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Variation in gene copy number can alter gene expression and influence downstream phenotypes; thus copy-number variation (CNV) provides a route for rapid evolution if the benefits outweigh the cost. We recently showed that genetic background significantly influences how yeast cells respond to gene over-expression (OE), revealing that the fitness costs of CNV can vary substantially with genetic background in a common-garden environment. But the interplay between CNV tolerance and environment remains unexplored on a genomic scale. Here we measured the tolerance to gene OE in four genetically distinctSaccharomyces cerevisiaestrains grown under sodium chloride (NaCl) stress. OE genes that are commonly deleterious during NaCl stress recapitulated those commonly deleterious under standard conditions. However, NaCl stress uncovered novel differences in strain responses to gene OE. West African strain NCYC3290 and North American oak isolate YPS128 are more sensitive to NaCl stress than vineyard BC187 and laboratory strain BY4743. Consistently, NCYC3290 and YPS128 showed the greatest sensitivities to gene OE. Although most genes were deleterious, hundreds were beneficial when overexpressed – remarkably, most of these effects were strain specific. Few beneficial genes were shared between the NaCl-sensitive isolates, implicating mechanistic differences behind their NaCl sensitivity. Transcriptomic analysis suggested underlying vulnerabilities and tolerances across strains, and pointed to natural CNV of a sodium export pump that likely contributes to strain-specific responses to OE of other genes. Our results reveal extensive strain-by-environment interaction in the response to gene CNV, raising important implications for the accessibility of CNV-dependent evolutionary routes under times of stress.

Organisms have evolved elaborate physiological pathways that regulate growth, proliferation, metabolism, and stress response. These pathways must be properly coordinated to elicit the appropriate response to an ever-changing environment. While individual pathways have been well studied in a variety of model systems, there remains much to uncover about how pathways are integrated to produce systemic changes in a cell, especially in dynamic conditions. We previously showed that deletion of Protein Kinase A (PKA) regulatory subunitBCY1can decouple growth and metabolism inSaccharomyces cerevisiaeengineered for anaerobic xylose fermentation, allowing for robust fermentation in the absence of division. This provides an opportunity to understand how PKA signaling normally coordinates these processes. Here, we integrated transcriptomic, lipidomic, and phosphor-proteomic responses upon a glucose to xylose shift across a series of strains with different genetic mutations promoting either coupled or decoupled xylose-dependent growth and metabolism. Together, results suggested that defects in lipid homeostasis limit growth in thebcy1Δstrain despite robust metabolism. To further understand this mechanism, we performed adaptive laboratory evolutions to re-evolve coupled growth and metabolism in thebcy1Δparental strain. Genetic mutations in PKA subunitTPK1and lipid regulatorOPI1, among other genes underscored a role for lipid homeostasis, which was further supported by evolved changes in lipid profiles and gene expression. We suggest several models for how cells coordinate growth, metabolism, and other responses in budding yeast and how restructuring these processes enables anaerobic xylose utilization.Author SummaryAll organisms utilize an energy source to generate the cellular resources needed to grow and divide. These individual processes have been well study, but the coordination and crosstalk between the process is not well understood. To study growth and metabolism coupling, we used a yeast strain that was genetically engineered to ferment the sugar xylose but lacked growth on the sugar. The decoupled growth and metabolism was caused by a single gene deletion in a highly conserved signaling pathway found in all eukaryotes. While our work is focused on xylose metabolism, we address the fundamental question of how cells coordinate growth with metabolism under non-ideal conditions. We identified vast changes in gene expression that implicated altered regulatory mechanisms involved in lipid metabolism correlating with decouple growth and metabolism. Our work highlights the complexity of engineering new cellular functions and that global regulatory modifications, rather than altering individual pathways, may be required for broad cellular changes.

Stress defense and cell growth are inversely related in bulk culture analyses; however, these studies miss substantial cell-to-cell heterogeneity, thus obscuring true phenotypic relationships. Here, we devised a microfluidics system to characterize multiple phenotypes in single yeast cells over time before, during, and after salt stress. The system measured cell and colony size, growth rate, and cell-cycle phase along with nuclear trans-localization of two transcription factors: stress-activated Msn2 that regulates defense genes and Dot6 that represses ribosome biogenesis genes during an active stress response. By tracking cells dynamically, we discovered unexpected discordance between Msn2 and Dot6 behavior that revealed subpopulations of cells with distinct growth properties. Surprisingly, post-stress growth recovery was positively corelated with activation of the Dot6 repressor. In contrast, cells lacking Dot6 displayed slower growth acclimation, even though they grow normally in the absence of stress. We show that wild-type cells with a larger Dot6 response display faster production of Msn2-regulated Ctt1 protein, separable from the contribution of Msn2. These results are consistent with the model that transcriptional repression during acute stress in yeast provides a protective response, likely by redirecting translational capacity to induced transcripts.

