System-level analysis of genes and functions affecting survival during nutrient starvation in Saccharomyces cerevisiae

Characterizing a panel of amino acid auxotrophs under auxotrophic starvation conditions

Auxotrophic strains starving for their cognate nutrient, termed auxotrophic starvation, are characterized by a shorter lifespan, higher glucose wasting phenotype, and inability to accomplish cell cycle arrest when compared to a "natural starvation," where a cell is starving for natural environmental growth-limiting nutrients such as phosphate. Since evidence of this physiological response is limited to only a subset of auxotrophs, we evaluated a panel of auxotrophic mutants to determine whether these responses are characteristic of a broader range of amino acid auxotrophs. Based on the starvation survival kinetics, the panel of strains was grouped into three categories-short-lived strains, strains with survival similar to a prototrophic wild type strain, and long-lived strains. Among the short-lived strains, we observed that the tyrosine, asparagine, threonine, and aspartic acid auxotrophs rapidly decline in viability, with all strains unable to arrest cell cycle progression. The three basic amino acid auxotrophs had a survival similar to a prototrophic strain starving in minimal media. The leucine, tryptophan, methionine, and cysteine auxotrophs displayed the longest lifespan. We also demonstrate how the phenomenon of glucose wasting is limited to only a subset of the tested auxotrophs, namely the asparagine, leucine, and lysine auxotrophs. Furthermore, we observed pleiotropic phenotypes associated with a subgroup of auxotrophs, highlighting the importance of considering unintended phenotypic effects when using auxotrophic strains especially in chronological aging experiments.

Divergence of TORC1-mediated stress response leads to novel acquired stress resistance in a pathogenic yeast

Acquired stress resistance (ASR) enables organisms to prepare for environmental changes that occur after an initial stressor. However, the genetic basis for ASR and how the underlying network evolved remain poorly understood. In this study, we discovered that a short phosphate starvation induces oxidative stress response (OSR) genes in the pathogenic yeast C. glabrata and protects it against a severe H2O2 stress; the same treatment, however, provides little benefit in the low pathogenic-potential relative, S. cerevisiae. This ASR involves the same transcription factors (TFs) as the OSR, but with different combinatorial logics. We show that Target-of-Rapamycin Complex 1 (TORC1) is differentially inhibited by phosphate starvation in the two species and contributes to the ASR via its proximal effector, Sch9. Therefore, evolution of the phosphate starvation-induced ASR involves the rewiring of TORC1's response to phosphate limitation and the repurposing of TF-target gene networks for the OSR using new regulatory logics.

Divergence of TORC1-mediated Stress Response Leads to Novel Acquired Stress Resistance in a Pathogenic Yeast

Acquired stress resistance (ASR) enables organisms to prepare for environmental changes that occur after an initial stressor. However, the genetic basis for ASR and how the underlying network evolved remain poorly understood. In this study, we discovered that a short phosphate starvation induces oxidative stress response (OSR) genes in the pathogenic yeast C. glabrata and protects it against a severe H2O2 stress; the same treatment, however, provides little benefit in the low pathogenic-potential relative, S. cerevisiae. This ASR involves the same transcription factors (TFs) as the OSR, but with different combinatorial logics. We show that Target-of-Rapamycin Complex 1 (TORC1) is differentially inhibited by phosphate starvation in the two species and contributes to the ASR via its proximal effector, Sch9. Therefore, evolution of the phosphate starvation-induced ASR involves the rewiring of TORC1's response to phosphate limitation and the repurposing of TF-target gene networks for the OSR using new regulatory logics.

Parallel proteomics and phosphoproteomics defines starvation signal specific processes in cell quiescence

Cells arrest growth and enter a quiescent state upon nutrient deprivation. However, the molecular processes by which cells respond to different starvation signals to regulate exit from the cell division cycle and initiation of quiescence remains poorly understood. To study the role of protein expression and signaling in quiescence we combined temporal profiling of the proteome and phosphoproteome using stable isotope labeling with amino acids in cell culture (SILAC) in Saccharomyces cerevisiae (budding yeast). We find that carbon and phosphorus starvation signals activate quiescence through largely distinct remodeling of the proteome and phosphoproteome. However, increased expression of mitochondrial proteins is associated with quiescence establishment in response to both starvation signals. Deletion of the putative quiescence regulator RIM15, which encodes a serine-threonine kinase, results in reduced survival of cells starved for phosphorus and nitrogen, but not carbon. However, we identified common protein phosphorylation roles for RIM15 in quiescence that are enriched for RNA metabolism and translation. We also find evidence for RIM15-mediated phosphorylation of some targets, including IGO1, prior to starvation consistent with a functional role for RIM15 in proliferative cells. Finally, our results reveal widespread catabolism of amino acids in response to nitrogen starvation, indicating widespread amino acid recycling via salvage pathways in conditions lacking environmental nitrogen. Our study defines an expanded quiescent proteome and phosphoproteome in yeast, and highlights the multiple coordinated molecular processes at the level of protein expression and phosphorylation that are required for quiescence.

Metabolic Consequences of Polyphosphate Synthesis and Imminent Phosphate Limitation

Cells stabilize intracellular inorganic phosphate (Pi) to compromise between large biosynthetic needs and detrimental bioenergetic effects of Pi. Pi homeostasis in eukaryotes uses Syg1/Pho81/Xpr1 (SPX) domains, which are receptors for inositol pyrophosphates. We explored how polymerization and storage of Pi in acidocalcisome-like vacuoles supports Saccharomyces cerevisiae metabolism and how these cells recognize Pi scarcity. Whereas Pi starvation affects numerous metabolic pathways, beginning Pi scarcity affects few metabolites. These include inositol pyrophosphates and ATP, a low-affinity substrate for inositol pyrophosphate-synthesizing kinases. Declining ATP and inositol pyrophosphates may thus be indicators of impending Pi limitation. Actual Pi starvation triggers accumulation of the purine synthesis intermediate 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR), which activates Pi-dependent transcription factors. Cells lacking inorganic polyphosphate show Pi starvation features already under Pi-replete conditions, suggesting that vacuolar polyphosphate supplies Pi for metabolism even when Pi is abundant. However, polyphosphate deficiency also generates unique metabolic changes that are not observed in starving wild-type cells. Polyphosphate in acidocalcisome-like vacuoles may hence be more than a global phosphate reserve and channel Pi to preferred cellular processes. IMPORTANCE Cells must strike a delicate balance between the high demand of inorganic phosphate (Pi) for synthesizing nucleic acids and phospholipids and its detrimental bioenergetic effects by reducing the free energy of nucleotide hydrolysis. The latter may stall metabolism. Therefore, microorganisms manage the import and export of phosphate, its conversion into osmotically inactive inorganic polyphosphates, and their storage in dedicated organelles (acidocalcisomes). Here, we provide novel insights into metabolic changes that yeast cells may use to signal declining phosphate availability in the cytosol and differentiate it from actual phosphate starvation. We also analyze the role of acidocalcisome-like organelles in phosphate homeostasis. This study uncovers an unexpected role of the polyphosphate pool in these organelles under phosphate-rich conditions, indicating that its metabolic roles go beyond that of a phosphate reserve for surviving starvation.

A Systematic Review on Quiescent State Research Approaches in S. cerevisiae

Quiescence, the temporary and reversible arrest of cell growth, is a fundamental biological process. However, the lack of standardization in terms of reporting the experimental details of quiescent cells and populations can cause confusion and hinder knowledge transfer. We employ the systematic review methodology to comprehensively analyze the diversity of approaches used to study the quiescent state, focusing on all published research addressing the budding yeast Saccharomyces cerevisiae. We group research articles into those that consider all cells comprising the stationary-phase (SP) population as quiescent and those that recognize heterogeneity within the SP by distinguishing phenotypically distinct subpopulations. Furthermore, we investigate the chronological age of the quiescent populations under study and the methods used to induce the quiescent state, such as gradual starvation or abrupt environmental change. We also assess whether the strains used in research are prototrophic or auxotrophic. By combining the above features, we identify 48 possible experimental setups that can be used to study quiescence, which can be misleading when drawing general conclusions. We therefore summarize our review by proposing guidelines and recommendations pertaining to the information included in research articles. We believe that more rigorous reporting on the features of quiescent populations will facilitate knowledge transfer within and between disciplines, thereby stimulating valuable scientific discussion.

Extreme Sensitivity of Fitness to Environmental Conditions: Lessons from #1BigBatch

The phrase "survival of the fittest" has become an iconic descriptor of how natural selection works. And yet, precisely measuring fitness, even for single-celled microbial populations growing in controlled laboratory conditions, remains a challenge. While numerous methods exist to perform these measurements, including recently developed methods utilizing DNA barcodes, all methods are limited in their precision to differentiate strains with small fitness differences. In this study, we rule out some major sources of imprecision, but still find that fitness measurements vary substantially from replicate to replicate. Our data suggest that very subtle and difficult to avoid environmental differences between replicates create systematic variation across fitness measurements. We conclude by discussing how fitness measurements should be interpreted given their extreme environment dependence. This work was inspired by the scientific community who followed us and gave us tips as we live tweeted a high-replicate fitness measurement experiment at #1BigBatch.

A Transcriptomic Analysis of Higher-Order Ecological Interactions in a Eukaryotic Model Microbial Ecosystem

Nonlinear ecological interactions within microbial ecosystems and their contribution to ecosystem functioning remain largely unexplored. Higher-order interactions, or interactions in systems comprised of more than two members that cannot be explained by cumulative pairwise interactions, are particularly understudied, especially in eukaryotic microorganisms. The wine fermentation ecosystem presents an ideal model to study yeast ecosystem establishment and functioning. Some pairwise ecological interactions between wine yeast species have been characterized, but very little is known about how more complex, multispecies systems function. Here, we evaluated nonlinear ecosystem properties by determining the transcriptomic response of Saccharomyces cerevisiae to pairwise versus tri-species culture. The transcriptome revealed that genes expressed during pairwise coculture were enriched in the tri-species data set but also that just under half of the data set comprised unique genes attributed to a higher-order response. Through interactive protein-association network visualizations, a holistic cell-wide view of the gene expression data was generated, which highlighted known stress response and metabolic adaptation mechanisms which were specifically activated during tri-species growth. Further, extracellular metabolite data corroborated that the observed differences were a result of a biotic stress response. This provides exciting new evidence showing the presence of higher-order interactions within a model microbial ecosystem. IMPORTANCE Higher-order interactions are one of the major blind spots in our understanding of microbial ecosystems. These systems remain largely unpredictable and are characterized by nonlinear dynamics, in particular when the system is comprised of more than two entities. By evaluating the transcriptomic response of S. cerevisiae to an increase in culture complexity from a single species to two- and three-species systems, we were able to confirm the presence of a unique response in the more complex setting that could not be explained by the responses observed at the pairwise level. This is the first data set that provides molecular targets for further analysis to explain unpredictable ecosystem dynamics in yeast.

Genome-wide effect of non-optimal temperatures under anaerobic conditions on gene expression in Saccharomyces cerevisiae

Understanding of thermal adaptation mechanisms in yeast is crucial to develop better-adapted strains to industrial processes, providing more economical and sustainable products. We have analyzed the transcriptomic responses of three Saccharomyces cerevisiae strains, a commercial wine strain, ADY5, a laboratory strain, CEN.PK113-7D and a commercial bioethanol strain, Ethanol Red, grown at non-optimal temperatures under anaerobic chemostat conditions. Transcriptomic analysis of the three strains revealed a huge complexity of cellular mechanisms and responses. Overall, cold exerted a stronger transcriptional response in the three strains comparing with heat conditions, with a higher number of down-regulating genes than of up-regulating genes regardless the strain analyzed. The comparison of the transcriptome at both sub- and supra-optimal temperatures showed the presence of common genes up- or down-regulated in both conditions, but also the presence of common genes up- or down-regulated in the three studied strains. More specifically, we have identified and validated three up-regulated genes at sub-optimal temperature in the three strains, OPI3, EFM6 and YOL014W. Finally, the comparison of the transcriptomic data with a previous proteomic study with the same strains revealed a good correlation between gene activity and protein abundance, mainly at low temperature. Our work provides a global insight into the specific mechanisms involved in temperature adaptation regarding both transcriptome and proteome, which can be a step forward in the comprehension and improvement of yeast thermotolerance.

Phosphate Restriction Promotes Longevity via Activation of Autophagy and the Multivesicular Body Pathway

Nutrient limitation results in an activation of autophagy in organisms ranging from yeast, nematodes and flies to mammals. Several evolutionary conserved nutrient-sensing kinases are critical for efficient adaptation of yeast cells to glucose, nitrogen or phosphate depletion, subsequent cell-cycle exit and the regulation of autophagy. Here, we demonstrate that phosphate restriction results in a prominent extension of yeast lifespan that requires the coordinated activity of autophagy and the multivesicular body pathway, enabling efficient turnover of cytoplasmic and plasma membrane cargo. While the multivesicular body pathway was essential during the early days of aging, autophagy contributed to long-term survival at later days. The cyclin-dependent kinase Pho85 was critical for phosphate restriction-induced autophagy and full lifespan extension. In contrast, when cell-cycle exit was triggered by exhaustion of glucose instead of phosphate, Pho85 and its cyclin, Pho80, functioned as negative regulators of autophagy and lifespan. The storage of phosphate in form of polyphosphate was completely dispensable to in sustaining viability under phosphate restriction. Collectively, our results identify the multifunctional, nutrient-sensing kinase Pho85 as critical modulator of longevity that differentially coordinates the autophagic response to distinct kinds of starvation.

Old yeasts, young beer-The industrial relevance of yeast chronological life span

Much like other living organisms, yeast cells have a limited life span, in terms of both the maximal length of time a cell can stay alive (chronological life span) and the maximal number of cell divisions it can undergo (replicative life span). Over the past years, intensive research revealed that the life span of yeast depends on both the genetic background of the cells and environmental factors. Specifically, the presence of stress factors, reactive oxygen species, and the availability of nutrients profoundly impact life span, and signaling cascades involved in the response to these factors, including the target of rapamycin (TOR) and cyclic adenosine monophosphate (cAMP)/protein kinase A (PKA) pathways, play a central role. Interestingly, yeast life span also has direct implications for its use in industrial processes. In beer brewing, for example, the inoculation of finished beer with live yeast cells, a process called "bottle conditioning" helps improve the product's shelf life by clearing undesirable carbonyl compounds such as furfural and 2-methylpropanal that cause staling. However, this effect depends on the reductive metabolism of living cells and is thus inherently limited by the cells' chronological life span. Here, we review the mechanisms underlying chronological life span in yeast. We also discuss how this insight connects to industrial observations and ultimately opens new routes towards superior industrial yeasts that can help improve a product's shelf life and thus contribute to a more sustainable industry.

Overexpression of a single ORF can extend chronological lifespan in yeast if retrograde signaling and stress response are stimulated

Systematic collections of single-gene deletions have been invaluable in uncovering determinants of lifespan in yeast. Overexpression of a single gene does not have such a clear outcome as cancellation of its function but it can lead to a variety of imbalances, deregulations and compensations, and some of them could be important for longevity. We report an experiment in which a genome-wide collection of strains overexpressing a single gene was assayed for chronological lifespan (CLS). Only one group of proteins, those locating to the inner membrane and matrix of mitochondria, tended to extend CLS when abundantly overproduced. We selected two such strains—one overexpressing Qcr7 of the respiratory complex III, the other overexpressing Mrps28 of the small mitoribosomal subunit—and analyzed their transcriptomes. The uncovered shifts in RNA abundance in the two strains were nearly identical and highly suggestive. They implied a distortion in the co-translational assembly of respiratory complexes followed by retrograde signaling to the nucleus. The consequent reprogramming of the entire cellular metabolism towards the resistance to stress resulted in an enhanced ability to persist in a non-proliferating state. Our results show that surveillance of the inner mitochondrial membrane integrity is of outstanding importance for the cell. They also demonstrate that overexpression of single genes could be used effectively to elucidate the mitochondrion-nucleus crosstalk.

Cellular quiescence in budding yeast

Cellular quiescence, the temporary and reversible exit from proliferative growth, is the predominant state of all cells. However, our understanding of the biological processes and molecular mechanisms that underlie cell quiescence remains incomplete. As with the mitotic cell cycle, budding and fission yeast are preeminent model systems for studying cellular quiescence owing to their rich experimental toolboxes and the evolutionary conservation across eukaryotes of pathways and processes that control quiescence. Here, we review current knowledge of cell quiescence in budding yeast and how it pertains to cellular quiescence in other organisms, including multicellular animals. Quiescence entails large-scale remodeling of virtually every cellular process, organelle, gene expression, and metabolic state that is executed dynamically as cells undergo the initiation, maintenance, and exit from quiescence. We review these major transitions, our current understanding of their molecular bases, and highlight unresolved questions. We summarize the primary methods employed for quiescence studies in yeast and discuss their relative merits. Understanding cell quiescence has important consequences for human disease as quiescent single-celled microbes are notoriously difficult to kill and quiescent human cells play important roles in diseases such as cancer. We argue that research on cellular quiescence will be accelerated through the adoption of common criteria, and methods, for defining cell quiescence. An integrated approach to studying cell quiescence, and a focus on the behavior of individual cells, will yield new insights into the pathways and processes that underlie cell quiescence leading to a more complete understanding of the life cycle of cells. TAKE AWAY: Quiescent cells are viable cells that have reversibly exited the cell cycle Quiescence is induced in response to a variety of nutrient starvation signals Quiescence is executed dynamically through three phases: initiation, maintenance, and exit Quiescence entails large-scale remodeling of gene expression, organelles, and metabolism Single-cell approaches are required to address heterogeneity among quiescent cells.

Genome-scale reconstruction of Gcn4/ATF4 networks driving a growth program

Growth and starvation are considered opposite ends of a spectrum. To sustain growth, cells use coordinated gene expression programs and manage biomolecule supply in order to match the demands of metabolism and translation. Global growth programs complement increased ribosomal biogenesis with sufficient carbon metabolism, amino acid and nucleotide biosynthesis. How these resources are collectively managed is a fundamental question. The role of the Gcn4/ATF4 transcription factor has been best studied in contexts where cells encounter amino acid starvation. However, high Gcn4 activity has been observed in contexts of rapid cell proliferation, and the roles of Gcn4 in such growth contexts are unclear. Here, using a methionine-induced growth program in yeast, we show that Gcn4/ATF4 is the fulcrum that maintains metabolic supply in order to sustain translation outputs. By integrating matched transcriptome and ChIP-Seq analysis, we decipher genome-wide direct and indirect roles for Gcn4 in this growth program. Genes that enable metabolic precursor biosynthesis indispensably require Gcn4; contrastingly ribosomal genes are partly repressed by Gcn4. Gcn4 directly binds promoter-regions and transcribes a subset of metabolic genes, particularly driving lysine and arginine biosynthesis. Gcn4 also globally represses lysine and arginine enriched transcripts, which include genes encoding the translation machinery. The Gcn4 dependent lysine and arginine supply thereby maintains the synthesis of the translation machinery. This is required to maintain translation capacity. Gcn4 consequently enables metabolic-precursor supply to bolster protein synthesis, and drive a growth program. Thus, we illustrate how growth and starvation outcomes are both controlled using the same Gcn4 transcriptional outputs that function in distinct contexts.

High-resolution yeast quiescence profiling in human-like media reveals complex influences of auxotrophy and nutrient availability

Yeast cells survive in stationary phase culture by entering quiescence, which is measured by colony-forming capacity upon nutrient re-exposure. Yeast chronological lifespan (CLS) studies, employing the comprehensive collection of gene knockout strains, have correlated weakly between independent laboratories, which is hypothesized to reflect differential interaction between the deleted genes, auxotrophy, media composition, and other assay conditions influencing quiescence. This hypothesis was investigated by high-throughput quiescence profiling of the parental prototrophic strain, from which the gene deletion strain libraries were constructed, and all possible auxotrophic allele combinations in that background. Defined media resembling human cell culture media promoted long-term quiescence and was used to assess effects of glucose, ammonium sulfate, auxotrophic nutrient availability, target of rapamycin signaling, and replication stress. Frequent, high-replicate measurements of colony-forming capacity from cultures aged past 60 days provided profiles of quiescence phenomena such as gasping and hormesis. Media acidification was assayed in parallel to assess correlation. Influences of leucine, methionine, glucose, and ammonium sulfate metabolism were clarified, and a role for lysine metabolism newly characterized, while histidine and uracil perturbations had less impact. Interactions occurred between glucose, ammonium sulfate, auxotrophy, auxotrophic nutrient limitation, aeration, TOR signaling, and/or replication stress. Weak correlation existed between media acidification and maintenance of quiescence. In summary, experimental factors, uncontrolled across previous genome-wide yeast CLS studies, influence quiescence and interact extensively, revealing quiescence as a complex metabolic and developmental process that should be studied in a prototrophic context, omitting ammonium sulfate from defined media, and employing highly replicable protocols.

Metabolic excretion associated with nutrient-growth dysregulation promotes the rapid evolution of an overt metabolic defect

In eukaryotes, conserved mechanisms ensure that cell growth is coordinated with nutrient availability. Overactive growth during nutrient limitation ("nutrient-growth dysregulation") can lead to rapid cell death. Here, we demonstrate that cells can adapt to nutrient-growth dysregulation by evolving major metabolic defects. Specifically, when yeast lysine-auxotrophic mutant lys- encountered lysine limitation, an evolutionarily novel stress, cells suffered nutrient-growth dysregulation. A subpopulation repeatedly evolved to lose the ability to synthesize organosulfurs (lys-orgS-). Organosulfurs, mainly reduced glutathione (GSH) and GSH conjugates, were released by lys- cells during lysine limitation when growth was dysregulated, but not during glucose limitation when growth was regulated. Limiting organosulfurs conferred a frequency-dependent fitness advantage to lys-orgS- by eliciting a proper slow growth program, including autophagy. Thus, nutrient-growth dysregulation is associated with rapid organosulfur release, which enables the selection of organosulfur auxotrophy to better tune cell growth to the metabolic environment. We speculate that evolutionarily novel stresses can trigger atypical release of certain metabolites, setting the stage for the evolution of new ecological interactions.

An Optimized Competitive-Aging Method Reveals Gene-Drug Interactions Underlying the Chronological Lifespan of Saccharomyces cerevisiae

The chronological lifespan of budding yeast is a model of aging and age-related diseases. This paradigm has recently allowed genome-wide screening of genetic factors underlying post-mitotic viability in a simple unicellular system, which underscores its potential to provide a comprehensive view of the aging process. However, results from different large-scale studies show little overlap and typically lack quantitative resolution to derive interactions among different aging factors. We previously introduced a sensitive, parallelizable approach to measure the chronological-lifespan effects of gene deletions based on the competitive aging of fluorescence-labeled strains. Here, we present a thorough description of the method, including an improved multiple-regression model to estimate the association between death rates and fluorescent signals, which accounts for possible differences in growth rate and experimental batch effects. We illustrate the experimental procedure-from data acquisition to calculation of relative survivorship-for ten deletion strains with known lifespan phenotypes, which is achieved with high technical replicability. We apply our method to screen for gene-drug interactions in an array of yeast deletion strains, which reveals a functional link between protein glycosylation and lifespan extension by metformin. Competitive-aging screening coupled to multiple-regression modeling provides a powerful, straight-forward way to identify aging factors in yeast and their interactions with pharmacological interventions.

Genetic interaction profiles of regulatory kinases differ between environmental conditions and cellular states

Cell growth and quiescence in eukaryotic cells is controlled by an evolutionarily conserved network of signaling pathways. Signal transduction networks operate to modulate a wide range of cellular processes and physiological properties when cells exit proliferative growth and initiate a quiescent state. How signaling networks function to respond to diverse signals that result in cell cycle exit and establishment of a quiescent state is poorly understood. Here, we studied the function of signaling pathways in quiescent cells using global genetic interaction mapping in the model eukaryotic cell, Saccharomyces cerevisiae (budding yeast). We performed pooled analysis of genotypes using molecular barcode sequencing (Bar-seq) to test the role of ~4,000 gene deletion mutants and ~12,000 pairwise interactions between all non-essential genes and the protein kinase genes TOR1, RIM15, and PHO85 in three different nutrient-restricted conditions in both proliferative and quiescent cells. We detect up to 10-fold more genetic interactions in quiescent cells than proliferative cells. We find that both individual gene effects and genetic interaction profiles vary depending on the specific pro-quiescence signal. The master regulator of quiescence, RIM15, shows distinct genetic interaction profiles in response to different starvation signals. However, vacuole-related functions show consistent genetic interactions with RIM15 in response to different starvation signals, suggesting that RIM15 integrates diverse signals to maintain protein homeostasis in quiescent cells. Our study expands genome-wide genetic interaction profiling to additional conditions, and phenotypes, and highlights the conditional dependence of epistasis.

Evaluation of Saccharomyces cerevisiae Wine Yeast Competitive Fitness in Enologically Relevant Environments by Barcode Sequencing

When a wine yeast is inoculated into grape juice the potential variation in juice composition that confronts it is huge. Assessing the performance characteristics of the many commercially available wine yeasts in the many possible grape juice compositions is a daunting task. To this end we have developed a barcoded Saccharomyces cerevisiae wine yeast collection to facilitate the task of performance assessment that will contribute to a broader understanding of genotype-phenotype relations. Barcode sequencing of mixed populations is used to monitor strain abundance in different grape juices and grape juice-like environments. Choice of DNA extraction method is shown to affect strain-specific barcode count in this highly related set of S. cerevisiae strains; however, the analytical approach is shown to be robust toward strain dependent variation in DNA extraction efficiency. Of the 38 unique compositional variables assessed, resistance to copper and SO₂ are found to be dominant discriminatory factors in wine yeast performance. Finally, a comparison of competitive fitness profile with performance in single inoculum fermentations reveal strain dependent correspondence of yeast performance using these two different approaches.

tRNA wobble-uridine modifications as amino acid sensors and regulators of cellular metabolic state

Cells must appropriately sense available nutrients and accordingly regulate their metabolic outputs, to survive. This mini-review considers the idea that conserved chemical modifications of wobble (U34) position tRNA uridines enable cells to sense nutrients and regulate their metabolic state. tRNA wobble uridines are chemically modified at the 2- and 5- positions, with a thiol (s2), and (commonly) a methoxycarbonylmethyl (mcm5) modification, respectively. These modifications reflect sulfur amino acid (methionine and cysteine) availability. The loss of these modifications has minor translation defects. However, they result in striking phenotypes consistent with an altered metabolic state. Using yeast, we recently discovered that the s2 modification regulates overall carbon and nitrogen metabolism, dependent on methionine availability. The loss of this modification results in rewired carbon (glucose) metabolism. Cells have reduced carbon flux towards the pentose phosphate pathway and instead increased flux towards storage carbohydrates-primarily trehalose, along with reduced nucleotide synthesis, and perceived amino acid starvation signatures. Remarkably, this metabolic rewiring in the s2U mutants is caused by mechanisms leading to intracellular phosphate limitation. Thus this U34 tRNA modification responds to methionine availability and integratively regulates carbon and nitrogen homeostasis, wiring cells to a 'growth' state. We interpret the importance of U34 modifications in the context of metabolic sensing and anabolism, emphasizing their intimate coupling to methionine metabolism.

A tRNA modification balances carbon and nitrogen metabolism by regulating phosphate homeostasis

Cells must appropriately sense and integrate multiple metabolic resources to commit to proliferation. Here, we report that S. cerevisiae cells regulate carbon and nitrogen metabolic homeostasis through tRNA U34-thiolation. Despite amino acid sufficiency, tRNA-thiolation deficient cells appear amino acid starved. In these cells, carbon flux towards nucleotide synthesis decreases, and trehalose synthesis increases, resulting in a starvation-like metabolic signature. Thiolation mutants have only minor translation defects. However, in these cells phosphate homeostasis genes are strongly down-regulated, resulting in an effectively phosphate-limited state. Reduced phosphate enforces a metabolic switch, where glucose-6-phosphate is routed towards storage carbohydrates. Notably, trehalose synthesis, which releases phosphate and thereby restores phosphate availability, is central to this metabolic rewiring. Thus, cells use thiolated tRNAs to perceive amino acid sufficiency, balance carbon and amino acid metabolic flux and grow optimally, by controlling phosphate availability. These results further biochemically explain how phosphate availability determines a switch to a 'starvation-state'.

Comparative Genomics Between Saccharomyces kudriavzevii and S. cerevisiae Applied to Identify Mechanisms Involved in Adaptation

Yeasts belonging to the Saccharomyces genus play an important role in human-driven fermentations. The species S. cerevisiae has been widely studied because it is the dominant yeast in most fermentations and it has been widely used as a model eukaryotic organism. Recently, other species of the Saccharomyces genus are gaining interest to solve the new challenges that the fermentation industry are facing. One of these species is S. kudriavzevii, which exhibits interesting physiological properties compared to S. cerevisiae, such as a better adaptation to grow at low temperatures, a higher glycerol synthesis and lower ethanol production. The aim of this study is to understand the molecular basis behind these phenotypic differences of biotechnological interest by using a species-based comparative genomics approach. In this work, we sequenced, assembled and annotated two new genomes of S. kudriavzevii. We used a combination of different statistical methods to identify functional divergence, signatures of positive selection and acceleration of substitution rates at specific amino acid sites of proteins in S. kudriavzevii when compared to S. cerevisiae, and vice versa. We provide a list of candidate genes in which positive selection could be acting during the evolution of both S. cerevisiae and S. kudriavzevii clades. Some of them could be related to certain important differences in metabolism previously reported by other authors such us DAL3 and ARO4, involved in nitrogen assimilation and amino acid biosynthesis. In addition, three of those genes (FBA1, ZIP1, and RQC2) showed accelerated evolutionary rates in Sk branch. Finally, genes of the riboflavin biosynthesis were also among those genes with a significant higher rate of nucleotide substitution and those proteins have amino acid positions contributing to functional divergence.

Functional genomics of dietary restriction and longevity in yeast

Dietary restriction-limitation of calories or other specific nutrients in the diet-is the sole non-genetic intervention known to extend the lifespan of a wide range of model organisms from yeast to mammals. Cell biology studies on the responses to dietary restriction have provided important clues about the mechanisms of longevity; however, a comprehensive genome-wide description of lifespan by dietary restriction has been mostly absent. Large-scale genetic analysis in the budding yeast Saccharomyces cerevisiae offers a great opportunity to uncover the conserved systems-level mechanisms that give way to longevity in response to diet. Here, we review recent advances in high-throughput phenotyping of the replicative and chronological life spans of yeast cells, which have contributed to our understanding of longevity by dietary restriction and the cellular crosstalks of nutrient-sensing regulation.

A collection of barcoded natural isolates of Saccharomyces paradoxus to study microbial evolutionary ecology

While the use of barcoded collections of laboratory microorganisms and the development of barcode-based cell tracking are rapidly developing in genetics and genomics research, tools to track natural populations are still lacking. The yeast Saccharomyces paradoxus is an emergent microbial model in ecology and evolution. More than five allopatric and sympatric lineages have been identified and hundreds of strains have been isolated for this species, allowing to assess the impact of natural diversity on complex traits. We constructed a collection of 550 barcoded and traceable strains of S. paradoxus, including all three North American lineages SpB, SpC, and SpC*. These strains are diploid, many have their genome fully sequenced and are barcoded with a unique 20 bp sequence that allows their identification and quantification. This yeast collection is functional for competitive experiments in pools as the barcodes allow to measure each lineage's and individual strains' fitness in common conditions. We used this tool to demonstrate that in the tested conditions, there are extensive genotype-by-environment interactions for fitness among S. paradoxus strains, which reveals complex evolutionary potential in variable environments. This barcoded collection provides a valuable resource for ecological genomics studies that will allow gaining a better understanding of S. paradoxus evolution and fitness-related traits.

Whi2 signals low leucine availability to halt yeast growth and cell death

Cells are exquisitely tuned to environmental ques. Amino acid availability is rapidly sensed, allowing cells to adjust molecular processes and implement short or long-term metabolic shifts accordingly. How levels of most individual amino acids may be sensed and subsequently signaled to inform cells of their nutrient status is largely unknown. We made the unexpected observation that small changes in the levels of specific amino acids can have a profound effect on yeast cell growth, leading to the identification of yeast Whi2 as a negative regulator of cell growth in low amino acids. Although Whi2 was originally thought to be fungi-specific, Whi2 appears to share a conserved structural domain found in a family of 25 largely uncharacterized human genes encoding the KCTD (potassium channel tetramerization domain) protein family. Insights gained from yeast Whi2 are likely to be revealing about human KCTDs, many of which have been implicated or demonstrated to cause disease when mutated. Here we report new evidence that Whi2 responds to specific amino acids in the medium, particularly low leucine levels. We also discuss the known pathways of amino acid signaling and potential points of regulation by Whi2 in nutrient signaling in yeast and mammals.

Comparative functional genomic screens of three yeast deletion collections reveal unexpected effects of genotype in response to diverse stress

The Yeast Knockout (YKO) collection has provided a wealth of functional annotations from genome-wide screens. An unintended consequence is that 76% of gene annotations derive from one genotype. The nutritional auxotrophies in the YKO, in particular, have phenotypic consequences. To address this issue, ‘prototrophic’ versions of the YKO collection have been constructed, either by introducing a plasmid carrying wild-type copies of the auxotrophic markers (Plasmid-Borne, PB_prot) or by backcrossing (Backcrossed, BC_prot) to a wild-type strain. To systematically assess the impact of the auxotrophies, genome-wide fitness profiles of prototrophic and auxotrophic collections were compared across diverse drug and environmental conditions in 250 experiments. Our quantitative profiles uncovered broad impacts of genotype on phenotype for three deletion collections, and revealed genotypic and strain-construction-specific phenotypes. The PB_prot collection exhibited fitness defects associated with plasmid maintenance, while BC_prot fitness profiles were compromised due to strain loss from nutrient selection steps during strain construction. The repaired prototrophic versions of the YKO collection did not restore wild-type behaviour nor did they clarify gaps in gene annotation resulting from the auxotrophic background. To remove marker bias and expand the experimental scope of deletion libraries, construction of a bona fide prototrophic collection from a wild-type strain will be required.

Bartender: a fast and accurate clustering algorithm to count barcode reads

Motivation

Barcode sequencing (bar-seq) is a high-throughput, and cost effective method to assay large numbers of cell lineages or genotypes in complex cell pools. Because of its advantages, applications for bar-seq are quickly growing-from using neutral random barcodes to study the evolution of microbes or cancer, to using pseudo-barcodes, such as shRNAs or sgRNAs to simultaneously screen large numbers of cell perturbations. However, the computational pipelines for bar-seq clustering are not well developed. Available methods often yield a high frequency of under-clustering artifacts that result in spurious barcodes, or over-clustering artifacts that group distinct barcodes together. Here, we developed Bartender, an accurate clustering algorithm to detect barcodes and their abundances from raw next-generation sequencing data.

Results

In contrast with existing methods that cluster based on sequence similarity alone, Bartender uses a modified two-sample proportion test that also considers cluster size. This modification results in higher accuracy and lower rates of under- and over-clustering artifacts. Additionally, Bartender includes unique molecular identifier handling and a 'multiple time point' mode that matches barcode clusters between different clustering runs for seamless handling of time course data. Bartender is a set of simple-to-use command line tools that can be performed on a laptop at comparable run times to existing methods.

Availability and implementation

Bartender is available at no charge for non-commercial use at https://github.com/LaoZZZZZ/bartender-1.1.

Contact

sasha.levy@stonybrook.edu or song.wu@stonybrook.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Whi2 is a conserved negative regulator of TORC1 in response to low amino acids

Yeast WHI2 was originally identified in a genetic screen for regulators of cell cycle arrest and later suggested to function in general stress responses. However, the function of Whi2 is unknown. Whi2 has predicted structure and sequence similarity to human KCTD family proteins, which have been implicated in several cancers and are causally associated with neurological disorders but are largely uncharacterized. The identification of conserved functions between these yeast and human proteins may provide insight into disease mechanisms. We report that yeast WHI2 is a new negative regulator of TORC1 required to suppress TORC1 activity and cell growth specifically in response to low amino acids. In contrast to current opinion, WHI2 is dispensable for TORC1 inhibition in low glucose. The only widely conserved mechanism that actively suppresses both yeast and mammalian TORC1 specifically in response to low amino acids is the conserved SEACIT/GATOR1 complex that inactivates the TORC1-activating RAG-like GTPases. Unexpectedly, Whi2 acts independently and simultaneously with these established GATOR1-like Npr2-Npr3-Iml1 and RAG-like Gtr1-Gtr2 complexes, and also acts independently of the PKA pathway. Instead, Whi2 inhibits TORC1 activity through its binding partners, protein phosphatases Psr1 and Psr2, which were previously thought to only regulate amino acid levels downstream of TORC1. Furthermore, the ability to suppress TORC1 is conserved in the SKP1/BTB/POZ domain-containing, Whi2-like human protein KCTD11 but not other KCTD family members tested.

Genomewide mechanisms of chronological longevity by dietary restriction in budding yeast

Dietary restriction is arguably the most promising nonpharmacological intervention to extend human life and health span. Yet, only few genetic regulators mediating the cellular response to dietary restriction are known, and the question remains which other regulatory factors are involved. Here, we measured at the genomewide level the chronological lifespan of Saccharomyces cerevisiae gene deletion strains under two nitrogen source regimens, glutamine (nonrestricted) and γ‐aminobutyric acid (restricted). We identified 473 mutants with diminished or enhanced extension of lifespan. Functional analysis of such dietary restriction genes revealed novel processes underlying longevity by the nitrogen source quality, which also allowed us to generate a prioritized catalogue of transcription factors orchestrating the dietary restriction response. Importantly, deletions of transcription factors Msn2, Msn4, Snf6, Tec1, and Ste12 resulted in diminished lifespan extension and defects in cell cycle arrest upon nutrient starvation, suggesting that regulation of the cell cycle is a major mechanism of chronological longevity. We further show that STE12 overexpression is enough to extend lifespan, linking the pheromone/invasive growth pathway with cell survivorship. Our global picture of the genetic players of longevity by dietary restriction highlights intricate regulatory cross‐talks in aging cells.

Construction of Comprehensive Dosage-Matching Core Histone Mutant Libraries for Saccharomyces cerevisiae

Saccharomyces cerevisiae contains two genes for each core histone, which are presented as pairs under the control of a divergent promoter, i.e., HHT1-HHF1, HHT2-HHF2, HTA1-HTB1 and HTA2-HTB2HHT1-HHF1, and HHT2-HHF2 encode histone H3 and H4 with identical amino acid sequences but under the control of differently regulated promoters. Previous mutagenesis studies were carried out by deleting one pair and mutating the other one. Here, we present the design and construction of three additional libraries covering HTA1-HTB1, HTA2-HTB2, and HHT1-HHF1 respectively. Together with the previously described library of HHT2-HHF2 mutants, a systematic and complete collection of mutants for each of the eight core S. cerevisiae histone genes becomes available. Each designed mutant was incorporated into the genome, generating three more corresponding libraries of yeast strains. We demonstrated that, although, under normal growth conditions, strains with single-copy integrated histone genes lacked phenotypes, in some growth conditions, growth deficiencies were observed. Specifically, we showed that addition of a second copy of the mutant histone gene could rescue the lethality in some previously known mutants that cannot survive with a single copy. This resource enables systematic studies of function of each nucleosome residue in plasmid, single-copy, and double-copy integrated formats.

A scalable double-barcode sequencing platform for characterization of dynamic protein-protein interactions

Several large-scale efforts have systematically catalogued protein-protein interactions (PPIs) of a cell in a single environment. However, little is known about how the protein interactome changes across environmental perturbations. Current technologies, which assay one PPI at a time, are too low throughput to make it practical to study protein interactome dynamics. Here, we develop a highly parallel protein-protein interaction sequencing (PPiSeq) platform that uses a novel double barcoding system in conjunction with the dihydrofolate reductase protein-fragment complementation assay in Saccharomyces cerevisiae. PPiSeq detects PPIs at a rate that is on par with current assays and, in contrast with current methods, quantitatively scores PPIs with enough accuracy and sensitivity to detect changes across environments. Both PPI scoring and the bulk of strain construction can be performed with cell pools, making the assay scalable and easily reproduced across environments. PPiSeq is therefore a powerful new tool for large-scale investigations of dynamic PPIs.

iSeq: A New Double-Barcode Method for Detecting Dynamic Genetic Interactions in Yeast

Systematic screens for genetic interactions are a cornerstone of both network and systems biology. However, most screens have been limited to characterizing interaction networks in a single environment. Moving beyond this static view of the cell requires a major technological advance to increase the throughput and ease of replication in these assays. Here, we introduce iSeq-a platform to build large double barcode libraries and rapidly assay genetic interactions across environments. We use iSeq in yeast to measure fitness in three conditions of nearly 400 clonal strains, representing 45 possible single or double gene deletions, including multiple replicate strains per genotype. We show that iSeq fitness and interaction scores are highly reproducible for the same clonal strain across replicate cultures. However, consistent with previous work, we find that replicates with the same putative genotype have highly variable genetic interaction scores. By whole-genome sequencing 102 of our strains, we find that segregating variation and de novo mutations, including aneuploidy, occur frequently during strain construction, and can have large effects on genetic interaction scores. Additionally, we uncover several new environment-dependent genetic interactions, suggesting that barcode-based genetic interaction assays have the potential to significantly expand our knowledge of genetic interaction networks.

Multiplex growth rate phenotyping of synthetic mutants in selection to engineer glucose and xylose co-utilization in Escherichia coli

Engineering the simultaneous consumption of glucose and xylose sugars is critical to enable the sustainable production of biofuels from lignocellulosic biomass. In most major industrial microorganisms glucose completely inhibits the uptake of xylose, limiting efficient sugar mixture conversion. In E. coli removal of the major glucose transporter PTS allows for glucose and xylose co-consumption but only after prolonged adaptation, which is an effective process but hard to control and prone to co-evolving undesired traits. Here we synthetically engineer mutants to target sugar co-consumption properties; we subject a PTS^- mutant to a short adaptive step and subsequently either delete or overexpress key genes previously suggested to affect sugar consumption. Screening the co-consumption properties of these mutants individually is very laborious. We show we can evaluate sugar co-consumption properties in parallel by culturing the mutants in selection and applying a novel approach that computes mutant growth rates in selection using chromosomal barcode counts obtained from Next-Generation Sequencing. We validate this multiplex growth rate phenotyping approach with individual mutant pure cultures, identify new instances of mutants cross-feeding on metabolic byproducts, and, importantly, find that the rates of glucose and xylose co-consumption can be tuned by altering glucokinase expression in our PTS^- background. Biotechnol. Bioeng. 2017;114: 885-893. © 2016 Wiley Periodicals, Inc.

Identification of Chemical-Genetic Interactions via Parallel Analysis of Barcoded Yeast Strains

The Yeast Knockout Collection is a complete set of gene deletion strains for the budding yeast, Saccharomyces cerevisiae In each strain, one of approximately 6000 open-reading frames is replaced with a dominant selectable marker flanked by two DNA barcodes. These barcodes, which are unique to each gene, allow the growth of thousands of strains to be individually measured from a single pooled culture. The collection, and other resources that followed, has ushered in a new era in chemical biology, enabling unbiased and systematic identification of chemical-genetic interactions (CGIs) with remarkable ease. CGIs link bioactive compounds to biological processes, and hence can reveal the mechanism of action of growth-inhibitory compounds in vivo, including those of antifungal, antibiotic, and anticancer drugs. The chemogenomic profiling method described here measures the sensitivity induced in yeast heterozygous and homozygous deletion strains in the presence of a chemical inhibitor of growth (termed haploinsufficiency profiling and homozygous profiling, respectively, or HIPHOP). The protocol is both scalable and amenable to automation. After competitive growth of yeast knockout collection cultures, with and without chemical inhibitors, CGIs can be identified and quantified using either array- or sequencing-based approaches as described here.

Functional genomic analysis reveals overlapping and distinct features of chronologically long-lived yeast populations

Yeast chronological lifespan (CLS) is extended by multiple genetic and environmental manipulations, including caloric restriction (CR). Understanding the common changes in molecular pathways induced by such manipulations could potentially reveal conserved longevity mechanisms. We therefore performed gene expression profiling on several long-lived yeast populations, including an ade4∆ mutant defective in de novo purine (AMP) biosynthesis, and a calorie restricted WT strain. CLS was also extended by isonicotinamide (INAM) or expired media derived from CR cultures. Comparisons between these diverse long-lived conditions revealed a common set of differentially regulated genes, several of which were potential longevity biomarkers. There was also enrichment for genes that function in CLS regulation, including a long-lived adenosine kinase mutant (ado1∆) that links CLS regulation to the methyl cycle and AMP. Genes co-regulated between the CR and ade4∆ conditions were dominated by GO terms related to metabolism of alternative carbon sources, consistent with chronological longevity requiring efficient acetate/acetic acid utilization. Alternatively, treating cells with isonicotinamide (INAM) or the expired CR media resulted in GO terms predominantly related to cell wall remodeling, consistent with improved stress resistance and protection against external insults like acetic acid. Acetic acid therefore has both beneficial and detrimental effects on CLS.

A nested parallel experiment demonstrates differences in intensity-dependence between RNA-seq and microarrays

Understanding the differences between microarray and RNA-Seq technologies for measuring gene expression is necessary for informed design of experiments and choice of data analysis methods. Previous comparisons have come to sometimes contradictory conclusions, which we suggest result from a lack of attention to the intensity-dependent nature of variation generated by the technologies. To examine this trend, we carried out a parallel nested experiment performed simultaneously on the two technologies that systematically split variation into four stages (treatment, biological variation, library preparation and chip/lane noise), allowing a separation and comparison of the sources of variation in a well-controlled cellular system, Saccharomyces cerevisiae. With this novel dataset, we demonstrate that power and accuracy are more dependent on per-gene read depth in RNA-Seq than they are on fluorescence intensity in microarrays. However, we carried out quantitative PCR validations which indicate that microarrays may demonstrate greater systematic bias in low-intensity genes than in RNA-seq.

Determination of in vivo RNA kinetics using RATE-seq

The abundance of a transcript is determined by its rate of synthesis and its rate of degradation; however, global methods for quantifying RNA abundance cannot distinguish variation in these two processes. Here, we introduce RNA approach to equilibrium sequencing (RATE-seq), which uses in vivo metabolic labeling of RNA and approach to equilibrium kinetics, to determine absolute RNA degradation and synthesis rates. RATE-seq does not disturb cellular physiology, uses straightforward normalization with exogenous spike-ins, and can be readily adapted for studies in most organisms. We demonstrate the use of RATE-seq to estimate genome-wide kinetic parameters for coding and noncoding transcripts in Saccharomyces cerevisiae.

Peroxisomes are required for lipid metabolism and muscle function in Drosophila melanogaster

Peroxisomes are ubiquitous organelles that perform lipid and reactive oxygen species metabolism. Defects in peroxisome biogenesis cause peroxisome biogenesis disorders (PBDs). The most severe PBD, Zellweger syndrome, is characterized in part by neuronal dysfunction, craniofacial malformations, and low muscle tone (hypotonia). These devastating diseases lack effective therapies and the development of animal models may reveal new drug targets. We have generated Drosophila mutants with impaired peroxisome biogenesis by disrupting the early peroxin gene pex3, which participates in budding of pre-peroxisomes from the ER and peroxisomal membrane protein localization. pex3 deletion mutants lack detectible peroxisomes and die before or during pupariation. At earlier stages of development, larvae lacking Pex3 display reduced size and impaired lipid metabolism. Selective loss of peroxisomes in muscles impairs muscle function and results in flightless animals. Although, hypotonia in PBD patients is thought to be a secondary effect of neuronal dysfunction, our results suggest that peroxisome loss directly affects muscle physiology, possibly by disrupting energy metabolism. Understanding the role of peroxisomes in Drosophila physiology, specifically in muscle cells may reveal novel aspects of PBD etiology.

The yeast deletion collection: a decade of functional genomics

The yeast deletion collections comprise >21,000 mutant strains that carry precise start-to-stop deletions of ∼6000 open reading frames. This collection includes heterozygous and homozygous diploids, and haploids of both MATa and MATα mating types. The yeast deletion collection, or yeast knockout (YKO) set, represents the first and only complete, systematically constructed deletion collection available for any organism. Conceived during the Saccharomyces cerevisiae sequencing project, work on the project began in 1998 and was completed in 2002. The YKO strains have been used in numerous laboratories in >1000 genome-wide screens. This landmark genome project has inspired development of numerous genome-wide technologies in organisms from yeast to man. Notable spinoff technologies include synthetic genetic array and HIPHOP chemogenomics. In this retrospective, we briefly describe the yeast deletion project and some of its most noteworthy biological contributions and the impact that these collections have had on the yeast research community and on genomics in general.

High-resolution profiling of stationary-phase survival reveals yeast longevity factors and their genetic interactions

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.

Design and analysis of Bar-seq experiments

High-throughput quantitative DNA sequencing enables the parallel phenotyping of pools of thousands of mutants. However, the appropriate analytical methods and experimental design that maximize the efficiency of these methods while maintaining statistical power are currently unknown. Here, we have used Bar-seq analysis of the Saccharomyces cerevisiae yeast deletion library to systematically test the effect of experimental design parameters and sequence read depth on experimental results. We present computational methods that efficiently and accurately estimate effect sizes and their statistical significance by adapting existing methods for RNA-seq analysis. Using simulated variation of experimental designs, we found that biological replicates are critical for statistical analysis of Bar-seq data, whereas technical replicates are of less value. By subsampling sequence reads, we found that when using four-fold biological replication, 6 million reads per condition achieved 96% power to detect a two-fold change (or more) at a 5% false discovery rate. Our guidelines for experimental design and computational analysis enables the study of the yeast deletion collection in up to 30 different conditions in a single sequencing lane. These findings are relevant to a variety of pooled genetic screening methods that use high-throughput quantitative DNA sequencing, including Tn-seq.

Yeast metabolic and signaling genes are required for heat-shock survival and have little overlap with the heat-induced genes

Genome-wide gene-expression studies have shown that hundreds of yeast genes are induced or repressed transiently by changes in temperature; many are annotated to stress response on this basis. To obtain a genome-scale assessment of which genes are functionally important for innate and/or acquired thermotolerance, we combined the use of a barcoded pool of ~4,800 nonessential, prototrophic Saccharomyces cerevisiae deletion strains with Illumina-based deep-sequencing technology. As reported in other recent studies that have used deletion mutants to study stress responses, we observed that gene deletions resulting in the highest thermosensitivity generally are not the same as those transcriptionally induced in response to heat stress. Functional analysis of identified genes revealed that metabolism, cellular signaling, and chromatin regulation play roles in regulating thermotolerance and in acquired thermotolerance. However, for most of the genes identified, the molecular mechanism behind this action remains unclear. In fact, a large fraction of identified genes are annotated as having unknown functions, further underscoring our incomplete understanding of the response to heat shock. We suggest that survival after heat shock depends on a small number of genes that function in assessing the metabolic health of the cell and/or regulate its growth in a changing environment.

Aging and differentiation in yeast populations: elders with different properties and functions

Over the past decade, it has become evident that similarly to cells forming metazoan tissues, yeast cells have the ability to differentiate and form specialized cell types. Examples of yeast cellular differentiation have been identified both in yeast liquid cultures and within multicellular structures occupying solid surfaces. Most current knowledge on different cell types comes from studies of the spatiotemporal internal architecture of colonies developing on various media. With a few exceptions, yeast cell differentiation often concerns nongrowing, stationary-phase cells and leads to the formation of cell subpopulations differing in stress resistance, cell metabolism, respiration, ROS production, and others. These differences can affect longevity of particular subpopulations. In contrast to liquid cultures, where various cell types are dispersed within stationary-phase populations, cellular differentiation depends on the specific position of particular cells within multicellular colonies. Differentiated colonies, thus, resemble primitive multicellular organisms, in which the gradients of certain compounds and the position of cells within the structure affect cellular differentiation. In this review, we summarize and compare the properties of diverse types of differentiated chronologically aging yeast cells that have been identified in colonies growing on different media, as well as of those found in liquid cultures.

The use of chemostats in microbial systems biology

Cells regulate their rate of growth in response to signals from the external world. As the cell grows, diverse cellular processes must be coordinated including macromolecular synthesis, metabolism and ultimately, commitment to the cell division cycle. The chemostat, a method of experimentally controlling cell growth rate, provides a powerful means of systematically studying how growth rate impacts cellular processes - including gene expression and metabolism - and the regulatory networks that control the rate of cell growth. When maintained for hundreds of generations chemostats can be used to study adaptive evolution of microbes in environmental conditions that limit cell growth. We describe the principle of chemostat cultures, demonstrate their operation and provide examples of their various applications. Following a period of disuse after their introduction in the middle of the twentieth century, the convergence of genome-scale methodologies with a renewed interest in the regulation of cell growth and the molecular basis of adaptive evolution is stimulating a renaissance in the use of chemostats in biological research.

Genomic phenotyping by barcode sequencing broadly distinguishes between alkylating agents, oxidizing agents, and non-genotoxic agents, and reveals a role for aromatic amino acids in cellular recovery after quinone exposure

Toxicity screening of compounds provides a means to identify compounds harmful for human health and the environment. Here, we further develop the technique of genomic phenotyping to improve throughput while maintaining specificity. We exposed cells to eight different compounds that rely on different modes of action: four genotoxic alkylating (methyl methanesulfonate (MMS), N-Methyl-N-nitrosourea (MNU), N,N′-bis(2-chloroethyl)-N-nitroso-urea (BCNU), N-ethylnitrosourea (ENU)), two oxidizing (2-methylnaphthalene-1,4-dione (menadione, MEN), benzene-1,4-diol (hydroquinone, HYQ)), and two non-genotoxic (methyl carbamate (MC) and dimethyl sulfoxide (DMSO)) compounds. A library of S. cerevisiae 4,852 deletion strains, each identifiable by a unique genetic ‘barcode’, were grown in competition; at different time points the ratio between the strains was assessed by quantitative high throughput ‘barcode’ sequencing. The method was validated by comparison to previous genomic phenotyping studies and 90% of the strains identified as MMS-sensitive here were also identified as MMS-sensitive in a much lower throughput solid agar screen. The data provide profiles of proteins and pathways needed for recovery after both genotoxic and non-genotoxic compounds. In addition, a novel role for aromatic amino acids in the recovery after treatment with oxidizing agents was suggested. The role of aromatic acids was further validated; the quinone subgroup of oxidizing agents were extremely toxic in cells where tryptophan biosynthesis was compromised.

Predicting complex phenotype-genotype interactions to enable yeast engineering: Saccharomyces cerevisiae as a model organism and a cell factory

There is an increasing use of systems biology approaches in both "red" and "white" biotechnology in order to enable medical, medicinal, and industrial applications. The intricate links between genotype and phenotype may be explained through the use of the tools developed in systems biology, synthetic biology, and evolutionary engineering. Biomedical and biotechnological research are among the fields that could benefit most from the elucidation of this complex relationship. Researchers have studied fitness extensively to explain the phenotypic impacts of genetic variations. This elaborate network of dependencies and relationships so revealed are further complicated by the influence of environmental effects that present major challenges to our achieving an understanding of the cellular mechanisms leading to healthy or diseased phenotypes or optimized production yields. An improved comprehension of complex genotype-phenotype interactions and their accurate prediction should enable us to more effectively engineer yeast as a cell factory and to use it as a living model of human or pathogen cells in intelligent screens for new drugs. This review presents different methods and approaches undertaken toward improving our understanding and prediction of the growth phenotype of the yeast Saccharomyces cerevisiae as both a model and a production organism.

Restricted pleiotropy facilitates mutational erosion of major life-history traits

Radical shifts to new natural and human made niches can make some functions unneeded and thus exposed to genetic degeneration. Here we ask not about highly specialized and rarely used functions but those relating to major life-history traits, rate of growth, and resistance to prolonged starvation. We found that in yeast each of the two traits was visibly impaired by at least several hundred individual gene deletions. There were relatively few deletions affecting negatively both traits and likely none harming one but improving the other. Functional profiles of gene deletions affecting either growth or survival were strikingly different: the first related chiefly to synthesis of macromolecules whereas the second to maintenance and recycling of cellular structures. The observed pattern of gene indispensability corresponds to that of gene induction, providing a rather rare example of agreement between the results of deletion and expression studies. We conclude that transitions to new environments in which the ability to grow at possibly fastest rate or survive under very long starvation become practically unnecessary can result in rapid erosion of these vital functions because they are coded by many genes constituting large mutational targets and because restricted pleiotropy is unlikely to constrain this process.

Abundant gene-by-environment interactions in gene expression reaction norms to copper within Saccharomyces cerevisiae

Genetic variation for plastic phenotypes potentially contributes phenotypic variation to populations that can be selected during adaptation to novel ecological contexts. However, the basis and extent of plastic variation that manifests in diverse environments remains elusive. Here, we characterize copper reaction norms for mRNA abundance among five Saccharomyces cerevisiae strains to 1) describe population variation across the full range of ecologically relevant copper concentrations, from starvation to toxicity, and 2) to test the hypothesis that plastic networks exhibit increased population variation for gene expression. We find that although the vast majority of the variation is small in magnitude (considerably <2-fold), not just some, but most genes demonstrate variable expression across environments, across genetic backgrounds, or both. Plastically expressed genes included both genes regulated directly by copper-binding transcription factors Mac1 and Ace1 and genes indirectly responding to the downstream metabolic consequences of the copper gradient, particularly genes involved in copper, iron, and sulfur homeostasis. Copper-regulated gene networks exhibited more similar behavior within the population in environments where those networks have a large impact on fitness. Nevertheless, expression variation in genes like Cup1, important to surviving copper stress, was linked with variation in mitotic fitness and in the breadth of differential expression across the genome. By revealing a broader and deeper range of population variation, our results provide further evidence for the interconnectedness of genome-wide mRNA levels, their dependence on environmental context and genetic background, and the abundance of variation in gene expression that can contribute to future evolution.