Abstract

Mitochondria are recognized as dynamic organelles, which constantly undergo morphological remodeling through fusion and fission processes. However, their geometric details including individual shape, size, and spatial distribution have not been quantitatively characterized in adult cardiomyocytes. Standard optical microscopy is unable to resolve neighboring mitochondria, which are intensely packed between myofilament bundles and narrow sub-sarcolemmal space. On the other hand, 3D reconstructs generated by serial thin-section transmission electron microscopy (EM) or EM tomography can only provide a limited field of view. We applied a novel advanced 3D electron microscopic technology, serial block-face scanning electron microscopy (SBFSEM), to adult mouse ventricular tissues, segmented mitochondria, and created geometric models of mitochondrial assembly. Substantially large volumes enclosing neighboring myocytes were imaged using SBFSEM. Subsequently, we applied spatial analysis tools using Spatstat R package to quantify organization of mitochondria. In cross-sectional slices generated from SBFSEM volumes, the boundaries of individual mitochondria were extracted and the centroid of each boundary was plotted. Analysis of the distribution of these centroids using a quadrat test of the intensity plot indicated borderline inhomogenity (p=0.053). The test was rerun after redrawing quadrats, now incorporating the location of the nucleus in the 3D stack. The results confirmed that mitochondria were clustered near the nucleus (p=0.017). The cell-wide inter-point interaction between mitochondrial centroids calculated by the L-function and the pair correlation function failed to support organized mitochondrial clustering. In summary, the study revealed the strength of the new integrated use of SBFSEM imaging and computational statistics to characterize and parameterize the spatial distribution of cellular organelles such as mitochondria that are dynamically remodeled under a physiological condition and more intensely in disease settings such as diabetic cardiomyopathy and heart failure.

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