Emergence of hypervirulent Pseudomonas aeruginosa pathotypically armed with co-expressed T3SS effectors ExoS and ExoU
Bibliographic record
Abstract
Pseudomonas aeruginosa is a significant pathogen mainly causing healthcare-associated infections (HAIs). Newly emerging high-risk clones of P. aeruginosa with elevated virulence profiles furtherly cause severe community-acquired infections (CAIs). Usually, it is not common for P. aeruginosa to co-carry exoU and exoS genes, encoding two type III secretion system (T3SS) effectors. The pathogenicity mechanism of exoS+/exoU+ strains of P. aeruginosa remains unclear. Here, we provide detailed evidence for a subset of hypervirulent P. aeruginosa strains, which abundantly co-express and secrete the T3SS effectors ExoS and ExoU. The exoS+/exoU+ P. aeruginosa strains were available to cause both HAIs and CAIs. The CAI-associated strains could elicit severe inflammation and hemorrhage, leading to higher death rates in a murine acute pneumonia model, and had great virulence potential in establishing chronic infections, demonstrating hypervirulence when compared to PAO1 (exoS+/exoU-) and PA14 (exoS-/exoU+). Both ExoS and ExoU were co-expressed and co-secreted in abundance in exoS+/exoU+ strains. Their abundant protein secretion could boost exoS+/exoU+ strains’ potentials for cytotoxicity in vitro and pathogenicity in vivo. Genomic evidence indicates that exoU acquisition is likely mediated by horizontal gene transfer (HGT) of the pathogenicity island PAPI-2, while deletion of exoU was sufficient to mitigate virulence in the exoS+/exoU+ strains. Furthermore, bioinformatics analysis showed that such exoS+/exoU+ P. aeruginosa strains turned out to be widely distributed across the globe. Overall, the research provide detailed evidence for the high virulence and epidemicity of exoS+/exoU+ strains of P. aeruginosa, highlighting an urgent need for surveillance against these high-risk hypervirulent strains.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".