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A Scalable, Easy-to-Deploy, Protocol for Cas13-Based Detection of SARS-CoV-2 Genetic Material

View ORCID ProfileJennifer N. Rauch, View ORCID ProfileEric Valois, Sabrina C. Solley, Friederike Braig, Ryan S. Lach, View ORCID ProfileMorgane Audouard, View ORCID ProfileJose Carlos Ponce-Rojas, Michael S. Costello, Naomi J. Baxter, View ORCID ProfileKenneth S. Kosik, View ORCID ProfileCarolina Arias, View ORCID ProfileDiego Acosta-Alvear, View ORCID ProfileMaxwell Z. Wilson
doi: https://doi.org/10.1101/2020.04.20.052159
Jennifer N. Rauch
1University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara
2Neuroscience Research Institute, University of California, Santa Barbara
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  • ORCID record for Jennifer N. Rauch
Eric Valois
1University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara
2Neuroscience Research Institute, University of California, Santa Barbara
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Sabrina C. Solley
1University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara
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Friederike Braig
1University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara
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Ryan S. Lach
1University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara
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Morgane Audouard
1University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara
2Neuroscience Research Institute, University of California, Santa Barbara
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Jose Carlos Ponce-Rojas
1University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara
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Michael S. Costello
1University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara
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Naomi J. Baxter
1University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara
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Kenneth S. Kosik
1University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara
2Neuroscience Research Institute, University of California, Santa Barbara
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Carolina Arias
1University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara
2Neuroscience Research Institute, University of California, Santa Barbara
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Diego Acosta-Alvear
1University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara
2Neuroscience Research Institute, University of California, Santa Barbara
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Maxwell Z. Wilson
1University of California Santa Barbara, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara
2Neuroscience Research Institute, University of California, Santa Barbara
3Center for BioEngineering, University of California, Santa Barbara
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  • For correspondence: mzw@ucsb.edu
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Abstract

The COVID-19 pandemic has created massive demand for widespread, distributed tools for detecting SARS-CoV-2 genetic material. The hurdles to scalable testing include reagent and instrument accessibility, availability of highly-trained personnel, and large upfront investment. Here we showcase an orthogonal pipeline we call CREST (Cas13-based, Rugged, Equitable, Scalable Testing) that addresses some of these hurdles. Specifically, CREST pairs commonplace and reliable biochemical methods (PCR) with low-cost instrumentation, without sacrificing detection sensitivity. By taking advantage of simple fluorescence visualizers, CREST allows for a binary interpretation of results. CREST may provide a point- of-care solution to increase the distribution of COVID-19 surveillance.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ↵a kosik{at}lifesci.ucsb.edu

  • ↵b carolinaarias{at}ucsb.edu

  • ↵c daa{at}lifesci.ucsb.edu

  • ↵d mzw{at}ucsb.edu

  • ↵† These authors are co-senior authors

  • In our updated version of this manuscript we deployed our testing protocol, CREST, on de-identified patient samples and compared the results to standard RT-qPCR testing results of the same samples. In addition, we showed that CREST could be coupled with a column-free RNA extraction method called PEARL, that we have also recently published.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted July 24, 2020.
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A Scalable, Easy-to-Deploy, Protocol for Cas13-Based Detection of SARS-CoV-2 Genetic Material
Jennifer N. Rauch, Eric Valois, Sabrina C. Solley, Friederike Braig, Ryan S. Lach, Morgane Audouard, Jose Carlos Ponce-Rojas, Michael S. Costello, Naomi J. Baxter, Kenneth S. Kosik, Carolina Arias, Diego Acosta-Alvear, Maxwell Z. Wilson
bioRxiv 2020.04.20.052159; doi: https://doi.org/10.1101/2020.04.20.052159
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A Scalable, Easy-to-Deploy, Protocol for Cas13-Based Detection of SARS-CoV-2 Genetic Material
Jennifer N. Rauch, Eric Valois, Sabrina C. Solley, Friederike Braig, Ryan S. Lach, Morgane Audouard, Jose Carlos Ponce-Rojas, Michael S. Costello, Naomi J. Baxter, Kenneth S. Kosik, Carolina Arias, Diego Acosta-Alvear, Maxwell Z. Wilson
bioRxiv 2020.04.20.052159; doi: https://doi.org/10.1101/2020.04.20.052159

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