Ubiquinone-binding Site Mutations in the Saccharomyces cerevisiae Succinate Dehydrogenase Generate Superoxide and Lead to the Accumulation of Succinate
Bibliographic record
Abstract
The mitochondrial succinate dehydrogenase (SDH) is an essential component of the electron transport chain and of the tricarboxylic acid cycle. Also known as complex II, this tetrameric enzyme catalyzes the oxidation of succinate to fumarate and reduces ubiquinone. Mutations in the human SDHB, SDHC, and SDHD genes are tumorigenic, leading to the development of several types of tumors, including paraganglioma and pheochromocytoma. The mechanisms linking SDH mutations to oncogenesis are still unclear. In this work, we used the yeast SDH to investigate the molecular and catalytic effects of tumorigenic or related mutations. We mutated Arg(47) of the Sdh3p subunit to Cys, Glu, and Lys and Asp(88) of the Sdh4p subunit to Asn, Glu, and Lys. Both Arg(47) and Asp(88) are conserved residues, and Arg(47) is a known site of cancer causing mutations in humans. All of the mutants examined have reduced ubiquinone reductase activities. The SDH3 R47K, SDH4 D88E, and SDH4 D88N mutants are sensitive to hyperoxia and paraquat and have elevated rates of superoxide production in vitro and in vivo. We also observed the accumulation and secretion of succinate. Succinate can inhibit prolyl hydroxylase enzymes, which initiate a proliferative response through the activation of hypoxia-inducible factor 1alpha. We suggest that SDH mutations can promote tumor formation by contributing to both reactive oxygen species production and to a proliferative response normally induced by hypoxia via the accumulation of succinate.
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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) | 0.001 | 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".