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Joosten, Han M.L.J.; Herst, Patricia M.; Drift, Chris Van Der
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by University of Groningen University of Groningen Characterization of Glutamine-Requiring Mutants of Pseudomonas aeruginosa Janssen, Dick B.; Joosten, Han M.L.J.; Herst, Patricia M.; Drift, Chris van der Published in: Archives of Microbiology IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 1982 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Janssen, D. B., Joosten, H. M. L. J., Herst, P. M., & Drift, C. V. D. (1982). Characterization of Glutamine- Requiring Mutants of Pseudomonas aeruginosa. Archives of Microbiology, 131(4). Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons). Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum. Download date: 12-11-2019 JOURNAL OF BACTERIOLOGY, Sept. 1982, p. 1176-1183 Vol. 151, No. -
Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse
Welcome to More Choice CD Marker Handbook For more information, please visit: Human bdbiosciences.com/eu/go/humancdmarkers Mouse bdbiosciences.com/eu/go/mousecdmarkers Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse CD3 CD3 CD (cluster of differentiation) molecules are cell surface markers T Cell CD4 CD4 useful for the identification and characterization of leukocytes. The CD CD8 CD8 nomenclature was developed and is maintained through the HLDA (Human Leukocyte Differentiation Antigens) workshop started in 1982. CD45R/B220 CD19 CD19 The goal is to provide standardization of monoclonal antibodies to B Cell CD20 CD22 (B cell activation marker) human antigens across laboratories. To characterize or “workshop” the antibodies, multiple laboratories carry out blind analyses of antibodies. These results independently validate antibody specificity. CD11c CD11c Dendritic Cell CD123 CD123 While the CD nomenclature has been developed for use with human antigens, it is applied to corresponding mouse antigens as well as antigens from other species. However, the mouse and other species NK Cell CD56 CD335 (NKp46) antibodies are not tested by HLDA. Human CD markers were reviewed by the HLDA. New CD markers Stem Cell/ CD34 CD34 were established at the HLDA9 meeting held in Barcelona in 2010. For Precursor hematopoetic stem cell only hematopoetic stem cell only additional information and CD markers please visit www.hcdm.org. Macrophage/ CD14 CD11b/ Mac-1 Monocyte CD33 Ly-71 (F4/80) CD66b Granulocyte CD66b Gr-1/Ly6G Ly6C CD41 CD41 CD61 (Integrin b3) CD61 Platelet CD9 CD62 CD62P (activated platelets) CD235a CD235a Erythrocyte Ter-119 CD146 MECA-32 CD106 CD146 Endothelial Cell CD31 CD62E (activated endothelial cells) Epithelial Cell CD236 CD326 (EPCAM1) For Research Use Only. -
Amino Acid Disorders 105
AMINO ACID DISORDERS 105 Massaro, A. S. (1995). Trypanosomiasis. In Guide to Clinical tions in biological fluids relatively easy. These Neurology (J. P. Mohrand and J. C. Gautier, Eds.), pp. 663– analyzers separate amino acids either by ion-ex- 667. Churchill Livingstone, New York. Nussenzweig, V., Sonntag, R., Biancalana, A., et al. (1953). Ac¸a˜o change chromatography or by high-pressure liquid de corantes tri-fenil-metaˆnicos sobre o Trypanosoma cruzi in chromatography. The results are plotted as a graph vitro: Emprego da violeta de genciana na profilaxia da (Fig. 1). The concentration of each amino acid can transmissa˜o da mole´stia de chagas por transfusa˜o de sangue. then be calculated from the size of the corresponding O Hospital (Rio de Janeiro) 44, 731–744. peak on the graph. Pagano, M. A., Segura, M. J., DiLorenzo, G. A., et al. (1999). Cerebral tumor-like American trypanosomiasis in Most amino acid disorders can be diagnosed by acquired immunodeficiency syndrome. Ann. Neurol. 