Diplomová Práce

Total Page:16

File Type:pdf, Size:1020Kb

Diplomová Práce PŘÍRODOVĚDECKÁ FAKULTA Diplomová práce Adéla Horáková Brno 2019 PŘÍRODOVĚDECKÁ FAKULTA Analýza genomických defektů podmiňujících klonální evoluci chronické lymfocytární leukémie Diplomová práce ADÉLA HORÁKOVÁ Vedoucí práce: Mgr. Karla Plevová, Ph.D. Interní hematologická a onkologická klinika LF MU a FN Brno Brno 2019 Bibliografický záznam Autor: Bc. Adéla Horáková Přírodovědecká fakulta, Masarykova Ústav experimentální biologie Název práce: Analýza genomických defektů podmiňujících klonální evoluci chronické lymfocytární leukémie Studijní program: Experimentální biologie Studijní obor: Molekulární biologie a genetika Vedoucí práce: Mgr. Karla Plevová, Ph.D. Akademický rok: 2018/2019 Počet stran: 80 Klíčová slova: Chronická lymfocytární leukémie, TP53, klonální evoluce, celoexomové sekvenování Bibliographic Entry Author: Bc. Adéla Horáková Faculty of Science, Masaryk University Department of Experimental Biology Title of Thesis: Analysis of genomic defects underlying clonal evolution in chronic lymphocytic leukemia Degree programme: Experimental Biology Field of Study: Molecular Biology and Genetics Supervisor: Mgr. Karla Plevová, Ph.D. Academic Year: 2018/2019 Number of Pages: 80 Keywords: Chronic lymphocytic leukemia, TP53, clonal evolution, whole-exome sequencing Abstrakt Chronická lymfocytární leukémie je nejčastější leukémií v západním světě a její průběh je velmi heterogenní. U části pacientů dochází během onemocnění k zisku aberací spojených se zhoršením nemoci a rozvojem rezistence k protinádorové léčbě. Z klinického hlediska má zásadní význam nalezení takových znaků leukemických buněk, např. genových mutací, které by umožnily identifikaci pacientů v riziku tohoto nepříznivého průběhu. V rámci diplomové práce byla u vybraného souboru pacientů provedena analýza dat z celoexomového sekvenování a označeny geny potenciálně zodpovědné za nepříznivou klonální evoluci chronické lymfocytární leukémie. Abstract Chronic lymphocytic leukemia is the most common leukemia in the western world and its clinical course is very heterogenous. In a subgroup of patients, a gain of aberrations connected with deterioration of the disease course occurs and resistence to anticancer treatmeant often develops. From the clinical point of view, identification of progression markers of leukemic cells, for example genetic mutations, which would allow distinguishing patients at risk of unfavourable course, has a crucial importance. In the scope of this diploma thesis, analysis of whole-exome sequencing data in a selected group of patients was performed with the aim to identify genes potentially responsible for unfavourable clonal evolution of chronical lymphocytic leukemia. Poděkování Na tomto místě bych chtěla především poděkovat své školitelce Mgr. Karle Plevové, Ph.D. za pomoc při vypracování této práce, cenné odborné rady, připomínky a věnovaný čas. Dále bych chtěla poděkovat své konzultance Mgr. Kamile Stránské, za odborný dohled a pomoc při zpracování experimentální části práce a za množství velmi praktických rad. V neposlední řadě bych ráda poděkovala všem laborantkám, bioinformatikům a dalšímu odbornému personálu, který mi pomohl ze všech úskalí, která se během zpracování této práce vyskytla. A nakonec bych chtěla poděkovat své rodině, bez jejíž podpory a pomoci by tato práce nevznikla. Prohlášení Prohlašuji, že jsem svoji diplomovou práci vypracovala samostatně s využitím informačních zdrojů, které jsou v práci citovány. Text práce jsem vypracovala podle pravidel a zodpovídám za jeho jazykovou správnost. Brno, 9. května 2019 …………………………………. Adéla Horáková Obsah: 1. Seznam použitých zkratek ................................................................................................... 9 2. Úvod a problematika ......................................................................................................... 10 2.1. Chronická lymfocytární leukémie ............................................................................ 10 2.1.1. Charakteristika CLL buněk ............................................................................ 10 2.1.2. Diagnostika ..................................................................................................... 11 2.1.3. Prognóza ......................................................................................................... 12 2.1.4. Terapie ............................................................................................................ 13 2.2. Způsoby detekce genomických změn ...................................................................... 14 2.2.1. Fluorescenční in situ hybridizace (FISH) ....................................................... 14 2.2.2. Analýza metafázních chromozomů (G pruhování). ....................................... 