PIPS: Pathogenicity Island Prediction Software

Soares SC, Abreu VAC, Ramos RTJ, Cerdeira L, Silva A, Baumbach J, Trost E, Tauch A, Hirata RJ, Mattos-Guaraldi AL, Miyoshi A, et al. (2012)
PLoS ONE 7(2): e30848.

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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.
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Soares SC, Abreu VAC, Ramos RTJ, et al. PIPS: Pathogenicity Island Prediction Software. PLoS ONE. 2012;7(2): e30848.
Soares, S. C., Abreu, V. A. C., Ramos, R. T. J., Cerdeira, L., Silva, A., Baumbach, J., Trost, E., et al. (2012). PIPS: Pathogenicity Island Prediction Software. PLoS ONE, 7(2), e30848. doi:10.1371/journal.pone.0030848
Soares, S. C., Abreu, V. A. C., Ramos, R. T. J., Cerdeira, L., Silva, A., Baumbach, J., Trost, E., Tauch, A., Hirata, R. J., Mattos-Guaraldi, A. L., et al. (2012). PIPS: Pathogenicity Island Prediction Software. PLoS ONE 7:e30848.
Soares, S.C., et al., 2012. PIPS: Pathogenicity Island Prediction Software. PLoS ONE, 7(2): e30848.
S.C. Soares, et al., “PIPS: Pathogenicity Island Prediction Software”, PLoS ONE, vol. 7, 2012, : e30848.
Soares, S.C., Abreu, V.A.C., Ramos, R.T.J., Cerdeira, L., Silva, A., Baumbach, J., Trost, E., Tauch, A., Hirata, R.J., Mattos-Guaraldi, A.L., Miyoshi, A., Azevedo, V.: PIPS: Pathogenicity Island Prediction Software. PLoS ONE. 7, : e30848 (2012).
Soares, Siomar C., Abreu, Vinicius A. C., Ramos, Rommel T. J., Cerdeira, Louise, Silva, Artur, Baumbach, Jan, Trost, Eva, Tauch, Andreas, Hirata, Raphael Jr, Mattos-Guaraldi, Ana L., Miyoshi, Anderson, and Azevedo, Vasco. “PIPS: Pathogenicity Island Prediction Software”. PLoS ONE 7.2 (2012): e30848.
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32 Citations in Europe PMC

Data provided by Europe PubMed Central.

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Soares SC, Trost E, Ramos RT, Carneiro AR, Santos AR, Pinto AC, Barbosa E, Aburjaile F, Ali A, Diniz CA, Hassan SS, Fiaux K, Guimarães LC, Bakhtiar SM, Pereira U, Almeida SS, Abreu VA, Rocha FS, Dorella FA, Miyoshi A, Silva A, Azevedo V, Tauch A., J Biotechnol 167(2), 2013
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Ramos RT, Carneiro AR, Soares Sde C, dos Santos AR, Almeida S, Guimarães L, Figueira F, Barbosa E, Tauch A, Azevedo V, Silva A., Microb Biotechnol 6(2), 2013
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The pan-genome of the animal pathogen Corynebacterium pseudotuberculosis reveals differences in genome plasticity between the biovar ovis and equi strains.
Soares SC, Silva A, Trost E, Blom J, Ramos R, Carneiro A, Ali A, Santos AR, Pinto AC, Diniz C, Barbosa EG, Dorella FA, Aburjaile F, Rocha FS, Nascimento KK, Guimarães LC, Almeida S, Hassan SS, Bakhtiar SM, Pereira UP, Abreu VA, Schneider MP, Miyoshi A, Tauch A, Azevedo V., PLoS One 8(1), 2013
PMID: 23342011
Pangenomic study of Corynebacterium diphtheriae that provides insights into the genomic diversity of pathogenic isolates from cases of classical diphtheria, endocarditis, and pneumonia.
Trost E, Blom J, Soares Sde C, Huang IH, Al-Dilaimi A, Schröder J, Jaenicke S, Dorella FA, Rocha FS, Miyoshi A, Azevedo V, Schneider MP, Silva A, Camello TC, Sabbadini PS, Santos CS, Santos LS, Hirata R, Mattos-Guaraldi AL, Efstratiou A, Schmitt MP, Ton-That H, Tauch A., J Bacteriol 194(12), 2012
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Ali A, Soares SC, Santos AR, Guimarães LC, Barbosa E, Almeida SS, Abreu VA, Carneiro AR, Ramos RT, Bakhtiar SM, Hassan SS, Ussery DW, On S, Silva A, Schneider MP, Lage AP, Miyoshi A, Azevedo V., Gene 508(2), 2012
PMID: 22890137

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