Novel toxin-based mRNA vaccine against Clostridium perfringens using in silico approaches

Abstract

Clostridium perfringens is a bacterium that causes gastrointestinal diseases in humans and animals. The several powerful toxins such as alpha toxin (CPA), beta toxin (CPB), enterotoxin (CPE), Epsilon toxin (ETX), and theta toxin, play a major role in its pathogenesis. Traditional vaccine development methods are time-consuming and costly. In silico approaches offer an alternative strategy for designing vaccines by analyzing biological data and predicting immunogenic peptides. In this study, computational tools were utilized to design a RNA vaccine targeting C. perfringens toxins. Toxin protein sequences were retrieved and their linear B-cell, MHCI, and MHCII binding epitopes were predicted. Allergenicity, toxigenicity, and IFN-γ induction were assessed to select non-allergenic, non-toxic, and IFN-γ-inducing epitopes. Molecular docking was performed to identify epitopes that fit within the binding cleft of MHC alleles. A final peptide vaccine construct was designed with selected epitopes separated by a linker sequence. The antigenicity and physicochemical properties of the vaccine were evaluated. Immune response simulation showed enhanced secondary and tertiary immune responses, increased levels of immunoglobulins, cytotoxic T lymphocytes, helper T lymphocytes, macrophage activity, and elevated levels IFN-γ and interleukin-2. Docking analysis was done to assess interactions between the vaccine structure and Toll-like receptors. Codon optimization was performed, and a final RNA vaccine construct was designed. The secondary structure of the RNA vaccine was predicted and validated. Overall, this study demonstrates the potential of in silico approaches for designing an RNA vaccine against C. perfringens toxins, contributing to improved prevention and control of associated diseases.