A synthetic microbial biosensor for high-throughput screening of lactam biocatalysts

Advances in microbial production of geraniol: from metabolic engineering to potential industrial applications

Geraniol, an acyclic monoterpene alcohol, has significant potential applications in various fields, including: food, cosmetics, biofuels, and pharmaceuticals. However, the current sources of geraniol mainly include plant tissue extraction or chemical synthesis, which are unsustainable and suffer severely from high energy consumption and severe environmental problems. The process of microbial production of geraniol has recently undergone vigorous development. Particularly, the sustainable construction of recombinant Escherichia coli (13.2 g/L) and Saccharomyces cerevisiae (5.5 g/L) laid a solid foundation for the microbial production of geraniol. In this review, recent advances in the development of geraniol-producing strains, including: metabolic pathway construction, key enzyme improvement, genetic modification strategies, and cytotoxicity alleviation, are critically summarized. Furthermore, the key challenges in scaling up geraniol production and future perspectives for the development of robust geraniol-producing strains are suggested. This review provides theoretical guidance for the industrial production of geraniol using microbial cell factories.

Hosts engineering and in vitro enzymatic synthesis for the discovery of novel natural products and their derivatives

Novel natural products (NPs) and their derivatives are important sources for drug discovery, which have been broadly applied in the fields of agriculture, livestock, and medicine, making the synthesis of NPs and their derivatives necessarily important. In recent years, biosynthesis technology has received increasing attention due to its high efficiency in the synthesis of high value-added novel products and its advantages of green, environmental protection, and controllability. In this review, the technological advances of biosynthesis strategies in the discovery of novel NPs and their derivatives are outlined, with an emphasis on two areas of host engineering and in vitro enzymatic synthesis. In terms of hosts engineering, multiple microorganisms, including Streptomyces, Aspergillus, and Penicillium, have been used as the biosynthetic gene clusters (BGCs) provider and host strain for the expression of BGCs to discover new compounds over the past years. In addition, the use of in vitro enzymatic synthesis strategy to generate novel compounds such as triterpenoid saponins and flavonoids is also hereby described.

Investigating and Engineering an 1,2-Propanediol-Responsive Transcription Factor-Based Biosensor

Transcription factor (TF)-based biosensors have arisen as powerful tools in the advancement of metabolic engineering. However, with the emergence of numerous bioproduction targets, the variety of applicable TF-based biosensors remains severely limited. In this study, we investigated and engineered an 1,2-propanediol (1,2-PD)-responsive transcription activator, PocR, from Salmonella typhimurium to enrich the current biosensor repertoire. Heterologous characterization of PocR in E. coli revealed a significantly limited operational range and dynamic range, primarily attributed to the leaky binding between PocR and its corresponding promoters in the absence of the 1,2-PD inducer. Promiscuity characterization uncovered the minor responsiveness of PocR toward glycerol and 1,2-butanediol (1,2-BD). Using AlphaFold-predicted structure and protein mutagenesis, we preliminarily explored the underlying mechanism of PocR. Based on the investigated mechanism, we engineered a PcoR-F46R/G105D variant with an altered inducer specificity to glycerol, as well as a PocR-ARE (Q107A/S192R/A203E) variant with nearly a 4-fold higher dynamic range (6.7-fold activation) and a 20-fold wider operational range (0-20 mM 1,2-PD). Finally, we successfully converted PocR to a repressor through promoter engineering. Integrating the activation and repression functions established a versatile 1,2-PD-induced bifunctional regulation system based on PocR-ARE. Our work showcases the exploration and exploitation of an underexplored type of transcriptional activator capable of recruiting RNA polymerase. It also expands the biosensor toolbox by providing a 1,2-PD-responsive bifunctional regulator and glycerol-responsive activator.

Natural diversity screening, assay development, and characterization of nylon-6 enzymatic depolymerization

Successes in biocatalytic polyester recycling have raised the possibility of deconstructing alternative polymers enzymatically, with polyamide (PA) being a logical target due to the array of amide-cleaving enzymes present in nature. Here, we screen 40 potential natural and engineered nylon-hydrolyzing enzymes (nylonases), using mass spectrometry to quantify eight compounds resulting from enzymatic nylon-6 (PA6) hydrolysis. Comparative time-course reactions incubated at 40-70 °C showcase enzyme-dependent variations in product distributions and extent of PA6 film depolymerization, with significant nylon deconstruction activity appearing rare. The most active nylonase, a NylCK variant we rationally thermostabilized (an N-terminal nucleophile (Ntn) hydrolase, NylCK-TS, Tm = 87.4 °C, 16.4 °C higher than the wild-type), hydrolyzes 0.67 wt% of a PA6 film. Reactions fail to restart after fresh enzyme addition, indicating that substrate-based limitations, such as restricted enzyme access to hydrolysable bonds, prohibit more extensive deconstruction. Overall, this study expands our understanding of nylonase activity distribution, indicates that Ntn hydrolases may have the greatest potential for further development, and identifies key targets for progressing PA6 enzymatic depolymerization, including improving enzyme activity, product selectivity, and enhancing polymer accessibility.

