In silico multi-epitope-based vaccine design for Mycobacterium avium complex species

Abstract

Introduction The Mycobacterium avium complex (MAC)—comprising M. colombiense, M. avium, andM. intracellulare—is an emerging group of opportunistic pathogens responsible for significant morbidity and mortality, particularly in immunocompromised individuals. Despite this growing burden, no vaccines currently provide cross-species protection. In silico vaccine design offers a rapid, cost-effective strategy to identify immunogenic epitopes and assemble multi-epitope constructs with optimized safety and efficacy. Accordingly, we aimed to develop a candidate multi-epitope vaccine (MEV) targeting conserved antigens across multiple MAC species. Methods From a genomic survey of nontuberculous mycobacteria (NTM) in Zimbabwe, we assembled complete genomes for M. colombiense (MCOL), M. avium (MAV), and M. intracellulare (MINT). Using both local and global reference datasets, we screened the conserved immunodominant proteins 85A, 85B, and 85C for high-affinity T-helper lymphocyte (THL) epitopes. Promising epitopes were further evaluated for antigenicity, immunogenicity, physicochemical stability, and population coverage. Results Epitope mapping across the nine target proteins yielded 82 THL epitopes predicted to bind 13 MHC class II (DRB*) alleles, ensuring broad coverage within Zimbabwean and pan-African populations. Clustering analyses consolidated 26 unique epitopes into 11 consensus peptides, 65.4% of which derived from the 85B proteins. In silico immune simulations predicted robust humoral and cellular responses, including elevated IgG titers, T-helper and T-cytotoxic cell proliferation and increased secretion of IFN-γ and IL-2 following MEV administration. Conclusion These findings indicate that our construct possesses strong immunogenic potential and cross-species applicability. We present here a rationally designed MEV candidate that merits further experimental validation as a broad-spectrum vaccine against multiple MAC species.