A CRISPR-based SARS-CoV-2 diagnostic assay that is robust against viral evolution and RNA editing

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Abstract

Extensive testing is essential to break the transmission of the new coronavirus SARS-CoV-2, which causes the ongoing COVID-19 pandemic. Recently, CRISPR-based diagnostics have emerged as attractive alternatives to quantitative real-time PCR due to their faster turnaround time and their potential to be used in point-of-care testing scenarios. However, existing CRISPR-based assays for COVID-19 have not considered viral genome mutations and RNA editing in human cells. Here, we present the VaNGuard (Variant Nucleotide Guard) test that is not only specific and sensitive for SARS-CoV-2, but can also detect the virus when its genome or transcriptome has evolved or has been edited by deaminases in infected human cells. We show that an engineered AsCas12a enzyme is more tolerant of mismatches than wildtype LbCas12a and that multiplexed Cas12a targeting can overcome the presence of single nucleotide variations. Our assay can be completed in 30 minutes with a dipstick for a rapid point-of-care test.

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  1. SciScore for 10.1101/2020.07.03.185850: (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

    Software and Algorithms
    SentencesResources
    Subsequently, cells were harvested by centrifugation at 3,220g for 20min and resuspended in lysis buffer [50mM HEPES, 500mM NaCl, 2mM MgCl2, 20mM imidazole, 1% Triton X-100, 1mM DTT, 0.005mg/ml lysozyme (Vivantis), 1X Halt Protease Inhibitor Cocktail (Thermo Fisher Scientific)], followed by sonication at high power for 10 cycles of 30s ON/OFF (Bioruptor Plus; Diagenode).
    Thermo Fisher Scientific)]
    suggested: None
    gRNA design: Complete genomes of SARS-CoV-2 (accession MN908947.3), SARS-CoV (accession NC_004718.3), and MERS-CoV (accession NC_019843.3) were retrieved from NCBI (https://www.ncbi.nlm.nih.gov/) and aligned with MUSCLE (https://www.ebi.ac.uk/Tools/msa/muscle/) using default settings.
    https://www.ncbi.nlm.nih.gov/
    suggested: (GENSAT at NCBI - Gene Expression Nervous System Atlas, RRID:SCR_003923)
    MUSCLE
    suggested: (MUSCLE, RRID:SCR_011812)
    Potential targets were filtered after a specificity check on BLASTn (https://blast.ncbi.nlm.nih.gov/Blast.cgi) to remove non-specific candidates.
    BLASTn
    suggested: (BLASTN, RRID:SCR_001598)
    https://blast.ncbi.nlm.nih.gov/Blast.cgi
    suggested: (TBLASTX, RRID:SCR_011823)

    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: Please consider improving the rainbow (“jet”) colormap(s) used on page 30. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.


    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.