Plants synthesize hundreds to thousands of different chemicals. These chemicals, called metabolites, help plants adapt their natural environments. Scientists use a method called mass spectrometry to detect and measure the abundances of many chemicals in a plant or another sample. However, it is more challenging to identify individual metabolites in a mixed sample and their origin. Researchers need improved methods for such chemical analysis. Such tools would help researchers understand the origin of the metabolites that plants synthesize. It would also accelerate the identification of those metabolites and the genes responsible for their synthesis.
The hundreds of thousands of metabolites found in flowering plants influence a huge range of characteristics, such as the scent and color that flowers use to attract bees and other pollinators. One method of studying the pathways in plants related to their synthesis of metabolites is to introduce precursors labeled using radioactivity or isotopes. Precursors are chemicals or compounds that are a step before the target chemical in a pathway. Scientists can then track these precursors as they move through plants’ synthesis pathways. Previous labeling studies used these approaches to track just one or a few substances involved with plant metabolites. However, these approaches did not allow researchers to follow all other substances that might have incorporated the label. This new research developed an easy-to-use computational tool called PODIUM. This tool locates all the substances that incorporate carbon-13 labeled precursors in an experiment.
Researchers developed an isotopic labeling approach that established a library of metabolites produced from the amino acid phenylalanine in the stems of Arabidopsis plants (also called thale cress). By varying genotype, using both of loss-of-function mutants and natural variants, the researchers enhanced their understanding of how soluble phenylpropanoids are affected by mutations in genes encoding steps in these metabolic pathways. In addition, the researchers identified phenylalanine-derived mass spectrometry features that associate with natural polymorphisms that contribute to plant chemical diversity in the wild. This process located several new gene candidates that affect soluble phenylpropanoids and identified novel phenylalanine-derived metabolites.
This work was supported by the Department of Energy Office of Science, Biological and Environmental Research program. One of the researchers was supported in part by a Department of Agriculture National Institute of Food and Agriculture postdoctoral grant.