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一种多态动力学过程赋予生物纳米机器机械适应性。

A multi-state dynamic process confers mechano-adaptation to a biological nanomachine.

机构信息

Department of Physics, Arizona State University, Tempe, AZ, 85287, USA.

Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ, 85287, USA.

出版信息

Nat Commun. 2022 Sep 10;13(1):5327. doi: 10.1038/s41467-022-33075-5.

Abstract

Adaptation is a defining feature of living systems. The bacterial flagellar motor adapts to changes in the external mechanical load by adding or removing torque-generating (stator) units. But the molecular mechanism behind this mechano-adaptation remains unclear. Here, we combine single motor eletrorotation experiments and theoretical modeling to show that mechano-adaptation of the flagellar motor is enabled by multiple mechanosensitive internal states. Dwell time statistics from experiments suggest the existence of at least two bound states with a high and a low unbinding rate, respectively. A first-passage-time analysis of a four-state model quantitatively explains the experimental data and determines the transition rates among all four states. The torque generated by bound stator units controls their effective unbinding rate by modulating the transition between the bound states, possibly via a catch bond mechanism. Similar force-mediated feedback enabled by multiple internal states may apply to adaptation in other macromolecular complexes.

摘要

适应是生命系统的一个决定性特征。细菌鞭毛马达通过添加或去除产生扭矩的(定子)单元来适应外部机械负载的变化。但是,这种机械适应的分子机制尚不清楚。在这里,我们结合单个马达电动旋转实验和理论模型表明,鞭毛马达的机械适应性是由多个机械敏感的内部状态实现的。来自实验的停留时间统计数据表明,至少存在两个具有高和低解结合率的束缚状态。对四态模型的首次通过时间分析定量解释了实验数据,并确定了所有四个状态之间的转变速率。绑定定子单元产生的扭矩通过调节绑定状态之间的转变来控制它们的有效解结合率,这可能是通过一种捕获键机制。类似的由多个内部状态提供的力介导反馈可能适用于其他大分子复合物的适应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca9a/9464220/67a43c9e6432/41467_2022_33075_Fig1_HTML.jpg

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