Wang Yu, Ju Zhengcai, Li Linnan, Zhang Ting, Zhang Siyu, Ding Lili, Zhan Changsen, Wang Zhengtao, Yang Li
The MOE Key Laboratory of Standardization of Chinese Medicines, The SATCM Key Laboratory of New Resources and Quality Evaluation of Chinese Medicines, The Shanghai Key Laboratory for Compound Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China; Shanghai Frontiers Science Center of TCM Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
The MOE Key Laboratory of Standardization of Chinese Medicines, The SATCM Key Laboratory of New Resources and Quality Evaluation of Chinese Medicines, The Shanghai Key Laboratory for Compound Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China; Shanghai Jemincare Pharmaceutical Co., Ltd., Shanghai 201203, China.
J Chromatogr A. 2022 Aug 16;1678:463342. doi: 10.1016/j.chroma.2022.463342. Epub 2022 Jul 14.
The complexity of natural ingredients and the diversity of preparations are the major obstacles to the quality evaluation of traditional Chinese medicines (TCMs). A more comprehensive characterization of herbal compounds using different types of chromatographic separation techniques and covering a diverse polarity range can help evaluate the quality of TCMs. In this study, we first proposed a comprehensive method for characterizing compounds derived from Imperatae Rhizoma by combining the complementary strengths of UPCC-QTOF-MS (ultra-performance convergence chromatography coupled with quadrupole-time of flight mass spectrometry) with UPLC-QTOF-MS (ultra-performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry). The method based on the UNIFI scientific platform significantly shortened the analysis time and enabled a more comprehensive characterization of known and unreported compounds. Meanwhile, a feature-based molecular network (FBMN) was established on the Global Natural Product Social (GNPS) to infer potential compounds by rapidly classifying and visualizing these components. A total of 62 compounds in Imperatae Rhizoma were jointly characterizedand classified into six types. In comparison, the UPCC-QTOF-MS technology individually characterized 17 components, including lactones, phenols, aldehydes, phenylpropanoids, and small polar organic acids. The UPLC-QTOF-MS technology characterized 16 compounds mainly phenylpropionic acids, flavonoid glycosides, and chromone glycosides. Furthermore, three types of characteristic compounds could be well aggregated into an FBMN approach. Five possible potential new compounds were detected through the supplementary identification of GNPS and the correlation analysis of vicinal known compounds. The strategy was first applied to Imperatae Rhizoma and facilitated the characterization of a large quantity of data to provide comprehensive chemical composition results. This approach can be easily extended to the study of the material basis of other herbs or preparations in order to improve the accuracy of herb quality evaluation.
天然成分的复杂性和制剂的多样性是中药质量评价的主要障碍。使用不同类型的色谱分离技术并覆盖不同极性范围对草药化合物进行更全面的表征有助于评估中药的质量。在本研究中，我们首次提出了一种综合方法，通过结合超高效汇聚色谱-四极杆飞行时间质谱（UPCC-QTOF-MS）与超高效液相色谱-四极杆飞行时间质谱（UPLC-QTOF-MS）的互补优势来表征白茅根中的化合物。基于UNIFI科学平台的方法显著缩短了分析时间，并能够对已知和未报道的化合物进行更全面的表征。同时，在全球天然产物社会（GNPS）上建立了基于特征的分子网络（FBMN），通过快速分类和可视化这些成分来推断潜在化合物。白茅根中共有62种化合物被联合表征并分为六类。相比之下，UPCC-QTOF-MS技术单独表征了17种成分，包括内酯、酚类、醛类、苯丙素类和小极性有机酸。UPLC-QTOF-MS技术表征了16种化合物，主要是苯丙酸类、黄酮苷类和色酮苷类。此外，三种特征化合物可以很好地聚集到FBMN方法中。通过GNPS的补充鉴定和邻近已知化合物的相关性分析，检测到五种可能的潜在新化合物。该策略首次应用于白茅根，有助于对大量数据进行表征，以提供全面的化学成分结果。这种方法可以很容易地扩展到其他草药或制剂的物质基础研究，以提高草药质量评价的准确性。
