Quantification Of Metabolic Fluxes Research Articles

Deuterated water as a substrate-agnostic isotope tracer for investigating reversibility and thermodynamics of reactions in central carbon metabolism

Stable isotope tracers are a powerful tool for the quantitative analysis of microbial metabolism, enabling pathway elucidation, metabolic flux quantification, and assessment of reaction and pathway thermodynamics. 13C and 2H metabolic flux analysis commonly relies on isotopically labeled carbon substrates, such as glucose. However, the use of 2H-labeled nutrient substrates faces limitations due to their high cost and limited availability in comparison to 13C-tracers. Furthermore, isotope tracer studies in industrially relevant bacteria that metabolize complex substrates such as cellulose, hemicellulose, or lignocellulosic biomass, are challenging given the difficulty in obtaining these as isotopically labeled substrates.In this study, we examine the potential of deuterated water (2H2O) as an affordable, substrate-neutral isotope tracer for studying central carbon metabolism. We apply 2H2O labeling to investigate the reversibility of glycolytic reactions across three industrially relevant bacterial species -C. thermocellum, Z. mobilis, and E. coli-harboring distinct glycolytic pathways with unique thermodynamics. We demonstrate that 2H2O labeling recapitulates previous reversibility and thermodynamic findings obtained with established 13C and 2H labeled nutrient substrates. Furthermore, we exemplify the utility of this 2H2O labeling approach by applying it to high-substrate C. thermocellum fermentations -a setting in which the use of conventional tracers is impractical-thereby identifying the glycolytic enzyme phosphofructokinase as a major bottleneck during high-substrate fermentations and unveiling critical insights that will steer future engineering efforts to enhance ethanol production in this cellulolytic organism.This study demonstrates the utility of deuterated water as a substrate-agnostic isotope tracer for examining flux and reversibility of central carbon metabolic reactions, which yields biological insights comparable to those obtained using costly 2H-labeled nutrient substrates.

Comprehensive quantification of metabolic flux during acute cold stress in mice

Cold-induced thermogenesis (CIT) is widely studied as a potential avenue to treat obesity, but a thorough understanding of the metabolic changes driving CIT is lacking. Here, we present a comprehensive and quantitative analysis of the metabolic response to acute cold exposure, leveraging metabolomic profiling and minimally perturbative isotope tracing studies in unanesthetized mice. During cold exposure, brown adipose tissue (BAT) primarily fueled the tricarboxylic acid (TCA) cycle with fat in fasted mice and glucose in fed mice, underscoring BAT's metabolic flexibility. BAT minimally used branched-chain amino acids or ketones, which were instead avidly consumed by muscle during cold exposure. Surprisingly, isotopic labeling analyses revealed that BAT uses glucose largely for TCA anaplerosis via pyruvate carboxylation. Finally, we find that cold-induced hepatic gluconeogenesis is critical for CIT during fasting, demonstrating a key functional role for glucose metabolism. Together, these findings provide a detailed map of the metabolic rewiring driving acute CIT.

Improved 13C metabolic flux analysis in Escherichia coli metabolism: application of a high-resolution MS (GC–EI–QTOF) for comprehensive assessment of MS/MS fragments

Abstract Gas chromatography–tandem mass spectrometry with electron ionization (GC–EI–MS/MS) provides rich information on stable-isotope labeling for 13C-metabolic flux analysis (13C-MFA). To pave the way for the routine application of tandem MS data for metabolic flux quantification, we aimed to compile a comprehensive library of GC–EI–MS/MS fragments of tert-butyldimethylsilyl (TBDMS) derivatized proteinogenic amino acids. First, we established an analytical workflow that combines high-resolution gas chromatography-quadrupole time-of-flight mass spectrometry and fully 13C-labeled biomass to identify and structurally elucidate tandem MS amino acid fragments. Application of the high-mass accuracy MS procedure resulted into the identification of 129 validated precursor–product ion pairs of 13 amino acids with 30 fragments being accepted for 13C-MFA. The practical benefit of the novel tandem MS data was demonstrated by a proof–of–concept study, which confirmed the importance of the compiled library for high-resolution 13C-MFA. One sentence summary An analytical workflow that combines high-resolution mass spectrometry (MS) and fully 13C-labeled biomass to identify and structurally elucidate tandem MS amino acid fragments, which provide positional information and therefore offering significant advantages over traditional MS to improve 13C-metabolic flux analysis.

