A Link Between Intrahepatic Cholestasis and Genetic Variations in Intracellular Trafficking Regulators
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A Large-Scale Conformational Change Couples Membrane Recruitment to Cargo Binding in the AP2 Clathrin Adaptor Complex
A Large-Scale Conformational Change Couples Membrane Recruitment to Cargo Binding in the AP2 Clathrin Adaptor Complex Lauren P. Jackson,1,5 Bernard T. Kelly,1,5 Airlie J. McCoy,1 Thomas Gaffry,2 Leo C. James,3 Brett M. Collins,4 Stefan Ho¨ ning,2 Philip R. Evans,3,* and David J. Owen1,* 1Cambridge Institute for Medical Research, Department of Clinical Biochemistry, University of Cambridge, Hills Road, Cambridge CB2 0XY, UK 2Institute of Biochemistry I and Center for Molecular Medicine Cologne, University of Cologne, Joseph-Stelzmann-Str. 52 50931 Cologne, Germany 3Medical Research Council Laboratory of Molecular Biology, Hills Road, Cambridge CB2 0QH, UK 4Institute for Molecular Bioscience, The University of Queensland, Brisbane QLD 4072, Australia 5These authors contributed equally to this work *Correspondence: [email protected] (P.R.E.), [email protected] (D.J.O.) DOI 10.1016/j.cell.2010.05.006 SUMMARY by clathrin adaptors to an outer polymeric clathrin scaffold (Cheng et al., 2007; Fotin et al., 2004). Clathrin adaptors contain The AP2 adaptor complex (a, b2, s2, and m2 sub- a folded membrane-proximal domain, which binds to phospha- units) crosslinks the endocytic clathrin scaffold to tidyl inositol polyphosphate (PIP) headgroups and/or Arf PtdIns4,5P2-containing membranes and transmem- GTPases in their membrane-attached, GTP-bound forms, and brane protein cargo. In the ‘‘locked’’ cytosolic form, at least one natively unstructured region, which harbors a cla- AP2’s binding sites for the two endocytic motifs, thrin-binding motif (Owen et al., 2004). Transmembrane proteins YxxF on the C-terminal domain of m2 (C-m2) and are generally selected as cargo for incorporation into a CCV through the direct interaction of either widely used, short, linear [ED]xxxL[LI] on s2, are blocked by parts of b2. -
Diagnosing Platelet Secretion Disorders: Examples Cases
Diagnosing platelet secretion disorders: examples cases Martina Daly Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield Disclosures for Martina Daly In compliance with COI policy, ISTH requires the following disclosures to the session audience: Research Support/P.I. No relevant conflicts of interest to declare Employee No relevant conflicts of interest to declare Consultant No relevant conflicts of interest to declare Major Stockholder No relevant conflicts of interest to declare Speakers Bureau No relevant conflicts of interest to declare Honoraria No relevant conflicts of interest to declare Scientific Advisory No relevant conflicts of interest to declare Board Platelet granule release Agonists (FIIa, Collagen, ADP) Signals Activation Shape change Membrane fusion Release of granule contents Platelet storage organelles lysosomes a granules Enzymes including cathepsins Adhesive proteins acid hydrolases Clotting factors and their inhibitors Fibrinolytic factors and their inhibitors Proteases and antiproteases Growth and mitogenic factors Chemokines, cytokines Anti-microbial proteins Membrane glycoproteins dense (d) granules ADP/ATP Serotonin histamine inorganic polyphosphate Platelet a-granule contents Type Prominent components Membrane glycoproteins GPIb, aIIbb3, GPVI Clotting factors VWF, FV, FXI, FII, Fibrinogen, HMWK, FXIII? Clotting inhibitors TFPI, protein S, protease nexin-2 Fibrinolysis components PAI-1, TAFI, a2-antiplasmin, plasminogen, uPA Other protease inhibitors a1-antitrypsin, a2-macroglobulin -
Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
Expression Gene Network Analyses Reveal Molecular Mechanisms And
www.nature.com/scientificreports OPEN Diferential expression and co- expression gene network analyses reveal molecular mechanisms and candidate biomarkers involved in breast muscle myopathies in chicken Eva Pampouille1,2, Christelle Hennequet-Antier1, Christophe Praud1, Amélie Juanchich1, Aurélien Brionne1, Estelle Godet1, Thierry Bordeau1, Fréderic Fagnoul2, Elisabeth Le Bihan-Duval1 & Cécile Berri1* The broiler industry is facing an increasing prevalence of breast myopathies, such as white striping (WS) and wooden breast (WB), and the precise aetiology of these occurrences remains poorly understood. To progress our understanding of the structural changes and molecular pathways involved in these myopathies, a transcriptomic analysis was performed using an 8 × 60 K Agilent chicken microarray and histological