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CYP2C9 encodes a cytochrome P450 enzyme responsible for metabolizing up to 15% of small molecule drugs, and CYP2C9 variants can alter the safety and efficacy of these therapeutics. In particular, the anti-coagulant warfarin is prescribed to over 15 million people annually and polymorphisms in CYP2C9 can affect patient response leading to an increased risk of hemorrhage. We developed Click-seq, a pooled yeast-based activity assay to test thousands of variants. Using Click-seq, we measured the activity of 6,142 missense variants expressed in yeast. We also measured the steady-state cellular abundance of 6,370 missense variants expressed in a human cell line using Variant Abundance by Massively Parallel sequencing (VAMP-seq). These data revealed that almost two-thirds of CYP2C9 variants showed decreased activity, and that protein abundance accounted for half of the variation in CYP2C9 function. We also measured activity scores for 319 previously unannotated human variants, many of which may have clinical relevance.

Drug resistance is a consequence of how most modern medicines work. Drugs exert pressure on cells that causes death or the evolution of resistance. Indeed, highly specific drugs are rendered ineffective by a single DNA mutation. In this study, we apply the drug methotrexate, which is widely used in cancer and rheumatoid arthritis, and perform evolution experiments on Baker’s yeast to ask the different ways in which cells become drug resistant. Because of the conserved nature of biological pathways between yeast and man, our results can inform how the same mechanism may operate to render human cells resistant to treatment. Exposure of cells to small molecules and drug therapies imposes a strong selective pressure. As a result, cells rapidly acquire mutations in order to survive. These include resistant variants of the drug target as well as those that modulate drug transport and detoxification. To systematically explore how cells acquire drug resistance in an unbiased manner, rapid cost-effective approaches are required. Methotrexate, as one of the first rationally designed anticancer drugs, has served as a prototypic example of such acquired resistance. Known methotrexate resistance mechanisms include mutations that increase expression of the dihydrofolate reductase (DHFR) target as well as those that maintain function yet reduce the drug’s binding affinity. Recent evidence suggests that target-independent, epistatic mutations can also result in resistance to methotrexate. Currently, however, the relative contribution of such unlinked resistance mutations is not well understood. To address this issue, we took advantage of Saccharomyces cerevisiae as a model eukaryotic system that combined with whole-genome sequencing and a rapid screening methodology, allowed the identification of causative mutations that modulate resistance to methotrexate. We found a recurrent missense mutation in SEC21 (orthologous to human COPG1), which we confirmed in 10 de novo methotrexate-resistant strains. This sec21 allele (S96L) behaves as a recessive, gain-of-function allele, conferring methotrexate resistance that is abrogated by the presence of a wild-type copy of SEC21. These observations indicate that the Sec21p/COPI transport complex has previously uncharacterized roles in modulating methotrexate stress.

Recent estimates suggest that >300 million people are afflicted by serious fungal infections worldwide. Current antifungal drugs are static and toxic and/or have a narrow spectrum of activity. Thus, there is an urgent need for the development of new antifungal drugs. The fungal sphingolipid glucosylceramide (GlcCer) is critical in promoting virulence of a variety of human-pathogenic fungi. In this study, we screened a synthetic drug library for compounds that target the synthesis of fungal, but not mammalian, GlcCer and found two compounds [N′-(3-bromo-4-hydroxybenzylidene)-2-methylbenzohydrazide (BHBM) and its derivative, 3-bromo-N′-(3-bromo-4-hydroxybenzylidene) benzohydrazide (D0)] that were highly effective in vitro and in vivo against several pathogenic fungi. BHBM and D0 were well tolerated in animals and are highly synergistic or additive to current antifungals. BHBM and D0 significantly affected fungal cell morphology and resulted in the accumulation of intracellular vesicles. Deep-sequencing analysis of drug-resistant mutants revealed that four protein products, encoded by genes APL5, COS111, MKK1, and STE2, which are involved in vesicular transport and cell cycle progression, are targeted by BHBM., IMPORTANCE Fungal infections are a significant cause of morbidity and mortality worldwide. Current antifungal drugs suffer from various drawbacks, including toxicity, drug resistance, and narrow spectrum of activity. In this study, we have demonstrated that pharmaceutical inhibition of fungal glucosylceramide presents a new opportunity to treat cryptococcosis and various other fungal infections. In addition to being effective against pathogenic fungi, the compounds discovered in this study were well tolerated by animals and additive to current antifungals. These findings suggest that these drugs might pave the way for the development of a new class of antifungals.

The Saccharomyces cerevisiae genome encodes five sirtuins (Sir2 and Hst1–4), which constitute a conserved family of NAD-dependent histone deacetylases. Cells lacking any individual sirtuin display mild growth and gene silencing defects. However, hst3Δ hst4Δ double mutants are exquisitely sensitive to genotoxins, and hst3Δ hst4Δ sir2Δ mutants are inviable. Our published data also indicate that pharmacological inhibition of sirtuins prevents growth of several fungal pathogens, although the biological basis is unclear. Here, we present genome-wide fitness assays conducted with nicotinamide (NAM), a pan-sirtuin inhibitor. Our data indicate that NAM treatment causes yeast to solicit specific DNA damage response pathways for survival, and that NAM-induced growth defects are mainly attributable to inhibition of Hst3 and Hst4 and consequent elevation of histone H3 lysine 56 acetylation (H3K56ac). Our results further reveal that in the presence of constitutive H3K56ac, the Slx4 scaffolding protein and PP4 phosphatase complex play essential roles in preventing hyperactivation of the DNA damage-response kinase Rad53 in response to spontaneous DNA damage caused by reactive oxygen species. Overall, our data support the concept that chromosome-wide histone deacetylation by sirtuins is critical to mitigate growth defects caused by endogenous genotoxins.

