Phenotypic and proteomic characterization of the human erythroid progenitor continuum reveal dynamic changes in cell cycle and in metabolic pathways.
Julien PapoinHongxia YanMarjorie LeducMorgane Le GallAnupama NarlaJames PalisLaurie A SteinerPatrick G GallagherChristopher D HillyerEmilie-Fleur GautierNarla MohandasLionel BlancPublished in: American journal of hematology (2023)
Human erythropoiesis is a complex process leading to the production of 2.5 million red blood cells per second. Following commitment of hematopoietic stem cells to the erythroid lineage, this process can be divided into three distinct stages: erythroid progenitor differentiation, terminal erythropoiesis, and reticulocyte maturation. We recently resolved the heterogeneity of erythroid progenitors into four different subpopulations termed EP1-EP4. Here, we characterized the growth factor(s) responsiveness of these four progenitor populations in terms of proliferation and differentiation. Using mass spectrometry-based proteomics on sorted erythroid progenitors, we quantified the absolute expression of ~5500 proteins from EP1 to EP4. Further functional analyses highlighted dynamic changes in cell cycle in these populations with an acceleration of the cell cycle during erythroid progenitor differentiation. The finding that E2F4 expression was increased from EP1 to EP4 is consistent with the noted changes in cell cycle. Finally, our proteomic data suggest that the protein machinery necessary for both oxidative phosphorylation and glycolysis is present in these progenitor cells. Together, our data provide comprehensive insights into growth factor-dependence of erythroid progenitor proliferation and the proteome of four distinct populations of human erythroid progenitors which will be a useful framework for the study of erythroid disorders.
Keyphrases
- cell cycle
- growth factor
- cell proliferation
- mass spectrometry
- endothelial cells
- stem cells
- cell fate
- poor prognosis
- single cell
- induced pluripotent stem cells
- pluripotent stem cells
- binding protein
- machine learning
- liquid chromatography
- gene expression
- dna methylation
- mesenchymal stem cells
- protein kinase
- artificial intelligence
- high performance liquid chromatography
- tandem mass spectrometry
- data analysis