Identification of metabolic fluxes in hepatic cells from transient 13C-labeling experiments: Part II. Flux estimation

Integrating a dynamic central metabolism model of cancer cells with a hybrid 3D multiscale model for vascular hepatocellular carcinoma growth

We develop here a novel modelling approach with the aim of closing the conceptual gap between tumour-level metabolic processes and the metabolic processes occurring in individual cancer cells. In particular, the metabolism in hepatocellular carcinoma derived cell lines (HEPG2 cells) has been well characterized but implementations of multiscale models integrating this known metabolism have not been previously reported. We therefore extend a previously published multiscale model of vascular tumour growth, and integrate it with an experimentally verified network of central metabolism in HEPG2 cells. This resultant combined model links spatially heterogeneous vascular tumour growth with known metabolic networks within tumour cells and accounts for blood flow, angiogenesis, vascular remodelling and nutrient/growth factor transport within a growing tumour, as well as the movement of, and interactions between normal and cancer cells. Model simulations report for the first time, predictions of spatially resolved time courses of core metabolites in HEPG2 cells. These simulations can be performed at a sufficient scale to incorporate clinically relevant features of different tumour systems using reasonable computational resources. Our results predict larger than expected temporal and spatial heterogeneity in the intracellular concentrations of glucose, oxygen, lactate pyruvate, f16bp and Acetyl-CoA. The integrated multiscale model developed here provides an ideal quantitative framework in which to study the relationship between dosage, timing, and scheduling of anti-neoplastic agents and the physiological effects of tumour metabolism at the cellular level. Such models, therefore, have the potential to inform treatment decisions when drug response is dependent on the metabolic state of individual cancer cells.

Compartment-specific 13C metabolic flux analysis reveals boosted NADPH availability coinciding with increased cell-specific productivity for IgG1 producing CHO cells after MTA treatment

Increasing cell-specific productivities (CSPs) for the production of heterologous proteins in Chinese hamster ovary (CHO) cells is an omnipresent need in the biopharmaceutical industry. The novel additive 5'-deoxy-5'-(methylthio)adenosine (MTA), a chemical degradation product of S-(5'-adenosyl)-ʟ-methionine (SAM) and intermediate of polyamine biosynthesis, boosts the CSP of IgG1-producing CHO cells by 50%. Compartment-specific 13C flux analysis revealed a fundamental reprogramming of the central metabolism after MTA addition accompanied by cell-cycle arrest and increased cell volumes. Carbon fluxes into the pentose-phosphate pathway increased 22 fold in MTA-treated cells compared to that in non-MTA-treated reference cells. Most likely, cytosolic ATP inhibition of phosphofructokinase mediated the carbon detour. Mitochondrial shuttle activity of the α-ketoglurarate/malate antiporter (OGC) reversed, reducing cytosolic malate transport. In summary, NADPH supply in MTA-treated cells improved three fold compared to that in non-MTA-treated cells, which can be regarded as a major factor for explaining the boosted CSPs.

Streamlining the Analysis of Dynamic 13C-Labeling Patterns for the Metabolic Engineering of Corynebacterium glutamicum as l-Histidine Production Host

Today’s possibilities of genome editing easily create plentitudes of strain mutants that need to be experimentally qualified for configuring the next steps of strain engineering. The application of design-build-test-learn cycles requires the identification of distinct metabolic engineering targets as design inputs for subsequent optimization rounds. Here, we present the pool influx kinetics (PIK) approach that identifies promising metabolic engineering targets by pairwise comparison of up- and downstream ¹³C labeling dynamics with respect to a metabolite of interest. Showcasing the complex l-histidine production with engineered Corynebacterium glutamicuml-histidine-on-glucose yields could be improved to 8.6 ± 0.1 mol% by PIK analysis, starting from a base strain. Amplification of purA, purB, purH, and formyl recycling was identified as key targets only analyzing the signal transduction kinetics mirrored in the PIK values.

HILIC-Enabled 13C Metabolomics Strategies: Comparing Quantitative Precision and Spectral Accuracy of QTOF High- and QQQ Low-Resolution Mass Spectrometry

Dynamic ¹³C-tracer-based flux analyses of in vivo reaction networks still require a continuous development of advanced quantification methods applying state-of-the-art mass spectrometry platforms. Utilizing alkaline HILIC chromatography, we adapt strategies for a systematic quantification study in non- and ¹³C-labeled multicomponent endogenous Corynebacterium glutamicum extracts by LC-QTOF high resolution (HRMS) and LC-QQQ tandem mass spectrometry (MS/MS). Without prior derivatization, a representative cross-section of 17 central carbon and anabolic key intermediates were analyzed with high selectivity and sensitivity under optimized ESI-MS settings. In column detection limits for the absolute quantification range were between 6.8-304.7 (QQQ) and 28.7-881.5 fmol (QTOF) with comparable linearities (3-5 orders of magnitude) and enhanced precision using QQQ-MRM detection. Tailor-made preparations of uniformly (U)¹³C-labeled cultivation extracts for isotope dilution mass spectrometry enabled the accurate quantification in complex sample matrices and extended linearities without effect on method parameters. Furthermore, evaluation of metabolite-specific m+1-to-m+0 ratios (ISR_1:0) in non-labeled extracts exhibited sufficient methodical spectral accuracies with mean deviations of 3.89 ± 3.54% (QTOF) and 4.01 ± 3.01% (QQQ). Based on the excellent HILIC performance, conformity analysis of time-resolved isotopic enrichments in ¹³C-tracer experiments revealed sufficient spectral accuracy for QQQ-SIM detection. However, only QTOF-HRMS ensures determination of the full isotopologue space in complex matrices without mass interferences.

