том 4 издание 12 номер публикации e70061

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

Тип публикацииJournal Article
Дата публикации2024-12-06
scimago Q1
Tоп 10% SciMago
wos Q3
white level БС3
SJR1.598
CiteScore6.2
Impact factor2.2
ISSN26911299
Краткое описание

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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International Journal of Molecular Sciences
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Bioinformatics
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bioRxiv
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Ustinova A. et al. Generate and Analyze Three‐Dimensional Dendritic Spine Morphology Datasets With SpineTool Software // Current Protocols. 2024. Vol. 4. No. 12. e70061
ГОСТ со всеми авторами (до 50) Скопировать
Ustinova A., Volkova E., Rakovskaya A., Smirnova D., Korovina O., Pchitskaya E. Generate and Analyze Three‐Dimensional Dendritic Spine Morphology Datasets With SpineTool Software // Current Protocols. 2024. Vol. 4. No. 12. e70061
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TY - JOUR
DO - 10.1002/cpz1.70061
UR - https://currentprotocols.onlinelibrary.wiley.com/doi/10.1002/cpz1.70061
TI - Generate and Analyze Three‐Dimensional Dendritic Spine Morphology Datasets With SpineTool Software
T2 - Current Protocols
AU - Ustinova, Anita
AU - Volkova, Ekaterina
AU - Rakovskaya, Anastasiya
AU - Smirnova, Daria
AU - Korovina, Olesya
AU - Pchitskaya, Ekaterina
PY - 2024
DA - 2024/12/06
PB - Wiley
IS - 12
VL - 4
PMID - 39641661
SN - 2691-1299
ER -
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@article{2024_Ustinova,
author = {Anita Ustinova and Ekaterina Volkova and Anastasiya Rakovskaya and Daria Smirnova and Olesya Korovina and Ekaterina Pchitskaya},
title = {Generate and Analyze Three‐Dimensional Dendritic Spine Morphology Datasets With SpineTool Software},
journal = {Current Protocols},
year = {2024},
volume = {4},
publisher = {Wiley},
month = {dec},
url = {https://currentprotocols.onlinelibrary.wiley.com/doi/10.1002/cpz1.70061},
number = {12},
pages = {e70061},
doi = {10.1002/cpz1.70061}
}
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