Identification of a Pseudomonas aeruginosa PAO1 DNA methyltransferase, its Targets, and physiological roles

DNA methylation is widespread among prokaryotes, and most DNA methylation reactions are catalyzed by adenine DNA methyltransferases, which are part of restriction-modification (R-M) systems. R-M systems are known for their role in the defense against foreign DNA; however, DNA methyltransferases also play functional roles in gene regulation. In this study, we used single-molecule real-time (SMRT) sequencing to uncover the genome-wide DNA methylation pattern in the opportunistic pathogen Pseudomonas aeruginosa PAO1. We identified a conserved sequence motif targeted by an adenine methyltransferase of a type I R-M system and quantified the presence of N(6)-methyladenine using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Changes in the PAO1 methylation status were dependent on growth conditions and affected P. aeruginosa pathogenicity in a Galleria mellonella infection model. Furthermore, we found that methylated motifs in promoter regions led to shifts in sense and antisense gene expression, emphasizing the role of enzymatic DNA methylation as an epigenetic control of phenotypic traits in P. aeruginosa Since the DNA methylation enzymes are not encoded in the core genome, our findings illustrate how the acquisition of accessory genes can shape the global P. aeruginosa transcriptome and thus may facilitate adaptation to new and challenging habitats.IMPORTANCE With the introduction of advanced technologies, epigenetic regulation by DNA methyltransferases in bacteria has become a subject of intense studies. Here we identified an adenosine DNA methyltransferase in the opportunistic pathogen Pseudomonas aeruginosa PAO1, which is responsible for DNA methylation of a conserved sequence motif. The methylation level of all target sequences throughout the PAO1 genome was approximated to be in the range of 65 to 85% and was dependent on growth conditions. Inactivation of the methyltransferase revealed an attenuated-virulence phenotype in the Galleria mellonella infection model. Furthermore, differential expression of more than 90 genes was detected, including the small regulatory RNA prrF1, which contributes to a global iron-sparing response via the repression of a set of gene targets. Our finding of a methylation-dependent repression of the antisense transcript of the prrF1 small regulatory RNA significantly expands our understanding of the regulatory mechanisms underlying active DNA methylation in bacteria

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

Single-nucleotide polymorphism-based genetic diversity analysis of clinical Pseudomonas aeruginosa isolates.

Extensive use of next-generation sequencing has the potential to transform our knowledge on how genomic variation within bacterial species impacts phenotypic versatility. Since different environments have unique selection pressures, they drive divergent evolution. However, there is also parallel or convergent evolution of traits in independent bacterial isolates inhabiting similar environments. The application of tools to describe population-wide genomic diversity provides an opportunity to measure the predictability of genetic changes underlying adaptation. Here we describe patterns of sequence variations in the core genome among 99 individual Pseudomonas aeruginosa clinical isolates and identified single nucleotide polymorphisms (SNPs) that are the basis for branching of the phylogenetic tree. We also identified SNPs that were acquired independently, in separate lineages, and not through inheritance from a common ancestor. While our results demonstrate that the P. aeruginosa core genome is highly conserved and in general, not subject to adaptive evolution, instances of parallel evolution will provide an opportunity to uncover genetic changes that underlie phenotypic diversity

Unravelling post-transcriptional PrmC-dependent regulatory mechanisms in Pseudomonas aeruginosa.

Transcriptional regulation has a central role in cellular adaptation processes and is well investigated. In contrast, the importance of the post-transcriptional regulation on these processes is less well defined. The technological advancements have been critical to precisely quantify protein and mRNA level changes and hold promise to provide more insights into how post-transcriptional regulation determines phenotypes. In Pseudomonas aeruginosa the methyltransferase PrmC methylates peptide chain release factors to facilitate translation termination. Loss of PrmC activity abolishes anaerobic growth and leads to reduced production of quorum sensing-associated virulence factors. Here, by applying SILAC technology in combination with mRNA-sequencing, they provide evidence that the P. aeruginosa phenotype can be attributed to a change in protein to mRNA ratios of selected protein groups. The UAG-dependent translation termination was more dependent on PrmC activity than the UAA- and UGA-dependent translation termination. Additionally, a bias toward UAG stop codons in global transcriptional regulators was found. The finding that this bias in stop codon usage determines the P. aeruginosa phenotype is unexpected and adds complexity to regulatory circuits. Via modulation of PrmC activity the bacterial cell can cross-regulate targets independently of transcriptional signals, a process with an underestimated impact on the bacterial phenotype

Establishment of an induced memory response in Pseudomonas aeruginosa during infection of a eukaryotic host.

In a given habitat, bacterial cells often experience recurrent exposures to the same environmental stimulus. The ability to memorize the past event and to adjust current behaviors can lead to efficient adaptation to the recurring stimulus. Here we demonstrate that the versatile bacterium Pseudomonas aeruginosa adopts a virulence phenotype after serial passage in the invertebrate model host Galleria mellonella. The virulence phenotype was not linked to the acquisition of genetic variations and was sustained for several generations, despite cultivation of the ex vivo virulence-adapted P. aeruginosa cells under rich medium conditions in vitro. Transcriptional reprogramming seemed to be induced by a host-specific food source, as reprogramming was also observed upon cultivation of P. aeruginosa in rich medium supplemented with polyunsaturated long-chain fatty acids. The establishment of induced memory responses adds a time dimension and seems to fill the gap between long-term evolutionary genotypic adaptation and short-term induced individual responses. Efforts to unravel the fundamental mechanisms that underlie the carry-over effect to induce such memory responses will continue to be of importance as hysteretic behavior can serve survival of bacterial populations in changing and challenging habitats

BACTOME-a reference database to explore the sequence- and gene expression-variation landscape of Pseudomonas aeruginosa clinical isolates.

Extensive use of next-generation sequencing (NGS) for pathogen profiling has the potential to transform our understanding of how genomic plasticity contributes to phenotypic versatility. However, the storage of large amounts of NGS data and visualization tools need to evolve to offer the scientific community fast and convenient access to these data. We introduce BACTOME as a database system that links aligned DNA- and RNA-sequencing reads of clinical Pseudomonas aeruginosa isolates with clinically relevant pathogen phenotypes. The database allows data extraction for any single isolate, gene or phenotype as well as data filtering and phenotypic grouping for specific research questions. With the integration of statistical tools we illustrate the usefulness of a relational database structure for the identification of phenotype-genotype correlations as an essential part of the discovery pipeline in genomic research. Furthermore, the database provides a compilation of DNA sequences and gene expression values of a plethora of clinical isolates to give a consensus DNA sequence and consensus gene expression signature. Deviations from the consensus thereby describe the genomic landscape and the transcriptional plasticity of the species P. aeruginosa. The database is available at https://bactome.helmholtz-hzi.de