Genome mining of B. subtilis group for the identification of antibiotic and secondary metabolite biosynthetic gene clusters

Abstract

Genome mining using bioinformatic tools has drastically increased the rate of discovery of specialized metabolite compared to traditional methods which rely on the isolation of individual compounds. Bacillus subtilis group devoted large portions of their genomes to the genes necessary for natural products biosynthesis. B.subtilis group possess ability to synthesize wide range of natural products known as specialized metabolite which played important roles in the physiology and metabolism of the bacteria and are also used as antibiotics, anticancer, enzymes, etc. The synthesis of these special metabolites depends on the abundance and distributions of biosynthetic gene clusters (BGCs) which can be identified in bacterial genome sequence. In the present study, 11genomic data of Bacillus subtilis group were retrieved from GeneBank database of the National Center for Biotechnology Information. The study employed antiSMASH v4.0 with default setting, the detection strictness was set to ‘’relaxed’’ that can allow the identification of known and unknown gene clusters and their distribution in the genome. The results of the analysis identified and reported total of 97 biosynthetic gene clusters across the 11 genomes, the clusters were classified into 22 different classes of natural product including non
ribosomal peptide synthetase (NRPS) with high abundance and distribution of 29 across the 11 genomes. Similarly, the study revealed 32 (32.89%) unknown clusters across the 11genomic data for which no similar specialized products could be identified. The unknown clusters identified across the genomes of the Bacillus subtilis group might be predicted to encode for novel natural products and offer
new avenue for drug discovery and development.