Ultrahigh-Throughput Directed Evolution of a Metal-Free α/β-Hydrolase with a Cys-His-Asp Triad into an Efficient Phosphotriesterase

Direct detection of acetylcholinesterase by Fe(HCOO)2.6(OH)0.3. H2O nanosheets with oxidase-like activity on a smartphone platform

Monitoring acetylcholinesterase (AChE) is crucial in clinical diagnosis and drug screening. Traditional methods for detecting AChE usually require the addition of intermediates like acetylthiocholine, which complicates the detection process and introduces interference risks. Herein, we develop a direct colorimetric assay based on alkaline iron formate nanosheets (Fe(HCOO)2.6(OH)0.3·H2O NSs, Fef NSs) for the detection of AChE without any intermediates. The as-prepared Fef NSs exhibit oxidase-like activity, catalyzing the generation of O2·-, 1O2 and ·OH, which leads to a color change from colorless to blue when exposed to 3,3',5,5'-tetramethylbenzidine. AChE directly inhibits the oxidase-like activity of Fef NSs, resulting in a hindered color reaction, enabling the detection of AChE. The biosensor has a linear detection range of 0.1-30 mU/mL, with a minimum detection limit of 0.0083 mU/mL (S/N = 3), representing a 100-fold improvement in detection sensitivity over the traditional Ellman's method. Satisfactory results were obtained when analyzing real AChE samples. Attractively, a method for the quantitative detection of AChE by a smartphone is established based on the Fef NSs. This method enables instant acquisition of AChE concentrations, achieving real-time visualized detection.

Selection of a promiscuous minimalist cAMP phosphodiesterase from a library of de novo designed proteins

The ability of unevolved amino acid sequences to become biological catalysts was key to the emergence of life on Earth. However, billions of years of evolution separate complex modern enzymes from their simpler early ancestors. To probe how unevolved sequences can develop new functions, we use ultrahigh-throughput droplet microfluidics to screen for phosphoesterase activity amidst a library of more than one million sequences based on a de novo designed 4-helix bundle. Characterization of hits revealed that acquisition of function involved a large jump in sequence space enriching for truncations that removed >40% of the protein chain. Biophysical characterization of a catalytically active truncated protein revealed that it dimerizes into an α-helical structure, with the gain of function accompanied by increased structural dynamics. The identified phosphodiesterase is a manganese-dependent metalloenzyme that hydrolyses a range of phosphodiesters. It is most active towards cyclic AMP, with a rate acceleration of ~109 and a catalytic proficiency of >1014 M-1, comparable to larger enzymes shaped by billions of years of evolution.

Ultrahigh Throughput Evolution of Tryptophan Synthase in Droplets via an Aptamer Sensor

Tryptophan synthase catalyzes the synthesis of a wide array of noncanonical amino acids and is an attractive target for directed evolution. Droplet microfluidics offers an ultrahigh throughput approach to directed evolution (up to 107 experiments per day), enabling the search for biocatalysts in wider regions of sequence space with reagent consumption minimized to the picoliter volume (per library member). While the majority of screening campaigns in this format on record relied on an optically active reaction product, a new assay is needed for tryptophan synthase. Tryptophan is not fluorogenic in the visible light spectrum and thus falls outside the scope of conventional droplet microfluidic readouts, which are incompatible with UV light detection at high throughput. Here, we engineer a tryptophan DNA aptamer into a sensor to quantitatively report on tryptophan production in droplets. The utility of the sensor was validated by identifying five-fold improved tryptophan synthases from ∼100,000 protein variants. More generally, this work establishes the use of DNA-aptamer sensors with a fluorogenic read-out in widening the scope of droplet microfluidic evolution.

