Determination of the fluxes in the central metabolism of Corynebacterium glutamicum by nuclear magnetic resonance spectroscopy combined with metabolite balancing

Review of the Proteomics and Metabolic Properties of Corynebacterium glutamicum

Corynebacterium glutamicum (C. glutamicum) has become industrially important in producing glutamic acid and lysine since its discovery and has been the subject of proteomics and central carbon metabolism studies. The proteome changes depending on environmental conditions, nutrient availability, and stressors. Post-translational modification (PTMs), such as phosphorylation, methylation, and glycosylation, alter the function and activity of proteins, allowing them to respond quickly to environmental changes. Proteomics techniques, such as mass spectrometry and two-dimensional gel electrophoresis, have enabled the study of proteomes, identification of proteins, and quantification of the expression levels. Understanding proteomes and central carbon metabolism in microorganisms provides insight into their physiology, ecology, and biotechnological applications, such as biofuels, pharmaceuticals, and industrial enzyme production. Several attempts have been made to create efficient production strains to increase productivity in several research fields, such as genomics and proteomics. In addition to amino acids, C. glutamicum is used to produce vitamins, nucleotides, organic acids, and alcohols, expanding its industrial applications. Considerable information has been accumulated, but recent research has focused on proteomes and central carbon metabolism. The development of genetic engineering technologies, such as CRISPR-Cas9, has improved production efficiency by allowing precise manipulation of the metabolic pathways of C. glutamicum. In addition, methods for designing new metabolic pathways and developing customized strains using synthetic biology technology are gradually expanding. This review is expected to enhance the understanding of C. glutamicum and its industrial potential and help researchers identify research topics and design studies.

Rethinking 13C-metabolic flux analysis - The Bayesian way of flux inference

Metabolic reaction rates (fluxes) play a crucial role in comprehending cellular phenotypes and are essential in areas such as metabolic engineering, biotechnology, and biomedical research. The state-of-the-art technique for estimating fluxes is metabolic flux analysis using isotopic labelling (13C-MFA), which uses a dataset-model combination to determine the fluxes. Bayesian statistical methods are gaining popularity in the field of life sciences, but the use of 13C-MFA is still dominated by conventional best-fit approaches. The slow take-up of Bayesian approaches is, at least partly, due to the unfamiliarity of Bayesian methods to metabolic engineering researchers. To address this unfamiliarity, we here outline similarities and differences between the two approaches and highlight particular advantages of the Bayesian way of flux analysis. With a real-life example, re-analysing a moderately informative labelling dataset of E. coli, we identify situations in which Bayesian methods are advantageous and more informative, pointing to potential pitfalls of current 13C-MFA evaluation approaches. We propose the use of Bayesian model averaging (BMA) for flux inference as a means of overcoming the problem of model uncertainty through its tendency to assign low probabilities to both, models that are unsupported by data, and models that are overly complex. In this capacity, BMA resembles a tempered Ockham's razor. With the tempered razor as a guide, BMA-based 13C-MFA alleviates the problem of model selection uncertainty and is thereby capable of becoming a game changer for metabolic engineering by uncovering new insights and inspiring novel approaches.

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.

H+-Translocating Membrane-Bound Pyrophosphatase from Rhodospirillum rubrum Fuels Escherichia coli Cells via an Alternative Pathway for Energy Generation

Inorganic pyrophosphatases (PPases) catalyze an essential reaction, namely, the hydrolysis of PP_i, which is formed in large quantities as a side product of numerous cellular reactions. In the majority of living species, PP_i hydrolysis is carried out by soluble cytoplasmic PPase (S-PPases) with the released energy dissipated in the form of heat. In Rhodospirillum rubrum, part of this energy can be conserved by proton-pumping pyrophosphatase (H⁺-PPase^Rru) in the form of a proton electrochemical gradient for further ATP synthesis. Here, the codon-harmonized gene hppa^Rru encoding H⁺-PPase^Rru was expressed in the Escherichia coli chromosome. We demonstrate, for the first time, that H⁺-PPase^Rru complements the essential native S-PPase in E. coli cells. ¹³C-MFA confirmed that replacing native PPase to H⁺-PPase^Rru leads to the re-distribution of carbon fluxes; a statistically significant 36% decrease in tricarboxylic acid (TCA) cycle fluxes was found compared with wild-type E. coli MG1655. Such a flux re-distribution can indicate the presence of an additional method for energy generation (e.g., ATP), which can be useful for the microbiological production of a number of compounds, the biosynthesis of which requires the consumption of ATP.

Metabolic Engineering: Methodologies and Applications

Metabolic engineering aims to improve the production of economically valuable molecules through the genetic manipulation of microbial metabolism. While the discipline is a little over 30 years old, advancements in metabolic engineering have given way to industrial-level molecule production benefitting multiple industries such as chemical, agriculture, food, pharmaceutical, and energy industries. This review describes the design, build, test, and learn steps necessary for leading a successful metabolic engineering campaign. Moreover, we highlight major applications of metabolic engineering, including synthesizing chemicals and fuels, broadening substrate utilization, and improving host robustness with a focus on specific case studies. Finally, we conclude with a discussion on perspectives and future challenges related to metabolic engineering.

