Leveraging mRNAs sequences to express SARS-CoV-2 antigens in vivo

  1. Chunxi Zeng
  2. Xucheng Hou
  3. Jingyue Yan
  4. Chengxiang Zhang
  5. Wenqing Li
  6. Weiyu Zhao
  7. Shi Du
  8. Yizhou Dong

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Abstract

SARS-CoV-2 has rapidly become a pandemic worldwide; therefore, an effective vaccine is urgently needed. Recently, messenger RNAs (mRNAs) have emerged as a promising platform for vaccination. Here, we systematically investigated the untranslated regions (UTRs) of mRNAs in order to enhance protein production. Through a comprehensive analysis of endogenous gene expression and de novo design of UTRs, we identified the optimal combination of 5’ and 3’ UTR, termed as NASAR, which was five to ten-fold more efficient than the tested endogenous UTRs. More importantly, NASAR mRNAs delivered by lipid-derived nanoparticles showed dramatic expression of potential SARS-CoV-2 antigens both in vitro and in vivo. These NASAR mRNAs merit further development as alternative SARS-CoV-2 vaccines.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.01.019877: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIACUC: Luciferase expression assay in vivo: All mouse studies were approved by the Institutional Animal Care and Use Committee at The Ohio State University and complied with local, state, and federal regulations.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    After blocking, primary rabbit anti-FLAG antibody (ab1162, abcam) at 1:1000 dilution was added, followed by incubation with HRP-linked anti-rabbit IgG (Cell Signaling, 7074).
    anti-FLAG
    suggested: (Abcam Cat# ab1162, RRID:AB_298215)
    anti-rabbit IgG (Cell Signaling, 7074
    suggested: (Cell Signaling Technology Cat# 7074, RRID:AB_2099233)
    Staining was conducted using primary rabbit anti-FLAG antibody (abcam, ab1162) at 1:200 dilution and FITC-linked secondary goat anti-rabbit polyclonal antibody (abcam, ab6717) at 1:1000 dilution.
    anti-rabbit
    suggested: (Abcam Cat# ab6717, RRID:AB_955238)
    Experimental Models: Cell Lines
    SentencesResources
    Firefly luciferase assay in vitro: Hep3B and 293T cells were cultured in Eagle’s Minimum Essential Medium (Corning) with 10% Fetal Bovine Serum (FBS) and Dulbecco’s Modified Eagle Medium (Corning) with 10% FBS, respectively.
    Hep3B
    suggested: None
    293T
    suggested: None
    Software and Algorithms
    SentencesResources
    After measurement of concentration by a NanoDrop 2000 Spectrophotometer (Thermo), all mRNAs were diluted to the desired concentration in 1× TE, aliquoted, and stored at -80°C for future use.
    Thermo
    suggested: (Thermo Xcalibur, RRID:SCR_014593)
    Data analysis: All data analysis was conducted in Prism 7 (GraphPad).
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    GraphPad
    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.
    • No funding statement was detected.
    • 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.

  2. Version published to 10.1101/2020.04.01.019877v1 on bioRxiv