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具有增殖效应的细胞分化的能量景观分解

Energy landscape decomposition for cell differentiation with proliferation effect.

作者信息

Shi Jifan, Aihara Kazuyuki, Li Tiejun, Chen Luonan

机构信息

Research Institute of Intelligent Complex Systems, Fudan University, Shanghai 200433, China.

International Research Center for Neurointelligence, The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Tokyo 113-0033, Japan.

出版信息

Natl Sci Rev. 2022 Jun 17;9(8):nwac116. doi: 10.1093/nsr/nwac116. eCollection 2022 Aug.

Abstract

Complex interactions between genes determine the development and differentiation of cells. We establish a landscape theory for cell differentiation with proliferation effect, in which the developmental process is modeled as a stochastic dynamical system with a birth-death term. We find that two different energy landscapes, denoted and , collectively contribute to the establishment of non-equilibrium steady differentiation. The potential is known as the energy landscape leading to the steady distribution, whose metastable states stand for cell types, while indicates the differentiation direction from pluripotent to differentiated cells. This interpretation of cell differentiation is different from the previous landscape theory without the proliferation effect. We propose feasible numerical methods and a mean-field approximation for constructing landscapes and . Successful applications to typical biological models demonstrate the energy landscape decomposition's validity and reveal biological insights into the considered processes.

摘要

基因之间的复杂相互作用决定了细胞的发育和分化。我们建立了一个具有增殖效应的细胞分化景观理论,其中发育过程被建模为一个带有生死项的随机动力系统。我们发现,两种不同的能量景观,分别记为 和 ,共同促成了非平衡稳态分化的建立。势 被称为导致稳态分布的能量景观,其亚稳态代表细胞类型,而 则表示从多能细胞到分化细胞的分化方向。这种对细胞分化的解释与先前没有增殖效应的景观理论不同。我们提出了构建景观 和 的可行数值方法和平均场近似。对典型生物学模型的成功应用证明了能量景观分解的有效性,并揭示了对所考虑过程的生物学见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5aa1/9385468/3f5e4be3c3d0/nwac116fig1.jpg

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