COVID-ONE-hi: The One-Stop Database for COVID-19-Specific Humoral Immunity and Clinical Parameters

  1. Zhaowei Xu
  2. Yang Li
  3. Qing Lei
  4. Likun Huang
  5. Dan-yun Lai
  6. Shu-juan Guo
  7. He-wei Jiang
  8. Hongyan Hou
  9. Yun-xiao Zheng
  10. Xue-ning Wang
  11. Jiaoxiang Wu
  12. Ming-liang Ma
  13. Bo Zhang
  14. Hong Chen
  15. Caizheng Yu
  16. Jun-biao Xue
  17. Hai-nan Zhang
  18. Huan Qi
  19. Siqi Yu
  20. Mingxi Lin
  21. Yandi Zhang
  22. Xiaosong Lin
  23. Zongjie Yao
  24. Huiming Sheng
  25. Ziyong Sun
  26. Feng Wang
  27. Xionglin Fan
  28. Sheng-ce Tao

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Abstract

Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, varies with regard to symptoms and mortality rates among populations. Humoral immunity plays critical roles in SARS-CoV-2 infection and recovery from COVID-19. However, differences in immune responses and clinical features among COVID-19 patients remain largely unknown. Here, we report a database for COVID-19-specific IgG/IgM immune responses and clinical parameters (named COVID-ONE-hi). COVID-ONE-hi is based on the data that contain the IgG/IgM responses to 24 full-length/truncated proteins corresponding to 20 of 28 known SARS-CoV-2 proteins and 199 spike protein peptides against 2360 serum samples collected from 783 COVID-19 patients. In addition, 96 clinical parameters for the 2360 serum samples and basic information for the 783 patients are integrated into the database. Furthermore, COVID-ONE-hi provides a dashboard for defining samples and a one-click analysis pipeline for a single group or paired groups. A set of samples of interest is easily defined by adjusting the scale bars of a variety of parameters. After the “START” button is clicked, one can readily obtain a comprehensive analysis report for further interpretation. COVID-ONE-hi is freely available at www.COVID-ONE.cn.

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  1. Version published to 10.1016/j.gpb.2021.09.006
  2. ScreenIT

    SciScore for 10.1101/2021.07.29.21261312: (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.

    Table 2: Resources

    Antibodies
    SentencesResources
    Anti-His (Millipore), anti-GST (Sigma), and anti-BSA (Sangon Biotech) antibodies were used for quality control of the SARS-CoV-2 proteome microarray.
    Anti-His
    suggested: None
    anti-GST
    suggested: None
    anti-BSA ( Sangon Biotech )
    suggested: None
    The arrays were washed with 1× PBST, and the bound antibodies were monitored by incubating with Cy3-conjugated goat anti-human IgG and Alexa Fluor 647-conjugated donkey anti-human IgM (Jackson ImmunoResearch, PA) diluted 1:1,000 in 1× PBST at room temperature for 1 h.
    anti-human IgG
    suggested: (Bio-Rad Cat# MCA647F, RRID:AB_808612)
    anti-human IgM
    suggested: None
    Recombinant DNA
    SentencesResources
    The optimized genes were synthesized and cloned into pET32a or pGEX-4T-1 by Sangon Biotech (Shanghai)
    pET32a
    suggested: RRID:Addgene_62310)
    pGEX-4T-1
    suggested: RRID:Addgene_113505)
    Software and Algorithms
    SentencesResources
    Pheatmap (1.0.12) and ggplot2 (3.3.2) carry out plotting.
    Pheatmap
    suggested: (pheatmap, RRID:SCR_016418)
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Nonetheless, there are some limitations for COVID-ONE humoral immunity. For example, it lacks data for convalescent patients, peptide-level humoral responses to proteins other than S protein, and multicentre samples. In the future, we will assay the dynamic responses of SARS-CoV-2-specific antibodies using ∼500 serum samples from ∼100 COVID-19 convalescent patients. We will also integrate published peptide microarray/phage display-related data[15-17, 30] and attempt to update the database covering the whole SARS-CoV-2 proteome at the peptide or amino acid level. In addition, the SARS-CoV-2 protein microarray has already been promoted by CDI Labs (www.cdi.bio) and ArrayJet (www.arrayjet.co.uk), and we anticipate more diverse data for SARS-CoV-2-specific antibody responses from multicentre samples. We strongly believe that by sharing a large dataset and facilitating data analysis, COVID-19 humoral immune is a valuable resource for COVID-19 research.

    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 10.1101/2021.07.29.21261312 on medRxiv