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

Engineering stilbene metabolic pathways in microbial cells

Numerous in vitro and in vivo studies on biological activities of phytostilbenes have brought to the fore the remarkable properties of these compounds and their derivatives, making them a top storyline in natural product research fields. However, getting stilbenes in sufficient amounts for routine biological activity studies and make them available for pharmaceutical and/or nutraceutical industry applications, is hampered by the difficulty to source them through synthetic chemistry-based pathways or extraction from the native plants. Hence, microbial cell cultures have rapidly became potent workhorse factories for stilbene production. In this review, we present the combined efforts made during the past 15 years to engineer stilbene metabolic pathways in microbial cells, mainly the Saccharomyces cerevisiae baker yeast, the Escherichia coli and the Corynebacterium glutamicum bacteria. Rationalized approaches to the heterologous expression of the partial or the entire stilbene biosynthetic routes are presented to allow the identification and/or bypassing of the major bottlenecks in the endogenous microbial cell metabolism as well as potential regulations of the genes involved in these metabolic pathways. The contributions of bioinformatics to synthetic biology are developed to highlight their tremendous help in predicting which target genes are likely to be up-regulated or deleted for controlling the dynamics of precursor flows in the tailored microbial cells. Further insight is given to the metabolic engineering of microbial cells with "decorating" enzymes, such as methyl and glycosyltransferases or hydroxylases, which can act sequentially on the stilbene core structure. Altogether, the cellular optimization of stilbene biosynthetic pathways integrating more and more complex constructs up to twelve genetic modifications has led to stilbene titers ranging from hundreds of milligrams to the gram-scale yields from various carbon sources. Through this review, the microbial production of stilbenes is analyzed, stressing both the engineering dynamic regulation of biosynthetic pathways and the endogenous control of stilbene precursors.

Regulatory Networks Governing Methionine Catabolism into Volatile Organic Sulfur-Containing Compounds in Clonostachys rosea

Adaptation to environmental perturbations requires living systems to coordinately regulate signaling pathways, gene expression, and metabolism. To better understand the mechanisms underlying adaptation, the regulatory nodes within networks must be elucidated. Here, ARO8-2 (which encodes an aminotransferase), PDC (which encodes a decarboxylase), and STR3 (which encodes a demethiolase) were identified as key genes involved in the catabolism of methionine in the mycoparasitic fungus Clonostachys rosea, isolated from Tuber melanosporum ascocarps. Exogenous Met induced the transcription of ARO8-2 and PDC but repressed the transcription of STR3, which is controlled by the putative MSN2 and GLN3 binding sites responding to nitrogen catabolite repression. Met and its structural derivatives function as glutamine synthetase inhibitors, resulting in the downregulation of STR3 expression. The putative GLN3 binding site was necessary for STR3 downregulation. In Saccharomyces cerevisiae, Met and its structural derivatives also triggered downregulation of demethiolase gene expression. Altogether, the results indicated that exogenous Met triggered nitrogen catabolite repression, which stimulated the Ehrlich pathway and negatively regulated the demethiolation pathway via the methionine sulfoximine-responsive regulatory pathway. This finding revealed the regulatory nodes within the networks controlling the catabolism of Met into volatile organic sulfur-containing compounds, thereby enhancing our understanding of adaptation.IMPORTANCE Methionine shuttles organic nitrogen and plays a central role in nitrogen metabolism. Exogenous Met strongly induces the expression of ARO8-2 and PDC, represses the expression of STR3, and generates volatile organic sulfur-containing compounds via the Ehrlich and demethiolation pathways. In this study, we used genetic, bioinformatic, and metabolite-based analyses to confirm that transcriptional control of the aminotransferase gene ARO8-2, the decarboxylase gene PDC, and the demethiolase gene STR3 modulates Met catabolism into volatile organic sulfur-containing compounds. Importantly, we found that, in addition to the Ehrlich pathway, the demethiolation pathway was regulated by a nitrogen catabolite repression-sensitive regulatory pathway that controlled the transcription of genes required to catabolize poor nitrogen sources. This work significantly advances our understanding of nitrogen catabolite repression-sensitive transcriptional regulation of sulfur-containing amino acid catabolism and provides a basis for engineering Met catabolism pathways for the production of fuel and valuable flavor alcohols.

Engineering a Glucosamine-6-phosphate Responsive glmS Ribozyme Switch Enables Dynamic Control of Metabolic Flux in Bacillus subtilis for Overproduction of N-Acetylglucosamine

Bacillus subtilis is a typical industrial microorganism and is widely used in industrial biotechnology, particularly for nutraceutical production. There are many studies on the static metabolic engineering of B. subtilis, whereas there are few reports on dynamic metabolic engineering due to the lack of appropriate elements. Here, we established a dynamic reprogramming strategy for reconstructing metabolic networks in B. subtilis, using a typical nutraceutical, N-acetylglucosamine (GlcNAc), as a model product and the glmS (encoding glucosamine-6-phosphate synthase) ribozyme as an engineering element. First, a trp terminator was introduced to effectively release the glmS ribozyme feedback inhibition. Further, we engineered the native glucosamine-6-phosphate (GlcN6P) responsive glmS ribozyme switch to dynamically control the metabolic flux in B. subtilis for overproduction of GlcNAc. With GlcN6P as a ligand, the native sensor glmS ribozyme is integrated at the 5'- of phosphoglucosamine mutase and 6-phosphofructokinase genes to decrease the flux dynamically toward the peptidoglycan synthesis and glycolysis pathway, respectively. The glmS ribozyme mutant M5 ( glmS ribozyme cleavage site AG → GG) with decreased ribozyme activity is integrated at the 5'- of glucose-6-phosphate isomerase gene to increase the flux dynamically toward the GlcNAc synthesis pathway. This strategy increased the GlcNAc titer from 9.24 to 18.45 g/L, and the specific GlcNAc productivity from 0.53 to 1.21 g GlcNAc/g cell. Since GlcN6P is involved in the biosynthesis of various products, here the developed strategy for multiple target dynamic engineering of metabolic pathways can be generally used in B. subtilis and other industrial microbes for chemical production.

