Pseudomonas aeruginosa prophages: a new and simplified bioinformatic analysis
Rodrigo Monteiro 1,2,3*, Maria Vieira 1,2, Jelena Erdmann 4, Susanne Häussler 4, Joana Azeredo 1,2
- CEB, Centre of Biological Engineering, Laboratory of Research in Biofilms Rosário Oliveira (LIBRO), University of Minho, Braga, Portugal
- LABBELS – Associated Laboratory, Braga, Guimarães, Portugal
- Department of Medical Microbiology - Molecular Bacteriology, UMCG, University Medical Center Groningen, Groningen, Netherlands
- Twincore, Centre for Experimental and Clinical Infection Research, a joint venture of the Helmholtz Centre for Infection Research and the Hannover Medical School, Hannover, Germany
ESKAPE pathogens are a global threat caused mainly by the misuse of antibiotics and, according to the World Health Organization (WHO), should be targeted with high priority. Horizontal gene transfer (HGT), which allows bacterial cells to exchange genetic information, leads to the widespread of antibiotic resistance genes (ARGs) and consequently the emergence of antibiotic-resistant variants. Transduction is an important mechanism of HGT and therefore understanding and controlling transduction events becomes crucial. In a previous work, we showed that prophages have a high impact on Acinetobacter baumannii genomic context, by encoding different virulence and fitness-related genes. In this study, we developed a pipeline to simplify the analyses of prophages from a set of genomes of Pseudomonas aeruginosa clinical isolates, by conjugating different publicly available bioinformatic tools.
For the analysis, 449 genomes from P. aeruginosa clinical isolates were submitted to PHASTEST to search for prophage regions. The detected prophage genomes were sorted by their type (intact, questionable, incomplete), and their size and frequency were analyzed. Intact prophages were selected for further analysis consisting of predicting their taxonomic family, searching for ARGs, and looking for other virulence/fitness-related genes
Results showed that prophages are prevalent among these P. aeruginosa isolates. The average number of intact prophages per genome was three, but some genomes carried up to ten intact prophages. Despite the analyzed genomes being organized in several contigs, surprisingly there is a low prevalence of incomplete prophages. We also found a worrying number of ARGs, such as catB and bcr1, as well as other virulence factors related to alginate, pili, and secretion systems, confirming these intact prophages’ potential role in virulence spread. Prophage morphology was also predicted with myovirus being the most prevalent (>70%) followed by siphovirus (<30%), no podovirus was found.
In conclusion, with our pipeline, we showed that prophages are widespread among P. aeruginosa clinical isolates, with a significant proportion of them being potentially inducible. Among the genes encoded, we found a significant portion of virulence genes, proving the importance these entities have in bacterial genetic evolution. More studies about prophages should be performed using large clinical isolates in order to understand the current status of these pathogens and monitor bacterial genes transfer among them.