Decreased secretion and profibrotic activity of tubular exosomes in diabetic kidney disease

Abstract

Tubular changes contribute to the development of renal pathologies in diabetic kidney disease (DKD), including interstitial fibrosis. It is unclear how tubular cells relay signals to interstitial fibroblasts. Recently, exosomes have been recognized as crucial mediators of intercellular communication. We hypothesized that exosomes secreted from tubular cells may stimulate fibroblasts for interstitial fibrosis in DKD. In this study, we isolated and purified exosomes from the renal cortex of DKD mice and high glucose-treated mouse proximal tubular cells. Compared with nondiabetic mice, exosome secretion in kidney tissues decreased in DKD mice. Likewise, high glucose incubation reduced exosome secretion in mouse kidney proximal tubular BUMPT cells. To study the effect of tubular cell exosomes on fibroblasts, exosomes from BUMPT cells were added to renal fibroblast NRK-49F cell cultures. Notably, exosomes from high glucose conditioned BUMPT cells induced higher proliferation, significant morphological change, and substantial production of fibronectin, α-smooth muscle actin, and collagen type Ι in NRK-49F fibroblasts. Proteomics analysis was further performed to profile the proteins within tubular cell exosomes. Interestingly, 22 proteins were found to be differentially expressed between tubular exosomes derived from high glucose conditioned cells and those from normal glucose conditioned cells. Cytoscape analysis suggested the existence of two protein-protein interaction networks in these exosomal differentially expressed proteins. While one of the protein-protein interaction networks comprised enolase 1 (Eno1), heat shock protein family A member 8 (Hspa8), thioredoxin 1 (Txn1), peptidylprolyl isomerase A (Ppia), phosphoglycerate kinase 1 (Pgk1), DNA topoisomerase II-β (Top2b), and β-actin (Actb), the other had the family proteins of human leucocyte antigen F (Ywhag), a component of the ND10 nuclear body (Ywhae), interferon regulatory factor-8 (Ywhaq), and human leucocyte antigen A (Ywhaz). Gene expression analysis via Nephroseq showed a correlation of Eno1 expression with DKD clinical manifestation. In conclusion, DKD is associated with a decrease in exosome secretion in renal tubular cells. Exosomes from high glucose conditioned tubular cells may regulate the proliferation and activation of fibroblasts, contributing to the paracrine signaling mechanism responsible for the pathological onset of renal interstitial fibrosis in DKD.

Keywords: diabetic kidney disease; exosome; renal fibrosis; tubular injury.

Fig. 1.

Characterization of exosomes derived from kidney cortex tissues of diabetic kidney disease (DKD) mice. Kidney cortical tissue of 11 wk (11W) or 20 wk (20W) Akita and wild-type (WT) mice were harvested and homogenized for exosome isolation and purification. The exosome pellets were collected for morphological and immunoblot analysis. A: representative morphological images of exosomes observed by transmission electron microscopy. Scale bars = 100 nm. B: size distribution of exosomes analyzed by nanoparticle tracking analysis. C: exosome quantification by nanoparticle tracking analysis after normalization with tissue weight. Values (in particle number/mg renal cortex tissue) are means ± SE of 4 animal groups (n = 4). **P < 0.01 vs. WT mice. D−F: induction of CD63 and CD9 expression in exosomes derived from 11W and 20W DKD mice. D: representative Western blot analysis demonstrating the decreased production of CD63 and CD9 expression in Akita mice. The loading volume of exosome protein lysis was normalized by tissue weight. E and F: semiquantitative analysis of the average optical density of CD63 (E) and CD9 (F). Values are presented as mean ± SD; n = 4. *P < 0.05, **P < 0.01, and *** P < 0.001 vs. the WT group.

Fig. 2.

