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Salmonella outbreak detection with MLVA

By Joe Whitworth+

27-Jun-2014
Last updated on 27-Jun-2014 at 12:38 GMT

 Salmonella Typhimurium. Picture copyright: Janice Haney Carr / Centers for Disease Control and Prevention
Salmonella Typhimurium. Picture copyright: Janice Haney Carr / Centers for Disease Control and Prevention

Profiles from a method to perform molecular typing can determine if it is a single incident or part of a larger outbreak, according to researchers from the University of Melbourne.

Multi-locus variable number tandem repeat (VNTR) analysis (MLVA) is a high-resolution typing method that has become widespread among public health laboratories for the investigation of Salmonella and other foodborne outbreaks.

It is increasingly used in outbreaks caused by Salmonella entericaserovar Typhimurium and other bacterial pathogens but MLVA data analysis relies on simple clustering approaches that may lead to incorrect interpretations, said the researchers.

Distinguishing outbreak strains

The study focuses on the technique which analyzes specific sequences of DNA (called loci) that change rapidly enough to distinguish outbreak strains from other circulating strains of the bacteria but not so quick that connections could be hidden by changes during an outbreak.

However the rates at which MLVA profiles change have not been directly investigated for Salmonella, so it is unclear how S.Typhimurium MLVA profiles should be interpreted in the context of outbreak detection and investigation.

Using a set of 203 isolates from a series of linked outbreaks, and whole genome sequencing of 12 representative isolates, researchers assessed the accuracy and utility of several alternative methods for analysing and interpreting S. Typhimurium MLVA data.

Using WGS data and detailed epidemiological trace-back to determine the true underlying genetic relationships behind a series of outbreaks, the analysis shows that accurate conclusions in the case study could be drawn from just MLVA data.

Rates of change

Relative rates of change were consistent across in vitro and in vivo growth (the study in plates and with mice) and could be accurately estimated from diversity measures of natural variation observed during large outbreaks.

Researchers estimated the rates of copy number change at the five loci commonly used for S. Typhimurium MLVA, during in vitro and in vivo passage.

Three of the loci saw changes in the DNA, but two did not. Based on these results, the researchers are recommending that isolates with zero or one variation in the three rapidly changing loci but no differences in the other two should be considered part of the same cluster.

With respect to cluster detection for identifying outbreaks and ruling out unrelated strains, our data indicate that the best cluster definition is one that includes isolates with variation in zero or one of the rapidly changing loci STTR5, STTR6 or STTR10, but excludes strains with more than one difference or with any 464 difference in locus STTR3 or STTR9.”

Source: American Society for Microbiology

Online ahead of print, DOI: 10.1128/JB.01820-14

Analysis of Salmonella Typhimurium variable number tandem repeat (VNTR) data for public health investigation based on measured mutation rates and whole-genome sequence comparisons

Authors:  Karolina Dimovski, Hanwei Cao, Odilia L. C. Wijburg, Richard A. Strugnell, Radha K. Mantena, Margaret Whipp, Geoff Hogg, Kathryn E. Holt