Rapid Communications in Mass Spectrometry · 2010 · 132 citations · 24 references
Life SciencesAgronomyPlant SciencesFood ChemistryMass Spectrometric AnalysisMetabolomicsLipidomicsMass Spectrometric ImagingMass SpectrometryMass Spectrometry-based MetabolomicsMass Spectrometry-based ProteomicsPlant MetabolomicsMass Spectrometry CharacterizationMass Spectrometry MetabolomicsMass Spectrometry-based Metabolite ProfilingMass Spectrometry-based ProfilingMatrix-assisted Laser Desorption/ionizationMatrix-assisted Laser Desorption/ionization ImagingMetabolite ImagingPlant Metabolite Profiling
Rice is one of the most important food crops in the world and new varieties have been bred for specific purposes, such as the development of drought-resistance, or the enrichment of functional food factors. The localization and composition of metabolites in such new varieties must be investigated because all artificial interventions are expected to change the metabolites of rice. Imaging mass spectrometry using matrix-assisted laser desorption/ionization (MALDI-IMS) is a suitable tool for investigating the localization and composition of metabolites; however, suitable methodologies for the MALDI-IMS analysis of rice have not yet been established. In this study, we optimized the methods for analyzing rice grains by MALDI-IMS using adhesive film and found the characteristic distribution of metabolites in rice. Lysophosphatidylcholine (LPC) was localized in the endosperm. Phosphatidylcholine (PC), gamma-oryzanol and phytic acid were localized in the bran (germ and seed coat), and alpha-tocopherol was distributed in the germ (especially in the scutellum). In addition, MALDI-IMS revealed the LPC and PC composition of the rice samples. The LPC composition, LPC (1-acyl 16:0), LPC (1-acyl 18:2), LPC (1-acyl 18:1) and LPC (1-acyl 18:0), was 59.4 +/- 4.5%, 19.6 +/- 2.5%, 14.2 +/- 4.5% and 6.8 +/- 1.4%. The PC composition, PC (diacyl 16:0/18:2), PC (diacyl 16:0/18:1), PC (diacyl 18:1/18:3), PC (diacyl 18:1/18:2) and PC (diacyl 18:1/18:2), was 19.6 +/- 1.0%, 21.0 +/- 1.0%, 15.0 +/- 1.4%, 26.7 +/- 0.7% and 17.8 +/- 1.9%. This approach can be applied to the assessment of metabolites not only in rice, but also in other foods for which the preparation of sections is a challenging task.
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