commercial tomato hybrid that was used as a reference. Values of tester inbreds, M82 × Testers, and IL789 × Testers (shown as Δ% from M82) represent the means of the four genotypes included in each group (see Figure 3 A). Base line and the letters attached to it represent M82. Means for each irrigation treatment with different letters are significantly different using a multiple-range means comparison (Tukey-Kramer; p < 0.01). The deduced exotic effect on BY is marked as black bars, and the contribution of the cultivated variation to BY is marked in gray. The absolute BY values of M82 were 303 g/m 2 in the wet treatment and 122 g/m 2 in the dry treatment. Combining Exotic and Cultivated Variation A correct assessment of the potential of exotic QTL is in the context of high-yield genetic backgrounds—those close to the “yield barrier.” This was achieved by crossing IL789 with the four inbred tester lines in a manner that combined the contribution of both the cultivated and the exotic variation (see Figure 1 ). These IL789 × Testers hybrids were nearly isogenic to the M82 × Testers hybrids, and thus the differences between them reflect the effect of the exotic alleles on BY. The effects of the three heterozygous introgressions on BY were consistent in all the hybrid combinations, and no genetic background × exotic effect interactions were found in any of the environments ( Figure 3 A). The mean BY increase of the four IL789 × Testers hybrids, compared to M82, was 170% (wet) and 115% (dry), while the mean contribution of the M82 × Testers hybrids was 71% (wet) and 51% (dry) ( Figure 3 B). Based on the consistent effect of the introgressions in the different genetic backgrounds, we could estimate the contribution of the S. pennellii pyramid as the mean difference between the nearly isogenic hybrid groups: 100% (wet) and 65% (dry). These estimates for the exotic effects on BY are very close to those obtained in the uniform M82 background, indicating additivity of the exotic and cultivated effects (see Figure 2 ). The highest BY was measured for the hybrid of IL789 with inbred #76. This hybrid was compared with M82 and BOS3155 in six independent experiments that differed in location, planting density, and irrigation regime ( Figure 4 ). The BY advantage of the IL789 × 76 hybrid relative to M82 was not accompanied by other negative traits originating from the wild species and was observed in all field environments, ranging from 60% in Mevo-Hama with wide spacing and wet treatment to 200% in Akko under similar conditions. Significantly, the mean BY improvement of this IL789 × 76 hybrid over the market leader BOS3155 was 67% in the irrigated conditions and 58% in the dry conditions. Figure 4 BY Phenotypes of M82, BOS3155, and the Best Hybrid Combination (IL789 × 76) in Six Independent Trials Plants were grown in two locations, under two planting densities and two irrigation regimes. The locations were (i) the Western Galilee Experimental Station in Akko and (ii) Kibbutz Mevo-Hama (MH) in the Golan Heights. The planting densities were (i) single plants (SP; 1 plant per m 2 ) and (ii) plots (14 plants per 4 m 2 , or 3.5 plants/m 2 ). The irrigation regimes were (i) wet (320 m 3 of water per 1,000 m 2 of field throughout the growing season) and (ii) dry (30 m 3 of water per 1,000 m 2 of field). All experiments were transplanted in a randomized block design with the following number of replications: Akko-SP-wet, 15 replications; Akko-SP-dry, 20 replications; Akko-plots-wet, 8 replications; Akko-plots-dry, 8 replications; MH-SP-wet, 15 replications; MH-SP-dry, 15 replications. Means not connected by the same letter are significantly different using a multiple-range means comparison (Tukey-Kramer; p < 0.01). The results of IL789 × 76 and the control varieties in the different environments provided the means to explore genotype × environment (G × E) interactions and the stability of BY improvement associated with the heterozygous S. pennellii introgressions ( Table 1 ). Generally, strong G × E interactions of new varieties indicate the lack of a predictable response, which is undesirable in breeding ( Dudley and Moll 1969 ). In the wet fields we detected significant genotypic, environmental, and G × E interaction effects for the varieties tested. However, the IL789 hybrid always had significantly higher BY than the commercial varieties, and the interaction was caused in part by differences between the commercial varieties M82 and BOS3155 ( Figure 4 ). In the dry trials there was a highly significant genotypic effect and marginally significant effects for the environment; no interaction between the two components was detected, and IL789 × 76 had higher BY in all experiments. This analysis highlights the potential of wild germplasm to affect yield stability in diverse environments, which has long been recognized as an important objective in plant breeding. Table 1 ANOVA of Genotype by Environment Interaction for BY in IL789 × 76, BOS3155, and M82 Combined analysis of variance of genotype (G), environment (E), and G × E interaction for BY of three varieties and three environments in each of the dry and wet treatments a df , degrees of freedom b MS, mean square We have demonstrated that an IL population derived from a wild tomato species, with no yield potential, can make a wide array of previously unexplored genetic variation rapidly available to plant breeders to improve crop productivity. The effectiveness of the introgressions in diverse genetic backgrounds indicates that alleles similar to those of the wild species are not present in the cultivated tomato gene pool. The results presented here using the tomato ILs establish a genetic infrastructure to explore the molecular basis underlying yield heterosis. With the coming sequence of the tomato genome it will be easier to isolate those factors that are responsible for the strong overdominant effects, such as those observed for IL8-3 and some additional lines that are described in the IL phenotypic database Real Time QTL ( Gur et al. 2004 ). Finally, our approach of pyramiding beneficial wild-species chromosome segments provides an alternative to the genetically modified organism strategy for crop improvement and offers a new paradigm to revitalize plant breeding ( Tanksley and McCouch 1997 ; Zamir 2001 ; Morgante and Salamini 2003 ; Koornneef et al. 2004 ). Can these results be extrapolated to the breeding of other crop plants? Wild species that are distantly related to crop plants can be viewed as vast naturally mutagenized resources where every gene and regulatory element has been refined and defined by evolution. We propose that for crops that rely on a rather narrow genetic basis (rice, wheat, soybean, etc.) and have rich biodiversity resources, the construction and screening of ILs will lead to dramatic improvements in yield and other quality traits that are important for human well-being ( Rosegrant and Cline 2003 ). As we are able to make a wider range of natural genetic diversity accessible to breeders, we will make progress in improving our global food security. Materials and Methods Field trials The results presented are from three growing seasons. In 2001 and 2002 all field trials were conducted at the Western Galilee Experimental Station in Akko, Israel, at a wide-spacing planting density of 1 plant per m 2 . In 2003, trials were conducted in two locations: Akko and Mevo-Hama, in the Golan Heights. In Akko, experiments were both at wide-spacing planting density and in plots of 14 plants per 4 m 2 (3.5 plants/m 2 ). In Mevo-Hama all experiments were at the wide-spacing density. The seedlings were grown in a greenhouse for 35–40 d and then transplanted in the field, at the beginning of April in Akko, and at the beginning of May in Mevo-Hama. In all seasons and locations both wet and dry trials were conducted. Both the wet and dry fields started the growing season at “field capacity,” which represents the maximum amount of water that the soil could hold. For the dry treatment only 30 m 3 of water was applied per 1,000 m 2 of field immediately after transplanting. In the wet treatment 320 m 3 of water was applied per 1,000 m 2 of field throughout the growing season according to the irrigation protocols in the area. All experiments were transplanted in a randomized block design. Genotyping and phenotyping To ensure the nearly isogenic nature of the ILs, we bred an M82 line that was heterozygous for all three introgressions and used RFLP markers to genotype 128 F2 plants segregating for the three S. pennellii genomic segments (CT252 for IL7-5-5, CT148 for IL8-3, and GP263 for IL9-2-5). Lines homozygous for each of the segments and IL789 homozygous for all three introgressions were selected and verified with RFLP markers that flanked the introgressed segments from both ends ( http://www.sgn.cornell.edu/ ). Phenotyping of the plants for Y, B, and BY was performed according to published protocols ( Fridman et al. 2002 ). Statistical analyses Statistical analyses were performed using the JMP V.5 software package (SAS Institute, Cary, North Carolina, United States). Mean values for the parameters measured for the tested genotypes were compared using the “Fit Y by X” function and “Compare all pairs” (Tukey-Kramer). All calculations were performed with the phenotypic values, while some of the results are presented as the percent difference from M82. The additive effect (a) was half of the difference between each IL and M82, and its significance level was determined by the comparison between the IL and M82. The dominance deviation (d) is the difference between ILH and the mid-value of its parents. Its significance level was calculated by contrasting the ILH (+1) with M82 (−0.5) and the appropriate IL (−0.5). The degree of dominance for each introgression (d/[a]) was calculated by dividing the mean dominance deviation by the mean additive effect. Deviation of the observed yield component values of the pyramided genotypes (IL789 and ILH789) from the expected values based on the assumption of additivity of the effects of the individual introgressions was tested using a t test at p < 0.05. G × E interaction was tested using a two-way ANOVA.

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509426

Optimizing the HIV/AIDS informed consent process in India

Background While the basic ethical issues regarding consent may be universal to all countries, the consent procedures required by international review boards which include detailed scientific and legal information, may not be optimal when administered within certain populations. The time and the technicalities of the process itself intimidate individuals in societies where literacy and awareness about medical and legal rights is low. Methods In this study, we examined pregnant women's understanding of group education and counseling (GEC) about HIV/AIDS provided within an antenatal clinic in Maharashtra, India. We then enhanced the GEC process with the use of culturally appropriate visual aids and assessed the subsequent changes in women's understanding of informed consent issues. Results We found the use of visual aids during group counseling sessions increased women's overall understanding of key issues regarding informed consent from 38% to 72%. Moreover, if these same visuals were reinforced during individual counseling, improvements in women's overall comprehension rose to 96%. Conclusions This study demonstrates that complex constructs such as informed consent can be conveyed in populations with little education and within busy government hospital settings, and that the standard model may not be sufficient to ensure true informed consent.

Background It is estimated that nearly 7.2 million people in Asia and the Pacific region are now living with HIV/AIDS, one million of whom acquired the virus in 2002 [ 1 ]. Of these, more than 2.4 million are women (ages 15–45) [ 1 ]. India's national HIV prevalence rate of less than 1% offers little indication of the serious situation facing the country. An estimated 3.97 million people were living with HIV in India at the end of 2001, ranking it second only to South Africa in numbers of people infected. Although recent data suggest that prevention efforts directed at high-risk populations has resulted in greater HIV/AIDS knowledge and condom use [ 2 , 3 ], the prevalence of HIV/AIDS continues to rise. For HIV-positive pregnant women who have the additional risk of transmitting the disease to their unborn child, fewer prevention efforts are in place and are acutely needed. In some states in India such as Andhra Pradesh, Karnataka, Maharashtra, Manipur, Nagaland and Tamil Nadu prevalence rates are greater than 1% [ 1 ], underlining the need for well-planned and sustained interventions on a large scale. In most industrialized countries, voluntary HIV counseling and testing services are a major component of HIV and AIDS control programs targeted toward pregnant women, although such programs are only now being advocated in developing countries [ 4 , 5 ]. Voluntary counseling and testing involves two basic components–an educational component on HIV/AIDS and an informed consent component related to an individual's choice to be HIV tested or not. The primary motivations for conducting voluntary HIV counseling and testing in lower risk populations such as pregnant women are that i) immediate knowledge of the woman's status can help reduce risk of HIV transmission to the unborn child; ii) if not infected, education at this point can help both the husband and wife to reduce risk behaviors to prevent transmission; and iii) testing of the partner can be encouraged [ 6 ]. Because voluntary HIV counseling and testing is the principal entry point for both prevention and care, it is critical that the content of the counseling is well understood and that procedures to ensure true informed consent are in place [ 7 , 8 ]. The basic ethical issues regarding consent may be universal to all countries. One of the potential limitations with the current approach is that consent has been reduced to a technical issue and is often removed from wider ethical considerations. The consent procedures required by international review boards include having to provide detailed scientific and legal information to participants. Although the intent is to increase knowledge, these messages may lose their meaning when administered within certain populations. The challenge then becomes one of how to balance the requirements of providing complete information while also obtaining true informed consent. To begin establishing voluntary counseling and testing for pregnant women in India, the Indian National AIDS Control Organization (NACO) in 2001 started voluntary HIV counseling and testing for women attending government-run antenatal clinics in 11 sites throughout the country. This study was conducted in one of these sites, Pune, Maharashtra, in order to develop tools to enhance, standardize and improve the communication of messages during the group education and counseling (GEC) sessions, and to enhance the informed consent process. Methods This study was conducted in the antenatal clinic of an urban government hospital in Pune. Eligible patients were newly registered pregnant women between 18 and 44 years of age who were less than 36 weeks gestation and had no physical or mental disabilities (as determined by a physician). After each eligible woman registered in the antenatal clinic and met with the attending physician, they were offered the opportunity to attend the HIV/AIDS GEC sessions. The eight major topics covered in the education component of the GEC included general transmission modes of HIV, sexual transmission, mother-to-infant HIV transmission, precautions to avoid HIV transmission, ways through which HIV does not transmit, identification of HIV in an individual, detection of HIV in the body, and symptoms of AIDS. In addition, nine major topics related to HIV testing and informed consent were covered, including procedural risks of HIV screening, social risks of HIV screening, availability of the report, the right to say no, repercussions of refusing to take the test, confidentiality of the testing procedures, the right to consult others, the benefits of HIV screening, what one's signature means, specific procedures of the HIV ELISA test and, if applicable, specific procedures of the rapid HIV test. Baseline data We conducted structured observations of 30 GEC sessions over the period from December 2000 to January 2001 to assess how well the information was being covered. The GEC sessions were chosen so that every clinic day (Monday-Saturday) and session time would be equally represented (there were, on average, four GEC sessions during the clinic hours of 9:30 am to 1:00 pm). The structured observation tool included a comprehensive checklist of each of the specific points for each main topic covered during the GEC. A topic would be considered adequately covered if the counselor conveyed all the specific points for the topic. Overall session adequacy was assigned if at least 80% of all topics were presented adequately during the session. To assess women's understanding of the key issues covered we interviewed 136 consecutively consenting women immediately after they attended one of the 30 sessions (89% of the total number of women who attended these sessions). Informed consent was obtained from each woman prior to the interview. After the interview, the women met briefly with an individual counselor, where they chose whether to have HIV testing and, if so, signed the appropriate informed consent form. The women's understanding of the GEC sessions was determined through structured interviews containing 17 questions covering each of the main topics discussed in the GEC. Their answers were scored as either adequate or inadequate based on predetermined criteria. Based in part on these observational and interview data we developed and enhanced the content of the GEC sessions. We also developed a comprehension test to evaluate women's understanding of key issues related to informed consent. The key enhancements to the GEC sessions were as follows: • Areas with greater privacy for both group counseling and individual counseling were established. • Posters illustrating the main topics were created and placed in the GEC rooms. • Similar visuals were made into a flipchart and used by the counselor during individual counseling to reinforce the messages. • All visuals developed included substantial input from the counselors. • The visuals were simple, using bold colors and conveying only one message each. • The posters were created to provide informational cues to the counselor to promote and maintain regularity and standardization in presentation. • The counselors completed further training in the use of the visuals. Development of the comprehension test of key informed consent issues Current standards for ethical treatment of human participants in a study do not require that participants demonstrate comprehension of the study prior to giving informed consent. However, given the volume and complexity of information conveyed during the GEC sessions, we felt it necessary to develop a concise yet complete comprehension test that could be used in HIV screening programs and adapted for future clinical trial enrollments. The questionnaire was developed by choosing eight of the 17 questions from the previous questionnaire used during the baseline evaluation. The eight questions were identified by the field team of counselors, physicians, and behavioral scientists as key issues related to informed consent. The questionnaires were administered by the hospital counselor. Adequacy of women's understanding for any topic was determined if the woman correctly answered the question based on pre-determined criteria. If a woman scored adequately on at least 80%, or six out of eight, questions she became eligible to sign the informed consent form and proceed with the HIV screening. Prior to signing the form, the counselor had the opportunity to clarify any previously misunderstood issues with the woman. The eight questions used to assess comprehension of informed consent issues were as follows: 1. What are the modes by which HIV germs are transmitted? 2. Can you say "No" to taking the HIV test? 3. What happens if you decide not to take the HIV test? 4. What do we mean by "the result of the test will be kept confidential"? 5. Do you have the right to consult your husband or other family members before taking the test? 6. What do you think are the benefits of finding out your HIV status? 7. What problems can a woman face on finding out her HIV-positive status? 8. What does your signature on the consent form mean? Post-intervention evaluation After the enhancements to the GEC were put into place and the comprehension test developed, we conducted structured observations of 40 GEC sessions from May-June 2001. We performed the comprehension test on 224 women who attended one of these 40 sessions (89% of the total women attending). These same women were re-interviewed after the completion of individual counseling. The time between the interview after group counseling and the re-interview after individual counseling was, on average, one-two hours. Analysis We compared the adequacy of GEC topic coverage prior to (baseline 30 GEC sessions) and after (40 GEC sessions) the inclusion of the enhancements. Also, improvements in the women's comprehension were assessed through a comparison of their responses to the eight key informed consent questions before GEC enhancements ( N = 136 ) and after ( N = 224 ). In addition, we examined the added improvements in knowledge when the second group of women ( N = 224 ) were tested after their individual counseling. Analysis of the improvements in topic coverage and women's understanding of topics covered was determined by a chi-square test of proportions or Z-scores (for changes in knowledge in the same population) using SPSS version 10 [ 9 ]. This research was approved by the Institutional Review Boards (IRB) at Johns Hopkins University, Baltimore, USA, the local IRBs in Pune, the local medical institutions involved in the research and the National Institutes of Health, USA, which funded this study. Results Coverage of topics in GEC sessions Topics related to informed consent and HIV testing were not well covered during the GEC sessions. Only three topics–availability of a report, the right to say no, and the benefits of screening–were covered in 90% or more of the sessions. The procedural and social risks of HIV screening, the right to consult others, and confidentiality were discussed in less than 10% of the sessions. The impact of refusing to be screened and what a signature means were discussed in 40% and 70% of the sessions, respectively. Coverage of informed consent issues with the use of visuals Focusing only on the eight key issues related to understanding informed consent (see previously listed questions), we compared topic coverage before (Group A) and after (Group B) the improvements were made to the GEC sessions (Table 1 ). With the use of visuals, there were improvements in coverage in nearly all topic areas. The coverage of "the meaning of the signature" increased significantly from 70% to 90% ( P < 0.01 ). Coverage of "social risk" during sessions showed a statistically significant increase from 7% to 23% ( P < 0.05 ), yet the overall coverage was still very low. Similarly, the coverage of "the right to consult others" showed a statistically significant increase ( P < 0.001 ), however, it was still only covered in 35% of the sessions. Non-significant improvements occurred in the area of "consequences of refusal", increasing from 40% to 55%. Overall, the use of visuals resulted in a statistically significant improvement in adequacy of coverage of the counselling sessions from 30% to 68% of all GEC sessions. Women's understanding of informed consent issues with the use of visuals Table 2 shows both women's topic-specific and overall comprehension of informed consent issues. We compare improvements in comprehension in two groups of women, Group A (without use of visual) and Group B (with use of visuals). We then examine improvements in comprehension in the same group of women (Group B), after enhanced group counselling and with the addition of enhanced individual counselling. There was significantly better understanding in three critical areas of appropriate informed consent when visuals were used, namely, "the right to refuse", "consequences of refusal", and "the meaning of the signature." "The right to refuse" rose from 54% at baseline to 79% and 96% ( P < 0.01 ) with enhanced group counseling and enhanced individual counseling, respectively. It should be noted that this topic was well covered in all sessions with or without the addition of visual aids. On the other hand, the discussion of "social risk if found to be HIV-positive" or "the right to consult others" was rarely covered in any of the counseling sessions. In spite of this, a considerable majority of women understood both these issues. Women's understanding of "consequences of refusal" showed marked improvements with use of visuals, rising from 19% at baseline to 75% with enhanced group counselling ( P < 0.01 ) and further to 96% ( P < 0.01 ) with enhanced individual counselling. Overall, based on adequately answering six out of eight questions, women's knowledge of informed consent topics in enhanced group counselling improved dramatically, from 38% to 72% ( P < 0.01 ). With the addition of individual counselling with visuals, women's overall understanding showed a statistically significant increase in all eight aspects of informed consent, and an overall increase from 72% to 96% ( P < 0.01). Conclusions There were two primary objectives of this study. The first was to enhance the communication of key concepts within the HIV/AIDS GEC setting and the second was to develop a simple tool to evaluate women's comprehension of informed consent issues. Many international health education and prevention programs have developed and tested creative and culturally appropriate communication strategies to provide information on issues as sensitive and diverse as family planning and changing defecation behaviors. However, innovation in, and evaluation of, the process of delivering the often complex information necessary for informed consent has been limited [ 10 ]. The use of simplified visuals and text as a means of communicating messages to populations with little or no literacy has commonly been used to convey information on family planning, health, nutrition and public health activities [ 11 , 12 ]. However, such visuals must be developed with the specific population in mind and by community members in order to ensure their positive impact on understanding [ 13 ]. There is very little evidence demonstrating that individuals in resource-poor countries cannot understand the basics of research design or biomedical treatment options just because they have little education or different views about health and illness. It may be difficult to communicate the purposes, conditions and risks of research, but the difficulty of doing so should not detract from the importance of obtaining individual informed consent. In fact, several researchers [ 10 , 14 ] have established that, with some effort, acceptable levels of information can be communicated. This study indicates that the full informed consent process (including both group and individual counselling), when combined with enhanced education and counselling materials, can lead to excellent comprehension of informed consent issues. The dramatic improvement we found in the women's comprehension of informed consent issues, despite their varying socioeconomic and educational backgrounds, is encouraging. Caution should be exercised, however, in interpreting the improvements in comprehension as being a result of the individual counseling and visuals. The second interview was done within one-two hours of the first, and the women may have had time to reconsider their responses to the previous questionnaire. The major limitation in this study was the experimental design, in that we did not have the opportunity to measure the impact of individual counseling without the use of visuals. This was mainly because during baseline data collection we were interested in comprehension immediately after the GEC session; interaction with the counselor for individual counseling directly following the GEC was very brief and, therefore, was not expected to have improved women's knowledge considerably. Moreover, by the time we tested the visuals we had developed, the counselors had gained a lot more experience in HIV counseling and the women might have received more information from various media about HIV. Despite these limitations, we can assert from our data that simple didactic group education on HIV/AIDS and testing issues is not sufficient to help women in this setting to understand the complexities of informed consent for HIV testing. The use of visuals in the form of posters and flipcharts provided structure and uniformity to the GEC sessions, thereby reinforcing the messages for these women and enhancing the overall informed consent process. Obtaining proper informed consent in the case of HIV screening is not a discrete action, but a process that can be enhanced through effective communication, repetition and reflection. Although the intent is to increase knowledge, information regarding informed consent may lose its meaning when administered within certain populations. The time and the technicalities of the process itself may intimidate women in societies where literacy and awareness about medical and legal rights is low. It has been argued that complicated concepts conveyed in a consent form, often to fulfill the requirements of funding agency for institutional and policy purposes, may in themselves be unethical and, indeed, pose the biggest barrier to the informed consent process [ 15 ]. It should also be recognized that implementing counseling and informed consent procedures is considerably more difficult in certain settings in India where facilities, supplies, personnel, and time are at a premium. In addition, educational levels for women in this population are low, where 36% have a primary school education or less and another 33% are illiterate [ 16 ]. Generally, for HIV screening, an individual reads or is read a prepared statement that includes detailed scientific and legal information on the aims and biological significance of the test, the risks and benefits of testing, and the individual's rights. The participant is expected to understand the main components of what is written within the document and make an autonomous decision on whether or not to be tested for HIV. This is further complicated by the fact that, in some studies, the original consent document is composed in English and then translated nearly verbatim into the local language, making the communication of already complex topics even more difficult. Typically, informed consent for pregnant women in most Indian hospitals and clinics is for operative procedures such as cesarean section or laparotomy. It is usual for the doctor or resident on duty to put down in his or her own handwriting the text of the consent on a patient's case papers. The content of this consent gives blanket permission to the hospital and doctors to undertake all procedures on the patient that are indicated in order to maintain the good health of the mother and her fetus, while at the same time absolving the attending physician and hospital of any blame in the event of a mishap. This is signed (or a thumbprint given) by the patient, her husband or an accompanying relative, and is generally considered to serve as legal consent; therefore, it is not interpreted as voluntary. Most often, due to time constraints, very little is explained to the patient about the procedure, risks, and benefits, or what her signature actually means. As found in other regions in India, there is a general perception by clinicians and other healthcare workers that women are "unable" to understand any of the procedures even if explained, because they are illiterate or have no medical background [ 17 , 18 ]. It is implicit in the physician-patient relationship that any treatment or procedures recommended by the physician will benefit the patient [ 19 - 21 ]. By de-mystifying the content and process of informed consent through standardization with structured visual cues and reiteration, we feel that these difficulties could be overcome. In creating the modifications to the GEC, we focused on improving communication of those concepts that were the most unfamiliar to these women. For example, for most women in India, there is relatively little sense of autonomy [ 22 ]. For many, the woman's role is defined first by her father; after marriage, her husband's decision-making and the wishes of his parents or the elders in his home prevails. For such a woman, when an incurable disease like HIV/AIDS is presented to her in terms of her "autonomy" and "power" with reference to the disease, this could be confusing and even frightening. The prevailing practice of obtaining familial input on such decisions was demonstrated through women's knowledge of this topic despite the fact that it was hardly mentioned during the counseling sessions. On the other hand, our data show that by enhancing the GEC and reinforcing its messages through individual counseling, a significantly greater number of women can correctly understand the idea of their "right to refuse", indicating that even complex constructs such as autonomy can be conveyed. The understanding of the "meaning of the signature" was clearly enhanced with the use of visuals, because the improvements in women's knowledge directly followed the increase in coverage during the counseling sessions. Clearly, some of the concepts related to informed consent may already be understood by these women. Women's understanding of "consequences of refusal" showed marked improvements in the second group of women studied. Although some of this improvement may be attributed to the individual counselling and visuals, the fact that only 55% of the GEC sessions actually adequately covered this topic indicates that other factors may have contributed to the women's knowledge of this topic. This process of refining and evaluating the informed consent process can benefit the clinic and research settings in both developed and developing countries. Data from clinics in the USA, Belgium, and France report that even under well suited environments, informed consent for HIV screening was generally only obtained in about 70–85% of cases, and documentation of consent was substantially less [ 23 , 24 ]. In research settings, studies suggest that, despite having signed a consent form, participants may not fully understand critical aspects of research participation or their individual rights [ 25 , 26 ]. We have modified the standard model of informed consent by adapting it to suit the population that was served, and have documented subsequent improvements in patient understanding of the informed consent process. This study shows that culturally appropriate enhancement of the standard informed consent process moves the process towards its goal of being one that is truly informed and voluntary. Thus it not only fulfills the ethical requirements, but, most importantly, helps to assure that women's rights are preserved. This last point is critical because previous research has pointed out that, although women may be fully informed, they still may not feel their choice is fully voluntary [ 14 ]. We suggest that the current requirements of informed consent procedures are inadequate and that it should be a process that communicates information in an effective manner, allows for reiteration of information and includes an evaluation of the woman's knowledge prior to signing the informed consent document. In an effort to allow all interested organizations involved in HIV counseling and testing to use or modify our visuals for their own programs, we are have created a downloadable version available for public access at our website . It is hoped that these types of visuals will become an integral part of all voluntary counseling and testing programs throughout India and elsewhere. Competing interests None declared. Author's contributions JS was involved in developing the research and visuals, implementing the study and preparing the manuscript. HP participated in the design of the visuals and in the analysis and coordination of the study. SS and AJ were involved in data collection and analysis. NK-K participated in the design of the visuals and in the analysis of the study. NS participated in the design of the study and the visuals. KEB, AS and MAP participated in the design and assisted in the implementation of the study. RCB assisted in all aspects of the study design and implementation. AVS participated in the design, conducted the analysis and wrote the manuscript. 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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300881

JAMM: A Metalloprotease-Like Zinc Site in the Proteasome and Signalosome

The JAMM (JAB1/MPN/Mov34 metalloenzyme) motif in Rpn11 and Csn5 underlies isopeptidase activities intrinsic to the proteasome and signalosome, respectively. We show here that the archaebacterial protein AfJAMM possesses the key features of a zinc metalloprotease, yet with a distinct fold. The histidine and aspartic acid of the conserved EX n HS/THX 7 SXXD motif coordinate a zinc, whereas the glutamic acid hydrogen-bonds an aqua ligand. By analogy to the active site of thermolysin, we predict that the glutamic acid serves as an acid-base catalyst and the second serine stabilizes a tetrahedral intermediate. Mutagenesis of Csn5 confirms these residues are required for Nedd8 isopeptidase activity. The active site-like architecture specified by the JAMM motif motivates structure-based approaches to the study of JAMM domain proteins and the development of therapeutic proteasome and signalosome inhibitors.

Introduction Many cellular proteins are degraded by the proteasome after they become covalently modified with a multiubiquitin chain. The 26S proteasome is a massive protein composed of a 20S core and two 19S regulatory particles ( Voges et al. 1999 ). The 20S core can be subdivided into a dimer of heptameric rings of β subunits—which contain the proteolytic active sites responsible for the protein degradation activity of the proteasome—flanked by heptameric rings of α subunits. The 19S regulatory particle can be divided into a base thought to comprise a hexameric ring of AAA ATPases and a lid composed of eight or more distinct subunits. Whereas 20S core particles and AAA ATPase rings have been found in compartmentalized proteases in prokaryotes, the lid domain of the 19S regulatory particle is unique to eukaryotes and provides the specificity of 26S proteasomes for ubiquitinated substrates ( Glickman et al. 1998 ). Ubiquitin (Ub), an 8 kD protein, is conjugated by Ub ligases to proteasome substrates via an isopeptide bond that links its carboxyl terminus to the amino sidechain of a lysine residue in the substrate. Ub-like proteins (Ubls), of which there are several, are conjugated to their target proteins in a similar manner. Ubls typically do not promote degradation of their targets by the proteasome, but rather regulate target activity in a more subtle manner reminiscent of protein phosphorylation ( Hershko and Ciechanover 1998 ; Peters et al. 1998 ). As is the case for protein phosphorylation, the attachment of Ub and Ubls to target proteins is opposed by isopeptidase enzymes that undo the handiwork of Ub ligases. For example, removal of the Ubl Nedd8 (neural precursor cell expressed, developmentally downregulated 8) regulatory modification from the Cullin 1 (Cul1) subunit of the SCF (Skp1/Cdc53/Cullin/F-box receptor) Ub ligase is catalyzed by the COP9 signalosome (CSN) ( Lyapina et al. 2001 ). The CSN was identified in Arabidopsis thaliana from genetic studies of constitutively photomorphogenic mutant plants ( Osterlund et al. 1999 ). It later became evident that CSN and the proteasome lid are paralogous complexes ( Glickman et al. 1998 ; Seeger et al. 1998 ; Wei et al. 1998 ). Csn5 of CSN and Rpn11 (regulatory particle number 11) of the proteasome lid are the subunits that are most closely related between the two complexes. CSN-dependent isopeptidase activity is sensitive to metal ion chelators, and Csn5 contains a conserved, putative metal-binding motif (EX n HS/THX 7 SXXD), referred to as the JAMM motif, that is embedded within the larger JAB1/MPN/Mov34 domain (hereafter referred to as the JAMM domain) and is critical for Csn5 function in vivo ( Cope et al. 2002 ). Removal of Ub from proteasome substrates is also promoted by a metal ion-dependent isopeptidase activity associated with the proteasome ( Verma et al. 2002 ; Yao and Cohen 2002 ). The JAMM/MPN + motif of Rpn11 is critical for its function in vivo ( Maytal-Kivity et al. 2002 ; Verma et al. 2002 ; Yao and Cohen 2002 ), and proteasomes that contain Rpn11 bearing a mutated JAMM motif are unable to promote deubiquitination and degradation of the proteasome substrate Sic1 ( Verma et al. 2002 ). Taken together, these observations suggested that the JAMM motif specifies a catalytic center that in turn defines a novel family of metalloisopeptidases. Interestingly, the JAMM motif is found in proteins from all three domains of life ( Cope et al. 2002 ; Maytal-Kivity et al. 2002 ), indicating that it has functions beyond the Ub system. In this study, we present the crystal structure of the Archaeoglobus fulgidus AF2198 gene product AfJAMM and explore the implications of its novel metalloprotease architecture. Results and Discussion We proposed that the subset of JAMM domain proteins that contain a JAMM motif comprise a novel family of metallopeptidases ( Cope et al. 2002 ). To gain a clearer understanding of these putative enzymes—in particular the pertinent subunits of the proteasome lid and signalosome ( Figure 1 )—we cloned and expressed in Escherichia coli a variety of JAMM motif-containing proteins to find a suitable candidate for crystallographic analysis. The expression of all candidates except for AfJAMM led to insoluble aggregates. Unlike many JAMM proteins that contain an additional domain, the AfJAMM protein consists entirely of the JAMM domain. We were able to purify and crystallize native and selenomethionine-substituted AfJAMM; the latter was used for phasing by employing the multiwavelength anomalous diffraction (MAD) technique (see Table 1 for statistics). Figure 1 Alignment of Eukaryotic JAMM Domains with AfJAMM Eukaryotic JAMM domain proteins were aligned with AfJAMM using ClustalX and manually refined. Sequences are named with a two-letter code corresponding to the genus and species of the respective organism followed by the name of the protein (see Supporting Information for accession numbers), and ‘hyp’ is an abbreviation for hypothetical. The JAMM motif comprises the residues highlighted in green (E22, H67, H69, S77, and D80), and the active site core is surrounded by a red box. Conserved residues are highlighted in gray. The disulfide cysteine residues are highlighted in yellow (C74, C95). Active site residues that were mutated in S. pombe Csn5 are marked with an asterisk beneath the alignment. The secondary structure of AfJAMM is indicated above the sequence; helices are blue, sheets are red arrows, and loops are yellow lines. The dashed yellow line indicates a loop (F42–G58) that is disordered in the crystal. Table 1 Data Collection Statistics a Owing to pseudocentering, reflections with l values such that cos 2 (0.54πl) < ½ are systematically weak, leading to an R-factor higher than would be expected for a nonpseudocentered crystal structure. R N are the R-factors calculated with only the reflections with cos 2 (0.54πl) > ½ (see Materials and Methods). Barring rearrangements of sidechains in the vicinity of the zinc atom, no significant changes were seen between the native and selenomethionine forms AfJAMM consists of an eight-stranded β sheet (β1–β8), flanked by a long α helix (α1) between the first and second strand, and a short α helix (α2) between the fourth and fifth strand. This β sheet resembles a β barrel halved longitudinally and curled around α1 ( Figure 2 A). The α2 helix is oriented lengthwise on the convex surface of the β sheet. The zinc-binding site is adjacent to a loop that spans the end of β4 to the beginning of α2 and is stabilized by a disulfide bond between C74 from this loop to C95 on β5. Although disulfide bonds are scarce in intracellular proteins, they are often present in homologous proteins found in hyperthermophiles ( Mallick et al. 2002 ). The overall fold resembles that of the zinc metalloenzyme cytidine deaminase (CDA). CDA from Bacillus subtilis ( Johansson et al. 2002 ) can be superimposed onto AfJAMM with a root-mean squared (RMS) deviation of 3.0 Å over 79 α carbons, despite only 9% sequence identity over structurally aligned residues. The catalytic zinc ions of AfJAMM and CDA, 4.9 Å apart in the superposition, occupy the same general vicinity in the tertiary structures but are coordinated by entirely different protein ligands, two histidines and an aspartic acid in AfJAMM compared to three cysteines in CDA, located at different positions in the sequence ( Figure 2 A). Consequently, the JAMM fold represents a departure from the papain-like cysteine protease architecture that underlies the deubiquitinating activity of the most thoroughly characterized deubiquitinating enzymes (DUBs), the Ub carboxy-terminal hydrolases (UCHs) ( Johnston et al. 1997 ) and Ub-specific proteases (UBPs) ( Hu et al. 2002 ). Figure 2 Crystal Structure of AfJAMM (A) On the left, the AfJAMM protomer is presented. The amino and carboxyl termini are marked by N and C. The catalytic zinc atom is depicted as a gray sphere. The zinc ligands (H67, H69, and D80) are colored in green. Secondary structure elements are numbered α1–α2 and β1–β8. The amino acids that mark the beginning and end of the disordered loop (P41–M60) are labeled. On the right, the crystal structure of the cytidine deaminase protomer is shown in the same orientation as AfJAMM to highlight the fold likeness as well as the similarly situated zinc-binding sites. The zinc ligands (C53, C86, and C89) are colored in green. (B) The dimer in the asymmetric unit of AfJAMM crystals. The side view is obtained by rotating the monomer in (A) by 90° as indicated by the quarter-arrow around the y-axis. The gold protomer is related to the green protomer by a 180° rotation around the crystallographic c-axis (shown as a black bar in the side view) and a translation of 3.38 Å. The two AfJAMM subunits in the asymmetric unit are connected through a parallel β sheet formed at the dimer interface ( Figure 2 B). The subunits are related by a 2-fold screw axis along the crystallographic c-axis with a translation of 3.38 Å, corresponding to a displacement of one residue along the β3 strand. AfJAMM behaves as a monomer during size exclusion chromatography, suggesting that the dimer observed in the asymmetric unit is an artifact of crystallization. Yet the residues of β3 are highly conserved among JAMM proteins (see Figure 1 ) and predominantly hydrophobic, which makes it difficult to regard the observed interaction as completely insignificant. Flanking β3 to the carboxy-terminal side, there is a striking covariation of residues, MPQSGTG in Rpn11 orthologues and LPVEGTE in Csn5 orthologues. The potential of β3 and the flanking region to mediate specific protein–protein interactions, such as the assembly of Rpn11 and Csn5 into their respective complexes or their specificity towards Ub or Nedd8, warrants further investigation. The zinc-binding site of AfJAMM is located in a furrow formed by the convex surface of the β2–β4 sheet and α2. The catalytic zinc has a tetrahedral coordination sphere ( Figure 3 A), with ligands provided by N ɛ2 of H67 and H69 on β4, the carboxylate of D80 on α2, and a water molecule. The latter hydrogen-bonds to the sidechain of E22 on β2. Thus, the crystal structure confirms previous predictions that the histidine and aspartic acid residues in the JAMM motif are ligands for a metal ( Cope et al. 2002 ; Verma et al. 2002 ; Yao and Cohen 2002 ). It must be noted that the identity of the physiological metal in AfJAMM and eukaryotic JAMM homologues is still unknown. The majority of metalloproteases naturally employ zinc but show altered activities with other substituted metals ( Auld 1995 ). Figure 3 Metalloprotease-Like Active Site of AfJAMM (A) The active site of AfJAMM is shown centered around the catalytic zinc ion, which is represented as a dark gray sphere surrounded by anomalous cross Fourier difference density (contoured at 9.5 σ) colored in red. The aqua ligand, which lies at 2.9 Å from the zinc, is shown as a red sphere surrounded by purple density (contoured at 3 σ) of an F obs – F calc map, in which the aqua ligand was omitted from the calculation. Residues that underlie isopeptide bond cleavage are shown in green. The carboxylate oxygen atoms of D80 lie 2.2 Å from the zinc. The N ɛ2 atoms of H67 and H69 lie 2.1 Å from the zinc. The carboxylate oxygen atoms of E22 lie 3.2–3.5 Å from the aqua ligand and 4.5–5.0 Å from the zinc. Ancillary active site residues and the backbone (ribbon diagram) are shown in grey. The disulfide bond that links C74 to C95 is shown in yellow. The JAMM motif is shown in the upper lefthand corner for reference. (B) Superimposition of active site residues in ScNP, thermolysin, and AfJAMM. AfJAMM is in green, ScNP in blue, and thermolysin in red. For clarity only, the sidechains from the residues that bind the zinc or aqua ligands are shown in their entirety. In addition, atoms that stabilize the putative tetrahedral intermediate are shown. These include O γ of S77 in AfJAMM, O η of Y95 in ScNP, and the N ɛ2 of H231 in thermolysin. The arrangement of zinc ligands in AfJAMM resembles that found in thermolysin, the Streptomyces caespitosus zinc endoprotease (ScNP), and neurolysin, a mammalian metalloprotease ( Kurisu et al. 2000 ; Brown et al. 2001 ; English et al. 2001 ). Thermolysin, neurolysin, and ScNP are homologues that have the classical HEXXH metalloprotease motif and adopt the same core fold. In contrast, the sequence, zinc-binding motif, and fold adopted by AfJAMM are entirely distinct. Nonetheless, the active site metal and ligand atoms of thermolysin and ScNP can be superimposed on those of AfJAMM with an RMS deviation of approximately 0.4–0.5 Å ( Figure 3 B). While this manuscript was under revision, an independent report of a crystal structure of the AF2198 gene product appeared ( Tran et al. 2003 ). These authors used the fold similarity to CDA as a framework to evaluate the function of the JAMM motif. Given the biochemical data supporting the JAMM motif's role in proteolysis, the common active site architecture seen in AfJAMM and thermolysin, and the similarity of zinc ligands between thermolysin and AfJAMM, we believe that the extensive body of mechanistic studies on thermolysin and related metalloproteases provide a better framework for the analysis of JAMM function than CDA. In addition to the correspondence between zinc ligands, the glutamic acid residue (E166) downstream of the HEXXH motif of thermolysin is functionally equivalent to the aspartic acid ligand of AfJAMM (D80). E22 in AfJAMM is functionally equivalent to the glutamic acid in thermolysin's HEXXH motif, which serves as the general acid-base catalyst. The conserved serine between the histidine ligands interacts with E22 through a sidechain–main chain hydrogen bond. In more distant JAMM relatives, the serine is replaced by a threonine or asparagine ( Aravind and Ponting 1998 ), both of which are capable of the same bracing function. Meanwhile, the γ-hydroxyl group of the highly conserved S77 in AfJAMM occupies a position similar to N ɛ2 of H231 in thermolysin. This atom flanks the ‘oxyanion hole’ and is implicated in stabilizing the tetrahedral intermediate formed during hydrolysis of the scissile bond ( Matthews 1988 ; Lipscomb and Strater 1996 ). AfJAMM was tested for the ability to hydrolyze a number of substrates, including Ub derivatives, resofurin-labeled casein, and D-alanine compounds. Unfortunately, none of the in vitro assays yielded positive results. As nothing is known about AfJAMM in the context of A. fulgidus biology, these negative results do not rule out the possibility that AfJAMM functions as a peptide hydrolase in vivo. To validate the suitability of the AfJAMM structure as a basic model for eukaryotic JAMM proteins, we performed site-directed mutagenesis of Schizosaccharomyces pombe csn5 + . The zinc ligands of Csn5 were previously established to be essential for its role in sustaining cleavage of the isopeptide bond that links Nedd8 to Cul1 ( Cope et al. 2002 ). Alanine substitutions for the putative general acid-base catalyst (E56A) and the catalytic serine (S128) in the JAMM motif of Csn5 likewise abolished its ability to remove the Nedd8 moiety from Cul1 in a csn5 + background ( Figure 4 A). The E56A mutation had no effect on the assembly of Csn5 with Csn1 myc13 , while assembly with S128A was slightly hindered ( Figure 4 A). Mutation of the equivalent serine codon in RPN11 destroyed complementing activity without altering assembly of Rpn11 into the lid. However, the effect of this mutation on Rpn11 isopeptidase activity was not evaluated ( Maytal-Kivity et al. 2002 ). Alanine substitutions for a catalytic residue (E56) or zinc ligands (H118A, D131N) exerted a modest dominant-negative phenotype in csn5 + cells ( Figure 4 B). Figure 4 Mutations in the JAMM Motif of Csn5 Abrogate the Deneddylating Activity of the CSN (A) Mutations in the glutamic acid (E56A) that positions the aqua ligand and in the proposed catalytic serine (S128A) of Csn5 disrupt deneddylation of Cul1 by CSN but have no effect on assembly with Csn1. A csn5Δ strain of S. pombe was transformed with an empty pREP-41 plasmid (lane 1) or with the plasmid encoding FLAG tagged: Csn5 (lane 2), Csn5 E56A (lane 3), or Csn5 S128A (lane 4). Whole-cell lysates were used for Western blot analysis with anti-Cul1 antibodies (top gel) and anti-FLAG antibodies (second from top). A strain with a myc13 -tagged Csn1 was transformed with the above plasmids, and whole-cell lysates were used for Western blot analysis. Antibodies to the Myc tag were used to detect Csn1 myc13 (third from top), and were used to pull down Csn1 myc13 and subsequently blot with anti-FLAG antibodies to detect coprecipitated Csn5 mutant proteins (bottom gel). (B) Mutations in the JAMM motif display a modest dominant-negative phenotype. Western blot analysis of crude cell lysates was performed as described in (A). (C) Selected JAMM motifs from proteins of diverse functions. The canonical JAMM motif residues are highlighted in green. The conserved proline is highlighted in blue, and semiconserved cysteine is highlighted in yellow. We have been able to assign biochemical functions to Csn5 and Rpn11 ( Cope et al. 2002 ; Verma et al. 2002 ; Yao and Cohen 2002 ), but the functions of other eukaryotic JAMM proteins ( Figure 4 C) such as AMSH and C6.1A, as well as the prokaryotic protein RadC and the viral phage λ tail assembly protein K, remain unknown. The structure of AfJAMM provides a useful tool for dissecting the functions of JAMM motifs in these varied contexts and inspires the search for specific JAMM active site inhibitors. The mechanistic implications of the AfJAMM structure explain why the deubiquitinating activity of the lid was unaffected by inhibitors of classical DUBs, the UCHs and UBPs. In classical DUBs, the nucleophile that attacks the carbon of the scissile bond is provided by a cysteine residue in the active site. This property is exploited by using the irreversible inhibitor Ub–aldehyde, which forms a nonhydrolyzable bond to the nucleophilic cysteine ( Johnston et al. 1999 ). In contrast, JAMM proteins likely hydrolyze Ub conjugates in a manner similar to thermolysin, in which the zinc-polarized aqua ligand serves as the nucleophile ( Lipscomb and Strater 1996 ). In the case of thermolysin, metal chelators and phosphonamidate peptides are effective inhibitors ( Bartlett and Marlowe 1987 ), whereas other zinc metalloproteases are sensitive to peptidomimetic substrates bearing a hydroxamate group ( Skiles et al. 2001 ). Metal chelators have been shown to be effective inhibitors of JAMM proteins ( Cope et al. 2002 ; Verma et al. 2002 ); it would be interesting to see whether phosphonamidate and hydroxamate peptide mimics of Ub conjugate isopeptides would be equally effective. The proteasome inhibitor PS-341 has gained attention for its novelty and effectiveness in treating various forms of cancer ( Adams 2002 ). PS-341 was recently approved by the United States' Food and Drug Administration for treatment of relapsed multiple myeloma, thereby validating the proteasome as a target for anticancer therapies. The active site of JAMM proteins is an intriguing target for second-generation therapeutics targeted at the Ub–proteasome pathway for two reasons: the JAMM motif in the proteasome lid is essential for the proteasome to function and the JAMM motif in the CSN specifically regulates the activity of a critical family of E3 Ub ligases ( Nalepa and Harper 2003 ). Inhibition of SCF and other Cullin-based ligases by way of the JAMM motif may be a more specific means of modulating levels of key proteasome substrates in cancer cells. Materials and Methods The gene for A. fulgidus JAMM ( Ponting et al. 1999 ), open reading frame AF2198 , was cloned from genomic DNA (ATCC #49558D; American Type Culture Collection, Manassas, Virginia, United States) into the pCRT7 vectors (Invitrogen, Carlsbad, California, United States). During cloning, the alternate start codon, GTG, was replaced with the canonical start codon, ATG. The construct was expressed in BL21(DE3)pLysS cells (Novagen, Madison, Wisconsin, United States). The cells were grown to midlog phase in terrific broth media and induced with 0.5 mM IPTG. The cells were lysed by sonication and the protein was isolated by immobilized metal ion chromatography using a Ni-NTA resin (Qiagen, Valencia, California, United States). The protein was further purified by gel filtration on a Sephacryl S100 column (Amersham Pharmacia Biotech, Chalfont St Giles, United Kingdom) and concentrated. The amino-terminal tag was removed by limited digestion with trypsin. Mass spectrometry analysis revealed that trypsin only cut AfJAMM in the amino-terminal tag region, and only a single band was evident on a Coomassie-stained polyacrylamide gel. The tag and uncut protein were removed with Ni-NTA resin followed by anion-exchange chromatography with SOURCE 30Q resin (Amersham Pharmacia Biotech). The processed protein was then concentrated to approximately 30 mg/ml by ultrafiltration. The selenomethionine protein was produced as described elsewhere ( Van Duyne et al. 1993 ) and purified using the same protocol as for the native protein. Protein crystals were obtained in 100 mM NH 4 H 2 PO 4 , 200 mM sodium citrate (pH 5) using vapor diffusion with sitting drops and hanging drops. Crystals were incubated for approximately 1 min in a cryo-solution of equal volumes of reservoir solution and 35% meso-erythritol for the selenomethionine crystals and supplemented with 5 mM ZnCl 2 for the native crystals. The crystals belonged to the space group P6 5 , with cell dimensions of a = b = 76 Å, c = 94 Å and two subunits per asymmetric unit. Data for the selenomethionine crystals were collected on Beamline 9.2 at the Stanford Synchrotron Radiation Laboratory (SSRL) (Stanford, California, United States) and data for the native crystals were collected on Beamline 8.2.1 at the Advanced Light Source (ALS) (Lawrence Berkeley National Laboratory, Berkeley, California, United States) (see Table 1 ). Phases were obtained by the MAD technique using data collected from selenomethionine-substituted crystals (see Table 1 ). Three Se atoms were located by SOLVE ( Terwilliger and Berendzen 1999 ) and used to calculate the initial phases. Phasing was subsequently improved by noncrystallographic symmetry averaging, using operators derived from the Se positions, and solvent flattening in RESOLVE ( Terwilliger 2000 ). The polypeptide model was built in O ( Jones et al. 1991 ) and refined with CNS ( Brünger et al. 1998 ). Since two monomers in the unit cell are related by a fractional translation along c of approximately 0.54, the intensities of the diffraction pattern are modulated by a factor of cos 2 (0.54πl). As a result, reflections with l-indices such that cos 2 (0.54πl) < ½ are systematically weak, leading to an R-factor higher than would be expected for a nonpseudocentered crystal structure. However, when only the reflections with cos 2 (0.54πl) > ½ (which will have a more normal intensity distribution) are used for the R-factor calculation, reasonable values for R are obtained. The geometry of the final model was analyzed with PROCHECK ( Morris et al. 1992 ). The Ramachandran plot shows 98.9% of the residues in the allowed regions and 1.1% in the disallowed regions. The main chain of K66, which constitutes the residue in the disallowed region, was modeled on segments taken from well-refined, high-resolution structures. The Protein Data Bank was searched for structural neighbors of AfJAMM using the DALI server ( Holm and Sander 1993 ). The superpositions with cytidine deaminase (1JTK), thermolysin (1FJQ), and ScNP (1C7K) were done using the LSQKAB program of the CCP4 distribution (CCP4 1994). All structural figures were made with PyMOL ( DeLano 2000 ).The experiments with S. pombe were performed as previously described by Cope et al. (2002 ). Supporting Information Accession Numbers The accession numbers for the proteins discussed in this paper are 20S proteasomes (PDB ID 1RYP), AfJAMM (Entrez Protein ID NP_071023; PDB ID 1R5X), AMSH (Entrez Protein ID NP_006454), AtCSN5/AJH1 (Entrez Protein ID NP_173705), AtRpn11 (Entrez Protein ID NP_197745), C6.1A (Entrez Protein ID NP_077308), CeCSN5 (Entrez Protein ID NP_500841), CeRpn11 (Entrez Protein ID NP_494712), Csn5 (Entrez Protein ID NP_593131), Cul1 (Entrez Protein ID NP_594259), cytidine deaminase (PDB ID 1JTK), DmCsn5/CH5 (Entrez Protein ID NP_477442), DmRpn11/p37b (Entrez Protein ID AAF08394), EcRadC (Entrez Protein ID NP_418095), HsAMSH (Entrez Protein ID NP_006454), HsC6.1A (Entrez Protein ID NP_077308), HsCsn5 (Entrez Protein ID NP_006828), HsRpn11/POH1 (Entrez Protein ID NP_005796), JAB1 (Entrez Protein ID AAC17179), lambdaK (Entrez Protein ID AAA96551), Mov34 (Entrez Protein ID NP_034947), Mpr1p (Entrez Protein ID AAN77865), Nedd8 (Swiss-Prot ID Q15843), neurolysin (PDB ID 1I1I), Pad1p (Entrez Protein ID NP_594014), phage λ tail assembly protein K (Entrez Protein ID AAA96551), RadC (Entrez Protein ID NP_418095), Rpn11 (Entrez Protein ID AAN77865), SCF (PDB ID 1LDK), ScNP (PDB ID 1C7K), ScRpn11 (Entrez Protein ID AAN77865), Sic1 (Entrez Protein ID 1360441), SpCsn5 (Entrez Protein ID NP_593131), SpRpn11/Pad1 (Entrez Protein ID NP_594014), thermolysin (PDB ID 1FJQ), ubiquitin (Swiss-Prot ID P04838), UBP (PDB ID 1NB8), and UCH (PDB ID 1UCH). These databases may be found at http://www.ncbi.nlm.nih.gov/entrez/ (Entrez Protein), http://www.rcsb.org/pdb/ (Protein Data Bank [PDB]), and http://us.expasy.org/sprot/ (Swiss-Prot).

/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC300881.xml

545604

A genome annotation-driven approach to cloning the human ORFeome

Using a new systematic approach to generating cDNA clones containing full-length open reading frames, clones representing 70% of genes on human chromosome 22 were obtained.

Background Many methods for high-throughput, experimental elucidation of gene function (functional genomics) depend on the availability of full-length cDNA clone collections [ 1 ]. These clones provide access to the protein-coding open reading frames (ORFs) and facilitate expression of large numbers of proteins in the native form or as fusion proteins. The value of ORF-containing full-length cDNA clone collections (ORF clones) has now been amply demonstrated by studies in model organisms, in particular in the area of protein interaction mapping using methods based on yeast two-hybrid or mass spectrometry [ 2 - 8 ]. Extension of functional genomic approaches to mammalian genomes requires development of adequate ORF clone collections. Several projects based on complete sequencing of clones isolated from cDNA libraries are in place to generate these collections for mouse [ 9 ] and human [ 10 - 13 ]. Additional efforts have also focused on subsequent manipulation and exploitation of the full-length clones using versatile recombinational cloning systems so that the ORFs are formatted for expression [ 14 - 16 ]. However, obtaining a complete set of human clones has been hampered by the inadequacies of cDNA libraries and uncertainty over the true number and identity of all protein-coding genes. Approaches based on cDNA libraries have two major limitations in mammals. The first is the difficulty in obtaining full-length cDNA clones and the complexities of alternate and partial splice forms. Hence, many clones have to be sampled to obtain a canonical full-length version of each cDNA. The second is that these projects inevitably reach a point of diminishing return when it is no longer financially viable to continue to sequence more clones from the same library or from different tissues in order to add small numbers of new full-length cDNAs to the collection. Therefore, it is pertinent to ask how complete the cDNA collections currently are, and whether they can be supplemented or replaced by other approaches in order to develop complete ORF clone sets. There is still uncertainty over the exact number of human and mouse genes and hence over the completeness of the existing cDNA collections. Therefore, we have investigated a defined subset of genes, namely the full-length protein-coding genes defined in our current annotation of human chromosome 22 [ 17 ]. In this study, we have found that in the currently available major cDNA collections, a total of 60% of chromosome 22 protein-coding genes are represented by complete ORF clones, although no single collection contains more than 48% (Table 1 ). This leaves a sizeable fraction of the genes unavailable. Thus there are still considerable challenges to be faced in identifying and isolating full-length cDNAs and ORFs for functional analyses. To extend the coverage of full-length ORF clones, we have developed an alternative method which exploits knowledge of gene structure based on genomic sequence. It involves the specific amplification of a targeted ORF plus short regions of the 5' and 3' untranslated regions from a mixed pool of cDNAs. Amplified fragments are cloned into a standard plasmid sequencing vector and their identity and integrity confirmed by DNA sequencing. The aim of the method is to provide cDNA clones containing confirmed full-length ORFs, which can later be manipulated into suitable vector systems such as Gateway (Invitrogen) or Creator (BD Biosciences) for functional genomics. We have applied this method to the same set of chromosome 22 protein-coding genes and have shown that we can obtain clones representing 70% of the targeted genes with a limited range of experimental conditions. We have also demonstrated a reasonable expectation that we can isolate clones for 83%. Results and discussion Analysis of full-length cDNA collections We have previously described a gene annotation of chromosome 22 [ 17 ] and its characterization [ 18 ]. In this annotation, 546 genes were defined as protein-coding genes, 387 being full length and the remainder (159) being partial, mostly as a result of unconfirmed 5' ends, incomplete genomic sequence or partial gene duplication events. We subsequently identified and removed two full-length genes which we now consider to be antisense transcripts and have extended 13 genes to full length to give a total of 398 full-length protein-coding genes (see [ 19 ] for details of the chromosome 22 ORFs). In the other cases of partial annotations we have not been able to extend the annotation sufficiently to allow identification of a complete ORF suitable for cloning. Therefore, for the purposes of this paper, where the aim is to identify clones containing complete ORFs, we only consider genes annotated as full-length protein coding as targets because of the difficulty of defining success for the partial genes. We first considered the completeness of available full-length human cDNA collections, by comparing the DNA sequences of available cDNA library clones with our targeted set of 398 ORFs. For this analysis we used cDNA sequences downloaded from the major collections in January 2004. The publicly available cDNA collections analyzed were those from the Mammalian Gene Collection (MGC) [ 11 ], the full-length long Japan collection (FLJ) [ 12 ], the German cDNA Consortium (DKFZ) [ 10 ] and the Kazusa cDNA project (KIAA) [ 13 ]. In addition, we analyzed a commercially available set of cDNAs from Invitrogen. We aligned each of our target chromosome 22 ORFs to the available cDNA sequences to assess whether clones representing the entirety or any part of each of the chromosome 22 ORFs existed in each collection (Table 1 , and see Materials and methods). This analysis showed that 240 out of 398 ORFs (60%) were represented by a cDNA clone with more than 95% identity over the full length of the ORF in at least one of the collections. In addition, a further 25 ORFs were covered by cDNA clones with gapped matches. However, only 227 (57% of the total ORFs) of these clones maintain the correct reading frame at the amino acid level. Examining the matches from individual cDNA clone collection showed that 80% of the full-length matches were provided by the MGC. This probably reflects the selection process in this program whereby initial sequencing of the ends of cDNA clones was used to select the optimal clone for complete sequencing. The KIAA collection provided full-length matches at approximately the same rate as the MGC, given the number of sequences available (1.25% chromosome 22 full-length matches out of the total MGC collection compared with 1.38% for KIAA) and notably provided the five largest clones matched that maintained the complete ORF (sizes between 4,719 base-pairs (bp) and 3,516 bp), reflecting the emphasis on long clones in the KIAA program. The FLJ and DKFZ collections gave rates of 0.28% and 0.27% respectively, presumably because a smaller proportion of full-length clones were sequenced. Analysis of the chromosome 22 genes from these collections shows that length, but not GC content, of the ORF is a significant factor in cloning success for these collections (Mann Whitney test, p < 0.0007), that is, there is bias against longer ORF clones. In summary, there is currently a 60% chance of obtaining a full-length cDNA clone from one of these collections, based on a sample of 1% of the human genome. The best single collection (MGC) provides 48% of the clones. This analysis of coverage, based on the subset of full-length protein-coding genes on chromosome 22, mimics the situation occurring in a positional cloning type strategy where one might want to obtain clones for a region identified by genetic mapping. However, it does not assess whether the collections are enriched or depleted for specific classes of gene by function, tissue distribution or level of expression. As chromosome 22 is particularly GC-rich, and compared to other human chromosomes the set of genes we have used for this assessment may be biased towards housekeeping genes with widespread or ubiquitous expression which are known to be enriched in GC-rich regions of the genome. Hence, results for specific classes of genes will differ. In any case, one can expect to obtain roughly half of the clones required from one of these collections. This is testimony to the considerable effort that has gone into constructing the resources, but is also frustrating, because other sources are required to make up the substantial remainder. To investigate whether other approaches could be used to address the completeness of cDNA clone resources, we developed an alternative method which is complimentary to cDNA library sequencing, and tested this approach on the same set of chromosome 22 ORFs. Strategy for assembling a chromosome 22 ORF clone collection Previous efforts in human to obtain cDNA clones suitable for future functional genomics studies have started by isolating the longest possible cDNA clones [ 10 - 13 ]. In Caenorhabditis elegans , an alternative strategy has been developed that is directly tailored to clone ORFs defined by gene annotations from cDNA libraries into Gateway vectors ready for functional genomics [ 20 ]. The strategy we have developed (Figure 1 ) uses genome annotation to define the full-length ORFs of interest. We then aim to amplify the ORF bracketed by short sequences at either end from uncloned primary cDNA (rather than cDNA libraries) using reverse transcription (RT) PCR with modifications to allow efficient and high-throughput application. The overall aim is to obtain cDNA clones containing the defined set of ORFs more efficiently than by cDNA library screening and to access ORFs not present in existing cDNA library collections. This strategy enables a single protocol to be used for all genes, and therefore does not require the import of any previously existing cDNA clones which might be from multiple laboratories and in several vector systems. In addition, it avoids potential biases associated with cloned cDNA libraries by utilizing uncloned cDNA. We chose not to format the ORF directly for a specific recombinational cloning system because this might compromise our ability to isolate some ORFs by RT PCR. Furthermore ORFs cloned into a generic vector will be useful for those who do not want to use a specific vector format. ORFs in clones derived and verified by this method can be readily transferred into recombinational cloning systems by PCR with appropriately designed oligonucleotides. For the 398 targets, a nested set of two pairs of PCR oligonucleotide primers surrounding each ORF and including a short region of the 5' and 3' untranslated regions was identified. As these primers were to be used to extract a fragment containing the ORF from an extremely complex cDNA template, design was not restricted to the sequences at the start and stop of the ORF. A highly processive, proof-reading thermostable DNA polymerase was use to amplify the ORF from a pool of cDNA derived from various tissues using two rounds of PCR. In 76% of cases amplification with KOD Hot Start polymerase was successful in generating a PCR product of expected size under one set of amplification conditions (see Additional data file 2). However, where the expected-sized PCR fragment was not obtained, we were often able to obtain a fragment by subsequent repeat of the procedure with slight modifications including increasing the annealing temperature, using Pfu -turbo DNA polymerase as an alternative enzyme for one or both rounds of PCR, or using a cDNA template from a single tissue rather than the pooled cDNA. Fragments of the correct size were cloned into a T-tailed plasmid and the inserts were verified by complete sequencing using vector primers and anticipated gene specific primers. Assembled sequence for each clone was then compared with the expected gene sequence. Clones were accepted as correct versions of the ORF if identical to the expected sequence or if they contained only base changes that were known to be single-nucleotide polymorphisms (SNPs) or resulted in silent codon changes. Clones were also accepted with an alternative splicing event that maintained the ORF. Clones were rejected (for this study) if they contained a nonsynonymous base change that could not be confirmed as a known SNP ('unconfirmed bases') or if they resulted from an alternative splice or partially processed mRNA that did not maintain the ORF. When a clone generated from a fragment of the correct size failed validation because of the presence of unconfirmed bases, or retention of a small intron, an alternative clone was picked and sequenced until a correct version was obtained. If alternative splicing or partial processing events gave unacceptable clones, a further round of reamplification was undertaken in order to obtain a correct fragment. Finally, if clone inserts were repeatedly unacceptable as a result of mispriming events, annotation error or amplification of a related gene, a new set of nested oligonucleotide primers were designed. Process error rate and SNPs One possible concern with a strategy that involves reverse transcription and multiple rounds of PCR amplification followed by cloning of a single molecule is that the process will introduce base errors that alter the sequence of the final cloned ORF. Analysis of error rate here is complicated by the frequency of SNPs in humans and the fact that the starting cDNA template is a mix of cDNA from multiple human donors. We estimated the error rate from reverse transcription, PCR and the cloning process by sequencing 48 clones (covering 70,656 bases) containing the ORF of the NAGA gene. These were derived by our cloning protocol using cDNA from 10 lymphoblastoid cell lines as a template, as polymorphism would be easier to identify where each cDNA mix could only be one of two haplotypes. We categorized observed base changes as known SNPs if they were found to exist in dbSNP, in ESTs or in independently sequenced cDNA clones. Base changes were categorized as putative errors if no equivalent sequence could be identified. From this analysis we identified six putative base errors, giving an overall estimate of 0.085 errors per kilobase (kb), or one error per 7.8 clones assuming a mean ORF size of 1.5 kb. Chromosome 22 ORF clone collection Applying the strategy outlined above to the 398 chromosome 22 ORFs, we were able to clone and confirm 278 (70%) of the targeted chromosome 22 ORFs (see Additional data file 1). Sequences of the valid ORF clones are available [ 19 ], and have been submitted to the EMBL database (accession numbers CR456339 to CR456616). Of these, 253 (91%) were derived from fragments generated with KOD polymerase. The remainder were generated using either an alternative polymerase (16; 6%) or a combination of polymerases (9; 3%) (see Additional data file 2). The universal cDNA pool was used for 249 (90%) of the clones, with 29 (10%) of clones derived from lower-complexity cDNA templates from single tissues. Of the accepted clones, 239 (86%) were the predicted splice form, with the remainder being an alternative splice which maintained the ORF; 183 (66%) clones matched the genomic DNA exactly. Of the 162 deviations from the genomic sequence (from 95 clones), 144 (89%) are previously identified SNPs either in dbSNP or dbEST, and 11 (7%) were not identified as known SNPs but did not alter the amino acid (see Additional data file 3). Seven changes were insertion/deletion events (see below). Of the 144 confirmed SNPs in a total of 372,916 bases (1 SNP every 2,590 bases), 81 were synonymous and 63 were nonsynonymous codon changes. Individual clones contained between one and eight SNPs (see Additional data file 3). Insertions or deletions that retained the ORF were observed in five clones. None of these significantly altered the ORF, as four cases involved three bases while one involved 12 bases. We also observed a polymorphism in MSE55 which involved the insertion or deletion of six amino acid repeat units and exists in three different alleles. We amplified and sequenced genomic DNA fragments across this region from 152 chromosomes of European ancestry and found that all three alleles are common and in Hardy-Weinberg equilibrium. In this case the clone chosen for the ORF collection was the same allele as seen in the publicly available genomic sequence. In three cases we obtained clones with insertion/deletion polymorphisms that altered the ORF but were supported by available chromosome 22 sequence. To determine whether to accept these clones as ORF cDNAs, we examined all three in more detail. The clone obtained for gene APOL4 contains a 2-bp insertion compared to the canonical genomic sequence annotation. This results in a frameshift that substantially extends the ORF from 127 amino acids to 348 amino acids. We designed a PCR reaction to directly interrogate the insertion/deletion and sequenced 144 chromosomes of European ancestry. Both alleles are common in this population, and are in Hardy-Weinberg equilibrium, with the 348-amino acid form being the minor allele at 46.5%. For bK216E10.6 we obtained an ORF clone with a 2-bp insertion compared to the genomic annotation, which results in an ORF that contains an extra 318 amino acids. Using the same strategy we sequenced 150 chromosomes and showed that the sequence producing the shorter peptide is the minor allele with a frequency of 20%, and the alleles are again in Hardy-Weinberg equilibrium. In this case we do not have an accepted clone, as the insertion increased the ORF length beyond the primer sequence. The third gene is TXN2 which shows a 2-bp insertion compared to the genomic sequence which is also found in an EST (AA586375), but has not been studied further. An insertion/deletion polymorphism that alters the ORF has previously been observed in MICA on chromosome 6 [ 21 ]. From these examples we concluded that insertion/deletion polymorphisms in ORFs that alter amino acid sequence may be relatively common, and can result in altered proteins. Complete ORF collections for outbred organisms like humans should ultimately address this issue and obtain examples of all common forms of the ORF. In addition, we were able to amplify a PCR fragment which could be identified as originating from the correct gene for an additional 53 ORFs, but have not yet been able to obtain an acceptable clone because of the presence of unconfirmed bases, or problems with splice forms including partially processed transcripts. In most cases, only one or two amino acids are changed, which could make these clones usable under some circumstances, perhaps after site-directed mutagenesis. It is also possible that these are rarer SNPs that are not currently present in dbSNP. This suggests that by sequencing more examples we will be able to obtain clones for these ORFs in the near future. Thus the clone collection would cover 83% (331) of the targeted ORFs. Process failure In total, we initiated the amplification and cloning process 538 times, excluding initial pilot trials. These 538 events break down as follows. For 180 (45%) targeted ORFs an acceptable clone was generated at the first attempt. Further rounds of clone-picking, reamplification or primer redesign generated a further 99 acceptable clones, 83 clones containing an unconfirmed base alteration, 54 clones containing an alternative splice which lost the ORF, 23 clones containing a rearrangement or erroneous amplification event, 19 clones with retained intron sequences, four clones containing unresolved sequencing problems and 36 clones which were not the expected gene. For 41 genes we were unable to amplify a suitable product or failed to clone the fragment. Hence the efficiency of the process in terms of the return of acceptable clones is approximately 52% (278/540). A significant area of concern is where we were unable to generate a PCR product at all corresponding to the targeted gene. To find explanations for this type of failure, we examined both the sequence characteristics of the targeted ORF and elements of the experimental design. First we examined the crude differences between the classes of ORFs that we could and could not amplify. Figure 2a shows a plot of the distributions of these two classes by GC content and length of ORF. Both GC content and length are significant predictors of success/failure to amplify (Mann Whitney test p < 0.0001), although logistic regression indicates there is no significant interaction between them. This suggests that alternative amplification protocols using different polymerases or PCR additives might result in additional ORFs being obtained. However, we have tested three additional enzymes or mixes ( Pfu Ultra (Stratagene), Phusion (Finnzymes) and Expand 20 kb+ PCR (Roche)) and additives including DMSO, glycerol and betaine so far without identifying a design that solves the problem. Next, we explored whether it was possible to amplify any part of the failed target cDNAs from the universal mix. For 51 of the genes where we failed to amplify the expected fragment, we designed additional nested oligonucleotide primer pairs to amplify a short (100-274 bp) sequence across a splice junction. In 39 cases (74%) we amplified a fragment of the correct size and sequence under our standard nested PCR conditions, suggesting that template is present in the cDNA mix for these ORFs (data not shown). Therefore, in most cases it is possible to amplify part of the targeted ORF from the cDNA mix using this protocol, indicating that the level of target in the mix is not limiting in these cases. Given that we know we can amplify parts of many of the problematic genes, one variation that could improve access to larger ORFs in the future would be to amplify larger transcripts in pieces that can then be reassembled into a single clone using appropriate restriction enzyme digestion and ligation or PCR cloning methods. We also examined whether successful amplification was biased towards genes expressed in many tissues. Su et al . [ 22 ] have generated microarray data indicating the distribution of expression for many human genes over 47 tissues. We downloaded these data [ 23 ] and were able to obtain tissue-distribution data for 206 of our 398 targeted genes. Codifying the diversity of tissues in which the genes were expressed as the proportion of positive tissues, and analyzing for the success or failure of amplification by logistic regression, indicated that the probability of amplifying a gene is not significantly affected by the diversity of its expression (data not shown). We also examined diversity of expression by analyzing serial analysis of gene expression (SAGE) data derived from 242 Nla III SAGE libraries downloaded from the SAGEmap resource [ 24 ]. SAGE tags could be uniquely mapped to 315 of the 398 ORFs targeted. Using the number of SAGE libraries in which a SAGE tag for an ORF was found to represent the diversity of tissues in which the gene was expressed, no significant relationship was found with the probability of amplifying a gene (Mann Whitney test, p = 0.84). Furthermore, because the SAGE tag data also gives an indication of expression level, we examined whether the mean expression level found by SAGE (mean normalized tags per million SAGE reads) affected probability of expression and again found no significant relationship (Mann Whitney test, p = 0.79). Taken together these analyses indicate that the success of our amplification strategy is not significantly influenced by either the range of tissues in which a gene is expressed or the level of expression. Clearly there will be some genes expressed at low levels, at specific times or in specific tissues that will need special treatment, but these data suggest that these cases may be few. Comparison of the chromosome 22 ORF collection with other cDNA sources Returning to the cDNA clone collections, of the 331 targeted genes for which we can obtain either an acceptable clone (278) or a clone of the correct ORF but currently with a problem in its sequence (53), 208 genes also have clones in the cDNA clone collections we analyzed; 123 genes only have clones in the new chromosome 22 ORF set described here. In addition, for 19 genes which are represented in the cDNA clone collections we were unable to isolate a clone (Figures 2b , 3 ). This means that 88% (350) of the full-length protein-coding genes on chromosome 22 have cDNA clones. This also suggests that achieving 88% coverage of the readily accessible human ORFeome should be possible with an approach that combines the existing cDNA collections with directed RT-PCR as implemented in this analysis. Of course, because the actual number of human genes is still unknown and a significant number of genes have only partial annotation, there is still an indeterminate number of genes for which there is insufficient annotation to attempt the current strategy. We analyzed the four classes of genes (isolated by us and in the cDNA collections (BOTH), isolated only here (SANGER), isolated only by the cDNA collections (OTHER) and not isolated (NOT)) by GC content, length and diversity of expression as defined above for microarray data and SAGE using nonparametric analysis of variance (Figure 3 , and Additional data file 5). ORF length was significantly higher ( p < 0.001) for genes not isolated (NOT) as compared to those isolated by us (SANGER) or those isolated both by us and the cDNA collections (BOTH). This suggests, as expected, that longer ORFs are harder to amplify or clone. A significant influence ( p < 0.05) was also found for higher GC content in the genes that were either not isolated (NOT) or found only in the cDNA collections (OTHER) compared with the SANGER or BOTH classes, reflecting the influence of GC content on the ability to amplify a cDNA target as discussed above. The only significant difference ( p < 0.05) for diversity of expression was between genes cloned only by us (SANGER) and those present in both our set and the cDNA collections (BOTH), with less diversely expressed genes slightly enriched in the SANGER class. This result was seen only in the microarray data, although the effect was also present in the SAGE data at just below significance. This suggests that the method described here may be able to access less widely expressed genes than have been sampled by existing cDNA library sequencing, although the effect is small. Finally, analysis of the mean level of expression of the genes in the four classes based on the normalized SAGE tag count showed no significant difference, indicating that level of expression is not a significant factor for this set of genes. Conclusions Even given a high-quality human genome sequence, we still face considerable challenges in identifying and isolating full-length cDNAs and ORFs in order to construct genome-wide clone sets for functional analyses. The method we have described here offers an alternative approach to obtaining full-length ORF clones compared with sequencing or amplifying from cDNA libraries. We have demonstrated that we can readily obtain clones for 70% of the full-length protein-coding genes on chromosome 22, increasing to 83% if we include the largely correct clones which have not passed the confirmation criteria. In addition, a small number of clones (19) that we could not obtain are present in the cDNA collections analyzed, and when these are included, the overall coverage of the known full-length protein-coding genes reaches 88%. While this represents a substantial gain over cDNA sequencing alone, it is clear that complete coverage may require further modification of the approach or additional strategies as well. The quality control that is introduced by starting with annotated genes on the genomic sequence allows identification of SNPs and artifacts within the clones, and allows confirmation or rejection of each clone as it is generated. The checking process also provides verification of gene structures annotated from assembled ESTs, and in a few cases revealed errors. Our approach also has some advantages for scale-up to whole genomes. The starting point is a single PCR reaction using a universal template, which could be adapted to standard automation platforms. Subsequent steps, including ligation, transformation, clone picking, sequencing and sequence analysis, are all amenable to existing robotic approaches or automation. At present, the gel-purification step of the amplified PCR fragment might be difficult to automate. It is also likely that the final sign-off on the sequence alignment of clones will require human intervention in much the same way as finishing genomic sequences does. However, application to whole genomes demands a high-quality gene annotation to be available for the whole genome. We have generated a set of quality-controlled ORFs surrounded by a short stretches of 5' and 3' untranslated sequence in a uniform vector. The ORF portions of these intermediary clones are currently being amplified and subcloned in frame into a mammalian expression vector which fuses the amino-terminal T7 phage major capsid protein to the amino or carboxy terminus of the protein. We have successfully performed subcellular localization studies using immunofluorescence microscopy with these clones. We are also transferring the ORFs into Gateway pDONR clones (Invitrogen) and subsequently using GFP fusion destination vectors for subcellular localization. The availability of the ORF in a generic vector provides flexibility in the future downstream formats in that the endogenous Kozak sequence and the translation start and stop are maintained, and without additional amino acids from recombination sites. Finally, it is worth noting that this approach could also be applied to amplifying and cloning the many alternatively spliced forms of genes, or ORFs from different individuals or haplotypes. The ability to access the many additional variants beyond the canonical ORFeome could prove a valuable tool for future studies. Materials and methods cDNA sequence sources and websites cDNA sequences were downloaded from the websites of the following publicly available cDNA collections in January 2004. For the Mammalian Gene Collection (MGC [ 11 , 25 ], 15,454 sequences were downloaded on 16 January 2004 [ 26 ]. For the full-length long Japan collection (FLJ [ 12 ]), 25,696 sequence accession numbers were obtained on 16 January 2004 [ 27 ] and the sequences were downloaded from the EMBL sequence database. For the German cDNA Consortium (DKFZ [ 10 ]) we identified 9,271 sequence accessions on 16 January 2004 [ 28 ] and sequences were downloaded from the EMBL database. For the Kazusa cDNA project (KIAA [ 13 , 29 ]), 2,037 sequence accession numbers were obtained on 26 January 2004 [ 29 ], and sequences were downloaded from the EMBL database, although two cDNA sequences were missing (KIAA0013 and KIAA0302). In addition, we downloaded 4,361 of the commercially available Invitrogen cDNAs on 8 December 2003 [ 30 ] (file datestamp 20 October 2003). Amplification and cloning of ORFs Chromosome 22 gene annotations containing full-length ORFs, as defined in Collins et al. [ 17 ], but not including the genes described as possible antisense, and 13 genes subsequently completed, provided 398 complete chromosome 22 gene sequences. Nested sets of two pairs of PCR primers surrounding each ORF were designed using Primer3 (Steve Rozen, Helen J. Skaletsky (1996, 1997), Primer3, Code available at [ 31 ]) and Perl (version 5.004) scripts to automate the process (see Additional data file 4 for primer pairs designed). Fragments were amplified with the outer primer pair from either 0.1 ng of a pool of cDNAs from 37 tissues (Human Universal QUICK-Clone cDNA, Clontech), or cDNA from a single tissue (cervix, liver, brain, testis, fetal liver or fetal brain obtained as RNA from Stratagene or QUICK-Clone cDNA from Clontech), or cDNA from lymphoblastoid cell lines (European Collection of Cell Cultures, Porton Down, UK HRC collection, cell lines lines C0043, C0092, CO118, C0127, C0139, C0143, C0155, C0167, C0179, C0259, C0573). For the lymphoblastoid cells lines, total RNA was extracted from tissue culture cells with TRIzol reagent (GibcoBRL/Invitrogen). Total RNA was reverse transcribed into cDNA with Superscript II (Invitrogen) according to the manufacturer's instructions. The first-round amplification protocol used KOD Hot Start DNA polymerase (Novagen), Pfu -turbo Hotstart DNA polymerase (Stratagene) or Pfu DNA polymerase (Stratagene) using the manufacturers' recommended cycling profiles for 30 or 35 cycles in a 25 μl reaction. Fragments were then diluted 1 in 50 with sterile water and 5 μl used as template for a second 25 μl amplification using the inner primer pair (see Additional data file 2 for variant amplification conditions). Additional enzymes including Pfu Ultra (Stratagene), Phusion (Finnzymes) and Expand 20 kb+ PCR (Roche) were trialed according to the manufacturers' recommendations. Fragments of the expected size were gel-purified, extracted with QIAquick spin columns (Qiagen), 3'-tailed with an adenosine residue using Amplitaq polymerase (Perkin Elmer) and subcloned using the pGEM-T Easy Vector System (Promega). Sequencing template was prepared either by plasmid miniprep or, in the majority of cases, by amplifying clone inserts with vector primers and cleaning the amplified fragment with either QIAquick Gel Extraction Kit or Shrimp alkaline phosphatase (1 unit, Amersham) and ExonucleaseI (1 unit, Amersham) (see below). Sequencing was performed with BigDye terminator v3 Cycle Sequencing Kits (Applied Biosystems) using vector primers, the inner nested primer pair and pairs of primers designed at 600-base intervals along the predicted gene sequence. Sequence was assembled using the contig assembly program CAP3 [ 32 ], aligned against the predicted transcript sequence and checked manually. Sequence comparison and analysis The 398 annotated ORF sequences were matched by blastn (version 2.0 MP-WashU, 10 April 2004 [ 33 ]) to cDNA collection databases MGC, FLJ, DKFZ, KIAA and Invitrogen. MSPcrunch [ 34 ] was used to parse blastn output and exclude matches with lower than 95% identity. ORFs were extracted from each of the matching cDNA sequences using the EMBOSS program getorf [ 35 ] and compared to the annotated ORFs using cross_match (P. Green, unpublished work). The GC content of the ORFs was calculated using the EMBOSS program geecee [ 35 ] and Perl scripts (version 5.004) were written to analyze and summarize data. Microarray data indicating the distribution of expression for many human genes over 47 tissues using the Affymetrix human U95A array [ 22 ] was downloaded [ 23 ]. Tissue distribution data for 206 genes was obtained and a gene was called as expressed in a tissue sample if the average difference was > 200 [ 22 ]. The tissue expression diversity of a gene was defined as the proportion of positive tissues. Where replicate experiments existed, the highest tissue-expression diversity value was used. For SAGE data, the 398 target ORF sequences were matched by blastn [ 33 ] against Unigene (Homo sapiens, 12 May 2004 Build 170 [ 36 ]) and the best (highest identity greater than 99%) full-length matching UniGene cluster was assigned to each ORF. SAGEmap data [ 24 ] was downloaded [ 37 ] together with a file of tag frequencies [ 38 ]. A Perl program was then used to search these files for SAGE tags mapping to each UniGene cluster and the tag counts for each Homo sapiens Nla III library (GPL4) were determined. Tag counts were normalized to tags per million for each library, and then averaged to give a mean expression level. Diversity of expression was defined as the number of libraries in which a tag occurred. Amplification and sequencing of genomic DNA for insertion/deletion analysis Fifty nanograms of genomic DNA from 78 unrelated individuals (ECACC Human Random Control Panel) was amplified in 15 μl reactions containing: 6.7 mM MgCl 2 , 67 mM Tris-HCl, 16.7 mM (NH 4 ) 2 SO 4 pH 8.8, 170 μg/ml BSA, 10 mM 2-mercaptoethanol, 500 μM each dATP, dCTP, dGTP, dTTP, 0.04 units/μl Amplitaq, 0.75 μM each primer, 10.13% sucrose, 0.0029% Cresol Red (sodium salt). Reactions were cycled in an MJ thermocycler at 94°C for 5 min, followed by 35 cycles of 30 seconds at 94°C; 30 sec at 65-66°C; 30 sec at 72°C, followed by a final 72°C for 5 min. PCR reactions were treated with 1 unit of shrimp alkaline phosphatase and 1 unit of exonuclease I in reaction buffer supplied by the manufacturer (USB, 10 × buffer - 200 mM Tris-HCl pH 8, 100 mM MgCl 2 ) for each 10 μl PCR reaction. Reactions were heated at 37°C for 30 min followed by 80°C for 15 min to inactivate the enzymes. PCR products were then sequenced from both ends using the primers used from the amplification step and BigDye terminator v3 Cycle Sequencing Kits (Applied Biosystems). Sequences were analyzed using GAP4 [ 39 ]. Additional data files The following additional data files are available with the online version of this article. Additional data file 1 lists the 278 successfully cloned ORFs (see also [ 19 ]); Additional data file 2 lists enzymes and templates used to amplify ORFs; Additional data file 3 lists the sequence variation between ORF clone and genomic sequence; Additional data file 4 lists the nested oligonucleotide primers designed for the 398 targeted genes; Additional data file 5 contains the results of nonparametric ANOVA (Kruskal-Wallis Test) for chromosome 22 genes isolated as cDNA by the method described here only (SANGER), found in the cDNA collections only (OTHER), isolated by both ourselves and the cDNA collections (BOTH) or not isolated (NOT). Mean rank differences and p -values are given after Dunn's multiple comparisons test. Additional data file 6 contains a list of the 278 cloned ORFs and Additional data file 7 contains a list of the 398 target ORFs; both files are also available at [ 19 ]. Supplementary Material Additional data file 1 The 278 successfully cloned ORFs Click here for additional data file Additional data file 2 Enzymes and templates used to amplify ORFs Click here for additional data file Additional data file 3 The sequence variation between ORF clone and genomic sequence Click here for additional data file Additional data file 4 The nested oligonucleotide primers designed for the 398 targeted genes Click here for additional data file Additional data file 5 The results of nonparametric ANOVA (Kruskal-Wallis Test) for chromosome 22 genes isolated as cDNA by the method described here only (SANGER), found in the cDNA collections only (OTHER), isolated by both ourselves and the cDNA collections (BOTH) or not isolated (NOT) Click here for additional data file Additional data file 6 A list of the 278 cloned ORFs Click here for additional data file Additional data file 7 A list of the 398 target ORFs Click here for additional data file

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Search for computational modules in the C. elegans brain

Background Does the C. elegans nervous system contain multi-neuron computational modules that perform stereotypical functions? We attempt to answer this question by searching for recurring multi-neuron inter-connectivity patterns in the C. elegans nervous system's wiring diagram. Results Our statistical analysis reveals that some inter-connectivity patterns containing two, three and four (but not five) neurons are significantly over-represented relative to the expectations based on the statistics of smaller inter-connectivity patterns. Conclusions Over-represented patterns (or motifs) are candidates for computational modules that may perform stereotypical functions in the C. elegans nervous system. These modules may appear in other species and need to be investigated further.

Background There is little doubt that neurons are elementary building blocks of the nervous system [ 1 ]. It is less clear, however, whether multi-neuron modules (smaller than invertebrate ganglia or vertebrate nuclei and cortical columns) can be meaningfully defined, either anatomically [ 2 ] or physiologically [ 3 ]. The existence of such multi-neuron modules would greatly simplify the description of nervous system structure and function. An example of such simplification can be found in electrical engineering. An electronic circuit is often represented in terms of modules such as operational amplifiers, logical gates and memory registers rather than as a wiring diagram showing each transistor, resistor and diode. However, unlike electrical engineers who designed these modules themselves, neurobiologists did not design the brain, and evolution rarely leaves records of its experimentation. Therefore, if multi-neuron modules have indeed evolved they need to be discovered. In this paper, we search for anatomically defined multi-neuron modules in the Caenorhabditis elegans nervous system. We choose C. elegans as a model organism because its wiring diagram is largely known, including the identities of all 302 neurons and most synapses between them [ 4 - 6 ]. Our approach follows the reasoning developed previously in the context of gene regulation and other networks [ 7 , 8 ]. If a certain multi-neuron module performs some stereotypical function it may appear in the nervous system repeatedly. Therefore, search for multi-neuron connectivity patterns that appear more often than by "chance" (compared with the expectations as defined below) may yield these multi-neuron modules. Of course, there may be functionally important modules that appear infrequently and would be missed by our analysis. In the electronic circuit analogy, our approach would discover logical gates in a processor wiring diagram but not a rectifier in a power supply, which is essential but appears only once. To search for N -neuron modules, we sort all N -neuron combinations into classes defined by their inter-connectivity pattern and count the number of combinations in each class. By comparing these counts with the mean counts from random networks, constructed based on our expectations, we detect significantly over-represented patterns, or motifs. In order to avoid assigning significance to a N -neuron pattern just because it contains N-1 -neuron motifs we incorporate the N-1 -neuron statistics into the expectations used to search for N -neuron motifs [ 8 ]. To do this, we perform our search sequentially, by starting with doublets (or neuronal pairs, N = 2) and then increasing the number N of neurons included in the pattern sequentially up to quintuplets ( N = 5). We look for motifs in the wiring diagram of the C. elegans nerve ring (a large fraction of the nervous system) assembled in two datasets [ 6 ]. Datasets 1 and 2 were obtained from serial-sections electron microscopic (EM) reconstructions of two different animals [ 4 ]; for details see Methods. The datasets contain the numbers of synapses formed in a subset of C. elegans neurons. Two given neurons may be connected by more than one synapse, which we call the multiplicity of connection. However, the small size of the dataset compels us to use the binary representation of these connections (connected or unconnected). In order to obtain binary connectivity matrices, we threshold the multiplicity of connections at various values Θ: Pairs having less than Θ synapses are considered unconnected while those having at least Θ synapses are considered connected. Such procedure is justified because more than a single synaptic contact may be necessary for an observable physiological effect of one neuron on another. Since we do not know the physiologically relevant count of synapses, we repeat our calculation for 1 ≤ Θ ≤ 7. Unfortunately, datasets 1 and 2 contain a caveat of synaptic ambiguities, which arises from the limitations of EM in C. elegans . When one pre-synaptic neuron makes contact with two adjacent processes of different neurons (send_joint in Durbin notation [ 6 ]), it is not known which of these processes acts as a post-synaptic terminal; both might be involved. We address this ambiguity by performing our analysis in two ways. In the main text we present the results obtained on the datasets that include both send and send_joint synaptic connections. We repeated the analysis on the datasets where send_joint synapses were split equally between the two potential post-synaptic partners. Specifically, we calculated multiplicity of connections by adding send_joint synapses at 50% synaptic strength. In the limit of high multiplicity, this is equivalent to assigning the post-synaptic neuron by chance. We find essentially the same results for this connectivity dataset (see Supplementary Information [ Additional file 1 ]). Results Bi-directionally connected doublets ( N = 2) are over-represented We classify all possible doublets (or pairs) of the C. elegans neurons into three classes: unconnected, uni-directionally connected and bi-directionally connected, and compare the number of doublets in each class to that expected in a random network (Figure 1 ). The random network ensemble consists of connectivity matrices that preserve the numbers of incoming and outgoing synapses for each neuron but not the identities of the partners [ 9 , 10 ]. The motivation behind this choice of the random matrix ensemble and the details of the algorithm are explained in Methods. We find that the number of doublets in each class deviates from the mean of the random matrix counts, as shown in Figure 1 for a representative threshold Θ = 3. For the purposes of module search, the most interesting finding is the over-representation of the reciprocally connected doublets (pattern #3), for two reasons. First, if a set of neurons were to function as a module it should not consist of two (or more) disconnected subsets. This consideration rules out pattern #1. Second, since our search for modules is aimed at identifying over-represented inter-connectivity patterns we are less interested in under-represented ones. This consideration rules out pattern #2. We note that pattern counts are not independent, but are subject to sum rules. For example, the number of neurons in the network fixes the total doublet count. Also, the total number of connections is equal to the count of pattern #2 plus twice the count of pattern #3. These sum rules place stringent constraints on possible combinations of doublet counts. Yet, for patterns with greater number of neurons ( N>2 ), these constraints become less stringent because the number of patterns increases (see below). We repeat the above calculations for other datasets and threshold values and consistently find the significant over-representation of bi-directionally connected doublets (data not shown). In C. elegans , such over-representation was reported previously on a qualitative level [ 4 ]. Interestingly, an over-representation of bi-directionally connected doublets was also found for pyramidal neurons in mammalian neocortex [ 11 - 13 ]. This suggests that motifs may represent evolutionary conservation or convergence driven by similar computational constraints. Next, we discuss whether C. elegans can provide a clue to the functional significance of the over-representation of reciprocally connected doublets. Can bilateral (left-right) symmetry of the C. elegans neuronal network account for the over-representation of the reciprocally connected doublets? Indeed, about two thirds of C. elegans neurons have a bilaterally symmetric partner. If connections between these pairs obeyed bilateral symmetry then they could not be uni-directional, creating a bias in favor of bi-directional connections. To see whether this is the case, we calculate the percentage of bi-directional connected doublets, which consist of a bilateral neuron pair. We find that these percentages are small: 7.1% and 5.5% in datasets 1 and 2, respectively. Therefore, bilateral symmetry is not sufficient to explain the observed result. The over-representation of reciprocally connected doublets in C. elegans has been explained [ 6 ] as a consequence of correlation between adjacency and connectivity of neurons. The argument is that, if there is a synapse from neuron A to neuron B, they must be adjacent. If neurons A and B are adjacent then a synapse from B to A is more likely than chance, increasing the probability of a reciprocal connection. Analysis of original EM reconstructions [ 4 ] supports this argument [ 6 , 14 ]. Adjacency in this case does not refer to the nearby placement of cell bodies but to the number of EM sections (divided by five) in which the processes of the two neurons are in contact [ 6 , 14 ]. Although correlation between adjacency and connectivity may account for the over-representation of reciprocally connected doublets, why such correlation would exist in C. elegans remains unclear. It could be that the number of neuronal pairs, which can be adjacent, is limited by physical constraints. This would restrict the adjacent pairs only to the ones that need to connect for functional reasons. Indeed, volume exclusion explains neuron dimensions in the cortical column ([ 15 ] and references therein). In the C. elegans network, however, the small number of neurons should in principle allow a contact between any pair of neurons. This argument is supported by the observation that many neuronal processes are longer than the distance between the corresponding cell bodies, suggesting that the connection can be made. However, processes tend to run in bundles and make synapses only in their (often varying) neighborhoods [ 14 ]. This suggests that other (e.g. developmental) constraints may restrict the number of adjacent neurons. Alternatively, it could be that network functionality requires over-representation of reciprocal connections (or clustering). These issues must be explored in the future. Several triplet classes ( N = 3) are over-represented We classify all connected triplets in the C. elegans wiring diagram into 13 classes and count the number of triplets in each class. We compare the actual number of triplets in each class to the null-hypothesis random matrix ensemble defined as follows. In order to include the observed over-representation of reciprocally connected doublets, we construct random networks that preserve the numbers of bi-directional and uni-directional connections for each neuron. Figure 2 shows triplet counts for each class relative to the mean of the random matrix ensemble. For threshold Θ = 2 we find that several triplet counts are noticeably different from the mean of the random matrix ensemble, e.g. patterns #10, #12, #14 and, possibly, #15 and/or #16 in Figure 2 . Similar results were found for other values of the threshold (within the biologically plausible range, Θ = 1 to 7). Are these differences between triplet counts in actual and random networks significant? One might answer this question by calculating, for each class, a significance p -value, i.e. the probability of finding a random matrix with deviation from the mean exceeding or equal to that for the actual network. Although such an approach would be correct if over-representation of a single class were examined, it would over-estimate the true significance (i.e. under-estimate the p -value) when many different classes are evaluated simultaneously. This situation is known as multiple hypothesis testing and requires an adjustment of the raw p -values (see Methods). We chose to perform multiple hypothesis testing adjustment by controlling the family-wise error rate, i.e. the probability of mistakenly reporting at least one non-over-represented pattern, by using the single-step min P procedure [ 16 , 17 ]. The adjusted p -values for every class and threshold represent the probability of finding a random matrix R , in which at least one class i has smaller (or equal) raw p -value than that found for a given class and threshold in the actual network. This measure can be calculated by counting the number of random matrices, which have a smaller (or equal) raw p -value (in at least one class) than that in the actual network for a given class and threshold. By dividing this number of matrices by the total size of the random matrix ensemble, we estimate the multiple hypotheses testing corrected significance measure P m for each class and threshold, Figure 3 (see Methods). According to the significance measure, P m , one of the most consistently over-represented motifs is the feedforward loop (triplet pattern #10), previously noticed in C. elegans [ 5 , 18 ] and other networks [ 7 , 8 ]. For the full list of feedforward loops see Supplementary Information [ Additional files 2 and 3 ]. Could some known feature of neuronal organization account for the observed over-representation of the feedforward loop? We consider two hypotheses: i. The three-layered feedforward neuronal network is not sufficient to account for over-representation of the feedforward loop If one views the C. elegans nervous system as a three-layer feedforward network, where sensory neurons synapse mostly on interneurons, and interneurons synapse on other interneurons or motorneurons, this could explain the over-representation of the feedforward loop. We argue that this is not the case for two reasons. First, the feedforward loop is also over-represented among interneurons (Figure 4 ). Second, the three-layer model of the C. elegans nervous system is overly simplified. For example, there are feedback connections from interneurons to sensory neurons and from motorneurons to interneurons. To evaluate whether detected feedforward loops fit the three-layer feedforward network, we analyze the function of the neurons in these loops. About 40% of the detected feedforward loops either contain all neurons from the same functional group or at least one connection goes from a neuron in a lower layer to a neuron in a higher layer, Table 1 . These loops do not fit into this three-layer model, undermining the hypothesis. ii. The likelihood of connectivity between nearby neurons may partially account for over-representation of the feedforward loop Since connectivity and adjacency are correlated in C. elegans and other nervous systems one could argue the following [ 4 ]. If two neurons have a common synaptic partner, then they are likely to be adjacent to that common partner, and hence to each other. If the two neurons are adjacent they are likely to be connected to each other. Again, adjacency cannot refer to the cell body position: The fraction of over-represented triplets that consist of neurons belonging to the same ganglia is typically less than 30%. Yet this argument could be valid if the adjacency refers to the contacts between neuronal processes (see above) and needs to be verified using original EM reconstructions [ 4 ]. The problem with this argument is that it would also predict an over-representation of all strongly connected patterns (#10 to #16), as opposed to the weakly connected patterns (#4 to #9). Yet, strongly connected triplet classes #13 and #11 (the feedback loop) are not over-represented (Figure 3 ) so further explanation is required. It is possible that the over-representation of the feedforward loop is a consequence of other factors or their combinations (such as feedforwardness and locality of connectivity combined). But even if these factors are found, the characterization of the network in terms of over-represented motifs remains valid. The over-representation of the feedforward loop still requires a functional explanation just as the bi-directionally connected doublet does. In gene transcription regulation networks, the feedforward loop was proposed to carry out information processing functions such as filtering out fluctuations and responding only to persistent stimuli [ 7 ]. Feedforward loop can also carry out other functions [ 5 , 18 ], depending on the polarity of synapses involved and the dynamic response of neurons. Once these factors are established experimentally, motif function can be analyzed theoretically. In addition to the feedforward loop, we find that two other (both symmetric) patterns are consistently over-represented: pattern #12 and pattern #14 (Figure 3 ). For the full list of these patterns see Supplementary information [ Additional files 2 and 3 ]. Previous work [ 8 ] did not identify these patterns as motifs because of their low absolute count at the only threshold considered (Θ = 5). Again, we ask whether this could be a consequence of the bilateral symmetry of the C. elegans nervous system. Indeed, the bilateral symmetry implies that pairs of bilaterally symmetric neurons are also connected symmetrically, meaning that triplets containing such a pair are likely to be symmetric. However, we find that the fraction of triplets #12 and #14 containing a bilaterally symmetric pair of neurons and an unpaired neuron is rather small (between 10% and 20% in datasets 1 and 2). This suggests that the bilateral symmetry of the nervous system is not sufficient to explain the over-representation of pattern #12 and #14. Just like in any other screening algorithm, our criteria for outliers are somewhat subjective and the goal is to draw attention to interesting candidates. We limit our discussion to over-represented patterns #10, #12 and #14 because in our judgment they are most robust outliers based on the several criteria used. The reader may judge that some other patterns are over-represented as well. For example, patterns #15 and #16 are significantly over-represented for small thresholds (Figure 3 ). Because the absolute counts of these patterns in the C. elegans network are small, we cannot verify that they are consistently over-represented. Further work on larger datasets will show whether these patterns may be viewed as motifs. Several quadruplet classes ( N = 4) are over-represented We classify all connected quadruplets into 199 classes and count the number of quadruplets in each class. Then we compare the actual counts of quadruplets in each class to the mean counts of quadruplets in a random matrix ensemble. In this case, random matrices preserve the numbers of uni-directional and bi-directional connections for each neuron and, in addition, the numbers of triplets (see Methods). Because of the large number of quadruplet classes, we show results (Figure 5 ) only for patterns selected according to the following criteria: the multiple hypothesis testing corrected significance values P m must be less than 0.1 for at least one threshold per pattern, while the number of quadruplets in the actual network must be at least 5. The last condition excludes patterns that may appear as over-represented due to very small quadruplet counts. We find that quadruplet pattern #45 is consistently over-represented [ 8 ]. Can we explain this observation by some other known factor? We consider the following two hypotheses: i. Bilateral symmetry of the nervous system is not sufficient to explain the over-representation of the quadruplet pattern #45 One could propose that symmetric patterns should be over-represented because of the bilateral symmetry of the nervous system. We think that this argument by itself cannot explain the observed over-representation for two reasons. First, the fraction of feedforward quadruplets containing two bilaterally symmetric neuron pairs in motif 45 is rather small (less than 10% in dataset 1 and less than 14.3% in dataset 2). Second, many symmetric patterns are not over-represented, such as, for example, patterns 25, 30, 31, 35, 43, 44 and 65 (Figure 6 ). ii. Feedforward structure of the nervous system may partially explain the over-representation of the feedforward quadruplet One could propose that the feedforward three-layer structure of the nervous system could account for this observation (see over-represented triplets). We find that 14% to 37% of the feedforward quadruplets do not fit into this proposition because either they contain a feedback connection or all neurons belong to the same layer (Table 2 ). After comparing these percentages to the relative excess values we conclude that the feedforward structure may explain over-representation for some threshold values but not for others. It is possible that some other factors (in addition to feedforwardness) account for the reported quadruplet over-representation. Just as argued in case of triplets, discovering these factors would be complementary to the characterization of the over-represented motif. It would be particularly interesting to determine the functional role of these motifs. Again, we arbitrarily limit our discussion of over-represented quadruplets to pattern #45. The reader may judge that some other patterns are over-represented and deserve attention (e.g. patterns #36, 50). This is why in Figure 5 we show all the outliers satisfying relatively weak criteria. We find no over-represented quintuplet classes (N = 5) We classify all connected quintuplets into 9364 classes (out of 9608 patterns total, i.e. connected and unconnected) and count the actual number of quintuplets in each class. We compare these counts with the mean of the random matrix ensemble. In this case, the random matrices preserve the numbers of uni- and bi-directional connections for each neuron and, in addition, keep the numbers of all triplets and quadruplets in a 10% range of the actual network. We do not find any significantly over-represented quintuplets. This could happen because there are no significantly over-represented quintuplets with a given number of quadruplets. Alternatively, this could happen because specifying the numbers of triplets and quadruplets constrains the number of quintuplets in any random matrix the size of the C. elegans network. Therefore, absence of significantly over-represented quintuplets in C. elegans does not rule out the existence of five-neuron modules that can be detected as motifs by applying our algorithm to larger networks. Discussion By comparing counts of multi-neuron patterns in the C. elegans wiring diagram to the mean counts of the appropriate random matrix ensemble, we find several over-represented motifs. First, we find that bi-directionally connected doublets (out of three possible doublet classes) are over-represented, given the number of connections on each neuron is fixed. Second, several triplet classes (out of thirteen possible connected patterns) are over-represented, given the actual number of bi-directional (as well as uni-directional) connections for each neuron. Third, we find that several quadruplet classes (out of 199 connected patterns) are over-represented, given the numbers of triplets are preserved in addition to previously listed constraints. We find no over-represented quintuplet classes. Some of these results, such as the over-representation of the feedforward loop and the feedforward quadruplet, have been reported previously [ 5 , 8 , 18 ]. The current paper extends and complements previous reports by performing a systematic motif search for various connection multiplicity thresholds and rigorous statistical significance assessment. Also, we consider whether the discovered motifs can be accounted for by previously known facts about the organization of the nervous system. There is no functional explanation for the existence of the motifs. Therefore, the identified motifs are candidates for modules that may perform stereotypical functions in the C. elegans nervous system, and they need to be investigated further. Although the main motivation for this work, search for modules, led to our focus on over-represented patterns, we also checked for under-representation. For example, previous work indicated that the number of triplets with pattern #11 (or feedback loops) was small [ 6 ]. To determine significance, we applied the single-step min P procedure to the absolute value of the deviation of counts from the mean. We found that the feedforward loop is not significantly under-represented, yet many other patterns, such as weakly connected triplets were significantly under-represented (see Supplementary Information [ Additional File 1 ]). Our motif search algorithm is different from previous attempts to find modules [ 19 ]. For example, traditional clustering approaches look for the subsets of nodes, which are connected with their own subset more strongly than with other subsets. In our algorithm, we consider all the connections within a pattern (unlike [ 20 ], who considered only some connections within the pattern) but ignore the connections with neurons outside the pattern. One could question the expediency of ignoring multiple possible inputs to the neurons in a module since those inputs could influence the operation of that module. To counter this, we point out that if there were a particularly recurring way to attach an external connection to a given N -neuron motif then it would appear as an N + 1-neuron motif. If, on the other hand, the motif is connected in many different ways in different instances, their significance will be washed out. Thus our approach may hierarchically detect modules with recurring input/output sites, growing them out of smaller patterns. A second justification for looking at N -neuron patterns is that the nervous system is capable of performing many different functions under different circumstances and neurons active in one case may be silent in another. Therefore, in any particular case, many of the anatomical inputs to the module may remain silent and can safely be ignored. This speculation may be verified experimentally by simultaneous monitoring of neuronal activity in different neurons. The strategy and algorithms we described in this paper can be applied to incompletely mapped networks because a highly significant pattern is also likely to be over-represented in a sub-network. However, the statistical power of our algorithm increases with the knowledge of the wiring diagram. Therefore it was natural to choose the C. elegans nervous system, whose wiring diagram is largely known. Unfortunately, C. elegans has some disadvantages when it comes to the interpretation of the results: the polarity of a synapse (excitatory vs. inhibitory) in C. elegans is often unknown; electrophysiological investigations are still difficult in C. elegans [ 21 ]; and the whole network contains only 302 neurons, limiting the statistical power of the approach. Yet we hope that recent technological developments [ 22 ] will eliminate the first two disadvantages and allow functional analysis of the discovered modules. Moreover, we expect that our results have implications for understanding nervous system structure and function beyond C. elegans . The modules we identify in C. elegans may be a general property of the nervous system, and, once identified, can be searched for in other species. Finally, the algorithm itself can be applied to other networks [ 8 ] once they become available. As in any other theoretical analysis, we made several simplifications. For example, we assumed that the strength of synaptic connection between a pair of neurons is characterized by its multiplicity (i.e. the number of synapses between that pair). This assumption may be questioned if synapses implementing high-multiplicity connections are weaker than those implementing low-multiplicity connections, as known to happen in nematodes [ 23 ]. Yet, this assumption represents a reasonable first step in the systematic quantitative analysis, which may be extended in the future by estimating synaptic strength from the original EM reconstructions. In addition, we ignored the polarity of the synapses and the existence of gap junctions. Yet our results are robust to the inclusion of these factors in the future because if an over-represented class is found, it will remain over-represented even if divided into smaller sub-classes. It would be interesting to see whether the inclusion of the above factors will reveal specific over-represented sub-classes. Conclusions We have shown that certain neuronal connectivity patterns are significantly over-represented in the C. elegans nervous system. These patterns, called motifs, are candidates for computational modules that may perform stereotypical functions. It would be interesting to determine what these functions are and whether these motifs appear in other nervous systems. Methods Representation of the networks We transformed the C. elegans synaptic connectivity data into a binary matrix A , called Adjacency Matrix or Connectivity Matrix , in which an entry A ij is 1 if there is a connection from neuron i to neuron j and 0 otherwise. The order in which neurons are assigned to rows in this matrix is not important for our calculations. The multiplicity of synapses between two given neurons is mapped to a binary value by applying a threshold to the data. We assume a synaptic connection of threshold Θ from neuron i to neuron j if neuron i makes at least Θ synapses on to neuron j . Adjacency matrices that we used are available in the Supplementary Information [ Additional files 2 and 3 ]. Detecting & counting patterns We implemented two strategies for counting the number of triplets, quadruplets and quintuplets in a given connectivity matrix. First, to obtain the count of all N -neuron patterns, we took all different N -neuron subsets and characterized their connectivity. Second, we took all possible N -neuron subsets out of the neighborhood of a neuron x . This neighborhood is defined by all neurons that can be reached from x , if the directed connectivity matrix is made undirected. In both cases it is crucial for the run time of the algorithm to detect the pattern class from these connectivity sub-matrices as quickly as possible. We realized this by defining a function that maps each possible N -neuron sub-matrix to a unique integer value. Then we classified all the sub-matrices based on the function value and a pre-calculated lookup table, which identifies the pattern class from the function value. Creating random matrices The number of neurons that receive synaptic input from a given neuron x is called out-degree of x . The number of neurons providing synaptic input to neuron x is called in-degree of x . In the binary matrix representation of a network as described above, the out-degree of a neuron x can be calculated as the sum of row x , the in-degree as the sum of column x . N = 2. For the first step of our analysis we create random matrices that preserve the in-degree and out-degree of every neuron but change their connection partners. Starting with an empty matrix, our algorithm selects neurons in a random order and connects each with the required number of other neurons, chosen randomly out of the remaining neurons with in-degree and out-degree less than that in the C. elegans network. This choice of random matrices is motivated by the observation that the distribution of in-degrees and out-degrees in C. elegans is significantly different from Poisson, which is expected for a randomly generated matrix without any correlations (Erdõs-Rényi random graph) (Figure 7 ). N = 3. We keep the number of incoming and outgoing uni-directional connections as well as the number of reciprocal connections for each neuron the same. One of the implemented algorithms starts with an empty matrix. Then it randomly selects a neuron and does three things. It reconnects all outgoing connections of that neuron to other neurons, as long as their in-degree does not exceed that in the C. elegans network. It reconnects all incoming connections of that neuron to other neurons, as long as their out-degree does not exceed that in the C. elegans network. It reconnects all reciprocal connections of that neuron to other neurons with available unconnected reciprocal connections. We also implemented a second algorithm to verify the robustness of our results. This algorithm [ 9 , 10 ] will randomly pick and swap 2 unidirectional or 2 bi-directional connections (a→b and c→d will be changed to a→d and c→b). N = 4. For comparing the count of quadruplets, we construct random matrices that keep the same not only in-degree and out-degree of uni-directional and bi-directional connections for each neuron but also the count of the 16 different 3-neuron pattern in the whole matrix. Starting from a random matrix for N = 3 as described above, we use the Simulated Annealing algorithm [ 24 ] by swapping two connections of the same type until the count for all triplets in the random matrix matches the real network. Since this swapping operation does not change the degrees of the various connection types for the neuron, the algorithm only has to check if the triplet count in all 16 classes is identical to C. elegans . N = 5. For the analysis of the quintuplets, we modified the Simulated Annealing algorithm to match the count of all 4-neuron patterns to the real network. With this algorithm we could only find random matrices for which the relative difference between the count of each pattern in the random matrix and the real dataset was less than 10%. Coin-tossing example of multiple hypothesis testing correction Here we illustrate the issue of multiple hypothesis testing by considering a classical coin-tossing example. Imagine determining whether a given coin is fair (i.e. yielding heads with probability 1/2) or not by tossing it 100 times and recording the number of heads. If the number of heads is not too different from 50, we expect that the coin is fair. The significance of the deviation in the number of heads from 50 is characterized by the p -value, which is the probability that a fair coin would have that or greater deviation. For example, the probability of getting 62 or more heads is about 1% and the corresponding p -value = 0.01. Now consider testing simultaneously 100 different coins by tossing each 100 times. Analyzing these 100 experiments for outliers reveals that one coin yielded 62 heads. Does this mean that this specific coin is unfair? Not necessarily. Even if all the coins are fair, such a seemingly unlikely result will be observed approximately once when examining 100 coins. In other words, the p -value estimated for a single coin is an underestimation of the true p -value when 100 coins are examined simultaneously. This situation is called multiple hypotheses testing and requires a modification of the p -value definition. p -Value calculation/multi hypotheses testing correction Assume the number of N -neuron patterns in the i -th class in the actual network A and a random network R is given by: c N , i ( A ) and c N , i ( R ). Then the raw p -value is defined by: p i = Pr( c N , i ( R k ) ≥ c N , i ( A ), R k ∈ { R }). Because we look for over-representation of all connected patterns in parallel (and there are m = 13 patterns for N = 3, m = 199 patterns for N = 4 and m = 9364 patterns for N = 5), there is an increased probability of finding an over-represented pattern by chance. We correct for that by calculating a multiple hypothesis testing corrected p -value for each pattern and threshold. This p -value, P m , reflects the probability that one random matrix R k 0 out of our random matrix ensemble { R } will have at least one pattern, i , which has smaller (or equal) raw p -value than the given pattern in C. elegans . This is known as the single-step min P procedure and controls for family-wide error rate [ 16 , 17 ]. In mathematical notation the single-step min P adjusted p- values are defined by: where denotes the complete null hypothesis, p i the probability that the count for pattern i in a random matrix R is greater than the count in C. elegans , and P j denotes the raw p-value for the i th pattern in a random matrix k 0 : P j = Pr( c N , j ( R ) ≥ c N , j ( R k 0 )). To determine P m for a pattern i we perform the following procedure: 1. For all random matrices ( k 0 is the index of the random matrix; we usually created n = 1000 of them) out of the ensemble we calculate between and all other random matrices in this ensemble for each pattern i : . 2. We then derive the raw p -value for as a minimum of these values across all patterns i : . 3. We calculate the probability that for a given pattern i the observed count in a random matrix R k out of our ensemble { R } is greater than the count in the C. elegans network : 4. Last, we calculate the single-step min P adjusted p- value P m for a given pattern i as: In addition, we verified our results with the alternative single-step max T adjusted p-value [ 16 , 17 ] (for figures and explanations see Supplementary Information [ Additional file 1 ]). Datasets/data sources We used data from [ 6 ], which provides separate connectivity data for the different reconstructions JSH and N2U done by White et al. (1986). We deleted 11 non-neuronal cell or classes from the dataset: CEPshDR, CEPshVL, CEPshVR, GLRDL, GLRDR, GLRL, GLRR, GLRVL, GLRVR, hyp, mu_bod. The classification of the neurons into their function and their location was taken from [ 20 ]. Supplementary Material Additional File 1 A document containing supplementary information and data not presented in the paper. See also Click here for file Additional File 2 Description of the files containing triplet lists and used data sets. See also Click here for file Additional File 3 Zip file containing files mentioned in Additional file 2 Click here for file

/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539283.xml

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HIV-1 Tat Stimulates Transcription Complex Assembly through Recruitment of TBP in the Absence of TAFs

The human immunodeficiency virus type I (HIV-1) transactivator protein Tat is an unusual transcriptional activator that is thought to act solely by promoting RNA polymerase II processivity. Here we study the mechanism of Tat action by analyzing transcription complex (TC) assembly in vivo using chromatin immunoprecipitation assays. We find, unexpectedly, that like typical activators Tat dramatically stimulates TC assembly. Surprisingly, however, the TC formed on the HIV-1 long terminal repeat is atypical and contains TATA-box-binding protein (TBP) but not TBP-associated factors (TAFs). Tat function involves direct interaction with the cellular cofactor positive transcription elongation factor b (P-TEFb). Artificial tethering of P-TEFb subunits to HIV-1 promoter DNA or nascent RNA indicates that P-TEFb is responsible for directing assembly of a TC containing TBP but not TAFs. On the basis of this finding, we identify P-TEFb-dependent cellular promoters that also recruit TBP in the absence of TAFs. Thus, in mammalian cells transcription of protein-coding genes involves alternative TCs that differ by the presence or absence of TAFs.

