Design of a dynamic sensor-regulator system for production of chemicals and fuels derived from fatty acids

Advances in engineering and optimization of transcription factor-based biosensors for plug-and-play small molecule detection

Transcription factor (TF)-based biosensors have been applied in biotechnology for a variety of functions, including protein engineering, dynamic control, environmental detection, and point-of-care diagnostics. Such biosensors are promising analytical tools due to their wide range of detectable ligands and modular nature. However, designing biosensors tailored for applications of interest with the desired performance parameters, including ligand specificity, remains challenging. Biosensors often require significant engineering and tuning to meet desired specificity, sensitivity, dynamic range, and operating range parameters. Another limitation is the orthogonality of biosensors across hosts, given the role of the cellular context. Here, we describe recent advances and examples in the engineering and optimization of TF-based biosensors for plug-and-play small molecule detection. We highlight novel developments in TF discovery and biosensor design, TF specificity engineering, and biosensor tuning, with emphasis on emerging computational methods.

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

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

Acyl-CoA:diacylglycerol acyltransferase: Properties, physiological roles, metabolic engineering and intentional control

Acyl-CoA:diacylglycerol acyltransferase (DGAT, EC 2.3.1.20) catalyzes the last reaction in the acyl-CoA-dependent biosynthesis of triacylglycerol (TAG). DGAT activity resides mainly in membrane-bound DGAT1 and DGAT2 in eukaryotes and bifunctional wax ester synthase-diacylglycerol acyltransferase (WSD) in bacteria, which are all membrane-bound proteins but exhibit no sequence homology to each other. Recent studies also identified other DGAT enzymes such as the soluble DGAT3 and diacylglycerol acetyltransferase (EaDAcT), as well as enzymes with DGAT activities including defective in cuticular ridges (DCR) and steryl and phytyl ester synthases (PESs). This review comprehensively discusses research advances on DGATs in prokaryotes and eukaryotes with a focus on their biochemical properties, physiological roles, and biotechnological and therapeutic applications. The review begins with a discussion of DGAT assay methods, followed by a systematic discussion of TAG biosynthesis and the properties and physiological role of DGATs. Thereafter, the review discusses the three-dimensional structure and insights into mechanism of action of human DGAT1, and the modeled DGAT1 from Brassica napus. The review then examines metabolic engineering strategies involving manipulation of DGAT, followed by a discussion of its therapeutic applications. DGAT in relation to improvement of livestock traits is also discussed along with DGATs in various other eukaryotic organisms.

Signal Amplification of araC pBAD Using a Standardised Translation Initiation Region

araC pBAD is a genetic fragment that regulates the expression of the araBAD operon in bacteria, which is required for the metabolism of L-arabinose. It is widely used in bioengineering applications because it can drive regulatable and titratable expression of genes and genetic pathways in microbial cell factories. A notable limitation of araC pBAD is that it generates a low signal when induced with high concentrations of L-arabinose (the maximum ON state). Herein we have amplified the maximum ON state of araC pBAD by coupling it to a synthetically evolved translation initiation region (TIR^EVOL). The coupling maintains regulatable and titratable expression from araC pBAD and yet increases the maximal ON state by >5-fold. The general principle demonstrated in the study can be applied to amplify the signal from similar genetic modules.

Graphical Abstract

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

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

Current status, challenges and prospects for lignin valorization by using Rhodococcus sp

Lignin represents the most abundant renewable aromatics in nature, which has complicated and heterogeneous structure. The rapid development of biotransformation technology has brought new opportunities to achieve the complete lignin valorization. Especially, Rhodococcus sp. possesses excellent capabilities to metabolize aromatic hydrocarbons degraded from lignin. Furthermore, it can convert these toxic compounds into high value added bioproducts, such as microbial lipids, polyhydroxyalkanoate and carotenoid et al. Accordingly, this review will discuss the potentials of Rhodococcus sp. as a cell factory for lignin biotransformation, including phenol tolerance, lignin depolymerization and lignin-derived aromatic hydrocarbon metabolism. The detailed metabolic mechanism for lignin biotransformation and bioproducts spectrum of Rhodococcus sp. will be comprehensively discussed. The available molecular tools for the conversion of lignin by Rhodococcus sp. will be reviewed, and the possible direction for lignin biotransformation in the future will also be proposed.

De Novo Design of the ArsR Regulated Pars Promoter Enables a Highly Sensitive Whole-Cell Biosensor for Arsenic Contamination

Whole-cell biosensors for arsenic contamination are typically designed based on natural bacterial sensing systems, which are often limited by their poor performance for precisely tuning the genetic response to environmental stimuli. Promoter design remains one of the most important approaches to address such issues. Here, we use the arsenic-responsive ArsR-P_ars regulation system from Escherichia coli MG1655 as the sensing element and coupled gfp or lacZ as the reporter gene to construct the genetic circuit for characterizing the refactored promoters. We first analyzed the ArsR binding site and a library of RNA polymerase binding sites to mine potential promoter sequences. A set of tightly regulated P_ars promoters by ArsR was designed by placing the ArsR binding sites into the promoter's core region, and a novel promoter with maximal repression efficiency and optimal fold change was obtained. The fluorescence sensor P_lacV-P_arsOC2 constructed with the optimized P_arsOC2 promoter showed a fold change of up to 63.80-fold (with green fluorescence visible to the naked eye) at 9.38 ppb arsenic, and the limit of detection was as low as 0.24 ppb. Further, the optimized colorimetric sensor P_lacV-P_arsOC2-lacZ with a linear response between 0 and 5 ppb was used to perform colorimetric reactions in 24-well plates combined with a smartphone application for the quantification of the arsenic level in groundwater. This study offers a new approach to improve the performance of bacterial sensing promoters and will facilitate the on-site application of arsenic whole-cell biosensors.

