Metabolic flux analysis: a powerful tool for monitoring tissue function

Implementing computational modeling in tissue engineering: where disciplines meet

In recent years, the mathematical and computational sciences have developed novel methodologies and insights that can aid in designing advanced bioreactors, microfluidic set-ups or organ-on-chip devices, in optimizing culture conditions, or predicting long-term behavior of engineered tissues in vivo. In this review, we introduce the concept of computational models and how they can be integrated in an interdisciplinary workflow for Tissue Engineering and Regenerative Medicine (TERM). We specifically aim this review of general concepts and examples at experimental scientists with little or no computational modeling experience. We also describe the contribution of computational models in understanding TERM processes and in advancing the TERM field by providing novel insights.

Effects of hypoglycaemia on neuronal metabolism in the adult brain: role of alternative substrates to glucose

Hypoglycaemia is characterized by decreased blood glucose levels and is associated with different pathologies (e.g. diabetes, inborn errors of metabolism). Depending on its severity, it might affect cognitive functions, including impaired judgment and decreased memory capacity, which have been linked to alterations of brain energy metabolism. Glucose is the major cerebral energy substrate in the adult brain and supports the complex metabolic interactions between neurons and astrocytes, which are essential for synaptic activity. Therefore, hypoglycaemia disturbs cerebral metabolism and, consequently, neuronal function. Despite the high vulnerability of neurons to hypoglycaemia, important neurochemical changes enabling these cells to prolong their resistance to hypoglycaemia have been described. This review aims at providing an overview over the main metabolic effects of hypoglycaemia on neurons, covering in vitro and in vivo findings. Recent studies provided evidence that non-glucose substrates including pyruvate, glycogen, ketone bodies, glutamate, glutamine, and aspartate, are metabolized by neurons in the absence of glucose and contribute to prolong neuronal function and delay ATP depletion during hypoglycaemia. One of the pathways likely implicated in the process is the pyruvate recycling pathway, which allows for the full oxidation of glutamate and glutamine. The operation of this pathway in neurons, particularly after hypoglycaemia, has been re-confirmed recently using metabolic modelling tools (i.e. Metabolic Flux Analysis), which allow for a detailed investigation of cellular metabolism in cultured cells. Overall, the knowledge summarized herein might be used for the development of potential therapies targeting neuronal protection in patients vulnerable to hypoglycaemic episodes.

Metabolomics-on-a-chip and metabolic flux analysis for label-free modeling of the internal metabolism of HepG2/C3A cells

In vitro microfluidic systems are increasingly used as an alternative to standard Petri dishes in bioengineering and metabolomic investigations, as they are expected to provide cellular environments close to the in vivo conditions. In this work, we combined the recently developed "metabolomics-on-a-chip" approach with metabolic flux analysis to model the metabolic network of the hepatoma HepG2/C3A cell line and to infer the distribution of intracellular metabolic fluxes in standard Petri dishes and microfluidic biochips. A high pyruvate reduction to lactate was observed in both systems, suggesting that the cells operate in oxygen-limited environments. Our results also indicate that HepG2/C3A cells in the biochip are characterized by a higher consumption rate of oxygen, presumably due to a higher oxygenation rate in the microfluidic environment. This leads to a higher entry of the ultimate glycolytic product, acetyl-CoA, into the Krebs cycle. These findings are supported by the transcriptional activity of HepG2/C3A cells in both systems since we observed that genes regulated by a HIF-1 (hypoxia-regulated factor-1) transcriptional factor were over expressed under the Petri conditions, but to a lesser extent in the biochip.

Modeling metabolic networks for mammalian cell systems: general considerations, modeling strategies, and available tools

Over the past decades, the availability of large amounts of information regarding cellular processes and reaction rates, along with increasing knowledge about the complex mechanisms involved in these processes, has changed the way we approach the understanding of cellular processes. We can no longer rely only on our intuition for interpreting experimental data and evaluating new hypotheses, as the information to analyze is becoming increasingly complex. The paradigm for the analysis of cellular systems has shifted from a focus on individual processes to comprehensive global mathematical descriptions that consider the interactions of metabolic, genomic, and signaling networks. Analysis and simulations are used to test our knowledge by refuting or validating new hypotheses regarding a complex system, which can result in predictive capabilities that lead to better experimental design. Different types of models can be used for this purpose, depending on the type and amount of information available for the specific system. Stoichiometric models are based on the metabolic structure of the system and allow explorations of steady state distributions in the network. Detailed kinetic models provide a description of the dynamics of the system, they involve a large number of reactions with varied kinetic characteristics and require a large number of parameters. Models based on statistical information provide a description of the system without information regarding structure and interactions of the networks involved. The development of detailed models for mammalian cell metabolism has only recently started to grow more strongly, due to the intrinsic complexities of mammalian systems, and the limited availability of experimental information and adequate modeling tools. In this work we review the strategies, tools, current advances, and recent models of mammalian cells, focusing mainly on metabolism, but discussing the methodology applied to other types of networks as well.

