Published September 12, 2025 | Version v1
Dataset Open

Tripartite synapse and perisynaptic astrocytic process meshes

  • 1. ROR icon Inria Lyon Centre
  • 2. ROR icon King Abdullah University of Science and Technology
  • 3. EDMO icon Okinawa Institute of Science and Technology
  • 4. ROR icon University of Turin

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

Japan Society for the Promotion of Science
Standard Postdoctoral Fellowship for Research in Japan 21F21733

Dates

Submitted
2025-09

Software

Repository URL
https://github.com/adenizot/PAP-ER
Programming language
Python