A growth selection system for the directed evolution of amine-forming or converting enzymes

Rich analytic toolbox for the exploration, characterization, screening, and application studies of ω-transaminases

Omega-transaminases (ωTAs) constitute an important class of biocatalysts in the pharmaceutical, agrochemical, and fine chemical industries, because of their generally good performance in the efficient, enantiospecific, and environment-friendly synthesis of chiral amines that possess diverse chemical structures and biological activities. However, their practical applications are often hindered by unfavorable reaction equilibria, product inhibition, limited robustness, and relatively small accommodation for substrates. Many efforts, including the exploration of novel enzymes from various environments and the targeted engineering of identified enzymes, have been made to develop more specific and efficient ωTA catalysts. A simple, rapid, and accurate evaluation of enzyme activity is important. In addition to the classic chromatography-based methods, to date, at least 18 analytic methods, which are based on cell growth or colorimetry/spectrophotometry, pH, fluorescence and conductivity changes, have been developed and applied in both qualitative and quantitative analyses of ωTAs. These methods differ in terms of their principles, accuracy, throughput, simplicity, and cost-effectiveness. Here, we present a detailed examination of the advantages and drawbacks of these methods. Guidance for method selection from the perspective of practical applications is proposed to assist investigators in choosing appropriate methods according to different research purposes and existing conditions.

Deep learning-driven semi-rational design in phenylalanine ammonia-lyase for enhanced catalytic efficiency

Phenylalanine ammonia-lyase (PAL) possesses significant potential in agriculture, industry, and the treatment of various diseases, including cancer. In particular, PAL derived from Anabaena variabilis (AvPAL) has been successfully utilized in clinical settings as an enzyme replacement therapy for phenylketonuria (PKU). Nonetheless, enhancing the catalytic efficiency of enzymes continues to be a formidable task. Herein, a deep learning-guided strategy was employed to identify potential sites in AvPAL that require modification to address current challenges. In conjunction with high-throughput screening and enzymatic assays, 26 out of 33 mutants were validated to exhibit enhanced activity. Notably, the probability of identifying mutants with increased activity at each targeted site was 100 %. Through multiple rounds of combinatorial mutagenesis, the catalytic efficiency (kcat/KM) was improved up to 3.4-fold (M222N/N36S) and the activity was enhanced up to 2.4-fold (M222N/I149D) compared to the wild type. Molecular dynamics simulations revealed that the stabilization of the proximate attack conformation is closely associated with the enhancement of catalytic activity. Furthermore, structural superposition, residue interaction network analysis, and dynamic cross-correlation matrices indicate that the most active mutant, M222N/I149D, induces local fluctuations and distal effects in loop 81-94, leading to a more favorable conformation and thus increased activity. Collectively, this study provides a feasible approach for engineering an efficient PAL.

An Update: Enzymatic Synthesis for Industrial Applications

Supported by rapid technological advancements, biocatalytic applications have matured into sustainable, scalable, and cost-competitive alternatives to established chemical catalysis. This review presents the most recent examples of enzyme-based solutions for the manufacturing of molecules with extended carbon-carbon frameworks and multiple stereogenic centers at commercial scale, including peptide building blocks, (rare) sugars, synthetic (oligo)nucleotides, and terpenoids, such as (-)-Ambrox®. Novel enzyme classes are highlighted along with their potential applications-the synthesis of DNA/RNA, the depolymerization of synthetic plastics, or fully enzymatic protection/deprotection schemes-pointing toward the diversification and broader industrial utilization of biocatalysis-based processes.

The pedal-like loop of (R)-selective transaminases plays a critical role to the functionality of the enzyme

In enzyme engineering, a lot of studies have focused on engineering the active site to broaden substrate specificity or enhance transaminase activity; however, relatively little is known about the mechanisms by which substrates are recognized and enter the binding pocket. Transaminases play a crucial role in the synthesis of chiral amines due to their exceptional stereoselectivity and catalytic efficiency. In this study, we explored how the pedal-like loop at the active site influences (R)-transaminase (ATA) activity and substrate recognition by modulating the substrate channel. The pedal-like loop at the active site was swapped with loops from other well-characterized transaminases, and the best-performing variant exhibited a 5.2-fold increase in activity toward (R)-phenylethylamine ((R)-PEA) and an 11.8-fold increase in activity toward isopropylamine (IPA). Additionally, some variants showed significant changes in substrate preference. Homology modeling and molecular docking analysis provided compelling evidence that the pedal-like loop is a critical determinant of both substrate recognition and catalytic activity in (R)-ATA.

