Optical Mapping of hiPSC-Derived Cardiac Monolayers Expressing Genetically-Encoded Voltage Indicators



Naim Shaheen, Rami Shinnawi, Irit Huber, Asaad Shiti, Gil Arbel, Amira Gepstein, Lior Gepstein
The Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Israel

Aims: To combine hiPSC-CM monolayers with either voltage sensitive dyes (VSDs, for short-term studies) or genetically-encoded voltage indicator (ArcLight, for long-term studies) to derive a unique model to study cardiac electrophysiology in human cardiac-tissue.

Methods and Results: Large monolayers (1cm diameter) were generated from normal and transgenic hiPSC-CMs expressing the genetically-encoded voltage indicator ArcLight. Synchronous beating developed in the monolayers as soon as 4d post-plating. A customized optical mapping setup was established (based on a fluorescent macroscope and an EMCCD). Loading the monolayers with voltage sensitive dye (VSD) Di-4-ANEPPS enabled monitoring action-potential wave propagation and construction of activation maps from both ArcLight and VSD signals. Despite ArcLight’s relatively slow kinetics, by optimizing the method for determining local activation time, we were able to construct ArcLight-based activation maps that did not differ from those constructed using VSD. Importantly, while VSD-based mapping was limited due to photobleaching and phototoxicity, ArcLight-based imaging displayed superior signal-to-noise (SNR) and allowed repeated imaging over several days. As expected, decreasing conduction velocities were observed when monolayers were paced with higher frequencies. Finally, programmed electrical stimulation allowed the generation of stable reentrant circuits in the ArcLight-hiPSC-CMs monolayers.

Conclusions: (1) A large-scale monolayer-based hiPSC-derived cardiac-tissue model and an optical-mapping system were established to study conduction and arrhythmogenesis. (2) With the superior SNR, photostability and minimal cellular-toxicity, the stable ArcLight-iPSC line offers a reliable and robust solution for long-term repeated phenotyping of human cardiac-tissue. (3) The generated model could bring a unique value for the study of arrhythmia mechanism, disease modeling, and drug screening