DOCSLIB.ORG

Search for New Steroid Hormone Metabolizing Enzymes: Functional Genomics of the Short-Chain Dehydrogenase/Reductase Superfamily

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Search for New Steroid Hormone Metabolizing Enzymes: Functional Genomics of the Short-Chain Dehydrogenase/Reductase Superfamily Institut fur¨ Experimentelle Genetik GSF-Forschungszentrum fur¨ Umwelt und Gesundheit, Neuherberg Search for New Steroid Hormone Metabolizing Enzymes: Functional Genomics of the Short-Chain Dehydrogenase/Reductase Superfamily Brigitte D. Keller Vollst¨andiger Abdruck der von der Fakult¨at Wissenschaftszentrum Weihenstephan fur¨ Ern¨ahrung, Landnutzung und Umwelt der Technischen Universit¨at Munc¨ hen zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften genehmigten Dissertation. Vorsitzender: Univ.-Prof. Dr. Martin Hrab´e de Angelis Pruf¨ er der Dissertation: 1. Univ.-Prof. Dr. Johannes Buchner 2. Univ.-Prof. Dr. Dr. Adelbert Bacher 3. apl. Prof. Dr. Jerzy Adamski Die Dissertation wurde am 02.06.2006 bei der Technischen Universit¨at Mun¨ chen einge- reicht und durch die Fakult¨at Wissenschaftszentrum Weihenstephan fu¨r Ern¨ahrung, Land- nutzung und Umwelt am 18.10.2006 angenommen. Meinen Eltern Contents Abbreviations . xi Zusammenfassung . 1 Abstract . 3 1. Introduction 5 1.1. The Short-Chain Dehydrogenase/Reductase superfamily . 5 1.1.1. Structural characteristics of SDRs . 6 1.1.2. Enzymatic characteristics and substrates of SDRs . 7 1.1.3. Medical impact of SDR superfamily . 8 1.2. Hormones . 8 1.2.1. Steroid hormones . 10 1.2.2. Distribution and action of steroid hormones . 10 1.2.3. Classes of steroid hormones . 11 1.2.4. Biosynthesis of steroid hormones . 12 1.3. Steroid metabolizing enzymes: Biosynthesis and pre-receptor control of steroid action . 15 1.3.1. 20α-Hydroxysteroid dehydrogenases . 15 1.3.2. 3α-Hydroxysteroid dehydrogenases . 15 1.3.3. 3β-Hydroxysteroid dehydrogenases/isomerases . 15 1.3.4. 11β-Hydroxysteroid dehydrogenases 1 and 2 . 16 1.3.5. 17β-Hydroxysteroid dehydrogenases . 16 1.4. The aim of the study . 17 2. Results 19 2.1. Introducing remarks . 19 2.2. Identification of SDR candidate enzymes and classification as SDRs . 19 2.2.1. Identification of putative SDRs using SDR Finder . 19 2.2.2. Verification of the SDR Finder identified enzymes and classification as SDR enzymes . 23 2.2.3. Identification and verification of MGC4172 and MGC18716 . 24 2.2.4. Annotation of the identified SDR type enzymes to the genome . 24 2.3. Selection of identified SDRs for in-depth characterization . 28 v Contents 2.4. Expression patterns of candidate enzymes . 33 2.4.1. Development of an automated In Silico Northern Blot (ISNB) . 33 2.4.2. Expression analysis of the candidate genes in silico and wet lab . 35 2.4.3. Expression pattern of murine orphan Sdr (mSdr-o) . 37 2.4.4. Expression pattern of human retSDR3 . 38 2.4.5. Expression pattern of rat dhrs7b . 38 2.4.6. Expression pattern of rat dhrs8 . 39 2.4.7. Expression pattern of murine Rdh12 . 40 2.4.8. Expression pattern of human RDH12 . 41 2.4.9. Expression pattern of human RDH13 . 42 2.4.10. Expression pattern of murine Dhrs4 . 43 2.4.11. Expression pattern of human DHRSX . 43 2.4.12. Expression pattern of human WWOX . 44 2.4.13. Expression pattern of murine Wwox . 45 2.4.14. Expression pattern of human MGC4172 . 46 2.4.15. Expression pattern of murine MGC18716 . 47 2.5. First hints to substrate specificity: phylogenetic analyses . 48 2.6. Investigation of substrate specificity: test of steroidogenic substrates . 51 2.6.1. Selection of substrates and establishment of measurement . 51 2.6.2. Establishment of substrate conversion assays . 52 2.6.3. Conduction of conversion assays for enzymes under investigation . 58 2.6.4. Expression plasmids . 60 2.6.5. Test of overexpression . 60 2.6.6. Enzymes not converting the tested substrates . 61 2.6.7. Human retSDR3 oxidizes 17β-estradiol to estrone . 62 2.6.8. Human RDH12, human DHRSX, and murine Dhrs4 reduce dihy- drotestosterone to androstanediol . 