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Mass spectrometry-based metabolomics: a guide for annotation, quantification and best reporting practices

  • Saleh Alseekh*
  • , Asaph Aharoni
  • , Yariv Brotman
  • , Kévin Contrepois
  • , John D’Auria
  • , Jan Ewald
  • , Jennifer C. Ewald
  • , Paul D. Fraser
  • , Patrick Giavalisco
  • , Robert D. Hall
  • , Matthias Heinemann
  • , Hannes Link
  • , Jie Luo
  • , Steffen Neumann
  • , Jens Nielsen
  • , Leonardo Perez de Souza
  • , Kazuki Saito
  • , Uwe Sauer
  • , Frank C. Schroeder
  • , Stefan Schuster
  • Gary Siuzdak, Aleksandra Skirycz, Lloyd W. Sumner, Michael P. Snyder, Huiru Tang, Takayuki Tohge, Yulan Wang, Weiwei Wen, Si Wu, Guowang Xu, Nicola Zamboni, Alisdair R. Fernie*
*Corresponding author for this work
  • Max Planck Institute of Molecular Plant Physiology
  • Centre for Plant Systems Biology and Biotechnology
  • Weizmann Institute of Science
  • Ben-Gurion University of the Negev
  • Stanford University
  • Leibniz Institute of Plant Genetics and Crop Plant Research
  • Friedrich Schiller University Jena
  • University of Tübingen
  • Royal Holloway University of London
  • Max Planck Institute for Biology of Ageing
  • Wageningen University & Research
  • University of Groningen
  • Max Planck Institute for Terrestrial Microbiology
  • Hainan University
  • Leibniz Institute of Plant Biochemistry
  • BioInnovation Institute
  • Chalmers University of Technology
  • Chiba University
  • RIKEN
  • ETH Zurich - Institute for Particle Physics and Astrophysics (IPA)
  • Cornell University
  • Scripps Research Institute
  • University of Missouri
  • Fudan University
  • Nara Institute of Science and Technology
  • Nanyang Technological University
  • Huazhong Agricultural University
  • CAS - Dalian Institute of Chemical Physics

Research output: Contribution to journalReview articlepeer-review

945 Scopus citations

Abstract

Mass spectrometry-based metabolomics approaches can enable detection and quantification of many thousands of metabolite features simultaneously. However, compound identification and reliable quantification are greatly complicated owing to the chemical complexity and dynamic range of the metabolome. Simultaneous quantification of many metabolites within complex mixtures can additionally be complicated by ion suppression, fragmentation and the presence of isomers. Here we present guidelines covering sample preparation, replication and randomization, quantification, recovery and recombination, ion suppression and peak misidentification, as a means to enable high-quality reporting of liquid chromatography– and gas chromatography–mass spectrometry-based metabolomics-derived data.

Original languageEnglish
Pages (from-to)747-756
Number of pages10
JournalNature Methods
Volume18
Issue number7
DOIs
StatePublished - Jul 2021
Externally publishedYes

Funding

FundersFunder number
Consortium of International Agricultural Research Centers
National Institutes of Health
Shanghai Municipal Science and Technology2017SHZDZX01
Deutsche Forschungsgemeinschaft210879364, 239748522
Huazhong Agricultural University2017RC002
National Human Genome Research InstituteU54HG010426
Forecast Public Art664620
National Natural Science Foundation of China21934006, 31821002
National Institute of Environmental Health SciencesU2CES030167
National Institute of General Medical SciencesR35GM131877, R35GM130385
Horizon 2020 Framework Programme739582
Japan Society for the Promotion of Science19H03249, 19K06723, R35GM130385
National Cancer InstituteU2CCA233311
Biotechnology and Biological Sciences Research CouncilBB/P001742/1, BB/M025829/1

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