Multidimensional-constrained Suspect Screening of Hydrophobic Chemicals Using Gas Chromatography-Atmospheric Pressure Chemical Ionization-Ion Mobility-Mass Spectrometry

Suspect screening strives to rapidly monitor a large number of substances in a sample using mass spectral libraries. For hydrophobic organic chemicals (HOCs), these libraries are primarily based on electron ionization mass spectra. To improve the efficacy of suspect screening, new libraries and workflows are required, leveraging the highly specific analytical data acquired by state-of-the-art mass spectrometers. In this study, we established a new library for 1,590 suspect contaminants, including exact mass and a combination of measured and model-predicted values for retention time (RT) and collision cross section (CCS). The accuracy of in silico predictions was assessed using standards for 102 environmental contaminants. Thereafter, using gas chromatography-atmospheric pressure chemical ionization-ion mobility-mass spectrometry, a suspect screening workflow constrained by exact mass, RT, CCS, and product ion data, together with a continuous scoring system, was established to reduce false positives and improve identification confidence. Application of the method to fortified and standard reference sediment samples demonstrated true positive rates of 79% and 64%, respectively, with all false positives attributed to suspect isomers, indicating high specificity of our method. This study offers a new workflow for improved suspect screening of HOCs using multidimensional information, and highlights the need to enrich CCS databases and extend the applicable chemical space of current in silico tools to non-polar substances.