Dynamic profiling of the glucose metabolic network in fasted rat hepatocytes using [1,2-13C2]glucose

Advancements in CHO metabolomics: techniques, current state and evolving methodologies

Background: Investigating the metabolic behaviour of different cellular phenotypes, i.e., good/bad grower and/or producer, in production culture is important to identify the key metabolite(s)/pathway(s) that regulate cell growth and/or recombinant protein production to improve the overall yield. Currently, LC-MS, GC-MS and NMR are the most used and advanced technologies for investigating the metabolome. Although contributed significantly in the domain, each technique has its own biasness towards specific metabolites or class of metabolites due to various reasons including variability in the concept of working, sample preparation, metabolite-extraction methods, metabolite identification tools, and databases. As a result, the application of appropriate analytical technique(s) is very critical. Purpose and scope: This review provides a state-of-the-art technological insights and overview of metabolic mechanisms involved in regulation of cell growth and/or recombinant protein production for improving yield from CHO cultures. Summary and conclusion: In this review, the advancements in CHO metabolomics over the last 10 years are traced based on a bibliometric analysis of previous publications and discussed. With the technical advancement in the domain of LC-MS, GC-MS and NMR, metabolites of glycolytic and nucleotide biosynthesis pathway (glucose, fructose, pyruvate and phenylalanine, threonine, tryptophan, arginine, valine, asparagine, and serine, etc.) were observed to be upregulated in exponential-phase thereby potentially associated with cell growth regulation, whereas metabolites/intermediates of TCA, oxidative phosphorylation (aspartate, glutamate, succinate, malate, fumarate and citrate), intracellular NAD+/NADH ratio, and glutathione metabolic pathways were observed to be upregulated in stationary-phase and hence potentially associated with increased cell-specific productivity in CHO bioprocess. Moreover, each of technique has its own bias towards metabolite identification, indicating their complementarity, along with a number of critical gaps in the CHO metabolomics pipeline and hence first time discussed here to identify their potential remedies. This knowledge may help in future study designs to improve the metabolomic coverage facilitating identification of the metabolites/pathways which might get missed otherwise and explore the full potential of metabolomics for improving the CHO bioprocess performances.

Metformin lowers glucose 6-phosphate in hepatocytes by activation of glycolysis downstream of glucose phosphorylation

The chronic effects of metformin on liver gluconeogenesis involve repression of the G6pc gene, which is regulated by the carbohydrate-response element-binding protein through raised cellular intermediates of glucose metabolism. In this study we determined the candidate mechanisms by which metformin lowers glucose 6-phosphate (G6P) in mouse and rat hepatocytes challenged with high glucose or gluconeogenic precursors. Cell metformin loads in the therapeutic range lowered cell G6P but not ATP and decreased G6pc mRNA at high glucose. The G6P lowering by metformin was mimicked by a complex 1 inhibitor (rotenone) and an uncoupler (dinitrophenol) and by overexpression of mGPDH, which lowers glycerol 3-phosphate and G6P and also mimics the G6pc repression by metformin. In contrast, direct allosteric activators of AMPK (A-769662, 991, and C-13) had opposite effects from metformin on glycolysis, gluconeogenesis, and cell G6P. The G6P lowering by metformin, which also occurs in hepatocytes from AMPK knockout mice, is best explained by allosteric regulation of phosphofructokinase-1 and/or fructose bisphosphatase-1, as supported by increased metabolism of [3-³H]glucose relative to [2-³H]glucose; by an increase in the lactate m2/m1 isotopolog ratio from [1,2-¹³C₂]glucose; by lowering of glycerol 3-phosphate an allosteric inhibitor of phosphofructokinase-1; and by marked G6P elevation by selective inhibition of phosphofructokinase-1; but not by a more reduced cytoplasmic NADH/NAD redox state. We conclude that therapeutically relevant doses of metformin lower G6P in hepatocytes challenged with high glucose by stimulation of glycolysis by an AMP-activated protein kinase-independent mechanism through changes in allosteric effectors of phosphofructokinase-1 and fructose bisphosphatase-1, including AMP, P_i, and glycerol 3-phosphate.

The landscape of tiered regulation of breast cancer cell metabolism

Altered metabolism is a hallmark of cancer, but little is still known about its regulation. In this study, we measure transcriptomic, proteomic, phospho-proteomic and fluxomics data in a breast cancer cell-line (MCF7) across three different growth conditions. Integrating these multiomics data within a genome scale human metabolic model in combination with machine learning, we systematically chart the different layers of metabolic regulation in breast cancer cells, predicting which enzymes and pathways are regulated at which level. We distinguish between two types of reactions, directly and indirectly regulated. Directly-regulated reactions include those whose flux is regulated by transcriptomic alterations (~890) or via proteomic or phospho-proteomics alterations (~140) in the enzymes catalyzing them. We term the reactions that currently lack evidence for direct regulation as (putative) indirectly regulated (~930). Many metabolic pathways are predicted to be regulated at different levels, and those may change at different media conditions. Remarkably, we find that the flux of predicted indirectly regulated reactions is strongly coupled to the flux of the predicted directly regulated ones, uncovering a tiered hierarchical organization of breast cancer cell metabolism. Furthermore, the predicted indirectly regulated reactions are predominantly reversible. Taken together, this architecture may facilitate rapid and efficient metabolic reprogramming in response to the varying environmental conditions incurred by the tumor cells. The approach presented lays a conceptual and computational basis for mapping metabolic regulation in additional cancers.

Acute metabolic responses to high fructose corn syrup ingestion in adolescents with overweight/obesity and diabetes

Introduction:

Childhood obesity remains high in prevalence. Sugar-sweetened beverages containing high fructose corn syrup (HFCS) are a common source of excess calories among children and adolescents. Fructose metabolism differs from glucose metabolism, which may also differ from fructose + glucose metabolism in HFCS consumption. The purpose of this study was to determine the acute metabolic effects of HFCS ingestion after soft drink consumption in adolescents who are lean, have overweight/obesity, or have type 2 diabetes (T2DM).

