Abstract

NMR-based approach to metabolomics typically involves the collection of two-dimensional (2D) heteronuclear correlation spectra for identification and assignment of metabolites. In case of spectral overlap, a 3D spectrum becomes necessary, which is hampered by slow data acquisition for achieving sufficient resolution. We describe here a method to simultaneously acquire three spectra (one 3D and two 2D) in a single data set, which is based on a combination of different fast data acquisition techniques such as G-matrix Fourier transform (GFT) NMR spectroscopy, parallel data acquisition and non-uniform sampling. The following spectra are acquired simultaneously: (1) 13C multiplicity edited GFT (3,2)D HSQC-TOCSY, (2) 2D [ 1H- 1H] TOCSY and (3) 2D [ 13C- 1H] HETCOR. The spectra are obtained at high resolution and provide high-dimensional spectral information for resolving ambiguities. While the GFT spectrum has been shown previously to provide good resolution, the editing of spin systems based on their CH multiplicities further resolves the ambiguities for resonance assignments. The experiment is demonstrated on a mixture of 21 metabolites commonly observed in metabolomics. The spectra were acquired at natural abundance of 13C. This is the first application of a combination of three fast NMR methods for small molecules and opens up new avenues for high-throughput approaches for NMR-based metabolomics. We describe here a first application of a combination of different fast NMR methods to simultaneously acquire three spectra in a single data set. The method combines G-matrix Fourier transform (GFT) NMR spectroscopy, parallel data acquisition and non-uniform sampling. This opens up new avenues for high-throughput approaches in metabolomics.

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