A Two-Layer Gene Circuit for Decoupling Cell Growth from Metabolite Production

A dual light-controlled co-culture system enables the regulation of population composition

With the development of metabolic engineering, increasing requirements for efficient microbial biosynthesis call for establishment of multi-strain co-culture system. Dynamic regulation of population ratios is crucial for optimizing bioproduction performance. Optogenetic systems with high universality and flexibility have the potential to realize dynamic control of population proportion. In this study, we utilized an optimized chromatic acclimation sensor/regulator (CcaS/R) system and a blue light-activated YF1-FixJ-PhlF system as induction modules. A pair of orthogonal quorum sensing systems and a toxin-antitoxin system were employed as communication module and effector module, respectively. By integrating these modules, we developed a dual light-controlled co-culture system that enables dynamic regulation of population ratios. This co-culture system provides a universal toolkit for applications in metabolic engineering and synthetic biology.

Creating a System of Dual Regulation of Translation and Transcription to Enhance the Production of Recombinant Protein

When constructing cell factories, it is crucial to reallocate intracellular resources towards the synthesis of target compounds. However, imbalanced resource allocation can lead to a tradeoff between cell growth and production, reducing overall efficiency. Reliable gene expression regulation tools are needed to coordinate cell growth and production effectively. The orthogonal translation system, developed based on genetic code expansion (GCE), incorporates non-canonical amino acids (ncAAs) into proteins by assigning them to expanded codons, which enables the control of target protein expression at the translational level in an ncAA-dependent manner. However, the stringency of this regulatory tool remains inadequate. This study achieved strict translational-level control of the orthogonal translation system by addressing the abnormal leakage caused by the arabinose-inducible promoter. Further validation was conducted on the relationship between ncAA concentration and expression level, as well as the host's adaptability to the system. Subsequently, the system's applicability across multiple Escherichia coli hosts was verified by examining the roles of RF1 (peptide chain release factor 1) and endogenous TAG codons. By combining this strategy with inducible promoters, dual-level regulation of target gene expression at both transcriptional and translational levels was achieved and the dynamic range was further increased to over 20-fold. When using ncAA to control the expression of T7 RNA polymerase (T7 RNAP), the leakage expression was reduced by 82.7%, mitigating the low production efficiency caused by extensive leakage in the T7 system. As proof of concept, the strategy enhanced the production of alcohol dehydrogenase (ADH) by 9.82-fold, demonstrating its excellent capability in controlling gene expression in developing cell factories.

CFSA: Comparative flux sampling analysis as a guide for strain design

Genome-scale metabolic models of microbial metabolism have extensively been used to guide the design of microbial cell factories, still, many of the available strain design algorithms often fail to produce a reduced list of targets for improved performance that can be implemented and validated in a step-wise manner. We present Comparative Flux Sampling Analysis (CFSA), a strain design method based on the extensive comparison of complete metabolic spaces corresponding to maximal or near-maximal growth and production phenotypes. The comparison is complemented by statistical analysis to identify reactions with altered flux that are suggested as targets for genetic interventions including up-regulations, down-regulations and gene deletions. We applied CFSA to the production of lipids by Cutaneotrichosporon oleaginosus and naringenin by Saccharomyces cerevisiae identifying engineering targets in agreement with previous studies as well as new interventions. CFSA is an easy-to-use, robust method that suggests potential metabolic engineering targets for growth-uncoupled production that can be applied to the design of microbial cell factories.

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.

Delaying production with prokaryotic inducible expression systems

BACKGROUND

Engineering bacteria with the purpose of optimizing the production of interesting molecules often leads to a decrease in growth due to metabolic burden or toxicity. By delaying the production in time, these negative effects on the growth can be avoided in a process called a two-stage fermentation.

MAIN TEXT

During this two-stage fermentation process, the production stage is only activated once sufficient cell mass is obtained. Besides the possibility of using external triggers, such as chemical molecules or changing fermentation parameters to induce the production stage, there is a renewed interest towards autoinducible systems. These systems, such as quorum sensing, do not require the extra interference with the fermentation broth to start the induction. In this review, we discuss the different possibilities of both external and autoinduction methods to obtain a two-stage fermentation. Additionally, an overview is given of the tuning methods that can be applied to optimize the induction process. Finally, future challenges and prospects of (auto)inducible expression systems are discussed.

CONCLUSION

There are numerous methods to obtain a two-stage fermentation process each with their own advantages and disadvantages. Even though chemically inducible expression systems are well-established, an increasing interest is going towards autoinducible expression systems, such as quorum sensing. Although these newer techniques cannot rely on the decades of characterization and applications as is the case for chemically inducible promoters, their advantages might lead to a shift in future inducible expression systems.

