Specific Detection of SARS-CoV-2 Variants B.1.1.7 (Alpha) and B.1.617.2 (Delta) Using a One-Step Quantitative PCR Assay

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

The new assays described herein enable rapid, straightforward, and cost-effective detection of severe acute respiratory syndrome coronavirus 2 (SC-2) with immediate classification of the examined sample as Alpha, Delta, non-Alpha, or non-Delta variant. This is highly important for two main reasons: (i) it provides the scientific and medical community with a novel diagnostic tool to rapidly detect and classify any SC-2 sample of interest as Alpha, Delta, or none and can be applied to both clinical and environmental samples, and (ii) it demonstrates how to respond to the emergence of new variants of concern by developing a variant-specific assay.

Article activity feed

  1. SciScore for 10.1101/2021.10.11.21264831: (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.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Cell culture: In order to culture positive SC-2 samples, the medium from the selected collection tubes was filtered using a 0.22μM filter (https://www.merckmillipore.com/) and used for inoculation of Vero E6 cells.
    Vero E6
    suggested: RRID:CVCL_XD71)
    Recombinant DNA
    SentencesResources
    Primer pair T7-21494 Fwd + Cov19 22475 were used for the Spike region amplification, and primer pair pT7 27945 Fwd + 28525 Rev were used for the Orf8 region amplification.
    pT7
    suggested: None
    Software and Algorithms
    SentencesResources
    Corresponding primers and probes that detect only the mutated sequences were designed for each region, and examined In silico for secondary structure formation, specificity and compatibility with qPCR assay using the Geneious software (https://www.geneious.com/) and using the NCBI BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi).
    Geneious
    suggested: (Geneious, RRID:SCR_010519)
    BLAST
    suggested: (BLASTX, RRID:SCR_001653)
    https://blast.ncbi.nlm.nih.gov/Blast.cgi
    suggested: (TBLASTX, RRID:SCR_011823)
    Whole genome sequencing: COVID-seq kit was used for library preparation as per manufacturer’s instructions (Illumina, https://www.illumina.com).
    https://www.illumina.com
    suggested: (Illumina, RRID:SCR_010233)
    Library validation and mean fragment size was determined by tapestation 4200 via DNA HS D1000 kit (Agilent, https://www.agilent.com/).
    https://www.agilent.com/
    suggested: (Agilent Technologies, RRID:SCR_013575)

    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.