Gene regulatory network inference and analysis of multidrug-resistant Pseudomonas aeruginosa

Abstract

BackgroundHealthcare-associated infections caused by bacteria such as Pseudomonas aeruginosa are a major public health problem worldwide. Gene regulatory networks computationally represent interactions among regulatory genes and their targets, an important approach to understand bacterial behavior and to provide novel ways of overcoming scientific challenges, including the identification of potential therapeutic targets and the development of new drugs.\n\nObjectivesOur goal in this manuscript is to present a reconstruction of multidrug-resistant P. aeruginosa gene regulatory network and to analyze its topological properties.\n\nMethodsThe methodology was based on gene orthology inference by the reciprocal best hit method. We used the genome of P. aeruginosa CCBH4851 as the basis of the reconstruction process. This multidrug-resistant strain is representative of an endemic outbreak in Brazilian territory belonging to ST277.\n\nFindingsAs the main finding, we obtained a network with a larger number of regulatory genes, target genes and interactions compared to previous work. Topological analysis results are accordant to the complex network representation of biological processes.\n\nMain conclusionsThe network properties are consistent with P. aeruginosa biological features. To the best of our knowledge, the P. aeruginosa gene regulatory network presented here is the most complete version available to date.