Recent estimates suggest that >300 million people are afflicted by serious fungal infections worldwide. Current antifungal drugs are static and toxic and/or have a narrow spectrum of activity. Thus, there is an urgent need for the development of new antifungal drugs. The fungal sphingolipid glucosylceramide (GlcCer) is critical in promoting virulence of a variety of human-pathogenic fungi. In this study, we screened a synthetic drug library for compounds that target the synthesis of fungal, but not mammalian, GlcCer and found two compounds [ N ′-(3-bromo-4-hydroxybenzylidene)-2-methylbenzohydrazide (BHBM) and its derivative, 3-bromo- N ′-(3-bromo-4-hydroxybenzylidene) benzohydrazide (D0)] that were highly effective in vitro and in vivo against several pathogenic fungi. BHBM and D0 were well tolerated in animals and are highly synergistic or additive to current antifungals. BHBM and D0 significantly affected fungal cell morphology and resulted in the accumulation of intracellular vesicles. Deep-sequencing analysis of drug-resistant mutants revealed that four protein products, encoded by genes APL5 , COS111 , MKK1 , and STE2 , which are involved in vesicular transport and cell cycle progression, are targeted by BHBM. IMPORTANCE Fungal infections are a significant cause of morbidity and mortality worldwide. Current antifungal drugs suffer from various drawbacks, including toxicity, drug resistance, and narrow spectrum of activity. In this study, we have demonstrated that pharmaceutical inhibition of fungal glucosylceramide presents a new opportunity to treat cryptococcosis and various other fungal infections. In addition to being effective against pathogenic fungi, the compounds discovered in this study were well tolerated by animals and additive to current antifungals. These findings suggest that these drugs might pave the way for the development of a new class of antifungals.

The emergence and prevalence of drug resistance demands streamlined strategies to identify drug resistant variants in a fast, systematic and cost-effective way. Methods commonly used to understand and predict drug resistance rely on limited clinical studies from patients who are refractory to drugs or on laborious evolution experiments with poor coverage of the gene variants. Here, we report an integrative functional variomics methodology combining deep sequencing and a Bayesian statistical model to provide a comprehensive list of drug resistance alleles from complex variant populations. Dihydrofolate reductase, the target of methotrexate chemotherapy drug, was used as a model to identify functional mutant alleles correlated with methotrexate resistance. This systematic approach identified previously reported resistance mutations, as well as novel point mutations that were validated in vivo. Use of this systematic strategy as a routine diagnostics tool widens the scope of successful drug research and development., Author Summary One of the most profound outcomes of fast, reliable genome sequencing is the ability to tailor drug therapy to an individual’s genotype. This ‘personalized’ or ‘precision medicine’ is the realization of a decades-long effort to maximize drug effect and limit unwanted side effects. An undesirable consequence of such targeted therapies, however, is the emergence of drug resistance. This outcome is the result of an evolutionary process where mutations in the drug target render the drug perturbation allow such mutant cells to proliferate. Because of the unbiased, and stochastic nature of the emergence of drug resistance, it is impossible to predict. We developed a test where hundreds of thousands of mutant cells are exposed to a drug simultaneously and those cells that modulate resistance survive. This method is innovative because it partners a high-throughput experimental protocol with a tailored statistical model to identify all mutations that modulate resistance. Finally, we used synthetic biology to re-create these mutations and demonstrate that they were, in fact, bona fide drug-resistant variants. These mutations were further extended and confirmed to also be resistant in the human orthologue. This combined biological-computational approach allows one to identify drug’s degree of resistance to both guide treatments and future drug discovery.

The ability to measure and quantify the fitness of an entire organism requires considerably more complex approaches than simply using traditional “omic” methods that examine, for example, the abundance of RNA transcripts, proteins, or metabolites. The yeast deletion collections represent the only systematic, comprehensive set of null alleles for any organism in which such fitness measurements can be assayed. Generated by the Saccharomyces Genome Deletion Project, these collections allow the systematic and parallel analysis of gene functions using any measurable phenotype. The unique 20-bp molecular barcodes engineered into the genome of each deletion strain facilitate the massively parallel analysis of individual fitness. Here, we present functional genomic protocols for use with the yeast deletion collections. We describe how to maintain, propagate, and store the deletion collections and how to perform growth fitness assays on single and parallel screening platforms. Phenotypic fitness analyses of the yeast mutants, described in brief here, provide important insights into biological functions, mechanisms of drug action, and response to environmental stresses. It is important to bear in mind that the specific assays described in this protocol represent some of the many ways in which these collections can be assayed, and in this description particular attention is paid to maximizing throughput using growth as the phenotypic measure.