Table SI. List of the Androgen‑Enhanced Palmitoylated Proteins in Lncap Cells by Palmitoylome Analysis
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Mena regulates the LINC complex to control actin–nuclear lamina associations, trans-nuclear membrane signalling and cancer gene expression Frederic Li Mow Chee!, Bruno Beernaert!, Alexander Loftus!, Yatendra Kumar", Billie G. C. Griffith!, Jimi C. Wills!, Ann P. Wheeler#, J. Douglas Armstrong$, Maddy Parsons%, Irene M. Leigh,(, Charlotte M. Proby&, Alex von Kriegsheim!, Wendy A. Bickmore", Margaret C. Frame,* & Adam Byron,* Supplementary Information Supplementary Figure 1 Supplementary Figure 2 Supplementary Figure 3 Supplementary Table 1 Supplementary Table 2 Supplementary Table 3 Supplementary Table 4 !Cancer Research UK Edinburgh Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH< =XR, UK. "MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH< =XU, UK. #Advanced Imaging Resource, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH< =XU, UK. $Simons Initiative for the Developing Brain, School of Informatics, University of Edinburgh, Edinburgh EHH IYL, UK. %Randall Centre for Cell and Molecular Biophysics, King’s College London, London SEM MUL, UK. &Division of Molecular and Clinical Medicine, School of Medicine, University of Dundee, Dundee DD <HN, UK. 'Institute of Dentistry, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EM =AT, UK. *email: [email protected] or [email protected] 1 a cSCC IAC correlation b cSCC IAC pathways c Core adhesome network ENAH −log10(q) MACF1 CSRP1 Met1 Met4 0 5 10 + + CORO2A Integrin signalling + CFL1 pathway PRNP ILK + HSPB1 PALLD PPFIA1 TES RDX Cytoskeletal regulation + VASP + + ARPC2 by Rho GTPase PPP2CA + Met1 + LASP1 MYH9 + VIM TUBA4A Huntington ITGA3 + disease ITGB4 VCL CAV1 ACTB ROCK1 KTN1 FLNA+ CALR DNA FBLIM1 CORO1B RAC1 + replication +ACTN1 ITGA6 + Met4 ITGAV Parkinson ITGB1 disease Actin cytoskel. -
Tubulin in Platelets: When the Shape Matters
International Journal of Molecular Sciences Review Tubulin in Platelets: When the Shape Matters Ernesto José Cuenca-Zamora 1 , Francisca Ferrer-Marín 1,2,*, José Rivera 1 and Raúl Teruel-Montoya 1 1 Servicio de Hematología y Oncología Médica, Centro Regional de Hemodonación, Hospital Universitario Morales Meseguer, IMIB-Arrixaca, Red CIBERER CB15/00055, 30003 Murcia, Spain 2 Grado de Medicina, Universidad Católica San Antonio (UCAM), Campus de los Jerónimos, 30107 Murcia, Spain * Correspondence: ff[email protected]; Tel.: +34-968-341990 Received: 1 May 2019; Accepted: 17 June 2019; Published: 16 July 2019 Abstract: Platelets are anuclear cells with a short lifespan that play an essential role in many pathophysiological processes, including haemostasis, inflammation, infection, vascular integrity, and metastasis. Billions of platelets are produced daily from megakaryocytes (platelet precursors). Despite this high production, the number of circulating platelets is stable and, under resting conditions, they maintain their typical discoid shape thanks to cytoskeleton proteins. The activation of platelets is associated with dynamic and rapid changes in the cytoskeleton. Two cytoskeletal polymer systems exist in megakaryocytes and platelets: actin filaments and microtubules, based on actin, and α- and β-tubulin heterodimers, respectively. Herein, we will focus on platelet-specific tubulins and their alterations and role of the microtubules skeleton in platelet formation (thrombopoiesis). During this process, microtubules mediate elongation -
Alpha Actinin 4: an Intergral Component of Transcriptional
ALPHA ACTININ 4: AN INTERGRAL COMPONENT OF TRANSCRIPTIONAL PROGRAM REGULATED BY NUCLEAR HORMONE RECEPTORS By SIMRAN KHURANA Submitted in partial fulfillment of the requirements for the degree of doctor of philosophy Thesis Advisor: Dr. Hung-Ying Kao Department of Biochemistry CASE WESTERN RESERVE UNIVERSITY August, 2011 CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES We hereby approve the thesis/dissertation of SIMRAN KHURANA ______________________________________________________ PhD candidate for the ________________________________degree *. Dr. David Samols (signed)_______________________________________________ (chair of the committee) Dr. Hung-Ying Kao ________________________________________________ Dr. Edward Stavnezer ________________________________________________ Dr. Leslie Bruggeman ________________________________________________ Dr. Colleen Croniger ________________________________________________ ________________________________________________ May 2011 (date) _______________________ *We also certify that written approval has been obtained for any proprietary material contained therein. TABLE OF CONTENTS LIST OF TABLES vii LIST OF FIGURES viii ACKNOWLEDEMENTS xii LIST OF ABBREVIATIONS xiii ABSTRACT 1 CHAPTER 1: INTRODUCTION Family of Nuclear Receptors 3 Mechanism of transcriptional regulation by co-repressors and co-activators 8 Importance of LXXLL motif of co-activators in NR mediated transcription 12 Cyclic recruitment of co-regulators on the target promoters 15 Actin and actin related proteins (ABPs) in transcription -
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. -
Β-Catenin Knockdown Affects Mitochondrial Biogenesis and Lipid Metabolism in Breast Cancer Cells
ORIGINAL RESEARCH published: 27 July 2017 doi: 10.3389/fphys.2017.00544 β-Catenin Knockdown Affects Mitochondrial Biogenesis and Lipid Metabolism in Breast Cancer Cells Daniele Vergara 1, 2 †, Eleonora Stanca 1, 2 †, Flora Guerra 1, Paola Priore 3, Antonio Gaballo 3, Julien Franck 4, Pasquale Simeone 5, Marco Trerotola 6, Stefania De Domenico 7, Isabelle Fournier 4, Cecilia Bucci 1, Michel Salzet 4, Anna M. Giudetti 1* and Michele Maffia 1, 2* 1 Department of Biological and Environmental Sciences and Technologies, University of Salento, Lecce, Italy, 2 Laboratory of Clinical Proteomic, “Giovanni Paolo II” Hospital, Lecce, Italy, 3 CNR NANOTEC - Institute of Nanotechnology, Lecce, Italy, 4 University of Lille, Institut national de la santé et de la recherche médicale, U-1192 - Laboratoire Protéomique, Réponse Edited by: Inflammatoire et Spectrométrie de Masse-PRISM, Lille, France, 5 Unit of Cytomorphology, CeSI-MeT and Department of Andrei Surguchov, Medicine and Aging Sciences, School of Medicine and Health Sciences, University “G. d’Annunzio,” Chieti, Italy, 6 Unit of Kansas University of Medical Center Cancer Pathology, CeSI-MeT and Department of Medical, Oral and Biotechnological Sciences, University “G. d’Annunzio,” Research Institute, United States Chieti, Italy, 7 C.N.R. Unit of Lecce, Institute of Food Production Sciences, Lecce, Italy Reviewed by: Kamal Datta, β-catenin plays an important role as regulatory hub in several cellular processes including Georgetown University, United States Silvana Gaetani, cell adhesion, metabolism, and epithelial mesenchymal transition. This is mainly achieved Sapienza Università di Roma, Italy by its dual role as structural component of cadherin-based adherens junctions, and as Clizia Chinello, University of Milano-Bicocca, Italy a key nuclear effector of the Wnt pathway. -
List of Genes Associated with Sudden Cardiac Death (Scdgseta) Gene
List of genes associated with sudden cardiac death (SCDgseta) mRNA expression in normal human heart Entrez_I Gene symbol Gene name Uniprot ID Uniprot name fromb D GTEx BioGPS SAGE c d e ATP-binding cassette subfamily B ABCB1 P08183 MDR1_HUMAN 5243 √ √ member 1 ATP-binding cassette subfamily C ABCC9 O60706 ABCC9_HUMAN 10060 √ √ member 9 ACE Angiotensin I–converting enzyme P12821 ACE_HUMAN 1636 √ √ ACE2 Angiotensin I–converting enzyme 2 Q9BYF1 ACE2_HUMAN 59272 √ √ Acetylcholinesterase (Cartwright ACHE P22303 ACES_HUMAN 43 √ √ blood group) ACTC1 Actin, alpha, cardiac muscle 1 P68032 ACTC_HUMAN 70 √ √ ACTN2 Actinin alpha 2 P35609 ACTN2_HUMAN 88 √ √ √ ACTN4 Actinin alpha 4 O43707 ACTN4_HUMAN 81 √ √ √ ADRA2B Adrenoceptor alpha 2B P18089 ADA2B_HUMAN 151 √ √ AGT Angiotensinogen P01019 ANGT_HUMAN 183 √ √ √ AGTR1 Angiotensin II receptor type 1 P30556 AGTR1_HUMAN 185 √ √ AGTR2 Angiotensin II receptor type 2 P50052 AGTR2_HUMAN 186 √ √ AKAP9 A-kinase anchoring protein 9 Q99996 AKAP9_HUMAN 10142 √ √ √ ANK2/ANKB/ANKYRI Ankyrin 2 Q01484 ANK2_HUMAN 287 √ √ √ N B ANKRD1 Ankyrin repeat domain 1 Q15327 ANKR1_HUMAN 27063 √ √ √ ANKRD9 Ankyrin repeat domain 9 Q96BM1 ANKR9_HUMAN 122416 √ √ ARHGAP24 Rho GTPase–activating protein 24 Q8N264 RHG24_HUMAN 83478 √ √ ATPase Na+/K+–transporting ATP1B1 P05026 AT1B1_HUMAN 481 √ √ √ subunit beta 1 ATPase sarcoplasmic/endoplasmic ATP2A2 P16615 AT2A2_HUMAN 488 √ √ √ reticulum Ca2+ transporting 2 AZIN1 Antizyme inhibitor 1 O14977 AZIN1_HUMAN 51582 √ √ √ UDP-GlcNAc: betaGal B3GNT7 beta-1,3-N-acetylglucosaminyltransfe Q8NFL0 -
Original Article Plasma CAMK2A Predicts Chemotherapy Resistance in Metastatic Triple Negative Breast Cancer
Int J Clin Exp Pathol 2018;11(2):650-663 www.ijcep.com /ISSN:1936-2625/IJCEP0069558 Original Article Plasma CAMK2A predicts chemotherapy resistance in metastatic triple negative breast cancer Bin Shao1*, Zhihua Tian2*, Huirong Ding2*, Qingsong Wang3, Guohong Song1, Lijun Di1, Hong Zhang2, Huiping Li1, Jing Shen2 Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), 1Department of Medical Oncology, 2Central Laboratory, Peking University Cancer Hospital & Institute, Beijing, P. R. China; 3State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, Beijing, P. R. China. *Equal contributors. Received November 21, 2017; Accepted December 15, 2017; Epub February 1, 2018; Published February 15, 2018 Abstract: Background: Chemotherapy resistance is a great obstacle in effective treatment for metastatic triple nega- tive breast cancer (TNBC). The ability to predict chemotherapy response would allow chemotherapy administration to be directed toward only those patients who would benefit, thus maximizing treatment efficiency. Differentially expressed plasma proteins may serve as putative biomarkers for predicting chemotherapy outcomes. Patients and methods: In this study, 26 plasma samples (10 samples with partial response (S) and 16 samples with progression disease (R)) from patients with metastatic TNBC were measured by Tandem Mass Tag (TMT)-based proteomics analysis to identify differentially expressed proteins between the S and R group. Potential proteinswere validated with enzyme-linked immunosorbent assay (ELISA) in another 67 plasma samples. Results: A total of 320 plasma proteins were identified, and statistical analysis showed that 108 proteins were significantly dysregulated between R and S groups in the screening stage. Bioinformatics revealed relevant pathways and regulatory networks of the differentially expressed proteins. -
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. -
Phenomic Profiling Through Live-Cell Imaging in a Panel of Reporter Cell
www.nature.com/scientificreports OPEN Tales of 1,008 small molecules: phenomic profling through live‑cell imaging in a panel of reporter cell lines Michael J. Cox1,5, Stefen Jaensch1,5*, Jelle Van de Waeter1, Laure Cougnaud2, Daan Seynaeve2, Soulaiman Benalla1, Seong Joo Koo1, Ilse Van Den Wyngaert1, Jean‑Marc Neefs1, Dmitry Malkov3, Mart Bittremieux1, Margino Steemans1, Pieter J. Peeters1, Jörg Kurt Wegner1, Hugo Ceulemans1, Emmanuel Gustin1, Yolanda T. Chong1,4 & Hinrich W. H. Göhlmann1 Phenomic profles are high‑dimensional sets of readouts that can comprehensively capture the biological impact of chemical and genetic perturbations in cellular assay systems. Phenomic profling of compound libraries can be used for compound target identifcation or mechanism of action (MoA) prediction and other applications in drug discovery. To devise an economical set of phenomic profling assays, we assembled a library of 1,008 approved drugs and well‑characterized tool compounds manually annotated to 218 unique MoAs, and we profled each compound at four concentrations in live‑cell, high‑content imaging screens against a panel of 15 reporter cell lines, which expressed a diverse set of fuorescent organelle and pathway markers in three distinct cell lineages. For 41 of 83 testable MoAs, phenomic profles accurately ranked the reference compounds (AUC‑ROC ≥ 0.9). MoAs could be better resolved by screening compounds at multiple concentrations than by including replicates at a single concentration. Screening additional cell lineages and fuorescent markers increased the number of distinguishable MoAs but this efect quickly plateaued. There remains a substantial number of MoAs that were hard to distinguish from others under the current study’s conditions. -
Regulation of Canonical Wnt Signalling by the Ciliopathy Protein MKS1 and the E2
