Genomic profiling of drug sensitivities via induced haploinsufficiency

Yeast chemical genomics and drug discovery: an update

The Saccharomyces cerevisiae sequencing project (the first eukaryotic genome decoded) was completed in 1995 and, subsequently, the first version of the yeast knockout collection was made available in 2002. Since then, many diverse studies have applied these resources to understand drug mechanism of action and to identify novel drug targets and target pathways. In this update of an earlier review, we present a snapshot of the current state of chemical genomic approaches in yeast, propose a set of integrated chemical genomic assays to move the field forward and consider its near-term future.

Off-target effects of psychoactive drugs revealed by genome-wide assays in yeast

To better understand off-target effects of widely prescribed psychoactive drugs, we performed a comprehensive series of chemogenomic screens using the budding yeast Saccharomyces cerevisiae as a model system. Because the known human targets of these drugs do not exist in yeast, we could employ the yeast gene deletion collections and parallel fitness profiling to explore potential off-target effects in a genome-wide manner. Among 214 tested, documented psychoactive drugs, we identified 81 compounds that inhibited wild-type yeast growth and were thus selected for genome-wide fitness profiling. Many of these drugs had a propensity to affect multiple cellular functions. The sensitivity profiles of half of the analyzed drugs were enriched for core cellular processes such as secretion, protein folding, RNA processing, and chromatin structure. Interestingly, fluoxetine (Prozac) interfered with establishment of cell polarity, cyproheptadine (Periactin) targeted essential genes with chromatin-remodeling roles, while paroxetine (Paxil) interfered with essential RNA metabolism genes, suggesting potential secondary drug targets. We also found that the more recently developed atypical antipsychotic clozapine (Clozaril) had no fewer off-target effects in yeast than the typical antipsychotics haloperidol (Haldol) and pimozide (Orap). Our results suggest that model organism pharmacogenetic studies provide a rational foundation for understanding the off-target effects of clinically important psychoactive agents and suggest a rational means both for devising compound derivatives with fewer side effects and for tailoring drug treatment to individual patient genotypes.

Genetic evidence that cellulose synthase activity influences microtubule cortical array organization

To identify factors that influence cytoskeletal organization we screened for Arabidopsis (Arabidopsis thaliana) mutants that show hypersensitivity to the microtubule destabilizing drug oryzalin. We cloned the genes corresponding to two of the 131 mutant lines obtained. The genes encoded mutant alleles of PROCUSTE1 and KORRIGAN, which both encode proteins that have previously been implicated in cellulose synthesis. Analysis of microtubules in the mutants revealed that both mutants have altered orientation of root cortical microtubules. Similarly, isoxaben, an inhibitor of cellulose synthesis, also altered the orientation of cortical microtubules while exogenous cellulose degradation did not. Thus, our results substantiate that proteins involved in cell wall biosynthesis influence cytoskeletal organization and indicate that this influence on cortical microtubule stability and orientation is correlated with cellulose synthesis rather than the integrity of the cell wall.

A comprehensive strategy enabling high-resolution functional analysis of the yeast genome

Functional genomic studies in Saccharomyces cerevisiae have contributed enormously to our understanding of cellular processes. Their full potential, however, has been hampered by the limited availability of reagents to systematically study essential genes and the inability to quantify the small effects of most gene deletions on growth. Here we describe the construction of a library of hypomorphic alleles of essential genes and a high-throughput growth competition assay to measure fitness with unprecedented sensitivity. These tools dramatically increase the breadth and precision with which quantitative genetic analysis can be performed in yeast. We illustrate the value of these approaches by using genetic interactions to reveal new relationships between chromatin-modifying factors and to create a functional map of the proteasome. Finally, by measuring the fitness of strains in the yeast deletion library, we addressed an enigma regarding the apparent prevalence of gene dispensability and found that most genes do contribute to growth.

Enhancing drug accumulation in Saccharomyces cerevisiae by repression of pleiotropic drug resistance genes with chimeric transcription repressors

Yeast is a powerful model system for studying the action of small-molecule therapeutics. An important limitation has been low efficacy of many small molecules in yeast due to limited intracellular accumulation. We used the DNA binding domain of the pleiotropic drug resistance regulator pleiotropic drug resistance 1 (Pdr1) fused in-frame to transcription repressors to repress Pdr1-regulated genes. Expression of these chimeric regulators conferred dominant enhancement of sensitivity to a different class of compounds and led to greatly diminished levels of Pdr1p-regulated transcripts, including the yeast p-glycoprotein homolog Pdr5. Enhanced sensitivity was seen for a wide range of small molecules. Biochemical measurements demonstrated enhanced accumulation of rhodamine in yeast cells expressing the chimeric repressors. These repressors of Pdr1p-regulated transcripts can be introduced into large collections of strains such as the Saccharomyces cerevisiae deletion set and enhance the utility of yeast for studying drug action and for mechanism-based drug discovery.

