Loss of disease tolerance during Citrobacter rodentium infection is associated with impaired epithelial differentiation and hyperactivation of T cell responses
Bibliographic record
Abstract
Abstract Citrobacter rodentium is an intestinal mouse pathogen widely used as a model to study the mucosal response to infection. Inbred mouse strains suffer one of two fates following infection: self-limiting colitis or fatal diarrheal disease. We previously reported that Rspo2 is a major genetic determinant of the outcome of C. rodentium infection; Rspo2 induction during infection of susceptible mice leads to loss of intestinal function and mortality. Rspo2 induction does not impact bacterial colonization, but rather, impedes the ability of the host to tolerate C. rodentium infection. Here, we performed deep RNA sequencing and systematically analyzed the global gene expression profiles of C. rodentium-infected colon tissues from susceptible and resistant congenic mice strains to determine the common responses to infection and the Rspo2-mediated dysfunction pathway signatures associated with loss of disease tolerance. Our results highlight changes in metabolism, tissue remodeling, and host defence as common responses to infection. Conversely, increased Wnt and stem cell signatures, loss of epithelial differentiation, and exaggerated CD4+ T cell activation through increased antigen processing and presentation were specifically associated with the response to infection in susceptible mice. These data provide insights into the molecular mechanisms underlying intestinal dysfunction and disease tolerance during C. rodentium infection.
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) | 0.000 | 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".