Transport-controlled growth decoupling for self-induced protein expression with a glycerol-repressible genetic circuit

Decoupling cell formation from recombinant protein synthesis is a potent strategy to intensify bioprocesses. Escherichia coli strains with mutations in the glucose uptake components lack catabolite repression, display low growth rate, no overflow metabolism, and high recombinant protein yields. Fast growth rates were promoted by the simultaneous consumption of glucose and glycerol, and this was followed by a phase of slow growth, when only glucose remained in the medium. A glycerol-repressible genetic circuit was designed to autonomously induce recombinant protein expression. The engineered strain bearing the genetic circuit was cultured in 3.9 g L-1 glycerol + 18 g L-1 glucose in microbioreactors with online oxygen transfer rate monitoring. The growth was fast during the simultaneous consumption of both carbon sources (C-sources), while expression of the recombinant protein was low. When glycerol was depleted, the growth rate decreased, and the specific fluorescence reached values 17% higher than those obtained with a strong constitutive promoter. Despite the relatively high amount of C-source used, no oxygen limitation was observed. The proposed approach eliminates the need for the substrate feeding or inducers addition and is set as a simple batch culture while mimicking fed-batch performance.

Advancements in synthetic biology-based bacterial cancer therapy: A modular design approach

Synthetic biology aims to program living bacteria cells with artificial genetic circuits for user-defined functions, transforming them into powerful tools with numerous applications in various fields, including oncology. Cancer treatments have serious side effects on patients due to the systemic action of the drugs involved. To address this, new systems that provide localized antitumoral action while minimizing damage to healthy tissues are required. Bacteria, often considered pathogenic agents, have been used as cancer treatments since the early 20th century. Advances in genetic engineering, synthetic biology, microbiology, and oncology have improved bacterial therapies, making them safer and more effective. Here we propose six modules for a successful synthetic biology-based bacterial cancer therapy, the modules include Payload, Release, Tumor-targeting, Biocontainment, Memory, and Genetic Circuit Stability Module. These will ensure antitumor activity, safety for the environment and patient, prevent bacterial colonization, maintain cell stability, and prevent loss or defunctionalization of the genetic circuit.

Microbial engineering for shikimate biosynthesis

Shikimate, a precursor to the antiviral drug oseltamivir (Tamiflu®), can influence aromatic metabolites and finds extensive use in antimicrobial, antitumor, and cardiovascular applications. Consequently, various strategies have been developed for chemical synthesis and plant extraction to enhance shikimate biosynthesis, potentially impacting environmental conditions, economic sustainability, and separation and purification processes. Microbial engineering has been developed as an environmentally friendly approach for shikimate biosynthesis. In this review, we provide a comprehensive summary of microbial strategies for shikimate biosynthesis. These strategies primarily include chassis construction, biochemical optimization, pathway remodelling, and global regulation. Furthermore, we discuss future perspectives on shikimate biosynthesis and emphasize the importance of utilizing advanced metabolic engineering tools to regulate microbial networks for constructing robust microbial cell factories.

Maximizing microbial bioproduction from sustainable carbon sources using iterative systems engineering

Maximizing the production of heterologous biomolecules is a complex problem that can be addressed with a systems-level understanding of cellular metabolism and regulation. Specifically, growth-coupling approaches can increase product titers and yields and also enhance production rates. However, implementing these methods for non-canonical carbon streams is challenging due to gaps in metabolic models. Over four design-build-test-learn cycles, we rewire Pseudomonas putida KT2440 for growth-coupled production of indigoidine from para-coumarate. We explore 4,114 potential growth-coupling solutions and refine one design through laboratory evolution and ensemble data-driven methods. The final growth-coupled strain produces 7.3 g/L indigoidine at 77% maximum theoretical yield in para-coumarate minimal medium. The iterative use of growth-coupling designs and functional genomics with experimental validation was highly effective and agnostic to specific hosts, carbon streams, and final products and thus generalizable across many systems.

Assessing and reducing phenotypic instability in cyanobacteria

Cyanobacteria have promising potential as sustainable cell factories. However, one challenge that is still largely unreported in scaling-up cyanobacteria bioproduction is phenotypic instability, where the emergence and selection of nonproducing cells leading to loss in production has longer evolutionary timescales to take place in industrial-scale bioreactors. Quantifying phenotypic instability early on in strain development allows researchers to make informed decisions on whether to proceed with scalable designs, or if present, devise countermeasures to reduce instability. One particularly effective strategy to mitigate instability is the use of genome-scale metabolic models to design growth-coupled production strains. In silico studies have predicted that creating certain cofactor imbalances or removing recycling reactions in cyanobacteria can be exploited to stably produce a wide variety of metabolites.

Synthetic biology of extremophiles: a new wave of biomanufacturing

Microbial biomanufacturing, powered by the advances of synthetic biology, has attracted growing interest for the production of diverse products. In contrast to conventional microbes, extremophiles have shown better performance for low-cost production owing to their outstanding growth and synthesis capacity under stress conditions, allowing unsterilized fermentation processes. We review increasing numbers of products already manufactured utilizing extremophiles in recent years. In addition, genetic parts, molecular tools, and manipulation approaches for extremophile engineering are also summarized, and challenges and opportunities are predicted for non-conventional chassis. Next-generation industrial biotechnology (NGIB) based on engineered extremophiles promises to simplify biomanufacturing processes and achieve open and continuous fermentation, without sterilization, and utilizing low-cost substrates, making NGIB an attractive green process for sustainable manufacturing.