14 2.2.3. CGH a čipové technologie .............................................................................. 15 2.2.4. MLPA a techniky založené na polymerázové řetězové reakci ....................... 16 2.2.5. Sekvenování DNA .......................................................................................... 16 2.3. Genetické abnormality a klonální vývoj CLL.......................................................... 18 2.3.1. Delece lokusu 13q14 ...................................................................................... 18 2.3.2. Delece lokusu 17p13 a mutace TP53 ............................................................. 18 2.3.3. Delece lokusu 11q22-q23 ............................................................................... 19 2.3.4. Trisomie chromozomu 12 ............................................................................... 20 2.3.5. Translokace ..................................................................................................... 20 2.3.6. Komplexní karyotyp ....................................................................................... 20 2.3.7. Další strukturní a numerické aberace ............................................................. 21 2.3.8. Somatické genové mutace a změny v expresi genů ....................................... 22 2.3.9. Klonální vývoj ................................................................................................ 29 3. Cíle diplomové práce ......................................................................................................... 30 4. Materiál a metody .............................................................................................................. 31 4.1. Sběr materiálu .......................................................................................................... 32 7 4.2. Separace buněk z periferní krve ............................................................................... 32 4.3. Analýza chromozomových aberací metodou FISH ................................................. 33 4.4. Stanovení mutace TP53 ........................................................................................... 34 4.5. Izolace DNA ............................................................................................................ 34 4.5.1. Izolace nádorové DNA pomocí QIAcube ...................................................... 35 4.5.2. Izolace nenádorové DNA ............................................................................... 35 4.5.3. Kontrola kvality a kvantity DNA ................................................................... 35 4.5.4. Hodnocení kvality DNA pomocí gelové elektroforézy .................................. 36 4.6. Celoexomové sekvenování ...................................................................................... 37 4.6.1. Příprava knihovny na sekvenování pomocí Truseq kitu ................................ 37 4.6.2. Příprava knihovny na sekvenování pomocí Nextera kitu ............................... 37 4.6.3. Měření koncentrace a hodnocení kvality DNA fragmentů ............................. 37 4.6.4. Sekvenování ................................................................................................... 38 4.6.5. Analýza dat ..................................................................................................... 39 5. Výsledky ............................................................................................................................ 41 5.1. Hodnocení pacientů ................................................................................................. 41 5.1.1. Pacienti s neexpandující mutací TP53 ............................................................ 41 5.1.2. Pacienti s expandující mutací TP53................................................................ 42 5.2. Celoxomové sekvenování ........................................................................................ 44 5.2.1. Hodnocení kvality DNA v rámci přípravy knihovny ..................................... 44 5.2.2. Kontrola správnosti přiřazení vzorků ............................................................. 45 5.2.3. Analýza získaných dat .................................................................................... 46 6. Diskuze .............................................................................................................................. 53 7. Souhrn ............................................................................................................................... 56 8. Summary ........................................................................................................................... 57 9. Přehled literatury ..............................................................................................................
