VarLOCK: sequencing-independent, rapid detection of SARS-CoV-2 variants of concern for point-of-care testing, qPCR pipelines and national wastewater surveillance

  1. Xinsheng Nan
  2. Patrick Hardinge
  3. Sven Hoehn
  4. Shrinivas Nivrutti Dighe
  5. John Ukeri
  6. Darius F. Pease
  7. Joshua Griffin
  8. Jessica I. Warrington
  9. Zack Saud
  10. Emma Hottinger
  11. Gordon Webster
  12. Davey Jones
  13. Peter Kille
  14. Andrew Weightman
  15. Richard Stanton
  16. Oliver K. Castell
  17. James A. H. Murray
  18. Tomasz P. Jurkowski

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Abstract

The COVID-19 pandemic demonstrated the need for rapid molecular diagnostics. Vaccination programs can provide protection and facilitate the opening of society, but newly emergent and existing viral variants capable of evading the immune system endanger their efficacy. Effective surveillance for Variants of Concern (VOC) is therefore important. Rapid and specific molecular diagnostics can provide speed and coverage advantages compared to genomic sequencing alone, benefitting the public health response and facilitating VOC containment. Here we expand the recently developed SARS-CoV-2 CRISPR-Cas detection technology (SHERLOCK) to provide rapid and sensitive discrimination of SARS-CoV-2 VOCs that can be used at point of care, implemented in the pipelines of small or large testing facilities, and even determine the proportion of VOCs in pooled population-level wastewater samples. This technology complements sequencing efforts to allow facile and rapid identification of individuals infected with VOCs to help break infection chains. We show the optimisation of our VarLOCK assays (Variant-specific SHERLOCK) for multiple specific mutations in the S gene of SARS-CoV-2 and validation with samples from the Cardiff University Testing Service. We also show the applicability of VarLOCK to national wastewater surveillance of SARS-CoV-2 variants and the rapid adaptability of the technique for new and emerging VOCs.

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  1. Version published to 10.1038/s41598-023-47289-0
  2. ScreenIT

    SciScore for 10.1101/2022.01.06.21268555: (What is this?)

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

    Table 1: Rigor

    EthicsField Sample Permit: Collection and preparation of wastewater samples for VarLOCK assays: Untreated wastewater samples (crude influent) were collected between November 2020 and November 2021 from Dŵr
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Recombinant DNA
    SentencesResources
    Purification of AapCas12b: pAG001 His6-TwinStrep-SUMO-AapCas12b was a gift from Omar Abudayyeh and Jonathan Gootenberg (Addgene plasmid # 153162) [4].
    pAG001
    suggested: RRID:Addgene_153162)
    Software and Algorithms
    SentencesResources
    VarLOCK assay with PCR or LAMP products: Synthetic DNA templates harbouring the wt or mutant sequences for PCR or LAMP amplification were synthesised by IDT or by Twist Bioscience.
    LAMP
    suggested: (LAMP, RRID:SCR_001740)
    LAMP primers were designed using the NEB LAMP primer design tool https://lamp.neb.com/#!/ or Primer Explorer v5.0 https://primerexplorer.jp/e/
    Primer Explorer
    suggested: None
    Whole genome sequencing was performed utilising NGS library preparation by RT-PCR using the Nimagen protocol, essentially as described (https://www.protocols.io/view/wastewater-sequencing-using-the-easyseq-rc-pcr-sar-bx6dpra6).
    NGS
    suggested: (ANGSD, RRID:SCR_021865)

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.
    • Thank you for including a protocol registration statement.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2022.01.06.21268555v1 on medRxiv