DOCSLIB.ORG

Transcriptional and Signaling Analysis As a Means of Investigating the Complexity of Aging Processes in Human and Mouse

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Transcriptional and Signaling Analysis As a Means of Investigating the Complexity of Aging Processes in Human and Mouse Transcriptional and signaling analysis as a means of investigating the complexity of aging processes in human and mouse Dissertation zur Erlangung des akademischen Grades des Doktors der Naturwissenschaften (Dr. rer. nat.) eingereicht im Fachbereich Biologie, Chemie, Pharmazie der Freien Universität Berlin vorgelegt von Thore C. Brink aus Herdecke August 2008 1. Gutachter: Prof. Dr. Hans Lehrach, Max-Planck-Institut für Molekulare Genetik 2. Gutachter: Prof. Dr. Volker Erdmann Freie Universität Berlin Disputation am 27.03.2009 Acknowledgment Acknowledgment Ich danke Herrn Professor Lehrach für die Betreuung, das Interesse und die Unterstützung beim Durchführen dieser Arbeit sowie für die Überlassung des Themas und die Möglichkeit die Dissertation am Max-Planck-Institut für Molekulare Genetik anzufertigen. Des Weiteren danke ich Herrn Professor Erdmann für das Interesse und die Unterstützung beim Durchführen dieser Arbeit. Ein besonderer Dank gebührt Herrn Dr. James Adjaye für die Korrektur, Unterstützung und Anleitung bei der Anfertigung meiner Dissertation sowie für die angenehme Zusammenarbeit während der letzten Jahre. Den Mitgliedern meiner Arbeitsgruppe sowie allen anderen Mitarbeitern und Doktoranden des Max-Planck-Instituts für Molekulare Genetik danke ich für die gute Zusammenarbeit und das gute Arbeitsklima. Meiner Familie danke ich herzlich für vielerlei Unterstützung, Aufmunterung und Anerkennung während der zurückliegenden Zeit. Hervorzuheben sind meine Frau Nicole und meine Eltern Dr. Kurt und Carmen Brink. Ich danke herzlich meinen Freunden für ihre Unterstützung und Aufmunterung während der zurückliegenden Zeit. Danke Andreas und Marc für die tatkräftige Unterstützung bei der Korrektur und viele anregende Gespräche. Vielen Dank Metzler für das Erstellen der PDF Version dieser Arbeit. Contents Contents ABBREVIATIONS V LIST OF FIGURES VII LIST OF TABLES IX ABSTRACT XI ABSTRACT (GERMAN) XIII 1. INTRODUCTION 1 1.1 Aging 1 1.1.1 Aging theories 1 1.1.2 Model systems in aging research 5 1.1.3 Human skin aging 9 1.2 Whole genome microarray analyses 10 1.2.1 Molecular methods employed for gene expression analyses 10 1.2.2 Advantages and disadvantages of whole genome studies 11 1.2.3 Gene expression microarrays and aging 12 1.3 Aim of this work 13 I Contents 2. MATERIAL AND METHODS 14 2.1 Model systems 14 2.1.1 Cell cultures 14 2.1.2 Human skin biopsies 14 2.1.3 Mice 15 2.2 RNA analyses 15 2.2.1 Total RNA isolation 15 2.2.2 RNA and cDNA quantification 16 2.2.3 Agarose gel electrophoresis 17 2.2.4 Reverse transcription 17 2.2.5 Real-time polymerase chain reaction (Real-Time PCR) 18 2.2.6 ENSEMBL chip hybridisation 18 2.2.7 Illumina bead chip hybridisation 20 2.2.8 Pathway analysis 21 2.3 Protein analyses 21 2.3.1 Protein isolation 21 2.3.2 Protein quantification (Bradford) 22 2.3.3 SDS-PAGE gel electrophoresis 22 2.3.4 Western blotting 23 2.4 Metabolite analyses 24 2.4.1 Lipid hydroperoxide (LPO) measurement 24 2.5 Histology 24 2.5.1 Section preparation 24 2.5.2 Hematoxylin Eosin staining 25 II Contents 3. RESULTS 27 3.1 Global data analysis 27 3.1.1 Global gene expression analysis 27 3.1.2 RNA quality control 29 3.1.3 Target gene lists 30 3.1.4 Pathway analyses 31 3.1.5 Array data confirmation by Real-Time PCR 31 3.2 Human skin aging 33 3.2.1 Genetic changes in age-dependent hormone-treated cell cultures 33 3.2.2 Gene expression in young and old sun-protected skin biopsies 35 3.2.3 Analogous gene expression of in vitro and in vivo skin samples 38 3.3 Mouse aging (brain, heart & kidney) 40 3.3.1 Synchronizing the sample