DNA Microarray Based Gene Expression Profiling in Human Hepatocyte Cells to Serve As a Basis for Dynamic Modelling of the Human Liver - a Systems Biology Approach

Total Page:16

File Type:pdf, Size:1020Kb

DNA Microarray Based Gene Expression Profiling in Human Hepatocyte Cells to Serve As a Basis for Dynamic Modelling of the Human Liver - a Systems Biology Approach DNA Microarray Based Gene Expression Profiling in Human Hepatocyte Cells to Serve as a Basis for Dynamic Modelling of the Human Liver - a Systems Biology Approach Von der Fakultät Energie-, Verfahrens- und Biotechnik der Universität Stuttgart zur Erlangung der Würde eines Doktors der Naturwissenschaften (Dr. rer. nat.) genehmigte Abhandlung vorgelegt von Thomas Reichart aus Sindelfingen Hauptberichter: Prof. Dr. Rolf D. Schmid, MBA Mitberichter: Prof. Dr. Dr. h.c. Matthias Reuss Tag der mündlichen Prüfung: 10. Juni 2008 Institut für Technische Biochemie der Universität Stuttgart 2008 TABLE OF CONTENTS TABLE OF CONTENTS...........................................................................................................................2 EIDESSTATTLICHE ERKLÄRUNG .....................................................................................................5 ACKNOWLEDGMENT............................................................................................................................6 ZUSAMMENFASSUNG............................................................................................................................7 ABSTRACT ..............................................................................................................................................15 ABBREVIATIONS ..................................................................................................................................21 1 INTRODUCTION ..........................................................................................................................24 1.1 SYSTEMS BIOLOGY - A NEW APPROACH ..................................................................................24 1.2 "HEPATOSYS" - A COMPUTATIONAL APPROACH TO UNDERSTAND FUNCTIONAL ASPECTS OF THE LIVER ...........................................................................................................................31 1.3 XENOBIOTIC METABOLISM ......................................................................................................34 1.4 MICROARRAY TECHNOLOGY....................................................................................................40 1.4.1 Microarrays in Drug Discovery, Drug Development and Future Applications .................50 1.4.2 Basics of Microarray Technology ......................................................................................55 1.4.3 Data Quantification and Interpretation of Microarray Experiments .................................66 1.4.4 Identifying Differentially Expressed Genes ........................................................................69 1.5 OBJECTIVE OF THIS THESIS ......................................................................................................76 2 MATERIALS AND METHODS ...................................................................................................78 2.1 CHEMICALS, ENZYMES AND KITS ............................................................................................78 2.2 HARDWARE EQUIPMENT ..........................................................................................................79 2.3 SOFTWARE TOOLS AND INTERNET RESOURCES........................................................................80 2.4 BUFFERS AND SOLUTIONS........................................................................................................81 2.4.1 Complex media ...................................................................................................................81 2.4.2 Antibiotics...........................................................................................................................82 2.5 MEDIA FOR CULTIVATION OF PRIMARY HUMAN HEPATOCYTES ..............................................82 2.6 PRIMARY HUMAN HEPATOCYTE CELLS, BACTERIAL STRAINS AND PLASMIDS USED IN THIS WORK ..............................................................................................................................83 2.6.1 Cultivation of Bacterial Cells .............................................................................................86 2.6.2 Conservation of Strains ......................................................................................................87 2.7 CELL CULTIVATION AND INDUCTION OF PRIMARY HEPATOCYTES...........................................87 2 TABLE OF CONTENTS 3 2.7.1 Bringing Primary Hepatocytes into Culture after Transport .............................................87 2.7.2 Induction Experiments of Primary Hepatocytes.................................................................88 2.7.3 Harvesting of Primary Hepatocytes ...................................................................................89 2.8 METHODS OF MOLECULAR BIOLOGY .......................................................................................90 2.8.1 Working with RNA..............................................................................................................90 2.8.2 Purification of Nucleic Acids..............................................................................................91 2.8.3 Quality Control of Nucleic Acids........................................................................................92 2.8.4 Precipitation of Nucleic Acids............................................................................................94 2.8.5 RNA Amplification..............................................................................................................94 2.8.6 Digestion of DNA..............................................................................................................100 