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

Application Evaluation and Performance-Directed Improvement of the Native and Engineered Biosensors

Transcription factor (TF)-based biosensors (TFBs) have received considerable attention in various fields due to their capability of converting biosignals, such as molecule concentrations, into analyzable signals, thereby bypassing the dependence on time-consuming and laborious detection techniques. Natural TFs are evolutionarily optimized to maintain microbial survival and metabolic balance rather than for laboratory scenarios. As a result, native TFBs often exhibit poor performance, such as low specificity, narrow dynamic range, and limited sensitivity, hindering their application in laboratory and industrial settings. This work analyzes four types of regulatory mechanisms underlying TFBs and outlines strategies for constructing efficient sensing systems. Recent advances in TFBs across various usage scenarios are reviewed with a particular focus on the challenges of commercialization. The systematic improvement of TFB performance by modifying the constituent elements is thoroughly discussed. Additionally, we propose future directions of TFBs for developing rapid-responsive biosensors and addressing the challenge of application isolation. Furthermore, we look to the potential of artificial intelligence (AI) technologies and various models for programming TFB genetic circuits. This review sheds light on technical suggestions and fundamental instructions for constructing and engineering TFBs to promote their broader applications in Industry 4.0, including smart biomanufacturing, environmental and food contaminants detection, and medical science.

Design of Thermoresponsive Genetic Controls with Minimal Heat-Shock Response

As temperature serves as a versatile input signal, thermoresponsive genetic controls have gained significant interest for recombinant protein production and metabolic engineering applications. The conventional thermoresponsive systems normally require the continuous exposure of heat stimuli to trigger the prolonged expression of targeted genes, and the accompanied heat-shock response is detrimental to the bioproduction process. In this study, we present the design of thermoresponsive quorum-sensing (ThermoQS) circuits to make Escherichia coli record transient heat stimuli. By conversion of the heat input into the accumulation of quorum-sensing molecules such as acyl-homoserine lactone derived from Pseudomonas aeruginosa, sustained gene expressions were achieved by a minimal heat stimulus. Moreover, we also demonstrated that we reprogrammed the E. coli Lac operon to make it respond to heat stimuli with an impressive signal-to-noise ratio (S/N) of 15.3. Taken together, we envision that the ThermoQS systems reported in this study are expected to remarkably diminish both design and experimental expenditures for future metabolic engineering applications.

GenoMine: a CRISPR-Cas9-based kill switch for biocontainment of Pseudomonas putida

Synthetic genetic circuits have revolutionised our capacity to control cell viability by conferring microorganisms with programmable functionalities to limit survival to specific environmental conditions. Here, we present the GenoMine safeguard, a CRISPR-Cas9-based kill switch for the biotechnological workhorse Pseudomonas putida that employs repetitive genomic elements as cleavage targets to unleash a highly genotoxic response. To regulate the system's activation, we tested various circuit-based mechanisms including the digitalised version of an inducible expression system that operates at the transcriptional level and different options of post-transcriptional riboregulators. All of them were applied not only to directly control Cas9 and its lethal effects, but also to modulate the expression of two of its inhibitors: the AcrIIA4 anti-CRISPR protein and the transcriptional repressor TetR. Either upon direct induction of the endonuclease or under non-induced conditions of its inhibitors, the presence of Cas9 suppressed cell survival which could be exploited beyond biocontainment in situations where further CRISPR genome editing is undesirable.

Relieving metabolic burden to improve robustness and bioproduction by industrial microorganisms

Metabolic burden is defined by the influence of genetic manipulation and environmental perturbations on the distribution of cellular resources. The rewiring of microbial metabolism for bio-based chemical production often leads to a metabolic burden, followed by adverse physiological effects, such as impaired cell growth and low product yields. Alleviating the burden imposed by undesirable metabolic changes has become an increasingly attractive approach for constructing robust microbial cell factories. In this review, we provide a brief overview of metabolic burden engineering, focusing specifically on recent developments and strategies for diminishing the burden while improving robustness and yield. A variety of examples are presented to showcase the promise of metabolic burden engineering in facilitating the design and construction of robust microbial cell factories. Finally, challenges and limitations encountered in metabolic burden engineering are discussed.

Synthetic gene circuit evolution: Insights and opportunities at the mid-scale

Directed evolution focuses on optimizing single genetic components for predefined engineering goals by artificial mutagenesis and selection. In contrast, experimental evolution studies the adaptation of entire genomes in serially propagated cell populations, to provide an experimental basis for evolutionary theory. There is a relatively unexplored gap at the middle ground between these two techniques, to evolve in vivo entire synthetic gene circuits with nontrivial dynamic function instead of single parts or whole genomes. We discuss the requirements for such mid-scale evolution, with hypothetical examples for evolving synthetic gene circuits by appropriate selection and targeted shuffling of a seed set of genetic components in vivo. Implementing similar methods should aid the rapid generation, functionalization, and optimization of synthetic gene circuits in various organisms and environments, accelerating both the development of biomedical and technological applications and the understanding of principles guiding regulatory network evolution.

Application of modern synthetic biology technology in aromatic amino acids and derived compounds biosynthesis

Aromatic amino acids (AAA) and derived compounds have enormous commercial value with extensive applications in the food, chemical and pharmaceutical fields. Microbial production of AAA and derived compounds is a promising prospect for its environmental friendliness and sustainability. However, low yield and production efficiency remain major challenges for realizing industrial production. With the advancement of synthetic biology, microbial production of AAA and derived compounds has been significantly facilitated. In this review, a comprehensive overview on the current progresses, challenges and corresponding solutions for AAA and derived compounds biosynthesis is provided. The most cutting-edge developments of synthetic biology technology in AAA and derived compounds biosynthesis, including CRISPR-based system, genetically encoded biosensors and synthetic genetic circuits, were highlighted. Finally, future prospects of modern strategies conducive to the biosynthesis of AAA and derived compounds are discussed. This review offers guidance on constructing microbial cell factory for aromatic compound using synthetic biology technology.

