Tolerance to high levels of ethanol is an ecologically and industrially relevant phenotype of microbes, but the molecular mechanisms underlying this complex trait remain largely unknown. Here, we use long-term experimental evolution of isogenic yeast populations of different initial ploidy to study adaptation to increasing levels of ethanol. Whole-genome sequencing of more than 30 evolved populations and over 100 adapted clones isolated throughout this two-year evolution experiment revealed how a complex interplay of de novo single nucleotide mutations, copy number variation, ploidy changes, mutator phenotypes, and clonal interference led to a significant increase in ethanol tolerance. Although the specific mutations differ between different evolved lineages, application of a novel computational pipeline, PheNetic, revealed that many mutations target functional modules involved in stress response, cell cycle regulation, DNA repair and respiration. Measuring the fitness effects of selected mutations introduced in non-evolved ethanol-sensitive cells revealed several adaptive mutations that had previously not been implicated in ethanol tolerance, including mutations in PRT1, VPS70 and MEX67. Interestingly, variation in VPS70 was recently identified as a QTL for ethanol tolerance in an industrial bio-ethanol strain. Taken together, our results show how, in contrast to adaptation to some other stresses, adaptation to a continuous complex and severe stress involves interplay of different evolutionary mechanisms. In addition, our study reveals functional modules involved in ethanol resistance and identifies several mutations that could help to improve the ethanol tolerance of industrial yeasts. Organisms can evolve resistance to specific stress factors, which allows them to thrive in environments where non-adapted organisms fail to grow. However, the molecular mechanisms that underlie adaptation to complex stress factors that interfere with basic cellular processes are poorly understood. In this study, we reveal how yeast populations adapt to high ethanol concentrations, an ecologically and industrially relevant stress that is still poorly understood. We exposed six independent populations of genetically identical yeast cells to gradually increasing ethanol levels, and we monitored the changes in their DNA sequence over a two-year period. Together with novel computational analyses, we could identify the mutational dynamics and molecular mechanisms underlying increased ethanol resistance. Our results show how adaptation to high ethanol is complex and can be reached through different mutational pathways. Together, our study offers a detailed picture of how populations adapt to a complex continuous stress and identifies several mutations that increase ethanol resistance, which opens new routes to obtain superior biofuel yeast strains.

In the yeast Saccharomyces cerevisiae, two NADP⁺-dependent glutamate dehydrogenases (NADP-GDHs) encoded by GDH1 andGDH3 catalyze the synthesis of glutamate from ammonium and α-ketoglutarate. The GDH2-encoded NAD⁺-dependent glutamate dehydrogenase degrades glutamate producing ammonium and α-ketoglutarate. Until very recently, it was considered that only one biosynthetic NADP-GDH was present in S. cerevisiae. This fact hindered understanding the physiological role of each isoenzyme and the mechanisms involved in α-ketoglutarate channeling for glutamate biosynthesis. In this study, we purified and characterized the GDH1- andGDH3-encoded NADP-GDHs; they showed different allosteric properties and rates of α-ketoglutarate utilization. Analysis of the relative levels of these proteins revealed that the expression ofGDH1 and GDH3 is differentially regulated and depends on the nature of the carbon source. Moreover, the physiological study of mutants lacking or overexpressing GDH1 orGDH3 suggested that these genes play nonredundant physiological roles. Our results indicate that the coordinated regulation of GDH1-, GDH3-, andGDH2-encoded enzymes results in glutamate biosynthesis and balanced utilization of α-ketoglutarate under fermentative and respiratory conditions. The possible relevance of the duplicated NADP-GDH pathway in the adaptation to facultative metabolism is discussed.

