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.
Department of Biological Sciences, Lehman College and The Graduate Center, City University of New York, 250 Bedford Park Boulevard West, Bronx, NY 10468, USA.
Shi-Biao
SB
Wu
Rachel S
RS
Meyer
Bruce D
BD
Whitaker
Amy
A
Litt
Edward J
EJ
Kennelly
D002851:Chromatography, High Pressure Liquid / Q000379:methods*; D013058:Mass Spectrometry / Q000379:methods*; D011801:Quinic Acid / Q000737:chemistry; D032322:Solanum / Q000737:chemistry* / Q000145:classification; D013045:Species Specificity
D011801:Quinic Acid
Discriminate analysis; Eggplant; LC–TOF-MS; Multivariate statistics; Phenolic compounds; Solanum