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Genome-Wide Analysis of 5-Hmc in the Peripheral Blood of Systemic Lupus Erythematosus Patients Using an Hmedip-Chip
INTERNATIONAL JOURNAL OF MOLECULAR MEDICINE 35: 1467-1479, 2015 Genome-wide analysis of 5-hmC in the peripheral blood of systemic lupus erythematosus patients using an hMeDIP-chip WEIGUO SUI1*, QIUPEI TAN1*, MING YANG1, QIANG YAN1, HUA LIN1, MINGLIN OU1, WEN XUE1, JIEJING CHEN1, TONGXIANG ZOU1, HUANYUN JING1, LI GUO1, CUIHUI CAO1, YUFENG SUN1, ZHENZHEN CUI1 and YONG DAI2 1Guangxi Key Laboratory of Metabolic Diseases Research, Central Laboratory of Guilin 181st Hospital, Guilin, Guangxi 541002; 2Clinical Medical Research Center, the Second Clinical Medical College of Jinan University (Shenzhen People's Hospital), Shenzhen, Guangdong 518020, P.R. China Received July 9, 2014; Accepted February 27, 2015 DOI: 10.3892/ijmm.2015.2149 Abstract. Systemic lupus erythematosus (SLE) is a chronic, Introduction potentially fatal systemic autoimmune disease characterized by the production of autoantibodies against a wide range Systemic lupus erythematosus (SLE) is a typical systemic auto- of self-antigens. To investigate the role of the 5-hmC DNA immune disease, involving diffuse connective tissues (1) and modification with regard to the onset of SLE, we compared is characterized by immune inflammation. SLE has a complex the levels 5-hmC between SLE patients and normal controls. pathogenesis (2), involving genetic, immunologic and envi- Whole blood was obtained from patients, and genomic DNA ronmental factors. Thus, it may result in damage to multiple was extracted. Using the hMeDIP-chip analysis and valida- tissues and organs, especially the kidneys (3). SLE arises from tion by quantitative RT-PCR (RT-qPCR), we identified the a combination of heritable and environmental influences. differentially hydroxymethylated regions that are associated Epigenetics, the study of changes in gene expression with SLE. -
Propranolol-Mediated Attenuation of MMP-9 Excretion in Infants with Hemangiomas
Supplementary Online Content Thaivalappil S, Bauman N, Saieg A, Movius E, Brown KJ, Preciado D. Propranolol-mediated attenuation of MMP-9 excretion in infants with hemangiomas. JAMA Otolaryngol Head Neck Surg. doi:10.1001/jamaoto.2013.4773 eTable. List of All of the Proteins Identified by Proteomics This supplementary material has been provided by the authors to give readers additional information about their work. © 2013 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/01/2021 eTable. List of All of the Proteins Identified by Proteomics Protein Name Prop 12 mo/4 Pred 12 mo/4 Δ Prop to Pred mo mo Myeloperoxidase OS=Homo sapiens GN=MPO 26.00 143.00 ‐117.00 Lactotransferrin OS=Homo sapiens GN=LTF 114.00 205.50 ‐91.50 Matrix metalloproteinase‐9 OS=Homo sapiens GN=MMP9 5.00 36.00 ‐31.00 Neutrophil elastase OS=Homo sapiens GN=ELANE 24.00 48.00 ‐24.00 Bleomycin hydrolase OS=Homo sapiens GN=BLMH 3.00 25.00 ‐22.00 CAP7_HUMAN Azurocidin OS=Homo sapiens GN=AZU1 PE=1 SV=3 4.00 26.00 ‐22.00 S10A8_HUMAN Protein S100‐A8 OS=Homo sapiens GN=S100A8 PE=1 14.67 30.50 ‐15.83 SV=1 IL1F9_HUMAN Interleukin‐1 family member 9 OS=Homo sapiens 1.00 15.00 ‐14.00 GN=IL1F9 PE=1 SV=1 MUC5B_HUMAN Mucin‐5B OS=Homo sapiens GN=MUC5B PE=1 SV=3 2.00 14.00 ‐12.00 MUC4_HUMAN Mucin‐4 OS=Homo sapiens GN=MUC4 PE=1 SV=3 1.00 12.00 ‐11.00 HRG_HUMAN Histidine‐rich glycoprotein OS=Homo sapiens GN=HRG 1.00 12.00 ‐11.00 PE=1 SV=1 TKT_HUMAN Transketolase OS=Homo sapiens GN=TKT PE=1 SV=3 17.00 28.00 ‐11.00 CATG_HUMAN Cathepsin G OS=Homo -
Table 2. Significant
Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S. -
Defining Functional Interactions During Biogenesis of Epithelial Junctions
ARTICLE Received 11 Dec 2015 | Accepted 13 Oct 2016 | Published 6 Dec 2016 | Updated 5 Jan 2017 DOI: 10.1038/ncomms13542 OPEN Defining functional interactions during biogenesis of epithelial junctions J.C. Erasmus1,*, S. Bruche1,*,w, L. Pizarro1,2,*, N. Maimari1,3,*, T. Poggioli1,w, C. Tomlinson4,J.Lees5, I. Zalivina1,w, A. Wheeler1,w, A. Alberts6, A. Russo2 & V.M.M. Braga1 In spite of extensive recent progress, a comprehensive understanding of how actin cytoskeleton remodelling supports stable junctions remains to be established. Here we design a platform that integrates actin functions with optimized phenotypic clustering and identify new cytoskeletal proteins, their functional hierarchy and pathways that modulate E-cadherin adhesion. Depletion of EEF1A, an actin bundling protein, increases E-cadherin levels at junctions without a corresponding reinforcement of cell–cell contacts. This unexpected result reflects a more dynamic and mobile junctional actin in EEF1A-depleted cells. A partner for EEF1A in cadherin contact maintenance is the formin DIAPH2, which interacts with EEF1A. In contrast, depletion of either the endocytic regulator TRIP10 or the Rho GTPase activator VAV2 reduces E-cadherin levels at junctions. TRIP10 binds to and requires VAV2 function for its junctional localization. Overall, we present new conceptual insights on junction stabilization, which integrate known and novel pathways with impact for epithelial morphogenesis, homeostasis and diseases. 1 National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK. 2 Computing Department, Imperial College London, London SW7 2AZ, UK. 3 Bioengineering Department, Faculty of Engineering, Imperial College London, London SW7 2AZ, UK. 4 Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK. -
The Purification and Identification of Interactors to Elucidate Novel Connections in the HEK 293 Cell Line
The Purification and Identification of Interactors to Elucidate Novel Connections in the HEK 293 Cell Line Brett Hawley Biochemistry, Microbiology and Immunology Faculty of Medicine University of Ottawa © Brett Hawley, Ottawa, Canada, 2012 ABSTRACT The field of proteomics studies the structure and function of proteins in a large scale and high throughput manner. My work in the field of proteomics focuses on identifying interactions between proteins and discovering novel interactions. The identification of these interactions provides new information on metabolic and disease pathways and the working proteome of a cell. Cells are lysed and purified using antibody based affinity purification followed by digestion and identification using an HPLC coupled to a mass spectrometer. In my studies, I looked at the interaction networks of several AD related genes (Apolipoprotein E, Clusterin variant 1 and 2, Low-density lipoprotein receptor, Phosphatidylinositol binding clathrin assembly protein, Alpha- synuclein and Platelet-activating factor receptor) and an endosomal recycling pathway involved in cholesterol metabolism (Eps15 homology domain 1,2 and 4, Proprotein convertase subtilisin/kexin type 9 and Low-density lipoprotein receptor). Several novel and existing interactors were identified and these interactions were validated using co-immunopurification, which could be the basis for future research. ii ACKNOWLEDGEMENTS I would like to take this opportunity to thank my supervisor, Dr. Daniel Figeys, for his support and guidance throughout my studies in his lab. It was a great experience to work in his lab and I am very thankful I was given the chance to learn and work under him. I would also like to thank the members of my lab for all their assistance in learning new techniques and equipment in the lab. -
