In silico aided metabolic engineering of Saccharomyces cerevisiae for improved bioethanol production
Research output: Contribution to journal › Journal article › Research › peer-review
In silico genome-scale cell models are promising tools for accelerating the design of cells with improved and desired properties. We demonstrated this by using a genome-scale reconstructed metabolic network of Saccharomyces cerevisiae to score a number of strategies for metabolic engineering of the redox metabolism that will lead to decreased glycerol and increased ethanol yields on glucose under anaerobic conditions. The best-scored strategies were predicted to completely eliminate formation of glycerol and increase ethanol yield with 10%. We successfully pursued one of the best strategies by expressing a non-phosphorylating, NADP+-dependent glyceraldehyde-3-phosphate dehydrogenase in S. cerevisiae. The resulting strain had a 40% lower glycerol yield on glucose while the ethanol yield increased with 3% without affecting the maximum specific growth rate. Similarly, expression of GAPN in a strain harbouring xylose reductase and xylitol dehydrogenase led to an improvement in ethanol yield by up to 25% on xylose/glucose mixtures.
Original language | English |
---|---|
Journal | Metabolic Engineering |
Volume | 8 |
Issue number | 2 |
Pages (from-to) | 102-111 |
Number of pages | 10 |
ISSN | 1096-7176 |
DOIs | |
Publication status | Published - 2006 |
Externally published | Yes |
- Ethanol, Genome-scale model, Glycerol, Non-phosphorylating NADP-dependent glyceraldehydes-3-phosphate dehydrogenase, Redox metabolism, Saccharomyces cerevisiae, Xylose
Research areas
ID: 239904834