Biosensor-guided discovery and engineering of metabolic enzymes

A variety of chemicals have been produced through metabolic engineering approaches, and enhancing biosynthesis performance can be achieved by using enzymes with high catalytic efficiency. Accordingly, a number of efforts have been made to discover enzymes in nature for various applications. In addition, enzyme engineering approaches have been attempted to suit specific industrial purposes. However, a significant challenge in enzyme discovery and engineering is the efficient screening of enzymes with the desired phenotype from extensive enzyme libraries. To overcome this bottleneck, genetically encoded biosensors have been developed to specifically detect target molecules produced by enzyme activity at the intracellular level. Especially, the biosensors facilitate high-throughput screening (HTS) of targeted enzymes, expanding enzyme discovery and engineering strategies with advances in systems and synthetic biology. This review examines biosensor-guided HTS systems and highlights studies that have utilized these tools to discover enzymes in diverse areas and engineer enzymes to enhance their properties, such as catalytic efficiency, specificity, and stability.

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.

Genetically Encoded Biosensor Engineering for Application in Directed Evolution

Although rational genetic engineering is nowadays the favored method for microbial strain improvement, building up mutant libraries based on directed evolution for improvement is still in many cases the better option. In this regard, the demand for precise and efficient screening methods for mutants with high performance has stimulated the development of biosensor-based high-throughput screening strategies. Genetically encoded biosensors provide powerful tools to couple the desired phenotype to a detectable signal, such as fluorescence and growth rate. Herein, we review recent advances in engineering several classes of biosensors and their applications in directed evolution. Furthermore, we compare and discuss the screening advantages and limitations of two-component biosensors, transcription-factor-based biosensors, and RNA-based biosensors. Engineering these biosensors has focused mainly on modifying the expression level or structure of the biosensor components to optimize the dynamic range, specificity, and detection range. Finally, the applications of biosensors in the evolution of proteins, metabolic pathways, and genome-scale metabolic networks are described. This review provides potential guidance in the design of biosensors and their applications in improving the bioproduction of microbial cell factories through directed evolution.

Multidimensional engineering of Escherichia coli for efficient synthesis of L-tryptophan

Development of microbial cell factory for L-tryptophan (L-trp) production has received widespread attention but still requires extensive efforts due to weak metabolic flux distribution and low yield. Here, the riboswitch-based high-throughput screening (HTS) platform was established to construct a powerful L-trp-producing chassis cell. To facilitate L-trp biosynthesis, gene expression was regulated by promoter and N-terminal coding sequences (NCS) engineering. Modules of degradation, transport and by-product synthesis related to L-trp production were also fine-tuned. Next, a novel transcription factor YihL was excavated to negatively regulate L-trp biosynthesis. Self-regulated promoter-mediated dynamic regulation of branch pathways was performed and cofactor supply was improved for further L-trp biosynthesis. Finally, without extra addition, the yield of strain Trp30 reached 42.5 g/L and 0.178 g/g glucose after 48 h of cultivation in 5-L bioreactor. Overall, strategies described here worked up a promising method combining HTS and multidimensional regulation for developing cell factories for products in interest.

Balancing Redox Homeostasis to Improve l-Cysteine Production in Corynebacterium glutamicum

l-Cysteine is a valuable sulfur-containing amino acid with applications across a wide range of fields. Recently, microbial fermentation has emerged as a method to produce l-cysteine. However, cellular redox stress from high levels of l-cysteine is a bottleneck for achieving efficient production. In this study, we aimed to facilitate l-cysteine biosynthesis by modulating cellular redox homeostasis through the introduction of the natural antioxidant astaxanthin in Corynebacterium glutamicum. To achieve this, we first introduced an exogenous astaxanthin synthesis module in C. glutamicum. Then, an l-cysteine-dependent autonomous bifunctional genetic switch was developed to dynamically regulate the l-cysteine and astaxanthin biosynthesis pathway to maintain cellular redox homeostasis. This regulation system achieved high biosynthesis of astaxanthin, which significantly facilitated l-cysteine production. Finally, engineered strain Cg-10 produced 8.45 g/L l-cysteine and 95 mg/L astaxanthin in a 5 L bioreactor, both of which are the highest reported levels in C. glutamicum.

TFBMiner: A User-Friendly Command Line Tool for the Rapid Mining of Transcription Factor-Based Biosensors

Transcription factors responsive to small molecules are essential elements in synthetic biology designs. They are often used as genetically encoded biosensors with applications ranging from the detection of environmental contaminants and biomarkers to microbial strain engineering. Despite our efforts to expand the space of compounds that can be detected using biosensors, the identification and characterization of transcription factors and their corresponding inducer molecules remain labor- and time-intensive tasks. Here, we introduce TFBMiner, a new data mining and analysis pipeline that enables the automated and rapid identification of putative metabolite-responsive transcription factor-based biosensors (TFBs). This user-friendly command line tool harnesses a heuristic rule-based model of gene organization to identify both gene clusters involved in the catabolism of user-defined molecules and their associated transcriptional regulators. Ultimately, biosensors are scored based on how well they fit the model, providing wet-lab scientists with a ranked list of candidates that can be experimentally tested. We validated the pipeline using a set of molecules for which TFBs have been reported previously, including sensors responding to sugars, amino acids, and aromatic compounds, among others. We further demonstrated the utility of TFBMiner by identifying a biosensor for S-mandelic acid, an aromatic compound for which a responsive transcription factor had not been found previously. Using a combinatorial library of mandelate-producing microbial strains, the newly identified biosensor was able to distinguish between low- and high-producing strain candidates. This work will aid in the unraveling of metabolite-responsive microbial gene regulatory networks and expand the synthetic biology toolbox to allow for the construction of more sophisticated self-regulating biosynthetic pathways.

