Novel biosensors based on flavonoid-responsive transcriptional regulators introduced into Escherichia coli

Ligify: Automated Genome Mining for Ligand-Inducible Transcription Factors

Prokaryotic transcription factors can be repurposed into biosensors for the ligand-inducible control of gene expression, but the landscape of chemical ligands for which biosensors exist is extremely limited. To expand this landscape, we developed Ligify, a web application that leverages information in enzyme reaction databases to predict transcription factors that may be responsive to user-defined chemicals. Candidate transcription factors are then incorporated into automatically generated plasmid sequences that are designed to express GFP in response to the target chemical. Our benchmarking analyses demonstrated that Ligify correctly predicted 31/100 previously validated biosensors and highlighted strategies for further improvement. We then used Ligify to build a panel of genetic circuits that could induce a 47-fold, 5-fold, 9-fold, and 27-fold change in fluorescence in response to D-ribose, L-sorbose, isoeugenol, and 4-vinylphenol, respectively. Ligify should enhance the ability of researchers to quickly develop biosensors for an expanded range of chemicals and is publicly available at https://ligify.groov.bio.

The naringenin-dependent regulator FdeR can be applied as a NIMPLY gate controlled by naringenin and arabinose

The FdeR regulator has been reported as a transcriptional activator dependent on the interaction with naringenin. Previously, FdeR and its cognate promoter were used to construct naringenin-sensitive sensors, though no correlation was associated between the FdeR level of expression and outputs. Therefore, to understand this correlation, we constructed a circuit with FdeR expression adjusted by the arabinose concentration through an AraC-PBAD system and the FdeR-regulated promoter controlling the expression of GFP. We observed a significant reduction in the activity of the target promoter by increasing FdeR expression, indicating that although FdeR has been primarily classified as a transcriptional activator, it also represses transcription. Leveraging the bifunctional feature of FdeR, acting as both transcriptional activator and repressor, we demonstrated that this genetic circuit, when previously switched on by naringenin, can be switched off by inducing an increased FdeR expression level. This engineered system functioned as a NIMPLY gate, effectively decreasing GFP expression by 50% when arabinose was added without removing naringenin from the medium. Exploiting FdeR versatility, this study demonstrates an innovative application of this transcriptional factor for developing novel NIMPLY gates activated by a molecule with low toxicity and nutraceutical properties that may be important for several applications. Graphical Abstract.

Establishing Tunable Genetic Logic Gates with Versatile Dynamic Performance by Varying Regulatory Parameters

Genetic logic gates can be employed in metabolic engineering and synthetic biology to regulate gene expression based on diverse inputs. Design of tunable genetic logic gates with versatile dynamic performance is essential for expanding the usability of these toolsets. Here, using the p-coumaric acid biosensor system as a proof-of-concept, we initially investigated the parameters influencing the buffer (BUF) genetic logic gates. Subsequently, integrating binding sequences from the p-coumaric acid biosensor system and tetR or lacI regulation systems into a constitutive promoter yielded AND genetic logic gates. Additionally, characterized antisense RNAs (asRNAs) or single guide RNAs (sgRNAs) with various repression efficiencies were combined with BUF gates to construct a suite of p-coumaric acid-triggered NOT genetic logic gates. Finally, the designed BUF and NOT gates were combined to construct bifunctional genetic circuits that were subjected to orthogonality evaluation. The genetic logic gates established in this study can serve as valuable tools in future applications of metabolic engineering and synthetic biology.

A versatile regulatory toolkit of arabinose-inducible artificial transcription factors for Enterobacteriaceae

The Gram-negative bacteria Salmonella enterica and Escherichia coli are important model organisms, powerful prokaryotic expression platforms for biotechnological applications, and pathogenic strains constitute major public health threats. To facilitate new approaches for research and biotechnological applications, we here develop a set of arabinose-inducible artificial transcription factors (ATFs) using CRISPR/dCas9 and Arabidopsis-derived DNA-binding proteins to control gene expression in E. coli and Salmonella over a wide inducer concentration range. The transcriptional output of the different ATFs, in particular when expressed in Salmonella rewired for arabinose catabolism, varies over a wide spectrum (up to 35-fold gene activation). As a proof-of-concept, we use the developed ATFs to engineer a Salmonella two-input biosensor strain, SALSOR 0.2 (SALmonella biosenSOR 0.2), which detects and quantifies alkaloid drugs through a measurable fluorescent output. Moreover, we use plant-derived ATFs to regulate β-carotene biosynthesis in E. coli, resulting in ~2.1-fold higher β-carotene production compared to expression of the biosynthesis pathway using a strong constitutive promoter.

Dynamic Metabolic Control: From the Perspective of Regulation Logic

Establishing microbial cell factories has become a sustainable and increasingly promising approach for the synthesis of valuable chemicals. However, introducing heterologous pathways into these cell factories can disrupt the endogenous cellular metabolism, leading to suboptimal production performance. To address this challenge, dynamic pathway regulation has been developed and proven effective in improving microbial biosynthesis. In this review, we summarized typical dynamic regulation strategies based on their control logic. The applicable scenarios for each control logic were highlighted and perspectives for future research direction in this area were discussed.

