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PubMedDate not supplied

Metabolic control analysis of eucaryotic pyruvate dehydrogenase multienzyme complex.

Metabolic control analysis (MCA) of pyruvate dehydrogenase multienzyme (PDH) complex of eucaryotic cells has been carried out using both in vitro and in vivo mechanistic models. Flux control coefficients (FCC) for the sensitivity of pyruvate decarboxylation rate to activities of various PDH complex reactions are determined. FCCs are shown to be strong functions of both pyruvate levels and various components of PDH complex. With the in vitro model, FCCs are shown to be sensitive to only the E1 component of the PDH complex at low pyruvate concentrations. At high pyruvate concentrations, the control is shared by all of the components, with E1 having a negative influence while the other three components, E2, X, and K, exert a positive control over the pyruvate decarboxylation rate. An unusual behavior of deactivation of the E1 component leading to higher net PDH activity is shown to be linked to the combined effect of protein X acylation and E1 deactivation. The steady-state analysis of the in vivo model reveals multiple steady state behavior of pyruvate metabolism with two stable and one unstable steady-states branches. FCCs also display multiplicity, showing completely different control distribution exerted by pyruvate and PDH components on three branches. At low pyruvate concentrations, pyruvate supply dominates the decarboxylation rate and PDH components do not exert any significant control. Reverse control distribution is observed at high pyruvate concentration. The effect of dilution due to cell growth on pyruvate metabolism is investigated in detail. While pyruvate dilution effects are shown to be negligible under all conditions, significant PDH complex dilution effects are observed under certain conditions. Comparison of in vitro and in vivo models shows that PDH components exert different degrees of control outside and inside the cells. At high pyruvate levels, PDH components are shown to exert a higher degree of control when reactions are taking place inside the cells as compared to the in vitro situation.

Cell Division↗
PubMed1999

Metabolic flux analysis for efficient pyruvate fermentation using vitamin-auxotrophic yeast of Torulopsis glabrata.

The metabolism of a vitamin-auxotrophic pyruvate-producing microorganism, Torulopsis glabrata IFO 0005, was investigated by metabolic flux analysis. Particular attention was focused on the effect of culture conditions, such as dissolved oxygen (DO) concentration and thiamine concentration, on specific pathway activities. The results of metabolic flux analysis indicate that the thiamine concentration significantly affected pyruvate dehydrogenase and pyruvate decarboxylase activities, and plays an important role in cell growth and pyruvate production. Metabolic flux analysis was also utilized to clarify the metabolism of this strain during pyruvate fermentation under different oxygen supply conditions, and the reason for the enhanced pyruvate production under conditions of 30-40% DO concentration was clarified from the viewpoint of intracellular flux distributions. Based on the analysis of the effect of thiamine concentration on the metabolic fluxes, we conducted a fed-batch experiment where the initial thiamine concentration was reduced to 30 microg/l and thiamine was added at 10 microg/l during fermentation when the cell growth rate decreased to 0.2 h(-1). With separate addition of thiamine, the overall pyruvate yield could be improved by 15% due to the decrease of ethanol production.

Journal Article↗
PubMed1999

Metabolite and isotopomer balancing in the analysis of metabolic cycles: I. Theory.

Proper analysis of label distribution in metabolic pathway intermediates is critical for correct interpretation of experimental data and strategic experimental design. While, for example, 13C nuclear magnetic resonance (NMR) spectroscopy is usually limited to the measurement of degrees of 13C enrichment, more information about metabolic fluxes can be extracted from the fine structure of NMR spectra, or molecular weight distributions of isotopomers of metabolic intermediates (measured by gas chromatography-mass spectrometry). For this purpose, rigorous accounting for the contribution of all pathways to label distribution is required, especially contributions resulting from multiple turns of metabolic cycles. In this paper we present a mathematical model developed to analyze isotopomer distributions of tricarboxylic acid cycle (TCA) intermediates following the administration of 13C (or 14C) labeled substrates. The theory presented provides the basis to analyze 13C NMR spectra and molecular weight distributions of metabolites. In a companion paper (Park et al., 1999), the theory is applied to the analysis of several cases of biological significance. Copyright 1999 John Wiley & Sons, Inc.

Journal Article↗
PubMed1992

The definitions of metabolic control analysis revisited.