bioRxiv preprint doi: https://doi.org/10.1101/2020.01.08.897959; this version posted March 28, 2020. 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-NC-ND 4.0 International license. Regulation of canonical Wnt signalling by the ciliopathy protein MKS1 and the E2 ubiquitin-conjugating enzyme UBE2E1. Katarzyna Szymanska1, Karsten Boldt2, Clare V. Logan1, Matthew Adams1, Philip A. Robinson1+, Marius Ueffing2, Elton Zeqiraj3, Gabrielle Wheway1,4#, Colin A. Johnson1#* *corresponding author: [email protected] ORCID: 0000-0002-2979-8234 # joint last authors + deceased 1 Leeds Institute of Medical Research, School of Medicine, University of Leeds, Leeds, UK 2 Institute of Ophthalmic Research, Center for Ophthalmology, University of Tübingen, Tübingen, Germany 3 Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK 4 Faculty of Medicine, University of Southampton, Human Development and Health, UK; University Hospital Southampton NHS Foundation Trust, UK 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.01.08.897959; this version posted March 28, 2020. 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-NC-ND 4.0 International license. Abstract A functional primary cilium is essential for normal and regulated signalling. Primary ciliary defects cause a group of developmental conditions known as ciliopathies, but the precise mechanisms of signal regulation by the cilium remain unclear. -
Serum Albumin OS=Homo Sapiens
Protein Name Cluster of Glial fibrillary acidic protein OS=Homo sapiens GN=GFAP PE=1 SV=1 (P14136) Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 Cluster of Isoform 3 of Plectin OS=Homo sapiens GN=PLEC (Q15149-3) Cluster of Hemoglobin subunit beta OS=Homo sapiens GN=HBB PE=1 SV=2 (P68871) Vimentin OS=Homo sapiens GN=VIM PE=1 SV=4 Cluster of Tubulin beta-3 chain OS=Homo sapiens GN=TUBB3 PE=1 SV=2 (Q13509) Cluster of Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 (P60709) Cluster of Tubulin alpha-1B chain OS=Homo sapiens GN=TUBA1B PE=1 SV=1 (P68363) Cluster of Isoform 2 of Spectrin alpha chain, non-erythrocytic 1 OS=Homo sapiens GN=SPTAN1 (Q13813-2) Hemoglobin subunit alpha OS=Homo sapiens GN=HBA1 PE=1 SV=2 Cluster of Spectrin beta chain, non-erythrocytic 1 OS=Homo sapiens GN=SPTBN1 PE=1 SV=2 (Q01082) Cluster of Pyruvate kinase isozymes M1/M2 OS=Homo sapiens GN=PKM PE=1 SV=4 (P14618) Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 Clathrin heavy chain 1 OS=Homo sapiens GN=CLTC PE=1 SV=5 Filamin-A OS=Homo sapiens GN=FLNA PE=1 SV=4 Cytoplasmic dynein 1 heavy chain 1 OS=Homo sapiens GN=DYNC1H1 PE=1 SV=5 Cluster of ATPase, Na+/K+ transporting, alpha 2 (+) polypeptide OS=Homo sapiens GN=ATP1A2 PE=3 SV=1 (B1AKY9) Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 Dihydropyrimidinase-related protein 2 OS=Homo sapiens GN=DPYSL2 PE=1 SV=1 Cluster of Alpha-actinin-1 OS=Homo sapiens GN=ACTN1 PE=1 SV=2 (P12814) 60 kDa heat shock protein, mitochondrial OS=Homo -
RNA Editing at Baseline and Following Endoplasmic Reticulum Stress
RNA Editing at Baseline and Following Endoplasmic Reticulum Stress By Allison Leigh Richards A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Human Genetics) in The University of Michigan 2015 Doctoral Committee: Professor Vivian G. Cheung, Chair Assistant Professor Santhi K. Ganesh Professor David Ginsburg Professor Daniel J. Klionsky Dedication To my father, mother, and Matt without whom I would never have made it ii Acknowledgements Thank you first and foremost to my dissertation mentor, Dr. Vivian Cheung. I have learned so much from you over the past several years including presentation skills such as never sighing and never saying “as you can see…” You have taught me how to think outside the box and how to create and explain my story to others. I would not be where I am today without your help and guidance. Thank you to the members of my dissertation committee (Drs. Santhi Ganesh, David Ginsburg and Daniel Klionsky) for all of your advice and support. I would also like to thank the entire Human Genetics Program, and especially JoAnn Sekiguchi and Karen Grahl, for welcoming me to the University of Michigan and making my transition so much easier. Thank you to Michael Boehnke and the Genome Science Training Program for supporting my work. A very special thank you to all of the members of the Cheung lab, past and present. Thank you to Xiaorong Wang for all of your help from the bench to advice on my career. Thank you to Zhengwei Zhu who has helped me immensely throughout my thesis even through my panic.