The Molecular Biology Database Collection: 2004 Update
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Tyrosine Kinase Oncogenes in Normal Hematopoiesis and Hematological Disease
Oncogene (2002) 21, 3314 ± 3333 ã 2002 Nature Publishing Group All rights reserved 0950 ± 9232/02 $25.00 www.nature.com/onc Tyrosine kinase oncogenes in normal hematopoiesis and hematological disease Blanca Scheijen1,2 and James D Grin*,1,2 1Department of Adult Oncology, Dana-Farber Cancer Institute, 44 Binney Street, Boston, Massachusetts, MA 02115, USA; 2Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA Tyrosine kinase oncogenes are formed as a result of Adaptors do not contain intrinsic catalytic activity but mutations that induce constitutive kinase activity. Many consist of independent functioning interaction modules of these tyrosine kinase oncogenes that are derived from like SH2-domain (mediates binding to phosphotyrosine genes, such as c-Abl, c-Fes, Flt3, c-Fms, c-Kit and residues), SH3-domain (interacts with polyproline-rich PDGFRb, that are normally involved in the regulation of PXXP stretch) or pleckstrin homology (PH) domain hematopoiesis or hematopoietic cell function. Despite (binds to inositol lipids). dierences in structure, normal function, and subcellular The ®rst tyrosine kinase oncogene associated with location, many of the tyrosine kinase oncogenes signal human hematologic disease, Bcr ± Abl, was identi®ed through the same pathways, and typically enhance almost twenty years ago, and there is now evidence for proliferation and prolong viability. They represent involvement of multiple tyrosine kinase oncogenes in excellent potential drug targets, and it is likely that acute and chronic leukemias, lymphomas, and myelo- additional mutations will be identi®ed in other kinases, mas. In each case, the tyrosine kinase activity of the their immediate downstream targets, or in proteins oncogene is constitutively activated by mutations that regulating their function. -
Anti-GRAP Antibody (ARG63124)
Product datasheet [email protected] ARG63124 Package: 100 μg anti-GRAP antibody Store at: -20°C Summary Product Description Goat Polyclonal antibody recognizes GRAP Tested Reactivity Hu Predict Reactivity Ms, Rat, Cow Tested Application WB Host Goat Clonality Polyclonal Isotype IgG Target Name GRAP Antigen Species Human Immunogen C-GFFPRSYVQPVHL Conjugation Un-conjugated Alternate Names GRB2-related adapter protein Application Instructions Application table Application Dilution WB 0.3 - 1 µg/ml Application Note WB: Recommend incubate at RT for 1h. * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Calculated Mw 25 kDa Properties Form Liquid Purification Purified from goat serum by ammonium sulphate precipitation followed by antigen affinity chromatography using the immunizing peptide. Buffer Tris saline (pH 7.3), 0.02% Sodium azide and 0.5% BSA Preservative 0.02% Sodium azide Stabilizer 0.5% BSA Concentration 0.5 mg/ml Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot and store at -20°C or below. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw cycles. Suggest spin the vial prior to opening. The antibody solution should be gently mixed before use. www.arigobio.com 1/2 Note For laboratory research only, not for drug, diagnostic or other use. Bioinformation Database links GeneID: 10750 Human Swiss-port # Q13588 Human Background This gene encodes a member of the GRB2/Sem5/Drk family and functions as a cytoplasmic signaling protein which contains an SH2 domain flanked by two SH3 domains. -
Biological Databases What Is a Database ?
