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Zoonotic Source Attribution of Salmonella enterica Serotype Typhimurium Using Genomic Surveillance Data, United States
Increasingly, routine surveillance and monitoring of foodborne pathogens using whole-genome sequencing is creating opportunities to study foodborne illness epidemiology beyond routine outbreak investigations and case–control studies. Using a global phylogeny of Salmonella enterica serotype Typhimuri...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Centers for Disease Control and Prevention
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6302586/ https://www.ncbi.nlm.nih.gov/pubmed/30561314 http://dx.doi.org/10.3201/eid2501.180835 |
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author | Zhang, Shaokang Li, Shaoting Gu, Weidong den Bakker, Henk Boxrud, Dave Taylor, Angie Roe, Chandler Driebe, Elizabeth Engelthaler, David M. Allard, Marc Brown, Eric McDermott, Patrick Zhao, Shaohua Bruce, Beau B. Trees, Eija Fields, Patricia I. Deng, Xiangyu |
author_facet | Zhang, Shaokang Li, Shaoting Gu, Weidong den Bakker, Henk Boxrud, Dave Taylor, Angie Roe, Chandler Driebe, Elizabeth Engelthaler, David M. Allard, Marc Brown, Eric McDermott, Patrick Zhao, Shaohua Bruce, Beau B. Trees, Eija Fields, Patricia I. Deng, Xiangyu |
author_sort | Zhang, Shaokang |
collection | PubMed |
description | Increasingly, routine surveillance and monitoring of foodborne pathogens using whole-genome sequencing is creating opportunities to study foodborne illness epidemiology beyond routine outbreak investigations and case–control studies. Using a global phylogeny of Salmonella enterica serotype Typhimurium, we found that major livestock sources of the pathogen in the United States can be predicted through whole-genome sequencing data. Relatively steady rates of sequence divergence in livestock lineages enabled the inference of their recent origins. Elevated accumulation of lineage-specific pseudogenes after divergence from generalist populations and possible metabolic acclimation in a representative swine isolate indicates possible emergence of host adaptation. We developed and retrospectively applied a machine learning Random Forest classifier for genomic source prediction of Salmonella Typhimurium that correctly attributed 7 of 8 major zoonotic outbreaks in the United States during 1998–2013. We further identified 50 key genetic features that were sufficient for robust livestock source prediction. |
format | Online Article Text |
id | pubmed-6302586 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Centers for Disease Control and Prevention |
record_format | MEDLINE/PubMed |
spelling | pubmed-63025862019-01-01 Zoonotic Source Attribution of Salmonella enterica Serotype Typhimurium Using Genomic Surveillance Data, United States Zhang, Shaokang Li, Shaoting Gu, Weidong den Bakker, Henk Boxrud, Dave Taylor, Angie Roe, Chandler Driebe, Elizabeth Engelthaler, David M. Allard, Marc Brown, Eric McDermott, Patrick Zhao, Shaohua Bruce, Beau B. Trees, Eija Fields, Patricia I. Deng, Xiangyu Emerg Infect Dis Research Increasingly, routine surveillance and monitoring of foodborne pathogens using whole-genome sequencing is creating opportunities to study foodborne illness epidemiology beyond routine outbreak investigations and case–control studies. Using a global phylogeny of Salmonella enterica serotype Typhimurium, we found that major livestock sources of the pathogen in the United States can be predicted through whole-genome sequencing data. Relatively steady rates of sequence divergence in livestock lineages enabled the inference of their recent origins. Elevated accumulation of lineage-specific pseudogenes after divergence from generalist populations and possible metabolic acclimation in a representative swine isolate indicates possible emergence of host adaptation. We developed and retrospectively applied a machine learning Random Forest classifier for genomic source prediction of Salmonella Typhimurium that correctly attributed 7 of 8 major zoonotic outbreaks in the United States during 1998–2013. We further identified 50 key genetic features that were sufficient for robust livestock source prediction. Centers for Disease Control and Prevention 2019-01 /pmc/articles/PMC6302586/ /pubmed/30561314 http://dx.doi.org/10.3201/eid2501.180835 Text en https://creativecommons.org/licenses/by/4.0/This is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited. |
spellingShingle | Research Zhang, Shaokang Li, Shaoting Gu, Weidong den Bakker, Henk Boxrud, Dave Taylor, Angie Roe, Chandler Driebe, Elizabeth Engelthaler, David M. Allard, Marc Brown, Eric McDermott, Patrick Zhao, Shaohua Bruce, Beau B. Trees, Eija Fields, Patricia I. Deng, Xiangyu Zoonotic Source Attribution of Salmonella enterica Serotype Typhimurium Using Genomic Surveillance Data, United States |
title | Zoonotic Source Attribution of Salmonella enterica Serotype Typhimurium Using Genomic Surveillance Data, United States |
title_full | Zoonotic Source Attribution of Salmonella enterica Serotype Typhimurium Using Genomic Surveillance Data, United States |
title_fullStr | Zoonotic Source Attribution of Salmonella enterica Serotype Typhimurium Using Genomic Surveillance Data, United States |
title_full_unstemmed | Zoonotic Source Attribution of Salmonella enterica Serotype Typhimurium Using Genomic Surveillance Data, United States |
title_short | Zoonotic Source Attribution of Salmonella enterica Serotype Typhimurium Using Genomic Surveillance Data, United States |
title_sort | zoonotic source attribution of salmonella enterica serotype typhimurium using genomic surveillance data, united states |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6302586/ https://www.ncbi.nlm.nih.gov/pubmed/30561314 http://dx.doi.org/10.3201/eid2501.180835 |
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