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Journal of Proteomics & Bioinformatics

Journal of Proteomics & Bioinformatics
Open Access

ISSN: 0974-276X

+44 1223 790975

Abstract

Proteomic Analysis of Bioreactor Cultures of an Antibody Expressing CHOGS Cell Line that Promotes High Productivity

Haimanti Dorai, Suli Liu, Xiang Yao, Yonghui Wang, Uelke Tekindemir, Michael J Lewis, Shiaw-Lin Wu and William Hancock

Antibody manufacturing cell line development at Janssen Research & Development involves transfection of therapeutic antibody genes into a CHO-GS host cell line and isolating primary transfectomas that upon cloning yield high expressing cell lines secreting the desired antibody products. Subsequently, these cell lines are cultivated in stirred tank bioreactors for the large-scale generation of the products. In an attempt to optimize this process for high productivity, a two pronged approach was undertaken.

First, in a Design of Experiment study, a CHO-GS cell line expressing a therapeutic antibody was cultivated in 2 L DasGip fed-batch mini-bioreactors under a variety of culture conditions. In general, culture conditions that promoted robust growth and high viable cell density resulted in high productivity. Then, cell culture harvests and cell lysates from two ‘high productivity’ and two ‘low productivity’ bioreactors were subjected to proteomic analysis using the CHO genome database, on two independent days. The levels of each protein expressed in these two sets of bioreactors were then compared. A total of 180 proteins that were modulated two-fold or more were thus identified, only 12 of which were consistently modulated across multiple days in culture. The modulated proteins have biological process functions that are related to cytoskeleton rearrangement, protein synthesis, cell metabolism and cell growth. Provided that these observations are validated by Western blot, one or more of these proteins, whose expression correlated to productivity can potentially be utilized as targets for manipulating a superior transfection host cell line. At a minimum, the expression levels of these proteins can provide insight for further process optimization efforts.

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