The role of Tir, EspA, and NleB in the colonization of cattle by Shiga toxin producing<i>Escherichia coli</i>O26:H11
Bibliographic record
Abstract
Shiga toxin producing Escherichia coli (STEC) O26:H11 is an enteric pathogen capable of causing severe hemorrhagic colitis that can lead to hemolytic uremic syndrome. This organism is able to colonize cattle and human intestinal epithelial cells by secreting effectors via a type III secretion system (T3SS). In this investigation, we examined the role of 2 effectors, Tir and NleB, and the structural translocator component EspA in the adherence of STEC to epithelial cells and in the colonization of cattle. Isogenic deletion mutants were constructed and using microscopy and flow cytometry compared to the wild-type strain in their ability to adhere to HEp-2 cells. A competitive assay was also used to measure the capacity of the mutants to colonize the intestinal tract of cattle, where both the mutant and the parental strains were introduced orally at the same time. Genomic DNA was extracted from enriched fecal samples collected at various time points, and quantitative real-time PCR was used to quantify bacteria. A significant reduction in fecal shedding was observed, and adherence to HEp-2 cells was decreased for the tir and espA mutants. Deletion of the nleB gene did not have a significant effect on the adherence of HEp-2 cells; however, in an in vivo model, it strongly reduced the ability of STEC O26:H11 to colonize the bovine intestinal tract.
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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 | 0.001 | 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".