Enabling genomic island prediction and comparison in multiple genomes to investigate bacterial evolution and outbreaks

Author:

Bertelli Claire12ORCID,Gray Kristen L.2ORCID,Woods Nolan2,Lim Adrian C.2,Tilley Keith E.2,Winsor Geoffrey L.2ORCID,Hoad Gemma R.3,Roudgar Ata3,Spencer Adam3,Peltier James3,Warren Derek3,Raphenya Amogelang R.456ORCID,McArthur Andrew G.645ORCID,Brinkman Fiona S. L.2ORCID

Affiliation:

1. Institute of Microbiology, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland

2. Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada

3. Research Computing Group, Simon Fraser University, Burnaby, BC, Canada

4. Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada

5. Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON, Canada

6. David Braley Centre for Antibiotic Discovery, McMaster University, Hamilton, ON, Canada

Abstract

Outbreaks of virulent and/or drug-resistant bacteria have a significant impact on human health and major economic consequences. Genomic islands (GIs; defined as clusters of genes of probable horizontal origin) are of high interest because they disproportionately encode virulence factors, some antimicrobial-resistance (AMR) genes, and other adaptations of medical or environmental interest. While microbial genome sequencing has become rapid and inexpensive, current computational methods for GI analysis are not amenable for rapid, accurate, user-friendly and scalable comparative analysis of sets of related genomes. To help fill this gap, we have developed IslandCompare, an open-source computational pipeline for GI prediction and comparison across several to hundreds of bacterial genomes. A dynamic and interactive visualization strategy displays a bacterial core-genome phylogeny, with bacterial genomes linearly displayed at the phylogenetic tree leaves. Genomes are overlaid with GI predictions and AMR determinants from the Comprehensive Antibiotic Resistance Database (CARD), and regions of similarity between the genomes are also displayed. GI predictions are performed using Sigi-HMM and IslandPath-DIMOB, the two most precise GI prediction tools based on nucleotide composition biases, as well as a novel blast-based consistency step to improve cross-genome prediction consistency. GIs across genomes sharing sequence similarity are grouped into clusters, further aiding comparative analysis and visualization of acquisition and loss of mobile GIs in specific sub-clades. IslandCompare is an open-source software that is containerized for local use, plus available via a user-friendly, web-based interface to allow direct use by bioinformaticians, biologists and clinicians (at https://islandcompare.ca).

Funder

Canadian Institutes of Health Research

Société Académique Vaudoise

Genome Canada

Simon Fraser University

Cisco Research Chair in Bioinformatics

David Braley Chair in Computational Biology

Swiss National Science Foundation

Omics and Data Science Initiative, Simon Fraser University

Natural Sciences and Engineering Research Council of Canada

Publisher

Microbiology Society

Subject

General Medicine

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