Carboxyl-Ester Lipase Maturity-Onset Diabetes of the Young Is

Total Page:16

File Type:pdf, Size:1020Kb

Carboxyl-Ester Lipase Maturity-Onset Diabetes of the Young Is Diabetes Page 2 of 61 Carboxyl-ester lipase Maturity-Onset Diabetes of the Young is Associated with Development of Pancreatic Cysts and Upregulated MAPK Signaling in Secretin- stimulated duodenal fluid Helge Ræder 1,2,3, Fiona E. McAllister4*, Erling Tjora2,3*, Shweta Bhatt1, Ingfrid Haldorsen5,6, Jiang Hu1, Stefan M. Willems4, Mette Vesterhus7, Abdelfattah El Ouaamari1, Manway Liu8, Maria B. Raeder3, Heike Immervoll9,10,11, Dag Hoem12, Georg Dimcevski7 , Pål R. Njolstad2,3, Anders Molven9,10, Steven P Gygi4, Rohit N. Kulkarni1 From the 1Section of Islet Cell Biology and Regenerative Medicine, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA, 2Department of Pediatrics, Haukeland University Hospital, Bergen, Norway; 3Department of Clinical Science, University of Bergen, Bergen, Norway, 4Department of Cell Biology, Harvard Medical School, Boston, MA, USA,5Department of Radiology, Haukeland University Hospital, Bergen, Norway; 6Section for Radiology, Department of Clinical Medicine, University of Bergen, 7Department of Medicine, Haukeland University Hospital, Bergen, Norway, 8Department of Biomedical Engineering, Boston University, Boston, MA,USA , 9The Gade Laboratory for Pathology, Department of Clinical Medicine, University of Bergen, Norway; 10Department of Pathology, Haukeland University Hospital, Bergen, Norway, 11Department of Pathology, Ålesund Hospital, Ålesund, Norway; 12Department of Surgery, Haukeland University Hospital, Bergen, Norway, *,These authors contributed equally. Corresponding author: Helge Raeder, [email protected] 1 Diabetes Publish Ahead of Print, published online September 23, 2013 Page 3 of 61 Diabetes Running title: PANCREATIC CYSTS AND MAPK SIGNALING IN CEL-MODY Original article: Word count, abstract: 200, Word count, main text: 3161, Number of references: 33, Number of figures: 5, Number of tables: 2. ABSTRACT CEL-MODY is a monogenic form of diabetes and pancreatic exocrine dysfunction due to mutations in the carboxyl-ester lipase gene CEL. The pathogenic mechanism for diabetes development is unknown. Since CEL is expressed mainly in pancreatic acinar cells, we asked whether we could find structural pancreatic changes in CEL-MODY subjects during the course of diabetes development. Furthermore, we hypotesized that the diseased pancreas releases proteins which are detectable in pancreatic fluid and potentially reflected activation or inactivation of disease-specific pathways. We therefore investigated non-diabetic and diabetic CEL mutation carriers by pancreatic imaging studies and secretin-stimulated duodenal juice sampling. The secretin-stimulated duodenal juice was studied using cytokine assays, triple-stage mass spectrometry (MS3) and multiplexed mass spectrometry-based measurement of kinase activities. We identified multiple pancreatic cysts in all the eight diabetic mutation carriers but not in any of the four non-diabetic mutation carriers or the six healthy controls. Furthermore, we identified upregulated MAPK target proteins and MAPK-driven cytokines and increased MAPK activity in the secretin-stimulated duodenal juice. These findings show that subjects with CEL- MODY develop multiple pancreatic cysts by the time they develop diabetes and that upregulated MAPK signaling in the pancreatic secretome may reflect the pathophysiological development of pancreatic cysts and diabetes. Keywords: MODY; Carboxyl-ester lipase, pancreatic cysts, proteome profiling; MAPK signaling 2 Diabetes Page 4 of 61 INTRODUCTION Studies of patients with Maturity-onset Diabetes of the Young have provided important insight into disease mechanisms of pancreatic beta cell failure and diabetes development and also contributed to novel treatment strategies based on this insight (1; 2). We have previously reported two families with a human monogenic syndrome of diabetes and pancreatic exocrine dysfunction (maturity-onset