Clustered Regularly Interspaced Short Palindromic Repeat-Based Colorimetric Aptasensor Combined with Smartphone...

Microplastics present significant risks to human health and ecosystem stability, creating an urgent need for analytical methods that are simple, rapid, sensitive, and field-deployable. Herein, we report a clustered regularly interspaced short palindromic repeat (CRISPR)-based colorimetric aptasensor for the detection of poly(vinyl chloride) (PVC) and polystyrene (PS) microplastics. This platform leverages the high specificity of PVC and PS aptamers integrated into a Fe₃O₄@Au-DNA magnetic complex, which facilitates capture, separation, and detection. Upon microplastic binding, a competitive reaction releases an activator DNA, initiating a dual CRISPR-Cas12a system for signal amplification. The activated Cas12a trans-cleavage activity is then linked to a hemin-aptamer DNAzyme colorimetric reaction, converting the signal into a visible color change. This colorimetric output is captured by smartphone imaging and processed in real time. Furthermore, a deep-learning-based regression model was developed to enable the quantitative prediction of PVC and PS micro/nanoplastics in diverse environmental matrices. The method exhibited high selectivity and a broad dynamic range from 10^-2 to 10³ μg/mL. In smartphone detection mode, the limits of detection for PVC and PS reached 3.1 ng/mL and 3.7 ng/mL, respectively. This approach significantly enhances detection performance and stability, enabling visual monitoring of microplastics in complex real samples. Collectively, this work provides a rapid and effective strategy for the extraction and real-time quantification of small molecules.