Transmembrane Topology of the Mammalian Slc11a2 Iron Transporter
Bibliographic record
Abstract
The mammalian Slc11a1 and Slc11a2 proteins define a large family of secondary metal transporters. Slc11a1 and Slc11a2 function as pH-dependent divalent cation transporters that play a critical role in host defenses against infections and in Fe2+ homeostasis, respectively. The position and polarity of individual transmembrane domains (TMD) of Slc11a2 were studied by an epitope tagging method based on the insertion of small antigenic hemagglutinin A (HA) peptides (YPYDVPDYAS) in predicted intra- or extracellular loops of the protein. The tagged proteins were expressed in transfected LLC-PK1 kidney cells and tested for transport activity, and the polarity of inserted tags with respect to the plasma membrane was determined by immunofluorescence in intact and permeabilized cells. HA epitope tags were inserted at positions 1, 98, 131, 175, 201, 243, 284, 344, 403, 432, 468, 504, and 561. Insertions at positions 98, 131, 175, 403, and 432 abrogated metal transport by Slc11a2, while insertions at positions 1, 201, 243, 284, 344, 468, 504, and 561 resulted in functional proteins. Topology mapping in functional HA-tagged Slc11a2 proteins indicated that the N-terminus (1), as well as loops delineated by TMD4-5 (201), TMD6-7 (284), and TMD10-11 (468), and C-terminus (561) are intracellular, while loops separating TMD5-6 (243), TMD7-8 (344), and TMD11-12 (504) are extracellular. These results are compatible with a topology of 12 transmembrane domains, with intracellular amino and carboxy termini. Structural models constructed by homology threading support this 12TMD topology and show 2-fold structural symmetry in the arrangement of membrane helices for TM1-5 and TM6-10 (conserved Slc11 hydrophobic core).
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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".