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Large-scale in silico modeling of metabolic interactions between cell types in the human brain.

Lewis NE, Schramm G, Bordbar A, Schellenberger J, Andersen MP, Cheng JK, Patel N, Yee A, Lewis RA, Eils R, König R, Palsson BØ - Nat. Biotechnol. (2010)

Bottom Line: Transport reactions are used to account for the transfer of metabolites between models of different cell types via the interstitial fluid.Analysis of the models identifies genes and pathways that may explain observed experimental phenomena, including the differential effects of the disease on cell types and regions of the brain.Constraint-based modeling can thus contribute to the study and analysis of multicellular metabolic processes in the human tissue microenvironment and provide detailed mechanistic insight into high-throughput data analysis.

View Article: PubMed Central - PubMed

Affiliation: Department of Bioengineering, University of California, San Diego, La Jolla, California, USA.

ABSTRACT
Metabolic interactions between multiple cell types are difficult to model using existing approaches. Here we present a workflow that integrates gene expression data, proteomics data and literature-based manual curation to model human metabolism within and between different types of cells. Transport reactions are used to account for the transfer of metabolites between models of different cell types via the interstitial fluid. We apply the method to create models of brain energy metabolism that recapitulate metabolic interactions between astrocytes and various neuron types relevant to Alzheimer's disease. Analysis of the models identifies genes and pathways that may explain observed experimental phenomena, including the differential effects of the disease on cell types and regions of the brain. Constraint-based modeling can thus contribute to the study and analysis of multicellular metabolic processes in the human tissue microenvironment and provide detailed mechanistic insight into high-throughput data analysis.

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General structure of the modelsThree models were built from the brain reconstruction. Each model consists of various compartments: 1) the endothelium/blood, 2) astrocytes, 3) astrocytic mitochondria, 4) neurons, 5) neuronal mitochondria, and 6) an interstitial space between the cell types. Each neuron metabolic network was tailored to represent a specific neuron type, containing genes and reactions generally accepted to be unique to the neuron type. Mito = mitochondrion, Int = interstitial space, CMR = cerebral metabolic rate.
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Figure 2: General structure of the modelsThree models were built from the brain reconstruction. Each model consists of various compartments: 1) the endothelium/blood, 2) astrocytes, 3) astrocytic mitochondria, 4) neurons, 5) neuronal mitochondria, and 6) an interstitial space between the cell types. Each neuron metabolic network was tailored to represent a specific neuron type, containing genes and reactions generally accepted to be unique to the neuron type. Mito = mitochondrion, Int = interstitial space, CMR = cerebral metabolic rate.

Mentions: This workflow was used to build three different multicellular models of brain energy metabolism. Each model represents one canonical neuron type (i.e., glutamatergic, GABAergic, or cholinergic), its interactions with the surrounding astrocytes, and the transport of metabolites through the blood-brain barrier (Fig. 2). This reconstruction focuses on the core of cerebral energy metabolism, including central metabolism, mitochondrial metabolic pathways, and pathways relevant to anabolism and catabolism of three neurotransmitters: glutamate, γ-aminobutarate (GABA), and acetylcholine. Thus, the three models contain the high flux pathways and important reactions in neuron and astrocyte metabolism. These models currently represent the largest and most detailed models of brain energy metabolism 13–15 (see Supplementary Notes). Our models contain 1066, 1067, and 1070 compartment-specific reactions, transformations, and exchanges, involving 983, 983, and 987 metabolite/compartment combinations, for the glutamatergic, GABAergic, and cholinergic models, respectively, and are associated with a total of 403 genes. Lists of reactions, genes, citations, and parameters used to constrain the models are detailed in Supplementary Tables 1– 5. The validity of these models is demonstrated through various tests and comparisons to physiological data. Specifically, our model predicts ATP production rates within 8% of the average published value, and internal flux measurements are consistent with experimentally measured values (see Supplementary Notes). Moreover, three analyses using the models are detailed here. Since most of these analyses cannot be done on previous brain models or HR1 as published, this work provides novel insight into brain energy metabolism.


