Genomic profiling of drug sensitivities via induced haploinsufficiency

Exploring the mode-of-action of bioactive compounds by chemical-genetic profiling in yeast

Discovering target and off-target effects of specific compounds is critical to drug discovery and development. We generated a compendium of "chemical-genetic interaction" profiles by testing the collection of viable yeast haploid deletion mutants for hypersensitivity to 82 compounds and natural product extracts. To cluster compounds with a similar mode-of-action and to reveal insights into the cellular pathways and proteins affected, we applied both a hierarchical clustering and a factorgram method, which allows a gene or compound to be associated with more than one group. In particular, tamoxifen, a breast cancer therapeutic, was found to disrupt calcium homeostasis and phosphatidylserine (PS) was recognized as a target for papuamide B, a cytotoxic lipopeptide with anti-HIV activity. Further, the profile of crude extracts resembled that of its constituent purified natural product, enabling detailed classification of extract activity prior to purification. This compendium should serve as a valuable key for interpreting cellular effects of novel compounds with similar activities.

The Saccharomyces cerevisiae orthologue of the human protein phosphatase 4 core regulatory subunit R2 confers resistance to the anticancer drug cisplatin

The anticancer agents cisplatin and oxaliplatin are widely used in the treatment of human neoplasias. A genome-wide screen in Saccharomyces cerevisiae previously identified PPH3 and PSY2 among the top 20 genes conferring resistance to these anticancer agents. The mammalian orthologue of Pph3p is the protein serine/threonine phosphatase Ppp4c, which is found in high molecular mass complexes bound to a regulatory subunit R2. We show here that the putative S. cerevisiae orthologue of R2, which is encoded by ORF YBL046w, binds to Pph3p and exhibits the same unusually high asymmetry as mammalian R2. Despite the essential function of Ppp4c-R2 in microtubule-related processes at centrosomes in higher eukaryotes, S. cerevisiae diploid strains with homozygous deletion of YBL046w and two or one functional copies of the TUB2 gene were viable and no more sensitive to microtubule-depolymerizing drugs than the control strain. The protein encoded by YBL046w exhibited a predominantly nuclear localization. These studies suggest that the centrosomal function of Ppp4c-R2 is not required or may be performed by a different phosphatase in yeast. Homozygous diploid deletion strains of S. cerevisiae, pph3Delta, ybl046wDelta and psy2Delta, were all more sensitive to cisplatin than the control strain. The YBL046w gene therefore confers resistance to cisplatin and was termed PSY4 (platinum sensitivity 4). Ppp4c, R2 and the putative orthologue of Psy2p (termed R3) are shown here to form a complex in Drosophila melanogaster and mammalian cells. By comparison with the yeast system, this complex may confer resistance to cisplatin in higher eukaryotes.

Yeast-based functional genomics and proteomics technologies: the first 15 years and beyond

Yeast-based functional genomics and proteomics technologies developed over the past decade have contributed greatly to our understanding of bacterial, yeast, fly, worm, and human gene functions. In this review, we highlight some of these yeast-based functional genomic and proteomic technologies that are advancing the utility of yeast as a model organism in molecular biology and speculate on their future uses. Such technologies include use of the yeast deletion strain collection, large-scale determination of protein localization in vivo, synthetic genetic array analysis, variations of the yeast two-hybrid system, protein microarrays, and tandem affinity purification (TAP)-tagging approaches. The integration of these advances with established technologies is invaluable in the drive toward a comprehensive understanding of protein structure and function in the cellular milieu.

Conserved fungal genes as potential targets for broad-spectrum antifungal drug discovery

The discovery of novel classes of antifungal drugs depends to a certain extent on the identification of new, unexplored targets that are essential for growth of fungal pathogens. Likewise, the broad-spectrum capacity of future antifungals requires the target gene(s) to be conserved among key fungal pathogens. Using a genome comparison (or concordance) tool, we identified 240 conserved genes as candidates for potential antifungal targets in 10 fungal genomes. To facilitate the identification of essential genes in Candida albicans, we developed a repressible C. albicans MET3 (CaMET3) promoter system capable of evaluating gene essentiality on a genome-wide scale. The CaMET3 promoter was found to be highly amenable to controlled gene expression, a prerequisite for use in target-based whole-cell screening. When the expression of the known antifungal target C. albicans ERG1 was reduced via down-regulation of the CaMET3 promoter, the CaERG1 conditional mutant strain became hypersensitive, specifically to its inhibitor, terbinafine. Furthermore, parallel screening against a small compound library using the CaERG1 conditional mutant under normal and repressed conditions uncovered several hypersensitive compound hits. This work therefore demonstrates a streamlined process for proceeding from selection and validation of candidate antifungal targets to screening for specific inhibitors.