collection 40 3.3.2 Physical and morphological differences of young and aged mice 45 3.3.3 Age-dependent gene expression in mouse brain, heart and kidney 46 3.3.4 Age-related post-transcriptional and structural changes 53 3.4 Comparison of human and mouse aging 55 3.4.1 Correlation of age-regulated target genes 55 3.4.2 Correlation of age-regulated Kegg pathways and Gene Ontologies (BP and CC) 57 3.4.3 Correlation of target genes to published data 62 III Contents 4. DISCUSSION 64 4.1 Global data analysis 64 4.2 Human skin aging 67 4.3 Mouse aging 72 4.4 The basis of aging 76 5. CONCLUSION 78 REFERENCES A PUBLICATIONS L CURRICULUM VITAE M APPENDIX N I Buffers for SDS-PAGE gel electrophoresis N II Buffers for western blotting O III Target gene lists P IV David output tables W IV Abbreviations Abbreviations Abbreviations AGEs advanced glycation end products aRNA amplified ribonucleic acid ATP adenosine triphosphate BP biological process BSA bovine serum albumin CC cellular compartment cDNA complementary deoxyribonucleic acid CLS chronological life span CR caloric restriction Ct threshold cycle DNA deoxyribonucleic acid dNTP deoxyribonucleotide triphosphate DR dietary restriction GO gene ontology LPO lipid hydroperoxide MHC major histocompatibility complex mRNA messenger ribonucleic acid PBS phosphate buffered saline PCR polymerase chain reaction PFA paraformaldehyde RLS replicative life span RNA ribonucleic acid ROS radical oxygen species RT room temperature SDS sodium dodecyl sulfate SSC sodium chloride/sodium citrate V Abbreviations Semantics °C degrees Celsius µg micrograms µl microlitres µM micromol g grams / gravity hr/hrs hours M mol mA milliampere mg milligrams min minutes ml millilitres mm millimetres mM millimol ng nanograms nm nanometres pg picograms pmol picomol s seconds U units V volt VI List of Figures List of Figures • Figure 1.1 The dual role of ROS and its contribution to aging. 4 • Figure 2.1 Sample output of pathway and GO analyses. 21 • Figure 3.1 Clustering of samples and correlation factors for mouse and human in vivo experiments. 28 • Figure 3.2 RNA quality control gel pictures. 30 • Figure 3.3 Venn diagrams visualizing the overlap of the in vitro and in vivo skin aging results. 39 • Figure 3.4 Clustering of samples and correlation factors for synchronization experiments. 41 • Figure 3.5 Scatter plots highlighting the regulation of circadian rhythm genes. 42 • Figure 3.6 Real-Time PCR experiments investigating circadian rhythm gene expression. 43 • Figure 3.7 Morphological differences of young and aged mice. 45 • Figure 3.8 Overlapping target genes of synchronised and unsynchronised aging samples. 50 • Figure 3.9 Investigations beyond the RNA levels. 53 • Figure 3.10 Venn diagram visualizing the overlap of common regulated target genes in the mouse in vivo and human in vivo and in vitro samples. 55 • Figure 3.11 4-way Venn diagrams visualizing the detailed overlap of regulated target genes in the mouse in vivo and human in vivo and in vitro samples. 56 • Figure 3.12 Venn diagram visualizing the overlap of common regulated Kegg pathways in the mouse in vivo and human in vivo and in vitro samples. 57 • Figure 3.13 4-way Venn diagrams visualizing the detailed overlap of regulated Kegg pathways in the mouse in vivo and human in vivo and in vitro samples. 58 VII List of Figures • Figure 3.14 Venn diagram visualizing the overlap of common regulated biological processes in the mouse in vivo and human in vivo and in vitro samples. 59 • Figure 3.15 4-way Venn diagrams visualizing the detailed overlap of regulated biological processes in the mouse in vivo and human in vivo and in vitro samples. 60 • Figure 3.16 Venn diagram visualizing the overlap of common regulated cellular compartments in the mouse in vivo and human in vivo samples. 61 • Figure 3.17 4-way Venn diagrams visualizing the detailed overlap of regulated cellular compartments in the mouse in vivo and human in vivo samples. 