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

Target Identification and Mechanism of Action of Picolinamide and Benzamide Chemotypes with Antifungal Properties

Invasive fungal infections are accompanied by high mortality rates that range up to 90%. At present, only three different compound classes are available for use in the clinic, and these often suffer from low bioavailability, toxicity, and drug resistance. These issues emphasize an urgent need for novel antifungal agents. Herein, we report the identification of chemically versatile benzamide and picolinamide scaffolds with antifungal properties. Chemogenomic profiling and biochemical assays with purified protein identified Sec14p, the major phosphatidylinositol/phosphatidylcholine transfer protein in Saccharomyces cerevisiae, as the sole essential target for these compounds. A functional variomics screen identified resistance-conferring residues that localized to the lipid-binding pocket of Sec14p. Determination of the X-ray co-crystal structure of a Sec14p-compound complex confirmed binding in this cavity and rationalized both the resistance-conferring residues and the observed structure-activity relationships. Taken together, these findings open new avenues for rational compound optimization and development of novel antifungal agents.

Design strategies of oxidosqualene cyclase inhibitors: Targeting the sterol biosynthetic pathway

Targeting the sterol biosynthesis pathway has been explored for the development of new bioactive compounds. Among the enzymes of this pathway, oxidosqualene cyclase (OSC) which catalyzes lanosterol cyclization from 2,3-oxidosqualene has emerged as an attractive target. In this work, we reviewed the most promising OSC inhibitors from different organisms and their potential for the development of new antiparasitic, antifungal, hypocholesterolemic and anticancer drugs. Different strategies have been adopted for the discovery of new OSC inhibitors, such as structural modifications of the natural substrate or the reaction intermediates, the use of the enzyme's structural information to discover compounds with novel chemotypes, modifications of known inhibitors and the use of molecular modeling techniques such as docking and virtual screening to search for new inhibitors. This review brings new perspectives on structural insights of OSC from different organisms and reveals the broad structural diversity of OSC inhibitors which may help evidence lead compounds for further investigations with various therapeutic applications.

Network-assisted target identification for haploinsufficiency and homozygous profiling screens

Chemical genomic screens have recently emerged as a systematic approach to drug discovery on a genome-wide scale. Drug target identification and elucidation of the mechanism of action (MoA) of hits from these noisy high-throughput screens remain difficult. Here, we present GIT (Genetic Interaction Network-Assisted Target Identification), a network analysis method for drug target identification in haploinsufficiency profiling (HIP) and homozygous profiling (HOP) screens. With the drug-induced phenotypic fitness defect of the deletion of a gene, GIT also incorporates the fitness defects of the gene's neighbors in the genetic interaction network. On three genome-scale yeast chemical genomic screens, GIT substantially outperforms previous scoring methods on target identification on HIP and HOP assays, respectively. Finally, we showed that by combining HIP and HOP assays, GIT further boosts target identification and reveals potential drug's mechanism of action.

A Mini HIP HOP Assay Uncovers a Central Role for Copper and Zinc in the Antifungal Mode of Action of Allicin

Garlic contains the organosulfur compound allicin which exhibits potent antifungal activity. Here we demonstrate the use of a highly simplified yeast chemical genetic screen to characterize its mode of action. By screening 24 validated yeast gene deletion "signature" strains for which hypersensitivity is characteristic for common antifungal modes of action, yeast lacking the high affinity Cu²⁺ transporter Ctr1 was found to be hypersensitive to allicin. Focusing on transition metal related genes identified two more hypersensitive strains lacking the Cu²⁺ and Zn²⁺ transcription factors Mac1 and Zap1. Hypersensitivity in these strains was reversed by the addition of Cu²⁺ and Zn²⁺ ions, respectively. The results suggest the antifungal activity of allicin is mediated through restricted Cu²⁺ and Zn²⁺ uptake or inhibition of Cu²⁺ and Zn²⁺ metalloproteins. As certain antimicrobial modes of action are much more common than others, the approach taken here provides a useful way to identify them early on.

Identification of Genes in Saccharomyces cerevisiae that Are Haploinsufficient for Overcoming Amino Acid Starvation

The yeast Saccharomyces cerevisiae responds to amino acid deprivation by activating a pathway conserved in eukaryotes to overcome the starvation stress. We have screened the entire yeast heterozygous deletion collection to identify strains haploinsufficient for growth in the presence of sulfometuron methyl, which causes starvation for isoleucine and valine. We have discovered that cells devoid of MET15 are sensitive to sulfometuron methyl, and loss of heterozygosity at the MET15 locus can complicate screening the heterozygous deletion collection. We identified 138 cases of loss of heterozygosity in this screen. After eliminating the issues of the MET15 loss of heterozygosity, strains isolated from the collection were retested on sulfometuron methyl. To determine the general effect of the mutations for a starvation response, SMM-sensitive strains were tested for the ability to grow in the presence of canavanine, which induces arginine starvation, and strains that were MET15 were also tested for growth in the presence of ethionine, which causes methionine starvation. Many of the genes identified in our study were not previously identified as starvation-responsive genes, including a number of essential genes that are not easily screened in a systematic way. The genes identified span a broad range of biological functions, including many involved in some level of gene expression. Several unnamed proteins have also been identified, giving a clue as to possible functions of the encoded proteins.

A novel approach to the discovery of anti-tumor pharmaceuticals: searching for activators of liponecrosis

A recently conducted chemical genetic screen for pharmaceuticals that can extend longevity of the yeast Saccharomyces cerevisiae has identified lithocholic acid as a potent anti-aging molecule. It was found that this hydrophobic bile acid is also a selective anti-tumor chemical compound; it kills different types of cultured cancer cells if used at concentrations that do not compromise the viability of non-cancerous cells. These studies have revealed that yeast can be successfully used as a model organism for high-throughput screens aimed at the discovery of selectively acting anti-tumor small molecules. Two metabolic traits of rapidly proliferating fermenting yeast, namely aerobic glycolysis and lipogenesis, are known to be similar to those of cancer cells. The mechanisms underlying these key metabolic features of cancer cells and fermenting yeast have been established; such mechanisms are discussed in this review. We also suggest how a yeast-based chemical genetic screen can be used for the high-throughput development of selective anti-tumor pharmaceuticals that kill only cancer cells. This screen consists of searching for chemical compounds capable of increasing the abundance of membrane lipids enriched in unsaturated fatty acids that would therefore be toxic only to rapidly proliferating cells, such as cancer cells and fermenting yeast.