Engineering an oleic acid-induced system for Halomonas, E. coli and Pseudomonas

Ligand-induced system plays an important role for microbial engineering due to its tunable gene expression control over timings and levels. An oleic acid (OA)-induced system was recently constructed based on protein FadR, a transcriptional regulator involved in fatty acids metabolism, for metabolic control in Escherichia coli. In this study, we constructed a synthetic FadR-based OA-induced systems in Halomonas bluephagenesis by hybridizing the porin promoter core region and FadR-binding operator (fadO). The dynamic control range was optimized over 150-fold, and expression leakage was significantly reduced by tuning FadR expression and positioning fadO, forming a series of OA-induced systems with various expression strengths, respectively. Additionally, ligand orthogonality and cross-species portability were also studied and showed highly linear correlation among Halomonas spp., Escherichia coli and Pseudomonas spp. Finally, OA-induced systems with medium- and small-dynamic control ranges were employed to dynamically control the expression levels of morphology associated gene minCD, and monomer precursor 4-hydroxybutyrate-CoA (4HB-CoA) synthesis pathway for polyhydroxyalkanoates (PHA), respectively, in the presence of oleic acid as an inducer. As a result, over 10 g/L of poly-3-hydroxybutyrate (PHB) accumulated by elongated cell sizes, and 6 g/L of P(3HB-co-9.57 mol% 4HB) were obtained by controlling the dose and induction time of oleic acid only. This study provides a systematic approach for ligand-induced system engineering, and demonstrates an alternative genetic tool for dynamic control of industrial biotechnology.

ERMer: a serverless platform for navigating, analyzing, and visualizing Escherichia coli regulatory landscape through graph database

Cellular regulation is inherently complex, and one particular cellular function is often controlled by a cascade of different types of regulatory interactions. For example, the activity of a transcription factor (TF), which regulates the expression level of downstream genes through transcriptional regulation, can be regulated by small molecules through compound–protein interactions. To identify such complex regulatory cascades, traditional relational databases require ineffective additional operations and are computationally expensive. In contrast, graph databases are purposefully developed to execute such deep searches efficiently. Here, we present ERMer (E. coli Regulation Miner), the first cloud platform for mining the regulatory landscape of Escherichia coli based on graph databases. Combining the AWS Neptune graph database, AWS lambda function, and G6 graph visualization engine enables quick search and visualization of complex regulatory cascades/patterns. Users can also interactively navigate the E. coli regulatory landscape through ERMer. Furthermore, a Q&A module is included to showcase the power of graph databases in answering complex biological questions through simple queries. The backend graph model can be easily extended as new data become available. In addition, the framework implemented in ERMer can be easily migrated to other applications or organisms. ERMer is available at https://ermer.biodesign.ac.cn/.

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.

Development and characterization of a glycine biosensor system for fine-tuned metabolic regulation in Escherichia coli

Background

In vivo biosensors have a wide range of applications, ranging from the detection of metabolites to the regulation of metabolic networks, providing versatile tools for synthetic biology and metabolic engineering. However, in view of the vast array of metabolite molecules, the existing number and performance of biosensors is far from sufficient, limiting their potential applications in metabolic engineering. Therefore, we developed the synthetic glycine-ON and -OFF riboswitches for metabolic regulation and directed evolution of enzyme in Escherichia coli.

Results

The results showed that a synthetic glycine-OFF riboswitch (glyOFF6) and an increased-detection-range synthetic glycine-ON riboswitch (glyON14) were successfully screened from a library based on the Bacillus subtilis glycine riboswitch using fluorescence-activated cell sorting (FACS) and tetA-based dual genetic selection. The two synthetic glycine riboswitches were successfully used in tunable regulation of lactate synthesis, dynamic regulation of serine synthesis and directed evolution of alanine-glyoxylate aminotransferase in Escherichia coli, respectively. Mutants AGXT22 and AGXT26 of alanine-glyoxylate aminotransferase with an increase of 58% and 73% enzyme activity were obtained by using a high-throughput screening platform based on the synthetic glycine-OFF riboswitch, and successfully used to increase the 5-aminolevulinic acid yield of engineered Escherichia coli.

Conclusions

A synthetic glycine-OFF riboswitch and an increased-detection-range synthetic glycine-ON riboswitch were successfully designed and screened. The developed riboswitches showed broad application in tunable regulation, dynamic regulation and directed evolution of enzyme in E. coli.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01779-4.