2.8.7 Separation of Nucleic Acids Using Agarose Gel Electrophoresis....................................101 2.8.8 Preparation and Transformation of Competent E. coli . ..................................................104 2.8.9 Reverse Transcription.......................................................................................................106 2.8.10 Quantitative Real-time PCR ........................................................................................108 2.9 PROTEIN BIOCHEMICAL METHODS.........................................................................................114 2.9.1 Protein Precipitation with Acetone...................................................................................114 2.9.2 SDS-Polyacrylamide Gel Electrophoresis (SDS-PAGE)..................................................114 2.9.3 Semi-dry Protein Transfer for Western Blotting...............................................................119 2.9.4 Immunological Detection of Proteins on Nitrocellulose Filters.......................................120 2.10 METHODS USING DNA MICROARRAYS ..................................................................................122 2.10.1 Labeling of aRNA/cDNA..............................................................................................122 2.10.2 Indirect Labeling of Amplified (a)RNA........................................................................122 2.10.3 Direct Labeling During Reverse Transcription ...........................................................123 2.10.4 Indirect Labeling During Reverse Transcription.........................................................125 2.10.5 Hybridization and Washing .........................................................................................127 2.10.6 Detection of Indirectly Labeled Targets ......................................................................129 2.10.7 Scanning of Arrays.......................................................................................................129 2.10.8 Extraction of Raw Data and Picture Analysis (Quantification)...................................130 2.10.9 Evaluation of DNA Microarrays and Data Analysis ...................................................131 2.10.10 Analysing Sub-Genome Data using the Eppendorf DualChip® Software................132 2.10.11 Analysing Full-Genome Data Using "Refiner" and "Analyst" from Genedata..........138 2.10.12 Literature Mining Using Bibliosphere from Genomatix..............................................147 3 RESULTS ......................................................................................................................................152 3.1 COMPARISON OF MICROARRAYS FROM DIFFERENT SUPPLIERS..............................................153 3.2 EXPERIMENTAL SETUP OF TIME-SERIES EXPERIMENTS..........................................................162 3.3 RNA ISOLATION AND QUALITY CONTROL.............................................................................165 3.4 VERIFICATION OF INDUCTION OF CELL CULTURES.................................................................173 3.4.1 Quantitative Real-Time PCR (qRT-PCR).........................................................................173 4 Introduction 3.4.2 Western Blotting ...............................................................................................................177 3.5 REVERSE TRANSCRIPTION (RT), AMPLIFICATION AND LABELING OF MRNA.........................178 3.5.1 Direct Labeling with Fluorescent Dyes............................................................................178 3.5.2 Amplification and Indirect Labeling Using Biotin Modified Nucleotides.........................181 3.6 HYBRIDIZATION OF ARRAYS AND QUALITY CONTROL...........................................................185 3.6.1 Quality Control for Sub-Genome Arrays from Eppendorf................................................185
Recommended publications
  • 1General Introduction and Outline Glycosphingolipids, Carbohydrate
    Lipophilic iminosugars : synthesis and evaluation as inhibitors of glucosylceramide metabolism Wennekes, T. Citation Wennekes, T. (2008, December 15). Lipophilic iminosugars : synthesis and evaluation as inhibitors of glucosylceramide metabolism. Retrieved from https://hdl.handle.net/1887/13372 Version: Corrected Publisher’s Version Licence agreement concerning inclusion of doctoral thesis in the License: Institutional Repository of the University of Leiden Downloaded from: https://hdl.handle.net/1887/13372 Note: To cite this publication please use the final published version (if applicable). General Introduction and Outline Glycosphingolipids, Carbohydrate- 1 processing Enzymes and Iminosugar Inhibitors General Introduction The study described in this thesis was conducted with the aim of developing lipophilic iminosugars as selective inhibitors for three enzymes involved in glucosylceramide metabolism. Glucosylceramide, a β-glycoside of the lipid ceramide and the carbohydrate d-glucose, is a key member of a class of biomolecules called the glycosphingolipids (GSLs). One enzyme, glucosylceramide synthase (GCS), is responsible for its synthesis and the two other enzymes, glucocerebrosidase (GBA1) and β-glucosidase 2 (GBA2), catalyze its degradation. Being able to influence glucosylceramide biosynthesis and degradation would greatly facilitate the study of GSL functioning in (patho)physiological processes. This chapter aims to provide background information and some history on the various subjects that were involved in this study. The chapter will start out with a brief overview of the discovery of GSLs and the evolving view of the biological role of GSLs and carbohydrate containing biomolecules in general during the last century. Next, the topology and dynamics of mammalian GSL biosynthesis and degradation will be described with special attention for the involved carbohydrate-processing enzymes.
