期刊
SENSORS AND ACTUATORS B-CHEMICAL
卷 382, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.snb.2023.133546
关键词
Methicillin-resistant Staphylococcus aureus; mecA gene; Colorimetric; Recombinase polymerase amplification; CRISPR; Cas12a
Rapid and accurate identification of Methicillin-resistant Staphylococcus aureus (MRSA) is crucial to prevent the spread of infections and guide effective treatment. In this study, a rapid, specific, and ultrasensitive colorimetric assay based on recombinase polymerase amplification (RPA) and magnetic nanoparticles (MNPs) assisted CRISPR/Cas12a was developed for the detection of the mecA gene in MRSA bacteria. This method allows for the rapid and accurate identification of MRSA within 2 hours through the observable color change.
Methicillin resistant Staphylococcus aureus (MRSA), as one of drug-resistant bacteria, severely affects public health. Rapid and accurate identification of MRSA is essential to prevent the spread of infections and guide effective treatment. Current methods for MRSA detection suffer from the disadvantages of time consuming or sophisticated instrument requirements, which hinder their practical application in resource-limited areas as well as for on-site detection. Herein, we develop a rapid, specific, ultrasensitive colorimetric assay based on the recombinase polymerase amplification (RPA) and magnetic nanoparticles (MNPs) assisted CRISPR/Cas12a for the detection of the mecA gene in MRSA bacteria. This method for detecting mecA gene has a good linear correlation from 1 to 1 * 10 boolean AND 6 aM with a low detection limit of 0.2 aM. Furthermore, this method has been successfully applied for detecting mecA gene from the patients infected with MRSA and the results are in good consistence with the culture-based and qPCR-based methods. The developed method can realize the rapid and accurate identification of MRSA within 2 h via the color change observable by naked eye, which is expected to have great prospects in future practical point-of-care testing (POCT) applications for drug-resistant bacteria identification.
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