Effects of altered cellular ultrastructure on energy metabolism in diabetic cardiomyopathy: an in silico study.

Diabetic cardiomyopathy is a leading cause of heart failure in diabetes. At the cellular level, diabetic cardiomyopathy leads to altered mitochondrial energy metabolism and cardiomyocyte ultrastructure. We combined electron microscopy (EM) and computational modelling to understand the impact of diabetes-induced ultrastructural changes on cardiac bioenergetics. We collected transverse micrographs of multiple control and type I diabetic rat cardiomyocytes using EM. Micrographs were converted to finite-element meshes, and bioenergetics was simulated over them using a biophysical model. The simulations also incorporated depressed mitochondrial capacity for oxidative phosphorylation (OXPHOS) and creatine kinase (CK) reactions to simulate diabetes-induced mitochondrial dysfunction. Analysis of micrographs revealed a 14% decline in mitochondrial area fraction in diabetic cardiomyocytes, and an irregular arrangement of mitochondria and myofibrils. Simulations predicted that this irregular arrangement, coupled with the depressed activity of mitochondrial CK enzymes, leads to large spatial variation in adenosine diphosphate (ADP)/adenosine triphosphate (ATP) ratio profile of diabetic cardiomyocytes. However, when spatially averaged, myofibrillar ADP/ATP ratios of a cardiomyocyte do not change with diabetes. Instead, average concentration of inorganic phosphate rises by 40% owing to lower mitochondrial area fraction and dysfunction in OXPHOS. These simulations indicate that a disorganized cellular ultrastructure negatively impacts metabolite transport in diabetic cardiomyopathy. This article is part of the theme issue 'The cardiomyocyte: new revelations on the interplay between architecture and function in growth, health, and disease'.

Insights on the impact of mitochondrial organisation on bioenergetics in high-resolution computational models of cardiac cell architecture.

Recent electron microscopy data have revealed that cardiac mitochondria are not arranged in crystalline columns but are organised with several mitochondria aggregated into columns of varying sizes spanning the cell cross-section. This raises the question-how does the mitochondrial arrangement affect the metabolite distributions within cardiomyocytes and what is its impact on force dynamics? Here, we address this question by employing finite element modeling of cardiac bioenergetics on computational meshes derived from electron microscope images. Our results indicate that heterogeneous mitochondrial distributions can lead to significant spatial variation across the cell in concentrations of inorganic phosphate, creatine (Cr) and creatine phosphate (PCr). However, our model predicts that sufficient activity of the creatine kinase (CK) system, coupled with rapid diffusion of Cr and PCr, maintains near uniform ATP and ADP ratios across the cell cross sections. This homogenous distribution of ATP and ADP should also evenly distribute force production and twitch duration with contraction. These results suggest that the PCr shuttle and associated enzymatic reactions act to maintain uniform force dynamics in the cell despite the heterogeneous mitochondrial organization. However, our model also predicts that under hypoxia activity of mitochondrial CK enzymes and diffusion of high-energy phosphate compounds may be insufficient to sustain uniform ATP/ADP distribution and hence force generation.

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 microscopy, the scientific community has unprecedented access to large datasets at sub-micrometer resolution that characterize the architectural remodeling that accompanies changes in cardiomyocyte function in health and disease. However, these datasets have been under-utilized for investigating the role of cellular architecture remodeling in cardiomyocyte function. The purpose of this protocol is to outline how to create an accurate finite element model of a cardiomyocyte using high resolution electron microscopy and confocal microscopy images. A detailed and accurate model of cellular architecture has significant potential to provide new insights into cardiomyocyte biology, more than experiments alone can garner. The power of this method lies in its ability to computationally fuse information from two disparate imaging modalities of cardiomyocyte ultrastructure to develop one unified and detailed model of the cardiomyocyte. This protocol outlines steps to integrate electron tomography and confocal microscopy images of adult male Wistar (name for a specific breed of albino rat) rat cardiomyocytes to develop a half-sarcomere finite element model of the cardiomyocyte. The procedure generates a 3D finite element model that contains an accurate, high-resolution depiction (on the order of ~35 nm) of the distribution of mitochondria, myofibrils and ryanodine receptor clusters that release the necessary calcium for cardiomyocyte contraction from the sarcoplasmic reticular network (SR) into the myofibril and cytosolic compartment. The model generated here as an illustration does not incorporate details of the transverse-tubule architecture or the sarcoplasmic reticular network and is therefore a minimal model of the cardiomyocyte. Nevertheless, the model can already be applied in simulation-based investigations into the role of cell structure in calcium signaling and mitochondrial bioenergetics, which is illustrated and discussed using two case studies that are presented following the detailed protocol.

An automated workflow for segmenting single adult cardiac cells from large-volume serial block-face scanning electron microscopy data.

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.

A computational study of the role of mitochondrial organization on cardiac bioenergetics.

All cells in the body have a specific shape and internal organization which is specific to that cell's function. Heart cells are rod-shaped, and contain arrays of contractile protines (myofibrils) and mitochondria (organelles that produce energy) that are aligned along the length of the rod. This arrangement is presumed to allow the cell to generate maximal contractile force for each heartbeat and for energy metabolites to be readily available to generate this force. Heart disease phenotypes, such as diabetic cardiomyopathy and heart failure, exhibit altered organization of mitochondria. However, physiological and computational studies have predominantly investigated the effect of the biochemical changes that accompany the disease alone, such as reduced rates of ATP production by mitochondria. We present a modeling study that examines the effect of mitochondrial organization on energy metabolite distribution during the heartbeat. A 2D micrograph of the cell cross-section was selected from a 3D image stack of structural data of a cardiac cell. The image was used to generate a 2D finite element model, on which mitochondrial oxidative phosphorylation and energy metabolite diffusion was modelled. Results illustrate that mitochondrial density can induce heterogeneity in the distribution of metabolites across the cell area. We discuss the implications of these findings and avenues for future, more indepth studies.

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

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.

Effect of stiffness of micron/sub-micron electrospun fibers in cell seeding.

The objective of this study was to develop a predictive model for cell seeding depth in electrospun scaffold as a function of fiber stiffness. Electrospun scaffolds (micron and submicron) and 3T3 fibroblasts are used as scaffold-cell systems under vacuum seeding conditions. Atomic force microscopy is used to determine the Young's modulus (E) as a function of fiber diameter. A higher E value led to a lower depth of cell seeding (closer to the surface) indicating that nanofibrous scaffolds offer higher resistance to cell movement compared to microfibrous scaffold. An energy balance model was developed to predict cell seeding depth as a function of E for various vacuum pressures. Experimental data was used in the model to extract unknown parameters to predict cell seeding depth as a function of vacuum pressure for different stiffness scaffolds.