Field-deployable viral diagnostics using CRISPR-Cas13

Cameron Myhrvold; Catherine A. Freije; Jonathan S. Gootenberg; Omar O. Abudayyeh; Hayden C. Metsky; Ann F. Durbin; Max J. Kellner; Amanda L. Tan; Lauren M. Paul; Leda A. Parham; Kimberly F. Garcia; Kayla G. Barnes; Bridget Chak; Adriano Mondini; Mauricio L. Nogueira; Sharon Isern; Scott F. Michael; Ivette Lorenzana; Nathan L. Yozwiak; Bronwyn L. MacInnis; Irene Bosch; Lee Gehrke; Feng Zhang; Pardis C. Sabeti

doi:10.1126/science.aas8836

Field-deployable viral diagnostics using CRISPR-Cas13

Cameron Myhrvold, Catherine A. Freije, Jonathan S. Gootenberg, Omar O. Abudayyeh, Hayden C. Metsky, Ann F. Durbin, Max J. Kellner, Amanda L. Tan, Lauren M. Paul, Leda A. Parham, Kimberly F. Garcia, Kayla G. Barnes, Bridget Chak, Adriano Mondini, Mauricio L. Nogueira, Sharon Isern, Scott F. Michael, Ivette Lorenzana, Nathan L. Yozwiak, Bronwyn L. MacInnisIrene Bosch, Lee Gehrke, Feng Zhang, Pardis C. Sabeti

Research output: Contribution to journal › Article › peer-review

1148 Scopus citations

Abstract

Mitigating global infectious disease requires diagnostic tools that are sensitive, specific, and rapidly field deployable. In this study, we demonstrate that the Cas13-based SHERLOCK (specific high-sensitivity enzymatic reporter unlocking) platform can detect Zika virus (ZIKV) and dengue virus (DENV) in patient samples at concentrations as low as 1 copy per microliter. We developed HUDSON (heating unextracted diagnostic samples to obliterate nucleases), a protocol that pairs with SHERLOCK for viral detection directly from bodily fluids, enabling instrument-free DENV detection directly from patient samples in <2 hours. We further demonstrate that SHERLOCK can distinguish the four DENV serotypes, as well as region-specific strains of ZIKV from the 2015–2016 pandemic. Finally, we report the rapid (<1 week) design and testing of instrument-free assays to detect clinically relevant viral single-nucleotide polymorphisms.

Original language	English (US)
Pages (from-to)	444-448
Number of pages	5
Journal	Science
Volume	360
Issue number	6387
DOIs	https://doi.org/10.1126/science.aas8836
State	Published - Apr 27 2018
Externally published	Yes

All Science Journal Classification (ASJC) codes

General

Access to Document

10.1126/science.aas8836

Cite this

Myhrvold, C., Freije, C. A., Gootenberg, J. S., Abudayyeh, O. O., Metsky, H. C., Durbin, A. F., Kellner, M. J., Tan, A. L., Paul, L. M., Parham, L. A., Garcia, K. F., Barnes, K. G., Chak, B., Mondini, A., Nogueira, M. L., Isern, S., Michael, S. F., Lorenzana, I., Yozwiak, N. L., ... Sabeti, P. C. (2018). Field-deployable viral diagnostics using CRISPR-Cas13. Science, 360(6387), 444-448. https://doi.org/10.1126/science.aas8836

@article{deab30a09fa9444fbf0490bd68a421f7,

title = "Field-deployable viral diagnostics using CRISPR-Cas13",

abstract = "Mitigating global infectious disease requires diagnostic tools that are sensitive, specific, and rapidly field deployable. In this study, we demonstrate that the Cas13-based SHERLOCK (specific high-sensitivity enzymatic reporter unlocking) platform can detect Zika virus (ZIKV) and dengue virus (DENV) in patient samples at concentrations as low as 1 copy per microliter. We developed HUDSON (heating unextracted diagnostic samples to obliterate nucleases), a protocol that pairs with SHERLOCK for viral detection directly from bodily fluids, enabling instrument-free DENV detection directly from patient samples in <2 hours. We further demonstrate that SHERLOCK can distinguish the four DENV serotypes, as well as region-specific strains of ZIKV from the 2015–2016 pandemic. Finally, we report the rapid (<1 week) design and testing of instrument-free assays to detect clinically relevant viral single-nucleotide polymorphisms.",

