A new study published in Cell Research reports on Apr. 8 that scientists have identified a key protein, GSK3α, which acts as a checkpoint controlling the identity of various stem cells across different developmental stages. The research was led by Qi-Long Ying at the University of Southern California and Guang Hu at the National Institute of Environmental Health Sciences, part of the National Institutes of Health.
The discovery is significant because it advances understanding in stem cell biology and could improve how scientists maintain stem cells in laboratories. Maintaining stable stem cells is essential for studying development, modeling diseases, testing drugs, developing therapies, and regenerating tissues.
Researchers found that GSK3α serves as a shared "stemness checkpoint" among several types of mouse stem cells—embryonic stem cells (mESCs) and epiblast stem cells (mEpiSCs)—which usually require different laboratory conditions to keep their identities. By inhibiting GSK3α, both mESCs and mEpiSCs were able to multiply and maintain their identities even when grown together for over a month. The team also demonstrated that this mechanism applies to other types like neural and formative stem cells.
Further experiments showed that this checkpoint function extends beyond mice to rats, rabbits, cows, and humans. This suggests that GSK3α has a fundamental role across species.
"We already knew that blocking differentiation is essential for maintaining stem cells," said Qi-Long Ying. "What this study shows is that there are specific checkpoints controlling this process, and that these checkpoints are shared across different stem cell states." He added: "This study suggests that stem cell aging may, in part, reflect the progressive activation of differentiation checkpoints... Controlling these checkpoints could provide a new strategy for maintaining tissue health over time."
Guang Hu said: "More broadly, the work establishes a new framework for understanding stem cell regulation across development and disease, with potential applications in regenerative medicine, disease modeling and cancer research." The work received funding from several NIH grants as well as private foundations.