Engineering microbial metabolic homeostasis for chemicals production

Microbial-based bio-refining promotes the development of a biotechnology revolution to encounter and tackle the enormous challenges in petroleum-based chemical production by biomanufacturing, biocomputing, and biosensing. Nevertheless, microbial metabolic homeostasis is often incompatible with the efficient synthesis of bioproducts mainly due to: inefficient metabolic flow, robust central metabolism, sophisticated metabolic network, and inevitable environmental perturbation. Therefore, this review systematically summarizes how to optimize microbial metabolic homeostasis by strengthening metabolic flux for improving biotransformation turnover, redirecting metabolic direction for rewiring bypass pathway, and reprogramming metabolic network for boosting substrate utilization. Future directions are also proposed for providing constructive guidance on the development of industrial biotechnology.

Genetically encoded Boolean logic operators to sense and integrate phenylpropanoid metabolite levels in plants

Synthetic biology has the potential to revolutionize biotechnology, public health, and agriculture. Recent studies have shown the enormous potential of plants as chassis for synthetic biology applications. However, tools to precisely manipulate metabolic pathways for bioproduction in plants are still needed. We used bacterial allosteric transcription factors (aTFs) that control gene expression in a ligand-specific manner and tested their ability to repress semi-synthetic promoters in plants. We also tested the modulation of their repression activity in response to specific plant metabolites, especially phenylpropanoid-related molecules. Using these aTFs, we also designed synthetic genetic circuits capable of computing Boolean logic operations. Three aTFs, CouR, FapR, and TtgR, achieved c. 95% repression of their respective target promoters. For TtgR, a sixfold de-repression could be triggered by inducing its ligand accumulation, showing its use as biosensor. Moreover, we designed synthetic genetic circuits that use AND, NAND, IMPLY, and NIMPLY Boolean logic operations and integrate metabolite levels as input to the circuit. We showed that biosensors can be implemented in plants to detect phenylpropanoid-related metabolites and activate a genetic circuit that follows a predefined logic, demonstrating their potential as tools for exerting control over plant metabolic pathways and facilitating the bioproduction of natural products.

Engineering Chimeric Chemoreceptors and Two-Component Systems for Orthogonal and Leakless Biosensing of Extracellular γ-Aminobutyric Acid

Two-component systems (TCSs) sensing and responding to various stimuli outside and inside cells are valuable resources for developing biosensors with synthetic biology applications. However, the use of TCS-based biosensors suffers from a limited effector spectrum, hypersensitivity, low dynamic range, and unwanted signal crosstalk. Here, we developed a tailor-made Escherichia coli whole-cell γ-aminobutyric acid (GABA) biosensor by engineering a chimeric GABA chemoreceptor PctC and TCS. By testing different TCSs, the chimeric PctC/PhoQ showed the response to GABA. Chimera-directed evolution and introduction of the insulated chimeric pair PctC/PhoQ*PhoP* produced biosensors with up to 3.50-fold dynamic range and good orthogonality. To further enhance the dynamic range and lower the basal leakage, three strategies, engineering of PhoP DNA binding sites, fine-tuning reporter expression by optimizing transcription/translation components, and a tobacco etch virus protease-controlled protein degradation, were integrated. This chimeric biosensor displayed a low basal leakage, a large dynamic range (15.8-fold), and a high threshold level (22.7 g L-1). Finally, the optimized biosensor was successfully applied in the high-throughput microdroplet screening of GABA-overproducing Corynebacterium glutamicum, demonstrating its desired properties for extracellular signal biosensing.

Species-specific design of artificial promoters by transfer-learning based generative deep-learning model

Native prokaryotic promoters share common sequence patterns, but are species dependent. For understudied species with limited data, it is challenging to predict the strength of existing promoters and generate novel promoters. Here, we developed PromoGen, a collection of nucleotide language models to generate species-specific functional promoters, across dozens of species in a data and parameter efficient way. Twenty-seven species-specific models in this collection were finetuned from the pretrained model which was trained on multi-species promoters. When systematically compared with native promoters, the Escherichia coli- and Bacillus subtilis-specific artificial PromoGen-generated promoters (PGPs) were demonstrated to hold all distribution patterns of native promoters. A regression model was developed to score generated either by PromoGen or by another competitive neural network, and the overall score of PGPs is higher. Encouraged by in silico analysis, we further experimentally characterized twenty-two B. subtilis PGPs, results showed that four of tested PGPs reached the strong promoter level while all were active. Furthermore, we developed a user-friendly website to generate species-specific promoters for 27 different species by PromoGen. This work presented an efficient deep-learning strategy for de novo species-specific promoter generation even with limited datasets, providing valuable promoter toolboxes especially for the metabolic engineering of understudied microorganisms.

Fine-Tuning Pyridoxal 5'-Phosphate Synthesis in Escherichia coli for Cadaverine Production in Minimal Culture Media

Cadaverine is a critical C5 monomer for the production of polyamides. Pyridoxal 5'-phosphate (PLP), as a crucial cofactor for the key enzyme lysine decarboxylase in the cadaverine biosynthesis pathway, has seen a persistent shortage, leading to limitations in cadaverine production. To address this issue, a dual-pathway strategy was implemented, synergistically enhancing both endogenous and heterologous PLP synthesis modules and resulting in improved PLP synthesis. Subsequently, a growth-stage-dependent molecular switch was introduced to balance the precursor competition between PLP synthesis and cell growth. Additionally, a PLP sensor-based negative feedback circuit was constructed by integrating a newly identified PLP-responsive promoter PygjH and an arabinose-regulated system, dynamically regulating the expression of the PLP synthetic genes and preventing excessive intracellular PLP accumulation. The optimal strain, L18, cultivated in the minimal medium AM1, demonstrated cadaverine production with a titer, yield, and productivity of 64.03 g/L, 0.23 g/g glucose, and 1.33 g/L/h, respectively. This represents the highest titer reported to date in engineered Escherichia coli by fed-batch fermentation in a minimal medium.

