Benefits of Collision Cross Section (CCS) data obtained by UPLC-ESI-IMS-QTOF MS and GC-APGC-IMS-QTOF for small molecules identification in screening applications

Izquierdo-Sandoval, David; Sancho, Juan V; Portoles, Tania

Benefits of Collision Cross Section (CCS) data obtained by UPLC-ESI-IMS-QTOF MS and GC-APGC-IMS-QTOF for small molecules identification in screening applications

2022

Izquierdo-Sandoval, David | Sancho, Juan V | Portoles, Tania

The coupling ion mobility separation to high-resolution mass spectrometry (IMS-HRMS) techniques, usually hyphenated with liquid or gas chromatography (LC/GC), are advanced tools for wide-scope screening for a large number of organic contaminants and residues in different fields of application. IMS technology provides an additional separation based on the charge, shape, and size of the ionized compounds facilitating the removal of matrix interferents and the separation of certain isomeric/isobaric species improving the method selectivity. From the measured drift time (DT) the rotationally averaged collision cross-section (CCS) can be calculated, a robust and matrix-independent parameter that permits enhancing the identification power of compounds in screening applications. In this work selected examples from different research projects are used to illustrate the benefits of including ion mobility separation and CCS data in LCESI-QTOF-MS and GC-APCI-QTOF-MS screening methodologies. First of all, it is possible to improve the identification power of the screening strategy when using data-independent acquisition since DT alignment of low and high energy spectra allows “removing” chromatographically co-eluants ions that mask the compound of interest. Furthermore, the inclusion of CCS deviation (e.g. < 2%) into the identification criteria is an extra value to enhance the reliability in the identification of target screening and also in the tentative identification of suspect compounds using CCS prediction tools. Additionally, the extensive collection of mobility data for LC and GC-amenable relevant multiclass organic pollutants generated CCS information for different adducts and ionic species.

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