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CRISPR-associated Plasmonic Colorimeter Method (Ca-PCM): A real-time RGB detection system for gold
Hernán Alarcón-Iniesta1, Guillermo de Arana1, María López-Valls1
1Fundación IMDEA Nanociencia, Madrid, Spain.
Analytica Chimica Acta
|January 20, 2025
Summary
A new CRISPR-associated Plasmonic Colorimeter Method (Ca-PCM) uses gold nanoparticles and real-time RGB analysis for sensitive RNA detection. This cost-effective biosensor approach enables quantitative molecular detection, even in resource-limited settings.
Area of Science:
- Nanotechnology
- Molecular Biology
- Biosensing
Background:
- Genetic sequence detection is crucial for diagnostics and pathogen identification.
- Plasmonic nanoparticle biosensors offer sensitive, label-free detection but often lack kinetic information.
- Developing cost-effective and accessible molecular detection methods is essential.
Purpose of the Study:
- To develop a novel biosensing method for quantitative molecular detection.
- To integrate CRISPR-Cas13a RNA recognition with plasmonic nanoparticle aggregation.
- To enable real-time, dose-dependent analysis of target molecules.
Main Methods:
- Developed the CRISPR-associated Plasmonic Colorimeter Method (Ca-PCM).
- Utilized CRISPR LwaCas13a for RNA target recognition and gold nanoparticle (AuNP) aggregation.
- Employed real-time Red-Green-Blue (RGB) colorimetric analysis with silicon photodiodes.
- Implemented an algorithm for signal analysis and dose-dependent correlation.
Main Results:
- Ca-PCM successfully combined CRISPR, AuNP aggregation, and real-time RGB analysis.
- The system achieved dose-dependent molecular detection of RNA targets.
- Real-time spectral patterns correlated with target concentration.
- Integration with isothermal amplification enabled detection in clinical samples.
Conclusions:
- RGB analysis with continuous temporal measurements offers a novel way to characterize AuNP biosensors.
- This method enables quantitative, dose-dependent target detection.
- The Ca-PCM approach is simple, cost-effective, and suitable for low-resource clinical environments.