Severe environmental stress can trigger a plethora of physiological changes and, in the process, significant cytoplasmic reorganization. Stress-activated RNA–protein granules have been implicated in this cellular overhaul by sequestering preexisting mRNAs and influencing their fates during and after stress acclimation. While the composition and dynamics of stress-activated granule formation have been well studied, their function and impact on RNA-cargo has remained murky. Several recent studies challenge the view that these granules degrade and silence mRNAs present at the onset of stress and instead suggest new roles for these structures in mRNA storage, transit, and inheritance. Here we discuss recent evidence for revised models of stress-activated granule functions and the role of these granules in stress survival and recovery.

The budding yeast Saccharomyces cerevisiae has been used extensively in fermentative industrial processes, including biofuel production from sustainable plant-based hydrolysates. Myriad toxins and stressors found in hydrolysates inhibit microbial metabolism and product formation. Overcoming these stresses requires mitigation strategies that include strain engineering. To identify shared and divergent mechanisms of toxicity and to implicate gene targets for genetic engineering, we used a chemical genomic approach to study fitness effects across a library of S. cerevisiae deletion mutants cultured anaerobically in dozens of individual compounds found in different types of hydrolysates. Relationships in chemical genomic profiles identified classes of toxins that provoked similar cellular responses, spanning inhibitor relationships that were not expected from chemical classification. Our results also revealed widespread antagonistic effects across inhibitors, such that the same gene deletions were beneficial for surviving some toxins but detrimental for others. This work presents a rich dataset relating gene function to chemical compounds, which both expands our understanding of plant-based hydrolysates and provides a useful resource to identify engineering targets.

CRISPR/Cas9 is a powerful tool for editing genomes, but design decisions are generally made with respect to a single reference genome. With population genomic data becoming available for an increasing number of model organisms, researchers are interested in manipulating multiple strains and lines. CRISpy-pop is a web application that generates and filters guide RNA sequences for CRISPR/Cas9 genome editing for diverse yeast and bacterial strains. The current implementation designs and predicts the activity of guide RNAs against more than 1000 Saccharomyces cerevisiae genomes, including 167 strains frequently used in bioenergy research. Zymomonas mobilis, an increasingly popular bacterial bioenergy research model, is also supported. CRISpy-pop is available as a web application (https://CRISpy-pop.glbrc.org/) with an intuitive graphical user interface. CRISpy-pop also cross-references the human genome to allow users to avoid the selection of guide RNAs with potential biosafety concerns. Additionally, CRISpy-pop predicts the strain coverage of each guide RNA within the supported strain sets, which aids in functional population genetic studies. Finally, we validate how CRISpy-pop can accurately predict the activity of guide RNAs across strains using population genomic data.

To cope with sudden changes in the external environment, the budding yeast Saccharomyces cerevisiae orchestrates a multifaceted response that spans many levels of physiology. Several studies have i...

Metabolic engineering strategies have been successfully implemented to improve the production of isobutanol, a next-generation biofuel, in

Copy number variation (CNV) through gene or chromosome amplification provides a route for rapid phenotypic variation and supports long-term evolution of gene functions. Although the evolutionary importance of CNV is known, little is understood about how genetic background influences CNV tolerance. Here, we measured fitness costs of over 4,000 over-expressed genes in 15 Saccharomyces cerevisiae strains representing different lineages, to explore natural variation in tolerating gene overexpression (OE). Strain-specific effects dominated the fitness costs of gene OE. We report global differences in the consequences of gene OE, independent of the amplified gene, as well as gene-specific effects that were dependent on the genetic background. Natural variation in the response to gene OE could be explained by several models, including strain-specific physiological differences, resource limitations, and regulatory sensitivities. This work provides new insight on how genetic background influences tolerance to gene amplification and the evolutionary trajectories accessible to different backgrounds.

