DOCSLIB.ORG

Cells Phenotype of Human Tolerogenic Dendritic Glycolytic

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Cells Phenotype of Human Tolerogenic Dendritic Glycolytic High Mitochondrial Respiration and Glycolytic Capacity Represent a Metabolic Phenotype of Human Tolerogenic Dendritic Cells This information is current as of September 26, 2021. Frano Malinarich, Kaibo Duan, Raudhah Abdull Hamid, Au Bijin, Wu Xue Lin, Michael Poidinger, Anna-Marie Fairhurst and John E. Connolly J Immunol published online 27 April 2015 http://www.jimmunol.org/content/early/2015/04/25/jimmun Downloaded from ol.1303316 Supplementary http://www.jimmunol.org/content/suppl/2015/04/25/jimmunol.130331 http://www.jimmunol.org/ Material 6.DCSupplemental Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists by guest on September 26, 2021 • Fast Publication! 4 weeks from acceptance to publication *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 © 2015 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published April 27, 2015, doi:10.4049/jimmunol.1303316 The Journal of Immunology High Mitochondrial Respiration and Glycolytic Capacity Represent a Metabolic Phenotype of Human Tolerogenic Dendritic Cells Frano Malinarich,*,† Kaibo Duan,† Raudhah Abdull Hamid,*,† Au Bijin,*,† Wu Xue Lin,*,† Michael Poidinger,† Anna-Marie Fairhurst,† and John E. Connolly*,†,‡ Human dendritic cells (DCs) regulate the balance between immunity and tolerance through selective activation by environmental and pathogen-derived triggers. To characterize the rapid changes that occur during this process, we analyzed the underlying met- abolic activity across a spectrum of functional DC activation states, from immunogenic to tolerogenic. We found that in contrast to the pronounced proinflammatory program of mature DCs, tolerogenic DCs displayed a markedly augmented catabolic pathway, related to oxidative phosphorylation, fatty acid metabolism, and glycolysis. Functionally, tolerogenic DCs demonstrated the highest Downloaded from mitochondrial oxidative activity, production of reactive oxygen species, superoxide, and increased spare respiratory capacity. Fur- thermore, assembled, electron transport chain complexes were significantly more abundant in tolerogenic DCs. At the level of gly- colysis, tolerogenic and mature DCs showed similar glycolytic rates, but glycolytic capacity and reserve were more pronounced in tolerogenic DCs. The enhanced glycolytic reserve and respiratory capacity observed in these DCs were reflected in a higher met- abolic plasticity to maintain intracellular ATP content. Interestingly, tolerogenic and mature DCs manifested substantially different expression of proteins involved in the fatty acid oxidation (FAO) pathway, and FAO activity was significantly higher in tolerogenic http://www.jimmunol.org/ DCs. Inhibition of FAO prevented the function of tolerogenic DCs and partially restored T cell stimulatory capacity, demonstrating their dependence on this pathway. Overall, tolerogenic DCs show metabolic signatures of increased oxidative phosphorylation pro- graming, a shift in redox state, and high plasticity for metabolic adaptation. These observations point to a mechanism for rapid genome-wide reprograming by modulation of underlying cellular metabolism during DC differentiation. The Journal of Immu- nology, 2015, 194: 000–000. endritic cell (DC) maturation status plays a key role in processes require energetic metabolic adaptations important for regulating the balance between immunity and tolerance DC survival, migration, and ultimately the development of pathogen- by guest on September 26, 2021 D (1, 2). DC maturation is a tightly coordinated response specific immunity. Understanding the metabolic changes underpin- involving multiple signaling pathways, molecular trafficking, cy- ning DC immune function could help develop new strategies for tokine production, and cytoskeletal remodeling (3–5). These controlling immunogenicity. Studies in mice have demonstrated that T cell activation and differentiation from naive into effector and memory T cells are processes highly dependent on energetic *Institute of Molecular and Cell Biology, Agency for Science, Technology and metabolic