    [Show full text]
  • To Study Mutant P53 Gain of Function, Various Tumor-Derived P53 Mutants
    Differential effects of mutant TAp63γ on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression. A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science By Shama K Khokhar M.Sc., Bilaspur University, 2004 B.Sc., Bhopal University, 2002 2007 1 COPYRIGHT SHAMA K KHOKHAR 2007 2 WRIGHT STATE UNIVERSITY SCHOOL OF GRADUATE STUDIES Date of Defense: 12-03-07 I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY SHAMA KHAN KHOKHAR ENTITLED Differential effects of mutant TAp63γ on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science Madhavi P. Kadakia, Ph.D. Thesis Director Daniel Organisciak , Ph.D. Department Chair Committee on Final Examination Madhavi P. Kadakia, Ph.D. Steven J. Berberich, Ph.D. Michael Leffak, Ph.D. Joseph F. Thomas, Jr., Ph.D. Dean, School of Graduate Studies 3 Abstract Khokhar, Shama K. M.S., Department of Biochemistry and Molecular Biology, Wright State University, 2007 Differential effect of TAp63γ mutants on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression. p63, a member of the p53 gene family, known to play a role in development, has more recently also been implicated in cancer progression. Mice lacking p63 exhibit severe developmental defects such as limb truncations, abnormal skin, and absence of hair follicles, teeth, and mammary glands. Germline missense mutations of p63 have been shown to be responsible for several human developmental syndromes including SHFM, EEC and ADULT syndromes and are associated with anomalies in the development of organs of epithelial origin.
    [Show full text]
  • Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
    Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7
    [Show full text]
  • The E–Id Protein Axis Modulates the Activities of the PI3K–AKT–Mtorc1
    Downloaded from genesdev.cshlp.org on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press The E–Id protein axis modulates the activities of the PI3K–AKT–mTORC1– Hif1a and c-myc/p19Arf pathways to suppress innate variant TFH cell development, thymocyte expansion, and lymphomagenesis Masaki Miyazaki,1,8 Kazuko Miyazaki,1,8 Shuwen Chen,1 Vivek Chandra,1 Keisuke Wagatsuma,2 Yasutoshi Agata,2 Hans-Reimer Rodewald,3 Rintaro Saito,4 Aaron N. Chang,5 Nissi Varki,6 Hiroshi Kawamoto,7 and Cornelis Murre1 1Department of Molecular Biology, University of California at San Diego, La Jolla, California 92093, USA; 2Department of Biochemistry and Molecular Biology, Shiga University of Medical School, Shiga 520-2192, Japan; 3Division of Cellular Immunology, German Cancer Research Center, D-69120 Heidelberg, Germany; 4Department of Medicine, University of California at San Diego, La Jolla, California 92093, USA; 5Center for Computational Biology, Institute for Genomic Medicine, University of California at San Diego, La Jolla, California 92093, USA; 6Department of Pathology, University of California at San Diego, La Jolla, California 92093, USA; 7Department of Immunology, Institute for Frontier Medical Sciences, Kyoto University, Kyoto 606-8507, Japan It is now well established that the E and Id protein axis regulates multiple steps in lymphocyte development. However, it remains unknown how E and Id proteins mechanistically enforce and maintain the naı¨ve T-cell fate. Here we show that Id2 and Id3 suppressed the development and expansion of innate variant follicular helper T (TFH) cells. Innate variant TFH cells required major histocompatibility complex (MHC) class I-like signaling and were associated with germinal center B cells.