Protein expression systems combining a flavonoid-inducible promoter and T7 RNA polymerase in Bacillus subtilis

Recombinant protein production must be tightly controlled when overproduction adversely affects the host bacteria. We developed a flavonoid-inducible T7 expression system in Bacillus subtilis using the qdoI promoter to control the T7 RNA polymerase gene (T7 pol). Using the egfp reporter gene controlled by the T7 promoter in a multicopy plasmid, we confirmed that this expression system is tightly regulated by flavonoids, such as quercetin and fisetin. Altering the qdoI promoter for T7 pol control to its hybrid derivative increased the expression level by 6.6-fold at maximum values upon induction. However, faint expression leakage was observed under a noninducing condition. Therefore, the two expression systems with the original qdoI promoter and the hybrid construct can be used selectively, depending on the high control accuracy or production yield required.

Application of Metabolite-Responsive Biosensors for Plant Natural Products Biosynthesis

Plant natural products (PNPs) have shown various pharmaceutical activities, possessing great potential in global markets. Microbial cell factories (MCFs) provide an economical and sustainable alternative for the synthesis of valuable PNPs compared with traditional approaches. However, the heterologous synthetic pathways always lack native regulatory systems, bringing extra burden to PNPs production. To overcome the challenges, biosensors have been exploited and engineered as powerful tools for establishing artificial regulatory networks to control enzyme expression in response to environments. Here, we reviewed the recent progress involved in the application of biosensors that are responsive to PNPs and their precursors. Specifically, the key roles these biosensors played in PNP synthesis pathways, including isoprenoids, flavonoids, stilbenoids and alkaloids, were discussed in detail.

Engineering the Substrate Specificity of Toluene Degrading Enzyme XylM Using Biosensor XylS and Machine Learning

Enzyme engineering using machine learning has been developed in recent years. However, to obtain a large amount of data on enzyme activities for training data, it is necessary to develop a high-throughput and accurate method for evaluating enzyme activities. Here, we examined whether a biosensor-based enzyme engineering method can be applied to machine learning. As a model experiment, we aimed to modify the substrate specificity of XylM, a rate-determining enzyme in a multistep oxidation reaction catalyzed by XylMABC in Pseudomonas putida. XylMABC naturally converts toluene and xylene to benzoic acid and toluic acid, respectively. We aimed to engineer XylM to improve its conversion efficiency to a non-native substrate, 2,6-xylenol. Wild-type XylMABC slightly converted 2,6-xylenol to 3-methylsalicylic acid, which is the ligand of the transcriptional regulator XylS in P. putida. By locating a fluorescent protein gene under the control of the Pm promoter to which XylS binds, a XylS-producing Escherichia coli strain showed higher fluorescence intensity in a 3-methylsalicylic acid concentration-dependent manner. We evaluated the 3-methylsalicylic acid productivity of XylM variants using the fluorescence intensity of the sensor strain as an indicator. The obtained data provided the training data for machine learning for the directed evolution of XylM. Two cycles of machine learning-assisted directed evolution resulted in the acquisition of XylM-D140E-V144K-F243L-N244S with 15 times higher productivity than wild-type XylM. These results demonstrate that an indirect enzyme activity evaluation method using biosensors is sufficiently quantitative and high-throughput to be used as training data for machine learning. The findings expand the versatility of machine learning in enzyme engineering.

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.

Establishing an Autonomous Cascaded Artificial Dynamic (AutoCAD) regulation system for improved pathway performance

Endogenous metabolic pathways in microbial cells are usually precisely controlled by sophisticated regulation networks. However, the lack of such regulations when introducing heterologous pathways in microbial hosts often causes unbalanced enzyme expression and carbon flux distribution, hindering the construction of highly efficient microbial biosynthesis systems. Here, using naringenin as the target compound, we developed an Autonomous Cascaded Artificial Dynamic (AutoCAD) regulation system to automatically coordinate the pathway expression and redirect carbon fluxes for enhanced naringenin production. The AutoCAD regulation system, consisting of both intermediate-based feedforward and product-based feedback control genetic circuits, resulted in a 16.5-fold increase in naringenin titer compared with the static control. Fed-batch fermentation using the strain with AutoCAD regulation further enhanced the naringenin titer to 277.2 mg/L. The AutoCAD regulation system, with intermediate-based feedforward control and product-triggered feedback control, provides a new paradigm of developing complicated cascade dynamic control to engineer heterologous pathways.

Genetic Circuit Design in Rhizobacteria

Genetically engineered plants hold enormous promise for tackling global food security and agricultural sustainability challenges. However, construction of plant-based genetic circuitry is constrained by a lack of well-characterized genetic parts and circuit design rules. In contrast, advances in bacterial synthetic biology have yielded a wealth of sensors, actuators, and other tools that can be used to build bacterial circuitry. As root-colonizing bacteria (rhizobacteria) exert substantial influence over plant health and growth, genetic circuit design in these microorganisms can be used to indirectly engineer plants and accelerate the design-build-test-learn cycle. Here, we outline genetic parts and best practices for designing rhizobacterial circuits, with an emphasis on sensors, actuators, and chassis species that can be used to monitor/control rhizosphere and plant processes.

