Phage-assisted continuous evolution of proteases with altered substrate specificity

PERRC: Protease Engineering with Reactant Residence Time Control

Proteases with engineered specificity hold great potential for targeted therapeutics, protein circuit construction, and biotechnology applications. However, many proteases exhibit broad substrate specificity, limiting their use in such applications. Engineering protease specificity remains challenging because evolving a protease to recognize a new substrate, without counterselecting against its native substrate, often results in high residual activity on the original substrate. To address this, we developed Protease Engineering with Reactant Residence Time Control (PERRC), a platform that exploits the correlation between endoplasmic reticulum (ER) retention sequence strength and ER residence time. PERRC allows precise control over the stringency of protease evolution by adjusting counterselection to selection substrate ratios. Using PERRC, we evolved an orthogonal tobacco etch virus protease variant, TEVESNp, that selectively cleaves a substrate (ENLYFES) that differs by only one amino acid from its parent sequence (ENLYFQS). TEVESNp exhibits a remarkable 65-fold preference for the evolved substrate, marking the first example of an engineered orthogonal protease driven by such a slight difference in substrate recognition. Furthermore, TEVESNp functions as a competent protease for constructing orthogonal protein circuits in bacteria, and molecular dynamics simulations analysis reveals subtle yet functionally significant active site rearrangements. PERRC is a modular dual-substrate display system that facilitates precise engineering of protease specificity.

Protease engineering: Approaches, tools, and emerging trends

Engineered proteases with bespoke substrate specificities and activities can empower broad and innovative applications in biomedicine, mass spectrometry-based proteomics, and chemical and synthetic biology. This review provides an authoritative, topical, and detailed description and discussion of the directed evolution and high-throughput strategies designed to engineer the substrate specificity of proteases in E. coli, yeast, phage, and cell-free systems. Second, we discuss emerging protease engineering strategies that complement directed evolution, including antibody-protease fusions that enable proximity catalysis, and protease substrate specificity switching driven by exogenous protein-protein interactions. Lastly, we discuss principles for engineering split and autoinhibited proteases, which are key signal-processing modules in protein circuits. Overall, readers will gain a valuable understanding of the latest advances in protease engineering, focusing on methodologies and strategies that enable precise control of protease activity and specificity.

Targeted degradation of α-Synuclein using an evolved botulinum toxin protease

There is considerable interest in the targeted degradation of proteins implicated in human disease. The use of sequence-specific proteases for this purpose is severely limited by the difficulty in engineering the numerous enzyme-substrate interactions required to yield highly selective proteases while maintaining catalytic activity. Herein, we report a strategy to evolve a protease for the programmed degradation of α-Synuclein, a presynaptic protein closely linked to Parkinson's disease. Our structure-guided evolution campaign uses the protease from botulinum neurotoxin and showcases the stepwise change of specificity from its native substrate SNAP25 to the selective degradation of α-Synuclein. The protease's selectivity is further demonstrated in human cells where near complete degradation of overexpressed human α-Synuclein is observed with no significant effects on cell proliferation. This stepwise strategy may serve as a general approach to evolve highly selective proteases targeting dysregulated proteins.

PERRC: Protease Engineering with Reactant Residence Time Control

Proteases with engineered specificity hold great potential for targeted therapeutics, protein circuit construction, and biotechnology applications. However, many proteases exhibit broad substrate specificity, limiting their applications. Engineering protease specificity remains challenging because evolving a protease to recognize a new substrate, without counterselecting against its native substrate, often results in high residual activity on the original substrate. To address this, we developed Protease Engineering with Reactant Residence Time Control (PERRC), a platform that exploits the correlation between endoplasmic reticulum (ER) retention sequence strength and ER residence time. PERRC allows precise control over the stringency of protease evolution by adjusting counterselection to selection substrate ratios. Using PERRC, we evolved an orthogonal tobacco etch virus protease variant, TEVESNp, that selectively cleaves a substrate (ENLYFES) that differs by only one amino acid from its parent sequence (ENLYFQS). TEVESNp exhibits a remarkable 65-fold preference for the evolved substrate, marking the first example of an engineered orthogonal protease driven by such a slight difference in substrate recognition. Furthermore, TEVESNp functions as a competent protease for constructing orthogonal protein circuits in bacteria, and molecular dynamic simulations analysis reveals subtle yet functionally significant active site rearrangements. PERRC is a modular dual-substrate display system that facilitates precise engineering of protease specificity.

Targeting clonal mutations with synthetic microbes

Recently concluded, large-scale cancer genomics studies involving multiregion sequencing of primary tumors and paired metastases appear to indicate that many or most cancer patients have one or more "clonal" mutations in their tumors. Clonal mutations are those that are present in all of a patient's cancer cells. Clonally mutated proteins can potentially be targeted by inhibitors or E3 ligase small molecule glues, but developing new small molecule drugs for each patient is not feasible currently. Certain companies are using immunotherapies to target clonal mutations. I have devised another approach for exploiting clonal mutations, which I call "Oncolytic Vector Efficient Replication Contingent on Omnipresent Mutation Engagement" (OVERCOME). The ideal version of OVERCOME would likely employ a bioengineered facultative intracellular bacterium. The bacterium would initially be attenuated, but (transiently) reverse its attenuation upon clonal mutation detection.

