Massively parallel interrogation and mining of natively paired human TCRαβ repertoires

Matthew J. Spindler, Ayla L. Nelson, Ellen K. Wagner, Natasha Oppermans, John S. Bridgeman, James M. Heather, Adam S. Adler, Michael A. Asensio, Robert C. Edgar, Yoong Wearn Lim, Everett H. Meyer, Robert E. Hawkins, Mark Cobbold, David S. Johnson

Research output: Contribution to journalArticlepeer-review

Abstract

T cells engineered to express antigen-specific T cell receptors (TCRs) are potent therapies for viral infections and cancer. However, efficient identification of clinical candidate TCRs is complicated by the size and complexity of T cell repertoires and the challenges of working with primary T cells. Here we present a high-throughput method to identify TCRs with high functional avidity from diverse human T cell repertoires. The approach used massively parallel microfluidics to generate libraries of natively paired, full-length TCRαβ clones, from millions of primary T cells, which were then expressed in Jurkat cells. The TCRαβ–Jurkat libraries enabled repeated screening and panning for antigen-reactive TCRs using peptide major histocompatibility complex binding and cellular activation. We captured more than 2.9 million natively paired TCRαβ clonotypes from six healthy human donors and identified rare (<0.001% frequency) viral-antigen-reactive TCRs. We also mined a tumor-infiltrating lymphocyte sample from a patient with melanoma and identified several tumor-specific TCRs, which, after expression in primary T cells, led to tumor cell killing.

Original languageEnglish
Pages (from-to)609-619
Number of pages11
JournalNature biotechnology
Volume38
Issue number5
DOIs
Publication statusPublished - 16 Mar 2020

Research Beacons, Institutes and Platforms

  • Manchester Cancer Research Centre

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