RESEARCH IN

FOCUSTranslational Biological and Chemical Genomics

Dr. Guri Giaever Dr. Corey Nislow

ISSUE FIvE: MAY 2014

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THE guri giaEvEr and corEy nislow lab

Lab Members

Guri Nina Giaever, Principal Investigator Corey Nislow, Principal Investigator Sunita Sinha, Lab Manager Jennifer Chiang, Project Manager Mauricio Neira, Senior BioinformaticianMichael Proctor, Senior Engineer Amy Lee, Postdoctoral Fellow Elisa Wong, Postdoctoral Fellow Sean Formby, Graduate Student Mark Matthew, Graduate Student Adrianna Paiero, Co-op Student Grant Tran, Research Assistant Sarah Cheng, Undergraduate Student

inTroducTion

A fundamental goal in biology is to understand how genotype influences the cellular and organism response to perturbation. In particular, understanding the systems-level response to small molecules and drugs is fundamental to improving human health. Indeed, most drugs fail in late-stage clinical trials due to lack of efficacy, and this can often be attributed to our incomplete understanding of the in vivo mechanism of action (MOA). These failures also reflect the fact that compounds which exhibit high potency and selectivity in vitro often manifest additional mechanisms when placed in the context of all proteins in the cell. Because of the technical challenges of systematically monitoring a drug’s mechanism in vivo, the pharmaceutical industry focuses on druggable targets, i.e. those proteins whose perturbation have already demonstrated efficacy. The HIPHOP approach uses chemogenomics to understand drug mechanisms in a cellular context with the potential to identify novel druggable targets.

rEsEarcH suMMary

Using our well-validated HaploInsufficiency Profiling (HIP) and HOmozygous Profiling (HOP) chemogenomic platform, we are exploring

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the druggable genome and the genetic dependency of the cellular response to small molecules by systematically screening 10,000+ small molecules. The platform utilizes powerful yeast genomic tools including the yeast deletion collection, a complete set of strains that differ only in the deletion of a single gene.

HIP exploits drug-induced haploinsufficiency, a phenotype whereby a growth inhibitory small molecule or drug induces a specific fitness defect in a heterozygous strain deleted for one copy of the drug’s target. In the HIP assay, a drug target can be identified de novo in by measuring the drug sensitivity, or fitness defect, of ~1,100 barcoded heterozygous strains in parallel, each deleted for a single copy of an essential gene, using a microarray or next-generation sequencing readout. Strains with increased drug sensitivity can be used to identify drug target candidates while also providing a relative measure of specificity in a cellular context. Similarly, HOP interrogates ~4,800 homozygous deletion strains for relative drug sensitivity providing rich information on the nonessential genes required to buffer the drug target pathway including those involved in metabolism, export and other mechanisms of detoxification.

Combined, HIPHOP generates a comprehensive chemogenomic profile, relaying the genome-wide response to a drug by reporting all deletion strains that exhibit fitness defects, representing chemical-genetic interactions between the compounds screened and the deleted gene products, and enabling an unbiased prediction that the fraction of the essential genome that is druggable is nearly twice that of current estimates.

Recently we have expanded the breadth and depth of our efforts to include translational projects by:

1. Developing HIPHOP assays that reflect the tumour micro-environment by screening drugs in hypoxic conditions and in conditions that induce cancer-specific metabolic changes.

2. Expanding our screens to human pathogens, including Salmonella and Burkholderia.

3. Developing genome engineering tools to generate loss-of-function mutant collections in human cancer cells.

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These efforts involve diverse biological disciplines, including biotechnology, computational biology and medicinal chemistry. Accordingly, we have established collaborations with:

1. The Centre for Drug Research and Development – To act as the hub of their Next Generation Genomics Node.

2. Novartis Biomedical Research Institute – To develop mutant human cells for chemogenomics.

3. Dr. David Grierson, UBC Pharmaceutical Sciences – To screen and perform mechanistic studies on novel compounds.

4. Dr. Julian Davies, UBC Microbiology and Immunology – To perform environmental microbial genomics.

5. Dr. Aaron Schimmer, Princess Margaret Hospital, University of Toronto -- To perform mechanism of action studies in leukemia cell lines.

6. National Aeronautics and Space Administration (NASA)- to examine the roles of microgravity, hypoxia and high energy radiation on cancer cell proliferation in space

Funding for these efforts comes in part from the Canadian Cancer Scientific Research Institute, National Institutes of Health, US Department of Agriculture, NASA, Novartis and Astra Zeneca.

sElEcTEd ProJEcT

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

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major chemogenomic signatures. Our results provide a resource for the discovery of functional interactions among genes, chemicals, and biological processes.

See Lee et al. Science 11 April 2014 for detail.

Figure 1.

Fig. 1. The cellular response is defined by a network of chemogenomic response signatures. Each circular node represents a major gene-based biological signature; size is proportional to confidence in the signature). Node color: dark blue if GO enriched (hypergeometric test FDR ≤ 0.1), pale blue otherwise. Node border

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Fig. 2. Validation of chemical-genetic probes. (A) Fluconazole HIPHOP profile. Fitness defect (FD) scores plotted for each deletion strain. HIP (left) identifies the established drug target Erg11. HOP (right) identifies processes directly (e.g., sterol biosynthesis) and indirectly (e.g., iron ion homeostasis) related to ERG11 function. Significant FDs (standard normal distribution P ≤ 0.001) are labeled except those (blue) not covered by the highlighted processes; *, dubious gene overlapping labeled gene.