Introduction In eukaryotes, gene regulation is largely controlled at the transcriptional level. Factors involved in the accurate transcription of eukaryotic structural genes by RNA polymerase II (class II genes) can be classified into two groups. First, general (or basic) transcription factors (GTFs) are necessary and can be sufficient for accurate transcription initiation in vitro (for review, see [ 1 ]). Such factors include RNA polymerase II itself and at least six GTFs: TFIID, TFIIA, TFIIB, TFIIE, TFIIF, and TFIIH. The GTFs assemble on the core promoter in an ordered fashion to form a transcription pre-initiation complex (PIC). The first step in PIC assembly is binding of the GTF TFIID to the TATA box. TFIID is a multi-subunit complex consisting of the TATA-box-binding protein (TBP) and a set of tightly bound TBP-associated factors (TAFs) [ 2 , 3 , 4 ]. Transcriptional activity is greatly stimulated by the second class of factors, promoter-specific activator proteins (activators). In general, cellular activators are sequence-specific DNA-binding proteins whose recognition sites are usually present in sequences upstream of the core promoter (reviewed in [ 5 , 6 ]). In addition to a sequence-specific DNA-binding domain, a typical activator also contains a separable activation domain. A variety of studies indicate that activators work, at least in part, by increasing PIC formation through a mechanism thought to involve direct interactions with one or more components of the transcription machinery [ 1 , 7 , 8 , 9 ]. Activators can also act through other mechanisms, such as increasing the rate of transcriptional elongation, promoting multiple rounds of transcription, and directing chromatin modifications (reviewed in [ 10 ]). The Tat protein of human immunodeficiency virus type I (HIV-1) is a potent activator of the viral long terminal repeat (LTR) and is required for viral replication (reviewed in [ 11 , 12 , 13 ]). Unlike typical activators, which bind to promoter DNA, Tat binds to nascent viral RNA through an RNA-binding site termed the TAR element. Tat function involves direct interaction with the cellular cofactor called positive transcription elongation factor b (P-TEFb), which is composed of two subunits, cyclin T1 (CycT1) and CDK9 (reviewed in [ 14 , 15 ]). Several lines of evidence have suggested that unlike typical activators, Tat stimulates transcriptional elongation rather than initiation. According to the current model (reviewed in [ 11 , 12 , 13 ]), in the absence of Tat, RNA polymerase II initiates from the HIV-1 LTR in a form unable to elongate efficiently and thus stalls (or pauses) near the transcription start site. When present, Tat binds to TAR and recruits P-TEFb, allowing CDK9 to phosphorylate the C-terminal domain of the RNA polymerase II large subunit, thereby increasing transcriptional processivity. The chromatin immunoprecipitation (ChIP) assay has provided a powerful approach to study in vivo the mechanism by which activators stimulate transcription and to delineate the composition of transcription complexes (TCs). In yeast, ChIP analysis has been used to show that activators function, at least in part, by stimulating TC assembly. These studies have also revealed that at certain promoters TBP is recruited in the absence of TAFs [ 16 , 17 ], indicating that, at least in yeast, some TCs contain TBP but not TFIID. Here we perform ChIP experiments to study the mechanism of transcription activation by Tat in vivo. Results Experimental Design To analyze transcription stimulation by Tat and other activators we performed ChIP experiments in transiently transfected mammalian tissue culture cells. Plasmids expressing a reporter construct, containing a core promoter and various combinations of activator-binding sites, were transiently transfected into HeLa or 293T cells. In some experiments, a second plasmid expressing an activator was co-transfected. Reporter activity or primer extension was used to quantitate transcription levels. TC assembly was analyzed by a ChIP assay using antibodies directed against components of four representative GTFs involved in distinct stages of TC assembly: TFIID (TBP and typically TAF1 and TAF5), TFIIB, mediator (CDK8 and hMed6), and RNA polymerase II (RBP1). In most experiments the analysis was performed using two sets of primers: one set encompassed the core promoter, transcription start site, and immediate downstream region, and a second set was located far downstream of the transcription start site, within the open reading frame (ORF). Diverse Activators Function by Increasing TC Assembly In yeast, it has been shown that activators stimulate TC assembly, which is evident at the earliest step of this process, interaction of TBP with the TATA box [ 18 , 19 ]. To confirm that this was also the case in mammalian cells, we used a ChIP assay to analyze TC assembly in three well-characterized model systems: transcription directed by Gal4-VP16, transcription directed by the SV40 enhancer, and transcription directed by the adenovirus (Ad) E1a protein. The artificial activator Gal4-VP16 contains an unusually potent acidic activation domain and can stimulate transcription in many species and cell types including mammalian tissue culture cells [ 5 ]. Figure 1 A shows, consistent with previous studies, that on a synthetic promoter containing four Gal4-binding sites upstream of the TATA box, transcription was not detectable in the absence of Gal4-VP16, whereas addition of Gal4-VP16 led to a large transcriptional increase. The accompanying ChIP assay shows that in the absence of Gal4-VP16 there was no detectable association of GTFs with the promoter. However, addition of Gal4-VP16 led to a large increase in recruitment of all GTFs analyzed, explaining the transcriptional stimulation. Consistent with the transcription results, RNA polymerase II was associated with the ORF in the presence but not absence of Gal4-VP16. Also, as expected, the GTFs were associated with the core promoter and not the ORF. Figure 1 Diverse Activators Function by Increasing TC Assembly (A) Gal4-VP16. Left: a CAT reporter construct containing the E1b core promoter and four Gal4-binding sites (G4E1bCAT) was transiently trans-fected into 293T cells, together with a plasmid expressing Gal4-VP16. Middle: transcription levels were determined by quantitating CAT reporter activity. Right: TC assembly was analyzed by a ChIP assay using the indicated antibodies. The percentage of DNA immunoprecipitated relative to input is indicated. The location of the primers used in the ChIP assay to analyze the promoter (black) or ORF (gray) is schematically shown on the left. (B) SV40 enhancer. Shown on the left is a schematic diagram of a construct containing a minimal rabbit β -globin promoter and harboring or lacking the SV40 enhancer. Also shown is transcription analysis by CAT assay (middle) and TC assembly (right) in transiently transfected HeLa cells. (C) Ad E1a. Left: a CAT reporter construct containing the Ad E4 promoter and upstream ATF-binding sites (E4CAT) was transiently transfected into HeLa cells, together with a plasmid expressing Ad E1a. Middle: transcription analysis by CAT assay is shown. Right: TC assembly is shown. Transcription of certain genes requires a cis- acting enhancer element that is often located at a distance from the transcription start site (reviewed in [ 20 ]). The enhancer functions by providing binding sites for cellular activators. For example, a minimal β-globin promoter is inefficiently expressed, but addition of an appropriate enhancer element dramatically increases transcription [ 21 ]. Figure 1 B shows, as expected, that a minimal rabbit β-globin promoter was virtually inactive, whereas transcriptional activity was greatly increased by addition of the SV40 enhancer. The ChIP analysis shows that in the absence of the SV40 enhancer there was no detectable association of GTFs with the β-globin promoter. Upon addition of the SV40 enhancer, there was a large increase in GTF recruitment that correlated with the increased transcriptional activity. Finally, we analyzed transcription directed by the Ad E1a protein. Efficient transcription from Ad early promoters requires the viral E1a protein as well as the participation of cellular transcription factors that also bind to the promoter (reviewed in [ 22 ]). For example, the Ad E4 promoter contains multiple binding sites for cellular ATF proteins, which are required for efficient transcription activation by E1a [ 23 ]. Figure 1 C shows, as expected, that in the absence of E1a there was only a background level of Ad E4 transcription, and that E1a increased transcription dramatically. The accompanying ChIP assay shows that in the absence of E1a there was no significant association of GTFs with the promoter, whereas transfection of E1a resulted in recruitment of all GTFs analyzed in a manner that paralleled the increased transcriptional activity. In summary, the results of Figure 1 indicate, as in yeast, that in three well-studied higher eukaryotic examples, transcription activation involves promotion of TC assembly. Moreover, as in yeast, the stimulatory effect is evident at the earliest step of TC assembly, the TBP– TATA box interaction. The HIV-1 Tat Protein Stimulates TC Assembly through Recruitment of TBP in the Absence of TAFs We next investigated Tat-mediated transcription activation and TC assembly on the HIV-1 LTR promoter. Figure 2 A shows, as expected, that in the absence of Tat there was no detectable transcription from the HIV-1 LTR, and that addition of Tat increased transcription dramatically. The accompanying ChIP experiment ( Figure 2 A, left) shows that in the absence of Tat, association of GTFs with the core promoter was virtually undetectable. Sp1, a constitutive cellular activator that binds upstream of the HIV-1 core promoter was, as expected, associated with the promoter in the absence of Tat and unaffected by Tat addition ( Figure 2 A, right). Significantly, in the absence of Tat there was no detectable association of RNA polymerase II near the transcription start site or within the ORF ( Figure 2 A, left). However, following addition of Tat, there was a large increase in association of TBP, TFIIB, mediator, and RNA polymerase II with the promoter, which paralleled the transcriptional increase. Also, as expected, there was a large increase in association of RNA polymerase II with the ORF. Following recruitment of P-TEFb to the HIV-1 LTR by Tat, P-TEFb associates with and phosphorylates RNA polymerase II [ 12 , 24 ]. Accordingly, the ChIP assay ( Figure 2 A, right) shows that in the presence of Tat the two P-TEFb subunits, CycT1 and CDK9, were present at both the promoter and the ORF. Unexpectedly, although TBP and the other GTFs were efficiently recruited to the promoter in the presence of Tat, there was no significant recruitment of the two TAFs analyzed, TAF1 or TAF5 (left panel). Figure 2 The HIV-1 Tat Protein Stimulates TC Assembly through Recruitment of TBP in the Absence of TAFs (A) A CAT reporter construct containing the TAR element and Sp1-binding sites ([−83]HIV LTRCAT) was transiently transfected into 293T cells, together with a plasmid expressing Tat. Left: transcription analysis by CAT assay is shown. Middle and right: TC assembly is shown. Bottom: a schematic diagram of the CAT reporter construct is shown. (B) TC assembly was monitored in a chronically HIV-1-infected cell line, 8E5/LAV, that harbors an integrated provirus that is constitutively transcribed. Virus production was confirmed by analysis of p24 levels and reverse transcriptase activity in the culture medium (data not shown). (C) TC assembly was monitored in the chronically infected cell line U1 on the integrated HIV-1 LTR in the presence or absence of PMA. We note that recruitment of Tat was not observed in the ChIP assay, which detects proteins bound either directly or indirectly to DNA (reviewed in [ 25 ]). Unlike all the other transcription factors, which associate with the TC through DNA–protein or protein–protein interactions, Tat is bound to nascent RNA [ 11 , 12 , 13 ]. To determine whether the lack of TAF recruitment was a general feature of Tat-directed transcription, we analyzed a chronically HIV-1-infected cell line, 8E5/LAV, which harbors an integrated provirus that is constitutively transcribed [ 26 ]. Figure 2 B shows that TBP, TFIIB, mediator, Sp1, P-TEFb, and RNA polymerase II, but not TAF1 or TAF5, were associated with the integrated proviral promoter, consistent with the results of the transient transfection assay. We also analyzed a second chronically HIV-1-infected cell line, U1, which has been used as a model to study viral latency. U1 cells harbor an integrated viral genome, but, unlike 8E5/LAV cells, the constitutive level of viral expression is extremely low. Viral expression can be induced by phorbol esters, which stimulate transcription through upstream NF-κB-binding sites in the HIV-1 LTR, leading to Tat synthesis and a subsequent substantial Tat-mediated transcriptional increase [ 27 , 28 ]. Thus, U1 cells provide an experimental system to analyze TC assembly from an integrated HIV-1 LTR in the inactive (−PMA) or active (+PMA) state. Figure 2 C shows that following activation of the HIV-1 LTR by PMA addition, there was a large increase in recruitment of TBP and RNA polymerase II, whereas TAF1 and TAF5 were once again not detected. To investigate further the composition of the TC formed on the HIV-1 LTR, we obtained a panel of antibodies directed against nine additional human TAFs (TAF2, TAF4, TAF6, TAF7, TAF8, TAF9, TAF11, TAF12, and TAF13), as well as antibodies against four subunits of the S TAGA complex (PAF65β, hSpt3, hGCN5, and TRRAP) and the TBP-interacting protein Mot1. The results ( Figure 3 A) show that when transcription was directed by Gal4-VP16, all 11 TAFs analyzed were bound to the promoter, as expected for recruitment of TFIID. By contrast, when transcription was directed by Tat, none of the 11 TAFs were recruited to the HIV-1 LTR. Gal4-VP16 also recruited all four S TAGA subunits analyzed, none of which were associated with the HIV-1 LTR in the presence of Tat. Finally, Mot1 was not recruited when transcription was directed by either Gal4-VP16 or Tat. On the basis of these data we conclude that the TC formed on the HIV-1 LTR lacks at least 11, and probably all, of the 14 TFIID TAFs. In the experiments presented below, TAF1 and TAF5 were analyzed as representative TAFs. Figure 3 TAFs Are Not Recruited to the HIV 1-LTR and Not Required by Tat for Transcription Activation (A) TC assembly was analyzed by a ChIP assay using antibodies directed against nine additional human TAFs, four subunits of the S TAGA complex, and Mot1. TAFs that are also present in S TAGA are indicated by asterisks. Bottom: schematic diagrams of the promoter constructs are shown. (B) Transcription analysis in ts13 cells, which harbor a temperature-sensitive mutation in TAF1. Ts13 cells grown at the permissive or non-permissive temperature were transiently transfected with a luciferase reporter plasmid and a plasmid expressing a transcriptional activator. Transcription was monitored by luciferase activity, and normalized relative to activity at the permissive temperature. (C) Left: immunoblot analysis is shown. 293A cells were transfected with a TAF5 or TAF12 shRNA expression vector or an empty vector (control) and analyzed by immunoblotting using the indicated antibodies. Right: transcription levels were monitored by luciferase reporter activity in shRNA-treated cells, and normalized relative to luciferase activity in non-shRNA-treated cells. TAFs Are Not Required for Tat-Mediated Transcription Activation The results of the ChIP experiments strongly suggested that transcription activation by Tat did not require TAFs. To confirm this supposition, we examined the ability of Tat to stimulate transcription following TAF inactivation. First, we examined the ability of Tat to activate transcription in ts13 cells, which harbor a temperature-sensitive mutation in TAF1 [ 29 , 30 ]. Figure 3 B shows, as expected, that inactivation of TAF1 significantly diminished transcription activation by VP16 and E1a, whereas Tat-mediated transcription activation was unaffected. In a second approach, we used short hairpin RNAs (shRNAs) to knockdown expression of TAF5 or TAF12 in 293A cells. Immunoblot analysis confirmed that shRNA-mediated knockdown of TAF expression was efficient and specific ( Figure 3 C, left). Transcriptional analysis revealed that knockdown of TAF5 or TAF12 substantially decreased transcription directed by VP16, whereas Tat-mediated transcription activation was unaffected ( Figure 3 C, right). (Because 293A cells are transformed by and express E1a, activation by E1a could not be analyzed in this experiment.) Collectively, the results of Figure 3 demonstrate that TAFs are not involved in transcription activation directed by the HIV-1 Tat protein. Tat and P-TEFb Direct Recruitment of TBP in the Absence of TAFs The results described above indicate that on the HIV-1 LTR transcription activation involves assembly of an atypical TC that contains TBP but not TAFs. However, these experiments do not distinguish whether the critical determinant for recruitment of TBP and not TFIID is Tat or the promoter, the HIV-1 LTR. To address this issue we performed a series of artificial tethering experiments. Previous studies have shown that Tat can activate transcription when directed to the HIV-1 LTR through a heterologous DNA-binding domain [ 31 , 32 , 33 ]. We analyzed TC assembly using an HIV-1 LTR derivative that lacked the TAR element and contained upstream Gal4-binding sites. We first examined the TCs formed on this promoter by three Gal4 fusion proteins: Gal4-VP16, Gal4-E1a, and Gal4-Tat. Consistent with previous studies [ 32 ], Figure 4 shows that all three Gal4 fusion proteins activated transcription from this modified HIV-1 LTR derivative. The accompanying ChIP experiments show that Gal4-VP16 and Gal4-E1a supported assembly of a TC that contained all of the GTFs, including TAF1 and TAF5. By contrast, Gal4-Tat directed assembly of a TC in which the TAFs were present at a level significantly below that of TBP and other GTFs. These results indicate that the activator Tat, and not the HIV-1 LTR promoter, directs the selective recruitment of TBP in the absence of TAFs. Figure 4 Tat and P-TEFb Direct Recruitment of TBP in the Absence of TAFs When Tethered to DNA Transcription (left) and TC assembly (right) were examined using an HIV-1 LTR derivative that lacks the TAR element and contains upstream Gal4-binding sites (G6[−83]HIV LTRΔTARCAT; bottom) and a series of Gal4 fusion proteins, as indicated. As discussed above, Tat interacts directly with CycT1, a subunit of the transcription elongation factor P-TEFb. Thus, Tat is an adaptor whose function is to recruit P-TEFb. We therefore considered that P-TEFb was ultimately responsible for the selective recruitment of TBP in the absence of TAFs. To address this possibility, we analyzed transcription activation by the two P-TEFb subunits, CycT1 and CDK9. Consistent with previous results [ 34 , 35 ], both Gal4-CycT1 and Gal4-CDK9 activated transcription. The ChIP analysis indicates that both Gal4-CycT1 and Gal4-CDK9 stimulated assembly of a TC that contained all of the GTFs but lacked TAF1 and TAF5. These results confirm that P-TEFb is responsible for directing selective recruitment of TBP in the absence of TAFs. In the experiments shown in Figure 4 , P-TEFb was tethered to DNA, whereas on the HIV-1 LTR, P-TEFb is normally bound through Tat to nascent RNA. We therefore sought to verify that P-TEFb, when bound to nascent RNA, would also selectively recruit TBP in the absence of TAFs. Previous studies have shown that recruitment of CycT1/P-TEFb to the HIV-1 LTR through a heterologous RNA-binding domain can activate transcription in the absence of Tat [ 36 ]. We therefore asked whether such an artificially recruited CycT1/P-TEFb protein would stimulate assembly of a TC that contained TBP but not TAFs. We used a previously characterized HIV-1 LTR derivative [ 36 ] in which the TAR element was replaced by a minimal binding site for the HIV-1 Rev protein, and examined the ability of a Rev-Tat or Rev-CycT1 fusion protein to stimulate TC assembly. Figure 5 shows that in the absence of a Rev fusion protein, both transcription and GTF recruitment were virtually undetectable. Addition of Rev-Tat or Rev-CycT1 resulted in a large transcriptional increase, as expected from previous studies. Significantly, addition of Rev-Tat or Rev-CycT1 also led to a large increase in recruitment of TBP, TFIIB, mediator, and RNA polymerase II, but not TAF1 or TAF5. Thus, in the absence of Tat, Rev-CycT1 stimulated assembly of a TC that contained TBP but not TAFs. Figure 5 Tat and P-TEFb Direct Recruitment of TBP in the Absence of TAFs When Tethered to RNA Transcription (left) and TC assembly (right) were examined using a Rev-Tat or Rev-CycT1 fusion protein and an HIV-1 LTR derivative in which the TAR element was replaced by stem loop IIB (SLIIB), a Rev-protein-binding site (HIV SLIIBCAT; bottom). Identification of Cellular Promoters That Recruit TBP in the Absence of TAFs P-TEFb is also a cofactor for several cellular activators, the best studied of which is CIITA, a transcription factor involved in the expression of major histocompatibility complex (MHC) class II genes (reviewed in [ 37 ]). In fact, overexpression of Tat can inhibit transcription of MHC class II genes by competing with CIITA for P-TEFb binding [ 38 , 39 ]. We therefore tested whether the promoters of MHC class II genes also recruited an atypical TC that contained TBP but not TAFs. We analyzed two MHC class II genes known to use CIITA, HLA-DM and HLA-DR, and, as a negative control, GAPDH . RT-PCR analysis confirmed, as expected, that both HLA-DM and HLA-DR were expressed in 293T cells (data not shown). The associated ChIP experiment ( Figure 6 ) shows that the TCs formed on both HLA-DM and HLA-DR contained all of the GTFs but lacked significant levels of TAF1 and TAF5. By contrast, the TC formed on GAPDH contained all of the GTFs, including TAF1 and TAF5. These results indicate that TBP, and not TFIID, is also selectively recruited to specific cellular promoters and strongly support the conclusion that P-TEFb directs this recruitment. Figure 6 The Cellular Activator CIITA Directs Recruitment of TBP in the Absence of TAFs TC assembly was monitored on the promoters of HLA-DM and HLA-DR, two MHC class II genes known to use CIITA, and, as a negative control, GAPDH . Discussion A variety of studies have proposed that Tat promotes transcriptional elongation [ 11 , 12 , 13 ]. However, the effect of Tat on TC assembly in vivo has not been previously analyzed. In this report, we studied the mechanism of Tat action using ChIP assays and found, unexpectedly, that Tat dramatically stimulates TC assembly on the HIV-1 LTR. Perhaps most surprising, the HIV-1 LTR contains an atypical TC that lacks TFIID and that has not been previously described in mammalian cells. By contrast, transcription activation by Gal4-VP16, the SV40 enhancer, or the Ad E1a protein involves assembly of a TC that contains TFIID. Thus, our results reveal mechanistic similarities between apparently diverse classes of activators and unanticipated differences in the composition of mammalian TCs. In an HIV-1-infected cell, a low level of Tat-independent transcription can be elicited by cellular activators, such as Sp1, NF-κB, and NFAT, which are bound to upstream regions of the HIV-1 LTR [ 12 ]. Tat is recruited to the vicinity of the promoter by binding to this low level of nascent TAR RNA, where it facilitates subsequent rounds of TC assembly and transcription initiation. Thus, once a threshold level of transcription is achieved, Tat stimulates additional transcription, thereby increasing the number of Tat-binding sites (reviewed in [ 40 ]). This positive feedback mechanism would ensure that viral transcription rapidly increases or decreases, which may be relevant to the ability of HIV-1 to enter latency and, conversely, to be activated from the latent state. Tat Stimulates TC Assembly Previous studies have provided two principal lines of evidence that Tat functions by stimulating transcription elongation. First, Tat has been found to stimulate elongation in an in vivo nuclear run-off assay [ 41 , 42 , 43 , 44 ], and in the absence of Tat, apparent prematurely terminated transcripts have been detected [ 41 , 45 ]. However, these in vivo results are complicated by the presence of a second promoter, the initiator of short transcripts, adjacent to the HIV-1 LTR [ 46 , 47 ]. In our experiments RNA polymerase II was not detected either near or far downstream of the transcription start site in the absence of Tat and thus provided no evidence for a paused (or stalled) RNA polymerase II. Consistent with our ChIP data, nuclear run-off experiments have shown that Tat increases the density of RNA polymerase II 9- to 15-fold within the first 25 nucleotides downstream of the transcription start site [ 42 , 43 ], indicating that Tat also stimulates initiation. A second line of evidence has been derived from in vitro experiments in which Tat was found to enhance elongation but not initiation (see, for example, [ 48 ]). However, in vitro transcription experiments may fail to faithfully recapitulate in vivo regulation: for example, under in vitro conditions using naked DNA templates, PIC assembly and initiation may no longer be rate-limiting on the HIV-1 LTR. Consistent with this possibility, the HIV-1 LTR is a relatively strong promoter when analyzed as naked DNA in vitro in the absence of Tat (see, for example, [ 49 ]). Moreover, initiation effects would not be observed if the cell-free system did not support multiple rounds of transcription from a single DNA template (see, for example, [ 50 ]). It is important to emphasize that our ChIP assay only analyzed TC assembly. Thus, our results do not rule out the possibility that in addition to stimulating TC assembly, Tat also promotes transcription elongation. Based upon the results presented here and previous studies (reviewed in [ 11 , 12 , 13 ]), we believe that Tat stimulates TC assembly, thereby promoting initiation and elongation. This dual mechanism of action may explain why Tat is such a potent activator of transcription. Tat and P-TEFb Direct Recruitment of TBP in the Absence of TAFs We have shown that transcription from the HIV-1 LTR involves TBP but not TFIID. This result was particularly unexpected because in mammalian cells TBP is bound to TAFs extremely tightly and numerous biochemical studies have failed to find free TBP [ 2 , 3 , 4 ]. None of the 11 TAFs, four S TAGA subunits, or Mot1 was present on the HIV-1 LTR, strongly suggesting that free TBP is recruited. However, we cannot exclude the possibility that TBP may be associated with unknown proteins that remain to be identified. Several considerations rule out the possibility that TFIID is actually present in the TC directed by Tat/P-TEFb but that the TAFs are not detected in the ChIP assay. First, numerous studies have shown ChIP to be a remarkably general and robust assay that has successfully detected a wide variety of activators, general initiation and elongation components, chromatin remodeling factors, and histone variants. Second, in experiments not involving Tat or P-TEFb, TAFs were detected at levels comparable to that of TBP on five different promoters (G4E1bCAT, β-globin , E4CAT, G6(−83)HIV LTRΔTARCAT, and GAPDH ). Third, when TC assembly was directed by Tat or P-TEFb the ChIP assay detected all GTFs analyzed, including TBP, but not TAFs on six different promoters ([−83]HIV LTRCAT, integrated HIV-1/LAV, HIV SLIIBCAT, G6[−83]HIV LTRΔTARCAT, HLA-DM , and HLA-DR ]. Finally, and perhaps most persuasively, on the same promoter the presence or absence of TAFs as monitored by ChIP was dictated solely by the upstream bound Gal4 fusion protein (see Figure 4 ). Artificial tethering experiments clearly demonstrate that P-TEFb directs recruitment of TBP in the absence of TAFs. Strongly supporting this conclusion is our identification of cellular promoters for which P-TEFb is a cofactor and whose TC contains TBP but not TAFs. How P-TEFb selectively recruits TBP and not TFIID remains to be determined. It has been previously thought that P-TEFb is purely an elongation factor [ 14 , 15 ]. However, we have shown that when tethered to DNA or nascent RNA, P-TEFb can also stimulate TC assembly and dictate the composition of the TC. In yeast, promoters have been grouped into two extreme classes based on their requirement for TAFs [ 16 , 17 ]. TAF-dependent promoters require TAFs for transcription, and on these promoters TBP and TAFs are present at comparable levels. TAF-independent promoters do not require TAFs for activity, and on these promoters TAFs are either absent or present at levels far below that of TBP. These yeast results are strikingly similar to the findings reported here, and taken together these results indicate that in both yeast and mammalian cells, transcription of protein-coding genes involves alternative TCs that differ by the presence or absence of TAFs. Materials and Methods Plasmids To generate the G4E1bCAT construct, pDSG39, four Gal4-binding sites were inserted upstream of the E1b TATA box and the CAT ORF in the vector pSP72 (Promega, Madison, Wisconsin, United States). The β-globin constructs containing (pBS) or lacking (pB/E) the SV40 enhancer were provided by Walter Schaffner; pBS contains a 196-bp SV40 enhancer–containing fragment inserted into a plasmid derived from pB6 [ 51 ], which harbors the β-globin gene. The E4CAT construct, pE4CAT, was previously described [ 52 ]. The pFR-Luc plasmid, containing five Gal4-binding sites upstream of the E1b TATA box and the luciferase reporter gene, was obtained from Stratagene (La Jolla, California, United States). The HIV LTR-luciferase construct was previously described [ 53 ]. The (−83)HIV LTRCAT and G6(−83)HIV LTRΔTARCAT constructs, were previously described [ 54 ]. The HIV SLIIBCAT construct, pHIV/SLIIB/CAT [ 36 ], was provided by Bryan Cullen. Plasmids expressing the Gal4-VP16 fusion protein (pGal4-VP16; [ 55 ]), E1a (pSV-E1a; [ 52 ]), Tat (CMV-Tat; [ 56 ]), and the Gal4-E1a fusion protein (pGal4-E1a; [ 52 ]) were previously described. To generate pGal4-Tat, pGal4-CycT1, and pGal4-CDK9, the full-length Tat protein, the hCycT1-containing EcoR1 fragment from phCycT1-Rev [ 36 ], or the CDK9-containing EcoR1 fragment from pSG5-CDK9 (a gift from Claude Gazin), respectively, were individually cloned into plasmid pSG424 [ 55 ] as an in-frame fusion with the Gal4 DNA-binding domain. Rev fusion-protein plasmids pTAT-Rev and phCycT1-Rev [ 36 ] were obtained from Bryan Cullen. Antibodies The α-Gal4 mouse monoclonal (sc-510), α-CDK8 goat polyclonal (sc-1521), α-CDK9 goat polyclonal (sc-7331), α-CycT1 goat polyclonal (sc-8127), α-Med6 goat polyclonal (sc-9434), α-GCN5 goat polyclonal (sc-6303); α-TRRAP rabbit polyclonal (sc-11411), α-TAF1 mouse monoclonal (sc-735), α-TAF5 mouse monoclonal (sc-743), α-Sp1 rabbit polyclonal (sc-59X), and α-alpha tubulin mouse monoclonal (sc-5268) antibodies were obtained from Santa Cruz Biotechnology (Santa Cruz, California, United States). The α-RNA polymerase II mouse monoclonal antibody (8WG16) was obtained from BAbCO (Berkeley, California, United States). The α-Tat rabbit antiserum was obtained from the National Institutes of Health AIDS Research and Reference Reagent Program (catalog number 705; [ 57 ]). The α-TBP mouse monoclonal antibody (SL30–3-563) was provided by Nouria Hernandez; the α-TAF2, α-TAF4, α-TAF6, α-TAF7, α-TAF8, α-TAF9, α-TAF11, α-TAF12, α-TAF13, and α-hSpt3 rabbit polyclonal antibodies were provided by Robert Roeder; the α-Mot1 rabbit polyclonal antibody was provided by Franklin Pugh; and the α-PAF65β rabbit polyclonal antibody was provided by Yoshihiro Nakatani. Transcription Transcription was measured either by RT-PCR analysis from total RNA isolated from transfected cells or by chloramphenicol acetyl transferase (CAT) assay [ 58 ] using 14 C chloramphenicol followed by thin layer chromatography. Signals were visualized by autoradiography and quantitated using National Institutes of Health Image 1.62 software. ChIP assay HeLa and 293T cells were transfected with 10 μg of effector plasmids and 5 μg of reporter plasmid using standard CaCl 2 transfection methods [ 59 ]. Forty-eight hours after transfection, cells were cross-linked by adding formaldehyde to the medium (1% final concentration) and incubated for 10 min at room temperature. The cross-linking reaction was quenched by adding glycine to a final concentration of 0.125 M and incubating for an additional 10 min at room temperature. Cells were then washed with ice-cold PBS containing protease inhibitors, scraped in the same buffer, and washed in PBS. Cells were then lysed in SDS-lysis buffer (1% SDS, 50 mM Tris-HCl [pH 8.0], 10 mM EDTA, and protease inhibitors), and sonicated at least 6–8 times at output 8 for 10 s, with 2 min incubation on ice in between. Lysates were centrifuged at 15,000 rpm for 15 min at 4 °C; 5% of the lysates were kept as input. Lysates were diluted 10-fold with ChIP dilution buffer (0.01% SDS, 1.1% Triton X-100, 1.2 mM EDTA, 16.7 mM Tris-HCl [pH 8.0], 16.7 mM NaCl, and protease inhibitors) and pre-cleared with 80 μl of Protein A Agarose-50% Slurry (Upstate Biotechnology, Lake Placid, New York, United States) for 30 min at 4 °C with constant agitation. The agarose beads were pelleted, and the supernatant was incubated overnight with the primary antibody. To each tube, 50 μl of Salmon Sperm DNA/Protein A Agarose-50% Slurry (Upstate Biotechnology) was added, and the mixture was incubated for 1 h at 4 °C. The agarose beads were pelleted by gentle centrifugation, the supernatant was removed, and the pellet was washed twice with low-salt immune complex wash buffer (0.1% SDS, 1% Triton X-100, 2 mM EDTA, 20 mM Tris-HCl [pH 8.0], and 150 mM NaCl), once with high-salt immune complex wash buffer (0.1% SDS, 1% Triton X-100, 2 mM EDTA, 20 mM Tris-HCl [pH 8.0], and 500 mM NaCl), once with LiCl immune complex wash buffer (0.25 M LiCl, 1% NP40, 1% C 24 H 39 NaO 4 , 1 mM EDTA, and 10 mM Tris-HCl [pH 8.0]), and twice with TE (10 mM Tris-HCl [pH 8.0] and 1 mM EDTA). Chromatin was eluted with freshly prepared elution buffer (1% SDS and 0.1 M CHNaO 3 ). After reversal of the cross-links, the samples were treated with proteinase K for 1 h at 45 °C, extracted by phenol/chloroform, and ethanol precipitated. The pellet was resuspended in TE, and PCR was performed. Autoradiograms were scanned and quantitated by the National Institutes of Health ImageJ program. IP DNA was quantitated and presented as the ratio of IP to input. Primer sequences are available upon request. TAF inactivation For TAF1 inactivation, ts13 cells [ 60 ] were initially cultured at the permissive temperature (33 °C), after which one set of 6-well plates was shifted to the non-permissive temperature (39.5 °C) while another set was kept at 33 °C. Sixteen hours later, cells were co-transfected with a plasmid expressing a transcriptional activator (Gal4-VP16, E1a, or Tat) and a luciferase reporter plasmid, and incubated further for 24 h prior to measuring transcription by luciferase assay. For shRNA-mediated inactivation of TAFs, 293A cells were transfected with either pcDNA3 (Invitrogen, Carlsbad, California, United States) or a TAF5 or TAF12 shRNA expression vector (Open Biosystems, Huntsville, Alabama, United States), and 18 h later were co-transfected with effector and reporter plasmids. Transcription activation was monitored by luciferase activity 24 h following transfection. Supporting Information Accession Numbers The LocusLink ( http://www.ncbi.nlm.nih.gov/LocusLink/ ) accession numbers for the genes and gene products discussed in this paper are CDK8 (1024), CDK9 (1025), CIITA (4261), CycT1 (904), GAPDH (2597), hGCN5 (2648), HLA-DM (3109), HLA-DR (3122), hSpt3 (8464), MED6 (10001), Mot1 (9044), PAF65β (27097), RBP1 (5430), TAF1 (6872), TAF11 (6882), TAF12 (6883), TAF13 (6884), TAF2 (6873), TAF4 (6874), TAF5 (6877), TAF6 (6878), TAF7 (6979), TAF8 (129685), TAF9 (6880), Tat (155871), TBP (6908), TFIIB (2959), and TRRAP (8295).

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539297

Membrane trafficking and mitochondrial abnormalities precede subunit c deposition in a cerebellar cell model of juvenile neuronal ceroid lipofuscinosis

Background JNCL is a recessively inherited, childhood-onset neurodegenerative disease most-commonly caused by a ~1 kb CLN3 mutation. The resulting loss of battenin activity leads to deposition of mitochondrial ATP synthase, subunit c and a specific loss of CNS neurons. We previously generated Cln3 Δex7/8 knock-in mice, which replicate the common JNCL mutation, express mutant battenin and display JNCL-like pathology. Results To elucidate the consequences of the common JNCL mutation in neuronal cells, we used P4 knock-in mouse cerebella to establish conditionally immortalized Cb Cln3 wild-type, heterozygous, and homozygous neuronal precursor cell lines, which can be differentiated into MAP-2 and NeuN-positive, neuron-like cells. Homozygous Cb Cln3 Δex7/8 precursor cells express low levels of mutant battenin and, when aged at confluency, accumulate ATPase subunit c. Recessive phenotypes are also observed at sub-confluent growth; cathepsin D transport and processing are altered, although enzyme activity is not significantly affected, lysosomal size and distribution are altered, and endocytosis is reduced. In addition, mitochondria are abnormally elongated, cellular ATP levels are decreased, and survival following oxidative stress is reduced. Conclusions These findings reveal that battenin is required for intracellular membrane trafficking and mitochondrial function. Moreover, these deficiencies are likely to be early events in the JNCL disease process and may particularly impact neuronal survival.

Background Juvenile neuronal ceroid lipofuscinosis (JNCL), or Batten disease, is a recessively inherited childhood-onset neurodegenerative disorder characterized by progressive blindness, seizures, motor and cognitive decline, and early death [ 1 ]. The primary genetic defect (>80% disease chromosomes) leading to JNCL is a 1.02 kb genomic DNA deletion in the CLN3 gene, which eliminates exons 7 and 8 and surrounding intronic DNA, predicting a non-functional protein product [ 2 ]. The pathological hallmark of JNCL is autofluorescent ceroid lipofuscin deposits within autolysosomes that are enriched in subunit c of the mitochondrial ATP synthase complex [ 3 - 5 ]. Remarkably, these deposits are not only found in CNS neurons but are also abundant in non-neuronal cells outside of the nervous system. The relationship of subunit c deposits to the JNCL disease process, and the underlying reason for the neuronal specificity of the disease remain poorly understood. The CLN3 -encoded protein (battenin, also called CLN3 or cln3 p) is a highly conserved, ubiquitously expressed, multi-pass membrane protein [ 6 ] that localizes to the lysosome and other vesicular compartments [ 7 - 9 ]. Battenin function remains to be elucidated, although studies of btn1 , the yeast CLN3 ortholog, have implicated battenin in lysosomal pH homeostasis and amino acid transport [ 10 , 11 ]. To explore JNCL pathogenesis and battenin function, we previously generated a genetically precise JNCL mouse model. Cln3 Δex7/8 knock-in mice harbor the ~1 kb common JNCL mutation and express a non-truncated mutant battenin isoform that is detectable with antibodies recognizing C-terminal epitopes. Homozygous Cln3 Δex7/8 knock-in mice exhibit a progressive JNCL-like disease, with perinatal onset of subunit c deposition in many cell types and later onset of neuronal dysfunction and behavioral deficits [ 12 ]. These findings suggest that the major JNCL defect leads to abnormal turnover of mitochondrial subunit c, in a manner that selectively compromises CNS neurons. Currently, there is no suitable neuronal cell system to investigate the impact of the common JNCL mutation on biological processes. Therefore, we have established cerebellar neuronal precursor cell lines from Cln3 Δex7/8 knock-in mice. Homozygous Cb Cln3 Δex7/8 cells exhibit pathological hallmarks of the disease, and a survey of membrane organelles revealed membrane trafficking defects and mitochondrial dysfunction in homozygous mutant Cb Cln3 Δex7/8 cells. Results Generation of a genetically precise cerebellar JNCL cell model To generate a precise genetic, neuron-derived JNCL cell culture system, we immortalized granule neurons cultured from postnatal day 4 (P4) cerebella of homozygous and heterozygous Cln3 Δex7/8 knock-in mice, and wild-type littermates. Primary cell cultures enriched for granule neurons were transduced with retroviral vector bearing a selection cassette and temperature-sensitive tsA58 SV40 large T antigen. Growth in G418 containing medium at the permissive temperature (33°C) allowed for selection and isolation of multiple clonal nestin-positive (Fig. 1a ), and GFAP-negative (Fig. 1b ), cell lines for each genotype. No genotype specific differences were observed in cellular morphology or doubling time (~46 hours) (data not shown). As expected, SV40 large T antigen expression was rapidly lost and cell division ceased when cells were shifted to the non-permissive temperature (39°C) (data not shown). Upon addition of neuronal differentiation cocktail, precursor cells became neuron-like in morphology and exhibited decreased nestin expression (data not shown) and increased MAP2 and NeuN expression (Fig. 1c,1d ), but not expression of the Purkinje marker, calbindin (Fig. 1e ). Figure 1 Neuronal marker expression in Cb Cln3 +/+ cells Characterization of Cb Cln3 +/+ cells by immunofluorescence with marker antibodies is shown. Cb Cln3 +/+ precursors exhibit nestin expression (a) but not GFAP expression (b), consistent with a neuronal precursor identity. Upon stimulation with a differentiation cocktail (see Methods), Cb Cln3 +/+ cells achieved neuron-like morphology, with rounded cell bodies and extension of processes, and MAP2 (c) and NeuN (d) expression was increased. Cb Cln3 +/+ cells are negative for the Purkinje neuron marker calbindin (e). Cb Cln3 +/Δex7/8 and Cb Cln3 Δex7/8/Δex7/8 cell lines exhibited identical marker immunofluorescence results. a, b) 20 × magnification; c, d, e) 40 × magnification. Homozygous Cb Cln3 Δex7/8 cells express mutant battenin and display JNCL-like pathology Homozygous Cb Cln3 Δex7/8 cells were first examined for JNCL-like characteristics. Homozygous Cln3 Δex7/8 knock-in mice express multiple Cln3 mRNA splice variants and mutant battenin protein that is detectable by batp1 antibody recognizing C-terminal epitopes [ 12 ]. To assess this molecular phenotype in Cb Cln3 Δex7/8 cells, RT-PCR and anti-battenin (batp1) immunostaining were performed. As shown in Figure 2 , Cln3 mRNA isoforms in wild-type and homozygous cells were similar to those observed in total RNA isolated from wild-type or homozygous Cln3 Δex7/8 knock-in brain, respectively (Fig. 2 ). In addition, batp1 immunostaining detected mutant battenin product in homozygous Cb Cln3 Δex7/8 cells, in a similar albeit reduced cytoplasmic, vesicular staining pattern as that seen in wild-type cells. Batp1 signal exhibited some overlap with the lysosomal marker, Lamp1, but had more significant overlap with early endosome antigen 1 (EEA1) and the late endosomal marker, Rab7 (Fig. 3 ). Only limited overlap was observed with recycling endosomes, as determined by transferrin receptor co-staining (data not shown). Intriguingly, Lamp1 and EEA1 immunocytochemical distribution were altered in homozygous Cb Cln3 Δex7/8 cells, with less perinuclear clustering than in wild-type cells, and Rab7 staining was frequently less intense in homozygous Cb Cln3 Δex7/8 cells (Fig. 3 ). Heterozygous Cb Cln3 Δex7/8 cells contained a mixture of Cln3 mRNA products from both the wild-type allele and the mutant allele, and batp1 signal was similar to that seen in wild-type cells (data not shown). Figure 2 RT-PCR of Cln3 mRNA in wild-type and homozygous Cb Cln3 Δex7/8 cells Cln3 Exon1-forward, Exon 15-reverse RT-PCR products are shown, from total wild-type (+/+) or homozygous mutant (Δex7/8/Δex7/8) brain and cell line RNA. Brain and cell line RT-PCR reaction products had identical band patterns on ethidium-bromide stained agarose gels. Wild-type RT-PCR product was a single ~1.6 kb band and mutant products were ~1.6, ~1.5, ~1.4, ~1.35, and ~1.3 kb, representing multiple mutant splice variants. Figure 3 Battenin and lysosomal and endosomal marker co-staining in wild-type and homozygous Cb Cln3 Δex7/8 cerebellar precursor cells Batp1 immunostaining of wild-type (Cb Cln3 +/+ ) and homozygous mutant (Cb Cln3 Δex7/8/Δex7/8 ) cerebellar precursor cells is shown, with co-staining for lysosomes (Lamp 1), early endosomes (EEA1), and late endosomes (Rab7). Significant overlap of Batp1 signal (red) with EEA1 (green, middle panels) and Rab7 (green, bottom panels) can be seen as yellow when the two channels are merged (Merge). The degree of Batp1 overlap is greatest with Rab7. Only limited overlap between Batp1 (red) and Lamp 1 (green, top panels) can be seen. Batp1 signal in homozygous Cb Cln3 Δex7/8 cells is significantly reduced, but significant overlap with EEA1 and Rab7, and very little Lamp 1 overlap, can be seen as yellow in the respective merged panels. Notably, Lamp 1 and EEA1 localization appear altered, and Rab7 staining was frequently less intense in homozygous Cb Cln3 Δex7/8 cells. Wild-type and homozygous Cb Cln3 Δex7/8 confocal images were captured with identical exposure settings. 60 × magnification. During sub-confluent growth conditions, neither wild-type nor homozygous Cb Cln3 Δex7/8 cells displayed autofluorescence or subunit c inclusion formation (data not shown). However, when cells were aged at confluency (3+ days post-confluency), homozygous Cb Cln3 Δex7/8 cellular subunit c levels were elevated beyond normal wild-type levels by immunostaining (Fig. 4a ) and immunoblot analysis (Fig. 4b ). Autofluorescent signal sometimes overlapped with subunit c signal, but also was elevated more diffusely (Fig. 4a ). Moreover, although multilamellar "fingerprint" profiles were not detected, confluency-aged homozygous Cb Cln3 Δex7/8 cells displayed numerous ultrastructural abnormalities including electron dense inclusions characteristic of lipofuscin and large autophagosomes that contained dense core structures, degenerating mitochondria, and many smaller vesicles (Fig. 4c ). Inclusion bodies and autophagosomes were infrequently observed in confluency-aged wild-type cultures (data not shown). Figure 4 Subunit c accumulation in homozygous Cb Cln3 Δex7/8 cerebellar precursor cells a. Subunit c immunostaining and autofluorescence of 7-day confluency-aged wild-type and homozygous Cb Cln3 Δex7/8 cells is shown. Wild-type cultures (Cb Cln3 +/+ ) exhibited limited subunit c immunostaining and autofluorescence. However, Cb Cln3 Δex7/8/Δex7/8 cells contained numerous subunit c puncta. Autofluorescence (7 days AF) was also significantly elevated (right panels), although limited overlap with subunit c puncta was observed (arrows). 40 × magnification. b. Immunoblot analysis of subunit c protein at sub-confluency or 7-day confluency incubation is shown. Total protein extracts from sub-confluency wild-type (+/+) and homozygous mutant (Δex7/8/Δex7/8) cultures contained approximately equal levels of subunit c protein (α-sub c). 7-day confluency extract from homozygous Cb Cln3 Δex7/8 cells (Δex7/8/Δex7/8) had elevated levels of subunit c protein (~1.5X), relative to wild-type extract (+/+). Protein levels were normalized to cytochrome c oxidase subunit IV (α-cox4). c. TEM analysis of inclusions in 7-day confluency-aged homozygous Cb Cln3 Δex7/8 cells is shown. A large autophagosome contained by double membrane (arrows) is filled with degenerating mitochondria (M d ), electron dense cores (left and right of *) and other smaller vesicular structures. A large electron-dense inclusion, with a lipofuscin (Ln) appearance, is also present. M, mitochondria. 10,000 × magnification. Homozygous Cb Cln3 Δex7/8 cells and Cln3 Δex7/8 knock-in mice process cathepsin D abnormally We next investigated the basis for subunit c accumulation, testing the hypothesis that cathepsin D is abnormal since it is required for ATP synthase subunit c degradation in the lysosome [ 13 ]. We first tested cathepsin D transport and processing in homozygous Cb Cln3 Δex7/8 cells and Cln3 Δex7/8 mice using anti-cathepsin D antibody that recognizes unprocessed and processed cathepsin D isoforms. Immunostaining of wild-type and homozygous Cb Cln3 Δex7/8 cells revealed a perinuclear and punctate vesicular cathepsin D distribution, consistent with its transport and processing through the secretory pathway and delivery to the lysosome (Fig. 5a ). However, in homozygous Cb Cln3 Δex7/8 cells, cathepsin D distribution was less vesicular and more perinuclear-clustered than in wild-type cells. Immunoblots of homozygous Cb Cln3 Δex7/8 cell and Cln3 Δex7/8 tissue extracts also showed altered relative levels of cathepsin D isoforms (Fig. 5b ). Cathepsin D isoforms, identified by relative molecular weights, represent the ~45 kDa precursor, the ~43 kDa intermediate single chain form of the enzyme, and the 31 kDa heavy chain of the double-chain form of the mature enzyme [ 14 ]. In homozygous Cb Cln3 Δex7/8 cell and Cln3 Δex7/8 tissue extracts, the precursor and heavy chains were reduced, and the single chain was slightly elevated compared to wild-type extracts. The cellular growth media did not contain altered levels of cathepsin D, indicating enzyme secretion was not affected. Heterozygous Cln3 Δex7/8 mice and Cb Cln3 Δex7/8 cells were indistinguishable from wild-type, as expected for a recessive disease phenotype (data not shown). Figure 5 Cathepsin D localization and processing in wild-type and homozygous Cb Cln3 Δex7/8 cells a. Immunostaining of wild-type and homozygous Cb Cln3 Δex7/8 precursor cells with anti-cathepsin D antibody, recognizing unprocessed and processed forms of cathepsin D protein is shown. Cb Cln3 +/+ cells (left panel) exhibited a perinuclear and cytoplasmic punctate signal. Cathepsin D signal in homozygous Cb Cln3 Δex7/8 cells (right panel) was more often perinuclear, with less cytoplasmic punctate signal, compared to wild-type Cb Cln3 +/+ cells. 40 × magnification. b. α-Cathepsin D-probed immunoblots of total wild-type versus homozygous Cln3 Δex7/8 knock-in tissue or Cb Cln3 Δex7/8 cellular extracts are shown. The ~45 kDa cathepsin D band, representing precursor, was the predominant band in wild-type (wt) tissue and cellular extracts, with lower levels of mature enzyme (single chain, ~43 kDa, and heavy chain, ~31 kDa). Conversely, homozygous Cln3 Δex7/8 and Cb Cln3 Δex7/8 mutant (m) extracts exhibited reduced levels of precursor and heavy chain of the double-chain form of the enzyme, with elevated levels of single-chain mature enzyme. The impact of the altered cathepsin D processing on enzymatic activity was next tested to determine if altered enzymatic activity accounts for inefficient subunit c turnover. In a fluorogenic in vitro assay, cathepsin D activity in total cellular extracts was not significantly altered in homozygous Cb Cln3 Δex7/8 cells (376 ± 89 RFU/μg total protein), versus wild-type cells (324 ± 58 RFU/μg total protein), although a consistent trend towards increased enzymatic activity in mutant cells was observed. Thus, cathepsin D transport and processing are disrupted in homozygous Cb Cln3 Δex7/8 cells in a manner such that enzymatic activity appears to be relatively unaffected. Homozygous Cb Cln3 Δex7/8 cells show abnormal membrane organelles The abnormal transport and processing of cathepsin D suggested membrane trafficking disruptions in homozygous Cb Cln3 Δex7/8 cells; therefore, we surveyed the subcellular distribution and morphology of membrane organelles. Components of the secretory pathway, including the ER, cis -Golgi, and trans -Golgi, did not appear altered from wild-type appearance when labeled with the respective markers, protein disulfide isomerase (PDI), GM130, and VVL (data not shown). By contrast, the lysosomal markers, Lysotracker and Lamp 2 had significantly altered signal in homozygous Cb Cln3 Δex7/8 cells, versus wild-type cells. Wild-type cells exhibited brightly stained lysosomes that were large and clustered in the perinuclear region whereas homozygous Cb Cln3 Δex7/8 lysosomes were lightly stained, smaller vesicles that were more diffusely scattered in the cytoplasm of the cell (Fig. 6 ). Lamp 1 distribution was also altered, as previously noted (Fig. 3 ). However, Lamp 1 and Lamp 2 total protein levels were similar in wild-type and homozygous Cb Cln3 Δex7/8 cells by immunoblot analysis, indicating the altered signal likely reflects dispersed lysosomes or altered localization and/or epitope availability (data not shown). It is noteworthy that Lysotracker dye, which selectively accumulates in acidic compartments, exhibited the most marked reduction in lysosomal labeling. This observation may reflect altered lysosomal pH, an established finding in JNCL [ 10 , 15 ]. Figure 6 Lysotracker and Lamp 2 labeling of wild-type and homozygous Cb Cln3 Δex7/8 lysosomes Lysosomal labeling of wild-type and homozygous Cb Cln3 Δex7/8 precursor cells with lysotracker and Lamp 2 antibody is shown. Lysotracker dye (top panels) labeled large, perinuclear-clustered lysosomes and scattered lysosomes in the periphery of wild-type cells (Cb Cln3 +/+ ). Lysotracker stain was dramatically reduced in homozygous mutant cells (Cb Cln3 Δex7/8/Δex7/8 ), with smaller labeled vesicles and less apparent perinuclear clustering. Lamp 2 (bottom panels) immunostaining also showed reduced signal intensity with less perinuclear clustering in homozygous Cb Cln3 Δex7/8 cells, although the effect was somewhat less dramatic than that observed with Lysotracker dye. Wild-type and homozygous Cb Cln3 Δex7/8 confocal images were captured with identical exposure settings. 60 × magnification. Consistent with the altered early endosome marker (EEA1) signal observed by immunostaining (Fig. 3 ), fluid-phase endocytosis was also altered in homozygous Cb Cln3 Δex7/8 cells, as measured by dextran-FITC uptake (Fig. 7 ). Following a 15-minute incubation in media containing dextran-FITC, wild-type and heterozygote cells displayed brightly stained, large endocytic vesicles that were clustered in the perinuclear region. However, homozygous Cb Cln3 Δex7/8 cells were less brightly stained with most dextran-FITC signal localizing to smaller vesicles scattered throughout the cytoplasm of the cell. Figure 7 Endocytosis in wild-type, heterozygous and homozygous Cb Cln3 Δex7/8 cells Dextran-FITC uptake in wild-type, heterozygous and homozygous Cb Cln3 Δex7/8 precursor cells is shown. In wild-type (Cb Cln3 +/+ , left panel) and heterozygous (Cb Cln3 +/Δex7/8 , middle panel) cells, dextran-FITC label was observed in a perinuclear-clustered vesicular pattern with scattered labeled vesicles also present in the periphery. In contrast, dextran-FITC label of homozygous mutant (Cb Cln3 Δex7/8/Δex7/8 , right panel) cells was reduced overall and exhibited smaller stained vesicles with less perinuclear clustering. Confocal images were captured with identical exposure settings. 40 × magnification. Finally, because subunit c is a mitochondrial protein and its turnover proceeds through autophagic engulfment of mitochondria [ 13 ], we analyzed homozygous Cb Cln3 Δex7/8 cell mitochondrial morphology and function. Mitochondrial distribution in homozygous Cb Cln3 Δex7/8 cells was indistinguishable from wild-type and heterozygous cells; however, homozygous Cb Cln3 Δex7/8 mitochondria appeared more elongated by grp75 marker immunostaining and TEM analysis (Fig. 8a ). 72% of homozygous mutant mitochondria were greater than 0.6 μm in length (range = 0.26 μm to 2.75 μm), while fewer wild-type mitochondria (51%) reached this length (range = 0.15 μm to 2.29 μm). Mitochondrial width was not altered in homozygous Cb Cln3 Δex7/8 cells (data not shown). Moreover, compared to wild-type or heterozygous cells, homozygous Cb Cln3 Δex7/8 cells had significantly reduced cellular ATP levels (1.3 fold less, Fig. 8b ) and exhibited reduced survival following hydrogen peroxide treatment (~50% of wild-type survival, Fig. 8c ), suggesting impaired energy metabolism and oxidative stress response. Taken together, these data support impaired mitochondrial function in homozygous Cb Cln3 Δex7/8 cells. Figure 8 Mitochondrial morphology and function in wild-type, heterozygous and homozygous Cb Cln3 Δex7/8 cells a. Confocal and TEM micrographs of wild-type and homozygous Cb Cln3 Δex7/8 mitochondrial morphology are shown. Immunostaining with the inner mitochondrial membrane marker, grp75 (top panels) highlighted elongated mitochondria in homozygous mutant cells (Cb Cln3 Δex7/8/Δex7/8 ), relative to wild-type mitochondria (Cb Cln3 +/+ ) (insets, zoom = 2.75x). Mitochondrial distribution was not altered from the wild-type pattern. Elongated homozygous Cb Cln3 Δex7/8 mitochondria were also observed by TEM analysis. 60 × magnification. b. Cellular ATP levels in wild-type, heterozygous and homozygous Cb Cln3 Δex7/8 precursor cells are shown. Wild-type (open bar) and heterozygous (gray bar) Cb Cln3 Δex7/8 cells contained ~39 μM ATP, while homozygous Cb Cln3 Δex7/8 cells (black bar) contained ~1.3 fold reduced levels of ATP (~30 μM), which was statistically significant in a t-test (p < 0.0001). Wild-type and heterozygous Cb Cln3 Δex7/8 cellular ATP levels were not statistically different from each other (p > 0.4). A representative of triplicate experiments is shown (n = 6 in each experiment). c. Cell survival following 24-hour hydrogen peroxide treatment is shown. Homozygous Cb Cln3 Δex7/8 cells were ~2-fold more sensitive to oxidative stress by hydrogen peroxide treatment. Wild-type (circle) and heterozygous (triangle) Cb Cln3 Δex7/8 cells exhibited ~50% survival rates with 75–100 μM H 2 O 2 , whereas homozygous Cb Cln3 Δex7/8 cells (squares) had a ~50% survival rate with 50 μM H 2 O 2 . A representative of triplicate experiments is shown (n = 4 in each experiment). Discussion Cb Cln3 Δex7/8 cerebellar precursor cells represent the first genetically accurate neuron-derived culture model of JNCL. Homozygous Cb Cln3 Δex7/8 cells express mutant battenin and JNCL-hallmark mitochondrial ATPase subunit c accumulation, upon aging of cells at confluency. Moreover, this is the first study to indicate recessive endosomal/lysosomal membrane trafficking defects and mitochondrial dysfunction that precedes subunit c deposition in an accurate JNCL model. Importantly, these defects are likely to be early events in the JNCL disease process and may particularly impact neuronal function. Abnormal cathepsin D localization and processing in homozygous Cb Cln3 Δex7/8 cells and Cln3 Δex7/8 mice likely reflects altered vesicular trafficking and/or lysosomal pH, which is known to impact cathepsin D processing [ 14 , 16 ]. Indeed, CLN3 overexpression in HEK-293 cells altered lysosomal pH and cathepsin D processing [ 17 ], and lysosomal pH homeostasis is disrupted in JNCL [ 10 , 15 ]. It is noteworthy that cathepsin B and the CLN2-encoded enzyme, TPPI, are also altered in JNCL [ 18 - 20 ]. Nevertheless, despite the cathepsin D protein alterations that are observed in homozygous Cb Cln3 Δex7/8 cells, cathepsin D enzymatic activity does not appear to be reduced. Thus, decreased cathepsin D activity is unlikely to account for subunit c accumulation in JNCL. Aging of homozygous Cb Cln3 Δex7/8 cells at confluency is necessary to induce significantly accumulated subunit c protein. However, membrane organelle disruptions precede subunit c accumulation in homozygous Cb Cln3 Δex7/8 cells, since they are observed without aging at confluency. Lysosomal and endosomal size and distribution are altered, and mitochondria are abnormally elongated and functionally compromised in sub-confluent homozygous Cb Cln3 Δex7/8 cultures. These observations argue that membrane trafficking defects do not result from excessive subunit c accumulation compromising the lysosome, but rather are early events in the disease process preceding subunit c accumulation. Mitochondrial abnormalities, which have also been reported in JNCL patients and other animal models [ 21 - 23 ], may result from ineffective turnover by autophagy, a lysosomal-targeted pathway [ 24 ]. Alternatively, or simultaneously, battenin deficiency may impact mitochondrial function upstream of turnover, affecting mitochondrial biogenesis and/or altered transport and processing of mitochondrial proteins. In wild-type Cb Cln3 neuronal precursor cells battenin primarily co-localizes with early and late endosomes. Battenin immunostaining in homozygous Cb Cln3 Δex7/8 neuronal precursors is significantly reduced in abundance, but mutant signal also co-localizes with endosomal markers suggesting mutant battenin protein with C-terminal epitopes is trafficked similar to wild-type protein. In other studies, CLN3/battenin protein localization has been reported to partially overlap with late endosomes and lysosomes in non-neuronal cells [ 7 ], and to lysosomes, synaptosomes [ 8 ] and endosomes [ 9 , 25 ] in neurons. These data jointly indicate that battenin resides in a subset of vesicular compartments linking multiple membrane trafficking pathways, perhaps functioning in vesicular transport and/or fusion. Endocytic and lysosomal-targeted pathways, including mitochondrial autophagy, are specifically implicated in this study. Conclusions The membrane trafficking and mitochondrial deficits uncovered in homozygous Cb Cln3 Δex7/8 cells are likely to particularly impact neuronal function. Neurotransmission heavily relies on membrane vesicle transport, and a high-energy metabolism may further sensitize neurons to the loss of battenin activity. Thus, our panel of wild-type, heterozygous, and homozygous Cb Cln3 Δex7/8 cerebellar cells provide an ideal model system to further elucidate battenin function and JNCL pathogenesis. Methods Antibody and cell staining reagents Nestin (clone Rat 401, 2 μg/ml), Lamp 1 (clone 1D4B, 6 μg/ml), and Lamp 2 (clone Abl-93; 6 μg/ml) monoclonal antibodies were obtained from the Developmental Studies Hybridoma Bank, maintained by The University of Iowa, Department of Biological Sciences. Batp1 (1 μg/ml) was previously described [ 12 ]. Anti-subunit c antibody (0.7 μg/ml) was kindly provided by Dr. Kominami (Juntendo University, Tokyo, Japan). Additional antibodies were as follows: GFAP, 1:2000 (DAKO Corporation); calbindin, 1:5000 (Sigma); NeuN, 10 μg/ml (Chemicon); SV40 T antigen (Pab 101), 2 μg/ml (Santa Cruz Biotechnology); cathepsin D (C-20), 2 μg/ml (Santa Cruz Biotechnology); cytochrome c oxidase subunit IV (cox4), 1:1000 (BD Biosciences Clontech); PDI (H-160), 2 μg/ml (Santa Cruz Biotechnology); GM130, 1 μg/ml (BD Transduction Labs); α-tubulin, 1:15,000 (Sigma); grp75, 1:200 (Stressgen); early endosome antigen-1 (EEA1), 2 μg/ml (Santa Cruz Biotechnology); rab 7, 4 μg/ml (Santa Cruz Biotechnology). All fluorescent secondary antibodies were obtained from Jackson ImmunoResearch Laboratories and HRP-conjugated secondary antibodies were obtained from Amersham Biosciences. Additional cell markers were as follows: VVL-biotin, 1:2000 (Vector Laboratories), 10,000 MW dextran-FITC, 1 mg/ml and Lysotracker Red DND-99, 500 nM (Molecular Probes). Generation, maintenance and differentiation of Cb Cln3 cerebellar neuronal precursor lines Cln3 Δex7/8 knock-in mice have been previously described [ 12 ]. Littermate pups from heterozygote crosses were used for primary culture establishment, by previously described methods that yield cerebellar granule neuron-enriched cultures [ 26 ]. Postnatal day 4 (P4) cerebella were dissected in Hank's Balanced Salt Solution (HBSS, Sigma), supplemented with 35 mM glucose. Tail biopsies were also collected for genomic DNA isolation and genotypic analysis. Trypsin/EDTA (10 mg/ml, Sigma) and DNase I (100 μg/ml, Sigma), suspended in HBSS, helped dissociate cerebella for primary culture plating onto 0.01% poly-ornithine (Sigma) coated 100 mm dishes. Primary cultures from individual cerebella were cultured overnight at 37°C, 5% CO 2 , in granule neuron growth media (Dulbecco's Modified Eagle Medium [DMEM, Gibco BRL #11995-065], 10% fetal bovine serum [Sigma #F-2442], supplemented with 24 mM KCl). Infection was performed the following day with defective retrovirus transducing the temperature-sensitive tsA58/U19 large T antigen and a selection neomycin-resistance cassette [ 27 ], as previously described [ 28 ]. Following infection, cultures were shifted to the tsA58/U19 permissive growth temperature of 33°C and selection was in the same growth media as above, with 200 μg/ml G418. Conditionally immortalized colonies were isolated 3–9 weeks post-infection and expanded for frozen stocks and further sub-clone isolation. Multiple clonal lines were obtained for each genotype and all phenotypes were confirmed in at least 2 independent Cb Cln3 cell lines. Cb Cln3 cell lines were maintained on 0.01% poly-ornithine coated dishes at 30–90% confluency, in 33°C and 5% CO 2 atmosphere. Passage number was recorded (up to ~20 passages), but had no apparent impact on phenotype. Neuronal differentiation was as previously described [ 29 ] with the following cocktail: 10 ng/ml α-FGF, 250 μM IBMX, 200 nM TPA, 50 μM forskolin, 5 μM dopamine (Sigma). Genotyping and RT-PCR Genomic DNA was extracted from tail biopsies and cell pellets as described (Cotman et al., 2002). Cln3 Δex7/8 knock-in allele PCR genotyping was with wild-type primers, WtF (5'-CAGCATCTCCTCAGGGCTA-3') and WtR (5'-CCAACATAGAAAGTAGGGTGTGC-3') to yield a ~250 bp band and knock-in primers, 552F (5'-GAGCTTTGTTCTGGTTGCCTTC-3') and Ex9RA (5'-GCAGTCTCTGCCTCGTTTTCT-3') to yield a ~500 bp band. PCR cycling conditions were 95°C for 30 seconds, 58°C for 30 seconds, and 72°C for 35 seconds, repeated for 34 cycles. Total RNA isolation and Cln3 RT-PCR primers and procedures have been previously described [ 12 ]. Subunit c accumulation assay Cells were seeded into 4-well chamber-slides (Falcon) at a density of 5 × 10 4 cells per well for microscopy studies, or into 100 mm dishes (Falcon) at a density of 5 × 10 5 cells per dish for protein extraction. Cells were typically >95% confluent one day post-plating, and the following day was considered 1-day post-confluency. At the indicated times, cells were either fixed with 4% formaldehyde in phosphate buffered saline (PBS), pH 7.4, for 20 minutes and processed for autofluorescence/subunit c immunostaining, or cell pellets were collected for total protein extraction. Alternatively, cells were fixed with 2.5% glutaraldehyde/2% paraformaldehyde in 0.1 M cacodylate buffer, pH 7.4 for 1 hour and subsequently post-fixed and processed for TEM analysis as described [ 12 ]. In confocal microscopy studies, autofluorescent signal was observed over multiple wavelengths. For co-staining, settings were reduced such that autofluorescent signal did not contribute to antibody label signal. Immunostaining and Immunoblot analysis For immunostaining, cells were seeded at a density of 3–5 × 10 4 cells per well in 4-well chamber-slides and grown overnight at 33°C, unless indicated otherwise. Fixation was with ice-cold 4% formaldehyde in PBS, pH 7.4, for 20 minutes, or with ice-cold methanol/acetone (1:1) for 10 minutes at -20°C followed by air-drying (antibody-dependent). Cells were washed with PBS at least 2 times, 5 minutes per wash, between each of the following steps of the staining procedure: 0.1 M glycine in PBS for 5 minutes, 0.05% or 0.1% (antibody-dependent) Triton X-100 (Fisher Scientific) in PBS for 5 minutes, 2% bovine serum albumin (BSA) in PBS for 30 minutes, primary antibody diluted in 2% BSA/PBS for 90 minutes, secondary antibody diluted in 2% BSA/PBS for 60 minutes. All incubations were carried out at room temperature. Following staining procedures, slides were coverslipped with Vectashield mounting medium (Vector Laboratories) and analyzed on a BioRad Radiance 2100 confocal microscope (Biorad), with identical exposure settings for wild-type and mutant like images. All comparisons of wild-type and mutant staining were performed in Adobe Photoshop with identical brightness and contrast adjustments. Total proteins were isolated from cell pellets by extraction with ice-cold 20 mM Tris, pH 7.4, 1% Triton X-100 (membrane-research grade, Roche), plus protease inhibitors (Complete mini tablet, 0.7 μg/ml pepstatin A, 2 μg/ml aprotinin, 5 μg/ml leupeptin [Roche]). Following homogenization through a 25-gauge needle (~10 passes), extracts were centrifuged at 1000 × g for 10 minutes, at 4°C, to remove debris. Typically, 20–40 μg of protein (determined by Bio-rad D c Protein Assay) was separated by SDS-PAGE, for subsequent immunoblotting, as described [ 12 ]. 16.5% tris-tricine SDS-PAGE gels were used for subunit c immunoblotting experiments. Cathepsin D activity assay 100 mm tissue culture dishes, which were approximately 80–90% confluent, were washed briefly with ice-cold PBS, and total protein extracts were isolated by scraping cells into 10 mM Tris, pH 7.4, 0.1% Triton X-100 followed by incubation on ice, for 20 minutes. The insoluble material was centrifuged at 14,000 g, the supernatant was isolated, and protein concentration was determined using the Bio-rad D c Protein Assay. 50–70 μg of total protein extract were used to measure cathepsin D activity using the Fluorogenic Innozyme™ Cathepsin D Immunocapture Activity Assay Kit (EMD Biosciences) according to the manufacturer's recommendations. Relative fluorescence was measured using an Analyst AD plate reader (Molecular Devices) with the following filters and settings: excitation filter, 360-35; emission filter, 400-20, Flash lamp with 100 readings/well, 100 ms between readings, and 100,000 μs integration time. Lysosomal staining and endocytic uptake Cells were seeded at a density of 3–5 × 10 4 cells per well in 4-well chamber-slides and grown overnight at 33°C. Growth media was exchanged for fresh, pre-warmed growth media containing 500 nM Lysotracker or 1 mg/ml dextran-FITC, and cells were incubated at 33°C for 45 minutes or 15 minutes, respectively. Following labeling, cells were immediately placed on ice and washed for 10 minutes in ice-cold dye-free media, and fixed with 4% formaldehyde in PBS, for 20 minutes on ice. Chambers were removed and slides were coverslipped with Vectashield mounting media for confocal microscopy analysis, as described above. Morphometric analysis of mitochondria TEM photomicrographs (10,000 × – 40,000 × magnification) were taken from random grid fields. For length measurements, the longest side of each mitochondria was measured in centimeters, and along the length of the mitochondria, width measurements were taken every 2.5–4 mm (dependent on the magnification of the micrograph image). Following measurement, all numbers were normalized to reflect one magnification and data was analyzed using Microsoft Excel software. To ascertain unmagnified mitochondrial size, final measurement data, in centimeters, was converted to nanometers according to scale bar representation. ATP measurement ATP was measured by using the CellTiter-GLO ® Luminescent Cell Viability kit (Promega), according to the manufacturer's recommendations. Briefly, cells were plated in a black opaque-walled 96 well plate (Packard Bioscience) at a density of 20000/well and incubated at 33°C overnight. The following day, CellTiter-GLO ® Reagent was added to each well and cell lysis was induced by mixing 2 minutes. An ATP standard curve was prepared in the same plate. Before recording luminescence with a microplate luminometer (MicroLumat Plus LB 96V, Berthold Techonologies), the plate was dark adapted for 10 minutes at room temperature to stabilize the luminescence signal. Hydrogen peroxide treatment assay Cells were plated at a density of 10,000 cells/well in 96-well plates and incubated at 33°C overnight. The following day, fresh media containing varying concentrations of hydrogen peroxide was dispersed to each well. Cells were incubated in the presence of hydrogen peroxide for 24 hours, at 33°C, and viability was measured using the CellTiter-96 ® AQueous Non-Radioactive Cell Proliferation Assay (Promega), according to the manufacturer's specifications. Authors' contributions EF participated in establishment and characterization of cell lines and performed ATP determinations. PW participated in mitochondrial analysis and immunocytochemistry. JE, TL-N, AMT, and HG participated in genotypic and additional phenotypic analysis of cell lines. DR and EC generated virus-conditioned medium for conditional immortalization of cells. MEM co-conceived of the study and assisted on drafting of the manuscript. SLC co-conceived of the study, participated in establishment and phenotypic analysis of cell lines, and drafted the manuscript. All authors read and approved the final manuscript.

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514489

Conflict over Male Parentage in Social Insects

Mutual policing is an important mechanism that maintains social harmony in group-living organisms by suppressing the selfish behavior of individuals. In social insects, workers police one another (worker-policing) by preventing individual workers from laying eggs that would otherwise develop into males. Within the framework of Hamilton's rule there are two explanations for worker-policing behavior. First, if worker reproduction is cost-free, worker-policing should occur only where workers are more closely related to queen- than to worker-produced male eggs (relatedness hypothesis). Second, if there are substantial costs to unchecked worker reproduction, worker-policing may occur to counteract these costs and increase colony efficiency (efficiency hypothesis). The first explanation predicts that patterns of the parentage of males (male parentage) are associated with relatedness, whereas the latter does not. We have investigated how male parentage varies with colony kin structure and colony size in 50 species of ants, bees, and wasps in a phylogenetically controlled comparative analysis. Our survey revealed that queens produced the majority of males in most of the species and that workers produced more than half of the males in less than 10% of species. Moreover, we show that male parentage does not vary with relatedness as predicted by the relatedness hypothesis. This indicates that intra- and interspecific variation in male parentage cannot be accounted for by the relatedness hypothesis alone and that increased colony efficiency is an important factor responsible for the evolution of worker-policing. Our study reveals greater harmony and more complex regulation of reproduction in social insect colonies than that expected from simple theoretical expectations based on relatedness only.

Introduction Major evolutionary transitions ( Maynard-Smith and Szathmáry 1995 ) require the evolution of mechanisms that moderate within-group conflict ( Keller 1999 ; Queller 2000 ; Michod and Roze 2001 ). One such mechanism is mutual policing, where members of a group collectively prevent individuals from acting in their own selfish interests ( Frank 1995 ). The best example of mutual policing behavior in nature is found in social insects, where workers police worker reproduction (worker-policing) by selectively removing worker-laid eggs that would otherwise develop into males ( Ratnieks and Visscher 1989 ; Foster and Ratnieks 2000 , 2001a ; Halling et al. 2001 ; Oldroyd et al. 2001 ), or by directing aggression toward workers with developing ovaries ( Monnin and Ratnieks 2001 ; Iwanishi et al. 2003 ). Selection for worker-policing depends upon two variables: the relative relatedness of workers to queen- and worker-produced males (relatedness hypothesis) and the colony-level cost of workers reproducing (efficiency hypothesis). Worker-policing theory ( Starr 1984 ; Woyciechowski and Lomnicki 1987 ; Ratnieks 1988 ), an extension of kin selection theory ( Hamilton 1964 ), has typically highlighted relatedness as the all-important variable that explains when workers should lay male-destined eggs and when they should police one another's reproduction. In contrast, the costs of worker reproduction ( Ratnieks 1988 ) have been largely ignored or given low prominence in the literature, with the effect that the relatedness hypothesis has become widely accepted as the explanation for worker-policing ( Whitfield 2002 ). Empirical investigations of worker-policing behavior initially focused on species with colony kin structures that predicted the behavior under the relatedness hypothesis, and worker-policing was first demonstrated in the multiply mated honey bee, Apis mellifera ( Estoup et al. 1994 ; Visscher 1996 ). Subsequently, similar patterns have been found in other multiply mated members of the genus Apis ( Halling et al. 2001 ; Oldroyd et al. 2001 ; Wattanachaiyingcharoen et al. 2002 ) and in the multiply mated wasp Vespula vulgaris ( Foster and Ratnieks 2001a ). Support for the relatedness hypothesis comes from contrasts between these species and closely related species that are singly mated ( Peters et al. 1999 ; Foster and Ratnieks 2001c ) and from an intraspecific study of the vespine wasp Dolichovespula saxonica, in which worker-policing behavior is facultative and occurs only in colonies headed by multiply mated queens ( Foster and Ratnieks 2000 ). There are, however, problems with the conclusion that relatedness is the underlying cause of policing behavior, because phylogeny is not controlled for in the interspecific comparisons described above. This is an important problem, because these species are clustered with respect to phylogeny (e.g., four Apis species), and related wasp species, such as Vespa crabro, show patterns of worker reproduction and worker-policing behavior that are consistent with the efficiency hypothesis but not the relatedness hypothesis ( Foster et al. 2002 ). The relatedness hypothesis explicitly predicts that the parentage of males (male parentage) is dependent upon colony kin structure. Importantly, males should be worker-produced in colonies headed by single, once-mated queens, and queen-produced in colonies headed by multiple related queens, or by multiply mated queens, because worker reproduction is prevented by worker-policing. By contrast, the efficiency hypothesis predicts no association of male parentage or worker-policing with colony kin structure. In this paper we test these predictions by analyzing, using methods that control for phylogenetic dependence, how the proportion of worker-produced males (WPM) varies with both colony kin structure and colony size. The theoretical difference in relatedness of workers to queen- and worker-produced males ( r diff ) was used to make predictions about male parentage based upon colony kin structure. We included colony size in our analyses because it potentially alters expected patterns of male parentage ( Bourke 1999 ) by altering power relationships within the colony. In small colonies a single individual may have the power to dominate male production completely, but such reproductive dominance becomes less likely as colony size increases. Results We found data for 50 species: 16 ants, 20 bees, and 14 wasps ( Table 1 ; Figure 1 ). WPM varied considerably (0%–85%), but in most species, queens produced the majority of males, with less than 10% of males being worker-produced in 72% of species surveyed. In only 10% of species were more than 50% of males worker-produced. There was great variation in the number of males ( n m = 13–1,426) and likewise in the number of assignable males ( n a = 10–677, where n a is the sample size corrected for the probability of nondetection [ Foster et al. 2001 ]) that were used to estimate the WPM. However, in those species for which we had relevant data, there was no significant correlation of n m or n a with WPM (Spearman's rank correlation: n m versus WPM: ρ = 0.17, n = 45, p = 0.27; n a versus WPM: ρ = 0.11, n = 27, p = 0.59), suggesting that there was no systematic bias in our dataset. Figure 1 Composite Phylogeny Used in Comparative Analyses Phylogeny includes within-species variation. Duplicated species labeled 1 or 2 (e.g., Leptothorax acervorum 1 and 2) refer to taxa in which within-species variation was included in some analyses (see text for details). Dotted lines, r diff is negative; solid lines, r diff is positive. Horizontal bars indicate WPM. Table 1 The WPM, Colony Kin Structure, and Colony Size in a Sample of Queenright Colonies of Eusocial Hymenoptera a Estimates based on pedigree relatedness NA, maximum likelihood methods were used; n c , number of queenright colonies in which male parentage was analyzed; n q , average number of queens per colony; n w , colony size defined as the number of workers Comparative Analysis Tests of serial independence showed that there was significant phylogenetic dependence for all variables when within-species variation was ignored (log 10 WPM, p = 0.016; r diff , p < 0.001; log 10 of colony size [log 10 n w ], p < 0.001) and when within-species variation was included (log 10 WPM, p = 0.002; r diff , p < 0.001). This confirmed that a comparative approach using an analysis of independent contrasts was warranted ( Abouheif 1999 ; Freckleton et al. 2002 ). The WPM was not significantly correlated with colony kin structure in any of our comparative analyses. Ignoring within-species variation, the slope of the line of regression of contrast in log 10 WPM against contrast in r diff was not significantly different from zero ( Figure 2 A; slope β = −2.14, t = –1.53, df = 48, p = 0.13), and the mean contrast in log 10 WPM (–1.70 ± 5.4) was not significantly different from zero when r diff was coded categorically ( t = 0.31, df = 2, p = 0.78). Likewise, neither analysis that included within-species variation was significant ( Figure 2 B; β = –1.31, t = –1.36, df = 55, p = 0.18; mean contrast in log 10 WPM = –0.14 ± 4.81, t = 0.03, df = 7, p = 0.98). The power was high ( Figure 3 ; power greater than 0.75) for both analyses of regression to detect a large effect of relatedness on WPM, and there was relatively high power (see Figure 3 ; power greater than 0.6) to detect a medium effect in the analysis that included within-species variation. The WPM also did not show any significant relationship with colony size when all species were included ( Figure 4 A; β = –0.12, t = –1.04, df = 48, p = 0.30) or when relatedness was controlled for and we included only species with positive r diff values ( Figure 4 B; β = –0.14, t = –1.05, df = 41, p = 0.30). Figure 2 Variation in Worker Reproduction with Colony Kin Structure Axes show standardized independent contrasts in WPM (log 10 WPM) and in r diff . (A) is based on species values; (B) includes intraspecific variation for seven species (see text). Lines of regression are forced through the origin. Figure 3 Statistical Power As a Function of the Slope β (Effect Size) in Comparative Analyses of r diff on WPM On the graph, + data points show the power of tests in which within-species variation was ignored, and × show the power of tests in which within-species variation was included. Figure 4 Variation in Worker Reproduction with Colony Size Axes show standardized independent contrasts in the proportion of worker-produced males (log 10 WPM) and in colony size (log 10 n w ). (A) includes all species; (B) includes only species in which relatedness predicts worker-produced males (i.e., r diff is positive). Lines of regression are forced through the origin. Discussion Our survey revealed that queens produced the majority of males in most of the species, and in less than 10% of the species did workers produce more than half of the males, in line with earlier surveys based largely on behavioral data ( Bourke 1988 ; Choe 1988 ). Since workers of all the species included in our survey have functional ovaries, this demonstrates that self-restraint and worker-policing are widespread and powerful mechanisms that regulate reproduction in colonies of social Hymenoptera. Our comparative study did not support the view that intra- and interspecific variation in male parentage can be accounted for by the relatedness hypothesis only. First, and most importantly, the proportion of males produced by workers was not significantly associated with colony kin structure. This was true both when within-species variation in colony kin structure was included and when it was ignored. In fact, although the relatedness hypothesis predicts a positive relationship between WPM and r diff , the analyses of relatedness revealed a tendency for a negative relationship. Importantly, our study included data from 50 species, and our power analyses showed that we had enough power to detect a relationship between male parentage and colony kin structure if it was of moderate or large effect. A second line of evidence against the relatedness hypothesis came from the finding that workers produce only very few males in a large number of species where, on purely relatedness grounds, they would benefit from producing males. Workers produce less than 10% of males in 30 of the 43 species (70%) in which workers were more related to worker-produced than to queen-produced males. A third line of evidence came from within-species comparisons. Only in Dolichovespula saxonica ( Foster and Ratnieks 2000 ) were patterns of male parentage compatible with the relatedness hypothesis. By contrast, patterns of male parentage contradicted the relatedness hypothesis in the ants Leptothorax acervorum ( Hammond et al. 2003 ), Lasius niger ( Fjerdingstad et al. 2002 ), Formica exsecta ( Sundström et al. 1996 ; Walin et al. 1998 ), and Myrmica tahoensis ( Evans 1998 ). Interestingly, intraspecific variation in colony sex ratios in agreement with relatedness predictions have been shown in L. acervorum ( Chan and Bourke 1994 ; Chan et al. 1999 ; Hammond et al. 2002 ), F. exsecta ( Sundström et al. 1996 ), and M. tahoensis ( Evans 1995 , 1998 ). This suggests that although workers in these species can assess within-colony relatedness, they do not appear to respond to it in the context of the conflict over male parentage ( Walin et al. 1998 ; Hammond et al. 2003 ). The lack of association between kin structure and the degree of male parentage by workers indicates that factors others than relatedness effectively act as a brake on worker reproduction. The finding of no significant effect of colony size on WPM suggests that the ratio of queens to workers is not an important general factor regulating reproductive division of labor in social Hymenoptera. The low instance of worker reproduction is therefore unlikely to be the consequence of queens using aggression or pheromones to suppress worker reproduction, except, perhaps, in the few species with very small numbers of workers (e.g., Strassmann et al. 2003 ). Most importantly, unchecked worker reproduction is likely to reduce overall colony productivity and may therefore reduce the average fitness of colony members. For example, reproductive workers have been found to spend time engaged in dominance interactions and egg-laying ( Cole 1986 ) that otherwise would be used for foraging and brood rearing. Unchecked worker reproduction could also cause a “tragedy of the commons” ( Hardin 1968 ; Frank 1995 , 1996 ), because there would be more male brood than can be reared by the colony. If queens conceal the sex of their eggs ( Nonacs 1993 ), these costs may also include workers mistakenly replacing queen-laid diploid eggs with their own male eggs. Furthermore, costs incurred by workers biasing colony sex ratios can select for worker-policing behavior ( Foster and Ratnieks 2001b ). Theory shows that these costs do not have to be large for worker-policing and self-restraint to be selected ( Ratnieks 1988 ). Our data showed considerable variation across species in the origin of males, raising the question, what are the factors underlying interspecific variation in male parentage? The efficiency hypothesis predicts that the extent of worker-produced males should depend largely on the shape and slope of the function relating colony productivity and worker efficiency. This property is expected to vary across species, and it is conceivable that closely related species, which are likely to live in similar habitats and have similar life histories, also have similar functions relating colony productivity and worker efficiency. Consistent with this prediction, our analysis revealed a significant phylogenetic signal, with closely related species being more similar in terms of the origin of males than expected by chance. Importantly, this similarity was not due to a greater similarity in kin structure and colony size between closely related species, because these two factors had no significant effect on the origin of males. Previous evidence for the view that the relatedness hypothesis can account for variation in male parentage comes mostly from matched comparisons between honey bees (genus Apis ) and singly mated stingless bees (tribe Meliponini) ( Ratnieks 1988 ; Peters et al. 1999 ) and comparisons within vespine wasps ( Foster and Ratnieks 2001c ). However, a closer inspection of these matched comparisons reveals problems. In the matched comparison with honey bees, stingless bees are generally assumed to have worker-produced males. However, there is considerable variation in levels of worker reproduction, with males in the majority of species being exclusively queen-produced ( Figure 1 ). Moreover, workers of some stingless bee species are completely sterile ( Suka and Inoue 1993 ; Boleli et al. 2000 ), indicating that considering stingless bees as a taxon with generalized worker reproduction is not warranted. Similarly, the matched comparison in vespine wasps also has problems. It is true that males are queen-produced, and that workers police one another in Vespula vulgaris, a species in which queens are multiply mated ( Foster and Ratnieks 2001a ), whereas at least some males are worker-produced in Dolichovespula, a species in which queens are singly mated ( Foster et al. 2001 ). However, the wasp most basal in the phylogeny (Vespa crabro) is singly mated, yet males are all queen-produced because workers police one another ( Foster et al. 2000 , 2002 ). Considering Vespa, Vespula, and Dolichovespula together, the most parsimonious explanation is that worker-policing is the ancestral state in vespines and it has been lost, or at least reduced, in Dolichovespula. In short, neither of these traditional lines of support for the relatedness hypothesis stand up to close scrutiny. In conclusion, our comparative analysis does not support relatedness as the general explanation of patterns of male parentage and occurrence of worker-policing in social Hymenoptera. The concentration of published examples of worker-policing in multiply mated bees and wasps probably reflects the influence of the relatedness hypothesis on the selection of study taxa, rather than relatedness being the ultimate explanation of worker-policing. Moreover, recent studies have revealed worker-policing in species in which the relatedness hypothesis predicts males to be produced by workers ( Kikuta and Tsuji 1999 ; Foster et al. 2002 ; Hartmann et al. 2003 ; Iwanishi et al. 2003 ). We conclude that costs associated with worker reproduction are likely to be significant and variation in these costs to be the main factor underlying differences across species in the origin of males. Experimental investigations of the colony-level costs of worker reproduction have begun ( Lopez-Vaamonde et al. 2003 ). More are needed. It will also be important to conduct behavioral assays to determine whether worker-policing, by either egg-eating or aggression toward workers with developing ovaries, is responsible for the lack of worker reproduction in the stingless bee genera Trigona and Plebeia. Finally, we would like to stress that the finding that kin structure alone cannot account for the intra- and interspecific variation in male parentage does not amount to saying that kin structure is unimportant. Rather, it may work in concert with costs as a force influencing patterns of male parentage in social insects. Thus, this study reveals greater harmony and more complex regulation of reproduction in social insect colonies than that expected from simple theoretical expectations based on relatedness alone. Materials and Methods Male parentage For all analyses, the response variable was WPM (see Table 1 ). For almost all studies, estimates of WPM took into account the power of the genetic markers to detect worker reproduction using either exclusion ( Foster et al. 2001 ) or maximum likelihood approaches ( Arévalo et al. 1998 ). Where this type of analysis was not included in the original paper we reanalyzed data using the exclusion-based approach of Foster et al. (2001) . Specific details of how we treated data are given for each species in Protocol S1 . With comparative analyses there is always the difficult question of deciding “quality control” criteria to ensure that data are reliable and comparable. We collated data from published, in-press, and unpublished sources where colony genetic structure and male parentage were known accurately from molecular genetic markers. We restricted our survey to those including molecular genetic data, because recent genetic studies have shown that colony kin structures inferred from behavioral observations are often incorrect (e.g., mating frequency in Leptothorax nylanderi c.f. Plateaux 1981 ; Foitzik et al. 1997 ; Foster and Ratnieks 2001c ), and in some social insect taxa (e.g., stingless bees and ants), workers lay trophic eggs that mistakenly could be counted as reproductive ( Bourke 1988 ). We also restricted our analysis to queen-containing (queenright) colonies and species in which workers have ovaries. We did this because our aim was to investigate the outcome of worker–queen and worker–worker conflict. For those studies that included data on both queenright and queenless colonies, we considered male parentage in queenright colonies only ( Protocol S1 ; e.g., Vespula germanica [ Goodisman et al. 2002 ]). For all but two species, Leptothorax unifaciatus and Epimyrma ravouxi (L. Keller, J. Heinze, and A. F. G. Bourke, unpublished data), data were for adult or pupal males. For these two exceptional species, we had estimates of WPM at only the egg stage. However, as we found few worker-laid male eggs in both species (see Table 1 ), our estimate of WPM at the egg stage most likely reflected WPM in adults. In our comparative analyses we used log 10 WPM. Colony genetic structure We made predictions about the parentage of males based on colony kin structure by calculating r diff , the theoretical difference in relatedness of workers to queen- ( r w–qm ) and to worker-produced males ( r w–wm ) (see Table 1 ). The relatedness hypothesis predicts that if r diff is positive, males are worker-produced, and if r diff is negative, males are queen-produced, because workers should police one another. For colonies headed by single queens, where variation in colony genetic structure is caused by variation in the effective mating frequency of queens ( Pamilo 1993 ), we calculated r diff as (2 r w–w – 1)/4, where r w–w is the relatedness among adult workers. For species with variation in queen number (polygyny), predictions about worker reproduction are more complicated because both queen number and queen relatedness are important ( Pamilo 1991 ). For these species, we estimated r diff from the actual relatedness of workers to queens ( r w–q ) and among workers ( r w–w ) as r diff = ( r w–w – r w–q )/2. In our comparative analyses we used r diff as a continuous explanatory variable, or we coded r diff categorically as one when r diff was greater than zero (worker-produced males predicted), or as zero when r diff was less than zero (queen-produced males predicted). Colony size We defined colony size as the number of adult workers per nest ( n w ; see Table 1 ). Where only ranges of worker number were given, we took the midpoint value, and if more than one estimate was available, we combined data by calculating unweighted means. In our comparative analysis we used log 10 n w as an explanatory variable. Comparative analysis We constructed an ant, bee, and wasp phylogeny (see Figure 1 ) by combining published phylogenies. For ants, we based our phylogeny on Keller and Genoud's (see Figure 3 in Keller and Genoud [1997] ), which we modified in light of a recent combined molecular and morphological phylogeny ( Ward and Brady 2003 ); for bees, we based it on a combined DNA and morphological phylogeny (see Figure 5 in Cameron and Mardulyn [2001] ), and for wasps, on a morphological and behavioral phylogeny ( Smith et al. 2001 ). In addition, we added phylogenetic details for the Meliponini (stingless bees) following Velthuis (1997) , and for leptothoracine ants, we used the molecular phylogeny of Baur et al. (1996) . We placed bees basal to ants and wasps (see Figure 1 ) ( Brothers and Carpenter 1993 ; Brothers 1999 ). We set all branch lengths equal, corresponding to a punctuational view of evolutionary change, and we considered ambiguous nodes to be unresolved. Using this tree, we tested the assumption of the phylogenetic independence of our three variables (log 10 WPM, r diff , and log 10 n w ) by a test for serial independence ( Abouheif 1999 ) calculated by the program Phylogenetic Independence ( Reeve and Abouheif 2003 ). For these analyses, we rotated nodes within our dataset 10,000 times and randomly shuffled our data 10,000 times to generate our null distribution. As all three variables showed significant phylogenetic nonindependence (see Results ), we used Felsenstein's method of independent contrasts in our comparative analyses ( Felsenstein 1985 ). Analyses using r diff coded categorically were carried out using the “Brunch” algorithm in CAIC ( Purvis and Rambaut 1995 ), whereas analyses using r diff and log 10 n w coded as continuous variables were analyzed using the program PDTREE ( Garland et al. 1999 ; Garland and Ives 2000 ). We tested Brunch analyses for significance by comparing the mean independent contrast against zero using t -tests. We tested for the significance of contrasts generated by PDTREE by regression through the origin. We did not reduce the number of degrees of freedom (df), as has been suggested for phylogenies containing polytomies ( Purvis and Garland 1993 ), because none of our analyses were significant without such adjustment. Power analyses (see below) were calculated using R ( http://www.r-project.org/ ). All other statistical tests were performed using SPSS (version 11). We tested the hypothesis that colony kin structure determines patterns of male parentage both when within-species variation in kin structure was ignored and when it was included. In our first set of two analyses, we used estimates of WPM and r diff that were mean values for each species. We calculated independent contrasts between log 10 WPM and r diff , and with r diff coded as a categorical variable. In our second set of two analyses, we included within-species variation in colony genetic structure that was present in seven species because of facultative variation in queen number or queen mating frequency (see Table 1 ). We did this by calculating r diff per colony and grouping colonies into those where r diff was positive (worker-production of males was predicted), and those where r diff was negative (males were predicted to be queen-produced because of worker-policing). We then estimated WPM for each group. We modified the phylogeny by adding an additional bifurcation at the tips corresponding to these seven species (see Figure 1 ). Although it is not necessary to control for phylogeny when testing hypotheses within species, doing so enabled us to combine evidence from within- and among-species comparisons ( Garland et al. 1992 ). Using our modified dataset, we calculated independent contrasts between log 10 WPM and r diff , and with r diff coded as a categorical variable. We tested the role of colony size in two ways. First, we ignored any effect of relatedness and simply compared contrasts in log 10 WPM with contrasts in log 10 n w . Second, we controlled for relatedness by limiting our analysis to species in which workers were more related to worker- than to queen-produced males (i.e., r diff was positive), and then compared contrasts in log 10 WPM with contrasts in log 10 n w in this subset of the data. Statistical power To investigate the power of our analysis, we first determined the expected relationship between WPM and r diff in our dataset. To do that we set WPM to 0% when r diff was less than zero, to 100% when r diff was greater than zero, and to 50% when r diff was equal to zero. An analysis of independent contrasts based on this hypothetical relationship gave a highly significant relationship between WPM and r diff both when within-species variation was ignored ( β = 5.48, t = 6.57, df = 48, p < 0.0001) and included ( β = 6.59, t = 9.12, df = 55, p < 0.0001). On the basis of these slopes, we conducted a power analysis by assuming two types of effects. We considered r diff to have a “large” effect on WPM when β was greater than 4.0, and a “moderate” effect when β was between 2.0 and 4.0. To test the power that our analysis had to detect a large and moderate effect, we used the model y = βx + “resampled residual of y ,” where x is the observed standardized contrast in r diff and “resampled residual of y ” is the residual of y estimated by resampling the distribution of residuals from our observed regressions through the origin. From this model, we defined power as the proportion of regressions (forced through the origin) in 1,000 simulated datasets that were significant at α ≤ 0.05 for a given slope β (the effect size). We investigated how power varied with effect size by increasing β incrementally from 1 to 5 in steps of 0.1 (see Figure 3 ). Supporting Information Protocol S1 Details of Data Selection Methods and Sources A detailed synopsis of how data used in this paper were selected from published and unpublished sources. (86 KB DOC). Click here for additional data file.

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526374

External metallic circle in hepaticojejunostomy

Background Biliary-enteric anastomosis especially Roux-en Y hepaticojejunostomy is frequently used for biliary diversion in benign biliary strictures. In this study, we present the results of hepaticojejunostomy with external metallic circle. Methods Hepaticojejunostomy with external metallic circle were performed in eight male Sprague-Dawley rats. At the end of the third month, anastomoses were analysed for patency and stability of external circles. Results Relaparotomy revealed that all the anastomoses were patent and circles were in original places. Conclusion To provide the patency of narrow hepaticojejunostomy anastomoses, external metallic circle can be a good alternative to use of internal stents in suitable cases.

Background Although the risk of late bile duct cancer complicating biliary-enteric anastomosis has been well documented [ 1 , 2 ], biliary-enteric anastomosis especially, Roux-en Y hepaticojejunostomy is frequently used for high biliary injuries and for biliary diversion in benign biliary strictures [ 3 ]. Among the surgical techniques hepaticojejunostomy yields the most favaroble results [ 4 ]. External metallic circle had been used for the end to end choledochocholedocostomy in rats by Tez et al [ 5 ]. The patency of anastomosis was higher than conventional primary anastomosis with this device. The aim of this study was to examine applicability of external metallic circle in hepaticojejunostomy. Methods Eight male Sprague-Dawley rats (Laboratory of Experimental Animals, Hacettepe University Faculty of Medicine, Ankara, Turkey) weighing 250 to 300 g were used. The animals housed under environmentally controlled conditions at 21 ± 2°C and 30% to 70% relative humidity with a 12-hour dark and 12-hour light cycle. Free access to water and standard laboratory food was provided. Before the operations, the rats were fasted overnight and were only allowed free access to water. Guiding Principles in the Care and Use of Laboratory Animals was strictly adhered to at all times together with the recommendations from the Declaration of Helsinki. Technique A surgical microscope (Zeiss, Opmi99, Germany), Codman microsurgical instruments, jeweler's forceps, and 10-0 Ethilon suture were used. Rats were anaesthesized with intramuscular injection of ketamine hydrochloride 100 mg/kg and xylazine 10 mg/kg. Under sterile conditions, a midline abdominal incision was made, and the peritoneal cavity was opened. After the traction of duodenum towards the left, the common bile duct was identified and a complete transection midway between the portal hilus and the duodenum was performed by means of sharp dissection. Proximal end was used for hepaticojejunostomy and distal end was closed by a tie. An opening was made on the wall of the jejunum, wide enough to match the size of the duct at a distance of 4–5 cm from the pylorus. Hepaticojejunostomy was performed by the help of surgical microscope with a silver made external metallic circle. All anastomoses were performed by the same investigator (S.K.). The principle of the technique was to tie the sutures over an external metallic circle 20 to 50 percent greater than the original outer diameter of the bile duct. The circle was handmade from a round-bodied silver wire 0.1 to 0.2 mm thick and 1.0 to 1.2 mm in diameter. The external metallic circle was incorporated at the anastomotic line without any effort to slip it over the cut end of the bile duct. The first suture was placed passing inside the circle and tied over the circle, passing through all layers of duct wall and intestinal wall. The remaining sutures were placed and tied according to the same principles. After completion of sutures, the circle was automatically exteriorised (Figure 1 ). In a preliminary work, we have performed relaparotomy at the end of third month. Eventhough all the anastomosis were patent, interestingly, we were not able to find any metallic circle around the anastomosis or anywhere else inside the abdomen. Therefore, we modified our technique in this study and placed 2–3 supporting sutures between the circle and jejunal serosa following hepaticojejunostomy anastomosis. These supporting sutures were passing only through the inside of circle and jejunal serosa 4 to 5 mm distant to anastomotic line. At the end of the third month, the rats underwent relaparotomy to investigate the patency of hepaticojejunostomy and stability of circles. Figure 1 View of hepaticojejunostomy. (Arrows indicates External Metallic Circle) Results All anastomoses were completed with five or six sutures. Mean operation time was 30 minutes. One rat died in the postoperative fourth day. In necropsy, there was anastomotic disruption on the anterior surface of anastomosis and external circle was on the original place. At the end of third month, relaparotomy was performed on the remaining seven rats. There were no anastomotic dehiscense or biliary leakage. In all animals, there was a good connective tissue mass between the bile duct and jejunum. Dissection of the anastomosis region revealed that all the anastomosis were patent and all the circles were staying in original places. Discussion For the past 10 to 15 years, hepaticojejunostomy has been the method of choice for the treatment of benign biliary stricrures [ 6 , 7 ]. In this study, our aim was to examine the applicability of external circle in hepaticojejunostomy, not comparing the hepaticojejunostomy with or without external metallic circle. Since the first description of injured bile duct repair, many stenting techniques have been used [ 8 ]. In clinical practice, there is arguement about the use of internal stents in hepaticojejunostomy. Some authors recommend internal stents when unhealty (ie, ischemic, scarred) and small bile ducts (<4 mm) are found [ 9 ]. Braasch [ 10 ], Saypol [ 11 ] and Cameron [ 12 ] have reported high long-term results. when biliary-enteric anastomosis was complimented with internal stent; 80%, 80% and 88% success rates respectively. On the other hand, some authors suggest that biliaryenteric anastomosis can be performed without anastomotic stents. Aust [ 13 ], Bismuth [ 14 ] and Innes [ 15 ] have reported 84%, 86%, 95% success rates respectively when biliary-enteric anastomosis was performed without using any stents and they suggest that a stent may promote fibrosis of the anastomosis due to constant irritation of ductal mucosa. Thus, transanastomotic stents appear to have little impact on outcome and probably should not be used routinely. However, stents still may be useful in selected cases in which poor outcome is considered preoperatively or intraoperatively. In a previous study of us [ 5 ], we showed that end to end biliary anastomosis with an external metallic circle had the advantage of shorter operating time and lower bile leakage rate compared to primary microsurgical anastomosis. And alkaline phosphatase levels were also found to be significantly lower for end to end biliary anastomosis with external metallic circle. This results directed us to search the applicability of external metallic circle in narrow hepaticojejunostomy anastomoses. Therefore, we designed a study to perform end to side hepaticojejunostomy with external metallic circle. During the relaparotomy performed at the end of third month, we found all the anastomosis were patent but we were not able to find circles in original places except in one rat. Later on, in this study, we modified our technique and added 2–3 supporting sutures between the circle and jejunal serosa. Relaparotomy revelad all the anastomosis were patent and circles were still in place. Conclusion We think that external metallic circles are also applicable to end to side hepaticojejunostomy anastomosis, should the extra sutures were placed between the circle and jejunal serosa neighbouring the anastomotic line following the completion of anastomosis. To provide the patency of narrow hepaticojejunostomy anastomoses, external metallic circle can be an alternative to use of internal stents in suitable cases. Competing interests The authors declare that they have no competing interests. Authors' contributions EG designed the study, performed the operations and prepared the manuscript. MK, MT, and MKı participated in performing the operations. MKo participated in the design of study and coordination. SK performed the microsurgical anastomosis. 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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539240

Pancreatic metastasis from gastric carcinoma: a case report

Background The pancreas is a rare but occasionally favored target for metastasis. Metastatic lesions in the pancreas have been described for various primary cancers, such as carcinomas of the lung, the breast, renal cell carcinoma and sarcomas. Case presentation We report the case of a 60-year old female with a mass in the pancreatic head four years after partial gastrectomy for gastric adenocarcinoma. The patient underwent a pancreatoduodenectomy. Pathological examination revealed metastases of the primary gastric carcinoma within the pancreatic head and in regional lymph nodes. Conclusions Pancreatic tumors in patients with a history of non-pancreatic malignancy should always be considered to be a putative metastatic lesion at an unusual site. If the pancreas can be identified as the only site of spread, radical resection may prolong survival.

Background The pancreas is an uncommon location for solitary metastasis from other primary cancers [ 1 ]. Despite this, in large autopsy series the prevalence of pancreatic metastasis has been described to be as high as 6% to 11% [ 2 ]. Whereas renal cell carcinoma appears to be the most common primary tumor to cause secondary pancreatic tumors, a variety of other cancers may spread to the pancreas, such as colon cancer, non-small cell lung cancer, and sarcomas [ 3 ]. This article presents the case of a pancreatic metastasis presenting as first site of gastric cancer recurrence four years after primary diagnosis. Case presentation A 60-year-old woman presented with elevated blood levels of the tumor markers CEA (17.3 μg/L, normal <2.5 μg/L) and CA 19-9 (121 U/ml, normal <37 U/ml). Four years before being referred to our institution, the patient had undergone gastric resection (Billroth II gastrectomy) for an adenocarcinoma of the stomach. The tumor was located at the lesser curvature of the gastric antrum, measuring 3 cm in the largest diameter. Pathologic examination revealed a gastric carcinoma of low differentiation, which infiltrated the gastric wall into the subserosal layer without penetrating the serosa. Microscopically, the carcinoma was mainly composed of tubular formations of mitotically active, atypical epithelial cells (Figure 1A ). The tumor also displayed areas of marked desmoplastic stromal reaction, as well as areas of rather glandular differentiation. The latter two were mainly observed in paragastric lymph node metastases (Figure 1B ). The carcinoma at stage pT2 pN1 (6/15) M0 G2 was completely resected (R0 resection). No recurrence was detected during the regular follow-ups. Figure 1 Histomorphologic appearance of the primary gastric carcinoma (A) and a paragastric lymph node metastasis (B). Photomicrograph shows that the primary tumor is mainly composed of solid and tubular formations, whereas, a marked desmoplastic stromal reaction is seen in the lymph node metastasis. (hematoxylin and eosin × 40). Four years after gastric resection, however, ultrasound examination, computed tomography and magnetic resonance imaging revealed an inhomogeneous mass of the pancreatic head, measuring 4 cm in largest diameter (Figure 2 ). Radiographically, no other masses were detected. For differential diagnosis, a primary carcinoma of the pancreas and a metastasis of the gastric carcinoma were considered. Following explorative laparotomy, the pancreatic mass was resected performing a partial pancreatoduodenectomy with resection of the distal bile duct (Whipple's procedure). Furthermore, the former gastroenterostomy was resected and revised. On pathologic examination, the tumor of the pancreatic head grossly presented as white to yellowish, firm mass. Microscopically, the tumor consisted of solid and glandular formations of atypical epithelial cells with distinct nuclear pleomorphism and presented marked desmoplastic stromal reaction, as well as areas of necrosis (Figure 3 ). The duodenal wall and the peripancreatic tissue were infiltrated by the tumor. Lymph node metastases were detected in two peripancreatic lymph nodes. The histomorphological appearance of the pancreatic tumor was in good accordance to some areas of the primary gastric tumor, and especially the growth pattern found in the paragastric lymph node metastases coped well with the microscopic picture found in the pancreatic tumor. Immunohistochemical analyses revealed identical expression patterns in the gastric carcinoma and the pancreatic mass, both displaying positive reactions with antibodies towards cytokeratins 8, 18 and 19, as well as carcinoembryonic antigen (CEA), whereas no reactions were seen with antibodies towards cytokeratins 7 and 20. Because of these findings and due to the lack of pancreatic cancer progenitor lesions, pancreatic intraepithelial neoplasias (PanINs), within the non-neoplastic pancreatic tissue of the Whipple's resection specimen, the pancreatic tumor and the two regional lymph node metastases were considered to be metastases of the primary gastric carcinoma. Figure 2 Computed tomography of the abdomen four years after Billroth II resection for gastric cancer, revealing an inhomogenous mass in the pancreatic head, 4 cm in diameter. (Picture courtesy the Division of Radiology, German Cancer Research Center, provided by PD Dr. med. S. Delorme). Figure 3 Histomorphologic appearance of the delayed pancreatic metastasis (hematoxylin and eosin × 100). As in the lymph node metastasis, a marked desmoplastic stromal reaction is seen in the pancreatic metastasis. The patient was discharged from the hospital without any perioperative morbidity on the ninth postoperative day. The postoperative blood levels of the tumor markers declined to normal values (CEA 2.6 μg/l, CA 19-9 24 U/ml). Due to the complete surgical resection and the lack of risk factors for recurrence, the patient received no further adjuvant therapy. Under regular follow-up for one year with determination of the tumor markers and computed tomography, the patient revealed no signs or symptoms of local or systemic recurrence. Discussion Death from recurrence of gastric adenocarcinoma occurs in 70–75% of patients during the first two years after surgical intervention, however, reports of recurrences more than 10 years after primary diagnosis have been reported as well [ 4 ]. The most frequent sites of tumor recurrences include local, regional and peripheral lymph nodes, as well as the liver, the lungs, and the peritoneum [ 5 ]. Furthermore, solitary metastasis in other organs, such as the thyroid gland or the spleen have been described [ 6 , 7 ]. In contrast to direct infiltration into the pancreas, metastases of gastric cancer into the pancreas are considered to be extremely rare and to our knowledge only four cases have been reported in the English literature [ 8 - 10 ]. Adenocarcinomas of the pancreas and of other primary sites frequently display a large histomorphological and immunohistochemical overlap. Thus the differential diagnosis of primary pancreatic cancer versus solitary metastases of other adenocarcinomas may be very difficult – if not impossible – using common pathological and immunohistochemical techniques. According to Robbins et al [ 3 ], solitary pancreatic masses can be classified as secondary tumors to the pancreas in only 2% of the cases, and they are frequently misdiagnosed as primary pancreatic cancers. As a consequence from this, the subtle diagnostic work-up for isolated masses in the pancreas needs to inherit a meticulous elaboration of the medical history of the patients, in particular focused on previous non-pancreatic malignancy. Pancreatic resections can nowadays be performed with low morbidity and mortality rates, in particular in high-volume centers [ 11 , 12 ]. Results of surgical extirpation of isolated metastases to the pancreas from various primary tumors provide improvement with regard to long-term survival [ 1 , 2 ]. Therefore, a resection of isolated metastases in the pancreas should be considered as a treatment option in patients with the history of non-pancreatic malignancy [ 13 ]. Competing Interests The authors declare that they have no competing interests. Authors' Contributions MNW collated the information, searched the literature and wrote the manuscript. FB and PS contributed to the pathological aspects of the manuscript and helped in preparing the manuscript. BEF assisted in literature search and writing of the manuscript. MWB and HF managed the patient and helped in preparing the manuscript and edited the final version with PS . All authors read and approved the final version of the manuscript.

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212705

PLoS Biology—We're Open

With this first issue of PLoS Biology, the editors present the aims and scope of the journal

Welcome to PLoS Biology . We would like to introduce you to your journal, one that is run by and for the scientific community in the broadest sense: researchers, teachers, students, physicians, and the public. One could argue whether scientists need more journals, but we believe there is a global need for greater access to scientific and medical information and that open-access journals can meet this need by removing subscription barriers to the written scientific record. As professional editors, each of us entered the publishing world from the research community with the desire to promote the effective communication and dissemination of science. Offered the opportunity to help spark the transition to open-access publishing by creating an open-access journal that would compete successfully with the most prestigious existing journals, we jumped at the chance. What you see in this issue is the result of a collaborative effort among the founders, the journal's editorial board, and its professional editors. A glance at the table of contents and the list of outstanding scientists on our editorial board will give you a sense for the scope of the journal, which ranges from molecules to ecosystems and spans the experimental and theoretical disciplines that help to explain our biological world. We aim to publish original articles that address an important question, that challenge our assumptions, that drive science forward. Our editorial and peer-review process combines the expertise of both professional editors, who are available on a full-time basis to survey the broad landscape of science as well as to engage reviewers and communicate decisions, and academic editors, who understand deeply the strengths and limitations of their area of research. 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554090

Canavanine-induced longevity in mice may require diets with greater than 15.7% protein

Background Dietary administration of 1% canavanine had been shown to improve survival in female BALB/c mice consuming diets containing 23.4% protein (dry matter basis). Methods In order to determine if this effect also obtains at more moderate dietary protein concentrations, 30 female BALB/c mice were fed a basal diet with 14% protein (15.7% dry matter basis) and another 30 were fed the same diet plus 1% canavanine. Results Neither mean (Control 873.2 d, Canavanine 870.0 d; SEM = 34.2 d; P = 0.949 from ANOVA) nor median (Control 902 d, Canavanine 884.5 d; P = 0.9058 from Mann-Whitney) lifespans differed between groups. Although mean antinuclear antibody (ANA) titers did not differ between control and canavanine-treated mice at 833 days of age (19.84 vs 20.39 respectively; SEM = 2.64; P = 0.889 from ANOVA), one canavanine-treated mouse displayed an outlying ANA value of 50 (next lower value = 30) denoting possible early sign of incipient autoimmune disease in that individual. Conclusion There may be an interaction between dietary protein level and canavanine with respect to lifespan in mice.

Background L-canavanine is a common non-protein amino acid found naturally in alfalfa sprouts, broad beans, jack beans, and a number of other legume foods and animal feed ingredients [ 1 ] at up to 2.4% of food dry matter. This analog of arginine (Figure 1 .) can also block NO synthesis [ 2 - 5 ], interfere with normal ammonia disposal [ 6 , 7 ], charge tRNAarg, cause the synthesis of canavanyl proteins [ 8 ], as well as prevent normal reproduction in arthropods [ 9 ] and rodents [ 10 ]. Figure 1 Chemical structure of canavanine and arginine Canavanine has also been reported to induce a condition that mimics systemic lupus erythematosus (SLE) in primates [ 11 , 12 ], to increase antibodies to nuclear components and promote SLE-like lesions in auto immune-susceptible (e.g., (NZB X NZW)F1) mice [ 13 ]. In our previous study [ 14 ], eighteen female BALB/c mice were fed a 23.4% protein diet containing 1.56% L-canavanine sulfate (equivalent to 1% L-canavanine base) and eighteen control mice received control diet (23.4% protein) from 84–477 days of age. More canavanine-fed mice (16 of 18) survived to age 477 days than those fed the basal diet (9 of 18) (X 2 with Yates correction = 24.8). The death rate and median life span of control mice were consistent with previously reported survival studies of female BALB-C mice fed high protein diets [ 15 ]. Necropsy and histopathology from both experimental animals and co-housed cages of contemporary sentinel mice performed by the University of California Comparative Pathology Laboratory (Davis, Ca.) did not detect any significant gross or histopathological lesions, parasites or pathogenic bacteria, viruses or mycoplasma. Serology results were negative as well. There was no evidence of infectious disease and no evidence of the lung tumors often found in older BALB-C mice [ 15 ]. One sentinel, but no experimental animals, showed evidence of a lymphosarcoma. Kristal and Yu [ 16 ] have suggested that aging "...results in deleterious changes in cellular, intercellular, tissue and organismic functions." Apparently, canavanine postponed the type of physiological decline that results in earlier death due to the inability of these aging mice to maintain homeostasis in the face of undetectable disease or some other stress. These were serendipitous findings during a project designed to explore the mechanism of diet-induced autoimmunity. Ironically, no positive ANAs or anti SSDNA or anti dsDNA titers were detected in these mice as a result of canavanine treatment. Previous reports of life span extension by restricting the intake of energy [ 17 ], protein [ 18 ], tryptophan [ 19 ] and methionine [ 20 ] have been accompanied by severe reductions in growth and eventual body size relative to controls. The severe stunting usually associated with amino acid deficiency and extended life span was not observed in the BALBc mice [ 14 ]. Our earlier results did leave unanswered the question of whether canavanine was extending life or merely offsetting the life-shortening effects of a very high protein diet. Since the objectives of the original investigation were unrelated to lifespan determination and required the harvest of body tissues, full lifespan data were not available. The purpose of the experiment reported here was to test the hypothesis that canavanine will reduce middle age mortality and extend the lifespan of female BALB/c mice consuming a diet containing moderate concentrations of protein (15.7% DMB). Methods Five female 100-day-old 20-gram BALB/cAnHsd mice (first generation offspring of mice obtained from Harlan Sprague-Dawley) were assigned to each of twelve cages and six cages were randomly assigned to each of two treatments: Control = 25 g of ground Agway 1000 lab animal feed or Canavanine = 25 g of a mixture containing 1.56% canavanine sulfate (prepared by the method of Rosenthal [ 21 ]) and 98.44% ground Agway 1000 lab animal feed resulting in a diet containing 1% L-canavanine base (Table 1 ). All animals were weighed monthly for the first 28 months of age and cause of death determined by symptoms and necropsy. As animals died, feed offerings were reduced, but 5 grams per head ratio was maintained. Table 1 Experimental Diets Nutrient Basal (Agway Prolab 1000) Basal Diet + canavanine Dry Master % 89.88 89.78 All others on DMBasis NX6.25 % 15.70 17.84 Lipids % 7.05 6.94 Ash % 6.54 6.44 Gross Energy kcal/g 4.5 4.5 Estimated Metabolizable Energy kcal/ 3.3 3.3 Calcium % 0.90 0.89 Phosphorus % 0.8 0.79 Arginine % 0.81 0.80 Canavanine % ----- 1.05 At 833 days of age, blood samples were taken from the supraorbital sinus of the 37 surviving mice (19 controls and 18 canavanine-fed) and analyzed for antinuclear antibodies (ANA) by the methods of Naiki, et al [ 22 ]. Variations in lifespan and ANA values were evaluated by analyses of variance and median values were contrasted by the Mann Whitney procedure [ 23 ]. Results Neither mean (870.0 vs 873.2, SEM = 34.2) nor median (885 vs 902, W = 923.5) lifespan differed significantly between mice fed canavanine and those fed the same basal diet without canavanine, respectively. (Figure 2 ). Figure 2 Survival of mice fed 15.7% dietary protein Although mean (20.39 vs 19.84) indices of ANA titers at 833 days of age were also similar for canavanine and control treatments, one canavanine-fed mouse displayed an unusually high titer (10X SEM above mean). (Figure 3 ). About half of the mice (48.3%) displayed mammary tumors, pulmonary adenocarcinomas or both at the time of death (17 canavanine mice and 12 controls; but the difference was not significant by Chi-square analysis, [ 23 ]) (Table 2 ). No infectious diseases were detected in either experimental or sentinel mice. Figure 3 Antinuclear Antibodies Table 2 Probable cause of death Mammary Tumor Pulmonary Adenocarcinoma Both Types of Tumor Total With Any Tumor Other Undetermined Canavanine 9 7 1 17 2 11 Control 6 4 2 12 3 15 X 2 (Yates) 0.44 0.37 0.56 0.35 0.65 0.43 P >0.50 >0.50 >0.30 >0.50 >0.30 >0.50 Discussion The median longevity of control mice observed in this experiment (in which a 15.7% protein was fed) considerably exceeds that of the previous trial in which the basal diet contained 23.4% protein (902 d vs 449 d). Storer [ 24 ] fed BALB/c mice a diet of protein content between those two extremes (17%, but probably closer to 19% on a dry matter basis) and observed mean longevity for females of 575 d, a result falling between our two observations. That decreasing protein concentrations should extend rodent lifespan is not a unique finding, the phenomenon is well known. The apparent corrective effect of canavanine at high protein concentrations and lack of effect at more moderate concentrations does offer a new dimension to dietary modulation of longevity that bears further study. A number of populations consume protein in amounts that far exceed known nutritional requirements (humans in some Western countries, alfalfa-fed horses in some Western States and pet dogs in most of the Northern Hemisphere). The impact of these protein intakes on human and domestic animal longevity and the possible corrective effects of non-protein amino acids on those effects should interest a variety of medical, veterinary and nutritional workers. For the second time, we have failed to induce significant autoimmune disease signs with dietary canavanine in BALB/c mice. Since this can be done in autoimmune susceptible strains and hybrids and in the "normal" (DBA/2) strain of mice [ 13 ], genetic differences may play a role in an animal's response to this secondary plant compound. These preliminary experiments were not contemporary comparisons, nor were they conducted with both sexes, with the same source of BALB/c mice, the same basal diets or at the same locations. Known autoimmune-susceptible lines were not challenged in those trials. Although the data from those trials did indicate a canavanine-protein concentration interaction, we propose a contemporary, comprehensive, integrated experiment including both autoimmune susceptible and more normal populations. The proposed work will be more conclusive and provide an opportunity to examine the generality of the canavanine longevity effect, suggest mechanisms for its occurrence and find out if positive effects on oxidation event-dependent aging might be offset by autoimmunity in susceptible individuals. Examination of such indices as tissue and urine nitrate/nitrite, 8-OH deoxyguanidine, canavanyl residues in specific and total proteins would all contribute to a better understanding of mechanisms of longevity modulation. Conclusion This and a previous study suggest that an interaction between dietary protein concentration and canavanine effects on longevity may exist in BALB/c mice. Contemporary trials that vary both protein and canavanine concentrations are needed to test this possibility more conclusively. Competing interests The author(s) declare that they have no competing interests.

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521180

A New Way to Look at Oxidative Stress

Chemical reactions lie at the heart of many biological processes, from photosynthesis and respiration to cell signaling and drug metabolism. Thanks to an atmosphere rich in oxygen, many organisms use oxygen to carry out these life processes. But oxygen metabolism produces highly toxic by-products called reactive oxygen species. When oxidation outpaces detoxifying reactions, oxidative stress occurs, and accumulating reactive oxygen species are free to wreak havoc on cellular machinery. Cysteine, one of the 20 different amino acids that make up proteins, contains a thiol group, which can be modified upon oxidation. A thiol group can stabilize protein structures by forming covalent disulfide bonds and can mediate cysteine-regulated redox reactions. At the same time, however, the high reactivity of thiol groups makes them also particularly vulnerable to nonspecific reactions during conditions of oxidative stress. Over the past few years, an increasing number of proteins have been discovered that use oxidative thiol chemistry to regulate their protein activity. In PLoS Biology, Lars Leichert and Ursula Jakob describe a novel method to monitor thiol modifications in proteins subjected to varying redox conditions in a living organism, the bacteria Escherichia coli . This technique is capable of providing a global snapshot of the redox state of protein cysteines during normal and oxidative stress conditions in the cell. To detect proteins that have the ability to undergo stress-induced thiol modifications, Leichert and Jakob differentially labeled the thiol groups of thiol-modified and non-thiol-modified proteins. The proteins were then separated on two-dimensional gels based on their charge and molecular weight. If the technique worked, most thiol-modified proteins should be detected in the oxidizing environment of the E. coli periplasm (the region between the cell's membrane layers), and they were. After proving the method's ability to detect proteins whose thiol groups were oxidized, the next logical step was to determine what proteins DsbA—the enzyme that catalyzes disulfide bond formation in the E. coli periplasm—was targeting. In E. coli mutant strains that lack DsbA, Leichert and Jakob identified a number of proteins with either substantially less or no thiol modification as compared to wild-type (non-mutant) strains, suggesting that these proteins are indeed DsbA substrates. A differential thiol-trapping technique provides a snapshot of the in vivo thiol status of proteins upon variations in the redox homeostasis of cells In contrast to the periplasm, the E. coli cytoplasm contains several reducing systems. When the researchers tested a mutant strain that lacked the gene for the reducing enzyme thioredoxin, they found that a large number of proteins accumulated in an oxidized state. Many of these proteins have cysteines and require a reduced thiol status for their activity. These results demonstrated that under normal growing conditions, many proteins contain cysteine residues that are vulnerable to even small amounts of reactive oxygen species and so require the constant attention of detoxifying enzymes. In a final set of experiments, Leichert and Jakob discovered a number of proteins whose thiol groups get specifically modified in the presence of reactive oxygen species. These results start to explain some of the many metabolic changes that occur in oxidatively stressed cells. Leichert and Jakob's technique should be applicable to many different cell types and organisms and can be used to investigate the in vivo thiol status of cellular proteins exposed to virtually any physiological or pathological condition that is accompanied by oxidative stress. The next step will be to investigate just how thiol modifications mediate the various functions of redox-regulated proteins.

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539254

Predictors of mortality of patients with acute respiratory failure secondary to chronic obstructive pulmonary disease admitted to an intensive care unit: A one year study

Background Patients with acute exacerbation of chronic obstructive pulmonary disease (COPD) commonly require hospitalization and admission to intensive care unit (ICU). It is useful to identify patients at the time of admission who are likely to have poor outcome. This study was carried out to define the predictors of mortality in patients with acute exacerbation of COPD and to device a scoring system using the baseline physiological variables for prognosticating these patients. Methods Eighty-two patients with acute respiratory failure secondary to COPD admitted to medical ICU over a one-year period were included. Clinical and demographic profile at the time of admission to ICU including APACHE II score and Glasgow coma scale were recorded at the time of admission to ICU. In addition, acid base disorders, renal functions, liver functions and serum albumin, were recorded at the time of presentation. Primary outcome measure was hospital mortality. Results Invasive ventilation was required in 69 patients (84.1%). Fifty-two patients survived to hospital discharge (63.4%). APACHE II score at the time of admission to ICU {odds ratio (95 % CI): 1.32 (1.138–1.532); p < 0.001} and serum albumin (done within 24 hours of admission) {odds ratio (95 % CI): 0.114 (0.03-0.432); p = 0.001}. An equation, constructed using the adjusted odds ratio for the two parameters, had an area under the ROC curve of 91.3%. For the choice of cut-off, sensitivity, specificity, positive and negative predictive value for predicting outcome was 90%, 86.5%, 79.4% and 93.7%. Conclusion APACHE II score at admission and SA levels with in 24 hrs after admission are independent predictors of mortality for patients with COPD admitted to ICU. The equation derived from these two parameters is useful for predicting outcome of these patients.