Surveying the Genetic Design Space for Transcription Factor-Based Metabolite Biosensors: Synthetic Gamma-Aminobutyric Acid and Propionate Biosensors in E. coli Nissle 1917

Engineered probiotic bacteria have been proposed as a next-generation strategy for noninvasively detecting biomarkers in the gastrointestinal tract and interrogating the gut-brain axis. A major challenge impeding the implementation of this strategy has been the difficulty to engineer the necessary whole-cell biosensors. Creation of transcription factor-based biosensors in a clinically-relevant strain often requires significant tuning of the genetic parts and gene expression to achieve the dynamic range and sensitivity required. Here, we propose an approach to efficiently engineer transcription-factor based metabolite biosensors that uses a design prototyping construct to quickly assay the gene expression design space and identify an optimal genetic design. We demonstrate this approach using the probiotic bacterium Escherichia coli Nissle 1917 (EcN) and two neuroactive gut metabolites: the neurotransmitter gamma-aminobutyric acid (GABA) and the short-chain fatty acid propionate. The EcN propionate sensor, utilizing the PrpR transcriptional activator from E. coli, has a large 59-fold dynamic range and >500-fold increased sensitivity that matches biologically-relevant concentrations. Our EcN GABA biosensor uses the GabR transcriptional repressor from Bacillus subtilis and a synthetic GabR-regulated promoter created in this study. This work reports the first known synthetic microbial whole-cell biosensor for GABA, which has an observed 138-fold activation in EcN at biologically-relevant concentrations. Using this rapid design prototyping approach, we engineer highly functional biosensors for specified in vivo metabolite concentrations that achieve a large dynamic range and high output promoter activity upon activation. This strategy may be broadly useful for accelerating the engineering of metabolite biosensors for living diagnostics and therapeutics.

Plant Flavonoid Production in Bacteria and Yeasts

Flavonoids, a major group of secondary metabolites in plants, are promising for use as pharmaceuticals and food supplements due to their health-promoting biological activities. Industrial flavonoid production primarily depends on isolation from plants or organic synthesis, but neither is a cost-effective or sustainable process. In contrast, recombinant microorganisms have significant potential for the cost-effective, sustainable, environmentally friendly, and selective industrial production of flavonoids, making this an attractive alternative to plant-based production or chemical synthesis. Structurally and functionally diverse flavonoids are derived from flavanones such as naringenin, pinocembrin and eriodictyol, the major basic skeletons for flavonoids, by various modifications. The establishment of flavanone-producing microorganisms can therefore be used as a platform for producing various flavonoids. This review summarizes metabolic engineering and synthetic biology strategies for the microbial production of flavanones. In addition, we describe directed evolution strategies based on recently-developed high-throughput screening technologies for the further improvement of flavanone production. We also describe recent progress in the microbial production of structurally and functionally complicated flavonoids via the flavanone modifications. Strategies based on synthetic biology will aid more sophisticated and controlled microbial production of various flavonoids.

Modeling and Optimization of a Molecular Biocontroller for the Regulation of Complex Metabolic Pathways

Achieving optimal production in microbial cell factories, robustness against changing intracellular and environmental perturbations requires the dynamic feedback regulation of the pathway of interest. Here, we consider a merging metabolic pathway motif, which appears in a wide range of metabolic engineering applications, including the production of phenylpropanoids among others. We present an approach to use a realistic model that accounts for in vivo implementation and then propose a methodology based on multiobjective optimization for the optimal tuning of the gene circuit parts composing the biomolecular controller and biosensor devices for a dynamic regulation strategy. We show how this approach can deal with the trade-offs between the performance of the regulated pathway, robustness to perturbations, and stability of the feedback loop. Using realistic models, our results suggest that the strategies for fine-tuning the trade-offs among performance, robustness, and stability in dynamic pathway regulation are complex. It is not always possible to infer them by simple inspection. This renders the use of the multiobjective optimization methodology valuable and necessary.

Metabolic Division in an Escherichia coli Coculture System for Efficient Production of Kaempferide

Kaempferide, a plant-derived natural flavonoid, exhibits excellent pharmacological activities with nutraceutical and medicinal applications in human healthcare. Efficient microbial production of complex flavonoids suffers from metabolic crosstalk and burden, which is a big challenge for synthetic biology. Herein, we identified 4'-O-methyltransferases and divided the artificial biosynthetic pathway of kaempferide into upstream, midstream, and downstream modules. By combining heterologous genes from different sources and fine-tuning the expression, we optimized each module for the production of kaempferide. Furthermore, we designed and evaluated four division patterns of synthetic labor in coculture systems by plug-and-play modularity. The linear division of three modules in a three-strain coculture showed higher productivity of kaempferide than that in two-strain cocultures. The U-shaped division by co-distributing the upstream and downstream modules in one strain led to the best performance of the coculture system, which produced 116.0 ± 3.9 mg/L kaempferide, which was 510, 140, and 50% higher than that produced by the monoculture, two-strain coculture, and three-strain coculture with the linear division, respectively. This is the first report of efficient de novo production of kaempferide in a robust Escherichia coli coculture. The strategy of U-shaped pathway division in the coculture provides a promising way for improving the productivity of valuable and complex natural products.

Harnessing plasmid replication mechanism to enable dynamic control of gene copy in bacteria

Dynamic regulation has been proved efficient in controlling gene expression at transcriptional, translational, and post-translational level. However, the dynamic regulation at gene replication level has been rarely explored so far. In this study, we established dynamic regulation at gene copy level through engineering controllable plasmid replication to dynamically control the gene expression. Prototypic genetic circuits with different control logic were applied to enable diversified dynamic behaviors of gene copy. To explore the applicability of this strategy, the dynamic gene copy control was employed in regulating the biosynthesis of p-coumaric acid, which resulted in an up to 78% increase in p-coumaric acid titer to 1.69 g/L in shake flasks. These results indicated the great potential of applying dynamic gene copy control for engineering biosynthesis of valuable compounds in metabolic engineering.