Enhancing biofuels production by engineering the actin cytoskeleton in Saccharomyces cerevisiae

Saccharomyces cerevisiae is widely employed as a cell factory for the production of biofuels. However, product toxicity has hindered improvements in biofuel production. Here, we engineer the actin cytoskeleton in S. cerevisiae to increase both the cell growth and production of n-butanol and medium-chain fatty acids. Actin cable tortuosity is regulated using an n-butanol responsive promoter-based autonomous bidirectional signal conditioner in S. cerevisiae. The budding index is increased by 14.0%, resulting in the highest n-butanol titer of 1674.3 mg L-1. Moreover, actin patch density is fine-tuned using a medium-chain fatty acid responsive promoter-based autonomous bidirectional signal conditioner. The intracellular pH is stabilized at 6.4, yielding the highest medium-chain fatty acids titer of 692.3 mg L-1 in yeast extract peptone dextrose medium. Engineering the actin cytoskeleton in S. cerevisiae can efficiently alleviate biofuels toxicity and enhance biofuels production.

PASIV: A Pooled Approach-Based Workflow to Overcome Toxicity-Induced Design of Experiments Failures and Inefficiencies

We present here a newly developed workflow—which we have called PASIV—designed to provide a solution to a practical problem with design of experiments (DoE) methodology: i.e., what can be done if the scoping phase of the DoE cycle is severely hampered by burden and toxicity issues (caused by either the metabolite or an intermediary), making it unreliable or impossible to proceed to the screening phase? PASIV—standing for pooled approach, screening, identification, and visualization—was designed so the (viable) region of interest can be made to appear through an interplay between biology and software. This was achieved by combining multiplex construction in a pooled approach (one-pot reaction) with a viability assay and with a range of bioinformatics tools (including a novel construct matching tool). PASIV was tested on the exemplar of the lycopene pathway—under stressful constitutive expression—yielding a region of interest with comparatively stronger producers.

Engineering Transcription Factor BmoR Mutants for Constructing Multifunctional Alcohol Biosensors

Native transcription factor-based biosensors (TFBs) have the potential for the in situ detection of value-added chemicals or byproducts. However, their industrial application is limited by their ligand promiscuity, low sensitivity, and narrow detection range. Alcohols exhibit similar structures, and no reported TFB can distinguish a specific alcohol from its analogues. Here, we engineered an alcohol-regulated transcription factor, BmoR, and obtained various mutants with remarkable properties. For example, the generated signal-molecule-specific BmoRs could distinguish the constitutional isomers n-butanol and isobutanol, with insensitivity up to an ethanol concentration of 800 mM (36.9 g/L). Linear detection of 0-60 mM of a specific higher alcohol could be achieved in the presence of up to 500 mM (23.0 g/L) ethanol as background noise. Furthermore, we obtained two mutants with raised outputs and over 10⁷-fold higher sensitivity and one mutant with an increased upper detection limit (14.8 g/L n-butanol or isobutanol). Using BmoR as an example, this study systematically explored the ultimate detection limit of a TFB toward its small-molecule ligands, paving the way for in situ detection in biofuel and wine industries.

Polymer Encapsulation of Bacterial Biosensors Enables Coculture with Mammalian Cells

Coexistence of different populations of cells and isolation of tasks can provide enhanced robustness and adaptability or impart new functionalities to a culture. However, generating stable cocultures involving cells with vastly different growth rates can be challenging. To address this, we developed living analytics in a multilayer polymer shell (LAMPS), an encapsulation method that facilitates the coculture of mammalian and bacterial cells. We leverage LAMPS to preprogram a separation of tasks within the coculture: growth and therapeutic protein production by the mammalian cells and l-lactate biosensing by Escherichia coli encapsulated within LAMPS. LAMPS enable the formation of a synthetic bacterial-mammalian cell interaction that enables a living biosensor to be integrated into a biomanufacturing process. Our work serves as a proof-of-concept for further applications in bioprocessing since LAMPS combine the simplicity and flexibility of a bacterial biosensor with a viable method to prevent runaway growth that would disturb mammalian cell physiology.

Fate of carotenoids in yeasts: synthesis and cleavage

Carotenoids and their cleavage products (norisoprenoids) have excellent functional properties with diverse applications in foods, medicaments, cosmetics, etc. Carotenoids can be oxidatively cleaved through nonspecific reactions or by carotenoid cleavage oxygenases (CCOs), the product of which could further modify food flavor. This review provides comprehensive information on both carotenoid synthesis and cleavage processes with emphasis on enzyme characterization and biosynthetic pathway optimization. The use of interdisciplinary approaches of bioengineering and computer-aided experimental technology for key enzyme modification and systematic pathway design is beneficial to monitor metabolic pathways and assess pathway bottlenecks, which could efficiently lead to accumulation of carotenoids in microorganisms. The identification of CCOs spatial structures isolated from different species has made a significant contribution to the current state of knowledge. Current trends in carotenoid-related flavor modification are also discussed. In particular, we propose the carotenoid-synthesizing yeast Rhodotorula spp. for the production of food bioactive compounds. Understanding the behavior underlying the formation of norisoprenoids from carotenoids using interdisciplinary approaches may point toward other areas of investigation that could lead to better exploiting the potential use of autochthonous yeast in flavor enhancement.

