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

Saleh Alseekh(Center of Plant Systems Biology and Biotechnology), Asaph Aharoni(Weizmann Institute of Science), Yariv Brotman(Ben-Gurion University of the Negev), Kévin Contrepois(Stanford University), John C. D’Auria(Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK)), Jan Ewald(Friedrich Schiller University Jena), Jennifer C. Ewald(Friedrich Schiller University Jena), Paul D. Fraser(Royal Holloway University of London), Patrick Giavalisco(Max Planck Institute for Biology of Ageing), Robert D. Hall(Wageningen University & Research), Matthias Heinemann(University of Groningen), Hannes Link(Max Planck Institute for Terrestrial Microbiology), Jie Luo(Hainan University), Steffen Neumann(Leibniz Institute of Plant Biochemistry), Jens Nielsen(BioInnovation Institute), Leonardo Perez de Souza(Max Planck Institute of Molecular Plant Physiology), Kazuki Saito(Chiba University), Uwe Sauer(ETH Zurich), Frank C. Schroeder(Cornell University), Stefan Schuster(Friedrich Schiller University Jena), Gary Siuzdak(Scripps Research Institute), Aleksandra Skirycz(Cornell University), Lloyd W. Sumner(University of Missouri), M Snyder(Stanford University), Huiru Tang(Fudan University), Takayuki Tohge(Nara Institute of Science and Technology), Yulan Wang(Nanyang Technological University), Weiwei Wen(Huazhong Agricultural University), Si Wu(Stanford University), Guowang Xu(Dalian Institute of Chemical Physics), Nicola Zamboni(ETH Zurich), Alisdair R. Fernie(Center of Plant Systems Biology and Biotechnology)
Nature Methods
July 1, 2021
Cited by 1,045Open Access
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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. 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.


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