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Electro-metabolic coupling in multi-chambered vascularized human cardiac organoids

Nature Biomedical Engineering volume 7, pages 1493–1513 (2023)Cite this article

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Abstract

The study of cardiac physiology is hindered by physiological differences between humans and small-animal models. Here we report the generation of multi-chambered self-paced vascularized human cardiac organoids formed under anisotropic stress and their applicability to the study of cardiac arrhythmia. Sensors embedded in the cardiac organoids enabled the simultaneous measurement of oxygen uptake, extracellular field potentials and cardiac contraction at resolutions higher than 10 Hz. This microphysiological system revealed 1 Hz cardiac respiratory cycles that are coupled to the electrical rather than the mechanical activity of cardiomyocytes. This electro-mitochondrial coupling was driven by mitochondrial calcium oscillations driving respiration cycles. Pharmaceutical or genetic inhibition of this coupling results in arrhythmogenic behaviour. We show that the chemotherapeutic mitoxantrone induces arrhythmia through disruption of this pathway, a process that can be partially reversed by the co-administration of metformin. Our microphysiological cardiac systems may further facilitate the study of the mitochondrial dynamics of cardiac rhythms and advance our understanding of human cardiac physiology.

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Fig. 1: Generation of hiPSC-derived vascularized cardiac organoids.
Fig. 2: Generation of hiPSC-derived vascularized cardiac organoids.
Fig. 3: Functional characterization of human cardiac organoids.
Fig. 4: Integrated opto-electrical sensors permit real-time simultaneous measurement of cardiac metabolism, contraction and field potential.
Fig. 5: Disruption of electro-mitochondrial coupling induces arrhythmic behaviour.
Fig. 6: CRISPR/Cas9 knockout of MCU disrupts electro-mitochondrial coupling and induces arrhythmic behaviour.
Fig. 7: Mitoxantrone inhibition of electro-mitochondrial coupling and the resultant arrhythmia are partly reversed by metformin.
Fig. 8: Validation of electro-mitochondrial coupling in an ex vivo porcine model.

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Data availability

Sequencing data are available at NCBI GEO, under the accession number GSE234907. Data for the figures are provided with this paper. All data supporting the results of this study are available within the paper and its Supplementary Information. Source data are provided with this paper.

Code availability

The custom analysis software is available at https://github.com/mohammadghosheh95/Heart-on-a-Chip.

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Acknowledgements

Funding was provided by the European Research Council Consolidator Grant OCLD (project no. 681870) and generous gifts from the Nikoh Foundation and the Sam and Rina Frankel Foundation. M.G. was supported by a Neubauer Foundation Graduate Fellowship. We thank O. Leitersdorf, Y. Kroiz, J. Gotlib, D. Viner, I. Shweky, H. Naimi, B. A. Berke, M. Ehrlich and S. Regenbaum. Figure 8a was generated using BioRender.com.

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Authors and Affiliations

  1. Alexander Grass Center for Bioengineering, The Hebrew University of Jerusalem, Jerusalem, Israel

    Mohammad Ghosheh, Avner Ehrlich, Konstantinos Ioannidis, Muneef Ayyash, Merav Cohen & Yaakov Nahmias

  2. The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel

    Mohammad Ghosheh, Avner Ehrlich, Konstantinos Ioannidis, Muneef Ayyash, Merav Cohen & Yaakov Nahmias

  3. Tissue Dynamics, LTD, Jerusalem, Israel

    Avner Ehrlich, Konstantinos Ioannidis & Yaakov Nahmias

  4. Sohnis Research Laboratory for Cardiac Electrophysiology and Regenerative Medicine, the Rappaport Faculty of Medicine and Research Institute, Technion- Israel Institute of Technology, Haifa, Israel

