DOCSLIB.ORG

Appendix: Receptor Proteins #          

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Appendix: Receptor Proteins #           Ligand-gated ion channels 1023 Receptors with intrinsic enzyme function 1026 Receptor tyrosine kinases (RTKs) 1026 Receptor serine/theorine kinases 1028 Receptor-linked guanylyl cyclases 1028 G-protein coupled receptors (GPCRs) 1028 Receptors 1028 Heterotrimeric G-proteins 1035 RGS proteins 1036 Cytokine receptors (Jak/STAT-coupled) 1037 TNF receptor superfamily 1038 IL-1 / toll-like receptors 1039 Nuclear receptors 1040 Channel proteins 1043 Sodium channels 1043 Potassium channels 1044 Voltage-dependent Ca2+-channels 1047 Chloride channels 1048 Cation channels 1049 TRP channels 1049 Cyclic nucleotide-regulated cation channels 1050 Calcium release channels 1050 Water channels 1051 Solute carriers (transporters) 1052 Transport ATPases (ATP-powered pumps) 1058 P-type ATPases 1058 V-type ATPases 1059 F-type ATPases 1060 ABC-transporter 1060 " Cadherins 1063 Classic cadherins 1063 Protocadherins 1064 Integrins 1066 Selectins 1067 Syndecans 1067 Immunoglobulin superfamily 1067 1022 "$ Serine/threonine kinases 1069 AGC (PKA, PKG and PKC containing) group 1069 CAMK (Calcium-calmodulin dependent protein kinase) group 1071 CK1 (Casein kinase 1) group 1073 CMGC (CDK, MAPK, GSK3 and CLK containing) group 1073 RGC (Receptor guanylyl cyclase) group 1074 STE (Sterile-7, -11 and -20 homologous) group 1075 TKL (Tyrosine kinase-like) group 1076 Atypical group 1077 Other groups 1078 Tyrosine kinases 1080 RTK (Receptor tyrosine kinase) group 1080 NRTK (Non-receptor tyrosine kinase) group 1081 % Receptor proteins are specialized structures that are able to nases, receptor serine/threonine kinases or receptor recognize mostly diffusable molecules with a very high spe- guanylyl cyclases. cificity and that are able to reversibly bind them with a high Receptors without intrinsic effector function interact with affinity. Ligand binding to the receptor initiates a signal proteins that are either effectors themselves or that can reg- transduction process which propagates the message of the ulate effectors. The largest group of such receptors are the G- ligand. There are many different types of receptors that dif- protein coupled receptors (GPCRs). Via heterotrimeric G- fer especially in their mode of signal propagation. Most re- proteins they are able to regulate the activity of a variety of ceptors are cell-surface receptors and respond to ligands effector proteins (enzymes, ion channels). Other receptors that usually cannot enter the cell. Lipophilic molecules (e.g. such as the cytokine receptors interact with and activate cy- steroids), however, are able to enter the cell and can act on tosolic protein kinases (Jak-family) upon ligand binding. A intracellular receptors. third group of receptors (TNF-receptor superfamily, IL-1/Toll- The group of cell-surface receptors can be subdivid- like receptors) recruit adaptor proteins (e.g. TRADD, MyD88) ed into those with an intrinsic effector function (en- following ligand-dependent activation which then serve as a zymes, ion channels) and others without intrinsic platform for the formation of an effector complex consisting effector function. The first group consists of receptor of various other proteins. operated ion channels or receptors with intrinsic enzy- The majority of intracellular receptors are so-called “nu- matic activity. In both cases the intrinsic effector func- clear receptors”. They are transcription factors that reside in tion is regulated by ligand binding. Receptors linked to the cytoplasm or nucleus and upon ligand binding translo- an intrinsic enzymatic activity are receptor tyrosine ki- cate to the nucleus to become transcriptionally active. Ligand-operated ion channels generate