63 2.6.9. Murine Dhrs4 has reductive enzymatic activity not only versus di- hydrotestosterone but also towards androstenedione and estrone . 65 2.6.10. Murine Wwox reduces androstenedione to testosterone and andros- terone to androstanediol . 68 2.7. Investigation of subcellular localization . 71 2.7.1. Bioinformatic means to predict subcellular localization . 72 2.7.2. Vectors and system of analysis . 72 2.7.3. Murine Sdr-o is a mitochondrial protein . 75 2.7.4. Human retSDR3 localizes to the cytoplasm . 76 2.7.5. dhrs7b from rat is localized in the endoplasmic reticulum . 77 2.7.6. Rat dhrs8 is an ER-localized SDR enzyme . 78 vi Contents 2.7.7. Murine Rdh12 is endoplasmic reticulum-localized . 79 2.7.8. Human RDH12 localizes to the ER . 80 2.7.9. Human type 13 retinol dehydrogenase localizes to the mitochondria 81 2.7.10. Murine Dhrs4 is neither a peroxisomal SDR nor mitochondrial but cytoplasmically distributed . 82 2.7.11. Human DHRSX co-localizes with ER-staining . 83 2.7.12. MGC4172 and MGC18716 may both be ER-localized . 84 3. Discussion 87 3.1. General remarks . 87 3.2. The set-up - is it functional genomics? . 87 3.3. Identification of candidate proteins and classification as SDRs . 88 3.3.1. The SDR Finder - friend or foe? . 88 3.3.2. On NCBI NonRedundant Database . 89 3.3.3. Annotation of identified SDRs to chromosomal location . 90 3.4. Analysis of the expression patterns . 92 3.4.1. Need of expression analysis . 92 3.4.2. Experimental expression analysis by Northern Blot . 93 3.4.3. In silico expression analysis . 93 3.5. Use of phylogenetics in predicting substrate specificities . 96 3.6. The substrate conversion assay . 98 3.6.1. Prokaryotic or eukaryotic overexpression? . 98 3.6.2. A steroid hormone conversion assay in living cells - what are the advantages? . 100 3.6.3. Considerations on the cell line used . 100 3.6.4. The conversion assay in living cells - is it in vivo? . 103 3.6.5. Michaelis-Menten kinetics in living cells . 103 3.6.6. Measurement of progestin conversion . 105 3.7. Studies on subcellular localization . 105 3.7.1. Prediction of subcellular localization . 105 3.7.2. Considerations on the experimental design . 106 3.8. Conclusions about the enzymes under investigation . 111 3.8.1. Murine orphan Sdr (Sdr-o) . 111 3.8.2. Human retSDR3 . 113 3.8.3. Rat SDRs under investigation: dhrs7b and dhrs8 . 115 3.8.4. Retinol dehydrogenases under investigation: murine type 12, human types 12 and 13 . 116 3.8.5. Murine Dhrs4 . 118 3.8.6. Human DHRSX . 119 vii Contents 3.8.7. Human and murine WW-box containing oxidoreductases . 120 3.8.8. MGC4172 and MGC18716 . 122 3.9. What else could be done? . 124 3.10. Outlook . 125 4. Methods 127 4.1. Work with E. coli . 127 4.1.1. Culture media . 127 4.1.2. Inhibitory and selective media supplements . 127 4.1.3. Growing of bacteria . 127 4.1.4. Short- and long-term-storage of bacterial culture . 128 4.1.5. Production of competent E. coli and transformation of plasmid DNA 128 4.2. Methods with eukaryotic cell lines . 129 4.2.1. Cultivation of cells . 129 4.2.2. Maintenance of cell culture: Splitting, thawing, freezing, and long- term storage of eukaryotic cells . 130 4.2.3. Transfection of eukaryotic cells . 131 4.2.4. Seeding of cells and transfection in different formats . 131 4.2.5. Immuncytochemical methods for subcellular localization studies . 132 4.3. DNA-based molecular biological methods . 134 4.3.1. Isolation and purification procedures . 134 4.3.2. Measurement and quality assessment of DNA solutions . 135 4.3.3. Cloning strategies . 137 4.3.4. PCR-based methods . 138 4.4. RNA-based methods . 139 4.4.1. Synthesis of RNA by in vitro transcription and digoxigenin labelling 139 4.4.2. Isolation and purification methods . 139 4.4.3. Handling and measurement . 140 4.5. Analysis of Gene Expression . 141 4.5.1. Reverse transcription of mRNA into cDNA . 141 4.5.2. Hybridization of cDNA probes to membrane bound RNA: Northern Blot . 141 4.5.3. Analysis of gene expression in mouse embryos . 142 4.6. Measurement of substrate specificity . 144 4.6.1. Measurement of substrate conversion in living cells . 144 4.6.2. Determination of Michaelis-Menten kinetics . 144 4.6.3. Purification of HPLC samples by solid phase extraction . 146 4.6.4. HPLC measurement . 147 4.7. Bioinformatic methods . 148 viii Contents 4.7.1. Identification of SDR candidate genes . 148 4.7.2. In silico Northern Blot . 148 4.7.3. Alignments and phylogeny . 149 4.7.4. Bioinformatic assessment of subcellular localization . 149 5. Programs, organisms, material 151 5.1. Programs . ..
