These authors contributed equally to this study and share first authorship.
Research Article
Dynamic mRNA and miRNA profiling of CHO-K1 suspension cell cultures
Article first published online: 5 AUG 2011
DOI: 10.1002/biot.201100143
Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Additional Information
How to Cite
Bort, J. A. H., Hackl, M., Höflmayer, H., Jadhav, V., Harreither, E., Kumar, N., Ernst, W., Grillari, J. and Borth, N. (2012), Dynamic mRNA and miRNA profiling of CHO-K1 suspension cell cultures. Biotechnology Journal, 7: 500–515. doi: 10.1002/biot.201100143
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These authors contributed equally to this study and share first authorship.
Publication History
- Issue published online: 28 MAR 2012
- Article first published online: 5 AUG 2011
- Accepted manuscript online: 21 JUN 2011 05:10AM EST
- Manuscript Accepted: 7 JUN 2011
- Manuscript Revised: 10 MAY 2011
- Manuscript Received: 1 MAR 2011
Keywords:
- CHO cells;
- Microarray;
- MicroRNA;
- mRNA;
- Transcriptomics
Abstract
In spite of the importance of Chinese hamster ovary (CHO) cells for recombinant protein production, very little is known about the molecular and gene regulatory mechanisms that control cellular phenotypes such as enhanced growth under serum-free conditions or high productivity. Most microarray analyses to this purpose are performed with samples taken during the exponential growth phase. However, the cellular transcriptome is dynamic, changing in response to external and internal stimuli and thus reflecting the current functional capacity of cells as well as their ability to adapt to a changing environment. Therefore, during batch or fed-batch cultivations it can be expected that the transcription pattern of genes will change and that such changes may give indications on the cellular state in terms of viability, growth, and productivity. In the current study we monitored the change in expression patterns of mRNAs and microRNAs (miRNA) during lag, exponential, and stationary phases in CHO-K1 suspension cell cultures. In total, over 1400 mRNAs and more than 100 miRNAs were differentially regulated (p<0.05) relative to the batch culture at the starting point. Functional clustering revealed groups of genes with similar expression patterns, which were subjected to functional pathway analysis. In addition, as miRNAs generally act as negative post-transcriptional regulators of mRNAs, we looked for changes in their expression that were inverse to those of their predicted target mRNAs.

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