Synchronized mammalian cell culture: part II--population ensemble modeling and analysis for development of reproducible processes

Abstract

The consideration of inherent population inhomogeneities of mammalian cell cultures becomes increasingly important for systems biology study and for developing more stable and efficient processes. However, variations of cellular properties belonging to different sub-populations and their potential effects on cellular physiology and kinetics of culture productivity under bioproduction conditions have not yet been much in the focus of research. Culture heterogeneity is strongly determined by the advance of the cell cycle. The assignment of cell-cycle specific cellular variations to large-scale process conditions can be optimally determined based on the combination of (partially) synchronized cultivation under otherwise physiological conditions and subsequent population-resolved model adaptation. The first step has been achieved using the physical selection method of countercurrent flow centrifugal elutriation, recently established in our group for different mammalian cell lines which is presented in Part I of this paper series. In this second part, we demonstrate the successful adaptation and application of a cell-cycle dependent population balance ensemble model to describe and understand synchronized bioreactor cultivations performed with two model mammalian cell lines, AGE1.HNAAT and CHO-K1. Numerical adaptation of the model to experimental data allows for detection of phase-specific parameters and for determination of significant variations between different phases and different cell lines. It shows that special care must be taken with regard to the sampling frequency in such oscillation cultures to minimize phase shift (jitter) artifacts. Based on predictions of long-term oscillation behavior of a culture depending on its start conditions, optimal elutriation setup trade-offs between high cell yields and high synchronization efficiency are proposed.

Keywords: cell-cycle control; overflow metabolism; physical synchronization; population heterogeneity; stochastic modeling.