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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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Overview of the content of the model. Main pathways included in the model and their cellular localisation.
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Figure 1: Overview of the content of the model. Main pathways included in the model and their cellular localisation.

Mentions: The model was built from a core of reactions involved in iron homeostasis. We included in the model the main biochemical pathways, carbon, nitrogen, sulphur and phosphate metabolism, taking into account the cellular distribution of the components and the reactions (see Methods and Figure 1). The connectivity between reactions is depicted in Figure 2. The extracellular space contains the nutrients imported into the cell when the appropriate permeases or uptake systems are synthesized. The nutrients include glucose as a source of carbon. Its uptake may be modified by assigning different weights to the import reaction. When transcribed, the nuclear genes produce proteins that are exported to the cytoplasm and then targeted to their final subcellular compartment (transcription and translation are modelled as one reaction because no alteration of the mRNAs, for example active degradations, was introduced). Mitochondria perform the main energy-related metabolic reactions. Substrates and products shuttle between cytoplasm and mitochondria through appropriate translocators. A limited number of functions were attributed to the vacuole, mostly relating to the homeostasis of metals and phosphate. Our model currently includes 642 elements and 1007 reactions (see Table 1 and Additional file 1 for the detailed list of reactions). The weights of the reactions were set to the default weight of 1 unless changing the weight of a reaction was necessary to model a phenomenon realistically (see Methods for more details and Table 2).


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)

Overview of the content of the model. Main pathways included in the model and their cellular localisation.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 1: Overview of the content of the model. Main pathways included in the model and their cellular localisation.
Mentions: The model was built from a core of reactions involved in iron homeostasis. We included in the model the main biochemical pathways, carbon, nitrogen, sulphur and phosphate metabolism, taking into account the cellular distribution of the components and the reactions (see Methods and Figure 1). The connectivity between reactions is depicted in Figure 2. The extracellular space contains the nutrients imported into the cell when the appropriate permeases or uptake systems are synthesized. The nutrients include glucose as a source of carbon. Its uptake may be modified by assigning different weights to the import reaction. When transcribed, the nuclear genes produce proteins that are exported to the cytoplasm and then targeted to their final subcellular compartment (transcription and translation are modelled as one reaction because no alteration of the mRNAs, for example active degradations, was introduced). Mitochondria perform the main energy-related metabolic reactions. Substrates and products shuttle between cytoplasm and mitochondria through appropriate translocators. A limited number of functions were attributed to the vacuole, mostly relating to the homeostasis of metals and phosphate. Our model currently includes 642 elements and 1007 reactions (see Table 1 and Additional file 1 for the detailed list of reactions). The weights of the reactions were set to the default weight of 1 unless changing the weight of a reaction was necessary to model a phenomenon realistically (see Methods for more details and Table 2).

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