Robust T cell immunity in convalescent individuals with asymptomatic or mild COVID-19

  1. Takuya Sekine
  2. André Perez-Potti
  3. Olga Rivera-Ballesteros
  4. Kristoffer Strålin
  5. Jean-Baptiste Gorin
  6. Annika Olsson
  7. Sian Llewellyn-Lacey
  8. Habiba Kamal
  9. Gordana Bogdanovic
  10. Sandra Muschiol
  11. David J. Wullimann
  12. Tobias Kammann
  13. Johanna Emgård
  14. Tiphaine Parrot
  15. Elin Folkesson
  16. Olav Rooyackers
  17. Lars I. Eriksson
  18. Anders Sönnerborg
  19. Tobias Allander
  20. Jan Albert
  21. Morten Nielsen
  22. Jonas Klingström
  23. Sara Gredmark-Russ
  24. Niklas K. Björkström
  25. Johan K. Sandberg
  26. David A. Price
  27. Hans-Gustaf Ljunggren
  28. Soo Aleman
  29. Marcus Buggert
  30. Karolinska COVID-19 Study Group

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Abstract

SARS-CoV-2-specific memory T cells will likely prove critical for long-term immune protection against COVID-19. We systematically mapped the functional and phenotypic landscape of SARS-CoV-2-specific T cell responses in a large cohort of unexposed individuals as well as exposed family members and individuals with acute or convalescent COVID-19. Acute phase SARS-CoV-2-specific T cells displayed a highly activated cytotoxic phenotype that correlated with various clinical markers of disease severity, whereas convalescent phase SARS-CoV-2-specific T cells were polyfunctional and displayed a stem-like memory phenotype. Importantly, SARS-CoV-2-specific T cells were detectable in antibody-seronegative family members and individuals with a history of asymptomatic or mild COVID-19. Our collective dataset shows that SARS-CoV-2 elicits robust memory T cell responses akin to those observed in the context of successful vaccines, suggesting that natural exposure or infection may prevent recurrent episodes of severe COVID-19 also in seronegative individuals.

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  1. ScreenIT

    SciScore for 10.1101/2020.06.29.174888: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: All participants enrolled in this study provided written informed consent in accordance with protocols approved by the regional ethical research boards and the Declaration of Helsinki.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Cells were washed in phosphate-buffered saline (PBS) supplemented with 2% fetal bovine serum (FBS) and 2 μM EDTA (FACS buffer) and stained with HLA class I tetramers and/or a directly conjugated antibody specific for CCR7 (clone G043H7; BioLegend) for 10 minutes at 37°C.
    CCR7
    suggested: None
    Directly conjugated monoclonal antibodies with the following specificities were used in flow cytometry experiments: CCR4–PE (clone 1G1), CCR6–PE-Cy7 (clone 11A9), CD3–BUV805 (clones RPA-T8 or UCHT1), CD8–BUV395 (clone RPA-T8), CD25–PE-Cy5 (clone M-A251), CD28–BUV563 (clone CD28.2), CD38–BUV496 (clone HIT29), CD69–BV750 (clone FN50), CD95–BB630 (clone DX2), CD107a–PE-CF594 (clone H4A3), CTLA-4–BB755 (clone BNI3), CXCR5–APC-R700 (clone RF8B2), granzyme B–BB790 (clone GB11), HLA-DR–BUV615 (clone G46-6), IL-2–APC-R700 (clone MQ1-17H12), Ki-67–BB660 (clone B56), LAG-3–BUV661 (clone T47-530), perforin– BB700 (clone dG9), TIGIT–BUV737 (clone 741182), and 2B4–PE/Dazzle 594 (clone C1.7) from BD Biosciences; CCR7–APC-Cy7 (clone G043H7), CD14–BV510 (clone M5E2), CD19–BV510 (clone HIB19), CD27–BV785 (clone O323), CD39–BV711 (clone A1), CD45RA–BV421 or CD45RA–BV570 (clone HI100), CD127–BV605 (clone A019D5), CXCR3–AF647 (clone G025H7), IFN-γ–BV785 (clone 4S.B3), PD-1–PE-Cy7 (clone EH12.2H7), TIM-3–BV650 (clone F38-2E2), and TNF–BV650 (clone Mab11) from BioLegend; TCF1–AF488 (clone C63D9) from Cell Signaling; TOX–A647 (clone REA473) from Miltenyi Biotec; and CD4–PE-Cy5.5 (clone S3.5) and IL-17A–PE (clone eBio64DEC17) from Thermo Fisher Scientific.
    CCR6–PE-Cy7
    suggested: None
    UCHT1
    suggested: (BD Biosciences Cat# 563546, RRID:AB_2744387)
    CD8–BUV395
    suggested: None
    CD25–PE-Cy5
    suggested: None
    CD28–BUV563
    suggested: None
    CD38–BUV496
    suggested: None
    CD69–BV750
    suggested: None
    CD95–BB630
    suggested: None
    CD107a–PE-CF594
    suggested: None
    CTLA-4–BB755
    suggested: None
    CXCR5–APC-R700
    suggested: None
    HLA-DR–BUV615
    suggested: None
    Ki-67–BB660
    suggested: None
    CD14–BV510
    suggested: None
    CD19–BV510
    suggested: None
    CD27–BV785
    suggested: None
    CD39–BV711
    suggested: None
    CD45RA–BV570
    suggested: None
    CXCR3–AF647
    suggested: None
    IFN-γ–BV785
    suggested: None
    PD-1–PE-Cy7
    suggested: None
    TIM-3–BV650
    suggested: None
    TNF–BV650
    suggested: None
    CD4–PE-Cy5.5
    suggested: None
    IL-17A–PE
    suggested: None
    SARS-CoV-2-specific antibodies were detected using both the iFLASH Anti-SARS-CoV-2 IgG chemiluminescent microparticle immunoassay against the nucleocapsid and envelope proteins (Shenzhen Yhlo Biotech Co. Ltd.) as well as the LIAISON SARS-CoV-2 IgG fully automated indirect chemiluminescent immunoassay serology assay against the S1 and S2 (spike) proteins (DiaSorin).
    Anti-SARS-CoV-2 IgG
    suggested: None
    S2
    suggested: None
    Software and Algorithms
    SentencesResources
    Directly conjugated monoclonal antibodies with the following specificities were used in flow cytometry experiments: CCR4–PE (clone 1G1), CCR6–PE-Cy7 (clone 11A9), CD3–BUV805 (clones RPA-T8 or UCHT1), CD8–BUV395 (clone RPA-T8), CD25–PE-Cy5 (clone M-A251), CD28–BUV563 (clone CD28.2), CD38–BUV496 (clone HIT29), CD69–BV750 (clone FN50), CD95–BB630 (clone DX2), CD107a–PE-CF594 (clone H4A3), CTLA-4–BB755 (clone BNI3), CXCR5–APC-R700 (clone RF8B2), granzyme B–BB790 (clone GB11), HLA-DR–BUV615 (clone G46-6), IL-2–APC-R700 (clone MQ1-17H12), Ki-67–BB660 (clone B56), LAG-3–BUV661 (clone T47-530), perforin– BB700 (clone dG9), TIGIT–BUV737 (clone 741182), and 2B4–PE/Dazzle 594 (clone C1.7) from BD Biosciences; CCR7–APC-Cy7 (clone G043H7), CD14–BV510 (clone M5E2), CD19–BV510 (clone HIB19), CD27–BV785 (clone O323), CD39–BV711 (clone A1), CD45RA–BV421 or CD45RA–BV570 (clone HI100), CD127–BV605 (clone A019D5), CXCR3–AF647 (clone G025H7), IFN-γ–BV785 (clone 4S.B3), PD-1–PE-Cy7 (clone EH12.2H7), TIM-3–BV650 (clone F38-2E2), and TNF–BV650 (clone Mab11) from BioLegend; TCF1–AF488 (clone C63D9) from Cell Signaling; TOX–A647 (clone REA473) from Miltenyi Biotec; and CD4–PE-Cy5.5 (clone S3.5) and IL-17A–PE (clone eBio64DEC17) from Thermo Fisher Scientific.
    BD Biosciences
    suggested: (BD Biosciences, RRID:SCR_013311)
    BioLegend
    suggested: (BioLegend, RRID:SCR_001134)
    Principal Component Analysis (PCA): PCA were performed in Python, using scikit-learn 0.22.1.
    Python
    suggested: (IPython, RRID:SCR_001658)
    scikit-learn
    suggested: (scikit-learn, RRID:SCR_002577)
    Dimensionality reduction was performed using the FlowJo plugin UMAP version 2.2 (FlowJo LLC).
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Clusters of phenotypically related cells were detected using PhenoGraph version 0.2.1.
    PhenoGraph
    suggested: (Phenograph, RRID:SCR_016919)
    GraphPad Software Inc.)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Statistics: Statistical analyses were performed using R studio or Prism version 7.0 (GraphPad Software Inc.)
    Prism
    suggested: (PRISM, RRID:SCR_005375)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on pages 28, 29 and 30. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. ScreenIT

    SciScore for 10.1101/2020.06.29.174888: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementAll participants enrolled in this study provided written informed consent in accordance with protocols approved by the regional ethical research boards and the Declaration of Helsinki.Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    These donors exhibited robust memory T cell responses months after infection , even in the absence of detectable circulating antibodies specific for SARS-CoV-2 , indicating a previously unanticipated degree of population-level immunity against COVID-19 .
    COVID-19
    suggested: None
    It remains to be determined if a robust memory T cell response in the absence of detectable circulating antibodies can protect against SARS-CoV-2 .
    SARS-CoV-2
    suggested: None
    Cells were washed in phosphate-buffered saline ( PBS ) supplemented with 2 % fetal bovine serum ( FBS ) and 2 μM EDTA ( FACS buffer ) and stained with HLA class I tetramers and/or a directly conjugated antibody specific for CCR7 ( clone G043H7; BioLegend ) for 10 minutes at 37°C .
    CCR7
    suggested: None
    Antibodies Directly conjugated monoclonal antibodies with the following specificities were used in flow cytometry experiments: CCR4–PE ( clone 1G1) , CCR6–PE-Cy7 ( clone 11A9) , CD3–BUV805 ( clones RPA-T8 or UCHT1) , CD8–BUV395 ( clone RPA-T8) , CD25–PECy5 ( clone M-A251) , CD28–BUV563 ( clone CD28.2) , CD38–BUV496 ( clone HIT29) , CD69–BV750 ( clone FN50) , CD95–BB630 ( clone DX2) , CD107a–PE-CF594 ( clone H4A3) , CTLA-4–BB755 ( clone BNI3) , CXCR5–APC-R700 ( clone RF8B2) , granzyme B–BB790 ( clone GB11) , HLA-DR–BUV615 ( clone G46-6) , IL-2–APC-R700 ( clone MQ1-17H12) , Ki-67–BB660 ( clone B56) , LAG-3–BUV661 ( clone T47-530) , perforin– BB700 ( clone dG9) , TIGIT–BUV737 ( clone 741182) , and 2B4–PE/Dazzle 594 ( clone C1.7 ) from BD Biosciences; CCR7–APC-Cy7 ( clone G043H7) , CD14–BV510 ( clone M5E2) , CD19–BV510 ( clone HIB19) , CD27–BV785 ( clone O323) , CD39–BV711 ( clone A1) , CD45RA–BV421 or CD45RA–BV570 ( clone HI100) , CD127–BV605 ( clone A019D5) , CXCR3–AF647 ( clone G025H7) , IFN-γ–BV785 ( clone 4S.B3) , PD-1–PECy7 ( clone EH12.2H7) , TIM-3–BV650 ( clone F38-2E2) , and TNF–BV650 ( clone Mab11 ) from BioLegend; TCF1–AF488 ( clone C63D9 ) from Cell Signaling; TOX–A647 ( clone REA473 ) from Miltenyi Biotec; and CD4–PE-Cy5.5 ( clone S3.5 ) and IL-17A–PE ( clone eBio64DEC17 ) from Thermo Fisher Scientific .
    CCR6–PE-Cy7
    suggested: None
          <div style="margin-bottom:8px">
        <div><b>UCHT1</b></div>
        <div>suggested: (BD Biosciences Cat# 563546, <a href="https://scicrunch.org/resources/Any/search?q=AB_2744387">AB_2744387</a>)</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CD8–BUV395</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CD28–BUV563</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CD38–BUV496</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CD69–BV750</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CD95–BB630</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CD107a–PE-CF594</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CTLA-4–BB755</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CXCR5–APC-R700</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>HLA-DR–BUV615</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>Ki-67–BB660</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CD14–BV510</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CD19–BV510</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CD27–BV785</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CD39–BV711</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CD45RA–BV570</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CXCR3–AF647</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>IFN-γ–BV785</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>PD-1–PECy7</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>TIM-3–BV650</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>TNF–BV650</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>CD4–PE-Cy5.5</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>IL-17A–PE</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">SARS-CoV2-specific antibodies were detected using both the iFLASH Anti-SARS-CoV-2 IgG chemiluminescent microparticle immunoassay against the nucleocapsid and envelope proteins ( Shenzhen Yhlo Biotech Co . Ltd. ) as well as the LIAISON SARSCoV-2 IgG fully automated indirect chemiluminescent immunoassay serology assay against the S1 and S2 ( spike ) proteins ( DiaSorin) .</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Anti-SARS-CoV-2 IgG</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>S2</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;text-align:center; padding-top:4px;" colspan="2"><b>Software and Algorithms</b></td></tr><tr><td style="min-width:100px;text=align:center"><i>Sentences</i></td><td style="min-width:100px;text-align:center"><i>Resources</i></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Antibodies Directly conjugated monoclonal antibodies with the following specificities were used in flow cytometry experiments: CCR4–PE ( clone 1G1) , CCR6–PE-Cy7 ( clone 11A9) , CD3–BUV805 ( clones RPA-T8 or UCHT1) , CD8–BUV395 ( clone RPA-T8) , CD25–PECy5 ( clone M-A251) , CD28–BUV563 ( clone CD28.2) , CD38–BUV496 ( clone HIT29) , CD69–BV750 ( clone FN50) , CD95–BB630 ( clone DX2) , CD107a–PE-CF594 ( clone H4A3) , CTLA-4–BB755 ( clone BNI3) , CXCR5–APC-R700 ( clone RF8B2) , granzyme B–BB790 ( clone GB11) , HLA-DR–BUV615 ( clone G46-6) , IL-2–APC-R700 ( clone MQ1-17H12) , Ki-67–BB660 ( clone B56) , LAG-3–BUV661 ( clone T47-530) , perforin– BB700 ( clone dG9) , TIGIT–BUV737 ( clone 741182) , and 2B4–PE/Dazzle 594 ( clone C1.7 ) from BD Biosciences; CCR7–APC-Cy7 ( clone G043H7) , CD14–BV510 ( clone M5E2) , CD19–BV510 ( clone HIB19) , CD27–BV785 ( clone O323) , CD39–BV711 ( clone A1) , CD45RA–BV421 or CD45RA–BV570 ( clone HI100) , CD127–BV605 ( clone A019D5) , CXCR3–AF647 ( clone G025H7) , IFN-γ–BV785 ( clone 4S.B3) , PD-1–PECy7 ( clone EH12.2H7) , TIM-3–BV650 ( clone F38-2E2) , and TNF–BV650 ( clone Mab11 ) from BioLegend; TCF1–AF488 ( clone C63D9 ) from Cell Signaling; TOX–A647 ( clone REA473 ) from Miltenyi Biotec; and CD4–PE-Cy5.5 ( clone S3.5 ) and IL-17A–PE ( clone eBio64DEC17 ) from Thermo Fisher Scientific .</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>BD Biosciences</b></div>
        <div>suggested: (BD Biosciences, <a href="https://scicrunch.org/resources/Any/search?q=SCR_013311">SCR_013311</a>)</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>BioLegend</b></div>
        <div>suggested: (BioLegend, <a href="https://scicrunch.org/resources/Any/search?q=SCR_001134">SCR_001134</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Principal Component Analysis ( PCA ) PCA were performed in Python , using scikit-learn 0.22.1 .</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Python</b></div>
        <div>suggested: (IPython, <a href="https://scicrunch.org/resources/Any/search?q=SCR_001658">SCR_001658</a>)</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>scikit-learn</b></div>
        <div>suggested: (scikit-learn, <a href="https://scicrunch.org/resources/Any/search?q=SCR_002577">SCR_002577</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Dimensionality reduction was performed using the FlowJo plugin UMAP version 2.2 ( FlowJo LLC) .</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>FlowJo</b></div>
        <div>suggested: (FlowJo, <a href="https://scicrunch.org/resources/Any/search?q=SCR_008520">SCR_008520</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Clusters of phenotypically related cells were detected using PhenoGraph version 0.2.1 .</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>PhenoGraph</b></div>
        <div>suggested: (Phenograph, <a href="https://scicrunch.org/resources/Any/search?q=SCR_016919">SCR_016919</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Plots were generated using Prism version 8.2.0 (</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Prism</b></div>
        <div>suggested: (PRISM, <a href="https://scicrunch.org/resources/Any/search?q=SCR_005375">SCR_005375</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Statistics Statistical analyses were performed using R studio or Prism version 7.0 ( GraphPad Software Inc . )</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>GraphPad</b></div>
        <div>suggested: (GraphPad Prism, <a href="https://scicrunch.org/resources/Any/search?q=SCR_002798">SCR_002798</a>)</div>
      </div>
    </td></tr></table>

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.06.29.174888 on bioRxiv