Flux profiling of photosynthetic carbon metabolism in intact plants

Full characterization of the metabolic state of a biological system involves quantifying the flux of the biochemical reactions. In this protocol, Arabidopsis rosettes are treated with 13 CO 2 , and 13 C-labeled metabolites are analyzed by GC- and LC-MS. Flux analysis has been carried out in plants f...

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Published in:Nature protocols Vol. 9; no. 8; pp. 1803 - 1824
Main Authors: Heise, Robert, Arrivault, Stéphanie, Szecowka, Marek, Tohge, Takayuki, Nunes-Nesi, Adriano, Stitt, Mark, Nikoloski, Zoran, Fernie, Alisdair R
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 01-08-2014
Nature Publishing Group
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Summary:Full characterization of the metabolic state of a biological system involves quantifying the flux of the biochemical reactions. In this protocol, Arabidopsis rosettes are treated with 13 CO 2 , and 13 C-labeled metabolites are analyzed by GC- and LC-MS. Flux analysis has been carried out in plants for decades, but technical innovations are now enabling it to be carried out in photosynthetic tissues in a more precise fashion with respect to the number of metabolites measured. Here we describe a protocol, using gas chromatography (GC)- and liquid chromatography (LC)-mass spectrometry (MS), to resolve intracellular fluxes of the central carbon metabolism in illuminated intact Arabidopsis thaliana rosettes using the time course of the unlabeled fractions in 40 major constituents of the metabolome after switching to 13 CO 2 . We additionally simplify modeling assumptions, specifically to cope with the presence of multiple cellular compartments. We summarize all steps in this 8–10-week-long process, including setting up the chamber; harvesting; liquid extraction and subsequent handling of sample plant material to chemical derivatization procedures such as silylation and methoxymation (necessary for gas chromatography only); choosing instrumentation settings and evaluating the resultant chromatogram in terms of both unlabeled and labeled peaks. Furthermore, we describe how quantitative insights can be gained by estimating both benchmark and previously unknown fluxes from collected data sets.
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ISSN:1754-2189
1750-2799
DOI:10.1038/nprot.2014.115