Molecular CellGenomicsPeer-reviewed journal article
In vivo single-cell ribosome profiling reveals cell-type-specific translational programs during aging
Clara DuréiD, Umesh GhoshdastideriD, Ramona WeberiD, Ameya KhandekariD, Fabiola Valdivia-FranciaiD, Peter F. RenziD, Federica SellaiD, Katie HyamsiD, David TaborskyiD, Merve YiğitiD, Mark Ormiston, Homare YamahachiiD, Mitchell Paul LevesqueiD, Stephanie J. EllisiD, Ataman SendoeliD
Abstract
Somatic stem cells are characterized by their low overall protein synthesis rates, a feature implicated in driving their stemness. However, how aging reshapes the translational landscape of stem cells and how these changes impact their regenerative capacity remains poorly understood. Here, we present an in vivo single-cell ribosome profiling strategy to monitor tissue-wide translational landscapes of the young and aged mouse epidermis. By implementing ribosomal elongation-inhibited cell isolation and switching to RNase I ribonuclease for generating ribosomal footprints, we expand the applicability of single-cell ribosome profiling to in vivo systems and facilitate the evaluation of triplet periodicity, a hallmark of high-quality ribosome profiling data. Leveraging this strategy and integrating ribosome profiling with single-cell RNA sequencing, we document the in vivo translational landscapes of the major epidermal cell types, outline cell-type-specific translational efficiencies and capture heterogeneity in differentiation commitment within stem cell populations. Notably, we identify a pronounced translational reprogramming of AP-1 subunits specifically in aged epidermal stem cells, with functional consequences for keratinocyte behavior. Our study illustrates the power of in vivo single-cell ribosome profiling to map cell-type-specific translational programs and offers a scalable strategy for tissue-wide interrogation of translational landscapes at single-cell resolution.
- organism: mouse
- assay: Ribo-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: experimental assay
- Citations
- 3
- FWCI
- 4.09
- Field percentile
- top 10%
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