Metabolic flux analysis: a comprehensive review on sample preparation, analytical techniques, data analysis, computational modelling, and main application areas

Metabolic flux analysis (MFA) quantitatively describes cellular fluxes to understand metabolic phenotypes and functional behaviour after environmental and/or genetic perturbations. In the last decade, the application of stable isotopes became extremely important to determine and integrate in vivo measurements of metabolic reactions in systems biology. 13C-MFA is one of the most informative methods used to study central metabolism of biological systems. This review aims to outline the current experimental procedure adopted in 13C-MFA, starting from the preparation of cell cultures and labelled tracers to the quenching and extraction of metabolites and their subsequent analysis performed with very powerful software. Here, the limitations and advantages of nuclear magnetic resonance spectroscopy and mass spectrometry techniques used in carbon labelled experiments are elucidated by reviewing the most recent published papers. Furthermore, we summarise the most successful approaches used for computational modelling in flux analysis and the main application areas with a particular focus in metabolic engineering.

Hot isopropanol quenching procedure for automated microtiter plate scale 13C-labeling experiments

Background

Currently, the generation of genetic diversity for microbial cell factories outpaces the screening of strain variants with omics-based phenotyping methods. Especially isotopic labeling experiments, which constitute techniques aimed at elucidating cellular phenotypes and supporting rational strain design by growing microorganisms on substrates enriched with heavy isotopes, suffer from comparably low throughput and the high cost of labeled substrates.

Results

We present a miniaturized, parallelized, and automated approach to ¹³C-isotopic labeling experiments by establishing and validating a hot isopropanol quenching method on a robotic platform coupled with a microbioreactor cultivation system. This allows for the first time to conduct automated labeling experiments at a microtiter plate scale in up to 48 parallel batches. A further innovation enabled by the automated quenching method is the analysis of free amino acids instead of proteinogenic ones on said microliter scale. Capitalizing on the latter point and as a proof of concept, we present an isotopically instationary labeling experiment in Corynebacterium glutamicum ATCC 13032, generating dynamic labeling data of free amino acids in the process.

Conclusions

Our results show that a robotic liquid handler is sufficiently fast to generate informative isotopically transient labeling data. Furthermore, the amount of biomass obtained from a sub-milliliter cultivation in a microbioreactor is adequate for the detection of labeling patterns of free amino acids. Combining the innovations presented in this study, isotopically stationary and instationary automated labeling experiments can be conducted, thus fulfilling the prerequisites for ¹³C-metabolic flux analyses in high-throughput.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01806-4.

INCA 2.0: A tool for integrated, dynamic modeling of NMR- and MS-based isotopomer measurements and rigorous metabolic flux analysis

Metabolic flux analysis (MFA) combines experimental measurements and computational modeling to determine biochemical reaction rates in live biological systems. Advancements in analytical instrumentation, such as nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), have facilitated chemical separation and quantification of isotopically enriched metabolites. However, no software packages have been previously described that can integrate isotopomer measurements from both MS and NMR analytical platforms and have the flexibility to estimate metabolic fluxes from either isotopic steady-state or dynamic labeling experiments. By applying physiologically relevant cardiac and hepatic metabolic models to assess NMR isotopomer measurements, we herein test and validate new modeling capabilities of our enhanced flux analysis software tool, INCA 2.0. We demonstrate that INCA 2.0 can simulate and regress steady-state 13C NMR datasets from perfused hearts with an accuracy comparable to other established flux assessment tools. Furthermore, by simulating the infusion of three different 13C acetate tracers, we show that MFA based on dynamic 13C NMR measurements can more precisely resolve cardiac fluxes compared to isotopically steady-state flux analysis. Finally, we show that estimation of hepatic fluxes using combined 13C NMR and MS datasets improves the precision of estimated fluxes by up to 50%. Overall, our results illustrate how the recently added NMR data modeling capabilities of INCA 2.0 can enable entirely new experimental designs that lead to improved flux resolution and can be applied to a wide range of biological systems and measurement time courses.

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.

Evolving a New Efficient Mode of Fructose Utilization for Improved Bioproduction in Corynebacterium glutamicum

Fructose utilization in Corynebacterium glutamicum starts with its uptake and concomitant phosphorylation via the phosphotransferase system (PTS) to yield intracellular fructose 1-phosphate, which enters glycolysis upon ATP-dependent phosphorylation to fructose 1,6-bisphosphate by 1-phosphofructokinase. This is known to result in a significantly reduced oxidative pentose phosphate pathway (oxPPP) flux on fructose (∼10%) compared to glucose (∼60%). Consequently, the biosynthesis of NADPH demanding products, e.g., L-lysine, by C. glutamicum is largely decreased when fructose is the only carbon source. Previous works reported that fructose is partially utilized via the glucose-specific PTS presumably generating fructose 6-phosphate. This closer proximity to the entry point of the oxPPP might increase oxPPP flux and, consequently, NADPH availability. Here, we generated deletion strains lacking either the fructose-specific PTS or 1-phosphofructokinase activity. We used these strains in short-term evolution experiments on fructose minimal medium and isolated mutant strains, which regained the ability of fast growth on fructose as a sole carbon source. In these fructose mutants, the deletion of the glucose-specific PTS as well as the 6-phosphofructokinase gene, abolished growth, unequivocally showing fructose phosphorylation via glucose-specific PTS to fructose 6-phosphate. Gene sequencing revealed three independent amino acid substitutions in PtsG (M260V, M260T, and P318S). These three PtsG variants mediated faster fructose uptake and utilization compared to native PtsG. In-depth analysis of the effects of fructose utilization via these PtsG variants revealed significantly increased ODs, reduced side-product accumulation, and increased L-lysine production by 50%.

