Valentina Ramundi, Mitja M Zdouc, Enrica Donati, Justin J J van der Hooft, Sara Cimini, Laura Righetti
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引用次数: 0
Abstract
Introduction and objective: Rumex sanguineus, a traditional medicinal plant of the Polygonaceae family, is gaining popularity as an edible resource. However, despite its historical and nutritional significance, its chemical composition remains poorly understood. To deepen the understanding of the of Rumex sanguineus composition, an in-depth analysis using non-targeted, mass spectrometry-based metabolomics was performed. METHODS: Rumex roots, stems and leaves samples were analyzed by UHPLC-HRMS and subsequently subjected to feature-based molecular networking.
Results and conclusion: Overall, 347 primary and specialized metabolites grouped into 8 biochemical classes were annotated. Most of these metabolites (60%) belong to the polyphenols and anthraquinones classes. To investigate potential' toxicity due to the presence of anthraquinones, the amount of emodin was quantified with analytical standard, revealing higher accumulation in leaves compared to stems and roots. This highlights the need for thorough metabolomic studies to understand both beneficial and harmful compounds, especially in plants with historical medicinal use transitioning to modern culinary use.
期刊介绍:
Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to:
metabolomic applications within man, including pre-clinical and clinical
pharmacometabolomics for precision medicine
metabolic profiling and fingerprinting
metabolite target analysis
metabolomic applications within animals, plants and microbes
transcriptomics and proteomics in systems biology
Metabolomics is an indispensable platform for researchers using new post-genomics approaches, to discover networks and interactions between metabolites, pharmaceuticals, SNPs, proteins and more. Its articles go beyond the genome and metabolome, by including original clinical study material together with big data from new emerging technologies.