Highly Accurate Detection and Identification Methodology of Xenobiotic Metabolites Using Stable Isotope Labeling, Data Mining Techniques, and Time-Dependent Profiling Based on LC/HRMS/MS
| Autor: | Eiichiro Fukusaki, Takeshi Bamba, Yasumune Nakayama, Mitsuhiko Iwakoshi, Fukumatsu Iwahashi, Yoshihiro Izumi, Masatomo Takahashi, Motonao Nakao, Seiji Yamato |
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| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
In silico Arabidopsis computer.software_genre Tandem mass spectrometry Orbitrap 01 natural sciences Xenobiotics Analytical Chemistry law.invention 03 medical and health sciences chemistry.chemical_compound Tandem Mass Spectrometry law Data Mining Cells Cultured Chromatography High Pressure Liquid Herbicides Chemistry 010401 analytical chemistry 0104 chemical sciences 030104 developmental biology Isotope Labeling Peak picking Stable Isotope Labeling Data mining 2 4-Dichlorophenoxyacetic Acid Xenobiotic computer Drug metabolism |
| Zdroj: | Analytical Chemistry. 90:9068-9076 |
| ISSN: | 1520-6882 0003-2700 |
| DOI: | 10.1021/acs.analchem.8b01388 |
| Popis: | A generally applicable method to discover xenobiotic metabolites is important to safely and effectively develop xenobiotics. We propose an advanced method to detect and identify comprehensive xenobiotic metabolites using stable isotope labeling, liquid chromatography coupled with benchtop quadrupole Orbitrap high-resolution tandem mass spectrometry (LC/HRMS/MS), data mining techniques (alignment, peak picking, and paired-peaks filtering), in silico metabolism prediction, and time-dependent profiling. The LC/HRMS analysis was carried out using Arabidopsis T87 cultured cells treated with unlabeled or with 13C- or 2H-labeled 2,4-dichlorophenoxyacetic acid (2,4-D). Paired-peak filtering enabled the accurate detection of 83 candidates for 2,4-D metabolites without any false positive peaks derived from solvents or the biological matrix. We confirmed 10 previously reported 2,4-D metabolites and identified 16 novel 2,4-D metabolites. Our method provides accurate detection and identification of comprehensive xenobiotic metabolites and represents a potentially useful tool for elucidating xenobiotic metabolism. |
| Databáze: | OpenAIRE |
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