Global reconstruction of the human metabolic network based on genomic and bibliomic data
Global reconstruction of the human metabolic network based on genomic and bibliomic data
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DOI：
10.1073/pnas.0610772104
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发表时间：
2007-02-06
影响因子：
11.1
通讯作者：
Palsson, Bernhard O.
中科院分区：
文献类型：
--
作者：
Duarte, Natalie C.;Becker, Scott A.;Palsson, Bernhard O.
新陈代谢是一个至关重要的细胞过程，其功能失调是人类疾病的一个主要诱因。代谢网络复杂且高度相互关联，因此需要系统层面的计算方法来阐明和理解代谢基因型 - 表型关系。我们基于基因组注释第35版以及对50多年遗留数据（即文献组学数据）的综合评估，手动重建了全球人类代谢网络。在此我们描述重建过程，并展示所得的基因组规模（或全球）网络如何能够被用于（i）发现缺失信息，（ii）构建一个计算机模拟模型，以及（iii）作为分析高通量生物数据集的结构化背景。我们对文献的综合评估揭示了当前对人类新陈代谢理解上的许多空白，这需要未来的实验研究。对网络结构的数学分析阐明了细胞内区室化的影响以及相关反应集在替代药物靶点识别中的潜在用途。在重建背景下对高通量数据集的综合分析能够对功能性代谢状态进行全局评估。这些结果突出了重建的人类代谢网络所实现的一些应用。这个网络的建立是朝着基因组规模的人类系统生物学迈出的重要一步。
Metabolism is a vital cellular process, and its malfunction is a major contributor to human disease. Metabolic networks are complex and highly interconnected, and thus systems-level computational approaches are required to elucidate and understand metabolic genotype-phenotype relationships. We have manually reconstructed the global human metabolic network based on Build 35 of the genome annotation and a comprehensive evaluation of > 50 years of legacy data (i.e., bibliomic data). Herein we describe the reconstruction process and demonstrate how the resulting genome-scale (or global) network can be used (i) for the discovery of missing information, (ii) for the formulation of an in silico model, and (iii) as a structured context for analyzing high-throughput biological data sets. Our comprehensive evaluation of the literature revealed many gaps in the current understanding of human metabolism that require future experimental investigation. Mathematical analysis of network structure elucidated the implications of intracellular compartmentalization and the potential use of correlated reaction sets for alternative drug target identification. Integrated analysis of high-throughput data sets within the context of the reconstruction enabled a global assessment of functional metabolic states. These results highlight some of the applications enabled by the reconstructed human metabolic network. The establishment of this network represents an important step toward genome-scale human systems biology.