DOCSLIB.ORG

Target Identification of Natural Products by Activity Based Protein Profiling and a Whole Proteome Inventory of Background Photocrosslinker Binding

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

TECHNISCHE UNIVERSITÄT MÜNCHEN FAKULTÄT CHEMIE LEHRSTUHL FÜR ORGANISCHE CHEMIE II Target identification of natural products by activity based protein profiling and A whole proteome inventory of background photocrosslinker binding Wolfgang Heydenreuter Vollständiger Abdruck der von der Fakultät für Chemie der Technischen Universität München zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften (Dr. rer. nat) genehmigten Dissertation. Vorsitzender: Prof. Dr. Lukas Hintermann Prüfer der Dissertation: 1. Prof. Dr. Stephan A. Sieber 2. Prof. Dr. Tobias A.M. Gulder Die Dissertation wurde am 06.07.2016 bei der bei der Technischen Universität München eingereicht und durch die Fakultät für Chemie am 28.07.2016 angenommen. TECHNISCHE UNIVERSITÄT MÜNCHEN FAKULTÄT CHEMIE LEHRSTUHL FÜR ORGANISCHE CHEMIE II Target identification of natural products by activity based protein profiling and A whole proteome inventory of background photocrosslinker binding Vollständiger Abdruck zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften (Dr. rer. nat) Wolfgang Heydenreuter Meiner Familie gewidmet “Success is not final, failure is not fatalμ it is the courage to continue that counts.” ― Winston S. Churchill Danksagung Zu allererst möchte ich mich sehr herzlich bei Prof. Dr. Stephan A. Sieber für die Aufnahme in seinen Arbeitskreis bedanken. Für sein stetiges Vertrauen in meine Arbeit, die Aufgeschlossenheit gegenüber neuer Projekte und besonders für seine große Begeisterung für die Forschung und die mir gegebenen Freiheiten bei der Entwicklung eigener Projekte bin ich sehr dankbar. Bedanken möchte ich mich auch bei den Mitgliedern der Prüfungskommission für ihre Bemühungen bei der Bewertung dieser Arbeit. Die vielen Ergebnisse wären nie ohne die großartige Zusammenarbeit mit Kooperations- partnern sowohl in als auch außerhalb des Sieber-Labs entstanden. Ganz besonders möchte ich Simone Braig und ihren Mitarbeitern vom Lehrstuhl für Pharmazeutische Biologie der LMU für die ausgesprochen produktive Zusammenarbeit im Rahmen des Neocarzilin–Projektes bedanken. Meinen Laborkollegen Philipp Kleiner, Elena Kunhold, Matthias Stahl, Jan Vomacka, Megan Wright und Vadim Korotkov danke ich für die gemeinsame Arbeit an diversen Projekten im Zuge meiner Doktorarbeit. Mein großer Dank gilt ebenso Megan Wright und Matthias Stahl für ihre Bemühungen dieser Arbeit die Mäkel auszutreiben. Für ihre jahrelange Unterstützung im Laboralltag danke ich ganz besonders Mona Wolff und Katja Bäuml, die durch ihren unermüdlichen Einsatz stets eine produktive Arbeitsumgebung aufrechterhalten haben. Ferner möchte ich mich bei den unzähligen Praktikanten (Forschungspraktikum oder Bachelorarbeit) bedanken, die durch ihr stetiges Engagement viele, besonders synthetische Projekte, maßgeblich vorangetrieben haben. Es ist schön zu sehen, dass einige nun fester Bestandteil des Sieber-Labs geworden sind. Bei meinen Laborkollegen möchte ich mich für die großartige Zeit und deren Hilfsbereitschaft bedanken. Besonders erwähnen möchte ich hier Dr. Georg “Eure Dudeheit“ Rudolf für legendäre Kino- und Bouldersessions sowie philosophische Diskussionen über die emotionale Tiefe von Sharknado-Filmen, Dr. Jürgen “Fernet Branca“ Eirich für entspannte Golfsessions an der