A Molecular Switch from STAT2-IRF9 to ISGF3 Underlies Interferon-Induced Gene Transcription
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Activated Peripheral-Blood-Derived Mononuclear Cells
Transcription factor expression in lipopolysaccharide- activated peripheral-blood-derived mononuclear cells Jared C. Roach*†, Kelly D. Smith*‡, Katie L. Strobe*, Stephanie M. Nissen*, Christian D. Haudenschild§, Daixing Zhou§, Thomas J. Vasicek¶, G. A. Heldʈ, Gustavo A. Stolovitzkyʈ, Leroy E. Hood*†, and Alan Aderem* *Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103; ‡Department of Pathology, University of Washington, Seattle, WA 98195; §Illumina, 25861 Industrial Boulevard, Hayward, CA 94545; ¶Medtronic, 710 Medtronic Parkway, Minneapolis, MN 55432; and ʈIBM Computational Biology Center, P.O. Box 218, Yorktown Heights, NY 10598 Contributed by Leroy E. Hood, August 21, 2007 (sent for review January 7, 2007) Transcription factors play a key role in integrating and modulating system. In this model system, we activated peripheral-blood-derived biological information. In this study, we comprehensively measured mononuclear cells, which can be loosely termed ‘‘macrophages,’’ the changing abundances of mRNAs over a time course of activation with lipopolysaccharide (LPS). We focused on the precise mea- of human peripheral-blood-derived mononuclear cells (‘‘macro- surement of mRNA concentrations. There is currently no high- phages’’) with lipopolysaccharide. Global and dynamic analysis of throughput technology that can precisely and sensitively measure all transcription factors in response to a physiological stimulus has yet to mRNAs in a system, although such technologies are likely to be be achieved in a human system, and our efforts significantly available in the near future. To demonstrate the potential utility of advanced this goal. We used multiple global high-throughput tech- such technologies, and to motivate their development and encour- nologies for measuring mRNA levels, including massively parallel age their use, we produced data from a combination of two distinct signature sequencing and GeneChip microarrays. -
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. -
List of Genes Used in Cell Type Enrichment Analysis
List of genes used in cell type enrichment analysis Metagene Cell type Immunity ADAM28 Activated B cell Adaptive CD180 Activated B cell Adaptive CD79B Activated B cell Adaptive BLK Activated B cell Adaptive CD19 Activated B cell Adaptive MS4A1 Activated B cell Adaptive TNFRSF17 Activated B cell Adaptive IGHM Activated B cell Adaptive GNG7 Activated B cell Adaptive MICAL3 Activated B cell Adaptive SPIB Activated B cell Adaptive HLA-DOB Activated B cell Adaptive IGKC Activated B cell Adaptive PNOC Activated B cell Adaptive FCRL2 Activated B cell Adaptive BACH2 Activated B cell Adaptive CR2 Activated B cell Adaptive TCL1A Activated B cell Adaptive AKNA Activated B cell Adaptive ARHGAP25 Activated B cell Adaptive CCL21 Activated B cell Adaptive CD27 Activated B cell Adaptive CD38 Activated B cell Adaptive CLEC17A Activated B cell Adaptive CLEC9A Activated B cell Adaptive CLECL1 Activated B cell Adaptive AIM2 Activated CD4 T cell Adaptive BIRC3 Activated CD4 T cell Adaptive BRIP1 Activated CD4 T cell Adaptive CCL20 Activated CD4 T cell Adaptive CCL4 Activated CD4 T cell Adaptive CCL5 Activated CD4 T cell Adaptive CCNB1 Activated CD4 T cell Adaptive CCR7 Activated CD4 T cell Adaptive DUSP2 Activated CD4 T cell Adaptive ESCO2 Activated CD4 T cell Adaptive ETS1 Activated CD4 T cell Adaptive EXO1 Activated CD4 T cell Adaptive EXOC6 Activated CD4 T cell Adaptive IARS Activated CD4 T cell Adaptive ITK Activated CD4 T cell Adaptive KIF11 Activated CD4 T cell Adaptive KNTC1 Activated CD4 T cell Adaptive NUF2 Activated CD4 T cell Adaptive PRC1 Activated -
