Gene Expression Profiling and Functional Studies of Astrocytes in SOD1-Related Amyotrophic Lateral Sclerosis

Total Page:16

File Type:pdf, Size:1020Kb

Gene Expression Profiling and Functional Studies of Astrocytes in SOD1-Related Amyotrophic Lateral Sclerosis Gene expression profiling and functional studies of astrocytes in SOD1-related amyotrophic lateral sclerosis David Baker Department of Neuroscience (SITraN) Supervisors: Dr Janine Kirby, Dr Daniel Blackburn and Prof. Dame Pamela Shaw PhD Thesis Submitted March 2015 Abstract Amyotrophic Lateral Sclerosis (ALS) is the most common adult onset motor neuron (MN) disorder, characterised by muscle wasting due to MN death. Astrocytes play an important role in disease progression in the SOD1G93A transgenic mouse model and patients of ALS. Although astrocytes display a selective toxicity to MN, the toxic factor(s) have not been identified. We hypothesise that differential gene expression in SOD1-ALS astrocytes will reveal targets for therapeutic intervention. Microarray analysis was performed upon Laser Capture Microdissected astrocytes isolated from spinal cord of symptomatic (90 day) and late-stage (120 day) SOD1G93A mice and non-transgenic (NTg) littermates, and from post- mortem human SOD1-ALS and control spinal cord. Functional studies were performed using enzymatic activity assays and immunohistochemistry upon spinal cord and in vitro validation studies were performed using murine neonatal cultures of astrocytes, microglia and embryonic MNs and “i-astrocytes” directly converted from human ALS fibroblasts. In murine astrocytes annotation clustering analysis showed increased expression of lysosomal transcripts which were validated by qPCR . Using functional experiments, we have found significantly higher activity of the lysosomal enzyme β-hexosamindase in the spinal cord of SOD1G93A mice. Immune response and phagocytic pathways are also enriched within both datasets, and phagocytosis assays using fluorescently labelled NSC34 cell debris show that SOD1G93A astrocytes engulf significantly higher amounts of neuronal debris compared to NTg controls, highlighting an increased reactivity of astrocytes at symptom onset. Human SOD1- astrocytes show down-regulation of transcripts involved in tight junction formation such as ZO-2, Claudin-5 and Occludin, and we hypothesise that ALS-astrocytes contribute to the breakdown in blood-brain-barrier (BBB) integrity seen in ALS. qPCR confirmed differential expression of BBB-influencing genes such as claudin-5, junctional adhesion molecule 2 and transforming growth factor beta-2. Model BBBs made with i-astrocytes from human patients co-cultured with endothelia show significantly lower transendothelial electrical resistance and dextran-permeability values pointing to an astrocyte role in increased BBB permeability during disease. These studies show the breadth of behaviours displayed by astrocytes during ALS disease progression and will provide an important guide for future therapeutic intervention. i Statement of contribution All of the work in this thesis is my own apart from where stated. ii Acknowledgments First of all, I would like to thank my supervisors (who were numerous!): Dr Laura Ferraiuolo, Dr Daniel Blackburn, Dr Janine Kirby and Professor Pamela Shaw. Your help, along with many of the researchers and PIs present in SITraN, has been greatly appreciated, never less so than in the writing of this thesis. I would also like to thank Dr Brian Kaspar of Ohio State University for allowing me to work in his lab for 3 months of my PhD. It was a once in a lifetime experience and I am extremely grateful to the entire Kaspar lab for their continuing help and friendship. I thank my parents and sister, who have always supported me in whatever I do, even if they do not understand what I am doing! It is no coincidence that I have managed to achieve a PhD after being brought up in such a loving and supportive environment. Finally, and most importantly, I would like to thank my fiancée Nicole, who has been a crutch to me whenever I have needed, and has accepted my travel to America and endless hours spent in the lab and office writing my thesis. Thank you for keeping me grounded. I only have two words left to say: never again. iii Contents Abstract ....................................................................................................................................... i Statement of contribution ......................................................................................................... ii Acknowledgments..................................................................................................................... iii List of Figures ............................................................................................................................. x List of Tables ........................................................................................................................... xiii Abbreviations ........................................................................................................................... xv CHAPTER 1.................................................................................................................................. 1 1. Introduction ....................................................................................................................... 2 1.1 Motor neuron disease ................................................................................................. 2 1.2 Amyotrophic lateral sclerosis ...................................................................................... 2 1.3 Genetic Subtypes of ALS .............................................................................................. 