Dynamic upregulation of the rate-limiting enzyme for valerolactam biosynthesis in Corynebacterium glutamicum

Valerolactam is a monomer used to manufacture high-value nylon-5 and nylon-6,5. However, the biological production of valerolactam has been limited by the inadequate efficiency of enzymes to cyclize 5-aminovaleric acid to produce valerolactam. In this study, we engineered Corynebacterium glutamicum with a valerolactam biosynthetic pathway consisting of DavAB from Pseudomonas putida to convert L-lysine to 5-aminovaleric acid and β-alanine CoA transferase (Act) from Clostridium propionicum to produce valerolactam from 5-aminovaleric acid. Most of the L-lysine was converted into 5-aminovaleric acid, but promoter optimization and increasing the copy number of Act were insufficient to significantly improve the titer of valerolactam. To eliminate the bottleneck at Act, we designed a dynamic upregulation system (a positive feedback loop based on the valerolactam biosensor ChnR/Pb). We used laboratory evolution to engineer ChnR/Pb to have higher sensitivity and a higher dynamic output range, and the engineered ChnR-B1/Pb-E1 system was used to overexpress the rate-limiting enzymes (Act/ORF26/CaiC) that cyclize 5-aminovaleric acid into valerolactam. In glucose fed-batch culture, we obtained 12.33 g/L valerolactam from the dynamic upregulation of Act, 11.88 g/L using ORF26, and 12.15 g/L using CaiC. Our engineered biosensor (ChnR-B1/Pb-E1 system) was also sensitive to 0.01-100 mM caprolactam, which suggests that this dynamic upregulation system can be used to enhance caprolactam biosynthesis in the future.

Development of a Transcriptional Factor PuuR-Based Putrescine-Specific Biosensor in Corynebacterium glutamicum

Corynebacterium glutamicum is regarded as an industrially important microbial cell factory and is widely used to produce various value-added chemicals. Because of the importance of C. glutamicum applications, current research is increasingly focusing on developing C. glutamicum synthetic biology platforms. Because of its ability to condense with adipic acid to synthesize the industrial plastic nylon-46, putrescine is an important platform compound of industrial interest. Developing a high-throughput putrescine biosensor can aid in accelerating the design-build-test cycle of cell factories (production strains) to achieve high putrescine-generating strain production in C. glutamicum. This study developed a putrescine-specific biosensor (pSenPuuR) in C. glutamicum using Escherichia coli-derived transcriptional factor PuuR. The response characteristics of the biosensor to putrescine were further improved by optimizing the genetic components of pSenPuuR, such as the response promoter, reporter protein, and promoter for controlling PuuR expression. According to the findings of the study, pSenPuuR has the potential to be used to assess putrescine production in C. glutamicum and is suitable for high-throughput genetic variant screening.

Recent advances in microbial production of diamines, aminocarboxylic acids, and diacids as potential platform chemicals and bio-based polyamides monomers

Recently, bio-based manufacturing processes of value-added platform chemicals and polymers in biorefineries using renewable resources have extensively been developed for sustainable and carbon dioxide (CO₂) neutral-based industry. Among them, bio-based diamines, aminocarboxylic acids, and diacids have been used as monomers for the synthesis of polyamides having different carbon numbers and ubiquitous and versatile industrial polymers and also as precursors for further chemical and biological processes to afford valuable chemicals. Until now, these platform bio-chemicals have successfully been produced by biorefinery processes employing enzymes and/or microbial host strains as main catalysts. In this review, we discuss recent advances in bio-based production of diamines, aminocarboxylic acids, and diacids, which has been developed and improved by systems metabolic engineering strategies of microbial consortia and optimization of microbial conversion processes including whole cell bioconversion and direct fermentative production.

Current advances and research prospects for agricultural and industrial uses of microbial strains available in world collections

Microorganisms are an important component of the ecosystem and have an enormous impact on human lives. Moreover, microorganisms are considered to have desirable effects on other co-existing species in a variety of habitats, such as agriculture and industries. In this way, they also have enormous environmental applications. Hence, collections of microorganisms with specific traits are a crucial step in developing new technologies to harness the microbial potential. Microbial culture collections (MCCs) are a repository for the preservation of a large variety of microbial species distributed throughout the world. In this context, culture collections (CCs) and microbial biological resource centres (mBRCs) are vital for the safeguarding and circulation of biological resources, as well as for the progress of the life sciences. Ex situ conservation of microorganisms tagged with specific traits in the collections is the crucial step in developing new technologies to harness their potential. Type strains are mainly used in taxonomic study, whereas reference strains are used for agricultural, biotechnological, pharmaceutical research and commercial work. Despite the tremendous potential in microbiological research, little effort has been made in the true sense to harness the potential of conserved microorganisms. This review highlights (1) the importance of available global microbial collections for man and (2) the use of these resources in different research and applications in agriculture, biotechnology, and industry. In addition, an extensive literature survey was carried out on preserved microorganisms from different collection centres using the Web of Science (WoS) and SCOPUS. This review also emphasizes knowledge gaps and future perspectives. Finally, this study provides a critical analysis of the current and future roles of microorganisms available in culture collections for different sustainable agricultural and industrial applications. This work highlights target-specific potential microbial strains that have multiple important metabolic and genetic traits for future research and use.

