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Analysis of mRNA expression of livers from (PR)97 expressing mice

GSE239319 Mus musculus Expression profiling by high throughput sequencing 4 samples Submitted 2024/03/08 Platform GPL19057
Summary
Nucleolar stress (NS) kills cells by p53-dependent and independent manners. To investigate the mechanisms of p53-indendendent toxicity, we here used (PR)n arginine-rich peptides as inducers of NS, which are found in patients of some neurodegenerative diseases. Although these peptides generate NS, how this translates to toxicity is poorly understood. We here reveal that whereas (PR)n expression leads to an overall decrease in protein abundance for the majority of the proteome, this occurs concomitant to an accumulation of free ribosomal proteins in the cytoplasm, which is a hallmark of ribosomopathies. Conversely, cells with acquired resistance to (PR)n peptides present a global downregulation of ribosomal proteins and low levels of mTOR signaling. In mice, systemic expression of (PR)97 drives widespread NS and accelerated ageing, associated to an increased expression of ribosomal proteins and mTOR hyperactivation. Furthermore, the progeroid phenotype of (PR)97-expressing mice is alleviated by rapamycin. Importantly, we show that the generalized accumulation of free ribosomal proteins is not restricted to (PR)n peptides, but is a common outcome in response to chemical or genetic perturbations that generate NS such as Actinomycin D, TIF-IA depletion or the expression or mutant HMGB1 forms recently associated to rare human diseases. Together, our study provides in vivo evidence for the role of NS as a driver of ageing in mammals, and describes a general model to understand the mechanisms behind p53-independent cell toxicity caused by NS.
Published in
Nucleolar stress caused by arginine-rich peptides triggers a ribosomopathy and accelerates aging in mice
Sirozh O, Saez-Mas A, Jung B et al. · Molecular cell 2024 · PMID 38521064 · doi:10.1016/j.molcel.2024.02.031
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Also filed as BioProject PRJNA998808 and SRA study SRP451628. Searching any of these in the dataset finder brings you back here.

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