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Disentangling astroglial physiology with a realistic cell model in silico.

ABSTRACT: Electrically non-excitable astroglia take up neurotransmitters, buffer extracellular K+ and generate Ca2+ signals that release molecular regulators of neural circuitry. The underlying machinery remains enigmatic, mainly because the sponge-like astrocyte morphology has been difficult to access experimentally or explore theoretically. Here, we systematically incorporate multi-scale, tri-dimensional astroglial architecture into a realistic multi-compartmental cell model, which we constrain by empirical tests and integrate into the NEURON computational biophysical environment. This approach is implemented as a flexible astrocyte-model builder ASTRO. As a proof-of-concept, we explore an in silico astrocyte to evaluate basic cell physiology features inaccessible experimentally. Our simulations suggest that currents generated by glutamate transporters or K+ channels have negligible distant effects on membrane voltage and that individual astrocytes can successfully handle extracellular K+ hotspots. We show how intracellular Ca2+ buffers affect Ca2+ waves and why the classical Ca2+ sparks-and-puffs mechanism is theoretically compatible with common readouts of astroglial Ca2+ imaging.

SUBMITTER: Savtchenko LP

PROVIDER: S-EPMC6120909 | biostudies-other | 2018 Sep

REPOSITORIES: biostudies-other

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Disentangling astroglial physiology with a realistic cell model in silico.

Savtchenko Leonid P LP Bard Lucie L Jensen Thomas P TP Reynolds James P JP Kraev Igor I Medvedev Nikolay N Stewart Michael G MG Henneberger Christian C Rusakov Dmitri A DA

Nature communications 20180903 1

Electrically non-excitable astroglia take up neurotransmitters, buffer extracellular K<sup>+</sup> and generate Ca<sup>2+</sup> signals that release molecular regulators of neural circuitry. The underlying machinery remains enigmatic, mainly because the sponge-like astrocyte morphology has been difficult to access experimentally or explore theoretically. Here, we systematically incorporate multi-scale, tri-dimensional astroglial architecture into a realistic multi-compartmental cell model, which ...[more]

PMID: 30177844

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Project description: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.

Project description:Neurodegeneration in Parkinson's disease (PD) affects mainly dopaminergic neurons in the substantia nigra, where age-related, increasing percentages of cells lose detectable respiratory activity associated with depletion of intact mitochondrial DNA (mtDNA). Replenishment of mtDNA might improve neuronal bioenergetic function and prevent further cell death. We developed a technology ("ProtoFection") that uses recombinant human mitochondrial transcription factor A (TFAM) engineered with an N-terminal protein transduction domain (PTD) followed by the SOD2 mitochondrial localization signal (MLS) to deliver mtDNA cargo to the mitochondria of living cells. MTD-TFAM (MTD = PTD + MLS = "mitochondrial transduction domain") binds mtDNA and rapidly transports it across plasma membranes to mitochondria. For therapeutic proof-of-principle we tested ProtoFection technology in Parkinson's disease cybrid cells, using mtDNA generated from commercially available human genomic DNA (gDNA; Roche). Nine to 11 weeks after single exposures to MTD-TFAM + mtDNA complex, PD cybrid cells with impaired respiration and reduced mtDNA genes increased their mtDNA gene copy numbers up to 24-fold, mtDNA-derived RNAs up to 35-fold, TFAM and ETC proteins, cell respiration, and mitochondrial movement velocities. Cybrid cells with no or minimal basal mitochondrial impairments showed reduced or no responses to treatment, suggesting the possibility of therapeutic selectivity. Exposure of PD but not control cybrid cells to MTD-TFAM protein alone or MTD-TFAM + mtDNA complex increased expression of PGC-1alpha, suggesting activation of mitochondrial biogenesis. ProtoFection technology for mitochondrial gene therapy holds promise for improving bioenergetic function in impaired PD neurons and needs additional development to define its pharmacodynamics and delineate its molecular mechanisms. It also is unclear whether single-donor gDNA for generating mtDNA would be a preferred therapeutic compared with the pooled gDNA used in this study.

Dataset Information

Disentangling astroglial physiology with a realistic cell model in silico.

Publications

Disentangling astroglial physiology with a realistic cell model in silico.

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