| First Author | Dzyubenko E | Year | 2016 |
| Journal | J Neurosci Methods | Volume | 273 |
| Pages | 149-159 | PubMed ID | 27615741 |
| Mgi Jnum | J:263381 | Mgi Id | MGI:6189263 |
| Doi | 10.1016/j.jneumeth.2016.09.001 | Citation | Dzyubenko E, et al. (2016) Colocalization of synapse marker proteins evaluated by STED-microscopy reveals patterns of neuronal synapse distribution in vitro. J Neurosci Methods 273:149-159 |
| abstractText | BACKGROUND: 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. NEW METHOD: 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. RESULTS: 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. COMPARISON WITH EXISTING METHODS: 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. CONCLUSIONS: Our results strongly substantiate the benefits of colocalization-based synapse detection. |
