A gene network-driven approach to infer novel pathogenicity-associated genes: application to Pseudomonas aeruginosa PAO1

We present here a new systems-level approach to decipher genetic factors and biological pathways associated with virulence and/or antibiotic treatment of bacterial pathogens. The power of this approach was demonstrated by application to a well-studied pathogen PAO1. Our gene co-expression network-based approach unraveled known and unknown genes and their networks associated with pathogenicity in PAO1. The systems-level investigation of PAO1 helped identify putative pathogenicity and resistance-associated genetic factors that could not otherwise be detected by conventional approaches of differential gene expression analysis. The network-based analysis uncovered modules that harbor genes not previously reported by several original studies on virulence and resistance. These could potentially act as molecular determinants of PAO1 pathogenicity and responses to antibiotics.