Understanding and application of Bacillus nitrogen regulation: A synthetic biology perspective

BACKGROUND

Nitrogen sources play an essential role in maintaining the physiological and biochemical activity of bacteria. Nitrogen metabolism, which is the core of microorganism metabolism, makes bacteria able to autonomously respond to different external nitrogen environments by exercising complex internal regulatory networks to help them stay in an ideal state. Although various studies have been put forth to better understand this regulation in Bacillus, and many valuable viewpoints have been obtained, these views need to be presented systematically and their possible applications need to be specified.

AIM OF REVIEW

The intention is to provide a deep and comprehensive understanding of nitrogen metabolism in Bacillus, an important industrial microorganism, and thereby apply this regulatory logic to synthetic biology to improve biosynthesis competitiveness. In addition, the potential researches in the future are also discussed.

KEY SCIENTIFIC CONCEPT OF REVIEW

Understanding the meticulous regulation process of nitrogen metabolism in Bacillus not only could facilitate research on metabolic engineering but also could provide constructive insights and inspiration for studies of other microorganisms.

A Gene Circuit Combining the Endogenous I-E Type CRISPR-Cas System and a Light Sensor to Produce Poly-β-Hydroxybutyric Acid Efficiently

‘Metabolic burden,’ which arises when introducing exogenic synthesizing pathways into a host strain, remains a challenging issue in metabolic engineering. Redirecting metabolic flux from cell growth to product synthesis at an appropriate culture timepoint is ideal for resolving this issue. In this report, we introduce optogenetics—which is capable of precise temporal and spatial control—as a genetic switch, accompanied by the endogenous type I-E CRISPRi system in Escherichia coli (E. coli) to generate a metabolic platform that redirects metabolic flux. Poly-β-hydroxybutyric acid (PHB) production was taken as an example to demonstrate the performance of this platform. A two-to-three-fold increase in PHB content was observed under green light when compared with the production of PHB under red light, confirming the regulatory activity of this platform and its potential to redirect metabolic flux to synthesize target products.

The Growth Dependent Design Constraints of Transcription-Factor-Based Metabolite Biosensors

Metabolite biosensors based on metabolite-responsive transcription factors are key synthetic biology components for sensing and precisely controlling cellular metabolism. Biosensors are often designed under laboratory conditions but are deployed in applications where cellular growth rate differs drastically from its initial characterization. Here we asked how growth rate impacts the minimum and maximum biosensor outputs and the dynamic range, which are key metrics of biosensor performance. Using LacI, TetR, and FadR-based biosensors in Escherichia coli as models, we find that the dynamic range of different biosensors have different growth rate dependencies. We developed a kinetic model to explore how tuning biosensor parameters impact the dynamic range growth rate dependence. Our modeling and experimental results revealed that the effects to dynamic range and its growth rate dependence are often coupled, and the metabolite transport mechanisms shape the dynamic range-growth rate response. This work provides a systematic understanding of biosensor performance under different growth rates, which will be useful for predicting biosensor behavior in broad synthetic biology and metabolic engineering applications.

Microbial chassis engineering drives heterologous production of complex secondary metabolites

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

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

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

Bifunctional optogenetic switch for improving shikimic acid production in E. coli

BACKGROUND

Biomass formation and product synthesis decoupling have been proven to be promising to increase the titer of desired value add products. Optogenetics provides a potential strategy to develop light-induced circuits that conditionally control metabolic flux redistribution for enhanced microbial production. However, the limited number of light-sensitive proteins available to date hinders the progress of light-controlled tools.

RESULTS

To address these issues, two optogenetic systems (TPRS and TPAS) were constructed by reprogramming the widely used repressor TetR and protease TEVp to expand the current optogenetic toolkit. By merging the two systems, a bifunctional optogenetic switch was constructed to enable orthogonally regulated gene transcription and protein accumulation. Application of this bifunctional switch to decouple biomass formation and shikimic acid biosynthesis allowed 35 g/L of shikimic acid production in a minimal medium from glucose, representing the highest titer reported to date by E. coli without the addition of any chemical inducers and expensive aromatic amino acids. This titer was further boosted to 76 g/L when using rich medium fermentation.

CONCLUSION

The cost effective and light-controlled switch reported here provides important insights into environmentally friendly tools for metabolic pathway regulation and should be applicable to the production of other value-add chemicals.

CRISPRi enables fast growth followed by stable aerobic pyruvate formation in Escherichia coli without auxotrophy

CRISPR interference (CRISPRi) was applied to enable the aerobic production of pyruvate in Escherichia coli MG1655 under glucose excess conditions by targeting the promoter regions of aceE or pdhR. Knockdown strains were cultivated in aerobic shaking flasks and the influence of inducer concentration and different sgRNA binding sites on the production of pyruvate was measured. Targeting the promoter regions of aceE or pdhR triggered pyruvate production during the exponential phase and reduced expression of aceE. In lab-scale bioreactor fermentations, an aceE silenced strain successfully produced pyruvate under fully aerobic conditions during the exponential phase, but loss of productivity occurred during a subsequent nitrogen-limited phase. Targeting the promoter region of pdhR enabled pyruvate production during the growth phase of cultivations, and a continued low-level accumulation during the nitrogen-limited production phase. Combinatorial targeting of the promoter regions of both aceE and pdhR in E. coli MG1655 pdCas9 psgRNA_aceE_234_pdhR_329 resulted in the stable aerobic production of pyruvate with non-growing cells at YP/S  =  0.36 ± 0.029 gPyruvate/gGlucose in lab-scale bioreactors throughout an extended nitrogen-limited production phase.

