A new genome-scale metabolic model of Corynebacterium glutamicum and its application

Genome-scale metabolic network models for industrial microorganisms metabolic engineering: Current advances and future prospects

The construction of high-performance microbial cell factories (MCFs) is the centerpiece of biomanufacturing. However, the complex metabolic regulatory network of microorganisms poses great challenges for the efficient design and construction of MCFs. The genome-scale metabolic network models (GSMs) can systematically simulate the metabolic regulation process of microorganisms in silico, providing effective guidance for the rapid design and construction of MCFs. In this review, we summarized the development status of 16 important industrial microbial GSMs, and further outline the technologies or methods that continuously promote high-quality GSMs construction from five aspects: I) Databases and modeling tools facilitate GSMs reconstruction; II) evolving gap-filling technologies; III) constraint-based model reconstruction; IV) advances in algorithms; and V) developed visualization tools. In addition, we also summarized the applications of GSMs in guiding metabolic engineering from four aspects: I) exploring and explaining metabolic features; II) predicting the effects of genetic perturbations on metabolism; III) predicting the optimal phenotype; IV) guiding cell factories construction in practical experiment. Finally, we discussed the development of GSMs, aiming to provide a reference for efficiently reconstructing GSMs and guiding metabolic engineering.

Model-guided metabolic rewiring to bypass pyruvate oxidation for pyruvate derivative synthesis by minimizing carbon loss

Engineering microbial hosts to synthesize pyruvate derivatives depends on blocking pyruvate oxidation, thereby causing severe growth defects in aerobic glucose-based bioprocesses. To decouple pyruvate metabolism from cell growth to improve pyruvate availability, a genome-scale metabolic model combined with constraint-based flux balance analysis, geometric flux balance analysis, and flux variable analysis was used to identify genetic targets for strain design. Using translation elements from a ~3,000 cistronic library to modulate fxpK expression in a bicistronic cassette, a bifido shunt pathway was introduced to generate three molecules of non-pyruvate-derived acetyl-CoA from one molecule of glucose, bypassing pyruvate oxidation and carbon dioxide generation. The dynamic control of flux distribution by T7 RNAP-mediated synthetic small RNA decoupled pyruvate catabolism from cell growth. Adaptive laboratory evolution and multi-omics analysis revealed that a mutated isocitrate dehydrogenase functioned as a metabolic switch to activate the glyoxylate shunt as the only C4 anaplerotic pathway to generate malate from two molecules of acetyl-CoA input and bypass two decarboxylation reactions in the tricarboxylic acid cycle. A chassis strain for pyruvate derivative synthesis was constructed to reduce carbon loss by using the glyoxylate shunt as the only C4 anaplerotic pathway and the bifido shunt as a non-pyruvate-derived acetyl-CoA synthetic pathway and produced 22.46, 27.62, and 6.28 g/L of l-leucine, l-alanine, and l-valine by a controlled small RNA switch, respectively. Our study establishes a novel metabolic pattern of glucose-grown bacteria to minimize carbon loss under aerobic conditions and provides valuable insights into cell design for manufacturing pyruvate-derived products.IMPORTANCEBio-manufacturing from biomass-derived carbon sources using microbes as a cell factory provides an eco-friendly alternative to petrochemical-based processes. Pyruvate serves as a crucial building block for the biosynthesis of industrial chemicals; however, it is different to improve pyruvate availability in vivo due to the coupling of pyruvate-derived acetyl-CoA with microbial growth and energy metabolism via the oxidative tricarboxylic acid cycle. A genome-scale metabolic model combined with three algorithm analyses was used for strain design. Carbon metabolism was reprogrammed using two genetic control tools to fine-tune gene expression. Adaptive laboratory evolution and multi-omics analysis screened the growth-related regulatory targets beyond rational design. A novel metabolic pattern of glucose-grown bacteria is established to maintain growth fitness and minimize carbon loss under aerobic conditions for the synthesis of pyruvate-derived products. This study provides valuable insights into the design of a microbial cell factory for synthetic biology to produce industrial bio-products of interest.

Co-Cultivated Enzyme Constraint Metabolic Network Model for Rational Guidance in Constructing Synthetic Consortia to Achieve Optimal Pathway Allocation Prediction

Synthetic consortia have emerged as a promising biosynthetic platform that offers new opportunities for biosynthesis. Genome-scale metabolic network models (GEMs) with complex constraints are extensively utilized to guide the synthesis in monocultures. However, few methods are currently available to guide the rational construction of synthetic consortia for predicting the optimal allocation strategy of synthetic pathways aimed at enhancing product synthesis. A standardized method to construct the co-cultivated Enzyme Constraint metabolic network model (CulECpy) is proposed, which integrates enzyme constraints and modular interaction scale constraints based on the research concept of "independent + global". This method is applied to construct several synthetic consortia models, which encompassed different target products, strains, synthetic pathways, and compositional structures. Analyzing the model, the optimal pathway allocation and initial inoculum ratio that enhance the synthesis of target products by synthetic consortia are predicted and verified. When comparing with the constructed co-culture synthesis system, the normalized root mean square error of all optimal theoretical yield simulations is found to be less than or equal to 0.25. The analyses and verifications demonstrate that the method CulECpy can guide the rational construction of synthetic consortia systems to facilitate biochemical synthesis.

Rapid screening of point mutations by mismatch amplification mutation assay PCR

Metabolic engineering frequently makes use of point mutation and saturation mutation library creation. At present, sequencing is the only reliable and direct technique to detect point mutation and screen saturation mutation library. In this study, mismatch amplification mutation assay (MAMA) PCR was used to detect point mutation and screen saturation mutation library. In order to fine-tune the expression of odhA encoding 2-oxoglutarate dehydrogenase E1 component, a saturating mutant library of the RBS of odhA was created in Corynebacterium glutamicum P12 based on the CRISPR-Cas2a genome editing system, which increased the L-proline production by 81.3%. MAMA PCR was used to filter out 42% of the non-mutant transformants in the mutant library, which effectively reduced the workload of the subsequent fermentation test and the number of sequenced samples. The rapid and sensitive MAMA-PCR method established in this study provides a general strategy for detecting point mutations and improving the efficiency of mutation library screening. KEY POINTS: • MAMA PCR was optimized and developed to detect point mutation. • MAMA PCR greatly improves the screening efficiency of point mutation. • Attenuation of odhA expression in P12 effectively improves proline production.

Structure-based functional analysis of a novel NADPH-producing glyceraldehyde-3-phosphate dehydrogenase from Corynebacterium glutamicum

Corynebacterium glutamicum is an industrial workhorse applied in the production of valuable biochemicals. In the process of bio-based chemical production, improving cofactor recycling and mitigating cofactor imbalance are considered major solutions for enhancing the production yield and efficiency. Although, glyceraldehyde-3-phosphate dehydrogenase (GapDH), a glycolytic enzyme, can be a promising candidate for a sufficient NADPH cofactor supply, however, most microorganisms have only NAD-dependent GapDHs. In this study, we performed functional characterization and structure determination of novel NADPH-producing GapDH from C. glutamicum (CgGapX). Based on the crystal structure of CgGapX in complex with NADP cofactor, the unique structural features of CgGapX for NADP stabilization were elucidated. Also, N-terminal additional region (Auxiliary domain, AD) appears to have an effect on enzyme stabilization. In addition, through structure-guided enzyme engineering, we developed a CgGapX variant that exhibited 4.3-fold higher kcat, and 1.2-fold higher kcat/KM values when compared with wild-type. Furthermore, a bioinformatic analysis of 100 GapX-like enzymes from 97 microorganisms in the KEGG database revealed that the GapX-like enzymes possess a variety of AD, which seem to determine enzyme stability. Our findings are expected to provide valuable information for supplying NADPH cofactor pools in bio-based value-added chemical production.

