Novel selective TOCSY method enables NMR spectral elucidation of metabolomic mixtures

2016 
Abstract Complex mixture analysis is routinely encountered in NMR-based investigations. With the aim of component identification, spectral complexity may be addressed chromatographically or spectroscopically, the latter being favored to reduce sample handling requirements. An attractive experiment is selective total correlation spectroscopy (sel-TOCSY), which is capable of providing tremendous spectral simplification and thereby enhancing assignment capability. Unfortunately, isolating a well resolved resonance is increasingly difficult as the complexity of the mixture increases and the assumption of single spin system excitation is no longer robust. We present TOCSY optimized mixture elucidation (TOOMIXED), a technique capable of performing spectral assignment particularly in the case where the assumption of single spin system excitation is relaxed. Key to the technique is the collection of a series of 1D sel-TOCSY experiments as a function of the isotropic mixing time ( τ m ), resulting in a series of resonance intensities indicative of the underlying molecular structure. By comparing these τ m -dependent intensity patterns with a library of pre-determined component spectra, one is able to regain assignment capability. After consideration of the technique’s robustness, we tested TOOMIXED firstly on a model mixture. As a benchmark we were able to assign a molecule with high confidence in the case of selectively exciting an isolated resonance. Assignment confidence was not compromised when performing TOOMIXED on a resonance known to contain multiple overlapping signals, and in the worst case the method suggested a follow-up sel-TOCSY experiment to confirm an ambiguous assignment. TOOMIXED was then demonstrated on two realistic samples (whisky and urine), where under our conditions an approximate limit of detection of 0.6 mM was determined. Taking into account literature reports for the sel-TOCSY limit of detection, the technique should reach on the order of 10  μ M sensitivity. We anticipate this technique will be highly attractive to various analytical fields facing mixture analysis, including metabolomics, foodstuff analysis, pharmaceutical analysis, and forensics.
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