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Öztürk-Çolak A, Marygold SJ, Antonazzo G, Attrill H, Goutte-Gattat D, Jenkins VK, Matthews BB, Millburn G, Dos Santos G, Tabone CJ. FlyBase: updates to the Drosophila genes and genomes database. Genetics 2024; 227:iyad211. [PMID: 38301657 DOI: 10.1093/genetics/iyad211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 11/27/2023] [Indexed: 02/03/2024] Open
Abstract
FlyBase (flybase.org) is a model organism database and knowledge base about Drosophila melanogaster, commonly known as the fruit fly. Researchers from around the world rely on the genetic, genomic, and functional information available in FlyBase, as well as its tools to view and interrogate these data. In this article, we describe the latest developments and updates to FlyBase. These include the introduction of single-cell RNA sequencing data, improved content and display of functional information, updated orthology pipelines, new chemical reports, and enhancements to our outreach resources.
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Affiliation(s)
- Arzu Öztürk-Çolak
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3DY, UK
| | - Steven J Marygold
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3DY, UK
| | - Giulia Antonazzo
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3DY, UK
| | - Helen Attrill
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3DY, UK
| | - Damien Goutte-Gattat
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3DY, UK
| | - Victoria K Jenkins
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Beverley B Matthews
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Gillian Millburn
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3DY, UK
| | - Gilberto Dos Santos
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Christopher J Tabone
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
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2
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Aleksander SA, Anagnostopoulos AV, Antonazzo G, Arnaboldi V, Attrill H, Becerra A, Bello SM, Blodgett O, Bradford YM, Bult CJ, Cain S, Calvi BR, Carbon S, Chan J, Chen WJ, Cherry JM, Cho J, Crosby MA, De Pons JL, D’Eustachio P, Diamantakis S, Dolan ME, dos Santos G, Dyer S, Ebert D, Engel SR, Fashena D, Fisher M, Foley S, Gibson AC, Gollapally VR, Gramates LS, Grove CA, Hale P, Harris T, Hayman GT, Hu Y, James-Zorn C, Karimi K, Karra K, Kishore R, Kwitek AE, Laulederkind SJF, Lee R, Longden I, Luypaert M, Markarian N, Marygold SJ, Matthews B, McAndrews MS, Millburn G, Miyasato S, Motenko H, Moxon S, Muller HM, Mungall CJ, Muruganujan A, Mushayahama T, Nash RS, Nuin P, Paddock H, Pells T, Perrimon N, Pich C, Quinton-Tulloch M, Raciti D, Ramachandran S, Richardson JE, Gelbart SR, Ruzicka L, Schindelman G, Shaw DR, Sherlock G, Shrivatsav A, Singer A, Smith CM, Smith CL, Smith JR, Stein L, Sternberg PW, Tabone CJ, Thomas PD, Thorat K, Thota J, Tomczuk M, Trovisco V, Tutaj MA, Urbano JM, Van Auken K, Van Slyke CE, Vize PD, Wang Q, Weng S, Westerfield M, Wilming LG, Wong ED, Wright A, Yook K, Zhou P, Zorn A, Zytkovicz M. Updates to the Alliance of Genome Resources central infrastructure. Genetics 2024; 227:iyae049. [PMID: 38552170 DOI: 10.1093/genetics/iyae049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 04/09/2024] Open
Abstract
The Alliance of Genome Resources (Alliance) is an extensible coalition of knowledgebases focused on the genetics and genomics of intensively studied model organisms. The Alliance is organized as individual knowledge centers with strong connections to their research communities and a centralized software infrastructure, discussed here. Model organisms currently represented in the Alliance are budding yeast, Caenorhabditis elegans, Drosophila, zebrafish, frog, laboratory mouse, laboratory rat, and the Gene Ontology Consortium. The project is in a rapid development phase to harmonize knowledge, store it, analyze it, and present it to the community through a web portal, direct downloads, and application programming interfaces (APIs). Here, we focus on developments over the last 2 years. Specifically, we added and enhanced tools for browsing the genome (JBrowse), downloading sequences, mining complex data (AllianceMine), visualizing pathways, full-text searching of the literature (Textpresso), and sequence similarity searching (SequenceServer). We enhanced existing interactive data tables and added an interactive table of paralogs to complement our representation of orthology. To support individual model organism communities, we implemented species-specific "landing pages" and will add disease-specific portals soon; in addition, we support a common community forum implemented in Discourse software. We describe our progress toward a central persistent database to support curation, the data modeling that underpins harmonization, and progress toward a state-of-the-art literature curation system with integrated artificial intelligence and machine learning (AI/ML).
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Affiliation(s)
| | | | | | - Giulia Antonazzo
- Department of Physiology, Development and Neuroscience , University of Cambridge, Downing Street, Cambridge CB2 3DY , UK
| | - Valerio Arnaboldi
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Helen Attrill
- Department of Physiology, Development and Neuroscience , University of Cambridge, Downing Street, Cambridge CB2 3DY , UK
| | - Andrés Becerra
- European Molecular Biology Laboratory, European Bioinformatics Institute , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD , UK
| | - Susan M Bello
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Olin Blodgett
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | | | - Carol J Bult
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Scott Cain
- Informatics and Bio-computing Platform, Ontario Institute for Cancer Research , Toronto, ON M5G0A3 , Canada
| | - Brian R Calvi
- Department of Biology, Indiana University , Bloomington, IN 47408 , USA
| | - Seth Carbon
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory , Berkeley, CA
| | - Juancarlos Chan
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Wen J Chen
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - J Michael Cherry
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - Jaehyoung Cho
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Madeline A Crosby
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Jeffrey L De Pons
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | | | - Stavros Diamantakis
- European Molecular Biology Laboratory, European Bioinformatics Institute , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD , UK
| | - Mary E Dolan
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Gilberto dos Santos
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Sarah Dyer
- European Molecular Biology Laboratory, European Bioinformatics Institute , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD , UK
| | - Dustin Ebert
- Department of Population and Public Health Sciences, University of Southern California , Los Angeles, CA 90033 , USA
| | - Stacia R Engel
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - David Fashena
- Institute of Neuroscience, University of Oregon , Eugene, OR 97403
| | - Malcolm Fisher
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center , 3333 Burnet Ave, Cincinnati, OH 45229 , USA
| | - Saoirse Foley
- Department of Biological Sciences, Carnegie Mellon University , 5000 Forbes Ave, Pittsburgh, PA 15203
| | - Adam C Gibson
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Varun R Gollapally
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - L Sian Gramates
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Christian A Grove
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Paul Hale
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Todd Harris
- Informatics and Bio-computing Platform, Ontario Institute for Cancer Research , Toronto, ON M5G0A3 , Canada
| | - G Thomas Hayman
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Yanhui Hu
- Department of Genetics, Howard Hughes Medical Institute , Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115 , USA
| | - Christina James-Zorn
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center , 3333 Burnet Ave, Cincinnati, OH 45229 , USA
| | - Kamran Karimi
- Department of Biological Sciences, University of Calgary , 507 Campus Dr NW, Calgary, AB T2N 4V8 , Canada
| | - Kalpana Karra
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - Ranjana Kishore
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Anne E Kwitek
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Stanley J F Laulederkind
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Raymond Lee
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Ian Longden
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Manuel Luypaert
- European Molecular Biology Laboratory, European Bioinformatics Institute , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD , UK
| | - Nicholas Markarian
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Steven J Marygold
- Department of Physiology, Development and Neuroscience , University of Cambridge, Downing Street, Cambridge CB2 3DY , UK
| | - Beverley Matthews
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Monica S McAndrews
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Gillian Millburn
- Department of Physiology, Development and Neuroscience , University of Cambridge, Downing Street, Cambridge CB2 3DY , UK
| | - Stuart Miyasato
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - Howie Motenko
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Sierra Moxon
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory , Berkeley, CA
| | - Hans-Michael Muller
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Christopher J Mungall
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory , Berkeley, CA
| | - Anushya Muruganujan
- Department of Population and Public Health Sciences, University of Southern California , Los Angeles, CA 90033 , USA
| | - Tremayne Mushayahama
- Department of Population and Public Health Sciences, University of Southern California , Los Angeles, CA 90033 , USA
| | - Robert S Nash
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - Paulo Nuin
- Informatics and Bio-computing Platform, Ontario Institute for Cancer Research , Toronto, ON M5G0A3 , Canada
| | - Holly Paddock
- Institute of Neuroscience, University of Oregon , Eugene, OR 97403
| | - Troy Pells
- Department of Biological Sciences, University of Calgary , 507 Campus Dr NW, Calgary, AB T2N 4V8 , Canada
| | - Norbert Perrimon
- Department of Genetics, Howard Hughes Medical Institute , Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115 , USA
| | - Christian Pich
- Institute of Neuroscience, University of Oregon , Eugene, OR 97403
| | - Mark Quinton-Tulloch
- European Molecular Biology Laboratory, European Bioinformatics Institute , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD , UK
| | - Daniela Raciti
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | | | | | - Susan Russo Gelbart
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Leyla Ruzicka
- Institute of Neuroscience, University of Oregon , Eugene, OR 97403
| | - Gary Schindelman
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - David R Shaw
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Gavin Sherlock
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - Ajay Shrivatsav
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - Amy Singer
- Institute of Neuroscience, University of Oregon , Eugene, OR 97403
| | - Constance M Smith
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Cynthia L Smith
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Jennifer R Smith
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Lincoln Stein
- Informatics and Bio-computing Platform, Ontario Institute for Cancer Research , Toronto, ON M5G0A3 , Canada
| | - Paul W Sternberg
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Christopher J Tabone
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Paul D Thomas
- Department of Population and Public Health Sciences, University of Southern California , Los Angeles, CA 90033 , USA
| | - Ketaki Thorat
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Jyothi Thota
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Monika Tomczuk
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Vitor Trovisco
- Department of Physiology, Development and Neuroscience , University of Cambridge, Downing Street, Cambridge CB2 3DY , UK
| | - Marek A Tutaj
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Jose-Maria Urbano
- Department of Physiology, Development and Neuroscience , University of Cambridge, Downing Street, Cambridge CB2 3DY , UK
| | - Kimberly Van Auken
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Ceri E Van Slyke
- Institute of Neuroscience, University of Oregon , Eugene, OR 97403
| | - Peter D Vize
- Department of Biological Sciences, University of Calgary , 507 Campus Dr NW, Calgary, AB T2N 4V8 , Canada
| | - Qinghua Wang
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Shuai Weng
- Department of Genetics, Stanford University , Stanford, CA 94305
| | | | - Laurens G Wilming
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Edith D Wong
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - Adam Wright
- Informatics and Bio-computing Platform, Ontario Institute for Cancer Research , Toronto, ON M5G0A3 , Canada
| | - Karen Yook
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Pinglei Zhou
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Aaron Zorn
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center , 3333 Burnet Ave, Cincinnati, OH 45229 , USA
| | - Mark Zytkovicz
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
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3
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Attrill H, Antonazzo G, Goodman JL, Thurmond J, Strelets VB, Brown NH, the FlyBase Consortium. A new experimental evidence-weighted signaling pathway resource in FlyBase. Development 2024; 151:dev202255. [PMID: 38230566 PMCID: PMC10911275 DOI: 10.1242/dev.202255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 01/09/2024] [Indexed: 01/18/2024]
Abstract
Research in model organisms is central to the characterization of signaling pathways in multicellular organisms. Here, we present the comprehensive and systematic curation of 17 Drosophila signaling pathways using the Gene Ontology framework to establish a dynamic resource that has been incorporated into FlyBase, providing visualization and data integration tools to aid research projects. By restricting to experimental evidence reported in the research literature and quantifying the amount of such evidence for each gene in a pathway, we captured the landscape of empirical knowledge of signaling pathways in Drosophila.