Genome Scale Modeling to Study the Metabolic Competition between Cells in the Tumor Microenvironment.

Simple SummaryImmune and cancer cells compete for nutrients within the tumor microenvironment, leading to a metabolic battle between these cell populations. In this battle, tumor cells reprogram their metabolism for a high demand of building blocks and energy and to gain advantages over immune cells. To study these mechanisms, we require the quantification of metabolic fluxes, which can be estimated at the genome-scale, with constraint-based or kinetic modeling.The tumor’s physiology emerges from the dynamic interplay of numerous cell types, such as cancer cells, immune cells and stromal cells, within the tumor microenvironment. Immune and cancer cells compete for nutrients within the tumor microenvironment, leading to a metabolic battle between these cell populations. Tumor cells can reprogram their metabolism to meet the high demand of building blocks and ATP for proliferation, and to gain an advantage over the action of immune cells. The study of the metabolic reprogramming mechanisms underlying cancer requires the quantification of metabolic fluxes which can be estimated at the genome-scale with constraint-based or kinetic modeling. Constraint-based models use a set of linear constraints to simulate steady-state metabolic fluxes, whereas kinetic models can simulate both the transient behavior and steady-state values of cellular fluxes and concentrations. The integration of cell- or tissue-specific data enables the construction of context-specific models that reflect cell-type- or tissue-specific metabolic properties. While the available modeling frameworks enable limited modeling of the metabolic crosstalk between tumor and immune cells in the tumor stroma, future developments will likely involve new hybrid kinetic/stoichiometric formulations.

HEME Degradation Enzyme Biliverdin IXb Reductase Is Required for Stem Cell Glutamine Metabolism

Bioenergetic requirements of pluripotent stem cells (PSC) vary with lineage fate, and cellular adaptations rely largely on substrate availability and mitochondrial function to balance TCA-derived anabolic and redox-regulated antioxidant functions. Heme (protoporphyrin IX complexed with iron) serves as an indispensable co-factor for all aerobic cells, and its cytotoxicity is minimized by a two-step catabolic reaction that generates biliverdin (BV) and bilirubin (BR) tetrapyrroles, the penultimate step regulated by two non-redundant biliverdin reductases (IXa, BLVRA and IXb, BLVRB) retaining isomeric specificity and NAD(P)H-dependent redox coupling linked to BR antioxidant function. Thus, heme biosynthesis (initiated by the condensation of glycine and succinyl CoA) can be considered a linear pathway that utilizes cataplerotic TCA-derived carbon (derived from glucose and glutamine) linked to the heme degradation pathway and bilirubin excretion. Given the overlapping glucose/glutamine requirements in both heme synthesis and PSC bioenergetics, we studied consequences of dysregulated heme metabolism by targeted BLVRB disruption in iPSCs derived from human umbilical cord CD34+ hematopoietic cells. Compared to control iPSCs, BLVRB-deficient iPSCs had no reciprocal BLVRA induction, no alterations in heme oxygenase expression, and no differences in isomeric BV accumulation, although phenotypically defective in antioxidant handling with exaggerated apoptotic cell death. To better delineate metabolic pathway perturbations causally implicated in BLVRB- deficient antioxidant function and cell viability, we generated gene/metabolite clusters and an extended network plot formulated on RNASeq data coupled with liquid chromatography/mass spectrometric-based targeted metabolomics profiling of 290 intracellular metabolites. Metabolic enrichment with topological pathway analysis identified a limited number of defective pathways involving purine/pyrimidine nucleotide synthesis, redox homeostasis (pentose phosphate pathway, PPP) and TCA cycle intermediates (a-ketoglutarate, fumarate, and malate). Mitochondrial staining using TMRE as a functional and quantifiable marker of the mitochondrial transmembrane potential (DYm) identified no defect across the genotypes, although BLVRB -deficient iPSCs demonstrated defective basal and maximal oxygen consumption rates (OCR) restricted to glutamine (but not glucose) utilization. Metabolic flux quantification using [U6-13C] glucose revealed high-level and comparable (>97%) fractional labeling of 13C lactate across the genotypes, consistent with an active glycolytic metabolism that was comparable between control and BLVRB-/- iPSCs. In contrast, isotopic tracing using [U-13C5] glutamine demonstrated statistically-diminished glutamate-derived aKG accumulation (along with downstream TCA metabolites fumarate and malate isotopomers), results confirming rewired glutamine TCA entry, and reliance on glucose as a preferred substrate. Since the parallel PPP pathway utilizes glycolysis as the preferred substrate for generating both reducing equivalents (NADPH) and essential nucleotide component ribose-5-phosphate, we characterized three-dimensional embryoid body (EB) formation in the presence of the PPP pathway inhibitor 6-aminonicotinamide (6-AN), establishing statistically-decreased EB size (p<0.001) compared to control iPSCs. These data place heme catabolism in a crucial pathway of glutamine-regulated bioenergetic metabolism, and also suggest in principle that BLVRB inhibition represents an alternative strategy for modulating cellular glutamine utilization, a key substrate for cancer and hematopoietic metabolism. DisclosuresNo relevant conflicts of interest to declare.

