Transition of the presynaptic vesicle cluster from a compact to dispersed organization during long-term potentiation
Abstract
Long-term potentiation (LTP) is a lasting form of synaptic plasticity that can persist for hours or even days. It is associated with structural changes in both the presynaptic terminal and the postsynaptic spine. Presynaptically, the number and distribution of synaptic vesicles (SVs) affect synaptic efficacy. How the functional changes in synaptic efficacy after the induction of LTP are mirrored by identifiable structural alterations in the SV cluster is not fully understood. Here, we interrogated presynaptic terminals in 3DEM reconstructions from CA3-to-CA1 synapses in stratum radiatum of adult rats that had undergone control stimulation, or theta-burst stimulation to produce LTP. An increase was observed in the dispersion of SVs at 2 h after LTP induction. This dispersion resulted in greater distances between neighboring SVs, longer distances to the center of the SV cluster, and an increased variance in SV position relative to the cluster’s center. Analysis of the SV clusters distinguished terminals that were potentiated based on their degree of dispersion, distances to neighboring SVs, and SV cluster densities. Our analysis demonstrates that the density of SVs is a property independent of the bouton or SV cluster volumes and is subject to strong regulation. Comparing the spatial distribution of SVs to randomized distributions revealed increased SV mobility following LTP induction. Moreover, theoretical calculations informed by the measured SV cluster densities suggest an increase in the mobility of SVs within the cluster during LTP. These findings provide evidence that the SV cluster undergoes a transition from tight to dispersed, making SVs more mobile during LTP.
Article Details
Journal Info
Proceedings of the National Academy of Sciences
National Academy of Sciences
Authors (6)
Guadalupe C. Garcia
Computational Neurobiology Laboratory
Thomas M. Bartol
Computational Neurobiology Laboratory
Lyndsey M. Kirk
Department of Neuroscience
Priyal Badala
Computational Neurobiology Laboratory
Kristen M. Harris
Department of Neuroscience, Center for Learning and Memory, The University of Texas at Austin
Terrence J. Sejnowski
Computational Neurobiology Laboratory