adaptations. This knowledge is currently being con- Research, Singapore 138673; †Singapore Immunology Network, Singapore 138648; and ‡Institute of Biomedical Studies, Baylor University, Waco, TX 76798 sidered for potential novel immune therapies (6–8). However, knowledge surrounding the immune-metabolic states of DCs is Received for publication December 11, 2013. Accepted for publication March 18, 2015. rather limited. This work was supported by Agency for Science, Technology and Research Core Maturation of murine bone marrow–derived DCs (BMDCs) is Funding (to J.E.C.). highly dependent on metabolic changes. In the immature state, The microarray data presented in this article have been submitted to the National oxidative phosphorylation (OXPHOS) and fatty acid oxidation Center for Biotechnology Information’s Gene Expression Omnibus (http://www.ncbi. (FAO) are the main energy sources. DC maturation coincides with nlm.nih.gov/geo/query/acc.cgi?token=arwhicsyrnchxmb&acc=GSE52894) under ac- cession number GSE52894. an increase in mitochondrial OXPHOS followed by a pronounced Address correspondence and reprint requests to Dr. John E. Connolly, Institute of switch to aerobic glycolysis (9–11). Importantly, pharmacological Molecular and Cell Biology, 61 Biopolis Drive, Proteos, Room 7-17B, Singapore inhibition of glycolysis prevents BMDC maturation, suggesting 138673. E-mail address: [email protected] the importance of this metabolic switch for DC immunogenicity The online version of this article contains supplemental material. (10, 11). Abbreviations used in this article: ACADM, acyl-CoA dehydrogenase, C-4 to C-12 Consistent with the studies in mice, downregulation of OXPHOS straight chain; BMDC, bone marrow–derived DC; CM-H2DCFDA, 5-(and-6)-chlor- omethyl-29,79-dichlorodihydrofluorescein diacetate, acetyl ester; COXII, cyclooxy- gene expression has been reported during human monocyte-derived genase II; DC, dendritic cell; DEG, differentially expressed gene; 2-DG, 2-deoxy-D- DC (moDC) maturation (12). In contrast to mature moDCs, pro- glucose; ECAR, extracellular acidification rate; FAO, fatty acid oxidation; FCCP, carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone; HADHA, hydroxyacyl-CoA teomic analysis of tolerogenic moDCs, which are resistant to dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase, a subunit; HADHB, maturation (13), has shown a predominance of OXPHOS pathway hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase, b subunit; iNOS, inducible NO synthase; IPA, ingenuity pathway analysis; LDHB, lactate proteins (14). Therefore, a comparative analysis across the spec- dehydrogenase B; moDC, monocyte-derived DC; OCR, oxygen consumption rate; trum of moDCs is required to explain the metabolic changes be- OXPHOS, oxidative phosphorylation; ROS, reactive oxygen species; SO, superoxide; tween immunogenic and tolerogenic moDC states. SRC, spare respiratory capacity. In this study, we compared the changes in energetic metabolism Copyright Ó 2015 by The American Association of Immunologists, Inc. 0022-1767/15/$25.00 among human moDCs. Protein expression and functional analyses www.jimmunol.org/cgi/doi/10.4049/jimmunol.1303316 2 ENERGY METABOLISM OF HUMAN TOLEROGENIC moDCs demonstrated that tolerogenic moDCs have a prominent and stable panel kits (Millipore), respectively, using a FLEXMAP 3D system OXPHOS program with high reactive oxygen species (ROS) and (Luminex). superoxide (SO) production, as well as a robust mitochondrial spare Mitochondrial DNA content determination respiratory capacity (SRC). Although tolerogenic and immature moDCs displayed similar levels of FAO activity, glycolytic ca- Total DNA from moDCs was isolated by phenol-chloroform extraction as pacity, and reserve, these catabolic pathways were maintained at previously described (15). Real-time PCR was performed in the Stratagene Mx3005P quantitative PCR system using the SYBR Green/ROX FAST a low level in mature moDCs. Finally, tolerogenic moDCs, in contrast Mastermix kit (Qiagen) with GAPDH (forward, 59-CCTAGGGCTGCT- to mature moDCs, demonstrate a high bioenergetic plasticity for CACATATTC-39, reverse: 59-CGCCCAATACGACCAAATCTA-39)and metabolic adaptation in terms of ATP production. cyclooxygenase