Salmonella enterica subsp. enterica serovar Newport (S. Newport) is the third most prevalent cause of food-borne salmonellosis. Rapid, efficient, and accurate methods for identification are required to track specific strains of S. Newport during outbreaks. By exploiting the hypervariable nature of virulence genes and clustered regularly interspaced short palindromic repeats (CRISPRs), we previously developed a sequence-based subtyping approach, designated CRISPR-multi-virulence-locus sequence typing (CRISPR-MVLST). To demonstrate the applicability of this approach, we analyzed a broad set of S. Newport isolates collected over a 5-year period by using CRISPR-MVLST and pulsed-field gel electrophoresis (PFGE). Among 84 isolates, we defined 38 S. Newport sequence types (NSTs), all of which were novel compared to our previous analyses, and 62 different PFGE patterns. Our data suggest that both subtyping approaches have high discriminatory abilities (>0.95) with a potential for clustering cases with common exposures. Importantly, we found that isolates from closely related NSTs were often similar by PFGE profile as well, further corroborating the applicability of CRISPR-MVLST. In the first full application of CRISPR-MVLST, we analyzed isolates from a recent S. Newport outbreak. In this blinded study, we confirmed the utility of CRISPR-MVLST and were able to distinguish the 10 outbreak isolates, as defined by PFGE and epidemiological data, from a collection of 20 S. Newport isolates. Together, our data show that CRISPR-MVLST could be a complementary approach to PFGE subtyping for S. Newport.
All Science Journal Classification (ASJC) codes
- Microbiology (medical)