title: PIPS: pathogenicity island prediction software.
abstract: 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.
authors.affiliation: Department of General Biology, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
authors.forename: Siomar C
authors.initials: SC
authors.lastname: Soares
authors.forename: Vinícius A C
authors.initials: VA
authors.lastname: Abreu
authors.forename: Rommel T J
authors.initials: RT
authors.lastname: Ramos
authors.forename: Louise
authors.initials: L
authors.lastname: Cerdeira
authors.forename: Artur
authors.initials: A
authors.lastname: Silva
authors.forename: Jan
authors.initials: J
authors.lastname: Baumbach
authors.forename: Eva
authors.initials: E
authors.lastname: Trost
authors.forename: Andreas
authors.initials: A
authors.lastname: Tauch
authors.forename: Raphael
authors.initials: R
authors.lastname: Hirata
authors.forename: Ana L
authors.initials: AL
authors.lastname: Mattos-Guaraldi
authors.forename: Anderson
authors.initials: A
authors.lastname: Miyoshi
authors.forename: Vasco
authors.initials: V
authors.lastname: Azevedo
mesh_terms: D001419:Bacteria / Q000235:genetics* / Q000472:pathogenicity*; D001424:Bacterial Infections / Q000235:genetics / Q000382:microbiology / Q000473:pathology*; D019295:Computational Biology; D016680:Genome, Bacterial; D044404:Genomic Islands / Q000235:genetics*; D012984:Software; D014774:Virulence / Q000235:genetics*