Department of Chemistry, Università di Roma "La Sapienza", Piazzale Aldo Moro 5, 00185, Rome, Italy.
Department of Life Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi 287, 41125, Modena, Italy; CNR NANOTEC, Campus Ecotekne, University of Salento, Via Monteroni, 73100, Lecce, Italy.
Talanta. 2020 Mar 1;209:120573. doi: 10.1016/j.talanta.2019.120573. Epub 2019 Nov 18.
Polyphenols are a broad class of plant secondary metabolites which carry out several biological functions for plant growth and protection and are of great interest as nutraceuticals for their antioxidant properties. However, due to their structural variability and complexity, the mass-spectrometric analysis of polyphenol content in plant matrices is still an issue. In this work, a novel approach for the identification of several classes of polyphenol derivatives based on ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry was developed. First, mass-spectrometric parameters were optimized in order to obtain a large set of diagnostic product ions for their high-confidence identification. The software Compound Discoverer 3.0 was then implemented with a comprehensive database of 45,567 polyphenol derivatives and with mass-spectrometric data for their building blocks, resulting in a specific tool for the semi-automatic identification of flavonoids, anthocyanins, ellagitannins, proanthocyanidins and phenolic acids. The method was then applied to the identification of polyphenols in industrial hemp (Cannabis sativa), a matrix whose use is recently spreading for pharmaceutical and nutraceutical purposes, resulting in the identification of 147 compounds belonging to the classes of flavonoids, proanthocyanidins and phenolic acids. The proposed method is applicable to the polyphenol profiling of any plant matrix and it is not dependent on data in the literature for their identification, allowing the discovery of compounds which have been never identified before.
多酚是一类广泛的植物次生代谢产物，具有多种生物功能，对植物的生长和保护具有重要意义，同时因其具有抗氧化特性，也作为营养保健品而备受关注。然而，由于其结构的可变性和复杂性，植物基质中多酚含量的质谱分析仍然是一个问题。在这项工作中，开发了一种基于超高效液相色谱与高分辨率质谱联用的鉴定多种类多酚衍生物的新方法。首先，优化了质谱参数，以获得大量用于高可信度鉴定的诊断产物离子。然后，使用包含 45,567 种多酚衍生物的综合数据库以及其构建块的质谱数据，实施了 Compound Discoverer 3.0 软件，从而得到一种专门用于半自动化鉴定类黄酮、花青素、鞣花单宁、原花青素和酚酸的工具。该方法随后应用于工业大麻（Cannabis sativa）中多酚的鉴定，工业大麻最近因其在医药和营养保健品方面的用途而得到广泛应用，共鉴定出 147 种属于类黄酮、原花青素和酚酸类的化合物。该方法适用于任何植物基质的多酚分析，且不依赖于文献数据进行鉴定，允许发现以前从未鉴定过的化合物。