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Affiliation(s)
- Helen Attrill
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Giulia Antonazzo
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Joshua L. Goodman
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | - Jim Thurmond
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | | | - Nicholas H. Brown
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
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4
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Aleksander SA, Anagnostopoulos AV, Antonazzo G, Arnaboldi V, Attrill H, Becerra A, Bello SM, Blodgett O, Bradford YM, Bult CJ, Cain S, Calvi BR, Carbon S, Chan J, Chen WJ, Michael Cherry J, Cho J, Crosby MA, De Pons JL, D’Eustachio P, Diamantakis S, Dolan ME, Santos GD, Dyer S, Ebert D, Engel SR, Fashena D, Fisher M, Foley S, Gibson AC, Gollapally VR, Sian Gramates L, Grove CA, Hale P, Harris T, Thomas Hayman G, Hu Y, James-Zorn C, Karimi K, Karra K, Kishore R, Kwitek AE, Laulederkind SJF, Lee R, Longden I, Luypaert M, Markarian N, Marygold SJ, Matthews B, McAndrews MS, Millburn G, Miyasato S, Motenko H, Moxon S, Muller HM, Mungall CJ, Muruganujan A, Mushayahama T, Nash RS, Nuin P, Paddock H, Pells T, Perrimon N, Pich C, Quinton-Tulloch M, Raciti D, Ramachandran S, Richardson JE, Gelbart SR, Ruzicka L, Schindelman G, Shaw DR, Sherlock G, Shrivatsav A, Singer A, Smith CM, Smith CL, Smith JR, Stein L, Sternberg PW, Tabone CJ, Thomas PD, Thorat K, Thota J, Tomczuk M, Trovisco V, Tutaj MA, Urbano JM, Auken KV, Van Slyke CE, Vize PD, Wang Q, Weng S, Westerfield M, Wilming LG, Wong ED, Wright A, Yook K, Zhou P, Zorn A, Zytkovicz M. Updates to the Alliance of Genome Resources Central Infrastructure Alliance of Genome Resources Consortium. bioRxiv 2023:2023.11.20.567935. [PMID: 38045425 PMCID: PMC10690154 DOI: 10.1101/2023.11.20.567935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
The Alliance of Genome Resources (Alliance) is an extensible coalition of knowledgebases focused on the genetics and genomics of intensively-studied model organisms. The Alliance is organized as individual knowledge centers with strong connections to their research communities and a centralized software infrastructure, discussed here. Model organisms currently represented in the Alliance are budding yeast, C. elegans, Drosophila, zebrafish, frog, laboratory mouse, laboratory rat, and the Gene Ontology Consortium. The project is in a rapid development phase to harmonize knowledge, store it, analyze it, and present it to the community through a web portal, direct downloads, and APIs. Here we focus on developments over the last two years. Specifically, we added and enhanced tools for browsing the genome (JBrowse), downloading sequences, mining complex data (AllianceMine), visualizing pathways, full-text searching of the literature (Textpresso), and sequence similarity searching (SequenceServer). We enhanced existing interactive data tables and added an interactive table of paralogs to complement our representation of orthology. To support individual model organism communities, we implemented species-specific "landing pages" and will add disease-specific portals soon; in addition, we support a common community forum implemented in Discourse. We describe our progress towards a central persistent database to support curation, the data modeling that underpins harmonization, and progress towards a state-of-the art literature curation system with integrated Artificial Intelligence and Machine Learning (AI/ML).
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5
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Attrill H. Comparing the history of signalling pathway research using the research publication record of representative genes. MicroPubl Biol 2023; 2023:10.17912/micropub.biology.000998. [PMID: 37954519 PMCID: PMC10638594 DOI: 10.17912/micropub.biology.000998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 10/10/2023] [Accepted: 10/16/2023] [Indexed: 11/14/2023]
Abstract
The development and application of genetic techniques in the fruit fly Drosophila melanogaster underlies some major advances in the understanding of metazoan development and biology. To examine whether the publication record for signalling pathway genes can indicate which factors have shaped pathway research, the publication history of selected genes is used to compare differences in research output over time. This is used to discuss how research trends may be shaped by a variety of factors such as advances in technology, ease of study and importance to human health.
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Affiliation(s)
- Helen Attrill
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, England, United Kingdom
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6
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Attrill H, Antonazzo G, Goodman JL, Thurmond J, Strelets VB, Brown NH. A new experimental evidence-weighted signaling pathway resource in FlyBase. bioRxiv 2023:2023.08.10.552786. [PMID: 37645956 PMCID: PMC10461922 DOI: 10.1101/2023.08.10.552786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Research in model organisms is central to the characterization of signaling pathways in multicellular organisms. Here, we present the systematic curation of 17 Drosophila signaling pathways using the Gene Ontology framework to establish a comprehensive and dynamic resource that has been incorporated into FlyBase, providing visualization and data integration tools to aid research projects. By restricting to experimental evidence reported in the research literature and quantifying the amount of such evidence for each gene in a pathway, we captured the landscape of empirical knowledge of signaling pathways in Drosophila . Summary statement Comprehensive curation of Drosophila signaling pathways and new visual displays of the pathways provides a new FlyBase resource for researchers, and new insights into signaling pathway architecture.
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7
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Hu Y, Comjean A, Attrill H, Antonazzo G, Thurmond J, Chen W, Li F, Chao T, Mohr SE, Brown NH, Perrimon N. PANGEA: a new gene set enrichment tool for Drosophila and common research organisms. Nucleic Acids Res 2023; 51:W419-W426. [PMID: 37125646 PMCID: PMC10320058 DOI: 10.1093/nar/gkad331] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 03/28/2023] [Accepted: 04/29/2023] [Indexed: 05/02/2023] Open
Abstract
Gene set enrichment analysis (GSEA) plays an important role in large-scale data analysis, helping scientists discover the underlying biological patterns over-represented in a gene list resulting from, for example, an 'omics' study. Gene Ontology (GO) annotation is the most frequently used classification mechanism for gene set definition. Here we present a new GSEA tool, PANGEA (PAthway, Network and Gene-set Enrichment Analysis; https://www.flyrnai.org/tools/pangea/), developed to allow a more flexible and configurable approach to data analysis using a variety of classification sets. PANGEA allows GO analysis to be performed on different sets of GO annotations, for example excluding high-throughput studies. Beyond GO, gene sets for pathway annotation and protein complex data from various resources as well as expression and disease annotation from the Alliance of Genome Resources (Alliance). In addition, visualizations of results are enhanced by providing an option to view network of gene set to gene relationships. The tool also allows comparison of multiple input gene lists and accompanying visualisation tools for quick and easy comparison. This new tool will facilitate GSEA for Drosophila and other major model organisms based on high-quality annotated information available for these species.
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Affiliation(s)
- Yanhui Hu
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Aram Comjean
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Helen Attrill
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Giulia Antonazzo
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Jim Thurmond
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | - Weihang Chen
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Fangge Li
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Tiffany Chao
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Stephanie E Mohr
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Nicholas H Brown
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Norbert Perrimon
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
- Howard Hughes Medical Institute, Boston, MA 02138, USA
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8
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Aleksander SA, Balhoff J, Carbon S, Cherry JM, Drabkin HJ, Ebert D, Feuermann M, Gaudet P, Harris NL, Hill DP, Lee R, Mi H, Moxon S, Mungall CJ, Muruganugan A, Mushayahama T, Sternberg PW, Thomas PD, Van Auken K, Ramsey J, Siegele DA, Chisholm RL, Fey P, Aspromonte MC, Nugnes MV, Quaglia F, Tosatto S, Giglio M, Nadendla S, Antonazzo G, Attrill H, Dos Santos G, Marygold S, Strelets V, Tabone CJ, Thurmond J, Zhou P, Ahmed SH, Asanitthong P, Luna Buitrago D, Erdol MN, Gage MC, Ali Kadhum M, Li KYC, Long M, Michalak A, Pesala A, Pritazahra A, Saverimuttu SCC, Su R, Thurlow KE, Lovering RC, Logie C, Oliferenko S, Blake J, Christie K, Corbani L, Dolan ME, Drabkin HJ, Hill DP, Ni L, Sitnikov D, Smith C, Cuzick A, Seager J, Cooper L, Elser J, Jaiswal P, Gupta P, Jaiswal P, Naithani S, Lera-Ramirez M, Rutherford K, Wood V, De Pons JL, Dwinell MR, Hayman GT, Kaldunski ML, Kwitek AE, Laulederkind SJF, Tutaj MA, Vedi M, Wang SJ, D'Eustachio P, Aimo L, Axelsen K, Bridge A, Hyka-Nouspikel N, Morgat A, Aleksander SA, Cherry JM, Engel SR, Karra K, Miyasato SR, Nash RS, Skrzypek MS, Weng S, Wong ED, Bakker E, Berardini TZ, Reiser L, Auchincloss A, Axelsen K, Argoud-Puy G, Blatter MC, Boutet E, Breuza L, Bridge A, Casals-Casas C, Coudert E, Estreicher A, Livia Famiglietti M, Feuermann M, Gos A, Gruaz-Gumowski N, Hulo C, Hyka-Nouspikel N, Jungo F, Le Mercier P, Lieberherr D, Masson P, Morgat A, Pedruzzi I, Pourcel L, Poux S, Rivoire C, Sundaram S, Bateman A, Bowler-Barnett E, Bye-A-Jee H, Denny P, Ignatchenko A, Ishtiaq R, Lock A, Lussi Y, Magrane M, Martin MJ, Orchard S, Raposo P, Speretta E, Tyagi N, Warner K, Zaru R, Diehl AD, Lee R, Chan J, Diamantakis S, Raciti D, Zarowiecki M, Fisher M, James-Zorn C, Ponferrada V, Zorn A, Ramachandran S, Ruzicka L, Westerfield M. The Gene Ontology knowledgebase in 2023. Genetics 2023; 224:iyad031. [PMID: 36866529 PMCID: PMC10158837 DOI: 10.1093/genetics/iyad031] [Citation(s) in RCA: 232] [Impact Index Per Article: 232.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/10/2023] [Accepted: 02/11/2023] [Indexed: 03/04/2023] Open
Abstract
The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.
