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Dynamic regulatory on/off minimization for biological systems under internal temporal perturbations.

Kleessen S, Nikoloski Z - BMC Syst Biol (2012)

Bottom Line: Here, we propose a suite of novel methods for analyzing the dynamics of (internally perturbed) metabolic networks and for quantifying their robustness with limited knowledge of kinetic parameters.By conducting a comparative analysis with a kinetic model of the Calvin-Benson cycle and a model of plant carbohydrate metabolism, we demonstrate that the principle of regulatory on/off minimization coupled with dynamic FBA can accurately predict the changes in metabolic states.Our methods outperform the existing dynamic FBA-based modeling alternatives, and could help in revealing the mechanisms for maintaining robustness of dynamic processes in metabolic networks over time.

View Article: PubMed Central - HTML - PubMed

Affiliation: Max-Planck Institute of Molecular Plant Physiology, Potsdam, Germany. kleessen@mpimp-golm.mpg.de

ABSTRACT

Background: Flux balance analysis (FBA) together with its extension, dynamic FBA, have proven instrumental for analyzing the robustness and dynamics of metabolic networks by employing only the stoichiometry of the included reactions coupled with adequately chosen objective function. In addition, under the assumption of minimization of metabolic adjustment, dynamic FBA has recently been employed to analyze the transition between metabolic states.

Results: Here, we propose a suite of novel methods for analyzing the dynamics of (internally perturbed) metabolic networks and for quantifying their robustness with limited knowledge of kinetic parameters. Following the biochemically meaningful premise that metabolite concentrations exhibit smooth temporal changes, the proposed methods rely on minimizing the significant fluctuations of metabolic profiles to predict the time-resolved metabolic state, characterized by both fluxes and concentrations. By conducting a comparative analysis with a kinetic model of the Calvin-Benson cycle and a model of plant carbohydrate metabolism, we demonstrate that the principle of regulatory on/off minimization coupled with dynamic FBA can accurately predict the changes in metabolic states.

Conclusions: Our methods outperform the existing dynamic FBA-based modeling alternatives, and could help in revealing the mechanisms for maintaining robustness of dynamic processes in metabolic networks over time.

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Related in: MedlinePlus

Overview of the ten approaches, which are used to analyze the dynamics of metabolite and flux profiles in the Calvin-Benson cycle and the plant carbohydrate metabolism. The novel methods proposed in this study are framed in red.
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Figure 1: Overview of the ten approaches, which are used to analyze the dynamics of metabolite and flux profiles in the Calvin-Benson cycle and the plant carbohydrate metabolism. The novel methods proposed in this study are framed in red.

Mentions: Here we describe the seven proposed methods and the comparison of their performance with two kinetic models--of the Calvin-Benson cycle and of the plant carbohydrate metabolism. Since the proposed methods build upon the DFBA approaches, we provide a brief overview of the mathematical apparatus used in their formulation. The suite of proposed methods and their relation to the existing DFBA approaches are depicted in Figure 1.


Dynamic regulatory on/off minimization for biological systems under internal temporal perturbations.

Kleessen S, Nikoloski Z - BMC Syst Biol (2012)

Overview of the ten approaches, which are used to analyze the dynamics of metabolite and flux profiles in the Calvin-Benson cycle and the plant carbohydrate metabolism. The novel methods proposed in this study are framed in red.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3361480&req=5

Figure 1: Overview of the ten approaches, which are used to analyze the dynamics of metabolite and flux profiles in the Calvin-Benson cycle and the plant carbohydrate metabolism. The novel methods proposed in this study are framed in red.
Mentions: Here we describe the seven proposed methods and the comparison of their performance with two kinetic models--of the Calvin-Benson cycle and of the plant carbohydrate metabolism. Since the proposed methods build upon the DFBA approaches, we provide a brief overview of the mathematical apparatus used in their formulation. The suite of proposed methods and their relation to the existing DFBA approaches are depicted in Figure 1.

Bottom Line: Here, we propose a suite of novel methods for analyzing the dynamics of (internally perturbed) metabolic networks and for quantifying their robustness with limited knowledge of kinetic parameters.By conducting a comparative analysis with a kinetic model of the Calvin-Benson cycle and a model of plant carbohydrate metabolism, we demonstrate that the principle of regulatory on/off minimization coupled with dynamic FBA can accurately predict the changes in metabolic states.Our methods outperform the existing dynamic FBA-based modeling alternatives, and could help in revealing the mechanisms for maintaining robustness of dynamic processes in metabolic networks over time.

View Article: PubMed Central - HTML - PubMed

Affiliation: Max-Planck Institute of Molecular Plant Physiology, Potsdam, Germany. kleessen@mpimp-golm.mpg.de

ABSTRACT

Background: Flux balance analysis (FBA) together with its extension, dynamic FBA, have proven instrumental for analyzing the robustness and dynamics of metabolic networks by employing only the stoichiometry of the included reactions coupled with adequately chosen objective function. In addition, under the assumption of minimization of metabolic adjustment, dynamic FBA has recently been employed to analyze the transition between metabolic states.

Results: Here, we propose a suite of novel methods for analyzing the dynamics of (internally perturbed) metabolic networks and for quantifying their robustness with limited knowledge of kinetic parameters. Following the biochemically meaningful premise that metabolite concentrations exhibit smooth temporal changes, the proposed methods rely on minimizing the significant fluctuations of metabolic profiles to predict the time-resolved metabolic state, characterized by both fluxes and concentrations. By conducting a comparative analysis with a kinetic model of the Calvin-Benson cycle and a model of plant carbohydrate metabolism, we demonstrate that the principle of regulatory on/off minimization coupled with dynamic FBA can accurately predict the changes in metabolic states.

Conclusions: Our methods outperform the existing dynamic FBA-based modeling alternatives, and could help in revealing the mechanisms for maintaining robustness of dynamic processes in metabolic networks over time.

Show MeSH
Related in: MedlinePlus