From nutritional wealth to autophagy: In vivo metabolic dynamics in the cytosol, mitochondrion and shuttles of IgG producing CHO cells

To fulfil the optimization needs of current biopharmaceutical processes the knowledge how to improve cell specific productivities is of outmost importance. This requires a detailed understanding of cellular metabolism on a subcellular level inside compartments such as cytosol and mitochondrion. Using IgG1 producing Chinese hamster ovary (CHO) cells, a pioneering protocol for compartment-specific metabolome analysis was applied. Various production-like growth conditions ranging from ample glucose and amino acid supply via moderate to severe nitrogen limitation were investigated in batch cultures. The combined application of quantitative metabolite pool analysis, ¹³C tracer studies and non-stationary flux calculations revealed that Pyr/H⁺ symport (MPC1/2) bore the bulk of the mitochondrial transport under ample nutrient supply. Glutamine limitation induced the concerted adaptation of the bidirectional Mal/aKG (OGC) and the Mal/HPO₄^2- antiporter (DIC), even installing completely reversed shuttle fluxes. As a result, NADPH and ATP formation were adjusted to cellular needs unraveling the key role of cytosolic malic enzyme for NADPH production. Highest cell specific IgG1 productivities were closely correlated to a strong mitochondrial malate export according to the anabolic demands. The requirement to install proper NADPH supply for optimizing the production of monoclonal antibodies is clearly outlined. Interestingly, it was observed that mitochondrial citric acid cycle activity was always maintained enabling constant cytosolic adenylate energy charges at physiological levels, even under autophagy conditions.

Hyperpolarized δ-[1-13 C]gluconolactone as a probe of the pentose phosphate pathway

The pentose phosphate pathway (PPP) is thought to be upregulated in trauma (to produce excess NADPH) and in cancer (to provide ribose for nucleotide biosynthesis), but simple methods for detecting changes in flux through this pathway are not available. MRI of hyperpolarized ¹³ C-enriched metabolites offers considerable potential as a rapid, non-invasive tool for detecting changes in metabolic fluxes. In this study, hyperpolarized δ-[1-¹³ C]gluconolactone was used as a probe to detect flux through the oxidative portion of the pentose phosphate pathway (PPP_ox ) in isolated perfused mouse livers. The appearance of hyperpolarized (HP) H¹³ CO₃^- within seconds after exposure of livers to HP-δ-[1-¹³ C]gluconolactone demonstrates that this probe rapidly enters hepatocytes, becomes phosphorylated, and enters the PPP_ox pathway to produce HP-H¹³ CO₃^- after three enzyme catalyzed steps (6P-gluconolactonase, 6-phosphogluconate dehydrogenase, and carbonic anhydrase). Livers perfused with octanoate as their sole energy source show no change in production of H¹³ CO₃^- after exposure to low levels of H₂ O₂ , while livers perfused with glucose and insulin showed a twofold increase in H¹³ CO₃^- after exposure to peroxide. This indicates that flux through the PPP_ox is stimulated by H₂ O₂ in glucose perfused livers but not in livers perfused with octanoate alone. Subsequent perfusion of livers with non-polarized [1,2-¹³ C]glucose followed by ¹ H NMR analysis of lactate in the perfusate verified that flux through the PPP_ox is indeed low in healthy livers and modestly higher in peroxide damaged livers. We conclude that hyperpolarized δ-[1-¹³ C]gluconolactone has the potential to serve as a metabolic imaging probe of this important biological pathway.

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.

(13)C metabolic flux analysis in neurons utilizing a model that accounts for hexose phosphate recycling within the pentose phosphate pathway

Glycolysis, mitochondrial substrate oxidation, and the pentose phosphate pathway (PPP) are critical for neuronal bioenergetics and oxidation-reduction homeostasis, but quantitating their fluxes remains challenging, especially when processes such as hexose phosphate (i.e., glucose/fructose-6-phosphate) recycling in the PPP are considered. A hexose phosphate recycling model was developed which exploited the rates of glucose consumption, lactate production, and mitochondrial respiration to infer fluxes through the major glucose consuming pathways of adherent cerebellar granule neurons by replicating [(13)C]lactate labeling from metabolism of [1,2-(13)C2]glucose. Flux calculations were predicated on a steady-state system with reactions having known stoichiometries and carbon atom transitions. Non-oxidative PPP activity and consequent hexose phosphate recycling, as well as pyruvate production by cytoplasmic malic enzyme, were optimized by the model and found to account for 28 ± 2% and 7.7 ± 0.2% of hexose phosphate and pyruvate labeling, respectively. From the resulting fluxes, 52 ± 6% of glucose was metabolized by glycolysis, compared to 19 ± 2% by the combined oxidative/non-oxidative pentose cycle that allows for hexose phosphate recycling, and 29 ± 8% by the combined oxidative PPP/de novo nucleotide synthesis reactions. By extension, 62 ± 6% of glucose was converted to pyruvate, the metabolism of which resulted in 16 ± 1% of glucose oxidized by mitochondria and 46 ± 6% exported as lactate. The results indicate a surprisingly high proportion of glucose utilized by the pentose cycle and the reactions synthesizing nucleotides, and exported as lactate. While the in vitro conditions to which the neurons were exposed (high glucose, no lactate or other exogenous substrates) limit extrapolating these results to the in vivo state, the approach provides a means of assessing a number of metabolic fluxes within the context of hexose phosphate recycling in the PPP from a minimal set of measurements.