Transcription factor-based biosensor: A molecular-guided approach for advanced biofuel synthesis

As a sustainable and renewable alternative to petroleum fuels, advanced biofuels shoulder the responsibility of energy saving, emission reduction and environmental protection. Traditional engineering of cell factories for production of advanced biofuels lacks efficient high-throughput screening tools and regulating systems, impeding the improvement of cellular productivity and yield. Transcription factor-based biosensors have been widely applied to monitor and regulate microbial cell factory products due to the advantages of fast detection and in-situ screening. This review updates the design and application of transcription factor-based biosensors tailored for advanced biofuels and related intermediates. The construction and genetic parts selection principle of biosensors are discussed. Strategies to enhance the performance of biosensor, including regulating promoter strength and RBS strength, optimizing plasmid copy number, implementing genetic amplifier, and modulating the structure of transcription factor, have also been summarized. We further review the application of biosensors in high-throughput screening of new metabolic engineering targets, evolution engineering, confirmation of protein function, and dynamic regulation of metabolic flux for higher production of advanced biofuels. At last, we discuss the current limitations and future trends of transcription factor-based biosensors.

Highly multiplexed design of an allosteric transcription factor to sense novel ligands

Allosteric transcription factors (aTF), widely used as biosensors, have proven challenging to design for detecting novel molecules because mutation of ligand-binding residues often disrupts allostery. We developed Sensor-seq, a high-throughput platform to design and identify aTF biosensors that bind to non-native ligands. We screened a library of 17,737 variants of the aTF TtgR, a regulator of a multidrug exporter, against six non-native ligands of diverse chemical structures - four derivatives of the cancer therapeutic tamoxifen, the antimalarial drug quinine, and the opiate analog naltrexone - as well as two native flavonoid ligands, naringenin and phloretin. Sensor-seq identified novel biosensors for each of these ligands with high dynamic range and diverse specificity profiles. The structure of a naltrexone-bound design showed shape-complementary methionine-aromatic interactions driving ligand specificity. To demonstrate practical utility, we developed cell-free detection systems for naltrexone and quinine. Sensor-seq enables rapid, scalable design of new biosensors, overcoming constraints of natural biosensors.

Standardized Iterative Genome Editing Method for Escherichia coli Based on CRISPR-Cas9

The introduction of complex biosynthetic pathways into the hosts' chromosomes is gaining attention with the development of synthetic biology. While CRISPR-Cas9 has been widely employed for gene knock-in, the process of multigene insertion remains cumbersome due to laborious and empirical gene cloning procedures. To address this, we devised a standardized iterative genome editing system for Escherichia coli, harnessing the power of CRISPR-Cas9 and MetClo assembly. This comprehensive toolkit comprises two fundamental elements based on the Golden Gate standard for modular assembly of sgRNA or CRISPR arrays and donor DNAs. We achieved a gene insertion efficiency of up to 100%, targeting a single locus. Expression of tracrRNA using a strong promoter enhances multiplex genomic insertion efficiency to 7.3%, compared with 0.76% when a native promoter is used. To demonstrate the robust capabilities of this genome editing toolbox, we successfully integrated 5-10 genes from the coenzyme B12 biosynthetic pathway ranging from 5.3 to 8 Kb in length into the chromosome of E. coli chassis cells, resulting in 14 antibiotic-free, plasmid-free producers. Following an extensive screening process involving genes from diverse sources, cistronic design modifications, and chromosome repositioning, we obtained a recombinant strain yielding 1.49 mg L-1 coenzyme B12, the highest known titer achieved by using E. coli as the producer. Illuminating its user-friendliness, this genome editing system is an exceedingly versatile tool for expediently integrating complex biosynthetic pathway genes into hosts' genomes, thus facilitating pathway optimization for chemical production.

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

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

Unleashing the capacity of Rhodococcus for converting lignin into lipids

Bioconversion of bioresources/wastes (e.g., lignin, chemical pulping byproducts) represents a promising approach for developing a bioeconomy to help address growing energy and materials demands. Rhodococcus, a promising microbial strain, utilizes numerous carbon sources to produce lipids, which are precursors for synthesizing biodiesel and aviation fuels. However, compared to chemical conversion, bioconversion involves living cells, which is a more complex system that needs further understanding and upgrading. Various wastes amenable to bioconversion are reviewed herein to highlight the potential of Rhodococci for producing lipid-derived bioproducts. In light of the abundant availability of these substrates, Rhodococcus' metabolic pathways converting them to lipids are analyzed from a "beginning-to-end" view. Based on an in-depth understanding of microbial metabolic routes, genetic modifications of Rhodococcus by employing emerging tools (e.g., multiplex genome editing, biosensors, and genome-scale metabolic models) are presented for promoting the bioconversion. Co-solvent enhanced lignocellulose fractionation (CELF) strategy facilitates the generation of a lignin-derived aromatic stream suitable for the Rhodococcus' utilization. Novel alkali sterilization (AS) and elimination of thermal sterilization (ETS) approaches can significantly enhance the bioaccessibility of lignin and its derived aromatics in aqueous fermentation media, which promotes lipid titer significantly. In order to achieve value-added utilization of lignin, biodiesel and aviation fuel synthesis from lignin and lipids are further discussed. The possible directions for unleashing the capacity of Rhodococcus through synergistically modifying microbial strains, substrates, and fermentation processes are proposed toward a sustainable biological lignin valorization.