Load more

Recommended publications
  • Differential Regulation of Gene Expression by Cholesterol Biosynthesis Inhibitors That Reduce (Pravastatin) Or Enhance (Squalest
    JPET Fast Forward. Published on May 25, 2016 as DOI: 10.1124/jpet.116.233312 This article has not been copyedited and formatted. The final version may differ from this version. Differential regulation of gene expression by cholesterol biosynthesis inhibitors that reduce (pravastatin) or enhance (squalestatin 1) nonsterol isoprenoid levels in primary cultured mouse and rat hepatocytes. Elizabeth A. Rondini, Zofia Duniec-Dmuchowski, Daniela Cukovic, Alan A. Dombkowski, and Thomas A. Kocarek Downloaded from Institute of Environmental Health Sciences, Wayne State University, Detroit, MI 48202, USA (E.A.R., Z.D-D, T.A.K.) jpet.aspetjournals.org Department of Pediatrics, Division of Clinical Pharmacology and Toxicology, Wayne State University, Detroit, MI 48202 (D.C., A.A.D) at ASPET Journals on September 27, 2021 JPET Fast Forward. Published on May 25, 2016 as DOI: 10.1124/jpet.116.233312 This article has not been copyedited and formatted. The final version may differ from this version. JPET #233312 Running title: Regulation of hepatocellular gene expression by isoprenoids Address correspondence to: Dr. Thomas A. Kocarek, Institute of Environmental Health Sciences, 6135 Woodward Avenue, IBio Building, Room 2126, Wayne State University, Detroit, MI 48202, USA. Tel: (313) 577-6580; FAX: (313) 972-8025; E-mail: [email protected] Number of text pages: 43 Downloaded from Number of tables: 2 Supplemental Number of figures: 8 jpet.aspetjournals.org Number of references: 77 Number of words in Abstract: 249 Number of words in Introduction: 745 at
    [Show full text]
  • Identification and Characterization of Zebrafish 17Beta-HSD Type 1 and Type 3: a Comparative Analysis of Androgen/Estrogen Activity Regulators
    Institut für Experimentelle Genetik GSF-Forschungzentrum für Umwelt und Gesundheit, Neuherberg Identification and characterization of zebrafish 17beta-HSD type 1 and type 3: A comparative analysis of androgen/estrogen activity regulators Rebekka Mindnich Vollständiger Abdruck der von der Fakultät Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt der Technischen Universität München zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften genehmigten Dissertation. Vorsitzender: Univ.- Prof. Dr. Bertold Hock Prüfer der Dissertation: 1. Priv.-Doz. Dr. Jerzy Adamski 2. Univ.-Prof. Dr. Johannes Buchner 3. Univ.-Prof. Dr. Wolfgang Wurst Die Dissertation wurde am 30.06.2004 bei der Technischen Universität München eingereicht und durch die Fakultät Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt am 07.10. 2004 angenommen. Table of contents Table of contents ABSTRACT................................................................................................................................... 7 ZUSAMMENFASSUNG................................................................................................................ 9 ABBREVIATIONS....................................................................................................................... 11 1 INTRODUCTION ................................................................................................................ 13 1.1 THE AIM OF THIS STUDY ...............................................................................................