Compartment-specific metabolomics for CHO reveals that ATP pools in mitochondria are much lower than in cytosol

Mammalian cells show a compartmented metabolism. Getting access to subcellular metabolite pools is of high interest to understand the cells' metabolomic state. Therefore a protocol is developed and applied for monitoring compartment-specific metabolite and nucleotide pool sizes in Chinese hamster ovary (CHO) cells. The approach consists of a subtracting filtering method separating cytosolic components from physically intact mitochondrial compartments. The internal standards glucose-6-phosphate and cis-aconitate were chosen to quantify cytosolic secession and mitochondrial membrane integrity. Extracts of related fractions were studied by liquid chromatography-isotope dilution mass spectrometry for the absolute quantification of a subset of glycolytic and tricarboxylic acid cycle intermediates together with the adenylate nucleotides ATP, ADP and AMP. The application of the protocol revealed highly dynamic changes in the related pool sizes as a function of distinct cultivation periods of IgG1 producing CHO cells. Mitochondrial and cytosolic pool dynamics were in agreement with anticipated metabolite pools of independent studies. The analysis of adenosine phosphate levels unraveled significantly higher ATP levels in the cytosol leading to the hypothesis that mitochondria predominantly serve for fueling ATP into the cytosol where it is tightly controlled at physiological adenylate energy charges about 0.9.

Tracking the metabolic pulse of plant lipid production with isotopic labeling and flux analyses: Past, present and future

Metabolism is comprised of networks of chemical transformations, organized into integrated biochemical pathways that are the basis of cellular operation, and function to sustain life. Metabolism, and thus life, is not static. The rate of metabolites transitioning through biochemical pathways (i.e., flux) determines cellular phenotypes, and is constantly changing in response to genetic or environmental perturbations. Each change evokes a response in metabolic pathway flow, and the quantification of fluxes under varied conditions helps to elucidate major and minor routes, and regulatory aspects of metabolism. To measure fluxes requires experimental methods that assess the movements and transformations of metabolites without creating artifacts. Isotopic labeling fills this role and is a long-standing experimental approach to identify pathways and quantify their metabolic relevance in different tissues or under different conditions. The application of labeling techniques to plant science is however far from reaching it potential. In light of advances in genetics and molecular biology that provide a means to alter metabolism, and given recent improvements in instrumentation, computational tools and available isotopes, the use of isotopic labeling to probe metabolism is becoming more and more powerful. We review the principal analytical methods for isotopic labeling with a focus on seminal studies of pathways and fluxes in lipid metabolism and carbon partitioning through central metabolism. Central carbon metabolic steps are directly linked to lipid production by serving to generate the precursors for fatty acid biosynthesis and lipid assembly. Additionally some of the ideas for labeling techniques that may be most applicable for lipid metabolism in the future were originally developed to investigate other aspects of central metabolism. We conclude by describing recent advances that will play an important future role in quantifying flux and metabolic operation in plant tissues.

Methods and advances in metabolic flux analysis: a mini-review

Metabolic flux analysis (MFA) is one of the pillars of metabolic engineering. Over the past three decades, it has been widely used to quantify intracellular metabolic fluxes in both native (wild type) and engineered biological systems. Through MFA, changes in metabolic pathway fluxes are quantified that result from genetic and/or environmental interventions. This information, in turn, provides insights into the regulation of metabolic pathways and may suggest new targets for further metabolic engineering of the strains. In this mini-review, we discuss and classify the various methods of MFA that have been developed, which include stoichiometric MFA, (13)C metabolic flux analysis, isotopic non-stationary (13)C metabolic flux analysis, dynamic metabolic flux analysis, and (13)C dynamic metabolic flux analysis. For each method, we discuss key advantages and limitations and conclude by highlighting important recent advances in flux analysis approaches.

MITOsym®: A Mechanistic, Mathematical Model of Hepatocellular Respiration and Bioenergetics

Purpose

MITOsym, a new mathematical model of hepatocellular respiration and bioenergetics, has been developed in partnership with the DILIsym® model with the purpose of translating in vitro compound screening data into predictions of drug induced liver injury (DILI) risk for patients. The combined efforts of these two models should increase the efficiency of evaluating compounds in drug development in addition to enhancing patient care.

Methods

MITOsym includes the basic, essential biochemical pathways associated with hepatocellular respiration and bioenergetics, including mitochondrial oxidative phosphorylation, electron transport chain activity, mitochondrial membrane potential, and glycolysis; also included are dynamic feedback signals based on perturbation of these pathways. The quantitative relationships included in MITOsym are based primarily on published data; additional new experiments were also performed in HepG2 cells to determine the effects on oxygen consumption rate as media glucose concentrations or oligomycin concentrations were varied. The effects of varying concentrations of FCCP on the mitochondrial proton gradient were also measured in HepG2 cells.

Results

MITOsym simulates and recapitulates the reported dynamic changes to hepatocellular oxygen consumption rates, extracellular acidification rates, the mitochondrial proton gradient, and ATP concentrations in the presence of classic mitochondrial toxins such as rotenone, FCCP, and oligomycin.

Conclusions

MITOsym can be used to simulate hepatocellular respiration and bioenergetics and provide mechanistic hypotheses to facilitate the translation of in vitro data collection to predictions of in vivo human hepatotoxicity risk for novel compounds.

Electronic supplementary material

The online version of this article (doi:10.1007/s11095-014-1591-0) contains supplementary material, which is available to authorized users.

Simultaneous extraction of proteins and metabolites from cells in culture

Proper sample preparation is an integral part of all omics approaches, and can drastically impact the results of a wide number of analyses. As metabolomics and proteomics research approaches often yield complementary information, it is desirable to have a sample preparation procedure which can yield information for both types of analyses from the same cell population. This protocol explains a method for the separation and isolation of metabolites and proteins from the same biological sample, in order for downstream use in metabolomics and proteomics analyses simultaneously. In this way, two different levels of biological regulation can be studied in a single sample, minimizing the variance that would result from multiple experiments. This protocol can be used with both adherent and suspension cell cultures, and the extraction of metabolites from cellular medium is also detailed, so that cellular uptake and secretion of metabolites can be quantified.

Advantages of this technique includes:1.

Inexpensive and quick to perform; this method does not require any kits.

2.

Can be used on any cells in culture, including cell lines and primary cells extracted from living organisms.

3.

A wide variety of different analysis techniques can be used, adding additional value to metabolomics data analyzed from a sample; this is of high value in experimental systems biology.