II (COXII; forward: 59-GTTGTAGCCCACTTCCAC- TATG, reverse: TAGGGTGTAGCCTGAGAATAGG-39)primers.The mitochondrial/nuclear DNA content was calculated by using the formula: Materials and Methods 22CT mitochondrial COXII/22CT nuclear GAPDH. Data were analyzed by MxPro moDC generation quantitative PCR software (Agilent Technologies). Monocytes were purified from PBMCs of healthy donors (Institutional Real-time metabolic characterization Review Board approval NUS-IRB 10-250) by density centrifugation (Ficoll–Paque, GE Healthcare), followed by magnetic separation (CD14 The mitochondria oxygen consumption rate (OCR, O2 mpH/min) and MicroBeads, Miltenyi
Load more

Recommended publications
  • Gene Symbol Gene Description ACVR1B Activin a Receptor, Type IB
    Table S1. Kinase clones included in human kinase cDNA library for yeast two-hybrid screening Gene Symbol Gene Description ACVR1B activin A receptor, type IB ADCK2 aarF domain containing kinase 2 ADCK4 aarF domain containing kinase 4 AGK multiple substrate lipid kinase;MULK AK1 adenylate kinase 1 AK3 adenylate kinase 3 like 1 AK3L1 adenylate kinase 3 ALDH18A1 aldehyde dehydrogenase 18 family, member A1;ALDH18A1 ALK anaplastic lymphoma kinase (Ki-1) ALPK1 alpha-kinase 1 ALPK2 alpha-kinase 2 AMHR2 anti-Mullerian hormone receptor, type II ARAF v-raf murine sarcoma 3611 viral oncogene homolog 1 ARSG arylsulfatase G;ARSG AURKB aurora kinase B AURKC aurora kinase C BCKDK branched chain alpha-ketoacid dehydrogenase kinase BMPR1A bone morphogenetic protein receptor, type IA BMPR2 bone morphogenetic protein receptor, type II (serine/threonine kinase) BRAF v-raf murine sarcoma viral oncogene homolog B1 BRD3 bromodomain containing 3 BRD4 bromodomain containing 4 BTK Bruton agammaglobulinemia tyrosine kinase BUB1 BUB1 budding uninhibited by benzimidazoles 1 homolog (yeast) BUB1B BUB1 budding uninhibited by benzimidazoles 1 homolog beta (yeast) C9orf98 chromosome 9 open reading frame 98;C9orf98 CABC1 chaperone, ABC1 activity of bc1 complex like (S. pombe) CALM1 calmodulin 1 (phosphorylase kinase, delta) CALM2 calmodulin 2 (phosphorylase kinase, delta) CALM3 calmodulin 3 (phosphorylase kinase, delta) CAMK1 calcium/calmodulin-dependent protein kinase I CAMK2A calcium/calmodulin-dependent protein kinase (CaM kinase) II alpha CAMK2B calcium/calmodulin-dependent
    [Show full text]
  • Increased COUP-TFII Expression in Adult Hearts Induces Mitochondrial Dysfunction Resulting in Heart Failure
    ARTICLE Received 9 Mar 2015 | Accepted 30 Jul 2015 | Published 10 Sep 2015 DOI: 10.1038/ncomms9245 OPEN Increased COUP-TFII expression in adult hearts induces mitochondrial dysfunction resulting in heart failure San-Pin Wu1,2, Chung-Yang Kao1, Leiming Wang1, Chad J. Creighton3,4, Jin Yang5, Taraka R. Donti6, Romain Harmancey7, Hernan G. Vasquez7, Brett H. Graham6,8, Hugo J. Bellen6,8, Heinrich Taegtmeyer7, Ching-Pin Chang5, Ming-Jer Tsai1,8 & Sophia Y. Tsai1,8 Mitochondrial dysfunction and metabolic remodelling are pivotal in the development of cardiomyopathy. Here, we show that myocardial COUP-TFII overexpression causes heart failure in mice, suggesting a causal effect of elevated COUP-TFII levels on development of dilated cardiomyopathy. COUP-TFII represses genes critical for mitochondrial electron transport chain enzyme activity, oxidative stress detoxification and mitochondrial dynamics, resulting in increased levels of reactive oxygen species and lower rates of oxygen consumption in mitochondria. COUP-TFII also suppresses the metabolic regulator PGC-1 network and decreases the expression of key glucose and lipid utilization genes, leading to a reduction in both glucose and oleate oxidation in the hearts. These data suggest that COUP- TFII affects mitochondrial function, impairs metabolic remodelling and has a key role in dilated cardiomyopathy. Last, COUP-TFII haploinsufficiency attenuates the progression of cardiac dilation and improves survival in a calcineurin transgenic mouse model, indicating that COUP-TFII may serve as a therapeutic target for the treatment of dilated cardiomyopathy. 1 Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas 77030, USA. 2 Adrienne Helis Malvin Medical Research Foundation, New Orleans, Louisiana 70130, USA.
