Aquaporins contribute to diarrhoea caused by attaching and effacing bacterial pathogens
Bibliographic record
Abstract
Attaching and effacing (A/E) pathogens such as enterohemorrhagic Escherichia coli (EHEC) and enteropathogenic E. coli (EPEC) cause serious global health problems. These bacteria colonize the gastrointestinal system, attach to intestinal epithelial cells, efface (collapse) infected cell microvilli and cause overt diarrhoea that may ultimately result in death of the host. Although pathogenically induced diarrhoea is a significant global health issue, the molecular mechanisms that underlie this disease remain largely unknown. A natural murine infection model, employing the A/E pathogen Citrobacter rodentium, has been helpful in studying the diseases in vivo. C. rodentium colonize the colon at high levels, attach to colonocytes, efface microvilli and cause hyperplasia and inflammation in infected mice. As the disease progresses, the mice develop a diarrhoea-like phenotype. Aquaporin (AQP) water channels have been proposed to play a role in the normal dehydration of faecal contents. Here we examine whether C. rodentium infection may alter AQP localization in colonocytes. We demonstrate that during infection, AQP2 and AQP3 are mislocalized from their normal location along cell membranes to the cell cytoplasm. The change in localization of these proteins correlates with the diarrhoea-like phenotype present in infected mice. Mice that recover from the infection at 28-35 days post inoculum regain their normal membrane AQP localization. The altered localization of AQPs is partially dependent on the bacterial type III effector proteins EspF and EspG. We conclude that altered AQP localization may be a contributing factor to diarrhoea during bacterial 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 | 0.001 | 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".