Marinella Gebbia

Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map

Defining the functional relationships between proteins is critical for understanding virtually all aspects of cell biology. Large-scale identification of protein complexes has provided one important step towards this goal; however, even knowledge of the stoichiometry, affinity and lifetime of every protein–protein interaction would not reveal the functional relationships between and within such complexes. Genetic interactions can provide functional information that is largely invisible to protein–protein interaction data sets. Here we present an epistatic miniarray profile (E-MAP) consisting of quantitative pairwise measurements of the genetic interactions between 743 Saccharomyces cerevisiae genes involved in various aspects of chromosome biology (including DNA replication/repair, chromatid segregation and transcriptional regulation). This E-MAP reveals that physical interactions fall into two well-represented classes distinguished by whether or not the individual proteins act coherently to carry out a common function. Thus, genetic interaction data make it possible to dissect functionally multi-protein complexes, including Mediator, and to organize distinct protein complexes into pathways. In one pathway defined here, we show that Rtt109 is the founding member of a novel class of histone acetyltransferases responsible for Asf1-dependent acetylation of histone H3 on lysine 56. This modification, in turn, enables a ubiquitin ligase complex containing the cullin Rtt101 to ensure genomic integrity during DNA replication.

A Library of Yeast Transcription Factor Motifs Reveals a Widespread Function for Rsc3 in Targeting Nucleosome Exclusion at Promoters

The sequence specificity of DNA-binding proteins is the primary mechanism by which the cell recognizes genomic features. Here, we describe systematic determination of yeast transcription factor DNA-binding specificities. We obtained binding specificities for 112 DNA-binding proteins representing 19 distinct structural classes. One-third of the binding specificities have not been previously reported. Several binding sequences have striking genomic distributions relative to transcription start sites, supporting their biological relevance and suggesting a role in promoter architecture. Among these are Rsc3 binding sequences, containing the core CGCG, which are found preferentially approximately 100 bp upstream of transcription start sites. Mutation of RSC3 results in a dramatic increase in nucleosome occupancy in hundreds of proximal promoters containing a Rsc3 binding element, but has little impact on promoters lacking Rsc3 binding sequences, indicating that Rsc3 plays a broad role in targeting nucleosome exclusion at yeast promoters.

INHIBITION OF MITOCHONDRIAL TRANSLATION AS A THERAPEUTIC STRATEGY FOR HUMAN ACUTE MYELOID LEUKEMIA

To identify FDA-approved agents targeting leukemic cells, we performed a chemical screen on two human leukemic cell lines and identified the antimicrobial tigecycline. A genome-wide screen in yeast identified mitochondrial translation inhibition as the mechanism of tigecycline-mediated lethality. Tigecycline selectively killed leukemia stem and progenitor cells compared to their normal counterparts and also showed antileukemic activity in mouse models of human leukemia. ShRNA-mediated knockdown of EF-Tu mitochondrial translation factor in leukemic cells reproduced the antileukemia activity of tigecycline. These effects were derivative of mitochondrial biogenesis that, together with an increased basal oxygen consumption, proved to be enhanced in AML versus normal hematopoietic cells and were also important for their difference in tigecycline sensitivity.

PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs

BackgroundIdentification of protein interaction networks has received considerable attention in the post-genomic era. The currently available biochemical approaches used to detect protein-protein interactions are all time and labour intensive. Consequently there is a growing need for the development of computational tools that are capable of effectively identifying such interactions.ResultsHere we explain the development and implementation of a novel Protein-Protein Interaction Prediction Engine termed PIPE. This tool is capable of predicting protein-protein interactions for any target pair of the yeast Saccharomyces cerevisiae proteins from their primary structure and without the need for any additional information or predictions about the proteins. PIPE showed a sensitivity of 61% for detecting any yeast protein interaction with 89% specificity and an overall accuracy of 75%. This rate of success is comparable to those associated with the most commonly used biochemical techniques. Using PIPE, we identified a novel interaction between YGL227W (vid30) and YMR135C (gid8) yeast proteins. This lead us to the identification of a novel yeast complex that here we term vid30 complex (vid30c). The observed interaction was confirmed by tandem affinity purification (TAP tag), verifying the ability of PIPE to predict novel protein-protein interactions. We then used PIPE analysis to investigate the internal architecture of vid30c. It appeared from PIPE analysis that vid30c may consist of a core and a secondary component. Generation of yeast gene deletion strains combined with TAP tagging analysis indicated that the deletion of a member of the core component interfered with the formation of vid30c, however, deletion of a member of the secondary component had little effect (if any) on the formation of vid30c. Also, PIPE can be used to analyse yeast proteins for which TAP tagging fails, thereby allowing us to predict protein interactions that are not included in genome-wide yeast TAP tagging projects.ConclusionPIPE analysis can predict yeast protein-protein interactions. Also, PIPE analysis can be used to study the internal architecture of yeast protein complexes. The data also suggests that a finite set of short polypeptide signals seem to be responsible for the majority of the yeast protein-protein interactions.

Mapping the Cellular Response to Small Molecules Using Chemogenomic Fitness Signatures

Yeasty HIPHOP In order to identify how chemical compounds target genes and affect the physiology of the cell, tests of the perturbations that occur when treated with a range of pharmacological chemicals are required. By examining the haploinsufficiency profiling (HIP) and homozygous profiling (HOP) chemogenomic platforms, Lee et al. (p. 208) analyzed the response of yeast to thousands of different small molecules, with genetic, proteomic, and bioinformatic analyses. Over 300 compounds were identified that targeted 121 genes within 45 cellular response signature networks. These networks were used to extrapolate the likely effects of related chemicals, their impact upon genetic pathways, and to identify putative gene functions. Guilt by association helps identify the chemogenomic signatures of compounds targeting yeast genes. 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.

