Model Based Control for Metabolic Shift Regulation In Mammalian Cells

Friday, October 21, 2011: 10:30 AM
101 D (Minneapolis Convention Center)
Damian Baeza, Department of Chemical Engineering and Biotechnology, University of Chile, Santiago, Chile, J. Cristian Salgado, Department of Chemical Engineering and Biotechnology, University of Chile, Millennium Institute for Cell Dynamics and Biotechnology: a Centre for Systems Biology, Santiago, Chile and Ziomara P. Gerdtzen, Centre for Biochemical Engineering and Biotechnology, Department of Chemical Engineering and Biotechnology, Millennium Institute for Cell Dynamics and Biotechnology, University of Chile, Santiago, Chile

The existence of multiple steady states in mammalian cell culture with distinct cellular metabolism is of great importance in bioprocess design [1]. Different metabolic states are represented by different lactate to glucose stoichiometric ratios. Low ΔL/ΔG are associated with increased culture's productivity. Experimental evidence suggests that the existence of multiple steady states involves the interaction between metabolic and gene networks and their regulation [2]. The problem of providing an optimized strategy for glucose feeding in order to achieve a specific metabolic state is yet to be studied. We propose a model based strategy for designing a control system for metabolic state regulation that considers the biological complexity of the regulation of the cellular system.

We formulated a detailed metabolic model for mammalian cell metabolism, based on a system of differential equations for the main metabolic variables, involving a large number of variables and parameters. The model’s parameters were obtained from literature and through a fitting process to experimental data. The existence of only one stable attractor supports the idea that metabolic regulation alone cannot explain the metabolic shift. Therefore, gene regulation is a crucial element that must be considered in a model that correctly describes this phenomenon. Based on experimental information [2] and the metabolic model, we identified the enzyme level changes that would have the largest impact in metabolism regulation. Using this information a continuous regultation model was proposed and coupled with the existing metabolic model in order to manipulate the metabolic response.

A simplified version of the metabolic model, which is capable of representing the metabolic shift of mammalian cells in low glucose cultures, was used for implementing a control strategy for maintaining a low metabolic state (ΔL/ΔG ratio under 0.5) under continuous operation. The input variables considered are glucose and lactate concentrations as well as the ΔL/ΔG ratio. The controller modifies the response of the system by manipulating the dilution rate and the glucose feed concentration of the culture.

[1] A. Europa, A. Gambhir, P-F Fu, W-S. Hu, Biotechnol. bioeng., 67, 25-34 (2000)

[2] R. Korke, M. Gatti, A. Lau, J. Lim, T. Seow, M. Chung, W-S. Hu, J. Biotech., 107, 1-17 (2004)


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