Laboratory evolution of the yeast Saccharomyces cerevisiae in bioreactor batch cultures yielded variants that grow as multicellular, fast-sedimenting clusters. Knowledge of the molecular basis of this phenomenon may contribute to the understanding of natural evolution of multicellularity and to manipulating cell sedimentation in laboratory and industrial applications of S. cerevisiae. Multicellular, fast-sedimenting lineages obtained from a haploid S. cerevisiae strain in two independent evolution experiments were analyzed by whole genome resequencing. The two evolved cell lines showed different frameshift mutations in a stretch of eight adenosines in ACE2, which encodes a transcriptional regulator involved in cell cycle control and mother-daughter cell separation. Introduction of the two ace2 mutant alleles into the haploid parental strain led to slow-sedimenting cell clusters that consisted of just a few cells, thus representing only a partial reconstruction of the evolved phenotype. In addition to single-nucleotide mutations, a whole-genome duplication event had occurred in both evolved multicellular strains. Construction of a diploid reference strain with two mutant ace2 alleles led to complete reconstruction of the multicellular-fast sedimenting phenotype. This study shows that whole-genome duplication and a frameshift mutation in ACE2 are sufficient to generate a fast-sedimenting, multicellular phenotype in S. cerevisiae. The nature of the ace2 mutations and their occurrence in two independent evolution experiments encompassing fewer than 500 generations of selective growth suggest that switching between unicellular and multicellular phenotypes may be relevant for competitiveness of S. cerevisiae in natural environments.

Successful reverse engineering of mutants that have been obtained by nontargeted strain improvement has long presented a major challenge in yeast biotechnology. This paper reviews the use of genome-wide approaches for analysis of Saccharomyces cerevisiae strains originating from evolutionary engineering or random mutagenesis. On the basis of an evaluation of the strengths and weaknesses of different methods, we conclude that for the initial identification of relevant genetic changes, whole genome sequencing is superior to other analytical techniques, such as transcriptome, metabolome, proteome, or array-based genome analysis. Key advantages of this technique over gene expression analysis include the independency of genome sequences on experimental context and the possibility to directly and precisely reproduce the identified changes in naive strains. The predictive value of genome-wide analysis of strains with industrially relevant characteristics can be further improved by classical genetics or simultaneous analysis of strains derived from parallel, independent strain improvement lineages.