Dynamic metabolic engineering: New strategies for developing responsive cell factories

2-Stage microfermentations

Cell based factories can be engineered to produce a wide variety of products. Advances in DNA synthesis and genome editing have greatly simplified the design and construction of these factories. It has never been easier to generate hundreds or even thousands of cell factory strain variants for evaluation. These advances have amplified the need for standardized, higher throughput means of evaluating these designs. Toward this goal, we have previously reported the development of engineered E. coli strains and associated 2-stage production processes to simplify and standardize strain engineering, evaluation and scale up. This approach relies on decoupling growth (stage 1), from production, which occurs in stationary phase (stage 2). Phosphate depletion is used as the trigger to stop growth as well as induce heterologous expression. Here, we describe in detail the development of protocols for the evaluation of engineered E. coli strains in 2-stage microfermentations. These protocols are readily adaptable to the evaluation of strains producing a wide variety of protein as well as small molecule products. Additionally, by detailing the approach to protocol development, these methods are also adaptable to additional cellular hosts, as well as other 2-stage processes with various additional triggers.

Manipulating gene expression levels in mammalian cell factories: An outline of synthetic molecular toolboxes to achieve multiplexed control

Mammalian cells have developed dedicated molecular mechanisms to tightly control expression levels of their genes where the specific transcriptomic signature across all genes eventually determines the cell's phenotype. Modulating cellular phenotypes is of major interest to study their role in disease or to reprogram cells for the manufacturing of recombinant products, such as biopharmaceuticals. Cells of mammalian origin, for example Chinese hamster ovary (CHO) and Human embryonic kidney 293 (HEK293) cells, are most commonly employed to produce therapeutic proteins. Early genetic engineering approaches to alter their phenotype have often been attempted by "uncontrolled" overexpression or knock-down/-out of specific genetic factors. Many studies in the past years, however, highlight that rationally regulating and fine-tuning the strength of overexpression or knock-down to an optimum level, can adjust phenotypic traits with much more precision than such "uncontrolled" approaches. To this end, synthetic biology tools have been generated that enable (fine-)tunable and/or inducible control of gene expression. In this review, we discuss various molecular tools used in mammalian cell lines and group them by their mode of action: transcriptional, post-transcriptional, translational and post-translational regulation. We discuss the advantages and disadvantages of using these tools for each cell regulatory layer and with respect to cell line engineering approaches. This review highlights the plethora of synthetic toolboxes that could be employed, alone or in combination, to optimize cellular systems and eventually gain enhanced control over the cellular phenotype to equip mammalian cell factories with the tools required for efficient production of emerging, more difficult-to-express biologics formats.

Production of D-glucaric acid with phosphoglucose isomerase-deficient Saccharomyces cerevisiae

D-Glucaric acid is a potential biobased platform chemical. Previously mainly Escherichia coli, but also the yeast Saccharomyces cerevisiae, and Pichia pastoris, have been engineered for conversion of D-glucose to D-glucaric acid via myo-inositol. One reason for low yields from the yeast strains is the strong flux towards glycolysis. Thus, to decrease the flux of D-glucose to biomass, and to increase D-glucaric acid yield, the four step D-glucaric acid pathway was introduced into a phosphoglucose isomerase deficient (Pgi1p-deficient) Saccharomyces cerevisiae strain. High D-glucose concentrations are toxic to the Pgi1p-deficient strains, so various feeding strategies and use of polymeric substrates were studied. Uniformly labelled 13C-glucose confirmed conversion of D-glucose to D-glucaric acid. In batch bioreactor cultures with pulsed D-fructose and ethanol provision 1.3 g D-glucaric acid L-1 was produced. The D-glucaric acid titer (0.71 g D-glucaric acid L-1) was lower in nitrogen limited conditions, but the yield, 0.23 g D-glucaric acid [g D-glucose consumed]-1, was among the highest that has so far been reported from yeast. Accumulation of myo-inositol indicated that myo-inositol oxygenase activity was limiting, and that there would be potential to even higher yield. The Pgi1p-deficiency in S. cerevisiae provides an approach that in combination with other reported modifications and bioprocess strategies would promote the development of high yield D-glucaric acid yeast strains.

FastKnock: an efficient next-generation approach to identify all knockout strategies for strain optimization

Overproduction of desired native or nonnative biochemical(s) in (micro)organisms can be achieved through metabolic engineering. Appropriate rewiring of cell metabolism is performed by making rational changes such as insertion, up-/down-regulation and knockout of genes and consequently metabolic reactions. Finding appropriate targets (including proper sets of reactions to be knocked out) for metabolic engineering to design optimal production strains has been the goal of a number of computational algorithms. We developed FastKnock, an efficient next-generation algorithm for identifying all possible knockout strategies (with a predefined maximum number of reaction deletions) for the growth-coupled overproduction of biochemical(s) of interest. We achieve this by developing a special depth-first traversal algorithm that allows us to prune the search space significantly. This leads to a drastic reduction in execution time. We evaluate the performance of the FastKnock algorithm using various Escherichia coli genome-scale metabolic models in different conditions (minimal and rich mediums) for the overproduction of a number of desired metabolites. FastKnock efficiently prunes the search space to less than 0.2% for quadruple- and 0.02% for quintuple-reaction knockouts. Compared to the classic approaches such as OptKnock and the state-of-the-art techniques such as MCSEnumerator methods, FastKnock found many more beneficial and important practical solutions. The availability of all the solutions provides the opportunity to further characterize, rank and select the most appropriate intervention strategy based on any desired evaluation index. Our implementation of the FastKnock method in Python is publicly available at https://github.com/leilahsn/FastKnock .