45, measuring the concentrations of amino acids in 403–406. blood plasma; however, some disorders of amino Rassi, A., Trancesi, J., and Tranchesi, B. (1982). Doenc¸ade acid transport are more easily recognized through the Chagas. In Doenc¸as Infecciosas e Parasita´rias (R. Veroesi, Ed.), analysis of urine amino acids. Therefore, screening 7th ed., pp. 674–712. Guanabara Koogan, Sa˜o Paulo, Brazil. Spina-Franc¸a, A., and Mattosinho-Franc¸a, L. C. (1988). for amino acid disorders is best done using both South American trypanosomiasis (Chagas’ disease). In blood and urine specimens. Occasionally, analysis of Handbook of Clinical Neurology (P. -
Effects of Glycosylation on the Enzymatic Activity and Mechanisms of Proteases
International Journal of Molecular Sciences Review Effects of Glycosylation on the Enzymatic Activity and Mechanisms of Proteases Peter Goettig Structural Biology Group, Faculty of Molecular Biology, University of Salzburg, Billrothstrasse 11, 5020 Salzburg, Austria; [email protected]; Tel.: +43-662-8044-7283; Fax: +43-662-8044-7209 Academic Editor: Cheorl-Ho Kim Received: 30 July 2016; Accepted: 10 November 2016; Published: 25 November 2016 Abstract: Posttranslational modifications are an important feature of most proteases in higher organisms, such as the conversion of inactive zymogens into active proteases. To date, little information is available on the role of glycosylation and functional implications for secreted proteases. Besides a stabilizing effect and protection against proteolysis, several proteases show a significant influence of glycosylation on the catalytic activity. Glycans can alter the substrate recognition, the specificity and binding affinity, as well as the turnover rates. However, there is currently no known general pattern, since glycosylation can have both stimulating and inhibiting effects on activity. Thus, a comparative analysis of individual cases with sufficient enzyme kinetic and structural data is a first approach to describe mechanistic principles that govern the effects of glycosylation on the function of proteases. The understanding of glycan functions becomes highly significant in proteomic and glycomic studies, which demonstrated that cancer-associated proteases, such as kallikrein-related peptidase 3, exhibit strongly altered glycosylation patterns in pathological cases. Such findings can contribute to a variety of future biomedical applications. Keywords: secreted protease; sequon; N-glycosylation; O-glycosylation; core glycan; enzyme kinetics; substrate recognition; flexible loops; Michaelis constant; turnover number 1. -
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, -
Amino Acid Catabolism in Staphylococcus Aureus
University of Nebraska Medical Center DigitalCommons@UNMC Theses & Dissertations Graduate Studies Fall 12-16-2016 Amino Acid Catabolism in Staphylococcus aureus Cortney Halsey University of Nebraska Medical Center Follow this and additional works at: https://digitalcommons.unmc.edu/etd Part of the Bacteriology Commons Recommended Citation Halsey, Cortney, "Amino Acid Catabolism in Staphylococcus aureus" (2016). Theses & Dissertations. 