DOCSLIB.ORG

Structural Insights Into Oligomerization and Mitochondrial Remodeling of Dynamin 1-Like Protein

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Structural Insights Into Oligomerization and Mitochondrial Remodeling of Dynamin 1-Like Protein Structural insights into oligomerization and mitochondrial remodeling of dynamin 1-like protein 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 Dipl.-Ing. Chris Fröhlich aus der Lutherstadt Eisleben Berlin 2013 ii Die vorliegende Arbeit wurde im Zeitraum April 2009 bis März 2013 am Max-Delbrück-Centrum für Molekulare Medizin Berlin-Buch unter Anleitung von PROF. DR. OLIVER DAUMKE angefertigt. 1. Gutachter: Prof. Dr. Udo Heinemann 2. Gutachter: Prof. Dr. Oliver Daumke Tag der Disputation: 29.07.2013 iii … to boldly go where no man has gone before. iv Contents ___________________________________________________________________________ Contents Contents ................................................................................................................................................... v List of Figures ........................................................................................................................................... ix List of Tables ............................................................................................................................................ xi 1. Introduction ..................................................................................................................................... 1 1.1. Mitochondria ........................................................................................................................... 1 1.1.1. The mitochondrial compartment .................................................................................... 2 1.1.2. The mitochondrial network ............................................................................................. 5 1.1.3. Mitochondria associated diseases .................................................................................. 6 1.2. G proteins ................................................................................................................................ 8 1.3. The dynamin superfamily of G proteins ................................................................................ 10 1.3.1. Dynamin ........................................................................................................................ 12 1.3.1.1. Dynamins are key players in clathrin-mediated endocytosis ................................ 12 1.3.1.2. The G domain and the bundle signaling element ................................................. 14 1.3.1.3. G domain dimerization is crucial for dynamin function ........................................ 15 1.3.1.4. Dynamin's PH domain mediates lipid binding ....................................................... 17 1.3.1.5. The stalk is the central assembly hub for dynamin oligomerization ..................... 17 1.3.1.6. Regulatory functions of the stalk .......................................................................... 20 1.3.1.7. Functional models of dynamin's mechano-chemical action ................................. 20 1.3.2. Myxovirus resistance (Mx) proteins .............................................................................. 22 1.3.2.1. Mx proteins mediate antiviral host response ....................................................... 22 1.3.2.2. Different functions - similar structures: MxA and dynamin 1 ............................... 23 1.3.2.3. The MxA stalk mediates oligomerization and regulatory function ....................... 24 1.3.2.4. The MxA stalk mediates assembly in rings rather than helices ............................ 25 1.3.3. Bacterial dynamin-like proteins (BDLPs) ....................................................................... 26 1.3.4. Guanylate-binding proteins (GBPs) ............................................................................... 28 1.3.5. Eps15 homology-domain containing proteins (EHDs) ................................................... 29 1.3.6. Mitochondrial fusion dynamins..................................................................................... 31 1.3.6.1. Mitochondrial outer membrane fusion dynamins ................................................ 31 1.3.6.2. Mitochondrial inner membrane fusion dynamins ................................................ 32 1.3.7. The mitochondrial fission dynamin 1-like protein (DNM1L) ......................................... 32 1.3.7.1. DNM1L is a key player in mitochondrial fission .................................................... 32 v Contents ___________________________________________________________________________ 1.3.7.2. Recruitment of DNM1L to mitochondria scission sites involves certain adaptor proteins and the endoplasmic reticulum (ER) ........................................................................... 33 1.3.7.3. Two-start versus one-start helix ............................................................................ 34 1.4. Scope of this work ................................................................................................................. 36 2. Materials and Methods ................................................................................................................. 38 2.1. Materials ................................................................................................................................ 38 2.1.1. Chemicals ....................................................................................................................... 38 2.1.2. Antibodies...................................................................................................................... 