Escherichia coli O157:H7 adherence to HEp-2 cells is implicated with curli expression and outer membrane integrity
Bibliographic record
Abstract
Escherichia coli (E. coli) has ability to express thin aggregative fimbriae, known as curli, on the cell surface. Previously, a few example of curli expression in serogroup O157:H7 of enterohemorrhagic E. coli (EHEC) were reported, compared to other E. coli groups. However, significance of curliation in the EHEC pathobiology has not been described well in the literature. A highly curliated O157:H7 strain was used in this study in order to elucidate role of curliation in EHEC adherence to cultured HEp-2 cells. The expression of curli in the EHEC isolate was consistent with strong positive indication of Congo-red (CR) binding and formation of clumps in the bottom of the tube containing Luria-Bertani (LB) broth when cultured overnight at 37 degrees C. A few CR-binding negative (CR-) colonies occurred spontaneously within the population of CR+ isolate. The CR+ EHEC showed massive aggregative adhesion pattern, whereas the spontaneous CR- strain showed typical localized adherence on HEp-2 cells. Electron microscopy confirmed highly curliated bacteria in the CR+ EHEC sample. Interestingly, the curliation disappeared in a msbB1 and msbB2 double mutant derived from the CR+ EHEC. These results suggest that the compromised outer membrane integrity caused by msbB mutations may abrogate curli production in the CR+ EHEC harbouring penta-acylated lipid A structure in their outer membrane.
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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".