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

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

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

The first small-molecule inhibitors of members of the ribonuclease E family

The Escherichia coli endoribonuclease RNase E is central to the processing and degradation of all types of RNA and as such is a pleotropic regulator of gene expression. It is essential for growth and was one of the first examples of an endonuclease that can recognise the 5′-monophosphorylated ends of RNA thereby increasing the efficiency of many cleavages. Homologues of RNase E can be found in many bacterial families including important pathogens, but no homologues have been identified in humans or animals. RNase E represents a potential target for the development of new antibiotics to combat the growing number of bacteria that are resistant to antibiotics in use currently. Potent small molecule inhibitors that bind the active site of essential enzymes are proving to be a source of potential drug leads and tools to dissect function through chemical genetics. Here we report the use of virtual high-throughput screening to obtain small molecules predicted to bind at sites in the N-terminal catalytic half of RNase E. We show that these compounds are able to bind with specificity and inhibit catalysis of Escherichia coli and Mycobacterium tuberculosis RNase E and also inhibit the activity of RNase G, a paralogue of RNase E

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

Lefschetz properties for complete intersection ideals generated by products of linear forms

In this paper, we study the strong Lefschetz property of artinian complete intersection ideals generated by products of linear forms. We prove the strong Lefschetz property for a class of such ideals with binomial generators

The essential peptidoglycan glycosyltransferase MurG forms a complex with proteins involved in lateral envelope growth as well as with proteins involved in cell division in Escherichia coli

In Escherichia coli many enzymes including MurG are directly involved in the synthesis and assembly of peptidoglycan. MurG is an essential glycosyltransferase catalysing the last intracellular step of peptidoglycan synthesis. To elucidate its role during elongation and division events, localization of MurG using immunofluorescence microscopy was performed. MurG exhibited a random distribution in the cell envelope with a relatively higher intensity at the division site. This mid-cell localization was dependent on the presence of a mature divisome. Its localization in the lateral cell wall appeared to require the presence of MreCD. This could be indicative of a potential interaction between MurG and other proteins. Investigating this by immunoprecipitation revealed the association of MurG with MreB and MraY in the same protein complex. In view of this, the loss of rod shape of ΔmreBCD strain could be ascribed to the loss of MurG membrane localization. Consequently, this could prevent the localized supply of the lipid II precursor to the peptidoglycan synthesizing machinery involved in cell elongation. It is postulated that the involvement of MurG in the peptidoglycan synthesis concurs with two complexes, one implicated in cell elongation and the other in division. A model representing the first complex is proposed

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