Untargeted proteomics reveals upregulation of stress response pathways during CHO-based monoclonal antibody manufacturing process leading to disulfide bond reduction.

Monoclonal antibody (mAb) interchain disulfide bond reduction can cause a loss of function and negatively impact the therapeutic's efficacy and safety. Disulfide bond reduction has been observed at various stages during the manufacturing process, including processing of the harvested material. The factors and mechanisms driving this phenomenon are not fully understood. In this study, we examined the host cell proteome as a potential factor affecting the susceptibility of a mAb to disulfide bond reduction in the harvested cell culture fluid (HCCF). We used untargeted liquid-chromatography-mass spectrometry-based proteomics experiments in conjunction with a semi-automated protein identification workflow to systematically compare Chinese hamster ovary (CHO) cell protein abundances between bioreactor conditions that result in reduction-susceptible and reduction-free HCCF. Although the growth profiles and antibody titers of these two bioreactor conditions were indistinguishable, we observed broad differences in host cell protein (HCP) expression. We found significant differences in the abundance of glycolytic enzymes, key protein reductases, and antioxidant defense enzymes. Multivariate analysis of the proteomics data determined that upregulation of stress-inducible endoplasmic reticulum (ER) and other chaperone proteins is a discriminatory characteristic of reduction-susceptible HCP profiles. Overall, these results suggest that stress response pathways activated during bioreactor culture increase the reduction-susceptibility of HCCF. Consequently, these pathways could be valuable targets for optimizing culture conditions to improve protein quality.

Metabolomic and quality data for early and late passages of an antibody-producing industrial CHO cell line.

In this article, we provide four data sets for an industrial Chinese Hamster Ovary (CHO) cell line producing antibodies during a 14-day bioreactor run. This cell line was selected for further evaluation because of its significant titer loss as the cells were passaged over time. Four conditions that differed in cell bank ages were run for this dataset. Specifically, cells were passaged to passage 12, 21, 25, and 37 and then used in this experiment. Once the run commenced the following datasets were gathered: 1). Glycosylation data for each reactor 2). Size Exclusion Chromatography (SEC) data for the antibodies produced which allowed for the identification of high and low molecular weight species in the samples (N-Glycan and SEC data was taken on day 14 only). 3/4). Metabolites levels measured using Nuclear Magnetic Resonance (NMR) and liquid chromatography-mass spectroscopy (LC-MS) for all reactors over the time course of days 1, 4, 6, 8, 12, and 14. We also provide a graph of the glutamine levels for cells of different ages as an example of the utility of the data. These metabolomics data provide relative amounts for 36 metabolites (NMR) and 109 metabolites (LC-MS) over the 14-day time course. These data were collected in connection with a co-submitted paper [1].

Effective temperature shift strategy development and scale confirmation for simultaneous optimization of protein productivity and quality in Chinese hamster ovary cells.

Temperature shifts to lower culture temperatures are frequently employed in the manufacturing of protein therapeutics in mammalian cells to improve productivity, viability, or quality attributes. The direction and extent to which a temperature shift affects productivity and quality may vary depending on the expression host and characteristics of the expressed protein. We demonstrated here that two Chinese hamster ovary (CHO) clones expressing different human monoclonal antibodies responded differently to a temperature shift despite sharing a common parental CHO cell line. Within a single CHO line, we observed a nonlinear response to temperature shift. A moderate shift to 35°C significantly decreased final titer relative to the unshifted control while a larger shift to 32°C significantly increased final titer by 25%. Therefore, we proposed a systematic empirical approach to assess the utility of a temperature shift for faster implementation during process development. By testing multiple shift parameters, we identified optimum shift conditions in shake flasks and successfully translated findings to benchtop bioreactors and 1,000-L bioreactor scale. Significant differences in final antibody titer and charge variants were observed with temperature shift increments as small as Δ1.5°C. Acidic charge variants decreased monotonically with decreasing shift temperature in both cell lines; however, final antibody titer required simultaneous optimization of shift day and temperature. Overall, we were able to show that a systematic approach to identify temperature shift parameters at small scales is useful to optimize protein production and quality for efficient and confident translation to large-scale production.