Semi-automated navigation for efficient targeting of electron tomography to regions of interest in volume correlative light and electron microscopy

Abstract

Electron microscopy is essential for the quantitative study of synaptic ultrastructure. At present, the correlation of functional and structural properties of the same synapse is extremely challenging. We introduce a novel integrated workflow designed to simplify sample navigation across spatial scales, allowing the identification of individual synapses from optical microscopy mouse brain image stacks that can be targeted for analysis using electron tomography imaging. We developed a software which has a function to register multimodal images using a novel segmentation-based image registration algorithm as well as a function to visualize all the registration results. Using our newly designed software we streamline mapping of high-resolution optical imaging onto reference maps using blood vessels as endogenous fiducial marks. Further we demonstrate significant improvements on the ultramicrotomy stage of volume Correlative Light and Electron Microscopy (vCLEM) workflows, providing real time guidance to targeted trimming to match previously acquired Regions Of Interest (ROIs), and reliable estimates of cutting depth relative to ROI, based on fluorescence imaging of TEM ready ultrathin sections. Using this workflow, we successfully targeted TEM tomography to the proximal axonal region containing the Axon Initial Segment identified using fluorescent light microscopy.