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Electrowetting-based Digital Microfluidics Platform for Automated Enzyme-linked Immunosorbent Assay
Published on: February 23, 2020
Droplet Microfluidic Device for Chemoenzymatic Sensing
Anton S Yakimov1, Ivan A Denisov1,2, Anton S Bukatin3,4
1Laboratory of Physical and Chemical Technologies for the Development of Hard-to-Recover Hydrocarbon Reserves, Siberian Federal University, 660041 Krasnoyarsk, Russia.
This study introduces a microfluidic system for rapid water pollution detection using bioluminescent enzymatic probes. The system enables continuous monitoring and early warning for pollutants like copper sulfate.
Area of Science:
- Analytical Chemistry
- Biotechnology
- Environmental Science
Background:
- Enzymatic probes offer rapid detection of water pollutants.
- Pollutant presence often decreases the catalytic light-emitting activity of these probes.
- Continuous monitoring systems are crucial for early-warning water pollution detection.
Purpose of the Study:
- To develop a microfluidic system for continuous chemoenzymatic biosensing.
- To utilize droplet microfluidics for enhanced reagent mixing and detection.
- To establish a basis for early-warning online water pollution monitoring systems.
Main Methods:
- A microfluidic chip was designed to generate water-in-oil emulsion droplets (0.1 μL) at a frequency of 12 drops/min.
- The system incorporated bacterial bioluminescent enzymes (luciferase and NAD(P)H:FMN-oxidoreductase) and necessary substrates.
- Bioluminescent signals from individual droplets were measured using a photomultiplier tube (signal-to-noise ratio up to 3000/1).
Main Results:
- The system successfully generated and manipulated emulsion droplets for chemoenzymatic reactions.
- The bioluminescent signal intensity correlated with copper sulfate concentration, with a detection limit of 5 μM.
- Bioluminescent enzymatic reactions were effectively performed in droplet reactors within dispersed streams.
Conclusions:
- Droplet microfluidics enables efficient chemoenzymatic sensing for water quality monitoring.
- The developed system demonstrates potential for real-time, online water pollution detection.
- This technology can form the foundation for advanced early-warning water pollution systems.
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