Sox9 and Rbpj Differentially Regulate Endothelial to Mesenchymal Transition and Wound Scarring in Murine Endovascular Progenitors
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Mutations and Altered Expression of SERPINF1 in Patients with Familial Otosclerosis Joanna L
Human Molecular Genetics, 2016, Vol. 25, No. 12 2393–2403 doi: 10.1093/hmg/ddw106 Advance Access Publication Date: 7 April 2016 Original Article ORIGINAL ARTICLE Mutations and altered expression of SERPINF1 in patients with familial otosclerosis Joanna L. Ziff1, Michael Crompton1, Harry R.F. Powell2, Jeremy A. Lavy2, Christopher P. Aldren3, Karen P. Steel4,†, Shakeel R. Saeed1,2 and Sally J. Dawson1,* 1UCL Ear Institute, University College London, London WC1X 8EE, UK, 2Royal National Throat Nose and Ear Hospital, London WC1X 8EE, UK, 3Department of ENT Surgery, The Princess Margaret Hospital, Windsor SL4 3SJ, UK and 4Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK *To whom correspondence should be addressed. Tel: þ44 2076798935; Email: [email protected] Abstract Otosclerosis is a relatively common heterogenous condition, characterized by abnormal bone remodelling in the otic capsule leading to fixation of the stapedial footplate and an associated conductive hearing loss. Although familial linkage and candidate gene association studies have been performed in recent years, little progress has been made in identifying disease- causing genes. Here, we used whole-exome sequencing in four families exhibiting dominantly inherited otosclerosis to identify 23 candidate variants (reduced to 9 after segregation analysis) for further investigation in a secondary cohort of 84 familial cases. Multiple mutations were found in the SERPINF1 (Serpin Peptidase Inhibitor, Clade F) gene which encodes PEDF (pigment epithelium-derived factor), a potent inhibitor of angiogenesis and known regulator of bone density. Six rare heterozygous SERPINF1 variants were found in seven patients in our familial otosclerosis cohort; three are missense mutations predicted to be deleterious to protein function. -
Core Transcriptional Regulatory Circuitries in Cancer
Oncogene (2020) 39:6633–6646 https://doi.org/10.1038/s41388-020-01459-w REVIEW ARTICLE Core transcriptional regulatory circuitries in cancer 1 1,2,3 1 2 1,4,5 Ye Chen ● Liang Xu ● Ruby Yu-Tong Lin ● Markus Müschen ● H. Phillip Koeffler Received: 14 June 2020 / Revised: 30 August 2020 / Accepted: 4 September 2020 / Published online: 17 September 2020 © The Author(s) 2020. This article is published with open access Abstract Transcription factors (TFs) coordinate the on-and-off states of gene expression typically in a combinatorial fashion. Studies from embryonic stem cells and other cell types have revealed that a clique of self-regulated core TFs control cell identity and cell state. These core TFs form interconnected feed-forward transcriptional loops to establish and reinforce the cell-type- specific gene-expression program; the ensemble of core TFs and their regulatory loops constitutes core transcriptional regulatory circuitry (CRC). Here, we summarize recent progress in computational reconstitution and biologic exploration of CRCs across various human malignancies, and consolidate the strategy and methodology for CRC discovery. We also discuss the genetic basis and therapeutic vulnerability of CRC, and highlight new frontiers and future efforts for the study of CRC in cancer. Knowledge of CRC in cancer is fundamental to understanding cancer-specific transcriptional addiction, and should provide important insight to both pathobiology and therapeutics. 1234567890();,: 1234567890();,: Introduction genes. Till now, one critical goal in biology remains to understand the composition and hierarchy of transcriptional Transcriptional regulation is one of the fundamental mole- regulatory network in each specified cell type/lineage. -
The Evolving Cardiac Lymphatic Vasculature in Development, Repair and Regeneration
REVIEWS The evolving cardiac lymphatic vasculature in development, repair and regeneration Konstantinos Klaourakis 1,2, Joaquim M. Vieira 1,2,3 ✉ and Paul R. Riley 1,2,3 ✉ Abstract | The lymphatic vasculature has an essential role in maintaining normal fluid balance in tissues and modulating the inflammatory response to injury or pathogens. Disruption of normal development or function of lymphatic vessels can have severe consequences. In the heart, reduced lymphatic function can lead to myocardial oedema and persistent inflammation. Macrophages, which are phagocytic cells of the innate immune system, contribute to cardiac development and to fibrotic repair and regeneration of cardiac tissue after myocardial infarction. In this Review, we discuss the cardiac lymphatic vasculature with a focus on developments over the past 5 years arising from the study of mammalian and zebrafish model organisms. In addition, we examine the interplay between the cardiac lymphatics and macrophages during fibrotic repair and regeneration after myocardial infarction. Finally, we discuss the therapeutic potential of targeting the cardiac lymphatic network to regulate immune cell content and alleviate inflammation in patients with ischaemic heart disease. The circulatory system of vertebrates is composed of two after MI. In this Review, we summarize the current complementary vasculatures, the blood and lymphatic knowledge on the development, structure and function vascular systems1. The blood vasculature is a closed sys- of the cardiac lymphatic vasculature, with an emphasis tem responsible for transporting gases, fluids, nutrients, on breakthroughs over the past 5 years in the study of metabolites and cells to the tissues2. This extravasation of cardiac lymphatic heterogeneity in mice and zebrafish. -
