Respirometric 13C flux analysis--Part II: in vivo flux estimation of lysine-producing Corynebacterium glutamicum

A novel method for metabolic flux studies of central metabolism which is based on respirometric (13)C flux analysis, i.e., parallel (13)C tracer studies with online CO(2) labeling measurements is applied to flux quantification of a lysine-producing mutant of Corynebacterium glutamicum. For this purpose, 3 respirometric (13)C labeling experiments with [1-(13)C(1)], [6-(13)C(1)] and [1,6-(13)C(2)] glucose were carried out in parallel. All fluxes comprising the reactions of glycolysis, of TCA cycle, of C3- and C4-metabolite interconversion and of lysine biosynthesis as well as the net reactions in the pentose phosphate pathway could be quantified solely using experimental data obtained from CO(2) labeling and extracellular rate measurements. At key branch points, 68+/-5% of glucose 6-phosphate were observed to be metabolized into pentose phosphate pathway and 48+/-1% of pyruvate into TCA cycle via pyruvate dehydrogenase. The results showed a good agreement with the previous studies using (13)C tracer cultivation and GC/MS analysis of proteinogenic amino acids. Also, respiratory quotient calculated from flux estimates using redox balance showed a high accordance with the value determined directly from the measured specific rates of O(2) consumption and CO(2) production. The results strongly support that the respirometric (13)C metabolic flux analysis is suited as an alternative to the conventional methods to study functional and regulatory activities of cells. The developed method is applicable to study growing or non-growing cells, primary and secondary metabolism and immobilized cells. Due to the non-accumulating nature of CO(2) labeling and instantaneous nature of the resulting fluxes, the method can also be used for dynamic profiling of metabolic activities. Therefore, it is complementary to conventional methods for metabolic flux analysis.     

Parallel labeling experiments with [U-(13)C]glucose validate E. coli metabolic network model for (13)C metabolic flux analysis

(13)C-metabolic flux analysis (MFA) is a widely used method for measuring intracellular metabolic fluxes in living cells. (13)C MFA relies on several key assumptions: (1) the assumed metabolic network model is complete, in that it accounts for all significant enzymatic and transport reactions; (2) (13)C-labeling measurements are accurate and precise; and (3) enzymes and transporters do not discriminate between (12)C- and (13)C-labeled metabolites. In this study, we tested these inherent assumptions of (13)C MFA for wild-type E. coli by parallel labeling experiments with [U-(13)C]glucose as tracer. Cells were grown in six parallel cultures in custom-constructed mini-bioreactors, starting from the same inoculum, on medium containing different mixtures of natural glucose and fully labeled [U-(13)C]glucose, ranging from 0% to 100% [U-(13)C]glucose. Macroscopic growth characteristics of E. coli showed no observable kinetic isotope effect. The cells grew equally well on natural glucose, 100% [U-(13)C]glucose, and mixtures thereof. (13)C MFA was then used to determine intracellular metabolic fluxes for several metabolic network models: an initial network model from literature; and extended network models that accounted for potential dilution effects of isotopic labeling. The initial network model did not give statistically acceptable fits and produced inconsistent flux results for the parallel labeling experiments. In contrast, an extended network model that accounted for dilution of intracellular CO(2) by exchange with extracellular CO(2) produced statistically acceptable fits, and the estimated metabolic fluxes were consistent for the parallel cultures. This study illustrates the importance of model validation for (13)C MFA. We show that an incomplete network model can produce statistically unacceptable fits, as determined by a chi-square test for goodness-of-fit, and return biased metabolic fluxes. The validated metabolic network model for E. coli from this study can be used in future investigations for unbiased metabolic flux measurements.     

