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1.  PIPS: Pathogenicity Island Prediction Software 
PLoS ONE  2012;7(2):e30848.
The adaptability of pathogenic bacteria to hosts is influenced by the genomic plasticity of the bacteria, which can be increased by such mechanisms as horizontal gene transfer. Pathogenicity islands play a major role in this type of gene transfer because they are large, horizontally acquired regions that harbor clusters of virulence genes that mediate the adhesion, colonization, invasion, immune system evasion, and toxigenic properties of the acceptor organism. Currently, pathogenicity islands are mainly identified in silico based on various characteristic features: (1) deviations in codon usage, G+C content or dinucleotide frequency and (2) insertion sequences and/or tRNA genetic flanking regions together with transposase coding genes. Several computational techniques for identifying pathogenicity islands exist. However, most of these techniques are only directed at the detection of horizontally transferred genes and/or the absence of certain genomic regions of the pathogenic bacterium in closely related non-pathogenic species. Here, we present a novel software suite designed for the prediction of pathogenicity islands (pathogenicity island prediction software, or PIPS). In contrast to other existing tools, our approach is capable of utilizing multiple features for pathogenicity island detection in an integrative manner. We show that PIPS provides better accuracy than other available software packages. As an example, we used PIPS to study the veterinary pathogen Corynebacterium pseudotuberculosis, in which we identified seven putative pathogenicity islands.
doi:10.1371/journal.pone.0030848
PMCID: PMC3280268  PMID: 22355329
2.  The Corynebacterium pseudotuberculosis in silico predicted pan-exoproteome 
BMC Genomics  2012;13(Suppl 5):S6.
Background
Pan-genomic studies aim, for instance, at defining the core, dispensable and unique genes within a species. A pan-genomics study for vaccine design tries to assess the best candidates for a vaccine against a specific pathogen. In this context, rather than studying genes predicted to be exported in a single genome, with pan-genomics it is possible to study genes present in different strains within the same species, such as virulence factors. The target organism of this pan-genomic work here presented is Corynebacterium pseudotuberculosis, the etiologic agent of caseous lymphadenitis (CLA) in goat and sheep, which causes significant economic losses in those herds around the world. Currently, only a few antigens against CLA are known as being the basis of commercial and still ineffective vaccines. In this regard, the here presented work analyses, in silico, five C. pseudotuberculosis genomes and gathers data to predict common exported proteins in all five genomes. These candidates were also compared to two recent C. pseudotuberculosis in vitro exoproteome results.
Results
The complete genome of five C. pseudotuberculosis strains (1002, C231, I19, FRC41 and PAT10) were submitted to pan-genomics analysis, yielding 306, 59 and 12 gene sets, respectively, representing the core, dispensable and unique in silico predicted exported pan-genomes. These sets bear 150 genes classified as secreted (SEC) and 227 as potentially surface exposed (PSE). Our findings suggest that the main C. pseudotuberculosis in vitro exoproteome could be greater, appended by a fraction of the 35 proteins formerly predicted as making part of the variant in vitro exoproteome. These genomes were manually curated for correct methionine initiation and redeposited with a total of 1885 homogenized genes.
Conclusions
The in silico prediction of exported proteins has allowed to define a list of putative vaccine candidate genes present in all five complete C. pseudotuberculosis genomes. Moreover, it has also been possible to define the in silico predicted dispensable and unique C. pseudotuberculosis exported proteins. These results provide in silico evidence to further guide experiments in the areas of vaccines, diagnosis and drugs. The work here presented is the first whole C. pseudotuberculosis in silico predicted pan-exoproteome completed till today.
doi:10.1186/1471-2164-13-S5-S6
PMCID: PMC3476999  PMID: 23095951

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