High-throughput protein binder discovery by rapid in vivo selection

Proteins that selectively bind to a target of interest are foundational components of research pipelines1,2, diagnostics3, and therapeutics4. Current immunization-based5,6, display-based7-14, and computational approaches15-1718 for discovering binders are laborious and time-consuming - taking months or more, suffer from high false positives - necessitating extensive secondary screening, and have a high failure rate, especially for disordered proteins and other challenging target classes. Here we establish Phage-Assisted Non-Continuous Selection of Protein Binders (PANCS-binders), an in vivo selection platform that links the life cycle of M13 phage to target protein binding though customized proximity-dependent split RNA polymerase biosensors, allowing for complete and comprehensive high-throughput screening of billion-plus member protein variant libraries with high signal-to-noise. We showcase the utility of PANCS-Binders by screening multiple protein libraries each against a panel of 95 separate therapeutically relevant targets, thereby individually assessing over 1011 protein-protein interaction pairs, completed in two days. These selections yielded large, high-quality datasets and hundreds of novel binders, which we showed can be affinity matured or directly used in mammalian cells to inhibit or degrade targets. PANCS-Binders dramatically accelerates and simplifies the binder discovery process, the democratization of which will help unlock new creative potential in proteome-targeting with engineered binder-based biotechnologies.

EvoAI enables extreme compression and reconstruction of the protein sequence space

Designing proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is extremely valuable. Here we establish a method called EvoScan to comprehensively segment and scan the high-fitness sequence space to obtain anchor points that capture its essential features, especially in high dimensions. Our approach is compatible with any biomolecular function that can be coupled to a transcriptional output. We then develop deep learning and large language models to accurately reconstruct the space from these anchors, allowing computational prediction of novel, highly fit sequences without prior homology-derived or structural information. We apply this hybrid experimental-computational method, which we call EvoAI, to a repressor protein and find that only 82 anchors are sufficient to compress the high-fitness sequence space with a compression ratio of 1048. The extreme compressibility of the space informs both applied biomolecular design and understanding of natural evolution.

Optimizing ABA-based chemically induced proximity for enhanced intracellular transcriptional activation and modification response to ABA

Abscisic acid (ABA)-based chemically induced proximity (CIP) is primarily mediated by the interaction of the ABA receptor pyrabactin resistance 1-like 1 (PYL1) and the 2C-type protein phosphatase ABI1, which confers ABA-induced proximity to their fusion proteins, and offers precise temporal control of a wide array of biological processes. However, broad application of ABA-based CIP has been limited by ABA response intensity. In this study, we demonstrated that ABA-induced interaction between another ABA receptor pyrabactin resistance 1 (PYR1) and ABI1 exhibited higher ABA response intensity than that between PYL1 and ABI1 in HEK293T cells. We engineered PYR1-ABI1 and PYL1-ABI1 into ABA-induced transcriptional activation tools in mammalian cells by integration with CRISPR/dCas9 and found that the tool based on PYR1-ABI1 demonstrated better ABA response intensity than that based on PYL1-ABI1 for both exogenous and endogenous genes in mammalian cells. We further achieved ABA-induced RNA m6A modification installation and erasure by combining ABA-induced PYR1-ABI1 interaction with CRISPR/dCas13, successfully inhibiting tumor cell proliferation. We subsequently improved the interaction of PYR1-ABI1 through phage-assisted continuous evolution (PACE), successfully generating a PYR1 mutant (PYR1m) whose interaction with ABI1 exhibited a higher ABA response intensity than that of the wild-type. In addition, we tested the transcriptional activation tool based on PYRm-ABI1 and found that it also showed a higher ABA response intensity than that of the wild type. These results demonstrate that we have developed a novel ABA-based CIP and further improved upon it using PACE, providing a new approach for the modification of other CIP systems.

A gradient phage-assisted continuous evolution method for screening suppressor tRNAs in Escherichia coli

Suppressor tRNAs, notable for their capability of reading through the stop codon while maintaining normal peptide synthesis, are promising in treating diseases caused by premature termination codons (PTC). However, the lack of effective engineering methods for suppressor tRNAs has curtailed their application potential. Here, we introduce a directed evolution technology that employs phage-assisted continuous evolution (PACE), combined with gradient biosensors featuring various PTCs in the M13 gene III. Utilizing this novel methodology, we have successfully evolved tRNATrp (UGG) reading through the UGA stop codon in Escherichia coli. Massively parallel sequencing revealed that these mutations predominantly occurred in the anticodon loop. Finally, two suppressor tRNATrp (UGA) mutants exhibited over fivefold increases in readthrough 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.

A combinatorial strategy for HRV 3C protease engineering to achieve the N-terminal free cleavage

Human rhinovirus 3C protease (HRV 3CP) has a high specificity against the substrate of LEVLFQ↓G at P1' site, which plays an important role in biotechnology and academia as a fusion tag removal tool. However, a non-ignorable limitation is that an extra residue of Gly would remain at the N terminus of the recombinant target protein after cleavage with HRV 3CP, thus potentially causing protein mis-functionality or immunogenicity. Here, we developed a combinatorial strategy by integrating structure-guided library design and high-throughput screening of eYESS approach for HRV 3CP engineering to expand its P1' specificity. Finally, a C3 variant was obtained, exhibiting a broad substrate P1' specificity to recognize 20 different amino acids with the highest activity against LEVLFQ↓M (kcat/KM = 3.72 ± 0.04 mM-1∙s-1). Further biochemical and NGS-mediated substrate profiling analysis showed that C3 variant still kept its substrate stringency at P1 site and good residue tolerance at P2' site, but with an expanded P1' specificity. Structural simulation of C3 indicated a reconstructed S1' binding pocket as well as new interactions with the substrates. Overall, our studies here prompt not only the practical applications and understanding of substrate recognition mechanisms of HRV 3CP, also provide new tools for other enzyme engineering.

