Transcriptomic analysis of cells following decreased mitochondrial DNA-copy number reveals compensatory mechanisms in mitochondrial DNA replication and cellular energetics
Bibliographic record
Abstract
Mitochondrial DNA copy number (mtDNA-CN) is a metric of mitochondrial function that has been associated with a variety of diseases including cardiovascular disease and all-cause mortality. To investigate genes and pathways affected by mtDNA-CN variation, we perturbed HEK 293T cells with ethidium bromide to deplete mtDNA. Using RNASeq and methylation microarrays, we evaluated transcriptomic and methylomic changes in treated cell lines. We observed an 8-fold decrease in mtDNA-CN and compensatory shifts in mitochondrial transcription to support mtDNA replication. Nuclear transcriptomic and methylomic analysis highlighted changes in metabolic pathways, including oxidative phosphorylation and canonical glycolysis. Longitudinal analyses revealed that the identified genes and pathways have different response timing, with nuclear response lagging behind mitochondrial response. These findings further elucidate the mechanisms behind mtDNA maintenance and responses to cellular energetics as well as mitochondrial-nuclear crosstalk dynamics.
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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) | 0.002 | 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".