bioRxivBioengineeringPreprint
Insights into single hiPSC-derived cardiomyocyte phenotypes and maturation using ConTraX, an efficient pipeline for tracking contractile dynamics
G. Pardon, H. Lewis, A. S. Vander Roest, E. A. Castillo, R. E. Wilson, A. K. Denisin, C. A. Blair, F. Birnbaum, C. Holbrook, K. Koleckar, A. C.-Y. Chang, H. M. Blau, B. Pruitt
Abstract
Cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs) are powerful in-vitro models to study the mechanisms underlying cardiomyopathies and cardiotoxicity. To understand how cellular mechanisms affect the heart, it is crucial to quantify the contractile function in single hiPSC-CMs over time, however, such measurements remain demanding and low-throughput, and are too seldom considered. We developed an open-access, versatile, streamlined, and highly automated pipeline to address these challenges and enable quantitative tracking of the contractile dynamics of single hiPSC- CMs over time: ConTraX. Three interlocking software modules enable: (i) parameter-based localization and selection of single hiPSC-CMs; (ii) automated video acquisition of >200 cells/hour; and (iii) streamlined measurements of the contractile parameters via traction force microscopy. Using ConTraX, we analyzed >2,753 hiPSC-CMs over time under orthogonal experimental conditions in terms of culture media and substrate stiffnesses. Using undirected high-dimensional clustering, we dissected the complex diversity of contractile phenotypes in hiPSC-CM populations and revealed converging maturation patterns. Our modular ConTraX pipeline empowers biologists with a potent quantitative analytic tool applicable to the development of cardiac therapies.
- organism: human
- assay: spatial transcriptomics
- assay: imaging
- research focus: cell type annotation
- research focus: trajectory inference
- research focus: differential expression
- approach: deep learning
- approach: statistical model
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