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Hu Y, Comjean A, Attrill H, Antonazzo G, Thurmond J, Li F, Chao T, Mohr SE, Brown NH, Perrimon N. PANGEA: A New Gene Set Enrichment Tool for Drosophila and Common Research Organisms. bioRxiv 2023:2023.02.20.529262. [PMID: 36865134 PMCID: PMC9980003 DOI: 10.1101/2023.02.20.529262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
Gene set enrichment analysis (GSEA) plays an important role in large-scale data analysis, helping scientists discover the underlying biological patterns over-represented in a gene list resulting from, for example, an 'omics' study. Gene Ontology (GO) annotation is the most frequently used classification mechanism for gene set definition. Here we present a new GSEA tool, PANGEA (PAthway, Network and Gene-set Enrichment Analysis; https://www.flyrnai.org/tools/pangea/ ), developed to allow a more flexible and configurable approach to data analysis using a variety of classification sets. PANGEA allows GO analysis to be performed on different sets of GO annotations, for example excluding high-throughput studies. Beyond GO, gene sets for pathway annotation and protein complex data from various resources as well as expression and disease annotation from the Alliance of Genome Resources (Alliance). In addition, visualisations of results are enhanced by providing an option to view network of gene set to gene relationships. The tool also allows comparison of multiple input gene lists and accompanying visualisation tools for quick and easy comparison. This new tool will facilitate GSEA for Drosophila and other major model organisms based on high-quality annotated information available for these species.
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Affiliation(s)
- Yanhui Hu
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Aram Comjean
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Helen Attrill
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Giulia Antonazzo
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Jim Thurmond
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | - Fangge Li
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Tiffany Chao
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Stephanie E. Mohr
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Nicholas H. Brown
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Norbert Perrimon
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
- Howard Hughes Medical Institute, Boston, MA 02138, USA
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10
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Agapite J, Albou LP, Aleksander SA, Alexander M, Anagnostopoulos AV, Antonazzo G, Argasinska J, Arnaboldi V, Attrill H, Becerra A, Bello SM, Blake JA, Blodgett O, Bradford YM, Bult CJ, Cain S, Calvi BR, Carbon S, Chan J, Chen WJ, Michael Cherry J, Cho J, Christie KR, Crosby MA, Davis P, da Veiga Beltrame E, De Pons JL, D’Eustachio P, Diamantakis S, Dolan ME, dos Santos G, Douglass E, Dunn B, Eagle A, Ebert D, Engel SR, Fashena D, Foley S, Frazer K, Gao S, Gibson AC, Gondwe F, Goodman J, Sian Gramates L, Grove CA, Hale P, Harris T, Thomas Hayman G, Hill DP, Howe DG, Howe KL, Hu Y, Jha S, Kadin JA, Kaufman TC, Kalita P, Karra K, Kishore R, Kwitek AE, Laulederkind SJF, Lee R, Longden I, Luypaert M, MacPherson KA, Martin R, Marygold SJ, Matthews B, McAndrews MS, Millburn G, Miyasato S, Motenko H, Moxon S, Muller HM, Mungall CJ, Muruganujan A, Mushayahama T, Nalabolu HS, Nash RS, Ng P, Nuin P, Paddock H, Paulini M, Perrimon N, Pich C, Quinton-Tulloch M, Raciti D, Ramachandran S, Richardson JE, Gelbart SR, Ruzicka L, Schaper K, Schindelman G, Shimoyama M, Simison M, Shaw DR, Shrivatsav A, Singer A, Skrzypek M, Smith CM, Smith CL, Smith JR, Stein L, Sternberg PW, Tabone CJ, Thomas PD, Thorat K, Thota J, Toro S, Tomczuk M, Trovisco V, Tutaj MA, Tutaj M, Urbano JM, Van Auken K, Van Slyke CE, Wang Q, Wang SJ, Weng S, Westerfield M, Williams G, Wilming LG, Wong ED, Wright A, Yook K, Zarowiecki M, Zhou P, Zytkovicz M. Harmonizing model organism data in the Alliance of Genome Resources. Genetics 2022; 220:iyac022. [PMID: 35380658 PMCID: PMC8982023 DOI: 10.1093/genetics/iyac022] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 01/26/2022] [Indexed: 02/06/2023] Open
Abstract
The Alliance of Genome Resources (the Alliance) is a combined effort of 7 knowledgebase projects: Saccharomyces Genome Database, WormBase, FlyBase, Mouse Genome Database, the Zebrafish Information Network, Rat Genome Database, and the Gene Ontology Resource. The Alliance seeks to provide several benefits: better service to the various communities served by these projects; a harmonized view of data for all biomedical researchers, bioinformaticians, clinicians, and students; and a more sustainable infrastructure. The Alliance has harmonized cross-organism data to provide useful comparative views of gene function, gene expression, and human disease relevance. The basis of the comparative views is shared calls of orthology relationships and the use of common ontologies. The key types of data are alleles and variants, gene function based on gene ontology annotations, phenotypes, association to human disease, gene expression, protein-protein and genetic interactions, and participation in pathways. The information is presented on uniform gene pages that allow facile summarization of information about each gene in each of the 7 organisms covered (budding yeast, roundworm Caenorhabditis elegans, fruit fly, house mouse, zebrafish, brown rat, and human). The harmonized knowledge is freely available on the alliancegenome.org portal, as downloadable files, and by APIs. We expect other existing and emerging knowledge bases to join in the effort to provide the union of useful data and features that each knowledge base currently provides.
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11
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Gramates LS, Agapite J, Attrill H, Calvi BR, Crosby MA, dos Santos G, Goodman JL, Goutte-Gattat D, Jenkins VK, Kaufman T, Larkin A, Matthews BB, Millburn G, Strelets VB. FlyBase: a guided tour of highlighted features. Genetics 2022; 220:6546290. [PMID: 35266522 PMCID: PMC8982030 DOI: 10.1093/genetics/iyac035] [Citation(s) in RCA: 210] [Impact Index Per Article: 105.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 02/23/2022] [Indexed: 11/23/2022] Open
Abstract
FlyBase provides a centralized resource for the genetic and genomic data of Drosophila melanogaster. As FlyBase enters our fourth decade of service to the research community, we reflect on our unique aspects and look forward to our continued collaboration with the larger research and model organism communities. In this study, we emphasize the dedicated reports and tools we have constructed to meet the specialized needs of fly researchers but also to facilitate use by other research communities. We also highlight ways that we support the fly community, including an external resources page, help resources, and multiple avenues by which researchers can interact with FlyBase.
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Affiliation(s)
- L Sian Gramates
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA,Corresponding author: Department of Molecular and Cellular Biology, Harvard University, 16 Divinity Avenue, Cambridge MA 02138, USA.
| | - Julie Agapite
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Helen Attrill
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 1TN, UK
| | - Brian R Calvi
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | - Madeline A Crosby
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Gilberto dos Santos
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Joshua L Goodman
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | - Damien Goutte-Gattat
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 1TN, UK
| | - Victoria K Jenkins
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Thomas Kaufman
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | - Aoife Larkin
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 1TN, UK
| | - Beverley B Matthews
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Gillian Millburn
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 1TN, UK
| | - Victor B Strelets
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
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12
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Liu Y, Li JSS, Rodiger J, Comjean A, Attrill H, Antonazzo G, Brown NH, Hu Y, Perrimon N. FlyPhoneDB: an integrated web-based resource for cell-cell communication prediction in Drosophila. Genetics 2021; 220:6491251. [PMID: 35100387 PMCID: PMC9176295 DOI: 10.1093/genetics/iyab235] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 12/20/2021] [Indexed: 01/02/2023] Open
Abstract
Multicellular organisms rely on cell-cell communication to exchange information necessary for developmental processes and metabolic homeostasis. Cell-cell communication pathways can be inferred from transcriptomic datasets based on ligand-receptor expression. Recently, data generated from single-cell RNA sequencing have enabled ligand-receptor interaction predictions at an unprecedented resolution. While computational methods are available to infer cell-cell communication in vertebrates such a tool does not yet exist for Drosophila. Here, we generated a high-confidence list of ligand-receptor pairs for the major fly signaling pathways and developed FlyPhoneDB, a quantification algorithm that calculates interaction scores to predict ligand-receptor interactions between cells. At the FlyPhoneDB user interface, results are presented in a variety of tabular and graphical formats to facilitate biological interpretation. To illustrate that FlyPhoneDB can effectively identify active ligands and receptors to uncover cell-cell communication events, we applied FlyPhoneDB to Drosophila single-cell RNA sequencing data sets from adult midgut, abdomen, and blood, and demonstrate that FlyPhoneDB can readily identify previously characterized cell-cell communication pathways. Altogether, FlyPhoneDB is an easy-to-use framework that can be used to predict cell-cell communication between cell types from single-cell RNA sequencing data in Drosophila.
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Affiliation(s)
- Yifang Liu
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA,Corresponding author: Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA. ; Corresponding author: Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA.
| | - Joshua Shing Shun Li
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
| | - Jonathan Rodiger
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
| | - Aram Comjean
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
| | - Helen Attrill
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, CB2 3DY, UK
| | - Giulia Antonazzo
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, CB2 3DY, UK
| | - Nicholas H Brown
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, CB2 3DY, UK
| | - Yanhui Hu
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
| | - Norbert Perrimon
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA,Howard Hughes Medical Institute, Boston, MA 02138, USA,Corresponding author: Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA. ; Corresponding author: Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA.
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13
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Saverimuttu SCC, Kramarz B, Rodríguez-López M, Garmiri P, Attrill H, Thurlow KE, Makris M, de Miranda Pinheiro S, Orchard S, Lovering RC. Gene Ontology curation of the blood-brain barrier to improve the analysis of Alzheimer's and other neurological diseases. Database (Oxford) 2021; 2021:baab067. [PMID: 34697638 PMCID: PMC8546235 DOI: 10.1093/database/baab067] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 09/07/2021] [Accepted: 10/06/2021] [Indexed: 01/08/2023]
Abstract
The role of the blood-brain barrier (BBB) in Alzheimer's and other neurodegenerative diseases is still the subject of many studies. However, those studies using high-throughput methods have been compromised by the lack of Gene Ontology (GO) annotations describing the role of proteins in the normal function of the BBB. The GO Consortium provides a gold-standard bioinformatics resource used for analysis and interpretation of large biomedical data sets. However, the GO is also used by other research communities and, therefore, must meet a variety of demands on the breadth and depth of information that is provided. To meet the needs of the Alzheimer's research community we have focused on the GO annotation of the BBB, with over 100 transport or junctional proteins prioritized for annotation. This project has led to a substantial increase in the number of human proteins associated with BBB-relevant GO terms as well as more comprehensive annotation of these proteins in many other processes. Furthermore, data describing the microRNAs that regulate the expression of these priority proteins have also been curated. Thus, this project has increased both the breadth and depth of annotation for these prioritized BBB proteins. Database URLhttps://www.ebi.ac.uk/QuickGO/.
