Improving fatty acids production by engineering dynamic pathway regulation and metabolic control

Dynamic Regulation of Transporter Expression to Increase L-Threonine Production Using L-Threonine Biosensors

The cytotoxicity of overexpressed transporters limits their application in biochemical production. To overcome this problem, we developed a feedback circuit for L-threonine production that uses a biosensor to regulate transporter expression. First, we used IPTG-induced rhtA regulation, L-threonine exporter, to simulate dynamic regulation for improving L-threonine production, and the results show that it had significant advantages compared with the constitutive overexpression of rhtA. To further construct a feedback circuit for rhtA auto-regulation, three L-threonine sensing promoters, PcysJ, PcysD, and PcysJH, were characterized with gradually decreasing strength. The dynamic expression of rhtA with a threonine-activated promoter considerably increased L-threonine production (21.19 g/L) beyond that attainable by the constitutive expression of rhtA (8.55 g/L). Finally, the autoregulation method was used in regulating rhtB and rhtC to improve L-threonine production and achieve a high titer of 26.78 g/L (a 161.01% increase), a yield of 0.627 g/g glucose, and a productivity of 0.743 g/L/h in shake-flask fermentation. This study analyzed in detail the influence of dynamic regulation and the constitutive expression of transporters on L-threonine production. For the first time, we confirmed that dynamically regulating transporter levels can efficiently promote L-threonine production by using the end-product biosensor.

Metabolic Engineering and Regulation of Diol Biosynthesis from Renewable Biomass in Escherichia coli

As bulk chemicals, diols have wide applications in many fields, such as clothing, biofuels, food, surfactant and cosmetics. The traditional chemical synthesis of diols consumes numerous non-renewable energy resources and leads to environmental pollution. Green biosynthesis has emerged as an alternative method to produce diols. Escherichia coli as an ideal microbial factory has been engineered to biosynthesize diols from carbon sources. Here, we comprehensively summarized the biosynthetic pathways of diols from renewable biomass in E. coli and discussed the metabolic-engineering strategies that could enhance the production of diols, including the optimization of biosynthetic pathways, improvement of cofactor supplementation, and reprogramming of the metabolic network. We then investigated the dynamic regulation by multiple control modules to balance the growth and production, so as to direct carbon sources for diol production. Finally, we proposed the challenges in the diol-biosynthesis process and suggested some potential methods to improve the diol-producing ability of the host.

New synthetic biology tools for metabolic control

In industrial bioprocesses, microbial metabolism dictates the product yields, and therefore, our capacity to control it has an enormous potential to help us move towards a bio-based economy. The rapid development of multiomics data has accelerated our systematic understanding of complex metabolic regulatory mechanisms, which allow us to develop tools to manipulate them. In the last few years, machine learning-based metabolic modeling, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) derived synthetic biology tools, and synthetic genetic circuits have been widely used to control the metabolism of microorganisms, manipulate gene expression, and build synthetic pathways for bioproduction. This review describes the latest developments for metabolic control, and focuses on the trends and challenges of metabolic engineering strategies.

Redesigning regulatory components of quorum-sensing system for diverse metabolic control

Quorum sensing (QS) is a ubiquitous cell–cell communication mechanism that can be employed to autonomously and dynamically control metabolic fluxes. However, since the functions of genetic components in the circuits are not fully understood, the developed QS circuits are still less sophisticated for regulating multiple sets of genes or operons in metabolic engineering applications. Here, we discover the regulatory roles of a CRP-binding site and the lux box to −10 region within luxR-luxI intergenic sequence in controlling the lux-type QS promoters. By varying the numbers of the CRP-binding site and redesigning the lux box to −10 site sequence, we create a library of QS variants that possess both high dynamic ranges and low leakiness. These circuits are successfully applied to achieve diverse metabolic control in salicylic acid and 4-hydroxycoumarin biosynthetic pathways in Escherichia coli. This work expands the toolbox for dynamic control of multiple metabolic fluxes under complex metabolic background and presents paradigms to engineer metabolic pathways for high-level synthesis of target products.

Existing quorum sensing (QS) circuits are less sophisticated for regulating multiple sets of genes or operons. Here, the authors redesign the luxR-luxI intergenic sequence of the lux-type QS system and apply it to achieve diverse metabolic control in salicylic acid and 4-hydroxycoumarin biosynthesis in E. coli.

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.

HepG2-Based Designer Cells with Heat-Inducible Enhanced Liver Functions

Functional human hepatocytes have been a pivotal tool in pharmacological studies such as those investigating drug metabolism and hepatotoxicity. However, primary human hepatocytes are difficult to obtain in large quantities and may cause ethical problems, necessitating the development of a new cell source to replace human primary hepatocytes. We previously developed genetically modified murine hepatoma cell lines with inducible enhanced liver functions, in which eight liver-enriched transcription factor (LETF) genes were introduced into hepatoma cells as inducible transgene expression cassettes. Here, we establish a human hepatoma cell line with heat-inducible liver functions using HepG2 cells. The genetically modified hepatoma cells, designated HepG2/8F_HS, actively proliferated under normal culture conditions and, therefore, can be easily prepared in large quantities. When the expression of LETFs was induced by heat treatment at 43 °C for 30 min, cells ceased proliferation and demonstrated enhanced liver functions. Furthermore, three-dimensional spheroid cultures of HepG2/8F_HS cells showed a further increase in liver functions upon heat treatment. Comprehensive transcriptome analysis using DNA microarrays revealed that HepG2/8F_HS cells had enhanced overall expression of many liver function-related genes following heat treatment. HepG2/8F_HS cells could be useful as a new cell source for pharmacological studies and for constructing bioartificial liver systems.

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.

