Fundação Oswaldo Cruz-Fiocruz, Programa de Computação Científica, Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz-Fiocruz, Instituto Nacional de Infectologia, Laboratório de Pesquisa Clínica em Doenças Febris Agudas, Rio de Janeiro, RJ, Brasil.
Mem Inst Oswaldo Cruz. 2022 Oct 14;117:e220111. doi: 10.1590/0074-02760220111. eCollection 2022.
Healthcare-associated infections due to multidrug-resistant (MDR) bacteria such as Pseudomonas aeruginosa are significant public health issues worldwide. A system biology approach can help understand bacterial behaviour and provide novel ways to identify potential therapeutic targets and develop new drugs. Gene regulatory networks (GRN) are examples of in silico representation of interaction between regulatory genes and their targets.
In this work, we update the MDR P. aeruginosa CCBH4851 GRN reconstruction and analyse and discuss its structural properties.
We based this study on the gene orthology inference methodology using the reciprocal best hit method. The P. aeruginosa CCBH4851 genome and GRN, published in 2019, and the P. aeruginosa PAO1 GRN, published in 2020, were used for this update reconstruction process.
Our result is a GRN with a greater number of regulatory genes, target genes, and interactions compared to the previous networks, and its structural properties are consistent with the complexity of biological networks and the biological features of P. aeruginosa.
Here, we present the largest and most complete version of P. aeruginosa GRN published to this date, to the best of our knowledge.
由于铜绿假单胞菌等多药耐药（MDR）细菌引起的医疗保健相关感染是全球重大的公共卫生问题。系统生物学方法可以帮助了解细菌的行为，并提供新的方法来识别潜在的治疗靶点和开发新药。基因调控网络（GRN）是调控基因与其靶基因之间相互作用的计算表示的示例。
在这项工作中，我们更新了 MDR 铜绿假单胞菌 CCBH4851 的 GRN 重建，并对其结构特性进行了分析和讨论。
我们基于使用相互最佳命中方法的基因直系同源推断方法进行了这项研究。该研究使用了 2019 年发表的铜绿假单胞菌 CCBH4851 基因组和 GRN，以及 2020 年发表的铜绿假单胞菌 PAO1 的 GRN，进行了这次更新重建过程。
与之前的网络相比，我们的结果是一个具有更多调控基因、靶基因和相互作用的 GRN，其结构特性与生物网络的复杂性以及铜绿假单胞菌的生物学特征一致。
据我们所知，这是迄今为止发表的最大和最完整的铜绿假单胞菌 GRN。
