Iron-dependent degradation of IRP2 requires its C-terminal region and IRP structural integrity
Bibliographic record
Abstract
BACKGROUND: Iron regulatory protein 2 (IRP2), a post-transcriptional regulator of cellular iron metabolism, undergoes iron-dependent degradation via the ubiquitin-proteasome pathway. A stretch of 73 amino acids within the N-terminal domain 1 of the protein was reported to function as an iron sensor. However, mutants lacking this fragment remain sensitive to degradation in iron-replete cells. RESULTS: To identify elements within IRP2 involved in the control of its stability, we undertook a systematic mutagenesis approach. Truncated versions of IRP2 were expressed in H1299 cells and analyzed for their response to iron. Deletion mutants lacking the entire C-terminal domain 4 (amino acids 719-963) of IRP2 remained stable following iron treatments. Moreover, the replacement of domain 4 of IRP1 with the corresponding region of IRP2 sensitized the chimerical IRP11-3/IRP24 protein to iron-dependent degradation, while the reverse manipulation gave rise to a stable chimerical IRP21-3/IRP14 protein. The deletion of just 26 or 34 C-terminal amino acids stabilized IRP2 against iron. However, the fusion of C-terminal IRP2 fragments to luciferase failed to sensitize the indicator protein for degradation in iron-loaded cells. CONCLUSION: Our data suggest that the C-terminus of IRP2 contains elements that are necessary but not sufficient for iron-dependent degradation. The functionality of these elements depends upon the overall IRP structure.
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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 | 0.001 |
| 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".