Synthetic redesign of central carbon and redox metabolism for high yield production of N-acetylglucosamine in Bacillus subtilis

One of the primary goals of microbial metabolic engineering is to achieve high titer, yield and productivity (TYP) of engineered strains. This TYP index requires optimized carbon flux toward desired molecule with minimal by-product formation. De novo redesign of central carbon and redox metabolism holds great promise to alleviate pathway bottleneck and improve carbon and energy utilization efficiency. The engineered strain, with the overexpression or deletion of multiple genes, typically can't meet the TYP index, due to overflow of central carbon and redox metabolism that compromise the final yield, despite a high titer or productivity might be achieved. To solve this challenge, we reprogramed the central carbon and redox metabolism of Bacillus subtilis and achieved high TYP production of N-acetylglucosamine. Specifically, a "push-pull-promote" approach efficiently reduced the overflown acetyl-CoA flux and eliminated byproduct formation. Four synthetic NAD(P)-independent metabolic routes were introduced to rewire the redox metabolism to minimize energy loss. Implementation of these genetic strategies led us to obtain a B. subtilis strain with superior TYP index. GlcNAc titer in shake flask was increased from 6.6 g L^-1 to 24.5 g L^-1, the yield was improved from 0.115 to 0.468 g GlcNAc g^-1 glucose, and the productivity was increased from 0.274 to 0.437 g L^-1 h^-1. These titer and yield are the highest levels ever reported and, the yield reached 98% of the theoretical pathway yield (0.478 g g^-1 glucose). The synthetic redesign of carbon metabolism and redox metabolism represent a novel and general metabolic engineering strategy to improve the performance of microbial cell factories.

Systems and Synthetic Biology Approaches to Engineer Fungi for Fine Chemical Production

Since the advent of systems and synthetic biology, many studies have sought to harness microbes as cell factories through genetic and metabolic engineering approaches. Yeast and filamentous fungi have been successfully harnessed to produce fine and high value-added chemical products. In this review, we present some of the most promising advances from recent years in the use of fungi for this purpose, focusing on the manipulation of fungal strains using systems and synthetic biology tools to improve metabolic flow and the flow of secondary metabolites by pathway redesign. We also review the roles of bioinformatics analysis and predictions in synthetic circuits, highlighting in silico systemic approaches to improve the efficiency of synthetic modules.

Controlling and exploiting cell-to-cell variation in metabolic engineering

Individual cells within a population can display diverse phenotypes due to differences in their local environment, genetic variation, and stochastic expression of genes. Understanding this cell-to-cell variation is important for metabolic engineering applications because variability can impact production. For instance, recent studies have shown that production can be highly heterogeneous among engineered cells, and strategies that manage this diversity improve yields of biosynthetic products. These results suggest the potential of controlling variation as a novel approach towards improving performance of engineered cells. In this review, we focus on identifying the origins of cell-to-cell variation in metabolic engineering applications and discuss recent developments on strategies that can be employed to diminish, accept, or even exploit cell-to-cell variation.

Dynamic decoupling of biomass and wax ester biosynthesis in Acinetobacter baylyi by an autonomously regulated switch

For improving the microbial production of fuels and chemicals, gene knock-outs and overexpression are routinely applied to intensify the carbon flow from substrate to product. However, their possibilities in dynamic control of the flux between the biomass and product synthesis are limited, whereas dynamic metabolic switches can be used for optimizing the distribution of carbon and resources. The production of single cell oils is especially challenging, as the synthesis is strictly regulated, competes directly with biomass, and requires defined conditions, such as nitrogen limitation. Here, we engineered a metabolic switch for redirecting carbon flow from biomass to wax ester production in Acinetobacter baylyi ADP1 using acetate as a carbon source. Isocitrate lyase, an essential enzyme for growth on acetate, was expressed under an arabinose inducible promoter. The autonomous downregulation of the expression is based on the gradual oxidation of the arabinose inducer by a glucose dehydrogenase gcd. The depletion of the inducer, occurring simultaneously to acetate consumption, switches the cells from a biomass mode to a lipid synthesis mode, enabling the efficient channelling of carbon to wax esters in a simple batch culture. In the engineered strain, the yield and titer of wax esters were improved by 3.8 and 3.1 folds, respectively, over the control strain. In addition, the engineered strain accumulated wax esters 19% of cell dry weight, being the highest reported among microbes. The study provides important insights into the dynamic engineering of the biomass-dependent synthesis pathways for the improved production of biocompounds from low-cost and sustainable substrates.

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Efficient conversion of acetate to storage lipids (wax ester) is demonstrated.

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AraC-pBAD promoter coupled with glucose dehydrogenase was used as a dynamic switch.

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The autonomous switch allowed dynamic shift from biomass to lipid synthesis mode.

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Wax ester yield and titer were improved by 3–4 folds over the wild type strain.

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The highest amount of wax esters produced in microbes, 19% of CDW, was achieved.

