TCR meta-clonotypes for biomarker discovery with tcrdist3 enabled identification of public, HLA-restricted clusters of SARS-CoV-2 TCRs.

Koshlan Mayer-Blackwell,Aisha Souquette,Jessica A Gaevert,Tomer Hertz,Jeremy C Crawford,Paul G Thomas,Stefan Schattgen,Andrew Fiore-Gartland,Liel Cohen-Lavi,Philip Bradley

doi:10.7554/elife.68605

Abstract

T-cell receptors (TCRs) encode clinically valuable information that reflects prior antigen exposure and potential future response. However, despite advances in deep repertoire sequencing, enormous TCR diversity complicates the use of TCR clonotypes as clinical biomarkers. We propose a new framework that leverages experimentally inferred antigen-associated TCRs to form meta-clonotypes - groups of biochemically similar TCRs - that can be used to robustly quantify functionally similar TCRs in bulk repertoires across individuals. We apply the framework to TCR data from COVID-19 patients, generating 1831 public TCR meta-clonotypes from the SARS-CoV-2 antigen-associated TCRs that have strong evidence of restriction to patients with a specific human leukocyte antigen (HLA) genotype. Applied to independent cohorts, meta-clonotypes targeting these specific epitopes were more frequently detected in bulk repertoires compared to exact amino acid matches, and 59.7% (1093/1831) were more abundant among COVID-19 patients that expressed the putative restricting HLA allele (false discovery rate [FDR]<0.01), demonstrating the potential utility of meta-clonotypes as antigen-specific features for biomarker development. To enable further applications, we developed an open-source software package, tcrdist3, that implements this framework and facilitates flexible workflows for distance-based TCR repertoire analysis.

Highlights

An individual’s unique repertoire of T-c ell receptors (TCRs) is shaped by antigen exposure and is a critical component of immunological memory (Emerson et al, 2017; Welsh and Selin, 2002)
It is helpful to demonstrate the concept with an example: suppose we generate background TCRs (i.e., OLGA-g enerated) from one V–J gene combination, if we find that 5/50,000 (i.e., 10–4) TCRs are within a TCR’s radius, but that they are sampled from a V–J gene combination with 1% (i.e., 10–2) prevalence, the estimated frequency in the full background would be 1 in 1 million (10−4 × 10−2 = 10−6)
We found that for each TCR, its radius-d efined meta-clonotype was more abundant within a repertoire and more prevalent in a human cohort than the exact clonotype; for example, TCR meta- clonotypes formed from the MIRA55:ORF1ab TCR set were detected in 3–12 of 15 human leukocyte antigen (HLA)- A*01 participants in the Multiplex Identification of Receptor Antigen (MIRA) cohort, despite 34 of the 46 centroid clonotype TCRs being private (Figure 6)

Summary

Introduction

An individual’s unique repertoire of T-c ell receptors (TCRs) is shaped by antigen exposure and is a critical component of immunological memory (Emerson et al, 2017; Welsh and Selin, 2002). The extreme diversity characterizing TCR repertoires, both within and between individuals, presents major hurdles to biomarker development. Using peptide—major histocompatibility complex (pMHC) tetramer sorting to focus on TCRs recognizing individual epitopes, which depends on knowing the peptide antigen and its MHC restriction, typically reveals that many distinct TCRs are able to recognize even a single pMHC (Coles et al, 2020; Meysman et al, 2019). This complicates detection of population- wide signatures of antigen exposure. Individual T-cell clonotypes are currently suboptimal and underpowered for population-level investigations of TCR specificity, which limits their application in the development of TCR-based clinical biomarkers

Methods

Results

Conclusion