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. 2023 Sep 29;14(1):277.
doi: 10.1186/s13287-023-03505-2.

CD73 mediates the therapeutic effects of endometrial regenerative cells in concanavalin A-induced hepatitis by regulating CD4+ T cells

Affiliations

CD73 mediates the therapeutic effects of endometrial regenerative cells in concanavalin A-induced hepatitis by regulating CD4+ T cells

Hong Qin et al. Stem Cell Res Ther. .

Abstract

Background: As a kind of mesenchymal-like stromal cells, endometrial regenerative cells (ERCs) have been demonstrated effective in the treatment of Concanavalin A (Con A)-induced hepatitis. However, the therapeutic mechanism of ERCs is not fully understood. Ecto-5`-nucleotidase (CD73), an enzyme that could convert immune-stimulative adenosine monophosphate (AMP) to immune-suppressive adenosine (ADO), was identified highly expressed on ERCs. The present study was conducted to investigate whether the expression of CD73 on ERCs is critical for its therapeutic effects in Con A-induced hepatitis.

Methods: ERCs knocking out CD73 were generated with lentivirus-mediated CRISPR-Cas9 technology and identified by flow cytometry, western blot and AMPase activity assay. CD73-mediated immunomodulatory effects of ERCs were investigated by CD4+ T cell co-culture assay in vitro. Besides, Con A-induced hepatitis mice were randomly assigned to the phosphate-buffered saline treated (untreated), ERC-treated, negative lentiviral control ERC (NC-ERC)-treated, and CD73-knockout-ERC (CD73-KO-ERC)-treated groups, and used to assess the CD73-mediated therapeutic efficiency of ERCs. Hepatic histopathological analysis, serum transaminase concentrations, and the proportion of CD4+ T cell subsets in the liver and spleen were performed to assess the progression degree of hepatitis.

Results: Expression of CD73 on ERCs could effectively metabolize AMP to ADO, thereby inhibiting the activation and function of conventional CD4+ T cells was identified in vitro. In addition, ERCs could markedly reduce levels of serum and liver transaminase and attenuate liver damage, while the deletion of CD73 on ERCs dampens these effects. Furthermore, ERC-based treatment achieved less infiltration of CD4+ T and Th1 cells in the liver and reduced the population of systemic Th1 and Th17 cells and the levels of pro-inflammatory cytokines such as IFN-γ and TNF-α, while promoting the generation of Tregs in the liver and spleen, while deletion of CD73 on ERCs significantly impaired their immunomodulatory effects locally and systemically.

Conclusion: Taken together, it is concluded that CD73 is critical for the therapeutic efficiency of ERCs in the treatment of Con A-induced hepatitis.