Genetically encoded ATP and NAD(P)H biosensors: potential tools in metabolic engineering

To date, many metabolic engineering tools and strategies have been developed, including tools for cofactor engineering, which is a common strategy for bioproduct synthesis. Cofactor engineering is used for the regulation of pyridine nucleotides, including NADH/NAD+ and NADPH/NADP+, and adenosine triphosphate/adenosine diphosphate (ATP/ADP), which is crucial for maintaining redox and energy balance. However, the intracellular levels of NADH/NAD+, NADPH/NADP+, and ATP/ADP cannot be monitored in real time using traditional methods. Recently, many biosensors for detecting, monitoring, and regulating the intracellular levels of NADH/NAD+, NADPH/NADP+, and ATP/ADP have been developed. Although cofactor biosensors have been mainly developed for use in mammalian cells, the potential application of cofactor biosensors in metabolic engineering in bacterial and yeast cells has received recent attention. Coupling cofactor biosensors with genetic circuits is a promising strategy in metabolic engineering for optimizing the production of biochemicals. In this review, we focus on the development of biosensors for NADH/NAD+, NADPH/NADP+, and ATP/ADP and the potential application of these biosensors in metabolic engineering. We also provide critical perspectives, identify current research challenges, and provide guidance for future research in this promising field.

Mechanisms and biotechnological applications of transcription factors

Transcription factors play an indispensable role in maintaining cellular viability and finely regulating complex internal metabolic networks. These crucial bioactive functions rely on their ability to respond to effectors and concurrently interact with binding sites. Recent advancements have brought innovative insights into the understanding of transcription factors. In this review, we comprehensively summarize the mechanisms by which transcription factors carry out their functions, along with calculation and experimental-based methods employed in their identification. Additionally, we highlight recent achievements in the application of transcription factors in various biotechnological fields, including cell engineering, human health, and biomanufacturing. Finally, the current limitations of research and provide prospects for future investigations are discussed. This review will provide enlightening theoretical guidance for transcription factors engineering.

Metabolic engineering of oleaginous yeast in the lipogenic phase enhances production of nervonic acid

Insufficient biosynthesis efficiency during the lipogenic phase can be a major obstacle to engineering oleaginous yeasts to overproduce very long-chain fatty acids (VLCFAs). Taking nervonic acid (NA, C24:1) as an example, we overcame the bottleneck to overproduce NA in an engineered Rhodosporidium toruloides by improving the biosynthesis of VLCFAs during the lipogenic phase. First, evaluating the catalytic preferences of three plant-derived ketoacyl-CoA synthases (KCSs) rationally guided reconstructing an efficient NA biosynthetic pathway in R. toruloides. More importantly, a genome-wide transcriptional analysis endowed clues to strengthen the fatty acid elongation (FAE) module and identify/use lipogenic phase-activated promoter, collectively addressing the stagnation of NA accumulation during the lipogenic phase. The best-designed strain exhibited a high NA content (as the major component in total fatty acid [TFA], 46.3%) and produced a titer of 44.2 g/L in a 5 L bioreactor. The strategy developed here provides an engineering framework to establish the microbial process of producing valuable VLCFAs in oleaginous yeasts.

Biosensors in microalgae: A roadmap for new opportunities in synthetic biology and biotechnology

Biosensors are powerful tools to investigate, phenotype, improve and prototype microbial strains, both in fundamental research and in industrial contexts. Genetic and biotechnological developments now allow the implementation of synthetic biology approaches to novel different classes of microbial hosts, for example photosynthetic microalgae, which offer unique opportunities. To date, biosensors have not yet been implemented in phototrophic eukaryotic microorganisms, leaving great potential for novel biological and technological advancements untapped. Here, starting from selected biosensor technologies that have successfully been implemented in heterotrophic organisms, we project and define a roadmap on how these could be applied to microalgae research. We highlight novel opportunities for the development of new biosensors, identify critical challenges, and finally provide a perspective on the impact of their eventual implementation to tackle research questions and bioengineering strategies. From studying metabolism at the single-cell level to genome-wide screen approaches, and assisted laboratory evolution experiments, biosensors will greatly impact the pace of progress in understanding and engineering microalgal metabolism. We envision how this could further advance the possibilities for unraveling their ecological role, evolutionary history and accelerate their domestication, to further drive them as resource-efficient production hosts.

Effect of fatty acids on intracellular pneumocandin B0 storage in the fermentation of Glarea lozoyensis

The natural product pneumocandin B0 is the precursor of the antifungal drug caspofungin. To explore the relationship between pneumocandin B0 and oil. We found that the addition of 1 g/L of oil to the fermentation medium is more conducive to the production of pneumocandin B0. The metabolic reaction mechanism was explored using different fatty acids and the results showed that stearic acid and acetic acid increased the total production of pneumocandin B0 by 22.98% and 9.08%, respectively, as well as increasing the content of intracellular lipid droplets. We also analyzed gene expression and pathway differences between the two different fatty acids using transcriptome analyses. The addition of both acetic acid and stearic acid promoted an active pentose phosphate pathway, providing cells with higher intracellular reducing power. We found that the addition of fatty acids can lead to lipid accumulation, and lipid droplets can sequester lipophilic secondary metabolites such as pneumocandin B0 to reduce cell damage. These results provide novel insights into the relationship between pneumocandin B0 biosynthesis and fatty acids in G. lozoyensis. In addition, this study provides important genetic information for improving the yield of pneumocandin B0 through a strategy of metabolic engineering in the future.

Dynamic Metabolic Control: From the Perspective of Regulation Logic

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

Towards universal synthetic heterotrophy using a metabolic coordinator

Engineering the utilization of non-native substrates, or synthetic heterotrophy, in proven industrial microbes such as Saccharomyces cerevisiae represents an opportunity to valorize plentiful and renewable sources of carbon and energy as inputs to bioprocesses. We previously demonstrated that activation of the galactose (GAL) regulon, a regulatory structure used by this yeast to coordinate substrate utilization with biomass formation during growth on galactose, during growth on the non-native substrate xylose results in a vastly altered gene expression profile and faster growth compared with constitutive overexpression of the same heterologous catabolic pathway. However, this effort involved the creation of a xylose-inducible variant of Gal3p (Gal3pSyn4.1), the sensor protein of the GAL regulon, preventing this semi-synthetic regulon approach from being easily adapted to additional non-native substrates. Here, we report the construction of a variant Gal3pMC (metabolic coordinator) that exhibits robust GAL regulon activation in the presence of structurally diverse substrates and recapitulates the dynamics of the native system. Multiple molecular modeling studies suggest that Gal3pMC occupies conformational states corresponding to galactose-bound Gal3p in an inducer-independent manner. Using Gal3pMC to test a regulon approach to the assimilation of the non-native lignocellulosic sugars xylose, arabinose, and cellobiose yields higher growth rates and final cell densities when compared with a constitutive overexpression of the same set of catabolic genes. The subsequent demonstration of rapid and complete co-utilization of all three non-native substrates suggests that Gal3pMC-mediated dynamic global gene expression changes by GAL regulon activation may be universally beneficial for engineering synthetic heterotrophy.