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Affiliation(s)
- Shirin C C Saverimuttu
- Functional Gene Annotation, Pre-clinical and Fundamental Science, Institute of Cardiovascular Science, University College London (UCL), Rayne Building, 5 University Street, London WC1E 6JF, UK
- European Molecular Biology Laboratory, Wellcome Genome Campus, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge CB10 1ST, UK
| | - Barbara Kramarz
- Functional Gene Annotation, Pre-clinical and Fundamental Science, Institute of Cardiovascular Science, University College London (UCL), Rayne Building, 5 University Street, London WC1E 6JF, UK
| | - Milagros Rodríguez-López
- European Molecular Biology Laboratory, Wellcome Genome Campus, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge CB10 1ST, UK
| | - Penelope Garmiri
- European Molecular Biology Laboratory, Wellcome Genome Campus, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge CB10 1ST, UK
| | - Helen Attrill
- FlyBase, Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Katherine E Thurlow
- Functional Gene Annotation, Pre-clinical and Fundamental Science, Institute of Cardiovascular Science, University College London (UCL), Rayne Building, 5 University Street, London WC1E 6JF, UK
| | - Marios Makris
- Functional Gene Annotation, Pre-clinical and Fundamental Science, Institute of Cardiovascular Science, University College London (UCL), Rayne Building, 5 University Street, London WC1E 6JF, UK
| | - Sandra de Miranda Pinheiro
- Functional Gene Annotation, Pre-clinical and Fundamental Science, Institute of Cardiovascular Science, University College London (UCL), Rayne Building, 5 University Street, London WC1E 6JF, UK
| | - Sandra Orchard
- European Molecular Biology Laboratory, Wellcome Genome Campus, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge CB10 1ST, UK
| | - Ruth C Lovering
- Functional Gene Annotation, Pre-clinical and Fundamental Science, Institute of Cardiovascular Science, University College London (UCL), Rayne Building, 5 University Street, London WC1E 6JF, UK
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14
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Larkin A, Marygold SJ, Antonazzo G, Attrill H, Dos Santos G, Garapati PV, Goodman JL, Gramates LS, Millburn G, Strelets VB, Tabone CJ, Thurmond J. FlyBase: updates to the Drosophila melanogaster knowledge base. Nucleic Acids Res 2021; 49:D899-D907. [PMID: 33219682 PMCID: PMC7779046 DOI: 10.1093/nar/gkaa1026] [Citation(s) in RCA: 257] [Impact Index Per Article: 85.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 10/13/2020] [Accepted: 10/22/2020] [Indexed: 01/04/2023] Open
Abstract
FlyBase (flybase.org) is an essential online database for researchers using Drosophila melanogaster as a model organism, facilitating access to a diverse array of information that includes genetic, molecular, genomic and reagent resources. Here, we describe the introduction of several new features at FlyBase, including Pathway Reports, paralog information, disease models based on orthology, customizable tables within reports and overview displays ('ribbons') of expression and disease data. We also describe a variety of recent important updates, including incorporation of a developmental proteome, upgrades to the GAL4 search tab, additional Experimental Tool Reports, migration to JBrowse for genome browsing and improvements to batch queries/downloads and the Fast-Track Your Paper tool.
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Affiliation(s)
- Aoife Larkin
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Steven J Marygold
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Giulia Antonazzo
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Helen Attrill
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Gilberto Dos Santos
- The Biological Laboratories, Harvard University, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - Phani V Garapati
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Joshua L Goodman
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | - L Sian Gramates
- The Biological Laboratories, Harvard University, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - Gillian Millburn
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Victor B Strelets
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | - Christopher J Tabone
- The Biological Laboratories, Harvard University, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - Jim Thurmond
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
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15
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Wood V, Carbon S, Harris MA, Lock A, Engel SR, Hill DP, Van Auken K, Attrill H, Feuermann M, Gaudet P, Lovering RC, Poux S, Rutherford KM, Mungall CJ. Term Matrix: a novel Gene Ontology annotation quality control system based on ontology term co-annotation patterns. Open Biol 2020; 10:200149. [PMID: 32875947 PMCID: PMC7536087 DOI: 10.1098/rsob.200149] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 08/06/2020] [Indexed: 12/11/2022] Open
Abstract
Biological processes are accomplished by the coordinated action of gene products. Gene products often participate in multiple processes, and can therefore be annotated to multiple Gene Ontology (GO) terms. Nevertheless, processes that are functionally, temporally and/or spatially distant may have few gene products in common, and co-annotation to unrelated processes probably reflects errors in literature curation, ontology structure or automated annotation pipelines. We have developed an annotation quality control workflow that uses rules based on mutually exclusive processes to detect annotation errors, based on and validated by case studies including the three we present here: fission yeast protein-coding gene annotations over time; annotations for cohesin complex subunits in human and model species; and annotations using a selected set of GO biological process terms in human and five model species. For each case study, we reviewed available GO annotations, identified pairs of biological processes which are unlikely to be correctly co-annotated to the same gene products (e.g. amino acid metabolism and cytokinesis), and traced erroneous annotations to their sources. To date we have generated 107 quality control rules, and corrected 289 manual annotations in eukaryotes and over 52 700 automatically propagated annotations across all taxa.
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Affiliation(s)
- Valerie Wood
- Cambridge Systems Biology Centre, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK
- Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK
| | - Seth Carbon
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Midori A. Harris
- Cambridge Systems Biology Centre, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK
- Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK
| | - Antonia Lock
- Department of Genetics, Evolution and Environment, University College London, London WC1E 6B, UK
| | - Stacia R. Engel
- Department of Genetics, Stanford University, Palo Alto, CA 94304-5477, USA
| | - David P. Hill
- Mouse Genome Informatics, The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | - Kimberly Van Auken
- Division of Biology and Biological Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, CA 91125, USA
| | - Helen Attrill
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Marc Feuermann
- Swiss Institute of Bioinformatics, 1 Michel-Servet, 1204 Geneva, Switzerland
| | - Pascale Gaudet
- Swiss Institute of Bioinformatics, 1 Michel-Servet, 1204 Geneva, Switzerland
| | - Ruth C. Lovering
- Functional Gene Annotation, Preclinical and Fundamental Science, Institute of Cardiovascular Science, University College London, London WC1E 6JF, UK
| | - Sylvain Poux
- Swiss Institute of Bioinformatics, 1 Michel-Servet, 1204 Geneva, Switzerland
| | - Kim M. Rutherford
- Cambridge Systems Biology Centre, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK
- Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK
| | - Christopher J. Mungall
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
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16
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Thurmond J, Goodman JL, Strelets VB, Attrill H, Gramates LS, Marygold SJ, Matthews BB, Millburn G, Antonazzo G, Trovisco V, Kaufman TC, Calvi BR. FlyBase 2.0: the next generation. Nucleic Acids Res 2020; 47:D759-D765. [PMID: 30364959 PMCID: PMC6323960 DOI: 10.1093/nar/gky1003] [Citation(s) in RCA: 484] [Impact Index Per Article: 121.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Accepted: 10/09/2018] [Indexed: 01/01/2023] Open
Abstract
FlyBase (flybase.org) is a knowledge base that supports the community of researchers that use the fruit fly, Drosophila melanogaster, as a model organism. The FlyBase team curates and organizes a diverse array of genetic, molecular, genomic, and developmental information about Drosophila. At the beginning of 2018, ‘FlyBase 2.0’ was released with a significantly improved user interface and new tools. Among these important changes are a new organization of search results into interactive lists or tables (hitlists), enhanced reference lists, and new protein domain graphics. An important new data class called ‘experimental tools’ consolidates information on useful fly strains and other resources related to a specific gene, which significantly enhances the ability of the Drosophila researcher to design and carry out experiments. With the release of FlyBase 2.0, there has also been a restructuring of backend architecture and a continued development of application programming interfaces (APIs) for programmatic access to FlyBase data. In this review, we describe these major new features and functionalities of the FlyBase 2.0 site and how they support the use of Drosophila as a model organism for biological discovery and translational research.
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Affiliation(s)
- Jim Thurmond
- Department of Biology, Indiana University, Bloomington, IN 47408, USA
| | - Joshua L Goodman
- Department of Biology, Indiana University, Bloomington, IN 47408, USA
| | - Victor B Strelets
- Department of Biology, Indiana University, Bloomington, IN 47408, USA
| | - Helen Attrill
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - L Sian Gramates
- The Biological Laboratories, Harvard University, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - Steven J Marygold
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Beverley B Matthews
- The Biological Laboratories, Harvard University, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - Gillian Millburn
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Giulia Antonazzo
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Vitor Trovisco
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
| | - Thomas C Kaufman
- Department of Biology, Indiana University, Bloomington, IN 47408, USA
| | - Brian R Calvi
- Department of Biology, Indiana University, Bloomington, IN 47408, USA
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17
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Marygold SJ, Attrill H, Speretta E, Warner K, Magrane M, Berloco M, Cotterill S, McVey M, Rong Y, Yamaguchi M. The DNA polymerases of Drosophila melanogaster. Fly (Austin) 2020; 14:49-61. [PMID: 31933406 PMCID: PMC7714529 DOI: 10.1080/19336934.2019.1710076] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
DNA synthesis during replication or repair is a fundamental cellular process that is catalyzed by a set of evolutionary conserved polymerases. Despite a large body of research, the DNA polymerases of Drosophila melanogaster have not yet been systematically reviewed, leading to inconsistencies in their nomenclature, shortcomings in their functional (Gene Ontology, GO) annotations and an under-appreciation of the extent of their characterization. Here, we describe the complete set of DNA polymerases in D. melanogaster, applying nomenclature already in widespread use in other species, and improving their functional annotation. A total of 19 genes encode the proteins comprising three replicative polymerases (alpha-primase, delta, epsilon), five translesion/repair polymerases (zeta, eta, iota, Rev1, theta) and the mitochondrial polymerase (gamma). We also provide an overview of the biochemical and genetic characterization of these factors in D. melanogaster. This work, together with the incorporation of the improved nomenclature and GO annotation into key biological databases, including FlyBase and UniProtKB, will greatly facilitate access to information about these important proteins.
