Cryo-electron Microscopy Structure of S-Trimer, a Subunit Vaccine Candidate for COVID-19

  1. Jiahao Ma
  2. Danmei Su
  3. Yinyan Sun
  4. Xueqin Huang
  5. Ying Liang
  6. Linqiang Fang
  7. Yan Ma
  8. Wenhui Li
  9. Peng Liang
  10. Sanduo Zheng

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Abstract

An effective vaccine against SARS-CoV-2 is critical to end the COVID-19 pandemic. In this study, using Trimer-Tag technology, we were able to produce stable and large quantities of WT S-Trimer, a subunit vaccine candidate for COVID-19 with high safety and efficacy from animal and phase 1 clinical trial studies.

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  1. Version published to 10.1128/jvi.00194-21
  2. ScreenIT

    SciScore for 10.1101/2020.09.21.306357: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Experimental Models: Organisms/Strains
    SentencesResources
    The expression vector was then stably transfected into GH-CHO (dhfr -/-) cell line and high expression clones were selected and adapted to SFM-4-CHO (Hyclone) serum free medium and ACE2-Fc was produced in a 15 L bioreactor as essentially as described for S-Trimer above.
    dhfr -/-
    suggested: None
    Software and Algorithms
    SentencesResources
    After stepwise gene amplification with increasing concentrations (0.0–10 nM) of MTX (Sigma), a high titer clone was then adapted to SFM-4CHO serum-free medium (GE BioSciences).
    GE BioSciences
    suggested: None
    Cryo-EM Image processing: For MT S-Trimer protein, motion correction for cryo-EM images and contrast transfer function (CTF) estimation were performed using motioncorr2 (4) and CTFFIND4 (5) respectively. 574,832 particles were automatically picked from 534 images collected on grid without graphene oxide (GO) using Laplacian-of-Gaussian in Relion 3.0.7 (6), and 1,029,938 particles was automatically picked from 1584 images collected on grid with GO.
    Relion
    suggested: (RELION, RRID:SCR_016274)
    The model was manually built in COOT (7) and real space refinement was performed in Phenix (8) using rotomer, Ramachandran and secondary structure restraints.
    COOT
    suggested: (Coot, RRID:SCR_014222)

    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: 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.

    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 10.1101/2020.09.21.306357v1 on bioRxiv