Designing of multiepitope-based vaccine against Leptospirosis using Immuno-Informatics approaches.

Abstract

Leptospira is a zoonotic pathogen causing significant morbidity and mortality both in animals and humans. Although several surface proteins have been identified as vaccine candidate, they failed to induce sterilizing immunity and cross protection against different serovars. Thus, identification of highly immunogenic antigens that are conserved among pathogenic serovars would be first step towards development of universal vaccine for Leptospirosis. Here we used reverse vaccinology pipeline to screen core genome of pathogenic Leptospira spp.in order to identify suitable vaccine candidates. Based on properties like sub cellular localization, adhesin, homology to human proteins, antigenicity and allergenicity, 18 antigenic proteins were identified and were further investigated for immunological properties. Based on immunogenicity, Protegenicity, Antigenicity, B-cell and promiscuous T-cell epitopes, 6 Potential Vaccine Candidates (PVCs) were finally selected which covered most of the affected world population. For designing a Multi-Epitope Vaccine (MEV), 6 B-cell and 6 promiscuous MHC-I and MHC-II epitopes from each candidate were clustered with linkers in between and stitched along with a TLR4 adjuvant (APPHALS) at the N-terminal to form a construct of 361 amino acids. The physiochemical properties, secondary and tertiary structure analysis revealed that MEV was highly stable. Molecular docking analysis revealed the deep binding interactions of the MEV construct within the grooves of human TLR4 (4G8A). In-silico codon optimization and cloning of the vaccine construct assured good expression. Further, immune simulations have shown that MEV could induce strong and diverse B and T cell responses. Taken together our results indicate that the designed MEV could be a promising subunit vaccine candidate against Leptospirosis, however it requires experimental validation.