Generate and Analyze Three‐Dimensional Dendritic Spine Morphology Datasets With SpineTool Software

树突棘 分割 神经科学 计算机科学 共焦 脊柱(分子生物学) 生物 人工智能 海马结构 生物信息学 物理 光学
作者
Anita Ustinova,E. N. Volkova,Anastasiya Rakovskaya,Daria Smirnova,Olesya Korovina,Ekaterina Pchitskaya
出处
期刊:Current protocols [Wiley]
卷期号:4 (12)
标识
DOI:10.1002/cpz1.70061
摘要

Abstract Dendritic spine morphology is associated with the current state of the synapse and neuron, and changes during synaptic plasticity in response to stimulus. At the same time, dendritic spine alterations are reported during various neurodegenerative and neurodevelopmental disorders and other brain states. Accurate and informative analysis of spine shape has an urgent need for studying the synaptic processes and molecular pathways in normal and pathological conditions, and for testing synapto‐protective strategies during preclinical studies. Primary neuronal cultures enable high quality imaging of dendritic spines and offer a wide spectrum of accessible experimental manipulations. This article outlines the protocol for isolating, culturing, fluorescent labeling, and imaging of mouse primary hippocampal neurons by three‐dimensional (3D) confocal microscopy in a normal state and in conditions of low amyloid toxicity—an in vitro model of Alzheimer's disease. An alternate protocol describes the neuronal morphology analysis using the EGFP expressing neurons in line‐M transgenic mouse brain slices. Since the dendritic spines are relatively small structures lying close to the confocal microscope resolution limit, their proper segmentation on the images is challenging. This protocol highlights the image‐preprocessing steps, including generation of theoretical point spread function and deconvolution, which enhances resolution and removes noise, thereby enhancing the 3D spine reconstruction results. SpineTool, an open source Python–based script, enables 3D segmentation of dendrites and spines and numerical metric calculation, including key measures, such as spine length, volume, and surface area, with a new feature, the chord length distribution histogram, improving clustering results. SpineTool supports both manual and machine learning spine classification (i.e., mushroom, thin, stubby, filopodia) and automated clustering using k‐means and DBSCAN methods. This protocol provides detailed instructions for using SpineTool to analyze and classify dendritic spines in control and experimental groups, enhancing our understanding of spine morphology across different experimental conditions. © 2024 Wiley Periodicals LLC. Basic Protocol 1 : Obtaining 3D confocal dendritic spine images of hippocampal neuronal culture in normal state and conditions of low amyloid toxicity Alternate Protocol : Obtaining confocal dendritic spine images of mice hippocampal neurons from fixed brain slices Support Protocol : Post‐processing deconvolution of confocal images Basic Protocol 2 : Segmentation of dendritic spines with SpineTool Basic Protocol 3 : Spine dataset preparation using SpineTool Basic Protocol 4 : Clustering of dendritic spines with SpineTool Basic Protocol 5 : Machine classification of dendritic spines with SpineTool

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