Coenzyme A Thioester Intermediates as Platform Molecules in Cell-Free Chemical Biomanufacturing

The in vitro synthesis of Coenzyme A (CoA)-thioester intermediates opens new avenues to transform simple molecules into more complex and multifunctional ones by assembling cell-free biosynthetic cascades. In this review, we have systematically cataloged known CoA-dependent enzyme reactions that have been successfully implemented in vitro. To faciliate their identification, we provide their UniProt ID when available. Based on this catalog, we have organized enzymes into three modules: activation, modification, and removal. i) The activation module includes enzymes capable of fusing CoA with organic molecules. ii) The modification module includes enzymes capable of catalyzing chemical modifications in the structure of acyl-CoA intermediates. And iii) the removal module includes enzymes able to remove the CoA and release an organic molecule different from the one activated in the upstream. Based on these reactions, we constructed a reaction network that summarizes the most relevant CoA-dependent biosynthetic pathways reported until today. From the information available in the articles, we have plotted the total turnover number of CoA as a function of the product titer, observing a positive correlation between both parameters. Therefore, the success of a CoA-dependent in vitro pathway depends on its ability to regenerate CoA, but also to regenerate other cofactors such as NAD(P)H and ATP.

Coordination of carbon partitioning and photosynthesis by a two-component signaling network in Synechococcus elongatus PCC 7942

Photosynthetic organisms need to balance the rate of photosynthesis with the utilization of photosynthetic products by downstream reactions. While such "source/sink" pathways are well-interrogated in plants, analogous regulatory systems are unknown or poorly studied in single-celled algal and cyanobacterial species. Towards the identification of energy/sugar sensors in cyanobacteria, we utilized an engineered strain of Synechococcus elongatus PCC 7942 that allows experimental manipulation of carbon status. We conducted a screening of all two-component systems (TCS) and serine/threonine kinases (STKs) encoded in S. elongatus PCC 7942 by analyzing phenotypes consistent with sucrose-induced relaxation of sink inhibition. We narrowed the candidate sensor proteins by analyzing changes observed after sucrose feeding. We show that a clustered TCS network containing RpaA, CikB, ManS and NblS are involved in the regulation of genes related to photosynthesis, pigment synthesis, and Rubisco concentration in response to sucrose. Altogether, these results highlight a regulatory TCS group that may play under-appreciated functions in carbon partitioning and energy balancing in cyanobacteria.

Green Biologics: Harnessing the Power of Plants to Produce Pharmaceuticals

Plants are increasingly used for the production of high-quality biological molecules for use as pharmaceuticals and biomaterials in industry. Plants have proved that they can produce life-saving therapeutic proteins (Elelyso™-Gaucher's disease treatment, ZMapp™-anti-Ebola monoclonal antibodies, seasonal flu vaccine, Covifenz™-SARS-CoV-2 virus-like particle vaccine); however, some of these therapeutic proteins are difficult to bring to market, which leads to serious difficulties for the manufacturing companies. The closure of one of the leading companies in the sector (the Canadian biotech company Medicago Inc., producer of Covifenz) as a result of the withdrawal of investments from the parent company has led to the serious question: What is hindering the exploitation of plant-made biologics to improve health outcomes? Exploring the vast potential of plants as biological factories, this review provides an updated perspective on plant-derived biologics (PDB). A key focus is placed on the advancements in plant-based expression systems and highlighting cutting-edge technologies that streamline the production of complex protein-based biologics. The versatility of plant-derived biologics across diverse fields, such as human and animal health, industry, and agriculture, is emphasized. This review also meticulously examines regulatory considerations specific to plant-derived biologics, shedding light on the disparities faced compared to biologics produced in other systems.

Taming CRISPRi: Dynamic range tuning through guide RNA diversion

CRISPRi is a powerful technique to repress gene expression in a targeted and highly efficient manner. However, this potency is a double-edged sword in inducible systems, as even leaky expression of guide RNA results in a repression phenotype, complicating applications such as dynamic metabolic engineering. We evaluated three methods to enhance the controllability of CRISPRi by modulating the level of free and DNA-bound guide RNA complexes. Overall repression can be attenuated through rationally designed mismatches in the reversibility determining region of the guide RNA sequence; decoy target sites can selectively modulate repression at low levels of induction; and the implementation of feedback control not only enhances the linearity of induction, but broadens the dynamic range of the output as well. Furthermore, feedback control significantly enhances the recovery rate after induction is removed. Used in combination, these techniques enable the fine-tuning of CRISPRi to meet restrictions imposed by the target and match the input signal required for induction.

