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Published on: December 23, 2022
A Novel CRISPR/Cas13a sensor for highly sensitive detection of DENV based on AuPt/g-C3N4@GO and Ag@NU-1000
Xia Zhang1, Zhu Wang2, Zhen Guo3
1Department of Clinical Laboratory, Zhejiang Provincial People's Hospital Bijie Hospital (The First People's Hospital of Bijie), Bijie, Guizhou, 551700, China.
Abstract:
Dengue virus, an arthropod-borne pathogen, poses a significant global public health concern, necessitating the development of sensitive and rapid diagnostic assays. This paper introduces a novel biosensing platform designed for the ultrasensitive detection of dengue viral RNA. The platform integrates recombinase polymerase amplification, CRISPR/Cas13a-based recognition, and electrochemiluminescence resonance energy transfer (ECL-RET). The sensor employs a highly efficient luminescent emitter, which is a ternary composite of gold-platinum nanoparticles supported on graphitic carbon nitride and graphene oxide. A suitable energy acceptor, consisting of silver-decorated metal-organic frameworks, effectively quenches the emitter's signal via resonance energy transfer. Upon the introduction of target nucleic acids, RPA rapidly generates numerous amplicons. These amplicons are specifically recognized by the CRISPR/Cas13a system, which subsequently activates the collateral cleavage activity of Cas13a. This enzymatic activity cleaves a DNA linker that tethers the acceptor to the electrode surface, leading to the release of the acceptor and a subsequent restoration of the electrochemiluminescence intensity. The recovered signal exhibits a linear proportionality to the target concentration across a broad dynamic range, spanning from 0.1 fg/mL to 100 ng/mL. The detection limits for the four dengue serotypes range from 1.09 to 2.5 fg/mL. The assay demonstrates excellent specificity, showing no cross-reactivity with Zika, Japanese encephalitis, or West Nile viruses, and also exhibits good reproducibility. By combining isothermal amplification, specific CRISPR targeting, and a sensitive luminescence readout, this work presents a straightforward and robust method for the early diagnosis of dengue and for outbreak surveillance. Furthermore, this platform can be readily adapted for the detection of other pathogens of interest.
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