A comprehensive metabolic profile of cultured astrocytes using isotopic transient metabolic flux analysis and C-labeled glucose

Metabolic models have been used to elucidate important aspects of brain metabolism in recent years. This work applies for the first time the concept of isotopic transient 13C metabolic flux analysis (MFA) to estimate intracellular fluxes in primary cultures of astrocytes. This methodology comprehensively explores the information provided by 13C labeling time-courses of intracellular metabolites after administration of a 13C-labeled substrate. Cells were incubated with medium containing [1-13C]glucose for 24 h and samples of cell supernatant and extracts collected at different time points were then analyzed by mass spectrometry and/or high performance liquid chromatography. Metabolic fluxes were estimated by fitting a carbon labeling network model to isotopomer profiles experimentally determined. Both the fast isotopic equilibrium of glycolytic metabolite pools and the slow labeling dynamics of TCA cycle intermediates are described well by the model. The large pools of glutamate and aspartate which are linked to the TCA cycle via reversible aminotransferase reactions are likely to be responsible for the observed delay in equilibration of TCA cycle intermediates. Furthermore, it was estimated that 11% of the glucose taken up by astrocytes was diverted to the pentose phosphate pathway. In addition, considerable fluxes through pyruvate carboxylase [PC; PC/pyruvate dehydrogenase (PDH) ratio = 0.5], malic enzyme (5% of the total pyruvate production), and catabolism of branched-chained amino acids (contributing with ∼40% to total acetyl-CoA produced) confirmed the significance of these pathways to astrocytic metabolism. Consistent with the need of maintaining cytosolic redox potential, the fluxes through the malate–aspartate shuttle and the PDH pathway were comparable. Finally, the estimated glutamate/α-ketoglutarate exchange rate (∼0.7 μmol mg prot−1 h−1) was similar to the TCA cycle flux. In conclusion, this work demonstrates the potential of isotopic transient MFA for a comprehensive analysis of energy metabolism.

FASIMU: flexible software for flux-balance computation series in large metabolic networks

Background

Flux-balance analysis based on linear optimization is widely used to compute metabolic fluxes in large metabolic networks and gains increasingly importance in network curation and structural analysis. Thus, a computational tool flexible enough to realize a wide variety of FBA algorithms and able to handle batch series of flux-balance optimizations is of great benefit.

Results

We present FASIMU, a command line oriented software for the computation of flux distributions using a variety of the most common FBA algorithms, including the first available implementation of (i) weighted flux minimization, (ii) fitness maximization for partially inhibited enzymes, and (iii) of the concentration-based thermodynamic feasibility constraint. It allows batch computation with varying objectives and constraints suited for network pruning, leak analysis, flux-variability analysis, and systematic probing of metabolic objectives for network curation. Input and output supports SBML. FASIMU can work with free (lp_solve and GLPK) or commercial solvers (CPLEX, LINDO). A new plugin (faBiNA) for BiNA allows to conveniently visualize calculated flux distributions. The platform-independent program is an open-source project, freely available under GNU public license at http://www.bioinformatics.org/fasimu including manual, tutorial, and plugins.

Conclusions

We present a flux-balance optimization program whose main merits are the implementation of thermodynamics as a constraint, batch series of computations, free availability of sources, choice on various external solvers, and the flexibility on metabolic objectives and constraints.

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.

Synergy between (13)C-metabolic flux analysis and flux balance analysis for understanding metabolic adaptation to anaerobiosis in E. coli

Genome-based Flux Balance Analysis (FBA) and steady-state isotopic-labeling-based Metabolic Flux Analysis (MFA) are complimentary approaches to predicting and measuring the operation and regulation of metabolic networks. Here, genome-derived models of Escherichia coli (E. coli) metabolism were used for FBA and ¹³C-MFA analyses of aerobic and anaerobic growths of wild-type E. coli (K-12 MG1655) cells. Validated MFA flux maps reveal that the fraction of maintenance ATP consumption in total ATP production is about 14% higher under anaerobic (51.1%) than aerobic conditions (37.2%). FBA revealed that an increased ATP utilization is consumed by ATP synthase to secrete protons from fermentation. The TCA cycle is shown to be incomplete in aerobically growing cells and submaximal growth is due to limited oxidative phosphorylation. An FBA was successful in predicting product secretion rates in aerobic culture if both glucose and oxygen uptake measurement were constrained, but the most-frequently predicted values of internal fluxes yielded from sampling the feasible space differ substantially from MFA-derived fluxes.