Transient Antibiotic Tolerance Triggered by Nutrient Shifts From Gluconeogenic Carbon Sources to Fatty Acid

Nutrient shifts from glycolytic-to-gluconeogenic carbon sources can create large sub-populations of extremely antibiotic tolerant bacteria, called persisters. Positive feedback in Escherichia coli central metabolism was believed to play a key role in the formation of persister cells. To examine whether positive feedback in nutrient transport can also support high persistence to β-lactams, we performed nutrient shifts for E. coli from gluconeogenic carbon sources to fatty acid (FA). We observed tri-phasic antibiotic killing kinetics characterized by a transient period of high antibiotic tolerance, followed by rapid killing then a slower persister-killing phase. The duration of transient tolerance (3-44 h) varies with pre-shift carbon source and correlates strongly with the time needed to accumulate the FA degradation enzyme FadD after the shift. Additionally, FadD accumulation time and thus transient tolerance time can be reduced by induction of the glyoxylate bypass prior to switching, highlighting that two interacting feedback loops simultaneously control the length of transient tolerance. Our results demonstrate that nutrient switches along with positive feedback are not sufficient to trigger persistence in a majority of the population but instead triggers only a temporary tolerance. Additionally, our results demonstrate that the pre-shift metabolic state determines the duration of transient tolerance and that supplying glyoxylate can facilitate antibiotic killing of bacteria.

Elucidation of Sequence-Function Relationships for an Improved Biobutanol In Vivo Biosensor in E. coli

Transcription factor (TF)–promoter pairs have been repurposed from native hosts to provide tools to measure intracellular biochemical production titer and dynamically control gene expression. Most often, native TF–promoter systems require rigorous screening to obtain desirable characteristics optimized for biotechnological applications. High-throughput techniques may provide a rational and less labor-intensive strategy to engineer user-defined TF–promoter pairs using fluorescence-activated cell sorting and deep sequencing methods (sort-seq). Based on the designed promoter library’s distribution characteristics, we elucidate sequence–function interactions between the TF and DNA. In this work, we use the sort-seq method to study the sequence–function relationship of a σ⁵⁴-dependent, butanol-responsive TF–promoter pair, BmoR-P_BMO derived from Thauera butanivorans, at the nucleotide level to improve biosensor characteristics, specifically an improved dynamic range. Activities of promoters from a mutagenized P_BMO library were sorted based on gfp expression and subsequently deep sequenced to correlate site-specific sequences with changes in dynamic range. We identified site-specific mutations that increase the sensor output. Double mutant and a single mutant, CA(129,130)TC and G(205)A, in P_BMO promoter increased dynamic ranges of 4-fold and 1.65-fold compared with the native system, respectively. In addition, sort-seq identified essential sites required for the proper function of the σ⁵⁴-dependent promoter biosensor in the context of the host. This work can enable high-throughput screening methods for strain development.

Refactoring transcription factors for metabolic engineering

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

Harnessing plasmid replication mechanism to enable dynamic control of gene copy in bacteria

Dynamic regulation has been proved efficient in controlling gene expression at transcriptional, translational, and post-translational level. However, the dynamic regulation at gene replication level has been rarely explored so far. In this study, we established dynamic regulation at gene copy level through engineering controllable plasmid replication to dynamically control the gene expression. Prototypic genetic circuits with different control logic were applied to enable diversified dynamic behaviors of gene copy. To explore the applicability of this strategy, the dynamic gene copy control was employed in regulating the biosynthesis of p-coumaric acid, which resulted in an up to 78% increase in p-coumaric acid titer to 1.69 g/L in shake flasks. These results indicated the great potential of applying dynamic gene copy control for engineering biosynthesis of valuable compounds in metabolic engineering.

Sensory Systems and Transcriptional Regulation in Escherichia coli

In free-living bacteria, the ability to regulate gene expression is at the core of adapting and interacting with the environment. For these systems to have a logic, a signal must trigger a genetic change that helps the cell to deal with what implies its presence in the environment; briefly, the response is expected to include a feedback to the signal. Thus, it makes sense to think of genetic sensory mechanisms of gene regulation. Escherichia coli K-12 is the bacterium model for which the largest number of regulatory systems and its sensing capabilities have been studied in detail at the molecular level. In this special issue focused on biomolecular sensing systems, we offer an overview of the transcriptional regulatory corpus of knowledge for E. coli that has been gathered in our database, RegulonDB, from the perspective of sensing regulatory systems. Thus, we start with the beginning of the information flux, which is the signal's chemical or physical elements detected by the cell as changes in the environment; these signals are internally transduced to transcription factors and alter their conformation. Signals transduced to effectors bind allosterically to transcription factors, and this defines the dominant sensing mechanism in E. coli. We offer an updated list of the repertoire of known allosteric effectors, as well as a list of the currently known different mechanisms of this sensing capability. Our previous definition of elementary genetic sensory-response units, GENSOR units for short, that integrate signals, transport, gene regulation, and the biochemical response of the regulated gene products of a given transcriptional factor fit perfectly with the purpose of this overview. We summarize the functional heterogeneity of their response, based on our updated collection of GENSORs, and we use them to identify the expected feedback as part of their response. Finally, we address the question of multiple sensing in the regulatory network of E. coli. This overview introduces the architecture of sensing and regulation of native components in E.coli K-12, which might be a source of inspiration to bioengineering applications.