Finding Drug Targeting Mechanisms with Genetic Evidence for Parkinson’S Disease
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.24.208975; this version posted July 24, 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-NC-ND 4.0 International license. Finding drug targeting mechanisms with genetic evidence for Parkinson’s disease Catherine S. Storm1,*, Demis A. Kia1, Mona Almramhi1, Sara Bandres-Ciga2, Chris Finan3, Aroon D. Hingorani3,4,5, International Parkinson’s Disease Genomics Consortium (IPDGC), Nicholas W. Wood1,6,* 1 Department of Clinical and Movement Neurosciences, University College London Queen Square Institute of Neurology, London, WC1N 3BG, United Kingdom 2 Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, United States of America 3 Institute of Cardiovascular Science, Faculty of Population Health, University College London, London WC1E 6BT, United Kingdom 4 University College London British Heart Foundation Research Accelerator Centre, New Delhi, India 5 Health Data Research UK, 222 Euston Road, London, United Kingdom 6 Lead Contact * Correspondence: [email protected] (CSS), [email protected] (NWW) Summary Parkinson’s disease (PD) is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation using human evidence. Here, we use Mendelian randomization to investigate more than 3000 genes that encode druggable proteins, seeking to predict their efficacy as drug targets for PD. We use expression and protein quantitative trait loci for druggable genes to mimic exposure to medications, and we examine the causal effect on PD risk (in two large case-control cohorts), PD age at onset and progression. -
Viral Resistance and IFN Signaling in STAT2 Knockout Fish Cells Carola E
Viral Resistance and IFN Signaling in STAT2 Knockout Fish Cells Carola E. Dehler, Katherine Lester, Giulia Della Pelle, Luc Jouneau, Armel Houel, Catherine Collins, Tatiana Dovgan, This information is current as Radek Machat, Jun Zou, Pierre Boudinot, Samuel A. M. of September 26, 2021. Martin and Bertrand Collet J Immunol published online 29 May 2019 http://www.jimmunol.org/content/early/2019/05/28/jimmun ol.1801376 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2019/05/28/jimmunol.180137 Material 6.DCSupplemental http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication by guest on September 26, 2021 *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2019 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published May 29, 2019, doi:10.4049/jimmunol.1801376 The Journal of Immunology Viral Resistance and IFN Signaling in STAT2 Knockout Fish Cells Carola E. Dehler,* Katherine Lester,† Giulia Della Pelle,‡ Luc Jouneau,‡ Armel Houel,‡ Catherine Collins,† Tatiana Dovgan,*,† Radek Machat,‡,1 Jun Zou,*,2 Pierre Boudinot,‡ Samuel A. -
CD38, CD157, and RAGE As Molecular Determinants for Social Behavior
cells Review CD38, CD157, and RAGE as Molecular Determinants for Social Behavior Haruhiro Higashida 1,2,* , Minako Hashii 1,3, Yukie Tanaka 4, Shigeru Matsukawa 5, Yoshihiro Higuchi 6, Ryosuke Gabata 1, Makoto Tsubomoto 1, Noriko Seishima 1, Mitsuyo Teramachi 1, Taiki Kamijima 1, Tsuyoshi Hattori 7, Osamu Hori 7 , Chiharu Tsuji 1, Stanislav M. Cherepanov 1 , Anna A. Shabalova 1, Maria Gerasimenko 1, Kana Minami 1, Shigeru Yokoyama 1, Sei-ichi Munesue 8, Ai Harashima 8, Yasuhiko Yamamoto 8, Alla B. Salmina 1,2 and Olga Lopatina 2 1 Department of Basic Research on Social Recognition and Memory, Research Center for Child Mental Development, Kanazawa University, Kanazawa 920-8640, Japan; [email protected] (M.H.); [email protected] (R.G.); [email protected] (M.T.); [email protected] (N.S.); [email protected] (M.T.); [email protected] (T.K.); [email protected] (C.T.); [email protected] (S.M.C.); [email protected] (A.A.S.); [email protected] (M.G.); minami-k@staff.kanazawa-u.ac.jp (K.M.); [email protected] (S.Y.) 2 Laboratory of Social Brain Study, Research Institute of Molecular Medicine and Pathobiochemistry, Krasnoyarsk State Medical University named after Prof. V.F. Voino-Yasenetsky, Krasnoyarsk 660022, Russia; [email protected] (A.B.S.); [email protected] (O.L.) 3 Division of Molecular Genetics and Clinical Research, National Hospital Organization Nanao Hospital, Nanao 926-0841, Japan 4 Molecular Biology and Chemistry, Faculty of Medical Science, University of Fukui, Fukui -
