Genome-Wide Expression Profiling of Urinary Bladder Implicates Desmosomal and Cytoskeletal Dysregulation in the Bladder Exstrophy-Epispadias Complex
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Lectin-Affinity Chromatography Brain Glycoproteomics and Alzheimer
50 DOI 10.1002/prca.201000070 Proteomics Clin. Appl. 2011, 5, 50–56 REVIEW Lectin-affinity chromatography brain glycoproteomics and Alzheimer disease: Insights into protein alterations consistent with the pathology and progression of this dementing disorder D. Allan Butterfield and Joshua B. Owen Department of Chemistry, Center of Membrane Sciences, and Sanders-Brown Center on Aging, University of Kentucky, Lexington KY, USA Alzheimer disease (AD) is a neurodegenerative disorder characterized pathologically by the Received: July 7, 2010 accumulation of senile plaques and neurofibrillary tangles, and both these pathological Revised: August 4, 2010 hallmarks of AD are extensively modified by glycosylation. Mounting evidence shows that Accepted: August 10, 2010 alterations in glycosylation patterns influence the pathogenesis and progression of AD, but the vast number of glycan motifs and potential glycosylation sites of glycoproteins has made the field of glycobiology difficult. However, the advent of glycoproteomics has produced major strides in glycoprotein identification and glycosylation site mapping. The use of lectins, proteins that have strong affinity for specific carbohydrate epitopes, to enrich glycoprotein fractions coupled with modern MS, have yielded techniques to elucidate the glycoproteome in AD. Proteomic studies have identified brain proteins in AD and arguably the earliest form of AD, mild cognitive impairment, with altered affinity for Concanavalin-A and wheat germ agglutinin lectins that are consistent with the pathology and progression of this disorder. This is a relatively nascent field of proteomics research in brain, so future studies of lectin-based brain protein separations may lead to additional insights into AD pathogenesis and progression. Keywords: Alzheimers disease (AD) / Lectin-chromatography / Mild cognitive impairment (MCI) / MS / Synaptic alterations 1 Introduction ized pathologically by the accumulation of senile plaques (SPs) and neurofibrillary tangles (NFTs). -
Targeted Genes and Methodology Details for Neuromuscular Genetic Panels
Targeted Genes and Methodology Details for Neuromuscular Genetic Panels Reference transcripts based on build GRCh37 (hg19) interrogated by Neuromuscular Genetic Panels Next-generation sequencing (NGS) and/or Sanger sequencing is performed Motor Neuron Disease Panel to test for the presence of a mutation in these genes. Gene GenBank Accession Number Regions of homology, high GC-rich content, and repetitive sequences may ALS2 NM_020919 not provide accurate sequence. Therefore, all reported alterations detected ANG NM_001145 by NGS are confirmed by an independent reference method based on laboratory developed criteria. However, this does not rule out the possibility CHMP2B NM_014043 of a false-negative result in these regions. ERBB4 NM_005235 Sanger sequencing is used to confirm alterations detected by NGS when FIG4 NM_014845 appropriate.(Unpublished Mayo method) FUS NM_004960 HNRNPA1 NM_031157 OPTN NM_021980 PFN1 NM_005022 SETX NM_015046 SIGMAR1 NM_005866 SOD1 NM_000454 SQSTM1 NM_003900 TARDBP NM_007375 UBQLN2 NM_013444 VAPB NM_004738 VCP NM_007126 ©2018 Mayo Foundation for Medical Education and Research Page 1 of 14 MC4091-83rev1018 Muscular Dystrophy Panel Muscular Dystrophy Panel Gene GenBank Accession Number Gene GenBank Accession Number ACTA1 NM_001100 LMNA NM_170707 ANO5 NM_213599 LPIN1 NM_145693 B3GALNT2 NM_152490 MATR3 NM_199189 B4GAT1 NM_006876 MYH2 NM_017534 BAG3 NM_004281 MYH7 NM_000257 BIN1 NM_139343 MYOT NM_006790 BVES NM_007073 NEB NM_004543 CAPN3 NM_000070 PLEC NM_000445 CAV3 NM_033337 POMGNT1 NM_017739 CAVIN1 NM_012232 POMGNT2 -
