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Design principles of a bacterial signalling network

机译:细菌信号网络的设计原理

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摘要

Cellular biochemical networks have to function in a noisy environment using imperfect components. In particular, networks involved in gene regulation or signal transduction allow only for small output tolerances, and the underlying network structures can be expected to have undergone evolution for inherent robustness against perturbations. Here we combine theoretical and experimental analyses to investigate an optimal design for the signalling network of bacterial chemotaxis, one of the most thoroughly studied signalling networks in biology. We experimentally determine the extent of intercellular variations in the expression levels of chemotaxis proteins and use computer simulations to quantify the robustness of several hypothetical chemotaxis pathway topologies to such gene expression noise. We demonstrate that among these topologies the experimentally established chemotaxis network of Escherichia coli has the smallest sufficiently robust network structure, allowing accurate chemotactic response for almost all individuals within a population. Our results suggest that this pathway has evolved to show an optimal chemotactic performance while minimizing the cost of resources associated with high levels of protein expression. Moreover, the underlying topological design principles compensating for intercellular variations seem to be highly conserved among bacterial chemosensory systems.
机译:细胞生化网络必须使用不完善的成分在嘈杂的环境中发挥作用。特别地,参与基因调控或信号转导的网络仅允许较小的输出公差,并且可以预期基础网络结构已经发生了演变,以具有固有的抵抗干扰的鲁棒性。在这里,我们结合理论和实验分析来研究细菌趋化性信号网络的最佳设计,细菌趋化性是生物学中研究最深入的信号网络之一。我们实验确定趋化蛋白表达水平的细胞间变化的程度,并使用计算机模拟来量化几种假设的趋化途径拓扑结构对这种基因表达噪声的鲁棒性。我们证明,在这些拓扑结构中,实验建立的大肠杆菌趋化性网络具有最小的足够健壮的网络结构,从而允许人口中几乎所有个体的准确趋化性反应。我们的结果表明,该途径已经进化为显示出最佳的趋化性能,同时将与高水平蛋白质表达相关的资源成本降至最低。此外,补偿细胞间变异的基础拓扑设计原理在细菌化学感应系统中似乎是高度保守的。

著录项

  • 来源
    《Nature》 |2005年第7067期|p.504-507|共4页
  • 作者单位

    Institut fuer Physik, Universitaet Freiburg, Hermann-Herder-Str. 3, D-79104 Freiburg, Germany;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自然科学总论;
  • 关键词

  • 入库时间 2022-08-18 02:56:53

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