61 VIII List of Tables List of Tables • Table 3.1 Number of target genes for all in vitro and in vivo aging experiments. 30 • Table 3.2 Array data confirmation by Real-Time PCR. 32 • Table 3.3 List of overlapping genes regulated in skin fibroblasts and sebocytes with age. 34 • Table 3.4 List of overlapping biological processes regulated in fibroblasts and sebocytes with age. 35 • Table 3.5 List of overlapping genes regulated in male and female skin biopsies with age. 37 • Table 3.6 List of overlapping pathways and GOs regulated in male and female skin biopsies with age. 38 • Table 3.7 List of overlapping biological processes regulated in the in vitro and in vivo experiments. 39 • Table 3.8 Circadian rhythm genes regulated in mouse brain, heart and kidney. 40 • Table 3.9 Most-regulated genes in a 16hrs period in mouse kidney. 44 • Table 3.10 List of overlapping genes regulated in mouse brain, heart and kidney with age. 47 • Table 3.11 List of overlapping pathways and GOs regulated in mouse brain, heart and kidney with age. 48 • Table 3.12 List of overlapping genes regulated in synchronised and unsynchronised brain samples. 49 • Table 3.13 List of overlapping genes regulated in synchronised and unsynchronised heart samples. 51 • Table 3.14 List of overlapping genes regulated in synchronised and unsynchronised kidney samples. 52 IX List of Tables • Table 3.15 Results of the LPO measurement. 54 • Table 3.16 List of overlapping target genes in Lener et al. (2006) and the investigated human skin samples. 62 • Table 3.17 List of overlapping target genes in the AGEMAP database and the investigated mouse tissues (brain, heart, kidney). 63 • Table X.1 Target gene list for human skin fibroblasts. P • Table X.2 Target gene list for human sebocytes. Q • Table X.3 Target gene list for female human skin biopsies. R • Table X.4 Target gene list for male human skin biopsies.
Load more

Recommended publications
  • Global Mef2 Target Gene Analysis in Skeletal and Cardiac Muscle
    GLOBAL MEF2 TARGET GENE ANALYSIS IN SKELETAL AND CARDIAC MUSCLE STEPHANIE ELIZABETH WALES A DISSERTATION SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY GRADUATE PROGRAM IN BIOLOGY YORK UNIVERSITY TORONTO, ONTARIO FEBRUARY 2016 © Stephanie Wales 2016 ABSTRACT A loss of muscle mass or function occurs in many genetic and acquired pathologies such as heart disease, sarcopenia and cachexia which are predominantly found among the rapidly increasing elderly population. Developing effective treatments relies on understanding the genetic networks that control these disease pathways. Transcription factors occupy an essential position as regulators of gene expression. Myocyte enhancer factor 2 (MEF2) is an important transcription factor in striated muscle development in the embryo, skeletal muscle maintenance in the adult and cardiomyocyte survival and hypertrophy in the progression to heart failure. We sought to identify common MEF2 target genes in these two types of striated muscles using chromatin immunoprecipitation and next generation sequencing (ChIP-seq) and transcriptome profiling (RNA-seq). Using a cell culture model of skeletal muscle (C2C12) and primary cardiomyocytes we found 294 common MEF2A binding sites within both cell types. Individually MEF2A was recruited to approximately 2700 and 1600 DNA sequences in skeletal and cardiac muscle, respectively. Two genes were chosen for further study: DUSP6 and Hspb7. DUSP6, an ERK1/2 specific phosphatase, was negatively regulated by MEF2 in a p38MAPK dependent manner in striated muscle. Furthermore siRNA mediated gene silencing showed that MEF2D in particular was responsible for repressing DUSP6 during C2C12 myoblast differentiation. Using a p38 pharmacological inhibitor (SB 203580) we observed that MEF2D must be phosphorylated by p38 to repress DUSP6.
