Biosensor-Based Evolution and Elucidation of a Biosynthetic Pathway in Escherichia coli

Engineering of L-threonine and L-proline biosensors by directed evolution of transcriptional regulator SerR and application for high-throughput screening

Amino acids are important bio-based products with a multi-billion-dollar market. The development of efficient high-throughput screening technologies utilizing biosensors is essential for the rapid identification of high-performance amino acid producers. However, there remains a pressing need for biosensors that specifically target certain critical amino acids, such as L-threonine and L-proline. In this study, a novel transcriptional regulator-based biosensor for L-threonine and L-proline was successfully developed, inspired by our new finding that SerE can export L-proline in addition to the previously known L-threonine and L-serine. Through directed evolution of SerR (the corresponding transcriptional regulator of SerE), the mutant SerRF104I which can recognize both L-threonine and L-proline as effectors and effectively distinguish strains with varying production levels was identified. Subsequently, the SerRF104I-based biosensor was employed for high-throughput screening of the superior enzyme mutants of L-homoserine dehydrogenase and γ-glutamyl kinase, which are critical enzymes in the biosynthesis of L-threonine and L-proline, respectively. A total of 25 and 13 novel mutants that increased the titers of L-threonine and L-proline by over 10% were successfully identified. Notably, six of the newly identified mutants exhibited similarities to the most effective mutants reported to date, indicating the promising application potential of the SerRF104I-based biosensor. This study illustrates an effective strategy for the development of transcriptional regulator-based biosensors for amino acids and other chemical compounds.

Biosensor-Assisted Engineering for Diverse Microbial Cellular Physiologies

Recent advancements in biosensor technology have revolutionized the field of microbial engineering, enabling efficient and precise optimization of strains for the production of valuable chemicals. This review comprehensively explores the innovative integration of biosensors to enhance microbial cell factories, with a particular emphasis on the crucial role of high-throughput biosensor-assisted screening. Biosensor-assisted approaches have enabled the identification of novel transporters, the elucidation of underlying transport mechanisms, and the fine-tuning of metabolic pathways for enhanced production. Furthermore, this review illustrates the utilization of biosensors for manipulating cellular behaviors, including interactions with environmental factors, and the reduction of nongenetic cell-to-cell variations. This review highlights the indispensable role of biosensors in advancing the field of microbial engineering through the modulation and exploitation of diverse cellular physiological processes.

Metabolic Engineering of Escherichia coli for High-Level Production of l-Phenylalanine

l-Phenylalanine (l-Phe) is widely used in the food and pharmaceutical industries. However, the biosynthesis of l-Phe using Escherichia coli remains challenging due to its lower tolerance to high concentration of l-Phe. In this study, to efficiently synthesize l-Phe, the l-Phe biosynthetic pathway was reconstructed by expressing the heterologous genes aroK1, aroL1, and pheA1, along with the native genes aroA, aroC, and tyrB in the shikimate-producing strain E. coli SA09, resulting in the engineered strain E. coli PHE03. Subsequently, adaptive evolution was conducted on E. coli PHE03 to enhance its tolerance to high concentrations of l-Phe, resulting in the strain E. coli PHE04, which reduced the cell mortality to 36.2% after 48 h of fermentation. To elucidate the potential mechanisms, transcriptional profiling was conducted, revealing MarA, a DNA-binding transcriptional dual regulator, as playing a crucial role in enhancing cell membrane integrity and fluidity for improving cell tolerance to high concentrations of l-Phe. Finally, the titer, yield, and productivity of l-Phe with E. coli PHE05 overexpressing marA were increased to 80.48 g/L, 0.27 g/g glucose, and 1.68 g/L/h in a 5-L fed-batch fermentation, respectively.

State-of-the-art in engineering small molecule biosensors and their applications in metabolic engineering

Genetically encoded biosensors are crucial for enhancing our understanding of how molecules regulate biological systems. Small molecule biosensors, in particular, help us understand the interaction between chemicals and biological processes. They also accelerate metabolic engineering by increasing screening throughput and eliminating the need for sample preparation through traditional chemical analysis. Additionally, they offer significantly higher spatial and temporal resolution in cellular analyte measurements. In this review, we discuss recent progress in in vivo biosensors and control systems-biosensor-based controllers-for metabolic engineering. We also specifically explore protein-based biosensors that utilize less commonly exploited signaling mechanisms, such as protein stability and induced degradation, compared to more prevalent transcription factor and allosteric regulation mechanism. We propose that these lesser-used mechanisms will be significant for engineering eukaryotic systems and slower-growing prokaryotic systems where protein turnover may facilitate more rapid and reliable measurement and regulation of the current cellular state. Lastly, we emphasize the utilization of cutting-edge and state-of-the-art techniques in the development of protein-based biosensors, achieved through rational design, directed evolution, and collaborative approaches.

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

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

Simple phenylpropanoids: recent advances in biological activities, biosynthetic pathways, and microbial production

Covering: 2000 to 2023Simple phenylpropanoids are a large group of natural products with primary C6-C3 skeletons. They are not only important biomolecules for plant growth but also crucial chemicals for high-value industries, including fragrances, nutraceuticals, biomaterials, and pharmaceuticals. However, with the growing global demand for simple phenylpropanoids, direct plant extraction or chemical synthesis often struggles to meet current needs in terms of yield, titre, cost, and environmental impact. Benefiting from the rapid development of metabolic engineering and synthetic biology, microbial production of natural products from inexpensive and renewable sources provides a feasible solution for sustainable supply. This review outlines the biological activities of simple phenylpropanoids, compares their biosynthetic pathways in different species (plants, bacteria, and fungi), and summarises key research on the microbial production of simple phenylpropanoids over the last decade, with a focus on engineering strategies that seem to hold most potential for further development. Moreover, constructive solutions to the current challenges and future perspectives for industrial production of phenylpropanoids are presented.

