Quantification of Intracellular Metabolic Fluxes from Fractional Enrichment and13C–13C Coupling Constraints on the Isotopomer Distribution in Labeled Biomass Components

Schmidt, Karsten; Nørregaard, Lars C.; Pedersen, Bent Nørgaard; Meißner, Axel; Duus, Jens Øllgaard; Nielsen, Jens; Villadsen, John

doi:10.1006/mben.1999.0114

Cited by 88 publications

(78 citation statements)

References 24 publications

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“…The results for C. glutamicum ATCC 13287 and ATCC 21526 revealed similar small ellipsoids in between the displayed strains (data not shown). The achieved high precision is a great advantage of the present MS approach compared (i) to metabolite balancing alone, which provides no information on NADPH but assumes a closed NADPH balance (26), and (ii) to NMR approaches, which result in much higher uncertainty for fluxes into PPP and glycolysis (7,19). NADPH is required for the growth and formation of lysine and by-products, such as alanine, valine, and glycine.…”

Section: Discussionmentioning

confidence: 99%

“…Statistical analysis aiming at the quantification of accuracy and confidence for the intracellular flux distributions obtained from the corresponding data sets for the different strains was carried out using a Monte Carlo approach. Monte Carlo approaches can provide precise information on the error distribution of flux parameters (10,19). For the present work, statistical analysis is of great importance in order to identify whether differences observed among intracellular flux distributions for the examined mutants can really be attributed to strain-specific differences.…”

Section: Vol 68 2002 Flux Genealogy Of Lysine-producing Corynebactementioning

confidence: 99%

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Genealogy Profiling through Strain Improvement by Using Metabolic Network Analysis: Metabolic Flux Genealogy of Several Generations of Lysine-Producing Corynebacteria

Wittmann

Heinzle

2002

Appl Environ Microbiol

169

144

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A comprehensive approach of metabolite balancing, 13 C tracer studies, gas chromatography-mass spectrometry, matrix-assisted laser desorption ionization-time of flight mass spectrometry, and isotopomer modeling was applied for comparative metabolic network analysis of a genealogy of five successive generations of lysine-producing Corynebacterium glutamicum. The five strains examined (C. glutamicum ATCC 13032, 13287, 21253, 21526, and 21543) were previously obtained by random mutagenesis and selection. Throughout the genealogy, the lysine yield in batch cultures increased markedly from 1.2 to 24.9% relative to the glucose uptake flux. Strain optimization was accompanied by significant changes in intracellular flux distributions. The relative pentose phosphate pathway (PPP) flux successively increased, clearly corresponding to the product yield. Moreover, the anaplerotic net flux increased almost twofold as a consequence of concerted regulation of C 3 carboxylation and C 4 decarboxylation fluxes to cover the increased demand for lysine formation; thus, the overall increase was a consequence of concerted regulation of C 3 carboxylation and C 4 decarboxylation fluxes. The relative flux through isocitrate dehydrogenase dropped from 82.7% in the wild type to 59.9% in the lysine-producing mutants. In contrast to the NADPH demand, which increased from 109 to 172% due to the increasing lysine yield, the overall NADPH supply remained constant between 185 and 196%, resulting in a decrease in the apparent NADPH excess through strain optimization. Extrapolated to industrial lysine producers, the NADPH supply might become a limiting factor. The relative contributions of PPP and the tricarboxylic acid cycle to NADPH generation changed markedly, indicating that C. glutamicum is able to maintain a constant supply of NADPH under completely different flux conditions. Statistical analysis by a Monte Carlo approach revealed high precision for the estimated fluxes, underlining the fact that the observed differences were clearly strain specific.Amino acid production by Corynebacterium glutamicum is one of the major processes in industrial biotechnology. The world market for amino acids amounts to several billion dollars, among which lysine, with a worldwide production of about 450,000 tons/year, is one of the most important products (17). The progress made in recent years in the area of metabolic engineering allows the optimization of amino acid-producing strains in a targeted and effective way. The targeted optimization of cellular processes requires a detailed understanding and knowledge of intracellular carbon flux distributions and their regulation. Knowledge of metabolic functioning and regulation is often limited, and its increase is still one of the major bottlenecks in metabolic engineering (23). For lysine-producing C. glutamicum, different metabolic network studies by nuclear magnetic resonance (NMR) and labeling analysis of protein hydrolysates have been carried out in continuous culture and have provided detailed insight ...

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Section: Discussionmentioning

confidence: 99%

Section: Vol 68 2002 Flux Genealogy Of Lysine-producing Corynebactementioning

confidence: 99%

Genealogy Profiling through Strain Improvement by Using Metabolic Network Analysis: Metabolic Flux Genealogy of Several Generations of Lysine-Producing Corynebacteria

Wittmann

Heinzle

2002

Appl Environ Microbiol

169

144

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“…The flux solutions were also subjected to statistical error analysis based on Monte Carlo simulations (40,52). For most fluxes we obtained 90% confidence intervals that were less than 8% of the estimated flux, but the 90% confidence intervals for the oxidative PP and ED pathway fluxes were less than 25%.…”

