DOCSLIB.ORG

Supp Material.Pdf

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Supp Material.Pdf Supplemental Material STRESS-INDUCED H3S28 PHOSPHORYLATION MODULATES LOCAL HISTONE ACETYLATION LEVELS Anna Sawicka, Dominik Hartl, Malgorzata Goiser, Oliver Pusch, Roman R Stocsits, Ido M Tamir, Karl Mechtler, Christian Seiser Supplemental Methods Supplemental Figure Legends Supplemental Tables (SUPPL. TABLES 1-2, 4-5) Supplemental Tables (SUPPL. TABLES 3, 6-9, provided as txt files) References Supplemental Figures (SUPPL. FIGURES 1-21) Supplemental Methods Histone peptides used for the pull-down assay and mass spectrometry analysis: H3unmodified (3-20): H2N-TKQTARKSTGGKAPRKQLC-CONH2 H3S10phK14ac (3-20): H2N-TKQTARKS(ph)TGGK(Ac)APRKQLC -CONH2 H3unmodified (19-36): H2N-QLATKAARKSAPATGGVKKC-CONH2 H3S28ph (19-36): H2N-QLATKAARKS(ph)APATGGVKKC-CONH2 Histone peptide pull-down assay For histone peptide pull down assays, 0.1 mg of synthetic peptides (peptide sequences are given above), corresponding to amino acids 3-20 and 19-36 of histone H3 (numbered from N-terminus of histone H3) with a C-terminal cysteine added were coupled to 40 µl (bed volume) of SulfoLink Coupling Resin (Thermo Scientific) according to the manufacturerʼs instructions. Peptide-coupled resin was incubated overnight at 4oC on a roller with 500 µg of nuclear extract (isolated from proliferating HeLa cells treated with 188.5 nM Anisomycin for 1 hour) diluted to 0.5 µg/µl in the binding buffer (20 mM Tris-HCl pH 8.0, 135 mM NaCl, 0.5% NP40, 10% glycerol). The beads were washed 3 times 20 mM Tris-HCl pH 8.0, 135 mM NaCl, 0.5% NP40, 10% glycerol, followed by two washes with 200 mM NaCl, 50 mM Tris-HCl pH 8.0, 0.1 % SDS, 0.1% NP40, 0.5% sodium deoxycholate. Bound proteins were eluted by heating at 95oC for 5 min in 20 µl of Laemmli Sample Buffer and analyzed by Western Blotting. All washing buffers as well as the binding buffer were supplemented with Complete Protease Inhibitor (Roche). Mass spectrometry analysis Histone pull down assay was performed as described above with the following changes: 1 mg of nuclear extract from HeLa cells treated for 1 h with 188.5 nM 2 anisomycin was used, together with 0.4 mg of synthetic peptides and 200 µl (bed volume) of SulfoLink Coupling Resin. Following 2 washes with 200 mM NaCl, 50 mM Tris-HCl pH 8.0, 0.1% SDS, 0.1% NP40, 0.5% sodium deoxycholate, the samples were washed 5 times with 20 mM Tris-HCl pH 8.0, 135 mM NaCl, 10% glycerol (without protease inhibitors) and 2 times with 150 mM NaCl. The samples were washed 3 times with 25 mM ammonium bicarbonate (ABC) and then resuspended in 30 µl of ABC, supplemented with 200 ng of LysC and incubated at 37oC for 4 h. The LysC fraction was taken out and the beads were resuspended in 30 µl of 100 mM glycine, pH 2.0. The glycine elution was repeated twice and all three elutions were pooled. Then both fractions, LysC and glycine fraction were subjected to alkylation and reduction followed by tryptic digestion with 200 ng of trypsin in 37oC overnight. The digest was terminated by adding 10 µl of 10% TFA. 50% of each fraction was pooled and run for 3 h on the Ultimate 3000 HPLC RSLC nano system (Thermo Scientific) coupled to Q Exactive mass spectrometer with Proxeon nanospray source. For peptide identification, the .RAW-files were loaded into Proteome Discoverer (version 1.4.0.288, Thermo Scientific) and MS/MS spectra were searched