Have you tried turning it off and on again? Oscillating selection to enhance fitness-landscape traversal in adaptive laboratory evolution experiments

Adaptive Laboratory Evolution (ALE) is a powerful tool for engineering and understanding microbial physiology. ALE relies on the selection and enrichment of mutations that enable survival or faster growth under a selective condition imposed by the experimental setup. Phenotypic fitness landscapes are often underpinned by complex genotypes involving multiple genes, with combinatorial positive and negative effects on fitness. Such genotype relationships result in mutational fitness landscapes with multiple local fitness maxima and valleys. Traversing local maxima to find a global maximum often requires an individual or sub-population of cells to traverse fitness valleys. Traversing involves gaining mutations that are not adaptive for a given local maximum but are necessary to 'peak shift' to another local maximum, or eventually a global maximum. Despite these relatively well understood evolutionary principles, and the combinatorial genotypes that underlie most metabolic phenotypes, the majority of applied ALE experiments are conducted using constant selection pressures. The use of constant pressure can result in populations becoming trapped within local maxima, and often precludes the attainment of optimum phenotypes associated with global maxima. Here, we argue that oscillating selection pressures is an easily accessible mechanism for traversing fitness landscapes in ALE experiments, and provide theoretical and practical frameworks for implementation.

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.

Transcriptomics and metabolomics analysis of L-phenylalanine overproduction in Escherichia coli

BACKGROUND

Highly efficient production of L-phenylalanine (L-Phe) in E. coli has been achieved by multiple rounds of random mutagenesis and modification of key genes of the shikimate (SHIK) and L-Phe branch pathways. In this study, we performed transcriptomic (16, 24 and 48 h) and metabolomic analyses (8, 16, 24, 32,40, and 48 h) based on time sequences in an engineered E. coli strain producing L-Phe, aiming to reveal the overall changes of metabolic activities during the fermentation process.

RESULTS

The largest biomass increase rate and the highest production rate were seen at 16 h and 24 h of fermentation, respectively reaching 5.9 h^-1 and 2.76 g/L/h, while the maximal L-Phe titer of 60 g/L was accumulated after 48 h of fermentation. The DEGs and metabolites involved in the EMP, PP, TCA, SHIIK and L-Phe-branch pathways showed significant differences at different stages of fermentation. Specifically, the significant upregulation of genes encoding rate-limiting enzymes (aroD and yidB) and key genes (aroF, pheA and aspC) pushed more carbon flux toward the L-Phe synthesis. The RIA changes of a number of important metabolites (DAHP, DHS, DHQ, Glu and PPN) enabled the adequate supply of precursors for high-yield L-Phe production. In addition, other genes related to Glc transport and phosphate metabolism increased the absorption of Glc and contributed to rerouting the carbon flux into the L-Phe-branch.

CONCLUSIONS

Transcriptomic and metabolomic analyses of an L-Phe overproducing strain of E. coli confirmed that precursor supply was not a major limiting factor in this strain, whereas the rational distribution of metabolic fluxes was achieved by redistributing the carbon flux (for example, the expression intensity of the genes tyrB, aspC, aroL and aroF/G/H or the activity of these enzymes is increased to some extent), which is the optimal strategy for enhancing L-Phe production.

Recent advances in screening amino acid overproducers

Microbial fermentation has contributed to 80% of global amino acid production. The key to microbial fermentation is to obtain fermentation strains with high performance to produce target amino acids with a high yield. These strains are primarily derived from screening enormous mutant libraries. Therefore, a high-throughput, rapid, accurate, and universal screening strategy for amino acid overproducers has become a guarantee for obtaining optional amino acid overproducers. In recent years, the rapid development of various novel screening strategies has been witnessed. However, proper analysis and discussion of these innovative technologies are lacking. Here we systematically reviewed recent advances in screening strategies: the auxotrophic-based strategy, the biosensor-based strategy, and the latest translation-based screening strategy. The design principle, application scope, working efficiency, screening accuracy, and universality of these strategies were discussed in detail. The potential for screening nonstandard amino acid overproducers was also analyzed. Guidance for the improvement of future screening strategies is provided in this review, which could expedite the reconstruction of amino acid overproducers and help promote the fermentation industry to reduce cost, increase yield, and improve quality.

Directed evolution of linker helix as an efficient strategy for engineering LysR-type transcriptional regulators as whole-cell biosensors

Whole-cell biosensors based on transcriptional regulators are powerful tools for rapid measurement, high-throughput screening, dynamic metabolic regulation, etc. To optimize the biosensing performance of transcriptional regulator, its effector-binding domain is commonly engineered. However, this strategy is encumbered by the limitation of diversifying such a large domain and the risk of affecting effector specificity. Molecular dynamics simulation of effector binding of LysG (an LysR-type transcriptional regulator, LTTR) suggests the crucial role of the short linker helix (LH) connecting effector- and DNA-binding domains in protein conformational change. Directed evolution of LH efficiently produced LysG variants with extended operational range and unaltered effector specificity. The whole-cell biosensor based on the best LysG^E58V variant outperformed the wild-type LysG in enzyme high-throughput screening and dynamic regulation of l-lysine biosynthetic pathway. LH mutations are suggested to affect DNA binding and facilitate transcriptional activation upon effector binding. LH engineering was also successfully applied to optimize another LTTR BenM for biosensing. Since LTTRs represent the largest family of prokaryotic transcriptional regulators with highly conserved structures, LH engineering is an efficient and universal strategy for development and optimization of whole-cell biosensors.

