Supplementary Material: the File Contains Supplementary Text, Figures and Tables in the Following Order
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
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. -
Nuclear Translocation of PDCD5 (TFAR19): Provided by Elsevier - Publisher Connector an Early Signal for Apoptosis?
FEBS 25453 FEBS Letters 509 (2001) 191^196 View metadata, citation and similar papers at core.ac.uk brought to you by CORE Nuclear translocation of PDCD5 (TFAR19): provided by Elsevier - Publisher Connector an early signal for apoptosis? Yingyu Chen, Ronghua Sun, Wenling Han, Yingmei Zhang, Quansheng Song, Chunhui Di, Dalong Ma* Laboratory of Medical Immunology, School of Basic Medical Science, Peking University, 38 Xueyuan Road, Beijing 100083, PR China Received 20 July 2001; revised 14 September 2001; accepted 16 October 2001 First published online 7 November 2001 Edited by Vladimir Skulachev could accelerate apoptosis of some tumor cells (HeLa, TF-1, Abstract The programmed cell death 5 (PDCD5) protein is a novel protein related to regulation of cell apoptosis. In this HL60, MCG-803, MCF-7) [5,7]. In order to further study the report, we demonstrate that the level of PDCD5 protein biological activities of PDCD5, we successfully produced spe- expressed in cells undergoing apoptosis is significantly increased ci¢c monoclonal antibodies against PDCD5. Then, we used compared with normal cells, then the protein translocates rapidly these monoclonal antibodies as probes to observe the expres- from the cytoplasm to the nucleus of cells. The appearance of sion and localization of PDCD5 in cell apoptosis process. We PDCD5 in the nuclei of apoptotic cells precedes the externaliza- demonstrate that PDCD5 protein can translocate to the nu- tion of phosphatidylserine and fragmentation of chromosome cleus rapidly in cells undergoing apoptosis and the accumu- DNA. This phenomenon is parallel to the loss of mitochondrial lation of PDCD5 in the nucleus precedes the chromosome membrane potential, independent of the feature of apoptosis- DNA fragmentation and phosphatidylserine (PS) externaliza- inducing stimuli and also independent of the cell types and the tion. -
Discovery of the First Genome-Wide Significant Risk Loci for Attention Deficit/Hyperactivity Disorder
ARTICLES https://doi.org/10.1038/s41588-018-0269-7 Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder Ditte Demontis 1,2,3,69, Raymond K. Walters 4,5,69, Joanna Martin5,6,7, Manuel Mattheisen1,2,3,8,9,10, Thomas D. Als 1,2,3, Esben Agerbo 1,11,12, Gísli Baldursson13, Rich Belliveau5, Jonas Bybjerg-Grauholm 1,14, Marie Bækvad-Hansen1,14, Felecia Cerrato5, Kimberly Chambert5, Claire Churchhouse4,5,15, Ashley Dumont5, Nicholas Eriksson16, Michael Gandal17,18,19,20, Jacqueline I. Goldstein4,5,15, Katrina L. Grasby21, Jakob Grove 1,2,3,22, Olafur O. Gudmundsson13,23,24, Christine S. Hansen 1,14,25, Mads Engel Hauberg1,2,3, Mads V. Hollegaard1,14, Daniel P. Howrigan4,5, Hailiang Huang4,5, Julian B. Maller5,26, Alicia R. Martin4,5,15, Nicholas G. Martin 21, Jennifer Moran5, Jonatan Pallesen1,2,3, Duncan S. Palmer4,5, Carsten Bøcker Pedersen1,11,12, Marianne Giørtz Pedersen1,11,12, Timothy Poterba4,5,15, Jesper Buchhave Poulsen1,14, Stephan Ripke4,5,27, Elise B. Robinson4,28, F. Kyle Satterstrom 4,5,15, Hreinn Stefansson 23, Christine Stevens5, Patrick Turley4,5, G. Bragi Walters 23,24, Hyejung Won 17,18, Margaret J. Wright 29, ADHD Working Group of the Psychiatric Genomics Consortium (PGC)30, Early Lifecourse & Genetic Epidemiology (EAGLE) Consortium30, 23andMe Research Team30, Ole A. Andreassen 31, Philip Asherson32, Christie L. Burton 33, Dorret I. Boomsma34,35, Bru Cormand36,37,38,39, Søren Dalsgaard 11, Barbara Franke40, Joel Gelernter 41,42, Daniel Geschwind 17,18,19, Hakon Hakonarson43, Jan Haavik44,45, Henry R. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Structure–Function Correlation of Human Programmed Cell Death 5 Protein
Archives of Biochemistry and Biophysics 486 (2009) 141–149 Contents lists available at ScienceDirect Archives of Biochemistry and Biophysics journal homepage: www.elsevier.com/locate/yabbi Structure–function correlation of human programmed cell death 5 protein Hongwei Yao a,1, Lanjun Xu b,1, Yingang Feng a, Dongsheng Liu a, Yingyu Chen b,*, Jinfeng Wang a,* a National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Beijing 100101, China b Laboratory of Medical Immunology, School of Basic Medical Science, Peking University Health Science Center, 38 Xueyuan Road, Beijing 100083, China article info abstract Article history: Human programmed cell death 5 (PDCD5) is a translocatory protein playing an important role in the Received 4 March 2009 apoptotic process of cells. Although there are accumulated data about PDCD5 function, the correlation and in revised form 25 March 2009 of the structure with the function of PDCD5 has not been investigated. Here, we report the studies of Available online 7 April 2009 structure–function relationship of PDCD5 by multidimensional NMR methods and by FACScan flow cytometer and fluorescence microscope. The 3D structure of intact PDCD5 and the internal motions of Keywords: PDCD5 have been determined. PDCD5 has a compact core structure of low flexibility with two mobile PDCD5 a-helices at N-terminal region and a flexible unstructured C-terminal region. The flow cytometry and NMR internalization measurements of different PDCD5 fragments indicate that the charged residues are crucial Structure–function relationship Cell translocation for the ability of apoptosis-promoting and cell translocation of the protein. Combined analyses reveal a Fragments of PDCD5 fact that the regions that seem to be most involved in the function also are more flexible in PDCD5. -
The 5V-Upstream Region of Human Programmed Cell Death 5 Gene Contains a Highly Active TATA-Less Promoter That Is Up-Regulated by Etoposide
http://www.paper.edu.cn Gene 329 (2004) 39–49 www.elsevier.com/locate/gene The 5V-upstream region of human programmed cell death 5 gene contains a highly active TATA-less promoter that is up-regulated by etoposide Mingxu Xu*, Ning Cheng, Liming Gui, Mouyi Lai, Ying Wang, Donglan Xia, Min Rui, Yingmei Zhang, Dalong Ma Laboratory of Medical Immunology, School of Basic Medical Sciences, Peking University Center for Human Disease Genomics, 38 Xueyuan Road, Beijing 100083, China Received 9 June 2003; received in revised form 3 December 2003; accepted 23 December 2003 Received by R. Di Lauro Abstract The PDCD5 (programmed cell death 5), a novel apoptosis related gene, is functionally associated with cell apoptosis, exhibits a ubiquitous expression pattern and is up-regulated in some types of tumor cells undergoing apoptosis. To study the transcriptional regulation of the PDCD5 gene, we have cloned 1.1 kb of its 5V-upstream region. The DNA sequencing analysis revealed a major transcriptional start site at 72 base pairs in front of the ATG translational start codon. The upstream of the transcriptional start site lacks a canonical TATA box and CAAT box. Transient transfection and luciferase assay demonstrate that this region presents extremely strong promoter activity. The 5V- deleted sequences fused to a luciferase reporter gene demonstrated that the À 555/ À 383 region from the transcription start site is crucial for transcriptional regulation, and the luciferase reporter gene’s expression significantly increased in the early stage of cell apoptosis induced by etoposide. These results imply that the PDCD5 gene may be a target gene under the control of some important apoptosis-related transcriptional factors during the cell apoptosis. -
Bioinformatics Analysis for the Identification of Differentially Expressed Genes and Related Signaling Pathways in H
Bioinformatics analysis for the identification of differentially expressed genes and related signaling pathways in H. pylori-CagA transfected gastric cancer cells Dingyu Chen*, Chao Li, Yan Zhao, Jianjiang Zhou, Qinrong Wang and Yuan Xie* Key Laboratory of Endemic and Ethnic Diseases , Ministry of Education, Guizhou Medical University, Guiyang, China * These authors contributed equally to this work. ABSTRACT Aim. Helicobacter pylori cytotoxin-associated protein A (CagA) is an important vir- ulence factor known to induce gastric cancer development. However, the cause and the underlying molecular events of CagA induction remain unclear. Here, we applied integrated bioinformatics to identify the key genes involved in the process of CagA- induced gastric epithelial cell inflammation and can ceration to comprehend the potential molecular mechanisms involved. Materials and Methods. AGS cells were transected with pcDNA3.1 and pcDNA3.1::CagA for 24 h. The transfected cells were subjected to transcriptome sequencing to obtain the expressed genes. Differentially expressed genes (DEG) with adjusted P value < 0.05, | logFC |> 2 were screened, and the R package was applied for gene ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The differential gene protein–protein interaction (PPI) network was constructed using the STRING Cytoscape application, which conducted visual analysis to create the key function networks and identify the key genes. Next, the Submitted 20 August 2020 Kaplan–Meier plotter survival analysis tool was employed to analyze the survival of the Accepted 11 March 2021 key genes derived from the PPI network. Further analysis of the key gene expressions Published 15 April 2021 in gastric cancer and normal tissues were performed based on The Cancer Genome Corresponding author Atlas (TCGA) database and RT-qPCR verification. -