Figure 2

color: green, signature represents two or more compounds of known mechanism (select compound names are shown, and are in bold if they drive bioactivity class enrichment); red, signature represents chemical-genetic probes (select HIP hits are shown, and are in bold if validation data are provided). Signatures are connected to chemical moiety nodes where signature compounds are enriched (hypergeometric test FDR ≤ 0.1) for a specific fragment. Fragment substitution sites are represented by R (any atom), or X (halides, oxygen, nitrogen or sulfur). Boxes indicate signatures discussed in the text. ERAD, endoplasmic reticulum–associated degradation; RNA pol III, RNA polymerase III; ROS, reactive oxygen species; TOFA, 5-tetradecoxyfuran-2-carboxylic acid; TRP, tryptophan.

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Figure 2

(B) Cdc12 inhibitor. In a wound-healing assay, HeLa cells with dimethyl sulfoxide (DMSO), 1 ųM 3013-0144, and 5 ųM forchlorfenuron (FCF) were fixed and stained as described, with DNA stained blue and antibodies against the Golgi visualized via green fluorescence. DMSO-treated cells show the Golgi reoriented toward the wound edge (white line); in contrast, 3013-0144 inhibited Golgi reorientation as effectively as FCF (scale bar, 10 ųm). (C) Dose-dependent inhibition of the phosphatidylinositol (PtdIns) transfer activity of purified recombinant Sec14. Transfer of radiolabeled PtdIns as a percentage of the untreated control (y axis), measured in the presence of 9131112, 9097855, 9053361, and 9045654 (an inactive derivative) at the indicated concentrations (x axis). Data are mean ± SD (N= 3).

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rElEvanT PublicaTions

Lee AY, St Onge RP, Proctor MJ, Wallace IM, Nile AH, Spagnuolo PA, Jitkova Y, Gronda M, Wu Y, Kim MK, Cheung-Ong K, Torres NP, Spear ED, Han MK,Schlecht U, Suresh S, Duby G, Heisler LE, Surendra A, Fung E, Urbanus ML, Gebbia M, Lissina E, Miranda M, Chiang JH, Aparicio AM, Zeghouf M, Davis RW,Cherfils J, Boutry M, Kaiser CA, Cummins CL, Trimble WS, Brown GW, Schimmer AD, Bankaitis VA, Nislow C, Bader GD, Giaever G. Mapping the cellular response to small molecules using chemogenomic fitness signatures. Science. 2014 Apr 11;344(6180):208-11. doi: 10.1126/science.1250217. PubMed PMID: 24723613; PubMed Central PMCID: in process.

Kittanakom S, Arnoldo A, Brown KR, Wallace I, Kunavisarut T, Torti D, Heisler LE, Surendra A, Moffat J, Giaever G, Nislow C. Miniature short hairpin RNA screens to characterize antiproliferative drugs. G3 (Bethesda). 2013 Aug 7;3(8):1375-87. doi: 10.1534/g3.113.006437. PubMed PMID: 23797109; PubMed Central PMCID: PMC3737177.

Cheung-Ong K, Giaever G, Nislow C. DNA-damaging agents in cancer chemotherapy: serendipity and chemical biology. Chem Biol. 2013 May 23;20(5):648-59. doi: 10.1016/j.chembiol.2013.04.007. Review. PubMed PMID: 23706631.

Hillenmeyer ME, Fung E, Wildenhain J, Pierce SE, Hoon S, Lee W, Proctor M, St Onge RP, Tyers M, Koller D, Altman RB, Davis RW, Nislow C, Giaever G. The chemical genomic portrait of yeast: uncovering a phenotype for all genes. Science. 2008 Apr 18;320(5874):362-5. doi: 10.1126/science.1150021. PubMed PMID: 18420932; PubMed Central PMCID: PMC2794835.

Wallace IM, Urbanus ML, Luciani GM, Burns AR, Han MK, Wang H, Arora K, Heisler LE, Proctor M, St Onge RP, Roemer T, Roy PJ, Cummins CL, Bader GD, Nislow C, Giaever G. Compound prioritization methods increase rates of chemical probe discovery in model organisms. Chem Biol. 2011 Oct 28;18(10):1273-83. doi: 10.1016/j.chembiol.2011.07.018. PubMed PMID: 22035796.

Hoon S, Smith AM, Wallace IM, Suresh S, Miranda M, Fung E, Proctor M, Shokat KM, Zhang C, Davis RW, Giaever G, St Onge RP, Nislow C. An integrated platform of genomic assays reveals small-molecule bioactivities. Nat Chem Biol. 2008 Aug;4(8):498-506. doi: 10.1038/nchembio.100. Epub 2008 Jul 11. Erratum in: Nat Chem Biol.2008 Oct;4(10):632.. StOnge, Robert P [corrected to St Onge,Robert P]. PubMed PMID: 18622389.

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