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Shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria
The persuasiveness of genomic evidence has pressured scientific agencies to supplement or replace well-established methodologies to inform public health and food safety decision-making. This study of 52 epidemiologically defined Listeria monocytogenes isolates, collected between 1981 and 2011, inclu...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Microbiology Society
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412057/ https://www.ncbi.nlm.nih.gov/pubmed/30648944 http://dx.doi.org/10.1099/mgen.0.000237 |
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author | Reimer, Aleisha Weedmark, Kelly Petkau, Aaron Peterson, Christy-Lynn Walker, Matthew Knox, Natalie Kent, Heather Mabon, Philip Berry, Chrystal Tyler, Shaun Tschetter, Lorelee Jerome, Morganne Allen, Vanessa Hoang, Linda Bekal, Sadjia Clark, Clifford Nadon, Celine Van Domselaar, Gary Pagotto, Franco Graham, Morag Farber, Jeff Gilmour, Matthew |
author_facet | Reimer, Aleisha Weedmark, Kelly Petkau, Aaron Peterson, Christy-Lynn Walker, Matthew Knox, Natalie Kent, Heather Mabon, Philip Berry, Chrystal Tyler, Shaun Tschetter, Lorelee Jerome, Morganne Allen, Vanessa Hoang, Linda Bekal, Sadjia Clark, Clifford Nadon, Celine Van Domselaar, Gary Pagotto, Franco Graham, Morag Farber, Jeff Gilmour, Matthew |
author_sort | Reimer, Aleisha |
collection | PubMed |
description | The persuasiveness of genomic evidence has pressured scientific agencies to supplement or replace well-established methodologies to inform public health and food safety decision-making. This study of 52 epidemiologically defined Listeria monocytogenes isolates, collected between 1981 and 2011, including nine outbreaks, was undertaken (1) to characterize their phylogenetic relationship at finished genome-level resolution, (2) to elucidate the underlying genetic diversity within an endemic subtype, CC8, and (3) to re-evaluate the genetic relationship and epidemiology of a CC8-delimited outbreak in Canada in 2008. Genomes representing Canadian Listeria outbreaks between 1981 and 2010 were closed and manually annotated. Single nucleotide variants (SNVs) and horizontally acquired traits were used to generate phylogenomic models. Phylogenomic relationships were congruent with classical subtyping and epidemiology, except for CC8 outbreaks, wherein the distribution of SNV and prophages revealed multiple co-evolving lineages. Chronophyletic reconstruction of CC8 evolution indicates that prophage-related genetic changes among CC8 strains manifest as PFGE subtype reversions, obscuring the relationship between CC8 isolates, and complicating the public health interpretation of subtyping data, even at maximum genome resolution. The size of the shared genome interrogated did not change the genetic relationship measured between highly related isolates near the tips of the phylogenetic tree, illustrating the robustness of these approaches for routine public health applications where the focus is recent ancestry. The possibility exists for temporally and epidemiologically distinct events to appear related even at maximum genome resolution, highlighting the continued importance of epidemiological evidence. |
format | Online Article Text |
id | pubmed-6412057 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Microbiology Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-64120572019-03-12 Shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria Reimer, Aleisha Weedmark, Kelly Petkau, Aaron Peterson, Christy-Lynn Walker, Matthew Knox, Natalie Kent, Heather Mabon, Philip Berry, Chrystal Tyler, Shaun Tschetter, Lorelee Jerome, Morganne Allen, Vanessa Hoang, Linda Bekal, Sadjia Clark, Clifford Nadon, Celine Van Domselaar, Gary Pagotto, Franco Graham, Morag Farber, Jeff Gilmour, Matthew Microb Genom Research Article The persuasiveness of genomic evidence has pressured scientific agencies to supplement or replace well-established methodologies to inform public health and food safety decision-making. This study of 52 epidemiologically defined Listeria monocytogenes isolates, collected between 1981 and 2011, including nine outbreaks, was undertaken (1) to characterize their phylogenetic relationship at finished genome-level resolution, (2) to elucidate the underlying genetic diversity within an endemic subtype, CC8, and (3) to re-evaluate the genetic relationship and epidemiology of a CC8-delimited outbreak in Canada in 2008. Genomes representing Canadian Listeria outbreaks between 1981 and 2010 were closed and manually annotated. Single nucleotide variants (SNVs) and horizontally acquired traits were used to generate phylogenomic models. Phylogenomic relationships were congruent with classical subtyping and epidemiology, except for CC8 outbreaks, wherein the distribution of SNV and prophages revealed multiple co-evolving lineages. Chronophyletic reconstruction of CC8 evolution indicates that prophage-related genetic changes among CC8 strains manifest as PFGE subtype reversions, obscuring the relationship between CC8 isolates, and complicating the public health interpretation of subtyping data, even at maximum genome resolution. The size of the shared genome interrogated did not change the genetic relationship measured between highly related isolates near the tips of the phylogenetic tree, illustrating the robustness of these approaches for routine public health applications where the focus is recent ancestry. The possibility exists for temporally and epidemiologically distinct events to appear related even at maximum genome resolution, highlighting the continued importance of epidemiological evidence. Microbiology Society 2019-01-16 /pmc/articles/PMC6412057/ /pubmed/30648944 http://dx.doi.org/10.1099/mgen.0.000237 Text en © 2019 The Authors and Her Majesty the Queen in Right of Canada http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Reimer, Aleisha Weedmark, Kelly Petkau, Aaron Peterson, Christy-Lynn Walker, Matthew Knox, Natalie Kent, Heather Mabon, Philip Berry, Chrystal Tyler, Shaun Tschetter, Lorelee Jerome, Morganne Allen, Vanessa Hoang, Linda Bekal, Sadjia Clark, Clifford Nadon, Celine Van Domselaar, Gary Pagotto, Franco Graham, Morag Farber, Jeff Gilmour, Matthew Shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria |
title | Shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria |
title_full | Shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria |
title_fullStr | Shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria |
title_full_unstemmed | Shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria |
title_short | Shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria |
title_sort | shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412057/ https://www.ncbi.nlm.nih.gov/pubmed/30648944 http://dx.doi.org/10.1099/mgen.0.000237 |
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