A comprehensive integrative analysis of the transcriptional network underlying the zebrafish heart regeneration

Despite a notable reduction in incidence of acute myocardial infarction (MI), patients who experienced it remain at risk for premature death and cardiac malfunction. The human cardiomyocytes are not able to achieve extensive regeneration upon MI. Remarkably, the adult zebrafish is able to achieve complete heart regeneration following amputation, cryoinjury or genetic ablation. This raises new potential opportunities on how to boost heart healing capacity in humans. The objective of our research is to characterize the transcriptional network of the zebrafish heart regeneration and underlying regulatory mechanisms.
To conduct our investigation, we used microarray data from zebrafish at 6 post-cryoinjury time points (4 hours, and 1, 3, 7, 14 and 90 days) and control samples. We thereon looked for the gene co-expression patterns in the data and, based on that, constructed a weighted gene co-expression network. To detect candidate functional sub-networks (modules), we used two different network clustering approaches: a density-based (ClusterONE) and a topological overlap-based (Hybrid Dynamic Branch Cut) algorithms. The visualization of the expression changes of the candidate modules reflected the dynamics of the recovery process. Also we aimed to identify candidate “hub” genes that might regulate the behavior of the biological modules and drive the regeneration process.
We identified eighteen distinct modules associated with heart recovery upon cryoinjury. Functional enrichment analysis displayed that the modules are involved in different cellular processes crucial for heart regeneration, including: cell fate specification (p-value < 0.006) and migration (p-value < 0.047), ribosome biogenesis (p-value < 0.004), cardiac cell differentiation (p-value < 3E-04), and various signaling events (p-value < 0.037). The visualization of the modules’ expression profiles confirmed the relevance of these functional enrichments. For instance, the genes of the module involved in regulation of endodermal cell fate specification were up-regulated upon injury until 3 days. Among the candidate hub genes detected in the network, there are genes relevant to atherosclerosis treatment and inflammation during cardiac arrest. These and other findings are currently undergoing deeper computational analyses. The top promising targets will be independently validated using our zebrafish (in vivo) model.
In conclusion, our findings provide insights into the complex regulatory mechanisms involved during heart regeneration in the zebrafish. These data will be useful for modelling specific network-based responses to heart injury, and for finding sensitive network points that may trigger or boost heart regeneration.