    [Show full text]
  • Alveolar Rhabdomyosarcoma-Associated Proteins PAX3/FOXO1A and PAX7/FOXO1A Suppress the Transcriptional Activity of Myod-Target Genes in Muscle Stem Cells
    Oncogene (2013) 32, 651 --662 & 2013 Macmillan Publishers Limited All rights reserved 0950-9232/13 www.nature.com/onc ORIGINAL ARTICLE Alveolar rhabdomyosarcoma-associated proteins PAX3/FOXO1A and PAX7/FOXO1A suppress the transcriptional activity of MyoD-target genes in muscle stem cells F Calhabeu1, S Hayashi2, JE Morgan3, F Relaix2 and PS Zammit1 Rhabdomyosarcoma (RMS) is the commonest soft-tissue sarcoma in childhood and is characterized by expression of myogenic proteins, including the transcription factors MyoD and myogenin. There are two main subgroups, embryonal RMS and alveolar RMS (ARMS). Most ARMS are associated with chromosomal translocations that have breakpoints in introns of either PAX3 or PAX7, and FOXO1A. These translocations create chimeric transcription factors termed PAX3/FOXO1A and PAX7/FOXO1A respectively. Upon ectopic PAX3/FOXO1A expression, together with other genetic manipulation in mice, both differentiating myoblasts and satellite cells (the resident stem cells of postnatal muscle) can give rise to tumours with ARMS characteristics. As PAX3 and PAX7 are part of transcriptional networks that regulate muscle stem cell function in utero and during early postnatal life, PAX3/FOXO1A and PAX7/FOXO1A may subvert normal PAX3 and PAX7 functions. Here we examined how PAX3/FOXO1A and PAX7/FOXO1A affect myogenesis in satellite cells. PAX3/FOXO1A or PAX7/FOXO1A inhibited myogenin expression and prevented terminal differentiation in murine satellite cells: the same effect as dominant-negative (DN) Pax3 or Pax7 constructs. The transcription of MyoD-target genes myogenin and muscle creatine kinase were suppressed by PAX3/FOXO1A or PAX7/ FOXO1A in C2C12 myogenic cells again as seen with Pax3/7DN. PAX3/FOXO1A or PAX7/FOXO1A did not inhibit the transcriptional activity of MyoD by perturbing MyoD expression, localization, phosphorylation or interaction with E-proteins.
    [Show full text]
  • (12) Patent Application Publication (10) Pub. No.: US 2017/0029891 A1 SHARP Et Al
    US 2017.0029891A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2017/0029891 A1 SHARP et al. (43) Pub. Date: Feb. 2, 2017 (54) BOMARKERS FOR DAGNOSING (60) Provisional application No. 61/584.232, filed on Jan. SCHEMA 7, 2012. (71) Applicant: The Regents of the University of California, Oakland, CA (US) Publication Classification (51) Int. C. (72) Inventors: Frank SHARP, Davis, CA (US); Glen CI2O I/68 (2006.01) C. JICKLING, Sacramento, CA (US) (52) U.S. C. (73) Assignee: The Regents of the University of CPC ....... CI2O 1/6883 (2013.01); C12O 2600/158 California, Oakland, CA (US) (2013.01); C12O 2600/118 (2013.01) (21) Appl. No.: 15/226,844 (57) ABSTRACT (22) Filed: Aug. 2, 2016 The present invention provides methods and compositions for diagnosing and predicting the occurrence of ischemia. Related U.S. Application Data For example, the present invention provides methods and (63) Continuation of application No. 14/370.709, filed on compositions for diagnosing and predicting the risk and Jul. 3, 2014, now Pat. No. 9,410,204, filed as appli cause of transient neurological events (TNE) as ischemic or cation No. PCT/US2013/020240 on Jan. 4, 2013. non-ischemic. Patent Application Publication Feb. 2, 2017. Sheet 1 of 3 US 2017/0029891 A1 TA (n=263 WS schemic Stroke (n=94) VRF Contro ra.) vs WRF Control (n=44) Fig. 1 A. Derivation Cross-Walidation 26 Gene 10-fold leave-one-out DA Prediction Model TA-DW+f Minor Stroke (n=17) Fia. 1 B. Validation g Nonischemic TNE {n=13) Fig.