Synthetic spatial patterning in bacteria: advances based on novel diffusible signals

Engineering multicellular patterning may help in the understanding of some fundamental laws of pattern formation and thus may contribute to the field of developmental biology. Furthermore, advanced spatial control over gene expression may revolutionize fields such as medicine, through organoid or tissue engineering. To date, foundational advances in spatial synthetic biology have often been made in prokaryotes, using artificial gene circuits. In this review, engineered patterns are classified into four levels of increasing complexity, ranging from spatial systems with no diffusible signals to systems with complex multi‐diffusor interactions. This classification highlights how the field was held back by a lack of diffusible components. Consequently, we provide a summary of both previously characterized and some new potential candidate small‐molecule signals that can regulate gene expression in Escherichia coli. These diffusive signals will help synthetic biologists to successfully engineer increasingly intricate, robust and tuneable spatial structures.

Dietary natural products as a potential inhibitor towards advanced glycation end products and hyperglycemic complications: A phytotherapy approaches

Natural products exist in various natural foods such as plants, herbs, fruits, and vegetables. Furthermore, marine life offers potential natural products with significant biological activity. The biochemical reaction is known as advanced glycation end products (AGEs) occurs in the human body. On the other hand, foods are capable of a wide range of processing conditions resulting in the generation of exogenous AGEs adducts. Protein glycation and the formation of advanced glycation end products both contribute to the pathogenesis of hyperglycemic complications. AGEs also play a pivotal role in microvascular and macrovascular complications progression by receptors for advanced glycation end products (RAGE). RAGE activate by AGEs leads to up-regulation of transcriptional factor NF-kB and inflammatory genes. Around the globe, researchers are working in various approaches for therapeutical implications on controlling AGEs mediated disease complications. In this regard, one of the potential promising agents observed with a wide range of AGEs inhibition by food-derived natural products. Current biotechnological tools have been turned to natural products or phytochemicals to manufacture the molecules without compromising their functionality. Metabolic engineering and bioinformatics perspectives have recently enabled the generation of a few potent metabolites with anti-diabetic activity. As the primary focus, this review article will also discuss multidisciplinary approaches that emphasize current advances in anti-diabetic therapeutic action and future perspectives of natural products.

Control of Gene Expression With Quercetin-Responsive Modular Circuits

Control of gene expression is crucial for several biotechnological applications, especially for implementing predictable and controllable genetic circuits. Such circuits are often implemented with a transcriptional regulator activated by a specific signal. These regulators should work independently of the host machinery, with low gratuitous induction or crosstalk with host components. Moreover, the signal should also be orthogonal, recognized only by the regulator with minimal interference with the host operation. In this context, transcriptional regulators activated by plant metabolites as flavonoids emerge as candidates to control gene expression in bacteria. However, engineering novel circuits requires the characterization of the genetic parts (e.g., genes, promoters, ribosome binding sites, and terminators) in the host of interest. Therefore, we decomposed the QdoR regulatory system of B. subtilis, responsive to the flavonoid quercetin, and reassembled its parts into genetic circuits programmed to have different levels of gene expression and noise dependent on the concentration of quercetin. We showed that only one of the promoters regulated by QdoR worked well in E. coli, enabling the construction of other circuits induced by quercetin. The QdoR expression was modulated with constitutive promoters of different transcriptional strengths, leading to low expression levels when QdoR was highly expressed and vice versa. E. coli strains expressing high and low levels of QdoR were mixed and induced with the same quercetin concentration, resulting in two stable populations expressing different levels of their gene reporters. Besides, we demonstrated that the level of QdoR repression generated different noise levels in gene expression dependent on the concentration of quercetin. The circuits presented here can be exploited in applications requiring adjustment of gene expression and noise using a highly available and natural inducer as quercetin.

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.

Recent Advances in Heterologous Synthesis Paving Way for Future Green-Modular Bioindustries: A Review With Special Reference to Isoflavonoids

Isoflavonoids are well-known plant secondary metabolites that have gained importance in recent time due to their multiple nutraceutical and pharmaceutical applications. In plants, isoflavonoids play a role in plant defense and can confer the host plant a competitive advantage to survive and flourish under environmental challenges. In animals, isoflavonoids have been found to interact with multiple signaling pathways and have demonstrated estrogenic, antioxidant and anti-oncologic activities in vivo. The activity of isoflavonoids in the estrogen pathways is such that the class has also been collectively called phytoestrogens. Over 2,400 isoflavonoids, predominantly from legumes, have been identified so far. The biosynthetic pathways of several key isoflavonoids have been established, and the genes and regulatory components involved in the biosynthesis have been characterized. The biosynthesis and accumulation of isoflavonoids in plants are regulated by multiple complex environmental and genetic factors and interactions. Due to this complexity of secondary metabolism regulation, the export and engineering of isoflavonoid biosynthetic pathways into non-endogenous plants are difficult, and instead, the microorganisms Saccharomyces cerevisiae and Escherichia coli have been adapted and engineered for heterologous isoflavonoid synthesis. However, the current ex-planta production approaches have been limited due to slow enzyme kinetics and traditionally laborious genetic engineering methods and require further optimization and development to address the required titers, reaction rates and yield for commercial application. With recent progress in metabolic engineering and the availability of advanced synthetic biology tools, it is envisaged that highly efficient heterologous hosts will soon be engineered to fulfill the growing market demand.

