| Literature DB >> 34608995 |
Rachel Mendelsohn1, Guadalupe C Garcia1, Thomas M Bartol1, Christopher T Lee2, Priya Khandelwal1, Emily Liu1, Donald J Spencer1, Adam Husar1, Eric A Bushong3, Sebastien Phan3, Guy Perkins3, Mark H Ellisman3, Alexander Skupin3,4, Terrence J Sejnowski1,5, Padmini Rangamani2.
Abstract
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 adenosine triphosphate 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 transmission electron microscopy (TEM) tomography images and converted to watertight meshes with minimal distortion of the original microscopy volumes with a granularity of 1.64 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 present across this population of mitochondria, which may contribute to future modeling studies of mitochondrial physiology and metabolism in neurons.Entities:
Keywords: EM tomography; energetics; mitochondria; morphology; neuronal
Mesh:
Year: 2021 PMID: 34608995 PMCID: PMC8831469 DOI: 10.1002/cne.25254
Source DB: PubMed Journal: J Comp Neurol ISSN: 0021-9967 Impact factor: 3.215