Engineering of global transcription factor FruR to redirect the carbon flow in Escherichia coli for enhancing L-phenylalanine biosynthesis

BACKGROUND

The catabolite repressor/activator protein (FruR) is a global regulatory protein known to control the expression of several genes concerned with carbon utilization and energy metabolism. This study aimed to illustrate effects of the FruR mutant on the _L-phenylalanine (_L-PHE) producing strain PHE01.

RESULTS

Random mutagenesis libraries of fruR generated in vitro were first integrated into the chromosome of PHE01 by CRISPR/Cas9 technique, and then the best mutant PHE07 (FruR^E173K) was obtained. With this mutant, a final _L-PHE concentration of 70.50 ± 1.02 g/L was achieved, which was 23.34% higher than that of PHE01. To better understand the mechanism, both transcriptomes and metabolomes of PHE07 were carried out and compared to that of PHE01. Specifically, the transcript levels of genes involved in gluconeogenesis pathway, pentose phosphate pathway, Krebs cycle, and glyoxylate shunt were up-regulated in the FruR^E173K mutant, whereas genes aceEF, acnB, and icd were down-regulated. From the metabolite level, the FruR^E173K mutation led to an accumulation of pentose phosphate pathway and Krebs cycle products, whereas the products of pyruvate metabolism pathway: acetyl-CoA and cis-aconic acid, were down-regulated. As a result of the altered metabolic flows, the utilization of carbon sources was improved and the supply of precursors (phosphoenolpyruvate and erythrose 4-phosphate) for _L-PHE biosynthesis was increased, which together led to the enhanced production of _L-PHE.

CONCLUSION

A novel strategy for _L-PHE overproduction by modification of the global transcription factor FruR in E. coli was reported. Especially, these findings expand the scope of pathways affected by the fruR regulon and illustrate its importance as a global regulator in _L-PHE production.

Biosensor and chemo-enzymatic one-pot cascade applications to detect and transform PET-derived terephthalic acid in living cells

Plastic waste imposes a serious problem to the environment and society. Hence, strategies for a circular plastic economy are demanded. One strategy is the engineering of polyester hydrolases toward higher activity for the biotechnological recycling of polyethylene terephthalate (PET). To provide tools for the rapid characterization of PET hydrolases and the detection of degradation products like terephthalic acid (TPA), we coupled a carboxylic acid reductase (CAR) and the luciferase LuxAB. CAR converted TPA into the corresponding aldehydes in Escherichia coli, which yielded bioluminescence that not only semiquantitatively reflected amounts of TPA in hydrolysis samples but is suitable as a high-throughput screening assay to assess PET hydrolase activity. Furthermore, the CAR-catalyzed synthesis of terephthalaldehyde was combined with a reductive amination cascade in a one-pot setup yielding the corresponding diamine, suggesting a new strategy for the transformation of TPA as a product obtained from PET biodegradation.

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First bioreduction of terephthalic acid (TPA) by a carboxylic acid reductase in vivo

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Real-time, high-throughput detection of TPA-derived aldehydes by luciferase LuxAB

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Bioluminescence reflects TPA amounts, assessing (engineered) PET hydrolase activity

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Transformation of TPA into the diamine through chemo-enzymatic one-pot cascade

Engineering Transcription Factor BmoR Mutants for Constructing Multifunctional Alcohol Biosensors

Native transcription factor-based biosensors (TFBs) have the potential for the in situ detection of value-added chemicals or byproducts. However, their industrial application is limited by their ligand promiscuity, low sensitivity, and narrow detection range. Alcohols exhibit similar structures, and no reported TFB can distinguish a specific alcohol from its analogues. Here, we engineered an alcohol-regulated transcription factor, BmoR, and obtained various mutants with remarkable properties. For example, the generated signal-molecule-specific BmoRs could distinguish the constitutional isomers n-butanol and isobutanol, with insensitivity up to an ethanol concentration of 800 mM (36.9 g/L). Linear detection of 0-60 mM of a specific higher alcohol could be achieved in the presence of up to 500 mM (23.0 g/L) ethanol as background noise. Furthermore, we obtained two mutants with raised outputs and over 10⁷-fold higher sensitivity and one mutant with an increased upper detection limit (14.8 g/L n-butanol or isobutanol). Using BmoR as an example, this study systematically explored the ultimate detection limit of a TFB toward its small-molecule ligands, paving the way for in situ detection in biofuel and wine industries.

Research progress of pathway and genome evolution in microbes

Microbes can produce valuable natural products widely applied in medicine, food and other important fields. Nevertheless, it is usually challenging to achieve ideal industrial yields due to low production rate and poor toxicity tolerance. Evolution is a constant mutation and adaptation process used to improve strain performance. Generally speaking, the synthesis of natural products in microbes is often intricate, involving multiple enzymes or multiple pathways. Individual evolution of a certain enzyme often fails to achieve the desired results, and may lead to new rate-limiting nodes that affect the growth of microbes. Therefore, it is inevitable to evolve the biosynthetic pathways or the whole genome. Here, we reviewed the pathway-level evolution including multi-enzyme evolution, regulatory elements engineering, and computer-aided engineering, as well as the genome-level evolution based on several tools, such as genome shuffling and CRISPR/Cas systems. Finally, we also discussed the major challenges faced by in vivo evolution strategies and proposed some potential solutions.