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.

Optogenetic control of Cdc48 for dynamic metabolic engineering in yeast

Dynamic metabolic engineering is a strategy to switch key metabolic pathways in microbial cell factories from biomass generation to accumulation of target products. Here, we demonstrate that optogenetic intervention in the cell cycle of budding yeast can be used to increase production of valuable chemicals, such as the terpenoid β-carotene or the nucleoside analog cordycepin. We achieved optogenetic cell-cycle arrest in the G2/M phase by controlling activity of the ubiquitin-proteasome system hub Cdc48. To analyze the metabolic capacities in the cell cycle arrested yeast strain, we studied their proteomes by timsTOF mass spectrometry. This revealed widespread, but highly distinct abundance changes of metabolic key enzymes. Integration of the proteomics data in protein-constrained metabolic models demonstrated modulation of fluxes directly associated with terpenoid production as well as metabolic subsystems involved in protein biosynthesis, cell wall synthesis, and cofactor biosynthesis. These results demonstrate that optogenetically triggered cell cycle intervention is an option to increase the yields of compounds synthesized in a cellular factory by reallocation of metabolic resources.

Using a synthetic machinery to improve carbon yield with acetylphosphate as the core

In microbial cell factory, CO2 release during acetyl-CoA production from pyruvate significantly decreases the carbon atom economy. Here, we construct and optimize a synthetic carbon conserving pathway named as Sedoheptulose-1,7-bisphosphatase Cycle with Trifunctional PhosphoKetolase (SCTPK) in Escherichia coli. This cycle relies on a generalist phosphoketolase Xfspk and converts glucose into the stoichiometric amounts of acetylphosphate (AcP). Furthermore, genetic circuits responding to AcP positively or negatively are created. Together with SCTPK, they constitute a gene-metabolic oscillator that regulates Xfspk and enzymes converting AcP into valuable chemicals in response to intracellular AcP level autonomously, allocating metabolic flux rationally and improving the carbon atom economy of bioconversion process. Using this synthetic machinery, mevalonate is produced with a yield higher than its native theoretical yield, and the highest titer and yield of 3-hydroxypropionate via malonyl-CoA pathway are achieved. This study provides a strategy for improving the carbon yield of microbial cell factories.

Genetic Engineering of Resident Bacteria in the Gut Microbiome

Techniques by which to genetically manipulate members of the microbiota enable both the evaluation of host-microbe interactions and an avenue by which to monitor and modulate human physiology. Genetic engineering applications have traditionally focused on model gut residents, such as Escherichia coli and lactic acid bacteria. However, emerging efforts by which to develop synthetic biology toolsets for "nonmodel" resident gut microbes could provide an improved foundation for microbiome engineering. As genome engineering tools come online, so too have novel applications for engineered gut microbes. Engineered resident gut bacteria facilitate investigations of the roles of microbes and their metabolites on host health and allow for potential live microbial biotherapeutics. Due to the rapid pace of discovery in this burgeoning field, this minireview highlights advancements in the genetic engineering of all resident gut microbes.

FastKnock: An efficient next-generation approach to identify all knockout strategies for strain optimization

Overproduction of desired native or nonnative biochemical(s) in (micro)organisms can be achieved through metabolic engineering. Appropriate rewiring of cell metabolism is performed making rational changes such as insertion, up-/down-regulation and knockout of genes and consequently metabolic reactions. Finding appropriate targets (including proper sets of reactions to be knocked out) for metabolic engineering to design optimal production strains has been the goal of a number of computational algorithms. We developed FastKnock, an efficient next-generation algorithm for identifying all possible knockout strategies for the growth-coupled overproduction of biochemical(s) of interest. We achieve this by developing a special depth-first traversal algorithm that allows us to prune the search space significantly. This leads to a drastic reduction in execution time. We evaluate the performance of the FastKnock algorithm using three Escherichia coli genome-scale metabolic models in different conditions (minimal and rich mediums) for the overproduction of a number of desired metabolites. FastKnock efficiently prunes the search space to less than 0.2% for quadruple and 0.02% for quintuple-reaction knockouts. Compared to the classic approaches such as OptKnock and the state-of-the-art techniques such as MCSEnumerator methods, FastKnock found many more useful and important practical solutions. The availability of all the solutions provides the opportunity to further characterize and select the most appropriate intervention strategy based on any desired evaluation index. Our implementation of the FastKnock method in Python is publicly available at https://github.com/leilahsn/FastKnock.

