Computational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, California, USA.
Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, California, USA.
J Comp Neurol. 2022 Apr;530(6):886-902. doi: 10.1002/cne.25254. Epub 2021 Nov 1.
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.
在神经元高度动态的代谢环境中，线粒体膜结构可以为细胞独特的能量平衡提供重要的见解。目前，对腺苷三磷酸和热量等功能输出的理论计算通常将线粒体表示为理想化的几何形状，因此可能会错误计算代谢通量。为了分析小鼠小脑神经胶质突中的神经元中线粒体的形态，使用一系列电子显微镜 (TEM) 断层摄影图像数据库构建了完整突触和轴突线粒体的 3D 轨迹，并将其转换为具有最小原始显微镜体积失真的水密网格，其粒度为 1.64 纳米各向同性体素。随后，通过微分几何方法根据平均曲率和高斯曲率、表面积、体积和膜基序对这些虚拟表示进行定量，所有这些都可以改变细胞器的代谢输出。最后，我们确定了存在于这群线粒体中的结构基序，这些基序可能有助于未来对神经元中线粒体生理学和代谢的建模研究。