Kinetic compartmentalization by unnatural reaction for itaconate production

Physical compartmentalization of metabolism using membranous organelles in eukaryotes is helpful for chemical biosynthesis to ensure the availability of substrates from competitive metabolic reactions. Bacterial hosts lack such a membranous system, which is one of the major limitations for efficient metabolic engineering. Here, we employ kinetic compartmentalization with the introduction of an unnatural enzymatic reaction by an engineered enzyme as an alternative strategy to enable substrate availability from competitive reactions through kinetic isolation of metabolic pathways. As a proof of concept, we kinetically isolate the itaconate synthetic pathway from the tricarboxylic acid cycle in Escherichia coli, which is natively separated by mitochondrial membranes in Aspergillus terreus. Specifically, 2-methylcitrate dehydratase is engineered to alternatively catalyze citrate and kinetically secure cis-aconitate for efficient production using a high-throughput screening system. Itaconate production can be significantly improved with kinetic compartmentalization and its strategy has the potential to be widely applicable.

Novel High-Throughput DNA Part Characterization Technique for Synthetic Biology

This study presents a novel DNA part characterization technique that increases throughput by combinatorial DNA part assembly, solid plate-based quantitative fluorescence assay for phenotyping, and barcode tagging-based long-read sequencing for genotyping. We confirmed that the fluorescence intensities of colonies on plates were comparable to fluorescence at the single-cell level from a high-end, flow-cytometry device and developed a high-throughput image analysis pipeline. The barcode tagging-based long-read sequencing technique enabled rapid identification of all DNA parts and their combinations with a single sequencing experiment. Using our techniques, forty-four DNA parts (21 promoters and 23 RBSs) were successfully characterized in 72 h without any automated equipment. We anticipate that this high-throughput and easy-to-use part characterization technique will contribute to increasing part diversity and be useful for building genetic circuits and metabolic pathways in synthetic biology.

Transcription Factor-Based Biosensors for Detecting Pathogens

Microorganisms are omnipresent and inseparable from our life. Many of them are beneficial to humans, while some are not. Importantly, foods and beverages are susceptible to microbial contamination, with their toxins causing illnesses and even death in some cases. Therefore, monitoring and detecting harmful microorganisms are critical to ensuring human health and safety. For several decades, many methods have been developed to detect and monitor microorganisms and their toxicants. Conventionally, nucleic acid analysis and antibody-based analysis were used to detect pathogens. Additionally, diverse chromatographic methods were employed to detect toxins based on their chemical and structural properties. However, conventional techniques have several disadvantages concerning analysis time, sensitivity, and expense. With the advances in biotechnology, new approaches to detect pathogens and toxins have been reported to compensate for the disadvantages of conventional analysis from different research fields, including electrochemistry, nanotechnology, and molecular biology. Among them, we focused on the recent studies of transcription factor (TF)-based biosensors to detect microorganisms and discuss their perspectives and applications. Additionally, the other biosensors for detecting microorganisms reported in recent studies were also introduced in this review.

Development of miniaturized agar based assays in 96-well microplates applicable to high-throughput screening of industrially valuable microorganisms

High-throughput screening (HTS) is a present-day approach for assaying thousands of cultures in parallel. This miniaturization allows rapid screening of large number of microorganims capable of producing bio-based materials thereby meeting the demands of the ever evolving food, pharmaceutical and cosmetic industry. In this study, agar-based assays for phosphate solubilization, cellulose degradation and lactic acid production were developed in 96-well microplates using Biomek FX^P Automated Liquid Handling system. Techno-economic analysis from this study reveals the lower overall cost per assay using HTS as compared to conventional Petri plate assays. Though automated liquid handling workstations have been used to perform liquid-based assays, there are very few studies which report their use for agar-based microplate assays. These findings thus corroborate the establishment of rapid and efficient miniaturized, qualitative agar-based screening methods for identifying microorganisms with potential for commercial application.

Model-Guided Metabolic Rewiring for Gamma-Aminobutyric Acid and Butyrolactam Biosynthesis in Corynebacterium glutamicum ATCC13032

Gamma-aminobutyric acid (GABA) can be used as a bioactive component in the pharmaceutical industry and a precursor for the synthesis of butyrolactam, which functions as a monomer for the synthesis of polyamide 4 (nylon 4) with improved thermal stability and high biodegradability. The bio-based fermentation production of chemicals using microbes as a cell factory provides an alternative to replace petrochemical-based processes. Here, we performed model-guided metabolic engineering of Corynebacterium glutamicum for GABA and butyrolactam fermentation. A GABA biosynthetic pathway was constructed using a bi-cistronic expression cassette containing mutant glutamate decarboxylase. An in silico simulation showed that the increase in the flux from acetyl-CoA to α-ketoglutarate and the decrease in the flux from α-ketoglutarate to succinate drove more flux toward GABA biosynthesis. The TCA cycle was reconstructed by increasing the expression of acn and icd genes and deleting the sucCD gene. Blocking GABA catabolism and rewiring the transport system of GABA further improved GABA production. An acetyl-CoA-dependent pathway for in vivo butyrolactam biosynthesis was constructed by overexpressing act-encoding ß-alanine CoA transferase. In fed-batch fermentation, the engineered strains produced 23.07 g/L of GABA with a yield of 0.52 mol/mol from glucose and 4.58 g/L of butyrolactam. The metabolic engineering strategies can be used for genetic modification of industrial strains to produce target chemicals from α-ketoglutarate as a precursor, and the engineered strains will be useful to synthesize the bio-based monomer of polyamide 4 from renewable resources.