author = "Cameron Myhrvold and Freije, \{Catherine A.\} and Gootenberg, \{Jonathan S.\} and Abudayyeh, \{Omar O.\} and Metsky, \{Hayden C.\} and Durbin, \{Ann F.\} and Kellner, \{Max J.\} and Tan, \{Amanda L.\} and Paul, \{Lauren M.\} and Parham, \{Leda A.\} and Garcia, \{Kimberly F.\} and Barnes, \{Kayla G.\} and Bridget Chak and Adriano Mondini and Nogueira, \{Mauricio L.\} and Sharon Isern and Michael, \{Scott F.\} and Ivette Lorenzana and Yozwiak, \{Nathan L.\} and MacInnis, \{Bronwyn L.\} and Irene Bosch and Lee Gehrke and Feng Zhang and Sabeti, \{Pardis C.\}",

note = "Publisher Copyright: 2017 {\textcopyright} The Authors.",

year = "2018",

month = apr,

day = "27",

doi = "10.1126/science.aas8836",

language = "English (US)",

volume = "360",

pages = "444--448",

journal = "Science",

issn = "0036-8075",

publisher = "American Association for the Advancement of Science",

number = "6387",

}

Myhrvold, C, Freije, CA, Gootenberg, JS, Abudayyeh, OO, Metsky, HC, Durbin, AF, Kellner, MJ, Tan, AL, Paul, LM, Parham, LA, Garcia, KF, Barnes, KG, Chak, B, Mondini, A, Nogueira, ML, Isern, S, Michael, SF, Lorenzana, I, Yozwiak, NL, MacInnis, BL, Bosch, I, Gehrke, L, Zhang, F & Sabeti, PC 2018, 'Field-deployable viral diagnostics using CRISPR-Cas13', Science, vol. 360, no. 6387, pp. 444-448. https://doi.org/10.1126/science.aas8836

TY - JOUR

T1 - Field-deployable viral diagnostics using CRISPR-Cas13

AU - Myhrvold, Cameron

AU - Freije, Catherine A.

AU - Gootenberg, Jonathan S.

AU - Abudayyeh, Omar O.

AU - Metsky, Hayden C.

AU - Durbin, Ann F.

AU - Kellner, Max J.

AU - Tan, Amanda L.

AU - Paul, Lauren M.

AU - Parham, Leda A.

AU - Garcia, Kimberly F.

AU - Barnes, Kayla G.

AU - Chak, Bridget

AU - Mondini, Adriano

AU - Nogueira, Mauricio L.

AU - Isern, Sharon

AU - Michael, Scott F.

AU - Lorenzana, Ivette

AU - Yozwiak, Nathan L.

AU - MacInnis, Bronwyn L.

AU - Bosch, Irene

AU - Gehrke, Lee

AU - Zhang, Feng

AU - Sabeti, Pardis C.

PY - 2018/4/27

Y1 - 2018/4/27

N2 - Mitigating global infectious disease requires diagnostic tools that are sensitive, specific, and rapidly field deployable. In this study, we demonstrate that the Cas13-based SHERLOCK (specific high-sensitivity enzymatic reporter unlocking) platform can detect Zika virus (ZIKV) and dengue virus (DENV) in patient samples at concentrations as low as 1 copy per microliter. We developed HUDSON (heating unextracted diagnostic samples to obliterate nucleases), a protocol that pairs with SHERLOCK for viral detection directly from bodily fluids, enabling instrument-free DENV detection directly from patient samples in <2 hours. We further demonstrate that SHERLOCK can distinguish the four DENV serotypes, as well as region-specific strains of ZIKV from the 2015–2016 pandemic. Finally, we report the rapid (<1 week) design and testing of instrument-free assays to detect clinically relevant viral single-nucleotide polymorphisms.

AB - Mitigating global infectious disease requires diagnostic tools that are sensitive, specific, and rapidly field deployable. In this study, we demonstrate that the Cas13-based SHERLOCK (specific high-sensitivity enzymatic reporter unlocking) platform can detect Zika virus (ZIKV) and dengue virus (DENV) in patient samples at concentrations as low as 1 copy per microliter. We developed HUDSON (heating unextracted diagnostic samples to obliterate nucleases), a protocol that pairs with SHERLOCK for viral detection directly from bodily fluids, enabling instrument-free DENV detection directly from patient samples in <2 hours. We further demonstrate that SHERLOCK can distinguish the four DENV serotypes, as well as region-specific strains of ZIKV from the 2015–2016 pandemic. Finally, we report the rapid (<1 week) design and testing of instrument-free assays to detect clinically relevant viral single-nucleotide polymorphisms.

UR - https://www.scopus.com/pages/publications/85045993900

UR - https://www.scopus.com/inward/citedby.url?scp=85045993900&partnerID=8YFLogxK

U2 - 10.1126/science.aas8836

DO - 10.1126/science.aas8836

M3 - Article

C2 - 29700266

AN - SCOPUS:85045993900

SN - 0036-8075

VL - 360

SP - 444

EP - 448

JO - Science

JF - Science

IS - 6387

ER -

Field-deployable viral diagnostics using CRISPR-Cas13

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this