    [Show full text]
  • (12) Patent Application Publication (10) Pub. No.: US 2003/0082511 A1 Brown Et Al
    US 20030082511A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2003/0082511 A1 Brown et al. (43) Pub. Date: May 1, 2003 (54) IDENTIFICATION OF MODULATORY Publication Classification MOLECULES USING INDUCIBLE PROMOTERS (51) Int. Cl." ............................... C12O 1/00; C12O 1/68 (52) U.S. Cl. ..................................................... 435/4; 435/6 (76) Inventors: Steven J. Brown, San Diego, CA (US); Damien J. Dunnington, San Diego, CA (US); Imran Clark, San Diego, CA (57) ABSTRACT (US) Correspondence Address: Methods for identifying an ion channel modulator, a target David B. Waller & Associates membrane receptor modulator molecule, and other modula 5677 Oberlin Drive tory molecules are disclosed, as well as cells and vectors for Suit 214 use in those methods. A polynucleotide encoding target is San Diego, CA 92121 (US) provided in a cell under control of an inducible promoter, and candidate modulatory molecules are contacted with the (21) Appl. No.: 09/965,201 cell after induction of the promoter to ascertain whether a change in a measurable physiological parameter occurs as a (22) Filed: Sep. 25, 2001 result of the candidate modulatory molecule. Patent Application Publication May 1, 2003 Sheet 1 of 8 US 2003/0082511 A1 KCNC1 cDNA F.G. 1 Patent Application Publication May 1, 2003 Sheet 2 of 8 US 2003/0082511 A1 49 - -9 G C EH H EH N t R M h so as se W M M MP N FIG.2 Patent Application Publication May 1, 2003 Sheet 3 of 8 US 2003/0082511 A1 FG. 3 Patent Application Publication May 1, 2003 Sheet 4 of 8 US 2003/0082511 A1 KCNC1 ITREXCHO KC 150 mM KC 2000000 so 100 mM induced Uninduced Steady state O 100 200 300 400 500 600 700 Time (seconds) FIG.
    [Show full text]
  • Functional Role of a Polysialic Acid- Carrying Proteolytic Fragment of the Neural Cell Adhesion Molecule NCAM in the Nervous System
    Functional role of a polysialic acid- carrying proteolytic fragment of the neural cell adhesion molecule NCAM in the nervous system DISSERTATION Zur Erlangung des Doktorgerades der Naturwissenschaften ( doctor rerum naturalium ) des Departments Biologie der Fakultät für Mathematik, Informatik und Naturwissenschaften an der Universität Hamburg Vorgelegt von NINAWESTPHAL Hamburg, 2017 Diese Arbeit wurde am Zentrum für Molekulare Neurobiologie Hamburg (ZMNH), im Institut für Biosynthese Neuraler Strukturen durchgeführt. Gutachter: Frau Prof. Dr. M. Schachner Herr Prof. Dr. T. Burmester Tag der Disputation: 07.03.2017 Contents Statement of Contribution ........................................................................................................................ I 1. Introduction ......................................................................................................................................... 1 1.1 Structure, isoforms and proteolytic processing of NCAM ........................................................................... 2 1.2. N-glycosylation of NCAM and attachment of polysialic acid ................................................................... 3 1.3 Functions of polysialylated NCAM in the central nervous system .............................................................. 5 1.4 Interaction of PSA and/or NCAM with other molecules.............................................................................. 6 1.5 PSA-NCAM- mediated downstream signalling ..........................................................................................
