COVID-19 Variant Detection with a High-Fidelity CRISPR-Cas12 Enzyme

  1. Clare L. Fasching
  2. Venice Servellita
  3. Bridget McKay
  4. Vaishnavi Nagesh
  5. James P. Broughton
  6. Alicia Sotomayor-Gonzalez
  7. Baolin Wang
  8. Noah Brazer
  9. Kevin Reyes
  10. Jessica Streithorst
  11. Rachel N. Deraney
  12. Emma Stanfield
  13. Carley G. Hendriks
  14. Steve Miller
  15. Jesus Ching
  16. Janice S. Chen
  17. Charles Y. Chiu

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Abstract

Laboratory tests for the accurate and rapid identification of SARS-CoV-2 variants can potentially guide the treatment of COVID-19 patients and inform infection control and public health surveillance efforts. Here we present the development and validation of a rapid COVID-19 variant DETECTR ® assay incorporating loop-mediated isothermal amplification (LAMP) followed by CRISPR-Cas12 based identification of single nucleotide polymorphism (SNP) mutations in the SARS-CoV-2 spike (S) gene. This assay targets the L452R, E484K/Q/A, and N501Y mutations that are associated with nearly all circulating viral lineages and identifies the two circulating variants of concern, Delta and Omicron. In a comparison of three different Cas12 enzymes, only the newly identified enzyme CasDx1 was able to accurately identify all targeted SNP mutations. An analysis pipeline for CRISPR-based SNP identification from 139 clinical samples yielded an overall SNP concordance of 98% and agreement with SARS-CoV-2 lineage classification of 138/139 compared to viral whole-genome sequencing. We also showed that detection of the single E484A mutation was necessary and sufficient to accurately identify Omicron from other major circulating variants in patient samples. These findings demonstrate the utility of CRISPR-based DETECTR ® as a faster and simpler diagnostic than sequencing for SARS-CoV-2 variant identification in clinical and public health laboratories.

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  1. Version published to 10.1101/2021.11.29.21267041v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2021.11.29.21267041: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Remnant sample biobanking was performed with a waiver of consent and according to no-subject contact study protocols approved by the UCSF Institutional Review Board (protocol numbers 10-01116 and 11-05519)
    IRB: Remnant sample biobanking was performed with a waiver of consent and according to no-subject contact study protocols approved by the UCSF Institutional Review Board (protocol numbers 10-01116 and 11-05519)
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Briefly, sequencing reads generated by Illumina sequencers (NextSeq 550 or NovaSeq 6000) were demultiplexed and converted to FASTQ files using bcl2fastq (v2.20.0.422).
    bcl2fastq
    suggested: (bcl2fastq , RRID:SCR_015058)
    Raw FASTQ files were first screened for SARS-CoV-2 sequences using BLASTn (BLAST+ package 2.9.0) alignment against the Wuhan-Hu-1 SARS-CoV-2 viral reference genome (NC_045512)
    BLASTn
    suggested: (BLASTN, RRID:SCR_001598)
    BLAST+
    suggested: (Japan Bioinformatics, RRID:SCR_012250)
    Reads containing adapters, the ARTIC primer sequences, and low-quality reads were filtered using BBDuk (version 38.87) and then mapped to the NC_045512 reference genome using BBMap (version 38.87).
    BBMap
    suggested: (BBmap, RRID:SCR_016965)
    Discordant sample retesting: Eleven samples were re-extracted as described above for the NP/OP swab samples and evaluated by viral WGS as described above.
    WGS
    suggested: None
    The time point is of importance here to rule out those samples that would amplify closer to the endpoint, signifying the LAMP intermediates to be the majority contributors of the rise in the signal and not the actual sample itself.
    LAMP
    suggested: (LAMP, RRID:SCR_001740)

    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: We detected the following sentences addressing limitations in the study:
    Although CRISPR-based diagnostic assays have been previously demonstrated for the detection of SARS-CoV-2 variants, these studies have limitations in coverage of circulating lineages and in the extent of clinical sample evaluation. For example, the miSHERLOCK variant assay uses LbCas12a (NEB) to detect N501Y, E484K and Y144Del covering eight lineages (WA-1, Alpha, Beta, Gamma, Eta, Iota, Mu and Zeta) and was tested only on contrived samples (RNA spiked into human saliva) (20). Additionally, the SHINEv2 assay uses LwaCas13a to detect 69/70Del, K417N/T, L452R and 156/157Del + R158G covering eight lineages (WA-1, Alpha, Beta, Gamma, Delta, Epsilon, Kappa and Mu) and was tested with only the 69/70Del gRNAs on 20 Alpha-positive NP clinical samples (37). In comparison, the DETECTR® assay presented here uses CasDx1 to detect N501Y, E484K and L452R covering 11 lineages (WA-1, Alpha, Beta, Gamma, Delta, Epsilon, Eta, Iota, Kappa, Mu and Zeta) and 91 clinical samples representing seven out of the 11 lineages were tested with successful detection of all 7. Some limitations of our study are as follows. First, as previously mentioned, the DETECTR® assay currently detects only three SNPs, which may not provide enough resolution to identify a specific lineage. Second, we observed variable performance of the assay in SNP discrimination, with more potential overlap in the calls between WT and MUT for the 452 position than for the other two sites, increasing the risk of misidentification. Thir...

    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.

    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 10.1101/2021.11.29.21267041v1 on medRxiv