Recent advances in 2D and 3D in vitro systems using primary hepatocytes, alternative hepatocyte sources and non-parenchymal liver cells and their use in investigating mechanisms of hepatotoxicity, cell signaling and ADME

This review encompasses the most important advances in liver functions and hepatotoxicity and analyzes which mechanisms can be studied in vitro. In a complex architecture of nested, zonated lobules, the liver consists of approximately 80 % hepatocytes and 20 % non-parenchymal cells, the latter being involved in a secondary phase that may dramatically aggravate the initial damage. Hepatotoxicity, as well as hepatic metabolism, is controlled by a set of nuclear receptors (including PXR, CAR, HNF-4α, FXR, LXR, SHP, VDR and PPAR) and signaling pathways. When isolating liver cells, some pathways are activated, e.g., the RAS/MEK/ERK pathway, whereas others are silenced (e.g. HNF-4α), resulting in up- and downregulation of hundreds of genes. An understanding of these changes is crucial for a correct interpretation of in vitro data. The possibilities and limitations of the most useful liver in vitro systems are summarized, including three-dimensional culture techniques, co-cultures with non-parenchymal cells, hepatospheres, precision cut liver slices and the isolated perfused liver. Also discussed is how closely hepatoma, stem cell and iPS cell-derived hepatocyte-like-cells resemble real hepatocytes. Finally, a summary is given of the state of the art of liver in vitro and mathematical modeling systems that are currently used in the pharmaceutical industry with an emphasis on drug metabolism, prediction of clearance, drug interaction, transporter studies and hepatotoxicity. One key message is that despite our enthusiasm for in vitro systems, we must never lose sight of the in vivo situation. Although hepatocytes have been isolated for decades, the hunt for relevant alternative systems has only just begun.

A metabolite-centric view on flux distributions in genome-scale metabolic models

Background

Genome-scale metabolic models are important tools in systems biology. They permit the in-silico prediction of cellular phenotypes via mathematical optimisation procedures, most importantly flux balance analysis. Current studies on metabolic models mostly consider reaction fluxes in isolation. Based on a recently proposed metabolite-centric approach, we here describe a set of methods that enable the analysis and interpretation of flux distributions in an integrated metabolite-centric view. We demonstrate how this framework can be used for the refinement of genome-scale metabolic models.

Results

We applied the metabolite-centric view developed here to the most recent metabolic reconstruction of Escherichia coli. By compiling the balance sheets of a small number of currency metabolites, we were able to fully characterise the energy metabolism as predicted by the model and to identify a possibility for model refinement in NADPH metabolism. Selected branch points were examined in detail in order to demonstrate how a metabolite-centric view allows identifying functional roles of metabolites. Fructose 6-phosphate aldolase and the sedoheptulose bisphosphate bypass were identified as enzymatic reactions that can carry high fluxes in the model but are unlikely to exhibit significant activity in vivo. Performing a metabolite essentiality analysis, unconstrained import and export of iron ions could be identified as potentially problematic for the quality of model predictions.

Conclusions

The system-wide analysis of split ratios and branch points allows a much deeper insight into the metabolic network than reaction-centric analyses. Extending an earlier metabolite-centric approach, the methods introduced here establish an integrated metabolite-centric framework for the interpretation of flux distributions in genome-scale metabolic networks that can complement the classical reaction-centric framework. Analysing fluxes and their metabolic context simultaneously opens the door to systems biological interpretations that are not apparent from isolated reaction fluxes. Particularly powerful demonstrations of this are the analyses of the complete metabolic contexts of energy metabolism and the folate-dependent one-carbon pool presented in this work. Finally, a metabolite-centric view on flux distributions can guide the refinement of metabolic reconstructions for specific growth scenarios.

Understanding metabolic regulation and its influence on cell physiology

Metabolism impacts all cellular functions and plays a fundamental role in biology. In the last century, our knowledge of metabolic pathway architecture and the genomic landscape of disease has increased exponentially. Combined with these insights, advances in analytical methods for quantifying metabolites and systems approaches to analyze these data now provide powerful tools to study metabolic regulation. Here we review the diverse mechanisms cells use to adapt metabolism to specific physiological states and discuss how metabolic flux analyses can be applied to identify important regulatory nodes to understand normal and pathological cell physiology.

Probing the metabolism of an inducible mammalian expression system using extracellular isotopomer analysis

In an effort to quantitatively assess the impact of recombinant protein expression on the primary metabolism of mammalian cells in culture, we have employed an efficient inducible expression system and conducted a comparative study of the intracellular flux map distribution with and without the induction of recombinant protein synthesis. Cells were grown in parallel semi-continuous cultures with various singly and uniformly labeled substrates and the resulting mass isotopomer distributions of lactate and extracellular amino acids were measured by mass spectrometry. These distributions were used to quantify the main intracellular fluxes. The analysis revealed that, under mild hypothermic conditions, the onset of protein expression is correlated with small but significant changes in several key pathways related to ATP and NADPH formation. More specifically, we observed that induced cells exhibit a more efficient utilization of glucose, characterized by an increased flux of pyruvate into the TCA cycle. In contrast, the catabolic rates of most amino acids remained relatively unaffected. Such analysis is instrumental to guide the identification of robust biomarkers of productivity, as well as the development of medium formulations optimized for recombinant protein production.

Isotopically nonstationary 13C metabolic flux analysis

(13)C metabolic flux analysis (MFA) is a powerful approach for quantifying cell physiology based upon a combination of extracellular flux measurements and intracellular isotope labeling measurements. In this chapter, we present the method of isotopically nonstationary (13)C MFA (INST-MFA), which is applicable to systems that are at metabolic steady state, but are sampled during the transient period prior to achieving isotopic steady state following the introduction of a (13)C tracer. We describe protocols for performing the necessary isotope labeling experiments, for quenching and extraction of intracellular metabolites, for mass spectrometry (MS) analysis of metabolite labeling, and for computational flux estimation using INST-MFA. By combining several recently developed experimental and computational techniques, INST-MFA provides an important new platform for mapping carbon fluxes that is especially applicable to animal cell cultures, autotrophic organisms, industrial bioprocesses, high-throughput experiments, and other systems that are not amenable to steady-state (13)C MFA experiments.

