Novel Analysis Software for Detecting and Classifying Ca2+ Transient Abnormalities in Stem Cell-Derived Cardiomyocytes

摘要

Comprehensive functioning of Ca²⁺ cycling is crucial for excitation–contraction coupling of cardiomyocytes (CMs). Abnormal Ca²⁺ cycling is linked to arrhythmogenesis, which is associated with cardiac disorders and heart failure. Accordingly, we have generated spontaneously beating CMs from induced pluripotent stem cells (iPSC) derived from patients with catecholaminergic polymorphic ventricular tachycardia (CPVT), which is an inherited and severe cardiac disease. Ca²⁺ cycling studies have revealed substantial abnormalities in these CMs. Ca²⁺ transient analysis performed manually lacks accepted analysis criteria, and has both low throughput and high variability. To overcome these issues, we have developed a software tool, AnomalyExplorer based on interactive visualization, to assist in the classification of Ca²⁺ transient patterns detected in CMs. Here, we demonstrate the usability and capability of the software, and we also compare the analysis efficiency to manual analysis. We show that AnomalyExplorer is suitable for detecting normal and abnormal Ca²⁺ transients; furthermore, this method provides more defined and consistent information regarding the Ca²⁺ abnormality patterns and cell line specific differences when compared to manual analysis. This tool will facilitate and speed up the analysis of CM Ca²⁺ transients, making it both more accurate and user-independent. AnomalyExplorer can be exploited in Ca²⁺ cycling analysis to study basic disease pathology and the effects of different drugs.