Bottlenecks in the efficient conversion of xylose into cost-effective biofuels have limited the widespread use of plant lignocellulose as a renewable feedstock. The yeast Saccharomyces cerevisiae ferments glucose into ethanol with such high metabolic flux that it ferments high concentrations of glucose aerobically, a trait called the Crabtree/Warburg Effect. In contrast to glucose, most engineered S. cerevisiae strains do not ferment xylose at economically viable rates and yields, and they require respiration to achieve sufficient xylose metabolic flux and energy return for growth aerobically. Here, we evolved respiration-deficient S. cerevisiae strains that can grow on and ferment xylose to ethanol aerobically, a trait analogous to the Crabtree/Warburg Effect for glucose. Through genome sequence comparisons and directed engineering, we determined that duplications of genes encoding engineered xylose metabolism enzymes, as well as TKL1, a gene encoding a transketolase in the pentose phosphate pathway, were the causative genetic changes for the evolved phenotype. Reengineered duplications of these enzymes, in combination with deletion mutations in HOG1, ISU1, GRE3, and IRA2, increased the rates of aerobic and anaerobic xylose fermentation. Importantly, we found that these genetic modifications function in another genetic background and increase the rate and yield of xylose-to-ethanol conversion in industrially relevant switchgrass hydrolysate, indicating that these specific genetic modifications may enable the sustainable production of industrial biofuels from yeast. We propose a model for how key regulatory mutations prime yeast for aerobic xylose fermentation by lowering the threshold for overflow metabolism, allowing mutations to increase xylose flux and to redirect it into fermentation products.

Individuals carrying an aberrant number of chromosomes can vary widely in their expression of aneuploidy phenotypes. A major unanswered question is the degree to which an individual’s genetic makeup influences its tolerance of karyotypic imbalance. Here we investigated within-species variation in aneuploidy prevalence and tolerance, using Saccharomyces cerevisiae as a model for eukaryotic biology. We analyzed genotypic and phenotypic variation recently published for over 1,000 S. cerevisiae strains spanning dozens of genetically defined clades and ecological associations. Our results show that the prevalence of chromosome gain and loss varies by clade and can be better explained by differences in genetic background than ecology. The relationships between lineages with high aneuploidy frequencies suggest that increased aneuploidy prevalence emerged multiple times in S. cerevisiae evolution. Separate from aneuploidy prevalence, analyzing growth phenotypes revealed that some genetic backgrounds—such as the European Wine lineage—show fitness costs in aneuploids compared to euploids, whereas other clades with high aneuploidy frequencies show little evidence of major deleterious effects. Our analysis confirms that chromosome gain can produce phenotypic benefits, which could influence evolutionary trajectories. These results have important implications for understanding genetic variation in aneuploidy prevalence in health, disease, and evolution.

Individuals carrying an aberrant number of chromosomes can vary widely in their expression of aneuploidy phenotypes. A major unanswered question is the degree to which an individual’s genetic makeup influences its tolerance of karyotypic imbalance. Here we took a population genetics perspective to investigate the selective forces influencing aneuploidy prevalence in Saccharomyces cerevisiae populations as a model for eukaryotic biology. We analyzed genotypic and phenotypic variation recently published for over 1,000 S. cerevisiae strains spanning dozens of genetically defined clades and ecological associations. Our results show that the prevalence of chromosome gain and loss varies by clade and can be better explained by differences in genetic background than ecology. The phylogenetic context of lineages showing high aneuploidy rates suggests that increased aneuploidy frequency arose multiple times in S. cerevisiae evolution. Separate from aneuploidy frequency, analyzing growth phenotypes reveals that some backgrounds – such as European Wine strains – show fitness costs upon chromosome duplication, whereas other clades with high aneuploidy rates show little evidence of major deleterious effects. Our analysis confirms that chromosome amplification can produce phenotypic benefits that can influence evolutionary trajectories. These results have important implications for understanding genetic variation in aneuploidy prevalence in health, disease, and evolution.ARTICLE SUMMARYAneuploidy, an imbalance in the normal chromosome copy number, is detrimental during human development; yet individuals show substantial variability in their aneuploidy susceptibility, suggesting the influence of genetic background on aneuploidy tolerance. Scopel et al. employed a population genetic approach to address this question, analyzing over 1,000 published Saccharomyces cerevisiae genomes. The results demonstrate that genetic background has a substantial effect on aneuploidy frequency and cellular tolerance of aneuploidy stress, presenting important new information on the forces that contribute to aneuploidy prevalence.

To cope with sudden changes in the external environment, the budding yeast Saccharomyces cerevisiae orchestrates a multi-faceted response that spans many levels of physiology. Several studies have interrogated the transcriptome response to endoplasmic reticulum (ER) stress and the role of regulators such as the Ire1 kinase and Hac1 transcription factor. However, less is known about responses to ER stress at other levels of physiology. Here, we used quantitative phosphoproteomics and computational network inference to uncover the yeast phosphoproteome response to the reducing agent DTT and the upstream signaling network that controls it. We profiled wild-type cells and mutants lacking IRE1 or MAPK kinases MKK1 and MKK2, before and at various times after DTT treatment. In addition to revealing downstream targets of these kinases, our inference approach predicted new regulators in the DTT response, including cell-cycle regulator Cdc28 and osmotic-response kinase Rck2, which we validated computationally. Our results also revealed similarities and surprising differences in responses to different stress conditions, especially in the response of Protein Kinase A (PKA) targets. These results have implications for the breadth of signaling programs that can give rise to common stress response signatures.

CRISPR/Cas9 is a powerful tool for editing genomes, but design decisions are generally made with respect to a single reference genome. With population genomic data becoming available for an increasing number of model organisms, researchers are interested in manipulating multiple strains and lines. CRISpy-pop is a web application that generates and filters guide RNA sequences for CRISPR/Cas9 genome editing for diverse yeast and bacterial strains. The current implementation designs and predicts the activity of guide RNAs against more than 1000 Saccharomyces cerevisiae genomes, including 167 strains frequently used in bioenergy research. Zymomonas mobilis, an increasingly popular bacterial bioenergy research model, is also supported. CRISpy-pop is available as a web application (https://CRISpy-pop.glbrc.org/) with an intuitive graphical user interface. CRISpy-pop also cross-references the human genome to allow users to avoid the selection of sgRNAs with potential biosafety concerns. Additionally, CRISpy-pop predicts the strain coverage of each guide RNA within the supported strain sets, which aids in functional population genetic studies. Finally, we validate how CRISpy-pop can accurately predict the activity of guide RNAs across strains using population genomic data.

Advances in systems biology have made clear the importance of network models for capturing knowledge about complex relationships in gene regulation, metabolism, and cellular signaling. A common approach to uncovering biological networks involves performing perturbations on elements of the network, such as gene knockdown experiments, and measuring how the perturbation affects some reporter of the process under study. In this article, we develop context-specific nested effects models (CSNEMs), an approach to inferring such networks that generalizes nested effects models (NEMs). The main contribution of this work is that CSNEMs explicitly model the participation of a gene in multiple contexts, meaning that a gene can appear in multiple places in the network. Biologically, the representation of regulators in multiple contexts may indicate that these regulators have distinct roles in different cellular compartments or cell cycle phases. We present an evaluation of the method on simulated data as well as on data from a study of the sodium chloride stress response in Saccharomyces cerevisiae.

Aneuploidy is highly detrimental during development yet common in cancers and pathogenic fungi – what gives rise to differences in aneuploidy tolerance remains unclear. We previously showed that wild isolates of Saccharomyces cerevisiae tolerate chromosome amplification while laboratory strains used as a model for aneuploid syndromes do not. Here, we mapped the genetic basis to Ssd1, an RNA-binding translational regulator that is functional in wild aneuploids but defective in laboratory strain W303. Loss of SSD1 recapitulates myriad aneuploidy signatures previously taken as eukaryotic responses. We show that aneuploidy tolerance is enabled via a role for Ssd1 in mitochondrial physiology, including binding and regulating nuclear-encoded mitochondrial mRNAs, coupled with a role in mitigating proteostasis stress. Recapitulating ssd1Δ defects with combinatorial drug treatment selectively blocked proliferation of wild-type aneuploids compared to euploids. Our work adds to elegant studies in the sensitized laboratory strain to present a mechanistic understanding of eukaryotic aneuploidy tolerance.

Phosphorylation of the carboxyl-terminal domain (CTD) of the largest subunit of RNA polymerase II (Pol II) governs stage-specific interactions with different cellular machines. The CTD consists of Y1S2P3T4S5P6S7 heptad repeats, and sequential phosphorylations of Ser7, Ser5 and Ser2 occur universally across Pol II-transcribed genes. Phosphorylation of Thr4, however, appears to selectively modulate transcription of specific classes of genes. Here, we identify 10 new Thr4 kinases from different kinase structural groups. Irreversible chemical inhibition of the most active Thr4 kinase, Hrr25, reveals a novel role for this kinase in transcription termination of specific class of noncoding snoRNA genes. Genome-wide profiles of Hrr25 reveal a selective enrichment at 3ʹ regions of noncoding genes that display termination defects. Importantly, phospho-Thr4 marks placed by Hrr25 are recognized by Rtt103, a key component of the termination machinery. Our results suggest that these uncommon CTD kinases selectively place phospho-Thr4 marks to regulate expression of targeted genes.

Imidazolium ionic liquids (IILs) have a range of biotechnological applications, including as pretreatment solvents that extract cellulose from plant biomass for microbial fermentation into sustainable bioenergy. However, residual levels of IILs, such as 1-ethyl-3-methylimidazolium chloride ([C2C1im]Cl), are toxic to biofuel-producing microbes, including the yeast Saccharomyces cerevisiae. S. cerevisiae strains isolated from diverse ecological niches differ in genomic sequence and in phenotypes potentially beneficial for industrial applications, including tolerance to inhibitory compounds present in hydrolyzed plant feedstocks. We evaluated >100 genome-sequenced S. cerevisiae strains for tolerance to [C2C1im]Cl and identified one strain with exceptional tolerance. By screening a library of genomic DNA fragments from the [C2C1im]Cl-tolerant strain for improved IIL tolerance, we identified SGE1, which encodes a plasma membrane multidrug efflux pump, and a previously uncharacterized gene that we named ionic liquid tolerance 1 (ILT1), which encodes a predicted membrane protein. Analyses of SGE1 sequences from our panel of S. cerevisiae strains together with growth phenotypes implicated two single nucleotide polymorphisms (SNPs) that associated with IIL tolerance and sensitivity. We confirmed these phenotypic effects by transferring the SGE1 SNPs into a [C2C1im]Cl-sensitive yeast strain using CRISPR/Cas9 genome editing. Further studies indicated that these SNPs affect Sge1 protein stability and cell surface localization, influencing the amount of toxic IILs that cells can pump out of the cytoplasm. Our results highlight the general potential for discovering useful biotechnological functions from untapped natural sequence variation and provide functional insight into emergent SGE1 alleles with reduced capacities to protect against IIL toxicity.

Proper cell function depends on networks of proteins that interact physically and functionally to carry out physiological processes. Thus, it seems logical that the impact of sequence variation in one protein could be significantly influenced by genetic variants at other loci in a genome. Nonetheless, the importance of such genetic interactions, known as epistasis, in explaining phenotypic variation remains a matter of debate in genetics. Recent work from our lab revealed that genes implicated from an association study of toxin tolerance in Saccharomyces cerevisiae show extensive interactions with the genetic background: most implicated genes, regardless of allele, are important for toxin tolerance in only one of two tested strains. The prevalence of background effects in our study adds to other reports of widespread genetic-background interactions in model organisms. We suggest that these effects represent many-way interactions with myriad features of the cellular system that vary across classes of individuals. Such gene-by-system interactions may influence diverse traits and require new modeling approaches to accurately represent genotype-phenotype relationships across individuals.

A major obstacle to sustainable lignocellulosic biofuel production is microbe inhibition by the combinatorial stresses in pretreated plant hydrolysate. Chemical biomass pretreatment releases a suite of toxins that interact with other stressors, including high osmolarity and temperature, which together can have poorly understood synergistic effects on cells. Improving tolerance in industrial strains has been hindered, in part because the mechanisms of tolerance reported in the literature often fail to recapitulate in other strain backgrounds. Here, we explored and then exploited variations in stress tolerance, toxin-induced transcriptomic responses, and fitness effects of gene overexpression in different Saccharomyces cerevisiae (yeast) strains to identify genes and processes linked to tolerance of hydrolysate stressors. Using six different S. cerevisiae strains that together maximized phenotypic and genetic diversity, first we explored transcriptomic differences between resistant and sensitive strains to identify common and strain-specific responses. This comparative analysis implicated primary cellular targets of hydrolysate toxins, secondary effects of defective defense strategies, and mechanisms of tolerance. Dissecting the responses to individual hydrolysate components across strains pointed to synergistic interactions between osmolarity, pH, hydrolysate toxins, and nutrient composition. By characterizing the effects of high-copy gene overexpression in three different strains, we revealed the breadth of the background-specific effects of gene fitness contributions in synthetic hydrolysate. Our approach identified new genes for engineering improved stress tolerance in diverse strains while illuminating the effects of genetic background on molecular mechanisms. IMPORTANCE Recent studies on natural variation within Saccharomyces cerevisiae have uncovered substantial phenotypic diversity. Here, we took advantage of this diversity, using it as a tool to infer the effects of combinatorial stress found in lignocellulosic hydrolysate. By comparing sensitive and tolerant strains, we implicated primary cellular targets of hydrolysate toxins and elucidated the physiological states of cells when exposed to this stress. We also explored the strain-specific effects of gene overexpression to further identify strain-specific responses to hydrolysate stresses and to identify genes that improve hydrolysate tolerance independent of strain background. This study underscores the importance of studying multiple strains to understand the effects of hydrolysate stress and provides a method to find genes that improve tolerance across strain backgrounds.

Genetic background effects have long been recognized and, in some cases studied, but they are often viewed as a nuisance by molecular biologists. We suggest that genetic variation currently represents a critical frontier for molecular studies. Human genetics has seen a surge of interest in genetic variation and its contributions to disease, but insights into disease mechanisms are difficult since information about gene function is lacking. By contrast, model organism genetics has excelled at revealing molecular mechanisms of cellular processes, but often de-emphasizes genetic variation and its functional consequences. We argue that model organism biology would benefit from incorporating natural variation, both to capture how well laboratory lines exemplify the species they represent and to inform on molecular processes and their variability. Such a synthesis would also greatly expand the relevance of model systems for studies of complex trait variation, including disease.

The normalization of RNA-seq data is essential for accurate downstream inference, but the assumptions upon which most normalization methods are based are not applicable in the single-cell setting. Consequently, applying existing normalization methods to single-cell RNA-seq data introduces artifacts that bias downstream analyses. To address this, we introduce SCnorm for accurate and efficient normalization of single-cell RNA-seq data.

Microbes in nature frequently experience “boom or bust” cycles of environmental stress. Thus, microbes that can anticipate the onset of stress would have an advantage. One way that microbes anticipate future stress is through acquired stress resistance, where cells exposed to a mild dose of one stress gain the ability to survive an otherwise lethal dose of a subsequent stress. In the budding yeast Saccharomyces cerevisiae, certain stressors can cross protect against high salt concentrations, though the mechanisms governing this acquired stress resistance are not well understood. In this study, we took advantage of wild yeast strains to understand the mechanism underlying ethanol-induced cross protection against high salt concentrations. We found that mild ethanol stress allows cells to resume growth on high salt, which involves a novel role for a well-studied salt transporter. Overall, this discovery highlights how leveraging natural variation can provide new insights into well-studied stress defense mechanisms., All living organisms must recognize and respond to various environmental stresses throughout their lifetime. In natural environments, cells frequently encounter fluctuating concentrations of different stressors that can occur in combination or sequentially. Thus, the ability to anticipate an impending stress is likely ecologically relevant. One possible mechanism for anticipating future stress is acquired stress resistance, where cells preexposed to a mild sublethal dose of stress gain the ability to survive an otherwise lethal dose of stress. We have been leveraging wild strains of Saccharomyces cerevisiae to investigate natural variation in the yeast ethanol stress response and its role in acquired stress resistance. Here, we report that a wild vineyard isolate possesses ethanol-induced cross protection against severe concentrations of salt. Because this phenotype correlates with ethanol-dependent induction of the ENA genes, which encode sodium efflux pumps already associated with salt resistance, we hypothesized that variation in ENA expression was responsible for differences in acquired salt tolerance across strains. Surprisingly, we found that the ENA genes were completely dispensable for ethanol-induced survival of high salt concentrations in the wild vineyard strain. Instead, the ENA genes were necessary for the ability to resume growth on high concentrations of salt following a mild ethanol pretreatment. Surprisingly, this growth acclimation phenotype was also shared by the lab yeast strain despite lack of ENA induction under this condition. This study underscores that cross protection can affect both viability and growth through distinct mechanisms, both of which likely confer fitness effects that are ecologically relevant. IMPORTANCE Microbes in nature frequently experience “boom or bust” cycles of environmental stress. Thus, microbes that can anticipate the onset of stress would have an advantage. One way that microbes anticipate future stress is through acquired stress resistance, where cells exposed to a mild dose of one stress gain the ability to survive an otherwise lethal dose of a subsequent stress. In the budding yeast Saccharomyces cerevisiae, certain stressors can cross protect against high salt concentrations, though the mechanisms governing this acquired stress resistance are not well understood. In this study, we took advantage of wild yeast strains to understand the mechanism underlying ethanol-induced cross protection against high salt concentrations. We found that mild ethanol stress allows cells to resume growth on high salt, which involves a novel role for a well-studied salt transporter. Overall, this discovery highlights how leveraging natural variation can provide new insights into well-studied stress defense mechanisms.

Imidazolium ionic liquids (IILs) have a range of biotechnological applications, including as pretreatment solvents that extract cellulose from plant biomass for microbial fermentation into sustainable bioenergy. However, residual levels of IILs, such as 1-ethyl-3-methylimidazolium chloride ([C2C1im]Cl), are toxic to biofuel-producing microbes, including the yeast Saccharomyces cerevisiae. S. cerevisiae strains isolated from diverse ecological niches differ in genomic sequence and in phenotypes potentially beneficial for industrial applications, including tolerance to inhibitory compounds present in hydrolyzed plant feedstocks. We evaluated >100 genome-sequenced S. cerevisiae strains for tolerance to [C2C1im]Cl and identified one strain with exceptional tolerance. By screening a library of genomic DNA fragments from the [C2C1im]Cl-tolerant strain for improved IIL tolerance, we identified SGE1, which encodes a plasma membrane multidrug efflux pump, and a previously uncharacterized gene that we named ionic liquid tolerance 1 (ILT1), which encodes a predicted membrane protein. Analyses of SGE1 sequences from our panel of S. cerevisiae strains together with growth phenotypes implicated two single nucleotide polymorphisms (SNPs) that associated with IIL tolerance and sensitivity. We confirmed these phenotypic effects by transferring the SGE1 SNPs into a [C2C1im]Cl-sensitive yeast strain using CRISPR/Cas9 genome editing. Further studies indicated that these SNPs affect Sge1 protein stability and cell surface localization, influencing the amount of toxic IILs that cells can pump out of the cytoplasm. Our results highlight the general potential for discovering useful biotechnological functions from untapped natural sequence variation and provide functional insight into emergent SGE1 alleles with reduced capacities to protect against IIL toxicity.

Cellulosic plant biomass is a promising sustainable resource for generating alternative biofuels and biochemicals with microbial factories. But a remaining bottleneck is engineering microbes that are tolerant of toxins generated during biomass processing, because mechanisms of toxin defense are only beginning to emerge. Here, we exploited natural diversity in 165 Saccharomyces cerevisiae strains isolated from diverse geographical and ecological niches, to identify mechanisms of hydrolysate-toxin tolerance. We performed genome-wide association (GWA) analysis to identify genetic variants underlying toxin tolerance, and gene knockouts and allele-swap experiments to validate the involvement of implicated genes. In the process of this work, we uncovered a surprising difference in genetic architecture depending on strain background: in all but one case, knockout of implicated genes had a significant effect on toxin tolerance in one strain, but no significant effect in another strain. In fact, whether or not the gene was involved in tolerance in each strain background had a bigger contribution to strain-specific variation than allelic differences. Our results suggest a major difference in the underlying network of causal genes in different strains, suggesting that mechanisms of hydrolysate tolerance are very dependent on the genetic background. These results could have significant implications for interpreting GWA results and raise important considerations for engineering strategies for industrial strain improvement., Author summary Understanding the genetic architecture of complex traits is important for elucidating the genotype-phenotype relationship. Many studies have sought genetic variants that underlie phenotypic variation across individuals, both to implicate causal variants and to inform on architecture. Here we used genome-wide association analysis to identify genes and processes involved in tolerance of toxins found in plant-biomass hydrolysate, an important substrate for sustainable biofuel production. We found substantial variation in whether or not individual genes were important for tolerance across genetic backgrounds. Whether or not a gene was important in a given strain background explained more variation than the alleleic differences in the gene. These results suggest substantial variation in gene contributions, and perhaps underlying mechanisms, of toxin tolerance.

We present an open-source, interactive program named Proteoform Suite that uses proteoform mass and intensity measurements from complex biological samples to identify and quantify proteoforms. It constructs families of proteoforms derived from the same gene, assesses proteoform function using gene ontology (GO) analysis, and enables visualization of quantified proteoform families and their changes. It is applied here to reveal systemic proteoform variations in the yeast response to salt stress.