Metabolic mapping of glioblastoma stem cells reveals NADH fluxes associated with glioblastoma phenotype and survival.

.Significance: Glioblastoma multiforme (GBM) is the most frequently diagnosed adult primary brain malignancy with poor patient prognosis. GBM can recur despite aggressive treatment due to therapeutically resistant glioblastoma stem cells (GSCs) that may exhibit metabolic plasticity.Aim: Intrinsic nicotinamide adenine dinucleotide (NADH) fluorescence can be acquired with fluorescence lifetime imaging microscopy (FLIM) to examine its bound and free metabolic states in GSC and GBM tissues.Approach: We compared the mean NADH fluorescence lifetime in live human GSCs and normal neural stem cells and validated those results by measuring oxygen consumption rates (OCRs). We also examined the role that invasive versus less-invasive GSCs had on tumor metabolism by measuring the mean NADH lifetimes and the relative amount of the longer-lived component of NADH and correlated these results with survival in an orthotopic mouse xenograft model.Results: Mean NADH lifetime, amount of bound NADH, and OCR were increased in GSCs. Compared with normal mouse brain, mean NADH lifetimes were longer for all GBM tissues. Invasive xenografts had higher relative amounts of the longer-lived NADH component, and this correlated with decreased survival.Conclusions: FLIM offers cellular resolution quantification of metabolic flux in GBM phenotypes, potentially informing biomedical researchers on improved therapeutic approaches.

Simultaneous tracers and a unified model of positional and mass isotopomers for quantification of metabolic flux in liver

Computational models based on the metabolism of stable isotope tracers can yield valuable insight into the metabolic basis of disease. The complexity of these models is limited by the number of tracers and the ability to characterize tracer labeling in downstream metabolites. NMR spectroscopy is ideal for multiple tracer experiments since it precisely detects the position of tracer nuclei in molecules, but it lacks sensitivity for detecting low-concentration metabolites. GC-MS detects stable isotope mass enrichment in low-concentration metabolites, but lacks nuclei and positional specificity. We performed liver perfusions and in vivo infusions of 2H and 13C tracers, yielding complex glucose isotopomers that were assigned by NMR and fit to a newly developed metabolic model. Fluxes regressed from 2H and 13C NMR positional isotopomer enrichments served to validate GC-MS-based flux estimates obtained from the same experimental samples. NMR-derived fluxes were largely recapitulated by modeling the mass isotopomer distributions of six glucose fragment ions measured by GC-MS. Modest differences related to limited fragmentation coverage of glucose C1–C3 were identified, but fluxes such as gluconeogenesis, glycogenolysis, cataplerosis and TCA cycle flux were tightly correlated between the methods. Most importantly, modeling of GC-MS data could assign fluxes in primary mouse hepatocytes, an experiment that is impractical by 2H or 13C NMR.

