STX13 Regulates Cargo Delivery from Recycling Endosomes During
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
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. -
Cell-Free Fusion of Bacteria-Containing Phagosomes with Endocytic Compartments
Cell-free fusion of bacteria-containing phagosomes with endocytic compartments Ulrike Becken, Andreas Jeschke, Katharina Veltman1, and Albert Haas2 Cell Biology Institute, University of Bonn, Ulrich-Haberland-Strasse 61a, 53121 Bonn, Germany Edited by Reinhard Jahn, Max Planck Institute for Biophysical Chemistry, Goettingen, Germany, and accepted by the Editorial Board October 4, 2010 (received for review June 2, 2010) Uptake of microorganisms by professional phagocytic cells leads to duced fusion of SCPs with lysosomes compared to phagosomes formation of a new subcellular compartment, the phagosome, containing inert particles (10–12), others did not (13). Fusogeni- which matures by sequential fusion with early and late endocytic city of SCPs with other endocytic organelles in macrophages has compartments, resulting in oxidative and nonoxidative killing of been investigated little (10). the enclosed microbe. Few tools are available to study membrane To truly understand the (dys)function of phagosome matura- fusion between phagocytic and late endocytic compartments in tion at a molecular level, the fusion of endocytic with microbe- general and with pathogen-containing phagosomes in particular. containing phagocytic organelles ought to be investigated in We have developed and applied a fluorescence microscopy assay reconstituted systems, yet most published assays used bead- to study fusion of microbe-containing phagosomes with different- containing but not microbe-containing phagosomes (3, 5) and aged endocytic compartments in vitro. This revealed that fusion were limited to fusion of early phagosomes with early endocytic of phagosomes containing nonpathogenic Escherichia coli with organelles (14, 15). Fusion of lysosomes with microbe-containing lysosomes requires Rab7 and SNARE proteins but not organelle phagosomes has been reconstituted only in permeabilized macro- acidification. -
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. -
Supplementary Materials
1 Supplementary Materials: Supplemental Figure 1. Gene expression profiles of kidneys in the Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice. (A) A heat map of microarray data show the genes that significantly changed up to 2 fold compared between Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice (N=4 mice per group; p<0.05). Data show in log2 (sample/wild-type). 2 Supplemental Figure 2. Sting signaling is essential for immuno-phenotypes of the Fcgr2b-/-lupus mice. (A-C) Flow cytometry analysis of splenocytes isolated from wild-type, Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice at the age of 6-7 months (N= 13-14 per group). Data shown in the percentage of (A) CD4+ ICOS+ cells, (B) B220+ I-Ab+ cells and (C) CD138+ cells. Data show as mean ± SEM (*p < 0.05, **p<0.01 and ***p<0.001). 3 Supplemental Figure 3. Phenotypes of Sting activated dendritic cells. (A) Representative of western blot analysis from immunoprecipitation with Sting of Fcgr2b-/- mice (N= 4). The band was shown in STING protein of activated BMDC with DMXAA at 0, 3 and 6 hr. and phosphorylation of STING at Ser357. (B) Mass spectra of phosphorylation of STING at Ser357 of activated BMDC from Fcgr2b-/- mice after stimulated with DMXAA for 3 hour and followed by immunoprecipitation with STING. (C) Sting-activated BMDC were co-cultured with LYN inhibitor PP2 and analyzed by flow cytometry, which showed the mean fluorescence intensity (MFI) of IAb expressing DC (N = 3 mice per group). 4 Supplemental Table 1. Lists of up and down of regulated proteins Accession No. -