Repurposing type III polyketide synthase as a malonyl-CoA biosensor for metabolic engineering in bacteria

Malonyl-CoA is an important central metabolite for the production of diverse valuable chemicals including natural products, but its intracellular availability is often limited due to the competition with essential cellular metabolism. Several malonyl-CoA biosensors have been developed for high-throughput screening of targets increasing the malonyl-CoA pool. However, they are limited for use only in Escherichia coli and Saccharomyces cerevisiae and require multiple signal transduction steps. Here we report development of a colorimetric malonyl-CoA biosensor applicable in three industrially important bacteria: E. coli, Pseudomonas putida, and Corynebacterium glutamicum RppA, a type III polyketide synthase producing red-colored flaviolin, was repurposed as a malonyl-CoA biosensor in E. coli Strains with enhanced malonyl-CoA accumulation were identifiable by the colorimetric screening of cells showing increased red color. Other type III polyketide synthases could also be repurposed as malonyl-CoA biosensors. For target screening, a 1,858 synthetic small regulatory RNA library was constructed and applied to find 14 knockdown gene targets that generally enhanced malonyl-CoA level in E. coli These knockdown targets were applied to produce two polyketide (6-methylsalicylic acid and aloesone) and two phenylpropanoid (resveratrol and naringenin) compounds. Knocking down these genes alone or in combination, and also in multiple different E. coli strains for two polyketide cases, allowed rapid development of engineered strains capable of enhanced production of 6-methylsalicylic acid, aloesone, resveratrol, and naringenin to 440.3, 30.9, 51.8, and 103.8 mg/L, respectively. The malonyl-CoA biosensor developed here is a simple tool generally applicable to metabolic engineering of microorganisms to achieve enhanced production of malonyl-CoA-derived chemicals.

Metabolic engineering for the production of chitooligosaccharides: advances and perspectives

Chitin oligosaccharides (CTOs) and its related compounds chitosan oligosaccharides (CSOs), collectively known as chitooligosaccharides (COs), exhibit numerous biological activities in applications in the nutraceutical, cosmetics, agriculture, and pharmaceutical industries. COs are currently produced by acid hydrolysis of chitin or chitosan, or enzymatic techniques with uncontrollable polymerization. Microbial fermentation by recombinant Escherichia coli, as an alternative method for the production of COs, shows new potential because it can produce a well-defined COs mixture and is an environmentally friendly process. In addition, Bacillus subtilis, a nonpathogenic, endotoxin-free, GRAS status bacterium, presents a new opportunity as a platform to produce COs. Here, we review the applications of COs and differences between CTOs and CSOs, summarize the current preparation approaches of COs, and discuss the future research potentials and challenges in the production of well-defined COs in B. subtilis by metabolic engineering.

Building a minimal and generalizable model of transcription factor-based biosensors: Showcasing flavonoids

Progress in synthetic biology tools has transformed the way we engineer living cells. Applications of circuit design have reached a new level, offering solutions for metabolic engineering challenges that include developing screening approaches for libraries of pathway variants. The use of transcription-factor-based biosensors for screening has shown promising results, but the quantitative relationship between the sensors and the sensed molecules still needs more rational understanding. Herein, we have successfully developed a novel biosensor to detect pinocembrin based on a transcriptional regulator. The FdeR transcription factor (TF), known to respond to naringenin, was combined with a fluorescent reporter protein. By varying the copy number of its plasmid and the concentration of the biosensor TF through a combinatorial library, different responses have been recorded and modeled. The fitted model provides a tool to understand the impact of these parameters on the biosensor behavior in terms of dose-response and time curves and offers guidelines to build constructs oriented to increased sensitivity and or ability of linear detection at higher titers. Our model, the first to explicitly take into account the impact of plasmid copy number on biosensor sensitivity using Hill-based formalism, is able to explain uncharacterized systems without extensive knowledge of the properties of the TF. Moreover, it can be used to model the response of the biosensor to different compounds (here naringenin and pinocembrin) with minimal parameter refitting.

Sensor-regulator and RNAi based bifunctional dynamic control network for engineered microbial synthesis

Writing artificial logic and dynamic function into complex cellular background to achieve desired phenotypes or improved outputs calls for the development of new genetic tools as well as their innovative use. In this study, we present a sensor-regulator and RNAi-based bifunctional dynamic control network that can provide simultaneous upregulation and downregulation of cellular metabolism for engineered biosynthesis. The promoter-regulator-mediated upregulation function and its transduced downregulation function through RNAi are systematically verified and characterized. We apply this dynamic control network to regulate the phosphoenolpyruvate metabolic node in Escherichia coli and achieve autonomous distribution of carbon flux between its native metabolism and the engineered muconic acid biosynthetic pathway. This allows muconic acid biosynthesis to reach 1.8 g L⁻¹. This study also suggests the circumstances where dynamic control approaches are likely to take effects.

Engineering dynamic control can improve microbial production of target chemicals. Here, the authors design a sensor-regulator and RNAi based bifunctional dynamic control network that can simultaneously and independently turn up and down cellular metabolism for engineered muconic acid production in E. coli.

Advances in bio-based production of dicarboxylic acids longer than C4

Growing concerns of environmental pollution and fossil resource shortage are major driving forces for bio-based production of chemicals traditionally from petrochemical industry. Dicarboxylic acids (DCAs) are important platform chemicals with large market and wide applications, and here the recent advances in bio-based production of straight-chain DCAs longer than C4 from biological approaches, especially by synthetic biology, are reviewed. A couple of pathways were recently designed and demonstrated for producing DCAs, even those ranging from C5 to C15, by employing respective starting units, extending units, and appropriate enzymes. Furthermore, in order to achieve higher production of DCAs, enormous efforts were made in engineering microbial hosts that harbored the biosynthetic pathways and in improving properties of biocatalytic elements to enhance metabolic fluxes toward target DCAs. Here we summarize and discuss the current advantages and limitations of related pathways, and also provide perspectives on synthetic pathway design and optimization for hyper-production of DCAs.

In vivo biosensors: mechanisms, development, and applications

In vivo biosensors can recognize and respond to specific cellular stimuli. In recent years, biosensors have been increasingly used in metabolic engineering and synthetic biology, because they can be implemented in synthetic circuits to control the expression of reporter genes in response to specific cellular stimuli, such as a certain metabolite or a change in pH. There are many types of natural sensing devices, which can be generally divided into two main categories: protein-based and nucleic acid-based. Both can be obtained either by directly mining from natural genetic components or by engineering the existing genetic components for novel specificity or improved characteristics. A wide range of new technologies have enabled rapid engineering and discovery of new biosensors, which are paving the way for a new era of biotechnological progress. Here, we review recent advances in the design, optimization, and applications of in vivo biosensors in the field of metabolic engineering and synthetic biology.

