Dataset Information

Computational Modeling of Lipid Metabolism in Yeast.

ABSTRACT: Lipid metabolism is essential for all major cell functions and has recently gained increasing attention in research and health studies. However, mathematical modeling by means of classical approaches such as stoichiometric networks and ordinary differential equation systems has not yet provided satisfactory insights, due to the complexity of lipid metabolism characterized by many different species with only slight differences and by promiscuous multifunctional enzymes. Here, we present an object-oriented stochastic model approach as a way to cope with the complex lipid metabolic network. While all lipid species are treated objects in the model, they can be modified by the respective converting reactions based on reaction rules, a hybrid method that integrates benefits of agent-based and classical stochastic simulation. This approach allows to follow the dynamics of all lipid species with different fatty acids, different degrees of saturation and different headgroups over time and to analyze the effect of parameter changes, potential mutations in the catalyzing enzymes or provision of different precursors. Applied to yeast metabolism during one cell cycle period, we could analyze the distribution of all lipids to the various membranes in time-dependent manner. The presented approach allows to efficiently treat the complexity of cellular lipid metabolism and to derive conclusions on the time- and location-dependent distributions of lipid species and their properties such as saturation. It is widely applicable, easily extendable and will provide further insights in healthy and diseased states of cell metabolism.

SUBMITTER: Schutzhold V

PROVIDER: S-EPMC5037213 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Computational Modeling of Lipid Metabolism in Yeast.

Schützhold Vera V Hahn Jens J Tummler Katja K Klipp Edda E

Frontiers in molecular biosciences 20160927

Lipid metabolism is essential for all major cell functions and has recently gained increasing attention in research and health studies. However, mathematical modeling by means of classical approaches such as stoichiometric networks and ordinary differential equation systems has not yet provided satisfactory insights, due to the complexity of lipid metabolism characterized by many different species with only slight differences and by promiscuous multifunctional enzymes. Here, we present an object ...[more]

PMID: 27730126

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Project description:Non-alcohol fatty liver disease (NAFLD) is a common disorder that has increased in prevalence 20-fold over the last three decades. It covers a spectrum of conditions resulting from excess lipid accumulation in the liver without alcohol abuse. Among all the risk factors, over-consumption of fructose has been repeatedly reported in both clinical and experimental studies to be highly associated with the development of NAFLD. However, studying in vivo systems is complicated, time consuming and expensive. A detailed kinetic model of fructose metabolism was constructed to investigate the metabolic mechanisms whereby fructose consumption can induce dyslipidaemia associated with NAFLD and to explore whether the pathological conditions can be reversed during the early stages of disease. The model contains biochemical components and reactions identified from the literature, including ~120 parameters, 25 variables, and 25 first order differential equations. Three scenarios were presented to demonstrate the behavior of the model. Scenario one predicts the acute effects of a change in carbohydrate input in lipid profiles. The results present progressive triglyceride accumulations in the liver and plasma for three diets. The rate of accumulation was greater in the fructose diet than that of the mixed or glucose only models. Scenario two explores the variability of metabolic reaction rate within the general population. Sensitivity analysis reveals that hepatic triglyceride concentration is most sensitive to the rate constant of pyruvate kinase and fructokinase. Scenario three tests the effect of one specific inhibitor that might be potentially administered. The simulations of fructokinase suppression provide a good model for potentially reversing simple steatosis induced by high fructose consumption, which can be corroborated by experimental studies. The predictions in these three scenarios suggest that the model is robust and it has sufficient detail to present the kinetic relationship between fructose and lipid in the liver.

Dataset Information

Computational Modeling of Lipid Metabolism in Yeast.

Publications

Computational Modeling of Lipid Metabolism in Yeast.

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