Engineering transcriptional regulation in Escherichia coli using an archaeal TetR-family transcription factor

Synthetic biology requires well-characterized biological parts that can be combined into functional modules. One type of biological parts are transcriptional regulators and their cognate operator elements, which enable to either generate an input-specific response or are used as actuator modules. A range of regulators has already been characterized and used for orthogonal gene expression engineering, however, previous efforts have mostly focused on bacterial regulators. This work aims to design and explore the use of an archaeal TetR family regulator, FadR_Sa from Sulfolobus acidocaldarius, in a bacterial system, namely Escherichia coli. This is a challenging objective given the fundamental difference between the bacterial and archaeal transcription machinery and the lack of a native TetR-like FadR regulatory system in E. coli. The synthetic σ⁷⁰-dependent bacterial promoter proD was used as a starting point to design hybrid bacterial/archaeal promoter/operator regions, in combination with the mKate2 fluorescent reporter enabling a readout. Four variations of proD containing FadR_Sa binding sites were constructed and characterized. While expressional activity of the modified promoter proD was found to be severely diminished for two of the constructs, constructs in which the binding site was introduced adjacent to the -35 promoter element still displayed sufficient basal transcriptional activity and showed up to 7-fold repression upon expression of FadR_Sa. Addition of acyl-CoA has been shown to disrupt FadR_Sa binding to the DNA in vitro. However, extracellular concentrations of up to 2 mM dodecanoate, subsequently converted to acyl-CoA by the cell, did not have a significant effect on repression in the bacterial system. This work demonstrates that archaeal transcription regulators can be used to generate actuator elements for use in E. coli, although the lack of ligand response underscores the challenge of maintaining biological function when transferring parts to a phylogenetically divergent host.

The Studies in Constructing Yeast Cell Factories for the Production of Fatty Acid Alkyl Esters

Fatty acid alkyl esters have broad applications in biofuels, lubricant formulas, paints, coatings, and cosmetics. Traditionally, these esters are mostly produced through unsustainable and energy-intensive processes. In contrast, microbial production of esters from renewable and sustainable feedstocks may provide a promising alternative and has attracted widespread attention in recent years. At present, yeasts are used as ideal hosts for producing such esters, due to their availability for high-density fermentation, resistance to phage infection, and tolerance against toxic inhibitors. Here, we summarize recent development on the biosynthesis of alkyl esters, including fatty acid ethyl esters (FAEEs), fatty acid short-branched chain alkyl esters (FASBEs), and wax esters (WEs) by various yeast cell factories. We focus mainly on the enzyme engineering strategies of critical wax ester synthases, and the pathway engineering strategies employed for the biosynthesis of various ester products. The bottlenecks that limit productivity and their potential solutions are also discussed in this review.

Metabolic engineering for valorization of macroalgae biomass

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

Trade-Offs in Biosensor Optimization for Dynamic Pathway Engineering

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

Strategies to increase tolerance and robustness of industrial microorganisms

The development of a cost-competitive bioprocess requires that the cell factory converts the feedstock into the product of interest at high rates and yields. However, microbial cell factories are exposed to a variety of different stresses during the fermentation process. These stresses can be derived from feedstocks, metabolism, or industrial production processes, limiting production capacity and diminishing competitiveness. Improving stress tolerance and robustness allows for more efficient production and ultimately makes a process more economically viable. This review summarises general trends and updates the most recent developments in technologies to improve the stress tolerance of microorganisms. We first look at evolutionary, systems biology and computational methods as examples of non-rational approaches. Then we review the (semi-)rational approaches of membrane and transcription factor engineering for improving tolerance phenotypes. We further discuss challenges and perspectives associated with these different approaches.

Biosensor for branched-chain amino acid metabolism in yeast and applications in isobutanol and isopentanol production

Branched-chain amino acid (BCAA) metabolism fulfills numerous physiological roles and can be harnessed to produce valuable chemicals. However, the lack of eukaryotic biosensors specific for BCAA-derived products has limited the ability to develop high-throughput screens for strain engineering and metabolic studies. Here, we harness the transcriptional regulator Leu3p from Saccharomyces cerevisiae to develop a genetically encoded biosensor for BCAA metabolism. In one configuration, we use the biosensor to monitor yeast production of isobutanol, an alcohol derived from valine degradation. Small modifications allow us to redeploy Leu3p in another biosensor configuration that monitors production of the leucine-derived alcohol, isopentanol. These biosensor configurations are effective at isolating high-producing strains and identifying enzymes with enhanced activity from screens for branched-chain higher alcohol (BCHA) biosynthesis in mitochondria as well as cytosol. Furthermore, this biosensor has the potential to assist in metabolic studies involving BCAA pathways, and offers a blueprint to develop biosensors for other products derived from BCAA metabolism.

There are a lack of eukaryotic biosensors specific for branched-chain amino acid (BCAA)-derived products. Here the authors report a genetically encoded biosensor for BCAA metabolism based on the Leu3p transcriptional regulator; they use this to monitor yeast production of isobutanol and isopentanol.

In Vivo Screening Method for the Identification and Characterization of Prokaryotic, Metabolite-Responsive Transcription Factors

In prokaryotes, transcription factors (TFs) are of uttermost importance for the regulation of gene expression. However, the majority of TFs are not characterized today, which hampers both the understanding of fundamental processes and the development of TF-based applications, such as biosensors, used in metabolic engineering, synthetic biology, diagnostics, etc. One way of analyzing TFs is through in vivo screening, enabling the study of TF-promoter interactions, ligand inducibility, and ligand specificity in a high-throughput fashion. Here, an approach is described for the selection and cloning of TF-promoter pairs, the development of a reporter system, and the measurement and analysis of fluorescent reporter assays. Furthermore, the importance of a suitable inducible plasmid system is illustrated together with prospective adaptations to modify a reporter system's output signal. The given approach can be used for the investigation of native, heterologous, or even artificially created TFs in Escherichia coli, and can be extended toward use in other microorganisms.