Biosensor for branched-chain amino acid metabolism in yeast and applications in isobutanol and isopentanol production

Branched-chain amino acid (BCAA) metabolism fulfills numerous physiological roles and can be harnessed to produce valuable chemicals. However, the lack of eukaryotic biosensors specific for BCAA-derived products has limited the ability to develop high-throughput screens for strain engineering and metabolic studies. Here, we harness the transcriptional regulator Leu3p from Saccharomyces cerevisiae to develop a genetically encoded biosensor for BCAA metabolism. In one configuration, we use the biosensor to monitor yeast production of isobutanol, an alcohol derived from valine degradation. Small modifications allow us to redeploy Leu3p in another biosensor configuration that monitors production of the leucine-derived alcohol, isopentanol. These biosensor configurations are effective at isolating high-producing strains and identifying enzymes with enhanced activity from screens for branched-chain higher alcohol (BCHA) biosynthesis in mitochondria as well as cytosol. Furthermore, this biosensor has the potential to assist in metabolic studies involving BCAA pathways, and offers a blueprint to develop biosensors for other products derived from BCAA metabolism.

There are a lack of eukaryotic biosensors specific for branched-chain amino acid (BCAA)-derived products. Here the authors report a genetically encoded biosensor for BCAA metabolism based on the Leu3p transcriptional regulator; they use this to monitor yeast production of isobutanol and isopentanol.

Construction of a p-coumaric and ferulic acid auto-regulatory system in Pseudomonas putida KT2440 for protocatechuate production from lignin-derived aromatics

Lignin is a robust and underutilized aromatic heteropolymer on earth. The effective valorization of lignin into value-added products is an attractive research topic in lignocellulosic biorefineries. However, a low bioconversion rate, high process cost, low yield, and high toxicity of substrates hinder its further applications. In this study, an auto-regulatory system was developed and identified as an effective solution to diminish these challenging bottlenecks. First, a lignin-derived standard model aromatic p-coumaric acid (p-CA)-responsive biosensor was successfully developed through a series of rational engineering approaches in Pseudomonas putida KT2440. Furthermore, an auto-regulatory system was established, which rapidly coexpressed key rate-limiting enzymes, 4-hydroxybenzoate hydroxylase, vanillate-O-demethylase, and transporter HcnK under the biosensor element, to convert the mixture of p-CA and ferulic acid into a value-added platform chemical protocatechuate with a titer of 12.7 g/L. This study demonstrated that the constructed auto-regulatory platform is effective and economical for lignin valorization.

Effective use of biosensors for high-throughput library screening for metabolite production

The development of fast and affordable microbial production from recombinant pathways is a challenging endeavor, with targeted improvements difficult to predict due to the complex nature of living systems. To address the limitations in biosynthetic pathways, much work has been done to generate large libraries of various genetic parts (promoters, RBSs, enzymes, etc.) to discover library members that bring about significantly improved levels of metabolite production. To evaluate these large libraries, high throughput approaches are necessary, such as those that rely on biosensors. There are various modes of operation to apply biosensors to library screens that are available at different scales of throughput. The effectiveness of each biosensor-based method is dependent on the pathway or strain to which it is applied, and all approaches have strengths and weaknesses to be carefully considered for any high throughput library screen. In this review, we discuss the various approaches used in biosensor screening for improved metabolite production, focusing on transcription factor-based biosensors.

Low-cost and cleanroom-free prototyping of microfluidic and electrochemical biosensors: Techniques in fabrication and bioconjugation

Integrated microfluidic biosensors enable powerful microscale analyses in biology, physics, and chemistry. However, conventional methods for fabrication of biosensors are dependent on cleanroom-based approaches requiring facilities that are expensive and are limited in access. This is especially prohibitive toward researchers in low- and middle-income countries. In this topical review, we introduce a selection of state-of-the-art, low-cost prototyping approaches of microfluidics devices and miniature sensor electronics for the fabrication of sensor devices, with focus on electrochemical biosensors. Approaches explored include xurography, cleanroom-free soft lithography, paper analytical devices, screen-printing, inkjet printing, and direct ink writing. Also reviewed are selected surface modification strategies for bio-conjugates, as well as examples of applications of low-cost microfabrication in biosensors. We also highlight several factors for consideration when selecting microfabrication methods appropriate for a project. Finally, we share our outlook on the impact of these low-cost prototyping strategies on research and development. Our goal for this review is to provide a starting point for researchers seeking to explore microfluidics and biosensors with lower entry barriers and smaller starting investment, especially ones from low resource settings.

Improvement of a synthetic live bacterial therapeutic for phenylketonuria with biosensor-enabled enzyme engineering

In phenylketonuria (PKU) patients, a genetic defect in the enzyme phenylalanine hydroxylase (PAH) leads to elevated systemic phenylalanine (Phe), which can result in severe neurological impairment. As a treatment for PKU, Escherichia coli Nissle (EcN) strain SYNB1618 was developed under Synlogic's Synthetic Biotic™ platform to degrade Phe from within the gastrointestinal (GI) tract. This clinical-stage engineered strain expresses the Phe-metabolizing enzyme phenylalanine ammonia lyase (PAL), catalyzing the deamination of Phe to the non-toxic product trans-cinnamate (TCA). In the present work, we generate a more potent EcN-based PKU strain through optimization of whole cell PAL activity, using biosensor-based high-throughput screening of mutant PAL libraries. A lead enzyme candidate from this screen is used in the construction of SYNB1934, a chromosomally integrated strain containing the additional Phe-metabolizing and biosafety features found in SYNB1618. Head-to-head, SYNB1934 demonstrates an approximate two-fold increase in in vivo PAL activity compared to SYNB1618.

