The Role of MSA in the Global Regulation of Virulence in \u3ci\u3eStaphylococcus aureus\u3c/i\u3e

Staphylococcus aureus is an important pathogen causing life threatening diseases in humans. Previously we showed that msa modulates the activity of sarA (Staphylococcal accessory regulator), which is one of a major global regulator of virulence in S. aureus. The objective of this study is to characterize the role of msa (Modulator of SarA) in the global regulation of virulence in S. aureus. Structure and function predictions were done using several computational tools and approaches to understand the nature of msa. A novel S. aureus microarray meta-database (SAMMD) was designed and developed to compare and contrast other transcriptomes with msa transcriptome. msa and sarA transcriptomes were generated using the microarray technology. Phenotypic and molecular assays were performed to support microarray results. The results show that msa is a putative transmembrane protein, with three transmembrane segments, a distinct N-terminal cleavable signal peptide, four phophorylation sites (two outside and two inside the membrane) and a binding site in the cytoplasmic region. Microarray results and comparative transcriptome analysis using SAMMD showed that several genes regulated by msa are also regulated by sarA. Based on these results I hypothesize that msa is a novel signal transducer, which modulates the activity of genes involved in virulence in a sar/\-dependent manner, while modulating the activity of genes involved in metabolism in a sar-4-independent manner

SAMMD: \u3ci\u3eStaphylococcus aureus\u3c/i\u3e Microarray Meta-Database

Background Staphylococcus aureus is an important human pathogen, causing a wide variety of diseases ranging from superficial skin infections to severe life threatening infections. S. aureus is one of the leading causes of nosocomial infections. Its ability to resist multiple antibiotics poses a growing public health problem. In order to understand the mechanism of pathogenesis of S. aureus, several global expression profiles have been developed. These transcriptional profiles included regulatory mutants of S. aureus and growth of wild type under different growth conditions. The abundance of these profiles has generated a large amount of data without a uniform annotation system to comprehensively examine them. We report the development of the Staphylococcus aureus Microarray meta-database (SAMMD) which includes data from all the published transcriptional profiles. SAMMD is a web-accessible database that helps users to perform a variety of analysis against and within the existing transcriptional profiles. Description SAMMD is a relational database that uses MySQL as the back end and PHP/JavaScript/DHTML as the front end. The database is normalized and consists of five tables, which holds information about gene annotations, regulated gene lists, experimental details, references, and other details. SAMMD data is collected from the peer-reviewed published articles. Data extraction and conversion was done using perl scripts while data entry was done through phpMyAdmin tool. The database is accessible via a web interface that contains several features such as a simple search by ORF ID, gene name, gene product name, advanced search using gene lists, comparing among datasets, browsing, downloading, statistics, and help. The database is licensed under General Public License (GPL). Conclusion SAMMD is hosted and available at http://www.bioinformatics.org/sammd/. Currently there are over 9500 entries for regulated genes, from 67 microarray experiments. SAMMD will help staphylococcal scientists to analyze their expression data and understand it at global level. It will also allow scientists to compare and contrast their transcriptome to that of the other published transcriptomes

SAMMD: Staphylococcus aureus Microarray Meta-Database

<p>Abstract</p> <p>Background</p> <p><it>Staphylococcus aureus </it>is an important human pathogen, causing a wide variety of diseases ranging from superficial skin infections to severe life threatening infections. <it>S. aureus </it>is one of the leading causes of nosocomial infections. Its ability to resist multiple antibiotics poses a growing public health problem. In order to understand the mechanism of pathogenesis of <it>S. aureus</it>, several global expression profiles have been developed. These transcriptional profiles included regulatory mutants of <it>S. aureus </it>and growth of wild type under different growth conditions. The abundance of these profiles has generated a large amount of data without a uniform annotation system to comprehensively examine them. We report the development of the <it>Staphylococcus aureus </it>Microarray meta-database (SAMMD) which includes data from all the published transcriptional profiles. SAMMD is a web-accessible database that helps users to perform a variety of analysis against and within the existing transcriptional profiles.</p> <p>Description</p> <p>SAMMD is a relational database that uses MySQL as the back end and PHP/JavaScript/DHTML as the front end. The database is normalized and consists of five tables, which holds information about gene annotations, regulated gene lists, experimental details, references, and other details. SAMMD data is collected from the peer-reviewed published articles. Data extraction and conversion was done using perl scripts while data entry was done through phpMyAdmin tool. The database is accessible via a web interface that contains several features such as a simple search by ORF ID, gene name, gene product name, advanced search using gene lists, comparing among datasets, browsing, downloading, statistics, and help. The database is licensed under General Public License (GPL).</p> <p>Conclusion</p> <p>SAMMD is hosted and available at <url>http://www.bioinformatics.org/sammd/</url>. Currently there are over 9500 entries for regulated genes, from 67 microarray experiments. SAMMD will help staphylococcal scientists to analyze their expression data and understand it at global level. It will also allow scientists to compare and contrast their transcriptome to that of the other published transcriptomes.</p

Structure and Function Predictions of the Msa Protein in \u3ci\u3eStaphylococcus aureus\u3c/i\u3e

