Decision making is essential for cell functions and realized through many underlying cellular processes, such as signaling, gene regulation, the development and differentiation in viruses, bacteria, yeast, metazoans, and mammals. Understanding the cell decision making for differentiation and reprograming, the biological process from a multi-potent stem or progenitor state to a mature cell and back, is crucial not only for uncovering the underlying mechanisms but also for the practice of tissue regeneration. Despite significant efforts and progress made in this field, there are still major challenges in the stem cell fate decision making: (1) how to define the cell states and cell fates and how to uncover the physical mechanism and dynamics of decision making; (2) how to quantify the differentiation and reprograming paths for the fate decision process; (3) how to identify key factors determining the cell fates; (4) what are the effects of epigenetics, micro RNAs and cell-cell communications on differentiation and reprograming; and (5) how is the study related to the reprograming and practice of tissue regeneration. Addressing these issues is the goal of this project and specifically the quantification of the stem cell fate decision making process, which is still difficult so far due in part to the lack of a quantitative physical theory as the foundation.
This project will meet these challenges through developing a physical landscape and flux theory for stem cell decision making. There are three aims. In Aim 1 the PI will develop the landscape and flux theory of stem cell differentiation and reprograming, and quantify cell states, dynamical rates, kinetic paths, and key regulations of the stem cell decision making process. In Aim 2, the PI will apply the theory to a core gene network of the stem cell differentiation in embryo development. He will further explore the mechanism of differentiation and reprograming. He will explore the effects of epigenetics through slow regulatory binding on differentiation and reprograming by modeling and experiments. In Aim 3, the PI will apply this theory to a realistic network for stem cell differentiation and reprograming involved in embryo development. He will quantify the underlying landscape topography, dynamical rates and paths, taking into consideration epigenetics, micro RNAs and cell-cell communications. He will also predict key genes and regulations for the stem cell fates and decision making process essential for reprogramming, which can be verified from experiments. This has potential applications on reprograming and tissue engineering.
This project is being jointly supported by the Physics of Living Systems program in the Division of Physics and the Systems and Synthetic Biology Cluster in the Division of Molecular and Cellular Biosciences.