Continuous evolution of compact protein degradation tags regulated by selective molecular glues

Conditional protein degradation tags (degrons) are usually >100 amino acids long or are triggered by small molecules with substantial off-target effects, thwarting their use as specific modulators of endogenous protein levels. We developed a phage-assisted continuous evolution platform for molecular glue complexes (MG-PACE) and evolved a 36-amino acid zinc finger (ZF) degron (SD40) that binds the ubiquitin ligase substrate receptor cereblon in complex with PT-179, an orthogonal thalidomide derivative. Endogenous proteins tagged in-frame with SD40 using prime editing are degraded by otherwise inert PT-179. Cryo-electron microscopy structures of SD40 in complex with ligand-bound cereblon revealed mechanistic insights into the molecular basis of SD40's activity and specificity. Our efforts establish a system for continuous evolution of molecular glue complexes and provide ZF tags that overcome shortcomings associated with existing degrons.

EvoAI enables extreme compression and reconstruction of the protein sequence space

Designing proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is extremely valuable. Here, we first establish a method called EvoScan to comprehensively segment and scan the high-fitness sequence space to obtain anchor points that capture its essential features, especially in high dimensions. Our approach is compatible with any biomolecular function that can be coupled to a transcriptional output. We then develop deep learning and large language models to accurately reconstruct the space from these anchors, allowing computational prediction of novel, highly fit sequences without prior homology-derived or structural information. We apply this hybrid experimental-computational method, which we call EvoAI, to a repressor protein and find that only 82 anchors are sufficient to compress the high-fitness sequence space with a compression ratio of 1048. The extreme compressibility of the space informs both applied biomolecular design and understanding of natural evolution.

Ultrahigh-throughput screening-assisted in vivo directed evolution for enzyme engineering

BACKGROUND

Classical directed evolution is a powerful approach for engineering biomolecules with improved or novel functions. However, it traditionally relies on labour- and time-intensive iterative cycles, due in part to the need for multiple molecular biology steps, including DNA transformation, and limited screening throughput.

RESULTS

In this study, we present an ultrahigh throughput in vivo continuous directed evolution system with thermosensitive inducible tunability, which is based on error-prone DNA polymerase expression modulated by engineered thermal-responsive repressor cI857, and genomic MutS mutant with temperature-sensitive defect for fixation of mutations in Escherichia coli. We demonstrated the success of the in vivo evolution platform with β-lactamase as a model, with an approximately 600-fold increase in the targeted mutation rate. Furthermore, the platform was combined with ultrahigh-throughput screening methods and employed to evolve α-amylase and the resveratrol biosynthetic pathway. After iterative rounds of enrichment, a mutant with a 48.3% improvement in α-amylase activity was identified via microfluidic droplet screening. In addition, when coupled with an in vivo biosensor in the resveratrol biosynthetic pathway, a variant with 1.7-fold higher resveratrol production was selected by fluorescence-activated cell sorting.

CONCLUSIONS

In this study, thermal-responsive targeted mutagenesis coupled with ultrahigh-throughput screening was developed for the rapid evolution of enzymes and biosynthetic pathways.

Steering and controlling evolution - from bioengineering to fighting pathogens

Control interventions steer the evolution of molecules, viruses, microorganisms or other cells towards a desired outcome. Applications range from engineering biomolecules and synthetic organisms to drug, therapy and vaccine design against pathogens and cancer. In all these instances, a control system alters the eco-evolutionary trajectory of a target system, inducing new functions or suppressing escape evolution. Here, we synthesize the objectives, mechanisms and dynamics of eco-evolutionary control in different biological systems. We discuss how the control system learns and processes information about the target system by sensing or measuring, through adaptive evolution or computational prediction of future trajectories. This information flow distinguishes pre-emptive control strategies by humans from feedback control in biotic systems. We establish a cost-benefit calculus to gauge and optimize control protocols, highlighting the fundamental link between predictability of evolution and efficacy of pre-emptive control.

Bringing enzymes to the proximity party

Enzymes are used to treat a wide variety of human diseases, including lysosomal storage disorders, clotting disorders, and cancers. While enzyme therapeutics catalyze highly specific reactions, they often suffer from a lack of cellular or tissue selectivity. Targeting an enzyme to specific disease-driving cells and tissues can mitigate off-target toxicities and provide novel therapeutic avenues to treat otherwise intractable diseases. Targeted enzymes have been used to treat cancer, in which the enzyme is either carefully selected or engineered to reduce on-target off-tumor toxicity, or to treat lysosomal storage disorders in cell types that are not addressed by standard enzyme replacement therapies. In this review, we discuss the different targeted enzyme modalities and comment on the future of these approaches.

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.

Virus-assisted directed evolution of biomolecules

Directed evolution is a powerful technique that uses principles of natural evolution to enable the development of biomolecules with novel functions. However, the slow pace of natural evolution does not support the demand for rapidly generating new biomolecular functions in the laboratory. Viruses offer a unique path to design fast laboratory evolution experiments, owing to their innate ability to evolve much more rapidly than most living organisms, facilitated by a smaller genome size that tolerate a high frequency of mutations, as well as a fast rate of replication. These attributes offer a great opportunity to evolve various biomolecules by linking their activity to the replication of a suitable virus. This review highlights the recent advances in the application of virus-assisted directed evolution of designer biomolecules in both prokaryotic and eukaryotic cells.

Prediction and design of protease enzyme specificity using a structure-aware graph convolutional network

Site-specific proteolysis by the enzymatic cleavage of small linear sequence motifs is a key posttranslational modification involved in physiology and disease. The ability to robustly and rapidly predict protease-substrate specificity would also enable targeted proteolytic cleavage by designed proteases. Current methods for predicting protease specificity are limited to sequence pattern recognition in experimentally derived cleavage data obtained for libraries of potential substrates and generated separately for each protease variant. We reasoned that a more semantically rich and robust model of protease specificity could be developed by incorporating the energetics of molecular interactions between protease and substrates into machine learning workflows. We present Protein Graph Convolutional Network (PGCN), which develops a physically grounded, structure-based molecular interaction graph representation that describes molecular topology and interaction energetics to predict enzyme specificity. We show that PGCN accurately predicts the specificity landscapes of several variants of two model proteases. Node and edge ablation tests identified key graph elements for specificity prediction, some of which are consistent with known biochemical constraints for protease:substrate recognition. We used a pretrained PGCN model to guide the design of protease libraries for cleaving two noncanonical substrates, and found good agreement with experimental cleavage results. Importantly, the model can accurately assess designs featuring diversity at positions not present in the training data. The described methodology should enable the structure-based prediction of specificity landscapes of a wide variety of proteases and the construction of tailor-made protease editors for site-selectively and irreversibly modifying chosen target proteins.

