Exploitation of host cells by enteropathogenic <i>Escherichia</i> <i>coli</i>
Bibliographic record
Abstract
Microbial pathogens have evolved many ingenious ways to infect their hosts and cause disease, including the subversion and exploitation of target host cells. One such subversive microbe is enteropathogenic Escherichia coli (EPEC). A major cause of infantile diarrhea in developing countries, EPEC poses a significant health threat to children worldwide. Central to EPEC-mediated disease is its colonization of the intestinal epithelium. After initial adherence, EPEC causes the localized effacement of microvilli and intimately attaches to the host cell surface, forming characteristic attaching and effacing (A/E) lesions. Considered the prototype for a family of A/E lesion-causing bacteria, recent in vitro studies of EPEC have revolutionized our understanding of how these pathogens infect their hosts and cause disease. Intimate attachment requires the type III-mediated secretion of bacterial proteins, several of which are translocated directly into the infected cell, including the bacteria's own receptor (Tir). Binding to this membrane-bound, pathogen-derived protein permits EPEC to intimately attach to mammalian cells. The translocated EPEC proteins also activate signaling pathways within the underlying cell, causing the reorganization of the host actin cytoskeleton and the formation of pedestal-like structures beneath the adherent bacteria. This review explores what is known about EPEC's subversion of mammalian cell functions and how this knowledge has provided novel insights into bacterial pathogenesis and microbe-host interactions. Future studies of A/E pathogens in animal models should provide further insights into how EPEC exploits not only epithelial cells but other host cells, including those of the immune system, to cause diarrheal disease.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".