Mouse adult hematopoietic stem cells actively synthesize ribosomal RNA.
Léonard JarzebowskiMarie Le BouteillerSabrina CoqueranAurélien RaveuxSandrine Vandormael-PourninAlexandre DavidAna CumanoMichel Cohen-TannoudjiPublished in: RNA (New York, N.Y.) (2018)
The contribution of basal cellular processes to the regulation of tissue homeostasis has just started to be appreciated. However, our knowledge of the modulation of ribosome biogenesis activity in situ within specific lineages remains very limited. This is largely due to the lack of assays that enable quantitation of ribosome biogenesis in small numbers of cells in vivo. We used a technique, named Flow-FISH, combining cell surface antibody staining and flow cytometry with intracellular ribosomal RNA (rRNA) FISH, to measure the levels of pre-rRNAs of hematopoietic cells in vivo. Here, we show that Flow-FISH reports and quantifies ribosome biogenesis activity in hematopoietic cell populations, thereby providing original data on this fundamental process notably in rare populations such as hematopoietic stem and progenitor cells. We unravel variations in pre-rRNA levels between different hematopoietic progenitor compartments and during erythroid differentiation. In particular, our data indicate that, contrary to what may be anticipated from their quiescent state, hematopoietic stem cells have significant ribosome biogenesis activity. Moreover, variations in pre-rRNA levels do not correlate with proliferation rates, suggesting that cell type-specific mechanisms might regulate ribosome biogenesis in hematopoietic stem cells and progenitors. Our study contributes to a better understanding of the cellular physiology of the hematopoietic system in vivo in unperturbed situations.
Keyphrases
- stem cells
- bone marrow
- induced apoptosis
- cell cycle arrest
- signaling pathway
- healthcare
- single cell
- emergency department
- big data
- cell death
- endoplasmic reticulum stress
- cell therapy
- oxidative stress
- electronic health record
- mass spectrometry
- high throughput
- machine learning
- mesenchymal stem cells
- high resolution
- liquid chromatography tandem mass spectrometry
- adverse drug
- artificial intelligence
- high performance liquid chromatography
- genetic diversity
- drug induced