Species of Saccharomyces genus have played an irreplaceable role in alcoholic beverage and baking industry for centuries. S. cerevisiae has also become an organism of choice for industrial production of alcohol and other valuable chemicals and a model organism shaping the rise of modern genetics and genomics in the past few decades. Today´s brewing industry faces challenges of decreasing consumption of traditional beer styles and increasing consumer demand for new styles, flavors and aromas. The number of currently used brewer's strains and their genetic diversity is yet limited and implementation of more genetic and phenotypic variation is seen as a solution to cope with the market challenges. This requires modification of current production strains or introduction of novel strains from other settings, e.g. industrial or wild habitats into the brewing industry. Due to legal regulation in many countries and negative customer perception of GMO organisms, the production of food and beverages requires non-GMO production organisms, whose development can be difficult and time-consuming. Here, we apply FIND-IT (Fast Identification of Nucleotide variants by DigITal PCR), an ultrafast genome-mining method, for isolation of novel yeast variants with varying flavor profiles. The FIND-IT method uses combination of random mutagenesis, droplet digital PCR with probes that target a specific desired mutation and a sub-isolation of the mutant clone. Such an approach allows the targeted identification and isolation of specific mutant strains with eliminated production of certain flavor and off-flavors and/or changes in the strain metabolism. We demonstrate that the technology is useful for the identification of loss-of function or gain of function mutations in unrelated industrial and wild strains differing in ploidy. Where no other phenotypic selection exists, this technology serves together with standard breeding techniques as a modern tool facilitating a modification of (brewer's) yeast strains leading to diversification of the product portfolio.

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Journal Article

Authors

Stovicek V, Lengeler KB, Wendt T, Rasmussen M, Katz M, Förster J

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