Renal interstitial fibrosis increases in 20-wk diabetic kidney disease mice. Renal interstitial fibrosis was estimated by sirius red staining. A: representative images of sirius red staining under microscopy with both ×10 and ×20 lens. Scale bars = 0.1 and 0.05 mm. B: quantitative analysis of fibronectin, α-smooth muscle actin (α-SMA), collagen type I, and collagen type IV by quantitative RT-PCR (n = 4). **P < 0.01 vs. the wild-type (WT) group.

Fig. 3.

Characterization of exosomes derived from high glucose (HG)-treated renal tubular cells. A: representative images of exosomes observed by transmission electron microscopy. Scale bars = 100 nm. B: size distribution of exosomes analyzed by nanoparticle tracking analysis. C: exosome quantification by nanoparticle tracking analysis after normalization with cell numbers. n = 5. ***P < 0.001 vs. the normal glucose (NG)-treated group. D−F: comparison of CD63 and CD9 expression in exosomes derived from tubular cells in NG- or HG-treated groups. D: representative Western blot analysis demonstrating the decreased production of CD63 and CD9 expression in the HG-treated group. The loading volume of exosome protein lysis was normalized by cell numbers. E and F: semiquantitative analysis of the average optical density of CD63 (E) and CD9 (F). Values are presented as means ± SD; n = 5. *P < 0.05 vs. the NG-treated group.

Fig. 4.

Exosomes from high glucose-treated renal tubular cells activate fibroblasts. High glucose-treated tubular cell exosomes (HG-Exo) or normal glucose-treated tubular cell exosomes (NG-Exo) were added to NRK-49F cells. A: representative images of phase contrast showing the cellular morphology of fibroblasts (n = 4). Scale bars = 100 and 200 μm. B: total cell numbers of NRK-49F fibroblasts. Data are expressed as means ± SD. *P < 0.05, significantly different from the control (Ctrl) group. C: total protein levels of NRK-49F fibroblasts. Data are expressed as means ± SD; n = 4. *P < 0.05, significantly different from the Ctrl group; **P < 0.01 vs. the NG-Exo group. D: representative images of immunoblot analysis of fibronectin, collagen type I, and α-smooth muscle actin (α-SMA). Cyclophilin B was used as a loading control (n = 4). E: densitometric analysis of fibronectin, collagen type I, and α-SMA signals. After being normalized with cyclophilin B, the protein signal of control was arbitrarily set as 1, and the signals of other conditions were normalized with controls to calculate fold changes. Data are expressed as means ± SD; n = 4. *P < 0.05 vs. the Ctrl group; #P < 0.05 vs. the NG-Exo group.

Fig. 5.

Correlation network of the differentially expressed proteins displayed by Cytoscape. A: the protein-protein interaction (PPI) network of differentially expressed proteins was constructed using Cytoscape. The most significant modules were obtained from the PPI network. B: one of the PPI networks comprised enolase 1 (Eno1), heat shock protein family A member 8 (Hspa8), thioredoxin 1 (Txn1), peptidylprolyl isomerase A (Ppia), phosphoglycerate kinase 1 (Pgk1), DNA topoisomerase II-β (Top2b), and β-actin (Actb). C: the other network had the family proteins of human leucocyte antigen F (Ywhag), a component of the ND10 nuclear body (Ywhae), interferon regulatory factor-8 (Ywhaq), and human leucocyte antigen A (Ywhaz).

Fig. 6.

The association between the differentially expressed protein enolase 1 (Eno1) and diabetic kidney disease (DKD). The 22 differentially expressed proteins in the study of DKD were analyzed on the Nephroseq v5 online platform. Eno1 demonstrated a strong correlation in patients with DKD. A: the expression level of Eno1 increased in patients with DKD. ***P < 0.001 vs. the nondiabetic control (Ctrl). B: Eno1 increased in tubulointerstitium tissue. ***P < 0.001 vs. glomeruli. C: Eno1 was negatively correlated with glomerular filtration rate (GFR). P = 0.0106. D: Eno1 increased in male patients. ***P < 0.001 vs. female patients. E and F: Eno1 was positively correlated with the increase in body mass index (BMI) and weight. P = 0.0148 and 0.0199 respectively.