Background
H5 subtype of influenza A virus is a re-emerging, highly pathogenic virus associated with high mortality rates in both avian species and humans. Its high mutation rate contributes to its pandemic potential and undermines the effectiveness of existing diagnostic tools and vaccine candidates. Existing vaccines typically elicit strain-specific immune responses, leaving populations vulnerable to newly emerging, reassorted variants. Additionally, there is limited validation of conserved and immunogenic regions that could serve as universal targets across H5 clades. Consequently, the identification of new conserved and immunogenic targets is critical for advancing serological surveillance and vaccine development.
Methodology
To address these challenges, we developed a bioinformatic and immunological pipeline that leverages large-scale viral genomics and immunoinformatics to systematically identify conserved neutralising B-cell epitopes within H5 hemagglutinin (HA) protein. We curated and analysed over 10,750 known publicly available H5Nx sequences and performed multiple sequence alignments to quantify conservation across major H5 lineages. We then mapped highly conserved regions to the Immune Epitope Database (IEDB). The epitope candidates were also assessed using peptide microarray with pooled human sera from individuals previously infected with or immunised against various influenza subtypes
Results and Discussion
Four conserved B-cell epitope candidates displayed strong binding affinity to the H5 subtype HA protein and could elicit a neutralising antibody response. Our findings underscore the potential of integrating big data viral genomics with immunological analyses to identify broadly conserved immune targets, offering a practical and scalable pathway towards rational, next-generation vaccine design.
Conclusions
The conserved epitopes identified in this study may inform the development of pan-H5 influenza vaccines, as well as enhance serological diagnostics capable of detecting a broad spectrum of H5 exposures. Beyond influenza, the scalable framework presented here can be applied to other rapidly evolving viral pathogens, contributing to global preparedness for future outbreaks