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Current state and challenges for dynamic metabolic modeling

Vasilakou E, Machado D, Theorell A, Rocha I, Noeh K, Oldiges M, Wahl SA (2016)

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Publication Type: Journal article, Review article

Publication year: 2016

Journal

Book Volume: 33

Pages Range: 97-104

DOI: 10.1016/j.mib.2016.07.008

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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How to cite

APA:

Vasilakou, E., Machado, D., Theorell, A., Rocha, I., Noeh, K., Oldiges, M., & Wahl, S.A. (2016). Current state and challenges for dynamic metabolic modeling. Current Opinion in Microbiology, 33, 97-104. https://dx.doi.org/10.1016/j.mib.2016.07.008

MLA:

Vasilakou, Eleni, et al. "Current state and challenges for dynamic metabolic modeling." Current Opinion in Microbiology 33 (2016): 97-104.

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