using Mascot 2.2.07 (Matrix Science) against the human Uniprot database with the FDR cutoff of 0.5% at PSM (peptide spectrum matches) level and minimum 2 peptides per protein. The complete list of identified proteins is contained in Supplemental Tables 7-9: Supplemental Table 7 contains the list of identified proteins and number of unique peptides, Supplemental Table 8 contains the coverage details and Supplemental Table 9 contains the PMS information. Primers used for quantitation of gene expression: mRNA_Rpl13a_F: GGAGAAACGGAAGGAAAAGG mRNA_Rpl13a_R: ACAGGAGCAGTGCCTAAGGA mRNA_Dusp1_F: CTCCAAGGAGGATATGAAGCG (Auger-Messier et al. 2013) mRNA_Dusp1_R: CTCCAGCATCCTTGATGGAGTC 3 mRNA_Optn_F: GTGGCCGGACCTGTTACC mRNA_Optn_R: CAAACAACAGGCGCTCTTCC mRNA_Ube2v2_F: TATTGGGCCACCAAGGACAAA mRNA_Ube2v2_R: TGATGGAGGAGCTTCTGGGTA mRNA_Mafk_F: GAAGCGCTTGTGAAGAGTGC mRNA_Mafk_R: CCTTCAATGCCTTGTTGGGC mRNA_Traf1_F: CACCAATGTCACCAAGC mRNA_Traf1_R: CAGGAGAGCATCGTATTC mRNA_Nfil3_F: TTTCTTTTCCCCCTCACGGA mRNA_Nfil3_R: CCTCGTCCTACAGACCGGAT mRNA_Ell_F: GGAGTTACGGGTTGTCGTGT mRNA_Ell_R: AGAGATGTGCCCTTGGCTTC mRNA_Tank_F: TTGACCCTTGATGAACCACA mRNA_Tank_R: ATCCCTTTCGTGATGCAGAG mRNA_Egr3_F: GGTGACCATGAGCAGTTTGC mRNA_Egr3_R: TCCATCACATTCTCTGTAGCCA mRNA_Fos_F: ATCTGTCCGTCTCTAGTG mRNA_Fos_R: GCTTGGAGTGTATCTGTC Adapters and primers used for scRNA-seq: 3ʼadaptor_PE: 5ʻ-/5Phos/rArGrATCGGAAGAGCGGTTCAGC/3ddC/ -3ʻ 5ʼadaptor_PE: 5ʻrArCrArCrUrCrUrUrUrCrCrCrUrArCrArCrGrArCrGrCr UrCrUrUrCrCrGrArUrCrU-3ʻ RT_Primer_PE (primer for reverse transcription): 5ʻ- TCTCGGCATTCCTGCTGAACCGCTCTTCCGATCT -3ʻ Library amplification primers: PE_PCR_Primer_1.0 (forward primer): 5ʻ-AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACG ACGCTCTTCCGATCT-3ʼ PE_PCR_Primer_2.0 (reversed primer): 5ʻ-CAAGCAGAAGACGGCATACGAGATCGGTCTCGGCATTCCTGC TGAACCGCTCTTCCGATCT-3ʼ Antibodies used for Western Blotting and dot blots: H3S28ph (Sigma, cat number H9908), dilution 1:1000 H3S10ph (Santa Cruz Biotechnology, cat number 8656R), dilution 1:5000 H3S10ph (Active Motif, cat number 39253), dilution 1:5000 Anti-histone H3 C-terminus (Abcam, cat number 1791), dilution 1:50000 Lamin A/C (clone 4C11, Active Motif, cat number 39287), dilution 1:500 MSK1 (Sigma, cat number M5437), dilution 1:2000 MSK2 (Bethyl, cat number A302-746A), dilution 1:2000 RNAPIIS5ph (Bethyl, cat number A300-655A), dilution 1:5000 RNAPIIS2ph (Bethyl, cat number A300-654A), dilution 1:5000 4 β-Actin (Sigma, cat number A5316), dilution 1:20000 HDAC1 (10E, Seiser Lab, available at Millipore cat number 06-720), dilution 1:500 HDAC2 (3F3, Seiser Lab, available at Millipore cat number 05-814), dilution 1:1000 14-3-3zeta (Santa Cruz Biotechnology, cat number sc-1019), dilution 1:1000 mSin3A (AK-11) (Santa Cruz Biotechnology, cat number sc-767), dilution 1:500 MTA1 (C-17) (Santa Cruz Biotechnology, cat number sc-9446), dilution 1:500 Antibodies used for chromatin immunoprecipitation: H3S28ph (Sigma, cat number H9908), 4 µg of antibody, 100 µg of chromatin RNAPIIS5ph (Bethyl, cat number A300-655A), 4 µl of antibody, 25 µg of chromatin RNAPIIS2ph (Bethyl, cat number A300-654A), 4 µl of antibody, 25 µg of chromatin H3S10ph (Santa Cruz Biotechnology, cat number 8656R), 4 µg of antibody, 50 µg of chromatin H3S10ph (Seiser Lab), 10 µl of serum, 50 µg of chromatin H3S10phK14ac (Seiser Lab), 10 µl of serum, 100 µg of chromatin H3K9ac (Millipore, cat number 06-942), 4 µg of antibody, 25 µg of chromatin