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Affiliation(s)
- Steven J Marygold
- FlyBase, Department of Physiology, Development and Neuroscience, University of Cambridge , Cambridge, UK
| | - Helen Attrill
- FlyBase, Department of Physiology, Development and Neuroscience, University of Cambridge , Cambridge, UK
| | - Elena Speretta
- UniProt, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI) , Cambridgeshire, UK
| | - Kate Warner
- UniProt, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI) , Cambridgeshire, UK
| | - Michele Magrane
- UniProt, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI) , Cambridgeshire, UK
| | - Maria Berloco
- Dipartimento di Biologia, Università degli Studi di Bari "Aldo Moro" , Bari, Italy
| | - Sue Cotterill
- Department Basic Medical Sciences, St Georges University London , London, UK
| | - Mitch McVey
- Department of Biology, Tufts University , Medford, MA, USA
| | - Yikang Rong
- School of Life Sciences, Sun Yat-sen University , Guangzhou, China
| | - Masamitsu Yamaguchi
- Department of Applied Biology and Advanced Insect Research Promotion Center, Kyoto Institute of Technology , Kyoto, Japan
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18
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Attrill H, Gaudet P, Huntley RP, Lovering RC, Engel SR, Poux S, Van Auken KM, Georghiou G, Chibucos MC, Berardini TZ, Wood V, Drabkin H, Fey P, Garmiri P, Harris MA, Sawford T, Reiser L, Tauber R, Toro S. Annotation of gene product function from high-throughput studies using the Gene Ontology. Database (Oxford) 2019; 2019:5304975. [PMID: 30715275 PMCID: PMC6355445 DOI: 10.1093/database/baz007] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 01/08/2019] [Indexed: 11/17/2022]
Abstract
High-throughput studies constitute an essential and valued source of information for researchers. However, high-throughput experimental workflows are often complex, with multiple data sets that may contain large numbers of false positives. The representation of high-throughput data in the Gene Ontology (GO) therefore presents a challenging annotation problem, when the overarching goal of GO curation is to provide the most precise view of a gene's role in biology. To address this, representatives from annotation teams within the GO Consortium reviewed high-throughput data annotation practices. We present an annotation framework for high-throughput studies that will facilitate good standards in GO curation and, through the use of new high-throughput evidence codes, increase the visibility of these annotations to the research community.
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Affiliation(s)
- Helen Attrill
- FlyBase, Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge , UK
| | - Pascale Gaudet
- CALIPHO group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, rue Michel Servet, CH Geneva, Switzerland
| | - Rachael P Huntley
- Institute of Cardiovascular Science, University College London, London, UK
| | - Ruth C Lovering
- Institute of Cardiovascular Science, University College London, London, UK
| | - Stacia R Engel
- Saccharomyces Genome Database, Department of Genetics, Stanford University, Porter Drive, Palo Alto, CA, USA
| | - Sylvain Poux
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, rue Michel Servet, CH Geneva, Switzerland
| | - Kimberly M Van Auken
- WormBase, Division of Biology and Biological Engineering, California Institute of Technology, E California Blvd, Pasadena, CA, USA
| | - George Georghiou
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Marcus C Chibucos
- Evidence and Conclusion Ontology, University of Maryland School of Medicine, W Baltimore St., Baltimore, MD, USA
| | - Tanya Z Berardini
- The Arabidopsis Information Resource, Phoenix Bioinformatics, Redwood City, CA, USA
| | - Valerie Wood
- PomBase, Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Sanger Building, Tennis Court Road, Cambridge, UK
| | - Harold Drabkin
- Mouse Genome Informatics, Department of Computational Biology and Bioinformatics, The Jackson Laboratory, Main St., Bar Harbor, ME, USA
| | - Petra Fey
- dictyBase, Biomedical Informatics Center and Center for Genetic Medicine, Northwestern University, Feinberg School of Medicine, North Lake Shore Drive, Chicago, IL, USA
| | - Penelope Garmiri
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Midori A Harris
- PomBase, Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Sanger Building, Tennis Court Road, Cambridge, UK
| | - Tony Sawford
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Leonore Reiser
- The Arabidopsis Information Resource, Phoenix Bioinformatics, Redwood City, CA, USA
| | - Rebecca Tauber
- Evidence and Conclusion Ontology, University of Maryland School of Medicine, W Baltimore St., Baltimore, MD, USA
| | - Sabrina Toro
- Zebrafish Information Network, University of Oregon, Eugene, OR, USA
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19
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Abstract
For more than 25 years, FlyBase ( flybase.org ) has served as an online database of biological information on the genus Drosophila, concentrating on the model organism D. melanogaster. Traditionally, FlyBase data have been organized and presented at a gene-by-gene level, which remains a useful perspective when the object of interest is a specific gene or gene product. However, in the modern era of a fully sequenced genome and an increasingly characterized proteome, it is often desirable to compile and analyze lists of genes related by a common function. This may be achieved in FlyBase by searching for genes annotated with relevant Gene Ontology (GO) terms and/or protein domain data. In addition, FlyBase provides preassembled lists of functionally related D. melanogaster genes within "Gene Group" reports. These are compiled manually from the published literature or expert databases and greatly facilitate access to, and analysis of, established gene sets. This chapter describes protocols to produce lists of functionally related genes in FlyBase using GO annotations, protein domain data and the Gene Groups resource, and provides guidance and advice for their further analysis and processing.
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Affiliation(s)
- Alix J Rey
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.
| | - Helen Attrill
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Steven J Marygold
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
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20
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Marygold SJ, Antonazzo G, Attrill H, Costa M, Crosby MA, dos Santos G, Goodman JL, Gramates LS, Matthews BB, Rey AJ, Thurmond J. Exploring FlyBase Data Using QuickSearch. Curr Protoc Bioinformatics 2016; 56:1.31.1-1.31.23. [PMID: 27930807 PMCID: PMC5152691 DOI: 10.1002/cpbi.19] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
FlyBase (flybase.org) is the primary online database of genetic, genomic, and functional information about Drosophila species, with a major focus on the model organism Drosophila melanogaster. The long and rich history of Drosophila research, combined with recent surges in genomic-scale and high-throughput technologies, mean that FlyBase now houses a huge quantity of data. Researchers need to be able to rapidly and intuitively query these data, and the QuickSearch tool has been designed to meet these needs. This tool is conveniently located on the FlyBase homepage and is organized into a series of simple tabbed interfaces that cover the major data and annotation classes within the database. This unit describes the functionality of all aspects of the QuickSearch tool. With this knowledge, FlyBase users will be equipped to take full advantage of all QuickSearch features and thereby gain improved access to data relevant to their research. © 2016 by John Wiley & Sons, Inc.
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Affiliation(s)
- Steven J. Marygold
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3DY, UK
| | - Giulia Antonazzo
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3DY, UK
| | - Helen Attrill
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3DY, UK
| | - Marta Costa
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3DY, UK
| | - Madeline A. Crosby
- The Biological Laboratories, Harvard University, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - Gilberto dos Santos
- The Biological Laboratories, Harvard University, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - Joshua L. Goodman
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | - L. Sian Gramates
- The Biological Laboratories, Harvard University, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - Beverley B. Matthews
- The Biological Laboratories, Harvard University, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - Alix J. Rey
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge, CB2 3DY, UK
| | - Jim Thurmond
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
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21
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Abstract
Synthesis of polypeptides from mRNA (translation) is a fundamental cellular process that is coordinated and catalyzed by a set of canonical ‘translation factors’. Surprisingly, the translation factors of Drosophila melanogaster have not yet been systematically identified, leading to inconsistencies in their nomenclature and shortcomings in functional (Gene Ontology, GO) annotations. Here, we describe the complete set of translation factors in D. melanogaster, applying nomenclature already in widespread use in other species, and revising their functional annotation. The collection comprises 43 initiation factors, 12 elongation factors, 3 release factors and 6 recycling factors, totaling 64 of which 55 are cytoplasmic and 9 are mitochondrial. We also provide an overview of notable findings and particular insights derived from Drosophila about these factors. This catalog, together with the incorporation of the improved nomenclature and GO annotation into FlyBase, will greatly facilitate access to information about the functional roles of these important proteins.
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Affiliation(s)
- Steven J Marygold
- a FlyBase, Department of Physiology , Development and Neuroscience, University of Cambridge , Cambridge , UK
| | - Helen Attrill
- a FlyBase, Department of Physiology , Development and Neuroscience, University of Cambridge , Cambridge , UK
| | - Paul Lasko
- b Department of Biology , McGill University , Bellini Life Sciences Complex, Montreal, Quebec , Canada
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22
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Attrill H, Falls K, Goodman JL, Millburn GH, Antonazzo G, Rey AJ, Marygold SJ. FlyBase: establishing a Gene Group resource for Drosophila melanogaster. Nucleic Acids Res 2015; 44:D786-92. [PMID: 26467478 PMCID: PMC4702782 DOI: 10.1093/nar/gkv1046] [Citation(s) in RCA: 237] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2015] [Accepted: 10/01/2015] [Indexed: 11/25/2022] Open
Abstract
Many publications describe sets of genes or gene products that share a common biology. For example, genome-wide studies and phylogenetic analyses identify genes related in sequence; high-throughput genetic and molecular screens reveal functionally related gene products; and advanced proteomic methods can determine the subunit composition of multi-protein complexes. It is useful for such gene collections to be presented as discrete lists within the appropriate Model Organism Database (MOD) so that researchers can readily access these data alongside other relevant information. To this end, FlyBase (flybase.org), the MOD for Drosophila melanogaster, has established a ‘Gene Group’ resource: high-quality sets of genes derived from the published literature and organized into individual report pages. To facilitate further analyses, Gene Group Reports also include convenient download and analysis options, together with links to equivalent gene groups at other databases. This new resource will enable researchers with diverse backgrounds and interests to easily view and analyse acknowledged D. melanogaster gene sets and compare them with those of other species.
