A dynamical model for the low efficiency of induced pluripotent stem cell reprogramming

• Main Authors: Abdallah, Hussein M. (Contributor), Qian, Yili (Contributor), Del Vecchio, Domitilla (Contributor)
• Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers (IEEE), 2017-04-05T14:43:47Z.
• Subjects: Article
• Online Access: Get fulltext

 In the past decade, researchers have been able to obtain pluripotent stem cells directly from an organism's differentiated cells through a process called cell reprogramming. This opens the way to potentially groundbreaking applications in regenerative and personalized medicine, in which ill patients could use self-derived induced pluripotent stem (iPS) cells where needed. While the process of reprogramming has been shown to be possible, its efficiency remains so low after almost ten years since its conception as to render its applicability limited to laboratory research. In this paper, we study a mathematical model of the core transcriptional circuitry among a set of key transcription factors, which is thought to determine the switch among pluripotent and early differentiated cell types. By employing standard tools from dynamical systems theory, we analyze the effects on the system's dynamics of overexpressing the core factors, which is what is performed during the reprogramming process. We demonstrate that the structure of the system is such that it can render the switch from an initial stable steady state (differentiated cell type) to the desired stable steady state (pluripotent cell type) highly unlikely. This finding provides insights into a possible reason for the low efficiency of current reprogramming approaches. We also suggest a strategy for improving the reprogramming process that employs simultaneous overexpression of one transcription factor along with enhanced degradation of another.