Utilizing Computational Machine Learning Tools to Understand Immunogenic Breadth in the Context of a CD8 T-Cell Mediated HIV Response

Autor: Gisele Umviligihozo, Ed McGowan, Jonathan Hare, David A. Morrison, Andrew Fiore-Gartland, Daniela C. Monaco, Jama Dalel, Dario A. Dilernia, Eric Hunter, Morten Nielsen, Gladys Macharia, Helen Coutinho, Claire Streatfield, Ling Yue, Sheila Balinda, Erick M. O. Muok, Jill Gilmour, Rachel Rosenthal, Anne Kapaata
Rok vydání: 2021
Předmět:
Zdroj: Frontiers in Immunology, Vol 12 (2021)
Frontiers in Immunology
ISSN: 1664-3224
Popis: Predictive models are becoming more and more commonplace as tools for candidate antigen discovery to meet the challenges of enabling epitope mapping of cohorts with diverse HLA properties. Here we build on the concept of using two key parameters, diversity metric of the HLA profile of individuals within a population and consideration of sequence diversity in the context of an individual's CD8 T-cell immune repertoire to assess the HIV proteome for defined regions of immunogenicity. Using this approach, analysis of HLA adaptation and functional immunogenicity data enabled the identification of regions within the proteome that offer significant conservation, HLA recognition within a population, low prevalence of HLA adaptation and demonstrated immunogenicity. We believe this unique and novel approach to vaccine design as a supplement to vitro functional assays, offers a bespoke pipeline for expedited and rational CD8 T-cell vaccine design for HIV and potentially other pathogens with the potential for both global and local coverage.
Databáze: OpenAIRE