Absence of NEFL in Patient-Specific Neurons in Early-Onset Charcot-Marie-Tooth Neuropathy Markus T
ARTICLE OPEN ACCESS Absence of NEFL in patient-specific neurons in early-onset Charcot-Marie-Tooth neuropathy Markus T. Sainio, MSc, Emil Ylikallio, MD, PhD, Laura M¨aenp¨a¨a, MSc, Jenni Lahtela, PhD, Pirkko Mattila, PhD, Correspondence Mari Auranen, MD, PhD, Johanna Palmio, MD, PhD, and Henna Tyynismaa, PhD Dr. Tyynismaa [email protected] Neurol Genet 2018;4:e244. doi:10.1212/NXG.0000000000000244 Abstract Objective We used patient-specific neuronal cultures to characterize the molecular genetic mechanism of recessive nonsense mutations in neurofilament light (NEFL) underlying early-onset Charcot- Marie-Tooth (CMT) disease. Methods Motor neurons were differentiated from induced pluripotent stem cells of a patient with early- onset CMT carrying a novel homozygous nonsense mutation in NEFL. Quantitative PCR, protein analytics, immunocytochemistry, electron microscopy, and single-cell transcriptomics were used to investigate patient and control neurons. Results We show that the recessive nonsense mutation causes a nearly total loss of NEFL messenger RNA (mRNA), leading to the complete absence of NEFL protein in patient’s cultured neurons. Yet the cultured neurons were able to differentiate and form neuronal networks and neuro- filaments. Single-neuron gene expression fingerprinting pinpointed NEFL as the most down- regulated gene in the patient neurons and provided data of intermediate filament transcript abundancy and dynamics in cultured neurons. Blocking of nonsense-mediated decay partially rescued the loss of NEFL mRNA. Conclusions The strict neuronal specificity of neurofilament has hindered the mechanistic studies of re- cessive NEFL nonsense mutations. Here, we show that such mutation leads to the absence of NEFL, causing childhood-onset neuropathy through a loss-of-function mechanism. -
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. -
Dependent Traits in Mice Models of Hyperthyroidism and Hypothyroidism
Phenotypical characterization of sex- dependent traits in mice models of hyperthyroidism and hypothyroidism Inaugural-Dissertation zur Erlangung des Doktorgrades Dr. rer. nat. der Fakultät für Biologie an der Universität Duisburg-Essen vorgelegt von Helena Rakov aus St. Petropawlowsk April 2017 Die der vorliegenden Arbeit zugrunde liegenden Experimente wurden am Universitätsklinikum Essen in der Klinik für Endokrinologie und Stoffwechselerkrankungen durchgeführt. 1. Gutachter: Prof. Dr. Dr. Dagmar Führer-Sakel 2. Gutachter: Prof. Dr. Elke Cario Vorsitzender des Prüfungsausschusses: Prof. Dr. Ruth Grümmer Tag der mündlichen Prüfung: 17.07.2017 Publications Publications Engels Kathrin*, Rakov Helena *, Zwanziger Denise, Moeller Lars C., Homuth Georg, Köhrle Josef, Brix Klaudia, Fuhrer Dagmar. Differences in mouse hepatic thyroid hormone transporter expression with age and hyperthyroidism. Eur Thyroid J 2015;4(suppl 1):81–86. DOI: 10.1159/000381020. *contributed equally Zwanziger Denise*, Rakov Helena*, Engels Kathrin, Moeller Lars C., Fuhrer Dagmar. Sex-dependent claudin-1 expression in liver of eu- and hypothyroid mice. Eur Thyroid J. 2015 Sep; 4(Suppl 1): 67–73. DOI: 10.1159/000431316. *contributed equally Engels Kathrin*, Rakov Helena*, Zwanziger Denise, Hoenes Georg Sebastian, Rehders Maren, Brix Klaudia, Koehrle Josef, Moeller Lars Christian, Fuhrer Dagmar. Efficacy of protocols for induction of chronic hyperthyroidism in male and female mice. Endocrine. 2016 Oct;54(1):47-54. DOI: 10.1007/s12020-016-1020-8. Rakov Helena*, Engels Kathrin*, Hönes Georg Sebastian, Strucksberg Karl-Heinz, Moeller Lars Christian, Köhrle Josef, Zwanziger Denise, Führer Dagmar. Sex-specific phenotypes of hyperthyroidism and hypothyroidism in mice. Biol Sex Differ. 2016 Aug 24;7(1):36. DOI: 10.1186/s13293-016-0089-3. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Ten Commandments for a Good Scientist