An integrated platform of genomic assays reveals small-molecule bioactivities

Bioactive compounds are widely used to modulate protein function and can serve as important leads for drug development. Identifying the in vivo targets of these compounds remains a challenge. Using yeast, we integrated three genome-wide gene-dosage assays to measure the effect of small molecules in vivo. A single TAG microarray was used to resolve the fitness of strains derived from pools of (i) homozygous deletion mutants, (ii) heterozygous deletion mutants and (iii) genomic library transformants. We demonstrated, with eight diverse reference compounds, that integration of these three chemogenomic profiles improves the sensitivity and specificity of small-molecule target identification. We further dissected the mechanism of action of two protein phosphatase inhibitors and in the process developed a framework for the rational design of multidrug combinations to sensitize cells with specific genotypes more effectively. Finally, we applied this platform to 188 novel synthetic chemical compounds and identified both potential targets and structure-activity relationships.

Analysis of the yeast kinome reveals a network of regulated protein localization during filamentous growth

The subcellular distribution of kinases and other signaling proteins is regulated in response to cellular cues; however, the extent of this regulation has not been investigated for any gene set in any organism. Here, we present a systematic analysis of protein kinases in the budding yeast, screening for differential localization during filamentous growth. Filamentous growth is an important stress response involving mitogen-activated protein kinase and cAMP-dependent protein kinase signaling modules, wherein yeast cells form interconnected and elongated chains. Because standard strains of yeast are nonfilamentous, we constructed a unique set of 125 kinase-yellow fluorescent protein chimeras in the filamentous Sigma1278b strain for this study. In total, we identified six cytoplasmic kinases (Bcy1p, Fus3p, Ksp1p, Kss1p, Sks1p, and Tpk2p) that localize predominantly to the nucleus during filamentous growth. These kinases form part of an interdependent, localization-based regulatory network: deletion of each individual kinase, or loss of kinase activity, disrupts the nuclear translocation of at least two other kinases. In particular, this study highlights a previously unknown function for the kinase Ksp1p, indicating the essentiality of its nuclear translocation during yeast filamentous growth. Thus, the localization of Ksp1p and the other kinases identified here is tightly controlled during filamentous growth, representing an overlooked regulatory component of this stress response.

GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function

BACKGROUND

Most successful computational approaches for protein function prediction integrate multiple genomics and proteomics data sources to make inferences about the function of unknown proteins. The most accurate of these algorithms have long running times, making them unsuitable for real-time protein function prediction in large genomes. As a result, the predictions of these algorithms are stored in static databases that can easily become outdated. We propose a new algorithm, GeneMANIA, that is as accurate as the leading methods, while capable of predicting protein function in real-time.

RESULTS

We use a fast heuristic algorithm, derived from ridge regression, to integrate multiple functional association networks and predict gene function from a single process-specific network using label propagation. Our algorithm is efficient enough to be deployed on a modern webserver and is as accurate as, or more so than, the leading methods on the MouseFunc I benchmark and a new yeast function prediction benchmark; it is robust to redundant and irrelevant data and requires, on average, less than ten seconds of computation time on tasks from these benchmarks.

CONCLUSION

GeneMANIA is fast enough to predict gene function on-the-fly while achieving state-of-the-art accuracy. A prototype version of a GeneMANIA-based webserver is available at http://morrislab.med.utoronto.ca/prototype.

In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen

The growing resistance to current first-line antimalarial drugs represents a major health challenge. To facilitate the discovery of new antimalarials, we have implemented an efficient and robust high-throughput cell-based screen (1,536-well format) based on proliferation of Plasmodium falciparum (Pf) in erythrocytes. From a screen of approximately 1.7 million compounds, we identified a diverse collection of approximately 6,000 small molecules comprised of >530 distinct scaffolds, all of which show potent antimalarial activity (<1.25 microM). Most known antimalarials were identified in this screen, thus validating our approach. In addition, we identified many novel chemical scaffolds, which likely act through both known and novel pathways. We further show that in some cases the mechanism of action of these antimalarials can be determined by in silico compound activity profiling. This method uses large datasets from unrelated cellular and biochemical screens and the guilt-by-association principle to predict which cellular pathway and/or protein target is being inhibited by select compounds. In addition, the screening method has the potential to provide the malaria community with many new starting points for the development of biological probes and drugs with novel antiparasitic activities.

Statistical analysis of fitness data determined by TAG hybridization on microarrays

TAG, or bar-code, microarrays allow measurement of the oligonucleotide sequences (TAGs) that mark each strain of deletion mutants in the Saccharomyces cerevisiae yeast knockout (YKO) collection. Comparison of genomic DNA from pooled YKO samples allows estimation of relative abundance of TAGs marking each deletion strain. Features of TAG hybridizations create unique challenges for analysis. Analysis is complicated by the presence of two TAGs in most YKO strains and the hybridization behavior of TAGs that may differ in sequence from array probes. The oligonucleotide size of labeled TAGs also results in difficulty with contaminating sequences that cause reduced specificity. We present methods for analysis that approach these unique features of TAG hybridizations.

