CRISPRi-Based Downregulation of Transcriptional Feedback Improves Growth and Metabolism of Arginine Overproducing E. coli

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

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

New strategies to study in depth the metabolic mechanism of astaxanthin biosynthesis in Phaffia rhodozyma

Astaxanthin, a ketone carotenoid known for its high antioxidant activity, holds significant potential for application in nutraceuticals, aquaculture, and cosmetics. The increasing market demand necessitates a higher production of astaxanthin using Phaffia rhodozyma. Despite extensive research efforts focused on optimizing fermentation conditions, employing mutagenesis treatments, and utilizing genetic engineering technologies to enhance astaxanthin yield in P. rhodozyma, progress in this area remains limited. This review provides a comprehensive summary of the current understanding of rough metabolic pathways, regulatory mechanisms, and preliminary strategies for enhancing astaxanthin yield. However, further investigation is required to fully comprehend the intricate and essential metabolic regulation mechanism underlying astaxanthin synthesis. Specifically, the specific functions of key genes, such as crtYB, crtS, and crtI, need to be explored in detail. Additionally, a thorough understanding of the action mechanism of bifunctional enzymes and alternative splicing products is imperative. Lastly, the regulation of metabolic flux must be thoroughly investigated to reveal the complete pathway of astaxanthin synthesis. To obtain an in-depth mechanism and improve the yield of astaxanthin, this review proposes some frontier methods, including: omics, genome editing, protein structure-activity analysis, and synthetic biology. Moreover, it further elucidates the feasibility of new strategies using these advanced methods in various effectively combined ways to resolve these problems mentioned above. This review provides theory and method for studying the metabolic pathway of astaxanthin in P. rhodozyma and the industrial improvement of astaxanthin, and provides new insights into the flexible combined use of multiple modern advanced biotechnologies.

Enabling pathway design by multiplex experimentation and machine learning

The remarkable metabolic diversity observed in nature has provided a foundation for sustainable production of a wide array of valuable molecules. However, transferring the biosynthetic pathway to the desired host often runs into inherent failures that arise from intermediate accumulation and reduced flux resulting from competing pathways within the host cell. Moreover, the conventional trial and error methods utilized in pathway optimization struggle to fully grasp the intricacies of installed pathways, leading to time-consuming and labor-intensive experiments, ultimately resulting in suboptimal yields. Considering these obstacles, there is a pressing need to explore the enzyme expression landscape and identify the optimal pathway configuration for enhanced production of molecules. This review delves into recent advancements in pathway engineering, with a focus on multiplex experimentation and machine learning techniques. These approaches play a pivotal role in overcoming the limitations of traditional methods, enabling exploration of a broader design space and increasing the likelihood of discovering optimal pathway configurations for enhanced production of molecules. We discuss several tools and strategies for pathway design, construction, and optimization for sustainable and cost-effective microbial production of molecules ranging from bulk to fine chemicals. We also highlight major successes in academia and industry through compelling case studies.

Mapping temperature-sensitive mutations at a genome scale to engineer growth switches in Escherichia coli

Temperature-sensitive (TS) mutants are a unique tool to perturb and engineer cellular systems. Here, we constructed a CRISPR library with 15,120 Escherichia coli mutants, each with a single amino acid change in one of 346 essential proteins. 1,269 of these mutants showed temperature-sensitive growth in a time-resolved competition assay. We reconstructed 94 TS mutants and measured their metabolism under growth arrest at 42°C using metabolomics. Metabolome changes were strong and mutant-specific, showing that metabolism of nongrowing E. coli is perturbation-dependent. For example, 24 TS mutants of metabolic enzymes overproduced the direct substrate metabolite due to a bottleneck in their associated pathway. A strain with TS homoserine kinase (ThrBF267D ) produced homoserine for 24 h, and production was tunable by temperature. Finally, we used a TS subunit of DNA polymerase III (DnaXL289Q ) to decouple growth from arginine overproduction in engineered E. coli. These results provide a strategy to identify TS mutants en masse and demonstrate their large potential to produce bacterial metabolites with nongrowing cells.

