Abstract

The balance between fast synchronous and delayed asynchronous release of neurotransmitters has a major role in defining computational properties of neuronal synapses and regulation of neuronal network activity. However, how it is tuned at the single synapse level remains poorly understood. Here, using the fluorescent glutamate sensor SF-iGluSnFR, we image quantal vesicular release in tens to hundreds of individual synaptic outputs from single pyramidal cells with 4 millisecond temporal and 75 nm spatial resolution. We find that the ratio between synchronous and asynchronous synaptic vesicle exocytosis varies extensively among synapses supplied by the same axon, and that the synchronicity of release is reduced at low release probability synapses. We further demonstrate that asynchronous exocytosis sites are more widely distributed within the release area than synchronous sites. Together, our results reveal a universal relationship between the two major functional properties of synapses – the timing and the overall efficacy of neurotransmitter release.

Neurotransmitters can be released with a delay in relation to action potentials. This work demonstrates how this asynchronous release is related to overall vesicle release probability and short-term plasticity.

Details

Title
Asynchronous glutamate release is enhanced in low release efficacy synapses and dispersed across the active zone
Author
Mendonça, Philipe R. F. 1 ; Tagliatti, Erica 2 ; Langley, Helen 2 ; Kotzadimitriou, Dimitrios 2 ; Zamora-Chimal, Criseida G. 3 ; Timofeeva, Yulia 4   VIAFID ORCID Logo  ; Volynski, Kirill E. 2   VIAFID ORCID Logo 

 University College London Institute of Neurology, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201); Federal University of Minas Gerais, Department of Physiology and Biophysics, Gerais, Brazil (GRID:grid.8430.f) (ISNI:0000 0001 2181 4888) 
 University College London Institute of Neurology, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201) 
 University of Warwick, Department of Computer Science, Coventry, UK (GRID:grid.7372.1) (ISNI:0000 0000 8809 1613) 
 University College London Institute of Neurology, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201); University of Warwick, Department of Computer Science, Coventry, UK (GRID:grid.7372.1) (ISNI:0000 0000 8809 1613) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2677954546
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.