A Simple Reverse Transcriptase PCR Melting-Temperature Assay To Rapidly Screen for Widely Circulating SARS-CoV-2 Variants

  1. Padmapriya Banada
  2. Raquel Green
  3. Sukalyani Banik
  4. Abby Chopoorian
  5. Deanna Streck
  6. Robert Jones
  7. Soumitesh Chakravorty
  8. David Alland

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Abstract

The increased transmission of SARS-CoV-2 variants of concern (VOC), which originated in the United Kingdom (B.1.1.7/alpha), South Africa (B1.351/beta), Brazil (P.1/gamma), the United States (B.1.427/429 or epsilon), and India (B.1.617.2/delta), requires a vigorous public health response, including real-time strain surveillance on a global scale. Although genome sequencing is the gold standard for identifying these VOCs, it is time-consuming and expensive.

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  1. Version published to 10.1128/jcm.00845-21
  2. Version published to 10.1101/2021.03.05.21252709v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.03.05.21252709: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethical considerations: The use of de-identified clinical samples from confirmed COVID-19 positive and negative patients for PCR testing and sequencing was approved by the Rutgers Institutional Review Board under protocol numbers 20170001218 and 2020001541.
    RandomizationWe randomly selected 20 COVID-19 positive samples of unknown genotype and a RT-PCR cycle threshold (Ct) <40 with either Xpert Xpress SARS-CoV-2 or Xpert Xpert CoV-2/Flu/RSV test, with 6 having been banked between October 2020 through December 31, 2020 and 14 having been banked from January 1, 2021 – February 2021.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    A 250-nucleotide region around the N501Y (A23063T) position in the reference strain (GenBank accession number MN908947) was selected and used to identify the corresponding regions in the GISAID dataset using BLAST (21).
    BLAST
    suggested: (BLASTX, RRID:SCR_001653)
    These matching sequences were condensed into a set of unique sequences and aligned using a multiple sequence alignment program, MAFFT (22)
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Candidate amplification primers and probes were identified on the basis of sequence conservation and predicted Tm using the algorithm of SantaLucia (23) and final set of primers were designed with the help of the Primer3 program (24)
    Primer3
    suggested: (Primer3, RRID:SCR_003139)
    The sequencing chromatograms and the sequences were analyzed using Ugene (ver 37) comparing against the known WT and MT sequences using MegAlign Pro software (DNAStar, ver16).
    MegAlign Pro
    suggested: None
    Statistical analysis: Standard statistical analyses (average, standard deviation) and graphing were performed using Microsoft excel (ver 2102) and GraphPad Prism 8.4.3 for Windows.
    Microsoft excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    GraphPad Prism
    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 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.

    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.

  4. Version published to 10.1101/2021.03.05.21252709v1 on medRxiv