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Photo-switchable CRISPR electrochemical system enables de-interferential biosensing signal output
Junhong Zhao1, Jinghang He1, Huanyu Du1
1State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai, 200433, China; Laboratory of Molecular Materials and Devices, Fudan University, Shanghai, 200433, China.
Biosensors & Bioelectronics
|July 29, 2026
Summary
This study introduces a novel photo-switchable CRISPR/Cas12a electrochemical (PSCE) system. The PSCE system precisely detects non-small cell lung cancer (NSCLC) gene mutations, minimizing false signals for reliable bioanalysis.
Area of Science:
- Biomedical Engineering
- Molecular Diagnostics
- CRISPR Technology
Background:
- CRISPR-based electrochemical biosensors often suffer from signal crosstalk, leading to false positives.
- A controllable switching function is needed to improve the reliability and accuracy of these biosensors.
Purpose of the Study:
- To develop a photo-switchable CRISPR/Cas12a electrochemical (PSCE) system for precise gene mutation detection.
- To mitigate signal crosstalk and enhance the accuracy of electrochemical biosensing.
Main Methods:
- Incorporation of a photocleavable (PC) linker and a light-responsive strategy into the CRISPR/Cas12a system.
- Decoupling nucleic acid amplification (NAA) from signal transduction for a photo-switchable response.
- Utilizing light irradiation to activate Cas12a activity and separate signal readout from sample pretreatment.
Main Results:
- The PSCE system demonstrated de-interference electrochemical signals, achieving high sensitivity and accuracy for non-small cell lung cancer (NSCLC) gene mutation detection.
- The system suppressed intrinsic amplification-derived signal crosstalk, resulting in an ultralow limit of detection (LoD).
- Achieved 98.1% sensitivity, 92.7% specificity, and 98.9% overall accuracy with 67 clinical samples.
Conclusions:
- The developed PSCE system offers a reliable and accurate method for bioanalysis by addressing signal crosstalk.
- The system shows significant potential for clinical diagnosis of mutation-associated diseases, including applications in wearable electronics and machine learning analysis.
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