H3K4me3 (Millipore, cat number 07-473), 4 µg of antibody, 25 µg of chromatin H3K27ac (Abcam, cat number ab4729), 4 µg of antibody, 25 µg of chromatin H4ac (Millipore, cat number 06-866), 4 µl of serum, 25 µg of chromatin Histone H3 (Active Motif, cat number 61475), 4 µg of antibody, 25 µg of chromatin p300 C-20 (Santa Cruz Biotechnology, cat number sc-585), 4 µg of antibody, 50 µg of chromatin PCAF H-369 (Santa Cruz Biotechnology, cat number sc-8999), 4 µg of antibody, 50 µg of chromatin Gcn5 H-75 (Santa Cruz Biotechnology, cat number sc-20698), 4 µg of antibody, 50 µg of chromatin mSin3A (K-20) (Santa Cruz Biotechnology, cat number sc-994X), 4 µg of antibody, 25 µg of chromatin HDAC1 (Abcam, cat number ab7028), 4 µg of antibody, 25 µg of chromatin HDAC2 (Bethyl, cat number A300-705A), 4 µl of antibody, 25 µg of chromatin Primers used for ChIP-qPCR: Dusp1(+108)_F: GACTTAGGGCCACAGGACAC Dusp1(+108)_R: AAGAAGGAGCGACAATCCAA Dusp1_+2517_F: TGTTTGAGGCAGTTTCTTCG Dusp1_+2517_R: TGAGGTATTTGGTTCTTCTATGAG Optn(-170)_F: TCCAAGAGAGGCTCTATCCCTA Optn(-170)_R: CCAAGAAATTTCCCAGACCA Optn(+42126)_F: GCCCAGCACAGCAGTACTTT Optn(+42126)_R: CCGGTGAGGCTATAAACCAA Ube2v2(-234)_F: TTCCCTTGGACACACTGACA Ube2v2(-234)_R: GTTGGTTCATCGGTTGTCCT Ube2v2(+38949)_F: GCAGGCGATTACAAGTTCCT Ube2v2(+38948)_R: CGGTGTCACAACAAGTGCTC Fosl1(+123)_F: CCCCCGTGGTGCAAGTGGTT (Drobic et al. 2010) Fosl1(+123)_R: TGGCGGCTGCGGTTCTGACT Fosl1(-962)_F: TCACCAGACTCAGCCACTTAC (Drobic et al. 2010) Fosl1(-962)_R: GCCATCATAACCCCCACT Mafk(+581)_F: GCCAAGGTCCCATCCAACTCTG Mafk(+581)_R: TGATTTCTCGCCGCACGCTC 5 Mafk(+9671)_F: GGGGTTCTCTGGGGCTTAG Mafk(+9671)_R: CCTGTCTACTTCGTTCCTGTTC Traf1(+2630)_F: GGTGCTGCCTCATTCTTACC Traf1(+2630)_R: ACTTGCTCCTGCGATCCTTA Traf1(+13803)_F: CCCCAGTATCCAGTGCAAAT Traf1(+13803)_R: ACAGGGAAGACACGGTTTTG Nfil3(+500)_F: CCGGATTTCAGGAAAATTGA Nfil3(+500)_R: GACTCAACCCTCCCCTTAGC Nfil3(+13547)_F: TCAAGAGATTCATAGCCACACAAC Nfil3(+13547)_R: ACACAAGGACACCCAGACAG Tank(+1023)_F: CCTTCTTGCGAAAAGCCATA Tank(+1023)_R: AACGTGAGTAGGCGCCTTTA Tank(+56840)_F: GTCAAGTTTCCGCCTATGG Tank(+56840)_R: AAAGTTTCCTGGGTTGTCTC Ell(+96)_F: AGGGTGTCGGTGTTC Ell(+96)_R: AGGTATCGCCAGGTG Ell(+38299)_F: TTGTTGAGTTTGAGTTCTGGGTAGG Ell(+38299)_R: GGGTCTTTGTGTAGTCTTGTCTGTC Detailed description of computational analysis Unless specified otherwise, the analysis was performed using Mac OS X system version 10.6.8, R version 3.0.1 (R Development Core Team 2014) and Bioconductor version 2.12 (Gentleman et al. 2004). We used Mus musculus genome annotation from July 2007 (NCBI37/mm9) throughout all our analysis. Mapping of short reads Mapping of the short reads was performed by the CSF NGS unit. In the case of ChIP- seq experiments, following the quality control, short reads were mapped to the mouse genome using Bowtie version 12.5 (Langmead et al. 2009), allowing up to two mismatches and retaining reads
Load more

Recommended publications
  • Expression and Prognostic Role of IKBKE and TBK1 in Stage I Non-Small Cell Lung Cancer
