pH-dependent Internalization of Muramyl Peptides from Early Endosomes Enables Nod1 and Nod2 Signaling
Bibliographic record
Abstract
Nod1 and Nod2 are members of the Nod-like receptor family that detect intracellular bacterial peptidoglycan-derived muramyl peptides. The biological effects of muramyl peptides have been described for over three decades, but the mechanism underlying their internalization to the cytosol remains unclear. Using the human epithelial cell line HEK293T as a model system, we demonstrate here that Nod1-activating ligands entered cells through endocytosis, most likely by the clathrin-coated pit pathway, as internalization was dynamin-dependent but not inhibited by methyl-beta-cyclodextrin. In the endocytic pathway, the cytosolic internalization of Nod1 ligands was pH-dependent, occurred prior to the acidification mediated by the vacuolar ATPase, and was optimal at pH ranging from 5.5 to 6. Similarly, the Nod2 ligand MDP was internalized into host cytosol through a similar pathway with optimal pH for internalization ranging from 5.5 to 6.5. Moreover, Nod1-activating muramyl peptides likely required processing by endosomal enzymes, prior to transport into the cytosol, suggesting the existence of a sterically gated endosomal transporter for Nod1 ligands. In support for this, we identified a role for SLC15A4, an oligopeptide transporter expressed in early endosomes, in Nod1-dependent NF-kappaB signaling. Interestingly, SLC15A4 expression was also up-regulated in colonic biopsies from patients with inflammatory bowel disease, a disorder associated with mutations in Nod1 and Nod2. Together, our results shed light on the mechanisms by which muramyl peptides get access to the host cytosol, where they are detected by Nod1 and Nod2, and might have implications for the understanding of human diseases, such as inflammatory bowel disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".