Article ID Journal Published Year Pages File Type
1162699 Analytica Chimica Acta 2016 9 Pages PDF
Abstract

•We address the screening of halogenated compounds in large Full Scan HRMS datasets.•The workflow involves peak picking, pairing script and review of paired features.•The pairing script is based on exact mass differences between Cl and Br isotopes.•H/Cl scale mass defect plots are used to review identified isotopic clusters.•Chlorinated paraffins and HBCDDs could be detected in an eel sample muscle extract.

In the present work, we addressed the question of global seeking/screening organohalogenated compounds in a large panel of complex biological matrices, with a particular focus on unknown chemicals that may be considered as potential emerging hazards. A fishing strategy was developed based on untargeted profiling among full scan acquisition datasets provided by high resolution mass spectrometry. Since large datasets arise from such profiling, filtering useful information stands as a central question. In this way, we took advantage of the exact mass differences between Cl and Br isotopes. Indeed, our workflow involved an innovative Visual Basic for Applications script aiming at pairing features according to this mass difference, in order to point out potential organohalogenated clusters, preceded by an automated peak picking step based on the centWave function (xcms package of open access R programming environment). Then, H/Cl-scale mass defect plots were used to visualize the datasets before and after filtering. The filtering script was successfully applied to a dataset generated upon liquid chromatography coupled to ESI(−)-HRMS measurement from one eel muscle extract, allowing for realistic manual investigations of filtered clusters. Starting from 9789 initial obtained features, 1994 features were paired in 589 clusters. Hexabromocyclododecane, chlorinated paraffin series and various other compounds have been identified or tentatively identified, allowing thus broad screening of organohalogenated compounds in this extract. Although realistic, manual review of paired clusters remains time consuming and much effort should be devoted to automation.

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Related Topics
Physical Sciences and Engineering Chemistry Analytical Chemistry
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