Separate Roles of Asparagine and Glutamine in Cytostatic Effect of L-Asparaginase - Stable Isotope Tracing Approach

L-asparaginase (ASNase) is one of the crucial components of acute lymphoblastic leukemia (ALL) therapy. Although we have previously shown that ASNase triggers metabolic reprogramming of leukemic cells, the significance and interconnections of the changes have not yet been elucidated. Metabolic reprogramming is an accompanying feature in therapy response and is also triggered by commonly used cytostatic drugs. ASNase hydrolyzes two non-essential amino acids asparagine (Asn) and glutamine (Gln). Therapeutic ASNase concentration used in vitro transforms all Asn and Gln to aspartate (Asp) and glutamate (Glu), respectively. We employed stable isotope tracing to understand the complexity and interconnection of metabolic processes altered in leukemia cells exposed to ASNase. Stable isotope tracing is a unique method enabling the quantification of metabolic flux. When substrate with 13C is metabolized by cells, enzymatic reactions rearrange 13C atoms resulting in specific labeling patterns in downstream metabolites. Therefore, this method allows us to determine exact pathways which are used to metabolize labeled nutrient. Glucose and Gln media concentrations were adjusted to 8mM and 1mM, respectively, to more resemble physiological conditions. All experiments were done with 0.8 IU/ml ASNase which is close to the plasma ASNase level in the induction phase of ALL treatment. We studied the effect of ASNase on two B-ALL cell lines with different sensitivity to this cytostatic drug: REH (IC50=0.000231 IU/ml) and NALM6 (IC50=0.328894 IU/ml). U13C glucose tracing revealed that although pyruvate and lactate intracellular concentrations are not changed after ASNase treatment, the relative flux from glucose to these metabolites (expressed as M+3 which represents 3 13C atoms in 1 molecule) is lowered (e.g. lactate (M+3): NALM6 - (0.5898±0.0026) vs (0.4473±0.0031), p&lt;0.0001); REH - (0.3417±0.0023) vs (0.2411±0.0024), p&lt;0.0001). Unlike glycolytic intermediates, the levels of tricarboxylic acid (TCA) cycle intermediates are lowered after ASNase administration (e.g. relative quantification of malate: NALM6 - (1.6120±0.1202) vs (0.4358±0.0247), p&lt;0.0001; REH - (0.8231±0.0689) vs (0.2484±0.0573), p&lt;0.0001). Interestingly, the relative flux from glucose to TCA cycle (expressed as e.g. malate (M+1-M+4) which represents at least 1 13C atom in a malate molecule) is increased in NALM6 ((0.0947±0.0021) vs (0.3605±0.0070), p&lt;0.0001) and lowered in REH cells ((0.3109±0.0100) vs (0.1449±0.0185), p&lt;0.0001) after ASNase. Since in our setting ASNase depletes both Asn and Gln, we tested what are the separate roles of Asn and Gln depletion in ASNase treatment. We discovered that omitting Gln from the media caused that TCA cycle intermediates are lowered in both cell lines to the same extent as after ASNase. Moreover, the flux from glucose to TCA cycle resembles the one after ASNase in both cell lines. In contrast the results of Asn withdrawal showed that level of TCA cycle intermediates are unchanged. The relative flux from glucose to TCA cycle is mildly downregulated without Asn in the media in both cell lines (e.g. malate (M+1-M+4): NALM6 - (0.1485±0.0014) vs (0.1158±0.0004), p&lt;0.0001; REH - (0.2662±0.0031) vs (0.2024±0.0015), p&lt;0.0001). Many studies emerged that highlight TCA cycle importance in Asp production and hence in sustaining cell viability and proliferation. Although TCA cycle is diminished after ASNase treatment, our results showed that both NALM6 and REH cells are able to maintain Asp and Glu levels. Using U13C Asp and U13C Glu, we discovered that, unexpectedly, both cell lines are able to import Asp and Glu from the media in a dose-dependent manner. Altogether, our results demonstrate different consequences of Asn and Gln depletion during ASNase treatment. According previous studies it is probably only Asn that is completely depleted after ASNase administration in ALL therapy with unchanged or lowered Gln concentration. Therefore, this fact should be considered in in vitro studies where Gln depletion could blur the effect of Asn depletion. Above that, we showed that leukemia cells are able to uptake Asp and Glu. This indicates the possible way how leukemic cells could cope with ASNase treatment. This work is supported by NV18-07-00129 and Charles University Grant agency 79421. Disclosures No relevant conflicts of interest to declare.

