Predictive macroscopic modeling of cell growth, metabolism and monoclonal antibody production: Case study of a CHO fed-batch production.

We describe a systematic approach to establish predictive models of CHO cell growth, cell metabolism and monoclonal antibody (mAb) formation during biopharmaceutical production. The prediction is based on a combination of an empirical metabolic model connecting extracellular metabolic fluxes with cellular growth and product formation with mixed Monod-inhibition type kinetics that we generalized to every possible external metabolite. We describe the maximum specific growth rate as a function of the integral viable cell density (IVCD). Moreover, we also take into account the accumulation of metabolites in intracellular pools that can influence cell growth. This is possible even without identification and quantification of these metabolites as illustrated with fed-batch cultures of Chinese Hamster Ovary (CHO) cells producing a mAb. The impact of cysteine and tryptophan on cell growth and cell productivity was assessed, and the resulting macroscopic model was successfully used to predict the impact of new, untested feeding strategies on cell growth and mAb production. This model combining piecewise linear relationships between metabolic rates, growth rate and production rate together with Monod-inhibition type models for cell growth did well in predicting cell culture performance in fed-batch cultures even outside the range of experimental data used for establishing the model. It could therefore also successfully be applied for in silico prediction of optimal operating conditions.

In-depth characterization of genome-scale network reconstructions for the in vitro synthesis in cell-free systems.

Cell-free systems containing multiple enzymes are becoming an increasingly interesting tool for one-pot syntheses of biochemical compounds. To extensively explore the enormous wealth of enzymes in the biological space, we present methods for assembling and curing data from databases to apply them for the prediction of pathway candidates for directed enzymatic synthesis. We use Kyoto Encyclopedia of Genes and Genomes to establish single organism models and a pan-organism model that is combining the available data from all organisms listed there. We introduce a filtering scheme to remove data that are not suitable, for example, generic metabolites and general reactions. In addition, a valid stoichiometry of reactions is required for acceptance. The networks created are analyzed by graph theoretical methods to identify a set of metabolites that are potentially reachable from a defined set of starting metabolites. Thus, metabolites not connected to such starting metabolites cannot be produced unless new starting metabolites or reactions are introduced. The network models also comprise stoichiometric and thermodynamic data that allow the definition of constraints to identify potential pathways. The resulting data can be directly applied using existing or future pathway finding tools.

Metabolic switches from quiescence to growth in synchronized Saccharomyces cerevisiae.

INTRODUCTION: The switch from quiescence (G0) into G1 and cell cycle progression critically depends on specific nutrients and metabolic capabilities. Conversely, metabolic networks are regulated by enzyme-metabolite interaction and transcriptional regulation that lead to flux modifications to support cell growth. How cells process and integrate environmental information into coordinated responses is challenging to analyse and not yet described quantitatively. OBJECTIVES: To quantitatively monitor the central carbon metabolism during G0 exit and the first 2 h after reentering the cell cycle from synchronized Saccharomyces cerevisiae. METHODS: Dynamic tailored 13C metabolic flux analysis was used to observe the intracellular metabolite flux changes, and the metabolome and proteome were observed to identify regulatory mechanisms. RESULTS: G0 cells responded immediately to an extracellular increase of glucose. The intracellular metabolic flux changed in time and specific events were observed. High fluxes into trehalose and glycogen synthesis were observed during the G0 exit. Both fluxes then decreased, reaching a minimum at t = 65 min. Here, storage degradation contributed significantly (i.e. 21%) to the glycolytic flux. In contrast to these changes, the glucose uptake rate remained constant after the G0 exit. The flux into the oxidative pentose phosphate pathway was highest (29-fold increase, 36.4% of the glucose uptake) at t = 65 min, while it was very low at other time points. The maximum flux seems to correlate with a late G1 state preparing for the S phase transition. In the G1/S phase (t = 87 min), anaplerotic reactions such as glyoxylate shunt increased. Protein results show that during this transition, proteins belonging to clusters related with ribosome biogenesis and assembly, and initiation transcription factors clusters were continuously synthetised. CONCLUSION: The intracellular flux distribution changes dynamically and these major rearrangements highlight the coordinate reorganization of metabolic flux to meet requirements for growth during different cell state.

Proteomic Characterization of Primary Mouse Hepatocytes in Collagen Monolayer and Sandwich Culture.