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.

An energetic profile of Corynebacterium glutamicum underpinned by measured biomass yield on ATP

The supply and usage of energetic cofactors in metabolism is a central concern for systems metabolic engineering, particularly in case of energy intensive products. One of the most important parameters for systems wide balancing of energetic cofactors is the ATP requirement for biomass formation Y_ATP/Biomass. Despite its fundamental importance, Y_ATP/Biomass values for non-fermentative organisms are still rough estimates deduced from theoretical considerations. For the first time, we present an approach for the experimental determination of Y_ATP/Biomass using comparative ¹³C metabolic flux analysis (¹³C MFA) of a wild type strain and an ATP synthase knockout mutant. We show that the energetic profile of a cell can then be deduced from a genome wide stoichiometric model and experimental maintenance data. Particularly, the contributions of substrate level phosphorylation (SLP) and electron transport phosphorylation (ETP) to ATP generation become available which enables the overall energetic efficiency of a cell to be characterized. As a model organism, the industrial platform organism Corynebacterium glutamicum is used. C. glutamicum uses a respiratory type of energy metabolism, implying that ATP can be synthesized either by SLP or by ETP with the membrane-bound F₁F_O-ATP synthase using the proton motive force (pmf) as driving force. The presence of two terminal oxidases, which differ in their proton translocation efficiency by a factor of three, further complicates energy balancing for this organism. By integration of experimental data and network models, we show that in the wild type SLP and ETP contribute equally to ATP generation. Thus, the role of ETP in respiring bacteria may have been overrated in the past. Remarkably, in the genome wide setting 65% of the pmf is actually not used for ATP synthesis. However, it turns out that, compared to other organisms C. glutamicum still uses its energy budget rather efficiently.

Comprehensive Analysis of C. glutamicum Anaplerotic Deletion Mutants Under Defined d-Glucose Conditions

Wild-type C. glutamicum ATCC 13032 is known to possess two enzymes with anaplerotic (C4-directed) carboxylation activity, namely phosphoenolpyruvate carboxylase (PEPCx) and pyruvate carboxylase (PCx). On the other hand, C3-directed decarboxylation can be catalyzed by the three enzymes phosphoenolpyruvate carboxykinase (PEPCk), oxaloacetate decarboxylase (ODx), and malic enzyme (ME). The resulting high metabolic flexibility at the anaplerotic node compromises the unambigous determination of its carbon and energy flux in C. glutamicum wild type. To circumvent this problem we performed a comprehensive analysis of selected single or double deletion mutants in the anaplerosis of wild-type C. glutamicum under defined d-glucose conditions. By applying well-controlled lab-scale bioreactor experiments in combination with untargeted proteomics, quantitative metabolomics and whole-genome sequencing hitherto unknown, and sometimes counter-intuitive, genotype-phenotype relationships in these mutants could be unraveled. In comparison to the wild type the four mutants C. glutamiucm Δpyc, C. glutamiucm Δpyc Δodx, C. glutamiucm Δppc Δpyc, and C. glutamiucm Δpck showed lowered specific growth rates and d-glucose uptake rates, underlining the importance of PCx and PEPCk activity for a balanced carbon and energy flux at the anaplerotic node. Most interestingly, the strain C. glutamiucm Δppc Δpyc could be evolved to grow on d-glucose as the only source of carbon and energy, whereas this combination was previously considered lethal. The prevented anaplerotic carboxylation activity of PEPCx and PCx was found in the evolved strain to be compensated by an up-regulation of the glyoxylate shunt, potentially in combination with the 2-methylcitrate cycle.

Revisiting the Growth Modulon of Corynebacterium glutamicum Under Glucose Limited Chemostat Conditions

Increasing the growth rate of the industrial host Corynebacterium glutamicum is a promising target to rise productivities of growth coupled product formation. As a prerequisite, detailed knowledge about the tight regulation network is necessary for identifying promising metabolic engineering goals. Here, we present comprehensive metabolic and transcriptional analysis of C. glutamicum ATCC 13032 growing under glucose limited chemostat conditions with μ = 0.2, 0.3, and 0.4 h^–1. Intermediates of central metabolism mostly showed rising pool sizes with increasing growth. ¹³C-metabolic flux analysis (¹³C-MFA) underlined the fundamental role of central metabolism for the supply of precursors, redox, and energy equivalents. Global, growth-associated, concerted transcriptional patterns were not detected giving rise to the conclusion that glycolysis, pentose-phosphate pathway, and citric acid cycle are predominately metabolically controlled under glucose-limiting chemostat conditions. However, evidence is found that transcriptional regulation takes control over glycolysis once glucose-rich growth conditions are installed.

