The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Nucleic Acid Detection Using CRISPR/Cas Biosensing Technologies
Abstract
Abstract For infectious diseases, rapid and accurate identification of the pathogen is critical for effective management and treatment, but diagnosis remains challenging, particularly in resource-limited areas. Methods that accurately detect pathogen nucleic acids can provide robust, accurate, rapid, and ultrasensitive technologies for point-of-care diagnosis of pathogens, and thus yield information that is invaluable for disease management and treatment. Several technologies, mostly PCR-based, have been employed for pathogen detection; however, these require expensive reagents and equipment, and skilled personnel. CRISPR/Cas systems have been used for genome editing, based on their ability to accurately recognize and cleave specific DNA and RNA sequences. Moreover, following recognition of the target sequence, certain CRISPR/Cas systems including orthologues of Cas13, Cas12a, and Cas14 exhibit collateral nonspecific catalytic activities that can be employed for nucleic acid detection, for example by degradation of a labeled nucleic acid to produce a fluorescent signal. CRISPR/Cas systems are amenable to multiplexing, thereby enabling a single diagnostic test to identify multiple targets down to attomolar (10–18 mol/L) concentrations of target molecules. Developing devices that couple CRISPR/Cas with lateral flow systems may allow inexpensive, accurate, highly sensitive, in-field deployable diagnostics. These sensors have myriad applications, from human health to agriculture. In this review, we discuss the recent advances in the field of CRISPR-based biosensing technologies and highlight insights of their potential use in a myriad of applications.
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Metadata
- Authors
- Aman, R., Mahas, A., & Mahfouz, M.
- Venue
- ACS Synthetic Biology
- Publisher
- American Chemical Society (ACS)
- Published
- 2020-03-11
- Volume
- 9
- Issue
- 6
- Pages
- 1226-1233
- ISSN
- 2161-5063 (ISSN-L)
- OpenAlex
- W3012071400
- Cited by
- 409
- References
- 47
- FWCI
- 15.85
- Type
- journal article
- Language
- en
- Open access
- closed
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