Engineering Enzymes for Environmental Sustainability

The development and implementation of sustainable catalytic technologies is key to delivering our net-zero targets. Here we review how engineered enzymes, with a focus on those developed using directed evolution, can be deployed to improve the sustainability of numerous processes and help to conserve our environment. Efficient and robust biocatalysts have been engineered to capture carbon dioxide (CO2) and have been embedded into new efficient metabolic CO2 fixation pathways. Enzymes have been refined for bioremediation, enhancing their ability to degrade toxic and harmful pollutants. Biocatalytic recycling is gaining momentum, with engineered cutinases and PETases developed for the depolymerization of the abundant plastic, polyethylene terephthalate (PET). Finally, biocatalytic approaches for accessing petroleum-based feedstocks and chemicals are expanding, using optimized enzymes to convert plant biomass into biofuels or other high value products. Through these examples, we hope to illustrate how enzyme engineering and biocatalysis can contribute to the development of cleaner and more efficient chemical industry.

Engineering Enzymes for Environmental Sustainability

The development and implementation of sustainable catalytic technologies is key to delivering our net-zero targets. Here we review how engineered enzymes, with a focus on those developed using directed evolution, can be deployed to improve the sustainability of numerous processes and help to conserve our environment. Efficient and robust biocatalysts have been engineered to capture carbon dioxide (CO2 ) and have been embedded into new efficient metabolic CO2 fixation pathways. Enzymes have been refined for bioremediation, enhancing their ability to degrade toxic and harmful pollutants. Biocatalytic recycling is gaining momentum, with engineered cutinases and PETases developed for the depolymerization of the abundant plastic, polyethylene terephthalate (PET). Finally, biocatalytic approaches for accessing petroleum-based feedstocks and chemicals are expanding, using optimized enzymes to convert plant biomass into biofuels or other high value products. Through these examples, we hope to illustrate how enzyme engineering and biocatalysis can contribute to the development of cleaner and more efficient chemical industry.

Analysing Megasynthetase Mutants at High Throughput Using Droplet Microfluidics

Nonribosomal peptide synthetases (NRPSs) are giant enzymatic assembly lines that deliver many pharmaceutically valuable natural products, including antibiotics. As the search for new antibiotics motivates attempts to redesign nonribosomal metabolic pathways, more robust and rapid sorting and screening platforms are needed. Here, we establish a microfluidic platform that reliably detects production of the model nonribosomal peptide gramicidin S. The detection is based on calcein-filled sensor liposomes yielding increased fluorescence upon permeabilization. From a library of NRPS mutants, the sorting platform enriches the gramicidin S producer 14.5-fold, decreases internal stop codons 250-fold, and generates enrichment factors correlating with enzyme activity. Screening for NRPS activity with a reliable non-binary sensor will enable more sophisticated structure-activity studies and new engineering applications in the future.

High-throughput bacterial co-encapsulation in microfluidic gel beads for discovery of antibiotic-producing strains

Bacteria with antagonistic activity inhibit the growth of other bacteria through different mechanisms, including the production of antibiotics. As a result, these microorganisms are a prolific source of such compounds. However, searching for antibiotic-producing strains requires high-throughput techniques due to the vast diversity of microorganisms. Here, we screened and isolated bacteria with antagonistic activity against Escherichia coli expressing the green fluorescent protein (E. coli-GFP). We used microfluidics to co-encapsulate and co-culture single cells from different strains within picoliter gel beads and analyzed them using fluorescence-activated cell sorting (FACS). To test the methodology, we used three bacterial isolates obtained from Mexican maize, which exhibit high, moderate, or no antagonistic activity against E. coli-GFP, as determined previously using agar plate assays. Single cells from each strain were separately co-incubated into gel beads with E. coli-GFP. We monitored the development of the maize bacteria microcolonies and tracked the growth or inhibition of E. coli-GFP using bright-field and fluorescent microscopy. We correlated these images with distinctive light scatter and fluorescence signatures of each incubated bead type using FACS. This analysis enabled us to sort gel beads filled with an antagonistic strain, starting from a mixture of the three different types of maize bacteria and E. coli-GFP. Likewise, culturing the FACS-sorted beads on agar plates confirmed the isolation and recovery of the two antagonistic strains. In addition, enrichment assays demonstrated the methodology's effectiveness in isolating rare antibiotic-producer strains (0.01% abundance) present in a mixture of microorganisms. These results show that associating light side scatter and fluorescent flow cytometry signals with microscopy images provides valuable controls to establish successful high-throughput methods for sorting beads in which microbial interaction assays are performed.