Engineering cofactor metabolism for improved protein and glucoamylase production in Aspergillus niger

Background

Nicotinamide adenine dinucleotide phosphate (NADPH) is an important cofactor ensuring intracellular redox balance, anabolism and cell growth in all living systems. Our recent multi-omics analyses of glucoamylase (GlaA) biosynthesis in the filamentous fungal cell factory Aspergillus niger indicated that low availability of NADPH might be a limiting factor for GlaA overproduction.

Results

We thus employed the Design-Build-Test-Learn cycle for metabolic engineering to identify and prioritize effective cofactor engineering strategies for GlaA overproduction. Based on available metabolomics and ¹³C metabolic flux analysis data, we individually overexpressed seven predicted genes encoding NADPH generation enzymes under the control of the Tet-on gene switch in two A. niger recipient strains, one carrying a single and one carrying seven glaA gene copies, respectively, to test their individual effects on GlaA and total protein overproduction. Both strains were selected to understand if a strong pull towards glaA biosynthesis (seven gene copies) mandates a higher NADPH supply compared to the native condition (one gene copy). Detailed analysis of all 14 strains cultivated in shake flask cultures uncovered that overexpression of the gsdA gene (glucose 6-phosphate dehydrogenase), gndA gene (6-phosphogluconate dehydrogenase) and maeA gene (NADP-dependent malic enzyme) supported GlaA production on a subtle (10%) but significant level in the background strain carrying seven glaA gene copies. We thus performed maltose-limited chemostat cultures combining metabolome analysis for these three isolates to characterize metabolic-level fluctuations caused by cofactor engineering. In these cultures, overexpression of either the gndA or maeA gene increased the intracellular NADPH pool by 45% and 66%, and the yield of GlaA by 65% and 30%, respectively. In contrast, overexpression of the gsdA gene had a negative effect on both total protein and glucoamylase production.

Conclusions

This data suggests for the first time that increased NADPH availability can indeed underpin protein and especially GlaA production in strains where a strong pull towards GlaA biosynthesis exists. This data also indicates that the highest impact on GlaA production can be engineered on a genetic level by increasing the flux through the pentose phosphate pathway (gndA gene) followed by engineering the flux through the reverse TCA cycle (maeA gene). We thus propose that NADPH cofactor engineering is indeed a valid strategy for metabolic engineering of A. niger to improve GlaA production, a strategy which is certainly also applicable to the rational design of other microbial cell factories.

Constructing a Novel Biosynthetic Pathway for the Production of Glycolate from Glycerol in Escherichia coli

Glycolate is an important α-hydroxy acid with a wide range of industrial applications. The current industrial production of glycolate mainly depends on chemical synthesis, but biochemical production from renewable resources using engineered microorganisms is increasingly viewed as an attractive alternative. Crude glycerol is an abundant byproduct of biodiesel production and a widely investigated potential sustainable feedstock. Here, we constructed a novel biosynthetic pathway for the production of glycolate from glycerol in Escherichia coli. The pathway starts from the oxidation of glycerol to d-glycerate by alditol oxidase, followed by sequential enzymatic dehydrogenation and decarboxylation as well as reduction reactions. We screened and characterized the catalytic activity of candidate enzymes, and a variant of alditol oxidase from Streptomyces coelicolor A3(2), 2-hydroxyglutarate-pyruvate transhydrogenase from Saccharomyces cerevisiae, α-ketoisovalerate decarboxylase from Lactococcus lactis, and aldehyde dehydrogenase from Escherichia coli were selected and assembled to create an artificial operon for the biosynthetic production of glycolate from glycerol. We also characterized the native strong constitutive promoter P_lpp from E. coli and compared it with the P_T7 promoter, which was employed to express the artificial operon on the plasmid pSC105-ADKA. To redirect glycerol flux toward glycolate synthesis, we deleted key genes of the native glycerol assimilation pathways and other branches of native E. coli metabolism, and we introduced a second plasmid expressing Dld3 to reduce the accumulation of the intermediate d-glycerate. Finally, the engineered strain TZ-108 harboring pSC105-ADKA and pACYC184-P_lpp-Dld3 produced 0.64 g/L glycolate in shake flasks, which was increased to 4.74 g/L in fed-batch fermentation. This study provides an alternative pathway for glycolate synthesis and demonstrates the potential for producing other commodity chemicals by redesigning glycerol metabolism.

Computer-Aided Rational Design of Efficient NADPH Production System by Escherichia coli pgi Mutant Using a Mixture of Glucose and Xylose

Lignocellulosic biomass can be hydrolyzed into two major sugars of glucose and xylose, and thus the strategy for the efficient consumption of both sugars is highly desirable. NADPH is the essential molecule for the production of industrially important value-added chemicals, and thus its availability is quite important. Escherichia coli mutant lacking the pgi gene encoding phosphoglucose isomerase (Pgi) has been preferentially used to overproduce the NADPH. However, there exists a disadvantage that the cell growth rate becomes low for the mutant grown on glucose. This limits the efficient NADPH production, and therefore, it is quite important to investigate how addition of different carbon source such as xylose (other than glucose) effectively improves the NADPH production. In this study, we have developed a kinetic model to propose an efficient NADPH production system using E. coli pgi-knockout mutant with a mixture of glucose and xylose. The proposed system adds xylose to glucose medium to recover the suppressed growth of the pgi mutant, and determines the xylose content to maximize the NADPH productivity. Finally, we have designed a mevalonate (MVA) production system by implementing ArcA overexpression into the pgi-knockout mutant using a mixture of glucose and xylose. In addition to NADPH overproduction, the accumulation of acetyl-CoA (AcCoA) is necessary for the efficient MVA production. In the present study, therefore, we considered to overexpress ArcA, where ArcA overexpression suppresses the TCA cycle, causing the overflow of AcCoA, a precursor of MVA. We predicted the xylose content that maximizes the MVA production. This approach demonstrates the possibility of a great progress in the computer-aided rational design of the microbial cell factories for useful metabolite production.