diabetes of the young, type 8, MODY8; CEL-MODY;OMIM #609812) caused by mutations in the carboxyl-ester lipase (CEL) gene (3). Patients with CEL mutations develop pancreatic exocrine dysfunction in early childhood (as measured by low fecal elastase levels), accumulate pancreatic fatty tissue, and develop diabetes and clinical malabsorption in their fourth decade of life (3; 4). The CEL gene is primarily expressed in pancreatic acinar cells and lactating mammary tissue, and encodes a digestive enzyme with a role in cholesterol ester digestion (5). Studies of animal models have not been able to explain the disease mechanism of diabetes development in CEL-MODY (6; 7), but cellular studies indicate that mutated CEL protein is misfolded (8). Hence, to gain further insight into the disease mechanism, we further studied human CEL mutation carriers using radiological methods and secretin-stimulated duodenal juice to examine the pancreatic proteome (9). We hypotesized that the diseased pancreas releases proteins which are detectable in pancreatic fluid and potentially reflected activation or inactivation of disease-specific pathways. To optimize the accuracy of the proteomics studies we applied triple-stage mass spectrometry, MS3 (10), and complemented this approach with cytokine assays and MS-based multiplex kinase activity assays (11) to cross-validate our findings. 3 Page 5 of 61 Diabetes RESEARCH DESIGN AND METHODS Patients. We have previously reported various clinical characteristics for the CEL mutation carrying subjects (3). In this study the studied CEL mutation carrying subjects (CEL+) were denoted with the prefix D if they had manifest diabetes (D1, D2, D3 and D4), with the prefix P if they had not yet developed diabetes (P1 or P2), or with the prefix C for the patient with pancreatic ductal adenocarcinoma (C1). The Supplemental Online Appendix contains the corresponding pedigree information. The non-family controls were denoted with the prefix N (N1, N2, N3, N4) for controls in the duodenal juice studies. We sampled duodenal juice from the patients by endoscopy. To enrich for pancreatic factors, we administered intravenous secretin ((Secrelux® Sanofi, Germany. 1 cU/kg, max 70 cU) to the patients and sampled duodenal juice from 30 to 45 minutes later since it has been shown that there is a peak secretion from pancreas in this time interval (12; 13). The controls for the secretin-stimulated duodenal juice studies were recruited from volunteers. The single pancreatic juice specimen from a CEL mutation carrier with PDAC was collected during a classical Whipple procedure. All studies were approved by the Norwegian regional committee for research ethics and the IRB at the Joslin Diabetes Center and performed according to the Helsinki Declaration. We obtained written informed consent from subjects or their parents. Patients were of North-European descent and recruited from the Norwegian MODY Registry. Protocol for pancreatic imaging. MR imaging was performed on a 1.5 T Siemens Avanto running Syngo MR B17 (Erlagen, Germany) using a 12-channel body coil. For clinical and anatomical evaluation of the pancreas a standard abdominal protocol was used: Axial TrueFISP (true Fast Imaging with Steady-state Precision; TR (repetition time) = 2.79 ms, TE (echo time) = 1.17 ms, slice thickness = 4.0 mm, spacing = 0, alfa = 63 degrees, FOV (field of view) = 380 mm x 380 mm, matrix = 156 x 192, acquisition time = 15 s) and axial fat-saturated T2-weighted 4 Diabetes Page 6 of 61 imaging (TR = 1000 ms, TE (echo time) = 90 ms, slice thickness = 5 mm, spacing = 0, alfa = 150 degrees, FOV (field of view) = 350 mm x 350 mm, matrix = 256 x 256, acquisition time = 24 s). For evaluation of the pancreatic and biliary ducts magnetic resonance cholangiopancreaticography (MRCP) was performed: Coronal T2-weigthed imaging (TR = 2000 ms, TE (echo time) = 691 ms, slice thickness = 1.1 mm, spacing = 0, alfa = 140 degrees, FOV (field of view) = 280 mm x 280 mm, matrix = 320 x 320, acquisition time = 5.23 min) with maximum intensity projection (MIP) and multiplanar reformatting (MPR). Cytokine assay. Forty-two cytokines were measured in secretin-stimulated duodenal juice samples (sample volume of 25 microliter), using the MILLIPLEX MAP Human Cytokine/Chemokine - Premixed 42 Plex kit from Millipore (Billerica, MA). This 42-plex kit was used to measure the concentrations of EGF, Eotaxin, FGF-2, Flt-3 ligand, Fractalkine, G- CSF, GM-CSF, GRO, IFN-α2, IFN-γ, IL-10, IL-12 (p40), IL-12 (p70), IL-13, IL-15, IL-17, IL- 1Rα, IL-1α, IL-1β, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IP-10, MCP-1, MCP-3, MDC (CCL22), MIP-1α, MIP-1β, PDGF-AA, PDGF-AB/BB, RANTES, TGF-α, TNF-α, TNF-β, VEGF, sCD40L, sIL-2Rα. All samples were analyzed with a Luminex 200 xMAP system, and MILLIPLEX Analyst Software (VigeneTech, Carlisle, MA) was used to analyse the results. Proteolytic degradation assay. A set of 45 synthetic peptide substrates, each at 1 µM, were incubated with 10 µg pancreatic fluid and reaction buffer containing Tris-Cl (25 mM, pH 7.5), MgCl2 (7.5 mM), EGTA (0.2 mM), β-glycerophosphate (7.5 mM), Na3VO4 (0.1 mM) and DTT (0.1 mM). The reaction was incubated at room temperature for 0, 15, 60 min, after which the reaction was quenched with 100 µL of 1% trifluoroacetic acid (TFA). Twenty five pmol of internal standard stable-isotope labeled substrate peptides was spiked into the quenched reaction. The solution was desalted using Sep-Pak C18 50 mg cartridges (Waters) and dried using vacuum 5 Page 7 of 61 Diabetes centrifugation. The desalted sample was then resuspended in 100 µL of 5% formic acid of which 2 µL was then subjected to analysis by mass spectrometry. Technical duplicates were performed for each sample at each time point. The peptides from proteolytic degradation assays were analysed by LC-MS on a high resolution Exactive Orbitrap mass spectrometer (Thermo). Briefly, a 45 minute gradient was used to separate the peptides from 10-37% solvent B (0.125% formic acid in acentonitrile) at a flow rate of 300 mL/min. LC-MS data was collected from 350-1500 m/z and the extracted ion chromatograms of the light and heavy peptides were used to quantitate the absolute kinase activity and the extent of peptide degradation respectively. Data analysis was performed using Pinpoint (Thermo).
Recommended publications
  • Cyclin D1/Cyclin-Dependent Kinase 4 Interacts with Filamin a and Affects the Migration and Invasion Potential of Breast Cancer Cells
    Published OnlineFirst February 28, 2010; DOI: 10.1158/0008-5472.CAN-08-1108 Tumor and Stem Cell Biology Cancer Research Cyclin D1/Cyclin-Dependent Kinase 4 Interacts with Filamin A and Affects the Migration and Invasion Potential of Breast Cancer Cells Zhijiu Zhong, Wen-Shuz Yeow, Chunhua Zou, Richard Wassell, Chenguang Wang, Richard G. Pestell, Judy N. Quong, and Andrew A. Quong Abstract Cyclin D1 belongs to a family of proteins that regulate progression through the G1-S phase of the cell cycle by binding to cyclin-dependent kinase (cdk)-4 to phosphorylate the retinoblastoma protein and release E2F transcription factors for progression through cell cycle. Several cancers, including breast, colon, and prostate, overexpress the cyclin D1 gene. However, the correlation of cyclin D1 overexpression with E2F target gene regulation or of cdk-dependent cyclin D1 activity with tumor development has not been identified. This suggests that the role of cyclin D1 in oncogenesis may be independent of its function as a cell cycle regulator. One such function is the role of cyclin D1 in cell adhesion and motility. Filamin A (FLNa), a member of the actin-binding filamin protein family, regulates signaling events involved in cell motility and invasion. FLNa has also been associated with a variety of cancers including lung cancer, prostate cancer, melanoma, human bladder cancer, and neuroblastoma. We hypothesized that elevated cyclin D1 facilitates motility in the invasive MDA-MB-231 breast cancer cell line. We show that MDA-MB-231 motility is affected by disturbing cyclin D1 levels or cyclin D1-cdk4/6 kinase activity.
    [Show full text]
  • Supplemental Information to Mammadova-Bach Et Al., “Laminin Α1 Orchestrates VEGFA Functions in the Ecosystem of Colorectal Carcinogenesis”
    Supplemental information to Mammadova-Bach et al., “Laminin α1 orchestrates VEGFA functions in the ecosystem of colorectal carcinogenesis” Supplemental material and methods Cloning of the villin-LMα1 vector The plasmid pBS-villin-promoter containing the 3.5 Kb of the murine villin promoter, the first non coding exon, 5.5 kb of the first intron and 15 nucleotides of the second villin exon, was generated by S. Robine (Institut Curie, Paris, France). The EcoRI site in the multi cloning site was destroyed by fill in ligation with T4 polymerase according to the manufacturer`s instructions (New England Biolabs, Ozyme, Saint Quentin en Yvelines, France). Site directed mutagenesis (GeneEditor in vitro Site-Directed Mutagenesis system, Promega, Charbonnières-les-Bains, France) was then used to introduce a BsiWI site before the start codon of the villin coding sequence using the 5’ phosphorylated primer: 5’CCTTCTCCTCTAGGCTCGCGTACGATGACGTCGGACTTGCGG3’. A double strand annealed oligonucleotide, 5’GGCCGGACGCGTGAATTCGTCGACGC3’ and 5’GGCCGCGTCGACGAATTCACGC GTCC3’ containing restriction site for MluI, EcoRI and SalI were inserted in the NotI site (present in the multi cloning site), generating the plasmid pBS-villin-promoter-MES. The SV40 polyA region of the pEGFP plasmid (Clontech, Ozyme, Saint Quentin Yvelines, France) was amplified by PCR using primers 5’GGCGCCTCTAGATCATAATCAGCCATA3’ and 5’GGCGCCCTTAAGATACATTGATGAGTT3’ before subcloning into the pGEMTeasy vector (Promega, Charbonnières-les-Bains, France). After EcoRI digestion, the SV40 polyA fragment was purified with the NucleoSpin Extract II kit (Machery-Nagel, Hoerdt, France) and then subcloned into the EcoRI site of the plasmid pBS-villin-promoter-MES. Site directed mutagenesis was used to introduce a BsiWI site (5’ phosphorylated AGCGCAGGGAGCGGCGGCCGTACGATGCGCGGCAGCGGCACG3’) before the initiation codon and a MluI site (5’ phosphorylated 1 CCCGGGCCTGAGCCCTAAACGCGTGCCAGCCTCTGCCCTTGG3’) after the stop codon in the full length cDNA coding for the mouse LMα1 in the pCIS vector (kindly provided by P.
    [Show full text]
  • Dog Coat Colour Genetics: a Review Date Published Online: 31/08/2020; 1,2 1 1 3 Rashid Saif *, Ali Iftekhar , Fatima Asif , Mohammad Suliman Alghanem
    www.als-journal.com/ ISSN 2310-5380/ August 2020 Review Article Advancements in Life Sciences – International Quarterly Journal of Biological Sciences ARTICLE INFO Open Access Date Received: 02/05/2020; Date Revised: 20/08/2020; Dog Coat Colour Genetics: A Review Date Published Online: 31/08/2020; 1,2 1 1 3 Rashid Saif *, Ali Iftekhar , Fatima Asif , Mohammad Suliman Alghanem Authors’ Affiliation: 1. Institute of Abstract Biotechnology, Gulab Devi Educational anis lupus familiaris is one of the most beloved pet species with hundreds of world-wide recognized Complex, Lahore - Pakistan breeds, which can be differentiated from each other by specific morphological, behavioral and adoptive 2. Decode Genomics, traits. Morphological characteristics of dog breeds get more attention which can be defined mostly by 323-D, Town II, coat color and its texture, and considered to be incredibly lucrative traits in this valued species. Although Punjab University C Employees Housing the genetic foundation of coat color has been well stated in the literature, but still very little is known about the Scheme, Lahore - growth pattern, hair length and curly coat trait genes. Skin pigmentation is determined by eumelanin and Pakistan 3. Department of pheomelanin switching phenomenon which is under the control of Melanocortin 1 Receptor and Agouti Signaling Biology, Tabuk Protein genes. Genetic variations in the genes involved in pigmentation pathway provide basic understanding of University - Kingdom melanocortin physiology and evolutionary adaptation of this trait. So in this review, we highlighted, gathered and of Saudi Arabia comprehend the genetic mutations, associated and likely to be associated variants in the genes involved in the coat color and texture trait along with their phenotypes.
