Activation of the phosphosignaling protein CheY. II. Analysis of activated mutants by 19F NMR and protein engineering

The Escherichia coli CheY protein is activated by phosphorylation, and in turn alters flagellar rotation. To investigate the molecular mechanism of activation, an extensive collection of mutant CheY proteins was analyzed by behavioral assays, in vitro phosphorylation, and 19F NMR chemical shift measurements. Substitution of a positively charged residue (Arg or Lys) in place of Asp13 in the CheY activation site results in activation, even for mutants which cannot be phosphorylated. Thus phosphorylation plays an indirect role in the activation mechanism. Lys109, a residue proposed to act as a conformational "switch" in the activation site, is required for activation of CheY by either phosphorylation or mutation. The 19F NMR chemical shift assay described in the preceding article (Drake, S. K., Bourret, R. B., Luck, L. A., Simon, M. I., and Falke, J. J. (1993) J. Biol Chem. 268, 13081-13088) was again used to monitor six phenylalanine positions in CheY, including one position which probed the vicinity of Lys109. Mutations which activate CheY were observed to perturb the Lys109 probe, providing further evidence that Lys109 is directly involved in the activating conformational change. Two striking contrasts were observed between activation by mutation and phosphorylation. (i) Each activating mutation generates a relatively localized perturbation in the activation site region, whereas phosphorylation triggers a global structural change. (ii) The perturbation of the Lys109 region observed for activating mutations is not detected in the phosphorylated protein. These results are consistent with a two-step model of activated CheY docking to the flagellar switch

Genoviz Software Development Kit: Java tool kit for building genomics visualization applications

<p>Abstract</p> <p>Background</p> <p>Visualization software can expose previously undiscovered patterns in genomic data and advance biological science.</p> <p>Results</p> <p>The Genoviz Software Development Kit (SDK) is an open source, Java-based framework designed for rapid assembly of visualization software applications for genomics. The Genoviz SDK framework provides a mechanism for incorporating adaptive, dynamic zooming into applications, a desirable feature of genome viewers. Visualization capabilities of the Genoviz SDK include automated layout of features along genetic or genomic axes; support for user interactions with graphical elements (Glyphs) in a map; a variety of Glyph sub-classes that promote experimentation with new ways of representing data in graphical formats; and support for adaptive, semantic zooming, whereby objects change their appearance depending on zoom level and zooming rate adapts to the current scale. Freely available demonstration and production quality applications, including the Integrated Genome Browser, illustrate Genoviz SDK capabilities.</p> <p>Conclusion</p> <p>Separation between graphics components and genomic data models makes it easy for developers to add visualization capability to pre-existing applications or build new applications using third-party data models. Source code, documentation, sample applications, and tutorials are available at <url>http://genoviz.sourceforge.net/</url>.</p

Composition-based statistics and translated nucleotide searches: Improving the TBLASTN module of BLAST

BACKGROUND: TBLASTN is a mode of operation for BLAST that aligns protein sequences to a nucleotide database translated in all six frames. We present the first description of the modern implementation of TBLASTN, focusing on new techniques that were used to implement composition-based statistics for translated nucleotide searches. Composition-based statistics use the composition of the sequences being aligned to generate more accurate E-values, which allows for a more accurate distinction between true and false matches. Until recently, composition-based statistics were available only for protein-protein searches. They are now available as a command line option for recent versions of TBLASTN and as an option for TBLASTN on the NCBI BLAST web server. RESULTS: We evaluate the statistical and retrieval accuracy of the E-values reported by a baseline version of TBLASTN and by two variants that use different types of composition-based statistics. To test the statistical accuracy of TBLASTN, we ran 1000 searches using scrambled proteins from the mouse genome and a database of human chromosomes. To test retrieval accuracy, we modernize and adapt to translated searches a test set previously used to evaluate the retrieval accuracy of protein-protein searches. We show that composition-based statistics greatly improve the statistical accuracy of TBLASTN, at a small cost to the retrieval accuracy. CONCLUSION: TBLASTN is widely used, as it is common to wish to compare proteins to chromosomes or to libraries of mRNAs. Composition-based statistics improve the statistical accuracy, and therefore the reliability, of TBLASTN results. The algorithms used by TBLASTN are not widely known, and some of the most important are reported here. The data used to test TBLASTN are available for download and may be useful in other studies of translated search algorithms

Saccharomyces

The Saccharomyces GenomeDatabase (SGD) provides Internet access to the complete Saccharomyces cerevisiae genomic sequence, its genes and their products, the phenotypes of its mutants, and the literature supporting these data. The amount of information and the number of features provided by SGD have increased greatly following the release of the S.cerevisiae genomic sequence, which is currently the only complete sequence of a eukaryotic genome. SGD aids researchers by providing not only basic information, but also tools such as sequence similarity searching that lead to detailed information about features of the genome and relationships between genes. SGD presents information using a variety of user-friendly, dynamically created graphical displays illustrating physical, genetic and sequence feature maps. SGD can be accessed via the World Wide Web at http://genome-www.stanford.edu/Saccharomyces/ INTRODUCTION The Saccharomyces Genome Database (SGD) was established to provide a convenient..