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突触簇优先由具有大再循环池大小的突触形成。

Synapse clusters are preferentially formed by synapses with large recycling pool sizes.

机构信息

Department of Psychiatry and Psychotherapy, University of Erlangen-Nuremberg, Erlangen, Germany.

出版信息

PLoS One. 2010 Oct 20;5(10):e13514. doi: 10.1371/journal.pone.0013514.

DOI:10.1371/journal.pone.0013514
PMID:20976002
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2958124/
Abstract

Synapses are distributed heterogeneously in neural networks. The relationship between the spatial arrangement of synapses and an individual synapse's structural and functional features remains to be elucidated. Here, we examined the influence of the number of adjacent synapses on individual synaptic recycling pool sizes. When measuring the discharge of the styryl dye FM1-43 from electrically stimulated synapses in rat hippocampal tissue cultures, a strong positive correlation between the number of neighbouring synapses and recycling vesicle pool sizes was observed. Accordingly, vesicle-rich synapses were found to preferentially reside next to neighbours with large recycling pool sizes. Although these synapses with large recycling pool sizes were rare, they were densely arranged and thus exhibited a high amount of release per volume. To consolidate these findings, functional terminals were marked by live-cell antibody staining with anti-synaptotagmin-1-cypHer or overexpression of synaptopHluorin. Analysis of synapse distributions in these systems confirmed the results obtained with FM 1-43. Our findings support the idea that clustering of synapses with large recycling pool sizes is a distinct developmental feature of newly formed neural networks and may contribute to functional plasticity.

摘要

突触在神经网络中呈异质分布。突触的空间排列与单个突触的结构和功能特征之间的关系仍有待阐明。在这里,我们研究了相邻突触数量对单个突触再循环池大小的影响。当测量大鼠海马组织培养物中电刺激突触释放的芘基染料 FM1-43 时,观察到相邻突触数量与再循环囊泡池大小之间存在强烈的正相关。因此,富含囊泡的突触优先存在于具有大再循环池大小的相邻突触旁边。尽管这些具有大再循环池大小的突触很少,但它们排列密集,因此每单位体积释放的量很高。为了证实这些发现,用抗突触结合蛋白 1-cypHer 或突触荧光素的活细胞抗体染色或过表达突触荧光素来标记功能末端。在这些系统中分析突触分布证实了用 FM1-43 获得的结果。我们的发现支持这样一种观点,即具有大再循环池大小的突触聚类是新形成的神经网络的一个独特发育特征,并可能有助于功能可塑性。

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