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

i

Zoonotic Source Attribution of Salmonella enterica Serotype Typhimurium Using Genomic Surveillance Data, United States

Supporting Files Public Domain

January 2019
By Zhang, Shaokang ; Li, Shaoting ; Gu, Weidong ; ...

File Language:

English

Details

Alternative Title:

Emerg Infect Dis
Personal 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
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.
Subjects:

Animals Case-Control Studies Disease Outbreaks Epidemiological Monitoring Foodborne Diseases Genomics Humans Livestock Phylogeny Research Retrospective Studies Salmonella Infections Salmonella Typhimurium Whole Genome Sequencing Zoonoses
Source:

Emerg Infect Dis. 25(1):82-91
Pubmed ID:

30561314
Pubmed Central ID:

PMC6302586
Document Type:

Journal Article
Place as Subject:

United States
Location:

North America
Volume:

25
Issue:

1
Collection(s):

Emerging Infectious Diseases
Main Document Checksum:

urn:sha256:f41d9f8d06835b4b6570370f21adc4b9865e90b15ec1a8a6e1007ce88e93368e
Download URL:

https://stacks.cdc.gov/view/cdc/75848/cdc_75848_DS1.pdf
File Type:

[PDF - 3.42 MB ]

File Language:

English

ON THIS PAGE

Details Supporting Files

CDC STACKS serves as an archival repository of CDC-published products including scientific findings, journal articles, guidelines, recommendations, or other public health information authored or co-authored by CDC or funded partners.

As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.