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.

Recent Advances in β-Glucosidase Sequence and Structure Engineering: A Brief Review

β-glucosidases (BGLs) play a crucial role in the degradation of lignocellulosic biomass as well as in industrial applications such as pharmaceuticals, foods, and flavors. However, the application of BGLs has been largely hindered by issues such as low enzyme activity, product inhibition, low stability, etc. Many approaches have been developed to engineer BGLs to improve these enzymatic characteristics to facilitate industrial production. In this article, we review the recent advances in BGL engineering in the field, including the efforts from our laboratory. We summarize and discuss the BGL engineering studies according to the targeted functions as well as the specific strategies used for BGL engineering.

Genetic engineering of bacteriophages: Key concepts, strategies, and applications

Bacteriophages are the most abundant biological entity in the world and hold a tremendous amount of unexplored genetic information. Since their discovery, phages have drawn a great deal of attention from researchers despite their small size. The development of advanced strategies to modify their genomes and produce engineered phages with desired traits has opened new avenues for their applications. This review presents advanced strategies for developing engineered phages and their potential antibacterial applications in phage therapy, disruption of biofilm, delivery of antimicrobials, use of endolysin as an antibacterial agent, and altering the phage host range. Similarly, engineered phages find applications in eukaryotes as a shuttle for delivering genes and drugs to the targeted cells, and are used in the development of vaccines and facilitating tissue engineering. The use of phage display-based specific peptides for vaccine development, diagnostic tools, and targeted drug delivery is also discussed in this review. The engineered phage-mediated industrial food processing and biocontrol, advanced wastewater treatment, phage-based nano-medicines, and their use as a bio-recognition element for the detection of bacterial pathogens are also part of this review. The genetic engineering approaches hold great potential to accelerate translational phages and research. Overall, this review provides a deep understanding of the ingenious knowledge of phage engineering to move them beyond their innate ability for potential applications.

Antibody-guided proteases enable selective and catalytic degradation of challenging therapeutic targets

The exquisite specificity, natural biological functions, and favorable development properties of antibodies make them highly effective agents as drugs. Monoclonal antibodies are particularly strong as inhibitors of systemically accessible targets where trough-level concentrations can sustain full target occupancy. Yet beyond this pharmacologic wheelhouse, antibodies perform suboptimally for targets of high abundance and those not easily accessible from circulation. Fundamentally, this restraint on broader application is due largely to the stoichiometric nature of their activity - one drug molecule is generally able to inhibit a maximum of two target molecules at a time. Enzymes in contrast are able to catalytically turnover multiple substrates, making them a natural sub-stoichiometric solution for targets of high abundance or in poorly accessible sites of action. However, enzymes have their own limitations as drugs, including, in particular the polypharmacology and broad specificity often seen with native enzymes. In this study, we introduce antibody-guided proteolytic enzymes to enable selective sub-stoichiometric turnover of therapeutic targets. We demonstrate that antibody-mediated substrate targeting can enhance enzyme activity and specificity, with proof of concept for two challenging target proteins, amyloid-β (Aβ) and immunoglobulin G (IgG). This work advances a new biotherapeutic platform that combines the favorable properties of antibodies and proteolytic enzymes to more effectively suppress high-bar therapeutic targets.

Modern non-polarizable force fields diverge in modeling the enzyme-substrate complex of a canonical serine protease

Classical molecular dynamics simulation is a powerful and established method of modern computational chemistry. Being able to obtain accurate information on molecular behavior is crucial to get valuable insights into structure-function relationships that translate into fundamental findings and practical applications. Active sites of enzymes are known to be particularly intricate, therefore, simpler non-polarizable force fields may provide an inaccurate description. In this work, we addressed this hypothesis in a case of a canonical serine triad protease trypsin in its complex with a substrate-mimicking inhibitor. We tested six modern and popular force fields to find that significantly diverging results may be obtained. Amber FB-15 and OPLS-AA/M turned out to model the active site incorrectly. Amber ff19sb and ff15ipq demonstrated mixed performance. The best performing force fields were CHARMM36m and Amber ff99sb-ildn, therefore, they are recommended for use with this and related systems. We speculate that a similar lack of cross-force field convergence may be characteristic of other enzymatic systems. Therefore, we advocate for careful consideration of different force fields in any study within the field of computational enzymology.

Evolution of protease activation and specificity via alpha-2-macroglobulin-mediated covalent capture

Tailoring of the activity and specificity of proteases is critical for their utility across industrial, medical and research purposes. However, engineering or evolving protease catalysts is challenging and often labour intensive. Here, we describe a generic method to accelerate this process based on yeast display. We introduce the protease selection system A2M^cap that covalently captures protease catalysts by repurposed alpha-2-macroglobulin (A2Ms). To demonstrate the utility of A2M^cap for protease engineering we exemplify the directed activity and specificity evolution of six serine proteases. This resulted in a variant of Staphylococcus aureus serin-protease-like (Spl) protease SplB, an enzyme used for recombinant protein processing, that no longer requires activation by N-terminal signal peptide removal. SCHEMA-based domain shuffling was used to map the specificity determining regions of Spl proteases, leading to a chimeric scaffold that supports specificity switching via subdomain exchange. The ability of A2M^cap to overcome key challenges en route to tailor-made proteases suggests easier access to such reagents in the future.

