Automated quantification of protein periodic nanostructures in fluorescence nanoscopy images: abundance and regularity of neuronal spectrin membrane-associated skeleton
Automated quantification of protein periodic nanostructures in fluorescence nanoscopy images: abundance and regularity of neuronal spectrin membrane-associated skeleton
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DOI：
10.1038/s41598-017-16280-x
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发表时间：
2017-11-22
影响因子：
4.6
通讯作者：
Stefani, Fernando D.
中科院分区：
文献类型：
--
作者：
Barabas, Federico M.;Masullo, Luciano A.;Stefani, Fernando D.
荧光纳米成像可以观察自然环境中周期性的超分子蛋白质结构，也可以揭示以前未知的蛋白质周期结构。要破译这种蛋白质纳米结构的生物学功能，需要对不同实验条件和特定刺激下的大量图像进行系统和定量的分析。在这里，我们提出了一种方法和一个开放源码软件，用于在超分辨率图像中自动量化蛋白质周期结构。通过对体外培养2~40天的海马神经细胞膜相关周期骨架的丰度和规律性进行分析，并用STED和STORM纳米显微镜进行成像，验证了该方法的有效性。自动分析表明，MPS的丰度和规律性都随着时间的推移而增加，并在14DIV后达到最大平台值。对相关系数分布的详细分析为MPS的动态组装和拆卸提供了指示。
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.