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介观化学系统中的离散诱导浓度反转。

Discreteness-induced concentration inversion in mesoscopic chemical systems.

机构信息

MOSAIC Group, Institute of Theoretical Computer Science, ETH Zurich, 8092 Zurich, Switzerland.

出版信息

Nat Commun. 2012 Apr 10;3:779. doi: 10.1038/ncomms1775.

Abstract

Molecular discreteness is apparent in small-volume chemical systems, such as biological cells, leading to stochastic kinetics. Here we present a theoretical framework to understand the effects of discreteness on the steady state of a monostable chemical reaction network. We consider independent realizations of the same chemical system in compartments of different volumes. Rate equations ignore molecular discreteness and predict the same average steady-state concentrations in all compartments. However, our theory predicts that the average steady state of the system varies with volume: if a species is more abundant than another for large volumes, then the reverse occurs for volumes below a critical value, leading to a concentration inversion effect. The addition of extrinsic noise increases the size of the critical volume. We theoretically predict the critical volumes and verify, by exact stochastic simulations, that rate equations are qualitatively incorrect in sub-critical volumes.

摘要

分子离散性在小体积化学系统中表现明显,如生物细胞,导致随机动力学。在这里,我们提出了一个理论框架来理解离散性对单稳化学反应网络稳态的影响。我们考虑了相同化学系统在不同体积隔室中的独立实现。速率方程忽略了分子离散性,并预测了所有隔室中相同的平均稳态浓度。然而,我们的理论预测到系统的平均稳态随体积而变化:如果一种物质在大体积中比另一种物质更丰富,那么在体积低于临界值时则相反,导致浓度反转效应。外加噪声的增加会增加临界体积的大小。我们从理论上预测了临界体积,并通过精确的随机模拟验证了在亚临界体积中速率方程是定性错误的。

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