WormBase 2007

WormBase (www.wormbase.org) is the major publicly available database of information about Caenorhabditis elegans, an important system for basic biological and biomedical research. Derived from the initial ACeDB database of C. elegans genetic and sequence information, WormBase now includes the genomic, anatomical and functional information about C. elegans, other Caenorhabditis species and other nematodes. As such, it is a crucial resource not only for C. elegans biologists but the larger biomedical and bioinformatics communities. Coverage of core areas of C. elegans biology will allow the biomedical community to make full use of the results of intensive molecular genetic analysis and functional genomic studies of this organism. Improved search and display tools, wider cross-species comparisons and extended ontologies are some of the features that will help scientists extend their research and take advantage of other nematode species genome sequences

Excitation test results on a single inner vertical coil for the Large Helical Device

Excitation experiments on a single inner vertical coil for the Large Helical Device (LHD) were carried out to confirm its performance. The coil is one of the LHD\u27s poloidal field coils and consists of a forced-flow Nb-Ti cable-in-conduit conductor (CICC). After cooldown for 250 hours, the superconducting transition of the whole coil was confirmed. Pressure drops were measured during the cooldown to determine the coil\u27s hydraulic characteristics. Then, the coil was successfully energized up to the specified current, 20.8 kA. In the experiments, heat generation of joints, radial displacement and acoustic emission (AE) were measured

Network centrality: an introduction

Centrality is a key property of complex networks that influences the behavior of dynamical processes, like synchronization and epidemic spreading, and can bring important information about the organization of complex systems, like our brain and society. There are many metrics to quantify the node centrality in networks. Here, we review the main centrality measures and discuss their main features and limitations. The influence of network centrality on epidemic spreading and synchronization is also pointed out in this chapter. Moreover, we present the application of centrality measures to understand the function of complex systems, including biological and cortical networks. Finally, we discuss some perspectives and challenges to generalize centrality measures for multilayer and temporal networks.Comment: Book Chapter in "From nonlinear dynamics to complex systems: A Mathematical modeling approach" by Springe

Computation of significance scores of unweighted Gene Set Enrichment Analyses

<p>Abstract</p> <p>Background</p> <p>Gene Set Enrichment Analysis (GSEA) is a computational method for the statistical evaluation of sorted lists of genes or proteins. Originally GSEA was developed for interpreting microarray gene expression data, but it can be applied to any sorted list of genes. Given the gene list and an arbitrary biological category, GSEA evaluates whether the genes of the considered category are randomly distributed or accumulated on top or bottom of the list. Usually, significance scores (p-values) of GSEA are computed by nonparametric permutation tests, a time consuming procedure that yields only estimates of the p-values.</p> <p>Results</p> <p>We present a novel dynamic programming algorithm for calculating exact significance values of unweighted Gene Set Enrichment Analyses. Our algorithm avoids typical problems of nonparametric permutation tests, as varying findings in different runs caused by the random sampling procedure. Another advantage of the presented dynamic programming algorithm is its runtime and memory efficiency. To test our algorithm, we applied it not only to simulated data sets, but additionally evaluated expression profiles of squamous cell lung cancer tissue and autologous unaffected tissue.</p

Structural and functional characterization of the LldR from Corynebacterium glutamicum: a transcriptional repressor involved in l-lactate and sugar utilization

LldR (CGL2915) from Corynebacterium glutamicum is a transcription factor belonging to the GntR family, which is typically involved in the regulation of oxidized substrates associated with amino acid metabolism. In the present study, the crystal structure of LldR was determined at 2.05-Å resolution. The structure consists of N- and C-domains similar to those of FadR, but with distinct domain orientations. LldR and FadR dimers achieve similar structures by domain swapping, which was first observed in dimeric assembly of transcription factors. A structural feature of Zn2+ binding in the regulatory domain was also observed, as a difference from the FadR subfamily. DNA microarray and DNase I footprint analyses suggested that LldR acts as a repressor regulating cgl2917-lldD and cgl1934-fruK-ptsF operons, which are indispensable for l-lactate and fructose/sucrose utilization, respectively. Furthermore, the stoichiometries and affinities of LldR and DNAs were determined by isothermal titration calorimetry measurements. The transcriptional start site and repression of LldR on the cgl2917-lldD operon were analysed by primer extension assay. Mutation experiments showed that residues Lys4, Arg32, Arg42 and Gly63 are crucial for DNA binding. The location of the putative ligand binding cavity and the regulatory mechanism of LldR on its affinity for DNA were proposed

How to identify essential genes from molecular networks?

