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

Alseekh, S.; Aharoni, Asaph; Brotman, Yariv; Contrepois, Kévin; D’Auria, John; Ewald, Jan; C. Ewald, Jennifer; Fraser, Paul D.; Giavalisco, Patrick; Hall, Robert D.; Heinemann, Matthias; Link, Hannes; Luo, Jie; Neumann, Steffen; Nielsen, Jens; de Souza, L. P.; Saito, Kazuki; Sauer, Uwe; Schroeder, Frank C.; Schuster, Stefan; Siuzdak, Gary; Skirycz, A.; Sumner, Lloyd W.; Snyder, Michael P.; Tang, Huiru; Tohge, Takayuki; Wang, Yulan; Wen, Weiwei; Wu, Si; Xu, Guowang; Zamboni, Nicola; Fernie, A. R.

doi:10.1038/s41592-021-01197-1

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学術論文

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

MPS-Authors

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Alseekh, S.
The Genetics of Crop Metabolism, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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de Souza, L. P.
Central Metabolism, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Skirycz, A.
Small-Molecule Signalling, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Fernie, A. R.
Central Metabolism, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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引用

Alseekh, S., Aharoni, A., Brotman, Y., Contrepois, K., D’Auria, J., Ewald, J., C. Ewald, J., Fraser, P. D., Giavalisco, P., Hall, R. D., Heinemann, M., Link, H., Luo, J., Neumann, S., Nielsen, J., de Souza, L. P., Saito, K., Sauer, U., Schroeder, F. C., Schuster, S., Siuzdak, G., Skirycz, A., Sumner, L. W., Snyder, M. P., Tang, H., Tohge, T., Wang, Y., Wen, W., Wu, S., Xu, G., Zamboni, N., & Fernie, A. R. (2021). Mass spectrometry-based metabolomics: a guide for annotation, quantification and best reporting practices. Nature Methods, 18(7), 747-756. doi:10.1038/s41592-021-01197-1.

引用: https://hdl.handle.net/21.11116/0000-0008-D920-F

要旨

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.