Various definitions of coefficients in metabolic control analysis are examined with respect to their theoretical consistency and practical applicability. We suggest agreement upon a definition for control coefficients which is clearly distinct from that for response coefficients, in such a way that the former describe inherent properties of the metabolic system while the latter refer to the influence of special parameters. Advantages and drawbacks of using normalized or non-normalized control coefficients are studied. It is shown that normalized control coefficients have the advantage of being invariant to a different rescaling of the particular fluxes. We demonstrate that some problems are easier to tackle if the consistency of time-independent control coefficients with their time-dependent counterparts is taken into account. It is shown that the matrix of flux control coefficients is an indempotent matrix. This allows an interpretation in terms of the transduction of the effect of parameter perturbations. Several aspects of the experimental measurement of control coefficients are discussed, with special reference to the different definitions.

Enzymes↗
PubMed1996

Top down metabolic control analysis.

In the top down approach to metabolic control analysis, reactions are grouped together into a few large blocks connected by a small number of intermediates. Control is analysed by adding inhibitor or activators that work within single blocks and measuring intermediates and fluxes, or by adding new branches and measuring changes in flux. The approach is experimentally and conceptually simple, and provides a complete but coarse description of control in complex metabolic systems that are not easily accessible using other approaches. This paper gives an overview of the method, its equations and their derivations. It discusses the ways the approach has been used in organelles and cells to identify the sites of action of effectors, to measure the distribution of control by blocks of reactions, and to measure regulation by effectors.

Animals↗
PubMed1997

Elasticities in Metabolic Control Analysis: algebraic derivation of simplified expressions.

MOTIVATION: Metabolic Control Analysis is one of many disciplines that make use of scaled derivatives. In particular, 'elasticities' are used to quantify the effect of an effector or substrate concentration on an enzyme rate under locally specified conditions. Normally an algebraic expression for the elasticity of an enzyme is obtained by differentiating its rate law, multiplying by the effector concentration and dividing by the rate law itself: this results in considerable expression expansion, and when the results are subsequently simplified it is often at the expense of biological comprehensibility. RESULTS: We present a novel algorithm which not only circumvents the expression expansion, but preserves an elegant separation of the components in enzyme behaviour. Easily implemented, and producing gains in both performance and numerical precision, the algorithm is potentially applicable to a number of existing packages. It also greatly assists the manual derivation and evaluation of elasticities, allowing the elasticity of even quite complex enzyme systems to be written by inspection.

Algorithms↗
PubMed2003

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.

Amino Acids↗
PubMed2000

Metabolic control analysis for lysine synthesis using Corynebacterium glutamicum and experimental verification.

Metabolic control analysis was carried out for the lysine biosynthetic pathway in Corynebacterium glutamicum ATCC 21253 using mechanism-based kinetic models developed for enzymatic reactions for this pathway. The rate-limiting steps during lysine production were determined with the aid of flux control coefficients, which indicated that the lysine synthesis flux is governed mainly by both aspartokinase and permease activity in the export system. Analyses indicated that an increase in the activity of aspartokinase would significantly alleviate its effect on the overall flux, and the limiting step is expected to shift to permease and other lysine synthetic enzymes. The influences of many participating precursors and cofactors on lysine synthesis flux were also investigated through the calculation of response coefficients for individual parameters. Although most parameters were not found to exert significant influences on lysine flux, extracellular lysine concentration was found to have a substantial effect on lysine production, and detailed analysis indicated that a decrease in the external lysine concentration will enhance the metabolite synthesis considerably and shift the control from export step to other steps. Although a decrease in external pH (pH0) seems to increase lysine flux, consideration of the export carrier concentration in response to external pH confirmed the optimum pH0 to be 7.0. Two types of recombinant strains overexpressing aspartokinase and dihydrodipicolinate synthase were constructed to verify the results obtained from metabolic sensitivity analysis.

Journal Article↗
PubMed2001

Energy model and metabolic flux analysis for autotrophic nitrifiers.

The behavior of pure cultures of nitrifying microorganisms under autotrophic growth operating conditions was investigated and the relations between their energy metabolism and their anabolism analyzed by means of metabolic network computation. The description of the metabolism of the nitrifiers is extended to their energy metabolism by introducing compartmentalization (cytoplasmic and periplasmic sides) and studying coupling between the electron transport chain and the proton gradient generation. The energy model of Nitrosomonas and Nitrobacter was developed based on the oxidoreduction reactions known to be involved. The electron transport chains and the associated proton translocation for these models are described. Several possible hypotheses are analyzed and discussed concerning the thermodynamic consistency of all the oxidoreduction reactions. For Nitrosomonas, the most delicate point is the second step of hydroxylamine oxidation. For Nitrobacter a new energy model is proposed in which NO plays an important role as node in the distribution of electrons from NO(2)(-) oxidation to the membrane electron transport chain. The compartmentalization enables us to consider a proton gradient dissipation flux as the expression of the overall energy loss in metabolic analysis (the so-called maintenance phenomena). The energy model (electron transport chain, proton gradient) is associated with an overall description of the metabolism of Nitrosomonas and Nitrobacter in terms of metabolic flux calculation. This representation demonstrates that a maintenance in nitrifiers expressed as a proton leak is no higher than for other aerobes. The yields calculated from the energy models integrated with the metabolic models of nitrifiers are consistent with the experimental yields in the literature.

