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Reconstruction and analysis of human kidney-specific metabolic network based on omics data.

Zhang AD, Dai SX, Huang JF - Biomed Res Int (2013)

Bottom Line: Importantly, a total of 267 potential metabolic biomarkers for kidney-related diseases were successfully explored using this model.Finally, the phenotypes of the differentially expressed genes in diabetic kidney disease were characterized, suggesting that these genes may affect disease development through altering kidney metabolism.Thus, the human kidney-specific model constructed in this study may provide valuable information for the metabolism of kidney and offer excellent insights into complex kidney diseases.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China ; Graduate School of the Chinese Academy of Sciences, Kunming 650223, China.

ABSTRACT
With the advent of the high-throughput data production, recent studies of tissue-specific metabolic networks have largely advanced our understanding of the metabolic basis of various physiological and pathological processes. However, for kidney, which plays an essential role in the body, the available kidney-specific model remains incomplete. This paper reports the reconstruction and characterization of the human kidney metabolic network based on transcriptome and proteome data. In silico simulations revealed that house-keeping genes were more essential than kidney-specific genes in maintaining kidney metabolism. Importantly, a total of 267 potential metabolic biomarkers for kidney-related diseases were successfully explored using this model. Furthermore, we found that the discrepancies in metabolic processes of different tissues are directly corresponding to tissue's functions. Finally, the phenotypes of the differentially expressed genes in diabetic kidney disease were characterized, suggesting that these genes may affect disease development through altering kidney metabolism. Thus, the human kidney-specific model constructed in this study may provide valuable information for the metabolism of kidney and offer excellent insights into complex kidney diseases.

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Related in: MedlinePlus

Reconstruction of human kidney-specific metabolic network. (a) illustrates the associations of genes with the linked reactions in the kidney metabolic network. The red circles represent genes (genes with the degree >10 are labeled with Entrez Gene ID), while the blue circles represent the linking reactions, and the lines represent the relationships between genes and reactions. (b) shows the node degrees distribution of the kidney metabolic network.
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fig1: Reconstruction of human kidney-specific metabolic network. (a) illustrates the associations of genes with the linked reactions in the kidney metabolic network. The red circles represent genes (genes with the degree >10 are labeled with Entrez Gene ID), while the blue circles represent the linking reactions, and the lines represent the relationships between genes and reactions. (b) shows the node degrees distribution of the kidney metabolic network.

Mentions: After applying the MBA method, the resulting kidney model consists of 2904 reactions, 1898 metabolites, and 1776 genes which are mainly enzymes and transporter genes. The kidney model of partially compartmentalization patterns, in SBML format, was generated (Supplementary File: kidney_model_par.xml in Supplementary Material available online at http://dx.doi.org/10.1155/2013/187509). The network visualization can be explored interactively using the freely available Cytoscape software. Figure 1(a) illustrates gene-reaction associations in the kidney metabolic network; it demonstrates that the genes are close to each other and each metabolic reaction is associated with one or more enzymes. The metabolic processes are largely involved in energy metabolism, extracellular transport, glycerophospholipid metabolism, heme synthesis, and nitrogen and lipid metabolism. The subcellular localization was ignored as the same metabolite could be localized in different cellular compartments being linked by transport reactions. By analyzing the network, we found that the degrees of this network follow the power-law distribution (Figure 1(b)), suggesting that most genes are involved only a few reactions while only a small number of genes participate in the generation of a large number of products.


Reconstruction and analysis of human kidney-specific metabolic network based on omics data.

Zhang AD, Dai SX, Huang JF - Biomed Res Int (2013)

Reconstruction of human kidney-specific metabolic network. (a) illustrates the associations of genes with the linked reactions in the kidney metabolic network. The red circles represent genes (genes with the degree >10 are labeled with Entrez Gene ID), while the blue circles represent the linking reactions, and the lines represent the relationships between genes and reactions. (b) shows the node degrees distribution of the kidney metabolic network.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3814056&req=5

fig1: Reconstruction of human kidney-specific metabolic network. (a) illustrates the associations of genes with the linked reactions in the kidney metabolic network. The red circles represent genes (genes with the degree >10 are labeled with Entrez Gene ID), while the blue circles represent the linking reactions, and the lines represent the relationships between genes and reactions. (b) shows the node degrees distribution of the kidney metabolic network.
Mentions: After applying the MBA method, the resulting kidney model consists of 2904 reactions, 1898 metabolites, and 1776 genes which are mainly enzymes and transporter genes. The kidney model of partially compartmentalization patterns, in SBML format, was generated (Supplementary File: kidney_model_par.xml in Supplementary Material available online at http://dx.doi.org/10.1155/2013/187509). The network visualization can be explored interactively using the freely available Cytoscape software. Figure 1(a) illustrates gene-reaction associations in the kidney metabolic network; it demonstrates that the genes are close to each other and each metabolic reaction is associated with one or more enzymes. The metabolic processes are largely involved in energy metabolism, extracellular transport, glycerophospholipid metabolism, heme synthesis, and nitrogen and lipid metabolism. The subcellular localization was ignored as the same metabolite could be localized in different cellular compartments being linked by transport reactions. By analyzing the network, we found that the degrees of this network follow the power-law distribution (Figure 1(b)), suggesting that most genes are involved only a few reactions while only a small number of genes participate in the generation of a large number of products.

Bottom Line: Importantly, a total of 267 potential metabolic biomarkers for kidney-related diseases were successfully explored using this model.Finally, the phenotypes of the differentially expressed genes in diabetic kidney disease were characterized, suggesting that these genes may affect disease development through altering kidney metabolism.Thus, the human kidney-specific model constructed in this study may provide valuable information for the metabolism of kidney and offer excellent insights into complex kidney diseases.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China ; Graduate School of the Chinese Academy of Sciences, Kunming 650223, China.

ABSTRACT
With the advent of the high-throughput data production, recent studies of tissue-specific metabolic networks have largely advanced our understanding of the metabolic basis of various physiological and pathological processes. However, for kidney, which plays an essential role in the body, the available kidney-specific model remains incomplete. This paper reports the reconstruction and characterization of the human kidney metabolic network based on transcriptome and proteome data. In silico simulations revealed that house-keeping genes were more essential than kidney-specific genes in maintaining kidney metabolism. Importantly, a total of 267 potential metabolic biomarkers for kidney-related diseases were successfully explored using this model. Furthermore, we found that the discrepancies in metabolic processes of different tissues are directly corresponding to tissue's functions. Finally, the phenotypes of the differentially expressed genes in diabetic kidney disease were characterized, suggesting that these genes may affect disease development through altering kidney metabolism. Thus, the human kidney-specific model constructed in this study may provide valuable information for the metabolism of kidney and offer excellent insights into complex kidney diseases.

Show MeSH
Related in: MedlinePlus