Metabolic alterations induced by ischemia in primary cultures of astrocytes: merging 13C NMR spectroscopy and metabolic flux analysis

Disruption of brain energy metabolism is the hallmark of cerebral ischemia, a major cause of death worldwide. Astrocytes play a key role in the regulation of brain metabolism and their vulnerability to ischemia has been described. Aiming to quantify the effects of an ischemic insult in astrocytic metabolism, primary cultures of astrocytes were subjected to 5 h of oxygen and glucose deprivation in a bioreactor. Flux distributions, before and after ischemia, were estimated by metabolic flux analysis using isotopic information and the consumption/secretion rates of relevant extracellular metabolites as constraints. During ischemia and early recovery, 30% of cell death was observed; several metabolic alterations were also identified reflecting a metabolic response by the surviving cells. In the early recovery ( approximately 10 h), astrocytes up-regulated glucose utilization by 30% and increased the pentose phosphate pathway and tricarboxylic acid cycle fluxes by three and twofold, respectively. Additionally, a two to fivefold enhancement in branched-chain amino acids catabolism suggested the importance of anaplerotic molecules to the fast recovery of the energetic state, which was corroborated by measured cellular ATP levels. Glycolytic metabolism was predominant in the late recovery. In summary, this work demonstrates that changes in fluxes of key metabolic pathways are implicated in the recovery from ischemia in astrocytes.

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

This contribution addresses the identification of metabolic fluxes and metabolite concentrations in mammalian cells from transient (13)C-labeling experiments. Whilst part I describes experimental set-up and acquisition of required metabolite and (13)C-labeling data, part II focuses on setting up network models and the estimation of intracellular fluxes. Metabolic fluxes were determined in glycolysis, pentose-phosphate pathway (PPP), and citric acid cycle (TCA) in a hepatoma cell line grown in aerobic batch cultures. In glycolytic and PPP metabolite pools isotopic stationarity was observed within 30 min, whereas in the TCA cycle the labeling redistribution did not reach isotopic steady state even within 180 min. In silico labeling dynamics were in accordance with in vivo (13)C-labeling data. Split ratio between glycolysis and PPP was 57%:43%; intracellular glucose concentration was estimated at 101.6 nmol per 10(6) cells. In contrast to isotopic stationary (13)C-flux analysis, transient (13)C-flux analysis can also be applied to industrially relevant mammalian cell fed-batch and batch cultures.

Gene expression profiling of long-term changes in rat liver following burn injury

The inflammatory response initiated upon burn injury is also associated with extensive metabolic adjustments. While there is a significant body of literature on the characterization of these changes at the metabolite level, little is known on the mechanisms of induction, especially with respect to the role of gene expression. We have comprehensively analyzed changes in gene expression in rat livers during the first 7 d after 20% total body surface area burn injury using Affymetrix microarrays. A total of 740 genes were significantly altered in expression at 1, 2, 4, and 7 d after burn injury compared to sham-burn controls. Functional classification based on gene ontology terms indicated that metabolism, transport, signaling, and defense/inflammation response accounted for more than 70% of the significantly altered genes. Fisher least-significant difference post-hoc testing of the 740 differentially expressed genes indicated that over 60% of the genes demonstrated significant changes in expression either on d 1 or on d 7 postburn. The gene expression trends were corroborated by biochemical measurements of triglycerides and fatty acids 24 h postburn but not at later time points. This suggests that fatty acids are used, at least in part, in the liver as energy substrates for the first 4 d after injury. Our data also suggest that long-term regulation of energy substrate utilization in the liver following burn injury is primarily at the posttranscriptional level. Last, relevance networks of significantly expressed genes indicate the involvement of key small molecules in the hepatic response to 20% total body surface area burn injury.

