Abstract
MotivationGenomic islands (GIs) are clusters of genes of probable horizontal origin that play a major role in bacterial and archaeal genome evolution and microbial adaptability. They are of high medical and industrial interest, due to their enrichment in virulence factors, some antimicrobial resistance genes and adaptive metabolic pathways. The development of more sensitive but precise prediction tools, using either sequence composition-based methods or comparative genomics, is needed as large-scale analyses of microbial genomes increase.ResultsIslandPath-DIMOB, a leading GI prediction tool in the IslandViewer webserver, has now been significantly improved by modifying both the decision algorithm to determine sequence composition biases, and the underlying database of HMM profiles for associated mobility genes. The accuracy of IslandPath-DIMOB and other major software has been assessed using a reference GI dataset predicted by comparative genomics, plus a manually curated dataset from literature review. Compared to the previous version (v0.2.0), this IslandPath-DIMOB v1.0.0 achieves 11.7% and 5.3% increase in recall and precision, respectively. IslandPath-DIMOB has the highest Matthews correlation coefficient among individual prediction methods tested, combining one of the highest recall measures (46.9%) at high precision (87.4%). The only method with higher recall had notably lower precision (55.1%). This new IslandPath-DIMOB v1.0.0 will facilitate more accurate studies of GIs, including their key roles in microbial adaptability of medical, environmental and industrial interest.Availability and implementationIslandPath-DIMOB v1.0.0 is freely available through the IslandViewer webserver {{http://www.pathogenomics.sfu.ca/islandviewer/}} and as standalone software {{https://github.com/brinkmanlab/islandpath/}} under the GNU-GPLv3.Supplementary information Supplementary data are available at Bioinformatics online.
Highlights
Horizontal gene transfer (HGT) is widely recognized as a major force that drives microbial genome evolution
To integrate the latest knowledge gathered from comparative genomics and refine the prediction of genomic islands (GIs), we have developed a new version of IslandPath-DIMOB, part of the IslandViewer suite of GI analysis tools (Bertelli et al, 2017), by implementing (i) a better score of dinucleotide bias to increase sensitivity, (ii) new extended HMM profiles to search for mobility genes, (iii) a better handling of pseudogenes and (iv) the concept of regions of GIs by considering closely positioned GIs as a single region
We report here a new version of IslandPath-DIMOB that significantly improves the identification of GIs in microbial genomes
Summary
Horizontal gene transfer (HGT) is widely recognized as a major force that drives microbial genome evolution. HGT enables bacteria and archaea to acquire foreign genetic material using various mechanisms, primarily conjugation, transduction and transformation (Dobrindt et al, 2004; Soucy et al, 2015). HGT disseminates beneficial, neutral and nearly neutral genes in integration hotspots, often tRNAs and tmRNAs, or interspersed within the core genome (Rodriguez-Valera et al, 2016). The core genome of bacteria generally only represents on average 50% of the total genome size (Rodriguez-Valera et al, 2016). Clusters of genes known or predicted to be acquired by HGT are called genomic islands (GIs), and were historically classified into different subtypes depending on the functions they encoded: symbiotic islands, metabolic islands, fitness islands, pathogenicity islands or antibiotic resistance islands (Hacker et al, 1990; Juhas et al, 2007, 2009; Sullivan and Ronson, 1998). GIs were shown to disproportionally encode virulence factors (Ho Sui et al, 2009) and to be an important source of novel genes (Hsiao et al, 2005), antimicrobial resistance genes (von Wintersdorff et al, 2016), and metabolic genes (Juhas et al, 2009)
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