Enhanced L-serine production by Corynebacterium glutamicum based on novel insights into L-serine exporters

The L-serine exporters ThrE and SerE play important roles in L-serine production by Corynebacterium glutamicum. Deletion of both thrE and serE decreased L-serine titer by 60%, suggesting the existence of other L-serine exporters. A comparative transcriptomics identified NCgl0254 and NCgl0255 as novel L-serine exporters. Further analysis of the contributions of ThrE, SerE, NCgl0254, and NCgl0255 found that SerE was the major L-serine exporter in C. glutamicum and these four L-serine exporters were responsible for 79.7% of L-serine export. Deletion of one L-serine exporter upregulated the transcription levels of the other three, which might be coursed by increased intracellular concentrations of L-serine. Overexpression of NCgl0254 and NCgl0255 increased L-serine titer by 20.8% in C. glutamicum A36, while overexpression of the four L-serine exporters increased L-serine production by 31.9% (41.1 g·L-1 ) in C. glutamicum A36. The identification of novel L-serine exporters in C. glutamicum will help to improve industrial production of L-serine.

Engineering Corynebacterium glutamicum for the efficient production of N-acetylglucosamine

N-acetylglucosamine (GlcNAc) is significant functional monosaccharides with diverse applications in medicine, food, and cosmetics. In this study, the GlcNAc synthesis pathway was constructed in Corynebacterium glutamicum and its reverse byproduct pathways were blocked. Simultaneously the driving force of GlcNAc synthesis was enhanced by screening key gene sources and inhibiting the GlcNAc consumption pathway. To maximize carbon flux, some competitive pathways (Pentose phosphate pathway, Glycolysis pathway and Mannose pathway) were weakened and the titer of GlcNAc reached 23.30 g/L in shake flasks. Through transcriptome analysis, it was found that dissolved oxygen was an important limiting factor, which was optimized in a 5 L bioreactor. Employing optimal fermentation conditions and feeding strategy, the titer of GlcNAc reached 138.9 g/L, with the yeild of 0.44 g/g glucose. This study significantly increased the yield and titer of GlcNAc, which lay a solid foundation for the industrial production of GlcNAc in C. glutamicum.

Characterization of the enzyme kinetics of EMP and HMP pathway in Corynebacterium glutamicum: reference for modeling metabolic networks

The model of intracellular metabolic network based on enzyme kinetics parameters plays an important role in understanding the intracellular metabolic process of Corynebacterium glutamicum, and constructing such a model requires a large number of enzymological parameters. In this work, the genes encoding the relevant enzymes of the EMP and HMP metabolic pathways from Corynebacterium glutamicum ATCC 13032 were cloned, and engineered strains for protein expression with E.coli BL21 and P.pastoris X33 as hosts were constructed. The twelve enzymes (GLK, GPI, TPI, GAPDH, PGK, PMGA, ENO, ZWF, RPI, RPE, TKT, and TAL) were successfully expressed and purified by Ni2+ chelate affinity chromatography in their active forms. In addition, the kinetic parameters (V max, K m, and K cat) of these enzymes were measured and calculated at the same pH and temperature. The kinetic parameters of enzymes associated with EMP and the HMP pathway were determined systematically and completely for the first time in C.glutamicum. These kinetic parameters enable the prediction of key enzymes and rate-limiting steps within the metabolic pathway, and support the construction of a metabolic network model for important metabolic pathways in C.glutamicum. Such analyses and models aid in understanding the metabolic behavior of the organism and can guide the efficient production of high-value chemicals using C.glutamicum as a host.

Elucidating the impact of in vitro cultivation on Nicotiana tabacum metabolism through combined in silico modeling and multiomics analysis

The systematical characterization and understanding of the metabolic behaviors are the basis of the efficient plant metabolic engineering and synthetic biology. Genome-scale metabolic networks (GSMNs) are indispensable tools for the comprehensive characterization of overall metabolic profile. Here we first constructed a GSMN of tobacco, which is one of the most widely used plant chassis, and then combined the tobacco GSMN and multiomics analysis to systematically elucidate the impact of in-vitro cultivation on the tobacco metabolic network. In-vitro cultivation is a widely used technique for plant cultivation, not only in the field of basic research but also for the rapid propagation of valuable horticultural and pharmaceutical plants. However, the systemic effects of in-vitro cultivation on overall plant metabolism could easily be overlooked and are still poorly understood. We found that in-vitro tobacco showed slower growth, less biomass and suppressed photosynthesis than soil-grown tobacco. Many changes of metabolites and metabolic pathways between in-vitro and soil-grown tobacco plants were identified, which notably revealed a significant increase of the amino acids content under in-vitro condition. The in silico investigation showed that in-vitro tobacco downregulated photosynthesis and primary carbon metabolism, while significantly upregulated the GS/GOGAT cycle, as well as producing more energy and less NADH/NADPH to acclimate in-vitro growth demands. Altogether, the combination of experimental and in silico analyses offers an unprecedented view of tobacco metabolism, with valuable insights into the impact of in-vitro cultivation, enabling more efficient utilization of in-vitro techniques for plant propagation and metabolic engineering.

Can Genome Sequencing Coupled to Flux Balance Analyses Offer Precision Guidance for Industrial Strain Development? The Lessons from Carbon Trafficking in Corynebacterium glutamicum ATCC 21573

Systems biology tools offer new prospects for industrial strain selection. For bacteria that are significant for industrial applications, whole-genome sequencing coupled to flux balance analysis (FBA) can help unpack the complex relationships between genome mutations and carbon trafficking. This work investigates the l-tyrosine (l-Tyr) overproducing model system Corynebacterium glutamicum ATCC 21573 with an eye to more rational and precision strain development. Using genome-wide mutational analysis of C. glutamicum, we identified 27,611 single nucleotide polymorphisms and 479 insertion/deletion mutations. Mutations in the carbon uptake machinery have led to phosphotransferase system-independent routes as corroborated with FBA. Mutations within the central carbon metabolism of C. glutamicum impaired the carbon flux, as evidenced by the lower growth rate. The entry to and flow through the tricarboxylic acid cycle was affected by mutations in pyruvate and α-ketoglutarate dehydrogenase complexes, citrate synthase, and isocitrate dehydrogenase. FBA indicated that the estimated flux through the shikimate pathway became larger as the l-Tyr production rate increased. In addition, protocatechuate export was probabilistically impossible, which could have contributed to the l-Tyr accumulation. Interestingly, aroG and cg0975, which have received previous attention for aromatic amino acid overproduction, were not mutated. From the branch point molecule, prephenate, the change in the promoter region of pheA could be an influential contributor. In summary, we suggest that genome sequencing coupled with FBA is well poised to offer rational guidance for industrial strain development, as evidenced by these findings on carbon trafficking in C. glutamicum ATCC 21573.

Automating the design-build-test-learn cycle towards next-generation bacterial cell factories

Automation is playing an increasingly significant role in synthetic biology. Groundbreaking technologies, developed over the past 20 years, have enormously accelerated the construction of efficient microbial cell factories. Integrating state-of-the-art tools (e.g. for genome engineering and analytical techniques) into the design-build-test-learn cycle (DBTLc) will shift the metabolic engineering paradigm from an almost artisanal labor towards a fully automated workflow. Here, we provide a perspective on how a fully automated DBTLc could be harnessed to construct the next-generation bacterial cell factories in a fast, high-throughput fashion. Innovative toolsets and approaches that pushed the boundaries in each segment of the cycle are reviewed to this end. We also present the most recent efforts on automation of the DBTLc, which heralds a fully autonomous pipeline for synthetic biology in the near future.

