Evidence that Tight Junctions Are Disrupted Due to Intimate Bacterial Contact and Not Inflammation during Attaching and Effacing Pathogen Infection In Vivo
Bibliographic record
Abstract
It is widely accepted that tight junctions are altered during infections by attaching and effacing (A/E) pathogens. These disruptions have been demonstrated both in vitro and more recently in vivo. For in vivo experiments, the murine model of A/E infection with Citrobacter rodentium is the animal model of choice. In addition to effects on tight junctions, these bacteria also colonize the colon at high levels, efface colonocyte microvilli, and cause hyperplasia and inflammation. Although we have recently demonstrated that tight junctions are disrupted by C. rodentium, the issue of direct effects of bacteria on epithelial cell junctions versus the indirect effects of inflammation still remains to be clarified. Here, we demonstrate that during the C. rodentium infections, inflammation plays no discernible role in the alteration of tight junctions. The distribution of the tight junction proteins, claudin-1, -3, and -5, are unaffected in inflamed colon, and junctions appear morphologically unaltered when viewed by electron microscopy. Additionally, tracer molecules are not capable of penetrating the inflamed colonic epithelium of infected mice that have cleared the bacteria. Finally, infected colonocytes from mice exposed to C. rodentium for 14 days, which have high levels of bacterial attachment to colonocytes as well as inflammation, have characteristic, altered claudin localization whereas cells adjacent to infected colonocytes retain their normal claudin distribution. We conclude that inflammation plays no discernible role in tight junction alteration during A/E pathogenesis and that tight junction disruption in vivo appears dependent only on the direct intimate attachment of the pathogenic bacteria to the cells.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".