Application of System Biology Tools for the Design of Improved Chinese Hamster Ovary Cell Expression Platforms
Vijeta Sharma, Manjul Tripathi and KJ Mukherjee*
School of Biotechnology, Jawaharlal Nehru University, New Delhi, India
- *Corresponding Author:
- KJ Mukherjee
Professor, School of Biotechnology
Jawaharlal Nehru University
New Delhi-110 067, India
E-mail: [email protected]
Received date: May 14, 2016; Accepted date: June 22, 2016; Published date: June 27, 2016
Citation: Sharma V, Tripathi M, Mukherjee KJ (2016) Application of System Biology Tools for the Design of Improved Chinese Hamster Ovary Cell Expression Platforms. J Bioprocess Biotech 6: 284. doi:10.4172/2155-9821.1000284
Copyright: © 2016 Sharma V, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
CHO cells have an impressive monopoly over other expression systems in the production of complex therapeutic proteins at large scale. There is thus a need to design superior cell lines with improved product quality and enhanced expression levels which requires an understanding of the cellular components and their interactions from a ‘systems’ point of view. With the emergence of critical ‘omics’ data sets for CHO cells which include transcriptomics, proteomics, metabolomics, fluxomics, and glycomics; some clarity has emerged in elucidating the global regulatory mechanisms that control protein over expression. Integrating this vast amount of information with bioprocess data can help point out significant targets for cellular modification that are required for hyper production. In mammalian systems, the information flow from genes to phenotype is mediated by complex regulatory networks and mathematical modeling which incorporates this framework would also assist in the identification of crucial targets for modification. This review updates recent advancements in OMICS technologies and the synergistic use of these platforms for designing improved cell lines.