Chemical biology--identification of small molecule modulators of cellular activity by natural product inspired synthesis

The aim of this tutorial review is to introduce the reader to the concept, synthesis and application of natural product-inspired compound collections as an important field in chemical biology. This review will discuss how potentially interesting scaffolds can be identified (structural classification of natural products), synthesized in an appropriate manner (including stereoselective transformations for solid phase-bound compounds) and tested in biological assays (cell-based screening as well as biochemical in vitro assays). These approaches will provide the opportunity to identify new and interesting compounds as well as new targets for chemical biology and medicinal chemistry research.

Discovery, in vivo activity, and mechanism of action of a small-molecule p53 activator

We have carried out a cell-based screen aimed at discovering small molecules that activate p53 and have the potential to decrease tumor growth. Here, we describe one of our hit compounds, tenovin-1, along with a more water-soluble analog, tenovin-6. Via a yeast genetic screen, biochemical assays, and target validation studies in mammalian cells, we show that tenovins act through inhibition of the protein-deacetylating activities of SirT1 and SirT2, two important members of the sirtuin family. Tenovins are active on mammalian cells at one-digit micromolar concentrations and decrease tumor growth in vivo as single agents. This underscores the utility of these compounds as biological tools for the study of sirtuin function as well as their potential therapeutic interest.

Bayesian inference of the sites of perturbations in metabolic pathways via Markov chain Monte Carlo

MOTIVATION

Genetic modifications or pharmaceutical interventions can influence multiple sites in metabolic pathways, and often these are 'distant' from the primary effect. In this regard, the ability to identify target and off-target effects of a specific compound or gene therapy is both a major challenge and critical in drug discovery.

RESULTS

We applied Markov Chain Monte Carlo (MCMC) for parameter estimation and perturbation identification in the kinetic modeling of metabolic pathways. Variability in the steady-state measurements in cells taken from a population can be caused by differences in initial conditions within the population, by variation of parameters among individuals and by possible measurement noise. MCMC-based parameter estimation is proposed as a method to help in inferring parameter distributions, taking into account uncertainties in the initial conditions and in the measurement data. The inferred parameter distributions are then used to predict changes in the network via a simple classification method. The proposed technique is applied to analyze changes in the pathways of pyruvate metabolism of mutants of Lactococcus lactis, based on previously published experimental data.

AVAILABILITY

MATLAB code used in the simulations is available from ftp://anonymous@dbkweb.mib.man.ac.uk/pub/Bioinformatics_BJ.zip

Chemogenomics and biotechnology

A robust knowledge of the interactions between small molecules and specific proteins aids the development of new biotechnological tools and the identification of new drug targets, and can lead to specific biological insights. Such knowledge can be obtained through chemogenomic screens. In these screens, each small molecule from a chemical library is applied to each cell type from a library of cells, and the resulting phenotypes are recorded. Chemogenomic screens have recently become very common and will continue to generate large amounts of data. The interpretation of this data will occupy biologists and chemists alike for some time to come. This review discusses methods for the acquisition and interpretation of chemogenomic data, in addition to possible applications of chemogenomics in biotechnology.

Diverse cellular functions of the Hsp90 molecular chaperone uncovered using systems approaches

A comprehensive understanding of the cellular functions of the Hsp90 molecular chaperone has remained elusive. Although Hsp90 is essential, highly abundant under normal conditions, and further induced by environmental stress, only a limited number of Hsp90 "clients" have been identified. To define Hsp90 function, a panel of genome-wide chemical-genetic screens in Saccharomyces cerevisiae were combined with bioinformatic analyses. This approach identified several unanticipated functions of Hsp90 under normal conditions and in response to stress. Under normal growth conditions, Hsp90 plays a major role in various aspects of the secretory pathway and cellular transport; during environmental stress, Hsp90 is required for the cell cycle, meiosis, and cytokinesis. Importantly, biochemical and cell biological analyses validated several of these Hsp90-dependent functions, highlighting the potential of our integrated global approach to uncover chaperone functions in the cell.

Selective pharmacological targeting of a DEAD box RNA helicase

RNA helicases represent a large family of proteins implicated in many biological processes including ribosome biogenesis, splicing, translation and mRNA degradation. However, these proteins have little substrate specificity, making inhibition of selected helicases a challenging problem. The prototypical DEAD box RNA helicase, eIF4A, works in conjunction with other translation factors to prepare mRNA templates for ribosome recruitment during translation initiation. Herein, we provide insight into the selectivity of a small molecule inhibitor of eIF4A, hippuristanol. This coral-derived natural product binds to amino acids adjacent to, and overlapping with, two conserved motifs present in the carboxy-terminal domain of eIF4A. Mutagenesis of amino acids within this region allowed us to alter the hippuristanol-sensitivity of eIF4A and undertake structure/function studies. Our results provide an understanding into how selective targeting of RNA helicases for pharmacological intervention can be achieved.

