Hydrophilic Interaction Liquid Chromatography–Hydrogen/Deuterium Exchange–Mass Spectrometry (HILIC-HDX-MS) for Untargeted Metabolomics

0583841 - FGÚ 2025 RIV CH eng J - Journal Article
Čajka, Tomáš - Hricko, Jiří - Rakušanová, Stanislava - Brejchová, Kristýna - Nováková, Michaela - Rudl Kulhavá, Lucie - Holá, Veronika - Paučová, Michaela - Fiehn, O. - Kuda, Ondřej
Hydrophilic Interaction Liquid Chromatography–Hydrogen/Deuterium Exchange–Mass Spectrometry (HILIC-HDX-MS) for Untargeted Metabolomics.
International Journal of Molecular Sciences. Roč. 25, č. 5 (2024), č. článku 2899. ISSN 1661-6596
R&D Projects: GA MŠMT(CZ) LX22NPO5104; GA ČR(CZ) GA20-21114S; GA ČR(CZ) GA21-00477S
Research Infrastructure: e-INFRA CZ II - 90254
Institutional support: RVO:67985823
Keywords : metabolomics * liquid chromatography * mass spectrometry * hydrogen/deuterium exchange * unknown identification
OECD category: Analytical chemistry
Impact factor: 5.6, year: 2022
Method of publishing: Open access
https://www.mdpi.com/1422-0067/25/5/2899

Liquid chromatography with mass spectrometry (LC-MS)-based metabolomics detects thousands of molecular features (retention time–m/z pairs) in biological samples per analysis, yet the metabolite annotation rate remains low, with 90% of signals classified as unknowns. To enhance the metabolite annotation rates, researchers employ tandem mass spectral libraries and challenging in silico fragmentation software. Hydrogen/deuterium exchange mass spectrometry (HDX-MS) may offer an additional layer of structural information in untargeted metabolomics, especially for identifying specific unidentified metabolites that are revealed to be statistically significant. Here, we investigate the potential of hydrophilic interaction liquid chromatography (HILIC)-HDX-MS in untargeted metabolomics. Specifically, we evaluate the effectiveness of two approaches using hypothetical targets: the post-column addition of deuterium oxide (D2O) and the on-column HILIC-HDX-MS method. To illustrate the practical application of HILIC-HDX-MS, we apply this methodology using the in silico fragmentation software MS-FINDER to an unknown compound detected in various biological samples, including plasma, serum, tissues, and feces during HILIC-MS profiling, subsequently identified as N1-acetylspermidine.
Permanent Link: https://hdl.handle.net/11104/0351844