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

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.

Keywords: Mycoplasma bovis; cattle; epitope prediction; immunoinformatic; messenger RNA vaccine; multiepitope vaccine.

Figure 1

Workflow of the study.

Figure 2

Construction of the modeled vaccine. At the N-terminal Kozak sequence and adjuvant, untranslated regions were added to both ends of the construct. 16 epitopes were used to construct the messenger RNA proposed vaccine, and each epitope was fused with a specific amino acid linker, as shown in graph.

Figure 3

Predicted secondary structure of the vaccine construct. The predicted secondary structure including alpha helix (blue), random coil (orange), and extended stand (red).

Figure 4

Modeled vaccine structure, refinement, and validity. (a) Three-domination structure of the vaccine construct. (b) Refinement of the 3D structure of the vaccine construct. (c) Analysis of Ramachandran plot and validation of vaccine construct. The Ramachandran plot indicates that 93.5% of residues are situated in the most favored regions, whereas 6.5% of residues are found in the additionally allowed regions. (d) Represents the modeled vaccine Z score.

Figure 5

Interaction between the modeled vaccine and bovine toll-like receptors 4 (TLR4). (a) Docking complex of the modeled vaccine with receptor. (b) Graph representing covariance of the complex. (c) Model of elastic network. (d) Model of interaction of amino acids within the docking complex (modeled vaccine and bovine TLR4). (e) B-factor. (f) Eigenvalues value the complex. (g) Individual and accumulative variance of the complex.

Figure 6

Structure of the messenger RNA (mRNA) construct. (a) Ideal secondary configuration. (b) Central secondary arrangement of the mRNA.