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A Boolean probabilistic model of metabolic adaptation to oxygen in relation to iron homeostasis and oxidative stress.

Achcar F, Camadro JM, Mestivier D - BMC Syst Biol (2011)

Bottom Line: The resulting model of 642 elements and 1007 reactions was validated by comparing simulations with a large body of experimental results (147 phenotypes and 11 metabolic flux experiments).Therefore, we compared the simulations of our model with different levels of oxygen to experimental metabolic flux data.All these results show that this model, and the underlying modelling strategy, are powerful tools for improving our understanding of complex biological problems.

View Article: PubMed Central - HTML - PubMed

Affiliation: Modelling in Integrative Biology, Institut Jacques Monod - UMR7592 - CNRS - Univ. Paris-Diderot, Paris, France.

ABSTRACT

Background: In aerobically grown cells, iron homeostasis and oxidative stress are tightly linked processes implicated in a growing number of diseases. The deregulation of iron homeostasis due to gene defects or environmental stresses leads to a wide range of diseases with consequences for cellular metabolism that remain poorly understood. The modelling of iron homeostasis in relation to the main features of metabolism, energy production and oxidative stress may provide new clues to the ways in which changes in biological processes in a normal cell lead to disease.

Results: Using a methodology based on probabilistic Boolean modelling, we constructed the first model of yeast iron homeostasis including oxygen-related reactions in the frame of central metabolism. The resulting model of 642 elements and 1007 reactions was validated by comparing simulations with a large body of experimental results (147 phenotypes and 11 metabolic flux experiments). We removed every gene, thus generating in silico mutants. The simulations of the different mutants gave rise to a remarkably accurate qualitative description of most of the experimental phenotype (overall consistency > 91.5%). A second validation involved analysing the anaerobiosis to aerobiosis transition. Therefore, we compared the simulations of our model with different levels of oxygen to experimental metabolic flux data. The simulations reproducted accurately ten out of the eleven metabolic fluxes. We show here that our probabilistic Boolean modelling strategy provides a useful description of the dynamics of a complex biological system. A clustering analysis of the simulations of all in silico mutations led to the identification of clear phenotypic profiles, thus providing new insights into some metabolic response to stress conditions. Finally, the model was also used to explore several new hypothesis in order to better understand some unexpected phenotypes in given mutants.

Conclusions: All these results show that this model, and the underlying modelling strategy, are powerful tools for improving our understanding of complex biological problems.

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Related in: MedlinePlus

Mean PoP of a number of elements in selected mutants. The gene was turned o after the first million of steps. A: PoP of protoporphyrin-IX when the gene HEM15 is turned o, B: superoxide anion and hydroxyl radical when the gene SOD1 is set to "OFF", C-F: PoP of glutamate, cysteine and glutathion C) when ACO1 is set to "OFF". Cysteine reached zero at steady-state, D: ACO1 is set to "OFF" and a source of glutamate is added, E: HEM1 is set to "OFF", F: HEM1 is set to "OFF" and a source of glutamate is added.
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Figure 4: Mean PoP of a number of elements in selected mutants. The gene was turned o after the first million of steps. A: PoP of protoporphyrin-IX when the gene HEM15 is turned o, B: superoxide anion and hydroxyl radical when the gene SOD1 is set to "OFF", C-F: PoP of glutamate, cysteine and glutathion C) when ACO1 is set to "OFF". Cysteine reached zero at steady-state, D: ACO1 is set to "OFF" and a source of glutamate is added, E: HEM1 is set to "OFF", F: HEM1 is set to "OFF" and a source of glutamate is added.

Mentions: We show the evolution of the PoP during the simulations for selected elements in representative mutants in Figure 4. Figure 4-A describes a simple situation in which deletion of the gene encoding ferrochelatase (is-hem15) leads to an increase in the PoP of protoporphyrin IX, the substrate of the enzyme, paralleling the situation occurring in vivo in the corresponding biological mutant [40]. Similarly, in a model in which superoxide dismutase was eliminated (is-sod1, Figure 4-B), the PoP of its substrate, the superoxide anion [41] increased strongly. As a consequence, the PoP of the hydroxyl radical also increased, due to the Fenton and Haber-Weiss reactions.


