Exploring the amino acid-derived metabolomes of Arabidopsis and their associated natural variation using isotope labeling and mGWAS.

In this study, we used stable isotope labeling coupled with reversed-phase HPLC-MS to annotate the origin of metabolite features in Arabidopsis (Arabidopsis thaliana) (Columbia-0) seedling rosettes and stems. Using this strategy, a total of 1,240 metabolite features were shown to be derived from 15 amino acids, and these represented 10% to 30% of the total ion counts detected by untargeted LC-MS. The amino acid-derived metabolomes (AADMs) of rosettes and stems exhibited differing patterns of accumulation. Precursor-of-origin annotations (POA) revealed that some metabolites were generated solely from individual amino acids, whereas others were derived from multiple sources. Amino acid feeding altered the abundance of their corresponding AADMs as well as the levels of features derived from other amino acids. These data suggest that the accumulation of amino acid-derived features (AADFs) is restricted by availability of their amino acid precursors and that perturbation of amino acid metabolic networks can lead to long distance changes in end-product accumulation. The alignment of annotated AADFs with features from a previous metabolic genome-wide association study (mGWAS) led to the identification of 87,820 and 61,618 metabolite feature-SNP associations (P < 10-4) in leaves and stems, respectively. Genes associated with AADF accumulation, including METHYLTHIOALKYLMALATE SYNTHASE 1 (MAM1) and D-AMINO ACID RACEMASE 1 (DAAR1), were retrieved from this analysis, demonstrating that the integration of isotope labeling and mGWAS can contribute to the identification of genes involved in plant metabolite accumulation.