Research ArticleFibrosis

Inhibition of hyperglycolysis in mesothelial cells prevents peritoneal fibrosis

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Science Translational Medicine  05 Jun 2019:
Vol. 11, Issue 495, eaav5341
DOI: 10.1126/scitranslmed.aav5341
  • Fig. 1 Identification of cell populations in normal human peritoneum and effluent of patients undergoing PD.

    (A) Unsupervised scRNA-seq analysis distinguishing seven different cell clusters in normal human peritoneum tissue presented by t-distributed stochastic neighbor embedding (t-SNE) plot (n = 3). (B) Violin plots demonstrating the expression of representative marker genes across the seven cell clusters. The y axis shows the log2 scale–normalized read count. (C) Unsupervised scRNA-seq analysis distinguishing nine different cell clusters in effluent-derived peritoneal cells from patients undergoing PD (t-SNE) (n = 10). Clusters and corresponding cell counts are listed in the table below the map. (D) Heat map showing expression of canonical marker genes in the cell clusters. Color indicates the gene expression value scaled by Z score. (E) t-SNE maps demonstrating the expression of extracellular matrix proteins. The color gradient is based on the log2-transformed read count. (F) t-SNE maps demonstrating expression of mesenchymal marker genes and epithelial marker genes in mesothelial cells from the long-term PD and the short-term PD groups. The color gradient is based on the log2-transformed read count. Jitter plots on the bottom panel of each t-SNE plot show the quantification results based on normalized read counts. *P < 0.05 and ***P < 0.001 by Kruskal-Wallis test.

  • Fig. 2 scRNA-seq reveals enhanced glycolytic enzyme expression associated with the development of MMT.

    (A and B) GSEA plots demonstrating enrichment score (ES) of gene sets in the scRNA-seq data of mesothelial cells. Genes in each gene set are ranked by signal-to-noise ratio according to their differential expression between normal mesothelial cells and the long-term PD group. FDR, false discovery rate. (C) Heat map showing the expression of key glycolytic enzymes in mesothelial cells of normal peritoneum, short-term PD, and long-term PD groups. (D) Scatter plots of the correlation between expression of glycolytic enzymes and mesenchymal marker genes. Spearman’s correlation analysis was performed, with ρ (Spearman’s correlation coefficient) and P values labeled in the plots. (E) Ordering of scRNA-seq expression data of peritoneal mesothelial cells according to the pseudotime produced by Monocle analysis. (F) Expression of mesenchymal marker genes, epithelial marker genes, and glycolytic enzyme–encoding genes demonstrated along the trajectory that depicts MMT. (G and H) Immunoblots and quantification of the expression of glycolytic enzymes (G) and fibrotic proteins (H) in mesothelial cells sorted by fluorescence-activated cell sorting using UPK3B antibody. Data are presented as means ± SEM; *P < 0.05, **P < 0.01, or ***P < 0.001 versus normal cells and #P < 0.05, ##P < 0.01, or ###P < 0.001 versus short-term PD by one-way analysis of variance (ANOVA) with Bonferroni’s multiple comparison test or Kruskal-Wallis test, n = 6 in each group.

  • Fig. 3 PD fluid induces fibrosis and metabolic reprogramming of the peritoneum in mice.