Background Chronic obstructive pulmonary disease (COPD) is characterized by irreversible airway obstruction that leads to chronic disability. Patients with COPD have a longstanding downhill course that is interspersed with episodes of exacerbations requiring hospitalization. COPD is known to be a common disease. There is lack of recent data regarding the burden of this disease from India, with only study on prevalence of COPD published in 1981 [ 1 ]. Data from United States indicate that incidence of disease is on the rise [ 2 ]. During the year 2000, approximately 24 million adults in United States had evidence of obstructive airway disease. COPD was responsible for 1.5 million emergency department visits, 726,000 hospitalizations, and 119,000 deaths [ 2 ]. It is obvious that this disease puts an enormous economic burden on the society. Andersson and coworkers estimated that almost 35-45% of the total per capita health-care costs for COPD are account for by exacerbations alone [ 3 ]. Severe exacerbations requiring hospitalizations are responsible for a large share of these costs and among these, treatment cost for those who require intensive care unit (ICU) admission is highest. In most of the third world countries, large number of ICU beds are occupied by patients with critical illnesses secondary to various infectious diseases, most of which are reversible. It is important to identify patients at the time of admission who are likely to have poor outcome, so that such patients can be managed aggressively. Many prognostic scoring systems have been devised for the same purpose. These scoring systems help to segregate patients who are the sickest and are likely to die from those who are expected to have better outcome and survive. Most of these scoring systems have been devised for a broad range of critically ill patients. The present study was planned to determine the predictors of mortality in patients with exacerbation of COPD admitted to ICU over a one-year period. An attempt was made to develop a scoring system using the predictors of mortality that would help to identify patients at high risk of dying. Methods Prospectively collected data of patients with acute respiratory failure secondary to COPD admitted to medical ICU of All India Institute of Medical sciences, New Delhi, India (a tertiary care center in north India) over a one-year period (January 2002 to December 2002) was reviewed. Diagnosis of COPD was based upon the characteristic findings on history and examination with typical radiographic abnormalities [ 4 ]. Patients admitted to the ICU with COPD but due to any other primary reason such as those with poisoning or acute coronary event were excluded. Similarly, patients in whom the primary cause of respiratory failure was bronchiectasis, bronchial asthma, pulmonary edema or pulmonary embolism were not included. Finally, 82 patients with a primary admission diagnosis of acute respiratory failure secondary to COPD were included. All patients were documented cases with prior pulmonary function test confirmation of irreversible airway obstruction and had been receiving a combination of various bronchodilators. Management of the patients was the primary responsibility of the ICU team. A treatment strategy was individualized for each patient and was the sole prerogative of the treating physician. All patients received regular nebulized bronchodilators including salbutamol (as frequently as 5 mg every 15 minutes to every 8 hours), ipratropium bromide (as frequently as 0.5 mg every 15 minutes to 0.25 mg every 8 hours), and intravenous corticosteroids. Most patients also received antibiotics (n = 75, 91.5%). Oxygen therapy (2-3 lt/min) was administered to spontaneously breathing patients. The decision to institute ventilatory support was taken by the treating physician. Wherever feasible non-invasive ventilation (NIV) was used as the initial strategy. Endotracheal intubation was done for usual indications such as respiratory arrest, deteriorating level of consciousness, rising PaCO 2 despite maximal pharmacological treatment and deteriorating acidemia. Initiation of weaning from mechanical ventilation was considered as soon as the patients were considered capable of breathing spontaneously. Method of weaning trials included t-piece trials, gradual reduction of synchronized intermittent mandatory ventilation (SIMV) breaths and pressure support ventilation (PSV). Clinical and demographic profile at the time of admission to ICU including age, sex, smoking status, history of previous hospital admissions, history of previous intubation and/or ventilatory support, prior evidence of cor pulmonale with or without congestive heart failure were recorded. Findings on clinical examination including heart rate, respiratory rate and mean blood pressure were recorded. Acute physiology and chronic health evaluation II (APACHE II) score and Glasgow coma scale (GCS) were recorded at the time of admission to the ICU. Acid-base abnormalities at the time of presentation were analyzed by recording the arterial blood gas analysis and serum electrolytes (estimations done on AVL 995S). Renal functions, liver functions and serum albumin (SA) done at the time of admission were also recorded. Development of complications during mechanical ventilator such as pneumothorax and ventilator associated pneumonia (VAP) were recorded. Development of acute respiratory distress syndrome (ARDS), sepsis and multi-organ failure was also documented. ARDS was defined as presence of bilateral pulmonary infiltrates on chest radiograph in presence of hypoxemia with PaO 2 / FiO 2 ratio less than 200 without any evidence of left atrial hypertension (American-European Consensus Conference) [ 5 ]. Sepsis was defined as the presence of a clinically identified site of infection ( eg , pneumonia) and two or more of the following: temperature > 38°C or < 36°C; heart rate > 90 beats/min; respiratory rate > 20 breaths/min or PaCO 2 < 32 mm Hg; and WBC count > 12 × 10 9 /L, < 4.0 × 10 9 /L, or > 0.10 immature forms ( ie , bands) (American College of Chest Physicians/Society of Critical Care Medicine Consensus Conference) [ 6 ]. Days on ventilator, days of ICU stay and days of hospital stay were recorded for all the patients. Primary outcome measure was hospital mortality. Statistical analysis Data were double entered to minimize errors and managed on an 'Excel' master sheet. Analysis was done using the statistical software ' SPSS version 10.0 ' (SPPS Corp, Chicago, IL, USA). Descriptive analysis consisted of mean with standard deviation and range for various parameters. Study group was split on the basis of final outcome. Various parameters were compared between the two groups to identify the predictors of mortality. Continuous variables were analyzed using student's t-test whereas Fisher's exact test was used to compare the ordinal variables. Baseline parameters significant on univariate analysis at p < 0.1 were identified as potential predictor variables. These parameters were evaluated using multivariate logistic regression analysis (backward stepwise method) to determine independent predictors of mortality. An equation was constructed using the independent predictors based on the adjusted odds ratios and a diagnostic rule was defined. To evaluate the predictive capability of the variables and the equation, receiver-operator characteristic (ROC) curves were constructed with sensitivity (on X-axis) and 1-specificity (on Y-axis) for various cut-offs. Significance was considered at p < 0.05 (only two tailed) for the present study. Results Baseline characteristics Demographic and baseline clinical and laboratory profile of the study group are presented in Table 1 . Almost all patients had type II respiratory failure (n = 74, 90.2%) and showed acute on chronic respiratory acidosis. Study cohort mostly consisted of critically ill patients as suggested by a high mean APACHE II score. History of smoking could be elicited in 65 patients (79.3%). A significant number of patients had history of previous hospitalization as well as intubation (39% and 18.3% respectively). Almost 55% of the patients (n = 45) had evidence of underlying cor pulmonale. Fifteen patients (18.3%) had underlying diabetes mellitus whereas 12 patients (14.6%) were on treatment for hypertension. None of the patients suffered from any other co-morbid condition. An attempt was made to define the cause of exacerbation for all patients. There was evidence of pneumonia in 67% (n = 55) of patients whereas pneumothorax was responsible for decompensation in 3 patients (3.7%). No obvious cause could be found in 24 patients (29%). Only one patient had evidence of sepsis, but none had ARDS at the time of admission to the ICU. Table 1 Descriptive profile of the study group (n = 82) Minimum Maximum Mean ± Std. Deviation Age (years) 35 85 60 ± 10 APACHE II score 3 33 13 ± 6 PR (per minute) 46 166 105 ± 19 RR (per minute) 10 46 27 ± 10 MBP (mmHg) 20 126 89 ± 19 GCS 3 15 12.1 ± 3 pH 6.87 7.44 7.25 ± 0.19 PaCO 2 (mmHg) 40.7 130.7 76.6 ± 23.5 PO 2 (mmHg) 31.5 142.3 83.9 ± 41.7 HCO 3 (mmHg) 5.4 55.4 32.3 ± 8.7 Serum Na (mEq/L) 115 152 136 ± 7 Serum K (mEq/L) 2.00 6.80 4.2 ± 0.9 Serum Albumin (gm%) 1.7 4.4 3.2 ± 0.7 Days on ventilator 1 33 8.7 ± 4.6 Days of ICU stay 1 35 9.6 ± 6.2 Days of hospital stay 1 63 16.3 ± 10.4 RR: Respiratory rate, PR: Pulse rate, MBP: Mean blood pressure, GCS: Glasgow coma scale, Serum Na: Serum sodium, Serum K: Serum potassium. Hospital course Non Invasive Ventilation (NIV) was used as initial strategy in 17 patients (20.7%). This strategy had a success rate of 59% (n = 10). Sixty-nine patients (84.1%) received invasive ventilation (including seven patients who failed NIV and had to be intubated). Sepsis developed in 11 patients (13.4%) and all these patients eventually died. Parameters associated with development of sepsis were high APACHE II score (18 vs. 12, p = 0.005) and low SA (2.6 gm/dL% vs. 3.3 gm/dL, p < 0.001). VAP developed in 6 patients (8.7%) and was associated with an increased stay in the ICU (18 days vs. 10 days, p = 0.021) as well as increased stay in the hospital (30 days vs. 15 days, p = 0.005). Outcome was not significantly affected by development of VAP (50% versus 42.8%). Outcome Hospital mortality was 36.6% (n = 30). Various parameters were compared for survivors and non-survivors (table 2 ). In addition to demographic characteristics (age and sex), presence of cor pulmonale and cause of exacerbation of COPD, baseline parameters significantly different between the two groups on univariate analysis were included in a multivariate equation. APACHE II score at admission to the ICU {odds ratio (95 % CI): 1.32 (1.138-1.532); p < 0.001} and SA (done within 24 hours of admission) {odds ratio (95 % CI): 0.114 (0.03-0.432); p = 0.001} emerged as the independent predictors of mortality. ROC curve showed that both these variables have good predictive capability with area under the ROC curve (AUC) of 86.9% for APACHE II score (Figure 1 ) and 82.2% for SA (Figure 2 ). Best cut-off, taken as the value on the ROC curve at the point where curve sharply angulated, was 13.5 for APACHE II score and that for SA was 3.05 gm/dL. Following equation was determined by combining the two variables using the adjusted odd ratio: Score = (0.278 × APACHE II score) - (2.17 × SA), where APACHE II score is the score at the time of admission and SA (gm/dL) is the level with in the first 24 hours. ROC curve for this equation showed an AUC value of 91.2% (Figure 3 ). We chose a cut-off of -2.97 for the equation. That is, a patient with a score above -2.97 is likely to die whereas the one with below -2.97 likely to survive. This diagnostic rule had a specificity of 86.5% with a sensitivity of 90%. Positive predictive value for this variable was 79.4% whereas negative predictive value was 93.7%. A cut-off of -0.45 was 100% specific for hospital mortality but sensitivity was only 40%. On the other hand a cut-off of -5.5 gave a sensitivity of 100% with specificity of 33%. Table 2 Predictors of mortality for patients with exacerbation of COPD Parameter Survivors (n = 52) Non-survivors (n = 30) p value Mean ± SD Mean ± SD APACHE II score 10.6 ± 4.3 17.5 ± 5.7 0.001 GCS 12.8 ± 2.1 10.8 ± 3.7 0.003 MBP (mmHg) 93 ± 13.6 82.5 ± 24.7 0.015 PR (per minute) 110.7 ± 16.9 102.2 ± 21.1 0.049 Serum Albumin (gm%) 3.5 ± 0.5 2.7 ± 0.6 0.001 PaCO 2 (mmHg) 81.2 ± 20.8 68.7 ± 25.8 0.018 HCO 3 (mmol/L) 33.8 ± 8.1 29.6 ± 9.1 0.035 Need of reintubation 35.3% 4.4% 0.001 Renal Failure Nil 16.7% 0.002 Sepsis Nil 36.7% <0.001 GCS: Glasgow coma scale, MBP: Mean blood pressure, PR: Pulse rate. Figure 1 Receiver operator characteristic (ROC) curve plotted for studying the diagnostic utility of Serum Albumin in predicting outcome of patients. The choice of cut-off is shown by an arrow (3.05 g/dL). Figure 2 Receiver operator characteristic (ROC) curve plotted for studying the diagnostic utility of APACHE II score in predicting outcome of patients. The choice of cut-off is shown by an arrow (13.5). Figure 3 Receiver operator characteristic (ROC) curve plotted for studying the diagnostic utility of score derived form equation in predicting outcome of patients. The choice of cut-off is shown by an arrow (-2.97). Discussion Primary outcome measure of the present study was hospital mortality. Overall mortality rate was 36.6%. There was a high incidence of need of MV (84.1%). In studies that have taken into account all the patients with COPD requiring hospitalization, mortality rate has been to the tune of 6-42% [ 7 - 10 ]. Weiss & Hudson [ 11 ] reviewed 11 studies carried out to study outcome of patients with exacerbation of COPD and found the combined mortality rate to be 20.3%. Selection bias in the inclusion of patients for the present study precludes the generalization of these figures for patients with exacerbation of COPD requiring hospitalization from India. Only a fraction of all the patients with exacerbation of COPD admitted to our hospital are managed in ICU. Many other patients with acute exacerbation of COPD, especially those who do not require ventilatory support, are managed in the wards only. Because of this fact, by including patients who were admitted to ICU the sickest group of patient with exacerbation of COPD was selected. Various physiological parameters estimated at the time of presentation were analyzed to find predictors of mortality. Only two parameters, namely APACHE II score at admission to ICU and SA in the first 24 hours of admission, were found to be independent predictors of hospital mortality. The same two parameters also predicted development of sepsis on bivariate analysis. Some of the earlier studies have found blood gas parameters like pH [ 12 ] and PaCO 2 [ 13 ] to be useful in predicting outcome in COPD patients, whereas others [ 14 - 16 ] did not. In the present study, although PaCO 2 and HCO 3 were not independent predictors of mortality they tended to be lower in patients who died and the difference was statistically significant on bivariate analysis. Also, mean pH was similar for the two groups. This has not been reported in the earlier studies and investigators in the past have mostly found high PaCO 2 levels to be associated with worse outcome. A possible reason for this finding is that patients with hypercapnia with concordantly high HCO 3 are usually taken care of by mechanical ventilation. On the other hand, low mean PaCO 2 and HCO 3 levels in non-survivors probably reflected underlying metabolic acidosis. It has been reported earlier also that, for similar level of acidosis, patients with respiratory failure resulting in respiratory acidosis have better outcome as compared to patients with metabolic acidosis, that is commonly secondary to associated non-pulmonary organ failure [ 17 ]. Mean pH was similar for both survivors and non-survivors but survivors comprised predominantly of patients with respiratory acidosis (higher PaCO 2 as well as HCO 3 ) whereas non-survivors consisted of patients with metabolic acidosis (lower PaCO 2 and HCO 3 but similar pH). Another finding that corroborates the same fact is that all patients, who had associated renal failure and/or sepsis, died. The incidence of these two complications was significantly higher in non-survivors (renal failure 16.7% vs nil, p = 0.002; sepsis 36.7% vs nil, p < 0.001). Patients with both these complications commonly have associated metabolic acidosis. Prognostic utility of APACHE II score has been extensively investigated. It has been found useful for prognosticating critically ill patients across a wide array of diagnostic categories. Earlier studies have also found APACHE II score to be useful in predicting mortality in COPD patients with acute exacerbation [ 18 - 21 ] although the timing of scoring after admission has varied in different studies. For example Nevins & Epstein [ 18 ] found APACHE II score at 6 hrs after initiation of ventilation to be a useful predictor of mortality. In the present study, APACHE II scoring done at the time of admission to medical ICU was analyzed. SA estimated with in first 24 hrs of admission was also found to be a strong predictor of mortality. SA has also been reported to be of good prognostic value in the past [ 21 - 23 ]. Utility of prognostic value of SA in patients with COPD is interesting. Albumin has a long half-life of approximately 18 days and because of this fact it is unlikely to change with development of acute respiratory failure in patients with COPD. On the other hand SA is known to reflect the underlying nutritional status and to be affected by the severity of chronic illness. These factors are of obvious significance in deciding the outcome of these patients. An important purpose of the present study was to define predictors, which could help to identify patients that are likely to have worse outcome. This would help us to segregate patients who need to be managed aggressively from the very beginning. We looked at individual predictive utility of the parameters (SA and APACHE II score) that were found to be independent predictors of mortality. Both these parameters had good predictive value as evidenced by high AUC values. To improve the predictive utility, an equation was constructed using the adjusted odds ratio of the two parameters. ROC curve for this equation had a superior AUC value of 0.912. A good prognostic marker needs to be highly specific so that false positives remain low. On the other hand, good sensitivity is also desirable so that false negatives are not too high. A cutoff value of -2.97 has been suggested, which is associated with good specificity (86.5%) as well as sensitivity (90%) for predicting mortality of these patients. Cut-off that were associated with 100% specificity and sensitivity were also determined as different ICU's across the globe may have different priorities at different times. Although prospective studies are required to validate the findings of present study, an equation devised by combination of APACHE II score and SA appears to make sense. Estimation of APACHE II score makes use of various physiological variables but does not include SA levels. Also, the chronic physiology score in APACHE II fails to stratify patients according to varying severity of chronic illnesses. This tends to happen in patients with COPD as well. Use of SA, which predominantly reflects the severity of chronic illness, in the equation seems to complement the predictive capability of APACHE II score. The results of the present study reflect the complex interplay of factors that occurs in patients with exacerbation of COPD. In these patients, an acute insult in the form of exacerbating illness develops on top of a chronic smoldering illness. Severity of both acute insult as well as the underlying disease in the background of the level of nutritional status tends to determine the outcome of these patients. Although the equation is useful in to identifying patients with exacerbation of COPD who are likely to have poor outcome, it cannot be looked at in isolation. Other particulars of these patients such as associated illnesses and co-morbidities must be kept in mind before taking a final decision. It cannot be overemphasized that given the sensitivity and specificity of the equation, certain patients with a score below the suggested cut-off may also be sick. Also, the state of patients with exacerbation of COPD tends to remain in a constant flux and need constant monitoring. In spite of having a low score at presentation many of these patients may deteriorate during hospital stay. It is concluded that APACHE II score at admission and SA levels with in first 24 hrs after admission are independent predictors of mortality for patients with exacerbation of COPD. The equation derived by combining these two parameters is useful for identifying patients that are likely to have poor outcome. Competing interests The author(s) declare that they have no competing interests. Authors' contributions GCK: concept and design of study, management of patients, preparation of the manuscript. AB: concept of the study, management of patients, statistical analysis, preparation of the manuscript. SKS: management of patients and critical review of the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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Dictyostelium Myosin Bipolar Thick Filament Formation: Importance of Charge and Specific Domains of the Myosin Rod

Myosin-II thick filament formation in Dictyostelium is an excellent system for investigating the phenomenon of self-assembly, as the myosin molecule itself contains all the information required to form a structure of defined size. Phosphorylation of only three threonine residues can dramatically change the assembly state of myosin-II. We show here that the C-terminal 68 kDa of the myosin-II tail (termed AD-Cterm) assembles in a regulated manner similar to full-length myosin-II and forms bipolar thick filament (BTF) structures when a green fluorescent protein (GFP) “head” is added to the N terminus. The localization of this GFP-AD-Cterm to the cleavage furrow of dividing Dictyostelium cells depends on assembly state, similar to full-length myosin-II. This tail fragment therefore represents a good model system for the regulated formation and localization of BTFs. By reducing regulated BTF assembly to a more manageable model system, we were able to explore determinants of myosin-II self-assembly. Our data support a model in which a globular head limits the size of a BTF, and the large-scale charge character of the AD-Cterm region is important for BTF formation. Truncation analysis of AD-Cterm tail fragments shows that assembly is delicately balanced, resulting in assembled myosin-II molecules that are poised to disassemble due to the phosphorylation of only three threonines.

Introduction The Assembly of Bipolar Thick Filaments Is Regulated During Cell Division Myosin-II (hereafter referred to as myosin) is a hexameric protein composed of two heavy chains, two regulatory light chains, and two essential light chains ( Figure 1 A). The heavy chain consists of an N-terminal globular head that contains ATP and actin-binding sites, an α-helical neck that contains the light-chain binding sites, and finally a long α-helix that dimerizes with the α-helix of the other heavy chain to form the coiled-coil tail. Figure 1 Domains and Charge Distribution within the Myosin Tail (A) The myosin head (1–818) and light chains are shown at the N terminus. In the coiled-coil tail, Ala 1 is red (1,348–1,530), the AD is blue (1,531–1,824), Ala 2 is purple (1,825–1,966), the C-terminal domain is green (1,967–2,116), and the remainder is black (819–1,347). Phospho-threonines (at positions 1,823, 1,833, and 2,029) are indicated by the letter T. (B and C) Plots of the average charge of each tail domain color coded as in (A). The y-axis is average charge; the x-axis is tail position. Aspartic acid and glutamic acid are assigned –1, lysine and arginine are assigned +1, and all other a.a. are assigned 0. The average charge in (B) was determined with a window size of 14 a.a., and the average charge in (C) was determined with a window size of 28 a.a.. Arrows highlight the 28 a.a. charge repeat in (B) and the 196 a.a. charge repeat in (C). (D) “Headless” AD-Cterm (3xThr) (1,531–2,116). A bipolar thick filament (BTF) is a highly organized structure composed of individual myosin molecules. In vitro, myosin from the cellular slime mold Dictyostelium discoideum assembles without the aid of a cofactor, demonstrating that the myosin molecule itself contains all the information needed to form a highly organized structure of a defined size ( Clarke and Spudich 1974 ). While proteins that co-assemble with muscle myosin have been discovered in some cell types, no such proteins have been identified in Dictyostelium ( Barral and Epstein 1999 ). In vivo, BTFs are important in a variety of cellular processes, including cell motility, chemotaxis, and development. In cytokinesis, BTFs provide the mechanical force to constrict an actin ring positioned at the midzone of the dividing cell ( De la Roche et al. 2002 ). In Dictyostelium, phosphorylation of myosin inhibits filament assembly ( Kuczmarski and Spudich 1980 ). Myosin is recruited to the cleavage furrow in the form of a BTF ( Sabry et al. 1997 ). After the BTF provides contractile force, a myosin heavy chain kinase is recruited that then drives the disassembly of the BTF ( Liang et al. 2002 ). Phosphorylation of only three threonines in the 2,116-amino acid (a.a.) heavy chain of myosin is sufficient to inhibit BTF formation ( Vaillancourt et al. 1988 ; Luck-Vielmetter et al. 1990 ). These threonines have been mutated to aspartic acid (3xAsp myosin) to create a mimic of a fully phosphorylated state ( Egelhoff et al. 1993 ). 3xAsp myosin is assembly-incompetent in vitro, and the phenotype of Dictyostelium cells expressing only 3xAsp myosin is similar to the myosin-null mutant, consistent with previous work demonstrating that BTF assembly is required for myosin function in vivo ( De Lozanne and Spudich 1987 ; Knecht and Loomis 1987 ; Manstein et al. 1989 ; Egelhoff et al. 1993 ). Mutation of the phosphorylation sites to alanines (3xAla myosin), in contrast, does not alter the filament formation properties of myosin in vitro. In vivo, 3xAla myosin is always assembled and therefore is a good mimic of an unphosphorylated state ( Egelhoff et al. 1993 ; Yumura 2001 ). The doubling time of 3xAla cells is 17 h, whereas in wild-type cells it is 13 h, suggesting that thick filament disassembly is required for efficient cytokinesis ( Egelhoff et al. 1993 ). The Role of Charge Repeats in the Myosin Tail Myosin tails have a striking pattern of charged a.a., with an average positive charge over 14 a.a. followed by an average negative charge over 14 a.a. to form a 28-a.a. charge repeat throughout the tail ( McLachlan and Karn 1983 ; McLachlan 1984 ). A second charge repeat found only in the C-terminal 68 kDa of the Dictyostelium myosin tail occurs every 196 a.a. ( Warrick et al. 1986 ; Shoffner and De Lozanne 1996 ). These repeating patterns can be visualized by considering the tail as a one-dimensional rod and calculating the average charge over a window of a.a. as a function of position in the tail ( Shoffner and De Lozanne 1996 ). A 14-a.a. window makes the 28-a.a. repeat apparent ( Figure 1 B), and a 28-a.a. window averages out the 28-a.a. pattern, making the 196 a.a. pattern more apparent ( Figure 1 C). The Myosin Tail Contains Functional Domains The C-terminal 68 kDa of the tail contains the 34-kDa assembly domain (AD; a.a. 1,531–1,824; Figure 1 , blue coiled-coil). The AD has salt-dependent solubility properties like full-length, wild-type myosin in vitro ( O'Halloran et al. 1990 ; Shoffner and De Lozanne 1996 ). However, unlike full-length myosin, which assembles into BTFs, the AD assembles into paracrystals having undefined size and number of elements. The AD also appears to be the minimal assembling portion of the Dictyostelium myosin tail. C-terminal truncation of full-length myosin to a.a. 1,819 yields an assembly-competent myosin, whereas deletion of an additional 35 a.a. abolishes assembly ( Lee et al. 1994 ). The Role of a Globular Head in Assembly Replacement of the catalytic domain and essential light chain binding domain of full-length Dictyostelium myosin with green fluorescent protein (GFP) produces a chimera that is apparently indistinguishable from full-length myosin in its ability to form BTFs ( Zang and Spudich 1998 ). Therefore, the myosin head is not required for BTF formation. However, the contribution of a globular head to the assembly process has not been closely examined. Models of Regulation Several models have been proposed for the mechanism of myosin regulation. In this discussion, the hexameric myosin molecule will be referred to as a monomer ( Figure 1 A). A monomer-sequestering model was hypothesized based on the characterization of 3xAsp myosin in vitro by rotary shadowing electron microscopy ( Pasternak et al. 1989 ; Liang et al. 1999 ) and in vivo by identification of myosin tail mutations that suppressed the 3xAsp phenotype ( Liang et al. 1999 ). In this model, the coiled-coil tail bends and folds back on itself, sequestering the AD from other myosin molecules. It was further hypothesized that the bent conformation is stabilized by an intramolecular interaction between two regions of the tail rich in alanines in core positions of the heptad repeat. These coiled-coil regions, termed Ala 1 (a.a. 1,348–1,530) and Ala 2 (a.a. 1,825–1,966), are shown in red and purple respectively in Figure 1 . A bias for alanines in core heptad positions is characteristic of antiparallel tetrameric coiled-coils ( Munson et al. 1996 ), prompting the speculation that Ala 1 and Ala 2 form an antiparallel tetrameric coiled-coil in a phosphorylation-dependent manner. An alternative monomer-sequestering mechanism might be destabilization of the coiled-coil. Threonine 1,823 is located at the C terminus of the AD, and is predicted to be in the D position of the heptad repeat. The D position is in the core of the coiled-coil where the two strands interact closely. It is possible that phosphorylation of threonine 1,823 would cause a local disruption of the coiled-coil and perturb self-assembly by introducing negative charge into the hydrophobic core ( Luck-Vielmetter et al. 1990 ; Liang et al. 1999 ; Nock et al. 2000 ). Consistent with this hypothesis, Nock et al. (2000) showed that in full-length myosin, position 1,823 makes the largest contribution to the 3xAsp phenotype. However, the susceptibility of the myosin tail to proteolysis by chymotrypsin does not change with phosphorylation, arguing that large structural changes due to phosphorylation are unlikely ( Cote and McCrea 1987 ). Another model postulates that regulation occurs at the level of assembly intermediates. The assembly pathway of full-length Dictyostelium myosin consists of a nucleation phase followed by an elongation phase ( Mahajan and Pardee 1996 ). In the nucleation phase, a parallel dimer forms in which two myosin monomers self-associate in a parallel orientation with a 14-nm stagger. When two myosin monomers are offset by 14 nm, both the 28-a.a. and 196-a.a. charge repeats are aligned to maximize charge complementation between the two tails ( De Lozanne 1988 ). Threonine 1,823 is positioned within a cluster of positively charged a.a. that forms part of the 196 a.a. repeat ( Luck-Vielmetter et al. 1990 ; Nock et al. 2000 ). The introduction of negative charge by phosphorylation of threonine 1,823 could disrupt critical charge-charge interactions required for assembly. Localization Models Determining the mechanism of regulated assembly will help elucidate the largely uncharacterized mechanism of myosin recruitment to the cleavage furrow. Reports that 3xAsp myosin does not localize, while 3xThr (i.e., wild-type) and 3xAla can localize, have demonstrated the necessity of BTF assembly for proper localization of myosin ( Sabry et al. 1997 ). However, the motor activity is not required, as the chimeric GFP-regulatory light-chain tail protein is capable of translocation to the cleavage furrow in dividing Dictyostelium cells ( Yumura and Uyeda 1997 ; Zang and Spudich 1998 ). Chimeric constructs consisting of the Dictyostelium motor domain and the Acanthamoeba, chicken smooth muscle, or skeletal muscle myosin tails translocate to the cleavage furrow of Dictyostelium cells despite almost no sequence homology between these tails and the Dictyostelium myosin tail ( Shu et al. 1999 ; Shu et al. 2002 ). This has led to the hypothesis that no specific a.a. sequence is required, but that assembly is both necessary and sufficient for cleavage furrow localization ( Shu et al. 1999 ; Shu et al. 2002 ; Shu et al. 2003 ). Reconstitution of Regulated BTF Assembly Characterization of Dictyostelium BTFs has identified functional domains and repeating patterns in the coiled-coil tail. How do these properties come together to form a BTF that can be regulated by phosphorylation of only three a.a.? How do these properties contribute to regulated assembly? How do these properties enable a myosin BTF to localize to the cleavage furrow during cytokinesis? We have approached these questions by reconstituting regulated assembly of BTFs and defining the minimal part of the molecule required for regulated BTF assembly in vitro and in vivo. Results The AD-Cterm (3xThr) and (3xAsp) Tail Fragments Reconstitute Regulated Assembly We wished to test whether both the Ala 1 and the Ala 2 domains of myosin are necessary to regulate BTF assembly ( Liang et al. 1999 ) or whether the AD-through-C-terminal portion of the tail is sufficient for formation of regulated BTFs. We constructed a tail fragment that starts at the AD and extends to the end of the C terminus (AD-Cterm) ( Figure 1 D), and therefore contains all three threonine phosphorylation sites but not the Ala1 region. We created both “wild-type” (AD-Cterm [3xThr]) and “3xAsp” (AD-Cterm [3xAsp]) versions; the latter construct had aspartic acids in place of the three threonine phosphorylation sites to mimic a constitutively phosphorylated state. We then compared the salt-dependent solubility of these tail fragments to full-length phosphorylated and unphosphorylated myosin to see whether AD-Cterm recapitulates regulated assembly. Thick filaments and paracrystals efficiently sediment upon centrifugation, whereas unassembled molecules remain soluble. Wild-type full-length myosin efficiently assembles in buffers of intermediate ionic strength (25–100 mM NaCl), while phosphorylated full-length myosin is unassembled ( Figure 2 A) ( Kuczmarski and Spudich 1980 ; Cote and McCrea 1987 ). Therefore, regulated assembly is biochemically defined as salt-dependent insolubility of unphosphorylated myosin and solubility of phosphorylated myosin. AD-Cterm (3xThr) and AD-Cterm (3xAsp) possess the same in vitro assembly properties as full-length unphosphorylated and full-length phosphorylated myosin, respectively, suggesting that this part of the tail contains all the information needed to regulate assembly in vitro ( Figure 2 A). Figure 2 Characterization of “Headless” AD-Cterm Tail Fragments (A) Analysis of assembly by sedimentation. Fraction of soluble protein as a function of NaCl concentration is plotted for the constructs depicted adjacent to the graph. The solubility of “headless” AD-Cterm (3xThr) and AD-Cterm (3xAsp) are compared to the solubility of unphosphorylated and phosphorylated full-length myosin having the globular motor domain (full-length myosin data from Cote and McCrea [1987] ). (B) Sedimentation equilibrium analysis of 52 μM “headless” AD-Cterm (3xThr) and AD-Cterm (3xAsp) in buffer containing 500 mM NaCl. The top graphs show the concentration distribution, fit, and residuals for AD-Cterm (3xThr), while the bottom graphs show the same data for AD-Cterm (3xAsp). The molecular weight obtained from the fit was 130 kDa for AD-Cterm (3xThr) and 120 kDa for AD-Cterm (3xAsp). (C) Thermal melts of “headless” AD-Cterm (3xThr) and AD-Cterm (3xAsp) in buffer containing 500 mM NaCl are shown as fraction of protein denatured as a function of temperature. The open circles are data for 50 μM “headless” AD-Cterm (3xThr), and the open squares are data for 50 μM “headless” AD-Cterm (3xAsp). The Global Stabilities of AD-Cterm (3xThr) and AD-Cterm (3xAsp) Are Identical We next tested whether AD-Cterm (3xThr) and AD-Cterm (3xAsp) tail fragments form coiled-coils, similar to full-length myosin. The oligomerization state of the tail fragments was determined by sedimentation equilibrium analysis, and the secondary structure was assessed by circular dichroism (CD). Neither tail fragment is expected to assemble in the buffers used for these studies, as they contain 500 mM NaCl. Sedimentation runs were carried out as a function of protein concentration, and equilibrium traces were obtained after 20 h of centrifugation. The profiles were fit to an equation describing the sedimentation behavior of a single, non-associating, ideal species ( Figure 2 B). The distribution of residuals around 0 suggests that the concentration distribution is well described by the model. The predicted molecular weight of the coiled-coil is 137 kDa, and the experimentally determined molecular weight ranged from 130 kDa to 160 kDa for the AD-Cterm (3xThr) tail fragment and 120 kDa to 150 kDa for the AD-Cterm (3xAsp) tail fragment. The range of molecular weights obtained for both tail fragments was due to an observed decrease in molecular weight as protein concentration was increased. This trend is a hallmark of non-ideality and has been observed for elongated, rod-like molecules such as DNA and skeletal muscle myosin ( Tanford 1961 ). Far-UV CD spectra at 4 °C show that both tail fragments are α-helical with similar α-helical content as assessed by comparing mean residue ellipticity at 222 nm (θ 222 ) (unpublished data). Therefore, both tail fragments behave as two-stranded coiled-coils in these assays. The sedimentation equilibrium analysis demonstrates that a direct comparison of coiled-coil stability can be made by thermal denaturation at 500 mM NaCl because neither tail fragment self-assembles to form larger species in this condition. Thermal melts are reversible and at equilibrium and far-UV CD spectra show both tail fragments are α-helical at the starting temperature of the melt (4 °C) and are random coil at the ending temperature (60 °C) (unpublished data). The melting temperature for the AD-Cterm (3xThr) and AD-Cterm (3xAsp) tail fragments at both protein concentrations are identical (29 °C at 50 μM and 28 °C at 2.5 μM; Figure 2 C). In summary, the AD-Cterm tail fragments behave as two-stranded coiled coils with similar thermal denaturation properties in high salt ( Figure 2 B and 2 C). Therefore, the difference in assembly observed between the wild-type and 3xAsp tail fragments cannot be attributed to a failure of AD-Cterm (3xAsp) to fold into an α-helical two-stranded coiled-coil. AD-Cterm Tail Fragments That Have a GFP “Head” Form BTFs The AD-Cterm data show that tail fragment solubility accurately predicts the bulk solubility properties of full-length myosin. However, they do not form true BTFs. When AD-Cterm (3xThr) is assembled in buffer containing 50 mM NaCl with 10 mM MgCl 2 and imaged using negative-stain (EM), it forms paracrystals with a 14-nm (98-a.a.) periodicity, corresponding to the periodicity of charge in the AD-through-C-terminal region of the myosin tail ( De Lozanne et al. 1987 ; O'Halloran et al. 1990 ) ( Figure 3 A). Figure 3 Analysis of “Headless” AD-Cterm (3xThr) and GFP-AD-Cterm (3xThr) Assembly by EM (A and B) The scale bars are 100 nm, and all panels are on the same scale. (A) The “headless” AD-Cterm (3xThr) tail fragment assembled for 2 h. (B) Three images of GFP-AD-Cterm (3xThr) assembled for 2–5 min. (C) Analysis of GFP AD-Cterm (3xThr) (open circles) and GFP-AD-Cterm (3xAsp) (open squares) assembly by sedimentation. To test whether the presence of a globular domain might induce AD-Cterm to form regulated, bipolar structures analogous to the thick filaments formed by full-length Dictyostelium myosin, we attached a GFP molecule to the N terminus of AD-Cterm (GFP-AD-Cterm). Both GFP-AD-Cterm (3xThr) and GFP-AD-Cterm (3xAsp) versions of this protein were made to mimic the unphosphorylated and phosphorylated states of myosin, respectively. We assembled purified GFP-AD-Cterm (3xThr) in buffer containing 50 mM NaCl with 10 mM MgCl 2 and imaged them using EM. Bipolar structures first formed on a time scale of 2–5 min ( Figure 3 B), then bound together and reorganized to form larger, but less well-defined structures on a time scale of more than 10 min. This result is consistent with previous data on full-length Dictyostelium myosin indicating that when it is prepared by dialysis rather than by rapid dilution as used here (see Materials and Methods ), it forms elongated structures ( Stewart and Spudich 1979 ). The bipolar structures have striations at their ends spaced 14.4 ± 2.9 nm ( n = 25) apart, corresponding well to the 14.3-nm offset of full-length myosin heads in a BTF ( Stewart and Spudich 1979 ). GFP-AD-Cterm (3xThr) BTFs Are Structurally Homologous to Full-Length Myosin BTFs We compared the dimensions of GFP-AD-Cterm (3xThr) and full-length myosin BTFs ( Clarke and Spudich 1974 ; Stewart and Spudich 1979 ). The width of GFP-AD-Cterm (3xThr) BTFs is 27 ± 6 nm ( n = 63) at the center of the bare zone (area where heads are absent), close to the width of full-length myosin BTFs (33 ± 1 nm). For both GFP-AD-Cterm and full-length myosin, the length of the bare zone is approximately equal to the length of the coiled-coil. This length is 130–190 nm for full-length myosin and 85 ± 11 nm ( n = 63) for GFP-AD-Cterm. This is an indication that GFP-AD-Cterm probably assembles in a manner similar to full-length myosin, with differences in BTF dimensions reflecting differences in myosin tail length. Notably, the solubility properties of GFP-AD-Cterm (3xThr) and GFP-AD-Cterm (3xAsp) ( Figure 3 C) are similar to the headless AD-Cterm (3xThr) and AD-Cterm (3xAsp) tail fragments, respectively, as well as to unphosphorylated and phosphorylated full-length myosin-II, respectively (see Figure 2 A). The AD-Cterm Tail Fragment Is Sufficient for Regulated Localization of Myosin To test the ability of GFP-tail fragments to localize to the cleavage furrow of Dictyostelium in vivo, we expressed our constructs in myosin-null Dictyostelium cells. However, the GFP-tail fragments were vastly overexpressed in vivo (unpublished data). Introducing the 31-a.a. regulatory light chain (RLC) binding site between the GFP and tail fragment sequences ( Zang and Spudich 1998 ) produced expression levels similar to wild-type myosin (unpublished data). We expressed 3xThr, 3xAla, and 3xAsp versions of GFP-RLC-AD-Cterm in myosin heavy chain-null Dictyostelium cells. To ensure that the RLC did not interfere with filament formation, we assayed for assembly of the GFP-RLC-tail fusions in Dictyostelium cell extracts. As expected, the 3xThr and 3xAla GFP-RLC-AD-Cterm proteins were assembly-competent in Dictyostelium extracts, while GFP-RLC-AD-Cterm (3xAsp) was not (unpublished data), demonstrating that the RLC does not interfere with regulated filament formation. We used live-cell fluorescence microscopy to study the localization of the GFP-RLC-tail fragments in Dictyostelium cells ( Figure 4 ). In 9 of 9 dividing cells, GFP-RLC-AD-Cterm (3xAla) localized to the cleavage furrow and remained at the site of cleavage furrow formation in the resulting daughter cells (termed “back end”) after cytokinesis. In contrast, GFP-RLC-AD-Cterm (3xAsp) did not go to the cleavage furrow in any of 11 observed dividing cells. GFP-RLC-AD-Cterm (3xThr) localized to the furrow in 6 of 12 dividing cells, and in these six cells localization was apparent only in the very late stage of furrow formation and at the back end of the resulting daughter cells. In three cells, GFP-RLC-AD-Cterm (3xThr) localization was clearly visible only at the back end of the resulting daughter cells, and in the remaining three cells no localization was clear. Thus, the AD-Cterm tail fragment is sufficient for localization, but does not localize as efficiently as full-length GFP-myosin (3xThr). The increased localization of GFP-RLC-AD-Cterm (3xAla) is consistent with the overassembly and increased localization reported for full-length GFP-myosin (3xAla) ( Sabry et al. 1997 ; Robinson et al. 2002 ). Figure 4 Localization of GFP-RLC-Tail Fragment Constructs in Live Dividing Dictyostelium Cells The localization of several GFP-RLC-myosin tail fragments during and just after cytokinesis in live Dictyostelium cells are shown. GFP-myosin (row 1) is clearly localized to the early and late cleavage furrow of the dividing cell and to the back end of the resulting daughter cells. By contrast, GFP-RLC-AD-Cterm (3xThr) (row 2) is localized correctly only at the late stages of cytokinesis and in the back end of one daughter cell. GFP-RLC-AD-Cterm (3xAla) (row 3) is localized to the furrow as well as to the back end of a daughter cell, while GFP-RLC-AD-Cterm (3xAsp) (row 4) shows diffuse localization throughout cytokinesis. The scale bar is 10 μm and the time is indicated in min:sec. Objects of Comparable Length to BTFs Are Not Enriched at the Cleavage Furrow During Cytokinesis To examine the specificity of myosin BTF localization, we examined whether any object of comparable length to a BTF is enriched at the cleavage furrow during cytokinesis ( Uyeda and Yumura 2000 ). We scrape-loaded 0.5 μm diameter fluorescent beads into Dictyostelium cells expressing GFP fused to the N terminus of full-length wild-type myosin. These are round beads, while Dictyostelium BTFs are rod-shaped, but the length of each structure is comparable (approximately 0.5 μm). Figure 5 A shows a time course of a representative Dictyostelium cell during cytokinesis. In these cells, GFP-myosin is recruited to the cell equator early during cytokinesis and remains there until the cell divides. Thereafter, myosin remains at the back end of the daughter cell as they move away from one another. In contrast, the labeled beads of similar size show no directed motion toward the furrow ( Figure 5 B). Figure 5 Localization of 0.5-μm Beads in Live Dividing Dictyostelium Cells (A) Time course of a representative GMO8B Dictyostelium cell (defined in Materials and Methods ; contains GFP myosin) during cytokinesis. GFP-myosin fluorescence is shown in green and the beads are shown in red. While GFP-myosin accumulates in the furrow, the beads show no directed motion. The scale bar is 10 μm and time is indicated in min:sec. (B) Plot of the location of each bead in each of six dividing cells in the six frames imaged during cytokinesis. The axes were defined in each frame to bisect the center of the cell both horizontally and vertically such that the center of the furrow is the origin of the axes. The position of each bead was then plotted relative to these axes. Different beads are represented by different colors. For three of the beads, the trajectory of the bead is shown with arrows. The average location of a cell is outlined on the plot in transparent green. Are All the Domains within the AD-Cterm Tail Fragment Required for Regulated Assembly The data detailed in Figures 2 – 4 show that the tail fragments examined in this study are a good model for a myosin BTF. To examine the roles of the various domains within this tail fragment, we have constructed several shorter fragments of the myosin tail ( Figure 6 ) and analyzed their regulated assembly properties. Figure 6 Tail Fragments Used for Truncation Analysis For tail fragments that include more than one domain, the name is determined by the first and last domain in the tail fragment. Phosphorylation sites are indicated in parentheses. 1xThr indicates that the fragment contains the threonine at a.a. 1,823; 2xThr indicates that the fragment contains the threonines at a.a. 1,823 and 1,833; and 3xThr indicates that the fragment contains the threonines at a.a. 1,823, 1,833, and 2,029. The same scheme is used to describe aspartic acid-containing constructs in the paper, except threonine is substituted with aspartic acid. The AD Does Not Reconstitute Regulated Assembly Given the large contribution that a.a. 1,823, the penultimate a.a. in the AD, makes to the 3xAsp phenotype ( Nock et al. 2000 ), we tested whether the AD could be regulated by this a.a. alone. The salt-dependent solubilities of the AD (1xThr) and a mutant in which threonine 1,823 had been changed to aspartic acid (AD [1xAsp]) were nearly identical in the sedimentation assay ( Figure 7 A), which suggests that the AD can assemble but is not sufficient for regulated assembly. Figure 7 Analysis of Assembly by Sedimentation The solubility of the various constructs used for the truncation analysis is compared. (A) Comparison of “headless” AD (1xThr) and “headless” AD (1xAsp). (B) Comparison of “headless” AD (1xThr), GFP-AD (1xThr), and GFP-AD-Cterm (3xThr). The GFP is located at the N-terminus in both GFP-containing constructs. (C) Comparison of “headless” extended AD (2xThr) and “headless” extended AD (2xAsp). (D) Comparison of “headless” AD-Ala2 (2xThr) and “headless” AD-Ala2 (2xAsp). (E) Comparison of “headless” AD-Cterm (3xThr), “headless” Ala1-Ala2 (2xThr), and “headless” Ala1-Cterm (3xThr). We attached a GFP “head” to the AD (1xThr) and, interestingly, this GFP-AD (1xThr) tail fragment had bulk sedimentation properties very similar to those of headless AD (1xThr), suggesting that the presence of a globular domain does not affect in vitro solubility, similar to AD-Cterm and GFP-AD-Cterm tail fragments ( Figure 7 B). The AD (1xThr) tail fragments are more salt-sensitive than AD-Cterm (3xThr) tail fragments, possibly because they have a shorter coiled-coil tail ( Figure 7 A and 7 B). EM showed that GFP-AD (1xThr) formed structures of fixed size that were not true BTFs because they did not contain bare zones (unpublished data). This demonstrates that a globular head fixes the size of assembling myosin structures, while C-terminal sequence elements in the myosin tail may be required for proper formation of the bare zone. Regulated Assembly Cannot Be Reconstituted with Tail Fragments Smaller Than AD-Cterm To determine whether the entire 34-kDa portion of the tail C-terminal to the AD is required for regulated assembly, we generated a series of tail fragments that all start at the AD and are truncated at different positions within the C-terminal 34 kDa of the tail (see Figure 6 for constructs). The first such fragments that we examined started at the AD and included threonine 1,833, the second phosphorylation site (extended AD [2xThr]) and extended AD [2xAsp]). Unlike AD (1xThr) and AD (1xAsp), extended AD (2xThr) and extended AD (2xAsp) show a four-fold difference in solubility ( Figure 7 C). This is significantly less than the eight-fold difference in solubility of full-length unphosphorylated and phosphorylated myosin, respectively, and AD-Cterm (3xThr) and AD-Cterm (3xAsp), respectively. To test whether adding on a larger portion of the tail results in a greater degree of regulated assembly, we constructed tail fragments that start at the AD and end at a.a. 1,966, the end of Ala 2 (AD-Ala 2). As with other tail fragments, the aspartic acid variant of this construct is more soluble than its wild-type counterpart ( Figure 7 D). Surprisingly, AD-Ala 2 (2xThr) exhibits inhibited assembly relative to shorter constructs ( Figure 7 D). This inhibition was not merely a consequence of where we truncated this tail fragment. A tail fragment was constructed that started at the AD and ended at a.a. 2,015 (AD-2015 [2xThr]). This construct contains an isoleucine in the C-terminal most heptad core position, making it less likely that the two strands of the coiled-coil will fray. Like AD-Ala 2 (2xThr), AD-2015 (2xThr) exhibits inhibited self-assembly (unpublished data). Furthermore, a far-UV CD spectrum of AD-Ala2 (2xThr) showed that it is α-helical (unpublished data), indicating that AD-Ala2 (2xThr) is structurally intact. All tail fragments truncated in the C-terminal 34 kDa of the tail exhibit altered assembly properties, while AD-Cterm (3xThr) and AD-Cterm (3xAsp) possess the same in vitro assembly properties as full-length, unphosphorylated, and phosphorylated myosin, respectively (see Figure 7 A) ( Cote and McCrea 1987 ). These data suggest that the entire AD-Cterm tail fragment is required to reconstitute regulated assembly of BTFs. The Ala 1 Domain Stabilizes Assembly When the entire C-terminal domain is included in the AD-Cterm tail fragment, the inhibitory effect of Ala 2 is overcome. To test whether this stabilizing effect is specific to the C-terminal domain, we determined if Ala 1 could also stabilize assembly. A tail fragment was constructed that starts at Ala 1 and ends at Ala 2 (Ala1-Ala2 [2xThr]). The salt-dependent assembly of Ala1-Ala2 (2xThr) is more efficient than that of AD-Ala2 (2xThr) ( Figure 7 E) at 5 μM protein. Thus, Ala 1 can partially overcome the inhibitory effect of Ala 2, but not as robustly as the C-terminal domain. A tail fragment containing both Ala 1 and the C-terminal domain (Ala1-Cterm [3xThr]) assembles essentially the same as AD-Cterm (3xThr) ( Figure 7 E). All of these data indicate that the assembly reaction is delicately balanced, because the various domains of the tail make both favorable and unfavorable contributions to assembly. A Globular Head Need Not Be Located N-Terminal to the AD to Promote Assembly of Fixed-Size Structures The 196-a.a. repeat is remarkably symmetric in the entire AD-Cterm region ( Figure 8 A). We created a protein identical to GFP-AD-Cterm (3xThr) except that the GFP is located at the C-terminus, after a.a. 2,116 (AD-Cterm-GFP [3xThr]) ( Figure 8 B). Because of the symmetry in this region of the myosin tail, the AD-Cterm-GFP (3xThr) and GFP-AD-Cterm (3xThr) proteins can distinguish between assembly mechanisms that require specific a.a. in specific positions relative to the globular head versus assembly mechanisms that require a very general charge pattern to occur. AD-Cterm-GFP (3xAsp) was also created to test whether the same three threonines can regulate assembly of this myosin tail fragment. Figure 8 Design and Assembly Characteristics of AD-Cterm-GFP (A) The AD-Cterm charge distribution (top) is aligned with the reverse charge distribution (bottom), showing the overall symmetry of the 196-a.a. charge repeat in this region of the tail. (B) Analysis of assembly by EM. The AD-Cterm (3xThr) tail fragment has GFP on the C-terminus (AD-Cterm-GFP [3xThr]). The scale bar indicates a distance of 100 nm. Shown are three images of AD-Cterm GFP (3xThr), assembled 2–5 min. (C) Analysis of assembly by sedimentation. The solubility of AD-Cterm-GFP (3xThr) and AD-Cterm-GFP (3xAsp) tail fragments constructs are compared to GFP-AD-Cterm (3xThr) and “headless” AD-Cterm (3xThr) tail fragments. AD-Cterm GFP (3xThr) Assembles into Bipolar Structures To test whether AD-Cterm-GFP (3xThr) can form BTFs, we performed EM ( Figure 8 B) and sedimentation assays ( Figure 8 C). Similar to GFP-AD-Cterm (3xThr), AD-Cterm-GFP (3xThr) formed clustered or larger structures when protein was assembled for more than 10 min prior to imaging, whereas BTFs were most prevalent when protein was assembled for 2–5 min. The striations at the ends of the AD-Cterm-GFP (3xThr) bipolar structures are spaced 14 ± 2 nm ( n = 118) apart, consistent with the 14-nm spacing of full-length Dictyostelium myosin. The AD-Cterm-GFP (3xThr) structures have a shorter bare zone than GFP-AD-Cterm (3xThr) structures (62 ± 8 [ n = 75] versus 85 nm), but a similar width to both GFP-AD-Cterm (3xThr) and full-length myosin BTFs (32 ± 5 nm [ n = 159] versus 27 nm and 33 nm, respectively). While the AD-Cterm-GFP (3xThr) structures differ slightly from those formed by full-length myosin and GFP-AD-Cterm (3xThr), it is clear that the presence of the globular domain leads to a fixed length, even in C-terminally capped myosin tail fragments. AD-Cterm GFP Assembly Is Regulated We next tested whether AD-Cterm-GFP assembly is regulated. AD-Cterm-GFP (3xAsp) is soluble at all NaCl concentrations, whereas AD-Cterm-GFP (3xThr) sediments efficiently between 25 mM and 150 mM NaCl ( Figure 8 C), very similar to “headless” AD-Cterm and full-length myosin ( Figure 2 A) as well as GFP-AD-Cterm (3xThr) ( Figure 3 C). Therefore, regulation of assembly does not require a specific distance between the threonine phosphorylation sites and a globular head. Discussion Regulation of AD-Cterm and Full-Length Myosin Is Identical In Vitro The assembly properties of both AD-Cterm (3xThr) and AD-Cterm (3xAsp) closely parallel those of full-length unphosphorylated and phosphorylated myosin described by Cote and McCrea (1987) . These data represent a good basis for comparison to AD-Cterm, because the myosin was heavily phosphorylated (2:1 stoichiometry of phosphate:myosin heavy chain), and Cote and McCrea performed a gel filtration step to eliminate any contaminating actin. Other sedimentation data for full-length myosin compare favorably with the AD-Cterm data as well ( Kuczmarski and Spudich 1980 ; Egelhoff et al. 1993 ). The parallel between the solubility of AD-Cterm and full-length myosin in vitro argues that AD-Cterm (3xAsp) is a good mimic of the phosphorylated state of full-length myosin and that all of the information necessary for regulated assembly is present in the AD-Cterm region of the myosin tail. Attaching a Globular Head to AD-Cterm Reconstitutes Regulated BTF Assembly The fact that GFP-AD-Cterm (3xThr) forms BTFs whereas AD-Cterm (3xThr) does not, demonstrates that the mere presence of a globular head differentiates BTFs from paracrystals, and that neither the myosin head nor the S2 region of the myosin coiled-coil is critical for BTF formation ( Zang and Spudich 1998 ; this study). While the presence of the globular head is critical for the size and shape of myosin structures in this study, it has no appreciable effect on the regulation of myosin BTF assembly. Furthermore, other cellular factors, with the exception of kinases and phosphatases, are not required for BTF formation, because the process can be completely reconstituted using recombinant, bacterially expressed protein. Regulation of GFP-AD-Cterm and Full-Length Myosin Is Similar In Vivo GFP-RLC-AD-Cterm tail fragments demonstrate regulated recruitment to the cleavage furrow during cytokinesis. While the localization of GFP-RLC-AD-Cterm (3xThr) is less robust than full-length myosin, constitutively assembled GFP-RLC-AD-Cterm (3xAla) always localizes to the cleavage furrow in cytokinesis (see Figure 4 ). In contrast, GFP-RLC-AD-Cterm (3xAsp) fails to localize (see Figure 4 ). These data are consistent with other observations ( Sabry et al. 1997 ; Shu et al. 2003 ) indicating that assembled myosin constructs localize to the cleavage furrow while unassembled myosin constructs do not. The difference in localization efficiency between full-length myosin and GFP-RLC-AD-Cterm (3xThr) might be due to differences in degree of assembly. The critical concentration of full-length myosin is estimated to be less than 20 nM ( Mahajan and Pardee 1996 ). One might expect the critical concentration of assembly for GFP-RLC-AD-Cterm (3xThr) to be higher than full-length myosin, because full-length myosin has a longer tail. Likewise, the critical concentration of GFP-RLC-AD (1xThr) is expected to be higher than that of GFP-RLC-AD-Cterm (3xThr). This argument may explain why GFP-RLC-AD-Cterm (3xThr) recruitment is less efficient than full-length myosin, and why GFP-RLC-AD (1xThr) does not go to the furrow at all (unpublished data). Interestingly, beads that are approximately the same length as the BTFs formed from full-length myosin do not localize to the cleavage furrow. Together with the previous in vivo localization data, this result argues that the majority of the information necessary for localization of BTFs to the cleavage furrow is in the AD-Cterm portion of the myosin tail, and that localization to the cleavage furrow is an active process, possibly involving another cellular factor that recruits myosin. It may be that this factor recognizes the charge repeats that distinguish assembled myosin BTFs from unassembled myosin. Consistent with this model is the localization of chimeric myosin molecules to the cleavage furrow in Dictyostelium cells ( Shu et al. 1999 ; Shu et al. 2002 ). These chimeras have myosin tails from other species with no sequence homology to the Dictyostelium tail, but contain the charge repeats common to all myosin tails. Regulation Does Not Require an Ala 1-Ala 2 Intramolecular Interaction Our finding that the in vitro self-assembly of AD-Cterm (3xThr) and AD-Cterm (3xAsp) are very similar to full-length, wild-type myosin and full-length, phosphorylated myosin, respectively, show that Ala 1 is not required for regulated assembly. This result has been confirmed in vivo by deleting Ala 1 from both full-length wild-type and 3xAsp myosin (W. Liang and JAS, unpublished data). Dictyostelium cells expressing the Ala 1 deletions as their sole source of myosin were phenotypically indistinguishable from cells expressing their full-length counterparts. It is possible that an Ala 1-Ala 2 intramolecular interaction is indeed one mode of regulation, but is not necessary, because redundant regulatory mechanisms occur at multiple points along the assembly pathway. Regulation Does Not Occur by Conformational Disruption of the Coiled-Coil The CD and analytical ultracentrifugation data show that AD-Cterm (3xAsp) has not simply failed to fold into a two-stranded α-helical coiled-coil. These data are consistent with rotary shadowed electron micrographs of full-length 3xAsp and phosphorylated myosin. Gross destabilization of the coiled-coil would result in a single-headed myosin, and none have been observed ( Pasternak et al. 1989 ; Liang et al. 1999 ). Global destabilization might result in a section of the tail unfolding, lowering resistance to thermal denaturation. However, thermal melts show that the melting temperature of AD-Cterm (3xThr) and AD-Cterm (3xAsp) are identical (see Figure 2 C). Local destabilization of the coiled-coil seems unlikely, because one of the chymotrypsin cleavage sites is close to threonine 1,823, which is in a core position of the heptad repeat, yet the proteolytic susceptibility of the myosin tail does not change upon phosphorylation ( Cote and McCrea 1987 ). Small numbers of assembled AD-Cterm (3xAsp) paracrystals were seen in electron micrographs of samples (unpublished data). These paracrystals, although quite rare, possess a 14-nm periodicity similar to the wild-type tail fragment. Consistent with this observation, approximately 10% of 3xAsp myosin sediments at 50 mM NaCl, demonstrating that regulation of assembly is not an all-or-none process. Together with the CD data, this result indicates that AD-Cterm (3xAsp) is structurally and functionally intact. Rather than being conformationally disrupted, the 3xAsp tail fragment fails to assemble because the critical concentration for assembly is higher than that of the wild-type tail fragment. Regulation of Assembly by Modulation of Charge-Charge Interactions The role of the 196 a.a. charge repeat in assembly The fact that AD-Cterm-GFP forms BTF-like structures with heads on the outside and tails in the center demonstrates the role of the 196-a.a. charge repeat in assembly. This charge repeat is symmetric in the AD-Cterm region of the tail (see Figure 8 A). If the 196 a.a. charge repeat is a major driving force of assembly, then BTF formation should be independent of whether a globular head is positioned on the N or C terminus of AD-Cterm. Since globular heads are clearly visible on the outer edges and not in the center of AD-Cterm-GFP (3xThr) structures, local interactions between a.a. in these filaments must be different than local interactions in filaments formed from GFP-AD-Cterm (3xThr) and from full-length myosin. Further structural characterization is required for a model that describes the packing of the coiled-coils within these filaments, but these data are consistent with the overall large scale charge character of the tail being important for forming BTFs. Interestingly, AD-Cterm-GFP (3xThr) structures are shorter than GFP-AD-Cterm (3xThr) filaments, and the bare zones are smaller as well. This may be because C-terminal sequence elements in the myosin tail may be required for proper formation of the bare zone and thereby determine the exact morphology of the BTF. The assembly reaction is delicately balanced. The truncation analysis provides evidence of a delicate balance between forces that drive assembly and disassembly of myosin tails. This is most strikingly demonstrated by the observation that Ala 2 was actually found to inhibit the assembly of AD, while Ala 1 and the C-terminal domain help to drive assembly. We propose that that this delicate balance is related to the 196-a.a. charge repeat in the tail. The attachment of Ala 2 (purple, Figure 1 ) to the AD (blue, Figure 1 ) adds a large cluster of negative charge onto the end of this tail fragment. Assembly might be inhibited because a proper balance of charge is required for efficient self-assembly. This balance is restored by addition of either the C-terminal portion of the tail (green, Figure 1 ) or Ala 1 (red, Figure 1 ), because both of these domains possess clusters of positive charge. Because the charge repeats likely play a role in each step in the assembly pathway, a small effect, such as the introduction of negative charge at key points in the molecule, could have a large effect on overall self-assembly. The threonine phosphorylation sites are positioned near the positive clusters of charge at the end of AD and in the C-terminal domain, suggesting that regulation by phosphorylation might have its largest effect on this charge pattern. Materials and Methods Construction of myosin tail fragments for expression in E. coli The polymerase chain reaction (PCR) was used to amplify the regions of a Dictyostelium expression vector (pBIG) containing either GFP (3xThr) myosin or GFP (3xAsp) myosin ( Sabry et al. 1997 ). An NdeI site was engineered at the 5′ end, and a stop codon followed by a SacI site was placed at the 3′ end of the PCR product. PCR products were directionally subcloned into the pET21a vector (Novagen, Madison, Wisconsin, United States) using these two restriction sites. Tail fragments contain an N-terminal methionine followed by these a.a. from Dictyostelium myosin: AD (1xThr and 1xAsp), a.a. 1,531–1,824; AD-Cterm (3xThr and 3xAsp), a.a. 1,531–2,116; extended AD (2xThr and 2xAsp), a.a. 1,531–1,840; AD-Ala 2 (2xThr and 2xAsp), a.a. 1,531–1,966; AD-2015 (2xThr), a.a. 1,531–2,015; Ala 1-Ala 2 (2xThr), a.a. 1,348–1,966; Ala 1-Cterm (3xThr), a.a. 1,348–2,116 (see Figure 6 ). The same set of PCR primers were used to construct the wild-type and aspartic acid variants of each tail fragment except for the AD (1xAsp) fragment. For AD (1xAsp), Quikchange site-directed mutagenesis (Stratagene, La Jolla, California, United States) was used to mutate threonine 1,823 to aspartic acid. The sequence of all constructs was confirmed. Construction of GFP tail fragments for expression in E. coli The constructs described above are the source of tail fragment DNA for all GFP constructions. To create N-terminal fusions, 5′ and 3′ ends of GFP-UV ( Crameri et al. 1996 ) were modified using PCR with primers that contain an NcoI site followed by a 6xhistidine tag at the 5′ end and an NdeI site at the 3′ end before the GFP-UV stop codon. Internal NdeI and NcoI sites were eliminated from the GFP-UV gene by Quikchange mutagenesis (Stratagene), and the modified GFP-UV gene was subcloned into the pET28a vector (Novagen) using NcoI and NdeI (GFP-UV-pET28a). Tail fragments were subcloned into GFP-UV-pET28a using NdeI and NotI. To create C-terminal GFP fusions, the 5′ and 3′ ends of GFP-UV in the GFP-UV-pET28a vector were modified by PCR. The 5′ primer eliminated the N-terminal 6xhistidine tag and introduced a SacI site. The 3′ primer eliminated an internal SacI site and introduced a 6xhistidine tag, followed by a stop codon, followed by a NotI site. Quikchange mutagenesis (Stratagene) was used to eliminate the stop codon immediately before the SacI site in the AD-Cterm tail fragments contained in pET21a. The modified GFP-UV was subcloned into this vector using SacI and NotI. All DNA sequences were verified. Construction of GFP tail fragments for localization studies in Dictyostelium To make N-terminal GFP-tail constructs for expression in Dictyostelium, the myosin regulatory light chain binding site (RLCBS) sequence was ligated into plasmid pTX-GFP ( Levi et al. 2000 ) to create pTX-GFP-RLCBS. The GFP sequence from pTX-GFP was subcloned into pET28a (Novagen) using NcoI and SacI. The NdeI site was removed from the GFP sequence using Quikchange mutagenesis (Stratagene) and then subcloned back into pTX-GFP to create pTX-GFPΔNde1. The RLCBS was amplified from pBigGFPRLC+ ( Zang and Spudich 1998 ) using primers to add a 5′ SacI site and 3′ NdeI and XhoI sites and ligated into pTX-GFPΔNde1 using SacI and XhoI digestion. This vector is called pTX-GFP-RLCBS. Myosin tail fragments were subcloned into pTX-GFP-RLCBS using the NdeI and XhoI sites from the corresponding pET21a-tail fragment vectors. All DNA sequences were verified. Protein expression in E. coli All tail fragment constructs were transformed into the BL21-CodonPlus (DE3)-RIL strain (Stratagene). LB media contained 34 μg/ml chloramphenicol and either 100 μg/ml kanamycin for pET28a or 100 μg/ml carbenicillin for pET21a. Cells were grown at 37 °C to an absorbance at 600 nm of approximately 0.6. Protein expression was induced by adding 1 mM IPTG and incubating for 1 h. Cells were harvested by centrifugation at 6,370 × g for 15 min. Purification of myosin tail fragments from E. coli Harvested cells were resuspended in 10 mM Tris (pH 7.4), 1 mM EDTA, 1 mM DTT, 500 mM NaCl, 30% sucrose, and protease inhibitor (PI) cocktail (final concentration of 0.7 μg/ml leupeptin, 0.7 μg/ml pepstatin A, 2 μg/ml aprotinin, and 1 mM PMSF). For a single protein prep, the pellet from 10 l of culture was resuspended in buffer for a final volume of 40 ml. Cells were added dropwise into liquid nitrogen and stored at –80 °C. Cells were thawed and 5 μg/ml RNase A (#78020Y; USB, Cleveland, Ohio, United States), 50 μg/ml RNase-free DNase I (#776 785; Roche, Basel, Switzerland), and 10 mM MgCl 2 were added. The cells were lysed with two passes through a French Press (American Instrument Company, Silver Spring, Maryland, United States) at 10,000 pounds per square inch. After the first pass, a new batch of the PI cocktail was added. The lysate was centrifuged at 100,000 × g for 30 min at 4 °C. The supernatant was boiled for 10 min, and then a new batch of the PI cocktail and 1 mM DTT was added. The boiled supernatant was centrifuged at 100,000 × g for 30 min at 4 °C and then dialyzed against DEAE Low-Salt Buffer (DEAE-LSB; 10 mM Tris [pH 8.0], 1 mM EDTA, 1 mM DTT, and PI cocktail). The protein was injected onto a column consisting of eight tandem HiTrap DEAE Sepharose Fast Flow columns (Amersham Biosciences, Little Chalfont, United Kingdom). The column was washed with 5 volumes of DEAE-LSB and protein was eluted on a linear gradient from 0 to 500 mM NaCl over 10 volumes. Fractions containing protein (typically eluting at 230 mM NaCl) were identified by SDS-PAGE. Protein was precipitated by addition of 85% (NH 4 ) 2 SO 4 , stirred at 4 °C for 30 min, and centrifuged at 100,000 × g for 30 min at 4 °C. The pellet was resuspended in a minimal volume of gel filtration buffer (10 mM Tris [pH 8.0], 1 mM EDTA, 1 mM DTT, and 500 mM NaCl) and loaded on a HiLoad 26/60 Superdex 200 column (Amersham Biosciences). Fractions were analyzed by SDS-PAGE, and those containing pure tail fragments were pooled and dialyzed against Mono-Q Low Salt Buffer (Mono-Q LSB; 10 mM Tris [pH 8], 1 mM EDTA). Protein was injected onto a Mono Q HR 5/5 column (Amersham Biosciences) and a gradient from 0 to 1 M NaCl was run. Tail fragments typically eluted at 450 mM NaCl. Protein concentration was determined by measuring the absorbance at 280 nm in 6M guanidine hydrochloride. The extinction coefficient was calculated using the sequence of one strand of the coiled-coil as described in Gill and von Hippel (1989) . Purification of GFP tail fragments from E. coli After harvesting, cells were resuspended in 50 mM sodium phosphate (pH 8.0) with 250 mM NaCl and containing PI cocktail. For a single protein prep, the pellet from 30 l of culture was resuspended in buffer for a final volume of 120 ml. Lysis and the first centrifugation step were identical to the myosin tail fragment protocol described above except that 5 mM MgCl 2 was added along with the DNase I and RNase A. The supernatant was batch-bound to Ni-NTA resin (Qiagen, Valencia, California, United States) at 4 °C for 1 h. The resin was washed with 40 ml of 50 mM sodium phosphate (pH 8.0) with 250 mM NaCl (starting buffer) followed by 20 ml of starting buffer containing 12.5 mM imidazole. Protein was eluted from the column using approximately 5 ml of starting buffer with 500 mM imidazole. Fractions containing protein were loaded onto a Hi-Load 26/60 Superdex 200 prep grade gel filtration column (Amersham). Both GFP-AD-Cterm and AD-Cterm-GFP tail fragments elute between 120 ml and 150 ml. GFP-AD elutes between 152 ml and 174 ml. Protein was dialyzed against Mono-Q LSB overnight and then injected onto the Mono-Q HR 5/5 column (Amersham Biosciences) as described above. Protein elutes at about 450 mM NaCl. Protein was used immediately after purification for microscopy and sedimentation assays. Electron microscopy Purified GFP-tail fragments were diluted to a final protein concentration of approximately 1 μM, a final MgCl 2 concentration of 10 mM, and a final NaCl concentration of 50 mM. This solution was deposited onto glow-discharged 300-mesh carbon stabilized copper grids coated with formvar (#01753-F; Ted Pella, Redding, California, United States). AD-Cterm and AD proteins were assembled for 2 h, while GFP-containing proteins were assembled for 2 min. A 1% uranyl acetate solution was applied before imaging on a JEOL 1230 transmission electron microscope (JEOL USA, Peabody, Massachusetts, United States). Sedimentation assembly assay Purified protein was dialyzed overnight against 10 mM imidazole (pH = 7.5), 0.1 mM EDTA, and 1 mM DTT. 10 μM protein was added to an equal volume of 10 mM imidazole, 0.1 mM EDTA, 1 mM DTT, 2× mM NaCl. The final concentration of NaCl was × mM NaCl, where × = 0, 25, 50, 75, 100, 150, and 250 mM. Samples were incubated on ice for at least 30 min and then centrifuged at 132,000 × g for 15 min at 4 °C. Three replicates of each sample were made to ensure reproducibility. Samples of the supernatant and pellet were run on SDS-PAGE gels. The intensity of bands was quantified with an AlphaImager 2000 Documentation and Analysis System (Alpha Innotech Corporation, San Leandro, California, United States). Circular dichroism An Aviv Circular Dichroism Spectrometer model 62A DS was used (Aviv Corporation, Acton, Massachusetts, United States). The protein was in 10 mM Tris (pH 7.4), 500 mM NaCl, 1 mM EDTA, 1 mM DTT. Wavelength scans were taken from 260 nm to 200 nm. Data were collected every 1 nm with a 1-nm bandwidth and averaging time of 10 s. The spectra presented are buffer subtracted. Thermal melts were taken from 4 °C to 60 °C. θ 222 was monitored with a 1 nm bandwidth. The temperature was increased in 1 °C increments, and the sample was equilibrated for 2 min at the new temperature before data collection. An averaging time of 30 s was used. The pmt dc voltage used was 1.0 V for 2.5 μM protein and 0.55 V for 50 μM protein. Kaleidagraph (Synergy Software, Essex Junction, Vermont, United States) was used for all data analysis. Plots of fraction denatured versus temperature were constructed as described in Allen and Pielak (1998) . Analytical ultracentrifugation AD-Cterm (3xThr) was assembled by diluting the NaCl concentration to 50 mM. Assembled protein was recovered by centrifugation at 100,000 × g for 15 min. Pellets were resuspended in 10 mM Tris (pH 7.4), 0.1 mM EDTA, 500 mM NaCl (High-Salt Buffer) and centrifuged at 100,000 × g for 15 min to remove aggregates. The AD-Cterm (3xAsp) tail fragment was centrifuged at 100,000 × g for 15 min to remove aggregates. Both tail fragments were exchanged several times into High-Salt Buffer using an Amicon Ultra-15 30,000 Dalton cut-off ultra-filtration device (Millipore, Billerica, Massachusetts, United States). The High-Salt Buffer was the blank in all analytical ultracentrifugation experiments. After buffer exchange, the protein was centrifuged at 14,000 rpm for 10 min in a microcentrifuge to remove aggregates. The protein was snap-frozen in liquid nitrogen and shipped in dry ice to the Macromolecular Interactions Facility at UNC-Chapel Hill. The protein used for all analytical ultracentrifugation experiments was centrifuged at room temperature for 15 min at 16,000 × g to remove aggregates. All sedimentation equilibrium experiments were performed at the UNC Chapel Hill Macromolecular Interactions Facility as described in Patel et al. (2002) . The rotor speed was set at 10,000 rpm, the temperature was maintained at 10 °C, and for the meniscus depletion experiment the conditions were centrifugation at 45,000 rpm for 8 h. AD-Cterm (3xThr) and AD-Cterm (3xAsp) were examined at protein concentrations of 52 μM, 35 μM, 17 μM, and 10.5 μM in High-Salt buffer. The measured densities of the buffers were 1.0 g/ml at 20 °C, and the partial specific volume of both tail fragments was calculated to be 0.73 ml/g at 10 °C ( Durschschlag 1986 ). All data analysis was done using XL-A/XL-I data analysis software version 4.0 (Beckman, Fullerton, California, United States). Culture of Dictyostelium cells expressing GFP-RLC-tail fragments HS1 myosin-null Dictyostelium cells ( Ruppel et al. 1994 ) were transformed using electroporation. Cells were grown in 10-cm petri dishes at 22 °C in HL5 medium ( Sussman 1987 ) supplemented with 60 μg/ml penicillin, 60 U/ml streptomycin, and 15 μg/ml G418 (Life Technologies, Carlsbad, California, United States) for plasmid selection. Sedimentation of lysates prepared from Dictyostelium cells expressing GFP-RLC-tail fragments 1 ml of nearly confluent Dictyostelium cells expressing the appropriate construct was centrifuged and resuspended in 10 mM imidazole (pH 7.5), 0.1 mM EDTA, and 50 mM NaCl in the presence of protease inhibitors. The cells were lysed by freezing in liquid nitrogen and thawing. Cell lysates were allowed to sit on ice for 2 h before centrifugation at 132,000 × g for 20 min. The pellets were resuspended in equal volumes of the lysis buffer. The supernatant and pellets were resolved by SDS-PAGE without boiling the samples. The GFP-fusion proteins were imaged in the gel by excitation at 532 nm on a Typhoon 8000 imager (Molecular Dynamics, Sunnyvale, California, United States). Creation of Dictyostelium GFP-myosin expressing stable cell line The GFP sequence was integrated into the Dictyostelium genome upstream of and in-frame with the gene encoding myosin-II (mhcA) by homologous recombination. The 167 bp just upstream of mhcA through the first 500 bp of the coding region were PCR-amplified from Dictyostelium genomic DNA using primers to add a 5′ XhoI site and a 3′ BamHI site. The PCR product was cloned into pBluescript digested with XhoI and BamHI. A PstI site was added between the upstream and mhcA coding regions by Quickchange mutagenesis (Stratagene) to create plasmid pBS/upstream- mhcA . GFP was amplified from pTX-GFP ( Levi et al. 2000 ) with primers to add 5′ and 3′ PstI sites. The PCR product was then cloned into pBS/upstream- mhcA digested with PstI to create pBS/upstream-GFP- mhcA . The resulting plasmid was digested with ApaI and XbaI, and the fragment containing GFP flanked by the upstream and coding regions of mhcA was gel purified. The fragment was mixed with the blasticidin-resistant plasmid pBsr2 ( Sutoh 1993 ) in a 10:1 excess and transformed into Dictyostelium . After the transformed cells were selected with 4 μg/ml blasticidin S (ICN Biochemicals, Costa Mesa, California, United States), a clonal cell line, GMO8B, was created by plating FACS-sorted GFP-positive cells on Klebsiella lawns and picking spores from individual GFP-positive plaques. The correct integration of GFP upstream of mhcA was verified by PCR and imaging of GFP fluorescence in-gel after SDS-PAGE of cell lysates. The cell line was able to develop normally and grow in suspension, and GFP localization in GMO8B was very similar to GFP-myosin localization in cells expressing GFP-myosin from a plasmid ( Moores et al. 1996 ). Scrape loading of beads into Dictyostelium cells Glass slides were coated with 10 μg/ml polylysine overnight. Approximately 1 ml of semi-confluent GMO8B Dictyostelium cells in HL5 medium were allowed to attach to the polylysine-coated slide for 30 min. The medium was then replaced by a 0.04% solution of 0.5 μm-diameter carboxylated red FluoSpheres (Molecular Probes, Eugene, Oregon, United States) in HL5 medium. The cells were immediately scraped off of the surface with a rubber policeman and transferred to a clean glass slide. After the cells were allowed to attach for approximately 30 min, the slide was rinsed in PBS to remove excess beads not taken up by the cells. The cells were then removed from the glass slide by pipetting up and down with HL-5 medium. Live cell fluorescence microscopy Live cells were transferred to imaging chambers (Applied Scientific, Santa Ana, California, United States) in HL-5 medium. GFP and FluoSphere fluorescence were imaged at room temperature using a Zeiss (Oberkochen, Germany) Axiovert 200 inverted epifluorescence microscope equipped with a 63× objective (N.A. 1.3). Cells were imaged at 20-s intervals. Images were collected using Metamorph (Universal Imaging Corporation, Downington, Pennsylvania, United States) and analyzed with ImageJ (NIH) and Photoshop (Adobe Systems, San Jose, California, United States).

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514891

Equivalence and noninferiority trials – are they viable alternatives for registration of new drugs? (III)

The scientific community's reliance on active-controlled trials is steadily increasing, as widespread agreement emerges concerning the role of these trials as viable alternatives to placebo trials. These trials present substantial challenges with regard to design and interpretation as their complexity increases, and the potential need for larger sample sizes impacts the cost and time variables of the drug development process. The potential efficacy and safety benefits derived from these trials may never be demonstrated by other methods. Active-controlled trials can develop valuable data to inform both prescribers and patients about the dose- and time-dependent actions of any new drug and can contribute to the management and communication of risks associated with the relevant therapeutic products.

Background In an era of cost containment, the need for rigorous examination of the cost-effectiveness of drugs, as well as their clinical effectiveness, is widely recognized not only by governments but also by the pharmaceutical industry [ 1 - 4 ]. Messages framed differently, but with the same basic content, have reached the community of prescribing physicians, who have come to understand that, although an effective drug may be prescribed for patients who would benefit from it, unless the drug is cost-effective, the resources that are expended might produce greater benefits for other patients. Such messages and updated recommendations to prescribing doctors, in addition to results derived from recent large, randomized trials, continue to have only minimal, if any, impact on the prescribing habits of doctors. The latest such example [ 5 ] concerns the outcomes of the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT), indicating that diuretics could be more effective than angiotensin-converting enzyme (ACE) inhibitors or calcium channel blockers in the treatment of hypertension, and at a much lower cost [ 6 ]. Despite this convincing evidence, a study presented at the annual conference of the American Heart Association in March 2004 showed that spending on antihypertensive drugs essentially doubled (from approximately $6 billion to approximately $12 billion) between 1990 and 2002. The explanation most commonly offered is that "doctors selected the more costly antihypertensive agents." Since cost-effectiveness is conventionally required for evaluating the efficacy of alternative healthcare interventions, the perspective commonly taken is that of the health services [ 7 ]. Therefore, establishing the superiority or equivalence of a new intervention relative to the standard one has been extended not only to new drug entities, but also to generic versions of innovator drugs [ 8 ], surgical techniques [ 9 ], medical devices [ 10 ], and such diverse factors as medical protocols [ 11 ]. Cost-effectiveness and clinical effectiveness should be pursued simultaneously to ensure that health care is efficient, ethical, and beneficial to patients. This paper deals with only one aspect of clinical effectiveness: drug treatment benefit and how it may be ascertained from claims of therapeutic equivalence. Ethical Issues The basis for the scientific and ethical underpinnings for the design and conduct of randomized clinical trials is the uncertainty principle , which states that a patient should be enrolled in a randomized controlled trial only when substantial uncertainty exists as to which of the trial treatments would benefit the patient more [ 12 ]. From this principle derives the fundamental ethical challenge of equivalence trials, reflected in the researcher's explicitly expressed belief that "the new drug might be not different from the old drug," a fact that should be acknowledged in the consent process whereby trial subjects are informed that "it is not known which drug is better or whether they are the same." Nevertheless, demonstrating equivalence of the drugs being compared implies starting from the assumption that the new drug is better. In other words, the hypothesis to be tested in equivalence trials (and the hypothesis that is refuted if equivalence is shown) is that one treatment is superior to the other. Altruistic patients are more likely to agree to participate in such a trial, whereas other, less altruistic patients are more likely to decline participation, as their interest lies in treatments with proven efficacy. Obviously, this situation is more patient-favorable than are placebo-controlled trials, in which the individual patient's well-being may be subordinated to the good of others [ 13 , 14 ]. Placebo-controlled trials are still used extensively to demonstrate the effectiveness of new drugs; however, a paradigm shift appears to be steadily emerging in this area [ 15 , 16 ]. Speaking metaphorically, Urquhart stated that placebos are predestined to be "roadkill on the highway of medical progress" [ 17 ]. For circumstances in which no increased risk for patients is foreseen, use of placebo-controlled trials seems appropriate and ethical, provided the patients are fully informed and that they give their written, informed consent. However, if these patients and their doctors were to find the placebo-controlled studies inappropriate, and if they were to exercise their option in large numbers, these studies would become unfeasible, regardless of the ethical justifications, scientific considerations, views of the trial sponsor, or, ultimately, the expectations of regulatory authorities. Apart from the extreme opinions that challenge the placebo-controlled trials as unethical [ 18 - 24 ] and those that advocate proactive use of the active-controlled equivalence trials [ 25 , 26 , 31 ] or question their scientific merits [ 16 , 26 - 32 ], a balanced approach is needed (i.e., one that recognizes the use of placebos in instances wherein efficacy cannot otherwise be demonstrated, and the use of active-controlled trials as the design of first choice when scientifically sound circumstances require it). Simultaneous use of both alternatives might be necessary in selected cases. The issue of assay sensitivity Defined as "the ability of a study to distinguish between active and inactive treatment," assay sensitivity is the sine qua non for the validity of equivalence claims derived from any active-controlled equivalence/noninferiority study. Methodological flaws affecting one or several of the specific elements inherent in assay sensitivity itself seem to have been more a rule than an exception in many trials carried out during the past decade. Illustrating this point is a systematic review of trials published between 1992 and 1996 that claim equivalence [ 33 ]. In the review, the authors showed that: • 88 papers were evaluated for five equivalence-specific methodological attributes. • Only 45 (51%) of the 88 reports specifically identified demonstration of equivalence as their aim; the others attempted to show superiority or did not state any research aim. • An equivalence boundary was set and confirmed with an appropriate statistical test in 23% of the reports; in 67% of reports, equivalence was declared after a failed test for comparative superiority; in 10%, the claim of equivalence was not evaluated statistically. • Sample sizes were calculated in advance in 33% of reports. • In 25% of reports, sample size was 20 patients per group or fewer. The main concern with such "equivalence claims" is certainly the risk of harm to patients, as poor sensitivity has the potential to cause a type II error (false conclusion of no efficacy) and thereby to thwart satisfaction of public health needs for effective medicines. Just as important as paying careful attention to all aspects of assay sensitivity is acknowledging from the outset that a large number of pharmaceutical products present sensitivity problems. That is, agents otherwise known to be clinically effective are often indistinguishable from placebo in well-designed and well-conducted trials. For this reason, such drugs are useless as comparators in active-controlled trials. A typical example is ondansetron, an antiemetic that, despite its known clinical effectiveness, showed no effect in many placebo-controlled trials [ 34 ]. Claims of equivalence of a new antiemetic agent with ondansetron would therefore be unreliable, given the lack of assay sensitivity of ondansetron (despite many trials in which it had proven to be superior in comparison with placebo). Similar examples include agents belonging to the class of antidepresssants, analgesics [ 35 ], beta-blockers used in postinfarct patients [ 36 ], antihypertensives, ACE inhibitors used in patients with heart failure, antianginal agents, and antihistamines. The explanation for this serious problem lies in the great variability of the random placebo effect, which at times may profoundly confound the direction and the magnitude of treatment effects, especially in studies based on small sample sizes [ 37 ]. Regarding the example of ondansetron, the incidence of nausea and vomiting ranged from 10% to 96% in the placebo-controlled trials. Furthermore, regarding situations in which multiple trials have demonstrated the efficacy of the active control when compared to placebo, the potential exists for referral bias due to eventual nonreporting of negative results. The risk in such instances is that the smallest clinically relevant effect of the control drug may not be valid [ 38 ]. Rationale for choice of active control In contrast to the scenarios described above, equivalence and noninferiority trials should be undertaken only when a well-proven standard therapy exists (i.e., when the intended control drug is accepted as the standard of care for the particular indication). Investigators should be confident that the efficacy of the control drug was proven to be superior in a previous placebo-controlled trial and that this efficacy will be preserved under the conditions of the current trial (i.e., the control drug has an established, predictable and quantifiable effect). Doubts about the validity of these assumptions mean uncertainty as to whether the two drugs in the current trial, which are allegedly equivalent, really are effective to a similar degree, or are equally ineffective, or cannot be evaluated definitively because the trial design was inadequate to demonstrate the real differences between the two agents. The goal of showing equivalence A recent editorial by Alderson [ 39 ] concluded as follows: "We need to create a culture that is comfortable with estimating and discussing uncertainty." This observation applies especially to the field of equivalence/noninferiority trials. Increasing the degree of certainty in these trials is a matter of paying careful attention to the elements of study design, conduct, and analysis – all supposed to mirror as closely as possible the design, conduct, and analysis performed in previous evaluations of the current active control against placebo. Such trials should be reported in a transparent and explicit fashion, to acknowledge that they are not really equivalent to superiority trials [ 40 ]. The primary objective of equivalence/noninferiority trials is to demonstrate that the efficacy of the new treatment matches that of the control treatment. However, "equivalence" should not be interpreted to mean 100% (absolute equivalence can never be demonstrated), but that despite some degree of difference, the two agents are clinically indistinguishable. Closer scrutiny should be afforded the secondary objectives of the study, as they might demonstrate some sort of superiority over the control, such as a more favorable safety profile, easier administration, or reduced cost. Alternatively, results might indicate that the new agent would be a reliable second-line treatment. All too often in the past, when trials that were designed to demonstrate the superiority of an agent over its comparator failed to reject the null hypothesis (i.e., a statistically significant difference was not demonstrated), results were interpreted as proof of the equivalence of the two drugs. A dangerous mismatch of the goals of the superiority and equivalence trials arises when the general reasoning employed in planning and evaluating superiority trials is simply extrapolated to active-controlled trials. The aim of the superiority trial is to rule out the equality of the two agents being compared by rejecting the null hypothesis that the two agents are the same. Failure to reject the null hypothesis does not mean that equivalence can be assumed. Lack of superiority might be consistent with equivalence but does not prove it. In other words, "absence of evidence of a difference is not evidence of absence of a difference" [ 41 ]. In equivalence trials, the goal is to rule out all differences of clinical importance between the two agents being compared. This goal is accomplished by rejecting the null hypothesis that the smallest difference of clinical importance exists in favor of the standard-of-care regimen (i.e., in favor of the active control in the current trial). Therefore, establishing equivalence is contingent upon determining what specifically and precisely constitutes a clinically important difference. This process translates into the need to prove that the two interventions do not differ by more than a certain amount, defined as the "equivalence margin" (i.e., the tested agent is not inferior to the active control by more than the predefined margin). Methodological requirements Patient compliance with therapy To assure the adequacy of the compliance component of assay sensitivity, prescreening of subjects selected to participate in active-controlled trials is necessary, as is reliable assessment of patient compliance with the trial requirements by means of appropriate methodologies [ 42 , 43 ]. Commonly, compliance is defined as the degree of correspondence between the patient's current dosing history and the prescribed drug regimen [ 44 ]. This seemingly simple definition covers the wide variability in patient compliance in the use of prescribed drugs. The degree of drug exposure has an impact on important clinical outcome variables and cost-effectiveness parameters [ 45 , 46 ]. Knowledge of the drug's kinetics and dynamics may allow pharmacokinetic/pharmacodynamic modeling, to address the consequences of temporal dosing patterns that result from variations in patient compliance with the recommended treatment regimen [ 17 ]. The most compelling example of treatment noncompliance occurs with antihypertensive medications. Noncompliance seems to be the main reason that blood pressure is adequately controlled in fewer than one fourth of patients treated for hypertension, both in the US and in European countries [ 47 , 48 ]. The classical "pill count" method of assessment grossly overestimates patient compliance, as self-reporting of medication use is highly skewed toward reports of excellent compliance [ 49 ] Over-reliance on inaccurate self-reports of compliance in research studies can result in misleading conclusions about both the efficacy of treatment and the dose-response relationships [ 48 ]. Electronic pill boxes that register the date and time of each access have become the "gold standard" and could be a valuable complement to conventional self-reporting of compliance [ 50 , 51 ]. Furthermore, compliance with the protocol-specified regimen can be improved by prescreening patients who are eligible for recruitment to active-controlled studies, with the aim of assessing the ability of individuals to comply with study-specific requirements. Concomitant medication Use of co-medication during active-controlled studies, whether the result of self-medication or prescription medication, can distort the study's final results. Co-medication can interfere with response to the tested drug or the control drug, or it can influence the trial endpoints and lead to false-positive conclusions of equivalence. Use of non-trial medication is quite common in clinical trials in general and should be assessed and minimized, particularly in active-controlled studies. Patients' baseline characteristics and outcome features A basic assumption is that the active agent in an equivalence/noninferiority study should have retained its known (historical) effect, demonstrated in a previous placebo-controlled comparison. Patients participating in the current study should be as similar as possible to the patients in the placebo-controlled trial with respect to all baseline values and treatment variables that might influence outcome. These variables include symptoms, signs, risk factors, morbidity, compliance with therapy, responsiveness to drug effects, nonuse of prohibited concomitant medication, consistent diagnostic criteria, inclusion and exclusion criteria, unbiased assessment of endpoints, and reasons for dropping out. Failure to achieve this similarity from the outset, failure to ensure high-quality study conduct, or both, can introduce bias into the study and compromise assay sensitivity. The classical method to minimize systematic differences between study groups is randomization , (i.e., random allocation of patients to test or control groups). Further, double blinding is intended to minimize potential biases resulting from differences in management, treatment, or assessment of patients, or differences in interpretation of results that could arise as a result of the subject's or investigator's knowledge of the assigned treatment. The type and frequency of outcome events in the current study are expected to be similar to those in the placebo-controlled comparison. Substantial differences, resulting most often from an imbalance in one or more of the variables mentioned above would render interpretation of differences between the new therapy and the active control very difficult. For example, because of lower baseline blood pressure values and fewer associated risk factors, patients in a hypertension study may display fewer outcome events. Choice and importance of outcome variables Equivalence trials are commonly designed to demonstrate that the test treatment is similar in efficacy to the active control, the assumption being that the control treatment is effective under the conditions of the current trial. In reality, however, most equivalence trials are actually noninferiority trials, attempting to show that the new drug is not less effective than the control by more than the defined amount (margin). Presence of assay sensitivity is essential for interpretation of such a study. In cases with doubtful assay sensitivity, a three-arm study design (test drug, active control, and placebo) might be optimal. Apart from being more complex and requiring a larger sample size, such a trial offers the advantage of measuring the effect of the test drug versus placebo while allowing comparison of the test drug and active control in a setting in which assay sensitivity is established by the active control-versus-placebo comparison. By making the active groups in such trials larger than the placebo groups, it is possible to increase the precision of the active drug comparison while minimizing the chance that patients will be randomly assigned to placebo groups. Furthermore, this design allows distinction between adverse events due to the drug and those due to underlying disease ("background noise") [ 52 ]. As mentioned earlier, equivalence/noninferiority trials should not only focus on efficacy, but also should prospectively define an analytical plan for safety assessment as a secondary objective. Accordingly, appropriate statistical power to detect adverse effects is a necessity, as is collection of data on the comparative safety of each treatment. Failure to meet these requirements not only undermines the chance to exploit a potentially favorable safety profile of the test drug versus the control, but also presents the risk of missing dangerous signals with regard to safety. A recent example relates to mibefradil, a calcium inhibitor that appeared to have an excellent safety profile until postmarketing surveillance revealed cases of sudden death in patients at high risk for polymorphic ventricular tachycardia or patients in whom concomitantly administered drugs either inhibited mibefradil metabolism or otherwise amplified its cardiac risk [ 53 ]. A more recent experience with COX-2 inhibitors illustrates another significant problem in current evaluations of new drug safety. In the VIGOR study [ 54 ], the extensively marketed product rofecoxib appeared to be inferior to naproxen with regard to the frequency of cardiovascular thrombotic events, raising the question of rofecoxib's inferiority versus naproxen's superiority to an imputed placebo [ 55 ]. Confidence interval and sample size The margin (Δ) itself clearly communicates a judgment as to what is and is not important. The margin defines the largest difference that is clinically acceptable. Setting the margin is critical to the design of both equivalence and noninferiority trials, and it is commonly established for the purpose of excluding a clinically important difference between treatments. However, what constitutes such a difference may vary widely for each patient and clinician and might fall below the margins set by the designer of the trial. For that reason, careful clinical judgment and statistical reasoning should be exercised in selecting a meaningful difference to be ruled out; furthermore, this difference should be specified and justified a priori in all equivalence/noninferiority trials. At the very least, the equivalence margin should be smaller than the lower 95% confidence limit for the absolute risk difference observed between standard therapy and placebo in the relevant superiority trial [ 31 ]. That is, this lower boundary of the 95% confidence interval is the smallest expected effect of the control over the placebo, and it should exceed the established margin [ 29 , 38 ]. Confidence interval is the method of choice to interpret equivalence and noninferiority trials. It defines a range for the possible true differences between the test drug and the active control. If every point within this range reflects a difference that is clinically nonrelevant, then the two agents may be considered equivalent. In other words, for an equivalence trial, the two-sided 95% confidence interval – defining the range of possible differences between the test and the control agent – should lie entirely within the interval (-Δ to +Δ) (Fig. 1 , lines c, d, and e). Figure 1 Confidence interval approach to analysis of equivalence and non-inferiority trials. For a noninferiority trial, the effect of the new drug may be shown to be similar to or greater than that of the control. The possible difference of interest occurs only in the - Δ direction, and the 95% confidence interval should lie entirely to the right of the - Δ value (Fig. 1 , line a). A p value associated with the null hypothesis of noninferiority can be calculated. A trial that is intended to demonstrate noninferiority may actually allow a claim of superiority for the test drug. In such a case, the one-sided 95% confidence interval lies to the right of not only the - Δ but also the zero line (Fig. 1 , line g). A p value can be calculated to verify whether the superiority test is sufficiently small to reject the hypothesis of no difference at the 5% α level (p < 0.05). A claim of superiority, however, would imply a careful assessment of the test drug's safety profile, which should be similar to or better than that of the control to increase the strength of the evidence in favor of superiority. A less favorable safety profile raises the question of whether the claimed superiority outweighs the eventual adverse effects and therefore requires a careful quantification of the overall risk-benefit in clinical terms. This latter emphasis is meant as a reminder that claimed superiority of a test agent in the context of a noninferiority trial is, in fact, superiority to "no treatment," based on the proven superiority of the control agent against placebo in a previous trial. Another possible scenario is that of a superiority trial that fails to detect a significant difference between the two agents being compared. An investigator who anticipates this outcome at the outset of the trial may want to downgrade the goal from superiority to noninferiority. That change is legitimate, provided that a noninferiority margin has been prospectively defined and the 95% confidence interval shown to lie to the right of the - Δ (Fig. 1 , lines a and f). A post hoc definition of the margin is not acceptable. For calculating sample size, values should be specified for the range of equivalence (Δ), and the α (type I error) and β (type II error) values should be selected on the basis of the same principles as for comparative trials. The distinction between one-sided and two-sided tests of statistical significance carries over into the confidence interval approach recommended by the Committee for Proprietary Medicine Products (CPMP) guidelines [ 56 , 57 ], which provide key information for making decisions about equivalence/noninferiority. Unlike superiority trials, in which intention-to-treat analysis is the rule, in equivalence/noninferiority trials both intention-to-treat and per-protocol analysis should be run. Both types of analysis would be expected to lead to similar conclusions for a robust interpretation. In a recent article, Gomberg-Maitland et al. [ 58 ] suggested the use of standard guidelines for reporting equivalence/noninferiority trials to facilitate qualitative assessment of the methodology applied (Table 1 ). Table 1 Guidelines for reporting equivalence/noninferiority trials. ( From Gomberg-Maitland et al ). 1. A table comparing the inclusion and exclusion criteria with those of previous trials on which the standard therapy was based. 2. A flow diagram delineating the number of eligible patients screened, the number randomised, the number of patients assigned to each group, the number of withdrawals and crossovers, and the number of patients in each group who successfully completed the trial on assigned treatment. 3. A statement on the projected and actual total treatment exposure (patient-years), the minimum per-patient exposure, and the respective impact of withdrawals and crossovers on exposure to initially assigned treatment. 4. The rationale of setting the margin of acceptable difference with specific reference to the minimum clinically important treatment effect and with the established efficacy advantage for the control over placebo. Where event rate ratios or floating margins are utilized, the rationale for their use, their prespecified criteria for adjustment, and the margin or ratios used to determine sample size should be provided. 5. The minimum requisite number of primary events should be established at the outset. 6. A comparison of event rates during treatment with the active control in the trial and in the historical trials that established its efficacy compared with placebo. Conclusions Each year, major advances in drug discovery generate a seemingly endless supply of new drugs in virtually all therapeutic areas; however, in most cases these new drugs provide only incremental improvement in efficacy, safety, or the overall risk-benefit ratio. In addition, ethics-based restrictions on the use of placebos as comparators have enhanced the viability of equivalence and noninferiority trials as viable alternatives for registration purposes, for risk management once the drug is on the market, and for a marked increase in confidence in the new drug on the part of doctors and patients. Given the complexity of these study designs, careful attention should be paid to the proper use of specific epidemiological features so as to avoid methodological deficiencies that may harm patients if clinically inferior treatments are erroneously deemed equivalent to the standard of care, or if potentially superior therapies are discarded as merely "equivalent."

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Locomotor activity in common spiny mice (Acomys cahirinuse): The effect of light and environmental complexity

Background Rodents typically avoid illuminated and open areas, favoring dark or sheltered environments for activity. While previous studies focused on the effect of these environmental attributes on the level of activity, the present study tested whether the spatio-temporal structure of activity was also modified in illuminated compared with dark and complex compared with open arenas. For this, we tested common spiny mice ( Acomys cahirinus ) in empty or stone-containing arenas with lights on or lights off. Results In an illuminated or open arena, spiny mice moved in less frequent but longer trips with relatively long distances between consecutive stops. In contrast, in either a dark arena or an arena with stones, the animals took shorter and more frequent trips, with more stops per trip and shorter inter-stop distances. In illuminated arenas spiny mice remained mainly along the walls, whereas locomotion in the center was more prevalent in dark empty arenas, and was carried out along convoluted paths. Increasing environmental complexity by adding stones to either illuminated or dark arenas increased locomotion along straight trajectories and away from walls. Conclusions Earlier findings of reduced activity in illuminated or open areas have been extended in the present study by demonstrating changes in the spatio-temporal structure of locomotor behavior. In the more complex arenas (with stones) spiny mice traveled along short straight segments whereas in the open their trips were longer and took the shape of a zigzag path which is more effective against fast or nearby predators. Alternatively, the zigzag path may reflect a difficulty in navigation.

Background Rodents typically avoid illuminated and open areas, favoring dark or sheltered environments for activity. Indeed, higher activity was described in numerous field and laboratory studies of nocturnal species tested in the dark, compared with their activity when tested under light. For example, common spiny mice ( Acomys cahirinus ) decreased activity and foraging in open spaces under moonlit compared with dark nights [ 1 ]. When tested in the dark, laboratory rats increase their activity and display behaviors that indicate reduced habituation, fear and anxiety [ 2 ]. Deermice ( Peromyscus maniculatus ) were shown to reduce activity in the open during moonlit nights and were active only near objects such as rocks, grasses, and walls, where they could successfully evade a predator attack [ 3 ]. Thus, it appears that rodents perceive increased risk of predation in open spaces and/or during moonlit nights and in consequence shift their activity to more protected microhabitats [ 4 - 7 ]. While many of these studies used indirect measures of locomotor activity, such as footprints [ 8 ], the present laboratory study was aimed at direct observation of locomotor behavior under various light levels and arena complexities. The 'open field' is a widely used apparatus in laboratory studies of rodents' locomotor activity [ 9 ]. This apparatus has been criticized for being "a poor and explicitly aversive environment with excess light and open spaces..."[ 10 ]. Nevertheless, it is a relatively simple testing environment for a variety of species, in which they display a typical behavioral structure [ 11 ] that withstands drastic environmental changes [ 12 ]. Studies in wild and laboratory rodents in an illuminated open field (e.g., [ 9 , 11 - 14 ]) have shown that their locomotor behavior is organized in reference to a key location – the home-base. At the home base, the rodent demonstrates typical behaviors (e.g. grooming and crouching), and sets out on round trips in the area. The building block of the round trip is a stop, with an upper limit of 8–10 stops per trip [ 15 ]. The limited number of stops/trip is preserved by scaling the distance between successive stops and adjusting the number of trips, even under large changes in arena size [ 12 , 16 ]. Accordingly, rodents in a larger area made fewer yet longer trips, whereas in a small area they made shorter but more frequent trips. Following these earlier studies, the present study tested open field behavior under varying light level and arena complexity. The common spiny mouse ( Acomys cahirinus ) was selected for this study since it is a strictly nocturnal species that displaces other species to crepescular or diurnal activity [ 17 , 18 ]. Common spiny mice were thus expected to be sensitive to tests in illuminated compared with dark environments. Also, they live in rocky environments, nimbly foraging in crevices between and under rocks and boulders [ 18 , 19 ], where the complex habitat structure provides shelter and escape from predators. They were thus expected to be also sensitive to changes in environmental complexity. Three questions were posed in this study of common spiny mice: i) is their behavior in an illuminated arena similar to that seen in mice, rats, and voles? ii) does behavior change in dark arena and/or with increased environmental complexity? iii) what is the functional mechanism that may underlie behavioral changes in dark or complex environments? As shown below, activity increased in dark or in complex environment, and took a different form of short straight trajectories. In contrast, spiny mice traveled through the center in a convoluted path in either lit or dark empty arenas. This later form of progression may have a defensive advantage. Results Level of locomotor activity In the illuminated arena, the distance traveled by spiny mice was significantly affected by the density of stones. In contrast, neither the number of stones nor arena size alone significantly increased activity. As shown for small arena in Fig. 1 , traveled distance was significantly greater when four stones were present than when stones were absent. Traveled distance was not greater in comparing small with large empty arenas, or small with large 4 stone arenas. Therefore, changing arena size alone did not increase activity. However, stone density of four/m2 significantely increased activity, as shown for small arena with four stones or large arena with 16 stones (Fig 1 ). This trend of increased activity with increased stone-density was also echoed in traveling speed (Table 1 ). Figure 1 Distance traveled (mean ± SEM) in the lit arenas (open bars) and dark arenas (dark bars). Arena size and number of stones in each arena are depicted along the x-axis. Significant comparisons, as revealed in Tukey HSD test, are depicted by lines at top left. As shown, traveled distance did not change with only arena size. Adding four stones to a small arena significantely increased traveled distance (compare small arena with 0 and with 4 stones); however, adding 4 stones to a large arena did not have a significant effect. In the dark arena, the number of stones did not have a significant effect on the traveld distance. Table 1 Parameters of locomotion in an illuminated small arena (1 × 1 m) and large arena (2 × 2 m). For most variables, values increased when stones were added or when arena size was increased. Bonferroni adjustment of p-value was calculated by P = 0.05/10 = 0.005. Mean (± SEM) are followed by superscript numerals that indicate the significantely different test groups (as appeared in the top row) in Tukey Honest Significant Difference (HSD) test. Small arena Large arena Empty (1) 4 Stones (2) Empty (3) 4 Stones (4) 16 Stones (5) F 45 ;p Level of activity Traveled distance (m.) 52.0 ± 9.7 2,4,5 86.7 ± 8.8 1 60.9 ± 9.5 5 90.4 ± 9.7 1 115.6 ± 7.3 1,3 8.68; <0.0001 Speed (m/sec) 0.10 ± 0.02 2,3,5 0.15 ± 0.04 1,5 0.12 ± 0.02 4,5 0.18 ± 0.02 1,3,5 0.36 ± 0.12 1–4 5.68; = 0.0012 Temporal Structure Stops 87.0 ± 31.4 2,4,5 228.6 ± 55.7 1,3,4 51.2 ± 13.9 2,4,5 146.9 ± 23.9 1–5 235.8 ± 48.6 1,3,4 7.15; = 0.0002 # of trips 18.5 ± 5.5 2,4,5 41.4 ± 11.0 1,3 12.2 ± 5.0 2,4,5 38.5 ± 7.8 1,2,5 74.7 ± 25.2 1,3,4 5.81; = 0.001 Stops/trip 5.0 ± 0.6 5.6 ± 0.4 5.5 ± 1.2 4.4 ± 0.6 3.6 ± 0.3 0.95; ns Trip length 4.9 ± 1.4 3,5 2.4 ± 0.4 3 10.2 ± 2.3 1,2,4,5 3.1 ± 0.6 3,5 2.0 ± 0.3 1,3,4 5.88; = 0.0009 Inter-stop distance (m.) 0.94 ± 0.22 0.43 ± 0.06 2.68 ± .1.14 0.70 ± 0.09 0.54 ± 0.06 2.51;ns Spatial Distribution Center stops (%) 9.3 ± 1.5 2–5 22.6 ± 4.9 1,5 55.5 ± 30.8 1 20.3 ± 1.9 1,5 41.7 ± 2.8 1,2,4 3.08; = 0.0277 Center time (%) 2.4 ± 1.1 2,4,5 19.2 ± 6.1 1,3 2.4 ± 1.1 2,4,5 12.8 ± 3.9 1,3,5 25.5 ± 7.1 1,3,4 8.99; <0.0001 Meander (deg/m) -1.87 ± 0.31 2 -0.99 ± 0.36 2 -1.52 ± 0.19 4,5 -0.60 ± 0.16 3,5 -0.46 ± 0.09 3,4 7.68; <0.0002 In a dark arena, the level of activity resembled the highest level that was measured in the illuminated arena, and did not vary significantly with the number of stones (Fig. 1 ). Thus, activity of spiny mice in a dark arena was steady and high, regardless of the number of stones or their density (Table 2 ). Table 2 Parameters of locomotion in a dark large arena (2 × 2 m). As shown, level of activity was not affected, whereas the spatiotemporal structure underwent significant changes. Bonferroni adjustment of p-value was calculated by P = 0.05/10 = 0.005. Mean (± SEM) are followed by the results of Tukey HSD test, indicating the numbers of the significantely different test groups (as appeared in the top row). Empty (1) 4 Stones (2) 16 Stones (3) F 18; p Level of activity Traveled distance (m.) 116.51 ± 7.52 110.17 ± 11.58 99.09 ± 10.38 0.91; ns Speed (m/sec) 0.21 ± 0.02 0.21 ± 0.02 0.20 ± 0.01 0.24; ns Temporal Structure Stops 159.1 ± 18.2 3 185.6 ± 9.4 3 322.7 ± 32.0 1,2 18.67; .0004 # of trips 40.14 ± 5.53 2,3 62.57 ± 3.26 1,3 134.14 ± 13.97 1,2 36.68; 0.000001 Stops/trip 4.04 ± 0.23 2,3 3.01 ± 0.23 1,3 2.41 ± 0.04 1,2 21.20; 0.00019 Trip length (m.) 3.08 ± 0.26 2,3 1.81 ± 0.25 1,3 0.74 ± 0.04 1,2 36.41;0.00000 Inter-stop distance (m.) 0.77 ± 0.07 2,3 0.59 ± 0.05 1,3 0.31 ± 0.01 1,2 26.75; <0.00001 Spatial Distribution Center stops (%) 25.8 ± 1.3 2,3 49.8 ± 4.8 1,2 70.0 ± 1.0 1,2 66.09; 0.00000 Center time (%) 29.3 ± 4.2 2,3 53.4 ± 6.0 1 57.7 ± 3.6 1 11.58; 0.00058 Meander -0.44 ± 0.03 1,2 -0.33 ± 0.02 1,3 -0.29 ± 0.05 1,2 7.10; 0.0053 Temporal organization of locomotor activity In illuminated arenas, increases in traveled distance were echoed in the number of stops, and it was not possible to distinguish whether the increase in stops was directly linked to increased traveled distance, or whether it was due to the increased number of stones. In the dark arena, however, traveled distance was not different in the three groups (Table 2 ; Fig. 1 ), but number of stops increased with number of stones, indicating that stops depended on the number of stones and not on the traveled distance. The number of trips to the home base increased with the number of stops, which increased with the number of stones. However, the mean number of stops in a trip did not vary in the various groups tested in the illuminated arena (Table 1 ). As shown in Table 1 , in the absence of stones, trip length significantly increased with arena size and spiny mice took fewer but longer trips in the large arena compared with more but shorter trips in the small arena. In addition, inter-stop distance was significantly higher in the large compared with the small illuminated arena. Consequently, the traveled distance was similar in both small and large arenas with same number of stones (Table 1 and Fig. 2 ). Figure 2 Scaling of interstop distance according to arena size. In the small arena (left illustration) the spiny mouse takes two round trips that start and end at the home base (top left corner), stopping only in the corners of the arena (4 stops/round trip, including the stop at the home base). In the large arena, the spiny mouse takes one trip, stopping only at the corners of the arena (again, 4 stops). Thus, trip length and interstop distance are shorter in the small arena, and the number of trips and overall number of stops are smaller in the large arena. The shorter but more frequent trips in the small arena and longer but fewer trips in a large arena result in the same overall traveled distance and the same number of stops per trip. When the number of trips increased with increase in number of stones, trip-length and inter-stop distance decreased, reflecting the tendency of spiny mice to stop at or near stones. Changes in the number of stops/trip were non-significant (Table 1 ). Overall, these changes imply that with increase in number of stones, spiny mice set out from the home base to more trips in the arena, but these trips were shorter in distance, had a shorter distance between successive stops, but preserved a relatively invariant number of stops per trip. A similar trend was evident in the dark arenas, where with increase in number of stones, spiny mice took more trips that were shorter in length and in inter-stop distance. However, the non-significant decrease in the number of stops per trip that was noted in illuminated arenas with increased number of stones, reached statistical significance in the dark. Indeed, the number of stops/trip significantly decreased in 4-stone and in 16-stone arenas (Table 2 ). Overall, while the level of activity underwent conspicuous changes in illuminated arenas and remained steady in dark arenas, the temporal structure of locomotor behavior underwent similar changes in both illuminated and dark arenas. Spatial distribution of locomotor activity and path shape In empty illuminated arenas, spiny mice spent more than 80% of the time in the corners, the rest of the time mostly along the walls, and as little as 3% of the time in the center. Adding stones changed this pattern and the animals spent 13–26% of the time in the center, as well as stopping more frequently in the center (Table 1 ). In the dark, however, spiny mice spent 30–60% of the time and 30–70% of their stops in the center, with both percentage of time and stops increasing with increase in number of stones (Table 1 ). In both small and large empty arenas, either dark or illuminated, spiny mice moved through the center in a convoluted path, changing frequently the direction of progression. When stones were added, trajectories comprised of more straight segments and fewer changes in direction of progression (Fig. 3 ). This change was reflected in the Meander index, which describes the angular change in direction of progression relative to distance moved. As shown, the meander was high without stones, and significantly decreased when stones were added (Tables 2 & 3 ). Changes in the level of activity and its spatio-temporal structure are summarized in Table 3 . Figure 3 Trajectories of locomotion of exemplary spiny mice in lit arenas (top) and dark arenas (bottom). Each square shows one spiny mouse. As shown, in both small and large empty arenas, either dark or lit, spiny mice moved through the center in a convoluted path, changing frequently the direction of progression. Locomotion in the center increased in the dark or with the number of stones. With stones, trajectories of locomotion comprised more straight segments and fewer changes in direction of progression. Table 3 Formal summary of the results shown in Tables 1 and 2. Dark vs . light With lights on With lights off Level of activity Distance traveled and speed Longer distances Increase with stone density Remains high Temporal structure # of stops and trips More stops and trips More stones = more stops and trips Trip length Shorter trips More stones = sorter trips Stops/trip Fewer stops/trip Did not change Decreased Spatial distribution Path shape Winding (zigzag) paths More stones = straighter path Time and stops at the perimeter More time and stops in center More stones = more time and stops in center Discussion Spiny mice in the wild inhabit rocky mountains, dwelling in the crevices between and under rocks and boulders. It was therefore assumed that adding stones to an arena would create a complex environment, more resembling their natural habitat. Indeed, in an empty illuminated arena, spiny mice spent extended periods in the corners, traveling mainly along the walls, rarely entering the center of the empty arena where they traveled in a winding path. When stones were placed in the illuminated arena, the animals traveled significantly longer distances, as expected. While it was the density of stones rather than their number that accounted for the increased activity in the illuminated arena, introducing stones into a dark arena did not affect the level of activity, and the distance traveled was high regardless of number of stones or their density. In the following discussion it is proposed that increased activity is due to a sense of security and/or easier navigation provided by the stones whereas the convulted path in empty arena is a defensive strategy or a refelction of a dificulty of navigation in environment without landmarks or shelter (=stones). Numerous field and laboratory studies found increased activity in nocturnal prey species tested in the dark, compared with their activity when tested under light [ 2 , 20 ]. In the same vein, foraging in rodents was shown to be closely associated with complex areas (shrubs) on bright nights but evenly distributed between sheltered and open areas on dark nights [ 8 , 21 , 22 ]. This avoidance of open areas probably reflects the finding that rodents are attacked and captured more frequently in the open [ 23 ]. It should be noted, however, that this anti-predatory pattern is effective against aerial raptors, but not necessarily against terrestrial predators, as indicated by the increased activity of snakes during dark nights [ 24 ], a time when rodents have higher activity. Therefore, the present findings that spiny mice avoid open illuminated spaces while demonstrating a higher level of locomotion in a more complex environment and/or in the dark areas, reinforces previous results on the effect of light level and habitat structure. The present study demonstrates a change in path shape when locomoting in the center: spiny mice traveled along convoluted trajectories and rarely took straight paths (Fig. 3 ). These frequent changes in the direction of progression decreased with the increase in number of stones, and were especially conspicuous in empty dark arena, when activity in the center was prevalent. This behavioral pattern is reminiscent of the finding that gerbils' foraging path [ 25 ]. A mathematical model [ 26 ] suggested that a zigzag trajectory is advantageous when encountering a close or fast predator, whereas a straight trajectory is advantageous in facing a distant and relatively slow predator. Spiny mice may therefore move in a zigzag pattern as a defence against aerial raptors (fast predator) or snakes (close predator). Indeed, when spiny mice were attacked by a barn owl, they continued to locomote fast while frequently changing direction of progression, forming a convoluted path [ 27 ]. Another explanation for the changes in path shape is that stones are landmarks, and without them, especially in the dark, spiny mice may have difficulty in navigating [ 28 ] and therefore move in a convoluted path. Once landmarks (stones) are available, mice can more easily navigate and travel in straight paths, whereas when stones are absent they travel in the relatively homogenous environment along a winding path. A reminiscent mechanism was described in desert ants ( Cataglyphis fortis ) that return to nest directly but not necessarily in a straight path, presumably turning as frequently to the right as they do to the left, to reduce overall directional bias [ 29 ]. A survey of the mechanisms that may underlie intermittent progression suggests that pauses increase the capacity of sensory systems to detect relevant stimuli, and may involve perceptual processes such as velocity blur, relative motion detection, foveation, attention and interference between sensory systems [ 30 ]. When stones (=landmarks) are present, stops are frequent and spatial information can be collected during stops, alowing traveling along straight trajectories, whereas the lack of such spatial information processing may result in a winding path, as seen in empty and/or dark arena. Light condition affected the spatial distribution of locomotor activity: while spiny mice remained most of the time along the walls of empty illuminated arenas, they increased the center time by 5–10 folds in complex environments. That the animals spent more time close to the walls in the empty illuminated arena compared with dark arena or complex arenas is unsurprising, probably linked to thigmotaxis, as shown in other rodent species (e.g., [ 20 , 31 - 33 ]). In the dark arena, however, center time and stops in the center were distinctly higher than in the illuminated arena, comprising 25%–70% of activity. This further supports the assumption that spiny mice move more in the center when afforded shelter by darkness and/or by the physical structure of the environment. Stopping may also have an anti-predatory role [ 34 ] since owls usually attack moving prey, after being stimulated by its movement [ 35 - 37 ]. In consequence, a common defensive strategy in prey species is to freeze and remain immobile in the face of life threat, in order to eliminate the auditory and visual cues that predators use in pinpointing prey [ 38 ]. In following the above discussion on a possible defensive significance of convoluted paths, it is possible that complex environment in the dark does not provide the same sense of security than it does in an illuminated arena. This could be a result of snake activity, which is higher in dark and complex habitats but lower in the open [ 22 , 24 , 31 ]. It should be noted, however, that the above explanations are not mutually exclusive, and stopping may have a synergistic role in orientation, physiological recovery, and anti-predatory defense [ 34 ]. The present results in spiny mice are thus consistent with previous similar results in rats and voles [ 15 , 16 ]. in that they indicate that the animals preserve activity level and temporal structure under changing arena size. This observation may be a general property of rodents' open field behavior, which is gained by scaling interstop distance and number of trips to the home base. When environmental complexity was increased by adding stones, the number of trips increased while their length decreased. Therefore, the higher level of locomotor activity in complex environments was the result of more frequent but shorter trips and not of longer trips. This was obvious in the dark arena, where level of activity was high regardless of environment complexity, while the number of trips increased and their length decreased with increase in space complexity. These differences in the structure of trips may serve as a search-image parameter in other studies in spiny mice. For example, it is expected that foraging (e.g. traveling to food patches) will be longer in distance and less frequent in illuminated or exposed environments, but shorter and more frequent in a dark or sheltered area [ 39 ]. Long trips in the open are more risky, however, and spiny mice therefore need to undertake measures that reduce this risk. One possible way of reducing risk may be achieved by changing the distribution of activity and path shape, as described above. Conclusions The present results follow previous studies that demonstrated lower activity in illuminated and open areas compared with dark and complex areas. Observations on the behavior of spiny mice under these conditions revealed changes in the number and length of trips, in stopping frequency, and in path shape. Altogether, these changes reflect a flexible adaptation of locomotor activity to environmental conditions in a way that may be interpreted as aimed at efficient navigation, preserving the temporal structure of behavior, and reducion of predatory risk. Methods Study animals The common spiny mouse ( Acomys cahirinus ) weighs 38–44 g and is 11 cm long, plus a 10-cm tail [ 40 ]. Spiny mice are an exceptional genus among murid rodents (Muridae) in being precocial and not having a nest. They differ from rats and mice in many aspects (see [ 41 ] for review); noteworthy are differences in depth perception [ 42 ], distance perception [ 43 ], exploration [ 44 ] and excitability [ 45 ]. We obtained 71 adult spiny mice bred in captive colonies at the research zoo of Tel-Aviv University. Fifty spiny mice were divided into five groups (n = 10; five males and five females per group); these groups were tested in a illuminated arena. The other 21 spiny mice were divided into three groups (n = 7; 3–4 males and 3–4 females per group); these groups were tested in a dark arena. The larger group size in light tests was due to the greater behavioral variability in light compared with dark tests. Several weeks before testing, the animals were housed in groups of 5–10, in metal cages measuring 40 cm × 70 cm and 25 cm, located outdoors in the zoo yard under natural (uncontrolled) temperature and light conditions. Overturned ceramic pots and wooden boxes were placed in each cage to provide shelter. Seeds, diced fresh vegetables, and live fly larvae were provided ad lib. Based on years of experience in maintaining colonies of spiny mice in our zoo, provision of water is unnecessary when sufficient fresh vegetables are provided. Apparatus A test arena was constructed by enclosing a tiled floor with plywood planks (50 cm high). Two arena sizes were used: 1 × 1 m and 2 × 2 m. Stones (tiles), 12 cm long, 12 cm wide and 6 cm high, were placed in the arena (details below). The arena was located inside an air-conditioned room (24°C), and could be illuminated by one of the following light-sources: (1) two 300 W light bulbs directed to the white ceiling in order to provide diffused illumination of the arena (Light tests); (2) two infrared lights ( Tracksys , IR LED Illuminator; UK) that emit light in a range invisible to rodents (Dark tests; light level was 0.0425 Lux as measured with Profisix Sbc, Gossen ). The video signal was recorded on a VCR (JVC HR-J737). Procedure C ages with spiny mice were brought to a room adjacent to the testing room 10 h before testing. For testing, a spiny mouse was removed in random order from the cage to a jar, and gently released from the jar into the center of the arena. Each spiny mouse was tested only once for 10 minutes, being randomly assigned to one of the above arenas. At the end of testing, animals were returned to the population at the research zoo. The first five groups of spiny mice (n = 10/group) were all tested in illuminated arenas under the following conditions: (1) small empty arena (no stones); (2) small arena with 4 stones; (3) large empty arena; (4) large arena with 4 stones; and (5) large arena with 16 stones (see Fig. 1 ). It should be noted that a setting of a small arena with 16 stones would have virtually prevent locomotion, and was therefore excluded. Three additional groups (n = 7/group) were tested in a large (2 × 2 m) dark arena with: i) no stones; ii) four stones; and iii) 16 stones, in order to compare the behavior in these three arenas with the behavior in the respective illuminated arenas. Behavioral analysis A tracking system ( Ethovision by Noldus, NL) was used for data acquisition. The tracking system was set to score the spiny mouse as "not moving" (=stopping) when its center of gravity moved at a speed lower than 2 cm/sec, or as "moving" when the speed exceeded this limit during tracking at a rate of 25 frames/sec. Each arena was divided into four zone types. These were corners – a 20 × 20 cm square at each of the four corners of the arena; walls – a 20 cm strip along the walls between the corner zones; stones – a 20 × 20 cm square centered with each stone; center , the remaining area that comprised the spaces between the stones and away from the walls and the corners of the arena. Based on our past studies, the parameters acquired from Ethovision were classified to represent three perspectives: i) level of activity, ii) temporal organization of locomotion, and iii) spatial distribution of locomotion. The parameters that were measured are described in Table 4 . Briefly, the level of activity refers to the amount of activity regardless of temporal structure of spatial distribution. For example, the metric distance traveled was measured regardless of whether it comprised intermittent or continuous locomotion, or whether it was along the perimeter or in the center of the arena. The temporal structure refers to the order of bouts of locomotion and stopping periods. Parameters on temporal organization were derived in past studies, showing that locomotor behavior is organized in relation to a home base; a place where a rodent spends the longest cumulative non-locomoting periods [ 11 , 12 , 16 ]. From the home base the rodent takes round trips in the environment. The spatial distribution was aimed at distinguishing where activity had occurred. For example, the same amount of activity with the same temporal structure could be executed along the perimeter of the arena, or only in its center. Alternatively, a spiny mouse could travel in a straight or a winding trajectory. For these, the representation of the spatial distribution of activity was required. Table 4 Parameters of locomotion that were measured for each spiny mouse. Behavior Description Level of activity Distance traveled Overall distance (m.) that a spiny mouse traveled during the 10-min observation. Traveling speed Overall traveled distance divided by the duration of locomoting periods (m/sec). Temporal organization Number of stops Incidence of "non-locomoting" intervals (stops), bounded by locomotion. Number of trips Trips are intervals between consecutive stops at the home base, which is the place with the highest rank among zones according to the accumulated "non-locomoting" intervals. Thus, a trip comprised progression out from home base through consecutive stops in the arena, until returning to the home base. Stops/trip Number of stops taken between two successive visits to the home base (= total number of stops divided by the total number of trips). Trip length Metric distance traveled in a round-trip to the home base (total distance divided by the total number of trips). Inter-stops distance The metric distance traveled between two consecutive stops (or, distance traveled in a "locomoting" interval = distance divided by number of stops). Spatial distribution Time spent along the perimeter (%) Calculated as percentage of the total time, in order to show how long spiny mice stayed at the vicinity of the walls of the arena, compared with the time spent in the center of the arena or near/on the stones. Stops along the perimeter (%) Calculated as percentage of the total stops, in order to show how many stops took place along the vicinity of the walls of the arena, compared with stopping in the center of the arena or at/on the stones. Meander The rate of change in direction of progression relative to the distance traveled, calculated automatically by Ethovision for each two successive time points by dividing the turn angle by the distance. Mean meander of each spiny mouse was used to calculate the mean of each group. + indicated a clockwise change in direction of progression, whereas - indicated a counterclockwise change. Thus, lower absolute (+ or -) meander values characterize locomotion along relatively straight trajectories, and higher meander absolute values describe circular or winding trajectories. It should be noted that meander is sensitive to tracking rate, animal size, and arena size. Therefore, meander may be compared only for the same animal size, same resolution, and same arena size. Statistics One way analysis of variance (ANOVA) was applied. Some of the data may not be strictly independent – i.e. trip length is the division of traveled distance by the number of trips, etc. – therefore, a Bonferroni correction was applied to set alpha level to 0.005 (0.05 divided by the 10 parameters that were used). Data calculated as proportions were transformed to the arcsine of the square-root-transformed raw data.

