Evaluation of whole-genome sequencing for outbreak detection of Verotoxigenic Escherichia coli O157:H7 from the Canadian perspective

Journal article


Rumore, Jillian, Tschetter, Lorelee, Kearney, Ashley, Kandar, Rima, McCormick, Rachel, Walker, Matthew, Peterson, Christy-Lynn, Reimer, Aleisha and Nadon, Celine. (2018). Evaluation of whole-genome sequencing for outbreak detection of Verotoxigenic Escherichia coli O157:H7 from the Canadian perspective. BMC Genomics. 19(1), p. Article 870. https://doi.org/10.1186/s12864-018-5243-3
AuthorsRumore, Jillian, Tschetter, Lorelee, Kearney, Ashley, Kandar, Rima, McCormick, Rachel, Walker, Matthew, Peterson, Christy-Lynn, Reimer, Aleisha and Nadon, Celine
Abstract

Background
Rapid and accurate identification of Verotoxigenic Escherichia coli (VTEC) O157:H7 is dependent on well-established, standardized and highly discriminatory typing methods. Currently, conventional subtyping tests for foodborne bacterial pathogen surveillance are rapidly being replaced with whole-genome sequencing (WGS) in public health laboratories. The capacity of WGS to revolutionize global foodborne disease surveillance has positioned this tool to become the new gold standard; however, to ensure evidence standards for public health decision making can still be achieved, the performance of WGS must be thoroughly validated against current gold standard methods prior to implementation. Here we aim to verify the performance of WGS in comparison to pulsed-field gel electrophoresis (PFGE) and multiple-locus variable-number tandem repeat analysis (MLVA) for eight retrospective outbreaks of VTEC O157:H7 from the Canadian perspective. Since real-time implementation and routine use of WGS in public health laboratories is highly reliant on standardized data analysis tools, we also provide a comparative analysis of two popular methodologies for WGS analyses; an in-house developed single nucleotide variant phylogenomics (SNVPhyl) pipeline and the BioNumerics whole genome multilocus sequence typing (wgMLST) tool. To provide a useful and consistent starting point for examining laboratory-based surveillance data for VTEC O157:H7 in Canada, we also aim to describe the number of genetic differences observed among outbreak-associated isolates.

Results
WGS provided enhanced resolution over traditional subtyping methods, and accurately distinguished outbreak-related isolates from non-outbreak related isolates with high epidemiological concordance. WGS also illuminated potential linkages between sporadic cases of illness and contaminated food, and isolates spanning multiple years. The topologies generated by SNVPhyl and wgMLST were highly congruent with strong statistical support. Few genetic differences were observed among outbreak-related isolates (≤5 SNVs/ < 10 wgMLST alleles) unless the outbreak was suspected to be multi-strain.

Conclusions
This study validates the superiority of WGS and indicates the BioNumerics wgMLST schema is suitable for surveillance and cluster detection of VTEC O157:H7. These findings will provide a useful and consistent starting point for examining WGS data for prospective laboratory-based surveillance of VTEC O157:H7, but however, the data will continue to be interpreted according to context and in combination with epidemiological and food safety evidence to inform public-health decision making in Canada.

KeywordsVTEC; escherichia coli; O157:H7; whole genome sequencing; outbreak; wgMLST; SNVPhyl
Year2018
JournalBMC Genomics
Journal citation19 (1), p. Article 870
PublisherBiomed Central Ltd
ISSN1471-2164
Digital Object Identifier (DOI)https://doi.org/10.1186/s12864-018-5243-3
PubMed ID30514209
Scopus EID2-s2.0-85057959304
PubMed Central IDPMC6278084
Open accessPublished as ‘gold’ (paid) open access
Page range1-13
FunderPublic Health Agency of Canada
Publisher's version
License
File Access Level
Open
Output statusPublished
Publication dates
Online04 Dec 2018
Publication process dates
Accepted13 Nov 2018
Deposited08 Apr 2025
Additional information

© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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