Methods:

Adolescents age 13–19 years were recruited into three groups: lean controls (n = 10), overweight/ obese without diabetes (n = 10), or uncomplicated T2DM on metformin monotherapy (n = 5). After an overnight fast, subjects drank 12 ounces of soda containing HFCS. Blood samples were collected at time zero and every 15 min for 120 min to be analyzed for fructose, glucose, and insulin levels.

Results:

Glucose and fructose concentrations rose quickly in the first 15 min. Fructose, which was very low at baseline, rose to 100–200 μM and remained higher than fasting concentrations even at 120 min in all groups. Glucose increased after soft drink consumption, with the highest concentrations among subjects with T2DM, but returned to baseline fasting levels at 120 min. Insulin levels increased 15 min after soft drink consumption and were the highest in the obese group. Lactate rose non-significantly in all subjects, with no differences between groups.

Conclusion:

Among adolescents who are lean, overweight/obese, or have T2DM, drinking an HFCS-containing soft drink exposes the liver to fructose. Glucose excursions in T2DM may be impacted by exaggerated glucose cycling, or fructose metabolism to glucose. The context of fructose consumption with or without other carbohydrates is an important consideration in studies of fructose metabolism.

HepatoDyn: A Dynamic Model of Hepatocyte Metabolism That Integrates 13C Isotopomer Data

The liver performs many essential metabolic functions, which can be studied using computational models of hepatocytes. Here we present HepatoDyn, a highly detailed dynamic model of hepatocyte metabolism. HepatoDyn includes a large metabolic network, highly detailed kinetic laws, and is capable of dynamically simulating the redox and energy metabolism of hepatocytes. Furthermore, the model was coupled to the module for isotopic label propagation of the software package IsoDyn, allowing HepatoDyn to integrate data derived from 13C based experiments. As an example of dynamical simulations applied to hepatocytes, we studied the effects of high fructose concentrations on hepatocyte metabolism by integrating data from experiments in which rat hepatocytes were incubated with 20 mM glucose supplemented with either 3 mM or 20 mM fructose. These experiments showed that glycogen accumulation was significantly lower in hepatocytes incubated with medium supplemented with 20 mM fructose than in hepatocytes incubated with medium supplemented with 3 mM fructose. Through the integration of extracellular fluxes and 13C enrichment measurements, HepatoDyn predicted that this phenomenon can be attributed to a depletion of cytosolic ATP and phosphate induced by high fructose concentrations in the medium.

The Warburg effect: a balance of flux analysis

Cancer metabolism is characterized by increased macromolecular syntheses through coordinated increases in energy and substrate metabolism. The observation that cancer cells produce lactate in an environment of oxygen sufficiency (aerobic glycolysis) is a central theme of cancer metabolism known as the Warburg effect. Aerobic glycolysis in cancer metabolism is accompanied by increased pentose cycle and anaplerotic activities producing energy and substrates for macromolecular synthesis. How these processes are coordinated is poorly understood. Recent advances have focused on molecular regulation of cancer metabolism by oncogenes and tumor suppressor genes which regulate numerous enzymatic steps of central glucose metabolism. In the past decade, new insights in cancer metabolism have emerged through the application of stable isotopes particularly from 13C carbon tracing. Such studies have provided new evidence for system-wide changes in cancer metabolism in response to chemotherapy. Interestingly, experiments using metabolic inhibitors on individual biochemical pathways all demonstrate similar system-wide effects on cancer metabolism as in targeted therapies. Since biochemical reactions in the Warburg effect place competing demands on available precursors, high energy phosphates and reducing equivalents, the cancer metabolic system must fulfill the condition of balance of flux (homeostasis). In this review, the functions of the pentose cycle and of the tricarboxylic acid (TCA) cycle in cancer metabolism are analyzed from the balance of flux point of view. Anticancer treatments that target molecular signaling pathways or inhibit metabolism alter the invasive or proliferative behavior of the cancer cells by their effects on the balance of flux (homeostasis) of the cancer metabolic phenotype.

Fructose Alters Intermediary Metabolism of Glucose in Human Adipocytes and Diverts Glucose to Serine Oxidation in the One-Carbon Cycle Energy Producing Pathway

Increased consumption of sugar and fructose as sweeteners has resulted in the utilization of fructose as an alternative metabolic fuel that may compete with glucose and alter its metabolism. To explore this, human Simpson-Golabi-Behmel Syndrome (SGBS) preadipocytes were differentiated to adipocytes in the presence of 0, 1, 2.5, 5 or 10 mM of fructose added to a medium containing 5 mM of glucose representing the normal blood glucose concentration. Targeted tracer [1,2-¹³C₂]-d-glucose fate association approach was employed to examine the influence of fructose on the intermediary metabolism of glucose. Increasing concentrations of fructose robustly increased the oxidation of [1,2-¹³C₂]-d-glucose to ¹³CO₂ (p < 0.000001). However, glucose-derived ¹³CO₂ negatively correlated with ¹³C labeled glutamate, ¹³C palmitate, and M₊₁ labeled lactate. These are strong markers of limited tricarboxylic acid (TCA) cycle, fatty acid synthesis, pentose cycle fluxes, substrate turnover and NAD⁺/NADP⁺ or ATP production from glucose via complete oxidation, indicating diminished mitochondrial energy metabolism. Contrarily, a positive correlation was observed between glucose-derived ¹³CO₂ formed and ¹³C oleate and doses of fructose which indicate the elongation and desaturation of palmitate to oleate for storage. Collectively, these results suggest that fructose preferentially drives glucose through serine oxidation glycine cleavage (SOGC pathway) one-carbon cycle for NAD⁺/NADP⁺ production that is utilized in fructose-induced lipogenesis and storage in adipocytes.

