The Gram-negative rod-shaped bacterium Pseudomonas aeruginosa is not only a major cause of nosocomial infections but also serves as a model species of bacterial RNA biology. While its transcriptome architecture and posttranscriptional regulation through the RNA-binding proteins Hfq, RsmA, and RsmN have been studied in detail, global information about stable RNA-protein complexes in this human pathogen is currently lacking. Here, we implement gradient profiling by sequencing (Grad-seq) in exponentially growing P. aeruginosa cells to comprehensively predict RNA and protein complexes, based on glycerol gradient sedimentation profiles of >73% of all transcripts and ∼40% of all proteins. As to benchmarking, our global profiles readily reported complexes of stable RNAs of P. aeruginosa, including 6S RNA with RNA polymerase and associated product RNAs (pRNAs). We observe specific clusters of noncoding RNAs, which correlate with Hfq and RsmA/N, and provide a first hint that P. aeruginosa expresses a ProQ-like FinO domain-containing RNA-binding protein. To understand how biological stress may perturb cellular RNA/protein complexes, we performed Grad-seq after infection by the bacteriophage ΦKZ. This model phage, which has a well-defined transcription profile during host takeover, displayed efficient translational utilization of phage mRNAs and tRNAs, as evident from their increased cosedimentation with ribosomal subunits. Additionally, Grad-seq experimentally determines previously overlooked phage-encoded noncoding RNAs. Taken together, the Pseudomonas protein and RNA complex data provided here will pave the way to a better understanding of RNA-protein interactions during viral predation of the bacterial cell. IMPORTANCE Stable complexes by cellular proteins and RNA molecules lie at the heart of gene regulation and physiology in any bacterium of interest. It is therefore crucial to globally determine these complexes in order to identify and characterize new molecular players and regulation mechanisms. Pseudomonads harbor some of the largest genomes known in bacteria, encoding ∼5,500 different proteins. Here, we provide a first glimpse on which proteins and cellular transcripts form stable complexes in the human pathogen Pseudomonas aeruginosa. We additionally performed this analysis with bacteria subjected to the important and frequently encountered biological stress of a bacteriophage infection. We identified several molecules with established roles in a variety of cellular pathways, which were affected by the phage and can now be explored for their role during phage infection. Most importantly, we observed strong colocalization of phage transcripts and host ribosomes, indicating the existence of specialized translation mechanisms during phage infection. All data are publicly available in an interactive and easy to use browser.
The Gram-negative bacterium P. aeruginosa is ubiquitously distributed in diverse environments and can cause severe biofilm-related infections in at-risk individuals. Although the presence of a large number of putative sRNAs and widely conserved RNA chaperones in this bacterium implies the importance of posttranscriptional regulatory networks for environmental fluctuations, limited information is available regarding the global role of RNA chaperones such as Hfq in the P. aeruginosa transcriptome, especially under different environmental conditions. Here, we characterize Hfq-dependent differences in gene expression and biological processes in two physiological states: the planktonic and biofilm forms. A combinatorial comparative CLIP-seq and total RNA-seq approach uncovered condition-dependent association of RNAs with Hfq in vivo and expands the potential direct regulatory targets of Hfq in the P. aeruginosa transcriptome.
Understanding the dynamics of dormant cells in microbial biofilms, in which the bacteria are embedded in extracellular matrix, is important for developing successful antibiotic therapies against pathogenic bacteria. Although some of the molecular mechanisms leading to bacterial persistence have been speculated in planktonic bacterial cell, how dormant cells emerge in the biofilms of pathogenic bacteria such as Pseudomonas aeruginosa remains unclear. The present study proposes four hypotheses of dormant cell formation; stochastic process, nutrient-dependent, oxygen-dependent, and time-dependent processes. These hypotheses were implemented into a three-dimensional individual-based model of biofilm formation. Numerical simulations of the different mechanisms yielded qualitatively different spatiotemporal distributions of dormant cells in the growing biofilm. Based on these simulation results, we discuss what kinds of experimental studies are effective for discriminating dormant cell formation mechanisms in biofilms.
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