RT-qPCR detection of SARS-CoV-2 mutations S 69–70 del, S N501Y and N D3L associated with variants of concern in Canadian wastewater samples

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Abstract

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  1. SciScore for 10.1101/2021.05.20.21257536: (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.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    (ThermoFisher Scientific, Waltham, MA) and Primer3 v4.1.0 (https://bioinfo.ut.ee/primer3/).
    Primer3
    suggested: (Primer3, RRID:SCR_003139)

    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: We detected the following sentences addressing limitations in the study:
    There are many limitations to detection of SARS-CoV-2 variants in wastewater. Wastewater is a highly complex and variable matrix containing numerous potential inhibitors and organisms in addition to multiple SARS-CoV-2 variants increasing the necessity for highly specific assays. Furthermore, SARS-CoV-2 viral RNA is present in low concentrations in wastewater, necessitating the development of assays with low limits of detection. Presence of high concentrations of the alternate allele was shown to increase LODs of these assays, however detectable ratios as high as 1:500 are highly unlikely due to the low concentration of SARS-CoV-2 in Canadian wastewater (95% <250 cp/mL N1). Of the three loci for which assays were designed, the SN501Y assay was the most robust, with no loss of sensitivity in the presence of competing template and the highest sensitivities and specificities. In addition, the SN501Y mutation is present within multiple SARS-CoV-2 lineages (B.1.1.7, B.1.351, P.1. and others). In a region with limited resources, the SN501Y assay alone would be effective for detecting any of these variants. However, consistent with other SARS-CoV-2 variant detection assays (Graber et al. (2021); Yaniv et al. (2021)), these assays cannot replace the use of the CDC N1 assay for quantitative detection of SARS-CoV-2 due to ~2-3 Ct later detection. Finally, while lineage specific strategies for RT-qPCR based detection of VoC in wastewater can be informative to public health, the rapid em...

    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.