Longitudinal high-throughput TCR repertoire profiling reveals the dynamics of T cell memory formation after mild COVID-19 infection
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Federation
- National Research Center for Hematology, Russian Federation
- École Normale Supérieure, France
- Kiel University, Germany
- 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
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A large-scale database of T-cell receptor beta (TCRb) sequences and binding associations from natural and synthetic exposure to SARS-CoV-2ImmuneAccess, DOI: https://doi.org/10.21417/ADPT2020COVID.
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Immunosequencing identifies signatures of cytomegalovirus exposure history and HLA-mediated effects on the T-cell repertoireImmuneAccess, DOI: https://doi.org/10.21417/B7001Z.
Article and author information
Author details
Anastasia A Minervina
Dmitriy M Chudakov
Aleksandra M Walczak
Mikhail V Pogorelyy
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
- 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
- Received: September 27, 2020
- Accepted: January 5, 2021
- Accepted Manuscript published: January 5, 2021 (version 1)
- 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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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
Further reading
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Accurate prediction of the structurally diverse complementarity determining region heavy chain 3 (CDR-H3) loop structure remains a primary and long-standing challenge for antibody modeling. Here, we present the H3-OPT toolkit for predicting the 3D structures of monoclonal antibodies and nanobodies. H3-OPT combines the strengths of AlphaFold2 with a pre-trained protein language model and provides a 2.24 Å average RMSDCα between predicted and experimentally determined CDR-H3 loops, thus outperforming other current computational methods in our non-redundant high-quality dataset. The model was validated by experimentally solving three structures of anti-VEGF nanobodies predicted by H3-OPT. We examined the potential applications of H3-OPT through analyzing antibody surface properties and antibody–antigen interactions. This structural prediction tool can be used to optimize antibody–antigen binding and engineer therapeutic antibodies with biophysical properties for specialized drug administration route.
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- Computational and Systems Biology
- Medicine
Background:
Preterm birth is the leading cause of neonatal morbidity and mortality worldwide. Most cases of preterm birth occur spontaneously and result from preterm labor with intact (spontaneous preterm labor [sPTL]) or ruptured (preterm prelabor rupture of membranes [PPROM]) membranes. The prediction of spontaneous preterm birth (sPTB) remains underpowered due to its syndromic nature and the dearth of independent analyses of the vaginal host immune response. Thus, we conducted the largest longitudinal investigation targeting vaginal immune mediators, referred to herein as the immunoproteome, in a population at high risk for sPTB.
Methods:
Vaginal swabs were collected across gestation from pregnant women who ultimately underwent term birth, sPTL, or PPROM. Cytokines, chemokines, growth factors, and antimicrobial peptides in the samples were quantified via specific and sensitive immunoassays. Predictive models were constructed from immune mediator concentrations.
Results:
Throughout uncomplicated gestation, the vaginal immunoproteome harbors a cytokine network with a homeostatic profile. Yet, the vaginal immunoproteome is skewed toward a pro-inflammatory state in pregnant women who ultimately experience sPTL and PPROM. Such an inflammatory profile includes increased monocyte chemoattractants, cytokines indicative of macrophage and T-cell activation, and reduced antimicrobial proteins/peptides. The vaginal immunoproteome has improved predictive value over maternal characteristics alone for identifying women at risk for early (<34 weeks) sPTB.
Conclusions:
The vaginal immunoproteome undergoes homeostatic changes throughout gestation and deviations from this shift are associated with sPTB. Furthermore, the vaginal immunoproteome can be leveraged as a potential biomarker for early sPTB, a subset of sPTB associated with extremely adverse neonatal outcomes.
Funding:
This research was conducted by the Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services (NICHD/NIH/DHHS) under contract HHSN275201300006C. ALT, KRT, and NGL were supported by the Wayne State University Perinatal Initiative in Maternal, Perinatal and Child Health.