<p>Abstract</p> <p>Background</p> <p>The prediction of essential genes from molecular networks is a way to test the understanding of essentiality in the context of what is known about the network. However, the current knowledge on molecular network structures is incomplete yet, and consequently the strategies aimed to predict essential genes are prone to uncertain predictions. We propose that simultaneously evaluating different network structures and different algorithms representing gene essentiality (centrality measures) may identify essential genes in networks in a reliable fashion.</p> <p>Results</p> <p>By simultaneously analyzing 16 different centrality measures on 18 different reconstructed metabolic networks for <it>Saccharomyces cerevisiae</it>, we show that no single centrality measure identifies essential genes from these networks in a statistically significant way; however, the combination of at least 2 centrality measures achieves a reliable prediction of most but not all of the essential genes. No improvement is achieved in the prediction of essential genes when 3 or 4 centrality measures were combined.</p> <p>Conclusion</p> <p>The method reported here describes a reliable procedure to predict essential genes from molecular networks. Our results show that essential genes may be predicted only by combining centrality measures, revealing the complex nature of the function of essential genes.</p

Molecular imaging of glycan chains couples cell-wall polysaccharide architecture to bacterial cell

Biopolymer composite cell walls maintain cell shape and resist forces in plants, fungi and bacteria. Peptidoglycan, a crucial antibiotic target and immunomodulator, performs this role in bacteria. The textbook structural model of peptidoglycan is a highly ordered, crystalline material. Here we use atomic force microscopy (AFM) to image individual glycan chains in peptidoglycan from Escherichia coli in unprecedented detail. We quantify and map the extent to which chains are oriented in a similar direction (orientational order), showing it is much less ordered than previously depicted. Combining AFM with size exclusion chromatography, we reveal glycan chains up to 200 nm long. We show that altered cell shape is associated with substantial changes in peptidoglycan biophysical properties. Glycans from E. coli in its normal rod shape are long and circumferentially oriented, but when a spheroid shape is induced (chemically or genetically) glycans become short and disordered

Fibulin-5, an integrin-binding matricellular protein: its function in development and disease

Interactions between the extracellular matrix (ECM) and cells are critical in embryonic development, tissue homeostasis, physiological remodeling, and tumorigenesis. Matricellular proteins, a group of ECM components, mediate cell-ECM interactions. One such molecule, Fibulin-5 is a 66-kDa glycoprotein secreted by various cell types, including vascular smooth muscle cells (SMCs), fibroblasts, and endothelial cells. Fibulin-5 contributes to the formation of elastic fibers by binding to structural components including tropoelastin and fibrillin-1, and to cross-linking enzymes, aiding elastic fiber assembly. Mice deficient in the fibulin-5 gene (Fbln5) exhibit systemic elastic fiber defects with manifestations of loose skin, tortuous aorta, emphysematous lung and genital prolapse. Although Fbln5 expression is down-regulated after birth, following the completion of elastic fiber formation, expression is reactivated upon tissue injury, affecting diverse cellular functions independent of its elastogenic function. Fibulin-5 contains an evolutionally conserved arginine-glycine-aspartic acid (RGD) motif in the N-terminal region, which mediates binding to a subset of integrins, including α5β1, αvβ3, and αvβ5. Fibulin-5 enhances substrate attachment of endothelial cells, while inhibiting migration and proliferation in a cell type- and context-dependent manner. The antagonistic function of fibulin-5 in angiogenesis has been demonstrated in vitro and in vivo; fibulin-5 may block angiogenesis by inducing the anti-angiogenic molecule thrompospondin-1, by antagonizing VEGF165-mediated signaling, and/or by antagonizing fibronectin-mediated signaling through directly binding and blocking the α5β1 fibronectin receptor. The overall effect of fibulin-5 on tumor growth depends on the balance between the inhibitory property of fibulin-5 on angiogenesis and the direct effect of fibulin-5 on proliferation and migration of tumor cells. However, the effect of tumor-derived versus host microenvironment-derived fibulin-5 remains to be evaluated