High-Resolution Genetics Identifies the Lipid Transfer Protein Sec14p as Target for Antifungal Ergolines

Invasive infections by fungal pathogens cause more deaths than malaria worldwide. We found the ergoline compound NGx04 in an antifungal screen, with selectivity over mammalian cells. High-resolution chemogenomics identified the lipid transfer protein Sec14p as the target of NGx04 and compound-resistant mutations in Sec14p define compound-target interactions in the substrate binding pocket of the protein. Beyond its essential lipid transfer function in a variety of pathogenic fungi, Sec14p is also involved in secretion of virulence determinants essential for the pathogenicity of fungi such as Cryptococcus neoformans, making Sec14p an attractive antifungal target. Consistent with this dual function, we demonstrate that NGx04 inhibits the growth of two clinical isolates of C. neoformans and that NGx04-related compounds have equal and even higher potency against C. neoformans. Furthermore NGx04 analogues showed fungicidal activity against a fluconazole resistant C. neoformans strain. In summary, we present genetic evidence that NGx04 inhibits fungal Sec14p and initial data supporting NGx04 as a novel antifungal starting point.

Emerging resistance to antibiotics led to an inglorious revival of infectious diseases. Furthermore, in the past 30 years, only one novel anti-fungal target has been discovered which was used to develop therapies against. Therefore pathogen-selective targets and knowledge about possible resistance determinants are of utmost importance to successfully develop new medicines. Here we describe the identification of anti-fungal ergolines, targeting the lipid transfer protein Sec14p, and inhibiting the growth of two clinical isolates of the pathogenic fungus Cryptococcus neoformans. Both, compound and target represent attractive points for further investigations: Sec14p as it differs significantly from the human homolog and as it has been implicated in fungal viability and pathogenicity, and, ergolines as they are used in the clinic against a variety of diseases demonstrating both efficacy and safety.

Insight into the RNA Exosome Complex Through Modeling Pontocerebellar Hypoplasia Type 1b Disease Mutations in Yeast

Pontocerebellar hypoplasia type 1b (PCH1b) is an autosomal recessive disorder that causes cerebellar hypoplasia and spinal motor neuron degeneration, leading to mortality in early childhood. PCH1b is caused by mutations in the RNA exosome subunit gene, EXOSC3 The RNA exosome is an evolutionarily conserved complex, consisting of nine different core subunits, and one or two 3'-5' exoribonuclease subunits, that mediates several RNA degradation and processing steps. The goal of this study is to assess the functional consequences of the amino acid substitutions that have been identified in EXOSC3 in PCH1b patients. To analyze these EXOSC3 substitutions, we generated the corresponding amino acid substitutions in the Saccharomyces cerevisiae ortholog of EXOSC3, Rrp40 We find that the rrp40 variants corresponding to EXOSC3-G31A and -D132A do not affect yeast function when expressed as the sole copy of the essential Rrp40 protein. In contrast, the rrp40-W195R variant, corresponding to EXOSC3-W238R in PCH1b patients, impacts cell growth and RNA exosome function when expressed as the sole copy of Rrp40 The rrp40-W195R protein is unstable, and does not associate efficiently with the RNA exosome in cells that also express wild-type Rrp40 Consistent with these findings in yeast, the levels of mouse EXOSC3 variants are reduced compared to wild-type EXOSC3 in a neuronal cell line. These data suggest that cells possess a mechanism for optimal assembly of functional RNA exosome complex that can discriminate between wild-type and variant exosome subunits. Budding yeast can therefore serve as a useful tool to understand the molecular defects in the RNA exosome caused by PCH1b-associated amino acid substitutions in EXOSC3, and potentially extending to disease-associated substitutions in other exosome subunits.

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

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

Systematic Mapping of Chemical-Genetic Interactions in Saccharomyces cerevisiae

Chemical-genetic interactions (CGIs) describe a phenomenon where the effects of a chemical compound (i.e., a small molecule) on cell growth are dependent on a particular gene. CGIs can reveal important functional information about genes and can also be powerful indicators of a compound's mechanism of action. Mapping CGIs can lead to the discovery of new chemical probes, which, in contrast to genetic perturbations, operate at the level of the gene product (or pathway) and can be fast-acting, tunable, and reversible. The simple culture conditions required for yeast and its rapid growth, as well as the availability of a complete set of barcoded gene deletion strains, facilitate systematic mapping of CGIs in this organism. This process involves two basic steps: first, screening chemical libraries to identify bioactive compounds affecting growth and, second, measuring the effects of these compounds on genome-wide collections of mutant strains. Here, we introduce protocols for both steps that have great potential for the discovery and development of new small-molecule tools and medicines.

Genome stability versus transcript diversity

Our genome is protected from the introduction of mutations by high fidelity replication and an extensive network of DNA damage response and repair mechanisms. However, the expression of our genome, via RNA and protein synthesis, allows for more diversity in translating genetic information. In addition, the splicing process has become less stringent over evolutionary time allowing for a substantial increase in the diversity of transcripts generated. The result is a diverse transcriptome and proteome that harbor selective advantages over a more tightly regulated system. Here, we describe mechanisms in place that both safeguard the genome and promote translational diversity, with emphasis on post-transcriptional RNA processing.

