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METACYC ID Description A0AR23 GO:0004842 (Ubiquitin-Protein Ligase
Electronic Supplementary Material (ESI) for Integrative Biology This journal is © The Royal Society of Chemistry 2012 Heat Stress Responsive Zostera marina Genes, Southern Population (α=0. -
Zebrafish Disease Models to Study the Pathogenesis of Inherited Manganese Transporter Defects and Provide A
Zebrafish disease models to study the pathogenesis of inherited manganese transporter defects and provide a route for drug discovery Dr Karin Tuschl University College London PhD Supervisors: Dr Philippa Mills & Prof Stephen Wilson A thesis submitted for the degree of Doctor of Philosophy University College London August 2016 Declaration I, Karin Tuschl, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. Part of the work of this thesis has been published in the following articles for which copyright clearance has been obtained (see Appendix): - Tuschl K, et al. Manganese and the brain. Int Rev Neurobiol. 2013. 110:277- 312. - Tuschl K, et al. Mutations in SLC39A14 disrupt manganese homeostasis and cause childhood-onset parkinsonism-dystonia. Nat Comms. 2016. 7:11601. I confirm that these publications were written by me and may therefore partly overlap with my thesis. 2 Abstract Although manganese is required as an essential trace element excessive amounts are neurotoxic and lead to manganism, an extrapyramidal movement disorder associated with deposition of manganese in the basal ganglia. Recently, we have identified the first inborn error of manganese metabolism caused by mutations in SLC30A10, encoding a manganese transporter facilitating biliary manganese excretion. Treatment is limited to chelation therapy with intravenous disodium calcium edetate which is burdensome due to its route of administration and associated with high socioeconomic costs. Whole exome sequencing in patients with inherited hypermanganesaemia and early- onset parkinsonism-dystonia but absent SLC30A10 mutations identified SLC39A14 as a novel disease gene associated with manganese dyshomeostasis. -
Basics on Bioinformafics Lecture 8
Basics on bioinforma-cs Lecture 8 Nunzio D’Agostino [email protected]; [email protected] Protein domain: terminology Superfamily: Proteins that have low sequence identity, but whose structural and functional features suggest a common evolutionary origin. Family: Proteins clustered together into families are clearly evolutionarily related (accepted rule: pairwise residue identity between the proteins >30% ). Domain: A domain is defined as a polypeptide chain or a part of polypeptide chain that can be independently fold into a stable tertiary structure. Domains are also units of function and are not unique to the protein products of one gene or one gene family but instead appear in a variety of proteins. Motif: A pattern of amino acids that is conserved across many proteins and confers a particular function to the protein. Site: Is the binding site where catalysis occurs. The structure and chemical properties of the active site allow the recognition and binding of the substrate. 2 Why protein domain identification? By iden*fying domains we can: o classify a new protein as belonging to a specific family o infer func*onality o infer cellular localizaon of a protein 3 Domain representation-patterns Some biologically significant amino acid paerns (mo*fs) can be summarised in the form of regular expressions. A regular expression is a powerful notaonal algebra that describes a string or a set of strings. One can use them whenever he/she wants to find paerns in strings. The standard notaons for describing regular expressions use these convenons: [AS] = A and S allowed. D = D allowed. x = Any symbol. -
Structure and Function of the Fgd Family of Divergent FYVE Domain Proteins
Biochemistry and Cell Biology Structure and Function of the Fgd Family of Divergent FYVE Domain Proteins Journal: Biochemistry and Cell Biology Manuscript ID bcb-2018-0185.R1 Manuscript Type: Mini Review Date Submitted by the 03-Aug-2018 Author: Complete List of Authors: Eitzen, Gary; University of Alberta Faculty of Medicine and Dentistry Smithers, Cameron C.; University of Alberta, Biochemistry Murray, Allan; University of Alberta Faculty of Medicine and Dentistry Overduin, Michael; University of Alberta Faculty of Medicine and Dentistry Draft Fgd, Pleckstrin Homology domain, FYVE domain, Dbl Homology Domain, Keyword: Rho GEF Is the invited manuscript for consideration in a Special CSMB Special Issue Issue? : https://mc06.manuscriptcentral.com/bcb-pubs Page 1 of 37 Biochemistry and Cell Biology Title: Structure and Function of the Fgd Family of Divergent FYVE Domain Proteins Authors: Gary Eitzen1, Cameron C. Smithers2, Allan