Accumulation mechanism of metabolite markers identified by machine learning between Qingyuan and Xiushui counties in Polygonatum cyrtonema Hua.
BMC Plant Biol
; 24(1): 173, 2024 Mar 06.
Article
em En
| MEDLINE
| ID: mdl-38443808
ABSTRACT
Polygonatum cyrtonema Hua is a traditional Chinese medicinal plant acclaimed for its therapeutic potential in diabetes and various chronic diseases. Its rhizomes are the main functional parts rich in secondary metabolites, such as flavonoids and saponins. But their quality varies by region, posing challenges for industrial and medicinal application of P. cyrtonema. In this study, 482 metabolites were identified in P. cyrtonema rhizome from Qingyuan and Xiushui counties. Cluster analysis showed that samples between these two regions had distinct secondary metabolite profiles. Machine learning methods, specifically support vector machine-recursive feature elimination and random forest, were utilized to further identify metabolite markers including flavonoids, phenolic acids, and lignans. Comparative transcriptomics and weighted gene co-expression analysis were performed to uncover potential candidate genes including CHI, UGT1, and PcOMT10/11/12/13 associated with these compounds. Functional assays using tobacco transient expression system revealed that PcOMT10/11/12/13 indeed impacted metabolic fluxes of the phenylpropanoid pathway and phenylpropanoid-related metabolites such as chrysoeriol-6,8-di-C-glucoside, syringaresinol-4'-O-glucopyranosid, and 1-O-Sinapoyl-D-glucose. These findings identified metabolite markers between these two regions and provided valuable genetic insights for engineering the biosynthesis of these compounds.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Polygonatum
Idioma:
En
Revista:
BMC Plant Biol
Assunto da revista:
BOTANICA
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
China