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A comparison of collision cross section values obtained via travelling wave ion mobility-mass spectrometry and ultra high performance liquid chromatography-ion mobility-mass spectrometry: Application to the characterisation of metabolites in rat urine

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Title: A comparison of collision cross section values obtained via travelling wave ion mobility-mass spectrometry and ultra high performance liquid chromatography-ion mobility-mass spectrometry: Application to the characterisation of metabolites in rat urine
Authors: Nye, LC
Williams, JP
Munjoma, NC
Letertre, MPM
Coen, M
Bouwmeester, R
Martens, L
Swann, JR
Nicholson, JK
Plumb, RS
McCullagh, M
Gethings, LA
Lai, S
Langridge, J
Vissers, JPC
Wilson, ID
Item Type: Journal Article
Abstract: A comprehensive Collision Cross Section (CCS) library was obtained via Travelling Wave Ion Guide mobility measurements through direct infusion (DI). The library consists of CCS and Mass Spectral (MS) data in negative and positive ElectroSpray Ionisation (ESI) mode for 463 and 479 endogenous metabolites, respectively. For both ionisation modes combined, TWCCSN2 data were obtained for 542 non-redundant metabolites. These data were acquired on two different ion mobility enabled orthogonal acceleration QToF MS systems in two different laboratories, with the majority of the resulting TWCCSN2 values (from detected compounds) found to be within 1% of one another. Validation of these results against two independent, external TWCCSN2 data sources and predicted TWCCSN2 values indicated to be within 1–2% of these other values. The same metabolites were then analysed using a rapid reversed-phase ultra (high) performance liquid chromatographic (U(H)PLC) separation combined with IM and MS (IM-MS) thus providing retention time (tr), m/z and TWCCSN2 values (with the latter compared with the DI-IM-MS data). Analytes for which TWCCSN2 values were obtained by U(H)PLC-IM-MS showed good agreement with the results obtained from DI-IM-MS. The repeatability of the TWCCSN2 values obtained for these metabolites on the different ion mobility QToF systems, using either DI or LC, encouraged the further evaluation of the U(H)PLC-IM-MS approach via the analysis of samples of rat urine, from control and methotrexate-treated animals, in order to assess the potential of the approach for metabolite identification and profiling in metabolic phenotyping studies. Based on the database derived from the standards 63 metabolites were identified in rat urine, using positive ESI, based on the combination of tr, TWCCSN2 and MS data.
Issue Date: 27-Sep-2019
Date of Acceptance: 26-Jun-2019
URI: http://hdl.handle.net/10044/1/77649
DOI: 10.1016/j.chroma.2019.06.056
ISSN: 0021-9673
Publisher: Elsevier
Start Page: 386
End Page: 396
Journal / Book Title: Journal of Chromatography A
Volume: 1602
Copyright Statement: © 2019 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Keywords: Science & Technology
Life Sciences & Biomedicine
Physical Sciences
Biochemical Research Methods
Chemistry, Analytical
Biochemistry & Molecular Biology
Chemistry
Ion mobility spectrometry
Collision cross section
Metabolic phenotyping
Metabonomics
Metabolomics
HIGH-THROUGHPUT
METABOLOMICS
IDENTIFICATION
PREDICTION
LIPIDOMICS
LIPIDS
Collision cross section
Ion mobility spectrometry
Metabolic phenotyping
Metabolomics
Metabonomics
Amines
Animals
Calibration
Chromatography, High Pressure Liquid
Ion Mobility Spectrometry
Machine Learning
Mass Spectrometry
Metabolome
Rats
Reference Standards
Urine
Urine
Animals
Rats
Amines
Calibration
Chromatography, High Pressure Liquid
Reference Standards
Mass Spectrometry
Metabolome
Machine Learning
Ion Mobility Spectrometry
Science & Technology
Life Sciences & Biomedicine
Physical Sciences
Biochemical Research Methods
Chemistry, Analytical
Biochemistry & Molecular Biology
Chemistry
Ion mobility spectrometry
Collision cross section
Metabolic phenotyping
Metabonomics
Metabolomics
HIGH-THROUGHPUT
METABOLOMICS
IDENTIFICATION
PREDICTION
LIPIDOMICS
LIPIDS
03 Chemical Sciences
09 Engineering
10 Technology
Analytical Chemistry
Publication Status: Published
Online Publication Date: 2019-06-27
Appears in Collections:Department of Surgery and Cancer