Assessing Cardiomyocyte Excitation-Contraction Coupling Site Detection From Live Cell Imaging Using a Structurally-Realistic Computational Model of Calcium Release

Abstract

Calcium signaling plays a pivotal role in cardiomyocytes, coupling electrical excitation to mechanical contraction of the heart. Determining locations of active calcium release sites, and how their recruitment changes in response to stimuli and in disease states is therefore of central interest in cardiac physiology. Current algorithms for detecting release sites from live cell imaging data are however not easily validated against a known “ground truth,” which makes interpretation of the output of such algorithms, in particular the degree of confidence in site detection, a challenging task. Computational models are capable of integrating findings from multiple sources into a consistent, predictive framework. In cellular physiology, such models have the potential to reveal structure and function beyond the temporal and spatial resolution limitations of individual experimental measurements. Here, we create a spatially detailed computational model of calcium release in an eight sarcomere section of a ventricular cardiomyocyte, using electron tomography reconstruction of cardiac ultrastructure and confocal imaging of protein localization. This provides a high-resolution model of calcium diffusion from intracellular stores, which can be used as a platform to simulate confocal fluorescence imaging in the context of known ground truth structures from the higher resolution model. We use this capability to evaluate the performance of a recently proposed method for detecting the functional response of calcium release sites in live cells. Model permutations reveal how calcium release site density and mitochondria acting as diffusion barriers impact the detection performance of the algorithm. We demonstrate that site density has the greatest impact on detection precision and recall, in particular affecting the effective detectable depth of sites in confocal data. Our findings provide guidance on how such detection algorithms may best be applied to experimental data and give insights into limitations when using two-dimensional microscopy images to analyse three-dimensional cellular structures.

Live-cell photoactivated localization microscopy correlates nanoscale ryanodine receptor configuration to calcium sparks in cardiomyocytes

“…2d). A second critical feature of our imaging and analysis pipeline is the application of DS 20,26 . By revealing only the 'new' Ca 2+ released in each frame, these analyses unveiled the mobile nature of Ca 2+ sparks, which can be obscured when multiple releases are temporally superimposed (Fig.…”

Analysis of Drug Effects on iPSC Cardiomyocytes with Machine Learning

“… 5 In addition, machine learning of cardiac drug effects on contractile force of electrically paced embryonic stem cell derived cardiomyocytes have been studied to create classification model to predict mechanistic actions of an unknown cardioactive drug. 11 With calcium signaling data, machine learning and classifications have been exploited to evaluate and detect the functional response of calcium release sites in cardiomyocytes 10 and in neuroscience to predict and classify epileptic seizures. 19 However, thus far, the use of machine learning to analyze and model drug effects originating particularly from calcium transient signals of iPSC-CMs is new.…”

A Novel Computational Model of the Rabbit Atrial Cardiomyocyte With Spatial Calcium Dynamics

“…Biophysically detailed models of CM ultrastructure with spatially-realistic RyR distribution are also important for understanding structure-function relationships in Ca 2+ handling. Rajagopal et al ( 2015 ) and Ladd et al ( 2019 ) developed such a model for the rat ventricular CM integrating spatial information from high-resolution imaging that included RyR, myofibrils, and mitochondria, and examined the role of these structures on Ca 2+ dynamics in a CM cross-section. They showed that incorporating spatially-realistic distribution of RyRs in the model captured the spatial Ca 2+ heterogeneities observed in line scans.…”