DOCSLIB.ORG

Nucleolin and Its Role in Ribosomal Biogenesis

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

NUCLEOLIN: A NUCLEOLAR RNA-BINDING PROTEIN INVOLVED IN RIBOSOME BIOGENESIS Inaugural-Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf vorgelegt von Julia Fremerey aus Hamburg Düsseldorf, April 2016 2 Gedruckt mit der Genehmigung der Mathematisch-Naturwissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf Referent: Prof. Dr. A. Borkhardt Korreferent: Prof. Dr. H. Schwender Tag der mündlichen Prüfung: 20.07.2016 3 Die vorgelegte Arbeit wurde von Juli 2012 bis März 2016 in der Klinik für Kinder- Onkologie, -Hämatologie und Klinische Immunologie des Universitätsklinikums Düsseldorf unter Anleitung von Prof. Dr. A. Borkhardt und in Kooperation mit dem ‚Laboratory of RNA Molecular Biology‘ an der Rockefeller Universität unter Anleitung von Prof. Dr. T. Tuschl angefertigt. 4 Dedicated to my family TABLE OF CONTENTS 5 TABLE OF CONTENTS TABLE OF CONTENTS ............................................................................................... 5 LIST OF FIGURES ......................................................................................................10 LIST OF TABLES .......................................................................................................12 ABBREVIATION .........................................................................................................13 ABSTRACT ................................................................................................................19 ZUSAMMENFASSUNG ..............................................................................................21 1 INTRODUCTION .................................................................................................23 1.1 The nucleolus, the site of ribosome biogenesis ..........................................23 1.2 Ribosome biogenesis in eukaryotes ............................................................24 1.2.1 The human ribosome and ribosomal proteins ........................................................... 27 1.2.2 Ribosomal RNA and the precursor ribosomal RNA transcript ................................... 28 1.2.3 Ribosome biogenesis factors ..................................................................................... 31 1.2.3.1 Phosphorylation of ribosome biogenesis factors by protein kinases ................ 34 1.2.3.2 RNA-helicases involved in ribosome biogenesis .............................................. 35 1.2.4 Structure and function of small nucleolar RNAs ........................................................ 37 1.2.5 The role of ribosome biogenesis in cancer and genetic diseases ............................. 40 1.3 RNA-binding proteins ....................................................................................44 1.3.1 RNA-binding domains ................................................................................................ 46 1.3.2 RNA-binding proteins in human diseases.................................................................. 49 1.3.3 Identification of RNA-protein interaction .................................................................... 50 1.4 Nucleolin, a nucleolar RNA-binding protein ................................................53 1.4.1 Localization of Nucleolin ............................................................................................ 55 1.4.2 The role of Nucleolin in ribosome biogenesis ............................................................ 56 1.4.3 The role of Nucleolin in cancer .................................................................................. 58 1.5 Aim of the thesis ............................................................................................60 2 MATERIAL AND METHODS ...............................................................................61 TABLE OF CONTENTS 6 2.1 Material ...........................................................................................................61 2.1.1 Media, Buffer and Solution ........................................................................................ 63 2.1.2 Cells ........................................................................................................................... 68 2.1.3 Cell Culture Media and Antibiotics ............................................................................. 68 2.1.4 Chemicals and Enzymes ........................................................................................... 69 2.1.5 Commercial Kits ......................................................................................................... 72 2.1.6 Plasmids of the Gateway Cloning System ................................................................. 72 2.1.7 DNA and RNA oligos ................................................................................................. 73 2.1.7.1 Primer ................................................................................................................ 75 2.1.7.2 siRNAs .............................................................................................................. 76 2.1.8 Inhibitors .................................................................................................................... 76 2.1.9 Antibodies and Peptides ............................................................................................ 77 2.1.10 Recombinant Protein ............................................................................................. 77 2.2 Methods ..........................................................................................................78 2.2.1 Generation of stable and inducible Flp-In T-REx HEK293 cells ................................ 78 2.2.1.1 The Gateway Recombination Cloning Technology ........................................... 79 2.2.1.2 Transfection of HEK293 cells using Lipofectamine 2000 ................................. 81 2.2.1.3 Cultivation of Flp-In T-REx HEK293 cells ......................................................... 82 2.2.1.4 Nucleolin constructs .......................................................................................... 82 2.2.2 SDS-PAGE and Western Blot analysis ...................................................................... 83 2.2.3 NoD, a nucleolar localization signal prediction tool ................................................... 84 2.2.4 Immunohistochemistry and RNA Fluorescent In-Situ Hybridization .......................... 85 2.2.5 TRIzol - Extraction of RNA ......................................................................................... 86 2.2.6 The 5’ and 3’ end labeling of RNA ............................................................................. 86 2.2.7 Deprotection of a 2’-ACE protected RNA oligo .......................................................... 88 2.2.8 Inhibition of the Casein Kinase II phosphorylation reaction ....................................... 89 2.2.9 Photoactivatable-ribonucleoside enhanced crosslinking and immunoprecipitation .. 89 2.2.9.1 4SU labeling and UV crosslinking at 365 nm .................................................... 92 2.2.9.2 Cell lysis and Immunoprecipitation ................................................................... 93 2.2.9.3 Dephosphorylation and radiolabeling of the crosslinked RNA .......................... 93 2.2.9.4 Radiolabeling of the 5’ end of the RNA size markers using γ 32P-ATP............. 94 2.2.9.5 SDS-PAGE and transfer to a nitrocellulose membrane .................................... 94 2.2.9.6 Proteinase-K digest and RNA isolation ............................................................. 95 2.2.9.7 The 3’- and 5’-adapter ligation .......................................................................... 95 2.2.9.8 cDNA library preparation ................................................................................... 97 2.2.9.9 Analysis of the PAR-CLIP library ...................................................................... 98 2.2.10 RNA Immunoprecipitation-sequencing .................................................................. 99 2.2.10.1 Cell lysis and Immunoprecipitation ................................................................. 100 2.2.10.2 RNA extraction, library preparation and Next-Generation Sequencing .......... 100 2.2.11 DREME: A motif discovery algorithm to identify binding motifs .......................... 101 2.2.12 Biochemical and structural binding studies ......................................................... 102 2.2.12.1 Electrophoretic mobility shift assay ................................................................. 103 TABLE OF CONTENTS 7 2.2.12.2 Isothermal-Titration Calorimetry ...................................................................... 104 2.2.12.3 Size-Exclusion Chromatography ..................................................................... 106 2.2.12.4 Crystallography ............................................................................................... 107 2.2.13 Mass-Spectrometry ............................................................................................. 108 2.2.13.1 Cell lysis, Immunoprecipitation and FLAG-peptide elution ............................. 110 2.2.13.2 SDS-PAGE and silver staining ........................................................................ 110 2.2.13.3 Liquid chromatography-electrospray ionization Mass-Spectrometry .............. 111 2.2.13.4 Data analysis of Mass-Spectrometry using SAINTexpress and SAM ............ 112
Recommended publications
  • Analysis of Gene Expression Data for Gene Ontology