38 2.1.3. Enzymes ......................................................................................................................... 38 2.1.4. Kits ................................................................................................................................. 39 2.1.5. Microorganisms and cell lines ....................................................................................... 39 2.1.6. Vectors ........................................................................................................................... 40 2.1.7. cDNA clone .................................................................................................................... 40 2.1.8. Primers .......................................................................................................................... 40 2.1.8.1. Cloning Primers ..................................................................................................... 40 2.1.8.2. Quick change mutagenesis primers ...................................................................... 40 2.1.9. Media and antibiotics .................................................................................................... 42 2.1.10. Buffers ........................................................................................................................... 42 2.2. Molecular biology methods................................................................................................... 43 2.2.1. Polymerase chain reaction ............................................................................................ 43 2.2.2. DNA digestion ................................................................................................................ 43 2.2.3. Agarose gel electrophoresis .......................................................................................... 43 2.2.4. DNA purification ............................................................................................................ 43 2.2.5. Ligation .......................................................................................................................... 44 2.2.6. Preparation of chemically competent E. coli ................................................................. 44 2.2.7. Transformation of chemically competent E. coli ........................................................... 44 2.2.8. Isolation of plasmid DNA ............................................................................................... 44 2.2.9. DNA sequencing ............................................................................................................ 44 2.2.10. Site specific mutagenesis............................................................................................... 44 2.2.11. Sequence alignments .................................................................................................... 45 2.2.12. Bacterial storage ............................................................................................................ 45 2.2.13. Construct design ............................................................................................................ 45 2.3. Biochemical methods ............................................................................................................ 45 2.3.1. SDS PAGE ....................................................................................................................... 45 2.3.2. Protein over-expression test in E. coli ........................................................................... 45 vi Contents ___________________________________________________________________________ 2.3.3. Protein solubility test .................................................................................................... 46 2.3.4. Large scale protein over-expression in E. coli ..............................................................
Load more

Recommended publications
  • Seq2pathway Vignette
    seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway.
    [Show full text]
  • Identification and Characterization of TPRKB Dependency in TP53 Deficient Cancers
    Identification and Characterization of TPRKB Dependency in TP53 Deficient Cancers. by Kelly Kennaley A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Molecular and Cellular Pathology) in the University of Michigan 2019 Doctoral Committee: Associate Professor Zaneta Nikolovska-Coleska, Co-Chair Adjunct Associate Professor Scott A. Tomlins, Co-Chair Associate Professor Eric R. Fearon Associate Professor Alexey I. Nesvizhskii Kelly R. Kennaley [email protected] ORCID iD: 0000-0003-2439-9020 © Kelly R. Kennaley 2019 Acknowledgements I have immeasurable gratitude for the unwavering support and guidance I received throughout my dissertation. First and foremost, I would like to thank my thesis advisor and mentor Dr. Scott Tomlins for entrusting me with a challenging, interesting, and impactful project. He taught me how to drive a project forward through set-backs, ask the important questions, and always consider the impact of my work. I’m truly appreciative for his commitment to ensuring that I would get the most from my graduate education. I am also grateful to the many members of the Tomlins lab that made it the supportive, collaborative, and educational environment that it was. I would like to give special thanks to those I’ve worked closely with on this project, particularly Dr. Moloy Goswami for his mentorship, Lei Lucy Wang, Dr. Sumin Han, and undergraduate students Bhavneet Singh, Travis Weiss, and Myles Barlow. I am also grateful for the support of my thesis committee, Dr. Eric Fearon, Dr. Alexey Nesvizhskii, and my co-mentor Dr. Zaneta Nikolovska-Coleska, who have offered guidance and critical evaluation since project inception.
