熵驱动的细胞决策预测多细胞系统中的流体到固体转变
Entropy-driven cell-decision making predicts fluid-to-solid transition in multicellular systems
摘要：
细胞决策使细胞能够在没有遗传变化的情况下，根据微环境线索呈现功能不同的表型。这是一个悬而未决的问题，如何个别细胞的决定影响在组织水平的动态。在这里，我们研究时空斑图形成在一个人口的细胞表现出表型可塑性，这是一个范例的细胞决策。我们专注于迁移/休息和迁移/增殖的可塑性，这是上皮间质转化（EMT）和去或生长二分法的基础。我们假设细胞改变其表型，以最小化其微环境熵（LEUP：最小微环境不确定原理）和研究的影响LEUP驱动的迁移/休息和迁移/增殖可塑性相应的多细胞时空动态与随机细胞为基础的数学模型的时空动态的细胞表型。在去或休息可塑性的情况下，相应的平均场近似允许识别扩散（流体）和上皮（固体）组织相之间的转换机制，这取决于表型对环境的敏感性。对于去或生长的可塑性，我们表明图灵斑图形成的“固体”组织相的可能性和它的关系与LEUP驱动的细胞决定的参数。
英文摘要：
Cellular decision making allows cells to assume functionally different phenotypes in response to microenvironmental cues, without genetic change. It is an open question, how individual cell decisions influence the dynamics at the tissue level. Here, we study spatio-temporal pattern formation in a population of cells exhibiting phenotypic plasticity, which is a paradigm of cell decision making. We focus on the migration/resting and the migration/proliferation plasticity which underly the epithelial-mesenchymal transition (EMT) and the go or grow dichotomy. We assume that cells change their phenotype in order to minimize their microenvironmental entropy (LEUP: Least microEnvironmental Uncertainty Principle) and study the impact of the LEUP-driven migration/resting and migration/proliferation plasticity on the corresponding multicellular spatio-temporal dynamics with a stochastic cell-based mathematical model for the spatio-temporal dynamics of the cell phenotypes. In the case of the go or rest plasticity, a corresponding mean-field approximation allows to identify a bistable switching mechanism between a diffusive (fluid) and an epithelial (solid) tissue phase which depends on the sensitivity of the phenotypes to the environment. For the go or grow plasticity, we show the possibility of Turing pattern formation for the "solid" tissue phase and its relation with the parameters of the LEUP-driven cell decisions.
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