Enterohaemorrhagic and enteropathogenic <i>Escherichia coli</i> use a different Tir‐based mechanism for pedestal formation
Bibliographic record
Abstract
Enterohaemorrhagic Escherichia coli (EHEC) adheres to the host intestinal epithelium, resulting in the formation of actin pedestals beneath adhering bacteria. EHEC and a related pathogen, enteropathogenic E. coli (EPEC), insert a bacterial receptor, Tir, into the host plasma membrane, which is required for pedestal formation. An important difference between EPEC and EHEC Tir is that EPEC but not EHEC Tir is tyrosine phosphorylated once delivered into the host. In this study, we assessed the role of Tir tyrosine phosphorylation in pedestal formation by EPEC and EHEC. In EPEC, pedestal formation is absolutely dependent on Tir tyrosine phosphorylation and is not complemented by EHEC Tir. The protein sequence surrounding EPEC Tir tyrosine 474 is critical for Tir tyrosine phosphorylation and pedestal formation by EPEC. In contrast, Tir tyrosine phosphorylation is not required for pedestal formation by EHEC. EHEC forms pedestals with both wild-type EPEC Tir and the non-tyrosine-phosphorylatable EPEC Tir Y474F. Pedestal formation by EHEC requires the type III delivery of additional EHEC factors into the host cell. These findings highlight differences in the mechanisms of pedestal formation by these closely related pathogens and indicate that EPEC and EHEC modulate different signalling pathways to affect the host actin cytoskeleton.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".