IMMUNE RESPONSE 2 Antibodies for Immune Response
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
The Role of the Ubiquitin Ligase Nedd4-1 in Skeletal Muscle Atrophy
The Role of the Ubiquitin Ligase Nedd4-1 in Skeletal Muscle Atrophy by Preena Nagpal A thesis submitted in conformity with the requirements for the degree of Masters in Medical Science Institute of Medical Science University of Toronto © Copyright by Preena Nagpal 2012 The Role of the Ubiquitin Ligase Nedd4-1 in Skeletal Muscle Atrophy Preena Nagpal Masters in Medical Science Institute of Medical Science University of Toronto 2012 Abstract Skeletal muscle (SM) atrophy complicates many illnesses, diminishing quality of life and increasing disease morbidity, health resource utilization and health care costs. In animal models of muscle atrophy, loss of SM mass results predominantly from ubiquitin-mediated proteolysis and ubiquitin ligases are the key enzymes that catalyze protein ubiquitination. We have previously shown that ubiquitin ligase Nedd4-1 is up-regulated in a rodent model of denervation- induced SM atrophy and the constitutive expression of Nedd4-1 is sufficient to induce myotube atrophy in vitro, suggesting an important role for Nedd4-1 in the regulation of muscle mass. In this study we generate a Nedd4-1 SM specific-knockout mouse and demonstrate that the loss of Nedd4-1 partially protects SM from denervation-induced atrophy confirming a regulatory role for Nedd4-1 in the maintenance of muscle mass in vivo. Nedd4-1 did not signal downstream through its known substrates Notch-1, MTMR4 or FGFR1, suggesting a novel substrate mediates Nedd4-1’s induction of SM atrophy. ii Acknowledgments and Contributions I would like to thank my supervisor, Dr. Jane Batt, for her undying support throughout my time in the laboratory. -
CD81 Antibody (C-Term) Purified Rabbit Polyclonal Antibody (Pab) Catalog # AP6631B
10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 CD81 Antibody (C-term) Purified Rabbit Polyclonal Antibody (Pab) Catalog # AP6631B Specification CD81 Antibody (C-term) - Product Information Application WB, IHC-P, FC,E Primary Accession P60033 Reactivity Human, Mouse Host Rabbit Clonality Polyclonal Isotype Rabbit Ig Antigen Region 176-203 CD81 Antibody (C-term) - Additional Information Gene ID 975 Other Names CD81 antigen, 26 kDa cell surface protein TAPA-1, Target of the antiproliferative antibody 1, Tetraspanin-28, Tspan-28, Western blot analysis of CD81 Antibody CD81, CD81, TAPA1, TSPAN28 (C-term) (Cat. #AP6631b) in mouse kidney(lane 1) and cerebellum(lane 2) tissue Target/Specificity lysates (35ug/lane). CD81 (arrow) was This CD81 antibody is generated from detected using the purified Pab. rabbits immunized with a KLH conjugated synthetic peptide between 176-203 amino acids from the C-terminal region of human CD81. Dilution WB~~1:1000 IHC-P~~1:10~50 FC~~1:10~50 Format Purified polyclonal antibody supplied in PBS with 0.09% (W/V) sodium azide. This antibody is prepared by Saturated Ammonium Sulfate (SAS) precipitation followed by dialysis against PBS. Storage Maintain refrigerated at 2-8°C for up to 2 Formalin-fixed and paraffin-embedded weeks. For long term storage store at -20°C in small aliquots to prevent freeze-thaw human brain tissue with CD81 Antibody cycles. (C-term), which was peroxidase-conjugated to the secondary antibody, followed by DAB Precautions staining. This data demonstrates the use of CD81 Antibody (C-term) is for research use this antibody for immunohistochemistry; Page 1/4 10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 only and not for use in diagnostic or clinical relevance has not been evaluated. -
Versican V2 Assembles the Extracellular Matrix Surrounding the Nodes of Ranvier in the CNS
