基于UHPLC-HRMS的植物中酚类次生代谢物深度结构解析新方法研究

Phenolic compounds are the most widely distributed small molecular secondary metabolites in plants with important physiological functions. The identification of them occurs some challenges because of the structural diversity, positional isomers, lack of standards and databases. The development of in-silico fragmentation technology makes it possible to deeply annotate structures of phenolic metabolites. Previous studies haven’t paied attention to positional isomers, and have some problems such as the lack of some phenolic acid derivatives and acylated flavonoid glycosides..In the previous experiments, the positional isomers could be distinguished by the energy-resolved fragmentation curves of the characteristic fragment ions with different collision energies. In the project, the fragmentation characteristics related to collision energy will be explored through MS/MS analysis with different collision energies, and a phenolic metabolites in-silico database will be established based on fragmentation characteristics with different collision energies. Then the chromatographic retention characteristics will be explored through correlation analysis of retention time and structure. Finally the deep annotation of phenolic secondary metabolites and isomers from complex plant samples will be developed based on the in-silico database and chromatographic retention characteristics, combining with molecular network method. The study will improve the breadth and depth of phenolic metabolites identification, which provides theoretical basis and technical support for the deep study of phenolic metabolic pathways and regulatory networks.

酚类化合物是植物中分布最广泛且具有重要生理功能的小分子次生代谢物，其结构的多样性、位置异构体的存在、标样的缺少及数据库的缺乏为其结构解析带来挑战。In-silico裂解技术的发展为酚类代谢物的深度结构解析提供了可能。已有报道未关注酚类位置异构体定性，且存在部分酚酸类衍生物、酰基化黄酮糖苷定性缺失等不全面问题。.前期实验发现特征碎片离子能量分辨曲线可以有效定性位置异构体。本项目拟通过多碰撞能MS/MS分析，探索与碰撞能相关的裂解特征，建立不同碰撞能诱导的酚类代谢物in-silico数据库；通过保留时间与结构相关性分析，探究不同亚类色谱保留特征；最后基于in-silico数据库和色谱保留特征，结合分子网络方法，建立从复杂植物样品中深度解析酚类代谢物及位置异构体的新方法。本研究提高了酚类代谢物定性的广度和深度，为酚类代谢通路及调控网络的深入研究提供理论基础和技术支撑。

酚类代谢物在植物中广泛存在，具有重要生理功能及药理活性。酚类化合物结构复杂且存在位置异构体，为其准确定性带来了挑战。本项目合成了羟基肉桂酰和羟基苯甲酰奎宁酸位置异构体（单取代1-、3-、4-、5-和二取代1,3-、1,4-、1,5-、3,4-、3,5-、4,5-），研究发现单取代位置异构体可通过特征子离子的相对强度进行识别，二取代位置异构体可通过特征子离子的相对强度和比值进行识别；对黄酮单糖苷和多糖苷位置异构体进行了研究，发现黄酮3-和7-位置异构体可通过负离子模式下的裂解特征进行识别，糖链结构可通过正离子模式下的特征子离子进行识别；以植物中常见的8种游离酚酸和奎宁酸，基于化学反应启发式构建了酚酸类的in-silico数据库，包括2128种酚酸奎宁酸酯以及5936种糖苷（单糖苷）。以常见的45种黄酮苷元为原型，构建了黄酮糖苷类的in-silico数据库，共613296种，包括单糖苷507种，二糖苷19344种、三糖苷18822种、单酰基化糖苷574623种；在金银花不同药用部位中定性出41种酚酸类和28种黄酮类代谢物，其中7种酚酸和3种黄酮为首次在金银花中发现；在不同加工方式的银杏叶中定性出27种黄酮糖苷类位置异构体，包括7种单糖苷、11种二糖苷、5种三糖苷和4种酰基化糖苷。本项目为植物中酚类代谢物的深度结构解析提供了一种新的策略，对拓展酚类代谢通路与调控网络的认识具有重要意义。