electrical signals in units two of which bind the ligand. Each subunit has four response to specific chemical neurotransmitters and are transmembrane domains. Heteropentameric channels are specialized in mediating the fast chemical synaptic trans- formed by GABAA-, glycine- nicotinic acetylcholine and, mission. Depending on their ion selectivity, ligand-gated 5-HT3-receptors. In contrast, the cation-selective iono- ion channels are either excitatory (glutamate-, P2X-, nico- tropic glutamate receptors have four subunits. Each subu- tinic, 5-HT3-receptors) or inhibitory (GABAA-, glycine-re- nit is able to bind glutamate. P2X purinoceptors subunits, ceptors). Ligand-gated ion channels can be grouped in finally, have only two transmembrane segments. P2X re- three distinct families based on the architecture of the ceptors are made up of three or four subunits. (᭤ Nicotinic channel. Most known ligand-operated ion channels con- Receptor, ᭤ Ionotropic Glutamate Receptor, ᭤ GABAergic sist of five subunits. This pentamer contains different sub- System, ᭤ Glycine Receptor). Receptor-subunit Ion selectivity Endogenous Ligand Ionotropic glutamate receptors NMDA receptors (tetrameric) NR1 Na+/K+/(Ca2+)Glutamate, Glycine NR2A Na+/K+/(Ca2+)Glutamate, Glycine NR2B Na+/K+/(Ca2+)Glutamate, Glycine NR2C Na+/K+/(Ca2+)Glutamate, Glycine NR2D Na+/K+/(Ca2+)Glutamate, Glycine NR3 Na+/K+/(Ca2+)Glutamate, Glycine AMPA receptors (tetrameric) GluR1 (GluR-A) Na+/K+ Glutamate GluR2 (GluR-B) Na+/K+ Glutamate GluR3 (GluR-C) Na+/K+ Glutamate GluR4 (GluR-D) Na+/K+ Glutamate 1024 Receptor Proteins Receptor-subunit Ion selectivity Endogenous Ligand Kainate receptors (tetrameric) GluR5 Na+/K+ Glutamate GluR6 Na+/K+ Glutamate GluR7 Na+/K+ Glutamate KA1 Na+/K+ Glutamate KA2 Na+/K+ Glutamate Purinoceptors (P2X) (trimeric) + + 2+ P2X1 Na /K /(Ca )ATP + + 2+ P2X2 Na /K /(Ca )ATP + + 2+ P2X3 Na /K /(Ca )ATP + + 2+ P2X4 Na /K /(Ca )ATP + + 2+ P2X5 Na /K /(Ca )ATP + + 2+ P2X6 Na /K /(Ca )ATP + + 2+ P2X7 Na /K /(Ca )ATP Nicotinic acetylcholine receptors (nAChR) (pentameric) Ligand-binding α1Na+/K+ Acetylcholine α2Na+/K+ Acetylcholine α3Na+/K+ Acetylcholine α4Na+/K+ Acetylcholine α6Na+/K+ Acetylcholine α7Na+/K+ Acetylcholine α8Na+/K+ Acetylcholine α9Na+/K+ Acetylcholine α10 Na+/K+ Acetylcholine Non-ligand-binding β1Na+/K+ β2Na+/K+ β3Na+/K+ β4Na+/K+ γ Na+/K+ δ Na+/K+ ε Na+/K+ Ionotropic serotonin receptors (5-HT3) (pentameric) + + 5-HT3A Na /K Serotonin + + 5-HT3B Na /K Serotonin Receptor-subunit Ion selectivity Endogenous Ligand GABAA receptors (pentameric) Ligand-binding α1Cl¯γ-Aminobutyric acid, (Benzodiazepines) α2Cl¯γ-Aminobutyric acid, (Benzodiazepines) α3Cl¯γ-Aminobutyric acid, (Benzodiazepines) α4Cl¯γ-Aminobutyric acid α5Cl¯γ-Aminobutyric acid, (Benzodiazepines) α6Cl¯γ-Aminobutyric acid Receptor Proteins 1025 Receptor-subunit Ion selectivity Endogenous Ligand Non-ligand-binding β1Cl¯ β2Cl¯ β3Cl¯ γ1Cl¯ γ2Cl¯ γ3Cl¯ δ Cl¯ ε Cl¯ θ Cl¯ ρ1Cl¯ ρ2Cl¯ ρ3Cl¯ Glycine receptors (GlyR) (pentameric) Ligand-binding α1Cl¯Glycine α2Cl¯Glycine α3Cl¯Glycine α4Cl¯Glycine Non-ligand-binding β Cl¯ 1026 Receptor Proteins Receptor tyrosine kinases (RTKs) are a group of trans- toplasmic domains. Tyrosine autophosphorylation of membrane receptors with an intrinsic tyrosine kinase ac- RTKs induces recruitment and activation of various sign- tivity. RTKs possess an extracellular ligand binding aling molecules via the interaction of SH2 (src homology domain and an intracellular conserved tyrosine kinase do- 2) or PTB (phosphotyrosine binding) domains with tyro- main. Almost 60 genes encoding RTKs have been identi- sine autophosphorylation sites at the cytoplasmic region. fied in the mammalian genome (Robinson et al., 2000, Some RTK ligands (e.g. FGFs) require accessory molecules Oncogene 19, 5548-5557). With the exception of members of for receptor activation. While some RTKs homodimerize, α β the insulin-receptor family that form 2 2 heterodimers, heterodimerization is a common feature among different all known RTKs are monomers which dimerize upon lig- RTK subfamilies. (᭤ Growth Factors, ᭤ Neurotrophic and binding resulting in autophosphorylation of their cy- Factors, ᭤ Insulin Receptor). Receptor Endogenous ligand(s) ErbB receptor family ErbB1 (EGFR) Epidermal growth factor (EGF), Heparin-binding (HB)- EGF, Transforming growth factor α (TGFα), Amphiregulin (AR), Betacellulin (BTC), Epiregulin (EPR) ErbB2 (Neu, HER2) dimerization partner for ErbB1,3,4 , no ligand so far found ErbB3 (HER3) Neuregulin-1 (Heregulin), Neuregulin-2 ErbB4 (HER4) Neuregulin-1, -2, -3, -4; BTC, HB-EGF, EPR Insulin-receptor family InsR Insulin IGF-1R Insulin-like growth factor-1 (IGF-1), IGF-2 InsRR (IRR) ? Platelet-derived growth factor-receptor family PDGFR-α / PDGFR-α PDGF-CC, PDGF-AA, PDGF-AB, PDGF-BB PDGFR-β / PDGFR-β PDGF-BB, PDGF-DD PDGFR-α / PDGFR-β PDGF-AA, PDGF-AB CSF-1R Colony stimulating factor (CSF) Kit/SCFR Stem cell factor (SCF, Steel factor) Flk2/Flt3 Flt3 Ligand Vascular endothelial growth factor (VEGF) receptor family VEGF-R1 (Flt-1) Placenta growth factor (PlGF), VEGF-A, VEGF-B VEGF-R2 (Flk-1) VEGF-A, VEGF-C, VEGF-D VEGF-R3 (Flt-4) VEGF-C, VEGF-D Fibroblast growth factor (FGF) receptor family FGF-R-1 FGF-1, -2, -3, -4, -5, -6, -10 FGF-R-2 FGF-1, -2, -3, -4, -5, -6, -7, -8, -9, -10 FGF-R-3 FGF-1, -2, -4, -8, -9 FGF-R-4 FGF-1, -2, -4, -6, -8, -9 KLG/CCK receptor family CCK4/PTK7 ? Nerve growth factor (NGF) receptor family TrkA Nerve growth factor (NGF) TrkB Brain derived neurotrophic factor (BDNF), Neurotrophin 4 (NT4), Neurotrophin 5, (NT5) TrkC Neurotrophin 3 (NT3) Receptor Proteins 1027 Receptor Endogenous ligand(s) Hepatocyte growth factor (HGF) receptor family Met HGF (Scatter factor) Ron/Skt Macrophage-stimulating protein (MSP) Eph family receptors EphA1 Ephrin-A1
Load more

Recommended publications
  • Establishing the Pathogenicity of Novel Mitochondrial DNA Sequence Variations: a Cell and Molecular Biology Approach
    Mafalda Rita Avó Bacalhau Establishing the Pathogenicity of Novel Mitochondrial DNA Sequence Variations: a Cell and Molecular Biology Approach Tese de doutoramento do Programa de Doutoramento em Ciências da Saúde, ramo de Ciências Biomédicas, orientada pela Professora Doutora Maria Manuela Monteiro Grazina e co-orientada pelo Professor Doutor Henrique Manuel Paixão dos Santos Girão e pela Professora Doutora Lee-Jun C. Wong e apresentada à Faculdade de Medicina da Universidade de Coimbra Julho 2017 Faculty of Medicine Establishing the pathogenicity of novel mitochondrial DNA sequence variations: a cell and molecular biology approach Mafalda Rita Avó Bacalhau Tese de doutoramento do programa em Ciências da Saúde, ramo de Ciências Biomédicas, realizada sob a orientação científica da Professora Doutora Maria Manuela Monteiro Grazina; e co-orientação do Professor Doutor Henrique Manuel Paixão dos Santos Girão e da Professora Doutora Lee-Jun C. Wong, apresentada à Faculdade de Medicina da Universidade de Coimbra. Julho, 2017 Copyright© Mafalda Bacalhau e Manuela Grazina, 2017 Esta cópia da tese é fornecida na condição de que quem a consulta reconhece que os direitos de autor são pertença do autor da tese e do orientador científico e que nenhuma citação ou informação obtida a partir dela pode ser publicada sem a referência apropriada e autorização. This copy of the thesis has been supplied on the condition that anyone who consults it recognizes that its copyright belongs to its author and scientific supervisor and that no quotation from the
    [Show full text]
  • Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
    Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A.