Myosin Myth4-FERM Structures Highlight Important Principles of Convergent Evolution
Myosin MyTH4-FERM structures highlight important principles of convergent evolution Vicente José Planelles-Herreroa,b, Florian Blanca,c, Serena Sirigua, Helena Sirkiaa, Jeffrey Clausea, Yannick Souriguesa, Daniel O. Johnsrudd, Beatrice Amiguesa, Marco Cecchinic, Susan P. Gilberte, Anne Houdussea,1,2, and Margaret A. Titusd,1,2 aStructural Motility, Institut Curie, CNRS, UMR 144, PSL Research University, F-75005 Paris, France; bUPMC Université de Paris 6, Institut de Formation Doctorale, Sorbonne Universités, 75252 Paris Cedex 05, France; cLaboratoire d’Ingénierie des Fonctions Moléculaires, Institut de Science et d’Ingénierie Supramoléculaires, UMR 7006 CNRS, Université de Strasbourg, F-67083 Strasbourg Cedex, France; dDepartment of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455; and eDepartment of Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY 12180 Edited by James A. Spudich, Stanford University School of Medicine, Stanford, CA, and approved March 31, 2016 (received for review January 15, 2016) Myosins containing MyTH4-FERM (myosin tail homology 4-band (Fig. 1). These MF myosins are widespread and likely quite an- 4.1, ezrin, radixin, moesin, or MF) domains in their tails are found cient because they are found in many different branches of the in a wide range of phylogenetically divergent organisms, such as phylogenetic tree (5, 6), including Opisthokonts (which includes humans and the social amoeba Dictyostelium (Dd). Interestingly, Metazoa, unicellular Holozoa, and Fungi), Amoebozoa, and the evolutionarily distant MF myosins have similar roles in the exten- SAR (Stramenopiles, Alveolates, and Rhizaria) (Fig. 1 A and B). sion of actin-filled membrane protrusions such as filopodia and Over the course of hundreds of millions years of parallel evolution bind to microtubules (MT), suggesting that the core functions of the MF myosins have acquired or maintained roles in the formation these MF myosins have been highly conserved over evolution. -
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. -
Circmyo10 Promotes Osteosarcoma Progression by Regulating Mir-370
Chen et al. Molecular Cancer (2019) 18:150 https://doi.org/10.1186/s12943-019-1076-1 RESEARCH Open Access CircMYO10 promotes osteosarcoma progression by regulating miR-370-3p/ RUVBL1 axis to enhance the transcriptional activity of β-catenin/LEF1 complex via effects on chromatin remodeling Junxin Chen1†, Gang Liu1†, Yizheng Wu1†, Jianjun Ma1†, Hongfei Wu2, Ziang Xie1, Shuai Chen1, Yute Yang1, Shengyu Wang1, Panyang Shen1, Yifan Fang3, Shunwu Fan1, Shuying Shen1* and Xiangqian Fang1* Abstract Background: CircMYO10 is a circular RNA generated by back-splicing of gene MYO10 and is upregulated in osteosarcoma cell lines, but its functional role in osteosarcoma is still unknown. This study aimed to clarify the mechanism of circMYO10 in osteosarcoma. Methods: CircMYO10 expression in 10 paired osteosarcoma and chondroma tissues was assessed by quantitative reverse transcription polymerase chain reaction (PCR). The function of circMYO10/miR-370-3p/RUVBL1 axis was assessed regarding two key characteristics: proliferation and endothelial–mesenchymal transition (EMT). Bioinformatics analysis, western blotting, real-time PCR, fluorescence in situ hybridization, immunoprecipitation, RNA pull-down assays, luciferase reporter assays, chromatin immunoprecipitation, and rescue experiments were used to evaluate the mechanism. Stably transfected MG63 cells were injected via tail vein or subcutaneously into nude mice to assess the role of circMYO10 in vivo. Results: CircMYO10 was significantly upregulated, while miR-370-3p was downregulated, in osteosarcoma cell lines and human osteosarcoma samples. Silencing circMYO10 inhibited cell proliferation and EMT in vivo and in vitro. Mechanistic investigations revealed that miR-370-3p targets RUVBL1 directly, and inhibits the interaction between RUVBL1 and β-catenin/LEF1 complex while circMYO10 showed a contrary effect via the inhibition of miR-370-3p. -
