bioRxivMolecular BiologyPreprint
Estrogen receptor-related receptor (Esrra) induces ribosomal protein Rplp1-mediated adaptive hepatic translation during prolonged starvation
Madhulika Tripathi, Karine Cécile GauthieriD, Reddemma Sandireddy, Jin ZhouiD, Priyanka Soni GuptaiD, Suganya Sakthivel, Nah Jiemin, Kabilesh AruliD, Keziah TiknoiD, Sung-Hee Park, Lijin WangiD, Lena HoiD, Vincent GiguèreiD, Sujoy GhoshiD, Donald Patrick McDonnelliD, Paul M. YeniD, Brijesh Kumar SinghiD
Abstract
Protein translation is an energy-intensive ribosome-driven process that is reduced during nutrient scarcity to conserve cellular resources. During prolonged starvation, cells selectively translate specific proteins to enhance their survival (adaptive translation); however, this process is poorly understood. Accordingly, we analyzed protein translation and mRNA transcription by multiple methods in vitro and in vivo to investigate adaptive hepatic translation during starvation. While acute starvation suppressed protein translation in general, proteomic analysis showed that prolonged starvation selectively induced translation of lysosome and autolysosome proteins. Significantly, the expression of the orphan nuclear receptor, estrogen-related receptor alpha (Esrra) increased during prolonged starvation and served as a master regulator of this adaptive translation by transcriptionally stimulating 60S acidic ribosomal protein P1 (Rplp1) gene expression. Overexpression or siRNA knockdown of Esrra expression in vitro or in vivo led to parallel changes in Rplp1 gene expression, lysosome/autophagy protein translation, and autophagy. Remarkably, we have found that Esrra had dual functions by not only regulating transcription but also controling adaptive translation via the Esrra/Rplp1/lysosome/autophagy pathway during prolonged starvation.
- organism: mouse
- assay: proteomics
- assay: multiome
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: cell-cell communication
- approach: statistical model
- approach: experimental assay
- Citations
- 2
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