Leuconostoc species are important microorganisms in food fermentation but also cause food spoilage. Although these species are commercially important, their taxonomy is still based on inaccurate identification methods. Here, we used computational pangenome analysis to develop a real-time PCR-based method for identifying and differentiating the 12 major Leuconostoc species found in food. Analysis of pan and core-genome phylogenies showed clustering of strains into 12 distinct groups according to the species. Pangenome analysis of 130 Leuconostoc genomes from these 12 species enabled the identification of each species-specific gene. In silico testing of the species-specific genes against 143 publicly available Leuconostoc and 100 other lactic acid bacterial genomes showed that all the assays had 100% inclusivity/exclusivity. We also verified the specificity for each primer pair targeting each specific gene using 23 target and 124 non-target strains and found high specificity (100%). The sensitivity of the real-time PCR method was 102 colony forming units (CFUs)/ml in pure culture and spiked food samples. All standard curves showed good linear correlations, with an R 2 value of ≥0.996, suggesting that screened targets have good specificity and strong anti-interference ability from food sample matrices and non-target strains. The real-time PCR method can be potentially used to determine the taxonomic status and identify the Leuconostoc species in foods.
Keywords: Leuconostoc; computational pangenome analysis; identification; real-time PCR; species-specific genes.
Copyright © 2022 Kim, Yang, Kim, Lee and Kim.