Yeast as a drug discovery platform in Huntington's and Parkinson's diseases

The high degree of conservation of cellular and molecular processes between the budding yeast Saccharomyces cerevisiae and higher eukaryotes have made it a valuable system for numerous studies of the basic mechanisms behind devastating illnesses such as cancer, infectious disease, and neurodegenerative disorders. Several studies in yeast have already contributed to our basic understanding of cellular dysfunction in both Huntington's and Parkinson's disease. Functional genomics approaches currently being undertaken in yeast may lead to novel insights into the genes and pathways that modulate neuronal cell dysfunction and death in these diseases. In addition, the budding yeast constitutes a valuable system for identification of new drug targets, both via target-based and non-target-based drug screening. Importantly, yeast can be used as a cellular platform to analyze the cellular effects of candidate compounds, which is critical for the development of effective therapeutics. While the molecular mechanisms that underlie neurodegeneration will ultimately have to be tested in neuronal and animal models, there are several distinct advantages to using simple model organisms to elucidate fundamental aspects of protein aggregation, amyloid toxicity, and cellular dysfunction. Here, we review recent studies that have shown that amyloid formation by disease-causing proteins and many of the resulting cellular deficits can be faithfully recapitulated in yeast. In addition, we discuss new yeast-based techniques for screening candidate therapeutic compounds for Huntington's and Parkinson's diseases.

Microarray-based method for monitoring yeast overexpression strains reveals small-molecule targets in TOR pathway

Identification of the cellular targets of small-molecule hits in phenotypic screens is a central challenge in the development of small molecules as biological tools and potential therapeutics. To facilitate the process of small-molecule target identification, we developed a global, microarray-based method for monitoring the growth of pools of yeast strains, each overexpressing a different protein, in the presence of small molecules. Specifically, the growth of Saccharomyces cerevisiae strains harboring approximately 3,900 different overexpression plasmids was monitored in the presence of rapamycin, which inhibits the target of rapamycin (TOR) proteins. TOR was successfully identified as a candidate rapamycin target, and many additional gene products were implicated in the TOR signaling pathway. We also characterized the mechanism of LY-83583, a small-molecule suppressor of rapamycin-induced growth inhibition. These data enabled functional links to be drawn between groups of genes implicated in the TOR pathway, identified several candidate targets for LY-83583, and suggested a role for mitochondrial respiration in mediating rapamycin sensitivity.

Genomic approaches for identifying DNA damage response pathways in S. cerevisiae

DNA damage response pathways have been studied extensively in the budding yeast Saccharomyces cerevisiae, yet new genes with roles in the DNA damage response are still being identified. In this chapter we describe the use of functional genomic approaches in the identification of DNA damage response genes and pathways. These techniques take advantage of the S. cerevisiae gene deletion mutant collection, either as an ordered array or as a pool, and can be automated for high throughput.

Global synthetic-lethality analysis and yeast functional profiling

The Saccharomyces genome-deletion project created >5900 'molecularly barcoded' yeast knockout mutants (YKO mutants). The YKO mutant collections have facilitated large-scale analyses of a multitude of mutant phenotypes. For example, both synthetic genetic array (SGA) and synthetic-lethality analysis by microarray (SLAM) methods have been used for synthetic-lethality screens. Global analysis of synthetic lethality promises to identify cellular pathways that 'buffer' each other biologically. The combination of global synthetic-lethality analysis, together with global protein-protein interaction analyses, mRNA expression profiling and functional profiling will, in principle, enable construction of a cellular 'wiring diagram' that will help frame a deeper understanding of human biology and disease.

