Screening for Enhanced Triacetic Acid Lactone Production by Recombinant Escherichia coli Expressing a Designed Triacetic Acid Lactone Reporter

A hybrid RNA-protein biosensor for high-throughput screening of adenosylcobalamin biosynthesis

Genetically encoded circuits have been successfully utilized to assess and characterize target variants with desirable traits from large mutant libraries. Adenosylcobalamin is an essential coenzyme that is required in many intracellular physiological reactions and is widely used in the pharmaceutical and food industries. High-throughput screening techniques capable of detecting adenosylcobalamin productivity and selecting superior adenosylcobalamin biosynthesis strains are critical for the creation of an effective microbial cell factory for the production of adenosylcobalamin at an industrial level. In this study, we developed an RNA-protein hybrid biosensor whose input part was an endogenous RNA riboswitch to specifically respond to adenosylcobalamin, the inverter part was an orthogonal transcriptional repressor to obtain signal inversion, and the output part was a fluorescent protein to be easily detected. The hybrid biosensor could specifically and positively correlate adenosylcobalamin concentrations to green fluorescent protein expression levels in vivo. This study also improved the operating concentration and dynamic range of the hybrid biosensor by systematic optimization. An individual cell harboring the hybrid biosensor presented over 20-fold higher fluorescence intensity than the negative control. Then, using such a biosensor combined with fluorescence-activated cell sorting, we established a high-throughput screening platform for screening adenosylcobalamin overproducers. This study demonstrates that this platform has significant potential to quickly isolate high-productive strains to meet industrial demand and that the framework is acceptable for various metabolites.

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.

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.

Biosensor and machine learning-aided engineering of an amaryllidaceae enzyme

A major challenge to achieving industry-scale biomanufacturing of therapeutic alkaloids is the slow process of biocatalyst engineering. Amaryllidaceae alkaloids, such as the Alzheimer's medication galantamine, are complex plant secondary metabolites with recognized therapeutic value. Due to their difficult synthesis they are regularly sourced by extraction and purification from the low-yielding daffodil Narcissus pseudonarcissus. Here, we propose an efficient biosensor-machine learning technology stack for biocatalyst development, which we apply to engineer an Amaryllidaceae enzyme in Escherichia coli. Directed evolution is used to develop a highly sensitive (EC50 = 20 μM) and specific biosensor for the key Amaryllidaceae alkaloid branchpoint 4'-O-methylnorbelladine. A structure-based residual neural network (MutComputeX) is subsequently developed and used to generate activity-enriched variants of a plant methyltransferase, which are rapidly screened with the biosensor. Functional enzyme variants are identified that yield a 60% improvement in product titer, 2-fold higher catalytic activity, and 3-fold lower off-product regioisomer formation. A solved crystal structure elucidates the mechanism behind key beneficial mutations.

Enhancing 2-Pyrone Synthase Efficiency by High-Throughput Mass-Spectrometric Quantification and In Vitro/In Vivo Catalytic Performance Correlation

Engineering efficient biocatalysts is essential for metabolic engineering to produce valuable bioproducts from renewable resources. However, due to the complexity of cellular metabolic networks, it is challenging to translate success in vitro into high performance in cells. To meet such a challenge, an accurate and efficient quantification method is necessary to screen a large set of mutants from complex cell culture and a careful correlation between the catalysis parameters in vitro and performance in cells is required. In this study, we employed a mass-spectrometry based high-throughput quantitative method to screen new mutants of 2-pyrone synthase (2PS) for triacetic acid lactone (TAL) biosynthesis through directed evolution in E. coli. From the process, we discovered two mutants with the highest improvement (46 fold) in titer and the fastest kcat (44 fold) over the wild type 2PS, respectively, among those reported in the literature. A careful examination of the correlation between intracellular substrate concentration, Michaelis-Menten parameters and TAL titer for these two mutants reveals that a fast reaction rate under limiting intracellular substrate concentrations is important for in-cell biocatalysis. Such properties can be tuned by protein engineering and synthetic biology to adopt these engineered proteins for the maximum activities in different intracellular environments.

