College of Traditional Chinese Medicine, China Pharmaceutical University, Nanjing 210009, People's Republic of China; Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Haike Road 501, Shanghai 201203, People's Republic of China.
Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Haike Road 501, Shanghai 201203, People's Republic of China.
Anal Chim Acta. 2017 Feb 1;952:59-70. doi: 10.1016/j.aca.2016.11.032. Epub 2016 Dec 4.
The simultaneous identification and quantification of target metabolites from herbal medicines are difficult to implement by the full-scan MS based nontargeted metabolomics approaches. Here an in-source multiple collision-neutral loss filtering (IMC-NLF) based nontargeted metabolomics approach is developed and applied to identify and quantify the variations of malonyl-ginsenosides, a common group of acyl saponins with potential anti-diabetic activity, among Panax ginseng, P. quinquefolius, and P. notoginseng. The key steps of the IMC-NLF strategy are the acquisition of specific high-resolution neutral loss data and the efficient filtering of target precursor ions from the full-scan spectra. Using a hybrid LTQ-Orbitrap mass spectrometer after UHPLC separation, abundant in-source product ions, [M-H-CO] (due to the vulnerability of the carboxyl group) and [M-H-Mal.], were generated at the energies of 70 V and 90 V, respectively. After spectral deconvolution, the generated peak list was screened by dual NLF using a Neutral Loss MS Finder software (NL of 43.9898 Da for CO and 86.0004 Da for the malonyl substituent). By combining the precursor ions list-triggered HCD-MS/MS and basic hydrolysis, a total of 101 malonyl-ginsenosides (including 69 from P. ginseng, 52 from P. quinquefolius, and 44 from P. notoginseng) were identified or tentatively characterized. The variations of 81 characterized malonyl-ginsenosides among 45 batches of Ginseng samples were statistically analyzed disclosing ten potential markers. It is the first systematic analysis of malonyl-ginsenosides. The IMC-NLF approach by a single analytical platform is promising in targeted analyses of modification-specific metabolites in metabolomics and drug metabolism.
基于全扫描 MS 的非靶向代谢组学方法很难同时鉴定和定量草药中的目标代谢物。在这里，我们开发了一种基于源内多重碰撞中性丢失过滤（IMC-NLF）的非靶向代谢组学方法，并将其应用于鉴定和定量分析人参、西洋参和三七中常见的酰基皂苷类化合物——丙二酰基人参皂苷的变化。IMC-NLF 策略的关键步骤是获取特定的高分辨率中性丢失数据，并从全扫描谱中有效过滤目标前体离子。使用混合 LTQ-Orbitrap 质谱仪在 UHPLC 分离后，分别在 70 V 和 90 V 的能量下产生丰富的源内产物离子 [M-H-CO]（由于羧基的脆弱性）和 [M-H-Mal.]。经过光谱解卷积后，使用 Neutral Loss MS Finder 软件（CO 的中性丢失 NL 为 43.9898 Da，丙二酰基取代基的 NL 为 86.0004 Da）对生成的峰列表进行双 NLF 筛选。通过结合前体离子列表触发的 HCD-MS/MS 和基本水解，共鉴定或初步鉴定了 101 种丙二酰基人参皂苷（包括 69 种来自人参、52 种来自西洋参和 44 种来自三七）。对 45 批人参样品中 81 种特征丙二酰基人参皂苷的变化进行了统计分析，揭示了 10 种潜在标志物。这是对丙二酰基人参皂苷的首次系统分析。通过单一分析平台的 IMC-NLF 方法有望用于代谢组学和药物代谢中特定修饰代谢物的靶向分析。