Continuous FACS sorting of double emulsion picoreactors with a 3D printed vertical mixer

High-throughput screening and directed evolution using microfluidic picoreactors have produced high-activity enzymes. In this approach, a substrate is co-encapsulated with a candidate enzyme and individual picoreactors are sorted based on an activity reporter. While many approaches use water-in-oil droplets (single emulsions) for fluorescence-activated droplet sorting (FADS) on custom-fabricated microfluidic devices that require integrated optics and electronics, recent approaches have lowered the engineering barriers to adoption by using simple microfluidic droplet generators to produce water-in-oil-in-water droplets (double emulsion picoreactors, DEs) that can be sorted with commercial FACS (fluorescence-activated cell sorting). Despite the simplified engineering requirements, high variability in loading rates and low yield during loading are barriers to efficient DE FACS sorting. Here, we optimized surfactants to enhance DE stability and demonstrated that a 3D-printed corkscrew on the sample line acts as a vertical mixer to enable more continuous loading. With these optimized loading conditions, we analyzed 1.17 million DEs in four 10-minute sorting rounds with a mean frequency of 480 Hz (390 Hz including sample exchanges); in a mock sort of 10% fluorescent DEs, we achieved 89.2±1.1% accuracy and 78±0.9% recovery with our optimized loading protocol. Overall, improved ease-of-use and throughput for FACS sortable DEs should expand the accessibility of directed evolution in controlled in vitro environments.

Combining Photochemical Oxyfunctionalization and Enzymatic Catalysis for the Synthesis of Chiral Pyrrolidines and Azepanes

Chiral heterocyclic alcohols and amines are frequently used building blocks in the synthesis of fine chemicals and pharmaceuticals. Herein, we report a one-pot photoenzymatic synthesis route for N-Boc-3-amino/hydroxy-pyrrolidine and N-Boc-4-amino/hydroxy-azepane with up to 90% conversions and >99% enantiomeric excess. The transformation combines a photochemical oxyfunctionalization favored for distal C-H positions with a stereoselective enzymatic transamination or carbonyl reduction step. Our study demonstrates a mild and operationally simple asymmetric synthesis workflow from easily available starting materials.

Direct asymmetric synthesis of β-branched aromatic α-amino acids using engineered phenylalanine ammonia lyases

β-Branched aromatic α-amino acids are valuable building blocks in natural products and pharmaceutically active compounds. However, their chemical or enzymatic synthesis is challenging due to the presence of two stereocenters. We design phenylalanine ammonia lyases (PAL) variants for the direct asymmetric synthesis of β-branched aromatic α-amino acids. Based on extensive computational analyses, we unravel the enigma behind PAL's inability to accept β-methyl cinnamic acid (β-MeCA) as substrate and achieve the synthesis of the corresponding amino acids of β-MeCA and analogs using a double (PcPAL-L256V-I460V) and a triple mutant (PcPAL-F137V-L256V-I460V). The reactions are scaled-up using an optimized E. coli based whole-cell biotransformation system to produce ten β-branched phenylalanine analogs with high diastereoselectivity (dr > 20:1) and enantioselectivity (ee > 99.5%) in yields ranging from 41-71%. Moreover, we decipher the mechanism of PcPAL-L256V-I460V for the acceptance of β-MeCA and converting it with excellent stereoselectivity by computational simulations. Thus, this study offers an efficient method for synthesizing β-branched aromatic α-amino acids.