    [Show full text]
  • Significant Shortest Paths for the Detection of Putative Disease Modules
    bioRxiv preprint doi: https://doi.org/10.1101/2020.04.01.019844; this version posted April 2, 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. SIGNIFICANT SHORTEST PATHS FOR THE DETECTION OF PUTATIVE DISEASE MODULES Daniele Pepe1 1Department of Oncology, KU Leuven, LKI–Leuven Cancer Institute, Leuven, Belgium Email address: DP: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.04.01.019844; this version posted April 2, 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. Keywords Structural equation modeling, significant shortest paths, pathway analysis, disease modules. Abstract Background The characterization of diseases in terms of perturbated gene modules was recently introduced for the analysis of gene expression data. Some approaches were proposed in literature, but many times they are inductive approaches. This means that starting directly from data, they try to infer key gene networks potentially associated to the biological phenomenon studied. However they ignore the biological information already available to characterize the gene modules. Here we propose the detection of perturbed gene modules using the combination of data driven and hypothesis-driven approaches relying on biological metabolic pathways and significant shortest paths tested by structural equation modeling.
    [Show full text]
  • Supplementary Table S1. Upregulated Genes Differentially
    Supplementary Table S1. Upregulated genes differentially expressed in athletes (p < 0.05 and 1.3-fold change) Gene Symbol p Value Fold Change 221051_s_at NMRK2 0.01 2.38 236518_at CCDC183 0.00 2.05 218804_at ANO1 0.00 2.05 234675_x_at 0.01 2.02 207076_s_at ASS1 0.00 1.85 209135_at ASPH 0.02 1.81 228434_at BTNL9 0.03 1.81 229985_at BTNL9 0.01 1.79 215795_at MYH7B 0.01 1.78 217979_at TSPAN13 0.01 1.77 230992_at BTNL9 0.01 1.75 226884_at LRRN1 0.03 1.74 220039_s_at CDKAL1 0.01 1.73 236520_at 0.02 1.72 219895_at TMEM255A 0.04 1.72 201030_x_at LDHB 0.00 1.69 233824_at 0.00 1.69 232257_s_at 0.05 1.67 236359_at SCN4B 0.04 1.64 242868_at 0.00 1.63 1557286_at 0.01 1.63 202780_at OXCT1 0.01 1.63 1556542_a_at 0.04 1.63 209992_at PFKFB2 0.04 1.63 205247_at NOTCH4 0.01 1.62 1554182_at TRIM73///TRIM74 0.00 1.61 232892_at MIR1-1HG 0.02 1.61 204726_at CDH13 0.01 1.6 1561167_at 0.01 1.6 1565821_at 0.01 1.6 210169_at SEC14L5 0.01 1.6 236963_at 0.02 1.6 1552880_at SEC16B 0.02 1.6 235228_at CCDC85A 0.02 1.6 1568623_a_at SLC35E4 0.00 1.59 204844_at ENPEP 0.00 1.59 1552256_a_at SCARB1 0.02 1.59 1557283_a_at ZNF519 0.02 1.59 1557293_at LINC00969 0.03 1.59 231644_at 0.01 1.58 228115_at GAREM1 0.01 1.58 223687_s_at LY6K 0.02 1.58 231779_at IRAK2 0.03 1.58 243332_at LOC105379610 0.04 1.58 232118_at 0.01 1.57 203423_at RBP1 0.02 1.57 AMY1A///AMY1B///AMY1C///AMY2A///AMY2B// 208498_s_at 0.03 1.57 /AMYP1 237154_at LOC101930114 0.00 1.56 1559691_at 0.01 1.56 243481_at RHOJ 0.03 1.56 238834_at MYLK3 0.01 1.55 213438_at NFASC 0.02 1.55 242290_at TACC1 0.04 1.55 ANKRD20A1///ANKRD20A12P///ANKRD20A2///
    [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]
  • 32-3099: PRKAB1 Recombinant Protein Description
