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海马星形胶质细胞结构域的特征及其与兴奋性和抑制性神经元的空间关系。

Features of hippocampal astrocytic domains and their spatial relation to excitatory and inhibitory neurons.

机构信息

Edmond and Lily Safra Center for Brain Sciences (ELSC), The Hebrew University of Jerusalem, Jerusalem, Israel.

ELSC Vector Core Facility, The Hebrew University of Jerusalem, Jerusalem, Israel.

出版信息

Glia. 2021 Oct;69(10):2378-2390. doi: 10.1002/glia.24044. Epub 2021 Jun 12.

Abstract

The mounting evidence for the involvement of astrocytes in neuronal circuits function and behavior stands in stark contrast to the lack of detailed anatomical description of these cells and the neurons in their domains. To fill this void, we imaged >30,000 astrocytes in hippocampi made transparent by CLARITY, and determined the elaborate structure, distribution, and neuronal content of astrocytic domains. First, we characterized the spatial distribution of >19,000 astrocytes across CA1 lamina, and analyzed the morphology of thousands of reconstructed domains. We then determined the excitatory somatic content of CA1 astrocytes, and measured the distance between inhibitory neuronal somata to the nearest astrocyte soma. We find that on average, there are almost 14 pyramidal neurons per domain in the CA1, increasing toward the pyramidal layer midline, compared to only five excitatory neurons per domain in the amygdala. Finally, we discovered that somatostatin neurons are found in close proximity to astrocytes, compared to parvalbumin and VIP inhibitory neurons. This work provides a comprehensive large-scale quantitative foundation for studying neuron-astrocyte interactions.

摘要

越来越多的证据表明星形胶质细胞参与神经元回路的功能和行为,但与之形成鲜明对比的是,这些细胞及其所在区域的神经元的详细解剖结构描述却非常缺乏。为了填补这一空白,我们对通过 CLARITY 技术透明化的海马体中的超过 30000 个星形胶质细胞进行了成像,并确定了星形胶质细胞结构域的精细结构、分布和神经元含量。首先,我们描述了跨越 CA1 层的超过 19000 个星形胶质细胞的空间分布,并分析了数千个重建结构域的形态。然后,我们确定了 CA1 星形胶质细胞的兴奋性胞体含量,并测量了抑制性神经元胞体到最近的星形胶质细胞胞体的距离。我们发现,与杏仁核中每个结构域平均有 5 个兴奋性神经元相比,CA1 中的每个结构域平均有近 14 个锥体神经元,并且这种数量朝着锥体层中线增加。最后,我们发现与 VIP 和 parvalbumin 抑制性神经元相比,生长抑素神经元与星形胶质细胞密切相关。这项工作为研究神经元-星形胶质细胞相互作用提供了全面的大规模定量基础。

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