Kluyveromyces as promising yeast cell factories for industrial bioproduction: From bio-functional design to applications

As the two most widely used Kluyveromyces yeast, Kluyveromyces marxianus and K. lactis have gained increasing attention as microbial chassis in biocatalysts, biomanufacturing and the utilization of low-cost raw materials owing to their high suitability to these applications. However, due to slow progress in the development of molecular genetic manipulation tools and synthetic biology strategies, Kluyveromyces yeast cell factories as biological manufacturing platforms have not been fully developed. In this review, we provide a comprehensive overview of the attractive characteristics and applications of Kluyveromyces cell factories, with special emphasis on the development of molecular genetic manipulation tools and systems engineering strategies for synthetic biology. In addition, future avenues in the development of Kluyveromyces cell factories for the utilization of simple carbon compounds as substrates, the dynamic regulation of metabolic pathways, and for rapid directed evolution of robust strains are proposed. We expect that more synthetic systems, synthetic biology tools and metabolic engineering strategies will adapt to and optimize for Kluyveromyces cell factories to achieve green biofabrication of multiple products with higher efficiency.

Systems biology elucidates the distinctive metabolic niche filled by the human gut microbe Eggerthella lenta

Human gut bacteria perform diverse metabolic functions with consequences for host health. The prevalent and disease-linked Actinobacterium Eggerthella lenta performs several unusual chemical transformations, but it does not metabolize sugars and its core growth strategy remains unclear. To obtain a comprehensive view of the metabolic network of E. lenta, we generated several complementary resources: defined culture media, metabolomics profiles of strain isolates, and a curated genome-scale metabolic reconstruction. Stable isotope-resolved metabolomics revealed that E. lenta uses acetate as a key carbon source while catabolizing arginine to generate ATP, traits which could be recapitulated in silico by our updated metabolic model. We compared these in vitro findings with metabolite shifts observed in E. lenta-colonized gnotobiotic mice, identifying shared signatures across environments and highlighting catabolism of the host signaling metabolite agmatine as an alternative energy pathway. Together, our results elucidate a distinctive metabolic niche filled by E. lenta in the gut ecosystem. Our culture media formulations, atlas of metabolomics data, and genome-scale metabolic reconstructions form a freely available collection of resources to support further study of the biology of this prevalent gut bacterium.

Machine learning for metabolic pathway optimization: A review

Optimizing the metabolic pathways of microbial cell factories is essential for establishing viable biotechnological production processes. However, due to the limited understanding of the complex setup of cellular machinery, building efficient microbial cell factories remains tedious and time-consuming. Machine learning (ML), a powerful tool capable of identifying patterns within large datasets, has been used to analyze biological datasets generated using various high-throughput technologies to build data-driven models for complex bioprocesses. In addition, ML can also be integrated with Design-Build-Test-Learn to accelerate development. This review focuses on recent ML applications in genome-scale metabolic model construction, multistep pathway optimization, rate-limiting enzyme engineering, and gene regulatory element designing. In addition, we have discussed some limitations of these methods as well as potential solutions.

Systematizing Microbial Bioplastic Production for Developing Sustainable Bioeconomy: Metabolic Nexus Modeling, Economic and Environmental Technologies Assessment

The excessive usage of non-renewable resources to produce plastic commodities has incongruously influenced the environment's health. Especially in the times of COVID-19, the need for plastic-based health products has increased predominantly. Given the rise in global warming and greenhouse gas emissions, the lifecycle of plastic has been established to contribute to it significantly. Bioplastics such as polyhydroxy alkanoates, polylactic acid, etc. derived from renewable energy origin have been a magnificent alternative to conventional plastics and reconnoitered exclusively for combating the environmental footprint of petrochemical plastic. However, the economically reasonable and environmentally friendly procedure of microbial bioplastic production has been a hard nut to crack due to less scouted and inefficient process optimization and downstream processing methodologies. Thereby, meticulous employment of computational tools such as genome-scale metabolic modeling and flux balance analysis has been practiced in recent times to understand the effect of genomic and environmental perturbations on the phenotype of the microorganism. In-silico results not only aid us in determining the biorefinery abilities of the model microorganism but also curb our reliance on equipment, raw materials, and capital investment for optimizing the best conditions. Additionally, to accomplish sustainable large-scale production of microbial bioplastic in a circular bioeconomy, extraction, and refinement of bioplastic needs to be investigated extensively by practicing techno-economic analysis and life cycle assessment. This review put forth state-of-the-art know-how on the proficiency of these computational techniques in laying the foundation of an efficient bioplastic manufacturing blueprint, chiefly focusing on microbial polyhydroxy alkanoates (PHA) production and its efficacy in outplacing fossil based plastic products.

Biosystem design of Corynebacterium glutamicum for bioproduction

Corynebacterium glutamicum, a natural glutamate-producing bacterium adopted for industrial production of amino acids, has been extensively explored recently for high-level biosynthesis of amino acid derivatives, bulk chemicals such as organic acids and short-chain alcohols, aromatics, and natural products, including polyphenols and terpenoids. Here, we review the recent advances with a focus on biosystem design principles, metabolic characterization and modeling, omics analysis, utilization of nonmodel feedstock, emerging CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) tools for Corynebacterium strain engineering, biosensors, and novel strains of C. glutamicum. Future research directions for developing C. glutamicum cell factories are also discussed.

Construction and Analysis of an Enzyme-Constrained Metabolic Model of Corynebacterium glutamicum

The genome-scale metabolic model (GEM) is a powerful tool for interpreting and predicting cellular phenotypes under various environmental and genetic perturbations. However, GEM only considers stoichiometric constraints, and the simulated growth and product yield values will show a monotonic linear increase with increasing substrate uptake rate, which deviates from the experimentally measured values. Recently, the integration of enzymatic constraints into stoichiometry-based GEMs was proven to be effective in making novel discoveries and predicting new engineering targets. Here, we present the first genome-scale enzyme-constrained model (ecCGL1) for Corynebacterium glutamicum reconstructed by integrating enzyme kinetic data from various sources using a ECMpy workflow based on the high-quality GEM of C. glutamicum (obtained by modifying the iCW773 model). The enzyme-constrained model improved the prediction of phenotypes and simulated overflow metabolism, while also recapitulating the trade-off between biomass yield and enzyme usage efficiency. Finally, we used the ecCGL1 to identify several gene modification targets for l-lysine production, most of which agree with previously reported genes. This study shows that incorporating enzyme kinetic information into the GEM enhances the cellular phenotypes prediction of C. glutamicum, which can help identify key enzymes and thus provide reliable guidance for metabolic engineering.

Designing Microbial Cell Factories for the Production of Chemicals

The sustainable production of chemicals from renewable, nonedible biomass has emerged as an essential alternative to address pressing environmental issues arising from our heavy dependence on fossil resources. Microbial cell factories are engineered microorganisms harboring biosynthetic pathways streamlined to produce chemicals of interests from renewable carbon sources. The biosynthetic pathways for the production of chemicals can be defined into three categories with reference to the microbial host selected for engineering: native-existing pathways, nonnative-existing pathways, and nonnative-created pathways. Recent trends in leveraging native-existing pathways, discovering nonnative-existing pathways, and designing de novo pathways (as nonnative-created pathways) are discussed in this Perspective. We highlight key approaches and successful case studies that exemplify these concepts. Once these pathways are designed and constructed in the microbial cell factory, systems metabolic engineering strategies can be used to improve the performance of the strain to meet industrial production standards. In the second part of the Perspective, current trends in design tools and strategies for systems metabolic engineering are discussed with an eye toward the future. Finally, we survey current and future challenges that need to be addressed to advance microbial cell factories for the sustainable production of chemicals.