Redox rebalance against genetic perturbations and modulation of central carbon metabolism by the oxidative stress regulation

The micro-aerophilic organisms and aerobes as well as yeast and higher organisms have evolved to gain energy through respiration (via oxidative phosphorylation), thereby enabling them to grow much faster than anaerobes. However, during respiration, reactive oxygen species (ROSs) are inherently (inevitably) generated, and threaten the cell's survival. Therefore, living organisms (or cells) must furnish the potent defense systems to keep such ROSs at harmless level, where the cofactor balance plays crucial roles. Namely, NADH is the source of energy generation (catabolism) in the respiratory chain reactions, through which ROSs are generated, while NADPH plays important roles not only for the cell synthesis (anabolism) but also for detoxifying ROSs. Therefore, the cell must rebalance the redox ratio by modulating the fluxes of the central carbon metabolism (CCM) by regulating the multi-level regulation machinery upon genetic perturbations and the change in the growth conditions. Here, we discuss about how aerobes accomplish such cofactor homeostasis against redox perturbations. In particular, we consider how single-gene mutants (including pgi, pfk, zwf, gnd and pyk mutants) modulate their metabolisms in relation to cofactor rebalance (and also by adaptive laboratory evolution). We also discuss about how the overproduction of NADPH (by the pathway gene mutation) can be utilized for the efficient production of useful value-added chemicals such as medicinal compounds, polyhydroxyalkanoates, and amino acids, all of which require NADPH in their synthetic pathways. We then discuss about the metabolic responses against oxidative stress, where αketoacids play important roles not only for the coordination between catabolism and anabolism, but also for detoxifying ROSs by non-enzymatic reactions, as well as for reducing the production of ROSs by repressing the activities of the TCA cycle and respiration (via carbon catabolite repression). Thus, we discuss about the mechanisms (basic strategies) that modulate the metabolism from respiration to respiro-fermentative metabolism causing overflow, based on the role of Pyk activity, affecting the NADPH production at the oxidative pentose phosphate (PP) pathway, and the roles of αketoacids for the change in the source of energy generation from the oxidative phosphorylation to the substrate level phosphorylation.

The Design of FluxML: A Universal Modeling Language for 13C Metabolic Flux Analysis

¹³C metabolic flux analysis (MFA) is the method of choice when a detailed inference of intracellular metabolic fluxes in living organisms under metabolic quasi-steady state conditions is desired. Being continuously developed since two decades, the technology made major contributions to the quantitative characterization of organisms in all fields of biotechnology and health-related research. ¹³C MFA, however, stands out from other "-omics sciences," in that it requires not only experimental-analytical data, but also mathematical models and a computational toolset to infer the quantities of interest, i.e., the metabolic fluxes. At present, these models cannot be conveniently exchanged between different labs. Here, we present the implementation-independent model description language FluxML for specifying ¹³C MFA models. The core of FluxML captures the metabolic reaction network together with atom mappings, constraints on the model parameters, and the wealth of data configurations. In particular, we describe the governing design processes that shaped the FluxML language. We demonstrate the utility of FluxML to represent many contemporary experimental-analytical requirements in the field of ¹³C MFA. The major aim of FluxML is to offer a sound, open, and future-proof language to unambiguously express and conserve all the necessary information for model re-use, exchange, and comparison. Along with FluxML, several powerful computational tools are supplied for easy handling, but also to maintain a maximum of flexibility. Altogether, the FluxML collection is an "all-around carefree package" for ¹³C MFA modelers. We believe that FluxML improves scientific productivity as well as transparency and therewith contributes to the efficiency and reproducibility of computational modeling efforts in the field of ¹³C MFA.

Focusing on “the important” through targeted NMR experiments: an example of selective13C–12C bond detection in complex mixtures

Here, a targeted NMR experiment is introduced which selectively detects the formation of¹³C–¹²C bonds in mixtures.

Real Time Monitoring of NADPH Concentrations in Corynebacterium glutamicum and Escherichia coli via the Genetically Encoded Sensor mBFP

Analyses of intracellular NADPH concentrations are prerequisites for the design of microbial production strains and process optimization. mBFP was described as metagenomics derived, blue fluorescent protein showing NADPH-dependent fluorescence. Characterization of mBFP showed a high specificity for binding of NADPH (K_D 0.64 mM) and no binding of NADH, the protein exclusively amplified fluorescence of NADPH. mBFP catalyzed the NADPH-dependent reduction of benzaldehyde and further aldehydes, which fits to its classification as short chain dehydrogenase. For in vivo NADPH analyses a codon-optimized gene for mBFP was introduced into Corynebacterium glutamicum WT and the phosphoglucoisomerase-deficient strain C. glutamicum Δpgi, which accumulates high levels of NADPH. For determination of intracellular NADPH concentrations by mBFP a calibration method with permeabilized cells was developed. By this means an increase of intracellular NADPH concentrations within seconds after the addition of glucose to nutrient-starved cells of both C. glutamicum WT and C. glutamicum Δpgi was observed; as expected the internal NADPH concentration was significantly higher for C. glutamicum Δpgi (0.31 mM) when compared to C. glutamicum WT (0.19 mM). Addition of paraquat to E. coli cells carrying mBFP led as expected to an immediate decrease of intracellular NADPH concentrations, showing the versatile use of mBFP as intracellular sensor.

