Current state and challenges for dynamic metabolic modeling

Review (2016)
Author(s)

Eleni Vasilakou (TU Delft - OLD BT/Cell Systems Engineering)

Daniel Machado (University of Minho)

Axel Theorell (Forschungszentrum Jülich)

Isabel Rocha (SilicoLife, University of Minho)

Katharina Nöh (Forschungszentrum Jülich)

Marco Oldiges (Forschungszentrum Jülich, RWTH Aachen University)

SA Wahl (TU Delft - OLD BT/Cell Systems Engineering)

Research Group
OLD BT/Cell Systems Engineering
Copyright
© 2016 E. Vasilakou, Daniel Machado, Axel Theorell, Isabel Rocha, Katharina Nöh, Marco Oldiges, S.A. Wahl
DOI related publication
https://doi.org/10.1016/j.mib.2016.07.008
More Info
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Publication Year
2016
Language
English
Copyright
© 2016 E. Vasilakou, Daniel Machado, Axel Theorell, Isabel Rocha, Katharina Nöh, Marco Oldiges, S.A. Wahl
Research Group
OLD BT/Cell Systems Engineering
Volume number
33
Pages (from-to)
97-104
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Abstract

While the stoichiometry of metabolism is probably the best studied cellular level, the dynamics in metabolism can still not be well described, predicted and, thus, engineered. Unknowns in the metabolic flux behavior arise from kinetic interactions, especially allosteric control mechanisms. While the stoichiometry of enzymes is preserved in vitro, their activity and kinetic behavior differs from the in vivo situation. Next to this challenge, it is infeasible to test the interaction of each enzyme with each intracellular metabolite in vitro exhaustively. As a consequence, the whole interacting metabolome has to be studied in vivo to identify the relevant enzymes properties. In this review we discuss current approaches for in vivo perturbation experiments, that is, stimulus response experiments using different setups and quantitative analytical approaches, including dynamic carbon tracing. Next to reliable and informative data, advanced modeling approaches and computational tools are required to identify kinetic mechanisms and their parameters.

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