    (A) Masson’s trichrome staining of peritoneal tissue from mice treated with saline or PD fluid. Representative images derived from six animals per group. Scale bar, 100 μm. (B) Heat map of PCR-based mRNA array showing the significantly differentially expressed genes involved in glucose metabolism (P < 0.05 by t test; fold change, >2). (C) KEGG pathway enrichment analysis of the genes significantly differentially expressed due to PD fluid in mouse peritoneum. (D) Real-time PCR analysis of glycolytic enzymes in the peritoneum of mice treated with PD fluid or saline. Data are presented as means ± SEM; *P < 0.05 and **P < 0.01 by t test, n = 6). (E) Immunoblots and quantification of glycolytic enzymes in peritoneum of mice treated with PD fluid or saline. Data are presented as means ± SEM; **P < 0.01 and ***P < 0.001 by t test, n = 6). (F) Volcano plot of metabolomics analysis (PD fluid versus saline, n = 6 in each group). (G) Statistical analysis of metabolites in the peritoneum from PD fluid–treated mice compared to the control group. Data are presented as means ± SEM; *P < 0.05, **P < 0.01, and ***P < 0.001 by t test, n = 6. Right: Pathway map showing up-regulated enzymes and metabolites in red color. G6P, glucose 6-phosphate; F1,6BP, fructose 1,6-bisphosphate; DHAP, dihydroxyacetone phosphate; G3P, glyceraldehyde 3-phosphate; R5P, ribose 5-phosphate; IMP, inosine monophosphate; AMP, adenosine monophosphate; UMP, uridine monophosphate; CMP, cytidine monophosphate; GMP, guanosine monophosphate; Leu, leucine; Phe, phenylalanine; Tyr, tyrosine; GPI, glucose-6-phosphate isomerase; ALDO, fructose-bisphosphate aldolase; TPI, triosephosphate isomerase. (H) Representative micrographs showing mitochondrial morphologic changes in response to PD fluid. Scale bars, 10 μm. Blue, nuclei. Red, cytokeratin 5. Green, mitochondria. Boxed regions areas are presented at higher magnification on the right. Scale bars, 5 μm.

  • Fig. 4 TGF-β1 stimulates hyperglycolytic metabolism in human mesothelial cells.

    (A) Volcano plots showing the results of PCR-based mRNA array from MeT-5A cells treated with TGF-β1 (5 ng/ml; left panel) or medium containing PD fluid (right panel), n = 3 in each group. (B) Heat map showing the significant gene expression changes for genes involved in energy metabolism (P < 0.05 by t test; fold change, >2) in MeT-5A cells treated with or without TGF-β1. The right panel shows the KEGG pathway enrichment analysis of these significantly changed genes. CTL, control group. AA, amino acids. (C) RT-PCR analysis of the expressions of glycolytic enzymes in MeT-5A cells treated with or without TGF-β1 (means ± SEM; *P < 0.05 and ***P < 0.001 by t test, n = 6). (D) Assessment of cellular respiration with Mito Stress assay in MeT-5A cells treated with or without TGF-β1. Results are normalized to protein expression; data are presented as means ± SEM. (E and F) Quantification of measurements in (D). **P < 0.01 and ***P < 0.001 by t test, n = 6 in each group. (G) Glycolysis stress test in MeT-5A cells treated with or without TGF-β1. Results are normalized to protein expression; data are presented as means ± SEM. (H and I) Quantification of measurement in (G). ***P < 0.001 by t test, n = 6. (J) Immunoblots and quantification of the expression of fibrotic proteins and E-cadherin in MeT-5A cells treated with or without TGF-β1 (means ± SEM; *P < 0.05 and **P < 0.01 by t test). (K) Cellular respiration of human primary mesothelial cells assessed by Mito Stress test. Results are normalized to protein expression and are presented as means ± SEM, n = 7. (L) Quantification analysis of measurement in (K), ***P < 0.001 by t test, n = 7. (M) Immunoblots and quantification of the expression of FN1, COL1A1, α-SMA, and E-cadherin in human primary mesothelial cells treated with or without TGF-β1 (means ± SEM; *P < 0.05 and **P < 0.01 by t test, n = 6).

  • Fig. 5 Inhibition of glycolysis attenuates the profibrotic phenotype of MeT-5A cells and peritoneal fibrosis in mice.

    (A) ECAR measurements of glycolysis stress test in MeT-5A cells treated with TGF-β1 and 2-DG (0.2 mM) or TGF-β1 (5 ng/ml) alone. Data are presented as means ± SEM. Right: Quantification analysis of basal ECAR, glycolysis, and glycolytic capacity. (B and C) RT-qPCR analysis and immunoblots of FN1, COL1A1, and α-SMA in MeT-5A cells with or without 2-DG treatment followed by TGF-β1 treatment. Quantitative analysis results are demonstrated as bar graphs. (D) ECAR measurements of glycolytic stress test in human primary mesothelial cells. Right: Quantification analysis of basal ECAR, glycolysis, and glycolytic capacity. (E) Representative immunoblots of human primary mesothelial cells. Quantitative analysis results are presented as a bar graph. Data (A to E) are presented as means ± SEM (*P < 0.05, **P < 0.01, or ***P < 0.001 for TGF-β1 versus CTL and #P < 0.05, ##P < 0.01, or ###P < 0.001 for TGF-β1 plus 2-DG versus TGF-β1, one-way ANOVA with Bonferroni’s multiple comparison test, n = 6 to 8). (F) Masson’s trichrome staining of peritoneal tissue from mice treated with or without 2-DG and PD fluid. Representative images derived from five animals per group. Scale bar, 100 μm. (G) Quantitative analysis of the thickness of the peritoneal submesothelial compact zone. (H) Immunoblots and quantification of protein expression of FN1, COL1A1, and α-SMA in peritoneal tissue from mice treated with PD fluid and 2-DG. Data (G and H) are presented as means ± SEM (**P < 0.01 or ***P < 0.001 versus saline; #P < 0.05 or ###P < 0.001 versus PD fluid, one-way ANOVA with Bonferroni’s multiple comparison test, n = 5).

  • Fig. 6 Identification of miRNAs involved in glycolysis during peritoneal fibrogenesis.

    (A) Volcano plot of miRNA microarray data of peritoneum from mice treated with PD fluid or saline. The red or blue dots represent miRNAs in peritoneum that are significantly (P < 0.05) up-regulated or down-regulated, respectively (n = 3 in each group). (B) Heat map showing relative expressions of the 41 miRNAs, which significantly changed (P < 0.05 by t test; fold change, >2) in peritoneum from PD fluid–treated mice compared to control group. Color gradient indicates expression value scaled by Z score. One-way hierarchical clustering of the 41 miRNAs performed (n = 3 in each group). (C) miRNA targets analysis for miRNAs involved in glycolysis and fibrogenesis. The up-regulated miRNAs are indicated by a red arrow, and down-regulated miRNAs are indicated with a blue arrow. (D) Table listing the eight miRNAs and their predicted target genes involved in glucose metabolism. (E) KEGG analysis of target genes of eight miRNAs, which are predicted to target both glycolysis pathways and fibrogenesis pathways. (F) The expression of miR-21a, miR-26a, and miR-200a in peritoneum from mice treated with PD fluid or saline. (G) The expressions of miR-21a, miR-26a, and miR-200a in PD fluid effluent-derived mesothelial cells from short-term and long-term patients undergoing PD. Results (F and G) are normalized to U6 small nuclear RNA (snRNA) and are presented as means ± SEM (**P < 0.01 or ***P < 0.001 by t test, n = 6). (H) Representative immunoblots and quantification of the expressions of PDP2, PFKFB3, and phosphofructokinase, muscle (PFKM) in MeT-5A cells after transfection of mimics of miR-21a, miR-26a, and miR-200a, respectively (data are presented as means ± SEM; *P < 0.05 by t test, n = 6).

  • Fig. 7 miRNA triad suppresses glycolysis and profibrotic phenotype induced by TGF-β1 in MeT-5A cells.

    (A) ECAR measurements of glycolysis stress test performed in MeT-5A cells treated with TGF-β1 plus miRNA triad or scrambled, control miRNA (miRNA CTL; data are represented as means ± SEM, n = 6). Because the glycolysis stress test for miR-21a inhibitor, miR-26a mimic, or miR-200a mimic and the triad of these microRNAs were performed in the same experiment, the data of miRNA CTL and TGF-β1 plus miRNA CTL group shown in (A) were the same as shown in fig. S7, A to C. (B and C) Quantitative analysis of glycolytic stress test data reported in (A) (***P < 0.001 TGF-β1 + miRNA CTL versus miRNA CTL and ##P < 0.01 TGF-β1 + miRNA triad versus TGF-β1 + miRNA CTL, one-way ANOVA with Bonferroni’s multiple comparison test, n = 6). (D) Representative immunoblots and quantification of the expressions of PFKM, PFKFB3, and PDP2 in mesothelial cells treated with miRNA triad plus TGF-β1 or scrambled control. (E) Representative immunoblot and quantification of FN1, COL1A1, and α-SMA stimulated by TGF-β1 with or without miRNA triad treatment. Data (D and E) are presented as means ± SEM (*P < 0.05, **P < 0.01, or ***P < 0.001 for TGF-β1 + miRNA CTL versus miRNA CTL and #P < 0.05 or ##P < 0.01 for TGF-β1 + miRNA triad versus TGF-β1 + miRNA CTL, one-way ANOVA with Bonferroni’s multiple comparison test, n = 6 in each group).