Profiling metabolic networks to study cancer metabolism

Cancer is a disease of unregulated cell growth and survival, and tumors reprogram biochemical pathways to aid these processes. New capabilities in the computational and bioanalytical characterization of metabolism have now emerged, facilitating the identification of unique metabolic dependencies that arise in specific cancers. By understanding the metabolic phenotype of cancers as a function of their oncogenic profiles, metabolic engineering may be applied to design synthetically lethal therapies for some tumors. This process begins with accurate measurement of metabolic fluxes. Here we review advanced methods of quantifying pathway activity and highlight specific examples where these approaches have uncovered potential opportunities for therapeutic intervention.

Stable isotope-assisted metabolomics to detect metabolic flux changes in mammalian cell cultures

The determination of metabolic fluxes provides detailed information of cellular physiology, and the assessment of metabolic flux changes upon a certain perturbation can help to improve biotechnological and pharmaceutical processes. Stable isotope-assisted metabolomics using tracer-labeled substrates is the method of choice to determine the fluxes. Though well-established for microbial cultures, the application to mammalian cells is generally complex and still limited. However, there have been great achievements in recent years and it is now emerging that stable isotope-assisted metabolic flux analysis in mammalian cell cultures will help improving biotechnological production and will also support drug development and discovery.

A kinetic-metabolic model based on cell energetic state: study of CHO cell behavior under Na-butyrate stimulation

A kinetic-metabolic model approach describing and simulating Chinese hamster ovary (CHO) cell behavior is presented. The model includes glycolysis, pentose phosphate pathway, TCA cycle, respiratory chain, redox state and energetic metabolism. Growth kinetic is defined as a function of the major precursors for the synthesis of cell building blocks. Michaelis-Menten type kinetic is used for metabolic intermediates as well as for regulatory functions from energy shuttles (ATP/ADP) and cofactors (NAD/H and NADP/H). Model structure and parameters were first calibrated using results from bioreactor cultures of CHO cells expressing recombinant t-PA. It is shown that the model can simulate experimental data for all available experimental data, such as extracellular glucose, glutamine, lactate and ammonium concentration time profiles, as well as cell energetic state. A sensitivity analysis allowed identifying the most sensitive parameters. The model was then shown to be readily adaptable for studying the effect of sodium butyrate on CHO cells metabolism, where it was applied to the cases with sodium butyrate addition either at mid-exponential growth phase (48 h) or at the early plateau phase (74 h). In both cases, a global optimization routine was used for the simultaneous estimation of the most sensitive parameters, while the insensitive parameters were considered as constants. Finally, confidence intervals for the estimated parameters were calculated. Results presented here further substantiate our previous findings that butyrate treatment at mid-exponential phase may cause a shift in cellular metabolism toward a sustained and increased efficiency of glucose utilization channeled through the TCA cycle.

Isotopically nonstationary 13C flux analysis of Myc-induced metabolic reprogramming in B-cells

We assessed several methods of (13)C metabolic flux analysis (MFA) and found that isotopically nonstationary MFA achieved maximum flux resolution in cultured P493-6 B-cells, which have been engineered to provide tunable expression of the Myc oncoprotein. Comparison of metabolic flux maps obtained under oncogenic (High) and endogenous (Low) Myc expression levels revealed network-wide reprogramming in response to ectopic Myc expression. High Myc cells relied more heavily on mitochondrial oxidative metabolism than Low Myc cells and globally upregulated their consumption of amino acids relative to glucose. TCA cycle and amphibolic mitochondrial pathways exhibited 2- to 4-fold flux increases in High Myc cells, in contrast to modest increases in glucose uptake and lactate excretion. Because our MFA approach relied exclusively upon isotopic measurements of protein-bound amino acids and RNA-bound ribose, it is readily applicable to more complex tumor models that are not amenable to direct extraction and isotopic analysis of free intracellular metabolites.

Systems biology tools for toxicology

An important goal of toxicology is to understand and predict the adverse effects of drugs and other xenobiotics. For pharmaceuticals, such effects often emerge unexpectedly in man even when absent from trials in vitro and in animals. Although drugs and xenobiotics act on molecules, it is their perturbation of intracellular networks that matters. The tremendous complexity of these networks makes it difficult to understand the effects of xenobiotics on their ability to function. Because systems biology integrates data concerning molecules and their interactions into an understanding of network behaviour, it should be able to assist toxicology in this respect. This review identifies how in silico systems biology tools, such as kinetic modelling, and metabolic control, robustness and flux analyse, may indeed help understanding network-mediated toxicity. It also shows how these approaches function by implementing them vis-à-vis the glutathione network, which is important for the detoxification of reactive drug metabolites. The tools enable the appreciation of the steady state concept for the detoxification network and make it possible to simulate and then understand effects of perturbations of the macromolecules in the pathway that are counterintuitive. We review how a glutathione model has been used to explain the impact of perturbation of the pathway at various molecular sites, as would be the effect of single-nucleotide polymorphisms. We focus on how the mutations impact the levels of glutathione and of two candidate biomarkers of hepatic glutathione status. We conclude this review by sketching how the various systems biology tools may help in the various phases of drug development in the pharmaceutical industry.