    [Show full text]
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
    [Show full text]
  • Supporting Information
    Supporting Information Pouryahya et al. SI Text Table S1 presents genes with the highest absolute value of Ricci curvature. We expect these genes to have significant contribution to the network’s robustness. Notably, the top two genes are TP53 (tumor protein 53) and YWHAG gene. TP53, also known as p53, it is a well known tumor suppressor gene known as the "guardian of the genome“ given the essential role it plays in genetic stability and prevention of cancer formation (1, 2). Mutations in this gene play a role in all stages of malignant transformation including tumor initiation, promotion, aggressiveness, and metastasis (3). Mutations of this gene are present in more than 50% of human cancers, making it the most common genetic event in human cancer (4, 5). Namely, p53 mutations play roles in leukemia, breast cancer, CNS cancers, and lung cancers, among many others (6–9). The YWHAG gene encodes the 14-3-3 protein gamma, a member of the 14-3-3 family proteins which are involved in many biological processes including signal transduction regulation, cell cycle pro- gression, apoptosis, cell adhesion and migration (10, 11). Notably, increased expression of 14-3-3 family proteins, including protein gamma, have been observed in a number of human cancers including lung and colorectal cancers, among others, suggesting a potential role as tumor oncogenes (12, 13). Furthermore, there is evidence that loss Fig. S1. The histogram of scalar Ricci curvature of 8240 genes. Most of the genes have negative scalar Ricci curvature (75%). TP53 and YWHAG have notably low of p53 function may result in upregulation of 14-3-3γ in lung cancer Ricci curvatures.
    [Show full text]
  • A Mutation in the Mitochondrial Fission Gene Dnm1l Leads to Cardiomyopathy
    A Mutation in the Mitochondrial Fission Gene Dnm1l Leads to Cardiomyopathy Houman Ashrafian1, Louise Docherty2, Vincenzo Leo3, Christopher Towlson2, Monica Neilan2, Violetta Steeples1, Craig A. Lygate1, Tertius Hough3, Stuart Townsend3, Debbie Williams4, Sara Wells4, Dominic Norris4, Sarah Glyn-Jones5, John Land6, Ivana Barbaric7, Zuzanne Lalanne4, Paul Denny4, Dorota Szumska1, Shoumo Bhattacharya1, Julian L. Griffin5, Iain Hargreaves6, Narcis Fernandez-Fuentes3, Michael Cheeseman4, Hugh Watkins1, T. Neil Dear2,3,4* 1 Department of Cardiovascular Medicine and Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom, 2 Mammalian Genetics of Disease Unit, School of Medicine, University of Sheffield, Sheffield, United Kingdom, 3 Leeds Institute of Molecular Medicine, Wellcome Trust Brenner Building, St. James’s University Hospital, Leeds, United Kingdom, 4 Mary Lyon Centre and Mammalian Genetics Unit, Medical Research Council, Harwell, United Kingdom, 5 Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom, 6 Neurometabolic Unit, National Hospital, London, United Kingdom, 7 Department of Biomedical Science, University of Sheffield, Sheffield, United Kingdom Abstract Mutations in a number of genes have been linked to inherited dilated cardiomyopathy (DCM). However, such mutations account for only a small proportion of the clinical cases emphasising the need for alternative discovery approaches to uncovering novel pathogenic mutations in hitherto unidentified pathways. Accordingly, as part
    [Show full text]
  • Expression of DDX11 and DNM1L at the 12P11 Locus Modulates Systemic Lupus Erythematosus Susceptibility
    International Journal of Molecular Sciences Article Expression of DDX11 and DNM1L at the 12p11 Locus Modulates Systemic Lupus Erythematosus Susceptibility Mohammad Saeed 1 , Alejandro Ibáñez-Costa 2 , Alejandra María Patiño-Trives 2, Laura Muñoz-Barrera 2, Eduardo Collantes Estévez 2 , María Ángeles Aguirre 2 and Chary López-Pedrera 2,* 1 ImmunoCure, Karachi 75500, Pakistan; [email protected] 2 Rheumatology Service, Maimonides Institute for Biomedical Research of Cordoba (IMIBIC), Reina Sofia Hospital, University of Cordoba, 14004 Cordoba, Spain; [email protected] (A.I.-C.); [email protected] (A.M.P.-T.); [email protected] (L.M.-B.); [email protected] (E.C.E.); [email protected] (M.Á.A.) * Correspondence: [email protected] Abstract: Objectives: This study employed genetic and functional analyses using OASIS meta- analysis of multiple existing GWAS and gene-expression datasets to identify novel SLE genes. Methods: Four hundred and ten genes were mapped using SNIPPER to 30 SLE GWAS loci and investigated for expression in three SLE GEO-datasets and the Cordoba GSE50395-dataset. Blood eQTL for significant SNPs in SLE loci and STRING for functional pathways of differentially expressed genes were used. Confirmatory qPCR on SLE monocytes was performed. The entire 12p11 locus was investigated for genetic association using two additional GWAS. Expression of 150 genes at Citation: Saeed, M.; Ibáñez-Costa, A.; this locus was assessed. Based on this significance, qPCRs for DNM1L and KRAS were performed. Patiño-Trives, A.M.; Muñoz-Barrera, Results: Fifty genes were differentially expressed in at least two SLE GEO-datasets, with all probes L.; Collantes Estévez, E.; Aguirre, M.Á.; López-Pedrera, C.
