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Expressomal Approach for Comprehensive Analysis and Visualization of Ligand Sensitivities of Xenoestrogen Responsive Genes

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Expressomal Approach for Comprehensive Analysis and Visualization of Ligand Sensitivities of Xenoestrogen Responsive Genes Expressomal approach for comprehensive analysis and visualization of ligand sensitivities of xenoestrogen responsive genes Toshi Shiodaa,b,1, Noël F. Rosenthala, Kathryn R. Cosera, Mizuki Sutoa, Mukta Phatakc, Mario Medvedovicc, Vincent J. Careyb,d, and Kurt J. Isselbachera,b,1 aMolecular Profiling Laboratory, Massachusetts General Hospital Center for Cancer Research, Charlestown, MA 02129; bDepartment of Medicine, Harvard Medical School, Boston, MA 02115; cLaboratory for Statistical Genomics and Systems Biology, Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH 45267; and dChanning Laboratory, Brigham and Women’s Hospital, Boston, MA 02115 Contributed by Kurt J. Isselbacher, August 26, 2013 (sent for review June 17, 2013) Although biological effects of endocrine disrupting chemicals Evidence is accumulating that the EDCs may cause significant (EDCs) are often observed at unexpectedly low doses with occa- biological effects in humans or animals at doses far lower than sional nonmonotonic dose–response characteristics, transcriptome- the exposure limits set by regulatory agencies (8, 9). In addition wide profiles of sensitivities or dose-dependent behaviors of the to such low-dose effects, an increasing number of studies also EDC responsive genes have remained unexplored. Here, we describe support the concept of the nonmonotonic EDC effects, whose dose–response curves show U shapes or inverted-U shapes (8- expressome analysis for the comprehensive examination of dose- – dependent gene responses and its applications to characterize es- 10). However, whereas nonmonotonic dose responses are often observed in the endocrine system, this notion conflicts with one trogen responsive genes in MCF-7 cells. Transcriptomes of MCF-7 – cells exposed to varying concentrations of representative natural of the Bradford Hill criteria for cause-and-effect relationships that requires stronger effects with greater degrees of exposure and xenobiotic estrogens for 48 h were determined by microarray (11), leading to controversies when biological effects are ob- and used for computational calculation of interpolated approxima- served most strongly with lower rather than higher doses of tions of estimated transcriptomes for 300 doses uniformly distrib- EDCs (12-14). On the other hand, when an EDC does not show uted in log space for each chemical. The entire collection of these significant biological effects at a high dose, that chemical is estimated transcriptomes, designated as the expressome, has pro- generally assumed safe at lower doses, and possible nonmonotonic vided unique opportunities to profile chemical-specific distributions dose–response characteristics are seldom appreciated in risk as- of ligand sensitivities for large numbers of estrogen responsive sessment. Thus, as the standard toxicological approaches com- genes, revealing that at low concentrations estrogens generally monly adopted by the industry and regulatory apparatus do not tended to suppress rather than to activate transcription. Gene on- presently assume the low-dose–specific toxicity or nonmonotonic tology analysis demonstrated distinct functional enrichment between dose–response relationship, it is urgently desired to establish high- and low-sensitivity estrogen responsive genes, supporting the solid scientific frameworks for proper handling of data possibly notion that a single EDC chemical can cause qualitatively distinct demonstrating the nonstandard dose-dependent effects. Because biological responses at different doses. Expressomal heatmap vi- most published studies on the EDC effects involve limited num- sualization of dose-dependent induction of Bisphenol A inducible bers of doses for each chemical species, research on mechanisms genes showed a weak gene activation peak at a very low concen- tration range (ca. 0.1 nM) in addition to the main, strong gene Significance activation peak at and above 100 nM. Thus, expressome analysis is a powerful approach to understanding the EDC dose-dependent Cells change their mRNA expression in response to biologically dynamic changes in gene expression at the transcriptomal level, active substances in a dose-dependent manner. Because dif- fi providing important information on the overall pro les of ligand ferent genes in a cell show distinct sensitivities to the same sensitivities and nonmonotonic responses. substance, changes in the genome-wide mRNA expression profile induced by low and high doses of a substance are es- he endocrine disrupting chemicals (EDCs) are environmen- sentially different, but this notion has been commonly