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Volume 8, Issue 5

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

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 -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).

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): antimicrobial resistance , comparative genomics , genomic islands , interactive visualization and web server
Funding
This study was supported by the:
  • Canadian Institutes of Health Research
    • Principle Award Recipient: AndrewG McArthur
  • Genome Canada
    • Principle Award Recipient: AndrewG McArthur
  • David Braley Chair in Computational Biology
    • Principle Award Recipient: AndrewG McArthur
  • Cisco Research Chair in Bioinformatics
    • Principle Award Recipient: AndrewG McArthur
  • Simon Fraser University (Award SFU Big Data Graduate Scholarship)
    • Principle Award Recipient: KristenLeanne Gray
  • Omics and Data Science Initiative, Simon Fraser University (Award Omics Data Science Initiative Graduate Scholarship)
    • Principle Award Recipient: KristenLeanne Gray
  • Simon Fraser University (Award Weyerhaeuser Graduate Scholarship)
    • Principle Award Recipient: KristenLeanne Gray
  • Natural Sciences and Engineering Research Council of Canada (Award UBC/SFU NSERC-CREATE Bioinformatics Scholarship)
    • Principle Award Recipient: KristenLeanne Gray
  • Canadian Institutes of Health Research (Award Frederick Banting and Charles Best Canada Graduate Scholarship)
    • Principle Award Recipient: KristenLeanne Gray
  • Société Académique Vaudoise
    • Principle Award Recipient: ClaireBertelli
  • Swiss National Science Foundation (Award P300-PA_164673)
    • Principle Award Recipient: ClaireBertelli
  • Genome Canada
    • Principle Award Recipient: FionaSL Brinkman
  • Canadian Institutes of Health Research
    • Principle Award Recipient: FionaSL Brinkman
© 2022 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
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2022-05-18
2024-12-06
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Enabling genomic island prediction and comparison in multiple genomes to investigate bacterial evolution and outbreaks
M Gen 8, 000818 (2022); https://doi.org/10.1099/mgen.0.000818
/content/journal/mgen/10.1099/mgen.0.000818
/content/journal/mgen/10.1099/mgen.0.000818
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