Bioinformatics and in-silico epitope prediction analysis of highly conserved pathogenic Leptospira genes

Abstract

The aim of this study was to identify potential candidates suitable for the development of a multivalent DNA vaccine that can stimulate significant antibody production that will aid the control and prevention of leptospirosis. Antigenic B cell epitopes from highly conserved pathogenic leptospiral genes lipL32, LipL41, ompL1, loa22 and ligA were predicted using bioinformatics tools as potential vaccine candidates. The vaccine constructs were composed of the lipopolysaccharide genes (lipL32, lipL41), the outer membrane protein and outer membrane-like protein (ompL1, loa22) and the immunoglobulin-like protein (ligA). Up to 250 sequences from different isolates with identities ranging from 54% to 100% across all sequences were obtained. The Bepipred software predicted 13 different overlapping and potentially immunogenic regions within the selected genes. This study was able to use a high throughput in-silico process in identifying potential vaccine candidates for use in the development of leptospira vaccine.

Keywords: BepiPred, DNA vaccine, Epitope, In-silico prediction, Leptospirosis