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

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

Advances in ligand-specific biosensing for structurally similar molecules

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

Biosensor-guided discovery and engineering of metabolic enzymes

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

Triacetic acid lactone production using 2-pyrone synthase expressing Yarrowia lipolytica via targeted gene deletion

An environmentally sustainable world can be realized by using microorganisms to produce value-added materials from renewable biomass. Triacetic acid lactone (TAL) is a high-value-added compound that is used as a precursor of various organic compounds such as food additives and pharmaceuticals. In this study, we used metabolic engineering to produce TAL from glucose using an oleaginous yeast Yarrowia lipolytica. We first introduced TAL-producing gene 2-pyrone synthase into Y. lipolytica, which enabled TAL production. Next, we increased TAL production by engineering acetyl-CoA and malonyl-CoA biosynthesis pathways by redirecting carbon flux to glycolysis. Finally, we optimized the carbon and nitrogen ratios in the medium, culminating in the production of 4078 mg/L TAL. The strategy presented in this study had the potential to improve the titer and yield of polyketide biosynthesis.

AraC-Based Biosensor for the Detection of Isoprene in E. coli

Isoprene is a valuable platform chemical, which is produced by engineered microorganisms, albeit in low quantities. The amount of isoprene produced is usually measured by gas chromatography, which can be time-consuming and expensive. Alternatively, biosensors have evolved as a powerful tool for real-time high-throughput screening and monitoring of product synthesis. The AraC-pBAD-inducible system has been widely studied, evolved, and engineered to develop biosensors for small molecules. In our preliminary studies, the AraC-pBAD system was mildly induced at higher isoprene concentrations when arabinose was also available. Hence, in the present study, we designed and constructed a synthetic biosensor based on the AraC-pBAD system, wherein the ligand-binding domain of AraC was replaced with IsoA. On introducing this chimeric AraC-IsoA (AcIa) transcription factor with the native PBAD promoter system regulating rfp gene expression, fluorescence output was observed only when wild-type Escherichia coli cells were induced with both isoprene and arabinose. The biosensor sensitivity and dynamic range were further enhanced by removing operator sequences and by substituting the native promoter (PAraC) with the strong tac promoter (Ptac). The chimeric sensor did not work in AraC knockout strains; however, functionality was restored by reintroducing AraC. Hence, AraC is essential for the functioning of our biosensor, while AcIa provides enhanced sensitivity and specificity for isoprene. However, insights into how AraC-AcIa interacts and the possible working mechanism remain to be explored. This study provides a prototype for developing chimeric AraC-based biosensors with proteins devoid of known dimerizing domains and opens a new avenue for further study and exploration.

Direct Utilization of Peroxisomal Acetyl-CoA for the Synthesis of Polyketide Compounds in Saccharomyces cerevisiae

Polyketides are a class of natural products with many applications but are mainly appealing as pharmaceuticals. Heterologous production of polyketides in the yeast Saccharomyces cerevisiae has been widely explored because of the many merits of this model eukaryotic microorganism. Although acetyl-CoA and malonyl-CoA, the precursors for polyketide synthesis, are distributed in several yeast subcellular organelles, only cytosolic synthesis of polyketides has been pursued in previous studies. In this study, we investigate polyketide synthesis by directly using acetyl-CoA in the peroxisomes of yeast strain CEN.PK2-1D. We first demonstrate that the polyketide flaviolin can be synthesized in this organelle upon peroxisomal colocalization of native acetyl-CoA carboxylase and 1,3,6,8-tetrahydroxynaphthalene synthase (a type III polyketide synthase). Next, using the synthesis of the polyketide triacetic acid lactone as an example, we show that (1) a new peroxisome targeting sequence, pPTS1, is more effective than the previously reported ePTS1 for peroxisomal polyketide synthesis; (2) engineering peroxisome proliferation is effective to boost polyketide production; and (3) peroxisomes provide an additional acetyl-CoA reservoir and extra space to accommodate enzymes so that utilizing the peroxisomal pathway plus the cytosolic pathway produces more polyketide than the cytosolic pathway alone. This research lays the groundwork for more efficient heterologous polyketide biosynthesis using acetyl-CoA pools in subcellular organelles.

