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基于结构光照明显微镜的树突棘的计算几何分析。

Computational geometry analysis of dendritic spines by structured illumination microscopy.

机构信息

Department of Cellular Neurobiology, Graduate School of Medicine, the University of Tokyo, Tokyo, 1130033, Japan.

Genes to Cognition Program, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK.

出版信息

Nat Commun. 2019 Mar 20;10(1):1285. doi: 10.1038/s41467-019-09337-0.

Abstract

Dendritic spines are the postsynaptic sites that receive most of the excitatory synaptic inputs, and thus provide the structural basis for synaptic function. Here, we describe an accurate method for measurement and analysis of spine morphology based on structured illumination microscopy (SIM) and computational geometry in cultured neurons. Surface mesh data converted from SIM images were comparable to data reconstructed from electron microscopic images. Dimensional reduction and machine learning applied to large data sets enabled identification of spine phenotypes caused by genetic mutations in key signal transduction molecules. This method, combined with time-lapse live imaging and glutamate uncaging, could detect plasticity-related changes in spine head curvature. The results suggested that the concave surfaces of spines are important for the long-term structural stabilization of spines by synaptic adhesion molecules.

摘要

树突棘是接收大部分兴奋性突触输入的突触后位点,为突触功能提供了结构基础。在这里,我们描述了一种基于结构光照明显微镜(SIM)和计算几何的培养神经元中树突棘形态测量和分析的精确方法。从 SIM 图像转换的表面网格数据与从电子显微镜图像重建的数据具有可比性。降维和机器学习应用于大型数据集,可以识别关键信号转导分子中的基因突变引起的树突棘表型。该方法与延时活成像和谷氨酸光解相结合,可以检测到与树突棘头部曲率相关的可塑性变化。结果表明,树突棘的凹面对于突触黏附分子对树突棘的长期结构稳定是重要的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c39/6427002/b329e0b4b268/41467_2019_9337_Fig1_HTML.jpg

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