Regulation of mammalian nucleotide metabolism and biosynthesis

Nucleotides are required for a wide variety of biological processes and are constantly synthesized de novo in all cells. When cells proliferate, increased nucleotide synthesis is necessary for DNA replication and for RNA production to support protein synthesis at different stages of the cell cycle, during which these events are regulated at multiple levels. Therefore the synthesis of the precursor nucleotides is also strongly regulated at multiple levels. Nucleotide synthesis is an energy intensive process that uses multiple metabolic pathways across different cell compartments and several sources of carbon and nitrogen. The processes are regulated at the transcription level by a set of master transcription factors but also at the enzyme level by allosteric regulation and feedback inhibition. Here we review the cellular demands of nucleotide biosynthesis, their metabolic pathways and mechanisms of regulation during the cell cycle. The use of stable isotope tracers for delineating the biosynthetic routes of the multiple intersecting pathways and how these are quantitatively controlled under different conditions is also highlighted. Moreover, the importance of nucleotide synthesis for cell viability is discussed and how this may lead to potential new approaches to drug development in diseases such as cancer.

Metabolic fate of fructose in human adipocytes: a targeted 13C tracer fate association study

The development of obesity is becoming an international problem and the role of fructose is unclear. Studies using liver tissue and hepatocytes have contributed to the understanding of fructose metabolism. Excess fructose consumption also affects extra hepatic tissues including adipose tissue. The effects of fructose on human adipocytes are not yet fully characterized, although in vivo studies have noted increased adiposity and weight gain in response to fructose sweetened-beverages. In order to understand and predict the metabolic responses of adipocytes to fructose, this study examined differentiating and differentiated human adipocytes in culture, exposed to a range of fructose concentrations equivalent to that reported in blood after consuming fructose. A stable isotope based dynamic profiling method using [U-¹³C₆]-d-fructose tracer was used to examine the metabolism and fate of fructose. A targeted stable isotope tracer fate association method was used to analyze metabolic fluxes and flux surrogates with exposure to escalating fructose concentration. This study demonstrated that fructose stimulates anabolic processes in adipocytes robustly, including glutamate and de novo fatty acid synthesis. Furthermore, fructose also augments the release of free palmitate from fully differentiated adipocytes. These results imply that in the presence of fructose, the metabolic response of adipocytes in culture is altered in a dose dependent manner, particularly favoring increased glutamate and fatty acid synthesis and release, warranting further in vivo studies.

(13)C metabolic flux analysis shows that resistin impairs the metabolic response to insulin in L6E9 myotubes

Background

It has been suggested that the adipokine resistin links obesity and insulin resistance, although how resistin acts on muscle metabolism is controversial. We aimed to quantitatively analyse the effects of resistin on the glucose metabolic flux profile and on insulin response in L6E9 myotubes at the metabolic level using a tracer-based metabolomic approach and our in-house developed software, Isodyn.

Results

Resistin significantly increased glucose uptake and glycolysis, altering pyruvate utilisation by the cell. In the presence of resistin, insulin only slightly increased glucose uptake and glycolysis, and did not alter the flux profile around pyruvate induced by resistin. Resistin prevented the increase in gene expression in pyruvate dehydrogenase-E1 and the sharp decrease in gene expression in cytosolic phosphoenolpyruvate carboxykinase-1 induced by insulin.

Conclusions

These data suggest that resistin impairs the metabolic activation of insulin. This impairment cannot be explained by the activity of a single enzyme, but instead due to reorganisation of the whole metabolic flux distribution.

Modeling the optimal central carbon metabolic pathways under feedback inhibition using flux balance analysis

Metabolism is a complex process for energy production for cellular activity. It consists of a cascade of reactions that form a highly branched network in which the product of one reaction is the reactant of the next reaction. Metabolic pathways efficiently produce maximal amount of biomass while maintaining a steady-state behavior. The steady-state activity of such biochemical pathways necessarily incorporates feedback inhibition of the enzymes. This observation motivates us to incorporate feedback inhibition for modeling the optimal activity of metabolic pathways using flux balance analysis (FBA). We demonstrate the effectiveness of the methodology on a synthetic pathway with and without feedback inhibition. Similarly, for the first time, the Central Carbon Metabolic (CCM) pathways of Saccharomyces cerevisiae and Homo sapiens have been modeled and compared based on the above understanding. The optimal pathway, which maximizes the amount of the target product(s), is selected from all those obtained by the proposed method. For this, we have observed the concentration of the product inhibited enzymes of CCM pathway and its influence on its corresponding metabolite/substrate. We have also studied the concentration of the enzymes which are responsible for the synthesis of target products. We further hypothesize that an optimal pathway would opt for higher flux rate reactions. In light of these observations, we can say that an optimal pathway should have lower enzyme concentration and higher flux rates. Finally, we demonstrate the superiority of the proposed method by comparing it with the extreme pathway analysis.

