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      Chemical and Hormonal Effects on STAT5b-Dependent Sexual Dimorphism of the Liver Transcriptome

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      PLoS ONE
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          Abstract

          The growth hormone (GH)-activated transcription factor signal transducer and activator of transcription 5b (STAT5b) is a key regulator of sexually dimorphic gene expression in the liver. Suppression of hepatic STAT5b signaling is associated with lipid metabolic dysfunction leading to steatosis and liver cancer. In the companion publication, a STAT5b biomarker gene set was identified and used in a rank-based test to predict both increases and decreases in liver STAT5b activation status/function with high (≥ 97%) accuracy. Here, this computational approach was used to identify chemicals and hormones that activate (masculinize) or suppress (feminize) STAT5b function in a large, annotated mouse liver and primary hepatocyte gene expression compendium. Exposure to dihydrotestosterone and thyroid hormone caused liver masculinization, whereas glucocorticoids, fibroblast growth factor 15, and angiotensin II caused liver feminization. In mouse models of diabetes and obesity, liver feminization was consistently observed and was at least partially reversed by leptin or resveratrol exposure. Chemical-induced feminization of male mouse liver gene expression profiles was a relatively frequent phenomenon: of 156 gene expression biosets from chemically-treated male mice, 29% showed feminization of liver STAT5b function, while <1% showed masculinization. Most (93%) of the biosets that exhibited feminization of male liver were also associated with activation of one or more xenobiotic-responsive receptors, most commonly constitutive activated receptor (CAR) or peroxisome proliferator-activated receptor alpha (PPARα). Feminization was consistently associated with increased expression of peroxisome proliferator-activated receptor gamma ( Pparg) but not other lipogenic transcription factors linked to steatosis. GH-activated STAT5b signaling in mouse liver is thus commonly altered by diverse chemicals, and provides a linkage between chemical exposure and dysregulated gene expression associated with adverse effects on the liver.

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          Adverse outcome pathways: a conceptual framework to support ecotoxicology research and risk assessment.

          Ecological risk assessors face increasing demands to assess more chemicals, with greater speed and accuracy, and to do so using fewer resources and experimental animals. New approaches in biological and computational sciences may be able to generate mechanistic information that could help in meeting these challenges. However, to use mechanistic data to support chemical assessments, there is a need for effective translation of this information into endpoints meaningful to ecological risk-effects on survival, development, and reproduction in individual organisms and, by extension, impacts on populations. Here we discuss a framework designed for this purpose, the adverse outcome pathway (AOP). An AOP is a conceptual construct that portrays existing knowledge concerning the linkage between a direct molecular initiating event and an adverse outcome at a biological level of organization relevant to risk assessment. The practical utility of AOPs for ecological risk assessment of chemicals is illustrated using five case examples. The examples demonstrate how the AOP concept can focus toxicity testing in terms of species and endpoint selection, enhance across-chemical extrapolation, and support prediction of mixture effects. The examples also show how AOPs facilitate use of molecular or biochemical endpoints (sometimes referred to as biomarkers) for forecasting chemical impacts on individuals and populations. In the concluding sections of the paper, we discuss how AOPs can help to guide research that supports chemical risk assessments and advocate for the incorporation of this approach into a broader systems biology framework.
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            Simpleaffy: a BioConductor package for Affymetrix Quality Control and data analysis.

            Quality Control is a fundamental aspect of successful microarray data analysis. Simpleaffy is a BioConductor package that provides access to a variety of QC metrics for assessing the quality of RNA samples and of the intermediate stages of sample preparation and hybridization. Simpleaffy also offers fast implementations of popular algorithms for generating expression summaries and detection calls. Simpleaffy can be downloaded from http://www.bioconductor.org. Additional information can be found on the supplementary website located at http://bioinformatics.picr.man.ac.uk.
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              FGF19 as a postprandial, insulin-independent activator of hepatic protein and glycogen synthesis.

              Fibroblast growth factor (FGF) 19 is an enterokine synthesized and released when bile acids are taken up into the ileum. We show that FGF19 stimulates hepatic protein and glycogen synthesis but does not induce lipogenesis. The effects of FGF19 are independent of the activity of either insulin or the protein kinase Akt and, instead, are mediated through a mitogen-activated protein kinase signaling pathway that activates components of the protein translation machinery and stimulates glycogen synthase activity. Mice lacking FGF15 (the mouse FGF19 ortholog) fail to properly maintain blood concentrations of glucose and normal postprandial amounts of liver glycogen. FGF19 treatment restored the loss of glycogen in diabetic animals lacking insulin. Thus, FGF19 activates a physiologically important, insulin-independent endocrine pathway that regulates hepatic protein and glycogen metabolism.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                9 March 2016
                2016
                : 11
                : 3
                : e0150284
                Affiliations
                [1 ]Integrated Systems Toxicology Division, National Health and Environmental Effects Research Laboratory/ Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America
                [2 ]Division of Cell and Molecular Biology, Department of Biology and Bioinformatics Program, Boston University, Boston, MA 02215, United States of America
                University of Nebraska Medical Center, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: JCC KO. Performed the experiments: JCC KO. Wrote the paper: JCC KO DJW.

                [¤]

                Current address: Toray Industries, Inc., Kanagawa, Japan

                Article
                PONE-D-15-27911
                10.1371/journal.pone.0150284
                4784907
                26959237
                c16bdc38-9722-4254-bc26-fa1350a51552

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 26 June 2015
                : 11 February 2016
                Page count
                Figures: 7, Tables: 0, Pages: 24
                Funding
                The information in this document has been funded in part by the U.S. Environmental Protection Agency, and by National Institutes of Health (NIH) grants ES024421 and DK33765 (to DJW).
                Categories
                Research Article
                Medicine and Health Sciences
                Gastroenterology and Hepatology
                Liver Diseases
                Fatty Liver
                Biology and Life Sciences
                Biochemistry
                Biomarkers
                Biology and Life Sciences
                Genetics
                Gene Expression
                Biology and Life Sciences
                Nutrition
                Diet
                Medicine and Health Sciences
                Nutrition
                Diet
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Anatomical Pathology
                Cytopathology
                Steatosis
                Biology and Life Sciences
                Biochemistry
                Hormones
                Peptide Hormones
                Leptin
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                Medicine and Health Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                Biology and Life Sciences
                Biochemistry
                Hormones
                Custom metadata
                All relevant data are within the paper and its Supporting Information files. Microarray data was from Gene Expression Omnibus (GEO) or ArrayExpress. The specific GEO or ArrayExpress numbers are as indicated throughout the manuscript.

                Uncategorized
                Uncategorized

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