Atg8ylation As a General Membrane Stress and Remodeling Response
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Since January 2020 Elsevier Has Created a COVID-19 Resource Centre with Free Information in English and Mandarin on the Novel Coronavirus COVID- 19
Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID- 19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. Journal Pre-proof Potential use of hydroxychloroquine, ivermectin and azithromycin drugs in fighting COVID-19: trends, scope and relevance Renuka Choudhary, Anil K. Sharma, Renuka Choudhary PII: S2052-2975(20)30036-6 DOI: https://doi.org/10.1016/j.nmni.2020.100684 Reference: NMNI 100684 To appear in: New Microbes and New Infections Received Date: 12 April 2020 Revised Date: 15 April 2020 Accepted Date: 16 April 2020 Please cite this article as: Choudhary R, Sharma AK, Choudhary R, Potential use of hydroxychloroquine, ivermectin and azithromycin drugs in fighting COVID-19: trends, scope and relevance, New Microbes and New Infections, https://doi.org/10.1016/j.nmni.2020.100684. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. -
Dr. Mary Ann Osley – Professor: Dr. Osley's Laboratory Is Focused on The
Dr. Vojo Deretic – Chair: Dr. Dr. Mary Ann Osley – Dr. Robert Rubin– Professor: Dr. Michelle Ozbun – Dr. David Peabody – Deretic's main contributions to Professor: Dr. Osley’s Dr. Rubin’s lab explores T cell Professor: Dr. Ozbun’s lab Professor: Dr. Peabody was science come from studies by laboratory is focused on the tolerance and autoimmunity, T studies the cellular and viral trained at Stanford University his team on the role of role of chromatin in gene cell development in the mechanisms that regulate the in the laboratory of Paul Berg autophagy in infection and expression, DNA replication, thymus, systemic and drug- life cycles of papillomaviruses (Nobel Prize, 1980) and has (PVs), aiming to understand immunity. Autophagy, a cytoplasmic and DNA repair as cells enter induced lupus, & autoantibody been associated with UNM the delicate virus-cell interactions that can since 1984. For a number of years his pathway for the removal of damaged or and exit quiescence. Her research uses biosensors. Dr. Rubin’s laboratory also become unbalanced, leading to group studied RNA viruses of bacteria as surplus organelles, has been previously budding yeast, Saccharomyces cerevisiae, studies the cellular and molecular basis for malignancies. Three areas of research model systems to understand gene implicated in cancer, neurodegeneration, to study these cellular processes. the capacity of lupus-inducing drugs to interests are understanding: a) strategies development, and aging. Dr. Deretic's disrupt central T cell tolerance. regulation. In recent years his group has for PV infection and persistence; b) PV group is one of those that made the focused on adapting the virus-like particles and host interactions; c) the mechanisms discovery that autophagic degradation is a of these bacteriophages as platforms for of HPV-induced malignant transformation. -
Paradigm Autophagy: an Emerging Immunological
Autophagy: An Emerging Immunological Paradigm Vojo Deretic Autophagy is a fundamental eukaryotic process with receptors (PRRs); 3) regulation of inflammasome activation multiple cytoplasmic homeostatic roles, recently ex- and alarmin secretion; and 4) cytoplasmic Ag processing for panded to include unique stand-alone immunological MHC II presentation and T cell homeostasis. We relate these functions and interactions with nearly all parts of the processes to conventional immunological functions, defense immune system. In this article, we review this growing against infectious agents, chronic inflammatory