PT  - JOURNAL ARTICLE
AU  - Rachel Mendelsohn
AU  - Guadalupe C. Garcia
AU  - Thomas M. Bartol
AU  - Christopher T. Lee
AU  - P. Khandelwal
AU  - Emily Liu
AU  - Donald J. Spencer
AU  - Adam Husar
AU  - Eric A. Bushong
AU  - Sebastien Phan
AU  - Guy Perkins
AU  - Mark H. Ellisman
AU  - Alexander Skupin
AU  - Terrence J. Sejnowski
AU  - Padmini Rangamani
TI  - Morphological principles of neuronal mitochondria
AID  - 10.1101/2021.03.15.435547
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.03.15.435547
4099  - http://biorxiv.org/content/early/2021/03/18/2021.03.15.435547.short
4100  - http://biorxiv.org/content/early/2021/03/18/2021.03.15.435547.full
AB  - In the highly dynamic metabolic landscape of a neuron, mitochondrial membrane architectures can provide critical insight into the unique energy balance of the cell. Current theoretical calculations of functional outputs like ATP and heat often represent mitochondria as idealized geometries and therefore can miscalculate the metabolic fluxes. To analyze mitochondrial morphology in neurons of mouse cerebellum neuropil, 3D tracings of complete synaptic and axonal mitochondria were constructed using a database of serial TEM tomography images and converted to watertight meshes with minimal distortion of the original microscopy volumes with a granularity of 1.6 nanometer isotropic voxels. The resulting in silico representations were subsequently quantified by differential geometry methods in terms of the mean and Gaussian curvatures, surface areas, volumes, and membrane motifs, all of which can alter the metabolic output of the organelle. Finally, we identify structural motifs that are present across this population of mitochondria; observations which may contribute to future modeling studies of mitochondrial physiology and metabolism in neurons.Competing Interest StatementThe authors have declared no competing interest.