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arXiv 1004.4986q-bio.CB
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大肠杆菌的趋化反应和适应动力学

Chemotactic response and adaptation dynamics in Escherichia coli

Diana Clausznitzer, Olga Oleksiuk, Linda Lovdok, Victor Sourjik, Robert G. Endres

摘要:

大肠杆菌的趋化性感觉通路的适应对于在广泛的背景浓度范围内检测化学物质是不可或缺的,最终允许细胞游向引诱剂的来源并远离驱避剂。其生化机制基于化学感受器的甲基化和去甲基化早已被人们所知。尽管适应对细胞记忆和行为的重要性,适应的动力学很难与当前精确适应的模型相协调。在这里,我们遵循的时间进程的信号在响应浓度阶跃变化的引诱剂使用体内荧光共振能量转移测量。具体来说,我们使用的适应时间课程的有效评估不同的适应模型的压缩表示。为了定量地解释这些数据,我们最后开发了一个动态模型,信号和适应的基础上吸引流在实验中,信号合作受体复合物,和多层的反馈调节适应。我们通过实验证实了改变酶表达水平和绕过去甲基化负反馈的预测效果。我们的数据分析表明,在适应大的增加显着的不精确性。此外,我们的模型预测高度调节,超快的适应,以响应吸引剂的去除,这可能是有用的细胞的快速重定向和适应中的噪声减少。

英文摘要:

Adaptation of the chemotaxis sensory pathway of the bacterium Escherichia coli is integral for detecting chemicals over a wide range of background concentrations, ultimately allowing cells to swim towards sources of attractant and away from repellents. Its biochemical mechanism based on methylation and demethylation of chemoreceptors has long been known. Despite the importance of adaptation for cell memory and behavior, the dynamics of adaptation are difficult to reconcile with current models of precise adaptation. Here, we follow time courses of signaling in response to concentration step changes of attractant using in vivo fluorescence resonance energy transfer measurements. Specifically, we use a condensed representation of adaptation time courses for efficient evaluation of different adaptation models. To quantitatively explain the data, we finally develop a dynamic model for signaling and adaptation based on the attractant flow in the experiment, signaling by cooperative receptor complexes, and multiple layers of feedback regulation for adaptation. We experimentally confirm the predicted effects of changing the enzyme-expression level and bypassing the negative feedback for demethylation. Our data analysis suggests significant imprecision in adaptation for large additions. Furthermore, our model predicts highly regulated, ultrafast adaptation in response to removal of attractant, which may be useful for fast reorientation of the cell and noise reduction in adaptation.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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