Tandem Mass Spectrometry for 13C Metabolic Flux Analysis: Methods and Algorithms Based on EMU Framework.

In the past two decades, 13C metabolic flux analysis (13C-MFA) has matured into a powerful and widely used scientific tool in metabolic engineering and systems biology. Traditionally, metabolic fluxes have been determined from measurements of isotopic labeling by means of mass spectrometry (MS) or nuclear magnetic resonance (NMR). In recent years, tandem MS has emerged as a new analytical technique that can provide additional information for high-resolution quantification of metabolic fluxes in complex biological systems. In this paper, we present recent advances in methods and algorithms for incorporating tandem MS measurements into existing 13C-MFA approaches that are based on the elementary metabolite units (EMU) framework. Specifically, efficient EMU-based algorithms are presented for simulating tandem MS data, tracing isotopic labeling in biochemical network models and for correcting tandem MS data for natural isotope abundances.

In vivo 13C MRS in the mouse brain at 14.1 Tesla and metabolic flux quantification under infusion of [1,6-13C2]glucose

In vivo 13C magnetic resonance spectroscopy (MRS) enables the investigation of cerebral metabolic compartmentation while, e.g. infusing 13C-labeled glucose. Metabolic flux analysis of 13C turnover previously yielded quantitative information of glutamate and glutamine metabolism in humans and rats, while the application to in vivo mouse brain remains exceedingly challenging. In the present study, 13C direct detection at 14.1 T provided highly resolved in vivo spectra of the mouse brain while infusing [1,6-13C2]glucose for up to 5 h. 13C incorporation to glutamate and glutamine C4, C3, and C2 and aspartate C3 were detected dynamically and fitted to a two-compartment model: flux estimation of neuron-glial metabolism included tricarboxylic acid cycle (TCA) flux in astrocytes (Vg = 0.16 ± 0.03 µmol/g/min) and neurons (VTCAn = 0.56 ± 0.03 µmol/g/min), pyruvate carboxylase activity (VPC = 0.041 ± 0.003 µmol/g/min) and neurotransmission rate (VNT = 0.084 ± 0.008 µmol/g/min), resulting in a cerebral metabolic rate of glucose (CMRglc) of 0.38 ± 0.02 µmol/g/min, in excellent agreement with that determined with concomitant 18F-fluorodeoxyglucose positron emission tomography (18FDG PET).We conclude that modeling of neuron-glial metabolism in vivo is accessible in the mouse brain from 13C direct detection with an unprecedented spatial resolution under [1,6-13C2]glucose infusion.

Dose-response in a high density three-dimensional liver device with real-time bioenergetic and metabolic flux quantification

Real-time dose-response curves for fructose have been non-invasively determined in primary rat hepatocyte alginate spheroids cultured in a NMR-compatible fluidized-bed bioreactor. Using 13C–labeled glucose and glycine culture medium, fructose dose was compared to glucose uptake and glycogen synthesis rate using 13C NMR spectroscopy, and to ATP and fructose-1-phosphate concentration using 31P NMR spectroscopy. A highly efficient multicoaxial perfusion system maintains high density 3-D hepatocyte cultures, permitting 13C and 31P NMR spectral time courses with 1min time points. The perfusion system was turned off to demonstrate its efficiency and effect on the metabolites. Within 16min, glycogen plummeted, lactate became the largest 13C–glucose metabolite via anaerobic glycolysis, while glutathione was the largest 13C–glycine metabolite. ATP depletion and fructose-1-phosphate formation demonstrated a dose response with a 3h EC50 of 19mM±8.9mM and 17.4mM±3.7mM, respectively. Computational modeling of mass transfer corroborated experimental results and helped determine the optimal bioreactor loading densities, oxygen concentration, and perfusion rates to maintain physiologically-relevant nutrient levels. The total bioreactor plus perfusion loop has a dead volume of 2ml, and contains 5 million hepatocytes. Due to the non-invasive measurements, there is a reduction of animal tissue by an order-of-magnitude, depending on the number of time points in an experiment. This dynamic flux approach may have generic utility for dose-response studies monitoring multiple metabolic reactions in other primary mammalian cells, such as human, that have strict oxygen demands.