Use of constraint-based modeling for the prediction and validation of antimicrobial targets

The overall process of antimicrobial drug discovery and development seems simple, to cure infectious disease by identifying suitable antibiotic drugs. However, this goal has been difficult to fulfill in recent years. Despite the promise of the high-throughput innovations sparked by the genomics revolution, discovery, and development of new antibiotics has lagged in recent years exacerbating the already serious problem of evolution of antibiotic resistance. Therefore, both new antimicrobials are desperately needed as are improvements to speed up or improve nearly all steps in the process of discovering novel antibiotics and bringing these to clinical use. Another product of the genomic revolution is the modeling of metabolism using computational methodologies. Genomic-scale networks of metabolic reactions based on stoichiometry, thermodynamics and other physico-chemical constraints that emulate microbial metabolism have been developed into valuable research tools in metabolic engineering and other fields. This constraint-based modeling is predictive in identifying critical reactions, metabolites, and genes in metabolism. This is extremely useful in determining and rationalizing cellular metabolic requirements. In turn, these methods can be used to predict potential metabolic targets for antimicrobial research especially if used to increase the confidence in prioritization of metabolic targets. The many different capacities of constraint-based modeling also enable prediction of cellular response to specific inhibitors such as antibiotics and this may, ultimately find a role in drug discovery and development. Herein, we describe the principles of metabolic modeling and how they might initially be applied to antimicrobial research.

Differential chromosome control of ploidy in the yeast Saccharomyces cerevisiae

In Saccharomyces cerevisiae, aneuploidy is well tolerated and stable. We analysed whether the induced loss of a disomic chromosome favours endo-reduplication of the remaining chromosome or the cells prefer to retain the acquired euploidy. Chromosome VIII disomes and trisomes were tagged with GFP (green fluorescent protein), DsRed (red fluorescent protein) and BFP (blue fluorescent protein) integrated at the thr1 locus, using our newly designed STIK (specific targeted integration of kanamycin resistance-associated, non-selectable DNA) plasmid system. A knockout cassette for centromere 8 was constructed with the hygromycin-B marker, which was transformed into the strains. The transformants lost sensitivity to hygromycin, thereby indicating the event of centromere replacement. Quantitative PCR and Southern analysis were performed for chromosome VIII copy number determination by probing the markers located on both the right (ARG4 and THR1) and left (GUT1) arm whereas, for chromosome V, markers such as HIS1, located on right arm, and URA3, on left arm, were used. The loss of an extranumerary chromosome VIII in a disome and trisome leads to stable euploidy. Furthermore, in a wild-type diploid, deletion of a copy of chromosome VIII, leads to monosomy, and restoration of euploidy after 22 generations, by reduplication of chromosome VIII, and consequent loss of heterozygosis (LOH). However, chromosome V knockouts in chromosome VIII trisome, still showed LOH and duplication of chromosome V, with return to the original aneuploid condition. These results suggest that yeast cells could control the integrity of their genetic complement acting at the individual chromosome level.

A small-molecule inhibitor of Mps1 blocks the spindle-checkpoint response to a lack of tension on mitotic chromosomes

The spindle checkpoint prevents chromosome loss by preventing chromosome segregation in cells with improperly attached chromosomes [1, 2 and 3]. The checkpoint senses defects in the attachment of chromosomes to the mitotic spindle [4] and the tension exerted on chromosomes by spindle forces in mitosis [5, 6 and 7]. Because many cancers have defects in chromosome segregation, this checkpoint may be required for survival of tumor cells and may be a target for chemotherapy. We performed a phenotype-based chemical-genetic screen in budding yeast and identified an inhibitor of the spindle checkpoint, called cincreasin. We used a genome-wide collection of yeast gene-deletion strains and traditional genetic and biochemical analysis to show that the target of cincreasin is Mps1, a protein kinase required for checkpoint function [8]. Despite the requirement for Mps1 for sensing both the lack of microtubule attachment and tension at kinetochores, we find concentrations of cincreasin that selectively inhibit the tension-sensitive branch of the spindle checkpoint. At these concentrations, cincreasin causes lethal chromosome missegregation in mutants that display chromosomal instability. Our results demonstrate that Mps1 can be exploited as a target and that inhibiting the tension-sensitive branch of the spindle checkpoint may be a way of selectively killing cancer cells that display chromosomal instability.

The concept of synthetic lethality in the context of anticancer therapy

Two genes are synthetic lethal if mutation of either alone is compatible with viability but mutation of both leads to death. So, targeting a gene that is synthetic lethal to a cancer-relevant mutation should kill only cancer cells and spare normal cells. Synthetic lethality therefore provides a conceptual framework for the development of cancer-specific cytotoxic agents. This paradigm has not been exploited in the past because there were no robust methods for systematically identifying synthetic lethal genes. This is changing as a result of the increased availability of chemical and genetic tools for perturbing gene function in somatic cells.

Genetic and genomic systems to study methylmalonic acidemia

Methylmalonic acidemia (MMAemia) is the biochemical hallmark of a group of genetic metabolic disorders that share a common defect in the ability to convert methylmalonyl-CoA into succinyl-CoA. This disorder is due to either a mutant methylmalonyl-CoA mutase apoenzyme or impaired synthesis of adenosylcobalamin, the cofactor for this enzyme. In this article, we will provide an overview of the pathways disrupted in these disorders, discuss the known metabolic blocks with a particular focus on molecular genetics, and review the use of selected model organisms to study features of methylmalonic acidemia.

A genome-wide overexpression screen in yeast for small-molecule target identification

We describe a multicopy gene suppression screen of drug sensitivity in Saccharomyces cerevisiae that facilitates the identification of cellular targets of small molecules. An array of yeast transformants harboring a multicopy yeast genomic library was screened for resistance to growth inhibitors. Comparison of array growth patterns for several such inhibitors allowed the differentiation of general and molecule-specific genetic suppressors. Specific resistance to phenylaminopyrimidine (1), an inhibitor identified from a kinase-directed library, was associated with the overexpression of Pkc1 and a subset of downstream kinases. Components of two other pathways (pheromone response/filamentous growth and Pho85 kinase) that genetically interact with the PKC1 MAPK signaling cascade were also identified. Consistent with the suppression screen, inhibitor 1 bound to Pkc1 in yeast cell lysate and inhibited its activity in vitro. These results demonstrate the utility of this approach for the rapid deconvolution of small-molecule targets.

From drug to protein: using yeast genetics for high-throughput target discovery

The budding yeast Saccharomyces cerevisiae has long been an effective eukaryotic model system for understanding basic cellular processes. The genetic tractability and ease of manipulation in the laboratory make yeast well suited for large-scale chemical and genetic screens. Several recent studies describing the use of yeast genetics for high-throughput drug target identification are discussed in this review.

Yeast as a model for medical and medicinal research

In the past, studies using the yeast Saccharomyces cerevisiae enabled major breakthroughs in the understanding of basic cellular and molecular processes. Today, the use of yeast is undergoing a "rebirth" in both fundamental and applied research. Indeed, advances in yeast technology have paved the way for a variety of new genome-wide screening approaches. Experimental strategies using yeast aim to unravel disease-related molecular events and to discover novel medicinal compounds. In this article, the impact of yeast as an experimental tool for disease-related studies is summarized and the use of yeast in high-throughput screenings for pharmacological purposes is evaluated. The recently applied and promising approach of so-called humanized yeast systems is also discussed.

A latent variable model for chemogenomic profiling

MOTIVATION

In haploinsufficiency profiling data, pleiotropic genes are often misclassified by clustering algorithms that impose the constraint that a gene or experiment belong to only one cluster. We have developed a general probabilistic model that clusters genes and experiments without requiring that a given gene or drug only appear in one cluster. The model also incorporates the functional annotation of known genes to guide the clustering procedure.

RESULTS

We applied our model to the clustering of 79 chemogenomic experiments in yeast. Known pleiotropic genes PDR5 and MAL11 are more accurately represented by the model than by a clustering procedure that requires genes to belong to a single cluster. Drugs such as miconazole and fenpropimorph that have different targets but similar off-target genes are clustered more accurately by the model-based framework. We show that this model is useful for summarizing the relationship among treatments and genes affected by those treatments in a compendium of microarray profiles.

AVAILABILITY

Supplementary information and computer code at http://genomics.lbl.gov/llda.

