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

Area of Science:

• Environmental Science
• Analytical Chemistry
• Biotechnology

Background:

• Microplastics pose significant risks to human health and ecosystems.
• Existing analytical methods often lack simplicity, speed, sensitivity, or field-deployability.
• There is an urgent need for advanced detection strategies for microplastics.

Purpose of the Study:

• To develop a simple, rapid, sensitive, and field-deployable analytical method for microplastic detection.
• To create a clustered regularly interspaced short palindromic repeat (CRISPR)-based colorimetric aptasensor for poly(vinyl chloride) (PVC) and polystyrene (PS) microplastics.
• To enable real-time, visual quantification of microplastics in diverse environmental matrices.

Main Methods:

• A CRISPR-Cas12a dual system was integrated with aptamers specific to PVC and PS.
• A Fe3O4@Au-DNA magnetic complex was utilized for microplastic capture, separation, and detection.
• A hemin-aptamer DNAzyme colorimetric reaction coupled with smartphone imaging and a deep-learning model was employed for signal transduction and quantification.

Main Results:

• The aptasensor demonstrated high selectivity for PVC and PS microplastics.
• A broad dynamic range from 10^-2 to 10^3 μg/mL was achieved.
• Smartphone-based detection yielded limits of detection as low as 3.1 ng/mL for PVC and 3.7 ng/mL for PS.

Conclusions:

• The developed CRISPR-based aptasensor provides a rapid, effective, and visual strategy for microplastic extraction and real-time quantification.
• This platform significantly enhances detection performance and stability, enabling field-deployable monitoring.
• The approach offers a promising solution for addressing the challenges of microplastic pollution analysis.