Simulation of calcium signaling in fine astrocytic processes: Effect of spatial properties on spontaneous activity

Abstract

Astrocytes, a glial cell type of the central nervous system, have emerged as detectors and regulators of neuronal information processing. Astrocyte excitability resides in transient variations of free cytosolic calcium concentration over a range of temporal and spatial scales, from sub-microdomains to waves propagating throughout the cell. Despite extensive experimental approaches, it is not clear how these signals are transmitted to and integrated within an astrocyte. The localization of the main molecular actors and the geometry of the system, including the spatial organization of calcium channels IP 3 R , are deemed essential. However, as most calcium signals occur in astrocytic ramifications that are too fine to be resolved by conventional light microscopy, most of those spatial data are unknown and computational modeling remains the only methodology to study this issue. Here, we propose an IP 3 R -mediated calcium signaling model for dynamics in such small sub-cellular volumes. To account for the expected stochasticity and low copy numbers, our model is both spatially explicit and particle-based. Extensive simulations show that spontaneous calcium signals arise in the model via the interplay between excitability and stochasticity. The model reproduces the main forms of calcium signals and indicates that their frequency crucially depends on the spatial organization of the IP 3 R channels. Importantly, we show that two processes expressing exactly the same calcium channels can display different types of calcium signals depending on the spatial organization of the channels. Our model with realistic process volume and calcium concentrations successfully reproduces spontaneous calcium signals that we measured in calcium micro-domains with confocal microscopy and predicts that local variations of calcium indicators might contribute to the diversity of calcium signals observed in astrocytes. To our knowledge, this model is the first model suited to investigate calcium dynamics in fine astrocytic processes and to propose plausible mechanisms responsible for their variability.

Control of Ca2+signals by astrocyte nanoscale morphology at tripartite synapses

“…GECIs however present a major drawback: as they are genetically encoded, their exact concentration and distribution within the cell is unknown and thus generally not reported. Our results, in agreement with previous reports [20,48,49], highlight the modulation of Ca 2+ signals by Ca 2+ buffers such as GECIs.…”

“…increased when d shaft decreased. Consistently with previous reports[20,30,31], free Ca 2+ signals Overall, our results suggest that the use of Ca 2+ indicators, and more generally Ca 2+ buffering, is associated with an increased Ca 2+ peak duration and a decreased peak probability and amplitude (Fig 6D). Note that, even though free Ca 2+ signals strongly differ from Ca-GCaMP signals, Ca-GCaMP signals can still provide relevant information on the qualitative effect of shaft width on Ca 2+ dynamics, such as the increased peak probability, duration and amplitude when d shaft decreases.…”

“…The same strategy as developed by Denizot et al [20] Ca] b . Peak duration corresponds to the time between peak initiation and peak termination.…”

Nicotine induces morphological and functional changes in astrocytes via nicotinic receptor activity

“…In addition to long proximal processes radiating from the cell soma, astrocytes contain fine processes branching out from these proximal processes and from the edge of the cell soma (Denizot, Arizono, Nagerl, Soula, & Berry, 2019). These fine processes are in the range of few hundreds of nanometers to a few micrometers in length (Derouiche, Haseleu, & Korf, 2015).…”

Simulation of Astrocytic Calcium Dynamics in Lattice Light Sheet Microscopy Images

“…We present a framework to simulate realistic astrocytic calcium signals in sequences of 2D and 3D LLSM images. To reproduce the spatio-temporal diversity of calcium signals, we adapt at the macroscale the kinetic model described in [18] which represents calcium dynamics at the nanoscale. For the background, we use real astrocytic processes and we recreate experimental conditions of LLSM acquisitions (e.g., noise and blurring).…”