    Analysis of Gene Expression Data for Gene Ontology

    ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins.
  • Efficacy and Mechanistic Evaluation of Tic10, a Novel Antitumor Agent

    Efficacy and Mechanistic Evaluation of Tic10, a Novel Antitumor Agent

    University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2012 Efficacy and Mechanisticv E aluation of Tic10, A Novel Antitumor Agent Joshua Edward Allen University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Oncology Commons Recommended Citation Allen, Joshua Edward, "Efficacy and Mechanisticv E aluation of Tic10, A Novel Antitumor Agent" (2012). Publicly Accessible Penn Dissertations. 488. https://repository.upenn.edu/edissertations/488 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/488 For more information, please contact [email protected]. Efficacy and Mechanisticv E aluation of Tic10, A Novel Antitumor Agent Abstract TNF-related apoptosis-inducing ligand (TRAIL; Apo2L) is an endogenous protein that selectively induces apoptosis in cancer cells and is a critical effector in the immune surveillance of cancer. Recombinant TRAIL and TRAIL-agonist antibodies are in clinical trials for the treatment of solid malignancies due to the cancer-specific cytotoxicity of TRAIL. Recombinant TRAIL has a short serum half-life and both recombinant TRAIL and TRAIL receptor agonist antibodies have a limited capacity to perfuse to tissue compartments such as the brain, limiting their efficacy in certain malignancies. To overcome such limitations, we searched for small molecules capable of inducing the TRAIL gene using a high throughput luciferase reporter gene assay. We selected TRAIL-inducing compound 10 (TIC10) for further study based on its induction of TRAIL at the cell surface and its promising therapeutic index. TIC10 is a potent, stable, and orally active antitumor agent that crosses the blood-brain barrier and transcriptionally induces TRAIL and TRAIL-mediated cell death in a p53-independent manner.
  • Allele-Specific Expression of Ribosomal Protein Genes in Interspecific Hybrid Catfish