Searching the Genomes of Inbred Mouse Strains for Incompatibilities That Reproductively Isolate Their Wild Relatives
Journal of Heredity 2007:98(2):115–122 ª The American Genetic Association. 2007. All rights reserved. doi:10.1093/jhered/esl064 For permissions, please email: [email protected]. Advance Access publication January 5, 2007 Searching the Genomes of Inbred Mouse Strains for Incompatibilities That Reproductively Isolate Their Wild Relatives BRET A. PAYSEUR AND MICHAEL PLACE From the Laboratory of Genetics, University of Wisconsin, Madison, WI 53706. Address correspondence to the author at the address above, or e-mail: [email protected]. Abstract Identification of the genes that underlie reproductive isolation provides important insights into the process of speciation. According to the Dobzhansky–Muller model, these genes suffer disrupted interactions in hybrids due to independent di- vergence in separate populations. In hybrid populations, natural selection acts to remove the deleterious heterospecific com- binations that cause these functional disruptions. When selection is strong, this process can maintain multilocus associations, primarily between conspecific alleles, providing a signature that can be used to locate incompatibilities. We applied this logic to populations of house mice that were formed by hybridization involving two species that show partial reproductive isolation, Mus domesticus and Mus musculus. Using molecular markers likely to be informative about species ancestry, we scanned the genomes of 1) classical inbred strains and 2) recombinant inbred lines for pairs of loci that showed extreme linkage disequi- libria. By using the same set of markers, we identified a list of locus pairs that displayed similar patterns in both scans. These genomic regions may contain genes that contribute to reproductive isolation between M. domesticus and M. -
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. -
Drp1 Overexpression Induces Desmin Disassembling and Drives Kinesin-1 Activation Promoting Mitochondrial Trafficking in Skeletal Muscle
Cell Death & Differentiation (2020) 27:2383–2401 https://doi.org/10.1038/s41418-020-0510-7 ARTICLE Drp1 overexpression induces desmin disassembling and drives kinesin-1 activation promoting mitochondrial trafficking in skeletal muscle 1 1 2 2 2 3 Matteo Giovarelli ● Silvia Zecchini ● Emanuele Martini ● Massimiliano Garrè ● Sara Barozzi ● Michela Ripolone ● 3 1 4 1 5 Laura Napoli ● Marco Coazzoli ● Chiara Vantaggiato ● Paulina Roux-Biejat ● Davide Cervia ● 1 1 2 1,4 6 Claudia Moscheni ● Cristiana Perrotta ● Dario Parazzoli ● Emilio Clementi ● Clara De Palma Received: 1 August 2019 / Revised: 13 December 2019 / Accepted: 23 January 2020 / Published online: 10 February 2020 © The Author(s) 2020. This article is published with open access Abstract Mitochondria change distribution across cells following a variety of pathophysiological stimuli. The mechanisms presiding over this redistribution are yet undefined. In a murine model overexpressing Drp1 specifically in skeletal muscle, we find marked mitochondria repositioning in muscle fibres and we demonstrate that Drp1 is involved in this