bluuebunny/crossref_metadata_2025 huggingface dataset:
Endocytosis of E-cadherin regulated by Rac and Cdc42 small G proteins through IQGAP1 and actin filaments
Authors: Izumi Genkichi , Sakisaka Toshiaki , Baba Takeshi , Tanaka Shintaro , Morimoto Koji , Takai Yoshimi
Published: July 2004

E-cadherin is a key cell–cell adhesion molecule at adherens junctions (AJs) and undergoes endocytosis when AJs are disrupted by the action of extracellular signals. To elucidate the mechanism of this endocytosis, we developed here a new cell-free assay system for this reaction using the AJ-enriched fraction from rat liver. We found here that non-trans-interacting, but not trans-interacting, E-cadherin underwent endocytosis in a clathrin-dependent manner. The endocytosis of trans-interacting E-cadherin was inhibited by Rac and Cdc42 small G proteins, which were activated by trans-interacting E-cadherin or trans-interacting nectins, which are known to induce the formation of AJs in cooperation with E-cadherin. This inhibition was mediated by reorganization of the actin cytoskeleton by Rac and Cdc42 through IQGAP1, an actin filament-binding protein and a downstream target of Rac and Cdc42. These results indicate the important role of the Rac/Cdc42-IQGAP1 system in the dynamic organization and maintenance of the E-cadherin–based AJs.
Cortactin and Crk cooperate to trigger actin polymerization during Shigella invasion of epithelial cells
Authors: Bougnères Laurence , Girardin Stéphane E. , Weed Scott A. , Karginov Andrei V. , Olivo-Marin Jean-Christophe , Parsons J. Thomas , Sansonetti Philippe J. , Van Nhieu Guy Tran
Published: July 2004

Shigella, the causative agent of bacillary dysentery, invades epithelial cells in a process involving Src tyrosine kinase signaling. Cortactin, a ubiquitous actin-binding protein present in structures of dynamic actin assembly, is the major protein tyrosine phosphorylated during Shigella invasion. Here, we report that RNA interference silencing of cortactin expression, as does Src inhibition in cells expressing kinase-inactive Src, interferes with actin polymerization required for the formation of cellular extensions engulfing the bacteria. Shigella invasion induced the recruitment of cortactin at plasma membranes in a tyrosine phosphorylation–dependent manner. Overexpression of wild-type forms of cortactin or the adaptor protein Crk favored Shigella uptake, and Arp2/3 binding–deficient cortactin derivatives or an Src homology 2 domain Crk mutant interfered with bacterial-induced actin foci formation. Crk was shown to directly interact with tyrosine-phosphorylated cortactin and to condition cortactin-dependent actin polymerization required for Shigella uptake. These results point at a major role for a Crk–cortactin complex in actin polymerization downstream of tyrosine kinase signaling.
Relocation of Aurora B from centromeres to the central spindle at the metaphase to anaphase transition requires MKlp2
Authors: Gruneberg Ulrike , Neef Rüdiger , Honda Reiko , Nigg Erich A. , Barr Francis A.
Published: July 2004

Mitotic kinases of the Polo and Aurora families are key regulators of chromosome segregation and cytokinesis. Here, we have investigated the role of MKlp1 and MKlp2, two vertebrate mitotic kinesins essential for cytokinesis, in the spatial regulation of the Aurora B kinase. Previously, we have demonstrated that MKlp2 recruits Polo-like kinase 1 (Plk1) to the central spindle in anaphase. We now find that in MKlp2 but not MKlp1-depleted cells the Aurora B–INCENP complex remains at the centromeres and fails to relocate to the central spindle. MKlp2 exerts dual control over Aurora B localization, because it is a binding partner for Aurora B, and furthermore for the phosphatase Cdc14A. Cdc14A can dephosphorylate INCENP and may contribute to its relocation to the central spindle in anaphase. We propose that MKlp2 is involved in the localization of Plk1, Aurora B, and Cdc14A to the central spindle during anaphase, and that the integration of signaling by these proteins is necessary for proper cytokinesis.
FAK and paxillin
Authors: Schaller Michael D.
Published: July 2004

FAK and paxillin are important components in integrin-regulated signaling. New evidence suggests that these two proteins function in crosstalk between cell–matrix and cell–cell adhesions. Further, new insight suggests that under some conditions these proteins inhibit cell migration, in contrast to their established roles in several cell systems as positive regulators of cell adhesion and migration.
Unique Clinical and Pathological Features in HLA-DRB1*0401–restricted MBP 111–129–specific Humanized TCR Transgenic Mice
Authors: Quandt Jacqueline A. , Baig Mirza , Yao Karen , Kawamura Kazuyuki , Huh Jaebong , Ludwin Samuel K. , Bian Hong-Jin , Bryant Mark , Quigley Laura , Nagy Zoltan A. , McFarland Henry F. , Muraro Paolo A. , Martin Roland , Ito Kouichi
Published: July 2004