A blueprint for a synthetic genetic feedback optimizer

Biomolecular control enables leveraging cells as biomanufacturing factories. Despite recent advancements, we currently lack genetically encoded modules that can be deployed to dynamically fine-tune and optimize cellular performance. Here, we address this shortcoming by presenting the blueprint of a genetic feedback module to optimize a broadly defined performance metric by adjusting the production and decay rate of a (set of) regulator species. We demonstrate that the optimizer can be implemented by combining available synthetic biology parts and components, and that it can be readily integrated with existing pathways and genetically encoded biosensors to ensure its successful deployment in a variety of settings. We further illustrate that the optimizer successfully locates and tracks the optimum in diverse contexts when relying on mass action kinetics-based dynamics and parameter values typical in Escherichia coli.

Application of Quorum Sensing in Metabolic Engineering

Metabolic engineering is widely utilized in the food and other fields and has the benefits of low-cost substrates, eco-friendly fermentation processes, and efficient substrate synthesis. Microbial synthesis by metabolic engineering requires maintaining the productive capacity of the microorganism. Moreover, economic reasons limit the use of inducers in the exogenous synthesis pathway. Most unicellular microorganisms can interact by emitting signaling molecules; this mechanism, known as quorum sensing (QS), is an autoinduced system of microorganisms. With the deepening research on QS systems of different microorganisms, its components are widely used to regulate the metabolic synthesis of microorganisms as a dynamic regulatory system. In this Review, we described the typical bacterial QS mechanisms. Then, we summarized various regulatory strategies for QS and their applications to metabolic engineering. Finally, we underlined the potential for QS modularity in future metabolic engineering and suggested stimulating research on fungal QS systems.

Dynamic upregulation of the rate-limiting enzyme for valerolactam biosynthesis in Corynebacterium glutamicum

Valerolactam is a monomer used to manufacture high-value nylon-5 and nylon-6,5. However, the biological production of valerolactam has been limited by the inadequate efficiency of enzymes to cyclize 5-aminovaleric acid to produce valerolactam. In this study, we engineered Corynebacterium glutamicum with a valerolactam biosynthetic pathway consisting of DavAB from Pseudomonas putida to convert L-lysine to 5-aminovaleric acid and β-alanine CoA transferase (Act) from Clostridium propionicum to produce valerolactam from 5-aminovaleric acid. Most of the L-lysine was converted into 5-aminovaleric acid, but promoter optimization and increasing the copy number of Act were insufficient to significantly improve the titer of valerolactam. To eliminate the bottleneck at Act, we designed a dynamic upregulation system (a positive feedback loop based on the valerolactam biosensor ChnR/Pb). We used laboratory evolution to engineer ChnR/Pb to have higher sensitivity and a higher dynamic output range, and the engineered ChnR-B1/Pb-E1 system was used to overexpress the rate-limiting enzymes (Act/ORF26/CaiC) that cyclize 5-aminovaleric acid into valerolactam. In glucose fed-batch culture, we obtained 12.33 g/L valerolactam from the dynamic upregulation of Act, 11.88 g/L using ORF26, and 12.15 g/L using CaiC. Our engineered biosensor (ChnR-B1/Pb-E1 system) was also sensitive to 0.01-100 mM caprolactam, which suggests that this dynamic upregulation system can be used to enhance caprolactam biosynthesis in the future.

Metabolic Engineering of Microorganisms to Produce Pyruvate and Derived Compounds

Pyruvate is a hub of various endogenous metabolic pathways, including glycolysis, TCA cycle, amino acid, and fatty acid biosynthesis. It has also been used as a precursor for pyruvate-derived compounds such as acetoin, 2,3-butanediol (2,3-BD), butanol, butyrate, and L-alanine biosynthesis. Pyruvate and derivatives are widely utilized in food, pharmaceuticals, pesticides, feed additives, and bioenergy industries. However, compounds such as pyruvate, acetoin, and butanol are often chemically synthesized from fossil feedstocks, resulting in declining fossil fuels and increasing environmental pollution. Metabolic engineering is a powerful tool for producing eco-friendly chemicals from renewable biomass resources through microbial fermentation. Here, we review and systematically summarize recent advances in the biosynthesis pathways, regulatory mechanisms, and metabolic engineering strategies for pyruvate and derivatives. Furthermore, the establishment of sustainable industrial synthesis platforms based on alternative substrates and new tools to produce these compounds is elaborated. Finally, we discuss the potential difficulties in the current metabolic engineering of pyruvate and derivatives and promising strategies for constructing efficient producers.

Engineering cell morphology by CRISPR interference in Acinetobacter baylyi ADP1

Microbial production of intracellular compounds can be engineered by redirecting the carbon flux towards products and increasing the cell size. Potential engineering strategies include exploiting clustered regularly interspaced short palindromic repeats interference (CRISPRi)-based tools for controlling gene expression. Here, we applied CRISPRi for engineering Acinetobacter baylyi ADP1, a model bacterium for synthesizing intracellular storage lipids, namely wax esters. We first established an inducible CRISPRi system for strain ADP1, which enables tightly controlled repression of target genes. We then targeted the glyoxylate shunt to redirect carbon flow towards wax esters. Second, we successfully employed CRISPRi for modifying cell morphology by repressing ftsZ, an essential gene required for cell division, in combination with targeted knock-outs to generate significantly enlarged filamentous or spherical cells respectively. The engineered cells sustained increased wax ester production metrics, demonstrating the potential of cell morphology engineering in the production of intracellular lipids.