    [Show full text]
  • GED) of DNM1L Leads to Static Encephalopathy and Seizures
    Downloaded from molecularcasestudies.cshlp.org on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press De novo missense variant in the GTPase effector domain (GED) of DNM1L leads to static encephalopathy and seizures Nurit Assia Batzir1,†, Pranjali K. Bhagwat1,2,†, Tanya N. Eble1, Pengfei Liu1,3, Christine M. Eng1,3, Sarah H. Elsea1,3, Laurie A. Robak1,2, Fernando Scaglia1,4, Alica M. Goldman1, Shweta U. Dhar1,5,* and Michael F. Wangler1,2,* 1Department of Molecular and Human Genetics, Baylor College of Medicine, Houston TX 77030, USA, 2Neurological Research Institute, Texas Children’s Hospital, Houston TX 77030, USA, 3Baylor Genetics, Houston, TX 77021 USA, 4BCM-CUHK Center of Medical Genetics, Prince of Wales Hospital, ShaTin, New Territories, Hong Kong SAR, 5Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA † Equal Contribution * To whom correspondence should be addressed at: Neurologic Research Institute, Suite N.1050, 1250 Moursund Ave, Houston, TX 77030 USA. Tel: +1 8328248716; Fax: +1 8328251240; Email: [email protected] AND Shweta Dhar: One Baylor Plz, MS 228, Baylor College of Medicine, Houston, TX 77030, USA. Tel: +1 7137987764; Fax: +1 7137986450; Email: [email protected] Running Title: DNM1L GTPase effector domain variant in epilepsy 1 Downloaded from molecularcasestudies.cshlp.org on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press ABSTRACT DNM1L encodes a GTPase of the dynamin superfamily which plays a crucial role in mitochondrial and peroxisomal fission. Pathogenic variants affecting the middle domain and the GTPase domain of DNM1L have been implicated in encephalopathy due to defective mitochondrial and peroxisomal fission 1 (EMPF1, MIM #614388).
    [Show full text]
  • Clinical-Genetic Features and Peculiar Muscle Histopathology in Infantile
    Adele D’Amico ORCID iD: 0000-0003-2438-2624 Daria Diodato ORCID iD: 0000-0003-3607-8523 Rosalba Carrozzo ORCID iD: 0000-0002-3327-4054 Clinical-genetic features and peculiar muscle histopathology in infantile DNM1L-related mitochondrial epileptic encephalopathy Daniela Verrigni1*, Michela Di Nottia1*, Anna Ardissone2,3*, Enrico Baruffini4*, Alessia Nasca5, Andrea Legati5, Emanuele Bellacchio6, Gigliola Fagiolari7, Diego Martinelli8, Lucia Fusco9, Domenica Battaglia10, Giulia Trani1, Gianmarco Versienti5, Silvia Marchet5, Alessandra Torraco1, Teresa Rizza1, Margherita Verardo1, Adele D’Amico1, Daria Diodato1, Isabella Moroni2, Costanza Lamperti5, Stefania Petrini11, Maurizio Moggio7, Paola Goffrini4, Daniele Ghezzi5,12#, Rosalba Carrozzo1#, Enrico Bertini1# 1Unit of Muscular and Neurodegenerative Disorders, Laboratory of Molecular Medicine, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy; 2Child Neurology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy; 3Department of Molecular and Translational Medicine DIMET, University of Milan- Bicocca, Milan, Italy; 4Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy; 5Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record.
    [Show full text]
  • The Impact of Exercise on Mitochondrial Dynamics and the Role of Drp1 in Exercise Performance and Training Adaptations in Skeletal Muscle
    Original Article The impact of exercise on mitochondrial dynamics and the role of Drp1 in exercise performance and training adaptations in skeletal muscle Timothy M. Moore 1,2, Zhenqi Zhou 2, Whitaker Cohn 3, Frode Norheim 4, Amanda J. Lin 2, Nareg Kalajian 2, Alexander R. Strumwasser 2, Kevin Cory 2, Kate Whitney 2, Theodore Ho 2, Timothy Ho 2, Joseph L. Lee 2, Daniel H. Rucker 2, Orian Shirihai 2, Alexander M. van der Bliek 5, Julian P. Whitelegge 3, Marcus M. Seldin 4, Aldons J. Lusis 4,6, Sindre Lee 7, Christian A. Drevon 7,8, Sushil K. Mahata 9,10, Lorraine P. Turcotte 1, Andrea L. Hevener 2,11,* ABSTRACT Objective: Mitochondria are organelles primarily responsible for energy production, and recent evidence indicates that alterations in size, shape, location, and quantity occur in response to fluctuations in energy supply and demand. We tested the impact of acute and chronic exercise on mitochondrial dynamics signaling and determined the impact of the mitochondrial fission regulator Dynamin related protein (Drp)1 on exercise performance and muscle adaptations to training. þ À Methods: Wildtype and muscle-specific Drp1 heterozygote (mDrp1 / ) mice, as well as dysglycemic (DG) and healthy normoglycemic men (control) performed acute and chronic exercise. The Hybrid Mouse Diversity Panel, including 100 murine strains of recombinant inbred mice, was used to identify muscle Dnm1L (encodes Drp1)-gene relationships. Results: Endurance exercise impacted all aspects of the mitochondrial life cycle, i.e. fission-fusion, biogenesis, and mitophagy. Dnm1L gene expression and Drp1Ser616 phosphorylation were markedly increased by acute exercise and declined to baseline during post-exercise recovery.
    [Show full text]
  • Elucidating the Unknown Role of Cyclin Dependent Kinase 5 in Cardiac Pathophysiological
    Elucidating the Unknown Role of Cyclin Dependent Kinase 5 in Cardiac Pathophysiological Conditions Danielle Aina-Badejo Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2021 © 2021 Danielle Aina-Badejo All Rights Reserved Abstract Elucidating the Unknown Role of Cyclin Dependent Kinase 5 in Cardiac Pathophysiological Conditions Danielle Aina-Badejo Until now, the role of cyclin dependent kinase 5 (CDK5) in cardiac pathophysiology has not been explored. While CDK5 has been well studied in the neuroscience/Alzheimer’s field as a cyclin-independent kinase, there is currently no investigation into the cardiac-specific role of CDK5. Recently, it was established that inhibition of CDK5 in stem cell derived cardiomyocytes from individuals with Timothy Syndrome (TS) rescued the delayed inactivation phenotype; TS is a fatal genetic long QT syndrome (LQTS) caused by delayed inactivation of the L-type voltage 2+ gated Ca channel Ca V1.2. While it is evident that CDK5 plays an important role in regulating Ca V1.2 function, its role in cardiac tissue remains to be elucidated. To determine whether CDK5 is essential for cardiac function, two separate mouse models were established—a cardiac-deficient Cdk5 mouse model ( Cdk5 flox x αMHC-MerCreMer +) and a Cdk5 activation mouse model via overexpression of Cdk5’s known activator, p35 (Cdk5r1/ p35 OE x αMHC-MerCreMer +). Immediately after spatiotemporal induction of deficiency/activation of Cdk5 in adult mice, echocardiography, histology and proteomic analysis were performed to examine effects on cardiac structure and function.