Isar und das Belächeln rheinischer Golfkünste, Dr. Maria “Marie“ Dahmen für die Präsentation dieser Künste und diverse Kletterhallenbesuche, Dr. Roman Kolb für das Vorleben von Sarkasmus und Zynismus in vollendeter Form, Volker “Rául von Schalke“ Kirsch und Christian “Fetzle“ Fetzer für exzellente Zockersessions und rege Diskussion über die Signifikanz bakterieller Proteasen. So isch lässig ! Des Weiteren danke ich Philipp Kleiner, Annabelle “Anni“ Hoegl, Johannes “Leeeman“ Lehmann, Mathias “Horst Seeler“ Hackl, Elena “Lenchen“ Kunhold, Dr. Franziska “Franjo“ Mandl, Dr. Max Koch, Dr. Megan Wright, Dr. Pavel Kielkowski, Barbara “Babsarella“ Hofbauer, Thomas “Elfmetergott“ Gronauer, Markus Lakemeyer, Matthias Stahl, Weining Zhao, Jan Vomacka, Dr. Nina Bach, Dóra Balogh, Dr. Joanna Krysiak, Dr. Malte Gersch, Dr. Matthew Nodwell, Dr. Johannes Kreuzer, Dr. Thomas Menzel, Dr. Vadim Korotkov und Dr. Tanja Wirth für die tolle Atmosphäre und die Unterstützung über all die Jahre. Der aktuellen Generation von Masterstudenten namentlich Johnny Drechsel, Ines Hübner und Anja Fux wünsche ich auf ihrem künftigen Weg alles Gute. Mein größter Dank gilt meinen Eltern, Gisela und Peter Heydenreuter, sowie meiner Schwester Christine für deren bedingungslose Unterstützung über all die Jahre. Auch möchte ich mich ganz besonders bei Isabel Buchsbaum für ihren liebvollen Rückhalt in den letzten drei Jahren bedanken. Ich kann mich glücklich schätzen, dass es euch gibt. ________________________________________________________________________________ Table of Contents Table of Contents I Introductory Remarks IV Summary V Zusammenfassung VI 1 Introduction 1 1.1 Activity based protein profiling (ABPP) 1 1.2 Electrophilic natural products and covalent inhibitors 5 1.3 Scope of this work 6 2 Target identification of falcarinol in human cancer cells 9 2.1 Polyynes and falcarinol 9 2.2 ALDH2 10 2.3 Results and discussion 12 2.3.1 Synthesis of activity-based probes 12 2.3.2 Total synthesis of falcarinol and stipudiol 13 2.3.3 Bioactivity in eukaryotic cells and bacteria 15 2.3.4 Protein reactivity in human cancer cells 16 2.4 Concluding remarks and outlook 22 3 A whole proteome inventory of background photocrosslinker binding 23 3.1 Photocrosslinkers 23 3.2 Results and discussion 26 3.2.1 Synthesis of minimal photoprobes 26 3.2.2 Protein reactivity in human cancer cells A549 and HeLa 27 3.2.3 Gel-free analysis of photocrosslinker-specific targets via quantitative proteomics 28 3.2.4 Diazirine-specific photome 30 3.2.5 Target analysis of the PKA inhibitor H8 as a proof-of-principle 34 3.3 Conclusion and outlook 38 4 Target identification of neocarzilin A-C in human cancer cells 39 4.1 Cancer as a challenge for mankind 39 4.1.1 Tumor migration 40 4.1.2 Neocarzilin 41 4.2 Results and discussion 41 4.2.1 Synthesis of an activity-based probe 41 4.2.2 Synthesis of neocarzilins A-C 42 4.2.3 Reactivity to proteins in human cancer cells 43 4.2.4 Quantitative proteomics 45 4.2.5 Target validation 47 4.2.5.1 Labeling of VAT-1 knockdown cells 47 4.2.5.2 Labeling of recombinant VAT-1 in E. coli 48 4.2.6 Function of VAT-1 48 4.2.7 Inhibition of migration and chemotaxis by neocarzilin A 49 4.2.8 Effects of neocarzilin A and C on cellular viability and apoptosis 50 I ________________________________________________________________________________ 4.2.9 Effect of neocarzilin A on mitochondria 52 4.2.10 Identification of potential interaction partners of VAT-1 by co- immunoprecipitation 54 4.3 Conclusion and outlook 57 5 Experimental Section 59 5.1 Organic Synthesis 59 5.1.1 General Methods and Materials 59 5.1.2 Synthetic procedures for chapter 2: Target identification of falcarinol in cancer cells. 