diseases, and repertoire of autophagy roles in innate and adaptive im- other immunological disorders. munity and inflammation. Its unique functions include cell-autonomous elimination of intracellular microbes Autophagy pathway facilitated by specific receptors. Other intersections of The key morphological features of autophagy are endomem- autophagy with immune processes encompass effects branous organelles, called autophagosomes (Fig. 1), whose on inflammasome activation and secretion of its sub- formation is controlled by the autophagy-related gene (Atg) strates, including IL-1b, effector and regulatory inter- and additional factors comprehensively reviewed elsewhere actions with TLRs and Nod-like receptors, Ag pre- (1). Briefly, the Atg system includes Ser/Thr kinases Ulk1 and sentation, naive T cell repertoire selection, and mature Ulk2 (Atg1), Beclin 1 (Atg6; a subunit of the class III PI3K T cell development and homeostasis. Genome-wide as- human vacuolar protein sorting 34 [hVPS34 complexes]), sociation studies in human populations strongly impli- Atg5–Atg12/Atg16L1 complex, and microtubule-associated cate autophagy in chronic inflammatory disease and protein L chain 3s (LC3s) (multiple Atg8 orthologs), with LC3B being a commonly used marker for identification of autoimmune disorders. -
A Minimum-Labeling Approach for Reconstructing Protein Networks Across Multiple Conditions
A Minimum-Labeling Approach for Reconstructing Protein Networks across Multiple Conditions Arnon Mazza1, Irit Gat-Viks2, Hesso Farhan3, and Roded Sharan1 1 Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. Email: [email protected]. 2 Dept. of Cell Research and Immunology, Tel Aviv University, Tel Aviv 69978, Israel. 3 Biotechnology Institute Thurgau, University of Konstanz, Unterseestrasse 47, CH-8280 Kreuzlingen, Switzerland. Abstract. The sheer amounts of biological data that are generated in recent years have driven the development of network analysis tools to fa- cilitate the interpretation and representation of these data. A fundamen- tal challenge in this domain is the reconstruction of a protein-protein sub- network that underlies a process of interest from a genome-wide screen of associated genes. Despite intense work in this area, current algorith- mic approaches are largely limited to analyzing a single screen and are, thus, unable to account for information on condition-specific genes, or reveal the dynamics (over time or condition) of the process in question. Here we propose a novel formulation for network reconstruction from multiple-condition data and devise an efficient integer program solution for it. We apply our algorithm to analyze the response to influenza in- fection in humans over time as well as to analyze a pair of ER export related screens in humans. By comparing to an extant, single-condition tool we demonstrate the power of our new approach in integrating data from multiple conditions in a compact and coherent manner, capturing the dynamics of the underlying processes. 1 Introduction With the increasing availability of high-throughput data, network biol- arXiv:1307.7803v1 [q-bio.QM] 30 Jul 2013 ogy has become the method of choice for filtering, interpreting and rep- resenting these data. -
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. -
The Schizophrenia Risk Gene Product Mir-137 Alters Presynaptic Plasticity