    Allele-Specific Expression of Ribosomal Protein Genes in Interspecific Hybrid Catfish

    Allele-specific Expression of Ribosomal Protein Genes in Interspecific Hybrid Catfish by Ailu Chen A dissertation submitted to the Graduate Faculty of Auburn University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Auburn, Alabama August 1, 2015 Keywords: catfish, interspecific hybrids, allele-specific expression, ribosomal protein Copyright 2015 by Ailu Chen Approved by Zhanjiang Liu, Chair, Professor, School of Fisheries, Aquaculture and Aquatic Sciences Nannan Liu, Professor, Entomology and Plant Pathology Eric Peatman, Associate Professor, School of Fisheries, Aquaculture and Aquatic Sciences Aaron M. Rashotte, Associate Professor, Biological Sciences Abstract Interspecific hybridization results in a vast reservoir of allelic variations, which may potentially contribute to phenotypical enhancement in the hybrids. Whether the allelic variations are related to the downstream phenotypic differences of interspecific hybrid is still an open question. The recently developed genome-wide allele-specific approaches that harness high- throughput sequencing technology allow direct quantification of allelic variations and gene expression patterns. In this work, I investigated allele-specific expression (ASE) pattern using RNA-Seq datasets generated from interspecific catfish hybrids. The objective of the study is to determine the ASE genes and pathways in which they are involved. Specifically, my study investigated ASE-SNPs, ASE-genes, parent-of-origins of ASE allele and how ASE would possibly contribute to heterosis. My data showed that ASE was operating in the interspecific catfish system. Of the 66,251 and 177,841 SNPs identified from the datasets of the liver and gill, 5,420 (8.2%) and 13,390 (7.5%) SNPs were identified as significant ASE-SNPs, respectively.
  • High Throughput Circrna Sequencing Analysis Reveals Novel Insights Into

    High Throughput Circrna Sequencing Analysis Reveals Novel Insights Into

    Xiong et al. Cell Death and Disease (2019) 10:658 https://doi.org/10.1038/s41419-019-1890-9 Cell Death & Disease ARTICLE Open Access High throughput circRNA sequencing analysis reveals novel insights into the mechanism of nitidine chloride against hepatocellular carcinoma Dan-dan Xiong1, Zhen-bo Feng1, Ze-feng Lai2,YueQin2, Li-min Liu3,Hao-xuanFu2, Rong-quan He4,Hua-yuWu5, Yi-wu Dang1, Gang Chen 1 and Dian-zhong Luo1 Abstract Nitidine chloride (NC) has been demonstrated to have an anticancer effect in hepatocellular carcinoma (HCC). However, the mechanism of action of NC against HCC remains largely unclear. In this study, three pairs of NC-treated and NC-untreated HCC xenograft tumour tissues were collected for circRNA sequencing analysis. In total, 297 circRNAs were differently expressed between the two groups, with 188 upregulated and 109 downregulated, among which hsa_circ_0088364 and hsa_circ_0090049 were validated by real-time quantitative polymerase chain reaction. The in vitro experiments showed that the two circRNAs inhibited the malignant biological behaviour of HCC, suggesting that they may play important roles in the development of HCC. To elucidate whether the two circRNAs function as “miRNA sponges” in HCC, we identified circRNA-miRNA and miRNA-mRNA interactions by using the CircInteractome and miRwalk, respectively. Subsequently, 857 miRNA-associated differently expressed genes in HCC were selected for weighted gene co-expression network analysis. Module Eigengene turquoise with 423 genes was found to be significantly related to the survival time, pathology grade and TNM stage of HCC patients. Gene functional enrichment 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; analysis showed that the 423 genes mainly functioned in DNA replication- and cell cycle-related biological processes and signalling cascades.
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus

    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.
  • A Molecular and Genetic Analysis of Otosclerosis