Dynamic metabolic control: towards precision engineering of metabolism

Advances in metabolic engineering have led to the synthesis of a wide variety of valuable chemicals in microorganisms. The key to commercializing these processes is the improvement of titer, productivity, yield, and robustness. Traditional approaches to enhancing production use the “push–pull-block” strategy that modulates enzyme expression under static control. However, strains are often optimized for specific laboratory set-up and are sensitive to environmental fluctuations. Exposure to sub-optimal growth conditions during large-scale fermentation often reduces their production capacity. Moreover, static control of engineered pathways may imbalance cofactors or cause the accumulation of toxic intermediates, which imposes burden on the host and results in decreased production. To overcome these problems, the last decade has witnessed the emergence of a new technology that uses synthetic regulation to control heterologous pathways dynamically, in ways akin to regulatory networks found in nature. Here, we review natural metabolic control strategies and recent developments in how they inspire the engineering of dynamically regulated pathways. We further discuss the challenges of designing and engineering dynamic control and highlight how model-based design can provide a powerful formalism to engineer dynamic control circuits, which together with the tools of synthetic biology, can work to enhance microbial production.

Spatially organizing biochemistry: choosing a strategy to translate synthetic biology to the factory

Natural biochemical systems are ubiquitously organized both in space and time. Engineering the spatial organization of biochemistry has emerged as a key theme of synthetic biology, with numerous technologies promising improved biosynthetic pathway performance. One strategy, however, may produce disparate results for different biosynthetic pathways. We use a spatially resolved kinetic model to explore this fundamental design choice in systems and synthetic biology. We predict that two example biosynthetic pathways have distinct optimal organization strategies that vary based on pathway-dependent and cell-extrinsic factors. Moreover, we demonstrate that the optimal design varies as a function of kinetic and biophysical properties, as well as culture conditions. Our results suggest that organizing biosynthesis has the potential to substantially improve performance, but that choosing the appropriate strategy is key. The flexible design-space analysis we propose can be adapted to diverse biosynthetic pathways, and lays a foundation to rationally choose organization strategies for biosynthesis.

Lighting up yeast cell factories by transcription factor-based biosensors

Our ability to rewire cellular metabolism for the sustainable production of chemicals, fuels and therapeutics based on microbial cell factories has advanced rapidly during the last two decades. Especially the speed and precision by which microbial genomes can be engineered now allow for more advanced designs to be implemented and tested. However, compared to the methods developed for engineering cell factories, the methods developed for testing the performance of newly engineered cell factories in high throughput are lagging far behind, which consequently impacts the overall biomanufacturing process. For this purpose, there is a need to develop new techniques for screening and selection of best-performing cell factory designs in multiplex. Here we review the current status of the sourcing, design and engineering of biosensors derived from allosterically regulated transcription factors applied to the biotechnology work-horse budding yeast Saccharomyces cerevisiae. We conclude by providing a perspective on the most important challenges and opportunities lying ahead in order to harness the full potential of biosensor development for increasing both the throughput of cell factory development and robustness of overall bioprocesses.

Sortase A-Assisted Metabolic Enzyme Ligation in Escherichia coli for Enhancing Metabolic Flux

Metabolic engineering has been an important approach for microbial bio-production. To produce bio-chemicals with engineered microorganisms, metabolic pathways have been edited using several common strategies, including gene disruption, gene overexpression, and gene attenuation. Here, we demonstrated metabolic channeling based on enzymatic metabolic enzyme ligation as a noteworthy approach for enhancing a desired metabolic flux. To achieve metabolic channeling , the metabolic enzymes should be in close proximity in cells. In the literature, several methodologies have been recently applied to achieve metabolic channeling . Meanwhile, we have proposed a strategy for possessing metabolic enzymes in close proximity, by utilizing sortase A as a stapler to tether such enzymes in Escherichia coli. By tethering metabolic enzymes that catalyze the reactions before and after a target metabolite, the metabolic flux may be enhanced. This chapter describes the approach for enhancing acetate-producing flux by sortase-A-assisted metabolic ligation in E. coli.

CRISPR interference-mediated metabolic engineering of Corynebacterium glutamicum for homo-butyrate production

Combinatorial metabolic engineering enabled the development of efficient microbial cell factories for modulating gene expression to produce desired products. Here, we report the combinatorial metabolic engineering of Corynebacterium glutamicum to produce butyrate by introducing a synthetic butyrate pathway including phosphotransferase and butyrate kinase reactions and repressing the essential acn gene-encoding aconitase, which has been targeted for downregulation in a genome-scale model. An all-in-one clustered regularly interspaced short palindromic repeats interference system for C. glutamicum was used for tunable downregulation of acn in an engineered strain, where by-product-forming reactions were deleted and the synthetic butyrate pathway was inserted, resulting in butyrate production (0.52 ± 0.02 g/L). Subsequently, biotin limitation enabled the engineered strain to produce butyrate (0.58 ± 0.01 g/L) without acetate formation for the entire duration of the culture. These results demonstrate the potential homo-production of butyrate using engineered C. glutamicum. This method can also be applied to other industrial microorganisms.

Applications of CRISPR/Cas System to Bacterial Metabolic Engineering

The clustered regularly interspaced short palindromic repeats/CRISPR-associated (CRISPR/Cas) adaptive immune system has been extensively used for gene editing, including gene deletion, insertion, and replacement in bacterial and eukaryotic cells owing to its simple, rapid, and efficient activities in unprecedented resolution. Furthermore, the CRISPR interference (CRISPRi) system including deactivated Cas9 (dCas9) with inactivated endonuclease activity has been further investigated for regulation of the target gene transiently or constitutively, avoiding cell death by disruption of genome. This review discusses the applications of CRISPR/Cas for genome editing in various bacterial systems and their applications. In particular, CRISPR technology has been used for the production of metabolites of high industrial significance, including biochemical, biofuel, and pharmaceutical products/precursors in bacteria. Here, we focus on methods to increase the productivity and yield/titer scan by controlling metabolic flux through individual or combinatorial use of CRISPR/Cas and CRISPRi systems with introduction of synthetic pathway in industrially common bacteria including Escherichia coli. Further, we discuss additional useful applications of the CRISPR/Cas system, including its use in functional genomics.