    [Show full text]
  • (10) Patent No.: US 8119385 B2
    US008119385B2 (12) United States Patent (10) Patent No.: US 8,119,385 B2 Mathur et al. (45) Date of Patent: Feb. 21, 2012 (54) NUCLEICACIDS AND PROTEINS AND (52) U.S. Cl. ........................................ 435/212:530/350 METHODS FOR MAKING AND USING THEMI (58) Field of Classification Search ........................ None (75) Inventors: Eric J. Mathur, San Diego, CA (US); See application file for complete search history. Cathy Chang, San Diego, CA (US) (56) References Cited (73) Assignee: BP Corporation North America Inc., Houston, TX (US) OTHER PUBLICATIONS c Mount, Bioinformatics, Cold Spring Harbor Press, Cold Spring Har (*) Notice: Subject to any disclaimer, the term of this bor New York, 2001, pp. 382-393.* patent is extended or adjusted under 35 Spencer et al., “Whole-Genome Sequence Variation among Multiple U.S.C. 154(b) by 689 days. Isolates of Pseudomonas aeruginosa” J. Bacteriol. (2003) 185: 1316 1325. (21) Appl. No.: 11/817,403 Database Sequence GenBank Accession No. BZ569932 Dec. 17. 1-1. 2002. (22) PCT Fled: Mar. 3, 2006 Omiecinski et al., “Epoxide Hydrolase-Polymorphism and role in (86). PCT No.: PCT/US2OO6/OOT642 toxicology” Toxicol. Lett. (2000) 1.12: 365-370. S371 (c)(1), * cited by examiner (2), (4) Date: May 7, 2008 Primary Examiner — James Martinell (87) PCT Pub. No.: WO2006/096527 (74) Attorney, Agent, or Firm — Kalim S. Fuzail PCT Pub. Date: Sep. 14, 2006 (57) ABSTRACT (65) Prior Publication Data The invention provides polypeptides, including enzymes, structural proteins and binding proteins, polynucleotides US 201O/OO11456A1 Jan. 14, 2010 encoding these polypeptides, and methods of making and using these polynucleotides and polypeptides.
    [Show full text]
  • Supplementary Table 1: Differentially Methylated Genes and Functions of the Genes Before/After Treatment with A) Doxorubicin and B) FUMI and in C) Responders Vs
    Supplementary Table 1: Differentially methylated genes and functions of the genes before/after treatment with a) doxorubicin and b) FUMI and in c) responders vs. non- responders for doxorubicin and d) FUMI Differentially methylated genes before/after treatment a. Doxo GENE FUNCTION CCL5, CCL8, CCL15, CCL21, CCR1, CD33, IL5, immunoregulatory and inflammatory processes IL8, IL24, IL26, TNFSF11 CCNA1, CCND2, CDKN2A cell cycle regulators ESR1, FGF2, FGF14, FGF18 growth factors WT1, RASSF5, RASSF6 tumor suppressor b. FUMI GENE FUNCTION CCL7, CCL15, CD28, CD33, CD40, CD69, TNFSF18 immunoregulatory and inflammatory processes CCND2, CDKN2A cell cycle regulators IGF2BP1, IGFBP3 growth factors HOXB4, HOXB6, HOXC8 regulation of cell transcription WT1, RASSF6 tumor suppressor Differentially methylated genes in responders vs. non-responders c. Doxo GENE FUNCTION CBR1, CCL4, CCL8, CCR1, CCR7, CD1A, CD1B, immunoregulatory and inflammatory processes CD1D, CD1E, CD33, CD40, IL5, IL8, IL20, IL22, TLR4 CCNA1, CCND2, CDKN2A cell cycle regulators ESR2, ERBB3, FGF11, FGF12, FGF14, FGF17 growth factors WNT4, WNT16, WNT10A implicated in oncogenesis TNFSF12, TNFSF15 apoptosis FOXL1, FOXL2, FOSL1,HOXA2, HOXA7, HOXA11, HOXA13, HOXB4, HOXB6, HOXB8, HOXB9, HOXC8, regulation of cell transcription HOXD8, HOXD9, HOXD11 GSTP1, MGMT DNA repair APC, WT1 tumor suppressor d. FUMI GENE FUNCTION CCL1, CCL3, CCL5,CCL14, CD1B, CD33, CD40, CD69, immunoregulatory and inflammatory IL20, IL32 processes CCNA1, CCND2, CDKN2A cell cycle regulators IGF2BP1, IGFBP3, IGFBP7, EGFR, ESR2,RARB2
    [Show full text]
  • United States Patent (19) 11 Patent Number: 5,919,673 Wong Et Al
    USOO59 19673A United States Patent (19) 11 Patent Number: 5,919,673 Wong et al. (45) Date of Patent: Jul. 6, 1999 54) ONE-POTENZYMATIC SULFATION Sekura, Methods in Enzymology, 77:413 (1981. PROCESS USING 3'-PHOSPHOADENOSINE Horwitz et al., Biochem. Biophy. Acta., 480:376 (1977). 5'-PHOSPHOSULEATE AND RECYCLED Satishchandran et al., J. Biol. Chem., 264:15012 (1989). PHOSPHORYLATED ADENOSINE Fernando et al., Biosci. Biotech. Biochem, 57:1974 (1993). INTERMEDIATES Mukai, Agric. Biol. Chem, 53:883 (1989). Leyh et al., J. Biol. Chem., 263:2409 (1988). 