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Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry


Untargeted metabolomics aims to gather information on as many metabolites as possible in biological systems by taking into account all information present in the data sets. Here we describe a detailed protocol for large-scale untargeted metabolomics of plant tissues, based on reversed phase liquid chromatography coupled to high-resolution mass spectrometry (LC-QTOF MS) of aqueous methanol extracts. Dedicated software, MetAlign, is used for automated baseline correction and alignment of all extracted mass peaks across all samples, producing detailed information on the relative abundance of thousands of mass signals representing hundreds of metabolites. Subsequent statistics and bioinformatics tools can be used to provide a detailed view on the differences and similarities between (groups of) samples or to link metabolomics data to other systems biology information, genetic markers and/or specific quality parameters. The complete procedure from metabolite extraction to assembly of a data matrix with aligned mass signal intensities takes about 6 days for 50 samples.

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Figure 1: LC-QTOF MS profiling of crude extracts from three different plant species.
Figure 2: Schematic overview of experimental setup and data flow for untargeted LC-QTOF MS-based metabolomics of plant materials.
Figure 3: Interface of MetAlign software used for untargeted processing of LC-QTOF MS data files.
Figure 4: Timing of standard procedure of untargeted LC-MS analyses, based on 50 Arabidopsis seedling samples and LC-MS analysis time of 1 h.
Figure 5: Stability of the LC-QTOF MS system during 240 h continuous analyses of crude plant extracts (ESI negative mode).
Figure 6: Correlation between conventional LC-PDA analysis and untargeted LC-MS-based metabolomics with regard to detection of the flavonoid rutin (for identification, see Fig.1f).
Figure 7: Hierarchical clustering (Pearson correlation) of 180 A. thaliana genotypes consisting of a recombinant inbred line (RIL) population and their parents, based on untargeted metabolomics data.


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The preparation of this paper and the work described herein was made possible through funding from the Centre for BioSystems Genomics (which is part of the Netherlands Genomics Initiative and The Netherlands Organisation for Scientific Research), Plant Research International (PRI) and the EU project META-PHOR (Food-CT-2006-03622). We thank Harry Jonker and Bert Schipper (PRI) and Jeroen Jansen (NIOO, Heteren, The Netherlands) for their excellent help in sample preparation and LC-PDA-QTOF MS analyses.

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Correspondence to Ric CH De Vos.

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De Vos, R., Moco, S., Lommen, A. et al. Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry. Nat Protoc 2, 778–791 (2007).

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