Pseudomonas aeruginosa is an opportunistic pathogen with a large repertoire of virulence factors that allow it to cause acute and chronic infections. Treatment of P. aeruginosa infections often fail due to its antibiotic resistance mechanisms, thus novel strategies aim at targeting virulence factors instead of growth-related features. Although the elements of the virulence networks of P. aeruginosa have been identified, how they interact and influence the overall virulence regulation is unclear. In this study, we reconstructed the signaling and transcriptional regulatory networks of 12 acute and 8 chronic virulence factors, and the 4 quorum sensing systems of P. aeruginosa . Using Boolean modelling, we showed that the static interactions and the time when they take place are important features in the quorum sensing network. We also found that the virulence factors of the acute networks are under strict repression or non-strict activation, while those of most of the chronic networks are under repression. In conclusion, Boolean modelling provides a system-level view of the P. aeruginosa virulence and quorum sensing networks to gain new insights into the various mechanisms that support its pathogenicity. Thus, we suggest that Boolean modelling could be used to guide the design of new treatments against P. aeruginosa .

中文翻译：

---

使用布尔建模揭示铜绿假单胞菌群体感知和毒力网络的动力学机制。

铜绿假单胞菌是一种机会病原体，具有大量致病因子，可引起急性和慢性感染。治疗铜绿假单胞菌感染通常由于其抗生素抗性机制而失败，因此新策略旨在针对毒力因子而不是与生长相关的特征。尽管毒力网络的要素铜绿假单胞菌已经确定，它们如何相互作用和影响总体毒力调节尚不清楚。在这项研究中，我们重建了12个急性和8个慢性毒力因子的信号传导和转录调控网络，以及4个群体的群体感应系统。铜绿假单胞菌 。使用布尔建模，我们显示了静态交互及其发生的时间是群体感应网络中的重要功能。我们还发现，急性网络的毒力因子处于严格抑制或非严格激活状态，而大多数慢性网络的毒力因子处于抑制状态。总之，布尔建模提供了系统级的视图铜绿假单胞菌毒力和群体感应网络，以获取有关支持其致病性的各种机制的新见解。因此，我们建议布尔模型可用于指导针对铜绿假单胞菌 。