The Transcription Activator AtxA from Bacillus Anthracis was Employed for Developing a Tight-Control, High-Level, Modulable, and Stationary-Phase Specific Transcription Activity in Escherichia Coli

The strong transcriptional activity of the virulent gene pagA in Bacillus anthracis has been proven to be anthrax toxin activator (AtxA)-regulated. However, the obscure pagA transcription mechanism hinders practical applications of this strong promoter. In this study, a 509-bp DNA fragment [termed 509sequence, (−508)-(+1) relative to the P2 transcription start site] was cloned upstream of rbs-GFPuv as pTOL02B to elucidate the AtxA-regulated transcription. The 509sequence was dissected into the −10 sequence, −35 sequence, AT_rich tract, SLI/SLII and upstream site. In conjunction with the heterologous co-expression of AtxA (under the control of the T7 promoter), the −10 sequence (TATACT) was sufficient for the AtxA-regulated transcription. Integration of pTOL02F + pTOLAtxA as pTOL03F showed that the AtxA-regulated transcription exhibited a strong specific fluorescence intensity/common analytical chemistry term (OD₆₀₀) of 40 597 ± 446 and an induction/repression ratio of 122. An improved induction/repression ratio of 276 was achieved by cultivating Escherichia coli/pTOL03F in M9 minimal medium. The newly developed promoter system termed P_AtxA consists of AtxA, the −10 sequence and Escherichia RNA polymerase. These three elements synergistically and cooperatively formed a previously undiscovered transcription system, which exhibited a tight-control, high-level, modulable and stationary-phase-specific transcription. The P_AtxA was used for phaCAB expression for the stationary-phase polyhydroxybutyrate production, and the results showed that a PHB yield, content and titer of 0.20 ± 0.27 g/g-glucose, 68 ± 11% and 1.5 ± 0.4 g/l can be obtained. The positive inducible P_AtxA, in contrast to negative inducible, should be a useful tool to diversify the gene information flow in synthetic biology.

Graphical Abstract

Complexity reduction and opportunities in the design, integration and intensification of biocatalytic processes for metabolite synthesis

The biosynthesis of metabolites from available starting materials is becoming an ever important area due to the increasing demands within the life science research area. Access to metabolites is making essential contributions to analytical, diagnostic, therapeutic and different industrial applications. These molecules can be synthesized by the enzymes of biological systems under sustainable process conditions. The facile synthetic access to the metabolite and metabolite-like molecular space is of fundamental importance. The increasing knowledge within molecular biology, enzyme discovery and production together with their biochemical and structural properties offers excellent opportunities for using modular cell-free biocatalytic systems. This reduces the complexity of synthesizing metabolites using biological whole-cell approaches or by classical chemical synthesis. A systems biocatalysis approach can provide a wealth of optimized enzymes for the biosynthesis of already identified and new metabolite molecules.

Transcriptional Tuning of Mevalonate Pathway Enzymes to Identify the Impact on Limonene Production in Escherichia coli

Heterologous production of limonene in microorganisms through the mevalonate (MVA) pathway has traditionally imposed metabolic burden and reduced cell fitness, where imbalanced stoichiometries among sequential enzymes result in the accumulation of toxic intermediates. Although prior studies have shown that changes to mRNA stability, RBS strength, and protein homology can be effective strategies for balancing enzyme levels in the MVA pathway, testing different variations of these parameters often requires distinct genetic constructs, which can exponentially increase assembly costs as pathways increase in size. Here, we developed a multi-input transcriptional circuit to regulate the MVA pathway, where four chemical inducers, l-arabinose (Ara), choline chloride (Cho), cuminic acid (Cuma), and isopropyl β-d-1-thiogalactopyranoside (IPTG), each regulate one of four orthogonal promoters. We tested modular transcriptional regulation of the MVA pathway by placing this circuit in an engineered Escherichia coli "marionette" strain, which enabled systematic and independent tuning of the first three enzymes (AtoB, HMGS, and HMGR) in the MVA pathway. By systematically testing combinations of chemical inducers as inputs, we investigated relationships between the expressions of different MVA pathway submodules, finding that limonene yields are sensitive to the coordinated transcriptional regulation of HMGS and HMGR.