Amino acid residues 111–129 represent an immunodominant epitope of myelin basic protein (MBP) in humans with human leukocyte antigen (HLA)-DRB1*0401 allele(s). The MBP 111–129–specific T cell clone MS2-3C8 was repeatedly isolated from a patient with multiple sclerosis (MS), suggesting an involvement of MS2-3C8 T cells in the pathogenesis. To address the pathogenic potential of the MS2-3C8 T cell clone, we generated transgenic (Tg) mice expressing its T cell receptor and restriction element, HLA-DRB1*0401, to examine the pathogenic characteristics of MS2-3C8 Tg T cells by adoptive transfer into HLA-DRB1*0401 Tg mice. In addition to the ascending paralysis typical of experimental autoimmune encephalomyelitis, mice displayed dysphagia due to restriction in jaw and tongue movements and abnormal gait. In accordance with the clinical phenotype, infiltrates of MS2-3C8 Tg T cells and inflammatory lesions were predominantly located in the brainstem and the cranial nerve roots in addition to the spinal cord and spinal nerve roots. Together, these data suggest a pathogenic role of MBP-specific T cells in inflammatory demyelination within the brainstem and cranial nerve roots during the progression of MS. This notion may help to explain the clinical and pathological heterogeneity of MS.
A Role for Thymic Stromal Lymphopoietin in CD4+ T Cell Development
Authors: Al-Shami Amin , Spolski Rosanne , Kelly John , Fry Terry , Schwartzberg Pamela L. , Pandey Akhilesh , Mackall Crystal L. , Leonard Warren J.
Published: July 2004

Thymic stromal lymphopoietin (TSLP) signals via a receptor comprising the interleukin (IL)-7 receptor α chain and a distinctive subunit, TSLP receptor (TSLPR), which is most related to the common cytokine receptor γ chain, γc. We have generated TSLPR knockout (KO) mice and found that although these mice had normal lymphocyte numbers, γc/TSLPR double KO mice had a greater lymphoid defect than γc KO mice. This indicates that TSLP contributes to lymphoid development and accounts for some of the residual lymphoid development in γc KO mice and presumably in patients with X-linked severe combined immunodeficiency. Injection of TSLP into γc KO mice induced the expansion of T and B cells. Moreover, sublethally irradiated TSLPR KO mice showed weaker recovery of lymphocyte populations than wild-type (WT) littermates, even when neutralizing anti–IL-7 antibodies were injected. Interestingly, TSLP preferentially stimulated the proliferation and survival of CD4+ single positive thymocytes and peripheral T cells in vitro. Additionally, CD4+ T cells from TSLPR KO mice expanded less efficiently than WT CD4+ T cells in irradiated hosts, and TSLP preferentially expanded CD4+ T cells both in vitro and in vivo. Thus, as compared with other known cytokines, TSLP is distinctive in exhibiting a lineage preference for the expansion and survival of CD4+ T cells.
Clinically Approved Heterocyclics Act on a Mitochondrial Target and Reduce Stroke-induced Pathology
Authors: Stavrovskaya Irina G. , Narayanan Malini V. , Zhang Wenhua , Krasnikov Boris F. , Heemskerk Jill , Young S. Stanley , Blass John P. , Brown Abraham M. , Beal M. Flint , Friedlander Robert M. , Kristal Bruce S.
Published: July 2004

Substantial evidence indicates that mitochondria are a major checkpoint in several pathways leading to neuronal cell death, but discerning critical propagation stages from downstream consequences has been difficult. The mitochondrial permeability transition (mPT) may be critical in stroke-related injury. To address this hypothesis, identify potential therapeutics, and screen for new uses for established drugs with known toxicity, 1,040 FDA-approved drugs and other bioactive compounds were tested as potential mPT inhibitors. We report the identification of 28 structurally related drugs, including tricyclic antidepressants and antipsychotics, capable of delaying the mPT. Clinically achievable doses of one drug in this general structural class that inhibits mPT, promethazine, were protective in both in vitro and mouse models of stroke. Specifically, promethazine protected primary neuronal cultures subjected to oxygen-glucose deprivation and reduced infarct size and neurological impairment in mice subjected to middle cerebral artery occlusion/reperfusion. These results, in conjunction with new insights provided to older studies, (a) suggest a class of safe, tolerable drugs for stroke and neurodegeneration; (b) provide new tools for understanding mitochondrial roles in neuronal cell death; (c) demonstrate the clinical/experimental value of screening collections of bioactive compounds enriched in clinically available agents; and (d) provide discovery-based evidence that mPT is an essential, causative event in stroke-related injury.
Protein Kinase C θ Is Critical for the Development of In Vivo T Helper (Th)2 Cell But Not Th1 Cell Responses
Authors: Marsland Benjamin J. , Soos Timothy J. , Späth Gerald , Littman Dan R. , Kopf Manfred
Published: July 2004

