重编程
细胞命运测定
效力
细胞分化
细胞生物学
生物
机制(生物学)
细胞
生物系统
化学
体外
基因
物理
生物化学
转录因子
量子力学
作者
Hanshuang Li,Chunshen Long,Hong Yan,Liaofu Luo,Yongchun Zuo
出处
期刊:Research
[AAAS00]
日期:2023-01-01
卷期号:6
被引量:7
标识
DOI:10.34133/research.0118
摘要
The precise characterization of cellular differentiation potency remains an open question, which is fundamentally important for deciphering the dynamics mechanism related to cell fate transition. We quantitatively evaluated the differentiation potency of different stem cells based on the Hopfield neural network (HNN). The results emphasized that cellular differentiation potency can be approximated by Hopfield energy values. We then profiled the Waddington energy landscape of embryogenesis and cell reprogramming processes. The energy landscape at single-cell resolution further confirmed that cell fate decision is progressively specified in a continuous process. Moreover, the transition of cells from one steady state to another in embryogenesis and cell reprogramming processes was dynamically simulated on the energy ladder. These two processes can be metaphorized as the motion of descending and ascending ladders, respectively. We further deciphered the dynamics of the gene regulatory network (GRN) for driving cell fate transition. Our study proposes a new energy indicator to quantitatively characterize cellular differentiation potency without prior knowledge, facilitating the further exploration of the potential mechanism of cellular plasticity.
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