Developing a Multi-Epitope Subunit Vaccine Candidate Against Fasciola gigantica Using Reverse Vaccinology and Immunoinformatic Approaches: A Nigerian Context

Fasciolosis caused by Fasciola gigantica imposes substantial economic losses on Nigeria's ruminant livestock sector and poses zoonotic risks to human populations consuming raw watercress and contaminated water, yet no commercially available vaccine exists for this parasite. This doctoral research employs reverse vaccinology and immunoinformatics to design and computationally validate a multi-epitope subunit vaccine candidate against F. gigantica, grounded in the genomic and transcriptomic characteristics of Nigerian isolates. Adult F. gigantica flukes were collected from cattle livers condemned at abattoirs in Kano, Benue, and Rivers States. Genomic DNA and total RNA were extracted for whole-genome sequencing and transcriptomic profiling of excretory-secretory proteins. Predicted secretory proteins were prioritised using signal peptide prediction, transmembrane topology, and antigenicity scoring. B cell, CD4+ and CD8+ T cell epitopes were predicted from high-priority targets using the IEDB analysis resource, NetMHCpan, and BepiPred algorithms. A chimeric multi-epitope construct was designed using EAAAK linkers and the toll-like receptor 4 agonist adjuvant. Molecular docking and dynamics simulation assessed construct binding affinity to ovine and bovine MHC class II molecules. Codon optimisation for expression in E. coli was performed and the recombinant protein expressed and purified. Immunological assessment of the purified vaccine candidate was performed in a murine model. Evidence from 2020 to 2024 confirms reverse vaccinology as a productive approach for neglected helminth vaccine discovery. This study produces a candidate ready for advanced preclinical evaluation. Keywords: Fasciola gigantica, reverse vaccinology, multi-epitope vaccine, immunoinformatics, Nigeria.