60 5.1.3 Synthetic procedures for chapter 3: A whole proteome inventory of background photocrosslinker binding 78 5.1.4 Synthetic procedures for Chapter 4: Target identification of neocarzilin A-C in human cancer cells. 88 5.2 Biochemistry 98 5.2.1 General methods and materials 98 5.2.1.1 Cell culture 98 5.2.1.2 MTT- Assay 98 5.2.1.3 Labeling reagents 100 5.2.1.4 In situ labeling 100 5.2.1.5 Analytical gel based analysis 101 5.2.2 Biochemical procedures for Chapter 2: Target identification of falcarinol in cancer cells 101 5.2.2.1 Click reaction and preparative gel-free analysis 101 5.2.2.2 Preparative gel based analysis 102 5.2.2.3 Gel based target identification 104 5.2.2.4 Gel free target identification 105 5.2.2.5 Binding peptide identification 106 5.2.2.6 Binding site identification 106 5.2.2.7 Recombinant expression of target protein 107 5.2.2.8 PCR 107 5.2.2.9 Gateway cloning 108 5.2.2.10 ALDH2 in vitro-labeling 108 5.2.2.11 ALDH2 activity assay 109 5.2.3 Biochemical procedures for Chapter 3: A whole proteome inventory of background photocrosslinker binding 109 5.2.3.1 Analytical in situ AfBPP labelling 109 5.2.3.2 Preparative in situ labelling and quantification via SILAC 110 5.2.3.3 Mass spectrometry 111 5.2.3.4 Bioinformatics 112 5.2.4 Biochemical procedures for Chapter 4: Target identification of neocarzilin A- C in human cancer cells 114 5.2.4.1 Click reaction and preparative gel-free analysis 114 5.2.4.2 Preparative gel free analysis using label free quantification 114 5.2.4.3 Mass spectrometry 115 5.2.4.4 Recombinant expression of target protein 116 5.2.4.5 PCR 117 5.2.4.6 Gateway cloning 117 5.2.4.7 Recombinant expression and analytical labeling in E.coli 118 5.2.4.8 Co-Immunoprecipitation 119 6 Bibliography 121 7 List of abbreviations, acronyms and symbols 141 II ________________________________________________________________________________ 8 Appendices 144 8.1 Selected 1H and 13C NMR Spectra for Chapter 2 144 8.2 Selected 1H and 13C NMR Spectra for Chapter 4 149 9 Curriculum Vitae 154 III ________________________________________________________________________________ Introductory Remarks The present doctoral dissertation was accomplished between February 2012 and July 2016 under the supervision of Prof. Dr. Stephan A. Sieber at the Chair of Organic Chemistry II of the Technische Universität München. Parts of this thesis are based on the following publications and manuscripts in preparation for publication: Chapter 2: Heydenreuter, W., Kunold, E. & Sieber, S. A. Alkynol natural products target ALDH2 in cancer cells by irreversible binding to the active site. Chem. Commun. (Camb) 51, 15784-15787 (2015). Chapter 3: Kleiner, P., Heydenreuter, W., Stahl, M., Korotkov, V. S., Sieber, S. A. A whole proteome inventory of background photocrosslinker binding. Submitted to Angewandte Chemie. Chapter 4: Manuscript in preparation. All compounds mentioned in the theoretical part of this thesis are indexed consecutively with Arabic numerals in the format X.Y while X being the number of the project chapter and Y being in the order of appearance.
Recommended publications
  • The Purification and Identification of Interactors to Elucidate Novel Connections in the HEK 293 Cell Line

