We present a yeast chemical-genomics approach designed to identify genes that when mutated confer drug resistance, thereby providing insight about the modes of action of compounds. We developed a molecular barcoded yeast open reading frame (MoBY-ORF) library in which each gene, controlled by its native promoter and terminator, is cloned into a centromere-based vector along with two unique oligonucleotide barcodes. The MoBY-ORF resource has numerous genetic and chemical-genetic applications, but here we focus on cloning wild-type versions of mutant drug-resistance genes using a complementation strategy and on simultaneously assaying the fitness of all transformants with barcode microarrays. The complementation cloning was validated by mutation detection using whole-genome yeast tiling microarrays, which identified unique polymorphisms associated with a drug-resistant mutant. We used the MoBY-ORF library to identify the genetic basis of several drug-resistant mutants and in this analysis discovered a new class of sterol-binding compounds.
The genome of budding yeast (Saccharomyces cerevisiae) contains approximately 5800 protein-encoding genes, the majority of which are associated with some known biological function. Yet the extent of amino acid sequence conservation of these genes over all phyla has only been partially examined. Here we provide a more comprehensive overview and visualization of the conservation of yeast genes and a means for browsing and exploring the data in detail, down to the individual yeast gene, at http://yeast-phylogroups.princeton.edu. We used data from the OrthoMCL database, which has defined orthologs from approximately 150 completely sequenced genomes, including diverse representatives of the archeal, bacterial, and eukaryotic domains. By clustering genes based on similar patterns of conservation, we organized and visualized all the protein-encoding genes in yeast as a single heat map. Most genes fall into one of eight major clusters, called “phylogroups.” Gene ontology analysis of the phylogroups revealed that they were associated with specific, distinct trends in gene function, generalizations likely to be of interest to a wide range of biologists.
yeast; evolution; phylogeny; orthology; genome
The Fluorescence in situ Hybridization (FISH) method allows one to detect nucleic acids in the native cellular environment. Here we provide a protocol for using FISH to quantify the number of mRNAs in single yeast cells. Cells can be grown in any condition of interest and then fixed and made permeable. Subsequently, multiple single-stranded deoxyoligonucleotides conjugated to fluorescent dyes are used to label and visualize mRNAs. Diffraction-limited fluorescence from single mRNA molecules is quantified using a spot-detection algorithm to identify and count the number of mRNAs per cell. While the more standard quantification methods of northern blots, RT-PCR and gene expression microarrays provide information on average mRNAs in the bulk population, FISH facilitates both the counting and localization of these mRNAs in single cells at single-molecule resolution.
Genetics; Issue 76; Molecular Biology; Cellular Biology; Microbiology; Biochemistry; Genomics; Life Sciences (General); FISH; single cells; mRNA; transcripts; Saccharomyces cerevisiae; yeast cells; single-molecule; yeast
High concentrations of ammonium at physiological concentrations of potassium are toxic for the standard laboratory strain of Saccharomyces cerevisiae. In the original description of this metabolic phenotype, we focused on the standard laboratory strains of Saccharomyces. In this study, we screened a large collection of S. cerevisiae natural isolates and identified one strain that is resistant to high concentrations of ammonium. This strain, K12, was isolated in sake breweries. When the K12 strain was crossed to the standard laboratory strain (FY4), the resulting tetrads displayed 2:2 segregation of the resistance phenotype, suggesting a single gene trait. Using a bulk segregant analysis strategy, we mapped this trait to a 150-kb region on chromosome X containing the TRK1 gene. This gene encodes a transporter required for high-affinity potassium transport in S. cerevisiae. Data from reciprocal hemizygosity experiments with TRK1 deletion strains in K12 and BY backgrounds, as well as analysis of the deletion of this gene in the K12 strain, demonstrate that the K12 allele of TRK1 is responsible for ammonium toxicity resistance. Furthermore, we determined the minimal amount of potassium required for both the K12 and laboratory strain needed for growth. These results demonstrate that the gene encoded by the K12 allele of TRK1 has a greater affinity for potassium than the standard allele of TRK1 found in Saccharomyces strains. We hypothesize that this greater-affinity allele of the potassium transporter reduces the flux of ammonium into the yeast cells under conditions of ammonium toxicity. These findings further refine our understanding of ammonium toxicity in yeast and provide an example of using natural variation to understand cellular processes.
