A new liquid chromatography-mass spectrometry-based strategy to integrate chemistry, morphology, and evolution of eggplant (Solanum) species.

This study presents a strategy based on repeatable reversed-phase LC-TOF-MS methods and statistical tools, including untargeted PCA and targeted PLS/OPLS-DA models, to analyze 31 accessions representing 24 species in the eggplant genus Solanum (Solanaceae), including eight species whose metabolic profiles were studied for the first time. Sixty-two Solanum metabolites were identified after detailed analysis of UV absorbance spectra, mass spectral fragmentation patterns, NMR spectra, and/or co-injection experiments with authentic standards. Among these were two new 5-O-caffeoylquinic acid derivatives that were identified by analyzing their MS/MS fragmentation. Based on these results, a Solanum metabolic database (SMD) and a detailed biosynthetic pathway of Solanum metabolites were created. Results of analyses identified seven marker metabolites that distinguish four Solanum sections, and revealed species-specific chemical patterns. Combining LC-MS data with multivariate statistical analysis was proven effective in studying the metabolic network within the large genus Solanum, allowing for integration of complicated chemistry, morphology, and evolutionary relationships.