G Murray3 and Michael Overduin2* Draft 1Department of Cell Biology, 2Department of Biochemistry, 3Department of Medicine, University of Alberta, Edmonton, Alberta, Canada *Corresponding author. Michael Overduin Telephone: +1 780 492 3518 Fax: +1 780 492-0886 E-mail: [email protected] https://mc06.manuscriptcentral.com/bcb-pubs Biochemistry and Cell Biology Page 2 of 37 Abstract FYVE domains are highly conserved protein modules that typically bind phosphatidylinositol 3-phosphate (PI3P) on the surface of early endosomes. Along with pleckstrin homology (PH) and phox homology (PX) domains, FYVE domains are the principal readers of the phosphoinositide (PI) code that mediate specific recognition of eukaryotic organelles. Of all the human FYVE domain-containing proteins, those within the Faciogenital dysplasia (Fgd) subfamily are particularly divergent, and couple with GTPases to exert unique cellular functions. -
Glycomics Goes Visual and Interactive
Glycomics & Lipidomics Extended Abstract Glycomics goes visual and interactive Alessandra Gastaldello structures attached to each of these sites. Mass spectrometry Abstract (MS) and microarray are high-throughput technologies that are commonly used in glycomics and glycoproteomics, which often result in the generation of large experimental datasets. Glycomics@ExPASy the glycomics tab of the Swiss Institute of Bioinformatics approaches play an essential role in automated Bioinformatics server (www.expasy.org/glycomics) was created analysis and interpretation of such data. This unit describes in 2016 to centralise web-based glycoinformatics resources and discusses the computational tools currently available for developed within an international network of glycoscientists. these analyses, and their glycomics and glycoproteomics The philosophy of this toolbox is to be {glycoscientist AND applications. protein scientist}???friendly with the aim of popularising (a) the use of bioinformatics in glycobiology and (b) the relation A key point in achieving accurate intact glycopeptide between glycobiology and protein-oriented bioinformatics identification is the definition of the glycan composition file resources. The scarcity of bridging data led us to design tools that is used to match experimental with theoretical masses by a as interactive as possible based on database connectivity in glycoproteomics search engine. At present, these files are order to facilitate data exploration and support hypothesis mainly built from searching the literature and/or querying building. The current set of resources is mostly built on top of data sources focused on posttranslational modifications. Most curated or experimental data relative to glycan structures, glycoproteomics search engines include a default composition glycoproteins, host-pathogen interactions and mass file that is readily used when processing MS data. -
Entrez Symbols Name Termid Termdesc 117553 Uba3,Ube1c
Entrez Symbols Name TermID TermDesc 117553 Uba3,Ube1c ubiquitin-like modifier activating enzyme 3 GO:0016881 acid-amino acid ligase activity 299002 G2e3,RGD1310263 G2/M-phase specific E3 ubiquitin ligase GO:0016881 acid-amino acid ligase activity 303614 RGD1310067,Smurf2 SMAD specific E3 ubiquitin protein ligase 2 GO:0016881 acid-amino acid ligase activity 308669 Herc2 hect domain and RLD 2 GO:0016881 acid-amino acid ligase activity 309331 Uhrf2 ubiquitin-like with PHD and ring finger domains 2 GO:0016881 acid-amino acid ligase activity 316395 Hecw2 HECT, C2 and WW domain containing E3 ubiquitin protein ligase 2 GO:0016881 acid-amino acid ligase activity 361866 Hace1 HECT domain and ankyrin repeat containing, E3 ubiquitin protein ligase 1 GO:0016881 acid-amino acid ligase activity 117029 Ccr5,Ckr5,Cmkbr5 chemokine (C-C motif) receptor 5 GO:0003779 actin binding 117538 Waspip,Wip,Wipf1 WAS/WASL interacting protein family, member 1 GO:0003779 actin binding 117557 TM30nm,Tpm3,Tpm5 tropomyosin 3, gamma GO:0003779 actin binding 24779 MGC93554,Slc4a1 solute carrier family 4 (anion exchanger), member 1 GO:0003779 actin binding 24851 Alpha-tm,Tma2,Tmsa,Tpm1 tropomyosin 1, alpha GO:0003779 actin binding 25132 Myo5b,Myr6 myosin Vb GO:0003779 actin binding 25152 Map1a,Mtap1a microtubule-associated protein 1A GO:0003779 actin binding 25230 Add3 adducin 3 (gamma) GO:0003779 actin binding 25386 AQP-2,Aqp2,MGC156502,aquaporin-2aquaporin 2 (collecting duct) GO:0003779 actin binding 25484 MYR5,Myo1e,Myr3 myosin IE GO:0003779 actin binding 25576 14-3-3e1,MGC93547,Ywhah -
University of Leicester, Msc Medical Statistics, Thesis, Wilmar
