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Rapid and accurate species identification for ecological studies and monitoring using CRISPR‐based SHERLOCK
Author(s) -
Baerwald Melinda R.,
Goodbla Alisha M.,
Nagarajan Raman P.,
Gootenberg Jonathan S.,
Abudayyeh Omar O.,
Zhang Feng,
Schreier Andrea D.
Publication year - 2020
Publication title -
molecular ecology resources
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.96
H-Index - 136
eISSN - 1755-0998
pISSN - 1755-098X
DOI - 10.1111/1755-0998.13186
Subject(s) - biology , identification (biology) , crispr , computational biology , ecology , evolutionary biology , data science , computer science , genetics , gene
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.