Directed Evolution of Transcription Factor-Based Biosensors for Altered Effector Specificity

Transcription factor-based biosensors are important tools in Synthetic Biology for the sensing of industrially valuable molecules and clinically important metabolites, therefore presenting applications in the bioremediation, industrial biotechnology, and biomedical fields. The directed evolution of allosteric transcription factors (aTFs) with the aim of altering effector specificity has the potential for the development of new biosensors to detect natural and nonnatural molecules, expanding the scope of available aTF-based biosensors. In this chapter, we delineate a general method for the directed evolution of aTFs. The theory of library design is discussed, along with the detailed methodology for an improved transformation of combined libraries, and the experimental search space by counterselection using fluorescence-activated cell sorting (FACS) is presented.

Development of a Highly Efficient Copper-Inducible GAL Regulation System (CuIGR) in Saccharomyces cerevisiae

Dynamic regulation of gene expression to decouple growth and production has been proven to be effective for improving the biosynthetic efficiency of microbial cell factories. However, the number of efficient regulatory systems available for regulation of Saccharomyces cerevisiae is limited. In the present study, a novel copper-inducible gene expression system (CuIGR) composed of the copper-induced transcriptional activator Gal4 and the copper-inhibited repressor Gal80 was constructed in S. cerevisiae. When Gal80 was fused with a N-degron tag (K15), the resulting CuIGR4 system exhibited the most stringent regulation of gene expression driven by GAL1/2/7/10 promoters. As compared to the native Cu²⁺-inducible CUP1 promoter, the CuIGR4 system amplified the response to copper by as much as 2.7 folds, resulting in 72-fold induction of EGFP expression and a 33-fold change in lycopene production (3-100 mg/L) with addition of 20 μM copper. This newly developed copper-inducible system provides a powerful tool for gene expression control in S. cerevisiae, which is expected to be widely applicable in the regulation of yeast cell factories for enhanced biosynthesis of valuable products.

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

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

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

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

Development of a Transcription Factor-Based Diamine Biosensor in Corynebacterium glutamicum

Diamines serve as major platform chemicals that can be employed to a variety of industrial scenarios, particularly as monomers for polymer synthesis. High-throughput sensors for diamine biosynthesis can greatly improve the biological production of diamines. Here, we identified and characterized a transcription factor-driven biosensor for putrescine and cadaverine in Corynebacterium glutamicum. The transcriptional TetR-family regulatory protein CgmR (CGL2612) is used for the specific detection of diamine compounds. This study also improved the dynamic range and the sensitivity to putrescine by systematically optimizing genetic components of pSenPut. By a single cell-based screening strategy for a library of CgmR with random mutations, this study obtained the most sensitive variant CgmR_I152T, which possessed an experimentally determined limit of detection (LoD) of ≤0.2 mM, a K of 11.4 mM, and a utility of 720. Using this highly sensitive putrescine biosensor pSenPut_I152T, we demonstrated that CgmRI_152T can be used as a sensor to detect putrescine produced biologically in a C. glutamicum system. This high sensitivity and the range of CgmR will be an influential tool for rewiring metabolic circuits and facilitating the directed evolution of recombinant strains toward the biological synthesis of diamine compounds.

Engineered microbial consortia: strategies and applications

Many applications of microbial synthetic biology, such as metabolic engineering and biocomputing, are increasing in design complexity. Implementing complex tasks in single populations can be a challenge because large genetic circuits can be burdensome and difficult to optimize. To overcome these limitations, microbial consortia can be engineered to distribute complex tasks among multiple populations. Recent studies have made substantial progress in programming microbial consortia for both basic understanding and potential applications. Microbial consortia have been designed through diverse strategies, including programming mutualistic interactions, using programmed population control to prevent overgrowth of individual populations, and spatial segregation to reduce competition. Here, we highlight the role of microbial consortia in the advances of metabolic engineering, biofilm production for engineered living materials, biocomputing, and biosensing. Additionally, we discuss the challenges for future research in microbial consortia.

Microbial production of advanced biofuels

Concerns over climate change have necessitated a rethinking of our transportation infrastructure. One possible alternative to carbon-polluting fossil fuels is biofuels produced by engineered microorganisms that use a renewable carbon source. Two biofuels, ethanol and biodiesel, have made inroads in displacing petroleum-based fuels, but their uptake has been limited by the amounts that can be used in conventional engines and by their cost. Advanced biofuels that mimic petroleum-based fuels are not limited by the amounts that can be used in existing transportation infrastructure but have had limited uptake due to costs. In this Review, we discuss engineering metabolic pathways to produce advanced biofuels, challenges with substrate and product toxicity with regard to host microorganisms and methods to engineer tolerance, and the use of functional genomics and machine learning approaches to produce advanced biofuels and prospects for reducing their costs.

