A Whole-Genome Single Nucleotide Polymorphism-Based Approach To Trace and Identify Outbreaks Linked to a Common Salmonella enterica subsp. enterica Serovar Montevideo Pulsed-Field Gel Electrophoresis Type
Published in
Applied and Environmental Microbiology, October 2011
In this study, we report a whole-genome single nucleotide polymorphism (SNP)-based evolutionary approach to study the epidemiology of a multistate outbreak of Salmonella enterica subsp. enterica serovar Montevideo. This outbreak included 272 cases that occurred in 44 states between July 2009 and April 2010. A case-control study linked the consumption of salami made with contaminated black and red pepper to the outbreak. We sequenced, on the SOLiD System, 47 isolates with XbaI PFGE pattern JIXX01.0011, a common pulsed-field gel electrophoresis (PFGE) pattern associated with isolates from the outbreak. These isolates represented 20 isolates collected from human sources during the period of the outbreak and 27 control isolates collected from human, food, animal, and environmental sources before the outbreak. Based on 253 high-confidence SNPs, we were able to reconstruct a tip-dated molecular clock phylogeny of the isolates and to assign four human isolates to the actual outbreak. We developed an SNP typing assay to rapidly discriminate between outbreak-related cases and non-outbreak-related cases and tested this assay on an extended panel of 112 isolates. These results suggest that only a very small percentage of the human isolates with the outbreak PFGE pattern and obtained during the outbreak period could be attributed to the actual pepper-related outbreak (20%), while the majority (80%) of the putative cases represented background cases. This study demonstrates that next-generation-based SNP typing provides the resolution and accuracy needed for outbreak investigations of food-borne pathogens that cannot be distinguished by currently used subtyping methods.
This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 October 2017.
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