A potential role of <i>Escherichia coli</i> pathobionts in the pathogenesis of pediatric inflammatory bowel disease
Bibliographic record
Abstract
Through genomic analysis of mucosa-associated Escherichia coli strains, we found a close genetic association among isolates from pediatric inflammatory bowel disease (IBD) patients. A specific E. coli pathovar, adherent-invasive E. coli (AIEC), was found in Crohn's disease (CD) adult patients - this pathovar has enhanced adhesive and invasive properties, mainly due to the mannose-bonding FimH protein. We aimed to characterize 52 mucosa-associated E. coli strains isolated from pediatric IBD and non-IBD patients. Eleven E. coli strains, showing a strong similarity in fimH gene sequence to that of E. coli AIEC LF82, were characterized for fimH gene sequence, genomic profiling, adhesive and invasive ability, and phylogrouping. The results were compared with E. coli strains AIEC LF82 and MG1655. The 11 E. coli isolates showed 82.4% ± 1.4% fimH sequence similarity and 80.6% ± 1.3% genomic similarity to strain AIEC LF82. All these strains harbored V27A and S78N FimH mutations, as found in LF82. Nine of them belonged to the more virulent B2 and D phylogroups. Neuraminidase treatment, mimicking inflamed mucosa, enhanced adhesion of all 11 strains by 3.5-fold, but none showed invasion ability. It could be argued that the 11 selected strains could be a branch of an E. coli subpopulation (pathobionts), that could take advantage in an inflamed context because of a suitable genomic and (or) genetic backdrop.
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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".