    [Show full text]
  • 140503 IPF Signatures Supplement Withfigs Thorax
    Supplementary material for Heterogeneous gene expression signatures correspond to distinct lung pathologies and biomarkers of disease severity in idiopathic pulmonary fibrosis Daryle J. DePianto1*, Sanjay Chandriani1⌘*, Alexander R. Abbas1, Guiquan Jia1, Elsa N. N’Diaye1, Patrick Caplazi1, Steven E. Kauder1, Sabyasachi Biswas1, Satyajit K. Karnik1#, Connie Ha1, Zora Modrusan1, Michael A. Matthay2, Jasleen Kukreja3, Harold R. Collard2, Jackson G. Egen1, Paul J. Wolters2§, and Joseph R. Arron1§ 1Genentech Research and Early Development, South San Francisco, CA 2Department of Medicine, University of California, San Francisco, CA 3Department of Surgery, University of California, San Francisco, CA ⌘Current address: Novartis Institutes for Biomedical Research, Emeryville, CA. #Current address: Gilead Sciences, Foster City, CA. *DJD and SC contributed equally to this manuscript §PJW and JRA co-directed this project Address correspondence to Paul J. Wolters, MD University of California, San Francisco Department of Medicine Box 0111 San Francisco, CA 94143-0111 [email protected] or Joseph R. Arron, MD, PhD Genentech, Inc. MS 231C 1 DNA Way South San Francisco, CA 94080 [email protected] 1 METHODS Human lung tissue samples Tissues were obtained at UCSF from clinical samples from IPF patients at the time of biopsy or lung transplantation. All patients were seen at UCSF and the diagnosis of IPF was established through multidisciplinary review of clinical, radiological, and pathological data according to criteria established by the consensus classification of the American Thoracic Society (ATS) and European Respiratory Society (ERS), Japanese Respiratory Society (JRS), and the Latin American Thoracic Association (ALAT) (ref. 5 in main text). Non-diseased normal lung tissues were procured from lungs not used by the Northern California Transplant Donor Network.
    [Show full text]
  • Core Circadian Clock Transcription Factor BMAL1 Regulates Mammary Epithelial Cell
    bioRxiv preprint doi: https://doi.org/10.1101/2021.02.23.432439; this version posted February 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 Title: Core circadian clock transcription factor BMAL1 regulates mammary epithelial cell 2 growth, differentiation, and milk component synthesis. 3 Authors: Theresa Casey1ǂ, Aridany Suarez-Trujillo1, Shelby Cummings1, Katelyn Huff1, 4 Jennifer Crodian1, Ketaki Bhide2, Clare Aduwari1, Kelsey Teeple1, Avi Shamay3, Sameer J. 5 Mabjeesh4, Phillip San Miguel5, Jyothi Thimmapuram2, and Karen Plaut1 6 Affiliations: 1. Department of Animal Science, Purdue University, West Lafayette, IN, USA; 2. 7 Bioinformatics Core, Purdue University; 3. Animal Science Institute, Agriculture Research 8 Origination, The Volcani Center, Rishon Letsiyon, Israel. 4. Department of Animal Sciences, 9 The Robert H. Smith Faculty of Agriculture, Food, and Environment, The Hebrew University of 10 Jerusalem, Rehovot, Israel. 5. Genomics Core, Purdue University 11 Grant support: Binational Agricultural Research Development (BARD) Research Project US- 12 4715-14; Photoperiod effects on milk production in goats: Are they mediated by the molecular 13 clock in the mammary gland? 14 ǂAddress for correspondence. 15 Theresa M. Casey 16 BCHM Room 326 17 175 South University St. 18 West Lafayette, IN 47907 19 Email: [email protected] 20 Phone: 802-373-1319 21 22 bioRxiv preprint doi: https://doi.org/10.1101/2021.02.23.432439; this version posted February 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
    [Show full text]
  • Transcriptomic and Proteomic Profiling Provides Insight Into
