Literature DB >> 29925689

Deep phenotyping of human induced pluripotent stem cell-derived atrial and ventricular cardiomyocytes.

Lukas Cyganek1,2, Malte Tiburcy2,3, Karolina Sekeres4, Kathleen Gerstenberg1, Hanibal Bohnenberger5, Christof Lenz6,7, Sarah Henze1, Michael Stauske1,2, Gabriela Salinas8, Wolfram-Hubertus Zimmermann2,3, Gerd Hasenfuss1,2, Kaomei Guan1,2,4.   

Abstract

Generation of homogeneous populations of subtype-specific cardiomyocytes (CMs) derived from human induced pluripotent stem cells (iPSCs) and their comprehensive phenotyping is crucial for a better understanding of the subtype-related disease mechanisms and as tools for the development of chamber-specific drugs. The goals of this study were to apply a simple and efficient method for differentiation of iPSCs into defined functional CM subtypes in feeder-free conditions and to obtain a comprehensive understanding of the molecular, cell biological, and functional properties of atrial and ventricular iPSC-CMs on both the single-cell and engineered heart muscle (EHM) level. By a stage-specific activation of retinoic acid signaling in monolayer-based and well-defined culture, we showed that cardiac progenitors can be directed towards a highly homogeneous population of atrial CMs. By combining the transcriptome and proteome profiling of the iPSC-CM subtypes with functional characterizations via optical action potential and calcium imaging, and with contractile analyses in EHM, we demonstrated that atrial and ventricular iPSC-CMs and -EHM highly correspond to the atrial and ventricular heart muscle, respectively. This study provides a comprehensive understanding of the molecular and functional identities characteristic of atrial and ventricular iPSC-CMs and -EHM and supports their suitability in disease modeling and chamber-specific drug screening.

Entities:  

Keywords:  Expression profiling; Muscle Biology; Proteomics; Stem cells; iPS cells

Mesh:

Substances:

Year:  2018        PMID: 29925689      PMCID: PMC6124434          DOI: 10.1172/jci.insight.99941

Source DB:  PubMed          Journal:  JCI Insight        ISSN: 2379-3708


  57 in total

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