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Metabolic Control Analysis (metabolic + control_analysis)

Distribution by Scientific Domains

Life Sciences	62%

Selected Abstracts

Metabolic Control Analysis of Monoclonal Antibody Synthesis

BIOTECHNOLOGY PROGRESS, Issue 2 2001
Ramon Gonzalez
A general route for protein synthesis in eukaryotic cells has been proposed and applied to monoclonal antibody (MAb) synthesis. It takes into account transcription of the gene, binding of ribosomes to mRNA, and polypeptide elongation including binding to SRP (signal recognition particles) and SRP-receptor, competing translocation, folding and glycosylation, assembly of the heavy and light chains in a tetrameric protein and Golgi processing and secretion. A comprehensive model was built on the basis of the proposed pathway. The model takes into account the mechanism of each step. Metabolic control analysis (MCA) principles were applied to the general pathway using the proposed model, and control coefficients were calculated. The results show a shared flux control (of both pathway flux and flux ratio at the branch) among different steps, i.e., transcription, folding, glycosylation, translocation and building blocks synthesis. The steps sharing the control depend on the concentration of building blocks, pathway flux and levels of OST (oligosacharyl transferase), BiP (heavy chain binding protein) and PDI (protein disulfide isomerase). Model predictions compare well with experimental data for MAb synthesis, explaining the control structure of the route and the heterogeneity of the product and also addressing future targets for improvement of the production rate of MAbs. [source]

Metabolic control analysis of an enzymatic biofuel cell

BIOTECHNOLOGY & BIOENGINEERING, Issue 6 2009
Doris J. Glykys
Abstract Metabolic control analysis (MCA) is an analytical technique that aims to quantify the distribution of control that enzymes exhibit over the steady-state fluxes through a metabolic network. In an enzymatic biofuel cell, the flux of interest is the electrical current generated by the system. Regardless of transport limitations and other constraints, kinetic limitations can become potential bottlenecks in the operation of a biofuel cell. We have used an indirect approach to MCA to investigate a common osmium-mediated glucose oxidase/laccase enzymatic biofuel cell. The results of the analysis show that the control of the electron flux strongly depends on the total mediator concentrations and the extent of polarization of the individual electrodes. The effect of varying oxygen concentrations is also examined, as oxygen is required for the cathode, but it participates in a non-productive reaction at the anode. Under normal operating conditions the electrodes will be highly polarized and will both contain high mediator concentrations. This configuration will result in a dominant FCC at the anode, and the conditions that are needed for balanced flux control between the anode and cathode are explored. As increasingly complex bioelectrocatalytic systems and architectures are envisioned, MCA will be a valuable framework to facilitate their design and subsequent operation. Biotechnol. Bioeng. 2009;102: 1624,1635. © 2008 Wiley Periodicals, Inc. [source]

Metabolic Control Analysis of Monoclonal Antibody Synthesis

Experimental validation of metabolic pathway modeling

FEBS JOURNAL, Issue 13 2008
An illustration with glycolytic segments from Entamoeba histolytica
In the search for new drug targets in the human parasite Entamoeba histolytica, metabolic control analysis was applied to determine, experimentally, flux control distribution of amebal glycolysis. The first (hexokinase, hexose-6-phosphate isomerase, pyrophosphate-dependent phosphofructokinase (PPi -PFK), aldolase and triose-phosphate isomerase) and final (3-phosphoglycerate mutase, enolase and pyruvate phosphate dikinase) glycolytic segments were reconstituted in vitro with recombinant enzymes under near-physiological conditions of pH, temperature and enzyme proportion. Flux control was determined by titrating flux with each enzyme component. In parallel, both glycolytic segments were also modeled by using the rate equations and kinetic parameters previously determined. Because the flux control distribution predicted by modeling and that determined by reconstitution were not similar, kinetic interactions among all the reconstituted components were experimentally revised to unravel the causes of the discrepancy. For the final segment, it was found that 3-phosphoglycerate was a weakly competitive inhibitor of enolase, whereas PPi was a moderate inhibitor of 3-phosphoglycerate mutase and enolase. For the first segment, PPi was both a strong inhibitor of aldolase and a nonessential mixed-type activator of amebal hexokinase; in addition, lower Vmax values for hexose-6-phosphate isomerase, PPi -PFK and aldolase were induced by PPi or ATP inhibition. It should be noted that PPi and other metabolites were absent from the 3-phosphoglycerate mutase and enolase or aldolase and hexokinase kinetics experiments, but present in reconstitution experiments. Only by incorporating these modifications in the rate equations, modeling predicted values of flux control distribution, flux rate and metabolite concentrations similar to those experimentally determined. The experimentally validated segment models allowed ,in silico experimentation' to be carried out, which is not easy to achieve in in vivo or in vitro systems. The results predicted a nonsignificant effect on flux rate and flux control distribution by adding parallel routes (pyruvate kinase for the final segment and ATP-dependent PFK for the first segment), because of the much lower activity of these enzymes in the ameba. Furthermore, modeling predicted full flux-control by 3-phosphoglycerate mutase and hexokinase, in the presence of low physiological substrate and product concentrations. It is concluded that the combination of in vitro pathway reconstitution with modeling and enzyme kinetics experimentation permits a more comprehensive understanding of the pathway behavior and control properties. [source]