13C-flux analysis reveals NADPH-balancing transhydrogenation cycles in stationary phase of nitrogen-starving Bacillus subtilis

In their natural habitat, microorganisms are typically confronted with nutritional limitations that restrict growth and force them to persevere in a stationary phase. Despite the importance of this phase, little is known about the metabolic state(s) that sustains it. Here, we investigate metabolically active but non-growing Bacillus subtilis during nitrogen starvation. In the absence of biomass formation as the major NADPH sink, the intracellular flux distribution in these resting B. subtilis reveals a large apparent catabolic NADPH overproduction of 5.0 ± 0.6 mmol g(-1)h(-1) that was partly caused by high pentose phosphate pathway fluxes. Combining transcriptome analysis, stationary (13)C-flux analysis in metabolic deletion mutants, (2)H-labeling experiments, and kinetic flux profiling, we demonstrate that about half of the catabolic excess NADPH is oxidized by two transhydrogenation cycles, i.e. isoenzyme pairs of dehydrogenases with different cofactor specificities that operate in reverse directions. These transhydrogenation cycles were constituted by the combined activities of the glyceraldehyde 3-phosphate dehydrogenases GapA/GapB and the malic enzymes MalS/YtsJ. At least an additional 6% of the overproduced NADPH is reoxidized by continuous cycling between ana- and catabolism of glutamate. Furthermore, in vitro enzyme data show that a not yet identified transhydrogenase could potentially reoxidize ∼20% of the overproduced NADPH. Overall, we demonstrate the interplay between several metabolic mechanisms that concertedly enable network-wide NADPH homeostasis under conditions of high catabolic NADPH production in the absence of cell growth in B. subtilis.

Advanced stoichiometric analysis of metabolic networks of mammalian systems

Metabolic engineering tools have been widely applied to living organisms to gain a comprehensive understanding about cellular networks and to improve cellular properties. Metabolic flux analysis (MFA), flux balance analysis (FBA), and metabolic pathway analysis (MPA) are among the most popular tools in stoichiometric network analysis. Although application of these tools into well-known microbial systems is extensive in the literature, various barriers prevent them from being utilized in mammalian cells. Limited experimental data, complex regulatory mechanisms, and the requirement of more complex nutrient media are some major obstacles in mammalian cell systems. However, mammalian cells have been used to produce therapeutic proteins, to characterize disease states or related abnormal metabolic conditions, and to analyze the toxicological effects of some medicinally important drugs. Therefore, there is a growing need for extending metabolic engineering principles to mammalian cells in order to understand their underlying metabolic functions. In this review article, advanced metabolic engineering tools developed for stoichiometric analysis including MFA, FBA, and MPA are described. Applications of these tools in mammalian cells are discussed in detail, and the challenges and opportunities are highlighted.

Stable isotope-resolved metabolomics and applications for drug development

Advances in analytical methodologies, principally nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS), during the last decade have made large-scale analysis of the human metabolome a reality. This is leading to the reawakening of the importance of metabolism in human diseases, particularly cancer. The metabolome is the functional readout of the genome, functional genome, and proteome; it is also an integral partner in molecular regulations for homeostasis. The interrogation of the metabolome, or metabolomics, is now being applied to numerous diseases, largely by metabolite profiling for biomarker discovery, but also in pharmacology and therapeutics. Recent advances in stable isotope tracer-based metabolomic approaches enable unambiguous tracking of individual atoms through compartmentalized metabolic networks directly in human subjects, which promises to decipher the complexity of the human metabolome at an unprecedented pace. This knowledge will revolutionize our understanding of complex human diseases, clinical diagnostics, as well as individualized therapeutics and drug response. In this review, we focus on the use of stable isotope tracers with metabolomics technologies for understanding metabolic network dynamics in both model systems and in clinical applications. Atom-resolved isotope tracing via the two major analytical platforms, NMR and MS, has the power to determine novel metabolic reprogramming in diseases, discover new drug targets, and facilitates ADME studies. We also illustrate new metabolic tracer-based imaging technologies, which enable direct visualization of metabolic processes in vivo. We further outline current practices and future requirements for biochemoinformatics development, which is an integral part of translating stable isotope-resolved metabolomics into clinical reality.

Metabolic flux analysis and visualization

One of the ultimate goals of systems biology research is to obtain a comprehensive understanding of the control mechanisms of complex cellular metabolisms. Metabolic Flux Analysis (MFA) is a important method for the quantitative estimation of intracellular metabolic flows through metabolic pathways and the elucidation of cellular physiology. The primary challenge in the use of MFA is that many biological networks are underdetermined systems; it is therefore difficult to narrow down the solution space from the stoichiometric constraints alone. In this tutorial, we present an overview of Flux Balance Analysis (FBA) and (13)C-Metabolic Flux Analysis ((13)C-MFA), both of which are frequently used to solve such underdetermined systems, and we demonstrate FBA and (13)C-MFA using the genome-scale model and the central carbon metabolism model, respectively. Furthermore, because such comprehensive study of intracellular fluxes is inherently complex, we subsequently introduce various pathway mapping and visualization tools to facilitate understanding of these data in the context of the pathways. Specific visualization of MFA results using the BioCyc Omics Viewer and Pathway Projector are shown as illustrative examples.

Reductive glutamine metabolism by IDH1 mediates lipogenesis under hypoxia

Acetyl coenzyme A (AcCoA) is the central biosynthetic precursor for fatty-acid synthesis and protein acetylation. In the conventional view of mammalian cell metabolism, AcCoA is primarily generated from glucose-derived pyruvate through the citrate shuttle and ATP citrate lyase in the cytosol. However, proliferating cells that exhibit aerobic glycolysis and those exposed to hypoxia convert glucose to lactate at near-stoichiometric levels, directing glucose carbon away from the tricarboxylic acid cycle and fatty-acid synthesis. Although glutamine is consumed at levels exceeding that required for nitrogen biosynthesis, the regulation and use of glutamine metabolism in hypoxic cells is not well understood. Here we show that human cells use reductive metabolism of α-ketoglutarate to synthesize AcCoA for lipid synthesis. This isocitrate dehydrogenase-1 (IDH1)-dependent pathway is active in most cell lines under normal culture conditions, but cells grown under hypoxia rely almost exclusively on the reductive carboxylation of glutamine-derived α-ketoglutarate for de novo lipogenesis. Furthermore, renal cell lines deficient in the von Hippel-Lindau tumour suppressor protein preferentially use reductive glutamine metabolism for lipid biosynthesis even at normal oxygen levels. These results identify a critical role for oxygen in regulating carbon use to produce AcCoA and support lipid synthesis in mammalian cells.