Multiomics Study of Bacterial Growth Arrest in a Synthetic Biology Application

We investigated the scalability of a previously developed growth switch based on external control of RNA polymerase expression. Our results indicate that, in liter-scale bioreactors operating in fed-batch mode, growth-arrested Escherichia coli cells are able to convert glucose to glycerol at an increased yield. A multiomics quantification of the physiology of the cells shows that, apart from acetate production, few metabolic side effects occur. However, a number of specific responses to growth slow-down and growth arrest are launched at the transcriptional level. These notably include the downregulation of genes involved in growth-associated processes, such as amino acid and nucleotide metabolism and translation. Interestingly, the transcriptional responses are buffered at the proteome level, probably due to the strong decrease of the total mRNA concentration after the diminution of transcriptional activity and the absence of growth dilution of proteins. Growth arrest thus reduces the opportunities for dynamically adjusting the proteome composition, which poses constraints on the design of biotechnological production processes but may also avoid the initiation of deleterious stress responses.

A portable library of phosphate-depletion based synthetic promoters for customable and automata control of gene expression in bacteria

Industrial biotechnology gene expression systems relay on constitutive promoters compromising cellular growth from the start of the bioprocess, or on inducible devices, which require manual addition of cognate inducers. To overcome this shortcoming, we engineered an automata regulatory system based on cell-stress mechanisms. Specifically, we engineered a synthetic and highly portable phosphate-depletion library of promoters inspired by bacterial PHO starvation system (Pliar promoters). Furthermore, we fully characterized 10 synthetic promoters within the background of two well-known bacterial workhorses such as E. coli W and P. putida KT2440. The promoters displayed an interesting host-dependent performance and a wide strength spectrum ranging from 0.4- to 1.3-fold when compared to the wild-type phosphatase alkaline promoter (PphoA). By comparing with available gene expression systems, we proved the suitability of this new library for the automata and effective decoupling of growth from production in P. putida. Growth phase-dependent expression of these promoters could therefore be activated by fine tuning the initial concentration of phosphate in the medium. Finally, the Pliar library was implemented in the SEVA platform in a ready-to-use mode allowing its broad use by the scientific community.

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.

Cycling between growth and production phases increases cyanobacteria bioproduction of lactate

Decoupling growth from product synthesis is a promising strategy to increase carbon partitioning and maximize productivity in cell factories. However, reduction in both substrate uptake rate and metabolic activity in the production phase are an underlying problem for upscaling. Here, we used CRISPR interference to repress growth in lactate-producing Synechocystis sp. PCC 6803. Carbon partitioning to lactate in the production phase exceeded 90%, but CO₂ uptake was severely reduced compared to uptake during the growth phase. We characterized strains during the onset of growth arrest using transcriptomics and proteomics. Multiple genes involved in ATP homeostasis were regulated once growth was inhibited, which suggests an alteration of energy charge that may lead to reduced substrate uptake. In order to overcome the reduced metabolic activity and take advantage of increased carbon partitioning, we tested a novel production strategy that involved alternating growth arrest and recovery by periodic addition of an inducer molecule to activate CRISPRi. Using this strategy, we maintained lactate biosynthesis in Synechocystis for 30 days in a constant light turbidostat cultivation. Cumulative lactate titers were also increased by 100% compared to a constant growth-arrest regime, and reached 1 g/L. Further, the cultivation produced lactate for 30 days, compared to 20 days for the non-growth arrest cultivation. Periodic growth arrest could be applicable for other products, and in cyanobacteria, could be linked to internal circadian rhythms that persist in constant light.

Microbial production of riboflavin: Biotechnological advances and perspectives

Riboflavin is an essential nutrient for humans and animals, and its derivatives flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD) are cofactors in the cells. Therefore, riboflavin and its derivatives are widely used in the food, pharmaceutical, nutraceutical and cosmetic industries. Advances in biotechnology have led to a complete shift in the commercial production of riboflavin from chemical synthesis to microbial fermentation. In this review, we provide a comprehensive review of biotechnologies that enhance riboflavin production in microorganisms, as well as representative examples. Firstly, the synthesis pathways and metabolic regulatory processes of riboflavin in microorganisms; and the current strategies and methods of metabolic engineering for riboflavin production are systematically summarized and compared. Secondly, the using of systematic metabolic engineering strategies to enhance riboflavin production is discussed, including laboratory evolution, histological analysis and high-throughput screening. Finally, the challenges for efficient microbial production of riboflavin and the strategies to overcome these challenges are prospected.

L-valine production in Corynebacterium glutamicum based on systematic metabolic engineering: progress and prospects

L-valine is an essential branched-chain amino acid that cannot be synthesized by the human body and has a wide range of applications in food, medicine and feed. Market demand has stimulated people's interest in the industrial production of L-valine. At present, the mutagenized or engineered Corynebacterium glutamicum is an effective microbial cell factory for producing L-valine. Because the biosynthetic pathway and metabolic network of L-valine are intricate and strictly regulated by a variety of key enzymes and genes, highly targeted metabolic engineering can no longer meet the demand for efficient biosynthesis of L-valine. In recent years, the development of omics technology has promoted the upgrading of traditional metabolic engineering to systematic metabolic engineering. This whole-cell-scale transformation strategy has become a productive method for developing L-valine producing strains. This review provides an overview of the biosynthesis and regulation mechanism of L-valine, and summarizes the current metabolic engineering techniques and strategies for constructing L-valine high-producing strains. Finally, the opinion of constructing a cell factory for efficiently biosynthesizing L-valine was proposed.