Refactoring transcription factors for metabolic engineering

Due to the ability to regulate target metabolic pathways globally and dynamically, metabolic regulation systems composed of transcription factors have been widely used in metabolic engineering and synthetic biology. This review introduced the categories, action principles, prediction strategies, and related databases of transcription factors. Then, the application of global transcription machinery engineering technology and the transcription factor-based biosensors and quorum sensing systems are overviewed. In addition, strategies for optimizing the transcriptional regulatory tools' performance by refactoring transcription factors are summarized. Finally, the current limitations and prospects of constructing various regulatory tools based on transcription factors are discussed. This review will provide theoretical guidance for the rational design and construction of transcription factor-based metabolic regulation systems.

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.

Encoding Genetic Circuits with DNA Barcodes Paves the Way for Machine Learning-Assisted Metabolite Biosensor Response Curve Profiling in Yeast

Genetically encoded biosensors are valuable tools used in the precise engineering of metabolism. Although a large number of biosensors have been developed, the fine-tuning of their dose-response curves, which promotes the applications of biosensors in various scenarios, still remains challenging. To address this issue, we leverage a DNA trackable assembly method and fluorescence-activated cell sorting coupled with next-generation sequencing (FACS-seq) technology to set up a novel workflow for construction and comprehensive characterization of thousands of biosensors in a massively parallel manner. An FapR-fapO-based malonyl-CoA biosensor was used as proof of concept to construct a trackable combinatorial library, containing 5184 combinations with 6 levels of transcription factor dosage, 4 different operator positions, and 216 possible upstream enhancer sequence (UAS) designs. By applying the FACS-seq technique, the response curves of 2632 biosensors out of 5184 combinations were successfully characterized to provide large-scale genotype-phenotype association data of the designed biosensors. Finally, machine-learning algorithms were applied to predict the genotype-phenotype relationships of the uncharacterized combinations to generate a panoramic scanning map of the combinatorial space. With the assistance of our novel workflow, a malonyl-CoA biosensor with the largest dynamic response range was successfully obtained. Moreover, feature importance analysis revealed that the recognition sequence insertion scheme and the choice of UAS have a significant impact on the dynamic range. Taken together, our pipeline provides a platform for the design, tuning, and profiling of biosensor response curves and shows great potential to facilitate the rational design of genetic circuits.

Bioengineered microbial platforms for biomass-derived biofuel production - A review

Global warming issues, rapid fossil fuel diminution, and increasing worldwide energy demands have diverted accelerated attention in finding alternate sources of biofuels and energy to combat the energy crisis. Bioconversion of lignocellulosic biomass has emerged as a prodigious way to produce various renewable biofuels such as biodiesel, bioethanol, biogas, and biohydrogen. Ideal microbial hosts for biofuel synthesis should be capable of using high substrate quantity, tolerance to inhibiting substances and end-products, fast sugar transportation, and amplified metabolic fluxes to yielding enhanced fermentative bioproduct. Genetic manipulation and microbes' metabolic engineering are fascinating strategies for the economical production of next-generation biofuel from lignocellulosic feedstocks. Metabolic engineering is a rapidly developing approach to construct robust biofuel-producing microbial hosts and an important component for future bioeconomy. This approach has been widely adopted in the last decade for redirecting and revamping the biosynthetic pathways to obtain a high titer of target products. Biotechnologists and metabolic scientists have produced a wide variety of new products with industrial relevance through metabolic pathway engineering or optimizing native metabolic pathways. This review focuses on exploiting metabolically engineered microbes as promising cell factories for the enhanced production of advanced biofuels.

Leveraging quorum sensing system for automatic coordination of Escherichia coli growth and lactic acid biosynthesis

Purpose

Overproduction of desired metabolites usually sacrifices cell growth. Here we report that quorum sensing (QS) can be exploited to coordinate cell growth and lactic acid production in Escherichia coli.

Methods

We engineered two QS strains: one strain overexpressing acyl-homoserine lactone (AHL) synthesis genes (“ON”), the other strain overexpressing both AHL synthesis and degradation gene (aiiA) (“ON to semi-OFF”). To clarify the impact of the QS system on lactic acid production, D-lactate dehydrogenase gene ldhA was deleted from the E. coli genome, and Enhanced Green Fluorescence Protein (eGFP) was used as the reporter.

Results

Compared to the “ON” strain, the “ON to semi-OFF” strain showed delayed log growth and decreased egfp expression at stationary phase. When egfp was replaced by ldhA for lactic acid production, compared to the wild-type strain, the “ON to semi-OFF” strain demonstrated 231.9% and 117.3% increase in D-lactic acid titer and space-time yield, respectively, while the “ON” strain demonstrated 83.6%, 31%, and 36% increase in growth rate, maximum OD600, and glucose consumption rate, respectively. Quantitative real-time PCR revealed that both ldhA and the genes for phosphotransferase system were up-regulated in ldhA-overexpressing “ON” strain compared to the strain only harboring QS system. Moreover, the “ON” strain showed considerable increase in glucose consumption after a short lag phase. Compared to the reference strain harboring only ldhA gene in vector, both the “ON” and “ON to semi-OFF” strains demonstrated synchronization between cell growth and D-lactic acid production.

Conclusions

Collectively, QS can be leveraged to coordinate microbial growth and product formation.

Metabolic engineering for valorization of macroalgae biomass

Marine macroalgae have huge potential as feedstocks for production of a wide spectrum of chemicals used in biofuels, biomaterials, and bioactive compounds. Harnessing macroalgae in these ways could promote wellbeing for people while mitigating climate change and environmental destruction linked to use of fossil fuels. Microorganisms play pivotal roles in converting macroalgae into valuable products, and metabolic engineering technologies have been developed to extend their native capabilities. This review showcases current achievements in engineering the metabolisms of various microbial chassis to convert red, green, and brown macroalgae into bioproducts. Unique features of macroalgae, such as seasonal variation in carbohydrate content and salinity, provide the next challenges to advancing macroalgae-based biorefineries. Three emerging engineering strategies are discussed here: (1) designing dynamic control of metabolic pathways, (2) engineering strains of halophilic (salt-tolerant) microbes, and (3) developing microbial consortia for conversion. This review illuminates opportunities for future research communities by elucidating current approaches to engineering microbes so they can become cell factories for the utilization of macroalgae feedstocks.

