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

Publication Title

bioRxiv

Authors

JingXin Liang, Institute for Systems Biology, 401 Terry Ave North, Seattle, WA, 98109-5263, USAFollow
Daniel G Chen, Institute for Systems Biology
William Chour, Institute for Systems Biology
Rachel H Ng, Institue for Systems Biology
Rongyu Zhang, Institute for Systems Biology
Dan Yuan, Institute for Systems Biology
Jongchan Choi, Institute for Systems Biology
Michaela McKasson, Institute for Systems Biology
Pamela Troisch, Institute for Systems Biology
Brett Smith, Institute for Systems Biology
Lesley Jones, Institute for Systems Biology
Andrew Webster, Institute for Systems Biology
Yusuf Rasheed, Institute for Systems Biology
Sarah Li, Institute for Systems Biology
Rick Edmark, Institute for Systems Biology
Sunga Hong, Institute for Systems Biology
Kim M Murray, Institute for Systems Biology
Jennifer K Logue
Nicholas M Franko
Christopher G Lausted, Institute for Systems Biology
Brian D. Piening, Molecular Genomics Laboratory, Providence Portland Medical Center, Portland, OR; Earle A. Chiles Research Institute, Robert W. Franz Cancer Research Center, Providence Portland Cancer Center, Portland, OR.Follow
Heather A Algren, Swedish Medical Center - Swedish Center for Research and InnovationFollow
Julie A Wallick, Swedish Medical Center - Swedish Center for Research and InnovationFollow
Andrew T Magis, Institute for Systems Biology
Kino Watanabe
Philip Mease, Swedish Medical Center/Providence St. Joseph Health, and University of Washington School of Medicine, Seattle, Washington, USAFollow
Philip D Greenberg
Helen Chu
Jason D. Goldman, ProvidenceFollow
Yapeng Su, Institute for Systems Biology
James R Heath, Institute for Systems Biology

Document Type

Article

Publication Date

1-9-2025

Keywords

washington; isb; seattle; swedish; genomics; covid-19

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 unique, 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.

Specialty/Research Institute

Infectious Diseases

Specialty/Research Institute

Institute for Systems Biology

DOI

10.1101/2025.01.08.631993

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