Modular tuning engineering and versatile applications of genetically encoded biosensors

Genetically encoded biosensors have a diverse range of detectable signals and potential applications in many fields, including metabolism control and high-throughput screening. Their ability to be used in situ with minimal interference to the bioprocess of interest could revolutionize synthetic biology and microbial cell factories. The performance and functions of these biosensors have been extensively studied and have been rapidly improved. We review here current biosensor tuning strategies and attempt to unravel how to obtain ideal biosensor functions through experimental adjustments. Strategies for expanding the biosensor input signals that increases the number of detectable compounds have also been summarized. Finally, different output signals and their practical requirements for biotechnology and biomedical applications and environmental safety concerns have been analyzed. This in-depth review of the responses and regulation mechanisms of genetically encoded biosensors will assist to improve their design and optimization in various application scenarios.

Development of an Haa1-based biosensor for acetic acid sensing in Saccharomyces cerevisiae

Acetic acid is one of the main inhibitors of lignocellulosic hydrolysates and acetic acid tolerance is crucial for the development of robust cell factories for conversion of biomass. As a precursor of acetyl-coenzyme A, it also plays an important role in central carbon metabolism. Thus, monitoring acetic acid levels is a crucial aspect when cultivating yeast. Transcription factor-based biosensors represent useful tools to follow metabolite concentrations. Here, we present the development of an acetic acid biosensor based on the Saccharomyces cerevisiae transcription factor Haa1 that upon binding to acetic acid relocates to the nucleus. In the biosensor, a synthetic transcription factor consisting of Haa1 and BM3R1 from Bacillus megaterium was used to control expression of a reporter gene under a promoter containing BM3R1 binding sites. The biosensor did not drive expression under a promoter containing Haa1 binding sites and responded to acetic acid over a linear range spanning from 10 to 60 mM. To validate its applicability, the biosensor was integrated into acetic acid-producing strains. A direct correlation between biosensor output and acetic acid production was detected. The developed biosensor enables high-throughput screening of strains producing acetic acid and could also be used to investigate acetic acid-tolerant strain libraries.

LuxAB-Based Microbial Cell Factories for the Sensing, Manufacturing and Transformation of Industrial Aldehydes

The application of genetically encoded biosensors enables the detection of small molecules in living cells and has facilitated the characterization of enzymes, their directed evolution and the engineering of (natural) metabolic pathways. In this work, the LuxAB biosensor system from Photorhabdus luminescens was implemented in Escherichia coli to monitor the enzymatic production of aldehydes from primary alcohols and carboxylic acid substrates. A simple high-throughput assay utilized the bacterial luciferase—previously reported to only accept aliphatic long-chain aldehydes—to detect structurally diverse aldehydes, including aromatic and monoterpene aldehydes. LuxAB was used to screen the substrate scopes of three prokaryotic oxidoreductases: an alcohol dehydrogenase (Pseudomonas putida), a choline oxidase variant (Arthrobacter chlorophenolicus) and a carboxylic acid reductase (Mycobacterium marinum). Consequently, high-value aldehydes such as cinnamaldehyde, citral and citronellal could be produced in vivo in up to 80% yield. Furthermore, the dual role of LuxAB as sensor and monooxygenase, emitting bioluminescence through the oxidation of aldehydes to the corresponding carboxylates, promises implementation in artificial enzyme cascades for the synthesis of carboxylic acids. These findings advance the bio-based detection, preparation and transformation of industrially important aldehydes in living cells.

Recent trends in biocatalysis

Biocatalysis has undergone revolutionary progress in the past century. Benefited by the integration of multidisciplinary technologies, natural enzymatic reactions are constantly being explored. Protein engineering gives birth to robust biocatalysts that are widely used in industrial production. These research achievements have gradually constructed a network containing natural enzymatic synthesis pathways and artificially designed enzymatic cascades. Nowadays, the development of artificial intelligence, automation, and ultra-high-throughput technology provides infinite possibilities for the discovery of novel enzymes, enzymatic mechanisms and enzymatic cascades, and gradually complements the lack of remaining key steps in the pathway design of enzymatic total synthesis. Therefore, the research of biocatalysis is gradually moving towards the era of novel technology integration, intelligent manufacturing and enzymatic total synthesis.

Engineering of a Biosensor in Response to Malate in Bacillus licheniformis

Malate is an essential intermediate in the tricarboxylic acid (TCA) cycle; it also has valuable uses in medicine and food. The production of malate with a microbial synthesis method is still in its early stages. One of the key problems in metabolic engineering is that the dynamic and subtle changes in malate are difficult to detect. It remains critical to develop techniques with direct and precise detection of malate in microbial metabolism, which facilitates high-throughput screening of the engineered strains. In this study, a genetically encoded biosensor in response to malate was constructed in B. licheniformis. Key regulator MalR and the action site of the biosensor were first identified. Then, the output of the reporter gene expression was amplified by introducing a strong constitutive promoter and iteratively tuning the action sites. The engineered biosensor can respond to malate from 5 to 15 g/L; within this range, it shows a linear correlation between eGFP fluorescence and malate concentration. This biosensor enrich our toolbox of synthetic biology in pathway engineering for malate production in microorganisms.

