Nature Communications (Feb 2025)

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

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

DOI
https://doi.org/10.1038/s41467-025-56659-3
Journal volume & issue
Vol. 16, no. 1
pp. 1 – 15

Abstract

Read online

Abstract 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.