Title: Multi-omic and predictive modeling approaches to engineer robust human pluripotent stem cell differentiation to cardiomyocytes
Abstract: Cardiovascular disease, specifically ischemic heart disease, has been the global leading cause of death for over a century. During myocardial infarction (MI), coronary artery thrombosis causes ischemia and massive cardiomyocyte (CM) death. Because human CMs lack the ability to regenerate, an MI is repaired through fibrosis, and the heart loses pumping ability in proportion to the number of lost CMs. Subsequently, patients often progress to heart failure, which negatively impacts quality of life and 5-year survival. Routine therapies for MI and heart failure delay disease progression; however, none address the fundamental issue of replacing lost contractile myocardium. Human pluripotent stem cells (hPSCs) hold immense promise for cardiovascular disease because they are an unlimited cell source for generating all cell types in the body. Several investigations have demonstrated the utility of hPSC-CMs in drug development, disease modeling, and cell therapy applications. However, first-generation hPSC-CM differentiation protocols largely rely on studies of signaling pathways underlying murine cardiogenesis. As such, hPSC-CM differentiation protocols are plagued by batch-to-batch and line-to-line variability in generating pure CMs, which is necessary for downstream applications. In this work, we employed emerging multi-omic, imaging, and machine learning strategies to characterize, predict, and improve CM differentiation efficiency. Specifically, we demonstrate strategies to enhance CM differentiation through modifying cell density, multi-omic analysis, and Wnt/MAPK signaling inhibition. Moreover, we accurately predict hPSC-CM differentiation efficiency within the first few days of hPSC-CM differentiation from phase contrast images and newly identified gene expression candidates. Lastly, we introduce single cell -omic technology as a powerful tool to establish CM differentiation failure mechanisms in vitro.
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