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Transcriptional profiling of batch and fed-batch protein-free 293-HEK cultures
- Source :
- Metabolic Engineering. 9:52-67
- Publication Year :
- 2007
- Publisher :
- Elsevier BV, 2007.
-
Abstract
- Dynamic nutrient feeding to control glutamine at low levels in protein-free fed-batch cultures of 293-human embryonic kidney (HEK) cells achieved cell concentrations of 6×10 6 cells/ml. This represented a 4-fold improvement in cell concentration compared to batch cultures. Reduction in glutamine and glucose consumption, as well as lactate and ammonia production, were also observed in these fed-batch cultures. High virus production titers of 3×10 11 pfu/ml were achieved in fed-batch cultures which were 10,000-fold higher than batch cultures. An investigation of the transcriptional regulation of the metabolic changes associated with the batch and the low-glutamine fed-batch cultures using DNA microarray was conducted. This analysis provides better understanding of the transcriptional regulatory mechanism resulting in the observed physiological changes. Transcriptional profiling of cells from the mid-exponential, late exponential and stationary phases of both the batch and fed-batch were undertaken using an 18,000 element human chip. Transcriptional profiles were ontologically classified to provide a global view of the genetic changes. Furthermore, a pathway-oriented analysis focusing on cellular metabolism was conducted to reveal the dynamic regulation of genes related to amino acid metabolism, tRNA synthetases, TCA cycle, electron transport chain and glycolysis.
- Subjects :
- Adenoviruses, Human
Gene Expression Profiling
Citric Acid Cycle
HEK 293 cells
Bioengineering
Biology
Polymerase Chain Reaction
Applied Microbiology and Biotechnology
Amino Acyl-tRNA Synthetases
Electron Transport
Citric acid cycle
Glutamine
Biochemistry
Cell culture
Transcriptional regulation
Humans
Glycolysis
Amino Acids
DNA microarray
Gene
Cells, Cultured
Cell Proliferation
Oligonucleotide Array Sequence Analysis
Biotechnology
Subjects
Details
- ISSN :
- 10967176
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- Metabolic Engineering
- Accession number :
- edsair.doi.dedup.....77a64cc3739ac5049f6ed205434c2a6c