Int J Stem Cells.  2022 May;15(2):122-135. 10.15283/ijsc21044.

The Differentiation of Pluripotent Stem Cells towards Endothelial Progenitor Cells – Potential Application in Pulmonary Arterial Hypertension

• Qin K
• Lei J
• Yang J

• KMID: 2529784
• DOI: http://doi.org/10.15283/ijsc21044

Abstract

Background and Objectives
Endothelial progenitor cells (EPCs) and endothelial cells (ECs) have been applied in the clinic to treat pulmonary arterial hypertension (PAH), a disease characterized by disordered pulmonary vasculature. However, the lack of sufficient transplantable cells before the deterioration of disease condition is a current limitation to apply cell therapy in patients. It is necessary to differentiate pluripotent stem cells (PSCs) into EPCs and identify their characteristics.
Methods and Results
Comparing previously reported methods of human PSCs-derived ECs, we optimized a highly efficient differentiation protocol to obtain cells that match the phenotype of isolated EPCs from healthy donors. The protocol is compatible with chemically defined medium (CDM), it could produce a large number of clinically applicable cells with low cost. Moreover, we also found PSCs-derived EPCs express CD133, have some characteristics of mesenchymal stem cells and are capable of homing to repair blood vessels in zebrafish xenograft assays. In addition, we further revealed that IPAH PSCs-derived EPCs have higher expression of proliferation-related genes and lower expression of immune-related genes than normal EPCs and PSCs-derived EPCs through microarray analysis.
Conclusions
In conclusion, we optimized a highly efficient differentiation protocol to obtain PSCs-derived EPCs with the phenotypic and molecular characteristics of EPCs from healthy donors which distinguished them from EPCs from PAH.

Keyword

Stem cell differentiation; Endothelial cell; Endothelial progenitor cell; Pulmonary arterial hypertension

Figure

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  Fig. 1 Identifying induction factors for PSCs-derived EPCs. (A) A schematic diagram of inducing human PSCs-derived ECs. (B) The impact of cell seeding number on differentia-tion efficiency of PSCs-derived EC was analysed by flow cytometry. (C) In the second step of PSCs-derived EC differentiation, flow cytometry analysis showed adding BMP4 promoted PSCs-derived EC differentia-tion efficiency. (D, E) In the second step of EC differentiation, increasing SB431542 dose (5∼20 μM) promoted PSCs-derived EC differentia-tion efficiency. (F, G) The inhibitor Y27632 enhanced 202-iPSCs-deri-ved EC differentiation efficiency in the first step of differentiation in which Y27632 was used for three days. Statistics of CD31＋CD34＋ cells, CD31＋ cells, CD34＋ cells and CD43＋ cells. Data are represented as the mean±SD. n=3∼4, the experiments were repeated more than three independent times. Student’s t test was performed (*p<0.05, **p< 0.01, ***p<0.001).

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  Fig. 2 DMSO improves EC and HE cell differentiation efficiency. (A, B) PSCs-derived EC (H1EC) differentia-tion efficiency increased when the cells were treated with DMSO in the first step for one day or three days. Statistics of CD31＋CD34＋ cells, CD31＋ cells, CD34＋ cells and CD43＋ cells were analysed by flow cytometry. (C, D) Improved protocol for the HE differentiation of PSCs. A schematic digram of the stepwise induction process was shown. DMSO treatment for three days in the first step promoted the differentiation efficiency as analysed by flow cyto-metry. Statistics of APLNR＋ cells, CD31＋CD34＋ cells, CD31＋ cells, CD34＋ cells and CD43＋cells. Data were represented as the mean±SD, n=3∼4, and the experiments were repeated more than three times. Student’s t test was performed (ns: not significant, **p<0.01，****p< 0.0001).

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  Fig. 3 Improved protocol for the highly efficient differentiation rate of PSCs-derived ECs. (A) Schematic diagram of inducing human PSCs-derived ECs via a mesoderm interme-diate. (B) Representative yields of APLNR＋ cells as analysed by flow cytometry. (C) Representative yields of CD34＋CD31＋ cells and CD43＋ cells were analysed by flow cytome-try after 7 days of differentiation. (D) Statistics of CD31＋CD34＋ and CD43＋ cells. Data were represented as the mean±SD, n=3, and the experiments were repeated three independent times.

