Computational prediction and characterization of genomic islands: insights into bacterial pathogenicity

Abstract

Genomic islands (GIs), including pathogenicity islands, are commonly defined as clusters of genes in prokaryotic genomes that have probable horizontal origins. These genetic elements have been associated with rapid adaptations in prokaryotes that are of medical, economical or environmental importance, such as pathogen virulence, antibiotic resistance, symbiotic interactions, and notable secondary metabolic capabilities. As the number of genomic sequences increases, the impact of GIs in prokaryotic evolution has become more apparent and detecting these regions using bioinformatics approaches has become an integral part of studying microbial evolution and function. In this dissertation, I describe a novel comparative genomics approach for identifying GIs, called IslandPick, and the application of this method to construct robust datasets that were used to test the accuracy of several previously published GI prediction programs. In addition, I will discuss the features of a new GI web resource, called IslandViewer, which integrates the most accurate GI predictors currently available. Further, the role of several GI and prophage regions and their involvement in virulence in an epidemic Pseudomonas aeruginosa strain that infects cystic fibrosis patients will be described; as well as an observation that recently discovered phage defence elements, CRISPRs, are over-represented within GIs.