The NAG Sensor NagC Regulates LEE Gene Expression and Contributes to Gut Colonization by Escherichia coli O157:H7
Bibliographic record
Abstract
Enterohemorrhagic Escherichia coli (EHEC) O157:H7 are human pathogens responsible for bloody diarrhea and renal failures. EHEC employ a type 3 secretion system to attach directly to the human colonic epithelium. This structure is encoded by the locus of enterocyte effacement (LEE) whose expression is regulated in response to specific nutrients. In this study, we show that the mucin-derived sugars N-acetylglucosamine (NAG) and N-acetylneuraminic acid (NANA) inhibit EHEC adhesion to epithelial cells through down-regulation of LEE expression. The effect of NAG and NANA is dependent on NagC, a transcriptional repressor of the NAG catabolism in E. coli. We show that NagC is an activator of the LEE1 operon and a critical regulator for the colonization of mice intestine by EHEC. Finally, we demonstrate that NAG and NANA as well as the metabolic activity of Bacteroides thetaiotaomicron affect the in vivo fitness of EHEC in a NagC-dependent manner. This study highlights the role of NagC in coordinating metabolism and LEE expression in EHEC and in promoting EHEC colonization in vivo.
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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".