A dynamic and multilocus metabolic regulation strategy using quorum-sensing-controlled bacterial small RNA

Metabolic regulation strategies have been developed to redirect metabolic fluxes to production pathways. However, it is difficult to screen out target genes that, when repressed, improve yield without affecting cell growth. Here, we report a strategy using a quorum-sensing system to control small RNA transcription, allowing cell-density-dependent repression of target genes. This strategy is shown with convenient operation, dynamic repression, and availability for simultaneous regulation of multiple genes. The parameters A_i, A_m, and R_A (3-oxohexanoyl-homoserine lactone [AHL] concentrations at which half of the maximum repression and the maximum repression were reached and value of the maximum repression when AHL was added manually, respectively) are defined and introduced to characterize repression curves, and the variant LuxR_I58N is identified as the most suitable tuning factor for shake flask culture. Moreover, it is shown that dynamic overexpression of the Hfq chaperone is the key to combinatorial repression without disruptions on cell growth. To show a broad applicability, the production titers of pinene, pentalenene, and psilocybin are improved by 365.3%, 79.5%, and 302.9%, respectively, by applying combinatorial dynamic repression.

Design and construction of novel biocatalyst for bioprocessing: Recent advances and future outlook

Bioprocess, a biocatalysis-based technology, is becoming popular in many research fields and widely applied in industrial manufacturing. However, low bioconversion, low productivity, and high costs during industrial processes are usually the limitation in bioprocess. Therefore, many biocatalyst strategies have been developed to meet these challenges in recent years. In this review, we firstly discuss protein engineering strategies, which are emerged for improving the biocatalysis activity of biocatalysts. Then, we summarize metabolic engineering strategies that are promoting the development of microbial cell factories. Next, we illustrate the necessity of using the combining strategy of protein engineering and metabolic engineering for efficient biocatalysts. Lastly, future perspectives about the development and application of novel biocatalyst strategies are discussed. This review provides theoretical guidance for the development of efficient, sustainable, and economical bioprocesses mediated by novel biocatalysts.

Rational engineering strategies for achieving high-yield, high-quality and high-stability of natural product production in actinomycetes

Actinomycetes are recognized as excellent producers of microbial natural products, which have a wide range of applications, especially in medicine, agriculture and stockbreeding. The three main indexes of industrialization (titer, purity and stability) must be taken into overall consideration in the manufacturing process of natural products. Over the past decades, synthetic biology techniques have expedited the development of industrially competitive strains with excellent performances. Here, we summarize various rational engineering strategies for upgrading the performance of industrial actinomycetes, which include enhancing the yield of natural products, eliminating the by-products and improving the genetic stability of engineered strains. Furthermore, the current challenges and future perspectives for optimizing the industrial strains more systematically through combinatorial engineering strategies are also discussed.

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.

Engineering of a robust Escherichia coli chassis and exploitation for large-scale production processes

In large-scale bioprocesses microbes are exposed to heterogeneous substrate availability reducing the overall process performance. A series of deletion strains was constructed from E. coli MG1655 aiming for a robust phenotype in heterogeneous fermentations with transient starvation. Deletion targets were hand-picked based on a list of genes derived from previous large-scale simulation runs. Each gene deletion was conducted on the premise of strict neutrality towards growth parameters in glucose minimal medium. The final strain of the series, named E. coli RM214, was cultivated continuously in an STR-PFR (stirred tank reactor - plug flow reactor) scale-down reactor. The scale-down reactor system simulated repeated passages through a glucose starvation zone. When exposed to nutrient gradients, E. coli RM214 had a significantly lower maintenance coefficient than E. coli MG1655 (Δm_s = 0.038 g_Glucose/g_CDW/h, p < 0.05). In an exemplary protein production scenario E. coli RM214 remained significantly more productive than E. coli MG1655 reaching 44% higher eGFP yield after 28 h of STR-PFR cultivation. This study developed E. coli RM214 as a robust chassis strain and demonstrated the feasibility of engineering microbial hosts for large-scale applications.

Biosynthesis of Commodity Chemicals From Oil Palm Empty Fruit Bunch Lignin

Lignin is one of the most abundant natural resources that can be exploited for the bioproduction of value-added commodity chemicals. Oil palm empty fruit bunches (OPEFBs), byproducts of palm oil production, are abundant lignocellulosic biomass but largely used for energy and regarded as waste. Pretreatment of OPEFB lignin can yield a mixture of aromatic compounds that can potentially serve as substrates to produce commercially important chemicals. However, separation of the mixture into desired individual substrates is required, which involves expensive steps that undermine the utility of OPEFB lignin. Here, we report successful engineering of microbial hosts that can directly utilize heterogeneous mixtures derived from OPEFB lignin to produce commodity chemicals, adipic acid and levulinic acid. Furthermore, the corresponding bioconversion pathway was placed under a genetic controller to autonomously activate the conversion process as the cells are fed with a depolymerized OPEFB lignin mixture. This study demonstrates a simple, one-pot biosynthesis approach that directly utilizes derivatives of agricultural waste to produce commodity chemicals.