BIOLOGICAL DATABASES WHAT IS A DATABASE ? A structured collection of data held in computer storage; esp. one that incorporates software to make it accessible in a variety of ways; any large collection of information. A collection of data structured searchable (index) -> table of contents updated periodically (release) -> new edition cross-referenced (hyperlinks ) -> links with other db Includes also associated tools (software) necessary for access, updating, information insertion, information deletion…. A database consists of basic units called records or entries. Each record consists of fields, which hold pre-defined data related to the record. For example, a protein database would have protein sequences as records and protein properties as fields (e.g., name of protein, length, amino-acid sequence, …) 2 DATABASES ON THE INTERNET Biological databases often have web interfaces, which allow users to send queries to the databases. Some databases can be accessed by different web servers, each offering a different interface. request query web page result User Web server Database server 3 WHY BIOLOGICAL DATABASES ? Exponential growth in biological data. Data (genomic sequences, 3D structures, 2D gel analysis, MS analysis, Microarrays….) are no longer published in a conventional manner, but directly submitted to databases. Essential tools for biological research. The only way to publish massive amounts of data without using all the paper in the world. 4 NUCLEOTIDES 5 COMPLETE GENOMES Until 2018: Eukaryotes 5262 Prokaryotes 131446 Viruses 14027 6 SOME STATISTICS More than 1000 different ‘biological’ databases Variable size: <100Kb to >20Gb DNA: > 20 Gb Protein: 1 Gb 3D structure: 5 Gb Other: smaller Update frequency: daily to annually to seldom to forget about it . -
Yeast As a Model Organism to Study Diseases of Protein Misfolding
Tiago Fleming de Oliveira Outeiro YEAST AS A MODEL ORGANISM TO STUDY DISEASES OF PROTEIN MISFOLDING Instituto de Ciências Biomédicas de Abel Salazar Universidade do Porto Porto 2004 Tiago Fleming de Oliveira Outeiro YEAST AS A MODEL ORGANISM TO STUDY DISEASES OF PROTEIN MISFOLDING Dissertação de candidatura ao Grau de Doutor em Ciências Biomédicas submetida ao Instituto de Ciências Biomédicas de Abel Salazar. Orientadora - Professora Susan Lindquist Co-orientadora - Professora Maria João Saraiva Para os devidos efeitos, e de acordo com o disposto no n° 2 do Artigo 8 do Decreto-Lei n° 388/70, o autor desta dissertação declara que interveio na concepção e execução do trabalho experimental, na interpretação e discussão dos resultados e na preparação dos manuscriptos publicados e em vias de publicação. Na presente dissertação incluem-se os resultados das seguintes publicações: Outeiro, TF, Lindquist, S, (2003) Yeast cells provide insight into alpha-synuclein biology and pathobiology, Science, 302:1772-5. Willingham S, Outeiro TF, DeVit MJ, Lindquist SL, Muchowski PJ (2003) Yeast genes that enhance the toxicity of a mutant huntingtin fragment or alpha- synuclein, Science, 302:1769-72. Outeiro, TF, et al., Drug screening yields new insight into neurodegeneration, Nature, in press. Table of Contents TABLE OF CONTENTS ACKNOWLEDGEMENTS XIII ABSTRACT XVII RESUMO XIX OVERVIEW XXIII ORGANIZATION OF THE THESIS XXV ABBREVIATIONS XXVII CHAPTER 1. GENERAL INTRODUCTION 3 1.1 PROTEIN FOLDING AND MISFOLDING 3 1.2 CELLULAR QUALITY CONTROL MECHANISMS 6 1.2.1 -
A Large-Scale Overexpression Screen in Saccharomyces Cerevisiae Identifies Previously Uncharacterized Cell Cycle Genes
A large-scale overexpression screen in Saccharomyces cerevisiae identifies previously uncharacterized cell cycle genes Lauren F. Stevenson*, Brian K. Kennedy, and Ed Harlow Massachusetts General Hospital Cancer Center, Building 149, 13th Street, Charlestown, MA 02129 Contributed by Ed Harlow, January 5, 2001 We have undertaken an extensive screen to identify Saccharomyces in some, if not many, instances, effects on the cell cycle might be cerevisiae genes whose products are involved in cell cycle progres- apparent in the absence of complete lethality. For this reason, we sion. We report the identification of 113 genes, including 19 hypo- devised a protocol that would uncover not only those genes whose thetical ORFs, which confer arrest or delay in specific compartments overproduction is lethal, but also those where