Relevance of the MEK/ERK signaling pathway in the metabolism of activated macrophages: a metabolomic approach

The activation of immune cells in response to a pathogen involves a succession of signaling events leading to gene and protein expression, which requires metabolic changes to match the energy demands. The metabolic profile associated with the MAPK cascade (ERK1/2, p38, and JNK) in macrophages was studied, and the effect of its inhibition on the specific metabolic pattern of LPS stimulation was characterized. A [1,2-[(13)C](2)]glucose tracer-based metabolomic approach was used to examine the metabolic flux distribution in these cells after MEK/ERK inhibition. Bioinformatic tools were used to analyze changes in mass isotopomer distribution and changes in glucose and glutamine consumption and lactate production in basal and LPS-stimulated conditions in the presence and absence of the selective inhibitor of the MEK/ERK cascade, PD325901. Results showed that PD325901-mediated ERK1/2 inhibition significantly decreased glucose consumption and lactate production but did not affect glutamine consumption. These changes were accompanied by a decrease in the glycolytic flux, consistent with the observed decrease in fructose-2,6-bisphosphate concentration. The oxidative and nonoxidative pentose phosphate pathways and the ratio between them also decreased. However, tricarboxylic acid cycle flux did not change significantly. LPS activation led to the opposite responses, although all of these were suppressed by PD325901. However, LPS also induced a small decrease in pentose phosphate pathway fluxes and an increase in glutamine consumption that were not affected by PD325901. We concluded that inhibition of the MEK/ERK cascade interferes with central metabolism, and this cross-talk between signal transduction and metabolism also occurs in the presence of LPS.

Compartmentation of glycogen metabolism revealed from 13C isotopologue distributions

Background

Stable isotope tracers are used to assess metabolic flux profiles in living cells. The existing methods of measurement average out the isotopic isomer distribution in metabolites throughout the cell, whereas the knowledge of compartmental organization of analyzed pathways is crucial for the evaluation of true fluxes. That is why we accepted a challenge to create a software tool that allows deciphering the compartmentation of metabolites based on the analysis of average isotopic isomer distribution.

Results

The software Isodyn, which simulates the dynamics of isotopic isomer distribution in central metabolic pathways, was supplemented by algorithms facilitating the transition between various analyzed metabolic schemes, and by the tools for model discrimination. It simulated ¹³C isotope distributions in glucose, lactate, glutamate and glycogen, measured by mass spectrometry after incubation of hepatocytes in the presence of only labeled glucose or glucose and lactate together (with label either in glucose or lactate). The simulations assumed either a single intracellular hexose phosphate pool, or also channeling of hexose phosphates resulting in a different isotopic composition of glycogen. Model discrimination test was applied to check the consistency of both models with experimental data. Metabolic flux profiles, evaluated with the accepted model that assumes channeling, revealed the range of changes in metabolic fluxes in liver cells.

Conclusions

The analysis of compartmentation of metabolic networks based on the measured ¹³C distribution was included in Isodyn as a routine procedure. The advantage of this implementation is that, being a part of evaluation of metabolic fluxes, it does not require additional experiments to study metabolic compartmentation. The analysis of experimental data revealed that the distribution of measured ¹³C-labeled glucose metabolites is inconsistent with the idea of perfect mixing of hexose phosphates in cytosol. In contrast, the observed distribution indicates the presence of a separate pool of hexose phosphates that is channeled towards glycogen synthesis.

Metabolic response of perfused livers to various oxygenation conditions

Isolated liver perfusion systems have been used to characterize intrinsic metabolic changes in liver as a result of various perturbations, including systemic injury, hepatotoxin exposure, and warm ischemia. Most of these studies were done using hyperoxic conditions (95% O(2)) but without the use of oxygen carriers in the perfusate. Prior literature data do not clearly establish the impact of oxygenation, and in particular that of adding oxygen carriers to the perfusate, on the metabolic functions of the liver. Therefore, herein the effects of oxygen delivery in the perfusion system on liver metabolism were investigated by comparing three modes of oxygenation. Rat livers were perfused via the portal and hepatic veins at a constant flow rate of 3 mL/min/g liver in a recirculating perfusion system. In the first group, the perfusate was equilibrated in a membrane oxygenator with room air (21% O(2)) before entering the liver. In the second group, the perfusate was equilibrated with a 95% O(2)/5% CO(2) gas mixture. In the third group, the perfusate was supplemented with washed bovine red blood cells (RBCs) at 10% hematocrit and also equilibrated with the 95% O(2)/5% CO(2) gas mixture. Oxygen and CO(2) gradients across the liver were measured periodically with a blood gas analyzer. The rate of change in the concentration of major metabolites in the perfusate was measured over time. Net extracellular fluxes were calculated from these measurements and applied to a stoichiometric-based optimization problem to determine the intracellular fluxes and active pathways in the perfused livers. Livers perfused with RBCs consumed oxygen at twice the rate observed using hyperoxic (95% O(2)) perfusate without RBCs, and also produced more urea and ketone bodies. At the flow rate used, the oxygen supply in perfusate without RBCs was just sufficient to meet the average oxygen demand of the liver but would be insufficient if it increased above baseline, as is often the case in response to environmental perturbations. Metabolic pathway analysis suggests that significant anaerobic glycolysis occurred in the absence of RBCs even using hyperoxic perfusate. Conversely, when RBCs were used, glucose production from lactate and glutamate, as well as pathways related to energy metabolism were upregulated. RBCs also reversed an increase in PPP fluxes induced by the use of hyperoxic perfusate alone. In conclusion, the use of oxygen carriers is required to investigate the effect of various perturbations on liver metabolism.

Assessment of usnic acid toxicity in rat primary hepatocytes using ¹³C isotopomer distribution analysis of lactate, glutamate and glucose

The lichen metabolite usnic acid (UA) has been promoted as a dietary supplement for weight loss, although cases of hepatotoxicity have been reported. Here we evaluated UA-associated hepatotoxicity in vitro using isolated rat hepatocytes. We measured cell viability and ATP content to evaluate UA induced cytotoxicity and applied (13)C isotopomer distribution measuring techniques to gain a better understanding of glucose metabolism during cytotoxicity. The cells were exposed to 0, 1, 5 or 10 μM UA concentrations for 2, 6 or 24h. Aliquots of media were collected at the end of these time periods and the (13)C mass isotopomer distribution determined for CO(2), lactate, glucose and glutamate. The 1 μM UA exposure did not appear to cause significant change in cell viability compared to controls. However, the 5 and 10 μM UA concentrations significantly reduced cell viability as exposure time increased. Similar results were obtained for ATP depletion experiments. The 1 and 5 μM UA doses suggest increased oxidative phosphorylation. Conversely, oxidative phosphorylation and gluconeogenesis were dramatically inhibited by 10 μM UA. Augmented oxidative phosphorylation at the lower UA concentrations may be an adaptive response by the cells to compensate for diminished mitochondrial function.

