Contributions of Epsinr and Gadkin to Clathrin- Mediated Intracellular Trafficking
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VAMP3 and VAMP8 Regulate the Development and Functionality of 5 Parasitophorous Vacuoles Housing Leishmania Amazonensis
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.09.195032; this version posted July 9, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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 4.0 International license. 1 2 3 4 VAMP3 and VAMP8 regulate the development and functionality of 5 parasitophorous vacuoles housing Leishmania amazonensis 6 7 8 Olivier Séguin1, Linh Thuy Mai1, Sidney W. Whiteheart2, Simona Stäger1, Albert Descoteaux1* 9 10 11 12 1Institut national de la recherche scientifique, Centre Armand-Frappier Santé Biotechnologie, 13 Laval, Québec, Canada 14 15 2Department of Molecular and Cellular Biochemistry, University of Kentucky College of 16 Medicine, Lexington, Kentucky, United States of America 17 18 19 *Corresponding author: 20 E-mail: [email protected] 21 22 23 24 Short title: SNAREs and Leishmania-harboring communal parasitophorous vacuoles 25 bioRxiv preprint doi: https://doi.org/10.1101/2020.07.09.195032; this version posted July 9, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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 4.0 International license. 26 ABSTRACT 27 28 To colonize mammalian phagocytic cells, the parasite Leishmania remodels phagosomes into 29 parasitophorous vacuoles that can be either tight-fitting individual or communal. The molecular 30 and cellular bases underlying the biogenesis and functionality of these two types of vacuoles are 31 poorly understood. -
A Yeast Phenomic Model for the Gene Interaction Network Modulating
Louie et al. Genome Medicine 2012, 4:103 http://genomemedicine.com/content/4/12/103 RESEARCH Open Access A yeast phenomic model for the gene interaction network modulating CFTR-ΔF508 protein biogenesis Raymond J Louie3†, Jingyu Guo1,2†, John W Rodgers1, Rick White4, Najaf A Shah1, Silvere Pagant3, Peter Kim3, Michael Livstone5, Kara Dolinski5, Brett A McKinney6, Jeong Hong2, Eric J Sorscher2, Jennifer Bryan4, Elizabeth A Miller3* and John L Hartman IV1,2* Abstract Background: The overall influence of gene interaction in human disease is unknown. In cystic fibrosis (CF) a single allele of the cystic fibrosis transmembrane conductance regulator (CFTR-ΔF508) accounts for most of the disease. In cell models, CFTR-ΔF508 exhibits defective protein biogenesis and degradation rather than proper trafficking to the plasma membrane where CFTR normally functions. Numerous genes function in the biogenesis of CFTR and influence the fate of CFTR-ΔF508. However it is not known whether genetic variation in such genes contributes to disease severity in patients. Nor is there an easy way to study how numerous gene interactions involving CFTR-ΔF would manifest phenotypically. Methods: To gain insight into the function and evolutionary conservation of a gene interaction network that regulates biogenesis of a misfolded ABC transporter, we employed yeast genetics to develop a ‘phenomic’ model, in which the CFTR-ΔF508-equivalent residue of a yeast homolog is mutated (Yor1-ΔF670), and where the genome is scanned quantitatively for interaction. We first confirmed that Yor1-ΔF undergoes protein misfolding and has reduced half-life, analogous to CFTR-ΔF. Gene interaction was then assessed quantitatively by growth curves for approximately 5,000 double mutants, based on alteration in the dose response to growth inhibition by oligomycin, a toxin extruded from the cell at the plasma membrane by Yor1. -
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. -
Protein Identities in Evs Isolated from U87-MG GBM Cells As Determined by NG LC-MS/MS