4 1.3.1 Superoxide dismutase 1 ....................................................................................... 7 1.4 Pathology of ALS .......................................................................................................... 9 1.4.1 ALS is a dying back axonopathy with impairment of axonal transport ............... 9 1.4.2 Inclusions ........................................................................................................... 10 1.4.3 Excitotoxicity ...................................................................................................... 11 1.4.4 Oxidative stress and reactive oxygen species (ROS) .......................................... 12 1.4.5 Mitochondrial damage ....................................................................................... 13 1.4.6 Inflammation and immune response ................................................................ 14 1.4.7 RNA processing .................................................................................................. 15 1.5 Non-cell autonomy in ALS ......................................................................................... 16 1.5.1 Astrocytes .......................................................................................................... 18 1.5.2 Astrocytes in ALS ................................................................................................ 22 1.5.3 Microglia ............................................................................................................ 29 1.5.4 Microglia in ALS .................................................................................................. 31 iv 1.5.5 Oligodendrocytes ............................................................................................... 35 1.5.6 The involvement of other cell types in ALS ....................................................... 36 1.6 Gene expression profiling identifies dysregulated pathways in ALS ........................ 38 1.6.1 Microarray technology ....................................................................................... 38 1.6.2 Chip manufacture .............................................................................................. 39 1.6.3 Competing technologies .................................................................................... 40 1.6.4 Application to ALS .............................................................................................. 40 1.7 Summary of the current situation ............................................................................. 43 1.8 Hypothesis and aims ................................................................................................. 45 1.8.1 Microarray of astrocytes from the SOD1G93A mouse model .............................. 45 1.8.2 Microarray of astrocytes from SOD1-ALS human subjects ............................... 46 CHAPTER 2................................................................................................................................ 47 2 Materials and methods .................................................................................................... 48 2.1.1 SOD1G93A transgenic mouse model .................................................................... 48 2.1.2 Cases for human microarray study .................................................................... 48 2.1.3 Chemicals and reagents ..................................................................................... 48 2.2 Methods .................................................................................................................... 50 2.2.1 Gene expression profiling of murine SOD1G93A astrocytes ................................ 50 2.2.2 Quantitative PCR (qPCR) validation ................................................................... 54 2.2.3 Functional studies of murine astrocytes............................................................ 57 2.2.4 Gene expression profiling of human astrocytes ...............................................
Recommended publications
  • KPNA1 Antibody Cat
    KPNA1 Antibody Cat. No.: 5981 Western blot analysis of KPNA1 in Hela cell lysate with KPNA1 antibody at 1μg/mL. Immunocytochemistry of KPNA1 in HeLa cells with KPNA1 antibody at 2.5 μg/mL. Immunofluorescence of KPNA1 in K562 cells with KPNA1 antibody at 20 μg/mL. Specifications HOST SPECIES: Rabbit SPECIES REACTIVITY: Human, Mouse, Rat HOMOLOGY: Predicted species reactivity based on immunogen sequence: Bovine: (100%) KPNA1 antibody was raised against a 15 amino acid synthetic peptide near the amino terminus of human KPNA1. IMMUNOGEN: The immunogen is located within amino acids 30 - 80 of KPNA1. TESTED APPLICATIONS: ELISA, ICC, IF, WB September 30, 2021 1 https://www.prosci-inc.com/kpna1-antibody-5981.html KPNA1 antibody can be used for detection of KPNA1 by Western blot at 1 μg/mL. Antibody can also be used for immunocytochemistry starting at 2.5 μg/mL. For immunofluorescence start at 20 μg/mL. APPLICATIONS: Antibody validated: Western Blot in human samples; Immunocytochemistry in human samples and Immunofluorescence in human samples. All other applications and species not yet tested. POSITIVE CONTROL: 1) Cat. No. 1201 - HeLa Cell Lysate 2) Cat. No. 17-001 - HeLa Cell Slide 3) Cat. No. 17-004 - K-562 Cell Slide Properties PURIFICATION: KPNA1 Antibody is affinity chromatography purified via peptide column. CLONALITY: Polyclonal ISOTYPE: IgG CONJUGATE: Unconjugated PHYSICAL STATE: Liquid BUFFER: KPNA1 Antibody is supplied in PBS containing 0.02% sodium azide. CONCENTRATION: 1 mg/mL KPNA1 antibody can be stored at 4˚C for three months and -20˚C, stable for up to one STORAGE CONDITIONS: year.