Metabolic Engineering of Pichia pastoris for the Production of Triacetic Acid Lactone

Triacetic acid lactone (TAL) is a promising renewable platform polyketide with broad biotechnological applications. In this study, we constructed an engineered Pichia pastoris strain for the production of TAL. We first introduced a heterologous TAL biosynthetic pathway by integrating the 2-pyrone synthase encoding gene from Gerbera hybrida (Gh2PS). We then removed the rate-limiting step of TAL synthesis by introducing the posttranslational regulation-free acetyl-CoA carboxylase mutant encoding gene from S. cerevisiae (ScACC1*) and increasing the copy number of Gh2PS. Finally, to enhance intracellular acetyl-CoA supply, we focused on the introduction of the phosphoketolase/phosphotransacetylase pathway (PK pathway). To direct more carbon flux towards the PK pathway for acetyl-CoA generation, we combined it with a heterologous xylose utilization pathway or endogenous methanol utilization pathway. The combination of the PK pathway with the xylose utilization pathway resulted in the production of 825.6 mg/L TAL in minimal medium with xylose as the sole carbon source, with a TAL yield of 0.041 g/g xylose. This is the first report on TAL biosynthesis in P. pastoris and its direct synthesis from methanol. The present study suggests potential applications in improving the intracellular pool of acetyl-CoA and provides a basis for the construction of efficient cell factories for the production of acetyl-CoA derived compounds.

Advanced one-pot deconstruction and valorization of lignocellulosic biomass into triacetic acid lactone using Rhodosporidium toruloides

BACKGROUND

Rhodosporidium toruloides is capable of co-utilization of complex carbon sources and robust growth from lignocellulosic hydrolysates. This oleaginous yeast is therefore an attractive host for heterologous production of valuable bioproducts at high titers from low-cost, deconstructed biomass in an economically and environmentally sustainable manner. Here we demonstrate this by engineering R. toruloides to produce the polyketide triacetic acid lactone (TAL) directly from unfiltered hydrolysate deconstructed from biomass with minimal unit process operations.

RESULTS

Introduction of the 2-pyrone synthase gene into R. toruloides enabled the organism to produce 2.4 g/L TAL from simple media or 2.0 g/L from hydrolysate produced from sorghum biomass. Both of these titers are on par with titers from other better-studied microbial hosts after they had been heavily engineered. We next demonstrate that filtered hydrolysates produced from ensiled sorghum are superior to those derived from dried sorghum for TAL production, likely due to the substantial organic acids produced during ensiling. We also demonstrate that the organic acids found in ensiled biomass can be used for direct synthesis of ionic liquids within the biomass pretreatment process, enabling consolidation of unit operations of in-situ ionic liquid synthesis, pretreatment, saccharification, and fermentation into a one-pot, separations-free process. Finally, we demonstrate this consolidation in a 2 L bioreactor using unfiltered hydrolysate, producing 3.9 g/L TAL.

CONCLUSION

Many steps involved in deconstructing biomass into fermentable substrate can be combined into a distinct operation, and directly fed to cultures of engineered R. toruloides cultures for subsequent valorization into gram per liter titers of TAL in a cost-effective manner.

Signal Amplification of araC pBAD Using a Standardised Translation Initiation Region

araC pBAD is a genetic fragment that regulates the expression of the araBAD operon in bacteria, which is required for the metabolism of L-arabinose. It is widely used in bioengineering applications because it can drive regulatable and titratable expression of genes and genetic pathways in microbial cell factories. A notable limitation of araC pBAD is that it generates a low signal when induced with high concentrations of L-arabinose (the maximum ON state). Herein we have amplified the maximum ON state of araC pBAD by coupling it to a synthetically evolved translation initiation region (TIR^EVOL). The coupling maintains regulatable and titratable expression from araC pBAD and yet increases the maximal ON state by >5-fold. The general principle demonstrated in the study can be applied to amplify the signal from similar genetic modules.