    [Show full text]
  • Harnessing Gene Expression Profiles for the Identification of Ex Vivo Drug
    cancers Article Harnessing Gene Expression Profiles for the Identification of Ex Vivo Drug Response Genes in Pediatric Acute Myeloid Leukemia David G.J. Cucchi 1 , Costa Bachas 1 , Marry M. van den Heuvel-Eibrink 2,3, Susan T.C.J.M. Arentsen-Peters 3, Zinia J. Kwidama 1, Gerrit J. Schuurhuis 1, Yehuda G. Assaraf 4, Valérie de Haas 3 , Gertjan J.L. Kaspers 3,5 and Jacqueline Cloos 1,* 1 Hematology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; [email protected] (D.G.J.C.); [email protected] (C.B.); [email protected] (Z.J.K.); [email protected] (G.J.S.) 2 Department of Pediatric Oncology/Hematology, Erasmus MC–Sophia Children’s Hospital, 3015 CN Rotterdam, The Netherlands; [email protected] 3 Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; [email protected] (S.T.C.J.M.A.-P.); [email protected] (V.d.H.); [email protected] (G.J.L.K.) 4 The Fred Wyszkowski Cancer Research, Laboratory, Department of Biology, Technion-Israel Institute of Technology, 3200003 Haifa, Israel; [email protected] 5 Emma’s Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric Oncology, 1081 HV Amsterdam, The Netherlands * Correspondence: [email protected] Received: 21 April 2020; Accepted: 12 May 2020; Published: 15 May 2020 Abstract: Novel treatment strategies are of paramount importance to improve clinical outcomes in pediatric AML. Since chemotherapy is likely to remain the cornerstone of curative treatment of AML, insights in the molecular mechanisms that determine its cytotoxic effects could aid further treatment optimization.
    [Show full text]
  • Investigating the Genetic Basis of Cisplatin-Induced Ototoxicity in Adult South African Patients
    --------------------------------------------------------------------------- Investigating the genetic basis of cisplatin-induced ototoxicity in adult South African patients --------------------------------------------------------------------------- by Timothy Francis Spracklen SPRTIM002 SUBMITTED TO THE UNIVERSITY OF CAPE TOWN In fulfilment of the requirements for the degree MSc(Med) Faculty of Health Sciences UNIVERSITY OF CAPE TOWN University18 December of Cape 2015 Town Supervisor: Prof. Rajkumar S Ramesar Co-supervisor: Ms A Alvera Vorster Division of Human Genetics, Department of Pathology, University of Cape Town 1 The copyright of this thesis vests in the author. No quotation from it or information derived from it is to be published without full acknowledgement of the source. The thesis is to be used for private study or non- commercial research purposes only. Published by the University of Cape Town (UCT) in terms of the non-exclusive license granted to UCT by the author. University of Cape Town Declaration I, Timothy Spracklen, hereby declare that the work on which this dissertation/thesis is based is my original work (except where acknowledgements indicate otherwise) and that neither the whole work nor any part of it has been, is being, or is to be submitted for another degree in this or any other university. I empower the university to reproduce for the purpose of research either the whole or any portion of the contents in any manner whatsoever. Signature: Date: 18 December 2015 ' 2 Contents Abbreviations ………………………………………………………………………………….. 1 List of figures …………………………………………………………………………………... 6 List of tables ………………………………………………………………………………….... 7 Abstract ………………………………………………………………………………………… 10 1. Introduction …………………………………………………………………………………. 11 1.1 Cancer …………………………………………………………………………….. 11 1.2 Adverse drug reactions ………………………………………………………….. 12 1.3 Cisplatin …………………………………………………………………………… 12 1.3.1 Cisplatin’s mechanism of action ……………………………………………… 13 1.3.2 Adverse reactions to cisplatin therapy ……………………………………….
