Rapid Increase of SARS-CoV-2 Variant B.1.1.7 Detected in Sewage Samples from England between October 2020 and January 2021

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Abstract

The recent appearance and growth of new SARS-CoV-2 variants represent a major challenge for the control of the COVID-19 pandemic. These variants of concern contain mutations affecting antigenicity, which raises concerns on their possible impact on human immune response to the virus and vaccine efficacy against them.

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  1. SciScore for 10.1101/2021.03.03.21252867: (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
    These libraries were pooled in equimolar concentrations and sequenced with 250 bp paired-end reads on MiSeq v2 (500 cycles) kits (Illumina, USA).
    MiSeq
    suggested: (A5-miseq, RRID:SCR_012148)
    Initial demultiplexing was performed on-board by the MiSeq Reporter software.
    MiSeq Reporter
    suggested: None
    FASTQ sequencing data was adapter and quality trimmed by Cutadapt v2.10 [29] for a minimum Phred score of Q30, minimal read length of 75 bp, and 0 ambiguous nucleotides.
    Cutadapt
    suggested: (cutadapt, RRID:SCR_011841)
    Phred
    suggested: (Phred, RRID:SCR_001017)
    Single nucleotide polymorphisms (SNPs) were identified using Geneious 10.2.3 default settings.
    Geneious
    suggested: (Geneious, RRID:SCR_010519)
    The COVID-19 Genomics (COG-UK) Consortium / Mutation Explorer with sequencing data generated by 28th February 2021 (http://sars2.cvr.gla.ac.uk/cog-uk/) was also used to examine the presence and proportion of selected viral amino acid variations in clinical samples.
    Mutation Explorer
    suggested: None
    Statistical analysis: Statistical analysis and graphical representation of sequence frequency data were conducted using GraphPad Prism version 8.1.2 software.
    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.