Non-Thermal Plasma Jet-Treated Medium Induces Selective Cytotoxicity against Mycobacterium tuberculosis-Infected Macrophages

Plasma-treated media (PTM) serve as an adjuvant therapy to postoperatively remove residual cancerous lesions. We speculated that PTM could selectively kill cells infected with Mycobacterium tuberculosis (Mtb) and remove postoperative residual tuberculous lesions. We therefore investigated the effects of a medium exposed to a non-thermal plasma jet on the suppression of intracellular Mtb replication, cell death, signaling, and selectivity. We propose that PTM elevates the levels of the detoxifying enzymes, glutathione peroxidase, catalase, and ataxia-telangiectasia mutated serine/threonine kinase and increases intracellular reactive oxygen species production in Mtb-infected cells. The bacterial load was significantly decreased in spleen and lung tissues and single-cell suspensions from mice intraperitoneally injected with PTM compared with saline and untreated medium. Therefore, PTM has the potential as a novel treatment that can eliminate residual Mtb-infected cells after infected tissues are surgically resected.

Construction and Application of a High-Throughput In Vivo Screening Platform for the Evolution of Nitrile Metabolism-Related Enzymes Based on a Desensitized Repressive Biosensor

Transcription factor (TF)-based biosensors are expected to serve as powerful tools for the high-throughput screening of biocatalytic systems; however, most of them respond to ligands in a narrow concentration range, which limits their application. In this study, we constructed a heterogenous niacin biosensor using the repressive TF BsNadR and its target promoters from Bacillus subtilis. The fine-tunable output of the niacin biosensor was expanded to a wide range of niacin concentrations (0-50 mM) through desensitization engineering, which was suitable for the accurate identification of differences in enzyme activity. Structural mechanism analysis indicated that weakening the affinity of BsNadR with the ligand niacin and with DNA alters its regulatory properties. Based on the desensitized niacin biosensor, a high-throughput in vivo screening platform was developed for evolving nitrile metabolism-related enzymes. The evolved nitrilase, amidase, and nitrile hydratase with 6.6-, 2.1-, and 21.3-fold improvements in activity were achieved, respectively. In addition, these mutants also exhibited elevated activity toward other cognate substrates, indicating the broad applicability of the screening platform. This study not only provided a universal high-throughput screening platform for different nitrile metabolism-related enzymes but also demonstrated the advantages of repressive biosensors and the vital role of desensitization engineering of the TF in the development of high-throughput screening platforms for enzymes.

Integrating dynamics into enzyme engineering

Enzyme engineering has become a widely adopted practice in research labs and industry. In parallel, the past decades have seen tremendous strides in characterizing the dynamics of proteins, using a growing array of methodologies. Importantly, links have been established between the dynamics of proteins and their function. Characterizing the dynamics of an enzyme prior to, and following, its engineering is beginning to inform on the potential of 'dynamic engineering', i.e. the rational modification of protein dynamics to alter enzyme function. Here we examine the state of knowledge at the intersection of enzyme engineering and protein dynamics, describe current challenges and highlight pioneering work in the nascent area of dynamic engineering.

Selective immobilization of his-tagged phosphomannose isomerase on Ni chelated nanoparticles with good reusability and activity

In this paper, self-stable precipitation polymerization was used to prepare the enzyme-immobilized microsphere composite. Phosphomannose isomerase (PMI) with His-tag was successfully immobilized on Ni 2+ charged pyridine-derived particles. The maximum amount of PMI immobilized on such particles was ~ 184 mg/g. Compared with the free enzymes, the activity of the immobilized enzymes has been significantly improved. In addition, the immoblized enzymes showed a much better thermostability than free enzymes. At the same time, the immobilized enzymes can be reused for multiple reaction cycles. We have observed that the enzyme activity did not decrease significantly after 6 cycles of repeating usages. We conclude that the pyridine-derived particles can be used to selectively immobilize His-tagged enzymes, which can couple the enzyme purification and catalysis steps and improve the efficiency of enzyme-catalyzed industrial processes.

Force in numbers: high-throughput screening approaches to unlock microbial transport

Biological membranes are inherently complex, making transport processes in microbial cell factories a significant bottleneck. Lack of knowledge on transport proteins' characteristics and the need for advanced technical equipment often hamper transporter identification and optimization. For these reasons, moving away from individual characterization and towards high-throughput mining, engineering, and screening of transporters is an increasingly attractive approach. Superior transporters can be selected from large libraries by coupling their activity to growth, for substrates that function as feedstocks or toxic compounds. Other compounds can be screened thanks to recent advances in the design and deployment of synthetic genetic circuits (biosensors). Furthermore, novel strategies are rapidly increasing the repertoire of biomolecule transporters susceptible to high-throughput selection methods.

