Genome Sequencing of Sewage Detects Regionally Prevalent SARS-CoV-2 Variants

  1. Alexander Crits-Christoph
  2. Rose S. Kantor
  3. Matthew R. Olm
  4. Oscar N. Whitney
  5. Basem Al-Shayeb
  6. Yue Clare Lou
  7. Avi Flamholz
  8. Lauren C. Kennedy
  9. Hannah Greenwald
  10. Adrian Hinkle
  11. Jonathan Hetzel
  12. Sara Spitzer
  13. Jeffery Koble
  14. Asako Tan
  15. Fred Hyde
  16. Gary Schroth
  17. Scott Kuersten
  18. Jillian F. Banfield
  19. Kara L. Nelson

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Abstract

Viral genome sequencing has guided our understanding of the spread and extent of genetic diversity of SARS-CoV-2 during the COVID-19 pandemic. SARS-CoV-2 viral genomes are usually sequenced from nasopharyngeal swabs of individual patients to track viral spread.

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  1. Version published to 10.1128/mbio.02703-20
  2. Rapid Reviews Infectious Diseases

    Blake Wiedenheft, Anna Nemudraia, Artem Nemudryy

    Review 2: "Genome sequencing of sewage detects regionally prevalent SARS-CoV-2 variants"

    This preprint offers a successful demonstration of WGS-based detection of emerging SARS-CoV-2 variants in wastewater samples. Reviewers deemed major claims reliable, but experimental methodology and justification should be described in further detail.

  3. Rapid Reviews Infectious Diseases

    Pei-ying Hong

    Review 1: "Genome sequencing of sewage detects regionally prevalent SARS-CoV-2 variants"

    This preprint offers a successful demonstration of WGS-based detection of emerging SARS-CoV-2 variants in wastewater samples. Reviewers deemed major claims reliable, but experimental methodology and justification should be described in further detail.

  4. Rapid Reviews Infectious Diseases

    Strength of evidence

    Reviewers: Pei-ying Hong (King Abdullah University of Science and Technology) | 📒📒📒◻️◻️
    Blake Wiedenheft (Montana State University Bozeman), Anna Nemudraia, Artem Nemudryy | 📘📘📘📘📘

  5. ScreenIT

    SciScore for 10.1101/2020.09.13.20193805: (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
    RT-qPCR and genome copy quantification: The number of viral genome copies in each sample was determined via qRT-PCR on an Applied Biosystems QuantStudio 3 Real-Time PCR System with the Thermo Fisher TaqPath 1-Step RT-qPCR Master Mix or TaqMan™ Fast Virus 1-Step Master Mix.
    Thermo Fisher TaqPath
    suggested: None
    Metatranscriptomic viral abundances: The abundances of viruses within wastewater were obtained by mapping reads with Bowtie 2 [35] to an index of all viral genomes downloaded from the RefSeq Database (Release 201).
    Bowtie
    suggested: (Bowtie, RRID:SCR_005476)
    RefSeq
    suggested: (RefSeq, RRID:SCR_003496)
    Duplicate reads were removed with the clumpify.sh dedup command from the BBTools software suite (Bushnell 2014).
    BBTools
    suggested: (Bestus Bioinformaticus Tools, RRID:SCR_016968)
    Consensus genomes from each sample were created using a custom Python script that required a minimum of 3 reads supporting each genomic position.
    Python
    suggested: (IPython, RRID:SCR_001658)
    Hypergeometric distributions were calculated with the stats.hypergeom function in scipy [37] to compare wastewater samples to all clinical data from each NextStrain “location” with at least 20 genomes deposited.
    scipy
    suggested: (SciPy, RRID:SCR_008058)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    While this illustrates the difficulty of detecting specific viruses in wastewater in unenriched sequencing datasets, larger sequencing efforts may overcome this limitation by sequencing more deeply. Other human viruses identified in the wastewater sequencing included Human bocaviruses 2c and 3 (

    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.

  6. Version published to 10.1101/2020.09.13.20193805v1 on medRxiv