Enteropathogenic <i>Escherichia coli</i> Infection Triggers Host Phospholipid Metabolism Perturbations
Bibliographic record
Abstract
Enteropathogenic Escherichia coli (EPEC) specifically recognizes phosphatidylethanolamine (PE) on the outer leaflet of host epithelial cells. EPEC also induces apoptosis in epithelial cells, which results in increased levels of outer leaflet PE and increased bacterial binding. Consequently, it is of interest to investigate whether EPEC infection perturbs host cell phospholipid metabolism and whether the changes play a role in the apoptotic signaling. Our findings indicate that EPEC infection results in a significant increase in the epithelial cell PE level and a corresponding decrease in the phosphatidylcholine (PC) level. PE synthesis via both the de novo pathway and the serine decarboxylation pathway was enhanced, and de novo synthesis of phosphatidylcholine via CDP-choline was reduced. The changes were transitory, and the maximum change was noted after 4 to 5 h of infection. Addition of exogenous PC or CDP-choline to epithelial cells prior to infection abrogated EPEC-induced apoptosis, suggesting that EPEC infection inhibits the CTP-phosphocholine cytidylyltransferase step in PC synthesis, which is reportedly inhibited during nonmicrobially induced apoptosis. On the other hand, incorporation of exogenous PE by the host cells enhanced EPEC-induced apoptosis and necrosis without increasing bacterial adhesion. This is the first report that pathogen-induced apoptosis is associated with significant changes in PE and PC metabolism, and the results suggest that EPEC adhesion to a host membrane phospholipid plays a role in disruption of host phospholipid metabolism.
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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 | 0.001 |
| 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".