    [Show full text]
  • Toxicogenomics Article
    Toxicogenomics Article Discovery of Novel Biomarkers by Microarray Analysis of Peripheral Blood Mononuclear Cell Gene Expression in Benzene-Exposed Workers Matthew S. Forrest,1 Qing Lan,2 Alan E. Hubbard,1 Luoping Zhang,1 Roel Vermeulen,2 Xin Zhao,1 Guilan Li,3 Yen-Ying Wu,1 Min Shen,2 Songnian Yin,3 Stephen J. Chanock,2 Nathaniel Rothman,2 and Martyn T. Smith1 1School of Public Health, University of California, Berkeley, California, USA; 2Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA; 3National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China were then ranked and selected for further exam- Benzene is an industrial chemical and component of gasoline that is an established cause of ination using several forms of statistical analysis. leukemia. To better understand the risk benzene poses, we examined the effect of benzene expo- We also specifically examined the expression sure on peripheral blood mononuclear cell (PBMC) gene expression in a population of shoe- of all cytokine genes on the array under the factory workers with well-characterized occupational exposures using microarrays and real-time a priori hypothesis that these key genes polymerase chain reaction (PCR). PBMC RNA was stabilized in the field and analyzed using a involved in immune function are likely to be comprehensive human array, the U133A/B Affymetrix GeneChip set. A matched analysis of six altered by benzene exposure (Aoyama 1986). exposed–control pairs was performed. A combination of robust multiarray analysis and ordering We then attempted to confirm the array find- of genes using paired t-statistics, along with bootstrapping to control for a 5% familywise error ings for the leading differentially expressed rate, was used to identify differentially expressed genes in a global analysis.
    [Show full text]
  • Acetyl-Coa Synthetase 3 Promotes Bladder Cancer Cell Growth Under Metabolic Stress Jianhao Zhang1, Hongjian Duan1, Zhipeng Feng1,Xinweihan1 and Chaohui Gu2
    Zhang et al. Oncogenesis (2020) 9:46 https://doi.org/10.1038/s41389-020-0230-3 Oncogenesis ARTICLE Open Access Acetyl-CoA synthetase 3 promotes bladder cancer cell growth under metabolic stress Jianhao Zhang1, Hongjian Duan1, Zhipeng Feng1,XinweiHan1 and Chaohui Gu2 Abstract Cancer cells adapt to nutrient-deprived tumor microenvironment during progression via regulating the level and function of metabolic enzymes. Acetyl-coenzyme A (AcCoA) is a key metabolic intermediate that is crucial for cancer cell metabolism, especially under metabolic stress. It is of special significance to decipher the role acetyl-CoA synthetase short chain family (ACSS) in cancer cells confronting metabolic stress. Here we analyzed the generation of lipogenic AcCoA in bladder cancer cells under metabolic stress and found that in bladder urothelial carcinoma (BLCA) cells, the proportion of lipogenic AcCoA generated from glucose were largely reduced under metabolic stress. Our results revealed that ACSS3 was responsible for lipogenic AcCoA synthesis in BLCA cells under metabolic stress. Interestingly, we found that ACSS3 was required for acetate utilization and histone acetylation. Moreover, our data illustrated that ACSS3 promoted BLCA cell growth. In addition, through analyzing clinical samples, we found that both mRNA and protein levels of ACSS3 were dramatically upregulated in BLCA samples in comparison with adjacent controls and BLCA patients with lower ACSS3 expression were entitled with longer overall survival. Our data revealed an oncogenic role of ACSS3 via regulating AcCoA generation in BLCA and provided a promising target in metabolic pathway for BLCA treatment. 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; Introduction acetyl-CoA synthetase short chain family (ACSS), which In cancer cells, considerable number of metabolic ligates acetate and CoA6.
