Abstract
Although the genus Rhododendron is globally distributed and rich in bioactive constituents, the metabolomic landscapes of most species remain unexplored, hampering elucidation of their adaptive strategies and pharmaceutical potential. OBJECTIVES: This study sought to construct comprehensive metabolic atlases of four representative yet understudied Rhododendron species-R. triflorum, R. faucium, R. nivale, and R. strigillosum-and to quantify inter-specific metabolic divergence by UPLC-MS/MS-based, widely targeted metabolomics. METHODS: The petals of four Rhododendron species were freeze-dried, pulverised, and extracted with 70% methanol (containing an internal standard). Metabolites were separated on an SB-C18 column (2.1 × 100 mm, 1.8 µm) using a 0-95% acetonitrile gradient (flow rate 0.35 mL min(-1), 40 °C) and analysed by tandem mass spectrometry. Reliable quantification was ensured by molecular weight database matching, ion source standardisation, and quality control (QC), achieving a coefficient of variation (CV) < 15%. Principal component analysis (PCA) and optimised partial least squares discriminant analysis (OPLS-DA) were performed on standardised data with unit variance. RESULTS: A total of 3705 metabolites were confidently identified, dominated by flavonoids (870), terpenoids (572), phenolic acids (394), and amino-acid derivatives (332). PCA and OPLS-DA models revealed clear species-specific clustering (R(2)Y ≥ 0.98, Q(2) ≥ 0.95; permutation test p < 0.01). Comparative analysis yielded 1495 significantly differential metabolites; R. triflorum exhibited the highest cumulative abundance, followed by R. faucium, R. nivale, and R. strigillosum. KEGG enrichment highlighted "metabolic pathways" as the most significantly over-represented, together with flavonoid biosynthesis, phenylpropanoid metabolism, and terpenoid backbone biosynthesis. CONCLUSIONS: The study delivers the first high-coverage metabolomic reference for four neglected Rhododendron species, evidencing profound inter-specific metabolic differentiation centred on flavonoids, terpenoids, and phenolic acids. The data provide a robust foundation for understanding molecular adaptation to alpine environments and for accelerating targeted drug discovery from Rhododendron resources.