DOCSLIB.ORG

Molecular Identification of the Volume-Regulated Anion Channel VRAC

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Molecular Identification of the Volume-Regulated Anion Channel VRAC Molecular identification of the volume-regulated anion channel VRAC by a genome-wide siRNA screen Inaugural-Dissertation to obtain the academic degree Doctor rerum naturalium (Dr. rer. nat.) Submitted to the Department of Biology, Chemistry and Pharmacy of the Freie Universität Berlin by Felizia Katharina Voß from Heidelberg Berlin 2014 This work was prepared under the supervision of Prof. Dr. Dr. Thomas J. Jentsch at the Max-Delbrück-Centrum für Molekulare Medizin (MDC) and the Leibniz- Institut für molekulare Pharmakologie (FMP) in Berlin. 15.10.2010 – 21.10.2014 1. Gutachter: Prof. Dr. Dr. Thomas Jentsch 2. Gutachter: Prof. Dr. Volker Haucke Tag der Disputation: 25.2.2015 Preface Part of this work has been published in: Voss F.K., Ullrich F., Münch J., Lazarow K., Lutter D., Mah N., Andrade-Navarro M.A., von Kries J.P., Stauber T., Jentsch T.J. (2014). Identification of LRRC8 Heteromers as an Essential Component of the Volume- Regulated Anion Channel VRAC. Science Vol. 344 no. 6184 pp. 634-638. http://dx.doi.org/10.1126/science.1252826 Part of the experimental data shown in this work were produced by Dr. Tobias Stauber, Florian Ullrich and Jonas Münch. Dr. Tobias Stauber performed the immunostainings and microscopy for the topology determination. Florian Ullrich and Jonas Münch performed and evaluated the whole-cell patch-clamp measurements. Dr. Katina Lazarow of the FMP Screening Unit assisted in the upscaling of the YFP-assay and siRNA transfection to the high-throughput format. Dr. Nancy Mah performed the bioinformatics analysis of the primary screening data. Table of Contents List of Figures ............................................................................................................................... III List of Tables ................................................................................................................................ III List of Abbreviations .................................................................................................................... IV Abstract ........................................................................................................................................... 1 Zusammenfassung .......................................................................................................................... 2 1. Introduction ................................................................................................................................ 3 1.1 Cell volume regulation ........................................................................................................... 3 1.2 Biophysical and pharmacological properties of VRAC/ I Cl(swell) ............................................ 6 1.3 (Postulated) regulatory mechanisms of VRAC activity ......................................................... 7 1.4 Proposed (patho-) physiological importance of VRAC ....................................................... 11 1.5 Former candidates for the molecular identity of VRAC ...................................................... 15 1.6 The LRRC8 protein family .................................................................................................. 18 2. Aim of the work ........................................................................................................................ 21 3. Materials and Methods ............................................................................................................ 23 3.1 Materials ............................................................................................................................... 23 3.1.1 Chemicals ...................................................................................................................... 23 3.1.2 Cell lines........................................................................................................................ 23 3.1.3 Cell culture reagents ...................................................................................................... 23 3.1.4 Genome-wide siRNA library ........................................................................................ 23 3.1.5 Expression constructs .................................................................................................... 24 3.1.6 Commercial antibodies .................................................................................................. 24 3.1.7 Lab-generated antibodies .............................................................................................. 24 3.2 Methods ................................................................................................................................ 25 3.2.1 Generation of the HEK293-YFP Cell Line ................................................................... 25 3.2.2 Plate layout and control siRNAs ................................................................................... 26 3.2.3 High-throughput siRNA transfection ............................................................................ 26 3.2.4 YFP-based screening-assay ........................................................................................... 27 3.2.5 Bioinformatics analysis and hit assessment .................................................................. 28 3.2.6 Cloning and mutagenesis of candidate constructs ......................................................... 30 3.2.7 Electrophysiology ......................................................................................................... 31 3.2.8 Deglycosylation experiments ........................................................................................ 