Desiccation is thought to impose many stresses. Which of these stresses is responsible for desiccation-induced death and how the stress response is regulated are unknown, however. Here we use Saccharomyces cerevisiae to show that reduction of a 60S biogenesis intermediate via RAS or TOR down-regulation increases desiccation tolerance.
Tolerance to desiccation in cultures of Saccharomyces cerevisiae is inducible; only one in a million cells from an exponential culture survive desiccation compared with one in five cells in stationary phase. Here we exploit the desiccation sensitivity of exponentially dividing cells to understand the stresses imposed by desiccation and their stress response pathways. We found that induction of desiccation tolerance is cell autonomous and that there is an inverse correlation between desiccation tolerance and growth rate in glucose-, ammonia-, or phosphate-limited continuous cultures. A transient heat shock induces a 5000–fold increase in desiccation tolerance, whereas hyper-ionic, -reductive, -oxidative, or -osmotic stress induced much less. Furthermore, we provide evidence that the Sch9p-regulated branch of the TOR and Ras-cAMP pathway inhibits desiccation tolerance by inhibiting the stress response transcription factors Gis1p, Msn2p, and Msn4p and by activating Sfp1p, a ribosome biogenesis transcription factor. Among 41 mutants defective in ribosome biogenesis, a subset defective in 60S showed a dramatic increase in desiccation tolerance independent of growth rate. We suggest that reduction of a specific intermediate in 60S biogenesis, resulting from conditions such as heat shock and nutrient deprivation, increases desiccation tolerance.
The nutrition and the growth rate of a cell are two interacting factors with pervasive physiological effects. Our experiments decouple these factors and demonstrate the role of a growth rate signal, independent of the actual rate of biomass increase, on gene regulation, the cell division cycle, and the switch to a respiro-fermentative metabolism.
To survive and proliferate, cells need to coordinate their metabolism, gene expression, and cell division. To understand this coordination and the consequences of its failure, we uncoupled biomass synthesis from nutrient signaling by growing, in chemostats, yeast auxotrophs for histidine, lysine, or uracil in excess of natural nutrients (i.e., sources of carbon, nitrogen, sulfur, and phosphorus), such that their growth rates (GRs) were regulated by the availability of their auxotrophic requirements. The physiological and transcriptional responses to GR changes of these cultures differed markedly from the respective responses of prototrophs whose growth-rate is regulated by the availability of natural nutrients. The data for all auxotrophs at all GRs recapitulated the features of aerobic glycolysis, fermentation despite high oxygen levels in the growth media. In addition, we discovered wide bimodal distributions of cell sizes, indicating a decoupling between the cell division cycle (CDC) and biomass production. The aerobic glycolysis was reflected in a general signature of anaerobic growth, including substantial reduction in the expression levels of mitochondrial and tricarboxylic acid genes. We also found that the magnitude of the transcriptional growth-rate response (GRR) in the auxotrophs is only 40–50% of the magnitude in prototrophs. Furthermore, the auxotrophic cultures express autophagy genes at substantially lower levels, which likely contributes to their lower viability. Our observations suggest that a GR signal, which is a function of the abundance of essential natural nutrients, regulates fermentation/respiration, the GRR, and the CDC.
Much of the spectacular progress in biomedical science over the last half-century is the direct consequence of the work of thousands of basic scientists whose primary goal was understanding of the fundamental working of living things. Despite this, many politicians, funders, and even scientists have come to believe that the pace of successful applications to medical diagnosis and therapy is limited by our willingness to focus directly on human health, rather than a continuing deficit of understanding. By this theory, curiosity-driven research, aimed at understanding, is no longer important or even useful. What is advocated instead is “translational” research aimed directly at treating disease. I believe this idea to be deeply mistaken. Recent history suggests instead that what we have learned in the last 50 years is only the beginning. The way forward is to invest more in basic science, not less.
