Combining NMR and Mass Spectrometry for Metabolomics
NMR Spectroscopy and Mass Spectrometry are two fundamental analytic techniques that are employed to obtain metabolomics data sets due to their unique properties. NMR spectroscopy gives quantitative data for metabolite identification, while it has limitation on detecting abundant metabolites samples; on the contrary, mass spectrometry is able to measure a wide range of metabolite concentrations, therefore, NMR and mass spectrometry are highly complementary. Combining these two approaches is likely to improve the overall quality of a study and enhance the coverage of the metabolome.
Approaches for combining NMR and MS
- Interfacing NMR and MS hardware
Interfacing liquid chromatography (LC), NMR, and MS instrumentation has been greatly simplified by the advent of shielded magnets, and an NMR and mass spectrometer can be interfaced to LC by using a post-column splitter or the Bruker NMR-Mass Spectrometry Interface (BNMI), which benefit metabolomics by increasing sensitivity and coverage, and by reducing the amount of sample required for a study.
- Stable isotope tracing by isotopically labeling metabolites
The combination of MS and NMR yielded positional isotope labeling information, 13C isotopologue distributions, and enabled the accurate and efficient identification of small molecules, such as glycerophospholipids, stable isotope-resolved metabolomics using both NMR and MS greatly improves the analysis of metabolomics.
- Using combined cheminformatics techniques on MS and NMR data sets for an accurate and rapid analysis
Combined cheminformatics approaches are increasingly being employed during metabolomics studies. An analysis approach, termed as NMR/MS translator, combines NMR and MS to elucidate the structure of unknown metabolites from complex mixtures. It incorporate COLMAR database search queries and experimental NMR and MS spectral data to gain accurate metabolite identification; another approach, structure of unknown metabolomics mixture components MS/NMR is employed as a high throughput approach that combines MS with NMR data to identify unknown metabolites in a complex biological sample.
- Unique data handling and data mining techniques which correlate trends in both NMR and MS data sets by using multivariate statistical-based methods
Multivariate statistical techniques have been applied for the combined analysis of MS and NMR data sets, new models were generated by integrating NMR and MS metabolomics show better group separation and greater level of model interpretability than with NMR or MS data set alone.
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References
- Marshall D., Powers R., (2017) Beyond the paradigm: combining mass spectrometry and nuclear magnetic resonance for metabolomics. Progress in Nuclear Magnetic Resonance Spectroscopy. 100: 1-16.
- Bingol K., Brüschweiler R., (2015) NMR/MS translator for the enhanced simultaneous analysis of metabolomics mixtures by NMR spectroscopy and Mass Spectrometry: Application to human urine. J. Proteome Res 14: 2642-2648.
