Dependence of bacterial chemotaxis on gradient shape and adaptation rate.
Dependence of bacterial chemotaxis on gradient shape and adaptation rate.
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DOI：
10.1371/journal.pcbi.1000242
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发表时间：
2008-12
影响因子：
4.3
通讯作者：
Sourjik, Victor
中科院分区：
文献类型：
--
作者：
Vladimirov, Nikita;Lovdok, Linda;Lebiedz, Dirk;Sourjik, Victor
在多个尺度上模拟细胞行为需要足够详细的模型来捕捉中央细胞内过程，但同时又能够以计算成本较低的方式模拟整个细胞群体。在本文中，我们提出了一种趋化性大肠杆菌的混合模型RapidCell，它结合了混合化学感受器簇对Monod-Wyman-Changeux信号的处理，用常微分方程组描述了适应动力学，以及一个详细的细胞翻滚模型。我们的模型极大地降低了计算成本，并允许高效地模拟大肠杆菌的趋化性。我们使用该模型研究了不同梯度下的趋化性，并提出了一种新的恒活性梯度类型来系统地研究虚拟细菌的趋化性行为。利用这种梯度的独特性质，我们发现在Chea激酶活性的狭窄范围内观察到最佳的趋化作用，其中反应调节因子Chey-P的浓度落在鞭毛发动机的工作范围内。我们的模拟也证实，CHEB磷酸化反馈通过改变平均Chey-P浓度来适应电机的工作范围，从而提高了趋化效率。我们的结果表明，在液体介质中，细胞间适应时间的差异性可能有利于确保在不同梯度下最优策略的亚群共存。然而，在多孔介质(琼脂)中，这种可变性似乎不那么重要，因为琼脂结构主要对适应酶水平较低的亚群进行负选择。如有需要，可从作者处获得RapidCell。趋化性在细菌的生活方式中扮演着重要的角色，为细菌提供了主动寻找最佳生长环境的能力。趋化系统很可能是高度优化的，因为在进化的时间尺度上，即使是其效率的适度提高也可以给细胞带来很大的竞争优势。在这项研究中，我们使用最新的实验和建模信息来构建一个新的趋化性大肠杆菌的计算模型，并以一种计算高效的方式实现它来模拟大型细菌种群。我们的模拟是在一种新型的吸引剂梯度中进行的，这种梯度确保了在任何位置都有恒定的趋化激发水平。我们发现在梯度中最佳的趋化运动是在兴奋和适应之间的微妙平衡的结果。因此，更陡峭的梯度需要更高的最佳适应速度。模拟表明，由基因表达噪声引起的适应时间的细胞间可变性，可能对细菌种群作为一个整体起到积极的作用，因为它允许其亚群在不同强度的梯度中处于最优策略。我们进一步表明，在多孔介质(琼脂)中的最佳趋化性与在液体中的不同。
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. Chemotaxis plays an important role in bacterial lifestyle, providing bacteria with the ability to actively search for an optimal growth environment. The chemotaxis system is likely to be highly optimized, because on the evolutionary time scale even a modest enhancement of its efficiency can give cells a large competitive advantage. In this study, we use up-to-date experimental and modeling information to construct a new computational model of chemotactic E. coli and implement it in a computationally efficient way to simulate large bacterial populations. Our simulations are performed in a new type of attractant gradient that ensures a constant level of chemotactic excitation at any position. We show that optimal chemotactic movement in a gradient results from a fine balance between excitation and adaptation. As a consequence, steeper gradients require higher optimal rates of adaptation. Simulations demonstrate that the observed intercellular variability of adaptation times, which is caused by gene expression noise, may play a positive role for the bacterial population as a whole, by allowing its subpopulations to be optimally tactic in gradients of different strengths. We further show that optimal chemotactic properties in a porous medium (agar) are different from those in a liquid.
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影响因子：
64.8
作者：
Alon, U;Surette, MG;Leibler, S
通讯作者：
Leibler, S
影响因子：
64.8
作者：
Barkai, N;Leibler, S
通讯作者：
Leibler, S
影响因子：
3.3
作者：
BRAY, D;BOURRET, RB
通讯作者：
BOURRET, RB
DOI：
10.1073/pnas.0603101103
发表时间：
2006-08-29
影响因子：
11.1
作者：
Endres, Robert G.;Wingreen, Ned S.
通讯作者：
Wingreen, Ned S.
影响因子：
3.2
作者：
BLOCK, SM;SEGALL, JE;BERG, HC
通讯作者：
BERG, HC