    Idit Goldfracht & Lior Gepstein

  5. Department of Cell and Developmental Biology, The Hebrew University of Jerusalem, Jerusalem, Israel

    Merav Cohen & Yaakov Nahmias

  6. Department of Biological Chemistry, Institute of Chemistry, The Hebrew University of Jerusalem, Jerusalem, Israel

    Amit Fischer

  7. Department of General Surgery, Hadassah Hebrew University Medical Center, Jerusalem, Israel

    Yoav Mintz

  8. Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel

    Yoav Mintz

  9. Cardiology Department, Rambam Health Care Campus, Haifa, Israel

    Lior Gepstein

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Contributions

M.G., A.E. and Y.N. conceived the hypothesis. M.G., A.E., M.A., L.G. and Y.N. designed the experiment. M.G., A.E., M.A., K.I., M.C., A.F. and Y.N. performed the experiments. Y.M. provided the porcine heart and prepared the ex-vivo heart tissue. M.G. and A.E. analysed the results. M.G., A.E. and Y.M. wrote the manuscript. M.G., A.E. and I.G. built the system. M.C., L.G. and Y.N supervised the project. All authors read the manuscript and agree with its contents.

Corresponding author

Correspondence to Yaakov Nahmias.

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Competing interests

Y.N. and A.E. are employees of Tissue Dynamics. M.G., A.E. and Y.N. filed a patent application through Hebrew University (US202163242091P; 2019, Israel). The other authors declare no competing interests.

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Nature Biomedical Engineering thanks Alessandro Prigione and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Vascular network development during cardiac organoid formation.

a, Representative time-lapse sequence confocal images depicting the formation of vascular networks in cardiac organoids formed from UN-1, ACS-1021, and ACS-1028 hiPSC-derived cardiomyocytes. Confocal microscopy shows the distribution of GFP-expressing rat microvascular cardiac endothelial cells (CECs) in the organoid. Vascular networks are apparent by day 10, stabilizing into a capillary-like network, distributed within the organoid at 25 d. UN-1 cardiac organoid images were taken from Fig.1b. Scale bar, 100 μm. b, Relative gene expression of the rat microvascular cardiac endothelial cells (CECs) and isolated rat primary endothelial cells. The CECs are showing expression signatures comparable with those of isolated rat primary endothelial cells across multiple endothelial markers. Anti-phospho-Nuclear Receptor (NR4A1), Cadherin 5 (CDH5), Von Willebrand factor (VWF), and tyrosine kinase with immunoglobulin-like and EGF-like domains 1 (TIE1) are similarly expressed among the CECs used and isolated rat primary endothelial cells.

Source data

Extended Data Fig. 2 Functional comparison of hiPSC-CMs and human cardiac organoids.

a, Principal component analysis (PCA) of 513 genes differentially expressed between hiPS-derived cardiomyocytes and vascularized cardiac organoids (methods). Cardiac organoids cluster with adult, but not fetal cardiomyocytes. b, Principal component analysis (PCA) of 513 genes differentially expressed between hiPS-derived cardiomyocytes and vascularized cardiac organoids (methods) separated into PC components. PC1 gene set is enriched for angiogenesis and cell adhesion, clustering the non-beating AC16 cell line, the negative control, with the mature heart tissue. This clearly suggests that PC1 is less relevant for comparative analysis. c, Visual contraction analysis of UN-1 vascularized cardiac organoids treated with DMSO (Control), 10 µM amiodarone, or 100 µM epinephrine (Supplementary. Video 3), normalized to the highest and lowest signal recorded through the entire measurement duration (30 seconds; methods). Analysis shows that untreated organoids acquire a homogenous synchronized spontaneous beating of 66 ± 5 beats per minute. Stimulation with 100 µM epinephrine increases the contraction rate to 88 ± 7 bpm and relative contraction by 18% (n = 5, p < 0.001), while stimulation with 10 µM amiodarone decreased the rate to 52 ± 4 bpm and contraction by 28% (n = 5, p < 0.001), resulting in a physiological-like response to the drugs. Mean of 5 biological replicates; error bars, s.e.m. Significance was determined using a one-way ANOVA with Dunnett correction. Graphs were taken from Fig. 3d. d, Visual contraction analysis of UN-1 hiPSC-derived cardiomyocytes (hiPSC-CMs) treated with DMSO (Control), 10 µM amiodarone, or 100 µM epinephrine. Analysis shows that untreated hiPSC-CMs acquire a homogenous unsynchronized beating of 97 ± 4 beats per minute. Stimulation with 100 µM epinephrine increases the contraction rate to 106 ± 4 bpm and relative contraction by 18% (n = 3, p < 0.01), while stimulation with 10 µM amiodarone decreased the rate to 92 ± 3 bpm and contraction by 28% (n = 3, p < 0.01). Mean of 3 biological replicates; error bars, s.e.m. Significance was determined using a one-way ANOVA with Dunnett correction. e, Seahorse MitoStress assay nested analysis of UN-1 cardiac organoids, UN-1 hiPSC-derived cardiomyocytes (hiPSC-CMs), and cardiac endothelial cells (CECs). CECs show basal respiration equal to 4.5% of the basal respiration of the cardiac organoids and less than 2% of maximal respiration, indicating that changes in respiration are attributed to changes in the cardiomyocytes (n = 9, p < 0.001). Significance was determined using one-way ANOVA and Dunnett multiple comparison correction. Lines represent independent experiments, Error bars mark standard error of mean among n = 3 biological repeats.