study. The study used pectoralis major muscles from three groups: slow-growing animals (n = 8), fast-growing animals visually free from defects (n = 8), or severely afected by both WS and WB (n = 8). In addition, a weighted correlation network analysis was performed to investigate the relationship between modules of co-expressed genes and histological traits. Functional analysis suggested that selection for fast growing and breast meat yield has progressively led to conditions favouring metabolic shifts towards alternative catabolic pathways to produce energy, leading to an adaptive response to oxidative stress and the frst signs of infammatory, regeneration and fbrosis processes. All these processes are intensifed in muscles afected by severe myopathies, in which new mechanisms related to cellular defences and remodelling seem also activated. Furthermore, our study opens new perspectives for myopathy diagnosis by highlighting fne histological phenotypes and genes whose expression was strongly correlated with defects. Te poultry industry relies on the production of fast-growing chickens, which are slaughtered at high weights and intended for cutting and processing. -
EXTENDED CARRIER SCREENING Peace of Mind for Planned Pregnancies
Focusing on Personalised Medicine EXTENDED CARRIER SCREENING Peace of Mind for Planned Pregnancies Extended carrier screening is an important tool for prospective parents to help them determine their risk of having a child affected with a heritable disease. In many cases, parents aren’t aware they are carriers and have no family history due to the rarity of some diseases in the general population. What is covered by the screening? Genomics For Life offers a comprehensive Extended Carrier Screening test, providing prospective parents with the information they require when planning their pregnancy. Extended Carrier Screening has been shown to detect carriers who would not have been considered candidates for traditional risk- based screening. With a simple mouth swab collection, we are able to test for over 419 genes associated with inherited diseases, including Fragile X Syndrome, Cystic Fibrosis and Spinal Muscular Atrophy. The assay has been developed in conjunction with clinical molecular geneticists, and includes genes listed in the NIH Genetic Test Registry. For a list of genes and disorders covered, please see the reverse of this brochure. If your gene of interest is not covered on our Extended Carrier Screening panel, please contact our friendly team to assist you in finding a gene test panel that suits your needs. Why have Extended Carrier Screening? Extended Carrier Screening prior to pregnancy enables couples to learn about their reproductive risk and consider a complete range of reproductive options, including whether or not to become pregnant, whether to use advanced reproductive technologies, such as preimplantation genetic diagnosis, or to use donor gametes. -
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. -
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. -
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 -
Supplementary Materials
1 Supplementary Materials: Supplemental Figure 1. Gene expression profiles of kidneys in the Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice. (A) A heat map of microarray data show the genes that significantly changed up to 2 fold compared between Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice (N=4 mice per group; p<0.05). Data show in log2 (sample/wild-type). 2 Supplemental Figure 2. Sting signaling is essential for immuno-phenotypes of the Fcgr2b-/-lupus mice. (A-C) Flow cytometry analysis of splenocytes isolated from wild-type, Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice at the age of 6-7 months (N= 13-14 per group). Data shown in the percentage of (A) CD4+ ICOS+ cells, (B) B220+ I-Ab+ cells and (C) CD138+ cells. Data show as mean ± SEM (*p < 0.05, **p<0.01 and ***p<0.001). 3 Supplemental Figure 3. Phenotypes of Sting activated dendritic cells. (A) Representative of western blot analysis from immunoprecipitation with Sting of Fcgr2b-/- mice (N= 4). The band was shown in STING protein of activated BMDC with DMXAA at 0, 3 and 6 hr. and phosphorylation of STING at Ser357. (B) Mass spectra of phosphorylation of STING at Ser357 of activated BMDC from Fcgr2b-/- mice after stimulated with DMXAA for 3 hour and followed by immunoprecipitation with STING. (C) Sting-activated BMDC were co-cultured with LYN inhibitor PP2 and analyzed by flow cytometry, which showed the mean fluorescence intensity (MFI) of IAb expressing DC (N = 3 mice per group). 4 Supplemental Table 1. Lists of up and down of regulated proteins Accession No. -
Clathrin-Dependent Mechanisms Modulate the Subcellular Distribution of Class C Vps/HOPS Tether Subunits in Polarized and Nonpolarized Cells Stephanie A
Clathrin-dependent mechanisms modulate the subcellular distribution of class C Vps/HOPS tether subunits in polarized and nonpolarized cells Stephanie A. Zlatic, Emory University Karine Tornieri, Emory University Steven L'Hernault, Emory University Victor Faundez, Emory University Journal Title: Molecular Biology of the Cell Volume: Volume 22, Number 10 Publisher: American Society for Cell Biology | 2011-05-15, Pages 1699-1715 Type of Work: Article | Final Publisher PDF Publisher DOI: 10.1091/mbc.E10-10-0799 Permanent URL: http://pid.emory.edu/ark:/25593/f71wm Final published version: http://www.molbiolcell.org/content/22/10/1699 Copyright information: © 2011 Zlatic et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License (http://creativecommons.org/licenses/by-nc-sa/3.0/). Accessed September 26, 2021 8:16 AM EDT M BoC | ARTICLE Clathrin-dependent mechanisms modulate the subcellular distribution of class C Vps/HOPS tether subunits in polarized and nonpolarized cells Stephanie A. Zlatica,b, Karine Tornierib, Steven W. L’Hernaulta,c,d, and Victor Faundeza,b,d aGraduate Program in Biochemistry, Cell, and Developmental Biology, bDepartment of Cell Biology, cBiology Department, and dCenter for Neurodegenerative Diseases, Emory University, Atlanta, GA 30322 ABSTRACT Coats define the composition of carriers budding from organelles. In addition, Monitoring Editor coats interact with membrane tethers required for vesicular fusion. -
Protein Sorting and Vesicular Traffic in the Golgi Apparatus
The Golgi Apparatus 63 E.G. Berger & J. Roth (eds) © 1997 Birkhauser Verlag Basel/Switzerland Protein sorting and vesicular traffic in the Golgi apparatus M.G. Farquhar1 and H.-P. Hauri2 JDivision ofCellular and Molecular Medicine and Department ofPathology, University ofCalifornia, San Diego, CA 92093-0651, USA 2Department ofPharmacology, Biozelltrum, University ofBasel, CH-4056 Basel, Switzerland Summary 65 Introduction 65 Major routes of protein and membrane traffic to and through the GA 66 Overview oftraffic along the exocytic pathway 66 Models ofGolgi organization 68 Mechanisms of sorting, targeting and transport from the ER 71 Exitfrom the ER occurs at specific export sites 71 Selective transportfrom the ER vs bulk-jlow models 72 Transit through the ER-Golgi intermediate compartment (ERGIC) 74 Other proximal pre-Golgi, pre-ERGIC, smooth ER compartments 76 Mechanisms for retention and retrieval ofresident ER proteins: Current models 79 Transport, processing and sorting by the GA 80 Contributions ofin vitro assays 82 The SNARE hypothesis 82 Golgi compartments and post-translational processing oftransported proteins 83 Golgi-specific functions . 83 How many Golgi compartments are there? 83 Proposed mechanisms for retention and retrieval ofresident Golgi proteins 86 Transmembrane domain retention signals 88 Formation ofinsoluble aggregates too large to enter transport vesicles 88 The kin recognition model 89 Bilayer-mediated sorting 89 Sorting at the TGN 90 Sorting oflysosomal enzymes 92 64 M.G. Farquhar and H.-P. Hauri Sorting and packaging -
Mouse Vipas39 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Vipas39 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Vipas39 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Vipas39 gene (NCBI Reference Sequence: NM_001142580 ; Ensembl: ENSMUSG00000021038 ) is located on Mouse chromosome 12. 20 exons are identified, with the ATG start codon in exon 2 and the TAA stop codon in exon 20 (Transcript: ENSMUST00000072744). Exon 3 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Vipas39 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-213E8 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Mice homozygous for a conditional allele activated by an inducible cre exhibit dry and scaly skin, hair loss, and defects in tail tendon collagen I structure. Exon 3 starts from about 6.38% of the coding region. The knockout of Exon 3 will result in frameshift of the gene. The size of intron 2 for 5'-loxP site insertion: 3170 bp, and the size of intron 3 for 3'-loxP site insertion: 1410 bp. The size of effective cKO region: ~603 bp. The cKO region does not have any other known gene. Page 1 of 8 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 3 4 20 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Vipas39 Homology arm cKO region loxP site Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats.