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Traditionally, tissue-specific organoids are generated as 3D aggregates of stem cells embedded in Matrigel or hydrogels, and the aggregates eventually end up a spherical shape and suspended in the matrix. Lack of geometrical control of organoid formation makes these spherical organoids limited for modeling the tissues with complex shapes. To address this challenge, we developed a new method to generate 3D spatial-organized cardiac organoids from 2D micropatterned human induced pluripotent stem cell (hiPSC) colonies, instead of directly from 3D stem cell aggregates. This new approach opens the possibility to create cardiac organoids that are templated by 2D non-spherical geometries, which potentially provides us a deeper understanding of biophysical controls on developmental organogenesis. Here, we designed 2D geometrical templates with quadrilateral shapes and pentagram shapes that had same total area but different geometrical shapes. Using this templated substrate, we grew cardiac organoids from hiPSCs and collected a series of parameters to characterize morphological and functional properties of the cardiac organoids. In quadrilateral templates, we found that increasing the aspect ratio impaired cardiac tissue 3D self-assembly, but the elongated geometry improved the cardiac contractile functions. However, in pentagram templates, cardiac organoid structure and function were optimized with a specific geometry of an ideal star shape. This study will shed a light on “organogenesis-by-design” by increasing the intricacy of starting templates from external geometrical cues to improve the organoid morphogenesis and functionality. 

Abstract 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. 

Abstract 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.