Eukaryotic metabolism: measuring compartment fluxes

A pathogen-specific isotope tracing approach reveals metabolic activities and fluxes of intracellular Salmonella

Pathogenic bacteria proliferating inside mammalian host cells need to rapidly adapt to the intracellular environment. How they achieve this and scavenge essential nutrients from the host has been an open question due to the difficulties in distinguishing between bacterial and host metabolites in situ. Here, we capitalized on the inability of mammalian cells to metabolize mannitol to develop a stable isotopic labeling approach to track Salmonella enterica metabolites during intracellular proliferation in host macrophage and epithelial cells. By measuring label incorporation into Salmonella metabolites with liquid chromatography-mass spectrometry (LC-MS), and combining it with metabolic modeling, we identify relevant carbon sources used by Salmonella, uncover routes of their metabolization, and quantify relative reaction rates in central carbon metabolism. Our results underline the importance of the Entner-Doudoroff pathway (EDP) and the phosphoenolpyruvate carboxylase for intracellularly proliferating Salmonella. More broadly, our metabolic labeling strategy opens novel avenues for understanding the metabolism of pathogens inside host cells.

From Protein Film Electrochemistry to Nanoconfined Enzyme Cascades and the Electrochemical Leaf

Protein film electrochemistry (PFE) has given unrivalled insight into the properties of redox proteins and many electron-transferring enzymes, allowing investigations of otherwise ill-defined or intractable topics such as unstable Fe-S centers and the catalytic bias of enzymes. Many enzymes have been established to be reversible electrocatalysts when attached to an electrode, and further investigations have revealed how unusual dependences of catalytic rates on electrode potential have stark similarities with electronics. A special case, the reversible electrochemistry of a photosynthetic enzyme, ferredoxin-NADP⁺ reductase (FNR), loaded at very high concentrations in the 3D nanopores of a conducting metal oxide layer, is leading to a new technology that brings PFE to myriad enzymes of other classes, the activities of which become controlled by the primary electron exchange. This extension is possible because FNR-based recycling of NADP(H) can be coupled to a dehydrogenase, and thence to other enzymes linked in tandem by the tight channelling of cofactors and intermediates within the nanopores of the material. The earlier interpretations of catalytic wave-shapes and various analogies with electronics are thus extended to initiate a field perhaps aptly named "cascade-tronics", in which the flow of reactions along an enzyme cascade is monitored and controlled through an electrochemical analyzer. Unlike in photosynthesis where FNR transduces electron transfer and hydride transfer through the unidirectional recycling of NADPH, the "electrochemical leaf" (e-Leaf) can be used to drive reactions in both oxidizing and reducing directions. The e-Leaf offers a natural way to study how enzymes are affected by nanoconfinement and crowding, mimicking the physical conditions under which enzyme cascades operate in living cells. The reactions of the trapped enzymes, often at very high local concentration, are thus studied electrochemically, exploiting the potential domain to control rates and direction and the current-rate analogy to derive kinetic data. Localized NADP(H) recycling is very efficient, resulting in very high cofactor turnover numbers and new opportunities for controlling and exploiting biocatalysis.

Analysis of plant secondary metabolism using stable isotope-labelled precursors

INTRODUCTION

Analysis of biochemical pathways typically involves feeding a labelled precursor to an organism, and then monitoring the metabolic fate of the label. Initial studies used radioisotopes as a label and then monitored radioactivity in the metabolic products. As analytical equipment improved and became more widely available, preference shifted the use stable 'heavy' isotopes like deuterium (² H)-, carbon-13 (¹³ C)- and nitrogen-15 (¹⁵ N)-atoms as labels. Incorporation of the labels could be monitored by mass spectrometry (MS), as part of a hyphenated tool kits, e.g. Liquid chromatography (LC)-MS, gas chromatography (GC)-MS, LC-MS/MS. MS offers great sensitivity but the exact location of an isotope label in a given metabolite cannot always be unambiguously established. Nuclear magnetic resonance (NMR) can also be used to pick up signals of stable isotopes, and can give information on the precise location of incorporated label in the metabolites. However, the detection limit for NMR is quite a bit higher than that for MS.

OBJECTIVES

A number of experiments involving feeding stable isotope-labelled precursors followed by NMR analysis of the metabolites is presented. The aim is to highlight the use of NMR analysis in identifying the precise fate of isotope labels after precursor feeding experiments. As more powerful NMR equipment becomes available, applications as described in this review may become more commonplace in pathway analysis.

CONCLUSION AND PROSPECTS

NMR is a widely accepted tool for chemical structure elucidation and is now increasingly used in metabolomic studies. In addition, NMR, combined with stable isotope feeding, should be considered as a tool for metabolic flux analyses.

