PROPHECY—a database for high-resolution phenomics

The rapid recent evolution of the field phenomics—the genome-wide study of gene dispensability by quantitative analysis of phenotypes—has resulted in an increasing demand for new data analysis and visualization tools. Following the introduction of a novel approach for precise, genome-wide quantification of gene dispensability in Saccharomyces cerevisiae we here announce a public resource for mining, filtering and visualizing phenotypic data—the PROPHECY database. PROPHECY is designed to allow easy and flexible access to physiologically relevant quantitative data for the growth behaviour of mutant strains in the yeast deletion collection during conditions of environmental challenges. PROPHECY is publicly accessible at http://prophecy.lundberg.gu.se

Systematic analysis of genome-wide fitness data in yeast reveals novel gene function and drug action

The relationship between co-fitness and co-inhibition of genes in chemicogenomic yeast screens provides insights into gene function and drug target prediction

PROPHECY—a yeast phenome database, update 2006

Connecting genotype to phenotype is fundamental in biomedical research and in our understanding of disease. Phenomics—the large-scale quantitative phenotypic analysis of genotypes on a genome-wide scale—connects automated data generation with the development of novel tools for phenotype data integration, mining and visualization. Our yeast phenomics database PROPHECY is available at . Via phenotyping of 984 heterozygous diploids for all essential genes the genotypes analysed and presented in PROPHECY have been extended and now include all genes in the yeast genome. Further, phenotypic data from gene overexpression of 574 membrane spanning proteins has recently been included. To facilitate the interpretation of quantitative phenotypic data we have developed a new phenotype display option, the Comparative Growth Curve Display, where growth curve differences for a large number of mutants compared with the wild type are easily revealed. In addition, PROPHECY now offers a more informative and intuitive first-sight display of its phenotypic data via its new summary page. We have also extended the arsenal of data analysis tools to include dynamic visualization of phenotypes along individual chromosomes. PROPHECY is an initiative to enhance the growing field of phenome bioinformatics

Security: Collective good or commodity?

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2008 Sage.The state monopoly on the legitimate use of violence in Europe and North America has been central to the development of security as a collective good. Not only has it institutionalized the state as the prime national and international security provider, it has helped to reduce the threat from other actors by either prohibiting or limiting their use of violence. The recent growth of the private security industry appears to undermine this view. Not only are private security firms proliferating at the national level; private military companies are also taking over an increasing range of military functions in both national defence and international interventions. This article seeks to provide an examination of the theoretical and practical implications of the shift from states to markets in the provision of security. Specifically, it discusses how the conceptualization of security as a commodity rather than a collective good affects the meaning and implementation of security in Western democracies.ESR

A comprehensive platform for highly multiplexed mammalian functional genetic screens

<p>Abstract</p> <p>Background</p> <p>Genome-wide screening in human and mouse cells using RNA interference and open reading frame over-expression libraries is rapidly becoming a viable experimental approach for many research labs. There are a variety of gene expression modulation libraries commercially available, however, detailed and validated protocols as well as the reagents necessary for deconvolving genome-scale gene screens using these libraries are lacking. As a solution, we designed a comprehensive platform for highly multiplexed functional genetic screens in human, mouse and yeast cells using popular, commercially available gene modulation libraries. The Gene Modulation Array Platform (GMAP) is a single microarray-based detection solution for deconvolution of loss and gain-of-function pooled screens.</p> <p>Results</p> <p>Experiments with specially constructed lentiviral-based plasmid pools containing ~78,000 shRNAs demonstrated that the GMAP is capable of deconvolving genome-wide shRNA "dropout" screens. Further experiments with a larger, ~90,000 shRNA pool demonstrate that equivalent results are obtained from plasmid pools and from genomic DNA derived from lentivirus infected cells. Parallel testing of large shRNA pools using GMAP and next-generation sequencing methods revealed that the two methods provide valid and complementary approaches to deconvolution of genome-wide shRNA screens. Additional experiments demonstrated that GMAP is equivalent to similar microarray-based products when used for deconvolution of open reading frame over-expression screens.</p> <p>Conclusion</p> <p>Herein, we demonstrate four major applications for the GMAP resource, including deconvolution of pooled RNAi screens in cells with at least 90,000 distinct shRNAs. We also provide detailed methodologies for pooled shRNA screen readout using GMAP and compare next-generation sequencing to GMAP (i.e. microarray) based deconvolution methods.</p

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

Chemical–Genetic Profiling of Imidazo[1,2-a]pyridines and -Pyrimidines Reveals Target Pathways Conserved between Yeast and Human Cells

Small molecules have been shown to be potent and selective probes to understand cell physiology. Here, we show that imidazo[1,2-a]pyridines and imidazo[1,2-a]pyrimidines compose a class of compounds that target essential, conserved cellular processes. Using validated chemogenomic assays in Saccharomyces cerevisiae, we discovered that two closely related compounds, an imidazo[1,2-a]pyridine and -pyrimidine that differ by a single atom, have distinctly different mechanisms of action in vivo. 2-phenyl-3-nitroso-imidazo[1,2-a]pyridine was toxic to yeast strains with defects in electron transport and mitochondrial functions and caused mitochondrial fragmentation, suggesting that compound 13 acts by disrupting mitochondria. By contrast, 2-phenyl-3-nitroso-imidazo[1,2-a]pyrimidine acted as a DNA poison, causing damage to the nuclear DNA and inducing mutagenesis. We compared compound 15 to known chemotherapeutics and found resistance required intact DNA repair pathways. Thus, subtle changes in the structure of imidazo-pyridines and -pyrimidines dramatically alter both the intracellular targeting of these compounds and their effects in vivo. Of particular interest, these different modes of action were evident in experiments on human cells, suggesting that chemical–genetic profiles obtained in yeast are recapitulated in cultured cells, indicating that our observations in yeast can: (1) be leveraged to determine mechanism of action in mammalian cells and (2) suggest novel structure–activity relationships

Genetic pleiotropy in Saccharomyces cerevisiae quantified by high-resolution phenotypic profiling

Genetic pleiotropy, the ability of a mutation in a single gene to give rise to multiple phenotypic outcomes, constitutes an important but incompletely understood biological phenomenon. We used a highresolution and high-precision phenotypic profiling approach to quantify the fitness contribution of genes on the five smallest yeast chromosomes during different forms of environmental stress, selected to probe a wide diversity of physiological features. We found that the extent of pleiotropy is much higher than previously claimed; 17% of the yeast genes were pleiotropic whereof one-fifth were hyper-pleiotropic. Pleiotropic genes preferentially participate in functions related to determination of protein fate, cell growth and morphogenesis, signal transduction and transcription. Contrary to what has earlier been proposed we did not find experimental evidence for slower evolutionary rate of pleiotropic genes/proteins. We also refute the existence of phenotypic islands along chromosomes but report on a remarkable loss both of pleiotropy and of phenotypic penetrance towards chromosomal ends. Thus, the here reported features of pleiotropy both have implications on our understanding of evolutionary processes as well as the mechanisms underlying disease