Optimized Pseudotyping Conditions for the SARS-COV-2 Spike Glycoprotein

This article has been Reviewed by the following groups

Read the full article

Abstract

In work with pathogenic viruses, it is useful to have rapid quantitative tests for viral infectivity that can be performed without strict biocontainment restrictions. A common way of accomplishing this is to generate viral pseudoparticles that contain the surface glycoprotein from the pathogenic virus incorporated into a replication-defective viral particle that contains a sensitive reporter system. These pseudoparticles enter cells using the glycoprotein from the pathogenic virus, leading to a readout for infection. Conditions that block entry of the pathogenic virus, such as neutralizing antibodies, will also block entry of the viral pseudoparticles. However, viral glycoproteins often are not readily suited for generating pseudoparticles. Here, we describe a series of modifications that result in the production of relatively high-titer SARS-COV-2 pseudoparticles that are suitable for the detection of neutralizing antibodies from COVID-19 patients.

Article activity feed

  1. SciScore for 10.1101/2020.05.28.122671: (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.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Cells were rinsed with PBS one hour after infection and replace with complete media supplemented with 2 microliters of mouse hybridoma supernatant containing anti-VSV-G antibody I1 (Kerafast) to neutralize input virus.
    anti-VSV-G
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    The ACE2 cell lines were generated by transfecting 293FT cells with 500 ng MLV GagPol expression vector, 400 ng of retroviral transfer vector pQCXIP-ACE2 or pQCXIH-ACE2, and 100 ng of VSV-G expression vector.
    293FT
    suggested: ATCC Cat# PTA-5077, RRID:CVCL_6911)
    The TMPRSS2 cell line was generated by transfecting 293FT cells with 500 ng MLV GagPol expression vector, 400 ng of retroviral transfer vector pQCXIH-TMPRSS2, and 100 ng of VSV-G expression vector.
    TMPRSS2
    suggested: JCRB Cat# JCRB1818, RRID:CVCL_YQ48)
    Viral media was used to transduce 293FT, 293FT/ACE2, or 293/Cre-sensor/ACE2 cells were selected with hygromycin (200 micrograms/ml) beginning 2 days post-transduction and maintained until control treated cells were all eliminated.
    293/Cre-sensor/ACE2
    suggested: None

    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:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • 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.