A growth-based screening strategy for engineering the catalytic activity of an oxygen-sensitive formate dehydrogenase

Enzyme engineering is a powerful tool for improving or altering the properties of biocatalysts for industrial, research, and therapeutic applications. Fast and accurate screening of variant libraries is often the bottleneck of enzyme engineering and may be overcome by growth-based screening strategies with simple processes to enable high throughput. The currently available growth-based screening strategies have been widely employed for enzymes but not yet for catalytically potent and oxygen-sensitive metalloenzymes. Here, we present a screening system that couples the activity of an oxygen-sensitive formate dehydrogenase to the growth of Escherichia coli. This system relies on the complementation of the E. coli formate hydrogenlyase (FHL) complex by Mo-dependent formate dehydrogenase H (EcFDH-H). Using an EcFDH-H-deficient strain, we demonstrate that growth inhibition by acidic glucose fermentation products can be alleviated by FHL complementation. This allows the identification of catalytically active EcFDH-H variants at a readily measurable cell density readout, reduced handling efforts, and a low risk of oxygen contamination. Furthermore, a good correlation between cell density and formate oxidation activity was established using EcFDH-H variants with variable catalytic activities. As proof of concept, the growth assay was employed to screen a library of 1,032 EcFDH-H variants and reduced the library size to 96 clones. During the subsequent colorimetric screening of these clones, the variant A12G exhibiting an 82.4% enhanced formate oxidation rate was identified. Since many metal-dependent formate dehydrogenases and hydrogenases form functional complexes resembling E. coli FHL, the demonstrated growth-based screening strategy may be adapted to components of such electron-transferring complexes.IMPORTANCEOxygen-sensitive metalloenzymes are highly potent catalysts that allow the reduction of chemically inert substrates such as CO2 and N2 at ambient pressure and temperature and have, therefore, been considered for the sustainable production of biofuels and commodity chemicals such as ammonia, formic acid, and glycine. A proven method to optimize natural enzymes for such applications is enzyme engineering using high-throughput variant library screening. However, most screening methods are incompatible with the oxygen sensitivity of these metalloenzymes and thereby limit their relevance for the development of biosynthetic production processes. A microtiter plate-based assay was developed for the screening of metal-dependent formate dehydrogenase that links the activity of the tested enzyme variant to the growth of the anaerobically grown host cell. The presented work extends the application range of growth-based screening to metalloenzymes and is thereby expected to advance their adoption to biosynthesis applications.

Development of growth selection system and pocket engineering of d-amino acid oxidase to enhance selective deamination activity toward d-phosphinothricin

D-amino acid oxidase (DAAO)-catalyzed selective oxidative deamination is a very promising process for synthesizing l-amino acids including l-phosphinothricin (l-PPT, a high-efficiency and broad-spectrum herbicide). However, the wild-type DAAO's low activity toward unnatural substrates like d-phosphinothricin (d-PPT) hampers its application. Herein, a DAAO from Caenorhabditis elegans (CeDAAO) was screened and engineered to improve the catalytic potential on d-PPT. First, we designed a novel growth selection system, taking into account the intricate relationship between the growth of Escherichia coli (E. coli) and the catalytic mechanism of DAAO. The developed system was used for high-throughput screening of gene libraries, resulting in the discovery of a variant (M6) with significantly increased catalytic activity against d-PPT. The variant displays different catalytic properties on substrates with varying hydrophobicity and hydrophilicity. Analysis using Alphafold2 modeling and molecular dynamic simulations showed that the reason for the enhanced activity was the substrate-binding pocket with enlarged size and suitable charge distribution. Further QM/MM calculations revealed that the crucial factor for enhancing activity lies in reducing the initial energy barrier of the reductive half reaction. Finally, a comprehensive binding-model index to predict the enhanced activity of DAAO toward d-PPT, and an enzymatic deracemization approach was developed, enabling the efficient synthesis of l-PPT with remarkable efficiency.

Systems and Methods for Continuous Evolution of Enzymes

Directed evolution generates novel biomolecules with desired functions by iteratively diversifying the genetic sequence of wildtype biomolecules, relaying the genetic information to the molecule with function, and selecting the variants that progresses towards the properties of interest. While traditional directed evolution consumes significant labor and time for each step, continuous evolution seeks to automate all steps so directed evolution can proceed with minimum human intervention and dramatically shortened time. A major application of continuous evolution is the generation of novel enzymes, which catalyze reactions under conditions that are not favorable to their wildtype counterparts, or on altered substrates. The challenge to continuously evolve enzymes lies in automating sufficient, unbiased gene diversification, providing selection for a wide array of reaction types, and linking the genetic information to the phenotypic function. Over years of development, continuous evolution has accumulated versatile strategies to address these challenges, enabling its use as a general tool for enzyme engineering. As the capability of continuous evolution continues to expand, its impact will increase across various industries. In this review, we summarize the working mechanisms of recently developed continuous evolution strategies, discuss examples of their applications focusing on enzyme evolution, and point out their limitations and future directions.

