Genome-wide RNAi screen identifies ATPase inhibitory factor 1 (ATPIF1) as essential for PARK2 recruitment and mitophagy
Bibliographic record
Abstract
Mitochondrial dysfunction is a hallmark of aging and numerous human diseases, including Parkinson disease (PD). Multiple homeostatic mechanisms exist to ensure mitochondrial integrity, including the selective autophagic program mitophagy, that is activated during starvation or in response to mitochondrial dysfunction. Following prolonged loss of potential across the inner mitochondrial membrane (ΔΨ), PTEN-induced putative kinase 1 (PINK1) and the E3-ubiquitin ligase PARK2 work in the same pathway to trigger mitophagy of dysfunctional mitochondria. Mutations in PINK1 and PARK2, as well as PARK7/DJ-1, underlie autosomal recessive Parkinsonism and impair mitochondrial function and morphology. In a genome-wide RNAi screen searching for genes that are required for PARK2 translocation to the mitochondria, we identified ATPase inhibitory factor 1 (ATPIF1/IF1) as essential for PARK2 recruitment and mitophagy in cultured cells. During uncoupling, ATPIF1 promotes collapse of ΔΨ and activation of the PINK-PARK2 mitophagy pathway by blocking the ATPase activity of the F 1-Fo ATP synthase. Restoration of ATPIF1 in Rho0 cells, which lack mtDNA and a functional electron transport chain, lowers ΔΨ and triggers PARK2 recruitment. Our findings identified ATPIF1 and the ATP synthase as novel components of the PINK1-PARK2 mitophagy pathway and provide genetic evidence that loss of ΔΨ is an essential trigger for mitophagy.
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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".