Model-Guided Metabolic Rewiring for Gamma-Aminobutyric Acid and Butyrolactam Biosynthesis in Corynebacterium glutamicum ATCC13032

Gamma-aminobutyric acid (GABA) can be used as a bioactive component in the pharmaceutical industry and a precursor for the synthesis of butyrolactam, which functions as a monomer for the synthesis of polyamide 4 (nylon 4) with improved thermal stability and high biodegradability. The bio-based fermentation production of chemicals using microbes as a cell factory provides an alternative to replace petrochemical-based processes. Here, we performed model-guided metabolic engineering of Corynebacterium glutamicum for GABA and butyrolactam fermentation. A GABA biosynthetic pathway was constructed using a bi-cistronic expression cassette containing mutant glutamate decarboxylase. An in silico simulation showed that the increase in the flux from acetyl-CoA to α-ketoglutarate and the decrease in the flux from α-ketoglutarate to succinate drove more flux toward GABA biosynthesis. The TCA cycle was reconstructed by increasing the expression of acn and icd genes and deleting the sucCD gene. Blocking GABA catabolism and rewiring the transport system of GABA further improved GABA production. An acetyl-CoA-dependent pathway for in vivo butyrolactam biosynthesis was constructed by overexpressing act-encoding ß-alanine CoA transferase. In fed-batch fermentation, the engineered strains produced 23.07 g/L of GABA with a yield of 0.52 mol/mol from glucose and 4.58 g/L of butyrolactam. The metabolic engineering strategies can be used for genetic modification of industrial strains to produce target chemicals from α-ketoglutarate as a precursor, and the engineered strains will be useful to synthesize the bio-based monomer of polyamide 4 from renewable resources.

Fermentative Indole Production via Bacterial Tryptophan Synthase Alpha Subunit and Plant Indole-3-Glycerol Phosphate Lyase Enzymes

Indole is produced in nature by diverse organisms and exhibits a characteristic odor described as animal, fecal, and floral. In addition, it contributes to the flavor in foods, and it is applied in the fragrance and flavor industry. In nature, indole is synthesized either from tryptophan by bacterial tryptophanases (TNAs) or from indole-3-glycerol phosphate (IGP) by plant indole-3-glycerol phosphate lyases (IGLs). While it is widely accepted that the tryptophan synthase α-subunit (TSA) has intrinsically low IGL activity in the absence of the tryptophan synthase β-subunit, in this study, we show that Corynebacterium glutamicum TSA functions as a bona fide IGL and can support fermentative indole production in strains providing IGP. By bioprospecting additional bacterial TSAs and plant IGLs that function as bona fide IGLs were identified. Capturing indole in an overlay enabled indole production to titers of about 0.7 g L^-1 in fermentations using C. glutamicum strains expressing either the endogenous TSA gene or the IGL gene from wheat.

Improved the lipopeptide production of Bacillus amyloliquefaciens HM618 under co-culture with the recombinant Corynebacterium glutamicum producing high-level proline

The application of antibacterial lipopeptides is limited by high cost and low yield. Herein, the exogenous L-proline significantly improved lipopeptide production by Bacillus amyloliquefaciens HM618. A recombinant Corynebacterium glutamicum producing high levels of proline using genetically modifying proB and putA was used to establish consortium, to improve lipopeptide production of strain HM618. Compared to a pure culture, the levels of iturin A, fengycin, and surfactin in consortium reached 67.75, 39.32, and 37.25 mg L^-1, respectively, an increase of 3.19-, 2.05-, and 1.63-fold over that produced by co-cultures of B. amyloliquefaciens and recombinant C. glutamicum with normal medium. Commercial amylase and recombinant Pichia pastoris with a heterologous amylase gene were used to hydrolyze kitchen waste. A three-strain consortium with recombinant P. pastoris and C. glutamicum increased the lipopeptide production of strain HM618 in medium containing KW. This work provides new strategies to improve lipopeptide production by B. amyloliquefaciens.

Production of indole by Corynebacterium glutamicum microbial cell factories for flavor and fragrance applications

Background

The nitrogen containing aromatic compound indole is known for its floral odor typical of jasmine blossoms. Due to its characteristic scent, it is frequently used in dairy products, tea drinks and fine fragrances. The demand for natural indole by the flavor and fragrance industry is high, yet, its abundance in essential oils isolated from plants such as jasmine and narcissus is low. Thus, there is a strong demand for a sustainable method to produce food-grade indole.

Results

Here, we established the biotechnological production of indole upon l-tryptophan supplementation in the bacterial host Corynebacterium glutamicum. Heterologous expression of the tryptophanase gene from E. coli enabled the conversion of supplemented l-tryptophan to indole. Engineering of the substrate import by co-expression of the native aromatic amino acid permease gene aroP increased whole-cell biotransformation of l-tryptophan to indole by two-fold. Indole production to 0.2 g L⁻¹ was achieved upon feeding of 1 g L⁻¹l-tryptophan in a bioreactor cultivation, while neither accumulation of side-products nor loss of indole were observed. To establish an efficient and robust production process, new tryptophanases were recruited by mining of bacterial sequence databases. This search retrieved more than 400 candidates and, upon screening of tryptophanase activity, nine new enzymes were identified as most promising. The highest production of indole in vivo in C. glutamicum was achieved based on the tryptophanase from Providencia rettgeri. Evaluation of several biological aspects identified the product toxicity as major bottleneck of this conversion. In situ product recovery was applied to sequester indole in a food-grade organic phase during the fermentation to avoid inhibition due to product accumulation. This process enabled complete conversion of l-tryptophan and an indole product titer of 5.7 g L⁻¹ was reached. Indole partitioned to the organic phase which contained 28 g L⁻¹ indole while no other products were observed indicating high indole purity.

Conclusions

The bioconversion production process established in this study provides an attractive route for sustainable indole production from tryptophan in C. glutamicum. Industrially relevant indole titers were achieved within 24 h and indole was concentrated in the organic layer as a pure product after the fermentation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01771-y.

CRISPR-assisted rational flux-tuning and arrayed CRISPRi screening of an L-proline exporter for L-proline hyperproduction

Development of hyperproducing strains is important for biomanufacturing of biochemicals and biofuels but requires extensive efforts to engineer cellular metabolism and discover functional components. Herein, we optimize and use the CRISPR-assisted editing and CRISPRi screening methods to convert a wild-type Corynebacterium glutamicum to a hyperproducer of L-proline, an amino acid with medicine, feed, and food applications. To facilitate L-proline production, feedback-deregulated variants of key biosynthetic enzyme γ-glutamyl kinase are screened using CRISPR-assisted single-stranded DNA recombineering. To increase the carbon flux towards L-proline biosynthesis, flux-control genes predicted by in silico analysis are fine-tuned using tailored promoter libraries. Finally, an arrayed CRISPRi library targeting all 397 transporters is constructed to discover an L-proline exporter Cgl2622. The final plasmid-, antibiotic-, and inducer-free strain produces L-proline at the level of 142.4 g/L, 2.90 g/L/h, and 0.31 g/g. The CRISPR-assisted strain development strategy can be used for engineering industrial-strength strains for efficient biomanufacturing.

Synthesis of C2-C4 diols from bioresources: Pathways and metabolic intervention strategies

Diols are important platform chemicals with extensive industrial applications in biopolymer synthesis, cosmetics, and fuels. The increased dependence on non-renewable sources to meet the energy requirement of the population raised issues regarding fossil fuel depletion and environmental impacts. The utilization of biological methods for the synthesis of diols by utilizing renewable resources such as glycerol and agro-residual wastes gained attention worldwide because of its advantages. Among these, biotransformation of 1,3-propanediol (1,3-PDO) and 2,3-butanediol (2,3-BDO) were extensively studied and at present, these diols are produced commercially in large scale with high yield. Many important isomers of C2-C4 diols lack natural synthetic pathways and development of chassis strains for the synthesis can be accomplished by adopting synthetic biology approaches. This current review depicts an overall idea about the pathways involved in C2-C4 diol production, metabolic intervention strategies and technologies in recent years.