    The Purification and Identification of Interactors to Elucidate Novel Connections in the HEK 293 Cell Line

    The Purification and Identification of Interactors to Elucidate Novel Connections in the HEK 293 Cell Line Brett Hawley Biochemistry, Microbiology and Immunology Faculty of Medicine University of Ottawa © Brett Hawley, Ottawa, Canada, 2012 ABSTRACT The field of proteomics studies the structure and function of proteins in a large scale and high throughput manner. My work in the field of proteomics focuses on identifying interactions between proteins and discovering novel interactions. The identification of these interactions provides new information on metabolic and disease pathways and the working proteome of a cell. Cells are lysed and purified using antibody based affinity purification followed by digestion and identification using an HPLC coupled to a mass spectrometer. In my studies, I looked at the interaction networks of several AD related genes (Apolipoprotein E, Clusterin variant 1 and 2, Low-density lipoprotein receptor, Phosphatidylinositol binding clathrin assembly protein, Alpha- synuclein and Platelet-activating factor receptor) and an endosomal recycling pathway involved in cholesterol metabolism (Eps15 homology domain 1,2 and 4, Proprotein convertase subtilisin/kexin type 9 and Low-density lipoprotein receptor). Several novel and existing interactors were identified and these interactions were validated using co-immunopurification, which could be the basis for future research. ii ACKNOWLEDGEMENTS I would like to take this opportunity to thank my supervisor, Dr. Daniel Figeys, for his support and guidance throughout my studies in his lab. It was a great experience to work in his lab and I am very thankful I was given the chance to learn and work under him. I would also like to thank the members of my lab for all their assistance in learning new techniques and equipment in the lab.
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus

    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.
  • Dependent Traits in Mice Models of Hyperthyroidism and Hypothyroidism

    Dependent Traits in Mice Models of Hyperthyroidism and Hypothyroidism

    Phenotypical characterization of sex- dependent traits in mice models of hyperthyroidism and hypothyroidism Inaugural-Dissertation zur Erlangung des Doktorgrades Dr. rer. nat. der Fakultät für Biologie an der Universität Duisburg-Essen vorgelegt von Helena Rakov aus St. Petropawlowsk April 2017 Die der vorliegenden Arbeit zugrunde liegenden Experimente wurden am Universitätsklinikum Essen in der Klinik für Endokrinologie und Stoffwechselerkrankungen durchgeführt. 1. Gutachter: Prof. Dr. Dr. Dagmar Führer-Sakel 2. Gutachter: Prof. Dr. Elke Cario Vorsitzender des Prüfungsausschusses: Prof. Dr. Ruth Grümmer Tag der mündlichen Prüfung: 17.07.2017 Publications Publications Engels Kathrin*, Rakov Helena *, Zwanziger Denise, Moeller Lars C., Homuth Georg, Köhrle Josef, Brix Klaudia, Fuhrer Dagmar. Differences in mouse hepatic thyroid hormone transporter expression with age and hyperthyroidism. Eur Thyroid J 2015;4(suppl 1):81–86. DOI: 10.1159/000381020. *contributed equally Zwanziger Denise*, Rakov Helena*, Engels Kathrin, Moeller Lars C., Fuhrer Dagmar. Sex-dependent claudin-1 expression in liver of eu- and hypothyroid mice. Eur Thyroid J. 2015 Sep; 4(Suppl 1): 67–73. DOI: 10.1159/000431316. *contributed equally Engels Kathrin*, Rakov Helena*, Zwanziger Denise, Hoenes Georg Sebastian, Rehders Maren, Brix Klaudia, Koehrle Josef, Moeller Lars Christian, Fuhrer Dagmar. Efficacy of protocols for induction of chronic hyperthyroidism in male and female mice. Endocrine. 2016 Oct;54(1):47-54. DOI: 10.1007/s12020-016-1020-8. Rakov Helena*, Engels Kathrin*, Hönes Georg Sebastian, Strucksberg Karl-Heinz, Moeller Lars Christian, Köhrle Josef, Zwanziger Denise, Führer Dagmar. Sex-specific phenotypes of hyperthyroidism and hypothyroidism in mice. Biol Sex Differ. 2016 Aug 24;7(1):36. DOI: 10.1186/s13293-016-0089-3.
  • Anti-Inflammatory Role of Curcumin in LPS Treated A549 Cells at Global Proteome Level and on Mycobacterial Infection

    Anti-Inflammatory Role of Curcumin in LPS Treated A549 Cells at Global Proteome Level and on Mycobacterial Infection

