Longitudinal high-throughput TCR repertoire profiling reveals the dynamics of T cell memory formation after mild COVID-19 infection

  1. Anastasia A Minervina
  2. Ekaterina A Komech
  3. Aleksei Titov
  4. Meriem Bensouda Koraichi
  5. Elisa Rosati
  6. Ilgar Z Mamedov
  7. Andre Franke
  8. Grigory A Efimov
  9. Dmitriy M Chudakov
  10. Thierry Mora
  11. Aleksandra M Walczak
  12. Yuri B Lebedev
  13. Mikhail V Pogorelyy  Is a corresponding author
  1. Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Federation
  2. National Research Center for Hematology, Russian Federation
  3. École Normale Supérieure, France
  4. Kiel University, Germany
  5. Ecole Normale Supérieure de Paris, France

Abstract

COVID-19 is a global pandemic caused by the SARS-CoV-2 coronavirus. T cells play a key role in the adaptive antiviral immune response by killing infected cells and facilitating the selection of virus-specific antibodies. However neither the dynamics and cross-reactivity of the SARS-CoV-2-specific T cell response nor the diversity of resulting immune memory are well understood. In this study we use longitudinal high-throughput T cell receptor (TCR) sequencing to track changes in the T cell repertoire following two mild cases of COVID-19. In both donors we identified CD4+ and CD8+ T cell clones with transient clonal expansion after infection. The antigen specificity of CD8+ TCR sequences to SARS-CoV-2 epitopes was confirmed by both MHC tetramer binding and presence in large database of SARS-CoV-2 epitope-specific TCRs. We describe characteristic motifs in TCR sequences of COVID-19-reactive clones and show preferential occurence of these motifs in publicly available large dataset of repertoires from COVID-19 patients. We show that in both donors the majority of infection-reactive clonotypes acquire memory phenotypes. Certain T cell clones were detected in the memory fraction at the pre-infection timepoint, suggesting participation of pre-existing cross-reactive memory T cells in the immune response to SARS-CoV-2.

Data availability

Raw sequencing data are deposited to the Short Read Archive (SRA) accession: PRJNA633317. Resulting repertoires of SARS-CoV-2-reactive clones can be found in SI Tables 3-6 and also accessed from: https://github.com/pogorely/Minervina_COVID Processed TCRalpha and TCRbeta repertoire datasets are available at : https://zenodo.org/record/3835955

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Anastasia A Minervina

    Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9884-6351
  2. Ekaterina A Komech

    Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
    Competing interests
    No competing interests declared.
  3. Aleksei Titov

    Laboratory for Transplantation Immunology, National Research Center for Hematology, Moscow, Russian Federation
    Competing interests
    No competing interests declared.
  4. Meriem Bensouda Koraichi

    Laboratoire de Physique Theorique, École Normale Supérieure, Paris, France
    Competing interests
    No competing interests declared.
  5. Elisa Rosati

    Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2635-6422
  6. Ilgar Z Mamedov

    Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
    Competing interests
    No competing interests declared.
  7. Andre Franke

    Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany
    Competing interests
    No competing interests declared.
  8. Grigory A Efimov

    Laboratory for Transplantation Immunology, National Research Center for Hematology, Moscow, Russian Federation
    Competing interests
    No competing interests declared.
  9. Dmitriy M Chudakov

    Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0430-790X
  10. Thierry Mora

    Laboratoire de physique, Ecole Normale Supérieure de Paris, Paris, France
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5456-9361
  11. Aleksandra M Walczak

    Laboratoire de Physique Theorique, École Normale Supérieure, Paris, France
    Competing interests
    Aleksandra M Walczak, Senior editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2686-5702
  12. Yuri B Lebedev

    Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4554-4733
  13. Mikhail V Pogorelyy

    Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
    For correspondence
    m.pogorely@gmail.com
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0773-1204

Funding

Russian Science Foundation (RSF 20-15-00351)

  • Yuri B Lebedev

Deutsche Forschungsgemeinschaft (Exc2167)

  • Andre Franke

Deutsche Forschungsgemeinschaft (4096610003)

  • Andre Franke

H2020 European Research Council (COG 724208)

  • Aleksandra M Walczak

Russian Foundation for Basic Research (19-54-12-011)

  • Ilgar Z Mamedov

Russian Foundation for Basic Research (18-19-09132)

  • Ilgar Z Mamedov

Ministry of Science and Higher Education of the Russian Federation (075-15-2019-1789)

  • Dmitriy M Chudakov

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

Reviewing Editor

  1. Sandeep Krishna, National Centre for Biological Sciences­‐Tata Institute of Fundamental Research, India

Ethics

Human subjects: All subjects gave written informed consent in accordance with the Declaration of Helsinki. The study protocol was approved by the Pirogov Russian National Research Medical University local ethics committee (#194 granted on March 16, 2020)

Version history

  1. Received: September 27, 2020
  2. Accepted: January 5, 2021
  3. Accepted Manuscript published: January 5, 2021 (version 1)
  4. Version of Record published: January 13, 2021 (version 2)

Copyright

© 2021, Minervina 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.

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  1. Anastasia A Minervina
  2. Ekaterina A Komech
  3. Aleksei Titov
  4. Meriem Bensouda Koraichi
  5. Elisa Rosati
  6. Ilgar Z Mamedov
  7. Andre Franke
  8. Grigory A Efimov
  9. Dmitriy M Chudakov
  10. Thierry Mora
  11. Aleksandra M Walczak
  12. Yuri B Lebedev
  13. Mikhail V Pogorelyy
(2021)
Longitudinal high-throughput TCR repertoire profiling reveals the dynamics of T cell memory formation after mild COVID-19 infection
eLife 10:e63502.
https://doi.org/10.7554/eLife.63502

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https://doi.org/10.7554/eLife.63502

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