Graphical Abstract

Metabolic engineering of oleaginous yeast Rhodotorula toruloides for overproduction of triacetic acid lactone

The plant‐sourced polyketide triacetic acid lactone (TAL) has been recognized as a promising platform chemical for the biorefinery industry. However, its practical application was rather limited due to low natural abundance and inefficient cell factories for biosynthesis. Here, we report the metabolic engineering of oleaginous yeast Rhodotorula toruloides for TAL overproduction. We first introduced a 2‐pyrone synthase gene from Gerbera hybrida (GhPS) into R. toruloides and investigated the effects of different carbon sources on TAL production. We then systematically employed a variety of metabolic engineering strategies to increase the flux of acetyl‐CoA by enhancing its biosynthetic pathways and disrupting its competing pathways. We found that overexpression of ATP‐citrate lyase (ACL1) improved TAL production by 45% compared to the GhPS overexpressing strain, and additional overexpression of acetyl‐CoA carboxylase (ACC1) further increased TAL production by 29%. Finally, we characterized the resulting strain I12‐ACL1‐ACC1 using fed‐batch bioreactor fermentation in glucose or oilcane juice medium with acetate supplementation and achieved a titer of 28 or 23 g/L TAL, respectively. This study demonstrates that R. toruloides is a promising host for the production of TAL and other acetyl‐CoA‐derived polyketides from low‐cost carbon sources.

Enriching intracellular macrolides in Escherichia coli improved the sensitivity of bioluminescent sensing systems

A repressor protein MphR and an enhanced green fluorescent protein (eGFP) were used to construct a bioluminescent sensing system for macrolide analysis in Escherichia coli host cells. We deleted TolC, an efflux pump for macrolides in E. coli, to promote the intracellular accumulation of macrolides. The binding constant (K_1/2) of the sensing system constructed in an E. coli strain was decreased up to 33-fold with deleted TolC, and its sensitivity to the macrolides erythromycin, azithromycin, roxithromycin, and pikromycin was increased. The limit of detection of the bioluminescent sensing system for serum azithromycin was 4.1 nM. The ability to detect serum azithromycin concentrations was confirmed by analyzing photographs using ImageJ software. We also developed a novel sensing system for the immune suppressor FK506, another macrolide that is frequently prescribed. Deleting TolC also significantly improved the sensitivity of this sensing system. Bioluminescent sensing systems constructed in TolC mutants were sensitive to various macrolides, indicating their potential for clinical application with hand-held devices.

Directed evolution of the PobR allosteric transcription factor to generate a biosensor for 4-hydroxymandelic acid

Hydroxy-mandelic acid (HMA) is widely applied in pharmaceuticals, food and cosmetics. In this study, we aimed to develop an allosteric transcription factors (aTFs) based biosensor for HMA. PobR, an aTF for HMA analog 4-hydroxybenzoic acid, was used to alter its selectivity and create novel aTFs responsive to HMA by directed evolution. We established a PobR mutant library with a capacity of 550,000 mutants using error-prone PCR and Megawhop PCR. Through our screening, two mutants were obtained with responsiveness to HMA. Analysis of each missense mutation indicating residues 122-126 were involved in its PobR ligand specificity. These results showed the effectiveness of directed evolution in switching the ligand specificity of a biosensor and improving HMA production.

Microbial chassis engineering drives heterologous production of complex secondary metabolites

The cryptic secondary metabolite biosynthetic gene clusters (BGCs) far outnumber currently known secondary metabolites. Heterologous production of secondary metabolite BGCs in suitable chassis facilitates yield improvement and discovery of new-to-nature compounds. The two juxtaposed conventional model microorganisms, Escherichia coli, Saccharomyces cerevisiae, have been harnessed as microbial chassis to produce a bounty of secondary metabolites with the help of certain host engineering. In last decade, engineering non-model microbes to efficiently biosynthesize secondary metabolites has received increasing attention due to their peculiar advantages in metabolic networks and/or biosynthesis. The state-of-the-art synthetic biology tools lead the way in operating genetic manipulation in non-model microorganisms for phenotypic optimization or yields improvement of desired secondary metabolites. In this review, we firstly discuss the pros and cons of several model and non-model microbial chassis, as well as the importance of developing broader non-model microorganisms as alternative programmable heterologous hosts to satisfy the desperate needs of biosynthesis study and industrial production. Then we highlight the lately advances in the synthetic biology tools and engineering strategies for optimization of non-model microbial chassis, in particular, the successful applications for efficient heterologous production of multifarious complex secondary metabolites, e.g., polyketides, nonribosomal peptides, as well as ribosomally synthesized and post-translationally modified peptides. Lastly, emphasis is on the perspectives of chassis cells development to access the ideal cell factory in the artificial intelligence-driven genome era.