A general method for the dynamic control of single gene expression in eukaryotes, with no off-target effects, is a long-sought tool for molecular and systems biologists. We engineered two artificial transcription factors (ATFs) that contain Cys2His2 zinc-finger DNA-binding domains of either the mouse transcription factor Zif268 (9 bp of specificity) or a rationally designed array of four zinc fingers (12 bp of specificity). These domains were expressed as fusions to the human estrogen receptor and VP16 activation domain. The ATFs can rapidly induce a single gene driven by a synthetic promoter in response to introduction of an otherwise inert hormone with no detectable off-target effects. In the absence of inducer, the synthetic promoter is inactive and the regulated gene product is not detected. Following addition of inducer, transcripts are induced >50-fold within 15 min. We present a quantitative characterization of these ATFs and provide constructs for making their implementation straightforward. These new tools allow for the elucidation of regulatory network elements dynamically, which we demonstrate with a major metabolic regulator, Gcn4p.
Here we establish the utility of a recently described perturbative method to study complex regulatory circuits in vivo. By combining rapid modulation of single TFs under physiological conditions with genome-wide expression analysis, we elucidate several novel regulatory features within the pathways of sulfur assimilation and beyond.
In yeast, the pathways of sulfur assimilation are combinatorially controlled by five transcriptional regulators (three DNA-binding proteins [Met31p, Met32p, and Cbf1p], an activator [Met4p], and a cofactor [Met28p]) and a ubiquitin ligase subunit (Met30p). This regulatory system exerts combinatorial control not only over sulfur assimilation and methionine biosynthesis, but also on many other physiological functions in the cell. Recently we characterized a gene induction system that, upon the addition of an inducer, results in near-immediate transcription of a gene of interest under physiological conditions. We used this to perturb levels of single transcription factors during steady-state growth in chemostats, which facilitated distinction of direct from indirect effects of individual factors dynamically through quantification of the subsequent changes in genome-wide patterns of gene expression. We were able to show directly that Cbf1p acts sometimes as a repressor and sometimes as an activator. We also found circumstances in which Met31p/Met32p function as repressors, as well as those in which they function as activators. We elucidated and numerically modeled feedback relationships among the regulators, notably feedforward regulation of Met32p (but not Met31p) by Met4p that generates dynamic differences in abundance that can account for the differences in function of these two proteins despite their identical binding sites.
The sulfur assimilation pathway is used to understand how combinatorial transcription coordinates cellular processes. Global gene expression was measured in yeast lacking different combinations of transcription factors in order to determine how these factors coordinate sulfur assimilation with diverse metabolic and physiological processes.
Methionine abundance affects diverse cellular functions, including cell division, redox homeostasis, survival under starvation, and oxidative stress response. Regulation of the methionine biosynthetic pathway involves three DNA-binding proteins—Met31p, Met32p, and Cbf1p. We hypothesized that there exists a “division of labor” among these proteins that facilitates coordination of methionine biosynthesis with diverse biological processes. To explore combinatorial control in this regulatory circuit, we deleted CBF1, MET31, and MET32 individually and in combination in a strain lacking methionine synthase. We followed genome-wide gene expression as these strains were starved for methionine. Using a combination of bioinformatic methods, we found that these regulators control genes involved in biological processes downstream of sulfur assimilation; many of these processes had not previously been documented as methionine dependent. We also found that the different factors have overlapping but distinct functions. In particular, Met31p and Met32p are important in regulating methionine metabolism, whereas p functions as a “generalist” transcription factor that is not specific to methionine metabolism. In addition, Met31p and Met32p appear to regulate iron–sulfur cluster biogenesis through direct and indirect mechanisms and have distinguishable target specificities. Finally, CBF1 deletion sometimes has the opposite effect on gene expression from MET31 and MET32 deletion.