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.

Understanding the high L-valine production in Corynebacterium glutamicum VWB-1 using transcriptomics and proteomics

Toward the elucidation of the advanced mechanism of l-valine production by Corynebacterium glutamicum, a highly developed industrial strain VWB-1 was analyzed, employing the combination of transcriptomics and proteomics methods. The transcriptional level of 1155 genes and expression abundance of 96 proteins were changed significantly by the transcriptome and proteome comparison of VWB-1 and ATCC 13869. It was indicated that the key genes involved in the biosynthesis of l-valine, ilvBN, ilvC, ilvD, ilvE were up-regulated in VWB-1, which together made prominent contributions in improving the carbon flow towards l-valine. The l-leucine and l-isoleucine synthesis ability were weakened according to the down-regulation of leuB and ilvA. The up-regulation of the branched chain amino acid transporter genes brnFE promoted the l-valine secretion capability of VWB-1. The NADPH and ATP generation ability of VWB-1 were strengthened through the up-regulation of the genes involved in phosphate pentose pathway and TCA pathway. Pyruvate accumulation was achieved through the weakening of the l-lactate, acetate and l-alanine pathways. The up-regulation of the genes coding for elongation factors and ribosomal proteins were beneficial for l-valine synthesis in C. glutamicum. All information acquired were useful for the genome breeding of better industrial l-valine producing strains.

Mu-driven transposition of recombinant mini-Mu unit DNA in the Corynebacterium glutamicum chromosome

A dual-component Mu-transposition system was modified for the integration/amplification of genes in Corynebacterium. The system consists of two types of plasmids: (i) a non-replicative integrative plasmid that contains the transposing mini-Mu(LR) unit bracketed by the L/R Mu ends or the mini-Mu(LER) unit, which additionally contains the enhancer element, E, and (ii) an integration helper plasmid that expresses the transposition factor genes for MuA and MuB. Efficient transposition in the C. glutamicum chromosome (≈ 2 × 10⁻⁴ per cell) occurred mainly through the replicative pathway via cointegrate formation followed by possible resolution. Optimizing the E location in the mini-Mu unit significantly increased the efficiency of Mu-driven intramolecular transposition–amplification in C. glutamicum as well as in gram-negative bacteria. The new C. glutamicum genome modification strategy that was developed allows the consequent independent integration/amplification/fixation of target genes at high copy numbers. After integration/amplification of the first mini-Mu(LER) unit in the C. glutamicum chromosome, the E-element, which is bracketed by lox-like sites, is excised by Cre-mediated fashion, thereby fixing the truncated mini-Mu(LR) unit in its position for the subsequent integration/amplification of new mini-Mu(LER) units. This strategy was demonstrated using the genes for the citrine and green fluorescent proteins, yECitrine and yEGFP, respectively.

Coproduction of cell-bound and secreted value-added compounds: Simultaneous production of carotenoids and amino acids by Corynebacterium glutamicum

Corynebacterium glutamicum is used for production of the food and feed amino acids l-glutamate and l-lysine at the million-ton-scale. One feed formulation of l-lysine simply involves spray-drying of the fermentation broth, thus, including secreted l-lysine and C. glutamicum cells which are pigmented by the C50 carotenoid decaprenoxanthin. C. glutamicum has been engineered for overproduction of various compounds including carotenoids. In this study, C. glutamicum was engineered for coproduction of a secreted amino acid with a cell-bound carotenoid. Asa proof of principle, coproduction of l-glutamate with the industrially relevant astaxanthin was shown. This strategy was applied to engineer l-lysine overproducing strains for combined overproduction of secreted l-lysine with the cell-bound carotenoids decaprenoxanthin, lycopene, β-carotene, zeaxanthin, canthaxanthin and astaxanthin. By fed-batch fermentation 48g/Ll-lysine and 10mg/L astaxanthin were coproduced. Moreover, C. glutamicum was engineered for coproduction of l-lysine and β-carotene from xylose and arabinose as alternative feedstocks.

Ion Pair Chromatography for Endogenous Metabolites LC-MS Analysis in Tissue Samples Following Targeted Acquisition

A protocol for the preparation of tissue extracts for the targeted analysis of ca. 150 polar metabolites, including those involved in central carbon metabolism is described, using a reversed-phase ion pair U(H)PLC-MS method. Data collection enabled by multiple-reaction monitoring provides highly specific, sensitive acquisition of metabolic intermediates with a wide range of physicochemical properties and pathway coverage. Technical aspects are discussed for method transfer along with the basic principles of sample sequence setup, data analysis, and validation. General comments are given to help the assessment of data quality and system performance.