160. https://digitalcommons.unmc.edu/etd/160 This Dissertation is brought to you for free and open access by the Graduate Studies at DigitalCommons@UNMC. It has been accepted for inclusion in Theses & Dissertations by an authorized administrator of DigitalCommons@UNMC. For more information, please contact [email protected]. Amino Acid Catabolism in Staphylococcus aureus By Cortney R. Halsey A DISSERTATION Presented to the Faculty of The Graduate College in the University of Nebraska In Partial Fulfillment of the Requirements For the Degree of Doctor of Philosophy Pathology and Microbiology Under the Supervision of Dr. Paul D. Fey University of Nebraska Medical Center Omaha, Nebraska October 2016 Supervisory Committee: Kenneth Bayles, Ph.D. Steven Carson, Ph.D. Paul Dunman, Ph.D. Rakesh Singh, Ph.D. ii Acknowledgements First and foremost, I would like to thank my mentor, Dr. Paul Fey, whose patience and support over the past six years has been critical to my success as a graduate student. Paul has given me opportunities to grow as a scientist and person, for which I will be forever thankful. I would also like to thank Dr. Ken Bayles, Dr. Steven Carson, Dr. Paul Dunman, and Dr. Rakesh Singh for serving on my supervisory committee. -
University of California, San Diego
UNIVERSITY OF CALIFORNIA, SAN DIEGO A Lipidomic Perspective on Inflammatory Macrophage Eicosanoid Signaling A Thesis submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Chemistry by Paul Christopher Norris Committee in charge: Professor Edward A. Dennis, Chair Professor Pieter C. Dorrestein Professor Partho Ghosh Professor Christopher K. Glass Professor Michael J. Sailor 2013 The Dissertation of Paul Christopher Norris is approved, and it is acceptable in quality and form for publication on microfilm and electronically: Chair University of California, San Diego 2013 iii DEDICATION To my parents, Darrell and Kathy, for always allowing me to think (and choose) for myself. iv TABLE OF CONTENTS Signature page ............................................................................................................................ iii Dedication .................................................................................................................................. iv Table of contents ......................................................................................................................... v List of symbols and abbreviations ........................................................................................... viii List of figures ............................................................................................................................. xi List of tables ............................................................................................................................ -
BIOCHEMISTRY of TRYPTOPHAN in HEALTH and DISEASE Contents
Molec. Aspects Med. Vol. 6, pp. 101-197, 1982 0098-2997/82/020101-97548.50/0 Printed in Great Britain. All rights reserved. Copyright © Pergamon Press Ltd. BIOCHEMISTRY OF TRYPTOPHAN IN HEALTH AND DISEASE David A. Bender Courtauld Institute of Biochemistry, The Middlesex Hospital Medical School, London WIP 7PN, U.K. Contents Chapter 1 THE DISCOVERY OF TRYPTOPHAN, ITS PHYSIOLOGICAL SIGNIFICANCE AND METABOLIC FATES 103 Tryptophan and glucose metabolism 105 Xanthurenic acid and insulin 105 The glucose tolerance factor 106 Inhibition of gluconeogenesis by tryptophan metabolites i07 Metabolic fates of tryptophan 108 Protein synthesis 108 Oxidative metabolism Ii0 5-Hydroxyindole synthesis 111 Intestinal bacterial metabolism iii Chapter 2 THE 5-HYDROXYINDOLE PATHWAY OF TRYPTOPHAN METABOLISM; SEROTONIN AND OTHER CENTRALLY ACTIVE TRYPTOPHAN METABOLITES 112 Tryptophan 5-hydroxylase 112 Inhibition of tryptophan hydroxylase and the carcinoid syndrome 116 Aromatic amino acid decarboxylase 118 The specificity of aromatic amino acid decarboxylase 120 Tryptophan metabolism in the pineal gland 121 Monoamine oxidase 124 The uptake of tryptophan into the brain 124 The binding of tryptophan to serum albumin 127 Competition for uptake by other neutral amino acids 129 Changes in tryptophan metabolism in response to food intake 129 Tryptophan uptake into the brain in liver failure 131 Sleep and tryptophan metabolism 134 101 102 D.A. Bender Tryptophan and serotonin in psychiatric disorders 135 Affective disorders 136 Evidence for a deficit of serotonin or tryptophan -