Layered dynamic regulation for improving metabolic pathway productivity in Escherichia coli

Microbial production of value-added chemicals from biomass is a sustainable alternative to chemical synthesis. To improve product titer, yield, and selectivity, the pathways engineered into microbes must be optimized. One strategy for optimization is dynamic pathway regulation, which modulates expression of pathway-relevant enzymes over the course of fermentation. Metabolic engineers have used dynamic regulation to redirect endogenous flux toward product formation, balance the production and consumption rates of key intermediates, and suppress production of toxic intermediates until later in the fermentation. Most cases, however, have utilized a single strategy for dynamically regulating pathway fluxes. Here we layer two orthogonal, autonomous, and tunable dynamic regulation strategies to independently modulate expression of two different enzymes to improve production of D-glucaric acid from a heterologous pathway. The first strategy uses a previously described pathway-independent quorum sensing system to dynamically knock down glycolytic flux and redirect carbon into production of glucaric acid, thereby switching cells from "growth" to "production" mode. The second strategy, developed in this work, uses a biosensor for myo-inositol (MI), an intermediate in the glucaric acid production pathway, to induce expression of a downstream enzyme upon sufficient buildup of MI. The latter, pathway-dependent strategy leads to a 2.5-fold increase in titer when used in isolation and a fourfold increase when added to a strain employing the former, pathway-independent regulatory system. The dual-regulation strain produces nearly 2 g/L glucaric acid, representing the highest glucaric acid titer reported to date in Escherichia coli K-12 strains.

Biosynthesis of nervonic acid and perspectives for its production by microalgae and other microorganisms

Nervonic acid (NA) is a major very long-chain monounsaturated fatty acid found in the white matter of mammalian brains, which plays a critical role in the treatment of psychotic disorders and neurological development. In the nature, NA has been synthesized by a handful plants, fungi, and microalgae. Although the metabolism of fatty acid has been studied for decades, the biosynthesis of NA has yet to be illustrated. Generally, the biosynthesis of NA is considered starting from oleic acid through fatty acid elongation, in which malonyl-CoA and long-chain acyl-CoA are firstly condensed by a rate-limiting enzyme 3-ketoacyl-CoA synthase (KCS). Heterologous expression of kcs gene from high NA producing species in plants and yeast has led to synthesis of NA. Nevertheless, it has also been reported that desaturases in a few plants can catalyze very long-chain saturated fatty acid into NA. This review highlights recent advances in the biosynthesis, the sources, and the biotechnological aspects of NA.

Metabolic Feedback Circuits Provide Rapid Control of Metabolite Dynamics

Metabolism constitutes the basis of life, and the dynamics of metabolism dictate various cellular processes. However, exactly how metabolite dynamics are controlled remains poorly understood. By studying an engineered fatty acid-producing pathway as a model, we found that upon transcription activation a metabolic product from an unregulated pathway required seven cell cycles to reach to its steady state level, with the speed mostly limited by enzyme expression dynamics. To overcome this limit, we designed metabolic feedback circuits (MeFCs) with three different architectures, and experimentally measured and modeled their metabolite dynamics. Our engineered MeFCs could dramatically shorten the rise-time of metabolites, decreasing it by as much as 12-fold. The findings of this study provide a systematic understanding of metabolite dynamics in different architectures of MeFCs and have potentially immense applications in designing synthetic circuits to improve the productivities of engineered metabolic pathways.

Design and Selection of a Synthetic Feedback Loop for Optimizing Biofuel Tolerance

Feedback control allows cells to dynamically sense and respond to environmental changes. However, synthetic controller designs can be challenging because of implementation issues, such as determining optimal expression levels for circuit components within a feedback loop. Here, we addressed this by coupling rational design with selection to engineer a synthetic feedback circuit to optimize tolerance of Escherichia coli to the biojet fuel pinene. E. coli can be engineered to produce pinene, but it is toxic to cells. Efflux pumps, such as the AcrAB-TolC pump, can improve tolerance, but pump expression impacts growth. To address this, we used feedback to dynamically regulate pump expression in response to stress. We developed a library with thousands of synthetic circuit variants and subjected it to three types of pinene treatment (none, constant, and varying pinene). We were able to select for strains that were biofuel tolerant without a significant growth cost in the absence of biofuel. Using next-generation sequencing, we found common characteristics in the designs and identified controllers that dramatically improved biofuel tolerance.

A Prototype for Modular Cell Engineering

When aiming to produce a target chemical at high yield, titer, and productivity, various combinations of genetic parts available to build the target pathway can generate a large number of strains for characterization. This engineering approach will become increasingly laborious and expensive when seeking to develop desirable strains for optimal production of a large space of biochemicals due to extensive screening. Our recent theoretical development of modular cell (MODCELL) design principles can offer a promising solution for rapid generation of optimal strains by coupling a modular cell with exchangeable production modules in a plug-and-play fashion. In this study, we experimentally validated some design properties of MODCELL by demonstrating the following: (i) a modular (chassis) cell is required to couple with a production module, a heterologous ethanol pathway, as a testbed, (ii) degree of coupling between the modular cell and production modules can be modulated to enhance growth and product synthesis, (iii) a modular cell can be used as a host to select an optimal pyruvate decarboxylase (PDC) of the ethanol production module and to help identify a hypothetical PDC protein, and (iv) adaptive laboratory evolution based on growth selection of the modular cell can enhance growth and product synthesis rates. We envision that the MODCELL design provides a powerful prototype for modular cell engineering to rapidly create optimal strains for synthesis of a large space of biochemicals.

