Comprehensive identification of polyphenolic metabolites in aspen knotwood by combination of 2D NMR and HPLC-HRMS.

IF 3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Anna V Faleva, Danil I Falev, Aleksandra A Onuchina, Nikolay V Ulyanovskii, Dmitry S Kosyakov
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引用次数: 0

Abstract

Introduction: European aspen (Populus tremula L.) knotwood contains large amounts of polyphenolic metabolites, mainly flavonoids, and can be considered as a promising industrial-scale source of valuable bioactive compounds. Valorization of knotwood extractives requires detailed information on their chemical composition and a relevant analytical methodology.

Objective: This study proposes combined analytical strategy for non-targeted screening and identification of polyphenolic plant metabolites and is aimed at comprehensive characterization of knotwood extractives.

Materials and methods: Aspen knotwood acetone extract with determined antioxidant activity was an object of the study. Two-dimensional NMR spectroscopy with Structure Elucidator expert system was used for preliminary search of major components and specific structures. Liquid chromatography-high-resolution mass spectrometry (HPLC-HRMS) with data-dependent MS/MS spectra acquisition was used as a complementary technique providing molecular-level characterization and identification of the detected metabolites.

Results: Twenty-eight phenolic metabolites were found and identified. Among them, flavonoids, aromadendrin and naringenin, as well as their glycosylated derivatives (mainly O-glucosides) and methyl ethers, dominated. Taxifolin and its 7-O-glucoside were detected as minor components. Other detected compounds are represented by p-coumaric acid and its rutinoside and small amounts of glycosylated ferulic acid. Nineteen of the detected compounds were discovered in aspen knotwood for the first time. The results were confirmed by preparative isolation of individual compounds and NMR studies.

Conclusion: The proposed analytical strategy based on 2D NMR and HPLC-HRMS can be considered a powerful tool in the analysis of plant extractives and allowed for the identification and semi-quantification of a large number of polyphenols in aspen knotwood.

结合二维 NMR 和 HPLC-HRMS 全面鉴定杨木中的多酚代谢物。
导言:欧洲山杨(Populus tremula L.)结材含有大量多酚代谢物,主要是黄酮类化合物,可被视为有价值生物活性化合物的一种有前途的工业级来源。节疤材提取物的价值评估需要有关其化学成分的详细信息和相关的分析方法:本研究提出了非靶向筛选和鉴定植物多酚代谢物的组合分析策略,旨在全面鉴定结缕草提取物的特征:研究对象为具有确定抗氧化活性的杨木结香丙酮提取物。使用二维核磁共振光谱和 Structure Elucidator 专家系统对主要成分和特定结构进行了初步搜索。液相色谱-高分辨质谱(HPLC-HRMS)与数据相关的 MS/MS 图谱采集技术作为补充技术,为检测到的代谢物提供分子级表征和鉴定:结果:发现并鉴定了 28 种酚类代谢物。结果:共发现并鉴定出 28 种酚类代谢物,其中以黄酮类、芳香丹皮苷和柚皮苷及其糖基化衍生物(主要是 O-葡萄糖苷)和甲基醚为主。检测到的次要成分是紫杉叶素及其 7-O-葡萄糖苷。检测到的其他化合物包括对香豆酸及其芸香甙和少量糖基化阿魏酸。检测到的化合物中有 19 种是首次在杨木中发现。个别化合物的制备分离和核磁共振研究证实了这一结果:结论:基于二维 NMR 和 HPLC-HRMS 的拟议分析策略可被视为植物提取物分析的有力工具,可对杨树结香中的大量多酚进行鉴定和半定量。
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来源期刊
Phytochemical Analysis
Phytochemical Analysis 生物-分析化学
CiteScore
6.00
自引率
6.10%
发文量
88
审稿时长
1.7 months
期刊介绍: Phytochemical Analysis is devoted to the publication of original articles concerning the development, improvement, validation and/or extension of application of analytical methodology in the plant sciences. The spectrum of coverage is broad, encompassing methods and techniques relevant to the detection (including bio-screening), extraction, separation, purification, identification and quantification of compounds in plant biochemistry, plant cellular and molecular biology, plant biotechnology, the food sciences, agriculture and horticulture. The Journal publishes papers describing significant novelty in the analysis of whole plants (including algae), plant cells, tissues and organs, plant-derived extracts and plant products (including those which have been partially or completely refined for use in the food, agrochemical, pharmaceutical and related industries). All forms of physical, chemical, biochemical, spectroscopic, radiometric, electrometric, chromatographic, metabolomic and chemometric investigations of plant products (monomeric species as well as polymeric molecules such as nucleic acids, proteins, lipids and carbohydrates) are included within the remit of the Journal. Papers dealing with novel methods relating to areas such as data handling/ data mining in plant sciences will also be welcomed.
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