    9853 Pacific Heights Blvd. Suite D. San Diego, CA 92121, USA Tel: 858-263-4982 Email: [email protected] 32-3099: PRKAB1 Recombinant Protein Alternative Name : AMPK,HAMPKb,5'-AMP-activated protein kinase subunit beta-1,AMPK subunit beta-1,AMPKb,PRKAB1. Description Source : E.coli. PRKAB1 Human Recombinant produced in E.Coli is a single, non-glycosylated, polypeptide chain containing 293 amino acids (1-270 a.a.) and having a molecular mass of 32.8 kDa. The PRKAB1 is fused to a 23 amino acid His Tag at N- Terminus and purified by proprietary chromatographic techniques. 5'-AMP-activated protein kinase subunit beta-1 (PRKAB1) hinders protein, carbohydrate and lipid biosynthesis, in addition to cell growth and proliferation. AMPK is a heterotrimer comprised of an alpha catalytic subunit, and non-catalytic beta and gamma subunits. AMPK acts via direct phosphorylation of metabolic enzymes, and longer-term effects by phosphorylation of transcription regulators. PRKAB1 is a regulator of cellular polarity by remodeling the actin cytoskeleton; most likely by indirectly activating myosin. Beta non-catalytic subunit acts as a scaffold on which the AMPK complex compiles, through its C-terminus that joins alpha (PRKAA1 or PRKAA2) and gamma subunits (PRKAG1, PRKAG2 or PRKAG3). Product Info Amount : 5 µg Purification : Greater than 85% as determined by SDS-PAGE. The PRKAB1 protein solution (0.5mg/ml) contains 20mM Tris-HCl buffer (pH 8.0), 0.15M NaCl, Content : 10% glycerol and 1mM DTT. Store at 4°C if entire vial will be used within 2-4 weeks. Store, frozen at -20°C for longer periods of Storage condition : time.
    [Show full text]
  • Mouse Rps6ka5 Antibody (C-Term) Purified Rabbit Polyclonal Antibody (Pab) Catalog # AW5466
    10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 Mouse Rps6ka5 Antibody (C-term) Purified Rabbit Polyclonal Antibody (Pab) Catalog # AW5466 Specification Mouse Rps6ka5 Antibody (C-term) - Product Information Application WB,E Primary Accession Q8C050 Reactivity Mouse Host Rabbit Clonality Polyclonal Calculated MW M=97,90 KDa Isotype Rabbit Ig Antigen Source HUMAN Mouse Rps6ka5 Antibody (C-term) - Additional Information Gene ID 73086 Antigen Region All lanes : Anti-Rps6ka5 Antibody (C-term) at 850-883 1:1000 dilution Lane 1: L929 whole cell Other Names lysates Lane 2: mouse spleen lysates Lane 3: Ribosomal protein S6 kinase alpha-5, mouse thymus lysates Lysates/proteins at 20 S6K-alpha-5, 90 kDa ribosomal protein S6 µg per lane. Secondary Goat Anti-Rabbit IgG, kinase 5, Nuclear mitogen- and (H+L),Peroxidase conjugated at 1/10000 stress-activated protein kinase 1, RSK-like dilution Predicted band size : 97 kDa protein kinase, RLSK, Rps6ka5, Msk1 Blocking/Dilution buffer: 5% NFDM/TBST. Dilution WB~~1:1000 Mouse Rps6ka5 Antibody (C-term) - Background Target/Specificity This Mouse Rps6ka5 antibody is generated Serine/threonine-protein kinase that is from a rabbit immunized with a KLH required for the mitogen or stress-induced conjugated synthetic peptide between phosphorylation of the transcription factors 850-883 amino acids from the C-terminal CREB1 and ATF1 and for the regulation of the region of Mouse Rps6ka5. transcription factors RELA, STAT3 and ETV1/ER81, and that contributes to gene Format activation by histone phosphorylation and Purified polyclonal antibody supplied in PBS functions in the regulation of inflammatory with 0.09% (W/V) sodium azide.
