Immunoinformatics-driven design of a multi-epitope vaccine against Clostridium perfringens in yaks.

چکیده اصلی

INTRODUCTION: Clostridium perfringens is the primary causative agent of enterotoxemia in yaks, resulting in substantial economic losses on the Qinghai-Tibet Plateau. Conventional vaccines exhibit limited protective breadth and suboptimal efficacy, highlighting the need for innovative strategies. Here, we aimed to construct a novel vaccine candidate incorporating epitopes from multiple prevalent toxinotypes (A, C, E) of C. perfringens affecting yaks, using immunoinformatics approach. METHODS: A hierarchical immunoinformatics pipeline was implemented, encompassing subtractive genomics to identify core virulence factors, prediction and filtering of immunogenic T-cell and B-cell epitopes, rational multi-epitope vaccine design incorporating adjuvant and linkers, three-dimensional structure modeling and validation, molecular docking to evaluate interactions with TLR4, molecular dynamics simulations to confirm complex stability, and codon optimization to facilitate heterologous expression. RESULTS AND DISCUSSION: Five core virulence proteins (Iap, CpsE, NanH, Plc, Pfo) were identified from genomic data, leading to the prediction and selection of ten cytotoxic T lymphocyte (CTL) epitopes, five helper T lymphocyte (HTL) epitopes, and five B-cell epitopes. The final 352-amino-acid multi-epitope vaccine (MEV) construct was assembled using the adjuvant human β-defensin-3 and specific linkers (AAY, GPGPG, KK). Computational evaluations confirmed the vaccine's high antigenicity (VaxiJen score: 0.9092), non-allergenic nature, and structural stability. Molecular docking revealed strong binding affinity with TLR2 (-1024.6 kcal/mol) and TLR4 (-1104.4 kcal/mol). Molecular dynamics simulations over 100 ns confirmed stable TLR4 complex with an average RMSD of 0.1971 ± 0.0377 nm, while the TLR2 complex showed an average RMSD of 0.2692 ± 0.0420 nm. Immune simulation profiles predicted the induction of robust humoral and cellular immune responses, including elevated antibody titers, T-cell activation, and cytokine production. In silico cloning verified the potential for efficient expression in E. coli. CONCLUSION: This study designed a novel multi-epitope vaccine against C. perfringens in yaks using an immunoinformatics approach. The vaccine showed high antigenicity, stability, and broad allelic coverage in silico, providing a promising candidate that requires rigorous in vitro and in vivo experimental validation to confirm these computational predictions. This work offers a foundation for the development of effective vaccines against yak C. perfringens infections on the Qinghai-Tibet Plateau.

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