The serine/threonine-specific protein kinase C (PKC)-θ is predominantly expressed in T cells and localizes to the center of the immunological synapse upon T cell receptor (TCR) and CD28 signaling. T cells deficient in PKC-θ exhibit reduced interleukin (IL)-2 production and proliferative responses in vitro, however, its significance in vivo remains unclear. We found that pkc-θ−/− mice were protected from pulmonary allergic hypersensitivity responses such as airway hyperresponsiveness, eosinophilia, and immunoglobulin E production to inhaled allergen. Furthermore, T helper (Th)2 cell immune responses against Nippostrongylus brasiliensis were severely impaired in pkc-θ−/− mice. In striking contrast, pkc-θ−/− mice on both the C57BL/6 background and the normally susceptible BALB/c background mounted protective Th1 immune responses and were resistant against infection with Leishmania major. Using in vitro TCR transgenic T cell–dendritic cell coculture systems and antigen concentration-dependent Th polarization, PKC-θ–deficient T cells were found to differentiate into Th1 cells after activation with high concentrations of specific peptide, but to have compromised Th2 development at low antigen concentration. The addition of IL-2 partially reconstituted Th2 development in pkc-θ−/− T cells, consistent with an important role for this cytokine in Th2 polarization. Taken together, our results reveal a central role for PKC-θ signaling during Th2 responses.
Role for CD4+ CD25+ Regulatory T Cells in Reactivation of Persistent Leishmaniasis and Control of Concomitant Immunity
Authors: Mendez Susana , Reckling Stacie K. , Piccirillo Ciriacco A. , Sacks David , Belkaid Yasmine
Published: July 2004

Reactivation of dormant infections causes an immense burden of morbidity and mortality in the world at large. Reactivation can occur as a result of immunosuppression, environmental insult, or aging; however, the cause of reactivation of such infections is often not clear. We have previously shown that persistence of the parasite Leishmania major is controlled by endogenous CD4+ CD25+ regulatory T (T reg) cells. In this report, we show that despite efficient parasite clearance at secondary sites of infection, Leishmania superinfection can cause disease reactivation at the primary site. Our results strongly suggest that T reg cells, whose numbers increase in sites of reactivation, are directly responsible for such reactivation. Depletion of CD25+ cells at the time of secondary challenge prevented disease reactivation at the site of persistent infection while strengthening the expression of immunity at the site of secondary challenge. Finally, transfer of T reg cells purified from infected mice into chronically infected mice was sufficient to trigger disease reactivation and prevent the expression of an effector memory response. Our results demonstrate that after persistence is achieved, an equilibrium between T reg cells and effector lymphocytes, which can be disturbed by superinfection, controls the efficiency of recall immune responses and disease reactivation.
A New Human Somatic Stem Cell from Placental Cord Blood with Intrinsic Pluripotent Differentiation Potential
Authors: Kögler Gesine , Sensken Sandra , Airey Judith A. , Trapp Thorsten , Müschen Markus , Feldhahn Niklas , Liedtke Stefanie , Sorg Rüdiger V. , Fischer Johannes , Rosenbaum Claudia , Greschat Susanne , Knipper Andreas , Bender Jörg , Degistirici Özer , Gao Jizong , Caplan Arnold I. , Colletti Evan J. , Almeida-Porada Graça , Müller Hans W. , Zanjani Esmail , Wernet Peter
Published: July 2004

Here a new, intrinsically pluripotent, CD45-negative population from human cord blood, termed unrestricted somatic stem cells (USSCs) is described. This rare population grows adherently and can be expanded to 1015 cells without losing pluripotency. In vitro USSCs showed homogeneous differentiation into osteoblasts, chondroblasts, adipocytes, and hematopoietic and neural cells including astrocytes and neurons that express neurofilament, sodium channel protein, and various neurotransmitter phenotypes. Stereotactic implantation of USSCs into intact adult rat brain revealed that human Tau-positive cells persisted for up to 3 mo and showed migratory activity and a typical neuron-like morphology. In vivo differentiation of USSCs along mesodermal and endodermal pathways was demonstrated in animal models. Bony reconstitution was observed after transplantation of USSC-loaded calcium phosphate cylinders in nude rat femurs. Chondrogenesis occurred after transplanting cell-loaded gelfoam sponges into nude mice. Transplantation of USSCs in a noninjury model, the preimmune fetal sheep, resulted in up to 5% human hematopoietic engraftment. More than 20% albumin-producing human parenchymal hepatic cells with absence of cell fusion and substantial numbers of human cardiomyocytes in both atria and ventricles of the sheep heart were detected many months after USSC transplantation. No tumor formation was observed in any of these animals.
SH2D1A Regulates T-dependent Humoral Autoimmunity
Authors: Hron Jonathan D. , Caplan Liron , Gerth Andrea J. , Schwartzberg Pamela L. , Peng Stanford L.
Published: July 2004

The signaling lymphocytic activation molecule (SLAM)/CD150 family includes a family of chromosome 1–encoded cell surface molecules with costimulatory functions mediated in part by the adaptor protein SH2D1A (SLAM-associated protein, SAP). Deficiency in SH2D1A protects mice from an experimental model of lupus, including the development of hypergammaglobulinemia, autoantibodies including anti–double stranded DNA, and renal disease. This protection did not reflect grossly defective T or B cell function per se because SH2D1A-deficient mice were susceptible to experimental autoimmune encephalomyelitis, a T cell–dependent disease, and they were capable of mounting normal T-independent antigen-specific immunoglobulin responses. Instead, T-dependent antibody responses were impaired in SH2D1A-deficient mice, reflecting defective germinal center formation. These findings demonstrate a specific role for the SLAM–SH2D1A system in the regulation of T-dependent humoral immune responses, implicating members of the CD150–SH2D1A family as targets in the pathogenesis and therapy of antibody-mediated autoimmune and allergic diseases.
The Scavenger Receptor MARCO Is Required for Lung Defense against Pneumococcal Pneumonia and Inhaled Particles
Authors: Arredouani Mohamed , Yang Zhiping , Ning YaoYu , Qin Guozhong , Soininen Raija , Tryggvason Karl , Kobzik Lester
Published: July 2004

