Ratio Analysis Nuclear Magnetic Resonance Spectroscopy for Selective Metabolite Identification in Complex Samples

Abstract

Metabolite identification in the complex NMR spectra of biological samples is a challenging task due to significant spectral overlap and limited signal to noise. In this study we present a new approach, RANSY (Ratio Analysis NMR Spectroscopy), which identifies all the peaks of a specific metabolite based on the ratios of peak heights or integrals. We show that the spectrum for an individual metabolite can be generated by exploiting the fact that the peak ratios for any metabolite in the NMR spectrum are fixed and proportional to the relative numbers of magnetically distinct protons. When the peak ratios are divided by their coefficient of variations derived from a set of NMR spectra, the generation of an individual metabolite spectrum is enabled. We first tested the performance of this approach using one-dimensional (1D) and two-dimensional (2D) NMR data of mixtures of synthetic analogues of common body fluid metabolites. Subsequently, the method was applied to 1H NMR spectra of blood serum samples to demonstrate the selective identification of a number of metabolites. The RANSY approach, which does not need any additional NMR experiments for spectral simplification, is easy to perform and has the potential to aid in the identification of unknown metabolites using 1D or 2D NMR spectra in virtually any complex biological mixture.

The future of NMR-based metabolomics

“…This approach has been extended to a calculated confidence level for compound identifications from NMR data [12]. Another approach for connecting signals from individual compounds in mixtures is based on searching for statistical correlations among the intensities of NMR signals from various samples [13]. Nuclei present at low natural abundance 2 H (deuteron), 13 C, and 15 N serve as ideal metabolic tracers [14].…”

Identification and MS-assisted interpretation of genetically influenced NMR signals in human plasma

“…We argue that in this case the ratio between signals at two neighboring chemical shifts, one of them in a localized peak, is equivalent to applying a local baseline correction, thus elevating the peak out of the background noise. Wei et al have described this effect in a recent publication where they present a ratio-based approach that effectively raises the signal-to-noise ratio in NMR spectra [28]. …”

NMR Metabolomics Analysis of Parkinson's Disease

“…As a result, alternative methods have been developed or implemented to simplify metabolite identification. These approaches include 1D NMR methods such as selective total correlation spectroscopy (TOCSY) [203, 204], and statistical methods such as statistical total correlation spectroscopy (STOCSY) [205] and ratio analysis nuclear magnetic resonance spectroscopy (RANSY) [206]. In addition, two-dimensional (2D) NMR experiments routinely employed to characterize natural products ( 1 H- 13 C heteronuclear single quantum correlation, HSQC; 2D 1 H- 1 H TOCSY) are also used for metabolite identification [158].…”