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PIPS: pathogenicity island prediction software

Soares, Siomar C ; Abreu, Vinícius A C ; Ramos, Rommel T J ; Cerdeira, Louise ; Silva, Artur ; Baumbach, Jan ; Trost, Eva ; Tauch, Andreas ; Hirata, Jr, Raphael ; Mattos-Guaraldi, Ana L ; Miyoshi, Anderson ; Azevedo, Vasco Mokrousov, Igor

PloS one, 2012-02, Vol.7 (2), p.e30848 [Periódico revisado por pares]

United States: Public Library of Science

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Título:
PIPS: pathogenicity island prediction software
Autor: Soares, Siomar C ; Abreu, Vinícius A C ; Ramos, Rommel T J ; Cerdeira, Louise ; Silva, Artur ; Baumbach, Jan ; Trost, Eva ; Tauch, Andreas ; Hirata, Jr, Raphael ; Mattos-Guaraldi, Ana L ; Miyoshi, Anderson ; Azevedo, Vasco
Mokrousov, Igor
Assuntos: Adaptability ; Adaptation ; Amino acids ; Bacteria ; Bacteria - genetics ; Bacteria - pathogenicity ; Bacterial Infections - genetics ; Bacterial Infections - microbiology ; Bacterial Infections - pathology ; Biochemistry ; Biology ; Chromosomes ; Codon ; Codons ; Colonization ; Computational Biology ; Computer applications ; Computer programs ; Computer Science ; Corynebacterium diphtheriae ; Corynebacterium glutamicum ; Deoxyribonucleic acid ; DNA ; E coli ; Escherichia coli ; Gene sequencing ; Gene transfer ; Genes ; Genetics ; Genome, Bacterial ; Genomes ; Genomic Islands - genetics ; Immune system ; Immunology ; Insertion ; Insertion sequences ; Islands ; Mutation ; Organisms ; Pathogenesis ; Pathogenicity ; Pathogenicity islands ; Pathogens ; Pseudotuberculosis ; Software ; Software packages ; Transfer RNA ; Transposase ; tRNA ; Veterinary medicine ; Veterinary Science ; Virulence ; Virulence - genetics
É parte de: PloS one, 2012-02, Vol.7 (2), p.e30848
Notas: Conceived and designed the experiments: AM VA. Performed the experiments: SCS VACA RTJR LC AS. Analyzed the data: SCS VACA RTJR LC AS JB ET AT RH ALMG AM VA. Contributed reagents/materials/analysis tools: SCS VACA RTJR LC AS JB ET AT RH ALMG AM VA. Wrote the paper: SCS VACA RTJR LC AS JB ET AT RH ALMG AM VA. Read and gave insights about the software: SCS VACA RTJR LC AS JB ET AT RH ALMG AM VA.
Descrição: 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.
Editor: United States: Public Library of Science
Idioma: Inglês

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PIPS: pathogenicity island prediction software

Soares, Siomar C ; Abreu, Vinícius A C ; Ramos, Rommel T J ; Cerdeira, Louise ; Silva, Artur ; Baumbach, Jan ; Trost, Eva ; Tauch, Andreas ; Hirata, Jr, Raphael ; Mattos-Guaraldi, Ana L ; Miyoshi, Anderson ; Azevedo, Vasco Mokrousov, Igor

United States: Public Library of Science

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