From unipotency to pluripotency: deciphering protein networks and signaling pathways in the generation of embryonic stem-like cells from murine spermatogonial stem cells - Ghasemi, Nima; Azizi, Hossein; Qorbanee, Ali; Skutella, Thomas (BMC genomics, 2025)
With the significant challenges in using human embryonic stem cells (ESCs) for research and clinical applications, there is a growing impetus to seek alternative pluripotent cell sources. Embryonic stem-like (ES-like) cells emerge as a promising avenue in this pursuit. Our research demonstrates the potential for deriving ES-like cells from spermatogonial stem cells (SSCs) in a time-dependent manner under defined culture conditions. To better understand this process, we investigated the gene expression dynamics and underlying pathways associated with ES-like cell generation from SSCs. A deeper understanding of the signaling pathways underlying this biological process can lead us to refine protocols for ES-like cell generation, which could catalyze the development of more efficient and expedited methodologies inspired by the derivation pathway for future research in regenerative medicine. To identify differentially expressed genes (DEGs), we analyzed publicly available microarray data from murine cells obtained from the Gene Expression Omnibus (GEO). This analysis enabled the prediction of protein-protein interactions (PPIs), which were subsequently used for pathway enrichment analysis to identify biologically relevant pathways. Complementing these computational findings, we conducted in vitro experiments, including Fluidigm qPCR and immunostaining. These experiments serve as validation for our microarray data and the DEGs identified, providing reassurance about the reliability of our research. Among the identified enriched pathways in our investigation are the Toll-like receptor (TLR), GDNF/RET, interleukins (ILs), FGF/FGFR, and SMAD signaling pathway, along with the activation of NIMA kinases. Additionally, miR-410-3p, miRNA let-7e, Miat, and Xist are among some of the predicted non-coding RNAs.