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Biotechnol Prog. 2012 Jan-Feb;28(1):103-13. doi: 10.1002/btpr.719. Epub 2011 Oct 19.

Predictive tool for recombinant protein production in Escherichia coli shake-flask cultures using an on-line monitoring system.

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  • 1AVT.Biochemical Engineering, RWTH Aachen University, Aachen 52074, Germany.

Abstract

As Escherichia coli (E. coli) is well defined with respect to its genome and metabolism, it is a favored host organism for recombinant protein production. However, many processes for recombinant protein production run under suboptimal conditions caused by wrong or incomplete information from an improper screening procedure, because appropriate on-line monitoring systems are still lacking. In this study, the oxygen transfer rate (OTR), determined on-line in shake flasks by applying a respiration activity monitoring system (RAMOS) device, was used to characterize the metabolic state of the recombinant organisms. Sixteen clones of E. coli SCS1 with foreign gene sequences, encoding for different target proteins, were cultivated in an autoinduction medium, containing glucose, lactose, and glycerol, to identify relationships between respiration activity and target protein production. All 16 clones showed a remarkably different respiration activity, biomass, and protein formation under induced conditions. However, the clones could be classified into three distinct types, and correlations could be made between OTR patterns and target protein production. For two of the three types, a decrease of the target protein was observed, after the optimal harvest time had passed. The acquired knowledge was used to modify the autoinduction medium to increase the product yield. Additional 1.5 g/L glucose accelerated the production process for one clone, shifting the time point of the maximal product yield from 24 to 17 h. For another clone, lactose addition led to higher volumetric product yields, in fact 25 and 38% more recombinant protein for 2 and 6 g/L additional lactose, respectively.

Copyright © 2011 American Institute of Chemical Engineers (AIChE).

PMID:
22012896
[PubMed - indexed for MEDLINE]
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