Side effects on cardiac ion channels causing lethal arrhythmias are one major reason for drug withdrawals from the market. Field potential (FP) recording from cardiomyocytes, is a well-suited tool to assess such cardiotoxic effects of drug candidates in preclinical drug development, but it is currently limited to the spontaneous beating of the cardiomyocytes and manual analysis. Herein, we present a novel optogenetic cardiotoxicity screening system suited for the parallel automated frequency-dependent analysis of drug effects on FP recorded from human pluripotent stem cell-derived cardiomyocytes. For the expression of the light-sensitive cation channel Channelrhodopsin-2, we optimised protocols using virus transduction or transient mRNA transfection. Optical stimulation was performed with a new light-emitting diode lid for a 96-well FP recording system. This enabled reliable pacing at physiologically relevant heart rates and robust recording of FP. Thereby we detected rate-dependent effects of drugs on Na⁺, Ca²⁺ and K⁺ channel function indicated by FP prolongation, FP shortening and the slowing of the FP downstroke component, as well as generation of afterdepolarisations. Taken together, we present a scalable approach for preclinical frequency-dependent screening of drug effects on cardiac electrophysiology. Importantly, we show that the recording and analysis can be fully automated and the technology is readily available using commercial products.

Drug-drug interactions pose a difficult drug safety problem, given the increasing number of individuals taking multiple medications and the relative complexity of assessing the potential for interactions. For example, sofosbuvir-based drug treatments have significantly advanced care for hepatitis C virus-infected patients, yet recent reports suggest interactions with amiodarone may cause severe symptomatic bradycardia and thus limit an otherwise extremely effective treatment. Here, we evaluated the ability of human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) to recapitulate the interaction between sofosbuvir and amiodarone in vitro, and more generally assessed the feasibility of hiPSC-CMs as a model system for drug-drug interactions. Sofosbuvir alone had negligible effects on cardiomyocyte electrophysiology, whereas the sofosbuvir-amiodarone combination produced dose-dependent effects beyond that of amiodarone alone. By comparison, GS-331007, the primary circulating metabolite of sofosbuvir, had no effect alone or in combination with amiodarone. Further mechanistic studies revealed that the sofosbuvir-amiodarone combination disrupted intracellular calcium (Ca²⁺) handling and cellular electrophysiology at pharmacologically relevant concentrations, and mechanical activity at supra-pharmacological (30x C_max) concentrations. These effects were independent of the common mechanisms of direct ion channel block and P-glycoprotein activity. These results support hiPSC-CMs as a comprehensive, yet scalable model system for the identification and evaluation of cardioactive pharmacodynamic drug-drug interactions.

The in situ observation of cell movements and morphological parameters over longer periods of time under physiological conditions is critical in basic cell research and biomedical applications. The quantitative phase-contrast microscope applied in this study has a remarkably small size, therefore it can be placed directly into a humidified incubator. Here, we report on the successful application of this M4 Holomonitor to observe cancer cell motility, motility speed, and migration in the presence of the green tea polyphenol, epigallocatechin gallate, as well as to monitor the adhesion of preosteoblast cells on nanostructured titanate coatings, relevant for biomedical applications. A special mechanical stage was developed to position the sample into that range of the optical arrangement where digital autofocusing works with high reproducibility and precision. By in-depth analyzing the obtained single cell morphological parameters, we show that the limited vertical resolution of the optical setup results in underestimated single cell contact area and volume and overestimated single cell averaged thickness. We propose a simple model to correct the recorded data to obtain more precise single cell parameters. We compare the results with the kinetic data recorded by a surface sensitive optical biosensor, optical waveguide lightmode spectroscopy.