    Cancer Management and Research Dovepress open access to scientific and medical research Open Access Full Text Article ORIGINAL RESEARCH Expression and prognostic role of IKBKE and TBK1 in stage I non-small cell lung cancer This article was published in the following Dove Press journal: Cancer Management and Research Xin Wang1,2 Background: The inhibitors of nuclear factor kappa-B kinase subunit epsilon (IKBKE) and Feifei Teng2 TANK-binding kinase 1 (TBK1) are important members of the nonclassical IKK family that Jie Lu3 share the kinase domain. They are important oncogenes for activation of several signaling Dianbin Mu4 pathways in several tumors. This study aims to explore the expression of IKBKE and TBK1 Jianbo Zhang4 and their prognostic role in stage I non-small cell lung cancer (NSCLC). Jinming Yu1,2 Patients and methods: A total of 142 surgically resected stage I NSCLC patients were enrolled and immunohistochemistry of IKBKE and TBK1 was performed. 1 Department of Oncology, Renmin Results: IKBKE and TBK1 were expressed in 121 (85.2%) and 114 (80.3%) of stage I Hospital of Wuhan University, Wuhan, fi Hubei 430060, People’s Republic of China; NSCLC patients respectively. IKBKE expression was signi cantly associated with TBK1 2Department of Radiation Oncology, expression (P=0.004). Furthermore, multivariate regression analyses showed there was a fi Shandong Cancer Hospital Af liated to significant relationship between patients with risk factors, the recurrence pattern of metas- Shandong University, Shandong Academy of Medical Sciences, Jinan, Shandong tasis and IKBKE+/TBK1+ co-expression (P=0.032 and P=0.022, respectively). In Kaplan– 250117, People’s Republic of China; Meier survival curve analyses, the IKBKE+/TBK1+ co-expression subgroup was signifi- 3Department of Neurosurgery, Shandong Province Qianfoshan Hospital of Shandong cantly associated with poor overall survival (P=0.014).
    [Show full text]
  • Workflows for Rapid Functional Annotation of Diverse
    insects Article Workflows for Rapid Functional Annotation of Diverse Arthropod Genomes Surya Saha 1,2 , Amanda M. Cooksey 2,3, Anna K. Childers 4 , Monica F. Poelchau 5 and Fiona M. McCarthy 2,* 1 Boyce Thompson Institute, 533 Tower Rd., Ithaca, NY 14853, USA; [email protected] 2 School of Animal and Comparative Biomedical Sciences, University of Arizona, 1117 E. Lowell St., Tucson, AZ 85721, USA; [email protected] 3 CyVerse, BioScience Research Laboratories, University of Arizona, 1230 N. Cherry Ave., Tucson, AZ 85721, USA 4 Bee Research Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, USDA, 10300 Baltimore Ave., Beltsville, MD 20705, USA; [email protected] 5 National Agricultural Library, Agricultural Research Service, USDA, 10301 Baltimore Ave., Beltsville, MD 20705, USA; [email protected] * Correspondence: fi[email protected] Simple Summary: Genomic technologies are accumulating information about genes faster than ever before, and sequencing initiatives, such as the Earth BioGenome Project, i5k, and Ag100Pest Initiative, are expected to increase this rate of acquisition. However, if genomic sequencing is to be used for the improvement of human health, agriculture, and our understanding of biological systems, it is necessary to identify genes and understand how they contribute to biological outcomes. While there are several well-established workflows for assembling genomic sequences and identifying genes, understanding gene function is essential to create actionable knowledge. Moreover, this functional annotation process must be easily accessible and provide information at a genomic scale to keep up Citation: Saha, S.; Cooksey, A.M.; with new sequence data. We report a well-defined workflow for rapid functional annotation of whole Childers, A.K.; Poelchau, M.F.; proteomes to produce Gene Ontology and pathways information.