Inactivation of Type I IFN Jak-STAT Pathway in EBV Latency
Ning S and Wang L, J Cancer Biol Treat 2016, 3: 009 DOI: 10.24966/CBT-7546/100009 HSOA Journal of Cancer Biology and Treatment Research Article defense system, among which IRF7 is the “master” regulator of type I Inactivation of Type I IFN Interferon (IFN-I) response to pathogenic infection [4]. Robust IFN-I response during infection requires a positive feedback loop between Jak-STAT Pathway in EBV IRF7 and IFN-I [5-6]. Aberrant production of IFN-I, however, is Latency associated with autoimmune disorders and malignancies [7-9]. Thus, tight regulation of IRF7 is important in balancing the appropriate Shunbin Ning and Ling Wang* immune response to clear invading pathogens while preventing Department of Internal Medicine, Center of Excellence for Inflammation, immune-mediated pathogenesis [10]. Infectious Diseases and Immunity, Quillen College of Medicine, East Tennessee State University, USA IFNs exert their functions through induction of IFN-Stimulated Genes (ISGs) via Jak-STAT pathways [11-13]. The IFN-I Jak-STAT pathway comprises of IFNAR1/2, Jak1, Tyk2, STAT1/2, and IRF9 [14]. Following IFN-I binding to IFNARs, signaling via protein kinases leads to tyrosine phosphorylation and activation of IFNAR1 Abstract at Y466 [15], Tyk2(Y1054/Y1055) and Jak1(Y1034/Y1035), and then to that Epstein-Barr Virus (EBV) latent infection is associated with a of STAT1(Y701) and STAT2(Y690 and S287) [16]. The phosphorylated variety of lymphomas and carcinomas. Interferon (IFN) Regulatory STAT1/2 then dimerize and associate with IRF9 to form a complex Factors (IRFs) are a family of transcription factors, among which termed interferon-stimulated gene factor 3 (ISGF3). -
Partner-Regulated Interaction of IFN Regulatory Factor 8 with Chromatin Visualized in Live Macrophages
Partner-regulated interaction of IFN regulatory factor 8 with chromatin visualized in live macrophages Leopoldo Laricchia-Robbio*, Tomohiko Tamura*, Tatiana Karpova†, Brian L. Sprague†, James G. McNally†, and Keiko Ozato*‡ *Laboratory of Molecular Growth Regulation, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD 20892-2753; and †Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892-5055 Edited by Laurie H. Glimcher, Harvard School of Public Health, Boston, MA, and approved August 18, 2005 (received for review May 17, 2005) IFN regulatory factor (IRF) 8 is a transcription factor that directs protein–protein interactions on fluorescence recovery have not macrophage differentiation. By fluorescence recovery after pho- been extensively studied. Moreover, many FRAP studies so far tobleaching, we visualized the movement of IRF8-GFP in differen- reported are qualitative, lacking quantitative insight into the tiating macrophages. Recovery data fitted to mathematical models chromatin-binding events. More recent efforts to fit FRAP data revealed two binding states for IRF8. The majority of IRF8 was to mathematical models begin to provide a clearer knowledge on highly mobile and transiently interacted with chromatin, whereas the property of FRAP mobility (16, 17). a small fraction of IRF8 bound to chromatin more stably. IRF8 IRF8, a member of the IFN regulatory factor (IRF) family, is mutants that did not stimulate macrophage differentiation a key factor that guides the development of macrophages (18). showed a faster recovery, revealing little interaction with chro- We previously established an in vitro model system where matin. A macrophage activation signal by IFN-␥͞LPS led to a global IRF8Ϫ/Ϫ myeloid progenitor cells called Tot2 differentiate into slowdown of IRF8 movement, leading to increased chromatin macrophages upon IRF8 introduction (19). -
