Abstract

The spectral resolution of 2D H-C heteronuclear single quantum coherence (H-C-HSQC) nuclear magnetic resonance (NMR) spectra facilitates both metabolite identification and quantification in nuclear magnetic resonance-based metabolomics. However, quantification is complicated by variations in magnetization transfer, which among others originate mainly from scalar coupling differences. Methods that compensate for variation in scalar coupling include the generation of calibration factors for individual signals or the use of additional pulse sequence schemes such as quantitative HSQC (Q-HSQC) that suppress the JCH-dependence by modulating the polarization transfer delays of HSQC or, additionally, employ a pure-shift homodecoupling approach in the H dimension, such as Quantitative, Perfected and Pure Shifted HSQC (QUIPU-HSQC). To test the quantitative accuracy of these three methods, employing a 600 MHz NMR spectrometer equipped with a helium cooled cryoprobe, a Latin-square design that covered the physiological concentration ranges of 10 metabolites was used. The results show the suitability of all three methods for the quantification of highly abundant metabolites. However, the substantially increased residual water signal observed in QUIPU-HSQC spectra impeded the quantification of low abundant metabolites located near the residual water signal, thus limiting its utility in high-throughput metabolite fingerprinting studies.

Highlights

  • IntroductionMeasurement of the metabolism of an organism provides important insights into its functions

  • Measurement of the metabolism of an organism provides important insights into its functions.This is the goal of metabolomics, which aims at the comprehensive analysis of the entirety of metabolites in a biological system [1]

  • A central element of Q- and QUIPU-HSQC experiments is the reduction of the influence of one-bond 1 H-13 C scalar couplings on signal intensities

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Summary

Introduction

Measurement of the metabolism of an organism provides important insights into its functions This is the goal of metabolomics, which aims at the comprehensive analysis of the entirety of metabolites in a biological system [1]. To this end, hyphenated mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy are commonly used [2]. The simplest way of quantifying compounds in a sample is the employment of 1D 1 H NMR. This approach often shows limitations due to the presence of signal overlap that renders integration of signals difficult, if not impossible. AB, Canada), Batman [4], Bayesil [5] and decon1d [6]

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