    [Show full text]
  • Molecular Basis of Tank-Binding Kinase 1 Activation by Transautophosphorylation
    Molecular basis of Tank-binding kinase 1 activation by transautophosphorylation Xiaolei Maa,1, Elizabeth Helgasonb,1, Qui T. Phungc, Clifford L. Quanb, Rekha S. Iyera, Michelle W. Leec, Krista K. Bowmana, Melissa A. Starovasnika, and Erin C. Dueberb,2 Departments of aStructural Biology, bEarly Discovery Biochemistry, and cProtein Chemistry, Genentech, South San Francisco, CA 94080 Edited by Tony Hunter, Salk Institute for Biological Studies, La Jolla, CA, and approved April 25, 2012 (received for review December 30, 2011) Tank-binding kinase (TBK)1 plays a central role in innate immunity: it the C-terminal scaffolding/dimerization domain (SDD), a do- serves as an integrator of multiple signals induced by receptor- main arrangement that appears to be shared among the IKK mediated pathogen detection and as a modulator of IFN levels. family of kinases (3). Deletion or mutation of the ULD in TBK1 Efforts to better understand the biology of this key immunological or IKKε severely impairs kinase activation and substrate phos- factor have intensified recently as growing evidence implicates phorylation in cells (22, 23). Furthermore, the integrity of the aberrant TBK1 activity in a variety of autoimmune diseases and ULD in IKKβ is not only required for kinase activity (24) but was fi cancers. Nevertheless, key molecular details of TBK1 regulation and shown also to confer substrate speci city in conjunction with the β substrate selection remain unanswered. Here, structures of phos- adjacent SDD (25). Recent crystal structures of the IKK phorylated and unphosphorylated human TBK1 kinase and ubiq- homodimer demonstrate that the ULD and SDD form a joint, uitin-like domains, combined with biochemical studies, indicate three-way interface with the KD within each protomer of the a molecular mechanism of activation via transautophosphorylation.
    [Show full text]
  • Downloaded As a CSV Dump file
    cells Article Transcriptome and Methylome Analysis Reveal Complex Cross-Talks between Thyroid Hormone and Glucocorticoid Signaling at Xenopus Metamorphosis Nicolas Buisine 1,† , Alexis Grimaldi 1,†, Vincent Jonchere 1,† , Muriel Rigolet 1, Corinne Blugeon 2 , Juliette Hamroune 2 and Laurent Marc Sachs 1,* 1 UMR7221 Molecular Physiology and Adaption, CNRS, Museum National d’Histoire Naturelle, 57 Rue Cuvier, CEDEX 05, 75231 Paris, France; [email protected] (N.B.); [email protected] (A.G.); [email protected] (V.J.); [email protected] (M.R.) 2 Genomics Core Facility, Département de Biologie, Institut de Biologie de l’ENS (IBENS), École Normale Supérieure, CNRS, INSERM, Université PSL, 75005 Paris, France; [email protected] (C.B.); [email protected] (J.H.) * Correspondence: [email protected] † Co-first authors, alphabetic order. Abstract: Background: Most work in endocrinology focus on the action of a single hormone, and very little on the cross-talks between two hormones. Here we characterize the nature of interactions between thyroid hormone and glucocorticoid signaling during Xenopus tropicalis metamorphosis. Methods: We used functional genomics to derive genome wide profiles of methylated DNA and measured changes of gene expression after hormonal treatments of a highly responsive tissue, tailfin. Clustering classified the data into four types of biological responses, and biological networks were Citation: Buisine, N.; Grimaldi, A.; modeled by system biology. Results: We found that gene expression is mostly regulated by either Jonchere, V.; Rigolet, M.; Blugeon, C.; T or CORT, or their additive effect when they both regulate the same genes. A small but non- Hamroune, J.; Sachs, L.M.
