Immunoinformatic development of a multiepitope messenger RNA vaccine targeting lipoate protein ligase and dihydrolipoamide dehydrogenase proteins of Mycoplasma bovis in cattle

利用免疫信息学方法开发针对牛支原体硫辛酸蛋白连接酶和二氢硫辛酰胺脱氢酶蛋白的多表位信使RNA疫苗

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Abstract

BACKGROUND AND AIM: Mycoplasma bovis is a significant pathogen in cattle, causing respiratory, reproductive, and mammary diseases, leading to substantial economic losses. Conventional control measures remain ineffective due to antimicrobial resistance and the absence of an approved vaccine. This study aimed to develop a multiepitope messenger RNA (mRNA)-based vaccine against M. bovis using immunoinformatic and molecular modeling approaches. MATERIALS AND METHODS: Two conserved surface-exposed proteins - lipoate protein ligase (LplA) and dihydrolipoamide dehydrogenase (PdhD) - were selected as vaccine targets. T- and B-cell epitopes were predicted using Immune Epitope Database and evaluated for antigenicity, allergenicity, toxicity, and conservancy. Selected epitopes were linked using specific amino acid linkers and combined with a resuscitation-promoting factor E (RpfE) adjuvant and untranslated regions (hemoglobin subunit beta and rabbit beta-globin) to improve translation and stability. The vaccine construct was modeled and validated through physicochemical profiling, secondary and tertiary structure prediction, molecular-docking with bovine toll-like receptors 4 (TLR4), and codon optimization. Molecular dynamics simulations were conducted to assess the stability of the vaccine-receptor complex. RESULTS: The modeled vaccine construct contained five cytotoxic T lymphocyte, six helper T lymphocyte, and five B-cell epitopes. The construct was predicted to be highly antigenic (score: 0.835), non-allergenic, and non-toxic. Structural validation showed 93.5% of residues in favored regions of the Ramachandran plot and a Z-score of -10.6. Docking simulations revealed strong binding affinity to bovine TLR4, supported by robust molecular dynamics simulation outcomes, including high stability, low eigenvalues, and favorable covariance patterns. Codon optimization yielded a guanine-cytosine content of 59.8% and a codon adaptation index of 0.87, indicating efficient expression in cattle. The predicted mRNA structure exhibited good thermodynamic stability (minimum free energy: -321.42 kcal/mol). CONCLUSION: This study presents a computationally designed mRNA vaccine candidate against M. bovis based on LplA and PdhD epitopes. The construct demonstrated promising immunogenicity, structural integrity, and receptor-binding properties, representing a viable vaccine strategy. Nonetheless, in vitro and in vivo validation is essential to confirm the construct's efficacy and safety in cattle.

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