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Kavšček, M.* ; Bhutada, G.* ; Madl, T. ; Natter, K.*

Optimization of lipid production with a genome-scale model of Yarrowia lipolytica.

BMC Syst. Biol. 9:72 (2015)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Background: Yarrowia lipolytica is a non-conventional yeast that is extensively investigated for its ability to excrete citrate or to accumulate large amounts of storage lipids, which is of great significance for single cell oil production. Both traits are thus of interest for basic research as well as for biotechnological applications but they typically occur simultaneously thus lowering the respective yields. Therefore, engineering of strains with high lipid content relies on novel concepts such as computational simulation to better understand the two competing processes and to eliminate citrate excretion. Results: Using a genome-scale model (GSM) of baker's yeast as a scaffold, we reconstructed the metabolic network of Y. lipolytica and optimized it for use in flux balance analysis (FBA), with the aim to simulate growth and lipid production phases of this yeast. We validated our model and found the predictions of the growth behavior of Y. lipolytica in excellent agreement with experimental data. Based on these data, we successfully designed a fed-batch strategy to avoid citrate excretion during the lipid production phase. Further analysis of the network suggested that the oxygen demand of Y. lipolytica is reduced upon induction of lipid synthesis. According to this finding we hypothesized that a reduced aeration rate might induce lipid accumulation. This prediction was indeed confirmed experimentally. In a fermentation combining these two strategies lipid content of the biomass was increased by 80 %, and lipid yield was improved more than four-fold, compared to standard conditions. Conclusions: Genome scale network reconstructions provide a powerful tool to predict the effects of genetic modifications and the metabolic response to environmental conditions. The high accuracy and the predictive value of a newly reconstructed GSM of Y. lipolytica to optimize growth conditions for lipid accumulation are demonstrated. Based on these findings, further strategies for engineering Y. lipolytica towards higher efficiency in single cell oil production are discussed.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Citrate ; Fed-batch Fermentation ; Flux Balance Analysis ; Oleaginous Yeast ; Oxygen Limitation
Sprache englisch
Veröffentlichungsjahr 2015
HGF-Berichtsjahr 2015
e-ISSN 1752-0509
Zeitschrift BMC Systems Biology
Quellenangaben Band: 9, Heft: , Seiten: , Artikelnummer: 72 Supplement: ,
Verlag BioMed Central
Begutachtungsstatus Peer reviewed
POF Topic(s) 30505 - New Technologies for Biomedical Discoveries
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-552800-001
PubMed ID 26503450
Scopus ID 84945151760
Erfassungsdatum 2015-11-04