In Silico Prediction of Plasmodium falciparum Epitopes as Vaccine Candidates

About This Grant

PROJECT SUMMARY/ABSTRACT Current recommended malaria vaccines, RTS,S and R21, are notable achievements in combating Plasmodium falciparum (Pf), but with only moderate efficacy, they face significant limitations. These vaccines are restricted to targeting a single protein in the liver stage of the parasite's lifecycle and are constrained by low immunogenicity and strain-dependent efficacy, highlighting the need for a more targeted approach to malaria vaccine design. An epitope-based vaccine strategy can target multiple well-defined peptide sequences, or epitopes, which are conserved in essential proteins expressed by the parasite and preferentially interact with T cell receptors to elicit focused and robust immune responses. The core of this proposal involves a multi- faceted strategy incorporating genomic, proteomic, and immunoinformatic tools for predicting and ranking T cell epitopes conserved within essential Pf proteins expressed in different parasite life stages. In Aim 1, I will identify T cell epitopes using parasite protein sequence datasets and host HLA allele frequency datasets, each comprised of samples from sub-Saharan African regions, to ensure the applicability of findings to the protection of individuals in endemic regions from circulating Pf strains. I will develop advanced computational down- selection models to prioritize T cell epitopes based on their immunogenic potential, sequence conservation, and endemic area-based HLA restriction patterns and identify sets of epitopes capable of achieving high population-level coverage of HLA alleles and minimizing immune escape. Aim 2 focuses on validating the immunogenicity of identified T cell epitopes through peptide stimulation and functional T cell assays performed on expanded T cells from malaria-exposed Malian adults. I will conduct T cell stimulation and FluoroSpot assays with approximately 100 putative epitopes, followed by intracellular cytokine staining and flow cytometry to quantify T cell response specificity and subset composition, determining which epitopes consistently elicit multifunctional antigen-specific CD8+ or CD4+ T cell responses across donors. Ultimately, this project aims to develop a more effective malaria vaccine by integrating innovative epitope-based strategies with cutting-edge computational and experimental techniques. This proposed work employs advanced bioinformatics tools for high-throughput analysis of endemic region data, integrating parasite protein and host HLA sequences to identify promising broadly immunogenic and conserved T cell epitopes for future use in a multi-epitope-based vaccine targeting multiple life stages of diverse Pf strains. The resulting computational pipeline will be adaptable to other antigenically variable pathogens and genetically diverse populations, extending its relevance beyond malaria and sub-Saharan Africa to support global efforts in rational vaccine design, accelerate epitope discovery across pathogens, and enhance preparedness for future emerging infectious diseases.