overproduction of the cell cycle when overexpressed. The collection of genes identi- causes impaired growth. We also reasoned that moderate overpro- fied by this screen overlaps with those identified in loss-of-function duction of proteins might be more physiologically relevant than cdc screens but also includes genes whose products have not previ- dramatic overproduction, therefore we used GAL promoter-driven ously been implicated in cell cycle control. Through analysis of strains libraries expressed from ARS-CEN vectors to control levels of gene lacking these hypothetical ORFs, we have identified a variety of new expression. CDC and checkpoint genes. Materials and Methods ell cycle studies performed with Saccharomyces cerevisiae have Screening of Libraries. Yeast strain K699 (W303 background) was Cserved as a guideline for understanding eukaryotic cell cycle transformed as previously described (14) with the cDNA library or progression. -
Chromosomal Instability and Copy Number Alterations in Barrett's Esophagus and Esophageal Adenocarcinoma Thomas G
Human Cancer Biology Chromosomal Instability and Copy Number Alterations in Barrett's Esophagus and Esophageal Adenocarcinoma Thomas G. Paulson,1,2 Carlo C. Maley,4,5 Xiaohong Li,2 Hongzhe Li,6 Carissa A. Sanchez,1,2 Dennis L. Chao,3 Robert D. Odze,7 Thomas L. Vaughan,2,8 Patricia L. Blount,1,2,10 and Brian J. Reid1,2,9,10 Abstract Purpose: Chromosomal instability, as assessed by many techniques, including DNA content aneuploidy, loss of heterozygosity, and comparative genomic hybridization, has consistently been reported to be common in cancer and rare in normal tissues. Recently, a panel of chromosome instability biomarkers, including loss of heterozygos- ity and DNA content, has been reported to identify patients at high and low risk of pro- gression from Barrett's esophagus (BE) to esophageal adenocarcinoma (EA), but required multiple platforms for implementation. Although chromosomal instability in- volving amplifications and deletions of chromosome regions have been observed in nearly all cancers, copy number alterations (CNA) in premalignant tissues have not been well characterized or evaluated in cohort studies as biomarkers of cancer risk. Experimental Design: We examined CNAs in 98 patients having either BE or EA using Bacterial Artificial Chromosome (BAC) array comparative genomic hybridization to char- acterize CNAs at different stages of progression ranging from early BE to advanced EA. Results: CNAs were rare in early stages (less than high-grade dysplasia) but were pro- gressively more frequent and larger in later stages (high-grade dysplasia and EA), in- cluding high-level amplifications. The number of CNAs correlated highly with DNA content aneuploidy. -
Protein Moonlighting Revealed by Non-Catalytic Phenotypes of Yeast Enzymes
Genetics: Early Online, published on November 10, 2017 as 10.1534/genetics.117.300377 Protein Moonlighting Revealed by Non-Catalytic Phenotypes of Yeast Enzymes Adriana Espinosa-Cantú1, Diana Ascencio1, Selene Herrera-Basurto1, Jiewei Xu2, Assen Roguev2, Nevan J. Krogan2 & Alexander DeLuna1,* 1 Unidad de Genómica Avanzada (Langebio), Centro de Investigación y de Estudios Avanzados del IPN, 36821 Irapuato, Guanajuato, Mexico. 2 Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, California, 94158, USA. *Corresponding author: [email protected] Running title: Genetic Screen for Moonlighting Enzymes Keywords: Protein moonlighting; Systems genetics; Pleiotropy; Phenotype; Metabolism; Amino acid biosynthesis; Saccharomyces cerevisiae 1 Copyright 2017. 1 ABSTRACT 2 A single gene can partake in several biological processes, and therefore gene 3 deletions can lead to different—sometimes unexpected—phenotypes. However, it 4 is not always clear whether such pleiotropy reflects the loss of a unique molecular 5 activity involved in different processes or the loss of a multifunctional protein. Here, 6 using Saccharomyces cerevisiae metabolism as a model, we systematically test 7 the null hypothesis that enzyme phenotypes depend on a single annotated 8 molecular function, namely their catalysis. We screened a set of carefully selected 9 genes by quantifying the contribution of catalysis to gene-deletion phenotypes 10 under different environmental conditions. While most phenotypes were explained 11 by loss of catalysis, slow growth was readily rescued by a catalytically-inactive 12 protein in about one third of the enzymes tested. Such non-catalytic phenotypes 13 were frequent in the Alt1 and Bat2 transaminases and in the isoleucine/valine- 14 biosynthetic enzymes Ilv1 and Ilv2, suggesting novel "moonlighting" activities in 15 these proteins. -
