ArticleFrontiers in plant science2024
Untargeted metabolomics in
Article in Frontiers in plant science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Methods: Samples were collected from the main production areas across five regions in Fujian Province, China. An untargeted metabolomics analysis was performed on the entire plants to explore their metabolic profiles. We utilized UPLC-MS/MS to specifically quantify eight targeted flavonoids in these samples. Subsequently, correlation analysis was conducted to investigate the relationships between the flavonoids content and both the biological characteristics and geographical features. Results: A comprehensive analysis identified a total of 3,170 differential metabolites, with terpenoids and flavonoids being the most prevalent classes. A region-specific metabolite analysis revealed that the Yongchun (YC) region showed the highest diversity of unique metabolites, including tangeretin and oleanolic acid. Conversely, the Youxi (YX) region was found to have the smallest number of unique metabolites, with only one distinct compound identified. Further investigation through KEGG pathway enrichment analysis highlighted a significant enrichment in pathways related to flavonoid biosynthesis. Further examination of the flavonoid category showed that flavonols were the most differentially abundant. We quantified eight specific flavonoids, finding that, on average, the YX region exhibited higher levels of these compounds. Correlation analysis highlighted a significant association between flavonoids and habitat, especially temperature and humidity. Discussion: Untargeted metabolomics via LC-MS was suitable for identifying region-specific metabolites and their influence via habitat heterogeneity. The results of this study serve as a new theoretical reference for unique markers exclusively present in a specific sample group.
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