Cx3cr1-Deficient Microglia Exhibit a Premature Aging Transcriptome
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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 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, -
Gene Symbol Category ACAN ECM ADAM10 ECM Remodeling-Related ADAM11 ECM Remodeling-Related ADAM12 ECM Remodeling-Related ADAM15 E
Supplementary Material (ESI) for Integrative Biology This journal is (c) The Royal Society of Chemistry 2010 Gene symbol Category ACAN ECM ADAM10 ECM remodeling-related ADAM11 ECM remodeling-related ADAM12 ECM remodeling-related ADAM15 ECM remodeling-related ADAM17 ECM remodeling-related ADAM18 ECM remodeling-related ADAM19 ECM remodeling-related ADAM2 ECM remodeling-related ADAM20 ECM remodeling-related ADAM21 ECM remodeling-related ADAM22 ECM remodeling-related ADAM23 ECM remodeling-related ADAM28 ECM remodeling-related ADAM29 ECM remodeling-related ADAM3 ECM remodeling-related ADAM30 ECM remodeling-related ADAM5 ECM remodeling-related ADAM7 ECM remodeling-related ADAM8 ECM remodeling-related ADAM9 ECM remodeling-related ADAMTS1 ECM remodeling-related ADAMTS10 ECM remodeling-related ADAMTS12 ECM remodeling-related ADAMTS13 ECM remodeling-related ADAMTS14 ECM remodeling-related ADAMTS15 ECM remodeling-related ADAMTS16 ECM remodeling-related ADAMTS17 ECM remodeling-related ADAMTS18 ECM remodeling-related ADAMTS19 ECM remodeling-related ADAMTS2 ECM remodeling-related ADAMTS20 ECM remodeling-related ADAMTS3 ECM remodeling-related ADAMTS4 ECM remodeling-related ADAMTS5 ECM remodeling-related ADAMTS6 ECM remodeling-related ADAMTS7 ECM remodeling-related ADAMTS8 ECM remodeling-related ADAMTS9 ECM remodeling-related ADAMTSL1 ECM remodeling-related ADAMTSL2 ECM remodeling-related ADAMTSL3 ECM remodeling-related ADAMTSL4 ECM remodeling-related ADAMTSL5 ECM remodeling-related AGRIN ECM ALCAM Cell-cell adhesion ANGPT1 Soluble factors and receptors -
Characteristics of B Cell-Associated Gene Expression in Patients With
MOLECULAR MEDICINE REPORTS 13: 4113-4121, 2016 Characteristics of B cell-associated gene expression in patients with coronary artery disease WENWEN YAN*, HAOMING SONG*, JINFA JIANG, WENJUN XU, ZHU GONG, QIANGLIN DUAN, CHUANGRONG LI, YUAN XIE and LEMIN WANG Department of Internal Medicine, Division of Cardiology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, P.R. China Received May 19, 2015; Accepted February 12, 2016 DOI: 10.3892/mmr.2016.5029 Abstract. The current study aimed to identify differentially with the two other groups. Additionally the gene expression expressed B cell-associated genes in peripheral blood mono- levels of B cell regulatory genes were measured. In patients nuclear cells and observe the changes in B cell activation at with AMI, CR1, LILRB2, LILRB3 and VAV1 mRNA expres- different stages of coronary artery disease. Groups of patients sion levels were statistically increased, whereas, CS1 and IL4I1 with acute myocardial infarction (AMI) and stable angina (SA), mRNAs were significantly reduced compared with the SA and as well as healthy volunteers, were recruited into the study control groups. There was no statistically significant difference (n=20 per group). Whole human genome microarray analysis in B cell-associated gene expression levels between patients was performed to examine the expression of B cell-associated with SA and the control group. The present study identified the genes among these three groups. The mRNA expression levels downregulation of genes associated with BCRs, B2 cells and of 60 genes associated with B cell activity and regulation were B cell regulators in patients with AMI, indicating a weakened measured using reverse transcription-quantitative polymerase T cell-B cell interaction and reduced B2 cell activation during chain reaction. -
Snipa Snpcard