Trade-Offs in Biosensor Optimization for Dynamic Pathway Engineering

Recent progress in synthetic biology allows the construction of dynamic control circuits for metabolic engineering. This technology promises to overcome many challenges encountered in traditional pathway engineering, thanks to its ability to self-regulate gene expression in response to bioreactor perturbations. The central components in these control circuits are metabolite biosensors that read out pathway signals and actuate enzyme expression. However, the construction of metabolite biosensors is a major bottleneck for strain design, and a key challenge is to understand the relation between biosensor dose-response curves and pathway performance. Here we employ multiobjective optimization to quantify performance trade-offs that arise in the design of metabolite biosensors. Our approach reveals strategies for tuning dose-response curves along an optimal trade-off between production flux and the cost of an increased expression burden on the host. We explore properties of control architectures built in the literature and identify their advantages and caveats in terms of performance and robustness to growth conditions and leaky promoters. We demonstrate the optimality of a control circuit for glucaric acid production in Escherichia coli, which has been shown to increase the titer by 2.5-fold as compared to static designs. Our results lay the groundwork for the automated design of control circuits for pathway engineering, with applications in the food, energy, and pharmaceutical sectors.

Fine-tuning gene expression for improved biosynthesis of natural products: From transcriptional to post-translational regulation

Microbial production of natural compounds has attracted extensive attention due to their high value in pharmaceutical, cosmetic, and food industries. Constructing efficient microbial cell factories for biosynthesis of natural products requires the fine-tuning of gene expressions to minimize the accumulation of toxic metabolites, reduce the competition between cell growth and product generation, as well as achieve the balance of redox or co-factors. In this review, we focus on recent advances in fine-tuning gene expression at the DNA, RNA, and protein levels to improve the microbial biosynthesis of natural products. Commonly used regulatory toolsets in each level are discussed, and perspectives for future direction in this area are provided.

Methods for the Development of Recombinant Microorganisms for the Production of Natural Products

Metabolic engineering strives to develop microbial strains that are capable of producing a target chemical in a biological organism. There are still many challenges to overcome in order to achieve titers, yields, and productivities necessary for industrial production. The use of recombinant microorganisms to meet these needs is the next step for metabolic engineers. In this chapter, we aim to provide insight on both the applications of metabolic engineering for natural product biosynthesis as well as optimization methods.

Engineering of Corynebacterium glutamicum for high-level γ-aminobutyric acid production from glycerol by dynamic metabolic control

Synthetic biology seeks to reprogram microbial cells for efficient production of value-added compounds from low-cost renewable substrates. A great challenge of chemicals biosynthesis is the competition between cell metabolism and target product synthesis for limited cellular resource. Dynamic regulation provides an effective strategy for fine-tuning metabolic flux to maximize chemicals production. In this work, we created a tunable growth phase-dependent autonomous bifunctional genetic switch (GABS) by coupling growth phase responsive promoters and degrons to dynamically redirect the carbon flux for metabolic state switching from cell growth mode to production mode, and achieved high-level GABA production from low-value glycerol in Corynebacterium glutamicum. A ribosome binding sites (RBS)-library-based pathway optimization strategy was firstly developed to reconstruct and optimize the glycerol utilization pathway in C. glutamicum, and the resulting strain CgGly2 displayed excellent glycerol utilization ability. Then, the initial GABA-producing strain was constructed by deleting the GABA degradation pathway and introducing an exogenous GABA synthetic pathway, which led to 5.26 g/L of GABA production from glycerol. In order to resolve the conflicts of carbon flux between cell growth and GABA production, we used the GABS to reconstruct the GABA synthetic metabolic network, in which the competitive modules of GABA biosynthesis, including the tricarboxylic acid (TCA) cycle module and the arginine biosynthesis module, were dynamically down-regulated while the synthetic modules were dynamically up-regulated after sufficient biomass accumulation. Finally, the resulting strain G7-1 accumulated 45.6 g/L of GABA with a yield of 0.4 g/g glycerol, which was the highest titer of GABA ever reported from low-value glycerol. Therefore, these results provide a promising technology to dynamically balance the metabolic flux for the efficient production of other high value-added chemicals from a low-value substrate in C. glutamicum.

Microbial production of small peptide: pathway engineering and synthetic biology

Small peptides are a group of natural products with low molecular weights and complex structures. The diverse structures of small peptides endow them with broad bioactivities and suggest their potential therapeutic use in the medical field. The remaining challenge is methods to address the main limitations, namely (i) the low amount of available small peptides from natural sources, and (ii) complex processes required for traditional chemical synthesis. Therefore, harnessing microbial cells as workhorse appears to be a promising approach to synthesize these bioactive peptides. As an emerging engineering technology, synthetic biology aims to create standard, well-characterized and controllable synthetic systems for the biosynthesis of natural products. In this review, we describe the recent developments in the microbial production of small peptides. More importantly, synthetic biology approaches are considered for the production of small peptides, with an emphasis on chassis cells, the evolution of biosynthetic pathways, strain improvements and fermentation.

Reconstructing a recycling and nonauxotroph biosynthetic pathway in Escherichia coli toward highly efficient production of L-citrulline

L-citrulline is a high-value amino acid with promising application in medicinal and food industries. Construction of highly efficient microbial cell factories for L-citrulline production is still an open issue due to complex metabolic flux distribution and L-arginine auxotrophy. In this study, we constructed a nonauxotrophic cell factory in Escherichia coli for high-titer L-citrulline production by coupling modular engineering strategies with dynamic pathway regulation. First, the biosynthetic pathway of L-citrulline was enhanced after blockage of the degradation pathway and introduction of heterologous biosynthetic genes from Corynebacterium glutamicum. Specifically, a superior recycling biosynthetic pathway was designed to replace the native linear pathway by deleting native acetylornithine deacetylase. Next, the carbamoyl phosphate and L-glutamate biosynthetic modules, the NADPH generation module, and the efflux module were modified to increase L-citrulline titer further. Finally, a toggle switch that responded to cell density was designed to dynamically control the expression of the argG gene and reconstruct a nonauxotrophic pathway. Without extra supplement of L-arginine during fermentation, the final CIT24 strain produced 82.1 g/L L-citrulline in a 5-L bioreactor with a yield of 0.34 g/g glucose and a productivity of 1.71 g/(L ⋅ h), which were the highest values reported by microbial fermentation. Our study not only demonstrated the successful design of cell factory for high-level L-citrulline production but also provided references of coupling the rational module engineering strategies and dynamic regulation strategies to produce high-value intermediate metabolites.