NLRP3 and ASC Differentially Affect the Lung Transcriptome During Pneumococcal Pneumonia
UvA-DARE (Digital Academic Repository) Cell-specific pattern recognition receptor signaling in antibacterial defense van Lieshout, M.H.P. Publication date 2015 Document Version Final published version Link to publication Citation for published version (APA): van Lieshout, M. H. P. (2015). Cell-specific pattern recognition receptor signaling in antibacterial defense. General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl) Download date:30 Sep 2021 Chapter 7 NLRP3 and ASC differentially affect the lung transcriptome during pneumococcal pneumonia American Journal of Respiratory Cell and Molecular Biology 2014 Apr;50(4):699-712 DOI: 10.1165/rcmb.2013-0015OC Miriam H.P. van Lieshout 1,2 Brendon P. Scicluna 1,2 Sandrine Florquin 3 Tom van der Poll 1,2,4 Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands: 1Center of Infection and Immunity Amsterdam 2Center of Experimental and Molecular Medicine 3Department of Pathology 4Division of Infectious Diseases Chapter 7 Abstract Streptococcus (S.) pneumoniae is the most frequently isolated causative pathogen of community-acquired pneumonia, a leading cause of mortality worldwide. -
GRAP (NM 006613) Human Tagged ORF Clone Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for RG208908 GRAP (NM_006613) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: GRAP (NM_006613) Human Tagged ORF Clone Tag: TurboGFP Symbol: GRAP Synonyms: DFNB114 Vector: pCMV6-AC-GFP (PS100010) E. coli Selection: Ampicillin (100 ug/mL) Cell Selection: Neomycin ORF Nucleotide >RG208908 representing NM_006613 Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC ATGGAGTCCGTGGCCCTGTACAGCTTTCAGGCTACAGAGAGCGACGAGCTGGCCTTCAACAAGGGAGACA CACTCAAGATCCTGAACATGGAGGATGACCAGAACTGGTACAAGGCCGAGCTCCGGGGTGTCGAGGGATT TATTCCCAAGAACTACATCCGCGTCAAGCCCCATCCGTGGTACTCGGGCAGGATTTCCCGGCAGCTGGCC GAAGAGATTCTGATGAAGCGGAACCATCTGGGAGCCTTCCTGATCCGGGAGAGTGAGAGCTCCCCAGGGG AGTTCTCTGTGTCTGTGAACTATGGAGACCAGGTGCAGCACTTCAAGGTGCTGCGTGAGGCCTCGGGGAA GTACTTCCTGTGGGAGGAGAAGTTCAACTCCCTCAACGAGCTGGTCGACTTCTACCGCACCACCACCATC GCCAAGAAGCGGCAGATCTTCCTGCGCGACGAGGAGCCCTTGCTCAAGTCACCTGGGGCCTGCTTTGCCC AGGCCCAGTTTGACTTCTCAGCCCAGGACCCCTCGCAGCTCAGCTTCCGCCGTGGCGACATCATTGAGGT CCTGGAGCGCCCAGACCCCCACTGGTGGCGGGGCCGGTCCTGCGGGCGCGTTGGCTTCTTCCCACGGAGT TACGTGCAGCCCGTGCACCTG ACGCGTACGCGGCCGCTCGAG - GFP Tag - GTTTAA Protein Sequence: >RG208908 representing NM_006613 Red=Cloning site Green=Tags(s) MESVALYSFQATESDELAFNKGDTLKILNMEDDQNWYKAELRGVEGFIPKNYIRVKPHPWYSGRISRQLA EEILMKRNHLGAFLIRESESSPGEFSVSVNYGDQVQHFKVLREASGKYFLWEEKFNSLNELVDFYRTTTI -
GRAP Rabbit Pab
Leader in Biomolecular Solutions for Life Science GRAP Rabbit pAb Catalog No.: A15391 Basic Information Background Catalog No. This gene encodes a member of the GRB2/Sem5/Drk family and functions as a A15391 cytoplasmic signaling protein which contains an SH2 domain flanked by two SH3 domains. The SH2 domain interacts with ligand-activated receptors for stem cell factor Observed MW and erythropoietin, and facilitates the formation of a stable complex with the BCR-ABL 36kDa oncoprotein. This protein also associates with the Ras guanine nucleotide exchange factor SOS1 (son of sevenless homolog 1) through its N-terminal SH3 domain. In Calculated MW general, it couples signals from receptor and cytoplasmic tyrosine kinases to the Ras 25kDa signaling pathway. Category Primary antibody Applications WB Cross-Reactivity Human Recommended Dilutions Immunogen Information WB 1:200 - 1:2000 Gene ID Swiss Prot 10750 Q13588 Immunogen Recombinant fusion protein containing a sequence corresponding to amino acids 128-217 of human GRAP (NP_006604.1). Synonyms GRAP Contact Product Information 400-999-6126 Source Isotype Purification Rabbit IgG Affinity purification [email protected] www.abclonal.com.cn Storage Store at -20℃. Avoid freeze / thaw cycles. Buffer: PBS with 0.02% sodium azide,50% glycerol,pH7.3. Validation Data Western blot analysis of extracts of various cell lines, using GRAP antibody (A15391) at 1:1000 dilution. Secondary antibody: HRP Goat Anti-Rabbit IgG (H+L) (AS014) at 1:10000 dilution. Lysates/proteins: 25ug per lane. Blocking buffer: 3% nonfat dry milk in TBST. Detection: ECL Basic Kit (RM00020). Exposure time: 5s. Antibody | Protein | ELISA Kits | Enzyme | NGS | Service For research use only. -