Bioreactor for quantification of cell metabolism by MR-hyperpolarization

Magnetic resonance (MR)-hyperpolarization based on dynamic nuclear polarization provides a strongly increased signal intensity allowing real-time metabolic spectroscopic imaging. The MR-hyperpolarization technique is, however, still limited by low signal when applied to cells in culture. To overcome this challenge we propose an integrated bioreactor and radio frequency coil system optimized to enhance signal sensitivity. The system allows 13C MR-hyperpolarization-based quantification of metabolic flux in cells grown in a 3D-printed scaffold. The scaffold is designed to enhance the cell density by providing a large surface area for accelerated growth and at the same time provides a controlled culture environment in terms of nutrient flow, oxygen supply and minimal disturbance of the cells. This study demonstrates that a bioreactor optimized for hyperpolarized 13C magnetic resonance spectroscopy in scaffolds can be used to assess fast metabolic fluxes in cultivated cells.

Direct noninvasive estimation of myocardial tricarboxylic acid cycle flux in vivo using hyperpolarized 13C magnetic resonance

BackgroundThe heart relies on continuous energy production and imbalances herein impair cardiac function directly. The tricarboxylic acid (TCA) cycle is the primary means of energy generation in the healthy myocardium, but direct noninvasive quantification of metabolic fluxes is challenging due to the low concentration of most metabolites. Hyperpolarized 13C magnetic resonance spectroscopy (MRS) provides the opportunity to measure cellular metabolism in real time in vivo. The aim of this work was to noninvasively measure myocardial TCA cycle flux (VTCA) in vivo within a single minute. Methods and resultsHyperpolarized [1-13C]acetate was administered at different concentrations in healthy rats. 13C incorporation into [1-13C]acetylcarnitine and the TCA cycle intermediate [5-13C]citrate was dynamically detected in vivo with a time resolution of 3s. Different kinetic models were established and evaluated to determine the metabolic fluxes by simultaneously fitting the evolution of the 13C labeling in acetate, acetylcarnitine, and citrate. VTCA was estimated to be 6.7±1.7μmol·g−1·min−1 (dry weight), and was best estimated with a model using only the labeling in citrate and acetylcarnitine, independent of the precursor. The TCA cycle rate was not linear with the citrate-to-acetate metabolite ratio, and could thus not be quantified using a ratiometric approach. The 13C signal evolution of citrate, i.e. citrate formation was independent of the amount of injected acetate, while the 13C signal evolution of acetylcarnitine revealed a dose dependency with the injected acetate. The 13C labeling of citrate did not correlate to that of acetylcarnitine, leading to the hypothesis that acetylcarnitine formation is not an indication of mitochondrial TCA cycle activity in the heart. ConclusionsHyperpolarized [1-13C]acetate is a metabolic probe independent of pyruvate dehydrogenase (PDH) activity. It allows the direct estimation of VTCA in vivo, which was shown to be neither dependent on the administered acetate dose nor on the 13C labeling of acetylcarnitine. Dynamic 13C MRS coupled to the injection of hyperpolarized [1-13C]acetate can enable the measurement of metabolic changes during impaired heart function.

Recent advances in mapping environmental microbial metabolisms through13C isotopic fingerprints