COMPLETE-MFA: Complementary parallel labeling experiments technique for metabolic flux analysis

We have developed a novel approach for measuring highly accurate and precise metabolic fluxes in living cells, termed COMPLETE-MFA, short for complementary parallel labeling experiments technique for metabolic flux analysis. The COMPLETE-MFA method is based on combined analysis of multiple isotopic labeling experiments, where the synergy of using complementary tracers greatly improves the precision of estimated fluxes. In this work, we demonstrate the COMPLETE-MFA approach using all singly labeled glucose tracers, [1-¹³C], [2-¹³C], [3-¹³C], [4-¹³C], [5-¹³C], and [6-¹³C]glucose to determine precise metabolic fluxes for wild-type Escherichia coli. Cells were grown in six parallel cultures on defined medium with glucose as the only carbon source. Mass isotopomers of biomass amino acids were measured by gas chromatography–mass spectrometry (GC–MS). The data from all six experiments were then fitted simultaneously to a single flux model to determine accurate intracellular fluxes. We obtained a statistically acceptable fit with more than 300 redundant measurements. The estimated flux map is the most precise flux result obtained thus far for E. coli cells. To our knowledge, this is the first time that six isotopic labeling experiments have been successfully integrated for high-resolution ¹³C-flux analysis.     

Quantification of compartmented metabolic fluxes in developing soybean embryos by employing biosynthetically directed fractional (13)C labeling, two-dimensional [(13)C, (1)H] nuclear magnetic resonance, and comprehensive isotopomer balancing

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 +/- 4.39 micromol d(-1) cotyledon(-1), or 104.2 carbon mol +/- 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 +/- 5.00 micromol d(-1) cotyledon(-1), or 113.2 carbon mol +/-26.0 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.     

Production process monitoring by serial mapping of microbial carbon flux distributions using a novel sensor reactor approach: I--Sensor reactor system

A novel Sensor Reactor technology is presented which permits 13C labeling experiments for metabolic flux analysis during large-scale, semi-industrial, (fed-) batch fermentation processes deriving a series of flux maps that document fermentation courses in detail. The small-scale Sensor Reactor can be inoculated within 1.50-1.20s via a special inoculation unit with an inoculation volume accuracy of 1.025+/-0.021 L. The large-scale production reactor (here: 300 L) and the Sensor Reactor were run in parallel master/slave modes to control the current pH, temperature, pressure and dissolved oxygen values as changing set points for the Sensor Reactor. Using an automated pulsing technology, glucose pulses of 5 g/L could be realized within 0.51 s. The similarity of fermentations in the Sensor Reactor with the production process was demonstrated by studying L-lysine production with C. glutamicum during multiple, 'simulated' labeling experiments each lasting 2.5h. 'Real' labeling experiments are presented in Part II.     

Optimal tracers for parallel labeling experiments and 13C metabolic flux analysis: A new precision and synergy scoring system

¹³C-Metabolic flux analysis (¹³C-MFA) is a widely used approach in metabolic engineering for quantifying intracellular metabolic fluxes. The precision of fluxes determined by ¹³C-MFA depends largely on the choice of isotopic tracers and the specific set of labeling measurements. A recent advance in the field is the use of parallel labeling experiments for improved flux precision and accuracy. However, as of today, no systemic methods exist for identifying optimal tracers for parallel labeling experiments. In this contribution, we have addressed this problem by introducing a new scoring system and evaluating thousands of different isotopic tracer schemes. Based on this extensive analysis we have identified optimal tracers for ¹³C-MFA. The best single tracers were doubly ¹³C-labeled glucose tracers, including [1,6-¹³C]glucose, [5,6-¹³C]glucose and [1,2-¹³C]glucose, which consistently produced the highest flux precision independent of the metabolic flux map (here, 100 random flux maps were evaluated). Moreover, we demonstrate that pure glucose tracers perform better overall than mixtures of glucose tracers. For parallel labeling experiments the optimal isotopic tracers were [1,6-¹³C]glucose and [1,2-¹³C]glucose. Combined analysis of [1,6-¹³C]glucose and [1,2-¹³C]glucose labeling data improved the flux precision score by nearly 20-fold compared to widely use tracer mixture 80% [1-¹³C]glucose +20% [U-¹³C]glucose.     

Kinetic analysis of dynamic 13C NMR spectra: metabolic flux, regulation, and compartmentation in hearts.