Development of a Transcription Factor-Based Diamine Biosensor in Corynebacterium glutamicum

Diamines serve as major platform chemicals that can be employed to a variety of industrial scenarios, particularly as monomers for polymer synthesis. High-throughput sensors for diamine biosynthesis can greatly improve the biological production of diamines. Here, we identified and characterized a transcription factor-driven biosensor for putrescine and cadaverine in Corynebacterium glutamicum. The transcriptional TetR-family regulatory protein CgmR (CGL2612) is used for the specific detection of diamine compounds. This study also improved the dynamic range and the sensitivity to putrescine by systematically optimizing genetic components of pSenPut. By a single cell-based screening strategy for a library of CgmR with random mutations, this study obtained the most sensitive variant CgmR_I152T, which possessed an experimentally determined limit of detection (LoD) of ≤0.2 mM, a K of 11.4 mM, and a utility of 720. Using this highly sensitive putrescine biosensor pSenPut_I152T, we demonstrated that CgmRI_152T can be used as a sensor to detect putrescine produced biologically in a C. glutamicum system. This high sensitivity and the range of CgmR will be an influential tool for rewiring metabolic circuits and facilitating the directed evolution of recombinant strains toward the biological synthesis of diamine compounds.

A roadmap for metagenomic enzyme discovery

Covering: up to 2021Metagenomics has yielded massive amounts of sequencing data offering a glimpse into the biosynthetic potential of the uncultivated microbial majority. While genome-resolved information about microbial communities from nearly every environment on earth is now available, the ability to accurately predict biocatalytic functions directly from sequencing data remains challenging. Compared to primary metabolic pathways, enzymes involved in secondary metabolism often catalyze specialized reactions with diverse substrates, making these pathways rich resources for the discovery of new enzymology. To date, functional insights gained from studies on environmental DNA (eDNA) have largely relied on PCR- or activity-based screening of eDNA fragments cloned in fosmid or cosmid libraries. As an alternative, shotgun metagenomics holds underexplored potential for the discovery of new enzymes directly from eDNA by avoiding common biases introduced through PCR- or activity-guided functional metagenomics workflows. However, inferring new enzyme functions directly from eDNA is similar to searching for a 'needle in a haystack' without direct links between genotype and phenotype. The goal of this review is to provide a roadmap to navigate shotgun metagenomic sequencing data and identify new candidate biosynthetic enzymes. We cover both computational and experimental strategies to mine metagenomes and explore protein sequence space with a spotlight on natural product biosynthesis. Specifically, we compare in silico methods for enzyme discovery including phylogenetics, sequence similarity networks, genomic context, 3D structure-based approaches, and machine learning techniques. We also discuss various experimental strategies to test computational predictions including heterologous expression and screening. Finally, we provide an outlook for future directions in the field with an emphasis on meta-omics, single-cell genomics, cell-free expression systems, and sequence-independent methods.

Directed Evolution Methods for Enzyme Engineering

Enzymes underpin the processes required for most biotransformations. However, natural enzymes are often not optimal for biotechnological uses and must be engineered for improved activity, specificity and stability. A rich and growing variety of wet-lab methods have been developed by researchers over decades to accomplish this goal. In this review such methods and their specific attributes are examined.

The iSplit GFP assay detects intracellular recombinant proteins in Bacillus subtilis

BACKGROUND

Bacillus subtilis is one of the most important microorganisms for recombinant protein production. It possesses the GRAS (generally recognized as safe) status and a potent protein secretion capacity. Secretory protein production greatly facilitates downstream processing and thus significantly reduces costs. However, not all heterologous proteins are secreted and intracellular production poses difficulties for quantification. To tackle this problem, we have established a so-called intracellular split GFP (iSplit GFP) assay in B. subtilis as a tool for the in vivo protein detection during expression in batch cultures and at a single-cell level. For the iSplit GFP assay, the eleventh β-sheet of sfGFP is fused to a target protein and can complement a detector protein consisting of the respective truncated sfGFP (GFP1-10) to form fluorescent holo-GFP.

RESULTS

As proof of concept, the GFP11-tag was fused C-terminally to the E. coli β-glucuronidase GUS, resulting in fusion protein GUS11. Variable GUS and GUS11 production levels in B. subtilis were achieved by varying the ribosome binding site via spacers of increasing lengths (4-12 nucleotides) for the GUS-encoding gene. Differences in intracellular enzyme accumulation were determined by measuring the GUS11 enzymatic activity and subsequently by adding the detector protein to respective cell extracts. Moreover, the detector protein was co-produced with the GUS11 using a two-plasmid system, which enabled the in vivo detection and online monitoring of glucuronidase production. Using this system in combination with flow cytometry and microfluidics, we were able to monitor protein production at a single-cell level thus yielding information about intracellular protein distribution and culture heterogeneity.

CONCLUSION

Our results demonstrate that the iSplit GFP assay is suitable for the detection, quantification and online monitoring of recombinant protein production in B. subtilis during cultivation as well as for analyzing production heterogeneity and intracellular localization at a single-cell level.

P450-driven plastic-degrading synthetic bacteria

Plastic contamination currently threatens a wide variety of ecosystems and presents damaging repercussions and negative consequences for many wildlife species. Sustainable plastic waste management is an important approach to environmental protection and a necessity in the current life cycle of plastics in nature. Plastic biodegradation by microorganisms is a notable possible solution. This opinion article includes a proposal to use hypothetical P450 enzymes with an engineered active site as potent trigger biocatalysts to biodegrade polyethylene (PE) via in-chain hydroxylation into smaller products of linear aliphatic alcohols and alkanoic acids based on cascade enzymatic reactions. Furthermore, we propose the adoption of P450 into plastic-eating synthetic bacteria for PE biodegradation. This strategy can be applicable to other dense plastics, such as polypropylene (PP) and polystyrene (PS).

