Computational modeling of trans-synaptic nanocolumns, a modulator of synaptic transmission

Li, Xiaoting and Hémond, Gabriel and Godin, Antoine G. and Doyon, Nicolas (2022) Computational modeling of trans-synaptic nanocolumns, a modulator of synaptic transmission. Frontiers in Computational Neuroscience, 16. ISSN 1662-5188

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Abstract

Understanding synaptic transmission is of crucial importance in neuroscience. The spatial organization of receptors, vesicle release properties and neurotransmitter molecule diffusion can strongly influence features of synaptic currents. Newly discovered structures coined trans-synaptic nanocolumns were shown to align presynaptic vesicles release sites and postsynaptic receptors. However, how these structures, spanning a few tens of nanometers, shape synaptic signaling remains little understood. Given the difficulty to probe submicroscopic structures experimentally, computer modeling is a useful approach to investigate the possible functional impacts and role of nanocolumns. In our in silico model, as has been experimentally observed, a nanocolumn is characterized by a tight distribution of postsynaptic receptors aligned with the presynaptic vesicle release site and by the presence of trans-synaptic molecules which can modulate neurotransmitter molecule diffusion. In this work, we found that nanocolumns can play an important role in reinforcing synaptic current mostly when the presynaptic vesicle contains a small number of neurotransmitter molecules. Our work proposes a new methodology to investigate in silico how the existence of trans-synaptic nanocolumns, the nanometric organization of the synapse and the lateral diffusion of receptors shape the features of the synaptic current such as its amplitude and kinetics.

Item Type: Article
Subjects: Asian STM > Medical Science
Depositing User: Managing Editor
Date Deposited: 27 Mar 2023 06:00
Last Modified: 13 Sep 2023 08:09
URI: http://journal.send2sub.com/id/eprint/1072

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