SNiPAcard Block annotations Block info genomic range chr19:55,117,749-55,168,602 block size 50,854 bp variant count 74 variants Basic features Conservation/deleteriousness Linked genes μ = -0.557 [-4.065 – AC009892.10 , AC009892.5 , AC009892.9 , AC245036.1 , AC245036.2 , phyloP 2.368] gene(s) hit or close-by AC245036.3 , AC245036.4 , AC245036.5 , AC245036.6 , LILRA1 , LILRB1 , LILRB4 , MIR8061 , VN1R105P phastCons μ = 0.059 [0 – 0.633] eQTL gene(s) CTB-83J4.2 , LILRA1 , LILRA2 , LILRB2 , LILRB5 , LILRP1 μ = -0.651 [-4.69 – 2.07] AC008984.5 , AC008984.5 , AC008984.6 , AC008984.6 , AC008984.7 , AC008984.7 , AC009892.10 , AC009892.10 , AC009892.2 , AC009892.2 , AC009892.5 , AC010518.3 , AC010518.3 , AC011515.2 , AC011515.2 , AC012314.19 , AC012314.19 , FCAR , FCAR , FCAR , FCAR , FCAR , FCAR , FCAR , FCAR , FCAR , FCAR , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL1 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL3 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , KIR2DL4 , -
Supplementary Figures and Tables
SUPPLEMENTARY DATA Supplementary Figure 1. Isolation and culture of endothelial cells from surgical specimens of FVM. (A) Representative pre-surgical fundus photograph of a right eye exhibiting a FVM encroaching on the optic nerve (dashed line) causing tractional retinal detachment with blot hemorrhages throughout retina (arrow heads). (B) Magnetic beads (arrows) allow for separation and culturing of enriched cell populations from surgical specimens (scale bar = 100 μm). (C) Cultures of isolated cells stained positively for CD31 representing a successfully isolated enriched population (scale bar = 40 μm). ©2017 American Diabetes Association. Published online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db16-1035/-/DC1 SUPPLEMENTARY DATA Supplementary Figure 2. Efficient siRNA knockdown of RUNX1 expression and function demonstrated by qRT-PCR, Western Blot, and scratch assay. (A) RUNX1 siRNA induced a 60% reduction of RUNX1 expression measured by qRT-PCR 48 hrs post-transfection whereas expression of RUNX2 and RUNX3, the two other mammalian RUNX orthologues, showed no significant changes, indicating specificity of our siRNA. Functional inhibition of Runx1 signaling was demonstrated by a 330% increase in insulin-like growth factor binding protein-3 (IGFBP3) RNA expression level, a known target of RUNX1 inhibition. Western blot demonstrated similar reduction in protein levels. (B) siRNA- 2’s effect on RUNX1 was validated by qRT-PCR and western blot, demonstrating a similar reduction in both RNA and protein. Scratch assay demonstrates functional inhibition of RUNX1 by siRNA-2. ns: not significant, * p < 0.05, *** p < 0.001 ©2017 American Diabetes Association. Published online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db16-1035/-/DC1 SUPPLEMENTARY DATA Supplementary Table 1. -
Genetic Variation, Big Data and Ageing
INFRAFRONTIER / IMPC Conference 2019 Genetic Variation, Big Data and Ageing June 3 to 5, 2019 | Helsinki #InfrafrontierConf #InfraConfHelsinki WELCOME Dear colleagues, After two productive meetings in Athens (2017) and Munich (2018), the joint conference of the INFRAFRONTIER research infrastructure and the International Mouse Phenotyping Consortium (IMPC) has successfully established itself as the global platform for scientific exchange between experts from basic research to clinical research in the biomedical field – with a focus on functional phenogenomics. Martin Hrabě de Angelis This summer, we welcome you to Helsinki, the beautiful capital of INFRAFRONTIER, Finland. The aim of the INFRAFRONTIER/IMPC Conference 2019 is to Scientific Director discuss three hot topics in modern biomedical research: Genetic Variation: Understanding the functional consequences of human genetic variation and its impact on genetic diseases is critically important. This task involves systematic mutagenesis in appropriate models emulating human genetic variation, together with comprehensive genotypic and phenotypic analysis. Big Data: The availability of vast amounts of genomic and pheno typic data in the IMPC and INFRAFRONTIER databases offers the po tential to transform the biomedical research landscape. To carefully collect, analyse and interpret these huge datasets will be essential Steve Brown IMPC, Scientific Chair for the progress of genomic medicine. Ageing: In a setting of rapidly ageing societies across Europe, Ame rica, and Asia, new findings into the genetics of ageing processes and agerelated disorders uncovered using animal models are pivo tal to not only extending life but also improving its quality. We are grateful to our colleagues at the University of Oulu, together with the Finnish Ministry of Education and Culture and the Acade my of Finland, for their kind support in organizing this conference. -
