Rapid Base-Specific Calling of SARS-CoV-2 Variants of Concern Using Combined RT-PCR Melting Curve Screening and SIRPH Technology

  1. Sascha Tierling
  2. Kathrin Kattler
  3. Markus Vogelgesang
  4. Thorsten Pfuhl
  5. Stefan Lohse
  6. Christina Lo Porto
  7. Beate Schmitt
  8. Seiwert Nastasja
  9. Abdulrahman Salhab
  10. Sigrun Smola
  11. Jörn Walter

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Abstract

Background

The emergence of novel variants of concern of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) demands fast and reliable detection of such variants in local populations.

Methods

Here we present a cost-efficient and fast workflow combining a prescreening of SARS-CoV-2-positive samples using reverse transcription polymerase chain reaction melting curve analysis with multiplexed IP-RP-HPLC-based single nucleotide primer extensions.

Results

The entire workflow from positive SARS-CoV-2 testing to base-specific identification of variants requires about 24 hours.

Conclusions

We applied the sensitive method to monitor local variant of concern outbreaks in SARS-CoV-2-positive samples collected in a confined region of Germany.

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  1. Version published to 10.1093/ofid/ofab364
  2. ScreenIT

    SciScore for 10.1101/2021.03.15.21253586: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved by the local ethics committee of the Saarland University Medical Center at Saarland Ärztekammer.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    NGS data processing: Viral genome data were processed using CoVpipe (https://gitlab.com/RKIBioinformaticsPipelines/ncov_minipipe).
    CoVpipe
    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 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.

  3. Version published to 10.1101/2021.03.15.21253586v1 on medRxiv