Alen Albreht
1, Elena Chekmeneva
2,3, Humma Hussain
2,4, Beatriz Jiménez
2,3, Luke Whiley
2, Matthias Witt
5, Matthew R. Lewis
2,31Laboratory for Food Chemistry, Department of Analytical Chemistry, National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia
2National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, United Kingdom
3Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, United Kingdom
4Division of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
5Bruker Daltonics GmbH & Co. KG, MRMS Solutions, 28359 Bremen, Germany
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Metabolomics comprehensively studies an entire set of metabolites within cells, biofluids, tissues or organisms, also known as the metabolome, and has been rapidly gaining interest through the last 10 – 15 years. Variations in the normal metabolite concentration levels or absence/appearance of certain metabolites can indicate the onset of a disease or can merely reflect a response to a particular treatment. Thus, there are great aspirations for metabolomics to be used in future clinical environments for the prognosis, diagnosis and treatment response in personalized medicine and in public healthcare.
The simultaneous study of the metabolome, which contains thousands of different compounds, has been made possible mainly through technological advancements of analytical techniques and data mining. Nuclear magnetic resonance (NMR) and liquid-chromatography mass spectrometry (LC-MS) are two most common and powerful techniques used in metabolomics, however, they are not without their drawbacks. Endogenous interferences can compromise the quality of metabolic profiling assays by negatively impacting their specificity, detection capability, sensitivity, precision and quantitation accuracy.
Here, we identify two chemical interferences based on NMR and LC-MS data as N,N,N-trimethyl-L-alanine-L-proline betaine (L,L-TMAP), which was previously detected in human plasma and N,N-dimethyl-L-proline-L-proline betaine (L,L-DMPP), which occupy an unexpectedly large portion of available chromatographic space in LC-MS profiling of human urine. These species have exceptionally broad and asymmetrical peak shapes in RP as well as HILIC chromatographic profiles, presenting an anomaly that causes significant ion suppression of many co-eluting compounds in positive MS acquisition mode. We demonstrate that this issue can be effectively tackled by fine tuning chromatographic separation through pH and/or temperature adjustments.