Recommended publications
  • 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]
  • Exploring the Human Protein Atlas (HPA) Portal for New Biomarkers in Urinary Bladder Carcinoma
    Exploring the Human Protein Atlas (HPA) Portal for New Biomarkers in Urinary Bladder Carcinoma Tina Bergström Bachelor degree project in biomedicine, 10 hp, 2010 Department of Genetics and Pathology, Uppsala University Supervisors: Ulrika Segersten and Kenneth Wester Summary Urinary bladder cancer is the fifth most common cancer form in industrial countries. The primary risk factors for bladder cancer are tobacco smoking, exposure to aromatic amines from occupational sources, cancer drugs and Schistosomal infection. Vegetables, fruit and a high intake of fluid are considered as risk reducing factors for developing bladder cancer. Diagnosis and management of bladder cancer includes cystoscopy, an invasive method causing patients pain and discomfort. Hence, there is great need for non-invasive methods, such as biomarkers predicting tumour recurrence or progression. The aim of this study was to finding new potential biomarkers for urinary bladder carcinoma by exploration of the Human Protein Atlas (HPA) database portal, an antibody-based protein atlas comprising histological images which are a resource for many areas of biomedical research, including biomarker discovery. Initially, 35 selected proteins were evaluated in 42 tissue scores, representing bladder cancer biopsies from 24 individual cancer patients of which 7 had low-grade and 17 had high-grade tumours. The protein expression in tumour cells was scored and related to high and low tumour grade. Expression pattern for two proteins, 4, also known as immunoglobulin binding protein 1 (IGBP1) and UPF0500 protein C1orf216, were significantly altered (p < 0.5) with tumour grades. The function of C1orf216 is so far unknown. 4 is a regulator of protein phosphatase 2 (PP2A) and thereby controls dephosphorylation of substrates important in cell survival, apoptosis and cell migration.
    [Show full text]
  • Human Induced Pluripotent Stem Cell–Derived Podocytes Mature Into Vascularized Glomeruli Upon Experimental Transplantation
    BASIC RESEARCH www.jasn.org Human Induced Pluripotent Stem Cell–Derived Podocytes Mature into Vascularized Glomeruli upon Experimental Transplantation † Sazia Sharmin,* Atsuhiro Taguchi,* Yusuke Kaku,* Yasuhiro Yoshimura,* Tomoko Ohmori,* ‡ † ‡ Tetsushi Sakuma, Masashi Mukoyama, Takashi Yamamoto, Hidetake Kurihara,§ and | Ryuichi Nishinakamura* *Department of Kidney Development, Institute of Molecular Embryology and Genetics, and †Department of Nephrology, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan; ‡Department of Mathematical and Life Sciences, Graduate School of Science, Hiroshima University, Hiroshima, Japan; §Division of Anatomy, Juntendo University School of Medicine, Tokyo, Japan; and |Japan Science and Technology Agency, CREST, Kumamoto, Japan ABSTRACT Glomerular podocytes express proteins, such as nephrin, that constitute the slit diaphragm, thereby contributing to the filtration process in the kidney. Glomerular development has been analyzed mainly in mice, whereas analysis of human kidney development has been minimal because of limited access to embryonic kidneys. We previously reported the induction of three-dimensional primordial glomeruli from human induced pluripotent stem (iPS) cells. Here, using transcription activator–like effector nuclease-mediated homologous recombination, we generated human iPS cell lines that express green fluorescent protein (GFP) in the NPHS1 locus, which encodes nephrin, and we show that GFP expression facilitated accurate visualization of nephrin-positive podocyte formation in
    [Show full text]
  • Drosophila and Human Transcriptomic Data Mining Provides Evidence for Therapeutic