Engineering photosynthetic production of L-lysine

L-lysine and other amino acids are commonly produced through fermentation using strains of heterotrophic bacteria such as Corynebacterium glutamicum. Given the large amount of sugar this process consumes, direct photosynthetic production is intriguing alternative. In this study, we report the development of a cyanobacterium, Synechococcus sp. strain PCC 7002, capable of producing L-lysine with CO2 as the sole carbon-source. We found that heterologous expression of a lysine transporter was required to excrete lysine and avoid intracellular accumulation that correlated with poor fitness. Simultaneous expression of a feedback inhibition resistant aspartate kinase and lysine transporter were sufficient for high productivities, but this was also met with a decreased chlorophyll content and reduced growth rates. Increasing the reductant supply by using NH4+, a more reduced nitrogen source relative to NO3-, resulted in a two-fold increase in productivity directing 18% of fixed carbon to lysine. Given this advantage, we demonstrated lysine production from media formulated with a municipal wastewater treatment sidestream as a nutrient source for increased economic and environmental sustainability. Based on our results, we project that Synechococcus sp. strain PCC 7002 could produce lysine at areal productivities approaching that of sugar cane to lysine via fermentation using non-agricultural lands and low-cost feedstocks.

The importance of accurately correcting for the natural abundance of stable isotopes

The use of isotopically labeled tracer substrates is an experimental approach for measuring in vivo and in vitro intracellular metabolic dynamics. Stable isotopes that alter the mass but not the chemical behavior of a molecule are commonly used in isotope tracer studies. Because stable isotopes of some atoms naturally occur at non-negligible abundances, it is important to account for the natural abundance of these isotopes when analyzing data from isotope labeling experiments. Specifically, a distinction must be made between isotopes introduced experimentally via an isotopically labeled tracer and the isotopes naturally present at the start of an experiment. In this tutorial review, we explain the underlying theory of natural abundance correction of stable isotopes, a concept not always understood by metabolic researchers. We also provide a comparison of distinct methods for performing this correction and discuss natural abundance correction in the context of steady state 13C metabolic flux, a method increasingly used to infer intracellular metabolic flux from isotope experiments.

Quantification of Microbial Phenotypes

Metabolite profiling technologies have improved to generate close to quantitative metabolomics data, which can be employed to quantitatively describe the metabolic phenotype of an organism. Here, we review the current technologies available for quantitative metabolomics, present their advantages and drawbacks, and the current challenges to generate fully quantitative metabolomics data. Metabolomics data can be integrated into metabolic networks using thermodynamic principles to constrain the directionality of reactions. Here we explain how to estimate Gibbs energy under physiological conditions, including examples of the estimations, and the different methods for thermodynamics-based network analysis. The fundamentals of the methods and how to perform the analyses are described. Finally, an example applying quantitative metabolomics to a yeast model by 13C fluxomics and thermodynamics-based network analysis is presented. The example shows that (1) these two methods are complementary to each other; and (2) there is a need to take into account Gibbs energy errors. Better estimations of metabolic phenotypes will be obtained when further constraints are included in the analysis.

Assessing compartmentalized flux in lipid metabolism with isotopes

Metabolism in plants takes place across multiple cell types and within distinct organelles. The distributions equate to spatial heterogeneity; though the limited means to experimentally assess metabolism frequently involve homogenizing tissues and mixing metabolites from different locations. Most current isotope investigations of metabolism therefore lack the ability to resolve spatially distinct events. Recognition of this limitation has resulted in inspired efforts to advance metabolic flux analysis and isotopic labeling techniques. Though a number of these efforts have been applied to studies in central metabolism; recent advances in instrumentation and techniques present an untapped opportunity to make similar progress in lipid metabolism where the use of stable isotopes has been more limited. These efforts will benefit from sophisticated radiolabeling reports that continue to enrich our knowledge on lipid biosynthetic pathways and provide some direction for stable isotope experimental design and extension of MFA. Evidence for this assertion is presented through the review of several elegant stable isotope studies and by taking stock of what has been learned from radioisotope investigations when spatial aspects of metabolism were considered. The studies emphasize that glycerolipid production occurs across several locations with assembly of lipids in the ER or plastid, fatty acid biosynthesis occurring in the plastid, and the generation of acetyl-CoA and glycerol-3-phosphate taking place at multiple sites. Considering metabolism in this context underscores the cellular and subcellular organization that is important to enhanced production of glycerolipids in plants. An attempt is made to unify salient features from a number of reports into a diagrammatic model of lipid metabolism and propose where stable isotope labeling experiments and further flux analysis may help address questions in the field. This article is part of a Special Issue entitled: Plant Lipid Biology edited by Kent D. Chapman and Ivo Feussner.

Metabolic Modeling of Dynamic (13)C NMR Isotopomer Data in the Brain In Vivo: Fast Screening of Metabolic Models Using Automated Generation of Differential Equations

Most current brain metabolic models are not capable of taking into account the dynamic isotopomer information available from fine structure multiplets in (13)C spectra, due to the difficulty of implementing such models. Here we present a new approach that allows automatic implementation of multi-compartment metabolic models capable of fitting any number of (13)C isotopomer curves in the brain. The new automated approach also makes it possible to quickly modify and test new models to best describe the experimental data. We demonstrate the power of the new approach by testing the effect of adding separate pyruvate pools in astrocytes and neurons, and adding a vesicular neuronal glutamate pool. Including both changes reduced the global fit residual by half and pointed to dilution of label prior to entry into the astrocytic TCA cycle as the main source of glutamine dilution. The glutamate-glutamine cycle rate was particularly sensitive to changes in the model.