Control of oxidative metabolism was studied using 13C NMR spectroscopy to detect rate-limiting steps in 13C labeling of glutamate. 13C NMR spectra were acquired every 1 or 2 min from isolated rabbit hearts perfused with either 2.5 mM [2-13C]acetate or 2.5 mM [2-13C]butyrate with or without KCl arrest. Tricarboxylic acid cycle flux (VTCA) and the exchange rate between alpha-ketoglutarate and glutamate (F1) were determined by least-square fitting of a kinetic model to NMR data. Rates were compared to measured kinetics of the cardiac glutamate-oxaloacetate transaminase (GOT). Despite similar oxygen use, hearts oxidizing butyrate instead of acetate showed delayed incorporation of 13C label into glutamate and lower VTCA, because of the influence of beta-oxidation: butyrate = 7.1 +/- 0.2 mumol/min/g dry wt; acetate = 10.1 +/- 0.2; butyrate + KCl = 1.8 +/- 0.1; acetate + KCl = 3.1 +/- 0.1 (mean +/- SD). F1 ranged from a low of 4.4 +/- 1.0 mumol/min/g (butyrate + KCl) to 9.3 +/- 0.6 (acetate), at least 20-fold slower than GOT flux, and proved to be rate limiting for isotope turnover in the glutamate pool. Therefore, dynamic 13C NMR observations were sensitive not only to TCA cycle flux but also to the interconversion between TCA cycle intermediates and glutamate.     

Integrated 13C-metabolic flux analysis of 14 parallel labeling experiments in Escherichia coli

The use of parallel labeling experiments for ¹³C metabolic flux analysis (¹³C-MFA) has emerged in recent years as the new gold standard in fluxomics. The methodology has been termed COMPLETE-MFA, short for complementary parallel labeling experiments technique for metabolic flux analysis. In this contribution, we have tested the limits of COMPLETE-MFA by demonstrating integrated analysis of 14 parallel labeling experiments with Escherichia coli. An effort on such a massive scale has never been attempted before. In addition to several widely used isotopic tracers such as [1,2-¹³C]glucose and mixtures of [1-¹³C]glucose and [U-¹³C]glucose, four novel tracers were applied in this study: [2,3-¹³C]glucose, [4,5,6-¹³C]glucose, [2,3,4,5,6-¹³C]glucose and a mixture of [1-¹³C]glucose and [4,5,6-¹³C]glucose. This allowed us for the first time to compare the performance of a large number of isotopic tracers. Overall, there was no single best tracer for the entire E. coli metabolic network model. Tracers that produced well-resolved fluxes in the upper part of metabolism (glycolysis and pentose phosphate pathways) showed poor performance for fluxes in the lower part of metabolism (TCA cycle and anaplerotic reactions), and vice versa. The best tracer for upper metabolism was 80% [1-¹³C]glucose+20% [U-¹³C]glucose, while [4,5,6-¹³C]glucose and [5-¹³C]glucose both produced optimal flux resolution in the lower part of metabolism. COMPLETE-MFA improved both flux precision and flux observability, i.e. more independent fluxes were resolved with smaller confidence intervals, especially exchange fluxes. Overall, this study demonstrates that COMPLETE-MFA is a powerful approach for improving flux measurements and that this methodology should be considered in future studies that require very high flux resolution.     

Modeling and experimental design for metabolic flux analysis of lysine-producing Corynebacteria by mass spectrometry