Downloaded by Academic Researchers from Academia.Nferx.Com and Will Be Made Accessible to Non-Academic Researchers Upon Reasonable Request
G C A T T A C G G C A T genes Article A Literature-Derived Knowledge Graph Augments the Interpretation of Single Cell RNA-seq Datasets Deeksha Doddahonnaiah 1,†, Patrick J. Lenehan 1,† , Travis K. Hughes 1, David Zemmour 1, Enrique Garcia-Rivera 1 , A. J. Venkatakrishnan 1, Ramakrishna Chilaka 2, Apoorv Khare 2, Akhil Kasaraneni 2, Abhinav Garg 2, Akash Anand 2, Rakesh Barve 2, Viswanathan Thiagarajan 2 and Venky Soundararajan 1,2,* 1 nference, One Main Street, Cambridge, MA 02142, USA; [email protected] (D.D.); [email protected] (P.J.L.); [email protected] (T.K.H.); [email protected] (D.Z.); [email protected] (E.G.-R.); [email protected] (A.J.V.) 2 nference Labs, Bengaluru, Karnataka 560017, India; [email protected] (R.C.); [email protected] (A.K.); [email protected] (A.K.); [email protected] (A.G.); [email protected] (A.A.); [email protected] (R.B.); [email protected] (V.T.) * Correspondence: [email protected] † These authors contributed equally. Abstract: Technology to generate single cell RNA-sequencing (scRNA-seq) datasets and tools to annotate them have advanced rapidly in the past several years. Such tools generally rely on existing transcriptomic datasets or curated databases of cell type defining genes, while the application of scalable natural language processing (NLP) methods to enhance analysis workflows has not been Citation: Doddahonnaiah, D.; adequately explored. Here we deployed an NLP framework to objectively quantify associations Lenehan, P.J.; Hughes, T.K.; between a comprehensive set of over 20,000 human protein-coding genes and over 500 cell type Zemmour, D.; Garcia-Rivera, E.; terms across over 26 million biomedical documents. -
The Immunomodulatory CEA Cell Adhesion Molecule 6 (CEACAM6/Cd66c) Is a Candidate Receptor for the Influenza a Virus
bioRxiv preprint doi: https://doi.org/10.1101/104026; this version posted January 30, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 The immunomodulatory CEA cell adhesion molecule 6 (CEACAM6/CD66c) is a 2 candidate receptor for the influenza A virus 3 Shah Kamranur Rahmana *, Mairaj Ahmed Ansarib, Pratibha Gaurc, Imtiyaz Ahmada, 4 Chandrani Chakravartya,d, Dileep Kumar Vermaa, Sanjay Chhibbere, Naila Nehalf, 5 Shanmugaapriya Sellathanbyd, Dagmar Wirthc, Gulam Warisb and Sunil K. Lala,g # 6 7 Virology Group, International Centre for Genetic Engineering & Biotechnology, New Delhi, 8 Indiaa. 9 Department of Microbiology and Immunology, H. M. Bligh Cancer Research Laboratories, 10 Rosalind Franklin University of Medicine and Science, Chicago Medical School, North 11 Chicago, Illinois, USAb. 12 Helmholtz Centre for Infection Research, Braunschweig, Germanyc. 13 Department of Biomedical Science, Bharathidasan University, Trichy, Indiad. 14 Microbiology Department, Panjab University, Chandigarh, Indiae. 15 Career Institute of Medical & Dental Sciences and Hospital, Lucknow, Indiaf. 16 School of Science, Monash University, Selangor DE, Malaysiag. 17 18 Running Head: Protein receptor for Influenza A Virus 19 20 # Corresponding author: Professor of Microbiology, School of Science, Monash University, 21 47500 Bandar Sunway, Selangor DE, Malaysia. 22 Email: [email protected]; Telephone: (+603) 551 59606 23 24 * Current address: Department of Pathogen Molecular Biology, London School of Hygiene & 25 Tropical Medicine, Keppel Street, London WC1E 7HT, United Kingdom. 26 1 bioRxiv preprint doi: https://doi.org/10.1101/104026; this version posted January 30, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. -