Metabolic Flux Analysis-Linking Isotope Labeling and Metabolic Fluxes

Metabolic flux analysis (MFA) is an increasingly important tool to study metabolism quantitatively. Unlike the concentrations of metabolites, the fluxes, which are the rates at which intracellular metabolites interconvert, are not directly measurable. MFA uses stable isotope labeled tracers to reveal information related to the fluxes. The conceptual idea of MFA is that in tracer experiments the isotope labeling patterns of intracellular metabolites are determined by the fluxes, therefore by measuring the labeling patterns we can infer the fluxes in the network. In this review, we will discuss the basic concept of MFA using a simplified upper glycolysis network as an example. We will show how the fluxes are reflected in the isotope labeling patterns. The central idea we wish to deliver is that under metabolic and isotopic steady-state the labeling pattern of a metabolite is the flux-weighted average of the substrates’ labeling patterns. As a result, MFA can tell the relative contributions of converging metabolic pathways only when these pathways make substrates in different labeling patterns for the shared product. This is the fundamental principle guiding the design of isotope labeling experiment for MFA including tracer selection. In addition, we will also discuss the basic biochemical assumptions of MFA, and we will show the flux-solving procedure and result evaluation. Finally, we will highlight the link between isotopically stationary and nonstationary flux analysis.

Metabolic flux analysis of secondary metabolism in plants

Numerous secondary metabolites from plants are important for their medicinal, nutraceutical or sensory properties. Recently, significant progress has been made in the identification of the genes and enzymes of plant secondary metabolic pathways. Hence, there is interest in using synthetic biology to enhance the production of targeted valuable metabolites in plants. In this article, we examine the contribution that metabolic flux analysis will have on informing the rational selection of metabolic engineering targets as well as analysis of carbon and energy efficiency. Compared to microbes, plants have more complex tissue, cellular and subcellular organization, making precise metabolite concentration measurements more challenging. We review different techniques involved in quantifying flux and provide examples illustrating the application of the techniques. For linear and branched pathways that lead to end products with low turnover, flux quantification is straightforward and doesn’t require isotopic labeling. However, for metabolites synthesized via parallel pathways, there is a requirement for isotopic labeling experiments. If the fed isotopically labeled carbons don’t scramble, one needs to apply transient label balancing methods. In the transient case, it is also necessary to measure metabolite concentrations. While flux analysis is not able to directly identify mechanisms of regulation, it is a powerful tool to examine flux distribution at key metabolic nodes in intermediary metabolism, detect flux to wasteful side pathways, and show how parallel pathways handle flux in wild-type and engineered plants under a variety of physiological conditions.

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Plant secondary metabolites have high economic value to human health and pleasure.

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Plant secondary metabolites are synthesized by pathways in subcellular compartments.

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Metabolic flux analysis can guide the selection of metabolic engineering targets.

Tracing metabolic flux through time and space with isotope labeling experiments

Metabolism is dynamic and must function in context-specific ways to adjust to changes in the surrounding cellular and ecological environment. When isotopic tracers are used, metabolite flow (i.e. metabolic flux) can be quantified through biochemical networks to assess metabolic pathway operation. The cellular activities considered across multiple tissues and organs result in the observed phenotype and can be analyzed to discover emergent, whole-system properties of biology and elucidate misconceptions about network operation. However, temporal and spatial challenges remain significant hurdles and require novel approaches and creative solutions. We survey current investigations in higher plant and animal systems focused on dynamic isotope labeling experiments, spatially resolved measurement strategies, and observations from re-analysis of our own studies that suggest prospects for future work. Related discoveries will be necessary to push the frontier of our understanding of metabolism to suggest novel solutions to cure disease and feed a growing future world population.

A guide to 13C metabolic flux analysis for the cancer biologist

Cancer metabolism is significantly altered from normal cellular metabolism allowing cancer cells to adapt to changing microenvironments and maintain high rates of proliferation. In the past decade, stable-isotope tracing and network analysis have become powerful tools for uncovering metabolic pathways that are differentially activated in cancer cells. In particular, ¹³C metabolic flux analysis (¹³C-MFA) has emerged as the primary technique for quantifying intracellular fluxes in cancer cells. In this review, we provide a practical guide for investigators interested in getting started with ¹³C-MFA. We describe best practices in ¹³C-MFA, highlight potential pitfalls and alternative approaches, and conclude with new developments that can further enhance our understanding of cancer metabolism.

Tracing tagged molecules can help researchers understand the altered metabolism of cancer cells. The abilities of cancer cells to multiply rapidly and invade new tissues are supported by metabolic alterations, which can be investigated by feeding tagged molecules to cells and tracing how they are metabolized. These techniques, such as ¹³C metabolic flux analysis (¹³C-MFA), have been perceived as difficult to use, but recent advances are making them more accessible. Maciek Antoniewicz, University of Delaware, Newark, USA, has published a practical guide for researchers wanting to use 13C-MFA. The review includes best practices, pitfalls, alternative approaches, and new developments, especially new user-friendly software that allows researchers without extensive training in mathematics, statistics, or coding to perform 13C-MFA. Broadening access to tools for investigating altered metabolic pathways may spur development of new cancer therapies targeting these pathways.