    [Show full text]
  • Identification and Characterization of TPRKB Dependency in TP53 Deficient Cancers
    Identification and Characterization of TPRKB Dependency in TP53 Deficient Cancers. by Kelly Kennaley A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Molecular and Cellular Pathology) in the University of Michigan 2019 Doctoral Committee: Associate Professor Zaneta Nikolovska-Coleska, Co-Chair Adjunct Associate Professor Scott A. Tomlins, Co-Chair Associate Professor Eric R. Fearon Associate Professor Alexey I. Nesvizhskii Kelly R. Kennaley [email protected] ORCID iD: 0000-0003-2439-9020 © Kelly R. Kennaley 2019 Acknowledgements I have immeasurable gratitude for the unwavering support and guidance I received throughout my dissertation. First and foremost, I would like to thank my thesis advisor and mentor Dr. Scott Tomlins for entrusting me with a challenging, interesting, and impactful project. He taught me how to drive a project forward through set-backs, ask the important questions, and always consider the impact of my work. I’m truly appreciative for his commitment to ensuring that I would get the most from my graduate education. I am also grateful to the many members of the Tomlins lab that made it the supportive, collaborative, and educational environment that it was. I would like to give special thanks to those I’ve worked closely with on this project, particularly Dr. Moloy Goswami for his mentorship, Lei Lucy Wang, Dr. Sumin Han, and undergraduate students Bhavneet Singh, Travis Weiss, and Myles Barlow. I am also grateful for the support of my thesis committee, Dr. Eric Fearon, Dr. Alexey Nesvizhskii, and my co-mentor Dr. Zaneta Nikolovska-Coleska, who have offered guidance and critical evaluation since project inception.
    [Show full text]
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
    [Show full text]
  • NSDHL, an Enzyme Involved in Cholesterol Biosynthesis, Traffics Through the Golgi and Accumulates on ER Membranes and on The
    Human Molecular Genetics, 2003, Vol. 12, No. 22 2981–2991 DOI: 10.1093/hmg/ddg321 NSDHL, an enzyme involved in cholesterol biosynthesis, traffics through the Golgi and accumulates on ER membranes and on the surface of lipid droplets Hugo Caldas1 and Gail E. Herman1,2,* Downloaded from https://academic.oup.com/hmg/article/12/22/2981/606598 by guest on 27 September 2021 1Center for Molecular and Human Genetics, Columbus Children’s Research Institute, Columbus, OH 43205, USA and 2Department of Pediatrics, The Ohio State University, Columbus, OH 43205, USA Received July 15, 2003; Revised August 29, 2003; Accepted September 11, 2003 NSDHL, for NAD(P)H steroid dehydrogenase-like, encodes a sterol dehydrogenase or decarboxylase involved in the sequential removal of two C-4 methyl groups in post-squalene cholesterol biosynthesis. Mutations in this gene are associated with human CHILD syndrome (congenital hemidysplasia with ichthyosiform nevus and limb defects), an X-linked, male lethal disorder, as well as the mouse mutations bare patches and striated. In the present study, we have investigated the subcellular localization of tagged proteins encoded by wild-type and selected mutant murine Nsdhl alleles using confocal microscopy. In addition to an ER localization commonly found for enzymes of post-squalene cholesterol biosynthesis, we have identified a novel association of NSDHL with lipid droplets, which are endoplasmic reticulum (ER)-derived cytoplasmic structures that contain a neutral lipid core. We further demonstrate that trafficking through the Golgi is necessary for ER membrane localization of the protein and propose a model for the association of NSDHL with lipid droplets.