Experimental design of (13)C-tracer studies for metabolic flux analysis with mass spectrometric determination of labeling patterns was performed for the central metabolism of Corynebacterium glutamicum comprising various flux scenarios. Ratio measurement of mass isotopomer pools of Corynebacterium products lysine, alanine, and trehalose is sufficient to quantify the flux partitioning ratios (i) between glycolysis and pentose phosphate pathways (Phi(PPP)), (ii) between the split pathways in the lysine biosynthesis (Phi(DH)), (iii) at the pyruvate node (Phi(PC)), and reversibilities of (iv) glucose 6-phosphate isomerase (zeta(PGI)), (v) at the pyruvate node (zeta(PC/PEPCK)), and (vi) of transaldolase and transketolases in the PPP. Weighted sensitivities for flux parameters were derived from partial derivatives to quantitatively evaluate experimental approaches and predict precision for estimated flux parameters. Deviation of intensity ratios from ideal values of 1 was used as weighting function. Weighted flux sensitivities can be used to identify optimal type and degree of tracer labeling or potential intensity ratios to be measured. Experimental design for lysine-producing strain C. glutamicum MH 20-22B (Marx et al., Biotechnol. Bioeng. 49, 111-129, 1996) and various potential mutants with different alterations in the flux pattern showed that specific tracer labelings are optimal to quantify a certain flux parameter uninfluenced by the overall flux situation. Identified substrates of choice are [1-(13)C]glucose for the estimation of Phi(PPP) and zeta(PGI) and a 1 : 1 mixture of [U-(12)C/U-(13)C]glucose for the determination of zeta(PC/PEPCK). Phi(PC) can be quantified by feeding [4-(13)C]glucose or [U-(12)C/U-(13)C]glucose (1 : 1), whereas Phi(DH) is accessible via [4-(13)C]glucose. The sensitivity for the quantification of a certain flux parameter can be influenced by superposition through other flux parameters in the network, but substrate and measured mass isotopomers of choice remain the same. In special cases, reduced labeling degree of the tracer substrate can increase the precision of flux analysis. Enhanced precision and flux information can be achieved via multiply labeled substrates. The presented approach can be applied for effective experimental design of (13)C tracer studies for metabolic flux analysis. Intensity ratios of other products such as glutamate, valine, phenylalanine, and riboflavin also sensitively reflect flux parameters, which underlines the great potential of mass spectrometry for flux analysis.     

Carbon conversion efficiency and central metabolic fluxes in developing sunflower (Helianthus annuus L.) embryos

The efficiency with which developing sunflower embryos convert substrates into seed storage reserves was determined by labeling embryos with [U-(14)C6]glucose or [U-(14)C5]glutamine and measuring their conversion to CO2, oil, protein and other biomass compounds. The average carbon conversion efficiency was 50%, which contrasts with a value of over 80% previously observed in Brassica napus embryos (Goffman et al., 2005), in which light and the RuBisCO bypass pathway allow more efficient conversion of hexose to oil. Labeling levels after incubating sunflower embryos with [U-(14)C4]malate indicated that some carbon from malate enters the plastidic compartment and contributes to oil synthesis. To test this and to map the underlying pattern of metabolic fluxes, separate experiments were carried out in which embryos were labeled to isotopic steady state using [1-(13)C1]glucose, [2-(13)C1]glucose, or [U-(13)C5]glutamine. The resultant labeling in sugars, starch, fatty acids and amino acids was analyzed by NMR and GC-MS. The fluxes through intermediary metabolism were then quantified by computer-aided modeling. The resulting flux map accounted well for the labeling data, was in good agreement with the observed carbon efficiency, and was further validated by testing for agreement with gas exchange measurements. The map shows that the influx of malate into oil is low and that flux through futile cycles (wasting ATP) is low, which contrasts with the high rates previously determined for growing root tips and heterotrophic cell cultures.     

Isotopic non-stationary 13C gluconate tracer method for accurate determination of the pentose phosphate pathway split-ratio in Penicillium chrysogenum

Current (13)C labeling experiments for metabolic flux analysis (MFA) are mostly limited by either the requirement of isotopic steady state or the extremely high computational effort due to the size and complexity of large metabolic networks. The presented novel approach circumvents these limitations by applying the isotopic non-stationary approach to a local metabolic network. The procedure is demonstrated in a study of the pentose phosphate pathway (PPP) split-ratio of Penicillium chrysogenum in a penicillin-G producing chemostat-culture grown aerobically at a dilution rate of 0.06h(-1) on glucose, using a tracer amount of uniformly labeled [U-(13)C(6)] gluconate. The rate of labeling inflow can be controlled by using different cell densities and/or different fractions of the labeled tracer in the feed. Due to the simplicity of the local metabolic network structure around the 6-phosphogluconate (6pg) node, only three metabolites need to be measured for the pool size and isotopomer distribution. Furthermore, the mathematical modeling of isotopomer distributions for the flux estimation has been reduced from large scale differential equations to algebraic equations. Under the studied cultivation condition, the estimated split-ratio (41.2+/-0.6%) using the novel approach, shows statistically no difference with the split-ratio obtained from the originally proposed isotopic stationary gluconate tracing method.     

