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Computational estimation of tricarboxylic acid cycle fluxes using noisy NMR data from cardiac biopsies
BACKGROUND: The aerobic energy metabolism of cardiac muscle cells is of major importance for the contractile function of the heart. Because energy metabolism is very heterogeneously distributed in heart tissue, especially during coronary disease, a method to quantify metabolic fluxes in small tissue...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3765389/ https://www.ncbi.nlm.nih.gov/pubmed/23965343 http://dx.doi.org/10.1186/1752-0509-7-82 |
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author | Hettling, Hannes Alders, David J C Heringa, Jaap Binsl, Thomas W Groeneveld, A B Johan van Beek, Johannes H G M |
author_facet | Hettling, Hannes Alders, David J C Heringa, Jaap Binsl, Thomas W Groeneveld, A B Johan van Beek, Johannes H G M |
author_sort | Hettling, Hannes |
collection | PubMed |
description | BACKGROUND: The aerobic energy metabolism of cardiac muscle cells is of major importance for the contractile function of the heart. Because energy metabolism is very heterogeneously distributed in heart tissue, especially during coronary disease, a method to quantify metabolic fluxes in small tissue samples is desirable. Taking tissue biopsies after infusion of substrates labeled with stable carbon isotopes makes this possible in animal experiments. However, the appreciable noise level in NMR spectra of extracted tissue samples makes computational estimation of metabolic fluxes challenging and a good method to define confidence regions was not yet available. RESULTS: Here we present a computational analysis method for nuclear magnetic resonance (NMR) measurements of tricarboxylic acid (TCA) cycle metabolites. The method was validated using measurements on extracts of single tissue biopsies taken from porcine heart in vivo. Isotopic enrichment of glutamate was measured by NMR spectroscopy in tissue samples taken at a single time point after the timed infusion of (13)C labeled substrates for the TCA cycle. The NMR intensities for glutamate were analyzed with a computational model describing carbon transitions in the TCA cycle and carbon exchange with amino acids. The model dynamics depended on five flux parameters, which were optimized to fit the NMR measurements. To determine confidence regions for the estimated fluxes, we used the Metropolis-Hastings algorithm for Markov chain Monte Carlo (MCMC) sampling to generate extensive ensembles of feasible flux combinations that describe the data within measurement precision limits. To validate our method, we compared myocardial oxygen consumption calculated from the TCA cycle flux with in vivo blood gas measurements for 38 hearts under several experimental conditions, e.g. during coronary artery narrowing. CONCLUSIONS: Despite the appreciable NMR noise level, the oxygen consumption in the tissue samples, estimated from the NMR spectra, correlates with blood-gas oxygen uptake measurements for the whole heart. The MCMC method provides confidence regions for the estimated metabolic fluxes in single cardiac biopsies, taking the quantified measurement noise level and the nonlinear dependencies between parameters fully into account. |
format | Online Article Text |
id | pubmed-3765389 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-37653892013-09-10 Computational estimation of tricarboxylic acid cycle fluxes using noisy NMR data from cardiac biopsies Hettling, Hannes Alders, David J C Heringa, Jaap Binsl, Thomas W Groeneveld, A B Johan van Beek, Johannes H G M BMC Syst Biol Methodology Article BACKGROUND: The aerobic energy metabolism of cardiac muscle cells is of major importance for the contractile function of the heart. Because energy metabolism is very heterogeneously distributed in heart tissue, especially during coronary disease, a method to quantify metabolic fluxes in small tissue samples is desirable. Taking tissue biopsies after infusion of substrates labeled with stable carbon isotopes makes this possible in animal experiments. However, the appreciable noise level in NMR spectra of extracted tissue samples makes computational estimation of metabolic fluxes challenging and a good method to define confidence regions was not yet available. RESULTS: Here we present a computational analysis method for nuclear magnetic resonance (NMR) measurements of tricarboxylic acid (TCA) cycle metabolites. The method was validated using measurements on extracts of single tissue biopsies taken from porcine heart in vivo. Isotopic enrichment of glutamate was measured by NMR spectroscopy in tissue samples taken at a single time point after the timed infusion of (13)C labeled substrates for the TCA cycle. The NMR intensities for glutamate were analyzed with a computational model describing carbon transitions in the TCA cycle and carbon exchange with amino acids. The model dynamics depended on five flux parameters, which were optimized to fit the NMR measurements. To determine confidence regions for the estimated fluxes, we used the Metropolis-Hastings algorithm for Markov chain Monte Carlo (MCMC) sampling to generate extensive ensembles of feasible flux combinations that describe the data within measurement precision limits. To validate our method, we compared myocardial oxygen consumption calculated from the TCA cycle flux with in vivo blood gas measurements for 38 hearts under several experimental conditions, e.g. during coronary artery narrowing. CONCLUSIONS: Despite the appreciable NMR noise level, the oxygen consumption in the tissue samples, estimated from the NMR spectra, correlates with blood-gas oxygen uptake measurements for the whole heart. The MCMC method provides confidence regions for the estimated metabolic fluxes in single cardiac biopsies, taking the quantified measurement noise level and the nonlinear dependencies between parameters fully into account. BioMed Central 2013-08-21 /pmc/articles/PMC3765389/ /pubmed/23965343 http://dx.doi.org/10.1186/1752-0509-7-82 Text en Copyright © 2013 Hettling et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methodology Article Hettling, Hannes Alders, David J C Heringa, Jaap Binsl, Thomas W Groeneveld, A B Johan van Beek, Johannes H G M Computational estimation of tricarboxylic acid cycle fluxes using noisy NMR data from cardiac biopsies |
title | Computational estimation of tricarboxylic acid cycle fluxes using noisy NMR data from cardiac biopsies |
title_full | Computational estimation of tricarboxylic acid cycle fluxes using noisy NMR data from cardiac biopsies |
title_fullStr | Computational estimation of tricarboxylic acid cycle fluxes using noisy NMR data from cardiac biopsies |
title_full_unstemmed | Computational estimation of tricarboxylic acid cycle fluxes using noisy NMR data from cardiac biopsies |
title_short | Computational estimation of tricarboxylic acid cycle fluxes using noisy NMR data from cardiac biopsies |
title_sort | computational estimation of tricarboxylic acid cycle fluxes using noisy nmr data from cardiac biopsies |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3765389/ https://www.ncbi.nlm.nih.gov/pubmed/23965343 http://dx.doi.org/10.1186/1752-0509-7-82 |
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