Discovery of quorum-sensing reprogramming determinants in Pseudomonas aeruginosa by a novel experimental evolution approach

LasR is a master regulator of quorum-sensing (QS) in Pseudomonas aeruginosa. LasR-null mutants commonly appear in lung isolates from chronically infected cystic fibrosis (CF) patients. However, numerous such CF isolates have a QS-active phenotype, but factors underlying QS-reprogramming in LasR-null mutants remain largely unknown. Mutations in the transcriptional regulator gene mexT are well known to be responsible for QS-reprogramming in a laboratory LasR-null mutant strain, however, simultaneous occurrence of lasR and mexT mutations is rare in CF isolates. To identify QS-reprogramming determinants, we developed an experimental evolution approach, for which a QS-inactive LasR null mutant with an extra copy of mexT was engineered. In such a strain, spontaneous single mextT mutations are expected to have no or little phenotypic consequences. This novel method, named “targeted gene duplication followed by mutant screening” (TGD-MS), resulted in identification of QS-active revertants with mutations in genes other than mexT. We characterized a QS-active revertant with a point mutation in rpoA, a gene encoding the α-subunit of RNA polymerase. QS activation in this mutant was found to be associated with down-regulated expression of mexEF-oprN efflux pump genes. In an iterative TGD-MS experiment, we discovered mutations in mexE, a gene encoding a membrane fusion protein of the MexEF-OprN efflux pump. Our results implicate that a regulatory circuit controlling the expression of the mexEF-oprN operon is critical for QS-reprogramming. In conclusion, our study reports on identification of non-MexT proteins associated with QS-reprogramming in a laboratory strain, shedding light on possible QS activation mechanisms in clinical P. aeruginosa isolates. More generally, we describe a novel experimental evolution approach, in which the populations contain extra copies of previously identified genes. The TGD-MS method facilitates the identification of mutations in unknown genes and opens the perspective of iterative application. We suggest that this method can be employed to uncover untapped pathways in any transformable haploid organism.