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526189

In vitro evaluation of the potential role of sulfite radical in morphine-associated histamine release

Background Intravenous morphine use is associated with elevated histamine release leading to bronchoconstriction, edema and hemodynamic instability in some patients. This study evaluated the possibility that sulfite, which is present as a preservative in many morphine preparations, might contribute to histamine release in vitro. Results The human mast cell line, HMC-1, was exposed to various morphine concentrations, in the absence of sulfite, under cell culture conditions. Clinically attained concentrations of morphine (0.018μg/ml and 0.45μg/ml) did not cause increased histamine release from mast cells. There was a significant increase in histamine release when the morphine concentration was increased by 1184-fold (668μg/ml morphine). Histamine release from mast cells exposed to morphine and/or sulfite required the presence of prostaglandin H synthetase. Histamine release in experiments using sulfite-containing morphine solutions was not statistically different from that observed in morphine-only solutions. Conclusion Sulfite in sulfite-containing morphine solutions, at concentrations seen clinically, is not responsible for histamine release in in vitro experiments of the human mast cell line, HMC-1. This does not preclude the fact that sulfite may lead to elevation of histamine levels in vivo .

Background Morphine is among the most common analgesic agents used in the intensive care setting. It is usually administered parenterally as an intravenous infusion. Despite its efficacy, its use is associated with a number of hazards including respiratory depression [ 1 ], tolerance [ 2 ], physiological dependence [ 2 ] and abstinence upon discontinuation of treatment [ 2 ]. Less frequent, but perhaps more profound, is the bronchoconstriction, edema and hemodynamic instability seen in some patients following intravenous bolus doses of the drug [ 3 - 7 ]. These effects have been attributed to histamine release from mast cells by morphine [ 3 - 7 ]. A number of clinical studies have demonstrated an increase in plasma histamine concentration following intravenous morphine administration [ 3 - 7 ], but these studies generally fail to provide details concerning the formulation of the morphine employed. Most of the morphine used in both clinical practice and for clinical investigations contains sodium bisulfite as a preservative [ 8 ]. Until the mid 1980's sulfite preservatives were generally considered universally safe; however, their status was changed after the receipt by the FDA of more than 250 reports of serious and life-threatening reactions related to sulfite exposure through both diet and therapeutic agents [ 9 , 10 ]. In the body, sulfites are generally oxidized by the mitochondrial enzyme sulfite oxidase and non-toxic metabolites are excreted in the urine [ 11 ]. A small amount of the sulfite, either ingested or injected may also be metabolically activated by a number of other enzyme systems including xanthine oxidase [ 12 ], peroxidase [ 11 ] and prostaglandin H synthetase [ 13 ]. As an electron acceptor in these reactions or through electron transfer from transition metals such as copper and iron, sulfite may accept an electron from the resulting hydroxyl, superoxide or sulfate radicals [ 14 ] leading to the formation of sulfite radical. Sulfite radicals are chemically reactive and have been implicated in lipid [ 15 ], protein [ 16 ] and nucleic acid [ 17 ] oxidation as well as neuronal injury [ 18 ]. They may stimulate neutrophils to release oxygen free radicals and augment the free radical response to other neutrophil activators [ 19 ]. In addition, their generation has been shown to contribute to oxidative stress resulting in sulfite toxicity and impaired B-cell function. The potential generation of free radicals from sulfite preservatives may confound our understanding the association of morphine with histamine release in man. A number of studies have demonstrated that, when exposed to free radicals, mast cells may release histamine [ 20 - 26 ]. It is possible; therefore, that the histamine released following morphine infusion may be the result of the formation of sulfite radicals from the preservative rather than the morphine itself. This study evaluated the possibility that sulfite and its activation might contribute to histamine release by mast cells in vitro. Results Mast cell histamine release Total histamine content of mast cells was calculated by freezing and thawing suspensions for 3 cycles. Cell suspensions containing 500,000 cells/ml released 1.27μg/ml (0.21) histamine, corresponding to 2.53 pg (0.41) histamine per mast cell. Mast cells stimulated with 0.25μg/ml calcium ionophore released 63% (7.2) of total histamine. Effect of sulfite-free morphine concentration on histamine release The effect of histamine release from mast cells treated with both clinically attained concentrations of morphine and concentrations above those seen clinically was determined. To chemically defined reaction mixtures, morphine was added at varying concentrations (18 ng/ml, 450 ng/ml, 6.68μg/ml and 668μg/ml). Enzymes causing free radical activation were not present. The blank sample contained no morphine. Reaction mixtures were incubated in a water bath at 37°C for 60 minutes. Experiments were performed in triplicate. Histamine release from samples was determined following derivitization with o-phthaldialdehyde and mercaptoethanol using high-performance liquid chromatography as detailed below. Histamine release from reaction mixtures was expressed as a % of total histamine present in the cell pellet. Histamine release from reaction mixtures containing morphine at all concentrations was not statistically different (p > 0.1) from histamine release from blank samples (Table 1 ). Table 1 Histamine release from HMC-1 cells stimulated with varying concentrations of morphine with and without sulfite Histamine release expressed as a percentage of release of histamine in comparison to control (SD). As a control, the HMC-1 cells were allowed to freeze and thaw for 3 cycles to release the remaining histamine from cells. Each value represents the mean (SD) of triplicate determinations. Morphine concentration (μg/ml) Histamine release (% total)* Sodium bisulfite + - 0 2.9 (2.6) 0.018 2.5 (0.75) 3.2 (1.1) 0.450 1.7 (0.4) 2.6 (0.4) 6.68 1.8 (0.6) 2.2 (1.3) 668 2.1 (0.06) 2.8 (0.2) To verify the time dependence of histamine release, a morphine concentration of 668 μg/ml was tested. Release was detectable as early as 5 minutes after the addition of drug and appeared to plateau between 40 and 60 minutes (Figure 1 ). Figure 1 Concentration-effect of morphine in the presence of prostaglandin Hsynthetase on histamine release from the mast cell line HMC-1 (mean of 3 experiments). Effect of sulfite-containing morphine solutions on histamine release To determine whether the addition of sodium bisulfite causes increased histamine release from mast cells, sodium bisulfite at a concentration of 0.1% of morphine concentration (the % of sulfite present in morphine most formulations) was added to the reaction mixtures described previously. Blank samples contained neither morphine nor sulfite. Specimens were incubated, dried, re-dissolved, derivitized and analyzed as above. There was no statistical difference in histamine release at any concentration of morphine with sulfite compared with blank samples (Table 1 ). Reaction mixtures containing 668μg/ml morphine with 0.1% sodium bisulfite were incubated for 5, 10, 20, 40 and 60 minutes yielded results identical to those observed in the absence of sodium bisulfite (results not shown). Effect of prostaglandin H synthetase on histamine release from mast cell reaction mixtures Prostaglandin H synthestase may catalyze free radical formation [ 20 ]. The first experiment investigated its effect on mast cell histamine release in the absence of sulfite and morphine. This ensured that any increase in histamine release in subsequent experiments was not due to the effect of the enzyme only. Prostaglandin H synthetase was added to reaction mixtures at a concentration of 25 mU. In reaction mixtures containing no drug, the enzyme was added to mast cell samples containing neither morphine nor sulfite. Controls contained no enzyme. Reaction mixtures containing the enzyme alone (no sulfite or morphine) produced similar histamine release compared to blank samples (3.2% (0.7) of total and 2.9% (2.6) of total respectively). The presence of prostaglandin H synthetase had no effect. The effect of clinically attained concentrations of morphine in the presence of prostaglandin H synthetase on mast cell histamine release was investigated. In vivo studies show histamine release at these concentrations of morphine [ 3 - 7 ]. Morphine sulfate was added to the mast cell solution at clinically attained concentrations of 450 ng/ml (a typical peak in vivo concentration following an intravenous morphine bolus) and 18 ng/ml (a typical steady-state concentration during a 20 μg/kg/hour morphine infusion) [ 27 ]. Mast cell histamine release from higher concentrations of morphine (668μg/ml and 6.68μg/ml) was also investigated. Blank samples contained water instead of morphine. All samples contained 25 mU of prostaglandin H synthetase. Specimens were incubated, dried, re-dissolved, derivitized and analyzed as described below. Histamine release values are shown in Table 2 . There was no statistical difference between histamine release from morphine samples at both clinically-attained concentrations (18 ng/ml (p = 0.87) and 450 ng/ml (p = 0.08)) and histamine release from blank samples. Histamine release from HMC-1 cells incubated with morphine 668μg/ml and 6.68μg/ml were significantly increased compared with blank samples (p = 0.03 at both concentrations). Results are shown in table 2 . Maximum histamine release (16.1% of total (6.3)) occurred at the highest concentration of morphine (668μg/ml) (Figure 1 ). Table 2 Histamine release from HMC-1 cells stimulated with varying concentrations of morphine with and without sulfite in the presence of prostaglandin H synthetase. Histamine release expressed as a percentage of release of histamine in comparison to control (SD). As a control, the HMC-1 cells were allowed to freeze and thaw for 3 cycles to release the remaining histamine from cells. Each value represents the mean (SD) of triplicate determinations. Morphine concentration (μg/ml) Histamine release (% total)* Sodium bisulfite + - 0 2.9 (2.6) 0.018 3.3 (2.9) 4.5 (1.4) 0.450 6.5 (0.9) 6.7 (1.8) 6.68 8 (0.3) 6.2 (1.5) 668 17.6 (7.8) 16.1 (6.3) The effect of sodium bisulfite 0.1% in varying concentrations of morphine in the presence of prostaglandin H synthetase was investigated. This preservative is present in many morphine preparations and its effect on histamine release from mast cells is determined here. Morphine was added to the mast cell samples at concentrations of 668μg/ml, 6.68μg/ml, 450 ng/ml and 18 ng/ml. Sodium bisulfite was added to samples at a concentration of 0.1% of morphine concentration. Controls contained morphine only. Each sample also contained 25 mU of prostaglandin H synthetase. Specimens were incubated, dried, re-dissolved, derivitized and analyzed as described below. Reaction mixtures containing morphine 668μg/ml with 0.1% sodium bisulfite showed a statistically significant increase in histamine release compared with blank samples (p = 0.03). There was no statistical difference in histamine release between morphine only samples at all concentrations and samples containing morphine and 0.1% sodium bisulfite (Table 2 ) (morphine 668μg/ml (p = 0.8), morphine 6.68μg/ml (p = 0.13), morphine 450 ng/ml (p = 0.89) and morphine 18 ng/ml (p = 0.56). Sulfite did not have any additive effect on histamine release from mast cells in the presence of morphine and prostaglandin H synthetase. Studies looking at plasma histamine levels following morphine administration in humans have shown peak histamine levels within 5 minutes of administration [ 3 , 4 , 6 ]. This experiment investigated whether maximum histamine release occurred at a similar time in vitro in the presence of the enzyme prostaglandin H synthetase. HMC-1 cells were incubated at 37°C for 5, 10, 20, 30 and 60 minutes with morphine 668μg/ml, 0.1% sodium bisulfite and 25 mU prostaglandin H synthetase. The cells were centrifuged and the supernatant was examined for the presence of histamine and expressed as a % of total histamine. Histamine release was time dependent with a maximum effect after 1 hour of incubation (Figure 2 ). Figure 2 Time response effects of morphine 668 μg/ml in the presence of 0.1% Na bisulfite and 25 mU prostaglandin H synthetase on histamine release in HMC-1 cells (mean of 3 experiments). Interestingly, reaction mixtures containing a typical peak morphine concentration (450 ng/ml) showed a significant increase in histamine release in the presence of prostaglandin H synthetase compared with no enzyme. This was true for both sulfite-free (p = 0.003) and sulfite-containing (p = 0.009) morphine solutions. This suggests that even at clinically-attained morphine concentrations, it is not only possible to cause the metabolic activation of sulfite, but also that of morphine. The effect of sulfite alone (without morphine) on histamine release from mast cells was investigated. To 4 mast cell reaction mixtures, varying concentrations of sulfite (0.018 ng/ml, 0.45 ng/ml, 0.007μg/ml and 0.67μg/ml) were added. These concentrations of sulfite correspond to the concentration of sulfite present in morphine solutions of 18 ng/ml, 450 ng/ml, 6.6μg/ml and 668μg/ml. To each sample 25 mU prostaglandin H synthetase was added. The highest concentration of sulfite (0.67μg/ml) was incubated for 10, 20, 40 and 60 minutes to assess time dependence. The reaction mixtures were incubated, centrifuged and analyzed as described below. In the presence of prostaglandin H synthetase, sulfite resulted in histamine release from mast cells. There was a significant increase in histamine release (9.7% (0.65) of total) in the reaction mixture containing 0.67μg/ml sulfite (p = 0.01). There was no statistically significant difference in histamine release compared with blank samples at all other concentrations of sulfite (0.018 ng/ml sulfite (2.8% (0.3) of total, p = 0.91), 0.45 ng/ml sulfite (1.93% (0.35) of total, p = 0.53) and 0.007μg/ml sulfite (4.5% (0.7) of total, p = 0.36) (Table 3 ). Table 3 Histamine release from HMC-1 cells stimulated with varying concentrations of sulfite-only solutions in the presence of prostaglandin H synthetase. Histamine release expressed as a percentage of release of histamine in comparison to control (SD). As a control, the HMC-1 cells were allowed to freeze and thaw for 3 cycles to release the remaining histamine from cells. Each value represents the mean (SD) of triplicate determinations. Sulfite concentration (ng/ml) Histamine release (% total) 0.018 2.8 (0.3) 0.45 1.93 (0.35) 7 4.5 (0.7) 670 9.7 (0.65) The time-dependent experiment showed histamine release of 8% of total (3.3) at 10 minutes incubation, 7.7% of total (2.2) at 20 minutes, 10.5% of total (6.1) at 40 minutes and 9.7% of total (0.65) at 60 minutes. Discussion Our experiments showed similar histamine release from the mast cell line HMC-1 stimulated with morphine with or without 0.1% sodium bisulfite. Maximum histamine release was 16.1% of total in morphine only samples and 17.6% of total in morphine with 0.1% sodium bisulfite samples. This percentage is similar to other studies of histamine release in the human mast cell line HMC-1, where maximum release was 20–30% [ 28 - 30 ]. In our study, the concentrations of morphine and sulfite required to achieve maximum histamine release were significantly higher than concentrations seen clinically. Reaction mixtures containing sulfite only also caused significant histamine release at high concentrations. Blank samples, containing neither morphine nor sulfite, did not cause a significant increase in histamine release (Table 2 ). These results suggest that at high concentrations, both sulfite and morphine could be responsible for elevated histamine release from mast cells. In addition to the formation of the sulfite radical from sulfite, it is possible that carbon-centered or nitrogen-centered free radicals are being generated from the metabolic activation of morphine [ 20 ], thereby inducing mast cell histamine release. HMC-1 cells contain histamine and release their histamine content in response to various exogenous stimuli [ 28 - 30 ]. Our study showed no evidence of elevated histamine release from mast cells when stimulated with morphine and/or sulfite at concentrations seen clinically (both peak and steady-state). Although HMC-1 exhibits a phenotype similar to that of human mast cells [ 31 ], it is possible that immature cells (cell lines) are less sensitive than mature (primary) cells [ 28 ]. The model used is an artificial system and may not represent physiological conditions. In addition, maximum histamine release occurred after a one hour incubation. This is significantly different from the in vivo situation, where maximum release usually occurs within 5 minutes of morphine administration, and suggests that we were not able to simulate exactly the human environment where histamine release occurs. It is likely that although the sulfite radical is formed rapidly in vitro , it may take some time for its effects to become evident [ 32 ]. Metabolic activation of sodium bisulfite may occur through a variety of mechanisms. We investigated a number of enzyme systems and our final model used prostaglandin H synthetase. Other enzyme systems (horseradish peroxidase/ hydrogen peroxide and hypoxanthine/ xanthine oxidase) did release histamine in our model (results not shown), but they produced excess background interference in the chromatograms and made identification of peaks difficult. Activation of sulfite following morphine administration may not occur through this mechanism, however, and is another possible flaw in our aim to construct a model similar to the one that exists in vivo . Morphine has been shown to cause significant histamine release in vivo, but it has not been investigated whether sulfite, in the form of the sulfite radical, is the cause of this release. Our study finds that sulfite in sulfite-containing morphine solutions, at clinically attained concentrations, is not responsible for histamine release in in vitro experiments of the mast cell line HMC-1, but this does not preclude the fact that sulfite may lead to marked elevation in histamine levels in vivo . The release of a significant amount of histamine with either sulfite or morphine at concentrations higher than those seen clinically suggests that both substances may be responsible for histamine release from mast cells. Further clinical research studies need to be performed to examine this possibility. Conclusions Our study finds that the sulfite in sulfite-containing morphine solutions, at concentrations seen clinically is not responsible for histamine release in in vitro experiments of the mast cell line, HMC-1, but this does not preclude the fact that sulfite may lead to marked elevation in histamine levels in vivo . Our experiments suggest that at high concentrations, both morphine and sulfite are responsible for histamine release from mast cells. Further in vivo research needs to be performed to examine this possibility. Methods Preparation of HMC-1 cells Human leukemic mast cells, HMC-1 [ 33 ] were kindly provided by J. Butterfield, Rochester, Minnesota. This cell line shows many characteristics of immature mast cells. They have been shown to release histamine following stimulation [ 28 - 30 ] Cells were carried in 75 cm 2 vented tissue culture flasks (BD Falcon, Franklin Lakes, NJ) containing Iscoves modified Dulbecco's medium (Sigma, St.Louis, MO) with 10% iron-supplemented calf serum (Hyclone, Logan, Utah) and monothioglycerol 1.2 mM (Sigma, St.Louis, MO). Incubations were conducted in a humidified atmosphere at 5% CO 2 and 37°C. Cells were passed weekly and fed only when necessary (evidence of color change in media). To pass cells, the cell suspension was placed in a 50 ml polypropylene centrifuge tube (BD Falcon, Franklin Lakes, NJ) and centrifuged at 250 × g at 4°C for 10 minutes. The culture medium was discarded and the cells were re-suspended in fresh medium. Cell density was maintained at 500,000 cells/ml. Chemicals Reagent grade O-phthaldialdehyde (OPA), mercaptoethanol, dihydrogen sodium phosphate, disodium EDTA, sodium bisulfite, morphine sulfate, hydrogen peroxide, xanthine oxidase, boric acid and phosphate buffered saline (PBS) were purchased from Sigma (St.Louis, MO, USA). Methanol (HPLC grade), acetonitrile (HPLC grade) and sodium hydroxide were from Fisher Scientific (Hampton, NH). Phosphate buffered saline (PBS) pH 7.4, contained 120 mmol/L NaCl, 2.7 mmol/L KCl and 10 mmol/L phosphate. Horseradish peroxidase was purchased from Cooper Biomedical. Prostaglandin H synthetase was purchased from Calbiochem (Darmstadt, Germany). Determination of histamine release Mast cell suspensions, containing approximately 500,000 mast cells were, aliquoted into 1 ml samples. These were rinsed 4 times with 4 ml of PBS, pH 7.4. Cells were then re-suspended in 1 ml PBS. Reaction mixtures were supplemented with morphine, sulfite and prostaglandin H synthase at this stage according to experimental design, unless otherwise specified. Reaction mixtures were incubated for 60 minutes in a water bath at 37°C. Reactions were stopped by centrifugation at 250 × g for 4 minutes at 4°C and placed on ice. Then 200μl of the supernatant was collected and dried under nitrogen at 40°C. Histamine in the supernatant was measured using derivitization with OPA and mercaptoethanol (ME) as described [ 34 ]. Dried samples were re-dissolved in 100μl of derivitisation buffer (0.4 M boric acid adjusted to pH 9.5 with 1 M sodium hydroxide) and then derivitized with 20 μL of a freshly made 1:1 mixture of OPA (3.8 mM in methanol) and ME (2.5 ml/L in methanol) and analyzed within 30 minutes. The derivitized samples were used for chromatography. The response of HMC-1 cells to the stimulant calcium ionophore was investigated to assess the releasability of HMC-1 cells. 0.25μg/ml calcium ionophore was added to mast cell suspensions. Reaction mixtures were incubated and analyzed as above. Recovery of total histamine from cells To extract the remaining histamine from the original sample, the mast cell pellet in suspension was frozen and thawed 3 times. It was then centrifuged at 250 × g for 4 minutes and 200μl of the supernatant was dried under nitrogen as described previously. Samples were re-dissolved, derivitized and analyzed as above. Histamine release during morphine incubations was expressed as a percentage of total histamine release. Chromatography system Histamine was measured by high-performance liquid chromatography using a Varian model 5500 chromatograph. The mobile phase was 0.1 M dihydrogen sodium phosphate and 1 mM disodium EDTA with 16% methanol and 14% acetonitrile adjusted to pH 6.4. The flow rate was 0.8 ml/minute. Separations were performed using a 15 cm × 4.6 mm, Ace 5 C18 reversed-phase cartridge column (Advanced Chromatography technologies, UK). A Zorbax C8 guard column with a 5 micron, 4.6 × 12.5 mm analytical guard-column cartridge (Agilent technologies, Palo Alto, CA) was used. Fluorescence detection was used with the fluorimeter (Varian 9070) set at an excitation of 348 nm and an emission of 444 nm (determined by running individual excitation and emission spectra on the fluorometer). Chromatographic conditions involved the use of a mobile phase gradient to optimize peak separation. A linear gradient starting at 90% mobile phase, 10% acetonitrile and ending at 80% mobile phase, 20% acetonitrile took place over 20 minutes. The column was washed by increasing the acetonitrile to 30% by 22 minutes and by 23 minutes the proportions were returned to the original values. The length of each run was 30 minutes. Data analysis Values are expressed as a mean +/- SD of 3 experiments. One-way analysis of variance was used to determine the significance of the difference between groups. Results were considered significantly different when p < 0.05. Authors' contributions EG participated in experiments and drafted the manuscript. JB conceived of the study and participated in its design. CM suggested the methodology of experiments. All authors read and approved the final manuscript.

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521194

Health-related quality of life as a predictor of pediatric healthcare costs: A two-year prospective cohort analysis

Background The objective of this study was to test the primary hypothesis that parent proxy-report of pediatric health-related quality of life (HRQL) would prospectively predict pediatric healthcare costs over a two-year period. The exploratory hypothesis tested anticipated that a relatively small group of children would account for a disproportionately large percent of healthcare costs. Methods 317 children (157 girls) ages 2 to 18 years, members of a managed care health plan with prospective payment participated in a two-year prospective longitudinal study. At Time 1, parents reported child HRQL using the Pediatric Quality of Life Inventory™ (PedsQL™ 4.0) Generic Core Scales, and chronic health condition status. Costs, based on health plan utilization claims and encounters, were derived for 6, 12, and 24 months. Results In multiple linear regression equations, Time 1 parent proxy-reported HRQL prospectively accounted for significant variance in healthcare costs at 6, 12, and 24 months. Adjusted regression models that included both HRQL scores and chronic health condition status accounted for 10.1%, 14.4%, and 21.2% of the variance in healthcare costs at 6, 12, and 24 months. Parent proxy-reported HRQL and chronic health condition status together defined a 'high risk' group, constituting 8.7% of the sample and accounting for 37.4%, 59.2%, and 62% of healthcare costs at 6, 12, and 24 months. The high risk group's per member per month healthcare costs were, on average, 12 times that of other enrollees' at 24 months. Conclusions While these findings should be further tested in a larger sample, our data suggest that parent proxy-reported HRQL can be used to prospectively predict healthcare costs. When combined with chronic health condition status, parent proxy-reported HRQL can identify an at risk group of children as candidates for proactive care coordination.

Background Predicting healthcare costs for pediatric populations has been challenging [ 1 ]. Although population-based risk prediction and case-mix adjustment can be used to inform policy, set rates, and compare outcomes across providers [ 2 ], a more immediate concern for healthcare providers is to clinically manage their enrolled population. In a prospective payment system with predetermined funding limits, providers must be able to proactively case-manage those enrollees at greatest risk of poor health while remaining within designated budget constraints. If healthcare providers knew in advance – for example at the time of health plan enrollment – which children were at the greatest risk for future health problems, then healthcare resources could be proactively targeted to those children in order to minimize or prevent morbidity and associated healthcare costs. Researchers working with adult populations have linked health status with several important outcomes. In general populations, self-reported health status has been shown to be a predictor of future health services charges [ 3 ], the use of physician services and mortality in working-age adults [ 4 ], and of frailty in the elderly [ 5 ]. For chronically ill adults, self-rated health status is an independent predictor of physiologic health in diabetes and hypertension[ 6 ], and self-reported quality of life is an independent predictor of survival in cancer patients [ 7 ]. For the hospitalized elderly, functional status [ 8 - 10 ] and depressive symptoms [ 11 ] have been shown to be predictive of resource utilization and mortality. Several researchers have demonstrated that both diagnostic information and self-rated health status are associated with costs for general adult populations [ 12 , 13 ]. In pediatric populations, diagnosis-based classification systems have achieved some degree of association with healthcare costs [ 14 , 15 ]. However, there remain limitations with current pediatric healthcare cost prediction methods, including the underestimation of healthcare costs for chronically ill children [ 14 ]. The ideal pediatric cost prediction model for clinical management would predict healthcare costs proactively in those patients at greatest risk. Increasingly, health-related quality of life (HRQL) has become recognized as an important health outcome, some contend the most important outcome in child health services research [ 16 - 18 ]. Researchers have made great strides in conceptualizing and measuring HRQL for children [ 19 - 27 ]. HRQL has been shown to be responsive to treatment in children with rheumatic disease [ 28 ], and to be related to treatment status in children with cancer [ 20 , 29 ], to chronic health condition status in a general sample [ 19 ], to severity of illness within children with cardiac diagnoses [ 30 ], and to parent reports of primary care quality [ 31 ] and barriers to care [ 32 ]. Measuring HRQL in large populations has several distinct benefits. It can aid in identifying subgroups of children who are at-risk for health problems [ 33 ], in determining the burden of a particular disease or disability [ 34 ], and, at least in general populations, in informing efforts aimed at prevention and intervention [ 13 ]. While self-report is considered the standard for measuring perceived HRQL as an outcome, it is typically parents' perceptions of their children's HRQL that influence healthcare utilization [ 35 , 36 ]. Consequently, the objective of this study was to test the primary hypothesis that parent proxy-report of pediatric HRQL would prospectively predict pediatric healthcare costs over a two-year period. The exploratory hypothesis tested anticipated that a relatively small group of children would account for a disproportionately large percent of healthcare costs. Method Participants and Settings The study took place in San Diego, California between January 1998 and December 2000. We recruited members of a 50,000-member federally supported (Medicaid) managed care health plan. Additional inclusion criteria were that children be between 2 and 18 years of age and that the parent be able to speak either English or Spanish. We exclude children under 2 years of age because the PedsQL™ does not assess parent proxy-report HRQOL below age 2 years. In order to maximize the heterogeneity of the sample, subjects were recruited from three types of healthcare settings: children presenting at pediatricians' offices for scheduled well-child checks (n = 18, 5.7%), children at one of two hospital specialty clinics – orthopedics (n = 6, 1.9%) and cardiology (n = 7, 2.1%) – or children who had been seen at the hospital or its outpatient clinics at least three months previously (n = 286, 90.3%). The data reported here were collected as part of the initial field test to assess the reliability and validity of the PedsQL™ 4.0 Generic Core Scales [ 19 ]. Only pediatric patients reported being members of the federally supported managed care health plan are included in the current data analysis. Measures The PedsQL™ 4.0 (Pediatric Quality of Life Inventory™ 4.0) Generic Core Scales The PedsQL™ 4.0 Generic Core Scales [ 19 ] were designed to measure the core physical, mental and social health dimensions as delineated by the World Health Organization [ 37 ], and to additionally include role (school) functioning. The 23-item PedsQL™ 4.0 encompasses both physical functioning (8 items) and psychosocial (emotional, social, role) functioning (15 items) and is comprised of parallel child self-report and parent proxy-report formats. The parent proxy-report form is designed to assess the parent's perceptions of their child's HRQL. Parent proxy-report includes ages 2–4 (toddler), 5–7 (young child), 8–12 (child), and 13–18 (adolescent). Higher PedsQL™ 4.0 scores indicate better HRQL. To create Scale Scores, the mean is computed as the sum of the items divided by the number of items answered (this accounts for missing data). If more than 50% of the items in the scale are missing, the Scale Score is not computed. Imputing the mean of the completed items in a scale when 50% or more are completed is generally the most unbiased and precise method [ 38 ]. Because parent proxy-report of HRQL has been shown to be related to utilization [ 35 , 36 ], we used only the parent proxy-report Physical Functioning and Psychosocial Functioning Summary Scales of the PedsQL™ 4.0 in the current investigation. Chronic health condition status Parents were asked to report on the presence of a chronic health condition for their child. They read the following statement: "A chronic health condition is: (1) a physical or mental health condition (2) that has lasted or is expected to last at least 6 months and (3) interferes with your child's activities." They then responded with yes or no to the question "In the past 6 months, has your child had a chronic health condition?" If yes, the parents were asked to identify the name of the chronic health condition. Parents who answered yes or who gave the name of a chronic health condition were coded as having a child with a chronic health condition. This method has been used in previous work [ 19 , 31 ], and the PedsQL™ 4.0 scores for the two groups defined using this method (with and without chronic health condition) are very similar to those observed in other studies [ 33 ]. Healthcare Costs Healthcare costs were calculated as the dollar amount paid by the health plan per patient. We first determined patients' eligibility from the health plan's eligibility data files for three consecutive cumulative periods: 0–6 months, 0–12 months, and 0–24 months after the date they completed the PedsQL™ 4.0. A pediatric patient was considered eligible for health plan benefits for those periods if they were eligible for at least 5 months out of the 6-month period. We then electronically captured healthcare costs (the dollar amount paid by the health plan) for each pediatric patient for those periods in which they were eligible. We did this by matching each eligible pediatric patient with the health plan's existing databse of claims and encounter data. These data include the dollar amount spent by the health plan. Healthcare costs included hospital and emergency room costs, professional fees, durable medical equipment, home health, specialty clinic, and primary care costs. We did not have access to pharmacy or mental health costs. In California, the site of the study, treatment for 22 specific diagnoses is "carved out," or paid through a separate program (called California Children's Services; CCS) regardless of a child's health plan membership. Thus, for health plans in California, treatment of CCS-covered diagnoses might not be measured in calculating utilization. However, because California's carve out may differ from other states' methods of financing treatment for these diagnoses, and to more completely describe healthcare costs, we included the costs for procedures covered by CCS in our healthcare costs calculations. To derive these costs, we linked the procedure codes on the health plan's CCS referral with the federally supported health plan's fee schedule. These data thus represent the dollar amount the health plan would have spent had the services not been carved out. Procedure A convenience sample – subects were recruited nonsystematically when research assistants were available – was recruited at pediatrician offices and specialty clinics. These pediatric patients were identified through examination of the clinic appointment schedules. At these sites, parents of children identified as possible study participants were informed of the study by one of the research assistants after checking in for their appointment, but before being seen by their healthcare provider. Written informed consent included permission for the researchers to examine the medical record to assess utilization. After written informed consent was obtained, the parent completed the proxy-report version of the PedsQL™ 4.0. The research assistant was available at all times to answer any questions. A random sample was recruited from children and adolescents ages 2–18 years who had been seen as inpatients or outpatients at Children's Hospital and Health Center between April 1 and June 30, 1998, and who were members of the health plan. This sample excluded children with a discharge status of expired, children whose payer was from the victim/witness fund, and children whose parents had requested their phone number and address to be kept private. Research assistants called parents of children on this list and obtained verbal informed consent. The research assistant verbally administered the PedsQL™ 4.0 to parents. This research protocol was approved by the institutional review board at Children's Hospital and Health Center, San Diego (#98-020). Statistical analysis We pooled the data from the two samples. Previous reasearch on the PedsQL™ has documented the lack of mode of administration effects [ 19 , 20 ]. In order to test the primary hypothesis that HRQL would prospectively predict healthcare costs, multiple linear regression analyses were conducted. We examined the association between age, gender, chronic health condition status (variables typically used by health plans to predict risk), and PedsQL™ 4.0 scores with healthcare costs at each of the three cumulative follow-up periods. We did not use socioeconomic status, as eligibility criteria for membership in the health plan requires families to have incomes below a certain level, and this restricts the range of this variable. Four models were constructed for each follow-up period. Model 1 included age and gender only, Model 2 included age, gender, and chronic health condition status, Model 3 included age, gender, and PedsQL™ 4.0 scores, and Model 4 included age, gender, chronic health condition status, and PedsQL™ 4.0 scores. We report the adjusted R 2 , a measure of the percent of variance in the dependent variable accounted for by the predictor variables while adjusting for the complexity of the model, and the standardized regression coefficient, or beta, for each predictor. PedsQL™ 4.0 scores were skewed toward the high end of the scale and were transformed by taking the square root of the reverse of the score (sqrt(100-score)) in order to create a more normal distribution. The distribution of cost data was skewed to the lower end, with many children having little cost and a relatively smaller number of children having high costs. These data were normalized by taking the log of the costs. In order to explore whether HRQL and chronic health condition status together would define a relatively small subset of enrollees who accounted for a disproportionately large percent of healthcare costs, we divided the sample into quintiles based on the PedsQL™ 4.0 Physical Functioning Scale score and into two groups based on chronic health condition status. Those children who fell in the lowest PedsQL™ 4.0 quintile and who reported the presence of a chronic health condition were assigned to the high-risk group. We describe the percent of costs, per member costs, and per member per month costs per child accounted for by this high risk group. Results Descriptive Statistics Data was collected from the parents of 317 children (157 girls, 160 boys) ages 2 to 18 years. The average age of the children was 8.3 years (SD = 4.14) with a range of 2.03 to 17.13 years. The sample was heterogeneous with respect to race/ethnicity, with 76 (25.4%) White non-Hispanic, 155 (51.8%) Hispanic, 39 (13.0%) Black non-Hispanic, 6 (2.0%) Asian/Pacific Islander, 3 (1.0%) American Indian or Alaskan Native, 20 (6.7%) Other, and 19 (6.0%) missing. With respect to mother's education, 36.4% had less than a high school education, 46.6% had a high school diploma or some college, and 7.0% were college graduates or beyond (18.8% missing). The measures were administered in two languages – English (n = 233, 73.6%) and Spanish (n = 84, 26.4%). The sample represented both chronically ill (n = 102, 32.1%) and healthy children (n = 215, 67.9%), based on parent report of the presence of a chronic health condition. Table 1 presents the chronic health conditions reported by parents for the high risk group and the non-high risk group. Table 1 Parent-reported chronic health conditions, by high risk group status. High risk group? Total no yes name of condition None 223 0 223 ADHD 7 1 8 allergies 1 0 1 arthritis 2 0 2 asthma 25 8 33 autism 2 1 3 back and leg pain 0 1 1 Battan disease 0 1 1 bi-polar 1 0 1 breathing problems 1 0 1 bronchitis 2 0 2 cancer 1 0 1 cerebral palsy 2 2 4 chronic ear infections 2 0 2 cough 2 0 2 CSF leak 0 1 1 depression 1 0 1 developmental delay 1 0 1 dislocated shoulder 0 1 1 doesn't produce salt 1 0 1 Down Syndrome 1 0 1 ear problems 0 1 1 epilepsy 1 0 1 gallbladder problems 1 0 1 gastrointestinal problem 1 0 1 hearing 1 0 1 heart murmur 2 0 2 heart problem 1 1 2 kidney reflux 1 0 1 leukemia 1 0 1 May Hegglin syndorme 1 0 1 migraine headaches 0 1 1 muscle condition 0 1 1 muscular dystrophy 0 1 1 osteomyelitis 1 0 1 pierre robyn syndrome 1 0 1 reactive airway disease 1 0 1 Rett syndrome 1 0 1 scleroderma 0 1 1 scoliosis 0 1 1 seizures 3 1 4 speech 1 0 1 spina bifida 0 2 2 stomach aches 1 0 1 stomach problems 1 0 1 unknown genetic syndrome 0 1 1 urinary tract infections 1 0 1 There were no differences found in PedsQL™ scores between the group sampled at well-child checks or specialty clinics and that sampled by phone. All 317 children were enrolled in the health plan after 6 months, with 314 (99.0%) enrolled after 12 months, and 244 (76.9%) after 24 months. There were no differences between those enrolled versus not enrolled at 24 months in percent with a chronic health condition, race/ethnicity, mother's education, or PedsQL™ scores. The cost per member per month (pmpm) for this sample, which represents the total cost divided by the number of members divided by the number of months enrolled, was $149 at 6 months, $137 at 12 months, and $115 at 24 months. The sample included 4,954 claims (there are multiple claims in a single clinical encounter) over the 24 months. The largest category of visits was for upper respiratory infections (URIs) and related infections (10.96%). Asthma, other infections, otitis media, and pain each account for 5 to 6% of visits, with acute orthopedic conditions accounting for 2.6% of visits. These most common diagnoses account for more than a third (38.7%) of the visits, the rest is comprised of a large number of relatively low-frequency diagnoses. This distribution of diagnoses is similar to the epidemiology of childhood illness, in that much of pediatric morbidity is accounted for by a large number of relatively low frequency diagnoses [ 39 , 40 ]. Table 2 displays the descriptive statistics for the PedsQL™ 4.0 parent proxy-report at Time 1. Consistent with previous PedsQL™ 4.0 findings, [ 19 ] chronically ill children had lower HRQL scores than healthy children (Table 2 ). Table 2 Descriptive Statistics for PedsQL™ 4.0 scores N Mean SD Minimum Maximum t ^ df p Total Sample Total Scale Score 316 84.38 13.67 25.00 100.00 Physical Functioning 316 85.39 19.87 0.00 100.00 Psychosocial Functioning 317 83.78 13.73 32.14 100.00 Children with Chronic Health Condition Total Scale Score 101 79.26 16.66 25.00 100.00 -4.73 313 0.001 Physical Functioning 100 79.69 25.00 0.00 100.00 -3.59 313 0.001 Psychosocial Functioning 102 79.27 16.59 32.14 100.00 -4.12 314 0.001 Children without Chronic Health Condition Total Scale Score 214 86.82 11.29 44.44 100.00 Physical Functioning 215 88.17 16.30 10.00 100.00 Psychosocial Functioning 214 85.91 11.61 48.33 100.00 ^comparing chronically ill to healthy children Multiple regression analysis Table 3 displays the results of the multiple regression analyses predicting healthcare costs for 6, 12, and 24 month follow-up. As can be seen, Model 1, with age and gender as the only predictors variables, did not account for significant variance in costs. Model 2 shows that age and gender, with chronic health condition status accounted for an increasing percentage of costs as the follow-up time lengthened. This pattern holds true as well for Model 3, which included age, gender, and the PedsQL™ 4.0 scores. Model 4, comprised of age, gender, chronic health condition status, and PedsQL™ 4.0 scores, accounted for the most variance, explaining 10.1% 14.4% and 21.2% of the variance in healthcare costs at 6, 12, and 24 month follow-up intervals. Inspection of the standardized regression coefficients for each predictor in Model 4 shows that, of the four predictors used, chronic health condition status and the PedsQL™ 4.0 Physical Functioning Scale scores consistently accounted for the greatest amount of variance. Table 3 Adjusted R-square (in bold) and standardized regression coefficients (betas) for models predicting costs at 6, 12, and 24 months Follow up 6 Months (N = 318) 12 Months (N = 315) 24 Months (N = 245) Model 1 Adjusted R-square 0.010 0.001 0.004 Beta Age -0.067 -0.037 -0.030 Gender .11 0.063 0.108 Model 2 Adjusted R-square 0.049** 0.066*** 0.130*** Beta Age -0.063 -0.031 0.008 Gender 0.118* 0.076 0.115 Chronic Health Condition 0.180** 0.265*** 0.360*** Model 3 Adjusted R-square 0.089*** 0.103*** 0.122*** Beta Age -0.103 -0.091 -0.079 Gender 0.080 0.030 0.076 PedsQL Physical Functioning 0.291*** 0.353*** 0.379*** PedsQL Psychosocial Functioning 0.004 0.057 0.081 Model 4 Adjusted R-square 0.101*** 0.144*** 0.212*** Beta Age 0.098 -0.083 -0.043 Gender 0.086 0.040 0.080 Chronic Health Condition 0.126 + 0.214*** 0.312*** PedsQL Physical Functioning 0.275*** 0.326*** 0.340*** PedsQL Psychosocial Functioning 0.025 0.093 0.123 + + = p < 0.05; * = p < 0.01; *** = p < 0.001; *** = p < 0.0001; R 2 = percent variance accounted for. Defining the high risk group We used the two variables accounting for most of the variance in the regression analysis – the PedsQL™ 4.0 Physical Functioning scores and chronic health condition status – to describe the percentage of costs accounted for by different groups of children. In order to create a single denominator for the percentages, we used the 241 children continuously enrolled in the health plan with complete data for this set of analyses. To create quintiles, we determined the values that divided the sample into five equal-sized groups based on PedsQL™ 4.0 Physical Functioning Scale scores. Enrollees with a score of less than 75 on the PedsQL™ 4.0's 0–100 scale were in the first quintile (N = 51; 21.0%). The second quintile (N = 45; 18.5%) was bounded by the scores 75.0 to 90.624, the third quintile (N = 48; 19.6%) by the scores 90.625 to 96.874, the fourth quintile by the scores 96.875 to 100 (N = 18; 7.3%), and the fifth quintile consisted of enrollees scoring 100 (N = 81; 33.4%). Because the distribution of these PedsQL™ 4.0 scores was skewed, we combined the fourth and fifth quintiles (N = 99; 40.7%; 2 missing). Table 4 shows the percentage of total costs accounted for by children across PedsQL™ 4.0 Physical Functioning Scale quintiles and chronic health condition status, for the three cumulative follow up periods. As can be seen, children in the high risk group (the subset of chronically ill children in the lowest quintile), account for a disproportionately large share of healthcare costs. This group, comprising just 8.7% of the sample, accounted for 37.42% of the healthcare costs over six months, 59.16 % of costs over 12 months, and 61.74% of costs over 24 months. Table 4 Percent of cost at each follow up period, by PedsQL quintile and chronic health condition status (n = 241) PedsQL Physical Functioning Quintile Lowest quintile (N = 51) 2nd quintile (N = 45) 3rd quintile (N = 48) 4th and 5th quintiles (N = 99) Chronic Health Condition Chronic Health Condition Chronic Health Condition Chronic Health Condition Yes (N = 21) No (N = 30) Yes (N = 18) No (N = 27) Yes (N = 12) No (N = 36) Yes (n = 26) No ( = 73) % of cost, 6 months 37.43 9.35 26.76 9.30 0.33 6.95 7.59 2.30 % of cost, 12 months 59.16 4.70 20.56 4.54 0.30 3.63 5.25 1.85 % of cost, 24 months 61.74 3.38 22.06 2.86 0.41 2.64 4.87 2.03 Bold = High-risk group Table 5 shows the total costs, the per member costs, and the per member per month (pmpm) costs for the high risk group and the not high risk group over the three follow-up periods. As can be seen, the high risk group was an extremely costly subset of enrollees for each of the cumulative 6 month periods, as measured by total, per member, or pmpm costs. Pmpm costs were quite disparate between the high risk group and other enrollees. For the high risk group at 6 months, pmpm was $432 (vs. $66 for the other patients), at 12 months pmpm was $809 (vs. $61), and at 24 months, pmpm was $722 (vs. $60). Table 5 Total costs, per member costs, and per member per month costs for high-risk* (N = 21) and not high-risk (N = 231) enrollees. Total Per member Per member per month Time Period High-risk Not high-risk High-risk Not high-risk High-risk Not high-risk 6 months $54,493 $91,484 $2,595 $396 $432 $66 12 months $203,875 $168,022 $9,708 $727 $809 $61 24 months $363,822 $330,846 $17,325 $1,432 $722 $60 *High risk is defined as parent reported chronic health condition and scoring in lowest quintile on PedsQL™ 4.0 Discussion This study tested the primary hypothesis that HRQL could prospectively predict healthcare cost in pediatric patients in a managed care environment. We measured age, chronic health condition status, and PedsQL™ 4.0 scores at Time 1, and prospectively measured utilization, via costs based on claims and encounter data, for three cumulative periods. These data demonstrate that parent-reported HRQL, as measured by the PedsQL™ 4.0, and chronic health condition status each accounted for significant variance in healthcare costs over 6, 12, and 24 months. The data further show how these two predictor variables, chronic health condition status, and PedsQL™ 4.0 Physical Functioning scores, define a relatively small group of enrollees that accounted for a large percentage of total healthcare costs. This high risk group displays disproportionately high costs as early as 6 months, and their pmpm costs peak at one year. This suggests the importance of managing high risk enrollees as soon as they are identified, perhaps as early as their initial enrollment. It also implies the potential for significant return on investment for better case management, even in the first six months of enrollment. The high risk group's costs remain disproportionately high throughout the 24 months of the study. This fact suggests that the method used here for identifying the high risk group succeeded in identifying children with high ongoing care needs and costs, as opposed to children with one-time health care needs. An anomalous finding was that children in the third quintile on PedsQL™ scores who had chronic health conditions were, for an unexplained reason, much less costly than their peers. It is worth comparing the mean PedsQL™ 4.0 scores for the high risk group to other published data. The high risk group had scores of 44.5 for the Physical Functioning Scale, 70.7 for the Psychosocial Summary Scale, and 61 for the Total Scale. This is placed in clinical perspective by other data showing that scores for children with cancer, in active treatment, are 65, 68, and 67 for the Physical, Psychosocial and Total scales, respectively. [ 31 ]. A hypothetical example is presented to illustrate the potential impact of these findings. In a typical health plan, the rate of chronic health conditions will most likely be between 5% [ 41 ] and 18% [ 42 ], rather than the 31.4% rate we found by selecting our sample, in part, from hospital specialty clinics. We will further conservatively assume that one-fifth (20%) of children with chronic health conditions would fall in the lowest quintile on the PedsQL™ 4.0. If this were so, then between 1% (5% chronic health condition × 20% in the lowest quintile) and 3.6% (18% chronic health condition × 20% in the lowest quintile) of enrollees in a health plan would fall into the high risk group. Thus, in a hypothetical medium to large health plan with 50,000 pediatric enrollees, the high risk group would be comprised of anywhere from 500 (1% of 50,000) to 1800 (3.6% of 50,000) children. Using the costs figures from this sample ($722 pmpm), this hypothetical high risk group represents between $8.6 and $31.2 million in costs over the course of 24 months. This example relies on speculation and is intended as a hypothetical case, for illustrative purposes only. Taken together, these findings represent an alternative method toward the prospective prediction of healthcare costs in pediatric federally supported managed care populations. While a percentage of these identified costs are inevitable, due to the costs of appropriate care for these chronically ill, poorly functioning children, the possibility exist that a proportion of these healthcare costs are avoidable. Evidence-based disease management has been shown to reduce healthcare costs and increase HRQL in certain chronic conditions such as asthma [ 43 , 44 ]. By identifying at-risk children with low PedsQL™ 4.0 scores, targeted interventions may avert certain future healthcare costs by ameliorating impaired HRQL when first identified. Certain limitations exist in this study. The first has to do with data not accounted for in this study. We did not have access to pharmacy and mental health costs, nor did we have access to out-of-plan expenditures. For mental health costs, however, recent data has shown that children referred for psychiatric services demonstrate child self-report and parent proxy-report PedsQL™ 4.0 Total Scale Scores comparable to children with chronic physical health conditions [ 45 ]. Those data suggest that this methodology may be useful in predicting mental health costs as well. We did not include children under the age of two. Neonatal intensive care, for example, is a large percent of the costs for Medicaid managed care plans [ 46 ]. The portion of health plan costs devoted to caring for children under two is not explored here. However, many of these costs cannot be avoided, and preventive efforts for these costs are most appropriately targeted at the prenatal and perinatal periods. Finally, we did not compare the performance of these variables to that of existing administrative risk adjustment methods currently available. The second limitation has to do with sampling issues and with generalizing these data beyond this study. Our data was not collected at enrollment, nor did we sample from the entire pool of enrollees. Further research is necessary to determine whether these findings hold true for children assessed at health plan enrollment, and to determine the extent to which the results may be influenced by the convenience sample used here. The sample was too small to use cross-validation techniques. Prediction models tend to overfit the development sample, and the predictive validity of these variables should be tested in other, larger samples. Although generalization of these findings to broader populations should be made with caution, the sample here is very diverse with respect to race/ethnicity, and thus likely to be similar to other federally support health plans. We also combined data from two different samples – specialty clinic patients, and health plan members who had been seen in the hospital or outpatient clinics at least three months after the clinical encounter. These two groups could have had unmeasured systematic differences, which could have biased the results. The third has to do with using a survey to gather these data. The costs of fielding a survey can be quite high, and, if tied to payment, survey responses are subject to "gaming". However, we submit that the potential gains from optimal management of an enrolled population will almost certainly be greater than the costs of survey administration. Moreover, while gaming might occur if health plans were to be compensated based on the HRQL of their enrolled population, the methods used here are suggested as strategies for clinical management, not for rate setting, thus reducing the incentives for gaming. We did not track refusal rates and so do not know what percent of potential participants consented to be in the study. Finally, using a survey means that parents reported on their children's chronic health condition information. Objective measures of chronic health condition would strengthen the validation process. However, in previous PedsQL™ 4.0 clinical research in pediatric patients with cancer, cardiac and rheumatic chronic health conditions, objective medical diagnosis of these chronic diseases demonstrated similar differences between healthy children and children with chronic health conditions as shown in the present findings [ 28 - 30 ]. Further research is necessary. First, a much larger, and randomly selected sample is necessary to confirm these results. Second, split-half validation should be performed so that the coefficients from one group are used to predict the costs in a different group. This could be done with split halves of one large group, or with two similar groups enrolled at different points in time. Given that our regression equation explains 21% of costs, further studies could be done to determine whether other variables might account for additional variance in costs. Further studies could also allow comparison and validation with the results here. Conclusion This is the first study we are aware of to use parent reports of pediatric HRQL and chronic health condition status to prospectively predict healthcare costs in a pediatric sample. These data have implications for healthcare decision makers such as pediatricians, health plan administrators, and policymakers. In a prospective payment system, providers are incentivized to actively manage high-risk patients and to provide care at the appropriate level. The idea behind such a system is that prevention and appropriate care accrues benefits to patients in the form of better health and to providers in the form of lower costs. If, as these data suggest, parent reports of HRQL can be used to predict healthcare costs, one could identify at-risk children proactively and intervene to avoid both illness and costs. In this way, these data can serve simultaneously to improve the health of children and the system that serves them. List of Abbreviations HRQL Health-related Quality of Life PedsQL™ 4.0 Pediatric Quality of Life Inventory™, Version 4.0 SD Standard Deviation CCS California Children's Services URI Upper respiratory infection PMPM per member per month Authors' Contributions MS, PSK, and JWV conceived of the research. MS and JWV supervised the data collection. MS and DS performed the data analysis. MS drafted the manuscript. JWV, PSK, and DS provided substantive input into the manuscript. All authors read and approved the final manuscript.

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549599

Towards Better Evaluation of Pneumococcal Vaccines

Pneumonia remains the leading cause of death worldwide in children. Several vaccines against pneumococcal pneumonia are at various stages of development, but the testing of their efficacy is hampered by the lack of noninvasive tests that are sensitive and specific for the disease. Diagnosis is usually based on chest radiographs, which are not very specific for pneumococcal disease. In their quest for a more specific diagnostic test, Shabir Madhi and colleagues—who are conducting clinical trials on pneumococcal vaccines in children—examined whether serum concentrations of procalcitonin and C-reactive protein could improve the specificity of chest radiographs to diagnose pneumococcal pneumonia and thus be useful in the future evaluation of pneumococcal vaccines. Elevated levels of both proteins are associated with bacterial disease. They might therefore help to differentiate bacterial from nonbacterial causes of pneumonia, and thus allow to “enrich” the analyzed disease cases for those of pneumococcal origin, against which the vaccine is potentially active. This study represents a first step, in which the researchers tested whether adding information about procalcitonin and C-reactive protein levels to data from a completed vaccine trial would affect the outcome regarding vaccine efficacy. When reanalyzing previous trial data under these conditions, the vaccine appeared more efficacious compared with placebo when either elevated procalcitonin or elevated C-reactive protein levels were taken into account. The efficacy estimate was greatest when cases of pneumonia that had elevated levels of both procalcitonin and C-reactive protein were compared against placebo. These data suggest that elevated levels of C-reactive protein and procalcitonin, in conjunction with chest radiography, could improve the specificity of a diagnosis of pneumococcal pneumonia over that of chest radiography alone. This combined diagnostic test could be useful for further evaluation of pneumococcal vaccines. The hope is that among patients identified as having pneumonia by the combined test, a higher proportion would have pneumonia of pneumococcal origin. As a consequence, there would be less “background noise” caused by other forms of pneumonia, and this should make it easier to assess the efficacy of vaccine candidates. However, as the researchers point out, this analysis was not a primary objective of the present trial. This analysis can therefore serve only as a hypothesis-generating study, and as such the hypothesis must be tested in other study settings. The study was sponsored by Wyeth, manufacturers of the pneumococcal vaccine used.

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546331

Organized Unidirectional Waves of ATP Hydrolysis within a RecA Filament

The RecA protein forms nucleoprotein filaments on DNA, and individual monomers within the filaments hydrolyze ATP. Assembly and disassembly of filaments are both unidirectional, occurring on opposite filament ends, with disassembly requiring ATP hydrolysis. When filaments form on duplex DNA, RecA protein exhibits a functional state comparable to the state observed during active DNA strand exchange. RecA filament state was monitored with a coupled spectrophotometric assay for ATP hydrolysis, with changes fit to a mathematical model for filament disassembly. At 37 °C, monomers within the RecA-double-stranded DNA (dsDNA) filaments hydrolyze ATP with an observed k cat of 20.8 ± 1.5 min −1 . Under the same conditions, the rate of end-dependent filament disassembly ( k off ) is 123 ± 16 monomers per minute per filament end. This rate of disassembly requires a tight coupling of the ATP hydrolytic cycles of adjacent RecA monomers. The relationship of k cat to k off infers a filament state in which waves of ATP hydrolysis move unidirectionally through RecA filaments on dsDNA, with successive waves occurring at intervals of approximately six monomers. The waves move nearly synchronously, each one transiting from one monomer to the next every 0.5 s. The results reflect an organization of the ATPase activity that is unique in filamentous systems, and could be linked to a RecA motor function.

Introduction There are three prominent protein families that both form filaments and hydrolyze nucleoside triphosphates (NTPs). These include the tubulins [ 1 , 2 , 3 ], the actins [ 4 , 5 , 6 ], and RecA protein and its homologs [ 7 , 8 , 9 , 10 , 11 ]. Of these, the RecA family is unique in its formation of filaments on a DNA cofactor and in the steady-state hydrolysis of ATP by monomers within an assembled filament [ 10 , 11 , 12 ]. The function of RecA-mediated ATP hydrolysis has been a source of conjecture and debate for over two decades [ 10 , 11 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ]. The bacterial RecA protein promotes the central steps of recombinational DNA repair [ 12 , 22 ]. In vitro, the RecA protein catalyzes a DNA strand exchange reaction that mimics the presumed function of RecA protein in vivo. The RecA protein first forms a filament on single-stranded DNA (ssDNA). The bound ssDNA is then aligned and paired with a homologous double-stranded DNA (dsDNA), forming a short (up to approximately 1 kilobasepair [kbp]) segment of paired DNA and initiating the DNA strand exchange [ 11 , 12 ]. The initial paired DNA can be extended in a reaction that generally requires ATP hydrolysis [ 10 , 11 , 12 ]. RecA filaments are assembled and disassembled in an end-dependent fashion. Filament assembly proceeds in steps, with a slow nucleation followed by a very rapid 5′ to 3′ extension phase to coat the available DNA [ 11 , 12 , 23 , 24 , 25 ]. The rapid extension phase does not limit overall filament assembly within the pH range normally used for RecA experiments [ 26 , 27 ]. Filament disassembly is also end-dependent and proceeds 5′ to 3′ such that monomers are subtracted from filaments at the end opposite to the end where monomers are added in the extension process ( Figure 1 ) [ 25 , 28 , 29 ]. In studies carried out to date, we have not detected RecA monomer addition to the disassembling end or RecA monomer subtraction from the assembly (extension) end [ 25 , 27 , 28 ], although both processes presumably occur at some low rate. Figure 1 RecA Filament Assembly and Disassembly on ssDNA The reaction is limited by a slow nucleation step, followed by rapid extension in the 5′ to 3′ direction. Disassembly is also uniquely 5′ to 3′, proceeding from the end opposite to that where extension occurs. Dissociation of RecA monomers at the disassembling end requires ATP hydrolysis (see text). The RecA protein also binds to dsDNA, but nucleation onto dsDNA is much slower than onto ssDNA [ 26 , 30 ]. Nucleation directly onto dsDNA is pH-dependent, occurring more rapidly as the pH declines from 7.0 to 6.0 [ 30 , 31 ]. At any pH, filament extension on dsDNA is rapid, with complete filaments incorporating thousands of RecA monomers within a few minutes [ 25 , 32 , 33 , 34 ]. Upon binding dsDNA, RecA underwinds the DNA by approximately 40% and extends the helix to about 18 basepairs (bp) per turn relative to the B-form helix [ 35 , 36 ]. A RecA monomer binds three nucleotides (nt) of ssDNA or 3 bp of dsDNA, so one helical turn of the nucleoprotein filament includes approximately six RecA monomers. RecA protein within a filament hydrolyzes ATP in a reaction that is almost completely DNA-dependent under standard reaction conditions [ 31 ]. Under our normal reaction conditions, the intrinsic k cat values for ssDNA and dsDNA-dependent ATP hydrolysis rates are approximately 30 and 20 min −1 , respectively, as determined in multiple trials over the past two decades [ 10 , 11 , 12 ]. ATPase rates are independent of pH in the range 6–9 [ 30 , 31 ]. ATP hydrolysis occurs uniformly throughout the filament of RecA-DNA complexes, and there is no detectable change or enhancement at filament ends [ 37 ]. In the presence of ATP analogs that are not hydrolyzed, RecA protein will form filaments on DNA and promote substantial DNA pairing and strand exchange [ 38 , 39 , 40 ]. However, RecA must hydrolyze ATP to bring about net filament disassembly [ 25 , 27 , 28 , 29 , 32 , 33 , 34 ], bypass of heterologous inserts during DNA strand exchange [ 41 , 42 ], DNA strand exchange with DNA substrates greater than 3 kbp in length [ 43 ], and DNA strand exchange between two duplex DNA molecules [ 42 , 44 , 45 ]. It is not clear how RecA protein-mediated ATP hydrolysis is coupled to these functions. Intriguingly, the core domain of the RecA protein (residues 34–269) is structurally homologous to several motor proteins, including hexameric helicases [ 46 ] and the mitochondrial F 1 -ATPase [ 47 ]. Models for a motor-like coupling of ATP hydrolysis to DNA strand exchange in certain DNA metabolic situations have been proposed [ 10 ]. There is now evidence for at least four different functional states of RecA protein, occurring at different reaction stages. These have recently been designated O, Ac, Ao, and P [ 10 , 48 , 49 ] ( Figure 2 ). The O state is largely inactive and found in the absence of nucleotide cofactors or in the presence of ADP [ 50 ]. RecA in the O state can bind to DNA, creating a helical filament with a pitch of 76 Å [ 50 ]. Addition of ATP, ATPγS, or dATP results in a conformation change to an active form that is manifested by extended filaments on DNA with a pitch of 95 Å [ 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 ]. When RecA filaments form on ssDNA, they are in a structural and functional state designated A. Interconversion between the two different A states, which have somewhat different properties, is mediated largely by the Mg 2+ concentration. However, all RecA filaments on ssDNA hydrolyze ATP with a k cat of approximately 30 min −1 . Addition of a second DNA strand to a RecA filament, as in a filament bound to dsDNA or a filament promoting DNA strand exchange, converts the filament to the P state. The P state is characterized by 30% lower rates of ATP hydrolysis [ 59 , 60 ], higher rates of exchange of RecA monomers into and out of the filament [ 61 , 62 ], and a higher degree of cooperativity in the ATPase function [ 27 , 49 , 61 ] than the A conformations. Figure 2 Four Structural States of RecA Protein The O state is present in the absence of ATP or ATP analogs, whether the protein is free in solution or bound to DNA. The A state is found on ssDNA in the presence of ATP. Two versions of the A state, Ac and Ao, are found at different Mg 2+ concentrations. Addition of a second DNA strand to the RecA filament converts it to the P state. How can RecA monomers be added to one end of a filament and deleted from the other end in the same test tube? The monomer-monomer interfaces are presumably the same at either end (and everywhere else) in the filament. As pointed out by Wegner [ 63 ], the dissociation constant, K D , for monomer addition to either filament end cannot be different unless an independent source of chemical energy is provided to affect the binding to one end or the other. As noted above, filament assembly does not require ATP hydrolysis, but filament disassembly does [ 25 , 27 , 28 , 29 , 32 , 33 , 34 ]. The hydrolysis of ATP by interior monomers does not generally result in dissociation, and under some conditions ATP hydrolysis can proceed with no evident dissociation of RecA monomers [ 25 , 61 , 64 ]. A simple model arises: ATP hydrolysis occurs everywhere, resulting in dissociation only for monomers at a disassembling end. Within a RecA filament, ATP hydrolysis could occur at random, or it could be highly organized as cooperative waves traveling through the filament. There is no convenient method for monitoring the effects of ATP hydrolysis in the middle of a RecA filament. However, important clues can be ascertained by examining one effect of ATP hydrolysis: the 5′ to 3′ end-dependent filament disassembly process. In effect, we cannot see waves of ATP hydrolysis within a filament, but we can monitor one of the waves—the one occurring at the disassembling filament end. The rate of disassembly can lead directly to an assessment of the degree of coupling of the ATP hydrolytic cycles of adjacent RecA monomers within the filament. For example, since RecA hydrolyzes ATP at a rate of approximately 30 min −1 on ssDNA, each RecA monomer is hydrolyzing one ATP molecule every 2 s. If the ATP hydrolytic cycles of adjacent monomers are not coupled in any way, this will be reflected in a predictable rate of filament disassembly. When the end monomer hydrolyzes ATP and dissociates, the next monomer in line could be at any point within its ATP hydrolytic cycle. However, in a large population of filaments, the next monomer will be on average halfway through the cycle, and it will hydrolyze ATP (and dissociate) one second later. Dissociation of one RecA monomer per second will lead to a measured disassembly rate of 60 monomers of RecA per minute per filament end. This is close to the situation observed for RecA monomers formed on ssDNA (functional state A), which disassemble with a rate of 60–70 monomers per minute per filament end [ 27 ]. Note that this is the slowest rate of disassembly compatible with the rate of ATP hydrolysis observed under the conditions of this experiment, and requires that every ATP hydrolytic event occurring in the RecA monomer at the disassembly end of the filament results in dissociation of that monomer. If the probability of dissociation upon ATP hydrolysis is less than 100%, the disassembly process would have to be slower than is observed. A coupling of the ATP hydrolytic cycles of adjacent monomers could in principle lead to greater rates of filament disassembly. We are particularly interested in the status of RecA filaments formed on dsDNA and those promoting DNA strand exchange. As indicated above, these filaments are in the P functional state and exhibit a higher degree of coupling involving the hydrolytic cycles of adjacent monomers than is seen for filaments formed on ssDNA. If ATP hydrolysis is organized into cooperative waves traveling through the filament, then the rate of disassembly from dsDNA will reveal the rate of movement of one of the waves and the interval, i, between successive waves within the entire filament. For example, consider monomers within RecA filaments on dsDNA that are hydrolyzing ATP at approximately 20 min −1 (or one ATP every 3 s). If ATP hydrolytic cycles of adjacent monomers are coupled within the filament so that ATP hydrolysis is organized in waves ( Figure 3 ), then a new wave must reach a given monomer every 3 s to account for the observed k cat . If the waves are four monomers apart ( i = 4 monomers, Figure 3 A), a wave must move from one monomer to the next one in line every 0.75 s. At the disassembling end (the ultimate wave), one monomer would dissociate every 0.75 s, giving a disassembly rate of 80 monomers min −1 filament end −1 . If instead the waves are organized at intervals of six monomers ( Figure 3 B), then to reach a given monomer every 3 s, a wave would have to move from one monomer to the next every 0.5 s. At the disassembling end, a monomer would dissociate every 0.5 s to yield a disassembly rate of 120 monomers min −1 filament end −1 . We define the rate of end-dependent filament disassembly as k off . Note that the numerical relationship between k off and the k cat for ATP hydrolysis by individual monomers reveals the distance between waves within the filament, i , such that k off / k cat = i . For the examples above, 80/20 = 4, and 120/20 = 6. Figure 3 Coupled Waves of ATP Hydrolysis in RecA Filaments (A) The interval between hydrolyzing monomers (i) is set at four monomers. The dark monomers are those at the hydrolytic step of their ATP hydrolytic cycle. Each monomer within the filament (e.g., the one marked with an “X”) is hydrolyzing an ATP every 3 s, so that a new wave must reach it within that time span. If i = 4 monomers, the waves must move every 0.75 s. The last wave, at the disassembling end, results in dissociation. (B) The same considerations in (A) for i = 4 monomers are illustrated for i = 6 monomers. The k cat for ATP hydrolysis for RecA monomers on dsDNA is readily measured. An accurate determination of k off , as needed to determine i, is a more substantial challenge that is met in this report. Results Experimental Design A model system has been developed that allows the rate of end-dependent RecA filament disassembly from ssDNA to be determined quantitatively by monitoring the rate of ATP hydrolysis during the disassembly process [ 10 , 27 ]. The system is outlined in Figure 4 A. RecA filaments are assembled on a linear ssDNA at a low pH, at which nucleation is fast enough that the DNA is saturated with RecA and there is little net disassembly (disassembling RecA monomers are rapidly replaced). The reaction mixture is then shifted to a higher pH, at which the rate of filament nucleation is slower and net filament disassembly can be observed. The rate of ATP hydrolysis will decline as RecA monomers dissociate from the DNA [ 27 ], reaching a nonzero steady-state endpoint ( Figure 4 B). The steady-state rate reflects the final balance between disassembly and renucleation of RecA protein and filament formation on the ssDNA vacated by the disassembling filament. Since filament extension is very fast relative to disassembly, any nucleation event will result in a filament that extends from the nucleation point to the disassembling end of the first filament, and in effect create a new point for disassembly ( Figure 4 A). On any of these DNA molecules, there is only one point where net disassembly occurs. Even when the second filament is not perfectly in phase with the first filament, such that some disassembly continues at the junction ( Figure 4 C), the RecA that dissociates from filament 1 at the junction is rapidly replaced by extension of filament 2 immediately behind it (filament extension is much faster than disassembly). Thus, there is no net change in bound RecA that would be reflected in the observed rates of ATP hydrolysis, except at the end of filament 2. To minimize the rebinding of RecA protein to vacated DNA, ssDNA-binding protein of Escherichia coli (SSB protein) is added at the time of the pH shift [ 27 ]. Bound SSB limits the nucleation of RecA filaments on ssDNA [ 25 , 65 , 66 , 67 ]. This in turn permits a measurable decline in ATP hydrolysis. Figure 4 Model for RecA Filament Disassembly from Linear ssDNA (A) In the model, end-dependent disassembly occurs, with SSB filling in the vacated DNA. At low frequency, additional RecA monomers nucleate filament formation on the vacated DNA, and the new filament (dark ovals) extends until it catches up with the original filament (open ovals). This creates a new disassembling end. (B) Kinetics of disassembly as monitored by DNA-dependent ATP hydrolysis. This curve is an approximation of curves reported in previous work [ 27 ]. The rate of ATP hydrolysis declines as RecA protein dissociates from the ssDNA, until a lower steady-state rate is reached. The steady state reflects a balance between disassembly and new filament formation. (C) If, upon rebinding, the new filament does match the old one in phase, the junction between the old and new filaments could be a site of RecA monomer exchange with the solution. There will be no net disassembly at this point and no resulting change in the rate of ATP hydrolysis, because any monomers that dissociate will be immediately replaced by extension of the trailing filament. The process in Figure 4 is modeled by equation 1 , where k nuc is the rate of renucleation of RecA filaments to vacated DNA during the disassembly process, k off is the end-dependent disassembly rate as noted in the Introduction, n tot is the total number of RecA protein binding sites on the DNA molecule used as substrate, [D-ends] is the concentration of disassembling ends, and k cat is the turnover number for ATP hydrolysis by RecA monomers in the filament. The derivation of equation 1 is described in detail elsewhere [ 27 ]. The assumptions incorporated into the equation and the model of Figure 4 are also detailed elsewhere [ 27 ]. In brief, the assumptions are as follows. First, nucleation of filament formation is the rate-limiting step for RecA filament assembly. This assumption is documented in the Introduction of this paper and in previous reports [ 23 , 27 ]. Second, filament extension is faster than filament disassembly under all conditions. The simplest of the arguments [ 27 ] underpinning this assertion is that filaments would never form on DNA if RecA were subtracted from the disassembling end faster than it could be added to the extending end. Third, the model assumes that net disassembly is occurring at only one point in each filament. This is addressed in Figure 4 C and follows from the fact that filament extension is faster than filament disassembly. There will be no net disassembly except at the 5′ proximal end of the RecA protein tracts on a given linear DNA. Any dissociation in the middle of a filament is rapidly replaced by the growth of trailing filament segments and thus cannot contribute to a net change in ATP hydrolysis. Finally, the assumption is made that the k cat for RecA-mediated ATP hydrolysis does not change in the range used for the pH shifts. This is documented elsewhere [ 26 , 27 , 30 ]. On dsDNA, the situation becomes more complicated because it is more difficult to define the orientation of the filaments. RecA protein binds to the two strands of a duplex DNA unequally. One strand is bound at the site normally occupied by ssDNA. This strand orients the filament, and it is protected from nuclease digestion better than the second strand of a duplex [ 33 , 68 ]. We will call this first strand the initiating strand [ 22 ]. In principle, either strand of a duplex can act as the initiating strand and organize the 5′ to 3′ assembly of RecA filaments. RecA filaments can thus form in two orientations on dsDNA ( Figure 5 A). If nucleation occurs in the middle of a linear duplex so that the filament extends to one end, and a second nucleation occurs on the same DNA but in the opposite orientation, there could be two filaments on the same DNA, both with disassembling ends ( Figure 5 A). This in turn would complicate the mathematical modeling of the disassembly reaction. This potential problem can be alleviated by supplying a good nucleation site in the form of a stretch of ssDNA. At pH 8 and above, RecA nucleation onto duplex DNA becomes very slow (measured in hours) [ 26 , 30 ]. If a 5′ single-strand extension is added to one end of the DNA, the nucleation occurs within a few minutes, and RecA readily extends from the single-stranded segment into the adjoining duplex [ 33 ]. A 3′ single-strand extension does not work [ 33 ], as would be predicted from the polarity of filament assembly from a nucleation site. This effect is seen in the experimental data presented in Figure 5 B. RecA binds to a linear duplex of 3,162 bp only after a lag lasting tens of minutes, even at pH 6.6. A linear duplex of similar length, but this time with a 5′ single-strand extension of 30 nt, is bound without a measurable lag at the same pH. This indicates that the filaments are nucleating on the single-strand extension, and virtually all of the resulting filaments in the population will have a unique orientation over the entire length of the DNA that is dictated by the single-stranded tail. Figure 5 RecA Filament Formation on dsDNA (A) RecA filaments can nucleate on dsDNA so as to have two different orientations. The initiating strand guides the orientation of each filament, with its polarity labeled in each panel. If two nucleations occur on the same filament, there can be two independent disassembly points. (B) The effect of the 30-nt 5′ extensions on RecA protein filament formation. Reactions contained 4 μM RecA protein, 4 μM DNA, and no SSB and were carried out at pH 6.6. The tailed DNA substrate has 2,900 bp of duplex DNA with the 30-nt 5′ extension on one end. The completely duplex DNA is 3,162 nt in length. The enhanced nucleation afforded by these tails is evident in the rapid ATP hydrolysis seen when the tailed DNA is used as cofactor. To isolate the disassembly process so that it can be measured accurately, we must limit the rate of RecA rebinding to DNA that has been vacated as the RecA dissociates. Several parameters can be adjusted to accomplish this. The first one is pH. The rate of RecA protein disassembly reaches an apparent maximum at pH 8 and above [ 33 ]. The rate of disassembly should reach a maximum when every ATP hydrolytic event at the disassembling end results in dissociation of a RecA monomer. The rate of nucleation on dsDNA declines with increased pH such that working at high pH minimizes RecA rebinding. The second parameter is DNA length, which can affect the consequences of rebinding to duplex DNA. A nucleated filament is rapidly extended to the DNA end. A nucleation event on a long DNA will generate more bound RecA than a nucleation event on a short DNA. Thus, the use of shorter DNAs will limit the effects of each nucleation event. However, the DNA length cannot be reduced too much to suppress the levels of RecA protein rebinding, because a longer DNA (and filament) allows for a more gradual decline in the ATPase reaction that is easier to monitor. Trials using DNAs of several lengths indicated that a linear dsDNA with a length of approximately 3 kbp was optimal for this work [ 33 , 69 ]. These dsDNAs result in bound RecA filaments long enough (about 1,000 monomers) to disassemble over a time period of multiple minutes, while limiting the effects of RecA rebinding. As shown later, we also carried out measurements using dsDNAs of 2 kbp and 4 kbp. A third parameter that can be adjusted is SSB concentration. Adding SSB when the pH shift is carried out inhibits the rebinding of free RecA protein to the ssDNA extension. The concentrations of SSB used in these experiments were determined empirically to provide the maximum possible suppression of RecA renucleation. The effectiveness of this SSB-mediated suppression is illustrated in Figure 6 . Figure 6 The Effect of SSB Protein in Suppressing Rebinding of RecA to the Single-Strand Tails (A) Normal RecA filament disassembly protocol. The RecA filaments were formed on the tailed DNA at pH 6.62. The pH was then shifted to 8.0 to allow disassembly to commence. Disassembly curves are shown in the presence and absence of SSB. Reactions contained (after the pH shift) 2 μM RecA protein, 2 μM DNA, and (where indicated) 0.05 μM SSB. (B) Direct binding of RecA protein to the tailed DNA at pH 8.0. Reactions contained 6 μM RecA protein, 6 μM DNA, and (where indicated) 0.15 μM SSB. When included, SSB was added prior to the RecA protein. Optimizing all of these considerations, the general protocol for these experiments is outlined in Figure 7 A. A linear duplex of 2,900 bp, with a 30-nucleotide 5′ single-strand extension, is bound with RecA protein at pH 6.62. The DNA concentration is 12 μM, so that the concentration of RecA binding sites is 2 μM. The RecA protein is added in excess (12 μM) to facilitate saturation of the DNA. After binding is complete, the rate of ATP hydrolysis is measured. The pH is then shifted abruptly to 8 by diluting the solution 2-fold into a solution with another buffer. The RecA and DNA concentrations undergo a 2-fold decrease during the pH shift, but the concentration of ATP and ATP regeneration components are kept constant. The pH shift initiates a net disassembly process that leads to a decline in ATP hydrolysis. Rebinding of RecA protein to the vacated single-strand extension is suppressed by SSB added with the pH shift buffers. The production of ADP is monitored. The ATP regeneration system is set up so as not to limit the observed results. For example, results were the same if the phosphoenolpyruvate (PEP) concentration was reduced from 3 to 1.5 mM. The starting k cat for ATP hydrolysis is reported as the measured rate of ATP hydrolysis prior to the pH shift (in μM min −1 ), divided by the initial concentration of bound RecA protein (in 2 μM). Figure 7 Quantitative Measurement of RecA Filament Disassembly from dsDNA (A) The experimental protocol, as described in the text. (B) A typical disassembly curve. The black line is the measured ADP production curve. The orange line is the fitting of the data by equation 1 . (C) The curve is identical to that shown in panel B for the 3-kbp DNA substrate, with the best fit line shown in orange. However, two additional curves (in solid black) are shown to illustrate the variation in fitting if the value of k off is constrained to values 10% above or 10% below the best-fit determination. With the filaments uniquely oriented on the tailed DNA and encompassing the entire length of the DNA, equation 1 can be applied to the measurement of disassembly from dsDNA in the same manner as it was used to analyze the disassembly from ssDNA. The rate of filament disassembly, k off , is obtained by fitting the equation to the ADP production curve. There is just one caveat. The renucleation onto the vacated DNA must be suppressed sufficiently so that there is, to a reasonable approximation, no more than one disassembling RecA filament end per bound DNA. If multiple filaments formed on the vacated dsDNA as a result of renucleation, this process would not be properly modeled by equation 1 (which was derived for a model in which all filaments had a single orientation [ 27 ]). As described below, the rates of renucleation are suppressed sufficiently in these experiments so that this condition is met. Measurement of Disassembly Rates from Duplex DNA A typical experiment is illustrated in Figure 7 B. Equation 1 relates the production of ADP in terms of the two primary unknowns, k off and k nuc , as well as several known parameters. All concentrations are in μM, and all times are in minutes. The data from ATP hydrolysis assays were converted to [ADP], plotted as a function of time, and fit to equation 1 using the program SigmaPlot from SPSS (Chicago, Illinois, United States). The terms [D-ends], n tot , and [RecA] were known for each experiment and held constant for fitting. The terms k off and k nuc were the fitting parameters. The apparent k cat for ATP hydrolysis was determined independently as the rate of ATP hydrolysis before the pH shift and initiation of net filament disassembly divided by the concentration of bound RecA protein. However, k cat can be determined as a fitting parameter as well. Therefore, each dataset was fit to equation 1 twice: once with k cat held constant at the value measured prior to the pH shift, and once with k cat as a fitting parameter in addition to k nuc and k off . The fit parameters for both fittings were compared. Experiments were discarded in which the measured and fit k cat did not agree to within 40%, or the measured k cat was less than 18 min −1 (generally corresponding to a problem with one or more reagents or equipment on that day). For the 3 kbp substrate used in Figure 7 , data were collected in 16 trials carried out over a period of 3 mo. During that time, 12 trials were utilized and four were discarded on the basis of these considerations. The plot in Figure 7 B is nonlinear, reflecting the decline in the rate of ATP hydrolysis as the RecA filament disassembles from the DNA. The form of the curve is the same as that shown in Figure 4 B, although the time scale is abbreviated. The rate of ATP hydrolysis settled to a slow steady-state rate in which disassembly and rebinding are balanced. The twelve trials that met the conditions elaborated above are detailed in Table 1 . The result presented in Figure 7 B is representative. The fitting performed with the k cat fixed at the average value measured prior to the pH shift, k cat = 19.5 ± 0.6 min −1 , yields the best-fit values (averaged over 12 experiments) of k off = 120 ± 20 min −1 and k nuc = 4.6 ± 0.75 × 10 −5 μM −1 min −1 . When k cat was allowed to vary as a fitting parameter along with k off and k nuc , the parameters were again obtained from the best-fit curves and averaged. This yielded k cat = 21.6 ± 4.4 , k off = 133 ± 24 min −1 , and k nuc = 5.1 ± 0.89 × 10 −5 μM −1 min −1 for the 12 datasets. The reasonable agreement between the measured and fit k cat values in most trials helped provide confidence that the k cat measured prior to the pH shift was consistent with the observed reaction progress curve obtained after the pH shift. Table 1 Experimental Parameters Obtained in Individual RecA Filament Disassembly Trials a Units of k cat , min −1 b Units of k off , monomers per minute per filament end c Units of k nuc , μM −1 min −1 Ave, average; s, standard deviation The fitting process is quite sensitive to small changes in the fitting parameters. Figure 7 C illustrates the result of constraining k off to values 10% above and 10% below the value obtained by fitting the data in Figure 7 B for the 3 kbp DNA substrate. In both cases, the curves deviate substantially from the data and demonstrate the sensitivity of our model. As long as the stated constraints on the use of equation 1 are met, the results should be independent of DNA length. To confirm, disassembly rates were obtained using DNA substrates of 1,961 and 3,900 bp (referred to as our 2 kbp and 4 kbp substrates, respectively). Each of these had a 5′ extension, with the same length (30 nt) and sequence as the one used for the 3-kbp DNA substrate. In this series of experiments, there were 16 trials with each DNA substrate. Of these, 12 and 14 trials (for the 2- and 4-kbp substrates, respectively) met the conditions established above for the 3-kbp DNA substrate trials, and these are reported in Table 1 . The total concentration of DNA base pairs was kept constant in these experiments, so that the concentrations of DNA molecules and thus disassembling ends either increased (2-kbp substrate) or decreased (4-kbp substrate). These new trials were carried out over the course of one month. The results agreed very well with those obtained with the 3-kbp DNA, with the k cat and k off values remaining constant (within experimental error) as a function of DNA length as summarized in Table 1 . For the 2-kbp DNA, constraining k cat to the value measured before the pH shift (average 20.9 ± 0.6 min −1 ) yields the best-fit values of k off = 125 ± 9 min −1 and k nuc = 1.0 ± 0.075 × 10 −4 μM −1 min −1 . In the same manner, the 4-kbp DNA substrate yielded average values of k off = 124 ± 19 min −1 and k nuc = 2.5 ± 0.52 × 10 −5 μM −1 min −1 with a measured k cat = 21.7 ± 1.8 min −1 . When k cat was allowed to vary as a fitting parameter along with k off and k nuc , the best-fit values for the 2-kbp DNA substrate averaged k cat = 20.5 ± 2.4 min −1 , k off = 121 ± 10 min −1 , and k nuc = 9.9 ± 0.76 × 10 −5 μM −1 min −1 for the 12 datasets. The 4-kbp DNA substrate yielded best-fit values of k cat = 23.6 ± 3.0 min −1 , k off = 136 ± 14 min −1 , and k nuc = 2.8 ± 0.26 × 10 −5 μM −1 min −1 for the 14 datasets. All of this work is summarized in Table 1 . If all of the data in Table 1 are averaged (38 total trials), the values obtained when constraining k cat to the value measured before the pH shift are k cat = 20.8 ± 1.5 min −1 and k off = 123 ± 16 min −1 . When k cat was not constrained, the values were k cat = 22 ± 3.5 min −1 and k off = 130 ± 18 min −1 . Unlike the other parameters, the nucleation of filament formation as expressed in k nuc should be affected by factors such as G:C content and sequence structure in the duplex DNA [ 26 , 30 ], and was not averaged over the three sets of trials. Within a single set of trials, k nuc was quite reproducible. Representative trials using the 2-, 3-, and 4-kbp DNA substrates are compared in Figure 8 . The initial rates are essentially the same in each case, since the concentration of bound RecA is the same. If RecA dissociates from one end of the filament at a constant rate, disassembly of the longer filaments formed on longer DNAs should require correspondingly more time. The pattern seen here is consistent with that expectation. The final steady state rate of ATP hydrolysis reflects both k nuc and the length of the DNA, and thus varies somewhat. Figure 8 RecA Filament Disassembly Rates Are Independent of DNA Length Typical disassembly curves are shown for the 2-, 3-, and 4-kbp DNA substrates. The black lines are the data, and the orange lines represent the best fits to the data by equation 1 . Note that the early, rapid phase of the curves are extended in concert with the increase in the length of the DNA substrates. The rates of disassembly derived from the curves are identical within experimental error, as summarized in Table 1 and the text. As already noted, equation 1 is useful only if there is no more than one disassembling end on a particular DNA molecule. The final steady state achieved after the major phase of filament disassembly is complete allows us to estimate the likelihood that multiple filaments with different orientations rebind to the same stretch of vacated DNA. We address this issue for the 3-kbp DNA substrate. Immediately following the pH shift, the concentration of RecA binding sites on the 6 μM DNA is 1 μM, and this represents the concentration of bound RecA at the outset. The average rate of ATP hydrolysis when disassembly was initiated was 19.5 ± 0.6 μM −1 min −1. The average final steady-state rate of ATP hydrolysis is 1.23 μM −1 min −1 , or 6.3% of the rate observed prior to disassembly. This final rate corresponds to 6.3% occupancy of the available RecA binding sites, or 0.063 μM bound RecA protein. We estimate that the average filament at steady state occupies one-quarter of the available RecA binding sites in the DNA to which it is bound from the following considerations. When a new RecA filament nucleates onto the vacated DNA, the nucleation could occur anywhere along the length of the DNA. On average, the nucleation would occur at the center of the DNA, and the fast unidirectional filament extension phase would quickly coat the DNA from that point to one end, so that the typical new filament would occupy half of the available RecA binding sites on the DNA to which it was bound. At steady state, filaments would be disassembling at a rate that just balances the rate of renucleation of filaments to replace them (with the rate of disassembly much slower than filament extension). A given filament could be anywhere in the disassembly process, but the average filament bound at steady state will have lost half of its length. The average filament at steady state will thus occupy one-quarter of the RecA binding sites on a given DNA molecule. If 6.3% of the available DNA binding sites are occupied by RecA thus distributed in filaments that coat one-quarter of a DNA molecule, then we can estimate that 25.2% of the DNA molecules have some bound RecA protein. About 6% of the DNAs ([0.252] 2 , or approximately 0.06) will have two filaments bound. Half of these will have two filaments with the same orientation, and thus effectively have only one end where net disassembly will occur. The remaining 3% of DNAs with the potential for two bound filaments and two disassembling ends represent the maximum percentage of DNAs in this condition, and this maximum can only be approached late in the disassembly process after the DNA initially bound by oriented filaments has been vacated completely. Since the potential for multiple filaments is limited early in the dissociation curve, and 3% in any case is well within the error limits of our measurements, we have not adjusted our model or corrected our reported rates for this effect. To the extent that multiple disassembling ends contribute to the observed rates, they would lead to a very slight overestimate of the disassembly rate. The interval between waves of ATP hydrolysis, i , is k off / k cat . We calculate i to be 6.0 ± 0.5, 6.2 ± 1.1, and 5.8 ± 1.1 monomers for the 2-, 3-, and 4-kbp DNA substrates, respectively. As with the other parameters, these values agree well and are identical within experimental error. When averaged across all 38 trials, i is 6.0 ± 0.9 monomers if k cat is constrained and 6.0 ± 0.8 monomers if k cat is not constrained (see Table 1 ). As noted in the Introduction, the quantitative disassembly model predicts a different k off value for different values of i . To explore further the significance of this determination, we carried out an additional exercise. Each filament disassembly dataset was fit to equation 1 with k cat held constant to the value measured before net filament disassembly and k off held constant to the value predicted by the model for values of i from 4 to 9. When the quality of the data fit (as measured by R 2 ) is plotted against i , an optimum is seen at i = 6.4 monomers for the 3-kbp DNA substrate ( Figure 9 ). The optimum is seen at i = 5.9 monomers for the 2-kbp DNA substrate, and at i = 5.8 monomers for the 4 kbp-DNA substrate (unpublished data). Figure 9 Quality of the Data Fitting, as Measured by R 2 , Varies with Changes in i The calculation is illustrated for the 3-kbp DNA substrate. A maximum is seen at i = 6.4 monomers. For each of the 12 independent datasets used in this work, the measured k cat was multiplied by the indicated value of i to get a predicted k off . This value of k off was then used to fit the data to equation 1 , constraining k off and k cat and allowing k nuc to vary. R 2 is then a measure of the quality of the resulting fit. The R 2 value in each case is averaged for 12 trials. Discussion We conclude that when RecA protein is bound to dsDNA, ATP hydrolysis within the filament occurs in highly organized and unidirectional waves. Successive waves occur at intervals of approximately six monomers and travel through the filament at a rate of approximately 120 monomers per minute. More precisely, the rate of RecA protein filament disassembly from dsDNA (which represents the ultimate wave) is 123 ± 16 RecA monomers per minute per filament end, under the conditions of these experiments. While this is occurring, ATP is being hydrolyzed by monomers within the filament with a measured k cat of 20.8 ± 1.5 min −1 . The ratio k off / k cat gives i , the interval between the waves of hydrolysis within the filament. The k off / k cat = i = 6.0 ± 0.9 monomers. These results are taken from data in which the k cat for ATP hydrolysis was constrained to the value measured prior to the pH shift. The results are quite similar when k cat is not so constrained ( Table 1 ). Given that there are six RecA monomers per helical turn of a RecA filament, this relationship reveals a striking pattern of ATP hydrolysis by RecA protein, one in which the ATP hydrolytic events at a given moment are lined up along one longitudinal face of the filament ( Figure 10 ). These “stripes” of ATP hydrolysis proceed around the circumference of the filament in six steps, with successive steps occurring at 0.5-s intervals. The overall pattern corresponds well to a rotary motor model for the coupling of RecA-mediated ATP hydrolysis to DNA strand exchange, and fulfills the last of three major predictions of that model [ 10 ]. The motor function of RecA may play a role in certain aspects of the repair of stalled replication forks [ 10 ]. Figure 10 Coordination of ATP Hydrolytic Waves in a RecA Filament The dark monomers are those in the hydrolytic step of their hydrolytic cycle. The successive steps are separated by 0.5 s. The model shown assumes exactly six RecA monomers per helical filament turn and i = 6.0. As noted in the text, both the helical organization in the filament and the organization of ATP hydrolytic waves in RecA filaments may deviate slightly from this ideal. Note that there is no evidence that a RecA monomer in a filament is in contact with another RecA located six monomers away, so each of the gray balls shown in these illustrations are separated from their gray neighbors. An animated version of this model is available in Video S1 . The rate of filament disassembly that we measure is consistent with a rough estimate of 2.4 monomers per second (144 min −1 ), obtained by Libchaber and colleagues [ 34 ]. This earlier estimate was based on single molecule experiments using very long DNAs, and ADP buildup that can contribute to aggregate filament dissociation [ 54 , 55 , 70 ] was not controlled. Importantly, the rate of RecA filament disassembly from dsDNA is nearly twice that from ssDNA [ 27 ], reflecting the change in functional state that is observed when a second strand of DNA is introduced into a RecA filament [ 10 , 48 , 49 ]. The observed rate of filament disassembly on dsDNA is three times that predicted for a similar filament with no ATP hydrolytic coupling between adjacent monomers. At a minimum, this must reflect an elaborate coordination of ATP hydrolytic cycles for adjacent RecA monomers in the filament. The functional state of RecA protein filaments on dsDNA is, in every experimental sense tested to date, identical to the functional state observed during active DNA strand exchange [ 10 , 12 , 49 , 62 ]. We therefore propose that the current results directly reflect the status of RecA filaments that are actively promoting DNA strand exchange. The extent of coupling between RecA monomers inferred from the current experiments can be correlated to information derived from EM observations of the nucleoprotein filament. The datasets fit best to equation 1 with a k off corresponding to ATP hydrolysis reflecting i = 5.8–6.4 RecA monomers. The directly measured average k off / k cat ratio for all datasets suggests that i = 6.0 ± 0.9 RecA monomers. Interestingly, previous EM reconstructions of the RecA-dsDNA complex indicate that there are 6.2 RecA monomers per helical turn of the nucleoprotein filament under at least some conditions [ 52 ]. This may imply an organization that is highly ordered, albeit not quite as ideal as the organization depicted in Figure 10 . The RecA crystal structure does not reveal any contact between every sixth monomer in the helix [ 71 , 72 ]. This suggests that coordination within the filament is mediated through adjacent monomer-monomer contacts. With ATP hydrolytic waves spaced at six-monomer intervals, it is tempting to postulate a hydrolytic cycle with six distinct steps. In one turn of the helix, there could be six slightly different monomer conformations, corresponding to various stages of binding, hydrolyzing, and releasing nucleotide. Indeed, multiple conformations of RecA protein within the RecA nucleoprotein filaments have been observed [ 73 ]. Unlike a hexameric circle (such as the hexameric helicases to which RecA appears related), the synchronization between steps in the hydrolytic cycle could readily produce a noninteger separation of ATP hydrolytic waves (e.g., 6.2 monomers) in a filament. Although our average value of 6.0 for the parameter i is consistent with the idealized picture of Figure 10 , the experimental error could readily accommodate such noninteger outcomes. The ATP hydrolytic cycle should now become the focus of more intensive investigation. We have little information about the steps in the cycle as they occur on RecA protein, nor do we know to which step dissociation of a RecA monomer might be coupled. For example, the dissociating form of RecA could be almost any species one could imagine as an intermediate in the ATP hydrolytic cycle, such as a RecA-ADP complex, a RecA-Pi complex, or any of a number of other possibilities. The model presented in Figures 3 B and10 works regardless of the precise mechanism of ATP hydrolysis proposed. The patterns of ATP hydrolysis we observe in RecA filaments are quite distinct from those documented for other major filament types. The tubulins [ 1 , 2 , 3 ] and the actins [ 4 , 5 , 6 ] are filament-forming proteins that bind and hydrolyze GTP and ATP, respectively. The NTP hydrolysis affects the capacity of the filaments to assemble or dissociate. The proteins most readily assemble as the ATP- or GTP-bound forms. Very slow hydrolysis of the bound NTP results in a form that is more readily dissociated from the filament [ 4 , 5 , 6 ]. These filaments thus expand and contract in a pattern that is dictated by NTP hydrolysis, as well as by the activities of numerous regulatory proteins. The assembly and disassembly produces work at the filament ends. The ADP- or GDP-bound monomers in the filament interiors do not exchange nucleotides to rebind ATP or GTP, so there is no active nucleotide turnover within the filaments. In contrast, ATP hydrolysis occurs uniformly throughout a RecA protein filament formed on DNA. This ATP hydrolysis can result in filament disassembly at one end, as we continue to document here. However, the steady-state hydrolysis of ATP in the interior of RecA filaments does not result in dissociation and has the capacity to do a different kind of work. The rotary motor illustrated in Figure 10 can be coupled to DNA strand exchange. That coupling is inferred by the capacity of RecA to drive strand exchange through heterologous DNA inserts [ 41 , 42 ], promote unidirectional strand exchange [ 13 , 43 ], and promote strand exchange between two duplex DNAs [ 42 , 44 , 45 ]—only when it is hydrolyzing ATP. The coupling is also seen in the predictable relationship that exists between the rates of ATP hydrolysis and branch movement during strand exchange [ 59 ], and in a kind of indirect DNA helicase reaction that RecA promotes with certain branched DNA substrates [ 74 ]. At least one potential biological role for this motor function can be found in the regression of stalled replication forks that is sometimes required for their repair [ 10 , 12 , 75 , 76 , 77 ]. Fork regression is promoted by RecA protein, but again only if ATP is hydrolyzed [ 10 , 78 , 79 ]. If RecA protein is bound to a chromosome at a replication fork, and ATP is available, the surrounding DNA will not remain static. We do not expect the organization revealed here for ATP hydrolysis in RecA filaments to apply generally to the eukaryotic homologs of RecA. The eukaryotic Rad51 protein hydrolyzes ATP at rates 30- to 40-fold below those reported for bacterial RecA proteins. RecA protein generally requires ATP hydrolysis for extensive strand exchange [ 17 , 42 , 43 ], while Rad51 protein does not [ 80 , 81 ]. There are no reports that Rad51 can promote the kinds of reactions to which RecA protein couples ATP hydrolysis (four-strand exchange and strand exchange past a significant heterology in the DNA substrates) [ 82 , 83 ]. Also unlike RecA, the Rad51 protein promotes DNA strand exchange with no intrinsic polarity [ 82 , 84 , 85 ]. RecA-mediated ATP hydrolysis is thus likely to have a role unique to bacterial DNA metabolism or a role that is supplanted by other proteins in eukaryotes. Materials and Methods Proteins and biochemicals E. coli RecA protein was purified to homogeneity as described [ 86 ]. Two different preparations were used for analysis, with one preparation having the final fraction subjected to an additional step. The protein was loaded onto a PBE-94 column equilibrated with R buffer (20 mM Tris-HCl [80% cation, pH 7.5], 1 mM dithiothreitol, 0.1 mM EDTA, and 10% [w/v] glycerol), and the column was developed with a linear gradient from 0 to 1.0 M KCl. The RecA protein was eluted at approximately 600 mM KCl, dialyzed extensively against R buffer, and concentrated as described. Results with both RecA protein preparations were the same and were combined. E. coli SSB was purified as described [ 42 , 87 ]. The RecA protein and SSB concentrations were determined by absorbance at 280 nm, using extinction coefficients of ɛ 280 = 0.59 A 280 mg −1 ml [ 88 ] and ɛ 280 = 1.5 A 280 mg −1 ml [ 89 ], respectively. RecA protein and SSB preparations were free of detectable endo- and exonuclease activities on dsDNA or ssDNA. Unless otherwise noted, all reagents were purchased from Fisher (Pittsburgh, Pennsylvania, United States). MES buffer, PEP, pyruvate kinase, lactate dehydrogenase, phosphocreatine, ATP, and NADH were purchased from Sigma (St. Louis, Missouri, United States). Creatine kinase and ATPγS were purchased from Roche Molecular Biochemicals (Indianapolis, Indiana, United States). Restriction enzymes were purchased from New England Biolabs (Beverly, Massachusetts, United States). T4 DNA polymerase was purchased from New England Biolabs, and T4 DNA ligase was purchased from Promega (Madison, Wisconsin, United States) and New England Biolabs. Dithiothreitol was purchased from Research Organics (Cleveland, Ohio, United States). Sephacryl S-500 and PBE-94 resins were purchased from Amersham Pharmacia Biotech (Piscataway, New Jersey, United States). DNA substrates Oligonucleotides were purchased from Integrated DNA Technologies. The concentrations of duplex DNA stock solutions were determined by absorbance at 260 nm using 50 μg ml −1 A 260 −1 as a conversion factor. All DNA concentrations are given in terms of total nucleotides unless otherwise noted. The 3-kbp linear double-stranded DNA substrate with a 30-nt single-stranded 5′ tail was generated by first digesting pUC119 plasmid DNA [ 90 ] with two restriction enzymes, SapI and SmaI. After digestion, residual protein was removed by sequential 1:1 extractions with phenol/chloroform/isoamyl alcohol (25:24:1) and chloroform/isoamyl alcohol (24:1). The resulting 2,883- and 279-bp fragments were concentrated by precipitation in ethanol. The 2,883-bp fragment was separated from the 279-bp fragment using size-exclusion chromatography with Sephacryl S-500 resin and concentrated with an Amicon Microcon concentrator (Millipore, Billerica, Massachusetts, United States). Residual protein was removed by sequential 1:1 extractions with phenol/chloroform/isoamyl alcohol (25:24:1) and chloroform/isoamyl alcohol (24:1). The 2,883-bp fragment was concentrated by precipitation in ethanol. Two complementary oligonucleotides, 47 and 20 nt in length, were annealed and ligated in excess to the staggered end of the 2,883-bp fragment. Excess oligonucleotides were separated from substrate DNA using size-exclusion chromatography with Sephacryl S-500 resin. The substrate DNA was concentrated with an Amicon Microcon concentrator (Millipore). Residual protein was removed by sequential 1:1 extractions with phenol/chloroform/isoamyl alcohol (25:24:1) and chloroform/isoamyl alcohol (24:1). The substrate DNA was concentrated by precipitation in ethanol. The 2-kbp linear dsDNA substrate with a 30-nt single-stranded 5′ tail was generated by first digesting pUC119 with EcoRI and AatII. The larger fragment was isolated via agarose gel extraction. The DNA ends were filled in with T4 DNA polymerase and ligated with T4 DNA ligase to result in the 2,223-bp pEAW373 plasmid DNA. The 4-kbp linear dsDNA substrate with a 30-nt single-stranded 5′ tail was generated by first digesting pUC119 with BanII that cuts at two sites, and the 2,766-bp fragment was separated from the 396-bp fragment via agarose gel extraction. Next, pACYC184 plasmid DNA [ 91 , 92 ] was digested with HindIII and AvaI, with the resulting 1,396-bp fragment isolated via agarose gel extraction. The DNA ends of the 2,766- and 1,396-bp fragments were filled in with T4 DNA polymerase and ligated with T4 DNA ligase to result in the 4,162-bp pEAW374 plasmid DNA. Both pEAW373 and pEAW374 maintained unique SapI and SmaI sites; they were treated in the same manner as the 3-kbp DNA substrate to yield 2- and 4-kbp linear dsDNA substrates with single-stranded 5′ tails. The lengths and sequences of the 5′ tails were the same in each of 2-, 3-, and 4-kbp DNA substrates. To confirm the identity of the linear dsDNA substrates, a sample of each DNA substrate was digested with AflIII to yield a 133-bp fragment with a 4-nt 3′ tail and 30-nt 5′ tail. Digest of the duplex fragments without annealed oligonucleotides would have resulted in a 113-bp fragment with a 4-nt 3′ tail and 3-nt 5′ tail. Product separation in a 3.5% agarose gel confirmed the identity of the linear dsDNA substrate with a 30-nt 5′ tail and allowed quantitation of yield. In all DNA preparations used in these trials, the final yield of complete substrate DNA was greater than 97%. Reaction conditions All reactions were carried out at 37 °C in 25 mM buffer (detailed below), 10 mM magnesium acetate, 5% (v/v) glycerol, 1 mM dithiothreitol, 3 mM potassium glutamate, 3 mM ATP, an ATP regenerating system (10 units/ml pyruvate kinase and 3 mM or 2 mM PEP), and concentrations of DNA and RecA protein as described below and in figure legends. The coupled spectrophotometric assay also contained 10 units/ml lactate dehydrogenase and 3 mM NADH. Specific buffers used are described below and in the figure legends. DNA and protein concentrations are indicated for each experiment. Reactions were incubated for 10 min before ATP was added to start the reaction. ATP hydrolysis assays A coupled spectrophotometric assay was used to measure DNA-dependent ATP hydrolysis by the RecA protein [ 29 , 93 ]. The regeneration of ATP from ADP and PEP was coupled to the oxidation of NADH and monitored by the decrease in absorbance of NADH at 380 nm. The 380-nm wavelength was used instead of the absorption maximum at 340 nm so that the signal would remain within the linear range of the spectrophotometer for the duration of the experiment. The assay was carried out using a Varian Cary 300 (Varian, Palo Alto, California, United States) dual beam spectrophotometer equipped with a temperature controller and 12-position cell changer. The cell path length and band pass were 0.5 cm and 2 nm, respectively. The NADH extinction coefficient at 380 nm of 1.21 mM −1 cm −1 was used to calculate rates of ATP hydrolysis. Filament disassembly reactions ATP hydrolysis reactions were started as described above in 25 mM MES/NaOH (76% anion, pH 6.62) buffer. Reactions contained 12 μM RecA protein, 12 μM (total nucleotides) linear duplex DNA, and the ATP and ATP regeneration conditions indicated above. These were incubated for approximately 20 min to reach a stable steady-state rate of ATP hydrolysis. The rate was determined and reflected a virtually complete binding of all available DNA by RecA protein. Under these conditions, we routinely achieved rates reflecting an apparent k cat for bound RecA protein (one monomer per three available DNA base pairs) of 18–24 min −1 . The few reactions displaying initial rates reflecting a k cat less than 18 min −1 generally reflected a problem with one or another reagent, and were discarded. After preincubation to achieve a DNA substrate saturated with RecA protein, the solution was subjected to a pH shift. The 200 μl reaction was diluted with gentle mixing into 200 μl of a solution (also preincubated at 37 °C), containing 25 mM Tris-acetate (30% cation, pH 8.50) buffer, 10 mM magnesium acetate, 5% (v/v) glycerol, 1 mM dithiothreitol, 3 mM potassium glutamate, 3 mM ATP, an ATP regenerating system (10 units/ml pyruvate kinase and 3 mM or 2 mM PEP), and 0.3 μM SSB. The final pH of the reaction after the pH shift was 8.00. The RecA and DNA concentrations were halved as a result of the pH shift, but the concentrations of ATP, Mg 2+ , and ATP regeneration system components were kept constant. Following the pH shift, the production of ADP was monitored spectrophotometrically as the RecA filaments disassembled. The rate of ATP hydrolysis declined, eventually settling to a slow steady-state rate of ATP hydrolysis that reflects the minimal amount of bound RecA protein for a given experiment (see Results). Supporting Information Video S1 Coordinated Waves of ATP Hydrolysis—The Movie This movie illustrates the model of Figure 10 . The red RecA monomers are the ones hydrolyzing ATP at any given moment. The transitions from one set of monomers to the next occur every 0.5 s. In this animation, the 5′-proximal end of the initiating DNA strand (the strand that orders the orientation of the filament; see text) is at the upper left. The filament structure is based on the RecA structure of Story and Steitz [ 72 ], as cited in the text. (PDF not available). (148 KB MOV). Click here for additional data file.

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548136

Red maca (Lepidium meyenii) reduced prostate size in rats

Background Epidemiological studies have found that consumption of cruciferous vegetables is associated with a reduced risk of prostate cancer. This effect seems to be due to aromatic glucosinolate content. Glucosinolates are known for have both antiproliferative and proapoptotic actions. Maca is a cruciferous cultivated in the highlands of Peru. The absolute content of glucosinolates in Maca hypocotyls is relatively higher than that reported in other cruciferous crops. Therefore, Maca may have proapoptotic and anti-proliferative effects in the prostate. Methods Male rats treated with or without aqueous extracts of three ecotypes of Maca (Yellow, Black and Red) were analyzed to determine the effect on ventral prostate weight, epithelial height and duct luminal area. Effects on serum testosterone (T) and estradiol (E2) levels were also assessed. Besides, the effect of Red Maca on prostate was analyzed in rats treated with testosterone enanthate (TE). Results Red Maca but neither Yellow nor Black Maca reduced significantly ventral prostate size in rats. Serum T or E2 levels were not affected by any of the ecotypes of Maca assessed. Red Maca also prevented the prostate weight increase induced by TE treatment. Red Maca administered for 42 days reduced ventral prostatic epithelial height. TE increased ventral prostatic epithelial height and duct luminal area. These increases by TE were reduced after treatment with Red Maca for 42 days. Histology pictures in rats treated with Red Maca plus TE were similar to controls. Phytochemical screening showed that aqueous extract of Red Maca has alkaloids, steroids, tannins, saponins, and cardiotonic glycosides. The IR spectra of the three ecotypes of Maca in 3800-650 cm (-1) region had 7 peaks representing 7 functional chemical groups. Highest peak values were observed for Red Maca, intermediate values for Yellow Maca and low values for Black Maca. These functional groups correspond among others to benzyl glucosinolate. Conclusions Red Maca, a cruciferous plant from the highland of Peru, reduced ventral prostate size in normal and TE treated rats.

