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Aron AT, Gentry EC, McPhail KL, Nothias LF, Nothias-Esposito M, Bouslimani A, Petras D, Gauglitz JM, Sikora N, Vargas F, van der Hooft JJJ, Ernst M, Kang KB, Aceves CM, Caraballo-Rodríguez AM, Koester I, Weldon KC, Bertrand S, Roullier C, Sun K, Tehan RM, Boya P CA, Christian MH, Gutiérrez M, Ulloa AM, Tejeda Mora JA, Mojica-Flores R, Lakey-Beitia J, Vásquez-Chaves V, Zhang Y, Calderón AI, Tayler N, Keyzers RA, Tugizimana F, Ndlovu N, Aksenov AA, Jarmusch AK, Schmid R, Truman AW, Bandeira N, Wang M, Dorrestein PC. Reproducible molecular networking of untargeted mass spectrometry data using GNPS. Nat Protoc 2020; 15:1954-1991. [PMID: 32405051 DOI: 10.1038/s41596-020-0317-5] [Citation(s) in RCA: 331] [Impact Index Per Article: 66.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Accepted: 03/03/2020] [Indexed: 02/06/2023]
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.
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Affiliation(s)
- Allegra T Aron
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Emily C Gentry
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Kerry L McPhail
- Department of Pharmaceutical Sciences, College of Pharmacy, Oregon State University, Corvallis, OR, USA
| | - Louis-Félix Nothias
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Mélissa Nothias-Esposito
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Amina Bouslimani
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Daniel Petras
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
| | - Julia M Gauglitz
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Nicole Sikora
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Fernando Vargas
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
- Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
| | | | - Madeleine Ernst
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Kyo Bin Kang
- College of Pharmacy, Sookmyung Women's University, Seoul, Korea
| | - Christine M Aceves
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | | | - Irina Koester
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
| | - Kelly C Weldon
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
- Center of Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
| | - Samuel Bertrand
- Groupe Mer, Molécules, Santé-EA 2160, UFR des Sciences Pharmaceutiques et Biologiques, Université de Nantes, Nantes, France
- ThalassOMICS Metabolomics Facility, Plateforme Corsaire, Biogenouest, Nantes, France
| | - Catherine Roullier
- College of Pharmacy, Sookmyung Women's University, Seoul, Korea
- ThalassOMICS Metabolomics Facility, Plateforme Corsaire, Biogenouest, Nantes, France
| | - Kunyang Sun
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Richard M Tehan
- Department of Pharmaceutical Sciences, College of Pharmacy, Oregon State University, Corvallis, OR, USA
| | - Cristopher A Boya P
- Centro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Panama City, Panama
- Department of Biotechnology, Acharya Nagarjuna University, Guntur, Nagarjuna Nagar, India
| | - Martin H Christian
- Centro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Panama City, Panama
| | - Marcelino Gutiérrez
- Centro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Panama City, Panama
| | | | | | - Randy Mojica-Flores
- Centro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Panama City, Panama
- Departamento de Química, Universidad Autónoma de Chiriquí (UNACHI), David, Chiriquí, Panama
| | - Johant Lakey-Beitia
- Centro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Panama City, Panama
| | - Victor Vásquez-Chaves
- Centro de Investigaciones en Productos Naturales (CIPRONA), Universidad de Costa Rica, San José, Costa Rica
| | - Yilue Zhang
- Department of Drug Discovery and Development, Harrison School of Pharmacy, Auburn University, Auburn, AL, USA
| | - Angela I Calderón
- Department of Drug Discovery and Development, Harrison School of Pharmacy, Auburn University, Auburn, AL, USA
| | - Nicole Tayler
- Centro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Panama City, Panama
- Department of Biotechnology, Acharya Nagarjuna University, Guntur, Nagarjuna Nagar, India
| | - Robert A Keyzers
- School of Chemical & Physical Sciences, Victoria University of Wellington, Wellington, New Zealand
| | - Fidele Tugizimana
- Centre for Plant Metabolomics Research, Department of Biochemistry, University of Johannesburg, Auckland Park, South Africa
- International R&D Division, Omnia Group (Pty) Ltd., Johannesburg, South Africa
| | - Nombuso Ndlovu
- Centre for Plant Metabolomics Research, Department of Biochemistry, University of Johannesburg, Auckland Park, South Africa
| | - Alexander A Aksenov
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Alan K Jarmusch
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Robin Schmid
- Institute of Inorganic and Analytical Chemistry, University of Münster, Münster, Germany
| | - Andrew W Truman
- Department of Molecular Microbiology, John Innes Centre, Norwich, UK
| | - Nuno Bandeira
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA.
| | - Mingxun Wang
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA.
| | - Pieter C Dorrestein
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA.
- Center for Computational Mass Spectrometry, University of California, San Diego, La Jolla, CA, USA.
- Department of Pharmacology, University of California, San Diego, La Jolla, CA, USA.
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
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Sugimura N, Furuya A, Yatsu T, Shibue T. Comparison of the applicability of mass spectrometer ion sources using a polarity- molecular weight scattergram with a 600 sample in-house chemical library. EUROPEAN JOURNAL OF MASS SPECTROMETRY (CHICHESTER, ENGLAND) 2015; 21:91-96. [PMID: 26181282 DOI: 10.1255/ejms.1345] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
To provide a practical guideline for the selection of a mass spectrometer ion source, we compared the applicability of three types of ion source: direct analysis in real time (DART), electrospray ionization (ESI) and fast atom bombardment (FAB), using an in-house high-resolution mass spectrometry sample library consisting of approximately 600 compounds. The great majority of the compounds (92%), whose molecular weights (MWs) were broadly distributed between 150 and 1000, were detected using all the ion sources. Nevertheless, some compounds were not detected using specific ion sources. The use of FAB resulted in the highest sample detection rate (>98%), whereas the detection rates obtained using DART and ESI were slightly lower (>96%). A scattergram constructed using MW and topological polar surface area (tPSA) as a substitute for molecular polarity showed that the performance of ESI was weak in the low-MW (<400), low-polarity (tPSA<60) area, whereas the performance of DART was weak in the high-MW (>800) area. These results might provide guidelines for the selection of ion sources for inexperienced mass spectrometry users.
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Affiliation(s)
- Natsuhiko Sugimura
- Materials Characterization Central Laboratory, Waseda University, 3-4-1 Ohkubo, Shinjyuku, Tokyo 169-8555, Japan.
| | - Asami Furuya
- Materials Characterization Central Laboratory, Waseda University, 3-4-1 Ohkubo, Shinjyuku, Tokyo 169-8555, Japan.
| | - Takahiro Yatsu
- Materials Characterization Central Laboratory, Waseda University, 3-4-1 Ohkubo, Shinjyuku, Tokyo 169-8555, Japan.
| | - Toshimichi Shibue
- Materials Characterization Central Laboratory, Waseda University, 3-4-1 Ohkubo, Shinjyuku, Tokyo 169-8555, Japan.
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