Evolving ω-amine transaminase AtATA guided by substrate-enzyme binding free energy for enhancing activity and stability against non-natural substrates

In the field of chiral amine synthesis, ω-amine transaminase (ω-ATA) is one of the most established enzymes capable of asymmetric amination under optimal conditions. However, the applicability of ω-ATA toward more non-natural complex molecules remains limited due to its low transamination activity, thermostability, and narrow substrate scope. Here, by employing a combined approach of computational virtual screening strategy and combinatorial active-site saturation test/iterative saturation mutagenesis strategy, we have constructed the best variant M14C3-V5 (M14C3-V62A-V116S-E117I-L118I-V147F) with improved ω-ATA from Aspergillus terreus (AtATA) activity and thermostability toward non-natural substrate 1-acetylnaphthalene, which is the ketone precursor for producing the intermediate (R)-(+)-1-(1-naphthyl)ethylamine [(R)-NEA] of cinacalcet hydrochloride, showing activity enhancement of up to 3.4-fold compared to parent enzyme M14C3 (AtATA-F115L-M150C-H210N-M280C-V149A-L182F-L187F). The computational tools YASARA, Discovery Studio, Amber, and FoldX were applied for predicting mutation hotspots based on substrate-enzyme binding free energies and to show the possible mechanism with features related to AtATA structure, catalytic activity, and stability in silico analyses. M14C3-V5 achieved 71.8% conversion toward 50 mM 1-acetylnaphthalene in a 50 mL preparative-scale reaction for preparing (R)-NEA. Moreover, M14C3-V5 expanded the substrate scope toward aromatic ketone compounds. The generated virtual screening strategy based on the changes in binding free energies has successfully predicted the AtATA activity toward 1-acetylnaphthalene and related substrates. Together with experimental data, these approaches can serve as a gateway to explore desirable performances, expand enzyme-substrate scope, and accelerate biocatalysis.IMPORTANCEChiral amine is a crucial compound with many valuable applications. Their asymmetric synthesis employing ω-amine transaminases (ω-ATAs) is considered an attractive method. However, most ω-ATAs exhibit low activity and stability toward various non-natural substrates, which limits their industrial application. In this work, protein engineering strategy and computer-aided design are performed to evolve the activity and stability of ω-ATA from Aspergillus terreus toward non-natural substrates. After five rounds of mutations, the best variant, M14C3-V5, is obtained, showing better catalytic efficiency toward 1-acetylnaphthalene and higher thermostability than the original enzyme, M14C3. The robust combinational variant acquired displayed significant application value for pushing the asymmetric synthesis of aromatic chiral amines to a higher level.

Engineering the next-generation synthetic cell factory driven by protein engineering

Synthetic cell factory offers substantial advantages in economically efficient production of biofuels, chemicals, and pharmaceutical compounds. However, to create a high-performance synthetic cell factory, precise regulation of cellular material and energy flux is essential. In this context, protein components including enzymes, transcription factor-based biosensors and transporters play pivotal roles. Protein engineering aims to create novel protein variants with desired properties by modifying or designing protein sequences. This review focuses on summarizing the latest advancements of protein engineering in optimizing various aspects of synthetic cell factory, including: enhancing enzyme activity to eliminate production bottlenecks, altering enzyme selectivity to steer metabolic pathways towards desired products, modifying enzyme promiscuity to explore innovative routes, and improving the efficiency of transporters. Furthermore, the utilization of protein engineering to modify protein-based biosensors accelerates evolutionary process and optimizes the regulation of metabolic pathways. The remaining challenges and future opportunities in this field are also discussed.

