Antigen discovery and specification of immunodominance hierarchies for MHCII-restricted epitopes.
Authors of this article are:
Graham DB,, Luo C,, O’Connell DJ, Lefkovith A, Brown EM, Yassour M, Varma M, Abelin JG, Conway KL, Jasso GJ, Matar CG, Carr SA, Xavier RJ,0,.
A summary of the article is shown below:
Identifying immunodominant T cell epitopes remains a significant challenge in the context of infectious disease, autoimmunity, and immuno-oncology. To address the challenge of antigen discovery, we developed a quantitative proteomic approach that enabled unbiased identification of major histocompatibility complex class II (MHCII)-associated peptide epitopes and biochemical features of antigenicity. On the basis of these data, we trained a deep neural network model for genome-scale predictions of immunodominant MHCII-restricted epitopes. We named this model bacteria originated T cell antigen (BOTA) predictor. In validation studies, BOTA accurately predicted novel CD4 T cell epitopes derived from the model pathogen Listeria monocytogenes and the commensal microorganism Muribaculum intestinale. To conclusively define immunodominant T cell epitopes predicted by BOTA, we developed a high-throughput approach to screen DNA-encoded peptide-MHCII libraries for functional recognition by T cell receptors identified from single-cell RNA sequencing. Collectively, these studies provide a framework for defining the immunodominance landscape across a broad range of immune pathologies.
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