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An algorithm for thorough background subtraction from high‐resolution LC/MS data: application for detection of glutathione‐trapped reactive metabolites
Author(s) -
Zhang Haiying,
Yang Yanou
Publication year - 2008
Publication title -
journal of mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.475
H-Index - 121
eISSN - 1096-9888
pISSN - 1076-5174
DOI - 10.1002/jms.1390
Subject(s) - analyte , chemistry , glutathione , mass spectrometry , algorithm , adduct , chromatography , subtraction , matrix (chemical analysis) , background subtraction , analytical chemistry (journal) , biochemistry , artificial intelligence , computer science , enzyme , pixel , arithmetic , mathematics , organic chemistry
A control sample background‐subtraction algorithm was developed for thorough subtraction of background and matrix‐related signals in high‐resolution, accurate mass liquid chromatography/mass spectrometry (LC/MS) data to reveal ions of interest in an analyte sample. This algorithm checked all ions in the control scans within a specified time window around the analyte scan for potential subtraction of ions found in that analyte scan. Applying this method, chromatographic fluctuations between runs were dealt with and background and matrix‐related signals in the sample could be thoroughly subtracted. The effectiveness of this algorithm was demonstrated using four test compounds, clozapine, diclofenac, imipramine, and tacrine, to reveal glutathione (GSH)‐trapped reactive metabolites after incubation with human liver microsomes supplemented with GSH (30 µ M compound, 45‐min incubation). Using this algorithm with a ± 1.0 min control scan time window, a ± 5 ppm mass error tolerance, and appropriate control samples, the GSH‐trapped metabolites were revealed as the major peaks in the processed LC/MS profiles. Such profiles allowed for comprehensive and reliable identification of these metabolites without the need for any presumptions regarding their behavior or properties with respect to mass spectrometric detection. The algorithm was shown to provide superior results when compared to several commercially available background‐subtraction algorithms. Many of the metabolites detected were doubly charged species which would be difficult to detect with traditional GSH adduct screening techniques, and thus, some of the adducts have not previously been reported in the literature. Copyright © 2008 John Wiley & Sons, Ltd.