Journal Article

APMAT analysis reveals the association between CD8 T cell receptors, cognate antigen, and T cell phenotype and persistence

Zhang, Rongyu, Lausted, Christopher G., Chen, Daniel G., Choi, Jongchan, Mease, Phil, Logue, Jennifer K., Hong, Sunga, Yuan, Dan, Edmark, Rick, Chu, Helen, Chour, William, Troisch, Pamela, Greenberg, Philip D., Piening, Brian, Wallick, Julie, Murray, Kim M., Algren, Heather, Jones, Lesley, Li, Sarah, Smith, Brett, Goldman, Jason D., Xie, Jingyi, Rasheed, Yusuf, Watanabe, Kino, Heath, James R., Su, Yapeng, Magis, Andrew T., Franko, Nicholas M., Webster, Andrew, McKasson, Michaela, Ng, Rachel H.

2025

Overview

Elucidating the relationships between a class I peptide antigen, a CD8 T cell receptor (TCR) specific to that antigen, and the T cell phenotype that emerges following antigen stimulation, remains a mostly unsolved problem, largely due to the lack of large data sets that can be mined to resolve such relationships. Here, we describe Antigen-TCR Pairing and Multiomic Analysis of T-cells (APMAT), an integrated experimental-computational framework designed for the high-throughput capture and analysis of CD8 T cells, with paired antigen, TCR sequence, and single-cell transcriptome. Starting with 951 putative antigens representing a comprehensive survey of the SARS-CoV-2 viral proteome, we utilize APMAT for the capture and single cell analysis of CD8 T cells from 62 HLA A*02:01 COVID-19 participants. We leverage this comprehensive dataset to integrate with peptide antigen properties, TCR CDR3 sequences, and T cell phenotypes to show that distinct physicochemical features of the antigen-TCR pairs strongly associate with both T cell phenotype and T cell persistence. This analysis suggests that CD8 T cell phenotype following antigen stimulation is at least partially deterministic, rather than the result of stochastic biological properties. Combinatorial experimental and bioinformatics methods can be used to analyse function and specificity of CD8 T cells. Here the authors propose a multiomic analysis framework Antigen-TCR Pairing and Multiomic Analysis of T cell (APMAT) to relate TCR specificity to transcriptomic phenotype indicating associations with physicochemical features.

• Publisher: Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
• Subject: 13 / 13/109 / 13/31 / 38 / 38/23 / 38/39 / 38/47 / 38/91 / 42 / 49 / 631/250/1619/554 / 631/250/1619/554/1775 / 631/250/2152/1566/1572 / 631/250/255/2514 / 631/61/338 / 82/80 / Antigens / Antigens, Viral - immunology / Bioinformatics / Biological effects / Biological properties / CD8 antigen / CD8-Positive T-Lymphocytes - immunology / CD8-Positive T-Lymphocytes - metabolism / Combinatorial analysis / Complementarity-determining region 3 / COVID-19 / COVID-19 - immunology / COVID-19 - virology / Genotype & phenotype / HLA-A2 Antigen - immunology / Humanities and Social Sciences / Humans / Lymphocytes / Lymphocytes T / multidisciplinary / Peptides / Phenotype / Phenotypes / Proteomes / Receptors / Receptors, Antigen, T-Cell - genetics / Receptors, Antigen, T-Cell - immunology / Receptors, Antigen, T-Cell - metabolism / SARS-CoV-2 - immunology / Science / Science (multidisciplinary) / Sequences / Severe acute respiratory syndrome coronavirus 2 / Single-Cell Analysis - methods / Stimulation / T cell receptors / Transcriptomes / Transcriptomics