Genetic evidence for involvement of membrane trafficking in the action of 5-fluorouracil

To identify novel genes that mediate cellular sensitivity and resistance to 5-fluorouracil (5-FU), we performed a genome-wide genetic screening to identify altered susceptibility to 5-FU by Schizosaccharomyces pombe haploid nonessential gene deletion library containing 3004 deletion mutants. We identified 50 hypersensitive and 12 resistant mutants to this drug. Mutants sensitive or resistant to 5-FU were classified into various categories based on their putative functions. The largest group of the genes whose disruption renders cells altered susceptibility to 5-FU is involved in nucleic acid metabolism, but to our surprise, the second largest group is involved in membrane trafficking. In addition, several other membrane traffic mutants examined including gdi1-i11, ypt3-i5, Δryh1, Δric1, and Δaps1 exhibited hypersensitivity to 5-FU. Furthermore, we found that 5-FU in low concentration that generally do not affect cell growth altered the localization of Syb1, a secretory vesicle SNARE synaptobrevin which is cycled between the plasma membrane and the endocytic pathway. Notably, 5-FU at such low concentration also significantly inhibited the secretion of acid phosphatase. Altogether, our findings revealed the first evidence that 5-FU influences membrane trafficking as the potential underlying mechanism of the drug action.

Genetic Strategies for Identifying New Drug Targets

Genetic strategies have yet to come into their own as tools for antibiotic development. While holding a lot of initial promise, they have only recently started to bear fruit in the quest for new drug targets. An ever-increasing body of knowledge is showing that genetics can lead to significant improvements in the success and efficiency of drug discovery. Techniques such as high-frequency transposon mutagenesis and expression modulation have matured and have been applied successfully not only to the identification and characterization of new targets, but also to their validation as tractable weaknesses of bacteria. Past experience shows that choosing targets must not rely on gene essentiality alone, but rather needs to incorporate knowledge of the system as a whole. The ability to manipulate genes and their expression is key to ensuring that we understand the entire set of processes that are affected by drug treatment. Focusing on exacerbating these perturbations, together with the identification of new targets to which resistance has not yet occurred--both enabled by genetic approaches--may point us toward the successful development of new combination therapies engineered based on underlying biology.

Compound annotation with real time cellular activity profiles to improve drug discovery

INTRODUCTION

In the past decade, a range of innovative strategies have been developed to improve the productivity of pharmaceutical research and development. In particular, compound annotation, combined with informatics, has provided unprecedented opportunities for drug discovery.

AREAS COVERED

In this review, a literature search from 2000 to 2015 was conducted to provide an overview of the compound annotation approaches currently used in drug discovery. Based on this, a framework related to a compound annotation approach using real-time cellular activity profiles for probe, drug, and biology discovery is proposed.

EXPERT OPINION

Compound annotation with chemical structure, drug-like properties, bioactivities, genome-wide effects, clinical phenotypes, and textural abstracts has received significant attention in early drug discovery. However, these annotations are mostly associated with endpoint results. Advances in assay techniques have made it possible to obtain real-time cellular activity profiles of drug molecules under different phenotypes, so it is possible to generate compound annotation with real-time cellular activity profiles. Combining compound annotation with informatics, such as similarity analysis, presents a good opportunity to improve the rate of discovery of novel drugs and probes, and enhance our understanding of the underlying biology.

The global effect of exposing bakers' yeast to 5-fluoruracil and nystatin; a view to Toxichip

A genome-wide screen of a haploid deletion library of bakers' yeast (Saccharomyces cerevisiae) was conducted to document the phenotypic and transcriptional impact of exposure to each of the two pharmaceutical products 5-fluorouracil (an anti-tumor agent) and nystatin (an anti-fungal agent). The combined data set was handled by applying a systems biology perspective. A Gene Ontology analysis identified functional categories previously characterized as likely targets for both compounds. Induced transcription profiles were well correlated in yeast and human HepG2 cells. The identified molecular targets for both compounds were used to suggest a small set of human orthologues as appropriate for testing on human material. The yeast system developed here (denoted "Toxichip") has likely utility for identifying biomarkers relevant for health and environmental risk assessment applications required as part of the development process for novel pharmaceuticals.

Pooled shRNA Screening in Mammalian Cells as a Functional Genomic Discovery Platform

Functional genomic screens using shRNA technology are a great tool in biomedical research. As more labs gain access to the necessary reagents and technology to perform such screens, some may lack in-depth knowledge on the difficulties often encountered. With this protocol, we aim to point out the most important caveats of performing shRNA based screens and provide a streamlined workflow that can be easily adapted to meet the specific needs of any particular screening project.

Rrp6: Integrated roles in nuclear RNA metabolism and transcription termination

The yeast RNA exosome is a eukaryotic ribonuclease complex essential for RNA processing, surveillance, and turnover. It is comprised of a barrel-shaped core and cap as well as a 3'-5' ribonuclease known as Dis3 that contains both endo- and exonuclease domains. A second exonuclease, Rrp6, is added in the nucleus. Dis3 and Rrp6 have both shared and distinct roles in RNA metabolism, and this review will focus primarily on Rrp6 and the roles of the RNA exosome in the nucleus. The functions of the nuclear exosome are modulated by cofactors and interacting partners specific to each type of substrate. Generally, the cofactor TRAMP (Trf4/5-Air2/1-Mtr4 polyadenylation) complex helps unwind unstable RNAs, RNAs requiring processing such as rRNAs, tRNAs, or snRNAs or improperly processed RNAs and direct it toward the exosome. In yeast, Rrp6 interacts with Nrd1, the cap-binding complex, and RNA polymerase II to aid in nascent RNA processing, termination, and polyA tail length regulation. Recent studies have shown that proper termination and processing of short, noncoding RNAs by Rrp6 is particularly important for transcription regulation across the genome and has important implications for regulation of diverse processes at the cellular level. Loss of proper Rrp6 and exosome activity may contribute to various pathologies such as autoimmune disease, neurological disorders, and cancer. WIREs RNA 2016, 7:91-104. doi: 10.1002/wrna.1317 For further resources related to this article, please visit the WIREs website.