A Peripheral Blood Gene Expression Signature to Diagnose Subclinical Acute Rejection
CLINICAL RESEARCH www.jasn.org A Peripheral Blood Gene Expression Signature to Diagnose Subclinical Acute Rejection Weijia Zhang,1 Zhengzi Yi,1 Karen L. Keung,2 Huimin Shang,3 Chengguo Wei,1 Paolo Cravedi,1 Zeguo Sun,1 Caixia Xi,1 Christopher Woytovich,1 Samira Farouk,1 Weiqing Huang,1 Khadija Banu,1 Lorenzo Gallon,4 Ciara N. Magee,5 Nader Najafian,5 Milagros Samaniego,6 Arjang Djamali ,7 Stephen I. Alexander,2 Ivy A. Rosales,8 Rex Neal Smith,8 Jenny Xiang,3 Evelyne Lerut,9 Dirk Kuypers,10,11 Maarten Naesens ,10,11 Philip J. O’Connell,2 Robert Colvin,8 Madhav C. Menon,1 and Barbara Murphy1 Due to the number of contributing authors, the affiliations are listed at the end of this article. ABSTRACT Background In kidney transplant recipients, surveillance biopsies can reveal, despite stable graft function, histologic features of acute rejection and borderline changes that are associated with undesirable graft outcomes. Noninvasive biomarkers of subclinical acute rejection are needed to avoid the risks and costs associated with repeated biopsies. Methods We examined subclinical histologic and functional changes in kidney transplant recipients from the prospective Genomics of Chronic Allograft Rejection (GoCAR) study who underwent surveillance biopsies over 2 years, identifying those with subclinical or borderline acute cellular rejection (ACR) at 3 months (ACR-3) post-transplant. We performed RNA sequencing on whole blood collected from 88 indi- viduals at the time of 3-month surveillance biopsy to identify transcripts associated with ACR-3, developed a novel sequencing-based targeted expression assay, and validated this gene signature in an independent cohort. -
Miz1 Is Required to Maintain Autophagic Flux
ARTICLE Received 3 Apr 2013 | Accepted 3 Sep 2013 | Published 3 Oct 2013 DOI: 10.1038/ncomms3535 Miz1 is required to maintain autophagic flux Elmar Wolf1,*, Anneli Gebhardt1,*, Daisuke Kawauchi2, Susanne Walz1, Bjo¨rn von Eyss1, Nicole Wagner3, Christoph Renninger3, Georg Krohne1, Esther Asan3, Martine F. Roussel2 & Martin Eilers1,4 Miz1 is a zinc finger protein that regulates the expression of cell cycle inhibitors as part of a complex with Myc. Cell cycle-independent functions of Miz1 are poorly understood. Here we use a Nestin-Cre transgene to delete an essential domain of Miz1 in the central nervous system (Miz1DPOZNes). Miz1DPOZNes mice display cerebellar neurodegeneration characterized by the progressive loss of Purkinje cells. Chromatin immunoprecipitation sequencing and biochemical analyses show that Miz1 activates transcription upon binding to a non-palin- dromic sequence present in core promoters. Target genes of Miz1 encode regulators of autophagy and proteins involved in vesicular transport that are required for autophagy. Miz1DPOZ neuronal progenitors and fibroblasts show reduced autophagic flux. Consistently, polyubiquitinated proteins and p62/Sqtm1 accumulate in the cerebella of Miz1DPOZNes mice, characteristic features of defective autophagy. Our data suggest that Miz1 may link cell growth and ribosome biogenesis to the transcriptional regulation of vesicular transport and autophagy. 1 Theodor Boveri Institute, Biocenter, University of Wu¨rzburg, Am Hubland, 97074 Wu¨rzburg, Germany. 2 Department of Tumor Cell Biology, MS#350, Danny Thomas Research Center, 5006C, St. Jude Children’s Research Hospital, Memphis, Tennessee 38105, USA. 3 Institute for Anatomy and Cell Biology, University of Wu¨rzburg, Koellikerstrasse 6, 97070 Wu¨rzburg, Germany. 4 Comprehensive Cancer Center Mainfranken, Josef-Schneider-Strasse 6, 97080 Wu¨rzburg, Germany. -
1471-2105-8-217.Pdf
BMC Bioinformatics BioMed Central Software Open Access GenMAPP 2: new features and resources for pathway analysis Nathan Salomonis1,2, Kristina Hanspers1, Alexander C Zambon1, Karen Vranizan1,3, Steven C Lawlor1, Kam D Dahlquist4, Scott W Doniger5, Josh Stuart6, Bruce R Conklin1,2,7,8 and Alexander R Pico*1 Address: 1Gladstone Institute of Cardiovascular Disease, 1650 Owens Street, San Francisco, CA 94158 USA, 2Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, 513 Parnassus Avenue, San Francisco, CA 94143, USA, 3Functional Genomics Laboratory, University of California, Berkeley, CA 94720 USA, 4Department of Biology, Loyola Marymount University, 1 LMU Drive, MS 8220, Los Angeles, CA 90045 USA, 5Computational Biology Graduate Program, Washington University School of Medicine, St. Louis, MO 63108 USA, 6Department of Biomolecular Engineering, University of California, Santa Cruz, CA 95064 USA, 7Department of Medicine, University of California, San Francisco, CA 94143 USA and 8Department of Molecular and Cellular Pharmacology, University of California, San Francisco, CA 94143 USA Email: Nathan Salomonis - [email protected]; Kristina Hanspers - [email protected]; Alexander C Zambon - [email protected]; Karen Vranizan - [email protected]; Steven C Lawlor - [email protected]; Kam D Dahlquist - [email protected]; Scott W Doniger - [email protected]; Josh Stuart - [email protected]; Bruce R Conklin - [email protected]; Alexander R Pico* - [email protected] * Corresponding author Published: 24 June 2007 Received: 16 November 2006 Accepted: 24 June 2007 BMC Bioinformatics 2007, 8:217 doi:10.1186/1471-2105-8-217 This article is available from: http://www.biomedcentral.com/1471-2105/8/217 © 2007 Salomonis et al; licensee BioMed Central Ltd. -
Views for Entrez
BASIC RESEARCH www.jasn.org Phosphoproteomic Analysis Reveals Regulatory Mechanisms at the Kidney Filtration Barrier †‡ †| Markus M. Rinschen,* Xiongwu Wu,§ Tim König, Trairak Pisitkun,¶ Henning Hagmann,* † † † Caroline Pahmeyer,* Tobias Lamkemeyer, Priyanka Kohli,* Nicole Schnell, †‡ †† ‡‡ Bernhard Schermer,* Stuart Dryer,** Bernard R. Brooks,§ Pedro Beltrao, †‡ Marcus Krueger,§§ Paul T. Brinkkoetter,* and Thomas Benzing* *Department of Internal Medicine II, Center for Molecular Medicine, †Cologne Excellence Cluster on Cellular Stress | Responses in Aging-Associated Diseases, ‡Systems Biology of Ageing Cologne, Institute for Genetics, University of Cologne, Cologne, Germany; §Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland; ¶Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; **Department of Biology and Biochemistry, University of Houston, Houston, Texas; ††Division of Nephrology, Baylor College of Medicine, Houston, Texas; ‡‡European Molecular Biology Laboratory–European Bioinformatics Institute, Hinxton, Cambridge, United Kingdom; and §§Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany ABSTRACT Diseases of the kidney filtration barrier are a leading cause of ESRD. Most disorders affect the podocytes, polarized cells with a limited capacity for self-renewal that require tightly controlled signaling to maintain their integrity, viability, and function. Here, we provide an atlas of in vivo phosphorylated, glomerulus- expressed -
Genome-Scale Analysis Identifies Paralog Lethality As a Vulnerability of Chromosome 1P Loss in Cancer
HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Nat Genet Manuscript Author . Author manuscript; Manuscript Author available in PMC 2018 December 28. Published in final edited form as: Nat Genet. 2018 July ; 50(7): 937–943. doi:10.1038/s41588-018-0155-3. Genome-scale analysis identifies paralog lethality as a vulnerability of chromosome 1p loss in cancer Srinivas R. Viswanathan1,2,3, Marina F. Nogueira#1,2, Colin G. Buss#4,5, John M. Krill- Burger2, Mathias J. Wawer6, Edyta Malolepsza2,11, Ashton C. Berger1,2, Peter S. Choi1,2,3, Juliann Shih2, Alison M. Taylor1,2,3, Benjamin Tanenbaum2, Chandra Sekhar Pedamallu1, Andrew D. Cherniack2, Pablo Tamayo2,7, Craig A. Strathdee2, Kasper Lage2,11, Steven A. Carr2, Monica Schenone2, Sangeeta N. Bhatia2,3,4,5,8,9,10, Francisca Vazquez2, Aviad Tsherniak2, William C. Hahn1,2,3, and Matthew Meyerson1,2,3,♦ 1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA 2Broad Institute of MIT and Harvard, Cambridge, MA, USA 3Harvard Medical School, Boston, MA, USA 4Harvard-MIT Department of Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Boston, MA USA 5Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA. 6Chemical Biology and Therapeutics Science Program, Broad Institute of Harvard and MIT, Cambridge, MA, USA 7UCSD Moores Cancer Center and Department of Medicine, University of California, San Diego, La Jolla, California 8Howard Hughes