Substrate Profile and Metal-ion Selectivity of Human Divalent Metal-ion Transporter-1
Bibliographic record
Abstract
Divalent metal-ion transporter-1 (DMT1) is a H(+)-coupled metal-ion transporter that plays essential roles in iron homeostasis. DMT1 exhibits reactivity (based on evoked currents) with a broad range of metal ions; however, direct measurement of transport is lacking for many of its potential substrates. We performed a comprehensive substrate-profile analysis for human DMT1 expressed in RNA-injected Xenopus oocytes by using radiotracer assays and the continuous measurement of transport by fluorescence with the metal-sensitive PhenGreen SK fluorophore. We provide validation for the use of PhenGreen SK fluorescence quenching as a reporter of cellular metal-ion uptake. We determined metal-ion selectivity under fixed conditions using the voltage clamp. Radiotracer and continuous measurement of transport by fluorescence assays revealed that DMT1 mediates the transport of several metal ions that were ranked in selectivity by using the ratio I(max)/K(0.5) (determined from evoked currents at -70 mV): Cd(2+) > Fe(2+) > Co(2+), Mn(2+) ≫ Zn(2+), Ni(2+), VO(2+). DMT1 expression did not stimulate the transport of Cr(2+), Cr(3+), Cu(+), Cu(2+), Fe(3+), Ga(3+), Hg(2+), or VO(+). (55)Fe(2+) transport was competitively inhibited by Co(2+) and Mn(2+). Zn(2+) only weakly inhibited (55)Fe(2+) transport. Our data reveal that DMT1 selects Fe(2+) over its other physiological substrates and provides a basis for predicting the contribution of DMT1 to intestinal, nasal, and pulmonary absorption of metal ions and their cellular uptake in other tissues. Whereas DMT1 is a likely route of entry for the toxic heavy metal cadmium, and may serve the metabolism of cobalt, manganese, and vanadium, we predict that DMT1 should contribute little if at all to the absorption or uptake of zinc. The conclusion in previous reports that copper is a substrate of DMT1 is not supported.
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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 | 0.001 |
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".