Dedifferentiation of primary hepatocytes in vitro makes their application in long-term studies difficult. Embedding hepatocytes in a sandwich of extracellular matrix is reported to delay the dedifferentiation process to some extent. In this study, we compared the intracellular proteome of primary mouse hepatocytes (PMH) in conventional monolayer cultures (ML) to collagen sandwich culture (SW) after 1 day and 5 days of cultivation. Quantitative proteome analysis of PMH showed no differences between collagen SW and ML cultures after 1 day. Glycolysis and gluconeogenesis were strongly affected by long-term cultivation in both ML and SW cultures. Interestingly, culture conditions had no effect on cellular lipid metabolism. After 5 days, PMH in collagen SW and ML cultures exhibit characteristic indications of oxidative stress. However, in the SW culture the defense system against oxidative stress is significantly up-regulated to deal with this, whereas in the ML culture a down-regulation of these important enzymes takes place. Regarding the multiple effects of ROS and oxidative stress in cells, we conclude that the down-regulation of these enzymes seem to play a role in the loss of hepatic function observed in the ML cultivation. In addition, enzymes of the urea cycle were clearly down-regulated in ML culture. Proteomics confirms lack in oxidative stress defense mechanisms as the major characteristic of hepatocytes in monolayer cultures compared to sandwich cultures. J. Cell. Biochem. 119: 447-454, 2018. © 2017 Wiley Periodicals, Inc.

Hepatocytes of Wistar and Sprague Dawley rats differ significantly in their central metabolism.

Wistar and Sprague-Dawley (SD) rats are most commonly used experimental rats. They have similar genetic background and are therefore, not discriminated in practical research. In this study, we compared metabolic profiles of Wistar and SD rat hepatocytes from middle (6 months) and old (23 months) age groups. Principle component analysis (PCA) on the specific uptake and production rates of amino acids, glucose, lactate and urea indicated clear differences between Wistar and SD rat hepatocytes. SD rat hepatocytes showed higher uptake rates of various essential and non-essential amino acids, particularly in early culture phases (0-12 h) compared to later phases (12-24 h). SD hepatocytes seem to be more sensitive to isolation procedure and in vitro culture requiring more amino acids for cellular maintenance and repair. Major differences between Wistar and SD rat hepatocytes were observed for glucose and branched chain amino acid metabolism. We conclude that the observed differences in the central carbon metabolism of isolated hepatocytes from these two rats should be considered when using one or the other rat type in studies on metabolic effects or diseases such as diabetes or obesity.

Network design and analysis for multi-enzyme biocatalysis.

BACKGROUND: As more and more biological reaction data become available, the full exploration of the enzymatic potential for the synthesis of valuable products opens up exciting new opportunities but is becoming increasingly complex. The manual design of multi-step biosynthesis routes involving enzymes from different organisms is very challenging. To harness the full enzymatic potential, we developed a computational tool for the directed design of biosynthetic production pathways for multi-step catalysis with in vitro enzyme cascades, cell hydrolysates and permeabilized cells. RESULTS: We present a method which encompasses the reconstruction of a genome-scale pan-organism metabolic network, path-finding and the ranking of the resulting pathway candidates for proposing suitable synthesis pathways. The network is based on reaction and reaction pair data from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the thermodynamics calculator eQuilibrator. The pan-organism network is especially useful for finding the most suitable pathway to a target metabolite from a thermodynamic or economic standpoint. However, our method can be used with any network reconstruction, e.g. for a specific organism. We implemented a path-finding algorithm based on a mixed-integer linear program (MILP) which takes into account both topology and stoichiometry of the underlying network. Unlike other methods we do not specify a single starting metabolite, but our algorithm searches for pathways starting from arbitrary start metabolites to a target product of interest. Using a set of biochemical ranking criteria including pathway length, thermodynamics and other biological characteristics such as number of heterologous enzymes or cofactor requirement, it is possible to obtain well-designed meaningful pathway alternatives. In addition, a thermodynamic profile, the overall reactant balance and potential side reactions as well as an SBML file for visualization are generated for each pathway alternative. CONCLUSION: We present an in silico tool for the design of multi-enzyme biosynthetic production pathways starting from a pan-organism network. The method is highly customizable and each module can be adapted to the focus of the project at hand. This method is directly applicable for (i) in vitro enzyme cascades, (ii) cell hydrolysates and (iii) permeabilized cells.

