Gene regulatory network inference and analysis of multidrug-resistant Pseudomonas aeruginosa
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Abstract
Background
Healthcare-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.
Objectives
Our goal in this manuscript is to present a reconstruction of multidrug-resistant P. aeruginosa gene regulatory network and to analyze its topological properties.
Methods
The 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.
Findings
As 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.
Main conclusions
The 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.
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Excerpt
By taking a holistic, network-based approach, the authors of this study were able to model and study a gene regulatory network for ~1000 genes in a pathogenic, multi-drug resistant strain of Pseudomonas aeruginosa.
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