Metabolic engineering of Escherichia coli for efficient osmotic stress-free production of compatible solute hydroxyectoine

Compatible solutes are key for the ability of halophilic bacteria to resist high osmotic stress. They have received wide attention from researchers for their excellent osmotic protection properties. Hydroxyectoine is a particularly important compatible solute, but its production by microbes faces several challenges, including low titer/yield, the presence of the byproduct ectoine, and the requirement of high salinity. Here, we aimed to metabolically engineer Escherichia coli to efficiently produce hydroxyectoine in the absence of osmotic stress without accumulating the byproduct ectoine. First, combinatorial optimization of the expression strength of key genes in the ectoine synthesis module and hydroxyectoine synthesis module was conducted. After optimization of the expression of these genes, 12.12 g/L hydroxyectoine and 0.24 g/L ectoine were obtained at 36 h in shake-flask fermentation with the addition of the co-substrate α-ketoglutarate. Further optimization of the addition of α-ketoglutarate achieved the sole production of hydroxyectoine (i.e., no ectoine accumulation), indicating that the supply of α-ketoglutarate is critically important for sole hydroxyectoine production. Finally, quorum sensing-based auto-regulation of intracellular α-ketoglutarate pool was implemented as an alternative to α-ketoglutarate addition by coupling the expression of sucA with the esaI/esaR circuit, which led to 14.93 g/L hydroxyectoine with a unit cell yield of 1.678 g/g and no ectoine accumulation in the absence of osmotic stress. This is the highest reported titer of sole hydroxyectoine production under salinity-free fermentation to date.

Development of bifunctional biosensors for sensing and dynamic control of glycolysis flux in metabolic engineering

Glycolysis is the primary metabolic pathway in all living organisms. Maintaining the balance of glycolysis flux and biosynthetic pathways is the crucial matter involved in the microbial cell factory. Few regulation systems can address the issue of metabolic flux imbalance in glycolysis. Here, we designed and constructed a bifunctional glycolysis flux biosensor that can dynamically regulate glycolysis flux for overproduction of desired biochemicals. A series of positive-and negative-response biosensors were created and modified for varied thresholds and dynamic ranges. These engineered glycolysis flux biosensors were verified to be able to characterize in vivo fructose-1,6-diphosphate concentration. Subsequently, the biosensors were applied for fine-tuning glycolysis flux to effectively balance the biosynthesis of two chemicals: mevalonate and N-acetylglucosamine. A glycolysis flux-dynamically controlled Escherichia coli strain achieved a 111.3 g/L mevalonate titer in a 1L fermenter.

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.

Two-stage dynamic deregulation of metabolism improves process robustness & scalability in engineered E. coli

We report that two-stage dynamic control improves bioprocess robustness as a result of the dynamic deregulation of central metabolism. Dynamic control is implemented during stationary phase using combinations of CRISPR interference and controlled proteolysis to reduce levels of central metabolic enzymes. Reducing the levels of key enzymes alters metabolite pools resulting in deregulation of the metabolic network. Deregulated networks are less sensitive to environmental conditions improving process robustness. Process robustness in turn leads to predictable scalability, minimizing the need for traditional process optimization. We validate process robustness and scalability of strains and bioprocesses synthesizing the important industrial chemicals alanine, citramalate and xylitol. Predictive high throughput approaches that translate to larger scales are critical for metabolic engineering programs to truly take advantage of the rapidly increasing throughput and decreasing costs of synthetic biology.

Genome-Wide Transcription Factor DNA Binding Sites and Gene Regulatory Networks in Clostridium thermocellum

Clostridium thermocellum is a thermophilic bacterium recognized for its natural ability to effectively deconstruct cellulosic biomass. While there is a large body of studies on the genetic engineering of this bacterium and its physiology to-date, there is limited knowledge in the transcriptional regulation in this organism and thermophilic bacteria in general. The study herein is the first report of a large-scale application of DNA-affinity purification sequencing (DAP-seq) to transcription factors (TFs) from a bacterium. We applied DAP-seq to > 90 TFs in C. thermocellum and detected genome-wide binding sites for 11 of them. We then compiled and aligned DNA binding sequences from these TFs to deduce the primary DNA-binding sequence motifs for each TF. These binding motifs are further validated with electrophoretic mobility shift assay (EMSA) and are used to identify individual TFs’ regulatory targets in C. thermocellum. Our results led to the discovery of novel, uncharacterized TFs as well as homologues of previously studied TFs including RexA-, LexA-, and LacI-type TFs. We then used these data to reconstruct gene regulatory networks for the 11 TFs individually, which resulted in a global network encompassing the TFs with some interconnections. As gene regulation governs and constrains how bacteria behave, our findings shed light on the roles of TFs delineated by their regulons, and potentially provides a means to enable rational, advanced genetic engineering of C. thermocellum and other organisms alike toward a desired phenotype.