MALE Protein Name Accession Number Molecular Weight CP1 CP2 H1 H2 PDAC1 PDAC2 CP Mean H Mean PDAC Mean T-Test PDAC Vs. H T-Test
MALE t-test t-test Accession Molecular H PDAC PDAC vs. PDAC vs. Protein Name Number Weight CP1 CP2 H1 H2 PDAC1 PDAC2 CP Mean Mean Mean H CP PDAC/H PDAC/CP - 22 kDa protein IPI00219910 22 kDa 7 5 4 8 1 0 6 6 1 0.1126 0.0456 0.1 0.1 - Cold agglutinin FS-1 L-chain (Fragment) IPI00827773 12 kDa 32 39 34 26 53 57 36 30 55 0.0309 0.0388 1.8 1.5 - HRV Fab 027-VL (Fragment) IPI00827643 12 kDa 4 6 0 0 0 0 5 0 0 - 0.0574 - 0.0 - REV25-2 (Fragment) IPI00816794 15 kDa 8 12 5 7 8 9 10 6 8 0.2225 0.3844 1.3 0.8 A1BG Alpha-1B-glycoprotein precursor IPI00022895 54 kDa 115 109 106 112 111 100 112 109 105 0.6497 0.4138 1.0 0.9 A2M Alpha-2-macroglobulin precursor IPI00478003 163 kDa 62 63 86 72 14 18 63 79 16 0.0120 0.0019 0.2 0.3 ABCB1 Multidrug resistance protein 1 IPI00027481 141 kDa 41 46 23 26 52 64 43 25 58 0.0355 0.1660 2.4 1.3 ABHD14B Isoform 1 of Abhydrolase domain-containing proteinIPI00063827 14B 22 kDa 19 15 19 17 15 9 17 18 12 0.2502 0.3306 0.7 0.7 ABP1 Isoform 1 of Amiloride-sensitive amine oxidase [copper-containing]IPI00020982 precursor85 kDa 1 5 8 8 0 0 3 8 0 0.0001 0.2445 0.0 0.0 ACAN aggrecan isoform 2 precursor IPI00027377 250 kDa 38 30 17 28 34 24 34 22 29 0.4877 0.5109 1.3 0.8 ACE Isoform Somatic-1 of Angiotensin-converting enzyme, somaticIPI00437751 isoform precursor150 kDa 48 34 67 56 28 38 41 61 33 0.0600 0.4301 0.5 0.8 ACE2 Isoform 1 of Angiotensin-converting enzyme 2 precursorIPI00465187 92 kDa 11 16 20 30 4 5 13 25 5 0.0557 0.0847 0.2 0.4 ACO1 Cytoplasmic aconitate hydratase IPI00008485 98 kDa 2 2 0 0 0 0 2 0 0 - 0.0081 - 0.0 -
Supplemental Text and Figures
Supplemental Materials and Methods Experimental bone metastasis assay Primary PCa cells were sorted by GFP marker from mTmG+ tumors, and 105 cells in 20μL PBS were injected using Hamilton syringe into the tibia of 6-week old NSG mice. Mice were monitored biweekly for moribund signs for euthanasia and organ harvest. Noninvasive mouse and ex vivo imaging MRI imaging with Bruker ICON and fluorescence imaging of fresh organs with metastasis enumeration were recently described (Lu et al. 2017). Primary prostate cell sphere formation assay Isolate of primary cells from prostate, culture and counting of prostatospheres on Matrigel were performed as described (Lukacs et al. 2010). For organoid culture assay, we followed a published matrigel embedding method (Chua et al. 2014). RNA-Seq and differential gene expression Total RNA was isolated from prostate tumors using Direct-zol RNA MiniPrep Kit (Zymo Research) and processed for stranded total RNA-Seq using Illumina HiSeq 4000 at Sequencing and Microarray Facility at MD Anderson Cancer Center. The differential expression analysis was performed using the DESeq2 package of R. P-values obtained after multiple binomial tests were adjusted using BH method. Significant genes are defined by using a cut-off of 0.05 on the BH corrected p-value and an absolute log2 fold change value of at least 1.5. Histology and western blot H&E stain, immunohistochemical (IHC) and western blot were performed as previously described (Ding et al. 2011; Wang et al. 2016). Primary antibodies for IHC include Ki67 (Fisher, RM-9106-S1), cleaved caspase 3 (Cell Signaling Technology aka CST, 9661), cyclin D1 (Fisher, clone SP4), TGFBR2 (Abcam, ab61213), BMPR2 (Abcam, ab130206), AR (EMD Millipore, 06-680), phospho- Akt (CST, 4060), GFP (CST, 2956), E-Cadherin (CST, 14472).