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

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

Fluxome analysis using GC-MS

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

Regenerative Medicine Bioprocessing: Building a Conceptual Framework Based on Early Studies

This paper reviews early studies of regenerative medicine using human cells and engineered tissues progressing from a laboratory-centered manual procedure toward automated manufacture. It then examines the distinctive bioprocesses by which autologous human material must be produced, the degree of simplification allowed by use of allogeneic cell lines and engineered tissue derived from them, and issues that affect both cell types. The paper concludes by drawing upon this discussion to suggest some factors that will determine how regenerative medicine bioprocessing can progress to provide many units of material economically.

Bayesian-based selection of metabolic objective functions

MOTIVATION

A critical component of in silico analysis of underdetermined metabolic systems is the identification of the appropriate objective function. A common assumption is that the objective of the cell is to maximize growth. This objective function has been shown to be consistent in a few limited experimental cases, but may not be universally appropriate. Here a method is presented to quantitatively determine the most probable objective function.

RESULTS

The genome-scale metabolism of Escherichia coli growing on succinate was used as a case-study for analysis. Five different objective functions, including maximization of growth rate, were chosen based on biological plausibility. A combination of flux balance analysis and linear programming was used to simulate cellular metabolism, which was then compared to independent experimental data using a Bayesian objective function discrimination technique. After comparing rates of oxygen uptake and acetate production, minimization of the production rate of redox potential was determined to be the most probable objective function. Given the appropriate reaction network and experimental data, the discrimination technique can be applied to any bacterium to test a variety of different possible objective functions.

SUPPLEMENTARY INFORMATION

Additional files, code and a program for carrying out model discrimination are available at http://www.engr.uconn.edu/~srivasta/modisc.html.

Identification of distributed metabolic objectives in the hypermetabolic liver by flux and energy balance analysis

A methodology for inferring distributed metabolic objectives from time series flux data is developed by combining metabolic flux analysis, pathway identification, free energy balances, and nested optimization. This methodology is used to investigate the metabolic response of the rat liver to burn injury-induced whole body inflammation. Gibbs free energy changes were computed for stoichiometrically balanced sequences of reactions, or pathways, rather than individual reactions, to account for energetic coupling between reactions. Systematic enumeration of pathways proceeded by elementary flux mode (EFM) analysis. Together with stoichiometric balances and external metabolite flux measurements, the DeltaG(PATH)(o) criterion provided sufficient constraints to solve a series of nested optimization problems on the metabolic goal functions and associated flux distributions of fasted livers during the first-week time course of burn injury. The optimization results suggest that there is a consistent metabolic goal function for the liver that is insensitive to the changing metabolic burdens experienced by the liver during the first-week time course. As defined by the goal function coefficients, the global metabolic objective was to distribute the metabolic resources between amino acid metabolism and ketone body synthesis. These findings point to a role for the time-invariant structure of the metabolic reaction network, expressed as stoichiometric and thermodynamic constraints, in shaping the cellular metabolic objective.

Effects of dehydroepiandrosterone administration on rat hepatic metabolism following thermal injury

BACKGROUND

Severe burns cause dramatic alterations in liver and whole-body metabolism. Recently, there has been interest in using dehydroepiandrosterone (DHEA) as a treatment for trauma patients, and enhanced survival and immune function have been reported using DHEA in animal trauma models. The specific effects of DHEA on hepatic metabolism following burn injury have not been explored.

MATERIALS AND METHODS

Male rats received either (1) a burn covering approximately 20% of the total body surface area or a sham burn or (2) burn injury followed by two intraperitoneal injections of DHEA or vehicle. After 4 days, the livers were isolated and perfused in vitro, and 28 metabolite fluxes were measured. Metabolic flux analysis was used to obtain the intracellular metabolic flux distribution and provide an overview of the metabolic state of the livers in each experimental group.

RESULTS

Burn injury decreased the uptake of lactate and the production of beta-hydroxybutyrate and increased the deamination of glutamine to glutamate and asparagine to aspartate. DHEA, compared to vehicle treatment, decreased pentose phosphate pathway (PPP) fluxes and the uptake of several amino acids in burned rats. Furthermore, DHEA treatment restored liver metabolism in burned rats to a state that was very similar to that of the sham control group.

CONCLUSIONS

DHEA administration appears to normalize hepatocellular metabolism in burned rats but also decreases the PPP flux, which may impair the liver's ability to recycle endogenous antioxidants. DHEA treatment combined with exogenous antioxidants should receive further consideration in the management of burn and trauma patients.