Background Staphylococcus aureus is a human pathogen that causes a wide variety of life-threatening infections using a large number of virulence factors. One of the major global regulators used by S. aureus is the staphylococcal accessory regulator (sarA). We have identified and characterized a new gene (modulator of sarA: msa) that modulates the expression of sarA. Genetic and functional analysis shows that msa has a global effect on gene expression in S. aureus. However, the mechanism of Msa function is still unknown. Function predictions of Msa are complicated by the fact that it does not have a homologous partner in any other organism. This work aims at predicting the structure and function of the Msa protein. Results Preliminary sequence analysis showed that Msa is a putative membrane protein. It would therefore be very difficult to purify and crystallize Msa in order to acquire structure information about this protein. We have used several computational tools to predict the physico-chemical properties, secondary structural features, topology, 3D tertiary structure, binding sites, motifs/patterns/domains and cellular location. We have built a consensus that is derived from analysis using different algorithms to predict several structural features. We confirm that Msa is a putative membrane protein with three transmembrane regions. We also predict that Msa has phosphorylation sites and binding sites suggesting functions in signal transduction. Conclusion Based on our predictions we hypothesise that Msa is a novel signal transducer that might be involved in the interaction of the S. aureus with its environment

SATRAT: \u3ci\u3eStaphylococcus aureus\u3c/i\u3e Transcript Regulatory Network Analysis Tool

Staphylococcus aureus is a commensal organism that primarily colonizes the nose of healthy individuals. S. aureus causes a spectrum of infections that range from skin and soft-tissue infections to fatal invasive diseases. S. aureus uses a large number of virulence factors that are regulated in a coordinated fashion. The complex regulatory mechanisms have been investigated in numerous high-throughput experiments. Access to this data is critical to studying this pathogen. Previously, we developed a compilation of microarray experimental data to enable researchers to search, browse, compare, and contrast transcript profiles. We have substantially updated this database and have built a novel exploratory tool—SATRAT—the S. aureus transcript regulatory network analysis tool, based on the updated database. This tool is capable of performing deep searches using a query and generating an interactive regulatory network based on associations among the regulators of any query gene. We believe this integrated regulatory network analysis tool would help researchers explore the missing links and identify novel pathways that regulate virulence in S. aureus. Also, the data model and the network generation code used to build this resource is open sourced, enabling researchers to build similar resources for other bacterial systems

The Role of \u3ci\u3emsa\u3c/i\u3e in \u3ci\u3eStaphylococcus aureus\u3c/i\u3e Biofilm Formation

BackgroundStaphylococcus aureus is an important pathogen that forms biofilms. The global regulator sarA is essential for biofilm formation. Since the modulator of sarA (msa) is required for full expression of sarA and regulates several virulence factors, we examined the capacity of the msa mutant to form biofilm. ResultsWe found that mutation of msa results in reduced expression of sarA in biofilm and that the msa mutant formed a weak and unstable biofilm. The msa mutant is able to adhere to surfaces and begins to form biofilm but fails to mature indicating that the defect of the msa mutant biofilm is in the accumulation stage but not in primary adhesion. ConclusionThe msa gene plays an important role in biofilm development which is likely due to its role in modulating the expression of sarA. This finding is significant because it identifies a new gene that plays a role in the development of biofilm

The Role of msa in Staphylococcus aureus Biofilm Formation

<p>Abstract</p> <p>Background</p> <p><it>Staphylococcus aureus </it>is an important pathogen that forms biofilms. The global regulator <it>sarA </it>is essential for biofilm formation. Since the modulator of <it>sarA </it>(<it>msa</it>) is required for full expression of <it>sarA </it>and regulates several virulence factors, we examined the capacity of the <it>msa </it>mutant to form biofilm.</p> <p>Results</p> <p>We found that mutation of <it>msa </it>results in reduced expression of <it>sarA </it>in biofilm and that the <it>msa </it>mutant formed a weak and unstable biofilm. The <it>msa </it>mutant is able to adhere to surfaces and begins to form biofilm but fails to mature indicating that the defect of the <it>msa </it>mutant biofilm is in the accumulation stage but not in primary adhesion.</p> <p>Conclusion</p> <p>The <it>msa </it>gene plays an important role in biofilm development which is likely due to its role in modulating the expression of <it>sarA</it>. This finding is significant because it identifies a new gene that plays a role in the development of biofilm.</p

A Fourier Transformation Based Method to Mine Peptide Space for Antimicrobial Activity

Background Naturally occurring antimicrobial peptides are currently being explored as potential candidate peptide drugs. Since antimicrobial peptides are part of the innate immune system of every living organism, it is possible to discover new candidate peptides using the available genomic and proteomic data. High throughput computational techniques could also be used to virtually scan the entire peptide space for discovering out new candidate antimicrobial peptides. Result We have identified a unique indexing method based on biologically distinct characteristic features of known antimicrobial peptides. Analysis of the entries in the antimicrobial peptide databases, based on our indexing method, using Fourier transformation technique revealed a distinct peak in their power spectrum. We have developed a method to mine the genomic and proteomic data, for the presence of peptides with potential antimicrobial activity, by looking for this distinct peak. We also used the Euclidean metric to rank the potential antimicrobial peptides activity. We have parallelized our method so that virtually any given protein space could be data mined, in search of antimicrobial peptides. Conclusion The results show that the Fourier transform based method with the property based coding strategy could be used to scan the peptide space for discovering new potential antimicrobial peptides