33 3.2.9 Co-immunoprecipitation, SDS-Page and Western blots ............................................... 33 3.2.10 Immunocytochemistry ................................................................................................. 35 3.2.11 Quantitative RT-PCR .................................................................................................. 35 I 3.2.12 Generation of monoclonal knockout cell lines using the CRISPR/Cas and zinc finger nuclease Technologies ........................................................................................................... 36 3.2.13 RVD Measurements .................................................................................................... 37 4. Results ....................................................................................................................................... 38 4.1 Assay set-up and up-scaling to high-throughput format ...................................................... 38 4.2. Prescreen ............................................................................................................................. 42 4.3 Genome-wide siRNA screen ................................................................................................ 44 4.4 Secondary screen .................................................................................................................. 47 4.5 Electrophysiological measurements of LRRC8A knockdown and overexpression ............. 49 4.6 Subcellular localization and trafficking of LRRC8 proteins ................................................ 50 4.7 Verification of the transmembrane topology of LRRC8A ................................................... 51 4.8 Heteromerization of LRRC8A with the other members of the LRRC8 protein family ....... 53 4.9 Generation of LRRC8 knockout cell lines ........................................................................... 55 4.10 Electrophysiological measurements of LRRC8 knockout cell lines .................................. 59 4.11 Inactivation kinetics in the reconstituted LRRC8 quintuple knockout .............................. 61 4.12 Differences in inactivation kinetics coincide with endogenous subunit expression .......... 62 4.13 LRRC8A as an essential component of regulatory volume decrease (RVD) .................... 63 5. Discussion .................................................................................................................................. 64 5.1 The genome-wide siRNA screen as superior approach for the identification of VRAC ..... 64 5.2 LRRC8A is essential for VRAC activity ............................................................................. 68 5.3 Heteromerization of LRRC8 proteins .................................................................................. 69 5.4 Evidence for a heteromeric LRRC8 channel complex ......................................................... 71 5.5 The molecular identity of VRAC from an evolutionary perspective ................................... 72 5.6 Transport of other osmolytes and substances through VRAC ............................................. 74 5.7 Possible regulatory sites in LRRC8 proteins ........................................................................ 78 5.8 Are we missing something? - The possibility of a limiting auxiliary subunit ...................... 79 5.9 Possible physiological significance of LRRC8 proteins ...................................................... 81 5.10 Expression pattern of LRRC8 proteins – a key to functional diversity? ............................ 85 6. References ................................................................................................................................. 87 7. Acknowledgements ................................................................................................................... 99 II List
Load more

Recommended publications
  • The Sensors of the Pain Pathway
    Nociceptors: the sensors of the pain pathway Adrienne E. Dubin, Ardem Patapoutian J Clin Invest. 2010;120(11):3760-3772. https://doi.org/10.1172/JCI42843. Review Series Specialized peripheral sensory neurons known as nociceptors alert us to potentially damaging stimuli at the skin by detecting extremes in temperature and pressure and injury-related chemicals, and transducing these stimuli into long- ranging electrical signals that are relayed to higher brain centers. The activation of functionally distinct cutaneous nociceptor populations and the processing of information they convey provide a rich diversity of pain qualities. Current work in this field is providing researchers with a more thorough understanding of nociceptor cell biology at molecular and systems levels and insight that will allow the targeted design of novel pain therapeutics. Find the latest version: https://jci.me/42843/pdf Review series Nociceptors: the sensors of the pain pathway Adrienne E. Dubin1 and Ardem Patapoutian1,2 1Department of Cell Biology, The Scripps Research Institute, La Jolla, California, USA. 2Genomics Institute of the Novartis Research Foundation, San Diego, California, USA. Specialized peripheral sensory neurons known as nociceptors alert us to potentially damaging stimuli at the skin by detecting extremes in temperature and pressure and injury-related chemicals, and transducing these stimuli into long-ranging electrical signals that are relayed to higher brain centers. The activation of functionally distinct cutaneous nociceptor populations and the processing of information they convey provide a rich diversity of pain qualities. Current work in this field is providing researchers with a more thorough understanding of nociceptor cell biology at molecular and systems levels and insight that will allow the targeted design of novel pain therapeutics.
    [Show full text]
  • Supplemental Figure 1. Vimentin
    Double mutant specific genes Transcript gene_assignment Gene Symbol RefSeq FDR Fold- FDR Fold- FDR Fold- ID (single vs. Change (double Change (double Change wt) (single vs. wt) (double vs. single) (double vs. wt) vs. wt) vs. single) 10485013 BC085239 // 1110051M20Rik // RIKEN cDNA 1110051M20 gene // 2 E1 // 228356 /// NM 1110051M20Ri BC085239 0.164013 -1.38517 0.0345128 -2.24228 0.154535 -1.61877 k 10358717 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 /// BC 1700025G04Rik NM_197990 0.142593 -1.37878 0.0212926 -3.13385 0.093068 -2.27291 10358713 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 1700025G04Rik NM_197990 0.0655213 -1.71563 0.0222468 -2.32498 0.166843 -1.35517 10481312 NM_027283 // 1700026L06Rik // RIKEN cDNA 1700026L06 gene // 2 A3 // 69987 /// EN 1700026L06Rik NM_027283 0.0503754 -1.46385 0.0140999 -2.19537 0.0825609 -1.49972 10351465 BC150846 // 1700084C01Rik // RIKEN cDNA 1700084C01 gene // 1 H3 // 78465 /// NM_ 1700084C01Rik BC150846 0.107391 -1.5916 0.0385418 -2.05801 0.295457 -1.29305 10569654 AK007416 // 1810010D01Rik // RIKEN cDNA 1810010D01 gene // 7 F5 // 381935 /// XR 1810010D01Rik AK007416 0.145576 1.69432 0.0476957 2.51662 0.288571 1.48533 10508883 NM_001083916 // 1810019J16Rik // RIKEN cDNA 1810019J16 gene // 4 D2.3 // 69073 / 1810019J16Rik NM_001083916 0.0533206 1.57139 0.0145433 2.56417 0.0836674 1.63179 10585282 ENSMUST00000050829 // 2010007H06Rik // RIKEN cDNA 2010007H06 gene // --- // 6984 2010007H06Rik ENSMUST00000050829 0.129914 -1.71998 0.0434862 -2.51672
    [Show full text]
  • Viewed Under 23 (B) Or 203 (C) fi M M Male Cko Mice, and Largely Unaffected Magni Cation; Scale Bars, 500 M (B) and 50 M (C)
    BRIEF COMMUNICATION www.jasn.org Renal Fanconi Syndrome and Hypophosphatemic Rickets in the Absence of Xenotropic and Polytropic Retroviral Receptor in the Nephron Camille Ansermet,* Matthias B. Moor,* Gabriel Centeno,* Muriel Auberson,* † † ‡ Dorothy Zhang Hu, Roland Baron, Svetlana Nikolaeva,* Barbara Haenzi,* | Natalya Katanaeva,* Ivan Gautschi,* Vladimir Katanaev,*§ Samuel Rotman, Robert Koesters,¶ †† Laurent Schild,* Sylvain Pradervand,** Olivier Bonny,* and Dmitri Firsov* BRIEF COMMUNICATION *Department of Pharmacology and Toxicology and **Genomic Technologies Facility, University of Lausanne, Lausanne, Switzerland; †Department of Oral Medicine, Infection, and Immunity, Harvard School of Dental Medicine, Boston, Massachusetts; ‡Institute of Evolutionary Physiology and Biochemistry, St. Petersburg, Russia; §School of Biomedicine, Far Eastern Federal University, Vladivostok, Russia; |Services of Pathology and ††Nephrology, Department of Medicine, University Hospital of Lausanne, Lausanne, Switzerland; and ¶Université Pierre et Marie Curie, Paris, France ABSTRACT Tight control of extracellular and intracellular inorganic phosphate (Pi) levels is crit- leaves.4 Most recently, Legati et al. have ical to most biochemical and physiologic processes. Urinary Pi is freely filtered at the shown an association between genetic kidney glomerulus and is reabsorbed in the renal tubule by the action of the apical polymorphisms in Xpr1 and primary fa- sodium-dependent phosphate transporters, NaPi-IIa/NaPi-IIc/Pit2. However, the milial brain calcification disorder.5 How- molecular identity of the protein(s) participating in the basolateral Pi efflux remains ever, the role of XPR1 in the maintenance unknown. Evidence has suggested that xenotropic and polytropic retroviral recep- of Pi homeostasis remains unknown. Here, tor 1 (XPR1) might be involved in this process. Here, we show that conditional in- we addressed this issue in mice deficient for activation of Xpr1 in the renal tubule in mice resulted in impaired renal Pi Xpr1 in the nephron.
    [Show full text]
  • The Mineralocorticoid Receptor Leads to Increased Expression of EGFR
    www.nature.com/scientificreports OPEN The mineralocorticoid receptor leads to increased expression of EGFR and T‑type calcium channels that support HL‑1 cell hypertrophy Katharina Stroedecke1,2, Sandra Meinel1,2, Fritz Markwardt1, Udo Kloeckner1, Nicole Straetz1, Katja Quarch1, Barbara Schreier1, Michael Kopf1, Michael Gekle1 & Claudia Grossmann1* The EGF receptor (EGFR) has been extensively studied in tumor biology and recently a role in cardiovascular pathophysiology was suggested. The mineralocorticoid receptor (MR) is an important efector of the renin–angiotensin–aldosterone‑system and elicits pathophysiological efects in the cardiovascular system; however, the underlying molecular mechanisms are unclear. Our aim was to investigate the importance of EGFR for MR‑mediated cardiovascular pathophysiology because MR is known to induce EGFR expression. We identifed a SNP within the EGFR promoter that modulates MR‑induced EGFR expression. In RNA‑sequencing and qPCR experiments in heart tissue of EGFR KO and WT mice, changes in EGFR abundance led to diferential expression of cardiac ion channels, especially of the T‑type calcium channel CACNA1H. Accordingly, CACNA1H expression was increased in WT mice after in vivo MR activation by aldosterone but not in respective EGFR KO mice. Aldosterone‑ and EGF‑responsiveness of CACNA1H expression was confrmed in HL‑1 cells by Western blot and by measuring peak current density of T‑type calcium channels. Aldosterone‑induced CACNA1H protein expression could be abrogated by the EGFR inhibitor AG1478. Furthermore, inhibition of T‑type calcium channels with mibefradil or ML218 reduced diameter, volume and BNP levels in HL‑1 cells. In conclusion the MR regulates EGFR and CACNA1H expression, which has an efect on HL‑1 cell diameter, and the extent of this regulation seems to depend on the SNP‑216 (G/T) genotype.
    [Show full text]
  • Table S1 the Four Gene Sets Derived from Gene Expression Profiles of Escs and Differentiated Cells
    Table S1 The four gene sets derived from gene expression profiles of ESCs and differentiated cells Uniform High Uniform Low ES Up ES Down EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol 269261 Rpl12 11354 Abpa 68239 Krt42 15132 Hbb-bh1 67891 Rpl4 11537 Cfd 26380 Esrrb 15126 Hba-x 55949 Eef1b2 11698 Ambn 73703 Dppa2 15111 Hand2 18148 Npm1 11730 Ang3 67374 Jam2 65255 Asb4 67427 Rps20 11731 Ang2 22702 Zfp42 17292 Mesp1 15481 Hspa8 11807 Apoa2 58865 Tdh 19737 Rgs5 100041686 LOC100041686 11814 Apoc3 26388 Ifi202b 225518 Prdm6 11983 Atpif1 11945 Atp4b 11614 Nr0b1 20378 Frzb 19241 Tmsb4x 12007 Azgp1 76815 Calcoco2 12767 Cxcr4 20116 Rps8 12044 Bcl2a1a 219132 D14Ertd668e 103889 Hoxb2 20103 Rps5 12047 Bcl2a1d 381411 Gm1967 17701 Msx1 14694 Gnb2l1 12049 Bcl2l10 20899 Stra8 23796 Aplnr 19941 Rpl26 12096 Bglap1 78625 1700061G19Rik 12627 Cfc1 12070 Ngfrap1 12097 Bglap2 21816 Tgm1 12622 Cer1 19989 Rpl7 12267 C3ar1 67405 Nts 21385 Tbx2 19896 Rpl10a 12279 C9 435337 EG435337 56720 Tdo2 20044 Rps14 12391 Cav3 545913 Zscan4d 16869 Lhx1 19175 Psmb6 12409 Cbr2 244448 Triml1 22253 Unc5c 22627 Ywhae 12477 Ctla4 69134 2200001I15Rik 14174 Fgf3 19951 Rpl32 12523 Cd84 66065 Hsd17b14 16542 Kdr 66152 1110020P15Rik 12524 Cd86 81879 Tcfcp2l1 15122 Hba-a1 66489 Rpl35 12640 Cga 17907 Mylpf 15414 Hoxb6 15519 Hsp90aa1 12642 Ch25h 26424 Nr5a2 210530 Leprel1 66483 Rpl36al 12655 Chi3l3 83560 Tex14 12338 Capn6 27370 Rps26 12796 Camp 17450 Morc1 20671 Sox17 66576 Uqcrh 12869 Cox8b 79455 Pdcl2 20613 Snai1 22154 Tubb5 12959 Cryba4 231821 Centa1 17897
    [Show full text]
  • Potassium Channels in Epilepsy