Partitioning metabolism between growth and product synthesis for coordinated production of wax esters in Acinetobacter baylyi ADP1

Microbial storage compounds, such as wax esters (WE), are potential high-value lipids for the production of specialty chemicals and medicines. Their synthesis, however, is strictly regulated and competes with cell growth, which leads to trade-offs between biomass and product formation. Here, we use metabolic engineering and synergistic substrate cofeeding to partition the metabolism of Acinetobacter baylyi ADP1 into two distinct modules, each dedicated to cell growth and WE biosynthesis, respectively. We first blocked the glyoxylate shunt and upregulated the WE synthesis pathway to direct the acetate substrate exclusively for WE synthesis, then we controlled the supply of gluconate so it could be used exclusively for cell growth and maintenance. We show that the two modules are functionally independent from each other, allowing efficient lipid accumulation while maintaining active cell growth. Our strategy resulted in 7.2- and 4.2-fold improvements in WE content and productivity, respectively, and the product titer was enhanced by 8.3-fold over the wild type strain. Notably, during a 24-h cultivation, a yield of 18% C-WE/C-total-substrates was achieved, being the highest reported for WE biosynthesis. This study provides a simple, yet powerful, means of controlling cellular operations and overcoming some of the fundamental challenges in microbial storage lipid production.

Approaches to genetic tool development for rapid domestication of non-model microorganisms

Non-model microorganisms often possess complex phenotypes that could be important for the future of biofuel and chemical production. They have received significant interest the last several years, but advancement is still slow due to the lack of a robust genetic toolbox in most organisms. Typically, "domestication" of a new non-model microorganism has been done on an ad hoc basis, and historically, it can take years to develop transformation and basic genetic tools. Here, we review the barriers and solutions to rapid development of genetic transformation tools in new hosts, with a major focus on Restriction-Modification systems, which are a well-known and significant barrier to efficient transformation. We further explore the tools and approaches used for efficient gene deletion, DNA insertion, and heterologous gene expression. Finally, more advanced and high-throughput tools are now being developed in diverse non-model microbes, paving the way for rapid and multiplexed genome engineering for biotechnology.

Dynamic control in metabolic engineering: Theories, tools, and applications

Metabolic engineering has allowed the production of a diverse number of valuable chemicals using microbial organisms. Many biological challenges for improving bio-production exist which limit performance and slow the commercialization of metabolically engineered systems. Dynamic metabolic engineering is a rapidly developing field that seeks to address these challenges through the design of genetically encoded metabolic control systems which allow cells to autonomously adjust their flux in response to their external and internal metabolic state. This review first discusses theoretical works which provide mechanistic insights and design choices for dynamic control systems including two-stage, continuous, and population behavior control strategies. Next, we summarize molecular mechanisms for various sensors and actuators which enable dynamic metabolic control in microbial systems. Finally, important applications of dynamic control to the production of several metabolite products are highlighted, including fatty acids, aromatics, and terpene compounds. Altogether, this review provides a comprehensive overview of the progress, advances, and prospects in the design of dynamic control systems for improved titer, rate, and yield metrics in metabolic engineering.

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

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

Automated engineering of synthetic metabolic pathways for efficient biomanufacturing

Metabolic engineering involves the engineering and optimization of processes from single-cell to fermentation in order to increase production of valuable chemicals for health, food, energy, materials and others. A systems approach to metabolic engineering has gained traction in recent years thanks to advances in strain engineering, leading to an accelerated scaling from rapid prototyping to industrial production. Metabolic engineering is nowadays on track towards a truly manufacturing technology, with reduced times from conception to production enabled by automated protocols for DNA assembly of metabolic pathways in engineered producer strains. In this review, we discuss how the success of the metabolic engineering pipeline often relies on retrobiosynthetic protocols able to identify promising production routes and dynamic regulation strategies through automated biodesign algorithms, which are subsequently assembled as embedded integrated genetic circuits in the host strain. Those approaches are orchestrated by an experimental design strategy that provides optimal scheduling planning of the DNA assembly, rapid prototyping and, ultimately, brings forward an accelerated Design-Build-Test-Learn cycle and the overall optimization of the biomanufacturing process. Achieving such a vision will address the increasingly compelling demand in our society for delivering valuable biomolecules in an affordable, inclusive and sustainable bioeconomy.