Synthetic biology strategies toward heterologous phytochemical production

This review summarizes the recent progress in heterologous phytochemical biosynthetic pathway reconstitution in plant, bacteria, and yeast, with a focus on the synthetic biology strategies applied in these engineering efforts.

An Automated Pipeline for Engineering Many-Enzyme Pathways: Computational Sequence Design, Pathway Expression-Flux Mapping, and Scalable Pathway Optimization

Engineering many-enzyme metabolic pathways suffers from the design curse of dimensionality. There are an astronomical number of synonymous DNA sequence choices, though relatively few will express an evolutionary robust, maximally productive pathway without metabolic bottlenecks. To solve this challenge, we have developed an integrated, automated computational-experimental pipeline that identifies a pathway's optimal DNA sequence without high-throughput screening or many cycles of design-build-test. The first step applies our Operon Calculator algorithm to design a host-specific evolutionary robust bacterial operon sequence with maximally tunable enzyme expression levels. The second step applies our RBS Library Calculator algorithm to systematically vary enzyme expression levels with the smallest-sized library. After characterizing a small number of constructed pathway variants, measurements are supplied to our Pathway Map Calculator algorithm, which then parameterizes a kinetic metabolic model that ultimately predicts the pathway's optimal enzyme expression levels and DNA sequences. Altogether, our algorithms provide the ability to efficiently map the pathway's sequence-expression-activity space and predict DNA sequences with desired metabolic fluxes. Here, we provide a step-by-step guide to applying the Pathway Optimization Pipeline on a desired multi-enzyme pathway in a bacterial host.

Increasing Extracellular Free Fatty Acid Production in Escherichia coli by Disrupting Membrane Transport Systems

Transposon mutagenesis was used to identify three mutants of E. coli that exhibited increased free fatty acid (FFA) production, which resulted from the disruption of genes related to membrane transport. Deletion of envR, gusC, and mdlA individually in a recombinant E. coli strain resulted in 1.4-, 1.8-, and 1.2-fold increases in total FFA production, respectively. In particular, deletion of envR increased the percentage of extracellular FFA to 46%, compared with 29% for the control strain. Multiple deletion of envR, gusC, mdlA, ompF, and fadL had a synergistic effect on FFA production, resulting in high extracellular FFA production, comprising up to 50% of total FFA production. This study has identified new membrane proteins involved in FFA production and showed that genetic engineering targeting these membrane transporters is important to increase both total FFA and extracellular FFA production.

Steps towards 'drop-in' biofuels: focusing on metabolic pathways

The past decade has witnessed rapid advance in microbial production of 'drop-in' biofuels from renewable resources. Various biosynthetic pathways have been constructed to produce biofuels with diverse structures, and multiple metabolic engineering strategies have been developed to increase biofuel titers, yields, productivities and system robustness. In this review, we intend to give a brief but comprehensive overview of the most recent progresses on four essential pathways leading to 'drop-in' biofuel production, with an emphasis on the metabolic pathway efficiencies and biofuel structures. Furthermore, we also provide an insightful discussion on optimization strategies to improve the robustness of the microbial platforms for biofuel production.

YaliBricks, a versatile genetic toolkit for streamlined and rapid pathway engineering in Yarrowia lipolytica

Effective metabolic engineering of microorganisms relies on balanced expression of both heterologous and endogenous genes to channel metabolic flux towards products of interest while achieving reasonable biomass buildup. To facilitate combinatorial pathway engineering and facile genetic operation, we engineered a set of modular cloning vectors compatible with BioBrick standards, called YaliBricks, to allow for rapid assembly of multigene pathways with customized genetic control elements (promoters, intronic sequences and terminators) in the oleaginous yeast Yarrowia lipolytica. We established a sensitive luciferase reporter and characterized a set of 12 native promoters to expand the oleaginous yeast genetic toolbox for transcriptional fine-tuning. We harnessed the intron alternative splicing mechanism and explored three unique gene configurations that allow us to encode genetic structural variations into metabolic function. We elucidated the role of how these genetic structural variations affect gene expression. To demonstrate the simplicity and effectiveness of streamlined genetic operations, we assembled the 12 kb five-gene violacein biosynthetic pathway in one week. We also expanded this set of vectors to accommodate self-cleavage ribozymes and efficiently deliver guide RNA (gRNA) for targeted genome-editing with a codon-optimized CRISPR-Cas9 nuclease. Taken together, the tools built in this study provide a standard procedure to streamline and accelerate metabolic pathway engineering and genetic circuits construction in Yarrowia lipolytica.

Metabolic Engineering of Oleaginous Yeasts for Production of Fuels and Chemicals

Oleaginous yeasts have been increasingly explored for production of chemicals and fuels via metabolic engineering. Particularly, there is a growing interest in using oleaginous yeasts for the synthesis of lipid-related products due to their high lipogenesis capability, robustness, and ability to utilize a variety of substrates. Most of the metabolic engineering studies in oleaginous yeasts focused on Yarrowia that already has plenty of genetic engineering tools. However, recent advances in systems biology and synthetic biology have provided new strategies and tools to engineer those oleaginous yeasts that have naturally high lipid accumulation but lack genetic tools, such as Rhodosporidium, Trichosporon, and Lipomyces. This review highlights recent accomplishments in metabolic engineering of oleaginous yeasts and recent advances in the development of genetic engineering tools in oleaginous yeasts within the last 3 years.

