Integrating NMR and multi-LC-MS-based untargeted metabolomics for comprehensive analysis of blood serum samples

Mass spectrometry (MS) and nuclear magnetic resonance (NMR) have emerged as pivotal tools in biofluid metabolomics, facilitating investigation of disease mechanisms and biomarker discovery. Despite complementary capabilities, these techniques are rarely combined, although their integration is often beneficial. Typically, different sample preparation approaches are used, and compatibility challenges potentially arise due to the requirement for deuterated buffered solvents in NMR but not MS techniques. Additionally, MS-based approaches necessitate protein removal from samples whilst in NMR proteins can be potentially useful biomarkers. In this study, we developed a blood serum preparation protocol enabling sequential NMR and multi-LC-MS untargeted metabolomics analysis using a single serum aliquot in a research discovery setting.

We analysed human serum samples using various untargeted NMR and multi-LC-MS platforms to assess the impact of deuterated solvents and buffers on detected compound-features. Employing multiple LC-MS profiling approaches, we observed no evidence of deuterium incorporation into metabolites following sample preparation with deuterated solvents. Furthermore, we demonstrated that buffers used in NMR were well tolerated by LC-MS. Protein removal, involving both solvent precipitation and molecular weight cut-off (MWCO) filtration, was identified as a primary factor influencing metabolite abundance. Our findings led to the development and validation of a serum sample preparation protocol enabling a combined NMR and multi-LC-MS analysis.

Using a single clinical serum aliquot for simultaneous untargeted profiling via NMR and multi-LC-MS represents a highly efficient alternative to current methods. This approach reduces sample volume requirements and substantially expands the potential for broader metabolome coverage. Our study offers comprehensive insights into the impact of sample preparation on complex metabolic biofluid profiles, highlighting the compatibility and complementarity of LC-MS and NMR in metabolomics research.