Insights into TOR function and rapamycin response: chemical genomic profiling by using a high-density cell array method

With the advent of complete genome sequences, large-scale functional analyses are generating new excitement in biology and medicine. To facilitate genomewide functional analyses, we developed a high-density cell array with quantitative and automated readout of cell fitness. Able to print at > x 10 higher density on a standard microtiter plate area than currently possible, our cell array allows single-plate screening of the complete set of Saccharomyces cerevisiae gene-deletion library and significantly reduces the amount of small molecules and other materials needed for the study. We used this method to map the relation between genes and cell fitness in response to rapamycin, a medically important natural product that targets the eukaryotic kinase Tor. We discuss the implications for pharmacogenomics and the uncharted complexity in genotype-dependent drug response in molecularly targeted therapies. Our analysis leads to several basic findings, including a class of gene deletions that confer better fitness in the presence of rapamycin. This result provides insights into possible therapeutic uses of rapamycin/CCI-779 in the treatment of neurodegenerative diseases (including Alzheimer's, Parkinson's, and Huntington's diseases), and cautions the possible existence of similar rapamycin-enhanceable mutations in cancer. It is well established in yeast that although TOR2 has a unique rapamycin-insensitive function, TOR1 and TOR2 are interchangeable in the rapamycin-sensitive functions. We show that even the rapamycin-sensitive functions are distinct between TOR1 and TOR2 and map the functional difference to a approximately 120-aa region at the N termini of the proteins. Finally, we discuss using cell-based genomic pattern recognition in designing electronic or optical biosensors.

Multicopy suppressors for novel antibacterial compounds reveal targets and drug efflux susceptibility

Gene dosage has frequently been exploited to select for genetic interactions between a particular mutant and clones from a random genomic library at high copy. We report here the first use of multicopy suppression as a forward genetic method to determine cellular targets and potential resistance mechanisms for novel antibacterial compounds identified through high-throughput screening. A screen of 8640 small molecules for growth inhibition of a hyperpermeable strain of Escherichia coli led to the identification of 49 leads for suppressor selection from clones harboring an E. coli genomic library. The majority of suppressors were found to encode the multidrug efflux pump AcrB, indicating that those compounds were substrates for efflux. Two leads, which produced clones containing the gene folA, encoding dihydrofolate reductase (DHFR), proved to target DHFR in vivo and were competitive inhibitors in vitro.

Chemogenomic profiling on a genome-wide scale using reverse-engineered gene networks

A major challenge in drug discovery is to distinguish the molecular targets of a bioactive compound from the hundreds to thousands of additional gene products that respond indirectly to changes in the activity of the targets. Here, we present an integrated computational-experimental approach for computing the likelihood that gene products and associated pathways are targets of a compound. This is achieved by filtering the mRNA expression profile of compound-exposed cells using a reverse-engineered model of the cell's gene regulatory network. We apply the method to a set of 515 whole-genome yeast expression profiles resulting from a variety of treatments (compounds, knockouts and induced expression), and correctly enrich for the known targets and associated pathways in the majority of compounds examined. We demonstrate our approach with PTSB, a growth inhibitory compound with a previously unknown mode of action, by predicting and validating thioredoxin and thioredoxin reductase as its target.

Yeast as a model system for anticancer drug discovery

Saccharomyces cerevisiae has been used extensively as a model for higher eukaryotes in the study of basic cellular processes. The high degree of conservation in terms of sequence similarity and function has made this organism useful in elucidating biological pathways, both yeast and human. Among these are pathways responsible for DNA damage repair and cell cycle control. This review presents an overview of opportunities for using yeast as a model system for anticancer drug discovery. It covers screens directed against specific cancer-related targets as well as contexts created by cancer-related alterations. The methodologies covered include pharmacological and genetic screens, as well as genome-wide approaches to drug target identification.

Chemical biology on PINs and NeeDLes

Systematic studies of the organization of biochemical networks that make up the living cell can be defined by studying the organization and dynamics of protein interaction networks (PINs). Here, we describe recent conceptual and experimental advances that can achieve this aim and how chemical perturbations of interactions can be used to define the organization of biochemical networks. Resulting perturbation profiles and subcellular locations of interactions allow us to 'place' each gene product at its relevant point in a network. We discuss how experimental strategies can be used in conjunction with other genome-wide analyses of physical and genetic protein interactions and gene transcription profiles to determine network dynamic linkage (NDL) in the living cell. It is through such dynamic studies that the intricate networks that make up the chemical machinery of the cell will be revealed.