    A Molecular and Genetic Analysis of Otosclerosis

    A molecular and genetic analysis of otosclerosis Joanna Lauren Ziff Submitted for the degree of PhD University College London January 2014 1 Declaration I, Joanna Ziff, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. Where work has been conducted by other members of our laboratory, this has been indicated by an appropriate reference. 2 Abstract Otosclerosis is a common form of conductive hearing loss. It is characterised by abnormal bone remodelling within the otic capsule, leading to formation of sclerotic lesions of the temporal bone. Encroachment of these lesions on to the footplate of the stapes in the middle ear leads to stapes fixation and subsequent conductive hearing loss. The hereditary nature of otosclerosis has long been recognised due to its recurrence within families, but its genetic aetiology is yet to be characterised. Although many familial linkage studies and candidate gene association studies to investigate the genetic nature of otosclerosis have been performed in recent years, progress in identifying disease causing genes has been slow. This is largely due to the highly heterogeneous nature of this condition. The research presented in this thesis examines the molecular and genetic basis of otosclerosis using two next generation sequencing technologies; RNA-sequencing and Whole Exome Sequencing. RNA–sequencing has provided human stapes transcriptomes for healthy and diseased stapes, and in combination with pathway analysis has helped identify genes and molecular processes dysregulated in otosclerotic tissue. Whole Exome Sequencing has been employed to investigate rare variants that segregate with otosclerosis in affected families, and has been followed by a variant filtering strategy, which has prioritised genes found to be dysregulated during RNA-sequencing.
  • Mito-Cytosolic Translational Balance Increased Cytoprotection And

    Mito-Cytosolic Translational Balance Increased Cytoprotection And

    Graphical Abstract Worms Human cells Mice Mito-cytosolic translational balance Genetically mrps-5 RNAi Mitochondrial Cytosolic ribosomes ribosomes ATF4/atf-5 Doxycycline Pharmacologically Increased cytoprotection and longevity Manuscript A conserved mito-cytosolic translational balance links two longevity pathways Marte Molenaars1*, Georges E. Janssens1*, Evan G. Williams2, Aldo Jongejan3, Jiayi Lan2, Sylvie Rabot4, Fatima Joly4, Perry D. Moerland3, Bauke V. Schomakers1,5, Marco Lezzerini1 Yasmine J. Liu1, Mark A. McCormick6,7, Brian K. Kennedy8,9, Michel van Weeghel1,5, Antoine H.C. van Kampen3, Ruedi Aebersold2,10, Alyson W. MacInnes1, Riekelt H. Houtkooper1,11# 1Laboratory Genetic Metabolic Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands 2Institute of Molecular Systems Biology, ETH Zurich, Zürich, Switzerland 3Bioinformatics Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands 4Micalis Institute, INRA, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France 5Core Facility Metabolomics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands. 6 Department of Biochemistry and Molecular Biology, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, USA 7Autophagy, Inflammation, and Metabolism Center of Biological Research Excellence, University of New Mexico Health Sciences Center, Albuquerque, USA 8Buck Institute for Research on Aging, Novato, USA 9Departments
  • Sox2-RNA Mechanisms of Chromosome Topological Control in Developing Forebrain

    Sox2-RNA Mechanisms of Chromosome Topological Control in Developing Forebrain

    bioRxiv preprint doi: https://doi.org/10.1101/2020.09.22.307215; this version posted September 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Title: Sox2-RNA mechanisms of chromosome topological control in developing forebrain Ivelisse Cajigas1, Abhijit Chakraborty2, Madison Lynam1, Kelsey R Swyter1, Monique Bastidas1, Linden Collens1, Hao Luo1, Ferhat Ay2,3, Jhumku D. Kohtz1,4 1Department of Pediatrics, Northwestern University, Feinberg School of Medicine, Department of Human Molecular Genetics, Stanley Manne Children's Research Institute 2430 N Halsted, Chicago, IL 60614 2Centers for Autoimmunity and Cancer Immunotherapy, La Jolla Institute for Immunology, 9420 Athena Circle, La Jolla, CA, 92037, USA 3School of Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA 4To whom correspondence should be addressed: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.09.22.307215; this version posted September 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Summary Precise regulation of gene expression networks requires the selective targeting of DNA enhancers. The Evf2 long non-coding RNA regulates Dlx5/6 ultraconserved enhancer(UCE) interactions with long-range target genes, controlling gene expression over a 27Mb region in mouse developing forebrain. Here, we show that Evf2 long range gene repression occurs through multi-step mechanisms involving the transcription factor Sox2, a component of the Evf2 ribonucleoprotein complex (RNP).
  • Proteomics Provides Insights Into the Inhibition of Chinese Hamster V79

