Simultaneous Quantification and Identification of Individual Chemicals in Metabolite Mixtures by Two-Dimensional Extrapolated Time-Zero 1H−13C HSQC (HSQC0)

Quantitative one-dimensional (1D) 1H NMR spectroscopy is a useful tool for determining metabolite concentrations because of the direct proportionality of signal intensity to the quantity of analyte. However, severe signal overlap in 1D 1H NMR spectra of complex metabolite mixtures hinders accurate quantification. Extension of 1D 1H to 2D 1H−13C HSQC leads to the dispersion of peaks along the 13C dimension and greatly alleviates peak overlapping. Although peaks are better resolved in 2D 1H−13C HSQC than in 1D 1H NMR spectra, the simple proportionality of cross peaks to the quantity of individual metabolites is lost by resonance-specific signal attenuation during the coherence transfer periods. As a result, peaks for individual metabolites usually are quantified by reference to calibration data collected from samples of known concentration. We show here that data from a series of HSQC spectra acquired with incremented repetition times (the time between the end of the first 1H excitation pulse to the beginning of data acquisition) can be extrapolated back to zero time to yield a time-zero 2D 1H−13C HSQC spectrum (HSQC0) in which signal intensities are proportional to concentrations of individual metabolites. Relative concentrations determined from cross peak intensities can be converted to absolute concentrations by reference to an internal standard of known concentration. Clustering of the HSQC0 cross peaks by their normalized intensities identifies those corresponding to metabolites present at a given concentration, and this information can assist in assigning these peaks to specific compounds. The concentration measurement for an individual metabolite can be improved by averaging the intensities of multiple, nonoverlapping cross peaks assigned to that metabolite.

[1]  Daniel Raftery,et al.  Solvent signal as an NMR concentration reference. , 2008, Analytical chemistry.

[2]  Neeraj Sinha,et al.  Quantification of metabolites from two-dimensional nuclear magnetic resonance spectroscopy: application to human urine samples. , 2009, Analytical chemistry.

[3]  Daniel Raftery,et al.  R: A quantitative measure of NMR signal receiving efficiency. , 2009, Journal of magnetic resonance.

[4]  Guido F Pauli,et al.  Quantitative 1H NMR: development and potential of a method for natural products analysis. , 2005, Journal of natural products.

[5]  Rafael Brüschweiler,et al.  Strategy for automated analysis of dynamic metabolic mixtures by NMR. Application to an insect venom. , 2007, Analytical chemistry.

[6]  N. Michel,et al.  The application of the ERETIC method to 2D-NMR. , 2004, Journal of magnetic resonance.

[7]  A. Imperiale,et al.  Metabolic characterization of primary human colorectal cancers using high resolution magic angle spinning 1H magnetic resonance spectroscopy , 2009, Metabolomics.

[8]  G. Wider,et al.  Measuring protein concentrations by NMR spectroscopy. , 2006, Journal of the American Chemical Society.

[9]  David S. Wishart,et al.  Quantitative metabolomics using NMR , 2008 .

[10]  S. Grzesiek,et al.  NMRPipe: A multidimensional spectral processing system based on UNIX pipes , 1995, Journal of biomolecular NMR.

[11]  F. Malz,et al.  Validation of quantitative NMR. , 2005, Journal of pharmaceutical and biomedical analysis.

[12]  G. Wider,et al.  Dissection of heteronuclear NMR experiments for studies of magnetization transfer efficiencies. , 2003, Journal of magnetic resonance.

[13]  John L Markley,et al.  Method for determining molar concentrations of metabolites in complex solutions from two-dimensional 1H-13C NMR spectra. , 2007, Analytical chemistry.

[14]  L. Barantin,et al.  Concentration Measurement by Proton NMR Using the ERETIC Method. , 1999, Analytical chemistry.

[15]  G. Wider,et al.  Concentration measurements by PULCON using X‐filtered or 2D NMR spectra , 2006, Magnetic resonance in chemistry : MRC.