Utilization of an In Silico 16S Ribosomal RNA Gene-Based Restriction Enzyme Approach for Identification of Lactic Acid Bacteria

Abstract

In silico 16S ribosomal RNA gene-based restriction enzyme approach is a computer-simulated polymerase chain reaction-restriction fragment length polymorphism analysis method, namely customizable in silico sequence evaluation for restriction sites. The purpose of this study was to identify lactic acid bacteria using restriction enzyme analysis of 16S gene (16S ribosomal RNA polymerase chain reaction-restriction fragment length polymorphism). An in silico investigation was conducted to detect species-specific molecular markers in different lactic acid bacteria strains. We selected six out of 20 16S ribosomal RNA gene sequences from probiotic-potential lactic acid bacteria strains. Initially, the corresponding 16S ribosomal RNA gene sequences were selected from the database aligned using the Clustal Omega program and their evolutionary relationships were determined. The results indicated that the studied lactic acid bacteria strains belonged to 6 distinct clades except for the genus of Lactobacillus. Furthermore, the in silico polymerase chain reactionrestriction fragment length polymorphism was conducted for further taxonomic classification. Different restriction enzymes were used to recognize sites present on the lactic acid bacteria 16S ribosomal RNA genes. Customizable in silico sequence evaluation for restriction sites output comprised a predicted agarose gel as virtual polymerase chain reaction-restriction fragment length polymorphism patterns, for proper selection of the appropriate enzyme (s) to be used for polymerase chain reaction-restriction fragment length polymorphism marker generation. Our study demonstrated that ApyPI, CchIII and NheI produced distinct restriction patterns as those of Ku324937_C species. The most abundant species-specific markers were seen for Ku324928_C (10 markers), followed by Ku324908_C (8 markers) of order Hemiptera, then Ku324909_C (5 markers), Ku324898_C (4 markers) and finally, Ku324937_C (3 markers). The results demonstrated that customizable in silico sequence evaluation for restriction sites is a powerful tool to detect species-specific markers to provide better understanding of organisms found in raw and/or fermented milk.