    Anti-inflammatory Role of Curcumin in LPS Treated A549 cells at Global Proteome level and on Mycobacterial infection. Suchita Singh1,+, Rakesh Arya2,3,+, Rhishikesh R Bargaje1, Mrinal Kumar Das2,4, Subia Akram2, Hossain Md. Faruquee2,5, Rajendra Kumar Behera3, Ranjan Kumar Nanda2,*, Anurag Agrawal1 1Center of Excellence for Translational Research in Asthma and Lung Disease, CSIR- Institute of Genomics and Integrative Biology, New Delhi, 110025, India. 2Translational Health Group, International Centre for Genetic Engineering and Biotechnology, New Delhi, 110067, India. 3School of Life Sciences, Sambalpur University, Jyoti Vihar, Sambalpur, Orissa, 768019, India. 4Department of Respiratory Sciences, #211, Maurice Shock Building, University of Leicester, LE1 9HN 5Department of Biotechnology and Genetic Engineering, Islamic University, Kushtia- 7003, Bangladesh. +Contributed equally for this work. S-1 70 G1 S 60 G2/M 50 40 30 % of cells 20 10 0 CURI LPSI LPSCUR Figure S1: Effect of curcumin and/or LPS treatment on A549 cell viability A549 cells were treated with curcumin (10 µM) and/or LPS or 1 µg/ml for the indicated times and after fixation were stained with propidium iodide and Annexin V-FITC. The DNA contents were determined by flow cytometry to calculate percentage of cells present in each phase of the cell cycle (G1, S and G2/M) using Flowing analysis software. S-2 Figure S2: Total proteins identified in all the three experiments and their distribution betwee curcumin and/or LPS treated conditions. The proteins showing differential expressions (log2 fold change≥2) in these experiments were presented in the venn diagram and certain number of proteins are common in all three experiments.
  • Lung Proteomic Biomarkers Associated with Chronic Obstructive Pulmonary Disease

    Lung Proteomic Biomarkers Associated with Chronic Obstructive Pulmonary Disease

    medRxiv preprint doi: https://doi.org/10.1101/2021.04.07.21255030; this version posted April 10, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Lung proteomic biomarkers associated with chronic obstructive pulmonary disease Yu-Hang Zhang1, Michael R. Hoopmann2, Peter J. Castaldi1, Kirsten A. Simonsen2, Mukul K. Midha2, Michael H. Cho1, Gerard J. Criner3, Raphael Bueno4, Jiangyuan Liu1, Robert L. Moritz2*, Edwin K. Silverman1* 1Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA 2Institute for Systems Biology, Seattle, WA, USA 3Temple University School of Medicine, Philadelphia, PA, USA 4Division of Thoracic Surgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA * These senior authors contributed equally to this work Corresponding Authors: Edwin K. Silverman, Email: [email protected] Robert L. Moritz, Email: [email protected] Keywords: chronic obstructive pulmonary disease, proteomics, biomarkers, mass spectrometry, machine learning NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2021.04.07.21255030; this version posted April 10, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. ABSTRACT Background: Identifying protein biomarkers for chronic obstructive pulmonary disease (COPD) has been challenging.
  • Ventura County Plant Species of Local Concern

    Ventura County Plant Species of Local Concern

    Checklist of Ventura County Rare Plants (Twenty-second Edition) CNPS, Rare Plant Program David L. Magney Checklist of Ventura County Rare Plants1 By David L. Magney California Native Plant Society, Rare Plant Program, Locally Rare Project Updated 4 January 2017 Ventura County is located in southern California, USA, along the east edge of the Pacific Ocean. The coastal portion occurs along the south and southwestern quarter of the County. Ventura County is bounded by Santa Barbara County on the west, Kern County on the north, Los Angeles County on the east, and the Pacific Ocean generally on the south (Figure 1, General Location Map of Ventura County). Ventura County extends north to 34.9014ºN latitude at the northwest corner of the County. The County extends westward at Rincon Creek to 119.47991ºW longitude, and eastward to 118.63233ºW longitude at the west end of the San Fernando Valley just north of Chatsworth Reservoir. The mainland portion of the County reaches southward to 34.04567ºN latitude between Solromar and Sequit Point west of Malibu. When including Anacapa and San Nicolas Islands, the southernmost extent of the County occurs at 33.21ºN latitude and the westernmost extent at 119.58ºW longitude, on the south side and west sides of San Nicolas Island, respectively. Ventura County occupies 480,996 hectares [ha] (1,188,562 acres [ac]) or 4,810 square kilometers [sq. km] (1,857 sq. miles [mi]), which includes Anacapa and San Nicolas Islands. The mainland portion of the county is 474,852 ha (1,173,380 ac), or 4,748 sq.
  • Supplementary Table S4. FGA Co-Expressed Gene List in LUAD

    Supplementary Table S4. FGA Co-Expressed Gene List in LUAD

    Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase
  • Supplementary Material

