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利用反相蛋白质微阵列进行心脏壁层蛋白质组的高分辨率图谱绘制。

High resolution mapping of the cardiac transmural proteome using reverse phase protein microarrays.

机构信息

Institute for Computational Medicine, Center for Cardiovascular Bioinformatics and Modeling, Johns Hopkins University, 3400 N. Charles Street, Hackerman Hall, Room 317, Baltimore, MD 21218, USA.

出版信息

Mol Cell Proteomics. 2011 Jul;10(7):M111.008037. doi: 10.1074/mcp.M111.008037. Epub 2011 Apr 13.

Abstract

The expression level of proteins governing the electrical excitability of and conduction within ventricular myocardium are known to vary as a function of distance through the heart wall. The expression patterns of a subset of these proteins are altered in disease. Precise measurement of such patterns is therefore essential to understanding structure-function relationships within the heart in health and disease. Here, we report a new experimental approach using reverse-phase protein microarrays to map the left ventricular transmural proteome. This approach can yield submillimeter spatial resolution, and when coupled with the method of array microenvironment normalization, reduces nonbiological components of variability to ∼10% of overall study variability. In addition, the experimental design provides sufficient statistical power to detect small, yet potentially biologically significant expression changes on the order of 1.1-fold. The usefulness of this technique is demonstrated by mapping the transmural expression of Serca2a in the left ventricle of 12 canine hearts, each in one of three states: normal, dyssynchronous heart failure, and dyssynchronous heart failure followed by cardiac resynchronization therapy. We confirm the existence of a 40% transmural gradient (epi>endo) of Serca2a, and demonstrate the ability of this technique to yield highly significant transmural expression differences within each individual heart.

摘要

已知控制心室心肌电兴奋性和传导性的蛋白质的表达水平会随心脏壁的距离而变化。这些蛋白质中的一部分的表达模式在疾病中会发生改变。因此,精确测量这些模式对于了解健康和疾病中心脏的结构-功能关系至关重要。在这里,我们报告了一种使用反相蛋白质微阵列来绘制左心室穿壁蛋白质组的新实验方法。这种方法可以实现亚毫米级的空间分辨率,并且当与阵列微环境归一化方法结合使用时,可以将非生物学变异性的成分降低到总研究变异性的约 10%。此外,该实验设计提供了足够的统计能力,可以检测到小但潜在生物学意义上的表达变化,幅度约为 1.1 倍。该技术的实用性通过绘制 12 只犬心脏的左心室中 Serca2a 的穿壁表达来证明,每只心脏处于正常、不同步心力衰竭和不同步心力衰竭后心脏再同步治疗三种状态之一。我们证实了 Serca2a 存在 40%的穿壁梯度(心外膜>心内膜),并且证明了该技术能够在每个心脏中产生高度显著的穿壁表达差异。

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本文引用的文献

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