Quantification of metabolic limitations during recombinant protein production in Escherichia coli.

Escherichia coli is one of the major microorganisms for recombinant protein production because it has been best characterized in terms of molecular genetics and physiology, and because of the availability of various expression vectors and strains. The synthesis of proteins is one of the most energy consuming processes in the cell, with the result that cellular energy supply may become critical. Indeed, the so called metabolic burden of recombinant protein synthesis was reported to cause alterations in the operation of the host's central carbon metabolism. To quantify these alterations in E. coli metabolism in dependence of the rate of recombinant protein production, (13)C-tracer-based metabolic flux analysis in differently induced cultures was used. To avoid dilution of the (13)C-tracer signal by the culture history, the recombinant protein produced was used as a flux probe, i.e., as a read out of intracellular flux distributions. In detail, an increase in the generation rate rising from 36 mmol(ATP)g(CDW)(-1)h(-1) for the reference strain to 45 mmol(ATP)g(CDW)(-1)h(-1) for the highest yielding strain was observed during batch cultivation. Notably, the flux through the TCA cycle was rather constant at 2.5±0.1 mmol g(CDW)(-1)h(-1), hence was independent of the induced strength for gene expression. E. coli compensated for the additional energy demand of recombinant protein synthesis by reducing the biomass formation to almost 60%, resulting in excess NADPH. Speculative, this excess NADPH was converted to NADH via the soluble transhydrogenase and subsequently used for ATP generation in the electron transport chain. In this study, the metabolic burden was quantified by the biomass yield on ATP, which constantly decreased from 11.7g(CDW)mmol(ATP)(-1) for the reference strain to 4.9g(CDW)mmol(ATP)(-1) for the highest yielding strain. The insights into the operation of the metabolism of E. coli during recombinant protein production might guide the optimization of microbial hosts and fermentation conditions.