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Spatial mapping of protein abundances in the mouse brain by voxelation integrated with high-throughput liquid chromatography–mass spectrometry

机译:体素结合高通量液相色谱-质谱联用体素分析小鼠大脑中蛋白质丰度的空间作图

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摘要

Temporally and spatially resolved mapping of protein abundance patterns within the mammalian brain is of significant interest for understanding brain function and molecular etiologies of neurodegenerative diseases; however, such imaging efforts have been greatly challenged by complexity of the proteome, throughput and sensitivity of applied analytical methodologies, and accurate quantitation of protein abundances across the brain. Here, we describe a methodology for comprehensive spatial proteome mapping that addresses these challenges by employing voxelation integrated with automated microscale sample processing, high-throughput liquid chromatography (LC) system coupled with high-resolution Fourier transform ion cyclotron resonance (FTICR) mass spectrometer, and a “universal” stable isotope labeled reference sample approach for robust quantitation. We applied this methodology as a proof-of-concept trial for the analysis of protein distribution within a single coronal slice of a C57BL/6J mouse brain. For relative quantitation of the protein abundances across the slice, an 18O-isotopically labeled reference sample, derived from a whole control coronal slice from another mouse, was spiked into each voxel sample, and stable isotopic intensity ratios were used to obtain measures of relative protein abundances. In total, we generated maps of protein abundance patterns for 1028 proteins. The significant agreement of the protein distributions with previously reported data supports the validity of this methodology, which opens new opportunities for studying the spatial brain proteome and its dynamics during the course of disease progression and other important biological and associated health aspects in a discovery-driven fashion.
机译:哺乳动物大脑中蛋白质丰度模式的时间和空间分辨图谱对于理解大脑功能和神经退行性疾病的分子病因具有重大意义。然而,蛋白质组学的复杂性,应用分析方法的通量和灵敏度以及大脑中蛋白质丰度的准确定量,极大地挑战了这种成像工作。在这里,我们描述了一种用于综合空间蛋白质组映射的方法,该方法通过将体素化与自动化的微型样品处理,高通量液相色谱(LC)系统与高分辨率傅里叶变换离子回旋共振(FTICR)质谱仪结合使用,解决了这些挑战,以及“通用”的稳定同位素标记的参考样品方法,可实现可靠的定量。我们将这种方法用作概念验证试验,用于分析C57BL / 6J小鼠大脑单个冠状切片内的蛋白质分布。为了相对定量切片中的蛋白质丰度,将来自另一只小鼠的整个对照冠状切片的 18 O同位素标记的参考样品掺入每个体素样品中,并测定稳定的同位素强度比用于获得相对蛋白质丰度的度量。总共,我们生成了1028种蛋白质的蛋白质丰度模式图。蛋白质分布与先前报道的数据之间的显着一致性支持了这种方法的有效性,这为研究疾病驱动下的空间脑蛋白质组及其动力学以及其他重要的生物学和相关健康方面提供了新的机会时尚。

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