A metabolic engineering strategy for producing free fatty acids by the Yarrowia lipolytica yeast based on impairment of glycerol metabolism

In recent years, bio-based production of free fatty acids from renewable resources has attracted attention for their potential as precursors for the production of biofuels and biochemicals. In this study, the oleaginous yeast Yarrowia lipolytica was engineered to produce free fatty acids by eliminating glycerol metabolism. Free fatty acid production was monitored under lipogenic conditions with glycerol as a limiting factor. Firstly, the strain W29 (Δgpd1), which is deficient in glycerol synthesis, was obtained. However, W29 (Δgpd1) showed decreased biomass accumulation and glucose consumption in lipogenic medium containing a limiting supply of glycerol. Analysis of substrate utilization from a mixture of glucose and glycerol by the parental strain W29 revealed that glycerol was metabolized first and glucose utilization was suppressed. Thus, the Δgpd1Δgut2 double mutant, which is deficient also in glycerol catabolism, was constructed. In this genetic background, growth was repressed by glycerol. Oleate toxicity was observed in the Δgpd1Δgut2Δpex10 triple mutant strain which is deficient additionally in peroxisome biogenesis. Consequently, two consecutive rounds of selection of spontaneous mutants were performed. A mutant released from growth repression by glycerol was able to produce 136.8 mg L^-1 of free fatty acids in a test tube, whereas the wild type accumulated only 30.2 mg L^-1 . Next, an isolated oleate-resistant strain produced 382.8 mg L^-1 of free fatty acids. Finely, acyl-CoA carboxylase gene (ACC1) over-expression resulted to production of 1436.7 mg L^-1 of free fatty acids. The addition of dodecane promoted free fatty acid secretion and enhanced the level of free fatty acids up to 2033.8 mg L^-1 during test tube cultivation.

Biosensor-aided high-throughput screening of hyper-producing cells for malonyl-CoA-derived products

Background

Malonyl-coenzyme A (CoA) is an important biosynthetic precursor in vivo. Although Escherichia coli is a useful organism for biosynthetic applications, its malonyl-CoA level is too low.

Results

To identify strains with the best potential for enhanced malonyl-CoA production, we developed a whole-cell biosensor for rapidly reporting intracellular malonyl-CoA concentrations. The biosensor was successfully applied as a high-throughput screening tool for identifying targets at a genome-wide scale that could be critical for improving the malonyl-CoA biosynthesis in vivo. The mutant strains selected synthesized significantly higher titers of the type III polyketide triacetic acid lactone (TAL), phloroglucinol, and free fatty acids compared to the wild-type strain, using malonyl-CoA as a precursor.

Conclusion

These results validated this novel whole-cell biosensor as a rapid and sensitive malonyl-CoA high-throughput screening tool. Further analysis of the mutant strains showed that the iron ion concentration is closely related to the intracellular malonyl-CoA biosynthesis.

Electronic supplementary material

The online version of this article (10.1186/s12934-017-0794-6) contains supplementary material, which is available to authorized users.

Engineering microbial fatty acid metabolism for biofuels and biochemicals

Traditional oleochemical industry chemically processes animal fats and plant oils to produce detergents, lubricants, biodiesel, plastics, coatings, and other products. Biotechnology offers an alternative process, where the same oleochemicals can be produced from abundant biomass feedstocks using microbial catalysis. This review summarizes the recent advances in the engineering of microbial metabolism for production of fatty acid-derived products. We highlight the efforts in engineering the central carbon metabolism, redox metabolism, controlling the chain length of the products, and obtaining metabolites with different functionalities. The prospects of commercializing microbial oleochemicals are also discussed.

Production of anthocyanins in metabolically engineered microorganisms: Current status and perspectives

Microbial production of plant-derived natural products by engineered microorganisms has achieved great success thanks to large extend to metabolic engineering and synthetic biology. Anthocyanins, the water-soluble colored pigments found in terrestrial plants that are responsible for the red, blue and purple coloration of many flowers and fruits, are extensively used in food and cosmetics industry; however, their current supply heavily relies on complex extraction from plant-based materials. A promising alternative is their sustainable production in metabolically engineered microbes. Here, we review the recent progress on anthocyanin biosynthesis in engineered bacteria, with a special focus on the systematic engineering modifications such as selection and engineering of biosynthetic enzymes, engineering of transportation, regulation of UDP-glucose supply, as well as process optimization. These promising engineering strategies will facilitate successful microbial production of anthocyanins in industry in the near future.

Design and application of genetically-encoded malonyl-CoA biosensors for metabolic engineering of microbial cell factories

Malonyl-CoA is the basic building block for synthesizing a range of important compounds including fatty acids, phenylpropanoids, flavonoids and non-ribosomal polyketides. Centering around malonyl-CoA, we summarized here the various metabolic engineering strategies employed recently to regulate and control malonyl-CoA metabolism and improve cellular productivity. Effective metabolic engineering of microorganisms requires the introduction of heterologous pathways and dynamically rerouting metabolic flux towards products of interest. Transcriptional factor-based biosensors translate an internal cellular signal to a transcriptional output and drive the expression of the designed genetic/biomolecular circuits to compensate the activity loss of the engineered biosystem. Recent development of genetically-encoded malonyl-CoA sensor has stood out as a classical example to dynamically reprogram cell metabolism for various biotechnological applications. Here, we reviewed the design principles of constructing a transcriptional factor-based malonyl-CoA sensor with superior detection limit, high sensitivity and broad dynamic range. We discussed various synthetic biology strategies to remove pathway bottleneck and how genetically-encoded metabolite sensor could be deployed to improve pathway efficiency. Particularly, we emphasized that integration of malonyl-CoA sensing capability with biocatalytic function would be critical to engineer efficient microbial cell factory. Biosensors have also advanced beyond its classical function of a sensor actuator for in situ monitoring of intracellular metabolite concentration. Applications of malonyl-CoA biosensors as a sensor-invertor for negative feedback regulation of metabolic flux, a metabolic switch for oscillatory balancing of malonyl-CoA sink pathway and source pathway and a screening tool for engineering more efficient biocatalyst are also presented in this review. We envision the genetically-encoded malonyl-CoA sensor will be an indispensable tool to optimize cell metabolism and cost-competitively manufacture malonyl-CoA-derived compounds.