Reduction of acetate synthesis, enhanced arginine export, and supply of precursors, cofactors, and energy for improved synthesis of L-arginine by Escherichia coli

L-arginine (L-Arg) is a semi-essential amino acid with many important physiological functions. However, achieving efficient manufacture of L-Arg on an industrial scale using Escherichia coli (E. coli) remains a major challenge. In previous studies, we constructed a strain of E. coli A7, which had good L-Arg production capacity. In this study, E. coli A7 was further modified, and E. coli A21 with more efficient L-Arg production capacity was obtained. Firstly, we reduced the acetate accumulation of strain A7 by weakening the poxB gene and overexpressing acs gene. Secondly, we improved the L-Arg transport efficiency of strains by overexpressing the lysE gene from Corynebacterium glutamicum (C. glutamicum). Finally, we enhanced the supplies of precursors for the synthesis of L-Arg and optimized the supplies of cofactor NADPH and energy ATP in strain. After fermentation in a 5-L bioreactor, the L-Arg titer of strain A21 was found to be 89.7 g/L. The productivity was 1.495 g/(L·h) and the glucose yield was 0.377 g/g. Our study further narrowed the titer gap between E. coli and C. glutamicum in the synthesis of L-Arg. In all recent studies on the L-Arg production by E. coli, this was the highest titer recorded. In conclusion, our study further promotes the efficient mass synthesis of L-Arg by E. coli. KEY POINTS: • The acetate accumulation of starting strain A7 was decreased. • Overexpression of gene lysE of C. glutamicum enhanced L-Arg transport in strain A10. • Enhance the supplies of precursors for the synthesis of L-Arg and optimize the supplies of cofactor NADPH and energy ATP. Finally, Strain A21 was detected to have an L-Arg titer of 89.7 g/L in a 5-L bioreactor.

A CRISPRi mediated self-inducible system for dynamic regulation of TCA cycle and improvement of itaconic acid production in Escherichia coli

Itaconic acid (ITA), an effective alternative fossil fuel, derives from the bypass pathway of the tricarboxylic acid (TCA) cycle. Therefore, the imbalance of metabolic flux between TCA cycle and ITA biosynthetic pathway seriously limits the production of ITA. The optimization of flux distribution between biomass and production has the potential to the productivity of ITA. Based on the previously constructed strain Escherichia coli MG1655 Δ1-SAS-3 (ITA titer: 1.87 g/L), a CRISPRi-mediated self-inducible system (CiMS), which contained a responsive module based on the ITA biosensor YpItcR/P ccl and a regulative CRISPRi-mediated interferential module, was developed to regulate the flux of the TCA cycle and to enhance the capacity of the strain to produce ITA. First, a higher ITA-yielding strain, Δ4-P rmd -SAS-3 (ITA titer: 3.20 g/L), derived from Δ1-SAS-3, was constructed by replacing the promoter P J23100 , for the expression of ITA synthesis genes, with P rmd and knocking out the three bypass genes poxB, pflB, and ldhA. Subsequently, the CiMS was used to inhibit the expression of key genes icd, pykA, and sucCD to dynamically balance the metabolic flux between TCA cycle and ITA biosynthetic pathway during the ITA production stage. The constructed strain Δ4-P rmd -SAS-3 under the dynamic regulation of the CiMS, showed a 23% increase in the ITA titer, which reached 3.93 g/L. This study indicated that CiMS was a practical strategy to dynamically and precisely regulated the metabolic flux in microbial cell factories.

Metabolic engineering of Escherichia coli for efficient production of L-arginine

As an important semi-essential amino acid, L-arginine (L-Arg) has important application prospects in medicine and health care. However, it remains a challenge to efficiently produce L-Arg by Escherichia coli (E. coli). In the present study, we obtained an E. coli A1 with L-Arg accumulation ability, and carried out a series of metabolic engineering on it, and finally obtained an E. coli strain A7 with high L-Arg production ability. First, genome analysis of strain A1 was performed to explore the related genes affecting L-Arg accumulation. We found that gene speC and gene speF played an important role in the accumulation of L-Arg. Second, we used two strategies to solve the feedback inhibition of the L-Arg pathway in E. coli. One was the combination of a mutation of the gene argA and the deletion of the gene argR, and the other was the combination of a heterologous insertion of the gene argJ and the deletion of the gene argR. The combination of exogenous argJ gene insertion and argR gene deletion achieved higher titer accumulation with less impact on strain growth. Finally, we inserted the gene cluster argCJBDF of Corynebacterium glutamicum (C. glutamicum) to enhance the metabolic flux of the L-Arg pathway in E. coli. The final strain obtained 70.1 g/L L-Arg in a 5-L bioreactor, with a yield of 0.326 g/g glucose and a productivity of 1.17 g/(L· h). This was the highest level of L-Arg production by E. coli ever reported. Collectively, our findings provided valuable insights into the possibility of the industrial production of L-Arg by E. coli. KEY POINTS: • Genetic background of E. coli A1 genome analysis. • Heterologous argJ substitution of argA mutation promoted excessive accumulation of L-Arg in E. coli A1. • The overexpression of L-Arg synthesis gene cluster argCJBDF of Corynebacterium glutamicum (C. glutamate) promoted the accumulation of L-Arg, and 70.1 g/L L-Arg was finally obtained in fed-batch fermentation.

