Pathogenic E. coli Cause Global Decreases in Ubiquitylated Host Cell Proteins
Bibliographic record
Abstract
Enteropathogenic E. coli (EPEC) infections cause severe infantile diarrhea, leading to high mortality in developing countries. These pathogens extensively alter normal host cell functions while remaining extracellular. Ubiquitylation is a widespread post‐translational regulatory system that governs a wide range of cellular events. This process relies on a heierarchical relay system, comprised of E1, E2 and E3 enzymes. Effects of EPEC on the host ubiquitin‐conjugation process have remained elusive. Thus, we sought to test the hypothesis that EPEC alter normal ubiquitylation signaling pathways during their infections. To test this, we infected epithelial cells with EPEC and monitored ubiquitylated protein levels by immunoblotting. We found that the presence of a large plasmid within EPEC called the E. coli adherence factor (EAF) caused a significant decrease in the overall levels of ubiquitylated host proteins. This occurred with a concomitant loss of host E1 activating enzymes, which are essential for initiating the ubiquitylation cascade. We conclude that EPEC exploits E1 enzymes to influence global protein regulatory cascades that are crucial for normal cellular functions. This novel strategy highlights that pathogens can exploit key targets to influence overall protein regulatory systems that are needed for normal cellular functions and disease progression. Grant Funding Source : CIHR
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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".