Abstract:
Bacteriocins are post-translationally modified antimicrobial peptides of bacterial origin. Bacteriocins have been suggested for various applications including food preservation and alternates to antibiotic treatments. Over the last 2 decades discovery of these peptides evolved from expensive, time-consuming lab based screening methods to reasonably high throughput computer-based alternatives via in silico gene mining such as BAGEL. In this project 932 genomes were mined for the presence of bacteriocin gene clusters. Of the 932, a total of 11 Eukaryotic genomes were used as a negative control. Analysis was performed to identify the type of bacteriocins and distribution amongst following phyla: Actinobacteria, BV4, Firmicutes, Glidobacteria and Proteobacteria. Novel bacteriocins identified were characterised in silico with respect to their physiochemical properties, including molecular weight, pI, extinction coefficient, aliphatic index, hydropathy index and estimated half-life in mammalian cells, yeast and bacteria. Characterisation of the 3D structures was done by homology modelling. All bacteriocins of the Actinobacteria, Firmicutes and Proteobacteria were then subjected to phylogenetic analysis. In this study the in silico mining of 932 genomes identified 407 novel bacteriocins. The physiochemical characterisation and homology models provide predicted chemical and structural characteristics of the identified bacteriocins. Sequence alignments indicate conservation of genetic clusters within the phyla. Phylogenetic trees were inferred from these alignments to study evolutionary relationships between bacteriocins and between producer species. The phylogeny of these species interestingly supports horizontal as well as lateral gene transfer patterns. The findings from this project will assist in laboratory investigations to further explore the growing field of bacteriocins and their possible application.
