Advancing NMR-based quantification in complex mixtures using fourier transform and complete reduction to amplitude frequency table - The case of sugars

Abstract

Background

Sugars are building blocks of polysaccharides, and they are involved in many food and biotechnological applications. However, current methods of analysis have several limitations, preventing our understanding about their functions and roles in different systems, such as biological mixtures. Thus, there is a constant need for analytical methods that allow their rigorous and convenient quantification. NMR-based methodologies have a great potential in sugar analysis, however the traditional Fourier transform approach is associated with significant challenges related to sensitivity, resolution and error prone processing steps.

Results

A “clean” and straightforward ¹³C-detected NMR method for sugar analysis was developed. Nine sugars commonly found as building blocks of polysaccharides were analyzed with ¹H and ¹³C NMR with the later found to be more effective due to the complexity of the mixtures. Minor tautomers were also identified and found to appear in relatively significant amounts in some cases. In addition to the traditional Fourier transform, integration-based approaches, CRAFT-based analysis was assessed for the quantification of sugars in a complex mixture. CRAFT utilizing Bayesian analysis was found to generate high quality and repeatable results in an automated and less error-prone manner. Finally, CRAFT allows for significant improvement in spectral resolution of the 2D HSQC, thus rendering the NMR assignment much more convenient, even for less experience users.

Significance

This novel and systematic study for the quantification of sugars in complex mixtures with Fourier transform and CRAFT, will advance our capabilities for sugar quantification. It is also expected to lay the groundwork for the application of time-domain NMR data for targeted analysis and can be extended to other matrices.