Nitric Oxide Storage and Transport in Cells Are Mediated by Glutathione S-Transferase P1-1 and Multidrug Resistance Protein 1 via Dinitrosyl Iron Complexes
Bibliographic record
Abstract
Nitrogen monoxide (NO) plays a role in the cytotoxic mechanisms of activated macrophages against tumor cells by inducing iron release. We showed that NO-mediated iron efflux from cells required glutathione (GSH) (Watts, R. N., and Richardson, D. R. (2001) J. Biol. Chem. 276, 4724-4732) and that the GSH-conjugate transporter, multidrug resistance-associated protein 1 (MRP1), mediates this release potentially as a dinitrosyl-dithiol iron complex (DNIC; Watts, R. N., Hawkins, C., Ponka, P., and Richardson, D. R. (2006) Proc. Natl. Acad. Sci. U.S.A. 103, 7670-7675). Recently, glutathione S-transferase P1-1 (GST P1-1) was shown to bind DNICs as dinitrosyl-diglutathionyl iron complexes. Considering this and that GSTs and MRP1 form an integrated detoxification unit with chemotherapeutics, we assessed whether these proteins coordinately regulate storage and transport of DNICs as long lived NO intermediates. Cells transfected with GSTP1 (but not GSTA1 or GSTM1) significantly decreased NO-mediated 59Fe release from cells. This NO-mediated 59Fe efflux and the effect of GST P1-1 on preventing this were observed with NO-generating agents and also in cells transfected with inducible nitric oxide synthase. Notably, 59Fe accumulated in cells within GST P1-1-containing fractions, indicating an alteration in intracellular 59Fe distribution. Furthermore, electron paramagnetic resonance studies showed that MCF7-VP cells transfected with GSTP1 contain significantly greater levels of a unique DNIC signal. These investigations indicate that GST P1-1 acts to sequester NO as DNICs, reducing their transport out of the cell by MRP1. Cell proliferation studies demonstrated the importance of the combined effect of GST P1-1 and MRP1 in protecting cells from the cytotoxic effects of NO. Thus, the DNIC storage function of GST P1-1 and ability of MRP1 to efflux DNICs are vital in protection against NO cytotoxicity.
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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".