Analytical methods in fatty acid analysis for microbial applications: the recent trends

Fatty acids are among the most important components of many biological systems and have been highlighted in many research fields in recent decades. In the food industry, it is important to check the amount and types of fatty acids in edible oils, beverages and other foods products, and checking the fatty acids parameters are among the quality control parameters for those products. In medical applications, investigation of fatty acids in biological samples and comparing imbalances in them can help to diagnose some diseases. On the other hand, the development of cell factories for the production of biofuels and other valuable chemicals requires the accurate analysis of fatty acids, which serve as precursors in development of those products. As a result, given all these different applications of fatty acids, rapid and accurate methods for characterization and quantification of fatty acids are essential. In recent years, various methods for the analysis of fatty acids have been proposed, which according to the specific purpose of the analysis, some of them can be used with consideration of speed, accuracy and cost. In this article, the available methods for the analysis of fatty acids are reviewed with a special emphasis on the analysis of microbial samples to pave the way for more widespread metabolic engineering research.

Applied evolution: Dual dynamic regulations-based approaches in engineering intracellular malonyl-CoA availability

Malonyl-CoA is an important building block for microbial synthesis of numerous pharmaceutically interesting or fatty acid-derived compounds including polyketides, flavonoids, phenylpropanoids and fatty acids. However, the tightly regulated intracellular malonyl-CoA availability often impedes overall product formation. Here, in order to unleash this tightly cellular behavior, we present evolution: dual dynamic regulations-based approaches to write artificial robust and dynamic function into intricate cellular background. Firstly, a conserved core domain based evolutionary principles were incorporated into genome mining to explore the biosynthetic diversities of discrete acetyl-CoA carboxylase (ACC) families, as malonyl-CoA is solely derived from carboxylation of acetyl-CoA by ACC in most organisms. A comprehensive phylogenomic and further experimental analysis, which included genomes of 50 strains throughout representative species, was performed to recapitulate the evolutionary history and reveal that previously unnoticed ACC families from Salmonella enterica exhibited the highest activities among all the candidates. A set of orthogonal and bi-functional quorum-sensing (QS)-based regulation tools were further designed and connected with T7 RNA polymerase as genetic amplifier to achieve dual dynamic control in a high dynamic range, which allowed us to efficiently activate and repress different sets of genes dynamically and independently. These genetic circuits were then combined with ACC of S. enterica and CRISPRi system to reprogram central metabolism that rewired the tightly regulated malonyl-CoA pathway to a robust and autonomous behavior, leading to a 29-fold increase of malony-CoA availability. We applied this dual regulation tool to successfully synthesizing malonyl-CoA-derived compound (2S)-naringenin, and achieved the highest production (1073.8 mg/L) reported to date associate with dramatic decreases of by-product formation. Notably, the whole fermentation presents as an autonomous behavior, totally eliminating human supervision and inducer supplementation. Hence, the constructed evolution: dual dynamic regulations-based approaches pave the way to develop an economically viable and scalable procedure for microbial production of malonyl-CoA derived compounds.

Metabolome and proteome analyses reveal transcriptional misregulation in glycolysis of engineered E. coli

Synthetic metabolic pathways are a burden for engineered bacteria, but the underlying mechanisms often remain elusive. Here we show that the misregulated activity of the transcription factor Cra is responsible for the growth burden of glycerol overproducing E. coli. Glycerol production decreases the concentration of fructose-1,6-bisphoshate (FBP), which then activates Cra resulting in the downregulation of glycolytic enzymes and upregulation of gluconeogenesis enzymes. Because cells grow on glucose, the improper activation of gluconeogenesis and the concomitant inhibition of glycolysis likely impairs growth at higher induction of the glycerol pathway. We solve this misregulation by engineering a Cra-binding site in the promoter controlling the expression of the rate limiting enzyme of the glycerol pathway to maintain FBP levels sufficiently high. We show the broad applicability of this approach by engineering Cra-dependent regulation into a set of constitutive and inducible promoters, and use one of them to overproduce carotenoids in E. coli.

Synthetic pathways represent a metabolic burden on host cells. Here the authors engineer Cra-binding sites to prevent misregulation in glycerol and carotenoid overproducing E. coli strains.

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

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

Recent trends in biocatalysis

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

Modular optimization in metabolic engineering

There is an increasing demand for bioproducts produced by metabolically engineered microbes, such as pharmaceuticals, biofuels, biochemicals and other high value compounds. In order to meet this demand, modular optimization, the optimizing of subsections instead of the whole system, has been adopted to engineer cells to overproduce products. Research into modularity has focused on traditional approaches such as DNA, RNA, and protein-level modularity of intercellular machinery, by optimizing metabolic pathways for enhanced production. While research into these traditional approaches continues, limitations such as scale-up and time cost hold them back from wider use, while at the same time there is a shift to more novel methods, such as moving from episomal expression to chromosomal integration. Recently, nontraditional approaches such as co-culture systems and cell-free metabolic engineering (CFME) are being investigated for modular optimization. Co-culture modularity looks to optimally divide the metabolic burden between different hosts. CFME seeks to modularly optimize metabolic pathways in vitro, both speeding up the design of such systems and eliminating the issues associated with live hosts. In this review we will examine both traditional and nontraditional approaches for modular optimization, examining recent developments and discussing issues and emerging solutions for future research in metabolic engineering.

Improved Bioproduction of 1-Octanol Using Engineered Synechocystis sp. PCC 6803

1-Octanol has gained interest as a chemical precursor for both high and low value commodities including fuel, solvents, surfactants, and fragrances. By harnessing the power from sunlight and CO₂ as carbon source, cyanobacteria has recently been engineered for renewable production of 1-octanol. The productivity, however, remained low. In the present work, we report efforts to further improve the 1-octanol productivity. Different N-terminal truncations were evaluated on three thioesterases from different plant species, resulting in several candidate thioesterases with improved activity and selectivity toward octanoyl-ACP. The structure/function trials suggest that current knowledge and/or state-of-the art computational tools are insufficient to determine the most appropriate cleavage site for thioesterases in Synechocystis. Additionally, by tuning the inducer concentration and light intensity, we further improved the 1-octanol productivity, reaching up to 35% (w/w) carbon partitioning and a titer of 526 ± 5 mg/L 1-octanol in 12 days. Long-term cultivation experiments demonstrated that the improved strain can be stably maintained for at least 30 days and/or over ten times serial dilution. Surprisingly, the improved strain was genetically stable in contrast to earlier strains having lower productivity (and hence a reduced chance of reaching toxic product concentrations). Altogether, improved enzymes and environmental conditions (e.g., inducer concentration and light intensity) substantially increased the 1-octanol productivity. When cultured under continuous conditions, the bioproduction system reached an accumulative titer of >3.5 g/L 1-octanol over close to 180 days.

