Genome-scale modeling enables metabolic engineering of Saccharomyces cerevisiae for succinic acid production.

In this work, we describe the application of a genome-scale metabolic model and flux balance analysis for the prediction of succinic acid overproduction strategies in Saccharomyces cerevisiae. The top three single gene deletion strategies, Δ mdh1, Δ oac1, and Δ dic1, were tested using knock-out strains cultivated anaerobically on glucose, coupled with physiological and DNA microarray characterization. While Δ mdh1 and Δ oac1 strains failed to produce succinate, Δ dic1 produced 0.02 C-mol/C-mol glucose, in close agreement with model predictions (0.03 C-mol/C-mol glucose). Transcriptional profiling suggests that succinate formation is coupled to mitochondrial redox balancing, and more specifically, reductive TCA cycle activity. While far from industrial titers, this proof-of-concept suggests that in silico predictions coupled with experimental validation can be used to identify novel and non-intuitive metabolic engineering strategies. [ABSTRACT FROM AUTHOR]