Computational Approaches on Stoichiometric and Kinetic Modeling for Efficient Strain Design

Engineering biological systems that are capable of overproducing products of interest is the ultimate goal of any biotechnology application. To this end, stoichiometric (or steady state) and kinetic models are increasingly becoming available for a variety of organisms including prokaryotes, eukaryotes, and microbial communities. This ever-accelerating pace of such model reconstructions has also spurred the development of optimization-based strain design techniques. This chapter highlights a number of such frameworks developed in recent years in order to generate testable hypotheses (in terms of genetic interventions), thus addressing the challenges in metabolic engineering. In particular, three major methods are covered in detail including two methods for designing strains (i.e., one stoichiometric model-based and the other by integrating kinetic information into a stoichiometric model) and one method for analyzing microbial communities.

Understanding metabolism with flux analysis: From theory to application

Quantitative and qualitative knowledge of metabolic rates (i.e. fluxes) over a metabolic network and in specific cellular compartments gives insights into the regulation of metabolism and helps to understand the contribution of metabolic alterations to pathology. In this review we introduce methodology to resolve metabolic fluxes from stable isotope labeling and relevant techniques in model development, model simplification, flux uncertainty analysis and experimental design that together is termed metabolic flux analysis. Finally we discuss applications using metabolic flux analysis to elucidate mechanisms pertinent to tumor cell metabolism. We hope that this review gives the readers a brief introduction of how flux analysis is conducted, how technical issues related to it are addressed, and how its application has contributed to our knowledge of tumor cell metabolism.

Strategies for Extending Metabolomics Studies with Stable Isotope Labelling and Fluxomics

This is a perspective from the peer session on stable isotope labelling and fluxomics at the Australian & New Zealand Metabolomics Conference (ANZMET) held from 30 March to 1 April 2016 at La Trobe University, Melbourne, Australia. This report summarizes the key points raised in the peer session which focused on the advantages of using stable isotopes in modern metabolomics and the challenges in conducting flux analyses. The session highlighted the utility of stable isotope labelling in generating reference standards for metabolite identification, absolute quantification, and in the measurement of the dynamic activity of metabolic pathways. The advantages and disadvantages of different approaches of fluxomics analyses including flux balance analysis, metabolic flux analysis and kinetic flux profiling were also discussed along with the use of stable isotope labelling in in vivo dynamic metabolomics. A number of crucial technical considerations for designing experiments and analyzing data with stable isotope labelling were discussed which included replication, instrumentation, methods of labelling, tracer dilution and data analysis. This report reflects the current viewpoint on the use of stable isotope labelling in metabolomics experiments, identifying it as a great tool with the potential to improve biological interpretation of metabolomics data in a number of ways.

Assessing compartmentalized flux in lipid metabolism with isotopes

Metabolism in plants takes place across multiple cell types and within distinct organelles. The distributions equate to spatial heterogeneity; though the limited means to experimentally assess metabolism frequently involve homogenizing tissues and mixing metabolites from different locations. Most current isotope investigations of metabolism therefore lack the ability to resolve spatially distinct events. Recognition of this limitation has resulted in inspired efforts to advance metabolic flux analysis and isotopic labeling techniques. Though a number of these efforts have been applied to studies in central metabolism; recent advances in instrumentation and techniques present an untapped opportunity to make similar progress in lipid metabolism where the use of stable isotopes has been more limited. These efforts will benefit from sophisticated radiolabeling reports that continue to enrich our knowledge on lipid biosynthetic pathways and provide some direction for stable isotope experimental design and extension of MFA. Evidence for this assertion is presented through the review of several elegant stable isotope studies and by taking stock of what has been learned from radioisotope investigations when spatial aspects of metabolism were considered. The studies emphasize that glycerolipid production occurs across several locations with assembly of lipids in the ER or plastid, fatty acid biosynthesis occurring in the plastid, and the generation of acetyl-CoA and glycerol-3-phosphate taking place at multiple sites. Considering metabolism in this context underscores the cellular and subcellular organization that is important to enhanced production of glycerolipids in plants. An attempt is made to unify salient features from a number of reports into a diagrammatic model of lipid metabolism and propose where stable isotope labeling experiments and further flux analysis may help address questions in the field. This article is part of a Special Issue entitled: Plant Lipid Biology edited by Kent D. Chapman and Ivo Feussner.

Quantifying plant phenotypes with isotopic labeling & metabolic flux analysis

Analyses of metabolic flux using stable isotopes in plants have traditionally been restricted to tissues with presumed homogeneous cell populations and long metabolic steady states such as developing seeds, cell suspensions, or cultured roots and root tips. It is now possible to describe these and other metabolically more dynamic tissues such as leaves in greater detail using novel methods in mass spectrometry, isotope labeling strategies, and transient labeling-based flux analyses. Such studies are necessary for a systems level description of plant function that more closely represents biological reality, and provides insights into the genes that will need to be modified as natural resources become ever more limited and environments change.

Identification of active elementary flux modes in mitochondria using selectively permeabilized CHO cells

Metabolic compartmentation is a key feature of mammalian cells. Mitochondria are the powerhouse of eukaryotic cells, responsible for respiration and the TCA cycle. We accessed the mitochondrial metabolism of the economically important Chinese hamster ovary (CHO) cells using selective permeabilization. We tested key substrates without and with addition of ADP. Based on quantified uptake and production rates, we could determine the contribution of different elementary flux modes to the metabolism of a substrate or substrate combination. ADP stimulated the uptake of most metabolites, directly by serving as substrate for the respiratory chain, thus removing the inhibitory effect of NADH, or as allosteric effector. Addition of ADP favored substrate metabolization to CO2 and did not enhance the production of other metabolites. The controlling effect of ADP was more pronounced when we supplied metabolites to the first part of the TCA cycle: pyruvate, citrate, α-ketoglutarate and glutamine. In the second part of the TCA cycle, the rates were primarily controlled by the concentrations of C4-dicarboxylates. Without ADP addition, the activity of the pyruvate carboxylase-malate dehydrogenase-malic enzyme cycle consumed the ATP produced by oxidative phosphorylation, preventing its accumulation and maintaining metabolic steady state conditions. Aspartate was taken up only in combination with pyruvate, whose uptake also increased, a fact explained by complex regulatory effects. Isocitrate dehydrogenase and α-ketoglutarate dehydrogenase were identified as the key regulators of the TCA cycle, confirming existent knowledge from other cells. We have shown that selectively permeabilized cells combined with elementary mode analysis allow in-depth studying of the mitochondrial metabolism and regulation.

Achieving Metabolic Flux Analysis for S. cerevisiae at a Genome-Scale: Challenges, Requirements, and Considerations

Recent advances in 13C-Metabolic flux analysis (13C-MFA) have increased its capability to accurately resolve fluxes using a genome-scale model with narrow confidence intervals without pre-judging the activity or inactivity of alternate metabolic pathways. However, the necessary precautions, computational challenges, and minimum data requirements for successful analysis remain poorly established. This review aims to establish the necessary guidelines for performing 13C-MFA at the genome-scale for a compartmentalized eukaryotic system such as yeast in terms of model and data requirements, while addressing key issues such as statistical analysis and network complexity. We describe the various approaches used to simplify the genome-scale model in the absence of sufficient experimental flux measurements, the availability and generation of reaction atom mapping information, and the experimental flux and metabolite labeling distribution measurements to ensure statistical validity of the obtained flux distribution. Organism-specific challenges such as the impact of compartmentalization of metabolism, variability of biomass composition, and the cell-cycle dependence of metabolism are discussed. Identification of errors arising from incorrect gene annotation and suggested alternate routes using MFA are also highlighted.

Rites of passage: requirements and standards for building kinetic models of metabolic phenotypes

The overarching ambition of kinetic metabolic modeling is to capture the dynamic behavior of metabolism to such an extent that systems and synthetic biology strategies can reliably be tested in silico. The lack of kinetic data hampers the development of kinetic models, and most of the current models use ad hoc reduced stoichiometry or oversimplified kinetic rate expressions, which may limit their predictive strength. There is a need to introduce the community-level standards that will organize and accelerate the future developments in this area. We introduce here a set of requirements that will ensure the model quality, we examine the current kinetic models with respect to these requirements, and we propose a general workflow for constructing models that satisfy these requirements.

Parallel labeling experiments for pathway elucidation and (13)C metabolic flux analysis

Metabolic pathway models provide the foundation for quantitative studies of cellular physiology through the measurement of intracellular metabolic fluxes. For model organisms metabolic models are well established, with many manually curated genome-scale model reconstructions, gene knockout studies and stable-isotope tracing studies. However, for non-model organisms a similar level of knowledge is often lacking. Compartmentation of cellular metabolism in eukaryotic systems also presents significant challenges for quantitative (13)C-metabolic flux analysis ((13)C-MFA). Recently, innovative (13)C-MFA approaches have been developed based on parallel labeling experiments, the use of multiple isotopic tracers and integrated data analysis, that allow more rigorous validation of pathway models and improved quantification of metabolic fluxes. Applications of these approaches open new research directions in metabolic engineering, biotechnology and medicine.

A roadmap for interpreting (13)C metabolite labeling patterns from cells

Measuring intracellular metabolism has increasingly led to important insights in biomedical research. (13)C tracer analysis, although less information-rich than quantitative (13)C flux analysis that requires computational data integration, has been established as a time-efficient method to unravel relative pathway activities, qualitative changes in pathway contributions, and nutrient contributions. Here, we review selected key issues in interpreting (13)C metabolite labeling patterns, with the goal of drawing accurate conclusions from steady state and dynamic stable isotopic tracer experiments.

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.

Engineering the supply chain for protein production/secretion in yeasts and mammalian cells

Metabolic bottlenecks play an increasing role in yeasts and mammalian cells applied for high-performance production of proteins, particularly of pharmaceutical ones that require complex posttranslational modifications. We review the present status and developments focusing on the rational metabolic engineering of such cells to optimize the supply chain for building blocks and energy. Methods comprise selection of beneficial genetic modifications, rational design of media and feeding strategies. Design of better producer cells based on whole genome-wide metabolic network analysis becomes increasingly possible. High-resolution methods of metabolic flux analysis for the complex networks in these compartmented cells are increasingly available. We discuss phenomena that are common to both types of organisms but also those that are different with respect to the supply chain for the production and secretion of pharmaceutical proteins.

