Mitochondria morphometry in 3D datasets obtained from mouse brains with serial block-face scanning electron microscopy

Abstract

The dysfunction of mitochondria is linked with many diseases. In the nervous system, evidence of their implication in neurodegenerative disease is growing. Mitochondria health is assessed by their impact on cellular metabolism but alterations in their morphologies and locations in the cells can also be markers of dysfunctions. Light microscopy techniques allow us to look at mitochondria in vivo in cells or tissue. But in the case of the nervous system, in order to assess the precise location of mitochondria in different cell types and neuronal compartments (cell bodies, dendrites or axons), electron microscopy is required. While the percentage of volume occupied by mitochondria can be assessed on 2D images, alterations in length, branching, and interactions with other organelles require three-dimensional (3D) segmentation of mitochondria in volumes imaged at ultrastructural level. Nowadays three-dimensional volume electron microscopy (vEM) imaging techniques such as serial block face scanning electron microscopy (SBF-SEM) enable us to image 3D volumes of tissue at ultrastructural level and can be done routinely. Segmentation of all the neuropil is also successfully achieved at a large scale in the nervous system. Here, we show a workflow based on open access resources, which allows us to image, segment, and analyze mitochondria in 3D volumes of regions of interest in the mouse brain. Taking advantage of recent developments, e.g., pre-trained models for mitochondria, we speed up the reconstruction and analysis. We also critically assess the impact on the results of the different reconstruction methods chosen and the level of manual corrections invested.

Keywords: 3D reconstruction of mitochondria; Automatic segmentation; Electron microscopy; MIB; Mitochondria volume; Morphometry; Mouse brain mitochondria; SBF-SEM.