Recruitment of Cytoskeletal and Signaling Proteins to Enteropathogenic and Enterohemorrhagic <i>Escherichia coli</i> Pedestals
Bibliographic record
Abstract
Enteropathogenic Escherichia coli (EPEC) is a human pathogen that attaches to intestinal epithelial cells and causes chronic watery diarrhea. A close relative, enterohemorrhagic E. coli (EHEC), causes severe bloody diarrhea and hemolytic-uremic syndrome. Both pathogens insert a protein, Tir, into the host cell plasma membrane where it binds intimin, the outer membrane ligand of EPEC and EHEC. This interaction triggers a cascade of signaling events within the host cell and ultimately leads to the formation of an actin-rich pedestal upon which the pathogen resides. Pedestal formation is critical in mediating EPEC- and EHEC-induced diarrhea, yet very little is known about its composition and organization. In EPEC, pedestal formation requires Tir tyrosine 474 phosphorylation. In EHEC Tir is not tyrosine phosphorylated, yet the pedestals appear similar. The composition of the EPEC and EHEC pedestals was analyzed by examining numerous cytoskeletal, signaling, and adapter proteins. Of the 25 proteins examined, only two, calpactin and CD44, were recruited to the site of bacterial attachment independently of Tir. Several others, including ezrin, talin, gelsolin, and tropomyosin, were recruited to the site of EPEC attachment independently of Tir tyrosine 474 phosphorylation but required Tir in the host membrane. The remaining proteins were recruited to the pedestal in a manner dependent on Tir tyrosine phosphorylation or were not recruited at all. Differences were also found between the EPEC and EHEC pedestals: the adapter proteins Grb2 and CrkII were recruited to the EPEC pedestal but were absent in the EHEC pedestal. These results demonstrate that although EPEC and EHEC recruit similar cytoskeletal proteins, there are also significant differences in pedestal composition.
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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".