    Drosophila and human transcriptomic data mining provides evidence for therapeutic mechanism of pentylenetetrazole in Down syndrome Author Abhay Sharma Institute of Genomics and Integrative Biology Council of Scientific and Industrial Research Delhi University Campus, Mall Road Delhi 110007, India Tel: +91-11-27666156, Fax: +91-11-27662407 Email: [email protected] Nature Precedings : hdl:10101/npre.2010.4330.1 Posted 5 Apr 2010 Running head: Pentylenetetrazole mechanism in Down syndrome 1 Abstract Pentylenetetrazole (PTZ) has recently been found to ameliorate cognitive impairment in rodent models of Down syndrome (DS). The mechanism underlying PTZ’s therapeutic effect is however not clear. Microarray profiling has previously reported differential expression of genes in DS. No mammalian transcriptomic data on PTZ treatment however exists. Nevertheless, a Drosophila model inspired by rodent models of PTZ induced kindling plasticity has recently been described. Microarray profiling has shown PTZ’s downregulatory effect on gene expression in fly heads. In a comparative transcriptomics approach, I have analyzed the available microarray data in order to identify potential mechanism of PTZ action in DS. I find that transcriptomic correlates of chronic PTZ in Drosophila and DS counteract each other. A significant enrichment is observed between PTZ downregulated and DS upregulated genes, and a significant depletion between PTZ downregulated and DS dowwnregulated genes. Further, the common genes in PTZ Nature Precedings : hdl:10101/npre.2010.4330.1 Posted 5 Apr 2010 downregulated and DS upregulated sets show enrichment for MAP kinase pathway. My analysis suggests that downregulation of MAP kinase pathway may mediate therapeutic effect of PTZ in DS. Existing evidence implicating MAP kinase pathway in DS supports this observation.
    [Show full text]
  • Human Liver Specific Transcriptional Factor TCP10L Binds to MAD4
    Journal of Biochemistry and Molecular Biology, Vol. 37, No. 4, July 2004, pp. 402-407 © KSBMB & Springer-Verlag 2004 Human Liver Specific Transcriptional Factor TCP10L Binds to MAD4 Dao-Jun Jiang, Hong-Xiu Yu, Sa-Yin Hexige, Ze-Kun Guo, Xiang Wang, Li-Jie Ma, Zheng Chen, Shou-Yuan Zhao and Long Yu* State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University, Shanghai 200433, P. R. China Received 6 August 2003, Accepted 9 September 2003 A human gene T-complex protein 10 like (TCP10L) was cancer is largely dependent on the basic research on the gene cloned in our lab. A previous study showed that it regulation in the liver undergoing tumorigenesis. Transcription expressed specifically in the liver and testis. A factors, especially those specifically expressed in the liver, transcription experiment revealed that TCP10L was a may play a key role in hepatocarcinogenesis. transcription factor with transcription inhibition activity. The Myc/Max/Mad transcription factor network is In this study, the human MAD4 was identified to interact profoundly involved in the regulation of cell proliferation and with TCP10L by a yeast two-hybrid screen. This finding differentiation (Baudino and Cleveland, 2001). Each member was confirmed by immunoprecipitation and subcellular of the network contains a conserved basic Helix-Loop-Helix localization experiments. As MAD4 is a member of the leucine zipper motif (bHLHZip) that facilitates protein-protein MAD family, which antagonizes the functions of MYC and heterodimerization and protein-DNA binding. MYC and promotes cell differentiation, the biological function of the MAD proteins are functionally antagonized through interaction between TCP10L and MAD4 may be to competitively heterodimerizing with MAX and binding to maintain the differentiation state in liver cells.
