A workflow for semi-automated volume correlative light microscopy and transmission electron tomography

Abstract

Volume Correlative Light and Electron Microscopy (vCLEM) is a powerful method for assessing the ultrastructure of molecularly defined subcellular domains. A central challenge in vCLEM has been the efficient navigation of Regions of Interest (ROIs) across multimodal and multiscale imaging datasets. We developed two key tools to overcome this challenge. First, we developed a multimodal image registration tool (SegReg) that utilizes segmentation of common objects across modalities and uses a Graphical Processing Unit (GPU) for registration of imaging datasets in two and three dimensions. Secondly, we developed a dedicated image viewer to visualize multimodal image registration in three dimensions (NavROI). Here, we demonstrate the integrated use of SegReg and NavROI to navigate large mouse tissue blocks with preserved fluorescent signals to allow selective targeting for TEM tomography of ROIs containing synapses and the cisternal organelle on the proximal region of the axon of a selected pyramidal neuron. By providing real time guidance to precise X-Y trimming of selected ROIs, reliable estimates of cutting depth relative to ROIs and a clear visual navigation of multimodal and multiscale images, our integrated workflow significantly improves the efficiency and accessibility of vCLEM analysis.