Esrra regulates Rplp1-mediated translation of lysosome proteins suppressed in non-alcoholic steatohepatitis and reversed by alternate day fasting
Bibliographic record
Abstract
Abstract Background Currently, little is known about the mechanism(s) regulating global and specific protein translation during non-alcoholic steatohepatitis (NASH). Methods We used puromycin-labelling, polysome profiling, ChIPseq and ChIP-qPCR, and gene manipulation in vitro and in dietary mouse models of NASH in this study. Results Using unbiased label-free quantitative proteome, puromycin-labelling and polysome profiling, we observed a global decrease in protein translation during lipotoxicity in human primary hepatocytes, mouse hepatic AML12 cells, and livers from a dietary mouse model of NASH. Interestingly, proteomic analysis showed that Rplp1, which regulates ribosome and translation pathways, was one of the most downregulated proteins. Moreover, decreased Esrra expression and binding to the Rplp1 promoter, diminished Rplp1 gene expression during lipotoxicity. This, in turn, reduced global protein translation and Esrra/Rplp1-dependent translation of lysosome (Lamp2, Ctsd) and autophagy (sqstm1, Map1lc3b) proteins. Of note, Esrra did not increase its binding to these gene promoters or their gene transcription, confirming its regulation of their translation during lipotoxicity. Notably, hepatic Esrra-Rplp1-dependent translation of lysosomal and autophagy proteins also was impaired in NASH patients and liver-specific Esrra knockout mice. Remarkably, alternate day fasting induced Essra-Rplp1-dependent expression of lysosomal proteins, restored autophagy, and reduced lipotoxicity, inflammation, and fibrosis in hepatic cell culture and in vivo models of NASH. Conclusion Esrra regulation of Rplp1-mediated translation of lysosome / autolysosome proteins was downregulated during NASH. Alternate day fasting activated this novel pathway and improved NASH, suggesting that Esrra and Rplp1 may serve as therapeutic targets for NASH. Our findings also provided the first example of a nuclear hormone receptor, Esrra, to not only regulate transcription but also protein translation, via induction of Rplp1.
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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) | 0.002 | 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".