Metabolism-Induced Oxidative Stress and DNA Damage Selectively Trigger Genome Instability in Polyploid Cells
Bibliographic record
Abstract
Abstract Understanding the forces impacting genome stability is important for diverse processes such as tumorigenesis and reproductive biology. The pathogenic yeast Candida albicans displays unusual genome dynamics in which tetraploid cells, but not diploid cells, become unstable when grown on a glucose-rich ‘pre-sporulation’ medium. Here, we reveal that C. albicans polyploid cells are metabolically hyperactive on this medium as evidenced by increased expression of metabolic genes as well as higher rates of fermentation and oxidative respiration. These cells also show elevated levels of reactive oxygen species (ROS), activate the ROS-responsive transcription factor Cap1, and accrue DNA double-strand breaks. Suppression of ROS levels reduced oxidative stress, DNA damage and chromosome instability. These studies reveal how metabolic flux can generate endogenous ROS, triggering DNA damage and genome instability in polyploid, but not diploid, cells. We discuss parallels with metabolism-induced instability in cancer cells and propose that ROS-induced DNA damage could have facilitated ploidy cycling in eukaryotes prior to the evolution of meiosis.
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 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) | 0.002 | 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".