Keywords: CD4+ T cell; CD73; Concanavalin A-induced hepatitis; Endometrial regenerative cells; Mice.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Characterization of ERCs and CD73-KO-ERCs. A Morphology of ERCs, and CD73-KO-ERCs at passage 3 (magnification 40 ×). B Flow cytometry analysis of stem cell surface markers. C Expression of CD73 in ERCs, NC-ERCs and CD73-KO-ERCs by western blot. Full-length blots/gels are presented in Additional file 2: Figure S2. D AMPase activity of ERCs, NC-ERCs, and CD73-KO-ERCs. Statistical analysis was done by one-way ANOVA, ***P < 0.001
Fig. 2
Fig. 2
CD73 as AMPase is essential for ERCs in the control of CD4+ T cell activation and function. Conventional CD4+ T cells were stimulated with αCD3/αCD28 and incubated with ERCs, NC-ERCs, CD73-KO-ERCs, and AMP (50 µM) as indicated. The CD4+ T cell activation and function were evaluated after 3 days by flow cytometry and ELISA. A, B The activation markers CD69 and CD154 were depicted and analyzed (gated on the CD4+ population). C, D The proliferation of CD4+ T cells was measured by the dilution of CFSE. E, F The representative pseudocolor plots and statistical graphs of the CD4+IFN-γ+ population. G IFN-γ production was detected by ELISA in the cell culture supernatant. n = 3 per group. Statistical analysis was performed using one-way ANOVA, *P < 0.05; **P < 0.01; ***P < 0.001. Data in bar graphs represent mean ± SD
Fig. 3
Fig. 3
CD73 mediated the therapeutic efficacy of ERCs against Con A-induced hepatitis. To assess the cell-homing ability between ERCs and CD73-KO-ERCs, these cells were labeled with CM-Dil and injected intravenously into the Con A-induced hepatitis mice. A 24 h later, the livers of these mice were isolated and observed under a live animal imaging system. To assess the influence of CD73 deletion on ERCs’ therapeutic efficiency in Con A-induced hepatitis, B macroscopic appearance and confluent liver necrosis (yellow lines) of representative livers after ERCs, NC-ERCs, and CD73-KO-ERCs treatment were identified on H&E staining. C Necrotic areas were quantified as [%] of liver section area. Concentrations of serum D alanine transaminase (ALT) and E aspartate aminotransferase (AST) in different groups are depicted. F Representative TUNEL staining of livers section from Con A-treated mice with the indicated treatments (green), nuclei were counterstained with DAPI (blue). G The statistical graphs of TUNEL staining. n = 6 per group. One-way ANOVA was used for statistical analysis, **P < 0.01; ***P < 0.001. Data in bar graphs represent mean ± SD
Fig. 4
Fig. 4
CD73 expressing ERCs modulated the hepatic local immune microenvironment. 24 h after model induction, liver tissue single-cell suspensions were made and mononuclear cells were isolated and stained with fluorochrome-conjugated antibodies, and then detected the CD4+ T cell subsets by flow cytometry (n =6 per group). The representative pseudocolor plots of A CD3+CD4+ cells, B CD4+IFN-γ+ cells, and C CD4+Foxp3+ cells were depicted. We also detected the CD4+ cells by immunohistochemistry (n = 6 per group), and D the representative images were exhibited. The positive staining area was shown by an arrow. E–H The percentage of CD3+CD4+, CD4+IFN-γ+ Th1 and CD4+Foxp3+ Tregs detected by flow cytometry or immunohistochemistry from liver tissues of different groups were analyzed. Data were dealt with one-way ANOVA. *P < 0.05; **P < 0.01; ***P < 0.001. Data in bar graphs represent mean ± SD
Fig. 5
Fig. 5
CD73 expression on ERCs reduced the splenic CD4+ T cell populations in the treatment of Con A-induced hepatitis. To evaluate the systemic T cell subsets population in different groups, we made the single-cell suspension of splenocytes and detected them by flow cytometry (n = 6 per group). A Representative pseudocolor plots depict the percentage of CD3+CD4+ T cells. B Representative pseudocolor plots depict the percentage of CD3+CD8+ T cells. C and D show the statistical graph. One-way ANOVA was used for statistical analysis, *P < 0.05; ***P < 0.001. Data in bar graphs represent mean ± SD
Fig. 6
Fig. 6
CD73 expression on ERCs reduced splenic Th1 and Th17 populations while increasing the generation of Tregs in the treatment of Con A-induced hepatitis. Splenocytes obtained from the model mice of each group were stained with anti-mouse CD4+IFN-γ, CD4+IL-17A, and CD4+CD25+Foxp3 antibodies, respectively (n = 6 per group). The representative pseudocolor plots of A Th1 cells (CD4+IFN-γ+), B Th17 cells (CD4+IL-17A+), and C Tregs (CD4+CD25+Foxp3+) were exhibited. The percentage of D Th1 cells, E Th17 cells, and F Tregs were analyzed by one-way ANOVA.*P < 0.05; **P < 0.01; ***P < 0.001. Data in bar graphs represent mean ± SD
Fig. 7
Fig. 7
CD73 expression on ERCs reduced the serum levels of pro-inflammatory cytokines in the treatment of Con A-induced hepatitis. To evaluate the CD73 expression of ERCs on the overall function of the model mice’s immune system, the production of pro-inflammatory cytokines (IFN-γ and TNF-α) in the liver tissues and sera was detected via ELISA assay. The liver tissue and serum samples were collected from mice of each group after 24 h of Con A injection (n = 6 per group). Here, the levels of IFN-γ in the liver tissue (A) and serum (B), as well as the levels of TNF-α in the liver tissue (C) and serum (D), are shown, respectively. Data were analyzed using one-way ANOVA, *P < 0.05; **P < 0.01; ***P < 0.001. Data in bar graphs represent mean ± SD

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