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Listeria monocytogenes  is the causative bacteria of listeriosis, which has a higher mortality rate than that of other causes of food poisoning.  Listeria  spp., of which  L. monocytogenes  is a member, have been isolated from food and manufacturing environments. Several methods have been published for identifying  Listeria  spp.; however, many of the methods cannot identify newly categorized  Listeria  spp. Additionally, they are often not suitable for the food industry, owing to their complexity, cost, or time consumption. Recently, high-resolution melting analysis (HRMA), which exploits DNA-sequence differences, has received attention as a simple and quick genomic typing method. In the present study, a new method for the simple, rapid, and low-cost identification of  Listeria  spp. has been presented using the genes  rarA  and  ldh  as targets for HRMA. DNA sequences of 9  Listeria  species were first compared, and polymorphisms were identified for each species for primer design. Species specificity of each HRM curve pattern was estimated using type strains of all the species. Among the 9 species, 7 were identified by HRMA using  rarA  gene, including 3 new species. The remaining 2 species were identified by HRMA of  ldh  gene. The newly developed HRMA method was then used to assess  Listeria  isolates from the food industry, and the method efficiency was compared to that of identification by 16S rDNA sequence analysis. The 2 methods were in coherence for 92.6% of the samples, demonstrating the high accuracy of HRMA. The time required for identifying  Listeria  spp. was substantially low, and the process was considerably simplified, providing a useful and precise method for processing multiple samples per day. Our newly developed method for identifying  Listeria  spp. is highly valuable; its use is not limited to the food industry, and it can be used for the isolates from the natural environment.

plos one

Establishment of a Simple and Rapid Identification Method for Listeria spp. by Using High-Resolution Melting Analysis, and Its Application in Food Industry