Dynamic control of the distribution of carbon flux between cell growth and butyrate biosynthesis in Escherichia coli

Microbial cell factories offer an economic and environmentally friendly method for the biosynthesis of acetyl-CoA-derived chemicals. However, the static control of carbon flux can cause direct and indirect competition for acetyl-CoA between cell growth and chemical biosynthesis, limiting the efficiency of microbial cell factories. Herein, recombinase-based genetic circuits were developed to achieve the optimal distribution of acetyl-CoA between cell growth and butyrate biosynthesis. First, three dynamic devices-a turn-on switch, a turn-off switch, and a recombinase-based inverter (RBI)-were constructed based on Bxb1 recombinase. Then, the turn-on switch was used to dynamically control the butyrate biosynthetic pathway, which directly improved the consumption of acetyl-CoA. Next, the turn-off switch was applied to dynamically control cell growth, which indirectly enhanced the supply of acetyl-CoA. Finally, an RBI was adopted for the dynamic dual control of the distribution of acetyl-CoA between cell growth and butyrate biosynthesis. The final butyrate production rate was increased to 34 g/L, with a productivity of 0.405 g/L/h. The strategy described herein will pave the way for the development of high-performance microbial cell factories for the production of other desirable chemicals. KEY POINTS: • Competition for acetyl-CoA between cell growth and synthesis limits productivity. • Recombinase-based genetic circuits were developed to dynamic control of acetyl-CoA. • Optimal distribution of acetyl-CoA between cell growth and synthesis was achieved.

Site-directed mutagenesis of the quorum-sensing transcriptional regulator SinR affects the biosynthesis of menaquinone in Bacillus subtilis

Background

Menaquinone (MK-7) is a highly valuable vitamin K₂ produced by Bacillus subtilis. Common static metabolic engineering approaches for promoting the production of MK-7 have been studied previously. However, these approaches caused an accumulation of toxic substances and reduced product yield. Hence, dynamic regulation by the quorum sensing (QS) system is a promising method for achieving a balance between product synthesis and cell growth.

Results

In this study, the QS transcriptional regulator SinR, which plays a significant role in biofilm formation and MK production simultaneously, was selected, and its site-directed mutants were constructed. Among these mutants, sinR knock out strain (KO-SinR) increased the biofilm biomass by 2.8-fold compared to the wild-type. SinR^quad maximized the yield of MK-7 (102.56 ± 2.84 mg/L). To decipher the mechanism of how this mutant regulates MK-7 synthesis and to find additional potential regulators that enhance MK-7 synthesis, RNA-seq was used to analyze expression changes in the QS system, biofilm formation, and MK-7 synthesis pathway. The results showed that the expressions of tapA, tasA and epsE were up-regulated 9.79-, 0.95-, and 4.42-fold, respectively. Therefore, SinR^quad formed more wrinkly and smoother biofilms than BS168. The upregulated expressions of glpF, glpk, and glpD in this biofilm morphology facilitated the flow of glycerol through the biofilm. In addition, NADH dehydrogenases especially sdhA, sdhB, sdhC and glpD, increased 1.01-, 3.93-, 1.87-, and 1.11-fold, respectively. The increased expression levels of NADH dehydrogenases indicated that more electrons were produced for the electron transport system. Electrical hyperpolarization stimulated the synthesis of the electron transport chain components, such as cytochrome c and MK, to ensure the efficiency of electron transfer. Wrinkly and smooth biofilms formed a network of interconnected channels with a low resistance to liquid flow, which was beneficial for the uptake of glycerol, and facilitated the metabolic flux of four modules of the MK-7 synthesis pathway.

Conclusions

In this study, we report for the first time that SinR^quad has significant effects on MK-7 synthesis by forming wrinkly and smooth biofilms, upregulating the expression level of most NADH dehydrogenases, and providing higher membrane potential to stimulate the accumulation of the components in the electron transport system.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-021-01603-5.

Dynamic Control of Metabolism

Metabolic engineering reprograms cells to synthesize value-added products. In doing so, endogenous genes are altered and heterologous genes can be introduced to achieve the necessary enzymatic reactions. Dynamic regulation of metabolic flux is a powerful control scheme to alleviate and overcome the competing cellular objectives that arise from the introduction of these production pathways. This review explores dynamic regulation strategies that have demonstrated significant production benefits by targeting the metabolic node corresponding to a specific challenge. We summarize the stimulus-responsive control circuits employed in these strategies that determine the criterion for actuating a dynamic response and then examine the points of control that couple the stimulus-responsive circuit to a shift in metabolic flux.

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.

Dynamic Control of Gene Expression with Riboregulated Switchable Feedback Promoters

One major challenge in synthetic biology is the deleterious impacts of cellular stress caused by expression of heterologous pathways, sensors, and circuits. Feedback control and dynamic regulation are broadly proposed strategies to mitigate this cellular stress by optimizing gene expression levels temporally and in response to biological cues. While a variety of approaches for feedback implementation exist, they are often complex and cannot be easily manipulated. Here, we report a strategy that uses RNA transcriptional regulators to integrate additional layers of control over the output of natural and engineered feedback responsive circuits. Called riboregulated switchable feedback promoters (rSFPs), these gene expression cassettes can be modularly activated using multiple mechanisms, from manual induction to autonomous quorum sensing, allowing control over the timing, magnitude, and autonomy of expression. We develop rSFPs in Escherichia coli to regulate multiple feedback networks and apply them to control the output of two metabolic pathways. We envision that rSFPs will become a valuable tool for flexible and dynamic control of gene expression in metabolic engineering, biological therapeutic production, and many other applications.

