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Efficient and reproducible generation of human iPSC-derived cardiomyocytes and cardiac organoids in stirred suspension systems

GSE263372 Homo sapiens Expression profiling by high throughput sequencing 5 samples Submitted 2024/06/05 Platform GPL24676
Summary
Human iPSC-derived cardiomyocytes (hiPSC-CMs) have proven invaluable for cardiac disease modeling and cardiac regeneration. Challenges with quality, inter-batch consistency, cryopreservation and scale remain, reducing experimental reproducibility and clinical translation. Here, we report a robust stirred suspension cardiac differentiation protocol with careful functional characterization of the resulting hiPSC-CMs. In a bioreactor, the protocol produced 1.2E6/mL hiPSC-CMs with ~94% purity from 14 iPSC lines. Bioreactor-differentiated CMs (bCMs) showed high viability after cryo-recovery (>90%) and predominantly ventricular identity. Compared to standard monolayer-differentiated CMs (mCMs), bCMs had greater reproducibility and more mature functional properties, including pacing capture to 4 Hz and greater force production in 3D engineered heart tissues. In more readily available magnetically stirred spinner flasks, the protocol yielded 1.8E6/mL spinner-differentiated CMs (sCMs) with 94% purity. Differentiation scaled readily in spinner flasks, as a 3.8-fold increase in cultured volume yielded 3.4E6/ml sCMs. sCMs had intermediate functional properties between mCMs and bCMs. Minor protocol modifications generated the first bioreactor-derived cardiac organoids (bCOs) fully generated in suspension. These reproducible, scalable, and resource efficient approaches to generate cardiac cells and organoids with well-characterized properties will expand the applications of hiPSC-CMs.
Published in
Efficient and reproducible generation of human iPSC-derived cardiomyocytes and cardiac organoids in stirred suspension systems
Prondzynski M, Berkson P, Trembley MA et al. · Nature communications 2024 · PMID 39009604 · doi:10.1038/s41467-024-50224-0
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Also filed as BioProject PRJNA1096957 and SRA study SRP500076. Searching any of these in the dataset finder brings you back here.

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