Journal
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
Volume 4, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fbioe.2016.00076
Keywords
flux analysis; C-13 metabolic flux analysis; -omits data; predictive biology; metabolic engineering
Funding
- NNF Center for Biosustainability [Synthetic Biology Tools for Yeast] Funding Source: researchfish
- Novo Nordisk Fonden [NNF10CC1016517] Funding Source: researchfish
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Efficient redirection of microbial metabolism into the abundant production of desired bioproducts remains non-trivial. Here, we used flux-based modeling approaches to improve yields of fatty acids in Saccharomyces cerevisiae. We combined C-13 labeling data with comprehensive genome-scale models to shed light onto microbial metabolism and improve metabolic engineering efforts. We concentrated on studying the balance of acetyl-CoA, a precursor metabolite for the biosynthesis of fatty acids. A genomewide acetyl-CoA balance study showed ATP citrate lyase from Yarrowia lipolytica as a robust source of cytoplasmic acetyl-CoA and malate synthase as a desirable target for downregulation in terms of acetyl-CoA consumption. These genetic modifications were applied to S. cerevisiae WRY2, a strain that is capable of producing 460 mg/L of free fatty acids. With the addition of ATP citrate lyase and downregulation of malate synthase, the engineered strain produced 26% more free fatty acids. Further increases in free fatty acid production of 33% were obtained by knocking out the cytoplasmic glycerol-3-phosphate dehydrogenase, which flux analysis had shown was competing for carbon flux upstream with the carbon flux through the acetyl-CoA production pathway in the cytoplasm. In total, the genetic interventions applied in this work increased fatty acid production by similar to 70%.
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