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      Characterization of drug-induced transcriptional modules: towards drug repositioning and functional understanding

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          Abstract

          • Biclustering of drug-induced gene expression profiles resulted in modules of drugs and genes, which were enriched in both drug and gene annotations.

          • Identifying drug-induced transcriptional modules separately in three human cell lines and rat liver allows assessment of their conservation across model systems. About 70% of modules are conserved across cell lines, a lower bound of 15% was estimated for their conservation across organisms, and between the in vitro and in vivo systems.

          • Drug-induced transcriptional modules can predict novel gene functions. A conserved module associated with (chole)sterol metabolism revealed novel regulators of cellular cholesterol homeostasis; 10 of them were validated in functional imaging assays.

          • Analysis of drugs clustered into modules can give new insights into their mechanisms of action and provide leads for drug repositioning. We predicted and experimentally validated novel cell cycle inhibitors and modulators of PPARγ, estrogen and adrenergic receptors, with potential for developing new therapies against diabetes and cancer.

          Abstract

          In pharmacology, it is crucial to understand the complex biological responses that drugs elicit in the human organism and how well they can be inferred from model organisms. We therefore identified a large set of drug-induced transcriptional modules from genome-wide microarray data of drug-treated human cell lines and rat liver, and first characterized their conservation. Over 70% of these modules were common for multiple cell lines and 15% were conserved between the human in vitro and the rat in vivo system. We then illustrate the utility of conserved and cell-type-specific drug-induced modules by predicting and experimentally validating (i) gene functions, e.g., 10 novel regulators of cellular cholesterol homeostasis and (ii) new mechanisms of action for existing drugs, thereby providing a starting point for drug repositioning, e.g., novel cell cycle inhibitors and new modulators of α-adrenergic receptor, peroxisome proliferator-activated receptor and estrogen receptor. Taken together, the identified modules reveal the conservation of transcriptional responses towards drugs across cell types and organisms, and improve our understanding of both the molecular basis of drug action and human biology.

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          Most cited references51

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          A gene-coexpression network for global discovery of conserved genetic modules.

          To elucidate gene function on a global scale, we identified pairs of genes that are coexpressed over 3182 DNA microarrays from humans, flies, worms, and yeast. We found 22,163 such coexpression relationships, each of which has been conserved across evolution. This conservation implies that the coexpression of these gene pairs confers a selective advantage and therefore that these genes are functionally related. Many of these relationships provide strong evidence for the involvement of new genes in core biological functions such as the cell cycle, secretion, and protein expression. We experimentally confirmed the predictions implied by some of these links and identified cell proliferation functions for several genes. By assembling these links into a gene-coexpression network, we found several components that were animal-specific as well as interrelationships between newly evolved and ancient modules.
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            The evolution of gene expression levels in mammalian organs.

            Changes in gene expression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of gene expression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of gene expression evolution varies among organs, lineages and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although gene expression evolution in mammals was strongly shaped by purifying selection, we identify numerous potentially selectively driven expression switches, which occurred at different rates across lineages and tissues and which probably contributed to the specific organ biology of various mammals.
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              Functional discovery via a compendium of expression profiles.

              Ascertaining the impact of uncharacterized perturbations on the cell is a fundamental problem in biology. Here, we describe how a single assay can be used to monitor hundreds of different cellular functions simultaneously. We constructed a reference database or "compendium" of expression profiles corresponding to 300 diverse mutations and chemical treatments in S. cerevisiae, and we show that the cellular pathways affected can be determined by pattern matching, even among very subtle profiles. The utility of this approach is validated by examining profiles caused by deletions of uncharacterized genes: we identify and experimentally confirm that eight uncharacterized open reading frames encode proteins required for sterol metabolism, cell wall function, mitochondrial respiration, or protein synthesis. We also show that the compendium can be used to characterize pharmacological perturbations by identifying a novel target of the commonly used drug dyclonine.
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                Author and article information

                Journal
                Mol Syst Biol
                Mol. Syst. Biol
                Molecular Systems Biology
                Nature Publishing Group
                1744-4292
                2013
                30 April 2013
                30 April 2013
                : 9
                : 662
                Affiliations
                [1 ]Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL) , Heidelberg, Germany
                [2 ]Cell Biology/Biophysics Unit, EMBL , Heidelberg, Germany
                [3 ]Molecular Medicine Partnership Unit (MMPU), EMBL, University of Heidelberg , Heidelberg, Germany
                [4 ]Institute for Bioinformatics and Systems Biology, Helmholtz Center Munich–German Research Center for Environmental Health (GmbH) , Neuherberg, Germany
                [5 ]German Center for Diabetes Research (DZD) , Neuherberg, Germany
                [6 ]Biotechnology Center, TU Dresden , Dresden, Germany
                [7 ]Institute of Human Genetics, University of Heidelberg , Heidelberg, Germany
                [8 ]Max-Delbrück-Centre for Molecular Medicine , Berlin, Germany
                Author notes
                [a ]Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL) , Meyerhofstrasse 1, Heidelberg, Germany. Tel.:+49 6221 387 8526; Fax:+49 6221 387 8517; bork@ 123456embl.de
                [*]

                Present address: International Institute of Molecular and Cell Biology in Warsaw, ul. Ks. Trojdena 4, 02-109 Warsaw, Poland

                Article
                msb201320
                10.1038/msb.2013.20
                3658274
                23632384
                b5fcc375-8be8-48cd-9ff8-cbf9c218d8be
                Copyright © 2013, EMBO and Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit

                History
                : 21 January 2013
                : 28 March 2013
                Categories
                Article

                Quantitative & Systems biology
                cell line models in drug discovery,drug-induced transcriptional modules,drug repositioning,gene function prediction,transcriptome conservation across cell types and organisms

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