    Supplementary Material

    BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Page 1 / 45 SUPPLEMENTARY MATERIAL Appendix A1: Neuropsychological protocol. Appendix A2: Description of the four cases at the transitional stage. Table A1: Clinical status and center proportion in each batch. Table A2: Complete output from EdgeR. Table A3: List of the putative target genes. Table A4: Complete output from DIANA-miRPath v.3. Table A5: Comparison of studies investigating miRNAs from brain samples. Figure A1: Stratified nested cross-validation. Figure A2: Expression heatmap of miRNA signature. Figure A3: Bootstrapped ROC AUC scores. Figure A4: ROC AUC scores with 100 different fold splits. Figure A5: Presymptomatic subjects probability scores. Figure A6: Heatmap of the level of enrichment in KEGG pathways. Kmetzsch V, et al. J Neurol Neurosurg Psychiatry 2021; 92:485–493. doi: 10.1136/jnnp-2020-324647 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Appendix A1. Neuropsychological protocol The PREV-DEMALS cognitive evaluation included standardized neuropsychological tests to investigate all cognitive domains, and in particular frontal lobe functions. The scores were provided previously (Bertrand et al., 2018). Briefly, global cognitive efficiency was evaluated by means of Mini-Mental State Examination (MMSE) and Mattis Dementia Rating Scale (MDRS). Frontal executive functions were assessed with Frontal Assessment Battery (FAB), forward and backward digit spans, Trail Making Test part A and B (TMT-A and TMT-B), Wisconsin Card Sorting Test (WCST), and Symbol-Digit Modalities test.
  • Identification of Potential Key Genes and Pathway Linked with Sporadic Creutzfeldt-Jakob Disease Based on Integrated Bioinformatics Analyses

    Identification of Potential Key Genes and Pathway Linked with Sporadic Creutzfeldt-Jakob Disease Based on Integrated Bioinformatics Analyses

    medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Identification of potential key genes and pathway linked with sporadic Creutzfeldt-Jakob disease based on integrated bioinformatics analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Abstract Sporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened.
  • Regulator of G Protein Signaling 2 Mediates Cardiac Compensation to Pressure Overload and Antihypertrophic Effects of PDE5 Inhibition in Mice

    Regulator of G Protein Signaling 2 Mediates Cardiac Compensation to Pressure Overload and Antihypertrophic Effects of PDE5 Inhibition in Mice

    Regulator of G protein signaling 2 mediates cardiac compensation to pressure overload and antihypertrophic effects of PDE5 inhibition in mice Eiki Takimoto, … , Michael E. Mendelsohn, David A. Kass J Clin Invest. 2009;119(2):408-420. https://doi.org/10.1172/JCI35620. Research Article Cardiology The heart initially compensates for hypertension-mediated pressure overload by enhancing its contractile force and developing hypertrophy without dilation. Gq protein–coupled receptor pathways become activated and can depress function, leading to cardiac failure. Initial adaptation mechanisms to reduce cardiac damage during such stimulation remain largely unknown. Here we have shown that this initial adaptation requires regulator of G protein signaling 2 (RGS2). Mice lacking RGS2 had a normal basal cardiac phenotype, yet responded rapidly to pressure overload, with increased myocardial Gq signaling, marked cardiac hypertrophy and failure, and early mortality. Swimming exercise, which is not accompanied by Gq activation, induced a normal cardiac response, while Rgs2 deletion in Gαq- overexpressing hearts exacerbated hypertrophy and dilation. In vascular smooth muscle, RGS2 is activated by cGMP- –/– dependent protein kinase (PKG), suppressing Gq-stimulated vascular contraction. In normal mice, but not Rgs2 mice, PKG activation by the chronic inhibition of cGMP-selective phosphodiesterase 5 (PDE5) suppressed maladaptive cardiac hypertrophy, inhibiting Gq-coupled stimuli. Importantly, PKG was similarly activated by PDE5 inhibition in myocardium from both genotypes, but PKG plasma membrane translocation was more transient in Rgs2–/– myocytes than in controls and was unaffected by PDE5 inhibition. Thus, RGS2 is required for early myocardial compensation to pressure overload and mediates the initial antihypertrophic and cardioprotective effects of PDE5 inhibitors.
  • Early Growth Response 1 Regulates Hematopoietic Support and Proliferation in Human Primary Bone Marrow Stromal Cells