Non-stationary 13C metabolic flux analysis of Chinese hamster ovary cells in batch culture using extracellular labeling highlights metabolic reversibility and compartmentation

BACKGROUND

Mapping the intracellular fluxes for established mammalian cell lines becomes increasingly important for scientific and economic reasons. However, this is being hampered by the high complexity of metabolic networks, particularly concerning compartmentation.

RESULTS

Intracellular fluxes of the CHO-K1 cell line central carbon metabolism were successfully determined for a complex network using non-stationary 13C metabolic flux analysis. Mass isotopomers of extracellular metabolites were determined using [U-13C6] glucose as labeled substrate. Metabolic compartmentation and extracellular transport reversibility proved essential to successfully reproduce the dynamics of the labeling patterns. Alanine and pyruvate reversibility changed dynamically even if their net production fluxes remained constant. Cataplerotic fluxes of cytosolic phosphoenolpyruvate carboxykinase and mitochondrial malic enzyme and pyruvate carboxylase were successfully determined. Glycolytic pyruvate channeling to lactate was modeled by including a separate pyruvate pool. In the exponential growth phase, alanine, glycine and glutamate were excreted, and glutamine, aspartate, asparagine and serine were taken up; however, all these amino acids except asparagine were exchanged reversibly with the media. High fluxes were determined in the pentose phosphate pathway and the TCA cycle. The latter was fueled mainly by glucose but also by amino acid catabolism.

CONCLUSIONS

The CHO-K1 central metabolism in controlled batch culture proves to be robust. It has the main purpose to ensure fast growth on a mixture of substrates and also to mitigate oxidative stress. It achieves this by using compartmentation to control NADPH and NADH availability and by simultaneous synthesis and catabolism of amino acids.

Non-stationary 13C metabolic flux analysis of Chinese hamster ovary cells in batch culture using extracellular labeling highlights metabolic reversibility and compartmentation

BACKGROUND

Mapping the intracellular fluxes for established mammalian cell lines becomes increasingly important for scientific and economic reasons. However, this is being hampered by the high complexity of metabolic networks, particularly concerning compartmentation.

RESULTS

Intracellular fluxes of the CHO-K1 cell line central carbon metabolism were successfully determined for a complex network using non-stationary 13C metabolic flux analysis. Mass isotopomers of extracellular metabolites were determined using [U-13C6] glucose as labeled substrate. Metabolic compartmentation and extracellular transport reversibility proved essential to successfully reproduce the dynamics of the labeling patterns. Alanine and pyruvate reversibility changed dynamically even if their net production fluxes remained constant. Cataplerotic fluxes of cytosolic phosphoenolpyruvate carboxykinase and mitochondrial malic enzyme and pyruvate carboxylase were successfully determined. Glycolytic pyruvate channeling to lactate was modeled by including a separate pyruvate pool. In the exponential growth phase, alanine, glycine and glutamate were excreted, and glutamine, aspartate, asparagine and serine were taken up; however, all these amino acids except asparagine were exchanged reversibly with the media. High fluxes were determined in the pentose phosphate pathway and the TCA cycle. The latter was fueled mainly by glucose but also by amino acid catabolism.

CONCLUSIONS

The CHO-K1 central metabolism in controlled batch culture proves to be robust. It has the main purpose to ensure fast growth on a mixture of substrates and also to mitigate oxidative stress. It achieves this by using compartmentation to control NADPH and NADH availability and by simultaneous synthesis and catabolism of amino acids.

Application of stable isotope-assisted metabolomics for cell metabolism studies

The applications of stable isotopes in metabolomics have facilitated the study of cell metabolisms. Stable isotope-assisted metabolomics requires: (1) properly designed tracer experiments; (2) stringent sampling and quenching protocols to minimize isotopic alternations; (3) efficient metabolite separations; (4) high resolution mass spectrometry to resolve overlapping peaks and background noises; and (5) data analysis methods and databases to decipher isotopic clusters over a broad m/z range (mass-to-charge ratio). This paper overviews mass spectrometry based techniques for precise determination of metabolites and their isotopologues. It also discusses applications of isotopic approaches to track substrate utilization, identify unknown metabolites and their chemical formulas, measure metabolite concentrations, determine putative metabolic pathways, and investigate microbial community populations and their carbon assimilation patterns. In addition, 13C-metabolite fingerprinting and metabolic models can be integrated to quantify carbon fluxes (enzyme reaction rates). The fluxome, in combination with other "omics" analyses, may give systems-level insights into regulatory mechanisms underlying gene functions. More importantly, 13C-tracer experiments significantly improve the potential of low-resolution gas chromatography-mass spectrometry (GC-MS) for broad-scope metabolism studies. We foresee the isotope-assisted metabolomics to be an indispensable tool in industrial biotechnology, environmental microbiology, and medical research.