  • Fig. 8 miRNA triad treatment alleviates hyperglycolysis and fibrogenesis in the peritoneum of a mouse model of peritoneal fibrosis.

    (A) Representative microscopic image of mouse peritoneum transfected with AAV1-GFP. Green, GFP. Red, nuclei of peritoneal cells. Scale bar, 100 μm. (B) Schematic graph of experimental design. Arrows denote the time point of PD fluid injection, AAV1-miRNA triad treatment, and peritoneum sample collection. (C) RT-qPCR showing the expression of miR-21a, miR-26a, and miR-200a in mouse peritoneum after the infection of AAV1-miRNA triad (means ± SEM; **P < 0.01 or ***P < 0.001 versus saline + AAV1 CTL and ###P < 0.001 for PD fluid + AAV1-miRNA triad versus PD fluid +AAV1 CTL; one-way ANOVA with Bonferroni’s multiple comparison test, n = 6). (D) Masson’s trichrome staining and collagen 1 staining of peritoneal tissue from mice treated with PD fluid plus miRNA CTL or miRNA triad. Representative images derived from six mice of each group. Scale bars, 100 μm. (E) Quantitative analysis of the thickness in mesentery and parietal peritoneal submesothelial compact zone of mice treated with PD fluid plus miRNA CTL or miRNA triad. (F) Peritoneal permeability of mice treated with PD fluid plus miRNA CTL or miRNA triad examined by modified peritoneal equilibration test. (G) Active TGF-β1 in effluent of peritoneal dialysate measured by enzyme-linked immunosorbent assay. (H) Immunoblots of phosphorylated and total SMAD2/3, ZEB1, and SNAI1 in peritoneum from mice treated with PD fluid plus AAV1-miRNA triad. (I) Immunoblots of PFKM, PFKFB3, and PDP2 in peritoneum from mice treated with PD fluid plus AAV1-miRNA triad. (J) Immunoblots of FN1, COL1A1, and α-SMA in peritoneal tissue from mice treated with PD fluid plus AAV1-miRNA triad. Data (E to J) were presented as means ± SEM (*P < 0.05, **P < 0.01, or ***P < 0.001 for PD fluid + AAV1 CTL versus saline + AAV1 CTL and #P < 0.05, ##P < 0.01, or ###P < 0.001 for PD fluid + AAV1-miRNA triad versus PD fluid + AAV1 CTL; one-way ANOVA with Bonferroni’s multiple comparison test, n = 6).

Supplementary Materials

  • stm.sciencemag.org/cgi/content/full/11/495/eaav5341/DC1

    Materials and Methods

    Fig. S1. Quality control and clustering of single cells.

    Fig. S2. Mesothelial cell marker gene expression in the single-cell maps.

    Fig. S3. Subclustering of peritoneal cells derived from PD effluent.

    Fig. S4. GSEA of cell clusters and immunohistochemical staining of human peritoneum.

    Fig. S5. PD fluid induces fibrosis in mouse peritoneum.

    Fig. S6. PD fluid activates TGF-β1 in mouse peritoneum.

    Fig. S7. miR-21a inhibitor, miR-26a mimic, and miR-200a mimic suppress hyperglycolysis and fibrogenesis in human mesothelial cells.

    Table S1. RT-qPCR primer sequences.

    Data file S1. Primary data.

  • The PDF file includes:

    • Materials and Methods
    • Fig. S1. Quality control and clustering of single cells.
    • Fig. S2. Mesothelial cell marker gene expression in the single-cell maps.
    • Fig. S3. Subclustering of peritoneal cells derived from PD effluent.
    • Fig. S4. GSEA of cell clusters and immunohistochemical staining of human peritoneum.
    • Fig. S5. PD fluid induces fibrosis in mouse peritoneum.
    • Fig. S6. PD fluid activates TGF-β1 in mouse peritoneum.
    • Fig. S7. miR-21a inhibitor, miR-26a mimic, and miR-200a mimic suppress hyperglycolysis and fibrogenesis in human mesothelial cells.
    • Table S1. RT-qPCR primer sequences.

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    Other Supplementary Material for this manuscript includes the following:

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