Proteomics

Dataset Information

0

Exoproteome in a perfusion bioreactor containing antibody-producing CHO cells at various cell densities


ABSTRACT: Chinese Hamster ovary (CHO) cells are the main platform used to produce recombinant proteins in the biopharmaceutical industry and are commonly cultured in either fed-batch or perfusion mode. However, the optimization of the complex biological systems used in such processes is extremely challenging. Omics approaches can reveal otherwise unknown characteristics of these systems and identify culture parameters that can be manipulated to optimize the cultivation process. Here we have applied proteomic profiling to a monoclonal antibody (mAb) production operated in perfusion mode to explore how cell biology and reactor environment change as the cell density reaches ≥ 200 x 106 cells/mL. The proteomics data show an increase of structural proteins as cell density increase, signs of oxidative stress and changes in glutathione metabolism at very high cell densities. Additionally, metabolomic profiling was carried out. See article “High cell density culture has a maintained exoproteome and metabolome” for more information.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Cricetulus Griseus (chinese Hamster) (cricetulus Barabensis Griseus)

TISSUE(S): Cell Suspension Culture

SUBMITTER: Magnus Lundqvist  

LAB HEAD: Johan Rockberg

PROVIDER: PXD008760 | Pride | 2018-07-04

REPOSITORIES: Pride

altmetric image

Publications


The optimization of bioprocesses for biopharmaceutical manufacturing by Chinese hamster ovary (CHO) cells can be a challenging endeavor and, today, heavily relies on empirical methods treating the bioreactor process and the cells as black boxes. Multi-omics approaches have the potential to reveal otherwise unknown characteristics of these systems and identify culture parameters to more rationally optimize the cultivation process. Here, the authors have applied both metabolomic and proteomic prof  ...[more]

Similar Datasets

2005-12-31 | E-MEXP-496 | biostudies-arrayexpress
2016-07-20 | E-GEOD-84574 | biostudies-arrayexpress
2016-07-20 | E-GEOD-84575 | biostudies-arrayexpress
| 2668668 | ecrin-mdr-crc
2010-06-09 | E-GEOD-996 | biostudies-arrayexpress
2018-12-24 | GSE124314 | GEO
2023-05-11 | E-MTAB-12198 | biostudies-arrayexpress
2022-08-12 | PXD026333 | Pride
2016-03-21 | GSE69206 | GEO
2010-05-07 | E-GEOD-18579 | biostudies-arrayexpress