Alveolar macrophages (AMs) express the class A scavenger receptor macrophage receptor with collagenous structure (MARCO), but its role in vivo in lung defense against bacteria and environmental particles has not been studied. We used MARCO-deficient mice to directly test the in vivo role of AM MARCO in innate defense against pneumococcal infection and environmental particles. In a murine model of pneumococcal pneumonia, MARCO−/− mice displayed an impaired ability to clear bacteria from the lungs, increased pulmonary inflammation and cytokine release, and diminished survival. In vitro binding of Streptococcus pneumoniae and in vivo uptake of unopsonized particles by MARCO−/− AMs were dramatically impaired. MARCO−/− mice treated with the “inert” environmental particle TiO2 showed enhanced inflammation and chemokine expression, indicating that MARCO-mediated clearance of inert particles by AMs prevents inflammatory responses otherwise initiated by other lung cells. Our findings point to an important role of MARCO in mounting an efficient and appropriately regulated innate immune response against inhaled particles and airborne pathogens.
Human Autoantibody Silencing by Immunoglobulin Light Chains
Authors: Wardemann Hedda , Hammersen Johanna , Nussenzweig Michel C.
Published: July 2004

Several newly arising human antibodies are polyreactive, but in normal individuals the majority of these potentially autodestructive antibodies are removed from the repertoire by receptor editing or B cell deletion in the bone marrow. To determine what proportion of naturally arising autoantibodies can be silenced by immunoglobulin (Ig) light chain receptor editing, we replaced the light chains in 12 such antibodies with a panel of representative Igκ and Igλ chains. We found that most naturally arising autoantibodies are readily silenced by light chain exchange. Thus, receptor editing may account for most autoreactive antibody silencing in humans. Light chain complementarity determining region (CDR) isoelectric points did not correlate with silencing activity, but Igλ genes were more effective than Igκ genes as silencers. The greater efficacy of Igλ chains as silencer of autoreactivity provides a possible explanation for the expansion and altered configuration of the Igλ locus in evolution.
Peyer's Patch Dendritic Cells Process Viral Antigen from Apoptotic Epithelial Cells in the Intestine of Reovirus-infected Mice
Authors: Fleeton Marina N. , Contractor Nikhat , Leon Francisco , Wetzel J. Denise , Dermody Terence S. , Kelsall Brian L.
Published: July 2004

We explored the role of Peyer's patch (PP) dendritic cell (DC) populations in the induction of immune responses to reovirus strain type 1 Lang (T1L). Immunofluorescence staining revealed the presence of T1L structural (σ1) and nonstructural (σNS) proteins in PPs of T1L-infected mice. Cells in the follicle-associated epithelium contained both σ1 and σNS, indicating productive viral replication. In contrast, σ1, but not σNS, was detected in the subepithelial dome (SED) in association with CD11c+/CD8α−/CD11blo DCs, suggesting antigen uptake by these DCs in the absence of infection. Consistent with this possibility, PP DCs purified from infected mice contained σ1, but not σNS, and PP DCs from uninfected mice could not be productively infected in vitro. Furthermore, σ1 protein in the SED was associated with fragmented DNA by terminal deoxy-UTP nick-end labeling staining, activated caspase-3, and the epithelial cell protein cytokeratin, suggesting that DCs capture T1L antigen from infected apoptotic epithelial cells. Finally, PP DCs from infected mice activated T1L-primed CD4+ T cells in vitro. These studies show that CD8α−/CD11blo DCs in the PP SED process T1L antigen from infected apoptotic epithelial cells for presentation to CD4+ T cells, and therefore demonstrate the cross-presentation of virally infected cells by DCs in vivo during a natural viral infection.
Partial Cox regression analysis for high-dimensional microarray gene expression data
Authors: Li Hongzhe , Gui Jiang
Published: July 2004

Motivation: An important application of microarray technology is to predict various clinical phenotypes based on the gene expression profile. Success has been demonstrated in molecular classification of cancer in which different types of cancer serve as categorical outcome variable. However, there has been less research in linking gene expression profile to censored survival outcome such as patients' overall survival time or time to cancer relapse. In this paper, we develop a partial Cox regression method for constructing mutually uncorrelated components based on microarray gene expression data for predicting the survival of future patients.

Results: The proposed partial Cox regression method involves constructing predictive components by repeated least square fitting of residuals and Cox regression fitting. The key difference from the standard principal components of Cox regression analysis is that in constructing the predictive components, our method utilizes the observed survival/censoring information. We also propose to apply the time-dependent receiver operating characteristic curve analysis to evaluate the results. We applied our methods to a publicly available dataset of diffuse large B-cell lymphoma. The outcomes indicated that combining the partial Cox regression method with principal components analysis results in parsimonious model with fewer components and better predictive performance. We conclude that the proposed partial Cox regression method can be very useful in building a parsimonious predictive model that can accurately predict the survival of future patients based on the gene expression profile and survival times of previous patients.