A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions

Background

Stable isotope tracing is a powerful technique for following the fate of individual atoms through metabolic pathways. Measuring isotopic enrichment in metabolites provides quantitative insights into the biosynthetic network and enables flux analysis as a function of external perturbations. NMR and mass spectrometry are the techniques of choice for global profiling of stable isotope labeling patterns in cellular metabolites. However, meaningful biochemical interpretation of the labeling data requires both quantitative analysis and complex modeling. Here, we demonstrate a novel approach that involved acquiring and modeling the timecourses of ¹³C isotopologue data for UDP-N-acetyl-D-glucosamine (UDP-GlcNAc) synthesized from [U-¹³C]-glucose in human prostate cancer LnCaP-LN3 cells. UDP-GlcNAc is an activated building block for protein glycosylation, which is an important regulatory mechanism in the development of many prominent human diseases including cancer and diabetes.

Results

We utilized a stable isotope resolved metabolomics (SIRM) approach to determine the timecourse of ¹³C incorporation from [U-¹³C]-glucose into UDP-GlcNAc in LnCaP-LN3 cells. ¹³C Positional isotopomers and isotopologues of UDP-GlcNAc were determined by high resolution NMR and Fourier transform-ion cyclotron resonance-mass spectrometry. A novel simulated annealing/genetic algorithm, called 'Genetic Algorithm for Isotopologues in Metabolic Systems' (GAIMS) was developed to find the optimal solutions to a set of simultaneous equations that represent the isotopologue compositions, which is a mixture of isotopomer species. The best model was selected based on information theory. The output comprises the timecourse of the individual labeled species, which was deconvoluted into labeled metabolic units, namely glucose, ribose, acetyl and uracil. The performance of the algorithm was demonstrated by validating the computed fractional ¹³C enrichment in these subunits against experimental data. The reproducibility and robustness of the deconvolution were verified by replicate experiments, extensive statistical analyses, and cross-validation against NMR data.

Conclusions

This computational approach revealed the relative fluxes through the different biosynthetic pathways of UDP-GlcNAc, which comprises simultaneous sequential and parallel reactions, providing new insight into the regulation of UDP-GlcNAc levels and O-linked protein glycosylation. This is the first such analysis of UDP-GlcNAc dynamics, and the approach is generally applicable to other complex metabolites comprising distinct metabolic subunits, where sufficient numbers of isotopologues can be unambiguously resolved and accurately measured.

Synergistic activity of histone deacetylase and proteasome inhibition against pancreatic and hepatocellular cancer cell lines

AIM

To determine the phenotypic effects of belinostat (bel) and bortezomib (bor) against pancreatic cancer (PC) and hepatocellular cancer (HCC) cell lines.

MATERIALS AND METHODS

Antiproliferative effects were assessed using a sulforhodamine B assay. Synergy was evaluated using the Chou and Talalay method. Apoptosis was measured by caspase-3/-7 activity and PARP cleavage. Downstream effector proteins were detected via immunoblotting. Quantitative nuclear magnetic resonance (NMR)-based metabolomics analysis was performed.

RESULTS

There were single-agent antiproliferative effects against PC and HCC cell lines; the combination of bel and bor (bel+bor) had a synergistic effect. There was up to a 45-fold induction of apoptosis over the control. Post-treatment cell death was associated with p21 up-regulation, more pronounced with treatment with bel+bor. Treatment with bel+bor enhanced hyperacetylation of histone H3 over single-agent bel. A metabolic signature was established for treatments with bor and bel+bor.

CONCLUSION

The combination of bel+bor displayed significant antiproliferative activity against PC and HCC cell lines, with exhibiting synergistic antiproliferative and proapoptotic patterns even at suboptimal single-agent doses.

Bioactive food components and cancer-specific metabonomic profiles

Cancer cells possess unique metabolic signatures compared to normal cells, including shifts in aerobic glycolysis, glutaminolysis, and de novo biosynthesis of macromolecules. Targeting these changes with agents (drugs and dietary components) has been employed as strategies to reduce the complications associated with tumorigenesis. This paper highlights the ability of several food components to suppress tumor-specific metabolic pathways, including increased expression of glucose transporters, oncogenic tyrosine kinase, tumor-specific M2-type pyruvate kinase, and fatty acid synthase, and the detection of such effects using various metabonomic technologies, including liquid chromatography/mass spectrometry (LC/MS) and stable isotope-labeled MS. Stable isotope-mediated tracing technologies offer exciting opportunities for defining specific target(s) for food components. Exposures, especially during the early transition phase from normal to cancer, are critical for the translation of knowledge about food components into effective prevention strategies. Although appropriate dietary exposures needed to alter cellular metabolism remain inconsistent and/or ill-defined, validated metabonomic biomarkers for dietary components hold promise for establishing effective strategies for cancer prevention.

