Incorporating metabolic flux ratios into constraint-based flux analysis by using artificial metabolites and converging ratio determinants

One of the well-established approaches for the quantitative characterization of large-scale underdetermined metabolic network is constraint-based flux analysis, which quantifies intracellular metabolic fluxes to characterize the metabolic status. The system is typically underdetermined, and thus usually is solved by linear programming with the measured external fluxes as constraints. Thus, the intracellular flux distribution calculated may not represent the true values. (13)C-constrained flux analysis allows more accurate determination of internal fluxes, but is currently limited to relatively small metabolic networks due to the requirement of complicated mathematical formulation and limited parameters available. Here, we report a strategy of employing such partial information obtained from the (13)C-labeling experiments as additional constraints during the constraint-based flux analysis. A new methodology employing artificial metabolites and converging ratio determinants (CRDs) was developed for improving constraint-based flux analysis. The CRDs were determined based on the metabolic flux ratios obtained from (13)C-labeling experiments, and were incorporated into the mass balance equations for the artificial metabolites. These new mass balance equations were used as additional constraints during the constraint-based flux analysis with genome-scale E. coli metabolic model, which allowed more accurate determination of intracellular metabolic fluxes.     

Metabolic Flux Responses to Pyruvate Kinase Knockout in Escherichia coli

The intracellular carbon flux distribution in wild-type and pyruvate kinase-deficient Escherichia coli was estimated using biosynthetically directed fractional 13C labeling experiments with [U-13C6]glucose in glucose- or ammonia-limited chemostats, two-dimensional nuclear magnetic resonance (NMR) spectroscopy of cellular amino acids, and a comprehensive isotopomer model. The general response to disruption of both pyruvate kinase isoenzymes in E. coli was a local flux rerouting via the combined reactions of phosphoenolpyruvate (PEP) carboxylase and malic enzyme. Responses in the pentose phosphate pathway and the tricarboxylic acid cycle were strongly dependent on the environmental conditions. In addition, high futile cycling activity via the gluconeogenic PEP carboxykinase was identified at a low dilution rate in glucose-limited chemostat culture of pyruvate kinase-deficient E. coli, with a turnover that is comparable to the specific glucose uptake rate. Furthermore, flux analysis in mutant cultures indicates that glucose uptake in E. coli is not catalyzed exclusively by the phosphotransferase system in glucose-limited cultures at a low dilution rate. Reliability of the flux estimates thus obtained was verified by statistical error analysis and by comparison to intracellular carbon flux ratios that were independently calculated from the same NMR data by metabolic flux ratio 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.     

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.     

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.     

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.     

Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS.

We describe here a novel methodology for rapid diagnosis of metabolic changes, which is based on probabilistic equations that relate GC-MS-derived mass distributions in proteinogenic amino acids to in vivo enzyme activities. This metabolic flux ratio analysis by GC-MS provides a comprehensive perspective on central metabolism by quantifying 14 ratios of fluxes through converging pathways and reactions from [1-13C] and [U-13C]glucose experiments. Reliability and accuracy of this method were experimentally verified by successfully capturing expected flux responses of Escherichia coli to environmental modifications and seven knockout mutations in all major pathways of central metabolism. Furthermore, several mutants exhibited additional, unexpected flux responses that provide new insights into the behavior of the metabolic network in its entirety. Most prominently, the low in vivo activity of the Entner-Doudoroff pathway in wild-type E. coli increased up to a contribution of 30% to glucose catabolism in mutants of glycolysis and TCA cycle. Moreover, glucose 6-phosphate dehydrogenase mutants catabolized glucose not exclusively via glycolysis, suggesting a yet unidentified bypass of this reaction. Although strongly affected by environmental conditions, a stable balance between anaplerotic and TCA cycle flux was maintained by all mutants in the upper part of metabolism. Overall, our results provide quantitative insight into flux changes that bring about the resilience of metabolic networks to disruption.     

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.     