Synthetic Biology Toolkits and Metabolic Engineering Applied in Corynebacterium glutamicum for Biomanufacturing

Corynebacterium glutamicum is an important workhorse in industrial white biotechnology. It has been widely applied in the producing processes of amino acids, fuels, and diverse value-added chemicals. With the continuous disclosure of genetic regulation mechanisms, various strategies and technologies of synthetic biology were used to design and construct C. glutamicum cells for biomanufacturing and bioremediation. This study mainly aimed to summarize the design and construction strategies of C. glutamicum-engineered strains, which were based on genomic modification, synthetic biological device-assisted metabolic flux optimization, and directed evolution-based engineering. Then, taking two important bioproducts (N-acetylglucosamine and hyaluronic acid) as examples, the applications of C. glutamicum cell factories were introduced. Finally, we discussed the current challenges and future development trends of C. glutamicum-engineered strain construction.

MarR-type transcription factor RosR regulates glutamate metabolism network and promotes accumulation of L-glutamate in Corynebacterium glutamicum G01

Transcription factors (TFs) perform a crucial function in the regulation of amino acids biosynthesis. Here, TFs involved in L-glutamate biosynthesis in Corynebacterium glutamicum were investigated. Compared to transcriptomic results of C. glutamicum 13032, 7 TFs regulated to glutamate biosynthesis were indentifed in G01 and E01. Among them, RosR was demonstrated to regulate L-glutamate metabolic network by binding to the promoters of glnA, pqo, ilvB, ilvN, ilvC, ldhA, odhA, dstr1, fas, argJ, ak and pta. Overexpression of RosR in G01 resulted in significantly decreased by-products yield and improved L-glutamate titer (130.6 g/L) and yield (0.541 g/g from glucose) in fed-batch fermentation. This study demonstrated the L-glutamate production improved by the expression of TFs in C. glutamicum, which provided a good reference for the transcriptional regulation engineering of strains for amino acid biosynthesis and suggested further metabolic engineering of C. glutamicum for L-glutamate production.

High-Quality Genome-Scale Reconstruction of Corynebacterium glutamicum ATCC 13032

Corynebacterium glutamicum belongs to the microbes of enormous biotechnological relevance. In particular, its strain ATCC 13032 is a widely used producer of L-amino acids at an industrial scale. Its apparent robustness also turns it into a favorable platform host for a wide range of further compounds, mainly because of emerging bio-based economies. A deep understanding of the biochemical processes in C. glutamicum is essential for a sustainable enhancement of the microbe's productivity. Computational systems biology has the potential to provide a valuable basis for driving metabolic engineering and biotechnological advances, such as increased yields of healthy producer strains based on genome-scale metabolic models (GEMs). Advanced reconstruction pipelines are now available that facilitate the reconstruction of GEMs and support their manual curation. This article presents iCGB21FR, an updated and unified GEM of C. glutamicum ATCC 13032 with high quality regarding comprehensiveness and data standards, built with the latest modeling techniques and advanced reconstruction pipelines. It comprises 1042 metabolites, 1539 reactions, and 805 genes with detailed annotations and database cross-references. The model validation took place using different media and resulted in realistic growth rate predictions under aerobic and anaerobic conditions. The new GEM produces all canonical amino acids, and its phenotypic predictions are consistent with laboratory data. The in silico model proved fruitful in adding knowledge to the metabolism of C. glutamicum: iCGB21FR still produces L-glutamate with the knock-out of the enzyme pyruvate carboxylase, despite the common belief to be relevant for the amino acid's production. We conclude that integrating high standards into the reconstruction of GEMs facilitates replicating validated knowledge, closing knowledge gaps, and making it a useful basis for metabolic engineering. The model is freely available from BioModels Database under identifier MODEL2102050001.

GPRuler: Metabolic gene-protein-reaction rules automatic reconstruction

Metabolic network models are increasingly being used in health care and industry. As a consequence, many tools have been released to automate their reconstruction process de novo. In order to enable gene deletion simulations and integration of gene expression data, these networks must include gene-protein-reaction (GPR) rules, which describe with a Boolean logic relationships between the gene products (e.g., enzyme isoforms or subunits) associated with the catalysis of a given reaction. Nevertheless, the reconstruction of GPRs still remains a largely manual and time consuming process. Aiming at fully automating the reconstruction process of GPRs for any organism, we propose the open-source python-based framework GPRuler. By mining text and data from 9 different biological databases, GPRuler can reconstruct GPRs starting either from just the name of the target organism or from an existing metabolic model. The performance of the developed tool is evaluated at small-scale level for a manually curated metabolic model, and at genome-scale level for three metabolic models related to Homo sapiens and Saccharomyces cerevisiae organisms. By exploiting these models as benchmarks, the proposed tool shown its ability to reproduce the original GPR rules with a high level of accuracy. In all the tested scenarios, after a manual investigation of the mismatches between the rules proposed by GPRuler and the original ones, the proposed approach revealed to be in many cases more accurate than the original models. By complementing existing tools for metabolic network reconstruction with the possibility to reconstruct GPRs quickly and with a few resources, GPRuler paves the way to the study of context-specific metabolic networks, representing the active portion of the complete network in given conditions, for organisms of industrial or biomedical interest that have not been characterized metabolically yet.

Production of l-glutamate family amino acids in Corynebacterium glutamicum: Physiological mechanism, genetic modulation, and prospects

l-glutamate family amino acids (GFAAs), consisting of l-glutamate, l-arginine, l-citrulline, l-ornithine, l-proline, l-hydroxyproline, γ-aminobutyric acid, and 5-aminolevulinic acid, are widely applied in the food, pharmaceutical, cosmetic, and animal feed industries, accounting for billions of dollars of market activity. These GFAAs have many functions, including being protein constituents, maintaining the urea cycle, and providing precursors for the biosynthesis of pharmaceuticals. Currently, the production of GFAAs mainly depends on microbial fermentation using Corynebacterium glutamicum (including its related subspecies Corynebacterium crenatum), which is substantially engineered through multistep metabolic engineering strategies. This review systematically summarizes recent advances in the metabolic pathways, regulatory mechanisms, and metabolic engineering strategies for GFAA accumulation in C. glutamicum and C. crenatum, which provides insights into the recent progress in l-glutamate-derived chemical production.

Insights on the Advancements of In Silico Metabolic Studies of Succinic Acid Producing Microorganisms: A Review with Emphasis on Actinobacillus succinogenes

Succinic acid (SA) is one of the top candidate value-added chemicals that can be produced from biomass via microbial fermentation. A considerable number of cell factories have been proposed in the past two decades as native as well as non-native SA producers. Actinobacillus succinogenes is among the best and earliest known natural SA producers. However, its industrial application has not yet been realized due to various underlying challenges. Previous studies revealed that the optimization of environmental conditions alone could not entirely resolve these critical problems. On the other hand, microbial in silico metabolic modeling approaches have lately been the center of attention and have been applied for the efficient production of valuable commodities including SA. Then again, literature survey results indicated the absence of up-to-date reviews assessing this issue, specifically concerning SA production. Hence, this review was designed to discuss accomplishments and future perspectives of in silico studies on the metabolic capabilities of SA producers. Herein, research progress on SA and A. succinogenes, pathways involved in SA production, metabolic models of SA-producing microorganisms, and status, limitations and prospects on in silico studies of A. succinogenes were elaborated. All in all, this review is believed to provide insights to understand the current scenario and to develop efficient mathematical models for designing robust SA-producing microbial strains.