Tracer-based metabolomics: concepts and practices

Tracer-based metabolomics is a systems biology tool that combines advances in tracer methodology for physiological studies, high throughput "-omics" technologies and constraint based modeling of metabolic networks. It is different from the commonly known metabolomics or metabonomics in that it is a targeted approach based on a metabolic network model in cells. Because of its complexity, it is the least understood among the various "-omics." In this review, the development of concepts and practices of tracer-based metabolomics is traced from the early application of radioactive isotopes in metabolic studies to the recent application of stable isotopes and isotopomer analysis using mass spectrometry; and from the modeling of biochemical reactions using flux analysis to the recent theoretical formulation of the constraint based modeling. How these newer experimental methods and concepts of constraint-based modeling approaches can be applied to metabolic studies is illustrated by examples of studies in determining metabolic responses of cells to pharmacological agents and nutrient environment changes.

Edelfosine-induced metabolic changes in cancer cells that precede the overproduction of reactive oxygen species and apoptosis

Background

Metabolic flux profiling based on the analysis of distribution of stable isotope tracer in metabolites is an important method widely used in cancer research to understand the regulation of cell metabolism and elaborate new therapeutic strategies. Recently, we developed software Isodyn, which extends the methodology of kinetic modeling to the analysis of isotopic isomer distribution for the evaluation of cellular metabolic flux profile under relevant conditions. This tool can be applied to reveal the metabolic effect of proapoptotic drug edelfosine in leukemia Jurkat cell line, uncovering the mechanisms of induction of apoptosis in cancer cells.

Results

The study of ¹³C distribution of Jukat cells exposed to low edelfosine concentration, which induces apoptosis in ≤5% of cells, revealed metabolic changes previous to the development of apoptotic program. Specifically, it was found that low dose of edelfosine stimulates the TCA cycle. These metabolic perturbations were coupled with an increase of nucleic acid synthesis de novo, which indicates acceleration of biosynthetic and reparative processes. The further increase of the TCA cycle fluxes, when higher doses of drug applied, eventually enhance reactive oxygen species (ROS) production and trigger apoptotic program.

Conclusion

The application of Isodyn to the analysis of mechanism of edelfosine-induced apoptosis revealed primary drug-induced metabolic changes, which are important for the subsequent initiation of apoptotic program. Initiation of such metabolic changes could be exploited in anticancer therapy.

A rational design approach for amino acid supplementation in hepatocyte culture

Improvement of culture media for mammalian cells is conducted via empirical adjustments, sometimes aided by statistical design methodologies. Here, we demonstrate a proof of principle for the use of constraints-based modeling to achieve enhanced performance of liver-specific functions of cultured hepatocytes during plasma exposure by adjusting amino acid supplementation and hormone levels in the medium. Flux balance analysis (FBA) is used to determine an amino acid flux profile consistent with a desired output; this is used to design an amino acid supplementation. Under conditions of no supplementation, empirical supplementation, and designed supplementation, hepatocytes were exposed to plasma and their morphology, specific cell functions (urea, albumin production) and lipid metabolism were measured. Urea production under the designed amino acid supplementation was found to be increased compared with previously reported (empirical) amino acid supplementation. Not surprisingly, the urea production attained was less than the theoretical value, indicating the existence of pathways or constraints not present in the current model. Although not an explicit design objective, albumin production was also increased by designed amino acid supplementation, suggesting a functional linkage between these outputs. In conjunction with traditional approaches to improving culture conditions, the rational design approach described herein provides a novel means to tune the metabolic outputs of cultured hepatocytes.

Metabolomics and fluxomics approaches

Systems biology is based on the understanding that the behaviour of the whole is greater than would be expected from the sum of its parts. Thus the ultimate goal of systems biology is to predict the behaviour of the whole system on the basis of the list of components involved. Recent advances in ‘-omics’ technologies and the development of new computational techniques and algorithms have greatly contributed to progress in this field of biology. Among the main ‘-omics’ technologies, metabolomics is expected to play a significant role in bridging the phenotype–genotype gap, since it amplifies changes in the proteome and provides a better representation of the phenotype of an organism than other methods. However, knowledge of the complete set of metabolites is not enough to predict the phenotype, especially for higher cells in which the distinct metabolic processes involved in their production and degradation are finely regulated and interconnected. In these cases, quantitative knowledge of intracellular fluxes is required for a comprehensive characterization of metabolic networks and their functional operation. These intracellular fluxes cannot be detected directly, but can be estimated through interpretation of stable isotope patterns in metabolites. Moreover, analysis of these fluxes by means of metabolic control theories offers a potentially unifying, holistic paradigm to explain the regulation of cell metabolism. In this chapter, we provide an overview of metabolomics and fluxomics, highlighting stable isotope strategies for fluxome characterization. We also discuss some of the tools used to quantitatively analyse the control exerted by components of the network over both the metabolome and the fluxome. Finally, we outline the role and future of metabolomics and fluxomics in drug discovery.

Extending the breadth of metabolite profiling by gas chromatography coupled to mass spectrometry

Gas chromatography coupled to mass spectrometry (GC-MS) is one of the most frequently used tools for profiling primary metabolites. Instruments are mature enough to run large sequences of samples; novel advancements increase the breadth of compounds that can be analyzed, and improved algorithms and databases are employed to capture and utilize biologically relevant information. Around half the published reports on metabolite profiling by GC-MS focus on biological problems rather than on methodological advances. Applications span from comprehensive analysis of volatiles to assessment of metabolic fluxes for bioengineering. Method improvements emphasize extraction procedures, evaluations of quality control of GC-MS in comparison to other techniques and approaches to data processing. Two major challenges remain: rapid annotation of unknown peaks; and, integration of biological background knowledge aiding data interpretation.

