Development of a novel multi-locus variable-number tandem repeat analysis (MLVA) combined with high resolution melting analysis (HRMA) for Listeria innocua typing and its application in a food processing plant

Abstract

Listeria monocytogenes is the causative bacteria of listeriosis, a type of food poisoning with high mortality, which mainly infects people through the consumption of ready-to-eat food. Most cases of L. monocytogenes contamination have occurred at food processing plants. Therefore, food companies must carefully monitor the proliferation and spread of this bacterium. Listeria innocua has often been reported to exist in food processing plants when the presence of the genus Listeria is investigated. In addition, because L. innocua and L. monocytogenes are known to act together, L. innocua is an important hygiene indicator for food companies. Multilocus variable-number tandem repeat analysis (MLVA) is a method used to discriminate between strains, based on the discrepancies in the number of repeating units within the tandem repeats (TRs). In many cases, MLVA uses capillary electrophoresis (CE) or base sequence analysis. However, the equipment used for these analyses is expensive, and requires a certain level of knowledge and skill for operation. Therefore, it is only used at research facilities. However, in order to rapidly trace the sources of contamination in food processing plants, it is necessary to easily discriminate between strains within the working areas. Therefore, in this study, we established a simpler MLVA method, using high resolution melting analysis (HRMA) to analyze the diversity of variable-number of tandem repeats (VNTRs). We investigated three VNTR loci (used in a previous MLVA-CE analysis) using MLVA-HRMA. The MLVA-HRMA of 23 L. innocua strains showed that this method differentiates between strains at a more or less equal level with MLVA, which uses base sequence analysis. HRMA is also used to investigate gene polymorphisms based on the Tm value of the PCR products. Therefore, a different peak pattern is observed depending on the internal SNP even if the number of repeating units are the same. We then evaluated the efficacy of MLVA-HRMA in differentiating between 96 strains isolated at food processing plants. This analysis demonstrated the usefulness of the MLVA-HRMA method and its discriminatory ability in tracing the sources of contamination in food processing plants. Since this method is simpler, and cheaper than the existing MLVA methods, it could see widespread use in food processing plants as a rapid investigative tool.