Lithocholic bile acid accumulated in yeast mitochondria orchestrates a development of an anti-aging cellular pattern by causing age-related changes in cellular proteome
Bibliographic record
Abstract
We have previously revealed that exogenously added lithocholic bile acid (LCA) extends the chronological lifespan of the yeast Saccharomyces cerevisiae, accumulates in mitochondria and alters mitochondrial membrane lipidome. Here, we use quantitative mass spectrometry to show that LCA alters the age-related dynamics of changes in levels of many mitochondrial proteins, as well as numerous proteins in cellular locations outside of mitochondria. These proteins belong to 2 regulons, each modulated by a different mitochondrial dysfunction; we call them a partial mitochondrial dysfunction regulon and an oxidative stress regulon. We found that proteins constituting these regulons (1) can be divided into several "clusters", each of which denotes a distinct type of partial mitochondrial dysfunction that elicits a different signaling pathway mediated by a discrete set of transcription factors; (2) exhibit 3 different patterns of the age-related dynamics of changes in their cellular levels; and (3) are encoded by genes whose expression is regulated by the transcription factors Rtg1p/Rtg2p/Rtg3p, Sfp1p, Aft1p, Yap1p, Msn2p/Msn4p, Skn7p and Hog1p, each of which is essential for longevity extension by LCA. Our findings suggest that LCA-driven changes in mitochondrial lipidome alter mitochondrial proteome and functionality, thereby enabling mitochondria to operate as signaling organelles that orchestrate an establishment of an anti-aging transcriptional program for many longevity-defining nuclear genes. Based on these findings, we propose a model for how such LCA-driven changes early and late in life of chronologically aging yeast cause a stepwise development of an anti-aging cellular pattern and its maintenance throughout lifespan.
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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) | 0.000 | 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".