Host Defense Peptide Resistance Contributes to Colonization and Maximal Intestinal Pathology by Crohn's Disease-Associated Adherent-Invasive Escherichia coli
Bibliographic record
Abstract
Host defense peptides secreted by colonocytes and Paneth cells play a key role in innate host defenses in the gut. In Crohn's disease, the burden of tissue-associated Escherichia coli commonly increases at epithelial surfaces where host defense peptides concentrate, suggesting that this bacterial population might actively resist this mechanism of bacterial killing. Adherent-invasive E. coli (AIEC) is associated with Crohn's disease; however, the colonization determinants of AIEC in the inflamed gut are undefined. Here, we establish that host defense peptide resistance contributes to host colonization by Crohn's-associated AIEC. We identified a plasmid-encoded genomic island (called PI-6) in AIEC strain NRG857c that confers high-level resistance to α-helical cationic peptides and α- and β-defensins. Deletion of PI-6 sensitized strain NRG857c to these host defense molecules, reduced its competitive fitness in a mouse model of infection, and attenuated its ability to induce cecal pathology. This phenotype is due to two genes in PI-6, arlA, which encodes a Mig-14 family protein implicated in defensin resistance, and arlC, an OmpT family outer membrane protease. Implicit in these findings are new bacterial targets whose inhibition might limit AIEC burden and disease in the gut.
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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".