Cell-line Engineering of Chinese Hamster Ovary Cells for Low-temperature Culture

Developments in mammalian cell culture and recombinant technology has allowed for the production of recombinant proteins for use as human therapeutics. Mammalian cell culture is typically operated at the physiological temperature of 37°. However, recent research has shown that the use of low-temperature conditions (30-33°) as a platform for cell-culture results in changes in cell characteristics, such as increased specific productivity and extended periods of cell viability, that can potentially improve the production of recombinant proteins. Furthermore, many recent reports have focused on investigating low-temperature mammalian cell culture of Chinese hamster ovary (CHO) cells, one of the principal cell-lines used in industrial production of recombinant proteins. Exposure to low ambient temperatures exerts an external stress on all living cells, and elicits a cellular response. This cold-stress response has been observed in bacteria, plants and mammals, and is regulated at the gene level. The exact genes and molecular mechanisms involved in the cold-stress response in prokaryotes and plants have been well studied. There are also various reports that detail the modification of cold-stress genes to improve the characteristics of bacteria or plant cells at low temperatures. However, there is very limited information on mammalian cold-stress genes or the related pathways governing the mammalian cold-stress response. This project seeks to investigate and characterise cold-stress genes that are differentially expressed during low-temperature culture of CHO cells, and to relate them to the various changes in cell characteristics observed in low-temperature culture of CHO cells. The gene information can then be used to modify CHO cell-lines for improved performance in the production of recombinant proteins.

Optimizing Product Line Designs: Efficient Methods and Comparisons

We compare a broad range of optimal product line design methods. The comparisons take advantage of recent advances that make it possible to identify the optimal solution to problems that are too large for complete enumeration. Several of the methods perform surprisingly well, including Simulated Annealing, Product-Swapping and Genetic Algorithms. The Product-Swapping heuristic is remarkable for its simplicity. The performance of this heuristic suggests that the optimal product line design problem may be far easier to solve in practice than indicated by complexity theory.