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Picking the best methods for metabolomics research

Comparison of different nuclear magnetic resonance spectroscopy methods has helped to identify the most robust approach for studying different types of biomolecules.

A study by KAUST NMR experts has highlighted the importance of optimizing the sensitivity and resolution of NMR methods for metabolomics research according to sample type. © 2023 KAUST; Image generated with AI by Bing Image Creator.

A comparative analysis of four methods of nuclear magnetic resonance spectroscopy (NMR) has helped to determine the best approach to study biomolecules in different sample types.[1]

Metabolomics, the large-scale study of small molecules within cells, biofluids, tissues or organisms, has greatly improved understanding of how genetic and environmental factors influence metabolic processes. A key technique to study biomolecules in solution is solution-state NMR spectroscopy.

Although NMR is relatively less sensitive than mass spectrometry, “its reliability and reproducibility, along with the fact that NMR is a noninvasive and nondestructive technique, makes it a powerful tool for studying metabolites in complex mixtures,” says Upendra Singh, a biomedical scientist at KAUST. “Our objective was to help select a robust NMR method for the metabolomics study of a range of biological, plants and marine samples,” he adds.

NMR allows researchers to observe local magnetic fields around atomic nuclei from which they can unequivocally identify proteins and other molecules, as well as obtain details about the structure, reaction state and chemical environment of molecules. NMR-based metabolomics studies can offer valuable information about the composition of foods and medical samples.

Many NMR active nuclei can be used to analyze metabolites in biological mixtures, but hydrogen-1 (1H) NMR is the most widely used because of its high natural abundance, sensitivity and prevalence in endogenous metabolites compared with other nuclei, such as 13C, 15N, and 31P.

Most NMR-metabolomics studies rely on one dimensional (1D) 1H NMR spectral data that can be rapidly acquired in a few minutes with maximal signal-to-noise ratio. But, as Singh points out, large solvent signals can be a major problem as they can conceal the analyte signal intensity. For samples in aqueous solution, suppressing the water signal is necessary to obtain a meaningful spectrum.

When Singh and colleagues compared the intensity and shape of the signals of metabolites using different methods, they found that the 1D 1H-presat NMR method with a simple pulse sequence is better for marine, plant and biological samples (such as human plasma) that have been extracted in methanol.

However, they noted that another method — the 1D 1H Carr−Purcell−Meiboom−Gill (CPMG) presat method, which suppresses macromolecule signals — is better for native biological samples.

Their study highlights the importance of optimizing the sensitivity and resolution of NMR methods for metabolomics research according to sample type.

The team is now developing NMR methods to increase the sensitivity of desired signals in various food samples. “We are looking forward to embarking on a collaboration with the Saudi Food and Drug Authority (SFDA) to apply NMR-based metabolomics to characterize and classify honey samples according to their origin and quality,” Singh concludes.

  1. Singh, U., Alsuhaymi, S., Al-Nemi, R., Emwas, A-H. & Jaremko, M. Compound-specific 1D 1H NMR pulse sequence selection for metabolomics analyses. ACS Omega 8, 23651–23663 (2023).| article
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