Collision Cross Section: A New Identification Point for a “Catch All” Non-Targeted Screening Approach

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Michael McCullagh, Gareth Cleland, Vincent Hanot, Sara Stead, Joanne Williams, Séverine Goscinny, Ramesh Rao, and Jennifer Burgess
Waters and the Scientific Institute of Public Health- Brussels, Belgium
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Application Notes
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Application Notes
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Pesticide residue analyses in food has become a more difficult task considering the increasing number of compounds that need to be monitored at lower concentrations using generic extraction procedures. Qualitative multi-residue methods focus only on detection (demonstration of neither recovery nor linearity is required), and can therefore alleviate the quantification process. Full-scan high resolution MS offers a higher specificity with theoretically no limitation on the number of compounds detected, but it is still challenging to rapidly and efficiently identify targeted compounds present in a sample with a large number of co-extracted matrix components.

The key to successful implementation is the ability to efficiently identify targeted compounds present in a sample with an acceptable level of false negative results (≤5%) as outlined in the EU guidelines Although there is no requirement in the guidelines regarding the number of false detects, it is desirable to keep their number as low as possible to minimize the time required for additional investigation and hence to reduce the overall cost. The challenge is to remove false detections through careful optimization of the software screening parameters, but also to deal with very complex matrices that can produce false negative identifications.

Collision cross section (CCS) is a robust and precise physicochemical property of an ion. CCS is an important distinguishing characteristic of an ion that is related to its chemical structure and three-dimensional conformation where the shadow of the rotating three-dimensional ion represents the average collision cross section. The use of CCS data offers the potential to reduce the initial specificity requirements of applied screening parameters. Previously generated CCS data have been entered into a scientific library within the Waters UNIFI Scientific Information System. Expected and previously determined CCS values can be utilized to reduce false identifications in proficiency test samples and matrix matched calibrant series analyzed, while applying wider screening tolerance parameters.

In this application note, we present CCS, derived from ion mobility drift times, as a new identification parameter that can efficiently reduce the number of false detections when used in combination with conventional accurate mass and retention time information.

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