Many duplicate genes maintain functional overlap despite divergence over long evolutionary time scales. Deleting one member of a paralogous pair often has no phenotypic effect, unless its paralog is also deleted. It has been suggested that this functional compensation might be mediated by active up-regulation of expression of a gene in response to deletion of its paralog. However, it is not clear how prevalent such paralog responsiveness is, nor whether it is hardwired or dependent on feedback from environmental conditions. Here, we address these questions at the genomic scale using high-throughput flow cytometry of single-cell protein levels in differentially labeled cocultures of wild-type and paralog-knockout Saccharomyces cerevisiae strains. We find that only a modest fraction of proteins (22 out of 202) show significant up-regulation to deletion of their duplicate genes. However, these paralog-responsive proteins match almost exclusively duplicate pairs whose overlapping function is required for growth. Moreover, media conditions that add or remove requirements for the function of a duplicate gene pair specifically eliminate or create paralog responsiveness. Together, our results suggest that paralog responsiveness in yeast is need-based: it appears only in conditions in which the gene function is required. Physiologically, such need-based responsiveness could provide an adaptive mechanism for compensation of genetic, environmental, or stochastic perturbations in protein abundance. Despite sequence divergence over long evolutionary times, many genes that have undergone duplication can still compensate for the loss of their duplicates. This compensation depends, not only on functional overlap between the paralogous genes, but also on overlap in their expression patterns. It has been proposed that compensation might therefore involve active up-regulation of a gene in response to deletion of its paralog. To test for such paralog responsiveness in the yeast Saccharomyces cerevisiae, we systematically measured changes in single-cell protein levels for approximately 200 duplicate genes in the presence or absence of their paralogs. Only a small fraction (∼11%) of proteins increased in level in response to deletion of their paralog, but this set matched almost exclusively the subset of paralogs whose overlapping function is required for viability. Further, when we examined yeast grown in different media, we found that genes had either gained or lost paralog responsiveness exactly according to their importance for growth in the tested conditions. Responsiveness, therefore, is need-based: it appears only in conditions in which the function of one or both paralogs is required. We propose that such need-based responsiveness of duplicate genes could play an important adaptive role, not just in the artificial event of paralog deletion, but also in the maintenance of functions that are compromised by natural genetic, environmental, or stochastic perturbations.

Lifespan is influenced by a large number of conserved proteins and gene-regulatory pathways. Here, we introduce a strategy for systematically finding such longevity factors in Saccharomyces cerevisiae and scoring the genetic interactions (epistasis) among these factors. Specifically, we developed an automated competition-based assay for chronological lifespan, defined as stationary-phase survival of yeast populations, and used it to phenotype over 5,600 single- or double-gene knockouts at unprecedented quantitative resolution. We found that 14% of the viable yeast mutant strains were affected in their stationary-phase survival; the extent of true-positive chronological lifespan factors was estimated by accounting for the effects of culture aeration and adaptive regrowth. We show that lifespan extension by dietary restriction depends on the Swr1 histone-exchange complex and that a functional link between autophagy and the lipid-homeostasis factor Arv1 has an impact on cellular lifespan. Importantly, we describe the first genetic interaction network based on aging phenotypes, which successfully recapitulated the core-autophagy machinery and confirmed a role of the human tumor suppressor PTEN homologue in yeast lifespan and phosphatidylinositol phosphate metabolism. Our quantitative analysis of longevity factors and their genetic interactions provides insights into the gene-network interactions of aging cells. The budding yeast Saccharomyces cerevisiae has emerged as an important model for the genetic analysis of aging, and insights gained about this process in yeast cells enhance our understanding of aging in other organisms, including humans. Even in yeast, our knowledge of the number and identity of the genes that determine lifespan is limited and we are still lacking a general picture of how different genetic aging factors work together. Here, using an innovative sensitive technique, we have characterized the stationary-phase survival of yeast single- and double-gene knockout mutants to screen for genes that control chronological aging and to score the genetic interactions among these genes. Our results showed that an important fraction (14%) of the genome contributes to the regulation of lifespan, including genes and pathways that had not been previously associated to this phenotype. We also constructed a genetic interaction map which recapitulated lifespan-determining pathways and highlighted genetic associations between the autophagy machinery and the phosphatidylinositol-phosphate and lipid-homeostasis pathways. Our study provides not only an accurate catalogue of yeast aging genes, but also a picture of the gene-network wiring of aging cells.