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BIOTEK2021-Bioteknologi for verdiskaping

GMO free systems optimization of wine yeast for wine production by massive scale directed evolution

Awarded: NOK 5.1 mill.

Industrial scale wine production is hampered by wine yeasts' ability to fully use available nutrients in grape must. This leaves compounds in the wine that may reduce its quality, or that allow unwanted microorganisms to grow and produce foul tasting or unhealthy by-products. The economic losses associated with this problem are substantial. Starting from wine yeasts currently used by the industry, we have produced 20,000 non-GMO wine yeasts, some with improved performance through a combination of laboratory work and computer modelling. We have tested 40 of the best performing wine yeasts in small-scale production on synthetic wine must. From these, we selected 4 strains for actual wine production to quantify their production properties. Our approach will serve as a proof of concept for a new paradigm to improve properties of microorganisms of industrial importance in a fast, cheap and GMO-free manner.

Ved avslutning av prosjektet hadde vi oppnådd alle hovedmålene fra da vi startet: Vi hadde evolvert et stort antall gjærstammer i flere situasjoner slik at vi kunne identifisere de som hadde oppnådd nye og ønskede egenskaper. Vi hadde muligheten til å prøve ut 4 evolverte gjærstammer i faktisk vinproduksjon. Resultatet av dette prosjektet var ikke bare at vi hadde demonstrert at konseptet fungerte, men det internasjonale forskerteamet utviklet unik tverrfaglig kompetanse: bruk av en eksperimental evolusjonsplattform i kombinasjon med avansert data modellering. Som et resultat av dette arbeidet og den økede kompetansen, har forskerteamet hatt suksess i å søke på EU midler i et relatert prosjekt, der det tette samspillet mellom evolusjonplatformen og data modellering / simulering blir videreutviklet (Prosjekt "CoolWine").

Industrial wine production at an estimated yearly value of 100 billion ? is hampered by poor evolutionary adaptation of yeast to grape musts, creating powerful incentives for optimizing wine yeast lineages of industrial relevance. Due to consumer aversion against genetically modified organisms (GMO), efforts to enhance wine yeasts for wine production through synthetic biology approaches have had little commercial impact. We propose to optimize wine yeast nitrogen and carbon use by a GMO free, massively parallelized directed laboratory evolution coupled with computational modeling and analysis. The scale maximizes chances that lineages with both enhanced carbon and nitrogen utilization and lacking negative effects on other industrial traits emerge. Multiple -omics data will be fed into constraint based models of yeast carbon and nitrogen metabolism to allow prediction of metabolite phenotypes critical to wine production. Iterative rounds of data acquisition and modeling will successively down-select the >10.000 evolved populations to crystalize out those that are of true wine industrial value. Our end product is a large set of wine yeasts that are (1) based on commercially established lineages but that (2) have superior carbon and nitrogen utilization properties with no negative effects on other traits of industrial interest. Analysis of top performers in a semi-industrial setting will validate the pipeline. The proposed platform will serve as a proof of concept for a new paradigm to optimize properties of industrial microorganisms in a fast, cheap and GMO free manner.

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BIOTEK2021-Bioteknologi for verdiskaping