The schizophrenia risk gene product miR-137 alters presynaptic plasticity The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Siegert, S., J. Seo, E. J. Kwon, A. Rudenko, S. Cho, W. Wang, Z. Flood, et al. 2015. “The schizophrenia risk gene product miR-137 alters presynaptic plasticity.” Nature neuroscience 18 (7): 1008-1016. doi:10.1038/nn.4023. http://dx.doi.org/10.1038/nn.4023. Published Version doi:10.1038/nn.4023 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:24983896 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA HHS Public Access Author manuscript Author Manuscript Author ManuscriptNat Neurosci Author Manuscript. Author manuscript; Author Manuscript available in PMC 2016 January 01. Published in final edited form as: Nat Neurosci. 2015 July ; 18(7): 1008–1016. doi:10.1038/nn.4023. The schizophrenia risk gene product miR-137 alters presynaptic plasticity Sandra Siegert1,2, Jinsoo Seo1,2,*, Ester J. Kwon1,2,*, Andrii Rudenko1,2,*, Sukhee Cho1,2, Wenyuan Wang1,2, Zachary Flood1,2, Anthony J. Martorell1,2, Maria Ericsson4, Alison E. Mungenast1,2, and Li-Huei Tsai1,2,3,5 1Picower Institute for Learning and Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA 2Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA 3Broad Institute of MIT and Harvard, Cambridge, MA, USA 4Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA Abstract Non-coding variants in the human MIR137 gene locus increase schizophrenia risk at a genome- wide significance level. -
Supplementary Tables
Supplementary Tables Supplementary Table S1: Preselected miRNAs used in feature selection Univariate Cox proportional hazards regression analysis of the endpoint freedom from recurrence in the training set (DKTK-ROG sample) allowed the pre-selection of 524 miRNAs (P< 0.5), which were used in the feature selection. P-value was derived from log-rank test. miRNA p-value miRNA p-value miRNA p-value miRNA p-value hsa-let-7g-3p 0.0001520 hsa-miR-1304-3p 0.0490161 hsa-miR-7108-5p 0.1263245 hsa-miR-6865-5p 0.2073121 hsa-miR-6825-3p 0.0004257 hsa-miR-4298 0.0506194 hsa-miR-4453 0.1270967 hsa-miR-6893-5p 0.2120664 hsa-miR-668-3p 0.0005188 hsa-miR-484 0.0518625 hsa-miR-200a-5p 0.1276345 hsa-miR-25-3p 0.2123829 hsa-miR-3622b-3p 0.0005885 hsa-miR-6851-3p 0.0531446 hsa-miR-6090 0.1278692 hsa-miR-3189-5p 0.2136060 hsa-miR-6885-3p 0.0006452 hsa-miR-1276 0.0557418 hsa-miR-148b-3p 0.1279811 hsa-miR-6073 0.2139702 hsa-miR-6875-3p 0.0008188 hsa-miR-3173-3p 0.0559962 hsa-miR-4425 0.1288330 hsa-miR-765 0.2141536 hsa-miR-487b-5p 0.0011381 hsa-miR-650 0.0564616 hsa-miR-6798-3p 0.1293342 hsa-miR-338-5p 0.2153079 hsa-miR-210-5p 0.0012316 hsa-miR-6133 0.0571407 hsa-miR-4472 0.1300006 hsa-miR-6806-5p 0.2173515 hsa-miR-1470 0.0012822 hsa-miR-4701-5p 0.0571720 hsa-miR-4465 0.1304841 hsa-miR-98-5p 0.2184947 hsa-miR-6890-3p 0.0016539 hsa-miR-202-3p 0.0575741 hsa-miR-514b-5p 0.1308790 hsa-miR-500a-3p 0.2185577 hsa-miR-6511b-3p 0.0017165 hsa-miR-4733-5p 0.0616138 hsa-miR-378c 0.1317442 hsa-miR-4515 0.2187539 hsa-miR-7109-3p 0.0021381 hsa-miR-595 0.0629350 hsa-miR-3121-3p -
(AIM) Center of Biomedical Research Excellence: Supporting the Next Generation of Autophagy Researchers and Fostering International Collaborations
Autophagy ISSN: 1554-8627 (Print) 1554-8635 (Online) Journal homepage: http://www.tandfonline.com/loi/kaup20 Autophagy, Inflammation, and Metabolism (AIM) Center of Biomedical Research Excellence: supporting the next generation of autophagy researchers and fostering international collaborations Vojo Deretic, Eric Prossnitz, Mark Burge, Matthew J. Campen, Judy Cannon, Ke Jian Liu, Larry A. Sklar, Lee Allers, Sally Ann Garcia, Eric H. Baehrecke, Christian Behrends, Francesco Cecconi, Patrice Codogno, Guang-Chao Chen, Zvulun Elazar, Eeva-Liisa Eskelinen, Bernard Fourie, Devrim Gozuacik, Wanjin Hong, Gokhan Hotamisligi, Marja Jäättelä, Eun-Kyeong Jo, Terje Johansen, Gábor Juhász, Adi Kimchi, Nicholas Ktistakis, Guido Kroemer, Noboru MIzushima, Christian Münz, Fulvio Reggiori, David Rubinsztein, Kevin Ryan, Kate