Anti-Matrix Metalloproteinase-25, Propeptide Region Developed in Rabbit Affinity Isolated Antibody
Anti-Matrix Metalloproteinase-25, Propeptide Region Developed in Rabbit Affinity Isolated Antibody Product Number M 5067 Product Description structurally. They fall within the matrixin subfamily and Anti-Matrix Metalloproteinase-25 (MMP-25), Propeptide are EC designated 3.4.24.x. This group also contains Region is developed in rabbit using a synthetic peptide astacin, reprolysin, and serralysin, as well as other corresponding to the propeptide region of human matrix more divergent metalloproteinases. All MMPs are metalloproteinase-25 (MMP-25), also known as synthesized as proenzymes, and most of them are membrane-type matrix metalloproteinase-6 (MT6-MMP) secreted from the cells as proenzymes. Thus, the as immunogen. Affinity isolated antigen specific activation of these proenzymes is a critical step that antibody is obtained from rabbit anti-MMP-25 antiserum leads to extracellular matrix breakdown. by immuno-specific purification which removes essentially all rabbit serum proteins, including MMPs are considered to play an important role in immunoglobulins, which do not specifically bind to the wound healing, apoptosis, bone elongation, embryo peptide. development, uterine involution, angiogenesis, 4 and tissue remodeling, and in diseases such as multiple Anti-Matrix Metalloproteinase-25, Propeptide Region sclerosis, 2, 5 Alzheimer’s, 2 malignant gliomas, 2 lupus, may be used for the detection and localization of arthritis, periodontis, glumerulonephritis, human and murine matrix metalloproteinase-25 atherosclerosis, tissue ulceration, and in cancer cell (MMP-25, MT6-MMP). The antibody binds to the invasion and metastasis.6 Numerous studies have propeptide domain of MMP-25 and does not cross react shown that there is a close association between with the other MMP family members (MMP-1, MMP-2, expression of various members of the MMP family by MMP-3, MMP-9, etc.). -
ILT2/Cd85j/LILRB1/LIR-1)
Killer Cell Ig-Like Receptor-Dependent Signaling by Ig-Like Transcript 2 (ILT2/CD85j/LILRB1/LIR-1) This information is current as Sheryl E. Kirwan and Deborah N. Burshtyn of September 29, 2021. J Immunol 2005; 175:5006-5015; ; doi: 10.4049/jimmunol.175.8.5006 http://www.jimmunol.org/content/175/8/5006 Downloaded from References This article cites 59 articles, 28 of which you can access for free at: http://www.jimmunol.org/content/175/8/5006.full#ref-list-1 Why The JI? Submit online. http://www.jimmunol.org/ • 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 *average by guest on September 29, 2021 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 © 2005 by The American Association of Immunologists All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology Killer Cell Ig-Like Receptor-Dependent Signaling by Ig-Like Transcript 2 (ILT2/CD85j/LILRB1/LIR-1)1 Sheryl E. Kirwan and Deborah N. Burshtyn2 Inhibitory killer cell Ig-like receptors (KIR) signal by recruitment of the tyrosine phosphatase Src homology region 2 domain- containing phosphatase-1 to ITIM. -
Supplementary Materials
Supplementary Materials Supplemental Figure S1. Distinct difference in expression of 576 sensome genes comparing cortex versus microglia. (A) This heatmap shows all 576 sensome candidate genes ordered by DE and with the left column shows if the gene is present in the “Hickman et al. sensome” Supplemental Figure S2. Mouse sensome and human sensome genes categorized by group. (A) Bar graph showing the number of mouse and human sensome genes per group (Cell-Cell Interactions, Chemokine and related receptors, Cytokine receptors, ECM receptors, Endogenous ligands receptors, sensors and transporters, Fc receptors, Pattern recognition and related receptors, Potential sensors but no known ligands and Purinergic and related receptors). Supplementary Figure S3. Overlap of ligands recognized by microglia sensome (A) Overlap between the ligands of the receptors from respectively human and mouse core sensome was shown using Venn Diagrams. (B) Ligands of human and mouse receptors categorized in groups (Glycoproteins, Cytokines, Immunoglobulin, Amino acids, Carbohydrates, Electrolytes, Lipopeptides, Chemokines, Neuraminic acids, Nucleic acids, Receptors, Lipids, Fatty