A new efficient method for synaptic vesicle quantification reveals differences between medial prefrontal cortex perforated and nonperforated synapses

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Communication between neurons is mediated by the release of neurotransmitter-containing vesicles from presynaptic terminals. Quantitative characterization of synaptic vesicles can be highly valuable for understanding mechanisms underlying synaptic function and plasticity. We performed a quantitative ultrastructural analysis of cortical excitatory synapses by mean of a new, efficient method, as an alternative to three-dimensional (3D) reconstruction. Based on a hierarchical sampling strategy and unequivocal identification of the region of interest, serial sections from excitatory synapses of medial prefrontal cortex (mPFC) of six Sprague-Dawley rats were acquired with a transmission electron microscope. Unbiased estimates of total 3D volume of synaptic terminals were obtained through the Cavalieri estimator, and adequate correction factors for vesicle profile number estimation were applied for final vesicle quantification. Our analysis was based on 79 excitatory synapses, nonperforated (NPSs) and perforated (PSs) subtypes. We found that total number of docked and reserve-pool vesicles in PSs significantly exceeded that in NPSs (by, respectively, 77% and 78%). These differences were found to be related to changes in size between the two subtypes (active zone area by 86%; bouton volume by 105%) rather than to postsynaptic density shape. Positive significant correlations were found between number of docked and reserve-pool vesicles, active zone area and docked vesicles, and bouton volume and reserve pool vesicles. Our method confirmed the large size of mPFC PSs and a linear correlation between presynaptic features of typical hippocampal synapses. Moreover, a greater number of docked vesicles in PSs may promote a high synaptic strength of these synapses. J. Comp. Neurol. 522:284-297, 2014. © 2013 Wiley Periodicals, Inc.
Original languageEnglish
JournalJournal of Comparative Neurology
Volume522
Issue2
Pages (from-to)284-97
Number of pages14
ISSN0021-9967
DOIs
Publication statusPublished - Feb 2014

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