Establishment of a Biosensor-based High-Throughput Screening Platform for Tryptophan Overproduction

With the flexibility to fold into complex structures, RNA is well-suited to act as a cellular sensor to recognize environmental fluctuations and respond to changes by regulating the corresponding genes. In this study, we established a high-throughput screening platform to screen tryptophan high-producing strains from a large repertoire of candidate strains. This platform consists of a tryptophan-specific aptamer-based biosensor and fluorescence-activated droplet sorting technology. One mutant strain, with a 165.9% increase in Trp titer compared with the parental strain, was successfully screened from a random mutagenesis library. Sequencing results revealed that a total of 10 single-nucleotide polymorphisms were discovered in the genome of the mutant strain, among which CRP(T29K) was proven to significantly increase Trp production through improving the strain's tolerance of the harsh environment during the stationary phase of the fermentation process. Our results indicate that this strategy has great potential for improving the production of other amino acids in Escherichia coli.

Construction of recombinant Escherichia coli for production of L-phenylalanine-derived compounds

L-phenylalanine is an important amino acid that is widely used in the fields of food flavors and pharmaceuticals. Apart from L-phenylalanine itself, various commercially valuable chemical compounds can also be generated via the L-phenylalanine biosynthesis pathway. Compared with direct extraction from plants or synthesis by chemical reaction, microbial production of L-phenylalanine -derived compounds can overcome the drawbacks of environmental pollution, low yield, and mixtures of stereoisomeric products. Accordingly, increasing intracellular levels of precursors, deregulating feedback inhibition and transcription repression, engineering global regulators and other effective strategies have been implemented to produce different L-phenylalanine -derived compounds in the excellent chassis host Escherichia coli. Finally, this review highlights principal strategies for improving the production of L-phenylalanine and/or its derivatives in E. coli, and discusses the future outlook for further enhancing the titer and yields of these compounds.

Flux redistribution of central carbon metabolism for efficient production of l-tryptophan in Escherichia coli

Microbial production of l-tryptophan (l-trp) has received considerable attention because of its diverse applications in food additives and pharmaceuticals. Overexpression of rate-limiting enzymes and blockage of competing pathways can effectively promote microbial production of l-trp. However, the biosynthetic process remains suboptimal due to imbalanced flux distribution between central carbon and tryptophan metabolism, presenting a major challenge to further improvement of l-trp yield. In this study, we redistributed central carbon metabolism to improve phosphoenolpyruvate (PEP) and erythrose-4-phosphate (E4P) pools in an l-trp producing strain of Escherichia coli for efficient l-trp synthesis. To do this, a phosphoketolase from Bifidobacterium adolescentis was introduced to strengthen E4P formation, and the l-trp titer and yield increased to 10.8 g/L and 0.148 g/g glucose, respectively. Next, the phosphotransferase system was substituted with PEP-independent glucose transport, meditated by a glucose facilitator from Zymomonas mobilis and native glucokinase. This modification improved l-trp yield to 0.164 g/g glucose, concomitant with 58% and 40% decreases of acetate and lactate accumulation, respectively. Then, to channel more central carbon flux to the tryptophan biosynthetic pathway, several metabolic engineering strategies were applied to rewire the PEP-pyruvate-oxaloacetate node. Finally, the constructed strain SX11 produced 41.7 g/L l-trp with an overall yield of 0.227 g/g glucose after 40 h fed-batch fermentation in 5-L bioreactor. This is the highest overall yield of l-trp ever reported from a rationally engineered strain. Our results suggest the flux redistribution of central carbon metabolism to maintain sufficient supply of PEP and E4P is a promising strategy for efficient l-trp biosynthesis, and this strategy would likely also increase the production of other aromatic amino acids and derivatives.

Recent Advances in Metabolically Engineered Microorganisms for the Production of Aromatic Chemicals Derived From Aromatic Amino Acids

Aromatic compounds derived from aromatic amino acids are an important class of diverse chemicals with a wide range of industrial and commercial applications. They are currently produced via petrochemical processes, which are not sustainable and eco-friendly. In the past decades, significant progress has been made in the construction of microbial cell factories capable of effectively converting renewable carbon sources into value-added aromatics. Here, we systematically and comprehensively review the recent advancements in metabolic engineering and synthetic biology in the microbial production of aromatic amino acid derivatives, stilbenes, and benzylisoquinoline alkaloids. The future outlook concerning the engineering of microbial cell factories for the production of aromatic compounds is also discussed.

Developing a highly efficient hydroxytyrosol whole-cell catalyst by de-bottlenecking rate-limiting steps

Hydroxytyrosol is an antioxidant free radical scavenger that is biosynthesized from tyrosine. In metabolic engineering efforts, the use of the mouse tyrosine hydroxylase limits its production. Here, we design an efficient whole-cell catalyst of hydroxytyrosol in Escherichia coli by de-bottlenecking two rate-limiting enzymatic steps. First, we replace the mouse tyrosine hydroxylase by an engineered two-component flavin-dependent monooxygenase HpaBC of E. coli through structure-guided modeling and directed evolution. Next, we elucidate the structure of the Corynebacterium glutamicum VanR regulatory protein complexed with its inducer vanillic acid. By switching its induction specificity from vanillic acid to hydroxytyrosol, VanR is engineered into a hydroxytyrosol biosensor. Then, with this biosensor, we use in vivo-directed evolution to optimize the activity of tyramine oxidase (TYO), the second rate-limiting enzyme in hydroxytyrosol biosynthesis. The final strain reaches a 95% conversion rate of tyrosine. This study demonstrates the effectiveness of sequentially de-bottlenecking rate-limiting steps for whole-cell catalyst development.

Whole-cell catalyst-based hydroxytyrosol production is low. Here, the authors increase the efficiency of its production in E. coli by de-bottlenecking two enzymatic steps catalyzed by monooxygenase and tyramine oxidase using structure-based enzyme redesign or in vivo-directed evolution with the aid of a newly developed biosensor.