process. Drp1 binds KLC1 and enhances microtubule-dependent transport of mitochondria. Drp1-KLC1 coupling triggers the displacement of KIF5B from 1234567890();,: 1234567890();,: kinesin-1 complex increasing its binding to microtubule tracks and mitochondrial transport. High levels of Drp1 exacerbate this mechanism leading to the repositioning of mitochondria closer to nuclei. The reduction of Drp1 levels decreases kinesin-1 activation and induces the partial recovery of mitochondrial distribution. Drp1 overexpression is also associated with higher cyclin-dependent kinase-1 (Cdk-1) activation that promotes the persistent phosphorylation of desmin at Ser-31 and its disassembling. Fission inhibition has a positive effect on desmin Ser-31 phosphorylation, regardless of Cdk-1 activation, suggesting that induction of both fission and Cdk-1 are required for desmin collapse. -
Bioinformatics Analyses of Genomic Imprinting
Bioinformatics Analyses of Genomic Imprinting Dissertation zur Erlangung des Grades des Doktors der Naturwissenschaften der Naturwissenschaftlich-Technischen Fakultät III Chemie, Pharmazie, Bio- und Werkstoffwissenschaften der Universität des Saarlandes von Barbara Hutter Saarbrücken 2009 Tag des Kolloquiums: 08.12.2009 Dekan: Prof. Dr.-Ing. Stefan Diebels Berichterstatter: Prof. Dr. Volkhard Helms Priv.-Doz. Dr. Martina Paulsen Vorsitz: Prof. Dr. Jörn Walter Akad. Mitarbeiter: Dr. Tihamér Geyer Table of contents Summary________________________________________________________________ I Zusammenfassung ________________________________________________________ I Acknowledgements _______________________________________________________II Abbreviations ___________________________________________________________ III Chapter 1 – Introduction __________________________________________________ 1 1.1 Important terms and concepts related to genomic imprinting __________________________ 2 1.2 CpG islands as regulatory elements ______________________________________________ 3 1.3 Differentially methylated regions and imprinting clusters_____________________________ 6 1.4 Reading the imprint __________________________________________________________ 8 1.5 Chromatin marks at imprinted regions___________________________________________ 10 1.6 Roles of repetitive elements ___________________________________________________ 12 1.7 Functional implications of imprinted genes _______________________________________ 14 1.8 Evolution and parental conflict ________________________________________________ -
Profilin-1 Is Required for Survival of Adult Hematopoietic Stem Cells
Extended methods Immunohistochemistry HepG-2, SMMC-7721, and 293T cells were obtained from Cell Resource Center of Shanghai Institute for Biological Science, Chinese Academy Science, Shanghai, China. HUVEC cells were kindly provided by Prof. Ping-Jin Gao at Institute of Health Sciences (Shanghai, China). All these cell lines were cultured in DMEM with 10% FBS. MDA- MB-231 cell line was kindly provided by Prof. Ming-Yao Liu (East China Normal University, Shanghai, China) and was cultured in Leibovitz L-15 medium with 10% FBS. All these cell lines were originally purchased from ATCC. MDA-MB-231, SMMC-7721 or HepG2 cells were grown on coverslips in 24-well plates and fixed in either 4% paraformaldehyde or pre-chilled methanol (-20°C) for 10 min. In some cases, WT or VPS33B-null Lin-Sca-1+c-Kit+Flk2-CD34- LT-HSCs were collected by flow cytometry and fixed for immunofluorescence staining. Cells were then blocked with 3% BSA in PBS for 60 min followed by incubation with primary antibodies overnight. The antibodies used were anti-HA (Sigma), anti-Flag (Sigma), anti-VPS33B (Sigma), anti- VPS16B (Abcam), anti-GDI2 (Proteintech), anti-LAMP1 (Proteintech), anti-FLOT1 (Abways), anti-CD63 (Proteintech), anti-ANGPTL2 (R&D system), anti-ANGPTL3 (R&D system), anti-TPO (Abways), anti-GLUT1 (Proteintech), anti-LDHA (Proteintech), anti-PKM2 (CST), anti-RAB11A (Abways), anti-RAB27A (Abways) and anti-V5 (Biodragon). Fluorescent-conjugated secondary antibodies (Alexa Fluor® 488 or Alexa Fluor® 555) against mouse, rabbit, or goat were obtained from the Thermo Scientific Inc. The details for all the antibodies are listed in Table S3. -