Regulation of Ras Exchange Factors and Cellular Localization of Ras Activation by Lipid Messengers Int Cells
REVIEW ARTICLE published: 04 September 2013 doi: 10.3389/fimmu.2013.00239 Regulation of Ras exchange factors and cellular localization of Ras activation by lipid messengers inT cells Jesse E. Jun1, Ignacio Rubio2 and Jeroen P.Roose 1* 1 Department of Anatomy, University of California San Francisco, San Francisco, CA, USA 2 Institute for Molecular Cell Biology, Center for Sepsis Control and Care (CSCC), University Hospital, Friedrich-Schiller-University, Jena, Germany Edited by: The Ras-MAPK signaling pathway is highly conserved throughout evolution and is acti- Karsten Sauer, The Scripps Research vated downstream of a wide range of receptor stimuli. Ras guanine nucleotide exchange Institute, USA factors (RasGEFs) catalyze GTP loading of Ras and play a pivotal role in regulating receptor- Reviewed by: Kjetil Taskén, University of Oslo, ligand induced Ras activity. In T cells, three families of functionally important RasGEFs are Norway expressed: RasGRF,RasGRP,and Son of Sevenless (SOS)-family GEFs. Early on it was rec- Balbino Alarcon, Consejo Superior de ognized that Ras activation is critical for T cell development and that the RasGEFs play an Investigaciones Cientificas, Spain important role herein. More recent work has revealed that nuances in Ras activation appear *Correspondence: to significantly impactT cell development and selection.These nuances include distinct bio- Jeroen P.Roose, Department of Anatomy, University of California San chemical patterns of analog versus digital Ras activation, differences in cellular localization Francisco, 513 Parnassus Avenue, of Ras activation, and intricate interplays between the RasGEFs during distinctT cell devel- Room HSW-1326, San Francisco, CA opmental stages as revealed by various new mouse models. -
The Yeast Deletion Collection: a Decade of Functional Genomics
YEASTBOOK CELL CYCLE The Yeast Deletion Collection: A Decade of Functional Genomics Guri Giaever and Corey Nislow University of British Columbia, Vancouver, British Columbia, Canada V6T1Z3 ABSTRACT The yeast deletion collections comprise .21,000 mutant strains that carry precise start-to-stop deletions of 6000 open reading frames. This collection includes heterozygous and homozygous diploids, and haploids of both MATa and MATa mating types. The yeast deletion collection, or yeast knockout (YKO) set, represents the first and only complete, systematically constructed deletion collection available for any organism. Conceived during the Saccharomyces cerevisiae sequencing project, work on the project began in 1998 and was completed in 2002. The YKO strains have been used in numerous laboratories in .1000 genome-wide screens. This landmark genome project has inspired development of numerous genome-wide technologies in organisms from yeast to man. Notable spinoff technologies include synthetic genetic array and HIPHOP chemogenomics. In this retrospective, we briefly describe the yeast deletion project and some of its most noteworthy biological contributions and the impact that these collections have had on the yeast research community and on genomics in general. TABLE OF CONTENTS Abstract 451 Yeast as a Model for Molecular Genetics 452 A Brief History of the Saccharomyces Genome Deletion Project 452 Managing the Collection: Cautions and Caveats 453 Early Applications of the Deletion Collection 455 Seminal publications 455 Genome-wide phenotypic screens 456 Early genome-wide screens 458 Comparing genome-wide studies between laboratories: 458 Mitochondrial respiration as a case study: 458 Metrics to assess deletion strain fitness: 458 Large-Scale Phenotypic Screens 459 Cell growth 459 Mating, sporulation, and germination 459 Membrane trafficking 460 Selected environmental stresses 460 Continued Copyright © 2014 by the Genetics Society of America doi: 10.1534/genetics.114.161620 Available freely online through the author-supported open access option.