Metalloprotease NleC suppresses host NF-κB/inflammatory responses by cleaving p65 and interfering with the p65/RPS3 interaction (MPF7P.703)
Bibliographic record
Abstract
Abstract The NF-κB signaling pathway has long been recognized as a crucial activator and regulator of the innate and adaptive immune responses. More recently, the ribosomal protein, RPS3 has been identified as a non-rel component of NF-κB and functions as a “specifier” protein critical for the induction of selective proinflammatory gene transcription. Attaching/effacing pathogens including enteropathogenic Escherichia coli, enterohemorrhagic E. coli and the rodent equivalent Citrobacter rodentium are important causative agents of foodborne diseases. A/E pathogens have evolved many strategies to evade the host immune response and encode various effector proteins that target NF-κB at different stages. Our work here, demonstrates how the A/E encoded metalloprotease NleC, specifically cleaves the p65 molecule at the N-terminus generating a fragment that is capable of selectively blocking the function of RPS3. This selective blockade of RPS3 results in a dampened immune response following infection, which amplifies the effect of cleaving only a small percentage of p65 to modulate NF-κB-mediated gene expression. Thus, our results reveal a novel mechanism for A/E pathogens to specifically block NF-κB signaling and inflammatory responses by cleaving a small percentage of p65 and targeting the p65/RPS3 interaction in host cells, thus providing novel insights into the pathogenic mechanisms of foodborne diseases.
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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 | 0.001 |
| 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".