Geographical variation in metabolite profiles and bioactivity of Thesium chinense Turcz. revealed by UPLC-Q-TOF-MS-based metabolomics

基于UPLC-Q-TOF-MS的代谢组学揭示了中华蓟(Thesium chinense Turcz.)代谢物谱和生物活性的地理差异

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Abstract

INTRODUCTION: This study aims to investigate the impact of geographical origin on the metabolite composition and bioactivity of Thesium chinense Turcz. (TCT), a member of the Apiaceae family renowned for its wide range of pharmacological properties, including antioxidant, antimicrobial, and anti-inflammatory effects. In this study, we investigated the whole plants of TCT from different regions in China, aiming to explore the geographical variation of TCT. METHODS: A non-targeted metabolomics approach was employed using ultra-high-performance liquid chromatography combined with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were utilized to identify and differentiate the metabolite profiles. We investigated the bioactivity, antioxidant activity, total flavonoid content (TFC), and the content of characteristic compounds from TCT sourced from different regions. This aims to further explore the metabolic differences and quality characteristics of TCT from various origins. RESULTS: PCA and PLS-DA analyses indicated that samples from different origins could be clearly distinguished. The analysis revealed 54 differential metabolites, predominantly flavonoids and alkaloids. KEGG pathway analysis indicated significant variations in the biosynthesis pathways of flavonoids and flavanols among the samples. TCT from Anhui province exhibited the highest TFC and strongest antioxidant and anti-inflammatory activities, while samples from Jilin province showed the lowest. DISCUSSION: A strong correlation was observed between metabolite content and geographical origins, suggesting that the bioactivity of TCT is significantly influenced by its provenance. Additionally, the antioxidant and anti-inflammatory activities of TCT were validated, showing a strong predictive relationship with TFC. This research highlights the potential of metabolomics in discerning the subtleties of plant metabolomes, contributing to the advancement of traditional Chinese medicine and its integration into modern healthcare practices.

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