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. 2013 Dec 3;110(49):E4698-707.
doi: 10.1073/pnas.1311120110. Epub 2013 Nov 19.

Design and formulation of functional pluripotent stem cell-derived cardiac microtissues

Affiliations

Design and formulation of functional pluripotent stem cell-derived cardiac microtissues

Nimalan Thavandiran et al. Proc Natl Acad Sci U S A. .

Erratum in

Abstract

Access to robust and information-rich human cardiac tissue models would accelerate drug-based strategies for treating heart disease. Despite significant effort, the generation of high-fidelity adult-like human cardiac tissue analogs remains challenging. We used computational modeling of tissue contraction and assembly mechanics in conjunction with microfabricated constraints to guide the design of aligned and functional 3D human pluripotent stem cell (hPSC)-derived cardiac microtissues that we term cardiac microwires (CMWs). Miniaturization of the platform circumvented the need for tissue vascularization and enabled higher-throughput image-based analysis of CMW drug responsiveness. CMW tissue properties could be tuned using electromechanical stimuli and cell composition. Specifically, controlling self-assembly of 3D tissues in aligned collagen, and pacing with point stimulation electrodes, were found to promote cardiac maturation-associated gene expression and in vivo-like electrical signal propagation. Furthermore, screening a range of hPSC-derived cardiac cell ratios identified that 75% NKX2 Homeobox 5 (NKX2-5)+ cardiomyocytes and 25% Cluster of Differentiation 90 OR (CD90)+ nonmyocytes optimized tissue remodeling dynamics and yielded enhanced structural and functional properties. Finally, we demonstrate the utility of the optimized platform in a tachycardic model of arrhythmogenesis, an aspect of cardiac electrophysiology not previously recapitulated in 3D in vitro hPSC-derived cardiac microtissue models. The design criteria identified with our CMW platform should accelerate the development of predictive in vitro assays of human heart tissue function.