Source data

Extended Data Fig. 3 Establishment of an Integrated 2-PMT Heart-on-a-chip platform.

a, Scheme and typical measurements depicting the advantages of using a 2-PMT system over a single PMT system. The addition of the second detector (cPMT), which measures the excitation signal, reduces the noise and enables accurate measurements at sub-second resolution. The second PMT also allows an emission-independent measurement of tissue contraction (methods). b, Representative calibration measurements of the reflected signal measured by the second PMT in different displacements. Curve fitting displays a sigmoidal relationship between the emission intensity, measured by peak-to-peak voltage (VP-P), and the sensor displacement. Cardiac displacement was measured by the embedded oxygen beads inside the cardiac organoids during a contraction when the beads move at different distances from the focal point. The Sigmoidal fit shows a correlation of R-square: 0.9835 and RMSE below 4. c, Representative continuous interstitial oxygen measurements in cardiac organoids measured continuously over 10 hours. Measurements show steady recordings that are unaffected by photobleaching or system sensitivity loss at prolonged measurements. Oxygen content and oscillation were unchanged even after 10 hours of measurement.

Source data

Extended Data Fig. 4 Quantitative and dynamic analyses of contraction, field potential, and oxygen content in vascularized cardiac organoids.

a, Representative simultaneous measurements and (b) Fast Fourier Transformation (FFT) analysis of contraction, field potential, and interstitial oxygen during spontaneous beating of cardiac organoids formed from UN-1, ACS-1021, and ACS-1028 hiPSC-derived cardiomyocytes. Interstitial oxygen concentration shows oscillatory behaviour during the cardiac cycle, yielding distinct single-frequency peaks in FFT analysis correlated to the mechanical and electrical behaviour of the cardiac tissue. UN-1 cardiac organoid graphs were taken from Fig. 4f–h. Nested analysis of the organoid’s contraction and oxygen oscillation (c) frequency and (d) amplitude in UN-1, ACS-1021, and ACS-1028 cardiac organoids. Treatment with 10 μM of myosin II inhibitor Blebbistatin. Blebbistatin completely inhibits the contraction of vascularized cardiac organoids (n = 3, p < 0.001) but does not affect the field potential or oxygen oscillation (n = 3, p > 0.05). Treatment with 25 μM of Nav channel inhibitor Tetrodotoxin (TTX) resulted in a complete loss of field potential generation, the coupled mechanical contraction (n = 3, p < 0.001), and a concurrent loss of oxygen oscillations (n = 3, p < 0.001). Middle represents mean of 3 biological repeats for each line; error bars,s.e.m. Significance was determined using a two-tailed nested t-test. e, Representative graph of the interstitial oxygen behaviours in ACS-1021 cardiac organoids following treatment with 25 μM of Nav channel inhibitor Tetrodotoxin (TTX). After 7 minutes of exposure to TTX, a complete loss of field potential generation occurs, coupled with decay in oxygen oscillations (n = 3). Graph was taken from Fig. 4l. Middle represents mean of 3 biological repeats for each line; error bars,s.e.m. Significance was determined using a two-tailed nested t-test.

Source data

Extended Data Fig. 5 Real-time metabolic measurement of vascularized cardiac organoids under epinephrine stimulation.

