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Multi-enzyme Screening Using a High-throughput Genetic Enzyme Screening System
Published on: August 8, 2016
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Efficient laboratory evolution of computationally designed enzymes with low starting activities using
Richard Obexer1, Moritz Pott1, Cathleen Zeymer1
1Laboratory of Organic Chemistry, ETH Zurich, 8093 Zurich, Switzerland.
Protein Engineering, Design & Selection : PEDS
|August 21, 2016
Summary
Microfluidic-based fluorescence-activated droplet sorting (FADS) rapidly optimizes computationally designed enzymes. This high-throughput screening method achieves significant catalytic improvements in a single round, accelerating enzyme evolution.
Area of Science:
- Biocatalysis
- Enzyme Engineering
- Synthetic Biology
Background:
- Computational enzyme design enables de novo biocatalysts with novel functions.
- Directed evolution is crucial for optimizing enzyme activity, but traditional methods are laborious.
- Achieving natural enzyme-level catalytic rates often requires extensive laboratory evolution.
Purpose of the Study:
- To demonstrate the efficacy of microfluidic-based screening using fluorescence-activated droplet sorting (FADS) for optimizing computationally designed enzymes.
- To showcase FADS's ability to efficiently enhance enzymes with low initial catalytic activity.
- To accelerate the directed evolution process for biocatalysts.
Main Methods:
- Utilized fluorescence-activated droplet sorting (FADS) for high-throughput microfluidic screening.
- Applied FADS to reoptimize the designed retro-aldolase RA95.0.
- Employed simultaneous randomization of up to five residues in large mutant libraries.
Main Results:
- FADS detected enzyme activities as low as kcat/Km = 0.5 M⁻¹s⁻¹.
- Achieved up to an 80-fold increase in catalytic activity within a single evolution round.
- Identified alternative active site configurations with enhanced efficiency and opposite enantioselectivity.
Conclusions:
- FADS is a powerful tool for the rapid optimization of designed enzymes with low initial activity.
- Ultra-high throughput screening with FADS enables direct identification of beneficial mutation combinations.
- This approach significantly accelerates enzyme evolution, enabling exploration of diverse catalytic solutions.