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

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

Improving the design of an oxidative stress sensing biosensor in yeast

Transcription factor (TF)-based biosensors have proven useful for increasing biomanufacturing yields, large-scale functional screening, and in environmental monitoring. Most yeast TF-based biosensors are built from natural promoters, resulting in large DNA parts retaining considerable homology to the host genome, which can complicate biological engineering efforts. There is a need to explore smaller, synthetic biosensors to expand the options for regulating gene expression in yeast. Here, we present a systematic approach to improving the design of an existing oxidative stress sensing biosensor in Saccharomyces cerevisiae based on the Yap1 transcription factor. Starting from a synthetic core promoter, we optimized the activity of a Yap1-dependent promoter through rational modification of a minimalist Yap1 upstream activating sequence. Our novel promoter achieves dynamic ranges of activation surpassing those of the previously engineered Yap1-dependent promoter, while reducing it to only 171 base pairs. We demonstrate that coupling the promoter to a positive-feedback-regulated TF further improves the biosensor by increasing its dynamic range of activation and reducing its limit of detection. We have illustrated the robustness and transferability of the biosensor by reproducing its activity in an unconventional probiotic yeast strain, Saccharomyces boulardii. Our findings can provide guidance in the general process of TF-based biosensor design.

Integrative Modeling of Gene Expression and Metabolic Networks of Arabidopsis Embryos for Identification of Seed Oil Causal Genes

Fatty acids in crop seeds are a major source for both vegetable oils and industrial applications. Genetic improvement of fatty acid composition and oil content is critical to meet the current and future demands of plant-based renewable seed oils. Addressing this challenge can be approached by network modeling to capture key contributors of seed metabolism and to identify underpinning genetic targets for engineering the traits associated with seed oil composition and content. Here, we present a dynamic model, using an Ordinary Differential Equations model and integrated time-course gene expression data, to describe metabolic networks during Arabidopsis thaliana seed development. Through in silico perturbation of genes, targets were predicted in seed oil traits. Validation and supporting evidence were obtained for several of these predictions using published reports in the scientific literature. Furthermore, we investigated two predicted targets using omics datasets for both gene expression and metabolites from the seed embryo, and demonstrated the applicability of this network-based model. This work highlights that integration of dynamic gene expression atlases generates informative models which can be explored to dissect metabolic pathways and lead to the identification of causal genes associated with seed oil traits.

Novel CRISPR-Cas Systems: An Updated Review of the Current Achievements, Applications, and Future Research Perspectives

According to Darwin's theory, endless evolution leads to a revolution. One such example is the Clustered Regularly Interspaced Palindromic Repeats (CRISPR)-Cas system, an adaptive immunity system in most archaea and many bacteria. Gene editing technology possesses a crucial potential to dramatically impact miscellaneous areas of life, and CRISPR-Cas represents the most suitable strategy. The system has ignited a revolution in the field of genetic engineering. The ease, precision, affordability of this system is akin to a Midas touch for researchers editing genomes. Undoubtedly, the applications of this system are endless. The CRISPR-Cas system is extensively employed in the treatment of infectious and genetic diseases, in metabolic disorders, in curing cancer, in developing sustainable methods for fuel production and chemicals, in improving the quality and quantity of food crops, and thus in catering to global food demands. Future applications of CRISPR-Cas will provide benefits for everyone and will save countless lives. The technology is evolving rapidly; therefore, an overview of continuous improvement is important. In this review, we aim to elucidate the current state of the CRISPR-Cas revolution in a tailor-made format from its discovery to exciting breakthroughs at the application level and further upcoming trends related to opportunities and challenges including ethical concerns.

Engineering a ComA Quorum-Sensing circuit to dynamically control the production of Menaquinone-4 in Bacillus subtilis

Menaquinone-4 (MK-4) plays a significant role in bone health and cardiovascular therapy. Although many strategies have been adopted to increase the yield of MK-4 in Bacillus subtilis 168, the effectiveness of MK-4 is still low due to the inherent limitations of metabolic pathways. However, dynamic regulation based on quorum sensing (QS) has been extensively applied as a fundamental tool for fine-tuning gene expression in reaction to changes in cell density without adding expensive inducers. Nevertheless, in most reports, QS systems depend on down-regulated expression rather than up-regulated expression, which greatly limit their potential as molecular switches to control metabolic flux. To address this challenge, a modular PhrQ-RapQ-ComA QS system is developed based on promoter P_A11, which is up-regulated by phosphorylated ComA (ComA-P). In this paper, firstly we analyzed the ComA-based gene expression regulation system in Bacillus subtilis 168. We constructed a promoter library of diff ;erent abilities, selected best promoters from a library, and performed mutation screening on the selected promoters. Furthermore, we constructed a PhrQ-RapQ-ComA QS system to dynamically control the synthesis of MK-4 in B. subtilis 168. Cell growth and efficient synthesis of the target product can be dynamically balanced by the QS system. Our dynamic adjustment approach increased the yield of MK-4 in shake flask from 120.1 ± 0.6 to 178.9 ± 2.8 mg/L, and reached 217 ± 4.1 mg/L in a 3-L bioreactor, which verified the effectiveness of this strategy. In summary, PhrQ-RapQ-ComA QS system can realize dynamic pathway regulation in B. subtilis 168, which can be stretched to a great deal of microorganisms to fine-tune gene expression and enhance the production of metabolites.

