Engineering polygenic traits in S. cerevisiae

Metabolic engineering is one of the key elements enabling contemporary microbial biotechnology. Design of improved industrial strains based on the knowledge about microbial cellular processes has given rise to an unprecedented improvement in the productivity of these strains. In this study, will focus on the yeast Saccharomyces cerevisiae, a eukaryotic model organism which is also one of the most frequently used microorganisms in biotechnology with various successful applications from bulk chemicals to protein production. Thousands of different yeast strains are stored in strain collections and due to their genetic diversity, they represent an enormous pool of phenotypic variability. Most of the biotechnologically important phenotypes, such as tolerance to various environmental stresses, are polygenic. Therefore, the identification of the genes that contribute to such a phenotype and its quantitative transfer between strains is not as simple as for Mendelian traits. In this project we will apply the methodology to identify and edit causative genes and alleles for polygenic traits in yeast, which has recently been developed by the collaborating research groups of this project. We will focus on two biotechnologically relevant traits: thermotolerance and protein secretion efficiency. Strains with extreme values of the two biotechnologically important polygenic traits will be selected and analyzed by state-of-the-art polygenic trait analysis methods. The identified causative genetic variants will be transferred to industrial yeast strains using CRISPR-Cas genome editing, thus creating a pipeline to engineer industrial yeast strains with additional biotechnologically important traits. We will assess the effects of thermotolerance in a strain that is engineered for the production of high amounts of unusual lipids, and of protein secretion capability in a strain engineered for the secretion of a nanobody against the SARS-CoV-2 spike protein. This is a proof-of-principle study to demonstrate the power of advanced genetic methods in the analysis of polygenic traits. The results of this project will not only improve our understanding of the investigated phenotypes, but they will also illustrate the potential of the use of large strain collections for such studies in general. Finally, the possibility to determine a set of causal alleles required for a certain phenotype will be important for the engineering of improved industrial strains. Principal investigators of the proposed projects are Uroš Petrovič from the Jožef Stefan Institute, Ljubljana (Slovenia), and Klaus Natter from the University Graz (Austria). The project team of the proposed project includes researchers who have been involved in the key studies enabling the execution of such a project. All the required expertise, and also necessary research equipment is available at the collaborating research institutions. The project team is therefore uniquely suited to carry out this cutting-edge project with worldwide importance in the field of biotechnology.