Metabolic control analysis using transient metabolite concentrations. Determination of metabolite concentration control coefficients.
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ABSTRACT:
SUBMITTER: Delgado J
PROVIDER: S-EPMC1132889 | biostudies-other | 1992 Aug
REPOSITORIES: biostudies-other
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Project description:Flux Control Coefficients have been used in the analysis of metabolic regulation for quantifying the effect of an enzyme on the overall steady-state flux. However, the experimental determination of these coefficients is very time-consuming, involving either determining the individual enzyme kinetics or perturbing the enzyme activity by genetic or other means. We developed a methodology that enables the determination of the Flux Control Coefficients from transient metabolite concentrations without knowing kinetic parameters. The transient states can be generated by changing the incubation conditions or adding the initial substrate. This approach is suitable for investigating metabolic regulation in vivo or multiple enzyme systems in vitro. It is particularly helpful if used in conjunction with n.m.r. measurements. The approach is based on a relationship between transient metabolite concentrations and the Flux Control Coefficients. The methodology has been improved from our previous results, and it is illustrated by three examples with simple pathway topologies.
| S-EPMC1130875 | biostudies-other
Project description:The influence of experimental errors on the determination of flux control coefficients from transient metabolite concentrations with the method proposed by Delgado and Liao [(1992) Biochem. J. 282, 919-927] has been investigated by using Monte Carlo simulations. The method requires least-squares fitting of the transient metabolite concentrations. Three different fitting methods have been evaluated. Simulated metabolite concentrations of a fictive metabolic pathway were scattered randomly, emulating experimental errors, before performing the fits. This was repeated a large number of times; the mean values and standard deviations of the resulting control coefficients are reported. The results show that the proposed method for determining control coefficients is too sensitive to experimental errors to be practicable, with theoretically justified fitting methods. This is in particular due to the high degree of correlation between the concentrations. An alternative ad hoc fitting method produced biased mean values of the estimates of the control coefficients, but with remarkably low standard deviations.
| S-EPMC1216970 | biostudies-other
Project description:The control structure of a metabolic system can in principle be determined without the need for purification of the component enzymes and study of their kinetic properties, provided that their activities can be perturbed by amounts sufficient to produce measurable changes in the steady-state variables, i.e. the fluxes through the system and the concentrations of the intermediates. Each perturbation is characterized in terms of the co-response coefficients of all pairs of variables, i.e. the slopes of the lines produced when the logarithm of one variable is plotted against the logarithm of another, both varying in response to the same perturbation. If all the co-response coefficients are assembled into a matrix, the inverse of this matrix can be transformed into a matrix containing all the component elasticities, which can be inverted to provide the complete matrix of control coefficients. In a simple three-enzyme pathway studied, the analysis proves not to require unrealistically high accuracy in the original co-response measurements: even with errors with standard deviation +/- 5.77 degrees in the angles to the horizontal of the lines in the co-response plots (equivalent at best to errors of +/- 20% in the corresponding co-response coefficients), the final control coefficient matrix may be adequate for assessing the control structure of the system. Examination of literature data from studies of mitochondrial respiration and of gluconeogenesis indicates that considerably higher precision than this is achievable.
| S-EPMC1137949 | biostudies-other
Project description:A computer program (MetaCon) is described for the evaluation of flux control, concentration control and branch-point distribution control coefficients of a metabolic pathway. Requiring only the reaction scheme as input, the program produces algebraic expressions for the control coefficients in terms of elasticity coefficients, metabolite concentrations and pathway fluxes. Any of these variables can be substituted by numeric or simple algebraic expressions; the expressions will then be automatically rearranged in terms of the remaining unknown variables. When all variables have been substituted, numeric values will be obtained for the control coefficients. The program is a computerized implementation of the matrix method for the determination of control coefficients. The features of MetaCon are compared with those of other programs available to workers in Metabolic Control Analysis. Potential benefits of, and methods of using, MetaCon are discussed. The mathematical background and validity of the matrix method rules are discussed, and the algorithm used by MetaCon is described. The matrix method is shown to be a specific case of a previously described general formalism for calculating control coefficients.
| S-EPMC1134216 | biostudies-other
Project description:A computer program is described that derives the Flux and Concentration Control Coefficients for linear and branched metabolic pathways. The program prompts the user to enter a concise description of the metabolic pathway. From this description, the program constructs the appropriate equations in matrix form. The algorithm employed to obtain the symbolic determinants is described, and this algorithm also provides a convenient method for manual derivation of the Control Coefficients. The computer-based method will accommodate unlimited feed-forward and feed-backward loops and a maximum of two branches from each metabolite on the main pathway. The utility of the method is illustrated with a linear path with feed-forward and feed-backward loops, and with a substrate cycle as an example of a path with two branches.