Mechanism-of-action determination of GMP synthase inhibitors and target validation in Candida albicans and Aspergillus fumigatus

Mechanism-of-action (MOA) studies of bioactive compounds are fundamental to drug discovery. However, in vitro studies alone may not recapitulate a compound's MOA in whole cells. Here, we apply a chemogenomics approach in Candida albicans to evaluate compounds affecting purine metabolism. They include the IMP dehydrogenase inhibitors mycophenolic acid and mizoribine and the previously reported GMP synthase inhibitors acivicin and 6-diazo-5-oxo-L-norleucine (DON). We report important aspects of their whole-cell activity, including their primary target, off-target activity, and drug metabolism. Further, we describe ECC1385, an inhibitor of GMP synthase, and provide biochemical and genetic evidence supporting its MOA to be distinct from acivicin or DON. Importantly, GMP synthase activity is conditionally essential in C. albicans and Aspergillus fumigatus and is required for virulence of both pathogens, thus constituting an unexpected antifungal target.

Chemical-genetic approaches for exploring the mode of action of natural products

Determining the mode of action of bioactive compounds, including natural products, is a central problem in chemical biology. Because many genes are conserved from the yeast Saccharomyces cerevisiae to humans and a number of powerful genomics tools and methodologies have been developed for this model system, yeast is making a major contribution to the field of chemical genetics. The set of barcoded yeast deletion mutants, including the set of approximately 5000 viable haploid and homozygous diploid deletion mutants and the complete set of approximately 6000 heterozygous deletion mutants, containing the set of approximately 1000 essential genes, are proving highly informative for identifying chemical-genetic interactions and deciphering compound mode of action. Gene deletions that render cells hypersensitive to a specific drug identify pathways that buffer the cell against the toxic effects of the drug and thereby provide clues about both gene and compound function. Moreover, compounds that show similar chemical-genetic profiles often perturb similar target pathways. Gene dosage can be exploited to discover connections between compounds and their targets. For example, haploinsufficiency profiling of an antifungal compound, in which the set of approximately 6000 heterozygous diploid deletion mutants are scored for hypersensitivity to a compound, may identify the target directly. Creating deletion mutant collections in other fungal species, including the major human fungal pathogen Candida albicans, will expand our chemical genomics tool set, allowing us to screen for antifungal lead drugs directly. The yeast deletion mutant collection is also being exploited to map large-scale genetic interaction data obtained from genome-wide synthetic lethal screens and the integration of this data with chemical genetic data should provide a powerful system for linking compounds to their target pathway. Extensive application of chemical genetics in yeast has the potential to develop a small molecule inhibitor for the majority of all approximately 6000 yeast genes.

Genetic variation in the cysteine biosynthesis pathway causes sensitivity to pharmacological compounds

Complex traits are the product of multiple genes with effects that depend on both the genetic and environmental background. Although this complexity makes a comprehensive genetic analysis difficult, identification of even a single gene provides insight into the biochemical and/or signaling pathway underlying a trait. However, it is unknown whether multiple pathways, and consequently multiple genes, must be identified to adequately understand a trait's molecular basis. Using crosses between three natural isolates of Saccharomyces cerevisiae, we mapped sensitivity to a number of pharmacologically active compounds to a single nonsynonymous polymorphism in cystathione-beta-synthase (CYS4), which is required for the first committed step in the cysteine biosynthesis pathway. Drug sensitivity is mediated by a deficiency in cysteine and consequently glutathione production, because drug sensitivity is abrogated by cysteine or glutathione supplementation. Within a diverse panel of 60 natural yeast isolates, the drug-sensitive CYS4 allele is rare, and glutathione supplementation failed to alleviate drug-dependent growth defects in two other drug-sensitive strains. These results implicate the cysteine/glutathione biosynthesis pathway as a significant, but not the sole contributor to pharmacological variation in yeast.

Evidence for distinct DNA- and RNA-based mechanisms of 5-fluorouracil cytotoxicity in Saccharomyces cerevisiae

5-Fluorouracil (5FU) is an effective chemotherapeutic drug developed as an inhibitor of thymidylate synthetase (TS). Inhibition of TS leads to 'thymine-less death', a condition resulting from depletion of dTTP pools and misincorporation of dUTP into newly synthesized or repaired DNA. 5FU is also incorporated into RNA and a growing body of evidence suggests that RNA-based effects play a significant role in its cytotoxicity. Indeed, recent experiments in yeast showed that defects in the nuclear RNA exosome subunit Rrp6p cause hypersensitivity to 5FU. The present study asked whether the 5FU hypersensitivity of an rrp6-Delta yeast strain reflects the DNA- or RNA-based effects of 5FU. Genetic analyses suggest that while a DNA repair mutation, apn1-Delta, causes sensitivity to 5FU-induced DNA damage, an rrp6-Delta mutation causes hypersensitivity, due to the RNA-based effects of 5FU. Analysis of a strain with normal DNA and RNA metabolism grown in the presence of 5FU shows that UMP suppresses the 5FU-induced defect more than dTMP, suggesting that the RNA-based toxicity of 5FU predominates in these cells. These findings underscore the importance of understanding the RNA-based mechanism of 5FU cytotoxicity and highlight the use of yeast as a model system for elucidating its details.