Ammonia↗
PubMed2000

Metabolic flux analysis in Streptomyces coelicolor under various nutrient limitations.

Metabolic flux analysis was applied to Streptomyces coelicolor continuous culture data obtained under nitrogen, phosphate, sulfate, and potassium limitations. The metabolic reaction network involved more than 200 reactions describing the major pathways as well as the secondary metabolism for the production of actinorhodin and excretion of certain metabolites. Linear programming was used for the optimization of specific growth rates and energy requirements. Two types of specific growth rates, stoichiometric and theoretical, were defined, maximized, and compared in order to investigate the microbial potential. Potassium limitation led to the largest and nitrogen limitation to the smallest difference between the stoichiometric and theoretical specific growth rates. Although the value of the maximum theoretical specific growth rate was close to that of the experimental specific growth rate with potassium limitation, this difference was the largest in the case of nitrogen limitation. Energy requirements during different nutrient limitations were also investigated. The model indicated that although the highest actinorhodin production rate was with nitrogen limitation, this was accompanied with the undesired excretion of certain metabolites.

Culture Media↗
PubMed1999

Metabolic control analysis of insulin-stimulated glucose disposal in rat skeletal muscle.

Metabolic control analysis was used to calculate the distributed control of insulin-stimulated skeletal muscle glucose disposal in awake rats. Three separate hyperinsulinemic infusion protocols were performed: 1) protocol I was a euglycemic (approximately 6 mM)-hyperinsulinemic (10 mU. kg(-1). min(-1)) clamp, 2) protocol II was a hyperglycemic ( approximately 11 mM)-hyperinsulinemic (10 mU. kg(-1). min(-1)) clamp, and 3) protocol III was a euglycemic (approximately 6 mM)-hyperinsulinemic (10 mU. kg(-1). min(-1))-lipid/heparin (increased plasma free fatty acid) clamp. [1-13C]glucose was administered in all three protocols for a 3-h period, during which time [1-13C]glucose label incorporation into [1-13)]glycogen, [3-13C]lactate, and [3-13C]alanine was detected in the hindlimb of awake rats via 13C-NMR. Combined steady-state and kinetic data were used to calculate rates of glycogen synthesis and glycolysis. Additionally, glucose 6-phosphate (G-6-P) was measured in the hindlimb muscles with the use of in vivo 31P-NMR during the three infusion protocols. The clamped glucose infusion rates were 31.6 +/- 2.9, 49.7 +/- 1.0, and 24.0 +/- 1.5 mg. kg(-1). min(-1) at 120 min in protocols I-III, respectively. Rates of glycolysis were 62.1 +/- 10.3, 71.6 +/- 11.8, and 19.5 +/- 3.6 nmol. g(-1). min(-1) and rates of glycogen synthesis were 125 +/- 15, 224 +/- 23, and 104 +/- 17 nmol. g(-1). min(-1) in protocols I-III, respectively. Insulin-stimulated G-6-P concentrations were 217 +/- 8, 265 +/- 12, and 251 +/- 9 nmol/g in protocols I-III, respectively. A top-down approach to metabolic control analysis was used to calculate the distributed control among glucose transport/phosphorylation [GLUT-4/hexokinase (HK)], glycogen synthesis, and glycolysis from the metabolic flux and G-6-P data. The calculated values for the control coefficients (C) of these three metabolic steps (C(J)(GLUT-4/HK) = 0.55 +/- 0.10, C(J)(glycogen syn) = 0.30 +/- 0.06, and C(J)(glycolysis) = 0.15 +/- 0.02; where J is glucose disposal flux, and glycogen syn is glycogen synthesis) indicate that there is shared control of glucose disposal and that glucose transport/phosphorylation is responsible for the majority of control of insulin-stimulated glucose disposal in skeletal muscle.

Animals↗
PubMed2006

Metabolic pathway analysis for rational design of L-methionine production by Escherichia coli and Corynebacterium glutamicum.

