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Resolution Matters: Correlating Quantitative Proteomics and Nanoscale‐Precision Microscopy for Reconstructing Synapse Identity

机译:分辨率很重要:定量蛋白质组学和纳米级精密显微镜的相关性可重建突触识别

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摘要

For more than a century, the precision at which any protein (or RNA) could be localized in living cells depends on the spatial resolution of microscopy. Light microscopy, even recently benchmarked laser‐scanning microscopy, is inherently liable to the diffraction limit of visible light. Electron microscopy that had existed as the only alternative for decades is, in turn, of low throughput and sensitive to processing artefacts. Therefore, researchers have looked for alternative technologies particularly with ever‐growing interest in resolving structural underpinnings of cellular heterogeneity in the human body. Computational (“in silico”) predictions provided only partial solutions given the incompleteness of existing databases and erroneous assumptions on evolutionarily conserved sequence homology across species. A breakthrough that facilitates subcellular protein localization came with the introduction of “super‐resolution” microscopy, which yields 20–60 nm resolution by overcoming diffraction‐limited technologies. The ensuing combination of “super‐resolution” microscopy with unbiased proteomics continues to produce never‐before‐seen gains by quantitatively addressing the distribution, interaction, turnover, and secretion of proteins in living cells. Here, we illustrate the power of this combined work flow by the example of transmembrane receptor localization at the neuronal synapse. We also discuss how dynamic analysis allows for inferences be made for cellular physiology and pathobiology.
机译:一个多世纪以来,任何蛋白质(或RNA)在活细胞中的定位精度取决于显微镜的空间分辨率。光学显微镜,甚至是最近进行基准测试的激光扫描显微镜,都固有地易受可见光衍射极限的影响。反过来,数十年来唯一存在的电子显微镜替代技术是低通量且对加工制品敏感。因此,研究人员一直在寻找替代技术,尤其是对解决人体细胞异质性的结构基础越来越感兴趣。鉴于现有数据库的不完整以及对物种间进化保守序列同源性的错误假设,计算(“计算机模拟”)预测仅提供了部分解决方案。促进亚细胞蛋白质定位的突破是“超分辨率”显微镜的引入,该技术通过克服衍射限制技术可产生20-60 nm的分辨率。随后的“超分辨率”显微镜与无偏蛋白质组学的结合,通过定量解决活细胞中蛋白质的分布,相互作用,周转和分泌,继续产生前所未有的收益。在这里,我们以跨膜受体在神经元突触处的定位为例,说明这种组合工作流程的功能。我们还将讨论动态分析如何允许对细胞生理学和病理生物学进行推论。

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