Fat from wood: Optimizing the yeast Yarrowia lipolytica for defined composition food oil production from lignocellulosic hydrolysate
The purpose of this project is to produce food oil from renewable carbon sources. We aim to develop strains of the oil accumulating yeast Yarrowia lipolytica which can rapidly produce triglyceride "oil", with defined composition, to higher final levels during growth on lignocellulosic hydrolysate medium.
Rapid and high oil production, combined with tolerance to inhibitory compounds in hydrolysate, will be achieved by repetitions of an adaptive laboratory evolution procedure, in which centrifugation based enrichment for high-oil cells is alternated with growth of the these cells in increasing concentration of inhibitors. Characterization of isolated strains will be carried out with regard to growth related parameters, lipid content and composition as well as use of carbon sources. The genomes of the best strains will be sequenced to identify the underlying mutations.
Identification of target genes which are suitable candidates for mutation in order to alter lipid composition will be identified, from gene expression and lipid composition data, from chemostat experiments in which different nitrogen sources and growth temperatures are used.
The relevance of identified target genes from both the evolution experiments and the screen for lipid composition alterations will be tested by insertions and deletions in the original strain of Y. lipolytica.
With a succesful project outcome, a yeast based production of oil with defined fatty acid composition would become feasible.
Jens B Nielsen (contact)
Full Professor at Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Education Administrator at Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Project ID: 2017-01281
Funding Chalmers participation during 2018–2021
Related Areas of Advance and Infrastructure
Chalmers Infrastructure for Mass spectrometry
Areas of Advance
C3SE (Chalmers Centre for Computational Science and Engineering)
Life Science Engineering (2010-2018)
Areas of Advance