Metabolic pathway analysis was carried out to predict the metabolic potential of Corynebacterium glutamicum and Escherichia coli for the production of L-methionine. Based on detailed stoichiometric models for these organisms, this allowed the calculation of the theoretically optimal methionine yield and related metabolic fluxes for various scenarios involving different mutants and process conditions. The theoretical optimal methionine yield on the substrates glucose, sulfate and ammonia for the wildtype of C. glutamicum is 0.49 (C-mol) (C-mol)(-1), whereas the E. coli wildtype exhibits an even higher potential of 0.52 (C-mol) (C-mol)(-1). Both strains showed completely different optimal flux distributions. C. glutamicum has a high flux through the pentose phosphate pathway (PPP), whereas the TCA cycle flux is very low. Additionally, it recruits a metabolic cycle, which involves 2-oxoglutarate and glutamate. In contrast, E. coli does minimize the flux through the PPP, and the flux through the TCA cycle is high. The improved potential of the E. coli wildtype is due to its membrane-bound transhydrogenase and its glycine cleavage system as shown by additional simulations with theoretical mutants. A key point for maximizing methionine yield is the choice of the sulfur source. Replacing sulfate by thiosulfate or sulfide increased the maximal theoretical yield in C. glutamicum up to 0.68 (C-mol) (C-mol)(-1). A further increase is possible by the application of additional C1 sources. The highest theoretical potential was obtained for C. glutamicum applying methanethiol as combined source for C1 carbon and sulfur (0.91 (C-mol) (C-mol)(-1)). Substrate requirement for maintenance purposes reduces theoretical methionine yields. In the case of sulfide used as sulfur source a maintenance requirement of 9.2 mmol ATP g(-1) h(-1), as was observed under stress conditions, would reduce the maximum theoretical yield from 67.8% to 47% at a methionine production rate of 0.65 mmol g(-1) h(-1). The enormous capability of both organisms encourages the development of biotechnological methionine production, whereby the use of metabolic pathway analysis, as shown, provides valuable advice for future strategies in strain and process improvement.

Bacterial Proteins↗
PubMed2002

Combinatorial complexity of pathway analysis in metabolic networks.

Elementary flux mode analysis is a promising approach for a pathway-oriented perspective of metabolic networks. However, in larger networks it is hampered by the combinatorial explosion of possible routes. In this work we give some estimations on the combinatorial complexity including theoretical upper bounds for the number of elementary flux modes in a network of a given size. In a case study, we computed the elementary modes in the central metabolism of Escherichia coli while utilizing four different substrates. Interestingly, although the number of modes occurring in this complex network can exceed half a million, it is still far below the upper bound. Hence, to a certain extent, pathway analysis of central catabolism is feasible to assess network properties such as flexibility and functionality.

Computer Simulation↗
PubMed2003

Bioinformatics research on inter-racial difference in drug metabolism I. Analysis on frequencies of mutant alleles and poor metabolizers on CYP2D6 and CYP2C19.

The enzyme activities of CYP2D6 and CYP2C19 show a genetic polymorphism, and the frequency of poor metabolizers (PMs) on these enzymes depends on races. In the present study, the frequencies of mutant alleles and PMs in each race were analyzed based on information from published studies, considering the genetic polymorphisms of CYP2D6 and CYP2C19 as the causal factors of racial and inter-individual differences in pharmacokinetics. As a result, it was shown that there were racial differences in the frequencies of each mutant allele and PMs. The frequencies of PMs on CYP2D6 are 1.9% of Asians and 7.7% of Caucasians, and those of PMs on CYP2C19 are 15.8% of Asians and 2.2% of Caucasians. Based on the results, it was suggested that there would be racial differences in the frequencies of PM subjects whose blood concentrations might be higher for drugs metabolized by these enzymes. Additionally, it was suggested that enzyme activities would vary according to the number of functional alleles even in subjects judged to be extensive metabolizers (EMs). In the bridging study, genetic information regarding CYP2D6 and CYP2C19 of the subjects will help extrapolate foreign clinical data to a domestic population.

Journal Article↗
PubMed2001

Role of stone analysis in metabolic evaluation and medical treatment of nephrolithiasis.

