Maximum entropy and population heterogeneity in continuous cell cultures.

Continuous cultures of mammalian cells are complex systems displaying hallmark phenomena of nonlinear dynamics, such as multi-stability, hysteresis, as well as sharp transitions between different metabolic states. In this context mathematical models may suggest control strategies to steer the system towards desired states. Although even clonal populations are known to exhibit cell-to-cell variability, most of the currently studied models assume that the population is homogeneous. To overcome this limitation, we use the maximum entropy principle to model the phenotypic distribution of cells in a chemostat as a function of the dilution rate. We consider the coupling between cell metabolism and extracellular variables describing the state of the bioreactor and take into account the impact of toxic byproduct accumulation on cell viability. We present a formal solution for the stationary state of the chemostat and show how to apply it in two examples. First, a simplified model of cell metabolism where the exact solution is tractable, and then a genome-scale metabolic network of the Chinese hamster ovary (CHO) cell line. Along the way we discuss several consequences of heterogeneity, such as: qualitative changes in the dynamical landscape of the system, increasing concentrations of byproducts that vanish in the homogeneous case, and larger population sizes.

A systematic approach for doing an a priori identifiability study of dynamical nonlinear models.

This paper presents a method for investigating, through an automatic procedure, the (lack of) structural identifiability of dynamical models parameters. This method takes into account constraints on parameters and returns parameters whose estimations turn unidentifiable parameters into identifiable ones. It is based on (i) an equivalence between an extension of the notion of identifiability and the existence of solutions of algebraic systems, (ii) the use of symbolic computations for testing their existence. This method is described in details and is applied to two examples, the last one involving 12 parameters.

Statistical optimization of culture medium to produce recombinant viral protein by Escherichia coli host for diagnostic kit to detect human immunodeficiency virus (HIV) infection.

The maximal production of recombinant HIV1 gp41 by E. coli was examined in optimal culture condition and medium compositions. The culture condition such as growth, initial medium pHs, IPTG concentrations, induction times, temperature (0.5 OD, 7.6, 0.75 mM, 4.6 h, 32 °C respectively), and yeast extract (7.51 g/l), tryptone (7.26 g/l), glucose (2.45 g/l), NaCl (20.40 g/l), betaine (10.41 mM) and ampicillin (71.23 µg/ml) was optimized using statistical experimental design and response surface method (RSM). One of the main popular methods to attain high cell density in fed-batch culture is by controlling the nutrient feeding, which is often necessary for high yield in protein (0.63-0.72 mg/l) and cell (1.7-2 g/l) of the desired product in four litter fermentations.

Using molecular markers to characterize productivity in Chinese hamster ovary cell lines.

Selection of high producing cell lines to produce maximum product concentration is a challenging and time consuming task for the biopharmaceutical industry. The identification of early markers to predict high productivity will significantly reduce the time required for new cell line development. This study identifies candidate determinants of high productivity by profiling the molecular and morphological characteristics of a panel of six Chinese Hamster Ovary (CHO) stable cell lines with varying recombinant monoclonal antibody productivity levels ranging between 2 and 50 pg/cell/day. We examined the correlation between molecular parameters and specific productivity (qp ) throughout the growth phase of batch cultures. Results were statistically analyzed using Pearson correlation coefficient. Our study revealed that, overall, heavy chain (HC) mRNA had the strongest association with qp followed by light chain (LC) mRNA, HC intracellular polypeptides, and intracellular antibodies. A significant correlation was also obtained between qp and the following molecular markers: growth rate, biomass, endoplasmic reticulum, and LC polypeptides. However, in these cases, the correlation was not observed at all-time points throughout the growth phase. The repeated sampling throughout culture duration had enabled more accurate predictions of productivity in comparison to performing a single-point measurement. Since the correlation varied from day to day during batch cultivation, single-point measurement was of limited use in making a reliable prediction.