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Ligand-Responsive Artificial Protein-Protein Communication for Field-Deployable Cell-Free Biosensing
Ke Wang1, Siqian Liu1, Shuqi Zhou2
1State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan Provincial Key Laboratory of Biomacromolecular Chemical Biology, Hunan University, Changsha, 410082, P. R. China.
Angewandte Chemie (International Ed. in English)
|November 18, 2024
Summary
We developed a rapid biosensing system using artificial protein-protein communication (LIRAC) that detects contaminants in minutes, not hours. This technology enhances field analysis for environmental and health monitoring.
Area of Science:
- Biotechnology
- Synthetic Biology
- Biosensing
Background:
- Cell-free biosensing systems rely on natural protein-protein interactions (PPIs) for transcription/translation (TXTL).
- TXTL-based systems face limitations including slow response times (hours) and complex in vitro compositions, hindering field applications.
Purpose of the Study:
- To develop a novel, rapid, and simplified cell-free biosensing system.
- To create a de novo-designed ligand-responsive artificial protein-protein communication (LIRAC) system.
Main Methods:
- Designed a chimeric DNA adaptor to link transcription factors (TFs) with CRISPR/Cas enzymes.
- Engineered specific binding affinities to enable rapid signal transduction.
- Utilized LIRAC to bypass RNA/protein biosynthesis steps inherent in TXTL systems.
Main Results:
- Achieved a significant reduction in reaction time from hours to 10 minutes.
- Demonstrated improved sensitivity and a tunable dynamic range for contaminant detection.
- Showcased LIRAC's versatility in detecting diverse contaminants like antibiotics and heavy metals.
- Enabled intelligent multi-contaminant detection using tristate logic.
Conclusions:
- LIRAC offers a rapid, simplified, and versatile platform for cell-free biosensing.
- The system is effective for field analysis of environmental and personal care products.
- LIRAC holds significant potential for advancing environmental and health monitoring applications.