    [Show full text]
  • Identification of Cancer and Cell-Cycle Genes with Protein Interactions And
    Royeretal. 81 Identification of cancer and cell-cycle genes with protein interactions and literaturemining Loic Royer,Conrad Plakeand Michael Schroeder {loic.royer,conrad.plake,michael.schroeder}@biotec.tu-dresden.de Biotec, TU Dresden, Dresden, Germany Abstract: Gene prioritization based on background knowledge mined from litera- ture has become an important method for the analysis of results from high-throughput experimental assays such as gene expression microarrays, RNAi screens and genome- wide association studies. We apply our gene mention identifier,which achievedthe best result of over80% in the BioCreative II text-mining challenge [HPR+08], and showhow text-mined associations canbecomplemented using guilt-by-association on high confidence protein interaction networks. First, we predict hand-curated gene-disease relationships in the OMIM database, Entrez Gene summaries and GeneRIFs with 37% success rate. Second, we confirm 24% of novelcell-cycle genes identified in arecent RNAi screen [KPH+07] by using text-mining and high confidence protein interactions. Moreover, we showhow 71% of GOAcell-cycle annotations can be automatically recovered. Third, we devise a method to rank genes based on novelty,increasing interest, impact, and popularity. 1Introduction With high-throughput methods such as gene expression analyses, high-throughput RNA interference, and genome-wide association studies, gene prioritization becomes an im- portant problem. Gene prioritization orders lists of genes according to their likelihood to be associated to aprocess, phenotype, or disease. In particular,genetic linkage anal- yses identify chromosomal regions, which are linked to adisease and which can con- tain hundred candidate genes linked to adisease. The problem becomes one of estab- lishing indirect links from the candidate genes to the disease.
    [Show full text]
  • Chromosome 21: a Small Land of Fascinating Disorders with Unknown Pathophysiology
    Int. J. Dev. Biol. 46: 89-96 (2002) Chromosome 21: a small land of fascinating disorders with unknown pathophysiology STYLIANOS E. ANTONARAKIS*, ROBERT LYLE, SAMUEL DEUTSCH and ALEXANDRE REYMOND Division of Medical Genetics, University of Geneva Medical School and University Hospitals, Geneva, Switzerland ABSTRACT In the year 2000 we celebrated the sequencing of the entire long arm of human chromosome 21. This achievement now provides unprecedented opportunities to understand the molecular pathophysiology of trisomy 21, elucidate the mechanisms of all monogenic disorders of chromosome 21, and discover genes and functional sequence variations that predispose to common complex disorders. All of that requires the functional analysis of gene products in model organisms, and the determination of the sequence variation of this chromosome. KEY WORDS: Down Syndrome, HC21, molecular pathology, trisomy 21, single nucleotide polymorphism The Sequence of HC21 and the Gene Catalogue gaps in regions with long stretches of repeats in which it was impossible to know if the entire repeat was sequenced. A region of On May 18, 2000, the (almost) entire sequence of 21q was 281 kb from the short arm 21p has also been sequenced and contains published and became freely available (Hattori et al., 2000). This just one gene (TPTE). landmark publication concluded research efforts of many investiga- Only approximately 3% of the sequence encodes for proteins; in tors and laboratories that studied the infrastructure of HC21 over the addition 1.3% encodes for short sequence repeats that may be last 15 years. Other historical landmarks of research on chromosome polymorphic in human populations. About 10.8% of the sequence are 21 include the first description of trisomy 21 in 1959 (Lejeune et al., SINE and 15.5% LINE repeats respectively; an additional 11.7% are 1959), first cloning of a chromosome 21 gene in 1982 (Lieman- other human repeats (total interspersed repeats 38% of the se- Hurwitz et al., 1982), first disease-related gene mutation identified in quence).
    [Show full text]
  • Human-Specific Transcriptional Networks in The
    Human-Specific Transcriptional Networks in the Brain Genevieve Konopka, University of California Tara Friedrich, University of California Jeremy Davis-Turak, University of California Kellen Winden, University of California Michael C. Oldham, University of California Fuying Gao, University of California Leslie Chen, University of California Guang-Zhong Wang, University of Texas Rui Luo, University of California Todd M Preuss, Emory University Only first 10 authors above; see publication for full author list. Journal Title: Neuron Volume: Volume 75, Number 4 Publisher: Elsevier (Cell Press) | 2012-08-23, Pages 601-617 Type of Work: Article | Post-print: After Peer Review Publisher DOI: 10.1016/j.neuron.2012.05.034 Permanent URL: https://pid.emory.edu/ark:/25593/s917g Final published version: http://dx.doi.org/10.1016/j.neuron.2012.05.034 Copyright information: © 2012 Elsevier Inc. Published by Elsevier Inc. This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0/). Accessed September 30, 2021 11:24 AM EDT NIH Public Access Author Manuscript Neuron. Author manuscript; available in PMC 2013 August 23. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Neuron. 2012 August 23; 75(4): 601–617. doi:10.1016/j.neuron.2012.05.034. Human-specific transcriptional networks in the brain Genevieve Konopka1,6, Tara Friedrich1, Jeremy Davis-Turak1, Kellen Winden1, Michael C. Oldham7, Fuying Gao1, Leslie Chen1, Guang-Zhong Wang6, Rui Luo2, Todd M. Preuss5, and Daniel H. Geschwind1,2,3,4 1Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA.