Development of Chemical and Metabolite Sensors for Rhodococcus opacus PD630

Rhodococcus opacus PD630 is a nonmodel, Gram-positive bacterium that possesses desirable traits for biomass conversion, including consumption capabilities for lignocellulose-based sugars and toxic lignin-derived aromatic compounds, significant triacylglycerol accumulation, relatively rapid growth rate, and genetic tractability. However, few genetic elements have been directly characterized in R. opacus, limiting its application for lignocellulose bioconversion. Here, we report the characterization and development of genetic tools for tunable gene expression in R. opacus, including: (1) six fluorescent reporters for quantifying promoter output, (2) three chemically inducible promoters for variable gene expression, and (3) two classes of metabolite sensors derived from native R. opacus promoters that detect nitrogen levels or aromatic compounds. Using these tools, we also provide insights into native aromatic consumption pathways in R. opacus. Overall, this work expands the ability to control and characterize gene expression in R. opacus for future lignocellulose-based fuel and chemical production.

Fundamental Design Principles for Transcription-Factor-Based Metabolite Biosensors

Metabolite biosensors are central to current efforts toward precision engineering of metabolism. Although most research has focused on building new biosensors, their tunability remains poorly understood and is fundamental for their broad applicability. Here we asked how genetic modifications shape the dose-response curve of biosensors based on metabolite-responsive transcription factors. Using the lac system in Escherichia coli as a model system, we built promoter libraries with variable operator sites that reveal interdependencies between biosensor dynamic range and response threshold. We developed a phenomenological theory to quantify such design constraints in biosensors with various architectures and tunable parameters. Our theory reveals a maximal achievable dynamic range and exposes tunable parameters for orthogonal control of dynamic range and response threshold. Our work sheds light on fundamental limits of synthetic biology designs and provides quantitative guidelines for biosensor design in applications such as dynamic pathway control, strain optimization, and real-time monitoring of metabolism.

Dynamic pathway regulation: recent advances and methods of construction

Microbial cell factories are a renewable source for the production of biofuels and valuable chemicals. Dynamic pathway regulation has proved successful in improving production of molecules by balancing flux between growth of cells and production of metabolites. Systems for autonomous induction of pathway regulation are increasingly being developed, which include metabolite responsive promoters, biosensors, and quorum sensing systems. Since engineering such systems are dependent on the available methods for controlling protein abundance in the desired host, we review recent tools used for gene repression at the transcriptional, post-transcriptional and post-translational levels in Escherichia coli and Saccharomyces cerevisiae. These approaches may facilitate pathway engineering for biofuel and biochemical production.

Enabling Graded and Large-Scale Multiplex of Desired Genes Using a Dual-Mode dCas9 Activator in Saccharomyces cerevisiae

Standard approaches for dCas9-based modification of gene expression are limited in the ability to multiplex targets, establish streamlined cassettes, and utilize commonly studied Pol II promoters. In this work, we repurpose the dCas9-VPR activator to act as a dual-mode activator/repressor that can be programmed solely on the basis of target position at gene loci. Furthermore, we implement this approach using a streamlined Pol II-ribozyme system that allows expression of many sgRNAs from a single transcript. By "stepping" dCas9-VPR within the promoter region and ORF we create graded activation and repression (respectively) of target genes, allowing precise control over multiplexed gene modulation. Expression from the Pol II system increased the net amount of sgRNA production in cells by 3.88-fold relative to the Pol III SNR52 promoter, leading to a significant improvement in dCas9-VPR repression strength. Finally, we utilize our Pol II system to create galactose-inducible switching of gene expression states and multiplex constructs capable of modulating up to 4 native genes from a single vector. Our approach represents a significant step toward minimizing DNA required to assemble CRISPR systems in eukaryotes while enhancing the efficacy (greater repression strength), scale (more sgRNAs), and scope (inducibility) of dCas9-mediated gene regulation.

Rapid evolution of regulatory element libraries for tunable transcriptional and translational control of gene expression

Engineering cell factories for producing biofuels and pharmaceuticals has spurred great interests to develop rapid and efficient synthetic biology tools customized for modular pathway engineering. Along the way, combinatorial gene expression control through modification of regulatory element offered tremendous opportunity for fine-tuning gene expression and generating digital-like genetic circuits. In this report, we present an efficient evolutionary approach to build a range of regulatory control elements. The reported method allows for rapid construction of promoter, 5'UTR, terminator and trans-activating RNA libraries. Synthetic overlapping oligos with high portion of degenerate nucleotides flanking the regulatory element could be efficiently assembled to a vector expressing fluorescence reporter. This approach combines high mutation rate of the synthetic DNA with the high assembly efficiency of Gibson Mix. Our constructed library demonstrates broad range of transcriptional or translational gene expression dynamics. Specifically, both the promoter library and 5'UTR library exhibits gene expression dynamics spanning across three order of magnitude. The terminator library and trans-activating RNA library displays relatively narrowed gene expression pattern. The reported study provides a versatile toolbox for rapidly constructing a large family of prokaryotic regulatory elements. These libraries also facilitate the implementation of combinatorial pathway engineering principles and the engineering of more efficient microbial cell factory for various biomanufacturing applications.

Design, Optimization and Application of Small Molecule Biosensor in Metabolic Engineering

The development of synthetic biology and metabolic engineering has painted a great future for the bio-based economy, including fuels, chemicals, and drugs produced from renewable feedstocks. With the rapid advance of genome-scale modeling, pathway assembling and genome engineering/editing, our ability to design and generate microbial cell factories with various phenotype becomes almost limitless. However, our lack of ability to measure and exert precise control over metabolite concentration related phenotypes becomes a bottleneck in metabolic engineering. Genetically encoded small molecule biosensors, which provide the means to couple metabolite concentration to measurable or actionable outputs, are highly promising solutions to the bottleneck. Here we review recent advances in the design, optimization and application of small molecule biosensor in metabolic engineering, with particular focus on optimization strategies for transcription factor (TF) based biosensors.