Metabolic Engineering of Bacillus amyloliquefaciens to Efficiently Synthesize L-Ornithine From Inulin

Bacillus amyloliquefaciens is the dominant strain used to produce γ-polyglutamic acid from inulin, a non-grain raw material. B. amyloliquefaciens has a highly efficient tricarboxylic acid cycle metabolic flux and glutamate synthesis ability. These features confer great potential for the synthesis of glutamate derivatives. However, it is challenging to efficiently convert high levels of glutamate to a particular glutamate derivative. Here, we conducted a systematic study on the biosynthesis of L-ornithine by B. amyloliquefaciens using inulin. First, the polyglutamate synthase gene pgsBCA of B. amyloliquefaciens NB was knocked out to hinder polyglutamate synthesis, resulting in the accumulation of intracellular glutamate and ATP. Second, a modular engineering strategy was applied to coordinate the degradation pathway, precursor competition pathway, and L-ornithine synthesis pathway to prompt high levels of intracellular precursor glutamate for l-ornithine synthesis. In addition, the high-efficiency L-ornithine transporter was further screened and overexpressed to reduce the feedback inhibition of L-ornithine on the synthesis pathway. Combining these strategies with further fermentation optimizations, we achieved a final L-ornithine titer of 31.3 g/L from inulin. Overall, these strategies hold great potential for strengthening microbial synthesis of high value-added products derived from glutamate.

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

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

Metabolic engineering of Escherichia coli for efficient production of l-arginine

As a semi-essential amino acid, l-arginine (l-Arg) plays an important role in food, health care, and medical treatment. At present, the main method of producing l-Arg is the use of microbial fermentation. Therefore, the selection and breeding of high-efficiency microbial strains is the top priority. To continuously improve the l-Arg production performance of the strains, a series of metabolic engineering strategies have been tried to transform the strains. The production of l-Arg by metabolically engineered Corynebacterium glutamicum (C. glutamicum) reached a relatively high level. Escherichia coli (E. coli), as a strain with great potential for l-Arg production, also has a large number of research strategies aimed at screening effective E. coli for producing l-Arg. E. coli also has a number of advantages over C. glutamicum in producing l-Arg. Therefore, it is of great significance to screen out excellent and stable E. coli to produce l-Arg. Here, based on recent research results, we review the metabolic pathways of l-Arg production in E. coli, the research progress of l-Arg production in E. coli, and various regulatory strategies implemented in E. coli.

Fine-tuning gene expression for improved biosynthesis of natural products: From transcriptional to post-translational regulation

Microbial production of natural compounds has attracted extensive attention due to their high value in pharmaceutical, cosmetic, and food industries. Constructing efficient microbial cell factories for biosynthesis of natural products requires the fine-tuning of gene expressions to minimize the accumulation of toxic metabolites, reduce the competition between cell growth and product generation, as well as achieve the balance of redox or co-factors. In this review, we focus on recent advances in fine-tuning gene expression at the DNA, RNA, and protein levels to improve the microbial biosynthesis of natural products. Commonly used regulatory toolsets in each level are discussed, and perspectives for future direction in this area are provided.

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

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

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.