Thesis MSc in Medical Statistics Department of Health Sciences University of Leicester, United Kingdom Application of Bayesian hierarchical generalized linear models using weakly informative prior distributions to identify rare genetic variant effects on blood pressure Wilmar Igl March 2015 Summary Background Currently rare genetic variants are discussed as a source of \missing heritability" of complex traits. Bayesian hierarchical models were proposed as an efficient method for the estimation and aggregation of conditional effects of rare variants. Here, such models are applied to identify rare variant effects on blood pressure. Methods Empirical data provided by the Genetic Analysis Workshop 19 (2014) included 1,851 Mexican-American individuals with diastolic blood pressure (DBP), systolic blood pressure (SBP), hypertension (HTN) and 461,868 variants from whole- exome sequencing of odd-numbered chromosomes. Bayesian hierarchical generalized linear models using weakly informative prior distributions were applied. Results Associations of rare variants chr1:204214013 (estimate = 39.6, Credible In- terval (CrI) 95% = [25.3, 53.9], Bayesian p = 6:8 × 10−8) in the PLEKHA6 gene and chr11:118518698 (estimate = 32.2, CrI95% = [20.6, 43.9], Bayesian p = 7:0 × 10−8) in the PHLEDB1 gene were identified. Joint effects of grouped rare variants on DBP in 23 genes (Bayesian p = [8:8 × 10−14, 9:3 × 10−8]) and on SBP in 21 genes (Bayesian p = [8:6 × 10−12, 7:8 × 10−8]) in pathways related to hemostasis, sodi- um/calcium transport, ciliary activity, and others were found. No association with hypertension was detected. Conclusions Bayesian hierarchical generalized linear models with weakly informa- tive priors can successfully be applied in exome-wide genetic association analyses of rare variants. -
Comparative Genomics and Functional Annotation of Bacterial Transporters
Physics of Life Reviews 5 (2008) 22–49 www.elsevier.com/locate/plrev Review Comparative genomics and functional annotation of bacterial transporters Mikhail S. Gelfand a,b,∗, Dmitry A. Rodionov a,c a Institute for Information Transmission Problems, Russian Academy of Sciences, Bolshoi Karetny pereulok 19, Moscow 127994, Russia b Department of Bioengineering and Bioinformatics, Moscow State University, Russia c Burnham Institute for Medical Research, La Jolla, CA 92037, USA Received 6 October 2007; received in revised form 8 October 2007; accepted 10 October 2007 Available online 24 October 2007 Communicated by M. Frank-Kamenetskii Abstract Transport proteins are difficult to study experimentally, and because of that their functional characterization trails that of en- zymes. The comparative genomic analysis is a powerful approach to functional annotation of proteins, which makes it possible to utilize the genomic sequence data from thousands of organisms. The use of computational techniques allows one to identify candidate transporters, predict their structure and localization in the membrane, and perform detailed functional annotation, which includes substrate specificity and cellular role. We overview the main techniques of analysis of transporters’ structure and function. We consider the most popular algorithms to identify transmembrane segments in protein sequences and to predict topology of multispanning proteins. We describe the main approaches of the comparative genomics, and how they may be applied to the analysis of transporters, and provide examples showing how combinations of these techniques is used for functional annotation of new transporter specificities in known families, characterization of new families, and prediction of novel transport mechanisms. © 2007 Elsevier B.V. -
PIR Brochure
Protein Information Resource Integrated Protein Informatics Resource for Genomic & Proteomic Research For four decades the Protein Information Resource (PIR) has provided databases and protein sequence analysis tools to the scientific community, including the Protein Sequence Database, which grew out from the Atlas of Protein Sequence and Structure, edited by Margaret Dayhoff [1965-1978]. Currently, PIR major activities include: i) UniProt (Universal Protein Resource) development, ii) iProClass protein data integration and ID mapping, iii) PIRSF protein pir.georgetown.edu classification, and iv) iProLINK protein literature mining and ontology development. UniProt – Universal Protein Resource What is UniProt? UniProt is the central resource for storing and UniProt (Universal Protein Resource) http://www.uniprot.org interconnecting information from large and = + + disparate sources and the most UniProt: the world's most comprehensive catalog of information on proteins comprehensive catalog of protein sequence and functional annotation. UniProt Knowledgebase UniProt Reference UniProt Archive (UniProtKB) Clusters (UniRef) (UniParc) When to use UniProt databases Integration of Swiss-Prot, TrEMBL Non-redundant reference A stable, and PIR-PSD sequences clustered from comprehensive Use UniProtKB to retrieve curated, reliable, Fully classified, richly and accurately UniProtKB and UniParc for archive of all publicly annotated protein sequences with comprehensive or fast available protein comprehensive information on proteins. minimal redundancy and extensive sequence searches at 100%, sequences for Use UniRef to decrease redundancy and cross-references 90%, or 50% identity sequence tracking from: speed up sequence similarity searches. TrEMBL section UniRef100 Swiss-Prot, Computer-annotated protein sequences TrEMBL, PIR-PSD, Use UniParc to access to archived sequences EMBL, Ensembl, IPI, and their source databases. -