Proteomic analysis reveals metabolic changes during yeast to hypha transition in Yarrowia lipolytica

Fungal dimorphism is important for survival in different environments and has been related to virulence. The ascomycete Yarrowia lipolytica can grow as yeast, pseudomycelial or mycelial forms. We have used a Y. lipolytica parental strain and a Deltahoy1 mutant, which is unable to form hypha, to set up a model for dimorphism and to characterize in more depth the yeast to hypha transition by proteomic techniques. A two-dimensional gel electrophoresis (2-DE) based differential expression analysis of Y. lipolytica yeast and hyphal cells was performed, and 45 differentially expressed proteins were detected; nine with decreased expression in hyphal cells were identified. They corresponded to the S. cerevisiae homologues of Imd4p, Pdx3p, Cdc19, Sse1p, Sol3p, Sod2p, Xpt1p, Mdh1p and to the unknown protein YALIOB00924g. Remarkably, most of these proteins are involved in metabolic pathways, with four showing oxidoreductase activity. Furthermore, taking into account that this is the first report of 2-DE analysis of Y. lipolytica protein extracts, 35 more proteins from the 2D map of soluble yeast proteins, which were involved in metabolism, cell rescue, energy and protein synthesis, were identified.

Genomics, systems biology and drug development for infectious diseases

Although a variety of drugs are available for many infectious diseases that predominantly affect the developing world reasons remain for continuing to search for new chemotherapeutics. First, the development of microbial resistance has made some of the most effective and inexpensive drug regimes unreliable and dangerous to use on severely ill patients. Second, many existing antimicrobial drugs show toxicity or are too expensive for countries where the per capita income is in the order of hundreds of dollars per year. In recognition of this, new publicly and privately financed drug discovery efforts have been established to identify and develop new therapies for diseases such as tuberculosis, malaria and AIDS. This in turn, has intensified the need for tools to facilitate drug identification for those microbes whose molecular biology is poorly understood, or which are difficult to grow in the laboratory. While much has been written about how functional genomics can be used to find novel protein targets for chemotherapeutics this review will concentrate on how genome-wide, systems biology approaches may be used following whole organism, cell-based screening to understand the mechanism of drug action or to identify biological targets of small molecules. Here we focus on protozoan parasites, however, many of the approaches can be applied to pathogenic bacteria or parasitic helminths, insects or disease-causing fungi.

Saccharomyces cerevisiae: a versatile eukaryotic system in virology

The yeast Saccharomyces cerevisiae is a well-established model system for understanding fundamental cellular processes relevant to higher eukaryotic organisms. Less known is its value for virus research, an area in which Saccharomyces cerevisiae has proven to be very fruitful as well. The present review will discuss the main achievements of yeast-based studies in basic and applied virus research. These include the analysis of the function of individual proteins from important pathogenic viruses, the elucidation of key processes in viral replication through the development of systems that allow the replication of higher eukayotic viruses in yeast, and the use of yeast in antiviral drug development and vaccine production.

A microarray-based protocol for monitoring the growth of yeast overexpression strains

Gene overexpression can be used to investigate the biological pathways that are important in the response to a small molecule or other perturbation. To facilitate the use of gene overexpression in the study of small-molecule mechanisms, we developed a microarray-based protocol for monitoring the growth of a pool of yeast strains, each overexpressing a different protein. In this protocol, yeast harboring a set of approximately 3,900 galactose-inducible overexpression plasmids are grown in the absence or presence of a small molecule for multiple generations. The plasmids are then extracted from the two populations, processed and labeled in such a manner that their relative concentrations can be determined by competitive hybridization to a microarray. Although this protocol was developed for monitoring a specific set of overexpression plasmids, it could presumably be adapted to monitor yeast that have been transformed with any set of plasmids for which the gene inserts have been spotted, or otherwise arrayed, in a microarray format. This protocol can be completed in approximately 15 hours of hands-on time over the course of several days.

Genome-wide fitness test and mechanism-of-action studies of inhibitory compounds in Candida albicans

Candida albicans is a prevalent fungal pathogen amongst the immunocompromised population, causing both superficial and life-threatening infections. Since C. albicans is diploid, classical transmission genetics can not be performed to study specific aspects of its biology and pathogenesis. Here, we exploit the diploid status of C. albicans by constructing a library of 2,868 heterozygous deletion mutants and screening this collection using 35 known or novel compounds to survey chemically induced haploinsufficiency in the pathogen. In this reverse genetic assay termed the fitness test, genes related to the mechanism of action of the probe compounds are clearly identified, supporting their functional roles and genetic interactions. In this report, chemical-genetic relationships are provided for multiple FDA-approved antifungal drugs (fluconazole, voriconazole, caspofungin, 5-fluorocytosine, and amphotericin B) as well as additional compounds targeting ergosterol, fatty acid and sphingolipid biosynthesis, microtubules, actin, secretion, rRNA processing, translation, glycosylation, and protein folding mechanisms. We also demonstrate how chemically induced haploinsufficiency profiles can be used to identify the mechanism of action of novel antifungal agents, thereby illustrating the potential utility of this approach to antifungal drug discovery.

