Differential gene expression in CHO cells cultivated in shake flasks and bioreactors
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ABSTRACT:
PROVIDER: PRJNA413823 | ENA |
REPOSITORIES: ENA
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Project description:Chinese Hamster Ovary cell lines are currently the primary host for production of therapeutic glycoproteins. Fast process development resulting in robust and scalable processes is a critical success factor in the highly competitive market for biosimilars. In process development screening of hundreds of clones and selection of process conditions are routinely performed in uncontrolled cultivation systems like shake flasks. A handful of potential candidate clones is nominated to be evaluated more intensively in well controlled small-scale bioreactors. Cell performance in the uncontrolled systems and to a lesser extent in the small-scale bioreactors may, however, be different from that in the final production reactor, which may result in failures during scale-up and thus extra development time. In this work, the focus is on better understanding the differences in cell performance between controlled and uncontrolled systems, which can be used to make process development faster and more robust in terms of scale-up. For this, we evaluated differences in gene expression profiles between shake flask and bioreactor cultures at three different time points during the exponential and stationary phase of a batch culture using commercially available Affymetrix GeneChip CHO Gene 2.1 ST arrays and multivariate data analysis on the outcomes. The outcomes were correlated with differences in glycosylation patterns and other culture parameters. Results showed large differences in gene expression over time and much smaller differences between the two cultivation systems. Furthermore, our study identified differentially expressed genes and corresponding metabolic and mechanistic pathways between the two systems, which were directly related to the degree of the control of the systems.
2023-11-04 | GSE104787 | GEO
Project description:Small-scale bioreactors used in Chinese hamster ovary (CHO) cell line development allow transcriptomic studies on multiple cell lines. Here we define the CHO cell long non-coding RNA (lncRNA) transcriptome from cells grown in controlled miniature bioreactors under fed-batch conditions using RNA-Seq to identify lncRNAs and how the expression of these changes throughout growth and between IgG producers. We identify lncRNAs associated with productivity and growth characteristics, finding that Adapt15, linked to ER stress, GAS5, linked to mTOR signalling/growth arrest, and PVT1, linked to Myc expression, are differentially regulated during fed-batch culture and whose expression relates to productivity and growth. Changes in (non)-coding RNA expression between the seed train and the equivalent day of fed-batch culture are also reported, showing large differences in gene expression between these, and compared with existing datasets. Collectively, we present a comprehensive lncRNA CHO cell profiling and identify targets for engineering growth and productivity characteristics of CHO cells.
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Project description:Small-scale bioreactors used in Chinese hamster ovary (CHO) cell line development allow transcriptomic studies on multiple cell lines. Here we define the CHO cell long non-coding RNA (lncRNA) transcriptome from cells grown in controlled miniature bioreactors under fed-batch conditions using RNA-Seq to identify lncRNAs and how the expression of these changes throughout growth and between IgG producers. We identify lncRNAs associated with productivity and growth characteristics, finding that Adapt15, linked to ER stress, GAS5, linked to mTOR signalling/growth arrest, and PVT1, linked to Myc expression, are differentially regulated during fed-batch culture and whose expression relates to productivity and growth. Changes in (non)-coding RNA expression between the seed train and the equivalent day of fed-batch culture are also reported, showing large differences in gene expression between these, and compared with existing datasets. Collectively, we present a comprehensive lncRNA CHO cell profiling and identify targets for engineering growth and productivity characteristics of CHO cells.
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