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

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

Interrogating the Role of the Two Distinct Fructose-Bisphosphate Aldolases of Bacillus methanolicus by Site-Directed Mutagenesis of Key Amino Acids and Gene Repression by CRISPR Interference

The Gram-positive Bacillus methanolicus shows plasmid-dependent methylotrophy. This facultative ribulose monophosphate (RuMP) cycle methylotroph possesses two fructose bisphosphate aldolases (FBA) with distinct kinetic properties. The chromosomally encoded FBA^C is the major glycolytic aldolase. The gene for the major gluconeogenic aldolase FBA^P is found on the natural plasmid pBM19 and is induced during methylotrophic growth. The crystal structures of both enzymes were solved at 2.2 Å and 2.0 Å, respectively, and they suggested amino acid residue 51 to be crucial for binding fructose-1,6-bisphosphate (FBP) as substrate and amino acid residue 140 for active site zinc atom coordination. As FBA^C and FBA^P differed at these positions, site-directed mutagenesis (SDM) was performed to exchange one or both amino acid residues of the respective proteins. The aldol cleavage reaction was negatively affected by the amino acid exchanges that led to a complete loss of glycolytic activity of FBA^P. However, both FBA^C and FBA^P maintained gluconeogenic aldol condensation activity, and the amino acid exchanges improved the catalytic efficiency of the major glycolytic aldolase FBA^C in gluconeogenic direction at least 3-fold. These results confirmed the importance of the structural differences between FBA^C and FBA^P concerning their distinct enzymatic properties. In order to investigate the physiological roles of both aldolases, the expression of their genes was repressed individually by CRISPR interference (CRISPRi). The fba ^C RNA levels were reduced by CRISPRi, but concomitantly the fba ^P RNA levels were increased. Vice versa, a similar compensatory increase of the fba ^C RNA levels was observed when fba ^P was repressed by CRISPRi. In addition, targeting fba ^P decreased tkt ^P RNA levels since both genes are cotranscribed in a bicistronic operon. However, reduced tkt ^P RNA levels were not compensated for by increased RNA levels of the chromosomal transketolase gene tkt ^C.

CRISPRi-Library-Guided Target Identification for Engineering Carotenoid Production by Corynebacterium glutamicum

Corynebacterium glutamicum is a prominent production host for various value-added compounds in white biotechnology. Gene repression by dCas9/clustered regularly interspaced short palindromic repeats (CRISPR) interference (CRISPRi) allows for the identification of target genes for metabolic engineering. In this study, a CRISPRi-based library for the repression of 74 genes of C. glutamicum was constructed. The chosen genes included genes encoding enzymes of glycolysis, the pentose phosphate pathway, and the tricarboxylic acid cycle, regulatory genes, as well as genes of the methylerythritol phosphate and carotenoid biosynthesis pathways. As expected, CRISPRi-mediated repression of the carotenogenesis repressor gene crtR resulted in increased pigmentation and cellular content of the native carotenoid pigment decaprenoxanthin. CRISPRi screening identified 14 genes that affected decaprenoxanthin biosynthesis when repressed. Carotenoid biosynthesis was significantly decreased upon CRISPRi-mediated repression of 11 of these genes, while repression of 3 genes was beneficial for decaprenoxanthin production. Largely, but not in all cases, deletion of selected genes identified in the CRISPRi screen confirmed the pigmentation phenotypes obtained by CRISPRi. Notably, deletion of pgi as well as of gapA improved decaprenoxanthin levels 43-fold and 9-fold, respectively. The scope of the designed library to identify metabolic engineering targets, transfer of gene repression to stable gene deletion, and limitations of the approach were discussed.

Programmable gene regulation for metabolic engineering using decoy transcription factor binding sites

Transcription factor decoy binding sites are short DNA sequences that can titrate a transcription factor away from its natural binding site, therefore regulating gene expression. In this study, we harness synthetic transcription factor decoy systems to regulate gene expression for metabolic pathways in Escherichia coli. We show that transcription factor decoys can effectively regulate expression of native and heterologous genes. Tunability of the decoy can be engineered via changes in copy number or modifications to the DNA decoy site sequence. Using arginine biosynthesis as a showcase, we observed a 16-fold increase in arginine production when we introduced the decoy system to steer metabolic flux towards increased arginine biosynthesis, with negligible growth differences compared to the wild type strain. The decoy-based production strain retains high genetic integrity; in contrast to a gene knock-out approach where mutations were common, we detected no mutations in the production system using the decoy-based strain. We further show that transcription factor decoys are amenable to multiplexed library screening by demonstrating enhanced tolerance to pinene with a combinatorial decoy library. Our study shows that transcription factor decoy binding sites are a powerful and compact tool for metabolic engineering.