Development of a growth coupled and multi-layered dynamic regulation network balancing malonyl-CoA node to enhance (2S)-naringenin biosynthesis in Escherichia coli

Metabolic heterogeneity and dynamic changes in metabolic fluxes are two inherent characteristics of microbial fermentation that limit the precise control of metabolisms, often leading to impaired cell growth and low productivity. Dynamic metabolic engineering addresses these challenges through the design of multi-layered and multi-genetic dynamic regulation network (DRN) that allow a single cell to autonomously adjust metabolic flux in response to its growth and metabolite accumulation conditions. Here, we developed a growth coupled NCOMB (Naringenin-Coumaric acid-Malonyl-CoA-Balanced) DRN with systematic optimization of (2S)-naringenin and p-coumaric acid-responsive regulation pathways for real-time control of intracellular supply of malonyl-CoA. In this scenario, the acyl carrier protein was used as a novel critical node for fine-tuning malonyl-CoA consumption instead of direct repression of fatty acid synthase commonly employed in previous studies. To do so, we first engineered a multi-layered DRN enabling single cells to concurrently regulate acpH, acpS, acpT, acs, and ACC in malonyl-CoA catabolic and anabolic pathways. Next, the NCOMB DRN was optimized to enhance the synergies between different dynamic regulation layers via a biosensor-based directed evolution strategy. Finally, a high producer obtained from NCOMB DRN approach yielded a 8.7-fold improvement in (2S)-naringenin production (523.7 ± 51.8 mg/L) with a concomitant 20% increase in cell growth compared to the base strain using static strain engineering approach, thus demonstrating the high efficiency of this system for improving pathway production.

Whole-Cell Biosensors Aid Exploration of Vanillin Transmembrane Transport

Transcriptional regulatory protein (TRP)-based whole-cell biosensors are widely used nowadays. Here, they were demonstrated to have great potential application in screening cell efflux and influx pumps for small molecules. First, a vanillin whole-cell biosensor was developed by altering the specificity of a TRP, VanR, and strains with improved vanillin productions that were selected from a random genome mutagenesis library by using this biosensor as a high-throughput screening tool. A high intracellular vanillin concentration was found to accumulate due to the inactivation of the AcrA protein, indicating the involvement of this protein in vanillin efflux. Then, the application of this biosensor was extended to explore efflux and influx pumps, combined with directed genome evolution. Elevated intracellular vanillin levels resulting from efflux pump inactivation or influx pump overexpression could be rapidly detected by the whole-cell biosensor, markedly facilitating the identification of genome targets related to small-molecule transmembrane transport, which is of great importance in metabolic engineering.

Translating New Synthetic Biology Advances for Biosensing Into the Earth and Environmental Sciences

The rapid diversification of synthetic biology tools holds promise in making some classically hard-to-solve environmental problems tractable. Here we review longstanding problems in the Earth and environmental sciences that could be addressed using engineered microbes as micron-scale sensors (biosensors). Biosensors can offer new perspectives on open questions, including understanding microbial behaviors in heterogeneous matrices like soils, sediments, and wastewater systems, tracking cryptic element cycling in the Earth system, and establishing the dynamics of microbe-microbe, microbe-plant, and microbe-material interactions. Before these new tools can reach their potential, however, a suite of biological parts and microbial chassis appropriate for environmental conditions must be developed by the synthetic biology community. This includes diversifying sensing modules to obtain information relevant to environmental questions, creating output signals that allow dynamic reporting from hard-to-image environmental materials, and tuning these sensors so that they reliably function long enough to be useful for environmental studies. Finally, ethical questions related to the use of synthetic biosensors in environmental applications are discussed.

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.

Re-engineering Plant Phenylpropanoid Metabolism With the Aid of Synthetic Biosensors

Phenylpropanoids comprise a large class of specialized plant metabolites with many important applications, including pharmaceuticals, food nutrients, colorants, fragrances, and biofuels. Therefore, much effort has been devoted to manipulating their biosynthesis to produce high yields in a more controlled manner in microbial and plant systems. However, current strategies are prone to significant adverse effects due to pathway complexity, metabolic burden, and metabolite bioactivity, which still hinder the development of tailor-made phenylpropanoid biofactories. This gap could be addressed by the use of biosensors, which are molecular devices capable of sensing specific metabolites and triggering a desired response, as a way to sense the pathway's metabolic status and dynamically regulate its flux based on specific signals. Here, we provide a brief overview of current research on synthetic biology and metabolic engineering approaches to control phenylpropanoid synthesis and phenylpropanoid-related biosensors, advocating for the use of biosensors and genetic circuits as a step forward in plant synthetic biology to develop autonomously-controlled phenylpropanoid-producing plant biofactories.

Efficient Biosynthesis of (2S)-Eriodictyol from (2S)-Naringenin in Saccharomyces cerevisiae through a Combination of Promoter Adjustment and Directed Evolution

The compound (2S)-eriodictyol is an important flavonoid that can be derived from (2S)-naringenin through flavonoid 3'-hydroxylase (F3'H) catalyzation. F3'H is a cytochrome P450 enzyme that requires a cytochrome P450 reductase (CPR) to function. However, P450s have limited applications in industrial scale biosynthesis, owing to their low activity. Here, an efficient SmF3'H and a matched SmCPR were identified from Silybum marianum. To improve the efficiency of SmF3'H, we established a high-throughput detection method for (2S)-eriodictyol, in which the promoter combination of SmF3'H and SmCPR were optimized in Saccharomyces cerevisiae. The results revealed that SmF3'H/SmCPR should be expressed by using promoters with similar and strong expression levels. Furthermore, directed evolution was applied to further improve the efficiency of SmF3'H/SmCPR. With the optimized promoter and mutated combinations SmF3'HD285N/SmCPRI453V, the (2S)-eriodictyol titer was improved to 3.3 g/L, the highest titer in currently available reports. These results indicated that S. cerevisiae is an ideal platform for functional expression of flavonoid related P450 enzymes.

