Kinetic models of glycogen metabolism in normal rat liver, Morris hepatoma 7787 and host liver

A Standardized Brain Molecular Atlas: A Resource for Systems Modeling and Simulation

Accurate molecular concentrations are essential for reliable analyses of biochemical networks and the creation of predictive models for molecular and systems biology, yet protein and metabolite concentrations used in such models are often poorly constrained or irreproducible. Challenges of using data from different sources include conflicts in nomenclature and units, as well as discrepancies in experimental procedures, data processing and implementation of the model. To obtain a consistent estimate of protein and metabolite levels, we integrated and normalized data from a large variety of sources to calculate Adjusted Molecular Concentrations. We found a high degree of reproducibility and consistency of many molecular species across brain regions and cell types, consistent with tight homeostatic regulation. We demonstrated the value of this normalization with differential protein expression analyses related to neurodegenerative diseases, brain regions and cell types. We also used the results in proof-of-concept simulations of brain energy metabolism. The standardized Brain Molecular Atlas overcomes the obstacles of missing or inconsistent data to support systems biology research and is provided as a resource for biomolecular modeling.

A minimal model of liver glycogen metabolism; feasibility for predicting flux rates

A minimal model of glycogen metabolism can allow the estimation of the flux rates in the glycogen pathway from the time course of the intermediates in the pathway, measured during substrate administration and hormonal stimulation. The comprehensive model of El-Refai & Bergman (Am. J. Physiol. 231, 1608, 1976) consisting of six compartments and 26 non-estimable parameters has successfully accounted for the responses of hepatic glycogenic intermediates in response to a glucose load in hepatocytes (Katz et al., J. biol. Chem. 253, 4530, 1978), in perfused liver (Nordlie et al., J. biol. Chem. 255, 1834, 1980) and during refeeding in vivo (Van DeWerve & Jeanrenaud, Am. J. Physiol. 247, E271, 1984). The comprehensive model is here reduced to a minimal model, consisting of five compartments representing extracellular and intracellular glucose, glucose-phosphate, uridine diphosphate glucose (UDPG), glycogen, and five parameters estimated from the hepatic response to a given stimulus. Estimation of these parameters requires the measurement of the net hepatic glucose balance, the net gluconeogenic flux, and the time course of glycogenic intermediates responding to a hormone or substrate stimulus. The hepatic glycogenolytic response predicted by the comprehensive model in response to an increase in glucagon is closely fitted by the minimal model. When Gaussian distributed random error was added, 0-5% SD in the glucose and glycogen compartments and 0-10% SD in the glucose-phosphate and UDPG compartments, the hepatic response predicted by the minimal model was virtually free of the added error, and the model parameters were found to be within 30% of their true values. When the minimal model was used to interpret the experimental response to an increase in glucose concentration it predicted that: (1) glucokinase can phosphorylate glucose at rates similar to maximal rates of net glycogen synthesis; (2) futile cycling at the glycogen/glucose-1-phosphate level can limit glycogen synthesis; and (3) glucose-6-phosphatase inhibition by glucose has a significant role in net glycogen synthesis.