SEQUIN multiscale imaging of mammalian central synapses reveals loss of synaptic microconnectivity resulting from diffuse traumatic brain injury

Abstract

The complex microconnectivity of the mammalian brain underlies its computational abilities, and its vulnerability to injury and disease. It has been challenging to illuminate the features of this synaptic network due in part to the small size and exceptionally dense packing of its elements. Here we describe a rapid and accessible super-resolution imaging and image analysis workflow--SEQUIN--that identifies, quantifies, and characterizes central synapses in animal models and in humans, enabling automated volumetric imaging of mesoscale synaptic networks without the laborious production of large histological arrays. Using SEQUIN, we identify delayed cortical synapse loss resulting from diffuse traumatic brain injury. Similar synapse loss is observed in an Alzheimer disease model, where SEQUIN mesoscale mapping of excitatory synapses across the hippocampus identifies region-specific synaptic vulnerability to neurodegeneration. These results establish a novel, easily implemented and robust nano-to-mesoscale synapse quantification and molecular characterization method. They furthermore identify a mechanistic link--synaptopathy--between Alzheimer neurodegeneration and its best-established epigenetic risk factor, brain trauma.