creating-structurally-realistic-finite-element-geometric-model

Creating a Structurally Realistic Finite Element Geometric Model of a Cardiomyocyte to Study the Role of Cellular Architecture in Cardiomyocyte Systems Biology

With the advent of three-dimensional (3D) imaging technologies such as electron tomography, serial-block-face scanning electron microscopy and confocal ...

University of Melbourne

Diabetic cardiomyopathy is accompanied by metabolic and ultrastructural alterations, but the impact of the structural changes on metabolism itself is yet to be determined. Morphometric analysis of mitochondrial shape and spatial organization within transverse sections of cardiomyocytes from control and streptozotocin-induced type I diabetic Sprague-Dawley rats revealed that mitochondria are 20% smaller in size while their spatial density increases by 53% in diabetic cells relative to control myocytes. Diabetic cells formed larger clusters of mitochondria (60% more mitochondria per cluster) and the effective surface-to-volume ratio of these clusters increased by 22.5%. Using a biophysical computational model we found that this increase can have a moderate compensatory effect by increasing the availability of ATP in the cytosol when ATP synthesis within the mitochondrial matrix is compromised.

Changes in mitochondrial morphology and organization can enhance energy supply from mitochondrial oxidative phosphorylation in diabetic cardiomyopathy.

This paper presents a new algorithm to automatically segment the myofibrils, mitochondria and nuclei within single adult cardiac cells that are part of a large serial-block-face scanning electron microscopy (SBF-SEM) dataset. The algorithm only requires a set of manually drawn contours that roughly demarcate the cell boundary at routine slice intervals (every 50th, for example). The algorithm correctly classified pixels within the single cell with 97% accuracy when compared to manual segmentations. One entire cell and the partial volumes of two cells were segmented. Analysis of segmentations within these cells showed that myofibrils and mitochondria occupied 47.5% and 51.6% on average respectively, while the nuclei occupy 0.7% of the cell for which the entire volume was captured in the SBF-SEM dataset. Mitochondria clustering increased at the periphery of the nucleus region and branching points of the cardiac cell. The segmentations also showed high area fraction of mitochondria (up to 70% of the 2D image slice) in the sub-sarcolemmal region, whilst it was closer to 50% in the intermyofibrillar space. We finally demonstrate that our segmentations can be turned into 3D finite element meshes for cardiac cell computational physiology studies. We offer our large dataset and MATLAB implementation of the algorithm for research use at www.github.com/CellSMB/sbfsem-cardiac-cell-segmenter/. We anticipate that this timely tool will be of use to cardiac computational and experimental physiologists alike who study cardiac ultrastructure and its role in heart function.

Shouryadipta Ghosh

Cell Structure and Mechanobiology Group,
Systems Biology Laboratory,
Melbourne School of Engineering,
Department of Biomedical Engineering,
Systems Biology Laboratory, Melbourne School of Engineering

University of Melbourne

Creating a Structurally Realistic Finite Element Geometric Model of a Cardiomyocyte to Study the Role of Cellular Architecture in Cardiomyocyte Systems Biology

Shouryadipta Ghosh

Cell Structure and Mechanobiology Group,Systems Biology Laboratory,Melbourne School of Engineering,Department of Biomedical Engineering,Systems Biology Laboratory, Melbourne School of Engineering

University of Melbourne

Creating a Structurally Realistic Finite Element Geometric Model of a Cardiomyocyte to Study the Role of Cellular Architecture in Cardiomyocyte Systems Biology

Cell Structure and Mechanobiology Group,
Systems Biology Laboratory,
Melbourne School of Engineering,
Department of Biomedical Engineering,
Systems Biology Laboratory, Melbourne School of Engineering