Intracellular biosensor-based dynamic regulation to manipulate gene expression at the spatiotemporal level

The use of intracellular, biosensor-based dynamic regulation strategies to regulate and improve the production of useful compounds have progressed significantly over previous decades. By employing such an approach, it is possible to simultaneously realize high productivity and optimum growth states. However, industrial fermentation conditions contain a mixture of high- and low-performance non-genetic variants, as well as young and aged cells at all growth phases. Such significant individual variations would hinder the precise controlling of metabolic flux at the single-cell level to achieve high productivity at the macroscopic population level. Intracellular biosensors, as the regulatory centers of metabolic networks, can real-time sense intra- and extracellular conditions and, thus, could be synthetically adapted to balance the biomass formation and overproduction of compounds by individual cells. Herein, we highlight advances in the designing and engineering approaches to intracellular biosensors. Then, the spatiotemporal properties of biosensors associated with the distribution of inducers are compared. Also discussed is the use of such biosensors to dynamically control the cellular metabolic flux. Such biosensors could achieve single-cell regulation or collective regulation goals, depending on whether or not the inducer distribution is only intracellular.

Directed Evolution of Transcription Factor-Based Biosensors for Altered Effector Specificity

Transcription factor-based biosensors are important tools in Synthetic Biology for the sensing of industrially valuable molecules and clinically important metabolites, therefore presenting applications in the bioremediation, industrial biotechnology, and biomedical fields. The directed evolution of allosteric transcription factors (aTFs) with the aim of altering effector specificity has the potential for the development of new biosensors to detect natural and nonnatural molecules, expanding the scope of available aTF-based biosensors. In this chapter, we delineate a general method for the directed evolution of aTFs. The theory of library design is discussed, along with the detailed methodology for an improved transformation of combined libraries, and the experimental search space by counterselection using fluorescence-activated cell sorting (FACS) is presented.

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.

Mapping enzyme catalysis with metabolic biosensing

Enzymes are represented across a vast space of protein sequences and structural forms and have activities that far exceed the best chemical catalysts; however, engineering them to have novel or enhanced activity is limited by technologies for sensing product formation. Here, we describe a general and scalable approach for characterizing enzyme activity that uses the metabolism of the host cell as a biosensor by which to infer product formation. Since different products consume different molecules in their synthesis, they perturb host metabolism in unique ways that can be measured by mass spectrometry. This provides a general way by which to sense product formation, to discover unexpected products and map the effects of mutagenesis.

The testing of engineered enzymes represents a bottleneck. Here the authors report a screening method combining microfluidics and mass spectrometry, to map the catalysis of a mutated enzyme, characterise the range of products generated and recover the sequences of variants with desired activities.

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

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

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.

Sorting for secreted molecule production using a biosensor-in-microdroplet approach

Sorting large libraries of cells for improved small molecule secretion is throughput limited. Here, we combine producer/secretor cell libraries with whole-cell biosensors using a microfluidic-based screening workflow. This approach enables a mix-and-match capability using off-the-shelf biosensors through either coencapsulation or pico-injection. We demonstrate the cell type and library agnostic nature of this workflow by utilizing single-guide RNA, transposon, and ethyl-methyl sulfonate mutagenesis libraries across three distinct microbes (Escherichia coli, Saccharomyces cerevisiae, and Yarrowia lipolytica), biosensors from two organisms (E. coli and S. cerevisiae), and three products (triacetic acid lactone, naringenin, and L-DOPA) to identify targets improving production/secretion.

