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基于网络的人血浆正交分离分析揭示了不同的高密度脂蛋白复合物。

Network-Based Analysis on Orthogonal Separation of Human Plasma Uncovers Distinct High Density Lipoprotein Complexes.

作者信息

Li Hailong, Gordon Scott M, Zhu Xiaoting, Deng Jingyuan, Swertfeger Debi K, Davidson W Sean, Lu L Jason

机构信息

§Institute for Systems Biology, Jianghan University, Wuhan, Hubei, 430056, P.R. China.

†Division of Biomedical Informatics, Cincinnati Children's Hospital Research Foundation, 3333 Burnet Avenue, MLC 7024, Cincinnati, Ohio 45229-3039, United States.

出版信息

J Proteome Res. 2015 Aug 7;14(8):3082-94. doi: 10.1021/acs.jproteome.5b00419. Epub 2015 Jun 30.

Abstract

High density lipoprotein (HDL) particles are blood-borne complexes whose plasma levels have been associated with protection from cardiovascular disease (CVD). Recent studies have demonstrated the existence of distinct HDL subspecies; however, these have been difficult to isolate and characterize biochemically. Here, we present the first report that employs a network-based approach to systematically infer HDL subspecies. Healthy human plasma was separated into 58 fractions using our previously published three orthogonal chromatography techniques. Similar local migration patterns among HDL proteins were captured with a novel similarity score, and individual comigration networks were constructed for each fraction. By employing a graph mining algorithm, we identified 183 overlapped cliques, among which 38 were further selected as candidate HDL subparticles. Each of these 38 subparticles had at least two literature supports. In addition, GO function enrichment analysis showed that they were enriched with fundamental biological and CVD protective functions. Furthermore, gene knockout experiments in mouse model supported the validity of these subparticles related to three apolipoproteins. Finally, analysis of an apoA-I deficient human patient's plasma provided additional support for apoA-I related complexes. Further biochemical characterization of these putative subspecies may facilitate the mechanistic research of CVD and guide targeted therapeutics aimed at its mitigation.

摘要

高密度脂蛋白(HDL)颗粒是血液中的复合物,其血浆水平与预防心血管疾病(CVD)有关。最近的研究表明存在不同的HDL亚类;然而,这些亚类很难通过生化方法分离和表征。在此,我们首次报告采用基于网络的方法系统推断HDL亚类。使用我们之前发表的三种正交色谱技术将健康人血浆分离成58个组分。通过一种新的相似性评分捕捉HDL蛋白之间相似的局部迁移模式,并为每个组分构建单独的共迁移网络。通过采用图挖掘算法,我们识别出183个重叠团,其中38个被进一步选为候选HDL亚颗粒。这38个亚颗粒中的每一个都至少有两个文献支持。此外,基因本体(GO)功能富集分析表明它们富含基本生物学功能和CVD保护功能。此外,小鼠模型中的基因敲除实验支持了这些与三种载脂蛋白相关的亚颗粒的有效性。最后,对一名载脂蛋白A-I缺乏症患者血浆的分析为与载脂蛋白A-I相关的复合物提供了额外支持。对这些假定亚类的进一步生化表征可能有助于CVD的机制研究,并指导旨在减轻CVD的靶向治疗。

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