Profiling of thiol-containing compounds by stable isotope labeling double precursor ion scan mass spectrometry.

Ping Liu, Yun-Qing Huang, Wen-Jing Cai, Bi-Feng Yuan, Yu-Qi Feng

Index: Anal. Chem. 86(19) , 9765-73, (2014)

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Abstract

Here we developed a novel strategy of isotope labeling in combination with high-performance liquid chromatography-double precursor ion scan mass spectrometry (IL-LC-DPIS-MS) analysis for nontargeted profiling of thiol-containing compounds. In this strategy, we synthesized a pair of isotope labeling reagents (ω-bromoacetonylquinolinium bromide, BQB; ω-bromoacetonylquinolinium-d7 bromide, BQB-d7) that contain a reactive group, an isotopically labeled moiety, and an ionizable group to selectively label thiol-containing compounds. The BQB and BQB-d7 labeled compounds can generate two characteristic product ions m/z 218 and 225, which contain an isotope tag and therefore were used for double precursor ion scans in mass spectrometry analysis. The peak pairs with characteristic mass differences can be readily extracted from the two precursor ion scan (PIS) spectra and assigned as potential thiol-containing candidates, which facilitates the identification of analytes. BQB and BQB-d7 labeled thiol-containing compounds can be clearly distinguished by generating two individual ion chromatograms. Thus, thiol-containing compounds from two samples labeled with different isotope reagents are ionized at the same time but recorded separately by mass spectrometry, offering good identification and accurate quantification by eliminating the MS response fluctuation and mutual interference from the two labeled samples. Using the IL-LC-DPIS-MS strategy, we profiled the thiol-containing compounds in beer and human urine, and 21 and 103 thiol candidates were discovered in beer and human urine, respectively. In addition, 9 and 17 thiol candidates in beer and human urine were successfully identified by further comparison with thiol standards or tandem mass spectrometry analysis. Taken together, the IL-LC-DPIS-MS method is demonstrated to be a promising strategy in the profiling of compounds with identical groups in metabolomics study.