Collisional fragmentation of central carbon metabolites in LC-MS/MS increases precision of ¹³C metabolic flux analysis

Experimental determination of fluxes by (13)C-tracers relies on detection of (13)C-patterns in metabolites or by-products. In the field of (13)C metabolic flux analysis, the most recent developments point toward recording labeling patterns by liquid chromatography (LC)-mass spectrometry (MS)/MS directly in intermediates in central carbon metabolism (CCM) to increase temporal resolution. Surprisingly, the flux studies published so far with LC-MS measurements were based on intact metabolic intermediates-thus neglected the potential benefits of using positional information to improve flux estimation. For the first time, we exploit collisional fragmentation to obtain more fine-grained (13)C-data on intermediates of CCM and investigate their impact in (13)C metabolic flux analysis. For the case study of Bacillus subtilis grown in mineral medium with (13)C-labeled glucose, we compare the flux estimates obtained by iterative isotopologue balancing of (13)C-data obtained either by LC-MS/MS for solely intact intermediates or LC-MS/MS for intact and fragmented intermediates of CCM. We show that with LC-MS/MS data, fragment information leads to more precise estimates of fluxes in pentose phosphate pathway, glycolysis, and to the tricarboxylic acid cycle. Additionally, we present an efficient analytical strategy to rapidly acquire large sets of (13)C-patterns by tandem MS, and an in-depth analysis of the collisional fragmentation of primary intermediates. In the future, this catalogue will enable comprehensive in silico calculability analyses to identify the most sensitive measurements and direct experimental design.

Eukaryotic metabolism: measuring compartment fluxes

Metabolic compartmentation represents a major characteristic of eukaryotic cells. The analysis of compartmented metabolic networks is complicated by separation and parallelization of pathways, intracellular transport, and the need for regulatory systems to mediate communication between interdependent compartments. Metabolic flux analysis (MFA) has the potential to reveal compartmented metabolic events, although it is a challenging task requiring demanding experimental techniques and sophisticated modeling. At present no ready-made solution can be provided to cope with the complexity of compartmented metabolic networks, but new powerful tools are emerging. This review gives an overview of different strategies to approach this issue, focusing on different MFA methods and highlighting the additional information that should be included to improve the outcome of an experiment and associate estimation procedures.

Metabolic flux analysis of CHO cell metabolism in the late non-growth phase

Chinese hamster ovary (CHO) cell cultures are commonly used for production of recombinant human therapeutic proteins. Often the goal of such a process is to separate the growth phase of the cells, from the non-growth phase where ideally the cells are diverting resources to produce the protein of interest. Characterizing the way that the cells use nutrients in terms of metabolic fluxes as a function of culture conditions can provide a deeper understanding of the cell biology offering guidance for process improvements. To evaluate the fluxes, metabolic flux analysis of the CHO cell culture in the non-growth phase was performed by a combination of steady-state isotopomer balancing and stoichiometric modeling. Analysis of the glycolytic pathway and pentose phosphate pathway (PPP) indicated that almost all of the consumed glucose is diverted towards PPP with a high NADPH production; with even recycle from PPP to G6P in some cases. Almost all of the pyruvate produced from glycolysis entered the TCA cycle with little or no lactate production. Comparison of the non-growth phase against previously reported fluxes from growth phase cultures indicated marked differences in the fluxes, in terms of the split between glycolysis and PPP, and also around the pyruvate node. Possible reasons for the high NADPH production are also discussed. Evaluation of the fluxes indicated that the medium strength, carbon dioxide level, and temperature with dissolved oxygen have statistically significant impacts on different nodes of the flux network.

Metabolic flux analysis in systems biology of mammalian cells

Reaction rates or metabolic fluxes reflect the integrated phenotype of genome, transcriptome and proteome interactions, including regulation at all levels of the cellular hierarchy. Different methods have been developed in the past to analyse intracellular fluxes. However, compartmentation of mammalian cells, varying utilisation of multiple substrates, reversibility of metabolite uptake and production, unbalanced growth behaviour and adaptation of cells to changing environment during cultivation are just some reasons that make metabolic flux analysis (MFA) in mammalian cell culture more challenging compared to microorganisms. In this article MFA using the metabolite balancing methodology and the advantages and disadvantages of (13)C MFA in mammalian cell systems are reviewed. Application examples of MFA in the optimisation of cell culture processes for the production of biopharmaceuticals are presented with a focus on the metabolism of the main industrial workhorse. Another area in which mammalian cell culture plays a key role is in medical and toxicological research. It is shown that MFA can be used to understand pathophysiological mechanisms and can assist in understanding effects of drugs or other compounds on cellular metabolism.

Quantitative characterization of metabolism and metabolic shifts during growth of the new human cell line AGE1.HN using time resolved metabolic flux analysis

For the improved production of vaccines and therapeutic proteins, a detailed understanding of the metabolic dynamics during batch or fed-batch production is requested. To study the new human cell line AGE1.HN, a flexible metabolic flux analysis method was developed that is considering dynamic changes in growth and metabolism during cultivation. This method comprises analysis of formation of cellular components as well as conversion of major substrates and products, spline fitting of dynamic data and flux estimation using metabolite balancing. During batch cultivation of AGE1.HN three distinct phases were observed, an initial one with consumption of pyruvate and high glycolytic activity, a second characterized by a highly efficient metabolism with very little energy spilling waste production and a third with glutamine limitation and decreasing viability. Main events triggering changes in cellular metabolism were depletion of pyruvate and glutamine. Potential targets for the improvement identified from the analysis are (i) reduction of overflow metabolism in the beginning of cultivation, e.g. accomplished by reduction of pyruvate content in the medium and (ii) prolongation of phase 2 with its highly efficient energy metabolism applying e.g. specific feeding strategies. The method presented allows fast and reliable metabolic flux analysis during the development of producer cells and production processes from microtiter plate to large scale reactors with moderate analytical and computational effort. It seems well suited to guide media optimization and genetic engineering of producing cell lines.

