Evolution of Pseudomonas aeruginosa toward higher fitness under standard laboratory conditions.

Identifying genetic factors that contribute to the evolution of adaptive phenotypes in pathogenic bacteria is key to understanding the establishment of infectious diseases. In this study, we performed mutation accumulation experiments to record the frequency of mutations and their effect on fitness in hypermutator strains of the environmental bacterium Pseudomonas aeruginosa in comparison to the host-niche-adapted Salmonella enterica. We demonstrate that P. aeruginosa, but not S. enterica, hypermutators evolve toward higher fitness under planktonic conditions. Adaptation to increased growth performance was accompanied by a reversible perturbing of the local genetic context of membrane and cell wall biosynthesis genes. Furthermore, we observed a fine-tuning of complex regulatory circuits involving multiple di-guanylate modulating enzymes that regulate the transition between fast growing planktonic and sessile biofilm-associated lifestyles. The redundancy and local specificity of the di-guanylate signaling pathways seem to allow a convergent shift toward increased growth performance across niche-adapted clonal P. aeruginosa lineages, which is accompanied by a pronounced heterogeneity of their motility, virulence, and biofilm phenotypes.

Untargeted LC-MS Metabolomics Differentiates Between Virulent and Avirulent Clinical Strains of Pseudomonas aeruginosa.

Pseudomonas aeruginosa is a facultative pathogen that can cause, inter alia, acute or chronic pneumonia in predisposed individuals. The gram-negative bacterium displays considerable genomic and phenotypic diversity that is also shaped by small molecule secondary metabolites. The discrimination of virulence phenotypes is highly relevant to the diagnosis and prognosis of P. aeruginosa infections. In order to discover small molecule metabolites that distinguish different virulence phenotypes of P. aeruginosa, 35 clinical strains were cultivated under standard conditions, characterized in terms of virulence and biofilm phenotype, and their metabolomes were investigated by untargeted liquid chromatography-mass spectrometry. The data was both mined for individual candidate markers as well as used to construct statistical models to infer the virulence phenotype from metabolomics data. We found that clinical strains that differed in their virulence and biofilm phenotype also had pronounced divergence in their metabolomes, as underlined by 332 features that were significantly differentially abundant with fold changes greater than 1.5 in both directions. Important virulence-associated secondary metabolites like rhamnolipids, alkyl quinolones or phenazines were found to be strongly upregulated in virulent strains. In contrast, we observed little change in primary metabolism. A hitherto novel cationic metabolite with a sum formula of C12H15N2 could be identified as a candidate biomarker. A random forest model was able to classify strains according to their virulence and biofilm phenotype with an area under the Receiver Operation Characteristics curve of 0.84. These findings demonstrate that untargeted metabolomics is a valuable tool to characterize P. aeruginosa virulence, and to explore interrelations between clinically important phenotypic traits and the bacterial metabolome.

Genetic determinants of Pseudomonas aeruginosa fitness during biofilm growth.

Pseudomonas aeruginosa is an environmental bacterium and an opportunistic human pathogen. It is also a well-established model organism to study bacterial adaptation to stressful conditions, such as those encountered during an infection process in the human host. Advancing knowledge on P. aeruginosa adaptation to biofilm growth conditions is bound to reveal novel strategies and targets for the treatment of chronic biofilm-associated infections. Here, we generated transposon insertion libraries in three P. aeruginosa strain backgrounds and determined the relative frequency of each insertion following biofilm growth using transposon sequencing. We demonstrate that in general the SOS response, several tRNA modifying enzymes as well as adaptation to microaerophilic growth conditions play a key role in bacterial survival under biofilm growth conditions. On the other hand, presence of genes involved in motility and PQS signaling were less important during biofilm growth. Several mutants exhibiting transposon insertions in genes detected in our screen were validated for their biofilm growth capabilities and biofilm specific transcriptional responses using independently generated transposon mutants. Our results provide new insights into P. aeruginosa adaptation to biofilm growth conditions. The detection of previously unknown determinants of biofilm survival supports the use of transposon insertion sequencing as a global genomic technology for understanding the establishment of difficult to treat biofilm-associated infections.