The Journal of Neuroscience, June 17, 2009 • 29(24):7731–7742 • 7731 Cellular/Molecular Versican V2 Assembles the Extracellular Matrix Surrounding the Nodes of Ranvier in the CNS María T. Dours-Zimmermann,1 Konrad Maurer,2 Uwe Rauch,3 Wilhelm Stoffel,4 Reinhard Fa¨ssler,5 and Dieter R. Zimmermann1 Institutes of 1Surgical Pathology and 2Anesthesiology, University Hospital Zurich, CH-8091 Zurich, Switzerland, 3Vascular Wall Biology, Department of Experimental Medical Science, University of Lund, S-221 00 Lund, Sweden, 4Center for Biochemistry, Medical Faculty, University of Cologne, D-50931 Cologne, Germany, and 5Department of Molecular Medicine, Max Planck Institute of Biochemistry, D-82152 Martinsried, Germany The CNS-restricted versican splice-variant V2 is a large chondroitin sulfate proteoglycan incorporated in the extracellular matrix sur- rounding myelinated fibers and particularly accumulating at nodes of Ranvier. In vitro, it is a potent inhibitor of axonal growth and therefore considered to participate in the reduction of structural plasticity connected to myelination. To study the role of versican V2 during postnatal development, we designed a novel isoform-specific gene inactivation approach circumventing early embryonic lethality of the complete knock-out and preventing compensation by the remaining versican splice variants. These mice are viable and fertile; however, they display major molecular alterations at the nodes of Ranvier. While the clustering of nodal sodium channels and paranodal structures appear in versican V2-deficient mice unaffected, the formation of the extracellular matrix surrounding the nodes is largely impaired. The conjoint loss of tenascin-R and phosphacan from the perinodal matrix provide strong evidence that versican V2, possibly controlled by a nodal receptor, organizes the extracellular matrix assembly in vivo. -
And MMP-Mediated Cell–Matrix Interactions in the Tumor Microenvironment
International Journal of Molecular Sciences Review Hold on or Cut? Integrin- and MMP-Mediated Cell–Matrix Interactions in the Tumor Microenvironment Stephan Niland and Johannes A. Eble * Institute of Physiological Chemistry and Pathobiochemistry, University of Münster, 48149 Münster, Germany; [email protected] * Correspondence: [email protected] Abstract: The tumor microenvironment (TME) has become the focus of interest in cancer research and treatment. It includes the extracellular matrix (ECM) and ECM-modifying enzymes that are secreted by cancer and neighboring cells. The ECM serves both to anchor the tumor cells embedded in it and as a means of communication between the various cellular and non-cellular components of the TME. The cells of the TME modify their surrounding cancer-characteristic ECM. This in turn provides feedback to them via cellular receptors, thereby regulating, together with cytokines and exosomes, differentiation processes as well as tumor progression and spread. Matrix remodeling is accomplished by altering the repertoire of ECM components and by biophysical changes in stiffness and tension caused by ECM-crosslinking and ECM-degrading enzymes, in particular matrix metalloproteinases (MMPs). These can degrade ECM barriers or, by partial proteolysis, release soluble ECM fragments called matrikines, which influence cells inside and outside the TME. This review examines the changes in the ECM of the TME and the interaction between cells and the ECM, with a particular focus on MMPs. Keywords: tumor microenvironment; extracellular matrix; integrins; matrix metalloproteinases; matrikines Citation: Niland, S.; Eble, J.A. Hold on or Cut? Integrin- and MMP-Mediated Cell–Matrix 1. Introduction Interactions in the Tumor Microenvironment. -
Propranolol-Mediated Attenuation of MMP-9 Excretion in Infants with Hemangiomas
Supplementary Online Content Thaivalappil S, Bauman N, Saieg A, Movius E, Brown KJ, Preciado D. Propranolol-mediated attenuation of MMP-9 excretion in infants with hemangiomas. JAMA Otolaryngol Head Neck Surg. doi:10.1001/jamaoto.2013.4773 eTable. List of All of the Proteins Identified by Proteomics This supplementary material has been provided by the authors to give readers additional information about their work. © 2013 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/01/2021 eTable. List of All of the Proteins Identified by Proteomics Protein Name Prop 12 mo/4 Pred 12 mo/4 Δ Prop to Pred mo mo Myeloperoxidase OS=Homo sapiens GN=MPO 26.00 143.00 ‐117.00 Lactotransferrin OS=Homo sapiens GN=LTF 114.00 205.50 ‐91.50 Matrix metalloproteinase‐9 OS=Homo sapiens GN=MMP9 5.00 36.00 ‐31.00 Neutrophil elastase OS=Homo sapiens GN=ELANE 24.00 48.00 ‐24.00 Bleomycin hydrolase