An Extremely Sensitive Ultra-High Throughput Growth Selection Assay for the Identification of Amidase Activity

In the last decades, biocatalysis has offered new perspectives for the synthesis of (chiral) amines, which are essential building blocks for pharmaceuticals, fine and bulk chemicals. In this regard, amidases have been employed due to their broad substrate scope and their independence from expensive cofactors. To expand the repertoire of amidases, tools for their rapid identification and characterization are greatly demanded. In this work an ultra-high throughput growth selection assay based on the production of the folate precursor p-aminobenzoic acid (PABA) is introduced to identify amidase activity. PABA-derived amides structurally mimic the broad class of commonly used chromogenic substrates derived from p-nitroaniline. This suggests that the assay should be broadly applicable for the identification of amidases. Unlike conventional growth selection assays that rely on substrates as nitrogen or carbon source, our approach requires PABA in sub-nanomolar concentrations, making it exceptionally sensitive and ideal for engineering campaigns that aim at enhancing amidase activities from minimally active starting points, for example. The presented assay offers flexibility in the adjustment of sensitivity to suit project-specific needs using different expression systems and fine-tuning with the antimetabolite sulfathiazole. Application of this PABA-based assay facilitates the screening of millions of enzyme variants on a single agar plate within two days, without the need for laborious sample preparation or expensive instruments, with transformation efficiency being the only limiting factor. KEY POINTS: • Ultra-high throughput assay (tens of millions on one agar plate) for amidase screening • High sensitivity by coupling selection to folate instead of carbon or nitrogen source • Highly adjustable in terms of sensitivity and expression of the engineering target.

A growth selection system for sucrose synthases (SuSy): design and test

High throughput screening (HTS) methods of enzyme variants are essential for the development of robust biocatalysts suited for low impact, industrial scale, biobased synthesis of a myriad of compounds. However, for the majority of enzyme classes, current screening methods have limited throughput, or need expensive substrates in combination with sophisticated setups. Here, we present a straightforward, high throughput selection system that couples sucrose synthase activity to growth. Enabling high throughput screening of this enzyme class holds the potential to facilitate the creation of robust variants, which in turn can significantly impact the future of cost effective industrial glycosylation.

Maximizing the potential of nitrilase: Unveiling their diversity, catalytic proficiency, and versatile applications

Nitrilases represent a distinct class of enzymes that play a pivotal role in catalyzing the hydrolysis of nitrile compounds, leading to the formation of corresponding carboxylic acids. These enzymatic entities have garnered significant attention across a spectrum of industries, encompassing pharmaceuticals, agrochemicals, and fine chemicals. Moreover, their significance has been accentuated by mounting environmental pressures, propelling them into the forefront of biodegradation and bioremediation endeavors. Nevertheless, the natural nitrilases exhibit intrinsic limitations such as low thermal stability, narrow substrate selectivity, and inadaptability to varying environmental conditions. In the past decade, substantial efforts have been made in elucidating the structural underpinnings and catalytic mechanisms of nitrilase, providing basis for engineering of nitrilases. Significant breakthroughs have been made in the regulation of nitrilases with ideal catalytic properties and application of the enzymes for industrial productions. This review endeavors to provide a comprehensive discourse and summary of recent research advancements related to nitrilases, with a particular emphasis on the elucidation of the structural attributes, catalytic mechanisms, catalytic characteristics, and strategies for improving catalytic performance of nitrilases. Moreover, the exploration extends to the domain of process engineering and the multifarious applications of nitrilases. Furthermore, the future development trend of nitrilases is prospected, providing important guidance for research and application in the related fields.

Automated in vivo enzyme engineering accelerates biocatalyst optimization

Achieving cost-competitive bio-based processes requires development of stable and selective biocatalysts. Their realization through in vitro enzyme characterization and engineering is mostly low throughput and labor-intensive. Therefore, strategies for increasing throughput while diminishing manual labor are gaining momentum, such as in vivo screening and evolution campaigns. Computational tools like machine learning further support enzyme engineering efforts by widening the explorable design space. Here, we propose an integrated solution to enzyme engineering challenges whereby ML-guided, automated workflows (including library generation, implementation of hypermutation systems, adapted laboratory evolution, and in vivo growth-coupled selection) could be realized to accelerate pipelines towards superior biocatalysts.