Metabolic control at the cytosol-mitochondria interface in different growth phases of CHO cells

Metabolism at the cytosol-mitochondria interface and its regulation is of major importance particularly for efficient production of biopharmaceuticals in Chinese hamster ovary (CHO) cells but also in many diseases. We used a novel systems-oriented approach combining dynamic metabolic flux analysis and determination of compartmental enzyme activities to obtain systems level information with functional, spatial and temporal resolution. Integrating these multiple levels of information, we were able to investigate the interaction of glycolysis and TCA cycle and its metabolic control. We characterized metabolic phases in CHO batch cultivation and assessed metabolic efficiency extending the concept of metabolic ratios. Comparing in situ enzyme activities including their compartmental localization with in vivo metabolic fluxes, we were able to identify limiting steps in glycolysis and TCA cycle. Our data point to a significant contribution of substrate channeling to glycolytic regulation. We show how glycolytic channeling heavily affects the availability of pyruvate for the mitochondria. Finally, we show that the activities of transaminases and anaplerotic enzymes are tailored to permit a balanced supply of pyruvate and oxaloacetate to the TCA cycle in the respective metabolic states. We demonstrate that knowledge about metabolic control can be gained by correlating in vivo metabolic flux dynamics with time and space resolved in situ enzyme activities.

Quantification of peptide m/z distributions from 13C-labeled cultures with high-resolution mass spectrometry

Isotopic labeling studies of primary metabolism frequently utilize GC/MS to quantify (13)C in protein-hydrolyzed amino acids. During processing some amino acids are degraded, which reduces the size of the measurement set. The advent of high-resolution mass spectrometers provides a tool to assess molecular masses of peptides with great precision and accuracy and computationally infer information about labeling in amino acids. Amino acids that are isotopically labeled during metabolism result in labeled peptides that contain spatial and temporal information that is associated with the biosynthetic origin of the protein. The quantification of isotopic labeling in peptides can therefore provide an assessment of amino acid metabolism that is specific to subcellular, cellular, or temporal conditions. A high-resolution orbital trap was used to quantify isotope labeling in peptides that were obtained from unlabeled and isotopically labeled soybean embryos and Escherichia coli cultures. Standard deviations were determined by estimating the multinomial variance associated with each element of the m/z distribution. Using the estimated variance, quantification of the m/z distribution across multiple scans was achieved by a nonlinear fitting approach. Observed m/z distributions of uniformly labeled E. coli peptides indicated no significant differences between observed and simulated m/z distributions. Alternatively, amino acid m/z distributions obtained from GC/MS were convolved to simulate peptide m/z distributions but resulted in distinct profiles due to the production of protein prior to isotopic labeling. The results indicate that peptide mass isotopologue measurements faithfully represent mass distributions, are suitable for quantification of isotope-labeling-based studies, and provide additional information over existing methods.

Quenching methods for the analysis of intracellular metabolites

Sampling and quenching methods for intracellular metabolite analysis in mammalian cells in adherent and suspension culture are described. Quenching of adherent cells is achieved by application of hot air after removal of the supernatant by suction. For suspension cultures, the addition of excess ice-cold saline results in a rapid inactivation of metabolism and significant dilution of extracellular metabolites. Medium carryover is prevented by rinsing the cells with washing solution. Separation of supernatant from suspension cells via centrifugation is incomplete due to required short centrifugation time. Thus, it is necessary to determine the reproducible cell recovery after quenching.

Publishing 13C metabolic flux analysis studies: a review and future perspectives

(13)C-Metabolic flux analysis ((13)C-MFA) is a powerful model-based analysis technique for determining intracellular metabolic fluxes in living cells. It has become a standard tool in many labs for quantifying cell physiology, e.g., in metabolic engineering, systems biology, biotechnology, and biomedical research. With the increasing number of (13)C-MFA studies published each year, it is now ever more important to provide practical guidelines for performing and publishing (13)C-MFA studies so that quality is not sacrificed as the number of publications increases. The main purpose of this paper is to provide an overview of good practices in (13)C-MFA, which can eventually be used as minimum data standards for publishing (13)C-MFA studies. The motivation for this work is two-fold: (1) currently, there is no general consensus among researchers and journal editors as to what minimum data standards should be required for publishing (13)C-MFA studies; as a result, there are great discrepancies in terms of quality and consistency; and (2) there is a growing number of studies that cannot be reproduced or verified independently due to incomplete information provided in these publications. This creates confusion, e.g. when trying to reconcile conflicting results, and hinders progress in the field. Here, we review current status in the (13)C-MFA field and highlight some of the shortcomings with regards to (13)C-MFA publications. We then propose a checklist that encompasses good practices in (13)C-MFA. We hope that these guidelines will be a valuable resource for the community and allow (13)C-flux studies to be more easily reproduced and accessed by others in the future.

