Dzyubenko Egor, Rozenberg Andrey, Hermann Dirk M, Faissner Andreas
Department of Cell Morphology and Molecular Neurobiology, Ruhr-University Bochum, Germany; International School of Neuroscience (IGSN), Ruhr-University Bochum, Germany.
Department of Animal Ecology, Evolution and Biodiversity, Ruhr-University Bochum, Germany.
J Neurosci Methods. 2016 Nov 1;273:149-159. doi: 10.1016/j.jneumeth.2016.09.001. Epub 2016 Sep 9.
Quantification of synapses and their morphological analysis are extensively used in network development and connectivity studies, drug screening and other areas of neuroscience. Thus, a number of quantitative approaches were introduced so far. However, most of the available methods are highly tailored to specific applications and have limitations for widespread use.
We present a new plugin for the open-source software ImageJ to provide a modifiable, high-throughput and easy to use method for synaptic puncta analysis. Our approach is based on colocalization of pre- and postsynaptic protein markers. Structurally completed glutamatergic and GABAergic synapses were identified by VGLUT1-PSD95 and VGAT-gephyrin colocalization, respectively. By combining conventional confocal microscopy with stimulated emission depletion (STED) imaging, we propose a method to quantify the number of scaffolding protein clusters, recruited to a single postsynaptic density.
In a proof-of-concept study, we reveal the differential distribution of glutamatergic and GABAergic synapse density with reference to perineuronal net (PNN) expression. Using super-resolution STED imaging, we demonstrate that postsynaptic puncta of completed synapses are composed of significantly more protein clusters, compared to uncompleted synapses.
Our Synapse Counter plugin for ImageJ offers a rapid and unbiased research tool for a broad spectrum of neuroscientists. The proposed method of synaptic protein clusters quantification exploits super-resolution imaging to provide a comprehensive approach to the analysis of postsynaptic density composition.
Our results strongly substantiate the benefits of colocalization-based synapse detection.
突触的定量分析及其形态学分析在网络发育、连接性研究、药物筛选及神经科学的其他领域中广泛应用。因此,迄今为止已引入了许多定量方法。然而,大多数现有方法都是高度针对特定应用定制的,并且在广泛应用方面存在局限性。
我们为开源软件ImageJ提供了一个新插件,以提供一种可修改、高通量且易于使用的突触小点分析方法。我们的方法基于突触前和突触后蛋白质标记物的共定位。分别通过VGLUT1-PSD95和VGAT-桥连蛋白的共定位来识别结构完整的谷氨酸能和γ-氨基丁酸能突触。通过将传统共聚焦显微镜与受激发射损耗(STED)成像相结合,我们提出了一种量化募集到单个突触后致密区的支架蛋白簇数量的方法。
在一项概念验证研究中,我们揭示了参照神经元周围网(PNN)表达的谷氨酸能和γ-氨基丁酸能突触密度的差异分布。使用超分辨率STED成像,我们证明与未完成的突触相比,完成的突触的突触后小点由明显更多的蛋白质簇组成。
我们为ImageJ开发的突触计数器插件为广大神经科学家提供了一种快速且无偏差的研究工具。所提出的突触蛋白簇定量方法利用超分辨率成像为突触后致密区组成分析提供了一种全面的方法。
我们的结果有力地证实了基于共定位的突触检测的益处。