    [Show full text]
  • Effects of Neonatal Stress and Morphine on Murine Hippocampal Gene Expression
    0031-3998/11/6904-0285 Vol. 69, No. 4, 2011 PEDIATRIC RESEARCH Printed in U.S.A. Copyright © 2011 International Pediatric Research Foundation, Inc. Effects of Neonatal Stress and Morphine on Murine Hippocampal Gene Expression SANDRA E. JUUL, RICHARD P. BEYER, THEO K. BAMMLER, FEDERICO M. FARIN, AND CHRISTINE A. GLEASON Department of Pediatrics [S.E.J., C.A.G.], Department of Environmental and Occupational Health Sciences [R.P.B., T.K.B., F.M.F.], University of Washington, Seattle, Washington 98195 ABSTRACT: Critically ill preterm infants experience multiple to severe impairment occurring in close to 50% of ex- stressors while hospitalized. Morphine is commonly prescribed to tremely LBW infants (4). Autism, attention deficit disorder, ameliorate their pain and stress. We hypothesized that neonatal and school failure also occur more frequently in NICU stress will have a dose-dependent effect on hippocampal gene survivors (5). Although some degree of impairment might expression, and these effects will be altered by morphine treat- ment. Male C57BL/6 mice were exposed to five treatment condi- be inevitable, it is likely that the stress and treatments these tions between postnatal d 5 and 9: 1) control, 2) mild stress ϩ infants undergo impact neurologic outcome. Improved un- saline, 3) mild stress ϩ morphine, 4) severe stress ϩ saline, and derstanding of these factors will provide the basis of better 5) severe stress ϩ morphine. Hippocampal RNA was extracted treatments and subsequent improvement in outcomes. and analyzed using Affymetrix Mouse Gene 1.0 ST Arrays. Single Many preterm infants receive opiates for sedation or gene analysis and gene set analysis were used to compare groups analgesia during their NICU stay.
    [Show full text]
  • Enzyme DHRS7
    Toward the identification of a function of the “orphan” enzyme DHRS7 Inauguraldissertation zur Erlangung der Würde eines Doktors der Philosophie vorgelegt der Philosophisch-Naturwissenschaftlichen Fakultät der Universität Basel von Selene Araya, aus Lugano, Tessin Basel, 2018 Originaldokument gespeichert auf dem Dokumentenserver der Universität Basel edoc.unibas.ch Genehmigt von der Philosophisch-Naturwissenschaftlichen Fakultät auf Antrag von Prof. Dr. Alex Odermatt (Fakultätsverantwortlicher) und Prof. Dr. Michael Arand (Korreferent) Basel, den 26.6.2018 ________________________ Dekan Prof. Dr. Martin Spiess I. List of Abbreviations 3α/βAdiol 3α/β-Androstanediol (5α-Androstane-3α/β,17β-diol) 3α/βHSD 3α/β-hydroxysteroid dehydrogenase 17β-HSD 17β-Hydroxysteroid Dehydrogenase 17αOHProg 17α-Hydroxyprogesterone 20α/βOHProg 20α/β-Hydroxyprogesterone 17α,20α/βdiOHProg 20α/βdihydroxyprogesterone ADT Androgen deprivation therapy ANOVA Analysis of variance AR Androgen Receptor AKR Aldo-Keto Reductase ATCC American Type Culture Collection CAM Cell Adhesion Molecule CYP Cytochrome P450 CBR1 Carbonyl reductase 1 CRPC Castration resistant prostate cancer Ct-value Cycle threshold-value DHRS7 (B/C) Dehydrogenase/Reductase Short Chain Dehydrogenase Family Member 7 (B/C) DHEA Dehydroepiandrosterone DHP Dehydroprogesterone DHT 5α-Dihydrotestosterone DMEM Dulbecco's Modified Eagle's Medium DMSO Dimethyl Sulfoxide DTT Dithiothreitol E1 Estrone E2 Estradiol ECM Extracellular Membrane EDTA Ethylenediaminetetraacetic acid EMT Epithelial-mesenchymal transition ER Endoplasmic Reticulum ERα/β Estrogen Receptor α/β FBS Fetal Bovine Serum 3 FDR False discovery rate FGF Fibroblast growth factor HEPES 4-(2-Hydroxyethyl)-1-Piperazineethanesulfonic Acid HMDB Human Metabolome Database HPLC High Performance Liquid Chromatography HSD Hydroxysteroid Dehydrogenase IC50 Half-Maximal Inhibitory Concentration LNCaP Lymph node carcinoma of the prostate mRNA Messenger Ribonucleic Acid n.d.
