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Electrophysiological Analysis of human Pluripotent Stem Cell-derived Cardiomyocytes hPSC-CMs Using Multi-electrode Arrays MEAs
Published on: May 12, 2017
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Integrated multi-omics analysis identifies features that predict human pluripotent stem cell-derived progenitor
Aaron D Simmons1, Claudia Baumann2, Xiangyu Zhang2
1Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.
Journal of Molecular and Cellular Cardiology
|September 2, 2024
Summary
Researchers identified early quality markers in cardiac progenitor cells (CPCs) to predict the success of human pluripotent stem cell-derived cardiomyocyte (hPSC-CM) production. This improves consistency and reliability in generating high-purity cardiomyocytes for research and therapy.
Area of Science:
- Stem Cell Biology
- Cardiovascular Research
- Genomics and Epigenomics
Background:
- Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) are crucial for cardiovascular research, disease modeling, drug testing, and regenerative medicine.
- Significant variability in hPSC-CM differentiation poses a major challenge to their reliable production and application.
- Early quality markers are needed to monitor lineage progression and predict differentiation outcomes, enhancing robustness and reproducibility.
Purpose of the Study:
- To identify predictive quality markers within cardiac progenitor cells (CPCs) that correlate with successful human cardiomyocyte differentiation.
- To develop predictive models for assessing terminal differentiation purity at the CPC stage.
- To elucidate the molecular mechanisms underlying differentiation batch failures and identify off-target cell populations.
Main Methods:
- Integrated transcriptomic and epigenomic analysis of cardiac progenitor cells (CPCs).
- Identification and validation of gene expression markers associated with high-purity cardiomyocyte differentiation.
- Development of predictive models using identified gene markers to forecast differentiation outcomes.
- Analysis of signaling pathways (EMT, MAPK, WNT) implicated in differentiation batch failures.
Main Results:
- Identification of key predictive markers (e.g., TTN, TRIM55, DGKI, MEF2C, MAB21L2, MYL7, LDB3, SLC7A11, CALD1) in CPCs that predict high-purity hPSC-CM batches.
- Development of accurate predictive models capable of determining terminal cardiomyocyte purities from the CPC stage.
- Elucidation of EMT, MAPK, and WNT signaling pathways as drivers of batch divergence, leading to off-target cell types like fibroblasts, skeletal myocytes, and epicardial cells.
Conclusions:
- Integrated multi-omic analysis of progenitor cells can effectively identify quality attributes and predict differentiation outcomes.
- The identified markers and predictive models significantly improve the robustness and reproducibility of hPSC-CM production protocols.
- Understanding the mechanisms of batch failure provides critical insights for optimizing differentiation strategies and ensuring consistent cardiomyocyte generation.