Transcription-Factor-based Biosensor Engineering for Applications in Synthetic Biology

Transcription-factor-based biosensors (TFBs) are often used for metabolite detection, adaptive evolution, and metabolic flux control. However, designing TFBs with superior performance for applications in synthetic biology remains challenging. Specifically, natural TFBs often do not meet real-time detection requirements owing to their slow response times and inappropriate dynamic ranges, detection ranges, sensitivity, and selectivity. Furthermore, designing and optimizing complex dynamic regulation networks is time-consuming and labor-intensive. This Review highlights TFB-based applications and recent engineering strategies ranging from traditional trial-and-error approaches to novel computer-model-based rational design approaches. The limitations of the applications and these engineering strategies are additionally reviewed.

An Integrated Cofactor/Co-Product Recycling Cascade for the Biosynthesis of Nylon Monomers from Cycloalkylamines

We report a highly atom-efficient integrated cofactor/co-product recycling cascade employing cycloalkylamines as multifaceted starting materials for the synthesis of nylon building blocks. Reactions using E. coli whole cells as well as purified enzymes produced excellent conversions ranging from >80 and 95 % into desired ω-amino acids, respectively with varying substrate concentrations. The applicability of this tandem biocatalytic cascade was demonstrated to produce the corresponding lactams by employing engineered biocatalysts. For instance, ϵ-caprolactam, a valuable polymer building block was synthesized with 75 % conversion from 10 mM cyclohexylamine by employing whole-cell biocatalysts. This cascade could be an alternative for bio-based production of ω-amino acids and corresponding lactam compounds.

Biosensor-Based Directed Evolution of Methanol Dehydrogenase from Lysinibacillus xylanilyticus

Methanol dehydrogenase (Mdh), is a crucial enzyme for utilizing methane and methanol as carbon and energy sources in methylotrophy and synthetic methylotrophy. Engineering of Mdh, especially NAD-dependent Mdh, has thus been actively investigated to enhance methanol conversion. However, its poor catalytic activity and low methanol affinity limit its wider application. In this study, we applied a transcriptional factor-based biosensor for the direct evolution of Mdh from Lysinibacillus xylanilyticus (Lxmdh), which has a relatively high turnover rate and low K_M value compared to other wild-type NAD-dependent Mdhs. A random mutant library of Lxmdh was constructed in Escherichia coli and was screened using formaldehyde-detectable biosensors by incubation with low methanol concentrations. Positive clones showing higher fluorescence were selected by fluorescence-activated cell sorting (FACS) system, and their catalytic activities toward methanol were evaluated. The successfully isolated mutants E396V, K318N, and K46E showed high activity, particularly at very low methanol concentrations. In kinetic analysis, mutant E396V, K318N, and K46E had superior methanol conversion efficiency, with 79-, 23-, and 3-fold improvements compared to the wild-type, respectively. These mutant enzymes could thus be useful for engineering synthetic methylotrophy and for enhancing methanol conversion to various useful products.

Transcription factor-based biosensors: a molecular-guided approach for natural product engineering

Natural products and their derivatives offer a rich source of chemical and biological diversity; however, traditional engineering of their biosynthetic pathways to improve yields and access to unnatural derivatives requires a precise understanding of their enzymatic processes. High-throughput screening platforms based on allosteric transcription-factor based biosensors can be leveraged to overcome the screening bottleneck to enable searching through large libraries of pathway/strain variants. Herein, the development and application of engineered allosteric transcription factor-based biosensors is described that enable optimization of precursor availability, product titers, and downstream product tailoring for advancing the natural product bioeconomy. We discuss recent successes for tailoring biosensor design, including computationally-based approaches, and present our future outlook with the integration of cell-free technologies and de novo protein design for rapidly generating biosensor tools.

Antagonistic Control of Genetic Circuit Performance for Rapid Analysis of Targeted Enzyme Activity in Living Cells

Genetic circuits have been developed for quantitative measurement of enzyme activity, metabolic engineering of strain development, and dynamic regulation of microbial cells. A genetic circuit consists of several bio-elements, including enzymes and regulatory cassettes, that can generate the desired output signal, which is then used as a precise criterion for enzyme screening and engineering. Antagonists and inhibitors are small molecules with inhibitory effects on regulators and enzymes, respectively. In this study, an antagonist and an inhibitor were applied to a genetic circuit for a dynamic detection range. We developed a genetic circuit relying on regulators and enzymes, allowing for straightforward control of its output signal without additional genetic modification. We used para-nitrophenol and alanine as an antagonist of DmpR and inhibitor of tyrosine phenol-lyase, respectively. We show that the antagonist resets the detection range of the genetic circuit similarly to a resistor in an electrical logic circuit. These biological resistors in genetic circuits can be used as a rapid and precise controller of variable outputs with minimal circuit configuration.

