TY - JOUR
T1 - Tcr meta-clonotypes for biomarker discovery with tcrdist3 enabled identification of public, hla-restricted clusters of sars-cov-2 tcrs
AU - Mayer-Blackwell, Koshlan
AU - Schattgen, Stefan
AU - Cohen-Lavi, Liel
AU - Crawford, Jeremy C.
AU - Souquette, Aisha
AU - Gaevert, Jessica A.
AU - Hertz, Tomer
AU - Thomas, Paul G.
AU - Bradley, Philip G.
AU - Fiore-Gartland, Andrew
N1 - Funding Information:
This work was funded by NIH NIAID R01 AI136514-03 (PI Thomas) and ALSAC at St. Jude. The authors thank M Pogorelyy and A Minervina for extensive feedback on the manuscript. Scientific Computing Infrastructure at Fred Hutchinson Cancer Research Center was funded by ORIP grant S10OD028685.
Publisher Copyright:
© Mayer-Blackwell et al.
PY - 2021/11/30
Y1 - 2021/11/30
N2 - 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 restric-tion 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.
AB - 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 restric-tion 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.
UR - http://www.scopus.com/inward/record.url?scp=85120159716&partnerID=8YFLogxK
U2 - 10.7554/eLife.68605
DO - 10.7554/eLife.68605
M3 - Article
C2 - 34845983
AN - SCOPUS:85120159716
SN - 2050-084X
VL - 10
JO - eLife
JF - eLife
M1 - e68605
ER -