The Helical Shape of Campylobacter jejuni Promotes <i>In Vivo</i> Pathogenesis by Aiding Transit through Intestinal Mucus and Colonization of Crypts
Bibliographic record
Abstract
Campylobacter jejuni is a helix-shaped enteric bacterial pathogen and a common cause of gastroenteritis. We recently developed a mouse model for this human pathogen utilizing the SIGIRR-deficient mouse strain, which exhibits significant intestinal inflammation in response to intestinal C. jejuni infection. In the current study, this mouse model was used to define whether C. jejuni's characteristic helical shape plays a role in its ability to colonize and elicit inflammation in the mouse intestine. Mice were infected with the previously characterized straight-rod Δpgp1 and Δpgp2 mutant strains, along with a newly characterized curved-rod Δ1228 mutant strain. We also compared the resultant infections and pathology to those elicited by the helix-shaped wild-type C. jejuni and complemented strains. Despite displaying wild-type colonization of the intestinal lumen, the straight-rod Δpgp1 and Δpgp2 mutants were essentially nonpathogenic, while all strains with a curved or helical shape retained their expected virulence. Furthermore, analysis of C. jejuni localization within the ceca of infected mice determined that the primary difference between the rod-shaped, nonpathogenic mutants and the helix-shaped, pathogenic strains was the ability to colonize intestinal crypts. Rod-shaped mutants appeared unable to colonize intestinal crypts due to an inability to pass through the intestinal mucus layer to directly contact the epithelium. Together, these results support a critical role for C. jejuni's helical morphology in enabling it to traverse and colonize the mucus-filled intestinal crypts of their host, a necessary step required to trigger intestinal inflammation in response to C. jejuni.
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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 | 0.000 |
| 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".