Global metabolic effects of glycerol kinase overexpression in rat hepatoma cells

Glycerol kinase has several diverse activities in mammalian cells. Glycerol kinase deficiency is a complex, single-gene, inborn error of metabolism wherein no genotype-phenotype correlation has been established. Since glycerol kinase has been suggested to exhibit additional activities than glycerol phosphorylation, expression level perturbation in this enzyme may affect cellular physiology globally. To investigate this possibility, we conducted metabolic investigations of wild-type and two glycerol kinase-overexpressing H4IIE rat hepatoma cell lines constructed in this study. The glycerol kinase-overexpressing cell lines exhibited a significantly higher consumption of carbon sources per cell, suggesting excess carbon expenditure. Furthermore, we quantified intracellular metabolic fluxes by employing stable isotope 13C labeling with a mathematically designed substrate mixture, gas chromatography-mass spectrometry, and comprehensive isotopomer balancing. This flux analysis revealed that the pentose phosphate pathway flux in the glycerol kinase-overexpressing cell lines was 2-fold higher than that in the wild-type, in addition to subtler flux changes in other pathways of carbohydrate metabolism. Furthermore, the activity and transcript level of the lipogenic enzyme glucose-6-phosphate dehydrogenase, the rate-limiting enzyme of the pentose phosphate pathway, were also about 2-fold higher than that of the wild-type; these data corroborate the flux analysis results. This study shows that glycerol kinase affects carbon metabolism globally, possibly through its additional functions, and highlights glycerol kinase's multifaceted role in cellular physiology.

Isotopomer-based metabolomic analysis by NMR and mass spectrometry

Nuclear magnetic resonance (NMR) and mass spectrometry (MS) together are synergistic in their ability to profile comprehensively the metabolome of cells and tissues. In addition to identification and quantification of metabolites, changes in metabolic pathways and fluxes in response to external perturbations can be reliably determined by using stable isotope tracer methodologies. NMR and MS together are able to define both positional isotopomer distribution in product metabolites that derive from a given stable isotope-labeled precursor molecule and the degree of enrichment at each site with good precision. Together with modeling tools, this information provides a rich functional biochemical readout of cellular activity and how it responds to external influences. In this chapter, we describe NMR- and MS-based methodologies for isotopomer analysis in metabolomics and its applications for different biological systems.

Contribution of gene expression to metabolic fluxes in hypermetabolic livers induced through burn injury and cecal ligation and puncture in rats

Severe injury activates many stress-related and inflammatory pathways that can lead to a systemic hypermetabolic state. Prior studies using perfused hypermetabolic rat livers have identified intrinsic metabolic flux changes that were not dependent upon the continual presence of elevated stress hormones and substrate loads. We investigated the hypothesis that such changes may be due to persistent alterations in gene expression. A systemic hypermetabolic response was induced in rats by applying a moderate burn injury followed 2 days later by cecum ligation and puncture (CLP) to produce sepsis. Control animals received a sham-burn followed by CLP, or a sham-burn followed by sham-CLP. Two days after CLP, livers were analyzed for gene expression changes using DNA microarrays and for metabolism alterations by ex vivo perfusion coupled with Metabolic Flux Analysis. Burn injury prior to CLP increased fluxes while decreases in gene expression levels were observed. Conversely, CLP alone significantly increased metabolic gene expression, but decreased many of the corresponding metabolic fluxes. Burn injury combined with CLP led to the most dramatic changes, where concurrent changes in fluxes and gene expression levels occurred in about 1/3 of the reactions. The data are consistent with the notion that in this model, burn injury prior to CLP increased fluxes through post-translational mechanisms with little contribution of gene expression, while CLP treatment up-regulated the metabolic machinery by transcriptional mechanisms. Overall, these data show that mRNA changes measured at a single time point by DNA microarray analysis do not reliably predict metabolic flux changes in perfused livers.

Quantification of intracellular phosphorylated carbohydrates in HT29 human colon adenocarcinoma cell line using liquid chromatography-electrospray ionization tandem mass spectrometry

The quantitative understanding of the role of sugar phosphates in regulating tumor energetic metabolism at the proteomic and genomic level is a prerequisite for an efficient rational design in combined drug chemotherapy. Therefore, it is necessary to determine accurately the concentration of the main sugar phosphate pools at the lower concentrations present in the often-limited volume of tumor cell samples. Taking as an example the human adenocarcinoma cell line HT29, we here report a fast and reliable quantitative method based on the use of liquid nitrogen, a weak acid extraction, and liquid chromatography-electrospray ionization tandem mass spectrometry to quantify simultaneously the intracellular concentration of sugar phosphate pools. The method was set up using standard addition curves. Thus, it is possible to identify and quantify hexose phosphate, pentose phosphate, and triose phosphate pools up to 0.02-0.10 ng x microL(-1), depending on the analyte. The method developed was here used for the quantitative study of changes in phosphorylated carbohydrates of central carbon metabolism when high or low glucose concentration conditions are induced in vitro in the HT29 human colon adenocarcinoma cell line.

Systems analysis of energy metabolism elucidates the affected respiratory chain complex in Leigh's syndrome

Leigh's syndrome is a complex neurological disease with little known correlation between causes and symptoms. Mutations in pyruvate dehydrogenase and electron transport chain complexes have been associated with this syndrome, although the identification of affected enzymes is difficult, if not impossible, with non-invasive clinical tests. In this study, isotopomer analysis is used to characterize the metabolic phenotype of normal and Leigh's syndrome fibroblasts (GM01503), thereby identifying affected enzymes in the diseased cells. Fibroblasts are grown with DMEM media enriched with (13)C labeled glucose. Amino acids from media and proteins as well as lactate are analyzed with GC-MS to identify their label distributions. A computational model accounting for all major pathways in fibroblast metabolism (including 430 metabolites and 508 reactions) is built to determine the metabolic steady states of the normal and Leigh's cell lines based on measured substrate uptake and secretion rates and isotopomer data. Results show that (i) Leigh's syndrome affected cells have slower metabolism than control fibroblasts as evidenced by their overall slower substrate utilization and lower secretion of end products; (ii) intracellular fluxes predicted by the models, some of which are validated by biochemical studies published in the literature, show that the respiratory chain in Leigh's affected cells can produce ATP at a similar rate as the controls, but with a more restricted flux range; and (iii) mutations causing the defects observed in the Leigh's cells are likely to be in succinate cytochrome c reductase.

