Dataset Information

Metabolic adaptation in phosphorylase kinase deficiency. Changes in metabolite concentrations during tetanic stimulation of mouse leg muscles.

ABSTRACT: 1. Glycogen, nucleotides and glycolytic intermediates and products were measured before and during tetanus in the hamstrings-muscle groups of normal (C3H) and phosphorylase kinase-deficient (ICR/IAn) mice. 2. Phosphorylase kinase-deficient muscles contained 3-4-fold more glycogen and sustained a larger (approx. 2-fold), more rapid (11 +/- 2 ng/s faster) and more prolonged glycogenolysis during 120s tetanus despite their lack of phosphorylase a. 3. No significant change in total adenine nucleotide contents occurred during tetanus in either strain, but there was a 60-100-fold rise in IMP concentration to approx. 2mM in both strains. The initial rate of IMP formation was 6-fold more rapid (112 nmol/s per g) in phosphorylase kinase-deficient muscle. 4. Adenylosuccinate content rose to 36 nmol/g in phosphorylase kinase-deficient muscle and to 9 nmol/g in normal muscle at 45s tetanus, but then fell. 5. In phosphorylase kinase-deficient muscle, glucose 6-phosphate, a powerful phosphorylase inhibitor, was 56% of that in normal muscle. 6. The mass-action ratio of the phosphoglucomutase-catalysed reaction [glucose 6-phosphate]/[glucose 1-phosphate] was markedly lower than Keq. (approx. 17) in relaxed muscle of both strains (approx. 5-7), but rose significantly during tetanus to the value for Keq. 7. The data for IMP satisfy the criteria put forward by Rahim, Perrett & Griffiths [(1976) FEBS Lett. 69, 203-206] for a nucleotide activator of phosphorylase b: it should be present at a higher concentration in phosphorylase kinase-deficient muscle, its concentration should rise during muscle work, and it should attain a concentration comparable with its activation constant for phosphorylase b.

SUBMITTER: Rahim ZH

PROVIDER: S-EPMC1161535 | biostudies-other | 1980 Jan

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

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.

Dataset Information

Metabolic adaptation in phosphorylase kinase deficiency. Changes in metabolite concentrations during tetanic stimulation of mouse leg muscles.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets