A chemiluminescent sensor based on CRISPR-HCR technology for the hypersensitive detection of Mycobacterium tuberculosis

Abstract

Tuberculosis is a highly infectious bacterial disease caused by Mycobacterium tuberculosis. The spread of this agent has caused serious health problems worldwide, and the rapid and accurate detection of M. tuberculosis is essential for controlling the spread of infection and for preventing the emergence of multidrug-resistant strains. In this study, the trans cleavage ability of CRISPR-Cas12a against single-stranded DNA was combined with hybridization chain reaction and chemiluminescent signal to establish an imaging sensor for the hypersensitive detection of M. tuberculosis DNA. We observed linear relationships between the concentration of M. tuberculosis DNA and the output signal over the ranges of 10 to 200 pM and 200 to 800 pM DNA. The equations of the standard curves were y = 56.08x + 3303, with R2 = 0.9916 for the lower range and y = 15.69x + 10 685, with R2 = 0.9929 for the higher range. The limit of detection was as low as 0.83 pM for genomic DNA, and a plasmid containing an M. tuberculosis-specific sequence was detected at 1 copy per μL. A detection accuracy of 100% was achieved in the analysis of DNA isolated from sputum of hospitalized tuberculosis patients. The sensitivity and specificity of the proposed sensor is combined with a long shelf-life and a low cost of materials. This study introduces a new method for tuberculosis detection and broadens the application of CRISPR-Cas12a-based sensors in clinical diagnosis.

Graphical abstract: A chemiluminescent sensor based on CRISPR-HCR technology for the hypersensitive detection of Mycobacterium tuberculosis

Article information

Article type
Paper
Submitted
14 Aug 2024
Accepted
25 Sep 2024
First published
25 Sep 2024

Anal. Methods, 2024, Advance Article

A chemiluminescent sensor based on CRISPR-HCR technology for the hypersensitive detection of Mycobacterium tuberculosis

Y. Qiao, X. Wang, X. Kang, Y. Song, J. Zhang and Q. Han, Anal. Methods, 2024, Advance Article , DOI: 10.1039/D4AY01517G

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