| Literature DB >> 32392471 |
Andrew D Sauerbeck1, Mihika Gangolli2, Sydney J Reitz1, Maverick H Salyards1, Samuel H Kim1, Christopher Hemingway3, Maud Gratuze1, Tejaswi Makkapati1, Martin Kerschensteiner4, David M Holtzman1, David L Brody5, Terrance T Kummer6.
Abstract
The brain's complex microconnectivity underlies its computational abilities and vulnerability to injury and disease. It has been challenging to illuminate the features of this synaptic network due to the small size and dense packing of its elements. Here, we describe a rapid, accessible super-resolution imaging and analysis workflow-SEQUIN-that quantifies central synapses in human tissue and animal models, characterizes their nanostructural and molecular features, and enables volumetric imaging of mesoscale synaptic networks without the production of large histological arrays. Using SEQUIN, we identify cortical synapse loss resulting from diffuse traumatic brain injury, a highly prevalent connectional disorder. Similar synapse loss is observed in three murine models of Alzheimer-related neurodegeneration, where SEQUIN mesoscale mapping identifies regional synaptic vulnerability. These results establish an easily implemented and robust nano-to-mesoscale synapse quantification and characterization method. They furthermore identify a shared mechanism-synaptopathy-between Alzheimer neurodegeneration and its best-established epigenetic risk factor, brain trauma.Entities:
Keywords: Alzheimer’s disease; SEQUIN; TBI; imaging; microconnectivity; neurodegeneration; super-resolution microscopy; synapse; synaptome; traumatic brain injury
Mesh:
Year: 2020 PMID: 32392471 PMCID: PMC7381374 DOI: 10.1016/j.neuron.2020.04.012
Source DB: PubMed Journal: Neuron ISSN: 0896-6273 Impact factor: 17.173