TY - JOUR
T1 - Whole genome DNA sequence analysis of Salmonella subspecies enterica serotype Tennessee obtained from related peanut butter foodborne outbreaks
AU - Wilson, Mark R.
AU - Brown, Eric
AU - Keys, Chris
AU - Strain, Errol
AU - Luo, Yan
AU - Muruvanda, Tim
AU - Grim, Christopher
AU - Beaubrun, Junia Jean Gilles
AU - Jarvis, Karen
AU - Ewing, Laura
AU - Gopinath, Gopal
AU - Hanes, Darcy
AU - Allard, Marc W.
AU - Musser, Steven
N1 - Publisher Copyright:
© This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
PY - 2016/6
Y1 - 2016/6
N2 - Establishing an association between possible food sources and clinical isolates requires discriminating the suspected pathogen from an environmental background, and distinguishing it from other closely-related foodborne pathogens. We used whole genome sequencing (WGS) to Salmonella subspecies enterica serotype Tennessee (S. Tennessee) to describe genomic diversity across the serovar as well as among and within outbreak clades of strains associated with contaminated peanut butter. We analyzed 71 isolates of S. Tennessee from disparate food, environmental, and clinical sources and 2 other closely-related Salmonella serovars as outgroups (S. Kentucky and S. Cubana), which were also shot-gun sequenced. A whole genome single nucleotide polymorphism (SNP) analysis was performed using a maximum likelihood approach to infer phylogenetic relationships. Several monophyletic lineages of S. Tennessee with limited SNP variability were identified that recapitulated several food contamination events. S. Tennessee cladeswere separated from outgroup salmonellae by more than sixteen thousand SNPs. Intra-serovar diversity of S. Tennessee was small compared to the chosen outgroups (1,153 SNPs), suggesting recent divergence of some S. Tennessee clades. Analysis of all 1,153 SNPs structuring an S. Tennessee peanut butter outbreak cluster revealed that isolates from several food, plant, and clinical isolates were very closely related, as they had only a few SNP differences between them. SNP-based cluster analyses linked specific food sources to several clinical S. Tennessee strains isolated in separate contamination events. Environmental and clinical isolates had very similar whole genome sequences; no markers were found that could be used to discriminate between these sources. Finally, we identified SNPs within variable S. Tennessee genes that may be useful markers for the development of rapid surveillance and typing methods, potentially aiding in traceback efforts during future outbreaks. Using WGS can delimit contamination sources for foodborne illnesses across multiple outbreaks and reveal otherwise undetected DNA sequence differences essential to the tracing of bacterial pathogens as they emerge.
AB - Establishing an association between possible food sources and clinical isolates requires discriminating the suspected pathogen from an environmental background, and distinguishing it from other closely-related foodborne pathogens. We used whole genome sequencing (WGS) to Salmonella subspecies enterica serotype Tennessee (S. Tennessee) to describe genomic diversity across the serovar as well as among and within outbreak clades of strains associated with contaminated peanut butter. We analyzed 71 isolates of S. Tennessee from disparate food, environmental, and clinical sources and 2 other closely-related Salmonella serovars as outgroups (S. Kentucky and S. Cubana), which were also shot-gun sequenced. A whole genome single nucleotide polymorphism (SNP) analysis was performed using a maximum likelihood approach to infer phylogenetic relationships. Several monophyletic lineages of S. Tennessee with limited SNP variability were identified that recapitulated several food contamination events. S. Tennessee cladeswere separated from outgroup salmonellae by more than sixteen thousand SNPs. Intra-serovar diversity of S. Tennessee was small compared to the chosen outgroups (1,153 SNPs), suggesting recent divergence of some S. Tennessee clades. Analysis of all 1,153 SNPs structuring an S. Tennessee peanut butter outbreak cluster revealed that isolates from several food, plant, and clinical isolates were very closely related, as they had only a few SNP differences between them. SNP-based cluster analyses linked specific food sources to several clinical S. Tennessee strains isolated in separate contamination events. Environmental and clinical isolates had very similar whole genome sequences; no markers were found that could be used to discriminate between these sources. Finally, we identified SNPs within variable S. Tennessee genes that may be useful markers for the development of rapid surveillance and typing methods, potentially aiding in traceback efforts during future outbreaks. Using WGS can delimit contamination sources for foodborne illnesses across multiple outbreaks and reveal otherwise undetected DNA sequence differences essential to the tracing of bacterial pathogens as they emerge.
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U2 - 10.1371/journal.pone.0146929
DO - 10.1371/journal.pone.0146929
M3 - Article
C2 - 27258142
AN - SCOPUS:84973636814
SN - 1932-6203
VL - 11
JO - PloS one
JF - PloS one
IS - 6
M1 - e0146929
ER -