    [Show full text]
  • Phospho-RPS6KA5-T581 Rabbit Pab
    Leader in Biomolecular Solutions for Life Science Phospho-RPS6KA5-T581 Rabbit pAb Catalog No.: AP1197 Basic Information Background Catalog No. Serine/threonine-protein kinase that is required for the mitogen or stress-induced AP1197 phosphorylation of the transcription factors CREB1 and ATF1 and for the regulation of the transcription factors RELA, STAT3 and ETV1/ER81, and that contributes to gene Observed MW activation by histone phosphorylation and functions in the regulation of inflammatory Refer to figures genes (PubMed:11909979, PubMed:12569367, PubMed:12763138, PubMed:9687510, PubMed:18511904, PubMed:9873047). Phosphorylates CREB1 and ATF1 in response to Calculated MW mitogenic or stress stimuli such as UV-C irradiation, epidermal growth factor (EGF) and 61kDa/81kDa/89kDa anisomycin (PubMed:11909979, PubMed:9873047). Plays an essential role in the control of RELA transcriptional activity in response to TNF and upon glucocorticoid, associates in Category the cytoplasm with the glucocorticoid receptor NR3C1 and contributes to RELA inhibition and repression of inflammatory gene expression (PubMed:12628924, Primary antibody PubMed:18511904). In skeletal myoblasts is required for phosphorylation of RELA at 'Ser-276' during oxidative stress (PubMed:12628924). In erythropoietin-stimulated cells, Applications is necessary for the 'Ser-727' phosphorylation of STAT3 and regulation of its WB transcriptional potential (PubMed:12763138). Phosphorylates ETV1/ER81 at 'Ser-191' and 'Ser-216', and thereby regulates its ability to stimulate transcription, which may be Cross-Reactivity important during development and breast tumor formation (PubMed:12569367). Directly Human, Mouse, Rat represses transcription via phosphorylation of 'Ser-1' of histone H2A (PubMed:15010469). Phosphorylates 'Ser-10' of histone H3 in response to mitogenics, stress stimuli and EGF, which results in the transcriptional activation of several Recommended Dilutions immediate early genes, including proto-oncogenes c-fos/FOS and c-jun/JUN (PubMed:12773393).
    [Show full text]
  • N-Glycan Trimming in the ER and Calnexin/Calreticulin Cycle
    Neurotransmitter receptorsGABA and A postsynapticreceptor activation signal transmission Ligand-gated ion channel transport GABAGABA Areceptor receptor alpha-5 alpha-1/beta-1/gamma-2 subunit GABA A receptor alpha-2/beta-2/gamma-2GABA receptor alpha-4 subunit GABAGABA receptor A receptor beta-3 subunitalpha-6/beta-2/gamma-2 GABA-AGABA receptor; A receptor alpha-1/beta-2/gamma-2GABA receptoralpha-3/beta-2/gamma-2 alpha-3 subunit GABA-A GABAreceptor; receptor benzodiazepine alpha-6 subunit site GABA-AGABA-A receptor; receptor; GABA-A anion site channel (alpha1/beta2 interface) GABA-A receptor;GABA alpha-6/beta-3/gamma-2 receptor beta-2 subunit GABAGABA receptorGABA-A receptor alpha-2receptor; alpha-1 subunit agonist subunit GABA site Serotonin 3a (5-HT3a) receptor GABA receptorGABA-C rho-1 subunitreceptor GlycineSerotonin receptor subunit3 (5-HT3) alpha-1 receptor GABA receptor rho-2 subunit GlycineGlycine receptor receptor subunit subunit alpha-2 alpha-3 Ca2+ activated K+ channels Metabolism of ingested SeMet, Sec, MeSec into H2Se SmallIntermediateSmall conductance conductance conductance calcium-activated calcium-activated calcium-activated potassium potassium potassiumchannel channel protein channel protein 2 protein 1 4 Small conductance calcium-activatedCalcium-activated potassium potassium channel alpha/beta channel 1 protein 3 Calcium-activated potassiumHistamine channel subunit alpha-1 N-methyltransferase Neuraminidase Pyrimidine biosynthesis Nicotinamide N-methyltransferase Adenosylhomocysteinase PolymerasePolymeraseHistidine basic
    [Show full text]
  • An Automated Pipeline for Inferring Variant-Driven Gene
    www.nature.com/scientificreports OPEN MAGPEL: an autoMated pipeline for inferring vAriant‑driven Gene PanEls from the full‑length biomedical literature Nafseh Saberian1, Adib Shaf 1, Azam Peyvandipour1 & Sorin Draghici 1,2* In spite of the eforts in developing and maintaining accurate variant databases, a large number of disease‑associated variants are still hidden in the biomedical literature. Curation of the biomedical literature in an efort to extract this information is a challenging task due to: (i) the complexity of natural language processing, (ii) inconsistent use of standard recommendations for variant description, and (iii) the lack of clarity and consistency in describing the variant-genotype-phenotype associations in the biomedical literature. In this article, we employ text mining and word cloud analysis techniques to address these challenges. The proposed framework extracts the variant- gene‑disease associations from the full‑length biomedical literature and designs an evidence‑based variant-driven gene panel for a given condition. We validate the identifed genes by showing their diagnostic abilities to predict the patients’ clinical outcome on several independent validation cohorts. As representative examples, we present our results for acute myeloid leukemia (AML), breast cancer and prostate cancer. We compare these panels with other variant‑driven gene panels obtained from Clinvar, Mastermind and others from literature, as well as with a panel identifed with a classical diferentially expressed genes (DEGs) approach. The results show that the panels obtained by the proposed framework yield better results than the other gene panels currently available in the literature. One crucial step in understanding the biological mechanism underlying a disease condition is to capture the relationship between the variants and the disease risk1.