A novel strategy for L-arginine production in engineered Escherichia coli

BACKGROUND

L-arginine is an important amino acid with applications in diverse industrial and pharmaceutical fields. N-acetylglutamate, synthesized from L-glutamate and acetyl-CoA, is a precursor of the L-arginine biosynthetic branch in microorganisms. The enzyme that produces N-acetylglutamate, N-acetylglutamate synthase, is allosterically inhibited by L-arginine. L-glutamate, as a central metabolite, provides carbon backbone for diverse biological compounds besides L-arginine. When glucose is the sole carbon source, the theoretical maximum carbon yield towards L-arginine is 96.7%, but the experimental highest yield was 51%. The gap of L-arginine yield indicates the regulation complexity of carbon flux and energy during the L-arginine biosynthesis. Besides endogenous biosynthesis, N-acetylglutamate, the key precursor of L-arginine, can be obtained by chemical acylation of L-glutamate with a high yield of 98%. To achieve high-yield production of L-arginine, we demonstrated a novel approach by directly feeding precursor N-acetylglutamate to engineered Escherichia coli.

RESULTS

We reported a new approach for the high yield of L-arginine production in E. coli. Gene argA encoding N-acetylglutamate synthase was deleted to disable endogenous biosynthesis of N-acetylglutamate. The feasibility of external N-acetylglutamate towards L-arginine was verified via growth assay in argA- strain. To improve L-arginine production, astA encoding arginine N-succinyltransferase, speF encoding ornithine decarboxylase, speB encoding agmatinase, and argR encoding an arginine responsive repressor protein were disrupted. Based on overexpression of argDGI, argCBH operons, encoding enzymes of the L-arginine biosynthetic pathway, ~ 4 g/L L-arginine was produced in shake flask fermentation, resulting in a yield of 0.99 mol L-arginine/mol N-acetylglutamate. This strain was further engineered for the co-production of L-arginine and pyruvate by removing genes adhE, ldhA, poxB, pflB, and aceE, encoding enzymes involved in the conversion and degradation of pyruvate. The resulting strain was shown to produce 4 g/L L-arginine and 11.3 g/L pyruvate in shake flask fermentation.

CONCLUSIONS

Here, we developed a novel approach to avoid the strict regulation of L-arginine on ArgA and overcome the metabolism complexity in the L-arginine biosynthesis pathway. We achieve a high yield of L-arginine production from N-acetylglutamate in E. coli. Co-production pyruvate and L-arginine was used as an example to increase the utilization of input carbon sources.

"In vivo biosynthesis of N,N-dimethyltryptamine, 5-MeO-N,N-dimethyltryptamine, and bufotenine in E.coli"

N,N-dimethyltryptamine (DMT), 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) and 5-hydroxy-N,N-dimethyltryptamine (bufotenine) are psychedelic tryptamines found naturally in both plants and animals and have shown clinical potential to help treat mental disorders, such as anxiety and depression. Advances in both metabolic and genetic engineering make it possible to engineer microbes as cell factories to produce DMT and its aforementioned derivatives to meet demand for ongoing clinical study. Here, we present the development of a biosynthetic production pathway for DMT, 5-MeO-DMT, and bufotenine in the model microbe Escherichia coli. Through the application of genetic optimization techniques and process optimization in benchtop fermenters, the in vivo production of DMT in E. coli was observed. DMT production with tryptophan supplementation reached maximum titers of 74.7 ± 10.5 mg/L under fed batch conditions in a 2-L bioreactor. Additionally, we show the first reported case of de novo production of DMT (from glucose) in E. coli at a maximum titer of 14.0 mg/L and report the first example of microbial 5-MeO-DMT and bufotenine production in vivo. This work provides a starting point for further genetic and fermentation optimization studies with the goal to increase methylated tryptamine production metrics to industrially competitive levels.

Bayesian Optimization for Design of Multiscale Biological Circuits

Recent advances in synthetic biology have enabled the construction of molecular circuits that operate across multiple scales of cellular organization, such as gene regulation, signaling pathways, and cellular metabolism. Computational optimization can effectively aid the design process, but current methods are generally unsuited for systems with multiple temporal or concentration scales, as these are slow to simulate due to their numerical stiffness. Here, we present a machine learning method for the efficient optimization of biological circuits across scales. The method relies on Bayesian optimization, a technique commonly used to fine-tune deep neural networks, to learn the shape of a performance landscape and iteratively navigate the design space toward an optimal circuit. This strategy allows the joint optimization of both circuit architecture and parameters, and provides a feasible approach to solve a highly nonconvex optimization problem in a mixed-integer input space. We illustrate the applicability of the method on several gene circuits for controlling biosynthetic pathways with strong nonlinearities, multiple interacting scales, and using various performance objectives. The method efficiently handles large multiscale problems and enables parametric sweeps to assess circuit robustness to perturbations, serving as an efficient in silico screening method prior to experimental implementation.