Background Lepidium meyenii , a traditional Peruvian cruciferous vegetable known as Maca, grows exclusively at altitudes over 4000 m. The hypocotyl, the edible part of the plant, is used as a nutritional supplement and for its enhancing sperm production properties [ 1 ]. Maca is presented in different ecotypes according to the colors of its hypocotyls, ranging from white to black [ 2 ]. Epidemiological studies have found that consumption of cruciferous vegetables is associated with a reduced risk of prostate cancer [ 3 - 5 ]. Cruciferous (Brassica) vegetables are broccoli, cabbage, mustard and collard greens, bok choy [ 3 ], and members of the genus Lepidium [ 1 , 6 ], including Maca. In the many hundreds of cruciferous species investigated, all are able to synthesize glucosinolates [ 7 ]. Glucosinolate content in cruciferous vegetables is highly variable, depending of plant age and environmental factors which can cause the broad range of values reported to vegetables of the same variety [ 8 ]. This variability may explain differences in epidemiological studies related to protection of intake of cruciferous vegetables against prostate cancer [ 3 - 5 , 9 - 11 ]. Upon ingestion by humans [ 12 ] or rats [ 13 ], glucosinolates are converted in isothiocyanates by gut microflora. As alternate mechanism, glucosinolates are catalyzed by dietary myrosinase [ 13 ]. Almost all of the mammalian chemoprotective activity from cruciferous is due to these isothiocyanates [ 7 , 14 ]. Therefore, glucosinolates after conversion to isothiocyanates have both antiproliferative and proapoptotic properties in prostate cells [ 14 - 18 ]. The isothiocyanates formed from aromatic glucosinolates decompose spontaneously to indole-3-carbinol (I3C) [ 7 ]. I3C and metabolites induce apoptosis in human prostate cancer cells [ 16 - 18 ]. The absolute content of glucosinolates in fresh Maca hypocotyls is relatively higher than reported in other cruciferous crops [ 19 ]. The most abundant glucosinolates detected in Maca were the aromatic glucosinolates: benzyl glucosinolate (glucotropaeolin) [ 19 - 21 ]; as a result, it is possible that Lepidium meyenii (Maca) may have important effects on prostate. More recently, it has been demonstrated that an integral suspension of Lepidium latifolium significantly reduced prostate size and volume in castrated rats where the hyperplasia was induced by steroid treatment [ 6 ]. For such reason, the present study has been designed to determine the effect of three ecotypes of Maca on ventral prostate of rats. Methods Animals Adult Holtzman rats were obtained from our Animal House at the Universidad Peruana Cayetano Heredia and used for the present study. The rats were maintained 4–6 per cage at environmental temperature (22°C) with a 12:12 h light/dark cycle. Also they were fed with Purina laboratory chow and tap water ad libitum . All animal experiments were conducted in compliance with "Guide for the care and use of laboratory animals" of the National Institutes of Health from the USA [ 22 ]. The Institutional Review Board of the Scientific Research Office from the Universidad Peruana Cayetano Heredia approved the study. Experimental protocol Experiment 1: Effect of different ecotypes of Maca on prostate size in rats Rats were treated with vehicle, Yellow Maca, Red Maca or Black Maca for 7 days in dose of 2 g dried Maca hypocotyls/Kg BW. This dose was selected from a previous dose response study [ 23 ]. Each Maca treated group included 12 animals, and Control (vehicle) sample size included 35 animals. Maca or vehicle was orally administered using an intubation needle No 18 (Fisher Scientific, Pittsburgh, Pennsylvania). Experiment 2: Effect of Red Maca on prostate size and histology in rats treated with testosterone enanthate (TE) Rats were injected (i.m) with 0.1 ml (25 mg) of testosterone enanthate (TE) on day 1 and day 7. Control rats received 0.1 ml oil (im) at day 1 and at day 7. A group treated with TE received also Red Maca (2 g/Kg) for 14 days and another group treated with TE received Red Maca for 42 days. Control rats received vehicle by oral route for 14 or 42 days. Oral treatment (Maca or vehicle) and intramuscular treatment (TE or vehicle) both started on day 1. Preparation of aqueous extract of Lepidium meyenii (Maca) The dried hypocotyls of Lepidium meyenii were obtained from Carhuamayo, Junin at 4000 m altitude. The ages of different Maca plants were similar. All hypocotyls were obtained at the same time. Irma Fernandez, a Botanist of the Department of Pharmaceutical Sciences at Universidad Peruana Cayetano Heredia, authenticated the identity of the plant by visual inspection. The biological activity of the plant is located in the hypocotyls, which are consumed by natives after natural drying. Traditionally, the dried hypocotyls of Maca are boiled and served as juice. For the present study, the aqueous extract of the hypocotyls was prepared according to the traditional method. First, 500 g of the dried hypocotyls were pulverized and placed in a container with 1500 ml of water, and boiled for 120 minutes. Next, the preparation was left standing to cool, and then it was filtered. Finally, the filtrate containing 333 mg of dry Maca hypocotyls in 1 ml was placed in small vials and kept in 4°C refrigerator. Sacrifice, Blood and sample of tissue One day after the last treatment, rats were sacrificed by decapitation. Blood sample was obtained from cervical trunk from rats treated for 7 days with different ecotypes of Maca. Blood samples were centrifuged at 1,000 g, and sera were separated, placed in vials and kept frozen until assayed for sex hormone levels. Ventral prostate was used for histological study. Organ Weights After animals were sacrificed several organs (testes, epididymis, ventral prostate, seminal vesicles, kidneys, liver, spleen, heart and lungs) were collected, dissected free of fat, and weighed. Measurement of serum estradiol and testosterone Serum estradiol and testosterone concentrations were measured by radioimmunoassay using commercial kits (Diagnostic Products Co, Los Angeles, USA). The hormone labeled with iodine-125 was used as radioactive marker. Samples were run in the same assay to avoid inter-assay variation. The intra-assay variation was 6.42% for estradiol, and 5.5% for testosterone. Sensitivity of testosterone assay was 4 ng/dl and for estradiol assay was 8 pg/ml. Histological study Ventral prostate lobes obtained from experiment 2 were excised and dissected free of fat. Ventral prostates (VP) were immersion-fixed in Bouin's fixative. After their dehydration, VP were embedded in paraffin. The tissue blocks were sectioned into 5 um thickness and stained with hematoxylin and eosine (H&E), and then observed under a light microscope. Epithelial height (um) and duct lumen area (um 2 ) were measured by sampling 10 random sections per slide in the peripheral region of the ventral prostate. In each duct, 20 cells were measured for epithelial height. All assessments were performed using an axiostar plus microscope (Carl Zeizz, Thornwood, New York, USA). The images were captured by a Moticam2000 (Richmond, B.C, Canada) coupled to a personal computer. Motic image plus 2.0 software (Motic Instruments Inc.) was used for measurements of prostatic epithelial height and duct luminal area and calculated by statistic ANOVA test. Pictures at 50× and 400× magnifications are included. Phytochemistry of Red Maca The phytochemical screening in the aqueous extract of Red Maca was performed using standard phytochemical procedures [ 24 , 25 ]. Maca aqueous extract was lyophilized previously to extraction procedures. After extraction in methanol or ethanol, the presence of alkaloids (Dragendorff reagent; Mayer's test), flavonoids (Shinoda test), steroids (Liebermann-Burchard/Thin Layer Chromatography test), anthraquinones (Bornträger reaction), tannins (Gelatin/Ferric chloride test), saponins (Froth test), sesquiterpene lactones (Vainillin test and Ferric hydroxamate test), coumarins (Vainillin test and Ferric hydroxamate test), cardiotonic glycosides (Raymond reagent), and cardenolids (Kedde reagent) were assessed [ 24 , 25 ]. Measurement of infrared (IR) spectra IR spectra of lyophilized aqueous extracts of Red, Yellow and Black Maca were measured from 3800 cm -1 to 650 cm -1 with an FT-IR spectrophotometer (SPECTRUM2000, Perkin Elmer Ltd., Beaconsfield, England). An overhead-attenuated total refraction (ATR) accessory was equipped as the sample stage for solid samples. All spectral measurements were done at 1 cm -1 resolutions. Data are presented as absorbance units. Each peak represents the presence of a functional chemical group. Differences in the height of absorbance peaks reflect differences in amount of functional groups. Statistical analysis Data were analyzed using the statistical package STATA (version 8.0) for personal computer (Stata Corporation, 702 University Drive East, College Station, TX, USA). Data are presented as mean ± standard error of the mean (SEM). Homogeneity of variances was assessed by the Bartlett test. If variances were homogeneous, differences between groups were assessed by analysis of variance (ANOVA). If F value in the ANOVA test was significant, the differences between pair of means were assessed by the Scheffeé test. If variances were non homogeneous, non parametric tests were used. A value of P < 0.05 was considered statistically significant. Results Red Maca but not Black or Yellow Maca reduced ventral prostate weight in rats Ventral prostate weight was significantly reduced in rats treated for 7 days with Red Maca (P < 0.05). Black Maca and Yellow Maca did not modify ventral prostate weight (Figure 1a ). Seminal vesicles weights were not modified by treatment with any ecotype of Maca (Figure 1b ). Body weight was similar in the control group (415.8 ± 3.3 g, mean ± SEM) and in rats treated with Red (407.5 ± 7.1 g), Yellow (421.5 ± 6.1 g) or Black Maca (426.5 ± 6.8 g). Figure 1 Ventral prostate (A) and seminal vesicles (B) weights in adult rats treated for 7 days with different ecotypes of Maca (2 g/kg BW). Data are Mean ± SEM *P < 0.05 with respect to control value. Number of animals was 35 for controls, 12 for Yellow Maca, 12 for Red Maca and 12 for Black Maca. None: control group receiving vehicle. Maca and serum sexual hormone levels Means of serum testosterone and estradiol levels were similar between control group and groups treated for 7 days (Figure 2a,b ) with Red, Yellow or Black Maca. The group treated with Yellow Maca showed higher serum testosterone levels than the group treated with Black Maca (P < 0.05). Higher serum testosterone levels in the group treated with Yellow Maca were due to two rats with high serum testosterone levels. Figure 2 Effects of different Maca ecotypes administered for 7 days on serum testosterone (A) or estradiol (B) levels in rats. Data are mean ± SEM. Maca (2 gr/Kg BW) was administered for 7 days. Number of rats was 10 in the control group, 6 in the Red Maca treated group, 6 in the Yellow Maca, and 6 in the Black Maca treated group. P:NS between groups treated with Maca and control rats. a P < 0.05 with respect to the Yellow Maca treated group. Red Maca reduced ventral prostate weight in rats treated with testosterone enanthate (TE) Treatment with TE increased significantly ventral prostate weight almost to double value of the control group (P < 0.05) (Figures 3a and 4a ). The increase in ventral prostate weight was maintained in high levels up to 5 weeks after last TE injection. Seminal vesicles weight increased 2.5 times that control values (P < 0.05) (Figures 3b and 4b ). Treatment with only Red Maca for 14 days (P < 0.05) (Figure 3a ) or 42 days (P < 0.05) (Figure 4a ) resulted in low ventral prostate weight compared with control values. Seminal vesicles values were not affected after treatment with Red Maca for 14 or 42 days (Figures 3b and 4b ). Figure 3 Ventral prostate (A) and seminal vesicles (B) weights in adult rats treated for 14 days with Red Maca. Data are mean ± SEM.TE: rats treated on day 1 and 7 with testosterone enanthate (25 mg each) i.m, Red Maca (2 g/Kg BW) was given orally during 14 days. Rats were sacrificed on day 15. * P < 0.05 with respect to vehicle group; a P < 0.05 with respect to TE group. b P < 0.05 with respect to the group treated with TE+Red Maca. Number of rats was 13 for the control group, 6 for the Red Maca, 6 for TE, and 6 for the TE plus Red Maca groups. Figure 4 Ventral prostate (A) and seminal vesicles (B) weights in adult rats treated for 42 days with Red Maca. Data are mean ± SEM.TE: rats treated on day 1 and 7 with testosterone enanthate (25 mg each) i.m. Red Maca (2 g/Kg BW) was given orally during 42 days. Rats were sacrificed on day 43. *P < 0.05 with respect to vehicle group; a P < 0.05 with respect to TE group. b P < 0.05 with respect to the group treated with TE+Red Maca. Number of animals was 12 in the control group, 7 in the Red Maca group, 5 in the TE group and 5 in the TE plus Red Maca group. Red Maca administered for 14 days also reduced ventral prostate weight in rats treated with TE (P < 0.05). The effect was more noticeable after 42 days of treatment with Red Maca (P < 0.05). After 42 days of treatment with Red Maca, the ventral prostate weight was reduced more than 50% (Figure 4a ). After 14 or 42 days of treatment with Red Maca, the increased seminal vesicles weights induced by TE was not affected (Figures 3b and 4b ). Ventral prostate weight related to body weight was lower in the group treated for 14 days with Red Maca (0.11 ± 0.01 g/100 g BW) than in controls (0.15 ± 0.006 g/100 g BW) (P < 0.05). Rats treated with TE plus Red Maca had lower prostate weight related to BW (0.23 ± 0.02 g/100 g BW, P < 0.05) than rats treated with TE (0.29 ± 0.01) but prostate weight relative to BW was still higher in rats treated with TE plus Red Maca than in controls (P < 0.05). The same pattern was observed when rats were treated for 42 days with Red Maca (Data not shown). Rats treated with two TE injections showed lower body weight at day 42 after the first injection (P < 0.05) compared to controls (290.63 ± 30.48 g and 383.60 ± 11.31 g in TE and vehicle treated groups). This low body weight was also observed in the group treated with TE plus Red Maca (319.30 ± 3.08 g) (P < 0.05). Weights of testes, epididymis, kidneys, liver, spleen, lungs and heart were not affected by treatment with Red Maca for 7, 14 or 42 days (Data not shown). Histological study Sections of ventral prostate in the peripheral region of the ductal system after 14 and 42 days of treatment with vehicle (control), Red Maca, ET, or ET plus Red Maca are shown in Figures 5 and 6 . Figure 5 The effects of Red Maca administered to rats for 14 days on ventral prostatic epithelial height and duct luminal area. A,B : Control group; C,D : Red Maca treated; E,F : TE treated; G,H : TE+Red Maca treated. HE stain. Left: ×50 magnification; Right: ×400 magnification. Figure 6 The effects of Red Maca administered to rats for 42 days on ventral prostatic epithelial height and duct luminal area. A,B : Control group; C,D : Red Maca treated; E,F : TE treated; G,H : TE+Red Maca treated. HE stain. Left: ×50 magnification; Right: ×400 magnification. At 50× magnification, the number of ducts per field from rats treated with Red Maca for 14 days was slightly higher than in controls (Figures 5a and 5c ). TE reduced the number of ducts per field as a consequence of increase in duct area (Figure 5e ). Red Maca increased the number of ducts per field in rats treated with TE (Figure 5g ). At 400× magnification, in Red Maca treated rats (alone or with TE), cell size was decreased and membrane blebbing and nuclear distortion are apparent (Figures 5d and 5h vs Figures 5b and 5F ). At 50× magnification, compared to control (Figure 6a ), the treatment with Red Maca for 42 days resulted in high number of ducts per field by Maca effect reducing the lumen area (Figure 6c ). Treatment with TE resulted in lower number of ducts per field as a result of testosterone induced high luminal area (Figure 6e ). Treatment with TE plus Red Maca (Figure 6g ) compared to TE (Figure 6e ) showed an increase in the number of ducts per field. At higher magnification (400×), it was observed secretory luminal cells lined with a single layer of columnar epithelium in the control group (Figure 6b ). In specimens treated with only Red Maca, the epithelium of the ventral prostate showed a change from columnar to cuboidal shape (Figure 6d ). TE caused an increase in proliferation of epithelial cells (Figure 6f ). Red Maca reduced the epithelium in rats treated with TE (Figure 6h ). Membrane blebbing and nuclear distortion are apparent in rats treated with Red Maca (Figures 6d and 6h ). Quantitative analyses of epithelial height and luminal area in rats treated for 42 days are presented in Figure 7 . Rats treated for 42 days with only Red Maca showed lower prostatic epithelial height (P < 0.05) and duct luminal area (P < 0.05) than control, TE and TE+Red Maca groups (Figure 7a–b ). Figure 7 Ventral prostatic epithelial height (A) and luminal area (B) in control rats, rats treated with Red Maca (RM) alone, testosterone enanthate (TE) alone or TE+Red Maca. Rats were treated for 42 days. *P < 0.05 with respect to control, a P < 0.05 respect to TE group; b P < 0.05 respect to TE+ Red Maca. Differences in duct luminal areas were assessed with Mann-Whitney U test. Rats treated during 2 weeks with injections of TE once a week showed higher prostatic epithelial height (P < 0.05) and duct luminal area (P < 0.05) at day 42 compared to controls (Figure 7a–b ). Rats treated with TE plus Red Maca for 42 days showed that prostatic epithelial height and luminal area were similar to those observed in the control group (Figures 7a–b ). Phytochemistry of Red Maca The phytochemical analysis of the ethanolic extract prepared from lyophilized aqueous extract of Red Maca hypocotyls revealed the presence of alkaloids, steroids, saponins and cardiotonic glycosides, and the absence of flavonoids, anthraquinones, tannins, sesquiterpene lactones and coumarins (Table 1 ). Table 1 Result of phytochemical screening of extracts of Red Maca. Tests Ethanolic extract Methanolic extract Alkaloids Dragendorff test + + Mayer's test + + Flavonoids Shinoda test - - Steroids Liebermann-Burchard test + + Anthraquinones Bornträger test - - Tannins Gelatin/Ferric Chloride test - + Saponins Froth test + + Sesquiterpene Lactones Ferric hydroxamate test - - Vainillin test - - Coumarins Ferric hydroxamate test - - Vainillin test - - Cardiotonic glycosides Raymond test + NA Cardenolids Kedde test NA - -, test negative; +, test positive; NA, not available The phytochemical analysis of the methanolic extract prepared from lyophilized aqueous extract of Red Maca hypocotyls revealed the presence of alkaloids, steroids, tannins and saponins, and the absence of flavonoids, coumarins, anthraquinones, sesquiterpene lactones and cardenolides (Table 1 ). The positive tests were more intense for alkaloids than for the other compounds. The IR spectra of the three Maca's ecotypes extracts are shown in Fig. 8 . The IR spectra of the three ecotypes of Maca in 3800-650 cm -1 region had 7 peaks, which were at 3291 cm -1 , 2927 cm -1 , 1614 cm -1 , 1406 cm -1 , 1022 cm -1 , 924 cm -1 and 862 cm -1 . These peaks are due to C-H, OH, amides, amines, carboxylic acids, aromatic, and alkyls groups, respectively. Highest peak values were observed for Red Maca, intermediate values for Yellow Maca and low values for Black Maca. These functional groups correspond among others to benzyl glucosinolate (Figure 9 ). Figure 8 Infrared (IR) spectra of lyophilized aqueous extract of three ecotypes of Lepidium meyenii (Maca). Data are expressed in absorbance units (A). Wave number is expressed in cm -1 . IR spectra were measured from 4000 cm -1 to 650 cm -1 with a FT-IR spectrophotometer equipped with an ATR apparatus. Highest absorbance values correspond to Red Maca, intermediate values to Yellow Maca and lowest values to Black Maca. Peaks of absorbance are recorded at 3291 cm -1 , 2927 cm -1 , 1614 cm -1 , 1406 cm -1 , 1022 cm -1 , 924 cm -1 and 862 cm -1 . Figure 9 Structure of Glucotropaeolin (Benzyl glucosinolate) Discussion The present study was designed to determine if different ecotypes of Lepidium meyenii (Maca), a cruciferous plant that grows exclusively over 4000 m in Peruvian Andes, affect ventral prostate size. It was of great interest to demonstrate that Red Maca reduced significantly ventral prostate weight. This effect was not observed after treatment with Yellow or Black Maca. The effect of Red Maca was specific for prostate, since other organs as testes, epididymis, seminal vesicles, kidneys, spleen, liver, lungs and heart were not affected. It was also demonstrated an effect of Red Maca on rats in which ventral prostate size was enlarged by two injections of testosterone enanthate. In fact, Red Maca administered for 14 or 42 days reduced the effect of TE. At 42 days, the ventral prostate size of rats treated with TE plus Red Maca was similar to that of control rats treated only with vehicle. Epithelial height and luminal areas were proved to be sensitive parameters for the evaluation of androgen effects on prostates [ 26 ]. The present study shows that prostatic epithelial height increased after treatment with TE. The same effect has been observed when castrated rats were treated with testosterone [ 26 ] suggesting that prostatic epithelial height is androgen dependent. Red Maca was able to reduce the prostatic epithelial height of TE treated rats. This would means that Red Maca interferes the androgen action. Growth of the prostate is a hormone-mediated phenomenon regulated by both androgens and estrogens [ 27 ]. However, data showed that Red Maca affect ventral prostate size without affecting serum testosterone or estradiol levels. This is not surprising because previously, it has been published that dietary phytoestrogens may affect prostate size without modify circulating testosterone or estrogen level [ 28 ], but affecting the androgen action in the rat prostate [ 27 ]. Our data on effect of Red Maca on ventral prostate size in rats previously treated with testosterone enanthate suggest that this cruciferous is acting by interfering the androgen action. Maca is characterized by its higher content on aromatic glucosinolates [ 19 - 21 ]. Recently, it has been described a metabolite of the aromatic glucosinolates that specifically antagonizes androgen receptor [ 18 ]; therefore, it is possible that effect of Red Maca on ventral prostate size may be due in part to an action of glucosinolate metabolites on androgen receptor. However, further studies will be required to clarify mechanism of action of this cruciferous plant. Recently, increasing evidence has been presented suggesting that cruciferous (Brassicas) vegetables may reduce the risk of prostate cancer development [ 3 , 4 ]. The genus Lepidium could be an important alternative for treatment of prostate diseases. Other Brassica from the genus Lepidium , as Lepidium latifolium reduced prostate weight [ 6 ] suggesting that cruciferous from the genus Lepidium may have important anti-proliferative and proapoptotic effects. In Red Maca treated rats, cell size has decreased and membrane blebbing and nuclear distortion are apparent suggesting a pro-apoptotic effect. It is still unknown the active principle for the effect of Red Maca on ventral prostate and why the action is specific since any other organ was affected. Moreover, the different effects among ecotypes seem to be due to different amount of active metabolites. This study used aqueous extract of dried hypocotyls of Lepidium meyenii . In the aqueous extract is possible to find glucosinolates [ 7 ] and anthocyanines [ 29 ]. Both compounds have antiproliferative and proapoptotic properties in prostate cancer cells [ 14 - 18 , 30 ]. As effect was specific for Red Maca and not for Yellow or Black Maca, it is probably that Red Maca has more glucosinolate content than other ecotypes. Results from the infrared (IR) spectroscopy showed that peaks of absorbance were higher for Red Maca, intermediate for Yellow Maca and lower for Black Maca. Each peak reflects specific chemical functional groups. Several functional groups found in the different Maca ecotypes correspond among others to benzyl glucosinolate. In such sense, it is suggested that benzyl glucosinolate content is higher in Red Maca, intermediate in Yellow Maca and lower in Black Maca. In addition to the potential glucosinolates effects on prostate, it is possible that other active metabolites may be acting on prostate. Maca aqueous extracts were further extracted with ethanol or methanol and assessed for different compounds. The compounds found are potential candidates to affect prostate; however, it is difficult at this time to ascertain which specific compound has the prostate effect. In fact, the phyto-chemical screening data showed that aqueous extract of Red Maca has alkaloids, steroids, tannins, saponins and cardiotonic glycosides, all of them may have effects on prostate. Phytochemical study showed that Red Maca was more positive for alkaloids than from other compounds. The alkaloid, (1R,3S)-1-methyltetrahydro-β-carboline-3-carboxylic acid has been reported as a constituent of Maca [ 20 ]. This alkaloid acts as antioxidants and free radical scavengers [ 31 ]. Beta carbolines are also proapoptotic compounds [ 32 ] and they have antitumor activities [ 33 ]. Further studies will be required to determine the impact of tetrahydro-beta-carbolines from Maca on prostate. Conclusions Indeed, the data presented here show that Red Maca reduced ventral prostate size in normal adult rats and also in rats treated with testosterone enanthate. Hence, it is proposed that Red Maca may have important implications under pathological conditions of the prostate. Authors' contributions GFG conceived of the study participating in its design, coordination, and drafting the manuscript. SM participated in the design of the study and the study of different ecotypes of Maca. JN participated in the biological study with different ecotypes of Maca. GF participated in the phytochemical screening JR participated in the statistical analysis SY participated in the histological study PY participated in the histological study MG participated in the design and analysis of results, and its interpretation. All authors read and approved the final manuscript.

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539056

A New Vision for Clinical Trials in Africa

A new funding body (the EDCTP) will fund clinical trials in developing countries, particularly in Africa, that help to develop affordable interventions against HIV, TB, and malaria. How is it doing so far?

Last year the European Parliament and Council formed the european and Developing Countries Clinical Trials Partnership (EDCTP). The aim of this new funding body, which has a budget of &euro;400 million spread over five years, is a noble one: to fund research in developing countries, particularly in Africa, that contributes to the development of affordable prophylactics and drugs for HIV/AIDS, tuberculosis, and malaria. Unfortunately, the organization has not got off to an auspicious start. Its executive director, Piero Olliaro, was ousted from power at the first EDCTP annual forum at the end of September. There have been rumblings of discontent among grant applicants who say that the first round of grant assessments was administered poorly. And not-for-profit organizations that would like to partner with EDCTP have been left in the dark regarding whom to speak to at the organization. This omission is significant because partnership is one of the key tenets of the EDCTP. European research agencies are slowly beginning to realize that they need to cooperate with each other if they are to be competitive with the United States. The history of many European countries is such that Europe has much stronger ties with Africa than does the United States, so it makes political sense for the European Union to fund research that provides a springboard for European researchers to compete effectively with US scientists. Crucially, the EDCTP was also set up to enable European and African scientists to work together as equal partners. There is increasing recognition that the paternalistic, colonial attitude that pervaded “tropical medicine” in the past just will not do. The EDCTP hoped to change that by having a Partnership Board that contains equal numbers of African and European representatives. However, the EDCTP Assembly, which contains a representative from each of 14 EU member states but none from African countries, has the power to veto the decisions of the Partnership Board, which is supposedly the scientific decision-making authority. Doing clinical trials in Africa is far from easy. There are too few adequately resourced research centers, and those that do consistently perform well are oversubscribed. Therefore, there is a clear need for "capacity building"—development of a research infrastructure, in terms of both equipment and personnel, that is capable of coping with the challenges of clinical trials. The EDCTP hopes to contribute to this essential endeavor by funding clinical trials that are sustainable in the long term. In particular, it believes that the best way to train a new generation of African scientists is by teaching them on the job, that is, involving them fully in the planning and execution of the trial, rather than flying in European experts who leave as soon as the trial is finished. A commitment from European researchers to be engaged for the long term is essential for the success of these projects. In addition, partnerships need to be brokered with national programs in Africa to ensure that the new capacity can be sustained over time. The end goal is to produce centers of excellence that are run by Africans doing internationally recognized research that conforms to Good Clinical Practice guidelines. But this will only happen if African researchers are treated as equal partners and are allowed to be fully engaged in the projects that are taking place in their countries. So can the EDCTP work, or is it doomed to failure? In many ways the organization has a great deal going for it. Although the budget of 3400 million spread over five years is tiny considering the combined burden of HIV/AIDS, tuberculosis, and malaria, it is important to remember that it is the biggest single European project for clinical trials in Africa. In many ways the EDCTP is a demonstration project: if some success can be achieved it is very likely that additional funds will follow. The project is certainly strengthened by the involvement of Pascoal Mocumbi, the former prime minister of Mozambique, as High Representative of the project. Mocumbi is highly respected by the global-health community and carries considerable weight with African politicians. Mobilization of political will within Africa will be essential if research capacity is to be sustained for the long term. On the downside, it seems clear to most insiders that the management structure needs to be radically changed and partnership with other organizations needs to be improved. The EDCTP Assembly met on October 28 and 29 to discuss these issues and to elect a new leader. At the time this editorial went to press, there was still no public announcement of the outcome of this meeting. In addition, the political infighting that pervades European politics at all levels needs to be controlled, or at least managed effectively. This might be a tall order, but it is essential if this worthwhile and high-profile project is to succeed.

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548687

Herpesvirus pan encodes a functional homologue of BHRF1, the Epstein-Barr virus v-Bcl-2

Background Epstein-Barr virus (EBV) latently infects about 90% of the human population and is associated with benign and malignant diseases of lymphoid and epithelial origin. BHRF1, an early lytic cycle antigen, is an apoptosis suppressing member of the Bcl-2 family. In vitro studies imply that BHRF1 is dispensable for both virus replication and transformation. However, the fact that BHRF1 is highly conserved not only in all EBV isolates studied to date but also in the analogous viruses Herpesvirus papio and Herpesvirus pan that infect baboons and chimpanzees respectively, suggests BHRF1 may play an important role in vivo . Results Herpesvirus papio BHRF1 has been shown to function in an analogous manner to EBV BHRF1 in response to DNA damaging agents in human keratinocytes. In this study we show that the heterologous expression of the previously uncharacterised Herpesvirus pan BHRF1 in the human Burkitt's lymphoma cell line Ramos-BL provides similar anti-apoptotic functions to that of EBV BHRF1 in response to apoptosis triggered by serum withdrawal, etoposide treatment and ultraviolet (UV) radiation. We also map the amino acid changes onto the recently solved structure of the EBV BHRF1 and reveal that these changes are unlikely to alter the 3D structure of the protein. Conclusions These findings show that the functional conservation of BHRF1 extends to a lymphoid background, suggesting that the primate virus proteins interact with cellular proteins that are themselves highly conserved across the higher primates. Further weight is added to this suggestion when we show that the difference in amino acid sequences map to regions on the 3D structure of EBV BHRF1 that are unlikely to change the conformation of the protein.

Background Apoptosis is a genetically programmed form of cell death employed to regulate cell number, spatial organisation and remove infected and damaged cell populations that may compromise the integrity of the organism [ 1 ]. Aberrant or unscheduled apoptotic responses are thought to contribute to various diseases including Alzheimer's disease, rheumatic diseases and neoplastic growth [ 2 ]. Induction of apoptosis in virally infected cells is a key weapon in the immune system's arsenal against viral attack. Many viruses have evolved multiple strategies to counteract host-mediated apoptosis in order to facilitate infection, replication or persistence [ 3 , 4 ]. Epstein-Barr virus (EBV) a human γ-herpesvirus that latently infects the majority of adults, was the first virus shown to influence the survival of infected cells [ 5 ]. In vivo , EBV is associated with a number of benign and malignant proliferative diseases, such as infectious mononucleosis, Burkitt's lymphoma and nasopharyngeal carcinoma [ 6 , 7 ]. Latent infection of B cells in vitro leads to outgrowth of apoptosis resistant lymphoblastoid cell lines (LCLs), which phenotypically resemble activated B-cells. Although B cells can produce progeny virus, epithelial cells are also known to be permissive for viral replication. Studies have shown that EBV has at least two mechanisms of suppressing apoptosis. During latent infection latent membrane protein 1 (LMP1) is the key mediator of protection. LMP1, a CD40 mimic, up-regulates cellular Bcl-2 [ 8 ] and A20 [ 9 ] via the NFκB pathway. The virus also encodes two structural homologues of Bcl-2: BHRF1 [ 10 , 11 ] and the less well characterised and more controversial BALF1 [ 12 , 13 ] which are thought to play their major roles during lytic infection. Whilst many other viruses also have Bcl-2 homologues (v-Bcl-2s) [ 14 ], EBV and its mammalian analogues appear unique in having two v-Bcl-2s. Despite being considered dispensable for EBV replication or cellular transformation in vitro [ 15 , 16 ], BHRF1 is extremely highly conserved in distinct geographical isolates of EBV [ 17 ], and its role in vivo remains unclear. BHRF1 is thought to act in lytic cycle to delay apoptosis during replication in terminally differentiating epithelium [ 18 ]. However, some EBV-positive B-cell lymphomas have been found to be positive for BHRF1 transcripts [ 19 ] and latent BHRF1 transcripts have been detected in T-cell lymphomas [ 20 ] and in EBV-transformed tightly latent B-cell lines in vitro [ 21 ]. Additionally, EBV BHRF1 has been shown to suppress apoptosis in lymphoid cells in response to a range of triggers including serum deprivation [ 11 ], DNA damaging agents and chemotherapeutic drugs [ 22 ] and cytokines [ 23 ]. It is possible then, that BHRF1 may play a role at some stage during latent infection, which warrants the study of this protein in B cells, the target for latent infection. Analogues of EBV are found in the higher primate species. Herpesvirus papio ( H. papio ) and Herpesvirus pan ( H. pan ) infect baboons and chimpanzees respectively. H. papio encodes a BHRF1 homologue that shares 65% amino acid identity (81% similarity) with EBV BHRF1, whilst the H. pan BHRF1 is even more similar at 82% identity and 90% similarity [ 24 ]. H. papio BHRF1 has been shown to confer resistance to cisplatin induced apoptosis in human keratinocytes akin to EBV BHRF1 [ 25 ], but this study represents the first functional analysis of a primate virus BHRF1 in a lymphoid cell background. Here we show that H. pan BHRF1 exhibits similar anti-apoptotic activity to that of EBV BHRF1 in the human Burkitt's lymphoma cell line Ramos-BL in response to apoptosis induced by either serum withdrawal, etoposide treatment and the previously untested trigger, ultraviolet radiation. These results show that H. pan BHRF1 is biologically active in human B-lymphocytes in vitro suggesting a conserved role for BHRF1 during in vivo infection of B-lymphocytes. Results Construction of BHRF1 expression vectors and selection of positive clones As the senior author has previously shown that EBV BHRF1 suppresses apoptosis in response to serum reduction in various BL cell lines [ 11 ], we initially elected to compare the abilities of H. pan BHRF1 and EBV BHRF1 to regulate serum reduction induced apoptosis in the EBV negative Ramos-BL cell line to ascertain whether the genes are functional, as well as structural, homologues. In order to produce expression vectors, the H. pan and EBV BHRF1 reading frames were amplified by PCR from template vectors pHVPanTW4 and pDH222 respectively using primers incorporating XhoI restriction sites. The PCR fragments were introduced into the pCR2.1Topo ® vector and the XhoI fragment was released by restriction digestion of the TopoBHRF1 constructs and cloned into the XhoI restriction site of the pcDNA4/HisMax mammalian expression vector (InVitrogen), which produces an N-terminal fusion protein with 6His and Xpress epitopes. Ramos-BL cells were electroporated with either control vector, EBV BHRF1 or H. pan BHRF1 and cloned by limiting dilution in medium containing 150 μg/ml zeocin. There was no obvious difference in the numbers of drug resistant clones that were produced by transfection with the vector or either of the BHRF1 constructs. Drug resistant clones were screened by RT-PCR for BHRF1 expression and approximately 50% of the clones were shown to be expressing detectable BHRF1. The RT-PCR profiles of two clones each of the three transfected populations which were selected for further analysis, are shown in Figure 1 . RT negative samples were included (lower panel) to rule out DNA contamination of RNA samples. Expression of the fusion proteins was confirmed by Western blot analysis (not shown) and by indirect immunofluorescence using an antibody directed against the 6His epitope (Figure 2 ). Some diffuse fluorescence is seen in the His C controls (A and B), but this is to be expected as the fusion part of the protein is at the amino terminus and the vector therefore can produce a small protein containing the 6His epitope. There is a distinctive crescent-like pattern of fluorescence in clones transfected with the EBV BHRF1 (C and D) and H. pan BHRF1 (E and F), indicative of BHRF1 expression. Determination of sensitivity to serum withdrawal induced apoptosis To determine the sensitivity of the transfected clones to the induction of apoptosis by serum reduction, EBV clones EBV 1B and EBV 3B, H. pan clones Pan 4 and Pan 5 and BHRF1 null vector control clones His C12 and His C13 were seeded in medium containing either 10% or 0.1% serum and the percentage of apoptotic cells was determined at 24-hourly intervals, using acridine orange to distinguish between apoptotic and viable cell nuclei. Necrotic nuclei that appeared after several days due to secondary necrosis of cells already lost by apoptosis were excluded from the counts. Apoptotic death was also confirmed by DNA laddering (not shown). We found that when maintained in medium containing 10% serum (Figure 3A ), both the EBV BHRF1 clones exhibited a slight drop in viability after 48 hours and thereafter viabilities increased to above 90%. A similar drop in viability was seen in the two vector clones, but after an increase at 72 hours, both clones began to show a decline in viability by 96 hours. Both the H. pan BHRF1 expressing clones, maintained viability above 90% throughout the 96 hours period. In contrast, the BHRF1 null vector controls showed higher rates of cell death compared to either the EBV or H. pan BHRF1 expressing clones from 24 hours onwards in medium containing 0.1 % serum (Figure 3B ). After 96 hours in culture, approximately 15% viability was observable in the BHRF1 null vector controls whilst the viability of the BHRF1 clones ranges from 35 to 49%. Clone EBV IB was the most resistant to apoptosis induced by serum deprivation with 49% viability after 96 hours. Two-way ANOVA and Tukey's pairwise analysis of arcsine transformed data showed that at all time points from 48 hours onwards there were significant differences (p < 0.001) between the BHRF1 expressing clones and the vector control clones, but not between the Pan and EBV BHRF1 clones, except at 96 hours when clone EBV 1B showed significantly higher viability than all other clones (eg p = 0.0001 when compared to EBV 3B). Therefore our data indicates that 0.1% serum is sub-optimal for survival of Ramos-BL since a high degree of apoptotic cells are observable at this concentration. Clearly however, both EBV and H. pan BHRF1 expression were able to delay the apoptotic response, and thus promote the survival of these cells which would otherwise undergo apoptosis. Determination of sensitivity to etoposide induced apoptosis We then investigated whether or not the proteins could regulate apoptosis induced by the DNA damaging agent etoposide. The transfected clones were seeded in medium containing either no etoposide or 200 ng/ml etoposide. The percentage of viable versus apoptotic cells was determined every 24 hours by acridine orange fluorescence. We found that, in the absence of etoposide, viability was maintained at above 90% in all clones (Figure 4A ). In the presence of etoposide (Figure 4B ), both the control clones showed a steady decline in viability from 24 hours onwards, with clone His C13 maintaining higher viability than His C12, whilst the BHRF1 clones remained viable for 48 hours before starting to show a decline in viability. Two way ANOVA and Tukey's pairwise comparisons of arcsine transformed data showed that the differences between the control and BHRF1 clones were significantly different from 24 hours onwards. Whilst clone His C13 was significantly different to the BHRF1 clones at all time points, it was also significantly different to His C12 at the 72 (p = 0.359) and 96 (p = 0.002) hour time points. There were no significant differences between the EBV and Pan BHRF1 clones. Determination of sensitivity to ultraviolet induced apoptosis Ultraviolet radiation has been shown to induce apoptosis in other cell lines within a 24 hour period. Having first determined the UV conditions necessary to induced apoptosis in the parent cell line, we then exposed the transfected clones to UV radiation at 30 Jm -2 . Acridine orange counts were taken after 24 hours and the results are shown in figure 5 . Statistical analysis was performed on both the transformed and untransformed data. The untransformed data is shown in Figure 4 , as the error bars were so small in the transformed data that they were not visible. The results are highly significant with p < 0.000001. Mapping the amino acid changes on to the 3D structure During the course of this study, the structure of BHRF1 was solved [ 26 ]. Using RasMol, v2.6, the freely available molecular visualisation software created by Roger Sayle, we have produced a 3D image of BHRF1, highlighting the regions where the EBV and H. pan proteins differ, as shown in Figure 6A . Non-conservative changes, shown in yellow, tend to be found at the end of helices, whereas conservative replacements tend to be within the helices. There are changes within the known functional BH domains (shown in red). The aligned primary amino acid sequences, with the BH domains and changes highlighted using the same colour scheme are shown in Figure 6B . Discussion In this study we present evidence that the BHRF1 protein encoded by H. pan is functionally homologous to the analogous protein in the EBV in human B cells. BHRF1 is one of two Bcl-2 homologues encoded by EBV. Previously the EBV BHRF1 protein has been shown to protect transfected B-cells from apoptosis [ 11 ] and delay the differentiation of epithelial cells in vitro [ 18 ]. The primate virus analogues of BHRF1 have now been cloned by us and others [ 24 , 25 ] and have been shown to be highly homologous in their primary structure both at the DNA and protein level. BHRF1 is normally expressed at high levels in during lytic replication in epithelial cells and the first functional studies of a primate BHRF1, namely the baboon virus BHRF1, were carried out in a keratinocyte system. Whilst a role for BHRF1 during latent infection has not been proven, circumstantial evidence that BHRF1 transcripts are found in certain lymphoid malignancies and that BHRF1 can suppress apoptosis in lymphoid cells suggests that BHRF1 has the potential to contribute to malignant transformation. Whilst infection of B cells is largely latent, lytic replication in B cells also plays an important role in EBV's lifecycle by providing virus to re-infect epithelial cells, ensuring the continued shedding of virus in the oropharynx. We therefore decided to investigate whether the functional homology extended to a lymphoid cell background by comparing EBV BHRF1 with the previously uncharacterised BHRF1 from H. pan . We used 3 triggers known to induce apoptosis at differing rates. Serum withdrawal is a slow trigger, with low levels of apoptosis for 48 hours followed by a precipitous drop in viability. The kinetics of etoposide activity are very different with a steady decline in viabilty over the 4 day period, whilst UV irradiation (never previously reported for BHRF1) induces apoptosis within hours. The EBV and H. pan BHRF1s afforded significant protection against the induction of apoptosis by all three triggers, compared to the vector controls. There was no statistical difference between the EBV and H. pan BHRF1s, (except for clone EBV1B at 96 hours in 0.1% serum), suggesting that H. pan BHRF1 is indeed a true functional homologue of EBV BHRF1. The difference between clone EBV1B and the other BHRF1 clones at 96 hours in low serum could possibly be attributed to slightly higher levels of BHRF-1 expression in this clone, although it is difficult to quantify absolute expression levels from the fluorescence images shown in Figure 2 . Clone His C13 maintained higher viability than clone His C12 against all three triggers and when exposed to etoposide this is statistically significant from 72 hours onwards. This possibly reflects genetic changes accumulated by the clones during selection and passage and highlights the importance of including more than one clone in assays such as these. When one looks more closely at the regions of the protein that differ between the human and chimpanzee viruses (Figure 6 ), it is perhaps not surprising that the two proteins are functional homologues, despite the changes in the amino acid sequence. The non-conservative changes are almost always at the end of a helix where they are least likely to disrupt the overall structure of the protein, whilst the conservative changes are mainly within the helices or loops. Notably there are some changes within the BH domains, known to be critical for the function of Bcl-2 family proteins, which are clearly tolerated in terms of conservation of function. None of the observed changes are likely to significantly alter the conformation of the protein, highlighting the fact that functional conservation of BHRF1 is subject to 3D structural constraints. These observations emphasise the importance of combining structural information with homology studies such as this one to identify regions of the protein that need to be conserved to retain structural integrity. That the two proteins appear to be so similar at the 3D level implies they probably interact with cellular proteins that are themselves highly conserved in the two species. There are only a few reports of proteins known to interact with BHRF1, including PRA1 [ 27 ] and although some studies have shown interactions with several Bcl-2 family proteins [ 28 , 29 ], the reported differences in the 3D structures of BHRF1 and Bcl-2 (namely the lack of a binding groove for pro-apoptotic Bcl-2 family members) [ 26 ] suggests that the anti-apoptotic activity of BHRF1 does not exactly parallel that of Bcl-2. This warrants further study into the viral and cellular proteins which interact with BHRF1, not only to yield more insight into the interplay between virus and host, but also to further our knowledge of the fundamental mechanisms of apoptosis. Conclusions Our results are the first demonstration of functional homology between a primate BHRF1 ( H. pan ) and EBV BHRF1 in a human lymphoid cell background. Both proteins protect against apoptosis induced by two previously described triggers and also a new trigger, UV radiation, against which BHRF1 has never been reported to provide protection. Comparison of the EBV and H. pan proteins at the 3D structural level reveals that none of the changes is likely to significantly alter the structure of the protein. Methods Construction of expression vectors The 573 bp coding sequences of EBV BHRF1 and H. pan BHRF1 were amplified by PCR from pDH222 [ 11 ] and pHVPanTW4 [ 24 ] respectively using primers which incorporated Xho I sites flanking the translational start and stop codons. We used Promega's PCR mastermix with 50 pmol each primer. The sequence of the forward primer was TTGCAGCTCGAGATGGCCTATTC and the reverse primer sequence was GAAAATCTCGAGATTAGTGTCTTCC. The PCR parameters were 35 cycles of 95°C (30 sec), 55°C (30 sec) and 72°C (60 sec). The PCR products were introduced by Topo TA cloning into pCR2.1-Topo ® (Invitrogen) and the XhoI fragments were released by digestion with XhoI and cloned into the Xho 1 site of pcDNA4/HisMaxC (Invitrogen). The plasmids were sequenced to verify that the sequences had joined in frame and contained no PCR induced errors. Transfection of Ramos-BL cells 6 × 10 6 Ramos-BL cells were independently transfected with 20 μg endotoxin-free EBV BHRF1, H. pan BHRF-1 or vector control constructs (pEBV9, pPan4 and pcDNA4/HisMax respectively) by electroporation in a BioRaD Gene Pulser II at 0.45 kV, 125 μF. The cells were seeded in 96-well plates at a density of 5 × 10 4 cells/ well in RPMI 1640 supplemented with 10% FetalClone III calf serum (HyClone) 2 mM L-glutamine (Sigma) 0.4% gentamycin (Sigma) and 200 μg/ml Zeocin (Invitrogen). Wells showing outgrowth of drug resistant cells were cloned by limiting dilution and clones were expanded into 2 ml cultures and maintained in medium containing 150 μg/ml Zeocin. All cultures were fed twice weekly by replacing 90% of the culture with fresh medium. RT-PCR Total RNA was purified from 5 × 10 6 cells using the RNA Safekit (Q Biogene) according to manufacturers instructions. Reverse transcription of 100 ng RNA with oligo dT primer using the Improm II kit (Promega) in a total volume of 20 μl according to manufacturer's instructions was followed by PCR (parameters as above) using 5 μl of the template cDNA and 50 pmols each of the forward and reverse primers CTGTACGACGATGACGATAAG and GTGTCTTCCTCTGGAGATA respectively, to amplify a 655 bp product. Indirect immunofluorescence Cells were suspended in PBS and spotted onto multiwell glass slides and air dried for 60 minutes. Slides were fixed for 20 minutes in methanol at -20°C followed by 5 minutes in acetone at -20°C. The cell spots were rehydrated in 20% normal rabbit serum (in PBS) for 20 minutes then incubated with a 1 in 500 dilution of the monoclonal anti-poly histidine antibody (Clone HIS-1, Sigma-Aldrich) for 1.5 hours at room temp. After three 5 minute washes with PBS, the cells were incubated with a 1 in 50 dilution of FITC goat anti-mouse IgG (Biomeda) for 1 hour at room temp. Thereafter the slides were washed thrice in PBS, a drop of DABCO was added and coverslips were placed over the cell spots. The cells were viewed with by fluorescence microscopy and photographed with a Leica digital camera using a 1.27 sec exposure time and 15× magnification. Apoptosis assays For the serum reduction assay cells were washed 3 times in PBS and then 0.5 × 10 6 cells (BHRF1 or vector clones) were seeded in either medium containing 10% serum or 0.1% serum and the percentage of viable versus apoptotic cells was determined by acridine orange flourescence at 24 hour intervals. For the etoposide assays, 0.5 × 10 6 cells (washed 3 times) were seeded in either routine medium containing DMSO (equivalent to the volume added to the etoposide samples) or medium containing 200 ng/ml etoposide (diluted from a 1 mg/ml solution in DMSO) and the % of apoptotic cells versus viable cells was determined every 24 hours by acridine orange fluorescence. For the UV induction assays, 1 × 10 6 cells in 10 ml of medium were placed in a Petri dish and exposed to 30 Jm -2 UV. The cells were then pelleted by centrifugation and resuspended at 2 × 10 5 cells/ml in medium and returned to culture flasks. Each clone was tested in triplicate and each experiment was repeated 3 times. Acridine orange fluorescence 10 μl acridine orange (100 μg/ml) was added to 100 μl of cell culture containing the individual clones. At least 200 cells were counted using a haemocytometer at 15 × magnification and the number of viable versus apoptotic cells in the population noted. List of abbreviations EBV – Epstein Barr virus, H. pan – Herpesvirus pan , PBS phosphate buffered saline, PCR – polymerase chain reaction, UV – ultraviolet, v-Bcl-2 – viral Bcl-2 homologue Authors' contributions MH did the RT-PCR and UV assay, TW constructed the expression vectors and carried out some of the statistical analyses and SAH produced the transfected clones, carried out the serum withdrawal and etoposide assays, some of the statistical analyses and did the structural comparisons.

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548678

Differential effects of ERK and p38 signaling in BMP-2 stimulated hypertrophy of cultured chick sternal chondrocytes

Background During endochondral bone formation, the hypertrophy of chondrocytes is accompanied by selective expression of several genes including type X collagen and alkaline phosphatase. This expression is stimulated by inducers including BMPs and ascorbate. A 316 base pair region of the type X collagen (Col X) promoter has been previously characterized as the site required for BMP regulation. The intent of this study was to examine the role of Mitogen Activated Protein (MAP) and related kinase pathways in the regulation of Col X transcription and alkaline phosphatase activity in pre-hypertrophic chick chondrocytes. Results Using a luciferase reporter regulated by the BMP-responsive region of the type X collagen promoter, we show that promoter activity is increased by inhibition of extra-cellular signal regulated kinases 1 or 2 (ERK1/2). In contrast the ability of BMP-2 to induce alkaline phosphatase activity is little affected by ERK1/2 inhibition. The previously demonstrated stimulatory affect of p38 on Col X was shown to act specifically at the BMP responsive region of the promoter. The inhibitory effect of the ERK1/2 pathway and stimulatory effect of the p38 pathway on the Col X promoter were confirmed by the use of mutant kinases. Inhibition of upstream kinases: protein kinase C (PKC) and phosphatidylinositol 3-(PI3) kinase pathways increased basal Col X activity but had no effect on the BMP-2 induced increase. In contrast, ascorbate had no effect on the BMP-2 responsive region of the Col X promoter nor did it alter the increase in promoter activity induced by ERK1/2 inhibition. The previously shown increase in alkaline phosphatase activity induced by ascorbate was not affected by any kinase inhibitors examined. However some reduction in the alkaline phosphatase activity induced by the combination of BMP-2 and ascorbate was observed with ERK1/2 inhibition. Conclusion Our results demonstrate that ERK1/2 plays a negative role while p38 plays a positive role in the BMP-2 activated transcription of type X collagen. This regulation occurs specifically at the BMP-2 responsive promoter region of Col X. Ascorbate does not modulate Col X at this region indicating that BMP-2 and ascorbate exert their action on chondrocyte hypertrophy via different transcriptional pathways. MAP kinases seem to have only a modest effect on alkaline phosphatase when activity is induced by the combination of both BMP-2 and ascorbate.

Background During skeletal development and growth, bone formation occurs either by intramembraneous or endochondral bone formation. In endochondral bone formation, which occurs at the growth plates of long bones, cartilage is formed first, then the chondrocytes undergo a proliferative phase followed by hypertrophy, changes in gene expression, and matrix calcification, after which the cartilage is replaced by bone. Although generally referred to as chondrocyte hypertrophy, cell enlargement is just one manifestation of the more complex process of chondrocyte maturation, which can be considered an end-stage of chondrocyte differentiation. It is important to define the mechanisms that induce chondrocyte maturation, not only to understand bone development, but also to help prevent hypertrophy and ossification during cartilage tissue engineering. Hypertrophic chondrocytes are characterized by their increased levels of alkaline phosphatase (ALP), reduced levels of type II and IX collagens, and the emergence of type X collagen (Col X), which is a specific marker of hypertrophy [ 1 , 2 ]. Ascorbate and bone morphogenetic proteins (BMPs) are among the factors previously shown to be inducers of ALP gene expression in chondrocytes. Either of these inducers alone will elevate ALP activity in chondrocytes derived from pre-hypertrophic regions of avian cartilage, but the combined effect of BMP and ascorbate is more than additive [ 3 ]. In early studies with avian chondrocytes, ascorbate-induced increases in type X collagen expression appeared to parallel increasing alkaline phosphatase activity, suggesting that both Col X and ALP might be controlled by common pathways [ 4 ]. However, analyses of BMP-stimulated hypertrophy suggested that ALP activity gradually increased over a 3 day period, while Col X mRNA reached maximal levels within 24 h. Experiments in which pre-hypertrophic chick chondrocytes were transfected with luciferase constructs regulated by sequences from the avian type X collagen gene demonstrated that a "b2" region 2.6-2.0 kilobases upstream of the ColX transcription start site, when joined to 640 base pair (bp) region of the proximal promoter, was transcriptionally activated by BMP-2, -4, and -7 [ 5 ]. Northern blot analyses after cyclohexamide treatment showed that new protein synthesis is not required for BMP-induced Col X expression [ 3 ]. Additional studies indicated that the mechanism for type X collagen promoter regulation probably involves BMP-activated Smads interacting with a Runx2/Cbfa1 transcription factor [ 6 ], and that retinoic acid stimulation of Col X expression is via the same 316 bp region [ 7 , 8 ]. Although long-term (4–7 day) treatment of chondrocytes with ascorbate results in increased levels of type X collagen mRNA [ 9 ], there is no data concerning the ability of ascorbate to regulate the type X collagen promoter. In osteoblastic cells, BMPs and ascorbate have been shown to operate via mechanisms that at least partly involve mitogen activated protein kinases (MAP kinases). For example, ascorbate promotes extracellular matrix production which, in turn, activates the extracellular-signal regulated kinases, (ERK1/2 or p42/ p44) in an osteoblastic cell line [ 10 ]. MAP kinases including ERK1/2 [ 11 , 12 ], p38 [ 13 ] and PI3 (phosphatidylinositol 3-) kinase [ 14 ] have also been reported to be required for BMP-dependent induction of osteoblast differentiation. However, these pathways can act oppositely in certain BMP induced processes such as osteocalcin synthesis by osteoblasts [ 15 ]. In general, MAP kinase pathways involving ERK1/2 stimulate proliferation, growth and differentiation, whereas those that stimulate p38 kinase lead to differentiation and apoptosis [ 16 ]. In early stages of chondrocyte differentiation, an increase in p38 and decrease in ERK1/2 activity is required for the progression to cartilage nodule formation in chick limb buds [ 17 ]. In hypertrophying chondrocytes p38 has been shown to be required for Col X mRNA synthesis [ 18 ]. In apoptosis of articular chondrocytes [ 19 ] and other cell types [ 20 ], ERK1/2 inhibits and p38 stimulates the apoptotic pathway. Chick sternal chondrocytes are a popular model for the study of chondrocyte maturation because under normal development chondrocytes from the cephalic portion of the sternum undergo hypertrophy followed by mineralization and bone formation, whereas the caudal portion remains as cartilage [ 3 , 8 ]. In this study we investigate the roles of ERK1/2, p38 and two upstream pathways, protein kinase C (PKC) and PI3 kinase, in the maturation of chick prehypertrophic sternal chondrocytes induced by BMP-2 and ascorbate. Results ERK signaling inhibits transcription of the BMP-2 responsive type X collagen promoter but is not involved in the regulation of alkaline phosphatase activity Studies with the ERK1/2 inhibitor U0126 indicated that blocking ERK1/2 signaling increased the activity of the type X collagen promoter but had no effect on alkaline phosphatase (ALP) activity in chick cephalic sternal chondrocytes (Fig. 1 ). Cells transfected with luciferase reporter plasmid containing the BMP-responsive b2/640 region of the Col X promoter showed a 3-fold (p < 0.05) increase in luciferase expression, as a ratio to the pRL null control vector, after the addition of 4 μM U0126, both with and without exogenous BMP-2 (Fig 1A ). In contrast neither basal nor BMP-stimulated ALP activity were significantly changed in the presence of U0126 (Fig. 1B ). Figure 1 Effects of BMP-2 and the ERK inhibitor, UO126, on the Col X promoter and alkaline phosphatase activity in chick cephalic sternal chondrocytes. A: Activity of the b2/640 type X collagen promoter; 24 hrs after seeding cells were transfected with PGLb2/640 and pRLnull luciferase vectors, 5 hrs after transfection 4 μM U0126 or vehicle (DMSO) was added. BMP-2 was added to selected wells after a further hour. Values are mean ± S.D of the mean ratio of promoter to empty vector fluorescence units, for 6 experiments assayed in triplicate. B: Alkaline phosphatase activity; 24 hrs after seeding, medium was changed and 4 μM U0126 or vehicle was added. BMP-2 was added to selected wells after a further hour. Cell extracts were prepared 72 hrs later. Data was obtained using 5 different isolates of chondrocytes assayed in triplicate. Values are mean ± SEM of 12–15 samples normalized to within experiment controls treated with BMP-2 but no inducers, *:p < 0.01 group differs from non BMP-2 treated group within inhibitor treatment, +: p < 0.05 that group differs from group with no UO126. ALP activity was highly variable between cell isolates and is expressed here normalized to BMP-2 treated controls for the purpose of combining experiments, typical ALP values ranged from approximately 0.5–2 nmol/min/μg DNA in controls to between 4 and 12 nmol/min/μg DNA in BMP-2 treated cultures. The effects of altered ERK1/2 signaling on Col X promoter activity in chick sternal chondrocytes was further studied both by transfection with mutant kinases and by treatment with additional kinase inhibitors. Col X promoter activity was increased, both in the presence and absence of BMP-2, when the mitogen-stimulated ERK pathway was suppressed by transfecting chondrocytes with dominant negative ERK-2 (Figs. 2A, 2B ). Conversely, stimulating the ERK1/2 pathway by over-expressing constitutively active MEK1, an upstream kinase of ERK1/2, decreased promoter activity by 50% (p < 0.05) and in BMP-2 treated cells it eliminated any BMP response. Figure 2 Effects of MAP kinase manipulation on b2/640 type X collagen promoter activity, in chick cephalic sternum chondrocytes. A and B : Mutant kinases; 24 hrs after seeding, cells were transfected with luciferase vectors and 0.5–1 μg mutant kinase DNA. After 5 hrs medium was changed ( A ) or medium changed and BMP-2 added ( B ). C and D : Inhibitor treatments; 5 hours after transfection with luciferase vectors, medium was changed and kinase inhibitor or vehicle (DMSO) was added as indicated. In D 30 ng/ml BMP-2 was added one hr after medium change. Data obtained using at least 2 independent isolates of chondrocytes, assayed in triplicate. Values are mean ± SEM of luciferase ratios of type X collagen promoter activity to control vector, normalized to BMP-2 treated controls. *:p < 0.05 that luciferase ratio differs from non BMP-2 treated group, +: p < 0.05 that luciferase ratio differs from group with no MAP kinase manipulation. As seen with the ERK1/2 inhibitor U0126, treatment with the more specific ERK1/2 inhibitor PD098059 increased b2/640 Col X promoter activity, in the presence of BMP-2 (Fig. 2D ). Dose response experiments indicated that concentrations of PD98059 as low as 10 μM significantly increased luciferase expression 2-fold (p < 0.001) in BMP-treated cells, but not in the absence of BMP-2 (Fig. 2C ). At a higher does, 50 μM, of PD90859 luciferase levels in BMP-2 treated cells were 10–20 fold higher (p < 0.005) than BMP-containing cultures without inhibitor (Fig. 2D ), at this dose PD90859 also stimulated the promoter in the absence of BMP-2 (Fig. 2C ). p38 MAP kinase signaling contributes to the response of the type X collagen promoter to BMP-2 Transfection with dominant negative p38 caused a decrease in Col X promoter activity in BMP-2 treated cephalic chondrocytes, reducing activity to half of that seen in BMP-2 treated controls (p < 0.005) and eliminating the BMP-2 response (Figs. 2A and 2B ). Similarly, 1 μM SB 203580, an inhibitor of p38, significantly decreased BMP-stimulated promoter activity (Fig. 2D ), but had little effect on promoter activity in the absence of BMP-2 (Fig. 2C ). Inhibiting PKC and PI3 kinases increases type X collagen promoter activity Addition of either PI3 kinase inhibitor or PKC inhibitor resulted in similar stimulation of the collagen type X promoter. Calphostin C, a PKC inhibitor, increased activity in BMP-2 treated cells more than 2-fold, an effect similar to that seen with the ERK1/2 inhibitor PD98059 at 10 μM (Fig. 2D ). Similarly, 50 μM LY294002, a PI3 kinase inhibitor, stimulated the b2/640 promoter approximately 2-fold (Fig. 2D ). However, both of these inhibitors also increased transcription of the collagen type X promoter in non-BMP-2 treated cells to levels as high as seen with the combination of BMP-2 and the respective inhibitor treatment (Fig. 2C ). Kinase inhibitor effects on viable cell number To assess the possible effects of protein kinase inhibitors on cell proliferation and survival, we measured relative numbers of live cells using a tetrazolium (MTS) assay. The results indicated that all cultures treated with inhibitors, with and without BMP-2 and/or ascorbate, had cell numbers within 10% of untreated controls (data not shown). Ascorbate has no effect on the type X collagen promoter and stimulates alkaline phosphatase activity regardless of kinase inhibitor treatment We examined the effect of 75 μM ascorbate-2-phosphate on the activity the Col X promoter in cultures treated with kinase inhibitors. Col X promoter activity was unaffected by addition of ascorbate, and 4 μM of the ERK1/2 inhibitor U0126 increased promoter activity to comparable levels both with and without ascorbate (Fig. 3A ). Figure 3 Effects of ascorbate and MAP kinase inhibitors on the Col X promoter and alkaline phosphatase activity in chick cephalic sternal chondrocytes. A: Activity of the b2/640 type X collagen promoter; 24 hrs after seeding cells were transfected with luciferase vectors, 5 hrs after transfection 4 μM U0126 or vehicle were added. Ascorbate was added to selected wells after a further hour. Values are mean ± S.D of the mean ratio of promoter to empty vector fluorescence units, for 3 experiments assayed in triplicate. B: Alkaline phosphatase activity; 24 hrs after seeding, medium was changed and 4 μM U0126 or vehicle was added. Ascorbate or ascorbate with BMP-2 was added to selected wells after a further hour. Cell extracts were prepared 72 hrs later. Data was obtained using 5 different isolates of chondrocytes assayed in triplicate. Values are mean ± SEM of 12–15 samples normalized to within experiment controls treated with BMP-2 but no inducers. *: p < 0.05 that group differs from non-supplemented group within inhibitor treatment. The increase in ALP caused by BMP-2 addition is shown, this increase is significantly smaller in UO126 treated cells, +:p < 0.05. The increase in alkaline phosphatase activity caused by adding BMP-2 to ascorbate treated cultures is reduced by ERK inhibitors ALP activity in the absence of exogenous BMP was stimulated at least 2-fold in ascorbate-treated cultures without inhibitors, as previously reported, and this stimulation was not significantly affected by addition of either ERK1/2 or p38 inhibitors (Fig. 3B ). In cultures treated with ascorbate and BMP-2 addition of ERK1/2 inhibitors resulted in ALP levels that were <60% of the level seen in cells without inhibitor (Fig. 3B ). The increase caused by BMP-2 addition, relative to ascorbate only-treated cultures was significantly reduced by treatment with U0126 (p < 0.05). The p38 inhibitor SB203580 did not cause a statistically significant inhibition of alkaline phosphatase activity. PI3 kinase and PKC inhibitors had no significant effects on ALP activity (data not shown). Discussion The present studies demonstrate that ERK1/2 inhibition increases activity of the BMP responsive region of the type X collagen promoter. This indicates that ERK1/2 signaling interferes with the ability of BMP-induced signals to stimulate type X collagen transcription. Interestingly ERK1/2 has also been shown to inhibit type I collagen expression in an osteoblastic cell line [ 21 ] suggesting there may be a common pattern of ERK1/2 inhibition of collagen transcription pathways. In contrast to the stimulatory effects of inhibiting the ERK pathway, p38 inhibition blocked BMP-stimulated Col X promoter activity. Zhen et al. [ 18 ] and Beier and Luvalle [ 22 ] also showed that p38 signaling is important for regulation of Col X expression, Beier and Luvalle suggested that the proximal promoter contained a site for p38 action. Here, we have confirmed these results and narrowed the region of p38 responsiveness to within the region of the Col X promoter that is also BMP responsive. While the classical pathway for BMP signaling is via activation of R-Smads, there is also evidence for BMP signaling via a TGF-activated kinase (TAK1) leading to p38 signaling [ 23 - 26 ]. However, in preliminary experiments Smad1 over-expression increased BMP-stimulated Col X promoter activity even in the presence of DN-TAK1 (data not shown). This suggests that BMP-activated Smad signaling and not TAK1 signaling is the major factor in Col X promoter regulation. Taken together these data suggest that the role of p38 is as a co-activator of Smads or Runx-2 rather than a downstream effector of BMP signaling. Inhibiting either protein kinase C (PKC) or phosphatidylinositol 3-kinase (PI3 kinase) increased type X collagen promoter activity both in BMP-2 treated cultures and controls. Both PKC and PI3 kinase have been reported to negatively regulate p38 [ 18 ] and positively regulate ERK1/2 [ 20 , 27 , 28 ]. The complex effects in which these kinases stimulate basal Col X promoter activity but inhibit BMP-2 from stimulating additional activity may be due to their simultaneously affecting both of these pathways. Although alkaline phosphatase expression, like type X collagen expression, increases during chondrocyte hypertrophy and is stimulated by BMPs, its regulation clearly differs from Col X in several respects. ERK1/2 inhibition has little effect on the ALP activity induced by BMP-2 or ascorbate acting alone and reduces the ability of BMP-2 to further stimulate ALP activity in ascorbate treated cultures. Inhibiting p38 does not have a clear effect on BMP-stimulated alkaline phosphatase activity in this model although it has been shown to reduce ALP activity in long-term (12–15 day) micromass cultures [ 29 ]. Preliminary studies with cyclohexamide indicate that new protein synthesis is required for the up-regulation of alkaline phosphatase mRNA in response to BMP-2. We propose that these differences reflect a direct Smad-mediated effect of BMPs on type X collagen expression and an indirect effect on ALP expression. A mechanism which could account for the observed effects of ERK and p38 signaling on expression of type X collagen and ALP is presented in Fig. 4 . The simplest explanation for our observation that a decrease in ERK1/2 signaling causes increased type X collagen promoter activity is that ERK1/2 can phosphorylate the linker region of BMP-activated Smads, preventing nuclear translocation of activated Smads, as suggested by Kretzschmar et al. [ 30 ]. Alternatively, products of ERK1/2 signaling may act directly on a silencer within the type X collagen promoter such as the region identified by Beier et al. [ 31 ] at 2864-2410 base pairs which would overlap with our b2-containing construct (2649 -2007). Figure 4 Possible mechanism for kinase involvement in BMP stimulated type X collagen expression. ERK1/2 is proposed to suppress activated Smad translocation to the nucleus as described by Kretschmer et al. [30] and thereby inhibit Col X transcription. ERK-specific Runx2 phosphorylation is required for regulation of typical osteoblastic genes but may not be required for Col X expression. However p38 facilitates Col X transcription, possibly via Runx2 phosphorylation and although was not shown to be involved in short term increases in ALP in our model, has been shown to be involved in long term increases in ALP over 15 days of chondrocyte differentiation in culture (question mark) [29]. Evidence that BMP stimulation of type X collagen requires both activated R-Smads and Runx2 has been previously reported [ 5 , 7 ]. Little is known concerning kinase phosphorylation of Runx2, except for the report that ERK phosphorylates Runx2 and increases its binding to the osteocalcin promoter [ 32 ] in osteoblasts. If ERK phosphorylation of Runx2 were required for BMP-stimulated type X collagen transcription, we might expect ERK1/2 inhibition to decrease the activity of the Col X promoter. However, as ERK1/2 inhibition increases Col X promoter activity while partially inhibiting ALP we propose that the Runx2-Smad complex binding to the Col X promoter may not be phosphorylated by ERK1/2, but that ALP expression does require Runx2 phosphorylated by ERK1/2. As well as its demonstrated role in Col X expression as found here and by [ 18 , 31 ], there are also reports that p38 inhibitors block osteoblast differentiation [ 33 , 34 ]. Because Runx2 plays an important role in both osteogenesis and chondrocyte maturation, we have suggested that p38 may function in Runx2 expression, activation or nuclear translocation. However, there are many other possible roles, including the suggestion that p38 is downstream of BMP-activated Smad signaling [ 35 ]. Retinoic acid [ 7 , 8 ], another stimulator of chondrocyte hypertrophy has also been shown to act at the BMP-2 responsive b2 region of the type X collagen promoter, however ascorbate, which does produce an increase in type X collagen mRNA expression [ 4 ], does not seem to have any effect on this promoter region. These results, in combination with previous findings that Col X mRNA expression only occurs after 4–9 days stimulation with ascorbate [ 9 ], suggest that the effects of ascorbate on regulation of type X collagen expression are via a separate mechanism than BMP stimulation and are probably indirect. Conclusions Elucidating the signaling pathways by which chondrocytes are driven to hypertrophy is necessary in order to better understand skeletal development, cartilage disease and improve the design of tissue engineered cartilage. We showed here that the ERK1/2 pathway inhibits type X collagen production by either directly or indirectly acting at the BMP responsive region of the promoter. p38 kinase signaling stimulates type X collagen transcription at the same promoter region, probably in conjunction with BMP-2 activated Smads. The factor upstream of p38 in this stimulatory pathway is unknown. Alkaline phosphatase activity is likely to be regulated in a different way from type X collagen since MAP kinases do not contribute in the same way to this pathway. Although ascorbate and BMPs both induce hypertrophy in chondrocytes ascorbate does not act at the same region of the Col X promoter as BMPs. Methods Inhibitors and plasmids The ERK1/2 inhibitor PD98059, which blocks the upstream kinase (MEK1) of ERK1/2, the p38 inhibitor SB203580, and the PKC inhibitor Calphostin C were obtained from Sigma (St. Louis, MO). UO126, also a MEK1 inhibitor, was obtained from Biomol (Plymouth Meeting, PA) and LY294002, a phosphatidylinositol 3- (PI3) kinase inhibitor from Cell Signaling Technology (Beverly, MA). Plasmids were kindly donated as follows: constitutively active MEK1 from Michael Webber (University of Virginia); dominant negative p38 [ 36 ] from Roger Davis at the Howard Hughes Medical Institute, University of Massachusetts Medical School, dominant negative ERK2 [ 37 ] from Melanie Cobb at University of Texas Southwestern Medical Center. Cell Culture Chondrocytes were cultured as previously described [ 3 ]. Cephalic and caudal sternal chondrocytes were isolated from 15 day chick embryos and cultured for 5 days. Dissection of chick cartilage was performed under a University of Pennsylvania IACUC exemption. On day 5 non-adherent cells were removed and plated in 12 well plates at 300,000 cells /well in DMEM supplemented with 10% NuSerum, 2 mM L-glutamine, 100 U/ml penn/strep and 4 U/ml hyaluronidase, to promote cell attachment. Transfection of cephalic (pre-hypertrophic) sternal chondrocytes On day 1 of secondary culture (24 hrs after plating) the cell layer was washed in HBSS and the media changed to DMEM supplemented with 10% FBS in place of NuSerum. Cells were co-transfected with pGL2 plasmid containing the b2/640 type X collagen promoter region attached to a firefly luciferase reporter (0.2–1 μg/well) (Promega, Madison, WI) and pRL null plasmid attached to a renilla luciferase reporter (0.4 μg/well) (Promega) which served as a transfection control [ 5 ]. When appropriate, mutant plasmids were added at 0.5 or 1 μg/well along with the luciferase vectors. Luciferase and mutant kinase plasmids were transfected either using CaPO 4 precipitation or Fugene transfection reagent at 6 μl/ml (Promega). Since preliminary experiments using green fluorescent protein showed that Fugene was more effective in terms of numbers of cells transfected, this method was used for the majority of the experiments; however, relative outcomes between controls and treated cells were not affected by the transfection method. Transfection proceeded for 5 hrs after which the cell layer was rinsed twice in HBSS and cultured with serum free medium (DMEM with 2 mM L-glutamine, 100 U/ml penn/strep, 4 U/ml hyaluronidase, 60 ng/ml insulin, 1 mM cysteine, and 10 pM triiodothyronine). Some wells were supplemented with 75 μM ascorbate-2-phosphate (Wako, Takara, Japan) or 30 ng/ml human recombinant BMP-2 (Wyeth, Cambridge, MA). Where inhibitors were used they were added at this point and cells incubated for 1 hr before the addition of BMP-2. Cells were cultured for a further 48 hours, then lysed and assayed using a dual luciferase assay kit (Promega). Alkaline Phosphatase Assay For alkaline phosphatase assays, cells were switched to serum free medium on day 1 of secondary culture, inhibitors were added and cells incubated for 1 hr before the addition of ascorbate or BMP-2, as described for the luciferase assay. Cells were cultured for a further 72 hrs and then rinsed twice in HBSS. Cells numbers were assayed either by DNA quantification (CyQUANT cell proliferation assay kit, Molecular Probes, Eugene, OR) or by MTS tetrazolium salt assay of mitochondrial activity (Cell Titer 96 AQueous One Solution Cell Proliferation Assay, Promega). When MTS was used, a 1:10 dilution of MTS was applied in phenol red-free media for 30–60 minutes, 200 μl of media plus MTS was transferred to a 96 well plate and assayed in a 'Multiskan ascent' plate reader (Thermolabsystems, Franklin, MA). The cell layer was then washed twice in HBSS and extracted with 0.15 M Tris, pH 9 with 0.1 mM ZnCl 2 , 0.1 mM MgCl 2 and 1% Triton X-100 for 30 mins at 37°C, followed by overnight storage at 4°C. A sample of the cell lysate was reacted with p-nitrophenyl phosphate substrate in 1.5 M Tris buffer pH 9 with 1 mM ZnCl 2 and 1 mM MgCl 2 . Phosphatase activity was measured specrophotometrically at 410 nm with 1 absorbance unit equivalent to 64 nmol of product. For DNA analysis, cells were trypsinized and a subsample of cell suspension centrifuged, the cell pellet lysed with the CyQUANT lysis buffer and the fluorescent DNA dye added. The resulting solution was transferred to a 96 well plate and DNA assayed fluorometrically. The remaining cells were extracted for the alkaline phosphatase assay as above. Alkaline phosphatase enzyme levels were calculated as nmol p-nitrophenol product per minute normalized to MTS units or μg DNA. Statistical analysis Statistics were performed using Minitab™ software. After expressing results as a ratio of experimental/control within each experiment, the data from at least 3 experiments were combined. The combined data was tested for normality using the Anderson-Darling test. Normally distributed or non-parametric data were tested for differences between treatments using two-sample Students t-test or the Mann-Whitney test respectively. Where groups of experiment means were compared a paired t-test was used. List of Abbreviations ALP – Alkaline Phosphatase BMP – Bone Morphogenetic Protein bp – base pairs CA – constitutively active cbfa – core binding factor alpha 1 Col X – Collagen type X DN – dominant negative ERK – extracellular signal regulated protein kinase MAP – Mitogen activated protein MEK – ERK kinase MTS – 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium, inner salt PI3 – phosphhatidylinositol 3 PKC – Protein Kinase C Runx – Runt associated protein TAK – Transforming growth factor beta activated kinase Competing interests The author(s) declare that they have no competing interests. Authors' contributions GCR was involved in experimental design, performed 90% of the experiments, analyzed the data and wrote the first draft of the manuscript. EBG isolated chondrocytes, performed preliminary experiments and contributed to trouble-shooting of the methods. GG-K, performed preliminary experiments and developed methodology. PSL was involved in experimental design and data analysis, wrote portions of and edited the whole manuscript and was the project supervisor.

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387285

A Wee Lesson in Science Communication

The University of Edinburgh encourages its Ph.D. students to participate in a broad programme of science communication activities, designed to enhance public engagement in science

The need for effective communication of research and the promotion of science is more important then ever. Public scepticism of research is high, and the number of students studying science continues to dwindle. In an attempt to combat this, the University of Edinburgh encourages its Ph.D. students to participate in a broad programme of science communication activities, designed to develop transferable skills they can use outside pure research and to enhance public engagement in science (PES). Included as part of the transferable skills programme, the University hosts a science communication module. The course provides an introduction to the different media, educational, ethical, and political issues surrounding the communication of science to a nonspecialist audience. Initially, the course addresses the presentation of science in written and oral forms. However, as the presentation of science to the public is not simply a practical skill, part of the course is dedicated to the tactical communication of science in society and the relationship between scientists and the media. Finally, students are introduced to ongoing PES opportunities. Any involvement requires the approval of supervisors, to ensure no adverse effects on academic performance. The activities available are diverse and flexible, and they enable students to undertake projects that reflect personal interest and availability. What opportunities are available? For enthusiastic students, membership of the Nikon–University of Edinburgh Post-Graduate Science Communication Team (PGSCT) is possible. The PGSCT requires a commitment of 15 days per academic year to paid science communication projects and events, including compulsory support of SCI-FUN, the University's established science and technology roadshow. The team is recruited annually from students of the Science and Engineering, Medicine, and Veterinary Medicine Colleges and takes a leading role in PES activities. Team members are supported by other graduate students who participate on a more casual basis. To ensure that a broad spectrum of activities is available to audiences, the PGSCT members are actively encouraged to design and develop their own ideas. An opportunity to do this is provided through the University's Science Zone, at the Royal Museum of Scotland, for the duration of the Edinburgh International Science Festival. From successful workshops, originally piloted at the science festival, several ex-PGSCT members have gone on to establish their own projects. One example of this is the Natural Environment Science Education scheme, which later received recognition through the Royal Society of Edinburgh/Scottish Executive ‘Science in the Community’ Award for 2003. A primary aim of this scheme was to deliver in isolated and remote communities innovative hands-on earth science- and natural science-based activities beyond city venues. For students, developing and presenting workshops are incredibly rewarding and allow them to experience the enthusiasm of participants and fellow presenters. Some activities are transferred from the Science Zone to the classroom, where students can communicate with children at all stages of their schooling. At primary school age (5–11 years) after-school science clubs, led by graduate students, provide an opportunity for presenters to share with pupils their enthusiasm for science. Alternative activities are directed at secondary school children (12–18 years), with a variety of workshops available across the different scientific disciplines. In particular, The Scottish Institute for Biotechnology Education (SIBE) has been set up within the University to facilitate PES activities such as the popular ‘Green Fingerprinting’ workshop where the principles of DNA fingerprinting are applied to an ecological scenario in the form of a practical activity ( Figure 1 ). The majority of workshops coordinated by SIBE have been funded by the Biotechnology and Biological Sciences Research Council (BBSRC). Figure 1 Students Studying a Stained Agarose Gel at a Green Fingerprinting Workshop (Photograph, with permission, by Douglas Robertson) The presentations may be in person or utilise new technologies such as video conferencing. A BBSRC Dialogue Award has recently been granted to SIBE to design, develop and deliver video-conferences addressing bio-ethical issues surrounding recent advances in biotechnology. Together, the two approaches of in-person and virtual presenting, enhance the schools' curriculum and facilitate dialogue between scientists and the public at a stage where promotion of science can influence the choice of further study and career options. The promotion of biotechnology within schools does not stop with the encouragement of school children's enthusiasm; SIBE also works closely with organisations such as ‘Science and Plants for Schools’ (SAPS) to assist with continuing professional development of biology teachers through the organisation of training days aimed at curriculum enhancement and the practical application of biotechnology in the classroom. Interested graduate students can co-present the workshops, though they are led by permanent staff. The students introduce their own research to highlight the applications of biotechnology and provide a useful technical resource. For students who prefer to communicate through the written word, though no guarantee of publication can be given, the University is in a position to highlight science-writing opportunities, usually as a contribution to publications specifically concerned with science communication or within the scientific press. At the Institute of Cell and Molecular Biology at the University a ‘press-gang’ meets on a monthly basis to discuss research carried out in the Institute and generate press releases for publication in the university press and national newspapers where appropriate. Complementing the University's efforts, many other organisations, such as UK Research Councils and the British Association for the Advancement of Science, endorse graduate students spending time on PES activities. Several schemes have been put in place to facilitate this; Researchers in Residence, the Science and Engineering Ambassadors Scheme and science communication courses. Hosted at the University's science campus—Kings Buildings—‘pgscicom’ provides up-to-date information on opportunities for PES at the University and beyond through regular email communications. As a PhD student and PGSCT member, I believe the approach of the University of Edinburgh to PES is of benefit to all involved. The combination of training and practical experience provides graduate students with new and valuable skills and opportunities to develop them further. The events and activities enthuse and engage audiences with the presentation of science in an informal but informative manner.

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548693

Managing change in the nursing handover from traditional to bedside handover – a case study from Mauritius

Background The shift handover forms an important part of the communication process that takes place twice within the nurses' working day in the gynaecological ward. This paper addresses the topic of implementing a new system of bedside handover, which puts patients central to the whole process of managing care and also addresses some of the shortcomings of the traditional handover system. Methods A force field analysis in terms of the driving forces had shown that there was dissatisfaction with the traditional method of handover which had led to an increase in the number of critical incidents and complaints from patients, relatives and doctors. The restraining forces identified were a fear of accountability, lack of confidence and that this change would lead to more work. A 3 – step planned change model consisting of unfreezing, moving and refreezing was used to guide us through the change process. Resistance to change was managed by creating a climate of open communication where stakeholders were allowed to voice opinions, share concerns, insights, and ideas thereby actively participating in decision making. Results An evaluation had shown that this process was successfully implemented to the satisfaction of patients, and staff in general. Conclusion This successful change should encourage other nurses to become more proactive in identifying areas for change management in order to improve our health care system.

Background This study was undertaken in a 28 – bedded gynaecological ward catering for female patients aged 16 and above. There were 21 nurses based in this ward of whom 14 were qualified and the remaining were health care assistants, with experience ranging from 1 1/2 – 33 years. The shift handover in this ward was conducted as "a ritual inheritance," [ 3 ] distant from patients hearing and vision, such as the ward manager's office or the nurses' station, thus excluding patients participation in their care. The traditional handover used to consist of one-way communication, where the nurse in charge gave the relevant information and instructions to the nurses resuming their shift. A very salient feature of the handover was the absence of individual care planning and where all information about patients was either written in the ward diaries or in the patient files or nursing notes. The sample size of patients involved in the evaluation part of the study was 58. The verbal handover was derived from written information on the office white board which included the patient's name, bed number, medical diagnosis and the treating doctor. This was in line with the findings of Sherlock [ 12 ] who argued that the shift handover was characterized by a focus on the biomedical model and marginalized the psychosocial aspects of care. The same style of reporting was repeated from one shift to another. As a result, the contents would sometimes degenerate into irrelevant and outdated statements, unrelated to the patient progress and often judgmental in nature with the likelihood of leading to omissions in care. It was therefore not uncommon that nurses were questioned on their practice by the ward manager or the treating doctor which gave rise to a blaming culture among nurses. There was also a level of dissatisfaction among patients who felt that they were not being involved enough in their care. Diagnose need for change The root cause of the problem identified was the model of handover used to communicate clinical information. As a benchmark, the findings from evidence on the bedside handover were used to give meaning and strength to the proposed change. Bedside handovers offer an immediate solution to the many problems that are associated with the traditional handover [ 5 , 15 , 16 ]. It has further advocated that bedside handover lay more emphasis on individualized patients care whereas bedside reporting is the most frequently used model of handover [ 5 ]. It puts the patients central to all care activities and does not rely purely on verbal information but which combines the key principle of patients/clients involvement and participation. In the same context, patients involved in handovers gain access to information that is thought to provide them with comfort and speed recovery [ 10 ]. Bed-side reporting makes it possible for nurses starting their shift to obtain a better insight into the care each patient requires [ 6 ]. Patients can discuss their health by asking questions and it was found to improve the consistency and continuity of patients care. The information style of bedside handover was informative, personal, shorter and comprehensive. In the light of the above findings, bedside handover had become a valid option for change in this ward. Methods Theories underpinning the change process An adaptation of Spradley's 8-step model and Lewin's 3-step model of Unfreezing , Moving and Refreezing provided us with useful frameworks for our change management [ 9 , 14 ]. Unfreezing Unfreezing is about encouraging people think about the current situation and helping them recognise the need for change [ 5 ]. Change to be initiated requires a sense of direction and considerable power of leadership [ 8 ]. The authors were also guided by the work of Swansburg and Swansburg, [ 15 ] who argued that "transformational leaders are seen in health care organizations as a commitment to excellence." The first move therefore was to create awareness by communicating the proposed change to all those who were going to be affected by the new practice: the nurses, patients and the ward manager so that they all had a shared vision of an improved handover system. A goal-seeking behavior with a clear logical sequence of action, were demonstrated throughout the process as advocated by Lancaster and Lancaster [ 8 , 17 ]. Research based articles were also used to demonstrate how this system was successfully implemented in different areas of the health care system. The proposed change was announced in advance by using different communication channels, e.g. personal contact with individual nurses, staff information/notice board by the authors. This initiated informal discussion among nurses of the ward by creating a cognitive dissonance which led to a quest for more information about the new handover. This consultation phase allowed the nurses to discuss various clinical scenarios and analyse the constraints and benefits of the new proposal in the local context. They were also involved in group work to identify and make proposals on how to deal with some of the problems that we may encounter in our local context e.g. handover coinciding with ward rounds or emergency situations and patients too distressed to talk. Case studies and research articles on this topic were used for discussion and to further reinforce the beliefs of staff of the ward that the current practice had shortcomings and could be improved. The status quo was therefore unsettled and this enabled us to rule out the first resistance through a normative re-educative strategy. A group of senior nurses who had experience in this particular area agreed take turn to act as mentors in order to facilitate this process and offer support to their junior colleagues in the first week until they become confident to carry out the process without supervision. Analysing the alternative options The extensive literature search also provided us with options for alternatives to bedside handover. These were thoroughly debated before reaching a decision. The options considered were the following: 1) Tape recorded handover 2) Computer generated handover using information technology 3) Bedside handover, based on individualized care plan The 'SMART' criteria were used to evaluate the feasibility of the alternatives to bedside of handover. The tape recorded handover would require a tape recorder being taken around to each of the patients and the interaction recorded. An informal discussion with the patients revealed that this method was distractive and the majority of them did not feel comfortable about their conversation being recorded. With regards to the computer generated handover using information technology, the patients felt this system will not enable them to engage fully in the process. It was also felt that since the first two options required extra financial, technical resources for implementation, these would not be feasible in the first instance whereas the bedside handover gained unanimous support from both patients and staff. This was also more realistic in term of its applicability in our practice area. It was specific, measurable in terms of its performance and achievable within existing resources and a defined time frame. Its foundation rested on evidence base practice, which showed theoretical soundness. Selecting the change There was a shared vision about the worth of the proposed change by the team and consequently bedside handover was logically considered as the best option for change. The vision formulated was that in three months' time, bedside handover would become the normal shift handover process of the ward. The mission statement agreed was "all handovers would be carried out at the patients' bedside between the incoming and outgoing nursing staff with the patients' involvement." Force-field analysis A force field analysis, as shown in table 1 was carried out to evaluate the driving and the restraining forces for the change as per Lewin's model [ 9 ]. The driving forces resided in the support of the ward manager, peers, evidence based arguments and our determination to see the change happen. The restraining forces were mostly related to a lack of information and uncertainty surrounding the change process. Other significant issues that were identified to cause resistance to the change were lateness at work, non-overlapping of shifts and maintaining confidentiality of patient's information. Table 1 A force field analysis using Lewin's (1951) driving and restraining forces DRIVING FORCES RESTRAINING FORCES • Critical incidents on the increase • Care given predominantly biomedical in orientation • Complaints from patients, doctors and relatives on the rise. • Increase in discharge against medical advice • Staff knowledgeable in change management • Ward manager's and peer lending support • Familiarity with ward culture • Ritualism and tradition • Fear that this may lead to more work • Lack of confidence on the part of some nurses • Fear of increased accountability • Problems associated with arriving late at work • Problems associated with disclosure of confidential information Planning the change Careful planning is essential if trauma is to be minimized [ 2 ]. It was quite important for us to provide information so as to unlock the status quo. This was done by drafting a protocol, (table 2 ) on a six points systematic step on how to proceed in practice with the change. This protocol was piloted over 2 morning and 2 evening handover sessions to ensure validity and reliability. There were no changes required to the protocol following the pilot study. Table 2 Results of protocol with 6 criteria based on observational data on 10 handovers 1. Outgoing and incoming nurses meet in the office to get a report on confidential matters. 100% 2 Outgoing and incoming nurses then move on to the patient's bedside. 100% 3 Nurses introduce themselves to the patient and initiate handover from patient's him/herself in the first instance. 100% 4 Patient's progress is reviewed as per care plan with a discussion of the future care of the patient. 100% 5 Any other queries from patient is dealt with 100% 6 Session with patient is concluded satisfactorily 90% The time frame earmarked to implement the change was three months starting from the 8 th of February 2003 up to 8 th May 2003. One-month time was judged sufficient to unfreeze the situation and the remainder to implement and evaluate the change. Selecting strategies for change Choosing a strategy for the change process depended upon various factors and good interpersonal relationship was a critical factor. It has been proposed that strong leadership and excellent communication skills were essential if an atmosphere of trust was to be engendered [ 7 , 8 ]. With this in mind, the change was announced in advance to encourage the nurses. It also offered the opportunity to share the reaction of colleagues where some valuable proposals were proposed, for example, how to cater for lateness at work, non-overlapping of shift as well as dealing with confidentiality of information. Confidential issues related to matters that the patients brought up during the admission procedure and during their stay, certain issues that were brought up during ward rounds and from the patients own requests. In cases of occasional lateness in resuming work, the handover would proceed with the other patients in first the instance and if the staff was still late, then some other colleague would step in her place. Reassurance was given with respect to 'no substantial overlapping' of shift in that it would not have major bearing on the handover process by explaining that shorter handover can reduce the likelihood of information overload and result in concise and pertinent information being exchanged as per care plans. There was a general agreement that fifteen minutes as officially allocated for handover would be sufficient for this purpose. Assurance was also given that confidentiality of patients' clinical information would be taken into consideration in drafting a protocol for bedside handover, as shown in table 2 . Empowering the staff Several meetings were organized with different groups of nurses to explain and clarify any shortcomings and to reach a consensus. This approach was recommended by Driscol [ 4 ], as it empowers the team to make the change for itself, without instruction or oversight and is believed to be a strategy for an effective and lasting transformation in a team spirit. The empirical rational strategy was used to convince others of the veracity of the change by making reference to evidence base documentation on the positive outcomes that bedside handover might bring, for example, increase patient satisfaction. Nurses within the ring of informal leaders were gradually encouraged to take some of the ownership of the change by entrusting role model responsibilities to them. This proved to be quite successful as a strategy to encourage participation to create attitudinal and behavioral change. Eventually, there was more acceptance and collaboration on the part of the team to implement the change. In keeping with Skinner's theory [ 13 ], positive reinforcement, was used to praise and encourage staff. The ward manager helped in the reinforcement process by complimenting the whole team for their excellent effort to bring the change during the weekly meeting of staff. The strategy of facilitation also involved providing training in the new skill demanded by the change. Mocked handover exercises were demonstrated with the different steps of bedside handover to different groups of nurses. This was done by adopting a democratic leadership style engendering a participative approach, which in turn generated a degree of enthusiasm for the change. Moving stage Following a pilot handover session involving senior staff in a participant and an observer capacity over 2 morning and 2 evening handover sessions, which did not require any major changes, implementation of the bedside handover was started on 8 th of March 2003. For the first week, six senior staff who had experience in this area volunteered and took turn to continue to be present in as many handovers as observers and participants, to monitor and reinforce the established protocol step by step. They also provided clarification and support to staff in cases of difficulty, and helped evaluate the extent of change that had taken place in an effective manner. The nurses present during the handover had no difficulty in adapting to this new situation, using a care plan incorporating a more psychosocial and patient-centered approach to bedside handover with the patients' participation. Results Evaluation of the change The evaluation of the implementation of bedside handover was carried out in two distinct phases. A protocol, as shown in table 2 , was developed which included 6 criteria was duly filled after every shift handover. As a benchmark, a good handover was one where at least five of the criteria were strictly followed. The data collection consisted of ten non-participant observation handovers. Semi-structured interviews, using a questionnaire derived from a focus group of staff and patients as shown in table 3 , with 40 patients were carried out to get their perceptions of the new handover. This was done randomly, consisting of both morning and evening handovers over a period of a week by a staff specifically chosen for this job from another ward to prevent bias from the hawthorn effects and ensure validity. Table 3 Evaluation of bedside handover from patients' perspectives – Results of semi-structured interviews with 40 patients 1. Do the outgoing and incoming nurse come to your bedside to handover in the morning and in the evening during the change of shifts? 95% – yes 2. How do you feel about their presence at your bedside to discuss your care? 100% – ok and most of them said it was a good thing 3. Do the nurses involve you in your care planning? 80% – yes, 10% – to a certain extent, 10% not sure 4. Are you satisfied with the way information about your care is passed on and followed by the incoming nurses? 100% – no problem 5. How do you feel issues of confidentiality are handled? 100% – sensitively 6. Any other comments you would like to make to improve on shift handovers? 1) Satisfied – 100% Other comments: 2) Doctors and other professionals to adopt this approach 3) Nurses should spend more time talking to them, not during the handover period only 4) Would like this to happen in all wards Analysis of results of the observational data on 10 handovers, Table 2 , showed that the first 5 criteria were met at 100% and the 6 th criteria at 90%. In one of the sessions, the nurse had left the patient whilst the bedside handover was in progress to attend to another patient without explaining the reason for this short absence to him which accounts for the 90%. Analysis of the results of semi-structured interviews with 40 patients, Table 3 , show that a 96% overall satisfaction level was achieved. This was beyond our expectations, as we had targeted a success rate to be 80% initially. We had to be cautious about the result for it could be either most of the staff had accepted the change or just doing it in this euphoric phase. Refreezing phase The result was evaluated at a full staff meeting and the ward manager and colleagues recognized the change. Despite unlearning of the old practice had taken place two nurses still displayed some difficulties with the new handover as they were always eager to report everything themselves rather than allowing the patients to have a say. After a reassessment of the situation, accurate feedback was given to them. With the group support, they became used to the new system by observing their colleagues in action during the handover and doing it in turn. After a couple of sessions they became fully conversant with the new system. By this time, this project was ready for the refreezing stage. Discussion One of the major difficulties encountered was to rally everybody behind this project. The normative re-education, in line Bernhard and Walsh [ 1 ], was used in order to help nurses value the new knowledge and create a readiness for learning. Various tasks identified for the future, for example on how to deal with issues of confidentiality, patients who would keep talking endlessly making the process drag on for a long time were allocated to members of the team according to their expertise to prepare so that they could be discussed in depth during the next meeting. A flexible and humanistic in approach was adopted in dealing with conflict, and resistance was not underestimated. Suggestions were treated with respect and dignity. Considerable effort was made to maintain good interpersonal relationship and to highlight motivating factors and safety needs. Constructive feedback was provided on their level of performance. Positive behaviors were rewarded equally in terms of recognition and praise and often with a simple and genuine "thank you". Application of this knowledge was reinforced from day one when this new handover became operational into the practice area through continuous coaching, supervision and mentorship. Conclusion Managing change in a hospital set up is a daunting task as it involves a change in the attitude and behavior of staff in a complex environment in order to gain their collaboration. The concept of no pain no gain was very evident throughout the process. Lewin's 3 – stage model was useful in implementing the change in a planned and structured way. Resistance was overcome by creating a climate which encouraged open communication. The support of the ward manager and key stakeholders were significant. Evaluation has shown that the new system of handover is working well but monitoring will be ongoing with evaluation of a larger sample of patients. This change has been an enriching experience for the staff, and has generated enthusiasm and given them confidence to question some of the practices on the ward. This new approach to handover can therefore be implemented in other areas of practice and evaluated to ensure that they are meeting patients' satisfaction. Further studies can be undertaken to explore how the multidisciplinary team could further consolidate this process. Competing interests The author(s) declare that they have no competing interests. Authors' contributions HKK taught this module and supervised this change management project. ZBJ implemented this change in the gynaecological ward as part of her assessment in the "Management Development" module. Both authors wrote this manuscript, read and approved the final version. Pre-publication history The pre-publication history for this paper can be accessed here:

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545214

Nepal's War and Conflict-Sensitive Development

I would like to share my experience from nearly a decade of civil war between the Maoist rebels and the Royal Nepalese Army in Nepal in reference to the article by Zwi [1] on the expanding role of health communities in times of conflict. The current war in Nepal has led to widespread destruction of limited infrastructure and has adversely impacted access to health-care services and personnel, affecting family planning, maternal and child health programs, and immunization services throughout the country. While Nepal is flooded with non-governmental organizations, paradoxically, humanitarian assistance may have unknowingly exacerbated the conflict by perpetuating the same inequalities that led to the conflict in the first place. This has brought to the fore the need for “conflict-sensitive development” [2] —development sensitive to the (conflict) environments in which they operate, in order to reduce the negative impacts of their activities—and to increase their positive impacts—on the situation and its dynamics. Development projects can continue in less affected areas with a need for transitional programs in conflict areas that can adapt to the rapidly changing environment. If agencies are unable to function, they have required the help of humanitarian agencies such as Médicins Sans Frontières with experience in conflict settings. Some agencies have adopted a participatory role in development and have involved neutral local agencies, increasing community participation in their projects with good success. But there is a need for increasing coordination between organizations working in various health-related projects. Health-care workers across the world in different conflicts are in a unique position to leverage something of universal importance—the promise of good health [3] . Raising awareness of the issues surrounding conflicts will act as a catalyst for change.

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539042

The Commercialisation of Medical and Scientific Reporting

Commercial influences on research results can in turn lead to "hype" in science and medicine news stories

There is a growing recognition of the importance of the popular press in the communication of science. The media is often the primary source of science information and, as such, can have a profound impact on how the public views the risks and benefits of scientific advances. Dorothy Nelkin suggests that the “media serve as brokers between science and the public, framing the social reality for their readers and shaping the public consciousness about science related events” [1] . Because of this influential role, many commentators have been highly critical of the quality of media reporting, suggesting that reporting is “hyped”, irresponsible, and hurtful to the public's understanding of important scientific issues. In 1999, the United Kingdom House of Commons Science and Technology Committee was concerned enough to recommend that the media be governed by a Code of Practice that “stipulates that scientific stories should be factually accurate” [2] . But is it fair to point an accusing finger solely at the popular press? There are many examples of science reporting that has been less than perfect, such as the coverage of behavioural genetics and human cloning. And there is no doubt that an entertaining or controversial spin will win out over a muted message. But there is also evidence that the media does a surprisingly good job [3] , often accurately conveying information found in peer-reviewed journals. A more subtle problem, and one that may have more long-term implications than simply bad reporting, is the faithful portrayal of commercially influenced research results. A Marketing Message? There is an expanding body of evidence that suggests that the increasingly commercial nature of biomedical research is having an impact on how science stories are portrayed. Studies have shown that papers in peer-reviewed journals are more likely to contain positive findings if the research is funded by industry [4] . A study that examined pharmaceutical research found that “among the authors of original research papers, reviews and letters to the editor that were supportive of the drugs' use, 96% had financial relationships with the drugs' manufacturers; for publications deemed neutral or critical the figure was only 60% and 37% respectively” [ 5 , 6 ]. To make matters worse, there is also evidence that negative results are either de-emphasised or simply not published [ 7 , 8 ]. This bias is picked up by the popular press and conveyed, largely uncritically, to the public [3] . Commercial influences can spin a story Commercial influence on public representations of science has the potential to create a skewed picture of biomedical research—a picture that emphasises benefits over risks, and predictions of unrealistic breakthroughs over a tempered explanation of the incremental nature of the advancement of scientific knowledge. In the area of genetics, for example, there is concern that this commercial influence will lead to a simplistic and overly deterministic view of the role of genes in human health and may have an adverse impact on public dialogue [1] . There is also concern that it will create unrealistic expectations about a given scientific advance or product. In the context of health care, this may lead to inappropriate and expensive utilisation patterns. Given the increasingly close connection between the media's portrayal of science and the broader agenda of commercialisation, some media representations can be viewed as a subtle form of marketing, albeit often inadvertent. One commentator has gone so far as to suggest that, to a large degree, “medical news is actually unpaid advertising” [9] . Further Reading on Media Hype Blum D Knudson M 1997 A field guide to science writing: The official guide of the national association of science writers New York Oxford University Press 304 p Bernhardt BA Geller G Tambor E Mountcastle-Shah E Mull JG et al 2000 Analysis of media reports on the discovery of breast and prostrate cancer susceptibility Am J Hum Genet Suppl 2 76 62 Caulfield T 2000 Underwhelmed: Hyperbole, regulatory policy and the genetic revolution McGill Law J 45 437 460 12688281 Cohn V Cope L 2001 News and numbers: A guide to reporting statistical claims and controversies in health and related fields, 2nd ed Ames (Iowa) Iowa State University Press 211 p Condit CM 1998 Determinism and mass media portrayals of genetics Am J Hum Genet 62 979 984 9529342 Conrad P 1999 Uses of expertise: Sources, quotes, and voice in the reporting of genetics in the news Public Underst Sci 8 285 302 Garfield E 1979 SIPI: Scientists taking scientific information to the public Curr Contents 41 290 293 Geller G Bernhardt B Holtzman N 2002 The media and public reaction to genetic research JAMA 287 773 11851549 Moynihan R Bero CL Ross-Degnan D Henry D Lee K et al 2000 Coverage by the news media of the benefits and risks of medications N Engl J Med 342 1645 1650 10833211 Nelkin D Lindee MS 1995 The DNA mystique: The gene as a cultural icon New York W. H. Freeman 312 p Hargreaves I Lewis J Speers T 2003 Toward a better map: Science, the public and the media Swindon (United Kingdom) Economic and Social Research Council Available: http://www.esrc.ac.uk/esrccontent/DownloadDocs/Mapdocfinal.pdf . Accessed 28 September 2004 Ransohoff D Ransohoff R 2001 Sensationalism in the media: When scientists and journalists may be complicit collaborators Eff Clin Pract 4 185 188 11525108 This is not to say that science reporting is part of a coordinated effort to promote a particular product. On the contrary, there is rarely a specific product to promote, and the media is just looking for an interesting and intriguing story that will help sell papers. However, in the long run, a continued, systemic trend toward positive, industry-influenced reporting may operate in much the same way as an explicit promotional campaign. In fact, optimistic media portrayals could be considered more powerful than promotional campaigns. The message is separated from an obvious marketing agenda and often includes a trusted voice, such as a university-based researcher. Paradoxically, this trust is based in part on a belief in the perceived independence of university researchers. Balancing the Message There is nothing inherently wrong with commercial involvement in biomedical research. After all, in most countries with an advanced biomedical research infrastructure, commercial entities, rightly or not, are an essential element of the technology-development process. Nevertheless, we need to be sensitive to the influence of market forces on how science is represented to the public. Eventually, the public will catch on. And when they do, public trust in the biomedical research enterprise may be irreparably harmed. In an increasingly knowledge-based economy, there seems to be little doubt that private industry will continue to play a significant role in the funding of science. The research community must adjust to this inevitability by taking steps to ensure that portrayals of science remain as balanced as possible. As thoughtfully noted by Tom Wilkie: “If science is to manage the transition from its older, academic tradition to a new style, while keeping popular assent and the popular image of science as an impartial means of getting at the truth, then the scientific community itself must recognise the importance of maintaining impartial sources of public information.” [10] What can be done? For a start, reporters should always ask for and researchers should always offer information about the nature of the funding and the financial relationship of the researchers to the sponsor. Increasingly, this information is disclosed in peer-reviewed journals. However, it may not be communicated in other popular representations of research results. As motivation, the research community should remember that the media also likes a good conflict-of-interest story [11] . Complete transparency should be the understood standard practice. The research community should also consider the establishment of various sources of independent science information, including a venue for the publishing of negative results and a list of respected researchers who may be able to provide an alternative view. Not only would this create an outlet for results that do not correspond with commercial interests, it would also serve as a resource for the media. Reporters are often under extremely tight deadlines, and it is not always easy to find an independent second opinion, an indispensable component of balanced reporting. Naturally, commercial pressure isn't the only source of science hype, and it is understandable that researchers may want to promote their latest findings. But commercial influence is emerging as a known source of bias, and it is a phenomenon that could have a profound impact on how the public perceives the entire research enterprise. Developing strategies, starting with the modest ones suggested above, seems to be an essential element of any communication strategy.

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A robust two-way semi-linear model for normalization of cDNA microarray data

Background Normalization is a basic step in microarray data analysis. A proper normalization procedure ensures that the intensity ratios provide meaningful measures of relative expression values. Methods We propose a robust semiparametric method in a two-way semi-linear model (TW-SLM) for normalization of cDNA microarray data. This method does not make the usual assumptions underlying some of the existing methods. For example, it does not assume that: (i) the percentage of differentially expressed genes is small; or (ii) the numbers of up- and down-regulated genes are about the same, as required in the LOWESS normalization method. We conduct simulation studies to evaluate the proposed method and use a real data set from a specially designed microarray experiment to compare the performance of the proposed method with that of the LOWESS normalization approach. Results The simulation results show that the proposed method performs better than the LOWESS normalization method in terms of mean square errors for estimated gene effects. The results of analysis of the real data set also show that the proposed method yields more consistent results between the direct and the indirect comparisons and also can detect more differentially expressed genes than the LOWESS method. Conclusions Our simulation studies and the real data example indicate that the proposed robust TW-SLM method works at least as well as the LOWESS method and works better when the underlying assumptions for the LOWESS method are not satisfied. Therefore, it is a powerful alternative to the existing normalization methods.

Background Microarray technology has become a useful tool for quantitatively monitoring gene expression patterns and has been widely used in functional genomics [ 1 , 2 ]. In a cDNA microarray experiment, cDNA segments representing a collection of transcripts and Expressed Sequence Tags (ESTs) are amplified by PCR and spotted in high density on glass microscope slides using a robotic system to produce cDNA microarrays. Each microarray contains thousands of such PCR products, named cDNA probes, which serve as reporters for the expression of the respective transcripts that represent the collection of genes or ESTs. The cDNA microarrays are queried in a co-hybridization assay using two fluorescently labeled biosamples derived from RNA obtained from the cell populations of interest. One sample is labeled with fluorescent dye Cy5 (red), and another with fluorescent dye Cy3 (green). Hybridization is assayed using a confocal laser scanner to measure fluorescence intensities, allowing simultaneous determination of the relative expression levels of all the genes represented on the slide [ 3 ]. A basic question in analyzing cDNA microarray data is normalization, the purpose of which is to remove systematic bias in the observed expression values by establishing a normalization curve across the whole dynamic range. A proper normalization method ensures that the normalized intensity ratios provide meaningful measures of relative expression levels. Normalization is needed because many factors, including different efficiency of dye incorporation, difference in the amount of RNA labeled between the two channels, uneven hybridizations, difference in the printing pin heads, among others, may cause bias in the observed expression values. Therefore, proper normalization is a critical component in the analysis of microarray data and can have important impact on higher level analysis such as detection of differentially expression genes, classification, and cluster analysis. Many normalization methods have been proposed in the literature. The earliest normalization method for cDNA microarray data goes back to Chen et al. [ 4 ] who proposed a ratio-based method. Yang et al. [ 5 ] summarized several normalization methods for cDNA microarray data such as global normalization, dye-swap normalization, block-wise normalization, and scale normalization. They also proposed a locally weighted scatter plot smoothing (LOWESS [ 6 ]) method for intensity dependent normalization. Quackenbush [ 7 ] and Bilban et al. [ 8 ] provided good reviews on normalization methods for cDNA microarray data. Tseng et al. [ 9 ] proposed using a rank based procedure to first select a set of invariant genes that are likely to be constantly expressed and then carrying out LOWESS normalization using this set of genes. But as pointed out by Tseng et al., selected invariant genes may not cover the whole dynamic range of the expression values, and extrapolation is needed to fill in the gaps that are not covered by the invariant genes. Kepler et al. [ 10 ] also first estimated a set of "constantly expressed genes" and then used the LOWESS method. Wang et al. [ 11 ] proposed an iterative normalization method for cDNA microarray data by estimating a normalization coefficient and identifying control genes. Workman et al. [ 12 ] used array signal distribution analysis for a robust non-linear method of normalization. Park et al. [ 13 ] compared a number of normalization methods, including global, linear and LOWESS normalization methods. Wolfinger et al. [ 14 ] used a mixed model for normalization. They proposed a normalization model for normalization and a gene model for inference and these two models are related by the residual terms in the normalization model. A constant normalization factor assumption is needed in this method. Fan et al. [ 15 ] considered a Semi-linear-In-slide Model (SLIM) method using within-array replications. The SLIM method requires replication of a subset of the genes in an array. If the number of replicated genes is small, the expression values of the replicated genes may not cover the entire dynamic range or reflect spatial variation in an array. Fan et al. [ 16 ] generalized the SLIM method to account for across-array information, resulting in an aggregated SLIM, so that replication within an array is no longer required. Huang et al. [ 17 ] proposed a two-way semi-linear model (TW-SLM) for normalization of cDNA microarray data. They used the least squares method for estimating the normalization curves based on B-splines. This method does not require the assumptions required by the LOWESS normalization method, i.e. (i) a small fraction of genes are differentially expressed or (ii) there is symmetry in the expression levels of up- and down-regulated genes. It is well known that the least squares method is not resistant to outliers which arise often in cDNA microarray experiments because of many sources of variations. In this paper, we propose a robust method for normalization in the framework of the TW-SLM. We conduct simulation studies and use a real cDNA microarray data set to compare the proposed method with the LOWESS normalization method. Results Simulation study Simulation was conducted to compare the mean square errors (MSE) and biases of estimated gene expression levels between the proposed robust TW-SLM and LOWESS normalization methods, between the proposed method and the TW-SLM using OLS. The MSE for the j th gene is calculated as the following: that is, , where N is the total number of replicates for each simulation, J is the number of unique genes, β j is the true gene expression level (base two log scale) for gene j , is the estimated value for β j , is the mean of for N replicates, j = 1, 2,..., J , where J is the total number of genes. The data simulation procedure is based on the method proposed by Balagurunathan et al. [ 18 ]. In each simulation, we generated 10 slides with twelve blocks in each, and 500 genes in each block. We repeated 100 times for each simulation. The simulation procedure can be summarized in the following steps: 1. Simulate true signal intensity for each gene j using the exponential distribution with the mean of 3,000, i.e. I j ~ exp( λ = 1/3000), for j = 1,..., J ; 2. Simulate fluorescent intensity for the Cy5 channel and the Cy3 channel with the normal distribution, respectively. Suppose the coefficients of variation for intensity in the Cy5 channel and the Cy3 channel are α rj and α gj , respectively, then the fluorescent intensity on the two channels can be generated by the normal distribution with mean I j and standard deviations α rj I j and α gj I j for the red channel and the green channel, respectively. Let R j and G j represent simulated fluorescent intensity for the Cy5 channel and the Cy3 channel for gene j , respectively; 3. Simulate differentially expressed genes. Suppose γ × 100% genes are differentially expressed in the whole simulated gene set, then the ratio of the expression level for gene j can be generated by t j = 10 ± b with b ~ Beta (1.7,4.8). The sign ± will determine if the gene is up- or down-regulated. The probability of the up-regulated genes within those γ × 100% differentially expressed genes is given as an input parameter. For the genes that are not differentially expressed, the b takes value zero; 4. Incorporate the t j into signal intensity of gene j . The R j and G j will be adjusted by adding the simulated expression ratio t j through the following formulae: for j = 1,..., J ; 5. Simulate a fluorescent system with the imperfect response characteristics. Due to various reasons, such as the unequal amount of mRNA for the two channels, different labeling efficiencies, or uneven laser powers at the scanning stage [ 18 ], actual intensity in the two channels are not exactly the same. More over, fluorescent intensity is not necessarily linearly related to the expression levels. Balagurunathan et al. proposed the following functional family, to distort the response characteristic functions of observed fluorescent intensity for the two channels, which are expressed as and , respectively. So four parameter values need to be determined for each channel before simulation. Different parameter values in the two channels will control the shape of the ratio vs. signal intensity plots (R-I plots); 6. Simulate background noise for each channel. The mean of background noise is determined by one input parameter: the signal to noise ratio (SNR) and the true mean of signal. The SNR is the ratio between the true mean of the signal and the true mean of background noise. The SNR controls variability of background noise. The normal distribution with a given mean value is used in simulating background noise. Variance of background noise will be controlled by the input parameters α br and α bg for the Cy5 channel and the Cy3 channel, respectively. These two parameters are the ratios between the mean and the standard deviations of background noise for the two channels, respectively. Simulated signal intensity for the two channels, and , are adjusted by subtracting background noise in each channel. Let and still denote background adjusted signal intensity for the two channels; 7. Add noise to the signal intensity for each channel. Finally, the signal intensity of each channel is generated by with , where α 1 ~ U ( a 1 , b 1 ), α 2 ~ U ( c 1 , d 1 ), α 3 ~ U ( a 2 , b 2 ), α 4 ~ U ( c 2 , d 2 ). The a 1 , b 1 , c 1 , d 1 , a 2 , b 2 , c 2 , d 2 are given as input parameters to control variability of fluorescent signal intensity. We simulated two situations, one is the no-dye bias case and another one is the shape case (dye bias exists). R-I plots of twelve blocks on one slide for two simulated cases are shown in Figures 2 and 3 , respectively. We considered five different percentage levels of differentially expressed genes: 1%, 5%, 10%, 20%, and 40%. The ratio of the up-regulated genes to the down-regulated genes takes three values, i.e., 1:1, 3:1, and 9:1 at each percentage level of differentially expressed genes. In addition, based on the suggestion of a reviewer, we simulated an extreme case for the scenario in Figure 3 , in which 70% genes are all up-regulated and the remaining ones are not differentially expressed. The trend of MSEs and biases of estimated gene expression levels are similar between the robust TW-SLM and the LOWESS normalization methods across different levels of the ratios between the up-regulated genes and the down-regulated genes. This trend also exists in the extreme case. We present the results of the following two scenarios: (a) a 9:1 ratio between the number of the up-regulated genes and that of the down-regulated genes and, (b) the extreme case. Tables 1 and 3 present MSEs, Tables 2 and 4 show biases of estimated gene expression levels. MSEs and biases for the extreme case (70% of the genes are up-regulated) are presented in the bottom of Tables 3 and 4 , which are displayed in Figures 6 and 7 , respectively. The robust TW-SLM method has smaller means of MSEs than the LOWESS normalization method and the TW-SLM using OLS, respectively. Also the ranges of MSEs for the proposed method are also smaller than those using the LOWESS method and the TW-SLM with OLS, respectively. Comparing the different robust weight functions, means of MSEs are slightly smaller using Tukey's weight function than that using Huber's weight function. These results are observed across different percentage levels of differentially expressed genes. Biases for estimated gene expression levels distributed similarly between the proposed method and the LOWESS normalization method. But the ranges of the biases for the proposed method are smaller than those of the LOWESS normalization method and the TW-SLM using OLS, respectively. These observations are true in both simulated situations. The extreme case is an example where the proposed method does better than the LOWESS method (Tables 3 and 4 , Figures 6 and 7 ). Estimates using the LOWESS method are downward biased in this case. This is what we would expect because the LOWESS method fits normalization curves through the majority of genes, which are mostly up-regulated here. In contrast, the TW-SLM method does not need the either of the two assumptions needed by the LOWESS method, neither of which is satisfied here. The distributions of MSEs and biases between the TW-SLM using OLS and the LOWESS method are similar for cases where there is a relatively small percentage of differentially expressed genes. However, the TW-SLM with OLS performs better than the LOWESS when a larger proportion of genes are differentially expressed. It appears that the more deviation from the two assumptions required by the LOWESS, the better the TW-SLM performs. This trend is consistent with findings in our previous work [ 17 ]. An example In this section, a real data set was analyzed to compare consistency of the LOWESS normalization method and the proposed robust TW-SLM method. A collection of human placenta cDNAs comprising 7,042 clones was identified and used as the probe set for cDNA microarray fabrication in this study [ 19 ]. Three kinds of RNA samples were used which include: (i) a common reference RNA obtained by in vitro transcription from a pool of cDNAs in equal amount comprising the entire probe set (PS); (ii) the "Universal Human Reference RNA" from Stratagene, a pool of RNAs derived from 10 different cell lines; and (iii) human full-term placenta RNA. The original goal of the study was to evaluate the performance of the PS RNA as a reference RNA in comparison with that of Stratagene's universal reference RNA. In this study, the Universal Human Reference RNA and the human placenta RNA were treated as two experimental samples. The PS RNA was used as the reference against which the two other bio-samples were compared. In the simple direct comparison, gene expression values were obtained through direct hybridizations between the human placenta RNA and the Universal Human Reference RNA. In the indirect comparison using the PS set as the common reference, hybridizations were performed between the human placenta RNA and the PS reference RNA, and between the Universal Human Reference RNA and the PS reference RNA. The design of this experiment is depicted in Figure 1 . After hybridization, slides were scanned with the Axon instruments 4000B scanner. The 633 and 532 lasers are used for excitation of the Cy5 and Cy3 fluorophores, respectively. For each of the three types of hybridizations (i.e., the human placenta vs. the universal reference, the human placenta vs. the PS reference, and the universal reference vs. the PS reference), there are four slides, including two dye-swapped slides. Each clone was printed three times on different blocks on each slide. Background adjusted medians for the Cy5 and Cy3 channels were used as expression levels. We removed negative controls including "Human Cot1", "PolyA" and "Empty" in the analysis. To evaluate the proposed method, we compare it with the LOWESS method by examining which method produces more consistent results between the direct comparison and the indirect comparison of human placenta and universal human reference RNA samples as described above (see also Figure 1 ). The rationale is that the results from the direct comparison design and the indirect comparison design should be similar, because the same RNA samples are compared in both designs, albeit the indirect comparison is through a third common reference. Therefore, a better normalization method is the one that yields more consistent results between the direct and indirect comparison experiments. The data were normalized using the LOWESS normalization method and the robust TW-SLM with Tukey's robust weight function separately. Significance analysis was carried out for the normalized data for each method by comparing gene expression levels in the human placenta tissue relative to the universal reference. One sample t-test was used for the direct comparison and two-sample t-test was used for the indirect comparison. We used 10 -5 and 10 -3 as cutoff points for p-values to determine if clones are statistical significant or not. Consistency of estimated relative gene expression levels was compared between the direct design and the indirect design for each method. We also compared overlap between the LOWESS normalization method and the robust TW-SLM for each design. The results are presented in Figures 4 and 5 . We used 10 -5 as a cutoff point for p-values in Figure 4 . Using the robust TW-SLM normalization and the t-tests, there are 2,907 genes with p-value less than 10 -5 in the direct comparison and 2,791 in the indirect comparison. There are 1,713 genes common in these two sets of genes with p-value less than 10 -5 , which account for about 59% (1713/2907) in the direct comparison and about 61% (1713/2791) in the indirect comparison. In comparison, using the LOWESS normalization and the t-tests, there are 1,447 genes with p-value less than 10 -5 in the direct comparison and 1,045 in the indirect comparison. The number of overlapping genes with p-value less than 10 -5 is 467, which is around 32% (467/1447) in the direct comparison and about 44% (467/1045) in the indirect comparison. It is clear that the proposed method performs more consistent between the direct comparison and the indirect comparison. We also examined overlap between the LOWESS and robust TW-SLM methods for the two comparisons. In the direct comparison, about 79% (1141/1447) of the genes found to be significant based on the LOWESS method are also found to be significant based on the robust TW-SLM method. But they only account for about 40% (1141/2907) of the significant genes detected based on the robust TW-SLM method. In the indirect comparison, about 71% (738/1045) of the significant genes based on the LOWESS method are also found to be significant based on the robust TW-SLM method. But they only account for about 26% (738/2791) significant genes detected based on the robust TW-SLM method. In our analysis, we used background adjusted intensity values. How to adjust background is an important issue in microarray data analysis. To evaluate if background affects our conclusions, we repeated the comparison analysis without adjusting background for the intensity values in both channels, the results are presented in Tables 5 and 6 . We see from these tables that the overall results are similar to those using background adjusted intensity values in normalization. This is what we would expect because of low and uniform distributed background noise in all arrays in this example (data description is not shown). Therefore, the robust TW-SLM method yields more consistent results between the direct comparison and the indirect comparison with the human placenta and the universal human reference RNA samples. In addition, the robust TW-SLM method detects more significant genes for a given cutoff p-value. This makes sense biologically because most of the 7,042 genes specifically discovered from human placenta are expected to have differential expressions relative to the universal reference RNAs. We would expect that the similar comparison results will be got if we compare the TW-SLM using OLS or Huber's weight function with the LOWESS method because the normalization curves for the TW-SLMs (TW-SLM:OLS, TW-SLM:Huber, TW-SLM:Tukey) are similar, but all these three curves are different from the LOWESS normalization curve (Figure 8 ). Discussion We have proposed a robust TW-SLM normalization method for cDNA microarray data. It is interesting to compare the proposed normalization method with the existing methods, such as the widely used LOWESS normalization proposed by Yang et al. (2001) [ 5 ] and further discussed by Tseng et al. (2001) [ 9 ]. In the LOWESS method, normalization is done separately by first fitting a separate curve for each slide through the R-I plot of log-intensity ratios versus log-intensity products. In comparison, the proposed method uses all the slides in estimating each normalization curve, using the gene effects β j as the thread linking these slides. In addition, in the proposed method, the normalization curves φ i and gene effects β j are estimated simultaneously. With this approach, there is no need to assume that the percentage of genes with differential expression levels is small or the expression levels of up- and down-regulated genes are symmetric, or when one of these assumptions is not satisfied, to use dye-swap normalization, which in turn requires the assumption that the two normalization curves are symmetric. (However, we note that dye-swap as a design strategy is useful to balance the experimental conditions and reduce bias due to different dye incorporation efficiencies.) An underlying condition required for the proposed method is independence of arrays, which is satisfied in a typical microarray experiment. Further theoretical conditions for the TW-SLM can be found in the paper by Huang et al. [ 17 ]. We have only considered the proposed robust TW-SLM method for the simple direct comparison design described in the Methods section. We can easily extend the method to more complicated designs. For example, we can adapt the proposed robust method to the TW-SLM that accommodates the design where a gene is printed multiple times. Such a design is helpful for improving the precision and for assessing the quality of an array using the coefficient of variation (Tseng et al. 2001 [ 9 ]). We can also adapt the robust TW-SLM to incorporate control genes with known concentration ratios in estimating the normalization curves. Model (1) can be easily extended to block-wise normalization by treating different blocks as separate arrays and normalization can be carried out as what we did here. Block-wise normalization considers spatial variation within an array. We did block-wise normalization on the data sets in the example and compared the results with that using the LOWESS method (Tables 5 and 6 ). The proposed method still outperforms the LOWESS method if we use block-wise normalization in this example. Conclusions In our simulation studies, the proposed method performs better than the LOWESS normalization method in terms of MSEs of estimated gene effects in the simulation models we considered. Analysis of the probe set reference data set [ 19 ] shows that the proposed method yields more consistent results between the direct and indirect comparisons than the LOWESS normalization method. In addition, the proposed method is more sensitive in detecting differentially expressed genes than the LOWESS method. Therefore, we believe that the proposed robust TW-SLM method is a powerful alternative to the existing normalization methods. We have coded the proposed method in an R package which is available from the corresponding authors. Methods We first describe the TW-SLM. For simplicity, we focus on the case of comparing two cell populations, in which two cDNA samples from the respective cell populations are competitively hybridized on the same array. Let n be the number of slides, and J be the number of genes in the study. Let R ij represent background corrected signal intensity from the Cy5 channel and G ij the background corrected signal intensity from the Cy3 channel, and let y ij = log 2 ( R ij / G ij ), x ij = (1/2) log 2 ( R ij × G ij ), for gene j on slide i . We assume that there is only one spot for each gene on each slide. The TW-SLM [ 17 ] is y ij = φ i ( x ij ) + β j + ∈ ij , i = 1,..., n , j = 1,..., J (1) In this model, the observed log intensity ratio is decomposed into three components. The first component is φ i which is the intensity dependent normalization curve for slide i , the second component is β j which represents the relative expression value of the j th gene after normalization, the last one is the residual error term. Let be a robust estimator of the i th normalization curve φ i based on this model described above. The normalized data are Huang et al. (2004) [ 17 ] considered the least squares method for estimating φ i and β j in the TW-SLM. However, it is well known that least squares estimates are not robust against outliers which often arise in microarray experiments. Therefore, we propose to use the robust method [ 20 ] for estimating φ i and β j . This is done by minimizing the objective function where ρ is an appropriately chosen function for robust estimation, λ is the collection of the coefficients in the spline representations of φ i described below, σ is the scale parameter, and α is a constant to be described below. We note here that estimation of φ i , β j are done jointly and uses data from all the arrays. This is different from the LOWESS normalization method in which estimation of normalization curves are done array by array. We consider two ρ functions: Huber's ρ function and Tukey's biweight function. Huber's ρ function is Tukey's biweight function is Two other usefull functions derived from ρ , ψ and χ , will be used repeatedly in the description of the algorithm below. They are defined as ψ ( x ) = ρ '( x ), χ ( x ) = x ψ ( x ) - ρ ( x ).     (4) The expressions of these functions are given in the Appendix. We choose commonly used constants in the literature for Huber's and Tukey's functions, i.e., H = 1.345 and k = 4.685. The influence of the choice of these constants on normalization methods is beyond the scope of this study. We use the cubic B-splines [ 21 , 22 ] to approximate the normalization curves φ i . Specifically, let b 1 ,..., b K be K B-spline basis functions. We approximate φ i by where b ( x ) = (1, b 1 ( x ),..., b K ( x ))' and λ i = ( λ i 0 , λ i 1 ,..., λ iK )'. We estimate the parameters in model (1) by minimizing objective function (3) using an iterative procedure. Two steps, a location step and a scale step, will be used in the computation. Location step We use the following vector and matrix notations in describing the location step: B i = ( b ( x i 1 ), b ( x i 2 ),..., b ( x iJ ))', y i = ( y i 1 , y i 2 ,..., y iJ )'. Let and let for i = 1,..., n . Given the scale parameter σ , and satisfy the equations: where and because of identifiability requirement in the TW-SLM. We can solve these equations iteratively to obtain and . The derivations of these equations are given in the Appendix. Scale step According to Huber's proposal [ 23 ], the estimation equation for σ is where r ij = y ij - b '( x ij ) , and N is the total number of observations in the data set. In general, equation (8) does not have an explicit solution. So we use the following updating equation to compute the estimated scale parameter σ , In order to obtain the consistent scale estimator at the normal distribution and obtain the classic estimates when using the least squares objective function, i.e., , we used the constant suggested by Huber [ 23 ], where E Φ denotes expectation with respect to the standard normal distribution function Φ. The procedure described above is called an iterative reweighted least squares (IWLS) algorithm that is used in many non-least squares estimation problems. The implementation of the IWLS algorithm can be carried out using the following steps: 1. Initialize for j = 1,..., J and σ (0) = 1, , for i = 1,..., n , j = 1,..., J ; 2. Calculate according to equation (6) given β ( m -1) , σ ( m -1) and for i = 1,..., n , j = 1,..., J , m = 1,...; 3. Check convergence of λ i , β , and σ . If the convergence criteria is met, then stop, otherwise continue; 4. Update σ ( m ) by equation (9) given , , σ ( m -1) , and , and set σ ( m -1) = σ ( m ) ; 5. Calculate weight given β ( m -1) , and σ ( m ) according to equation (5), and set ; 6. Calculate β ( m ) given σ ( m -1) and using equation (7), and set ; 7. Go to step 2 and iteratively update the estimators of parameters and the weights between steps 2 and 6 until convergence. Authors' contributions DW devised and implemented the procedure described in the paper, drafted and finalized the manuscript. JH helped with writing and revising the manuscript. JH and MBS supervised and provided support for this work. HX and LM conducted the experiment that generated the data set used in the example. Appendix Derivation of and We derive estimation equations for location parameters presented in the Methods section in this appendix. Again the notations from the Methods section: b ( x ) = (1, b 1 ( x ),..., b K ( x ))', λ i = ( λ i 0 , λ i 1 ,..., λ iK )'. φ i ( x ij ) can be approximated by a linear combination of B-spline basis functions, i.e. b '( x ij ) λ i , where b k ( x ij ) is the k th B-spline basis function of x ij . Let A = ( a 1 , a 2 ,..., a n )', C = ( c 1 , c 2 ,..., c n )', and define Given scale parameter σ , the first partial derivatives of S ( λ , β , σ ) (3) with respect to λ and β can be expressed in the matrix form as where B i ; = ( b ( x i1 ), b ( x i2 ),..., b ( x iJ ))', y i = ( y i 1 , y i 2 ,..., y iJ )', ψ ( x ) = ρ '( x ). As defined in equation (5) and W i = diag( w i 1 , w i 2 ,..., w iJ ), Plugging W i into equations (10) and (11) and setting them to zeros, and solving these two equations and yielding estimation equations for in equation (6) and in equation (7). They are Let then equation (7) can also be expressed as = ( Z'WZ ) -1 Z'W ( y - B ). The solution of ( Z'WZ ) -1 can be explicitly calculates using the following matrix, where , and for j = 1,..., J . We can get the explicit solution of after doing some linear algebra. It is for j = 2,..., J . And because of identifiability requirement in model (1). Derivation of scale parameter estimator The ψ and χ functions derived from Huber's ρ ( z ) function are The related weight function has the form where H is a constant. The constant α used in the scale step for Huber's robust estimation can be calculated as the following where Φ is the distribution function of the standard normal distribution, N is the total number of observations in the dataset, and p is the total number of parameters in the model. The ψ and χ functions derived from Tukey's ρ ( z ) function are The associated weight function has the form where k is a constant and the constant a in the scale step takes value where is the Chi-square probability function with n degrees of freedom evaluated at s . When Tukey's weight function is used, equation (8) is solved directly for the estimator of σ instead of iteratively updating equation (9) in our R program. It can be shown that equation (8) for Tukey's χ ( z ) function has an unique real root. This real root is just the solution for the estimator of σ . Let n * be the total number of observations that satisfy the second case of Tukey's χ function, i.e. | z | > k , let J * be the total number of clones that satisfy the first case of the χ , i.e. | z | ≤ k . Replacing z by and plugging Tukey's χ into equation (8), we get where Let Then equation (12) becomes ax 3 + bx 2 + cx + d = 0.     (13) Let x = y - b /3 a , divided by a in the both sides of equation (13), and plugs x into equation (13), then we get the Cardan's cubic equation Let p = c / a - b 2 /3 a 2 , q = d / a - bc /(3 a 2 ) + 2 b 3 /(27 a 3 ), the above equation becomes y 3 + py + q = 0.     (15) The determinant for Cardan's equation (15) is It can be shown that the determined function Δ must be positive. The first term in the determinant equation must be positive because of the square function and q cannot be zero. If we can show that the p is greater or equal to zero, then the Δ must be positive. Because So the Δ is positive if only if 3 ac - b 2 is non-negative. We can see that According to the Cauchy inequality [ 24 ], we have Therefore, the p must be non-negative and the Δ must be positive. Thus there is only one real root for equation (15), that is Then the solution for σ in equation (12) is

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545200

Educating the Brain to Avoid Dementia: Can Mental Exercise Prevent Alzheimer Disease?