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Affiliation(s)
- Helen Attrill
- Department of Genetics, University of Cambridge, Downing Street, Cambridge, CB2 3EH, UK
| | - Kathleen Falls
- The Biological Laboratories, Harvard University, 16 Divinity Avenue, Cambridge, MA 02138, USA
| | - Joshua L Goodman
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | - Gillian H Millburn
- Department of Genetics, University of Cambridge, Downing Street, Cambridge, CB2 3EH, UK
| | - Giulia Antonazzo
- Department of Genetics, University of Cambridge, Downing Street, Cambridge, CB2 3EH, UK
| | - Alix J Rey
- Department of Genetics, University of Cambridge, Downing Street, Cambridge, CB2 3EH, UK
| | - Steven J Marygold
- Department of Genetics, University of Cambridge, Downing Street, Cambridge, CB2 3EH, UK
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23
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Oates J, Faust B, Attrill H, Harding P, Orwick M, Watts A. The role of cholesterol on the activity and stability of neurotensin receptor 1. Biochimica et Biophysica Acta (BBA) - Biomembranes 2012; 1818:2228-33. [DOI: 10.1016/j.bbamem.2012.04.010] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2011] [Revised: 03/15/2012] [Accepted: 04/12/2012] [Indexed: 10/28/2022]
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24
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Dorfmueller HC, Fang W, Rao FV, Blair DE, Attrill H, van Aalten DMF. Structural and biochemical characterization of a trapped coenzyme A adduct of Caenorhabditis elegans glucosamine-6-phosphate N-acetyltransferase 1. Acta Crystallogr D Biol Crystallogr 2012; 68:1019-29. [PMID: 22868768 PMCID: PMC3413214 DOI: 10.1107/s0907444912019592] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/26/2012] [Accepted: 05/02/2012] [Indexed: 01/31/2023]
Abstract
Glucosamine-6-phosphate N-acetyltransferase is an essential enzyme of the eukaryotic UDP-GlcNAc biosynthetic pathway. A crystal structure at 1.55 Å resolution revealed a highly unusual covalent product complex and biochemical studies investigated the function of a fully conserved active-site cysteine. Glucosamine-6-phosphate N-acetyltransferase 1 (GNA1) produces GlcNAc-6-phosphate from GlcN-6-phosphate and acetyl coenzyme A. Early mercury-labelling experiments implicated a conserved cysteine in the reaction mechanism, whereas recent structural data appear to support a mechanism in which this cysteine plays no role. Here, two crystal structures of Caenorhabditis elegans GNA1 are reported, revealing an unusual covalent complex between this cysteine and the coenzyme A product. Mass-spectrometric and reduction studies showed that this inactive covalent complex can be reactivated through reduction, yet mutagenesis of the cysteine supports a previously reported bi-bi mechanism. The data unify the apparently contradictory earlier reports on the role of a cysteine in the GNA1 active site.
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Affiliation(s)
- Helge C Dorfmueller
- Division of Molecular Microbiology, College of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland
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25
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Selmi DN, Adamson RJ, Attrill H, Goddard AD, Gilbert RJC, Watts A, Turberfield AJ. DNA-templated protein arrays for single-molecule imaging. Nano Lett 2011; 11:657-660. [PMID: 21218848 DOI: 10.1021/nl1037769] [Citation(s) in RCA: 63] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Single-particle electron cryomicroscopy permits structural characterization of noncrystalline protein samples, but throughput is limited by problems associated with sample preparation and image processing. Three-dimensional density maps are reconstructed from high resolution but noisy images of individual molecules. We show that self-assembled DNA nanoaffinity templates can create dense, nonoverlapping arrays of protein molecules, greatly facilitating data collection. We demonstrate this technique using a G-protein-coupled membrane receptor, a soluble G-protein, and a signaling complex of both molecules.
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Affiliation(s)
- Daniele N Selmi
- Department of Physics, Clarendon Laboratory, University of Oxford, Oxford, UK
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26
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Tapaneeyakorn S, Ross S, Attrill H, Watts A. Heterologous high yield expression and purification of neurotensin and its functional fragment in Escherichia coli. Protein Expr Purif 2010; 74:65-8. [DOI: 10.1016/j.pep.2010.06.014] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2010] [Revised: 06/24/2010] [Accepted: 06/28/2010] [Indexed: 11/29/2022]
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27
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Harding PJ, Attrill H, Boehringer J, Ross S, Wadhams GH, Smith E, Armitage JP, Watts A. Constitutive dimerization of the G-protein coupled receptor, neurotensin receptor 1, reconstituted into phospholipid bilayers. Biophys J 2009; 96:964-73. [PMID: 19186134 DOI: 10.1016/j.bpj.2008.09.054] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2008] [Accepted: 09/22/2008] [Indexed: 12/30/2022] Open
Abstract
Neurotensin receptor 1 (NTS1), a Family A G-protein coupled receptor (GPCR), was expressed in Escherichia coli as a fusion with the fluorescent proteins eCFP or eYFP. A fluorophore-tagged receptor was used to study the multimerization of NTS1 in detergent solution and in brain polar lipid bilayers, using fluorescence resonance energy transfer (FRET). A detergent-solubilized receptor was unable to form FRET-competent complexes at concentrations of up to 200 nM, suggesting that the receptor is monomeric in this environment. When reconstituted into a model membrane system at low receptor density, the observed FRET was independent of agonist binding, suggesting constitutive multimer formation. In competition studies, decreased FRET in the presence of untagged NTS1 excludes the possibility of fluorescent protein-induced interactions. A simulation of the experimental data indicates that NTS1 exists predominantly as a homodimer, rather than as higher-order multimers. These observations suggest that, in common with several other Family A GPCRs, NTS1 forms a constitutive dimer in lipid bilayers, stabilized through receptor-receptor interactions in the absence of other cellular signaling components. Therefore, this work demonstrates that well-characterized model membrane systems are useful tools for the study of GPCR multimerization, allowing fine control over system composition and complexity, provided that rigorous control experiments are performed.
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Affiliation(s)
- Peter J Harding
- Biomembrane Structure Unit, Department of Biochemistry, University of Oxford, Oxford, United Kingdom
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28
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Abstract
Disappointed with the overall performance of weighted and unweighted nasogastric feeding tubes, a design programme was initiated which resulted in the development of two new nasogastric tubes, one weighted and one unweighted. The tubes were manufactured with polyurethane rather than polyvinylchloride (PVC) which permitted an increase in diameter of the internal lumen which in turn was coated with water activated lubricant to ease removal of the introducer wire. A specially modelled outflow port was incorporated into the tips of both tubes. The performance of the two new polyurethane nasogastric feeding tubes was assessed under controlled trial condition using as a reference a widely used PVC unweighted open ended tube. While intubation times were similar in patients without concurrent endotracheal intubation, it took a significantly shorter time to intubate patients with concurrent endotracheal intubation with the new weighted tube. Following tube intubation, it was possible to aspirate gastric contents significantly more often through the new polyurethane tubes (p < 0.001) than through the PVC tube, and the unweighted polyurethane tube stayed in situ longer (p < 0.05) than the PVC tube. The newly designed polyurethane nasogastric feeding tubes are the first tubes that have been shown to have advantages over the simpler type of open ended, unweighted PVC nasogastric feeding tubes.
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Affiliation(s)
- R G Rees
- Department of Gastroenterology & Nutrition, Central Middlesex Hospital, Acton Lane, London NW10 7NS, U.K
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29
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Patil DH, Grimble GK, Keohane P, Attrill H, Love M, Silk DB. Do fibre containing enteral diets have advantages over existing low residue diets? Clin Nutr 2008; 4:67-71. [PMID: 16831708 DOI: 10.1016/0261-5614(85)90044-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/1984] [Accepted: 04/04/1985] [Indexed: 12/25/2022]
Abstract
This study investigated the influence of fibre on the pattern of absorption of protein and carbohydrate following administration of polymeric enteral diet and also the effect of added fibre on frequency of bowel action, stool weight and gastrointestinal side effects during enteral nutrition. No difference was seen in frequency of bowel action, stool weight or gastrointestinal side effects in five patients fed with either a fibre free polymeric diet or with the same diet augmented with 24 g fibre/24 h. Addition of fibre did not significantly alter breath hydrogen excretion. In an oral tolerance test on six normal subjects, the post prandial rises in blood glucose and levels of 17 amino acids were similar on ingestion of a fibre containing or fibre free test meal.
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Affiliation(s)
- D H Patil
- Department of Gastroenterology & Nutrition, Central Middlesex Hospital, Acton Lane, London NW10 7NS UK
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30
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Abstract
The clinical use of unweighted nasogastric feeding tubes (n = 491) was compared with that of weighted nasogastric feeding tubes. No advantage was found in the use of the weighted tubes.
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Affiliation(s)
- P P Keohane
- Department of Gastroenterology and Nutrition, Central Middlesex Hospital, Acton Lane, London NW10 UK
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31
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Keohane PP, Attrill H, Jones BJ, Brown I, Frost P, Silk DB. The roles of lactose and Clostridium difficile in the pathogenesis of enteral feeding associated diarrhoea. Clin Nutr 2008; 1:259-64. [PMID: 16829389 DOI: 10.1016/0261-5614(83)90003-1] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
This study investigated the influence of the disaccharide lactose on the incidence of clinically significant enteral feeding associated diarrhoea. In this double blind study both groups each of 25 patients were randomised to receive either a lactose containing diet Clinifeed 400 in 25 patients or a lactose free diet Ensure in 25 patients. Diarrhoea occurred with equal frequency in both treatment groups, even in those patients with symptomatic and biochemical evidence of impaired lactose handling. Although the onset of diarrhoea was significantly associated with antibiotic administration (p<0.01), Cl. difficile was not isolated from the stools of any patient with diarrhoea.
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Affiliation(s)
- P P Keohane
- Departments of Gastroenterology and Clinical Nutrition and Chemical Pathology, Central Middlesex Hospital, London NW10, U.K
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32
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Harding PJ, Attrill H, Ross S, Koeppe JR, Kapanidis AN, Watts A. Neurotensin receptor type 1: Escherichia coli expression, purification, characterization and biophysical study. Biochem Soc Trans 2007; 35:760-3. [PMID: 17635142 DOI: 10.1042/bst0350760] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
NT (neurotensin) is an endogenous tridecapeptide neurotransmitter found in the central nervous system and gastrointestinal tract. One receptor for NT, NTS1, belongs to the GPCR (G-protein-coupled receptor) superfamily, has seven putative transmembrane domains, and is being studied by a range of single-molecule, functional and structural approaches. To enable biophysical characterization, sufficient quantities of the receptor need to be expressed and purified in an active form. To this end, rat NTS1 has been expressed in Escherichia coli in an active ligand-binding form at the cell membrane and purified in sufficient amounts for structural biology studies either with or without fluorescent protein [YFP (yellow fluorescent protein) and CFP (cyan fluorescent protein)] fusions. Ligand binding has been demonstrated in a novel SPR (surface plasmon resonance) approach, as well as by conventional radioligand binding measurements. These improvements in production of NTS1 now open up the possibility of direct structural studies, such as solid-state NMR to interrogate the NT-binding site, EM (electron microscopy), and X-ray crystallography and NMR.
