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首页> 外文期刊>BioSystems >Escherichia coli autoinducer-2 uptake network does not display hysteretic behavior but AI-2 synthesis rate controls transient bifurcation
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Escherichia coli autoinducer-2 uptake network does not display hysteretic behavior but AI-2 synthesis rate controls transient bifurcation

机译:大肠杆菌autoinducer-2摄取网络未显示迟滞行为,但AI-2合成速率控制瞬时分叉

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Analysis of different architectures of quorum sensing networks has been the center of attention in recent times. The approach employs mathematical models to uncover the factors behind the dynamics. Quorum sensing networks mostly display autoregulation such as Pseudomonas aeruginosa and Vibrio cholerae. However, Escherichia coli autoinducer-2 (AI-2) synthesis does not display autoinduction (i.e. autoregulation). This and other features have raised questions about the actual function of AI-2 inside the cell. In this paper we propose a model for lsr operon regulation which explains or at least is consistent with AI-2 uptake in E. coli. The model was employed to determine the main factors that control the concentration of the signal and the uptake activation. We investigated deterministic and stochastic variants of the network model and we found no states that could lead to the typical bistability in quorum sensing systems. However, stochastic simulations predict a transient bifurcation (positively regulated by AI-2 synthesis) that could provide some advantage in adapting to new environments. LsrR inactivation was found to play a crucial role in the uptake activation compared to AI-2 synthesis, lsr transcription and AI-2 excretion. Our hypothesis is that positive regulation of the level of expression is the main factor in understanding the function of the lsr operon. This is in contrast to the conventionally held belief that the main factor is the onset of activation.
机译:对群体感应网络的不同体系结构的分析已成为近来关注的焦点。该方法采用数学模型来揭示动力学背后的因素。群体感应网络主要显示自动调节功能,例如铜绿假单胞菌和霍乱弧菌。但是,大肠杆菌自动诱导剂2(AI-2)的合成不显示自动诱导(即自动调节)。此功能和其他功能引发了有关AI-2实际功能的疑问。在本文中,我们提出了lsr操纵子调控模型,该模型可以解释或至少与AI-2在大肠杆菌中的摄取一致。该模型用于确定控制信号浓度和摄取激活的主要因素。我们研究了网络模型的确定性和随机变体,没有发现可能导致群体感应系统中典型双稳态的状态。但是,随机模拟预测会出现瞬时分叉(由AI-2合成积极调节),这可能会在适应新环境方面提供一些优势。与AI-2合成,lsr转录和AI-2排泄相比,发现LsrR失活在摄取激活中起关键作用。我们的假设是,表达水平的正调控是了解lsr操纵子功能的主要因素。这与传统上认为主要因素是激活的开始相反。

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