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Using regulatory information to manipulate glycerol metabolism in Saccharomyces cerevisiae
- Hou, Jin, Vemuri, Goutham N.
- Applied microbiology and biotechnology 2010 v.85 no.4 pp. 1123-1130
- NAD (coenzyme), Saccharomyces cerevisiae, aerobiosis, biomass, carbon, enzymes, factories, fermentation, gene overexpression, genes, glycerol, metabolic engineering, mutagenesis, oxidative phosphorylation, screening, specific growth rate
- Metabolic engineering has emerged as an attractive alternative to random mutagenesis and screening to design cell factories for industrial fermentation processes. The design of metabolic networks has been realized by gene deletions or strong overexpression of heterologous genes. There is an increasing body of evidence that indicates complete inactivation of native genes and high-level activity of heterologous enzymes may be deleterious to the cell. To moderately implement their expression, genes of interest are expressed under the control of promoters with different strengths. Constructing a promoter library is labor-intensive and requires precise quantification of the promoter strength. However, when the mechanisms of pathway regulation are known, it is possible to exploit this information to effect genetic changes efficiently. We report the implementation of this concept to reducing glycerol production during aerobic growth of Saccharomyces cerevisiae. Glycerol is produced to dispose excess cytosolic reduced nicotinamide adenine dinucleotide (NADH), and the regulating step in the pathway is mediated by glycerol 3-phosphate dehydrogenase (encoded by GPD1 and GPD2 genes). We expressed NADH oxidase in S. cerevisiae under the control of the GPD2 promoter to modulate the decrease in cytosolic NADH to the right level where the heterologous enzyme does not compete with oxidative phosphorylation while at the same time, decreasing glycerol production. This metabolic design resulted in substantially decreasing glycerol production and indeed, the excess carbon was redirected to biomass, resulting in a 14% increase in the specific growth rate. We believe that such strategies are more efficient than conventional methods and will find applications in bioprocesses.