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. -
Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7 -
Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1. -
Isolation and Characterisation of Lymphatic Endothelial Cells From
www.nature.com/scientificreports OPEN Isolation and characterisation of lymphatic endothelial cells from lung tissues afected by lymphangioleiomyomatosis Koichi Nishino1,2*, Yasuhiro Yoshimatsu3,4, Tomoki Muramatsu5, Yasuhito Sekimoto1,2, Keiko Mitani1,2, Etsuko Kobayashi1,2, Shouichi Okamoto1,2, Hiroki Ebana1,2,6,7, Yoshinori Okada8, Masatoshi Kurihara2,6, Kenji Suzuki9, Johji Inazawa5, Kazuhisa Takahashi1, Tetsuro Watabe3 & Kuniaki Seyama1,2 Lymphangioleiomyomatosis (LAM) is a rare pulmonary disease characterised by the proliferation of smooth muscle-like cells (LAM cells), and an abundance of lymphatic vessels in LAM lesions. Studies reported that vascular endothelial growth factor-D (VEGF-D) secreted by LAM cells contributes to LAM-associated lymphangiogenesis, however, the precise mechanisms of lymphangiogenesis and characteristics of lymphatic endothelial cells (LECs) in LAM lesions have not yet been elucidated. In this study, human primary-cultured LECs were obtained both from LAM-afected lung tissues (LAM-LECs) and normal lung tissues (control LECs) using fuorescence-activated cell sorting (FACS). We found that LAM-LECs had signifcantly higher ability of proliferation and migration compared to control LECs. VEGF-D signifcantly promoted migration of LECs but not proliferation of LECs in vitro. cDNA microarray and FACS analysis revealed the expression of vascular endothelial growth factor receptor (VEGFR)-3 and integrin α9 were elevated in LAM-LECs. Inhibition of VEGFR-3 suppressed proliferation and migration of LECs, and blockade of integrin α9 reduced VEGF-D-induced migration of LECs. Our data uncovered the distinct features of LAM-associated LECs, increased proliferation and migration, which may be due to higher expression of VEGFR-3 and integrin α9. Furthermore, we also found VEGF-D/VEGFR-3 and VEGF-D/ integrin α9 signaling play an important role in LAM-associated lymphangiogenesis. -
Targets TFIID and TFIIA to Prevent Activated Transcription
Downloaded from genesdev.cshlp.org on September 26, 2021 - Published by Cold Spring Harbor Laboratory Press The mammalian transcriptional repressor RBP (CBF1) targets TFIID and TFIIA to prevent activated transcription Ivan Olave, Danny Reinberg,1 and Lynne D. Vales2 Department of Biochemistry and 1Howard Hughes Medical Institute, University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School, Piscataway, New Jersey 08854 USA RBP is a cellular protein that functions as a transcriptional repressor in mammalian cells. RBP has elicited great interest lately because of its established roles in regulating gene expression, in Drosophila and mouse development, and as a component of the Notch signal transduction pathway. This report focuses on the mechanism by which RBP represses transcription and thereby regulates expression of a relatively simple, but natural, promoter. The results show that, irrespective of the close proximity between RBP and other transcription factors bound to the promoter, RBP does not occlude binding by these other transcription factors. Instead, RBP interacts with two transcriptional coactivators: dTAFII110, a subunit of TFIID, and TFIIA to repress transcription. The domain of dTAFII110 targeted by RBP is the same domain that interacts with TFIIA, but is disparate from the domain that interacts with Sp1. Repression can be thwarted when stable transcription preinitiation complexes are formed before RBP addition, suggesting that RBP interaction with TFIIA and TFIID perturbs optimal interactions between these coactivators. Consistent with this, interaction between RBP and TFIIA precludes interaction with dTAFII110. This is the first report of a repressor specifically targeting these two coactivators to subvert activated transcription. [Key Words: RBP; transcriptional repression; TFIIA/TFIID targeting] Received November 17, 1997; revised version accepted April 1, 1998. -
140503 IPF Signatures Supplement Withfigs Thorax
