Secretory phospholipase A2-IIA targets bacterial extracellular vesicles to modulate immune signaling
Bibliographic record
Abstract
Secretory phospholipase A2-IIA (sPLA2-IIA) is a bactericidal enzyme that hydrolyzes membrane phospholipids, releasing lipid metabolites that can affect inflammation. sPLA2-IIA exhibits poor activity toward eukaryotic cells but preferentially targets gram-positive bacterial membranes. While sPLA2-IIA is constitutively expressed in the intestine and upregulated by inflammation in various bodily fluids, its precise physiological substrates remain debated. Intriguingly, sPLA2-IIA can modulate the intestinal lipidome without altering the microbiota composition. Here, we investigated whether sPLA2-IIA could use membranes from bacterial extracellular vesicles (bEVs) as alternative substrates to modulate immune signaling. We found that bEVs from both Staphylococcus aureus and Escherichia coli could mitigate the bactericidal effects of sPLA2-IIA on gram-positive bacteria. Enzymatic hydrolysis of bacteria, bEVs and fecal extracellular vesicles released distinct lipid metabolites and differentially impacted Toll-like receptor activation. These findings suggest that sPLA2-IIA can use bEVs as substrates and modulate inflammatory signaling through the generation of pathogen-associated molecular patterns, thus linking bacterial lipid metabolism to host immune response. Secretory phospholipase A2-IIA, a bactericidal enzyme whose main expression is in the intestine, uses bacterial extracellular vesicles as substrates to release lipid metabolites and affect immune pathways.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 |
| 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".