    [Show full text]
  • Mechanisms of IKBKE Activation in Cancer Sridevi Challa University of South Florida, [email protected]
    University of South Florida Scholar Commons Graduate Theses and Dissertations Graduate School 1-29-2017 Mechanisms of IKBKE Activation in Cancer Sridevi Challa University of South Florida, [email protected] Follow this and additional works at: http://scholarcommons.usf.edu/etd Part of the Biochemistry Commons, Biology Commons, and the Cell Biology Commons Scholar Commons Citation Challa, Sridevi, "Mechanisms of IKBKE Activation in Cancer" (2017). Graduate Theses and Dissertations. http://scholarcommons.usf.edu/etd/6617 This Dissertation is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. Mechanisms of IKBKE Activation in Cancer by Sridevi Challa A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Cell Biology, Microbiology, and Molecular Biology College of Arts and Sciences University of South Florida Major Professor: Mokenge P. Malafa, M.D. Gary Reuther, Ph.D. Eric Lau, Ph.D. Domenico Coppola, M.D. Date of Approval: January 12, 2017 Keywords: EGFR, Olaparib, resistance Copyright © 2017, Sridevi Challa DEDICATION This dissertation is dedicated to my kind and courageous mother. ACKNOWLEDGMENTS I would like to acknowledge Dr. Cheng for trusting me with completion of the projects. I would like to thank him for giving me the freedom to explore any aspect of research and always willing to provide the necessary resources and guidance for my projects. I want to also acknowledge Ted and the Cheng lab personnel for their support.
    [Show full text]
  • The Human Gene Connectome As a Map of Short Cuts for Morbid Allele Discovery
    The human gene connectome as a map of short cuts for morbid allele discovery Yuval Itana,1, Shen-Ying Zhanga,b, Guillaume Vogta,b, Avinash Abhyankara, Melina Hermana, Patrick Nitschkec, Dror Friedd, Lluis Quintana-Murcie, Laurent Abela,b, and Jean-Laurent Casanovaa,b,f aSt. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY 10065; bLaboratory of Human Genetics of Infectious Diseases, Necker Branch, Paris Descartes University, Institut National de la Santé et de la Recherche Médicale U980, Necker Medical School, 75015 Paris, France; cPlateforme Bioinformatique, Université Paris Descartes, 75116 Paris, France; dDepartment of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; eUnit of Human Evolutionary Genetics, Centre National de la Recherche Scientifique, Unité de Recherche Associée 3012, Institut Pasteur, F-75015 Paris, France; and fPediatric Immunology-Hematology Unit, Necker Hospital for Sick Children, 75015 Paris, France Edited* by Bruce Beutler, University of Texas Southwestern Medical Center, Dallas, TX, and approved February 15, 2013 (received for review October 19, 2012) High-throughput genomic data reveal thousands of gene variants to detect a single mutated gene, with the other polymorphic genes per patient, and it is often difficult to determine which of these being of less interest. This goes some way to explaining why, variants underlies disease in a given individual. However, at the despite the abundance of NGS data, the discovery of disease- population level, there may be some degree of phenotypic homo- causing alleles from such data remains somewhat limited. geneity, with alterations of specific physiological pathways under- We developed the human gene connectome (HGC) to over- come this problem.
    [Show full text]
  • UC San Diego Electronic Theses and Dissertations
    UC San Diego UC San Diego Electronic Theses and Dissertations Title Cardiac Stretch-Induced Transcriptomic Changes are Axis-Dependent Permalink https://escholarship.org/uc/item/7m04f0b0 Author Buchholz, Kyle Stephen Publication Date 2016 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, SAN DIEGO Cardiac Stretch-Induced Transcriptomic Changes are Axis-Dependent A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioengineering by Kyle Stephen Buchholz Committee in Charge: Professor Jeffrey Omens, Chair Professor Andrew McCulloch, Co-Chair Professor Ju Chen Professor Karen Christman Professor Robert Ross Professor Alexander Zambon 2016 Copyright Kyle Stephen Buchholz, 2016 All rights reserved Signature Page The Dissertation of Kyle Stephen Buchholz is approved and it is acceptable in quality and form for publication on microfilm and electronically: Co-Chair Chair University of California, San Diego 2016 iii Dedication To my beautiful wife, Rhia. iv Table of Contents Signature Page ................................................................................................................... iii Dedication .......................................................................................................................... iv Table of Contents ................................................................................................................ v List of Figures ...................................................................................................................
