College of Professional Studies, The George Washington University, Washington, DC, United States of America.
PLoS Comput Biol. 2011 Sep;7(9):e1002172. doi: 10.1371/journal.pcbi.1002172. Epub 2011 Sep 29.
Quorum sensing (QS) enables bacterial multicellularity and selective advantage for communicating populations. While genetic "switching" phenomena are a common feature, their mechanistic underpinnings have remained elusive. The interplay between circuit components and their regulation are intertwined and embedded. Observable phenotypes are complex and context dependent. We employed a combination of experimental work and mathematical models to decipher network connectivity and signal transduction in the autoinducer-2 (AI-2) quorum sensing system of E. coli. Negative and positive feedback mechanisms were examined by separating the network architecture into sub-networks. A new unreported negative feedback interaction was hypothesized and tested via a simple mathematical model. Also, the importance of the LsrR regulator and its determinant role in the E. coli QS "switch", normally masked by interfering regulatory loops, were revealed. Our simple model allowed mechanistic understanding of the interplay among regulatory sub-structures and their contributions to the overall native functioning network. This "bottom up" approach in understanding gene regulation will serve to unravel complex QS network architectures and lead to the directed coordination of emergent behaviors.
群体感应(QS)使细菌具有多细胞性和群体通信的选择优势。虽然遗传“开关”现象是一个常见的特征,但它们的机制基础仍然难以捉摸。电路组件及其调节之间的相互作用是交织和嵌入的。可观察的表型是复杂的,依赖于上下文。我们采用实验工作和数学模型相结合的方法,解析大肠杆菌中自动诱导物-2(AI-2)群体感应系统的网络连接和信号转导。通过将网络架构分为子网,研究了负反馈和正反馈机制。通过一个简单的数学模型,假设并测试了一种新的未报道的负反馈相互作用。还揭示了 LsrR 调节剂的重要性及其在大肠杆菌 QS“开关”中的决定性作用,通常被干扰的调节环所掩盖。我们的简单模型允许对调节子结构之间的相互作用及其对整体原生功能网络的贡献进行机械理解。这种理解基因调控的“自下而上”方法将有助于揭示复杂的 QS 网络架构,并导致新兴行为的定向协调。