Sensitive and multiplexed RNA detection with Cas13 droplets and kinetic barcoding

  1. Sungmin Son
  2. Amy Lyden
  3. Jeffrey Shu
  4. Stephanie I. Stephens
  5. Parinaz Fozouni
  6. Gavin J. Knott
  7. Dylan C. J. Smock
  8. Tina Y. Liu
  9. Daniela Boehm
  10. Camille Simoneau
  11. G. Renuka Kumar
  12. Jennifer A. Doudna
  13. Melanie Ott
  14. Daniel A. Fletcher

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Abstract

Rapid and sensitive quantification of RNA is critical for detecting infectious diseases and identifying disease biomarkers. Recent direct detection assays based on CRISPR-Cas13a 1–4 avoid reverse transcription and DNA amplification required of gold-standard PCR assays 5 , but these assays have not yet achieved the sensitivity of PCR and are not easily multiplexed to detect multiple viruses or variants. Here we show that Cas13a acting on single target RNAs loaded into droplets exhibits stochastic nuclease activity that can be used to enable sensitive, rapid, and multiplexed virus quantification. Using SARS-CoV-2 RNA as the target and combinations of CRISPR RNA (crRNA) that recognize different parts of the viral genome, we demonstrate that reactions confined to small volumes can rapidly achieve PCR-level sensitivity. By tracking nuclease activity within individual droplets over time, we find that Cas13a exhibits rich kinetic behavior that depends on both the target RNA and crRNA. We demonstrate that these kinetic signatures can be harnessed to differentiate between different human coronavirus species as well as SARS-CoV-2 variants within a single droplet. The combination of high sensitivity, short reaction times, and multiplexing makes this droplet-based Cas13a assay with kinetic barcoding a promising strategy for direct RNA identification and quantification.

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    SciScore for 10.1101/2021.08.02.21261509: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Isolate USA-WA1/2020 of SARS-CoV-2 (NR-52281 BEI Resources) and CA427 (B.1.427, received from CA DPH) were propagated in Vero CCL-81 cells.
    Vero CCL-81
    suggested: None
    Isolate Amsterdam I of HCoV-NL-63 (NR-470, BEI Resources) was propagated in Huh7.5.1-ACE2 cells (all virus cultures were performed in a Biosafety Level 3 laboratory).
    Huh7.5.1-ACE2
    suggested: None
    Software and Algorithms
    SentencesResources
    We first performed binary classification of trajectories based on the Supported Vector Machine (SVM) in MATLAB.
    MATLAB
    suggested: (MATLAB, RRID:SCR_001622)

    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.
    • No protocol registration statement was detected.

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

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  2. Version published to 10.1101/2021.08.02.21261509v1 on medRxiv