Novel regulation of equlibrative nucleoside transporter 1 (ENT1) by receptor-stimulated Ca<sup>2+</sup>-dependent calmodulin binding
Bibliographic record
Abstract
Equilibrative nucleoside transporters (ENTs) facilitate the flux of nucleosides, such as adenosine, and nucleoside analog (NA) drugs across cell membranes. A correlation between adenosine flux and calcium-dependent signaling has been previously reported; however, the mechanistic basis of these observations is not known. Here we report the identification of the calcium signaling transducer calmodulin (CaM) as an ENT1-interacting protein, via a conserved classic 1-5-10 motif in ENT1. Calcium-dependent human ENT1-CaM protein interactions were confirmed in human cell lines (HEK293, RT4, U-87 MG) using biochemical assays (HEK293) and the functional assays (HEK293, RT4), which confirmed modified nucleoside uptake that occurred in the presence of pharmacological manipulations of calcium levels and CaM function. Nucleoside and NA drug uptake was significantly decreased (∼12% and ∼39%, respectively) by chelating calcium (EGTA, 50 μM; BAPTA-AM, 25 μM), whereas increasing intracellular calcium (thapsigargin, 1.5 μM) led to increased nucleoside uptake (∼26%). Activation of N-methyl-d-aspartate (NMDA) receptors (in U-87 MG) by glutamate (1 mM) and glycine (100 μM) significantly increased nucleoside uptake (∼38%) except in the presence of the NMDA receptor antagonist, MK-801 (50 μM), or CaM antagonist, W7 (50 μM). These data support the existence of a previously unidentified novel receptor-dependent regulatory mechanism, whereby intracellular calcium modulates nucleoside and NA drug uptake via CaM-dependent interaction of ENT1. These findings suggest that ENT1 is regulated via receptor-dependent calcium-linked pathways resulting in an alteration of purine flux, which may modulate purinergic signaling and influence NA drug efficacy.
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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".