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.
Highlights
The Importance of Lipid Metabolism in Health and DiseaseLipids are crucial players in a wide range of cellular processes
To solve the problem of combinatorial expansion and to allow time-dependent simulation of lipid metabolism in normal and perturbed states, we developed a hybrid object-oriented approach that combines aspects from agent-based modeling and generic stochastic simulation via the Gillespie algorithm
Due to the object nature of the substrates, the reactions can be promiscuous, choosing with defined probabilities from a set of allowed substrates. This drastically reduces the complexity of the model setup, as we do not need to define all possible combinations of substrates and enzymes as individual reactions
Summary
Lipids are crucial players in a wide range of cellular processes. Their production is required for cell cycle progression and cell division. Lipids are important mediators in signaling pathways, components of essential cofactors, building blocks of lipoproteins and glycerolipids and can be used to store and mobilize excess energy. In those contexts lipids execute structural as well as functional roles: By building membranes, they can create isolated reaction environments. Lipids can be direct mediators of cellular signaling, for example in the regulation of endocytosis, ubiquitin dependent proteolysis or cell cycle control (Nielsen, 2009)
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