Cytoprotective functions of a 20S proteasome activator were investigated. Saccharomyces cerevisiae
Blm10 and human 20S proteasome activator 200 (PA200) are homologs. Comparative genome-wide analyses of untreated diploid cells lacking Blm10 and growing at steady state at defined growth rates revealed downregulation of numerous genes required for accurate chromosome structure, assembly and repair, and upregulation of a specific subset of genes encoding protein-folding chaperones. Blm10 loss or truncation of the Ubp3/Blm3 deubiquitinating enzyme caused massive chromosomal damage and cell death in homozygous diploids after phleomycin treatments, indicating that Blm10 and Ubp3/Blm3 function to stabilize the genome and protect against cell death. Diploids lacking Blm10 also were sensitized to doxorubicin, hydroxyurea, 5-fluorouracil, rapamycin, hydrogen peroxide, methyl methanesulfonate, and calcofluor. Fluorescently tagged Blm10 localized in nuclei, with enhanced fluorescence after DNA replication. After DNA damage that caused a classic G2/M arrest, fluorescence remained diffuse, with evidence of nuclear fragmentation in some cells. Protective functions of Blm10 did not require the carboxyl-terminal region that makes close contact with 20S proteasomes, indicating that protection does not require this contact or the truncated Blm10 can interact with the proteasome apart from this region. Without its carboxyl-terminus, Blm10(−339aa) localized to nuclei in untreated, nonproliferating (G0) cells, but not during G1 S, G2, and M. The results indicate Blm10 functions in protective mechanisms that include the machinery that assures proper assembly of chromosomes. These essential guardian functions have implications for ubiquitin-independent targeting in anticancer therapy. Targeting Blm10/PA200 together with one or more of the upregulated chaperones or a conventional treatment could be efficacious.
20S proteasome activator; BLM10/PA200; UBP3/BLM3; DNA damage; molecular chaperones
Transitions between the two phases of the cell growth cycle can account for the environmental stress response, the growth-rate response, and the cross-protection between slow growth and various types of stress factors. It is suggested that this mechanism is conserved across budding and fission yeast and normal human cells.
The respiratory metabolic cycle in budding yeast (Saccharomyces cerevisiae) consists of two phases that are most simply defined phenomenologically: low oxygen consumption (LOC) and high oxygen consumption (HOC). Each phase is associated with the periodic expression of thousands of genes, producing oscillating patterns of gene expression found in synchronized cultures and in single cells of slowly growing unsynchronized cultures. Systematic variation in the durations of the HOC and LOC phases can account quantitatively for well-studied transcriptional responses to growth rate differences. Here we show that a similar mechanism—transitions from the HOC phase to the LOC phase—can account for much of the common environmental stress response (ESR) and for the cross-protection by a preliminary heat stress (or slow growth rate) to subsequent lethal heat stress. Similar to the budding yeast metabolic cycle, we suggest that a metabolic cycle, coupled in a similar way to the ESR, in the distantly related fission yeast, Schizosaccharomyces pombe, and in humans can explain gene expression and respiratory patterns observed in these eukaryotes. Although metabolic cycling is associated with the G0/G1 phase of the cell division cycle of slowly growing budding yeast, transcriptional cycling was detected in the G2 phase of the division cycle in fission yeast, consistent with the idea that respiratory metabolic cycling occurs during the phases of the cell division cycle associated with mass accumulation in these divergent eukaryotes.
We developed systems to rapidly express any yeast gene or to specifically degrade any protein, each with minimal untargeted disturbance of cell physiology. We illustrate applications of these new tools for elucidating the architecture and dynamics of genetic regulatory networks.
We describe the development and characterization of a system that allows the rapid and specific induction of individual genes in the yeast Saccharomyces cerevisiae without changes in nutrients or temperature. The system is based on the chimeric transcriptional activator Gal4dbd.ER.VP16 (GEV). Upon addition of the hormone β-estradiol, cytoplasmic GEV localizes to the nucleus and binds to promoters containing Gal4p consensus binding sequences to activate transcription. With galactokinase Gal1p and transcriptional activator Gal4p absent, the system is fast-acting, resulting in readily detectable transcription within 5 min after addition of the inducer. β-Estradiol is nearly a gratuitous inducer, as indicated by genome-wide profiling that shows unintended induction (by GEV) of only a few dozen genes. Response to inducer is graded: intermediate concentrations of inducer result in production of intermediate levels of product protein in all cells. We present data illustrating several applications of this system, including a modification of the regulated degron method, which allows rapid and specific degradation of a specific protein upon addition of β-estradiol. These gene induction and protein degradation systems provide important tools for studying the dynamics and functional relationships of genes and their respective regulatory networks.