Knowledge extraction from literature and enzyme sequences complements FBA analysis in metabolic engineering

Flux balance analysis (FBA) using genome-scale metabolic model (GSM) is a useful method for improving the bio-production of useful compounds. However, FBA often does not impose important constraints such as nutrients uptakes, by-products excretions and gases (oxygen and carbon dioxide) transfers. Furthermore, important information on metabolic engineering such as enzyme amounts, activities, and characteristics caused by gene expression and enzyme sequences is basically not included in GSM. Therefore, simple FBA is often not sufficient to search for metabolic manipulation strategies that are useful for improving the production of target compounds. In this study, we proposed a method using literature and enzyme search to complement the FBA-based metabolic manipulation strategies. As a case study, this method was applied to shikimic acid production by Corynebacterium glutamicum to verify its usefulness. As unique strategies in literature-mining, overexpression of the transcriptional regulator SugR and gene disruption related to by-products productions were complemented. In the search for alternative enzyme sequences, it was suggested that those candidates are searched for from various species based on features captured by deep learning, which are not simply homologous to amino acid sequences of the base enzymes.

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

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

Corynebacterium lizhenjunii sp. nov., isolated from the respiratory tract of Marmota himalayana, and Corynebacterium qintianiae sp. nov., isolated from the lung tissue of Pseudois nayaur

Four Gram-stain-positive, non-motile and asporous bacilli (strains ZJ-599^T, ZJ-621, MC1420^T and MC1482), isolated from animal tissue and environmental samples collected on the Qinghai-Tibet Plateau, PR China, were taxonomically characterized. Based on the results of 16S rRNA gene sequence analyses, the closest relatives of strains ZJ-599^T and ZJ-621 were Corynebacterium endometrii LMM-1653^T (97.5 %), Corynebacterium phocae M408/89/1^T (96.5 %) and Corynebacterium flavescens OJ8^T (96.3 %), whereas strains MC1420^T and MC1482 were closest to Corynebacterium sanguinis CCUG 58655^T (98.9 %), Corynebacterium mycetoides DSM 20632^T (98.4 %) and Corynebacterium lipophiloflavum DSM 44291^T (97.9 %). The results of rpoB gene sequence similarity analysis indicated that C. phocae M408/89/1^T and C. sanguinis CCUG 58655^T were closest to strains ZJ-599^T/ZJ-621 (83.5 %) and MC1420^T/MC1482 (91.8 %), respectively. The two novel type strains shared a similarity of 95.2 % in 16S rRNA and 81.3 % in rpoB gene sequences. The TAP-PCR DNA fingerprint and MALDI-TOF MS spectrum patterns clearly differentiated the novel isolates within and between each pair of strains. Strain ZJ-599^T had 21.9-22.4 % digital DNA-DNA hybridization (dDDH) scores with C. endometrii LMM-1653^T, C. phocae M408/89/1^T and C. flavescens OJ8^T, and 72.3-72.9 % of average nucleotide identity (ANI) with them. Similarly, strain MC1420^T had 22.9-23.7 % dDDH values with C. sanguinis CCUG 58655^T, C. mycetoides DSM 20632^T and C. lipophiloflavum DSM 44291^T, and 80.4-81.3 % ANI scores with them. Strain ZJ-599^T had a 23.1 % dDDH value and 70.5 % ANI score with strain MC1420^T, both below the corresponding thresholds for species delineation. Strains ZJ-599^T and MC1420^T both contain mycolic acids and have MK-8(H₂) and MK-9(H₂) as the predominant respiratory quinones, meso-diaminopimelic acid as the diagnostic diamino acid, and C_18 : 1  ω9c as the main fatty acid. C_17 : 1  ω8c and C_15 : 1  ω8c were predominant in strain ZJ-599^T in contrast to C_17 : 1  ω7c being predominant in strain MC1420^T. The main polar lipids in strain ZJ-599^T were diphosphatidylglycerol, phosphatidylinositol and one unidentified glycolipid, while strain MC1420^T had diphosphatidylglycerol, phosphatidylglycerol and one unidentified lipid as the major components. Since the two pairs of novel strains (ZJ-599^T/ZJ-621, MC1420^T/MC1482) distinctly differ from each other and from their nearest relatives, two novel species of the genus Corynebacterium are proposed, namely Corynebacterium lizhenjunii (type strain ZJ-599^T=GDMCC 1.1779^T=JCM 34341^T) and Corynebacterium qintianiae (type strain MC1420^T=GDMCC 1.1783^T=JCM 34340^T), respectively.

Metabolic engineering strategy for synthetizing trans-4-hydroxy-L-proline in microorganisms

Trans-4-hydroxy-L-proline is an important amino acid that is widely used in medicinal and industrial applications, particularly as a valuable chiral building block for the organic synthesis of pharmaceuticals. Traditionally, trans-4-hydroxy-L-proline is produced by the acidic hydrolysis of collagen, but this process has serious drawbacks, such as low productivity, a complex process and heavy environmental pollution. Presently, trans-4-hydroxy-L-proline is mainly produced via fermentative production by microorganisms. Some recently published advances in metabolic engineering have been used to effectively construct microbial cell factories that have improved the trans-4-hydroxy-L-proline biosynthetic pathway. To probe the potential of microorganisms for trans-4-hydroxy-L-proline production, new strategies and tools must be proposed. In this review, we provide a comprehensive understanding of trans-4-hydroxy-L-proline, including its biosynthetic pathway, proline hydroxylases and production by metabolic engineering, with a focus on improving its production.

De Novo Engineering of Corynebacterium glutamicum for l-Proline Production

l-Proline is an important amino acid that has various industrial applications. Industrial l-proline-producing strains are obtained by the mutagenesis of Corynebacterium glutamicum. In this study, the optimized C. glutamicum genome-editing tools were further applied in the de novo construction of a hyper-l-proline-producing strain. Overexpression of a feedback inhibition-resistant γ-glutamic kinase mutant ProBG149K, deletion of a proline dehydrogenase to block l-proline degradation, overexpression of glutamate dehydrogenase to increase glutamate synthesis flux, the mutation of 6-phosphate gluconate dehydrogenase and glucose-6-phosphate-dehydrogenase in the pentose phosphate pathway to enhance NADPH supply, the deletion of pyruvate aminotransferase to decrease the byproduct l-alanine synthesis, and weakening of α-ketoglutarate dehydrogenase to regulate the TCA cycle were combined to obtain ZQJY-9. ZQJY-9 produced 19.68 ± 0.22 g/L of l-proline in flask fermentation and was also demonstrated at the 3 L bioreactor level by fed-batch fermentation producing 120.18 g/L of l-proline at 76 h with the highest productivity of 1.581 g/L/h.

Directed Evolution of Ornithine Cyclodeaminase Using an EvolvR-Based Growth-Coupling Strategy for Efficient Biosynthesis of l-Proline

l-Proline takes a significant role in the pharmaceutical and chemical industries as well as graziery. Typical biosynthesis of l-proline is from l-glutamate, involving three enzyme reactions as well as a spontaneous cyclization. Alternatively, l-proline can be also synthesized in l-ornithine and/or l-arginine producing strains by an ornithine aminotransferase (OCD). In this study, a strategy of directed evolution combining rare codon selection and pEvolvR was developed to screen OCD with high catalytic efficiency, improving l-proline production from l-arginine chassis cells. The mutations were generated by CRISPR-assisted DNA polymerases and were screened by growth-coupled rare codon selection system. OCD_{K205G/M86K/T162A} from Pseudomonas putida was identified with 2.85-fold increase in catalytic efficiency for the synthesis of l-proline. Furthermore, we designed and optimized RBS for the BaargI and Ppocd coupling cascade using RedLibs, as well as sRNA inhibition of argF to moderate l-proline biosynthesis in l-arginine overproducing Corynebacterium crenatum. The strain PS6 with best performance reached 15.3 g/L l-proline in the shake flask and showed a titer of 38.4 g/L in a 5 L fermenter with relatively low concentration of residual l-ornithine and/or l-arginine.

