期刊
SYNTHETIC AND SYSTEMS BIOTECHNOLOGY
卷 6, 期 4, 页码 283-291出版社
KEAI PUBLISHING LTD
DOI: 10.1016/j.synbio.2021.09.007
关键词
CRISPR; Cas12a; Aptamer; Antigen detection; SARS-CoV-2; PCR-Free amplification; Synergistic sensing
资金
- National Key R&D program of China [2020YFA0907800]
- National Natural Science Foundation of China [31922002, 31720103901, 31772242, 31870040]
- 111 Project [B18022]
- Fundamental Research Funds for the Central Universities [22221818014]
- Youth Innovation Promotion Association CAS [Y202027]
- Open Project Funding of the State Key Laboratory of Bioreactor Engineering
The study introduces a new antigen detection method that combines CRISPR/Cas12a and aptamers, providing ultra-sensitive, fast, and stable detection capabilities. The method was able to detect the SARS-CoV-2 antigen nucleocapsid protein at the single virus level in saliva or serum samples within 20 minutes, showing promise for general applications in CRISPR/Cas12a-aptamer-based detection.
Antigen detection provides particularly valuable information for medical diagnoses; however, the current detection methods are less sensitive and accurate than nucleic acid analysis. The combination of CRISPR/Cas12a and aptamers provides a new detection paradigm, but sensitive sensing and stable amplification in antigen detection remain challenging. Here, we present a PCR-free multiple trigger dsDNA tandem-based signal amplification strategy and a de novo designed dual aptamer synergistic sensing strategy. Integration of these two strategies endowed the CRISPR/Cas12a and aptamer-based method with ultra-sensitive, fast, and stable antigen detection. In a demonstration of this method, the limit of detection was at the single virus level (0.17 fM, approximately two copies/mu L) in SARS-CoV-2 antigen nucleocapsid protein analysis of saliva or serum samples. The entire procedure required only 20 min. Given our system's simplicity and modular setup, we believe that it could be adapted reasonably easily for general applications in CRISPR/Cas12a-aptamer-based detection.
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