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. 2016 Jan 29:15:4.
doi: 10.1186/s12941-016-0119-3.

The evaluation and application of multilocus variable number tandem repeat analysis (MLVA) for the molecular epidemiological study of Salmonella enterica subsp. enterica serovar Enteritidis infection

Yao Liu  1 , Xiaolu Shi  2 , Yinghui Li  3 , Qiongcheng Chen  4 , Min Jiang  5 , Wanli Li  6 , Yaqun Qiu  7 , Yiman Lin  8 , Yixiang Jiang  9 , Biao Kan  10 , Qun Sun  11 , Qinghua Hu  12   13
Affiliations

The evaluation and application of multilocus variable number tandem repeat analysis (MLVA) for the molecular epidemiological study of Salmonella enterica subsp. enterica serovar Enteritidis infection

Yao Liu et al. Ann Clin Microbiol Antimicrob. .

Abstract

Background: Salmonella enterica subsp. enterica serovar Enteritidis (S. Enteritidis) is one of the most prevalent Salmonella serotypes that cause gastroenteritis worldwide and the most prevalent serotype causing Salmonella infections in China. A rapid molecular typing method with high throughput and good epidemiological discrimination is urgently needed for detecting the outbreaks and finding the source for effective control of S. Enteritidis infections.

Methods: In this study, 194 strains which included 47 from six outbreaks that were well-characterized epidemiologically were analyzed with pulse field gel electrophoresis (PFGE) and multilocus variable number tandem repeat analysis (MLVA). Seven VNTR loci published by the US Center for Disease Control and Prevention (CDC) were used to evaluate and develop MLVA scheme for S. Enteritidis molecular subtyping by comparing with PFGE, and then MLVA was applied to the suspected outbreaks detection. All S. Enteritidis isolates were analyzed with MLVA to establish a MLVA database in Shenzhen, Guangdong province, China to facilitate the detection of S. Enteritidis infection clusters.

Results: There were 33 MLVA types and 29 PFGE patterns among 147 sporadic isolates. These two measures had Simpson indices of 0.7701 and 0.8043, respectively, which did not differ significantly. Epidemiological concordance was evaluated by typing 47 isolates from six epidemiologically well-characterized outbreaks and it did not differ for PFGE and MLVA. We applied the well established MLVA method to detect two S. Enteritidis foodborne outbreaks and find their sources successfully in 2014. A MLVA database of 491 S. Enteritidis strains isolated from 2004 to 2014 was established for the surveillance of clusters in the future.

Conclusions: MLVA typing of S. Enteritidis would be an effective tool for early warning and epidemiological surveillance of S. Enteritidis infections.

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Figures

Fig. 1
Fig. 1
Dendrograms for PFGE a using restriction enzyme XbaI and MLVA b performed on six S. Enteritidis outbreaks. The PFGE dendrogram was generated using the Dice coefficient (optimization 1.5 % and position tolerance 1.5 %) and unweighted-pair group method with arithmetic averages algorithm (UPGMA) algorithm. The MLVA dendrogram was generated using the categorical coefficient and UPGMA algorithm
Fig. 2
Fig. 2
Dendrogram of 18 isolates evaluated by MLVA on two S. Enteritidis outbreaks in 2014. The MLVA dendrogram was generated using the categorical coefficient and unweighted pair group method with arithmetic means. “Allele string of VNTR loci” in the figure means a string of the actual number of repeats at each locus (in order of SE1–SE2–SE3–SE5–SE6–SE8–SE9)
Fig. 3
Fig. 3
Annual distribution of Shenzhen S. Enteritidis isolates over an 11-year period (2004–2014) according to the MLVA database. Other types: all MLVA types with less than 2.8 % occurrence in the database. The number of JEGMT0001 type was 14 in the MLVA database and the proportion of the type was 2.8 %, so we defined other types as all MLVA types with less than 2.8 % occurrence in the MLVA database
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