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Efficient and Accurate Synapse Detection With Selective Structured Illumination Microscopy on the Putative Regions of Interest of Ultrathin Serial Sections

Title
Efficient and Accurate Synapse Detection With Selective Structured Illumination Microscopy on the Putative Regions of Interest of Ultrathin Serial Sections
Author(s)
Kim, Gyeong TaeBahn, SangkyuKim, NariChoi, Joon HoKim, Jinseop S.Rah, Jong-Cheol
Issued Date
2021-11
Citation
Frontiers in Neuroanatomy, v.15
Type
Article
Author Keywords
structured illumination microscopyarray tomographysynapse locationposterior medial nucleusbarrel cortex
Keywords
RESOLUTIONCEREBRAL-CORTEXORGANIZATION
ISSN
1662-5129
Abstract
Critical determinants of synaptic functions include subcellular locations, input sources, and specific molecular characteristics. However, there is not yet a reliable and efficient method that can detect synapses. Electron microscopy is a gold-standard method to detect synapses due to its exceedingly high spatial resolution. However, it requires laborious and time-consuming sample preparation and lengthy imaging time with limited labeling methods. Recent advances in various fluorescence microscopy methods have highlighted fluorescence microscopy as a substitute for electron microscopy in reliable synapse detection in a large volume of neural circuits. In particular, array tomography has been verified as a useful tool for neural circuit reconstruction. To further improve array tomography, we developed a novel imaging method, called "structured illumination microscopy on the putative region of interest on ultrathin sections", which enables efficient and accurate detection of synapses-of-interest. Briefly, based on low-magnification conventional fluorescence microscopy images, synapse candidacy was determined. Subsequently, the coordinates of the regions with candidate synapses were imaged using super-resolution structured illumination microscopy. Using this system, synapses from the high-order thalamic nucleus, the posterior medial nucleus in the barrel cortex were rapidly and accurately imaged. © 2021 Kim, Bahn, Kim, Choi, Kim and Rah. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
URI
http://hdl.handle.net/20.500.11750/15985
DOI
10.3389/fnana.2021.759816
Publisher
Frontiers Media
Files in This Item:
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