Phosphatidylserine externalization and procoagulant activation of erythrocytes induced by <i>Pseudomonas aeruginosa</i> virulence factor pyocyanin
Bibliographic record
Abstract
The opportunistic pathogen Pseudomonas aeruginosa causes a wide range of infections in multiple hosts by releasing an arsenal of virulence factors such as pyocyanin. Despite numerous reports on the pleiotropic cellular targets of pyocyanin toxicity in vivo, its impact on erythrocytes remains elusive. Erythrocytes undergo an apoptosis-like cell death called eryptosis which is characterized by cell shrinkage and phosphatidylserine (PS) externalization; this process confers a procoagulant phenotype on erythrocytes as well as fosters their phagocytosis and subsequent clearance from the circulation. Herein, we demonstrate that P. aeruginosa pyocyanin-elicited PS exposure and cell shrinkage in erythrocyte while preserving the membrane integrity. Mechanistically, exposure of erythrocytes to pyocyanin showed increased cytosolic Ca(2+) activity as well as Ca(2+) -dependent proteolytic processing of μ-calpain. Pyocyanin further up-regulated erythrocyte ceramide abundance and triggered the production of reactive oxygen species. Pyocyanin-induced increased PS externalization in erythrocytes translated into enhanced prothrombin activation and fibrin generation in plasma. As judged by carboxyfluorescein succinimidyl-ester labelling, pyocyanin-treated erythrocytes were cleared faster from the murine circulation as compared to untreated erythrocytes. Furthermore, erythrocytes incubated in plasma from patients with P. aeruginosa sepsis showed increased PS exposure as compared to erythrocytes incubated in plasma from healthy donors. In conclusion, the present study discloses the eryptosis-inducing effect of the virulence factor pyocyanin, thereby shedding light on a potentially important mechanism in the systemic complications of P. aeruginosa infection.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".