Tools for target identification and validation

Reliable technologies for addressing target identification and validation are the foundation of successful drug development. Microarrays have been well utilized in genomics/proteomics approaches for gene/protein expression profiling and tissue/cell-scale target validation. Besides being used as an essential step in analyzing high-throughput experiments such as those involving microarrays, bioinformatics can also contribute to the processes of target identification and validation by providing functional information about target candidates and positioning information to biological networks. Antisense technologies (including RNA interference technology, which is recently very 'hot') enable sequence-based gene knockdown at the RNA level. Zinc finger proteins are a DNA transcription-targeting version of knockdown. Chemical genomics and proteomics are emerging tools for generating phenotype changes, thus leading to target and hit identifications. NMR-based screening, as well as activity-based protein profiling, are trying to meet the requirement of high-throughput target identification.

Yeast as a budding technology in target validation

Yeast biology has yielded major insights into fundamental cellular biology and has served as a remarkable platform for technical innovation. We review how these resources can be applied to the validation of mammalian or anti-fungal drug targets. These approaches range from elucidating synergistic interactions between drugs and targets to facile methods for tracking proteins in the cell or characterization of receptor biology. We also discuss web-based resources that integrate the extensive biochemical, cell biological, and genetic literature exploring the basic biology of these model eukaryotic cells.:

Discrimination of modes of action of antifungal substances by use of metabolic footprinting

Diploid cells of Saccharomyces cerevisiae were grown under controlled conditions with a Bioscreen instrument, which permitted the essentially continuous registration of their growth via optical density measurements. Some cultures were exposed to concentrations of a number of antifungal substances with different targets or modes of action (sterol biosynthesis, respiratory chain, amino acid synthesis, and the uncoupler). Culture supernatants were taken and analyzed for their "metabolic footprints" by using direct-injection mass spectrometry. Discriminant function analysis and hierarchical cluster analysis allowed these antifungal compounds to be distinguished and classified according to their modes of action. Genetic programming, a rule-evolving machine learning strategy, allowed respiratory inhibitors to be discriminated from others by using just two masses. Metabolic footprinting thus represents a rapid, convenient, and information-rich method for classifying the modes of action of antifungal substances.

Chemical genomics in yeast

Four recent 'chemical genomic' studies, using genome-scale collections of yeast gene deletions, have presented complementary approaches to identifying gene-drug and pathway-drug interactions.

Many drugs have unknown, controversial or multiple mechanisms of action. Four recent 'chemical genomic' studies, using genome-scale collections of yeast gene deletions that were either arrayed or barcoded, have presented complementary approaches to identifying gene-drug and pathway-drug interactions.

Exploration of essential gene functions via titratable promoter alleles

Nearly 20% of yeast genes are required for viability, hindering genetic analysis with knockouts. We created promoter-shutoff strains for over two-thirds of all essential yeast genes and subjected them to morphological analysis, size profiling, drug sensitivity screening, and microarray expression profiling. We then used this compendium of data to ask which phenotypic features characterized different functional classes and used these to infer potential functions for uncharacterized genes. We identified genes involved in ribosome biogenesis (HAS1, URB1, and URB2), protein secretion (SEC39), mitochondrial import (MIM1), and tRNA charging (GSN1). In addition, apparent negative feedback transcriptional regulation of both ribosome biogenesis and the proteasome was observed. We furthermore show that these strains are compatible with automated genetic analysis. This study underscores the importance of analyzing mutant phenotypes and provides a resource to complement the yeast knockout collection.

Characterization of synthetic DNA bar codes in Saccharomyces cerevisiae gene-deletion strains

Incorporation of strain-specific synthetic DNA tags into yeast Saccharomyces cerevisiae gene-deletion strains has enabled identification of gene functions by massively parallel growth rate analysis. However, it is important to confirm the sequences of these tags, because mutations introduced during construction could lead to significant errors in hybridization performance. To validate this experimental system, we sequenced 11,812 synthetic 20-mer molecular bar codes and adjacent sequences (>1.8 megabases synthetic DNA) by pyrosequencing and Sanger methods. At least 31% of the genome-integrated 20-mer tags contain differences from those originally synthesized. However, these mutations result in anomalous hybridization in only a small subset of strains, and the sequence information enables redesign of hybridization probes for arrays. The robust performance of the yeast gene-deletion dual oligonucleotide bar-code design in array hybridization validates the use of molecular bar codes in living cells for tracking their growth phenotype.

The uses of genome-wide yeast mutant collections

We assess five years of usage of the major genome-wide collections of mutants from Saccharomyces cerevisiae: single deletion mutants, double mutants conferring 'synthetic' lethality and the 'TRIPLES' collection of mutants obtained by random transposon insertion. Over 100 experimental conditions have been tested and more than 5,000 novel phenotypic traits have been assigned to yeast genes using these collections.

Genetic and Genomic Approaches to Identify and Study the Targets of Bioactive Small Molecules

Natural and synthetic bioactive small molecules form the backbone of modern therapeutics. These drugs primarily exert their effect by targeting cellular host or foreign proteins that are critical for the progression of disease. Therefore, a crucial step in the process of recognizing valuable new drug leads is identification of their protein targets; this is often a time consuming and difficult task. This report is intended to provide a comprehensive review of recent developments in genetic and genomic approaches to overcome the hurdle of discovering the protein targets of bioactive small molecules.

An ER packaging chaperone determines the amino acid uptake capacity and virulence of Candida albicans

The Candida albicans CSH3 gene encodes a functional and structural homologue of Shr3p, a yeast protein that is specifically required for proper uptake and sensing of extracellular amino acids in Saccharomyces cerevisiae. A Candida csh3delta/csh3delta null mutant has a reduced capacity to take up amino acids, and is unable to switch morphologies on solid and in liquid media in response to inducing amino acids. CSH3/csh3delta heterozygous strains display normal amino acid induced morphological switching. However, although heterozygous cells apparently sense and properly react to amino acid induced signals they cannot take up amino acids at wild-type rates. Strikingly, both CSH3/csh3delta heterozygous and csh3delta/csh3delta homozygous strains are unable to efficiently mount virulent infections in a mouse model. The haploinsufficiency phenotypes indicate that both CSH3 alleles contribute to maintain high-capacity amino acid uptake in wild-type strains. These results strongly suggest that C. albicans cells use amino acids, presumably as nitrogen sources, during growth in mammalian hosts.

Yeast genome-wide drug-induced haploinsufficiency screen to determine drug mode of action

Methods to systematically test drugs against all possible proteins in a cell are needed to identify the targets underlying their therapeutic action and unwanted effects. Here, we show that a genome-wide drug-induced haploinsufficiency screen by using yeast can reveal drug mode of action in yeast and can be used to predict drug mode of action in human cells. We demonstrate that dihydromotuporamine C, a compound in preclinical development that inhibits angiogenesis and metastasis by an unknown mechanism, targets sphingolipid metabolism. The systematic, unbiased and genome-wide nature of this technique makes it attractive as a general approach to identify cellular pathways affected by drugs.

Old drugs, new tricks: using genetically sensitized yeast to reveal drug targets

A study in this issue of Cell illustrates the power of applying genomic approaches with model systems to characterize the biological activity of small molecules and to identify their cellular targets, which can clarify the mode of action of human therapeutics.

Discovering modes of action for therapeutic compounds using a genome-wide screen of yeast heterozygotes

Modern medicine faces the challenge of developing safer and more effective therapies to treat human diseases. Many drugs currently in use were discovered without knowledge of their underlying molecular mechanisms. Understanding their biological targets and modes of action will be essential to design improved second-generation compounds. Here, we describe the use of a genome-wide pool of tagged heterozygotes to assess the cellular effects of 78 compounds in Saccharomyces cerevisiae. Specifically, lanosterol synthase in the sterol biosynthetic pathway was identified as a target of the antianginal drug molsidomine, which may explain its cholesterol-lowering effects. Further, the rRNA processing exosome was identified as a potential target of the cell growth inhibitor 5-fluorouracil. This genome-wide screen validated previously characterized targets or helped identify potentially new modes of action for over half of the compounds tested, providing proof of this principle for analyzing the modes of action of clinically relevant compounds.

