Predicting involvement of polycomb repressive complex 2 in direct conversion of mouse fibroblasts into induced neural stem cells

Abstract

Introduction: Mouse fibroblasts could be directly converted into induced neural stem cells (iNSCs), by introducing a set of known transcription factors (TFs). This process, known as direct reprogramming, is an alternative source of NSCs production for cell therapy applications, hence, more common sources for such cells including embryonic stem cell (ESCs) and induced pluripotent stem cell (iPSCs) are also in use. Despite their importance, the exact role of different TFs involved in the conversion of fibroblasts into iNSCs and the interactions between these factors has not been studied. Methods: Here, we have used available microarray data to construct a gene regulatory network to understand the dynamic of regulatory interactions during this conversion. We have implemented other types of data such as information regarding TFs binding sites and valid protein-protein interactions to improve the network reliability. The network contained 1857 differentially expressed (DE) genes, linked by11054 interactions. The most important TFs identified based on topology analysis of the network. Furthermore, in selecting such TFs, we have also considered their role in the regulation of nervous system development. Results: Based on these analyses, we found that Ezh2, Jarid2, Mtf2, Nanog, Pou5f1, Sall4, Smarca4, Sox2, Suz12, and Tcf3 are the main regulators of direct conversion of mouse fibroblasts into iNSCs. Because, members of the polycomb repressive complex 2 (PRC2) were present in the most effective TFs' list, we have concluded that this complex is one of the major factors in this conversion. Additionally, gene expression profiling of iNSCs, obtained from a different data sets, showed that Sox2 and Ezh2 are two main regulators of the direct reprogramming process. Conclusions: Our results provide an insight into molecular events that occur during direct reprogramming of fibroblasts into iNSCs. This information could be useful in simplifying the production of iNSCs, by reducing the number of required factors, for use in regenerative medicine.