Kavšček2015 - Genome-scale metabolic model of Yarrowia lipolytica (iMK735)
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ABSTRACT:
Kavšček2015 - Genome-scale
metabolic model of Yarrowia lipolytica (iMK735)
This model is described in the article:
Optimization of lipid
production with a genome-scale model of Yarrowia
lipolytica.
Kavšček M, Bhutada G, Madl
T, Natter K.
BMC Syst Biol 2015; 9: 72
Abstract:
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.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.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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SUBMITTER: Nicolas Rodriguez
PROVIDER: MODEL1510060001 | BioModels | 2016-01-20
REPOSITORIES: BioModels
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