over- Ttal pollutants that interfere with the endocrine system to looked in previously published studies. Using a human cell disturb biological processes such as development, reproduction, culture model and microarray, we performed genome-wide and metabolism (1-4). EDCs consist of a wide variety of man- determinations of gene sensitivities to hormonally active sub- made and natural compounds with highly diversified chemical stances with statistically rigorous approaches. Our study pro- structures (4). Some EDCs are agonistic ligands that directly vides a conceptual and methodological framework for the bind to hormone receptors, whereas others inhibit receptor systematic examination of gene sensitivities and demonstrates effective detection of nonmonotonic dose-dependent responses, functions as antagonists. For example, xenoestrogens such as introducing the importance of gene sensitivity analysis to phar- Bisphenol A (BPA) (1) and genistein (5) are EDCs that activate macogenomic and toxicogenomic research. estrogen receptors by direct binding. Tributyltin is an obesogenic EDC that binds to peroxisome proliferation-activated receptor γ Author contributions: T.S. and K.J.I. designed research; T.S., N.F.R., and K.R.C. performed (PPAR-γ) to activate the retinoid X receptor (RXR)–PPAR research; T.S., M.S., and V.J.C. contributed new reagents/analytic tools; T.S., M.P., M.M., and heterodimer nuclear receptor complex, enhancing adipo- V.J.C. analyzed data; and T.S. and K.J.I. wrote the paper. genesis (6). Some other EDCs more indirectly disrupt the en- The authors declare no conflict of interest. docrine system by affecting hormone synthesis, metabolism, Freely available online through the PNAS open access option. sensitivity, or the negative feedback system (4). For example, Data deposition: The data reported in this paper have been deposited in the Gene Ex- pression Omnibus (GEO) database, www.ncbi.nlm.nih.gov/geo (accession no. GSE50705). thyroid hormone EDCs such as polychlorinated biphenyl con- 1To whom correspondence may be addressed. E-mail: [email protected] or geners reduce the circulating thyroid hormone levels, and some [email protected]. of them may also bind to the thyroid hormone receptors as This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. functional ligands (7). 1073/pnas.1315929110/-/DCSupplemental. 16508–16513 | PNAS | October 8, 2013 | vol. 110 | no. 41 www.pnas.org/cgi/doi/10.1073/pnas.1315929110 Downloaded by guest on October 1, 2021 of the low-dose and nonmonotonic actions is still in its infancy 120 (15, 16). Obviously, the lack of widely applicable standard approaches to study the low-dose and nonmonotonic EDC 100 effects on gene expression is a critical obstacle to understanding the mechanisms of the genetic and genomic actions of EDCs. 80 Our present study attempts to introduce frameworks for comprehensive analyses and data visualization of the EDC dose- 60 Strong estrogens dependent transcriptomal dynamism and its possible non- monotonic characteristics. We describe the expressome as a li- 40 17-estradiol brary of interpolated approximations of transcriptomal profiles diethylstilbestrol ethynylestradiol for hundreds of doses uniformly distributed in the log space 20 within the range of doses for which the seed transcriptomes are experimentally determined (ACR, analyzed concentration range). Relative cell number (%) 0 Our expressome analysis of representative xenoestrogens has de- 120 termined transcriptome-wide profiles of ligand sensitivities of es- Medium strength trogen responsive genes in MCF-7 cells and provided visualization 100 estrogens of the nonmonotonic aspects of the transcriptomal effects of BPA inducible genes. We propose that expressome analysis is a pow- 80 Bisphenol A erful approach for the comprehensive and statistically rigorous p-nonylphenol examination of the dose-dependent dynamic aspects of tran- 60 scriptomal responses to EDCs. 40 Results Generation of Computational Models of Dose-Dependent Transcriptomal 20 Responses to Natural and Xenobiotic Estrogens. As an initial step to Relative cell number (%) 0 characterize estrogen dose-dependent responses of animal cells, 120 we classified estrogens into three groups by their strength to Weak estrogens support proliferation of the estrogen-dependent MCF-7 cells 100 (Fig. 1). The strong estrogens that supported MCF-7 cell pro- daidzein β liferation at subnanomolar concentrations included 17 -estradiol 80 genistein (E2), diethylstilbestrol (DES) (17), and 17α-ethynylestradiol (EE2) (18). Estrogens with intermediate strength supported MCF-7 cell 60 proliferation at 1–100 nM and included two representative in- dustrial chemicals BPA and p-nonylphenol (PNP) (1, 19). The 40 isoflavone phytoestrogens genistein and daidzein, which require metabolic activation for their full-strength estrogenic actions 20 (20), were weak estrogens that supported
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