Probing microdomain Ca2+ activity and synaptic transmission with a node-based tripartite synapse model

Abstract

Astrocytic fine processes are the most minor structures of astrocytes but host much of the Ca2+ activity. These localized Ca2+ signals spatially restricted to microdomains are crucial for information processing and synaptic transmission. However, the mechanistic link between astrocytic nanoscale processes and microdomain Ca2+ activity remains hazily understood because of the technical difficulties in accessing this structurally unresolved region. In this study, we used computational models to disentangle the intricate relations of morphology and local Ca2+ dynamics involved in astrocytic fine processes. We aimed to answer: 1) how nano-morphology affects local Ca2+ activity and synaptic transmission, 2) and how fine processes affect Ca2+ activity of large process they connect. To address these issues, we undertook the following two computational modeling: 1) we integrated the in vivo astrocyte morphological data from a recent study performed with super-resolution microscopy that discriminates sub-compartments of various shapes, referred to as nodes and shafts to a classic IP3R-mediated Ca2+ signaling framework describing the intracellular Ca2+ dynamics, 2) we proposed a node-based tripartite synapse model linking with astrocytic morphology to predict the effect of structural deficits of astrocytes on synaptic transmission. Extensive simulations provided us with several biological insights: 1) the width of nodes and shafts could strongly influence the spatiotemporal variability of Ca2+ signals properties but what indeed determined the Ca2+ activity was the width ratio between nodes and shafts, 2) the connectivity of nodes to larger processes markedly shaped the Ca2+ signal of the parent process rather than nodes morphology itself, 3) the morphological changes of astrocytic part might potentially induce the abnormality of synaptic transmission by affecting the level of glutamate at tripartite synapses. Taken together, this comprehensive model which integrated theoretical computation and in vivo morphological data highlights the role of the nanomorphology of astrocytes in signal transmission and its possible mechanisms related to pathological conditions.

Characterisation of ligand gating, ion conduction and the ion selectivity mechanism in the endo-lysosomal ion channel hTPC2

“…The CHARMM36m force field was used for the protein, ions other than Ca 2+ , and the lipids [36] . For the Ca 2+ ions, the multi-site model developed by Zhang et al was used, which has recently been shown by us and other groups to reliably model Ca 2+ currents in a range of ion channels [37][38][39][40][41] Hydrogen mass re-partitioning (HMR) of the system was used in the simulations with Na + ions such that 4-fs time steps could be employed [42] . However, 4-fs time steps are incompatible with the multi-site Ca 2+ model, and consequently, a standard 2-fs time step was used in all simulations with Ca 2+ , retaining HMR for consistency.…”

“…The CHARMM36m force field was used for the protein, ions other than Ca 2+ , and the lipids [36] . For the Ca 2+ ions, the multi-site model developed by Zhang et al was used, which has recently been shown by us and other groups to reliably model Ca 2+ currents in a range of ion channels [37–41]…”

The role of calcium dynamics with amyloid beta on neuron-astrocyte coupling

“…The system appears to be inactive based on the principal variable rates. By initializing both variables to zero, experimental measurements have been made for Ca 2+ and h. To duplicate the model, IP 3 levels have been limited at 0.16µM (that is equal to IP * 3 ) until Ca 2+ and h have been balanced [36][37][38].…”

Slow ion concentration oscillations and multiple states in neuron–glia interaction—insights gained from reduced mathematical models

“…Many of these models are characterised by highly detailed neuron models and glial models of much lower biophysical detail ( Kager et al, 2000 ; Kager et al, 2002 ; Kager et al, 2007 ; Fröhlich et al, 2006 ; Cressman et al, 2009 ; Florence et al, 2009 ; Ullah and Schiff, 2010 ), such that the models can assess qualitative effects of glial potassium buffering but cannot provide insights into how individual glial actors operate during potassium clearance. Recent scientific and technological advances have stimulated the emergence of more complex neuron–glia models (e.g., Sibille et al, 2015 ; Du et al, 2016 ; Depannemaecker et al, 2022 ; Du et al, 2022 ; Liu et al, 2023 ), which are capable of reproducing and predicting quantitatively a wide range of phenomena. However, their complexity makes it challenging to pinpoint which part of the model is responsible for a certain type of behaviour.…”