Novel, Synergistic Antifungal Combinations that Target Translation Fidelity

There is an unmet need for new antifungal or fungicide treatments, as resistance to existing treatments grows. Combination treatments help to combat resistance. Here we develop a novel, effective target for combination antifungal therapy. Different aminoglycoside antibiotics combined with different sulphate-transport inhibitors produced strong, synergistic growth-inhibition of several fungi. Combinations decreased the respective MICs by ≥8-fold. Synergy was suppressed in yeast mutants resistant to effects of sulphate-mimetics (like chromate or molybdate) on sulphate transport. By different mechanisms, aminoglycosides and inhibition of sulphate transport cause errors in mRNA translation. The mistranslation rate was stimulated up to 10-fold when the agents were used in combination, consistent with this being the mode of synergistic action. A range of undesirable fungi were susceptible to synergistic inhibition by the combinations, including the human pathogens Candida albicans, C. glabrata and Cryptococcus neoformans, the food spoilage organism Zygosaccharomyces bailii and the phytopathogens Rhizoctonia solani and Zymoseptoria tritici. There was some specificity as certain fungi were unaffected. There was no synergy against bacterial or mammalian cells. The results indicate that translation fidelity is a promising new target for combinatorial treatment of undesirable fungi, the combinations requiring substantially decreased doses of active components compared to each agent alone.

Functional genomics to uncover drug mechanism of action

The upswing in US Food and Drug Administration and European Medicines Agency drug approvals in 2014 may have marked an end to the dry spell that has troubled the pharmaceutical industry over the past decade. Regardless, the attrition rate of drugs in late clinical phases remains high, and a lack of target validation has been highlighted as an explanation. This has led to a resurgence in appreciation of phenotypic drug screens, as these may be more likely to yield compounds with relevant modes of action. However, cell-based screening approaches do not directly reveal cellular targets, and hence target deconvolution and a detailed understanding of drug action are needed for efficient lead optimization and biomarker development. Here, recently developed functional genomics technologies that address this need are reviewed. The approaches pioneered in model organisms, particularly in yeast, and more recently adapted to mammalian systems are discussed. Finally, areas of particular interest and directions for future tool development are highlighted.

Collateral Lethality: A new therapeutic strategy in oncology

Genomic deletion of tumor suppressor genes (TSG) is a rite of passage for virtually all human cancers. The synthetic lethal paradigm has provided a framework for the development of molecular targeted therapeutics that are functionally linked to the loss of specific TSG functions. In the course of genomic events that delete TSGs, a large number of genes with no apparent direct role in tumor promotion also sustain deletion as a result of chromosomal proximity to the target TSG. In this perspective, we review the novel concept of "collateral lethality", which has served to identify cancer-specific therapeutic vulnerabilities resulting from co-deletion of passenger genes neighboring TSG. The large number of collaterally deleted genes, playing diverse functions in cell homeostasis, offers a rich repertoire of pharmacologically targetable vulnerabilities presenting novel opportunities for the development of personalized anti-neoplastic therapies.

Efforts to make and apply humanized yeast

Despite a billion years of divergent evolution, the baker’s yeast Saccharomyces cerevisiae has long proven to be an invaluable model organism for studying human biology. Given its tractability and ease of genetic manipulation, along with extensive genetic conservation with humans, it is perhaps no surprise that researchers have been able to expand its utility by expressing human proteins in yeast, or by humanizing specific yeast amino acids, proteins or even entire pathways. These methods are increasingly being scaled in throughput, further enabling the detailed investigation of human biology and disease-specific variations of human genes in a simplified model organism.

Yeast: a microbe with macro-implications to antimicrobial drug discovery

Paramount to any rational discovery of new antibiotics displaying novel mechanisms of action is a deep knowledge of the genetic basis of microbial growth, division and virulence. The bakers' yeast,Saccharomyces cerevisiae, illustrates the highest understanding of the genetic underpinnings of microbial life, and from this framework, a systems biology paradigm has evolved, begging to be emulated in antibacterial discovery. Here, we review landmark events in the history of yeast genomics that provide this new foundation for antibacterial drug discovery.

Modelling of compound combination effects and applications to efficacy and toxicity: state-of-the-art, challenges and perspectives

The development of treatments involving combinations of drugs is a promising approach towards combating complex or multifactorial disorders. However, the large number of compound combinations that can be generated, even from small compound collections, means that exhaustive experimental testing is infeasible. The ability to predict the behaviour of compound combinations in biological systems, whittling down the number of combinations to be tested, is therefore crucial. Here, we review the current state-of-the-art in the field of compound combination modelling, with the aim to support the development of approaches that, as we hope, will finally lead to an integration of chemical with systems-level biological information for predicting the effect of chemical mixtures.

Confirmation of the cellular targets of benomyl and rapamycin using next-generation sequencing of resistant mutants in S. cerevisiae

Investigating the mechanisms of action (MOAs) of bioactive compounds and the deconvolution of their cellular targets is an important and challenging undertaking. Drug resistance in model organisms such as S. cerevisiae has long been a means for discovering drug targets and MOAs. Strains are selected for resistance to a drug of interest, and the resistance mutations can often be mapped to the drug's molecular target using classical genetic techniques. Here we demonstrate the use of next generation sequencing (NGS) to identify mutations that confer resistance to two well-characterized drugs, benomyl and rapamycin. Applying NGS to pools of drug-resistant mutants, we develop a simple system for ranking single nucleotide polymorphisms (SNPs) based on their prevalence in the pool, and for ranking genes based on the number of SNPs that they contain. We clearly identified the known targets of benomyl (TUB2) and rapamycin (FPR1) as the highest-ranking genes under this system. The highest-ranking SNPs corresponded to specific amino acid changes that are known to confer resistance to these drugs. We also found that by screening in a pdr1Δ null background strain that lacks a transcription factor regulating the expression of drug efflux pumps, and by pre-screening mutants in a panel of unrelated anti-fungal agents, we were able to mitigate against the selection of multi-drug resistance (MDR) mutants. We call our approach "Mutagenesis to Uncover Targets by deep Sequencing", or "MUTseq", and show through this proof-of-concept study its potential utility in characterizing MOAs and targets of novel compounds.