OS=Homo sapiens GN=BLMH 3.00 25.00 ‐22.00 CAP7_HUMAN Azurocidin OS=Homo sapiens GN=AZU1 PE=1 SV=3 4.00 26.00 ‐22.00 S10A8_HUMAN Protein S100‐A8 OS=Homo sapiens GN=S100A8 PE=1 14.67 30.50 ‐15.83 SV=1 IL1F9_HUMAN Interleukin‐1 family member 9 OS=Homo sapiens 1.00 15.00 ‐14.00 GN=IL1F9 PE=1 SV=1 MUC5B_HUMAN Mucin‐5B OS=Homo sapiens GN=MUC5B PE=1 SV=3 2.00 14.00 ‐12.00 MUC4_HUMAN Mucin‐4 OS=Homo sapiens GN=MUC4 PE=1 SV=3 1.00 12.00 ‐11.00 HRG_HUMAN Histidine‐rich glycoprotein OS=Homo sapiens GN=HRG 1.00 12.00 ‐11.00 PE=1 SV=1 TKT_HUMAN Transketolase OS=Homo sapiens GN=TKT PE=1 SV=3 17.00 28.00 ‐11.00 CATG_HUMAN Cathepsin G OS=Homo -
Table 2. Significant
Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S. -
Role of Negative Regulation of Immune Signaling Pathways in Neutrophil Function
Role of negative regulation of immune signaling pathways in neutrophil function Veronica Azcutia *, Charles A. Parkos *, Jennifer C. Brazil * *Department of Pathology, University of Michigan, Ann Arbor, MI 48109 USA. Summary statement: Review on how PMN functions are negatively regulated by immune signaling pathways. Running title: Negative regulation of PMN function. Send correspondence to V.A and J.C.B, and the Editorial and Production Office information to V.A.: *Veronica Azcutia, Ph.D. Department of Pathology, University of Michigan. Biomedical Science Research Building (BSRB),109 Zina Pitcher Place, Ann Arbor, MI 48109 USA. This is the author manuscript accepted for publication and has undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/JLB.3MIR0917-374R. This article is protected by copyright. All rights reserved. Tel: (734)-936-1856, Fax: (734)-615-2331, e-Mail: [email protected] *Jennifer C. Brazil, Ph.D. Department of Pathology, University of Michigan. Biomedical Science Research Building (BSRB),109 Zina Pitcher Place, Ann Arbor, MI 48109 USA. Tel: (734)-936-1856, Fax: (734)-615-2331, e-Mail: [email protected] Key words: neutrophils, ITIM, inflammation. Total character count: 43,451; 2 Figures: Figure 1 and 2 are in color; 89 references; 144 words in Abstract; 12 words in summary statement. Abbreviations A(A2)AR = adenosine receptor BM = bone marrow CEACAM = carcinoembryonic antigen-related cell adhesion molecule Csk = C-terminal Scr kinase fMLF = formyl-methionyl-leucyl phenylalanine peptide GAP = GTPase activating proteins GEF = guanine nucleotide exchange factor G-CSF = Granulocyte colony stimulating factor G-CSFR = Granulocyte colony stimulating factor receptor GPCR = G protein coupled receptor GRK = G protein coupled receptor kinase IBD = Inflammatory bowel disease ICAM-1 = Intracellular Adhesion molecule-1 2 This article is protected by copyright. -
Therapeutic and Prophylactic Use of Oral, Low-Dose Ifns in Species of Veterinary Interest: Back to the Future
veterinary sciences Review Therapeutic and Prophylactic Use of Oral, Low-Dose IFNs in Species of Veterinary Interest: Back to the Future Sara Frazzini 1 , Federica Riva 2,* and Massimo Amadori 3 1 Gastroenterology and Endoscopy Unit, Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy; [email protected] 2 Dipartimento di Medicina Veterinaria, Università degli Studi di Milano, 26900 Lodi, Italy 3 Rete Nazionale di Immunologia Veterinaria, 25125 Brescia, Italy; [email protected] * Correspondence: [email protected]; Tel.: +39-0250334519 Abstract: Cytokines are important molecules that orchestrate the immune response. Given their role, cytokines have been explored as drugs in immunotherapy in the fight against different pathological conditions such as bacterial and viral infections, autoimmune diseases, transplantation and cancer. One of the problems related to their administration consists in the definition of the correct dose to avoid severe side effects. In the 70s and 80s different studies demonstrated the efficacy of cytokines in veterinary medicine, but soon the investigations were abandoned in favor of more profitable drugs such as antibiotics. Recently, the World Health Organization has deeply discouraged the use of antibiotics in order to reduce the spread of multi-drug resistant microorganisms. In this respect, the use of cytokines to prevent or ameliorate infectious diseases has been highlighted, and several studies show the potential of their use in therapy and prophylaxis also in the veterinary field. In this review we aim to review the principles of cytokine treatments, mainly IFNs, and to update the experiences encountered in animals. Keywords: veterinary immunotherapy; cytokines; IFN; low dose treatment; oral treatment Citation: Frazzini, S.; Riva, F.; Amadori, M. -