After feeding microbes with a defined (13)C substrate, unique isotopic patterns (isotopic fingerprints) can be formed in their metabolic products. Such labelling information not only can provide novel insights into functional pathways but also can determine absolute carbon fluxes through the metabolic network via metabolic modelling approaches. This technique has been used for finding pathways that may have been mis-annotated in the past, elucidating new enzyme functions, and investigating cell metabolisms in microbial communities. In this review paper, we summarize the applications of (13)C approaches to analyse novel cell metabolisms for the past 3 years. The isotopic fingerprints (defined as unique isotopomers useful for pathway identifications) have revealed the operations of the Entner-Doudoroff pathway, the reverse tricarboxylic acid cycle, new enzymes for biosynthesis of central metabolites, diverse respiration routes in phototrophic metabolism, co-metabolism of carbon nutrients and novel CO(2) fixation pathways. This review also discusses new isotopic methods to map carbon fluxes in global metabolisms, as well as potential factors influencing the metabolic flux quantification (e.g. metabolite channelling, the isotopic purity of (13)C substrates and the isotopic effect). Although (13)C labelling is not applicable to all biological systems (e.g. microbial communities), recent studies have shown that this method has a significant value in functional characterization of poorly understood micro-organisms, including species relevant for biotechnology and human health.

Metabolic cartography: experimental quantification of metabolic fluxes from isotopic labelling studies

For the past decade, flux maps have provided researchers with an in-depth perspective on plant metabolism. As a rapidly developing field, significant headway has been made recently in computation, experimentation, and overall understanding of metabolic flux analysis. These advances are particularly applicable to the study of plant metabolism. New dynamic computational methods such as non-stationary metabolic flux analysis are finding their place in the toolbox of metabolic engineering, allowing more organisms to be studied and decreasing the time necessary for experimentation, thereby opening new avenues by which to explore the vast diversity of plant metabolism. Also, improved methods of metabolite detection and measurement have been developed, enabling increasingly greater resolution of flux measurements and the analysis of a greater number of the multitude of plant metabolic pathways. Methods to deconvolute organelle-specific metabolism are employed with increasing effectiveness, elucidating the compartmental specificity inherent in plant metabolism. Advances in metabolite measurements have also enabled new types of experiments, such as the calculation of metabolic fluxes based on (13)CO(2) dynamic labelling data, and will continue to direct plant metabolic engineering. Newly calculated metabolic flux maps reveal surprising and useful information about plant metabolism, guiding future genetic engineering of crops to higher yields. Due to the significant level of complexity in plants, these methods in combination with other systems biology measurements are necessary to guide plant metabolic engineering in the future.

FluxMap: A VANTED add-on for the visual exploration of flux distributions in biological networks

BackgroundThe quantification of metabolic fluxes is gaining increasing importance in the analysis of the metabolic behavior of biological systems such as organisms, tissues or cells. Various methodologies (wetlab or drylab) result in sets of fluxes which require an appropriate visualization for interpretation by scientists. The visualization of flux distributions is a necessary prerequisite for intuitive flux data exploration in the context of metabolic networks.ResultsWe present FluxMap, a tool for the advanced visualization and exploration of flux data in the context of metabolic networks. The template-based flux data import assigns flux values and optional quality parameters (e. g. the confidence interval) to biochemical reactions. It supports the discrimination between mass and substance fluxes, such as C- or N-fluxes. After import, flux data mapping and network-based visualization allow the interactive exploration of the dataset. Various visualization options enable the user to adapt layout and network representation according to individual purposes.ConclusionsThe Vanted add-on FluxMap comprises a comprehensive set of functionalities for visualization and advanced visual exploration of flux distributions in biological networks. It is available as a Java open source tool from http://www.vanted.org/fluxmap.

Computational quantification of metabolic fluxes from a single isotope snapshot: application to an animal biopsy

Quantitative determination of metabolic fluxes in single tissue biopsies is difficult. We report a novel analysis approach and software package for in vivo flux quantification using stable isotope labeling. We developed a protocol based on brief, timed infusion of (13)C isotope-enriched substrates for the tricarboxylic acid (TCA) cycle followed by quick freezing of tissue biopsies. NMR measurements of tissue extracts were used for flux estimation based on a computational model of carbon transitions between TCA cycle metabolites and related amino acids. To this end, we developed a computational framework in which metabolic systems can be flexibly assembled, simulated and analyzed. Flux parameters were quantified from NMR multiplets by a partial grid search followed by repeated Nelder-Mead optimizations implemented on a computer grid. We implemented a model of the TCA cycle and showed by extensive simulations that the timed infusion protocol reliably quantitates multiple fluxes. Experimental validation of the method was done in vivo on hearts of anesthetized pigs under two different conditions: basal state (n = 7) and cardiac stress caused by infusion of dobutamine (n = 7). About nine tissue samples (40-200 mg dry-weight) were taken per heart. TCA cycle flux was 6.11 +/- 0.28 (SEM) micromol/min x gdw at baseline versus 9.29 +/- 1.03 micromol/min x gdw for dobutamine stress. Oxygen consumption calculated from the TCA cycle flux and from 'gold standard' blood gas-based measurements were close, correlating with r=0.88 (P < 10(-4)). Spatial heterogeneity in metabolic fluxes is detectable amongst the small samples. We propose that our novel isotope snapshot methodology is suitable for flux measurements in biopsies in vivo. Non-profit organizations will, upon request, be granted a non-exclusive license to use the software for internal research and teaching purposes at no charge. A web interface for using the software on our computer grid is available under http://www.ibi.vu.nl/programs/

