Computational estimation of tricarboxylic acid cycle fluxes using noisy NMR data from cardiac biopsies

BMC Systems Biology

Johannes H G M van Beek⁴  A B Johan Groeneveld¹  Thomas W Binsl³  Jaap Heringa⁴  David J C Alders²  Hannes Hettling⁴ 

[1] Department of Intensive Care, Erasmus Medical Center, PO Box 2040, 3000 CA Rotterdam, The Netherlands;Department of Anesthesiology, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands;Centre for Integrative Bioinformatics (IBIVU), Vrije Universiteit Amsterdam, de Boelelaan 1081A, 1081 HV Amsterdam, The Netherlands;Netherlands Bioinformatics Centre (NBIC), Nijmegen, The Netherlands

关键词: ¹³C metabolic flux analysis;    Sensitivity analysis;    Metabolomics;    Metabolic modeling;    Cardiac physiology;   

Others  :  1142342
DOI  :  10.1186/1752-0509-7-82

 received in 2013-01-31, accepted in 2013-08-15,  发布年份 2013

【 摘 要 】

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 ¹³C 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.

【 授权许可】

   
2013 Hettling et al.; licensee BioMed Central Ltd.

【 图 表 】

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