    [Show full text]
  • Guidelines for Human Gene Nomenclature
    Nomenclature doi:10.1006/geno.2002.6748, available online at http://www.idealibrary.com on IDEAL Guidelines for Human Gene Nomenclature Hester M. Wain, Elspeth A. Bruford, Ruth C. Lovering, Michael J. Lush, Mathew W. Wright, and Sue Povey HUGO Gene Nomenclature Committee, The Galton Laboratory, Department of Biology, University College London, Wolfson House, 4, Stephenson Way, London, NW1 2HE, UK. E-mail: [email protected]. INTRODUCTION 1.2 Locus The word “locus” is not a synonym for gene but refers to a Guidelines for human gene nomenclature were first pub- map position. A more precise definition is given in the Rules lished in 1979 [1], when the Human Gene Nomenclature and Guidelines from the International Committee on Standardized Committee was first given the authority to approve and Genetic Nomenclature for Mice, which states: “A locus is a point implement human gene names and symbols. Updates of these in the genome, identified by a marker, which can be mapped guidelines were published in 1987 [2], 1995 [3], and 1997 [4]. by some means. It does not necessarily correspond to a gene; With the recent publications of the complete human genome it could, for example, be an anonymous non-coding DNA sequence there is an estimated total of 26,000–40,000 genes, segment or a cytogenetic feature. A single gene may have as suggested by the International Human Genome several loci within it (each defined by different markers) and Sequencing Consortium [5] and Venter et al. [6]. Thus, the these markers may be separated in genetic or physical map- guidelines (http://www.gene.ucl.ac.uk/nomenclature/ ping experiments.
    [Show full text]
  • Investigating Contributions of Trisomy 21 in Down Syndrome to Alzheimer Disease Phenotypes in a Novel Mouse Cross
    Investigating contributions of trisomy 21 in Down syndrome to Alzheimer disease phenotypes in a novel mouse cross A thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy from University College London Xun Yu Choong Department of Neurodegenerative Disease Institute of Neurology University College London 2016 1 Declaration I, Xun Yu Choong, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. 2 Acknowledgements The work done in this project was only possible with the support of numerous friends and colleagues, with whom I have grown an incredible amount. Foremost thanks go to Prof. Elizabeth Fisher and Dr. Frances Wiseman, who have been inexhaustibly dedicated supervisors and inspirational figures. Special mention also goes to two unofficial mentors who have looked out for me throughout the PhD, Dr. Karen Cleverley and Dr. Sarah Mizielinska. The Fisher and Isaacs groups have been a joy to work with and have always unhesitatingly offered time and help. Thank you to the Down syndrome group: Olivia Sheppard, Dr. Toby Collins, Dr. Suzanna Noy, Amy Nick, Laura Pulford, Justin Tosh, Matthew Rickman; other members of Lizzy’s group: Dr. Anny Devoy, Dr. Rosie Bunton-Stasyshyn, Dr. Rachele Saccon, Julian Pietrzyk, Dr. Beverley Burke, Heesoon Park, Julian Jaeger; the Isaacs group: Dr. Adrian Isaacs, Dr. Emma Clayton, Dr. Roberto Simone, Charlotte Ridler, Frances Norona. The PhD office has also been a second home in more ways than one, thanks to: Angelos Armen, Dr.