Expression of the pyrG gene determines the pool sizes of CTP and dCTP in Lactococcus lactis

FEBS JOURNAL, Issue 12 2004
Casper M. Jørgensen
The pyrG gene from Lactococcus lactis encodes CTP synthase (EC 6.4.3.2), an enzyme converting UTP to CTP. A series of strains were constructed with different levels of pyrG expression by insertion of synthetic constitutive promoters with different strengths in front of pyrG. These strains expressed pyrG levels in a range from 3 to 665% relative to the wild-type expression level. Decreasing the level of CTP synthase to 43% had no effect on the growth rate, showing that the capacity of CTP synthase in the cell is in excess in a wild-type strain. We then studied how pyrG expression affected the intracellular pool sizes of nucleotides and the correlation between pyrG expression and nucleotide pool sizes was quantified using metabolic control analysis in terms of inherent control coefficients. At the wild-type expression level, CTP synthase had full control of the CTP concentration with a concentration control coefficient close to one and a negative concentration control coefficient of ,0.28 for the UTP concentration. Additionally, a concentration control coefficient of 0.49 was calculated for the dCTP concentration. Implications for the homeostasis of nucleotide pools are discussed. [source]

The effect of thiamine supplementation on tumour proliferation

FEBS JOURNAL, Issue 15 2001
A metabolic control analysis study
Thiamine deficiency frequently occurs in patients with advanced cancer and therefore thiamine supplementation is used as nutritional support. Thiamine (vitamin B1) is metabolized to thiamine pyrophosphate, the cofactor of transketolase, which is involved in ribose synthesis, necessary for cell replication. Thus, it is important to determine whether the benefits of thiamine supplementation outweigh the risks of tumor proliferation. Using oxythiamine (an irreversible inhibitor of transketolase) and metabolic control analysis (MCA) methods, we measured an in vivo tumour growth control coefficient of 0.9 for the thiamine-transketolase complex in mice with Ehrlich's ascites tumour. Thus, transketolase enzyme and thiamine clearly determine cell proliferation in the Ehrlich's ascites tumour model. This high control coefficient allows us to predict that in advanced tumours, which are commonly thiamine deficient, supplementation of thiamine could significantly increase tumour growth through transketolase activation. The effect of thiamine supplementation on tumour proliferation was demonstrated by in vivo experiments in mice with the ascites tumour. Thiamine supplementation in doses between 12.5 and 250 times the recommended dietary allowance (RDA) for mice were administered starting on day four of tumour inoculation. We observed a high stimulatory effect on tumour growth of 164% compared to controls at a thiamine dose of 25 times the RDA. This growth stimulatory effect was predicted on the basis of correction of the pre-existing level of thiamine deficiency (42%), as assayed by the cofactor/enzyme ratio. Interestingly, at very high overdoses of thiamine, ,,2500 times the RDA, thiamine supplementation had the opposite effect and caused 10% inhibition of tumour growth. This effect was heightened, resulting in a 36% decrease, when thiamine supplementation was administered from the 7th day prior to tumour inoculation. Our results show that thiamine supplementation sufficient to correct existing thiamine deficiency stimulates tumour proliferation as predicted by MCA. The tumour inhibitory effect at high doses of thiamine is unexplained and merits further study. [source]

DATE analysis: A general theory of biological change applied to microarray data

BIOTECHNOLOGY PROGRESS, Issue 5 2009
David Rasnick
Abstract In contrast to conventional data mining, which searches for specific subsets of genes (extensive variables) to correlate with specific phenotypes, DATE analysis correlates intensive state variables calculated from the same datasets. At the heart of DATE analysis are two biological equations of state not dependent on genetic pathways. This result distinguishes DATE analysis from other bioinformatics approaches. The dimensionless state variable F quantifies the relative overall cellular activity of test cells compared to well-chosen reference cells. The variable ,i is the fold-change in the expression of the ith gene of test cells relative to reference. It is the fraction , of the genome undergoing differential expression,not the magnitude ,,that controls biological change. The state variable , is equivalent to the control strength of metabolic control analysis. For tractability, DATE analysis assumes a linear system of enzyme-connected networks and exploits the small average contribution of each cellular component. This approach was validated by reproducible values of the state variables F, RNA index, and , calculated from random subsets of transcript microarray data. Using published microarray data, F, RNA index, and , were correlated with: (1) the blood-feeding cycle of the malaria parasite, (2) embryonic development of the fruit fly, (3) temperature adaptation of Killifish, (4) exponential growth of cultured S. pneumoniae, and (5) human cancers. DATE analysis was applied to aCGH data from the great apes. A good example of the power of DATE analysis is its application to genomically unstable cancers, which have been refractory to data mining strategies. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009 [source]