Schroder, Anne Simonsen, Sharon Tooze, Maria I. Vaccaro, Tamotsu Yoshimori, Li Yu, Hong Zhang & Daniel J. Klionsky To cite this article: Vojo Deretic, Eric Prossnitz, Mark Burge, Matthew J. Campen, Judy Cannon, Ke Jian Liu, Larry A. Sklar, Lee Allers, Sally Ann Garcia, Eric H. Baehrecke, Christian Behrends, Francesco Cecconi, Patrice Codogno, Guang-Chao Chen, Zvulun Elazar, Eeva-Liisa Eskelinen, Bernard Fourie, Devrim Gozuacik, Wanjin Hong, Gokhan Hotamisligi, Marja Jäättelä, Eun-Kyeong Jo, Terje Johansen, Gábor Juhász, Adi Kimchi, Nicholas Ktistakis, Guido Kroemer, Noboru MIzushima, Christian Münz, Fulvio Reggiori, David Rubinsztein, Kevin Ryan, Kate Schroder, Anne Simonsen, Sharon Tooze, Maria I. Vaccaro, Tamotsu Yoshimori, Li Yu, Hong Zhang & Daniel J. Klionsky (2018) Autophagy, Inflammation, and Metabolism (AIM) Center of Biomedical Research Excellence: supporting the next generation of autophagy researchers and fostering international collaborations, Autophagy, 14:6, 925-929, DOI: 10.1080/15548627.2018.1465784 To link to this article: https://doi.org/10.1080/15548627.2018.1465784 Accepted author version posted online: 23 Jun 2018. -
Syntaxin 16'S Newly Deciphered Roles in Autophagy
cells Perspective Syntaxin 16’s Newly Deciphered Roles in Autophagy Bor Luen Tang 1,2 1 Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117596, Singapore; [email protected]; Tel.: +65-6516-1040 2 NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore 119077, Singapore Received: 19 November 2019; Accepted: 6 December 2019; Published: 17 December 2019 Abstract: Syntaxin 16, a Qa-SNARE (soluble N-ethylmaleimide-sensitive factor activating protein receptor), is involved in a number of membrane-trafficking activities, particularly transport processes at the trans-Golgi network (TGN). Recent works have now implicated syntaxin 16 in the autophagy process. In fact, syntaxin 16 appears to have dual roles, firstly in facilitating the transport of ATG9a-containing vesicles to growing autophagosomes, and secondly in autolysosome formation. The former involves a putative SNARE complex between syntaxin 16, VAMP7 and SNAP-47. The latter occurs via syntaxin 16’s recruitment by Atg8/LC3/GABARAP family proteins to autophagosomes and endo-lysosomes, where syntaxin 16 may act in a manner that bears functional redundancy with the canonical autophagosome Qa-SNARE syntaxin 17. Here, I discuss these recent findings and speculate on the mechanistic aspects of syntaxin 16’s newly found role in autophagy. Keywords: ATG9; autophagy; autophagosome; SNARE; syntaxin 16; syntaxin 17; VAMP7 1. Introduction Vesicular membrane trafficking [1] and macroautophagy [2] are two highly conserved cellular membrane remodeling processes in eukaryotes. The former mediates the transfer of materials between membrane compartments, while the latter serves to degrade and recycle cytosolic as well as membranous cellular materials. -
WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT (51) International Patent Classification: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, C12Q 1/68 (2018.01) A61P 31/18 (2006.01) DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, C12Q 1/70 (2006.01) HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (21) International Application Number: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, PCT/US2018/056167 OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (22) International Filing Date: SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 16 October 2018 (16. 10.2018) TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, (26) Publication Language: English GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, (30) Priority Data: UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, 62/573,025 16 October 2017 (16. 10.2017) US TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, ΓΕ , IS, IT, LT, LU, LV, (71) Applicant: MASSACHUSETTS INSTITUTE OF MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TECHNOLOGY [US/US]; 77 Massachusetts Avenue, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, Cambridge, Massachusetts 02139 (US). -
