Whole genome sequencing of Salmonella Typhimurium illuminates distinct outbreaks caused by an endemic multi-locus variable number tandem repeat analysis type in Australia, 2014. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Phillips, Anastasia; Sotomayor, Cristina; Wang, Qinning; Holmes, Nadine; Furlong, Catriona; Ward, Kate; Howard, Peter; Octavia, Sophie; Lan, Ruiting; Sintchenko, Vitali
• Is Part Of: BMC microbiology. Volume 16:Issue 1(2016)
• Page Start: 1
• Page End: 9
• Publication Date: 2016-12
• Subjects: Salmonella Typhimurium -- Molecular epidemiology -- Foodborne outbreaks -- Whole genome sequencing -- Public health surveillance; Microbiology -- Periodicals; 579.05
• DOI: 10.1186/s12866-016-0831-3
• Languages: English
• ISSNs: 1471-2180

Abstract

Abstract Background Salmonella Typhimurium (STM) is an important cause of foodborne outbreaks worldwide. Subtyping of STM remains critical to outbreak investigation, yet current techniques (e.g. multilocus variable number tandem repeat analysis, MLVA) may provide insufficient discrimination. Whole genome sequencing (WGS) offers potentially greater discriminatory power to support infectious disease surveillance. Methods We performed WGS on 62 STM isolates of a single, endemic MLVA type associated with two epidemiologically independent, food-borne outbreaks along with sporadic cases in New South Wales, Australia, during 2014. Genomes of case and environmental isolates were sequenced using HiSeq (Illumina) and the genetic distance between them was assessed by single nucleotide polymorphism (SNP) analysis. SNP analysis was compared to the epidemiological context. Results The WGS analysis supported epidemiological evidence and genomes of within-outbreak isolates were nearly identical. Sporadic cases differed from outbreak cases by a small number of SNPs, although their close relationship to outbreak cases may represent an unidentified common food source that may warrant further public health follow up. Previously unrecognised mini-clusters were detected. Conclusions WGS of STM can discriminate foodborne community outbreaks within a single endemic MLVA clone. Our findings support the translation of WGS into public health laboratory surveillance of salmonellosis.