Tripartite synapse and perisynaptic astrocytic process meshes
Authors/Creators
Description
The ultrastructural properties of the endoplasmic reticulum govern microdomain signaling in perisynaptic astrocytic processes
Dataset DOI: 10.5281/zenodo.17106549
Description of the data and file structure
This dataset contains the 28 fully reconstructed tripartite synapse meshes and the perisynaptic astrocytic process (PAP) meshes from the following study:
Denizot, A.; Veloz Castillo, M. F.; Puchenkov, P.; Cali, C.; De Schutter, E. (2025). The ultrastructural properties of the endoplasmic reticulum govern microdomain signaling in perisynaptic astrocytic processes. DOI: 10.1101/2022.02.28.482292
The data are organized into 2 main folders:
- "TripartiteSynapseMeshes", which contains the 28 fully reconstructed tripartite synapse meshes of the study (Figures 1 and 2). Each contains 4 elements: the presynaptic bouton, the postsynaptic dendritic spine head, the post-synaptic density, and the perisynaptic astrocytic process.
- "PAPMeshes", which contains 3D meshes of perisynaptic astrocytic processes and is subvidided into 2 folders:
- "EMPAPMeshes" contains the PAP meshes extracted from electron microscopy presented in Figure 3 of the manuscript.
- "RealisticPAPMeshes" contains realistic PAP meshes generated based on PAP geometries reconstructed from volume electron microscopy. These meshes are presented in Figures 4 and 5 of the manuscript.
More details can be found in the README files of each folder.
License: Creative Commons Attribution 4.0 International
Please cite this repository and the original paper if using the dataset in your research.
Code/software
The code used in this study is available at https://github.com/adenizot/PAP-ER
Files are organized within different folders, as follows:
- 'Ca2+Model' contains the simulation code used in Fig. 3, 4 and 5. The code was written for simulations using the STochastic Engine for Pathway Simulations (STEPS, http://steps.sourceforge.net/STEPS/default.php) 3.5.0
- 'GeometryAnalysis' contains the analysis code used to measure PM-PSD, ER-PSD or ER-PM distances.
- 'PAPMeshGeneration' contains the algorithm that allows the generation of realistic PAP meshes with various ER distributions in the PAP, with constant ER and PAP shape.
The codes in 'GeometryAnalysis' and 'PAPMeshGeneration' were implemented for Blender 4.3.2.
Access information
Data was derived from the following source:
Calì, C. et al. Three-dimensional immersive virtual reality for studying cellular compartments in 3D models from EM preparations of neural tissues. J. Comp. Neurol. 524, 23–38 (2016), DOI: 10.1002/cne.23852
We thank Graham Knott for kindly sharing the original EM dataset.
Contact
audrey.denizot@inria.fr
Files
Denizotetal2025_meshes.zip
Files
(305.0 MB)
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Additional details
Related works
- Is derived from
- Publication: 10.1002/cne.23852 (DOI)
Funding
Dates
- Submitted
-
2025-09
Software
- Repository URL
- https://github.com/adenizot/PAP-ER
- Programming language
- Python