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首页> 外文期刊>Scientific reports. >Automated quantification of protein periodic nanostructures in fluorescence nanoscopy images: abundance and regularity of neuronal spectrin membrane-associated skeleton
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Automated quantification of protein periodic nanostructures in fluorescence nanoscopy images: abundance and regularity of neuronal spectrin membrane-associated skeleton

机译：荧光纳米图像中蛋白质周期纳米结构的自动定量：神经元光谱膜相关骨架的丰度和规律性

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Fluorescence nanoscopy imaging permits the observation of periodic supramolecular protein structures in their natural environment, as well as the unveiling of previously unknown protein periodic structures. Deciphering the biological functions of such protein nanostructures requires systematic and quantitative analysis of large number of images under different experimental conditions and specific stimuli. Here we present a method and an open source software for the automated quantification of protein periodic structures in super-resolved images. Its performance is demonstrated by analyzing the abundance and regularity of the spectrin membrane-associated periodic skeleton (MPS) in hippocampal neurons of 2 to 40 days in vitro, imaged by STED and STORM nanoscopy. The automated analysis reveals that both the abundance and the regularity of the MPS increase over time and reach maximum plateau values after 14 DIV. A detailed analysis of the distributions of correlation coefficients provides indication of dynamical assembly and disassembly of the MPS.
机译：荧光纳米显微镜成像可以观察其自然环境中的周期性超分子蛋白质结构，以及揭示以前未知的蛋白质周期性结构。解密这种蛋白质纳米结构的生物学功能需要在不同的实验条件和特定刺激下对大量图像进行系统和定量的分析。在这里，我们介绍了一种用于自动定量超分辨图像中蛋白质周期结构的方法和开源软件。通过分析STED和STORM纳米显微镜对体外2至40天海马神经元中与血影蛋白膜相关的周期性骨架（MPS）的丰度和规律性进行验证，证明了其性能。自动化分析表明，MPS的丰度和规律性随时间增加，并在14 DIV后达到最大平稳值。相关系数分布的详细分析提供了MPS动态组装和拆卸的指示。

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