Identification and characterization of a novel family of membrane magnesium transporters, MMgT1 and MMgT2
Bibliographic record
Abstract
Magnesium is an essential metal, but few selective transporters have been identified at the molecular level. Microarray analysis was used to identify two similar transcripts that are upregulated with low extracellular Mg(2+). The corresponding cDNAs encode proteins of 131 and 123 amino acids with two predicted transmembrane domains. The two separate gene products comprise the family that we have termed "membrane Mg(2+) transporters" (MMgTs), because the proteins reside in the membrane and mediate Mg(2+) transport. When expressed in Xenopus laevis oocytes, MMgT1 and MMgT2 mediate Mg(2+) transport as determined with two-electrode voltage-clamp analysis and fluorescence measurements. Transport is saturable Mg(2+) uptake with Michaelis constants of 1.47 +/- 0.17 and 0.58 +/- 0.07 mM, respectively. Real-time RT-PCR demonstrated that MMgT mRNAs are present in a wide variety of cells. Subcellular localization with immunohistochemistry determined that the MMgT1-hemagglutinin (HA) and MMgT2-V5 fusion proteins reside in the Golgi complex and post-Golgi vesicles, including the early endosomes in COS-7 cells transfected with the respective tagged constructs. Interestingly, MMgT1-HA and MMgT2-V5 were found in separate populations of post-Golgi vesicles. MMgT1 and MMgT2 mRNA increased by about threefold, respectively, in kidney epithelial cells cultured in low-magnesium media relative to normal media and in the kidney cortex of mice maintained on low-magnesium diets compared with those animals consuming normal diets. With the increase in transcripts, there was an apparent increase in MMgT1 and MMgT2 protein in the Golgi and post-Golgi vesicles. These experiments suggest that MMgT proteins may provide regulated pathways for Mg(2+) transport in the Golgi and post-Golgi organelles of epithelium-derived cells.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".