acids, Leukotrienes, Hormones, Steroids and Phospholipids) and spread of different groups shown as parts of whole again highlighting that the distribution of ligands what the human and mouse sensome genes can sense (Categorization of ligands in Supplementary Table S1). Supplementary Figure S4. Microglia core sensome expression during aging. (A) Two-log fold change of microglia core sensome genes in aging mice derived from Holtman et al. [12]. (B) Accelerated aging model (ERCC1), with impaired DNA repair mechanism, shows changes of microglia core sensome expression [12]. (C) Microglia core sensome expression during aging in human derived from Olah et al. -
Ivtigation of the Effects of Mechanical Strain in Human Tenocytes
Investigation of the effects of Mechanical Strain in Human Tenocytes Eleanor Rachel Jones In partial fulfilment of the requirements for the Degree of Doctor of Philosophy University of East Anglia, Biological Sciences September 2012 This copy of the thesis has been supplied on condition that anyone who consults it is understood to recognise that its copyright rests with the author and that use of any information derived there from must be in accordance with current UK Copyright Law. In addition, any quotation or extract must be included full attribution. Abstract Tendinopathies are a range of diseases characterised by pain and insidious degeneration. Although poorly understood, onset is often associated with physical activity. Metalloproteinases are regulated differentially in tendinopathy causing disruptions in extracellular matrix (ECM) homeostasis. An increase in the anti-inflammatory cytokine TGFβ has also been documented. This project aims to investigate the effect of cyclic tensile strain loading and TGFβ stimulation on protease and ECM protein expression by human tenocytes and begin to characterise the pathway of mechanotransduction. Human tenocytes were seeded at 1.5x106 cells/ml into collagen gels (rat tail type I, 1mg/ml) and stretched using a sinusoidal waveform of 0-5% at 1Hz using the Flexcell FX4000T™ system. Cultures were treated with or without 1ng/ml TGFβ1 or inhibitors of TGFβRI, metalloproteinases, RGD, Mannose-6-phosphate, integrin β1 and a thrombospondin as appropriate. qRT-PCR and a cell based luciferase assay were used to assess RNA and TGFβ activity respectively. The prolonged application of 5% cyclic mechanical strain in a 3D culture system induced an anabolic response in protease and matrix genes. -
Importance of HLA Class I Amino Acid Position 194 and LILRB1 Receptor
tics: O ne pe ge n o A n c u c e m s s m I Immunogenetics: Open access Grifoni, et al., Immunogenet open access 2016, 1:1 Editorial Open Access Importance of HLA Class I Amino Acid Position 194 and LILRB1 Receptor in HIV Disease Progression Alba Grifoni1 and Massimo Amicosante1,2* 1ProxAgen Ltd, Sofia, Bulgaria 2Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy *Corresponding author: Massimo Amicosante, Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy, Tel: 390672596202; Fax: 390672596202; E-mail: [email protected] Received date: March 26, 2016; Accepted date: March 28, 2016; Published date: March 31, 2016 Copyright: © 2016 Grifoni A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Editorial HLA-B/LILRB1 interaction [13]. This is consistent with previous results showing a different binding capability of LILRB1 with HLA- HIV-specific T-cell response, and in particular CTL, plays a key role B*27:05 carrying different peptides [15]. in controlling HIV infection [1]. An increasing importance is currently recognised also to innate immune response, particularly the one In HIV infection expression of LILRB1 is increased respect to associated to NK cells and the interaction of its receptor with HLA healthy donor. Higher is HIV viremia, higher is LILRB1 expression class I molecules [2]. We have recently performed an immunogenetic [11,16]. The evaluation of patients developing primary HIV-1 infection study in a defined cohort of children infected during a hospital showed that a significant proportion of HIV-1 specific CD8 T cells outbreak with a monophyletic strain of HIV-1 [3], assessing the role of express LILRB1 and the expression increase over the time in these cells amino acid polymorphisms in HLA molecules [4,5].