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). -
Supplementary Table 4
Li et al. mir-30d in human cancer Table S4. The probe list down-regulated in MDA-MB-231 cells by mir-30d mimic transfection Gene Probe Gene symbol Description Row set 27758 8119801 ABCC10 ATP-binding cassette, sub-family C (CFTR/MRP), member 10 15497 8101675 ABCG2 ATP-binding cassette, sub-family G (WHITE), member 2 18536 8158725 ABL1 c-abl oncogene 1, receptor tyrosine kinase 21232 8058591 ACADL acyl-Coenzyme A dehydrogenase, long chain 12466 7936028 ACTR1A ARP1 actin-related protein 1 homolog A, centractin alpha (yeast) 18102 8056005 ACVR1 activin A receptor, type I 20790 8115490 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 15688 7979904 ADAM21 ADAM metallopeptidase domain 21 14937 8054254 AFF3 AF4/FMR2 family, member 3 23560 8121277 AIM1 absent in melanoma 1 20209 7921434 AIM2 absent in melanoma 2 19272 8136336 AKR1B10 aldo-keto reductase family 1, member B10 (aldose reductase) 18013 7954777 ALG10 asparagine-linked glycosylation 10, alpha-1,2-glucosyltransferase homolog (S. pombe) 30049 7954789 ALG10B asparagine-linked glycosylation 10, alpha-1,2-glucosyltransferase homolog B (yeast) 28807 7962579 AMIGO2 adhesion molecule with Ig-like domain 2 5576 8112596 ANKRA2 ankyrin repeat, family A (RFXANK-like), 2 23414 7922121 ANKRD36BL1 ankyrin repeat domain 36B-like 1 (pseudogene) 29782 8098246 ANXA10 annexin A10 22609 8030470 AP2A1 adaptor-related protein complex 2, alpha 1 subunit 14426 8107421 AP3S1 adaptor-related protein complex 3, sigma 1 subunit 12042 8099760 ARAP2 ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 2 30227 8059854 ARL4C ADP-ribosylation factor-like 4C 32785 8143766 ARP11 actin-related Arp11 6497 8052125 ASB3 ankyrin repeat and SOCS box-containing 3 24269 8128592 ATG5 ATG5 autophagy related 5 homolog (S. -
Analysis of Mir-34A-5P Over-Expression by Qrt-PCR
Supplementary material files Supplementary Figure 1: Analysis of miR-34a-5p over-expression by qRT-PCR. Primary CD4+ T cells were transfected either with allstars negative control (ANC) or miR-34a-5p mimic. 48 h post transfection the total RNA was isolated and analyzed by qRT-PCR using a specific hsa-miR-34a-5p primer. Supplementary Figure 2: FACS Controls CD4+ T cells were stained for CD4 and co-stained for CD11A or the respective isotype controls for 30 min at 4°C. Cells were analyzed by flow cytometry. Gated CD4+ T cells (A) were analyzed for CD11A expression (B, dark grey) in comparison to isotype controls (light grey). CD8+ T cells were stained for CD8 and co-stained for CD11A or the respective isotype controls for 30 min at 4°C. Cells were analyzed by flow cytometry. Gated CD8+ T cells (C) were analyzed for CD11A expression (D, dark grey) in comparison to isotype controls (light grey). Supplementary Table 1 target cloning sequence ID gene primers (restriction sites are underlined) 5'-VAMP2-SpeI ggactagtccatcatcctcatcatcatc VAMP2 NM_014232.2 3'-VAMP2-NaeI gccggccctcaatcagttcacccaatgag 5'-IKBKE-SpeI ggactagtcacatgaggcatcctgaag IKBKE NM_014002.3 3'-IKBKE-SacI cgagctcgcatagaaagaacaggaggctc 5'-MYH9-SpeI ggactagtcgaagaggtagatggcaaagc MYH9 NM_002473.5 3'-MYH9-SacI cgagctccctttgtgacagcaactggg 5'-MARCH8-SpeI ggactagtgtgtgcgggttgtcattttc MARCH8 NM_001282866.1 3'-MARCH8-SacI cgagctccagaatgcactgagagtggg 5'-KLRK1-SpeI ggactagtgagactgtgcactctatgcctc KLRK1 NM_007360.3 3'-KLRK1-SacI cgagctcccttcttaactgtgaacctgtg 5'-CD11A-SpeI ggactagtgagaaggactctgagagtgg -
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. -
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