The combination of CRISPR-MVLST and PFGE provides increased discriminatory power for differentiating human clinical isolates of Salmonella enterica subsp. enterica serovar Enteritidis

Nikki Shariat, Michael J. DiMarzio, Shuang Yin, Lisa Dettinger, Carol H. Sandt, James R. Lute, Rodolphe Barrangou, Edward G. Dudley

Research output: Contribution to journalArticlepeer-review

61 Scopus citations

Abstract

Salmonella enterica subsp. enterica serovar Enteritidis (S. Enteritidis) is a major cause of foodborne salmonellosis. Rapid, efficient and accurate methods for identification are required to track specific strains of S. Enteritidis during outbreaks of human salmonellosis. By exploiting the hypervariable nature of virulence genes and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs), we previously developed a powerful sequence-based subtyping approach, designated CRISPR-MVLST. To substantiate the applicability of CRISPR-MVLST, we analyzed a broad set of S. Enteritidis isolates collected over a six-year period. Among 141 isolates we defined 22 Enteritidis Sequence Types (ESTs), the majority of which were novel. Notably, strains exhibiting the common PFGE pattern, JEGX01.0004 (characteristic of ∼40% of S. Enteritidis isolates in the United States), were separated into twelve distinct sequence types. Conversely, isolates of EST4, the most predominant EST we observed, comprised eight different PFGE patterns. Importantly, we showed that some genotypes that were previously associated with the food supply chain at the farm level have now been identified in clinical samples. CRISPR sequence data shows subtle but distinct differences among different alleles of S. Enteritidis, suggesting that evolution of these loci occurs vertically, as opposed to previously reported evolution by spacer acquisition in other bacteria.

Original languageEnglish (US)
Pages (from-to)164-173
Number of pages10
JournalFood Microbiology
Volume34
Issue number1
DOIs
StatePublished - May 2013

All Science Journal Classification (ASJC) codes

  • Food Science
  • Microbiology

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