Nested analysis of the organoid’s contraction and oxygen oscillation (a) frequency and (b) amplitude during prolonged stimulation by 100 µM epinephrine in UN-1, ACS-1021, and ACS-1028 cardiac organoids. Analysis shows that epinephrine exposure significantly increases the frequency of cardiac contraction and oxygen oscillations (n = 3, p < 0.001), and the amplitude of cardiac contraction and oxygen oscillation amplitudes (n = 3, p < 0.001). c, Analysis of the kinetic behaviour of the organoid’s contraction rate during prolonged stimulation by 100 µM epinephrine. Kinetic analysis suggests that epinephrine stimulation results in a sigmoidal-like change in the organoid contraction rate. Representative relation graphs between (d) contraction amplitude (contractility) to contraction rate, and (e) interstitial oxygen content to contraction rate during prolonged epinephrine stimulation. Analysis suggests a correlation between an increase in cardiac organoid contractility and oxygen consumption. f, Representative frequency histograms of interstitial oxygen measurements at 0, 15, and 90 minutes after stimulation with 100 µM epinephrine. Analysis shows that an increase in oxygen consumption correlates to an increase in interstitial oxygen content variability correlative to the increased oxygen amplitudes measured. Representative correlation analysis between (g) oxygen oscillation frequency to contraction frequency and (h) oxygen oscillation amplitude to contractility reveals a direct linear correlation between the oscillatory behaviour of the interstitial oxygen and organoid contraction. i, Representative graphs of the cardiac organoid’s contraction and interstitial oxygen content 60 mins prior to epinephrine stimulation and 5 hours post-stimulation with 100 µM epinephrine. Oxygen returns to the baseline value after 300 minutes, indicating hypoxia, stimulation-induced or ischemia-like injuries did not occur. Middle represents mean of 3 biological repeats for each line; error bars,s.e.m. Significance was determined using a two-tailed nested t-test.

Source data

Extended Data Fig. 6 Live mitochondrial imaging reveals oscillations in mitochondrial membrane potential.

a, Immunofluorescent micrograph of mitochondrial membrane potential measured using live imaging of TMRE dye (Supplementary. Video 2; methods). b, Kinetic analysis of mitochondrial membrane potential using TMRE. The mitochondrial membrane potential of hiPSC-derived cardiomyocytes oscillates in the frequency of contraction. The mitochondrial membrane potential of non-beating cells did not oscillate and was lower overall. Rainbow heatmaps of (c) mean mitochondrial membrane potential and (d) major oscillating frequency of (MMP) measured using TMRE (methods). The heatmaps suggest a correlation between areas with high mean mitochondrial membrane potential and oscillation frequency. e, Immunofluorescent micrograph of mitochondrial membrane potential measured using live imaging of JC-1 dye (Supplementary. Video 3; methods). f, Kinetic analysis of mitochondrial membrane potential following aggregation of JC-1 dye. Mitochondrial membrane potential showed distinct polarization peaks in contracting cells, while non-beating cells did not oscillate and show lower mitochondrial membrane potential overall. Rainbow heatmaps of (g) mean mitochondrial membrane potential and (h) major oscillating frequency of (MMP) measured using JC-1 (methods). Similar to the behaviour measured by TMRE, JC-1 heatmaps suggest a correlation between areas with high mean mitochondrial membrane potential and oscillation frequency. Scale bar, 25 μm.

Source data

Extended Data Fig. 7 CRISPR/Cas9 knockout of MCU disrupts electro-mitochondrial coupling and induces arrhythmic behaviour.

a, Kinetic measurements of mitochondrial calcium in beating 2D-cultured hiPSC-derived cardiomyocytes. Non-targeting sgRNA had no effect on [Ca2+]m showing a dominant frequency of 0.8 Hz, while MCU knockout (MCUKO) showed a 35–50% decrease in [Ca2+]m and oscillation magnitude while increasing oscillation rate to 1.3–1.4 Hz. b, Immunofluorescent confocal microscopy demonstrated a marked reduction in MCU expression in the MCU knockout (MCUKO) compared to the non-targeting control. Scale bar, 100 µm. c, Relative gene expression of the MCU gene was markedly reduced by 46% (n = 3, p < 0.001) and 27% (n = 3, p < 0.1) in the MCU knockout MCUKO cardiac organoids compared to the non-targeting cardiac organoids in ACS-1021 and UN-1 cell lines respectively. Mean of 3 biological replicates; error bars, s.e.m. d, Interstitial oxygen showed a 78% (n = 3, p < 0.001) and 126% (n = 4, p < 0.001) increase in the MCUKO cardiac organoids compared to the non-targeting organoids in ACS-1021 and UN-1 cell lines, respectively. Mean of 3 biological replicates; error bars,s.e.m. Significance was determined using a one-way ANOVA with Dunnett correction. UN-1 cardiac organoid graphs were taken from Fig. 6a.