Metabolic flux analysis with a comprehensive isotopomer model in Bacillus subtilis

Fluxes in central carbon metabolism of a genetically engineered, riboflavin-producing Bacillus subtilis strain were investigated in glucose-limited chemostat cultures at low (0.11 h(-1)) and high (0.44 h(-1)) dilution rates. Using a mixture of 10% [U-(13)C] and 90% glucose labeled at natural abundance, (13)C-labeling experiments were carried out to provide additional information for metabolic flux balancing. The resulting labeling pattern in the proteinogenic amino acids were analyzed by two-dimensional [(13)C, (1)H] nuclear magnetic resonance (NMR) spectroscopy. To account rigorously for all available data from these experiments, we developed a comprehensive isotopomer model of B. subtilis central metabolism. Using this model, intracellular carbon net and exchange fluxes were estimated on the basis of validated physiological data and biomass composition in combination with 2D NMR data from 45 individual carbon atom spectra in the amino acids. Glucose catabolism proceeded primarily via glycolysis but pentose phosphate pathway fluxes increased with increasing growth rate. Moreover, significant back fluxes from the TCA cycle to the lower part of glycolysis via the gluconeogenic PEP carboxykinase were detected. The malic enzyme reaction, in contrast, was found to be inactive. A thorough statistical analysis was performed to prove the reliability of the isotopomer balance model and the obtained results. Specifically, a chi(2) test was applied to validate the model and the chi-square criterion was used to explore the sensitivity of model predictions to the experimental data.     

Responses of the central metabolism in Escherichia coli to phosphoglucose isomerase and glucose-6-phosphate dehydrogenase knockouts

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.     

Network flux analysis: impact of 13C-substrates on metabolism in Arabidopsis thaliana cell suspension cultures

The aim of this study was to test the assumption that (13)C-enrichment of respiratory substrate does not perturb metabolism. Cell suspension cultures of Arabidopsis thaliana were grown in MS medium containing unlabelled glucose (with (13)C at natural abundance), 100% [1-(13)C]glucose, 100% [U-(13)C(6)]glucose or 10% [U-(13)C(6)]glucose plus 90% unlabelled glucose. There was no significant difference in the metabolism of [U-(14)C]glucose between the cultures. Similarly, the pattern of (14)CO(2) release from specifically labelled [(14)C]-substrates was unaffected. Principal component analysis of (13)C-decoupled (1)H NMR metabolite fingerprints of cell extracts was unable to discriminate between the different culture conditions. It is concluded that (13)C-enrichment of the growth substrate has no effect on flux through the central pathways of carbon metabolism in higher plants. This conclusion supports the implicit assumption in metabolic flux analysis that steady-state (13)C-labelling does not perturb fluxes through the reactions of the metabolic network it seeks to quantify.     

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.     

Metabolic flux analysis of CHO cells in perfusion culture by metabolite balancing and 2D [13C, 1H] COSY NMR spectroscopy

The physiological state of CHO cells in perfusion culture was quantified by determining fluxes through the bioreaction network using ¹³C glucose and 2D-NMR spectroscopy. CHO cells were cultivated in a 2.5 L perfusion bioreactor with glucose and glutamine as the primary carbon and energy sources. The reactor was inoculated at a cell density of 8×10⁶ cells/mL and operated at ～10×10⁶ cells/mL using unlabeled glucose for the first 13 days. The second phase lasted 12 days and the medium consisted of 10% [U-¹³C]glucose, 40% labeled [1-¹³C]glucose with the balance unlabeled. After the culture attained isotopic steady state, biomass samples from the last 3 days of cultivation were considered representative and used for flux estimation. They were hydrolyzed and analyzed by 2D [¹³C, ¹H] COSY measurements using the heteronuclear single quantum correlation sequence with gradients for artifacts suppression. Metabolic fluxes were determined using the 13C-Flux software package by minimizing the residuals between the experimental and the simulated NMR data. Normalized residuals exhibited a Gaussian distribution indicating good model fit to experimental data. The glucose consumption rate was 5-fold higher than that of glutamine with 41% of glucose channeled through the pentose phosphate pathway. The fluxes at the pyruvate branch point were almost equally distributed between lactate and the TCA cycle (55% and 45%, respectively). The anaplerotic conversion of pyruvate to oxaloacetate by pyruvate carboxylase accounted for 10% of the pyruvate flux with the remaining 90% entering the TCA cycle through acetyl-CoA. The conversion of malate to pyruvate catalyzed by the malic enzyme was 70% higher than that for the anaplerotic reaction catalyzed by pyruvate carboxylase. Most amino acid catabolic and biosynthetic fluxes were significantly lower than the glycolytic and TCA cycle fluxes. Metabolic flux data from NMR analysis validated a simplified model where metabolite balancing was used for flux estimation. In this reduced flux space, estimates from these two methods were in good agreement. This simplified model can routinely be used in bioprocess development experiments to estimate metabolic fluxes with much reduced analytical investment. The high resolution flux information from 2D-NMR spectroscopy coupled with the capability to validate a simplified metabolite balancing based model for routine use make ¹³C-isotopomer analysis an attractive bioprocess development tool for mammalian cell cultures.     

