| Popis: |
Several studies have suggested that induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) and human embryonic stem cell-derived cardiomyocytes (hESC-CM) are sufficiently comparable to adult myocardium to facilitate application in a wide range of toxicology, drug development and disease modelling applications. Evidence from the literature is however, inconstant. We tested the hypothesis that iPSC-CM and hESC-CM have a predictable and consistent response to pharmacological manipulation, finding in many instances this was not true. We then focused on methods to improve the maturity of iPSC-CM, in particular, on the effect of cell alignment on intra-cellular Ca2+ cycling. For much of the exploratory work and validation of the techniques we used neonatal rat ventricular myocytes (NRVM). They are more readily available than iPSC-CM and have similar properties. We hypothesized that cell alignment of immature cardiomyocytes, in a fashion analogous to the adult myocardium, would improve the speed of intra-cellular Ca2+ cycling. We found that structured culture modulated Ca2+ cycling in iPSC-CM, and that this was probably due to improvements in sarcoplasmic reticulum Ca2+ release mechanisms. In contrast to NRVM, structured culture did not appear to have a significant effect on Ca2+ extrusion mechanisms in iPSC-CM. Furthermore, we found that the physical properties of the constructs made it difficult to fully explore the mechanisms underlying these experimental findings. Consequently, we developed and validated novel constructs which would facilitate exploration of the mechanisms underlying the association between cell-alignment and the functional properties of immature cardiomyocytes. These findings suggest that tissue engineering approaches are likely to be relevant to in vitro modelling with iPSC-CM. An important next step will be to conclusively demonstrate that these techniques overcome the limitations of iPSC-CM highlighted in the first part of this thesis, and improve their efficacy for myocardial disease modelling. |