Section: Figmentioning

confidence: 98%

Responses of theCentral Metabolism in Escherichia coli to PhosphoglucoseIsomerase and Glucose-6-Phosphate DehydrogenaseKnockouts

et al. 2003

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The responses of Escherichia coli central carbon metabolism to knockout mutations in phosphoglucose isomerase and glucose-6-phosphate (G6P) dehydrogenase genes were investigated by using glucose-and ammonia-limited chemostats. The metabolic network structures and intracellular carbon fluxes in the wild type and in the knockout mutants were characterized by using the complementary methods of flux ratio analysis and metabolic flux analysis based on [U-13 C]glucose labeling and two-dimensional nuclear magnetic resonance (NMR) spectroscopy of cellular amino acids, glycerol, and glucose. Disruption of phosphoglucose isomerase resulted in use of the pentose phosphate pathway as the primary route of glucose catabolism, while flux rerouting via the Embden-Meyerhof-Parnas pathway and the nonoxidative branch of the pentose phosphate pathway compensated for the G6P dehydrogenase deficiency. Furthermore, additional, unexpected flux responses to the knockout mutations were observed. Most prominently, the glyoxylate shunt was found to be active in phosphoglucose isomerase-deficient E. coli. The Entner-Doudoroff pathway also contributed to a minor fraction of the glucose catabolism in this mutant strain. Moreover, although knockout of G6P dehydrogenase had no significant influence on the central metabolism under glucose-limited conditions, this mutation resulted in extensive overflow metabolism and extremely low tricarboxylic acid cycle fluxes under ammonia limitation conditions.The central carbon pathways constitute the backbone of cell metabolism by providing energy, building blocks, and reducing power for biomass synthesis. Due to the extensive redundancy and the presence of isozymes, most single-gene knockout mutations in central metabolism do not block cell growth on glucose (13, 18). To reveal gene-phenotype relationships, it is important to gain insight into the complex responses of the metabolic network in its entirety to these mutations. The most important properties of biochemical networks are the per se nonmeasurable in vivo reaction rates, which may be estimated by metabolic flux analysis (41).The most common approach is based on flux balancing of extracellular uptake and secretion rates within a stoichiometric reaction model (26,45). This approach usually requires assumptions about redox or energy balances, and the validity of these assumptions strongly affects the flux estimates. To increase the reliability and resolution of such flux balance analyses, additional information may be obtained from 13 C labeling experiments (43,48). In this approach, the isotope labeling patterns of intracellular metabolites are analyzed by either nuclear magnetic resonance (NMR) or mass spectrometry. The data are then used for identification of the metabolic network structure or for quantification of the intracellular carbon fluxes.Direct analytical interpretation of 13 C labeling patterns may provide direct evidence for a particular flux or reaction (24,34). Recently, a more general method of flux ratio analysis has been developed...

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“…All reversible reactions were modeled as two fluxes (see Supplemental Material IV, p. 10). The reaction from succinate to malate (Mal) in the TCA cycle can lead to an inversion of the labeling pattern, owing to the fact that succinate is a symmetrical molecule while Mal is not (Schmidt et al, 1999). To account for this fact, this reaction was modeled as two parallel fluxes, one that conserves the carbon skeleton and another that inverts the same (see Supplemental Material IV, p. 10).…”

Section: Metabolic Network Modelmentioning

confidence: 99%

Quantification of Compartmented Metabolic Fluxes in Developing Soybean Embryos by Employing Biosynthetically Directed Fractional 13C Labeling, Two-Dimensional [13C, 1H] Nuclear Magnetic Resonance, and Comprehensive Isotopomer Balancing

et al. 2004

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Metabolic flux quantification in plants is instrumental in the detailed understanding of metabolism but is difficult to perform on a systemic level. Toward this aim, we report the development and application of a computer-aided metabolic flux analysis tool that enables the concurrent evaluation of fluxes in several primary metabolic pathways. Labeling experiments were performed by feeding a mixture of U-13 C Suc, naturally abundant Suc, and Gln to developing soybean (Glycine max) embryos. Two-dimensional [ 13 C, 1 H] NMR spectra of seed storage protein and starch hydrolysates were acquired and yielded a labeling data set consisting of 155 13 C isotopomer abundances. We developed a computer program to automatically calculate fluxes from this data. This program accepts a user-defined metabolic network model and incorporates recent mathematical advances toward accurate and efficient flux evaluation. Fluxes were calculated and statistical analysis was performed to obtain SDs. A high flux was found through the oxidative pentose phosphate pathway (19.99 6 4.39 mmol d 21 cotyledon 21 , or 104.2 carbon mol 6 23.0 carbon mol per 100 carbon mol of Suc uptake). Separate transketolase and transaldolase fluxes could be distinguished in the plastid and the cytosol, and those in the plastid were found to be at least 6-fold higher. The backflux from triose to hexose phosphate was also found to be substantial in the plastid (21.72 6 5.00 mmol d 21 cotyledon 21, or 113.2 carbon mol 626.0 carbon mol per 100 carbon mol of Suc uptake). Forward and backward directions of anaplerotic fluxes could be distinguished. The glyoxylate shunt flux was found to be negligible. Such a generic flux analysis tool can serve as a quantitative tool for metabolic studies and phenotype comparisons and can be extended to other plant systems.

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Quantification of Intracellular Metabolic Fluxes from Fractional Enrichment and13C–13C Coupling Constraints on the Isotopomer Distribution in Labeled Biomass Components

Cited by 88 publications

References 24 publications

Genealogy Profiling through Strain Improvement by Using Metabolic Network Analysis: Metabolic Flux Genealogy of Several Generations of Lysine-Producing Corynebacteria

Genealogy Profiling through Strain Improvement by Using Metabolic Network Analysis: Metabolic Flux Genealogy of Several Generations of Lysine-Producing Corynebacteria

Responses of theCentral Metabolism in Escherichia coli to PhosphoglucoseIsomerase and Glucose-6-Phosphate DehydrogenaseKnockouts

Quantification of Compartmented Metabolic Fluxes in Developing Soybean Embryos by Employing Biosynthetically Directed Fractional 13C Labeling, Two-Dimensional [13C, 1H] Nuclear Magnetic Resonance, and Comprehensive Isotopomer Balancing

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