| S-EPMC1151482 | biostudies-other
Project description:BackgroundIn recent years, constrained optimization - usually referred to as flux balance analysis (FBA) - has become a widely applied method for the computation of stationary fluxes in large-scale metabolic networks. The striking advantage of FBA as compared to kinetic modeling is that it basically requires only knowledge of the stoichiometry of the network. On the other hand, results of FBA are to a large degree hypothetical because the method relies on plausible but hardly provable optimality principles that are thought to govern metabolic flux distributions.ResultsTo augment the reliability of FBA-based flux calculations we propose an additional side constraint which assures thermodynamic realizability, i.e. that the flux directions are consistent with the corresponding changes of Gibb's free energies. The latter depend on metabolite levels for which plausible ranges can be inferred from experimental data. Computationally, our method results in the solution of a mixed integer linear optimization problem with quadratic scoring function. An optimal flux distribution together with a metabolite profile is determined which assures thermodynamic realizability with minimal deviations of metabolite levels from their expected values. We applied our novel approach to two exemplary metabolic networks of different complexity, the metabolic core network of erythrocytes (30 reactions) and the metabolic network iJR904 of Escherichia coli (931 reactions). Our calculations show that increasing network complexity entails increasing sensitivity of predicted flux distributions to variations of standard Gibb's free energy changes and metabolite concentration ranges. We demonstrate the usefulness of our method for assessing critical concentrations of external metabolites preventing attainment of a metabolic steady state.ConclusionOur method incorporates the thermodynamic link between flux directions and metabolite concentrations into a practical computational algorithm. The weakness of conventional FBA to rely on intuitive assumptions about the reversibility of biochemical reactions is overcome. This enables the computation of reliable flux distributions even under extreme conditions of the network (e.g. enzyme inhibition, depletion of substrates or accumulation of end products) where metabolite concentrations may be drastically altered.
| S-EPMC1903363 | biostudies-literature
Project description:Recent development of high-throughput analytical techniques has made it possible to qualitatively identify a number of metabolites simultaneously. Correlation and multivariate analyses such as principal component analysis have been widely used to analyse those data and evaluate correlations among the metabolic profiles. However, these analyses cannot simultaneously carry out identification of metabolic reaction networks and prediction of dynamic behaviour of metabolites in the networks. The present study, therefore, proposes a new approach consisting of a combination of statistical technique and mathematical modelling approach to identify and predict a probable metabolic reaction network from time-series data of metabolite concentrations and simultaneously construct its mathematical model. Firstly, regression functions are fitted to experimental data by the locally estimated scatter plot smoothing method. Secondly, the fitted result is analysed by the bivariate Granger causality test to determine which metabolites cause the change in other metabolite concentrations and remove less related metabolites. Thirdly, S-system equations are formed by using the remaining metabolites within the framework of biochemical systems theory. Finally, parameters including rate constants and kinetic orders are estimated by the Levenberg-Marquardt algorithm. The estimation is iterated by setting insignificant kinetic orders at zero, i.e., removing insignificant metabolites. Consequently, a reaction network structure is identified and its mathematical model is obtained. Our approach is validated using a generic inhibition and activation model and its practical application is tested using a simplified model of the glycolysis of Lactococcus lactis MG1363, for which actual time-series data of metabolite concentrations are available. The results indicate the usefulness of our approach and suggest a probable pathway for the production of lactate and acetate. The results also indicate that the approach pinpoints a probable strong inhibition of lactate on the glycolysis pathway.
| S-EPMC3542379 | biostudies-literature
Project description:Within the premises of the flux-oriented theory of Crabtree & Newsholme [(1987) Biochem. J. 247, 113-120], I have used a graph-theoretic approach for calculating the Control Coefficients of metabolic pathways. It is shown that a directed graph representing the control structure of a metabolic pathway can be constructed in a heuristic manner directly from the reaction diagram of the pathway, without the necessity of writing down the governing equations for the Control Coefficients. The Control Coefficients are derived from an analysis of the topology of the directed graph. The graph-theoretic approach also provides a visual framework for analysing the functional relationships of the individual enzymes. The control structures of the following pathways are examined here: (a) a simple unbranched pathway with four enzymes, (b) a simple branched pathway with three enzymes, and (c) a branched pathway with both carbon and energy (ATP) fluxes.
| S-EPMC1151546 | biostudies-other
Project description:BackgroundA considerable challenge in quantification of the antimalarial piperaquine in plasma is carryover of analyte signal between assays. Current intensive pharmacokinetic studies often rely on the merging of venous and capillary sampling. Drug levels in capillary plasma may be different from those in venous plasma, Thus, correlation between capillary and venous drug levels needs to be established.MethodsLiquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was used to develop the method. Piperaquine was measured in 205 pairs of capillary and venous plasma samples collected simultaneously at ≥24hr post dose in children, pregnant women and non-pregnant women receiving dihydroartemisinin-piperaquine as malaria chemoprevention. Standard three-dose regimen over three days applied to all participants with three 40mg dihydroartemisinin/320mg PQ tablets per dose for adults and weight-based dose for children. Correlation analysis was performed using the program Stata® SE12.1. Linear regression models were built using concentrations or logarithm transformed concentrations and the final models were selected based on maximal coefficient of determination (R2) and visual check.ResultsAn LC-MS/MS method was developed and validated, utilizing methanol as a protein precipitation agent, a Gemini C18 column (50x2.0mm, 5μm) eluted with basic mobile phase solvents (ammonium hydroxide as the additive), and ESI+ as the ion source. This method had a calibration range of 10-1000 ng/mL and carryover was negligible. Correlation analysis revealed a linear relationship: Ccap = 1.04×Cven+4.20 (R2 = 0.832) without transformation of data, and lnCcap = 1.01×lnCven+0.0125, (R2 = 0.945) with natural logarithm transformation. The mean ratio (±SD) of Ccap/Cven was 1.13±0.42, and median (IQR) was 1.08 (0.917, 1.33).ConclusionsCapillary and venous plasma PQ measures are nearly identical overall, but not readily exchangeable due to large variation. Further correlation study accounting for disposition phases may be necessary.
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