    Downloaded from http://perspectivesinmedicine.cshlp.org/ on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press Potassium Channels in Epilepsy Ru¨diger Ko¨hling and Jakob Wolfart Oscar Langendorff Institute of Physiology, University of Rostock, Rostock 18057, Germany Correspondence: [email protected] This review attempts to give a concise and up-to-date overview on the role of potassium channels in epilepsies. Their role can be defined from a genetic perspective, focusing on variants and de novo mutations identified in genetic studies or animal models with targeted, specific mutations in genes coding for a member of the large potassium channel family. In these genetic studies, a demonstrated functional link to hyperexcitability often remains elusive. However, their role can also be defined from a functional perspective, based on dy- namic, aggravating, or adaptive transcriptional and posttranslational alterations. In these cases, it often remains elusive whether the alteration is causal or merely incidental. With 80 potassium channel types, of which 10% are known to be associated with epilepsies (in humans) or a seizure phenotype (in animals), if genetically mutated, a comprehensive review is a challenging endeavor. This goal may seem all the more ambitious once the data on posttranslational alterations, found both in human tissue from epilepsy patients and in chronic or acute animal models, are included. We therefore summarize the literature, and expand only on key findings, particularly regarding functional alterations found in patient brain tissue and chronic animal models. INTRODUCTION TO POTASSIUM evolutionary appearance of voltage-gated so- CHANNELS dium (Nav)andcalcium (Cav)channels, Kchan- nels are further diversified in relation to their otassium (K) channels are related to epilepsy newer function, namely, keeping neuronal exci- Psyndromes on many different levels, ranging tation within limits (Anderson and Greenberg from direct control of neuronal excitability and 2001; Hille 2001).
    [Show full text]
  • Supplementary Table S1. Upregulated Genes Differentially
    Supplementary Table S1. Upregulated genes differentially expressed in athletes (p < 0.05 and 1.3-fold change) Gene Symbol p Value Fold Change 221051_s_at NMRK2 0.01 2.38 236518_at CCDC183 0.00 2.05 218804_at ANO1 0.00 2.05 234675_x_at 0.01 2.02 207076_s_at ASS1 0.00 1.85 209135_at ASPH 0.02 1.81 228434_at BTNL9 0.03 1.81 229985_at BTNL9 0.01 1.79 215795_at MYH7B 0.01 1.78 217979_at TSPAN13 0.01 1.77 230992_at BTNL9 0.01 1.75 226884_at LRRN1 0.03 1.74 220039_s_at CDKAL1 0.01 1.73 236520_at 0.02 1.72 219895_at TMEM255A 0.04 1.72 201030_x_at LDHB 0.00 1.69 233824_at 0.00 1.69 232257_s_at 0.05 1.67 236359_at SCN4B 0.04 1.64 242868_at 0.00 1.63 1557286_at 0.01 1.63 202780_at OXCT1 0.01 1.63 1556542_a_at 0.04 1.63 209992_at PFKFB2 0.04 1.63 205247_at NOTCH4 0.01 1.62 1554182_at TRIM73///TRIM74 0.00 1.61 232892_at MIR1-1HG 0.02 1.61 204726_at CDH13 0.01 1.6 1561167_at 0.01 1.6 1565821_at 0.01 1.6 210169_at SEC14L5 0.01 1.6 236963_at 0.02 1.6 1552880_at SEC16B 0.02 1.6 235228_at CCDC85A 0.02 1.6 1568623_a_at SLC35E4 0.00 1.59 204844_at ENPEP 0.00 1.59 1552256_a_at SCARB1 0.02 1.59 1557283_a_at ZNF519 0.02 1.59 1557293_at LINC00969 0.03 1.59 231644_at 0.01 1.58 228115_at GAREM1 0.01 1.58 223687_s_at LY6K 0.02 1.58 231779_at IRAK2 0.03 1.58 243332_at LOC105379610 0.04 1.58 232118_at 0.01 1.57 203423_at RBP1 0.02 1.57 AMY1A///AMY1B///AMY1C///AMY2A///AMY2B// 208498_s_at 0.03 1.57 /AMYP1 237154_at LOC101930114 0.00 1.56 1559691_at 0.01 1.56 243481_at RHOJ 0.03 1.56 238834_at MYLK3 0.01 1.55 213438_at NFASC 0.02 1.55 242290_at TACC1 0.04 1.55 ANKRD20A1///ANKRD20A12P///ANKRD20A2///
    [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]