Unravelling the mechanism of differential biological responses induced by food-borne xeno- and phyto-estrogenic compounds Ana María Sotoca Covaleda Wageningen 2010 Thesis committee Thesis supervisors Prof. dr. ir. Ivonne M.C.M. Rietjens Professor of Toxicology Wageningen University Prof. dr. Albertinka J. Murk Personal chair at the sub-department of Toxicology Wageningen University Thesis co-supervisor Dr. ir. Jacques J.M. Vervoort Associate professor at the Laboratory of Biochemistry Wageningen University Other members Prof. dr. Michael R. Muller, Wageningen University Prof. dr. ir. Huub F.J. Savelkoul, Wageningen University Prof. dr. Everardus J. van Zoelen, Radboud University Nijmegen Dr. ir. Toine F.H. Bovee, RIKILT, Wageningen This research was conducted under the auspices of the Graduate School VLAG Unravelling the mechanism of differential biological responses induced by food-borne xeno- and phyto-estrogenic compounds Ana María Sotoca Covaleda Thesis submitted in fulfillment of the requirements for the degree of doctor at Wageningen University by the authority of the Rector Magnificus Prof. dr. M.J. Kropff, in the presence of the Thesis Committee appointed by the Academic Board to be defended in public on Tuesday 14 September 2010 at 4 p.m. in the Aula Unravelling the mechanism of differential biological responses induced by food-borne xeno- and phyto-estrogenic compounds. Ana María Sotoca Covaleda Thesis Wageningen University, Wageningen, The Netherlands, 2010, With references, and with summary in Dutch. ISBN: 978-90-8585-707-5 “Caminante no hay camino, se hace camino al andar. Al andar se hace camino, y al volver la vista atrás se ve la senda que nunca se ha de volver a pisar” - Antonio Machado – A mi madre. -
G Protein-Coupled Receptors
www.aladdin-e.com Address:800 S Wineville Avenue, Ontario, CA 91761,USA Website:www.aladdin-e.com Email USA: [email protected] Email EU: [email protected] Email Asia Pacific: [email protected] G PROTEIN-COUPLED RECEPTORS Overview: The completion of the Human Genome Project allowed the identification of a large family of proteins with a common motif of seven groups of 20–24 hydrophobic amino acids arranged as a-helices. Approximately 800 of these seven transmembrane (7TM) receptors have been identified of which over 300 are non-olfactory receptors (see Fredriksson et al., 2003; Lagerstrom and Schioth, 2008). Subdivision on the basis of sequence homology allows the definition of rhodopsin, secretin, adhesion, glutamate and Frizzled receptor families. NC-IUPHAR recognizes Classes A, B, and C, which equate to the rhodopsin, secretin, and glutamate receptor families. The nomenclature of 7TM receptors is commonly used interchangeably with G protein-coupled receptors (GPCR), although the former nomenclature recognises signalling of 7TM receptors through pathways not involving G proteins. For example, adiponectin and membrane progestin receptors have some sequence homology to 7TM receptors but signal independently of G proteins and appear to reside in membranes in an inverted fashion compared to conventional GPCR. Additionally, the NPR-C natriuretic peptide receptor (see Page S195) has a single transmembrane domain structure, but appears to couple to G proteins to generate cellular responses. The 300+ non-olfactory GPCR are the targets for the majority of drugs in clinical usage (Overington et al., 2006), although only a minority of these receptors are exploited therapeutically. -
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