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Automatic Identification of Dendritic Branches and their Orientation
In This Article
Summary
Presented is a computational tool that allows simple and direct automatic measurement of orientations of neuronal dendritic branches from 2D fluorescence images.
Abstract
The structure of neuronal dendritic trees plays a key role in the integration of synaptic inputs in neurons. Therefore, characterization of the morphology of dendrites is essential for a better understanding of neuronal function. However, the complexity of dendritic trees, both when isolated and especially when located within neuronal networks, has not been completely understood. We developed a new computational tool, SOA (Segmentation and Orientation Analysis), which allows automatic measurement of the orientation of dendritic branches from fluorescence images of 2D neuronal cultures. SOA, written in Python, uses segmentation to distinguish dendritic branches from the image background and accumulates a database on the spatial direction of each branch. The database is then used to calculate morphological parameters such as the directional distribution of dendritic branches in a network and the prevalence of parallel dendritic branch growth. The data obtained can be used to detect structural changes in dendrites in response to neuronal activity and to biological and pharmacological stimuli.
Introduction
Dendritic morphogenesis is a central subject in neuroscience, as the structure of the dendritic tree affects the computational properties of synaptic integration in neurons1,2,3. Moreover, morphological abnormalities and modifications in dendritic branches are implicated in degenerative and neuro-developmental disorders4,5,6. In neuronal cultures where dendritic ramification can be more readily visualized, the interactions between non-sister dendritic branches regulate the sites and ....
Protocol
NOTE: The Israeli Ministry of Health approved the use of mice under protocol IL-218-01-21 for the ethical use of experimental animals. SOA is only compatible with Windows 10 and Python 3.9. It is available as an open-source code: https://github.com/inbar2748/DendriteProject. At this link, there is also a README.DM file that has directions for downloading the software, a link to the software's website, and a requirements file containing information on the required versions of all the packages. Additional examples.......
Representative Results
A representative analysis was performed on images of dendritic networks in culture. Cells were extracted as described by Baranes et al.16,17. Briefly, hippocampal cells were extracted from the brains of postnatal rats and cultivated on 2D glass coverslips for 1-2 weeks. The cultures were then fixed and stained through indirect immunofluorescence using an antibody against the dendritic protein marker, microtubule-associated protein 2 (MAP2). Images of den.......
Discussion
Effective strategies for extracting morphological information from 2D images are urgently required to keep up with biological imaging data. Although imaging data can be generated in hours, in-depth analysis of the images takes a long time. As a result, image processing has clearly become a major obstacle in many fields. This is due in part to the high complexity of the data, especially when dealing with biological samples. Furthermore, as many users lack specialized programming and image processing skills, automated tool.......
Acknowledgements
The authors would like to thank Dr. Orly Weiss for the preparation of the culture images.
....Materials
| Name | Company | Catalog Number | Comments |
| Matplotlib | 2002 - 2012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the Matplotlib development team; 2012 - 2021 The Matplotlib development team. | 3.4.2 | a Python 2D plotting library |
| matplotlib-scalebar | Philippe Pinard | 0.7.2 | artist for matplotlib to display a scale bar |
| NumPy | The NumPy community. | 1.20.3 | fundamental package for scientific computing library |
| OpenCV | OpenCV team | 4.5.2.54 | Open Source Computer Vision Library |
| PyCharm | JetBrains | 2020.3.1 (Community Edition) version | Build #PC-203.6682.86, built on December 18, 2020. Runtime version: 11.0.9.1+11-b1145.37 amd64. VM: OpenJDK 64-Bit Server VM by JetBrains s.r.o. Windows 10 10.0. Memory: 978M, Cores: 4 |
| PyQt5 | Riverbank Computing | 5.15.4 | manage the GUI |
| python | Python Software Foundation License | 3.9 version | |
| Qt Designer | The QT Company Ltd. | 5.11.1 version | |
| scipy | Community library project | 1.6.3 | Python-based ecosystem of open-source software for mathematics, science, and engineering |
| Seaborn | Michael Waskom. | 0.11.1 | Python's Statistical Data Visualization Library. |
| Windows 10 | Microsoft | ||
| Xlsxwriter | John McNamara | 1.4.3 | Python module for creating Excel XLSX files |
References
- Ferrante, M., Migliore, M., Ascoli, G. Functional impact of dendritic branch-point morphology. Journal of Neuroscience. 33 (5), 2156-2165 (2013).
- Spruston, N. Pyramidal neurons: dendritic structure and synaptic integration.
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