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Updated: Jul 2, 2025

High Efficiency Differentiation of Human Pluripotent Stem Cells to Cardiomyocytes and Characterization by Flow Cytometry
Published on: September 23, 2014
CD151 expression marks atrial- and ventricular- differentiation from human induced pluripotent stem cells
Misato Nakanishi-Koakutsu1,2,3,4, Kenji Miki5,6,7,8, Yuki Naka1,2
1Center for iPS Cell Research and Application, Kyoto University, Kyoto, 606-8507, Japan.
Researchers identified CD151 as a cell surface marker to distinguish human induced pluripotent stem cell-derived atrial and ventricular cardiomyocytes. This discovery enables efficient generation of chamber-specific cells for disease modeling.
Area of Science:
- Stem Cell Biology
- Cardiovascular Research
- Cell Differentiation
Background:
- Current protocols for differentiating human induced pluripotent stem cells (hiPSCs) yield heterogeneous cardiomyocytes (CMs).
- Chamber-specific CM selection using cell surface antigens is valuable, but a marker distinguishing hiPSC-derived atrial CMs (ACMs) from ventricular CMs (VCMs) is lacking.
Purpose of the Study:
- To develop a method for obtaining functional hiPSC-derived ACMs and VCMs.
- To identify a cell surface marker for distinguishing between hiPSC-derived ACMs and VCMs.
Main Methods:
- Investigated CD151 expression in differentiating hiPSCs.
- Utilized Notch signaling modulation and CD151 expression for cell population selection.
- Assessed cell identity through gene expression and electrophysiology.
Main Results:
- ACMs are enriched in the CD151low population, correlating with Notch4 expression.
- Notch signaling inhibition and CD151low selection efficiently generated ACMs.
- VCMs are enriched in the CD151high population, exhibiting ventricular characteristics.
Conclusions:
- CD151 expression serves as a reliable marker to distinguish hiPSC-derived ACMs and VCMs.
- This approach enables the efficient production of high-quality, chamber-specific cardiomyocytes.
- The findings support the development of hiPSC-derived chamber-specific disease models.
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