    [Show full text]
  • Seq2pathway Vignette
    seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway.
    [Show full text]
  • Iron Depletion Reduces Abce1 Transcripts While Inducing The
    Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 22 October 2019 doi:10.20944/preprints201910.0252.v1 1 Research Article 2 Iron depletion Reduces Abce1 Transcripts While 3 Inducing the Mitophagy Factors Pink1 and Parkin 4 Jana Key 1,2, Nesli Ece Sen 1, Aleksandar Arsovic 1, Stella Krämer 1, Robert Hülse 1, Suzana 5 Gispert-Sanchez 1 and Georg Auburger 1,* 6 1 Experimental Neurology, Goethe University Medical School, 60590 Frankfurt am Main; 7 2 Faculty of Biosciences, Goethe-University Frankfurt am Main, Germany 8 * Correspondence: [email protected] 9 10 Abstract: Lifespan extension was recently achieved in Caenorhabditis elegans nematodes by 11 mitochondrial stress and mitophagy, triggered via iron depletion. Conversely in man, deficient 12 mitophagy due to Pink1/Parkin mutations triggers iron accumulation in patient brain and limits 13 survival. We now aimed to identify murine fibroblast factors, which adapt their mRNA expression 14 to acute iron manipulation, relate to mitochondrial dysfunction and may influence survival. After 15 iron depletion, expression of the plasma membrane receptor Tfrc with its activator Ireb2, the 16 mitochondrial membrane transporter Abcb10, the heme-release factor Pgrmc1, the heme- 17 degradation enzyme Hmox1, the heme-binding cholesterol metabolizer Cyp46a1, as well as the 18 mitophagy regulators Pink1 and Parkin showed a negative correlation to iron levels. After iron 19 overload, these factors did not change expression. Conversely, a positive correlation of mRNA levels 20 with both conditions of iron availability was observed for the endosomal factors Slc11a2 and Steap2, 21 as well as for the iron-sulfur-cluster (ISC)-containing factors Ppat, Bdh2 and Nthl1.
    [Show full text]
  • Stelios Pavlidis3, Matthew Loza3, Fred Baribaud3, Anthony
    Supplementary Data Th2 and non-Th2 molecular phenotypes of asthma using sputum transcriptomics in UBIOPRED Chih-Hsi Scott Kuo1.2, Stelios Pavlidis3, Matthew Loza3, Fred Baribaud3, Anthony Rowe3, Iaonnis Pandis2, Ana Sousa4, Julie Corfield5, Ratko Djukanovic6, Rene 7 7 8 2 1† Lutter , Peter J. Sterk , Charles Auffray , Yike Guo , Ian M. Adcock & Kian Fan 1†* # Chung on behalf of the U-BIOPRED consortium project team 1Airways Disease, National Heart & Lung Institute, Imperial College London, & Biomedical Research Unit, Biomedical Research Unit, Royal Brompton & Harefield NHS Trust, London, United Kingdom; 2Department of Computing & Data Science Institute, Imperial College London, United Kingdom; 3Janssen Research and Development, High Wycombe, Buckinghamshire, United Kingdom; 4Respiratory Therapeutic Unit, GSK, Stockley Park, United Kingdom; 5AstraZeneca R&D Molndal, Sweden and Areteva R&D, Nottingham, United Kingdom; 6Faculty of Medicine, Southampton University, Southampton, United Kingdom; 7Faculty of Medicine, University of Amsterdam, Amsterdam, Netherlands; 8European Institute for Systems Biology and Medicine, CNRS-ENS-UCBL, Université de Lyon, France. †Contributed equally #Consortium project team members are listed under Supplementary 1 Materials *To whom correspondence should be addressed: [email protected] 2 List of the U-BIOPRED Consortium project team members Uruj Hoda & Christos Rossios, Airways Disease, National Heart & Lung Institute, Imperial College London, UK & Biomedical Research Unit, Biomedical Research Unit, Royal
    [Show full text]
  • The Purification and Identification of Interactors to Elucidate Novel Connections in the HEK 293 Cell Line