Development of a Biosensor Platform for Phenolic Compounds Using a Transition Ligand Strategy

The time-consuming and laborious characterization of protein or microbial strain designs limits the development of high-performance biocatalysts for biotechnological applications. Here, transcriptional biosensors emerged as valuable tools as they allow for rapid characterization of several thousand variants within a very short time. However, for many molecules of interest, no specific transcriptional regulator determining a biosensor's specificity is available. We present an approach for rapidly engineering biosensor specificities using a semirational transition ligand approach combined with fluorescence-activated cell sorting. In this two-step approach, a biosensor is first evolved toward a more relaxed-ligand specificity before using the resulting variant as the starting point in a second round of directed evolution toward high specificity for several chemically different ligands. By following this strategy, highly specific biosensors for 4-hydroxybenzoic acid, p-coumaric acid, 5-bromoferulic acid, and 6-methyl salicylic acid were developed, starting from a biosensor for the intracellular detection of trans-cinnamic acid.

Exploring the Tunability and Dynamic Properties of MarR-PmarO Sensor System in Escherichia coli

Transcriptional factor-based biosensors (TFBs) have been widely used in dynamic pathway control or high-throughput screening. Here, we systematically explored the tunability of a salicylic acid responsive regulator MarR from Escherichia coli aiming to explore its engineering potential. The effect of endogenous MarR in E. coli on the MarR-PmarO biosensor system was investigated. Furthermore, to investigate the function of marO binding boxes in this biosensor system, a series of hybrid promoters were constructed by placing the marO binding boxes in the strong constitutive pL promoter. The engineered hybrid promoters became responsive to MarR and salicylic acid. To further study the influence of each nucleotide in the marO box on MarR binding, we employed dynamic modeling to simulate the interaction and binding energy between each nucleotide in the marO boxes with the corresponding residues on MarR. Guided by the results of the simulation, we introduced mutations to key positions on the hybrid promoters and investigated corresponding dynamic performance. Two promoter variants I12AII4T and I12AII14T that exhibited improved responsive strengths and shifted dynamic ranges were obtained, which can be beneficial for future metabolic engineering research.

Multilayer Genetic Circuits for Dynamic Regulation of Metabolic Pathways

The dynamic regulation of metabolic pathways is based on changes in external signals and endogenous changes in gene expression levels and has extensive applications in the field of synthetic biology and metabolic engineering. However, achieving dynamic control is not trivial, and dynamic control is difficult to obtain using simple, single-level, control strategies because they are often affected by native regulatory networks. Therefore, synthetic biologists usually apply the concept of logic gates to build more complex and multilayer genetic circuits that can process various signals and direct the metabolic flux toward the synthesis of the molecules of interest. In this review, we first summarize the applications of dynamic regulatory systems and genetic circuits and then discuss how to design multilayer genetic circuits to achieve the optimal control of metabolic fluxes in living cells.

Production of Piperidine and δ-Lactam Chemicals from Biomass-Derived Triacetic Acid Lactone

Piperidine and δ-Lactam chemicals have wide application, which are currently produced from fossil resource in industry. Production of this kind of chemicals from lignocellulosic biomass is of great importance, but is challenging and the reported routes give low yield. Herein, we demonstrate the strategy to synthesize 2-methyl piperidine (MP) and 6-methylpiperidin-2-one (MPO) from biomass-derived triacetic acid lactone (TAL) that is produced microbially from glucose. In this route, TAL was firstly converted into 4-hydroxy-6-methylpyridin-2(1H)-one (HMPO) through facile aminolysis, subsequently HMPO was selectively transformed into MP or MPO over Ru catalysts supported on beta zeolite (Ru/BEA-X, X is the molar ratio of Si to Al) via the tandem reaction. It was found that the yield of MP could reach 76.5 % over Ru/BEA-60 in t-BuOH, and the yield of MPO could be 78.5 % in dioxane. Systematic studies reveal that the excellent catalytic performance of Ru/BEA-60 was closely correlated with the cooperative effects between active metal and acidic zeolite with large pore geometries. The related reaction pathway was studied on the basis of control experiments.

Transcription Factors as Evolvable Biosensors

One of the most prominent features of genetically encoded biosensors (GEBs) is their evolvability-the ability to invent new sensory functions using mutations. Among the GEBs, the transcription factor-based biosensors (TF-biosensors) is the focus of this review. We also discuss how this class of sensors can be highly evolvable and how we can exploit it. With an established platform for directed evolution, researchers can create, or evolve, new TF-biosensors. Directed evolution experiments have revealed the TF-biosensors' evolvability, which is based partially on their characteristic physicochemical properties.