Light-induced fermenter production of derivatives of the sweet protein monellin is maximized in prestationary Saccharomyces cerevisiae cultures

Optogenetics has great potential for biotechnology and metabolic engineering due to the cost-effective control of cellular activities. The usage of optogenetics techniques for the biosynthesis of bioactive molecules ensures reduced costs and enhanced regulatory possibilities. This requires development of efficient methods for light-delivery during a production process in a fermenter. Here, we benchmarked the fermenter production of a low-caloric sweetener in Saccharomyces cerevisiae with optogenetic tools against the production in small scale cell culture flasks. An expression system based on the light-controlled interaction between Cry2 and Cib1 was used for sweet-protein production. Optimization of the fermenter process was achieved by increasing the light-flux during the production phase to circumvent shading by yeast cells at high densities. Maximal amounts of the sweet-protein were produced in a pre-stationary growth phase, whereas at later stages, a decay in protein abundance was observable. Our investigation showcases the upscaling of an optogenetic production process from small flasks to a bioreactor. Optogenetic-controlled production in a fermenter is highly cost-effective due to the cheap inducer and therefore a viable alternative to chemicals for a process that requires an induction step. This article is protected by copyright. All rights reserved.

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.

Emerging landscape of molecular interaction networks: Opportunities, challenges and prospects

Network biology finds application in interpreting molecular interaction networks and providing insightful inferences using graph theoretical analysis of biological systems. The integration of computational bio-modelling approaches with different hybrid network-based techniques provides additional information about the behaviour of complex systems. With increasing advances in high-throughput technologies in biological research, attempts have been made to incorporate this information into network structures, which has led to a continuous update of network biology approaches over time. The newly minted centrality measures accommodate the details of omics data and regulatory network structure information. The unification of graph network properties with classical mathematical and computational modelling approaches and technologically advanced approaches like machine-learning- and artificial intelligence-based algorithms leverages the potential application of these techniques. These computational advances prove beneficial and serve various applications such as essential gene prediction, identification of drug–disease interaction and gene prioritization. Hence, in this review, we have provided a comprehensive overview of the emerging landscape of molecular interaction networks using graph theoretical approaches. With the aim to provide information on the wide range of applications of network biology approaches in understanding the interaction and regulation of genes, proteins, enzymes and metabolites at different molecular levels, we have reviewed the methods that utilize network topological properties, emerging hybrid network-based approaches and applications that integrate machine learning techniques to analyse molecular interaction networks. Further, we have discussed the applications of these approaches in biomedical research with a note on future prospects.

Multi-layer CRISPRa/i circuits for dynamic genetic programs in cell-free and bacterial systems

CRISPR-Cas transcriptional circuits hold great promise as platforms for engineering metabolic networks and information processing circuits. Historically, prokaryotic CRISPR control systems have been limited to CRISPRi. Creating approaches to integrate CRISPRa for transcriptional activation with existing CRISPRi-based systems would greatly expand CRISPR circuit design space. Here, we develop design principles for engineering prokaryotic CRISPRa/i genetic circuits with network topologies specified by guide RNAs. We demonstrate that multi-layer CRISPRa/i cascades and feedforward loops can operate through the regulated expression of guide RNAs in cell-free expression systems and E. coli. We show that CRISPRa/i circuits can program complex functions by designing type 1 incoherent feedforward loops acting as fold-change detectors and tunable pulse-generators. By investigating how component characteristics relate to network properties such as depth, width, and speed, this work establishes a framework for building scalable CRISPRa/i circuits as regulatory programs in cell-free expression systems and bacterial hosts. A record of this paper's transparent peer review process is included in the supplemental information.

Synthetic gene networks recapitulate dynamic signal decoding and differential gene expression

Cells live in constantly changing environments and employ dynamic signaling pathways to transduce information about the signals they encounter. However, the mechanisms by which dynamic signals are decoded into appropriate gene expression patterns remain poorly understood. Here, we devise networked optogenetic pathways that achieve dynamic signal processing functions that recapitulate cellular information processing. Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling edge pulse detector and show that this circuit can be employed to demultiplex dynamically encoded signals. We combine this demultiplexer with dCas9-based gene networks to construct pulsatile signal filters and decoders. Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state. Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway. Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.

Refactoring transcription factors for metabolic engineering

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

Engineering a Controllable Targeted Protein Degradation System and a Derived OR-GATE-Type Inducible Gene Expression System in Synechococcus elongatus PCC 7942

Cyanobacteria are important model organisms for exploring the mechanisms of photosynthesis and are considered as promising microbial platforms for photosynthetic biomanufacturing. The development of efficient cyanobacteria cell factories requires efficient and convenient tools to dynamically regulate and manipulate target proteins, modules, and pathways. Targeted protein degradation is important to achieve rapid responses of cellular metabolic networks to artificial or environmental signals, and there are currently limited approaches to induce protein degradation in cyanobacteria. In this work, we developed an Escherichia coli sourced ssrA-tagging system in an important cyanobacteria strain, Synechococcus elongatus PCC 7942, to achieve inducible degradation of target proteins. A modified version of the E. coli ssrA tag (ssrA_DAS) proved to be immune to the native ClpXP system in Synechococcus elongatus PCC 7942, while induced expression of the E. coli sourced adaptor SspB and ClpXP resulted in effective degradation of the tagged proteins. Compared to the previously developed down-regulation approaches, the inducible ssrA_DAS-SspB-ClpXP_Ec system facilitated the smart and rapid degradation of target proteins in PCC7942 cells at different growth stages. Furthermore, when used to regulate the degradation of LacI, the repressor element of LacO-LacI transcription regulation system, an efficient and stringent inducible gene expression system was obtained based on an OR-GATE type genetic circuit design. The tools developed in this work expanded the cyanobacteria synthetic biology toolbox and will facilitate the success of future dynamic metabolic engineering.