Development of a Novel Biosensor-Driven Mutation and Selection System via in situ Growth of Corynebacterium crenatum for the Production of L-Arginine

The high yield mutants require a high-throughput screening method to obtain them quickly. Here, we developed an L-arginine biosensor (ARG-Select) to obtain increased L-arginine producers among a large number of mutant strains. This biosensor was constructed by ArgR protein and argC promoter, and could provide the strain with the output of bacterial growth via the reporter gene sacB; strains with high L-arginine production could survive in 10% sucrose screening. To extend the screening limitation of 10% sucrose, the sensitivity of ArgR protein to L-arginine was decreased. Corynebacterium crenatum SYPA5-5 and its systems pathway engineered strain Cc6 were chosen as the original strains. This biosensor was employed, and L-arginine hyperproducing mutants were screened. Finally, the HArg1 and DArg36 mutants of C. crenatum SYPA5-5 and Cc6 could produce 56.7 and 95.5 g L^-1 of L-arginine, respectively, which represent increases of 35.0 and 13.5%. These results demonstrate that the transcription factor-based biosensor could be applied in high yield strains selection as an effective high-throughput screening method.

Transcription Factor Engineering for High-Throughput Strain Evolution and Organic Acid Bioproduction: A Review

Metabolic regulation of gene expression for the microbial production of fine chemicals, such as organic acids, is an important research topic in post-genomic metabolic engineering. In particular, the ability of transcription factors (TFs) to respond precisely in time and space to various small molecules, signals and stimuli from the internal and external environment is essential for metabolic pathway engineering and strain development. As a key component, TFs are used to construct many biosensors in vivo using synthetic biology methods, which can be used to monitor the concentration of intracellular metabolites in organic acid production that would otherwise remain “invisible” within the intracellular environment. TF-based biosensors also provide a high-throughput screening method for rapid strain evolution. Furthermore, TFs are important global regulators that control the expression levels of key enzymes in organic acid biosynthesis pathways, therefore determining the outcome of metabolic networks. Here we review recent advances in TF identification, engineering, and applications for metabolic engineering, with an emphasis on metabolite monitoring and high-throughput strain evolution for the organic acid bioproduction.

High-Throughput Screening Technology in Industrial Biotechnology

Based on the development of automatic devices and rapid assay methods, various high-throughput screening (HTS) strategies have been established for improving the performance of industrial microorganisms. We discuss the most significant factors that can improve HTS efficiency, including the construction of screening libraries with high diversity and the use of new detection methods to expand the search range and highlight target compounds. We also summarize applications of HTS for enhancing the performance of industrial microorganisms. Current challenges and potential improvements to HTS in industrial biotechnology are discussed in the context of rapid developments in synthetic biology, nanotechnology, and artificial intelligence. Rational integration will be an important driving force for constructing more efficient industrial microorganisms with wider applications in biotechnology.

Emerging molecular biology tools and strategies for engineering natural product biosynthesis

Natural products and their related derivatives play a significant role in drug discovery and have been the inspiration for the design of numerous synthetic bioactive compounds. With recent advances in molecular biology, numerous engineering tools and strategies were established to accelerate natural product synthesis in both academic and industrial settings. However, many obstacles in natural product biosynthesis still exist. For example, the native pathways are not appropriate for research or production; the key enzymes do not have enough activity; the native hosts are not suitable for high-level production. Emerging molecular biology tools and strategies have been developed to not only improve natural product titers but also generate novel bioactive compounds. In this review, we will discuss these emerging molecular biology tools and strategies at three main levels: enzyme level, pathway level, and genome level, and highlight their applications in natural product discovery and development.

Model-guided mechanism discovery and parameter selection for directed evolution

Directed evolution is frequently applied to identify genetic variants with improvements in a single or multiple properties. When used to improve multiple properties simultaneously, a common strategy is to apply alternating rounds of selection criteria to enrich for variants with each desirable trait. In particular, counterselection, or selection against undesired traits rather than for desired ones, has been successfully employed in many studies. Although the sequence and stringency of alternating selective pressures for different traits are known to be highly consequential for the outcome of the screen, the effects of these parameters have not been systematically evaluated. We developed a method for producing a statistical modeling framework to elucidate these effects. The model uses single-cell fluorescence intensity distributions to estimate the proportions of phenotypic populations within a library and then predicts the changes in these proportions depending on specified positive selective or counterselective pressures. We validated the approach using recently described systems for metabolite-responsive bacterial transcription factors and yeast G-protein-coupled receptors. Finally, we applied the model to identify biological sources that exert undesirable selective pressure on libraries during sorting. Notably, these pressures produce substantial artifacts that, if unaddressed, can lead to failure of the screen. This method for model generation can be applied to FACS-based directed evolution experiments to create a quantitative framework that identifies subtle population effects. Such models can guide the choice of experimental design parameters to better enrich for true positive genetic variants and improve the chance of successful directed evolution.

Development of a Vanillate Biosensor for the Vanillin Biosynthesis Pathway in E. coli

The engineered de novo vanillin biosynthesis pathway constructed in Escherichia coli is industrially relevant but limited by the reaction catalyzed by catechol O-methyltransferase, which is intended to catalyze the conversion of protocatechuate to vanillate. To identify alternative O-methyltransferases, we constructed a vanillate sensor based on the Caulobacter crescentus VanR-VanO system. Using an E. coli promoter library, we achieved greater than 14-fold dynamic range in our best rationally constructed sensor. We found that this construct and an evolved variant demonstrate remarkable substrate selectivity, exhibiting no detectable response to the regioisomer byproduct isovanillate and minimal response to structurally similar pathway intermediates. We then harnessed the evolved biosensor to conduct rapid bioprospecting of natural catechol O-methyltransferases and identified three previously uncharacterized but active O-methyltransferases. Collectively, these efforts enrich our knowledge of how biosensing can aid metabolic engineering and constitute the foundation for future improvements in vanillin pathway productivity.

