Metabolomic Analysis of Key Regulatory Metabolites in Hepatitis C Virus-infected Tree Shrews
Metabolomic Analysis of Key Regulatory Metabolites in Hepatitis C Virus-infected Tree Shrews
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DOI：
10.1074/mcp.m112.019141
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发表时间：
2013-03-01
影响因子：
7
通讯作者：
Wang, Xijun
中科院分区：
文献类型：
--
作者：
Sun, Hui;Zhang, Aihua;Wang, Xijun
代谢组学是一种强大的新技术，可以评估生物系统中的全局低分子量代谢物，并在生物标志物发现方面显示出巨大的潜力。体液中关键代谢物的分析已成为改善疾病诊断、预后和治疗的重要组成部分。丙型肝炎病毒（HCV）是世界范围内肝病的主要原因，也是公共卫生的严重负担。然而，缺乏小动物模型阻碍了HCV发病机制的分析。我们假设HCV的动物模型（树鼩）将产生独特的代谢表型特征。超高效液相色谱/电喷雾电离-SYNAPT-高清晰度质谱（UPLC/ESI-SYNAPT-HDMS）结合模式识别方法和系统分析进行，以获得大生物数据集的全面代谢组学分析和途径。牛磺酸、亚牛磺酸、醚脂质、甘油磷脂、花生四烯酸、色氨酸和初级胆汁酸代谢途径受到严重干扰，鉴定出38种差异代谢产物。更重要的是，通过“微阵列显著性分析”方法选择了五种代谢物标志物作为最具区分性和最有趣的生物标志物，用于诊断HCV。网络构建导致了与多个扰动途径相关的代谢物的整合。关键代谢物的综合网络分析产生与差异表达蛋白相关的高度相关的信号通路，这表明创建新的治疗范式靶向和激活这些网络的整体，而不是单一蛋白质，可能是有效控制和治疗HCV所必需的。Molecular & Cellular Proteomics 12：10.1074/mcp. M112.019141，710-719，2013.
Metabolomics is a powerful new technology that allows the assessment of global low-molecular-weight metabolites in a biological system and which shows great potential in biomarker discovery. Analysis of the key metabolites in body fluids has become an important part of improving the diagnosis, prognosis, and therapy of diseases. Hepatitis C virus (HCV) is a major leading cause of liver disease worldwide and a serious burden on public health. However, the lack of a small-animal model has hampered the analysis of HCV pathogenesis. We hypothesize that an animal model (Tupaia belangeri chinensis) of HCV would produce a unique characterization of metabolic phenotypes. Ultra-performance liquid-chromatography/electrospray ionization-SYNAPT-high-definition mass spectrometry (UPLC/ESI-SYNAPT-HDMS) coupled with pattern recognition methods and system analysis was carried out to obtain comprehensive metabolomics profiling and pathways of large biological data sets. Taurine, hypotaurine, ether lipid, glycerophospholipid, arachidonic acid, tryptophan, and primary bile acid metabolism pathways were acutely perturbed, and 38 differential metabolites were identified. More important, five metabolite markers were selected via the "significance analysis for microarrays" method as the most discriminant and interesting biomarkers that were effective for the diagnosis of HCV. Network construction has led to the integration of metabolites associated with the multiple perturbation pathways. Integrated network analysis of the key metabolites yields highly related signaling pathways associated with the differentially expressed proteins, which suggests that the creation of new treatment paradigms targeting and activating these networks in their entirety, rather than single proteins, might be necessary for controlling and treating HCV efficiently. Molecular & Cellular Proteomics 12: 10.1074/mcp.M112.019141, 710-719, 2013.