P2X7 receptor cross-talk regulates ATP-induced pannexin 1 internalization
Bibliographic record
Abstract
In the nervous system, extracellular ATP levels transiently increase in physiological and pathophysiological circumstances, effecting key signalling pathways in plasticity and inflammation through purinergic receptors. Pannexin 1 (Panx1) forms ion- and metabolite-permeable channels that mediate ATP release and are particularly enriched in the nervous system. Our recent study demonstrated that elevation of extracellular ATP triggers Panx1 internalization in a concentration- and time-dependent manner. Notably, this effect was sensitive to inhibition of ionotropic P2X7 purinergic receptors (P2X7Rs). Here, we report our novel findings from the detailed investigation of the mechanism underlying P2X7R–Panx1 cross-talk in ATP-stimulated internalization. We demonstrate that extracellular ATP triggers and is required for the clustering of P2X7Rs and Panx1 on Neuro2a cells through an extracellular physical interaction with the Panx1 first extracellular loop (EL1). Importantly, disruption of P2X7R–Panx1 clustering by mutation of tryptophan 74 within the Panx1 EL1 inhibits Panx1 internalization. Notably, P2X7R–Panx1 clustering and internalization are independent of P2X7R-associated intracellular signalling pathways (Ca2+ influx and Src activation). Further analysis revealed that cholesterol is required for ATP-stimulated P2X7R–Panx1 clustering at the cell periphery. Taken together, our data suggest that extracellular ATP induces and is required for Panx1 EL1-mediated, cholesterol-dependent P2X7R–Panx1 clustering and endocytosis. These findings have important implications for understanding the role of Panx1 in the nervous system and provide important new insights into Panx1–P2X7R cross-talk.
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 | 0.001 | 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".