A Robust Growth-Based Selection Platform to Evolve an Enzyme via Dependency on Noncanonical Tyrosine Analogues

Growth-based selections evaluate the fitness of individual organisms at a population level. In enzyme engineering, such growth selections allow for the rapid and straightforward identification of highly efficient biocatalysts from extensive libraries. However, selection-based improvement of (synthetically useful) biocatalysts is challenging, as they require highly dependable strategies that artificially link their activities to host survival. Here, we showcase a robust and scalable growth-based selection platform centered around the complementation of noncanonical amino acid-dependent bacteria. Specifically, we demonstrate how serial passaging of populations featuring millions of carbamoylase variants autonomously selects biocatalysts with up to 90,000-fold higher initial rates. Notably, selection of replicate populations enriched diverse biocatalysts, which feature distinct amino acid motifs that drastically boost carbamoylase activity. As beneficial substitutions also originated from unintended copying errors during library preparation or cell division, we anticipate that our growth-based selection platform will be applicable to the continuous, autonomous evolution of diverse biocatalysts in the future.

Transaminase-catalysis to produce trans-4-substituted cyclohexane-1-amines including a key intermediate towards cariprazine

Cariprazine-the only single antipsychotic drug in the market which can handle all symptoms of bipolar I disorder-involves trans-4-substituted cyclohexane-1-amine as a key structural element. In this work, production of trans-4-substituted cyclohexane-1-amines was investigated applying transaminases either in diastereotope selective amination starting from the corresponding ketone or in diastereomer selective deamination of their diasteromeric mixtures. Transaminases were identified enabling the conversion of the cis-diastereomer of four selected cis/trans-amines with different 4-substituents to the corresponding ketones. In the continuous-flow experiments aiming the cis diastereomer conversion to ketone, highly diastereopure trans-amine could be produced (de > 99%). The yield of pure trans-isomers exceeding their original amount in the starting mixture could be explained by dynamic isomerization through ketone intermediates. The single transaminase-catalyzed process-exploiting the cis-diastereomer selectivity of the deamination and thermodynamic control favoring the trans-amines due to reversibility of the steps-allows enhancement of the productivity of industrial cariprazine synthesis.

Growth-Coupled Evolutionary Pressure Improving Epimerases for D-Allulose Biosynthesis Using a Biosensor-Assisted In Vivo Selection Platform

Fast screening strategies that enable high-throughput evaluation and identification of desired variants from diversified enzyme libraries are crucial to tailoring biocatalysts for the synthesis of D-allulose, which is currently limited by the poor catalytic performance of ketose 3-epimerases (KEases). Here, the study designs a minimally equipment-dependent, high-throughput, and growth-coupled in vivo screening platform founded on a redesigned D-allulose-dependent biosensor system. The genetic elements modulating regulator PsiR expression levels undergo systematic optimization to improve the growth-responsive dynamic range of the biosensor, which presents ≈30-fold facilitated growth optical density with a high signal-to-noise ratio (1.52 to 0.05) toward D-allulose concentrations from 0 to 100 mm. Structural analysis and evolutionary conservation analysis of Agrobacterium sp. SUL3 D-allulose 3-epimerase (ADAE) reveal a highly conserved catalytic active site and variable hydrophobic pocket, which together regulate substrate recognition. Structure-guided rational design and directed evolution are implemented using the growth-coupled in vivo screening platform to reprogram ADAE, in which a mutant M42 (P38N/V102A/Y201L/S207N/I251R) is identified with a 6.28-fold enhancement of catalytic activity and significantly improved thermostability with a 2.5-fold increase of the half-life at 60 °C. The research demonstrates that biosensor-assisted growth-coupled evolutionary pressure combined with structure-guided rational design provides a universal route for engineering KEases.

