首页> 外文期刊>Journal of chromatography, A: Including electrophoresis and other separation methods >A targeted strategy to analyze untargeted mass spectral data: Rapid chemical profiling of Scutellaria baicalensis using ultra-high performance liquid chromatography coupled with hybrid quadrupole orbitrap mass spectrometry and key ion filtering
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A targeted strategy to analyze untargeted mass spectral data: Rapid chemical profiling of Scutellaria baicalensis using ultra-high performance liquid chromatography coupled with hybrid quadrupole orbitrap mass spectrometry and key ion filtering

机译:分析非目标质谱数据的一种有针对性的策略:使用超高效液相色谱结合混合四极杆Orbitrap质谱和关键离子过滤技术对黄cut进行快速化学分析

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摘要

Structural identification of natural products by tandem mass spectrometry requires laborious spectral analysis. Herein, we report a targeted post-acquisition data processing strategy, key ion filtering (KIF), to analyze untargeted mass spectral data. This strategy includes four steps: (1) untargeted data acquisition by ultra-high performance liquid chromatography coupled with hybrid quadrupole orbitrap mass spectrometry (UHPLC/orbitrap-MS); (2) construction of a key ion database according to diagnostic MS/MS fragmentations and conservative substructures of natural compounds; (3) high-resolution key ion filtering of the acquired data to recognize substructures; and (4) structural identification of target compounds by analyzing their MS/MS spectra. The herbal medicine Huang-Qin (Scutellaria baicalensis Georgi) was used to illustrate this strategy. Its extract was separated within 20 min on a C-18 column (1.8 mu m, 2.1 x 150 mm) eluted with acetonitrile, methanol, and water containing 0.1% formic acid. The compounds were detected in the (-)-ESI mode, and their MS/MS spectra were recorded in the untargeted manner. Key ions were then filtered from the LC/MS data to recognize flavones, flavanones, O-/C-glycosides, and phenylethanoid glycosides. Finally, a total of 132 compounds were identified from Huang-Qin, and 59 of them were reported for the first time. This study provides an efficient data processing strategy to rapidly profile the chemical constituents of complicated herbal extracts. (C) 2016 Elsevier B.V. All rights reserved.
机译:通过串联质谱对天然产物进行结构鉴定需要费力的光谱分析。在本文中,我们报告了一种有针对性的采集后数据处理策略,即关键离子过滤(KIF),以分析非目标质谱数据。该策略包括四个步骤:(1)通过超高效液相色谱-混合四极杆Orbitrap质谱仪(UHPLC / orbitrap-MS)进行无目标数据采集; (2)根据诊断性MS / MS碎片和天然化合物的保守亚结构构建关键离子数据库; (3)对获取的数据进行高分辨率键离子滤波,以识别子结构; (4)通过分析目标化合物的MS / MS光谱进行结构鉴定。黄草药(黄cut(Scutellaria baicalensis Georgi))被用来说明这一策略。在20分钟内,将其提取物在C-18色谱柱(1.8μm,2.1 x 150 mm)上分离,用乙腈,甲醇和含0.1%甲酸的水洗脱。以(-)-ESI模式检测化合物,并以非靶向方式记录其MS / MS光谱。然后从LC / MS数据中过滤出关键离子,从而识别出黄酮,黄烷酮,O- / C-糖苷和苯基乙醛糖苷。最终,从黄勤中鉴定出132种化合物,其中59种为首次报道。这项研究提供了一种有效的数据处理策略,可以快速分析复杂草药提取物的化学成分。 (C)2016 Elsevier B.V.保留所有权利。

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