Analysis of Escherichia coli anaplerotic metabolism and its regulation mechanisms from the metabolic responses to altered dilution rates and phosphoenolpyruvate carboxykinase knockout

The gluconeogenic phosphoenolpyruvate (PEP) carboxykinase is active in Escherichia coli during its growth on glucose. The present study investigated the influence of growth rates and PEP carboxykinase knockout on the anaplerotic fluxes in E. coli. The intracellular fluxes were determined using the complementary methods of flux ratio analysis and metabolic flux analysis based on [U-(13)C(6)]glucose labeling experiments and 2D nuclear magnetic resonance (NMR) spectroscopy of cellular amino acids and glycerol. Significant activity of PEP carboxykinase was identified in wild-type E. coli, and the ATP dissipation for the futile cycling via this reaction accounted for up to 8.2% of the total energy flux. Flux analysis of pck deletion mutant revealed that abolishment of PEP carboxykinase activity resulted in a remarkably reduced flux through the anaplerotic PEP carboxylase and the activation of the glyoxylate shunt, with 23% of isocitrate found being channeled in the glyoxylate shunt. The changes in intracellular metabolite concentrations and specific enzyme activities associated with different growth rates and pck deletion, were also determined. Combining the measurement data of in vivo fluxes, metabolite concentrations and enzyme activities, the in vivo regulations of PEP carboxykinase flux, PEP carboxylation, and glyoxylate shunt in E. coli are discussed.     

Evidence for transketolase-like TKTL1 flux in CHO cells based on parallel labeling experiments and 13C-metabolic flux analysis

The pentose phosphate pathway (PPP) is a fundamental component of cellular metabolism. It provides precursors for the biosynthesis of nucleotides and contributes to the production of reducing power in the form of NADPH. It has been hypothesized that mammalian cells may contain a hidden reaction in PPP catalyzed by transketolase-like protein 1 (TKTL1) that is closely related to the classical transketolase enzyme; however, until now there has been no direct experimental evidence for this reaction. In this work, we have applied state-of-the-art techniques in ¹³C metabolic flux analysis (¹³C-MFA) based on parallel labeling experiments and integrated flux fitting to estimate the TKTL1 flux in CHO cells. We identified a set of three parallel labeling experiments with [1-¹³C]glucose+[4,5,6-¹³C]glucose, [2-¹³C]glucose+[4,5,6-¹³C]glucose, and [3-¹³C]glucose+[4,5,6-¹³C]glucose and developed a new method to measure ¹³C-labeling of fructose 6-phosphate by GC-MS that allows intuitive interpretation of mass isotopomer distributions to determine key fluxes in the model, including glycolysis, oxidative PPP, non-oxidative PPP, and the TKTL1 flux. Using these tracers we detected a significant TKTL1 flux in CHO cells at the stationary phase. The flux results suggest that the main function of oxidative PPP in CHO cells at the stationary phase is to fuel the TKTL1 reaction. Overall, this study demonstrates for the first time that carbon atoms can be lost in the PPP, by means other than the oxidative PPP, and that this loss of carbon atoms is consistent with the hypothesized TKTL1 reaction in mammalian cells.     

