Combining DI-ESI–MS and NMR datasets for metabolicprofiling

摘要

Metabolomics datasets are commonly acquired by either mass spectrometry (MS) or nuclear magnetic resonance spectroscopy (NMR), despite their fundamental complementarity. In fact, combining MS and NMR datasets greatly improves the coverage of the metabolome and enhances the accuracy of metabolite identification, providing a detailed and high-throughput analysis of metabolic changes due to disease, drug treatment, or a variety of other environmental stimuli. Ideally, a single metabolomics sample would be simultaneously used for both MS and NMR analyses, minimizing the potential for variability between the two datasets. This necessitates the optimization of sample preparation, data collection and data handling protocols to effectively integrate direct-infusion MS data with one-dimensional (1D) ¹H NMR spectra. To achieve this goal, we report for the first time the optimization of (i) metabolomics sample preparation for dual analysis by NMR and MS, (ii) high throughput, positive-ion direct infusion electrospray ionization mass spectrometry (DI-ESI-MS) for the analysis of complex metabolite mixtures, and (iii) data handling protocols to simultaneously analyze DI-ESI-MS and 1D ¹H NMR spectral data using multiblock bilinear factorizations, namely multiblock principal componentanalysis (MB-PCA) and multiblock partial least squares (MB-PLS). Finally, wedemonstrate the combined use of backscaled loadings, accurate mass measurementsand tandem MS experiments to identify metabolites significantly contributing toclass separation in MB-PLS-DA scores. We show that integration of NMR andDI-ESI-MS datasets yields a substantial improvement in the analysis ofneurotoxin involvement in dopaminergic cell death.