Fermentation and Metabolic Pathway Optimization to De Novo Synthesize (2S)-Naringenin in Escherichia coli

Flavonoids have diverse biological functions in human health. All flavonoids contain a common 2-phenyl chromone structure (C6-C3-C6) as a scaffold. Hence, in using such a scaffold, plenty of highvalue-added flavonoids can be synthesized by chemical or biological catalyzation approaches. (2S)-Naringenin is one of the most commonly used flavonoid scaffolds. However, biosynthesizing (2S)-naringenin has been restricted not only by low production but also by the expensive precursors and inducers that are used. Herein, we established an induction-free system to de novo biosynthesize (2S)-naringenin in Escherichia coli. The tyrosine synthesis pathway was enhanced by overexpressing feedback inhibition-resistant genes (aroG^fbr and tyrA^fbr) and knocking out a repressor gene (tyrR). After optimizing the fermentation medium and conditions, we found that glycerol, glucose, fatty acids, potassium acetate, temperature, and initial pH are important for producing (2S)-naringenin. Using the optimum fermentation medium and conditions, our best strain, Nar-17LM1, could produce 588 mg/l (2S)-naringenin from glucose in a 5-L bioreactor, the highest titer reported to date in E. coli.

De novo design of an intercellular signaling toolbox for multi-channel cell-cell communication and biological computation

Intercellular signaling is indispensable for single cells to form complex biological structures, such as biofilms, tissues and organs. The genetic tools available for engineering intercellular signaling, however, are quite limited. Here we exploit the chemical diversity of biological small molecules to de novo design a genetic toolbox for high-performance, multi-channel cell-cell communications and biological computations. By biosynthetic pathway design for signal molecules, rational engineering of sensing promoters and directed evolution of sensing transcription factors, we obtain six cell-cell signaling channels in bacteria with orthogonality far exceeding the conventional quorum sensing systems and successfully transfer some of them into yeast and human cells. For demonstration, they are applied in cell consortia to generate bacterial colony-patterns using up to four signaling channels simultaneously and to implement distributed bio-computation containing seven different strains as basic units. This intercellular signaling toolbox paves the way for engineering complex multicellularity including artificial ecosystems and smart tissues.

Extended Metabolic Biosensor Design for Dynamic Pathway Regulation of Cell Factories

Transcription factor-based biosensors naturally occur in metabolic pathways to maintain cell growth and to provide a robust response to environmental fluctuations. Extended metabolic biosensors, i.e., the cascading of a bio-conversion pathway and a transcription factor (TF) responsive to the downstream effector metabolite, provide sensing capabilities beyond natural effectors for implementing context-aware synthetic genetic circuits and bio-observers. However, the engineering of such multi-step circuits is challenged by stability and robustness issues. In order to streamline the design of TF-based biosensors in metabolic pathways, here we investigate the response of a genetic circuit combining a TF-based extended metabolic biosensor with an antithetic integral circuit, a feedback controller that achieves robustness against environmental fluctuations. The dynamic response of an extended biosensor-based regulated flavonoid pathway is analyzed in order to address the issues of biosensor tuning of the regulated pathway under industrial biomanufacturing operating constraints.

Protein Engineering for Improving and Diversifying Natural Product Biosynthesis

Proteins found in nature have traditionally been the most frequently used biocatalysts to produce numerous natural products ranging from commodity chemicals to pharmaceuticals. Protein engineering has emerged as a powerful biotechnological toolbox in the development of metabolic engineering, particularly for the biosynthesis of natural products. Recently, protein engineering has become a favored method to improve enzymatic activity, increase enzyme stability, and expand product spectra in natural product biosynthesis. This review summarizes recent advances and typical strategies in protein engineering, highlighting the paramount role of protein engineering in improving and diversifying the biosynthesis of natural products. Future prospects and research directions are also discussed.

Coupling metabolic addiction with negative autoregulation to improve strain stability and pathway yield

Metabolic addiction, an organism that is metabolically addicted with a compound to maintain its growth fitness, is an underexplored area in metabolic engineering. Microbes with heavily engineered pathways or genetic circuits tend to experience metabolic burden leading to degenerated or abortive production phenotype during long-term cultivation or scale-up. A promising solution to combat metabolic instability is to tie up the end-product with an intermediary metabolite that is essential to the growth of the producing host. Here we present a simple strategy to improve both metabolic stability and pathway yield by coupling chemical addiction with negative autoregulatory genetic circuits. Naringenin and lipids compete for the same precursor malonyl-CoA with inversed pathway yield in oleaginous yeast. Negative autoregulation of the lipogenic pathways, enabled by CRISPRi and fatty acid-inducible promoters, repartitions malonyl-CoA to favor flavonoid synthesis and increased naringenin production by 74.8%. With flavonoid-sensing transcriptional activator FdeR and yeast hybrid promoters to control leucine synthesis and cell grwoth fitness, this amino acid feedforward metabolic circuit confers a flavonoid addiction phenotype that selectively enrich the naringenin-producing pupulation in the leucine auxotrophic yeast. The engineered yeast persisted 90.9% of naringenin titer up to 324 generations. Cells without flavonoid addiction regained growth fitness but lost 94.5% of the naringenin titer after cell passage beyond 300 generations. Metabolic addiction and negative autoregulation may be generalized as basic tools to eliminate metabolic heterogeneity, improve strain stability and pathway yield in long-term and large-scale bioproduction.