Engineering sensitivity and specificity of AraC-based biosensors responsive to triacetic acid lactone and orsellinic acid

We previously described the design of triacetic acid lactone (TAL) biosensor ‘AraC-TAL1’, based on the AraC regulatory protein. Although useful as a tool to screen for enhanced TAL biosynthesis, this variant shows elevated background (leaky) expression, poor sensitivity and relaxed inducer specificity, including responsiveness to orsellinic acid (OA). More sensitive biosensors specific to either TAL or OA can aid in the study and engineering of polyketide synthases that produce these and similar compounds. In this work, we employed a TetA-based dual-selection to isolate new TAL-responsive AraC variants showing reduced background expression and improved TAL sensitivity. To improve TAL specificity, OA was included as a ‘decoy’ ligand during negative selection, resulting in the isolation of a TAL biosensor that is inhibited by OA. Finally, to engineer OA-specific AraC variants, the iterative protein redesign and optimization computational framework was employed, followed by 2 rounds of directed evolution, resulting in a biosensor with 24-fold improved OA/TAL specificity, relative to AraC-TAL1.

Genetically Encoded Biosensor-Based Screening for Directed Bacteriophage T4 Lysozyme Evolution

Lysozyme is widely used as a model protein in studies of structure–function relationships. Recently, lysozyme has gained attention for use in accelerating the degradation of secondary sludge, which mainly consists of bacteria. However, a high-throughput screening system for lysozyme engineering has not been reported. Here, we present a lysozyme screening system using a genetically encoded biosensor. We first cloned bacteriophage T4 lysozyme (T4L) into a plasmid under control of the araBAD promoter. The plasmid was expressed in Escherichia coli with no toxic effects on growth. Next, we observed that increased soluble T4L expression decreased the fluorescence produced by the genetic enzyme screening system. To investigate T4L evolution based on this finding, we generated a T4L random mutation library, which was screened using the genetic enzyme screening system. Finally, we identified two T4L variants showing 1.4-fold enhanced lytic activity compared to native T4L. To our knowledge, this is the first report describing the use of a genetically encoded biosensor to investigate bacteriophage T4L evolution. Our approach can be used to investigate the evolution of other lysozymes, which will expand the applications of lysozyme.

Synthetic Biology on Acetogenic Bacteria for Highly Efficient Conversion of C1 Gases to Biochemicals

Synthesis gas, which is mainly produced from fossil fuels or biomass gasification, consists of C1 gases such as carbon monoxide, carbon dioxide, and methane as well as hydrogen. Acetogenic bacteria (acetogens) have emerged as an alternative solution to recycle C1 gases by converting them into value-added biochemicals using the Wood-Ljungdahl pathway. Despite the advantage of utilizing acetogens as biocatalysts, it is difficult to develop industrial-scale bioprocesses because of their slow growth rates and low productivities. To solve these problems, conventional approaches to metabolic engineering have been applied; however, there are several limitations owing to the lack of required genetic bioparts for regulating their metabolic pathways. Recently, synthetic biology based on genetic parts, modules, and circuit design has been actively exploited to overcome the limitations in acetogen engineering. This review covers synthetic biology applications to design and build industrial platform acetogens.

A designed whole-cell biosensor for live diagnosis of gut inflammation through nitrate sensing

Microbes reprogrammed using advanced genetic circuits are envisaged as emerging living diagnostics for a wide range of diseases and play key roles in regulating gut microbiota to treat disease-associated symptoms in a non-invasive manner. Here, we developed a designer probiotic Escherichia coli that senses and responds to nitrate, a biomarker of gut inflammation. To this end, we first employed the NarX-NarL two-component regulatory system in E. coli to construct a nitrate-responsive genetic circuit. Next, we optimized the nitrate biosensor for the best performance using measures of sensitivity and specificity. We then introduced this genetic circuit into a probiotic E. coli Nissle 1917. We demonstrated that the designed biosensor can sense elevated nitrate levels during gut inflammation in mice with native gut microbiota. Moreover, using Boolean AND gate, we generated a genetically encoded biosensor for simultaneous sensing of the thiosulfate and nitrate biomarkers, thus increasing the tool's specificity for diagnosing gut inflammation. The nitrate-responsive genetic circuit will enable new approaches for non-invasive diagnostics of inflammation-associated diseases.

Sequence-Based Prediction of Promiscuous Acyltransferase Activity in Hydrolases

Certain hydrolases preferentially catalyze acyl transfer over hydrolysis in an aqueous environment. However, the molecular and structural reasons for this phenomenon are still unclear. Herein, we provide evidence that acyltransferase activity in esterases highly correlates with the hydrophobicity of the substrate-binding pocket. A hydrophobicity scoring system developed in this work allows accurate prediction of promiscuous acyltransferase activity solely from the amino acid sequence of the cap domain. This concept was experimentally verified by systematic investigation of several homologous esterases, leading to the discovery of five novel promiscuous acyltransferases. We also developed a simple yet versatile colorimetric assay for rapid characterization of novel acyltransferases. This study demonstrates that promiscuous acyltransferase activity is not as rare as previously thought and provides access to a vast number of novel acyltransferases with diverse substrate specificity and potential applications.

Genetic Biosensor Design for Natural Product Biosynthesis in Microorganisms

Low yield and low titer of natural products are common issues in natural product biosynthesis through microbial cell factories. One effective way to resolve such bottlenecks is to design genetic biosensors to monitor and regulate the biosynthesis of target natural products. In this review, we evaluate the most recent advances in the design of genetic biosensors for natural product biosynthesis in microorganisms. In particular, we examine strategies for selection of genetic parts and construction principles for the design and evaluation of genetic biosensors. We also review the latest applications of transcription factor- and riboswitch-based genetic biosensors in natural product biosynthesis. Lastly, we discuss challenges and solutions in designing genetic biosensors for the biosynthesis of natural products in microorganisms.