Unknown

Dataset Information

0

Quantitative analysis of metabolic mixtures by two-dimensional 13C constant-time TOCSY NMR spectroscopy.


ABSTRACT: An increasing number of organisms can be fully (13)C-labeled, which has the advantage that their metabolomes can be studied by high-resolution two-dimensional (2D) NMR (13)C-(13)C constant-time (CT) total correlation spectroscopy (TOCSY) experiments. Individual metabolites can be identified via database searching or, in the case of novel compounds, through the reconstruction of their backbone-carbon topology. Determination of quantitative metabolite concentrations is another key task. Because strong peak overlaps in one-dimensional (1D) NMR spectra prevent straightforward quantification through 1D peak integrals, we demonstrate here the direct use of (13)C-(13)C CT-TOCSY spectra for metabolite quantification. This is accomplished through the quantum mechanical treatment of the TOCSY magnetization transfer at short and long-mixing times or by the use of analytical approximations, which are solely based on the knowledge of the carbon-backbone topologies. The methods are demonstrated for carbohydrate and amino acid mixtures.

SUBMITTER: Bingol K 

PROVIDER: S-EPMC4447502 | biostudies-other | 2013 Jul

REPOSITORIES: biostudies-other

altmetric image

Publications

Quantitative analysis of metabolic mixtures by two-dimensional 13C constant-time TOCSY NMR spectroscopy.

Bingol Kerem K   Zhang Fengli F   Bruschweiler-Li Lei L   Brüschweiler Rafael R  

Analytical chemistry 20130617 13


An increasing number of organisms can be fully (13)C-labeled, which has the advantage that their metabolomes can be studied by high-resolution two-dimensional (2D) NMR (13)C-(13)C constant-time (CT) total correlation spectroscopy (TOCSY) experiments. Individual metabolites can be identified via database searching or, in the case of novel compounds, through the reconstruction of their backbone-carbon topology. Determination of quantitative metabolite concentrations is another key task. Because st  ...[more]

Similar Datasets

| S-EPMC3993867 | biostudies-literature
| S-EPMC3843499 | biostudies-literature
| S-EPMC7445029 | biostudies-literature
| S-EPMC3220947 | biostudies-literature
| S-EPMC5226623 | biostudies-literature
| S-EPMC7074231 | biostudies-literature
| S-EPMC2533272 | biostudies-literature
| S-EPMC2365922 | biostudies-literature
| S-EPMC6040279 | biostudies-literature
| S-EPMC3660528 | biostudies-literature