Thermogenetics: Applications come of age

Temperature is a ubiquitous physical cue that is non-invasive, penetrative and easy to apply. In the growing field of thermogenetics, through beneficial repurposing of natural thermosensing mechanisms, synthetic biology is bringing new opportunities to design and build robust temperature-sensitive (TS) sensors which forms a thermogenetic toolbox of well characterised biological parts. Recent advancements in technological platforms available have expedited the discovery of novel or de novo thermosensors which are increasingly deployed in many practical temperature-dependent biomedical, industrial and biosafety applications. In all, the review aims to convey both the exhilarating recent technological developments underlying the advancement of thermosensors and the exciting opportunities the nascent thermogenetic field holds for biomedical and biotechnology applications.

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

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

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.

Quantitative metabolomics for dynamic metabolic engineering using stable isotope labeled internal standards mixture (SILIS)

The production of chemicals and fuels from renewable resources using engineered microbes is an attractive alternative for current fossil-dependent industries. Metabolic engineering has contributed to pathway engineering for the production of chemicals and fuels by various microorganisms. Recently, dynamic metabolic engineering harnessing synthetic biological tools has become a next-generation strategy in this field. The dynamic regulation of metabolic flux during fermentation optimizes metabolic states according to each fermentation stage such as cell growth phase and compound production phase. However, it is necessary to repeat the evaluation and redesign of the dynamic regulation system to achieve the practical use of engineered microbes. In this study, we performed quantitative metabolome analysis to investigate the effects of dynamic metabolic flux regulation on engineered Escherichia coli for γ-amino butyrate (GABA) fermentation. We prepared a stable isotope-labeled internal standard mixture (SILIS) for the stable isotope dilution method (SIDM), a mass spectrometry-based quantitative metabolome analysis method. We found multiple candidate bottlenecks for GABA production. Some metabolic reactions in the GABA production pathway should be engineered for further improvement in the direct GABA fermentation with dynamic metabolic engineering strategy.

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

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

Optogenetic strategies for the control of gene expression in yeasts

Optogenetics involves the use of light to control cellular functions and has become increasingly popular in various areas of research, especially in the precise control of gene expression. While this technology is already well established in neurobiology and basic research, its use in bioprocess development is still emerging. Some optogenetic switches have been implemented in yeasts for different purposes, taking advantage of a wide repertoire of biological parts and relatively easy genetic manipulation. In this review, we cover the current strategies used for the construction of yeast strains to be used in optogenetically controlled protein or metabolite production, as well as the operational aspects to be considered for the scale-up of this type of process. Finally, we discuss the main applications of optogenetic switches in yeast systems and highlight the main advantages and challenges of bioprocess development considering future directions for this field.

Rapid prototyping and design of cybergenetic single-cell controllers

The design and implementation of synthetic circuits that operate robustly in the cellular context is fundamental for the advancement of synthetic biology. However, their practical implementation presents challenges due to low predictability of synthetic circuit design and time-intensive troubleshooting. Here, we present the Cyberloop, a testing framework to accelerate the design process and implementation of biomolecular controllers. Cellular fluorescence measurements are sent in real-time to a computer simulating candidate stochastic controllers, which in turn compute the control inputs and feed them back to the controlled cells via light stimulation. Applying this framework to yeast cells engineered with optogenetic tools, we examine and characterize different biomolecular controllers, test the impact of non-ideal circuit behaviors such as dilution on their operation, and qualitatively demonstrate improvements in controller function with certain network modifications. From this analysis, we derive conditions for desirable biomolecular controller performance, thereby avoiding pitfalls during its biological implementation.

Advances in promoter engineering: novel applications and predefined transcriptional control

Synthetic biology continues to progress by relying on more robust tools for transcriptional control, of which promoters are the most fundamental component. Numerous studies have sought to characterize promoter function, determine principles to guide their engineering, and create promoters with stronger expression or tailored inducible control. In this review, we will summarize promoter architecture and highlight recent advances in the field, focusing on the novel applications of inducible promoter design and engineering towards metabolic engineering and cellular therapeutic development. Additionally, we will highlight how the expansion of new, machine learning techniques for modeling and engineering promoter sequences are enabling more accurate prediction of promoter characteristics. This article is protected by copyright. All rights reserved.

