S-Space College of Veterinary Medicine (수의과대학) Dept. of Veterinary Medicine (수의학과) Journal Papers (저널논문_수의학과)
Single-nucleotide polymorphism typing analysis for molecular subtyping of Salmonella Tennessee isolates associated with the 2007 nationwide peanut butter outbreak in the United States
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- Issue Date
- BioMed Central
- Gut Pathogens, 9(1):25
- S. Tennessee ; SNP typing ; Peanut butter outbreak
In 2007, a nationwide Salmonella Tennessee outbreak occurred via contaminated peanut butter. Here, we developed a single-nucleotide polymorphism (SNP)-typing method for S. Tennessee to determine the clonal subtypes of S. Tennessee that were associated with the peanut butter outbreak.
Methods and results
One seventy-six S. Tennessee isolates from various sources, including humans, animals, food, and the environment, were analyzed by using the SNP technique. Eighty-four representative SNP markers were selected by comparing the sequences of three representative S. Tennessee strains with different multi-locus sequence typing and variable number tandem repeats from our collection. The set of eighty-four SNP markers showed 100% typeability for the 176 strains, with the nucleotide diversity ranging from 0.011 to 0.107 (mean = 0.049 ± 0.018, median = 0.044) for each marker. Among the four clades and nine subtypes generated by the SNP typing, subtype 1, which comprised 142 S. Tennessee strains, was the most predominant. The dominance of single-strain clones in subtype 1 revealed that S. Tennessee is highly clonal regardless of outbreak-association, source, or period of isolation, suggesting the presence of an S. Tennessee strain prototype. Notably, a minimum 18 SNP set was able to determine clonal S. Tennessee strains with similar discrimination power, potentially allowing more rapid and economic strain genotyping for both outbreaks and sporadic cases.
The SNP-typing method described here might aid the investigation of the epidemiology and microevolution of pathogenic bacteria by discriminating between outbreak-related and sporadic clinical cases. In addition, this approach enables us to understand the population structure of the bacterial subtypes involved in the outbreak.
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