BACKGROUND AND PURPOSE: Comprehensive metabolic evaluation has become an important aspect of the management of recurrent nephrolithiasis, yet the role of stone analysis is often neglected or perhaps underestimated. The purpose of this study was to determine the role of stone analysis in medical decision making in patients with recurrent nephrolithiasis. MATERIALS AND METHODS: We evaluated 100 consecutive stone-forming patients who had undergone compositional stone analysis as well as comprehensive metabolic evaluation at our institution. An analysis of stone composition in relation to metabolic disturbances was performed. Patients were stratified into two groups: calcium and non-calcium stone formers. RESULTS: Patients having non-calcium stones were found to have a metabolic analysis reflecting specific metabolic disorders. Alternatively, patients with calcium stones were heterogeneous with regard to metabolic disorders, but there was a significant likelihood of renal tubular acidosis in those patients with calcium phosphate calculi. On the basis of these results, a simplified metabolic evaluation and nonselective medical therapy based on stone composition was formulated to facilitate assessment, management, and monitoring of stone disease. CONCLUSIONS: Compositional stone analysis should be an integral part of the metabolic evaluation of patients with nephrolithiasis. Moreover, stone analysis alone may provide guidance for therapeutic treatment and obviate a formal metabolic evaluation.

Acidosis, Renal Tubular↗
PubMed2005

Theoretical aspects of 13C metabolic flux analysis with sole quantification of carbon dioxide labeling.

The potential of using sole respirometric CO2 labeling measurement for 13C metabolic flux analysis was investigated by metabolic simulations. For this purpose a model was created, considering all CO2 forming and consuming reactions in the central catabolic and anabolic pathways. To facilitate the interpretation of the simulation results, the underlying metabolic network was parameterized by physiologically meaningful flux parameters such as flux partitioning ratios at metabolic branch points and reaction reversibilities. For real case flux scenarios of the industrial amino acid producer Corynebacterium glutamicum and different commercially available (13)C-labeled tracer substrates, observability and output sensitivity towards key flux parameters was investigated. Metabolic net fluxes in the central metabolism, involving, e.g. glycolysis, pentose phosphate pathway, tricarboxylic acid cycle, anaplerotic carboxylation, and glyoxylate pathway were found to be determinable by the respirometric approach using a combination of [1-13C] and [6-13C] glucose in two parallel studies. The reversibilities of bidirectional reactions influence the isotopic labeling of CO2 only to a negligible degree. On one hand, they therefore cannot be determined. On the other hand, their precise values are not required for the quantification of net fluxes. Computer-aided optimal experimental design was carried out to predict the quality of the information from the respirometric tracer experiments and identify suitable tracer substrates. A combination of [1-13C] and [6-13C] glucose in two parallel studies was found to yield a similar quality of information as compared to an approach with mass spectrometric labeling analysis of secreted products. The quality of information can be further increased by additional studies with [1,2-13C2] or [1,6-13C2] glucose. Respirometric tracer studies with sole labeling analysis of CO2 are therefore promising for 13C metabolic flux analysis.

Carbon Dioxide↗
PubMed2003

MRAD: Metabolic reaction analysis database--an entity-relationship approach.

The Metabolic Reaction Analysis Database (MRAD) is a relational database based on the Entity-Relationship (ER) model which combines information about organisms, biochemical pathways, reactions, enzymes, substrates, products and genes. It describes 244,596 genes in 79 organisms, 6,552 enzymes, and 3,552 reactions, 3,100 substrates, 2,866 products and 118 metabolic pathways. The MRAD graphical user interface allows for the identification of metabolic reactions which are similar and dissimilar in multiple organisms, reactions in a pathway which are missing in an organism and using any combination between one to six of the biological entities of organisms, genes, pathways, enzymes, substrates and products to determine metabolic reactions. MRAD provides a powerful and efficient tool for the construction of flux balance models for metabolic engineering applications.

Computer Graphics↗
PubMed2007

Modular metabolic control analysis of large responses.

Deciphering the laws that govern metabolic responses of complex systems is essential to understand physiological functioning, pathological conditions and the outcome of experimental manipulations of intact cells. To this aim, a theoretical and experimental sensitivity analysis, called modular metabolic control analysis (MMCA), was proposed. This field was previously developed under the assumptions of infinitesimal changes and/or proportionality between parameters and rates, which are usually not fulfilled in vivo. Here we develop a general MMCA for two modules, not relying on those assumptions. Control coefficients and elasticity coefficients for large changes are defined. These are subject to constraints: summation and response theorems, and relationships that allow calculating control from elasticity coefficients. We show how to determine the coefficients from top-down experiments, measuring the rates of the isolated modules as a function of the linking intermediate (there is no need to change parameters inside the modules). The novel formalism is applied to data of two experimental studies from the literature. In one of these, 40% increase in the activity of the supply module results in less than 4% increase in flux, while infinitesimal MMCA predicts more than 30% increase in flux. In addition, it is not possible to increase the flux by manipulating the activity of demand. The impossibility of increasing the flux by changing the activity of a single module is due to an abrupt decrease of the control of the modules when their corresponding activities are increased. In these cases, the infinitesimal approach can give highly erroneous predictions.

Algorithms↗