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MLVA subtyping of Listeria monocytogenes isolates from meat products and meat processing plants
- Martín, Belén, Bover-Cid, Sara, Aymerich, Teresa
- Food research international 2018 v.106 pp. 225-232
- DNA, Listeria monocytogenes, alleles, livestock and meat industry, meat processing plants, meat products, monitoring, multilocus sequence typing, multiple-locus variable number tandem-repeat analysis, risk
- Listeria monocytogenes is widely distributed in meat products and the meat-processing industry thus posing a risk to consumers. The aim of this study was to evaluate the suitability of the multilocus variable-number tandem-repeat analysis (MLVA) for use as a L. monocytogenes subtyping technique for surveillance and routine control in meat products and meat processing plants. A collection of 113 isolates (including control strains and isolates from meat products and meat processing plants) were subject to MLVA analysis using two different platforms for fragment sizing: 1.) ABI 3730xl DNA analyzer (Life Technologies) as the reference method and 2.) The QIAxcel Advanced System (Qiagen). Although discrepancies in fragment sizing were observed it was possible to standardize results in order to assign the same allele for a given fragment independently of the platform used for fragment sizing. A total of 27 different MLVA profiles were obtained considering all the isolates (N=113), 24 of them corresponding to the meat industry isolates (N=106). MLVA and multilocus sequence typing (MLST) results were compared and yielded Simpson's diversity indices of 0.907 and 0.872, respectively. The congruence between both typing methods was measured with the adjusted Wallace coefficient (AW). Using MLVA as the primary method, AW=0.946 suggested that MLVA can predict the sequence type with high accuracy. Given its discriminatory power and high throughput, MLVA could be considered a rapid, reliable, and high-throughput alternative to existing subtyping methods for surveillance and control of L. monocytogenes in the meat-processing industry.