There is a growing interest in creating 2D cardiac tissue models that display native extracellular matrix (ECM) cues of the heart tissue. Cellular alignment alone is known to be a crucial cue for cardiac tissue development by regulating cell-cell and cell-ECM interactions. In this study, we report a simple and robust approach to create lamellar surface wrinkling patterns enabling spatial control of pattern dimensions with a wide range of pattern amplitude (A ≈ 2-55 μm) and wavelength (λ ≈ 35-100 μm). For human cardiomyocytes (hCMs) and human cardiac fibroblasts (hCFs), our results indicate that the degree of cellular alignment and pattern recognition are correlated with pattern A and λ. We also demonstrate fabrication of devices composed of micro-well arrays with user-defined lamellar patterns on the bottom surface of each well for high-throughput screening studies. Results from a screening study indicate that cellular alignment is strongly diminished with increasing seeding density. In another study, we show our ability to vary hCM/hCF seeding ratio for each well to create co-culture systems where seeding ratio is independent of cellular alignment.
Keywords: biomaterial; cardiac co-culture; cardiac tissue model; combinatorial culture; combinatorial platform; high-throughput; human cardiac fibroblasts; human cardiomyocytes; tissue engineering.
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