Breath [13CO2] recovery from an oral glucose load during exercise: comparison between [U-13C] and [1,2-13C]glucose.

The purpose of the present experiment was to compare 13CO2 recovery at the mouth, and the corresponding exogenous glucose oxidation computed, during a 100-min exercise at 63 +/- 3% maximal O2 uptake with ingestion of glucose (1.75 g/kg) in six active male subjects, by use of [U-13C] and [1,2-13C]glucose. We hypothesized that 13C recovery and exogenous glucose oxidation could be lower with [1,2-13C] than [U-13C]glucose because both tracers provide [13C]acetate, with possible loss of 13C in the tricarboxylic acid (TCA) cycle, but decarboxylation of pyruvate from [U-13C]glucose also provides 13CO2, which is entirely recovered at the mouth during exercise. The recovery of 13C (25.8 +/- 2.3 and 27.4 +/- 1.2% over the exercise period) and the amounts of exogenous glucose oxidized computed were not significantly different with [1,2-13C] and [U-13C]glucose (28.9 +/- 2.6 and 30.7 +/- 1.3 g, between minutes 40 and 100), suggesting that no significant loss of 13C occurred in the TCA cycle. This stems from the fact that, during exercise, the rate of exogenous glucose oxidation is probably much larger than the flux of the metabolic pathways fueled from TCA cycle intermediates. It is thus unlikely that a significant portion of the 13C entering the TCA cycle could be diverted to these pathways. From a methodological standpoint, this result indicates that when a large amount of [13C]glucose is ingested and oxidized during exercise, 13CO2 production at the mouth accurately reflects the rate of glucose entry in the TCA cycle and that no correction factor is needed to compute the oxidative flux of exogenous glucose.     

Glucose production, gluconeogenesis, and hepatic tricarboxylic acid cycle fluxes measured by nuclear magnetic resonance analysis of a single glucose derivative

A triple-tracer method was developed to provide absolute fluxes contributing to endogenous glucose production and hepatic tricarboxylic acid (TCA) cycle fluxes in 24-h-fasted rats by (2)H and (13)C nuclear magnetic resonance (NMR) analysis of a single glucose derivative. A primed, intravenous [3,4-(13)C(2)]glucose infusion was used to measure endogenous glucose production; intraperitoneal (2)H(2)O (to enrich total body water) was used to quantify sources of glucose (TCA cycle, glycerol, and glycogen), and intraperitoneal [U-(13)C(3)] propionate was used to quantify hepatic anaplerosis, pyruvate cycling, and TCA cycle flux. Plasma glucose was converted to monoacetone glucose (MAG), and a single (2)H and (13)C NMR spectrum of MAG provided the following metabolic data (all in units of micromol/kg/min; n = 6): endogenous glucose production (40.4+/-2.9), gluconeogenesis from glycerol (11.5+/-3.5), gluconeogenesis from the TCA cycle (67.3+/-5.6), glycogenolysis (1.0+/-0.8), pyruvate cycling (154.4+/-43.4), PEPCK flux (221.7+/-47.6), and TCA cycle flux (49.1+/-16.8). In a separate group of rats, glucose production was not different in the absence of (2)H(2)O and [U-(13)C]propionate, demonstrating that these tracers do not alter the measurement of glucose turnover.     