    Proteomics Provides Insights Into the Inhibition of Chinese Hamster V79

    www.nature.com/scientificreports OPEN Proteomics provides insights into the inhibition of Chinese hamster V79 cell proliferation in the deep underground environment Jifeng Liu1,2, Tengfei Ma1,2, Mingzhong Gao3, Yilin Liu4, Jun Liu1, Shichao Wang2, Yike Xie2, Ling Wang2, Juan Cheng2, Shixi Liu1*, Jian Zou1,2*, Jiang Wu2, Weimin Li2 & Heping Xie2,3,5 As resources in the shallow depths of the earth exhausted, people will spend extended periods of time in the deep underground space. However, little is known about the deep underground environment afecting the health of organisms. Hence, we established both deep underground laboratory (DUGL) and above ground laboratory (AGL) to investigate the efect of environmental factors on organisms. Six environmental parameters were monitored in the DUGL and AGL. Growth curves were recorded and tandem mass tag (TMT) proteomics analysis were performed to explore the proliferative ability and diferentially abundant proteins (DAPs) in V79 cells (a cell line widely used in biological study in DUGLs) cultured in the DUGL and AGL. Parallel Reaction Monitoring was conducted to verify the TMT results. γ ray dose rate showed the most detectable diference between the two laboratories, whereby γ ray dose rate was signifcantly lower in the DUGL compared to the AGL. V79 cell proliferation was slower in the DUGL. Quantitative proteomics detected 980 DAPs (absolute fold change ≥ 1.2, p < 0.05) between V79 cells cultured in the DUGL and AGL. Of these, 576 proteins were up-regulated and 404 proteins were down-regulated in V79 cells cultured in the DUGL. KEGG pathway analysis revealed that seven pathways (e.g.
  • Solution Structure of the GUCT Domain from Human RNA Helicase II/Gu[Beta]

    Solution Structure of the GUCT Domain from Human RNA Helicase II/Gu[Beta]

    proteins STRUCTURE O FUNCTION O BIOINFORMATICS Solution structure of the GUCT domain from human RNA helicase II/Gub reveals the RRM fold, but implausible RNA interactions Satoshi Ohnishi,1 Kimmo Pa¨a¨kko¨nen,1 Seizo Koshiba,1 Naoya Tochio,1 Manami Sato,1 Naohiro Kobayashi,1 Takushi Harada,1 Satoru Watanabe,1 Yutaka Muto,1 Peter Gu¨ntert,1 Akiko Tanaka,1 Takanori Kigawa,1,2 and Shigeyuki Yokoyama1,3* 1 Systems and Structural Biology Center, RIKEN, Tsurumi, Yokohama 230-0045, Japan 2 Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Midori-ku, Yokohama 226-8503, Japan 3 Department of Biophysics and Biochemistry, Graduate School of Science, The University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan INTRODUCTION ABSTRACT a a a a Human RNA helicase II/Gu (RH-II/Gu or Deadbox Human RNA helicase II/Gu (RH-II/Gu ) and RNA helicase protein 21) is a multifunctional enzyme that unwinds dou- II/Gub (RH-II/Gub) are paralogues that share the same ble-stranded RNA in the 50 to 30 direction and folds single- domain structure, consisting of the DEAD box helicase 1–5 domain (DEAD), the helicase conserved C-terminal domain stranded RNA in an ATP-dependent manner. These (helicase_C), and the GUCT domain. The N-terminal regions RNA-unwinding and RNA-folding activities are independ- of the RH-II/Gu proteins, including the DEAD domain and ent, and they reside in distinct regions of the protein. The the helicase_C domain, unwind double-stranded RNAs. The RNA helicase activity is catalyzed by the N-terminal three- 1 C-terminal tail of RH-II/Gua, which follows the GUCT do- quarters of the molecule in the presence of Mg2 , where as main, folds a single RNA strand, while that of RH-II/Gub the RNA-foldase activity is located in the C-terminal region 1 does not, and the GUCT domain is not essential for either and functions in a Mg2 independent manner.2 As shown the RNA helicase or foldase activity.
  • Integrated Analysis of Differentially Expressed Genes in Breast Cancer Pathogenesis