  • Common Variants in KCNK5 and FHL5 Genes Contributed to The
    www.nature.com/scientificreports OPEN Common variants in KCNK5 and FHL5 genes contributed to the susceptibility of migraine without aura in Han Chinese population Zhao Jiang1,2,5, Longrui Zhao1,5, Xiaojie Zhang3, Wenjuan Zhang2, Yuxing Feng4 & Tao Li1* A recent genome-wide meta study suggested that rs67338227 in the FHL5 gene and rs10456100 in the KCNK5 gene are associated with migraine from 27 population-based cohorts excluding Chinese population. Given that migraine without aura (MO) is the most common subtype of migraine, our aim was to systematically investigate the relationship of common variants in FHL5 and KCNK5 genes with the susceptibility to MO and provide clues as to the nature of the mechanisms involved in the etiology of migraine. A total of 3306 subjects including 1042 patients with MO and 2264 controls were recruited for the discovery stage, and 2530 individuals including 842 patients with MO and 1688 controls for the replication stage. Twenty-two tag SNPs (7 from FHL5 and 15 from KCNK5) were selected for genotyping. Genetic associations were analyzed at both single-marker and haplotype levels. Potential functional consequences of the signifcant SNPs were analyzed using gene expression data obtained from the GTEx database. Two SNPs, rs10456100 (KCNK5, P = 9.01 × ­10–9) and rs7775721 (FHL5, P = 6.86 × ­10–13), were determined to be signifcantly associated with MO in the discovery sample and were then replicated in another sample. In the combined sample set, the T allele of both SNPs was signifcantly associated with the increased risk of MO. Signifcant eQTL signals were identifed for both SNP rs10456100 and rs7775721.
    [Show full text]
  • Circular RNA Hsa Circ 0005114‑Mir‑142‑3P/Mir‑590‑5P‑ Adenomatous
    ONCOLOGY LETTERS 21: 58, 2021 Circular RNA hsa_circ_0005114‑miR‑142‑3p/miR‑590‑5p‑ adenomatous polyposis coli protein axis as a potential target for treatment of glioma BO WEI1*, LE WANG2* and JINGWEI ZHAO1 1Department of Neurosurgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033; 2Department of Ophthalmology, The First Hospital of Jilin University, Jilin University, Changchun, Jilin 130021, P.R. China Received September 12, 2019; Accepted October 22, 2020 DOI: 10.3892/ol.2020.12320 Abstract. Glioma is the most common type of brain tumor APC expression with a good overall survival rate. UALCAN and is associated with a high mortality rate. Despite recent analysis using TCGA data of glioblastoma multiforme and the advances in treatment options, the overall prognosis in patients GSE25632 and GSE103229 microarray datasets showed that with glioma remains poor. Studies have suggested that circular hsa‑miR‑142‑3p/hsa‑miR‑590‑5p was upregulated and APC (circ)RNAs serve important roles in the development and was downregulated. Thus, hsa‑miR‑142‑3p/hsa‑miR‑590‑5p‑ progression of glioma and may have potential as therapeutic APC‑related circ/ceRNA axes may be important in glioma, targets. However, the expression profiles of circRNAs and their and hsa_circ_0005114 interacted with both of these miRNAs. functions in glioma have rarely been studied. The present study Functional analysis showed that hsa_circ_0005114 was aimed to screen differentially expressed circRNAs (DECs) involved in insulin secretion, while APC was associated with between glioma and normal brain tissues using sequencing the Wnt signaling pathway. In conclusion, hsa_circ_0005114‑ data collected from the Gene Expression Omnibus database miR‑142‑3p/miR‑590‑5p‑APC ceRNA axes may be potential (GSE86202 and GSE92322 datasets) and explain their mecha‑ targets for the treatment of glioma.