Dynamic Cell Programming with Quorum Sensing-Controlled CRISPRi Circuit

Synthetic biology is enabling rapid advances in the areas of biomanufacturing and live therapeutics. Dynamic circuits that can be used to regulate cellular resources and microbial community behavior represent a defining focus of synthetic biology, and have attracted tremendous interest. However, the existing dynamic circuits are mostly gene editing-dependent or cell lysis-based, which limits their broad and convenient application, and in some cases, such lysis-based circuits can suffer from genetic instability due to evolution. There is limited research in quorum sensing-assisted CRISPRi, which can function in a gene editing-independent manner. Here, we constructed a series of quorum sensing controlled CRISPRi systems (Q-CRISPRi), which can dynamically program bacteria by using customized sgRNA without introducing cell lysis. We successfully applied Q-CRISPRi circuits to dynamically program gene expression, population density, phenotype, physical property, and community composition of microbial consortia. The strategies reported here represent methods for dynamic cell programming and could be effective in programming industrially and medically important microorganisms to offer better control of their metabolism and behavior.

Toward fine-tuned metabolic networks in industrial microorganisms

There are numerous microorganisms in nature capable of synthesizing diverse useful compounds; however, these natural microorganisms are generally inefficient in the production of target products on an industrial scale, relative to either chemical synthesis or extraction methods. To achieve industrial production of useful compounds, these natural microorganisms must undergo a certain degree of mutation or effective fine-tuning strategies. This review describes how to achieve an ideal metabolic fine-tuned process, including static control strategies and dynamic control strategies. The static control strategies mainly focus on various matabolic engineering strategies, including protein engineering, upregulation/downregulation, and combinatrorial control of these metabolic engineering strategies, to enhance the flexibility of their application in fine-tuned metabolic metworks. Then, we focus on the dynamic control strategies for fine-tuned metabolic metworks. The design principles derived would guide us to construct microbial cell factories for various useful compounds.

Application of combinatorial optimization strategies in synthetic biology

In the first wave of synthetic biology, genetic elements, combined into simple circuits, are used to control individual cellular functions. In the second wave of synthetic biology, the simple circuits, combined into complex circuits, form systems-level functions. However, efforts to construct complex circuits are often impeded by our limited knowledge of the optimal combination of individual circuits. For example, a fundamental question in most metabolic engineering projects is the optimal level of enzymes for maximizing the output. To address this point, combinatorial optimization approaches have been established, allowing automatic optimization without prior knowledge of the best combination of expression levels of individual genes. This review focuses on current combinatorial optimization methods and emerging technologies facilitating their applications.

High-throughput enrichment of temperature-sensitive argininosuccinate synthetase for two-stage citrulline production in E. coli

Controlling metabolism of engineered microbes is important to modulate cell growth and production during a bioprocess. For example, external parameters such as light, chemical inducers, or temperature can act on metabolism of production strains by changing the abundance or activity of enzymes. Here, we created temperature-sensitive variants of an essential enzyme in arginine biosynthesis of Escherichia coli (argininosuccinate synthetase, ArgG) and used them to dynamically control citrulline overproduction and growth of E. coli. We show a method for high-throughput enrichment of temperature-sensitive ArgG variants with a fluorescent TIMER protein and flow cytometry. With 90 of the thus derived ArgG variants, we complemented an ArgG deletion strain showing that 90% of the strains exhibit temperature-sensitive growth and 69% of the strains are auxotrophic for arginine at 42 °C and prototrophic at 30 °C. The best temperature-sensitive ArgG variant enabled precise and tunable control of cell growth by temperature changes. Expressing this variant in a feedback-dysregulated E. coli strain allowed us to realize a two-stage bioprocess: a 33 °C growth-phase for biomass accumulation and a 39 °C stationary-phase for citrulline production. With this two-stage strategy, we produced 3 g/L citrulline during 45 h cultivation in a 1-L bioreactor. These results show that temperature-sensitive enzymes can be created en masse and that they may function as metabolic valves in engineered bacteria.

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Method to enrich temperature-sensitive enzymes en masse.

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Temperature-sensitive enzymes function as metabolic valve.

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Temperature controlled two-stage production of citrulline.