Availability: R codes are available upon request.
A nucleotide substitution model with nearest-neighbour interactions
Authors: Lunter Gerton , Hein Jotun
Published: July 2004

Motivation: It is well known that neighbouring nucleotides in DNA sequences do not mutate independently of each other. In this paper, we introduce a context-dependent substitution model and derive an algorithm to calculate the likelihood of sequences evolving under this model. We use this algorithm to estimate neighbour-dependent substitution rates, as well as rates for dinucleotide substitutions, using a Bayesian sampling procedure. The model is irreversible, giving an arrow to time, and allowing the position of the root between a pair of sequences to be inferred without using out-groups.

Results: We applied the model upon aligned human–mouse non-coding data. Clear neighbour dependencies were observed, including 17–18-fold increased CpG to TpG/CpA rates compared with other substitutions. Root inference positioned the root halfway the mouse and human tips, suggesting an approximately clock-like behaviour of the irreversible part of the subsitution process.
Phylogenomics and the number of characters required for obtaining an accurate phylogeny of eukaryote model species
Authors: Dopazo Hernán , Santoyo Javier , Dopazo Joaquín
Published: July 2004

Motivation: Through the most extensive phylogenomic analysis carried out to date, complete genomes of 11 eukaryotic species have been examined in order to find the homologous of more than 25 000 amino acid sequences. These sequences correspond to the exons of more than 3000 genes and were used as presence/absence characters to test one of the most controversial hypotheses concerning animal evolution, namely the Ecdysozoa hypothesis. Distance, maximum parsimony and Bayesian methods of phylogenetic reconstruction were used to test the hypothesis.

Results: The reliability of the ecdysozoa, grouping arthropods and nematodes in a single clade was unequivocally rejected in all the consensus trees. The Coelomata clade, grouping arthropods and chordates, was supported by the highest statistical confidence in all the reconstructions. The study of the dependence of the genomes' tree accuracy on the number of exons used, demonstrated that an unexpectedly larger number of characters are necessary to obtain robust phylogenies. Previous studies supporting ecdysozoa, could not guarantee an accurate phylogeny because the number of characters used was clearly below the minimum required.
Analysis of domain correlations in yeast protein complexes
Authors: Betel Doron , Isserlin Ruth , Hogue Christopher W. V.
Published: July 2004

Motivation: A growing body of research has concentrated on the identification and definition of conserved sequence motifs. It is widely recognized that these conserved sequence and structural units often mediate protein functions and interactions. The continuing advancements in high-throughput experiments necessitate the development of computational methods to critically assess the results. In this work, we analyzed high-throughput protein complexes using the domain composition of their protein constituents. Domains that mediate similar or related functions may consistently co-occur in protein complexes.

Results: We analyzed Saccharomyces cerevisiae protein complexes from curated and high-throughput experimental datasets to identify statistically significant functional associations between domains. The resulting correlations are represented as domain networks that form the basis of comparison between the datasets, as well as to binary protein interactions. The results show that the curated datasets produce domain networks that map to known biological assemblies, such as ribosome, RNA polymerase, proteasome regulators, transcription initiation and histones. Furthermore, many of these domain correlations were also found in binary protein interactions. In contrast, the high-throughput datasets contain one large network of domain associations. High connectivity of RNA processing and binding domains in the high-throughput datasets reflects the abundance of RNA binding proteins in yeast, in agreement with a previous report that identified a nucleolar protein cluster, possibly mediated by rRNA, from these complexes.

Availability: The software is available upon request from the authors and is dependent on the NCBI C++ toolkit.
Protein names precisely peeled off free text
Authors: Mika Sven , Rost Burkhard
Published: July 2004

Motivation: Automatically identifying protein names from the scientific literature is a pre-requisite for the increasing demand in data-mining this wealth of information. Existing approaches are based on dictionaries, rules and machine-learning. Here, we introduced a novel system that combines a pre-processing dictionary- and rule-based filtering step with several separately trained support vector machines (SVMs) to identify protein names in the MEDLINE abstracts.

Results: Our new tagging-system NLProt is capable of extracting protein names with a precision (accuracy) of 75% at a recall (coverage) of 76% after training on a corpus, which was used before by other groups and contains 200 annotated abstracts. For our estimate of sustained performance, we considered partially identified names as false positives. One important issue frequently ignored in the literature is the redundancy in evaluation sets. We suggested some guidelines for removing overly inadequate overlaps between training and testing sets. Applying these new guidelines, our program appeared to significantly out-perform other methods tagging protein names. NLProt was so successful due to the SVM-building blocks that succeeded in utilizing the local context of protein names in the scientific literature. We challenge that our system may constitute the most general and precise method for tagging protein names.

Availability:  http://cubic.bioc.columbia.edu/services/nlprot/
HyBrow: a prototype system for computer-aided hypothesis evaluation
Authors: Racunas S. A. , Shah N. H. , Albert I. , Fedoroff N. V.
Published: July 2004

Motivation: Experimental design, hypothesis-testing and model-building in the current data-rich environment require the biologists' to collect, evaluate and integrate large amounts of information of many disparate kinds. Developing a unified framework for the representation and conceptual integration of biological data and processes is a major challenge in bioinformatics because of the variety of available data and the different levels of detail at which biological processes can be considered.

