COLMAR1d2d: Synergistic Combination of 1D with 2D NMR for Enhanced High-Throughput Identification and Quantification of Metabolites in Complex Mixtures

Abstract

A major challenge in 1D ¹H NMR-based metabolomics studies is the occurrence of slight shifts of the resonances of mixture compounds compared to the reference spectra in the metabolomics spectral databases due to variations in buffer conditions, temperature, and matrix effects. This hampers both the automated spectral deconvolution and metabolite quantification of crowded regions in 1D ¹H NMR spectra of complex mixtures whose analysis is particularly susceptible to such effects. 2D NMR-based metabolomics, on the other hand, is substantially more robust but also much more demanding in terms of NMR spectrometer time. Here we introduce an approach, termed COLMAR1d2d, which uses selected 2D ¹H–¹³C HSQC and ¹H–¹H TOCSY NMR spectra of a subset of samples along with 1D ¹H NMR spectra of all samples to overcome this bottleneck. It relies on our 2D NMR-based platform COLMARm using 2D ¹H–¹³C HSQC and 2D ¹H–¹H TOCSY spectra measured for a representative subset of samples to unambiguously and comprehensively determine the metabolite composition and the exact peak positions of the identified compounds under the sample conditions present. This information is then used to update the spectral database for the automated analysis of a potentially large cohort of 1D ¹H NMR spectra using the COLMAR1d platform. It is demonstrated how this synergistic combination of 1D with selected 2D NMR spectra allows the analysis of a significantly larger number of metabolites than would be possible with 1D NMR alone. Moreover, COLMAR1d2d also improves quantitation, as is demonstrated for samples from mouse urine and Pseudomonas aeruginosa biofilm.