Rapid Identification of Chemoresistance Mechanisms Using Yeast DNA Mismatch Repair Mutants

Resistance to cancer therapy is a major obstacle in the long-term treatment of cancer. A greater understanding of drug resistance mechanisms will ultimately lead to the development of effective therapeutic strategies to prevent resistance from occurring. Here, we exploit the mutator phenotype of mismatch repair defective yeast cells combined with whole genome sequencing to identify drug resistance mutations in key pathways involved in the development of chemoresistance. The utility of this approach was demonstrated via the identification of the known CAN1 and TOP1 resistance targets for two compounds, canavanine and camptothecin, respectively. We have also experimentally validated the plasma membrane transporter HNM1 as the primary drug resistance target of mechlorethamine. Furthermore, the sequencing of mitoxantrone-resistant strains identified inactivating mutations within IPT1, a gene encoding inositolphosphotransferase, an enzyme involved in sphingolipid biosynthesis. In the case of bactobolin, a promising anticancer drug, the endocytosis pathway was identified as the drug resistance target responsible for conferring resistance. Finally, we show that that rapamycin, an mTOR inhibitor previously shown to alter the fitness of the ipt1 mutant, can effectively prevent the formation of mitoxantrone resistance. The rapid and robust nature of these techniques, using Saccharomyces cerevisiae as a model organism, should accelerate the identification of drug resistance targets and guide the development of novel therapeutic combination strategies to prevent the development of chemoresistance in various cancers.

Involvement of flocculin in negative potential-applied ITO electrode adhesion of yeast cells

The purpose of this study was to develop novel methods for attachment and cultivation of specifically positioned single yeast cells on a microelectrode surface with the application of a weak electrical potential. Saccharomyces cerevisiae diploid strains attached to an indium tin oxide/glass (ITO) electrode to which a negative potential between −0.2 and −0.4 V vs. Ag/AgCl was applied, while they did not adhere to a gallium-doped zinc oxide/glass electrode surface. The yeast cells attached to the negative potential-applied ITO electrodes showed normal cell proliferation. We found that the flocculin FLO10 gene-disrupted diploid BY4743 mutant strain (flo10Δ /flo10Δ) almost completely lost the ability to adhere to the negative potential-applied ITO electrode. Our results indicate that the mechanisms of diploid BY4743 S. cerevisiae adhesion involve interaction between the negative potential-applied ITO electrode and the Flo10 protein on the cell wall surface. A combination of micropatterning techniques of living single yeast cell on the ITO electrode and omics technologies holds potential of novel, highly parallelized, microchip-based single-cell analysis that will contribute to new screening concepts and applications.

Yeast Saccharomyces cerevisiae were selectively attached on the negative potential-applied indium tin oxide/glass electrode. Mechanisms of the yeast cell attachment involve Flocculin Flo10 proteins.

Network-based inference methods for drug repositioning

Mining potential drug-disease associations can speed up drug repositioning for pharmaceutical companies. Previous computational strategies focused on prior biological information for association inference. However, such information may not be comprehensively available and may contain errors. Different from previous research, two inference methods, ProbS and HeatS, were introduced in this paper to predict direct drug-disease associations based only on the basic network topology measure. Bipartite network topology was used to prioritize the potentially indicated diseases for a drug. Experimental results showed that both methods can receive reliable prediction performance and achieve AUC values of 0.9192 and 0.9079, respectively. Case studies on real drugs indicated that some of the strongly predicted associations were confirmed by results in the Comparative Toxicogenomics Database (CTD). Finally, a comprehensive prediction of drug-disease associations enables us to suggest many new drug indications for further studies.

Rapid identification of chemical genetic interactions in Saccharomyces cerevisiae

Determining the mode of action of bioactive chemicals is of interest to a broad range of academic, pharmaceutical, and industrial scientists. Saccharomyces cerevisiae, or budding yeast, is a model eukaryote for which a complete collection of ~6,000 gene deletion mutants and hypomorphic essential gene mutants are commercially available. These collections of mutants can be used to systematically detect chemical-gene interactions, i.e. genes necessary to tolerate a chemical. This information, in turn, reports on the likely mode of action of the compound. Here we describe a protocol for the rapid identification of chemical-genetic interactions in budding yeast. We demonstrate the method using the chemotherapeutic agent 5-fluorouracil (5-FU), which has a well-defined mechanism of action. Our results show that the nuclear TRAMP RNA exosome and DNA repair enzymes are needed for proliferation in the presence of 5-FU, which is consistent with previous microarray based bar-coding chemical genetic approaches and the knowledge that 5-FU adversely affects both RNA and DNA metabolism. The required validation protocols of these high-throughput screens are also described.

Quantifying the impact of transporters on cellular drug permeability

The conventional model of drug permeability has recently been challenged. An alternative model proposes that transporter-mediated flux is the sole mechanism of cellular drug permeation, instead of existing in parallel with passive transmembrane diffusion. We examined a central assumption of this alternative hypothesis; namely, that transporters can give rise to experimental observations that would typically be explained with passive transmembrane diffusion. Using systems-biology simulations based on available transporter kinetics and proteomic expression data, we found that such observations are possible in the absence of transmembrane diffusion, but only under very specific conditions that rarely or never occur for known human drug transporters.