Starch biosynthesis and intermediary metabolism in maize kernels. Quantitative analysis of metabolite flux by nuclear magnetic resonance

The seeds of cereals represent an important sink for metabolites during the accumulation of storage products, and seeds are an essential component of human and animal nutrition. Understanding the metabolic interconversions (networks) underpinning storage product formation could provide the foundation for effective metabolic engineering of these primary nutritional sources. In this paper, we describe the use of retrobiosynthetic nuclear magnetic resonance analysis to establish the metabolic history of the glucose (Glc) units of starch in maize (Zea mays) kernels. Maize kernel cultures were grown with [U-(13)C(6)]Glc, [U-(13)C(12)]sucrose, or [1,2-(13)C(2)]acetate as supplements. After 19 d, starch was hydrolyzed, and the isotopomer composition of the resulting Glc was determined by quantitative nuclear magnetic resonance analysis. [1,2-(13)C(2)]Acetate was not incorporated into starch. [U-(13)C(6)]Glc or [U-(13)C(12)]sucrose gave similar labeling patterns of polysaccharide Glc units, which were dominated by [1,2,3-(13)C(3)]- and [4,5,6-(13)C(3)]-isotopomers, whereas the [U-(13)C(6)]-, [3,4,5,6-(13)C(4)]-, [1,2-(13)C(2)]-, [5,6-(13)C(2)], [3-(13)C(1)], and [4-(13)C(1)]-isotopomers were present at lower levels. These isotopomer compositions indicate that there is extensive recycling of Glc before its incorporation into starch, via the enzymes of glycolytic, glucogenic, and pentose phosphate pathways. The relatively high abundance of the [5,6-(13)C(2)]-isotopomer can be explained by the joint operation of glycolysis/glucogenesis and the pentose phosphate pathway.     

Towards dynamic metabolic network measurements by multi-dimensional NMR-based fluxomics

Novel technologies for measuring biological systems and methods for visualizing data have led to a revolution in the life sciences. Nuclear magnetic resonance (NMR) techniques can provide information on metabolite structure and metabolic dynamics at the atomic level. We have been developing a new method for measuring the dynamic metabolic network of crude extracts that combines [(13)C(6)]glucose stable isotope labeling of Arabidopsis thaliana and multi-dimensional heteronuclear NMR analysis, whereas most conventional metabolic flux analyses examine proteinogenic amino acids that are specifically labeled with partially labeled substrates such as [2-(13)C(1)]glucose or 10% [(13)C(6)]glucose. To show the validity of our method, we investigated how to obtain information about biochemical reactions, C-C bond formation, and the cleavage of the main metabolites, such as free amino acids, in crude extracts based on the analysis of the (13)C-(13)C coupling pattern in 2D-NMR spectra. For example, the combination of different extraction solvents allows one to distinguish complicated (13)C-(13)C fine couplings at the C2 position of amino acids. As another approach, f1-f3 projection of the HCACO spectrum also helps in the analysis of (13)C-(13)C connectivities. Using these new methods, we present an example that involves monitoring the incorporation profile of [(13)C(6)]glucose into A. thaliana and its metabolic dynamics, which change in a time-dependent manner with atmospheric (12)CO(2) assimilation.     

Metabolic interactions between glucose, glycerol, alanine and acetate in Leishmania braziliensis panamensis promastigotes

13C-nuclear magnetic resonance (NMR) spectroscopy was used to investigate the products of glycerol and acetate metabolism released by Leishmania braziliensis panamensis promastigotes and also to examine the interaction of each of these substrates with glucose or alanine. The NMR data were supplemented by measurements of the rates of oxygen consumption and substrate utilization, and of 14CO2 production from 14C-labeled substrate. Cells incubated with [2-13C]glycerol released acetate, succinate and D-lactate in addition to CO2. Cells incubated with acetate released only CO2. More succinate C-2/C-3 than C-1/C-4 was released from both [2-13C]glycerol and [2-13C]glucose, indicating that succinate was formed predominantly by CO2 fixation followed by reverse flux through part of the Krebs cycle. Some redistribution of the position of labeling was also seen in alanine and pyruvate, suggesting cycling through pyruvate/oxaloacetate/phosphoenolpyruvate. Cells incubated with combinations of 2 substrates consumed oxygen at the same rate as cells incubated with 1 or no substrate, even though the total substrate utilization had increased. When promastigotes were incubated with both glycerol and glucose, the rate of glucose consumption was unchanged but glycerol consumption decreased about 50%, and the rate of 14CO2 production from [1,(3)-14C]glycerol decreased about 60%. Alanine did not affect the rates of consumption of glucose or glycerol, but decreased 14CO2 production from these substrates by increasing flow of label into alanine. Although glucose decreased alanine consumption by 70%, it increased the rate of 14CO2 production from [U-14C]- and [l-14C]alanine by about 20%.(ABSTRACT TRUNCATED AT 250 WORDS)     

