The understanding of the metabolic behavior of complex systems-such as eukaryotic cells- needs the development of new approaches able to deal with the complexity arising from the huge amount of interactions occurring within a living system. Since these interactions are ultimately responsible for an organism's form and functions we developed a mathematical model including many metabolic compartments interacting each other by fluxes of material. In this paper we will discuss the ability of this approach to describe the metabolic responses of Saccharomyces cerevisiae - which represents an ideal eukaryotic cell - to exogenous and endogenous stress conditions. Metabolic data of the fermentative process in yeast has been collected by in vivo 13C NMR spectroscopy; consecutively the data has been used to validate the compartimental model allowing also the estimation of kinetic constants associated with the fluxes within the model. The robustness of the model is confirmed by the excellent agreement between the experimental and simulated data furthermore the model correctly predicts the fermentative metabolism of yeast undergoing different stress conditions.
Rossi, C., Bartolini, F., Magnani, A., Foletti, A., Martini, S., Ricci, M. (2008). Saccharomyces cerevisiae metabolic process by mathematical modelling and in-vivo C-13-NMR. In Proceedings of the 1stWSEAS International Conference on Biomedical Electronics and Biomedical Informatics (pp.172-177). Long, CA; Anninos, P; Pham, T; Anastassopoulos, G; Mastorakis, NE.
Saccharomyces cerevisiae metabolic process by mathematical modelling and in-vivo C-13-NMR
ROSSI, CLAUDIO;MAGNANI, AGNESE;
2008-01-01
Abstract
The understanding of the metabolic behavior of complex systems-such as eukaryotic cells- needs the development of new approaches able to deal with the complexity arising from the huge amount of interactions occurring within a living system. Since these interactions are ultimately responsible for an organism's form and functions we developed a mathematical model including many metabolic compartments interacting each other by fluxes of material. In this paper we will discuss the ability of this approach to describe the metabolic responses of Saccharomyces cerevisiae - which represents an ideal eukaryotic cell - to exogenous and endogenous stress conditions. Metabolic data of the fermentative process in yeast has been collected by in vivo 13C NMR spectroscopy; consecutively the data has been used to validate the compartimental model allowing also the estimation of kinetic constants associated with the fluxes within the model. The robustness of the model is confirmed by the excellent agreement between the experimental and simulated data furthermore the model correctly predicts the fermentative metabolism of yeast undergoing different stress conditions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11365/41691
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