Abstract

T cells use their T-cell receptors (TCRs) to discriminate between lower-affinity self and higher-affinity non-self pMHC antigens. Although the discriminatory power of the TCR is widely believed to be near-perfect, technical difficulties have hampered efforts to precisely quantify it. Here, we describe a method for measuring very low TCR/pMHC affinities, and use it to measure the discriminatory power of the TCR, and the factors affecting it. We find that TCR discrimination, although enhanced compared with conventional cell-surface receptors, is imperfect: primary human T cells can respond to pMHC with affinities as low as KD ~1 mM. The kinetic proofreading mechanism fit our data, providing the first estimates of both the time delay (2.8 s) and number of biochemical steps (2.67) that are consistent with the extraordinary sensitivity of antigen recognition. Our findings explain why self pMHC frequently induce autoimmune diseases and anti-tumour responses, and suggest ways to modify TCR discrimination.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 1, 2, 4, S3, and S7 and Table S1 and S2.

Article and author information

Author details

  1. Johannes Pettmann

    Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1979-8943
  2. Anna Huhn

    Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
  3. Enas Abu Shah

    Kennedy Institute of Rheumatology, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5033-8171
  4. Mikhail A Kutuzov

    Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3386-4350
  5. Daniel B Wilson

    Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
  6. Michael L Dustin

    Kennedy Institute of Rheumatology, University of Oxford, Oxford, United Kingdom
    Competing interests
    Michael L Dustin, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4983-6389
  7. Simon J Davis

    Kennedy Institute of Rheumatology, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
  8. P Anton van der Merwe

    Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9902-6590
  9. Omer Dushek

    Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
    For correspondence
    omer.dushek@path.ox.ac.uk
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5847-5226

Funding

Wellcome Trust (207537/Z/17/Z)

  • Johannes Pettmann
  • Anna Huhn
  • Enas Abu Shah
  • Mikhail A Kutuzov
  • Daniel B Wilson
  • Omer Dushek

Wellcome Trust (098274/Z/12/Z)

  • Simon J Davis

Wellcome Trust (100262Z/12/Z)

  • Michael L Dustin

Wellcome Trust (203737/Z/16/Z)

  • Johannes Pettmann

UCB-Oxford Post-doctoral Fellowship

  • Enas Abu Shah

National Science Foundation Division of Mathematical Sciences USA (NSF-DMS 1902854)

  • Daniel B Wilson

Edward Penley Abraham Trust Studentship

  • Anna Huhn

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Frederik Graw, Heidelberg University, Germany

Ethics

Human subjects: Ethical approval was provided by the Medical Sciences Inter-divisional Research Ethics Committee (IDREC) at the University of Oxford (R51997/RE001).

Version history

  1. Received: January 30, 2021
  2. Accepted: May 15, 2021
  3. Accepted Manuscript published: May 25, 2021 (version 1)
  4. Version of Record published: June 22, 2021 (version 2)
  5. Version of Record updated: January 5, 2022 (version 3)

Copyright

© 2021, Pettmann et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 7,638
    views
  • 1,151
    downloads
  • 54
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Johannes Pettmann
  2. Anna Huhn
  3. Enas Abu Shah
  4. Mikhail A Kutuzov
  5. Daniel B Wilson
  6. Michael L Dustin
  7. Simon J Davis
  8. P Anton van der Merwe
  9. Omer Dushek
(2021)
The discriminatory power of the T cell receptor
eLife 10:e67092.
https://doi.org/10.7554/eLife.67092

Share this article

https://doi.org/10.7554/eLife.67092

Further reading

    1. Computational and Systems Biology
    Maksim Kleverov, Daria Zenkova ... Alexey A Sergushichev
    Research Article

    Transcriptomic profiling became a standard approach to quantify a cell state, which led to accumulation of huge amount of public gene expression datasets. However, both reuse of these datasets or analysis of newly generated ones requires significant technical expertise. Here we present Phantasus - a user-friendly web-application for interactive gene expression analysis which provides a streamlined access to more than 96000 public gene expression datasets, as well as allows analysis of user-uploaded datasets. Phantasus integrates an intuitive and highly interactive JavaScript-based heatmap interface with an ability to run sophisticated R-based analysis methods. Overall Phantasus allows users to go all the way from loading, normalizing and filtering data to doing differential gene expression and downstream analysis. Phantasus can be accessed on-line at https://alserglab.wustl.edu/phantasus or can be installed locally from Bioconductor (https://bioconductor.org/packages/phantasus). Phantasus source code is available at https://github.com/ctlab/phantasus under MIT license.

    1. Computational and Systems Biology
    2. Evolutionary Biology
    Ryan T Bell, Harutyun Sahakyan ... Eugene V Koonin
    Research Article

    A comprehensive census of McrBC systems, among the most common forms of prokaryotic Type IV restriction systems, followed by phylogenetic analysis, reveals their enormous abundance in diverse prokaryotes and a plethora of genomic associations. We focus on a previously uncharacterized branch, which we denote coiled-coil nuclease tandems (CoCoNuTs) for their salient features: the presence of extensive coiled-coil structures and tandem nucleases. The CoCoNuTs alone show extraordinary variety, with three distinct types and multiple subtypes. All CoCoNuTs contain domains predicted to interact with translation system components, such as OB-folds resembling the SmpB protein that binds bacterial transfer-messenger RNA (tmRNA), YTH-like domains that might recognize methylated tmRNA, tRNA, or rRNA, and RNA-binding Hsp70 chaperone homologs, along with RNases, such as HEPN domains, all suggesting that the CoCoNuTs target RNA. Many CoCoNuTs might additionally target DNA, via McrC nuclease homologs. Additional restriction systems, such as Type I RM, BREX, and Druantia Type III, are frequently encoded in the same predicted superoperons. In many of these superoperons, CoCoNuTs are likely regulated by cyclic nucleotides, possibly, RNA fragments with cyclic termini, that bind associated CARF (CRISPR-Associated Rossmann Fold) domains. We hypothesize that the CoCoNuTs, together with the ancillary restriction factors, employ an echeloned defense strategy analogous to that of Type III CRISPR-Cas systems, in which an immune response eliminating virus DNA and/or RNA is launched first, but then, if it fails, an abortive infection response leading to PCD/dormancy via host RNA cleavage takes over.