The development and validation of new methods to help direct rational strain design for metabolite overproduction remains an important problem in metabolic engineering. Here we show that computationally predicted E. coli strain designs, calculated from a genome-scale metabolic model, can lead to successful production strains and that adaptive evolution of the engineered strains can lead to improved production capabilities. Three strain designs for lactate production were implemented yielding a total of 11 evolved production strains that were used to demonstrate the utility of this integrated approach. Strains grown on 2 g/L glucose at 37 degrees C showed lactate titers ranging from 0.87 to 1.75 g/L and secretion rates that were directly coupled to growth rates.

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