Programming Super DNA-Enzyme Molecules for On-Demand Enzyme Activity Modulation

Dynamic interactions of enzymes, including programmable configuration and cycling of enzymes, play important roles in the regulation of cellular metabolism. Here, we constructed a super DNA-enzymes molecule (SDEM) that comprises at least two cascade enzymes and multiple linked DNA strands to control and detect metabolism. We found that the programmable SDEM, which comprises glucose oxidase (GOx) and horseradish peroxidase (HRP), has a 20-fold lower detection limit and a 1.6-fold higher reaction rate than free enzymes. An SDEM can be assembled and disassembled using a hairpin structure and a displacement DNA strand to complete multiple cycles. An entropically driven catalytic assembly (catassembly) enables different SDEMs to switch from an SDEM with GOx and HRP cascades to an SDEM with sarcosine oxidase (SOX) and HRP cascades in over six orders of magnitude less time than without the catassembly to detect different metabolisms (GO and sarcosine) on demand.

Phenotype-specific estimation of metabolic fluxes using gene expression data

A cell's genome influences its metabolism via the expression of enzyme-related genes, but transcriptome and fluxome are not perfectly correlated as post-transcriptional mechanisms also regulate reaction's kinetics. Here, we addressed the question: given a transcriptome, how unobserved mechanisms of reaction kinetics should be systematically accounted for when inferring the fluxome? To infer the most likely and least biased fluxome, we present Pheflux, a constraint-based model maximizing Shannon's entropy of fluxes per mRNA. Benchmarked against 13C fluxes of yeast and bacteria, Pheflux accurately estimates the carbon core metabolism. We applied Pheflux to thousands of normal and tumor cell transcriptomes obtained from The Cancer Genome Atlas. Pheflux showed statistically significantly higher glucose yields on lactate in breast, kidney, and bronchus-lung tumoral cells than their normal counterparts. Results are consistent with the Warburg effect, a hallmark of cancer metabolism, suggesting that Pheflux can be efficiently used to study the metabolism of eukaryotic cells.

Transcription factor-based biosensors for screening and dynamic regulation

Advances in synthetic biology and genetic engineering are bringing into the spotlight a wide range of bio-based applications that demand better sensing and control of biological behaviours. Transcription factor (TF)-based biosensors are promising tools that can be used to detect several types of chemical compounds and elicit a response according to the desired application. However, the wider use of this type of device is still hindered by several challenges, which can be addressed by increasing the current metabolite-activated transcription factor knowledge base, developing better methods to identify new transcription factors, and improving the overall workflow for the design of novel biosensor circuits. These improvements are particularly important in the bioproduction field, where researchers need better biosensor-based approaches for screening production-strains and precise dynamic regulation strategies. In this work, we summarize what is currently known about transcription factor-based biosensors, discuss recent experimental and computational approaches targeted at their modification and improvement, and suggest possible future research directions based on two applications: bioproduction screening and dynamic regulation of genetic circuits.

Natural promoters and promoter engineering strategies for metabolic regulation in Saccharomyces cerevisiae

Sharomyces cerevisiae is currently one of the most important foreign gene expression systems. S. cerevisiae is an excellent host for high-value metabolite cell factories due to its advantages of simplicity, safety, and nontoxicity. A promoter, as one of the basic elements of gene transcription, plays an important role in regulating gene expression and optimizing metabolic pathways. Promoters control the direction and intensity of transcription, and the application of promoters with different intensities and performances will largely determine the effect of gene expression and ultimately affect the experimental results. Due to its significant role, there have been many studies on promoters for decades. While some studies have explored and analyzed new promoters with different functions, more studies have focused on artificially modifying promoters to meet their own scientific needs. Thus, this article reviews current research on promoter engineering techniques and related natural promoters in S. cerevisiae. First, we introduce the basic structure of promoters and the classification of natural promoters. Then, the classification of various promoter strategies is reviewed. Finally, by grouping related articles together using various strategies, this review anticipates the future development direction of promoter engineering.

Spatial-temporal regulation of fatty alcohol biosynthesis in yeast

BACKGROUND

Construction of efficient microbial cell factories is one of the core steps for establishing green bio-manufacturing processes. However, the complex metabolic regulation makes it challenging in driving the metabolic flux toward the product biosynthesis. Dynamically coupling the biosynthetic pathways with the cellular metabolism at spatial-temporal manner should be helpful for improving the production with alleviating the cellular stresses.

RESULTS

In this study, we observed the mismatch between fatty alcohol biosynthesis and cellular metabolism, which compromised the fatty alcohol production in Saccharomyces cerevisiae. To enhance the fatty alcohol production, we spatial-temporally regulated fatty alcohol biosynthetic pathway by peroxisomal compartmentalization (spatial) and dynamic regulation of gene expression (temporal). In particular, fatty acid/acyl-CoA responsive promoters were identified by comparative transcriptional analysis, which helped to dynamically regulate the expression of acyl-CoA reductase gene MaFAR1 and improved fatty alcohol biosynthesis by 1.62-fold. Furthermore, enhancing the peroxisomal supply of acyl-CoA and NADPH further improved fatty alcohol production to 282 mg/L, 2.52 times higher than the starting strain.

CONCLUSIONS

This spatial-temporal regulation strategy partially coordinated fatty alcohol biosynthesis with cellular metabolism including peroxisome biogenesis and precursor supply, which should be applied for production of other products in microbes.

Construction and Optimization of Malonyl-CoA Sensors in Saccharomyces cerevisiae by Combining Promoter Engineering Strategies

Biosensors can be used for high-throughput screening, real-time monitoring of metabolites, and dynamic regulation of metabolic processes, which have been a popular research direction in recent years. Here, five promoters from Saccharomyces cerevisiae were selected to construct Malonyl-CoA sensors with the fapO/fapR system derived from Bacillus subtilis, and pCCW12 was finally selected for further optimization. Based on pCCW12, a series of sensors with different response sensitivities were obtained by selecting different fapO insertion sites and combining the best two or three of them. Then, through a combination of promoter hybrid, intron insertion, and transcription factor modification strategies, we obtained sensors with different effects, one of which, the H-pCCW12(TFBS)-Cti6~fapR sensor, had the lowest background noise, doubled response range and higher response sensitivity compared to the original sensor. Sensors with different characteristics constructed in this study, can be applied to Malonyl-CoA related high-throughput screening and finer regulation of metabolism. It also proves that the combined application of different promoter engineering strategies is a feasible idea for the precise construction and regulation of biosensors.