Roles of the N-terminal motif in improving the activity and soluble expression of phenylalanine ammonia lyases in Escherichia coli

Phenylalanine ammonia-lyase (PAL) has various applications in fine chemical manufacturing and the pharmaceutical industry. In particular, PAL derived from Anabaena variabilis (AvPAL) is used as a therapeutic agent to the treat phenylketonuria in clinical settings. In this study, we aligned the amino acid sequences of AvPAL and PAL derived from Nostoc punctiforme (NpPAL) to obtain several mutants with enhanced activity, expression yield, and thermal stability via amino acid substitution and saturation mutagenesis at the N-terminal position. Enzyme kinetic experiments revealed that the kcat values of NpPAL-N2K, NpPAL-I3T, and NpPAL-T4L mutants were increased to 3.2-, 2.8-, and 3.3-fold that of the wild-type, respectively. Saturation mutagenesis of the fourth amino acid in AvPAL revealed that the kcat values of AvPAL-L4N, AvPAL-L4P, AvPAL-L4Q and AvPAL-L4S increased to 4.0-, 3.7-, 3.6-, and 3.2-fold, respectively. Additionally, the soluble protein yield of AvPAL-L4K increased to approximately 14 mg/L, which is approximately 3.5-fold that of AvPAL. Molecular dynamics studies further revealed that maintaining the attacking state of the reaction and N-terminal structure increased the rate of catalytic reaction and improved the solubility of proteins. These findings provide new insights for the rational design of PAL in the future.

Laboratory Evolution of Metalloid Reductase Substrate Recognition and Nanoparticle Product Size

Glutathione reductase-like metalloid reductase (GRLMR) is an enzyme that reduces selenodiglutathione (GS-Se-SG), forming zerovalent Se nanoparticles (SeNPs). Error-prone polymerase chain reaction was used to create a library of ∼10,000 GRLMR variants. The library was expressed in BL21Escherichia coli in liquid culture with 50 mM of SeO32- present, under the hypothesis that the enzyme variants with improved GS-Se-SG reduction kinetics would emerge. The selection resulted in a GRLMR variant with two mutations. One of the mutations (D-E) lacks an obvious functional role, whereas the other mutation is L-H within 5 Å of the enzyme active site. This mutation places a second H residue within 5 Å of an active site dicysteine. This GRLMR variant was characterized for NADPH-dependent reduction of GS-Se-SG, GSSG, SeO32-, SeO42-, GS-Te-SG, and TeO32-. The evolved enzyme demonstrated enhanced reduction of SeO32- and gained the ability to reduce SeO42-. This variant is named selenium reductase (SeR) because of its emergent broad activity for a wide variety of Se substrates, whereas the parent enzyme was specific for GS-Se-SG. This study overall suggests that new biosynthetic routes are possible for inorganic nanomaterials using laboratory-directed evolution methods.

Directed Evolution of 4-Hydroxyphenylpyruvate Biosensors Based on a Dual Selection System

Biosensors based on allosteric transcription factors have been widely used in synthetic biology. In this study, we utilized the Acinetobacter ADP1 transcription factor PobR to develop a biosensor activating the PpobA promoter when bound to its natural ligand, 4-hydroxybenzoic acid (4HB). To screen for PobR mutants responsive to 4-hydroxyphenylpyruvate(HPP), we developed a dual selection system in E. coli. The positive selection of this system was used to enrich PobR mutants that identified the required ligands. The following negative selection eliminated or weakened PobR mutants that still responded to 4HB. Directed evolution of the PobR library resulted in a variant where PobRW177R was 5.1 times more reactive to 4-hydroxyphenylpyruvate than PobRWT. Overall, we developed an efficient dual selection system for directed evolution of biosensors.

Enzyme engineering for functional lipids synthesis: recent advance and perspective

Functional lipids, primarily derived through the modification of natural lipids by various processes, are widely acknowledged for their potential to impart health benefits. In contrast to chemical methods for lipid modification, enzymatic catalysis offers distinct advantages, including high selectivity, mild operating conditions, and reduced byproduct formation. Nevertheless, enzymes face challenges in industrial applications, such as low activity, stability, and undesired selectivity. To address these challenges, protein engineering techniques have been implemented to enhance enzyme performance in functional lipid synthesis. This article aims to review recent advances in protein engineering, encompassing approaches from directed evolution to rational design, with the goal of improving the properties of lipid-modifying enzymes. Furthermore, the article explores the future prospects and challenges associated with enzyme-catalyzed functional lipid synthesis.

