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Transcriptional Induction of Transferrin Receptors By Heme in Erythroid Cells

2015· article· en· W4249401145 on OpenAlexaff
Daniel Garcia‐Santos, Matthias Schranzhofer, Nam Lok Chun, Amel Hamdi, Prem Ponka

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsTransferrin receptorTransferrinEndosomeEndocytic cycleEndocytosisBiologyCell biologyReceptorAsialoglycoprotein receptorMolecular biologyBiochemistryIntracellularIn vitroHepatocyte

Abstract

fetched live from OpenAlex

Abstract The transferrin receptor (TfR) is a membrane glycoprotein whose only clearly defined function is to mediate cellular uptake of iron (Fe) from a plasma glycoprotein, transferrin. Iron uptake from diferric transferrin (Tf) involves the binding of transferrin to the TfR followed by internalization of Tf within an endocytic vesicle by receptor-mediated endocytosis. Iron is then released from transferrin within endosomes by a combination of Fe3+ reduction by Steap3 (likely when transferrin is still bound to TfR) and a decrease in pH (~pH 5.5). Following this, Fe2+ is transported across the endosomal membrane by DMT1. Transferrin receptors are highly expressed on immature erythroid cells, placental tissue, and rapidly dividing cells, both normal and malignant. In proliferating nonerythroid cells the expression of TfR is negatively regulated post-transcriptionally by intracellular iron through iron responsive elements (IREs) in the 3' untranslated region (UTR) of transferrin receptor mRNA. IREs are recognized by specific cytoplasmic proteins (iron regulatory proteins; IRPs) that, in the absence of iron in the labile pool, bind to the IREs of transferrin receptor mRNA, preventing its degradation. On the other hand, the expansion of the labile iron pool leads to a rapid degradation of transferrin receptor mRNA that is not protected, since IRPs are not bound to it. However, some cells and tissues with specific requirements for iron probably evolved mechanisms that can override the IRE/IRP-dependent control of transferrin receptor expression. We previously documented that the TfR gene promoter contains an erythroid active element that stimulates the receptor gene transcription upon induction of hemoglobin synthesis (1). In this study we have demonstrated that incubation of erythroid cells with 5-aminolevulinic acid (ALA) increased TfR expression as well as 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 primarily a result of increased mRNA synthesis, since the effect of ALA can be abolished by actinomycin D. Moreover, we found that the TfR promoter was activated in vitro by the addition of ALA or hemin to murine erythroleukemia (MEL) cells induced to differentiate using DMSO. Furtehermore, site-directed mutation of erythroid active element (1) in the TfR promoter abolished the effects of ALA or hemin. These results indicate that heme may directly or indirectly interact with the TfR promoter, consequently enhancing the gene expression. Hence, our results show that in erythroid cells heme serves as a positive feedback regulator that maintains high TfR levels thus ensuring adequate iron availability for hemoglobin synthesis. In conclusion, erythroid cells, which are the most avid consumers of iron in the organism, use a transcriptional mechanism to maintain very high transferrin receptor levels. 1 Chun-Nam Lok Ponka P. (2000) Identification of an Erythroid Active Element in the Transferrin Receptor Gene. J. Biol. Chem. 275: 24185-24190. Disclosures No relevant conflicts of interest to declare.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.021
GPT teacher head0.240
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations1
Published2015
Admission routes1
Has abstractyes

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