Dataset Information

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

ABSTRACT: 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.

SUBMITTER: McGowan E

PROVIDER: S-EPMC7930081 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

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

McGowan Ed E Rosenthal Rachel R Fiore-Gartland Andrew A Macharia Gladys G Balinda Sheila S Kapaata Anne A Umviligihozo Gisele G Muok Erick E Dalel Jama J Streatfield Claire L CL Coutinho Helen H Dilernia Dario D Monaco Daniela C DC Morrison David D Yue Ling L Hunter Eric E Nielsen Morten M Gilmour Jill J Hare Jonathan J

Frontiers in immunology 20210218

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 ap ...[more]

PMID: 33679745

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Dataset Information

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

Publications

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

Similar Datasets

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