A Boolean probabilistic model of metabolic adaptation to oxygen in relation to iron homeostasis and oxidative stress.

Achcar F, Camadro JM, Mestivier D - BMC Syst Biol (2011)

Mean PoP of a number of elements in selected mutants. The gene was turned o after the first million of steps. A: PoP of protoporphyrin-IX when the gene HEM15 is turned o, B: superoxide anion and hydroxyl radical when the gene SOD1 is set to "OFF", C-F: PoP of glutamate, cysteine and glutathion C) when ACO1 is set to "OFF". Cysteine reached zero at steady-state, D: ACO1 is set to "OFF" and a source of glutamate is added, E: HEM1 is set to "OFF", F: HEM1 is set to "OFF" and a source of glutamate is added.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3094212&req=5

Figure 4: Mean PoP of a number of elements in selected mutants. The gene was turned o after the first million of steps. A: PoP of protoporphyrin-IX when the gene HEM15 is turned o, B: superoxide anion and hydroxyl radical when the gene SOD1 is set to "OFF", C-F: PoP of glutamate, cysteine and glutathion C) when ACO1 is set to "OFF". Cysteine reached zero at steady-state, D: ACO1 is set to "OFF" and a source of glutamate is added, E: HEM1 is set to "OFF", F: HEM1 is set to "OFF" and a source of glutamate is added.
Mentions: We show the evolution of the PoP during the simulations for selected elements in representative mutants in Figure 4. Figure 4-A describes a simple situation in which deletion of the gene encoding ferrochelatase (is-hem15) leads to an increase in the PoP of protoporphyrin IX, the substrate of the enzyme, paralleling the situation occurring in vivo in the corresponding biological mutant [40]. Similarly, in a model in which superoxide dismutase was eliminated (is-sod1, Figure 4-B), the PoP of its substrate, the superoxide anion [41] increased strongly. As a consequence, the PoP of the hydroxyl radical also increased, due to the Fenton and Haber-Weiss reactions.

Bottom Line: The resulting model of 642 elements and 1007 reactions was validated by comparing simulations with a large body of experimental results (147 phenotypes and 11 metabolic flux experiments).Therefore, we compared the simulations of our model with different levels of oxygen to experimental metabolic flux data.All these results show that this model, and the underlying modelling strategy, are powerful tools for improving our understanding of complex biological problems.

View Article: PubMed Central - HTML - PubMed

Affiliation: Modelling in Integrative Biology, Institut Jacques Monod - UMR7592 - CNRS - Univ. Paris-Diderot, Paris, France.

ABSTRACT

Background: In aerobically grown cells, iron homeostasis and oxidative stress are tightly linked processes implicated in a growing number of diseases. The deregulation of iron homeostasis due to gene defects or environmental stresses leads to a wide range of diseases with consequences for cellular metabolism that remain poorly understood. The modelling of iron homeostasis in relation to the main features of metabolism, energy production and oxidative stress may provide new clues to the ways in which changes in biological processes in a normal cell lead to disease.

Results: Using a methodology based on probabilistic Boolean modelling, we constructed the first model of yeast iron homeostasis including oxygen-related reactions in the frame of central metabolism. The resulting model of 642 elements and 1007 reactions was validated by comparing simulations with a large body of experimental results (147 phenotypes and 11 metabolic flux experiments). We removed every gene, thus generating in silico mutants. The simulations of the different mutants gave rise to a remarkably accurate qualitative description of most of the experimental phenotype (overall consistency > 91.5%). A second validation involved analysing the anaerobiosis to aerobiosis transition. Therefore, we compared the simulations of our model with different levels of oxygen to experimental metabolic flux data. The simulations reproducted accurately ten out of the eleven metabolic fluxes. We show here that our probabilistic Boolean modelling strategy provides a useful description of the dynamics of a complex biological system. A clustering analysis of the simulations of all in silico mutations led to the identification of clear phenotypic profiles, thus providing new insights into some metabolic response to stress conditions. Finally, the model was also used to explore several new hypothesis in order to better understand some unexpected phenotypes in given mutants.

Conclusions: All these results show that this model, and the underlying modelling strategy, are powerful tools for improving our understanding of complex biological problems.

Show MeSH
Related in: MedlinePlus