High-throughput Patterning of Labile Proteins for Fabricating Cardiac Micropatterned Co-cultures

Reliable in vitro platforms that accurately mimic the heart’s cellular and structural organization are essential for advancing cardiac research, including disease modeling, drug discovery, and regenerative medicine. This thesis represents preliminary work toward developing a high throughput 96-well plate platform designed to model the microenvironment and characteristics of the human heart. Such platforms serve as a crucial middle ground, bridging the gap between basic two dimensional cultures and the complexities of in vivo studies. By providing controlled environments, they replicate key features necessary for the development of adult-like iPSC-derived cardiomyocytes. This approach builds on the state-of-the-art understanding that co-culturing cardiac fibroblasts (CFs) with cardiomyocytes significantly enhances both the function and maturity of cardiomyocytes. The first goal of the thesis was to develop a robust protocol for patterning labile proteins, specifically fibronectin (FN) and bovine serum albumin (BSA), on a 96-well plate. This protocol enables the spatial organization of iPSC-derived ventricular cardiomyocytes (iPSC-vCMs) and vCFs, mimicking the physical and biochemical cues found in the native cardiac microenvironment. Subsequently, this thesis investigated how iPSC-vCMs respond to co-culture within this micropatterned platform compared to random co-cultures. This includes analyzing structural and functional maturation markers under varying seeding densities to determine the conditions that most effectively promote cardiomyocyte maturation. Finally, an exploratory analysis was conducted to evaluate the influence of secreted frizzled related protein 2 (Sfrp2) on iPSC-vCM differentiation. This analysis compared Sfrp2-mediated differentiation to an in-house protocol modeled after commercially available differentiation methods, with the aim of understanding its potential role in improving the maturity of iPSC-vCMs. In conclusion, this body of work provides a foundation for future studies to refine the platform and explore its applications in cardiac disease modeling, drug discovery, and regenerative medicine.