A genomic screen revealing the importance of vesicular trafficking pathways in genome maintenance and protection against genotoxic stress in diploid Saccharomyces cerevisiae cells

The ability to survive stressful conditions is important for every living cell. Certain stresses not only affect the current well-being of cells but may also have far-reaching consequences. Uncurbed oxidative stress can cause DNA damage and decrease cell survival and/or increase mutation rates, and certain substances that generate oxidative damage in the cell mainly act on DNA. Radiomimetic zeocin causes oxidative damage in DNA, predominantly by inducing single- or double-strand breaks. Such lesions can lead to chromosomal rearrangements, especially in diploid cells, in which the two sets of chromosomes facilitate excessive and deleterious recombination. In a global screen for zeocin-oversensitive mutants, we selected 133 genes whose deletion reduces the survival of zeocin-treated diploid Saccharomyces cerevisiae cells. The screen revealed numerous genes associated with stress responses, DNA repair genes, cell cycle progression genes, and chromatin remodeling genes. Notably, the screen also demonstrated the involvement of the vesicular trafficking system in cellular protection against DNA damage. The analyses indicated the importance of vesicular system integrity in various pathways of cellular protection from zeocin-dependent damage, including detoxification and a direct or transitional role in genome maintenance processes that remains unclear. The data showed that deleting genes involved in vesicular trafficking may lead to Rad52 focus accumulation and changes in total DNA content or even cell ploidy alterations, and such deletions may preclude proper DNA repair after zeocin treatment. We postulate that functional vesicular transport is crucial for sustaining an integral genome. We believe that the identification of numerous new genes implicated in genome restoration after genotoxic oxidative stress combined with the detected link between vesicular trafficking and genome integrity will reveal novel molecular processes involved in genome stability in diploid cells.

A miRNA-driven inference model to construct potential drug-disease associations for drug repositioning

Increasing evidence discovered that the inappropriate expression of microRNAs (miRNAs) will lead to many kinds of complex diseases and drugs can regulate the expression level of miRNAs. Therefore human diseases may be treated by targeting some specific miRNAs with drugs, which provides a new perspective for drug repositioning. However, few studies have attempted to computationally predict associations between drugs and diseases via miRNAs for drug repositioning. In this paper, we developed an inference model to achieve this aim by combining experimentally supported drug-miRNA associations and miRNA-disease associations with the assumption that drugs will form associations with diseases when they share some significant miRNA partners. Experimental results showed excellent performance of our model. Case studies demonstrated that some of the strongly predicted drug-disease associations can be confirmed by the publicly accessible database CTD (www.ctdbase.org), which indicated the usefulness of our inference model. Moreover, candidate miRNAs as molecular hypotheses underpinning the associations were listed to guide future experiments. The predicted results were released for further studies. We expect that this study will provide help in our understanding of drug-disease association prediction and in the roles of miRNAs in drug repositioning.

Genetic Approaches to Facilitate Antibacterial Drug Development

Very few chemically novel agents have been approved for antibacterial chemotherapies during the last 50 yr. Yet new antibacterial drugs are needed to reduce the impact on global health of an increasing number of drug-resistant infections, including highly drug-resistant forms of tuberculosis. This review discusses how genetic approaches can be used to study the mechanism of action of whole-cell screening hits and facilitate target-driven strategies for antimicrobial drug development.

A haploproficient interaction of the transaldolase paralogue NQM1 with the transcription factor VHR1 affects stationary phase survival and oxidative stress resistance

BACKGROUND

Studying the survival of yeast in stationary phase, known as chronological lifespan, led to the identification of molecular ageing factors conserved from yeast to higher organisms. To identify functional interactions among yeast chronological ageing genes, we conducted a haploproficiency screen on the basis of previously identified long-living mutants. For this, we created a library of heterozygous Saccharomyces cerevisiae double deletion strains and aged them in a competitive manner.

RESULTS

Stationary phase survival was prolonged in a double heterozygous mutant of the metabolic enzyme non-quiescent mutant 1 (NQM1), a paralogue to the pentose phosphate pathway enzyme transaldolase (TAL1), and the transcription factor vitamin H response transcription factor 1 (VHR1). We find that cells deleted for the two genes possess increased clonogenicity at late stages of stationary phase survival, but find no indication that the mutations delay initial mortality upon reaching stationary phase, canonically defined as an extension of chronological lifespan. We show that both genes influence the concentration of metabolites of glycolysis and the pentose phosphate pathway, central metabolic players in the ageing process, and affect osmolality of growth media in stationary phase cultures. Moreover, NQM1 is glucose repressed and induced in a VHR1 dependent manner upon caloric restriction, on non-fermentable carbon sources, as well as under osmotic and oxidative stress. Finally, deletion of NQM1 is shown to confer resistance to oxidizing substances.

CONCLUSIONS

The transaldolase paralogue NQM1 and the transcription factor VHR1 interact haploproficiently and affect yeast stationary phase survival. The glucose repressed NQM1 gene is induced under various stress conditions, affects stress resistance and this process is dependent on VHR1. While NQM1 appears not to function in the pentose phosphate pathway, the interplay of NQM1 with VHR1 influences the yeast metabolic homeostasis and stress tolerance during stationary phase, processes associated with yeast ageing.

Genetic basis of haloperidol resistance in Saccharomyces cerevisiae is complex and dose dependent

The genetic basis of most heritable traits is complex. Inhibitory compounds and their effects in model organisms have been used in many studies to gain insights into the genetic architecture underlying quantitative traits. However, the differential effect of compound concentration has not been studied in detail. In this study, we used a large segregant panel from a cross between two genetically divergent yeast strains, BY4724 (a laboratory strain) and RM11_1a (a vineyard strain), to study the genetic basis of variation in response to different doses of a drug. Linkage analysis revealed that the genetic architecture of resistance to the small-molecule therapeutic drug haloperidol is highly dose-dependent. Some of the loci identified had effects only at low doses of haloperidol, while other loci had effects primarily at higher concentrations of the drug. We show that a major QTL affecting resistance across all concentrations of haloperidol is caused by polymorphisms in SWH1, a homologue of human oxysterol binding protein. We identify a complex set of interactions among the alleles of the genes SWH1, MKT1, and IRA2 that are most pronounced at a haloperidol dose of 200 µM and are only observed when the remainder of the genome is of the RM background. Our results provide further insight into the genetic basis of drug resistance.