    BASIC RESEARCH www.jasn.org Transcriptomic and Proteomic Profiling Provides Insight into Mesangial Cell Function in IgA Nephropathy † † ‡ Peidi Liu,* Emelie Lassén,* Viji Nair, Celine C. Berthier, Miyuki Suguro, Carina Sihlbom,§ † | † Matthias Kretzler, Christer Betsholtz, ¶ Börje Haraldsson,* Wenjun Ju, Kerstin Ebefors,* and Jenny Nyström* *Department of Physiology, Institute of Neuroscience and Physiology, §Proteomics Core Facility at University of Gothenburg, University of Gothenburg, Gothenburg, Sweden; †Division of Nephrology, Department of Internal Medicine and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan; ‡Division of Molecular Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan; |Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden; and ¶Integrated Cardio Metabolic Centre, Karolinska Institutet Novum, Huddinge, Sweden ABSTRACT IgA nephropathy (IgAN), the most common GN worldwide, is characterized by circulating galactose-deficient IgA (gd-IgA) that forms immune complexes. The immune complexes are deposited in the glomerular mesangium, leading to inflammation and loss of renal function, but the complete pathophysiology of the disease is not understood. Using an integrated global transcriptomic and proteomic profiling approach, we investigated the role of the mesangium in the onset and progression of IgAN. Global gene expression was investigated by microarray analysis of the glomerular compartment of renal biopsy specimens from patients with IgAN (n=19) and controls (n=22). Using curated glomerular cell type–specific genes from the published literature, we found differential expression of a much higher percentage of mesangial cell–positive standard genes than podocyte-positive standard genes in IgAN. Principal coordinate analysis of expression data revealed clear separation of patient and control samples on the basis of mesangial but not podocyte cell–positive standard genes.
    [Show full text]
  • Microarray-Based Analysis of Genes, Transcription Factors, and Epigenetic Modifications in Lung Cancer Exposed to Nitric Oxide
    CANCER GENOMICS & PROTEOMICS 17 : 401-415 (2020) doi:10.21873/cgp.20199 Microarray-based Analysis of Genes, Transcription Factors, and Epigenetic Modifications in Lung Cancer Exposed to Nitric Oxide ARNATCHAI MAIUTHED 1, ORNJIRA PRAKHONGCHEEP 2,3 and PITHI CHANVORACHOTE 2,3 1Department of Pharmacology, Faculty of Pharmacy, Mahidol University, Bangkok, Thailand; 2Cell-based Drug and Health Product Development Research Unit, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand; 3Department of Pharmacology and Physiology, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand Abstract. Background/Aim: Nitric oxide (NO) is recognized NO exposure of lung cancer cells resulted in a change in as an important biological mediator that exerts several transcription factors (TFs) and epigenetic modifications human physiological functions. As its nature is an aqueous (histone modification and miRNA). Interestingly, NO soluble gas that can diffuse through cells and tissues, NO treatment was shown to potentiate cancer stem cell-related can affect cell signaling, the phenotype of cancer and modify genes and transcription factors Oct4, Klf4, and Myc. surrounding cells. The variety of effects of NO on cancer cell Conclusion: Through this comprehensive approach, the biology has convinced researchers to determine the defined present study illustrated the scheme of how NO affects mechanisms of these effects and how to control this mediator molecular events in lung cancer cells. for a better understanding as well as for therapeutic gain. Materials and Methods: We used bioinformatics and Lung cancer is one of the leading causes of cancer-related pharmacological experiments to elucidate the potential deaths worldwide (1, 2). Since the aggressive phenotypes regulation and underlying mechanisms of NO in non-small and treatment failures have been frequently observed in lung a lung cancer cell model.
