Flux control coefficients determined by inhibitor titration: the design and analysis of experiments to minimize errors.
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ABSTRACT:
SUBMITTER: Small JR
PROVIDER: S-EPMC1137713 | biostudies-other | 1993 Dec
REPOSITORIES: biostudies-other
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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.
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Project description:Chromatographically pure porphyrin esters free from metalloporphyrins were titrated with Cu2+ to determine the molar amount of porphyrin present. The end point of the titration was defined by a t.l.c. method detecting traces of metal-free porphyrin ester in admxture to its copper complex. From spectrometric measurement at the Soret maximum and the molar amounts found by the titration, epsilonM was calculated for proto-, copro-, penta-, hexa- and hepta-carboxylic and uro-porphyrin permethyl esters. The values for uroporphyrin showed perfect agreement with those of previous workers, whereas those for coproporphyrin were about 5% lower and those for protoporphyrin more than 20% lower. The implications of the findings are discussed. Determinations of epsilonM of some higher esters (ethyl to pentyl) and some partial methyl esters with one carboxyl group free are also presented.
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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.
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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.
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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.
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Project description:Background¹³C-Metabolic flux analysis (¹³C-MFA) is a standard technique to probe cellular metabolism and elucidate in vivo metabolic fluxes. 13C-Tracer selection is an important step in conducting ¹³C-MFA, however, current methods are restricted to trial-and-error approaches, which commonly focus on an arbitrary subset of the tracer design space. To systematically probe the complete tracer design space, especially for complex systems such as mammalian cells, there is a pressing need for new rational approaches to identify optimal tracers.ResultsRecently, we introduced a new framework for optimal ¹³C-tracer design based on elementary metabolite units (EMU) decomposition, in which a measured metabolite is decomposed into a linear combination of so-called EMU basis vectors. In this contribution, we applied the EMU method to a realistic network model of mammalian metabolism with lactate as the measured metabolite. The method was used to select optimal tracers for two free fluxes in the system, the oxidative pentose phosphate pathway (oxPPP) flux and anaplerosis by pyruvate carboxylase (PC). Our approach was based on sensitivity analysis of EMU basis vector coefficients with respect to free fluxes. Through efficient grouping of coefficient sensitivities, simple tracer selection rules were derived for high-resolution quantification of the fluxes in the mammalian network model. The approach resulted in a significant reduction of the number of possible tracers and the feasible tracers were evaluated using numerical simulations. Two optimal, novel tracers were identified that have not been previously considered for ¹³C-MFA of mammalian cells, specifically [2,3,4,5,6-¹³C]glucose for elucidating oxPPP flux and [3,4-¹³C]glucose for elucidating PC flux. We demonstrate that ¹³C-glutamine tracers perform poorly in this system in comparison to the optimal glucose tracers.ConclusionsIn this work, we have demonstrated that optimal tracer design does not need to be a pure simulation-based trial-and-error process; rather, rational insights into tracer design can be gained through the application of the EMU basis vector methodology. Using this approach, rational labeling rules can be established a priori to guide the selection of optimal ¹³C-tracers for high-resolution flux elucidation in complex metabolic network models.
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Project description:Enzymatic processing of DNA underlies all DNA repair, yet inappropriate DNA processing must be avoided. In vertebrates, double-strand breaks are repaired predominantly by non-homologous end joining (NHEJ), which directly ligates DNA ends. NHEJ has the potential to be highly mutagenic because it uses DNA polymerases, nucleases, and other enzymes that modify incompatible DNA ends to allow their ligation. Using frog egg extracts that recapitulate NHEJ, we show that end processing requires the formation of a "short-range synaptic complex" in which DNA ends are closely aligned in a ligation-competent state. Furthermore, single-molecule imaging directly demonstrates that processing occurs within the short-range complex. This confinement of end processing to a ligation-competent complex ensures that DNA ends undergo ligation as soon as they become compatible, thereby minimizing mutagenesis. Our results illustrate how the coordination of enzymatic catalysis with higher-order structural organization of substrate maximizes the fidelity of DNA repair.
