Quantification of Stem Cell Derived Cardiomyocyte Beating Mechanics using Video Microscopy Image Analysis

Until recently, the studying of human cardiac cells had been a difficult and to some extent dangerous task due to the risks involved in cardiac biopsies. Induced pluripotent stem cell technology enables the conversion of human adult cells to stem cells, which can be further differentiated to cardiac cells. These cells have the same genotype as the patient from whom they were derived, allowing the studying of genetic cardiac diseases, as well as the cardiac safety and efficacy screening of pharmaceutical agents using human cardiac cells instead of animal cell models. Using the stem cell derived cardiac cells in these studies, however, requires novel and specialized measurement methods for understanding the functioning of these cells.

Long QT syndrome and catecholaminergic polymorphic ventricular tachycardia (CPVT) are genetic cardiac diseases, which can induce deadly arrhythmias. The induced pluripotent stem cell derived cardiac cells allow the studying of these diseases in laboratory conditions. A greater understanding of these diseases is important for prevention of sudden cardiac death, more accurate diagnosis, and development of possible treatment options. In order to understand the functioning of these cells, new methods are sought after. Traditionally, the electrical function of these cells are measured. However, the primary function of the cardiac cells is to beat in order to pump blood for circulation. The methods to quantify this mechanical function, the contraction and relaxation movement of cells, has been in lesser focus.

The main objective of this work is to develop a measurement method, which allows the in vitro quantification of biomechanics of single human cardiac cells using video microscopy. The method uses digital image correlation to determine movement occurring in cardiac cells during contractile movement. The method is implemented in a software tool, which enables the characterization and parametrization of the cardiomyocyte beating function. The beating function itself can be affected by environmental factors, pharmacological agents and cardiac disease.

Here, the quantification of mechanical function is performed using digital image correlation to estimate displacement between subsequent video frames. Velocity vector fields can then be used to calculate signals that characterize the contraction and relaxation movement. We estimate its accuracy in cardiac cell studies using artificial data sets and its feasibility with concurrent electrical measurements. Cardiac diseases are studied by quantifying beating mechanics from Long QT and CPVT specific cell lines. Traditional electrophysiological measurements are used for validation and comparison. The interaction between calcium and contraction is studied with a simultaneous measurement of biomechanics and calcium imaging.

This thesis resulted a new and accessible analysis method capable of measuring cardiomyocyte biomechanics. This method was determined to be non-toxic and minimally invasive, and found capable to be automated for high-throughput analysis. Due to not harming the cells, repeated measurements are enabled. Using the method, we observed for the first time abnormal beating phenotypes in two long QT associated mutations in single cardiomyocytes. Further, we demonstrated a concurrent calcium and motion measurement without background corrections. This provided also evidence that this combined analysis could be particularly useful in some cardiac disease cases. The methods and results shown in the thesis represent key early advances in the field.

The method was implemented in a software tool, which enabled cell biologists to use it different stages of cardiomyocyte studies. Overall, the results of the thesis represent an accessible method of studying cardiomyocyte biomechanics, which improves the understanding of contraction-calcium coupling and paves way for high-throughput analysis of cardiomyocytes in genetic cardiac disease and pharmacological research.