Phenotypic Modulation of Smooth Muscle Cells in Atherosclerosis Is Associated with Downregulation of LMOD1, SYNPO2, PDLIM7, PLN and SYNM
Markers of smooth muscle cells Perisic et al. Phenotypic modulation of smooth muscle cells in atherosclerosis is associated with downregulation of LMOD1, SYNPO2, PDLIM7, PLN and SYNM Perisic L1, Rykaczewska U1, Razuvaev A1, Sabater-Lleal M2, Lengquist M1, Miller CL3, Ericsson I1, Röhl S1, Kronqvist M1, Aldi S1, Magné J2, Vesterlund M4, Li Y2, Yin H2, Gonzalez Diez M2, Roy J1, Baldassarre D5,6, Veglia F6, Humphries SE7, de Faire U8,9, Tremoli E5,6, on behalf of the IMPROVE study group, Odeberg J10, Vukojević V11, Lehtiö J4, Maegdefessel L2, Ehrenborg E2, Paulsson-Berne G2, Hansson GK2, Lindeman JHN12, Eriksson P2, Quertermous T3, Hamsten A2, Hedin U1 1Department of Molecular Medicine and Surgery, Karolinska Institutet, Sweden, 2Department of Medicine, Karolinska Institutet, Sweden, 3Division of Vascular Surgery, Stanford University, USA, 4Science for Life Laboratory, Sweden, 5Dipartimento di Scienze Farmacologiche e Biomolecolari, Università di Milano, Milan, Italy, 6Centro Cardiologico Monzino, IRCCS, Milan, Italy, 7British Heart Foundation Laboratories, University College of London, Department of Medicine, Rayne Building, London, United Kingdom, 8Division of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 9Department of Cardiology, Karolinska University Hospital Solna, Karolinska Institutet, Stockholm, Sweden, 10Science for Life Laboratory, Department of Proteomics, Sweden, 11Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Sweden, 12Department of Vascular -
The Transcriptomic Landscape of Prostate Cancer Development and Progression: an Integrative Analysis
cancers Article The Transcriptomic Landscape of Prostate Cancer Development and Progression: An Integrative Analysis Jacek Marzec 1,† , Helen Ross-Adams 1,*,† , Stefano Pirrò 1 , Jun Wang 1 , Yanan Zhu 2, Xueying Mao 2, Emanuela Gadaleta 1 , Amar S. Ahmad 3, Bernard V. North 3, Solène-Florence Kammerer-Jacquet 2, Elzbieta Stankiewicz 2, Sakunthala C. Kudahetti 2, Luis Beltran 4, Guoping Ren 5, Daniel M. Berney 2,4, Yong-Jie Lu 2 and Claude Chelala 1,6,* 1 Bioinformatics Unit, Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; [email protected] (J.M.); [email protected] (S.P.); [email protected] (J.W.); [email protected] (E.G.) 2 Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; [email protected] (Y.Z.); [email protected] (X.M.); solenefl[email protected] (S.-F.K.-J.); [email protected] (E.S.); [email protected] (S.C.K.); [email protected] (D.M.B.); [email protected] (Y.-J.L.) 3 Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine, Queen Mary University of London, London EC1M 6BQ, UK; [email protected] (A.S.A.); [email protected] (B.V.N.) 4 Department of Pathology, Barts Health NHS, London E1 F1R, UK; [email protected] 5 Department of Pathology, The First Affiliated Hospital, Zhejiang University Medical College, Hangzhou 310058, China; [email protected] 6 Centre for Computational Biology, Life Sciences Initiative, Queen Mary University London, London EC1M 6BQ, UK * Correspondence: [email protected] (H.R.-A.); [email protected] (C.C.) † These authors contributed equally to this work.