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.

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.

Soil organic matter attenuates the efficacy of flavonoid-based plant-microbe communication

Plant-microbe interactions are mediated by signaling compounds that control vital plant functions, such as nodulation, defense, and allelopathy. While interruption of signaling is typically attributed to biological processes, potential abiotic controls remain less studied. Here, we show that higher organic carbon (OC) contents in soils repress flavonoid signals by up to 70%. Furthermore, the magnitude of repression is differentially dependent on the chemical structure of the signaling molecule, the availability of metal ions, and the source of the plant-derived OC. Up to 63% of the signaling repression occurs between dissolved OC and flavonoids rather than through flavonoid sorption to particulate OC. In plant experiments, OC interrupts the signaling between a legume and a nitrogen-fixing microbial symbiont, resulting in a 75% decrease in nodule formation. Our results suggest that soil OC decreases the lifetime of flavonoids underlying plant-microbe interactions.

Switching the Ligand Specificity of the Biosensor XylS from meta to para-Toluic Acid through Directed Evolution Exploiting a Dual Selection System

The Pseudomonas putida transcriptional activator XylS induces transcription from the Pm promoter in the presence of several benzoic acid effectors, with m-toluic acid being the most effective and p-toluic acid being much less effective. To alter the effector specificity of XylS, we developed a dual selection system in Escherichia coli, which consists of (i) an artificial operon of an ampicillin resistance gene and tetR under Pm promoter control and (ii) a chloramphenicol resistance gene under tetR promoter control. This system enabled both positive selection to concentrate XylS mutants recognizing a desired ligand and negative selection to exclude undesired XylS mutants such as those recognizing undesired ligands and those that are active without effectors. Application of a random mutagenesis library of xylS to directed evolution that exploited this selection system yielded two XylS mutants that recognize p-toluic acid more effectively. Analysis of each missense mutation indicated three amino acid residues (N7, T74, and I205) important for p-toluic acid recognition. Then, a codon-randomized xylS library at these three residues was similarly screened, resulting in three XylS mutants with increased p-toluic acid-recognition specificity. Analysis of each amino acid substitution revealed that T74P attributes to both m-toluic acid sensitivity loss and subtle p-toluic acid sensitivity acquisition, and that N7R increases the overall ligand-sensitivity. Finally, the combination of these two mutations generated a desirable XylS mutant, which has a high p-toluic acid sensitivity and scarcely responds to m-toluic acid. These results demonstrate the effectiveness of the dual selection system in the directed evolution of biosensors.

Development of an autonomous and bifunctional quorum-sensing circuit for metabolic flux control in engineered Escherichia coli

Metabolic engineering seeks to reprogram microbial cells to efficiently and sustainably produce value-added compounds. Since chemical production can be at odds with the cell's natural objectives, strategies have been developed to balance conflicting goals. For example, dynamic regulation modulates gene expression to favor biomass and metabolite accumulation at low cell densities before diverting key metabolic fluxes toward product formation. To trigger changes in gene expression in a pathway-independent manner without the need for exogenous inducers, researchers have coupled gene expression to quorum-sensing (QS) circuits, which regulate transcription based on cell density. While effective, studies thus far have been limited to one control point. More challenging pathways may require layered dynamic regulation strategies, motivating the development of a generalizable tool for regulating multiple sets of genes. We have developed a QS-based regulation tool that combines components of the lux and esa QS systems to simultaneously and dynamically up- and down-regulate expression of 2 sets of genes. Characterization of the circuit revealed that varying the expression level of 2 QS components leads to predictable changes in switching dynamics and that using components from 2 QS systems allows for independent tuning capability. We applied the regulation tool to successfully address challenges in both the naringenin and salicylic acid synthesis pathways. Through these case studies, we confirmed the benefit of having multiple control points, predictable tuning capabilities, and independently tunable regulation modules.

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.

Robust Characterization of Two Distinct Glutarate Sensing Transcription Factors of Pseudomonas putida l-Lysine Metabolism

A significant bottleneck in synthetic biology involves screening large genetically encoded libraries for desirable phenotypes such as chemical production. However, transcription factor-based biosensors can be leveraged to screen thousands of genetic designs for optimal chemical production in engineered microbes. In this study we characterize two glutarate sensing transcription factors (CsiR and GcdR) from Pseudomonas putida. The genomic contexts of csiR homologues were analyzed, and their DNA binding sites were bioinformatically predicted. Both CsiR and GcdR were purified and shown to bind upstream of their coding sequencing in vitro. CsiR was shown to dissociate from DNA in vitro when exogenous glutarate was added, confirming that it acts as a genetic repressor. Both transcription factors and cognate promoters were then cloned into broad host range vectors to create two glutarate biosensors. Their respective sensing performance features were characterized, and more sensitive derivatives of the GcdR biosensor were created by manipulating the expression of the transcription factor. Sensor vectors were then reintroduced into P. putida and evaluated for their ability to respond to glutarate and various lysine metabolites. Additionally, we developed a novel mathematical approach to describe the usable range of detection for genetically encoded biosensors, which may be broadly useful in future efforts to better characterize biosensor performance.