Large-scale in silico modeling of metabolic interactions between cell types in the human brain.

Lewis NE, Schramm G, Bordbar A, Schellenberger J, Andersen MP, Cheng JK, Patel N, Yee A, Lewis RA, Eils R, König R, Palsson BØ - Nat. Biotechnol. (2010)

General structure of the modelsThree models were built from the brain reconstruction. Each model consists of various compartments: 1) the endothelium/blood, 2) astrocytes, 3) astrocytic mitochondria, 4) neurons, 5) neuronal mitochondria, and 6) an interstitial space between the cell types. Each neuron metabolic network was tailored to represent a specific neuron type, containing genes and reactions generally accepted to be unique to the neuron type. Mito = mitochondrion, Int = interstitial space, CMR = cerebral metabolic rate.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3140076&req=5

Figure 2: General structure of the modelsThree models were built from the brain reconstruction. Each model consists of various compartments: 1) the endothelium/blood, 2) astrocytes, 3) astrocytic mitochondria, 4) neurons, 5) neuronal mitochondria, and 6) an interstitial space between the cell types. Each neuron metabolic network was tailored to represent a specific neuron type, containing genes and reactions generally accepted to be unique to the neuron type. Mito = mitochondrion, Int = interstitial space, CMR = cerebral metabolic rate.
Mentions: This workflow was used to build three different multicellular models of brain energy metabolism. Each model represents one canonical neuron type (i.e., glutamatergic, GABAergic, or cholinergic), its interactions with the surrounding astrocytes, and the transport of metabolites through the blood-brain barrier (Fig. 2). This reconstruction focuses on the core of cerebral energy metabolism, including central metabolism, mitochondrial metabolic pathways, and pathways relevant to anabolism and catabolism of three neurotransmitters: glutamate, γ-aminobutarate (GABA), and acetylcholine. Thus, the three models contain the high flux pathways and important reactions in neuron and astrocyte metabolism. These models currently represent the largest and most detailed models of brain energy metabolism 13–15 (see Supplementary Notes). Our models contain 1066, 1067, and 1070 compartment-specific reactions, transformations, and exchanges, involving 983, 983, and 987 metabolite/compartment combinations, for the glutamatergic, GABAergic, and cholinergic models, respectively, and are associated with a total of 403 genes. Lists of reactions, genes, citations, and parameters used to constrain the models are detailed in Supplementary Tables 1– 5. The validity of these models is demonstrated through various tests and comparisons to physiological data. Specifically, our model predicts ATP production rates within 8% of the average published value, and internal flux measurements are consistent with experimentally measured values (see Supplementary Notes). Moreover, three analyses using the models are detailed here. Since most of these analyses cannot be done on previous brain models or HR1 as published, this work provides novel insight into brain energy metabolism.

Bottom Line: Transport reactions are used to account for the transfer of metabolites between models of different cell types via the interstitial fluid.Analysis of the models identifies genes and pathways that may explain observed experimental phenomena, including the differential effects of the disease on cell types and regions of the brain.Constraint-based modeling can thus contribute to the study and analysis of multicellular metabolic processes in the human tissue microenvironment and provide detailed mechanistic insight into high-throughput data analysis.

View Article: PubMed Central - PubMed

Affiliation: Department of Bioengineering, University of California, San Diego, La Jolla, California, USA.

ABSTRACT
Metabolic interactions between multiple cell types are difficult to model using existing approaches. Here we present a workflow that integrates gene expression data, proteomics data and literature-based manual curation to model human metabolism within and between different types of cells. Transport reactions are used to account for the transfer of metabolites between models of different cell types via the interstitial fluid. We apply the method to create models of brain energy metabolism that recapitulate metabolic interactions between astrocytes and various neuron types relevant to Alzheimer's disease. Analysis of the models identifies genes and pathways that may explain observed experimental phenomena, including the differential effects of the disease on cell types and regions of the brain. Constraint-based modeling can thus contribute to the study and analysis of multicellular metabolic processes in the human tissue microenvironment and provide detailed mechanistic insight into high-throughput data analysis.

Show MeSH
Related in: MedlinePlus