Protein identities in EVs isolated from U87-MG GBM cells as determined by NG LC-MS/MS. No. Accession Description Σ Coverage Σ# Proteins Σ# Unique Peptides Σ# Peptides Σ# PSMs # AAs MW [kDa] calc. pI 1 A8MS94 Putative golgin subfamily A member 2-like protein 5 OS=Homo sapiens PE=5 SV=2 - [GG2L5_HUMAN] 100 1 1 7 88 110 12,03704523 5,681152344 2 P60660 Myosin light polypeptide 6 OS=Homo sapiens GN=MYL6 PE=1 SV=2 - [MYL6_HUMAN] 100 3 5 17 173 151 16,91913397 4,652832031 3 Q6ZYL4 General transcription factor IIH subunit 5 OS=Homo sapiens GN=GTF2H5 PE=1 SV=1 - [TF2H5_HUMAN] 98,59 1 1 4 13 71 8,048185945 4,652832031 4 P60709 Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 - [ACTB_HUMAN] 97,6 5 5 35 917 375 41,70973209 5,478027344 5 P13489 Ribonuclease inhibitor OS=Homo sapiens GN=RNH1 PE=1 SV=2 - [RINI_HUMAN] 96,75 1 12 37 173 461 49,94108966 4,817871094 6 P09382 Galectin-1 OS=Homo sapiens GN=LGALS1 PE=1 SV=2 - [LEG1_HUMAN] 96,3 1 7 14 283 135 14,70620005 5,503417969 7 P60174 Triosephosphate isomerase OS=Homo sapiens GN=TPI1 PE=1 SV=3 - [TPIS_HUMAN] 95,1 3 16 25 375 286 30,77169764 5,922363281 8 P04406 Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 - [G3P_HUMAN] 94,63 2 13 31 509 335 36,03039959 8,455566406 9 Q15185 Prostaglandin E synthase 3 OS=Homo sapiens GN=PTGES3 PE=1 SV=1 - [TEBP_HUMAN] 93,13 1 5 12 74 160 18,68541938 4,538574219 10 P09417 Dihydropteridine reductase OS=Homo sapiens GN=QDPR PE=1 SV=2 - [DHPR_HUMAN] 93,03 1 1 17 69 244 25,77302971 7,371582031 11 P01911 HLA class II histocompatibility antigen, -
Mig-6 Controls EGFR Trafficking and Suppresses Gliomagenesis
Mig-6 controls EGFR trafficking and suppresses gliomagenesis Haoqiang Yinga,1, Hongwu Zhenga,1, Kenneth Scotta, Ruprecht Wiedemeyera, Haiyan Yana, Carol Lima, Joseph Huanga, Sabin Dhakala, Elena Ivanovab, Yonghong Xiaob,HaileiZhangb,JianHua, Jayne M. Stommela, Michelle A. Leea, An-Jou Chena, Ji-Hye Paika,OresteSegattoc, Cameron Brennand,e, Lisa A. Elferinkf,Y.AlanWanga,b, Lynda China,b,g, and Ronald A. DePinhoa,b,h,2 aDepartment of Medical Oncology, bBelfer Institute for Applied Cancer Science, Belfer Foundation Institute for Innovative Cancer Science, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02115; cLaboratory of Immunology, Istituto Regina Elena, Rome 00158, Italy; dHuman Oncology and Pathogenesis Program and eDepartment of Neurosurgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10065; fDepartment of Neuroscience and Cell Biology, University of Texas Medical Branch, Galveston, TX 77555; gDepartment of Dermatology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115; and hDepartment of Medicine and Genetics, Harvard Medical School, Boston, MA 02115 Edited* by Webster K. Cavenee, Ludwig Institute, University of California, La Jolla, CA, and approved March 8, 2010 (received for review December 23, 2009) Glioblastoma multiforme (GBM) is the most common and lethal structural aberrations that serve as a key pathological driving primary brain cancer that is driven by aberrant signaling of growth force for tumor progression and many of them remain to be factor receptors, particularly the epidermal growth factor receptor characterized (6, 7). GBM possesses a highly rearranged genome (EGFR). EGFR signaling is tightly regulated by receptor endocytosis and high-resolution genome analysis has uncovered myriad and lysosome-mediated degradation, although the molecular somatic alterations on the genomic and epigenetic levels (2, 3). -
UVRAG Is Required for Virus Entry Through Combinatorial Interaction with the Class C-Vps Complex and Snares
UVRAG is required for virus entry through combinatorial interaction with the class C-Vps complex and SNAREs Sara Dolatshahi Pirooza, Shanshan Hea, Tian Zhanga, Xiaowei Zhanga, Zhen Zhaoa, Soohwan Oha, Douglas O’Connella, Payam Khalilzadeha, Samad Amini-Bavil-Olyaeea, Michael Farzanb, and Chengyu Lianga,1 aDepartment of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033; and bDepartment of Infectious Diseases, The Scripps Research Institute, Jupiter, FL 33458 Edited by Peter Palese, Icahn School of Medicine at Mount Sinai, New York, NY, and approved January 15, 2014 (received for review November 4, 2013) Enveloped viruses exploit the endomembrane system to enter host (R)-SNAREs embedded in the other (3). Specifically, syntaxin 7 cells. Through a