    The Purification and Identification of Interactors to Elucidate Novel Connections in the HEK 293 Cell Line Brett Hawley Biochemistry, Microbiology and Immunology Faculty of Medicine University of Ottawa © Brett Hawley, Ottawa, Canada, 2012 ABSTRACT The field of proteomics studies the structure and function of proteins in a large scale and high throughput manner. My work in the field of proteomics focuses on identifying interactions between proteins and discovering novel interactions. The identification of these interactions provides new information on metabolic and disease pathways and the working proteome of a cell. Cells are lysed and purified using antibody based affinity purification followed by digestion and identification using an HPLC coupled to a mass spectrometer. In my studies, I looked at the interaction networks of several AD related genes (Apolipoprotein E, Clusterin variant 1 and 2, Low-density lipoprotein receptor, Phosphatidylinositol binding clathrin assembly protein, Alpha- synuclein and Platelet-activating factor receptor) and an endosomal recycling pathway involved in cholesterol metabolism (Eps15 homology domain 1,2 and 4, Proprotein convertase subtilisin/kexin type 9 and Low-density lipoprotein receptor). Several novel and existing interactors were identified and these interactions were validated using co-immunopurification, which could be the basis for future research. ii ACKNOWLEDGEMENTS I would like to take this opportunity to thank my supervisor, Dr. Daniel Figeys, for his support and guidance throughout my studies in his lab. It was a great experience to work in his lab and I am very thankful I was given the chance to learn and work under him. I would also like to thank the members of my lab for all their assistance in learning new techniques and equipment in the lab.
    [Show full text]
  • 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.
    [Show full text]
  • PROTEOMIC ANALYSIS of HUMAN URINARY EXOSOMES. Patricia
    ABSTRACT Title of Document: PROTEOMIC ANALYSIS OF HUMAN URINARY EXOSOMES. Patricia Amalia Gonzales Mancilla, Ph.D., 2009 Directed By: Associate Professor Nam Sun Wang, Department of Chemical and Biomolecular Engineering Exosomes originate as the internal vesicles of multivesicular bodies (MVBs) in cells. These small vesicles (40-100 nm) have been shown to be secreted by most cell types throughout the body. In the kidney, urinary exosomes are released to the urine by fusion of the outer membrane of the MVBs with the apical plasma membrane of renal tubular epithelia. Exosomes contain apical membrane and cytosolic proteins and can be isolated using differential centrifugation. The analysis of urinary exosomes provides a non- invasive means of acquiring information about the physiological or pathophysiological state of renal cells. The overall objective of this research was to develop methods and knowledge infrastructure for urinary proteomics. We proposed to conduct a proteomic analysis of human urinary exosomes. The first objective was to profile the proteome of human urinary exosomes using liquid chromatography-tandem spectrometry (LC- MS/MS) and specialized software for identification of peptide sequences from fragmentation spectra. We unambiguously identified 1132 proteins. In addition, the phosphoproteome of human urinary exosomes was profiled using the neutral loss scanning acquisition mode of LC-MS/MS. The phosphoproteomic profiling identified 19 phosphorylation sites corresponding to 14 phosphoproteins. The second objective was to analyze urinary exosomes samples isolated from patients with genetic mutations. Polyclonal antibodies were generated to recognize epitopes on the gene products of these genetic mutations, NKCC2 and MRP4. The potential usefulness of urinary exosome analysis was demonstrated using the well-defined renal tubulopathy, Bartter syndrome type I and using the single nucleotide polymorphism in the ABCC4 gene.
    [Show full text]
  • 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,
    [Show full text]
  • 4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
    Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4).