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.

Multiple Means to the Same End: The Genetic Basis of Acquired Stress Resistance in Yeast

In nature, stressful environments often occur in combination or close succession, and thus the ability to prepare for impending stress likely provides a significant fitness advantage. Organisms exposed to a mild dose of stress can become tolerant to what would otherwise be a lethal dose of subsequent stress; however, the mechanism of this acquired stress tolerance is poorly understood. To explore this, we exposed the yeast gene-deletion libraries, which interrogate all essential and non-essential genes, to successive stress treatments and identified genes necessary for acquiring subsequent stress resistance. Cells were exposed to one of three different mild stress pretreatments (salt, DTT, or heat shock) and then challenged with a severe dose of hydrogen peroxide (H2O2). Surprisingly, there was little overlap in the genes required for acquisition of H2O2 tolerance after different mild-stress pretreatments, revealing distinct mechanisms of surviving H2O2 in each case. Integrative network analysis of these results with respect to protein–protein interactions, synthetic–genetic interactions, and functional annotations identified many processes not previously linked to H2O2 tolerance. We tested and present several models that explain the lack of overlap in genes required for H2O2 tolerance after each of the three pretreatments. Together, this work shows that acquired tolerance to the same severe stress occurs by different mechanisms depending on prior cellular experiences, underscoring the context-dependent nature of stress tolerance.

A Compendium of Nucleosome and Transcript Profiles Reveals Determinants of Chromatin Architecture and Transcription

Nucleosomes in all eukaryotes examined to date adopt a characteristic architecture within genes and play fundamental roles in regulating transcription, yet the identity and precise roles of many of the trans-acting factors responsible for the establishment and maintenance of this organization remain to be identified. We profiled a compendium of 50 yeast strains carrying conditional alleles or complete deletions of genes involved in transcriptional regulation, histone biology, and chromatin remodeling, as well as compounds that target transcription and histone deacetylases, to assess their respective roles in nucleosome positioning and transcription. We find that nucleosome patterning in genes is affected by many factors, including the CAF-1 complex, Spt10, and Spt21, in addition to previously reported remodeler ATPases and histone chaperones. Disruption of these factors or reductions in histone levels led genic nucleosomes to assume positions more consistent with their intrinsic sequence preferences, with pronounced and specific shifts of the +1 nucleosome relative to the transcription start site. These shifts of +1 nucleosomes appear to have functional consequences, as several affected genes in Ino80 mutants exhibited altered expression responses. Our parallel expression profiling compendium revealed extensive transcription changes in intergenic and antisense regions, most of which occur in regions with altered nucleosome occupancy and positioning. We show that the nucleosome-excluding transcription factors Reb1, Abf1, Tbf1, and Rsc3 suppress cryptic transcripts at their target promoters, while a combined analysis of nucleosome and expression profiles identified 36 novel transcripts that are normally repressed by Tup1/Cyc8. Our data confirm and extend the roles of chromatin remodelers and chaperones as major determinants of genic nucleosome positioning, and these data provide a valuable resource for future studies.

Mitochondrial Electron Transport Is the Cellular Target of the Oncology Drug Elesclomol

Elesclomol is a first-in-class investigational drug currently undergoing clinical evaluation as a novel cancer therapeutic. The potent antitumor activity of the compound results from the elevation of reactive oxygen species (ROS) and oxidative stress to levels incompatible with cellular survival. However, the molecular target(s) and mechanism by which elesclomol generates ROS and subsequent cell death were previously undefined. The cellular cytotoxicity of elesclomol in the yeast S. cerevisiae appears to occur by a mechanism similar, if not identical, to that in cancer cells. Accordingly, here we used a powerful and validated technology only available in yeast that provides critical insights into the mechanism of action, targets and processes that are disrupted by drug treatment. Using this approach we show that elesclomol does not work through a specific cellular protein target. Instead, it targets a biologically coherent set of processes occurring in the mitochondrion. Specifically, the results indicate that elesclomol, driven by its redox chemistry, interacts with the electron transport chain (ETC) to generate high levels of ROS within the organelle and consequently cell death. Additional experiments in melanoma cells involving drug treatments or cells lacking ETC function confirm that the drug works similarly in human cancer cells. This deeper understanding of elesclomols mode of action has important implications for the therapeutic application of the drug, including providing a rationale for biomarker-based stratification of patients likely to respond in the clinical setting.

Lysosomal disruption preferentially targets acute myeloid leukemia cells and progenitors

Despite efforts to understand and treat acute myeloid leukemia (AML), there remains a need for more comprehensive therapies to prevent AML-associated relapses. To identify new therapeutic strategies for AML, we screened a library of on- and off-patent drugs and identified the antimalarial agent mefloquine as a compound that selectively kills AML cells and AML stem cells in a panel of leukemia cell lines and in mice. Using a yeast genome-wide functional screen for mefloquine sensitizers, we identified genes associated with the yeast vacuole, the homolog of the mammalian lysosome. Consistent with this, we determined that mefloquine disrupts lysosomes, directly permeabilizes the lysosome membrane, and releases cathepsins into the cytosol. Knockdown of the lysosomal membrane proteins LAMP1 and LAMP2 resulted in decreased cell viability, as did treatment of AML cells with known lysosome disrupters. Highlighting a potential therapeutic rationale for this strategy, leukemic cells had significantly larger lysosomes compared with normal cells, and leukemia-initiating cells overexpressed lysosomal biogenesis genes. These results demonstrate that lysosomal disruption preferentially targets AML cells and AML progenitor cells, providing a rationale for testing lysosomal disruption as a novel therapeutic strategy for AML.