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
- J Chromatogr A. 2016 Apr 8:1441:83-95. doi: 10.1016/j.chroma.2016.02.079.
- 1. State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Beijing 100191, China.
- 2. Institute of Systems Biomedicine, School of Basic Medical Sciences, Peking University, 38 Xueyuan Road, Beijing 100191, China.
- 3. School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong Special Administrative Region, China.
- 4. State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Beijing 100191, China. Electronic address: [email protected].
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 C18 column (1.8 μm, 2.1×150 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.
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Cat. No.Product NameDescriptionTargetResearch Area
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target: Endogenous MetaboliteResearch Areas: Others