Vladimirov Nikita, Løvdok Linda, Lebiedz Dirk, Sourjik Victor
Interdisziplinäres Zentrum für Wissenschaftliches Rechnen, University of Heidelberg, Heidelberg, Germany.
PLoS Comput Biol. 2008 Dec;4(12):e1000242. doi: 10.1371/journal.pcbi.1000242. Epub 2008 Dec 19.
Simulation of cellular behavior on multiple scales requires models that are sufficiently detailed to capture central intracellular processes but at the same time enable the simulation of entire cell populations in a computationally cheap way. In this paper we present RapidCell, a hybrid model of chemotactic Escherichia coli that combines the Monod-Wyman-Changeux signal processing by mixed chemoreceptor clusters, the adaptation dynamics described by ordinary differential equations, and a detailed model of cell tumbling. Our model dramatically reduces computational costs and allows the highly efficient simulation of E. coli chemotaxis. We use the model to investigate chemotaxis in different gradients, and suggest a new, constant-activity type of gradient to systematically study chemotactic behavior of virtual bacteria. Using the unique properties of this gradient, we show that optimal chemotaxis is observed in a narrow range of CheA kinase activity, where concentration of the response regulator CheY-P falls into the operating range of flagellar motors. Our simulations also confirm that the CheB phosphorylation feedback improves chemotactic efficiency by shifting the average CheY-P concentration to fit the motor operating range. Our results suggest that in liquid media the variability in adaptation times among cells may be evolutionary favorable to ensure coexistence of subpopulations that will be optimally tactic in different gradients. However, in a porous medium (agar) such variability appears to be less important, because agar structure poses mainly negative selection against subpopulations with low levels of adaptation enzymes. RapidCell is available from the authors upon request.
既要有足够的细节来捕捉核心的细胞内过程，又要能以计算成本较低的方式模拟整个细胞群体。在本文中，我们提出了RapidCell，这是一种趋化性大肠杆菌的混合模型，它结合了混合化学感受器簇的莫诺德-怀曼-尚热信号处理、常微分方程描述的适应动力学以及细胞翻滚的详细模型。我们的模型显著降低了计算成本，并允许对大肠杆菌趋化性进行高效模拟。我们使用该模型研究不同梯度下的趋化性，并提出一种新的恒定活性类型的梯度，以系统地研究虚拟细菌的趋化行为。利用这种梯度的独特性质，我们表明在CheA激酶活性的狭窄范围内观察到最佳趋化性，此时响应调节因子CheY-P的浓度落入鞭毛马达的工作范围内。我们的模拟还证实，CheB磷酸化反馈通过改变平均CheY-P浓度以适应马达工作范围来提高趋化效率。我们的结果表明，在液体介质中，细胞间适应时间的变异性可能在进化上有利于确保亚群体的共存，这些亚群体在不同梯度下将具有最佳趋化性。然而，在多孔介质（琼脂）中，这种变异性似乎不太重要，因为琼脂结构主要对适应酶水平低的亚群体进行负选择。如有需要，可向作者索取RapidCell。