Fluorescence coupling strategies in fluorescence-activated droplet sorting (FADS) for ultrahigh-throughput screening of enzymes, metabolites, and antibodies

Fluorescence-activated droplet sorting (FADS) has emerged as a powerful tool for ultrahigh-throughput screening of enzymes, metabolites, and antibodies. Fluorescence coupling strategies (FCSs) are key to the development of new FADS methods through their coupling of analyte properties such as concentration, activities, and affinity with fluorescence signals. Over the last decade, a series of FCSs have been developed, greatly expanding applications of FADS. Here, we review recent advances in FCS for different analyte types, providing a critical comparison of the available FCSs and further classification into four categories according to their principles. We also summarize successful FADS applications employing FCSs in enzymes, metabolites, and antibodies. Further, we outline possible future developments in this area.

Ultrahigh-Throughput Enzyme Engineering and Discovery in In Vitro Compartments

Novel and improved biocatalysts are increasingly sourced from libraries via experimental screening. The success of such campaigns is crucially dependent on the number of candidates tested. Water-in-oil emulsion droplets can replace the classical test tube, to provide in vitro compartments as an alternative screening format, containing genotype and phenotype and enabling a readout of function. The scale-down to micrometer droplet diameters and picoliter volumes brings about a >10⁷-fold volume reduction compared to 96-well-plate screening. Droplets made in automated microfluidic devices can be integrated into modular workflows to set up multistep screening protocols involving various detection modes to sort >10⁷ variants a day with kHz frequencies. The repertoire of assays available for droplet screening covers all seven enzyme commission (EC) number classes, setting the stage for widespread use of droplet microfluidics in everyday biochemical experiments. We review the practicalities of adapting droplet screening for enzyme discovery and for detailed kinetic characterization. These new ways of working will not just accelerate discovery experiments currently limited by screening capacity but profoundly change the paradigms we can probe. By interfacing the results of ultrahigh-throughput droplet screening with next-generation sequencing and deep learning, strategies for directed evolution can be implemented, examined, and evaluated.

Ultra-High-Throughput Absorbance-Activated Droplet Sorting for Enzyme Screening at Kilohertz Frequencies

Droplet microfluidics is a valuable method to "beat the odds" in high throughput screening campaigns such as directed evolution, where valuable hits are infrequent and large library sizes are required. Absorbance-based sorting expands the range of enzyme families that can be subjected to droplet screening by expanding possible assays beyond fluorescence detection. However, absorbance-activated droplet sorting (AADS) is currently ∼10-fold slower than typical fluorescence-activated droplet sorting (FADS), meaning that, in comparison, a larger portion of sequence space is inaccessible due to throughput constraints. Here we improve AADS to reach kHz sorting speeds in an order of magnitude increase over previous designs, with close-to-ideal sorting accuracy. This is achieved by a combination of (i) the use of refractive index matching oil that improves signal quality by removal of side scattering (increasing the sensitivity of absorbance measurements); (ii) a sorting algorithm capable of sorting at this increased frequency with an Arduino Due; and (iii) a chip design that transmits product detection better into sorting decisions without false positives, namely a single-layered inlet to space droplets further apart and injections of "bias oil" providing a fluidic barrier preventing droplets from entering the incorrect sorting channel. The updated ultra-high-throughput absorbance-activated droplet sorter increases the effective sensitivity of absorbance measurements through better signal quality at a speed that matches the more established fluorescence-activated sorting devices.