    [Show full text]
  • Mitofusins Deficiency Elicits Mitochondrial Metabolic Reprogramming to Pluripotency
    Cell Death and Differentiation (2015) 22, 1957–1969 & 2015 Macmillan Publishers Limited All rights reserved 1350-9047/15 www.nature.com/cdd Mitofusins deficiency elicits mitochondrial metabolic reprogramming to pluripotency MJ Son1,2, Y Kwon1,2, M-Y Son1, B Seol1, H-S Choi1, S-W Ryu3, C Choi3 and YS Cho*,1,2 Cell reprogramming technology has allowed the in vitro control of cell fate transition, thus allowing for the generation of highly desired cell types to recapitulate in vivo developmental processes and architectures. However, the precise molecular mechanisms underlying the reprogramming process remain to be defined. Here, we show that depleting p53 and p21, which are barriers to reprogramming, yields a high reprogramming efficiency. Deletion of these factors results in a distinct mitochondrial background with low expression of oxidative phosphorylation subunits and mitochondrial fusion proteins, including mitofusin 1 and 2 (Mfn1/2). Importantly, Mfn1/2 depletion reciprocally inhibits the p53-p21 pathway and promotes both the conversion of somatic cells to a pluripotent state and the maintenance of pluripotency. Mfn1/2 depletion facilitates the glycolytic metabolic transition through the activation of the Ras-Raf and hypoxia-inducible factor 1α (HIF1α) signaling at an early stage of reprogramming. HIF1α is required for increased glycolysis and reprogramming by Mfn1/2 depletion. Taken together, these results demonstrate that Mfn1/2 constitutes a new barrier to reprogramming, and that Mfn1/2 ablation facilitates the induction of pluripotency
    [Show full text]
  • Dema and Faust Et Al., Suppl. Material 2020.02.03
    Supplementary Materials Cyclin-dependent kinase 18 controls trafficking of aquaporin-2 and its abundance through ubiquitin ligase STUB1, which functions as an AKAP Dema Alessandro1,2¶, Dörte Faust1¶, Katina Lazarow3, Marc Wippich3, Martin Neuenschwander3, Kerstin Zühlke1, Andrea Geelhaar1, Tamara Pallien1, Eileen Hallscheidt1, Jenny Eichhorst3, Burkhard Wiesner3, Hana Černecká1, Oliver Popp1, Philipp Mertins1, Gunnar Dittmar1, Jens Peter von Kries3, Enno Klussmann1,4* ¶These authors contributed equally to this work 1Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Robert- Rössle-Strasse 10, 13125 Berlin, Germany 2current address: University of California, San Francisco, 513 Parnassus Avenue, CA 94122 USA 3Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Rössle-Strasse 10, 13125 Berlin, Germany 4DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Oudenarder Strasse 16, 13347 Berlin, Germany *Corresponding author Enno Klussmann Max Delbrück Center for Molecular Medicine Berlin in the Helmholtz Association (MDC) Robert-Rössle-Str. 10, 13125 Berlin Germany Tel. +49-30-9406 2596 FAX +49-30-9406 2593 E-mail: [email protected] 1 Content 1. CELL-BASED SCREENING BY AUTOMATED IMMUNOFLUORESCENCE MICROSCOPY 3 1.1 Screening plates 3 1.2 Image analysis using CellProfiler 17 1.4 Identification of siRNA affecting cell viability 18 1.7 Hits 18 2. SUPPLEMENTARY TABLE S4, FIGURES S2-S4 20 2 1. Cell-based screening by automated immunofluorescence microscopy 1.1 Screening plates Table S1. Genes targeted with the Mouse Protein Kinases siRNA sub-library. Genes are sorted by plate and well. Accessions refer to National Center for Biotechnology Information (NCBI, BLA) entries. The siRNAs were arranged on three 384-well microtitre platres.
    [Show full text]