cascade of membrane-trafficking events, virus-bearing (STX7; Qa), Vti1b (Qb), and STX8 (Qc) on the LE, when paired vesicles fuse with acidic endosomes and/or lysosomes mediated by with VAMP7 (R), mediate the LE fusion with the lysosome, but SNAREs triggering viral fusion. However, the molecular mechanisms when paired with VAMP8 (R), regulate homotypic fusion of the underlying this process remain elusive. Here, we found that UV- LEs (4). The upstream process regulating LE-associated SNARE radiation resistance-associated gene (UVRAG), an autophagic tumor pairing relies on the class C vacuolar protein sorting (Vps) complex suppressor, is required for the entry of the prototypic negative- (hereafter referred to as C-Vps), composed of Vps11, Vps16, strand RNA virus, including influenza A virus and vesicular stoma- Vps18, and Vps33 as core subunits (5, 6). A recent study indicated titis virus, by a mechanism independent of IFN and autophagy. -
Functions of Syntaxin 8 in Human Cytotoxic T Lymphocytes
Aus dem Bereich Biophysik Theoretische und Klinische Medizin der Medizinischen Fakultät der Universität des Saarlandes, Homburg/Saar Functions of Syntaxin 8 in human cytotoxic T lymphocytes Dissertation zur Erlangung des Grades eines Doktors der Naturwissenschaften der Medizinischen Fakultät der UNIVERSITÄT DES SAARLANDES 2013 vorgelegt von: Shruthi. S. Bhat geb.am: 27.03.1985 in Manipal, India Tag des Promotionskolloquiums: __________________________________ Dekan: __________________________________ Vorsitzender: __________________________________ Berichterstatter: __________________________________ __________________________________ __________________________________ __________________________________ To my beloved parents and teachers Index INDEX I ABBREVIATIONS VI ZUSAMMENFASSUNG VII 1. INTRODUCTION 1 1.1. Immune system 1 1.2. Cell mediated and humoral immunity 2 1.3. Cytotoxic T Lymphocytes (CTLs) 4 1.3.1. T Cell Receptor complex 5 1.3.2. Immunological Synapse 6 1.3.3. Lytic granules, the secretory lysosomes in immune cells 7 1.3.3.1. Perforin 8 1.3.3.2. Granzymes, lytic granule serine proteases 9 1.3.4. Fas and Fas ligand pathway 11 1.4. Sorting, delivery and maturation of proteins and vesicles through endosomal pathway 12 1.5. SNARE proteins 15 1.6. SNARE and related proteins in immune cells 17 1.7. Syntaxin 8: the protein of interest 20 1.8. Aims of this study 21 2. MATERIALS AND METHODS 23 2.1. Antibodies and Reagents 23 2.2. Peripheral blood mononuclear cell (PBMC) isolation 23 2.3. Stimulation of PBLs with Staphylococcal enterotoxin A 24 2.4. Positive isolation of CD8+ T lymphocytes 25 2.5. Negative isolation of CD8+ T lymphocytes 26 2.6. siRNA transfection of CTLs 27 I Index 2.7. -
Supplementary Figures 1-14 and Supplementary References
SUPPORTING INFORMATION Spatial Cross-Talk Between Oxidative Stress and DNA Replication in Human Fibroblasts Marko Radulovic,1,2 Noor O Baqader,1 Kai Stoeber,3† and Jasminka Godovac-Zimmermann1* 1Division of Medicine, University College London, Center for Nephrology, Royal Free Campus, Rowland Hill Street, London, NW3 2PF, UK. 2Insitute of Oncology and Radiology, Pasterova 14, 11000 Belgrade, Serbia 3Research Department of Pathology and UCL Cancer Institute, Rockefeller Building, University College London, University Street, London WC1E 6JJ, UK †Present Address: Shionogi Europe, 33 Kingsway, Holborn, London WC2B 6UF, UK TABLE OF CONTENTS 1. Supplementary Figures 1-14 and Supplementary References. Figure S-1. Network and joint spatial razor plot for 18 enzymes of glycolysis and the pentose phosphate shunt. Figure S-2. Correlation of SILAC ratios between OXS and OAC for proteins assigned to the SAME class. Figure S-3. Overlap matrix (r = 1) for groups of CORUM complexes containing 19 proteins of the 49-set. Figure S-4. Joint spatial razor plots for the Nop56p complex and FIB-associated complex involved in ribosome biogenesis. Figure S-5. Analysis of the response of emerin nuclear envelope complexes to OXS and OAC. Figure S-6. Joint spatial razor plots for the CCT protein folding complex, ATP synthase and V-Type ATPase. Figure S-7. Joint spatial razor plots showing changes in subcellular abundance and compartmental distribution for proteins annotated by GO to nucleocytoplasmic transport (GO:0006913). Figure S-8. Joint spatial razor plots showing changes in subcellular abundance and compartmental distribution for proteins annotated to endocytosis (GO:0006897). Figure S-9. Joint spatial razor plots for 401-set proteins annotated by GO to small GTPase mediated signal transduction (GO:0007264) and/or GTPase activity (GO:0003924). -
