L-Valine

Appl Environ Microbiol. 2007 Apr;73(7):2079-84.

L-valine production with pyruvate dehydrogenase complex-deficient Corynebacterium glutamicum.[Pubmed: 17293513 ]

METHODS AND RESULTS:
Corynebacterium glutamicum was engineered for the production of L-Valine from glucose by deletion of the aceE gene encoding the E1p enzyme of the pyruvate dehydrogenase complex and additional overexpression of the ilvBNCE genes encoding the L-Valine biosynthetic enzymes acetohydroxyacid synthase, isomeroreductase, and transaminase B. In the absence of cellular growth, C. glutamicum DeltaaceE showed a relatively high intracellular concentration of pyruvate (25.9 mM) and produced significant amounts of pyruvate, L-alanine, and L-Valine from glucose as the sole carbon source. Lactate or acetate was not formed. Plasmid-bound overexpression of ilvBNCE in C. glutamicum DeltaaceE resulted in an approximately 10-fold-lower intracellular pyruvate concentration (2.3 mM) and a shift of the extracellular product pattern from pyruvate and L-alanine towards L-Valine.
CONCLUSIONS:
In fed-batch fermentations at high cell densities and an excess of glucose, C. glutamicum DeltaaceE(pJC4ilvBNCE) produced up to 210 mM L-Valine with a volumetric productivity of 10.0 mM h(-1) (1.17 g l(-1) h(-1)) and a maximum yield of about 0.6 mol per mol (0.4 g per g) of glucose.

Biotechnol Bioeng. 2005 Aug 5;91(3):356-68.

Application of model discriminating experimental design for modeling and development of a fermentative fed-batch L-valine production process.[Pubmed: 15984033]

A model discriminating experimental design approach for fed-batch processes has been developed and applied to the fermentative production of L-Valine by a genetically modified Corynebacterium glutamicum strain possessing multiple auxotrophies as an example.
METHODS AND RESULTS:
Being faced with the typical situation of uncertain model information based on preliminary experiments, model discriminating design was successfully applied to improve discrimination between five competing models. Within the same modeling and experimental design framework, also the planning of an optimized production process with respect to the total volumetric productivity is shown. Simulation results were experimentally affirmed, yielding an increased total volumetric productivity of 6.2 mM L-Valine per hour.
CONCLUSIONS:
However, also so far unknown metabolic mechanisms were observed in the optimized process, underlining the importance of process optimization during modeling to avoid problems of extreme extrapolation of model predictions during the final process optimization.