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13C labeling experiments at metabolic nonstationary conditions: an exploratory study.

Wahl SA, Nöh K, Wiechert W - BMC Bioinformatics (2008)

Bottom Line: Different scenarios regarding available measurements are analyzed and compared to a non-labeled reference experiment.It was found that the use of a (specifically) labeled substrate will significantly increase the parameter estimation accuracy.This also leads to a significant decrease in correlation of the kinetic parameters compared to an experiment without 13C-labeled substrate.

View Article: PubMed Central - HTML - PubMed

Affiliation: Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany. awahl@mpi-magdeburg.mpg.de

ABSTRACT

Background: Stimulus Response Experiments to unravel the regulatory properties of metabolic networks are becoming more and more popular. However, their ability to determine enzyme kinetic parameters has proven to be limited with the presently available data. In metabolic flux analysis, the use of 13C labeled substrates together with isotopomer modeling solved the problem of underdetermined networks and increased the accuracy of flux estimations significantly.

Results: In this contribution, the idea of increasing the information content of the dynamic experiment by adding 13C labeling is analyzed. For this purpose a small example network is studied by simulation and statistical methods. Different scenarios regarding available measurements are analyzed and compared to a non-labeled reference experiment. Sensitivity analysis revealed a specific influence of the kinetic parameters on the labeling measurements. Statistical methods based on parameter sensitivities and different measurement models are applied to assess the information gain of the labeled stimulus response experiment.

Conclusion: It was found that the use of a (specifically) labeled substrate will significantly increase the parameter estimation accuracy. An overall information gain of about a factor of six is observed for the example network. The information gain is achieved from the specific influence of the kinetic parameters towards the labeling measurements. This also leads to a significant decrease in correlation of the kinetic parameters compared to an experiment without 13C-labeled substrate.

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Color visualization of the correlation matrix. The parameter correlation matrix for the reference experiment (left) and the labeled experiment Sall (right). Deep blue represents a correlation of 1, deep red represents -1.
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Figure 9: Color visualization of the correlation matrix. The parameter correlation matrix for the reference experiment (left) and the labeled experiment Sall (right). Deep blue represents a correlation of 1, deep red represents -1.

Mentions: So far, the improvement of the absolute variances of all parameters was investigated. In order to characterize the influence of the additional information from 13C labeling on the relationship among different parameters, the correlation matrix (Figure 9) will now be analyzed. The correlations for the reference experiment and the labeled scenario Sall are shown. The parameters are grouped with respect to the reactions and a block structure becomes visible.


13C labeling experiments at metabolic nonstationary conditions: an exploratory study.

Wahl SA, Nöh K, Wiechert W - BMC Bioinformatics (2008)

Color visualization of the correlation matrix. The parameter correlation matrix for the reference experiment (left) and the labeled experiment Sall (right). Deep blue represents a correlation of 1, deep red represents -1.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2373788&req=5

Figure 9: Color visualization of the correlation matrix. The parameter correlation matrix for the reference experiment (left) and the labeled experiment Sall (right). Deep blue represents a correlation of 1, deep red represents -1.
Mentions: So far, the improvement of the absolute variances of all parameters was investigated. In order to characterize the influence of the additional information from 13C labeling on the relationship among different parameters, the correlation matrix (Figure 9) will now be analyzed. The correlations for the reference experiment and the labeled scenario Sall are shown. The parameters are grouped with respect to the reactions and a block structure becomes visible.

Bottom Line: Different scenarios regarding available measurements are analyzed and compared to a non-labeled reference experiment.It was found that the use of a (specifically) labeled substrate will significantly increase the parameter estimation accuracy.This also leads to a significant decrease in correlation of the kinetic parameters compared to an experiment without 13C-labeled substrate.

View Article: PubMed Central - HTML - PubMed

Affiliation: Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany. awahl@mpi-magdeburg.mpg.de

ABSTRACT

Background: Stimulus Response Experiments to unravel the regulatory properties of metabolic networks are becoming more and more popular. However, their ability to determine enzyme kinetic parameters has proven to be limited with the presently available data. In metabolic flux analysis, the use of 13C labeled substrates together with isotopomer modeling solved the problem of underdetermined networks and increased the accuracy of flux estimations significantly.

Results: In this contribution, the idea of increasing the information content of the dynamic experiment by adding 13C labeling is analyzed. For this purpose a small example network is studied by simulation and statistical methods. Different scenarios regarding available measurements are analyzed and compared to a non-labeled reference experiment. Sensitivity analysis revealed a specific influence of the kinetic parameters on the labeling measurements. Statistical methods based on parameter sensitivities and different measurement models are applied to assess the information gain of the labeled stimulus response experiment.

Conclusion: It was found that the use of a (specifically) labeled substrate will significantly increase the parameter estimation accuracy. An overall information gain of about a factor of six is observed for the example network. The information gain is achieved from the specific influence of the kinetic parameters towards the labeling measurements. This also leads to a significant decrease in correlation of the kinetic parameters compared to an experiment without 13C-labeled substrate.

Show MeSH