    Early Growth Response 1 Regulates Hematopoietic Support and Proliferation in Human Primary Bone Marrow Stromal Cells

    Hematopoiesis SUPPLEMENTARY APPENDIX Early growth response 1 regulates hematopoietic support and proliferation in human primary bone marrow stromal cells Hongzhe Li, 1,2 Hooi-Ching Lim, 1,2 Dimitra Zacharaki, 1,2 Xiaojie Xian, 2,3 Keane J.G. Kenswil, 4 Sandro Bräunig, 1,2 Marc H.G.P. Raaijmakers, 4 Niels-Bjarne Woods, 2,3 Jenny Hansson, 1,2 and Stefan Scheding 1,2,5 1Division of Molecular Hematology, Department of Laboratory Medicine, Lund University, Lund, Sweden; 2Lund Stem Cell Center, Depart - ment of Laboratory Medicine, Lund University, Lund, Sweden; 3Division of Molecular Medicine and Gene Therapy, Department of Labora - tory Medicine, Lund University, Lund, Sweden; 4Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands and 5Department of Hematology, Skåne University Hospital Lund, Skåne, Sweden ©2020 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol. 2019.216648 Received: January 14, 2019. Accepted: July 19, 2019. Pre-published: August 1, 2019. Correspondence: STEFAN SCHEDING - [email protected] Li et al.: Supplemental data 1. Supplemental Materials and Methods BM-MNC isolation Bone marrow mononuclear cells (BM-MNC) from BM aspiration samples were isolated by density gradient centrifugation (LSM 1077 Lymphocyte, PAA, Pasching, Austria) either with or without prior incubation with RosetteSep Human Mesenchymal Stem Cell Enrichment Cocktail (STEMCELL Technologies, Vancouver, Canada) for lineage depletion (CD3, CD14, CD19, CD38, CD66b, glycophorin A). BM-MNCs from fetal long bones and adult hip bones were isolated as reported previously 1 by gently crushing bones (femora, tibiae, fibulae, humeri, radii and ulna) in PBS+0.5% FCS subsequent passing of the cell suspension through a 40-µm filter.
  • Role of GSH and Iron-Sulfur Glutaredoxins in Iron Metabolism—Review

    Role of GSH and Iron-Sulfur Glutaredoxins in Iron Metabolism—Review

    molecules Review Role of GSH and Iron-Sulfur Glutaredoxins in Iron Metabolism—Review 1, 1, 1 1 Trnka Daniel y , Hossain Md Faruq y , Jordt Laura Magdalena , Gellert Manuela and Lillig Christopher Horst 2,* 1 Institute for Medical Biochemistry and Molecular Biology, University Medicine, University of Greifswald, 17475 Greifswald, Germany; [email protected] (T.D.); [email protected] (H.M.F.); [email protected] (J.L.M.); [email protected] (G.M.) 2 Christopher Horst Lillig, Institute for Medical Biochemistry and Molecular Biology, University Medicine Greifswald, Ferdinand-Sauerbruch-Straße, 17475 Greifswald, Germany * Correspondence: [email protected]; Tel.: +49-3834-865407; Fax: +49-3834-865402 These authors contributed equally to this work. y Academic Editor: Pál Perjési Received: 29 July 2020; Accepted: 22 August 2020; Published: 25 August 2020 Abstract: Glutathione (GSH) was initially identified and characterized for its redox properties and later for its contributions to detoxification reactions. Over the past decade, however, the essential contributions of glutathione to cellular iron metabolism have come more and more into focus. GSH is indispensable in mitochondrial iron-sulfur (FeS) cluster biosynthesis, primarily by co-ligating FeS clusters as a cofactor of the CGFS-type (class II) glutaredoxins (Grxs). GSH is required for the export of the yet to be defined FeS precursor from the mitochondria to the cytosol. In the cytosol, it is an essential cofactor, again of the multi-domain CGFS-type Grxs, master players in cellular iron and FeS trafficking. In this review, we summarize the recent advances and progress in this field. The most urgent open questions are discussed, such as the role of GSH in the export of FeS precursors from mitochondria, the physiological roles of the CGFS-type Grx interactions with BolA-like proteins and the cluster transfer between Grxs and recipient proteins.