Cdna Cloning, Expression and Homology Modeling of a Luciferase from the Firefly Lampyroidea Maculata
Journal of Biochemistry and Molecular Biology, Vol. 39, No. 5, September 2006, pp. 578-585 cDNA Cloning, Expression and Homology Modeling of a Luciferase from the Firefly Lampyroidea maculata Abdo Rahman Emamzadeh1, Saman Hosseinkhani1,*, Majid Sadeghizadeh2, Maryam Nikkhah3, Mohammad Javad Chaichi4 and Mojtaba Mortazavi1 1Department of Biochemistry, Faculty of Basic Sciences, Tarbiat Modarres University, Tehran, Iran 2Department of Genetics, Faculty of Basic Sciences, Tarbiat Modarres University, Tehran, Iran 3Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran 4Department of Chemistry, Mazandaran University, Babolsar, Iran Received 7 April 2006, Accepted 23 May 2006 The cDNA of a firefly luciferase from lantern mRNA of Introduction Lampyroidea maculata has been cloned, sequenced and functionally expressed. The cDNA has an open reading Firefly luciferase (EC 1.13.12.7) is a well-characterized enzyme frame of 1647 bp and codes for a 548-residue-long that is responsible for the bioluminescence reaction. It polypeptide. Noteworthy, sequence comparison as well as catalyzes the oxidation of firefly luciferin with molecular homology modeling showed the highest degree of similarity oxygen in the presence of ATP and Mg2+ to emit yellow-green with H. unmunsana and L. mingrelica luciferases, light (McElroy, 1969; White et al., 1971; DeLuca, 1976; suggesting a close phylogenetic relationship despite the Wood, 1995). The initial reaction catalyzed by firefly geographical distance separation. The deduced amino acid luciferase is the formation of luciferyl adenylate with the sequence of the luciferase gene of firefly L. maculata release of inorganic pyrophosphate. The luciferase-bound showed 93% identity to H. unmunsana. Superposition of luciferyl adenylate reacts rapidly with molecular oxygen to the three-dimensional model of L. -
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, -
Molecular Mechanism of Membrane Targeting by the GRP1 PH Domain
Supplemental Material can be found at: http://www.jlr.org/cgi/content/full/M800150-JLR200/DC1 Molecular mechanism of membrane targeting by the GRP1 PH domain † † † Ju He,* Rachel M. Haney, ,§ Mohsin Vora, Vladislav V. Verkhusha,** Robert V. Stahelin, ,§ and Tatiana G. Kutateladze1,* Department of Pharmacology,* University of Colorado Health Sciences Center, Aurora, CO; † Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, South Bend, IN; Department of Chemistry and Biochemistry and The Walther Center for Cancer Research,§ University of Notre Dame, South Bend, IN; and Department of Anatomy and Structural Biology,** Downloaded from Albert Einstein College of Medicine, Bronx, NY Abstract The general receptor for phosphoinositides iso- Supplementary key words general receptor for phosphoinositides iso- • • • form 1 (GRP1) is recruited to the plasma membrane in re- form 1 pleckstrin homology domain phosphoinositide phosphati- dylinositol 3,4,5-trisphosphate sponse to activation of phosphoinositide 3-kinases and www.jlr.org accumulation of phosphatidylinositol 3,4,5-trisphosphate ʼ [PtdIns(3,4,5)P3]. GRP1 s pleckstrin homology (PH) do- main recognizes PtdIns(3,4,5)P3 with high specificity and af- The signaling lipid phosphatidylinositol 3,4,5-trisphos- finity, however, the precise mechanism of its association phate [PtdIns(3,4,5)P3] is produced in plasma membranes at Albert Einstein College of Medicine Library on July 14, 2008 with membranes remains unclear. Here, we detail the mo- in response to stimulation of cell surface receptors by lecular basis of membrane anchoring by the GRP1 PH do- growth factors and hormones (1). Class I phosphoinositide main. Our data reveal a multivalent membrane docking (PI) 3-kinases phosphorylate the inositol headgroup of the involving PtdIns(3,4,5)P binding, regulated by pH and fa- 3 relatively abundant phosphatidylinositol 4,5-bisphosphate cilitated by electrostatic interactions with other anionic lip- [Ptdns(4,5)P2], transiently elevating the level of PtdIns ids.