4.6 Article

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

Journal

JOURNAL OF CHROMATOGRAPHY A
Volume 1441, Issue -, Pages 83-95

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.chroma.2016.02.079

Keywords

Flavanones; Flavones; Key ion filtering; Phenylethanoid glycosides; Quadrupole-orbitrap mass spectrometry; Scutellaria baicalensis Georgi

Funding

  1. National Natural Science Foundation of China [81222054, 81470172]
  2. National Science and Technology Mega Project for Primary Drug Innovation of China [2014ZX09304-307]

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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.

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