Quantifying the survival of multiple Salmonella enterica serovars in vivo via massively parallel whole-genome sequencing to predict zoonotic risk

Prerna Vohra, Marie Bugarel, Frances Turner, Guy H. Loneragan, Jayne C. Hope, John Hopkins, Mark P. Stevens

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Salmonella enterica is an animal and zoonotic pathogen of worldwide importance. Salmonella serovars that differ in their host and tissue tropisms exist. Cattle are an important reservoir of human nontyphoidal salmonellosis, and contaminated bovine peripheral lymph nodes enter the food chain via ground beef. The relative abilities of different serovars to survive within the bovine lymphatic system are poorly understood and constrain the development of control strategies. This problem was addressed by developing a massively parallel whole-genome sequencing method to study mixed-serovar infections in vivo. Salmonella serovars differ genetically by naturally occurring single nucleotide polymorphisms (SNPs) in certain genes. It was hypothesized that these SNPs could be used as markers to simultaneously identify serovars in mixed populations and quantify the abundance of each member in a population. The performance of the method was validated in vitro using simulated pools containing up to 11 serovars in various proportions. It was then applied to study serovar survival in vivo in cattle challenged orally with the same 11 serovars. All the serovars successfully colonized the bovine lymphatic system, including the peripheral lymph nodes, and thus pose similar risks of zoonosis. This method enables the fates of multiple genetically unmodified strains to be evaluated simultaneously in a single animal. It could be useful in reducing the number of animals required to study mixed-strain infections and in testing the cross-protective efficacy of vaccines and treatments. It also has the potential to be applied to diverse bacterial species which possess shared but polymorphic alleles.

Original languageEnglish
Article numbere02262-17
JournalApplied and environmental microbiology
Volume84
Issue number4
DOIs
StatePublished - Feb 1 2018

Keywords

  • Cattle
  • Salmonella
  • Whole-genome sequencing
  • Zoonotic infections

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