    [Show full text]
  • Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant
    Appendix 2. Significantly Differentially Regulated Genes in Term Compared With Second Trimester Amniotic Fluid Supernatant Fold Change in term vs second trimester Amniotic Affymetrix Duplicate Fluid Probe ID probes Symbol Entrez Gene Name 1019.9 217059_at D MUC7 mucin 7, secreted 424.5 211735_x_at D SFTPC surfactant protein C 416.2 206835_at STATH statherin 363.4 214387_x_at D SFTPC surfactant protein C 295.5 205982_x_at D SFTPC surfactant protein C 288.7 1553454_at RPTN repetin solute carrier family 34 (sodium 251.3 204124_at SLC34A2 phosphate), member 2 238.9 206786_at HTN3 histatin 3 161.5 220191_at GKN1 gastrokine 1 152.7 223678_s_at D SFTPA2 surfactant protein A2 130.9 207430_s_at D MSMB microseminoprotein, beta- 99.0 214199_at SFTPD surfactant protein D major histocompatibility complex, class II, 96.5 210982_s_at D HLA-DRA DR alpha 96.5 221133_s_at D CLDN18 claudin 18 94.4 238222_at GKN2 gastrokine 2 93.7 1557961_s_at D LOC100127983 uncharacterized LOC100127983 93.1 229584_at LRRK2 leucine-rich repeat kinase 2 HOXD cluster antisense RNA 1 (non- 88.6 242042_s_at D HOXD-AS1 protein coding) 86.0 205569_at LAMP3 lysosomal-associated membrane protein 3 85.4 232698_at BPIFB2 BPI fold containing family B, member 2 84.4 205979_at SCGB2A1 secretoglobin, family 2A, member 1 84.3 230469_at RTKN2 rhotekin 2 82.2 204130_at HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 81.9 222242_s_at KLK5 kallikrein-related peptidase 5 77.0 237281_at AKAP14 A kinase (PRKA) anchor protein 14 76.7 1553602_at MUCL1 mucin-like 1 76.3 216359_at D MUC7 mucin 7,
    [Show full text]
  • Linking Gaucher's Disease And
    Journal of Young Investigators RESEARCH REVIEW The Role of Mutant Glucocerebrosidase and α-Synuclein Oligomerization in Neurodegeneration: Linking Gaucher’s Disease and Parkinson’s Disease Brendan Scot Tanner1* and John Porter 2 Gaucher’s disease is a pathology associated with intracellular accumulation of glucosylceramide due to glucocerebrosidase dysfuntion. Gaucher’s disease, type I in particular, does not usually present with neurologic components; however, researchers and physicians have recently noted an increased incidence of Parkinsonism in patients with type I Gaucher’s. Parkinson’s disease is a pathology affecting dopaminergic nerve tracts in motor cortices, most notably the substantia nigra. The disease is microscopically characterized by the presence of α-synuclein inclusions (Lewy bodies) in dopaminergic neurons. In an attempt to link the pathologies at a biomolecular level, researchers utilized numerous strategies, all culminating in several common observations: mutations of glucocerebrosidase, mutations of α-synuclein, and lysosomal dysfunction. Accumulated mutations and lysosomal dysfunction result in a complex feed-forward mechanism leading to aberrant ER-Golgi function. This review aims to highlight the previously unknown mechanism of Gaucher-linked Parkinsonism and to shed light on the future direction of linking and treating similar pathologies. INTRODUCTION chromosome 1q22 (Cullen et al. 2011). Each variant of the Observing an increased incidence of Parkinsonism in patients disease manifests in a slightly different manner. This paper will with type I Gaucher’s disease focus on type I Gaucher's disease, common among the Ashkenazi Jews. Type I Gaucher’s disease is the non-neuropathic variant Researchers have spent considerable amounts of energy in an that results in hepatomegaly, splenomegaly, thrombocytopenia, attempt to link two pathophysiological events, α-synuclein and leukopenia, although most patients remain asymptomatic aggregation and glucocerebrosidase dysfunction.
    [Show full text]