Automatic CCS and MS/MS Library Creation and Application for Large Scale Metabolic and Lipidomic Profiling

Library Number:
PSTR134948104
Author(s):
Jonathan P Williams, David Eatough, Lee A Gethings, Christopher J Hughes, Mark Towers, Leanne Nye, Steven Lai, Mark Bennett
Source:
Waters, Nonlinear Dynamics
Content Type:
Posters
Content Subtype:
Other Symposium
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Metabolomics and Lipidomics involve identification and quantification of chemical fingerprint of cellular processes within a biological system. Precise identification is a major challenge since polar metabolites and lipids are chemically and structurally diverse and span a wide mass range. Chromatographic separation does not typically resolve all components, and often lacks retention time reproducibility. The addition of ion mobility, a gas phase separation of ion, increases peak capacity, selectivity, and can potentially resolve isomeric/isobaric. Benefits of collision cross-section (CCS) library obtained from mobility drift times together with accurate tandem mass spectrometry data (MS/MS) of human metabolites/lipids, will be shown to be an additional source of reference to aid metabolite and lipid identification.

ESI and MALDI-MS were used to measure ion drift-times on Synapt G2-Si and Vion time-of-flight (TOF) high resolution mass spectrometers. IM was used to measure CCS values in both positive and negative ESI modes in three differently laboratories. The preliminary data showed excellent correlation (median centering < 2%). A tandem mass spectrum of each ionised metabolite/lipid was also acquired and added to the scientific database. A sub-set of the CCS values were verified a Vion instrument to show the across instrument transferability of CCS, and on a MALDI-IM-MS to demonstrate the ionization independence of CCS measurements.

Utility of CCS library is demonstrated using an analysis of human plasma sample.  Spiked metabolite/lipid standards were identified using a combination of accurate mass measurements and CCS values. The addition of CCS measurements improved the confidence in identification compared to traditional analytical approaches.


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