    [Show full text]
  • Propranolol-Mediated Attenuation of MMP-9 Excretion in Infants with Hemangiomas
    Supplementary Online Content Thaivalappil S, Bauman N, Saieg A, Movius E, Brown KJ, Preciado D. Propranolol-mediated attenuation of MMP-9 excretion in infants with hemangiomas. JAMA Otolaryngol Head Neck Surg. doi:10.1001/jamaoto.2013.4773 eTable. List of All of the Proteins Identified by Proteomics This supplementary material has been provided by the authors to give readers additional information about their work. © 2013 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/01/2021 eTable. List of All of the Proteins Identified by Proteomics Protein Name Prop 12 mo/4 Pred 12 mo/4 Δ Prop to Pred mo mo Myeloperoxidase OS=Homo sapiens GN=MPO 26.00 143.00 ‐117.00 Lactotransferrin OS=Homo sapiens GN=LTF 114.00 205.50 ‐91.50 Matrix metalloproteinase‐9 OS=Homo sapiens GN=MMP9 5.00 36.00 ‐31.00 Neutrophil elastase OS=Homo sapiens GN=ELANE 24.00 48.00 ‐24.00 Bleomycin hydrolase OS=Homo sapiens GN=BLMH 3.00 25.00 ‐22.00 CAP7_HUMAN Azurocidin OS=Homo sapiens GN=AZU1 PE=1 SV=3 4.00 26.00 ‐22.00 S10A8_HUMAN Protein S100‐A8 OS=Homo sapiens GN=S100A8 PE=1 14.67 30.50 ‐15.83 SV=1 IL1F9_HUMAN Interleukin‐1 family member 9 OS=Homo sapiens 1.00 15.00 ‐14.00 GN=IL1F9 PE=1 SV=1 MUC5B_HUMAN Mucin‐5B OS=Homo sapiens GN=MUC5B PE=1 SV=3 2.00 14.00 ‐12.00 MUC4_HUMAN Mucin‐4 OS=Homo sapiens GN=MUC4 PE=1 SV=3 1.00 12.00 ‐11.00 HRG_HUMAN Histidine‐rich glycoprotein OS=Homo sapiens GN=HRG 1.00 12.00 ‐11.00 PE=1 SV=1 TKT_HUMAN Transketolase OS=Homo sapiens GN=TKT PE=1 SV=3 17.00 28.00 ‐11.00 CATG_HUMAN Cathepsin G OS=Homo
    [Show full text]
  • 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]
  • Acinar Cell Apoptosis in Serpini2-Deficient Mice Models Pancreatic Insufficiency
    Acinar Cell Apoptosis in Serpini2-Deficient Mice Models Pancreatic Insufficiency Stacie K. Loftus1*, Jennifer L. Cannons1, Arturo Incao1, Evgenia Pak1, Amy Chen1, Patricia M. Zerfas2, Mark A. Bryant2, Leslie G. Biesecker1, Pamela L. Schwartzberg1, William J. Pavan1 1 Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America, 2 Division of Veterinary Resources, Office of Research Services, National Institutes of Health, Bethesda, Maryland, United States of America Pancreatic insufficiency (PI) when left untreated results in a state of malnutrition due to an inability to absorb nutrients. Frequently, PI is diagnosed as part of a larger clinical presentation in cystic fibrosis or Shwachman–Diamond syndrome. In this study, a mouse model for isolated exocrine PI was identified in a mouse line generated by a transgene insertion. The trait is inherited in an autosomal recessive pattern, and homozygous animals are growth retarded, have abnormal immunity, and have reduced life span. Mice with the disease locus, named pequen˜o (pq), exhibit progressive apoptosis of pancreatic acinar cells with severe exocrine acinar cell loss by 8 wk of age, while the islets and ductal tissue persist. The mutation in pq/pq mice results from a random transgene insertion. Molecular characterization of the transgene insertion site by fluorescent in situ hybridization and genomic deletion mapping identified an approximately 210-kb deletion on Chromosome 3, deleting two genes. One of these genes, Serpini2, encodes a protein that is a member of the serpin family of protease inhibitors. Reintroduction of only the Serpini2 gene by bacterial artificial chromosome transgenic complementation corrected the acinar cell defect as well as body weight and immune phenotypes, showing that deletion of Serpini2 causes the pequen˜o phenotype.
    [Show full text]
  • Transcriptomic Analysis of the Aquaporin (AQP) Gene Family
    Pancreatology 19 (2019) 436e442 Contents lists available at ScienceDirect Pancreatology journal homepage: www.elsevier.com/locate/pan Transcriptomic analysis of the Aquaporin (AQP) gene family interactome identifies a molecular panel of four prognostic markers in patients with pancreatic ductal adenocarcinoma Dimitrios E. Magouliotis a, b, Vasiliki S. Tasiopoulou c, Konstantinos Dimas d, * Nikos Sakellaridis d, Konstantina A. Svokos e, Alexis A. Svokos f, Dimitris Zacharoulis b, a Division of Surgery and Interventional Science, Faculty of Medical Sciences, UCL, London, UK b Department of Surgery, University of Thessaly, Biopolis, Larissa, Greece c Faculty of Medicine, School of Health Sciences, University of Thessaly, Biopolis, Larissa, Greece d Department of Pharmacology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Biopolis, Larissa, Greece e The Warren Alpert Medical School of Brown University, Providence, RI, USA f Riverside Regional Medical Center, Newport News, VA, USA article info abstract Article history: Background: This study aimed to assess the differential gene expression of aquaporin (AQP) gene family Received 14 October 2018 interactome in pancreatic ductal adenocarcinoma (PDAC) using data mining techniques to identify novel Received in revised form candidate genes intervening in the pathogenicity of PDAC. 29 January 2019 Method: Transcriptome data mining techniques were used in order to construct the interactome of the Accepted 9 February 2019 AQP gene family and to determine which genes members are differentially expressed in PDAC as Available online 11 February 2019 compared to controls. The same techniques were used in order to evaluate the potential prognostic role of the differentially expressed genes. Keywords: PDAC Results: Transcriptome microarray data of four GEO datasets were incorporated, including 142 primary Aquaporin tumor samples and 104 normal pancreatic tissue samples.
    [Show full text]
  • Figure S1. DMD Module Network. the Network Is Formed by 260 Genes from Disgenet and 1101 Interactions from STRING. Red Nodes Are the Five Seed Candidate Genes
    Figure S1. DMD module network. The network is formed by 260 genes from DisGeNET and 1101 interactions from STRING. Red nodes are the five seed candidate genes. Figure S2. DMD module network is more connected than a random module of the same size. It is shown the distribution of the largest connected component of 10.000 random modules of the same size of the DMD module network. The green line (x=260) represents the DMD largest connected component, obtaining a z-score=8.9. Figure S3. Shared genes between BMD and DMD signature. A) A meta-analysis of three microarray datasets (GSE3307, GSE13608 and GSE109178) was performed for the identification of differentially expressed genes (DEGs) in BMD muscle biopsies as compared to normal muscle biopsies. Briefly, the GSE13608 dataset included 6 samples of skeletal muscle biopsy from healthy people and 5 samples from BMD patients. Biopsies were taken from either biceps brachii, triceps brachii or deltoid. The GSE3307 dataset included 17 samples of skeletal muscle biopsy from healthy people and 10 samples from BMD patients. The GSE109178 dataset included 14 samples of controls and 11 samples from BMD patients. For both GSE3307 and GSE10917 datasets, biopsies were taken at the time of diagnosis and from the vastus lateralis. For the meta-analysis of GSE13608, GSE3307 and GSE109178, a random effects model of effect size measure was used to integrate gene expression patterns from the two datasets. Genes with an adjusted p value (FDR) < 0.05 and an │effect size│>2 were identified as DEGs and selected for further analysis. A significant number of DEGs (p<0.001) were in common with the DMD signature genes (blue nodes), as determined by a hypergeometric test assessing the significance of the overlap between the BMD DEGs and the number of DMD signature genes B) MCODE analysis of the overlapping genes between BMD DEGs and DMD signature genes.
    [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]
  • Protein Identities in Evs Isolated from U87-MG GBM Cells As Determined by NG LC-MS/MS
    Protein identities in EVs isolated from U87-MG GBM cells as determined by NG LC-MS/MS. No. Accession Description Σ Coverage Σ# Proteins Σ# Unique Peptides Σ# Peptides Σ# PSMs # AAs MW [kDa] calc. pI 1 A8MS94 Putative golgin subfamily A member 2-like protein 5 OS=Homo sapiens PE=5 SV=2 - [GG2L5_HUMAN] 100 1 1 7 88 110 12,03704523 5,681152344 2 P60660 Myosin light polypeptide 6 OS=Homo sapiens GN=MYL6 PE=1 SV=2 - [MYL6_HUMAN] 100 3 5 17 173 151 16,91913397 4,652832031 3 Q6ZYL4 General transcription factor IIH subunit 5 OS=Homo sapiens GN=GTF2H5 PE=1 SV=1 - [TF2H5_HUMAN] 98,59 1 1 4 13 71 8,048185945 4,652832031 4 P60709 Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 - [ACTB_HUMAN] 97,6 5 5 35 917 375 41,70973209 5,478027344 5 P13489 Ribonuclease inhibitor OS=Homo sapiens GN=RNH1 PE=1 SV=2 - [RINI_HUMAN] 96,75 1 12 37 173 461 49,94108966 4,817871094 6 P09382 Galectin-1 OS=Homo sapiens GN=LGALS1 PE=1 SV=2 - [LEG1_HUMAN] 96,3 1 7 14 283 135 14,70620005 5,503417969 7 P60174 Triosephosphate isomerase OS=Homo sapiens GN=TPI1 PE=1 SV=3 - [TPIS_HUMAN] 95,1 3 16 25 375 286 30,77169764 5,922363281 8 P04406 Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 - [G3P_HUMAN] 94,63 2 13 31 509 335 36,03039959 8,455566406 9 Q15185 Prostaglandin E synthase 3 OS=Homo sapiens GN=PTGES3 PE=1 SV=1 - [TEBP_HUMAN] 93,13 1 5 12 74 160 18,68541938 4,538574219 10 P09417 Dihydropteridine reductase OS=Homo sapiens GN=QDPR PE=1 SV=2 - [DHPR_HUMAN] 93,03 1 1 17 69 244 25,77302971 7,371582031 11 P01911 HLA class II histocompatibility antigen,
    [Show full text]
  • Mouse CELA3B ORF Mammalian Expression Plasmid, C-His Tag
    Mouse CELA3B ORF mammalian expression plasmid, C-His tag Catalog Number: MG53134-CH General Information Plasmid Resuspension protocol Gene : chymotrypsin-like elastase family, 1. Centrifuge at 5,000×g for 5 min. member 3B 2. Carefully open the tube and add 100 l of sterile water to Official Symbol : CELA3B dissolve the DNA. Synonym : Ela3; Ela3b; AI504000; 0910001F22Rik; 2310074F01Rik 3. Close the tube and incubate for 10 minutes at room Source : Mouse temperature. cDNA Size: 810bp 4. Briefly vortex the tube and then do a quick spin to RefSeq : NM_026419.2 concentrate the liquid at the bottom. Speed is less than Description 5000×g. Lot : Please refer to the label on the tube 5. Store the plasmid at -20 ℃. Vector : pCMV3-C-His Shipping carrier : The plasmid is ready for: Each tube contains approximately 10 μg of lyophilized plasmid. • Restriction enzyme digestion Storage : • PCR amplification The lyophilized plasmid can be stored at ambient temperature for three months. • E. coli transformation Quality control : • DNA sequencing The plasmid is confirmed by full-length sequencing with primers in the sequencing primer list. E.coli strains for transformation (recommended Sequencing primer list : but not limited) pCMV3-F: 5’ CAGGTGTCCACTCCCAGGTCCAAG 3’ Most commercially available competent cells are appropriate for pcDNA3-R : 5’ GGCAACTAGAAGGCACAGTCGAGG 3’ the plasmid, e.g. TOP10, DH5α and TOP10F´. Or Forward T7 : 5’ TAATACGACTCACTATAGGG 3’ ReverseBGH : 5’ TAGAAGGCACAGTCGAGG 3’ pCMV3-F and pcDNA3-R are designed by Sino Biological Inc. Customers can order the primer pair from any oligonucleotide supplier. Manufactured By Sino Biological Inc., FOR RESEARCH USE ONLY. NOT FOR USE IN HUMANS.
    [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]