    [Show full text]
  • MITF—The First 25 Years
    Downloaded from genesdev.cshlp.org on October 5, 2021 - Published by Cold Spring Harbor Laboratory Press SPECIAL SECTION: REVIEW MITF—the first 25 years Colin R. Goding1 and Heinz Arnheiter2 1Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, University of Oxford, Headington, Oxford OX3 7DQ, United Kingdom; 2National Institute of Neurological Disorders and Stroke, National Institutes of Heath, Bethesda, Maryland 20824, USA All transcription factors are equal, but some are more ness, microphthalmia (Fig. 1A), and deafness and, depend- equal than others. In the 25 yr since the gene encod- ing on the allele, may show auxiliary symptoms such as ing the microphthalmia-associated transcription factor osteopetrosis, mast cell deficiencies, heart hypotrophy, (MITF) was first isolated, MITF has emerged as a key co- or altered nephron numbers. In some cases only a minor ordinator of many aspects of melanocyte and melanoma reduction in the levels of the pigment enzyme tyrosinase biology. Like all transcription factors, MITF binds to spe- is observed, as seen with homozygosity for mi-spotted, cific DNA sequences and up-regulates or down-regulates an allele that was found only because it renders mice spot- its target genes. What marks MITF as being remarkable ted when combined with other mi alleles. Because the among its peers is the sheer range of biological proces- phenotypes associated with specific alleles or allele ses that it appears to coordinate. These include cell sur- combinations reveal a high degree of complexity, it was vival, differentiation, proliferation, invasion, senescence, originally thought that the full phenotypic spectrum asso- metabolism, and DNA damage repair.
    [Show full text]
  • TRAF2 Is an NF-ΚB-Activating Oncogene in Epithelial
    Oncogene (2015) 34, 209–216 & 2015 Macmillan Publishers Limited All rights reserved 0950-9232/15 www.nature.com/onc ORIGINAL ARTICLE TRAF2 is an NF-kB-activating oncogene in epithelial cancers RR Shen1,2,3, AY Zhou1,2,3, E Kim1,2,3, JT O’Connell1,2,3, D Hagerstrand1,2,3, R Beroukhim1,2,3 and WC Hahn1,2,3 Aberrant nuclear factor (NF)-kB activation is frequently observed in human cancers. Genome characterization efforts have identified genetic alterations in multiple components of the NF-kB pathway, some of which have been shown to be essential for cancer initiation and tumor maintenance. Here, using patient tumors and cancer cell lines, we identify the NF-kB regulator, TRAF2 (tumor necrosis factor (TNF) receptor-associated factor 2), as an oncogene that is recurrently amplified and rearranged in 15% of human epithelial cancers. Suppression of TRAF2 in cancer cells harboring TRAF2 copy number gain inhibits proliferation, NF-kB activation, anchorage-independent growth and tumorigenesis. Cancer cells that are dependent on TRAF2 also require NF-kB for survival. The phosphorylation of TRAF2 at serine 11 is essential for the survival of cancer cells harboring TRAF2 amplification. Together, these observations identify TRAF2 as a frequently amplified oncogene. Oncogene (2015) 34, 209–216; doi:10.1038/onc.2013.543; published online 23 December 2013 Keywords: TRAF2; NF-kB; cancer; 9q34 amplification INTRODUCTION for the recruitment of the canonical IKK complex, the central The nuclear factor-kB (NF-kB) transcription factors play pivotal mediator of NF-kB activation. roles in immunity, inflammation, cell differentiation, proliferation Several studies suggest that TRAF2 plays an important role in and survival.
