Development and Analysis of a Mathematical Model for Antibody-Producing GS-NS0 Cells Under Normal and Hyperosmotic Culture Conditions

Apoptosis: A mammalian cell bioprocessing perspective

Apoptosis is a form of programmed and controlled cell death that accounts for the majority of cellular death in bioprocesses. Cell death affects culture longevity and product quality; it is instigated by several stresses experienced by the cells within a bioreactor. Understanding the factors that cause apoptosis as well as developing strategies that can protect cells is crucial for robust bioprocess development. This review aims to a) address apoptosis from a bioprocess perspective; b) describe the significant apoptotic mechanisms linking them to the most relevant stresses encountered in bioreactors; c) discuss the design of operating conditions in order to avoid cell death; d) focus on industrially relevant cell lines; and e) present anti-apoptosis strategies including cell engineering and model-based optimization of bioprocesses. In addition, the importance of apoptosis in quality-by-design bioprocess development from clone screening to production scale are highlighted.

Sequential Parameter Estimation for Mammalian Cell Model Based on In Silico Design of Experiments

Due to the complicated metabolism of mammalian cells, the corresponding dynamic mathematical models usually consist of large sets of differential and algebraic equations with a large number of parameters to be estimated. On the other hand, the measured data for estimating the model parameters are limited. Consequently, the parameter estimates may converge to a local minimum far from the optimal ones, especially when the initial guesses of the parameter values are poor. The methodology presented in this paper provides a systematic way for estimating parameters sequentially that generates better initial guesses for parameter estimation and improves the accuracy of the obtained metabolic model. The model parameters are first classified into four subsets of decreasing importance, based on the sensitivity of the model’s predictions on the parameters’ assumed values. The parameters in the most sensitive subset, typically a small fraction of the total, are estimated first. When estimating the remaining parameters with next most sensitive subset, the subsets of parameters with higher sensitivities are estimated again using their previously obtained optimal values as the initial guesses. The power of this sequential estimation approach is illustrated through a case study on the estimation of parameters in a dynamic model of CHO cell metabolism in fed-batch culture. We show that the sequential parameter estimation approach improves model accuracy and that using limited data to estimate low-sensitivity parameters can worsen model performance.

Using simple models to describe the kinetics of growth, glucose consumption, and monoclonal antibody formation in naive and infliximab producer CHO cells

Despite their practical and commercial relevance, there are few reports on the kinetics of growth and production of Chinese hamster ovary (CHO) cells-the most frequently used host for the industrial production of therapeutic proteins. We characterize the kinetics of cell growth, substrate consumption, and product formation in naive and monoclonal antibody (mAb) producing recombinant CHO cells. Culture experiments were performed in 125 mL shake flasks on commercial culture medium (CD Opti CHO™ Invitrogen, Carlsbad, CA, USA) diluted to different glucose concentrations (1.2-4.8 g/L). The time evolution of cell, glucose, lactic acid concentration and monoclonal antibody concentrations was monitored on a daily basis for mAb-producing cultures and their naive counterparts. The time series were differentiated to calculate the corresponding kinetic rates (rx = d[X]/dt; rs = d[S]/dt; rp = d[mAb]/dt). Results showed that these cell lines could be modeled by Monod-like kinetics if a threshold substrate concentration value of [S]t = 0.58 g/L (for recombinant cells) and [S]t = 0.96 g/L (for naïve cells), below which growth is not observed, was considered. A set of values for μmax, and Ks was determined for naive and recombinant cell cultures cultured at 33 and 37 °C. The yield coefficient (Yx/s) was observed to be a function of substrate concentration, with values in the range of 0.27-1.08 × 10(7) cell/mL and 0.72-2.79 × 10(6) cells/mL for naive and recombinant cultures, respectively. The kinetics of mAb production can be described by a Luedeking-Piret model (d[mAb]/dt = αd[X]/dt + β[X]) with values of α = 7.65 × 10(-7) µg/cell and β = 7.68 × 10(-8) µg/cell/h for cultures conducted in batch-agitated flasks and batch and instrumented bioreactors operated in batch and fed-batch mode.

