Monitoring the propagation of SARS CoV2 variants by tracking identified mutation in wastewater using specific RT-qPCR

  1. S Wurtzer
  2. P Waldman
  3. M Levert
  4. JM Mouchel
  5. O Gorgé
  6. M Boni
  7. Y Maday
  8. OBEPINE consortium
  9. V Marechal
  10. L Moulin

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Abstract

Since the end of 2020, the COVID-19 pandemic has experienced a major turning point with the appearance and rapid spread of new variants, causing a significant increase in the number of new cases requiring hospitalization. These so-called UK, South African or Brazilian variants are characterized by combinations of mutations which allow them to be distinguished from the variants which have circulated since the start of the epidemic. The impact of these variants on the functioning of healthcare systems requires monitoring the spread of these variants, which are more contagious, more lethal and may reinfect people who are already immune to a natural infection or to a vaccination. Monitoring the viral genome in wastewater has shown great value in early detection of the dynamics of virus spreading in populations.

The sequencing of viral genomes is used in humans, but its application and interpretation on wastewater matrices are much more complex due to the diversity of circulating strains. Also this study demonstrates the possibility of following certain mutations found in these new variants by targeted RT-qPCR. This study is the first carried out in France demonstrating the spreading dynamics of the 69-70 deletion in the Spike protein of SARS-CoV-2.

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  1. ScreenIT

    SciScore for 10.1101/2021.03.10.21253291: (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
    Design of RT-qPCR specific of the deletion 69-70: Based on sequences published in GISAID database, new couples of oligonucleotides were designed using AlleleID 9.0 software.
    AlleleID
    suggested: (AlleleID, RRID:SCR_014790)

    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.

  2. Version published to 10.1101/2021.03.10.21253291v1 on medRxiv