Genome-scale modeling for Bacillus coagulans to understand the metabolic characteristics

Lactic acid is widely used in many industries, especially in the production of poly-lactic acid. Bacillus coagulans is a promising lactic acid producer in industrial fermentation due to its thermophilic property. In this study, we developed the first genome-scale metabolic model (GEM) of B. coagulans iBag597, together with an enzyme-constrained model ec-iBag597. We measured strain-specific biomass composition and integrated the data into a biomass equation. Then, we validated iBag597 against experimental data generated in this study, including amino acid requirements and carbon source utilization, showing that simulations were generally consistent with the experimental results. Subsequently, we carried out chemostats to investigate the effects of specific growth rate and culture pH on metabolism of B. coagulans. Meanwhile, we used iBag597 to estimate the intracellular metabolic fluxes for those conditions. The results showed that B. coagulans was capable of generating ATP via multiple pathways, and switched among them in response to various conditions. With ec-iBag597, we estimated the protein cost and protein efficiency for each ATP-producing pathway to investigate the switches. Our models pave the way for systems biology of B. coagulans, and our findings suggest that maintaining a proper growth rate and selecting an optimal pH are beneficial for lactate fermentation.

Current Status and Applications of Adaptive Laboratory Evolution in Industrial Microorganisms

Adaptive laboratory evolution (ALE) is an evolutionary engineering approach in artificial conditions that improves organisms through the imitation of natural evolution. Due to the development of multi-level omics technologies in recent decades, ALE can be performed for various purposes at the laboratory level. This review delineates the basics of the experimental design of ALE based on several ALE studies of industrial microbial strains and updates current strategies combined with progressed metabolic engineering, in silico modeling and automation to maximize the evolution efficiency. Moreover, the review sheds light on the applicability of ALE as a strain development approach that complies with non-recombinant preferences in various food industries. Overall, recent progress in the utilization of ALE for strain development leading to successful industrialization is discussed.

Adaptive laboratory evolution enhances methanol tolerance and conversion in engineered Corynebacterium glutamicum

Synthetic methylotrophy has recently been intensively studied to achieve methanol-based biomanufacturing of fuels and chemicals. However, attempts to engineer platform microorganisms to utilize methanol mainly focus on enzyme and pathway engineering. Herein, we enhanced methanol bioconversion of synthetic methylotrophs by improving cellular tolerance to methanol. A previously engineered methanol-dependent Corynebacterium glutamicum is subjected to adaptive laboratory evolution with elevated methanol content. Unexpectedly, the evolved strain not only tolerates higher concentrations of methanol but also shows improved growth and methanol utilization. Transcriptome analysis suggests increased methanol concentrations rebalance methylotrophic metabolism by down-regulating glycolysis and up-regulating amino acid biosynthesis, oxidative phosphorylation, ribosome biosynthesis, and parts of TCA cycle. Mutations in the O-acetyl-l-homoserine sulfhydrylase Cgl0653 catalyzing formation of l-methionine analog from methanol and methanol-induced membrane-bound transporter Cgl0833 are proven crucial for methanol tolerance. This study demonstrates the importance of tolerance engineering in developing superior synthetic methylotrophs.

Wang et al. improve the methanol tolerance for the synthetic methylotroph, Corynebacterium glutamicum. They generate 3 new strains by directed evolution and use biochemical, transcriptomic, and genetic approaches to characterize the pathways underlying the enhanced methanol metabolism. Their findings are important for biomanufacturing purposes.

Significantly enhancing production of trans-4-hydroxy-l-proline by integrated system engineering in Escherichia coli

Trans-4-hydroxy-l-proline is produced by trans-proline-4-hydroxylase with l-proline through glucose fermentation. Here, we designed a thorough "from A to Z" strategy to significantly improve trans-4-hydroxy-l-proline production. Through rare codon selected evolution, Escherichia coli M1 produced 18.2 g L-1 l-proline. Metabolically engineered M6 with the deletion of putA, proP, putP, and aceA, and proB mutation focused carbon flux to l-proline and released its feedback inhibition. It produced 15.7 g L-1 trans-4-hydroxy-l-proline with 10 g L-1 l-proline retained. Furthermore, a tunable circuit based on quorum sensing attenuated l-proline hydroxylation flux, resulting in 43.2 g L-1 trans-4-hydroxy-l-proline with 4.3 g L-1 l-proline retained. Finally, rationally designed l-proline hydroxylase gave 54.8 g L-1 trans-4-hydroxy-l-proline in 60 hours almost without l-proline remaining-the highest production to date. The de novo engineering carbon flux through rare codon selected evolution, dynamic precursor modulation, and metabolic engineering provides a good technological platform for efficient hydroxyl amino acid synthesis.

A seamless and iterative DNA assembly method named PS-Brick and its assisted metabolic engineering for threonine and 1-propanol production

BACKGROUND

DNA assembly is an essential technique enabling metabolic engineering and synthetic biology. Combining novel DNA assembly technologies with rational metabolic engineering can facilitate the construction of microbial cell factories. Amino acids and derived biochemicals are important products in industrial biotechnology with wide application and huge markets. DNA assembly scenarios encountered in metabolic engineering for the construction of amino acid and related compound producers, such as design-build-test-learn cycles, construction of precise genetic circuits and repetitive DNA molecules, usually require for iterative, scarless and repetitive sequence assembly methods, respectively.

RESULTS

Restriction endonuclease (RE)-assisted strategies constitute one of the major categories of DNA assembly. Here, we developed a Type IIP and IIS RE-assisted method named PS-Brick that comprehensively takes advantage of the properties of PCR fragments and REs for iterative, seamless and repetitive sequence assembly. One round of PS-Brick reaction using purified plasmids and PCR fragments was accomplished within several hours, and transformation of the resultant reaction product from this PS-Brick assembly reaction exhibited high efficiency (104-105 CFUs/µg DNA) and high accuracy (~ 90%). An application of metabolic engineering to threonine production, including the release of feedback regulation, elimination of metabolic bottlenecks, intensification of threonine export and inactivation of threonine catabolism, was stepwise resolved in E. coli by rounds of "design-build-test-learn" cycles through the iterative PS-Brick paradigm, and 45.71 g/L threonine was obtained through fed-batch fermentation. In addition to the value of the iterative character of PS-Brick for sequential strain engineering, seamless cloning enabled precise in-frame fusion for codon saturation mutagenesis and bicistronic design, and the repetitive sequence cloning ability of PS-Brick enabled construction of tandem CRISPR sgRNA arrays for genome editing. Moreover, the heterologous pathway deriving 1-propanol pathway from threonine, composed of Lactococcus lactis kivD and Saccharomyces cerevisiae ADH2, was assembled by one cycle of PS-Brick, resulting in 1.35 g/L 1-propanol in fed-batch fermentation.

CONCLUSIONS

To the best of our knowledge, the PS-Brick framework is the first RE-assisted DNA assembly method using the strengths of both Type IIP and IIS REs. In this study, PS-Brick was demonstrated to be an efficient DNA assembly method for pathway construction and genome editing and was successfully applied in design-build-test-learn (DBTL) cycles of metabolic engineering for the production of threonine and threonine-derived 1-propanol. The PS-Brick presents a valuable addition to the current toolbox of synthetic biology and metabolic engineering.

Modular systems metabolic engineering enables balancing of relevant pathways for l-histidine production with Corynebacterium glutamicum

BACKGROUND

l-Histidine biosynthesis is embedded in an intertwined metabolic network which renders microbial overproduction of this amino acid challenging. This is reflected in the few available examples of histidine producers in literature. Since knowledge about the metabolic interplay is limited, we systematically perturbed the metabolism of Corynebacterium glutamicum to gain a holistic understanding in the metabolic limitations for l-histidine production. We, therefore, constructed C. glutamicum strains in a modularized metabolic engineering approach and analyzed them with LC/MS-QToF-based systems metabolic profiling (SMP) supported by flux balance analysis (FBA).

