Multi Epitope Based Vaccine Design and Analysis against Mycoplasma bovis Using Immunoinformatic Approaches

Mycoplasma bovis belongs to Mollicutesclass, is responsible for the respiratory and reproductive diseases in dairy farms. Vaccination is essential for protection from M. bovis bacteria. Previously, several vaccines have been reported that are rendered useless with the passage of time due to versatile changes in bacteria. This study aims to identify the conserved regions for B and T cell epitopes of chromate transporter protein. Different bioinformatics tools including Ellipro, NetCTL and NETMHCIIpan were used to predict B cell, CTL and HTL epitopes, respectively. Altogether, we predicted 14 peptide epitopes (11 CTL and 3HTL epitopes) of chromate transporter protein that induce the immune system. These epitopes used to predict vaccine against M. bovis. Total length of predicted multi epitope vaccine consists upon 239 amino acids in its primary structure. To check interactions, molecular docking was performed by patchDock and analyzed through LigPlot. To evaluate multi epitope vaccine's immunogenic profile, an Insilico immune response was produced by C-ImmSim server. JCat was used for optimization of codon and the reverse translation resulting in a vaccine cDNA sequence that can be used for an efficient expression. Antigenicity and allergenicity was studied by Vaxijen 2.0 and Allertop server. It was observed that epitope-based vaccine helped to avoid the outbreaks of pandemics in dairy farms with more efficacy and fewer side effects. This research work will help researchers in testing the effectiveness of epitopebased vaccine design against M. bovis.