Modeling and CFD simulation of nutrient distribution in picoliter bioreactors for bacterial growth studies on single-cell level

A microfluidic device for microbial single-cell cultivation of bacteria was modeled and simulated using COMSOL Multiphysics. The liquid velocity field and the mass transfer within the supply channels and cultivation chambers were calculated to gain insight in the distribution of supplied nutrients and metabolic products secreted by the cultivated bacteria. The goal was to identify potential substrate limitations or product accumulations within the cultivation device. The metabolic uptake and production rates, colony size, and growth medium composition were varied covering a wide range of operating conditions. Simulations with glucose as substrate did not show limitations within the typically used concentration range, but for alternative substrates limitations could not be ruled out. This lays the foundation for further studies and the optimization of existing picoliter bioreactor systems.

Cutting the Gordian Knot: Identifiability of anaplerotic reactions in Corynebacterium glutamicum by means of (13) C-metabolic flux analysis

Corynebacterium glutamicum is the major workhorse for the microbial production of several amino and organic acids. As long as these derive from tricarboxylic acid cycle intermediates, the activity of anaplerotic reactions is pivotal for a high biosynthetic yield. To determine single anaplerotic activities (13) C-Metabolic Flux Analysis ((13) C-MFA) has been extensively used for C. glutamicum, however with different network topologies, inconsistent or poorly determined anaplerotic reaction rates. Therefore, in this study we set out to investigate whether a focused isotopomer model of the anaplerotic node can at all admit a unique solution for all fluxes. By analyzing different scenarios of active anaplerotic reactions, we show in full generality that for C. glutamicum only certain anaplerotic deletion mutants allow to uniquely determine the anaplerotic fluxes from (13) C-isotopomer data. We stress that the result of this analysis for different assumptions on active enzymes is directly transferable to other compartment-free organisms. Our results demonstrate that there exist biologically relevant metabolic network topologies for which the flux distribution cannot be inferred by classical (13) C-MFA.

Reconstruction and analysis of a genome-scale metabolic network of Corynebacterium glutamicum S9114

Corynebacterium glutamicum S9114 is commonly used for industrial glutamate production. Therefore, a comprehensive understanding of the physiological and metabolic characteristics of C. glutamicum is important for developing its potential for industrial production. A genome-scale metabolic model, iJM658, was reconstructed based on genome annotation and literature mining. The model consists of 658 genes, 984 metabolites and 1065 reactions. The model quantitatively predicted C. glutamicum growth on different carbon and nitrogen sources and determined 129 genes to be essential for cell growth. The iJM658 model predicted that C. glutamicum had two glutamate biosynthesis pathways and lacked eight key genes in biotin synthesis. Robustness analysis indicated a relative low oxygen level (1.21mmol/gDW/h) would improve glutamate production rate. Potential metabolic engineering targets for improving γ-aminobutyrate and isoleucine production rate were predicted by in silico deletion or overexpression of some genes. The iJM658 model is a useful tool for understanding and optimizing the metabolism of C. glutamicum and a valuable resource for future metabolic and physiological research.

Anaerobic growth of Corynebacterium glutamicum via mixed-acid fermentation

Corynebacterium glutamicum, a model organism in microbial biotechnology, is known to metabolize glucose under oxygen-deprived conditions to l-lactate, succinate, and acetate without significant growth. This property is exploited for efficient production of lactate and succinate. Our detailed analysis revealed that marginal growth takes place under anaerobic conditions with glucose, fructose, sucrose, or ribose as a carbon and energy source but not with gluconate, pyruvate, lactate, propionate, or acetate. Supplementation of glucose minimal medium with tryptone strongly enhanced growth up to a final optical density at 600 nm (OD600) of 12, whereas tryptone alone did not allow growth. Amino acids with a high ATP demand for biosynthesis and amino acids of the glutamate family were particularly important for growth stimulation, indicating ATP limitation and a restricted carbon flux into the oxidative tricarboxylic acid cycle toward 2-oxoglutarate. Anaerobic cultivation in a bioreactor with constant nitrogen flushing disclosed that CO2 is required to achieve maximal growth and that the pH tolerance is reduced compared to that under aerobic conditions, reflecting a decreased capability for pH homeostasis. Continued growth under anaerobic conditions indicated the absence of an oxygen-requiring reaction that is essential for biomass formation. The results provide an improved understanding of the physiology of C. glutamicum under anaerobic conditions.

A roadmap for interpreting (13)C metabolite labeling patterns from cells

Measuring intracellular metabolism has increasingly led to important insights in biomedical research. (13)C tracer analysis, although less information-rich than quantitative (13)C flux analysis that requires computational data integration, has been established as a time-efficient method to unravel relative pathway activities, qualitative changes in pathway contributions, and nutrient contributions. Here, we review selected key issues in interpreting (13)C metabolite labeling patterns, with the goal of drawing accurate conclusions from steady state and dynamic stable isotopic tracer experiments.