RESULTS

The engineered strains produced l-histidine, equimolar amounts of glycine, and possessed heavily decreased intracellular adenylate concentrations, despite a stable adenylate energy charge. FBA identified regeneration of ATP from 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) as crucial step for l-histidine production and SMP identified strong intracellular accumulation of inosine monophosphate (IMP) in the engineered strains. Energy engineering readjusted the intracellular IMP and ATP levels to wild-type niveau and reinforced the intrinsic low ATP regeneration capacity to maintain a balanced energy state of the cell. SMP further indicated limitations in the C1 supply which was overcome by expression of the glycine cleavage system from C. jeikeium. Finally, we rerouted the carbon flux towards the oxidative pentose phosphate pathway thereby further increasing product yield to 0.093 ± 0.003 mol l-histidine per mol glucose.

CONCLUSION

By applying the modularized metabolic engineering approach combined with SMP and FBA, we identified an intrinsically low ATP regeneration capacity, which prevents to maintain a balanced energy state of the cell in an l-histidine overproduction scenario and an insufficient supply of C1 units. To overcome these limitations, we provide a metabolic engineering strategy which constitutes a general approach to improve the production of ATP and/or C1 intensive products.

Reconstruction of tricarboxylic acid cycle in Corynebacterium glutamicum with a genome-scale metabolic network model for trans-4-hydroxyproline production

trans-4-Hydroxy- l-proline (Hyp) is an abundant component of mammalian collagen and functions as a chiral synthon for the syntheses of anti-inflammatory drugs in the pharmaceutical industry. Proline 4-hydroxylase (P4H) can catalyze the conversion of l-proline to Hyp; however, it is still challenging for the fermentative production of Hyp from glucose using P4H due to the low yield and productivity. Here, we report the metabolic engineering of Corynebacterium glutamicum for the fermentative production of Hyp by reconstructing tricarboxylic acid (TCA) cycle together with heterologously expressing the p4h gene from Dactylosporangium sp. strain RH1. In silico model-based simulation showed that α-ketoglutarate was redirected from the TCA cycle toward Hyp synthetic pathway driven by P4H when the carbon flux from succinyl-CoA to succinate descended to zero. The interruption of the TCA cycle by the deletion of sucCD-encoding the succinyl-CoA synthetase (SUCOAS) led to a 60% increase in Hyp production and had no obvious impact on the growth rate. Fine-tuning of plasmid-borne ProB* and P4H abundances led to a significant increase in the yield of Hyp on glucose. The final engineered Hyp-7 strain produced up to 21.72 g/L Hyp with a yield of 0.27 mol/mol (Hyp/glucose) and a volumetric productivity of 0.36 g·L ^-1 ·hr ^-1 in the shake flask fermentation. To our knowledge, this is the highest yield and productivity achieved by microbial fermentation in a glucose-minimal medium for Hyp production. This strategy provides new insights into engineering C. glutamicum by flux coupling for the fermentative production of Hyp and related products.

In silico model-guided identification of transcriptional regulator targets for efficient strain design

BACKGROUND

Cellular metabolism is tightly regulated by hard-wired multiple layers of biological processes to achieve robust and homeostatic states given the limited resources. As a result, even the most intuitive enzyme-centric metabolic engineering endeavours through the up-/down-regulation of multiple genes in biochemical pathways often deliver insignificant improvements in the product yield. In this regard, targeted engineering of transcriptional regulators (TRs) that control several metabolic functions in modular patterns is an interesting strategy. However, only a handful of in silico model-added techniques are available for identifying the TR manipulation candidates, thus limiting its strain design application.

RESULTS

We developed hierarchical-Beneficial Regulatory Targeting (h-BeReTa) which employs a genome-scale metabolic model and transcriptional regulatory network (TRN) to identify the relevant TR targets suitable for strain improvement. We then applied this method to industrially relevant metabolites and cell factory hosts, Escherichia coli and Corynebacterium glutamicum. h-BeReTa suggested several promising TR targets, many of which have been validated through literature evidences. h-BeReTa considers the hierarchy of TRs in the TRN and also accounts for alternative metabolic pathways which may divert flux away from the product while identifying suitable metabolic fluxes, thereby performing superior in terms of global TR target identification.

CONCLUSIONS

In silico model-guided strain design framework, h-BeReTa, was presented for identifying transcriptional regulator targets. Its efficacy and applicability to microbial cell factories were successfully demonstrated via case studies involving two cell factory hosts, as such suggesting several intuitive targets for overproducing various value-added compounds.

Metabolic engineering of Corynebacterium glutamicum for anthocyanin production

Background

Anthocyanins such as cyanidin 3-O-glucoside (C3G) have wide applications in industry as food colorants. Their current production heavily relies on extraction from plant tissues. Development of a sustainable method to produce anthocyanins is of considerable interest for industrial use. Previously, E. coli-based microbial production of anthocyanins has been investigated extensively. However, safety concerns on E. coli call for the adoption of a safe production host. In the present study, a GRAS bacterium, Corynebacterium glutamicum, was introduced as the host strain to synthesize C3G. We adopted stepwise metabolic engineering strategies to improve the production titer of C3G.

Results

Anthocyanidin synthase (ANS) from Petunia hybrida and 3-O-glucosyltransferase (3GT) from Arabidopsis thaliana were coexpressed in C. glutamicum ATCC 13032 to drive the conversion from catechin to C3G. Optimized expression of ANS and 3GT improved the C3G titer by 1- to 15-fold. Further process optimization and improvement of UDP-glucose availability led to ~ 40 mg/L C3G production, representing a > 100-fold titer increase compared to production in the un-engineered, un-optimized starting strain.

Conclusions

For the first time, we successfully achieved the production of the specialty anthocyanin C3G from the comparatively inexpensive flavonoid precursor catechin in C. glutamicum. This study opens up more possibility of C. glutamicum as a host microbe for the biosynthesis of useful and value-added natural compounds.

Electronic supplementary material

The online version of this article (10.1186/s12934-018-0990-z) contains supplementary material, which is available to authorized users.

Physiological Response of Corynebacterium glutamicum to Increasingly Nutrient-Rich Growth Conditions

To ensure economic competitiveness, bioprocesses should achieve maximum productivities enabled by high growth rates (μ) and equally high substrate consumption rates (qS) as a prerequisite of sufficient carbon-to-product conversion. Both traits were investigated and improved via bioprocess engineering approaches studying the industrial work horse Corynebacterium glutamicum. Standard minimal medium CGXII with glucose as sole carbon source was supplemented with complex brain-heart-infusion (BHI) or amino acid (AA) cocktails. Maximum μ of 0.67 h-1 was exclusively observed in 37 g BHI L-1 whereas only minor growth stimulation was found after AA supplementation (μ = 0.468 h-1). Increasing glucose consumption rates (qGlc) were solely observed in certain dosages of BHI (1-10 g L-1), while 37 g BHI L-1 and AA addition revealed qGlc below the reference experiments. Moreover, BHI supplementation revealed Monod-type saturation kinetics of μ (KBHI = 2.73 g BHI L-1) referring to the preference of non-AAs as key boosting nutrients. ATP-demands under reference, 1 g BHI L-1, and AA conditions were nearly constant but halved in BHI concentrations above 5 g L-1 reflecting the energetic advantage of consuming complex nutrient components in addition to "simple" building blocks such as AAs. Furthermore, C. glutamicum revealed maximum biomass per carbon yields of about 18 gCDW C-mol-1 irrespective of the medium. In AA supplementation experiments, simultaneous uptake of 17 AAs was observed, maximum individual consumption rates determined, and L-asparagine and L-glutamine were distinguished as compounds with the highest consumption rates. Employment of the expanded stoichiometric model iMG481 successfully reproduced experimental results and revealed the importance of C. glutamicum's transaminase network to compensate needs of limiting AA supply. Model-based sensitivity studies attributed the highest impact on μ to AAs with high ATP and NADPH demands such as L-tryptophan or L-phenylalanine.