Engineering an Alcohol-Forming Fatty Acyl-CoA Reductase for Aldehyde and Hydrocarbon Biosynthesis in Saccharomyces cerevisiae

Aldehydes are a class of highly versatile chemicals that can undergo a wide range of chemical reactions and are in high demand as starting materials for chemical manufacturing. Biologically, fatty aldehydes can be produced from fatty acyl-CoA by the action of fatty acyl-CoA reductases. The aldehydes produced can be further converted enzymatically to other valuable derivatives. Thus, metabolic engineering of microorganisms for biosynthesizing aldehydes and their derivatives could provide an economical and sustainable platform for key aldehyde precursor production and subsequent conversion to various value-added chemicals. Saccharomyces cerevisiae is an excellent host for this purpose because it is a robust organism that has been used extensively for industrial biochemical production. However, fatty acyl-CoA-dependent aldehyde-forming enzymes expressed in S. cerevisiae thus far have extremely low activities, hence limiting direct utilization of fatty acyl-CoA as substrate for aldehyde biosynthesis. Toward overcoming this challenge, we successfully engineered an alcohol-forming fatty acyl-CoA reductase for aldehyde production through rational design. We further improved aldehyde production through strain engineering by deleting competing pathways and increasing substrate availability. Subsequently, we demonstrated alkane and alkene production as one of the many possible applications of the aldehyde-producing strain. Overall, by protein engineering of a fatty acyl-CoA reductase to alter its activity and metabolic engineering of S. cerevisiae, we generated strains with the highest reported cytosolic aliphatic aldehyde and alkane/alkene production to date in S. cerevisiae from fatty acyl-CoA.

Genome-scale metabolic rewiring improves titers rates and yields of the non-native product indigoidine at scale

High titer, rate, yield (TRY), and scalability are challenging metrics to achieve due to trade-offs between carbon use for growth and production. To achieve these metrics, we take the minimal cut set (MCS) approach that predicts metabolic reactions for elimination to couple metabolite production strongly with growth. We compute MCS solution-sets for a non-native product indigoidine, a sustainable pigment, in Pseudomonas putida KT2440, an emerging industrial microbe. From the 63 solution-sets, our omics guided process identifies one experimentally feasible solution requiring 14 simultaneous reaction interventions. We implement a total of 14 genes knockdowns using multiplex-CRISPRi. MCS-based solution shifts production from stationary to exponential phase. We achieve 25.6 g/L, 0.22 g/l/h, and ~50% maximum theoretical yield (0.33 g indigoidine/g glucose). These phenotypes are maintained from batch to fed-batch mode, and across scales (100-ml shake flasks, 250-ml ambr®, and 2-L bioreactors).

Microbial cell engineering to improve cellular synthetic capacity

Rapid technological progress in gene assembly, biosensors, and genetic circuits has led to reinforce the cellular synthetic capacity for chemical production. However, overcoming the current limitations of these techniques in maintaining cellular functions and enhancing the cellular synthetic capacity (e.g., catalytic efficiency, strain performance, and cell-cell communication) remains challenging. In this review, we propose a strategy for microbial cell engineering to improve the cellular synthetic capacity by utilizing biotechnological tools along with system biology methods to regulate cellular functions during chemical production. Current strategies in microbial cell engineering are mainly focused on the organelle, cell, and consortium levels. This review highlights the potential of using biotechnology to further develop the field of microbial cell engineering and provides guidance for utilizing microorganisms as attractive regulation targets.

Titrating bacterial growth and chemical biosynthesis for efficient N-acetylglucosamine and N-acetylneuraminic acid bioproduction

Metabolic engineering facilitates chemical biosynthesis by rewiring cellular resources to produce target compounds. However, an imbalance between cell growth and bioproduction often reduces production efficiency. Genetic code expansion (GCE)-based orthogonal translation systems incorporating non-canonical amino acids (ncAAs) into proteins by reassigning non-canonical codons to ncAAs qualify for balancing cellular metabolism. Here, GCE-based cell growth and biosynthesis balance engineering (GCE-CGBBE) is developed, which is based on titrating expression of cell growth and metabolic flux determinant genes by constructing ncAA-dependent expression patterns. We demonstrate GCE-CGBBE in genome-recoded Escherichia coli Δ321AM by precisely balancing glycolysis and N-acetylglucosamine production, resulting in a 4.54-fold increase in titer. GCE-CGBBE is further expanded to non-genome-recoded Bacillus subtilis to balance growth and N-acetylneuraminic acid bioproduction by titrating essential gene expression, yielding a 2.34-fold increase in titer. Moreover, the development of ncAA-dependent essential gene expression regulation shows efficient biocontainment of engineered B. subtilis to avoid unintended proliferation in nature.

An imbalance between cell growth and bioproduction of engineered microbes often reduces production efficiency. Here, the authors report genetic code expansion-based cell growth and biosynthesis balance engineering to achieve high levels production of N-acetylglucosamine in E. coli and N-acetylneuraminic acid in B. subtilis.

A model-driven approach towards rational microbial bioprocess optimization

Due to sustainability concerns, bio-based production capitalizing on microbes as cell factories is in demand to synthesize valuable products. Nevertheless, the nonhomogenous variations of the extracellular environment in bioprocesses often challenge the biomass growth and the bioproduction yield. To enable a more rational bioprocess optimization, we have established a model-driven approach that systematically integrates experiments with modeling, executed from flask to bioreactor scale, and using ferulic acid to vanillin bioconversion as a case study. The impacts of mass transfer and aeration on the biomass growth and bioproduction performances were examined using minimal small-scale experiments. An integrated model coupling the cell factory kinetics with the three-dimensional computational hydrodynamics of bioreactor was developed to better capture the spatiotemporal distributions of bioproduction. Full-factorial predictions were then performed to identify the desired operating conditions. A bioconversion yield of 94% was achieved, which is one of the highest for recombinant Escherichia coli using ferulic acid as the precursor.

