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UHPLC-HRMS/MS on untargeted metabolomics: a case study with (Fabaceae)
Untargeted metabolomics is a powerful tool in chemical fingerprinting. It can be applied in phytochemistry to aid species identification, systematic studies and quality control of bioproducts. This approach aims to produce as much chemical information as possible, without focusing on any specific ch...
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Published in: | RSC advances 2021-07, Vol.11 (4), p.2596-2513 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | |
Online Access: | Get full text |
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Summary: | Untargeted metabolomics is a powerful tool in chemical fingerprinting. It can be applied in phytochemistry to aid species identification, systematic studies and quality control of bioproducts. This approach aims to produce as much chemical information as possible, without focusing on any specific chemical class, thus, requiring extensive chemometric effort. This study aimed to evaluate the feasibly of an untargeted metabolomics method in phytochemistry by a study case of the
Copaifera
genus (Fabaceae). This genus contains significant medicinal species used worldwidely.
Copaifera
exploitation issues include a lack of chemical data, ambiguous species identification methods and absence of quality control for its bioproducts. Different organs of five
Copaifera
species were analysed by UHPLC-HRMS/MS, GNPS platform and chemometric tools. Untargeted metabolomics enabled the identification of 19 chemical markers and 29 metabolites, distinguishing each sample by species, plant organs, and biome type. Chemical markers were classified as flavonoids, terpenoids and condensed tannins. The applied method provided reliable information about species chemodiversity using fast workflow with little sampling size. The untargeted approach by UHPLC-HRMS/MS proved to be a promising tool for species identification, pharmacological prospecting and in the future for the quality control of extracts used in the manufacture of bioproducts.
UHPLC-HRMS/MS untargeted metabolomics enabled distinction of
Copaifera
extracts by species, vegetative parts, and biome of origin based on 19 chemical markers. |
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ISSN: | 2046-2069 |
DOI: | 10.1039/d1ra03163e |