Reference : Enhancing spectral quality in complex environmental matrices: Supporting suspect and ...
Scientific journals : Article
Life sciences : Environmental sciences & ecology
Computational Sciences
Enhancing spectral quality in complex environmental matrices: Supporting suspect and non-target screening in zebra mussels with ion mobility
Menger, Frank [> >]
Celma, Alberto [> >]
Schymanski, Emma mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
Lai, Foon Yin [> >]
Bijlsma, Lubertus [> >]
Wiberg, Karin [> >]
Hernández, Félix [> >]
Sancho, Juan V. [> >]
Ahrens, Lutz [> >]
Environment International
[en] Identification of bioaccumulating contaminants of emerging concern (CECs) via suspect and non-target screening remains a challenging task. In this study, ion mobility separation with high-resolution mass spectrometry (IM-HRMS) was used to investigate the effects of drift time (DT) alignment on spectrum quality and peak annotation for screening of CECs in complex sample matrices using data independent acquisition (DIA). Data treatment approaches (Binary Sample Comparison) and prioritisation strategies (Halogen Match, co-occurrence of features in biota and the water phase) were explored in a case study on zebra mussel (Dreissena polymorpha) in Lake Mälaren, Sweden’s largest drinking water reservoir. DT alignment evidently improved the fragment spectrum quality by increasing the similarity score to reference spectra from on average (±standard deviation) 0.33 ± 0.31 to 0.64 ± 0.30 points, thus positively influencing structure elucidation efforts. Thirty-two features were tentatively identified at confidence level 3 or higher using MetFrag coupled with the new PubChemLite database, which included predicted collision cross-section values from CCSbase. The implementation of predicted mobility data was found to support compound annotation. This study illustrates a quantitative assessment of the benefits of IM-HRMS on spectral quality, which will enhance the performance of future screening studies of CECs in complex environmental matrices.
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FnR ; FNR12341006 > Emma Schymanski > ECHIDNA > Environmental Cheminformatics To Identify Unknown Chemicals And Their Effects > 01/10/2018 > 30/09/2023 > 2018

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