Introduction of a new method for two-dimensional NMR quantitative analysis in metabolomics studies

Abstract

NMR is one of the most important platforms for metabolomic studies. Though 2D NMR has been applied in metabolomics, most applications have mainly focused on metabolite identification whilst limitations causing a bottle-neck for applying high-throughput 2D NMR data for quantity related statistical analysis lies on the data interpretation methods. In this study, instead of using the traditional methods of calculating the 2D NMR data to search for the important features, a new procedure, which applies the high-resolution 1D NMR metabolites chemical shift range to filter the 2D NMR data, was developed. This new method was demonstrated using both a mixture of standard metabolites and a case study on plant extracts using 2D non-uniform sampling (NUS) total correlation spectroscopy (TOCSY) data. As a result, our method successfully filtered out the important features with a high success rate, and the extracted peaks showed high linearity between the calculated intensities and the concentrations of metabolites from a range of 0.05 mM–2 mM. The method was successfully applied to a metabolomics case study which included 18 Begonia samples that showed excellent peak extractions. In summary, our study has provided a practical new 2D NMR data extraction method for use in future metabolomics studies.