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 Table 3 Complete List of RNA-Sequencing Analysis of Gene Expression Changed by ≥ Tenfold Between Xenograft and Cells Cultured in 10%O2
Supplementary Table 3 Complete list of RNA-Sequencing analysis of gene expression changed by ≥ tenfold between xenograft and cells cultured in 10%O2 Expr Log2 Ratio Symbol Entrez Gene Name (culture/xenograft) -7.182 PGM5 phosphoglucomutase 5 -6.883 GPBAR1 G protein-coupled bile acid receptor 1 -6.683 CPVL carboxypeptidase, vitellogenic like -6.398 MTMR9LP myotubularin related protein 9-like, pseudogene -6.131 SCN7A sodium voltage-gated channel alpha subunit 7 -6.115 POPDC2 popeye domain containing 2 -6.014 LGI1 leucine rich glioma inactivated 1 -5.86 SCN1A sodium voltage-gated channel alpha subunit 1 -5.713 C6 complement C6 -5.365 ANGPTL1 angiopoietin like 1 -5.327 TNN tenascin N -5.228 DHRS2 dehydrogenase/reductase 2 leucine rich repeat and fibronectin type III domain -5.115 LRFN2 containing 2 -5.076 FOXO6 forkhead box O6 -5.035 ETNPPL ethanolamine-phosphate phospho-lyase -4.993 MYO15A myosin XVA -4.972 IGF1 insulin like growth factor 1 -4.956 DLG2 discs large MAGUK scaffold protein 2 -4.86 SCML4 sex comb on midleg like 4 (Drosophila) Src homology 2 domain containing transforming -4.816 SHD protein D -4.764 PLP1 proteolipid protein 1 -4.764 TSPAN32 tetraspanin 32 -4.713 N4BP3 NEDD4 binding protein 3 -4.705 MYOC myocilin -4.646 CLEC3B C-type lectin domain family 3 member B -4.646 C7 complement C7 -4.62 TGM2 transglutaminase 2 -4.562 COL9A1 collagen type IX alpha 1 chain -4.55 SOSTDC1 sclerostin domain containing 1 -4.55 OGN osteoglycin -4.505 DAPL1 death associated protein like 1 -4.491 C10orf105 chromosome 10 open reading frame 105 -4.491 -
CD226 T Cells Expressing the Receptors TIGIT and Divergent Phenotypes of Human Regulatory
The Journal of Immunology Divergent Phenotypes of Human Regulatory T Cells Expressing the Receptors TIGIT and CD226 Christopher A. Fuhrman,*,1 Wen-I Yeh,*,1 Howard R. Seay,* Priya Saikumar Lakshmi,* Gaurav Chopra,† Lin Zhang,* Daniel J. Perry,* Stephanie A. McClymont,† Mahesh Yadav,† Maria-Cecilia Lopez,‡ Henry V. Baker,‡ Ying Zhang,x Yizheng Li,{ Maryann Whitley,{ David von Schack,x Mark A. Atkinson,* Jeffrey A. Bluestone,‡ and Todd M. Brusko* Regulatory T cells (Tregs) play a central role in counteracting inflammation and autoimmunity. A more complete understanding of cellular heterogeneity and the potential for lineage plasticity in human Treg subsets may identify markers of disease pathogenesis and facilitate the development of optimized cellular therapeutics. To better elucidate human Treg subsets, we conducted direct transcriptional profiling of CD4+FOXP3+Helios+ thymic-derived Tregs and CD4+FOXP3+Helios2 T cells, followed by comparison with CD4+FOXP32Helios2 T conventional cells. These analyses revealed that the coinhibitory receptor T cell Ig and ITIM domain (TIGIT) was highly expressed on thymic-derived Tregs. TIGIT and the costimulatory factor CD226 bind the common ligand CD155. Thus, we analyzed the cellular distribution and suppressive activity of isolated subsets of CD4+CD25+CD127lo/2 T cells expressing CD226 and/or TIGIT. We observed TIGIT is highly expressed and upregulated on Tregs after activation and in vitro expansion, and is associated with lineage stability and suppressive capacity. Conversely, the CD226+TIGIT2 population was associated with reduced Treg purity and suppressive capacity after expansion, along with a marked increase in IL-10 and effector cytokine production. These studies provide additional markers to delineate functionally distinct Treg subsets that may help direct cellular therapies and provide important phenotypic markers for assessing the role of Tregs in health and disease. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like,