Integrating traction force microscopy and finite element analysis to assess hiPSC-CM mechanics on micropatterned substrates.

Abstract

Traction force microscopy (TFM) is a well-established technique for quantifying the forces that cells exert on their underlying substrates. However, its application to dynamically beating cells-such as cardiomyocytes (CMs) cultured as two-dimensional monolayers-remains challenging, particularly when the cells are grown on non-planar or micropatterned substrates. In this study, we present an integrated TFM-finite element analysis (FEA) workflow integrated with dual-plane fluorescence imaging. This approach enables quantification of the stress and strain energy density (SED) fields generated by human-induced pluripotent stem cell-derived CMs (hiPSC-CMs) cultured on micropatterned polydimethylsiloxane (PDMS) substrates with tunable stiffness. Substrate stiffness was tuned to mimic both healthy (∼5 kPa) and fibrotic (∼50 kPa) cardiac microenvironments. Displacement fields captured from the top and bottom planes of the micropatterns were interpolated and mapped onto a finite element model to reconstruct local stress and strain energy distributions. Results showed that substrate stiffness and micropatterning synergistically modulate cardiomyocyte contractility. Micropatterning promoted cellular alignment and directional force transmission, resulting in anisotropic stress fields and increased SED, particularly on stiff substrates. Moreover, proteomic data revealed a shift from oxidative phosphorylation to glycolysis in cells cultured on stiff micropatterned substrates, consistent with pathological cardiac remodeling. Collectively, these findings demonstrate that soft micropatterned substrates recreate a physiological cardiac microenvironment that supports oxidative metabolism and efficient contractility, whereas stiff micropatterned substrates mimic cardiac remodeling characterized by enhanced stress generation and glycolytic metabolism. The proposed TFM-FEA platform provides a robust and quantitative framework for studying cardiomyocyte mechanobiology under physiologically relevant conditions and can be readily applied to cardiac tissue engineering, disease modeling, and drug screening.