75 Inventors: Chi-Huey Wong, Rancho Sante Fe; Renosto et al., J. Biol. Chem., 259:2113 (1989). Chun-Hung Lin, San Diego; Marcus et al., Anal. Biochem., 107:296 (1980). GWO-Jenn Shen, Carlsbad, all of Calif. Suzuki et al., Biochim. Biophys. Acta, 50:169 (1961). Robinson, Biochem. J., 113:543 (1969). 73 Assignee: The Scripps Research Institute, Kimata et al., Mol. Cell. Biochem. 1:211(1973). LaJolla, Calif. Silbert, J. Biol. Chem., 239:1310 (1964). Kim et al., J. Biol. Chem., 252:8292 (1977). 21 Appl. No.: 08/408,774 Habuchi et al., Biochim. Biophys. Acta, 208:616 (1980). Habuchi et al., Biochim. Biophys. Acta, 414:717 (1982). 22 Filed: Mar. 22, 1995 Habuchi et al., J. Biol. Chem., 246:7357 (1971). 51) Int. Cl. ............................. C12P 11/00; C12P33/00; Nakanishi et al., J. Biol. Chem., 256:5443 (1981). C12P 19/04; C12P 19/32 Sugumaran et al., J. Biol. Chem., 261: 12659 (1986). 52 U.S. Cl. ............................ 435/130; 435/101; 435/52; Fisher et al., Nature, 357:655 (1992). 435/92 LeRouge et al., Nature, 344:781 (1990).
    [Show full text]
  • RAB-GAP Immunity Signaling by the Tbc1d23 Spatiotemporal Inhibition
    Downloaded from http://www.jimmunol.org/ by guest on September 27, 2021 is online at: average * The Journal of Immunology , 17 of which you can access for free at: 2012; 188:2905-2913; Prepublished online 6 from submission to initial decision 4 weeks from acceptance to publication February 2012; doi: 10.4049/jimmunol.1102595 http://www.jimmunol.org/content/188/6/2905 Spatiotemporal Inhibition of Innate Immunity Signaling by the Tbc1d23 RAB-GAP Lesly De Arras, Ivana V. Yang, Brad Lackford, David W. H. Riches, Rytis Prekeris, Jonathan H. Freedman, David A. Schwartz and Scott Alper J Immunol cites 58 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription http://www.jimmunol.org/content/suppl/2012/02/06/jimmunol.110259 5.DC1 This article http://www.jimmunol.org/content/188/6/2905.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 All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 27, 2021. The Journal of Immunology Spatiotemporal Inhibition of Innate Immunity Signaling by the Tbc1d23 RAB-GAP Lesly De Arras,*,† Ivana V. Yang,†,‡ Brad Lackford,x David W.
    [Show full text]
  • Genome-Scale Phylogenetic Function Annotation of Large and Diverse Protein Families
    Downloaded from genome.cshlp.org on October 1, 2021 - Published by Cold Spring Harbor Laboratory Press 1 Genome-scale phylogenetic function annotation of large and diverse protein families 1∗ Barbara E Engelhardt Electrical Engineering and Computer Science Department, University of California, Berkeley, Berkeley, CA, USA Current address: Computer Science Department, University of Chicago, Chicago, IL, USA 2 Michael I Jordan Statistics Department and Electrical Engineering and Computer Science Department, University of California, Berkeley, Berkeley, CA, USA 3 John R Srouji Plant & Microbial Biology, University of California, Berkeley, Berkeley, CA USA Current address: Molecular and Cellular Biology Department, Harvard University, Cambridge, MA, USA 4 Steven E Brenner Plant and Microbial Biology Department, University of California, Berkeley, Berkeley, CA, USA ∗ Corresponding author: [email protected] Running Title: Phylogenetic function annotation Keywords: Protein molecular function annotation, statistical model, protein function evolution, Gene Ontology, whole-genome annotation. Downloaded from genome.cshlp.org on October 1, 2021 - Published by Cold Spring Harbor Laboratory Press 2 Abstract The Statistical Inference of Function Through Evolutionary Relationships (SIFTER) framework uses a statistical graphical model that applies phylogenetic principles to automate precise protein function pre- diction (Engelhardt et al., 2005, 2006). Here we present a significant revision of the approach (SIFTER version 2.0) that allows annotations to be made on a genomic scale. We confirm that SIFTER 2.0 pro- duces equivalently precise predictions to the earlier version of SIFTER on a carefully studied family and on a collection of one hundred protein families with limited functional diversity. We have added an ap- proximation method to SIFTER 2.0, and show a 500-fold improvement in speed with minimal impact on prediction results in the functionally diverse sulfotransferase protein family.