Physicians often recommend to older adults that they should engage in mentally stimulating activity to reduce the risk of dementia. But is this recommendation based on sound evidence?

Physicians now commonly advise older adults to engage in mentally stimulating activity as a way of reducing their risk of dementia. Indeed, the recommendation is often followed by the acknowledgment that evidence of benefit is still lacking, but “it can't hurt.” What could possibly be the problem with older adults spending their time doing crossword puzzles and anagrams, completing figural logic puzzles, or testing their reaction time on a computer? In certain respects, there is no problem. Patients will probably improve at the targeted skills, and may feel good—particularly if the activity is both challenging and successfully completed. But can it hurt? Possibly. There are two ways that encouraging mental activity programs might do more harm than good. First, they may offer false hope. Second, individuals who do develop dementia might be blamed for their condition. When heavy smokers get lung cancer, they are sometimes seen as having contributed to their own fates. People with Alzheimer disease might similarly be viewed as having brought it on themselves through failure to exercise their brains. What Does the Evidence Show? Three types of evidence are cited to support the idea that mental exercise can improve one's chances of escaping Alzheimer disease. Epidemiological studies Having more years of education has been shown to be related to a lower prevalence of Alzheimer disease in cross-sectional, population-based studies [1] and to a lower incidence of Alzheimer disease in cohorts followed longitudinally [2] . Typically, the risk of Alzheimer disease is two to four times higher in those who have fewer years of education, as compared to those who have more years of education. Other epidemiological studies, albeit with less consistency, have suggested that those who engage in more leisure activities, especially activities that are mentally stimulating, have a lower prevalence and incidence of Alzheimer disease [ 3 , 4 ]. Additionally, longitudinal studies have found that older adults without dementia who participate in more intellectually challenging daily activities show less decline over time on various tests of cognitive performance [5] . How effective is mental exercise in holding back dementia? (Illustration: Sapna Khandwala, Public Library of Science) In epidemiological studies, people cannot be randomly assigned to different levels of education, or to different kinds and levels of participation in leisure activities. Consequently, researchers must try to identify confounders and take them into account analytically. However, uncertainties remain. Both education and leisure activities are imperfect measures of mental exercise. For instance, leisure activities represent a combination of influences. Not only is there mental activation, but there may also be broader health effects, including stress reduction and improved vascular health—both of which may contribute to reducing dementia risk [6] . It could also be that a third factor, such as intelligence, leads to greater levels of education (and more engagement in cognitively stimulating activities), and independently, to lower risk of dementia. Research in Scotland, for example, showed that IQ test scores at age 11 were predictive of future dementia risk [7] . Another problem with these epidemiological studies is that reverse causation could be involved—in other words, that incipient dementia could be causing reduced engagement in leisure activities, although some prospective studies have been particularly attentive to controlling for this possibility [8] . Clinical trials are needed to test the hypotheses that emerge from the best epidemiological research. Moreover, because the onset of Alzheimer disease can be hard to pinpoint, and early changes may occur years before the disease is diagnosed, conclusions must be based on large samples, followed over a long period of time. Randomized clinical trials Many studies support the possibility of enhancing memory and other cognitive performance, or of slowing cognitive decline in older adults without dementia [9] . The most effective programs teach mnemonic strategies, provide practice, and give supportive feedback. Mnemonic strategies include the organization of items into meaningful groups, the use of imagery, and the method of loci (visualizing items to be remembered in a sequence of specific, well-learned locations). Comprehensive programs can also include: encouraging memory aids (such as appointment books), teaching relaxation techniques, and providing instruction about memory changes in normal aging. However, improvements are not found in all studies. When improvements are found, they are often modest, may not be maintained over time, and do not generalize beyond the skill being trained. Often, the subjective gains rival the objective ones; for example, participants do tend to report fewer complaints about their memory. These limitations are evident in one of the largest randomized controlled trials of cognitive training with older adults, a large, multisite study named ACTIVE (Advanced Cognitive Training for Independent and Vital Elderly) [10] . Participants were assigned to receive training in one of three cognitive skills: memory, reasoning, or speed of processing. Tests of cognitive abilities given immediately after training showed large improvements on the particular cognitive skill on which the individual had been trained, but no transfer to the other two cognitive domains. Additionally, for the control group that received no training, simply taking the test battery at pre-test led to improvement on the post-test. The effects of training were maintained over a two-year follow-up. However, the cognitive training program had no significant effect on measures of everyday functioning. Finally, for participants in ACTIVE or in other memory training programs, it remains unknown whether eventual rates of Alzheimer disease will be reduced. Neurobiology studies The third type of evidence suggesting that mental exercise may help to prevent Alzheimer disease comes from neurobiology studies that show greater brain complexity in those with higher levels of mental activity. Many such studies, done with animals, show greater neural complexity after having been exposed to an enriched environment that provides lots of stimulation, for example by including wheels, tunnels, toys, and gnawing sticks [11] . One human study with magnetic resonance spectroscopy showed changes in the hippocampus in elderly memory training participants compared to controls [12] . Another report found changes on positron emission tomography scanning following two weeks of a comprehensive memory program that included memory training, special diet, physical exercise, and stress reduction [13] . Mental Exercise and Cognitive Reserve The concept of cognitive reserve is often used to explain why education and mental stimulation are beneficial. The term cognitive reserve is sometimes taken to refer directly to brain size or to synaptic density in the cortex. At other times, cognitive reserve is defined as the ability to compensate for acquired brain pathology. This definition encompasses coping skills as well as recruitment of other brain areas, with cognitive reserve thus accounting for individual differences in severity of cognitive dysfunction when there are pathological neural changes. People with a higher level of education have greater cognitive reserve. In some studies, education or occupation are even used as proxy measures of cognitive reserve, while others are beginning to measure neural substrates that correspond to reserve [14] . Taken together, the evidence is very suggestive that having greater cognitive reserve is related to a reduced risk of Alzheimer disease. But the evidence that mental exercise per se can increase cognitive reserve and stave off dementia is weaker. Epidemiological studies suggest that individual differences in cognitive reserve may actually be lifelong. In addition, people with greater cognitive reserve may choose mentally stimulating leisure activities and jobs, leading to a chicken-and-egg dilemma for the interpretation of the relationship between mentally stimulating activities in adulthood and dementia risk. Cognitive training has demonstrable effects on performance, on views of self, and on brain function—but the results are very specific to the skills that are trained, and it is as yet entirely unknown whether there is any effect on when or whether an individual develops Alzheimer disease. Further, the types of skills taught by practicing mental puzzles may be less helpful in everyday life than more prosaic “tricks,” such as concentrating, or taking notes, or putting objects in the same place each time so that they won't be lost. Conclusion So far, we have little evidence that mental practice will help prevent the development of dementia. We have better evidence that good brain health is multiply determined, that brain development early in life matters, and that genetic influences are of great importance in accounting for individual differences in cognitive reserve and in explaining who develops Alzheimer disease and who does not. At least half of the explanation for individual differences in susceptibility to Alzheimer disease is genetic, although the genes involved have not yet been completely discovered [15] . The balance of the explanation lies in environmental influences and behavioral health practices, alone or in interaction with genetic factors. For older adults, health practices that could influence the brain include sound nutrition, sufficient sleep, stress management, treatment of mood or anxiety disorders, good vascular health, physical exercise, and avoidance of head trauma. But there is no convincing evidence that memory practice and other cognitively stimulating activities are sufficient to prevent Alzheimer disease; it is not just a case of “use it or lose it.”

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514715

Lymphoedema management knowledge and practices among patients attending filariasis morbidity control clinics in Gampaha District, Sri Lanka

Background Little information is available on methods of treatment practiced by patients affected by filarial lymphoedema in Sri Lanka. The frequency and duration of acute dematolymphangioadenitis (ADLA) attacks in these patients remain unclear. This study reports the knowledge, practices and perceptions regarding lymphoedema management and the burden of ADLA attacks among patients with lymphoedema. Methods A semi-structured questionnaire was used to assess morbidity alleviation knowledge, practices and perceptions. The burden of ADLA attacks was assessed using one-year recall data. Results 66 patients (22 males, 44 females) with mean age 51.18 years (SD ± 13.9) were studied. Approximately two thirds of the patients were aware of the importance of skin and nail hygiene, limb elevation and use of footwear. Washing was practiced on a daily and twice daily basis by 40.9% and 48.5% respectively. However, limb elevation, exercise and use of footwear were practiced only by 21–42.4% (while seated and lying down), 6% and 34.8% respectively. The majority of patients considered regular intake of diethylcarbamazine citrate (DEC) important. Approximately two thirds (65.2%) had received health education from filariasis clinics. Among patients who sought private care (n = 48) the average cost of treatment for an ADLA attack was Rs. 737.91. Only 18.2% had feelings of isolation and reported community reactions ranging from sympathy to fear and ridicule. Conclusions Filariasis morbidity control clinics play an essential role in the dissemination of morbidity control knowledge. Referral of lymphoedema patients to morbidity control clinics is recommended.

Background Lymphatic filariasis, identified as one of the leading causes of permanent disability worldwide, has been targeted for global elimination [ 1 , 2 ]. Interrupting transmission and controlling morbidity are the twin pillars of the global filariasis elimination programme [ 3 ]. Mass drug administration (MDA) for control of transmission began in the filarial endemic areas of Sri Lanka in 1999 and to-date 5-6 rounds of treatment have been completed. Morbidity management for those with filarial lymphoedema is still in its infancy. A regime of rigorous skin hygiene and simple self-help measures such as limb elevation, exercise, use of topical antibiotics and antifungals aimed at minimizing episodes of acute dermatolymphangioadenitis (ADLA) attacks and lymph stasis is the model recommended by the World Health Organization for management of filarial lymphoedema [ 4 ]. Little information is available on the methods of treatment practiced by patients affected by filarial lymphoedema in Sri Lanka. Furthermore, the frequency and the duration of debilitating acute attacks in Sri Lankan patients with filarial lymphoedema remains unclear. The objectives of this study were to determine the knowledge, practices and perceptions regarding lymphoedema management and the burden of ADLA attacks among patients with lymphoedema attending filariasis morbidity control clinics in an endemic area. Methods The study was carried out in the Gampaha district in the Western province of Sri Lanka in November 2003. Ethical clearance for the study was obtained from the Ethics Committee, Faculty of Medicine, University of Kelaniya. Patients with lymphoedema attending morbidity control clinics conducted by the National Antifilariasis Campaign (AFC) were selected as the study population. These clinics are distributed in the operational areas of the AFC (Western, Northwestern and Southern provinces of Sri Lanka) and offer treatment exclusively to microfilaraemics and patients with chronic filariasis. Two weekly filariasis clinics (3.5 km apart) serve a population of 2,066,096 in a 1,387 km 2 area of the Gampaha district. A structured questionnaire was formulated to gather information on knowledge of lymphoedema management and limb care activities practiced along with frequency, treatment seeking behavior, cost and the degree of disability incurred in relation to ADLA attacks. A medical officer interviewed all patients regarding their disease history, examined and staged the limb affected by lymphoedema using World Health Organization criteria [ 5 ]. The presence of entry lesions, state of skin and nail hygiene of the affected part were recorded. Informed consent was obtained from the study participants prior to administering the questionnaire. The pre-tested questionnaire was administered in the local language: each patient was interviewed in depth by medical and paramedical staff (trained in lymphatic filariasis disability management) to explore their knowledge of lymphoedema management and the limb care activities practiced. The questions on lymphoedema management knowledge focused on the degree of importance attached to limb washing, elevation, exercise, nail hygiene, minimizing skin trauma, use of foot wear, intake of diethylcarbamazine citrate (DEC) and use of antiseptics/ topical antibiotics on entry lesions. The limb care activities practiced by the subjects were assessed by exploring how frequently they practiced the activities mentioned above in the knowledge component of the questionnaire. Questions were asked on prevalence of acute attacks during the preceding year, treatment seeking behavior during an acute attack, treatment cost per acute attack and the degree of disability incurred by an acute attack. An episode of ADLA was defined by the following criteria; painful swelling of the affected part with increased local warmth, redness and tenderness with or without associated constitutional symptoms such as fever, nausea and vomiting. Patient perceptions of disease reversibility and community attitudes towards their altered physical appearance were also explored. At the end of the interview all patients were educated on lymphoedema management practices recommended by the World Health Organization [ 5 ]. Results A total of 66 patients [male:female ratio 22 (43.3%): 44 (66.7%)] with a mean age of 51.18 years (SD ± 13.9) were enrolled in the study. A substantial proportion of this study sample (24.3%) had received only primary school level education. Most subjects had lymphoedema of a single lower limb [n = 56, 84.8%]. Both lower limbs were affected in 6 (9%), a single upper limb in 3 (4.4%) and a single upper limb and a breast in one subject. The oedema was completely reversible (stage 1) in 21 (31.8%) subjects; 30 (45.5%) were in stage 2. Subjects with non-reversible lymphoedema had associated shallow skin folds 11 (16.7%) (stage 3), one (1.5%) had skin knobs (stage 4) and three (4.5%) had deep skin folds (stage 5). The common entry lesions were sole fissures (n = 14), minor injuries (n = 5) and eczema (n = 2). Knowledge Knowledge and attitudes regarding lymphoedema management are summarized in Figure 1 . Almost two thirds of the population were aware of the importance of skin and nail hygiene, limb elevation and use of foot wear. However, exercising the affected part was considered important by only 21 (31.8%) subjects. Regular treatment with DEC and avoidance of certain food items (fatty foods) were considered as important measures by 92% and 30.3% of the subjects respectively. Most patients (71.2%) had received advice regarding lymphoedema management from the medical officer at the morbidity control clinic (65.2%), from general practitioners (7.6%) and public health inspectors (6.7%). Few had also acquired their knowledge by reading leaflets / booklets on lymphatic filariasis (18.2%). Figure 1 Lymphoedema management knowledge of the population. Washing: Washing the affected part with soap and water Avoidance of foods: Avoidance of food items Elevation: Keeping the affected limb elevated Exercise: Exercising the affected limb Nail hygiene: Keeping the nails of the affected limb clean and short Trauma reduction: Minimizing trauma to the affected part Entry lesion survey: Examining the affected part for entry lesions Antiseptics: Use of antiseptics on entry lesions on the affected part Footwear: Use of footwear for lower limb lymphoedema Practices Most of the study subjects washed the affected body part with soap and water either daily (n = 29, 40.9%) or twice daily (n = 32, 48.5%). A significant proportion of the study sample (n = 19, 29%) also used coir (coconut fibre) to rub the skin while washing. Half and one third of the study population practiced limb elevation on a regular basis while lying and sitting down respectively. Exercising the affected limb was practiced on a regular basis only by a minority (n = 4, 6%) of the patients. Footwear was used on a regular basis by 34.8% of the subjects, while 48.5% used them only outdoors. 7.6% of the sample did not use footwear at all. Almost all the subjects took DEC daily (n = 59, 89.4%) or periodically (n = 7, 10.6%). Only 14.3% required assistance to clean the affected body part and it was usually a family member who assisted them. The need for assistance was associated with advanced age and/or stage of lymphoedema and ADLA attacks. Assistance was required not only for cleaning the affected part (fetching water, washing) but also for surveying for entry lesions owing to failing sight in the elderly. ADLA attacks Thirty-one (46.97%) subjects had one or more ADLA attacks during the preceding year. Although around 50% of those who reported acute attacks suffered only one, some had experienced as many as 12 attacks during the past year (Table 1 ). The mean number of ADLA attacks tended to rise with stage of lymphoedema. Table 1 Frequency of ADLA attacks according to the stage of lymphoedema ADLA attacks/year> Numbers affected according to lymphoedema stage Stage 1 n = 21 Stage 2 n = 30 Stage 3 n = 11 Stage 4 n = 1 Stage 5 n = 3 Stage 6 n = 0 Stage 7 n = 0 1 7 6 2 0 1 0 0 2 0 1 0 0 0 0 0 3 2 3 0 0 0 0 0 4 1 2 0 0 1 0 0 5 0 0 1 0 0 0 0 6 0 0 2 0 0 0 0 12 0 0 1 0 1 0 0 Mean 0.81 0.83 2.82 0 5.67 - - Out patient departments (OPD) of Government hospitals (44.9%), private practitioners (30.6%) and filariasis clinics (14.3%) were the preferred sources of treatment for acute attacks. The treatment cost of an acute attack ranged from Rs.100 to 3500 (1 US$ = 100 SLR) with an average cost of Rs. 737.91 per attack for those who sought private care (n = 48). The average duration of an acute attack was 3.5 days. Fifty two percent of those who had experienced an acute attack in the past (n = 48) were totally incapacitated (unable to attend to any domestic / economic activity) while 31.3% were moderately incapacitated (able to attend to some domestic / economic activity) for the duration of the acute attack. Almost all subjects (n = 60, 92.3%) believed that their lymphoedema was reversible and treatment with antiparasitic drugs was identified as the most important therapeutic option for reversing/ halting the progression of the disease. Only 18.2% of the study sample felt that they were being shunned by the society and that their altered physical appearance elicited various reactions ranging from sympathy to fear and ridicule from the community. Non-clinic attendees During the period of this study an attempt was also made to collect comparable data from non-clinic attendees. However, it was possible to identify only 10 subjects, all seeking treatment in the OPD of the University Teaching Hospital. These 10 patients were in lymphoedema stages I (n = 2), II (n = 2) and III (n = 6) respectively. According to the data elicited by using the same questionnaire, 8 of these 10 non-clinic attendees (80%) were unaware of the currently recommended disability management measures. Further analysis was not carried out since the sample size was not comparable with that of clinic attendees. Discussion The results of this survey indicate that the majority of patients attending filariasis clinics are aware of the importance of the currently recommended morbidity control measures. It was also encouraging to note that many practiced at least some of the morbidity control measures that they had learnt, especially washing the affected part with soap and clean water once or twice a day. Although many were aware of the importance of minimizing skin trauma, a sizeable proportion used coir to clean the skin of the affected part during washing. This is a harmful practice which could traumatize the skin and lead to entry lesions; therefore demonstration of suitable alternatives is clearly necessary. A community educational programme may be especially beneficial as it would also involve the family members of the affected population who are often the caregivers of patients affected with severe grades of lymphoedema. Involving the family in the care of the patient will also help to reduce the feelings of stigma, isolation and neglect experienced by some of the patients. Limb elevation was identified as an important measure by most patients but not practiced on a regular basis by many. Poor compliance with limb elevation has also been reported in Southern India [ 6 ]. The authors attributed this to inconvenience and the belief that it caused only a temporary reduction in lymphoedema. Movement and elevation has been shown to play an important role on the lymphatic and venous systems of the body [ 7 - 9 ]. However, only 31.8% of the study population was aware of the importance of exercise and very few practiced it on a regular basis. Patients with lymphoedema tend to become increasingly immobile and the affected limb is most often in a dependent position causing venous hypertension and resultant overloading of the failing lymphatics [ 9 ]. Therefore, health education emphasizing the long-term benefits of exercise and limb elevation should be provided in a comprehensive manner to patients and caregivers. It is also important to ensure that footwear is used indoors as well as outdoors, as the commonest entry lesions noted in the study population were sole fissures which are highly likely to become infected when walking barefoot. In contrast to previous reports [ 10 ], fungal infections of the interdigital spaces were not seen in any participants in the present study – perhaps because most of the study population had early grades of lymphoedema. The practice of prescribing DEC on a regular basis to patients affected with chronic disease needs to be discouraged as there is no conclusive evidence regarding any beneficial effects of long term use of DEC in the management of lymphoedema [ 10 , 11 ]. Misconceptions regarding the need to avoid fatty foods seem to be based on the belief that such foods may increase the volume (fatness) of the affected limb. Such beliefs may have originated from health messages of the lymphatic filariasis program with regard to management of chyluria. These misconceptions need to be corrected, as patients tend to avoid some commonly available food items. Although the data regarding acute attacks may not be highly accurate as it was based on one-year recall, there is reason to believe that recall data reliably reflect the burden imposed by ADLA attacks on the affected population [ 12 , 13 ]. Where patients had sought private care for ADLA attacks, average total expenditure on treatment was about Rs. 737.91 per attack – it is not surprising, therefore, that more than 50% of the population (59.1%) sought treatment from Government health facilities which provide free health care. Income lost by patients during an ADLA attack due to physical incapacitation was not determined in this study. The findings of this study may not be generalized to all patients with lymphoedema in the Gampaha district as the subjects surveyed were patients already enrolled in morbidity control clinics. Limited information gathered from non-clinic attendees indicated that the level of knowledge among clinic attendees might be far superior to that of non-clinic attendees. Lymphatic filariasis continues to be a major public health burden. Globally an estimated 15 million suffer disfiguring symptoms of lymphoedema and elephantiasis [ 14 ]. Although the national burden of lymphoedema has not been fully quantified, a prevalence of 3% has been reported from some parts of the country [ 15 ]. Therefore, in Sri Lanka, morbidity management needs to be strengthened. Conclusions Referral of lymphoedema patients to morbidity control clinics is recommended as they appear to play an important role in the dissemination of morbidity control knowledge. The services of these clinics needs to be further improved to ensure that all clinic attendees receive proper education on disability management. Training and education of specialists in the management of lymphoedema may be a useful investment for eliminating the handicap caused by chronic lymphatic filariasis. List of abbreviations used ADLA: Acute dematolymphangioadenitis MDA: Mass drug administration programme AFC: Anti Filariasis Campaign DEC: Diethylcarbamazine citrate SD: Standard deviation OPD: Out patients Department SLR: Sri Lanka rupee US$: U.S. dollar Competing interests None declared Authors Contributions TC designed the questionnaire, conducted the survey and drafted the manuscript. RP Participated in data collection and interpretation. NS provided overall supervision of the study and preparation of the manuscript. All authors read and approved the final manuscript.

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555761

Validity of Simpson-Angus Scale (SAS) in a naturalistic schizophrenia population

Background Simpson-Angus Scale (SAS) is an established instrument for neuroleptic-induced parkinsonism (NIP), but its statistical properties have been studied insufficiently. Some shortcomings concerning its content have been suggested as well. According to a recent report, the widely used SAS mean score cut-off value 0.3 of for NIP detection may be too low. Our aim was to evaluate SAS against DSM-IV diagnostic criteria for NIP and objective motor assessment (actometry). Methods Ninety-nine chronic institutionalised schizophrenia patients were evaluated during the same interview by standardised actometric recording and SAS. The diagnosis of NIP was based on DSM-IV criteria. Internal consistency measured by Cronbach's α, convergence to actometry and the capacity for NIP case detection were assessed. Results Cronbach's α for the scale was 0.79. SAS discriminated between DSM-IV NIP and non-NIP patients. The actometric findings did not correlate with SAS. ROC-analysis yielded a good case detection power for SAS mean score. The optimal threshold value of SAS mean score was between 0.65 and 0.95, i.e. clearly higher than previously suggested threshold value. Conclusion We conclude that SAS seems a reliable and valid instrument. The previously commonly used cut-off mean score of 0.3 has been too low resulting in low specificity, and we suggest a new cut-off value of 0.65, whereby specificity could be doubled without loosing sensitivity.

Background Reported prevalences for neuroleptic-induced parkinsonism (NIP) in schizophrenia patients are usually in the range 19% to 36% [ 1 - 5 ]. As NIP can severely impair activities of daily life, and it can be treated or at least alleviated, its diagnosis and assessment are an important focus in clinical practice. A reliable diagnosis of NIP is a demanding task [ 6 ]. NIP may be missed due to overlap with negative and depressive symptoms in treated schizophrenia patients [ 7 ]. Diagnostic and Statistical Manual, fourth edition, (DSM-IV) [ 8 ] criteria for NIP consist of parkinsonian tremor, muscular rigidity or akinesia, developing within a few weeks of starting or raising the dose of a neuroleptic medication (or after reducing a medication used to treat extrapyramidal symptoms). Like other motor adverse effects of antipsychotic drugs, the NIP is usually assessed by clinical observation or by rating scales, which are based on clinician's judgement. Movement disorders such as NIP, however, can be measured objectively by recording motor activity [ 9 - 12 ]. Simpson-Angus Scale (SAS) is a 10-item rating scale that has been used widely for assessment of NIP in both clinical practice and research settings [ 13 ]. It consists of one item measuring gait (hypokinesia), six items measuring rigidity and three items measuring glabella tap, tremor and salivation, respectively. It is an established rating scale, but some shortcomings have been suggested: the rigidity items may be given too much emphasis, the statistical properties have been studied insufficiently, and the instructions as well as the definitions are somewhat unclear [ 14 ]. Several items of the scale have failed to show appropriate interrater reliability or insufficient variability across elderly patients [ 15 ], and a modified version has been used to determine the prevalence of spontaneous parkinsonism and the incidence of NIP in this population [ 16 ]. According to our recent study [ 17 ] there was a discrepancy between SAS and DSM-IV based NIP prevalence estimates. We suggested that the commonly used cut-off point of 0.3 mean SAS score was too low in a naturalistic clinical population [ 17 ]. Accelerometric methods have been developed to identify and monitor motor NIP symptoms, such as tremor [ 18 , 19 ] and hypokinesia [ 20 ]. A standardized actometric method has been developed for the assessment of neuroleptic-induced akathisia (NIA) [ 21 ]. This method discriminated pure NIA patients from healthy controls and from themselves in remission phase with no overlap [ 21 ]. In the current clinical population (including patients with NIP and tardive dyskinesia in addition to NIA), however, the method evidenced less diagnostic power [ 22 ]. NIP symptoms may have confounded these actometric findings. The discrepancy between SAS and DSM-IV based NIP prevalence estimates as well as other above mentioned shortcomings suggest that SAS needs an evaluation as a method to assess NIP severity and to find reliably NIP cases. Our aims were to check the internal consistency of SAS, improve the convergence between DSM IV and SAS based NIP case finding, and to evaluate how well the scale measures objective motor symptoms verified by actometry. Methods We recruited 99 chronic schizophrenic institutionalized adult patients from a state nursing home in central Estonia [ 17 ]. Inclusion criteria were DSM-IV diagnosis of schizophrenia or schizoaffective disorder, stable antipsychotic medication (for at least one month), and age of 18–65 years. Diagnosis was made using a semi-structured interview according to DSM-IV criteria for schizophrenia by a psychiatrist (SJ) and medical records. Patients with severe somatic illness or neurological illness were excluded. Written informed consent was obtained from the subjects and the study was approved by the Ethics Review Committee on Human Research of the University of Tartu. Data were collected from 29.10.2001 to 27.03.2002. An experienced clinician (SJ) assessed all the subjects to identify NIP cases in accordance with DSM-IV. The DSM-IV diagnostic criteria for other neuroleptic-induced movement disorders (NIMD) were also checked because of frequent comorbidity and common aetiology. Clinical NIP symptoms were assessed by SAS and the motor activity during rest was measured by actometry. Each item of the 10-item SAS is rated on a 5-point scale (0–4), and the mean score is obtained by adding the items and dividing by 10 [ 13 ]. Neuroleptic-induced akathisia and tardive dyskinesia were rated by Barnes Akathisia Rating Scale (BARS) [ 23 ] and Abnormal Involuntary Movement Scale (AIMS) [ 24 ]. The actometric recording was performed during sitting in a standardized clinical interview for 30 minutes, a method described previously as measuring "controlled rest activity" [ 19 , 21 ]. Controlled rest activity is a parameter of motor activity in a situation where sitting still is adequate and expected, but not instructed or required. The actometers (PAM3, Individual Monitoring Systems, Baltimore, USA) were attached to the ankles of the subjects to measure lower limb motor activity. Actometers are wireless, computerized movement detectors of match-box-size, which do not influence normal moving of the patient. Cronbach's α was assessed to evaluate the internal consistency of the scale. The correlations between the lower limb activity (the mean of right and left ankle movement indices) and individual item scores and mean SAS scores were analysed. Differences between the NIP and non-NIP, as well as the NIMD and the non-NIMD groups in the SAS mean score and lower limb activity were analysed. The performance of SAS mean score and individual item scores in case identification was evaluated by receiver operating characteristics (ROC) analyses against DSM-IV NIP diagnosis. Validity coefficients (specificity, sensitivity, positive and negative predictive value [PPV and NPV, respectively]) for different mean SAS score thresholds were calculated. To explore the discriminatory power of each single SAS item we performed ROC analyses for each item separately. We also explored the effect on the validity coefficients of merging the six rigidity items of SAS into one single item, to de-emphasise the influence of rigidity on the mean SAS score. The Spearman test was used to correlation analysis and the Mann-Whitney 2-tailed U-test for the comparison between two groups because of the non-normal distribution of the data. The software used in analyses was SPSS 11.0. [ 25 ]. Results Of the 99 participants, 45 (45.5%) were male and 54 (54.5%) female. The mean age was 49.7 (SD 9.5) years. The mean continuous treatment in hospital or in nursing home was 13.6 (SD 9.0) years. Seventy-nine (79.8%) patients used conventional antipsychotics (70 on low-dose, and 9 on high-dose neuroleptics) and 20 (20.2%) used clozapine (one was receiving clozapine combined with sulpiride). Low-dose antipsychotics in this study were haloperidol, cyclopentixol, perphenazine and fluphenazine; high dose antipsychotics were chlorpromazine, thioridazine, levomepromazine, chlorprotixen and sulpiride. Sixteen (16.2%) patients were receiving combinations of typical antipsychotics (either predominantly low-dose [N = 10] or predominantly high-dose [N = 6] neuroleptic regimens), and 63 (63.6%) were receiving monotherapy (haloperidol: N = 29; zuclopenthixol: N = 28; perphenazine, chlorpromazine, or thioridazine: N = 6). No new atypical antipsychotics were used. The mean daily chlorpromazine equivalent conditions. The prevalence of any NIMD according to DSM-IV was 61.6% in the whole sample. Cronbach's α for SAS was 0.79. dose [ 26 ] was 328 (SD 221) mg. The prevalence of NIP according to DSM-IV criteria was 23.2%. Fourteen patients, all from non-NIP subgroup, used an anticholinergic drug (trihexyphenidyl). Only 10 of the 23 patients with NIP presented as pure NIP without comorbidity of other motor disorders. Among patients with NIP, 10 had comorbid akathisia and 6 tardive dyskinesia; three of them had all three The SAS mean score correlated significantly with age in our population (r = 0.203, p = 0.044). Convergence of SAS and actometry to DSM-IV NIP diagnosis The SAS mean score for DSM-IV NIP patients (1.24, SD = 0.44) was significantly higher from that (0.56, SD = 0.33) of non-NIP patients (U = -6.90, p = 0.000). The mean scores of each single SAS item are presented in Table 1 . The mean scores of "glabella tap" and "salivation" items for NIP patients were not significantly higher from that of non-NIP patients. The SAS mean score for NIMD patients was significantly higher from that of non-NIMD patients (U=-5.77, p = 0.000). Table 1 Mean scores of Simpson-Angus Scale (SAS) items in Neuroleptic-Induced Parkinsonism (NIP) group and non-NIP group. SAS item NIP-group Non-NIP group Gait 1.04 0.38 Arm dropping 1.43 0.59 Shoulder shaking 1.09 0.33 Elbow rigidity 1.83 0.47 Wrist rigidity 0.91 0.16 Leg pendulousness 0.91 0.28 Head dropping 1.48 0.66 Glabella tap 1.09 0.86 Tremor 1.78 1.14 Salivation 0.83 0.71 Mean of SAS items 1.24 0.56 Actometric data was missing for one male patient due to non-co-operation. The median lower limb activity for NIP patients was not significantly higher than that of non-NIP patients (U = -0.46, p = 0.643). The median lower limb activity for NIMD patients was significantly higher from that of non-NIMD patients (U=-2.66, p = 0.008). Convergence of SAS to actometry The SAS mean score did not correlate significantly with actometric lower limb activity either in the whole population (r = 0.04, p = 0.717), in the NIP group (r = -0.29, p = 0.192), or in the pure NIP subgroup (r = -0.21, p = 0.587). Even after a post-hoc analysis of co-variance in the whole population, where the effect of akathisia (BARS global score) and tardive dyskinesia (AIMS severity score) were controlled for, no significant correlation between SAS mean score and the lower limb activity could be found (r = 0.07, p = 0.494). The tremor item of the SAS correlated significantly with the lower limb activity in the whole population (r = 0.25, p = 0.013) but not in the NIP population (r = 0.26, p = 0.248) or in the pure NIP subgroup (r = 0.51, p = 0.160). No correlation was evidenced between the hypokinesia item of the SAS and lower limb activity in the whole population (r = -0.07, p = 0.513) either in NIP population (r = -0.24, p = 0.290) or in pure NIP subgroup (r = -0.37, p = 0.797). No correlation was evidenced between the mean of rigidity items of the SAS and lower limb activity in the whole population (r = -0.12, p = 0.256) either in NIP population (r = -0.37, p = 0.090) or in pure NIP subgroup (r = -0.30, p = 0.426). NIP case finding by SAS ROC-curve for screening performance of SAS mean score is presented in Fig 1 . Area under the ROC-curve (AUC) for SAS mean score was 0.92 (CI = 0.87–0.97). AUC of the ROC curve for SAS elbow rigidity item was 0.93 (CI = 0.86 – 1.0). AUC for the other items was less than 0.82. AUC in ROC analyses may range from of 0.5 (no case finding power) to 1.0 (optimal case finding performance). The validity coefficients of the SAS mean score are presented in Table 2 . Figure 1 Receiver Operating Characteristic (ROC) curve for SAS mean score against DSM-IV defined Neuroleptic-Induced Parkinsonism (NIP). Table 2 Validity coefficients of the Simpson-Angus Scale (SAS) mean score at different cutoff values. The optimal cut-off point range is presented in bold text. SAS mean cut-off 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95 1.05 1.15 Sensitivity 1.0 1.0 1.0 1.0 1.0 0.96 0.87 0.78 0.70 0.52 Specificity 0.17 0.36 0.45 0.49 0.62 0.74 0.86 0.86 0.89 0.93 Positive Predictive Value 0.27 0.32 0.35 0.37 0.44 0.96 0.65 0.64 0.67 0.71 Negative Predictive Value 1.0 1.0 1.0 1.0 1.0 0.98 0.96 0.93 0.91 0.87 ROC-curve for screening performance of SAS mean with single averaged rigidity item was clearly inferior to the original SAS mean curve with AUC of 0.80 (CI = 0.70–0.89). The screening performances of the individual SAS items for NIP case finding are shown at Table 3 . Table 3 Area under the ROC curve of Simpson-Angus Scale (SAS) parameters against DSM-IV diagnosis of Neuroleptic-Induced Parkinsonism. SAS item Area under the ROC curve Gait 0.71 Arm dropping 0.79 Shoulder shaking 0.81 Elbow rigidity 0.93 Wrist rigidity 0.75 Leg pendulousness 0.73 Head dropping 0.75 Glabella tap 0.57 Tremor 0.66 Salivation 0.53 Mean of rigidity items 0.92 Mean of mean rigidity items and other SAS items 0.80 Mean of SAS items 0.92 As SAS elbow rigidity item had case finding power similar to SAS mean score, we calculated optimal cut-off for this item. Cut-off threshold of 1.5, with sensitivity of 0.826 and specificity of 0.974, was superior to cut-off threshold of 0.5 with sensitivity of 0.957 and specificity 0.553. Discussion Our study aimed to evaluate some of the characteristics of the SAS and its utility for identifying and measuring NIP in a naturalistic schizophrenia sample. The internal consistency of SAS was satisfactory, which suggests sufficient reliability for the scale. We compared the SAS with the DSM-IV to assess its discriminant validity and evaluate it in detecting NIP cases. The comparison with objective movement assessment aimed to estimate the concurrent validity of SAS in NIP severity measurement. As expected, the SAS had discriminant validity for a clinical diagnosis of NIMD. SAS mean score discriminated NIMD patients well from those without NIMD, and more specifically, also NIP patients from other patients. Actometry discriminated NIMD patients from non-NIMD patients, but did not identify DSM-IV NIP patients. According to ROC analysis the SAS had good case finding properties converging with the DSM IV NIP diagnosis. In our population the commonly used threshold 0.3 was inappropriate: according to our results the optimal cut-off point should be between 0.65 – 0.95 depending on the emphasis in the trade-off between sensitivity and specificity. We suggest that the new cut-off value for screening NIP could be 0.65, whereby specificity could be doubled without loosing any sensitivity. To be useful for diagnostic purposes a combination of high specificity and high positive predictive value (PPV) is reached at cut-off – 0.75 [ 27 ]. To answer to criticism about the overrepresentation of rigidity items, we averaged the six items into one item. This procedure worsened the NIP case detection capacity of the SAS. Using the single elbow rigidity item for case detection had the same (or slightly better) case detection capacity as the SAS mean score. This finding supports the use of elbow rigidity testing when assessing parkinsonism in clinical settings, as cut-off value 0.5 has good sensitivity and specificity for DSM-IV NIP. We found that SAS mean score did not correlate with actometric lower limb activity, and hypokinesia observed during gait item of SAS did not correlate with actometric motor activity during the 30-minute recording. There are a few explanations for that: First, actometry measures only the productive motor dimension of the parkinsonian symptoms while SAS takes into account also rigidity, gait, salivation and glabella tap, with a clear emphasis on rigidity. Lack of correlation with actometric findings in NIP subgroup indicates that tremor may not be the core feature of NIP. This is also supported by the small AUC for the tremor item of SAS. Secondly, we used lower-limb actometry while the clinical assessment by SAS and DSM-IV considered predominantly upper limbs. Parkinsonism may be more symptomatic in upper limbs, and the upper limb disturbances may have influenced our SAS and DSM IV assessments more than lower limb disturbances. Our findings indicate that lower limb actometry is not suitable for diagnosing NIP. Thirdly, diurnal naturalistic actometry may have more power in detecting hypokinesia. Limitations This study was limited to a few aspects of utility/validity of the SAS: internal consistency, convergence to DSM-IV NIP diagnosis and convergence to objectively measured motor activity. Many aspects of the scale's reliability (e.g. test-retest and inter-rater reliability) and validity (e.g. construct) were not evaluated. DSM-IV was used as a standard in this study, but there is not much data available on the validity of NIP criteria of the DSM-IV. A better golden standard in this study would probably have been an expert-consensus diagnosis. Furthermore, as there was only one rater for the scales, a cross-scale contamination issue might have occurred. It is known that with age the prevalence of spontaneous NIMD rises. Our material did not allow a thorough examination of the issue, but age correlated with SAS mean score in our sample. The measurement of motor activity here was purely quantitative; we did not assess the patterns of the disordered movements. Conclusion As a conclusion, SAS seems be a reliable and a valid instrument. It performs well and similarly to DSM-IV in NIP case detection. The optimal SAS mean score cut-off value in a naturalistic population of neuroleptic-treated schizophrenia patients is higher than the commonly used 0.3. We suggest that the new cut-off value for screening NIP could be 0.65, whereby specificity could be doubled without loosing sensitivity. Combining SAS rigidity items does not seem to improve the performance of the scale. Competing interests The author(s) declare that they have no competing interests. Authors' contributions SJ contributed to the study design, collected the data, contributed to the analyses and data interpretation, made the literature search and was responsible for manuscript preparation with MMH. MMH contributed to study design, made most of the analyses and data interpretation, and was equally responsible for manuscript preparation with SJ. KT contributed to study design, statistical analysis, data interpretation and manuscript preparation. KW supervised the study design and contributed to statistical analysis, data interpretation and preparation of the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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Transcriptional Control in the Segmentation Gene Network of Drosophila

The segmentation gene network of Drosophila consists of maternal and zygotic factors that generate, by transcriptional (cross-) regulation, expression patterns of increasing complexity along the anterior-posterior axis of the embryo. Using known binding site information for maternal and zygotic gap transcription factors, the computer algorithm Ahab recovers known segmentation control elements (modules) with excellent success and predicts many novel modules within the network and genome-wide. We show that novel module predictions are highly enriched in the network and typically clustered proximal to the promoter, not only upstream, but also in intronic space and downstream. When placed upstream of a reporter gene, they consistently drive patterned blastoderm expression, in most cases faithfully producing one or more pattern elements of the endogenous gene. Moreover, we demonstrate for the entire set of known and newly validated modules that Ahab's prediction of binding sites correlates well with the expression patterns produced by the modules, revealing basic rules governing their composition. Specifically, we show that maternal factors consistently act as activators and that gap factors act as repressors, except for the bimodal factor Hunchback. Our data suggest a simple context-dependent rule for its switch from repressive to activating function. Overall, the composition of modules appears well fitted to the spatiotemporal distribution of their positive and negative input factors. Finally, by comparing Ahab predictions with different categories of transcription factor input, we confirm the global regulatory structure of the segmentation gene network, but find odd skipped behaving like a primary pair-rule gene. The study expands our knowledge of the segmentation gene network by increasing the number of experimentally tested modules by 50%. For the first time, the entire set of validated modules is analyzed for binding site composition under a uniform set of criteria, permitting the definition of basic composition rules. The study demonstrates that computational methods are a powerful complement to experimental approaches in the analysis of transcription networks.

Introduction The development of higher eukaryotes depends on the establishment of complex spatiotemporal patterns of gene expression. Thus, an important key to understanding development is to decode the transcriptional control of patterned gene expression. The segmentation gene network of Drosophila has long been one of the prime paradigms for studying the role of transcription control in pattern formation ( Carroll 1990 ; Rivera-Pomar and Jackle 1996 ). The regulation within the network is almost entirely transcriptional, and many of the cis - and trans -acting components are well characterized. The network comprises maternal and zygotic factors that act in a hierarchical fashion to generate increasingly refined and complex expression patterns along the anterior-posterior (ap) axis in the blastoderm embryo ( St Johnston and Nusslein-Volhard 1992 ; Driever 1993 ; Pankratz and Jäckle 1993 ; Sprenger and Nüsslein-Volhard 1993 ; St Johnston 1993 ; Furriols and Casanova 2003 ): The maternal factors form gradients stretching along the entire ap axis; the zygotic gap factors are expressed in one or more broad, slightly overlapping domains; the pair-rule genes are expressed in seven stripes and segment-polarity genes in fourteen stripes, prefiguring the segmental organization of the larva; finally, the homeotic genes specify segment identity (for schematic see Figure 6 A). Figure 6 Module Predictions within the Segmentation Gene Network (A) Schematic depiction of the regulatory relationships within the segmentation gene network. (B) Ahab-predicted modules in the control regions of segmentation genes were classified based on their composition into pair-rule driven (pr, red), maternal/gap driven (mg, green), and mixed but predominantly pair-rule (pr(mg), light red) or predominantly maternal/gap driven (mg(pr), light green); see text for details. For each gene, the number and type of modules in the control region is shown; grouping of genes is indicated by brackets and follows the hierarchy as depicted in (A). The type of regulatory input a gene receives is indicative of its position within the gene network. Many of the segmentation genes are transcription factors themselves; their principal targets are segmentation genes acting at the same level or below. From a large body of genetic and molecular studies (for review see Akam 1987 ; Cohen and Jurgens 1991 ; McGinnis and Krumlauf 1992 ; St Johnston and Nusslein-Volhard 1992 ; Martinez Arias 1993 ; Pankratz and Jäckle 1993 ), the following broad rules for regulation within the network have been gleaned (cf. schematic in Figure 6 A): Gap genes receive input from the maternal factors; the gap genes of the trunk heavily cross-regulate, while the gap genes of the head do not. The pair-rule genes are divided into a primary and a secondary tier: The primary pair-rule genes generate their seven-stripe pattern mainly through maternal and gap input, while the secondary pair-rule genes depend on (primary) pair-rule gene input; but the debate about which pair-rule genes belong to the primary tier is not resolved ( Carroll 1990 ; Klingler and Gergen 1993 ; Klingler et al. 1996 ). Segment-polarity genes receive pair-rule gene input, and the homeotic genes receive both gap and pair-rule input. Like other factors controlling the transcription of protein-encoding genes, the segmentation gene transcription factors bind to cis -regulatory elements, also called modules, and positively or negatively regulate the recruitment of the basal transcription machinery to the core promoter (for review see Gray and Levine 1996 ; Arnone and Davidson 1997 ; Zhou et al. 1997 ; Blackwood and Kadonaga 1998 ; Roeder 1998 ; Naar et al. 2001 ; Roth et al. 2001 ; Arnosti 2003 ). Specifically, the maternal factors were found to act as activators, while the gap factors act mostly as repressors; however, there is a body of data suggesting that gap factors can act as activators or repressors in a context-dependent fashion (see below). The expression patterns of the segmentation genes are typically complex, and in many cases different aspects of the pattern are controlled by separate modules. An individual module typically receives input from multiple transcription factors and contains multiple binding sites for each of the factors; in many cases the relevant binding sites are clustered within a small interval of 0.5–1 kb. The combinatorial and redundant nature of the input and its clustering are features that are readily exploited for the computational detection of transcriptional control elements. We have recently developed an algorithm, Ahab, which uses a thermodynamic model to detect cis -regulatory modules ( Rajewsky et al. 2002 ). Ahab uses binding site information for multiple transcription factors participating in a common process and seeks an optimal binding of the factors to a given sequence window. Binding site information for the factors is provided in the form of position weight matrices ( Stormo 2000 ), which Ahab uses to infer binding energies. Ahab then optimizes the total free energy of binding the factors to the sequence. The factors compete for binding with a local background model computed from the base composition within the sequence window; the competition between factors is treated as in standard thermodynamics. The result is then the best partitioning of the sequence window into binding sites and background. The total free energy under this partitioning is taken as the score, and can be used to rank modules. Thus, in contrast to other methods for module detection ( Berman et al. 2002 ; Halfon et al. 2002 ; Markstein et al. 2002 ; Papatsenko et al. 2002 ; Rebeiz et al. 2002 ), Ahab requires no predefined factor-dependent cutoffs, which means that clusters of weak sites can be detected. We used Ahab for a genome-wide prediction of segmentation gene modules with maternal and gap input and found that it recovers known modules with excellent success ( Rajewsky et al. 2002 ). Here, we use Ahab to identify novel modules within the segmentation gene network. We test 16 significant novel predictions and find that 13 faithfully produce pattern elements of the endogenous gene, while the remaining three produce more or less aberrant blastoderm patterns. Our combined computational and experimental analysis increases the number of characterized segmentation modules by 50% and provides effective de novo control region dissections for ten of the 29 genes with gap and pair-rule patterns. Furthermore, we systematically analyze Ahab's prediction of binding site composition for all experimentally validated modules. By correlating the expression patterns of modules with their binding site composition, we are able to show that the composition of modules is generally well fitted to the distribution of input factors, and we are able to determine the mode of action for six of the nine maternal/gap input factors. Finally, we explore Ahab's predictive ability when binding site information is less well defined, as is the case with the pair-rule factors. Despite the handicap, Ahab traces the global architecture of the segmentation gene network and pinpoints the unexpected behavior of odd skipped as a primary pair-rule gene. Results Prediction and Validation of Segmentation Modules As the principal arena for our investigation, we selected the top two tiers of the segmentation gene network, namely the gap and pair-rule genes (for references see Dataset S1 ). Using Ahab, we searched the genomic regions surrounding these genes for cis- regulatory modules containing clusters of binding sites for maternal and gap factors. As input for Ahab, we provided binding site information (in the form of position weight matrices derived from the literature; Dataset S2 ) for nine transcription factors: the maternal factors Bicoid (Bcd), Hunchback (Hb), Caudal (Cad), the Torso-response element (TorRE), and Stat92E (D-Stat), and the gap factors Kruppel (Kr), Knirps (Kni), Giant (Gt), and Tailless (Tll). Note that the weight matrices for Kni and Tll are quite unspecific, which leads to an increased number of binding site predictions. Conversely, the available binding site information for D-Stat and Gt is rather limited and thus appears artificially specific, resulting in fewer predictions. Ahab was run over the genomic regions of 29 genes with gap and pair-rule patterns consisting of 0.75 Mb of total genomic sequence (see Materials and Methods ). We experimented with two adjustable parameters of Ahab, free energy cutoff and the order of the background model, i.e., whether pairs or triples of bases are used as background sequence. We favored the lower order background, which is less stringent and increases the number of factor binding sites, and set the free energy cutoff at 15, which is approximately four standard deviations above the mean of genome-wide window scores ( Figure 1 A). The window size was set at 500 bp, which we had previously found to deliver the most efficient recovery of known modules ( Rajewsky et al. 2002 ). Figure 1 Ahab Predictions and Recovery of Known Modules (A) Histogram of genome-wide window scores for the Ahab mg run (maternal/gap input, window size 500 bp, window shift 50 bp, background model 2). As free energy cutoff we chose 15, which is approximately four standard deviations above the genome-wide mean (indicated by light blue line). (B) Pie chart summarizing results of Ahab predictions for gap and pair-rule genes, including recovery of known modules and testing of novel predictions. (C–F) For the genomic regions of selected gap and pair-rule genes, the free energy profiles of two Ahab runs (mg and mgpr) are shown. The free energy cutoffs are marked by dotted lines; statistically significant predictions for the mg run are marked by black arrow heads (cf. Figure 4 ). In the header above, the blastoderm expression pattern of the locus is depicted schematically, anterior to the left, posterior to the right. The position of experimentally validated modules within the control region is delineated by colored bars; the aspect of the endogenous pattern they drive is highlighted in matching color. Overall, the control regions of the gap genes hb and Kr and of the primary pair-rule genes eve and h are computationally well delineated with maternal/gap input. References: (1) Schroder et al. (1988) , (2) Margolis et al. (1995) , (3) Hoch et al. (1990) , (4) Goto et al. (1989) , (5) Fujioka et al. (1999) , (6) Riddihough and Ish-Horowicz (1991) , (7) Howard and Struhl (1990) , and (8) Langeland and Carroll (1993) . Under these conditions, Ahab predicts 52 modules within the genomic region of the 29 genes of interest, an average of about two modules per gene. This hit rate represents a 5-fold enrichment compared to the genome-wide rate. Of the 52 predicted modules, 43 are located in intergenic regions, nine in introns, and none in coding regions, indicating a bias of the predictions toward transcriptional control regions. Of the 31 known modules, we recover 22 as significant predictions (score >15; because of overlaps, 20 Ahab predictions cover the 22 known modules), and three overlap with free energy peaks just below the cutoff ( Figure 1 ; cf. Figure 4 ). In the six cases where Ahab misses known modules completely, the reasons are most likely missing input factors (e.g., hkb_ventral_element module; Hader et al. 2000 ) or a low number of binding sites (e.g., ems_head module; Hartmann et al. 2001 ). The likelihood of recovering 22 modules at random is negligible ( p < 10 −8 ). We also predict 32 novel modules, and we expect at least some predictions with scores below 15 to be functional as well. Figure 4 Correlation of Expression Patterns with Module Composition Based on the expression pattern they give rise to, known and newly validated modules are sorted into anterior, posterior, and terminal (if expression bridges the 50% EL line, the module is labeled ant/post), and their binding site composition is evaluated using Ahab output from the mg run. The expression pattern of a module is depicted schematically (anterior = 100% EL, left; posterior = 0% EL, right), followed by name of gene, name of module, recovery as significant prediction (marked by X) or as subthreshold peak (marked by (X)) in D. melanogaster and D. pseudoobscura, distance to the gene's transcription start site (negative values denote upstream location), and binding site composition. For references see Dataset S1 . Expression patterns of previously known modules are in black, those of newly validated modules are in dark pink, and modules with unfaithful/unstable patterns are in light pink. Binding site composition is given in the form of integrated profile values for individual input factors (see Materials and Methods ); higher color intensity emphasizes higher values. Diagnostic features are emphasized by black trim: In anterior modules Bcd sites are overrepresented and Cad sites are underrepresented, while in posterior modules Cad sites are overrepresented and Bcd sites underrepresented. Terminal modules are enriched in TorRE sites. For experimental validation, we selected 16 module predictions with scores greater than 15 and five with scores below 15 ( Figures 2 and 3 ), located near genes with gap and pair-rule patterns whose control regions had not or only partially been dissected: cad , cap ‘n' collar (cnc), Dichaete (D), fork head (fkh), gt, kni, knirps-like (knrl), nubbin (nub), ocelliless (oc), POU domain protein 2 (pdm2), odd skipped (odd), and sloppy paired 2 (slp2) . We used the free energy profiles to delineate the module and then tested its ability to drive blastoderm expression using a lacZ reporter construct (see Materials and Methods ). All of the predicted modules we tested drive expression in the blastoderm. However, the faithfulness of the patterns produced by the modules varies. Of the 16 modules with scores greater than 15, 13 produce faithful patterns that reproduce one or more aspects of the endogenous pattern, two produce unfaithful patterns, and one has an unstable, insertion-dependent pattern. Of the five modules with scores below 15, two produce faithful and three produce unstable blastoderm patterns. This indicates that Ahab has excellent success in predicting modules driving blastoderm expression and that the free energy cutoff is well chosen, with few false positives and negatives. The fact that unfaithful or unstable patterns are produced by some of the modules is likely a reflection of the fact that Ahab makes predictions simply on the basis of the total free energy without any explicit rules as to the number and type of factors that have to contribute to the binding. By comparing the composition of modules of different degrees of faithfulness or stability, one can attempt to formulate such rules (see below). Figure 2 Expression Patterns Driven by Ahab-Predicted Modules I Ahab-predicted modules in the control region of gap and pair-rule genes were tested by fusing putative modules to a basal promoter driving lacZ (module-basal promoter-lacZ; Thummel and Pirrotta 1991 ). The genomic regions, with free energy profiles, for two Ahab runs (mg and mgpr) are shown on the right. The free energy cutoffs are marked by dotted lines; mg run predictions with scores greater than 15 are marked by black arrowheads, tested subthreshold peaks with scores below 15 by open arrowheads. The transcribed region of the locus is marked in blue, the experimentally tested genomic regions are marked by pink bars and named according to distance from transcription start site to middle of the enhancer, and previously known modules are marked by orange bars. The endogenous gene expression is shown on the left (blue frame), the expression pattern driven by the module(s) in the center (pink frame). Embryos are oriented anterior to left, dorsal up. In a few cases, the patterns driven by Ahab-predicted modules are unfaithful to the endogenous gene expression; we distinguish “unfaithful” and insertion-dependent “unstable” patterns. For further description see text. (A) gt, (B) cnc, (C) oc, (D) D, (E) cad, (F) fkh, and (G) slp2. References: (1) Berman et al. (2002) , (2) Gao and Finkelstein (1998) , (3) Lee and Frasch (2000) , and (4) Pankratz et al. (1992) and Rivera-Pomar et al. (1995) . Figure 3 Expression Patterns Driven by Ahab-Predicted Modules II See legend for Figure 2 . (A) kni, (B) knrl, (C) pdm2, (D) nub, and (E) odd. Using Ahab for the Dissection of Segmentation Gene Control Regions The gap gene gt is initially expressed in two domains in the blastoderm, one anterior and one posterior; as cellularization progresses, the anterior domain splits into two stripes, and, finally, a third expression domain develops at the anterior terminus. We predict three modules , gt_(−1), (−3), and (−6), all of which we tested; in addition, we tested one subthreshold peak further upstream, gt_(−10) (see Figure 2 A). We can account for all gt pattern elements: the subthreshold gt_(−10) faithfully produces the anterior expression, gt_(−6) produces the anterior tip expression, and the gt_(−3) module produces the posterior expression (cf. Berman et al. 2002 ). Interestingly, gt_(−1) is bifunctional and produces both the anterior and the posterior expression domain. The gap gene kni is expressed in two domains in the blastoderm, one at the anterior tip and one in the posterior, but only the module driving the posterior expression had previously been identified ( Pankratz et al. 1992 ). In addition to the known module kni_kd, we predict two additional modules, one further upstream, kni_(−5), and one in the first intron, kni_(+1) . The kni_(−5) module faithfully produces the expression at the anterior tip, while the kni_(+1) module drives an imprecise kni pattern with an aberrant anterior and an abnormally widened posterior expression domain (see Figure 3 A). The sister gene knrl is expressed in the same pattern as kni . We find two significant predictions in the control region; we tested one, knrl_(+8), which produces an unfaithful pair-rule-like pattern (see Figure 3 B). The less well known gap genes nub and pdm2 are both expressed in a broad posterior domain; pdm2 , but not nub, develops a segmental pattern during gastrulation. The control regions of the two genes have not been dissected ( Kambadur et al. 1998 ). We find one significant prediction for nub, nub_(−2), and two for pdm2, pdm2_(+1) and (+3). nub_(−2 ) faithfully reproduces the posterior expression of the gene (see Figure 3 D). For pdm2, pdm2_(+1) faithfully reproduces the posterior domain as well as the segmental expression of the gene, while pdm2_(+3) produces line-dependent variable patterns of blastoderm expression (see Figure 3 C). The cad gene is expressed both maternally and zygotically. Its zygotic expression in the blastoderm consists of a single posterior stripe. We make a single significant prediction, cad_(+14), which faithfully reproduces the pattern (see Figure 2 E). fkh is initially expressed in a single domain at the posterior end, to which a second domain at the anterior end is added later in the blastoderm. We make a single significant prediction, fkh_(−2), which faithfully produces the early domain at the posterior end (see Figure 2 F). The head gap gene cnc is expressed in two domains, an anterior cap and a collar. Our single significant prediction, cnc_(+5), faithfully produces the pattern (see Figure 2 B). Similarly, the single significant prediction for oc, oc_(+7), faithfully produces the single head gap domain of the endogenous gene (see Figure 2 C). D is initially expressed in a broad domain encompassing the entire segmented portion of the blastoderm embryo, and an anterior patch is added at the end of the blastoderm. The control region of D has not been dissected ( Sanchez-Soriano and Russell 2000 ). Our single significant prediction, D_(+4), faithfully produces the early blastoderm pattern (see Figure 2 D). Finally, the pair-rule genes: slp1 and slp2 are first expressed in a gap-like pattern in the head, followed by expression in seven and then fourteen stripes. The dissection of the upstream region of slp1 had identified the stripe element but not the gap-like expression in the head ( Lee and Frasch 2000 ). We find a subthreshold peak upstream of slp2 that nicely reproduces the missing head gap pattern (see Figure 2 G). odd is first expressed in a pair-rule and then in a segmental pattern and has traditionally been placed among the secondary pair-rule genes, which are thought to generate their pattern through pair-rule input rather than direct maternal/gap input. Surprisingly, we find two significant predictions in the upstream region of the gene, odd_(−3) and (−5). Both these modules drive expression in two stripes: odd_(−3) drives expression in stripes 3 and 6, while odd_(−5) drives expression in stripe 1 and a broader region encompassing stripes 5 and 6 of the endogenous pattern (see Figure 3 E). This behavior is reminiscent of the two-stripe modules of eve (eve_stripe3_7 and eve_ stripe4_6). Thus, at least four of the seven odd stripes are formed as individual stripes by maternal/gap input rather than as a complete seven-stripe pattern, indicating that odd has primary pair-rule character. Overall, our experimental validation demonstrates that Ahab is highly successful in predicting modules that drive patterned expression in the blastoderm. The algorithm finds missing modules that complement existing ones to collectively produce the expression pattern of a gene and identifies, with surprising accuracy, relevant modules in previously undissected control regions. Most of the modules faithfully produce pattern elements of the endogenous gene, suggesting that our delineation of modules, which is based on the free energy profile of the prediction, is generally quite accurate. Module Composition and Pattern of Expression Ahab's success in finding modules encouraged us to examine in greater detail its prediction of the binding site content of modules. We sought to examine whether the expression patterns of the previously known and our newly tested modules correlate with their composition. In its optimization procedure, Ahab fits all input factors simultaneously to the genomic region of interest, while experimental sites for transcription factors are typically determined in the absence of any competition. Ahab reports binding site composition in the form of integrated profile values, which tally the fractional occupancy of sites for a given factor, and are thus a measure of the strength of binding by this factor (see Materials and Methods ). In order to gauge the accuracy of Ahab predictions of module composition, we examined how well Ahab performs in recovering known binding sites (for detailed description see Materials and Methods ). Overall, the recovery of known sites ranges from 50% to 100%, with the most specific factors/position weight matrices showing the best recovery. The missed sites are typically weak and are not misattributed to other factors but rather to background. Thus, Ahab should provide a reliable profile of module composition. In order to correlate the binding site composition with the ap expression pattern of the modules, we charted the previously known modules and all the newly validated modules with faithful expression and sorted them according to their expression along the ap axis (see Figure 4 ). We ask which, if any, features are diagnostic. The Maternal Factors In anterior modules (driving expression at 50%–100% egg length ), Bcd sites are overrepresented and Cad sites underrepresented (see Figure 4 ), including seven known and six newly tested modules. In posterior modules (driving expression at 0%–50% EL), Bcd sites are underrepresented and Cad sites overrepresented, including five known and five newly tested modules. Finally, in terminal modules (driving expression at 0%–20% and 80%–100% EL), TorRE sites are strongly overrepresented, including four known and one newly tested modules. In addition to the TorRE-terminal signature, terminal modules expressed at the anterior terminus often contain Bcd sites, and those expressed at the posterior end, Cad sites. Thus, there is a strong positive correlation between the expression pattern of the module and the maternal input they receive, supporting the general interpretation that the maternal factors act as transcriptional activators in their realm of expression. To take a closer look at this relationship, we computed for each input factor and for every position along the ap axis the average number of binding sites found in the modules driving expression at that position. We plotted this number as a function of ap position and compared the resulting curve with the input factor distribution as determined by Reinitz and coworkers ( Myasnikova et al. 2001 ) ( Figure 5 A). For TorRE, the distribution of binding sites beautifully follows the expression profile of the input factor (as inferred from expression of its negative regulator, Capicua), indicating that binding sites are present almost exclusively where the cognate factor is active. The distributions of Bcd and Cad binding sites broadly conform with the anterior and posterior gradients of their respective input factors. The rise in the curves at the posterior terminus for Bcd and at the anterior terminus for Cad is caused by terminal modules expressed at both ends of the embryo. Overall, for the maternal activators, the binding site composition of modules is well fitted to the input factor distribution. Figure 5 Ap Distribution of Binding Sites and Cognate Input Factors (A) Plots depict distribution of input factors (black) along the ap axis (anterior tip = 100, posterior tip = 0) (based on Myasnikova et al. [2001] ) and the average number of binding sites (as measured by integrated profile values; Figure 4 ) found in all modules driving expression at a given percent EL (red) (see Materials and Methods ). For TorRE, Bcd, and Cad, the distributions of binding sites and input factors are positively correlated. For Hb, Gt, and Kr, the distributions are negatively correlated; note that the number of binding sites is particularly high in modules expressed adjacent to the expression domain of these factors. In the case of Hb, modules with more Hb sites than Bcd sites (blue) show negative correlation with input factor distribution, and modules with fewer Hb sites than Bcd sites (green) show positive correlation, indicating bimodal function of Hb. For Kni and Tll, no clear correlations are found, possibly because of the unspecificity of their weight matrices. (B) Information scores of the Kr, Kni, and Tll weight matrices. The Gap Factors The situation regarding the gap factors is more complex. When examining the distributions of Hb, Gt, and Kr binding sites and comparing them with the input factor distributions, we clearly find an anticorrelative relationship: The number of sites is lower in regions where the cognate factor is present, and higher in regions where the factor is absent ( Figure 5 A). Remarkably, the number of sites is particularly high in regions immediately adjacent to the expression domain of the factor. These findings are consistent with the experimental evidence that gap factors act as repressors. Thus, modules which have many sites efficiently suppress expression within the domain of the input factor, and permit expression only outside the domain. The great majority of modules conform to this anticorrelative relationship; we can therefore conclude that, overall, repression is the prevalent mode of action for these gap factors. However, we do find some modules that appear to be coextensively expressed with the presumptive repressors. One possible explanation is that the input factor has a different mode of action in these modules, that is, instead of repression it may mediate activation. Hb appears to be an example for such a switch in the mode of action. We find many modules with a small number of Hb sites that are coextensively expressed with Hb in the anterior, and it has been shown experimentally that Hb function is context dependent: Repressor function has been demonstrated for several posterior modules (e.g., kni_kd, eve_stripe3_7, and eve_stripe4_6 ) ( Pankratz et al. 1992 ; Fujioka et al. 1999 ), while activator function has been demonstrated for several anterior modules (e.g., hb_anterior, Kr_CD1, and eve_stripe2 ) ( Treisman and Desplan 1989 ; Hoch et al. 1990 ; Small et al. 1991 ; Stanojevic et al. 1991 ). It is thought that Hb is converted from a repressor to an activator by the concurrent presence of homeobox factors such as Bcd ( Zuo et al. 1991 ; Simpson-Brose et al. 1994 ). We examined the composition of these two sets of known modules and found that in the posterior modules, in which Hb acts as a repressor, the profile values of Hb exceed those of Bcd, while in anterior modules, in which Hb acts as an activator, the profile values of Hb are lower than those of Bcd. When we apply the simple rule suggested by this observation to all modules containing Hb sites, we find that it significantly improves the picture: the Hb>Bcd (Hb as repressor) set is strongly negatively correlated with Hb factor expression, while the Hb<Bcd (Hb as activator) set is positively correlated with Hb factor expression (the only exception is the D_(+4) module, which drives expression in a broad domain straddling the 50% EL line). Thus, the global distribution profile of Hb sites can largely be explained by introducing a simple contextual rule. By contrast, for Gt and Kr, the number of modules expressed coextensively with the input factor is comparatively small. In the case of Gt, all experimental evidence points to its acting as a repressor. Increasing the spatiotemporal resolution of the plot to reflect the modulation of Gt expression over time may be sufficient to account for the presence of Gt sites in at least some of the potentially “noncompliant” modules ( cnc_(+5), oc_(+7), oc_otd_early, and hb_ant ). In the case of Kr, context-dependent function has been suggested, but mostly based on tissue culture experiments ( Sauer et al. 1995 ; La Rosee et al. 1997 ; La Rosee-Borggreve et al. 1999 ). The four potentially noncompliant modules ( Kr_CD2, run_stripe3, nub_(+5), D_(+4)) are clearly expressed coextensively or overlapping with the Kr input factor. Since the average number of binding sites is low in these modules, it is possible that Kr acts as a repressor but that this manifests itself only in a reduced expression level. In fact, the Kr_CD2 module has been noted to be more weakly expressed than its sister module Kr_CD1, which lacks Kr sites ( Hoch et al. 1990 ), but there are too many other differences in their binding site composition to draw any firm conclusions. These noncompliant modules provide a solid experimental platform for resolving the issue of whether or not Kr truly switches its mode of action in vivo. Finally, for Kni and Tll, most experimental evidence points to repression, but context-dependent activation has been suggested in a few cases ( Langeland et al. 1994 ; Margolis et al. 1995 ; Kuhnlein et al. 1997 ; Hartmann et al. 2001 ). As noted at the beginning, the weight matrices for both factors are fairly unspecific ( Figure 5 B), resulting in a lower level of confidence in the predictions, which typically show a large number of binding sites. When plotting binding site and input factor distributions, no clear positive or negative correlations are visible ( Figure 5 A), suggesting either strong context-dependent function—which is not really supported by the extant literature—true indiscriminate binding, or simply poor binding site information. Unfaithful Modules In our experimental tests, we found a few novel modules that drive unfaithful patterns. Can we understand their behavior based on the composition profile of the module? We observed two flavors of unfaithful expression: strong invariant and weak variable. The kni_(+1) module is an example of the former: It drives expression in a posterior domain that is wider than the endogenous pattern (see Figure 3 A). When compared to the faithful kni_kd module, kni_(+1) contains the same types of binding sites, but with different profile values: The profile values for the activator Cad are higher and the ones for the repressors Hb, Kr, and Tll are lower (see Figure 4 ). This suggests that an increase in activator binding together with a decrease in binding by adjacently expressed repressors may be responsible for the widening of the posterior domain. The pdm2_(+3) module is an example of weak and unstable expression (see Figure 3 C), which we find more often when analyzing subthreshold peaks. Such modules typically suffer from a reduced number of activator sites and an increase in sites for coextensively expressed repressors (see Figure 4 ). Thus, the two flavors of unfaithful patterns, strong invariant and weak variable, appear to correlate with the ratio of activator to repressor sites in the module and the degree to which the distributions of the relevant input factors are compatible. Further experimental and computational work will be required to determine precise module composition rules, but both faithful and unfaithful modules can contribute to defining them. Evolutionary Conservation The availability of the Drosophila pseudoobscura genome makes it possible to ask how well segmentation modules are conserved. In a previous study, Emberly et al. (2003) showed that the degree of sequence conservation between D. melanogaster and D. pseudoobscura is not significantly higher in known segmentation modules than in surrounding noncoding regions, suggesting that sequence conservation per se is not sufficient to identify such modules. We obtain the same result for our Ahab predictions (data not shown). However, when we run Ahab over the aligned segmentation gene control regions in D. pseudoobscura, using D. melanogaster weight matrices as input, we recover as significant predictions about the same number of known modules as in D. melanogaster, indicating that there is substantial functional conservation (see Materials and Methods ). However, only 24 of the 35 known and newly validated modules that are recovered in D. melanogaster also score as significant predictions in D. pseudoobscura, with an additional seven as subthreshold peaks (see Figure 4 ). Conversely, four subthreshold D. melanogaster modules are recovered as significant predictions in D. pseudoobscura, and three known modules are recovered only in D. pseudoobscura . Thus, modules with maternal/gap input appear to be in some evolutionary flux, which needs to be taken into consideration if evolutionary conservation is employed as a tool in module discovery. Regulatory Input within the Segmentation Gene Hierarchy Given Ahab's success in predicting modules with maternal and gap input, we decided to expand the analysis to the entire segmentation gene network and explore the algorithm's performance when less well defined binding site information is available. To this end, we included the control regions of a total of 48 genes: To the genes with gap-like and pair-rule patterns, we added segment-polarity and homeotic genes (for references see Dataset S1 ). Concurrently, we expanded the set of binding site inputs. The maternal and gap factors were used as before (mg run). In addition, we collected binding site information from the literature for the pair-rule factors Hairy (H), Even skipped (Eve), Runt (Run), Fushi tarazu (Ftz), Ftz transcription factor 1 (Ftz-f1), Paired (Prd), and Tramtrack (Ttk) ( Dataset S2 ). For all these factors the available binding site information is generally less extensive and relies less on in vivo and more on in vitro experiments such as Selex. This again has the consequence that the weight matrices are artificially more specific, resulting in the prediction of fewer sites but higher scores for a match. The pair-rule factors were run by themselves (pr run) and in combination with the maternal and gap factors (mgpr run), with window size 500 and background model 2. In the combined control regions of the entire set of 48 segmentation genes, which total 1.7 Mb in length, we find 82 significant peaks for the mg run (score >15), 56 for the pr run (score >15), and 69 for the mgpr run (score >22, cutoff set to equal genome-wide mean plus four standard deviations), in total 145 distinct putative modules, an average of approximately three per gene. Interestingly, the mg run and pr run peaks are completely nonoverlapping. We determined the relative contribution of maternal/gap and pair-rule input to each predicted module by evaluating its binding site composition as revealed by the mgpr run, i.e., using all input factors. Modules were classified into four types: maternal/gap driven, pair-rule driven, or driven by both but with bias towards maternal/gap input or pair rule input (see Materials and Methods ). The number and types of modules found within the control region of each target gene are shown in Figure 6 B. For the genes with gap-like expression, maternal and gap input strongly predominates; for pair-rule and segment-polarity genes, pair-rule input predominates. The homeotic genes receive both types of input. This global result reflects very well the overall regulatory structure of the segmentation gene network. However, we find interesting exceptions to the global rules. Among the pair-rule genes, odd stands out as receiving unexpectedly strong maternal/gap input. odd is expressed in a pair-rule and then segment-polarity pattern ( Coulter et al. 1990 ) and has traditionally been placed among the secondary pair-rule genes ( Klingler and Gergen 1993 ; Pankratz and Jäckle 1993 ; Pick 1998 ). But as our dissection reveals (see Figure 3 E), odd receives strong maternal/gap input and generates at least four of its seven stripes via two-stripe modules, suggesting that it in fact belongs to the primary pair-rule tier. In addition, as noted above, the control region of the secondary pair-rule gene slp2 contains a subthreshold peak with maternal/gap input that drives its early gap-like expression in the head region (see Figure 2 G). Finally, we also examined the position of known and predicted modules relative to the transcription start site of the gene ( Figure 7 ) We found that maternal/gap-driven (mg run) modules are strongly biased toward the proximal upstream region (−6 to 0 kb), the first 2 kb of intronic space, and the proximal downstream region (+2 to +4 kb). This clustering is found for the gap, pair-rule, and segment-polarity genes, whose genomic organization is typically simple, but not for the homeotic genes, which typically have much larger control regions and multiple large introns, with wide scattering of predicted modules. For pair-rule-driven (pr run) modules, a similar though less pronounced clustering is observed (data not shown). Figure 7 Genomic Position of Modules Position of modules predicted by the Ahab mg run relative to the transcription start site of the cognate loci; predictions for the homeotic genes are excluded. The number of modules found at a given position is shown in blue. The black line indicates the probability of a module occurring at a given position (calculated by dividing the number of modules at a given position by the number of control regions extending to that position). The stippled black line shows that probability if modules were randomly distributed. Modules with maternal/gap input are clustered within the first 6 kb upstream, in the first 2 kb of intronic space, and around 2 kb downstream (measured from the end of the gene). Discussion In this study we have demonstrated that the Ahab algorithm can be used successfully for two purposes: the prediction of novel segmentation modules within genomic sequence and the prediction of module binding site composition. The computational analysis of control regions with Ahab dramatically improves the efficiency of the experimental dissection, allowing us to significantly increase the number of validated cis- regulatory elements from 31 to 46 and to provide effective de novo dissections for ten segmentation genes. Two principal factors contribute to this success. First, the existing experimental data for the segmentation gene network provide a rich substrate for the computational effort. Second, the biochemistry underlying the regulation of transcription, that is, the binding of transcription factors to DNA, is well described by equilibrium thermodynamics ( von Hippel and Berg 1986 ; Berg and von Hippel 1987 , 1988a , 1988b ; Ptashne and Gann 2001 ), and thus Ahab's use of equilibrium conditions to predict the number, type, and occupancy of binding sites within a window of genomic sequence mimics the intrinsic process. The global analysis of the segmentation gene hierarchy shows that the prevalence of maternal/gap input strongly correlates with gap-like expression, while the prevalence of pair-rule input strongly correlates with segmental expression. Integrating the inputs over all modules within the control region of a gene provides a reliable indication of its type of expression pattern and position within the hierarchy. In fact, the integrated predictions are so accurate as to pinpoint abnormalities in the gene classification, such as the known head gap function of slp2, and also the hitherto unknown primary pair-rule character of odd . Since our knowledge of input factor sites is incomplete (particularly regarding the pair-rule factors), these positive results are likely to reflect the redundant and combinatorial nature of the input. Ahab performs well not only in identifying modules, but also in predicting their composition, thus permitting an analysis of binding site composition under uniform criteria for the entire set of known and newly validated maternal/gap-driven modules. Gene expression studies in mutant embryos have revealed the global regulatory interactions within the segmentation gene network ( St Johnston and Nusslein-Volhard 1992 ; Pankratz and Jäckle 1993 ; Rivera-Pomar and Jackle 1996 ; Furriols and Casanova 2003 ), but are not suited to uncover redundancies within the network or to separate direct from indirect effects. This becomes possible by examining the inputs into the cis- regulatory modules. We find that the vast majority of the modules expressed in the early blastoderm contain maternal factor sites, which strongly suggests that the maternal gradient systems of Cad, Hb, Bcd, and Torso (through its transcriptional effectors) have most, if not all, of the early zygotic patterning along the ap axis under their direct control. Together with the strong interdependence of the maternal gradient systems, this massively parallel output would explain the coordinated and long-range effects on segmentation gene expression patterns that are observed when maternal factors are titrated up or down through genetic manipulation. Further, by correlating the binding site content of modules driving expression at a given position with input factor distributions, we are able to infer the mode of action for six of the nine factors and to show that modules are generally well fitted to the distributions of their positive and negative input factors. The maternal factors act as activators within their domain of expression, while the gap factors act largely as repressors. This overall result confirms previously existing data and demonstrates that the rules gleaned earlier from rather small datasets generalize very well over the entire set. Interestingly, our data also provide support for the idea that Hb functions in a bimodal fashion and suggest a simple rule for its context-dependent switch from repression to activation. Modules with few Hb and many Bcd sites drive expression in the anterior half of the embryo, while modules with more Hb than Bcd sites do not. Depending on module composition and Bcd availability, Hb can thus activate transcription; this Bcd/Hb synergy could serve to bolster transcriptional activation in regions where Bcd levels taper off. For Kni and Tll, the mode of action cannot be assessed on the basis of the extant binding site information. The comparison of modules with faithful and unfaithful or unstable patterns provides some interesting additional clues for composition rules, such as the ratio and compatibility of activator and repressor sites. However, to address the question of how the precise domain boundaries are established within a given region of the embryo, a more detailed examination of composition rules and of the internal organization of modules will be needed, specifically of rules governing the number, affinity, spacing, and arrangement of binding sites. This analysis will require different types of experimentation as well as additional computational analysis. The performance of Ahab is influenced by a number of parameters, but the most important is the quality of the input factor weight matrices. To further improve weight matrices, more sites for undersampled factors will have to be collected (D-Stat and Gt), and existing sites for the unspecific factors will have to be scrutinized (Kni and Tll). More importantly, the relative affinity of binding sites for their factor will have to be measured in a more comprehensive fashion. The ideal experiment would measure, under identical conditions, the relative binding affinity of the consensus sequence to all possible single base mutations in the consensus binding site ( Benos et al. 2002 ). For some segmentation modules, the currently predicted binding site composition is clearly insufficient to explain their expression, indicating that some of the relevant input has not been characterized. We have experimented with motif-finding algorithms and found that novel, biologically functional binding motifs can be identified by searching for locally overrepresented motifs within known modules and filtering out the known input factor binding sites (see Rajewsky et al. 2002 ; J. F., M. P., M. D. S., and U. G., unpublished data), which suggests that computational methods can also assist the identification of novel input factors. With an Ahab run that recovers 70% of the known modules with predominant maternal/gap input, we predict another 32 putative modules in the control regions of gap and pair-rule genes. Most of these look plausible in terms of genomic location and composition, and as our validation shows, many drive blastoderm expression that faithfully reproduces the endogenous pattern of the gene. However, we also found modules whose expression does not match the endogenous pattern (unfaithful/unstable) or whose composition does not suggest any coherent expression pattern (e.g., no activator sites); among the latter are some predictions dominated by Kni and Tll sites, which are potentially problematic because of the unspecificity of their weight matrices. The apparently anomalous modules could drive expression at later stages of development or could simply be artifacts of improper delineation or missing relevant input. A more intriguing possibility is that some of these modules are in evolutionary transit—nascent or dying. Such modules might be held in check by relatively few point mutations (“pseudo” modules), by nearby insulator elements, or by restricted access to the basal promoter when competing with the functional modules. The effort to discover the true nature and function of these anomalous modules will be aided by the computational and experimental comparison of corresponding modules in D. melanogaster and D. pseudoobscura . Materials and Methods Position weight matrices and Ahab runs When possible, previously compiled position weight matrices were used: for Bcd, Hb, Cad, TorRE, Kr, Kni, and Tll ( Rajewsky et al. 2002 ), and for Ftz, Prd_HD, and Ttk ( Papatsenko et al. 2002 ). For H, Run/CBF, and D-Stat, we directly used in vitro selection data ( Melnikova et al. 1993 ; Van Doren et al. 1994 ; Yan et al. 1996 ). For Eve_HD, the alignment was taken from the literature ( Hoey et al. 1988 ), for Gt, Eve_t2, and Ftz-f1, footprinted sites from the literature were aligned ( Hoey et al. 1988 ; Biggin and Tjian 1989 ; Ueda et al. 1990 ; Jiang et al. 1991 ; Capovilla et al. 1992 ; Fujioka et al. 1996 ; Florence et al. 1997 ; Yu et al. 1997 ; Shimell et al. 2000 ). The binding sites, alignments, and weight matrices used plus references are listed in Dataset S2 . For description and mathematical details of the algorithm, see Rajewsky et al. (2002) . All runs were carried out on Drosophila genome sequence Release 2 after masking tandem repeats in the genomic sequence as described in Rajewsky et al. (2002) . Control regions were defined as the sequence surrounding a gene and limited by the two flanking genes, up to a maximum of 20 kb upstream and 10 kb downstream, and with a buffer for the flanking genes of 2 kb upstream and 1 kb downstream. For the homeotic genes, no maximum for the upstream or downstream extension of the control region was imposed. Mapping of known modules The genomic position of known modules was derived from literature ( Papatsenko et al. 2002 ; Rajewsky et al. 2002 ) or mapped to genomic sequence from the literature using restriction sites, PCR primers, or distances relative to transcription start site. For a complete list and description see Dataset S3 . Significance of Ahab predictions To assess the significance of Ahab module predictions, we calculated the overlap between predictions and known modules in basepairs, and compared it with the overlap achieved when predictions are randomly placed within the delineated control regions (minus masked and coding sequence). We failed to match the actual overlap through 10 8 randomizations, resulting in an estimate of p < 10 −8 for the significance of the recovery of known modules by Ahab. When we remove from the calculation the 13 modules that were used for the construction of weight matrices (Kr_CD1, Kr_CD2_AD1, eve_stripe3_7, eve_stripe2, h_stripe5, h_stripe6, hb_anterior_actv, hb_central_&_posterior_actv, kni_kd, oc_head, tll_K2, tll_P2, and tll_P3 ), along with the kni, hb, and tll control regions, which contain no additional annotated modules, we find p = 4.9 × 10 −6 . Ahab recovery of known binding sites The experimental binding sites that define our weight matrices are derived from a variety of in vitro experiments that typically neglect competition between transcription factors, whereas Ahab, in its prediction of binding sites, fits all factors simultaneously. To gauge whether Ahab can be used as a predictor of module composition, we examined what fraction of known binding sites the algorithm recovers. The only free parameter in the comparison is the profile value (between 0 and 1), which measures the fractional occupancy of a site by its factor; a profile value of 1 means that a site is always occupied by its factor. A site was scored as found if the prediction exceeded a certain profile value cutoff and overlapped the experimental footprint by more than 50%. Table 1 correlates the recovery of sites with the specificity of the weight matrices for two profile value cutoffs. Overall, the recovery ranges from 50% to 100%, with the most specific factors/matrices showing the best recovery. Table 1 Recovery of Known Binding Sites The table shows the fraction of known maternal and gap factor binding sites recovered by Ahab, with profile value cutoffs of 0.25 and 0.5, respectively. The specificity of the weight matrices (“WM Specificity”) is characterized in terms of the distribution of profile values reported by Ahab when run over the sequence of all modules containing known binding sites. The numbers indicate the portion of profile values that exceed the cutoff compared to all profile values; for example, column five for Kr means that 60% of the predicted sites have a profile value greater than 0.50 We further examined whether Ahab misses known sites by misclassification. We found that Ahab generally does not misattribute the missing sites to another factor. A cogent example is provided by Cad and Hb, which have very similar binding sites containing an oligoT stretch. Surprisingly, none of the 21 Hb sites that were missed at a profile value cutoff of 0.5 were misclassified as Cad; conversely, only one of the 11 missed Cad sites was classified as Hb. This discrimination is far better than that achieved by a simple weight matrix scan over the same modules: for this scan, we counted information scores greater than five, which is the score of the weakest experimental binding sites, and overlaps between matrix and binding site of 50% or more. The matrix scans correctly classified 29/43 Hb sites and 16/21 Cad sites; but misclassified five Hb sites as Cad and two Cad sites as Hb. Taken together, Ahab finds the majority of known binding sites and rarely misclassifies; it is thus a reliable indicator of module composition. A complete listing of the integrated profile values reported by Ahab for known, newly validated, and predicted modules is available in Dataset S6 (mg run) and Dataset S7 (mgpr run). Recovery of modules in Drosophila pseudoobscura To assess the conservation of known and Ahab-predicted modules, we aligned D. melanogaster and D. pseudoobscura genomic sequence as described in Emberly et al. (2003) and ran Ahab over the aligned D. pseudoobscura control regions, with D. melanogaster weight matrices as input and with cutoffs for significant predictions (15 in D. melanogaster ) and subthreshold peaks (12 in D. melanogaster , equal to genome-wide mean plus three standard deviations) set to obtain equivalent numbers of predictions in D. pseudoobscura. D. pseudoobscura predictions were then mapped to D. melanogaster coordinates and examined for overlap with the known and predicted D. melanogaster modules. Processing of Ahab output and module classification To associate predictions from different Ahab runs, each run was processed and the highest point on the free energy plot within an interval of the window size was marked as a “peak.” Peaks are thus spaced by at least the window size. Peaks in two different runs correspond if they are closer than half the window size; their correspondence is unique and order independent. For the three-way comparison, the mg and pr runs were separately compared to the mgpr run. In no case did mg run and pr run peaks correspond without at least one of them matching a mgpr run peak. For the purposes of broadly classifying predicted modules as to type of input, we defined four classes: mostly maternal/gap input, mostly pair-rule, and mixed input but with a bias towards maternal/gap or pair-rule. Two classification methods were used. The first relied on a single Ahab run with all factors (mgpr run) and then compared the sum of the maternal/gap factor profile values for a given module with the sum of the pair-rule profile values, after normalization to make the mean and standard deviation of maternal/gap profile values over all peaks equal to the mean and standard deviation of all pair-rule profile values. An alternative scheme used the free energy plots for the three runs (mg, pr, and mgpr), identified corresponding peaks, and then compared their rank in the different runs. The two methods yielded very similar results. Since Ahab does not adapt its window size to the data, modules that are wider than the window size needed to be delineated to be captured accurately. To this end, we defined the start of the module as the first local maximum in the free energy plot that is above the cutoff. The end point was initialized as the other end of the corresponding Ahab window. The plot was then scanned from left to right, and when another local maximum or rise in window score above the cutoff was encountered, the end point of the module was reset as the end of the corresponding window. The sequence of all delineated predicted modules is available in Dataset S5 . Molecular biology and RNA in situ hybridization Module predictions were tested as follows. The module was delineated within the genomic sequence as described above and further expanded to include good primer sites for touch-down PCR. Primers were designed following manufacturer's guidelines (Clontech, Palo Alto, California, United States), restriction sites (Xba, Asp718) were added for subsequent cloning. Genomic PCR products were cloned into TOPO (Invitrogen, Carlsbad, California, United States), sequenced to confirm identity, and subcloned into Casper hs43ßGAL ( Thummel and Pirrotta 1991 ). A Fasta file with the primers and cloned regions is available in Dataset S4 . Transgenic fly strains were generated using standard methods. For each construct three independent insertions were analyzed for expression patterns by RNA in situ hybridization with a lacZ probe. RNA in situ hybridizations were carried out as described by Noordermeer and Kopczynski ( http://www.fruitfly.org/about/methods/RNAinsitu.html ). Delineation of protein and transcript patterns The protein expression profiles of the maternal and gap input factors were obtained from http://flyex.ams.sunysb.edu ( Myasnikova et al. 2001 ) (temporal class 4, 10% strip, normalized and registered by FRDWT, averaged over 5% EL). In cases where these data were not available, input factor expression profiles were inferred from literature (D-Stat) or our own data (TorRE, measured by expression of the negative regulator Capicua). The output transcript patterns of segmentation gene modules were determined using images of our own RNA in situ hybridizations of blastoderm embryos, and complemented by data from the literature. Embryos were viewed in the sagittal plane, and the intersection of the domain boundaries with the longitudinal axis was determined and calculated as percent EL. Measurements were performed using the Zeiss (Oberkochen, Germany) Axiovision 3.1 measurement tool and averaged over 2–5 embryos. A complete listing of the references for the expression patterns of segmentation genes is found in Dataset S1 . To generate the plots in Figure 5 A, we calculated, for every input factor and for every position along the ap axis, the average of the integrated profile values reported by Ahab for the modules driving expression at that position. Values were calculated in 1% EL increments, then averaged over 5% EL. Supporting Information The Gbrowse display of free energy profiles for genome-wide Ahab runs (mg, pr, mgpr) can be viewed at http://edsc.rockefeller.edu/cgi-bin/gbrowse_ms/cgi-bin/gbrowse?src=fly . Dataset S1 Segmentation Genes Referred to in This Study The dataset gives name, symbol, flybase identifier, and references for expression pattern, control region dissection, and binding site information. (178 KB DOC). Click here for additional data file. Dataset S2 Compilation of Position Weight Matrices and Binding Sites Used in This Study (8 KB TXT). Click here for additional data file. Dataset S3 Sequence Information for Known Segmentation Modules in Fasta Format (80 KB TXT). Click here for additional data file. Dataset S4 Sequence Information for Transgenic Constructs Used in This Study in Fasta Format (37 KB TXT). Click here for additional data file. Dataset S5 Sequence Information for Ahab-Predicted Modules in the Control Regions of 48 Segmentation Genes Data based on mg run, Fasta format. (53 KB TXT). Click here for additional data file. Dataset S6 Profile Value Output for Ahab Mg Run Input: Bcd, Hb, Kr, Gt, Kni, Tll, Cad, TorRE, and Dstat. Performed over defined sequences of known modules ( Dataset S3 ), tested constructs ( Dataset S4 ), and Ahab-predicted modules ( Dataset S5 ). (62 KB TXT). Click here for additional data file. Dataset S7 Profile Value Output for Ahab Mgpr Run Input: Bcd, Hb, Kr, Gt, Kni, Tll, Cad, TorRE, Dstat, H, Eve_HD, Eve_t2, Run, Ftz, Ftz-f1, Ttk, and Prd_HD. Performed over defined sequences of known modules ( Dataset S3 ), tested constructs ( Dataset S4 ), and Ahab-predicted modules ( Dataset S5 ). (77 KB TXT). Click here for additional data file. Accession Numbers The FlyBase ( http://flybase.bio.indiana.edu ) accession numbers for the genes and gene products discussed in this paper are Bcd (FBgn0000166), Cad (FBgn0000251), Capicua (FBgn0028386), cnc (FBgn0000338) , D (FBgn0000411), D-Stat (FBgn0016917), Eve (FBgn0000606), fkh (FBgn0000659) , Ftz (FBgn0001077), Ftz-f1 (FBgn0001078), Gt (FBgn0001150), H (FBgn0001168), Hb (FBgn0001180), Kni (FBgn0001320), knrl (FBgn0001323) , Kr (FBgn0001325), nub (FBgn0002970), oc (FBgn0004102), odd (FBgn0002985) , pdm2 (FBgn0004394), Prd (FBgn0003145), Run (FBgn0003300), slp2 (FBgn0004567), Tll (FBgn0003720), TorRE (cf. FBgn0003733), and Ttk (FBgn0003870).

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529251

Single photon emission computed tomography (SPECT) of anxiety disorders before and after treatment with citalopram

Background Several studies have now examined the effects of selective serotonin reuptake inhibitor (SSRI) treatment on brain function in a variety of anxiety disorders including obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD), and social anxiety disorder (social phobia) (SAD). Regional changes in cerebral perfusion following SSRI treatment have been shown for all three disorders. The orbitofrontal cortex (OFC) (OCD), caudate (OCD), medial pre-frontal/cingulate (OCD, SAD, PTSD), temporal (OCD, SAD, PTSD) and, thalamic regions (OCD, SAD) are some of those implicated. Some data also suggests that higher perfusion pre-treatment in the anterior cingulate (PTSD), OFC, caudate (OCD) and antero-lateral temporal region (SAD) predicts subsequent treatment response. This paper further examines the notion of overlap in the neurocircuitry of treatment and indeed treatment response across anxiety disorders with SSRI treatment. Methods Single photon emission computed tomography (SPECT) using Tc- 99 m HMPAO to assess brain perfusion was performed on subjects with OCD, PTSD, and SAD before and after 8 weeks (SAD) and 12 weeks (OCD and PTSD) treatment with the SSRI citalopram. Statistical parametric mapping (SPM) was used to compare scans (pre- vs post-medication, and responders vs non-responders) in the combined group of subjects. Results Citalopram treatment resulted in significant deactivation (p = 0.001) for the entire group in the superior (t = 4.78) and anterior (t = 4.04) cingulate, right thalamus (t = 4.66) and left hippocampus (t = 3.96). Deactivation (p = 0.001) within the left precentral (t = 4.26), right mid-frontal (t = 4.03), right inferior frontal (t = 3.99), left prefrontal (3.81) and right precuneus (t= 3.85) was more marked in treatment responders. No pattern of baseline activation distinguished responders from non-responders to subsequent pharmacotherapy. Conclusions Although each of the anxiety disorders may be mediated by different neurocircuits, there is some overlap in the functional neuro-anatomy of their response to SSRI treatment. The current data are consistent with previous work demonstrating the importance of limbic circuits in this spectrum of disorders. These play a crucial role in cognitive-affective processing, are innervated by serotonergic neurons, and changes in their activity during serotonergic pharmacotherapy seem crucial.

Background Significant advances in our understanding of the mediating psychobiology and the development of effective treatments for anxiety disorders have been made in recent years. Modern brain imaging techniques have proved useful in exposing specific albeit overlapping neurocircuitry that underlies individual anxiety disorders [ 1 , 2 ]. However, relatively little work has focused on the extent to which the anxiety disorders overlap with respect to changes in brain perfusion that accompany response to first-line treatment that is after all pharmacologically similar for different disorders. The selective serotonin reuptake inhibitors (SSRIs) are currently recommended as first line medications for most anxiety disorders, including obsessive-compulsive disorder (OCD) [ 3 ], posttraumatic stress disorder [ 4 ] and social anxiety disorder [ 5 ]. A number of imaging studies have now examined the effects of SSRI's on brain perfusion in individual anxiety disorders. In OCD, attenuation of pre-treatment regional activation has been shown to correlate with treatment response in the anterolateral orbitofrontal cortex (OFC), caudate nucleus, thalamus, and temporal regions [ 6 - 11 ]. Results for studies assessing pre-treatment cerebral perfusion as a predictor of response, have, however, yielded mixed results. In some, an inverse relationship appears to exist with pre-treatment regional activation of the OFC [ 12 ], anterior cingulate, caudate [ 6 ] and subsequent responses to treatment. Conversely findings of higher prefrontal, cingulate and basal ganglia activation correlating with subsequent treatment response have also been reported [ 13 , 14 ]. In OCD co-morbid with depression, substrates of response to the SSRI, paroxetine, appear to differ based on pretreatment [ 15 ] activation patterns as well as changes that accompany treatment response when an SSRI is given in identical doses for either of the two conditions separately [ 16 ]. In social anxiety disorder SSRI treatment response accompanies attenuation of frontal, anterior and lateral temporal cortex, cingulate, and thalamic activity [ 17 , 18 ]. Higher anterior and lateral temporal cortical perfusion at baseline correlated with subsequent treatment response in the former study. The latter study also demonstrated some overlap of regions demonstrating attenuation of activity for both cognitive and pharmacotherapy interventions. In PTSD, a single study by our group demonstrated medial temporal lobe deactivation with treatment irrespective of clinical response and medial prefrontal cortex activation correlated with treatment response. In addition, no baseline differences distinguished responders and non-responders to subsequent SSRI treatment [ 19 ]. In this present study, we hypothesised firstly, that response to SSRI treatment in this combined group of subjects with anxiety disorders (OCD, PTSD, SAD) would effect shared changes in rCBF affecting primarily limbic and related prefrontal regions and thus suggest some overlap between disorders in the mechanism of their response to effective treatment with SSRI's. Secondly, pre-treatment differences in regional perfusion would likely differentiate responders to subsequent treatment with citalopram across the anxiety disorders. Methods Subjects Adult subjects with a primary diagnosis of OCD (n = 11), PTSD (n = 11) or SAD (n = 15) were recruited from the Anxiety Disorders Clinic of our tertiary hospital. All subjects were interviewed with the Structured Clinical Interview for the Diagnosis of Axis-I Disorders [ 20 ] to ascertain diagnosis according to DSM-IV criteria. Results for the PTSD group have been reported previously [ 19 ]. Comorbid major depression was an exclusion criterion in the OCD and SAD, but not in the PTSD subjects. Nevertheless, in all cases comorbid disorders were considered secondary in terms of temporal course, symptom severity, and associated distress. Patients previously treated with SSRI's had been free of medication for a minimum of four weeks for fluoxetine and two weeks for other SSRI's. In total 30 (81%) of the group were SSRI naïve. Subjects with other central nervous system disorders including previous head injury or epilepsy were excluded. The Institutional Review Board of our University approved the protocol and all patients gave informed written consent after a full explanation of the possible risks and benefits. Pharmacotherapy and measures All patients underwent treatment with citalopram, the most selective of the currently available selective serotonin reuptake inhibitors (SSRIs). The duration of the trial of treatment was 12 weeks for OCD and PTSD, and 8 weeks for SAD. Dosage was initiated at 20 mg daily for the first two weeks and then maintained at 40 mg daily for the remainder of the study. Measures of symptom improvement were made bi-weekly by clinicians using the Clinical Global Impressions (CGI) scale [ 21 ]. Subjects with a CGI change score of 2 or less post-treatment were defined as responders, while those with scores greater than 2 were defined as non-responders. Anxiety symptoms were also rated using disorder specific scales including the Liebowitz Social Anxiety Scale(LSAS) [ 22 ], the Yale Brown Obsessive-Compulsive Scale (YBOCS) [ 23 ] and the Clinician Administered Scale for PTSD [ 24 ]. Depressive symptoms were rated using the Montgomery-Asberg Depression Rating Scale (MADRS) [ 25 ]. SPECT imaging Single photon emission computed tomography (SPECT) was conducted before and after pharmacotherapy. Subjects lay supine in a quiet dimly lit room for 30 minutes prior to injection of the radiopharmaceutical. Apart from administration of the injection by a physician, they remained alone in the room during this period. Subjects were asked to remain at rest during the 30 minute period and for 10 minutes after injection of the radiopharmaceutical. An injection of 555 MBq (15 mCi) of technetium-99 m hexamethylpropylene amine oxime (Tc-99 m HMPAO) was given into an arm vein through a previously placed intravenous cannula. After completion of the rest period, SPECT imaging of the brain was performed, with the subject's head supported by a headrest, using a dual detector gamma camera (Elscint, Helix, GE Medical Systems, USA) equipped with fan beam collimators. Data were acquired in the step-and-shoot mode, using a 360 degree circular orbit, with the detectors of the gamma camera as close as possible to the subject's head. The height of the imaging table and radius of rotation were noted for each subject and the same measurements were used for the follow-up study. Data were acquired using a 128 × 128 image matrix in 3 degree steps of 15 seconds per step. Data were reconstructed by filtered backprojection, using a Metz filter (power = 5, FWHM = 14 mm) and a zoom factor of 2.29. The Chang (1978) method was used for attenuation correction. Scatter correction was not performed. The final reconstructed pixel size was 3.87 mm by 3.87 mm. Image files were converted from interfile to analyze format using conversion software (Medcon, Erik Nolf, UZ Ghent). Stastical analyses were conducted on a voxel-by-voxel basis using the Statistical Parametric Mapping (SPM99, Wellcome Department of Cognitive Neurology, UK) [ 26 ]. The realign function was used to co-register baseline and posttreatment SPECT images for each subject and to generate a mean image for each subject. Realigned images were then normalised to the Montreal Neurological Institute (MNI) standard anatomical space to a value of 50 using proportional scaling. For this the transform function from the mean image for each subject to the normalised image with 4 mm 3 voxels using 12 affine transformations and 7 × 8 × 7 non-linear basis functions was used. Standardised images were then smoothed using a Gaussian kernel with a FWHM of 12 mm 3 . A multi-group study design was performed using 2 groups (responders and non-responders) with 2 conditions each (pre- and post-treatment). Contrasts were applied to look for areas of significant change post-treatment compared to pre-treatment. Contrasts were also used to search for areas of relative change in treatment responders compared to non-responders. A second design was employed to compare the baseline scans of responders to SSRI pharmacotherapy with those of non-responders. Contrasts were used to search for regions of significant differences on the baseline scans of responders compared to non-responders. In view of a priori knowledge suggesting involvement of the cingulate, hippocampus, inferior frontal cortex, and striatum in the anxiety disorders, an uncorrected p-value of p < 0.001 corresponding to a t value of 3.34, was chosen for the analysis of these regions in order to minimize type I errors. Given the relative paucity of data in this area, we chose this uncorrected p-value, based on work using a similar methodology [ 19 ]. In order to minimize type I errors a significance level of p < 0.05 corrected for Gaussian Random Field Theory was used for the remainder of the brain. A spatial extent threshold of 5 voxels was also used at all times. Masking using a threshold proportional to 0.4 times the mean voxel value was used to minimize the analysis of voxels not located in grey matter. Furthermore, clusters were ignored if co-registration with a SPECT template demonstrated that they were located outside of grey matter. Results Twenty-two males and fifteen females with a mean age of 33.5 years (SD 9.8) completed the study. Clinical changes with pharmacotherapy for each disorder are provided in Table 1 . This shows that for each of the anxiety disorders being studied, citalopram was effective in significantly reducing clinical measures of severity as determined by a CGI change score of 2 or less (much or very much improved). As such, 20 of 37 patients (54%) were responders to citalopram. Table 1 Clinical parameters for all the groups (mean ± SD), (paired t-test). Baseline Endpoint p OCD (n = 11) YBOCS 26.6 ± 4.7 23.7 ± 5.8 0.001 MADRS 13.64 ± 9.6 9.9 ± 6.4 0.119 CGI-severity 4.7 ± 0.647 4.18 ± 1.1 0.025 CGI-improvement 3.1 ± 0.7 SAD (n = 15) LSAS 79.2 ± 30.2 63.1 ± 28.5 0.003 MADRS 15 ± 4.9 9.1 ± 5.9 0.004 CGI-severity 4.6 ± 0.8 3.3 ± 1.1 0.001 CGI-improvement 2.7 ± 1.2 PTSD (n = 11) CAPS 78.1 ± 16.9 45.5 ± 23.9 <0.01 MADRS 25 ± 6.7 15.9 ± 8.0 <0.01 CGI -severity 4.5 ± 0.5 2.5 ± 0.7 <0.01 CGI-improvement 1.9 ± 0.7 YBOCS, Yale Brow Obsessive-compulsive scale; MADRS, Montgomery Asberg Depression Rating scale; CGI-s, Clinical global impressions severity; CGI-I, Clinical global impressions – improvement; LSAS, Liebowitz Social Anxiety Scale; CAPS, Clinician Administered PTSD scale. Comparison of pre- and post-treatment scans for the whole group showed decreased activity in 4 significant clusters in grey matter (Figure 1 ): These included the superior cingulate, right thalamus, anterior cingulate, and the left hippocampus (Table 2 ). Comparison of pre- and post-medication scans showed no significant areas of activation. Figure 1 Combined group deactivation following treatment with citalopram. Regions of deactivation for the combined group of OCD + SAD + PTSD following treatment with citalopram. Significant grey matter clusters are seen in the superior cingulate, anterior cingulate, left medial temporal region (hippocampus). Table 2 Localisation of significant clusters of deactivation following treatment for the combined group of OCD, SAD, PTSD. Z max set to threshold of t = 3.34 corresponding to p < 0.001 Cluster size (voxels) t MNI co-ordinates (x,y,z) Brain region 44 4.78 -4,12,36 Superior cingulate 19 4.66 24,-28,12 Right thalamus 10 4.04 0,48,8 Anterior cingualate 7 3.96 -24,-12,-20 Left hippocampus Comparison of responders with non-responders demonstrated that responders had a significantly greater decrease of activity in 4 clusters (Figure 2 ). These clusters were localised to the left precentral, right middle frontal, right inferior frontal and, left prefrontal regions (Table 3 ). Comparison of baseline scans of responders and non-responders did not reveal any significant differences. Figure 2 Regional deactivation (responders > non-responders). Grey matter clusters of greater deactivation in responders vs non-responders were detected in the left precentral, prefrontal and right mid - and inferior-frontal regions. Table 3 Localisation of significant clusters of deactivation in responders vs non-responders to SSRI treatment for the combined group of OCD, SAD, PTSD. Z max set to threshold of t = 3.34 corresponding to p < 0.001 Cluster size (voxels) t MNI co-ordinates (x,y,z) Brain region 21 4.26 -24,-20,56 Left precentral 33 4.03 12,64,-8 Right mid-frontal 17 3.99 36,32,-20 Right inferior frontal cortex 5 3.85 8,-48,16 Right precuneus 18 3.81 -28,60,-8 Left prefrontal Discussion The main finding of this paper was that citalopram pharmacotherapy resulted in significant deactivation within anterior and superior cingulate cortex, the left hippocampus and the right thalamus in a combined group of patients with different anxiety disorders (OCD, PTSD, and SAD). Furthermore, deactivation was significantly more apparent in responders than in non-responders to SSRI treatment within precentral, right inferior, middle frontal and left prefrontal regions. Interestingly, no pre-treatment differences in regional perfusion between subsequent treatment responders vs non-responders were found. Although there are important differences in the symptomatology of the anxiety disorders, these conditions do share certain aspects of their phenomenology, including heightened anxiety and avoidance behaviour. Furthermore, previous functional brain imaging work has demonstrated overlapping neurocircuitry across different anxiety disorders with activation of paralimbic circuitry and right inferior frontal cortex in a combined group comprising subjects with OCD, PTSD, and specific phobia [ 1 ]. Results in the present study now also point to an overlap in the functional neuroanatomy, primarily implicating paralimbic neurocircuitry, in treatment response to the same SSRI, citalopram, across anxiety disorders. In citalopram responders, effects across disorders were most pronounced in the mid, inferior and prefrontal cortex. In other regions, such as the striatum, data on treatment response and symptom provocation seems to indicate less overlap across anxiety disorders, which may suggest only partial and regionally specific overlap between disorders [ 1 , 2 ]. Specific limbic regions are well-known to play a role in broadly mediating anxiety. Early observations of epileptogenic cingulate lesions support its role in regulating affect [ 27 ]. Furthermore, recent work has suggested a role for the anterior cingulate in integrating cognitive and motivational processes. These include evaluating environmental cues and monitoring performance [ 28 ] On the other hand, a central role for the hippocampus in contextual aspects of fear conditioning has been demonstrated [ 29 , 30 ]. The findings here complement previous studies of OCD, PTSD, and SAD that have demonstrated a specific role for the cingulate and hippocampus in these conditions. Studies in OCD have shown increased anterior cingulate activity at baseline, or deactivation during pharmacotherapy with serotonergic agents [ 31 ]. In PTSD, anterior cingulate activity is also increased in some, although not all, studies of PTSD [ 32 , 33 ] Further, the anterior cingulate is deactivated during citalopram treatment of SAD patients [ 17 ]. Dysfunction of the hippocampus, as indicated by smaller hippocampal volume and declarative memory deficits, may play an important role in PTSD [ 34 ]. The medial prefrontal cortex comprises several related areas including anterior cingulate cortex. Lesions of this area are associated with suboptimal responses to stress, and the area has important inhibitory inputs to the amygdala which mediate extinction of fear conditioning [ 29 ]. The middle and inferior frontal cortex, on the other hand, is involved in encoding and retrieval of verbal memories. Our finding that the right inferior frontal cortex was more deactivated in responders is perhaps consistent with previous findings showing increased activity pre-treatment in this region across different anxiety disorders [ 2 ] and in some, but not all, studies of PTSD [ 35 ]. Serotonergic circuits innervate the medial prefrontal cortex and other limbic structures, and chronic administration of a serotonin reuptake inhibitor may lead to an increase in their neurotransmission. It is possible that the medial prefrontal cortex deactivation during serotonergic pharmacotherapy indicates that a compensatory increase of activity in this region is no longer needed after symptom improvement. Along these lines, a number of functional and electrophysiological imaging studies of depression have found that anterior cingulate hyperactivity predicts a positive response to pharmacotherapy, a finding that has also been interpreted as indicating the baseline presence of an adaptive compensatory response [ 36 ]. In addition changes in cognitive processing of frontal cortex may be secondary to symptom reduction caused by primary drug-induced changes within the limbic system. We have previously demonstrated similarly higher pre-treatment prefrontal perfusion in subsequent responders relative to non-responders using inositol in OCD [ 37 ]. Interestingly, inositol responsive disorders overlap with those responsive to SSRI's which may suggest that it is serotonergic components of these disorders that account for at least some of the overlap in perfusion patterns demonstrated here. In contrast, however, increased activity in anterior cingulate or orbitofrontal region in OCD has also been shown to predict a poorer response to pharmacotherapy [ 9 ]. Perhaps increased activity in particular limbic circuits plays a different functional role in different psychiatric disorders. Only limited functional imaging studies of pharmacotherapy effects have involved provocation paradigms [ 38 ] and such differences in design may account for certain inconsistencies across studies. Alternatively, it is feasible that different effects in different disorders may also help explain inconsistencies. In the current dataset, however, we were unable to demonstrate any associations between baseline activity and pharmacotherapy response for the combined group. This study is limited by the slightly different inclusion criteria (inclusion of secondary depression in PTSD group) and pharmacotherapy duration for different disorders. While the absence of untreated controls may to some extent limit the conclusions we can draw, comparing non-responders to responders we believe serves as a reasonable evaluation of changes that result from treatment response. The lower spatial resolution of SPECT may be considered a limitation nevertheless this study usefully emphasizes the importance of limbic regions (amygdala, hippocampus) in mediating anxiety. Furthermore, deactivation within these regions as well as richly connected frontal regions following SSRI treatment, particularly in responders, is clearly demonstrated. Further research combining pharmacological interventions and functional methodologies, and using tracers tailored to specific neurotransmitter receptors, will undoubtedly lead to increased understanding of the pathogenesis of the anxiety disorders and the mechanisms of response to treatment in the future. Competing interests The authors declare that they have no competing interests. Authors' contributions The authors contributed to the work in the following ways: drafting of manuscript (PDC, JW, DJS), data analysis (JW, PDC), psychiatric evaluations (DJHN, GVDL, SS, DJS), SPECT imaging (JW, BBVH). All authors have read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:

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374245

Evolutionary History of a Gene Controlling Brain Size

Biologists have long known that the African great apes (including the chimpanzee, bonobo, and gorilla) are our closest relatives, evolutionarily speaking. The recent release of the chimp draft genome sequence confirms this relationship at the nucleotide level, showing that human and chimp DNA is roughly 99% identical. Given the genetic similarity between human and nonhuman primates, the next big challenge is to identify those changes in the human genotype (the genetic complement of an organism) that generated the complex phenotype (the physical manifestation of gene expression) that distinguishes humans from the great apes. For example, modern humans have larger brains and a larger cerebral cortex than both nonhuman primates and their forebears, the early hominids. Elucidating the molecular mechanisms that account for this expansion will provide insight into brain evolution. MRIs of a normal individual (bottom left) and a patient with microcephaly caused by an ASPM mutation (bottom right). Primate skulls provided courtesy of the Museum of Comparative Zoology, Harvard University One way to figure out which genes are involved in a physiological process is to analyze mutations in the genotype that generate an abnormal phenotype. Such efforts are easier in the relatively rare instance that one gene affects a single trait. Mutations in the ASPM gene cause microencephaly, a rare incurable disorder characterized by an abnormally small cerebral cortex. Since the microencephalic brain is about the same size as the early hominid brain, researchers hypothesized that ASPM —whose normal function is unclear—may have been a target of natural selection in the expansion of the primate cerebral cortex. Last year, researchers showed that selective pressure on the ASPM gene correlated with increased human brain size over the past few million years, when humans and chimps diverged from their common ancestor. Now, Vladimir Larionov and colleagues report that the selective pressure began even earlier—as far back as 7–8 million years ago, when gorillas, chimps, and humans shared a common ancestor. The researchers used a newly developed technology (called TAR-cloning) to extract specialized cloning agents in yeast (called yeast artificial chromosomes, or YACs) containing the entire ASPM gene, including promoter and intronic (noncoding) sequences, from chimpanzees, gorillas, orangutans, and rhesus macaques. They sequenced these YACs to determine the complete genomic sequence of the ASPM gene from each species. Next, they characterized sequence changes among these species, based on whether the resulting substitutions in amino acids produced changes in the ASPM protein, to determine how fast the protein was evolving. Larionov and colleagues found that different parts of the protein evolved at different rates, with the rapidly evolving sequences under positive selection (beneficial mutations were selected for, or retained) and the slowly evolving sequences under “purifying” selection (significant disruptions were jettisoned). Positive selection on genes is one important way to drive evolutionary change. By reconstructing the evolutionary history of the ASPM gene, Larionov and colleagues show that the increase in human brain size—which began some 2–2.5 million years ago—happened millions of years after the gene underwent accelerated selective pressure. The ASPM gene, they conclude, likely plays a significant role in brain evolution. The next big challenge will be identifying the forces that preferentially acted on the human genotype to kick-start the process of brain expansion, forces that promise to shed light on what makes us human. New genomic technologies like TAR-cloning will likely accelerate this process.

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535903

Identitag, a relational database for SAGE tag identification and interspecies comparison of SAGE libraries

Background Serial Analysis of Gene Expression (SAGE) is a method of large-scale gene expression analysis that has the potential to generate the full list of mRNAs present within a cell population at a given time and their frequency. An essential step in SAGE library analysis is the unambiguous assignment of each 14 bp tag to the transcript from which it was derived. This process, called tag-to-gene mapping, represents a step that has to be improved in the analysis of SAGE libraries. Indeed, the existing web sites providing correspondence between tags and transcripts do not concern all species for which numerous EST and cDNA have already been sequenced. Results This is the reason why we designed and implemented a freely available tool called Identitag for tag identification that can be used in any species for which transcript sequences are available. Identitag is based on a relational database structure in order to allow rapid and easy storage and updating of data and, most importantly, in order to be able to precisely define identification parameters. This structure can be seen like three interconnected modules : the first one stores virtual tags extracted from a given list of transcript sequences, the second stores experimental tags observed in SAGE experiments, and the third allows the annotation of the transcript sequences used for virtual tag extraction. It therefore connects an observed tag to a virtual tag and to the sequence it comes from, and then to its functional annotation when available. Databases made from different species can be connected according to orthology relationship thus allowing the comparison of SAGE libraries between species. We successfully used Identitag to identify tags from our chicken SAGE libraries and for chicken to human SAGE tags interspecies comparison. Identitag sources are freely available on web site. Conclusions Identitag is a flexible and powerful tool for tag identification in any single species and for interspecies comparison of SAGE libraries. It opens the way to comparative transcriptomic analysis, an emerging branch of biology.