Reprogramming the Cleavage Specificity of Botulinum Neurotoxin Serotype B1

Proteases with reprogrammed specificity for nonnative substrates are highly desired in synthetic biology and biomedicine. However, generating reprogrammed proteases that are orthogonal and highly specific for a new target has been a major challenge. In this work, we sought to expand the versatility of protease systems by engineering an orthogonal botulinum neurotoxin serotype B (BoNT/B) protease that recognizes an orthogonal substrate. We designed and validated an orthogonal BoNT/B protease system in mammalian cells, combining mutations in the protease with compensatory mutations in the protease substrate and incorporating a truncated target sequence and then demonstrated use of this orthogonal BoNT/B protease-substrate combination to regulate complex transcriptional circuitry in mammalian cells. Transposing this platform into yeast, we demonstrated utility of this approach for in vivo protease evolution. We tested this platform with the newly designed orthogonal protease and then used it in a high-throughput screen to identify novel orthogonal protease/protease substrate combinations. While carrying out this work, we also generated new cleavage reporters that could be used to report botulinum toxin protease activity in mammalian cells using simple fluorescent readouts. We envision that these approaches will expand the applications of botulinum protease in new directions and aid in the development of new reprogrammed proteases.

From polymerase engineering to semi-synthetic life: artificial expansion of the central dogma

Nucleic acids have been extensively modified in different moieties to expand the scope of genetic materials in the past few decades. While the development of unnatural base pairs (UBPs) has expanded the genetic information capacity of nucleic acids, the production of synthetic alternatives of DNA and RNA has increased the types of genetic information carriers and introduced novel properties and functionalities into nucleic acids. Moreover, the efforts of tailoring DNA polymerases (DNAPs) and RNA polymerases (RNAPs) to be efficient unnatural nucleic acid polymerases have enabled broad application of these unnatural nucleic acids, ranging from production of stable aptamers to evolution of novel catalysts. The introduction of unnatural nucleic acids into living organisms has also started expanding the central dogma in vivo. In this article, we first summarize the development of unnatural nucleic acids with modifications or alterations in different moieties. The strategies for engineering DNAPs and RNAPs are then extensively reviewed, followed by summarization of predominant polymerase mutants with good activities for synthesizing, reverse transcribing, or even amplifying unnatural nucleic acids. Some recent application examples of unnatural nucleic acids with their polymerases are then introduced. At the end, the approaches of introducing UBPs and synthetic genetic polymers into living organisms for the creation of semi-synthetic organisms are reviewed and discussed.

Exploiting spatial dimensions to enable parallelized continuous directed evolution

Current strategies to improve the throughput of continuous directed evolution technologies often involve complex mechanical fluid-controlling system or robotic platforms, which limits their popularization and application in general laboratories. Inspired by our previous study on bacterial range expansion, in this study, we report a system termed SPACE for rapid and extensively parallelizable evolution of biomolecules by introducing spatial dimensions into the landmark phage-assisted continuous evolution system. Specifically, M13 phages and chemotactic Escherichia coli cells were closely inoculated onto a semisolid agar. The phages came into contact with the expanding front of the bacterial range, and then comigrated with the bacteria. This system leverages competition over space, wherein evolutionary progress is closely associated with the production of spatial patterns, allowing the emergence of improved or new protein functions. In a prototypical problem, SPACE remarkably simplified the process and evolved the promoter recognition of T7 RNA polymerase (RNAP) to a library of 96 random sequences in parallel. These results establish SPACE as a simple, easy to implement, and massively parallelizable platform for continuous directed evolution in general laboratories.

Directed evolution of colE1 plasmid replication compatibility: a fast tractable tunable model for investigating biological orthogonality

Plasmids of the ColE1 family are among the most frequently used in molecular biology. They were adopted early for many biotechnology applications, and as models to study plasmid biology. Their mechanism of replication is well understood, involving specific interactions between a plasmid encoded sense-antisense gene pair (RNAI and RNAII). Due to such mechanism, two plasmids with the same origin cannot be stably maintained in cells-a process known as incompatibility. While mutations in RNAI and RNAII can make colE1 more compatible, there has been no systematic effort to engineer new compatible colE1 origins, which could bypass technical design constraints for multi-plasmid applications. Here, we show that by diversifying loop regions in RNAI (and RNAII), it is possible to select new viable colE1 origins compatible with the wild-type one. We demonstrate that sequence divergence is not sufficient to enable compatibility and pairwise interactions are not an accurate guide for higher order interactions. We identify potential principles to engineer plasmid copy number independently from other regulatory strategies and we propose plasmid compatibility as a tractable model to study biological orthogonality.

Reengineering the specificity of the highly selective Clostridium botulinum protease via directed evolution

The botulinum neurotoxin serotype A (BoNT/A) cuts a single peptide bond in SNAP25, an activity used to treat a wide range of diseases. Reengineering the substrate specificity of BoNT/A’s protease domain (LC/A) could expand its therapeutic applications; however, LC/A’s extended substrate recognition (≈ 60 residues) challenges conventional approaches. We report a directed evolution method for retargeting LC/A and retaining its exquisite specificity. The resultant eight-mutation LC/A (omLC/A) has improved cleavage specificity and catalytic efficiency (1300- and 120-fold, respectively) for SNAP23 versus SNAP25 compared to a previously reported LC/A variant. Importantly, the BoNT/A holotoxin equipped with omLC/A retains its ability to form full-length holotoxin, infiltrate neurons, and cleave SNAP23. The identification of substrate control loops outside BoNT/A’s active site could guide the design of improved BoNT proteases and inhibitors.

