Identification of Key Genetic Drivers in Multidrug Resistance: A Co-Expression Network Analysis of Pseudomonas aeruginosa

Antimicrobial resistance (AMR) in Pseudomonas aeruginosa, a critical pathogen in healthcare-associated infections, demands new insights into underlying genetic mechanisms. This study aimed to identify key regulatory genes contributing to multidrug resistance (MDR) through a comprehensive analysis of gene expression in clinical isolates. RNA-Seq data from 246 clinical isolates of P. aeruginosa was analyzed using Weighted Gene Co-Expression Network Analysis (WGCNA) to construct co-expression networks. Modules of co-expressed genes were identified, and hub genes with high connectivity were selected, focusing on those within and across modules, including the largest module enriched with resistance-related genes. Pathway enrichment was performed using STRING and ShinyGO, highlighting key resistance-associated pathways. Pathway enrichment analysis of hub genes identified polA as a central player in DNA repair and replication processes, crucial for bacterial survival under antibiotic stress. In addition to polA, other highly connected hub genes, such as dnaB, tatC, and ppnK, were enriched in pathways including protein transport and mismatch repair. Within the turquoise module, hub genes like dnaA, uvrD, and gyrA were primarily involved in ATP-binding, ligase activity, and biosynthetic processes, essential for antibiotic resistance. Network analysis further emphasized the centrality of polA and its role in bridging multiple resistance pathways, highlighting its potential as a therapeutic target. This research highlights polA and other critical hub genes as key regulatory elements within the MDR networks of P. aeruginosa, playing essential roles in pathways vital for bacterial survival. The identification of these genes provides promising biomarkers and potential therapeutic targets to counteract MDR in clinical settings.