Background In order to characterize the molecular basis underlying self-renewal versus differentiation decision-making process we investigated the transcriptomic changes of various states related to this process, in two model systems : one derived from chicken and the other from human cells. We decided to use Serial Analysis of Gene Expression (SAGE) [ 1 ] to attain this aim, for a number of reasons including the absence of available pan-genomic DNA arrays in the chicken and the ability to compare SAGE libraries across different experiments. We therefore had to resolve two problems : tag-to-gene mapping in chicken and comparing SAGE libraries from two different species (here chicken and man). Serial Analysis of Gene Expression is a comprehensive method for analyzing transcriptomes (i.e. the complete set of mRNAs expressed in one given biological situation at one given time point) without any a priori regarding the genes to be studied. It can be used with mRNAs derived from cells of any eukaryotic species. SAGE is based on the isolation of a unique sequence tag from each individual transcript and on serial concatenation of several tags into long DNA molecules. Sequencing of concatemer clones reveals individual tags and allows quantification and identification of transcripts. Tag counts are digitally archived and statistically significant comparisons of expression levels can be made between tag counts derived from different populations of cells. An essential step in SAGE library analysis is the unambiguous assignment of each 14 bp tag to the transcript from which it was derived. This process, called tag-to-gene mapping, represents a step that has yet to be completed in the analysis of SAGE libraries. The automated version of this process mostly involves extracting "virtual tags" from sequence databanks : these virtual tags are predictions of the 14 bp sequences that might be produced by a SAGE experiment. The quality of the databanks from which the virtual tags are extracted represents a limiting step in this process. Ideally, the databanks should represent the complete collection of each and every transcript, fully sequenced and annotated. This clearly has yet to be achieved for most species, and therefore one must use the available information that comes mainly from large EST (Expressed Sequence Tags) projects. Different resources have already been described for tag identification in human and mouse, including the SAGE Map [ 2 ], the SAGE Genie [ 3 ], the Melbourne Brain Genome Project [ 4 ], the Mouse SAGE site [ 5 ] and the Human Transcriptome Map [ 6 ] web sites, but fewer resources are available for tag-to-gene mapping in other species. Nevertheless, a very large number of species have been subjected to a SAGE analysis (for an up to date bibliography, see the SAGEnet web site [ 7 ]) and actually the SAGE Map web site hosts a SAGE tag to UniGene mapping for 11 species ( Arabidopsis thaliana , Bos taurus , Homo sapiens , Medicago truncatula , Meleagris gallopavo , Mus musculus , Pinus taeda , Rattus norvegicus , Sus scrofa , Triticum aestivum and Vitis vinifera ). However, this site doesn't include tag to UniGene mapping for several other species for which numerous EST and cDNA have already been sequenced. This is the reason why we designed and implemented a freely available tool for tag identification that can be used in any species for which transcript sequences are available. It can include both complete cDNAs and EST cluster sequences and allow to interrogate the database according to the source of data, to assess the quality of virtual tags derived from different transcript sequences. In this paper we describe the use of this tool for the chicken ( Gallus gallus ) where a large EST sequencing effort was completed [ 8 ]. In order to allow rapid and easy storage and updating of data and, most importantly, in order to be able to query the results using sophisticated combinations of criteria, we have designed a relational database structure. We implemented this relational database called Identitag using the freely available MySQL database management system (DBMS) [ 9 ]. One important function of Identitag is the possibility to compare the tags obtained in a given species to their counterpart present in another species. This allows a direct comparison of SAGE transcription profiles obtained from different species. To the best of our knowledge, this is the first tool that allows SAGE libraries interspecies comparison : this open the way to comparative transcriptomic analysis. Here we describe the use of Identitag for chicken SAGE tag identification as well as for chicken to human interspecies comparison. Implementation Database for tag identification : Identitag Database organization The Identitag relational schema is presented in Figure 1 , and a complete data dictionary of the database is available on the Identitag web site . We implemented this database using the freely available and cross-platform Mysql DBMS. A perl script which generates the SQL script creating Identitag tables according to the name of the species considered, is also available on Identitag web site. Completing the database Various sources of data presented in Figure 1 are needed to complete Identitag. Transcript sequences in Fasta format and a file resulting from their comparison with protein from databanks using the BLASTX algorithm [ 10 ] are needed for completing the first and third Identitag modules. For chicken Identitag we used various transcript sequences : 3425 chicken mRNA from Genbank (extracted using query software [ 11 ]) and 88504 SIGENAE chicken EST cluster consensus sequences (INRA, M. Douaire, P. Deshais and C. Klopp, personal communication). As consensus sequence orientation is not always known, we used both sequences and their reverse complementary. Then we could assess the correct orientation of the sequences using various sources of information stored in Identitag database (see results section). For completing the second module, a flat file with tag sequences and their relative frequency is required, for each library. So far in chicken Identitag we have stored four different libraries generated from normal chicken immature erythroid progenitors called T2ECs [ 12 ]. The first two libraries were generated from self-renewing T2EC cells and from T2EC cells induced to differentiate for 24 hours respectively [ 13 ]. The last two libraries have been generated from T2EC cells treated with two inhibitors of the MEK-1 signaling pathway which is important for maintaining self-renewal (S. Dazy et al, in preparation). For these four libraries, we used SAGE 2000 software [ 14 ] in order to extract tags from concatemer sequences : we generated 4 files for the 4 SAGE libraries considered, with 17853, 19736, 16631 and 11669 tags respectively. 6440 different tags appear more than once in these 4 libraries. Several programs were then used for loading these data into Identitag database. They are written in Perl and Shell and are available on Identitag web site. A Shell script that allows to launch all these programs is also available on this web site : it asks for all information required by these different programs, then launches all programs with adapted arguments and loads the files generated by these programs in the corresponding Identitag tables. The creation and completion of Identitag tables with these programs was successfully tested on SUN, Linux and Mac OS X operating systems. Querying the database The completed database can be interrogated using SQL (Structured Query Language) and allows a number of tag identification procedures to be launched (see for example the procedure described in results section). Redundancy reduction When several transcripts identify a same tag, these transcripts are compared with each other using Blastclust [ 15 ] to determine whether they correspond to redundant sequences of the same transcript or to different transcripts. We consider that two sequences are redundant if they share more than 95% similarity over more than 100 bp. Database for interspecies comparison of SAGE libraries We connected two Identitag databases from two different species by using orthology relationships between transcripts that identify SAGE tags (Figure 2A ). Design of the orthology relationship We designed a method for identifying transcript sequence pairs that are putatively orthologous between the two species considered. This method (described in figure 3A and in text below) is an approximation of the search for reciprocal best BLAST hits for two datasets with redundancy and that do not represent the entire transcriptome of the two species considered. The first step of this method (Figure 3A , step 1) consists of two reciprocal TBLASTX. First, we compare each species A transcript with a databank containing species B transcripts, using the TBLASTX algorithm [ 10 ] (Figure 3A , TBLASTX(1)). We store all the best hits for which the corresponding E-value is less than 0.001 : all these sequences form a subset of species B transcripts. Second, we compare each sequence from this subset with a databank containing species A transcripts, using the TBLASTX algorithm (Figure 3A , TBLASTX(2)). We further consider corresponding best hits harboring an E-value lower than 0.001, they form a subset of species A transcripts that are considered for further analysis. The second step (Figure 3A , step 2) consists in staring only pairs of transcript sequences sufficiently similar between TBLASTX(1) and TBLASTX(2). For example, transcript sequence A1 is similar to transcript sequence B1 (result provided by TBLASTX(1)), and transcript sequence B1 is similar to transcript sequence AX (result provided by TBLASTX(2)). If the two transcript datasets were complete and non-redundant, X should be equal to 1 : when that is the case, A1 is paired with B1. If not, we search if AX transcript sequence is redundant with A1, with the same criteria as described above to asses if two sequences are redundant. If AX is similar to A1, we further consider the pair A1-B1. If not, the A1-B1 pair is discarded from further analysis. We use the same method for each transcript pair obtained in first step. If the set of transcripts from species A and B are not complete, the best reciprocal hits might correspond to paralogs (see figure 3B ). To limit this risk of erroneous orthology assignment we consider the pairs stored in previous step: we compare the species A transcript sequence from each pair with species B proteins from SwissProt and TrEMBL databanks, using the BLASTX algorithm (Figure 3A , step 3). We compare the best resulting hit (a protein from species B) with the species B transcript putatively orthologous to species A transcript : if these two sequences are similar (i.e. they share more than 95% similarity over more than 100 bp), we consider the pair of the species A transcript and the species B transcript as a pair of orthologous sequences. If these two sequences are not similar, it means that protein databanks contain a species B sequence that is more similar to species A transcript than the species B sequence found using best reciprocal hit. Thus the pair of the species A transcript and the species B transcript might correspond to a pair of paralogous sequences. These three steps allow us to obtain pairs of transcripts which are probably orthologous, by trying to eliminate erroneous assignments of orthology for paralogous sequences instead of orthologous ones. However a limiting aspect of this method is the identification of only 1-1 orthology relationships : if one transcript sequence from species A has several orthologous sequences in species B this method will only identify one of the pairs of orthologous sequences. The scripts that implement this method are available on Identitag web site. We applied this method to chicken and human. For this we used chicken transcript sequences from Genbank, chicken SIGENAE EST cluster consensus sequences and human transcript sequences from Refseq release 2 (19902 mRNA sequences, with the accession prefix "NM_"). Connecting two Identitag databases by using this relationship The database for interspecies comparisons of SAGE libraries is composed of two Identitag databases for tag identification in two different species, and connected through the SpeciesA_SpeciesB_Transcript table (see for example the organization of the database for chicken-human interspecies comparison in Figure 2B ). A shell script available on Identitag web site asks for all information required. Then it searches for putative orthologous sequences using the method previously described, creates the table SpeciesA_SpeciesB_Transcript, and then loads corresponding data in this table. Results The use of Identitag for identification purpose Database organization Identitag can be depicted as three interconnected modules, as presented in Figure 1 . The first module stores data concerning transcript sequences and virtual tags extracted from these sequences. The Species_Transcript table contains transcript identification (identification number and the databank from which they originate), together with information that can then be used for assessing the quality of the "virtual" SAGE. The quality of virtual tags depends on the source of the transcript sequence from which it was derived (e.g. the sequence quality of mRNA is higher than that of EST clusters), this is why this information is stored in the Species_Transcript table. Other information can also be used for assessing the quality of the "virtual" SAGE. This information allows one to assess if a transcript sequence is complete and if its orientation correct. This includes the presence or absence of different polyA signals (AATAAA and its most common variant ATTAAA) as well as their localization along the sequence and the length of the possible poly A tail. This length corresponds to the longest poly A stretch among the 50 last base pairs of the transcript sequence : this calculation allows us to take into account the polyA tail even if there are some bases belonging to a cloning vector or sequencing errors at the end of the corresponding transcript sequence. Some of the EST we used were labeled as constructed and sequenced from the 3' region. When available this information was stored in the database. The Species_Transcript table is linked with an NN relationship to the Species_Virtual_Tag table. This table contains virtual tags extracted from the transcript sequences and information about how the tags were extracted. This includes the anchoring enzyme considered (e.g. NlaIII) and the position of its recognition site in the transcript sequence : the Species_Virtual_Tag table stores both the 10 bp sequence immediately downstream of the most 3' anchoring enzyme recognition site and 10 bp sequence downstream of the next-to-last anchoring enzyme recognition site. Indeed, the cutting enzyme may on rare occasions (0,1 %, [ 16 ]) cut not its most 3' but its recognition site that is just 5' from the last one (called next-to-last). Both conventional 10 bp tag sequences as well as virtual long-SAGE 17 bp tag sequences [ 17 ] are stored in the Species_Virtual_Tag table. The second Identitag module allows storage and retrieval of the experimental part of the SAGE experiments. It consists of a table containing information about the construction of SAGE libraries (Species_SAGE_Library table), connected with a table that stores tag sequences from that SAGE library and their corresponding count (Species_Observed_Tag table). The connection between modules 1 and 2 leads to a direct comparison between observed and virtual tags : it is the key to the tag identification procedure. Only perfect matches are allowed at that stage. The third Identitag module allows annotation of transcript sequences from which virtual tags are extracted, via their similarity to known proteins. For this purpose we compare each transcript sequence with the protein sequences from Swissprot and TrEMBL databanks, using the BLASTX algorithm [ 10 ]. For this sequence comparison we only consider the same transcript sequence orientation as the orientation that we used for tag extraction. When available, the best BLASTX hits (harboring an E-value < 0.001) are stored in Identitag (in the Protein table), together with different BLAST statistics (stored in Species_Transcript_Protein table). This information can then be used for assessing the quality of the annotation. Identitag web site provides all scripts necessary to build a such Identitag database and to load all data into this database, for any species from which transcript sequences are available. To do this one need data represented in figure 1 . After running the main script one just have to answer all questions asked by the script and then all tables of the database are created and completed, for the species considered. Various identification situations Identitag can be interrogated in various ways, using different identification criteria concerning the quality of the virtual SAGE and the annotation provided. For example, the interrogator can use the following step-by-step procedure (Figure 4 ), for each observed tag from the SAGE experiment considered (an example of each identification situation is provided in table 1 ) : 1. If the observed tag matched to no virtual tag, then it is declared unidentified and the identification process is aborted : approximately 25% of the tags belonging to the four chicken SAGE libraries we have studied are unidentified. If this is not the case it means that the observed tag corresponds to a virtual tag extracted from one or more transcript sequence(s) ; the identification process proceeds to the next step. 2. If these transcript sequences are not annotated (i.e. they do not have any BLASTX hit with an E-value < 0.001), the observed tag is identified as matching non-annotated EST cluster(s) : 37% of the tags belonging to the four chicken SAGE libraries we studied correspond to non-annotated EST cluster(s). Then we distinguish tags identified as matching one EST cluster (57% of these tags) or more than one EST clusters. For tags corresponding to more than one EST clusters, we compare these sequences to determine whether they are redundant or not. Indeed, there could be redundancy in transcript databanks based on EST clusters due to the threshold for sequence similarity being to high to assign different EST to the same cluster. Therefore, there could be different EST clusters corresponding to the same transcript. This is the reason why we use the procedure described in implementation section to identify sequence redundancy. Among the tag identifications corresponding to more than one EST clusters, 19% correspond to redundant sequences. Finally, 65% of identifications corresponding to non-annotated EST cluster(s) are unambiguous (one corresponding EST cluster or more than one but redundant corresponding EST clusters). If the observed tag does not correspond to previous identification cases, it means that the observed tag corresponds to a virtual tag extracted from one or more annotated transcript sequence(s) and the identification process proceeds to the next step. 3. If there is only one annotated transcript sequence from which this virtual tag has been extracted, then the protein name (i.e. the description field corresponding to its Swissprot or TrEMBL accession number) is used to identify this tag and the identification process is stopped : 26% of the tags belonging to the four chicken libraries we studied correspond to this identification case. We call these tags "annotated tags". When this is not the case it means that the observed tag corresponds to a virtual tag extracted from different annotated transcript sequences ; the identification process proceeds to the next step. 4. If the different transcript sequences have the same annotation (i.e. the same best BLASTX hit), then the protein name is used as the identification and the identification process halts. This case is mainly due to transcript databank redundancy. Thus by using annotation to identify SAGE tags, we reduce the number of multiple matches. As in previous identification situation we designate the corresponding tags as "annotated tags" because their annotation is not ambiguous : 4% of the tags belonging to the four chicken libraries we studied correspond to this identification case. When this is not the case it means that the observed tag corresponds to a virtual tag extracted from several transcript sequences differently annotated ; the identification process proceeds to the next step. 5. The last case corresponds to an observed tag matching to more than one transcript sequences with more than one different annotations. This corresponds to 8% of the tags belonging to the four chicken SAGE libraries we studied. By using annotation to identify SAGE tags, we reduce the number of multiple matches that may occur because of redundancy in transcript databanks. Nevertheless, some of these multiple matches remain. This may occur because there is redundancy in protein databank, thus the redundant transcripts can be differently annotated : this leads to a multiple match. It also appear when redundant transcripts match to the same protein but in different species. Indeed the annotation is provided by a BLASTX against Swissprot and TrEMBL databanks (with all species considered) : thus we could annotate transcripts for which we don't already know the corresponding protein in the species considered, but which is identified in another species. However, this method presents the drawback of causing multiple matches when redundant transcripts match to the same protein in different species. This case is considered as a multiple match because the best BLASTX hits of transcripts identifying the same tag are different. To reduce these two cases of ambiguity, we align the different transcript sequences identifying the same tag (see implementation section) : according to the sequence similarity between them we could avoid these cases of multiple matches. Among the 521 identifications corresponding to more than one transcript sequences with more than one different annotations in our four chicken libraries, 28% could be discarded by this method. The cases of multiple matches remaining occur presumably mainly due to different transcripts that really have the same tag. We provide an example illustrating the repartition of these different situations regarding tag identification in the chicken libraries we studied (figure 5 ). When we don't consider the next-to-last tag during the identification procedure, we reduce the number of multiple matches, but increase the number unidentified tags. This process could be pursued further by discriminating between multiple matches, using criteria concerning the quality of the virtual SAGE, e.g. the quality of the transcript sequences (cDNA or EST), the tag position in the transcript sequence (last or next-to-last) and/or the availability of the transcript sequence end. One can also consider a process for tag identification based only on high quality tag identifications. For example, one could obtain an identification based solely on cDNA sequences, or only using tags appearing at the last position. One can also use any logical combination of the above criteria. The use of Identitag for interspecies comparison of SAGE libraries In order to directly compare SAGE libraries performed in chicken (4 libraries performed in our lab until now) with those performed in human (273 libraries available as of 08/03/04 on SAGE Genie web site : [ 3 ]), one first needs to associate each chicken tag with its human counterpart. For this we decided to connect the chicken Identitag to its human counterpart. This connection relies upon the concept of orthology (Figure 2A ) [ 18 ]. Two genes in two different species are said to be orthologous if they diverged after a speciation event. It is important to note that conservation of function is not part of the definition of orthology, but rather its consequence. It can also be envisaged that after the speciation event, the function of the resulting genes diverged in the two species. A tool for interspecies comparison of expression data would be very helpful for investigating such questions, and notably the level of conservation in expression patterns of orthologous genes, a task that has only begun using DNA arrays ([ 19 , 20 ]). The structure of Identitag was originally designed with this purpose in mind and therefore chicken and human Identitag could easily be connected together (Figure 2B ). For example, this procedure will allow the chicken GATA-1 tag (GGGGACCCCG) to be associated with its human counterpart (GCCTCCAGAG) via the chicken transcript GATA-1 <-> human transcript GATA-1 orthology. We designed a method for identifying transcript sequence pairs that are putatively orthologous between the two species considered. This method (described in figure 3A ) is an approximation of the search for reciprocal best BLAST hits for two datasets with redundancy and that do not represent the entire transcriptome of the two species considered. We first perform two reciprocal TBLASTX between species A and species B transcript sequences (TBLASTX(1) and TBLASTX(2)). We then conserve only the pairs of transcript sequences originating consistent TBLASTX(1) and TBLASTX(2) results. We finally consider previously obtained pairs in order to limit erroneous assignment of orthologous pairs for paralogous ones. For a more precise description of the design of this design of orthology relationship see implementation section. Among the 3500 transcripts corresponding to unambiguously identified tags from our 4 chicken libraries (either annotated or unambiguously identified by EST cluster(s)), 1190 have a human orthologue as previously defined. Therefore the corresponding tags can now be translated into their human counterpart and thus SAGE libraries from two different species can be compared. Discussion We have designed and implemented a tool allowing the identification of SAGE tags, based on a relational database. This structure allows to use Identitag in two different ways. First one can precisely choose identification criteria and obtain only the tag identifications provided by using these criteria. One can specify different criteria and thus determine the quality of the identification : e.g. identification generated from EST clusters or mRNA sequences, from last or next-to-last tag, presence of the 3' end of the transcript sequence that could be inferred through the presence of a 3' label or a poly A tail and/or signal. One can also specify different criteria allowing the quality of the annotation to be controlled, e.g. quality of the similarity between transcript and protein sequences through BLAST parameters, quality of the protein sequence used to annotate the transcript via the databank from which the protein originated (Swissprot or TrEMBL) and its species (an annotation with a protein from the same species than that we consider is more accurate than with a protein from another species). All these criteria can be combined allowing the investigator to perform sophisticated interrogations of the database. To the best of our knowledge it is the first tool that allows the user to precisely adjust the identification parameters depending upon its needs. The second way to use Identitag is to ask for all identifications available, for example for a tag of interest, and how these identifications have been generated : it is then possible to consider all these identifications and to further choose among the different identifications if necessary. These two different ways of using Identitag can be used for any species for which transcript sequences are available. Identitag is an open source tool, the programs necessary to build and run the database are available on the Identitag web site . Identitag can therefore be used to build a tag-to-gene mapping procedure in any species, using a flat file containing transcript sequences and a BLASTX file results as input of these programs. Identitag was successfully used for tag-to-gene mapping in chicken. It played a key role for allowing biological interpretation of the SAGE libraries obtained from normal chicken erythroid progenitor cells and allowed us to better understand the changes underlying the self-renewal versus differentiation-making process in these cells [ 13 ]. Among the identifications provided by Identitag, a few were investigated further and the vast majority of these identifications were subsequently confirmed by real-time PCR [ 13 ]. Identitag has also been successfully used for tag-to-gene mapping in Bombyx mori (J. Briolay et al, in preparation).Identitag is currently in use to identify human tags from SAGE libraries generated in order to investigate the molecular basis underlying the self-renewal versus differentiation decision-making process in human cells. The next step will be to compare gene expression patterns between our chicken and human model systems, in order to study the possible conservation of the molecular basis of self-renewal during evolution. Comparisons of gene expression between two organisms have recently been initiated with DNA arrays ([ 19 , 20 ]). But it is one on the main limitations of DNA arrays that comparisons between experiments done in different laboratories (not to mention on different species) are at best approximate. It is one of the main advantage of the SAGE technique for which results can be compared without the need for sophisticated and approximative normalization procedures. The SAGE technique is therefore ideally suited for quantitative comparisons to be performed between different libraries made from different cell types in different laboratories. We therefore expect that Identitag will become a standard tool for comparative transcriptomic analysis using SAGE data, an emerging branch of biology consisting in the comparison of large scale transcriptomes obtained from various cell types belonging to different species. Conclusions Identitag is a flexible and powerful tool for tag identification in any single species and for interspecies comparison of SAGE libraries. It opens the way to comparative transcriptomic analysis, an emerging branch of biology. Availability and requirements • Project name: Identitag • Project home page: • Operating system(s): SUN, Linux, Mac OS X • Programming languages: Perl, Bourne Shell, MySQL • License: GNU GPL Authors' contributions CK participated to the design of Identitag, implemented Identitag, and participated to the biological validation of Identitag with SAGE libraries. FD constructed the first two SAGE libraries with which Identitag was tested and participated to the biological validation of Identitag with these data. LD and DM brought their expertise in the orthology area, in order to design the orthology relationship. OG supervised this work. All authors participated in the writing of the manuscript, read and approved the final manuscript.

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423152

Initiation of DNA Replication: The Genomic Context

Every time a cell divides, it must first duplicate its entire genome. Barring the occasional error, the daughter cells inherit identical copies of the parent cell's genome. With a typical human cell containing almost 9 feet of DNA made of 3 billion base pairs crammed into a nucleus about 5 microns (.0002 inches) in diameter, that's no small feat. To accomplish the job, cells engage specialized teams of protein machines, each performing different tasks during the various stages of DNA replication: initiation, duplication, quality control, and repair. Much of what we know about the molecular mechanisms of DNA replication comes from studies of bacteria. In the bacterial genome, which consists of several million base pairs, replication begins at a single site, spanning about 100 base pairs. The regulation and mechanisms of replication, even in the compact bacterial genome, are so complex that 51 years after Watson and Crick reported that the structure of DNA “immediately suggests” a mechanism for its replication, biologists are still working out the details and regulation of that mechanism. Linearized EBV episome imaged by fluorescent microscopy and aligned with the corresponding genomic map Before duplication, aptly named initiator proteins bind to DNA at replication initiation sites and break the bonds holding the complementary base pairs together, separating the double helix locally into single strands and creating two Y-shaped junctions at either end called replication forks. At each replication fork, a complex of proteins continues the business of unzipping the DNA and using the exposed single strands as templates to generate complementary daughter strands. What controls when and how individual initiation sites are activated in mammalian cells has remained obscure. Is initiation restricted to specific sites? Do specific DNA sequences control initiation events locally? Examining individual molecules of fluorescently labeled replicating DNA, Paolo Norio and Carl Schildkraut report that initiation events are not controlled by individual initiation sites but occur throughout the genome. And the activation of these sites appears to depend on what's happening at the genomic level. Using a novel technique called single molecule analysis of replicated DNA (SMARD), Norio and Schildkraut use the Epstein Barr virus (EBV) in human B cells as a model system for studying DNA replication. During the latent stage of infection, the EBV genome exists as an episome—a circular piece of extrachromosomal DNA. It replicates only once per cell cycle, during the DNA synthesis stage, and uses its host's replication machinery to do so. Using nucleotide analogs that can be detected by immunofluorescence (since the analogs attract antibodies that are fluorescently labeled), the researchers can determine the position, direction, and density of the replication forks, and then determine how replication starts, progresses, and terminates. Norio and Schildkraut studied replication using two strains of the EBV virus grown in human B cells, their natural target. Previous studies, which had largely focused on the activity of individual initiation sites, had suggested that different EBV strains vary in how initiation sites are activated and that specific initiation sites or regions likely regulate replication. Looking at larger genomic regions, Norio and Schildkraut found something different: not only do initiation sites occur throughout the genomes, but their activity “differs dramatically” in the two EBV strains and even within a strain. Differences were seen in the order of initiation site activation, in the direction of replication fork movement, and in the speed of duplication in different parts of the genome. While the two largely similar viral genomes do show some genetic differences, the authors dismiss the idea that these local differences could explain the observed variations in replication control. It's more likely, they conclude, that epigenetic modifications (such as changes in chromatin structure) produce the differences in the order and frequency of activation of initiation sites across genomic regions. It seems that initiation events are not restricted to specific genomic areas, and experimentally induced loss of individual initiation sites does not significantly affect EBV genome replication (because other sites take up the slack). This redundancy provides flexibility in determining which sites are activated. Since the EBV genome uses human replication machinery to duplicate its genome, these findings likely apply to DNA replication in mammalian cells as well. The very survival of the cell—and the health of the organism it inhabits—depends upon the faithful replication of the genome. Using processes that operate at the genomic level may afford cells the means to manage an unwieldy genome, and perhaps, more importantly, guarantee their genes safe passage to the next generation.

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544888

Hierarchical structure and modules in the Escherichia coli transcriptional regulatory network revealed by a new top-down approach

Background Cellular functions are coordinately carried out by groups of genes forming functional modules. Identifying such modules in the transcriptional regulatory network (TRN) of organisms is important for understanding the structure and function of these fundamental cellular networks and essential for the emerging modular biology. So far, the global connectivity structure of TRN has not been well studied and consequently not applied for the identification of functional modules. Moreover, network motifs such as feed forward loop are recently proposed to be basic building blocks of TRN. However, their relationship to functional modules is not clear. Results In this work we proposed a top-down approach to identify modules in the TRN of E. coli . By studying the global connectivity structure of the regulatory network, we first revealed a five-layer hierarchical structure in which all the regulatory relationships are downward. Based on this regulatory hierarchy, we developed a new method to decompose the regulatory network into functional modules and to identify global regulators governing multiple modules. As a result, 10 global regulators and 39 modules were identified and shown to have well defined functions. We then investigated the distribution and composition of the two basic network motifs (feed forward loop and bi-fan motif) in the hierarchical structure of TRN. We found that most of these network motifs include global regulators, indicating that these motifs are not basic building blocks of modules since modules should not contain global regulators. Conclusion The transcriptional regulatory network of E. coli possesses a multi-layer hierarchical modular structure without feedback regulation at transcription level. This hierarchical structure builds the basis for a new and simple decomposition method which is suitable for the identification of functional modules and global regulators in the transcriptional regulatory network of E. coli . Analysis of the distribution of feed forward loops and bi-fan motifs in the hierarchical structure suggests that these network motifs are not elementary building blocks of functional modules in the transcriptional regulatory network of E. coli .

Background Genome sequencing and high-throughput technologies of functional genomics generate a huge amount of information about cellular components and their functions in an unprecedented pace. These advances make it possible to reconstruct large scale biological networks (metabolism, gene regulation, signal transduction, protein-protein interaction etc.) at a whole cell level [ 1 - 4 ]. One of the key issues in the contemporary genomic biology is to understand the structure and function of these cellular networks at different molecular levels. Among them, the transcriptional regulatory network (TRN) plays a central role in cellular function because it regulates gene expression and metabolism and is often the final step of signal transduction [ 5 , 6 ]. Genome scale TRNs have been reconstructed for well studied organisms such as Escherichia coli and Saccharomyces cerevisiae [ 4 , 5 , 7 , 8 ]. Recent studies of TRNs have been concentrated on the topological structure and its correlation with gene expression data from microarray experiments, the evolutionary relationship between regulators, the network motifs and the global regulators in the network etc [ 7 - 15 ]. Network motifs are regarded as the basic building blocks of complex networks [ 16 , 17 ]. Feed forward loop (FF loop) and Bi-fan motif were found to be the two most important network motifs in TRN [ 7 ]. In a recent study, Dobrin et al. [ 9 ] reported that the motifs in E. coli TRN aggregated into homologous motif clusters that largely overlapped with known biological functions and further formed a giant motif supercluster which comprised about half of the nodes in the giant component of the whole network. This study provided interesting information for understanding the organization principle of regulatory networks. A different approach for studying network organization is the so called "top-down view"[ 18 ]. It starts from the whole network structure and identifies subsystems or modules by network decomposition. It is generally recognized that most cellular functions are coordinately carried out by groups of genes forming functional modules [ 19 - 25 ]. The identification of modules is thus an essential step for obtaining any testable biological hypotheses from the network structure. Several methods have been proposed to detect modules in metabolic networks and protein-protein interaction networks based on the topology of the network [ 21 , 26 - 30 ]. As shown in our recent work [ 27 ] the global connectivity structure of metabolic network was useful for a more reasonable decomposition of it into functional modules. However, the global structure of TRN has been so far not taken into account in its decomposition. In fact, little is known about the global connectivity structure of TRN. In this work we demonstrated the applicability of a top-down approach for the identification of functional modules in TRN with the well established transcriptional regulatory network of E. coli as an example. For this purpose we first showed an uncovered global hierarchical structure. Global regulators and modules with clearly defined functions were then identified by a new network decomposition method based on the hierarchical structure. We further investigated the distribution of the two basic network motifs, feed forward loop and bi-fan motif, in the network hierarchical structure and examined their relationship to functional modules. Results and discussion The hierarchical structure of regulatory network The transcriptional regulatory network of E. coli considered in this work is based on RegulonDB [ 5 ] and complemented by Shen-Orr et al [ 7 ]. It consists of 413 nodes and 576 links as shown in Fig. 1A . To investigate the network global connectivity, we calculated the weakly connected components and the strongly connected components in the network using the software Pajek [ 31 ]. A subset of nodes in a network is called a weakly connected component (WCC) if from every node of the subset all the other nodes belonging to the same subset can be reached when ignoring the direction of the links. If the direction is considered such a fully connected subset is then called a strongly connected component (SCC). We found 28 WCCs in the network. The largest one (the so-called giant component) consists of 325 operons which accounts for more than three quarters of the whole network. Among the other WCCs 20 of them contain only two operons and only 4 WCCs contain more than five operons. The existence of the giant component in TRN is similar to that found previously in metabolic networks[ 32 ]. However, different from metabolic networks we find that there is no SCC in the TRN of E. coli . This means that there are no regulatory cycles (e.g. gene A regulates gene B and gene B also regulates gene A through another path) in the TRN of E. coli . This result implies an acyclic structure of the E. coli TRN in which the nodes can be placed in different layers according to their depth. To identify such a hierachical structure we rearranged the operons in the following way: (1) operons which do not code for transcription factors (TFs) or code for a TF which only regulates its own expression (auto-regulatory loop) were assigned to layer 1 (the lowest layer); (2) then we removed all the operons in layer 1 and from the remaining network identified TFs which do not regulate other operons and assigned the corresponding operons in layer 2; (3) we repeated step 2 to remove nodes which have been assigned to a layer and identified a new layer until all the operons were assigned to different layers. As a result, a five layer hierarchical structure was uncovered as shown in Fig. 1B . All the regulatory links in this graph are downward and there is no link between operons in the same layer (except the auto-regulatory loops). Figure 1 Hierarchical structure of E. coli transcriptional regulatory network. A: The original unorganized network. B: the hierarchical regulation structure in which all the regulatory links are downward. Nodes in the graph are operons. Links show the transcriptional regulatory relationships. The global regulators found in this work are shown in red. The yellow marked nodes are operons in the longest regulatory pathway related with flagella motility. The multi-layer hierarchical structure of the E. coli TRN implies that no feed back regulation exists at transcription level. We noticed that Shen-Orr et al have also reported that there was no feed back loop in the E. coli regulatory network [ 7 ]. We further examined the yeast regulatory network proposed by Guelzim et al [ 8 ] and found it also has a similar hierarchical structure (result not shown). This gives rise to the question why the transcriptional regulatory networks of these organisms possess such an acyclic hierarchical structure. A possible explanation is that the interactions in TRN are interactions between proteins and DNAs. Therefore, a regulated gene must has been transcribed and translated into its protein product (which is eventually further modified by cofactor binding) to make a feedback interaction between it and its regulator gene possible. The well studied lac operon may be used as an example to further illustrate this point. Lac operon is not expressed unless lactose is available for the cell because it is repressed by the lac repressor. Lac repressor (the protein but not the gene) is the control element of the system. Its existence (expression) is necessary for the cell to properly response to environmental changes (i.e. the presence and absence of lactose). Therefore, for cells to quickly and properly response to changes of environmental conditions it is of advantage to keep a set of proteins expressed in all conditions and through them to regulate the expression of other genes in a hierarchical way. Feedback control of gene expression may be mainly through other interactions (e.g. metabolite and protein interaction) rather than through transcriptional interactions between proteins and genes. In fact, many transcription factors can bind small molecules to gain or loss their ability to bind DNA. The five-layer hierarchy shown in Fig. 1B does not necessarily mean that TFs at the top layer require 4 steps to regulate operons at the bottom layer. In fact, many operons at the bottom layer are directly regulated by top layer TFs. Among the 717 linked pairs of operons, 516 are directly connected. The average path length of the network is only 1.36, suggesting a fast and efficient response of cells to environment perturbations in general. The longest regulation path in the network is IHF → OmpR → FlhDC → FliA and further to seven operons (marked yellow in Fig. 1B ) related to flagella motility. The finding that there is no short-cut between these regulators and the regulated operons is unexpected. Regulatory relationships may exist between them but are not yet identified. Actually five operons that are regulated by FliA are also directly regulated by FlhDC , resulting in a shorter path between the upper layer regulators ( FlhDC ) and these operons. Network decomposition, global regulators and modules Based on the uncovered hierarchical organization structure we propose a new method to identify functional modules in TRN. As discussed above, there is a giant weakly connected component in the whole TRN of E. coli . We find that the giant component preserves the five layer hierarchical structure of the whole network. It also includes the single large motif super cluster found by Dorbin et al. [ 9 ] and thus preserves most of the network motifs in the whole network. Therefore, in the subsequent steps we focus on this giant component to present a new method to identify global regulators and modules in the network. First we removed all the operons in the top three layers and the operons which are regulated only by them, resulting in a network with 221 nodes and 186 links as shown in Fig. 2 . We found 41 weakly connected components in this reduced network (shown in different colors in Fig. 2 ). In contrast to the whole network, there is no giant component in the reduced network. The three largest components contain 38, 36 and 21 operons respectively (the nodes in blue, yellow and red respectively). It can be seen from Fig. 2 that these three components are connected by only one or two nodes. Therefore we can decompose them into two relatively independent parts by cutting through these nodes. For example, the largest component was separated by cutting gcvTHP which codes enzymes for glycine cleavage. We checked the function of the operons in the two separated parts by using EcoGene database [ 33 ]. The left part of this WCC is mainly for purine synthesis and the right part for amino acid uptake. All the other WCCs are very small with less than 12 operons. Most of them are regulated by only one regulator and thus they are in the same regulon. The functions of the operons in these WCCs are closely related. Therefore, we considered the WCCs (the two split parts for the three largest WCCs) which contain at least three nodes as preliminary modules in the network. Altogether 24 preliminary modules were obtained. The 20 small WCCs which contain only two nodes may be regulated by the same regulators at upper layers and thus can be grouped in the next organization level. In the next step, we extended the 24 preliminary modules by moving upward to include the regulators at the third, fourth and fifth layers consecutively and their regulated operons. Each of the regulator was investigated to find its linked preliminary modules and the number of links between them. The regulator was then classified into the module with the most connections. If a regulator has more links with operons which have not been assigned to any preliminary module than with any preliminary module, it formed a new module together with its regulated operons. In this way, the many small two-node components in the low hierarchy level can be grouped to form new modules. On the other hand, the regulators that regulate operons in three or more preliminary modules were regarded as global regulators and not assigned to any module. Using this method, 10 global regulators (Table 1 and Fig. 1B ) and 33 modules (Table 2 and Fig. 3 ) are identified. In addition, 6 modules found from the small WCCs of the whole network which contain at least three operons are also included in Table 2 . In Fig. 3 we place the ten global regulators in the central part, whereas the 33 modules are in the periphery part around them. We can see that the periphery modules are connected mainly through the global regulators. Figure 2 Preliminary modules in the reduced transcriptional regulatory network of E. coli. All the operons in the top three layers (Fig. 1b) and operons which are regulated only by them were removed to reduce the network. The weakly connected components of the reduced network were calculated and shown in different colors. Only WCCs which contain at least three nodes were considered as preliminary modules. The small WCCs which contain only two nodes were grouped at upper regulation level. The three largest WCCs were split into two preliminary modules by investigating their connectivity. Figure 3 Functional modules in the transcriptional regulatory network of E. coli . Operons in different modules are shown in different colors. The ten global regulators form the core part of the network. The periphery modules are connected mainly through the global regulators. Depending on the connectivity between the modules and their connectivity to the global regulators, these modules can be further grouped to larger modules at a higher level. Table 1 Global regulators and their regulated operons and functions in the regulatory network of E. coli . Global regulator directly regulated Operons Total regulated operons Modules regulated Function IHF 21 39 15 integration host factor CspA 2 24 5 Cold shock protein CRP 72 112 21 cAMP receptor protein FNR 22 38 16 anaerobic regulator, regulatory gene for nitrite and nitrate reductases, fumarate reductase HNS 7 22 5 DNA-binding global regulator; involved in chromosome organization; preferentially binds bent DNA OmpR 6 20 3 Response regulator for osmoregulation; regulates production of membrane proteins RpoN 12 17 4 RNA polymerase sigma 54 subunit RpoS 14 24 8 stationary phase sigma factor ArcA 20 21 6 Response regulator protein represses aerobic genes under anaerobic growth conditions and activates some anaerobic genes NarL 13 15 5 Two-component regulator protein for nitrate/nitrite response Table 2 Functional investigation of modules identified. index Operons included Biological function description 1 aceBAK, acs, adhE, fruBKA, fruR, icdA, iclMR, mlc, ppsA, ptsG, ptsHI_crr, pykF Hexose PTS transport system, PEP generation, Acetate usage, glyoxylate shunt 2 acnA, fpr, fumC, marRAB, nfo, sodA, soxR, soxS, zwf Oxidative stress response 3 ada_alkB, aidB, alkA, ahpCF, dps, gorA, katG, oxyR Oxidative stress response, Alkylation 4 alaWX, aldB, argU, argW, argX_hisR_leuT_proM, aspV, dnaA, leuQPV, leuX, lysT_valT_lysW, metT_leuW_glnUW_metU_glnVX, metY_yhbC_nusA_infB, nrdAB, pdhR_aceEF_lpdA, pheU, pheV, proK, proL, proP, sdhCDAB_b0725_sucABCD, serT, serX, thrU_tyrU_glyT_thrT, thrW, tyrTV, valUXY_lysV, yhdG_fis rRNA, tRNA genes, DNA synthesis system, pyruvate dehydrogenase and ketoglutarate dehydrogenase system 5 araBAD, araC, araE, araFGH, araJ Arabinose uptake and usage 6 argCBH, argD, argE, argF, argI, argR, carAB Arginine usage, urea cycle 7 caiF, caiTABCDE, fixABCX Carnitine usage 8 clpP, dnaKJ, grpE, hflB, htpG, htpY, ibpAB, lon, mopA, mopB, rpoH Heat shock response 9 codBA, cvpA_purF_ubiX, glnB, glyA, guaBA, metA, metH, metR, prsA, purC, purEK, purHD, purL, purMN, purR, pyrC, pyrD, speA, ycfC_purB, metC, metF, metJ Purine synthesis, purine and pyrimidine salvage pathway, methionine synthesis 10 cpxAR, cpxP, dsbA, ecfI, htrA, motABcheAW, ppiA, skp_lpxDA_fabZ, tsr, xprB_dsbC_recJ Stress response, Conjugative plasmid expression, cell motility and Chemotaxis 11 dctA, dcuB_fumB, frdABCD, yjdHG C4 dicarboxylate uptake 12 edd_eda, gntKU, gntR, gntT Gluconate usage, ED pathway 13 csgBA, csgDEFG, envY_ompT, evgA, gcvA, gcvR, gcvTHP, gltBDF, ilvIH, kbl_tdh, livJ, livKHMGF, lrp, lysU, ompC, ompF, oppABCDF, osmC, sdaA, serA, stpA Amino acid uptake and usage 14 fdhF, fhlA, hycABCDEFGH, hypABCDE Formate hydrogenlyase system 15 flgAMN, flgBCDEFGHIJ, flgKL, flgMN, flhBAE, flhDC, fliAZY, fliC, fliDST, fliE, fliFGHIJK, fliLMNOPQR, tarTapcheRBYZ Flagella motility system 16 ftsQAZ, rcsAB, wza_wzb_b2060_wcaA_wcaB Capsule synthesis, cell division 17 gdhA, glnALG, glnHPQ, nac, putAP Glutamine and proline utilization 18 glmUS, manXYZ, nagBACD, nagE Glucosamine, mannose utilization 19 glpACB, glpD, glpFK, glpR, glpTQ Glycerol phosphate utilization 20 lysA, lysR, tdcABCDEFG, tdcR Serine, threonine usage 21 malEFG, malK_lamB_malM, malPQ, malS, malT, malZ Maltose utilization 22 rhaBAD, rhaSR, rhaT Rhamnose utilization 23 appCBA, appY, betIBA, betT, cydAB, cyoABCDE, fadBA, focA_pflB, fumA, glcC, glcDEFGB, gltA, lctPRD, mdh, nuoABCEFGHIJKLMN, fabA, fadL, fadR, uspA Oxidative phosphorylation, Glycolate, lactose utilization, fatty acid degradation 24 cytR, deoCABD, deoR, nupC, nupG, tsx, udp Nucleosides uptake and usage 25 cirA, entCEBA, fecABCDE, fecIR, fepA_entD, fepB, fepDGC, fhuACDB, fur, tonB Iron uptake system 26 galETKM, galR, galS, mglBAC Galactose uptake and usage 27 dmsABC, fdnGHI, narGHJI, narK, nirBDC_cysG, nrfABCDEFG, torCAD, torR Nitrogen metabolism, Nitrate and nitrite reductase, 28 narZYWV, nhaA, nhaR, osmY intracellular pH regulation 29 aslB, inaA, mdlA, rob, ybaO, ybiS, yfhD Stress response 30 cutC, dapA_nlpB_purA, ecfABC, ecfD, ecfF, ecfG, ecfH, ecfJ, ecfK, ecfLM, fkpA, ksgA_epaG_epaH, lpxDA_fabZ, mdoGH, nlpB_purA, ostA_surA_pdxA, rfaDFCL, rfbO, rpoE_rseABC, uppS_cdsA_ecfE RpoE regulated stress response, lipopolysaccharide synthesis 31 ansB, cpdB, cyaA, dadAX, epd_pgk, glgCAP, glgS, ivbL_ilvBN, ompA, speC, srlAEBD_gutM_srlR_gutQ, tnaLAB, ubiG, yhfA Sorbitol and Glycogen metabolism 32 atoC, atoB, hydHG, hypA, pspABCDE, pspF, rtcAB, rtcR, zraP Phage shock protein, Zn-resistence system, Acetoacetate metabolism 33 dsdC, dsdXA, ebgAC, ebgR, fucAO, fucPIKUR, lacI, lacZYA, malI, malXY, melAB, melR, uhpA, uhpT, yiaJ, yiaKLMNOPQRS Lactose, maltose, fucose, dehydroascorbate, xylulose, melibiose transport and metabolism 34 aroF_tyrA, aroG, aroH, aroL_yaiA_aroM, aroP, mtr, trpLEDCBA, trpR, tyrP, tyrR Aromatic amino acid synthesis 35 bioA, bioBFCD, birA_murA Biotin synthesis 36 cbl, cysB, cysDNC, cysJIH, cysK, cysPUWAM, ssuEADCB, tauABCD Sulfur metabolism, cysteine synthesis, Taurine utilization 37 exuR, exuT, uidR, uidABC, uxaCA, uxuABR Utilization of hexUronide 38 lexA_dinF, polB, recA, recN, rpsU_dnaG_rpoD, ssb, sulA, umuDC, uvrA, uvrB, uvrC, uvrD DNA recombination and repair, UV resistent 39 phnCDE_f73_phnFGHIJKLMNOP, phoA, phoBR, phoE, pstSCAB_phoU Phosphate metabolism To investigate if the modules identified from anaylisis of the network structure are really functionally related, we checked the functions of the genes in the individual modules by using database EcoGene [ 33 ]. Most genes in the same module turned out to have closely related biological function. Thus, we can assign clearly defined functions for most of the modules. However, there are also several modules which include operons that are seemingly functionally not closely related. For example, there are also several operons for acetate usage in module 1 (Table 2 ) besides the operons for the PTS sugar transport system. One of the acetate usage operons aceBAK is also repressed by FruR , the regulator for fructose uptake. This makes the cell not to use acetate as a substrate in the presence of fructose. Therefore, the two different pathways are actually functionally related from a regulation viewpoint. The other three modules (module 4, 23 and 32) which include operons with different functions are actually linked by certain global regulators ( fis, arcA and rpoN respectively). They are not connected by any local regulators with specific functions. Thus, it is not strange that they are not closely functionally related. One reason for this problem is probably the information incompleteness of the network. The regulatory network considered in this work contains only about twenty percent of the genes in the E. coli genome. With more and more information available we can include more interactions and genes in the network to obtain more reasonable modules by structural analysis. Identifying these functional modules can help us to gain a general view of the function (or ability) of organisms. Furthermore, we can compare these structure based modules with modules from hierarchical classification results of microarray experiments to find unknown regulatory relationships. We compared the ten global regulators with those found in three previous studies by considering the number of directly or indirectly regulated genes (operons) and their structure and function diversity [ 7 , 10 , 11 ]. Five of them ( CRP, IHF, FNR, HNS, ArcA ) have been identified in all the three studies. The other five regulators have also been recognized as global in either one or two of the three studies. Our definition of global regulators is directly linked to the identification of functional modules. Modules are sets of genes with closely related function. An important criterion for a regulator to be regarded as global is that it regulates genes with diverse but concerted functions. Therefore, determination of global regulators by the number of regulated modules is more reasonable than that solely by the number of genes or operons. From Fig. 3 we can see that the number of links among the modules is far less than that between the global regulators and the modules. This indicates that the global regulators introduce the major cross-talks between modules and link them together to form the whole network. Therefore, breaking the links through the global regulators can help to identify the true modules as shown in this work. Network motifs and motif clusters To investigate if network motifs, which are considered to be the elementary building blocks of the whole network [ 17 ], are basic building blocks of modules and if motif clusters are generally equivalent to functional modules, we calculated the feed forward loops (FF loops) in the TRN of E. coli . In agreement with the results of Dobrin et al [ 9 ], the 42 FF loops in the network aggregate to seven homologous motif clusters (see Additional file Additional file 1 ). Four of the motif clusters are generally in consistence with the modules identified in this study (Table 2 ), including the flagellar-motor module (module 15), the osmoregulated porin gene module (13), the oxidative stress response module (2) and the methionine biosynthesis module (9). The third feed forward cluster found by Dorbin et al. [ 9 ] comprises genes of nitrogen regulation and formate regulon. They are found in two separate modules (14 and 17 respectively) in this work. In contrast to the good agreement for the five motif clusters, the other two clusters include genes belonging to many different modules. For example, the CRP cluster (see Additional file 1 ) consists of genes for usage of different carbon sources such as arabinose (module 5), carnitine (7), fucose (33), maltose (21), galactose (26) and mannose (18). The reason for this discrepancy is that each of the two clusters contains a global regulator ( FNR and CRP respectively) which regulates genes with various functions. We further investigated the distribution of the 42 FF loops in the hierarchical structure and find that 32 of them contain one of the ten global regulators. Because modules are defined as subsets of genes with closely related functions, while global regulators tend to regulate functionally far related genes, clusters formed from network motifs which contain global regulators are not proper candidates for modules. For the four consistent motif clusters, three of them are formed from the ten FF loops that do not contain global regulators. Cluster four (osmoregulated porin gene) contains the global regulators IHF and OmpR . As shown in Fig. 1B , these two global regulators also regulate genes with flagellar motility function (module 15) and many other genes with different functions. Therefore, these two regulators cannot be properly placed in one module though most of the other genes in the cluster are functionally related. We also calculated the bi-fan motifs and find that 180 of the 209 bi-fan motifs contain global regulators. Among them 130 bi-fan motifs contain two global regulators. This means that two target operons would be coregulated by two global regulators. The fact that most network motifs contain global regulators which regulate functionally far related operons indicates that motifs cannot be regarded as elementary building blocks of functional modules because global regulators should not belong to any module with specific functions. Conclusions The E. coli transcriptional regulatory network presently known possesses a multi-layer hierarchical structure with no feedback regulation at transcription level. Regulators in the top layers of the hierarchical structure can be considered as global regulators that often act together with local regulators to regulate genes in the bottom layer. Based on the hierarchical structure a new decomposition method is proposed which can be used to identify functional modules in the network. Analysis of operon composition of the two well-known network motifs (feed forward loop and bi-fan motif) and their distribution in the hierarchical structure suggests that they are not elementary building blocks of functional modules in the transcriptional regulatory network of E. coli . Methods Network reconstruction and representation The original transcriptional regulatory database of E. coli was obtained from the website of Alon's research group[ 34 ]. This database is mainly based on the RegulonDB [ 5 ] and complemented by Shen-Orr et al [ 7 ]. We removed three operons ( gatR_1 , rcsA and rotA ) because they are either the same with another operon or inside another operon. GatR_1 has been merged with gatR_2 in the updated annotation of E. coli genome in the database EcoGene [ 33 ]. RcsA is part of the rcsAB operon, while rotA is the same with ppiA . Another operon, nycA , was not found in any E. coli genome database. We searched the original literature [ 35 ] for this gene from the database obtained from Shen-Orr et al [ 7 ] and could still not find it. Therefore, we removed the nycA operon from the network. There are also six operons ( emrRAB , gatYZABCDR , hipBA , idnDOTR , moaABCDE and mtlADR ) in the network that are only autoregulated and hence do not connected with other operons. Therefore, we ignored these operons as well when analyzing the network connectivity structure. The resulting network consists of 413 nodes (operons) and 576 directed links (regulatory relationships). The 54 autoregulatory relationships in the network are represented as loops in the graph. Network structure analysis Calculations for the network structure analysis were carried out by using the software Pajek [ 31 ]. The number of directly regulated operons of a regulator gene equals to its output degree, while the total number of directly and indirectly regulated operons equals to its output domain. The connected components were found by calculating the weakly connected components (the direction ignored because the regulatory network is an acyclic directed graph). Network motif calculation From the hierarchical structure, feed forward loops are easily found by searching for all the fully connected triads which are located in different regulatory layers (not necessary to be three nearby layers). Bi-fan motifs are searched by using the subgraph searching algorithm in Pajek [ 31 ]. Authors' contributions HWM performed the analyses and drafted the manuscript. JB contributed to the concept and promoted the work. APZ is the project leader. He contributed to the concept, supervised the study and was involved in writing the manuscript. All authors have read and approved the final manuscript. Supplementary Material Additional File 1 Supplenmentary table 1 : Network motifs and motif clusters in the E. coli transcriptional regulatory network. Supplenmentary fig 1 : Modules in the hierarchical structure of the E. coli transcriptional regulatory network. Click here for file

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Role of health-related quality of life measures in the routine care of people with multiple sclerosis

Health-related quality of life instruments are expected to be of particular value in routine care of people with multiple sclerosis (MS), where they may facilitate the detection of disease aspects that would otherwise go unrecognised, help clinicians appreciate patient priorities particularly in terms of treatment goals, facilitate physician-patient communication, and promote shared decision-making. However, it appears that these instruments are little used routine clinical approaches to people with MS. To address this issue, I performed a bibliographic search of studies that evaluated the efficacy of generic or disease-specific health-related quality of life (HRQOL) instruments in MS clinical practice from clinicians' or patients' perspectives. I found only one cross-sectional study, which compared preferences for three instruments, and assessed acceptability in people with MS. Reasons for lack of transfer of HRQOL measurements to clinical practice may be cultural, methodological, or practical. With regard to MS, the proliferation of instruments seems to constitute a barrier, with no particular instrument having gained wide popularity or consensus. Other barriers are lack of resources for the administration, collection and storage of the data, and inability of clinicians to score, interpret, and use HRQOL instrument to guide clinical care. It is therefore important to refine existing tools, extending clinical validation to wider contexts and cultures. More studies assessing acceptability and clinicians' and patients' preferences for different instruments are also required.

Review Multiple sclerosis (MS) is a demyelinating disease of the central nervous system of unknown etiology and poorly understood pathogenesis. There is a north-south gradient of MS prevalence in the northern hemisphere, with highest levels (over 100 per 100,000) in northern regions [ 1 , 2 ]. It is a chronic disease with a modest effect on life expectancy, but a broad spectrum of consequences, of variable severity, on physical and psychological characteristics, that vary between individuals and within individuals over time. The disease typically strikes women (2:1) in their peak years of career development and family life; commonly there are exacerbations and remissions followed by progression whose rate and extent vary [ 3 ]. There is also a benign form of MS, characterised by few relapses, long periods of remission, and mild activity limitations over the long term [ 4 ]. The available treatments have at best a modest benefit on the course of the disease [ 5 ]. Health-related quality of life measures Interest in measuring outcomes in MS has increased markedly over the past 20 years. Standardised instruments have been developed, the most-used being the Expanded Disability Status Scale (EDSS) [ 6 ] which is a mixed impairment/activity limitations scale based on neurological examination of eight functional systems, plus ambulation/mobility status. Despite major limitations – bias towards locomotor function, variable sensitivity to change according to scale score, and suboptimal inter-rater reliability – the EDSS is widely-used by researchers and clinicians because its scores are readily understood by all. More recently, the importance of MS outcome assessment from the perspective of the person with the disease has been recognised [ 7 ]. After 1992, the number of publications on health-related quality of life (HRQOL) increased steadily, as did those employing MS-specific instruments (see Figure). Generic instruments were applied to MS [ 7 - 12 ], and disease-specific instruments were devised and validated [ 13 - 24 ]. The seven available MS-specific HRQOL instruments are listed in the Table 1 ; all were published between 1995 and 2001. Three consist of a generic module (SF-36 [ 13 , 15 ] or FACT-G [ 14 ]) plus an MS-specific module. In most cases people with MS participated in their development [ 13 , 16 ]. Except for the MS Quality of Life 54 (MSQOL-54), which has been translated into several languages [ 13 , 20 - 23 ], and the Functional Assessment of MS (FAMS), which is also available in Portuguese [ 24 ], these questionnaires are available only their original versions. Aspects of responsiveness were evaluated in four of the seven instruments, but in general sensitivity to change has been insufficiently investigated [ 18 , 25 - 28 ] Table 1 Characteristics of MS-specific HRQOL questionnaires MSQOL-54 FAMS MSQLI RAYS HAQUAMS MSIS-29 LMSQoL Publication year 1995 1996 1999 2000 2001 2001 2001 Generic module SF-36 (36 items) FACT-G (28 items) SF-36 (36 items) -- -- -- -- MS module 18 items 31 items 9 scales 50 items 38 items 29 items 8 items People with MS involved in development No Yes -- No Yes Yes Yes Versions US English [13] Italian [20] French [21] Canadian French [22] Japanese [23] US English [14] Portuguese [24] US English [15] Hebrew [16] German [17] English [18] English [19] Reliability Alpha Test-retest [13,20–23] Alpha [14,24] Alpha Test-retest [15] Alpha [16] Alpha Test-retest [17] Alpha Test-retest [18] Alpha Test-retest [19] Responsiveness RCT [25] RCT [26] -- RCT [27] -- RCT [28] Effect size [18] -- Domains not assessed Vision Vision Bladder/ bowel Sexual function -- -- -- Vision Sexual function Vision Time period assessed Past 4 weeks Current time Past week -- Past week Past year Past 4 weeks Past week Past 2 weeks Past month Time to complete 20 minutes 20 minutes -- -- 20 minutes -- -- Publications (no.) 16 10 5 1 3 7 2 Publication period 1995–2004 1996–2004 1999–2003 2000 2001–2004 2001–2004 2001 MSQOL-54 is the MS quality-of-life 54; FAMS is the Functional Assessment of MS; MSQLI is the MS Quality of Life; HAQUAMS is the Hamburg Quality of Life Questionnaire in MS; FACT-G is the Functional Assessment of Cancer Therapy, General version; LMSQoL is the Leeds MS Quality of Life. Alpha is Cronbach's coefficient alpha. RCT aspects of responsiveness assessed in randomized controlled trial. HRQOL and routine clinical practice HRQOL studies in MS have drawn attention to the multiplicity of domains that may be compromised by the disease, and the effects of this compromise on ability to cope. As expected, people with MS, especially those with a progressive course, report reduced physical functioning compared to the general population [ 10 , 11 , 29 - 31 ]; they are more likely to suffer fatigue [ 29 , 32 ] and depression [ 32 , 33 ] than the general population, and are also more likely to be unemployed [ 8 , 10 , 30 , 31 , 34 , 35 ]. Unexpectedly, however, it has been reported that the importance attached to compromise in different HRQOL domains may vary considerably between MS sufferers and their neurologists [ 7 ]. The ultimate aim of measuring HRQOL is to provide a comprehensive assessment of patients' health status, to serve as a baseline from which to tailor interventions, pharmacological or otherwise, and assess their effectiveness, both in the clinical trial setting and in routine care. HRQOL instruments are expected to be of particular value in routine care, where they may improve the detection of disease aspects that would otherwise go unrecognised, help clinicians appreciate patient priorities particularly in terms of treatment goals, facilitate physician-patient communication, and promote shared decision making. In addition HRQOL data from clinical trials can provide information that clinicians can usefully discuss with their patients [ 36 ]. Unfortunately, although recent MS trials include some HRQOL assessment, there is no internationally agreed gold standard for conducting such assessment or reporting outcomes. HRQOL evaluations are not required as endpoints in MS trials by the European Agency for the Evaluation of Medicinal Products [ 37 ]. Even when HRQOL endpoints are included, data collection and reporting are often of poor quality [ 38 ] with the consequence that cost effectiveness issues, which HRQOL instruments can throw light on, such as preserved function, less work missed, and improved emotional well-being, are not analysed. Literature survey It appears that HRQOL instruments are little used in routine clinical approaches to people with MS. To address this issue, I searched MEDLINE (1966–2004), the Cochrane Library (Issue 1, 2005) and the Cochrane MS Group trials register (2004) for studies that evaluated the efficacy of generic or MS-specific HRQOL instruments in clinical practice from the clinicians' or MS patients' perspective, also checking study references. Studies considering patient-reported outcomes other than HRQOL, and domain-specific measures were excluded. I found only one study, a cross-sectional postal survey conducted in Canada, published in 2004 [ 39 ]. This study assessed MS sufferers' preferences regarding two generic instruments (the EuroQol EQ-5D and the SF-36), and an MS-specific instrument (MSQOL-54). Over 90% of 183 participants reported that EuroQol EQ-5D and the SF-36 were acceptable or very acceptable, and 85% did so for MSQOL-54. Surprisingly, over 75% of participants felt that a combination of the three instruments best described their HRQOL. The reasons for lack of transfer of HRQOL assessment into clinical practice may be cultural, practical, or methodological [ 40 - 43 ]. With regard to cultural factors, patients generally welcome the opportunity to provide clinicians with information regarding their HRQOL [ 43 ]. That this is also the case for people with MS is suggested by high participation rates in most postal surveys assessing patient-reported health status [ 30 , 35 , 39 , 44 ], and by the good acceptability of HRQOL instruments [ 39 ]. By contrast, information on practicing clinicians' perceptions of the utility of HRQOL data is limited and conflicting: studies have uncovered a lack of knowledge of HRQOL as well as concerns that these instruments may be a covert means of assessing physicians' performance [ 45 , 46 ]. Practical considerations be particularly important in clinical settings, where data must be provided promptly and in an understandable manner to be of use. Instruments must be administered, processed, scored, stored and retrieved – all of which have logistic and financial implications [ 47 ]. Most HRQOL instruments are lengthy and may be burdensome for patients and clinicians. For most existing instruments, the score is not immediately available, but needs to be calculated, while score interpretation may not be straightforward. For example a recently published study on transplant physicians found that 55% would be more likely to use HRQOL data if it were more comprehensible [ 48 ]. In the United States time spent gathering and interpreting HRQOL information as part of the clinical encounter is not built into reimbursement by third-party payers [ 49 ]. It is noteworthy, however, that questionnaire length seems not to be a drawback for people with MS since a combination of HRQOL instruments was preferred by over 75% of participants in the only study found [ 39 ]. Another factor limiting the dissemination of HRQOL tools in MS clinical practice is likely to be that too many instruments are available, and unlike EDSS, none has emerged as clearly superior to any other. Conclusion Existing HRQOL tools for people with MS should be refined and their clinical validation pursued in the widest possible cultural context. More studies assessing instrument acceptability and preferences of clinicians and people with MS are also needed. It would be useful for example to implement computer-based technology (touch-screens and adaptive administration to reduce respondent burden by selecting pertinent items and omitting inappropriate ones) and other alternatives to traditional paper-and-pencil or interview methods, which should of course be evaluated for acceptability and reliability [ 48 ]. The objective is not to add HRQOL measurements to the chores of everyday practice, but to incorporate meaningful HRQOL instruments into the care process [ 50 ]. Figure 1 Number of publications on HRQOL in people with MS between 1992 and 2004. Blue bars indicate all studies on HRQOL; light blue bars indicate studies employing MS-specific instruments. Studies considering patient-reported outcomes other than HRQOL, or domain-specific measures are excluded.

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Nucleus accumbens core lesions retard instrumental learning and performance with delayed reinforcement in the rat

Background Delays between actions and their outcomes severely hinder reinforcement learning systems, but little is known of the neural mechanism by which animals overcome this problem and bridge such delays. The nucleus accumbens core (AcbC), part of the ventral striatum, is required for normal preference for a large, delayed reward over a small, immediate reward (self-controlled choice) in rats, but the reason for this is unclear. We investigated the role of the AcbC in learning a free-operant instrumental response using delayed reinforcement, performance of a previously-learned response for delayed reinforcement, and assessment of the relative magnitudes of two different rewards. Results Groups of rats with excitotoxic or sham lesions of the AcbC acquired an instrumental response with different delays (0, 10, or 20 s) between the lever-press response and reinforcer delivery. A second (inactive) lever was also present, but responding on it was never reinforced. As expected, the delays retarded learning in normal rats. AcbC lesions did not hinder learning in the absence of delays, but AcbC-lesioned rats were impaired in learning when there was a delay, relative to sham-operated controls. All groups eventually acquired the response and discriminated the active lever from the inactive lever to some degree. Rats were subsequently trained to discriminate reinforcers of different magnitudes. AcbC-lesioned rats were more sensitive to differences in reinforcer magnitude than sham-operated controls, suggesting that the deficit in self-controlled choice previously observed in such rats was a consequence of reduced preference for delayed rewards relative to immediate rewards, not of reduced preference for large rewards relative to small rewards. AcbC lesions also impaired the performance of a previously-learned instrumental response in a delay-dependent fashion. Conclusions These results demonstrate that the AcbC contributes to instrumental learning and performance by bridging delays between subjects' actions and the ensuing outcomes that reinforce behaviour.

Background Animals learn to control their environment through instrumental (operant) conditioning. When an animal acts to obtain reward or reinforcement, there is often a delay between its action and the outcome; thus, animals must learn instrumental action-outcome contingencies using delayed reinforcement. Although such delays impair learning, animals can nevertheless bridge substantial delays to acquire instrumental responses [ 1 ]. Little is known of the neural basis of this process. However, abnormalities in learning from delayed reinforcement may be of considerable clinical significance [ 2 ]. Impulsivity is part of the syndrome of many psychiatric disorders, including mania, drug addiction, antisocial personality disorder, and attention-deficit/hyperactivity disorder [ 3 ]. Impulsive choice, one aspect of impulsivity [ 4 ], is exemplified by the tendency to choose small rewards that are available immediately instead of larger rewards that are only available after a delay [ 5 , 6 ], and may reflect dysfunction of reinforcement learning systems mediating the effects of delayed rewards [ 5 , 7 ]. The nucleus accumbens (Acb) responds to anticipated rewards in humans, other primates, and rats [ 8 - 15 ], and is innervated by dopamine (DA) neurons that respond to errors in reward prediction in a manner appropriate for a teaching signal [ 16 - 19 ]. The Acb may therefore represent a reinforcement learning system specialized for learning with delayed reinforcement [ 20 , 21 ]. If this is the case, then damage to the Acb should not interfere with reinforcement learning in all circumstances, but should produce selective impairments in learning when reinforcement is delayed. This prediction has not previously been tested. However, lesions of the AcbC cause rats to prefer small immediate rewards (a single food pellet delivered immediately) to large delayed rewards (four pellets delivered after a delay); that is, AcbC-lesioned rats exhibit impulsive choice [ 22 , 23 ]. The reason for this is not clear. It might be that AcbC-lesioned rats exhibit steeper temporal discounting, such that the subjective utility (value) of future rewards declines more rapidly than normal as the reward is progressively delayed [ 24 , 25 ]. It might also be that AcbC-lesioned rats are less good at representing the contingency between actions and their outcomes when the outcomes are delayed, so that they choose impulsively because they are less certain or less aware that their choosing the delayed reward does in fact lead to that reward being delivered [ 24 , 25 ]. Both explanations would reflect a problem in dealing with delayed reinforcement in AcbC-lesioned rats. However, there might be a simpler explanation for the impulsive choice exhibited by AcbC-lesioned rats: they might perceive the size (magnitude) of rewards differently. For example, if they do not perceive the delayed reward to be as large, relative to the immediate reward, as normal rats did, then they might choose impulsively despite processing the delays to reward normally, simply because the delayed reinforcer is not subjectively large enough to compensate for the normal effects of the delay [ 24 - 26 ]. To investigate whether the AcbC is a reinforcement learning system specialized for delayed reinforcement, we first determined the ability of AcbC-lesioned rats to detect instrumental contingencies across a delay. The ability of AcbC-lesioned rats to acquire instrumental responding with delayed reinforcement was compared to that of sham-operated controls; each subject was allowed to respond freely on two levers, one of which produced reinforcement after a delay of 0, 10, or 20 s (Figure 1 ). We report that AcbC lesions only retarded instrumental learning when reinforcement was delayed, demonstrating a role for the AcbC in bridging action-outcome delays during learning. Subsequently, to establish whether AcbC-lesioned rats perceive reward magnitude abnormally, we assessed these subjects' sensitivity to reinforcer magnitude by measuring their relative preference for two different reinforcers using concurrent interval schedules of reinforcement. We report that reinforcer magnitude discrimination in AcbC-lesioned rats in this task was at least as good as in sham-operated controls, consistent with previous evidence of reinforcer magnitude discrimination following lesions of the whole Acb e.g. [ 27 , 28 ]. Together, these results suggest that the impulsive choice seen in AcbC-lesioned rats [ 22 ] is due to a problem in processing delayed reward, not in processing the magnitudes of the reward alternatives. Finally, to establish whether the AcbC is required for the performance of an instrumental response for delayed reinforcement, as well as for the learning of such a response, we trained naïve rats to respond for delayed reinforcement (Figure 1 ) before destroying the AcbC. We report that such lesions also impaired performance of a previously-learned instrumental response only when reinforcement was delayed, indicating that the AcbC makes an enduring contribution to bridging delays between subjects' actions and the ensuing outcomes. Figure 1 Task schematic: free-operant instrumental responding on a fixed-ratio-1 (FR-1) schedule with delayed reinforcement Subjects are offered two levers; one (the active lever) delivers a single food pellet for every press (an FR-1 schedule) and the other (the inactive lever) has no programmed consequence. Food can either be delivered immediately (a) or after a delay (b) following responses on the active lever. The levers remain available throughout the session (hence, free-operant responding: animals are free to perform the operant at any time). Events of interest are lever presses, delivery of food pellets, and collection of food by the rat (when it pokes its nose into the food alcove following food delivery). To obtain food, the hungry rat must discriminate the active from the inactive lever, which is more difficult when the outcome is delayed. In these examples, the rat's response patterns (active and inactive lever presses, and collection of food) are fictional, while food delivery is contingent upon active lever pressing. Results In Experiment 1, rats received excitotoxic lesions of the AcbC or sham lesions, and were then tested on an instrumental free-operant acquisition task with delayed reinforcement (Experiment 1A; see Methods) and subsequently a reinforcer magnitude discrimination task (Experiment 1B). In Experiment 2, naïve rats were trained on the free-operant task for delayed reinforcement; AcbC lesions were then made and the rats were retested. Histology In Experiment 1, there were two postoperative deaths. Histological analysis revealed that the lesions were incomplete or encroached significantly on neighbouring structures in four subjects. These subjects were excluded; final group numbers were therefore 8 (sham, 0 s delay), 6 (AcbC, 0 s delay), 8 (sham, 10 s delay), 7 (AcbC, 10 s delay), 8 (sham, 20 s delay), and 7 (AcbC, 20 s delay). In Experiment 2, one rat spontaneously fell ill with a colonic volvulus during preoperative training and was killed, and there were three postoperative deaths. Lesions were incomplete or too extensive in seven subjects; final group numbers were therefore 7 (sham, 0 s delay), 5 (AcbC, 0 s delay), 8 (sham, 10 s delay), 4 (AcbC, 10 s delay), 8 (sham, 20 s delay), and 5 (AcbC, 20 s delay). Lesions of the AcbC encompassed most of the core subregion; neuronal loss and associated gliosis extended in an anteroposterior direction from approximately 2.7 mm to 0.5 mm anterior to bregma, and did not extend ventrally or caudally into the ventral pallidum or olfactory tubercle. Damage to the ventromedial caudate-putamen was occasionally seen; damage to AcbSh was restricted to the lateral edge of the dorsal shell. Schematics of the lesions are shown in Figure 2 . Photomicrographs of one lesion are shown in Figure 3 , and are similar to lesions with identical parameters that have been presented before [ 29 , 30 ]. Figure 2 Schematic of lesions of the AcbC Black shading indicates the extent of neuronal loss common to all subjects; grey indicates the area lesioned in at least one subject. Coronal sections are (from top to bottom) +2.7, +2.2, +1.7, +1.2, and +0.7 mm relative to bregma. Diagrams are modified from reference [83]. Panels a-c correspond to Experiment 1, in which lesions were made before training; panels d-f correspond to Experiment 2, in which lesions were made after initial training. Panels a & d show groups trained with no delays; panels b & e show groups trained with 10 s delays; panels c & f show groups trained with 20 s delays. Figure 3 Photomicrographs of lesions of the AcbC Lesions of the AcbC: photomicrographs of sections ~1.2 mm anterior to bregma, stained with cresyl violet. (a) Sham-operated rat, low-magnification view, right hemisphere (medial to the left). LV, lateral ventricle; CPu, caudate/putamen; AcbSh, nucleus accumbens shell; AcbC, nucleus accumbens core; ac, anterior commissure. The box marks the area magnified in (b). (b) Sham-operated rat, high-magnification view. Cresyl violet is basic and stains for Nissl substance, primarily nucleic acids (DNA and RNA); it therefore stains cytoplasmic rough endoplasmic reticulum, nuclei, and nucleoli. Individual neuronal nuclei are visible (circles ~10 μm in diameter). (c) AcbC-lesioned rat, low-magnification view. Dotted lines show the approximate extent of the lesion. There is some tissue collapse within the lesion and the lateral ventricle is slightly expanded. The box marks the area magnified in (d). (d) AcbC-lesioned rat, high-magnification view. In the region of the lesion, neurons have been replaced by smaller, densely-staining cells, indicating gliosis. (e) Coronal diagram of the rat brain at the same anteroposterior level [83], with scale. The light grey box indicates approximately the region shown in (a) and (c); the dark grey box indicates approximately the region shown in (b) and (e). Acquisition of instrumental responding (Experiment 1A) The imposition of response-reinforcer delays retarded the acquisition of free-operant lever pressing, in sham-operated rats and in AcbC-lesioned rats (Figure 4 ). AcbC-lesioned rats responded slightly more than shams on both the active and inactive levers in the absence of response-reinforcers delays, but when such delays were present, AcbC lesions retarded acquisition relative to sham-operated controls (Figure 5 ). Figure 4 Effects of delays to reinforcement on acquisition of free-operant responding under an FR-1 schedule Data plotted to show the effects of delays. All groups discriminated between the active and the inactive lever, and delays retarded acquisition of the active lever response in both groups. (a) Responding of sham-operated control rats, under all three response-reinforcer delay conditions. (b) Responding of AcbC-lesioned rats under all delay conditions. The next figure replots these data to show the effect of the lesion more clearly. Figure 5 Effect of AcbC lesions on acquisition of free-operant responding with delayed reinforcement Data plotted to show the effects of AcbC lesions (same data as in the previous figure). There was a delay-dependent impairment in AcbC-lesioned rats, who learned less well than shams only when reinforcement was delayed. (a) With a delay of 0 s, AcbC-lesioned rats learned just as well as shams; in fact, they responded more on the active lever than shams did. (b) With a 10 s delay, AcbC-lesioned rats were impaired at learning compared to shams. (c) With a 20 s delay, the impairment in AcbC-lesioned rats was larger still. An overall ANOVA using the model lesion 2 × delay 3 × (session 14 × lever 2 × S) revealed multiple significant interactions, including lever × delay × lesion ( F 2,38 = 5.17, p = .01) and session × lever × delay ( F 6.0,229.1 = 5.47, = .464, p < .001), justifying sub-analysis. All six groups learned to respond more on the active lever than the inactive lever ( p ≤ .002, main effect of lever or session × lever interaction for each group alone). For sham-operated rats, delays reduced the rate of acquisition of the active lever response and reduced the asymptotic level of responding attained (Figure 4a ; delay: F 2,21 = 11.7, p < .001; = .276, p < .001; session × delay: F 7.2,75.3 = 2.46, = .276, p = .024). The presence of a delay also increased responding on the inactive lever slightly (delay: F 2,21 = 4.06, p = .032), though not systematically (the 10 s group differed from the 0 s group, p = .036, but no other groups differed, p ≥ .153). There was a further, delay-dependent impairment in AcbC-lesioned rats, who responded more than shams at 0 s delay but substantially less than shams at 10 s and 20 s delay. As in the case of sham-operated controls, delays reduced the rate of acquisition and the maximum level of responding attained in AcbC-lesioned rats (Figure 4b ; delay: F 2,17 = 54.6, p < .001; delay × session: F 6.9,58.7 = 2.64, = .266, p = .02). Responding on the inactive lever was not significantly affected by the delays (maximum F 15.8,134.2 = 1.65, = .607, p = .066). At 0 s delay, AcbC-lesioned subjects responded more than shams on the active lever (Figure 5a ; lesion: F 1,12 = 5.30, p = .04) and the inactive lever (lesion: F 1,12 = 9.12, p = .011). However, at 10 s delay, AcbC-lesioned rats responded significantly less than shams on the active lever (Figure 5b ; lesion: F 1,13 = 9.04, p = .01); there was no difference in responding on the inactive lever ( F < 1, NS). At 20 s delay, again, AcbC-lesioned rats responded significantly less than shams on the active lever (Figure 5c ; lesion: F 1,13 = 9.87, p = .008) and there was no difference in responding on the inactive lever ( F < 1, NS). Experienced response-delivery and response-collection delays (Experiment 1A) For every reinforcer delivered, the active lever response most closely preceding it in time was identified, and the time between that response and delivery of the reinforcer (the 'response-delivery delay') was calculated. This time can therefore be equal to or less than the programmed delay, and is only relevant for subjects experiencing non-zero programmed response-reinforcer delays. The response-to-reinforcer-collection ('response-collection') delays were also calculated: for every reinforcer delivered, the response most closely preceding it and the nosepoke most closely following it were identified, and the time between these two events calculated. This time can be shorter or longer than the programmed delay, and is relevant for all subjects. AcbC-lesioned rats experienced the same response-delivery delays as shams when the programmed delay was 10 s, but experienced longer response-delivery delays when the programmed delay was 20 s (Figure 6a ). Similarly, AcbC-lesioned rats experienced the same response-collection delays as shams when the programmed delay was 0 s, slightly but not significantly longer response-collection delays when the programmed delay was 10 s, and significantly longer response-collection delays when the programmed delay was 20 s (Figure 6b ). These differences in the mean delay experienced by each rat were reflected in differences in the distribution of response-delivery and response-collection delays when the programmed delay was non-zero (Figure 6c,d ). Since AcbC-lesioned rats experienced slightly longer delays than sham-operated rats, it was necessary to take this into account when establishing the effect of delays on learning, as follows. Figure 6 Programmed and experienced delays to reinforcement AcbC-lesioned rats experienced slightly longer response-delivery delays (the delay between the most recent active lever press and pellet delivery) than shams in the 20 s condition, and slightly longer response-collection delays (the delay between the most recent active lever press and pellet collection) in the 10 s and 20 s conditions. (a) Mean experienced response-delivery delays (one value calculated per subject). When the programmed delay was 0 s, reinforcers were delivered immediately so no data are shown. There was a lesion × programmed delay interaction ( F 1,26 = 12.0, p = .002): when the programmed delay was 10 s, the experienced delays did not differ between groups ( F < 1, NS), but when the programmed delay was 20 s, AcbC-lesioned rats experienced longer response-delivery delays (one-way ANOVA, F 1,13 = 19.0, ** p = .001). (b) Mean experienced response-collection delays (one value calculated per subject). There was a lesion × programmed delay interaction ( F 2,38 = 7.14, p = .002): AcbC-lesioned rats did not experience significantly different delays when the programmed delay was 0 s ( F < 1, NS) or 10 s ( F 1,13 = 4.52, p = .053), but experienced significantly longer response-collection delays when the programmed delay was 20 s ( F 1,13 = 15.4, ** p = .002). (c) Distribution of experienced response-delivery delays. All experienced delays for a given subject were aggregated across all sessions, and the proportion falling into different 2 s ranges were calculated to give one value per range per subject; the graphs show means ± SEMs of these values. The interval notation '[ a , b )' indicates that a given delay x falls in the range a ≤ x < b . There were no differences in the distribution of delays experienced by AcbC-lesioned and sham rats in the 10 s condition (lesion and lesion × range, F s < 1, NS), but in the 20 s condition AcbC-lesioned rats experienced slightly fewer short delays and slightly more long delays (lesion × range, F 2.1,27.7 = 6.60, = .213, p = .004). (d) Distribution of experienced response-collection delays, displayed in the same manner as (c). There were no differences in the distribution of delays experienced by AcbC-lesioned and sham rats in the 0 s condition (lesion and lesion × range, F s < 1, NS). In the 10 s condition, AcbC-lesioned rats experienced a slightly higher proportion of long response-collection delays and a slightly lower proportion of short response-collection delays (lesion, F 1,13 = 6.36, p = .036, though the lesion × range interaction was not significant, F 2.6,34.3 = 1.74, = .139, p = .181). Similarly, in the 20 s condition, AcbC-lesioned rats experienced a slightly higher proportion of long response-collection delays and a slightly lower proportion of short response-collection delays than shams (lesion × range, F 4.2,54.8 = 6.65, = .222, p < .001). Effect of delays on learning (Experiment 1A) There was a systematic relationship between the acquisition rate and the programmed delay of reinforcement, and this was altered in AcbC-lesioned rats. Figure 7a replots the rates of responding on the active lever on session 10 of acquisition [ 1 ]. Despite the comparatively low power of such an analysis, lever-pressing was analysed for this session only using the model lesion 2 × delay 3 . This revealed a significant lesion × delay interaction ( F 2,38 = 12.6, p < .001), which was analysed further. Increasing delays significantly reduced the rate of responding in this session for shams ( F 2,21 = 17.3, p < .001) and AcbC-lesioned rats ( F 2,17 = 54.4, p < .001). AcbC-lesioned rats responded more than shams at zero delay ( F 1,12 = 8.52, p = .013) but less than shams at 10 s delay ( F 1,13 = 4.71, p = .049) and at 20 s delay ( F 1,13 = 17.3, p = .001). Figure 7 Learning as a function of programmed and experienced delays to reinforcement The imposition of response-reinforcer delays systematically retarded the acquisition of free-operant instrumental responding, and this relationship was altered in AcbC-lesioned rats, even allowing for differences in experienced response-collection delays. (a) The rate of responding on the active lever in session 10 is plotted against the programmed response-reinforcer delay. AcbC-lesioned rats responded more than shams at zero delay (* p = .013), but less than shams at 10 s (* p = .049) and 20 s delay (*** p = .001). (b) Responding on the active lever in session 10 plotted against the experienced response-to-reinforcer collection delays for sessions 1–10 (vertical error bars: SEM of the square-root-transformed number of responses in session 10; horizontal error bars: SEM of the experienced response-collection delay, calculated up to and including that session). The gradients of the two lines differed significantly (### p = .001; see text), indicating that the relationship between experienced delays and responding was altered in AcbC-lesioned rats. Since the AcbC group experienced slightly longer response-delivery and response-collection delays than shams when the programmed delay was non-zero (Figure 6 ), it was important to establish whether this effect alone was responsible for the retardation of learning, or whether delays retarded learning in AcbC-lesioned rats over and above any effect to increase the experienced delay. The mean experienced response-collection delay was calculated for each subject, up to and including session 10. The square-root-transformed number of responses on the active lever in session 10 was then analysed using a general linear model of the form lesion 2 × experienced delay cov . Unlike a standard analysis of covariance, the factor × covariate interaction term was included in the model. This confirmed that the lesion retarded the acquisition of responding in AcbC-lesioned rats, compared to controls, in a delay-dependent manner, over and above the differences in experienced delay (Figure 7b ; lesion × experienced delay: F 1,40 = 12.4, p = .001). Experienced delays and learning on the inactive lever (Experiment 1A) No such delay-dependent effects were observed for the inactive lever. Experienced inactive-response-delivery delays (calculated across all sessions in the same manner as for the active lever) were much longer and more variable than corresponding delays for the active lever, because subjects responded on the inactive lever so little. Means ± SEMs were 250 ± 19 s (sham, 0 s), 214 ± 29 s (AcbC, 0 s), 167 ± 23 s (sham, 10 s), 176 ± 33 s (AcbC, 10 s), 229 ± 65 s (sham, 20 s), and 131 ± 37 s (AcbC, 20 s). ANOVA of these data revealed no effects of lesion or programmed delay and no interaction (maximum F 1,38 = 1.69, NS). Experienced inactive-response-collection delays were 252 ± 19 s (sham, 0 s), 217 ± 29 s (AcbC, 0 s), 169 ± 23 s (sham, 10 s), 179 ± 33 s (AcbC, 10 s), 231 ± 65 s (sham, 20 s), and 136 ± 37 s (AcbC, 20 s). Again, ANOVA revealed no effects of lesion or programmed delay and no interaction (maximum F 1,38 = 1.61, NS). When the square-root-transformed number of responses on the inactive lever in session 10 was analysed with the experienced delays up to that point as a predictor, using the model lesion 2 × experienced inactive-response-collection delay cov just as for the active lever analysis, there was no lesion × experienced delay interaction ( F < 1, NS). Discrimination of relative reinforcer magnitude (Experiment 1B) Relative preference for two reinforcers may be inferred from the distribution of responses on concurrent variable interval schedules of reinforcement [ 31 - 33 ]. According to Herrnstein's matching law [ 31 ], if subjects respond on two concurrent schedules A and B delivering reinforcement at rates r A and r B respectively, they should allocate their response rates R A and R B such that R A /( R A + R B ) = r A /( r A + r B ). Overmatching is said to occur if subjects prefer the schedule with the higher reinforcement rate more than predicted by the matching law; undermatching is the opposite. Both sham-operated and AcbC-lesioned rats were sensitive to the distribution of reinforcement that they received on two concurrent random interval (RI) schedules, altering their response allocation accordingly. Subjects preferred the lever on which they received a greater proportion of reinforcement. In general, subjects did not conform to the matching law, but exhibited substantial undermatching; this is common [ 33 ]. AcbC-lesioned rats exhibited better matching (less undermatching) than shams (Figure 8 ), suggesting that their sensitivity to the relative magnitudes of the two reinforcers was as good as, or better than, shams'. Figure 8 Discrimination of reinforcer magnitude: matching of relative response rate to relative reinforcement rate AcbC-lesioned rats exhibited better sensitivity to the difference between 1 and 4 food pellets than shams did. Subjects responded on two concurrent RI-60-s schedules, designated A and B, and the reinforcer magnitude for each schedule was varied. Data from the last session of each condition are plotted (sessions 11, 19, and 27; see Table 1 ); programmed reinforcement ratios were 0.2 (1 food pellet on schedule A and 4 pellets on schedule B), 0.5 (1:1 pellets), and 0.8 (4:1 pellets). The abscissa (horizontal axis) shows experienced reinforcement ratios (mean ± SEM); the ordinate (vertical axis) shows response allocation (mean ± SEM). Both groups exhibited substantial undermatching (deviation away from the predictions of the matching law and towards indifference). However, neither group was indifferent to the reinforcement ratio: the sham and AcbC groups both adjusted their response allocation towards the lever delivering the reinforcer with the greater magnitude (*** p < .001). Matching was better in AcbC-lesioned rats than in shams (lines of different gradient, # p = .021), suggesting that they were more sensitive to the difference between 1 and 4 food pellets. Table 1 Training and testing schedule for reinforcer magnitude matching task (Experiment 1B) Subjects were trained to respond on two levers (designated A and B) separately and then concurrently under interval schedules of reinforcement. In sessions 8–27, their preference for reinforcers of different magnitudes was assessed. The third column, labelled ' f A', indicates the fraction of responses that would be allocated to lever A [i.e. A/(A+B)] were the subject to obey the matching law [31]. All concurrent (two-lever) schedules were subject to a 2 s changeover delay (COD), described in the Methods. Day Condition f A Lever A Lever B 1 One-lever training -- RI-2s, 1-pellet reinforcer absent 2 One-lever training -- absent RI-2s, 1-pellet reinforcer 3 One-lever training -- RI-15s, 1-pellet reinforcer absent 4 One-lever training -- absent RI-15s, 1-pellet reinforcer 5 One-lever training -- RI-30s, 1-pellet reinforcer absent 6 One-lever training -- absent RI-30s, 1-pellet reinforcer 7 Two-lever training 0.5 RI-30s, 1-pellet reinforcer RI-30s, 1-pellet reinforcer 8–11 1:1 magnitude 0.5 RI-60s, 1-pellet reinforcer RI-60s, 1-pellet reinforcer 12–19 4:1 magnitude 0.8 RI-60s, 4-pellet reinforcer RI-60s, 1-pellet reinforcer 20–27 1:4 magnitude 0.2 RI-60s, 1-pellet reinforcer RI-60s, 4-pellet reinforcer To analyse these data, the proportion of pellets delivered by lever A (see Methods), and the proportion of responses allocated to lever A, were calculated for each subject for the last session in each of the three programmed reinforcement distribution contingencies (session 11, programmed reinforcement proportion 0.5; session 19, programmed proportion 0.8; session 27, programmed proportion 0.2; see Table 1 ). The analysis used a model of the form response proportion = lesion 2 × (experienced reinforcer distribution cov × S); the factor × covariate term was included in the model. Analysis of sham and AcbC groups separately demonstrated that both groups altered their response allocation according to the distribution of reinforcement, i.e. that both groups discriminated the two reinforcers on the basis of their magnitude (effects of reinforcer distribution; sham: F 1,47 = 16.6, p < .001; AcbC: F 1,39 = 97.2, p < .001). There was also a significant lesion × reinforcer distribution interaction ( F 1,86 = 5.5, p = .021), indicating that the two groups' matching behaviour differed, with the AcbC-lesioned rats showing better sensitivity to the relative reinforcer magnitude than the shams (Figure 8 ). These statistical conclusions were not altered by including counterbalancing terms accounting for whether lever A was the left or right lever (the left having been the active lever previously in Experiment 1A), or whether a given rat had been trained with 0, 10, or 20 s delays in Experiment 1A. Switching behaviour during concurrent schedule performance (Experiment 1B) Because switching behaviour has the potential to influence behaviour on concurrent schedules e.g. [ 34 ], we also analysed switching probabilities. AcbC-lesioned rats were less likely than shams to switch between levers when responding on two identical concurrent RI schedules with a changeover delay (COD) of 2 s. Responses on the left and right levers were sequenced for sessions 8–11 (concurrent RI-60s schedules, each delivering a one-pellet reinforcer; see Methods and Table 1 ), and the probabilities of switching from one type of response to another, or repeating the same type of response, were calculated. The switch probabilities were analysed by one-way ANOVA; this revealed an effect of lesion ( F 1,42 = 8.88, p = .005). Mean switch probabilities (± SEMs) were 0.41 ± 0.02 (AcbC) and 0.49 ± 0.01 (sham). Effects of AcbC lesions on performance of a previously-learned instrumental response for delayed reinforcement (Experiment 2) Due to mechanical faults, data from four subjects in session 10 (preoperative) and data from one subject in session 22 (postoperative) were not collected. Both sessions were removed from analysis completely, and data points for those sessions are plotted using the mean and SEM of the remaining unaffected subjects (but not analysed). Preoperatively, the groups remained matched following later histological selection. Analysis of the last 3 preoperative sessions, using the model lesion intent 2 × delay 3 × (session 3 × lever 2 × S), indicated that responding was affected by the delays to reinforcement (delay: F 2,31 = 5.46, p = .009; delay × lever: F 2,31 = 19.5, p < .001), but there were no differences between the groups due to receive AcbC and sham lesions (terms involving lesion intent: maximum F was for session × lever × lesion intent, F 2,62 = 1.844, NS). As expected, delays reduced the rate of responding on the active lever ( F 2,31 = 15.6, p < .001) and increased responding on the inactive lever ( F 2,31 = 8.12, p = .001) preoperatively. AcbC lesions selectively impaired performance of instrumental responding only when there was a response-reinforcer delay. There was no effect of the lesion on responding under the 0 s delay condition, but in the presence of delays, AcbC lesions impaired performance on the active lever (Figure 9 ; Figure 10 ). These conclusions were reached statistically as follows. Figure 9 Postoperative performance under an FR-1 schedule for delayed reinforcement Data plotted to show the effects of delays. All groups discriminated between the active and the inactive lever, and delays retarded acquisition of the active lever response in both groups. Postoperatively, shams' performance was unaltered, as was that of AcbC-lesioned rats in the 0 s delay condition. However, active lever responding was impaired postoperatively in AcbC-lesioned rats in the 10 s and 20 s conditions. (a) Responding of sham-operated control rats, under all three response-reinforcer delay conditions. The vertical black line indicates the time of surgery, between testing sessions 14 and 15. (b) Responding of AcbC-lesioned rats under all delay conditions. The next figure replots these data to show the effect of the lesion more clearly. Figure 10 Effect of AcbC lesions on performance of free-operant responding for delayed reinforcement Data plotted to show the effects of AcbC lesions (same data as in the previous figure). There was a delay-dependent impairment in AcbC-lesioned rats, who were impaired by the lesion only when reinforcement was delayed. (a) With a delay of 0 s, AcbC-lesioned rats performed just as well as shams postoperatively. The vertical black line indicates the time of surgery, between testing sessions 14 and 15. (b) With a 10 s delay, AcbC-lesioned rats were impaired postoperatively compared to shams. (c) With a 20 s delay, the postoperative impairment in AcbC-lesioned rats was larger still, to the extent that their discrimination between active and inactive levers was no longer significant. Subjects' responding on the relevant lever in the last preoperative session (session 14) was used as a covariate to increase the power of the analysis [ 35 ]. As expected, there were no significant differences in the covariates themselves between groups due to receive AcbC or sham surgery (terms involving lesion intent for the active lever: F s < 1, NS; for the inactive lever, lesion intent: F 1,31 = 2.99, p = .094; lesion intent × delay: F < 1, NS). Analysis of the postoperative sessions, using the model lesion 2 × delay 3 × (session 17 × lever 2 × session-14-active-lever-responses cov × S), revealed a near-significant lesion × delay × session × lever interaction ( F 22.4,335.5 = 1.555, = .699, p = .054). Furthermore, analysis of postoperative responding on the active lever, using the model lesion 2 × delay 3 × (session 17 × session-14-active-lever-responses cov × S), revealed a session × delay × lesion interaction ( F 17.3,259.5 = 1.98, = .541, p = .013) and a delay × lesion interaction ( F 2,30 = 3.739, p = .036), indicating that the lesion affected responding on the active lever in a delay-dependent manner. In an identical analysis of responding on the inactive lever (using inactive lever responding on session 14 as the covariate), no terms involving lesion were significant (maximum F : lesion, F 1,30 = 1.96, p = .172), indicating that the lesion did not affect responding on the inactive lever. Postoperatively, response-reinforcer delays continued systematically to decrease responding on the active lever, both in shams (Figure 9a ; delay: F 2,20 = 11.78, p < .001; session × delay: F 12.4,124.1 = 2.36, = .388, p = .008) and in AcbC-lesioned rats (Figure 9b ; delay: F 2,11 = 13.9, p = .001). Shams continued to discriminate between the active and inactive lever at all delays (lever: all groups p ≤ .002; lever × session: all groups p ≤ .003). AcbC-lesioned rats continued to discriminate at 0 s and 10 s (lever: p ≤ .011; lever × session: p ≤ .036), but AcbC-lesioned subjects in the 20 s condition failed to discriminate between the active and inactive levers postoperatively (lever: F 1,4 = 1.866, p = .244; lever × session: F < 1, NS). Lesioned subjects responded as much as shams at 0 s delay, but substantially less than shams at 10 s and 20 s delay (Figure 10 ). Again, analysis was conducted using responding on the relevant lever in session 14 (the last preoperative session) as a covariate. At 0 s, the lesion did not affect responding on the active lever (lesion: F < 1, NS; lesion × session: F 16,144 = 1.34, NS). However, at 10 s, AcbC-lesioned rats responded significantly less than shams on the active lever (lesion: F 1,9 = 7.08, p = .026; lesion × session: F 15.0,135.3 = 3.04, = .94, p < .001). Similarly, at 20 s, AcbC-lesioned rats responded less than shams on the active lever (lesion: F 1,10 = 6.282, p = .031). There were no differences on responding on the inactive lever at any delay ( F s ≤ 1.31, NS). Experienced response-delivery and response-collection delays (Experiment 2) As in Experiment 1, AcbC-lesioned rats experienced the same response-delivery delays as shams when the programmed delay was 10 s, but experienced longer response-delivery delays when the programmed delay was 20 s (Figure 11a ). Similarly, AcbC-lesioned rats experienced the same response-collection delays as shams when the programmed delay was 0 s, slightly but not significantly longer response-collection delays when the programmed delay was 10 s, and significantly longer response-collection delays when the programmed delay was 20 s (Figure 11b ). Figure 11 Programmed and experienced delays to reinforcement following AcbC lesions made after initial training AcbC-lesioned rats experienced slightly longer response-delivery and response-collection delays than shams in the 20 s condition. Lesions were made after initial training; postoperative experienced delays are plotted. (Compare Figure 6 , in which rats had no preoperative experience of the task.) (a) Mean experienced response-delivery delays (one value calculated per subject). When the programmed delay was 0 s, reinforcers were delivered immediately so no data are shown. There were main effects of lesion ( F 1,21 = 9.14) and delay ( F 1,21 = 87.5, p < .001) but no lesion × delay interaction ( F 1,21 = 1.91, NS). When the programmed delay was 10 s, the experienced delays did not quite differ significantly between groups ( F 1,10 = 4.61, p = .057), but when the programmed delay was 20 s, AcbC-lesioned rats experienced longer response-delivery delays ( F 1,11 = 6.29, * p = .029). (b) Mean experienced response-collection delays (one value calculated per subject). There was a lesion × delay interaction ( F 2,31 = 3.85, p = .032), as well as main effects of lesion ( F 1,31 = 11.9, p = .002) and delay ( F 2,31 = 171, p < .001). AcbC-lesioned rats did not experience significantly different delays when the programmed delay was 0 s ( F 1,10 = 1.74, NS) or 10 s ( F 1,10 = 1.49, NS), but experienced significantly longer response-collection delays when the programmed delay was 20 s ( F 1,11 = 13.7, ** p = .003). Relationship between experienced delays and performance (Experiment 2) There was a systematic relationship between the postoperative response rate and the programmed delay of reinforcement, and this was altered in AcbC-lesioned rats. Figure 12a replots the rates of lever-pressing on session 24, the 10 th postoperative session (compare Figure 7 ). An analysis using the model lesion 2 × programmed delay 3 revealed a significant lesion × delay interaction ( F 2,31 = 5.09, p = .012). In this session, there was no significant effect of delays on shams' performance ( F 2,20 = 2.15, p = .143), though there was for AcbC-lesioned rats ( F 2,11 = 9.01, p = .005). There were no significant differences in responding on this session between shams and AcbC-lesioned rats in the 0 s condition ( F 1,10 = 3.10, p = .109) or the 10 s condition ( F < 1, NS), but AcbC-lesioned rats responded less at 20 s delay ( F 1,11 = 6.74, p = .025). Figure 12 Performance as a function of delays to reinforcement in animals trained preoperatively Response-reinforcer delays systematically lowered the rate of free-operant instrumental responding, and this relationship was altered in AcbC-lesioned rats, even allowing for differences in response-collection delays experienced postoperatively. Lesions were made after initial training; postoperative experienced delays and response rates are plotted. (Compare Figure 7 , in which rats had no preoperative experience of the task.) (a) The rate of responding on the active lever in session 24 (the 10 th postoperative session; compare Figure 7 ) is plotted against the programmed response-reinforcer delay. AcbC-lesioned rats responded significantly less than shams in the 20 s delay condition (* p = .025). (b) Responding on the active lever in session 24 (the 10 th postoperative session) plotted against the experienced response-to-reinforcer-collection delays for postoperative sessions up to and including session 24 (vertical error bars: SEM of the square-root-transformed number of responses in session 24; horizontal error bars: SEM of the experienced response-collection delay). The gradients of the two lines differed significantly (# p = .015; see text), indicating that the relationship between experienced delays and responding was altered in AcbC-lesioned rats, compared to sham-operated controls. Since the AcbC group experienced slightly longer response-delivery and response-collection delays than shams when the programmed delay was non-zero (Figure 11 ), as before, the rate of responding in session 24 was analysed as a function of the delays experienced postoperatively. The mean experienced response-collection delay was calculated for postoperative sessions up to and including session 24; the square-root-transformed number of lever presses in session 24 was then analysed using a general linear model of the form lesion 2 × experienced delay cov , with the factor × covariate interaction term included in the model. This confirmed that the lesion affected responding in AcbC-lesioned rats, compared to controls, in a delay-dependent manner, over and above the postoperative differences in experienced delay (Figure 12b ; lesion × experienced delay: F 1,33 = 6.53, p = .015). Locomotor activity and body mass AcbC-lesioned animals were hyperactive compared to sham-operated controls, and gained less mass then shams across the experiments (Figure 13 ), consistent with previous results [ 22 , 29 , 36 ]. Figure 13 Locomotor activity in a novel environment and body mass AcbC-lesioned rats were significantly hyperactive compared to sham-operated controls, and gained less weight, in both Experiments 1 & 2. (a) Locomotor activity in Experiment 1. Analysis using the model lesion 2 × (bin 12 × S) revealed effects of lesion ( F 1,42 = 5.12, * p = .029), reflecting hyperactivity in the AcbC group, with additional effects of bin ( F 5.7,237.9 = 13.3, = .515, p < .001), reflecting habituation, and a lesion × bin interaction ( F 5.7,237.9 = 2.52, = .515, # p = .024). (b) Locomotor activity in Experiment 2. The same patterns were observed (data from five subjects were not recorded due to a mechanical error; lesion: F 1,37 = 9.155, ** p = .004; bin: F 9.3,345.2 = 13.5, = .848, p < .001; lesion × bin: F 9.3,345.2 = 3.18, = .848, ## p = .001). (c) Preoperative and final body mass in both experiments. Preoperatively, masses did not differ between groups (Experiment 1: F < 1, NS; Experiment 2: F 1,42 = 1.008, NS), but in both cases, AcbC-lesioned subjects gained less mass than controls (Experiment 1: lesion × time: F 1,41 = 95.9, ### p < .001; group difference at second time point: F 1,42 = 88.4, *** p < .001; Experiment 2: lesion × time: F 1,42 = 13.53, ## p = .001; group difference at second time point: F 1,42 = 7.37, ** p = .01). Discussion These results establish that the AcbC contributes to learning of actions when the outcome is delayed. Lesions of the AcbC did not impair instrumental learning when the reinforcer was delivered immediately, but substantially impaired learning with delayed reinforcement, indicating that the AcbC 'bridges' action-outcome delays during learning. Lesions made after learning also impaired performance of the instrumental response in a delay-dependent fashion, indicating that the AcbC also contributes to the performance of actions for delayed reinforcement. Finally, the lesions did not impair the perception of relative reward magnitude as assessed by responding on identical concurrent interval schedules for reinforcers of different magnitude, suggesting that the impulsive choice previously exhibited by AcbC-lesioned rats [ 22 ] is attributable to deficits in dealing with delays to reinforcement. Effect of delays on instrumental learning in normal animals Delays have long been known to retard instrumental learning [ 1 , 37 ]. Despite this, normal rats have been shown to acquire free-operant responding with programmed response-reinforcer delays of up to 32 s, or even 64 s if the subjects are pre-exposed to the learning environment [ 1 ]. Delays do reduce the asymptotic level of responding [ 1 ], though the reason for this phenomenon is not clear. It may be that when subjects learn a response with a substantial response-reinforcer delay, they never succeed in representing the instrumental action-outcome contingency fully. Alternatively, they may value the delayed reinforcer slightly less; finally, the delay may also retard the acquisition of a procedural stimulus-response habit and this might account for the decrease in asymptotic responding. It is not presently known to what degree responses acquired with a response-reinforcer delay are governed by declarative processes (the action-outcome contingency plus a representation of the instrumental incentive value of the outcome) or procedural mechanisms (stimulus-response habits), both of which are known to influence instrumental responding [ 38 , 39 ]; it is similarly not known whether the balance of these two controlling mechanisms differs from that governing responses learned without such a delay. Effect of AcbC lesions on instrumental learning and performance with or without delays In the absence of response-reinforcer delays, AcbC-lesioned rats acquired an instrumental response normally, responding even more than sham-operated controls. In contrast, blockade of N -methyl-D-aspartate (NMDA) glutamate receptors in the AcbC has been shown to retard instrumental learning for food under a variable-ratio-2 (VR-2) schedule [in which P (reinforcer | response) ≅ 0.5] [ 40 ], as has inhibition or over-stimulation of cyclic-adenosine-monophosphate-dependent protein kinase (protein kinase A; PKA) within the Acb [ 41 ]. Concurrent blockade of NMDA and DA D1 receptors in the AcbC synergistically prevents learning of a VR-2 schedule [ 42 ]. Once the response has been learned, subsequent performance on this schedule is not impaired by NMDA receptor blockade within the AcbC [ 40 ]. Furthermore, infusion of a PKA inhibitor [ 41 ] or a protein synthesis inhibitor [ 43 ] into the AcbC after instrumental training sessions impairs subsequent performance, implying that PKA activity and protein synthesis in the AcbC contribute to the consolidation of instrumental behaviour. Thus, manipulation of Acb neurotransmission can affect instrumental learning. However, it is also clear that excitotoxic destruction of the AcbC or even the entire Acb does not impair simple instrumental conditioning to any substantial degree. Rats with Acb or AcbC lesions acquire lever-press responses on sequences of random ratio schedules [in which P (reinforcer | response) typically declines from around 1 to 0.05 over training] at near-normal levels [ 44 , 45 ]. In such ratio schedules, where several responses are required to obtain reinforcement, there is no delay between the final response and reinforcement, but there are delays between earlier responses and eventual reinforcement. It is therefore of interest that when differences between AcbC-lesioned rats and shams have been observed, AcbC-lesioned animals have been found to respond somewhat less than shams on such schedules late in training, when the ratio requirement is high [ 44 , 45 ], consistent with our present results. However, lesioned rats are fully sensitive to changes in the instrumental contingency [ 27 , 44 , 45 ]. Our present results indicate that when AcbC-lesioned rats are exposed to a FR-1 schedule for food [ P (reinforcer | response) = 1] in the absence of response-reinforcer delays, they acquire the response at normal rates. In contrast, when a delay was imposed between responding and reinforcement, AcbC-lesioned rats were impaired relative to sham-operated controls, in a systematic and delay-dependent fashion. The observation that learning was not affected at zero delay rules out a number of explanations of this effect. For example, it cannot be that AcbC-lesioned rats are in some way less motivated for the food per se , since they responded normally (in fact, more than shams) when the food was not delayed. Thus although the Acb and its dopaminergic innervation are clearly very important in motivating behaviour e.g. [ 23 , 46 - 48 ], this is not on its own a sufficient explanation for the present results. An explanation in terms of a rate-dependent impairment is also not tenable, since the AcbC-lesioned rats were capable (in the zero-delay condition) of responding at a level greater than they exhibited in the non-zero-delay conditions. Depletion of Acb DA also impairs rats' ability to work on high-effort schedules, where many, or very forceful, responses are required to obtain a given amount of food [ 47 , 48 ]. However, in the present experiments the ratio requirement (one response per reinforcer) and the force required per press were both held constant across delays, so this effect cannot explain the present results. Similarly, although AcbC lesions are known to impair the control over behaviour by Pavlovian conditioned stimuli e.g. [ 23 , 29 , 49 - 52 ], there was no Pavlovian stimulus that was differentially associated with delayed as opposed to immediate reinforcement in this task, so this cannot explain the present results. Our results also indicated that when there were programmed delays to reinforcement, AcbC-lesioned animals experienced longer response-reinforcer collection delays, partly due to their failure to collect the reinforcer as promptly as shams. These additional experienced delays probably retarded learning. However, in addition to this effect, there was a further deficit exhibited by AcbC-lesioned rats: even allowing for the longer response-collection delays that they experienced, their instrumental learning was impaired more by delays than that of sham-operated controls. Deficits in learning with delayed reinforcement may account for some of the variability in the effect of AcbC lesions or local pharmacological manipulations on instrumental learning across different schedules. The fact that pre-exposure to the context improves instrumental learning in normal rats [ 1 ] suggests one possible mechanism by which AcbC lesions might retard learning when delays are present. When a reinforcer arrives, it may be associated either with a preceding response, or with the context. Therefore, in normal animals, pre-exposure to the context may retard the formation of context-reinforcer associations by latent inhibition, or it might serve to retard the formation of associations between irrelevant behaviours and reinforcement. Similarly, non-reinforced exposure to the context forces the subjects to experience a zero-response, zero-reinforcer situation, i.e. P ( outcome | no action ) = 0. When they are then exposed to the instrumental contingency, such that P ( outcome | action ) > 0, this prior experience may enhance their ability to detect the instrumental contingency Δ P = P ( outcome | action ) - P ( outcome | no action ). In one aversive Pavlovian conditioning procedure in which a conditioned stimulus (CS) was paired with electric shock, AcbC lesions have been shown to impair conditioning to discrete CSs, but simultaneously to enhance conditioning to contextual (background) CSs [ 53 ], though not all behavioural paradigms show this effect [ 54 , 55 ]. It is therefore possible that enhanced formation of context-reinforcer associations may explain the retardation of response-reinforcer learning in AcbC-lesioned rats in the presence of delays. The instrumental task used requires animals either to associate their response with the delayed food outcome (an action-outcome association that can be used for goal-directed behaviour), or to strengthen a stimulus-response association (habit) when the reinforcer eventually arrives [ 38 , 39 ]. Both mechanisms require the animal to maintain a representation of their past action so it can be reinforced (as a habit) or associated with food when the food finally arrives. This mnemonic requirement is not obviated even if the animal learns to predict the arrival of food using discriminative stimuli, and uses these stimuli to reinforce its responding (conditioned reinforcement): in either case, since the action precedes reinforcement, some trace of past actions or stimuli must persist to be affected by the eventual delivery of food. A delay-dependent impairment was also seen when AcbC lesions were made after training. This indicates that the AcbC does not only contribute to the learning of a response when there is an action-outcome delay: it also contributes to the performance of a previously-learned response. Again, AcbC-lesioned rats were only impaired when that previously-learned response was for delayed (and not immediate) reinforcement. Of course, learning of an instrumental response depends upon the animal being able to perform that response; preventing an animal from pressing a lever (a performance deficit) would clearly impair its ability to learn an instrumental response on that lever to obtain food. In the present set of experiments, it is clear that AcbC-lesioned rats were just as able to perform the response itself (to press the active lever and to discriminate it physically from the inactive lever) as controls, as shown by their normal performance in the zero-delay condition, so it is not clear whether the delay-dependent impairments in learning and performance can be attributed to the same process. Again, since responding was unaffected in the zero-delay condition, many alternative interpretations (such as a lack of motivation to work for the food) are ruled out. It may be that AcbC-lesioned rats are impaired at representing a declarative instrumental action-outcome contingency when the outcome is delayed, or in forming or executing a procedural stimulus-response habit when the reinforcing event does not follow the response immediately. It may also be that they represent the action-outcome contingency normally but value the food less because it is delayed, and that this affects responding in a free-operant situation even though there is no alternative reinforcer available. Discrimination of reinforcer magnitude in AcbC-lesioned rats Excitotoxic lesions of the whole Acb do not prevent rats from detecting changes in reward value (induced either by altering the concentration of a sucrose reward or by changing the deprivational state of the subject) [ 27 ]. Such lesions also do not impair rats' ability to respond faster when environmental cues predict the availability of larger rewards [ 28 ], and nor does inactivation of the Acb with local anaesthetic or blockade of AMPA glutamate receptors in the Acb [ 56 ]; the effects of intra-Acb NMDA receptor antagonists have varied [ 57 , 58 ]. AcbC-lesioned rats can still discriminate large from small rewards [ 24 , 25 ]. Similarly, DA depletion of the Acb does not affect the ability to discriminate large from small reinforcers [ 59 - 61 ], and systemic DA antagonists do not affect the perceived quantity of food as assessed in a psychophysical procedure [ 62 ]. Our study extends these findings by demonstrating that excitotoxic AcbC lesions do not impair rats' ability to allocate their responses across two schedules in proportion to the experienced reinforcement rate, even when the two schedules are identical except in the magnitude of the reinforcements they provide, thus demonstrating their sensitivity to reinforcer magnitude is quantitatively no worse than shams'. In this experiment, there was substantial undermatching, but this is common [ 33 , 63 ] see also [ 64 , 65 ]; differential cues signalling the two rewards might have improved matching but were not used in the present experiments since it is known that AcbC lesions can themselves affect rats' sensitivity to cues signalling reinforcement [ 23 , 29 , 49 - 52 ]. Given that AcbC-lesioned subjects showed a reduced probability of switching between two identical RI schedules, it may be the case that an enhanced sensitivity to the COD accounts for the better matching exhibited by the AcbC-lesioned rats [ 34 ]. Alternatively, the lesion may have enhanced reinforcer magnitude discrimination or improved the process by which behaviour allocation is matched to environmental contingencies. In summary, the present results suggest that AcbC damage leads to pathological impulsive choice (preferring a small, immediate reinforcer to a large, delayed reinforcer) [ 22 ] not through any relative lack of value of large reinforcers, but through a specific deficit in responding for delayed reinforcement. Contribution of the AcbC to reinforcement learning The term 'reinforcement learning' simply means learning to act on the basis of reinforcement received; it is a term used in artificial intelligence research [ 66 ] that does not specify the mechanism of such learning [ 67 , 68 ]. Our present results indicate that the AcbC is a reinforcement learning structure that is critical for instrumental conditioning when outcomes are delayed, consistent with electrophysiological and functional neuroimaging evidence indicating that the ventral striatum responds to recent past actions [ 10 , 15 ] and to predicted future rewards [ 8 - 15 ], and with computational models suggesting a role for the striatum in predicting future primary reinforcement [ 20 , 21 ]. However, when reward is certain and delivered immediately, the AcbC is not necessary for the acquisition of instrumental responding. The delay-dependent role of the AcbC indicates that it plays a role in allowing actions to be reinforced by bridging action-outcome delays through a representation of past acts or future rewards. Acb lesions have also produced delay-dependent impairments in a delayed-matching-to-position task [ 69 , 70 ]; their effects on the delayed-matching-to-sample paradigm have also been studied, but a more profound and delay-independent deficit was observed, likely due to differences in the specific task used [ 71 ]. Finally, the AcbC is not alone in containing neurons that respond to past actions and future rewards. The dorsal striatum is another such structure [ 10 , 15 , 72 , 73 ]; expression of stimulus-response habits requires the dorsal striatum [ 74 , 75 ], and the rate at which rats learn an arbitrary response that delivers electrical stimulation to the substantia nigra is correlated with the degree of potentiation of synapses made by cortical afferents onto striatal neurons, a potentiation that requires DA receptors [ 76 , 77 ]. The prelimbic area of rat prefrontal cortex is important for the detection of instrumental contingencies and contributes to goal-directed, rather than habitual, action [ 78 , 79 ]. Similarly, the orbitofrontal cortex and basolateral amygdala encode reinforcement information and project to the AcbC, and lesions of these structures can produce impulsive choice see [ 24 , 80 - 82 ]. It is not yet known whether lesions of these structures also impair learning with delayed reinforcement. Conclusions We have demonstrated that excitotoxic lesions of the AcbC do not prevent rats from learning a simple instrumental response when the reinforcing outcome follows their action immediately. However, AcbC lesions impair rats' ability to learn the same instrumental response when the outcome is delayed. The lesions also impair performance of an instrumental response that was learned preoperatively, but again only when response-reinforcer delays were present. These results suggest that the AcbC makes a specific contribution to reinforcement learning and instrumental performance when reinforcing outcomes do not arrive immediately but are delayed. AcbC dysfunction, which is known to promote impulsive choice, appears to cause rats to be temporally short-sighted, learning preferentially about the proximal consequences of their actions and preferring immediate over delayed rewards. Methods Overview of experiments Experiment 1A: Effects of AcbC lesions on acquisition of instrumental responding with delayed reinforcement Fifty naïve rats received excitotoxic lesions of the AcbC ( n = 26) or sham lesions ( n = 24). Two died postoperatively. Subjects were next trained in a task in which they had continuous access to two identical levers; one lever delivered a single food pellet each time it was pressed, and the other lever had no effect. For some rats, the food pellet was delivered immediately after the lever press (0 s condition; n = 8 AcbC-lesioned rats and 8 shams). For others, each pellet was delayed by either 10 s (8 AcbC, 8 sham) or 20 s (8 AcbC, 8 sham). Subjects were trained for 14 sessions. Experiment 1B: Effects of AcbC lesions on the ability to match response distribution to reinforcer magnitude distribution After the same rats had their locomotor activity assessed, they moved on to a task testing their ability to judge differences in the magnitude of two reinforcers. They were again offered two levers, but this time both levers delivered reinforcement on a variable-interval schedule, which provides reinforcement in an intermittent and temporally unpredictable fashion. Reinforcers consisted of either 1 or 4 sucrose pellets. Over sessions, the levers' roles changed so that the ratio of the sizes of the reinforcers available on the two levers was 4:1, 1:1, or 1:4. Subjects' responding was measured to establish their ability to judge the relative differences in reinforcer magnitudes and to allocate their responses according to the matching law [ 31 - 33 ]. Finally, they were killed and perfused for histology. Experiment 2: Effects of AcbC lesions on performance of a previously-learned instrumental response for delayed reinforcement A further 48 naïve rats were trained to acquire an instrumental response as before, with delays to reinforcement of 0 s ( n = 16), 10 s ( n = 16), or 20 s ( n = 16). One rat spontaneously fell ill with a colonic volvulus and was killed. Once the subjects had been trained for 14 sessions, they were allocated to receive either AcbC lesions or sham surgery (0 s: 8 AcbC, 7 sham; 10 s: 8 AcbC, 8 sham; 20 s: 8 AcbC, 8 sham). Sham and AcbC groups were matched for performance preoperatively: within each delay condition, rats were ranked by their rates of responding on the active lever at the end of training, and rats with equivalent levels of performance were randomized to receive sham or AcbC lesion surgery. They were then retested postoperatively on the same task for a further 18 sessions (giving 32 sessions in total), with each rat experiencing the same delay as it had preoperatively. These rats then had their locomotor activity assessed, and were killed and perfused for histology. Subjects and housing conditions Subjects were male Lister hooded rats (Harlan-Olac UK Ltd) housed in a temperature-controlled room (minimum 22°C) under a 12:12 h reversed light-dark cycle (lights off 07:30 to 19:30). Subjects were approximately 15 weeks old on arrival at the laboratory and were given a minimum of a week to acclimatize, with free access to food, before experiments began. Experiments took place between 09:00 and 21:00, with individual subjects being tested at a consistent time of day. Subjects had free access to water. During behavioural testing, they were maintained at 85–90% of their free-feeding mass using a restricted feeding regimen. Feeding occurred in the home cages at the end of the experimental day. All procedures were subject to UK Home Office approval (Project Licences PPL 80/1324 and 80/1767) under the Animals (Scientific Procedures) Act 1986. Excitotoxic lesions of the nucleus accumbens core Subjects were anaesthetized with Avertin (2% w/v 2,2,2-tribromoethanol, 1% w/v 2-methylbutan-2-ol, and 8% v/v ethanol in phosphate-buffered saline, sterilized by filtration, 10 ml/kg i.p.) and placed in a Kopf or Stoelting stereotaxic frame (David Kopf Instruments, Tujunga, California, USA; Stoelting Co., Wood Dale, Illinois, USA) fitted with atraumatic ear bars. The skull was exposed and a dental drill was used to remove the bone directly above the injection and cannulation sites. The dura mater was broken with the tip of a hypodermic needle, avoiding damage to underlying venous sinuses. Excitotoxic lesions of the AcbC were made by injecting 0.5 μl of 0.09 M quinolinic acid (Sigma, UK) through a glass micropipette at coordinates 1.2 mm anterior to bregma, ± 1.8 mm from the midline, and 7.1 mm below the skull surface at bregma; the incisor bar was 3.3 mm below the interaural line [ 83 ]. The toxin had been dissolved in 0.1 M phosphate buffer (composition 0.07 M Na 2 HPO 4 , 0.028 M NaH 2 PO 4 in double-distilled water, sterilized by filtration) and adjusted with NaOH to a final pH of 7.2–7.4. Toxin was injected over 3 min and the micropipette was left in place for 2 min following injections. Sham lesions were made in the same manner except that vehicle was infused. At the end of the operation, animals were given 15 ml/kg of sterile 5% w/v glucose, 0.9% w/v sodium chloride intraperitoneally. They were given a week to recover, with free access to food, and were handled regularly. Any instances of postoperative constipation were treated with liquid paraffin orally and rectally. At the end of this period, food restriction commenced or was resumed. Behavioural apparatus Behavioural testing was conducted in one of two types of operant chamber of identical configuration (from Med Associates Inc, Georgia, Vermont, USA, or Paul Fray Ltd, Cambridge, UK). Each chamber was fitted with a 2.8 W overhead house light and two retractable levers on either side of an alcove fitted with an infrared photodiode to detect head entry. Sucrose pellets (45 mg, Rodent Diet Formula P, Noyes, Lancaster, New Hampshire, USA) could be delivered into the alcove. The chambers were enclosed within sound-attenuating boxes fitted with fans to provide air circulation. The apparatus was controlled by software written by RNC in C++ [ 84 ] using the Whisker control system [ 85 ]. Instrumental conditioning with delayed reinforcement A variety of free-operant schedules may be used to assess instrumental acquisition with delayed reinforcement [ 1 ]. We used the simplest possible free-operant schedule: each response scheduled a reinforcer after the programmed delay (Figure 1 ). In such a schedule, if the subject responds during the delay, the experienced response-reinforcer delay will not match the programmed delay (as the second response is temporally close to the first reinforcer). However, this schedule has the advantage that the response-reinforcer contingency is constant (every response does in fact cause the delivery of reinforcement) and the reinforcement rate is not constrained [ 1 ]. So that responding could be attributed to the instrumental response-reinforcer contingency, rather than the effects of general activity or reinforcement itself, responding on the active lever was compared to responding on a control lever that had no programmed consequence. Different groups of lesioned and sham-operated subjects were trained using different delays; the delay was consistent for every subject. Delays of 0, 10, and 20 s were used. Alternative free-operant schedules for this purpose exist, such as one in which the first response sets up reinforcement, and a subsequent response made before the reinforcer is delivered postpones reinforcement, in order to keep the delay between the last response and the reinforcer constant (known as a tandem fixed-ratio-1 differential-reinforcement-of-other-behaviour or FR-1-DRO schedule). However, the tandem FR-1-DRO schedule constrains the maximum rate of reinforcement, which also decreases as the delay being used increases. Furthermore, it does not hold constant the probability of reinforcement given a response, and it introduces two opposing contingencies: some responses make reinforcement more likely, while others (those during the delay) make it less likely [ 1 ]. Therefore, we did not use this schedule. Similarly, the acquisition of instrumental responding with delayed reinforcement may be assessed with discrete-trial tasks. For example, two levers could be presented in trials occurring at fixed intervals, the levers could be retracted when a response had been made, and responding on one lever could be reinforced after a delay, taking care to avoid a differential Pavlovian contingency between presentation or retraction of one lever and reinforcement, since responding might then be due to Pavlovian conditioning autoshaping; [ 86 , 87 ] rather than the instrumental contingency. However, this discrete-trial schedule would also divide up the session explicitly into response-food delays and food-response (intertrial) times, a process that might aid learning and/or be affected by the lesion. Furthermore, there is prior evidence that AcbC lesions impair rats' ability to choose a delayed reward over an immediate reward in the discrete-trial situation [ 22 ]. Therefore, to address the more general question of whether the AcbC is required to acquire instrumental responding with delayed reinforcement, we chose instead to use a free-operant schedule; this seemed to us to mimic best the real-life problem of relating actions to their outcomes with no explicit demarcation of when a response had been made or when a response was permissible. Immediately after subjects were placed in the operant chamber, the sessions began. The houselight was illuminated, and remained on for each 30-min session. Two levers were extended into the chamber. All lever responses were first 'debounced' to 10 ms (i.e. if a response occurred within 10 ms of a previous valid response it was attributed to mechanical bounce and ignored). Other than this, all lever presses and nosepokes into the food alcove were recorded. Responding on the left (active) lever caused a single pellet to be delivered following a delay, under a fixed-ratio-1 (FR-1) schedule (Figure 1 ). To attribute acquisition of a lever-press response to the instrumental contingency, it is also necessary to control for the effects of reinforcer delivery itself [ 1 ]; therefore, responding on the active lever was compared to responding on the right (inactive) lever, which had no programmed consequence. To minimize any potential contribution of conditioned reinforcement to the task, no explicit signals were associated with pellet delivery other than the noise of the pellet dispenser apparatus. Locomotor activity in a novel environment Since general activity levels might influence instrumental responding, locomotor activity was also measured, using wire mesh cages, 25 (W) × 40 (D) × 18 (H) cm, equipped with two horizontal photocell beams situated 1 cm from the floor that enabled movements along the long axis of the cage to be registered. Subjects were placed in these cages, which were initially unfamiliar to them, and their activity was recorded for 2 h. All animals were tested in the food-deprived state. Locomotor hyperactivity and reduced weight gain have previously been part of the phenotype of AcbC-lesioned rats, though without alterations in the consumption of the reinforcer used in the present experiments [ 22 , 29 , 36 ]. Matching of response distribution to reinforcer magnitude distribution on a concurrent schedule Subjects were trained in 30-min sessions to respond on both levers separately under interval schedules of reinforcement. The two levers were designated A and B; these were counterbalanced left/right (thus, for half the subjects in each group, lever A was the lever reinforced previously in the delay task; for the other half, it was the lever previously unreinforced). As before, responses were debounced to 10 ms. Training and testing proceeded according to Table 1 . Random-interval- x -second (RI- x ) schedules were implemented by having a clock tick once a second; each tick set up reinforcement with a probability p = 1/ x . Once reinforcement had been set up for a schedule, the next response caused reinforcement to be delivered. Multiple pellets were delivered 0.5 s apart. For concurrent RI schedules, a 2 s changeover delay (COD) was imposed to discourage frequent switching between schedules [ 32 - 34 , 88 ]. The COD was implemented as follows: if a subject pressed lever B, it could only be reinforced if more than 2 s had elapsed since it last pressed lever A (and vice versa). The RI schedules could still set up reinforcement during the COD, but the subject could not earn that reinforcement until the COD had elapsed. Histology Rats were deeply anaesthetized with pentobarbitone sodium (200 mg/ml, minimum of 1.5 ml i.p.) and perfused transcardially with 0.01 M phosphate-buffered saline (PBS) followed by 4% paraformaldehyde in PBS. Their brains were removed and postfixed in paraformaldehyde before being dehydrated in 20% sucrose for cryoprotection. The brains were sectioned coronally at 60 μm thickness on a freezing microtome and every third section mounted on chromium potassium sulphate/gelatin-coated glass microscope slides and allowed to dry. Sections were passed through a series of ethanol solutions of descending concentration (3 minutes in each of 100%, 95%, and 70% v/v ethanol in water) and stained for ~5 min with cresyl violet. The stain comprises 0.05% w/v aqueous cresyl violet (Raymond A. Lamb Ltd, Eastbourne, UK), 2 mM acetic acid, and 5 mM formic acid in water. Following staining, sections were rinsed in water and 70% ethanol before being differentiated in 95% ethanol. Finally, they were dehydrated and delipidated in 100% ethanol and Histoclear (National Diagnostics, UK) before being cover-slipped using DePeX mounting medium (BDH, UK) and allowed to dry. The sections were used to verify cannula and lesion placement and assess the extent of lesion-induced neuronal loss. Lesions were detectable as the absence of visible neurons (cell bodies of the order of 100 μm in diameter with a characteristic shape and appearance), often associated with a degree of tissue collapse (sometimes with consequent ventricular expansion when the lesion was adjacent to a ventricle) and gliosis (visible as the presence of smaller, densely-staining cells). Data analysis Data collected by the chamber control programs were imported into a relational database (Microsoft Access 97) for case selection and analysed with SPSS 11. Figures were created with SigmaPlot 2001/v7 and Adobe Illustrator 8. All graphs show group means and error bars are ± 1 standard error of the mean (SEM) unless otherwise stated. Count data (lever presses and locomotor activity counts), for which variance increases with the mean, were subjected to a square-root transformation prior to any analysis [ 35 ]. Homogeneity of variance was verified using Levene's test [ 89 ]. General linear models are described as dependent variable = A 2 × B cov × ( C 5 × D cov × S ) where A is a between-subjects factor with two levels, B is a between-subjects covariate, C is a within-subjects factor with five levels, and D is a within-subjects covariate; S denotes subjects in designs involving within-subjects factors [ 90 ]. For repeated measures analyses, Mauchly's test of sphericity of the covariance matrix was applied [ 91 ] and the degrees of freedom corrected to more conservative values using the Huynh-Feldt epsilon for any terms involving factors in which the sphericity assumption was violated [ 92 ]. List of abbreviations used , Huynh-Feldt epsilon Acb, nucleus accumbens AcbC, nucleus accumbens core AcbSh, nucleus accumbens shell AMPA, α-amino-3-hydroxy-5-methyl-4-isoxazolpropionate ANCOVA, analysis of covariance ANOVA, analysis of variance COD, changeover delay DA, dopamine DRO, differential reinforcement of other behaviour FR, fixed ratio i.p., intraperitoneal h, hour min, minute NMDA, N -methyl-D-aspartate P (A), probability of event A occurring P (A | B), probability of A occurring, given that B has occurred PBS, phosphate-buffered saline PKA, protein kinase A (cyclic-adenosine-monophosphate-dependent protein kinase) RI, random interval SEM, standard error of the mean VR, variable ratio v/v, volume per unit volume w/v, weight per unit volume Authors' contributions RNC conceived and designed the studies, supervised THCC, wrote the software, and drafted the manuscript. THCC participated in the design of the studies and tested the animals. The work contributed to THCC's MPhil thesis. Both authors performed surgery, processed histological material, analysed the results, and read and approved the final manuscript.

