Location: Animal Disease ResearchTitle: Proteome-wide epitope prediction: Leveraging bioinformatic technologies in rational vaccine design
Submitted to: Cellular Immunology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/23/2021
Publication Date: 11/2/2022
Citation: Wright, L.M., White, S.N. 2022. Proteome-wide epitope prediction: Leveraging bioinformatic technologies in rational vaccine design. Cellular Immunology. 3(6):375-379. https://doi.org/10.33696/immunology.3.120.
Interpretive Summary: Epitopes are small proteins recognized by the immune system, and a recent publication identifying epitopes in the bacterium Coxiella burnetii led to an invitation to write a commentary in a separate research journal. This commentary focuses on the methodology used in the previous manuscript, "Proteome-wide Analysis of Coxiella burnetii for Conserved T-cell Epitopes with Presentation Across Multiple Host Species," in order to promote a shift in paradigm to better leverage computational tools in rational vaccine design for bacterial and other pathogens with larger proteomes. Many prior studies using bioinformatic tools to define agent interaction with the immune system limit the number of proteins assessed to perhaps 10-20 in a viral proteome and focus on one aspect of the disease. We addressed a larger number of proteins totaling roughly 2,000 in a bacterial pathogen to prioritize targets for rational vaccine design. Our group eliminated proteins that were not comparable between bacterial isolates and which may cause an autoimmune reaction if used during vaccination efforts. Afterwards, every protein was studied in its ability to interact with multiple host species (cow, human, and mouse) and alternate immune system presentation methods (MHCI and MHCII, which correspond to intracellular pathogen and general T-cell immune responses). In doing so, the resultant data set defines epitopes that interact strongly with immune system T-cells, which are responsible for coordinating the immune response. Furthermore, the dataset allows for flexibility in future vaccine studies through the expansive nature of the resulting catalog of protein vaccine targets. In all, this shift in methodology promotes rational vaccine design efforts for agents with large numbers of proteins to screen.
Technical Abstract: Artificial intelligence-based prediction technologies have allowed definition of T-cell epitopes presented by Major Histocompatibility Complex (MHC) molecules with allele-specificity of presentation. While some have utilized these technologies on a smaller scale, recent work has expanded manageable proteome size, leveraged both the more restrictive MHC Class I and the more widely useful MHC Class II presentation, extended range of host species in comparative analysis, and incorporated pathogen genetic diversity to highlight broadly useful epitopes even for pathogens with multi-species host range. A recent study on the zoonotic pathogen Coxiella burnetii exemplifies possibilities for such analyses. These data suggest an expanding role for epitope prediction in rational vaccine design for a very broad range of pathogen and host systems.