单细胞和外差群体中突发性 mRNA 表达和不可逆性的原理

James Holehouse
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摘要

mRNA 表达的典型模型是电报模型,描述的是受转录和衰变影响而开关的基因。它描述了mRNA的稳态分布,这种分布服从于具有一阶衰变的突发性转录,被称为超泊松比表达。利用类图模型,我提出了一个答案:为什么基因表达首先是突发性的?利用对熵产生率的分析,我发现当基因状态之间的开和关切换率大致相等时,熵产生率最大。这与保持系统不平衡所需的自由能下限有关,这意味着突发性基因表达的进化可能部分归因于自由能效率。研究表明,缓慢的核输出(可减少细胞质 mRNA 噪声)与保持系统平衡所需的能量之间存在权衡--核分隔带来了相关的自由能成本。在群体水平上,我发现外在变异(表现为细胞间动力学参数的差异)可以使系统具有或多或少的可逆性--以及潜在的能量效率--这取决于噪声所在的位置。这突出表明,除了分子碰撞产生的内在随机性之外,外在噪声的抑制也受到进化的制约,而外在噪声的来源是细胞的异质性。最后,我研究了大多数 mRNA 表达数据的部分观察性质,这些数据似乎遵守了详细的平衡,但仍然不可避免地处于失衡状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Principles of bursty mRNA expression and irreversibility in single cells and extrinsically varying populations
The canonical model of mRNA expression is the telegraph model, describing a gene that switches on and off, subject to transcription and decay. It describes steady-state mRNA distributions that subscribe to transcription in bursts with first-order decay, referred to as super-Poissonian expression. Using a telegraph-like model, I propose an answer to the question of why gene expression is bursty in the first place, and what benefits it confers. Using analytics for the entropy production rate, I find that entropy production is maximal when the on and off switching rates between the gene states are approximately equal. This is related to a lower bound on the free energy necessary to keep the system out of equilibrium, meaning that bursty gene expression may have evolved in part due to free energy efficiency. It is shown that there are trade-offs between having slow nuclear export, which can reduce cytoplasmic mRNA noise, and the energy required to keep the system out of equilibrium -- nuclear compartmentalization comes with an associated free energy cost. At the population level, I find that extrinsic variation, manifested in cell-to-cell differences in kinetic parameters, can make the system more or less reversible -- and potentially energy efficient -- depending on where the noise is located. This highlights that there evolutionary constraints on the suppression of extrinsic noise, whose origin is in cellular heterogeneity, in addition to intrinsic randomness arising from molecular collisions. Finally, I investigate the partially observed nature of most mRNA expression data which seems to obey detailed balance, yet remains unavoidably out-of-equilibrium.
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