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Project description:Patients with an inborn error of metabolism (IEM) are deficient of an enzyme involved in metabolism, and as a consequence metabolism reprograms itself to reach a new steady state. This new steady state underlies the clinical phenotype associated with the deficiency. Hence, we need to know the flux of metabolites through the different metabolic pathways in this new steady state of the reprogrammed metabolism. Stable isotope technology is best suited to study this. In this review the progress made in characterizing the altered metabolism will be presented. Studies done in patients to estimate the residual flux through the metabolic pathway affected by enzyme deficiencies will be discussed. After this, studies done in model systems will be reviewed. The focus will be on glycogen storage disease type I, medium-chain acyl-CoA dehydrogenase deficiency, propionic and methylmalonic aciduria, urea cycle defects, phenylketonuria, and combined D,L-2-hydroxyglutaric aciduria. Finally, new developments are discussed, which allow the tracing of metabolic reprogramming in IEM on a genome-wide scale. In conclusion, the outlook for flux analysis of metabolic derangement in IEMs looks promising.
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Project description:Drug resistant tuberculosis (TB) infections are on the rise and antibiotics that inhibit Mycobacterium tuberculosis through a novel mechanism could be an important component of evolving TB therapy. Protein kinase A (PknA) and protein kinase B (PknB) are both essential serine-threonine kinases in M. tuberculosis. Given the extensive knowledge base in kinase inhibition, these enzymes present an interesting opportunity for antimycobacterial drug discovery. This study focused on targeting both PknA and PknB while improving the selectivity window over related mammalian kinases. Compounds achieved potent inhibition (Ki ? 5 nM) of both PknA and PknB. A binding pocket unique to mycobacterial kinases was identified. Substitutions that filled this pocket resulted in a 100-fold differential against a broad selection of mammalian kinases. Reducing lipophilicity improved antimycobacterial activity with the most potent compounds achieving minimum inhibitory concentrations ranging from 3 to 5 ?M (1-2 ?g/mL) against the H37Ra isolate of M. tuberculosis.
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Project description:BackgroundWe developed a novel approach to minimize batch effects when assigning samples to batches. Our algorithm selects a batch allocation, among all possible ways of assigning samples to batches, that minimizes differences in average propensity score between batches. This strategy was compared to randomization and stratified randomization in a case-control study (30 per group) with a covariate (case vs control, represented as β1, set to be null) and two biologically relevant confounding variables (age, represented as β2, and hemoglobin A1c (HbA1c), represented as β3). Gene expression values were obtained from a publicly available dataset of expression data obtained from pancreas islet cells. Batch effects were simulated as twice the median biological variation across the gene expression dataset and were added to the publicly available dataset to simulate a batch effect condition. Bias was calculated as the absolute difference between observed betas under the batch allocation strategies and the true beta (no batch effects). Bias was also evaluated after adjustment for batch effects using ComBat as well as a linear regression model. In order to understand performance of our optimal allocation strategy under the alternative hypothesis, we also evaluated bias at a single gene associated with both age and HbA1c levels in the 'true' dataset (CAPN13 gene).ResultsPre-batch correction, under the null hypothesis (β1), maximum absolute bias and root mean square (RMS) of maximum absolute bias, were minimized using the optimal allocation strategy. Under the alternative hypothesis (β2 and β3 for the CAPN13 gene), maximum absolute bias and RMS of maximum absolute bias were also consistently lower using the optimal allocation strategy. ComBat and the regression batch adjustment methods performed well as the bias estimates moved towards the true values in all conditions under both the null and alternative hypotheses. Although the differences between methods were less pronounced following batch correction, estimates of bias (average and RMS) were consistently lower using the optimal allocation strategy under both the null and alternative hypotheses.ConclusionsOur algorithm provides an extremely flexible and effective method for assigning samples to batches by exploiting knowledge of covariates prior to sample allocation.
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