    [Show full text]
  • BMC Genomics Biomed Central
    BMC Genomics BioMed Central Research article Open Access Histone deacetylase inhibitors: A new mode for inhibition of cholesterol metabolism Sridar V Chittur*1, Niquiche Sangster-Guity2 and Paulette J McCormick1 Address: 1Center for Functional Genomics, University at Albany, State University of New York, Cancer Research Center, One Discovery Drive, Rm 310, Rensselaer, NY 12144, USA and 2Johns Hopkins University, School of Medicine, 1550 Orleans St, CRBII Rm 456, Baltimore, MD 21231, USA Email: Sridar V Chittur* - [email protected]; Niquiche Sangster-Guity - [email protected]; Paulette J McCormick - [email protected] * Corresponding author Published: 29 October 2008 Received: 6 March 2008 Accepted: 29 October 2008 BMC Genomics 2008, 9:507 doi:10.1186/1471-2164-9-507 This article is available from: http://www.biomedcentral.com/1471-2164/9/507 © 2008 Chittur et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: Eukaryotic gene expression is a complex process involving multiple cis and trans activating molecules to either facilitate or inhibit transcription. In recent years, many studies have focused on the role of acetylation of histone proteins in modulating transcription, whereas deacetylation of these same proteins is associated with inactivation or repression of gene expression. This study explores gene expression in HepG2 and F9 cell lines treated with Trichostatin A (TSA), a potent histone deacetylase inhibitor. Results: These experiments show that TSA treatment results in clear repression of genes involved in the cholesterol biosynthetic pathway as well as other associated pathways including fatty acid biosynthesis and glycolysis.
    [Show full text]
  • Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
    Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase
    [Show full text]
  • Supplementary Material
    BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Page 1 / 45 SUPPLEMENTARY MATERIAL Appendix A1: Neuropsychological protocol. Appendix A2: Description of the four cases at the transitional stage. Table A1: Clinical status and center proportion in each batch. Table A2: Complete output from EdgeR. Table A3: List of the putative target genes. Table A4: Complete output from DIANA-miRPath v.3. Table A5: Comparison of studies investigating miRNAs from brain samples. Figure A1: Stratified nested cross-validation. Figure A2: Expression heatmap of miRNA signature. Figure A3: Bootstrapped ROC AUC scores. Figure A4: ROC AUC scores with 100 different fold splits. Figure A5: Presymptomatic subjects probability scores. Figure A6: Heatmap of the level of enrichment in KEGG pathways. Kmetzsch V, et al. J Neurol Neurosurg Psychiatry 2021; 92:485–493. doi: 10.1136/jnnp-2020-324647 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Appendix A1. Neuropsychological protocol The PREV-DEMALS cognitive evaluation included standardized neuropsychological tests to investigate all cognitive domains, and in particular frontal lobe functions. The scores were provided previously (Bertrand et al., 2018). Briefly, global cognitive efficiency was evaluated by means of Mini-Mental State Examination (MMSE) and Mattis Dementia Rating Scale (MDRS). Frontal executive functions were assessed with Frontal Assessment Battery (FAB), forward and backward digit spans, Trail Making Test part A and B (TMT-A and TMT-B), Wisconsin Card Sorting Test (WCST), and Symbol-Digit Modalities test.
    [Show full text]