Flux quantification in central carbon metabolism of Catharanthus roseus hairy roots by 13C labeling and comprehensive bondomer balancing

Methods for accurate and efficient quantification of metabolic fluxes are desirable in plant metabolic engineering and systems biology. Toward this objective, we introduce the application of “bondomers”, a computationally efficient and intuitively appealing alternative to the commonly used isotopomer concept, to flux evaluation in plants, by using Catharanthus roseus hairy roots as a model system. We cultured the hairy roots on (5% w/w U– 13C, 95% w/w naturally abundant) sucrose, and acquired two-dimensional [ 13C, 1H] and [ 1H, 1H] NMR spectra of hydrolyzed aqueous extract from the hairy roots. Analysis of these spectra yielded a data set of 116 bondomers of β-glucans and proteinogenic amino acids from the hairy roots. Fluxes were evaluated from the bondomer data by using comprehensive bondomer balancing. We identified most fluxes in a three-compartmental model of central carbon metabolism with good precision. We observed parallel pentose phosphate pathways in the cytosol and the plastid with significantly different fluxes. The anaplerotic fluxes between phosphoenolpyruvate and oxaloacetate in the cytosol and between malate and pyruvate in the mitochondrion were relatively high (60.1 ± 2.5 mol per 100 mol sucrose uptake, or 22.5 ± 0.5 mol per 100 mol mitochondrial pyruvate dehydrogenase flux). The development of a comprehensive flux analysis tool for this plant hairy root system is expected to be valuable in assessing the metabolic impact of genetic or environmental changes, and this methodology can be extended to other plant systems.

A global optimization approach for metabolic flux analysis based on labeling balances

The flux quantification step in metabolic flux analysis (MFA) includes the mathematical modeling of metabolism (based on both metabolite and isotope balancing) and its optimization, which minimizes a weighted distance between measurements and model predictions. When GC–MS is used for assessing the 13C-labeling in intracellular metabolites, the metabolic flux quantification problem originates a non-convex optimization model with bilinear constraints for which the existence of multiple local minima is a special difficulty. In the present work, we propose a global optimization technique that relies on a spatial branch and bound search. A linearization technique is applied on the constraints from labeling balances, in order to obtain a convex relaxed problem that provides a lower bound to the global optimum; due to the nature of the linearization, the initial variable (measured) and parameter (non-measured) bounds strongly affect the model convergence. The global optimization algorithm estimates fluxes in the central metabolism of Saccharomyces cerevisiae, based on experimental data previously reported [Gombert, A. K., dos Santos, M. M., Christensen, B., Nielsen, J. (2001). Network identification and flux quantification in the central metabolism of Saccharomyces cerevisiae under different conditions of glucose repression. Journal of Bacteriology, 183(4), 1441–1451]. To attain global convergence, a detailed bound tightening procedure is developed. Measured labelings and non-measured net fluxes are the branching variables, and the branching is performed on the one that has the largest difference between its values in the convex and non-convex models. Results were compared to the ones obtained using an evolutionary algorithm that requires extensive computational effort to achieve a feasible solution. We found that there are local solutions with important differences on the central pathways. In the global optimum, the calculated fluxes for the central pathways are similar to the best result obtained by evolutionary search, whereas the quadratic errors for both variable sets, measured labelings and fluxes, are smaller.

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.