Genetically encoded biosensors for lignocellulose valorization

Modern society is hugely dependent on finite oil reserves for the supply of fuels and chemicals. Moving our dependence away from these unsustainable oil-based feedstocks to renewable ones is, therefore, a critical factor towards the development of a low carbon bioeconomy. Lignin derived from biomass feedstocks offers great potential as a renewable source of aromatic compounds if methods for its effective valorization can be developed. Synthetic biology and metabolic engineering offer the potential to synergistically enable the development of cell factories with novel biosynthetic routes to valuable chemicals from these sustainable sources. Pathway design and optimization is, however, a major bottleneck due to the lack of high-throughput methods capable of screening large libraries of genetic variants and the metabolic burden associated with bioproduction. Genetically encoded biosensors can provide a solution by transducing the target metabolite concentration into detectable signals to provide high-throughput phenotypic read-outs and allow dynamic pathway regulation. The development and application of biosensors in the discovery and engineering of efficient biocatalytic processes for the degradation, conversion, and valorization of lignin are paving the way towards a sustainable and economically viable biorefinery.

Design and Characterization of Biosensors for the Screening of Modular Assembled Naringenin Biosynthetic Library in Saccharomyces cerevisiae

A common challenge in the assembly and optimization of plant natural product biosynthetic pathways in recombinant hosts is the identification of gene orthologues that will result in best production titers. Here, we describe the modular assembly of a naringenin biosynthetic pathway in Saccharomyces cerevisiae that was facilitated by optimized naringenin-inducible prokaryotic transcription activators used as biosensors. The biosensors were designed and developed in S. cerevisiae by a multiparametric engineering strategy, which further was applied for the in vivo, high-throughput screening of the established yeast library. The workflow for assembling naringenin biosynthetic pathways involved Golden gate-directed combinatorial assembly of genes and promoters, resulting in a strain library ideally covering 972 combinations in S. cerevisiae. For improving the performance of our screening biosensor, a series of fundamental components was optimized, affecting the efficiency of the biosensor such as nuclear localization signal (NLS), the detector module and the effector module. One biosensor (pTDH3_NLS_FdeR-N_tPGK1-pGPM1-fdeO_mcherry_tTDH1-MV2) showed better performance, defined as better dynamic range and sensitivity than others established in this study as well as other previously reported naringenin biosensors. Using this biosensor, we were able to identify a recombinant S. cerevisiae strain as the most efficient candidate for the production of naringenin from the established naringenin biosynthetic library. This approach can be exploited for the optimization of other metabolites derived from the flavonoid biosynthetic pathways and more importantly employed in the characterization of putative flavonoid biosynthetic genes.

Recent advancement of engineering microbial hosts for the biotechnological production of flavonoids

Flavonoids are polyphenols that are important organic chemicals in plants. The health benefits of flavonoids that result in high commercial values make them attractive targets for large-scale production through bioengineering. Strategies such as engineering a flavonoid biosynthetic pathway in microbial hosts provide an alternative way to produce these beneficial compounds. Escherichia coli, Saccharomyces cerevisiae and Streptomyces sp. are among the expression systems used to produce recombinant products, as well as for the production of flavonoid compounds through various bioengineering approaches including clustered regularly interspaced short palindromic repeats (CRISPR)-based genome engineering and genetically encoded biosensors to detect flavonoid biosynthesis. In this study, we review the recent advances in engineering model microbial hosts as being the factory to produce targeted flavonoid compounds.

Chimeric LysR-Type Transcriptional Biosensors for Customizing Ligand Specificity Profiles toward Flavonoids

Transcriptional biosensors enable key applications in both metabolic engineering and synthetic biology. Due to nature's immense variety of metabolites, these applications require biosensors with a ligand specificity profile customized to the researcher's needs. In this work, chimeric biosensors were created by introducing parts of a donor regulatory circuit from Sinorhizobium meliloti, delivering the desired luteolin-specific response, into a nonspecific biosensor chassis from Herbaspirillum seropedicae. Two strategies were evaluated for the development of chimeric LysR-type biosensors with customized ligand specificity profiles toward three closely related flavonoids, naringenin, apigenin, and luteolin. In the first strategy, chimeric promoter regions were constructed at the biosensor effector module, while in the second strategy, chimeric transcription factors were created at the biosensor detector module. Via both strategies, the biosensor repertoire was expanded with luteolin-specific chimeric biosensors demonstrating a variety of response curves and ligand specificity profiles. Starting from the nonspecific biosensor chassis, a shift from 27.5% to 95.3% luteolin specificity was achieved with the created chimeric biosensors. Both strategies provide a compelling, faster, and more accessible route for the customization of biosensor ligand specificity, compared to de novo design and construction of each biosensor circuit for every desired ligand specificity.

Development of a Synthetic 3-Dehydroshikimate Biosensor in Escherichia coli for Metabolite Monitoring and Genetic Screening

Biosensors for target metabolites provide powerful high-throughput screening tools to obtain high-performing strains. However, well-characterized metabolite-sensing modules are often unavailable and limit rapid access to the robust biosensors with successful applications. In this study, we developed a strategy of transcriptome-assisted metabolite-sensing (TAMES) to identify the target metabolite-sensing module based on selectively comparative transcriptome analysis between the target metabolite producing and nonproducing strains and a subsequent quantative reverse transcription (RT-qPCR) evaluation. The strategy was applied to identify the sensing module cusR that responds positively to the metabolite 3-dehydroshikimate (DHS) and proved it was effective to narrow down the candidates. We further constructed the cusR-based synthetic biosensor and established the DHS biosensor-based high-throughput screening (HTS) platform to screen higher DHS-producing strains and successfully increased DHS production by more than 90%. This study demonstrated that the TAMES strategy was effective at exploiting the metabolite-sensing transcriptional regulator, and this could likely be extended to develop the biosensor-based HTS platforms for other molecules.