Synthetic biology-inspired strategies and tools for engineering of microbial natural product biosynthetic pathways

Microbial-derived natural products (NPs) and their derivative products are of great importance and used widely in many fields, especially in pharmaceutical industries. However, there is an immediate need to establish innovative approaches, strategies, and techniques to discover new NPs with novel or enhanced biological properties, due to the less productivity and higher cost on traditional drug discovery pipelines from natural bioresources. Revealing of untapped microbial cryptic biosynthetic gene clusters (BGCs) using DNA sequencing technology and bioinformatics tools makes genome mining possible for NP discovery from microorganisms. Meanwhile, new approaches and strategies in the area of synthetic biology offer great potentials for generation of new NPs by engineering or creating synthetic systems with improved and desired functions. Development of approaches, strategies and tools in synthetic biology can facilitate not only exploration and enhancement in supply, and also in the structural diversification of NPs. Here, we discussed recent advances in synthetic biology-inspired strategies, including bioinformatics and genetic engineering tools and approaches for identification, cloning, editing/refactoring of candidate biosynthetic pathways, construction of heterologous expression hosts, fitness optimization between target pathways and hosts and detection of NP production.

A Perspective on Synthetic Biology in Drug Discovery and Development-Current Impact and Future Opportunities

The global impact of synthetic biology has been accelerating, because of the plummeting cost of DNA synthesis, advances in genetic engineering, growing understanding of genome organization, and explosion in data science. However, much of the discipline's application in the pharmaceutical industry remains enigmatic. In this review, we highlight recent examples of the impact of synthetic biology on target validation, assay development, hit finding, lead optimization, and chemical synthesis, through to the development of cellular therapeutics. We also highlight the availability of tools and technologies driving the discipline. Synthetic biology is certainly impacting all stages of drug discovery and development, and the recognition of the discipline's contribution can further enhance the opportunities for the drug discovery and development value chain.

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.

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.

Ring opening polymerization of β-acetoxy-δ-methylvalerolactone, a triacetic acid lactone derivative

We report here the synthesis and polymerization of a novel disubstituted valerolactone, β-acetoxy-δ-methylvalerolactone, derived from the renewable feedstock triacetic acid lactone (TAL).

Current Challenges and Opportunities in Non-native Chemical Production by Engineered Yeasts

Yeasts are promising industrial hosts for sustainable production of fuels and chemicals. Apart from efficient bioethanol production, yeasts have recently demonstrated their potential for biodiesel production from renewable resources. The fuel-oriented product profiles of yeasts are now expanding to include non-native chemicals with the advances in synthetic biology. In this review, current challenges and opportunities in yeast engineering for sustainable production of non-native chemicals will be discussed, with a focus on the comparative evaluation of a bioethanol-producing Saccharomyces cerevisiae strain and a biodiesel-producing Yarrowia lipolytica strain. Synthetic pathways diverging from the distinctive cellular metabolism of these yeasts guide future directions for product-specific engineering strategies for the sustainable production of non-native chemicals on an industrial scale.

An overview and future prospects of sialic acids

Sialic acids (Sias) are negatively charged functional monosaccharides present in a wide variety of natural sources (plants, animals and microorganisms). Sias play an important role in many life processes, which are widely applied in the medical and food industries as intestinal antibacterials, antivirals, anti-oxidative agents, food ingredients, and detoxification agents. Most Sias are composed of N-acetylneuraminic acid (Neu5Ac, >99%), and Sia is its most commonly used name. In this article, we review Sias in terms of their structures, applications, determination methods, metabolism, and production strategies. In particular, we summarise and compare different production strategies, including extraction from natural sources, chemical synthesis, polymer decomposition, enzymatic synthesis, whole-cell catalysis, and de novo biosynthesis via microorganism fermentation. We also discuss research on their physiological functions and applications, barriers to efficient production, and strategies for overcoming these challenges. We focus on efficient de novo biosynthesis strategies for Neu5Ac via microbial fermentation using novel synthetic biology tools and methods that may be applied in future. This work provides a comprehensive overview of recent advances on Sias, and addresses future challenges regarding their functions, applications, and production.

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

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

Engineering and application of a biosensor with focused ligand specificity

Cell factories converting bio-based precursors to chemicals present an attractive avenue to a sustainable economy, yet screening of genetically diverse strain libraries to identify the best-performing whole-cell biocatalysts is a low-throughput endeavor. For this reason, transcriptional biosensors attract attention as they allow the screening of vast libraries when used in combination with fluorescence-activated cell sorting (FACS). However, broad ligand specificity of transcriptional regulators (TRs) often prohibits the development of such ultra-high-throughput screens. Here, we solve the structure of the TR LysG of Corynebacterium glutamicum, which detects all three basic amino acids. Based on this information, we follow a semi-rational engineering approach using a FACS-based screening/counterscreening strategy to generate an l-lysine insensitive LysG-based biosensor. This biosensor can be used to isolate l-histidine-producing strains by FACS, showing that TR engineering towards a more focused ligand spectrum can expand the scope of application of such metabolite sensors.

Transcriptional biosensors represent powerful tools for the screening of vast strain libraries, but the broad ligand specificity of some transcriptional regulators (TRs) can prohibit such applications. Here authors present the engineering of a LysG-based biosensor with a focused ligand specificity to isolate L-histidine-producing strains.

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.

Biosensors design in yeast and applications in metabolic engineering

Engineering microbial cell factories is a potential approach of sustainable production of chemicals, fuels and pharmaceuticals. However, testing the production of molecules in high throughput is still a time-consuming and laborious process since product synthesis usually does not confer a clear phenotype. Therefore, it is necessary to develop new techniques for fast high-producer screening. Genetically encoded biosensors are considered to be promising devices for high-throughput analysis owing to their ability to sense metabolites and couple detection to an actuator, thereby facilitating the rapid detection of small molecules at single-cell level. Here, we review recent advances in the design and engineering of biosensors in Saccharomyces cerevisiae, and their applications in metabolic engineering. Three types of biosensor are introduced in this review: transcription factor based, RNA-based and enzyme-coupled biosensors. The studies to improve the features of biosensors are also described. Moreover, we summarized their metabolic engineering applications in dynamic regulation and high producer selection. Current challenges in biosensor design and future perspectives on sensor applications are also discussed.

Primary metabolites from overproducing microbial system using sustainable substrates

Primary (or secondary) metabolites are produced by animals, plants, or microbial cell systems either intracellularly or extracellularly. Production capabilities of microbial cell systems for many types of primary metabolites have been exploited at a commercial scale. But the high production cost of metabolites is a big challenge for most of the bioprocess industries and commercial production needs to be achieved. This issue can be solved to some extent by screening and developing the engineered microbial systems via reconstruction of the genome-scale metabolic model. The predicted genetic modification is applied for an increased flux in biosynthesis pathways toward the desired product. Wherein the resulting microbial strain is capable of converting a large amount of carbon substrate to the expected product with minimum by-product formation in the optimal operating conditions. Metabolic engineering efforts have also resulted in significant improvement of metabolite yields, depending on the nature of the products, microbial cell factory modification, and the types of substrate used. The objective of this review is to comprehend the state of art for the production of various primary metabolites by microbial strains system, focusing on the selection of efficient strain and genetic or pathway modifications, applied during strain engineering.

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.

Improvement of l-Valine Production by Atmospheric and Room Temperature Plasma Mutagenesis and High-Throughput Screening in Corynebacterium glutamicum

As one of the branched-chain amino acids, l-valine is an essential nutrient for most mammalian species. In this study, the l-valine producer Corynebacterium glutamicum ΔppcΔaceEΔalatΔpqo was first constructed. Additionally, an improved biosensor based on the Lrp-type transcriptional regulator and temperature-sensitive replication was built. Then, the C. glutamicum strain was mutagenized by atmospheric and room temperature plasma. A sequential three-step procedure was carried out to screen l-valine-producing strains, including the fluorescence-activated cell sorting (FACS), 96-well plate screening, and flask fermentation. The final mutant HL2-7 obtained by screening produced 3.20 g/L of l-valine, which was 21.47% higher than the titer produced by the starting strain. This study demonstrates that the l-valine-producing mutants can be successfully isolated based on the Lrp sensor system in combination with FACS screening after random mutagenesis.

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.