Universal strategies in research and drug discovery based on protein-fragment complementation assays

Changes in the interactions among proteins that participate in a biochemical pathway can reflect the immediate regulatory responses to intrinsic or extrinsic perturbations of the pathway. Thus, methods that allow for the direct detection of the dynamics of protein-protein interactions can be used to probe the effects of any perturbation on any pathway of interest. Here we describe experimental strategies - based on protein-fragment complementation assays (PCAs) - that can achieve this. PCA-based strategies can be used with or instead of traditional target-based drug discovery strategies to identify novel pathway-component proteins of therapeutic interest, to increase the quantity and quality of information about the actions of potential drugs, and to gain insight into the intricate networks that make up the molecular machinery of living cells.

Essential gene identification and drug target prioritization in Aspergillus fumigatus

Aspergillus fumigatus is the most prevalent airborne filamentous fungal pathogen in humans, causing severe and often fatal invasive infections in immunocompromised patients. Currently available antifungal drugs to treat invasive aspergillosis have limited modes of action, and few are safe and effective. To identify and prioritize antifungal drug targets, we have developed a conditional promoter replacement (CPR) strategy using the nitrogen-regulated A. fumigatus NiiA promoter (pNiiA). The gene essentiality for 35 A. fumigatus genes was directly demonstrated by this pNiiA-CPR strategy from a set of 54 genes representing broad biological functions whose orthologs are confirmed to be essential for growth in Candida albicans and Saccharomyces cerevisiae. Extending this approach, we show that the ERG11 gene family (ERG11A and ERG11B) is essential in A. fumigatus despite neither member being essential individually. In addition, we demonstrate the pNiiA-CPR strategy is suitable for in vivo phenotypic analyses, as a number of conditional mutants, including an ERG11 double mutant (erg11BΔ, pNiiA-ERG11A), failed to establish a terminal infection in an immunocompromised mouse model of systemic aspergillosis. Collectively, the pNiiA-CPR strategy enables a rapid and reliable means to directly identify, phenotypically characterize, and facilitate target-based whole cell assays to screen A. fumigatus essential genes for cognate antifungal inhibitors.

Aspergillus fumigatus is an opportunistic filamentous fungal pathogen of emerging clinical significance. Although virulence factors are seen as potential drug targets, neither genetic analyses nor genomic comparisons have identified genuine virulence factors in A. fumigatus. Essential genes required for fungal growth and viability also serve as potential drug targets, yet few have been described in this pathogen. To begin to catalog essential genes in A. fumigatus, we devised a genetic strategy for creating conditional mutants by promoter replacement of target genes using a nitrogen-regulated promoter. Applying this genetic approach to A. fumigatus genes orthologous to known essential genes of the nonpathogenic yeast, Saccharomyces cerevisiae and Candida albicans, we demonstrate a robust enrichment for identifying essential genes conserved within this pathogen. We show that A. fumigatus conditional mutants can be evaluated according to their terminal phenotypes (e.g., conidial germination, growth, morphology, and cidal versus static consequences) and pathogenesis in a murine model of systemic aspergillosis to prioritize essential genes as novel drug targets suitable for developing broad-spectrum antifungal agents.

Genetic basis for dosage sensitivity in Arabidopsis thaliana

Aneuploidy, the relative excess or deficiency of specific chromosome types, results in gene dosage imbalance. Plants can produce viable and fertile aneuploid individuals, while most animal aneuploids are inviable or developmentally abnormal. The swarms of aneuploid progeny produced by Arabidopsis triploids constitute an excellent model to investigate the mechanisms governing dosage sensitivity and aneuploid syndromes. Indeed, genotype alters the frequency of aneuploid types within these swarms. Recombinant inbred lines that were derived from a triploid hybrid segregated into diploid and tetraploid individuals. In these recombinant inbred lines, a single locus, which we call SENSITIVE TO DOSAGE IMBALANCE (SDI), exhibited segregation distortion in the tetraploid subpopulation only. Recent progress in quantitative genotyping now allows molecular karyotyping and genetic analysis of aneuploid populations. In this study, we investigated the causes of the ploidy-specific distortion at SDI. Allele frequency was distorted in the aneuploid swarms produced by the triploid hybrid. We developed a simple quantitative measure for aneuploidy lethality and using this measure demonstrated that distortion was greatest in the aneuploids facing the strongest viability selection. When triploids were crossed to euploids, the progeny, which lack severe aneuploids, exhibited no distortion at SDI. Genetic characterization of SDI in the aneuploid swarm identified a mechanism governing aneuploid survival, perhaps by buffering the effects of dosage imbalance. As such, SDI could increase the likelihood of retaining genomic rearrangements such as segmental duplications. Additionally, in species where triploids are fertile, aneuploid survival would facilitate gene flow between diploid and tetraploid populations via a triploid bridge and prevent polyploid speciation. Our results demonstrate that positional cloning of loci affecting traits in populations containing ploidy and chromosome number variants is now feasible using quantitative genotyping approaches.