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Affiliation(s)
- P J Harding
- Biomembrane Structure Unit, Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, U.K
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Abstract
The siglecs (sialic acid-binding Ig-like lectins) are a family of transmembrane receptors expressed in the haemopoietic, immune and nervous systems. The CD33-related siglecs are a distinct subset mostly expressed in the innate immune system where they can function as inhibitory receptors by suppressing the signalling mediated by receptors coupled with ITAMs (immunoreceptor tyrosine-based activation motifs). CD33-related siglecs contain ITIMs (immunoreceptor tyrosine-based inhibitory motifs) that recruit and activate SHP-1 [SH2 (Src homology 2) domain-containing phosphatase-1] and SHP-2. In addition, the ITIMs of CD33-related siglecs can suppress siglec-dependent adhesion of sialylated ligands and mediate endocytosis. Siglec-H is a recently characterized murine CD33-related endocytic receptor that lacks intrinsic tyrosine-based signalling motifs and is expressed selectively on PDCs (plasmacytoid dendritic cells). Siglec-H depends on DAP12 (DNAX-activating protein of 12 kDa) for surface expression and cross-linking with anti-siglec-H antibodies can selectively inhibit interferon-alpha production by PDCs following TLR9 (Toll-like receptor 9) ligation. Thus CD33-related siglecs are able to mediate diverse inhibitory functions of leucocytes in the innate immune system via both ITIM-dependent and -independent pathways.
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Affiliation(s)
- T Avril
- Wellcome Trust Biocentre, University of Dundee, Dow Street, Dundee DD1 5EH, Scotland, UK
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34
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Attrill H, Imamura A, Sharma RS, Kiso M, Crocker PR, van Aalten DMF. Siglec-7 undergoes a major conformational change when complexed with the alpha(2,8)-disialylganglioside GT1b. J Biol Chem 2006; 281:32774-83. [PMID: 16895906 DOI: 10.1074/jbc.m601714200] [Citation(s) in RCA: 69] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
The siglecs are a group of mammalian sialic acid binding receptors expressed predominantly in the immune system. The CD33-related siglecs show complex recognition patterns for sialylated glycans. Siglec-7 shows a preference for alpha(2,8)-disialylated ligands and provides a structural template for studying the key interactions that drive this selectivity. We have co-crystallized Siglec-7 with a synthetic oligosaccharide corresponding to the alpha(2,8)-disialylated ganglioside GT1b. The crystal structure of the complex offers a first glimpse into how this important family of lectins binds the structurally diverse gangliosides. The structure reveals that the C-C' loop, a region implicated in previous studies as driving siglec specificity, undergoes a dramatic conformational shift, allowing it to interact with the underlying neutral glycan core of the ganglioside. The structural data in combination with mutagenesis studies show that binding of the ganglioside is driven by extensive hydrophobic contacts together with key polar interactions and that the binding site structure is complementary to preferred solution conformations of GT1b.
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Affiliation(s)
- Helen Attrill
- Division of Biological Chemistry and Molecular Microbiology, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland, United Kingdom
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35
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Attrill H, Takazawa H, Witt S, Kelm S, Isecke R, Brossmer R, Ando T, Ishida H, Kiso M, Crocker P, van Aalten D. The structure of siglec-7 in complex with sialosides: leads for rational structure-based inhibitor design. Biochem J 2006; 397:271-8. [PMID: 16623661 PMCID: PMC1513286 DOI: 10.1042/bj20060103] [Citation(s) in RCA: 58] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Siglecs (sialic acid binding Ig-like lectins) are transmembrane receptors for sialylated glycoconjugates that modulate cellular interactions and signalling events in the haematopoietic, immune and nervous systems. Siglec-7 is a structural prototype for the recently described family of immune inhibitory CD33-related siglecs and is predominantly expressed on natural killer cells and monocytes, as well as subsets of CD8 T-cells. Siglec-specific inhibitors are desired for the detection of masked and unmasked forms of siglecs, to aid in dissection of signalling pathways and as tools to investigate siglecs as potential therapeutic targets. As a first step towards this end, we present the crystal structure of siglec-7 in complex with a sialylated ligand, the ganglioside analogue DSLc4 [alpha(2,3)/alpha(2,6) disialyl lactotetraosyl 2-(trimethylsilyl)ethyl], which allows for a detailed description of the binding site, required for structure-guided inhibitor design. Mutagenesis and binding assays were used to demonstrate a key structural role for Lys131, a residue that changes conformation upon sialic acid binding. Differences between the binding sites of siglec family members were then exploited using alpha-methyl Neu5Ac (N-acetylneuraminic acid) as a basic scaffold. A co-crystal of siglec-7 in complex with the sialoside inhibitor, oxamido-Neu5Ac [methyl alpha-9-(amino-oxalyl-amino)-9-deoxy-Neu5Ac] and inhibition data for the sialosides gives clear leads for future inhibitor design.
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Affiliation(s)
- Helen Attrill
- *Divisions of Biological Chemistry and Molecular Microbiology, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland, U.K
- †Department of Cell Biology and Immunology, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland, U.K
| | - Hirokazu Takazawa
- †Department of Cell Biology and Immunology, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland, U.K
| | - Simone Witt
- ‡Centre for Biomolecular Interactions Bremen, Department of Biology and Chemistry, University Bremen, 28334 Bremen, Germany
| | - Soerge Kelm
- ‡Centre for Biomolecular Interactions Bremen, Department of Biology and Chemistry, University Bremen, 28334 Bremen, Germany
| | - Rainer Isecke
- §Biochemistry Center Heidelberg, University of Heidelberg, 69120, Heidelberg, Germany
| | - Reinhard Brossmer
- §Biochemistry Center Heidelberg, University of Heidelberg, 69120, Heidelberg, Germany
| | - Takayuki Ando
- ¶Department of Applied Bioorganic Chemistry, Faculty of Applied Biological Sciences, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
| | - Hideharu Ishida
- ¶Department of Applied Bioorganic Chemistry, Faculty of Applied Biological Sciences, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
| | - Makoto Kiso
- ¶Department of Applied Bioorganic Chemistry, Faculty of Applied Biological Sciences, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
| | - Paul R. Crocker
- †Department of Cell Biology and Immunology, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland, U.K
| | - Daan M. F. van Aalten
- *Divisions of Biological Chemistry and Molecular Microbiology, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland, U.K
- To whom correspondence should be addressed (email )
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36
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Avril T, Freeman SD, Attrill H, Clarke RG, Crocker PR. Siglec-5 (CD170) Can Mediate Inhibitory Signaling in the Absence of Immunoreceptor Tyrosine-based Inhibitory Motif Phosphorylation. J Biol Chem 2005; 280:19843-51. [PMID: 15769739 DOI: 10.1074/jbc.m502041200] [Citation(s) in RCA: 80] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Siglec-5 (CD170) is a member of the recently described human CD33-related siglec subgroup of sialic acid binding Ig-like lectins and is expressed on myeloid cells of the hemopoietic system. Similar to other CD33-related siglecs, Siglec-5 contains two tyrosine-based motifs in its cytoplasmic tail implicated in signaling functions. To investigate the role of these motifs in Siglec-5-dependent signaling, we used transfected rat basophil leukemia cells as a model system. Tyrosine phosphorylation of Siglec-5 led to recruitment of the tyrosine phosphatases SHP-1 and SHP-2, as seen in both pull-down assays and microscopy. Siglec-5 could efficiently inhibit FcepsilonRI-mediated calcium fluxing and serotonin release after co-cross-linking. Surprisingly, a double tyrosine to alanine mutant of Siglec-5 could still mediate strong inhibition of serotonin release in the absence of detectable tyrosine phosphorylation, whereas a double tyrosine to phenylalanine mutant lost all inhibitory activity. In comparison, suppression of Siglec-5-dependent adhesion to red blood cells was reversed by either tyrosine to alanine or tyrosine to phenylalanine mutations of the membrane proximal tyrosine-based motif. Using an in vitro phosphatase assay with synthetic and recombinant forms of the cytoplasmic tail, it was shown that a double alanine mutant of Siglec-5 had weak, but significant SHP-1 activating properties similar to those of wild type, non-phosphorylated cytoplasmic tail, whereas a double phenylalanine mutant was inactive. These findings establish that Siglec-5 can be classified as an inhibitory receptor with the potential to mediate SHP-1 and/or SHP-2-dependent signaling in the absence of tyrosine phosphorylation.
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MESH Headings
- Amino Acid Motifs
- Amino Acid Sequence
- Amino Acid Substitution
- Animals
- Antigens, CD/chemistry
- Antigens, CD/genetics
- Antigens, CD/metabolism
- Antigens, Differentiation, Myelomonocytic/chemistry
- Antigens, Differentiation, Myelomonocytic/genetics
- Antigens, Differentiation, Myelomonocytic/metabolism
- Base Sequence
- Cell Adhesion/physiology
- Cell Line
- DNA/genetics
- Humans
- In Vitro Techniques
- Intracellular Signaling Peptides and Proteins
- Lectins/chemistry
- Lectins/genetics
- Lectins/metabolism
- Molecular Sequence Data
- Mutagenesis, Site-Directed
- Phosphorylation
- Protein Tyrosine Phosphatase, Non-Receptor Type 11
- Protein Tyrosine Phosphatase, Non-Receptor Type 6
- Protein Tyrosine Phosphatases/genetics
- Protein Tyrosine Phosphatases/metabolism
- Rats
- Recombinant Fusion Proteins/chemistry
- Recombinant Fusion Proteins/genetics
- Recombinant Fusion Proteins/metabolism
- Signal Transduction
- Transfection
- Tyrosine/chemistry
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Affiliation(s)
- Tony Avril
- Division of Cell Biology and Immunology, The Wellcome Trust Biocentre, School of Life Sciences, University of Dundee, UK
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37
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Dimasi N, Attrill H, van Aalten DMF, Moretta A, Moretta L, Biassoni R, Mariuzza RA. Structure of the saccharide-binding domain of the human natural killer cell inhibitory receptor p75/AIRM1. Erratum. Acta Crystallogr D Biol Crystallogr 2004. [DOI: 10.1107/s0907444904002951] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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38
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Alphey MS, Attrill H, Crocker PR, van Aalten DMF. High resolution crystal structures of Siglec-7. Insights into ligand specificity in the Siglec family. J Biol Chem 2003; 278:3372-7. [PMID: 12438315 DOI: 10.1074/jbc.m210602200] [Citation(s) in RCA: 88] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Sialic acid-binding immunoglobulin-like lectins (Siglecs) recognize sialylated glycoconjugates and play a role in cell-cell recognition. Siglec-7 is expressed on natural killer cells and displays unique ligand binding properties different from other members of the Siglec family. Here we describe the high resolution structures of the N-terminal V-set Ig-like domain of Siglec-7 in two crystal forms, at 1.75 and 1.9 A. The latter crystal form reveals the full structure of this domain and allows us to speculate on the differential ligand binding properties displayed by members of the Siglec family. A fully ordered N-linked glycan is observed, tethered by tight interactions with symmetry-related protein molecules in the crystal. Comparison of the structure with that of sialoadhesin and a model of Siglec-9 shows that the unique preference of Siglec-7 for alpha(2,8)-linked disialic acid is likely to reside in the C-C' loop, which is variable in the Siglec family. In the Siglec-7 structure, the ligand-binding pocket is occupied by a loop of a symmetry-related molecule, mimicking the interactions with sialic acid.
