The parent grant, ?Engineered Human Heart Slice for Testing Drug-Induced Arrhythmia?, aims to develop a pharmacologic testing platform for in vitro prediction of drug-induced cardiac arrhythmia using engineered heart slices (EHS) embedded with human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs).
Aim 1 focuses on improving methods of quantifying and controlling the maturity of hiPSC-CMs, which is key to the implementation and interpretation of these models. The work proposed here will supplement Aim 1 of the parent grant by expanding beyond healthy wildtype hiPSC-CMs to understand maturity in hiPSCs harboring genetic cardiac disorders, specifically arrhythmogenic right ventricular cardiomyopathy (ARVC).
The first aim of this work is to establish the maturation trajectory of diseased hiPSC-CMs in comparison to wildtype cells. This will be accomplished by assessing, at several time points, structural features (i.e. sarcomere organization, troponin isoform expression), CD36 positivity (marker of metabolic maturity), and transcriptomic entropy scoring (a novel RNA-sequencing based method).
The second aim i s to evaluate the effects of targeted metabolic maturation on diseased vs healthy hiPSC-CMs. We will measure maturity in cells treated with standard differentiation procedures and media against cells supplemented with a novel nutrient formula shown to boost maturity in wildtype hiPSC-CMs. By providing insight into the maturational differences of healthy and disease cells and potentially allowing us to account for that confounding variable, this work will facilitate the creation of robust disease models for drug response testing and therapeutic development.
The development of a robust in vitro model of human cardiac tissue for pharmacologic testing and disease modelling largely relies on cardiomyocytes derived from stem cell sources. However, the process by which these cells mature into cardiomyocytes is variable and has a major impact on their behavior. This project aims to compare maturation in healthy and diseased stem cell lines to improve the implementation and interpretation of these disease models.