Cellular processes and pathways that protect Saccharomyces cerevisiae cells against the plasma membrane-perturbing compound chitosan

Global fitness analysis makes use of a genomic library of tagged deletion strains. We used this approach to study the effect of chitosan, which causes plasma membrane stress. The data were analyzed using T-profiler, which was based on determining the sensitivities of groups of deletion strains to chitosan, as defined by Gene Ontology (GO) and by genomic synthetic lethality screens, in combination with t statistics. The chitosan-hypersensitive groups included a group of deletion strains characterized by a defective HOG (high-osmolarity glycerol) signaling pathway, indicating that the HOG pathway is required for counteracting chitosan-induced stress. Consistent with this, activation of this pathway in wild-type cells by hypertonic conditions offered partial protection against chitosan, whereas hypotonic conditions sensitized the cells to chitosan. Other chitosan-hypersensitive groups were defective in RNA synthesis and processing, actin cytoskeleton organization, protein N-glycosylation, ergosterol synthesis, endocytosis, or cell wall formation, predicting that these cellular functions buffer the cell against the deleterious effect of chitosan. These predictions were supported by showing that tunicamycin, miconazole, and staurosporine (which target protein N-glycosylation, ergosterol synthesis, and the cell wall integrity pathway, respectively) sensitized Saccharomyces cerevisiae cells to chitosan. Intriguingly, the GO-defined group of deletion strains belonging to the "cytosolic large ribosomal subunit" was more resistant to chitosan. We propose that global fitness analysis of yeast in combination with T-profiler is a powerful tool to identify specific cellular processes and pathways that are required for survival under stress conditions.

Onge RP, Proctor MJ, Giaever G, Davis RW, Crews P, Holman TR, Lokey RS. Accelerating the discovery of biologically active small molecules using a high-throughput yeast halo assay

The budding yeast Saccharomyces cerevisiae, a powerful model system for the study of basic eukaryotic cell biology, has been used increasingly as a screening tool for the identification of bioactive small molecules. We have developed a novel yeast toxicity screen that is easily automated and compatible with high-throughput screening robotics. The new screen is quantitative and allows inhibitory potencies to be determined, since the diffusion of the sample provides a concentration gradient and a corresponding toxicity halo. The efficacy of this new screen was illustrated by testing materials including 3104 compounds from the NCI libraries, 167 marine sponge crude extracts, and 149 crude marine-derived fungal extracts. There were 46 active compounds among the NCI set. One very active extract was selected for bioactivity-guided fractionation, resulting in the identification of crambescidin 800 as a potent antifungal agent.

Screening and characterization of microbial inhibitors against eukaryotic protein phosphatases (PP1 and PP2A)

AIM

To identify novel microbial inhibitors of protein phosphatase 1 (PP1).

METHODS AND RESULTS

750 actinomycetes and 408 microfungi were isolated from Sabah forest soils and screened for production of potential PP1 inhibitors using an in vivo screening system, in which candidate inhibitors were identified through mimicking the properties of PP1-deficient yeast cells. Acetone extracts of two fungi, H9318 (Penicillium) and H9978 (non-Penicillium) identified in this way showed inhibitory activity towards both mammalian PP1 and PP2A in an in vitro phosphatase assay, while extract from H7520 (Streptomyces) inhibited PP2A but not PP1. Consistently, using a drug-induced haploinsufficiency test, strains with either reduced PP1 or PP2A function were hypersensitive to H9318 and H9978 extracts whereas only the latter strain showed hypersensitivity to H7250 extract. H9318 extract was fractionated using RP-HPLC into two active peaks (S1 and S2). A yeast strain with reduced PP1 function showed hypersensitivity to fraction S2 whereas a strain with reduced PP2A function was hypersensitive to fraction S1. However, S1 and S2 inhibited both PP1 and PP2A activities to a similar extent.

CONCLUSION

Three candidate PP inhibitors have been identified.

SIGNIFICANCE AND IMPACT OF THE STUDY

Further development may generate useful research tools and ultimately therapeutic agents.

Functional and comparative characterization of Saccharomyces cerevisiae RVB1 and RVB2 genes with bacterial Ruv homologues

Expression of yeast RuvB-like gene analogues of bacterial RuvB is self-regulated, as episomal overexpression of RVB1 and RVB2 decreases the expression of their chromosomal copies by 85%. Heterozygosity for either gene correlates with lower double-strand break repair of inverted-repeat DNA and decreased survival after UV irradiation, suggesting their haploinsufficiency, while overexpression of the bacterial RuvAB complex improves UV survival in yeast. Rvb2p preferentially binds artificial DNA Holiday junctions like the bacterial RuvAB complex, whereas Rvb1p binds to duplex or cruciform DNA. As both proteins also interact with chromatin, their role in recombination and repair through chromatin remodelling, and their evolutionary relationship to the bacterial homologue, is discussed.

dSLAM analysis of genome-wide genetic interactions in Saccharomyces cerevisiae

Analysis of genetic interactions has been extensively exploited to study gene functions and to dissect pathway structures. One such genetic interaction is synthetic lethality, in which the combination of two non-lethal mutations leads to loss of organism viability. We have developed a dSLAM (heterozygote diploid-based synthetic lethality analysis with microarrays) technology that effectively studies synthetic lethality interactions on a genome-wide scale in the budding yeast Saccharomyces cerevisiae. Typically, a query mutation is introduced en masse into a population of approximately 6000 haploid-convertible heterozygote diploid Yeast Knockout (YKO) mutants via integrative transformation. Haploid pools of single and double mutants are freshly generated from the resultant heterozygote diploid double mutant pool after meiosis and haploid selection and studied for potential growth defects of each double mutant combination by microarray analysis of the "molecular barcodes" representing each YKO. This technology has been effectively adapted to study other types of genome-wide genetic interactions including gene-compound synthetic lethality, secondary mutation suppression, dosage-dependent synthetic lethality and suppression.