    [Show full text]
  • In Vitro Pharmacological Profiling of R406 Identifies Molecular Targets
    ORIGINAL ARTICLE In vitro pharmacological profiling of R406 identifies molecular targets underlying the clinical effects of fostamatinib Michael G. Rolf, Jon O. Curwen, Margaret Veldman-Jones, Cath Eberlein, Jianyan Wang, Alex Harmer, Caroline J. Hellawell & Martin Braddock AstraZeneca R&D Alderley Park, Macclesfield, Cheshire SK10 4TG, United Kingdom Keywords Abstract Blood pressure elevation, fostamatinib, in vitro pharmacological profiling, R406, SYK Off-target pharmacology may contribute to both adverse and beneficial effects of a new drug. In vitro pharmacological profiling is often applied early in drug Correspondence discovery; there are fewer reports addressing the relevance of broad profiles to Michael G. Rolf, AstraZeneca R&D Molndal,€ clinical adverse effects. Here, we have characterized the pharmacological profile Pepparedsleden 1, 431 83 Mo¨ lndal, Sweden. of the active metabolite of fostamatinib, R406, linking an understanding of drug Tel: +46 31 776 60 40; Fax: +46 31 776 37 selectivity to the increase in blood pressure observed in clinical studies. R406 60; E-mail: [email protected] was profiled in a broad range of in vitro assays to generate a comprehensive Funding Information pharmacological profile and key targets were further investigated using func- No funding information provided. tional and cellular assay systems. A combination of traditional literature searches and text-mining approaches established potential mechanistic links Received: 9 April 2015; Accepted: 14 July between the profile of R406 and clinical side effects. R406 was selective outside 2015 the kinase domain, with only antagonist activity at the adenosine A3 receptor in the range relevant to clinical effects. R406 was less selective in the kinase Pharma Res Per, 3(5), 2015, e00175, doi: 10.1002/prp2.175 domain, having activity at many protein kinases at therapeutically relevant con- centrations when tested in multiple in vitro systems.
    [Show full text]
  • Proteomic and Metabolomic Analyses of Mitochondrial Complex I-Deficient
    THE JOURNAL OF BIOLOGICAL CHEMISTRY VOL. 287, NO. 24, pp. 20652–20663, June 8, 2012 © 2012 by The American Society for Biochemistry and Molecular Biology, Inc. Published in the U.S.A. Proteomic and Metabolomic Analyses of Mitochondrial Complex I-deficient Mouse Model Generated by Spontaneous B2 Short Interspersed Nuclear Element (SINE) Insertion into NADH Dehydrogenase (Ubiquinone) Fe-S Protein 4 (Ndufs4) Gene*□S Received for publication, November 25, 2011, and in revised form, April 5, 2012 Published, JBC Papers in Press, April 25, 2012, DOI 10.1074/jbc.M111.327601 Dillon W. Leong,a1 Jasper C. Komen,b1 Chelsee A. Hewitt,a Estelle Arnaud,c Matthew McKenzie,d Belinda Phipson,e Melanie Bahlo,e,f Adrienne Laskowski,b Sarah A. Kinkel,a,g,h Gayle M. Davey,g William R. Heath,g Anne K. Voss,a,h René P. Zahedi,i James J. Pitt,j Roman Chrast,c Albert Sickmann,i,k Michael T. Ryan,l Gordon K. Smyth,e,f,h b2 a,h,m,n3 David R. Thorburn, and Hamish S. Scott Downloaded from From the aMolecular Medicine Division, gImmunology Division, and eBioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia, the bMurdoch Childrens Research Institute, Royal Children’s Hospital and Department of Paediatrics, University of Melbourne, Parkville, Victoria 3052, Australia, the cDépartement de Génétique Médicale, Université de Lausanne, 1005 Lausanne, Switzerland, the dCentre for Reproduction and Development, Monash Institute of Medical Research, Clayton, Victoria 3168, Australia, the hDepartment of Medical Biology
    [Show full text]