Quantitative effects of thermal injury and insulin on the metabolism of the skeletal muscle using the perfused rat hindquarter preparation

Injury from a severe burn or trauma can propel the body into a hypermetabolic state that can lead to the significant erosion of lean muscle mass. Investigations describing this process have been somewhat limited due to the lack of adequate experimental models. Here we report the use of a perfused rat hindquarter preparation to study the consequences of a moderate burn injury (approximately 20% total body surface area), with or without the addition of exogenous insulin (12.5 mU/mL), on the fluxes of major metabolites across the isolated skeletal muscle. The metabolic flux data was further analyzed using metabolic flux analysis (MFA), which allows for the estimation of the impact of these conditions on the intracellular muscle metabolism. Results indicate that this model is able to capture the increased rate of proteolysis, glutamine formation, and the negative nitrogen balance associated with the burn-induced hypermetabolic state. The inclusion of exogenous insulin resulted in significant changes in several fluxes, including an increase in the metabolism of glucose and the flux through the pentose phosphate pathway, as well as a reduction in the metabolism of glutamine, alanine, and leucine. However, insulin administration did not affect the nitrogen balance or the rate of proteolysis in the muscle, as has been suggested using other techniques. The use of the perfused hindquarter model coupled with MFA is a physiologically relevant and experimentally flexible platform for the exploration of skeletal muscle metabolism under catabolic conditions, and it will be useful in quantifying the specific metabolic consequences of other therapeutic advances.

Novel quantitative tools for engineering analysis of hepatocyte cultures in bioartificial liver systems

Extracorporeal bioartificial liver devices (BAL) are perhaps among the most promising technologies for the treatment of liver failure, but significant technical challenges remain in order to develop systems with sufficient processing capacity and of manageable size. One key limitation is that during BAL operation, when the device is exposed to plasma from the patient, hepatocytes are prone to accumulate intracellular lipids and exhibit poor liver-specific functions. Based on hepatic intermediary metabolism, we have utilized mathematical programming techniques to optimize the biochemical environment of hepatocyte cultures towards the desired effect of increased albumin and urea synthesis. To investigate the feasible range of optimal hepatic function, we have obtained a Pareto optimal set of solutions corresponding to liver-specific functions of urea and albumin secretion in the metabolic framework using multiobjective optimization. The importance of amino acids in the supplementation and the criticality of the metabolic pathways have been investigated using logic-based programming techniques. Since the metabolite measurements are bound to be patient specific, and hence subject to variability, uncertainty has to be integrated with system analysis to improve the prediction of hepatic function. We have used the concept of two stage stochastic programming to obtain robust solutions by considering extracellular variability. The proposed analysis represents a new systematic approach to analyze behavior of hepatocyte cultures and optimize different operating parameters for an extracorporeal device based on real-time conditions.

Metabolic engineering: advances in modeling and intervention in health and disease

The field of metabolic engineering encompasses a powerful set of tools that can be divided into (a) methods to model complex metabolic pathways and (b) techniques to manipulate these pathways for a desired metabolic outcome. These tools have recently seen increased utility in the medical arena, and this paper aims to review significant accomplishments made using these approaches. The modeling of metabolic pathways has been applied to better understand disease-state physiology in a variety of cellar, subcellular, and organ systems, including the liver, heart, mitochondria, and cancerous cells. Metabolic pathway engineering has been used to generate cells with novel biochemical functions for therapeutic use, and specific examples are provided in the areas of glycosylation engineering and dopamine-replacement therapy. In order to document the potential of applying both metabolic modeling and pathway manipulation, we describe pertinent advances in the field of diabetes research. Undoubtedly, as the field of metabolic engineering matures and is applied to a wider array of problems, new advances and therapeutic strategies will follow.

