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Whole-Genome Sequencing and Bioinformatic Analysis of Isolates from Foodborne Illness Outbreaks of Campylobacter jejuni and Salmonella enterica
Whole-genome sequencing (WGS) via next-generation sequencing (NGS) technologies is a powerful tool for determining the relatedness of bacterial isolates in foodborne illness detection and outbreak investigations. WGS has been applied to national outbreaks (for example, Listeria monocytogenes); howev...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Microbiology
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6204689/ https://www.ncbi.nlm.nih.gov/pubmed/30158193 http://dx.doi.org/10.1128/JCM.00161-18 |
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author | Oakeson, Kelly F. Wagner, Jennifer Marie Rohrwasser, Andreas Atkinson-Dunn, Robyn |
author_facet | Oakeson, Kelly F. Wagner, Jennifer Marie Rohrwasser, Andreas Atkinson-Dunn, Robyn |
author_sort | Oakeson, Kelly F. |
collection | PubMed |
description | Whole-genome sequencing (WGS) via next-generation sequencing (NGS) technologies is a powerful tool for determining the relatedness of bacterial isolates in foodborne illness detection and outbreak investigations. WGS has been applied to national outbreaks (for example, Listeria monocytogenes); however, WGS has rarely been used in smaller local outbreaks. The current study demonstrates the superior resolution of genetic and evolutionary relatedness generated by WGS data analysis, compared to pulsed-field gel electrophoresis (PFGE). The current study retrospectively applies WGS and a reference-free bioinformatic analysis to a Utah-specific outbreak of Campylobacter jejuni associated with raw milk and to a national multistate outbreak of Salmonella enterica subsp. enterica serovar Typhimurium associated with rotisserie chicken, both of which were characterized previously by PFGE. Together, these analyses demonstrate how a reference-free WGS workflow is not reliant on determination of a reference sequence, like WGS workflows that are based on single-nucleotide polymorphisms, or the need for curated allele databases, like multilocus sequence typing workflows. |
format | Online Article Text |
id | pubmed-6204689 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Society for Microbiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-62046892018-11-15 Whole-Genome Sequencing and Bioinformatic Analysis of Isolates from Foodborne Illness Outbreaks of Campylobacter jejuni and Salmonella enterica Oakeson, Kelly F. Wagner, Jennifer Marie Rohrwasser, Andreas Atkinson-Dunn, Robyn J Clin Microbiol Bacteriology Whole-genome sequencing (WGS) via next-generation sequencing (NGS) technologies is a powerful tool for determining the relatedness of bacterial isolates in foodborne illness detection and outbreak investigations. WGS has been applied to national outbreaks (for example, Listeria monocytogenes); however, WGS has rarely been used in smaller local outbreaks. The current study demonstrates the superior resolution of genetic and evolutionary relatedness generated by WGS data analysis, compared to pulsed-field gel electrophoresis (PFGE). The current study retrospectively applies WGS and a reference-free bioinformatic analysis to a Utah-specific outbreak of Campylobacter jejuni associated with raw milk and to a national multistate outbreak of Salmonella enterica subsp. enterica serovar Typhimurium associated with rotisserie chicken, both of which were characterized previously by PFGE. Together, these analyses demonstrate how a reference-free WGS workflow is not reliant on determination of a reference sequence, like WGS workflows that are based on single-nucleotide polymorphisms, or the need for curated allele databases, like multilocus sequence typing workflows. American Society for Microbiology 2018-10-25 /pmc/articles/PMC6204689/ /pubmed/30158193 http://dx.doi.org/10.1128/JCM.00161-18 Text en Copyright © 2018 Oakeson et al. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Bacteriology Oakeson, Kelly F. Wagner, Jennifer Marie Rohrwasser, Andreas Atkinson-Dunn, Robyn Whole-Genome Sequencing and Bioinformatic Analysis of Isolates from Foodborne Illness Outbreaks of Campylobacter jejuni and Salmonella enterica |
title | Whole-Genome Sequencing and Bioinformatic Analysis of Isolates from Foodborne Illness Outbreaks of Campylobacter jejuni and Salmonella enterica |
title_full | Whole-Genome Sequencing and Bioinformatic Analysis of Isolates from Foodborne Illness Outbreaks of Campylobacter jejuni and Salmonella enterica |
title_fullStr | Whole-Genome Sequencing and Bioinformatic Analysis of Isolates from Foodborne Illness Outbreaks of Campylobacter jejuni and Salmonella enterica |
title_full_unstemmed | Whole-Genome Sequencing and Bioinformatic Analysis of Isolates from Foodborne Illness Outbreaks of Campylobacter jejuni and Salmonella enterica |
title_short | Whole-Genome Sequencing and Bioinformatic Analysis of Isolates from Foodborne Illness Outbreaks of Campylobacter jejuni and Salmonella enterica |
title_sort | whole-genome sequencing and bioinformatic analysis of isolates from foodborne illness outbreaks of campylobacter jejuni and salmonella enterica |
topic | Bacteriology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6204689/ https://www.ncbi.nlm.nih.gov/pubmed/30158193 http://dx.doi.org/10.1128/JCM.00161-18 |
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