Transcriptome analysis of SARS-CoV-2 naïve and recovered individuals vaccinated with inactivated vaccine

  1. Yuwei Zhang
  2. Xingyu Guo
  3. Cunbao Li
  4. Zengqiang Kou
  5. Lanfang Lin
  6. Mingxiao Yao
  7. Bo Pang
  8. Xiaomei Zhang
  9. Qing Duan
  10. Xueying Tian
  11. Yufang Xing
  12. Xiaolin Jiang

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

The urgent approval of the use of the inactivated COVID-19 vaccine is essential to reduce the threat and burden of the epidemic on global public health, however, our current understanding of the host immune response to inactivated vaccine remains limited. Herein, we performed serum IgG antibody detection and transcriptomics analysis on 20 SARS-CoV-2 naïve individuals who received multiple doses of inactivated vaccine and 5 SARS-CoV-2 recovered individuals who received single dose of inactivated vaccine. Our research revealed the important role of many innate immune pathways after vaccination, identified a significant correlation with the third dose of booster vaccine and proteasome-related genes, and found that SARS-CoV-2 recovered individuals can produces a strong immune response to a single dose of inactivated vaccine. These results help us understand the reaction mechanism of the host’s molecular immune system to the inactivated vaccine, and provide a basis for the choice of vaccination strategy.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.11.05.467537: (What is this?)

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

    Table 1: Rigor

    EthicsIACUC: This study was approved by the Ethical Approval Committee of Shandong Center for Disease Control and Prevention.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Qualitative SARS-CoV-2 IgG detection: The IgG antibodies were detected using an indirect ELISA kit (Beijing Wantai Biological Pharmacy Enterprise Co, China)(15, 16) based on a recombinant nucleoprotein of SARS-CoV-2.
    IgG
    suggested: None
    A serum sample with an OD value ≥cut-off OD value was considered to be an anti-N IgG antibody positive.
    anti-N IgG
    suggested: None
    Experimental Models: Organisms/Strains
    SentencesResources
    The TOM obtained was then clustered by dissimilarity between genes, and we performed hierarchical clustering to identify modules, each containing at least 30 genes (minModuleSize=30).
    TOM
    suggested: None
    Software and Algorithms
    SentencesResources
    PPI network construction: The initial PPI network for the protein products of identified up and down regulated DEGs was constructed using the STRING Database(19) (STRING v11.5; https://string-db.org/), and then the network was visualized and analyzed with Cytoscape software(20).
    STRING
    suggested: (STRING, RRID:SCR_005223)
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)
    Pathway enrichment analysis: To be aware of the prospective functions of characteristic genes identified by the PPI network analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were identified using CluGO from Cytoscape software.
    KEGG
    suggested: (KEGG, RRID:SCR_012773)
    Weighted Gene Co-expression Network Analysis (WGCNA): We constructed the co-expression network through WGCNA package(21) in R software.
    Weighted Gene Co-expression Network Analysis
    suggested: (Weighted Gene Co-expression Network Analysis, RRID:SCR_003302)
    WGCNA
    suggested: (Weighted Gene Co-expression Network Analysis, RRID:SCR_003302)
    The genes in significant modules were analyzed using cytoHubba and GeneMANIA in Cytoscape software.
    cytoHubba
    suggested: (cytoHubba, RRID:SCR_017677)
    GeneMANIA
    suggested: (GeneMANIA, RRID:SCR_005709)

    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.

    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.

  2. Version published to 10.1101/2021.11.05.467537v1 on bioRxiv