BioProcess Engineering Group, IIM-CSIC. Spanish National Research Council, Eduardo Cabello 6, 36208, Vigo, Spain.
Department of Mathematics, University of A Coruña, Campus Elviña s/n, 15071, A Coruña, Spain.
Nat Commun. 2019 Oct 8;10(1):4581. doi: 10.1038/s41467-019-12344-w.
Cell fate determination, the process through which cells commit to differentiated states is commonly mediated by gene regulatory motifs with mutually exclusive expression states. The classical deterministic picture for cell fate determination includes bistability and hysteresis, which enables the persistence of the acquired cellular state after withdrawal of the stimulus, ensuring a robust cellular response. However, stochasticity inherent to gene expression dynamics is not compatible with hysteresis, since the stationary solution of the governing Chemical Master Equation does not depend on the initial conditions. We provide a quantitative description of a transient hysteresis phenomenon reconciling experimental evidence of hysteretic behaviour in gene regulatory networks with inherent stochasticity: under sufficiently slow dynamics hysteresis is transient. We quantify this with an estimate of the convergence rate to the equilibrium and introduce a natural landscape capturing system's evolution that, unlike traditional cell fate potential landscapes, is compatible with coexistence at the microscopic level.
细胞命运决定是指细胞向特化状态分化的过程,通常由具有互斥表达状态的基因调控基序介导。细胞命运决定的经典确定性图景包括双稳态和滞后现象,这使得在刺激物去除后获得的细胞状态得以持续存在,从而确保了稳健的细胞反应。然而,基因表达动力学固有的随机性与滞后现象不兼容,因为控制化学主方程的定态解不依赖于初始条件。我们提供了一个定量描述瞬态滞后现象的方法,该方法调和了基因调控网络中滞后行为的实验证据与内在随机性之间的矛盾:在足够缓慢的动力学条件下,滞后现象是瞬态的。我们通过对平衡态收敛速率的估计来量化这一点,并引入了一个自然景观来捕捉系统的演化,与传统的细胞命运势景观不同,它在微观水平上是兼容共存的。