Advances in ligand-specific biosensing for structurally similar molecules

The specificity of biological systems makes it possible to develop biosensors targeting specific metabolites, toxins, and pollutants in complex medical or environmental samples without interference from structurally similar compounds. For the last two decades, great efforts have been devoted to creating proteins or nucleic acids with novel properties through synthetic biology strategies. Beyond augmenting biocatalytic activity, expanding target substrate scopes, and enhancing enzymes' enantioselectivity and stability, an increasing research area is the enhancement of molecular specificity for genetically encoded biosensors. Here, we summarize recent advances in the development of highly specific biosensor systems and their essential applications. First, we describe the rational design principles required to create libraries containing potential mutants with less promiscuity or better specificity. Next, we review the emerging high-throughput screening techniques to engineer biosensing specificity for the desired target. Finally, we examine the computer-aided evaluation and prediction methods to facilitate the construction of ligand-specific biosensors.

Growth-coupled high throughput selection for directed enzyme evolution

Directed enzyme evolution has revolutionized the rapid development of enzymes with desired properties. However, the lack of a high-throughput method to identify the most suitable variants from a large pool of genetic diversity poses a major bottleneck. To overcome this challenge, growth-coupled in vivo high-throughput selection approaches (GCHTS) have emerged as a novel selection system for enzyme evolution. GCHTS links the survival of the host cell with the properties of the target protein, resulting in a screening system that is easily measurable and has a high throughput-scale limited only by transformation efficiency. This allows for the rapid identification of desired variants from a pool of >109 variants in each experiment. In recent years, GCHTS approaches have been extensively utilized in the directed evolution of multiple enzymes, demonstrating success in catalyzing non-native substrates, enhancing catalytic activity, and acquiring novel functions. This review introduces three main strategies employed to achieve GCHTS: the elimination of toxic compounds via desired variants, enabling host cells to thrive in hazardous conditions; the complementation of an auxotroph with desired variants, where essential genes for cell growth have been eliminated; and the control of the transcription or expression of a reporter gene related to host cell growth, regulated by the desired variants. Additionally, we highlighted the recent developments in the in vivo continuous evolution of enzyme technology, including phage-assisted continuous evolution (PACE) and orthogonal DNA Replication (OrthoRep). Furthermore, this review discusses the challenges and future prospects in the field of growth-coupled selection for protein engineering.

Advances in ultrahigh-throughput screening technologies for protein evolution

Inspired by natural evolution, directed evolution randomly mutates the gene of interest through artificial evolution conditions with variants being screened for the required properties. Directed evolution is vital to the enhancement of protein properties and comprises the construction of libraries with considerable diversity as well as screening methods with sufficient efficiency as key steps. Owing to the various characteristics of proteins, specific methods are urgently needed for library screening, which is one of the main limiting factors in accelerating evolution. This review initially organizes the principles of ultrahigh-throughput screening from the perspective of protein properties. It then provides a comprehensive introduction to the latest progress and future trends in ultrahigh-throughput screening technologies for directed evolution.

Directed evolution of Rhodotorula gracilisd-amino acid oxidase using single-cell hydrogel encapsulation and ultrahigh-throughput screening

Engineering catalytic and biophysical properties of enzymes is an essential step en route to advanced biomedical and industrial applications. Here, we developed a high-throughput screening and directed evolution strategy relying on single-cell hydrogel encapsulation to enhance the performance of d-Amino acid oxidase from Rhodotorula gracilis (RgDAAOx), a candidate enzyme for cancer therapy. We used a cascade reaction between RgDAAOx variants surface displayed on yeast and horseradish peroxidase (HRP) in the bulk media to trigger enzyme-mediated crosslinking of phenol-bearing fluorescent alginate macromonomers, resulting in hydrogel formation around single yeast cells. The fluorescent hydrogel capsules served as an artificial phenotype and basis for pooled library screening by fluorescence activated cell sorting (FACS). We screened a RgDAAOx variant library containing ∼10⁶ clones while lowering the d-Ala substrate concentration over three sorting rounds in order to isolate variants with low K_m. After three rounds of FACS sorting and regrowth, we isolated and fully characterized four variants displayed on the yeast surface. We identified variants with a more than 5-fold lower K_m than the parent sequence, with an apparent increase in substrate binding affinity. The mutations we identified were scattered across the RgDAAOx structure, demonstrating the difficulty in rationally predicting allosteric sites and highlighting the advantages of scalable library screening technologies for evolving catalytic enzymes.