Despite its being a leading cause of nosocomal and community-acquired infections, surprisingly little is known about Staphylococcus aureus stress responses. In the current study, Affymetrix S. aureus GeneChips were used to define transcriptome changes in response to cold shock, heat shock, stringent, and SOS responseinducing conditions. Additionally, the RNA turnover properties of each response were measured. Each stress response induced distinct biological processes, subsets of virulence factors, and antibiotic determinants. The results were validated by real-time PCR and stress-mediated changes in antimicrobial agent susceptibility. Collectively, many S. aureus stress-responsive functions are conserved across bacteria, whereas others are unique to the organism. Sets of small stable RNA molecules with no open reading frames were also components of each response. Induction of the stringent, cold shock, and heat shock responses dramatically stabilized most mRNA species. Correlations between mRNA turnover properties and transcript titers suggest that S. aureus stress response-dependent alterations in transcript abundances can, in part, be attributed to alterations in RNA stability. This phenomenon was not observed within SOS-responsive cells.
The National Microbial Pathogen Data Resource (NMPDR) () is a National Institute of Allergy and Infections Disease (NIAID)-funded Bioinformatics Resource Center that supports research in selected Category B pathogens. NMPDR contains the complete genomes of ∼50 strains of pathogenic bacteria that are the focus of our curators, as well as >400 other genomes that provide a broad context for comparative analysis across the three phylogenetic Domains. NMPDR integrates complete, public genomes with expertly curated biological subsystems to provide the most consistent genome annotations. Subsystems are sets of functional roles related by a biologically meaningful organizing principle, which are built over large collections of genomes; they provide researchers with consistent functional assignments in a biologically structured context. Investigators can browse subsystems and reactions to develop accurate reconstructions of the metabolic networks of any sequenced organism. NMPDR provides a comprehensive bioinformatics platform, with tools and viewers for genome analysis. Results of precomputed gene clustering analyses can be retrieved in tabular or graphic format with one-click tools. NMPDR tools include Signature Genes, which finds the set of genes in common or that differentiates two groups of organisms. Essentiality data collated from genome-wide studies have been curated. Drug target identification and high-throughput, in silico, compound screening are in development.
SUMMARY Many enzymes and other proteins are difficult subjects for bioinformatic analysis because they exhibit variant catalytic, structural, regulatory, and fusion mode features within a protein family whose sequences are not highly conserved. However, such features reflect dynamic and interesting scenarios of evolutionary importance. The value of experimental data obtained from individual organisms is instantly magnified to the extent that given features of the experimental organism can be projected upon related organisms. But how can one decide how far along the similarity scale it is reasonable to go before such inferences become doubtful? How can a credible picture of evolutionary events be deduced within the vertical trace of inheritance in combination with intervening events of lateral gene transfer (LGT)? We present a comprehensive analysis of a dehydrogenase protein family (TyrA) as a prototype example of how these goals can be accomplished through the use of cohesion group analysis. With this approach, the full collection of homologs is sorted into groups by a method that eliminates bias caused by an uneven representation of sequences from organisms whose phylogenetic spacing is not optimal. Each sufficiently populated cohesion group is phylogenetically coherent and defined by an overall congruence with a distinct section of the 16S rRNA gene tree. Exceptions that occasionally are found implicate a clearly defined LGT scenario whereby the recipient lineage is apparent and the donor lineage of the gene transferred is localized to those organisms that define the cohesion group. Systematic procedures to manage and organize otherwise overwhelming amounts of data are demonstrated.
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