Protein Cages: From Fundamentals to Advanced Applications

Proteins that self-assemble into polyhedral shell-like structures are useful molecular containers both in nature and in the laboratory. Here we review efforts to repurpose diverse protein cages, including viral capsids, ferritins, bacterial microcompartments, and designed capsules, as vaccines, drug delivery vehicles, targeted imaging agents, nanoreactors, templates for controlled materials synthesis, building blocks for higher-order architectures, and more. A deep understanding of the principles underlying the construction, function, and evolution of natural systems has been key to tailoring selective cargo encapsulation and interactions with both biological systems and synthetic materials through protein engineering and directed evolution. The ability to adapt and design increasingly sophisticated capsid structures and functions stands to benefit the fields of catalysis, materials science, and medicine.

Biotechnological Innovations and Therapeutic Application of Pediococcus and Lactic Acid Bacteria: The Next-Generation Microorganism

Lactic acid bacteria represent a worthwhile organism within the microbial consortium for the food sector, health, and biotechnological applications. They tend to offer high stability to environmental conditions, with an indicated increase in product yield, alongside their moderate antimicrobial activity. Lack of endotoxins and inclusion bodies, extracellular secretion, and surface display with other unique properties, are all winning attributes of these Gram-positive lactic acid bacteria, of which, Pediococcus is progressively becoming an attractive and promising host, as the next-generation probiotic comparable with other well-known model systems. Here, we presented the biotechnological developments in Pediococcal bacteriocin expression system, contemporary variegated models of Pediococcus and lactic acid bacteria strains as microbial cell factory, most recent applications as possible live delivery vector for use as therapeutics, as well as upsurging challenges and future perspective. With the radical introduction of artificial intelligence and neural network in Synthetic Biology, the microbial usage of lactic acid bacteria as an alternative eco-friendly strain, with safe use properties compared with the already known conventional strains is expected to see an increase in various food and biotechnological applications in years to come as it offers better hope of safety, accuracy, and higher efficiency.

Making the cut with protease engineering

Proteases cut with enviable precision and regulate diverse molecular events in biology. Such qualities drive a seemingly inexhaustible appetite for proteases with new activities and capabilities. Comprising 25% of the total industrial enzyme market, proteases appear in consumer goods, such as detergents, textile processing, and numerous foods; additionally, proteases include 25 US Food and Drug Administration-approved medicines and various research tools. Recent advances in protease engineering strategies address target specificity, catalytic efficiency, and stability. This guide to protease engineering surveys best practices and emerging strategies. We further highlight gaps and flexibilities inherent to each system that suggest opportunities for new technology development along with engineered proteases to solve challenges in proteomics, protein sequencing, and synthetic gene circuits.

Methods to Analyze the Redox Reactivity of Plant Proteins

Proteins can be covalently modified by a broad range of highly reactive chemicals and redox mechanisms. Reversible redox-mediated post-translational modifications of sensitive cysteine thiol groups in proteins impact protein characteristics such as interaction behavior and activity state. Evaluating the response of proteins to redox perturbation or reactive chemical species is critical for understanding the underlying mechanisms involved and their contribution to plant stress physiology. Here we provide a detailed workflow that includes procedures for (i) purification, processing, and analysis of protein samples with redox agents, (ii) determining redox-modulated monomer to oligomer transitions using size exclusion chromatography, and (iii) activity assays for monitoring the impact of redox agents on purified enzymes and in crude extracts from plants subjected to oxidative stress. We exemplified how to apply several of the methods discussed for analyzing redox-sensing metallopeptidases, such as thimet oligopeptidases. We anticipate that these protocols should find broad applications in monitoring biochemical properties of other classes of redox-sensitive plant proteins.

The past, present, and future of enzyme-based therapies

Enzyme-based therapeutics (EBTs) have the potential to tap into an almost unmeasurable amount of enzyme biodiversity and treat myriad conditions. Although EBTs were some of the first biologics used clinically, the rate of development of newer EBTs has lagged behind that of other biologics. Here, we review the history of EBTs, and discuss the state of each class of EBT, their potential clinical advantages, and the unique challenges to their development. Additionally, we discuss key remaining technical barriers that, if addressed, could increase the diversity and rate of the development of EBTs.

Disulfide-compatible phage-assisted continuous evolution in the periplasmic space

The directed evolution of antibodies has yielded important research tools and human therapeutics. The dependence of many antibodies on disulfide bonds for stability has limited the application of continuous evolution technologies to antibodies and other disulfide-containing proteins. Here we describe periplasmic phage-assisted continuous evolution (pPACE), a system for continuous evolution of protein-protein interactions in the disulfide-compatible environment of the E. coli periplasm. We first apply pPACE to rapidly evolve novel noncovalent and covalent interactions between subunits of homodimeric YibK protein and to correct a binding-defective mutant of the anti-GCN4 Ω-graft antibody. We develop an intein-mediated system to select for soluble periplasmic expression in pPACE, leading to an eight-fold increase in soluble expression of the Ω-graft antibody. Finally, we evolve disulfide-containing trastuzumab antibody variants with improved binding to a Her2-like peptide and improved soluble expression. Together, these results demonstrate that pPACE can rapidly optimize proteins containing disulfide bonds, broadening the applicability of continuous evolution.