Isolation and Proteomics of the Insulin Secretory Granule
H OH metabolites OH Review Isolation and Proteomics of the Insulin Secretory Granule Nicholas Norris , Belinda Yau * and Melkam Alamerew Kebede Charles Perkins Centre, School of Medical Sciences, University of Sydney, Camperdown, NSW 2006, Australia; [email protected] (N.N.); [email protected] (M.A.K.) * Correspondence: [email protected] Abstract: Insulin, a vital hormone for glucose homeostasis is produced by pancreatic beta-cells and when secreted, stimulates the uptake and storage of glucose from the blood. In the pancreas, insulin is stored in vesicles termed insulin secretory granules (ISGs). In Type 2 diabetes (T2D), defects in insulin action results in peripheral insulin resistance and beta-cell compensation, ultimately leading to dysfunctional ISG production and secretion. ISGs are functionally dynamic and many proteins present either on the membrane or in the lumen of the ISG may modulate and affect different stages of ISG trafficking and secretion. Previously, studies have identified few ISG proteins and more recently, proteomics analyses of purified ISGs have uncovered potential novel ISG proteins. This review summarizes the proteins identified in the current ISG proteomes from rat insulinoma INS-1 and INS-1E cell lines. Here, we also discuss techniques of ISG isolation and purification, its challenges and potential future directions. Keywords: insulin secretory granule; beta-cells; granule protein purification 1. Insulin Granule Biogenesis and Function Citation: Norris, N.; Yau, B.; Kebede, The insulin secretory granule (ISG) is the storage vesicle for insulin in pancreatic M.A. Isolation and Proteomics of the beta-cells. It was long treated as an inert carrier for insulin but is now appreciated as a Insulin Secretory Granule. -
WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT (51) International Patent Classification: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, C12Q 1/68 (2018.01) A61P 31/18 (2006.01) DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, C12Q 1/70 (2006.01) HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (21) International Application Number: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, PCT/US2018/056167 OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (22) International Filing Date: SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 16 October 2018 (16. 10.2018) TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, (26) Publication Language: English GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, (30) Priority Data: UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, 62/573,025 16 October 2017 (16. 10.2017) US TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, ΓΕ , IS, IT, LT, LU, LV, (71) Applicant: MASSACHUSETTS INSTITUTE OF MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TECHNOLOGY [US/US]; 77 Massachusetts Avenue, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, Cambridge, Massachusetts 02139 (US). -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Identification of Potential Key Genes and Pathway Linked with Sporadic Creutzfeldt-Jakob Disease Based on Integrated Bioinformatics Analyses
medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Identification of potential key genes and pathway linked with sporadic Creutzfeldt-Jakob disease based on integrated bioinformatics analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Abstract Sporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened.