Broad and strong memory CD4+ and CD8+ T cells induced by SARS-CoV-2 in UK convalescent individuals following COVID-19

  1. Yanchun Peng
  2. Alexander J. Mentzer
  3. Guihai Liu
  4. Xuan Yao
  5. Zixi Yin
  6. Danning Dong
  7. Wanwisa Dejnirattisai
  8. Timothy Rostron
  9. Piyada Supasa
  10. Chang Liu
  11. César López-Camacho
  12. Jose Slon-Campos
  13. Yuguang Zhao
  14. David I. Stuart
  15. Guido C. Paesen
  16. Jonathan M. Grimes
  17. Alfred A. Antson
  18. Oliver W. Bayfield
  19. Dorothy E. D. P. Hawkins
  20. De-Sheng Ker
  21. Beibei Wang
  22. Lance Turtle
  23. Krishanthi Subramaniam
  24. Paul Thomson
  25. Ping Zhang
  26. Christina Dold
  27. Jeremy Ratcliff
  28. Peter Simmonds
  29. Thushan de Silva
  30. Paul Sopp
  31. Dannielle Wellington
  32. Ushani Rajapaksa
  33. Yi-Ling Chen
  34. Mariolina Salio
  35. Giorgio Napolitani
  36. Wayne Paes
  37. Persephone Borrow
  38. Benedikt M. Kessler
  39. Jeremy W. Fry
  40. Nikolai F. Schwabe
  41. Malcolm G. Semple
  42. J. Kenneth Baillie
  43. Shona C. Moore
  44. Peter J. M. Openshaw
  45. M. Azim Ansari
  46. Susanna Dunachie
  47. Eleanor Barnes
  48. John Frater
  49. Georgina Kerr
  50. Philip Goulder
  51. Teresa Lockett
  52. Robert Levin
  53. Yonghong Zhang
  54. Ronghua Jing
  55. Ling-Pei Ho
  56. Oxford Immunology Network Covid-19 Response T cell Consortium
  57. Eleanor Barnes
  58. Danning Dong
  59. Tao Dong
  60. Susanna Dunachie
  61. John Frater
  62. Philip Goulder
  63. Georgina Kerr
  64. Paul Klenerman
  65. Guihai Liu
  66. Andrew McMichael
  67. Giorgio Napolitani
  68. Graham Ogg
  69. Yanchun Peng
  70. Mariolina Salio
  71. Xuan Yao
  72. Zixi Yin
  73. ISARIC4C Investigators
  74. J. Kenneth Baillie
  75. Paul Klenerman
  76. Alexander J. Mentzer
  77. Shona C. Moore
  78. Peter J. M. Openshaw
  79. Malcolm G. Semple
  80. David I. Stuart
  81. Lance Turtle
  82. Richard J. Cornall
  83. Christopher P. Conlon
  84. Paul Klenerman
  85. Gavin R. Screaton
  86. Juthathip Mongkolsapaya
  87. Andrew McMichael
  88. Julian C. Knight
  89. Graham Ogg
  90. Tao Dong

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Abstract

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  1. Version published to 10.1038/s41590-020-0782-6
  2. ScreenIT

    SciScore for 10.1101/2020.06.05.134551: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Written informed consent was obtained from all patients.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    To determine EPTs to RBD and NP, immunoplates were coated with 0.125ug of Tetra-His antibody (34670; QIAGEN) followed by 2 ug/ml and 5 ug/ml of soluble RBD and NP, respectively.
    NP
    suggested: None
    On the second day, the PBMCs were stimulated with pooled or individual peptides at a final concentration of 10 μg/mL per individual peptide for 1 h in the presence of 2 μg/mL monoclonal antibodies against human CD28 (BD Pharmingen) and CD49d (BD Pharmingen) then for an additional 5h with GolgiPlug (
    human CD28
    suggested: None
    CD49d
    suggested: None
    Dead cells were first labelled for FACS analysis using LIVE/DEAD™ Fixable Aqua Dead Cell Stain Kit (Invitrogen) and with CD3-BUV395, CD8-PerCP.Cy5.5 as well as a panel of antibodies for dumping, cell activation, differentiation and inhibitory markers : CD14-BV510 (Biolegend UK), CD16-BV510 (Biolegend UK), CD19-BV510 (Biolegend UK), CD28-BV711, CD27-APC-R700, HLA-DR-BB515, CD38-BUV737, CD45RA-APC-H7, PD-1-BV650, CD57-BV785 (Biolegend, UK) and NKG2A (R&D).
    CD14-BV510
    suggested: None
    CD16-BV510
    suggested: None
    CD19-BV510
    suggested: None
    CD57-BV785
    suggested: None
    NKG2A
    suggested: None
    Software and Algorithms
    SentencesResources
    Synthetic peptides: A total of 423 15- to 18-mer peptides overlapping by 10 amino acid residues and spanning the full proteome of the SARS-CoV-2 except ORF-1 (253 spike, 29 M, 9 E, 35 ORF3a, 7ORF6, 15 ORF7a, 16 ORF8, 59 NP) were designed using the Los Alamos National Library web-based software PeptGen (http://www.hiv.lanl.gov/content/sequence/PEPTGEN/peptgen.html) and synthesized (purity >75%; Proimmune).
    PeptGen
    suggested: None
    Finally, surface markers including BUV395-anti-CD3 (BD Biosciences), BUV737-anti-CD4 (BD Biosciences), PerCP-Cy5.5-anti-CD8 (BD Biosciences), BV510-anti-CD14 (Biolegend), BV510-anti-CD16 (Biolegend) and BV510-anti-CD19 (Biolegend) were stained.
    BD Biosciences
    suggested: (BD Biosciences, RRID:SCR_013311)
    All samples were acquired on BD LSR Fortessa (BD Biosciences) flow cytometer and analyzed using FlowJo™ v.10 software for Mac (Becton, Dickinson and Company; 2019).
    FlowJo™
    suggested: (FlowJo, RRID:SCR_008520)
    Cell events were acquired on Fortessa X20 (BD Bioscience) and data files were analyzed using FlowJo software.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Statistical analysis: Statistical analysis was performed with IBM SPSS Statistics 25 and figures were made with GraphPad Prism 8.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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 32, 25 and 28. 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.

  3. Version published to 10.1101/2020.06.05.134551v1 on bioRxiv