Table S2.Up Or Down Regulated Genes in Tcof1 Knockdown Neuroblastoma N1E-115 Cells Involved in Differentbiological Process Anal
Table S2.Up or down regulated genes in Tcof1 knockdown neuroblastoma N1E-115 cells involved in differentbiological process analysed by DAVID database Pop Pop Fold Term PValue Genes Bonferroni Benjamini FDR Hits Total Enrichment GO:0044257~cellular protein catabolic 2.77E-10 MKRN1, PPP2R5C, VPRBP, MYLIP, CDC16, ERLEC1, MKRN2, CUL3, 537 13588 1.944851 8.64E-07 8.64E-07 5.02E-07 process ISG15, ATG7, PSENEN, LOC100046898, CDCA3, ANAPC1, ANAPC2, ANAPC5, SOCS3, ENC1, SOCS4, ASB8, DCUN1D1, PSMA6, SIAH1A, TRIM32, RNF138, GM12396, RNF20, USP17L5, FBXO11, RAD23B, NEDD8, UBE2V2, RFFL, CDC GO:0051603~proteolysis involved in 4.52E-10 MKRN1, PPP2R5C, VPRBP, MYLIP, CDC16, ERLEC1, MKRN2, CUL3, 534 13588 1.93519 1.41E-06 7.04E-07 8.18E-07 cellular protein catabolic process ISG15, ATG7, PSENEN, LOC100046898, CDCA3, ANAPC1, ANAPC2, ANAPC5, SOCS3, ENC1, SOCS4, ASB8, DCUN1D1, PSMA6, SIAH1A, TRIM32, RNF138, GM12396, RNF20, USP17L5, FBXO11, RAD23B, NEDD8, UBE2V2, RFFL, CDC GO:0044265~cellular macromolecule 6.09E-10 MKRN1, PPP2R5C, VPRBP, MYLIP, CDC16, ERLEC1, MKRN2, CUL3, 609 13588 1.859332 1.90E-06 6.32E-07 1.10E-06 catabolic process ISG15, RBM8A, ATG7, LOC100046898, PSENEN, CDCA3, ANAPC1, ANAPC2, ANAPC5, SOCS3, ENC1, SOCS4, ASB8, DCUN1D1, PSMA6, SIAH1A, TRIM32, RNF138, GM12396, RNF20, XRN2, USP17L5, FBXO11, RAD23B, UBE2V2, NED GO:0030163~protein catabolic process 1.81E-09 MKRN1, PPP2R5C, VPRBP, MYLIP, CDC16, ERLEC1, MKRN2, CUL3, 556 13588 1.87839 5.64E-06 1.41E-06 3.27E-06 ISG15, ATG7, PSENEN, LOC100046898, CDCA3, ANAPC1, ANAPC2, ANAPC5, SOCS3, ENC1, SOCS4, -
Unveiling the Roles of Autophagy in Innate and Adaptive Immunity
REVIEWS Unveiling the roles of autophagy in innate and adaptive immunity Beth Levine* and Vojo Deretic‡ Abstract | Cells digest portions of their interiors in a process known as autophagy to recycle nutrients, remodel and dispose of unwanted cytoplasmic constituents. This ancient pathway, conserved from yeast to humans, is now emerging as a central player in the immunological control of bacterial, parasitic and viral infections. The process of autophagy may degrade intracellular pathogens, deliver endogenous antigens to MHC-class-II-loading compartments, direct viral nucleic acids to Toll-like receptors and regulate T‑cell homeostasis. This Review describes the mechanisms of autophagy and highlights recent advances relevant to the role of autophagy in innate and adaptive immunity. Lysosomal degradation Our armamentarium for fighting intracellular patho- proteins and other macromolecules, either to supply The digestion of gens includes multiple facets of the innate and adap- nutrients for essential anabolic needs under conditions macromolecules in lysosomal tive immune response. In the past few decades, we of nutrient deprivation or growth factor withdrawal, organelles, which are the have witnessed an explosion in our understanding or to rid cells of potentially toxic aggregate-prone terminal organelles of of the mechanisms underlying antigen presentation, proteins2. The broad spectrum of autophagy func- degradative pathways, such as phagosomal or immune recognition of infected cells, cellular sensing tions is intricately linked to a wide