32-6317: BST1 Human Description Product Info
9853 Pacific Heights Blvd. Suite D. San Diego, CA 92121, USA Tel: 858-263-4982 Email: [email protected] 32-6317: BST1 Human Bone Marrow Stromal Cell Antigen 1, ADP-Ribosyl Cyclase 2, Bone Marrow Stromal Antigen 1, Cyclic ADP- Alternative Ribose Hydrolase 2, NAD(+) Nucleosidase, CADPr Hydrolase 2, ADP-Ribosyl Cyclase/Cyclic ADP-Ribose Name : Hydrolase 2, CD157 Antigen, EC 3.2.2.6, CD157, BST-1, ADP-ribosyl cyclase/cyclic ADP-ribose hydrolase 2, ADP-ribosyl cyclase 2, Bone marrow stromal antigen 1, Cyclic ADP-ribose hydrolase 2, cADPr hydrolase 2. Description Source: Sf9, Baculovirus cells. Sterile filtered colorless solution. BST1 (Bone Marrow Stromal Cell Antigen 1), is a GPI (glycosylphosphatidylinositol) anchored membrane protein which is part of the CD38 family. BST1 was initially recognized as a bone marrow stromal cell molecule. BST1 is an ectoenzyme sharing more than a few features with ADP-ribosyl cyclase CD38. BST1 together with CD38, exhibit both DP-ribosyl cyclase and cyclinc ADP ribose hydrolase activities. BST1 participates in rheumatoid arthritis due to its enhanced expression in RA-derived bone marrow stromal cell lines. Moreover, BST1 is expressed by cells of the myeloid lineage and could perform as a receptor with a signal transduction capability. BST1 produced in Sf9 Baculovirus cells is a single, glycosylated polypeptide chain containing 267 amino acids (33-293a.a.) and having a molecular mass of 30.5kDa. (Molecular size on SDS-PAGE will appear at approximately 40-57kDa).BST1 is expressed with a 6 amino acid His tag at C-Terminus and purified by proprietary chromatographic techniques. -
An Immunoevasive Strategy Through Clinically-Relevant Pan-Cancer Genomic and Transcriptomic Alterations of JAK-STAT Signaling Components
bioRxiv preprint doi: https://doi.org/10.1101/576645; this version posted March 14, 2019. 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-NC-ND 4.0 International license. An immunoevasive strategy through clinically-relevant pan-cancer genomic and transcriptomic alterations of JAK-STAT signaling components Wai Hoong Chang1 and Alvina G. Lai1, 1Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7FZ, United Kingdom Since its discovery almost three decades ago, the Janus ki- Although cytokines are responsible for inflammation in nase (JAK)-signal transducer and activator of transcription cancer, spontaneous eradication of tumors by endoge- (STAT) pathway has paved the road for understanding inflam- nous immune processes rarely occurs. Moreover, the matory and immunity processes related to a wide range of hu- dynamic interaction between tumor cells and host immu- man pathologies including cancer. Several studies have demon- nity shields tumors from immunological ablation, which strated the importance of JAK-STAT pathway components in overall limits the efficacy of immunotherapy in the clinic. regulating tumor initiation and metastatic progression, yet, the extent of how genetic alterations influence patient outcome is far from being understood. Focusing on 133 genes involved in Cytokines can be pro- or anti-inflammatory and are inter- JAK-STAT signaling, we found that copy number alterations dependent on each other’s function to maintain immune underpin transcriptional dysregulation that differs within and homeostasis(3). -
