Rapid and accurate species identification for ecological studies and monitoring using CRISPR-based SHERLOCK.

Cas13a DNA extraction-free Osmerid smelt field-based diagnostic genetic species identification noninvasive sampling

Journal

Molecular ecology resources
ISSN: 1755-0998
Titre abrégé: Mol Ecol Resour
Pays: England
ID NLM: 101465604

Informations de publication

Date de publication:
Jul 2020
Historique:
received: 11 12 2019
revised: 17 03 2020
accepted: 23 04 2020
pubmed: 13 5 2020
medline: 5 6 2021
entrez: 13 5 2020
Statut: ppublish

Résumé

One of the most fundamental aspects of ecological research and monitoring is accurate species identification, but cryptic speciation and observer error can confound phenotype-based identification. The CRISPR-Cas toolkit has facilitated remarkable advances in many scientific disciplines, but the fields of ecology and conservation biology have yet to fully embrace this powerful technology. The recently developed CRISPR-Cas13a platform SHERLOCK (Specific High-sensitivity Enzymatic Reporter unLOCKing) enables highly accurate taxonomic identification and has all the characteristics needed to transition to ecological and environmental disciplines. Here we conducted a series of "proof of principle" experiments to characterize SHERLOCK's ability to accurately, sensitively and rapidly distinguish three fish species of management interest co-occurring in the San Francisco Estuary that are easily misidentified in the field. We improved SHERLOCK's ease of field deployment by combining the previously demonstrated rapid isothermal amplification and CRISPR genetic identification with a minimally invasive and extraction-free DNA collection protocol, as well as the option of instrument-free lateral flow detection. This approach opens the door for redefining how, where and by whom genetic identifications occur in the future.

Identifiants

pubmed: 32396992
doi: 10.1111/1755-0998.13186
pmc: PMC7497203
doi:

Substances chimiques

DNA 9007-49-2

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

961-970

Subventions

Organisme : Department of Water Resources
ID : 4600012328

Informations de copyright

© 2020 The Authors. Molecular Ecology Resources published by John Wiley & Sons Ltd.

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Auteurs

Melinda R Baerwald (MR)

California Department of Water Resources, Sacramento, CA, USA.

Alisha M Goodbla (AM)

Department of Animal Science, University of California Davis, Davis, CA, USA.

Raman P Nagarajan (RP)

Department of Animal Science, University of California Davis, Davis, CA, USA.

Jonathan S Gootenberg (JS)

Broad Institute of the Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
McGovern Institute for Brain Research, MIT, Cambridge, MA, USA.
Department of Brain and Cognitive Science, MIT, Cambridge, MA, USA.
Department of Biological Engineering, MIT, Cambridge, MA, USA.
Department of Systems Biology, Harvard University, Boston, MA, USA.

Omar O Abudayyeh (OO)

Broad Institute of the Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
McGovern Institute for Brain Research, MIT, Cambridge, MA, USA.
Department of Brain and Cognitive Science, MIT, Cambridge, MA, USA.
Department of Biological Engineering, MIT, Cambridge, MA, USA.
Department of Health Sciences and Technology, MIT, Cambridge, MA, USA.

Feng Zhang (F)

Broad Institute of the Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
McGovern Institute for Brain Research, MIT, Cambridge, MA, USA.
Department of Brain and Cognitive Science, MIT, Cambridge, MA, USA.
Department of Biological Engineering, MIT, Cambridge, MA, USA.

Andrea D Schreier (AD)

Department of Animal Science, University of California Davis, Davis, CA, USA.

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Classifications MeSH