Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography–mass spectrometry (GC–MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC–MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples. © 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.

Авторы
Aksenov A.A. 1, 2 , Laponogov I. 3 , Zhang Z. 1 , Doran S.L.F. 3 , Belluomo I. 3 , Veselkov D. 5, 4 , Bittremieux W. 2, 6, 1 , Nothias L.F. 2, 1 , Nothias-Esposito M. 1, 2 , Maloney K.N. 7, 1 , Misra B.B. 8 , Melnik A.V. 1 , Smirnov A. 9 , Du X. 9 , Jones K.L. 1 , II , Panitchpakdi M. 1 , Ernst M. 10, 1 , Van Der Hooft J.J.J. , Gonzalez M. 12 , Carazzone C. 12 , Amézquita A. 13 , Callewaert C. 15, 14 , Morton J.T. 15, 41 , Quinn R.A. 16 , Bouslimani A. 2, 1 , Orio A.A. 17 , Petras D. 1, 2 , Smania A.M. 18, 19 , Couvillion S.P. 20 , Burnet M.C. 20 , Nicora C.D. 20 , Zink E. 20 , Metz T.O. 20 , Artaev V. 21 , Humston-Fulmer E. 21 , Gregor R. 22 , Meijler M.M. 22 , Mizrahi I. 23 , Eyal S. 23 , Anderson B. 24 , Dutton R. 24 , Lugan R. 25 , Boulch P.L. 25 , Guitton Y. 26 , Prevost S. 26 , Poirier A. 26 , Dervilly G. 26 , Le Bizec B. , Fait A. 27 , Persi N.S. 27 , Song C. 27 , Gashu K. 27 , Coras R. 28 , Guma M. 28 , Manasson J. 29 , Scher J.U. 29 , Barupal D.K. 30 , Alseekh S. 31, 32 , Fernie A.R. 31, 32 , Mirnezami R. 33 , Vasiliou V. 34 , Schmid R. 35 , Borisov R.S. 36 , Kulikova L.N. 37 , Knight R. 38, 39, 40, 15 , Wang M. 2, 1 , Hanna G.B. 3 , Dorrestein P.C. 15, 1, 2, 38 , Veselkov K. 3
Journal
Nature Biotechnology
Издательство
Nature Research
Номер выпуска
2
Язык
English
Страницы
169-173
Статус
Published
Ссылка
Внешняя ссылка
DOI
10.1038/S41587-020-0700-3
Том
39
Год
2021
Организации
  • 1 Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, United States
  • 2 Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California,San Diego, La Jolla, CA, United States
  • 3 Department of Surgery and Cancer, Imperial College London, South Kensington Campus, London, United Kingdom
  • 4 Intelligify Limited, London, United Kingdom
  • 5 Department of Computing, Imperial College, South Kensington Campus, London, United Kingdom
  • 6 Department of Computer Science, University of Antwerp, Antwerp, Belgium
  • 7 Department of Chemistry, Point Loma Nazarene University, San Diego, CA, United States
  • 8 Center for Precision Medicine, Department of Internal Medicine, Section of Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC, United States
  • 9 Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC, United States
  • 10 Section for Clinical Mass Spectrometry, Department of Congenital Disorders, Danish Center for Neonatal Screening, Statens Serum Institut, Copenhagen, Denmark
  • 11 Bioinformatics Group, Wageningen University, Wageningen, Netherlands
  • 12 Department of Chemistry, Universidad de los Andes, Bogotá, Colombia
  • 13 Department of Biological Sciences, Universidad de los Andes, Bogotá, Colombia
  • 14 Center for Microbial Ecology and Technology, Ghent, Belgium
  • 15 Department of Pediatrics, University of California, San Diego, La Jolla, CA, United States
  • 16 Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, United States
  • 17 IRNASUS, Universidad Católica de Córdoba, CONICET, Facultad de Ciencias Agropecuarias, Córdoba, Argentina
  • 18 Universidad Nacional de Córdoba, Facultad de Ciencias Químicas, Departamento de Química Biológica Ranwel Caputto, Córdoba, Argentina
  • 19 CONICET, Universidad Nacional de Córdoba, Centro de Investigaciones en Química Biológica de Córdoba (CIQUIBIC), Córdoba, Argentina
  • 20 Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
  • 21 LECO Corporation, St. Joseph, MI, United States
  • 22 Department of Chemistry and the National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
  • 23 Department of Life Sciences and the National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
  • 24 Division of Biological Sciences, University of California, San Diego, La Jolla, CA, United States
  • 25 UMR Qualisud, Université d’Avignon et des Pays du Vaucluse, Agrosciences, Avignon, France
  • 26 Laboratoire d’Etude des Résidus et Contaminants dans les Aliments (LABERCA), Oniris, INRAe, Nantes, France
  • 27 The French Associates Institute for Agriculture and Biotechnology of Dryland, The Jacob Blaustein Institutes for Desert Research, Ben Gurion University of the Negev, Sede Boqer Campus, Beer Sheva, Israel
  • 28 Division of Rheumatology, Department of Medicine, University of California, San Diego, La Jolla, CA, United States
  • 29 Division of Rheumatology, Department of Medicine, New York University School of Medicine, New York, NY, United States
  • 30 Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
  • 31 Max Planck Institute for Molecular Plant Physiology, Potsdam-Golm, Germany
  • 32 Center of Plant Systems Biology and Biotechnology (CPSBB), Plovdiv, Bulgaria
  • 33 Department of Colorectal Surgery, Royal Free Hospital NHS Foundation Trust, Hampstead, London, United Kingdom
  • 34 Department of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven, CT, United States
  • 35 Institute of Inorganic and Analytical Chemistry, University of Münster, Münster, Germany
  • 36 A.V. Topchiev Institute of Petrochemical Synthesis RAS, Moscow, Russian Federation
  • 37 Рeoples’ Friendship University of Russia (RUDN University), Moscow, Russian Federation
  • 38 UCSD Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, United States
  • 39 Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States
  • 40 Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA, United States
  • 41 Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, United States
Ключевые слова
Drug products; Factorization; Mass spectrometry; Turing machines; Fragmentation patterns; Machine learning approaches; Mass spectrometry data; Natural products; Nonnegative matrix factorization; Reproducibilities; Work-flows; Gas chromatography; algorithm; animal; Anura; human; mass fragmentography; metabolomics; Algorithms; Animals; Anura; Gas Chromatography-Mass Spectrometry; Humans; Metabolomics
Цитировать
ГОСТ MLA RIS BibTex
Поделиться

Другие записи