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Cardiac tissues are able to adjust their contractile behavior to adapt to the local mechanical environment. Nonuniformity of the native tissue mechanical properties contributes to the development of heart dysfunctions, yet the current in vitro cardiac tissue models often fail to recapitulate the mechanical nonuniformity. To address this issue, a 3D cardiac microtissue model is developed with engineered mechanical nonuniformity, enabled by 3D‐printed hybrid matrices composed of fibers with different diameters. When escalating the complexity of tissue mechanical environments, cardiac microtissues start to develop maladaptive hypercontractile phenotypes, demonstrated in both contractile motion analysis and force‐power analysis. This novel hybrid system could potentially facilitate the establishment of “pathologically‐inspired” cardiac microtissue models for deeper understanding of heart pathology due to nonuniformity of the tissue mechanical environment.

 

Understanding the complexity of biological signals has been gaining widespread attention due to increasing knowledge on the nonlinearity that exists in these systems. Cardiac signals are known to exhibit highly complex dynamics, consisting of high degrees of interdependency that regulate the cardiac contractile functions. These regulatory mechanisms are important to understand for the development of novelin vitrocardiac systems, especially with the exponential growth in deriving cardiac tissue directly from human induced pluripotent stem cells (hiPSCs). This work describes a unique analytical approach that integrates linear amplitude and frequency analysis of physical cardiac contraction, with nonlinear analysis of the contraction signals to measure the signals’ complexity. We generated contraction motion waveforms reflecting the physical contraction of hiPSC-derived cardiomyocytes (hiPSC-CMs) and implemented these signals to nonlinear analysis to compute the capacity and correlation dimensions. These parameters allowed us to characterize the dynamics of the cardiac signals when reconstructed into a phase space and provided a measure of signal complexity to supplement contractile physiology data. Thus, we applied this approach to evaluate drug response and observed that relationships between contractile physiology and dynamic complexity were unique to each tested drug. This illustrated the applicability of this approach in not only characterization of cardiac signals, but also monitoring and diagnostics of cardiac health in response to external stress.

 

Combination of stem cell technology and 3D biofabrication approaches provides physiological similarity to in vivo tissues and the capability of repairing and regenerating damaged human tissues. Mesenchymal stem cells (MSCs) have been widely used for regenerative medicine applications because of their immunosuppressive properties and multipotent potentials. To obtain large amount of high-quality MSCs without patient donation and invasive procedures, we differentiated MSCs from human-induced pluripotent stem cells (hiPSC-MSCs) using serum-free E6 media supplemented with only one growth factor (bFGF) and two small molecules (SB431542 and CHIR99021). The differentiated cells showed a high expression of common MSC-specific surface markers (CD90, CD73, CD105, CD106, CD146, and CD166) and a high potency for osteogenic and chondrogenic differentiation. With these cells, we have been able to manufacture MSC tissue rings with high consistency and robustness in pluronic-coated reusable PDMS devices. The MSC tissue rings were characterized based on inner diameter and outer ring diameter and observed cell-type-dependent tissue contraction induced by cell-matrix interaction. Our approach of simplified hiPSC-MSC differentiation, modular fabrication procedure, and serum-free culture conditions has a great potential for scalable manufacturing of MSC tissue rings for different regenerative medicine applications.