Attenuator LRR - a regulatory tool for modulating gene expression in Gram-positive bacteria

With the rapid development of synthetic biology in recent years, particular attention has been paid to RNA devices, especially riboswitches, because of their significant and diverse regulatory roles in prokaryotic and eukaryotic cells. Due to the limited performance and context-dependence of riboswitches, only a few of them (such as theophylline, tetracycline and ciprofloxacin riboswitches) have been utilized as regulatory tools in biotechnology. In the present study, we demonstrated that a ribosome-dependent ribo-regulator, LRR, discovered in our previous work, exhibits an attractive regulatory performance. Specifically, it offers a 60-fold change in expression in the presence of retapamulin and a low level of leaky expression of about 1-2% without antibiotics. Moreover, LRR can be combined with different promoters and performs well in Bacillus thuringiensis, B. cereus, B. amyloliquefaciens, and B. subtilis. Additionally, LRR also functions in the Gram-negative bacterium Escherichia coli. Furthermore, we demonstrate its ability to control melanin metabolism in B. thuringiensis BMB171. Our results show that LRR can be applied to regulate gene expression, construct genetic circuits and tune metabolic pathways, and has great potential for many applications in synthetic biology.

Importance of the 5' regulatory region to bacterial synthetic biology applications

The field of synthetic biology is evolving at a fast pace. It is advancing beyond single-gene alterations in single hosts to the logical design of complex circuits and the development of integrated synthetic genomes. Recent breakthroughs in deep learning, which is increasingly used in de novo assembly of DNA components with predictable effects, are also aiding the discipline. Despite advances in computing, the field is still reliant on the availability of pre-characterized DNA parts, whether natural or synthetic, to regulate gene expression in bacteria and make valuable compounds. In this review, we discuss the different bacterial synthetic biology methodologies employed in the creation of 5' regulatory regions - promoters, untranslated regions and 5'-end of coding sequences. We summarize methodologies and discuss their significance for each of the functional DNA components, and highlight the key advances made in bacterial engineering by concentrating on their flaws and strengths. We end the review by outlining the issues that the discipline may face in the near future.

Dynamic metabolic engineering of Escherichia coli improves fermentation for the production of pyruvate and its derivatives

Pyruvate is a key intermediate that is involved in various synthetic metabolic pathways for microbial chemical and fuel production. It is widely used in the food, chemical, and pharmaceutical industries. However, the microbial production of pyruvate and its derivatives compete with microbial cell growth, as pyruvate is an important metabolic intermediate that serves as a hub for various endogenous metabolic pathways, including gluconeogenesis, amino acid synthesis, TCA cycle, and fatty acid biosynthesis. To achieve a more efficient bioprocess for the production of pyruvate and its derivatives, it is necessary to reduce the metabolic imbalance between cell growth and target chemical production. For this purpose, we devised a dynamic metabolic engineering strategy within an Escherichia coli model, in which a metabolic toggle switch (MTS) was employed to redirect metabolic flux from the endogenous pathway toward the target synthetic pathway. Through a combination of TCA cycle interruption through MTS and reduction of pyruvate consumption in endogenous pathways, we achieved a drastic improvement (163 mM, 26-fold) in pyruvate production. In addition, we demonstrated the redirection of metabolic flux from excess pyruvate toward isobutanol production. The final isobutanol production titer of the strain harboring MTS was 26% improved compared with that of the control strain.

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

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

Modular tuning engineering and versatile applications of genetically encoded biosensors

Genetically encoded biosensors have a diverse range of detectable signals and potential applications in many fields, including metabolism control and high-throughput screening. Their ability to be used in situ with minimal interference to the bioprocess of interest could revolutionize synthetic biology and microbial cell factories. The performance and functions of these biosensors have been extensively studied and have been rapidly improved. We review here current biosensor tuning strategies and attempt to unravel how to obtain ideal biosensor functions through experimental adjustments. Strategies for expanding the biosensor input signals that increases the number of detectable compounds have also been summarized. Finally, different output signals and their practical requirements for biotechnology and biomedical applications and environmental safety concerns have been analyzed. This in-depth review of the responses and regulation mechanisms of genetically encoded biosensors will assist to improve their design and optimization in various application scenarios.

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.

Recent Progress and Trends in the Development of Microbial Biofuels from Solid Waste—A Review

This review covers the recent progress in the design and application of microbial biofuels, assessing the advancement of genetic engineering undertakings and their marketability, and lignocellulosic biomass pretreatment issues. Municipal solid waste (MSW) is a promising sustainable biofuel feedstock due to its high content of lignocellulosic fiber. In this review, we compared the production of fatty alcohols, alkanes, and n-butanol from residual biogenic waste and the environmental/economic parameters to that of conventional biofuels. New synthetic biology tools can be used to engineer fermentation pathways within micro-organisms to produce long-chain alcohols, isoprenoids, long-chain fatty acids, and esters, along with alkanes, as substitutes to petroleum-derived fuels. Biotechnological advances have struggled to address problems with bioethanol, such as lower energy density compared to gasoline and high corrosive and hygroscopic qualities that restrict its application in present infrastructure. Biofuels derived from the organic fraction of municipal solid waste (OFMSW) may have less environmental impacts compared to traditional fuel production, with the added benefit of lower production costs. Unfortunately, current advanced biofuel production suffers low production rates, which hinders commercial scaling-up efforts. Microbial-produced biofuels can address low productivity while increasing the spectrum of produced bioenergy molecules.

