Electronic Thesis/Dissertation


High-Throughput All-Optical Cardiac Electrophysiology: Design, Validation, and Applications in vitro and in vivo Open Access

Downloadable Content

Download PDF

Biological systems are inherently dynamic, requiring active interrogation and recording to provide a full understanding of their underlying mechanics. In order to fully characterize such a system, both readily quantifiable signals as well as a means of dynamic control are necessary. In the heart, the propagation of electrical waves driving contraction are mediated by the flow of ions through various ion channels working in concert to drive de- and re-polarization of the cell membrane. Typically, the culprit of electrical dysfunction in the heart is due to some disruption of normal function of one or more of these ion channels. In order to study these complex electrical disturbances, known as arrhythmias, high spatiotemporal resolution imaging and interrogation are necessary. Traditional methods of interrogation have relied on the use of electrodes and patch clamp methods, which are inherently low throughput and have limited spatial resolution. Additionally, these approaches do not lend well for in vivo use. While studies of cardiac tissue have also employed optical mapping techniques where voltage- or calcium-sensitive fluorescent reporters provide detailed information about cell activation, repolarization, and wave propagation maps, stimulation has remained primarily limited to electrical means. However, recently developed optogenetic tools provide a means of high-spatiotemporal resolution (and potentially tissue-type specific) means of interrogation. By combining both of these methods, high-spatiotemporal dynamic characterization of cardiac electrophysiology can be achieved.Here we present how all-optical approaches can be achieved via employing optogenetics in order to explore cardiac electrophysiology at the in vitro as well as in vivo scale. The main optical design is first implemented for in vitro use, where we demonstrate how OptoDyCE, our all-optical dynamic cardiac electrophysiology platform, can be used to screen drug effects in both isolated primary myocytes and human induced pluripotent stem-cell derived cardiomyocytes (hiPSC-CMs) grown in monolayers and 3D tissue constructs. We then characterize an upgraded version of OptoDyCE, capable of simultaneous imaging of membrane voltage and intracellular calcium signals. The system is used for screening of 12 blinded compounds to demonstrate how the platform can used for pro-arrhythmia prediction at the high-throughput (HT) scale. All compounds were properly identified as ‘safe’ or ‘unsafe’ using the multi-parameter endpoints, made possible with high-spatiotemporal resolution recordings under spontaneous and paced conditions. To further demonstrate how all-optical approaches improve proarrhythmia prediction, we tested vanoxerine, a compound that failed Phase III clinical trials, and demonstrate OptoDyCE’s ability to easily identify the compound as pro-arrhythmic, unlike techniques employing patch clamp and in silico modeling that deemed the compound safe for use in humans. As hiPSC-CMs provide a novel testbed for drug testing and disease modeling, we then use OptoDyCE to characterize these cells, both in terms of their potential immaturity (a common criticism) and their ability to recapitulate genetic diseases for use in disease modeling. Finally, the requirements for translating OptoDyCE for in vivo use are considered, and successful demonstration in vivo expression of ChR2 in the rat heart by employing systemic viral delivery, providing a model for development and testing of an optical system in intact tissue and for long-term use in behaving animals. Ultimately, we demonstrate the OptoDyCE platform has capacity to revolutionize pre-clinical drug testing, reduce cost, reduce animal use, and make clinically implemented personalized medicine an obtainable goal.

Author Language Keyword Date created Type of Work Rights statement GW Unit Degree Advisor Committee Member(s) Persistent URL