The sulfur assimilation and phospholipid biosynthesis pathways interact metabolically and transcriptionally. Genetic analysis, genome-wide sequencing, and expression microarrays show that regulators of these pathways, Met4p and Opi1p, control cellular methylation capacity that can limit the growth rate.
A yeast strain lacking Met4p, the primary transcriptional regulator of the sulfur assimilation pathway, cannot synthesize methionine. This apparently simple auxotroph did not grow well in rich media containing excess methionine, forming small colonies on yeast extract/peptone/dextrose plates. Faster-growing large colonies were abundant when overnight cultures were plated, suggesting that spontaneous suppressors of the growth defect arise with high frequency. To identify the suppressor mutations, we used genome-wide single-nucleotide polymorphism and standard genetic analyses. The most common suppressors were loss-of-function mutations in OPI1, encoding a transcriptional repressor of phospholipid metabolism. Using a new system that allows rapid and specific degradation of Met4p, we could study the dynamic expression of all genes following loss of Met4p. Experiments using this system with and without Opi1p showed that Met4 activates and Opi1p represses genes that maintain levels of S-adenosylmethionine (SAM), the substrate for most methyltransferase reactions. Cells lacking Met4p grow normally when either SAM is added to the media or one of the SAM synthetase genes is overexpressed. SAM is used as a methyl donor in three Opi1p-regulated reactions to create the abundant membrane phospholipid, phosphatidylcholine. Our results show that rapidly growing cells require significant methylation, likely for the biosynthesis of phospholipids.
Metabolic gene clusters—functionally related and physically clustered genes—are a common feature of some eukaryotic genomes. Two hypotheses have been advanced to explain the origin and maintenance of metabolic gene clusters: coordinated gene expression and genetic linkage. Here we test the hypothesis that selection for coordinated gene expression underlies the clustering of GAL genes in the yeast genome. We find that, although clustering coordinates the expression of GAL1 and GAL10, disrupting the GAL cluster does not impair fitness, suggesting that other mechanisms, such as genetic linkage, drive the origin and maintenance metabolic gene clusters.
We discovered that the relative durations of the phases of the yeast metabolic cycle change with the growth rate. These changes can explain mechanistically the transcriptional growth-rate responses of all yeast genes (25% of the genome) that we find to be the same across all studied nutrient limitations in either ethanol or glucose media.
We studied the steady-state responses to changes in growth rate of yeast when ethanol is the sole source of carbon and energy. Analysis of these data, together with data from studies where glucose was the carbon source, allowed us to distinguish a “universal” growth rate response (GRR) common to all media studied from a GRR specific to the carbon source. Genes with positive universal GRR include ribosomal, translation, and mitochondrial genes, and those with negative GRR include autophagy, vacuolar, and stress response genes. The carbon source–specific GRR genes control mitochondrial function, peroxisomes, and synthesis of vitamins and cofactors, suggesting this response may reflect the intensity of oxidative metabolism. All genes with universal GRR, which comprise 25% of the genome, are expressed periodically in the yeast metabolic cycle (YMC). We propose that the universal GRR may be accounted for by changes in the relative durations of the YMC phases. This idea is supported by oxygen consumption data from metabolically synchronized cultures with doubling times ranging from 5 to 14 h. We found that the high oxygen consumption phase of the YMC can coincide exactly with the S phase of the cell division cycle, suggesting that oxidative metabolism and DNA replication are not incompatible.
The fate of a newly arising beneficial mutation depends on many factors, such as the population size and the availability and fitness effects of other mutations that accumulate in the population. It has proved difficult to understand how these factors influence the trajectories of particular mutations, since experiments have primarily focused on characterizing successful clones emerging from a small number of evolving populations. Here, we present the results of a massively parallel experiment designed to measure the full spectrum of possible fates of new beneficial mutations in hundreds of experimental yeast populations, whether these mutations are ultimately successful or not. Using strains in which a particular class of beneficial mutation is detectable by fluorescence, we followed the trajectories of these beneficial mutations across 592 independent populations for 1000 generations. We find that the fitness advantage provided by individual mutations plays a surprisingly small role. Rather, underlying “background” genetic variation is quickly generated in our initially clonal populations and plays a crucial role in determining the fate of each individual beneficial mutation in the evolving population.
Comparative analysis of predicted protein sequences encoded by the genomes of Caenorhabditis elegans and Saccharomyces cerevisiae suggests that most of the core biological functions are carried out by orthologous proteins (proteins of different species that can be traced back to a common ancestor) that occur in comparable numbers. The specialized processes of signal transduction and regulatory control that are unique to the multicellular worm appear to use novel proteins, many of which re-use conserved domains. Major expansion of the number of some of these domains seen in the worm may have contributed to the advent of multicellularity. The proteins conserved in yeast and worm are likely to have orthologs throughout eukaryotes; in contrast, the proteins unique to the worm may well define metazoans.
Genetic and physical maps for the 16 chromosomes of Saccharomyces cerevisiae are presented. The genetic map is the result of 40 years of genetic analysis. The physical map was produced from the results of an international systematic sequencing effort. The data for the maps are accessible electronically from the Saccharomyces Genome Database (SGD: http://genome-www.stanford.edu/Saccharomyces/).
The S. cerevisiae genome is the most well-characterized eukaryotic genome and one of the simplest in terms of identifying open reading frames (ORFs), yet its primary annotation has been updated continually in the decade since its initial release in 1996 (Goffeau et al., 1996). The Saccharomyces Genome Database (SGD; www.yeastgenome.org) (Hirschman et al., 2006), the community-designated repository for this reference genome, strives to ensure that the S. cerevisiae annotation is as accurate and useful as possible. At SGD, the S. cerevisiae genome sequence and annotation are treated as a working hypothesis, which must be repeatedly tested and refined. In this paper, in celebration of the tenth anniversary of the completion of the S. cerevisiae genome sequence, we discuss the ways in which the S. cerevisiae sequence and annotation have changed, consider the multiple sources of experimental and comparative data on which these changes are based, and describe our methods for evaluating, incorporating and documenting these new data.
S. cerevisiae; genome sequence; genome annotation; comparative genomics; exon/intron boundaries
GO::TermFinder comprises a set of object-oriented Perl modules for accessing Gene Ontology (GO) information and evaluating and visualizing the collective annotation of a list of genes to GO terms. It can be used to draw conclusions from microarray and other biological data, calculating the statistical significance of each annotation. GO::TermFinder can be used on any system on which Perl can be run, either as a command line application, in single or batch mode, or as a web-based CGI script.
The full source code and documentation for GO::TermFinder are freely available from http://search.cpan.org/dist/GO-TermFinder/
The completion of the Saccharomyces cerevisiae genome sequencing project11 and the continued development of improved technology for large-scale genome analysis have led to tremendous growth in the amount of new yeast genetics and molecular biology data. Efficient organization, presentation, and dissemination of this information are essential if researchers are to exploit this knowledge. In addition, the development of tools that provide efficient analysis of this information and link it with pertinent information from other systems is becoming increasingly important at a time when the complete genome sequences of other organisms are becoming available. The aim of this review is to familiarize biologists with the type of data resources currently available on the World Wide Web (WWW).
World Wide Web; Saccharomyces Genome Database; Munich Information Center for Protein Sequences; Yeast Protein Database
A scientific database can be a powerful tool for biologists in an era where large-scale genomic analysis, combined with smaller-scale scientific results, provides new insights into the roles of genes and their products in the cell. However, the collection and assimilation of data is, in itself, not enough to make a database useful. The data must be incorporated into the database and presented to the user in an intuitive and biologically significant manner. Most importantly, this presentation must be driven by the user’s point of view; that is, from a biological perspective. The success of a scientific database can therefore be measured by the response of its users – statistically, by usage numbers and, in a less quantifiable way, by its relationship with the community it serves and its ability to serve as a model for similar projects. Since its inception ten years ago, the Saccharomyces Genome Database (SGD) has seen a dramatic increase in its usage, has developed and maintained a positive working relationship with the yeast research community, and has served as a template for at least one other database. The success of SGD, as measured by these criteria, is due in large part to philosophies that have guided its mission and organisation since it was established in 1993. This paper aims to detail these philosophies and how they shape the organisation and presentation of the database.
S. cerevisiae; database; genome-wide analysis; bioinformatics; yeast
Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.