Phenotypic and proteomic characterization of the human erythroid progenitor continuum reveal dynamic changes in cell cycle and in metabolic pathways

Abstract

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.

Figure 1.. Dose-dependence responses of erythroid progenitor subpopulations to growth factors.

Peripheral blood derived CD34+ cells were differentiated for 5 days in modified 3-phase medium as described in the methods and four erythroid progenitor populations including EP1, EP2, EP3 and EP4 were sorted and cultured for an additional 2 days according to the gating strategy presented in (A) for erythroid maturation in the presence of different doses of IL3, SCF and EPO. (B) No significant effects of IL3 on EPs proliferation were observed, with presence of 100 ng/mL SCF and 3 IU/mL EPO in all groups. (C) Representative flow cytometric plots of CD105 and GPA showing differentiation of sorted EPs with or without presence of IL3, after 2 days of culture. (D) No significant effects of IL3 on EPs differentiation were observed, as demonstrated by GPA+ %. (E) Effects of SCF on EPs proliferation, with presence of 3 IU/mL EPO in all groups. (F) Representative flow cytometric plots of CD105 and GPA showing differentiation progression of sorted EPs with presence of different concentration of SCF, after 2 days of culture. (G) Effects of SCF on EPs differentiation, as shown by GPA+ % after 2 days of differentiation. (H) Effects of EPO on EPs proliferation, with presence of 100 ng/mL SCF. (I) Representative analysis of EPs’ apoptosis with or without presence of different concentration of EPO, after 4 days of culture. (J) Representative flow cytometric plots of CD105 and GPA showing differentiation progression of sorted EPs with presence of different concentration of EPO, after 2 days of culture. (K) Effects of EPO on EPs differentiation, as shown by GPA+ % after 2 days of differentiation. Statistical significance was determined by two-tailed Student’s T-test (*p<0.05; **p<0.01; ***p<0.001). Means ± SEM are presented (n=3–4).

Figure 2.. Overview of proteomic data.

(A) Mean of quantified proteins for the different EPs. (B) Venn diagram showing shared proteins identified between EPs. (C) Heatmap of EPs mean log2(Copy number), the hierarchical clustering distance is Euclidean. (D) Principal Component Analysis done using z-score (Copy number) for proteins having at least 3 quantification values in a least one condition and after imputation of missing values. (E) Scatter plot representations and Pearson correlation factors for the most distant replicates at each EP stage.

Figure 3.. Evolution of specific proteins and dynamics of the proteome during erythroid progenitors’ differentiation.

Quantitative expression in copy number per cell of (A) erythroid-specific transcription factors, (B) transporters for cell nutrients and amino acids, (C) mitochondrial membrane transporters, and (D) ribosomal proteins. (E) Heatmap representation of z-score of proteins differentially expressed (Anova test with q-value < 5%). (F) TOP 20 of enriched pathways between each adjacent stage of progenitor differentiation selected on their p-value.

Figure 4.. Cell cycle analyses and identification of E2F4.

(A) Cyclin & Cell Cycle regulation pathway is the sixth most relevant pathway between the adjacent stages EP1 and EP2 according to IPA (p-value=2,96E-02). The 7 proteins involved in this pathway that are upregulated in EP2 compared to EP1 are colored in red. Some of them are grouped in the same shape. CCNA2 is annotated “Cyclin A” as CCNB1 & CCNB2 are merged in “Cyclin B”. ABL1 & E2F4 are members of “E2F-RB1”and PPP2R2A & PPP1R5D are grouped into “PP2A” node. Based on the seven experimental expression values and relationships between pathway’s nodes, IPA predicts the activation status of other involved proteins: blue ones are predicted to be inhibited and orange ones activated. As for cell cycle stages, IPA predicts that S phase event is promoted downstream of the cascade. (B) Cyclins and (C) Cyclin-dependent kinases expression during progenitors’ differentiation. (D) E2F4 protein expression in each progenitor stages. (E) Western blot analyses on sorted populations for the proteins indicated on the left. Statistical significance was determined by two-tailed Student’s T-test (*p<0.05; **p<0.01; ***p<0.001).

Figure 5.. Proliferation kinetics of EPs are coupled with distinct cell cycle patterns.

(A) Growth curve of sorted EP1, EP2, EP3 and EP4 under optimal concentration of SCF (100 ng/mL) and EPO (3 IU/mL). The red circle marks different proliferation kinetics of EPs. (B) Quantitative analysis of EPs proliferation after 2 days of in vitro culture. (C) Representative flow cytometric analysis of EPs proliferation in 2 days using CellTrace^™ Violet dye. (D) Quantitative analysis of Violet dye dilution using fold change of Median Fluorescence Intensity. (E) Representative flow cytometric plots showing stage-wise analysis of cell cycle kinetics during early erythropoiesis by EdU (5-ethynyl-2´-deoxyuridine) incorporation assay, using primary human bone marrow cells. (F) Quantitative analysis of EPs at the different phases of the cell cycle in the primary human bone marrow. (G) Normalized mean fluorescence intensity (MFI) of the S-phase for each EP and ProEB stage in primary bone marrow. (H) Representative flow cytometric plots showing stage-wise analysis of cell cycle kinetics during early erythropoiesis, using an in vitro model of human erythropoiesis. (I) Quantitative analysis of EPs at the different phases of the cell cycle in an in vitro model of human erythropoiesis. (J) Normalized mean fluorescence intensity (MFI) of the S-phase for each EP and ProEB stage in the in vitro system. Statistical significance was determined by two-tailed Student’s T-test except for (G and J) where ANOVA was used (*p<0.05; **p<0.01; ***p<0.001, #p<0.0001). Means ± SEM are presented (n=3–5).

Figure 6.. Metabolic regulation of erythroid progenitors.

(A) The MFI of the mitotracker green and mitotracker red was obtained for each EP population to determine the mitochondrial biomass and mitochondrial potential respectively. (B) Heatmap representation of mitochondrial proteins expression in z-score (Copy number). (C) Oxidative phosphorylation pathway is the eighth most activated pathway between the adjacent stages EP2 and EP1 according to IPA (z-score = 2.236). The 5 differentially involved proteins upregulated in EP2 compared to EP1 are colored in red. This trend is expected in the context of oxphos activated pathway. NDUFB9 & MT-ND5 are part of complex I, MT-CO2 (annotated “COX2”) in the complex IV and ATP5A1 in the complex V. As for CYCS, it belongs to “CYT C” group. Based on the five experimental expression values and relationships between pathway’s nodes, IPA predicts the upregulation of other involved proteins and downstream metabolites (orange nodes). (D) Expression of glycolytic enzymes. (E) Schematic representation of glycolysis along with the expression of the different proteins involved. (F) Differential expression of proteins between each adjacent stage of progenitors. Statistical significance was determined by two-tailed Student’s T-test (*p<0.05; **p<0.01; ***p<0.001). Means ± SEM are presented (n=5). ns: not significant.