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544877

Effects of home visits by home nurses to elderly people with health problems: design of a randomised clinical trial in the Netherlands [ISRCTN92017183]

Background Preventive home visits to elderly people by public health nurses aim to maintain or improve the functional status of elderly and reduce the use of institutional care services. A number of trials that investigated the effects of home visits show positive results, but others do not. The outcomes can depend on differences in characteristics of the intervention programme, but also on the selection of the target population. A risk group approach seems promising, but further evidence is needed. We decided to carry out a study to investigate the effects in a population of elderly with (perceived) poor health rather than the general population. Also, we test whether nurses who are qualified at a lower professional level (home nurses instead of public health nurses) are able to obtain convincing effects. The results of this study will contribute to the discussion on effective public health strategies for the aged. Methods/design The study is carried out as a parallel group randomised trial. To screen eligible participants, we sent a postal questionnaire to 4901 elderly people (70–84 years) living at home in a town in the south of the Netherlands. After applying inclusion criteria (e.g., self-reported poor health status) and exclusion criteria (e.g., those who already receive home nursing care), we selected 330 participants. They entered the randomisation procedure; 160 were allocated to the intervention group and 170 to the control group. The intervention consists of (at least) 8 systematic home visits over an 18 months period. Experienced home nurses from the local home care organisation carry out the visits. The control group receives usual care. Effects on health status are measured by means of postal questionnaires after 12 months, 18 months (the end of the intervention period) and after 24 months (the end of 6-months follow-up), and face-to-face interviews after 18 months. Data on mortality and service use are continuously registered during 24 months. A cost-benefit analysis is included. The design and setting of the study, the selection of eligible participants and the study interventions are described in this article. Other included items are: the primary and secondary outcome measures, the statistical analysis and the economic evaluation.

Background The number of elderly people is increasing. Due to the ageing population, more demands are made on health care services [ 1 ]. In the last two decades, preventive programmes have been developed aiming at reducing health care cost and improving the independent functioning of elderly people. One of such programmes is home visitation by public health nurses of elderly people living in the community. This aims to maintain or improve the functional abilities and well-being of elderly people and reduce the use of institutional care services. Such programmes for elderly people are part of national policy in several countries, including the UK, Denmark and Australia. However, the results of trials on the effects of home visits have been inconsistent [ 2 ]. Investigators are still in search of the most effective strategy. In the past years 3 reviews were published on the effects of preventive home visits to elderly people living in the community [ 2 - 4 ]. These used different methodological approaches. Apart from a number of similar trials, each review also included a series of different trials, depending on the inclusion criteria and the date of publication. Van Haastregt et al [ 2 ] reviewed 15 studies and concluded that no clear evidence exists for the effectiveness of the visits: the observed effects are considered to be fairly modest and inconsistent. Nine trials reported at least one (significant) favourable effect and 6 trials reported no effects. In most of the studies the intervention was aimed at the general population aged 65 years or over, without any selection. The other 2 reviews [ 3 , 4 ] included a meta-analysis of the data and were more positive about the effects of the home visits. Stuck et al [ 4 ] indicated that home visits can reduce the risk of functional decline and nursing home admission, provided that the interventions are based on a multi-dimensional geriatric assessment and include multiple follow-up visits. Home visiting programmes improved functional status more in people with the lowest mortality risk (younger population, < 80 years). Elkan et al [ 3 ] reported a favourable effect on mortality and nursing home admissions among members of the general population and frail older people who are at risk of adverse outcomes. However, they did not find improvement in functional status. One can argue about the differences in the approach of each review, but in general the results of the home visiting studies are heterogeneous with respect to the different outcome measures. Many factors can play a role in the effectiveness of the interventions, including the target population, characteristics of the intervention, the persons carrying out the visits and the compliance to the given advice. Research in the Netherlands showed that preventive home visits do not seem to be useful for the general population of elderly people [ 5 ]. In that trial, experienced public health nurses visited the intervention group (n = 300) at least four times a year over a period of 3 years. The control group (n = 300) received usual care. After 3 years, no or hardly any effects were demonstrated on the health and service use of the total group of visited elderly (see table 1 ). However, a subgroup analysis indicated that the visits seemed to be effective for elderly with a poor (perceived) health status. Visited persons with poor health at baseline scored considerably better on several health measures (e.g., functional status) compared to similar persons in the control group. Mortality rates after three years were lower (24% versus 40%) and substantial effects were found for referrals to outpatient clinics (61% versus 79%) and also for hospital admissions, especially re-admissions. In the intervention subgroup 47% were admitted at least once to the hospital, with a total of 1,134 days; in the control subgroup these figures were 74% and 2,043 days (table 1 ). These effects emerged already during the first year of the intervention period [ 6 ]. The probable usefulness of home visits for a high risk group was confirmed in five controlled studies [ 7 - 11 ]. However, the results of three other trials did not support this assumption [ 12 - 14 ]. Although home visits for a restricted population seem a promising approach, further evidence is needed. The findings of the earlier Dutch subgroup analysis were based on a relatively small number of subjects (53 in the control and 57 persons in the intervention group). Therefore, we decided to carry out a new trial in which the risk group approach is tested in a larger population of those with (perceived) poor health. At the same time, we appointed nurses who are qualified at a lower professional level (enrolled home nurses instead of public health nurses) to carry out the visits. An experienced public health nurse will supervise them. This study will investigate the effects of systematic home visits by home nurses to elderly people with (perceived) health problems in terms of their health status, the use of care services and the cost-effectiveness. We expect that the visits will improve the functional abilities, perceived health and quality of life of the participants. We also hypothesize that they will reduce specialist care, institutionalisation, especially hospital (re-) admissions, and total health care expenditures. Evidence regarding the usefulness of the proposed risk group approach is needed to decide on the future implementation of the visits. This article presents the design of this new trial. Methods/design Study design and setting The study is carried out as a parallel group randomised trial. It is conducted in co-operation with a large home care organisation in the south of the Netherlands (Sittard and surroundings). The addresses we used to screen eligible persons for the study were drawn from the population register of the municipality. After the screening procedure we randomised 330 elderly. Effects of the intervention are measured by means of postal questionnaires after 12 months, 18 months (at the end of the intervention period) and after 24 months (at the end of a 6-months follow-up period) and by face-to-face interviews after 18 months. Mortality and data on the use of care services are continuously registered over the 24-months research period. A cost-benefit analysis is also included. The design of the study is shown in figure 1 . The design is, unless otherwise mentioned, carried out according to plan. The study has obtained the approval by the Medical Ethical Committee of Maastricht University/Academic Hospital Maastricht. Identification of eligible participants We sent a postal questionnaire to 4901 elderly people between the age of 70 and 84 years who were still living at home. These lived in 14 districts in the research area. We included districts with close proximity to the centre of town where the home care organisation is situated. In this way we limited the travelling time of the nurses to carry out the visits. Districts with large industrial areas were excluded. Reminders were sent after 2–3 weeks to 45% of the elderly. The response rate was 76% after about 6 weeks. The response rates per district fluctuated between 65% and 81%. The average time to fill out the questionnaire was about 30 minutes. The elderly could do this by themselves or, if they needed help, with the assistance of family, friends or volunteers. A list of names and addresses of volunteers was added to the questionnaire. Even if persons did not want to participate in the study, we kindly requested them to fill out the questionnaire and return it to us. A postage free envelope was included. The questionnaire was used as a screening instrument and also served as a baseline measurement for the participants of the trial. Among the respondents (n = 3,689, see figure 1 ), we found 872 persons who reported their health status as poor (on a scale ranging from 1–10 points, report marks 1–5 are considered poor, 6–7 fairly good, and 8–10 good). Our previous home visitation study indicated positive effects for this subgroup. Five persons did not sign the informed consent form and 273 persons with a poor health status did not want to participate in the study. Of the remaining 594 persons, we excluded those who already received home nursing care at baseline, in order to avoid contamination of (other) nursing care. Referral to nursing services after the start of the intervention period has no consequences for the scheduled home visits in the intervention group. It is regarded as a possible effect of the intervention and it is registered as outcome in terms of service use. Persons on a waiting list for admission to nursing homes or homes for the elderly were also excluded. The local independent committee dealing with applications for the use of care services already granted them this service. It is likely that most of them already receive regular supervision of professional caregivers. Six persons were excluded on the advice of their GPs. They were severely or terminally ill and would probably die within 6 months. On the basis of these exclusion criteria, a total of 102 persons were excluded. After applying the in- and exclusion criteria, 492 persons were eligible to take part in the study. However, we excluded 162 more persons for the following reasons: their GP did not want to co-operate with the study (n = 139), respondents had too many missing values on the functional status scale (n = 11), the health insurance company was unknown (n = 1) or it was uncertain whether the health insurance company would be willing to co-operate (n = 11). The health insurance companies of 96% of the finally selected participants had already given consent to provide us with data on health service use. As we selected persons whose GP was willing to co-operate, relevant health care data from the GP practices are available for all participants. A flow diagram of the selection of participants is shown in figure 1 . Finally, 330 persons entered the randomisation procedure. In consideration of the available working hours of the nurses, the maximum number of participants to receive home visits was 160. The control group was hence set at 170. Sample size consideration We calculated the sample size from the data of our previous home visitation study in the Netherlands [ 5 ]. Participants were categorized on the primary outcome measure self-rated health, perceiving their health status as (a) better or the same compared to the start of the study, or (b) worse or deceased. We expect to demonstrate a difference of 20% between the study groups (65% score (a) in group I versus 45% in group II). Based on a 0.9 power to detect a significant difference (α = 0.05, one-sided), 104 participants are required for both study groups. Accounting for a loss to follow up of 30%, we planned to enrol 150 participants per group. This number is also large enough (again extrapolated from our own data) to detect differences in specialist care and institutionalisation (e.g., to detect a difference in mean hospital days of 10 days over a 1.5 year period). Based on data of the selection criteria we estimated that about 10% of the screened population was eligible for the study (including informed consent). Therefore, we needed to mail a minimum of 3,500 questionnaires to persons aged 70–84 years living in the community. To account for unforeseen circumstances, we decided to send out about 5,000 questionnaires. After applying the inclusion and exclusion criteria, and taking into account the GPs' willingness to co-operate with the study, there were sufficient participants eligible for the study to raise the selected number to 330. This slightly increased the power of the study. Randomisation The baseline measurements included questions on relevant prognostic factors related to the health status and service use. Before randomisation we divided the 330 participants into two groups: couples (n = 46) and those for whom this did not apply (n = 284). In this way we made sure that eligible persons who lived together, were always allocated to the same study group (in order to avoid contamination of the intervention). The 23 couples were divided into 3 strata on the basis of their (added) score on functional status (0–4, 5–7 or more than 7 out of 18 activities that cannot be carried out independently). The other 284 participants were stratified into 8 strata based on 3 prognostic factors – two health-variables and one service use-variable: 1. functional status (0–2 or more than 2 activities that the elderly cannot carry out independently) 2. changes in health during the 3 months prior to completion of the questionnaire (same/better or worse) 3. contact with a medical specialist in the 3 months prior to completion of the questionnaire (contact yes or no). The participants in each of the 8 strata were then randomised into either a control or intervention group using a computer generated randomisation list with a block length of 4 [ 15 ]. Randomly, we allocated 160 persons to the intervention group and 170 persons to the control group. Table 2 shows the baseline characteristics of the intervention and control group. The study groups are well matched; there were hardly any differences between the groups at the start of the study. The participants in the intervention group were assigned to one of the three home nurses. This depended on the location of their GP practice, as each nurse was assigned to a number of GP practices. We assumed that this would facilitate the co-operation with the GPs. Each nurse was responsible for 52–56 elderly during the intervention period. Study interventions Our previous study showed that positive effects of the visits for people with a poor health status emerged already within 1.5 years. In the new trial the intervention period is restricted to this period. At the same time we increased the frequency of the visits. This enables the nurses to intervene more promptly on identified problems and risks, and to establish a position of trust in a shorter time period. Experienced home nurses therefore visit the intervention group at least 8 times over an 18 months period. If necessary, extra visits can be made. The duration of the visits can last between 60 and 90 minutes. Participants in the control group receive usual care. As before, they can use or apply for all available services in the area. Three nurses work half time for the trial. An experienced public health nurse supervises the visits on a weekly basis. All 3 home nurses are recruited from the co-operating home care organisation. Home nurses, as well as public health nurses, are well trained to conduct home visits. They are embedded in community care organisations that traditionally have preventive tasks. The home nurses are not part of a multidisciplinary team, but advice can be obtained from in-home specialists within the home care organisation, e.g., a dietician, a diabetes specialist and an occupational therapist. A nurse geriatric specialist from the local hospital can also be consulted, if necessary. At regular intervals, once every 6–8 weeks during the intervention period, he also advises the nurses on important geriatric issues. Home visit protocol The home visits can be described as "systematic home visits to elderly people with health problems carried out by a home nurse". The 3 most important elements of the visits are (1) to detect problems or risks, (2) to give advice and (3) to refer to other professional or community services. This brief description is applicable to all home visiting studies that have been carried out so far. However, there are large differences in the protocols that have been used in earlier studies, ranging from an interview to collect information on social and health conditions [ 16 ] to a 'multidimensional geriatric assessment' in which medical, functional, psychosocial, and environmental evaluation of the problems and resources are assessed [ 12 , 17 ]. Earlier studies did not show any clear relation between the structure of the visits and the effects. So far, the active components of the intervention are not known yet, but a number of elements seems to be of importance for the contents of the visits. We tried as much as possible to include these elements into the protocol: e.g., face-to-face assessment, good communication between the nurse and the elderly including an empathic attitude by the nurse, an individual plan, a client-centred approach, good compliance with the given advice and multiple visits [ 4 , 18 ]. The visits are carried out in a systematic way according to a nursing model [ 19 ] that distinguishes 4 steps: diagnosis, planning of activities, carrying out the activities and evaluation. Diagnosis Our starting-point is a client-centred approach. The elderly can indicate which problems they experience and which needs they have. The EasyCare Questionnaire [ 20 , 21 ], an elderly assessment system, is used to detect further problems. Also, additional checklists are used on a variety of topics: e.g., vision, hearing and use of medication. A number of instruments are used for further diagnostic assessment: the get-up-and-go test [ 22 ], the Geriatric Depression Scale [ 23 ] and the Mini Mental State Examination [ 24 ]. During the visits no physical examination takes place, as the home nurses are not qualified to do so. If necessary, the elderly are referred to their GPs. Planning of activities An individual plan for each elderly person is set up. The activities are planned in agreement with the elderly, as this will improve compliance. We only included elderly with a poor (perceived) health, hence a broad range of problems can come forward, including physical, mental as well as social problems. Guidelines on a number of geriatric topics are used for advice and referral regarding problems and risks that are identified. A Handbook of Nursing Diagnosis [ 25 ] is also used to set up goals and interventions. A maximum of three problems (and 2 interventions per problem) is being dealt with at one visit. Among the planned activities are referrals to professional or community services, and advice or information is given regarding, e.g., nutrition, social and physical activities and home aids. Carrying out the activities The elderly are primarily themselves responsible to carry out the planned activities. The home nurse only supports the elderly. In order to improve compliance, the nurses contact the elderly by telephone 1 to 4 weeks after each visit, depending on the type of advice. They ask whether the advice has been followed, and if not, what the impediments are and if further assistance is necessary. The participants are offered consultation with the nurses by telephone each morning between 9.00 – 9.30 hours. Evaluation The evaluation of each home visit takes place at the next visit. The cycle is then repeated and new or old, but not solved, problems can be dealt with. In the 3-months period before the start of the visits, the home nurses were actively involved in the development of the visiting protocol. They also received relevant training in communication skills and using assessment tools. They took courses on several subjects, e.g., relevant geriatric health topics, behaviour change and the usage of the Handbook of Nursing Diagnosis [ 25 ]. Several pilot visits were carried out, in which different aspects of the protocol were trained, e.g., using assessment tools and measuring instruments. Communication between the nurses and the GPs is according to the 'normal' communication lines between nurses of the home care organisations and the GPs. Before the start of the study all GPs received a list of eligible participants registered at their practice, to screen very ill persons. After randomisation a definite list of participants was sent to them, but no reference was made to which treatment group they belong. The allocation of the participants to the 2 groups was disclosed after conclusion of the first 3 home visits. The GPs then received an overview of all treated problems for each participant in the intervention group, including the accompanying recommendations and the results of the interventions. The GPs were asked for their comments or suggestions and in this way they could become involved, if they wanted to. A similar overview will be sent to them for visits 4–6 and 7–8. Process evaluation All elements of the intervention are monitored as part of a process evaluation. This includes the registration of topics discussed at each visit, treated problems, advice given and referral to other services. The evaluation of each visit is registered at each next visit and includes the compliance with the given advice. Reasons for non-compliance are noted. The nurses' experiences with the visiting protocol, the role of the supervising public health nurse and the patient's experiences with the home visits will be assessed at the end of the intervention period by means of face-to-face-interviews. Other aspects of the intervention process assessed are: the time spent on the visits, including the travelling and preparation time and the time spent on telephone contacts. Elements of the telephone conversation after each visit, most importantly whether the elderly complied with the given advice, are registered. Detailed analyses of the intervention process and outcome data might help to identify which programme characteristics are related to possible favourable effects of the visits and may result in the development of more effective interventions. It might also provide additional information for the possible implementation of the visits in daily practice. Outcome measures The primary health related outcome measures are: self-rated health, functional status, quality of life and changes in self-reported problems. In addition, a variety of other health measures (secondary outcome measures) will be assessed. Information will be obtained, among other things, on health complaints, medication use, and loneliness and mental health. The municipality will supply mortality data (secondary outcome measure) over the entire research period. The use of services relates to the frequency and duration of care from the following services: domestic and community nursing care, GP, physiotherapy, day care in institutional care settings, hospital outpatient clinics, hospital, nursing home, home for the elderly, use of aids and modifications to the home. The primary outcomes for service use are specialist medical care and hospital (re-) admission. The health insurance companies will supply data on the use of services over the two-year research period. Additional data not covered by the health insurance companies, will be supplied by GPs, the hospital, the home care organisations, etc. Table 3 shows an overview of the outcome measures, their operationalisation and at which time points the measures are carried out. Statistical analyses The main analyses will be conducted according to the intention-to-treat principle. Analysis of primary and secondary endpoints will be performed using relevant significance tests (e.g., chi-square, t-test or analysis of variance). Regression techniques will be used, if necessary, to estimate the effects for the various outcome measures, adjusting for small differences between the groups at the start of the study. In addition, we will conduct per-protocol analyses; these are restricted to those participants who complied fully with the intervention protocol and outcome measurements. Preplanned subgroup analysis will be performed for the following subgroups: living alone/together; health deterioration over the previous 3 months; functional status and locus of control. Differences in approaches between the nurses will be investigated. Economic evaluation A cost-effectiveness analysis will be carried out in which we consider costs from a societal perspective. The economic evaluation will measure and evaluate the 'real' costs. In this study we will include direct health care costs, i.e. costs made for the home visit programme and health care costs made by the participants. Costs of the intervention programme consist of costs for the screening procedure, salaries of the nurses, travel expenses, costs of training sessions for the nurses, etc. Health care costs include costs of inpatient and outpatient treatment, consultation by GPs and other medical practising specialists, physiotherapy, medication, professional home care, nursing home, meals on wheels, aids and appliances, etc. In order to estimate the costs, the quantity of each resource will be multiplied by its assigned unit cost of price. Direct non health care costs (e.g., the travel costs made by participants) are not included. These should preferably be gathered prospectively by means of a cost-diary [ 26 ]. We considered this too burdensome for the participants. Indirect health care costs (costs which are made during extra gained years of life) and indirect non health care costs (the value of production lost to society due to illness-related absence from work and days of inactivity) are often also included in an economic evaluation. We decided however not to include those costs, because of their limited relevance in a population of retired elderly people. Time plan for this study The screening procedure was carried out in the fall of 2002. In January 2003 we sent a letter to the elderly notifying them that they were selected to participate in the study and whether they would receive home visits or not. In February the home visits started. They are carried out according to plan and will end in September 2004. The first effect evaluation, 12 months after the start of the intervention period, has taken place: 302 questionnaires were sent out in March 2004. The response rate was 95%. Since the beginning of the intervention period, a total of 24 participants died and 4 persons withdrew from the study. Three more effect evaluations will take place: two evaluations after the intervention period in October 2004 (a postal questionnaire and a face-to-face interview) and one after the 6 months follow-up in March 2005 (postal questionnaire). Discussion The use of postal questionnaires turned out to be a good and inexpensive method to screen elderly people – there were more than sufficient eligible persons to participate in the research project. The response rate was high and less than one percent of the questionnaires were omitted due to too many missing values. For most of the variables, the percentage of missing values varied between 0 and 2 per cent. Media coverage shortly before sending out the questionnaires and accompanying letters from the municipality and the university may have contributed to the high response rate. It is not certain whether the results are comparable to other (larger) towns in the Netherlands. The response rate of the postal questionnaires used for the first effect evaluation (12 months after the start of the study) was 95%. Nearly all included elderly seemed to be motivated to participate. We selected elderly with a poor perceived health status, because we expected the home visits to be more beneficial for this group rather than for those who are still in good health [ 5 ]. Results from the data analysis of the first postal questionnaire (the screening instrument and the baseline measurement) showed that the eligible persons indeed scored worse on most health related variables, including functional status, mental health and social functioning [ 27 ]. We considered including a third group of elderly with poor health status to receive home visits from voluntary workers. This was, however, not feasible, mainly because the number of participants with a participating GP was too low. The frequency of the visits and the level of professionalism, nurses versus voluntary aids (usually without any professional qualifications), could be a topic of study in another trial depending on the outcome of this study. Competing interests The author(s) declare that they have no competing interests. Authors' contributions Erik van Rossum and Paul Knipschild were responsible for the research question. They contributed to drafting of the study protocol, as did Ruud Kempen. Ans Nicolaides-Bouman made the first draft of this paper. The other 3 authors commented on it and approved the final version. Pre-publication history The pre-publication history for this paper can be accessed here:

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Effects of recombinant adenovirus-mediated expression of IL-2 and IL-12 in human B lymphoma cells on co-cultured PBMC

Background Modulation of the immune system by genetically modified lymphoma cell vaccines is of potential therapeutic value in the treatment of B cell lymphoma. However, the anti-tumor effect of any single immunogene transfer has so far been limited. Combination treatment of recombinant IL-2 and IL-12 has been reported to be synergistic for inducing anti-tumor responses in solid tumors but the potential of IL-2/IL-12 gene modified B cell lymphoma cells has not been explored yet. Methods Using three different human B cell lymphoma cell lines and primary samples from patients with B cell neoplasms, expression levels of the coxsackie B-adenovirus receptor (CAR) and alpha (v) integrins were analyzed by fluorescence-activated cell sorter (FACS). Adenoviral transduction efficiencies were determined by GFP expression analysis and IL-2 and IL-12 cytokine production was quantified by enzyme-linked immunosorbent (ELISA) assays. Proliferative activities of peripheral blood mononuclear cells (PBMC) stimulated with either cytokine derived from supernatants of transduced lymphoma cells were measured by cell proliferation (MTT) assays. An EuTDA cytotoxicity assay was used to compare cytotoxic activities of IL-2 and/or IL-12 stimulated PBMC against unmodified lymphoma cells. Results We found that B cell lymphoma cell lines could be transduced with much higher efficiency than primary tumor samples, which appeared to correlate with the expression of CAR. Adenoviral-expressed IL-2 and IL-12 similarly led to dose-dependent increases in proliferation rates of PBMC obtained from healthy donors. IL-2 and/or IL-12 transduced lymphoma cells were co-cultured with PBMC, which were assayed for their cytolytic activity against unmodified lymphoma cells. We found that IL-2 stimulated PBMC elicited a significant anti-tumor effect but not the combined effect of IL-2/IL-12 or IL-12 alone. Conclusion This study demonstrates that the generation of recombinant adenovirus modified lymphoma cell vaccines based on lymphoma cell lines expressing IL-2 and IL-12 cytokine genes is technically feasible, induces increases in proliferation rates and cytotoxic activity of co-cultured PBMC, and warrants further development for the treatment of lymphoma patients in the future.

Background Lymphoma cells are attractive targets for gene transfer, because these cells are potentially susceptible to immunotherapeutic strategies [ 1 ]. Among the various cancer gene therapies using a variety of genes with different gene transfer systems, immunogene therapy focuses on the use of genes for cytokines, chemokines, and co-stimulatory molecules [ 2 ]. Using an ex vivo approach of tumor cell transduction, it was shown that many cytokines could modulate tumorigenicity and protect the host from untreated tumor cells [ 3 ]. However, the effect of any single immunogene transfer has been limited, especially against low immunogenic tumors [ 4 ]. Interleukin-2 (IL-2) and interleukin-12 (IL-12) are cytokines that elicit strong antitumor effects by stimulating immune cells, including T cells and natural killer (NK) cells. Although either cytokine stimulates the proliferation of T cells, the production of interferon-γ (IFN-γ) by NK cells, and ultimately the cytolytic activity, the magnitude, and the spectrum of stimulatory effects by IL-2 and IL-12 are different. Although IL-2 is a stronger stimulator of proliferation and cytolytic activity, IL-12 is a stronger inducer of IFN-γ from NK cells and activated T cells. Although the combination of recombinant IL-2 and IL-12 treatment has been reported to be synergistic for inducing anti-tumor responses, systemic administration of these cytokines causes toxic side effects. Recent reports of intra-tumoral co-injection of adenoviral vectors expressing IL-2 and IL-12 demonstrated the regression of pre-established solid tumors with high frequency [ 5 ]. However, the significance of IL-2 and IL-12 immunogene therapy of hematopoietic neoplasms such as B cell lymphoma, has not been addressed yet. Recently, we described an adenoviral protocol accomplishing highly efficient gene transfer to B-lymphoma cell lines [ 6 ]. The use of genes or genetically modified cells for therapeutic benefit may have a significant therapeutic role for patients with B cell lymphomas in the future. Adoptive immunotherapy using donor leukocyte infusion to treat aggressive B cell neoplasms in immunosuppressed patients has shown great promise clinically, and studies of idiotypic vaccination in patients with low grade B cell neoplasms are also underway. Results from in vitro and animal studies continue to suggest that it may become possible to use the immune system for therapeutic benefit, and many current basic research strategies in the gene therapy of B cell lymphoma are based on immune modulation of T cells or tumor cells themselves. Other major approaches to gene therapy for B cell malignancies are the introduction of directly toxic or suicide genes into B cells. In the present study, we have evaluated the relationship between the amount of cytokine production by the combination IL-2 and IL-12 and the in vitro effective anti-tumor activity. Using three different human B cell lymphoma cell lines and primary samples from patients with B cell neoplasms, we transduced both IL-2 and IL-12 genes by adenoviral vectors, and monitored cytokine production and effects on proliferation and cytolytic activity of co-cultured human peripheral blood mononuclear cells (PBMC). Methods Cell culture and primary lymphoma cells The following cell lines were analyzed: Raji (human Burkitt lymphoma cell line; obtained from "Deutsche Sammlung von Mikroorganismen und Zellkulturen" (DSMZ), Braunschweig, Germany), Daudi (human Burkitt lymphoma cell line; obtained from DSMZ), and OCI-Ly8-LAM53 (human follicular lymphoma cell line; obtained from R. Levy, Stanford University, CA). The cell lines were grown in RPMI 1640 with Glutamax (Life Technologies, Berlin, Germany) supplemented with 10% heat-inactivated fetal calf serum (FCS) (PAA, Martinsried, Germany), 50 μg/ml streptomycin, and 50 μg/ml penicillin (PAA), and were kept in a humified incubator with 5% CO 2 at 37°C. Virus propagation was performed in the Ad5 E1-transformed human embryonic retina cell line 911 [ 7 ]. This cell line was grown in Dulbecco's modified Eagle's medium (DMEM) (Life Technologies) supplemented with 10% FCS, 50 μg/ml streptomycin, and 50 μg/ml penicillin. Non-adherent Ficoll-Hypaque (Seromed, Berlin, Germany) separated human PBMC were obtained from whole blood from healthy donors and maintained in RPMI 1640 with Glutamax (Life Technologies) supplemented with 10% FCS (PAA), 50 μg/ml streptomycin, and 50 μg/ml penicillin. Cytokine-induced killer (CIK) cells were generated as described previously [ 8 , 9 ]. In brief, 100 U/ml recombinant interferon-gamma (Boehringer Mannheim, Germany) was added on day 0. After 24 h of incubation, 50 ng/ml of an antibody against CD3, 100 U/ml interleukin-1 (IL-1), and 300 U/ml interleukin-2 (IL-2) (PromoCell, Heidelberg, Germany) were added. Cells were incubated at 37°C in a humified atmosphere of 5% CO 2 and subcultured every 3 days in fresh complete medium and IL-2. Five patients diagnosed with lymphoma were included into this study; four patients with chronic B cell lymphocytic leukemia (B-CLL) and one patient with immunocytoma (IC). After informed consent, peripheral blood was obtained and lymphoma cells were isolated by Ficoll-Hypaque (Seromed) density centrifugation. Cell surface antigens were analyzed for the expression of CD19, integrin avβ3, integrin avβ5, and the coxsackie B-adenovirus receptor (CAR). Primary cultures were maintained in liquid culture in RPMI 1640 with Glutamax (Life Technologies) supplemented with 10% heat-inactivated FCS, 50 μg/ml streptomycin, and 50 μg/ml penicillin at 37°C, 5% CO 2 and could be maintained in culture for 10–12 days. Adenoviral transduction of lymphoma cells Transduction of lymphoma cells with CsCl-purified adenovirus was carried out in 24-well plates with 5 × 10 5 cells in 50 μl of PBS plus 1 mM MgCl 2 /1% HS, at different multiplicities of infection (MOI). After 2 hours of incubation at 37°C, 5% CO 2 , 1 ml of complete culture medium was added to the cells. Because no visible toxic effect was observed in comparison with the controls (only PBS plus 1 mM MgCl 2 /1% HS), it was not necessary to remove the virus. Adenoviral transduction of primary lymphoma cells was considered successful if concurrent CD19 expression with green fluorescent protein (GFP) was observed. Adenoviral vector preparation The recombinant adenoviral Ad.GFP vector (pQB-AdBM5GFP), an E1- and E3-deleted replication-defective adenovirus type 5 under control of the cytomegalovirus (CMV) promoter, was purchased from Quantum Biotechnologies (Montreal, Canada). The adenovirus vector (Ad.IL-2) containing the human IL-2 sequence was kindly provided by Frank L. Graham, McMaster University, Hamilton, Ontario, Canada [ 10 ]. The E1/E3-deleted recombinant Ad5 vector expresses human IL-2 under control of the CMV immediate early promoter (HCMV IE) and the simian virus 40poly(A) signals (SV40 An). The Ad.Flexi-12 vector contains cDNA that encodes a single-chain protein, called Flexi-12, which retains all of the biological characteristics of recombinant IL-12 [ 11 ]. This E1/E3-deleted recombinant adenovirus type 5 was generated using the AdEasy system [ 12 ] and was kindly provided by Robert Anderson, Royal Free Hospital School of Medicine, London, UK. Infection of Ad.Flexi-12 can be tracked using GFP expression analysis which is present as an additional expression cassette in the viral genome. Production of the adenovirus lots was performed as described previously [ 7 ]. Briefly, near confluent 911 cell monolayers in 175-cm 2 flasks were infected with ~5 plaque-forming units (PFU)/cell in 2 ml of phosphate-buffered saline (PBS) containing 1% horse sera (HS). After 2 hours incubation at 37° in a humidified atmosphere of 5% CO 2 , the inoculum was replaced by fresh medium (DMEM/2% HS). After 48 h, nearly completely detached 911 cells were harvested and collected in 1 ml PBS/1% HS. Virus was isolated by three cycles of flash-freeze thawing. The lysates were cleared by centrifugation at 3000 rpm for 10 minutes. Viruses were then purified on double cesium chloride gradients and stored in PBS/10% glycerol at -80°C. Plaque assays were essentially performed as described by Graham and Prevec [ 13 ]. Briefly, adenovirus stocks were serially diluted in 2 ml of DMEM (Life Technologies) containing 2% HS and added to nearly confluent 911 cells in 6-well plates. After 2 hours of incubation at 37°C, 5% CO 2 , the medium was replaced by F-15 minimal essential medium (Life Technologies) containing 1% agarose (Sigma, Deisenhofen, Germany), 20 mM N-2-hydroxyethylpiperazine-N'-2-ethanesulfonic acid (pH 7.4), 0.0025% L-Glutamine, 5% yeast extract, 8.4% NaHCO 3 , 50 μg/mL streptomycin, 50 μg/mL penicillin, and 2% HS. The titers of the virus stocks were at least 1 × 10 10 PFU/ml. IL-2 and IL-12 enzyme-linked immunosorbent assays (ELISA) IL-2 and IL-12 levels in conditioned medium were determined by an enzyme-linked immunosorbent assay (ELISA) method. The ELISA reagents were purchased from Endogen, (Cambridge, USA). Briefly, a microtiter plate was coated with a monoclonal antibody specific for IL-2 or IL-12. The IL-12 antibody recognizes only the p70 heterodimer and neither of the individual subunits, p35 or p40, or the homodimeric form of p40. The cytokines present in samples are bound by the immobilized antibody. After several washes to remove unbound proteins, an enzyme-linked (horseradish peroxidase) polyclonal antibody was added to the wells which binds IL-2 or IL-12. After washing, the substrate solution was added, and the color which developed was measured using a spectrophotometer at a wavelength of 450 nm. The optical density of the samples was then compared to a standard curve. Cell proliferation assays An MTT (3-(4,5-dimethylthiazol-2yl)-2,5-diphenyl tetrazolium bromide) based colorimetic assay [ 14 ] was performed to measure the proliferative activity of PBMC stimulated with cytokines either derived from supernatants of transduced Raji cells or recombinant with or without addition of neutralizing anti-IL-2 or anti-IL-12 antibodies. In brief, 2 × 10 5 PBMC were incubated in 96-well flat-bottom plates (Nunc, Denmark) in a final volume of 200 μl per well. After 3 days 20 μl of EZ4U reagent (Biozol, Eching, Germany) was added to each well and results were obtained on a multi-well scanning spectrophotometer at 450 nm. Cytotoxicity assays A EuTDA nonradioactive cytotoxicity assay (Wallac, Turku, Finland) was used to compare the cytotoxic activity of IL-2 and IL-12 stimulated PBMC against unmodified lymphoma cells [ 15 ]. This assay is a colorimetric alternative to the 51 Cr release assay. The procedure is based on loading the target cells with a fluorescence enhancing ligand (BATDA, bis(acteoxymethyl)2,2:6,2-terpyridine-6,6-dicarboxylate). The hydrophobic ligand penetrates the membrane quickly and within the cell the esterbonds are hydrolysed to form a hydrophilic ligand (TDA, 2,2:6,2-terpyridine-6,6-dicarboxylic acid) which no longer passes the membrane. After cytolysis the ligand is released and introduced to the europium solution. The europium and the ligand form a highly fluorescent and stable chelate (EuTDA). The measured signal correlates directly with the amount of lysed cells. Briefly, 2 × 10 6 lymphoma cells were washed and resuspended in 2 ml PBS. 4.5 μl BATDA solution was added and incubated at 37° for 30 min. Then, cells were washed 3 times, resuspended in 100 μl PBS, and incubated in 96-well flat-bottom plates (Nunc) at a density of 10,000 cells/well. 100 μl of effector PBL cells of varying cell concentations were added so that effector to target cell ratio ranged from 5:1 to 20:1. After incubation at 37° for 2 h cells were centrifuged for 5 min at 500 × g and 20 μl of the supernatant was transfered to a new flat-bottom plate. 180 μl of Europium solution was added, and after 15 min incubtion at room temperature the fluorescence was measured in a time-resolved fluorometer (Wallac). The percent specific release was calculated from Statistical analysis Wilcoxon matched-pairs test was used to analyze for statistical significance. A p value < 0.05 was considered significant. Data is presented as the mean ± standard error of the mean (SEM). Results Transduction efficiencies of lymphoma cells and CAR/integrin expression Lymphoma cell lines, primary lymphoma cells, and CIK cells were transduced with Ad.Flexi-12 at various MOI (0, 50, 100, 200) and analyzed 72 h later. Transduction efficiencies were determined by GFP expression analysis using a fluorescence-activated cell sorter (FACS). Additionally, cell surface antigens were analyzed by FACS for the expression of CD19, integrin avβ3, integrin avβ5, and CAR. Adenoviral transduction of primary lymphoma cells was considered successful if concurrent CD19 expression with GFP was observed. It was demonstrated that most B cell lymphoma cell lines could be transduced with much higher efficiency than primary tumor samples or CIK cells. At an MOI of 200, up to 40% of Daudi cells and 70% of Raji cells could be transduced (Fig. 1A ). In contrast, primary B-CLL cells were found to be relatively resistant with transduction efficiencies up to 6 %, whereas OCI-Ly8-Lam53 (LAM53) cells, primary IC cells, and CIK cells were completely refractory (Fig. 1B ). Transduction efficiency could be correlated with the expression of CAR. High expression of CAR was evident in Raji and Daudi cells, averaging 72% and 86%, respectively. Primary B-CLL cells were found to have moderate CAR expression of 36%. In contrast, there was no CAR expression detectable in LAM53, IC, and CIK cells (Table 1 ). Expression of integrin receptors, however, was low or absent in all lymphoma cells examined. Figure 1 Transduction efficiencies in various human lymphoma cell lines (A), primary human lymphoma cells, and CIK cells (B). All cell types were transduced with Ad.Flexi-12 at various MOI as indicated and analyzed for GFP expression 72 h later by FACS analysis (mean ± SEM; n = 3). Table 1 Expression analysis of adenovirus binding (CAR) and internalization receptors (avβ3, avβ5) on various human lymphoma cell lines (Raji, Daudi, OCI-Ly3-LAM53), primary B lymphoma cells (B-CLL, IC), and CIK cells by FACS analysis (mean ± SEM; n = 3; n.d., not detectable). CAR avβ3 avβ5 Cell lines: Raji 72.5 ± 6.2 1.2 ± 0.1 1.0 Daudi 86.3 ± 1.8 1.1 ± 0.1 1.0 OCI-Ly8-LAM53 3.9 ± 1.5 1.1 ± 0.1 1.0 Primary cells: B-CLL 36 ± 6.4 0.6 13.6 IC 3.2 n.d. n.d. CIK 1.3 ± 0.2 15.0 2.0 Adenoviral-mediated expression of IL-2 and IL-12 in lymphoma cells in vitro Cytokine gene expression was analyzed in lymphoma cell lines using an ELISA assay as described above. Daudi, Raji, and LAM53 cells were infected with Ad.IL-2 or Ad.Flexi-12 at various MOI (0, 50, 100, 200) with Ad.GFP as a control vector. Cytokine production was assayed 72 h post-infection. As shown in Fig. 2A , IL-2 produced by Ad.IL-2-transduced Raji and Daudi cells at an MOI of 200 averaged 10.6 ng/ml/10 6 cells and 2.7 ng/ml/10 6 cells, respectively. In contrast, there was no IL-2 detectable in Ad.IL-2-transduced LAM53 cells. Kinetic analysis of IL-2 production in Raji cells revealed peak secretions between day 2 and 3. IL-2 was detectable until day 8 post-infection (Fig 2B ). Similarly, IL-12 gene expression of Ad.Flexi-12 transduced Raji and Daudi cells revealed 219 ng/ml/10 6 cells and 15.6 ng/ml/10 6 cells, respectively. No expression was detectable in Ad.Flexi-12-transduced LAM53 cells (Fig. 3A ). Peak expression of IL-12 was evident between day 1 and 3, with IL-12 detectable by ELISA until day 10 post-infection (Fig. 3B ). Figure 2 IL-2 gene expression analysis in human lymphoma cell lines by using an ELISA assay. (A) Daudi, Raji and LAM53 cells were infected with Ad.IL-2 or Ad.GFP at various MOI (0, 5, 100, 200). 72 h post-infection, IL-2 produced by Ad.IL-2-transduced Raji and Daudi cells at an MOI of 200 averaged 10.6 ng/ml/10 6 cells and 2.7 ng/ml/10 6 cells, respectively (mean ± SEM; n = 3). (B) Kinetic analysis of IL-2 production in Raji cells transduced at an MOI of 200 revealed peak secretions between day 2 and 3 and IL-2 was detectable until day 8 post-infection (mean ± SEM; n = 3). All experiments were performed in triplicates. Figure 3 (A) IL-12 gene expression of Ad.Flexi-12 transduced Raji and Daudi cells revealed 219 ng/ml/10 6 cells and 15.6 ng/ml/10 6 cells at 72 h post-infection, respectively (mean ± SEM; n = 3). No expression was detectable in Ad-Flexi-12 transduced LAM53 cells. (B) Peak expression of IL-12 in transduced Raji cells was evident between day 1 and 3, with IL-12 detectable until day 10 post-infection (mean ± SEM; n = 3). All experiments were performed in triplicates. Increase in proliferation rates of PBMC stimulated with adenoviral-expressed cytokines To determine if adenoviral-expressed cytokines from transduced lymphoma cells would have an impact on the proliferation rates of PBMC from healthy donors, the following experiment was performed. PBMC were freshly isolated and various concentrations of cytokines (1–1000 pg/ml) either derived from the supernatants of transduced lymphoma cells or recombinant were added. Then, an MTT assay to assess the proliferation rate was performed five days later. For blocking experiments, a neutralizing monoclonal antibody against IL-2 or IL-12 was used. Figure 4 shows that addition of adenoviral-expressed IL-2 (Fig. 4A ) and IL-12 (Fig. 4B ) led to dose-dependent increases in proliferation rates of PBMC. There was no significant difference between the effects of both cytokines. Furthermore, the proliferative effect could be blocked by addition of a neutralizing antibody against either cytokine. Finally, it was demonstrated that there was no significant difference between adenoviral-expressed and recombinant cytokines. Figure 4 PBMC were incubated with cytokines (1–1000 pg/ml) either derived from supernatants of transduced Raji cells or recombinant with supernatants from Ad.GFP-transduced Raji cells as controls and assayed for their proliferative activity (mean ± SEM; n = 3). Adenoviral-expressed IL-2 (A) and IL-12 (B) led to dose-dependent increases in proliferation rates of PBMC. No significant difference between the effects of either cytokine was found. The proliferation effect could be blocked by addition of a neutralizing antibody against either cytokine. There was no significant difference between the effects of adenoviral-expressed or recombinant cytokines. MTT assays were performed in triplicates. Cytolytic activity of co-cultured PBMC against unmodified lymphoma cells Raji cells were transduced with Ad.IL-2 (MOI 200), Ad.Flexi-12 (MOI 200), or Ad.IL-2 and Ad.Flexi-12 together (MOI 100 each) and co-cultured with PBMC for 72 h. Non-transduced (control) and Ad.GFP transduced Raji cells were used as controls. Stimulated PBMC were harvested and assayed for their cytolytic activity against unmodified lymphoma cells using a EuTDA nonradioactive cytotoxicity assay. It could be shown that Ad.IL-2 transduced lymphoma cells produced a significant (p < 0.05) anti-tumor effect but not the combined effect of Ad.IL-2/Flexi-12 or Flexi-12 alone (Fig. 5 ). Figure 5 Raji cells were transduced with Ad.IL-2 (MOI 200), Ad.Flexi-12 (MOI 200), or Ad.IL-2 and Ad.Flexi-12 (MOI 100 each) and co-cultured with PBMC for 72 h. Non-transduced (control) and Ad.GFP-transduced Raji cells were used as controls. Stimulated PBMC were harvested and assayed for their cytolytic activity against unmodified lymphoma cells by using an EuTDA non-radioactive cytotoxicity assay. Ad.IL-2-transduced lymphoma cells elicited a significant anti-tumor effect but not the combined effect of IL-2/IL-12 or IL-12 alone (mean ± SEM; n = 5; * p < 0.05). Discussion The rationale for genetically modified lymphoma cell vaccines is to augment the immunogenicity of poorly immunogenic lymphoma cells, thereby eliciting a systemic immune reponse that is capable of controlling the disseminated disease. Transgene candidates to potentially achieve that goal include genes encoding for cytokines, lymphotactic chemokines, allogeneic MHC molecules, or co-stimulatory molecules [ 4 ]. The co-stimulatory molecule CD40 ligand expressed from a recombinant adenoviral vector in autologous chronic lymphocytic leukemia cells has been tested in a recent clinical trial with encouraging results. [ 16 ]. Immunotherapy that combines two or more of these immunostimulatory molecules will likely prove more effective than single agents [ 17 ]. In this regard, adenoviral-mediated expression of both the IL-2 and IL-12 cytokine genes in several solid tumor models has been found to induce strong and specific anti-tumor responses [ 5 , 18 ]. Interestingly, Wang et al. demonstrated that IL-2 enhances the reponse of NK cells to IL-12 through up-regulation of the IL-12 receptor, signal transducer, and transcription protein STAT4 [ 19 ]. Therefore, we were interested in evaluating the potential of IL-2 and IL-12 transduced lymphoma cells for their ability to stimulate and activate immunologic effector cells. Lymphoma cells are relatively resistant to transduction with most currently available vector systems [ 20 , 21 ]. This problem may be overcome ex vivo by using Epstein-Barr virus vectors [ 22 ], adeno-associated virus vectors [ 23 ], or modified adenoviral vectors [ 24 , 25 ]. Recently, we described a transduction method accomplishing highly efficient adenoviral-mediated gene transfer in lymphoma cells [ 6 ]. Using this protocol, expression of the wild-type p53 tumor-suppressing gene in lymphoma cell lines with mutant p53 showed increased sensitivity to cytotoxic drug and immuno-mediated toxicity [ 26 ]. In the current study, we observed low expression levels of cell surface integrins avβ3 and avβ5 on all lymphoma cells studied, which suggests that the adenoviral entry into these cells may be mediated by CAR, expressed at high levels on Raji and Daudi cells. As a consequence, Raji and Daudi lymphoma cell lines could be transduced with higher efficiency, whereas primary lymphoma cells and normal lymphocytes with low-level expression of CAR were refractory. Turturro et al. have also shown that anaplastic large cell lymphoma cells express high levels of CAR and integrins, which could be transduced by adenoviral vectors with high efficiency [ 27 ]. These results indicate the importance of determining the expression levels of CAR and integrins in tissues or cells derived from patients for the generation of adenoviral vector-modified lymhoma cell vaccines. Previously reported transduction efficiencies of adenoviral vector-transduced lymphoma cells were obtained with non-purified viruses [ 6 ]. Since this protocol is not feasible for clinical application, the present studies were performed with CsCl-purified viruses and lower transduction efficiencies were achieved. The exact reason for this difference is currently unknown and will be elucidated in the future. In our hands, human Burkitt's lymphoma cell lines were most efficiently transduced with adenoviral vectors. Expression of IL-2 and IL-12 cytokines in Raji cells transduced at a relatively low MOI of 200 was transient, peaked between 1 and 3 days post-infection, and was detectable up to 10 days. The produced cytokines were assayed for their biological ability to stimulate PBMC from healthy donors in comparison with recombinant cytokines as controls. Our data indicates that adenoviral expressed cytokines were equally effective compared with recombinant cytokines in enhancing the proliferation rates of PBMC. This effect could be blocked by the addition of neutralizing antibodies against either cytokine. In a cytotoxicity assay, IL-2 stimulated PBMC were able to lyse unmodified Raji cells, while IL-12 or the combined IL-2 and IL-12 stimulated PBMC were clearly less effective. Previously, we have shown that cytotoxic CD8+ NKT cells are readily expandable in vitro in large quantities suitable for adoptive immunotherapy. These activated effector cells have significant cytotoxic activity against human lymphoma xenografts with limited toxicity [ 8 , 28 ]. We have also demonstrated that CD8+ NKT cells can be generated in vitro using either IL-2 or IL-12 [ 29 ]. Interestingly, adoptive T cell therapy combined with intratumoral administration of adenoviral expressed IL-12 was shown to have strong synergistic effects against large transplanted tumors [ 30 ]. Therefore, expression of IL-2 and IL-12 in lymphoma cells may be used to further increase their sensitivity towards adoptively transferred CD8+ NKT cells in the future. Conclusion This study demonstrates that the generation of recombinant adenovirus modified lymphoma cell vaccines based on lymphoma cell lines expressing IL-2 and IL-12 cytokine genes is technically feasible, induces increases in proliferation rates and cytotoxic activity of co-cultured PBMC, and warrants further development for the treatment of lymphoma patients in the future. Competing interests The author(s) declare that they have no competing interests. Authors contributions OE and DW designed the experiments and performed the experimental studies presented in this paper. PB developed the experimental protocols and assisted in the analysis of the results. CZ, DF, and ISW participated in the design of the study and its coordination. All authors have read and approved this manuscript.

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529325

This Is Your Fly's Brain on Drugs

Cocaine addiction wreaks profound changes on the brain, hijacking reward circuits and depressing inhibitory loops to the point that drug seeking and taking become central drivers of behavior. Lying at the core of these behavioral changes are molecular ones; at its most basic level, addiction alters the sensitivity of neurons. While primates and rats are useful for mapping out the neural complexity of these behavioral manifestations, insights into the molecular basis of drug abuse can be garnered more easily from simpler models, such as the fruitfly, Drosophila . The reigning model of cocaine's effects on the brain has highlighted its ability to block reuptake of dopamine by cells of a brain region called the nucleus accumbens. But numerous experiments show this is not the whole story. Ulrike Heberlein and colleagues describe their discovery of a new gene that modulates sensitivity to cocaine within the cells of the fruitfly's internal clock. They further show that the cells' role in regulating cocaine sensitivity is distinct from its function as a timekeeper. One known effect of cocaine on Drosophila is loss of “negative geotaxis,” or wall climbing, in response to startle. Using this behavior to screen 400 different mutants, the researchers identified seven with an increased response to cocaine, and for two of these, the disrupted gene was the same, Lmo . The Lmo protein, whose levels were reduced by the mutations, is known to regulate certain transcription factors during development. Despite this, no developmental defects were detected in the loss-of-function mutants that might explain the cocaine effect. The researchers also found that a third mutation in the same gene, previously associated with disruption in wing formation, increased levels of the Lmo protein, and decreased response to cocaine. Thus, Lmo appears to play a central role in regulating cocaine sensitivity. While Lmo is found throughout the body, it is enriched in the brain, and by expressing normal Lmo in oversensitive mutants, Heberlein and colleagues discovered that its cocaine-related effects were localized to the ventral lateral neurons (LN v s). Comprising about ten cells per hemisphere, these neurons provide the fly with an internal clock, driving circadian activities even in the absence of light. Not surprisingly, Lmo mutants had weaker circadian rhythms than normal flies. But is increased cocaine sensitivity a simple consequence of a broken clock? Apparently not. To date, the only known output of the LN v is a small peptide called PDF, and PDF mutation causes circadian disruptions. It does not, however, alter cocaine sensitivity. Furthermore, completely obliterating the LN v , or blocking its ability to fire, disrupted circadian rhythmicity but reduced cocaine sensitivity, rather than increasing it. These results indicate than the LN v normally enhances sensitivity to cocaine, a function enhanced further by Lmo mutants, and does so independently of circadian regulation. Based on their results, Heberlein and colleagues propose a possible model for Lmo' s role in modulating cocaine sensitivity. Drawing on recent evidence that a subset of LN v cells possess dopamine receptors, they suggest that Lmo expression normally regulates the density of these receptors on LN v cells. Loss of Lmo would raise the number of receptors, thereby increasing the sensitivity to cocaine. A key prediction from their findings is that the LN v has another output, as yet undetected, in parallel with PDF that mediates responsiveness to cocaine. Because Lmo -related proteins are found in key areas of mammalian brains, these results may have important implications for understanding innate differences in sensitivity to cocaine in humans, and potentially provide targets for development of drugs to treat or prevent addiction.

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514701

Influence of microarrays experiments missing values on the stability of gene groups by hierarchical clustering

Background Microarray technologies produced large amount of data. The hierarchical clustering is commonly used to identify clusters of co-expressed genes. However, microarray datasets often contain missing values (MVs) representing a major drawback for the use of the clustering methods. Usually the MVs are not treated, or replaced by zero or estimated by the k-Nearest Neighbor ( kNN ) approach. The topic of the paper is to study the stability of gene clusters, defined by various hierarchical clustering algorithms, of microarrays experiments including or not MVs. Results In this study, we show that the MVs have important effects on the stability of the gene clusters. Moreover, the magnitude of the gene misallocations is depending on the aggregation algorithm. The most appropriate aggregation methods (e.g. complete-linkage and Ward) are highly sensitive to MVs, and surprisingly, for a very tiny proportion of MVs (e.g. 1%). In most of the case, the MVs must be replaced by expected values. The MVs replacement by the kNN approach clearly improves the identification of co-expressed gene clusters. Nevertheless, we observe that kNN approach is less suitable for the extreme values of gene expression. Conclusion The presence of MVs (even at a low rate) is a major factor of gene cluster instability. In addition, the impact depends on the hierarchical clustering algorithm used. Some methods should be used carefully. Nevertheless, the kNN approach constitutes one efficient method for restoring the missing expression gene values, with a low error level. Our study highlights the need of statistical treatments in microarray data to avoid misinterpretation.

Background The genome projects have increased our knowledge of genomic sequences for several organisms. Taking advantage of this knowledge, the microarrays technologies allow the characterization of a whole-genome expression by showing the relative transcript levels of thousand of genes in one experiment [ 1 ]. Numerous applications were developed apart gene expression analysis like single nucleotide polymorphism (SNP) and genotyping [ 2 , 3 ], diagnosis [ 4 ] and comparative genomics [ 5 ] analysis. Particularly, the transcriptome analysis provides insight into gene regulations and functions. To help the characterization of relevant information in microarray data, specific computational tools are needed. The identification of co-expressed genes is commonly performed with unsupervised approaches, such as clustering methods with the Hierarchical Clustering (HC) [ 6 ], the k -means [ 7 ] and the Self-Organizing Map (SOM) [ 8 , 9 ], or with projection methods such as the Principal Component Analysis (PCA) [ 10 ] and Independent Component Analysis (ICA) [ 11 ]. Among these techniques, the HC approach is a widely held method to group genes sharing similar expression levels under different experimental conditions [ 12 ]. The HC is performed from the distance matrix between genes computed from the microarray data, i.e . the gene expression levels for various experimental conditions. Different aggregation methods can be used for the construction of the dendogram generally leading to different tree topologies and a fortiori to various cluster definitions [ 13 ]. For instance, the single-linkage algorithm is based to the concept of joining the two closest objects ( i.e . genes) of two clusters to create a new cluster. Thus the single-linkage clusters contain numerous members and are branched in high-dimensional space. The resulting clusters are affected by the chaining phenomenon ( i.e . the observations are added to the tail of the biggest cluster). In the complete-linkage algorithm, the distance between clusters is defined as the distance between the most distant pair of objects ( i.e . genes). This method gives compact clusters. The average-linkage algorithm is based on the mean similarity of the observations to all the members of the cluster. Yeung and co-workers [ 14 ] showed that single-linkage hierarchical clustering is inappropriate to analyze microarray data. Gibbons and Roth [ 15 ] showed by using gene ontology that single-and average-linkage algorithms produce worse results than random. In addition these authors conclude that the complete-linkage method is the only appropriate HC method to analyze microarrays experiments. The microarrays experiments frequently contain some missing values. The missing values are part of the experimental errors due to the spotting conditions (e.g. spotting buffer, temperature, relative humidity...) and hybridization (e.g. dust on the slide...) [ 16 , 17 ]. The users commonly discard suspicious dots during the images analysis step. Thus, the resulting data matrix contains missing values (MVs) which may disturb the gene clustering obtained by the classical clustering methods, e.g. HC, SOM, or projection methods, e.g. PCA. To limit the effects of MVs in the clustering analyses, different strategies have been proposed: (i) the genes containing MVs are removed, (ii) the MVs are replaced by a constant (usually zero), or (iii) the MVs are re-estimated on the basis of the whole gene expression data. Few estimation techniques have been applied to such data. The k -nearest neighbors approach ( kNN ) computes the estimated value from the k closest expression profiles among the dataset. Troyanskaya and co-workers showed that the weighted kNN approach, with k = 15, is the most accurate method to estimate MVs in microarray data compared to replacement by zero, row average, or Singular Value Decomposition [ 18 ]. A recent work proposes Bayesian principal component analysis to deal with MVs [ 19 ]. In the same way, Zhou and co-workers [ 20 ] have used a Bayesian gene selection to estimate the MVs with linear and non-linear regression. However, the kNN approach is the most popular approach for estimating the MVs. To explore the incidence of MVs in gene clustering, we first assessed the proportion of MVs in different sets of public data from Saccharomyces cerevisiae and human. Observing that MVs are widely present in the expression data, we then analyzed the effects of MVs on the results of a hierarchical clustering (HC) according to the chosen clustering algorithm. In the same way, we evaluated the impact of MVs replacement and estimation in the gene cluster definition by using a hierarchical clustering method. Results and Discussion Missing values overview Table 1 summarizes the proportions of MVs in eight series of microarray experiments [ 21 - 28 ]. The number of genes and experimental conditions are within the range ( 552 ; 16523 ) and ( 4 ; 178 ) respectively. The percentage of MVs varies from 0.8% to 10.6%. No relation had been found between the number of genes and the percentage of MVs or the percentage of genes without MVs. As expected, the percentage of genes with MVs increases in function of the number of experimental conditions. In the Sorlie [ 22 ], Spellman [ 28 ] and Gasch sets [ 25 ] respectively, 94.7%, 91.8% and 87.7% of the genes profiles have MVs. In these cases, it is not possible to systematically delete the genes profiles with MVs in the data analysis. Indeed, the percentage of MVs is not negligible in the microarrays data and may be a strong factor of gene clustering instability. Hence, we evaluated in this study the effects of MVs on gene group definition by using hierarchical clustering algorithms. Main steps of the analysis Figure 1 describes the four steps of the analysis. (i) Definition of a complete datafile : We selected from literature a set of microarray data. This set was filtered to retain only genes without MVs. (ii) Construction of reference gene clusters : A gene clustering was performed by different HC algorithms ( algo ). Seven types of algorithms were used (see section Methods). For each analysis, we defined a number K algo of gene clusters, representing the reference clusters. (iii) Generation of a datafile with MVs : MVs were randomly inserted with a fixed rate τ . This rate correspond to the percentage of genes with 1 missing value. So, we defined data with MVs. (iv) Analysis of the newly generated expression data: We carry out a data processing similar to step (ii), with the construction of dendograms for each algorithm ( algo ) and the definition of the K algo new clusters in the different experiments (no replacement of MVs was carried out). Finally, we assessed the stability of the gene clustering by calculating an index measuring the percentage of conserved genes between the clusters of the reference set and the generated set. Moreover, two other experiments were (v) designed and (vi) evaluated: clustering with MVs estimated by the kNN approach, and clustering with MVs replaced by zero. Experimental sets As we work on the impact of MVs in gene clustering, we need at first biological datasets without MVs. These sets have been extracted from Ogawa set [ 26 ] (noted OS) and Gasch set [ 25 ] (noted GS). OS and GS have been chosen because they contain few MVs and, after filtering the number of genes remains important, ( ca. 6000). The original Ogawa set contained 6013 genes with 230 genes having MVs. The elimination of the genes with MVs (i.e. 3.8% of the genes) leads to a set with 5783 genes. For the GS, the number of MVs is more important and some experimental conditions have more than 50% of MVs. So we have limited the final number of selected experimental conditions from 178 to 42 (see section Methods), it allows to conserve 5843 genes, i.e. only 310 genes are not analyzed, representing 5.0% of all the genes. Moreover, we have defined two smaller sets, GS H2O2 and GS HEAT , from GS corresponding respectively to H 2 O 2 and heat shock experimental conditions. To assess the influence of size of the datasets and the number of observations (genes), we have generated smaller sets corresponding to a ratio 1/ n ( n = 2, 3, ..., 7) of the initial OS, GS, GS H2O2 and GS HEAT gene content (see section Methods). Example of clustering disturbance caused by missing values introduction Figure 2 gives an example of significant clustering disturbance caused by the MVs. Figures 2a and 2b show the dendograms obtained with the complete-linkage hierarchical clustering of the gene set before and after introducing 1% of MVs. Surprisingly, the genes belonging to one cluster in the reference dataset are reallocated in several clusters after this slight data transformation. Number of clusters To perform the comparison of the gene clustering by HC, the numbers of clusters according to every type of hierarchical clustering algorithms have to be defined. Hence we defined the number of clusters, K algo , for each clustering algorithm ( algo ). The rule consists in determining K algo clusters as the 10 most important clusters correspond to 80% of the genes of the dataset (see section Methods). The results for OS are shown in Table 2 (column 1) for each clustering methods. As expected, we observe a correlation with the type of algorithm used. The number of clusters is lower for the well-balanced tree generally obtained by the Ward and complete-linkage methods, e.g. 19 and 36 clusters respectively, compared to those providing by the other methods. For instance, the single-and centroid-linkage methods lead to the definition of 175 clusters. Index "Conserved Pairs Proportion (CPP)" The clusters defined from the reference data and the data with MVs are compared using Conserved Pairs Proportion (CPP) index which corresponds to the percentage of genes found associated in the reference clusters and found again associated in the clusters generated from the data with MVs. Figure 3 summarizes the results about the influence of MVs on the hierarchical clustering. The given results were computed on the (1/7) subset from OS using the seven aggregative algorithms. The metric used is the Euclidean distance. We observe that (i) the single-and the centroid-linkage methods show a low CPP decrease, the CPP values are always greater than 95%, (ii) the average-and median-linkage methods are within the range [65%; 80%] and (iii) the mcquitty, Ward and complete-linkage methods show the most striking loss. We observe a drastic loss of the clustering stability since τ = 1% of MVs. For instance, with 5% of genes with MVs, i.e . 40 missing data, the mcquitty, Ward and complete-linkage methods have a CPP of 62%, 57% and 52%, respectively. Beyond a rate of τ equal to 10%, the decrease becomes lower. Similar results are observed for all the sets OS, GS, GS H2O2 and GS HEAT and all the generated sets from 1/2 to 1/7. These last results show that the quality of the gene clustering is not disturbed by the reduction of the number of genes. It must be clearly noted that to limit the effect of the topology of each algorithm, we have fixed that the 10 most populated clusters must represent 80% of the genes. The number of the most populated clusters is fixed at 10 due to the Ward linkage method that gives a very limited number of clusters. Then, the percentage of genes belonging to the 10 most populated clusters have been tested ranging from 70% to 90% (data not shown). For example with a percentage equal to 90%, the CPP values of single-and the centroid-linkage methods remain too stable to observe a clear decrease as seen in Figure 3 . The choice of 80% allows to analyze the precise decrease of the different CPP values and to compare the different aggregation methods. k -Nearest Neighbor ( kNN ) The kNN method has been described by Troyanskaya and co-workers [ 18 ] for the MVs in microarray data. The kNN approach goal is to compute the expected value of a missing value from the k nearest vectors without a missing value. As no theoretical approach exists to define the optimal k values ( k opt ), we have assessed every value of k within the range 1 to 100 and, selected the k opt value as the k value which has the minimal error rate. Table 3 shows the k opt values obtained for the four sets used in this study and their corresponding error rates. The k opt values are lower in OS subsets showing a low number of genes. The k opt values of GS H2O2 are within the range 11 to 17. The GS and GS HEAT sets exhibit more important variations within the range 8 to 28. The error rate decreases slightly according to the number of genes, but these variations are not significant. Nevertheless, this poor correlation may be due to the subsets composition. Indeed, they keep an equivalent number of clusters with a smaller number of genes per cluster. In the same way, it may simply be due to the k opt variation. Figure 4 shows that the kNN method gives worse prediction of the extreme values than the values close to zero. The real data distribution follows approximately a normal distribution and the kNN approximation leads to a reduction of the standard deviation of this distribution. So, the prediction of the extreme values increases the global error rate implying a higher k opt to reduce this effect. For instance, in the OS sets, we observe that the values within the range [-1.0; 1.0] are approximated with a mean error rate within the range [0.12; 0.14]. Conversely the values more than 1.5 or less than -1.5 are approximated with a mean error rate superior to 1.8. The misestimating of extreme values has an impact on the clustering. One can notice that the unweighted kNN (mean of the k observations) exhibits worse results compared to the weighted kNN used in this study (data not shown). Improvements of CPP with kNN approach and zero-value replacements The CPP was computed for the seven agglomeration methods. We have compared the HC results obtained with the reference sets and the generated sets without replacement of MVs, with kNN replacement or with zero-value replacement methods. Table 2a shows that the kNN and zero-value replacements both improved the mean CPP whatever the clustering method used, except for the Ward method with the zero value replacement. The kNN approach is the most relevant method to replace MVs. In 55.2% to 66.3% of the simulations, kNN is better and globally gives a mean increase of the CPP within the range [0.7; 2.1]. The centroid-and single-linkage methods have better increase in 74.8% and 99.3% of the simulations respectively due to their particular topologies. The zero value replacement is clearly less efficient. Nevertheless, as a slight variation can displace one gene into a close cluster, we have characterized another index named CPP f to consider the f closest clusters of the selected cluster. This index is similar to the previous one and takes into account that the genes may be relocated in close clusters (see section Methods). It allows the evaluation of the topology conservation. We used f = 5. We observed that the co-associated genes in the reference sets are often displaced to close clusters in the simulated sets. As observed for the CPP , the kNN approach improves the CPP f for all the clustering methods in 51.9% to 60.2% of the simulations within the range [0.2; 1.5]. Due to their high initial CPP values (97.7% and 98.8%), single-and centroid-linkage methods do not have a gain as previously observed for the CPP . Similar results are obtained with the other sets with slight variations. For example, GS H2O2 have CPP and CPP f close to the one of OS. Conversely, the CPP and CPP f of GS HEAT are better than the ones of OS and GS H2O2 for the complete-linkage and Ward methods, but lower for the others. The GS set has higher CPP and CPP f for single-likage to mcquitty method due to a lower influence of the MVs in a vector with a higher number of experimental conditions. Nevertheless, the complete-linkage and Ward linkage still remain at a very low CPP (close to 50%). Moreover, we have tested the influence of the number of MVs per gene by introducing more than one missing value per gene. We obtained similar results showing less than 0.2% of variations of the CPP values. In addition we have tested the consequences of using k values different of k opt values in the range [ k opt -10 ; k opt +10] and we observed a decrease of CPP within the range [1%; 5%] (data not shown). Extreme values We have followed the same methodology to analyze the extreme values, i.e . values superior to 1.5 and lower than -1.5. Table 2b summarizes the results of the OS (1/7). The CPP values are superior to the CPP values obtained previously, because only the genes with important variations have MVs and are members of small clusters. We observe that MVs replacement has little effect. Indeed, the kNN and zero – value replacement cannot restore a correct distribution (cf. Figure 4 ). However, the CPP f shows that the kNN is better than the replacement by zero, allowing a better topology preservation. Same results are observed for the other sets (data not shown). Conclusions MVs are a common trait of microarrays experiments. Few works had been reported about MVs replacements [ 18 - 20 ] and none analyse their influence in the clustering of microarrays data. In our study, we showed that MVs significantly biased the hierarchical clustering. In addition, we observed that the effects of MVs are correlated to the chosen clustering method. The single linkage-method is the most stable due to the building of cluster of large size and numerous small clusters and singletons. At the opposite, the Ward and complete-linkage methods create well distributed population of clusters inducing a higher sensitivity to MVs. The topology of the dendogram is highly disturbed by transferring genes in distant clusters. We showed that the kNN replacement method was the most efficient approach to compensate the MVs effects compared to the classical replacement by zero. The k opt depends on the sample size. It is important to keep in mind that the MVs corresponding to extreme values are difficult to estimate with the kNN method. The impact of their approximation upon the clustering is significant. Hence, new approaches like the Bayesian Principal Component Analysis (BPCA) may overcome this problem. In a recent work Liu and co-workers suggest to potentially eliminate the incomplete series of data by using robust Singular Values Decomposition [ 29 ]. In addition, our work showed clearly the need of evaluation of the data quality and statistical measurements as noted by Tilstone [ 30 ]. Contrary to Yeung and co-workers [ 14 ] and Gibbons and Roth [ 15 ], we have defined for each type of hierarchical clustering algorithm ( algo ) a specific number of clusters ( K algo ). This point is one of the main difficulties noted by Yeung and co-workers [ 31 ] to evaluate the clustering methods as the topology generated are different. The comparison of the different aggregative clustering algorithms remains constrained by the topology (e.g. 175 clusters defined in our study for single-linkage compared to 19 clusters for Ward method). All these results are in accordance with the results of Nikkilä and co-workers [ 32 ] which show a hieratic problem of topology preservation in hierarchical clustering. Recent methods like SOTA [ 33 , 34 ] or Growing SOM (Self-Organizing Maps) [ 35 ] have combined a hierarchical clustering visualization with the preservation of the topology allowed by the SOM. Our future works will address the definition of a most robust clustering method. Methods Data sets We used 8 public data sets from the SMD database ([ 36 ]; see Table 1 ). Two sets were used for a thorough analysis. The first one (Ogawa set) was initially composed of N = 6013 genes and n = 8 experimental conditions about the phosphate accumulation and the polyphosphate metabolism of the yeast Saccharomyces cerevisiae [ 26 ]. The second one corresponds to various environmental stress responses in S. cerevisiae [ 25 ]. This set (Gasch set) contains N = 6153 genes and n = 178 experimental conditions. Due to the diversity of conditions in this set, we focused on two experimental subsets corresponding to heat shock and H2O2 osmotic shock respectively. Data sets refinement: missing values enumeration To evaluate the incidence of MVs on hierarchical clustering, we built complete datasets without MVs. All the genes containing at least one missing value were eliminated from the Ogawa set (noted OS). The resulting OS set contains N = 5783 genes and n = 8 experimental conditions. The second set without MVs was taken from Gasch et al. and called GS. The experimental conditions (column) containing more than 80 MVs were removed. The resulting GS matrix contains N = 5843 genes and n = 42 experimental conditions. Two subsets were generated from GS and has been noted GS HEAT and GS H2O2 . They correspond to specific stress conditions as described previously. GS HEAT and GS H2O2 contain respectively N = 3643 genes with n = 8 experimental conditions and N = 5007 genes with n = 10 experimental conditions. To test the influence of the matrix size, i.e . the number of genes, we built six smaller sets corresponding to 1/2, 1/3, 1/4, 1/5, 1/6 and 1/7 of OS, GS, GS HEAT and GS H2O2 . To obtain representative subsets, we can not use a random generation which can bias the results. So, we searched for each subset the series of genes which reflect at best all the genes of the complete set. First, the distance matrices between all the genes were computed. Then, we performed an iterative process by: (i) computing the sum of the distances for each possible t-uplets ( t= 2 to 7) of the set, (ii) choosing the t genes which have the minimal distance, (iii) selecting 1 representative gene upon the t selected genes, this gene is chosen as the closest to the barycenter of the cluster, (iv) eliminating from the process the t genes. Step (i) to step (iv) are repeated until all the genes are used. All the representative genes constitute the subset (1/ t ). This procedure allows one to reduce the redundancy of similar genes and to maintain approximately a number of gene clusters constant. Missing values generation From the sets without MVs, we introduced a rate τ of genes containing one MV ( τ = 1 to 50.0%), these MVs are randomly drawn. Each random simulation is generated at least 100 times per experiment to ensure a correct sampling. Replacement of MVs by the kNN method To fulfill v i , a missing value i for a given expression vector v ( i.e . a gene), with the kNN method, the k vectors w corresponding to the k most nearest vectors to v (without taking the i th elements of the w -vectors into account) are searched. The missing value v i is then estimated by a weighted value of the k retained w i values. The similar vectors are identified by calculating the Euclidean distance d between the vector v and every vector w . The k minimal distances d ( v , w ) are selected and the estimated value is computed as follow [ 18 , 19 ]: In the weighted kNN , s ( v , w t ) = 1 / d ( v , w t ), this similarity measure s ( v , w t ) is deduced from the distance d ( v , w t ) between v and its neighbors w . In equation (1), more a vector w close to v , more it contributes to the estimation of the missing value. The kNN approach has no theoretical criterion to select the optimal k value ( k opt ) [ 19 ]. We have estimated for each subset the corresponding k opt using the sets without MVs to ensure a minimal bias in the comparison of the hierarchical clustering results. The determined k opt value is associated with a minimal global error rate as defined by Troyanskaya and co-workers [ 18 ]. Hierarchical Clustering The hierarchical clustering (HC) algorithm allows the construction of a dendogram of nested clusters based on proximity information [ 6 ]. The HC have been performed using the hclust package in R software [ 37 ]. Seven hierarchical clustering algorithms have been tested: average-linkage, complete-linkage, median-linkage, mcquitty, centroid-linkage, single-linkage and Ward minimum variance [ 13 ]. The distance matrix between all the vectors ( i.e . genes) is calculated by using an external module written in C language. We used the normalized Euclidean distance d* to take account of the MV: v and w are two distinct vectors and m is the number of MVs between the two vectors. Thus, ( v i - w i ) is not computed if v i and/or w i is a missing value An index for clustering results comparison: Conserved Pairs Proportion ( CPP ) To assess the influence of missing data rates and different replacement methods into clustering results, we have analysed the co-associated genes of an original dataset (without MVs) compared to these genes location in a set with MVs. Hence, we realized in a first step the clusterings with the data sets without MV by each aggregative clustering algorithm. The results obtained by these first analyses are denoted reference clusterings (RC) . In a second step, we generated MVs in data. The MVs are replaced by using the different replacement methods. Then we performed the hierarchical clustering for each new set. The results obtained by these second analyses are denoted generated clusterings (GC) . We compared the resulting clusters defined in RC and GC . We assessed the divergence by using an index named Conserved Pair Proportions ( CPP ). The CPP is the maximal proportion of genes belonging to two clusters, one from the RC and the other one from the GC (cf. Figure 1 ). The procedure for computing the index CPP is as follow (figure 5 gives an example of CPP computation): i) For each reference clustering based on a given clustering algorithm ( algo ), we defined K algo , the number of clusters. As every type of hierarchical clustering algorithm gives a particular topology, we cannot use the same number of clusters to compare each aggregative method. So, we defined K algo such as its 10 most important cluster must represent 80% of the genes. For this purpose, we defined K init , an important initial number of clusters (equals to 500), and counted the number of occurrences associated to the 10 most populated clusters. Then we diminished K init by one unit and counted again. We stopped the process when the 10 most important clusters represent 80% of the occurrences ( K algo = K init ). We denote by the j th cluster for a given clustering algorithm with j = {1, ..., K algo }. The clusters are associated with their corresponding gene list . ii) Three hierarchical clusterings are performed after generating MVs in proportion τ in the data, the first one without replacing data – in this case, the normalized Euclidean distance (Eq.2) is used -, the second one after estimating the missing data by the kNN method (Eq.1), and the third one after replacing the missing data by zero. For each resulting tree, K algo clusters are defined. The clusters are associated with their corresponding gene list , with j' = {1, ..., K algo }. iii) Finally, to estimate the CPP index, we searched for each cluster the closest cluster. For each clustering algorithm ( algo ), the corresponding cluster is selected as the maximum number of genes from the gene list found in . Then, the Conserved Pairs Proportion (CPP) is computed as follow for one simulation: where . The term is the Kronecker symbol, i.e . it is equal to 1 when the genes i and i' in the two gene lists are identical, otherwise 0. G denotes the total number of genes. This index takes the maximal value 1 when the clusterings RC and GR are identical. In addition, a variation of the tree topology may induce a CPP -variation. If the remaining genes of a cluster are in the direct neighbour clusters, the use of CPP can bias the analysis. Thus, we characterized the CPP f ratio to consider the f closest clusters of the cluster. The computation of CPP f ratio is based on the previous ratio and corresponds to the f clusters which are the closest to the winning cluster. From a selected , the upper node of the dendrogram is examined. If the number of clusters linked to this node is inferior to f , the upper node is selected. This process is performed until the number of clusters is inferior or equals to f . The last node tested ( i.e . with the number of clusters inferior or equal to f ) is used to compute the CPP f ratio. Authors' contributions AdB conceived of the study and carried out the MVs generation and the hierarchical clustering results. SH worked on the statistical analysis. AM has the initial idea of evaluating the MV influence on clustering, and participated in its design and coordination. All authors read and approved the final manuscript.

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544863

Development of a real-time QPCR assay for the detection of RV2 lineage-specific rhadinoviruses in macaques and baboons

Background Two distinct lineages of rhadinoviruses related to Kaposi's sarcoma-associated herpesvirus (KSHV/HHV8) have been identified in macaques and other Old World non-human primates. We have developed a real-time quantitative PCR (QPCR) assay using a TaqMan probe to differentially detect and quantitate members of the rhadinovirus-2 (RV2) lineage. PCR primers were derived from sequences within ORF 60 and the adjacent ORF 59/60 intergenic region which were highly conserved between the macaque RV2 rhadinoviruses, rhesus rhadinovirus (RRV) and Macaca nemestrina rhadinovirus-2 (MneRV2). These primers showed little similarity to the corresponding sequences of the macaque RV1 rhadinoviruses, retroperitoneal fibromatosis herpesvirus Macaca nemestrina (RFHVMn) and Macaca mulatta (RFHVMm). To determine viral loads per cell, an additional TaqMan QPCR assay was developed to detect the single copy cellular oncostatin M gene. Results We show that the RV2 QPCR assay is linear from less than 2 to more than 300,000 copies using MneRV2 DNA, and is non-reactive with RFHVMn DNA up to 1 billion DNA templates per reaction. RV2 loads ranging from 6 to 2,300 viral genome equivalent copies per 10 6 cells were detected in PBMC from randomly sampled macaques from the Washington National Primate Research Center. Screening tissue from other primate species, including another macaque, Macaca fascicularis , and a baboon, Papio cynocephalus , revealed the presence of novel rhadinoviruses, MfaRV2 and PcyRV2, respectively. Sequence comparison and phylogenetic analysis confirmed their inclusion within the RV2 lineage of KSHV-like rhadinoviruses. Conclusions We describe a QPCR assay which provides a quick and sensitive method for quantitating rhadinoviruses belonging to the RV2 lineage of KSHV-like rhadinoviruses found in a variety of macaque species commonly used for biomedical research. While this assay broadly detects different RV2 rhadinovirus species, it is unreactive with RV1 rhadinovirus species which commonly co-infect the same primate hosts. We also show that this QPCR assay can be used to identify novel RV2 rhadinoviruses in different primate species.

Background Members of the Rhadinovirus genus of the gammaherpesviruses are lymphotrophic and are associated with a variety of lymphoproliferative diseases. Herpesvirus saimiri (HVS), the prototype rhadinovirus isolated from the South American squirrel monkey, causes fulminant T-cell lymphomas in closely related host species [ 1 ]. Kaposi's sarcoma-associated herpesvirus (KSHV)/human herpesvirus 8, the only known human rhadinovirus, is associated with classical and AIDS-related Kaposi's sarcoma, primary effusion lymphoma and multicentric Castleman's disease [ 2 ]. Other rhadinoviruses have been isolated from ruminants, including wildebeest, sheep and cows, that are associated with malignant catarrhal fever, a lymphoproliferative syndrome [ 3 , 4 ]. We and others have demonstrated the existence of two distinct lineages of KSHV-like rhadinoviruses in Old World non-human primates [ 5 , 6 ]. The rhadinovirus-1 (RV1) lineage includes KSHV and closely related homologs infecting different Old World non-human primate species. In macaques, the RV1 lineage is represented by retroperitoneal fibromatosis herpesvirus (RFHV) that was identified in retroperitoneal fibromatosis (RF) tumor lesions of two macaque species at the Washington National Primate Research Center (WaNPRC) [ 7 , 8 ]. The RV2 lineage in macaques includes rhesus rhadinovirus (RRV) which was first identified in co-cultures of peripheral blood mononuclear cells (PBMC) of rhesus macaques ( M. mulatta ) in the New England National Primate Research Center (NENPRC) [ 9 ] and pig-tailed macaque rhadinovirus/ M. nemestrina RV2 (MneRV2) [ 5 , 10 , 11 ]. While sequence analysis of the RRV genome demonstrated a close similarity to KSHV [ 12 , 13 ], phylogenetic analysis of multiple gene sequences has grouped RRV and the closely related MneRV2 within the RV2 lineage distinct from RFHV and KSHV [ 5 ]. Although RV2 rhadinoviruses have been identified in all Old World non-human primates tested, including gorillas and chimpanzees, no evidence of a human homolog has so far been found [ 6 , 14 - 17 ]. While complete genomic sequences have been obtained for two closely related strains of the RV2 lineage rhadinovirus of rhesus macaques, RRV strain H26-95 from the NENPRC [ 13 ] and RRV strain 17577 from the Oregon National Primate Research Center (ONPRC) [ 12 ], little information is known regarding the sequences of RV2 rhadinoviruses from other macaque species, and assays to detect these rhadinoviruses have not been developed. Quantitative real-time PCR assays (QPCR) have been developed to specifically detect RRV in rhesus macaque samples [ 18 , 19 ], but these assays have not be shown to cross to other RV2 rhadinovirus species. Since the WaNPRC and other primate research centers in the US and abroad utilize macaque species other than rhesus for biomedical research, we decided to obtain sequence information from the RV2 rhadinovirus of pig-tailed macaques, MneRV2, in order to develop a general assay to detect RV2 rhadinoviruses from different macaque species. Our strategy was to identify gene sequences that were highly conserved between different RV2 species but not conserved within macaque RV1 rhadinoviruses, such as RFHVMn or RFHVMm, which are sometimes found in conjunction with RV2 rhadinovirus infections. Previous nucleotide sequence information for MneRV2 consisted only of a region of the DNA polymerase which had significant sequence similarity with the macaque RV1 rhadinoviruses, and therefore was unsuitable for the desired assay [ 5 ]. We analyzed several regions of the RV1 and RV2 rhadinovirus genomes as targets for a general RV2 specific assay and identified the ORF 59/60 junctional region as a suitable target. This region was highly conserved within macaque RV2 rhadinovirus species but not within macaque RV1 rhadinoviruses. In this paper, we report the development of a sensitive and specific TaqMan QPCR assay and its use in detecting and quantitating RV2 rhadinoviruses from different primate species. Results Identification of the ORF 59/60 junctional region from the RV1 and RV2 rhadinovirus species from Macaca nemestrina , RFHVMn and MneRV2 The ORF 59 and ORF 60 genes show high levels of homology between the related rhadinoviruses, KSHV and RRV, with 52% and 70% identity at the amino acid level, respectively [ 13 ]. Using the CODEHOP approach [ 20 , 21 ], we developed degenerate primers targeting conserved amino acid motifs "RDEL" (ORF 60) and "PQFV" (ORF 59) that would enable the amplification and sequence analysis of the ORF 59/60 junctional region of novel RV1 and RV2 rhadinovirus species as described in Materials and Methods. The CODEHOP primers were used in PCR amplification of DNA obtained from spleen tissue from 442N, a M. nemestrina , which has been previously shown to contain a co-infection of both MneRV-2 and RFHVMn rhadinoviruses [ 5 ]. PCR products from both MneRV2 and RFHVMn were obtained as described in Materials and Methods. Sequence analysis revealed a close similarity between the 833 bp of the ORF59/60 junctional region between the "RDEL" and "PQFV" motifs of MneRV2 and the corresponding region of RRV, with an 87% nucleotide identity. The 834 bp sequence of the RFHVMn junctional region was 67% identical to the corresponding region of KSHV and 60% identical to the RRV sequence. Phylogenetic analysis using DNA maximum-likelihood demonstrated a close clustering of the MneRV2 and RRV sequences, while the RFHVMn sequence clustered with the KSHV ORF59/60 sequence, as expected for the macaque homolog of KSHV (Figure 1 ). Figure 1 Phylogenetic analysis of the nucleotide sequences of the ORF59/60 junctional region from various rhadinoviruses . Sequences of the PCR products obtained using CODEHOP PCR primers from the rhadinoviruses MneRV2 ( M. nemestrina ), MfaRV2 ( M. fascicularis ), PcyRV2 ( Papio cynocephalus ) and RFHVMn ( M. nemestrina ) were aligned with the corresponding published sequences for KSHV ( homo sapiens ; U93872, bp 96678–97514), RRV ( M. mulatta ; AF083501, bp 92374–93205), and HVS (squirrel monkey, HSGEND, bp 81608–82613) using ClustalW. Phylogenetic analysis was performed using the DNA maximum likelihood procedure from Phylip. The division of New and Old World primate hosts is indicated. The RV1 and RV2 lineages of the Old World primate rhadinoviruses are shown. Novel viruses identified with the RV2 QPCR assay are underlined. TaqMan quantitative PCR (QPCR) assay specific for RV2 rhadinoviruses Multiple alignment of the RRV and MneRV2 nucleotide sequences revealed large regions of identical sequences within both the ORF 59 and ORF 60 coding regions and the ORF 59/60 intergenic region. As shown in Figure 2 , a region of 71 identical nucleotides in the MneRV2 and RRV sequences was identified at the 3' end of the ORF 60 gene and the adjacent intergenic region. This region was only 43% conserved with the corresponding sequence of RFHVMn. Using Primer Express software (Applied Biosystems), a set of PCR primers (RV2a and RV2b) and a probe (RV2-FAM) were identified for a TaqMan QPCR assay (71 bp amplicon) which would specifically detect these macaque RV2 rhadinoviruses and not cross to known RV1 rhadinoviruses (Fig. 2 and Table 1 ). Figure 2 Primer location and specificity of the RV2 QPCR assay . Corresponding sequences from the end of ORF 60 and the adjacent intergenic region from different rhadinoviruses (see legend to Figure 1) were aligned. Rhadinovirus species and lineages are indicated. The primer set and probe were designed from the RRV and MneRV2 sequences. The RV2a primer and RV2-FAM probe were derived from the sense strand, as shown, while the RV2b primer was derived from the antisense strand. The alignment shows the mismatches between the primer and probe sequences and the MfaRV2 and PcyRV2 sequences identified with the RV2 assay in this study. Dots represent residues identical to those in the RRV sequence, and highlight the similarity of the primer sequences within the RV2 lineage of rhadinoviruses and the dissimilarity with members of the RV1 lineage of rhadinoviruses. Table 1 PCR primers Primer 1 Gene Target Sequence 2 RV2 QPCR Assay (Figure 2) RV2a RV2 ORF 60 5'-TCTGAATATGTCACATCCGTTCATA-3' RV2b RV2 ORF 59/60 intergenic 5'-GGCCCGGAAAATGAGTAACA-3' RV2-FAM 3 RV2 ORF 60 and 59/60 intergenic 5'-(6-FAM)-TGATCTGTAGTCCCCATGTGTCC-(BHQ-1)-3' OSM QPCR Assay (Figure 3) OSMa Exon 3 OSM 5'-CCTCGGGCTCAGGAACAAC-3' OSMb Exon 3 OSM 5'-GGCCTTCGTGGGCTCAG-3' OSM-FAM Exon 3 OSM 5'-(6-FAM)-TACTGCATGGCCCAGCTGCTGGACAA-(BHQ-1)-3' ORF 59/60 CODEHOP Primers RDELa 4 ORF 60 bias 5 KSHV 5'-CTTGCCAACGATTACATTTCCAGRGAYGARCT-3' SRDEa 4 ORF 60 bias RRV 5' CTGGCTAACGACTACATCTCCAGRGAYGARCT-3' NFFEa ORF 60 bias KSHV 5'-GGCAGTTTCAAGGCTGTGAATTTYTTYGARCG-3' PQFVb 6 ORF 59 bias KSHV 5'-CCGTAAGAAATGGTGGTCCTGACRAAYTGNGG-3' QFVRb 6 ORF 59 bias RRV 5'-CCGTAGGCGATGGTCGTCCTAACRAAYTGNGG-3' CFICb ORF 59 bias RRV 5'-TACAAAATACAGCGAGTGATANATRAARCA-3' Gene-Specific Primer MPVDb ORF 59 (RFHV/KSHV) 7 5'-TGAAAATCCACAGGCATGAT-3' 1 The terminal "a" or "b" in the primer name indicates the plus or minus sense of the gene transcription, respectively. 2 IUB code for ambiguous nucleotides: R = A or G; Y = C or T; N = A, C, G, or T 3 FAM indicates a TaqMan dual-labeled probe with the fluorescent dye 6-FAM at the 5' end and the "black hole quencher" (BHQ) dye at the 3' end. 4 These CODEHOP primers target the same motif but are biased differently (see below). 5 "bias" indicates that the 5' consensus region of the CODEHOP primer was derived from a particular sequence" see [20]. 6 These CODEHOP primers target the same motif but are biased differently. 7 This primer sequence is identical to the RFHVMn, RFHVMm and KSHV sequences TaqMan QPCR assay for the cellular gene, oncostatin M, to determine cell number In order to determine viral copy number per cell, an additional TaqMan QPCR assay was developed to detect a single copy cellular gene, oncostatin M (OSM) [ 22 ]. We had previously determined the sequence of the OSM gene in an African green monkey which was highly conserved with the human gene (unpublished results). Using PCR primers derived from consensus sequences of the human and monkey gene, we determined the sequence of the entire OSM coding sequence of the M. nemestrina OSM gene (data not shown). Multiple alignment of the human, monkey and macaque OSM sequences revealed a region within exon 3 which was highly conserved. Using Primer Express software, a set of primers (OSMa and OSMb; 76 bp amplicon) and a probe (OSM-FAM) were identified (Fig. 3 and Table 1 ) which could be used to detect OSM DNA from macaque, monkey and human sources allowing quantitation of cell number in tissue samples. Figure 3 Primer location and specificity for the OSM QPCR assay to detect cell copy number . Corresponding sequences from the third exon of the OSM gene from human, African green monkey (AGM) and pig-tailed macaque (Mn) are aligned with the positions of the OSM primer set and probe indicated. The OSMa primer and OSM-FAM probe were derived from the sense strand, as shown, while the OSMb primer was derived from the antisense strand. QPCR Assay Development and Characterization The RV2 and OSM QPCR assays were optimized using DNA obtained from the spleen of a rhesus macaque, MmuA01111, which we have previously determined to contain RRV DNA in a background of macaque genomic DNA [ 23 ]. Initially, a temperature gradient PCR was performed to determine annealing temperatures that gave a single PCR product. An annealing temperature of 62°C was chosen because that temperature was optimal in both the RV2 and OSM assays (data not shown). The magnesium chloride, nucleotide, primer and probe concentrations were then varied to determine conditions which gave optimal efficiency. Standard curves were obtained from a dilution series using the optimal conditions for the RV2 and OSM assays as described in Material and Methods. For the RV2 assay, purified MneRV2 DNA obtained from a lytic infection of rhesus primary fetal fibroblasts (RPFF) was assayed in duplicate using 4-fold dilutions. As seen in Figure 4A , the assay was linear across a range of dilutions from less than 2 to more than 3.0 × 10 5 copies of MneRV2, with a slope of -3.320 (100% efficiency) and r 2 = 0.997. For the OSM assay, MmuA01111 genomic DNA was assayed in duplicate using 4-fold dilutions, with the amount of DNA tested ranging from 0.06 ng (corresponding to 20 diploid OSM gene copies: equivalent to 10 cells) up to 1 μg (corresponding to 3.2 × 10 5 diploid OSM gene copies: equivalent to 1.6 × 10 5 cells). The assay was linear across this range with a slope of -3.322 (100% efficiency) and r 2 = 0.999 (Fig. 4B ). Figure 4 Standard curves obtained from the RV2 rhadinovirus and OSM reference cellular gene assays . A) The standard RV2 assay was performed on purified MneRV2 DNA in a series of four-fold dilutions over the range of 2 copies to 3.0 × 10 5 copies of MneRV2. (slope = -3.320, 100% efficiency; r 2 = 0.997). B) The standard OSM assay was performed on MmuA01111 spleen DNA in a series of four-fold dilutions over the range of 0.06 ng (20 diploid OSM gene copies) to 1 μg (3.2 × 10 5 diploid OSM gene copies). (slope = -3.322, 100% efficiency; r 2 = 0.999) To determine the linearity of the RV2 assay with a biologically relevant sample, DNA from the spleen of MmuA01111 which contains cells naturally infected with RRV was subjected to 4-fold dilutions while keeping genomic DNA levels constant at 1 μg per reaction by the addition of DNA from an uninfected animal. The results demonstrate that the assay was linear from less than 66 copies of RRV (256-fold dilution of MmuA01111 DNA in uninfected macaque DNA) to more than 1.7 × 10 4 RRV copies per μg genomic DNA (MmuA01111 DNA undiluted) with a slope of -3.318 (100% efficiency) and r 2 = 0.988 (Fig. 5 ). This shows that the viral load determination would be accurate down to 410 RRV genomes/10 6 cells which is 1 viral copy per 2400 cells. The upper limit in this assay was determined to be greater than 110,000 viral genomes/10 6 cells which is the number of viral copies of RRV in 1 μg of DNA from the MmuA01111 spleen. Figure 5 Biologically relevant standard curve obtained with the RV2 rhadinovirus assay using RV2 DNA in a constant amount (1 μg) of genomic DNA . DNA from MmuA01111 which was naturally infected with RRV was assayed in duplicate in four-fold dilutions made with uninfected macaque DNA. (slope = -3.318, 100% efficiency; r 2 = 0.988]. To ensure that the RV2 assay does not detect RV1 viruses, the assay was performed using DNA from the human and macaque RV1 rhadinoviruses. A DNA sample from the KSHV infected BCBL-1 cell line [ 24 ] containing approximately 4 × 10 6 copies of the KSHV genome and a sample containing 10 9 copies of a PCR product of the ORF59/60 junctional region from RFHVMn were used as templates in the RV2 assay. The RV-2 QPCR assay was negative for these templates under the standard reaction conditions. Identification of a novel RV2 rhadinovirus in Macaca fascicularis using the RV2 QPCR assay Since the RV2 QPCR assay was based on consensus sequences shared by two distinct members of the RV2 lineage from M. mulatta and M. nemestrina , RRV and MneRV2, respectively, we tested to see if this assay could be used to identify a novel RV2 rhadinovirus in M. fascicularis . DNA was obtained from spleen tissue of Mfa95044, an M. fascicularis from the Tissue Distribution Program at the WaNPRC. Approximately 250 ng of spleen DNA produced a positive result in the RV2 QPCR assay with an average cycle threshold (C T ) of 31.9 cycles. In order to prove that the assay detected a novel rhadinovirus, CODEHOP primers were used in a PCR amplification reaction with the Mfa95044 spleen DNA to obtain the ORF59/60 intergenic region of this rhadinovirus as described in the Materials and Methods. An 832 bp PCR product was obtained and sequenced. A comparison of this sequence with the corresponding region from RRV and MneRV2 showed 94% and 86% nucleotide identity, respectively. The nucleotide identity with the corresponding region in RFHV and KSHV was only 59% and 60%, respectively. Phylogenetic analysis showed a close clustering of the M. fascicularis sequence with the RRV sequence and a more distant relationship with the MneRV2 sequence, confirming its origin from an RV2 rhadinovirus of M. fascicularis , herein termed MfaRV2 (Figure 1 ). The evolutionary relationship of these rhadinovirus species mirrors that determined for the host macaque species themselves, where the M. mulatta and M. fascicularis have been shown to be more closely related to each other than to M. nemestrina [ 25 ]. Our data supports the hypothesis of a co-speciative divergence of the Old World primate rhadinoviruses and their hosts [ 26 ] Identification of a novel RV2 rhadinovirus in the baboon, Papio cynocephalus , using the RV2 QPCR assay To further determine the specificity of the RV2 QPCR assay, DNA obtained from lymphocytes of baboon Pcy78404 was tested for the presence of a related RV2 rhadinovirus species under the standard assay conditions. Approximately 250 ng of lymphocyte DNA produced a positive result with an average C T of 33.8 cycles. In order to determine the identity of the reactive DNA species, CODEHOP primers were used in a PCR reaction with the baboon DNA as template as described in Materials and Methods. A product was obtained that yielded an 834 bp sequence which was 83% identical to the ORF59/60 intergenic region of each of the macaque RV2 rhadinoviruses, RRV, MneRV2 and MfaRV2, and 58% identical to the corresponding region in both KSHV and RFHVMn. The baboon sequence clustered with the macaque RV2 rhadinovirus sequences confirming its origin from an RV2 rhadinovirus of the baboon ( Papio cynocephalus ), herein termed PcyRV2. Phylogenetic analysis demonstrated that while PcyRV2 clustered within the RV2 rhadinovirus lineage, it branched off separately from the macaque RV2 rhadinoviruses as expected for a baboon rhadinovirus (Fig. 1 ). Previously, an RV2 rhadinovirus, PapRV2, was detected in a baboon ( Papio anubis ) [ 27 ], and a partial sequence of the DNA polymerase was obtained. In order to compare PcyRV2 with PapRV2, we utilized CODEHOP PCR primers [ 7 ] to amplify a region of the polymerase gene of PcyRV2 that could be compared to the sequence available for PapRV2. DNA sequence for 352 bp of the DNA polymerase gene was obtained. An alignment of this sequence with the corresponding sequence of the PapRV2 rhadinovirus revealed a 97% sequence identity with 11 nucleotide differences which altered one amino acid. Specificity of the RV2 QPCR assay In order to compare the ability of the RV2 QPCR assay to detect different rhadinovirus templates, test samples containing roughly equivalent viral copy numbers in a background of genomic DNA were prepared. DNA from purified MneRV2, DNA from MmuA01111 spleen which contains RRV, and DNA from Mfa95044 spleen which contains MfaRV2 were diluted in DNA from a virus negative macaque to have approximately the same virus load as that found in the baboon lymphocyte DNA containing PcyRV2. As shown in Figure 6 , all four samples have relatively similar levels of the different viruses, as indicated by the similar C T values (30.3, MneRV2; 30.8, RRV; 31.6, MfaRV2; and 33.2, PcyRV2). The cumulative fluorescence curve for the MneRV2 and RRV samples were superimposable with slopes typical of those seen in the assays performed in Figures 4 and 5 which showed amplification efficiencies of 100%. In contrast, both the M. fascicularis and baboon templates produced fluorescence curves with significantly decreased slopes, indicating lower amplification efficiencies. The efficiencies of these PCR reactions were calculated to be approximately 81% (r 2 = 0.900) for the MfaRV2 and 72% (r 2 = 0.929) for the PcyRV2, however, the low levels of virus in these samples made it difficult to accurately determine the efficiencies, as indicated by the correlation coefficients. Figure 6 Comparison of the RV2 QPCR assay using different rhadinovirus templates diluted in genomic DNA . The PcyRV2 results were obtained using 1 μg of spleen DNA from baboon, Pcy78404, naturally infected with PcyRV2. The other rhadinovirus DNA templates were diluted in uninfected macaque genomic DNA to yield approximately equivalent C T values. The MneRV2 results were obtained using DNA from purified MneRV2 in macaque genomic DNA. The RRV results were obtained using DNA from spleen of MmuA01111, naturally infected with RRV. The MfaRV2 results were obtained using DNA from spleen of Mfa95044, naturally infected with MfaRV2. The released reporter fluorophore is plotted as a function of the amplification cycle number. The novel ORF 59/60 intergenic regions of MfaRV2 and PcyRV2 were aligned with the corresponding sequences of RRV, MneRV2, RFHVMn, and KSHV. Also aligned was a partial sequence of the ORF 59/60 region obtained from RFHVMm (see Materials and Methods). As shown in Figure 2 , the MfaRV2 sequence contained single nucleotide mismatches with the RV2a primer and RV2-FAM probe; an exact match was seen with the RV2b primer. The PcyRV2 sequence contained the same nucleotide mismatches seen in MfaRV2 and additionally had a second nucleotide mismatch within both the RV2a primer and the RV2-FAM probe. An additional mismatch was found between the PcyRV2 sequence and the RV2b primer. These nucleotide mismatches correlated with the decreased amplification efficiency of the assay with this template, as shown in Figure 6 . RV2 QPCR screen of the prevalence of RV2 rhadinoviruses in macaques housed at the WaNPRC DNA samples were obtained from PBMC of a random assortment of thirty macaques housed at the WaNPRC and analyzed using the standard RV2 and OSM QPCR assays. While all of the samples were positive for the single copy OSM gene, only six of the thirty macaques were positive for the presence of an RV2 rhadinovirus. In all of these six cases, both duplicate reactions in the assay were positive yielding average viral loads of 6–2300 per 10 6 cells (Table 2 ). However, in four of the six positive macaques, the RV-2 assay result was low and outside the linear range of the assay. Table 2 RV2 rhadinovirus load in PBMC of 30 healthy macaques in the WaNPRC colony Animal RV2 DNA load in PBMC (Viral copies per 10 6 cells; mean ± SD 1 ) M. nemestrina (pig-tail) A98078 2300 ± 1200 F94132 650 ± 460 A98079 340 ± 49* 90152 5.8 ± 4.2* 16 other M. nemestrina Below the limit of detection M. fascicularis (crab-eating) 98023 250 ± 96* 7 other M. fascicularis Below the limit of detection Unknown macaque species 98062 57 ± 52* 1 other unknown species Below the limit of detection % of all macaques testing positive 6/30 = 20% 1 Samples (1 μg) were assayed in duplicate and the means were determined. Standard deviations were calculated using the sum of the errors of the viral and OSM copy number determinations, as described in Materials and Methods. * These results, while positive for both duplicates, were outside of the linear range of the assay. Discussion We have developed a TaqMan probe-based QPCR assay to quantitate the viral load of macaque rhadinoviruses belonging to the RV2 lineage of KSHV-like rhadinoviruses. The primers and probe for this assay were based on sequences within the 3' end of the ORF 60 coding sequence and the ORF 59/60 intergenic region which were identical between the pig-tailed and rhesus macaque rhadinoviruses, MneRV2 and RRV, respectively, but were not conserved with the corresponding macaque viruses from the RV1 lineage of KSHV-like rhadinoviruses RFHVMn and RFHVMm. We have also developed a TaqMan probe-based QPCR assay targeting the single copy cellular gene, OSM, to serve as an internal control for quantitating cell copy number. Both assays were designed to give 100% PCR efficiency at the same annealing temperature, are linear over more than 4 orders of magnitude and are sensitive enough to detect less than 20 copies of the DNA target. The RV2 assay is able to accurately detect less than 66 copies of viral DNA in a genomic DNA background, even when the viral load is as low as 1 copy per 2400 cells. Quantitation of the cellular DNA and viral DNA copy numbers in a tissue sample provides a suitable method for comparing viral loads, even between samples of unknown purity or degradation status. Because of the small size of the amplicons for both assays, OSM (76 bp) and RV2 (71 bp), viral loads can even be determined in formalin-fixed paraffin embedded tissue in which significant degradation of the DNA has occurred. Due to the similarities in sequence of the human, macaque and African green monkey OSM genes, the OSM QPCR assay may be suitable for quantitation of DNA in tissue from a number of other Old World primate species. We have screened DNA from a number of random PBMC samples from macaques at the WaNPRC for the presence of an RV2 rhadinovirus. We detected RV2 rhadinovirus DNA in 6 of 30 macaques; 4 of 20 M. nemestrina , 1 of 7 M. fascicularis and 1 of 2 macaques whose species is not known. In these macaques, the viral copy number was determined to range from 6–2300 per 10 6 cells. Although the copy number in the single positive M. fascicularis was calculated to be 250 viruses per 10 6 cells, this would be a low estimate due to the 81% efficiency of the amplification of that template, as discussed above. Our results for RV2 rhadinoviruses in the macaque species tested at the WaNPRC were similar to those determined for RRV in rhesus macaques at the Tulane National Primate Research Center [ 18 ]. In the Tulane study, a QPCR assay developed against the interleukin-6 homolog of RRV found infrequent and low levels of RRV in PBMC of healthy and SIV-infected rhesus macaques. Only two healthy macaques had detectable RRV DNA with levels of 320 and 880 genomes per 10 6 cells. In the other 28 animals, the RRV load was below the level of detection. While RRV was detected more frequently in SIV-infected macaques in this study, the virus load was similar to that seen in healthy macaques. The Tulane RRV assay had a similar sensitivity to our RV2 assay, with a lower limit of one RRV genome per 10,000 cell equivalents however, it was designed to specifically target only RRV while our RV2 assay is capable of detecting RRV, MneRV2 and other macaque and baboon rhadinoviruses. In this report, we have used the RV2 assay to detect novel RV2 rhadinovirus homologs in both the spleen of a crab-eating macaque ( Macaca fascicularis ) and the lymphocytes of a baboon ( Papio cynocephalus ). The standard RV2 assay had an amplification efficiency less than 100% with the M. fascicularis and P. cynocephalus templates which cautions against its use for accurate quantitation of the MfaRV2 and PcyRV2 rhadinoviruses. The primer and probe binding regions of these two rhadinoviruses showed nucleotide mismatches which correlate with the decrease amplification efficiency of the assay. We have shown that the RV2 QPCR assay is capable of detecting a novel RV2 rhadinovirus, PcyRV2, in a baboon. Previously, an RV2 rhadinovirus, PapRV2, was also detected in baboons by others [ 27 ] using the degenerate PCR primer approach targeting the DNA polymerase gene that we had originally developed to detect novel herpesviruses [ 7 ]. In order to compare the two baboon viruses, we have sequenced a region of the DNA polymerase gene of PcyRV2. An alignment of this sequence with the corresponding sequence of the PapRV2 rhadinovirus revealed a 97% sequence identity with 11 nucleotide differences. This nucleotide similarity is consistent with the origin of these two viruses from two related species of baboons; the PcyRV2 rhadinovirus was isolated from the baboon species Papio cynocephalus , while the PapRV2 rhadinovirus was isolated from the baboon species Papio anubis . Conclusions In this report, we describe a QPCR assay which provides a quick and sensitive method for screening RV2 rhadinoviruses found in the variety of non-human primate species commonly found in the National primate centers. While this assay broadly detects different RV2 rhadinoviruses species, it is unreactive with several RV1 rhadinovirus species. We also show that this QPCR assay can be used to identify novel RV-2 rhadinoviruses in primates. Methods and Materials Animals Fresh frozen spleen tissue samples from Macaca nemestrina (Mne) 442N were provided by R. Shibata while at the National Institutes of Health, Bethesda, MD. This pig-tailed macaque had been experimentally infected with a pathogenic SHIV strain [ 28 ]. We have previously obtained PCR evidence for the presence of both RV1 and RV2 macaque rhadinoviruses, RFHVMn and MneRV2, respectively, in RF tumor and spleen tissue of this animal [ 5 ]. Fresh frozen RF tumor tissue from Macaca mulatta (Mmu) YN91-224, an SIV-infected rhesus macaque diagnosed with RF, was kindly provided by H. McClure, Yerkes National Primate Research Center. Fresh frozen spleen tissue samples were also obtained from Macaca mulatta (Mmu) A01111 at the WaNPRC, a rhesus macaque that had been experimentally infected with SIV which we have shown to be co-infected with the RV1 and RV2 macaque rhadinoviruses, RFHVMm and RRV, respectively (unpublished observations). Fresh frozen spleen tissue from a Macaca fascicularis (Mfa) 95044 and lymphocytes from a baboon ( Papio cynocephalus ) (Pcy78404) were kindly provided by H. Bielefeldt-Ohmann and C.-C. Tsai, respectively, from the WaNPRC. DNA from the PBMC of thirty random healthy colony macaques was also obtained from the virus screening program at the WaNPRC. Cells The KSHV-infected pleural effusion lymphoma cell line, BCBL-1, was obtained from D. Ganem (Howard Hughes Institute – UCSF), and was carried in RPMI 1640 supplemented with 10% fetal bovine serum, penicillin, streptomycin, glutamine, and β-mercaptoethanol. Rhesus primary fetal fibroblasts (RPFF) were kindly provided by Dr. Michael Axthelm (ONPRC). Rhadinovirus An isolate of MneRV2, was obtained from an M. nemestrina , MneJ97167, at the WaNPRC. The MneRV2 was used to infect cultures of RPFF and viral particles were harvested from culture supernatent by high speed centrifugation. Viral DNA used as positive controls in the PCR assays was obtained by disruption of the viral particles using phenol/chloroform and ethanol precipitation. DNA samples DNA was extracted from frozen tissues using standard proteinase K-phenol/chloroform extractions and concentrated by ethanol precipitation. PCR amplification primers The protein sequences of the ORF 59 and ORF 60 genes from KSHV and RRV were aligned using ClustalW. The consensus-degenerate hybrid oligonucleotide primer (CODEHOP) technique [ 20 , 21 ] was used to design two sets of degenerate PCR primers within both ORF 59 and ORF 60 that would enable the amplification and sequence analysis of the ORF 59/60 junctional region of novel RV1 and RV2 rhadinovirus species. The ORF 59 and ORF 60 genes are arranged in the same transcriptional orientiation in both RRV and KSHV. Two sense-strand CODEHOP primers, RDELa and SRDEa contained nucleotides encoding the highly conserved amino acid motif, Arg-Asp-Glu-Leu (RDEL; 8 fold degenerate), in ORF 60. Primer RDELa was biased toward the RV1 rhadinoviruses and contained a 5' consensus region derived from the KSHV sequence (Accession no. NC_003409). Primer SRDEa was biased toward the RV2 rhadinoviruses and contained a 5' consensus region derived from the RRV sequence (Accession no. AF210726). Two antisense-strand CODEHOP primers, PQFVb and QFVRb contained all coding possibilities for the highly conserved motif, Pro-Gln-Phe-Val (PQFV) in ORF 59 (16 fold degenerate), and were biased to the KSHV and RRV sequences, respectively (see Table 1 ). An additional anti-sense strand CODEHOP primer, CFICb (16 fold degenerate), was designed from a Cys-Phe-Ile-Cys (CFIC) motif in the ORF 59 gene, downstream of the PQFV motif and contained all coding possibilities for the CFIC motif and was biased to RRV. Amplification of the ORF 59/60 junctional region of novel rhadinoviruses To obtain the ORF 59/60 junctional regions between the RDEL motif of ORF 60 and the PQFV motif of ORF 59 of MneRV2, PcyRV2, RFHVMn, and RFHVMm, DNA was obtained from different sources and used in PCR amplification with different CODEHOP PCR primers. Reactions were performed in 1 μM forward and reverse primers, 200 μM each dNTP, 20 mM Tris-HCl (pH 8.4), 50 mM KCl, and 2.5 units Platinum Taq polymerase (Invitrogen) using a 55–70°C annealing temperature gradient (BioRad Icycler). For MneRV2, PCR amplification was performed on Mne442N spleen DNA using primers RDELa and PQFVb. For PcyRV2, PCR amplification was performed on lymphocyte DNA from baboon Pcy78404, using SRDEa and QFVRb. In both cases an ~830 bp PCR fragment was obtained and sequenced. To obtain the sequence of RFHVMn which had a low copy number, it was necessary to amplify the RDEL-PQFV region in two fragments. A CODEHOP primer NFFEa (See Table 1 ), downstream of the RDEL motif was designed and used in conjunction with PQFVb to amplify an ~600 bp product from the Mne442N DNA. From the sequence of this product a specific primer, MPVDb, was derived and used in conjunction with RDELa to obtain an overlapping ~400 bp product. A similar strategy was used with RF tumor DNA obtained from MmuYN91-224 to obtain sequence from the ORF 59/60 junctional region of RFHVMm, however, only the sequence from NFFEA to PQFVB was obtained for comparison purposes. The ORF 59/60 junctional region of MfaRV2 was also obtained in two fragments. An ~400 bp PCR product was obtained after amplification of spleen DNA from Mfa95044, using the RV2 QPCR assay primer RV2b (see QPCR assay below and Table 1 ) and CODEHOP primer RDELa. An overlapping ~1400 bp PCR product was obtained using the RV2 QPCR assay primer, RV2a, in conjunction with an additional CODEHOP primer, CFICb. Sequence alignment and phylogenetic analysis Nucleotide sequences were aligned using ClustalW and analyzed using the DNA maximum-likelihood program from the Phylip package, version 3.62 (University of Washington, Seattle). Phylogenetic tree output was produced using TreeView. Real-time QPCR design The RV2 assay was designed to amplify a 71-bp amplicon from the ORF 59/60 junctional region of macaque viruses belonging to the RV2 rhadinovirus lineage using consensus primers "RV2a" (forward primer 5'-TCTGAATATGTCACATCCGTTCATA-3') and "RV2b" (reverse primer 5'-GGCCCGGAAAATGAGTAACA-3') with a TaqMan probe "RV2" 5'-(6-FAM)-TGATCTGTAGTCCCCATGTGTCC-(BHQ-1)-3' (Table 1 and Figure 1 ). As an internal control for cellular DNA which would allow the determination of the viral copy number per cell, a QPCR assay was developed to detect exon 3 of oncostatin M (OSM), a single copy cellular gene [Rose, 1993 #18]). The OSM assay amplifies a 76-bp amplicon from the macaque OSM gene using "OSMa" (forward primer 5'-CCTCGGGCTCAGGAACAAC-3') and "OSMb" (reverse primer 5'-GGCCTTCGTGGGCTCAG-3') with a TaqMan probe "OSM" 5'-(6-FAM)-TACTGCATGGCCCAGCTGCTGGACAA-(BHQ-1)-3' (Table 1 and Figure 2 ) Reactions (50 μl) contained approximately 250–1000 ng of template DNA, 1 μM forward and reverse primers, 100 nM probe, 200 μM each dNTP, 20 mM Tris-HCl (pH 8.4), 50 mM KCl, and 2.5 units Platinum Taq polymerase (Invitrogen). Magnesium chloride concentrations were 4.0 mM for the RV2 assay and 2.0 mM for the OSM assay. After activation of the polymerase by incubation for 1 minute at 95°C, amplification was performed on a Bio-Rad iCycler equipped with an optical module for 45 cycles of 95°C for 30 s, 62°C for 30 s and 72°C for 30 s. The copy number for each assay was calculated from the cycle threshold (C T ) determined using the Bio-Rad software. The viral load was calculated as a cellular genome copy equivalent by using the formula: Viral load (genome equivalent copies) = Viral copy number/diploid OSM copy number Samples were assayed in duplicate and the means were determined. Standard deviations were calculated using the sum of the errors of the viral and OSM copy number determinations. List of Abbreviations AGM, African green monkey; CODEHOP, consensus-degenerate hybrid oligonucleotide primer; C T , cycle threshold; KSHV/HHV8, Kaposi's sarcoma-associated herpesvirus/human herpesvirus 8; Mfa, Macaca fascicularis ; MfaRV2, Macaca fascicularis rhadinovirus-2; Mm/Mmu, Macaca mulatta ; Mn/Mne, Macaca nemestrina ; MneRV2, Macaca nemestrina rhadinovirus-2; ORF, open-reading frame; OSM, oncostatin M; Pcy, Papio cynocephalus ; PcyRV2, Papio cynocephalus rhadinovirus-2; PCR, polymerase chain reaction; QPCR, quantitative PCR; RFHV, retroperitoneal fibromatosis herpesvirus; RRV, rhesus rhadinovirus; RV1, rhadinovirus-1; RV2, rhadinovirus-2; Competing Interests The author(s) declare that they have no competing interests. Authors' Contribution Design and conception of the study (AGB, TMR); development of the methods for amplification of the ORF59/60 regions (AGB, TMR); Development of the QPCR assays and quantitative analysis (AGB, AMB); Virus isolation and preparation (MET); Sequence analysis, alignment and phylogeny (AGB, AMB, TMR); Manuscript preparation (AGB, AMB, MET, TMR). All authors read and approved the final manuscript.

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