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Public Library of Science, PLoS ONE, 9(11), p. e0163258

DOI: 10.1371/journal.pone.0163258

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Metabolic Profiling of Intact Arabidopsis thaliana Leaves during Circadian Cycle Using 1H High Resolution Magic Angle Spinning NMR.

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Arabidopsis thaliana is the most widely used model organism for research in plant biology. While significant advances in understanding plant growth and development have been made by focusing on the molecular genetics of Arabidopsis, extracting and understanding the functional framework of metabolism is challenging, both from a technical perspective due to losses and modification during extraction of metabolites from the leaves, and from the biological perspective, due to random variation obscuring how well the function is performed. The purpose of this work is to establish the in vivo metabolic profile directly from the Arabidopsis thaliana leaves without metabolite extraction, to reduce the complexity of the results by multivariate analysis, and to unravel the mitigation of cellular complexity by predominant functional periodicity. To achieve this, we use the circadian cycle that strongly influences metabolic and physiological processes and exerts control over the photosynthetic machinery. High resolution-magic angle spinning nuclear magnetic resonance (HR-MAS NMR) was applied to obtain the metabolic profile directly from intact Arabidopsis leaves. Combining one- and two-dimensional 1H HR-MAS NMR allowed the identification of several metabolites including sugars and amino acids in intact leaves. Multivariate analysis on HR-MAS NMR spectra of leaves throughout the circadian cycle revealed modules of primary metabolites with significant and consistent variations of their molecular components at different time points of the circadian cycle. Since robust photosynthetic performance in plants relies on the functional periodicity of the circadian rhythm, our results show that HR-MAS NMR promises to be an important non-invasive method that can be used for metabolomics of the Arabidopsis thaliana mutants with altered physiology and photosynthetic efficiency.