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Establishment of a Simple and Rapid Identification Method for Listeria spp. by Using High-Resolution Melting Analysis, and Its Application in Food Industry
Author(s) -
Chihiro Ohshima,
Hajime Takahashi,
Chirapiphat Phraephaisarn,
Mongkol Vesaratchavest,
Suwimon Keeratipibul,
Takashi Kuda,
Bon Kimura
Publication year - 2014
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0099223
Subject(s) - listeria , high resolution melt , listeria monocytogenes , biology , typing , multilocus sequence typing , melting curve analysis , microbiology and biotechnology , genetics , gene , polymerase chain reaction , bacteria , genotype
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.

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