PROFICS: A bacterial selection system for directed evolution of proteases

Proteases serve as important tools in biotechnology and as valuable drugs or drug targets. Efficient protein engineering methods to study and modulate protease properties are thus of great interest for a plethora of applications. We established PROFICS (PRotease Optimization via Fusion-Inhibited Carbamoyltransferase-based Selection), a bacterial selection system, which enables the optimization of proteases for biotechnology, therapeutics or diagnosis in a simple overnight process. During the PROFICS process, proteases are selected for their ability to specifically cut a tag from a reporter enzyme and leave a native N-terminus. Precise and efficient cleavage after the recognition sequence reverses the phenotype of an Escherichia coli knockout strain deficient in an essential enzyme of pyrimidine synthesis. A toolbox was generated to select for proteases with different preferences for P1' residues (the residue immediately following the cleavage site). The functionality of PROFICS is demonstrated with viral proteases and human caspase-2. PROFICS improved caspase-2 activity up to 25-fold after only one round of mutation and selection. Additionally, we found a significantly improved tolerance for all P1' residues caused by a mutation in a substrate interaction site. We showed that this improved activity enables cells containing the new variant to outgrow cells containing all other mutants, facilitating its straightforward selection. Apart from optimizing enzymatic activity and P1' tolerance, PROFICS can be used to reprogram specificities, erase off-target activity, optimize expression via tags/codon usage, or even to screen for potential drug-resistance-conferring mutations in therapeutic targets such as viral proteases in an unbiased manner.

Phage-Assisted Continuous Evolution and Selection of Enzymes for Chemical Synthesis

Ligand-dependent biosensors are valuable tools for coupling the intracellular concentrations of small molecules to easily detectable readouts such as absorbance, fluorescence, or cell growth. While ligand-dependent biosensors are widely used for monitoring the production of small molecules in engineered cells and for controlling or optimizing biosynthetic pathways, their application to directed evolution for biocatalysts remains underexplored. As a consequence, emerging continuous evolution technologies are rarely applied to biocatalyst evolution. Here, we develop a panel of ligand-dependent biosensors that can detect a range of small molecules. We demonstrate that these biosensors can link enzymatic activity to the production of an essential phage protein to enable biocatalyst-dependent phage-assisted continuous evolution (PACE) and phage-assisted continuous selection (PACS). By combining these phage-based evolution and library selection technologies, we demonstrate that we can evolve enzyme variants with improved and expanded catalytic properties. Finally, we show that the genetic diversity resulting from a highly mutated PACS library is enriched for active enzyme variants with altered substrate scope. These results lay the foundation for using phage-based continuous evolution and selection technologies to engineer biocatalysts with novel substrate scope and reactivity.

Microbial production of riboflavin: Biotechnological advances and perspectives

Riboflavin is an essential nutrient for humans and animals, and its derivatives flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD) are cofactors in the cells. Therefore, riboflavin and its derivatives are widely used in the food, pharmaceutical, nutraceutical and cosmetic industries. Advances in biotechnology have led to a complete shift in the commercial production of riboflavin from chemical synthesis to microbial fermentation. In this review, we provide a comprehensive review of biotechnologies that enhance riboflavin production in microorganisms, as well as representative examples. Firstly, the synthesis pathways and metabolic regulatory processes of riboflavin in microorganisms; and the current strategies and methods of metabolic engineering for riboflavin production are systematically summarized and compared. Secondly, the using of systematic metabolic engineering strategies to enhance riboflavin production is discussed, including laboratory evolution, histological analysis and high-throughput screening. Finally, the challenges for efficient microbial production of riboflavin and the strategies to overcome these challenges are prospected.

Biofilm Management in Wound Care

LEARNING OBJECTIVES

After studying this article, the participant should be able to: 1. Understand the basics of biofilm infection and be able to distinguish between planktonic and biofilm modes of growth. 2. Have a working knowledge of conventional and emerging antibiofilm therapies and their modes of action as they pertain to wound care. 3. Understand the challenges associated with testing and marketing antibiofilm strategies and the context within which these strategies may have effective value.

SUMMARY

The Centers for Disease Control and Prevention estimate for human infectious diseases caused by bacteria with a biofilm phenotype is 65 percent and the National Institutes of Health estimate is closer to 80 percent. Biofilms are hostile microbial aggregates because, within their polymeric matrix cocoons, they are protected from antimicrobial therapy and attack from host defenses. Biofilm-infected wounds, even when closed, show functional deficits such as deficient extracellular matrix and impaired barrier function, which are likely to cause wound recidivism. The management of invasive wound infection often includes systemic antimicrobial therapy in combination with débridement of wounds to a healthy tissue bed as determined by the surgeon who has no way of visualizing the biofilm. The exceedingly high incidence of false-negative cultures for bacteria in a biofilm state leads to missed diagnoses of wound infection. The use of topical and parenteral antimicrobial therapy without wound débridement have had limited impact on decreasing biofilm infection, which remains a major problem in wound care. Current claims to manage wound biofilm infection rest on limited early-stage data. In most cases, such data originate from limited experimental systems that lack host immune defense. In making decisions on the choice of commercial products to manage wound biofilm infection, it is important to critically appreciate the mechanism of action and significance of the relevant experimental system. In this work, the authors critically review different categories of antibiofilm products, with emphasis on their strengths and limitations as evident from the published literature.

Directed Evolution: Methodologies and Applications

Directed evolution aims to expedite the natural evolution process of biological molecules and systems in a test tube through iterative rounds of gene diversifications and library screening/selection. It has become one of the most powerful and widespread tools for engineering improved or novel functions in proteins, metabolic pathways, and even whole genomes. This review describes the commonly used gene diversification strategies, screening/selection methods, and recently developed continuous evolution strategies for directed evolution. Moreover, we highlight some representative applications of directed evolution in engineering nucleic acids, proteins, pathways, genetic circuits, viruses, and whole cells. Finally, we discuss the challenges and future perspectives in directed evolution.