    Integrated Analysis of Differentially Expressed Genes in Breast Cancer Pathogenesis

    2560 ONCOLOGY LETTERS 9: 2560-2566, 2015 Integrated analysis of differentially expressed genes in breast cancer pathogenesis DAOBAO CHEN and HONGJIAN YANG Department of Breast Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang 310022, P.R. China Received October 20, 2014; Accepted March 10, 2015 DOI: 10.3892/ol.2015.3147 Abstract. The present study aimed to detect the differences ducts or from the lobules that supply the ducts (1). Breast between breast cancer cells and normal breast cells, and inves- cancer affects ~1.2 million women worldwide and accounts tigate the potential pathogenetic mechanisms of breast cancer. for ~50,000 mortalities every year (2). Despite major advances The sample GSE9574 series was downloaded, and the micro- in surgical and nonsurgical management of the disease, breast array data was analyzed to identify differentially expressed cancer metastasis remains a significant clinical challenge genes (DEGs). Gene Ontology (GO) cluster analysis using affecting numerous of patients (3). The prognosis and survival the GO Enrichment Analysis Software Toolkit platform and rates for breast cancer are highly variable, and depend on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway the cancer type, treatment strategy, stage of the disease and analysis for DEGs was conducted using the Gene Set Analysis geographical location of the patient (4). Toolkit V2. In addition, a protein-protein interaction (PPI) Microarray technology, which may be used to simultane- network was constructed, and target sites of potential transcrip- ously interrogate 10,000-40,000 genes, has provided new tion factors and potential microRNA (miRNA) molecules were insight into the molecular classification of different cancer screened.
  • Mitochondrial Misreading in Skeletal Muscle Accelerates Metabolic Aging and Confers Lipid Accumulation and Increased Inflammation

    Mitochondrial Misreading in Skeletal Muscle Accelerates Metabolic Aging and Confers Lipid Accumulation and Increased Inflammation

    Downloaded from rnajournal.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press REPORT Mitochondrial misreading in skeletal muscle accelerates metabolic aging and confers lipid accumulation and increased inflammation DIMITRI SHCHERBAKOV,1,4 STEFAN DUSCHA,1,4 REDA JUSKEVICIENE,1 LISA M. RESTELLI,2 STEPHAN FRANK,2 ENDRE LACZKO,3 and ERIK C. BÖTTGER1 1Institut für Medizinische Mikrobiologie, Universität Zürich, 8006 Zürich, Switzerland 2Division of Neuropathology, Institute of Medical Genetics and Pathology, Basel University Hospital, 4031 Basel, Switzerland 3Functional Genomics Center Zurich, ETH Zürich und Universität Zürich, 8057 Zürich, Switzerland ABSTRACT We have recently reported on an experimental model of mitochondrial mistranslation conferred by amino acid exchange V338Y in mitochondrial ribosomal protein MrpS5. Here we used a combination of RNA-seq and metabolic profiling of ho- mozygous transgenic Mrps5V338Y/V338Y mice to analyze the changes associated with the V338Y mutation in postmitotic skeletal muscle. Metabolome analysis demonstrated enhanced levels of age-associated metabolites in the mutant V338Y animals accompanied by increased glycolysis, lipid desaturation and eicosanoid biosynthesis, and alterations of the pentose phosphate pathway. In addition, transcriptome signatures of aged V338Y mutant muscle pointed to elevated inflammation, likely reflecting the increased levels of bioactive lipids. Our findings indicate that mistranslation-mediated impairment of mitochondrial function affects specific bioenergetic processes in muscle in an age-dependent manner. Keywords: mitochondria; misreading; skeletal muscle; aging; metabolome INTRODUCTION express a mtDNA mutator phenotype, with a threefold to fivefold increase in the levels of random point mutations A decline in mitochondrial function has been associated in mtDNA, display respiratory chain dysfunction and fea- with aging and complex age-related changes in metabo- tures of accelerated aging (Trifunovic et al.