A Study of the Detection of SARS-CoV-2 by the Use of Electrochemiluminescent Biosensor Based on Asymmetric Polymerase Chain Reaction Amplification Strategy.
IEEE Sens J
; 23(8): 8094-8100, 2023 Apr.
Article
in English
| MEDLINE | ID: covidwho-2297186
ABSTRACT
A new and reliable method has been constructed for detecting severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) open reading frames 1ab (ORF1ab) gene via highly sensitive electrochemiluminescence (ECL) biosensor technology based on highly efficient asymmetric polymerase chain reaction (asymmetric PCR) amplification strategy. This method uses magnetic particles coupled with biotin-labeled one complementary nucleic acid sequence of the SARS-CoV-2 ORF1ab gene as the magnetic capture probes, and [Formula see text]-labeled amino-modified another complementary nucleic acid sequence as the luminescent probes, and then a detection model of magnetic capture probes-asymmetric PCR amplification nucleic acid products-[Formula see text]-labeled luminescent probes is formed, which combines the advantages of highly efficient asymmetric PCR amplification strategy and highly sensitive ECL biosensor technology, enhancing the method sensitivity of detecting the SARS-CoV-2 ORF1ab gene. The method enables the rapid and sensitive detection of the ORF1ab gene and has a linear range of 1-[Formula see text] copies/[Formula see text], a regression equation of [Formula see text] = [Formula see text] + 2919.301 ([Formula see text] = 0.9983, [Formula see text] = 7), and a limit of detection (LOD) of 1 copy/[Formula see text]. In summary, it can meet the analytical requirements for simulated saliva and urine samples and has the benefits of easy operation, reasonable reproducibility, high sensitivity, and anti-interference abilities, which can provide a reference for developing efficient field detection methods for SARS-CoV-2.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Diagnostic study
Language:
English
Journal:
IEEE Sens J
Year:
2023
Document Type:
Article
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