High-throughput Identification and Analysis of Antigen-specific CD4+ T Cells

Abstract

We present a toolset for the high throughput detection and analysis of antigen-specific CD4+ T cells using DNA-barcoded, large libraries of single-chain trimers (SCTs) designed to mimic peptide-MHC multimers for class II human leukocyte antigen (HLA). Following platform validation, we executed an unbiased screen to capture and simultaneously analyze 2,188 CD4+ T cells with specificity to the Receptor Binding Domain (RBD) of SARS-CoV-2 Spike protein, from a longitudinal cohort of 24 HLA-DR1 matched participants. We tracked RBD-antigen-specific CD4+ T cell phenotypes out to over two years post-infection, and identified metrics for defining immunogenic class II-restricted viral antigens. We also identified human papilloma virus (HPV)-16 E6-specific CD4+ T cell receptors (TCRs) from HPV16+ patients with precancerous lesions. Those TCRs are analyzed for their therapeutic potential for treating HPV+ cancers. This platform enables detailed investigation of CD4+ T cell immune responses and can accelerate the discovery of both relevant epitopes and TCRs for immunotherapies.