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Dynamics of central metabolism in MDCK cells: modelling approach on 30 intracellular metabolites

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons86447

Rehberg,  M.
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons86451

Ritter,  J. B.
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

Genzel,  G.
Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons86448

Reichl,  U.
Otto-von-Guericke-Universität Magdeburg;
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Citation

Rehberg, M., Ritter, J. B., Genzel, G., & Reichl, U. (2010). Dynamics of central metabolism in MDCK cells: modelling approach on 30 intracellular metabolites. Poster presented at Systems Biology of Mammalian Cells, Freiburg, Germany.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-8F97-A
Abstract
Adherently growing Madin Darby canine kidney (MDCK) cells are currently used as host cells for influenza vaccine production. Understanding cellular growth, nutrient consumption and production capacity of this process is essential for process design and optimisation strategies. Over the past decades metabolism of diverse eukaryotic cell lines was investigated intensively to elucidate the functionality of energy and metabolite generation. However, especially in mammalian cells, a comprehensive understanding of the complex dynamics of glycolysis and citric acid cycle still poses a serious challenge. Here, we present a systems biology approach which combines high temporal resolution experiments with a mathematical model to analyse the central metabolism of MDCK cells during batch cultivation. Model validation is based on experimental data of more than 30 intracellular metabolites, including organic acids, sugar phosphates and nucleotides. Focus will be on investigation of crucial metabolic pathways and regulatory mechanisms for various growth phases and cultivation conditions of this adherent cell line. First results indicate that the time course of several metabolites involves complex interactions between metabolite concentrations and enzyme activities, which allows to draw conclusions about appropriate reaction kinetics. Validating parts of the model already enables the design of new experiments, which may help to further characterise key regulatory mechanisms.