Switching metabolic flux by engineering tryptophan operon-assisted CRISPR interference system in Klebsiella pneumoniae

One grand challenge for bioproduction of desired metabolites is how to coordinate cell growth and product synthesis. Here we report that a tryptophan operon-assisted CRISPR interference (CRISPRi) system can switch glycerol oxidation and reduction pathways in Klebsiella pneumoniae, whereby the oxidation pathway provides energy to sustain growth, and the reduction pathway generates 1,3-propanediol and 3-hydroxypropionic acid (3-HP), two economically important chemicals. Reverse transcription and quantitative PCR (RT-qPCR) showed that this CRISPRi-dependent switch affected the expression of glycerol metabolism-related genes and in turn improved 3-HP production. In shake-flask cultivation, the strain coexpressing dCas9-sgRNA and PuuC (an aldehyde dehydrogenase native to K. pneumoniae for 3-HP biosynthesis) produced 3.6 g/L 3-HP, which was 1.62 times that of the strain only overexpressing PuuC. In a 5 L bioreactor, this CRISPRi strain produced 58.9 g/L 3-HP. When circulation feeding was implemented to alleviate metabolic stress, biomass was substantially improved and 88.8 g/L 3-HP was produced. These results indicated that this CRISPRi-dependent switch can efficiently reconcile biomass formation and 3-HP biosynthesis. Furthermore, this is the first report of coupling CRISPRi system with trp operon, and this architecture holds huge potential in regulating gene expression and allocating metabolic flux.

Reversible thermal regulation for bifunctional dynamic control of gene expression in Escherichia coli

Genetically programmed circuits allowing bifunctional dynamic regulation of enzyme expression have far-reaching significances for various bio-manufactural purposes. However, building a bio-switch with a post log-phase response and reversibility during scale-up bioprocesses is still a challenge in metabolic engineering due to the lack of robustness. Here, we report a robust thermosensitive bio-switch that enables stringent bidirectional control of gene expression over time and levels in living cells. Based on the bio-switch, we obtain tree ring-like colonies with spatially distributed patterns and transformer cells shifting among spherical-, rod- and fiber-shapes of the engineered Escherichia coli. Moreover, fed-batch fermentations of recombinant E. coli are conducted to obtain ordered assembly of tailor-made biopolymers polyhydroxyalkanoates including diblock- and random-copolymer, composed of 3-hydroxybutyrate and 4-hydroxybutyrate with controllable monomer molar fraction. This study demonstrates the possibility of well-organized, chemosynthesis-like block polymerization on a molecular scale by reprogrammed microbes, exemplifying the versatility of thermo-response control for various practical uses.

Transcription Factor-Based Biosensor for Dynamic Control in Yeast for Natural Product Synthesis

The synthesis of natural products in yeast has gained remarkable achievements with intensive metabolic engineering efforts. In particular, transcription factor (TF)-based biosensors for dynamic control of gene circuits could facilitate strain evaluation, high-throughput screening (HTS), and adaptive laboratory evolution (ALE) for natural product synthesis. In this review, we summarized recent developments of several TF-based biosensors for core intermediates in natural product synthesis through three important pathways, i.e., fatty acid synthesis pathway, shikimate pathway, and methylerythritol-4-phosphate (MEP)/mevalonate (MVA) pathway. Moreover, we have shown how these biosensors are implemented in synthetic circuits for dynamic control of natural product synthesis and also discussed the design/evaluation principles for improved biosensor performance.

Fine tuning the glycolytic flux ratio of EP-bifido pathway for mevalonate production by enhancing glucose-6-phosphate dehydrogenase (Zwf) and CRISPRi suppressing 6-phosphofructose kinase (PfkA) in Escherichia coli

BACKGROUND

Natural glycolysis encounters the decarboxylation of glucose partial oxidation product pyruvate into acetyl-CoA, where one-third of the carbon is lost at CO₂. We previously constructed a carbon saving pathway, EP-bifido pathway by combining Embden-Meyerhof-Parnas Pathway, Pentose Phosphate Pathway and "bifid shunt", to generate high yield acetyl-CoA from glucose. However, the carbon conversion rate and reducing power of this pathway was not optimal, the flux ratio of EMP pathway and pentose phosphate pathway (PPP) needs to be precisely and dynamically adjusted to improve the production of mevalonate (MVA).

RESULT

Here, we finely tuned the glycolytic flux ratio in two ways. First, we enhanced PPP flux for NADPH supply by replacing the promoter of zwf on the genome with a set of different strength promoters. Compared with the previous EP-bifido strains, the zwf-modified strains showed obvious differences in NADPH, NADH, and ATP synthesis levels. Among them, strain BP10BF accumulated 11.2 g/L of MVA after 72 h of fermentation and the molar conversion rate from glucose reached 62.2%. Second, pfkA was finely down-regulated by the clustered regularly interspaced short palindromic repeats interference (CRISPRi) system. The MVA yield of the regulated strain BiB1F was 8.53 g/L, and the conversion rate from glucose reached 68.7%.

CONCLUSION

This is the highest MVA conversion rate reported in shaken flask fermentation. The CRISPRi and promoter fine-tuning provided an effective strategy for metabolic flux redistribution in many metabolic pathways and promotes the chemicals production.

Optimization of a p-Coumaric Acid Biosensor System for Versatile Dynamic Performance

Metabolic engineering is a promising approach for the synthesis of valuable compounds. Transcriptional factor-based biosensors are efficient tools to regulate the metabolic pathway dynamically. Here, we engineered the p-coumaric acid responsive regulator PadR from Bacillus subtilis. We found that yveF and yveG, two previously uncharacterized components in the sensor system, showed positive impacts on the regulation of PadR-P_padC sensor system, mostly on assisting the release of the repression by PadR. By site directed PadR engineering, we obtained two mutants, K64A and H38A, which exhibited increased dynamic range and superior sensitivity. To increase the promoter strength of the sensor system and investigate whether the PadR binding boxes can function in a "plug-and-play" manner, a series of hybrid promoters were constructed. Four of them, P1, P2, P7, and P9, showed increased strength compared to P_padC and can be regulated by PadR and p-coumaric acid. The PadR variants and hybrid promoters obtained in this paper would expand the applicability of this sensor system in future metabolic engineering research.