Chemical Genomics and Medicinal Systems Biology: Chemical Control of Genomic Networks in Human Systems Biology for Innovative Medicine

With advances in determining the entire DNA sequence of the human genome, it is now critical to systematically identify the function of a number of genes in the human genome. These biological challenges, especially those in human diseases, should be addressed in human cells in which conventional (e.g. genetic) approaches have been extremely difficult to implement. To overcome this, several approaches have been initiated. This review will focus on the development of a novel "chemical genetic/genomic approach" that uses small molecules to "probe and identify" the function of genes in specific biological processes or pathways in human cells. Due to the close relationship of small molecules with drugs, these systematic and integrative studies will lead to the "medicinal systems biology approach" which is critical to "formulate and modulate" complex biological (disease) networks by small molecules (drugs) in human bio-systems.

Chemogenomic profiling: identifying the functional interactions of small molecules in yeast

We demonstrate the efficacy of a genome-wide protocol in yeast that allows the identification of those gene products that functionally interact with small molecules and result in the inhibition of cellular proliferation. Here we present results from screening 10 diverse compounds in 80 genome-wide experiments against the complete collection of heterozygous yeast deletion strains. These compounds include anticancer and antifungal agents, statins, alverine citrate, and dyclonine. In several cases, we identified previously known interactions; furthermore, in each case, our analysis revealed novel cellular interactions, even when the relationship between a compound and its cellular target had been well established. In addition, we identified a chemical core structure shared among three therapeutically distinct compounds that inhibit the ERG24 heterozygous deletion strain, demonstrating that cells may respond similarly to compounds of related structure. The ability to identify on-and-off target effects in vivo is fundamental to understanding the cellular response to small-molecule perturbants.

Chemical Genomics

Chemical genomics is concerned with the effects of both genetic variation and chemical perturbation on the cellular effects of small molecules. Chemical genomics relies on selecting biological networks for study, such as those represented by different cell types or disease models, in order to build the desired specificity into the experimental design. The most relevant network property for such experiments is the global connectivity of all cellular proteins comprising the functional ensemble, as illustrated by case studies of the evolution of cyclooxygenase inhibitors and heat-shock protein modulators. Recent examples of chemical genomic profiling, particularly of different cell types, highlight the power of carefully planned experimental approaches in chemical genomics. These new approaches demonstrate the use of the genome to find new targets or new modes of biological interaction.

High-resolution yeast phenomics resolves different physiological features in the saline response

We present a methodology for gene functional prediction based on extraction of physiologically relevant growth variables from all viable haploid yeast knockout mutants. This quantitative phenomics approach, here applied to saline cultivation, identified marginal but functionally important phenotypes and allowed the precise determination of time to adapt to an environmental challenge, rate of growth, and efficiency of growth. We identified approximately 500 salt-sensitive gene deletions, the majority of which were previously uncharacterized and displayed salt sensitivity for only one of the three physiological features. We also report a high correlation to protein-protein interaction data; in particular, several salt-sensitive subcellular networks indicating functional modules were revealed. In contrast, no correlation was found between gene dispensability and gene expression. It is proposed that high-resolution phenomics will be instrumental in systemwide descriptions of intragenomic functional networks.

Integration of chemical-genetic and genetic interaction data links bioactive compounds to cellular target pathways

Bioactive compounds can be valuable research tools and drug leads, but it is often difficult to identify their mechanism of action or cellular target. Here we investigate the potential for integration of chemical-genetic and genetic interaction data to reveal information about the pathways and targets of inhibitory compounds. Taking advantage of the existing complete set of yeast haploid deletion mutants, we generated drug-hypersensitivity (chemical-genetic) profiles for 12 compounds. In addition to a set of compound-specific interactions, the chemical-genetic profiles identified a large group of genes required for multidrug resistance. In particular, yeast mutants lacking a functional vacuolar H(+)-ATPase show multidrug sensitivity, a phenomenon that may be conserved in mammalian cells. By filtering chemical-genetic profiles for the multidrug-resistant genes and then clustering the compound-specific profiles with a compendium of large-scale genetic interaction profiles, we were able to identify target pathways or proteins. This method thus provides a powerful means for inferring mechanism of action.

A chemical genomics approach to understanding drug action

The complete collection of yeast deletion strains represents a unique, living biological computer for understanding gene function. The molecular 'barcodes' present in each of the deletion strains allow a quantitative ranking of the importance of any gene under any experimental condition of choice. In this article, some of the recent results generated from experiments that exploit the yeast deletion collection to understand mechanisms of drug action are discussed.