    [Show full text]
  • Environmental Influences on Endothelial Gene Expression
    ENDOTHELIAL CELL GENE EXPRESSION John Matthew Jeff Herbert Supervisors: Prof. Roy Bicknell and Dr. Victoria Heath PhD thesis University of Birmingham August 2012 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT Tumour angiogenesis is a vital process in the pathology of tumour development and metastasis. Targeting markers of tumour endothelium provide a means of targeted destruction of a tumours oxygen and nutrient supply via destruction of tumour vasculature, which in turn ultimately leads to beneficial consequences to patients. Although current anti -angiogenic and vascular targeting strategies help patients, more potently in combination with chemo therapy, there is still a need for more tumour endothelial marker discoveries as current treatments have cardiovascular and other side effects. For the first time, the analyses of in-vivo biotinylation of an embryonic system is performed to obtain putative vascular targets. Also for the first time, deep sequencing is applied to freshly isolated tumour and normal endothelial cells from lung, colon and bladder tissues for the identification of pan-vascular-targets. Integration of the proteomic, deep sequencing, public cDNA libraries and microarrays, delivers 5,892 putative vascular targets to the science community.
    [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]
  • Supplementary Table 3 Complete List of RNA-Sequencing Analysis of Gene Expression Changed by ≥ Tenfold Between Xenograft and Cells Cultured in 10%O2
    Supplementary Table 3 Complete list of RNA-Sequencing analysis of gene expression changed by ≥ tenfold between xenograft and cells cultured in 10%O2 Expr Log2 Ratio Symbol Entrez Gene Name (culture/xenograft) -7.182 PGM5 phosphoglucomutase 5 -6.883 GPBAR1 G protein-coupled bile acid receptor 1 -6.683 CPVL carboxypeptidase, vitellogenic like -6.398 MTMR9LP myotubularin related protein 9-like, pseudogene -6.131 SCN7A sodium voltage-gated channel alpha subunit 7 -6.115 POPDC2 popeye domain containing 2 -6.014 LGI1 leucine rich glioma inactivated 1 -5.86 SCN1A sodium voltage-gated channel alpha subunit 1 -5.713 C6 complement C6 -5.365 ANGPTL1 angiopoietin like 1 -5.327 TNN tenascin N -5.228 DHRS2 dehydrogenase/reductase 2 leucine rich repeat and fibronectin type III domain -5.115 LRFN2 containing 2 -5.076 FOXO6 forkhead box O6 -5.035 ETNPPL ethanolamine-phosphate phospho-lyase -4.993 MYO15A myosin XVA -4.972 IGF1 insulin like growth factor 1 -4.956 DLG2 discs large MAGUK scaffold protein 2 -4.86 SCML4 sex comb on midleg like 4 (Drosophila) Src homology 2 domain containing transforming -4.816 SHD protein D -4.764 PLP1 proteolipid protein 1 -4.764 TSPAN32 tetraspanin 32 -4.713 N4BP3 NEDD4 binding protein 3 -4.705 MYOC myocilin -4.646 CLEC3B C-type lectin domain family 3 member B -4.646 C7 complement C7 -4.62 TGM2 transglutaminase 2 -4.562 COL9A1 collagen type IX alpha 1 chain -4.55 SOSTDC1 sclerostin domain containing 1 -4.55 OGN osteoglycin -4.505 DAPL1 death associated protein like 1 -4.491 C10orf105 chromosome 10 open reading frame 105 -4.491
    [Show full text]
  • Transcriptional Control of Tissue-Resident Memory T Cell Generation
    Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2019 © 2019 Filip Cvetkovski All rights reserved ABSTRACT Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Tissue-resident memory T cells (TRM) are a non-circulating subset of memory that are maintained at sites of pathogen entry and mediate optimal protection against reinfection. Lung TRM can be generated in response to respiratory infection or vaccination, however, the molecular pathways involved in CD4+TRM establishment have not been defined. Here, we performed transcriptional profiling of influenza-specific lung CD4+TRM following influenza infection to identify pathways implicated in CD4+TRM generation and homeostasis. Lung CD4+TRM displayed a unique transcriptional profile distinct from spleen memory, including up-regulation of a gene network induced by the transcription factor IRF4, a known regulator of effector T cell differentiation. In addition, the gene expression profile of lung CD4+TRM was enriched in gene sets previously described in tissue-resident regulatory T cells. Up-regulation of immunomodulatory molecules such as CTLA-4, PD-1, and ICOS, suggested a potential regulatory role for CD4+TRM in tissues. Using loss-of-function genetic experiments in mice, we demonstrate that IRF4 is required for the generation of lung-localized pathogen-specific effector CD4+T cells during acute influenza infection. Influenza-specific IRF4−/− T cells failed to fully express CD44, and maintained high levels of CD62L compared to wild type, suggesting a defect in complete differentiation into lung-tropic effector T cells.
