Literature DB >> 20136149

Reconstruction and analysis of human liver-specific metabolic network based on CNHLPP data.

Jing Zhao1, Chao Geng, Lin Tao, Duanfeng Zhang, Ying Jiang, Kailin Tang, Ruixin Zhu, Hong Yu, Weidong Zhang, Fuchu He, Yixue Li, Zhiwei Cao.   

Abstract

Liver is the largest internal organ in the body that takes central roles in metabolic homeostasis, detoxification of various substances, as well as in the synthesis and storage of nutrients. To fulfill these complex tasks, thousands of biochemical reactions are going on in liver to cope with a wide range of foods and environmental variations, which are densely interconnected into an intricate metabolic network. Here, the first human liver-specific metabolic network was reconstructed according to proteomics data from Chinese Human Liver Proteome Project (CNHLPP), and then investigated in the context of the genome-scale metabolic network of Homo sapiens. Topological analysis shows that this organ-specific metabolic network exhibits similar features as organism-specific networks, such as power-law degree distribution, small-world property, and bow-tie structure. Furthermore, the structure of liver network exhibits a modular organization where the modules are formed around precursors from primary metabolism or hub metabolites from derivative metabolism, respectively. Most of the modules are dominated by one major category of metabolisms, while enzymes within same modules have a tendency of being expressed concertedly at protein level. Network decomposition and comparison suggest that the liver network overlays a predominant area in the global metabolic network of H. sapiens genome; meanwhile the human network may develop extra modules to gain more specialized functionality out of liver. The results of this study would permit a high-level interpretation of the metabolite information flow in human liver and provide a basis for modeling the physiological and pathological metabolic states of liver.

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Year:  2010        PMID: 20136149     DOI: 10.1021/pr9006188

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


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