Exploring the metabolomic diversity of plant species across spatial (leaf and stem) components and phylogenic groups
| Autor: | Dong-Gu Oh, Digar Singh, Jong-Seok Lee, Choong Hwan Lee, Sarah Lee, Sunmin Lee |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0106 biological sciences
Metabolite Plant Science Biology Asteraceae 01 natural sciences Antioxidants Gas Chromatography-Mass Spectrometry 03 medical and health sciences chemistry.chemical_compound Metabolomics Antioxidant activity Metabolite profiling Tandem Mass Spectrometry lcsh:Botany Aromatic amino acids Shikimate pathway Amino Acids Rosaceae Chromatography High Pressure Liquid 030304 developmental biology chemistry.chemical_classification Flavonoids 0303 health sciences Plant Stems Monophenol Monooxygenase Plant Extracts Fatty Acids Catechin Fabaceae Amino acid lcsh:QK1-989 Plant Leaves Chemodiversity chemistry Biochemistry Tyrosinase inhibition activity Metabolome Kaempferol Plant parts Metabolic Networks and Pathways 010606 plant biology & botany Ellagic acid Chromatography Liquid Research Article |
| Zdroj: | BMC Plant Biology, Vol 20, Iss 1, Pp 1-10 (2020) BMC Plant Biology |
| ISSN: | 1471-2229 |
| Popis: | Background Plants have been used as an important source of indispensable bioactive compounds in various cosmetics, foods, and medicines. However, the subsequent functional annotation of these compounds seems arduous because of the largely uncharacterized, vast metabolic repertoire of plant species with known biological phenotypes. Hence, a rapid multi-parallel screening and characterization approach is needed for plant functional metabolites. Results Fifty-one species representing three plant families, namely Asteraceae, Fabaceae, and Rosaceae, were subjected to metabolite profiling using gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) and ultrahigh-performance liquid chromatography quadrupole orbitrap ion trap tandem mass spectrometry (UHPLC-Q-orbitrap-MS/MS) as well as multivariate analyses. Partial least squares discriminant analysis (PLS-DA) of the metabolite profiling datasets indicated a distinct clustered pattern for 51 species depending on plant parts (leaves and stems) and relative phylogeny. Examination of their relative metabolite contents showed that the extracts from Fabaceae plants were abundant in amino acids, fatty acids, and genistein compounds. However, the extracts from Rosaceae had higher levels of catechin and ellagic acid derivatives, whereas those from Asteraceae were higher in kaempferol derivatives and organic acids. Regardless of the different families, aromatic amino acids, branch chain amino acids, chlorogenic acid, flavonoids, and phenylpropanoids related to the shikimate pathway were abundant in leaves. Alternatively, certain amino acids (proline, lysine, and arginine) as well as fatty acids levels were higher in stem extracts. Further, we investigated the associated phenotypes, i.e., antioxidant activities, affected by the observed spatial (leaves and stem) and intra-family metabolomic disparity in the plant extracts. Pearson’s correlation analysis indicated that ellagic acid, mannitol, catechin, epicatechin, and quercetin derivatives were positively correlated with antioxidant phenotypes, whereas eriodictyol was positively correlated with tyrosinase inhibition activity. Conclusions This work suggests that metabolite profiling, including multi-parallel approaches and integrated bioassays, may help the expeditious characterization of plant-derived metabolites while simultaneously unraveling their chemodiversity. |
| Databáze: | OpenAIRE |
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