Programmable kinetic barcoding for multiplexed RNA detection with Cas13a

Rapid identification of viral infections and specific variants in patient samples requires a simple and multiplexed RNA detection method that does not rely on DNA sequencing. Although recent direct detection assays based on CRISPR-Cas13a offer rapid RNA detection by avoiding reverse transcription and DNA amplification required of gold-standard PCR assays, these assays are not easily multiplexed to detect multiple viruses or variants without dividing the sample into separate reactions. Here we show that Cas13a acting on single-target RNAs exhibits variable nuclease activity that depends on the interaction between the target RNA and crRNA. To exploit this feature for multiplexed detection, we devised a crRNA modification strategy that enables programmable tuning of Cas13a's nuclease enzymatic rates. Using a droplet-based Cas13a assay, we demonstrate that kinetic signatures can be harnessed to differentiate among respiratory viruses and SARS-CoV-2 variants in contrived and clinical samples. This kinetic barcoding strategy can be extended to additional RNA targets through simple modification of crRNAs.

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Publication Details

Journal
Nature Biomedical Engineering
Published
2026-03-31
DOI
https://doi.org/10.1038/s41551-026-01642-6
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

Programmable kinetic barcoding for multiplexed RNA detection with Cas13a

Gavin J. Knott, Daniela Boehm, Jeffrey Shu, Carlos F. Ng et al.
Nature Biomedical Engineering
CRISPR and Genetic Engineering
article

Programmable kinetic barcoding for multiplexed RNA detection with Cas13a

Gavin J. Knott, Daniela Boehm, Jeffrey Shu, Carlos F. Ng, Tina Y. Liu, Stephanie I. Stephens, Parinaz Fozouni, Mélanie Ott, Dylan C. J. Smock, Amy Lyden, Camille R. Simoneau, Daniel A. Fletcher, Andres Dextre, Sungmin Son, G. Ravindra Kumar, Jennifer A. Doudna
article en

Abstract

Rapid identification of viral infections and specific variants in patient samples requires a simple and multiplexed RNA detection method that does not rely on DNA sequencing. Although recent direct detection assays based on CRISPR-Cas13a offer rapid RNA detection by avoiding reverse transcription and DNA amplification required of gold-standard PCR assays, these assays are not easily multiplexed to detect multiple viruses or variants without dividing the sample into separate reactions. Here we show that Cas13a acting on single-target RNAs exhibits variable nuclease activity that depends on the interaction between the target RNA and crRNA. To exploit this feature for multiplexed detection, we devised a crRNA modification strategy that enables programmable tuning of Cas13a's nuclease enzymatic rates. Using a droplet-based Cas13a assay, we demonstrate that kinetic signatures can be harnessed to differentiate among respiratory viruses and SARS-CoV-2 variants in contrived and clinical samples. This kinetic barcoding strategy can be extended to additional RNA targets through simple modification of crRNAs.

Nature Biomedical Engineering
Rutgers, The State University of New Jersey (US), QB3 (US), Gladstone Institutes (US), Howard Hughes Medical Institute (US), Berkeley College (US), Lawrence Berkeley National Laboratory (US), Korea Advanced Institute of Science and Technology (KR), University of California, San Francisco (US), Discovery Institute (US), Innovative Genomics Institute (US), Chan Zuckerberg Initiative (United States) (US), University of California, Berkeley (US)
Howard Hughes Medical Institute, Blum Center for Developing Economies, University of California Berkeley, Gladstone Institutes, James B. Pendleton Charitable Trust, Innovative Genomics Institute, Korea Advanced Institute of Science and Technology, Snow Medical, National Institutes of Health, Centers for Disease Control and Prevention, National Health and Medical Research Council, National Institute of Allergy and Infectious Diseases
Openalex Percentile: Top 35%
CRISPR and Genetic Engineering
DOIOpen Access PDFOpenAlex
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