Improved pyrrolysine biosynthesis through phage assisted non-continuous directed evolution of the complete pathway

Pyrrolysine (Pyl, O) exists in nature as the 22^nd proteinogenic amino acid. Despite being a fundamental building block of proteins, studies of Pyl have been hindered by the difficulty and inefficiency of both its chemical and biological syntheses. Here, we improve Pyl biosynthesis via rational engineering and directed evolution of the entire biosynthetic pathway. To accommodate toxicity of Pyl biosynthetic genes in Escherichia coli, we also develop Alternating Phage Assisted Non-Continuous Evolution (Alt-PANCE) that alternates mutagenic and selective phage growths. The evolved pathway provides 32-fold improved yield of Pyl-containing reporter protein compared to the rationally engineered ancestor. Evolved PylB mutants are present at up to 4.5-fold elevated levels inside cells, and show up to 2.2-fold increased protease resistance. This study demonstrates that Alt-PANCE provides a general approach for evolving proteins exhibiting toxic side effects, and further provides an improved pathway capable of producing substantially greater quantities of Pyl-proteins in E. coli.

Pyrrolysine (Pyl) exists in nature as the 22^nd proteinogenic amino acid, but studies of Pyl have been hindered by the difficulty and inefficiency of both its chemical and biological syntheses. Here, the authors developed an improved PANCE approach to evolve the pylBCD pathway for increased production of Pyl proteins in E. coli.

Integrated laboratory evolution and rational engineering of GalP/Glk-dependent Escherichia coli for higher yield and productivity of L-tryptophan biosynthesis

L-Tryptophan (Trp) is a high-value aromatic amino acid with diverse applications in food and pharmaceutical industries. Although production of Trp by engineered Escherichia coli has been extensively studied, the need of multiple precursors for its synthesis and the complex regulations of the biosynthetic pathways make the achievement of a high product yield still very challenging. Metabolic flux analysis suggests that the use of a phosphoenolpyruvate:sugar phosphotransferase system (PTS) independent glucose uptake system, i.e. the galactose permease/glucokinase (GalP/Glk) system, can theoretically double the Trp yield from glucose. To explore this possibility, a PTS- and GalP/Glk-dependent E. coli strain was constructed from a previously rationally developed Trp producer strain S028. However, the growth rate of the S028 mutant was severely impaired. To overcome this problem, promoter screening for modulated gene expression of GalP/Glk was carried out, following by a batch mode of adaptive laboratory evolution (ALE) which resulted in a strain K3 with a similar Trp yield and concentration as S028. In order to obtain a more efficient Trp producer, a novel continuous ALE system was developed by combining CRISPR/Cas9-facilitated in vivo mutagenesis with real-time measurement of cell growth and online monitoring of Trp-mediated fluorescence intensity. With the aid of this automatic system (auto-CGSS), a promising strain T5 was obtained and fed-batch fermentations showed an increase of Trp yield by 19.71% with this strain compared with that obtained by the strain K3 (0.164 vs. 0.137 ​g/g). At the same time, the specific production rate was increased by 52.93% (25.28 vs. 16.53 ​mg/g DCW/h). Two previously engineered enzyme variants AroGD6G-D7A and AnTrpCR378F were integrated into the strain T5, resulting in a highly productive strain T5AA with a Trp yield of 0.195 ​g/g and a specific production rate of 28.83 ​mg/g DCW/h.

Systems for in vivo hypermutation: a quest for scale and depth in directed evolution

Traditional approaches to the directed evolution of genes of interest (GOIs) place constraints on the scale of experimentation and depth of evolutionary search reasonably achieved. Engineered genetic systems that dramatically elevate the mutation of target GOIs in vivo relieve these constraints by enabling continuous evolution, affording new strategies in the exploration of sequence space and fitness landscapes for GOIs. We describe various in vivo hypermutation systems for continuous evolution, discuss how different architectures for in vivo hypermutation facilitate evolutionary search scale and depth in their application to problems in protein evolution and engineering, and outline future opportunities for the field.

Phage-assisted evolution of botulinum neurotoxin proteases with reprogrammed specificity

Although bespoke, sequence-specific proteases have the potential to advance biotechnology and medicine, generation of proteases with tailor-made cleavage specificities remains a major challenge. We developed a phage-assisted protease evolution system with simultaneous positive and negative selection and applied it to three botulinum neurotoxin (BoNT) light-chain proteases. We evolved BoNT/X protease into separate variants that preferentially cleave vesicle-associated membrane protein 4 (VAMP4) and Ykt6, evolved BoNT/F protease to selectively cleave the non-native substrate VAMP7, and evolved BoNT/E protease to cleave phosphatase and tensin homolog (PTEN) but not any natural BoNT protease substrate in neurons. The evolved proteases display large changes in specificity (218- to >11,000,000-fold) and can retain their ability to form holotoxins that self-deliver into primary neurons. These findings establish a versatile platform for reprogramming proteases to selectively cleave new targets of therapeutic interest.

YESS 2.0, a Tunable Platform for Enzyme Evolution, Yields Highly Active TEV Protease Variants

Here we describe YESS 2.0, a highly versatile version of the yeast endoplasmic sequestration screening (YESS) system suitable for engineering and characterizing protein/peptide modifying enzymes such as proteases with desired new activities. By incorporating features that modulate gene transcription as well as substrate and enzyme spatial sequestration, YESS 2.0 achieves a significantly higher operational and dynamic range compared with the original YESS. To showcase the new advantages of YESS 2.0, we improved an already efficient TEV protease variant (TEV-EAV) to obtain a variant (eTEV) with a 2.25-fold higher catalytic efficiency, derived almost entirely from an increase in turnover rate (k_cat). In our analysis, eTEV specifically digests a fusion protein in 2 h at a low 1:200 enzyme to substrate ratio. Structural modeling indicates that the increase in catalytic efficiency of eTEV is likely due to an enhanced interaction between the catalytic Cys151 with the P1 substrate residue (Gln). Furthermore, the modeling showed that the ENLYFQS peptide substrate is buried to a larger extent in the active site of eTEV compared with WT TEV. The new eTEV variant is functionally the fastest TEV variant reported to date and could potentially improve efficiency in any TEV application.