Fluxome analysis using GC-MS

Fluxome analysis aims at the quantitative analysis of in vivo carbon fluxes in metabolic networks, i. e. intracellular activities of enzymes and pathways. It allows investigating the effects of genetic or environmental modifications and thus precisely provides a global perspective on the integrated genetic and metabolic regulation within the intact metabolic network. The experimental and computational approaches developed in this area have revealed fascinating insights into metabolic properties of various biological systems. Most of the comprehensive approaches for metabolic flux studies today involve isotopic tracer studies and GC-MS for measurement of the labeling pattern of metabolites. Initially developed and applied mainly in the field of biomedicine these GC-MS based metabolic flux approaches have been substantially extended and optimized during recent years and today display a key technology in metabolic physiology and biotechnology.

Integration of enzyme kinetic models and isotopomer distribution analysis for studies of in situ cell operation

A current trend in neuroscience research is the use of stable isotope tracers in order to address metabolic processes in vivo. The tracers produce a huge number of metabolite forms that differ according to the number and position of labeled isotopes in the carbon skeleton (isotopomers) and such a large variety makes the analysis of isotopomer data highly complex. On the other hand, this multiplicity of forms does provide sufficient information to address cell operation in vivo. By the end of last millennium, a number of tools have been developed for estimation of metabolic flux profile from any possible isotopomer distribution data. However, although well elaborated, these tools were limited to steady state analysis, and the obtained set of fluxes remained disconnected from their biochemical context. In this review we focus on a new numerical analytical approach that integrates kinetic and metabolic flux analysis. The related computational algorithm estimates the dynamic flux based on the time-dependent distribution of all possible isotopomers of metabolic pathway intermediates that are generated from a labeled substrate. The new algorithm connects specific tracer data with enzyme kinetic characteristics, thereby extending the amount of data available for analysis: it uses enzyme kinetic data to estimate the flux profile, and vice versa, for the kinetic analysis it uses in vivo tracer data to reveal the biochemical basis of the estimated metabolic fluxes.

Software for dynamic analysis of tracer-based metabolomic data: estimation of metabolic fluxes and their statistical analysis

MOTIVATION

Metabolic flux analysis of biochemical reaction networks using isotope tracers requires software tools that can analyze the dynamics of isotopic isomer (isotopomer) accumulation in metabolites and reveal the underlying kinetic mechanisms of metabolism regulation. Since existing tools are restricted by the isotopic steady state and remain disconnected from the underlying kinetic mechanisms, we have recently developed a novel approach for the analysis of tracer-based metabolomic data that meets these requirements. The present contribution describes the last step of this development: implementation of (i) the algorithms for the determination of the kinetic parameters and respective metabolic fluxes consistent with the experimental data and (ii) statistical analysis of both fluxes and parameters, thereby lending it a practical application.

RESULTS

The C++ applications package for dynamic isotopomer distribution data analysis was supplemented by (i) five distinct methods for resolving a large system of differential equations; (ii) the 'simulated annealing' algorithm adopted to estimate the set of parameters and metabolic fluxes, which corresponds to the global minimum of the difference between the computed and measured isotopomer distributions; and (iii) the algorithms for statistical analysis of the estimated parameters and fluxes, which use the covariance matrix evaluation, as well as Monte Carlo simulations. An example of using this tool for the analysis of (13)C distribution in the metabolites of glucose degradation pathways has demonstrated the evaluation of optimal set of parameters and fluxes consistent with the experimental pattern, their range and statistical significance, and also the advantages of using dynamic rather than the usual steady-state method of analysis.

AVAILABILITY

Software is available free from http://www.bq.ub.es/bioqint/selivanov.htm

Measuring multiple fluxes through plant metabolic networks

Fluxes through metabolic networks are crucial for cell function, and a knowledge of these fluxes is essential for understanding and manipulating metabolic phenotypes. Labeling provides the key to flux measurement, and in network flux analysis the measurement of multiple fluxes allows a flux map to be superimposed on the metabolic network. The principles and practice of two complementary methods, dynamic and steady-state labeling, are described, emphasizing best practice and illustrating their contribution to network flux analysis with examples taken from the plant and microbial literature. The principal analytical methods for the detection of stable isotopes are also described, as well as the procedures for obtaining flux maps from labeling data. A series of boxes summarizing the key concepts of network flux analysis is provided for convenience.

Characterizing phenotype with tracer based metabolomics

In the post-genomic era, a pressing challenge to biological scientists is to understand the organization of gene functions, the interaction between gene and nutrient environment, and the genesis of phenotypes. Metabolomics, the quantitation of low molecular weight compounds, has been used to provide a phenotypic description of a cell or tissue by a set of metabolites. Gene function is hypothesized from its correlation with the corresponding set of macromolecules by transcriptomics or proteomics. Another approach to genotype-phenotype correlation is by the reconstruction of genome-scale metabolic maps. The utilization of specific pathways as predicted by reaction network analysis provides the phenotypic characterization of a cell, which can be plotted on a phenotypic phase plane. Tracer based metabolomics is the experimental approach to reaction network analysis using stable isotope tracers. The redistribution of the isotope tracer among metabolic intermediates is used to identify a finite number of pathways, the utilization of which is characteristic of the phenotypic behavior of cells. In this paper, we review tracer based metabolomic methods for the construction of phenotypic phase plane plots, and discuss the functional implications of phenotypic phase plane analysis. Examples of phenotypic changes in response to differentiation, inhibition of signaling pathways and perturbation in nutrient environment are provided.