Jun Lao, Nannan Wang, Chuyu Yao, Xiangmin Piao
Based on the metabolomic profiles, we hypothesize a putative trade-off model in which floral color divergence may change upstream carbon flux allocation between the triterpenoid saponin and flavonoid pathways. The young fruit stage of white-flowered plants is a candidate harvesting period for bioactive saponins. These conclusions are based only on the pattern of metabolite accumulation and need to be validated by multi-omics.
BACKGROUND: Flower color is a well-defined trait in Platycodon grandiflorus, whereas little is known about the effects of flower color variation on the metabolic profiles of reproductive organs. Triterpenoid saponins and flavonoids have common precursors upstream, suggesting a potential carbon flux trade-off.
METHODS: Untargeted UPLC-MS/MS metabolomics was performed on the reproductive organs of purple- and white-flowered P. grandiflorus at six stages of flower development. Mfuzz time-series clustering, PCA, and metabolite correlation networks were used for data analysis.
RESULTS: Six clusters were assigned to 25 metabolites (17 triterpenoid saponins and 8 flavonoids). Flavonoid glycosides were found to possess a conserved inverted V-shaped accumulation pattern in both germplasms. By contrast, saponins derived from triterpenoids showed strong germplasm-dependent accumulation patterns. White-flowered plants showed sustained accumulation, with a peak at the young fruit stage. In purple-flowered plants, accumulation peaked transiently at the withering stage, followed by a decline. PCA validated that metabolic divergence increased with developmental progression.
CONCLUSIONS: Based on the metabolomic profiles, we hypothesize a putative trade-off model in which floral color divergence may change upstream carbon flux allocation between the triterpenoid saponin and flavonoid pathways. The young fruit stage of white-flowered plants is a candidate harvesting period for bioactive saponins. These conclusions are based only on the pattern of metabolite accumulation and need to be validated by multi-omics.