Results: We have developed the HyBrow (Hypothesis Browser) system as a prototype bioinformatics tool for designing hypotheses and evaluating them for consistency with existing knowledge. HyBrow consists of a modeling framework with the ability to accommodate diverse biological information sources, an event-based ontology for representing biological processes at different levels of detail, a database to query information in the ontology and programs to perform hypothesis design and evaluation. We demonstrate the HyBrow prototype using the galactose gene network in Saccharomyces cerevisiae as our test system, and evaluate alternative hypotheses for consistency with stored information.

Availability:  www.hybrow.org
Learning kernels from biological networks by maximizing entropy
Authors: Tsuda Koji , Noble William Stafford
Published: July 2004

Motivation: The diffusion kernel is a general method for computing pairwise distances among all nodes in a graph, based on the sum of weighted paths between each pair of nodes. This technique has been used successfully, in conjunction with kernel-based learning methods, to draw inferences from several types of biological networks.

Results: We show that computing the diffusion kernel is equivalent to maximizing the von Neumann entropy, subject to a global constraint on the sum of the Euclidean distances between nodes. This global constraint allows for high variance in the pairwise distances. Accordingly, we propose an alternative, locally constrained diffusion kernel, and we demonstrate that the resulting kernel allows for more accurate support vector machine prediction of protein functional classifications from metabolic and protein–protein interaction networks.

Availability: Supplementary results and data are available at noble.gs.washington.edu/proj/maxent
High density linkage disequilibrium mapping using models of haplotype block variation
Authors: Greenspan G. , Geiger D.
Published: July 2004

Motivation: The presence of millions of single nucleotide polymorphisms (SNPs) in the human genome has spurred interest in genetic mapping methods based on linkage disequilibrium. The recently discovered haplotype block structure of human variation promises to improve the effectiveness of these methods. A key difficulty for mapping techniques is the cost involved in separately identifying the haplotypes on each of an individual's chromosomes.

Results: We present a new approach for performing linkage disequilibrium mapping using high density haplotype or genotype data. Our method is based on a statistical model of haplotype block variation, which takes account of recombination hotspots, bottlenecks, genetic drift and mutation. We test our technique on two empirically determined high density datasets, attempting to recover the location of an SNP which was hidden and converted into phenotype information. We compare the results against a mapping method based on individual SNPs as well as a competing haplotype-based approach. We show that our strategy significantly outperforms these other approaches when used as a guide for resequencing and that it can also deal with both unphased genotype data and low penetrance diseases.

Availability: HaploBlock executables for Linux, Mac OS X and Sun OS, as well as user documentation, are available online at http://bioinfo.cs.technion.ac.il/haploblock/
Functional inference from non-random distributions of conserved predicted transcription factor binding sites
Authors: Dieterich Christoph , Rahmann Sven , Vingron Martin
Published: July 2004

Motivation: Our understanding of how genes are regulated in a concerted fashion is still limited. Especially, complex phenomena like cell cycle regulation in multicellular organisms are poorly understood. Therefore, we investigated conserved predicted transcription factor binding sites (TFBSs) in man–mouse upstream regions of genes that can be associated to a particular cell cycle phase in HeLa cells. TFBSs were predicted from selected binding site motifs (represented by position weight matrices, PWMs) based on a statistical approach. A regulatory role for a transcription factor is more probable if its predicted TFBSs are enriched in upstream regions of genes, that are associated with a subset of cell cycle phases. We tested for this association by computing exact P-values for the observed phase distributions under the null distribution defined by the relative amount of conserved upstream sequence of genes per cell cycle phase. We considered non-exonic and 5′-untranslated region (5′-UTR) binding sites separately and corrected for multiple testing by taking the false discovery rate into account.

Results: We identified 22 non-exonic and 11 5′-UTR significant PWM phase distributions although expecting one false discovery. Many of the corresponding transcription factors (e.g. members of the thyroid hormone/retinoid receptor subfamily) have already been associated with cell cycle regulation, proliferation and development. It appears that our method is a suitable tool for detecting putative cell cycle regulators in the realm of known human transcription factors.

Availability: Further details and supplementary data can be obtained from http://corg.molgen.mpg.de/cellcycle
Finding disease specific alterations in the co-expression of genes
Authors: Kostka Dennis , Spang Rainer
Published: July 2004

Motivation: Standard analysis routines for microarray data aim at differentially expressed genes. In this paper, we address the complementary problem of detecting sets of differentially co-expressed genes in two phenotypically distinct sets of expression profiles.

Results: We introduce a score for differential co-expression and suggest a computationally efficient algorithm for finding high scoring sets of genes. The use of our novel method is demonstrated in the context of simulations and on real expression data from a clinical study.
Protein network inference from multiple genomic data: a supervised approach
Authors: Yamanishi Y. , Vert J.-P. , Kanehisa M.
Published: July 2004

Motivation: An increasing number of observations support the hypothesis that most biological functions involve the interactions between many proteins, and that the complexity of living systems arises as a result of such interactions. In this context, the problem of inferring a global protein network for a given organism, using all available genomic data about the organism, is quickly becoming one of the main challenges in current computational biology.

Results: This paper presents a new method to infer protein networks from multiple types of genomic data. Based on a variant of kernel canonical correlation analysis, its originality is in the formalization of the protein network inference problem as a supervised learning problem, and in the integration of heterogeneous genomic data within this framework. We present promising results on the prediction of the protein network for the yeast Saccharomyces cerevisiae from four types of widely available data: gene expressions, protein interactions measured by yeast two-hybrid systems, protein localizations in the cell and protein phylogenetic profiles. The method is shown to outperform other unsupervised protein network inference methods. We finally conduct a comprehensive prediction of the protein network for all proteins of the yeast, which enables us to propose protein candidates for missing enzymes in a biosynthesis pathway.

Availability: Softwares are available upon request.
Tracking repeats using significance and transitivity
Authors: Szklarczyk Radek , Heringa Jaap
Published: July 2004

Motivation: Internal repeats in coding sequences correspond to structural and functional units of proteins. Moreover, duplication of fragments of coding sequences is known to be a mechanism to facilitate evolution. Identification of repeats is crucial to shed light on the function and structure of proteins, and explain their evolutionary past. The task is difficult because during the course of evolution many repeats diverged beyond recognition.

Results: We introduce a new method TRUST, for ab initio determination of internal repeats in proteins. It provides an improvement in prediction quality as compared to alternative state-of-the-art methods. The increased sensitivity and accuracy of the method is achieved by exploiting the concept of transitivity of alignments. Starting from significant local suboptimal alignments, the application of transitivity allows us to (1) identify distant repeat homologues for which no alignments were found; (2) gain confidence about consistently well-aligned regions; and (3) recognize and reduce the contribution of non-homologous repeats. This re-assessment step enables us to derive a virtually noise-free profile representing a generalized repeat with high fidelity. We also obtained superior specificity by employing rigid statistical testing for self-sequence and profile-sequence alignments. Assessment was done using a database of repeat annotations based on structural superpositioning. The results show that TRUST is a useful and reliable tool for mining tandem and non-tandem repeats in protein sequence databases, capable of predicting multiple repeat types with varying intervening segments within a single sequence.

Availability: The TRUST server (together with the source code) is available at http://ibivu.cs.vu.nl/programs/trustwww
Mining frequent patterns in protein structures: a study of protease families
Authors: Chen Shann-Ching , Bahar Ivet
Published: July 2004

Motivation: Analysis of protein sequence and structure databases usually reveal frequent patterns (FP) associated with biological function. Data mining techniques generally consider the physicochemical and structural properties of amino acids and their microenvironment in the folded structures. Dynamics is not usually considered, although proteins are not static, and their function relates to conformational mobility in many cases.

Results: This work describes a novel unsupervised learning approach to discover FPs in the protein families, based on biochemical, geometric and dynamic features. Without any prior knowledge of functional motifs, the method discovers the FPs for each type of amino acid and identifies the conserved residues in three protease subfamilies; chymotrypsin and subtilisin subfamilies of serine proteases and papain subfamily of cysteine proteases. The catalytic triad residues are distinguished by their strong spatial coupling (high interconnectivity) to other conserved residues. Although the spatial arrangements of the catalytic residues in the two subfamilies of serine proteases are similar, their FPs are found to be quite different. The present approach appears to be a promising tool for detecting functional patterns in rapidly growing structure databases and providing insights in to the relationship among protein structure, dynamics and function.

Availability: Available upon request from the authors.
Striped sheets and protein contact prediction
Authors: MacCallum Robert M.
Published: July 2004

Motivation: Current approaches to contact map prediction in proteins have focused on amino acid conservation and patterns of mutation at sequentially distant positions. This sequence information is poorly understood and very little progress has been made in this area during recent years.

Results: In this study, an observation of ‘striped’ sequence patterns across β-sheets prompted the development of a new type of contact map predictor. Computer program code was evolved with an evolutionary algorithm (genetic programming) to select residues and residue pairs likely to make contacts based solely on local sequence patterns extracted with the help of self-organizing maps. The mean prediction accuracy is 27% on a validation set of 156 domains up to 400 residues in length, where contacts are separated by at least 8 residues and length/10 pairs are predicted. The retrospective accuracy on a set of 15 CASP5 targets is 27% and 14% for length/10 and length/2 predicted pairs, respectively (both using a minimum residue separation of 24). This compares favourably to the equivalent 21% and 13% obtained for the best automated contact prediction methods at CASP5. The results suggest that protein architectures impose regularities in local sequence environments. Other sources of information, such as correlated/compensatory mutations, may further improve accuracy.

Availability: A web-based prediction service is available at http://www.sbc.su.se/~maccallr/contactmaps
Mining MEDLINE for implicit links between dietary substances and diseases
Authors: Srinivasan Padmini , Libbus Bisharah
Published: July 2004

Motivation: Text mining systems aim at knowledge discovery from text collections. This work presents our text mining algorithm and demonstrates its use to uncover information that could form the basis of new hypotheses. In particular, we use it to discover novel uses for Curcuma longa, a dietary substance, which is highly regarded for its therapeutic properties in Asia.

Results: Several disease were identified that offer novel research contexts for curcumin. We analyze select suggestions, such as retinal diseases, Crohn's disease and disorders related to the spinal cord. Our analysis suggests that there is strong evidence in favor of a beneficial role for curcumin in these diseases. The evidence is based on curcumin's influence on several genes, such as COX-2, TNF-alpha, JNK, p38 MAPK and TGF-beta. This research suggests that our discovery algorithm may be used to suggest novel uses for dietary and pharmacological substances. More generally, our text mining algorithm may be used to uncover information that potentially sheds new light on a given topic of interest.

Availability: Contact authors.
Deconvolving cell cycle expression data with complementary information
Authors: Bar-Joseph Ziv , Farkash Shlomit , Gifford David K. , Simon Itamar , Rosenfeld Roni
Published: July 2004

Motivation: In the study of many systems, cells are first synchronized so that a large population of cells exhibit similar behavior. While synchronization can usually be achieved for a short duration, after a while cells begin to lose their synchronization. Synchronization loss is a continuous process and so the observed value in a population of cells for a gene at time t is actually a convolution of its values in an interval around t. Deconvolving the observed values from a mixed population will allow us to obtain better models for these systems and to accurately detect the genes that participate in these systems.

Results: We present an algorithm which combines budding index and gene expression data to deconvolve expression profiles. Using the budding index data we first fit a synchronization loss model for the cell cycle system. Our deconvolution algorithm uses this loss model and can also use information from co-expressed genes, making it more robust against noise and missing values. Using expression and budding data for yeast we show that our algorithm is able to reconstruct a more accurate representation when compared with the observed values. In addition, using the deconvolved profiles we are able to correctly identify 15% more cycling genes when compared to a set identified using the observed values.

Availability: Matlab implementation can be downloaded from the supporting website http://www.cs.cmu.edu/~zivbj/decon/decon.html
Application of a new probabilistic model for recognizing complex patterns in glycans
Authors: Aoki Kiyoko F. , Ueda Nobuhisa , Yamaguchi Atsuko , Kanehisa Minoru , Akutsu Tatsuya , Mamitsuka Hiroshi
Published: July 2004

Motivation: The study of carbohydrate sugar chains, or glycans, has been one of slow progress mainly due to the difficulty in establishing standard methods for analyzing their structures and biosynthesis. Glycans are generally tree structures that are more complex than linear DNA or protein sequences, and evidence shows that patterns in glycans may be present that spread across siblings and into further regions that are not limited by the edges in the actual tree structure itself. Current models were not able to capture such patterns.

Results: We have applied a new probabilistic model, called probabilistic sibling-dependent tree Markov model (PSTMM), which is able to inherently capture such complex patterns of glycans. Not only is the ability to capture such patterns important in itself, but this also implies that PSTMM is capable of performing multiple tree structure alignments efficiently. We prove through experimentation on actual glycan data that this new model is extremely useful for gaining insight into the hidden, complex patterns of glycans, which are so crucial for the development and functioning of higher level organisms. Furthermore, we also show that this model can be additionally utilized as an innovative approach to multiple tree alignment, which has not been applied to glycan chains before. This extension on the usage of PSTMM may be a major step forward for not only the structural analysis of glycans, but it may consequently prove useful for discovering clues into their function.
Efficient approximations for learning phylogenetic HMM models from data
Authors: Jojic Vladimir , Jojic Nebojsa , Meek Chris , Geiger Dan , Siepel Adam , Haussler David , Heckerman D.
Published: July 2004

Motivation: We consider models useful for learning an evolutionary or phylogenetic tree from data consisting of DNA sequences corresponding to the leaves of the tree. In particular, we consider a general probabilistic model described in Siepel and Haussler that we call the phylogenetic-HMM model which generalizes the classical probabilistic models of Neyman and Felsenstein. Unfortunately, computing the likelihood of phylogenetic-HMM models is intractable. We consider several approximations for computing the likelihood of such models including an approximation introduced in Siepel and Haussler, loopy belief propagation and several variational methods.

Results: We demonstrate that, unlike the other approximations, variational methods are accurate and are guaranteed to lower bound the likelihood. In addition, we identify a particular variational approximation to be best—one in which the posterior distribution is variationally approximated using the classic Neyman–Felsenstein model. The application of our best approximation to data from the cystic fibrosis transmembrane conductance regulator gene region across nine eutherian mammals reveals a CpG effect.
A knowledge based approach for representing and reasoning about signaling networks
Authors: Baral C. , Chancellor K. , Tran N. , Tran N.L. , Joy A. , Berens M.
Published: July 2004

Motivation: In this paper we propose to use recent developments in knowledge representation languages and reasoning methodologies for representing and reasoning about signaling networks. Our approach is different from most other qualitative systems biology approaches in that it is based on reasoning (or inferencing) rather than simulation. Some of the advantages of our approach are, we can use recent advances in reasoning with incomplete and partial information to deal with gaps in signal network knowledge; and can perform various kinds of reasoning such as planning, hypothetical reasoning and explaining observations.

Results: Using our approach we have developed the system BioSigNet-RR for representation and reasoning about signaling networks. We use a NFκB related signaling pathway to illustrate the kinds of reasoning and representation that our system can currently do.

Availability: The system is available on the Web at http://www.public.asu.edu/~cbaral/biosignet