Bioreaction network topology and metabolic flux ratio analysis by biosynthetic fractional 13C labeling and two-dimensional NMR spectroscopy

Biosynthetically directed fractional 13C labeling of the proteinogenic amino acids is achieved by feeding a mixture of uniformly 13C-labeled and unlabeled carbon source compounds into a bioreaction network. Analysis of the resulting labeling pattern enables both a comprehensive characterization of the network topology and the determination of metabolic flux ratios. Attractive features with regard to routine applications are (i) an inherently small demand for 13C-labeled source compounds and (ii) the high sensitivity of two-dimensional [13C,1H]-correlation nuclear magnetic resonance spectroscopy for analysis of 13C-labeling patterns. A user-friendly program, FCAL, is available to allow rapid data analysis. This novel approach, which recently also has been employed in conjunction with metabolic flux balancing to obtain reliable estimates of in vivo fluxes, enables efficient support of metabolic engineering and biotechnology process design.     

A flux model of glycolysis and the oxidative pentosephosphate pathway in developing Brassica napus embryos

Developing oilseeds synthesize large quantities of triacylglycerol from sucrose and hexose. To understand the fluxes involved in this conversion, a quantitative metabolic flux model was developed and tested for the reaction network of glycolysis and the oxidative pentose phosphate pathway (OPPP). Developing Brassica napus embryos were cultured with [U-13C6]glucose, [1-13C]glucose, [6-13C]glucose, [U-13C12]sucrose, and/or [1,2-13C2]glucose and the labeling patterns in amino acids, lipids, sucrose, and starch were measured by gas chromatography/mass spectrometry and NMR. Data were used to verify a reaction network of central carbon metabolism distributed between the cytosol and plastid. Computer simulation of the steady state distribution of isotopomers in intermediates of the glycolysis/OPPP network was used to fit metabolic flux parameters to the experimental data. The observed distribution of label in cytosolic and plastidic metabolites indicated that key intermediates of glycolysis and OPPP have similar labeling in these two compartments, suggesting rapid exchange of metabolites between these compartments compared with net fluxes into end products. Cycling between hexose phosphate and triose phosphate and reversible transketolase velocity were similar to net glycolytic flux, whereas reversible transaldolase velocity was minimal. Flux parameters were overdetermined by analyzing labeling in different metabolites and by using data from different labeling experiments, which increased the reliability of the findings. Net flux of glucose through the OPPP accounts for close to 10% of the total hexose influx into the embryo. Therefore, the reductant produced by the OPPP accounts for at most 44% of the NADPH and 22% of total reductant needed for fatty acid synthesis.     

Quantification of Metabolic Rearrangements During Neural Stem Cells Differentiation into Astrocytes by Metabolic Flux Analysis

Proliferation and differentiation of neural stem cells (NSCs) have a crucial role to ensure neurogenesis and gliogenesis in the mammalian brain throughout life. As there is growing evidence for the significance of metabolism in regulating cell fate, knowledge on the metabolic programs in NSCs and how they evolve during differentiation into somatic cells may provide novel therapeutic approaches to address brain diseases. In this work, we applied a quantitative analysis to assess how the central carbon metabolism evolves upon differentiation of NSCs into astrocytes. Murine embryonic stem cell (mESC)-derived NSCs and astrocytes were incubated with labelled [1-¹³C]glucose and the label incorporation into intracellular metabolites was followed by GC-MS. The obtained ¹³C labelling patterns, together with uptake/secretion rates determined from supernatant analysis, were integrated into an isotopic non-stationary metabolic flux analysis (¹³C-MFA) model to estimate intracellular flux maps. Significant metabolic differences between NSCs and astrocytes were identified, with a general downregulation of central carbon metabolism during astrocytic differentiation. While glucose uptake was 1.7-fold higher in NSCs (on a per cell basis), a high lactate-secreting phenotype was common to both cell types. Furthermore, NSCs consumed glutamine from the medium; the highly active reductive carboxylation of alpha-ketoglutarate indicates that this was converted to citrate and used for biosynthetic purposes. In astrocytes, pyruvate entered the TCA cycle mostly through pyruvate carboxylase (81%). This pathway supported glutamine and citrate secretion, recapitulating well described metabolic features of these cells in vivo. Overall, this fluxomics study allowed us to quantify the metabolic rewiring accompanying astrocytic lineage specification from NSCs.