Synthesis of natural variants and synthetic derivatives of the cyclic nonribosomal peptide luminmide in permeabilized E. coli Nissle and product formation kinetics.

We used a recombinant, permeabilized E. coli Nissle strain harbouring the plu3263 gene cluster from Photorhabdus luminescens for the synthesis of luminmide type cyclic pentapeptides belonging to the class of nonribosomally biosynthesized peptides (NRP). Cells could be fully permeabilized using 1 % v/v toluene. Synthesis of luminmides was increased fivefold when 0.3 mM EDTA was added to the substrate mixture acting as an inhibitor of metal proteases. Luminmide formation was studied applying different amino acid concentrations. Apparent kinetic parameters for the synthesis of the main product luminmide A from leucine, phenylalanine and valine were calculated from the collected data. K sapp values ranged from 0.17 mM for leucine to 0.57 mM for phenylalanine, and r maxapp was about 3 × 10-8 mmol min-1(g CDW)-1). By removing phenylalanine from the substrate mixture, the formation of luminmide A was reduced tenfold while luminmide B was increased from 50 to 500 µg/l becoming the main product. Two new luminmides were synthesized in this study. Luminmide H incorporates tryptophan replacing phenylalanine in luminmide A. In luminmide I, leucine was replaced with 4,5-dehydro-leucine, a non-proteinogenic amino acid fed to the incubation mixture. Our study shows new opportunities for increasing the spectrum of luminmide variants produced, for improving production selectivity and for kinetic in vitro studies of the megasynthetases.

How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology.

Efforts are underway to transform regulatory toxicology and chemical safety assessment from a largely empirical science based on direct observation of apical toxicity outcomes in whole organism toxicity tests to a predictive one in which outcomes and risk are inferred from accumulated mechanistic understanding. The adverse outcome pathway (AOP) framework provides a systematic approach for organizing knowledge that may support such inference. Likewise, computational models of biological systems at various scales provide another means and platform to integrate current biological understanding to facilitate inference and extrapolation. We argue that the systematic organization of knowledge into AOP frameworks can inform and help direct the design and development of computational prediction models that can further enhance the utility of mechanistic and in silico data for chemical safety assessment. This concept was explored as part of a workshop on AOP-Informed Predictive Modeling Approaches for Regulatory Toxicology held September 24-25, 2015. Examples of AOP-informed model development and its application to the assessment of chemicals for skin sensitization and multiple modes of endocrine disruption are provided. The role of problem formulation, not only as a critical phase of risk assessment, but also as guide for both AOP and complementary model development is described. Finally, a proposal for actively engaging the modeling community in AOP-informed computational model development is made. The contents serve as a vision for how AOPs can be leveraged to facilitate development of computational prediction models needed to support the next generation of chemical safety assessment.

Segmented linear modeling of CHO fed-batch culture and its application to large scale production.

We describe a systematic approach to model CHO metabolism during biopharmaceutical production across a wide range of cell culture conditions. To this end, we applied the metabolic steady state concept. We analyzed and modeled the production rates of metabolites as a function of the specific growth rate. First, the total number of metabolic steady state phases and the location of the breakpoints were determined by recursive partitioning. For this, the smoothed derivative of the metabolic rates with respect to the growth rate were used followed by hierarchical clustering of the obtained partition. We then applied a piecewise regression to the metabolic rates with the previously determined number of phases. This allowed identifying the growth rates at which the cells underwent a metabolic shift. The resulting model with piecewise linear relationships between metabolic rates and the growth rate did well describe cellular metabolism in the fed-batch cultures. Using the model structure and parameter values from a small-scale cell culture (2 L) training dataset, it was possible to predict metabolic rates of new fed-batch cultures just using the experimental specific growth rates. Such prediction was successful both at the laboratory scale with 2 L bioreactors but also at the production scale of 2000 L. This type of modeling provides a flexible framework to set a solid foundation for metabolic flux analysis and mechanistic type of modeling. Biotechnol. Bioeng. 2017;114: 785-797. © 2016 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

Comparative Proteome Analysis in Schizosaccharomyces pombe Identifies Metabolic Targets to Improve Protein Production and Secretion.

