Expression and characterization of soluble transferrin receptor in BHK cells: effect of mutations at the three asparagine glycosylation sites
Bibliographic record
Abstract
Transferrin (TF) is a bilobal iron transport protein that specifically binds to receptors (TFR) on the cell surface and delivers iron to cells by a process involving receptor mediated endocytosis and a pH change. The TF binding portion of the TFR (residues 121–760) containing a hexa‐His tag has been expressed by baby hamster kidney (BHK) cells as a secreted entity. TFR has three Asn linked glycosylation sites at position 251, 317 and 727. To prevent glycosylation at each site, three single point mutants in which Asn is mutated to Asp have been constructed. For wild type (WT), N251D and N727D TFR a maximum of 40 mg/L is produced, whereas maximum production of the N317D TFR mutant is considerably lower. Characterization of the WT and the mutant TFR constructs includes analysis by mass spectrometry and estimation of binding constants for interaction with diferric TF, monoferric TF C‐lobe (Fe C ‐TF) and a Fe C ‐TF mutant. Additionally the rate of iron release from Fe C ‐TF in the presence and absence of the various TFR constructs has been determined. The N317D TFR mutant binds more weakly to Fe C ‐TF and shows a reduced ability to stimulate the release of iron from Fe C ‐TF at pH 5.6 compared to WT TFR and the other two mutants. A structural basis for these findings is presented. This work was supported by USPHS Grant R01 DK 21739 (ABM) and R01 GM061666 (IAK).
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".