Keywords: arrhythmia disease model; cardiac toxicity; heart regeneration; microfabrication; tissue engineering.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Overview of experimental and computational strategies for investigating the evolution and contractility of sarcomeric filaments in cardiac microtissues. Two microtissue geometries were simulated using a finite element-based computational model: The first modeled biaxial intratissue tension forces, and the other modeled uniaxial intratissue tension forces, which we termed cardiac microwire. Simulations allowed sarcomeric α-actinin formation in all directions in the finite-element mesh. A cartoon of a representative volume element (RVE) within the finite-element mesh is provided for illustration. The nondimensional sarcomere activation level, η(ϕ), is computed in all directions (ϕ). A first-order kinetic equation governs the evolution of sarcomeric filaments, whereby filament formation is driven by a signal that decays exponentially with time. The dimensionless constants kf and kb govern the rates of formation and dissociation, respectively, of the sarcomere filaments. For additional simulation details, please see SI Appendix.
Fig. 2.
Fig. 2.
Self-assembling microtissues composed of heart cells in the ECM induce stress-mediated alignment and patterned expression of sarcomeric filaments. (A) Simulation predicts stress (represented by nondimensional effective stress; formula image) and sarcomeric expression (represented by formula image) in BITF microtissue geometry colocalizing in border regions. (B) The simulation predicts stress and sarcomeric α-actinin expression in CMW geometry along the longitudinal axis. (C) Immunostaining for sarcomeric α-actinin (green) confirms expression in border regions of BITF microtissue. (D) Immunostaining for sarcomeric α-actinin (green; Upper) and cardiac troponin T (green; Lower) in CMWs confirms sarcomere protein expression in all regions along the longitudinal axis. DAPI-stained nuclei are shown in blue.
Fig. 3.
Fig. 3.
Aligned tissue architecture can be induced by controlling ECM topography and intratissue mechanical stress. (A) Cell elongation of heart cells on pseudo-3D–aligned and unaligned collagen substrates (Left) and cell elongation of heart cells in CMWs (Right). Measurement of cell elongation is the ratio of the major axis to the minor axis of a cell. (B) Cell orientation of heart cells on pseudo-3D–aligned and unaligned collagen substrates (Left) and cell orientation of heart cells in CMWs (Right). Measurement of cell orientation on pseudo-3D substrates is relative to the direction of alignment of patterned collagen. Measurement of cell orientation in CMWs is relative to the direction of the longitudinal axis. (C and D) Fibrillar collagen content of CMWs measured with the quantitative birefringence imaging system. Pixel color corresponds to the angle of birefringent fibrillar collagen in CMWs. (Insets) Higher-magnification images. (C) CMW held taut shows unidirectionally aligned collagen. (D) Compacted CMW maintains fibrillar collagen alignment in the direction of the curl. Data are reported as the mean ± SEM. *P < 0.05 (Mann–Whitney U test).
Fig. 4.
Fig. 4.
Controlling input-population compositions of hPSC-derived heart cells guides tissue morphogenesis and levels of maturation in CMWs. (A) Flow cytometric cell-sorting plots of NKX2-5-GFP+ (cardiomyocytes) and CD90+ (fibroblasts) mixing experiments. Fluorescence-activated cell sorting of day 20 embryonic stem cell-derived embryoid bodies. EBs were dissociated and sorted for NKX2-5-GFP+ (red gate) and CD90+ (blue gate) fractions (Left). Purity control of NKX2-5-GFP+– and CD90+-sorted fractions (Right). (B) NKX2-5-GFP+ cells and CD90+ cells were sorted from hPSC–CMs and mixed at specific ratios in CMWs and aggregates. (C) CMWs composed of pure NKX2-5-GFP+ cells (CMW A) formed tissues consisting of nonintegrating globular colonies of cells (Left). Live-cell imaging of the tissues indicated that the globular areas were 3D colonies of CMs. CMWs composed of 75% NKX2-5-GFP+ cells and 25% CD90+ cells (CMW B) produced well-integrated tissue with robust architecture (Right). Bright-field live (Upper) and fluorescence images are shown (Lower). NKX2-5-GFP+ cells are shown in green. (D) Immunofluorescence micrographs of CMWs of condition CMW B are shown. (Insets) Immunofluorescence micrographs of nondissociated hESC–CM aggregates. DAPI-stained nuclei are shown in blue, NKX2-5-GFP+ cells are shown in green, and vimentin expression is shown in red. (E) Gene expression of cardiomyocyte and nonmyocyte control markers shows input-cell composition of CMWs relative to aggregates. (F) Gene expression of cardiomyocyte control markers, normalized to NKX2-5 expression, in CMWs relative to aggregates. (G) Gene expression of cardiomyocyte maturation markers, normalized to NKX2-5 expression. Conditions A, B, C, and D correspond, respectively, to 100%, 75%, 50%, and 25% NKX2-5-GFP+ cells, with the remainder consisting of CD90+ cells. Data are reported as the mean ± SEM. *P < 0.05 (Mann–Whitney U test).
Fig. 5.
Fig. 5.
Functional assessment of CMWs indicates that electrical stimulation improves electrophysiological properties. (A) Excitation threshold and (B) maximum capture rate of nondissociated hESC–CM aggregates, nonstimulated CMWs, and stimulated CMWs. (C and D) Optical mapping was used to record transmembrane action potentials and intracellular calcium transients in CMWs. (C) Mapping of transmembrane action potentials revealed that epinephrine (0.1 µg/mL), an adrenergic neurotransmitter, increased the activation rate (ii), and lidocaine (2.0 µg/mL), an antiarrhythmic drug, decreased the activation rate (iii and iv) relative to the baseline control (i). (D) Mapping of intracellular calcium transients revealed verapamil (0.25 µg/mL), an L-type Ca2+-channel blocker, reduced the amplitude of calcium waves in CMWs (ii) relative to the baseline control (i). Further supplementing with epinephrine increased the rate of calcium transients (iii). Df/f, change in fluorescence intensity relative to fluorescence intensity at baseline. Data are reported as the mean ± SEM. *P < 0.05 (Mann–Whitney U test).
Fig. 6.
Fig. 6.
CMW activation propagation is disposed to directional modulation using electrical stimulation. (A) Activation propagation of normal CMWs. Each panel depicts a time lapse of the activation propagation along the longitudinal axis of the CMW. Phase-contrast image of CMWs, isochronal map, and timescale are indicated. (B) Direction of spontaneous activation propagation of normal CMWs (Upper) can be reversed using electrical point stimulation (Lower). (C) Activation propagation of CMWs observed to be obstructed by a conduction block, resulting in an incomplete reentrant wave-like system. (D) CMWs generated using a circular substrate (CMWcirc) designed to create a ring of tissue mimicking a reentrant wave during arrhythmia. Assessment revealed spontaneous infinite loop-like cycles of activation propagation traversing the ring; one cycle is shown. Signal tracings show multiple cycles. (E) Normal rhythm was observed in CMWcirc after defibrillation. An electrical field stimulation of 10 V was used to defibrillate arrhythmias in CMWcirc geometries to a normal rhythm. Signal tracings show multiple cycles. The initiation site in blue (I*) indicates the starting location of impulse propagation, and the termination site in blue (T*) indicates the final location of impulse propagation.

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