Reproducible molecular networking of untargeted mass spectrometry data using GNPS View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2020-05-13

AUTHORS

Allegra T. Aron, Emily C. Gentry, Kerry L. McPhail, Louis-Félix Nothias, Mélissa Nothias-Esposito, Amina Bouslimani, Daniel Petras, Julia M. Gauglitz, Nicole Sikora, Fernando Vargas, Justin J. J. van der Hooft, Madeleine Ernst, Kyo Bin Kang, Christine M. Aceves, Andrés Mauricio Caraballo-Rodríguez, Irina Koester, Kelly C. Weldon, Samuel Bertrand, Catherine Roullier, Kunyang Sun, Richard M. Tehan, Cristopher A. Boya P., Martin H. Christian, Marcelino Gutiérrez, Aldo Moreno Ulloa, Javier Andres Tejeda Mora, Randy Mojica-Flores, Johant Lakey-Beitia, Victor Vásquez-Chaves, Yilue Zhang, Angela I. Calderón, Nicole Tayler, Robert A. Keyzers, Fidele Tugizimana, Nombuso Ndlovu, Alexander A. Aksenov, Alan K. Jarmusch, Robin Schmid, Andrew W. Truman, Nuno Bandeira, Mingxun Wang, Pieter C. Dorrestein

ABSTRACT

Global Natural Product Social Molecular Networking (GNPS) is an interactive online small molecule–focused tandem mass spectrometry (MS2) data curation and analysis infrastructure. It is intended to provide as much chemical insight as possible into an untargeted MS2 dataset and to connect this chemical insight to the user’s underlying biological questions. This can be performed within one liquid chromatography (LC)-MS2 experiment or at the repository scale. GNPS-MassIVE is a public data repository for untargeted MS2 data with sample information (metadata) and annotated MS2 spectra. These publicly accessible data can be annotated and updated with the GNPS infrastructure keeping a continuous record of all changes. This knowledge is disseminated across all public data; it is a living dataset. Molecular networking—one of the main analysis tools used within the GNPS platform—creates a structured data table that reflects the molecular diversity captured in tandem mass spectrometry experiments by computing the relationships of the MS2 spectra as spectral similarity. This protocol provides step-by-step instructions for creating reproducible, high-quality molecular networks. For training purposes, the reader is led through a 90- to 120-min procedure that starts by recalling an example public dataset and its sample information and proceeds to creating and interpreting a molecular network. Each data analysis job can be shared or cloned to disseminate the knowledge gained, thus propagating information that can lead to the discovery of molecules, metabolic pathways, and ecosystem/community interactions. More... »

PAGES

1954-1991

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  • Journal

    TITLE

    Nature Protocols

    ISSUE

    6

    VOLUME

    15

    Author Affiliations

  • Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
  • Department of Pharmaceutical Sciences, College of Pharmacy, Oregon State University, Corvallis, OR, USA
  • Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
  • Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
  • Bioinformatics Group, Wageningen University, Wageningen, the Netherlands
  • College of Pharmacy, Sookmyung Women’s University, Seoul, Korea
  • Center of Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
  • ThalassOMICS Metabolomics Facility, Plateforme Corsaire, Biogenouest, Nantes, France
  • Department of Biotechnology, Acharya Nagarjuna University, Guntur, Nagarjuna Nagar, India
  • Centro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Panama City, Panama
  • Biomedical Innovation Department, CICESE, Ensenada, Mexico
  • Departamento de Química, Universidad Autónoma de Chiriquí (UNACHI), David, Chiriquí, Panama
  • Centro de Investigaciones en Productos Naturales (CIPRONA), Universidad de Costa Rica, San José, Costa Rica
  • Department of Drug Discovery and Development, Harrison School of Pharmacy, Auburn University, Auburn, AL, USA
  • School of Chemical & Physical Sciences, Victoria University of Wellington, Wellington, New Zealand
  • International R&D Division, Omnia Group (Pty) Ltd., Johannesburg, South Africa
  • Centre for Plant Metabolomics Research, Department of Biochemistry, University of Johannesburg, Auckland Park, South Africa
  • Institute of Inorganic and Analytical Chemistry, University of Münster, Münster, Germany
  • Department of Molecular Microbiology, John Innes Centre, Norwich, UK
  • Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
  • Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41596-020-0317-5

    DOI

    http://dx.doi.org/10.1038/s41596-020-0317-5

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1127540344

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/32405051


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