Application of the comprehensive set of heterozygous yeast deletion mutants to elucidate the molecular basis of cellular chromium toxicity

BACKGROUND

The serious biological consequences of metal toxicity are well documented, but the key modes of action of most metals are unknown. To help unravel molecular mechanisms underlying the action of chromium, a metal of major toxicological importance, we grew over 6,000 heterozygous yeast mutants in competition in the presence of chromium. Microarray-based screens of these heterozygotes are truly genome-wide as they include both essential and non-essential genes.

RESULTS

The screening data indicated that proteasomal (protein degradation) activity is crucial for cellular chromium (Cr) resistance. Further investigations showed that Cr causes the accumulation of insoluble and toxic protein aggregates, which predominantly arise from proteins synthesised during Cr exposure. A protein-synthesis defect provoked by Cr was identified as mRNA mistranslation, which was oxygen-dependent. Moreover, Cr exhibited synergistic toxicity with a ribosome-targeting drug (paromomycin) that is known to act via mistranslation, while manipulation of translational accuracy modulated Cr toxicity.

CONCLUSION

The datasets from the heterozygote screen represent an important public resource that may be exploited to discover the toxic mechanisms of chromium. That potential was validated here with the demonstration that mRNA mistranslation is a primary cause of cellular Cr toxicity.

Signature-tagged mutagenesis: barcoding mutants for genome-wide screens

DNA signature tags (molecular barcodes) facilitate functional screens by identifying mutants in mixed populations that have a reduced or increased adaptation to a particular environment. Many innovative adaptations and refinements in the technology have been described since its original use with Salmonella; they have yielded a wealth of information on a broad range of biological processes--mainly in bacteria, but also in yeast and other fungi, viruses, parasites and, most recently, in mammalian cells. By combining whole-genome microarrays and comprehensive ordered libraries of mutants, high-throughput functional screens can now be achieved on a genomic scale.

Systems biology, metabolic modelling and metabolomics in drug discovery and development

Unlike signalling pathways, metabolic networks are subject to strict stoichiometric constraints. Metabolomics amplifies changes in the proteome, and represents more closely the phenotype of an organism. Recent advances enable the production (and computer-readable encoding as SBML) of metabolic network models reconstructed from genome sequences, as well as experimental measurements of much of the metabolome. There is increasing convergence between the number of human metabolites estimated via genomics ( approximately 3000) and the number measured experimentally. It is thus both timely, and now possible, to bring these two approaches together as an integrated (if distributed) whole to help understand the genesis of metabolic biomarkers, the progress of disease, and the modes of action, efficacy, off-target effects and toxicity of pharmaceutical drugs.

Towards high-throughput characterization of small molecule mechanisms of action

Drug discovery is hampered by the lack of general strategies to characterize the mechanisms of action and intracellular targets of bioactive small molecules. Genomics and proteomics promise to aid in this process. Genome-wide approaches in yeast have proven useful to infer the targets and target pathways of small molecules. These approaches are being systematically transferred into mammalian cell culture systems in order to interrogate more complex pathways in a more relevant setting. Advances in proteomics and in vivo genetic screening in multicellular model organism systems are also becoming increasingly powerful and amenable to high-throughput. Current methodologies and technologies are discussed, including how these global approaches complement affinity-based target identification strategies.

Yeast as a tool to uncover the cellular targets of drugs

Knowledge of the spectrum of cellular proteins targeted by experimental therapeutic agents would greatly facilitate drug development. However, identifying the targets of drugs is a daunting challenge. The yeast Saccharomyces cerevisiae is a valuable model organism for human diseases and pathways because it is genetically tractable and shares many functional homolog with humans. In yeast, it is possible to increase or decrease the expression level of essentially every gene and measure changes in drug sensitivity to uncover potential targets. It is also possible to infer mechanism of action from comparing the changes in mRNA expression elicited by drug treatment with those induced by gene deletions or by other drugs. Proteins that bind drugs directly can be identified using yeast protein chips. This review of the use of yeast for discovering targets of drugs discusses the advantages and drawbacks of each approach and how combining methods may reveal targets more efficiently.

A unique and universal molecular barcode array

Molecular barcode arrays allow the analysis of thousands of biological samples in parallel through the use of unique 20-base-pair (bp) DNA tags. Here we present a new barcode array, which is unique among microarrays in that it includes at least five replicates of every tag feature. The use of smaller dispersed replicate features dramatically improves performance versus a single larger feature and allows the correction of previously undetectable hybridization defects.