Metabolic engineering of escherichia coli for the production of L-valine based on systems biotechnology

Abstract

The L-valine production strain of Escherichia coli was constructed by rational metabolic engineering and stepwise improvement based on transcriptome analysis and gene knock-out simulation of the in silico genome scale metabolic network. Feedback inhibition of acetohydroxy acid synthase isoenzyme III by L-valine was removed by site-directed mutagenesis and the native promoter containing the transcriptional attenuator leader regions of the ilvGMEDA and ilvBN operon were replaced with the tac promoter. The ilvA, leuA and panB genes were deleted to make more precursors available for L-valine biosynthesis. This engineered Val strain harboring a plasmid overexpressing the ilvBN genes produced 1.31 g/liter L-valine. Comparative transcriptome profiling was performed during batch fermentation of the engineered and control strains. Among the down-regulated genes, the lrp and ygaZH genes, which encode a global regulator Lrp and L-valine exporter, respectively, were overexpressed. Amplification of the lrp, ygaZH, and lrp-ygaZH genes led to the enhanced production of L-valine by 21.6%, 47.1%, and 113%, respectively. Further improvement was achieved by using in silico gene knock-out simulation, which identified the aceF, mdh and pfkA genes as knock-out targets. The VAMF strain $(Val \Delta aceF \Delta mdh \Delta pfkA)$ overexpressing the ilvBN, ilvCED, ygaZH and lrp genes was able to produce 7.55 g/liter L-valine from 20 g/liter glucose in batch culture, resulting in a high yield of 0.378 g L-valine per g glucose. Finally, the Val strain harboring pKBRilv$BN^{mut}$CED and pTrc184ygaZHlrp, which has feedback inhibition-resistant AHAS (acetohydroxy acid synthase) I, produced 18.37 g/liter L-valine by fed-batch fermentation with 200 g glucose. These results suggest that an industrially competitive strain can be efficiently developed by metabolic engineering based on combined rational modification, transcriptome profiling and systems-level in silico analysis.