Measuring Single-Cell Calcium Dynamics Using a Myofilament-Localized Optical Biosensor in hiPSC-CMs Derived from DCM Patients.

Synchronized contractions of cardiomyocytes within the heart are tightly coupled to electrical stimulation known as excitation-contraction coupling. Calcium plays a key role in this process and dysregulated calcium handling can significantly impair cardiac function and lead to the development of cardiomyopathies and heart failure. Here, we describe a method and analytical technique to study myofilament-localized calcium signaling using the intensity-based fluorescent biosensor, RGECO-TnT. Dilated cardiomyopathy is a heart muscle disease that negatively impacts the heart's contractile function following dilatation of the left ventricle. We demonstrate how this biosensor can be used to characterize 2D hiPSC-CMs monolayers generated from a healthy control subject compared to two patients diagnosed with dilated cardiomyopathy. Lastly, we provide a step-by-step guide for single-cell data analysis and describe a custom Transient Analysis application, specifically designed to quantify features of calcium transients. All in all, we explain how this analytical approach can be applied to phenotype hiPSC-CM behaviours and stratify patient responses to identify perturbations in calcium signaling.

Biosensor-based profiling to track cellular signalling in patient-derived models of dilated cardiomyopathy.

Dilated cardiomyopathies (DCM) represent a diverse group of cardiovascular diseases impacting the structure and function of the myocardium. To better treat these diseases, we need to understand the impact of such cardiomyopathies on critical signalling pathways that drive disease progression downstream of receptors we often target therapeutically. Our understanding of cellular signalling events has progressed substantially in the last few years, in large part due to the design, validation and use of biosensor-based approaches to studying such events in cells, tissues and in some cases, living animals. Another transformative development has been the use of human induced pluripotent stem cells (hiPSCs) to generate disease-relevant models from individual patients. We highlight the importance of going beyond monocellular cultures to incorporate the influence of paracrine signalling mediators. Finally, we discuss the recent coalition of these approaches in the context of DCM. We discuss recent work in generating patient-derived models of cardiomyopathies and the utility of using signalling biosensors to track disease progression and test potential therapeutic strategies that can be later used to inform treatment options in patients.

Measuring hypertrophy in neonatal rat primary cardiomyocytes and human iPSC-derived cardiomyocytes.

In the heart, left ventricular hypertrophy is initially an adaptive mechanism that increases wall thickness to preserve normal cardiac output and function in the face of coronary artery disease or hypertension. Cardiac hypertrophy develops in response to pressure and volume overload but can also be seen in inherited cardiomyopathies. As the wall thickens, it becomes stiffer impairing the distribution of oxygenated blood to the rest of the body. With complex cellular signalling and transcriptional networks involved in the establishment of the hypertrophic state, several model systems have been developed to better understand the molecular drivers of disease. Immortalized cardiomyocyte cell lines, primary rodent and larger animal models have all helped understand the pathological mechanisms underlying cardiac hypertrophy. Induced pluripotent stem cell-derived cardiomyocytes are also used and have the additional benefit of providing access to human samples with direct disease relevance as when generated from patients suffering from hypertrophic cardiomyopathies. Here, we briefly review in vitro and in vivo model systems that have been used to model hypertrophy and provide detailed methods to isolate primary neonatal rat cardiomyocytes as well as to generate cardiomyocytes from human iPSCs. We also describe how to model hypertrophy in a "dish" using gene expression analysis and immunofluorescence combined with automated high-content imaging.