NMR-Based Metabolomics of Food

Restore High-Resolution Nuclear Magnetic Resonance Spectra from Inhomogeneous Magnetic Fields Using a Neural Network

High-resolution nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical tool with wide applications. However, the conventional shim technique may not guarantee the homogeneity of the magnetic field when the experimental conditions are unfavorable. In this study, we proposed a data postprocessing method called Restore High-resolution Unet (RH-Unet), which uses a convolutional neural network to restore distorted NMR spectra that have been acquired in inhomogeneous magnetic fields. The method generates feature-label pairs from singlet peak regions and ideal Lorentzian line shapes and trains a RH-Unet model to map low-resolution spectra to high-resolution spectra. The method was applied to different samples and showed superior performance than the reference deconvolution method incorporated in Bruker Topspin software. The proposed method provides a simple and fast way to obtain high-resolution NMR spectra in inhomogeneous fields that can facilitate the application of NMR spectroscopy in various fields.

NMR-Based Metabolomic Study on Phaseolus vulgaris Flour Fermented by Lactic Acid Bacteria and Yeasts

In recent years, fermented foods have attracted increasing attention due to their important role in the human diet, since they supply beneficial health effects, providing important sources of nutrients. In this respect, a comprehensive characterization of the metabolite content in fermented foods is required to achieve a complete vision of physiological, microbiological, and functional traits. In the present preliminary study, the NMR-based metabolomic approach combined with chemometrics has been applied, for the first time, to investigate the metabolite content of Phaseolus vulgaris flour fermented by different lactic acid bacteria (LAB) and yeasts. A differentiation of microorganisms (LAB and yeasts), LAB metabolism (homo- and heterofermentative hexose fermentation), LAB genus (Lactobacillus, Leuconostoc, and Pediococcus), and novel genera (Lacticaseibacillus, Lactiplantibacillus, and Lentilactobacillus) was achieved. Moreover, our findings showed an increase of free amino acids and bioactive molecules, such as GABA, and a degradation of anti-nutritional compounds, such as raffinose and stachyose, confirming the beneficial effects of fermentation processes and the potential use of fermented flours in the production of healthy baking foods. Finally, among all microorganisms considered, the Lactiplantibacillus plantarum species was found to be the most effective in fermenting bean flour, as a larger amount of free amino acids were assessed in their analysis, denoting more intensive proteolytic activity.

1H Nuclear Magnetic Resonance: A Future Approach to the Metabolic Profiling of Psychedelics in Human Biofluids?

While psychedelics may have therapeutic potential for treating mental health disorders such as depression, further research is needed to better understand their biological effects and mechanisms of action when considering the development of future novel therapy approaches. Psychedelic research could potentially benefit from the integration of metabonomics by proton nuclear magnetic resonance (1H NMR) spectroscopy which is an analytical chemistry-based approach that can measure the breakdown of drugs into their metabolites and their metabolic consequences from various biofluids. We have performed a systematic review with the primary aim of exploring published literature where 1H NMR analysed psychedelic substances including psilocin, lysergic acid diethylamide (LSD), LSD derivatives, N,N-dimethyltryptamine (DMT), 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) and bufotenin. The second aim was to assess the benefits and limitations of 1H NMR spectroscopy-based metabolomics as a tool in psychedelic research and the final aim was to explore potential future directions. We found that the most current use of 1H NMR in psychedelic research has been for the structural elucidation and analytical characterisation of psychedelic molecules and that no papers used 1H NMR in the metabolic profiling of biofluids, thus exposing a current research gap and the underuse of 1H NMR. The efficacy of 1H NMR spectroscopy was also compared to mass spectrometry, where both metabonomics techniques have previously shown to be appropriate for biofluid analysis in other applications. Additionally, potential future directions for psychedelic research were identified as real-time NMR, in vivo 1H nuclear magnetic resonance spectroscopy (MRS) and 1H NMR studies of the gut microbiome. Further psychedelic studies need to be conducted that incorporate the use of 1H NMR spectroscopy in the analysis of metabolites both in the peripheral biofluids and in vivo to determine whether it will be an effective future approach for clinical and naturalistic research.