Location: Food Quality Laboratory
Title: A New LC-MS-based Strategy to integrate chemistry, morphology, and evolution of eggplant (Solanum) species Authors
|Wu, Shi-Biao -|
|Meyer, Rachel -|
|Litt, Amy -|
|Kennelly, Edward -|
Submitted to: Journal of Chromatography A
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 6, 2013
Publication Date: N/A
Repository URL: http://handle.nal.usda.gov/10113/58955
Interpretive Summary: The economically important plant genus Solanum includes the valuable crop species tomato, potato, and eggplant as well as numerous wild relatives that are mostly regarded as noxious weeds. While the major Solanum vegetables do not entirely lack human health-promoting metabolites, their levels and arrays of beneficial compounds could be much improved by introducing selected genes from related wild species. Using cutting-edge analytical tools, a Solanum metabolic database was generated representing 62 compounds of interest from 24 species. The new database enabled creation of a detailed biosynthetic pathway of metabolites in Solanum, which is essential to determine how the abundant and diverse bioactive chemicals are produced in wild and cultivated species. This knowledge will aid public and private plant breeders in developing new lines of Solanum crops with superior nutritive value. A long-range benefit of this research is a reduced incidence of diabetes, cardiovascular disease, and other chronic health problems in the U.S. that cost many billions of dollars annually.
Technical Abstract: The economically valuable giant genus Solanum, containing dozens of functional food species such as eggplant and tomato, affords an excellent system to compare and correlate metabolic chemistry with species morphology and evolution. Here, we devised 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, 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 detailed biosynthetic pathway of Solanum metabolites was created. In addition, three statistical models, PCA, PLS, and OPLS-DA, were used to classify the origin of eggplant species and find the differences between groups of phylogenetically-related species and species sharing the same use (food or medicine). As a result, seven marker metabolites were identified to distinguish four Solanum sections. This is the first metabolic study of the genus Solanum that provides a means to investigate the origin of compounds in the evolutionary process. This new strategy combining an LC-MS data with multivariate statistical analysis was proven effective in studying the metabolic network within a large genus; integrating complicated chemistry, morphology, and evolutionary relationships. Another product of this study was the creation of a useful new tool for metabolic analysis, the Solanum metabolic database (SMD).