Computational Bacterial Genome-Wide Analysis of Phylogenetic Profiles Reveals Potential Virulence Genes of Streptococcus agalactiae

被引:24
作者
Lin, Frank Po-Yen [1 ]
Lan, Ruiting [2 ]
Sintchenko, Vitali [1 ,3 ,4 ]
Gilbert, Gwendolyn L. [3 ,4 ]
Kong, Fanrong [3 ,4 ]
Coiera, Enrico [1 ]
机构
[1] Univ New S Wales, Ctr Hlth Informat, Sydney, NSW, Australia
[2] Univ New S Wales, Sch Biotechnol & Biomol Sci, Sydney, NSW, Australia
[3] Univ Sydney, Westmead Hosp, Ctr Infect Dis & Microbiol Publ Hlth, Sydney, NSW 2006, Australia
[4] Univ Sydney, Sydney Med Sch, Sydney, NSW 2006, Australia
来源
PLOS ONE | 2011年 / 6卷 / 04期
基金
英国医学研究理事会;
关键词
HOST-PATHOGEN INTERACTIONS; NEISSERIA-MENINGITIDIS; STAPHYLOCOCCUS-AUREUS; PROTEIN; SEQUENCE; IDENTIFICATION; INFECTION; AFFINITY; ADHESIN; ISLANDS;
D O I
10.1371/journal.pone.0017964
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The phylogenetic profile of a gene is a reflection of its evolutionary history and can be defined as the differential presence or absence of a gene in a set of reference genomes. It has been employed to facilitate the prediction of gene functions. However, the hypothesis that the application of this concept can also facilitate the discovery of bacterial virulence factors has not been fully examined. In this paper, we test this hypothesis and report a computational pipeline designed to identify previously unknown bacterial virulence genes using group B streptococcus (GBS) as an example. Phylogenetic profiles of all GBS genes across 467 bacterial reference genomes were determined by candidate-against-all BLAST searches, which were then used to identify candidate virulence genes by machine learning models. Evaluation experiments with known GBS virulence genes suggested good functional and model consistency in cross-validation analyses (areas under ROC curve, 0.80 and 0.98 respectively). Inspection of the top-10 genes in each of the 15 virulence functional groups revealed at least 15 (of 119) homologous genes implicated in virulence in other human pathogens but previously unrecognized as potential virulence genes in GBS. Among these highly-ranked genes, many encode hypothetical proteins with possible roles in GBS virulence. Thus, our approach has led to the identification of a set of genes potentially affecting the virulence potential of GBS, which are potential candidates for further in vitro and in vivo investigations. This computational pipeline can also be extended to in silico analysis of virulence determinants of other bacterial pathogens.
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页数:10
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