    [Show full text]
  • Enzymatic Synthesis of Glycosaminoglycans: Improving on Nature
    Fronteirs in Modern Carbohydrate Chemistry, ACS Symposium Series 960, Alexei V. Demchenko, Editor, ACS, Washington, DC, 2007 Chapter 15 ENZYMATIC SYNTHESIS OF GLYCOSAMINOGLYCANS: IMPROVING ON NATURE Fikri Y. Avci,1 Paul L. DeAngelis,2 Jian Liu,3 Robert J. Linhardt,*1 1Departments of Chemistry and Chemical Biology, Biology and Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, 2Department of Biochemistry and Molecular Biology, Oklahoma Center for Medical Glycobiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, 3Division of Medicinal Chemistry and Natural Products, School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599. The chemoenzymatic synthesis of glycosaminoglycan (GAG) analogs is described. This chapter is divided into three main sections, each describing the use of one enzyme family in GAG synthesis. First, the polysaccharide lyase enzymes are described. These enzymes play crucial role in obtaining homogenous GAG oligosaccharides. Second, GAG synthases, bacterial enzymes that transfer UDP-monosaccharides to acceptor oligosaccharide, GAG synthases are used to obtain homogenous oligosaccharides and polysaccharides. Finally, GAG sulfotransferases, playing a major role in the biosynthesis, are described for the introduction of sulfo groups to the appropriate positions on the polysaccharide backbone. © 2007 American Chemical Society 253 254 1. INTRODUCTION Glycosaminoglycans (GAGs) are highly charged polysaccharides consisting of repeating 1→3 and/or 1→4 linked hexosamine and uronic acid residues (Figure 1).1, 2 GAGs are polydisperse mixtures of polysaccharide chains of varying lengths with an average molecular weight of 104-106 Da.2 GAGs are synthesized by both prokaryotes3 and eukaryotes and are found in all animal cells.2 Pharmaceutical heparin is an example of a structurally complex GAG that is prepared from porcine intestinal mucosa and bovine lung in amounts of 30 metric tons/yr.
    [Show full text]
  • 12) United States Patent (10
    US007635572B2 (12) UnitedO States Patent (10) Patent No.: US 7,635,572 B2 Zhou et al. (45) Date of Patent: Dec. 22, 2009 (54) METHODS FOR CONDUCTING ASSAYS FOR 5,506,121 A 4/1996 Skerra et al. ENZYME ACTIVITY ON PROTEIN 5,510,270 A 4/1996 Fodor et al. MICROARRAYS 5,512,492 A 4/1996 Herron et al. 5,516,635 A 5/1996 Ekins et al. (75) Inventors: Fang X. Zhou, New Haven, CT (US); 5,532,128 A 7/1996 Eggers Barry Schweitzer, Cheshire, CT (US) 5,538,897 A 7/1996 Yates, III et al. s s 5,541,070 A 7/1996 Kauvar (73) Assignee: Life Technologies Corporation, .. S.E. al Carlsbad, CA (US) 5,585,069 A 12/1996 Zanzucchi et al. 5,585,639 A 12/1996 Dorsel et al. (*) Notice: Subject to any disclaimer, the term of this 5,593,838 A 1/1997 Zanzucchi et al. patent is extended or adjusted under 35 5,605,662 A 2f1997 Heller et al. U.S.C. 154(b) by 0 days. 5,620,850 A 4/1997 Bamdad et al. 5,624,711 A 4/1997 Sundberg et al. (21) Appl. No.: 10/865,431 5,627,369 A 5/1997 Vestal et al. 5,629,213 A 5/1997 Kornguth et al. (22) Filed: Jun. 9, 2004 (Continued) (65) Prior Publication Data FOREIGN PATENT DOCUMENTS US 2005/O118665 A1 Jun. 2, 2005 EP 596421 10, 1993 EP 0619321 12/1994 (51) Int. Cl. EP O664452 7, 1995 CI2O 1/50 (2006.01) EP O818467 1, 1998 (52) U.S.