Carbon and nitrogen provisions alter the metabolic flux in developing soybean embryos

Soybean (Glycine max) seeds store significant amounts of their biomass as protein, levels of which reflect the carbon and nitrogen received by the developing embryo. The relationship between carbon and nitrogen supply during filling and seed composition was examined through a series of embryo-culturing experiments. Three distinct ratios of carbon to nitrogen supply were further explored through metabolic flux analysis. Labeling experiments utilizing [U-(13)C5]glutamine, [U-(13)C4]asparagine, and [1,2-(13)C2]glucose were performed to assess embryo metabolism under altered feeding conditions and to create corresponding flux maps. Additionally, [U-(14)C12]sucrose, [U-(14)C6]glucose, [U-(14)C5]glutamine, and [U-(14)C4]asparagine were used to monitor differences in carbon allocation. The analyses revealed that: (1) protein concentration as a percentage of total soybean embryo biomass coincided with the carbon-to-nitrogen ratio; (2) altered nitrogen supply did not dramatically impact relative amino acid or storage protein subunit profiles; and (3) glutamine supply contributed 10% to 23% of the carbon for biomass production, including 9% to 19% of carbon to fatty acid biosynthesis and 32% to 46% of carbon to amino acids. Seed metabolism accommodated different levels of protein biosynthesis while maintaining a consistent rate of dry weight accumulation. Flux through ATP-citrate lyase, combined with malic enzyme activity, contributed significantly to acetyl-coenzyme A production. These fluxes changed with plastidic pyruvate kinase to maintain a supply of pyruvate for amino and fatty acids. The flux maps were independently validated by nitrogen balancing and highlight the robustness of primary metabolism.

Metabolic network flux analysis for engineering plant systems

Metabolic network flux analysis (NFA) tools have proven themselves to be powerful aids to metabolic engineering of microbes by providing quantitative insights into the flows of material and energy through cellular systems. The development and application of NFA tools to plant systems has advanced in recent years and are yielding significant insights and testable predictions. Plants present substantial opportunities for the practical application of NFA but they also pose serious challenges related to the complexity of plant metabolic networks and to deficiencies in our knowledge of their structure and regulation. By considering the tools available and selected examples, this article attempts to assess where and how NFA is most likely to have a real impact on plant biotechnology.

Parallel labeling experiments and metabolic flux analysis: Past, present and future methodologies

Radioactive and stable isotopes have been applied for decades to elucidate metabolic pathways and quantify carbon flow in cellular systems using mass and isotope balancing approaches. Isotope-labeling experiments can be conducted as a single tracer experiment, or as parallel labeling experiments. In the latter case, several experiments are performed under identical conditions except for the choice of substrate labeling. In this review, we highlight robust approaches for probing metabolism and addressing metabolically related questions though parallel labeling experiments. In the first part, we provide a brief historical perspective on parallel labeling experiments, from the early metabolic studies when radioisotopes were predominant to present-day applications based on stable-isotopes. We also elaborate on important technical and theoretical advances that have facilitated the transition from radioisotopes to stable-isotopes. In the second part of the review, we focus on parallel labeling experiments for (13)C-metabolic flux analysis ((13)C-MFA). Parallel experiments offer several advantages that include: tailoring experiments to resolve specific fluxes with high precision; reducing the length of labeling experiments by introducing multiple entry-points of isotopes; validating biochemical network models; and improving the performance of (13)C-MFA in systems where the number of measurements is limited. We conclude by discussing some challenges facing the use of parallel labeling experiments for (13)C-MFA and highlight the need to address issues related to biological variability, data integration, and rational tracer selection.

Perspectives in metabolic engineering: understanding cellular regulation towards the control of metabolic routes

Metabolic engineering seeks to redirect metabolic pathways through the modification of specific biochemical reactions or the introduction of new ones with the use of recombinant technology. Many of the chemicals synthesized via introduction of product-specific enzymes or the reconstruction of entire metabolic pathways into engineered hosts that can sustain production and can synthesize high yields of the desired product as yields of natural product-derived compounds are frequently low, and chemical processes can be both energy and material expensive; current endeavors have focused on using biologically derived processes as alternatives to chemical synthesis. Such economically favorable manufacturing processes pursue goals related to sustainable development and "green chemistry". Metabolic engineering is a multidisciplinary approach, involving chemical engineering, molecular biology, biochemistry, and analytical chemistry. Recent advances in molecular biology, genome-scale models, theoretical understanding, and kinetic modeling has increased interest in using metabolic engineering to redirect metabolic fluxes for industrial and therapeutic purposes. The use of metabolic engineering has increased the productivity of industrially pertinent small molecules, alcohol-based biofuels, and biodiesel. Here, we highlight developments in the practical and theoretical strategies and technologies available for the metabolic engineering of simple systems and address current limitations.

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.