Engineering transcription factor BmoR for screening butanol overproducers

The wild-type transcription factors are sensitive to their corresponding signal molecules. Using wild-type transcription factors as biosensors to screen industrial overproducers are generally impractical because of their narrow detection ranges. This study took transcription factor BmoR as an example and aimed to expand the detection range of BmoR for screening alcohols overproducers. Firstly, a BmoR mutation library was established, and the mutations distributed randomly in all predicted functional domains of BmoR. Structure of BmoR-isobutanol complex were modelled, and isobutanol binding sites were confirmed by site-directed mutagenesis. Subsequently, the effects of the mutations on the detection range or output were confirmed in the BmoR mutants. Four combinatorial mutants containing one increased-detection-range mutation and one enhanced-output mutation were constructed. Compared with wild-type BmoR, F276A/E627N BmoR and D333N/E627N BmoR have wider detection ranges (0-100 mM) and relatively high outputs to the isobutanol added quantitatively or produced intracellularly, demonstrating they have potential for screening isobutanol overproduction strains. This work presented an example of engineering the wild-type transcription factors with physiological significance for industrial utilization.

Establishment of BmoR-based biosensor to screen isobutanol overproducer

Background

Isobutanol, a C4 branched-chain higher alcohol, is regarded as an attractive next-generation transport fuel. Metabolic engineering for efficient isobutanol production has been achieved in many studies. BmoR, an alcohol-regulated transcription factor, mediates a σ⁵⁴-dependent promoter P_bmo of alkane monooxygenase in n-alkane metabolism of Thauera butanivorans and displays high sensitivity to C4–C6 linear alcohols and C3–C5 branched-chain alcohols. In this study, to achieve the high-level production of isobutanol, we established a screening system which relied on the combination of BmoR-based biosensor and isobutanol biosynthetic pathway and then employed it to screen isobutanol overproduction strains from an ARTP mutagenesis library.

Results

Firstly, we constructed and verified a GFP-based BmoR-P_bmo device responding to the isobutanol produced by the host. Then, this screening system was employed to select three mutants which exhibited higher GFP/OD₆₀₀ values than that of wild type. Significantly, GFP/OD₆₀₀ of mutant 10 was 190.7 ± 4.8, a 1.4-fold higher value than that of wild type. Correspondingly, the isobutanol titer of that strain was 1597.6 ± 129.6 mg/L, 2.0-fold higher than the wild type. With the overexpression of upstream pathway genes, the isobutanol production from mutant 10 reached 14.0 ± 1.0 g/L after medium optimization in shake flask. The isobutanol titer reached 56.5 ± 1.8 g/L in a fed-batch production experiment.

Conclusions

This work screened out isobutanol overproduction strains from a mutagenesis library by using a screening system which depended on the combination of BmoR-based biosensor and isobutanol biosynthetic pathway. Optimizing fermentation condition and reinforcing upstream pathway could realize the increase of isobutanol production from the overproducer. Lastly, fed-batch fermentation of the mutant enhanced the isobutanol production to 56.5 ± 1.8 g/L.

In vivo biosensors: mechanisms, development, and applications

In vivo biosensors can recognize and respond to specific cellular stimuli. In recent years, biosensors have been increasingly used in metabolic engineering and synthetic biology, because they can be implemented in synthetic circuits to control the expression of reporter genes in response to specific cellular stimuli, such as a certain metabolite or a change in pH. There are many types of natural sensing devices, which can be generally divided into two main categories: protein-based and nucleic acid-based. Both can be obtained either by directly mining from natural genetic components or by engineering the existing genetic components for novel specificity or improved characteristics. A wide range of new technologies have enabled rapid engineering and discovery of new biosensors, which are paving the way for a new era of biotechnological progress. Here, we review recent advances in the design, optimization, and applications of in vivo biosensors in the field of metabolic engineering and synthetic biology.

Directed evolution of the 3-hydroxypropionic acid production pathway by engineering aldehyde dehydrogenase using a synthetic selection device

3-Hydroxypropionic acid (3-HP) is an important platform chemical, and biological production of 3-HP from glycerol as a carbon source using glycerol dehydratase (GDHt) and aldehyde dehydrogenase (ALDH) has been revealed to be effective because it involves a relatively simple metabolic pathway and exhibits higher yield and productivity than other biosynthetic pathways. Despite the successful attempts of 3-HP production from glycerol, the biological process suffers from problems arising from low activity and inactivation of the two enzymes. To apply the directed evolutionary approach to engineer the 3-HP production system, we constructed a synthetic selection device using a 3-HP-responsive transcription factor and developed a selection approach for screening 3-HP-producing microorganisms. The method was applied to an ALDH library, specifically aldehyde-binding site library of alpha-ketoglutaric semialdehyde dehydrogenase (KGSADH). Only two serial cultures resulted in enrichment of strains showing increased 3-HP production, and an isolated KGSADH variant enzyme exhibited a 2.79-fold higher catalytic efficiency toward its aldehyde substrate than the wild-type one. This approach will provide the simple and efficient tool to engineer the pathway enzymes in metabolic engineering.