Copper Modulates the Degradation of Copper Chaperone for Cu,Zn Superoxide Dismutase by the 26 S Proteosome
Bibliographic record
Abstract
Copper chaperones are copper-binding proteins that directly insert copper into specific targets, preventing the accumulation of free copper ions that can be toxic to the cell. Despite considerable advances in the understanding of copper transfer from copper chaperones to their target, to date, there is no information regarding how the activity of these proteins is regulated in higher eukaryotes. The insertion of copper into the antioxidant enzyme Cu,Zn superoxide dismutase (SOD1) depends on the copper chaperone for SOD1 (CCS). We have recently reported that CCS protein is increased in tissues of rats fed copper-deficient diets suggesting that copper may regulate CCS expression. Here we show that whereas copper deficiency increased CCS protein in rats, mRNA level was unaffected. Rodent and human cell lines cultured in the presence of the specific copper chelator 2,3,2-tetraamine displayed a dose-dependent increase in CCS protein that could be reversed with the addition of copper but not iron or zinc to the cells. Switching cells from copper-deficient to copper-rich medium promoted the rapid degradation of CCS, which could be blocked by the proteosome inhibitors MG132 and lactacystin but not a cysteine protease inhibitor or inhibitors of the lysosomal degradation pathway. In addition, CCS degradation was slower in copper-deficient cells than in cells cultured in copper-rich medium. Together, these data show that copper regulates CCS expression by modulating its degradation by the 26 S proteosome and suggest a novel role for CCS in prioritizing the utilization of copper when it is scarce.
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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".