Source data

Extended Data Fig. 8 Reduced oxygen consumption coordinated with electro-mitochondrial decoupling.

a, Representative kinetic measurements of interstitial oxygen content and mean oxygen content analysis in non-homogenous MCUKO or Non-targeting sgRNA cardiac organoids. Analysis shows a decrease in oscillation amplitude and an increase in oscillation frequency in the MCUKO organoids, coupled with an increase in mean oxygen content (n = 3, p < 0.001). Mean of 3 biological replicates; error bars,s.e.m. Significance was determined using two tailed t-test. Cardiac organoid graphs were taken from Fig. 6c. b, Representative kinetic measurements of interstitial oxygen content and mean oxygen content analysis in cardiac organoids treated with DMSO (Control), 10 μM mitoxantrone (Mitoxantrone) or 10 μM mitoxantrone, and 100 μM AMP-activated protein kinase (AMPK) activator metformin (Mitoxantrone + Metformin). Analysis shows a decrease in oscillation amplitude and an increase in oscillation frequency in the mitoxantrone-treated organoids, coupled with an increase in mean oxygen content (n = 3, p < 0.001). Metformin reverts these changes, restoring mean oxygen content to levels not significantly different than the control (n = 3, p > 0.05). Cardiac organoid graphs were taken from Fig. 6e. Mean of 3 biological replicates; error bars,s.e.m. Significance was determined using two tailed t-test. c, Representative kinetic measurements of interstitial oxygen content and mean oxygen content analysis in porcine cardiac tissue exposed to DMSO (control), 10 μM of blebbistatin, 10 µM mitoxantrone, or 10 µM mitoxantrone, and 100 μM metformin (mitoxantrone + metformin). Analysis shows that blebbistatin does not change oscillation amplitude and oscillation frequency or mean oxygen content (n = 3, p > 0.05). Mitoxantrone-treated organoids show a decrease in oscillation amplitude and an increase in oscillation frequency, coupled with an increase in mean oxygen content (n = 3, p < 0.001). Metformin partly reverts these changes, increasing mean oxygen content by 29% (n = 3, p < 0.001). Porcine cardiac tissue graphs were taken from Fig. 8d. Mean of 3 biological replicates; error bars,s.e.m. Significance was determined using one-way ANOVA with Dunnett multiple comparison correction.

Source data

Supplementary information

Supplementary Information

Supplementary figures.

Reporting Summary

Supplementary Video 1

Representative time-lapse sequence of brightfield images showing vascularized cardiac organoids during organoid formation.

Supplementary Video 2

Synchronized beating cardiac organoid embedded with oxygen sensors.

Supplementary Video 3

The effect of pharmaceutical stimulation of epinephrine and amiodarone on the contraction rate and contractility of a cardiac organoid.

Supplementary Video 4

Immunofluorescent live imaging of mitochondrial membrane-potential oscillations by TMRE stain in homogeneous beating hiPSC-derived cardiomyocytes.

Supplementary Video 5

Beating cardiac organoids under epinephrine stimulation at different timepoints.

Supplementary Video 6

MATLAB projection of the desynchronization of cardiac organoids due to MCU inhibition by KB-R7943.

Supplementary Video 7

Beating cardiac organoids embedded with oxygen sensors on an MEA chip.

Supplementary Video 8

Non-targeting CRISPR knockout cardiomyocyte wells display cardiac contractions, whereas none of the MCU CRISPR KO wells display cardiac contraction.

Supplementary Video 9

Time-lapse sequence of brightfield and fluorescent images of cardiac organoids loaded with the cell-impermeable Dextran-Texas Red.

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Ghosheh, M., Ehrlich, A., Ioannidis, K. et al. Electro-metabolic coupling in multi-chambered vascularized human cardiac organoids. Nat. Biomed. Eng 7, 1493–1513 (2023). https://doi.org/10.1038/s41551-023-01071-9

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