Transcriptional Regulation of Transferrin Receptor by Heme in Erythroid Cells
Bibliographic record
Abstract
Abstract Abstract 2049 Erythroid cells are the largest consumers of iron which is delivered to them by tansferrin (Tf) by its cognate receptor (TfR). In contrast to other cells, developing red blood cells (RBC) regulate TfR expression not only at the level of mRNA stability via the iron regulatory proteins (IRP) 1 and 2, but also by transcription (Lok & Ponka, J Biol Chem 275:24185-90, 2000). Here we provide evidence that TfR expression and cellular uptake of iron from Tf is stimulated by enhanced heme synthesis. Incubation of erythroid cells with 5-aminolevulinic acid (ALA) increased TfR expression accompanied by increased iron incorporation into heme. This effect of ALA can be completely prevented by the inhibitors of heme biosynthesis (succinylacetone [blocks ALA dehydratase] or N-methylprotoporphyrin [blocks ferrochelatase]), indicating that the effect of ALA requires its metabolism to heme. The induction of TfR mRNA expression by ALA is mainly a result of increased mRNA synthesis since the effect of ALA can be abolished by actinomycin D. Recently, IRP2 was proposed to play a role in maintaining TfR mRNA stability in developing RBC (Cooperman et al., Blood 106:1084-91; 2005; Galy et al., Blood 106:2580-9, 2005). Importantly, we have demonstrated that ALA added to cultures of erythroid cells derived from IRP2 knock out mice restores the expression of TfR to levels observed in cells obtained from wild type mice. In conclusion, our results indicate that in erythroid cells heme serves as a positive feedback regulator that maintains high TfR levels thus ensuring adequate iron availability for hemoglobin synthesis. Disclosures: No relevant conflicts of interest to declare.
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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".