Metaball skinning of synthetic astroglial morphologies into realistic mesh models for visual analytics and in silico simulations.

Marwan Abdellah,Alessandro Foni,Daniel Keller,Samuel Lapere,Nadir Román Guerrero,Eleftherios Zisis,Felix Schürmann,Jay S Coggan,Henry Markram

doi:10.1093/bioinformatics/btab280

Abstract

MotivationAstrocytes, 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.ResultsWe 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.Availability and implementationOur 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 informationSupplementary data are available at Bioinformatics online.

Highlights

Most mammalian brains are comprised of two broad categories of cell types, neurons and glia, each of which contains a variety of constituent subtypes
We present a robust algorithm for skinning astrocytic morphologies into high fidelity polygonal mesh models based on metaballs in Blender
The pipeline was tested with 5000 astrocytic morphologies that were synthesized with a recent NGV multi-populated circuit

Summary

Introduction

Most mammalian brains are comprised of two broad categories of cell types, neurons and glia, each of which contains a variety of constituent subtypes. Much evidence points to a critical role for astrocytes in the normal formation of developing neuronal circuits as well as their function in maturity (Khakh and Sofroniew, 2015). Brain astrocytes are involved in modulating synaptic activity, integrating intracellular and extracellular signals and responding to or mediating pathological states, including numerous neurodegenerative disorders such as Parkinson’s and Alzheimer’s diseases (Rossi and Volterra, 2009). There is clear evidence for glial contributions to almost every conceivable brain function or disorder. Almost none of the multiple aspects of neuro-glia signaling briefly described here, as well as many others not mentioned, can be understood at a macroscopic or whole-cell scale.

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