Regulation of APD and Force by the Na + /Ca 2+ Exchanger in Human-Induced Pluripotent Stem Cell-Derived Engineered Heart Tissue.
Djemail IsmailiKatrin GurrAndrás HorváthLei YuanMarc D LemoineCarl SchulzJascha SaniJohannes PetersenHermann ReichenspurnerPaulus F KirchhofThomas JespersenThomas EschenhagenArne HansenJussi T KoivumäkiTorsten ChristPublished in: Cells (2022)
The physiological importance of NCX in human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) is not well characterized but may depend on the relative strength of the current, compared to adult cardiomyocytes, and on the exact spatial arrangement of proteins involved in Ca 2+ extrusion. Here, we determined NCX currents and its contribution to action potential and force in hiPSC-CMs cultured in engineered heart tissue (EHT). The results were compared with data from rat and human left ventricular tissue. The NCX currents in hiPSC-CMs were larger than in ventricular cardiomyocytes isolated from human left ventricles (1.3 ± 0.2 pA/pF and 3.2 ± 0.2 pA/pF for human ventricle and EHT, respectively, p < 0.05). SEA0400 (10 µM) markedly shortened the APD 90 in EHT (by 26.6 ± 5%, p < 0.05) and, to a lesser extent, in rat ventricular tissue (by 10.7 ± 1.6%, p < 0.05). Shortening in human left ventricular preparations was small and not different from time-matched controls (TMCs; p > 0.05). Force was increased by the NCX block in rat ventricle (by 31 ± 5.4%, p < 0.05) and EHT (by 20.8 ± 3.9%, p < 0.05), but not in human left ventricular preparations. In conclusion, hiPSC-CMs possess NCX currents not smaller than human left ventricular tissue. Robust NCX block-induced APD shortening and inotropy makes EHT an attractive pharmacological model.
Keyphrases
- endothelial cells
- left ventricular
- high glucose
- heart failure
- induced pluripotent stem cells
- oxidative stress
- hypertrophic cardiomyopathy
- acute coronary syndrome
- percutaneous coronary intervention
- cardiac resynchronization therapy
- drug induced
- climate change
- coronary artery
- deep learning
- protein kinase
- data analysis
- human health