Inducible Expression Systems Based on Xenogeneic Silencing and Counter-Silencing and Design of a Metabolic Toggle Switch

Inducible expression systems represent key modules in regulatory circuit design and metabolic engineering approaches. However, established systems are often limited in terms of applications due to high background expression levels and inducer toxicity. In bacteria, xenogeneic silencing (XS) proteins are involved in the tight control of horizontally acquired, AT-rich DNA. The action of XS proteins may be opposed by interference with a specific transcription factor, resulting in the phenomenon of counter-silencing, thereby activating gene expression. In this study, we harnessed this principle for the construction of a synthetic promoter library consisting of phage promoters targeted by the Lsr2-like XS protein CgpS of Corynebacterium glutamicum. Counter-silencing was achieved by inserting the operator sequence of the gluconate-responsive transcription factor GntR. The GntR-dependent promoter library is comprised of 28 activated and 16 repressed regulatory elements featuring effector-dependent tunability. For selected candidates, background expression levels were confirmed to be significantly reduced in comparison to established heterologous expression systems. Finally, a GntR-dependent metabolic toggle switch was implemented in a C. glutamicum l-valine production strain allowing the dynamic redirection of carbon flux between biomass and product formation.

CRISPR interference of nucleotide biosynthesis improves production of a single-domain antibody in Escherichia coli

Growth decoupling can be used to optimize the production of biochemicals and proteins in cell factories. Inhibition of excess biomass formation allows for carbon to be utilized efficiently for product formation instead of growth, resulting in increased product yields and titers. Here, we used CRISPR interference to increase the production of a single‐domain antibody (sdAb) by inhibiting growth during production. First, we screened 21 sgRNA targets in the purine and pyrimidine biosynthesis pathways and found that the repression of 11 pathway genes led to the increased green fluorescent protein production and decreased growth. The sgRNA targets pyrF, pyrG, and cmk were selected and further used to improve the production of two versions of an expression‐optimized sdAb. Proteomics analysis of the sdAb‐producing pyrF, pyrG, and cmk growth decoupling strains showed significantly decreased RpoS levels and an increase of ribosome‐associated proteins, indicating that the growth decoupling strains do not enter stationary phase and maintain their capacity for protein synthesis upon growth inhibition. Finally, sdAb production was scaled up to shake‐flask fermentation where the product yield was improved 2.6‐fold compared to the control strain with no sgRNA target sequence. An sdAb content of 14.6% was reached in the best‐performing pyrG growth decoupling strain.

Recent advances in improving metabolic robustness of microbial cell factories

Engineering microbial cell factories has been widely applied to produce compounds spanning from intricate natural products to bulk commodities. In each case, host robustness is essential to ensure the reliable and sustainable production of targeted metabolites. However, it can be negatively affected by metabolic burden, pathway toxicity, and harsh environment, resulting in a decreased titer and productivity. Enhanced robustness enables host to have better production performance under complicated growth circumstances. Here, we review current strategies for boosting host robustness, including metabolic balancing, genetic and phenotype stability enhancement, and tolerance engineering. In addition, we discuss the challenges and future perspectives on microbial host engineering for increased robustness.

Genome-Wide CRISPRi-Based Identification of Targets for Decoupling Growth from Production

Growth decoupling can be used to optimize microbial production of biobased compounds by inhibiting excess biomass formation and redirect carbon flux from growth to product formation. However, identifying suitable genetic targets through rational design is challenging. Here, we conduct a genome-wide CRISPRi screen to discover growth switches suitable for decoupling growth and production. Using an sgRNA library covering 12 238 loci in the Escherichia coli genome, we screen for targets that inhibit growth while allowing for continued protein production. In total, we identify 1332 sgRNAs that simultaneously decrease growth and maintain or increase accumulation of GFP. The top target sibB/ibsB shows more than 5-fold increase in GFP accumulation and 45% decrease in biomass formation. Overall, our genome-wide CRISPRi screen provides key targets for growth decoupling, and the approach can be applied to improve biobased production in other microorganisms.

Development of High-Performance Whole Cell Biosensors Aided by Statistical Modeling

Whole cell biosensors are genetic systems that link the presence of a chemical, or other stimulus, to a user-defined gene expression output for applications in sensing and control. However, the gene expression level of biosensor regulatory components required for optimal performance is nonintuitive, and classical iterative approaches do not efficiently explore multidimensional experimental space. To overcome these challenges, we used a design of experiments (DoE) methodology to efficiently map gene expression levels and provide biosensors with enhanced performance. This methodology was applied to two biosensors that respond to catabolic breakdown products of lignin biomass, protocatechuic acid and ferulic acid. Utilizing DoE we systematically modified biosensor dose-response behavior by increasing the maximum signal output (up to 30-fold increase), improving dynamic range (>500-fold), expanding the sensing range (∼4-orders of magnitude), increasing sensitivity (by >1500-fold), and modulated the slope of the curve to afford biosensors designs with both digital and analogue dose-response behavior. This DoE method shows promise for the optimization of regulatory systems and metabolic pathways constructed from novel, poorly characterized parts.

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

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