Integrating 16S rRNA identification for a promising epitope-based vaccine strategy against Bacillus licheniformis infections causing foodborne illness

Background: Bacillus licheniformis is a Gram-positive bacterium associated with foodborne illnesses and opportunistic infections in immunocompromised individuals, resulting in significant economic and health burdens. Despite its significance, no preventive or therapeutic vaccines currently exist against B. licheniformis. Objective: This study aimed to design a multi-epitope vaccine construct against B. licheniformis using immunoinformatic and bioinformatic approaches, integrating the One Health perspective. Materials and Methods: Strains of B. licheniformis were isolated from soil and food samples and identified through 16S rRNA gene amplification and sequence analysis. Two antigenic proteins, WP_075876128.1 (hypothetical protein) and WP_009328059.1 (MATE family efflux transporter), were selected as vaccine targets based on antigenicity scores of 0.582 and 0.835, respectively. Immunoinformatics tools were used for epitope prediction, vaccine construct assembly, structural modeling, and immune simulations. Molecular docking was used to assess vaccine-receptor interactions with Toll-like receptors (TLRs) 1, 2, and 5. Results: The designed vaccine construct exhibited favorable physicochemical properties, including structural stability, thermostability, solubility, and hydrophilicity. Immune simulation predicted a strong immune response, characterized by approximately 225 B-memory cells per mm3 and around 8,500 combined IgM and IgG counts. Docking studies revealed the stable binding of the vaccine construct to TLR1, TLR2, and TLR5, supported by favorable binding free energy values, indicating a robust immunogenic potential. Conclusion: The immunoinformatically designed multi-epitope vaccine candidate demonstrated high antigenicity, stability, and strong immune-stimulatory capacity against B. licheniformis. These findings support its potential for further in vitro and in vivo validation. This study highlights the effectiveness of immunoinformatic tools in rational vaccine design and reinforces the One Health approach, which links human, animal, and environmental health.