    [Show full text]
  • Transcriptome Profiling Reveals the Complexity of Pirfenidone Effects in IPF
    ERJ Express. Published on August 30, 2018 as doi: 10.1183/13993003.00564-2018 Early View Original article Transcriptome profiling reveals the complexity of pirfenidone effects in IPF Grazyna Kwapiszewska, Anna Gungl, Jochen Wilhelm, Leigh M. Marsh, Helene Thekkekara Puthenparampil, Katharina Sinn, Miroslava Didiasova, Walter Klepetko, Djuro Kosanovic, Ralph T. Schermuly, Lukasz Wujak, Benjamin Weiss, Liliana Schaefer, Marc Schneider, Michael Kreuter, Andrea Olschewski, Werner Seeger, Horst Olschewski, Malgorzata Wygrecka Please cite this article as: Kwapiszewska G, Gungl A, Wilhelm J, et al. Transcriptome profiling reveals the complexity of pirfenidone effects in IPF. Eur Respir J 2018; in press (https://doi.org/10.1183/13993003.00564-2018). This manuscript has recently been accepted for publication in the European Respiratory Journal. It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. Copyright ©ERS 2018 Copyright 2018 by the European Respiratory Society. Transcriptome profiling reveals the complexity of pirfenidone effects in IPF Grazyna Kwapiszewska1,2, Anna Gungl2, Jochen Wilhelm3†, Leigh M. Marsh1, Helene Thekkekara Puthenparampil1, Katharina Sinn4, Miroslava Didiasova5, Walter Klepetko4, Djuro Kosanovic3, Ralph T. Schermuly3†, Lukasz Wujak5, Benjamin Weiss6, Liliana Schaefer7, Marc Schneider8†, Michael Kreuter8†, Andrea Olschewski1,
    [Show full text]
  • METTL16, Methyltransferase-Like Protein 16: Current Insights Into Structure and Function
    International Journal of Molecular Sciences Review METTL16, Methyltransferase-Like Protein 16: Current Insights into Structure and Function Agnieszka Ruszkowska Department of Structural Chemistry and Biology of Nucleic Acids, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland; [email protected] Abstract: Methyltransferase-like protein 16 (METTL16) is a human RNA methyltransferase that in- stalls m6A marks on U6 small nuclear RNA (U6 snRNA) and S-adenosylmethionine (SAM) synthetase pre-mRNA. METTL16 also controls a significant portion of m6A epitranscriptome by regulating SAM homeostasis. Multiple molecular structures of the N-terminal methyltransferase domain of METTL16, including apo forms and complexes with S-adenosylhomocysteine (SAH) or RNA, provided the structural basis of METTL16 interaction with the coenzyme and substrates, as well as indicated autoinhibitory mechanism of the enzyme activity regulation. Very recent structural and functional studies of vertebrate-conserved regions (VCRs) indicated their crucial role in the interaction with U6 snRNA. METTL16 remains an object of intense studies, as it has been associated with numerous RNA classes, including mRNA, non-coding RNA, long non-coding RNA (lncRNA), and rRNA. Moreover, the interaction between METTL16 and oncogenic lncRNA MALAT1 indicates the existence of METTL16 features specifically recognizing RNA triple helices. Overall, the number of known human m6A methyltransferases has grown from one to five during the last five years. METTL16, CAPAM, and two rRNA methyltransferases, METTL5/TRMT112 and ZCCHC4, have joined the well-known METTL3/METTL14. This work summarizes current knowledge about METTL16 in the landscape of human m6A RNA methyltransferases. Citation: Ruszkowska, A. METTL16, Methyltransferase-Like Protein 16: Keywords: METTL16; m6A methyltransferases; SAM homeostasis; U6 snRNA Current Insights into Structure and Function.
    [Show full text]