    [Show full text]
  • Transcriptomic Analysis of Native Versus Cultured Human and Mouse Dorsal Root Ganglia Focused on Pharmacological Targets Short
    bioRxiv preprint doi: https://doi.org/10.1101/766865; this version posted September 12, 2019. 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-ND 4.0 International license. Transcriptomic analysis of native versus cultured human and mouse dorsal root ganglia focused on pharmacological targets Short title: Comparative transcriptomics of acutely dissected versus cultured DRGs Andi Wangzhou1, Lisa A. McIlvried2, Candler Paige1, Paulino Barragan-Iglesias1, Carolyn A. Guzman1, Gregory Dussor1, Pradipta R. Ray1,#, Robert W. Gereau IV2, # and Theodore J. Price1, # 1The University of Texas at Dallas, School of Behavioral and Brain Sciences and Center for Advanced Pain Studies, 800 W Campbell Rd. Richardson, TX, 75080, USA 2Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine # corresponding authors [email protected], [email protected] and [email protected] Funding: NIH grants T32DA007261 (LM); NS065926 and NS102161 (TJP); NS106953 and NS042595 (RWG). The authors declare no conflicts of interest Author Contributions Conceived of the Project: PRR, RWG IV and TJP Performed Experiments: AW, LAM, CP, PB-I Supervised Experiments: GD, RWG IV, TJP Analyzed Data: AW, LAM, CP, CAG, PRR Supervised Bioinformatics Analysis: PRR Drew Figures: AW, PRR Wrote and Edited Manuscript: AW, LAM, CP, GD, PRR, RWG IV, TJP All authors approved the final version of the manuscript. 1 bioRxiv preprint doi: https://doi.org/10.1101/766865; this version posted September 12, 2019. 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]
  • Control Qpatch Htx Multi-Hole
    41577_Poster 170x110.qxd:Poster 170x110 07/04/10 8:52 Side 1 SOPHION BIOSCIENCE A/S SOPHION BIOSCIENCE, INC. SOPHION JAPAN Baltorpvej 154 675 US Highway One 1716-6, Shimmachi ENHANCING THROUGHPUT WITH MULTIPLE DK-2750 Ballerup North Brunswick, NJ 08902 Takasaki-shi, Gumma 370-1301 DENMARK USA JAPAN [email protected] Phone: +1 732 745 0221 Phone: +81 274 50 8388 CELL LINES PER WELL WITH THE QPATCH HTX www.sophion.com www.sophion.com www.sophion.com HERVØR LYKKE OLSEN l DORTHE NIELSEN l MORTEN SUNESEN QPATCH HTX MULTI-HOLE: TEMPORAL CURRENT QPATCH HTX MULTI-HOLE: PHARMACOLOGICAL SEPARATION BASED ON DISCRETE RECORDING SEPARATION BASED ON ION CHANNEL INHIBITORS TIME WINDOWS KvLQT1/minK (KCNQ1/KCNE1) INTRODUCTION Kv1.5 (KCNA5) ABRaw traces (A) and Hill plot (B) for XE991. ABC hERG and Nav1.5 blocked by E-4031 and The QPatch HTX automated patch clamp technology was developed to 1) increase throughput in ion channel drug TTX, respectively. screening by parallel operation of 48 multi-hole patch clamp sites, each comprising 10 individual patch clamp holes, in a single measurements site on a QPlate X, and 2) diminish problems with low-expressing cell lines. Thus, parallel recording from 10 cells represents a 10-fold signal amplification, and it increases the success rate at each site substantially. To further increase throughput we explored the possibility of simultaneous recording of a number of ion channel currents. IC50 (μM) XE991 Two or three cell lines, each expressing a specific ion channel, were applied at each site simultaneously. The ion channel Measured Literature currents were separated temporally or pharmacologically by proper choices of voltage protocols or ion channel KvLQT1 3.5±1.0 (n=12) 1-6 (Ref.
    [Show full text]