Structural assessment of HLA-A2-restricted SARS-CoV-2 spike epitopes recognized by public and private T-cell receptors

  1. Daichao Wu
  2. Alexander Kolesnikov
  3. Rui Yin
  4. Johnathan D. Guest
  5. Ragul Gowthaman
  6. Anton Shmelev
  7. Yana Serdyuk
  8. Dmitry V. Dianov
  9. Grigory A. Efimov
  10. Brian G. Pierce
  11. Roy A. Mariuzza

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

T cells play a vital role in combatting SARS-CoV-2 and forming long-term memory responses. Whereas extensive structural information is available on neutralizing antibodies against SARS-CoV-2, such information on SARS-CoV-2-specific T-cell receptors (TCRs) bound to their peptide–MHC targets is lacking. Here we determine the structures of a public and a private TCR from COVID-19 convalescent patients in complex with HLA-A2 and two SARS-CoV-2 spike protein epitopes (YLQ and RLQ). The structures reveal the basis for selection of particular TRAV and TRBV germline genes by the public but not the private TCR, and for the ability of the TCRs to recognize natural variants of RLQ but not YLQ. Neither TCR recognizes homologous epitopes from human seasonal coronaviruses. By elucidating the mechanism for TCR recognition of an immunodominant yet variable epitope (YLQ) and a conserved but less commonly targeted epitope (RLQ), this study can inform prospective efforts to design vaccines to elicit pan-coronavirus immunity.

Article activity feed

  1. Version published to 10.1038/s41467-021-27669-8
  2. ScreenIT

    SciScore for 10.1101/2021.07.28.454232: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    1.25 × 105 J76 cells were co-incubated with 2.5 × 105 K562 cells transgenic for HLA-A*02:01 in 96 well plates filled with 200 μL of IMDM media 10% FCS (Gibco) containing serial dilutions peptide of interest in three independent replicates.
    J76
    suggested: None
    K562
    suggested: None
    Recombinant DNA
    SentencesResources
    Codon-optimized genes encoding the α and β chains of these TCRs (TCR RLQ3 residues 1–204 and 1–244; TCR YLQ7 residues 1–203 and 1–241, respectively) were synthesized (Supplementary Table 11) and cloned into the expression vector pET22b (GenScript).
    pET22b
    suggested: RRID:Addgene_84863)
    Software and Algorithms
    SentencesResources
    The acquired data was processed by FlowJo (version 10.6.2) and Prizm Software for analysis.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Structure determination and refinement: Before structure determination and refinement, all data reductions were performed using the CCP4 software suite (69).
    CCP4
    suggested: (CCP4, RRID:SCR_007255)
    Structures were determined by molecular replacement with the program Phaser (70) and refined with Phenix (71).
    Phenix
    suggested: (Phenix, RRID:SCR_014224)
    The models were further refined by manual model building with Coot (72) based on 2Fo – Fc and Fo – Fc maps.
    Coot
    suggested: (Coot, RRID:SCR_014222)
    The PyMOL program (https://pymol.org/) was used to prepare figures.
    PyMOL
    suggested: (PyMOL, RRID:SCR_000305)
    Representative spike glycoprotein sequences for other coronaviruses, corresponding to an adaptation of a set of spike sequences from the CoV3D database (77), were obtained from NCBI and GISAID, and aligned using MAFFT software (78) to generate a multiple sequence alignment which was used to obtain sequences corresponding to the YLQ and RLQ epitope positions in those viruses.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)

    Results from OddPub: Thank you for sharing your data.

    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: We did not find any issues relating to colormaps.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.21203/rs.3.rs-726298/v1 on Research Square
  4. Version published to 10.1101/2021.07.28.454232v1 on bioRxiv