Protein secretion in yeast is a complex process and its efficiency depends on a variety of parameters. We performed a comparative proteome analysis of a set of Schizosaccharomyces pombe strains producing the α-glucosidase maltase in increasing amounts to investigate the overall proteomic response of the cell to the burden of protein production along the various steps of protein production and secretion. Proteome analysis of these strains, utilizing an isobaric labeling/two dimensional LC-MALDI MS approach, revealed complex changes, from chaperones and secretory transport machinery to proteins controlling transcription and translation. We also found an unexpectedly high amount of changes in enzyme levels of the central carbon metabolism and a significant up-regulation of several amino acid biosyntheses. These amino acids were partially underrepresented in the cellular protein compared with the composition of the model protein. Additional feeding of these amino acids resulted in a 1.5-fold increase in protein secretion. Membrane fluidity was identified as a second bottleneck for high-level protein secretion and addition of fluconazole to the culture caused a significant decrease in ergosterol levels, whereas protein secretion could be further increased by a factor of 2.1. In summary, we show that high level protein secretion causes global changes of protein expression levels in the cell and that precursor availability and membrane composition limit protein secretion in this yeast. In this respect, comparative proteome analysis is a powerful tool to identify targets for an efficient increase of protein production and secretion in S. pombe Data are available via ProteomeXchange with identifiers PXD002693 and PXD003016.

Selective oxidation of UDP-glucose to UDP-glucuronic acid using permeabilized Schizosaccharomyces pombe expressing human UDP-glucose 6-dehydrogenase.

OBJECTIVES: To use permeabilized cells of the fission yeast, Schizosaccharomyces pombe, that expresses human UDP-glucose 6-dehydrogenase (UGDH, EC 1.1.1.22), for the production of UDP-glucuronic acid from UDP-glucose. RESULTS: In cell extracts no activity was detected. Therefore, cells were permeabilized with 0.3 % (v/v) Triton X-100. After washing away all low molecular weight metabolites, the permeabilized cells were directly used as whole cell biocatalyst. Substrates were 5 mM UDP-glucose and 10 mM NAD(+). Divalent cations were not added to the reaction medium as they promoted UDP-glucose hydrolysis. With this reaction system 5 mM UDP-glucose were converted into 5 mM UDP-glucuronic acid within 3 h. CONCLUSIONS: Recombinant permeabilized cells of S. pombe can be used to synthesize UDP-glucuronic acid with 100 % yield and selectivity.

In Silico Modeling for the Prediction of Dose and Pathway-Related Adverse Effects in Humans From In Vitro Repeated-Dose Studies.

Long-term repeated-dose toxicity is mainly assessed in animals despite poor concordance of animal data with human toxicity. Nowadays advanced human in vitro systems, eg, metabolically competent HepaRG cells, are used for toxicity screening. Extrapolation of in vitro toxicity to in vivo effects is possible by reverse dosimetry using pharmacokinetic modeling. We assessed long-term repeated-dose toxicity of bosentan and valproic acid (VPA) in HepaRG cells under serum-free conditions. Upon 28-day exposure, the EC50 values for bosentan and VPA decreased by 21- and 33-fold, respectively. Using EC(10) as lowest threshold of toxicity in vitro, we estimated the oral equivalent doses for both test compounds using a simplified pharmacokinetic model for the extrapolation of in vitro toxicity to in vivo effect. The model predicts that bosentan is safe at the considered dose under the assumed conditions upon 4 weeks exposure. For VPA, hepatotoxicity is predicted for 4% and 47% of the virtual population at the maximum recommended daily dose after 3 and 4 weeks of exposure, respectively. We also investigated the changes in the central carbon metabolism of HepaRG cells exposed to orally bioavailable concentrations of both drugs. These concentrations are below the 28-day EC(10) and induce significant changes especially in glucose metabolism and urea production. These metabolic changes may have a pronounced impact in susceptible patients such as those with compromised liver function and urea cycle deficiency leading to idiosyncratic toxicity. We show that the combination of modeling based on in vitro repeated-dose data and metabolic changes allows the prediction of human relevant in vivo toxicity with mechanistic insights.

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.

Macroscopic modeling of mammalian cell growth and metabolism.

We review major modeling strategies and methods to understand and simulate the macroscopic behavior of mammalian cells. These strategies comprise two important steps: the first step is to identify stoichiometric relationships for the cultured cells connecting the extracellular inputs and outputs. In a second step, macroscopic kinetic models are introduced. These relationships together with bioreactor and metabolite balances provide a complete description of a system in the form of a set of differential equations. These can be used for the simulation of cell culture performance and further for optimization of production.

Multistep synthesis of UDP-glucose using tailored, permeabilized cells of E. coli.

We constructed and applied a recombinant, permeabilized Escherichia coli strain for the multistep synthesis of UDP-glucose. Sucrose phosphorylase (E.C. 2.4.1.7) of Leuconostoc mesenteroides was over expressed and the pgm gene encoding for phosphoglucomutase (E.C. 5.4.2.2) was deleted in E. coli to yield the E. coli JW 0675-1 SP strain. The cells were permeabilized with the detergent Triton X-100 at 0.05 % v/v. The synthesis of UDP-glucose with permeabilized cells was then optimized with regard to pH, cell density during the synthesis and growth phase during cell harvest, metal cofactor, other media components, and temperature. In one configuration sucrose, phosphate, UMP, and ATP were used as substrates. At pH 7.8, 27 mg/ml cell dry weight, cell harvest during the early stationary phase of growth and Mn(2+) as cofactor a yield of 37 % with respect to UMP was achieved at 33 °C. In a second step, ATP was regenerated by feeding glucose and using only catalytic amounts of ATP and NAD(+). A UDP-glucose yield of 60 % with respect to UMP was obtained using this setup. With the same setup but without addition of external ATP, the yield was 54%.

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.

The SEURAT-1 approach towards animal free human safety assessment.

SEURAT-1 is a European public-private research consortium that is working towards animal-free testing of chemical compounds and the highest level of consumer protection. A research strategy was formulated based on the guiding principle to adopt a toxicological mode-of-action framework to describe how any substance may adversely affect human health.The proof of the initiative will be in demonstrating the applicability of the concepts on which SEURAT-1 is built on three levels:(i) Theoretical prototypes for adverse outcome pathways are formulated based on knowledge already available in the scientific literature on investigating the toxicological mode-of-actions leading to adverse outcomes (addressing mainly liver toxicity);(ii)adverse outcome pathway descriptions are used as a guide for the formulation of case studies to further elucidate the theoretical model and to develop integrated testing strategies for the prediction of certain toxicological effects (i.e., those related to the adverse outcome pathway descriptions);(iii) further case studies target the application of knowledge gained within SEURAT-1 in the context of safety assessment. The ultimate goal would be to perform ab initio predictions based on a complete understanding of toxicological mechanisms. In the near-term, it is more realistic that data from innovative testing methods will support read-across arguments. Both scenarios are addressed with case studies for improved safety assessment. A conceptual framework for a rational integrated assessment strategy emerged from designing the case studies and is discussed in the context of international developments focusing on alternative approaches for evaluating chemicals using the new 21st century tools for toxicity testing.

Mass isotopomer analysis of nucleosides isolated from RNA and DNA using GC/MS.

Nucleosides are biosynthesized from metabolites that are at key nodes of intermediary metabolism. Therefore, (13)C labeling patterns in nucleosides from ribonucleic acid (RNA) and deoxyribonucleic acid (DNA) in suitably designed isotopic tracer studies provide information on metabolic flux distributions of proliferating cells. Here, we present a gas chromatography (GC)-mass spectrometry (MS)-based approach that permits one to exploit that potential. In order to elucidate positional isotopomers of nucleosides from RNA and DNA, we screened the fragmentation spectra of their trimethylsilyl derivatives. We identified the molecular ion moieties retained in the respective fragment ions, focusing particularly on the carbon backbone. Nucleosides fragmented at the N-glycosidic bond provide nucleobase and/or ribose or 2'-deoxyribose fragment ions and fragments thereof. Nucleoside fragments composed of the nucleobase plus some carbons of the ribose ring were also observed. In total, we unequivocally assigned 31 fragments. The mass-isotopic distribution of the assigned fragments provides valuable information for later (13)C metabolic flux analysis as indicated by a labeling experiment applying [1-(13)C]glucose in a yeast culture.

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.

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.