Beyond Viral Interferon Regulatory Factors: Immune Evasion Strategies Jinjong Myoung1, Shin-Ae Lee2, and Hye-Ra Lee3*
J. Microbiol. Biotechnol. (2019), 29(12), 1873–1881 https://doi.org/10.4014/jmb.1910.10004 Research Article Review jmb Beyond Viral Interferon Regulatory Factors: Immune Evasion Strategies Jinjong Myoung1, Shin-Ae Lee2, and Hye-Ra Lee3* 1Korea Zoonosis Research Institute, Genetic Engineering Research Institute and Department of Bioactive Material Science, College of Natural Science, Jeonbuk National University, Jeonju 54531, Republic of Korea 2Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA 3Department of Biotechnology and Bioinformatics, College of Science and Technology, Korea University, Sejong 30019, Republic of Korea Received: October 8, 2019 Revised: October 8, 2019 The innate immune response serves as a first-line-of-defense mechanism for a host against Accepted: October 24, 2019 viral infection. Viruses must therefore subvert this anti-viral response in order to establish an First published online: efficient life cycle. In line with this fact, Kaposi’s sarcoma-associated herpesvirus (KSHV) October 25, 2019 encodes numerous genes that function as immunomodulatory proteins to antagonize the host *Corresponding author immune system. One such mechanism through which KSHV evades the host immunity is by Phone: +82-44-860-1831 encoding a viral homolog of cellular interferon (IFN) regulatory factors (IRFs), known as Fax: +82-44-860-1598 E-mail: [email protected] vIRFs. Herein, we summarize recent advances in the study of the immunomodulatory strategies of KSHV vIRFs and their effects on KSHV-associated pathogenesis. pISSN 1017-7825, eISSN 1738-8872 Copyright© 2019 by Keywords: KSHV, viral interferon regulatory factor, immune evasion strategy, PRR-mediated The Korean Society for Microbiology signaling pathway, apoptosis pathway and Biotechnology Introduction various transcription factors. -
Herpes Simplex Virus 1 Targets IRF7 Via ICP0 to Limit Type I IFN Induction David Shahnazaryan1,2, Rana Khalil3, Claire Wynne4, Caroline A
www.nature.com/scientificreports OPEN Herpes simplex virus 1 targets IRF7 via ICP0 to limit type I IFN induction David Shahnazaryan1,2, Rana Khalil3, Claire Wynne4, Caroline A. Jeferies5,6, Joan Ní Gabhann‑Dromgoole1,3,6* & Conor C. Murphy1,2,6 Herpes simplex keratitis (HSK), caused by herpes simplex virus type 1 (HSV‑1) infection, is the commonest cause of infectious blindness in the developed world. Following infection the virus is initially suspended in the tear flm, where it encounters a multi‑pronged immune response comprising enzymes, complement, immunoglobulins and crucially, a range of anti‑viral and pro‑infammatory cytokines. However, given that HSV‑1 can overcome innate immune responses to establish lifelong latency throughout a susceptible individual’s lifetime, there is signifcant interest in understanding the mechanisms employed by HSV‑1 to downregulate the anti‑viral type I interferon (IFN) mediated immune responses. This study aimed to investigate the interactions between infected cell protein (ICP)0 and key elements of the IFN pathway to identify possible novel targets that contribute to viral immune evasion. Reporter gene assays demonstrated the ability of ICP0 to inhibit type I IFN activity downstream of pathogen recognition receptors (PRRs) which are known to be involved in host antiviral defences. Further experiments identifed interferon regulatory factor (IRF)7, a driver of type I IFN, as a potential target for ICP0. These fndings increase our understanding of the pathogenesis of HSK and suggest IRF7 as a potential therapeutic target. Herpes simplex keratitis (HSK) is the commonest cause of infectious corneal blindness in the western world1. Tere are over 500,000 afected individuals in the United States (US) alone2.