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Affiliation(s)
- Magnus S Alphey
- Division of Cell Biology and Immunology, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland, United Kingdom
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39
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Magee J, Freeman R, Barrett A, Attrill H, Lightfoot NF. Testing for tuberculosis. Lancet 1996; 347:476. [PMID: 8618515 DOI: 10.1016/s0140-6736(96)90056-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
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40
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Silk DB, Rees RG, Keohane PP, Attrill H. Clinical efficacy and design changes of "fine bore" nasogastric feeding tubes: a seven-year experience involving 809 intubations in 403 patients. JPEN J Parenter Enteral Nutr 1987; 11:378-83. [PMID: 3112428 DOI: 10.1177/0148607187011004378] [Citation(s) in RCA: 48] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
We report here our clinical experiences of "fine bore" nasogastric feeding tubes. Data have been collated over a 7-year period (1978-1985). A total of 403 patients were intubated on 809 occasions. In the first retrospective study, the clinical use of 491 unweighted tubes was compared with that of fifty 3.5-g weighted tubes. No advantage was found in the use of the weighted tubes. In the second prospective controlled clinical trial, these results were confirmed. Forty-six patients were intubated on 76 occasions with an 85-cm open-ended, unweighted nasogastric feeding tube (Prima, Portex UK), and 57 patients were intubated on 79 occasions with a 91-cm 3.0-g weighted tube (Entriflex, Biosearch, Raritan, NJ). Mean duration of placement was similar in each case, and 62% of both types of tubes were inadvertently removed. Without exception, all the tubes remained in the stomach throughout. Disappointed with the similar and overall performance of both types of tubes, we initiated a design program which resulted in the development of two new nasogastric tubes, one weighted and one unweighted. The tubes were manufactured with polyurethane, rather than polyvinylchloride (PVC), which permitted an increase in diameter of the internal lumen which, in turn, was coated with water-activated lubricant to ease removal of the introducer wire. A specially modeled outflow port was incorporated into the tips of both tubes. The performance of the two new polyurethane nasogastric feeding tubes was assessed under controlled trial conditions; as a reference, a widely used PVC unweighted open-ended tube was used.(ABSTRACT TRUNCATED AT 250 WORDS)
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41
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Rees RG, Keohane PP, Grimble GK, Frost PG, Attrill H, Silk DB. Elemental diet administered nasogastrically without starter regimens to patients with inflammatory bowel disease. JPEN J Parenter Enteral Nutr 1986; 10:258-62. [PMID: 3086582 DOI: 10.1177/0148607186010003258] [Citation(s) in RCA: 20] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
The present study questions the concept of routinely using 'starter regimens' at the outset of enteral feeding with chemically defined elemental diets. A hypertonic elemental diet with an osmolality of 630 mOsm/kg was administered by 24-hr nasogastric infusion to 12 patients with exacerbations of inflammatory bowel disease and to two patients with short bowel syndrome. Starter regimens were not used. Upper gastrointestinal symptoms of nausea, abdominal bloating, and colicky pain occurred transiently in only five of 14 patients. Stool frequency did not increase during full-strength feeding, and daily stool weights decreased significantly (p less than 0.01). These findings show that it is safe to administer undiluted hypertonic elemental diets by constant nasogastric infusion to patients with inflammatory bowel disease. Avoiding starter regimens leads to increased nutrient intake and improved nitrogen balance.
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42
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Rees RG, Keohane PP, Grimble GK, Frost PG, Attrill H, Silk DB. Tolerance of elemental diet administered without starter regimen. Br Med J (Clin Res Ed) 1985; 290:1869-70. [PMID: 3924289 PMCID: PMC1416811 DOI: 10.1136/bmj.290.6485.1869] [Citation(s) in RCA: 18] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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43
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Keohane PP, Attrill H, Love M, Frost P, Silk DB. Relation between osmolality of diet and gastrointestinal side effects in enteral nutrition. Br Med J (Clin Res Ed) 1984; 288:678-80. [PMID: 6421429 PMCID: PMC1444378 DOI: 10.1136/bmj.288.6418.678] [Citation(s) in RCA: 152] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
One hundred and eighteen patients with normal gastrointestinal function were randomly allocated to one of three feeding regimens in a double blind study to determine the relation between the tonicity of the diet and gastrointestinal side effects related to the diet and to evaluate the efficacy of "starter" regimens in reducing gastrointestinal side effects during enteral nutrition. Patients received a hypertonic diet with an osmolality of 430 mmol (mosmol)/kg (group 1), the same diet but with the osmolality increasing from 145 to 430 mmol/kg over the first four days (group 2), or an isotonic diet (300 mmol/kg) (group 3). All diets were prepared aseptically and administered by 24 hour nasogastric infusion. The mean daily nitrogen intake in group 1 was significantly greater (p less than 0.05) than that in both groups 2 and 3, and the mean overall daily nitrogen balance was significantly better (p less than 0.05) in group 1 than groups 2 and 3. The incidence of side effects related to the diet was similar in all three groups, but diarrhoea was significantly (p less than 0.001) associated with concurrent treatment with antibiotics. These findings show that undiluted hypertonic diet results in significantly better nitrogen intake and balance, that starter regimens reduce nutrient intake but not symptoms, and that diarrhoea is significantly related to treatment with antibiotics and not to administration of an undiluted hypertonic polymeric diet.
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44
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Keohane PP, Jones BJ, Attrill H, Cribb A, Northover J, Frost P, Silk DB. Effect of catheter tunnelling and a nutrition nurse on catheter sepsis during parenteral nutrition. A controlled trial. Lancet 1983; 2:1388-90. [PMID: 6140494 DOI: 10.1016/s0140-6736(83)90922-4] [Citation(s) in RCA: 145] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
In a three-year controlled trial of subcutaneous catheter tunnelling as a method of reducing total parenteral nutrition (TPN) catheter sepsis 99 silicone catheters (52 tunnelled, 47 untunnelled) were inserted into the subclavian (94%) or jugular (6%) veins under aseptic conditions. The influence of a nutrition nurse, who joined the nutrition team after 18 months, on catheter sepsis rate was also documented. Catheter sepsis was confirmed in 13 of 47 (28%) untunnelled catheters and only 6 of 52 (11.5%) tunnelled catheters (p less than 0.05). A nutrition nurse reduced sepsis rate from 33% (tunnelled 6, untunnelled 11) to 4% (0 tunnelled; 2 untunnelled) (p less than 0.001). There was no significant difference between tunnelled and untunnelled catheters in sepsis rates after the arrival of the nutrition nurse. Although 85% patients had concurrent internal sepsis, the pathogens implicated in catheter sepsis came from superficial sites in 16 of 19 cases (p less than 0.01). Rigorous aseptic nursing care is thus the most significant factor in the reduction of TPN catheter sepsis, but tunnelling can reduce sepsis rate when nursing care is suboptimum.
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45
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Keohane PP, Attrill H, Grimble G, Spiller R, Frost P, Silk DB. Enteral nutrition in malnourished patients with hepatic cirrhosis and acute encephalopathy. JPEN J Parenter Enteral Nutr 1983; 7:346-50. [PMID: 6413710 DOI: 10.1177/0148607183007004346] [Citation(s) in RCA: 41] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Ten patients with histologically proven cirrhosis, admitted in grade I to II acute hepatic coma, received in addition to a standard dietary protein free "anticoma" regime, a continuous nasogastric infusion of a branched-chain amino acid enriched chemically defined enteral diet (Hepaticaid) containing an equivalent of 70 g protein/day for a mean of 7.3 days (range 3-23). No complications of therapy were observed and, specifically, the use of fine bore tubes did not provoke variceal hemorrhage. Overall positive nitrogen balance (4.3 +/- 1.7 g N/day) was observed in patients fed 7 or more days. Improvement to coma grade 0 was seen in all patients save one, who died from hepatorenal failure. While serum ammonia levels remained elevated during the study period, there was a significant increase in the branched-chain/aromatic ratio (p less than 0.01) as plasma branched-chain amino acids rose (p less than 0.05) and tyrosine levels fell (p less than 0.05).
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46
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Keohane P, Attrill H, Love M, Frost P, Silk DB. A controlled trial of aseptic enteral diet preparation — Significant effects on bacterial contamination and nitrogen balance. Clin Nutr 1983; 2:119-22. [PMID: 16829421 DOI: 10.1016/0261-5614(83)90044-4] [Citation(s) in RCA: 29] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
This study was performed to evaluate the clinical effectiveness of the 'standard' and aseptic enteral diet preparation techniques and to investigate the relationship between bacterial contamination of diets and symptoms during enteral nutrition. In this controlled study patients were prescribed isonitrogenous polymeric diets prepared using either 'standard' or aseptic techniques, administered by 24 nasogastric infusion. 'Standard' diet preparation resulted in significant bacterial contamination (p<0.01), but this did not increase incidence of diet related symptoms. Use of sterile techniques permitted safe use of large volumes (1.5-2 litre) containers, and this resulted in significantly better nitrogen intake (p<0.05) and balance (p<0.05).
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Affiliation(s)
- P Keohane
- Department of Gastroenterology and Clinical Nutrition, Central Middlesex Hospital, London NW10 UK
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47
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Abstract
Simple unweighted fine bore feeding tubes have been used by our Nutritional Support Team for routine nasogastric feeding with success in large numbers of patients. Three clinical situations where mercury or tungsten weighted tubes offer advantages over fine bore tubes have been defined. Significant advantages in patients with concurrent endotracheal intubation, gastric atony and severe oesophageal stricturing are described.
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Affiliation(s)
- P P Keohane
- Department of Gastroenterology and Clinical Nutrition, Central Middlesex Hospital, Acton Lane, London NW10, England
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48
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Abstract
In a small proportion of patients requiring enteral nutrition it may not be possible to site nasogastric or nasoenteric feeding tubes using standard intubation techniques. We describe an endoscopic method of tube placement applicable not only for positioning nasogastric feeding tubes in patients with coexisting oesophageal pathology, but also for placement of nasoenteric feeding tubes when disordered gastric emptying is present.
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Affiliation(s)
- P P Keohane
- Department of Gastroenterology and Nutrition, Central Middlesex Hospital, London NW10 UK
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