    [Show full text]
  • A SARS-Cov-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing
    A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing Supplementary Information Supplementary Discussion All SARS-CoV-2 protein and gene functions described in the subnetwork appendices, including the text below and the text found in the individual bait subnetworks, are based on the functions of homologous genes from other coronavirus species. These are mainly from SARS-CoV and MERS-CoV, but when available and applicable other related viruses were used to provide insight into function. The SARS-CoV-2 proteins and genes listed here were designed and researched based on the gene alignments provided by Chan et. al. 1 2020 .​ Though we are reasonably sure the genes here are well annotated, we want to note that not every ​ protein has been verified to be expressed or functional during SARS-CoV-2 infections, either in vitro or in vivo. ​ ​ In an effort to be as comprehensive and transparent as possible, we are reporting the sub-networks of these functionally unverified proteins along with the other SARS-CoV-2 proteins. In such cases, we have made notes within the text below, and on the corresponding subnetwork figures, and would advise that more caution be taken when examining these proteins and their molecular interactions. Due to practical limits in our sample preparation and data collection process, we were unable to generate data for proteins corresponding to Nsp3, Orf7b, and Nsp16. Therefore these three genes have been left out of the following literature review of the SARS-CoV-2 proteins and the protein-protein interactions (PPIs) identified in this study.
    [Show full text]
  • Redefining the Specificity of Phosphoinositide-Binding by Human
    bioRxiv preprint doi: https://doi.org/10.1101/2020.06.20.163253; this version posted June 21, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Redefining the specificity of phosphoinositide-binding by human PH domain-containing proteins Nilmani Singh1†, Adriana Reyes-Ordoñez1†, Michael A. Compagnone1, Jesus F. Moreno Castillo1, Benjamin J. Leslie2, Taekjip Ha2,3,4,5, Jie Chen1* 1Department of Cell & Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801; 2Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205; 3Department of Biophysics, Johns Hopkins University, Baltimore, MD 21218; 4Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205; 5Howard Hughes Medical Institute, Baltimore, MD 21205, USA †These authors contributed equally to this work. *Correspondence: [email protected]. bioRxiv preprint doi: https://doi.org/10.1101/2020.06.20.163253; this version posted June 21, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. ABSTRACT Pleckstrin homology (PH) domains are presumed to bind phosphoinositides (PIPs), but specific interaction with and regulation by PIPs for most PH domain-containing proteins are unclear. Here we employed a single-molecule pulldown assay to study interactions of lipid vesicles with full-length proteins in mammalian whole cell lysates.
    [Show full text]
  • 1 Supporting Information for a Microrna Network Regulates
    Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia.
    [Show full text]
  • Supplementary Table 1: Adhesion Genes Data Set
    Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like,
    [Show full text]
  • (KPNA7), a Divergent Member of the Importin a Family of Nuclear Import
    Kelley et al. BMC Cell Biology 2010, 11:63 http://www.biomedcentral.com/1471-2121/11/63 RESEARCH ARTICLE Open Access Karyopherin a7 (KPNA7), a divergent member of the importin a family of nuclear import receptors Joshua B Kelley1, Ashley M Talley1, Adam Spencer1, Daniel Gioeli2, Bryce M Paschal1,3* Abstract Background: Classical nuclear localization signal (NLS) dependent nuclear import is carried out by a heterodimer of importin a and importin b. NLS cargo is recognized by importin a, which is bound by importin b. Importin b mediates translocation of the complex through the central channel of the nuclear pore, and upon reaching the nucleus, RanGTP binding to importin b triggers disassembly of the complex. To date, six importin a family members, encoded by separate genes, have been described in humans. Results: We sequenced and characterized a seventh member of the importin a family of transport factors, karyopherin a 7 (KPNA7), which is most closely related to KPNA2. The domain of KPNA7 that binds Importin b (IBB) is divergent, and shows stronger binding to importin b than the IBB domains from of other importin a family members. With regard to NLS recognition, KPNA7 binds to the retinoblastoma (RB) NLS to a similar degree as KPNA2, but it fails to bind the SV40-NLS and the human nucleoplasmin (NPM) NLS. KPNA7 shows a predominantly nuclear distribution under steady state conditions, which contrasts with KPNA2 which is primarily cytoplasmic. Conclusion: KPNA7 is a novel importin a family member in humans that belongs to the importin a2 subfamily. KPNA7 shows different subcellular localization and NLS binding characteristics compared to other members of the importin a family.
    [Show full text]