Prediction of immunodominant CD4+ SARS-CoV-2 epitopes with TCR repertoire sequencing data

Abstract

Abstract The T cell receptor (TCR) is a hypervariable molecule defining the specificity of T cells for peptide-MHC complex. Defining exact epitopes is crucial to profile T cell responses in COVID-19 and yet very few MHC-II restricted SARS-CoV-2 epitopes are currently known. Here, we propose a reverse epitope discovery technique, which, instead of using large pools of peptides to identify reactive T cells, utilizes TCR repertoire sequencing data as the means to predict immunodominant epitopes. The core idea of the approach is to combine information from large, publicly available TCR repertoire datasets: TCRbeta repertoires from cohorts of COVID-19 patients and controls, and paired TCR repertoires of single T cells activated by SARS-CoV-2 peptides. Our pipeline allows us to predict the HLA-restriction of public SARS-CoV-2 specific TCR clonotypes, which in turn allows us to predict binding to a specific peptide. We applied this approach to single cell TCR repertoires of CD4+ T cells from COVID-19 patients, and predicted six MHC-II restricted immunodominant epitopes and alpha-beta TCR motifs recognising them and tested our predictions experimentally. We further applied this technique to bulk TCRalpha repertoires from T follicular helper cells from draining lymph nodes of healthy donors after BNT162b2 mRNA vaccination. We found that the DPB1*04 restricted S167–180 epitope is responsible for the largest public CD4+ response, and recognition of this epitope is driven by a semi-invariant TCR alpha chain. This finding led to generation of the DPB1*04 S167–180 tetramer, allowing to track SARS-CoV-2 specific CD4 cells in peripheral blood and lymph node samples with flow cytometry. This work was partially supported by R01AI136514 grant. This work was partially supported by R01AI136514 grant.