Quantification of intracellular metabolic fluxes from fractional enrichment and 13C-13C coupling constraints on the isotopomer distribution in labeled biomass components

A method for the quantification of intracellular metabolic flux distributions from steady-state mass balance constraints and from the constraints posed by the measured 13C labeling state of biomass components is presented. Two-dimensional NMR spectroscopy is used to analyze the labeling state of cell protein hydrolysate and cell wall components. No separation of the biomass hydrolysate is required to measure the degree of 13C-13C coupling and the fractional 13C enrichment in various carbon atom positions. A mixture of [1-13C]glucose and uniformly labeled [13C6]glucose is applied to make fractional 13C enrichment data and measurements of the degree of 13C-13C coupling informative with respect to the intracellular flux distribution. Simulation models that calculate the complete isotopomer distribution in biomass components on the basis of isotopomer mapping matrices are used for the estimation of intracellular fluxes by least-squares minimization. The statistical quality of the estimated intracellular flux distributions is assessed by Monte Carlo methods. Principal component analysis is performed on the outcome of the Monte Carlo procedure to identify groups of fluxes that contribute major parts to the total variance in the multiple flux estimations. The methods described are applied to a steady-state culture of a glucoamylase-producing recombinant Aspergillus niger strain.     

13C metabolic flux analysis for larger scale cultivation using gas chromatography-combustion-isotope ratio mass spectrometry

¹³C-based metabolic flux analysis (¹³CMFA) is limited to smaller scale experiments due to very high costs of labeled substrates. We measured ¹³C enrichment in proteinogenic amino acid hydrolyzates using gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) from a series of parallel batch cultivations of Corynebacterium glutamicum utilizing mixtures of natural glucose and [1-¹³C] glucose, containing 0%, 0.5%, 1%, 2%, and 10% [1-¹³C] glucose. Decreasing the [1-¹³C] glucose content, kinetic isotope effects played an increasing role but could be corrected. From the corrected ¹³C enrichments in vivo fluxes in the central metabolism were determined by numerical optimization. The obtained flux distribution was very similar to those obtained from parallel labeling experiments using conventional high labeling GC-MS method and to published results. The GC-C-IRMS-based method involving low labeling degree of expensive tracer substrate, e.g. 1%, is well suited for larger laboratory and industrial pilot scale fermentations.     

C Isotopomer Analysis of Glutamate by Tandem Mass Spectrometry

Tandem mass spectrometry allows a compound to be isolated from the rest of the sample and dissociated into smaller fragments. We show here that fragmentation of glutamate mass isotopomers yields additional mass spectral data that significantly improve the analysis of metabolic fluxes compared to full-scan mass spectrometry. In order to validate the technique, tandem and full-scan mass spectrometry were used along with (13)C NMR to analyze glutamate from rat hearts perfused with three substrate mixtures (5 mM glucose plus 5 mM [2-(13)C]acetate, 5 mM [1-(13)C]glucose plus 5 U/L insulin, and 5 mM glucose plus 1 mM [3-(13)C]pyruvate). Analysis by tandem mass spectrometry showed that the enriched substrate contributed 98 +/- 2, 53 +/- 2, and 84 +/- 7%, respectively, of acetyl-coenzyme A while the rate of anaplerotic substrate entry was 7 +/- 3, 25 +/- 8, and 16 +/- 8%. Similar results were obtained with (13)C NMR data, while values from full-scan data had higher error. We believe that this is the first use of tandem mass spectrometry to determine pathway flux using (13)C-enriched substrates. Although analysis of the citric acid cycle by NMR is simpler (and more intuitive), tandem mass spectrometry has the potential to combine high sensitivity with the high information yield previously available only by NMR.