Global profiling strategies for mapping dysregulated metabolic pathways in cancer

Cancer cells possess fundamentally altered metabolism that provides a foundation to support tumorigenicity and malignancy. Our understanding of the biochemical underpinnings of cancer has benefited from the integrated utilization of large-scale profiling platforms (e.g., genomics, proteomics, and metabolomics), which, together, can provide a global assessment of how enzymes and their parent metabolic networks become altered in cancer to fuel tumor growth. This review presents several examples of how these integrated platforms have yielded fundamental insights into dysregulated metabolism in cancer. We will also discuss questions and challenges that must be addressed to more completely describe, and eventually control, the diverse metabolic pathways that support tumorigenesis.

Butanol production from renewable biomass by clostridia

Global energy crisis and limited supply of petroleum fuels have rekindled the worldwide focus towards development of a sustainable technology for alternative fuel production. Utilization of abundant renewable biomass offers an excellent opportunity for the development of an economical biofuel production process at a scale sufficiently large to have an impact on sustainability and security objectives. Additionally, several environmental benefits have also been linked with the utilization of renewable biomass. Butanol is considered to be superior to ethanol due to its higher energy content and less hygroscopy. This has led to an increased research interest in butanol production from renewable biomass in recent years. In this paper, we review the various aspects of utilizing renewable biomass for clostridial butanol production. Focus is given on various alternative substrates that have been used for butanol production and on fermentation strategies recently reported to improve butanol production.

Parallel labeling experiments with [1,2-(13)C]glucose and [U-(13)C]glutamine provide new insights into CHO cell metabolism

We applied a parallel labeling strategy using two isotopic tracers, [1,2-(13)C]glucose and [U-(13)C]glutamine, to determine metabolic fluxes in Chinese hamster ovary (CHO) cells. CHO cells were grown in parallel cultures over a period of six days with glucose and glutamine feeding. On days 2 and 5, isotopic tracers were introduced and (13)C-labeling of intracellular metabolites was measured by gas chromatography-mass spectrometry (GC-MS). Metabolites in glycolysis pathway reached isotopic steady state for [1,2-(13)C]glucose within 1.5h, and metabolites in the TCA cycle reached isotopic steady state for [U-(13)C]glutamine within 3h. Combined analysis of multiple data sets produced detailed flux maps at two key metabolic phases, exponential growth phase (day 2) and early stationary phase (day 5). Flux results revealed significant rewiring of intracellular metabolism in the transition from growth to non-growth, including changes in oxidative pentose phosphate pathway, anaplerosis, amino acid metabolism, and fatty acid biosynthesis. At the growth phase, de novo fatty acid biosynthesis correlated well with the lipid requirements for cell growth. However, surprisingly, at the non-growth phase the fatty acid biosynthesis flux remained high even though no new lipids were needed for cell growth. Additionally, we identified a discrepancy in the estimated TCA cycle flux obtained using traditional stoichiometric flux balancing and (13)C-metabolic flux analysis. Our results suggested that CHO cells produced additional metabolites from glucose that were not captured in previous metabolic models. Follow-up experiments with [U-(13)C]glucose confirmed that additional metabolites were accumulating in the medium that became M+3 and M+6 labeled.

Rational design of ¹³C-labeling experiments for metabolic flux analysis in mammalian cells

Background

¹³C-Metabolic flux analysis (¹³C-MFA) is a standard technique to probe cellular metabolism and elucidate in vivo metabolic fluxes. ¹³C-Tracer selection is an important step in conducting ¹³C-MFA, however, current methods are restricted to trial-and-error approaches, which commonly focus on an arbitrary subset of the tracer design space. To systematically probe the complete tracer design space, especially for complex systems such as mammalian cells, there is a pressing need for new rational approaches to identify optimal tracers.

Results

Recently, we introduced a new framework for optimal ¹³C-tracer design based on elementary metabolite units (EMU) decomposition, in which a measured metabolite is decomposed into a linear combination of so-called EMU basis vectors. In this contribution, we applied the EMU method to a realistic network model of mammalian metabolism with lactate as the measured metabolite. The method was used to select optimal tracers for two free fluxes in the system, the oxidative pentose phosphate pathway (oxPPP) flux and anaplerosis by pyruvate carboxylase (PC). Our approach was based on sensitivity analysis of EMU basis vector coefficients with respect to free fluxes. Through efficient grouping of coefficient sensitivities, simple tracer selection rules were derived for high-resolution quantification of the fluxes in the mammalian network model. The approach resulted in a significant reduction of the number of possible tracers and the feasible tracers were evaluated using numerical simulations. Two optimal, novel tracers were identified that have not been previously considered for ¹³C-MFA of mammalian cells, specifically [2,3,4,5,6-¹³C]glucose for elucidating oxPPP flux and [3,4-¹³C]glucose for elucidating PC flux. We demonstrate that ¹³C-glutamine tracers perform poorly in this system in comparison to the optimal glucose tracers.

Conclusions

In this work, we have demonstrated that optimal tracer design does not need to be a pure simulation-based trial-and-error process; rather, rational insights into tracer design can be gained through the application of the EMU basis vector methodology. Using this approach, rational labeling rules can be established a priori to guide the selection of optimal ¹³C-tracers for high-resolution flux elucidation in complex metabolic network models.