Computational Modeling of Lipid Metabolism in Yeast

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 sati...

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Main Authors: Vera Schützhold, Jens Hahn, Katja Tummler, Edda Klipp
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-09-01
Series:Frontiers in Molecular Biosciences
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fmolb.2016.00057/full
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spelling doaj-3df563977ccd4052ace3d30b3248a21a2020-11-25T01:08:30ZengFrontiers Media S.A.Frontiers in Molecular Biosciences2296-889X2016-09-01310.3389/fmolb.2016.00057206819Computational Modeling of Lipid Metabolism in YeastVera Schützhold0Jens Hahn1Katja Tummler2Edda Klipp3Humboldt-Universität zu BerlinHumboldt-Universität zu BerlinHumboldt-Universität zu BerlinHumboldt-Universität zu BerlinLipid 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 a 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.http://journal.frontiersin.org/Journal/10.3389/fmolb.2016.00057/fullSaccharomyces cerevisiaelipidomicsGillespie AlgorithmFatty acid saturationspatial distribution of lipids
collection DOAJ
language English
format Article
sources DOAJ
author Vera Schützhold
Jens Hahn
Katja Tummler
Edda Klipp
spellingShingle Vera Schützhold
Jens Hahn
Katja Tummler
Edda Klipp
Computational Modeling of Lipid Metabolism in Yeast
Frontiers in Molecular Biosciences
Saccharomyces cerevisiae
lipidomics
Gillespie Algorithm
Fatty acid saturation
spatial distribution of lipids
author_facet Vera Schützhold
Jens Hahn
Katja Tummler
Edda Klipp
author_sort Vera Schützhold
title Computational Modeling of Lipid Metabolism in Yeast
title_short Computational Modeling of Lipid Metabolism in Yeast
title_full Computational Modeling of Lipid Metabolism in Yeast
title_fullStr Computational Modeling of Lipid Metabolism in Yeast
title_full_unstemmed Computational Modeling of Lipid Metabolism in Yeast
title_sort computational modeling of lipid metabolism in yeast
publisher Frontiers Media S.A.
series Frontiers in Molecular Biosciences
issn 2296-889X
publishDate 2016-09-01
description 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 a 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.
topic Saccharomyces cerevisiae
lipidomics
Gillespie Algorithm
Fatty acid saturation
spatial distribution of lipids
url http://journal.frontiersin.org/Journal/10.3389/fmolb.2016.00057/full
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