Literature DB >> 10935932

Metabolic modeling of Saccharomyces cerevisiae using the optimal control of homeostasis: a cybernetic model definition.

M L Giuseppin1, N A van Riel.   

Abstract

A model is presented to describe the observed behavior of microorganisms that aim at metabolic homeostasis while growing and adapting to their environment in an optimal way. The cellular metabolism is seen as a network with a multiple controller system with both feedback and feedforward control, i.e., a model based on a dynamic optimal metabolic control. The dynamic network consists of aggregated pathways, each having a control setpoint for the metabolic states at a given growth rate. This set of strategies of the cell forms a true cybernetic model with a minimal number of assumptions. The cellular strategies and constraints were derived from metabolic flux analysis using an identified, biochemically relevant, stoichiometry matrix derived from experimental data on the cellular composition of continuous cultures of Saccharomyces cerevisiae. Based on these data a cybernetic model was developed to study its dynamic behavior. The growth rate of the cell is determined by the structural compounds and fluxes of compounds related to central metabolism. In contrast to many other cybernetic models, the minimal model does not consist of any assumed internal kinetic parameters or interactions. This necessitates the use of a stepwise integration with an optimization of the fluxes at every time interval. Some examples of the behavior of this model are given with respect to steady states and pulse responses. This model is very suitable for describing semiquantitatively dynamics of global cellular metabolism and may form a useful framework for including structured and more detailed kinetic models.

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Year:  2000        PMID: 10935932     DOI: 10.1006/mben.1999.0134

Source DB:  PubMed          Journal:  Metab Eng        ISSN: 1096-7176            Impact factor:   9.783


  5 in total

1.  Kinetic and chemical mechanisms of homocitrate synthase from Thermus thermophilus.

Authors:  Vidya Prasanna Kumar; Ann H West; Paul F Cook
Journal:  J Biol Chem       Date:  2011-07-06       Impact factor: 5.157

2.  Dynamic flux balance analysis of diauxic growth in Escherichia coli.

Authors:  Radhakrishnan Mahadevan; Jeremy S Edwards; Francis J Doyle
Journal:  Biophys J       Date:  2002-09       Impact factor: 4.033

3.  DMPy: a Python package for automated mathematical model construction of large-scale metabolic systems.

Authors:  Robert W Smith; Rik P van Rosmalen; Vitor A P Martins Dos Santos; Christian Fleck
Journal:  BMC Syst Biol       Date:  2018-06-19

Review 4.  Metabolic Modelling as a Framework for Metabolomics Data Integration and Analysis.

Authors:  Svetlana Volkova; Marta R A Matos; Matthias Mattanovich; Igor Marín de Mas
Journal:  Metabolites       Date:  2020-07-24

5.  A novel process-based model of microbial growth: self-inhibition in Saccharomyces cerevisiae aerobic fed-batch cultures.

Authors:  Stefano Mazzoleni; Carmine Landi; Fabrizio Cartenì; Elisabetta de Alteriis; Francesco Giannino; Lucia Paciello; Palma Parascandola
Journal:  Microb Cell Fact       Date:  2015-07-30       Impact factor: 5.328

  5 in total

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