An Integrative Toolbox for Synthetic Biology in Rhodococcus

The development of microbial cell factories requires robust synthetic biology tools to reduce design uncertainty and accelerate the design-build-test-learn process. Herein, we developed a suite of integrative genetic tools to facilitate the engineering of Rhodococcus, a genus of bacteria with considerable biocatalytic potential. We first created pRIME, a modular, copy-controlled integrative-vector, to provide a robust platform for strain engineering and characterizing genetic parts. This vector was then employed to benchmark a series of strong promoters. We found P_M6 to be the strongest constitutive rhodococcal promoter, 2.5- to 3-fold stronger than the next in our study, while overall promoter activities ranged 23-fold between the weakest and strongest promoters during exponential growth. Next, we used an optimized variant of P_M6 to develop hybrid-promoters and integrative vectors to allow for tetracycline-inducible gene expression in Rhodococcus. The best of the resulting hybrid-promoters maintained a maximal activity of ∼50% of P_M6 and displayed an induction factor of ∼40-fold. Finally, we developed and implemented a uLoop-derived Golden Gate assembly strategy for high-throughput DNA assembly in Rhodococcus. To demonstrate the utility of our approaches, pRIME was used to engineer Rhodococcus jostii RHA1 to grow on vanillin at concentrations 10-fold higher than what the wild-type strain tolerated. Overall, this study provides a suite of tools that will accelerate the engineering of Rhodococcus for various biocatalytic applications, including the sustainable production of chemicals from lignin-derived aromatics.

Synthetic Cellobiose-Inducible Regulatory Systems Allow Tight and Dynamic Controls of Gene Expression in Streptomyces

Precise control of microbial gene expression is crucial for synthetic biotechnological applications. This is particularly true for the bacterial genus Streptomyces, major producers of diverse natural products including many antibiotics. Although a plethora of genetic tools have been developed for Streptomyces, there is still an urgent need for effective gene induction systems. We herein created two novel cellobiose-inducible regulatory systems referred to as Cel-RS1 and Cel-RS2. The regulatory systems are based upon the well-characterized repressor/operator pair CebR/cebO from Streptomyces scabies and the well-defined constitutive kasO* promoter. Both Cel-RS1 and Cel-RS2 exhibit a high level of induced reporter activity and virtually no leaky expression in three model Streptomyces species, which are commonly used as surrogate hosts for expression of natural product biosynthetic gene clusters. Cel-RS2 has been proven successful for programmable control of gene expression and controllable production of specialized metabolites in multiple Streptomyces species. The strategy can be used to expand the toolkit of inducible regulatory systems that will be broadly applicable to various Streptomyces.

Exploring the Tunability and Dynamic Properties of MarR-PmarO Sensor System in Escherichia coli

Transcriptional factor-based biosensors (TFBs) have been widely used in dynamic pathway control or high-throughput screening. Here, we systematically explored the tunability of a salicylic acid responsive regulator MarR from Escherichia coli aiming to explore its engineering potential. The effect of endogenous MarR in E. coli on the MarR-PmarO biosensor system was investigated. Furthermore, to investigate the function of marO binding boxes in this biosensor system, a series of hybrid promoters were constructed by placing the marO binding boxes in the strong constitutive pL promoter. The engineered hybrid promoters became responsive to MarR and salicylic acid. To further study the influence of each nucleotide in the marO box on MarR binding, we employed dynamic modeling to simulate the interaction and binding energy between each nucleotide in the marO boxes with the corresponding residues on MarR. Guided by the results of the simulation, we introduced mutations to key positions on the hybrid promoters and investigated corresponding dynamic performance. Two promoter variants I12AII4T and I12AII14T that exhibited improved responsive strengths and shifted dynamic ranges were obtained, which can be beneficial for future metabolic engineering research.

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

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

Genome-scale target identification in Escherichia coli for high-titer production of free fatty acids

To construct a superior microbial cell factory for chemical synthesis, a major challenge is to fully exploit cellular potential by identifying and engineering beneficial gene targets in sophisticated metabolic networks. Here, we take advantage of CRISPR interference (CRISPRi) and omics analyses to systematically identify beneficial genes that can be engineered to promote free fatty acids (FFAs) production in Escherichia coli. CRISPRi-mediated genetic perturbation enables the identification of 30 beneficial genes from 108 targets related to FFA metabolism. Then, omics analyses of the FFAs-overproducing strains and a control strain enable the identification of another 26 beneficial genes that are seemingly irrelevant to FFA metabolism. Combinatorial perturbation of four beneficial genes involving cellular stress responses results in a recombinant strain ihfA^L−-aidB⁺-ryfA^M−-gadA^H−, producing 30.0 g L⁻¹ FFAs in fed-batch fermentation, the maximum titer in E. coli reported to date. Our findings are of help in rewiring cellular metabolism and interwoven intracellular processes to facilitate high-titer production of biochemicals.

Identification of gene targets is one of the major challenges to construct superior microbial cell factory for chemical synthesis. Here, the authors employ CRISPRi and omics analyses for genome-scale target genes identification for high-titer production of free fatty acids in E. coli.

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

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

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