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  Fig. 4 The functional characteristics of PSCs-derived ECs. (A) Uptake assay of Dil-acetylated LDL by the cells (scale bars: 50 μm). (B) Tube formation assay of H1-derived ECs after 4 hours and 12 hours (scale bars: 500 μm). (C) Brief outline of Zebrafish experiments. (D) Vascular competence of PSCs-derived ECs in a zebrafish xenograft model. Representative image of ECs-derived vessel-type structures (in red) within embryonic zebrafish (Flk: GFP; in green) 2 days after implantation, with magnification of the vessel. Scale bars are 300 μm. (E) Using a zebrafish model for gene therapy. Data were represented as the mean±SD, n=3, the experiments were repeated three times with 20∼30 fish per condition. Student’s t test was performed (*p<0.05). (F) CD34＋EPCs (labelled with FITC-CD34, green) were injected into the ventral end of the duct of Cuvier of Zebra fish, the cells stained with green fluorescence incorporated into the vasculature of kdr1:mcherry (red) line at 24 hour and 48 hour.

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  Fig. 5 PSCs-derived ECs have characteristics of EPCs. (A) Comparison of the cell morphology of PSCs-derived ECs (H7EC, 202EC) with peripheral blood-derived normal EPCs (normal EPC1, normal EPC2) and IPAH-EPCs (IPAH EPC1, IPAH EPC2) (scale bars: 50 μm). (B) qRT-PCR of NRP1, which was reported to promote ECFC proliferation. GAPDH was used as an internal control. (C) ECs from DAY 5 or DAY 7 were analysed by the expression of the genes CD133, EFNB2, and EPHB4. GAPDH was used as an internal control. Data were represented as the mean±SD, n=3, and the experiments were repeated three times and analysed with student’s t test (*p<0.05, **p< 0.01, ***p<0.001).

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  Fig. 6 Bioinformatics analysis further reveals the characteristics of PSCs-derived EPCs. (A, B) Heatmap of EC-related genes from the 2D_MG_H1EC and 2D_MG_HUVEC datasets from GSE93511 and our microarray data in IPAH-EPCs (IPAH1, IPAH2, IPAH3), normal EPCs (Con1, Con2, Con3) and PSCs-derived EPCs (H7EC, H9EC, 202EC). PROM1, SPN and PTPRC were not expressed, and EFNB2 had a higher expression level in HUVECs (A), but PROM1, SPN and PTPRC were highly expressed in PSCs-derived EPCs, normal EPCs, IPAH-EPCs and 2D-MGH1EC (B). Moreover, EFNB2 also had a higher expression level in PSCs-derived EPCs than in normal EPCs and IPAH-EPCs (B). (C, D) Heatmap of homing-related genes from the 2D_MG_H1EC and 2D_MG_HUVEC datasets from GSE93511 and our microarray data in IPAH-EPCs (IPAH1, IPAH2, IPAH3), normal EPCs (Con1, Con2, Con3) and PSCs-derived EPCs (H7EC, H9EC, 202EC). IGF2, CXCL12 and CD90 (THY1) were not expressed in HUVECs (C), but had higher expression levels in PSCs-derived EPCs, normal EPCs, IPAH-EPCs (D) and 2D-MG-H1EC (C). IGFBP3 had a lower expression level in IPAH-EPCs than in PSCs-derived EPCs and normal EPCs (D).

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  Fig. 7 PSCs-derived EPCs have special molecular characteristics compared with normal EPCs and IPAH-EPCs (IPAH1, IPAH2 and IPAH3) based on our microarray data. (A) Correlation analysis between normal EPCs (Con1, Con2, Con3) and PSCs-derived EPCs (H7EC, H9EC, 202EC). (B) MKi67 relative expression from microarray data. Data were represented as the mean±SD. n=3, Student’s t test was performed (*p<0.05). (C, D) GOBP analysis (TOP20) of PSCs-derived EPCs and IPAH-EPCs relative to normal EPCs. (E, F) GOBP analysis (TOP20) of PSCs-derived EPCs and normal EPCs relative to IPAH-EPCs.

Reference

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