Immuno-informatics strategy for designing and development of a multi-epitope chimeric vaccine for livestock against Taenia infections

Abstract

Livestock production is a major contributor to food security and livelihoods worldwide. Among the parasitic diseases affecting livestock, Taenia solium infection remains a significant veterinary and public health concern, causing substantial economic losses. Therefore, effective and affordable vaccine development is required for disease prevention and improved livestock health. A multi-epitopic chimeric vaccine for livestock against Taenia spp. was computationally designed using subtractive proteomics and immuno-informatics. Antigenic proteins were selected based on antigenicity, allergenicity, and physicochemical profiling. HTL, CTL, and B-cell epitopes were predicted and assembled into a chimeric structure along with a suitable adjuvant. Structure modeling and physical characteristics, such as docking tendency with TLRs, along with the immune stimulatory response, were analysed. Molecular dynamics simulations for the TLR4-Vaccine complexes were also done for 100 ns. Immune simulation and codon optimisation predicted immunogenicity and expression potential in E. coli. 11 epitopes were identified from 3 antigenic homologous proteins. A multiepitope chimeric vaccine was designed by adding β-defensin adjuvant to mount a robust immune response. The proposed vaccine construct had 272 Amino acid residues and a molecular weight of 28.94 kDa. Upon binding with TLR4 receptors, it establishes a stable conformation, and molecular dynamics simulations also demonstrated a dynamic interplay. A multi-epitope vaccine capable of disrupting the life cycle of Taenia species across all known hosts was designed. The computationally designed vaccine meets all essential criteria and has shown immense potential to be an effective vaccine through in silico analysis. However, additional In-vitro and In-vivo validations are imperative.