Analysis of Chinese hamster ovary cell metabolism through a combined computational and experimental approach

Optimization of cell culture processes can benefit from the systematic analysis of experimental data and their organization in mathematical models, which can be used to decipher the effect of individual process variables on multiple outputs of interest. Towards this goal, a kinetic model of cytosolic glucose metabolism coupled with a population-level model of Chinese hamster ovary cells was used to analyse metabolic behavior under batch and fed-batch cell culture conditions. The model was parameterized using experimental data for cell growth dynamics, extracellular and intracellular metabolite profiles. The results highlight significant differences between the two culture conditions in terms of metabolic efficiency and motivate the exploration of lactate as a secondary carbon source. Finally, the application of global sensitivity analysis to the model parameters highlights the need for additional experimental information on cell cycle distribution to complement metabolomic analyses with a view to parameterize kinetic models.

Modeling and measuring intracellular fluxes of secreted recombinant protein in Pichia pastoris with a novel 34S labeling procedure

Background

The budding yeast Pichia pastoris is widely used for protein production. To determine the best suitable strategy for strain improvement, especially for high secretion, quantitative data of intracellular fluxes of recombinant protein are very important. Especially the balance between intracellular protein formation, degradation and secretion defines the major bottleneck of the production system. Because these parameters are different for unlimited growth (shake flask) and carbon-limited growth (bioreactor) conditions, they should be determined under "production like" conditions. Thus labeling procedures must be compatible with minimal production media and the usage of bioreactors. The inorganic and non-radioactive ³⁴S labeled sodium sulfate meets both demands.

Results

We used a novel labeling method with the stable sulfur isotope ³⁴S, administered as sodium sulfate, which is performed during chemostat culivations. The intra- and extracellular sulfur 32 to 34 ratios of purified recombinant protein, the antibody fragment Fab3H6, are measured by HPLC-ICP-MS. The kinetic model described here is necessary to calculate the kinetic parameters from sulfur ratios of consecutive samples as well as for sensitivity analysis. From the total amount of protein produced intracellularly (143.1 μg g^-1 h^-1 protein per yeast dry mass and time) about 58% are degraded within the cell, 35% are secreted to the exterior and 7% are inherited to the daughter cells.

Conclusions

A novel ³⁴S labeling procedure that enables in vivo quantification of intracellular fluxes of recombinant protein under "production like" conditions is described. Subsequent sensitivity analysis of the fluxes by using MATLAB, indicate the most promising approaches for strain improvement towards increased secretion.

An empirical modeling platform to evaluate the relative control discrete CHO cell synthetic processes exert over recombinant monoclonal antibody production process titer

In this study we have combined empirically derived mathematical models of intracellular Mab synthesis to quantitatively compare the degree to which individual cellular processes limit recombinant IgG(4) monoclonal antibody production by GS-CHO cells throughout a state-of-the-art industrial fed-batch culture process. Based on the calculation of a production process control coefficient for each stage of the intracellular Mab synthesis and secretion pathway, we identified the major cellular restrictions on Mab production throughout the entire culture process to be recombinant heavy chain gene transcription and heavy chain mRNA translation. Surprisingly, despite a substantial decline in the rate of cellular biomass synthesis during culture, with a concomitant decline in the calculated rate constants for energy-intensive Mab synthetic processes (Mab folding/assembly and secretion), these did not exert significant control of Mab synthesis at any stage of production. Instead, cell-specific Mab production was maintained by increased Mab gene transcription which offset the decline in cellular biosynthetic rates. Importantly, this study shows that application of this whole-process predictive modeling strategy should rationally precede and inform cell engineering approaches to increase production of a recombinant protein by a mammalian host cell--where control of productivity is inherently protein product and cell line specific.

Long-term prediction of fish growth under varying ambient temperature using a multiscale dynamic model

Background

Feed composition has a large impact on the growth of animals, particularly marine fish. We have developed a quantitative dynamic model that can predict the growth and body composition of marine fish for a given feed composition over a timespan of several months. The model takes into consideration the effects of environmental factors, particularly temperature, on growth, and it incorporates detailed kinetics describing the main metabolic processes (protein, lipid, and central metabolism) known to play major roles in growth and body composition.

Results

For validation, we compared our model's predictions with the results of several experimental studies. We showed that the model gives reliable predictions of growth, nutrient utilization (including amino acid retention), and body composition over a timespan of several months, longer than most of the previously developed predictive models.

Conclusion

We demonstrate that, despite the difficulties involved, multiscale models in biology can yield reasonable and useful results. The model predictions are reliable over several timescales and in the presence of strong temperature fluctuations, which are crucial factors for modeling marine organism growth. The model provides important improvements over existing models.