PRKN/parkin-mediated mitophagy is induced by the probiotics <i>Saccharomyces boulardii</i> and <i>Lactococcus lactis</i>
Bibliographic record
Abstract
Mitochondrial impairment is a hallmark feature of neurodegenerative disorders, such as Parkinson disease, and PRKN/parkin-mediated mitophagy serves to remove unhealthy mitochondria from cells. Notably, probiotics are used to alleviate several symptoms of Parkinson disease including impaired locomotion and neurodegeneration in preclinical studies and constipation in clinical trials. There is some evidence to suggest that probiotics can modulate mitochondrial quality control pathways. In this study, we screened 49 probiotic strains and tested distinct stages of mitophagy to determine whether probiotic treatment could upregulate mitophagy in cells undergoing mitochondrial stress. We found two probiotics, Saccharomyces boulardii and Lactococcus lactis, that upregulated mitochondrial PRKN recruitment, phospho-ubiquitination, and MFN degradation in our cellular assays. Administration of these strains to Drosophila that were exposed to paraquat, a mitochondrial toxin, resulted in improved longevity and motor function. Further, we directly observed increased lysosomal degradation of dysfunctional mitochondria in the treated Drosophila brains. These effects were replicated in vitro and in vivo with supra-physiological concentrations of exogenous soluble factors that are released by probiotics in cultures grown under laboratory conditions. We identified methyl-isoquinoline-6-carboxylate as one candidate molecule, which upregulates mitochondrial PRKN recruitment, phospho-ubiquitination, MFN degradation, and lysosomal degradation of damaged mitochondria. Addition of methyl-isoquinoline-6-carboxylate to the fly food restored motor function to paraquat-treated Drosophila. These data suggest a novel mechanism that is facilitated by probiotics to stimulate mitophagy through a PRKN-dependent pathway, which could explain the potential therapeutic benefit of probiotic administration to patients with Parkinson disease.
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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".