New approaches for population-based kinetic study and modeling of cell culture under high cell density

tIt is conventionally assumed that mammalian cell cultures cultivated in bioreactors exhibit a homogeneous and indifferent kinetic behavior. However, real cell cultures consist of a mixture of multiple subpopulations with variable composition that interact with each other via the culture medium. A major cause for the occurrence of such subpopulations is the progress of individual cells within the cell cycle. Potential metabolic and regulatory variations of the behavior of mammalian cell cultures during the different cell cycle phases have not been systematically examined in literature. Experimental results are often incomplete and contradictory, leading to intense disputes with a spectrum of opinions ranging from the assumption of completely eventless metabolism and regulation in the cell cycles towards extremely complex and not mechanistically explained cell-cycle dependent regulation cascades. A main reason for these discrepancies lies in incompletely validated or non-physiological synchronization methods and insufficient statistic analysis and proper model description. During the last few years, our group has established the necessary framework regarding process control, cell culture techniques and modeling in order to conduct systematic kinetic and well validated experimental examinations of cell-cycle related metabolic processes and regulations in cell cultures under widely undisturbed, that is process relevant physiological conditions. First analyses already indicated cell cycle dependent variations of cell mass specific substrate turnover rates. In the proposed project, a systematic elucidation of relevant cell cycle specific metabolic processes in cell cultures under process conditions, especially at high cell density, shall be performed utilizing population based analysis and statistic evaluation methods. The focus is especially laid on the regulation kinetics of the pyruvate metabolism under stress conditions and the influence of high cell density on growth kinetics and central metabolism. Furthermore, we intend also to explore the possibility of using such population-based kinetic relationships for optimal control of process stability under variable cultivation conditions.

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