    [Show full text]
  • NF-Κb Activation by a Signaling Complex Containing TRAF2, TANK and TBK1, a Novel IKK-Related Kinase
    The EMBO Journal Vol.18 No.23 pp.6694–6704, 1999 NF-κB activation by a signaling complex containing TRAF2, TANK and TBK1, a novel IKK-related kinase Joel L.Pomerantz and David Baltimore1 signals from the tumor necrosis factor (TNF) and Toll/ interleukin-1 (IL-1) receptor families, from CD3/CD28 Division of Biology, California Institute of Technology, Pasadena, co-stimulation of T cells and from the LMP-1 signaling CA 91125, USA protein of Epstein–Barr virus (EBV), and is also the 1Corresponding author target of the Tax gene product of HTLV-1 (Zandi and e-mail: [email protected] Karin, 1999). κ The IKK complex is activated by the NIK kinase The activation of NF- B by receptors in the tumor (Malinin et al., 1997), and other MAP3K kinases including necrosis factor (TNF) receptor and Toll/interleukin-1 MEKK1, 2 and 3 (Lee et al., 1998; Nakano et al., 1998; (IL-1) receptor families requires the TRAF family of Nemoto et al., 1998; Zhao and Lee, 1999). NIK is a adaptor proteins. Receptor oligomerization causes the potent activator of NF-κB, and kinase-dead NIK blocks recruitment of TRAFs to the receptor complex, fol- NF-κB activation by TNF-α, IL-1, Fas (Malinin et al., lowed by the activation of a kinase cascade that results 1997), Toll-like receptors 2 and 4 (Kirschning et al., 1998; in the phosphorylation of IκB. TANK is a TRAF- Muzio et al., 1998), LMP-1 (Sylla et al., 1998) and CD3/ binding protein that can inhibit the binding of TRAFs CD28 stimulation (Lin et al., 1999).
    [Show full text]
  • Genetic Background: Understanding Its Importance in Mouse-Based Biomedical Research a Jackson Laboratory Resource Manual
    Genetic Background: Understanding its importance in mouse-based biomedical research A Jackson Laboratory Resource Manual This resource manual highlights the importance of using genetically well-defined mice for biomedical research. It briefly describes the following: • The importance of genetic background • Resources for helping researchers choose the appropriate mouse model • Proper nomenclature to communicate the genetic makeup of mouse models • The Jackson Laboratory’s Genetic Quality Control and Genetic Stability programs Cover Photos Front cover, left: JAX® Mice strain C3H/HeJ (000659) Front cover, middle: Technician displaying holders with straws in the liquid nitrogen storage tank in our Cryopreservation Repository. Front cover, right: JAX® Mice strain C57BL/6J (000664) Table of Contents Introduction ........................................................................................................................ 1 Genetic Background Definition and Examples ............................................................................................ 2 Genetic Background Makes a Difference ................................................................. 2 The Influence of 129 Substrain Backgrounds on Targeted Mutations ................. 4 Consequences of Using Inappropriate Backgrounds .............................................. 4 Minimizing the Confounding Effects of Genetic Background .............................. 5 How Substrains Arise .................................................................................................
    [Show full text]
  • SARS-Cov-2 Membrane Protein Inhibits Type I Interferon Production Through Ubiquitin-Mediated Degradation of TBK1
    ORIGINAL RESEARCH published: 18 May 2021 doi: 10.3389/fimmu.2021.662989 SARS-CoV-2 Membrane Protein Inhibits Type I Interferon Production Through Ubiquitin-Mediated Degradation of TBK1 Liyan Sui 1, Yinghua Zhao 1, Wenfang Wang 2, Ping Wu 3, Zedong Wang 1, Yang Yu 4, Zhijun Hou 3, Guangyun Tan 5* and Quan Liu 1,6* 1 Laboratory of Emerging Infectious Disease, Institute of Translational Medicine, The First Hospital of Jilin University, Changchun, China, 2 College of Basic Medical Science, Jilin University, Changchun, China, 3 College of Wildlife and Protected Area, Northeast Forestry University, Harbin, China, 4 Hospital of Stomatology, Jilin University, Changchun, China, 5 Department of Immunology, Institute of Translational Medicine, The First Hospital of Jilin University, Changchun, China, 6 School of Life Sciences and Engineering, Foshan University, Foshan, China The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the causative Edited by: pathogen of current COVID-19 pandemic, and insufficient production of type I interferon Kai Deng, Sun Yat-Sen University, China (IFN-I) is associated with the severe forms of the disease. Membrane (M) protein of SARS- Reviewed by: CoV-2 has been reported to suppress host IFN-I production, but the underlying Shuai Chen, mechanism is not completely understood. In this study, SARS-CoV-2 M protein was Sun Yat-Sen University Cancer Center confirmed to suppress the expression of IFNb and interferon-stimulated genes induced by (SYSUCC), China Chi Ping Chan, RIG-I, MDA5, IKKϵ, and TBK1, and to inhibit IRF3 phosphorylation and dimerization The University of Hong Kong, caused by TBK1.
    [Show full text]