Curation, integration and visualization of bacterial virulence factors in PATRIC.

MOTIVATION: We've developed a highly curated bacterial virulence factor (VF) library in PATRIC (Pathosystems Resource Integration Center, www.patricbrc.org) to support infectious disease research. Although several VF databases are available, there is still a need to incorporate new knowledge found in published experimental evidence and integrate these data with other information known for these specific VF genes, including genomic and other omics data. This integration supports the identification of VFs, comparative studies and hypothesis generation, which facilitates the understanding of virulence and pathogenicity. RESULTS: We have manually curated VFs from six prioritized NIAID (National Institute of Allergy and Infectious Diseases) category A-C bacterial pathogen genera, Mycobacterium, Salmonella, Escherichia, Shigella, Listeria and Bartonella, using published literature. This curated information on virulence has been integrated with data from genomic functional annotations, trancriptomic experiments, protein-protein interactions and disease information already present in PATRIC. Such integration gives researchers access to a broad array of information about these individual genes, and also to a suite of tools to perform comparative genomic and transcriptomics analysis that are available at PATRIC. AVAILABILITY AND IMPLEMENTATION: All tools and data are freely available at PATRIC (http://patricbrc.org). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PATRIC, the bacterial bioinformatics database and analysis resource.

The Pathosystems Resource Integration Center (PATRIC) is the all-bacterial Bioinformatics Resource Center (BRC) (http://www.patricbrc.org). A joint effort by two of the original National Institute of Allergy and Infectious Diseases-funded BRCs, PATRIC provides researchers with an online resource that stores and integrates a variety of data types [e.g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data] and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes in PATRIC, currently more than 10,000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. All the data and integrated analysis and visualization tools are freely available. This manuscript describes updates to the PATRIC since its initial report in the 2007 NAR Database Issue.

Evolution of drug resistance in multiple distinct lineages of H5N1 avian influenza.

Some predict that influenza A H5N1 will be the cause of a pandemic among humans. In preparation for such an event, many governments and organizations have stockpiled antiviral drugs such as oseltamivir (Tamiflu). However, it is known that multiple lineages of H5N1 are already resistant to another class of drugs, adamantane derivatives, and a few lineages are resistant to oseltamivir. What is less well understood is the evolutionary history of the mutations that confer drug resistance in the H5N1 population. In order to address this gap, we conducted phylogenetic analyses of 676 genomic sequences of H5N1 and used the resulting hypotheses as a basis for asking 3 molecular evolutionary questions: (1) Have drug-resistant genotypes arisen in distinct lineages of H5N1 through point mutation or through reassortment? (2) Is there evidence for positive selection on the codons that lead to drug resistance? (3) Is there evidence for covariation between positions in the genome that confer resistance to drugs and other positions, unrelated to drug resistance, that may be under selection for other phenotypes? We also examine how drug-resistant lineages proliferate across the landscape by projecting or phylogenetic analysis onto a virtual globe. Our results for H5N1 show that in most cases drug resistance has arisen by independent point mutations rather than reassortment or covariation. Furthermore, we found that some codons that mediate resistance to adamantane derivatives are under positive selection, but did not find positive selection on codons that mediate resistance to oseltamivir. Together, our phylogenetic methods, molecular evolutionary analyses, and geographic visualization provide a framework for analysis of globally distributed genomic data that can be used to monitor the evolution of drug resistance.