Combinatorial Metabolic Engineering Strategies for the Enhanced Production of Free Fatty Acids in Escherichia coli

In this study, we evaluated the effects of several metabolic engineering strategies in a systematic and combinatorial manner to enhance the free fatty acid (FFA) production in Escherichia coli. The strategies included (i) overexpression of mutant thioesterase I ('TesA^R64C) to efficiently release the FFAs from fatty acyl-ACP; (ii) coexpression of global regulatory protein FadR; (iii) heterologous expression of methylmalonyl-CoA carboxyltransferase and phosphoenolpyruvate carboxylase to synthesize fatty acid precursor molecule malonyl-CoA; and (iv) disruption of genes associated with membrane proteins (GusC, MdlA, and EnvR) to improve the cellular state and export the FFAs outside the cell. The synergistic effects of these genetic modifications in strain SBF50 yielded 7.2 ± 0.11 g/L FFAs at the shake flask level. In fed-batch cultivation under nitrogen-limiting conditions, strain SBF50 produced 33.6 ± 0.02 g/L FFAs with a productivity of 0.7 g/L/h from glucose, which is the maximum titer reported in E. coli to date. Combinatorial metabolic engineering approaches can prove to be highly useful for the large-scale production of FA-derived chemicals and fuels.

A review on design-build-test-learn cycle to potentiate progress in isoprenoid engineering of photosynthetic microalgae

Currently, the generation of isoprenoid factories in microalgae relies on two strategies: 1) enhanced production of endogenous isoprenoids; or 2) production of heterologous terpenes by metabolic engineering. Nevertheless, low titers and productivity are still a feature of isoprenoid biotechnology and need to be addressed. In this context, the mechanisms underlying isoprenoid biosynthesis in microalgae and its relationship with central carbon metabolism are reviewed. Developments in microalgal biotechnology are discussed, and a new approach of integrated "design-build-test-learn" cycle is advocated to the trends, challenges and prospects involved in isoprenoid engineering. The emerging and promising strategies and tools are discussed for microalgal engineering in the future. This review encourages a systematic engineering perspective aimed at potentiating progress in isoprenoid engineering of photosynthetic microalgae.

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

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

Engineering the xylose metabolism in Schizochytrium sp. to improve the utilization of lignocellulose

BACKGROUND

Schizochytrium sp. is a heterotrophic, oil-producing microorganism that can efficiently produce lipids. However, the industrial production of bulk chemicals using Schizochytrium sp. is still not economically viable due to high-cost culture medium. Replacing glucose with cheap and renewable lignocellulose is a highly promising approach to reduce production costs, but Schizochytrium sp. cannot efficiently metabolize xylose, a major pentose in lignocellulosic biomass.

RESULTS

In order to improve the utilization of lignocellulose by Schizochytrium sp., we cloned and functionally characterized the genes encoding enzymes involved in the xylose metabolism. The results showed that the endogenous xylose reductase and xylulose kinase genes possess corresponding functional activities. Additionally, attempts were made to construct a strain of Schizochytrium sp. that can effectively use xylose by using genetic engineering techniques to introduce exogenous xylitol dehydrogenase/xylose isomerase; however, the introduction of heterologous xylitol dehydrogenase did not produce a xylose-utilizing engineered strain, whereas the introduction of xylose isomerase did. The results showed that the engineered strain 308-XI with an exogenous xylose isomerase could consume 8.2 g/L xylose over 60 h of cultivation. Xylose consumption was further elevated to 11.1 g/L when heterologous xylose isomerase and xylulose kinase were overexpressed simultaneously. Furthermore, cultivation of 308-XI-XK(S) using lignocellulosic hydrolysates, which contained glucose and xylose, yielded a 22.4 g/L of dry cell weight and 5.3 g/L of total lipid titer, respectively, representing 42.7 and 30.4% increases compared to the wild type.

CONCLUSION

This study shows that engineering of Schizochytrium sp. to efficiently utilize xylose is conducive to improve its utilization of lignocellulose, which can reduce the costs of industrial lipid production.

A p-Coumaroyl-CoA Biosensor for Dynamic Regulation of Naringenin Biosynthesis in Saccharomyces cerevisiae

In vivo biosensors that can convert metabolite concentrations into measurable output signals are valuable tools for high-throughput screening and dynamic pathway control in the field of metabolic engineering. Here, we present a novel biosensor in Saccharomyces cerevisiae that is responsive to p-coumaroyl-CoA, a central precursor of many flavonoids. The sensor is based on the transcriptional repressor CouR from Rhodopseudomonas palustris and was applied in combination with a previously developed malonyl-CoA biosensor for dual regulation of p-coumaroyl-CoA synthesis within the naringenin production pathway. Using this approach, we obtained a naringenin titer of 47.3 mg/L upon external precursor feeding, representing a 15-fold increase over the nonregulated system.

Enhanced production of iturin A by strengthening fatty acid synthesis modules in Bacillus amyloliquefaciens

Iturin A is a biosurfactant with various applications, and its low synthesis capability limits its production and application development. Fatty acids play a critical role in cellular metabolism and target product syntheses, and the relationship between fatty acid supplies and iturin A synthesis is unclear. In this study, we attempted to increase iturin A production via strengthening fatty acid synthesis pathways in Bacillus amyloliquefaciens. First, acetyl-CoA carboxylase AccAD and ACP S-malonyltransferase fabD were overexpressed via promoter replacement, and iturin A yield was increased to 1.36 g/L by 2.78-fold in the resultant strain HZ-ADF1. Then, soluble acyl-ACP thioesterase derived from Escherichia coli showed the best performance for iturin A synthesis, as compared to those derived from B. amyloliquefaciens and Corynebacterium glutamicum, the introduction of which in HZ-ADF1 further led to a 57.35% increase of iturin A yield, reaching 2.14 g/L. Finally, long-chain fatty acid-CoA ligase LcfA was overexpressed in HZ-ADFT to attain the final strain HZ-ADFTL2, and iturin A yield reached 2.96 g/L, increasing by 6.59-fold, and the contents of fatty acids were enhanced significantly in HZ-ADFTL2, as compared to the original strain HZ-12. Taken together, our results implied that strengthening fatty acid supplies was an efficient approach for iturin A production, and this research provided a promising strain for industrial production of iturin A.