Modular optimization in metabolic engineering

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

Designing an irreversible metabolic switch for scalable induction of microbial chemical production

Bacteria can be harnessed to synthesise high-value chemicals. A promising strategy for increasing productivity uses inducible control systems to switch metabolism from growth to chemical synthesis once a large population of cell factories are generated. However, use of expensive chemical inducers limits scalability of this approach for biotechnological applications. Switching using cheap nutrients is an appealing alternative, but their tightly regulated uptake and consumption again limits scalability. Here, using mathematical models of fatty acid uptake in E. coli as an exemplary case study, we unravel how the cell's native regulation and program of induction can be engineered to minimise inducer usage. We show that integrating positive feedback loops into the circuitry creates an irreversible metabolic switch, which, requiring only temporary induction, drastically reduces inducer usage. Our proposed switch should be widely applicable, irrespective of the product of interest, and brings closer the realization of scalable and sustainable microbial chemical production.

Highly Efficient Production of N-Acetyl-glucosamine in Escherichia coli by Appropriate Catabolic Division of Labor in the Utilization of Mixed Glycerol/Glucose Carbon Sources

Currently, microbial production is becoming a competitive method for N-acetyl-glucosamine production. As the biosynthesis of N-acetyl-glucosamine originating from fructose-6-P directly competes with central carbon metabolism for precursor supply, the consumption of glucose for cell growth and cellular metabolism severely limits the yield of N-acetyl-glucosamine. In this study, appropriate catabolic division of labor in the utilization of mixed carbon sources was achieved by deleting the pfkA gene and enhancing the utilization of glycerol by introducing the glpK mutant. Glycerol thus mainly contributed to cell growth and cellular metabolism, and more glucose was saved for efficient N-acetyl-glucosamine synthesis. By optimizing the ratio of glycerol to glucose, the balancing of cell growth/cellular metabolism and N-acetyl-glucosamine synthesis was achieved. The resulting strain GLALD-7 produced 179.7 g/L N-acetyl-glucosamine using mixed glycerol/glucose (1:8, m/m) carbon sources in a 5 L bioreactor, with a yield of 0.458 g/g total carbon sources (0.529 g/g glucose) and a productivity of 2.57 g/L/h. Coherent high titer/yield/productivity was obtained, with the highest values ever reported, suggesting that an appropriate catabolic division of labor using mixed glycerol/glucose carbon sources is a useful strategy for facilitating the microbial production of chemicals originating from glucose or metabolites upstream of glycolysis.

Dynamic Control of Gene Expression with Riboregulated Switchable Feedback Promoters

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

Recent advances in tuning the expression and regulation of genes for constructing microbial cell factories

To overcome environmental problems caused by the use of fossil resources, microbial cell factories have become a promising technique for the sustainable and eco-friendly development of valuable products from renewable resources. Constructing microbial cell factories with high titers, yields, and productivity requires a balance between growth and production; to this end, tuning gene expression and regulation is necessary to optimise and precisely control complicated metabolic fluxes. In this article, we review the current trends and advances in tuning gene expression and regulation and consider their engineering at each of the three stages of gene regulation: genomic, mRNA, and protein. In particular, the technological approaches utilised in a diverse range of genetic-engineering-based tools for the construction of microbial cell factories are reviewed and representative applications of these strategies are presented. Finally, the prospects for strategies and systems for tuning gene expression and regulation are discussed.

Opportunities at the Interface of Network Science and Metabolic Modeling

Metabolism plays a central role in cell physiology because it provides the molecular machinery for growth. At the genome-scale, metabolism is made up of thousands of reactions interacting with one another. Untangling this complexity is key to understand how cells respond to genetic, environmental, or therapeutic perturbations. Here we discuss the roles of two complementary strategies for the analysis of genome-scale metabolic models: Flux Balance Analysis (FBA) and network science. While FBA estimates metabolic flux on the basis of an optimization principle, network approaches reveal emergent properties of the global metabolic connectivity. We highlight how the integration of both approaches promises to deliver insights on the structure and function of metabolic systems with wide-ranging implications in discovery science, precision medicine and industrial biotechnology.

Dynamic control over feedback regulatory mechanisms improves NADPH flux and xylitol biosynthesis in engineered E. coli

We report improved NADPH flux and xylitol biosynthesis in engineered E. coli. Xylitol is produced from xylose via an NADPH dependent reductase. We utilize 2-stage dynamic metabolic control to compare two approaches to optimize xylitol biosynthesis, a stoichiometric approach, wherein competitive fluxes are decreased, and a regulatory approach wherein the levels of key regulatory metabolites are reduced. The stoichiometric and regulatory approaches lead to a 20-fold and 90-fold improvement in xylitol production, respectively. Strains with reduced levels of enoyl-ACP reductase and glucose-6-phosphate dehydrogenase, led to altered metabolite pools resulting in the activation of the membrane bound transhydrogenase and an NADPH generation pathway, consisting of pyruvate ferredoxin oxidoreductase coupled with NADPH dependent ferredoxin reductase, leading to increased NADPH fluxes, despite a reduction in NADPH pools. These strains produced titers of 200 g/L of xylitol from xylose at 86% of theoretical yield in instrumented bioreactors. We expect dynamic control over the regulation of the membrane bound transhydrogenase as well as NADPH production through pyruvate ferredoxin oxidoreductase to broadly enable improved NADPH dependent bioconversions or production via NADPH dependent metabolic pathways.

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.