4.8 Article

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

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NATURE METHODS
卷 18, 期 7, 页码 747-756

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NATURE PORTFOLIO
DOI: 10.1038/s41592-021-01197-1

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资金

  1. European Union's Horizon 2020 research and innovation program, under PlantaSYST [739582, 664620]
  2. German Research Foundation (DFG) [210879364, 239748522]
  3. CGIAR Research Program on Roots, Tubers and Bananas (RTB)
  4. Biotechnology and Biological Sciences Research Council OPTICAR Project [BB/P001742/1]
  5. Huazhong Agricultural University Scientific & Technological Self-Innovation Foundation [2017RC002]
  6. NIH [5U54HG010426-03, 1U2CCA233311-01, R35GM130385]
  7. Shanghai Municipal Science and Technology Major Project [2017SHZDZX01]
  8. National Natural Science Foundation of China [31821002, 21934006]
  9. JSPS KAKENHI [19H03249, 19K06723]
  10. Grants-in-Aid for Scientific Research [19H03249, 19K06723] Funding Source: KAKEN

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Compound identification and reliable quantification in metabolomics are complicated by the chemical complexity and dynamic range of the metabolome, while quantification in complex mixtures can be further complicated by ion suppression and the presence of isomers.
This Perspective, from a large group of metabolomics experts, provides best practices and simplified reporting guidelines for practitioners of liquid chromatography- and gas chromatography-mass spectrometry-based metabolomics. 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.

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