A Novel Data-Independent Acquisition Strategy for Nontargeted Accurate Mass Contaminant Screening

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Gareth Cleland, Lauren Mullin, Adam Ladak, Simon Hird, Kirsten Craven
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Several fruit and vegetable samples, previously characterized by a collaborator, were screened against a pesticide library using several Data-Independent-Acquisitions (DIA). DIA strategies for complex mixture analysis, particularly within a contaminant screening environment offer significant efficiency advantages in that they enable a generic, non-biased strategy for data acquisition. The work will discuss the use of a novel DIA method – SONAR, in which precursor and product ion data are acquired with a sliding quadrupole window - for use in accurate mass screening applications and its use alongside more traditional DIA strategies such as full scan low and high collision energy acquisition (MSE), and its ion-mobility enhanced variant (HDMSE). 

A comparison of the outcomes from MSE, HDMSE and SONAR screening sets will be presented.

All techniques were able to detect contaminants present. However, the comparison of each technique with increasing matrix complexity shows that the ability of non-selective full scan experiments (MSE) to generate clean product ion spectra is reduced when compared to HDMSE and SONAR datasets.

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