Metabolic flux analysis of cultured hepatocytes exposed to plasma

Hepatic metabolism can be investigated using metabolic flux analysis (MFA), which provides a comprehensive overview of the intracellular metabolic flux distribution. The characterization of intermediary metabolism in hepatocytes is important for all biotechnological applications involving liver cells, including the development of bioartificial liver (BAL) devices. During BAL operation, hepatocytes are exposed to plasma or blood from the patient, at which time they are prone to accumulate intracellular lipids and exhibit poor liver-specific functions. In a prior study, we found that preconditioning the primary rat hepatocytes in culture medium containing physiological levels of insulin, as opposed to the typical supraphysiological levels found in standard hepatocyte culture media, reduced lipid accumulation during subsequent plasma exposure. Furthermore, supplementing the plasma with amino acids restored hepatospecific functions. In the current study, we used MFA to quantify the changes in intracellular pathway fluxes of primary rat hepatocytes in response to low-insulin preconditioning and amino acid supplementation. We found that culturing hepatocytes in medium containing lower physiological levels of insulin decreased the clearance of glucose and glycerol with a concomitant decrease in glycolysis. These findings are consistent with the general notion that low insulin, especially in the presence of high glucagon levels, downregulates glycolysis in favor of gluconeogenesis in hepatocytes. The MFA model shows that, during subsequent plasma exposure, low-insulin preconditioning upregulated gluconeogenesis, with lactate as the primary precursor in unsupplemented plasma, with a greater contribution from deaminated amino acids in amino acid-supplemented plasma. Concomitantly, low-insulin preconditioning increased fatty acid oxidation, an effect that was further enhanced by amino acid supplementation to the plasma. The increase in fatty acid oxidation reduced intracellular triglyceride accumulation. Overall, these findings are consistent with the notion that the insulin level in medium culture presets the metabolic machinery of hepatocytes such that it directly impacts on their metabolic behavior during subsequent plasma culture.

Metabolic flux analysis using mass spectrometry

Detailed knowledge on carbon flux distributions is crucial for the understanding and targeted optimization of cellular systems. Analytical methods to identify the topology of metabolic networks and to quantify fluxes through its different pathways are therefore in the core of metabolic engineering. An elegant approach for metabolic flux analysis is provided by tracer experiments. In such studies tracer substrates with stable isotopes such as 13C are applied and the labeling pattern of metabolites is subsequently measured. Detailed flux distributions can be obtained by a combination of tracer experiments and stoichiometric balancing. In recent years, mass spectrometry (MS) has emerged as an interesting method for labeling measurements in metabolic flux analysis and provided valuable insights into the cellular metabolism. The present review provides an overview on current experimental and modeling tools for metabolic flux analysis by MS. The application of MS for flux analysis is illustrated by examples from the literature for various biological systems, including bacteria, fungi, tissue cultures and in vivo studies in humans.

Application of radiolabeled tracers to biocatalytic flux analysis

Radiolabeled tracers can provide valuable information about the structure of and flux distributions in biocatalytic reaction networks. This method derives from prior studies of glucose metabolism in mammalian systems and is implemented by pulsing a culture with a radiolabeled metabolite that can be transported into the cells and subsequently measuring the radioactivity of all network metabolites following separation by liquid chromatography. Intracellular fluxes can be directly determined from the transient radioactivity count data by tracking the depletion of the radiolabeled metabolite and/or the accompanying accumulation of any products formed. This technique differs from previous methods in that it is applied within a systems approach to the problem of flux determination. It has been used for the investigation of the indene bioconversion network expressed in Rhodococcus sp. KY1. Flux estimates obtained by radioactive tracers were confirmed by macroscopic metabolite balancing and showed that indene oxidation in steady state chemostat cultures proceeds primarily through a monooxygenase activity forming (1S,2R)-indan oxide, with no dehydrogenation of trans-(1R,2R)-indandiol. These results confirmed the significance of indan oxide formation and identified the hydrolysis of indan oxide as a key step in maximizing the production of (2R)-indandiol, a chiral precursor of the HIV protease inhibitor, Crixivan.

Metabolic flux analysis of postburn hepatic hypermetabolism

The hepatic response to severe injury is characterized by a marked upregulation of glucose, fatty acid, and amino acid turnover, which, if persistent, predisposes the patient to progressive organ dysfunction. To study the effect of injury on liver intermediary metabolism, metabolic flux analysis was applied to isolated perfused livers of burned and sham-burned rats. Intracellular fluxes were calculated using metabolite measurements and a stoichiometric balance model. Significant flux increases were found for multiple pathways, including mitochondrial electron transport, the TCA and urea cycles, gluconeogenesis, and pentose phosphate pathway (PPP). The burn-induced increase in gluconeogenesis did not significantly increase glucose output. Instead, glucose-6-phosphate was diverted into the PPP. These changes were paralleled by increases in glucose-6-phosphate dehydrogenase (G6PDH) and glutathione reductase (GR) activities. Given that G6PDH and GR are the most significant NADPH producers and consumers in the liver, respectively, and that GR is responsible for recycling the free radical scavenger glutathione, these data are consistent with the notion that hepatic metabolic changes are in part due to the induction of liver antioxidant defenses.

Towards a circuit engineering discipline

Genetic circuits can now be engineered that perform moderately complicated switching functions or exhibit predictable dynamical behavior. These 'forward engineering' techniques may have to be combined with directed evolution techniques to produce robustness comparable with naturally occurring circuits.