(425j) In Silico Modeling and Simulation of Mouse Hybridoma Cells for the Enhanced Production of Monoclonal Antibodies

Mammalian cell cultures represent one of the major sources for producing very high-value biopharmaceutical products as therapeutics. They include monoclonal antibodies, recombinant proteins, viral vaccines, and hormones, a number of which are now under clinical trials. The increasing market demand for such commercially valuable compounds can be satisfied by developing processes for high-yielding mammalian cell culture. However, even slight deviations in the culture conditions lead to either reduced productivity or cell death. In addition, the difficulty in elucidating the behavior of the mammalian cellular system is magnified by the system's structural, functional and dynamic complexities as well as the heterogeneous interactions between multiple and different types of cells [1]. Thus, an urgent need exists for a systems-level analysis of the mammalian cellular system. Toward this end, mathematical modeling and simulation of this complex biological system is invaluable in characterizing and understanding the cellular physiology, regulation and metabolism. This would help us design appropriate experiments to optimize their performance. For example, in silico perturbation of the metabolic system can provide crucial information on cellular behavior under varying degrees of genetic and environmental perturbations, thereby suggesting a variety of strategies for the development of efficient biotechnological processes. Furthermore, the number of real wet experiments can be minimized by carrying out in silico (computational) experiments using the computational models.

Working with one of industrially important host cells, mouse hybridoma cells, the research activities of the current work focus on reconstructing a genome-scale metabolic model of the cells based on the previous work [2] and combining the model with experimentally generated data. The model includes 1129 unique biochemical reactions with 1065 intermediate metabolites. Our model has been analyzed for the cell growth and enhanced production of monoclonal antibody IgG1[3]. In the model, precursor balances and energetic requirements for antidoy production are also considered. Based on the model, the capability and flexibility of the network have been investigated by resorting to various analysis techniques including alternate optima and flux variability analysis [4]. In addition, gene deletion analysis has been performed to identify essential genes for the cell growth and recombinant protein production. Novel optimization models have also been developed to identify the sets of necessary and sufficient genes for both cell growth and recombinant production. Thus, the presented approaches could be directly applied in identifying potential cell engineering targets for the enhanced production of recombinant proteins or monoclonal antibody in cultures, thereby developing high-yielding mammalian cell culture processes.

Keywords: Genome scale reconstruction, Mus musculus, metabolic flux analysis

References

1. Fukanaga R, Sokawa Y, Nagata S. 1984. Constitutive production of human interferons by mouse cells with bovine papillomavirus as a vector. Proc. Natl. Acad. Sci. 81:5086-5090.

2. Sheikh K, Forster J, Nielson LK. 2005. Modeling hybridoma cell metabolism using a generic genome-scale metabolic model of Mus musculus. Biotech. Prog. 21:112-121.

3. Mahadevan R, Schilling CH. 2003. The effects of alternate optimal solutions in constrained-based genome-scale metabolic models. Metab. Eng. 5:264-276.