    [Show full text]
  • Supplementary Table S1. Prioritization of Candidate FPC Susceptibility Genes by Private Heterozygous Ptvs
    Supplementary Table S1. Prioritization of candidate FPC susceptibility genes by private heterozygous PTVs Number of private Number of private Number FPC patient heterozygous PTVs in heterozygous PTVs in tumors with somatic FPC susceptibility Hereditary cancer Hereditary Gene FPC kindred BCCS samples mutation DNA repair gene Cancer driver gene gene gene pancreatitis gene ATM 19 1 - Yes Yes Yes Yes - SSPO 12 8 1 - - - - - DNAH14 10 3 - - - - - - CD36 9 3 - - - - - - TET2 9 1 - - Yes - - - MUC16 8 14 - - - - - - DNHD1 7 4 1 - - - - - DNMT3A 7 1 - - Yes - - - PKHD1L1 7 9 - - - - - - DNAH3 6 5 - - - - - - MYH7B 6 1 - - - - - - PKD1L2 6 6 - - - - - - POLN 6 2 - Yes - - - - POLQ 6 7 - Yes - - - - RP1L1 6 6 - - - - - - TTN 6 5 4 - - - - - WDR87 6 7 - - - - - - ABCA13 5 3 1 - - - - - ASXL1 5 1 - - Yes - - - BBS10 5 0 - - - - - - BRCA2 5 6 1 Yes Yes Yes Yes - CENPJ 5 1 - - - - - - CEP290 5 5 - - - - - - CYP3A5 5 2 - - - - - - DNAH12 5 6 - - - - - - DNAH6 5 1 1 - - - - - EPPK1 5 4 - - - - - - ESYT3 5 1 - - - - - - FRAS1 5 4 - - - - - - HGC6.3 5 0 - - - - - - IGFN1 5 5 - - - - - - KCP 5 4 - - - - - - LRRC43 5 0 - - - - - - MCTP2 5 1 - - - - - - MPO 5 1 - - - - - - MUC4 5 5 - - - - - - OBSCN 5 8 2 - - - - - PALB2 5 0 - Yes - Yes Yes - SLCO1B3 5 2 - - - - - - SYT15 5 3 - - - - - - XIRP2 5 3 1 - - - - - ZNF266 5 2 - - - - - - ZNF530 5 1 - - - - - - ACACB 4 1 1 - - - - - ALS2CL 4 2 - - - - - - AMER3 4 0 2 - - - - - ANKRD35 4 4 - - - - - - ATP10B 4 1 - - - - - - ATP8B3 4 6 - - - - - - C10orf95 4 0 - - - - - - C2orf88 4 0 - - - - - - C5orf42 4 2 - - - -
    [Show full text]
  • Dependent Traits in Mice Models of Hyperthyroidism and Hypothyroidism
    Phenotypical characterization of sex- dependent traits in mice models of hyperthyroidism and hypothyroidism Inaugural-Dissertation zur Erlangung des Doktorgrades Dr. rer. nat. der Fakultät für Biologie an der Universität Duisburg-Essen vorgelegt von Helena Rakov aus St. Petropawlowsk April 2017 Die der vorliegenden Arbeit zugrunde liegenden Experimente wurden am Universitätsklinikum Essen in der Klinik für Endokrinologie und Stoffwechselerkrankungen durchgeführt. 1. Gutachter: Prof. Dr. Dr. Dagmar Führer-Sakel 2. Gutachter: Prof. Dr. Elke Cario Vorsitzender des Prüfungsausschusses: Prof. Dr. Ruth Grümmer Tag der mündlichen Prüfung: 17.07.2017 Publications Publications Engels Kathrin*, Rakov Helena *, Zwanziger Denise, Moeller Lars C., Homuth Georg, Köhrle Josef, Brix Klaudia, Fuhrer Dagmar. Differences in mouse hepatic thyroid hormone transporter expression with age and hyperthyroidism. Eur Thyroid J 2015;4(suppl 1):81–86. DOI: 10.1159/000381020. *contributed equally Zwanziger Denise*, Rakov Helena*, Engels Kathrin, Moeller Lars C., Fuhrer Dagmar. Sex-dependent claudin-1 expression in liver of eu- and hypothyroid mice. Eur Thyroid J. 2015 Sep; 4(Suppl 1): 67–73. DOI: 10.1159/000431316. *contributed equally Engels Kathrin*, Rakov Helena*, Zwanziger Denise, Hoenes Georg Sebastian, Rehders Maren, Brix Klaudia, Koehrle Josef, Moeller Lars Christian, Fuhrer Dagmar. Efficacy of protocols for induction of chronic hyperthyroidism in male and female mice. Endocrine. 2016 Oct;54(1):47-54. DOI: 10.1007/s12020-016-1020-8. Rakov Helena*, Engels Kathrin*, Hönes Georg Sebastian, Strucksberg Karl-Heinz, Moeller Lars Christian, Köhrle Josef, Zwanziger Denise, Führer Dagmar. Sex-specific phenotypes of hyperthyroidism and hypothyroidism in mice. Biol Sex Differ. 2016 Aug 24;7(1):36. DOI: 10.1186/s13293-016-0089-3.
    [Show full text]