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Abstract
Congenital heart defects constitute the most common human birth defect, however understanding of how these disorders originate is limited by our ability to model the human heart accurately in vitro. Here we report a method to generate developmentally relevant human heart organoids by self-assembly using human pluripotent stem cells. Our procedure is fully defined, efficient, reproducible, and compatible with high-content approaches. Organoids are generated through a three-step Wnt signaling modulation strategy using chemical inhibitors and growth factors. Heart organoids are comparable to age-matched human fetal cardiac tissues at the transcriptomic, structural, and cellular level. They develop sophisticated internal chambers with well-organized multi-lineage cardiac cell types, recapitulate heart field formation and atrioventricular specification, develop a complex vasculature, and exhibit robust functional activity. We also show that our organoid platform can recreate complex metabolic disorders associated with congenital heart defects, as demonstrated by an in vitro model of pregestational diabetes-induced congenital heart defects.
There is a pressing need to develop representative organ-like platforms recapitulating complex in vivo phenotypes to study human development and disease in vitro. Here the authors present a method to generate human heart organoids by self-assembly using pluripotent stem cells, compare these to age-matched fetal cardiac tissues and recreate a model of pregestational diabetes.
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1 Michigan State University, Division of Developmental and Stem Cell Biology, Institute for Quantitative Health Science and Engineering, East Lansing, USA (GRID:grid.17088.36) (ISNI:0000 0001 2150 1785); Michigan State University, Department of Biomedical Engineering, College of Engineering, East Lansing, USA (GRID:grid.17088.36) (ISNI:0000 0001 2150 1785)
2 Washington University in Saint Louis, Department of Biomedical Engineering, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002)
3 Michigan State University, Division of Biomedical Devices, Institute for Quantitative Health Science and Engineering, East Lansing, USA (GRID:grid.17088.36) (ISNI:0000 0001 2150 1785); Michigan State University, Department of Electrical and Computer Engineering, College of Engineering, East Lansing, USA (GRID:grid.17088.36) (ISNI:0000 0001 2150 1785)
4 Michigan State University, Department of Chemical Engineering and Material Science, College of Engineering, East Lansing, USA (GRID:grid.17088.36) (ISNI:0000 0001 2150 1785)