13C-metabolic flux analysis for batch culture of Escherichia coli and its Pyk and Pgi gene knockout mutants based on mass isotopomer distribution of intracellular metabolites

Since most bio-production processes are conducted in a batch or fed-batch manner, the evaluation of metabolism with respect to time is highly desirable. Toward this aim, we applied (13)C-metabolic flux analysis to nonstationary conditions by measuring the mass isotopomer distribution of intracellular metabolites. We performed our analysis on batch cultures of wild-type Escherichia coli, as well as on Pyk and Pgi mutants, obtained the fluxes and metabolite concentrations as a function of time. Our results for the wild-type indicated that the TCA cycle flux tended to increase during growth on glucose. Following glucose exhaustion, cells controlled the branch ratio between the glyoxylate pathway and the TCA cycle, depending on the availability of acetate. In the Pyk mutant, the concentrations of glycolytic intermediates changed drastically over time due to the dumping and feedback inhibition caused by PEP accumulation. Nevertheless, the flux distribution and free amino acid concentrations changed little. The growth rate and the fluxes remained constant in the Pgi mutant and the glucose-6-phosphate dehydrogenase reaction was the rate-limiting step. The measured fluxes were compared with those predicted by flux balance analysis using maximization of biomass yield or ATP production. Our findings indicate that the objective function of biosynthesis became less important as time proceeds on glucose in the wild-type, while it remained highly important in the Pyk mutant. Furthermore, ATP production was the primary objective function in the Pgi mutant. This study demonstrates how cells adjust their metabolism in response to environmental changes and/or genetic perturbations in the batch cultivation.

Unraveling the metabolism of HEK-293 cells using lactate isotopomer analysis

HEK-293 is the most extensively used human cell line for the production of viral vectors and is gaining increasing attention for the production of recombinant proteins by transient transfection. To further improve the metabolic characterization of this cell line, we have performed cultures using ¹³C-labeled substrates and measured the resulting mass isotopomer distributions in lactate by LC/MS. Simultaneous metabolite and isotopomer balancing allowed improvement and validation of the metabolic model and quantification of key intracellular pathways. We have determined the amounts of glucose carbon channeled through the PPP, incorporated into the TCA cycle for energy production and lipids biosynthesis, as well as the cytosolic and mitochondrial malic enzyme fluxes. Our analysis also revealed that glutamine did not significantly contribute to lactate formation. An improved and quantitative understanding of the central carbon metabolism is greatly needed to pursue the rational development of engineering approaches at both the cellular and process levels.

Soft constraints-based multiobjective framework for flux balance analysis

The current state of the art for linear optimization in Flux Balance Analysis has been limited to single objective functions. Since mammalian systems perform various functions, a multiobjective approach is needed when seeking optimal flux distributions in these systems. In most of the available multiobjective optimization methods, there is a lack of understanding of when to use a particular objective, and how to combine and/or prioritize mutually competing objectives to achieve a truly optimal solution. To address these limitations we developed a soft constraints based linear physical programming-based flux balance analysis (LPPFBA) framework to obtain a multiobjective optimal solutions. The developed framework was first applied to compute a set of multiobjective optimal solutions for various pairs of objectives relevant to hepatocyte function (urea secretion, albumin, NADPH, and glutathione syntheses) in bioartificial liver systems. Next, simultaneous analysis of the optimal solutions for three objectives was carried out. Further, this framework was utilized to obtain true optimal conditions to improve the hepatic functions in a simulated bioartificial liver system. The combined quantitative and visualization framework of LPPFBA is applicable to any large-scale metabolic network system, including those derived by genomic analyses.

Dynamics and control of the central carbon metabolism in hepatoma cells

BACKGROUND

The liver plays a major role in metabolism and performs a number of vital functions in the body. Therefore, the determination of hepatic metabolite dynamics and the analysis of the control of the respective biochemical pathways are of great pharmacological and medical importance. Extra- and intracellular time-series data from stimulus-response experiments are gaining in importance in the identification of in vivo metabolite dynamics, while dynamic network models are excellent tools for analyzing complex metabolic control patterns. This is the first study that has been undertaken on the data-driven identification of a dynamic liver central carbon metabolism model and its application in the analysis of the distribution of metabolic control in hepatoma cells.

RESULTS

Dynamic metabolite data were collected from HepG2 cells after they had been deprived of extracellular glucose. The concentration of 25 extra- and intracellular intermediates was quantified using HPLC, LC-MS-MS, and GC-MS. The in silico metabolite dynamics were in accordance with the experimental data. The central carbon metabolism of hepatomas was further analyzed with a particular focus on the control of metabolite concentrations and metabolic fluxes. It was observed that the enzyme glucose-6-phosphate dehydrogenase exerted substantial negative control over the glycolytic flux, whereas oxidative phosphorylation had a significant positive control. The control over the rate of NADPH consumption was found to be shared between the NADPH-demand itself (0.65) and the NADPH supply (0.38).

CONCLUSIONS

Based on time-series data, a dynamic central carbon metabolism model was developed for the investigation of new and complex metabolic control patterns in hepatoma cells. The control patterns found support the hypotheses that the glucose-6-phosphate dehydrogenase and the Warburg effect are promising targets for tumor treatment. The systems-oriented identification of metabolite dynamics is a first step towards the genome-based assessment of potential risks posed by nutrients and drugs.