    [Show full text]
  • Immune Cells in Spleen and Mucosa + CD127 Neg Production of IL-17 and IL-22 by CD3 TLR5 Signaling Stimulates the Innate
    Downloaded from http://www.jimmunol.org/ by guest on September 23, 2021 neg is online at: average * The Journal of Immunology , 23 of which you can access for free at: 2010; 185:1177-1185; Prepublished online 21 Immune Cells in Spleen and Mucosa from submission to initial decision + 4 weeks from acceptance to publication TLR5 Signaling Stimulates the Innate Production of IL-17 and IL-22 by CD3 CD127 Laurye Van Maele, Christophe Carnoy, Delphine Cayet, Pascal Songhet, Laure Dumoutier, Isabel Ferrero, Laure Janot, François Erard, Julie Bertout, Hélène Leger, Florent Sebbane, Arndt Benecke, Jean-Christophe Renauld, Wolf-Dietrich Hardt, Bernhard Ryffel and Jean-Claude Sirard June 2010; doi: 10.4049/jimmunol.1000115 http://www.jimmunol.org/content/185/2/1177 J Immunol cites 51 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://www.jimmunol.org/content/185/2/1177.full#ref-list-1 http://www.jimmunol.org/content/suppl/2010/06/21/jimmunol.100011 5.DC1 This article 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 © 2010 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606.
    [Show full text]
  • Caractérisation Moléculaire De Tumeurs Pulmonaires Radon-Induites Chez Le Rat
    UNIVERSITÉ PARIS XI FACULTÉ DE MÉDECINE PARIS-SUD Ecole doctorale de Cancérologie : Biologie, Médecine, Santé Année 2008 Thèse n° THÈSE Pour obtenir le grade de DOCTEUR DE L’UNIVERSITÉ DE PARIS XI Spécialité : Radiobiologie Présentée et soutenue publiquement par Kristell GUILLET BASTIDE Le 13 novembre 2008 TITRE CARACTÉRISATION MOLÉCULAIRE DE TUMEURS PULMONAIRES RADON-INDUITES CHEZ LE RAT tel-00349902, version 1 - 5 Jan 2009 Directeur de thèse : Pr Jean-François BERNAUDIN JURY Pr Christian BRAMBILLA Président Dr Xavier GIDROL Rapporteur Dr Marc BENDERITTER Rapporteur Pr Philippe GAULARD Examinateur Dr Sylvie CHEVILLARD Examinateur Pr Jean-François BERNAUDIN Directeur de thèse Remerciements Je remercie vivement Monsieur Gidrol et Monsieur Benderitter d’avoir accepté d’être les rapporteurs de cette thèse. Merci à Monsieur Gaulard pour son travail d’examinateur et à Monsieur Brambilla qui a accepté de présider le jury. Merci également au professeur Bernaudin, directeur de thèse auprès de l’Université, qui m’a soutenue et m’a apportée une aide précieuse pour ce travail. Je tiens à remercier Sylvie Chevillard de m’avoir intégrée dans son laboratoire de Cancérologie Expérimentale au CEA de Fontenay-aux-Roses et de m’avoir encadrée pour préparer cette thèse. Sa rigueur scientifique et ses précieux conseils ont été des plus formateurs. Mes remerciements vont également à Monsieur Bernard Malfoy de l’Institut Curie dont la disponibilité et l’écoute ont contribué de façon significative à la progression de ce travail de thèse. Tous mes remerciements vont aussi à mes collègues de travail du laboratoire de Cancérologie Expérimentale qui ont suivi de près ou de loin l’évolution de cette thèse.
    [Show full text]