Variation in response to a drug can be determined by many factors. In the model organism baker's yeast, many studies of chemical resistance traits have uncovered a complex genetic basis of such resistance. However, an in-depth study of how drug dose alters the effects of underlying genetic factors is lacking. Here, we employed linkage analysis to map the specific genetic loci underlying response to haloperidol, a small molecule therapeutic drug, using a large panel of segregants from a cross between two genetically divergent yeast strains BY (a laboratory strain) and RM (a vineyard strain). We found that loci associated with haloperidol resistance are dose-dependent. We also showed that variants in the oxysterol-binding-protein-like domain of the gene SWH1 underlie the major locus detected at all doses of haloperidol. Genetic interactions among genes SWH1, MKT1, and IRA2 in the RM background contribute to the differential response at high concentrations of haloperidol.

Angiotensin II type 1 receptor blockers increase tolerance of cells to copper and cisplatin

The human pathology Wilson disease (WD) is characterized by toxic copper (Cu) accumulation in brain and liver, resulting in, among other indications, mitochondrial dysfunction and apoptosis of hepatocytes. In an effort to identify novel compounds that can alleviate Cu-induced toxicity, we screened the Pharmakon 1600 repositioning library using a Cu-toxicity yeast screen. We identified 2 members of the drug class of Angiotensin II Type 1 receptor blockers (ARBs) that could increase yeast tolerance to Cu, namely Candesartan and Losartan. Subsequently, we show that specific ARBs can increase yeast tolerance to Cu and/or the chemotherapeutic agent cisplatin (Cp). The latter also induces mitochondrial dysfunction and apoptosis in mammalian cells. We further demonstrate that specific ARBs can prevent the prevalence of Cu-induced apoptotic markers in yeast, with Candesartan Cilexetil being the ARB which demonstrated most pronounced reduction of apoptosis-related markers. Next, we tested the sensitivity of a selection of yeast knockout mutants affected in detoxification of reactive oxygen species (ROS) and Cu for Candesartan Cilexetil rescue in presence of Cu. These data indicate that Candesartan Cilexetil increases yeast tolerance to Cu irrespectively of major ROS-detoxifying proteins. Finally, we show that specific ARBs can increase mammalian cell tolerance to Cu, as well as decrease the prevalence of Cu-induced apoptotic markers. All the above point to the potential of ARBs in preventing Cu-induced toxicity in yeast and mammalian cells.

Diversity-oriented synthesis as a tool for chemical genetics

Chemical genetics is an approach for identifying small molecules with the ability to induce a biological phenotype or to interact with a particular gene product, and it is an emerging tool for lead generation in drug discovery. Accordingly, there is a need for efficient and versatile synthetic processes capable of generating complex and diverse molecular libraries, and Diversity-Oriented Synthesis (DOS) of small molecules is the concept of choice to give access to new chemotypes with high chemical diversity. In this review, the combination of chemical genetics and diversity-oriented synthesis to identify new chemotypes as hit compounds in chemical biology and drug discovery is reported, giving an overview of basic concepts and selected case studies.

Synthetic lethal vulnerabilities of cancer

The great majority of targeted anticancer drugs inhibit mutated oncogenes that display increased activity. Yet many tumors do not contain such actionable aberrations, such as those harboring loss-of-function mutations. The notion of targeting synthetic lethal vulnerabilities in cancer cells has provided an alternative approach to exploiting more of the genetic and epigenetic changes acquired during tumorigenesis. Here, we review synthetic lethality as a therapeutic concept that exploits the inherent differences between normal cells and cancer cells. Furthermore, we provide an overview of the screening approaches that can be used to identify synthetic lethal interactions in human cells and present several recently identified interactions that may be pharmacologically exploited. Finally, we indicate some of the challenges of translating synthetic lethal interactions into the clinic and how these may be overcome.

The Mcm2-7 replicative helicase: a promising chemotherapeutic target

Numerous eukaryotic replication factors have served as chemotherapeutic targets. One replication factor that has largely escaped drug development is the Mcm2-7 replicative helicase. This heterohexameric complex forms the licensing system that assembles the replication machinery at origins during initiation, as well as the catalytic core of the CMG (Cdc45-Mcm2-7-GINS) helicase that unwinds DNA during elongation. Emerging evidence suggests that Mcm2-7 is also part of the replication checkpoint, a quality control system that monitors and responds to DNA damage. As the only replication factor required for both licensing and DNA unwinding, Mcm2-7 is a major cellular regulatory target with likely cancer relevance. Mutations in at least one of the six MCM genes are particularly prevalent in squamous cell carcinomas of the lung, head and neck, and prostrate, and MCM mutations have been shown to cause cancer in mouse models. Moreover various cellular regulatory proteins, including the Rb tumor suppressor family members, bind Mcm2-7 and inhibit its activity. As a preliminary step toward drug development, several small molecule inhibitors that target Mcm2-7 have been recently discovered. Both its structural complexity and essential role at the interface between DNA replication and its regulation make Mcm2-7 a potential chemotherapeutic target.

The yeast deletion collection: a decade of functional genomics

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

The haploinsufficiency profile of α-hederin suggests a caspofungin-like antifungal mode of action

The leaves of common ivy (Hedera helix) contain the cytotoxic saponin α-hederin, which is inhibitory to Candida albicans at low concentrations. To investigate the mode of action of α-hederin, a haploinsufficiency screen was carried out using a library of 1152 Saccharomyces cerevisiae deletion strains. An ethanol ivy extract containing α-hederin was used in the initial screen to reduce the amount of compound required. Strains exhibiting disproportionately low growth were then examined in more detail by comparing growth curves in the presence and absence of α-hederin. This approach identified three hypersensitive strains carrying gene deletions for components of the transcription related proteins SWI/SNF, RNA polymerase II and the RSC complex. Saponin cytotoxicity is often attributed to membrane damage, however α-hederin did not induce hypersensitivity with an aminophospholipid translocase deletion strain that is frequently hypersensitive to membrane damaging agents. The haploinsufficiency profile of α-hederin is most similar to that reported for drugs such as caspofungin that inhibit synthesis of the fungal cell wall. Screening with plant extracts rather than isolated compounds, provides a valuable shortcut in haploinsufficiency screening provided hypersensitive strains are then confirmed as such using purified active principles.

Mapping the cellular response to small molecules using chemogenomic fitness signatures

Genome-wide characterization of the in vivo cellular response to perturbation is fundamental to understanding how cells survive stress. Identifying the proteins and pathways perturbed by small molecules affects biology and medicine by revealing the mechanisms of drug action. We used a yeast chemogenomics platform that quantifies the requirement for each gene for resistance to a compound in vivo to profile 3250 small molecules in a systematic and unbiased manner. We identified 317 compounds that specifically perturb the function of 121 genes and characterized the mechanism of specific compounds. Global analysis revealed that the cellular response to small molecules is limited and described by a network of 45 major chemogenomic signatures. Our results provide a resource for the discovery of functional interactions among genes, chemicals, and biological processes.

Large-scale identification and analysis of suppressive drug interactions

One drug may suppress the effects of another. Although knowledge of drug suppression is vital to avoid efficacy-reducing drug interactions or discover countermeasures for chemical toxins, drug-drug suppression relationships have not been systematically mapped. Here, we analyze the growth response of Saccharomyces cerevisiae to anti-fungal compound ("drug") pairs. Among 440 ordered drug pairs, we identified 94 suppressive drug interactions. Using only pairs not selected on the basis of their suppression behavior, we provide an estimate of the prevalence of suppressive interactions between anti-fungal compounds as 17%. Analysis of the drug suppression network suggested that Bromopyruvate is a frequently suppressive drug and Staurosporine is a frequently suppressed drug. We investigated potential explanations for suppressive drug interactions, including chemogenomic analysis, coaggregation, and pH effects, allowing us to explain the interaction tendencies of Bromopyruvate.

5-Fluorouracil affects assembly of stress granules based on RNA incorporation

The antimetabolite 5-fluorouracil is a widely used chemotherapeutic for the treatment of several solid cancers. However, resistance to 5-fluorouracil remains a major drawback in its clinical use. In this study we report that treatment of HeLa cells with 5-fluorouracil resulted in de novo assembly of stress granules. Moreover, we revealed that stress granule assembly under stress conditions as well as disassembly is altered in cells treated with 5-fluorouracil. Notably, we discovered that RACK1, a protein mediating cell survival and apoptosis, is a component of 5-fluorouracil-induced stress granules. To explore the mode of action of 5-fluorouracil accountable for de novo stress granule assembly, we analyzed 5-fluorouracil metabolites and noticed that stress granule assembly is caused by RNA, not DNA incorporating 5-fluorouracil metabolites. Interestingly, we observed that other RNA incorporating drugs also cause assembly of stress granules. Thus, our results suggest that incorporation of chemotherapeutics into RNA may result in stress granule assembly with potential significance in chemoresistance.

A drug similarity network for understanding drug mechanism of action

Chemogenomic experiments, where genetic and chemical perturbations are combined, provide data for discovering the relationships between genotype and phenotype. Traditionally, analysis of chemogenomic datasets has been done considering the sensitivity of the deletion strains to chemicals, and this has shed light on drug mechanism of action and detecting drug targets. Here, we computationally analyzed a large chemogenomic dataset, which combines more than 300 chemicals with virtually all gene deletion strains in the yeast S. cerevisiae. In addition to sensitivity relation between deletion strains and chemicals, we also considered the deletion strains that are resistant to chemicals. We found a small set of genes whose deletion makes the cell resistant to many chemicals. Curiously, these genes were enriched for functions related to RNA metabolism. Our approach allowed us to generate a network of drugs and genes that are connected with resistance or sensitivity relationships. As a quality assessment, we showed that the higher order motifs found in this network are consistent with biological expectations. Finally, we constructed a biologically relevant network projection pertaining to drug similarities, and analyzed this network projection in detail. We propose this drug similarity network as a useful tool for understanding drug mechanism of action.

Improvement of experimental testing and network training conditions with genome-wide microarrays for more accurate predictions of drug gene targets

Background

Genome-wide microarrays have been useful for predicting chemical-genetic interactions at the gene level. However, interpreting genome-wide microarray results can be overwhelming due to the vast output of gene expression data combined with off-target transcriptional responses many times induced by a drug treatment. This study demonstrates how experimental and computational methods can interact with each other, to arrive at more accurate predictions of drug-induced perturbations. We present a two-stage strategy that links microarray experimental testing and network training conditions to predict gene perturbations for a drug with a known mechanism of action in a well-studied organism.

Results

S. cerevisiae cells were treated with the antifungal, fluconazole, and expression profiling was conducted under different biological conditions using Affymetrix genome-wide microarrays. Transcripts were filtered with a formal network-based method, sparse simultaneous equation models and Lasso regression (SSEM-Lasso), under different network training conditions. Gene expression results were evaluated using both gene set and single gene target analyses, and the drug’s transcriptional effects were narrowed first by pathway and then by individual genes. Variables included: (i) Testing conditions – exposure time and concentration and (ii) Network training conditions – training compendium modifications. Two analyses of SSEM-Lasso output – gene set and single gene – were conducted to gain a better understanding of how SSEM-Lasso predicts perturbation targets.

Conclusions

This study demonstrates that genome-wide microarrays can be optimized using a two-stage strategy for a more in-depth understanding of how a cell manifests biological reactions to a drug treatment at the transcription level. Additionally, a more detailed understanding of how the statistical model, SSEM-Lasso, propagates perturbations through a network of gene regulatory interactions is achieved.