Supplementary material for Heterogeneous gene expression signatures correspond to distinct lung pathologies and biomarkers of disease severity in idiopathic pulmonary fibrosis Daryle J. DePianto1*, Sanjay Chandriani1⌘*, Alexander R. Abbas1, Guiquan Jia1, Elsa N. N’Diaye1, Patrick Caplazi1, Steven E. Kauder1, Sabyasachi Biswas1, Satyajit K. Karnik1#, Connie Ha1, Zora Modrusan1, Michael A. Matthay2, Jasleen Kukreja3, Harold R. Collard2, Jackson G. Egen1, Paul J. Wolters2§, and Joseph R. Arron1§ 1Genentech Research and Early Development, South San Francisco, CA 2Department of Medicine, University of California, San Francisco, CA 3Department of Surgery, University of California, San Francisco, CA ⌘Current address: Novartis Institutes for Biomedical Research, Emeryville, CA. #Current address: Gilead Sciences, Foster City, CA. *DJD and SC contributed equally to this manuscript §PJW and JRA co-directed this project Address correspondence to Paul J. Wolters, MD University of California, San Francisco Department of Medicine Box 0111 San Francisco, CA 94143-0111 [email protected] or Joseph R. Arron, MD, PhD Genentech, Inc. MS 231C 1 DNA Way South San Francisco, CA 94080 [email protected] 1 METHODS Human lung tissue samples Tissues were obtained at UCSF from clinical samples from IPF patients at the time of biopsy or lung transplantation. All patients were seen at UCSF and the diagnosis of IPF was established through multidisciplinary review of clinical, radiological, and pathological data according to criteria established by the consensus classification of the American Thoracic Society (ATS) and European Respiratory Society (ERS), Japanese Respiratory Society (JRS), and the Latin American Thoracic Association (ALAT) (ref. 5 in main text). Non-diseased normal lung tissues were procured from lungs not used by the Northern California Transplant Donor Network. -
An RBPJ-Drosophila Model Reveals Dependence of RBPJ Protein Stability on the Formation of Transcription–Regulator Complexes
cells Article An RBPJ-Drosophila Model Reveals Dependence of RBPJ Protein Stability on the Formation of Transcription–Regulator Complexes Bernd M. Gahr 1,2, Franziska Brändle 1, Mirjam Zimmermann 1 and Anja C. Nagel 1,* 1 Institute of Genetics (240), University of Hohenheim, Garbenstr. 30, 70599 Stuttgart, Germany; [email protected] (B.M.G.); [email protected] (F.B.); [email protected] (M.Z.) 2 Present address: Molecular Cardiology, Department of Internal Medicine II, University of Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany * Correspondence: [email protected]; Tel.: +49-711-45922210 Received: 23 August 2019; Accepted: 10 October 2019; Published: 14 October 2019 Abstract: Notch signaling activity governs widespread cellular differentiation in higher animals, including humans, and is involved in several congenital diseases and different forms of cancer. Notch signals are mediated by the transcriptional regulator RBPJ in a complex with activated Notch (NICD). Analysis of Notch pathway regulation in humans is hampered by a partial redundancy of the four Notch receptor copies, yet RBPJ is solitary, allowing its study in model systems. In Drosophila melanogaster, the RBPJ orthologue is encoded by Suppressor of Hairless [Su(H)]. Using genome engineering, we replaced Su(H) by murine RBPJ in order to study its function in the fly. In fact, RBPJ largely substitutes for Su(H)’s function, yet subtle phenotypes reflect increased Notch signaling activity. Accordingly, the binding of RBPJ to Hairless (H) protein, the general Notch antagonist in Drosophila, was considerably reduced compared to that of Su(H). An H-binding defective RBPJLLL mutant matched the respective Su(H)LLL allele: homozygotes were lethal due to extensive Notch hyperactivity. -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
Transcription Factor Gene Expression Profiling and Analysis of SOX Gene Family Transcription Factors in Human Limbal Epithelial
Transcription factor gene expression profiling and analysis of SOX gene family transcription factors in human limbal epithelial progenitor cells Der Naturwissenschaftlichen Fakultät der Friedrich-Alexander-Universität Erlangen-Nürnberg zur Erlangung des Doktorgrades Dr. rer. nat. vorgelegt von Dr. med. Johannes Menzel-Severing aus Bonn Als Dissertation genehmigt von der Naturwissenschaftlichen Fakultät der Friedrich-Alexander-Universität Erlangen-Nürnberg Tag der mündlichen Prüfung: 7. Februar 2018 Vorsitzender des Promotionsorgans: Prof. Dr. Georg Kreimer Gutachter: Prof. Dr. Andreas Feigenspan Prof. Dr. Ursula Schlötzer-Schrehardt 1 INDEX 1. ABSTRACTS Page 1.1. Abstract in English 4 1.2. Zusammenfassung auf Deutsch 7 2. INTRODUCTION 2.1. Anatomy and histology of the cornea and the corneal surface 11 2.2. Homeostasis of corneal epithelium and the limbal stem cell paradigm 13 2.3. The limbal stem cell niche 15 2.4. Cell therapeutic strategies in ocular surface disease 17 2.5. Alternative cell sources for transplantation to the corneal surface 18 2.6. Transcription factors in cell differentiation and reprogramming 21 2.7. Transcription factors in limbal epithelial cells 22 2.8. Research question 25 3. MATERIALS AND METHODS 3.1. Human donor corneas 27 3.2. Laser Capture Microdissection (LCM) 28 3.3. RNA amplification and RT2 profiler PCR arrays 29 3.4. Real-time PCR analysis 33 3.5. Immunohistochemistry 34 3.6. Limbal epithelial cell culture 38 3.7. Transcription-factor knockdown/overexpression in vitro 39 3.8. Proliferation assay 40 3.9. Western blot 40 3.10. Statistical analysis 41 2 4. RESULTS 4.1. Quality control of LCM-isolated and amplified RNA 42 4.2.