High-concentration COD wastewater treatment with simultaneous removal of nitrogen and phosphorus by a novel Candida tropicalis strain: Removal capability and mechanism

Aerobic and anaerobic continuous stirred-tank reactor (CSTR), up-flow anaerobic sludge blanket (UASB) were set up and inoculated with newly isolated Candida tropicalis. Reactors were operated at high concentrations of chemical oxygen demand (COD) (8000 mg/L), the modified UASB expressed better COD removal rate simultaneously removal of nitrogen and phosphate than other two reactors. Notably, under both aerobic or anaerobic conditions, large amounts of organic acids and alcohol were generated. Transcriptomic analysis showed that carbon metabolism under anaerobic conditions shared the same pathway with aerobic conditions by regulating and inhibiting some functional genes. Experiments utilizing different carbon sources proved that our strain has excellent performances in utilizing organic materials, which were verified by transcriptomic analysis. Finally, the strain was applied to treat four types of sugar-containing wastewaters. Among them, our strain exerts the best removal capability of COD (90%), nitrogen (89%), and phosphate (82%) for brewery wastewater.

Engineering of a TrpR-Based Biosensor for Altered Dynamic Range and Ligand Preference

Transcriptional factors play a crucial role in regulating cellular functions. Understanding and altering the dynamic behavior of the transcriptional factor-based biosensors will expand our knowledge in investigating biomolecular interactions and facilitating biosynthetic applications. In this study, we characterized and engineered a TrpR-based tryptophan repressor system in Escherichia coli. We found that the reconstructed TrpR1-PtrpO1 biosensor system exhibited low basal expression and narrow dynamic range in the presence of tryptophan or its analogue 5-hydroxytryptophan (5-HTP). Given the application potential of the biosensor, we introduced engineering approaches in multiple levels to optimize its dynamic behavior. First, the I57 and V58 residues in the ligand-binding pocket were rationally mutated in search of variants with altered ligand specificity. Two TrpR1 variants, V58E and V58K, successfully acquired ligand preference toward tryptophan and 5-HTP, respectively. The biosensor-induced expression levels were increased up to 10-fold with those variants. Furthermore, to pursue broader operational range, we tuned the regulator-operator binding affinity by mutating the binding box of TrpR1. Collectively, we demonstrated that the biosynthesis-significant biosensor TrpR1-PtrpO1 can be engineered to acquire extended dynamic ranges and improved ligand preference. The engineered biosensor variants with remarkable dynamic behavior can serve as key genetic elements in high-throughput screening and dynamic regulation in biosynthetic scenarios.

Sustainable production of 4-hydroxyisoleucine with minimised carbon loss by simultaneously utilising glucose and xylose in engineered Escherichia coli

4-Hydroxyisoleucine is a promising drug for diabetes therapy; however, microbial production of 4-hydroxyisoleucine is not economically efficient because of the carbon loss in the form of CO₂. This study aims to achieve de novo synthesis of 4-hydroxyisoleucine with minimised carbon loss in engineered Escherichia coli. Initially, an L-isoleucine-producing strain, ILE-5, was established, and the 4-hydroxyisoleucine synthesis pathway was introduced. The flux toward α-ketoglutarate was enhanced by reinforcing the anaplerotic pathway and disrupting competitive pathways. Subsequently, the metabolic flux for 4-hydroxyisoleucine synthesis was redistributed by dynamically modulating the α-ketoglutarate dehydrogenase complex activity, achieving a 4-hydroxyisoleucine production of 16.53 g/L. Finally, carbon loss was minimised by employing the Weimberg pathway, resulting in a 24.5% decrease in sugar consumption and a 31.6% yield increase. The 4-hydroxyisoleucine production by strain IEOH-11 reached 29.16 g/L in a 5-L fermenter. The 4-hydroxyisoleucine yield (0.29 mol/mol sugar) and productivity (0.91 g/(L⋅h)) were higher than those previously reported.

The Expression Modulation of the Key Enzyme Acc for Highly Efficient 3-Hydroxypropionic Acid Production

3-Hydroxypropionic acid (3-HP) is a promising high value-added chemical. Acetyl-CoA carboxylase (Acc) is a vital rate-limiting step in 3-HP biosynthesis through the malonyl-CoA pathway. However, Acc toxicity in cells during growth blocks its ability to catalyze acetyl-CoA to malonyl-CoA. The balancing of Acc and malonyl-CoA reductase (MCR) expression is another an unexplored but key process in 3-HP production. To solve these problems, in the present study, we developed a method to mitigate Acc toxicity cell growth through Acc subunits (AccBC and DtsR1) expression adjustment. The results revealed that cell growth and 3-HP production can be accelerated through the adjustment of DtsR1 and AccBC expression. Subsequently, the balancing Acc and MCR expression was also employed for 3-HP production, the engineered strain achieved the highest titer of 6.8 g/L, with a high yield of 0.566 g/g glucose and productivity of 0.13 g/L/h, in shake-flask fermentation through the malonyl-CoA pathway. Likewise, the engineered strain also had the highest productivity (1.03 g/L/h) as well as a high yield (0.246 g/g glucose) and titer (up to 38.13 g/L) in fed-batch fermentation, constituting the most efficient strain for 3-HP production through the malonyl-CoA pathway using a cheap carbon source. This strategy might facilitate the production of other malonyl-CoA-derived chemical compounds in the future.

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.

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.

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.