Metaball skinning of synthetic astroglial morphologies into realistic mesh models for visual analytics and in silico simulations.
Journal
Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944
Informations de publication
Date de publication:
12 07 2021
12 07 2021
Historique:
entrez:
12
7
2021
pubmed:
13
7
2021
medline:
16
7
2021
Statut:
ppublish
Résumé
Astrocytes, the most abundant glial cells in the mammalian brain, have an instrumental role in developing neuronal circuits. They contribute to the physical structuring of the brain, modulating synaptic activity and maintaining the blood-brain barrier in addition to other significant aspects that impact brain function. Biophysically, detailed astrocytic models are key to unraveling their functional mechanisms via molecular simulations at microscopic scales. Detailed, and complete, biological reconstructions of astrocytic cells are sparse. Nonetheless, data-driven digital reconstruction of astroglial morphologies that are statistically identical to biological counterparts are becoming available. We use those synthetic morphologies to generate astrocytic meshes with realistic geometries, making it possible to perform these simulations. We present an unconditionally robust method capable of reconstructing high fidelity polygonal meshes of astroglial cells from algorithmically-synthesized morphologies. Our method uses implicit surfaces, or metaballs, to skin the different structural components of astrocytes and then blend them in a seamless fashion. We also provide an end-to-end pipeline to produce optimized two- and three-dimensional meshes for visual analytics and simulations, respectively. The performance of our pipeline has been assessed with a group of 5000 astroglial morphologies and the geometric metrics of the resulting meshes are evaluated. The usability of the meshes is then demonstrated with different use cases. Our metaball skinning algorithm is implemented in Blender 2.82 relying on its Python API (Application Programming Interface). To make it accessible to computational biologists and neuroscientists, the implementation has been integrated into NeuroMorphoVis, an open source and domain specific package that is primarily designed for neuronal morphology visualization and meshing. Supplementary data are available at Bioinformatics online.
Identifiants
pubmed: 34252950
pii: 6319688
doi: 10.1093/bioinformatics/btab280
pmc: PMC8275327
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
i426-i433Subventions
Organisme : Swiss Government's ETH Board of the Swiss Federal Institutes of Technology
Organisme : King Abdullah University of Science and Technology
Organisme : Office of Sponsored Research
ID : OSR-2017-CRG6-3438
Informations de copyright
© The Author(s) 2021. Published by Oxford University Press.
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