A sprayable exosome-loaded hydrogel with controlled release and multifunctional synergistic effects for diabetic wound healing

Abstract

Diabetic wound healing is hindered by bacterial infections, oxidative stress, impaired vascularization, and chronic inflammation. Conventional dressings, limited by static drug release and single-functionality, fail to dynamically match the varying demands of different healing stages and dressing replacement frequencies. This study developed a multifunctional sprayable hydrogel dressing (Exo@AMCN) by photocrosslinking methacrylated decellularized dermal matrix co-loaded with human umbilical cord mesenchymal stem cell-derived exosomes (hUCMSC-Exo) and β-cyclodextrin-borneol inclusion complexes (CN). The hydrogel can be sprayed onto irregularly shaped wounds, with its crosslinking density and degradation kinetics precisely modulated by adjusting the photocuring duration. This tunability enables controlled release of exosomes and borneol over 2-7 days. Experimental findings demonstrate that Exo@AMCN displays excellent biocompatibility, broad-spectrum antibacterial activity (>85 % efficacy), and robust reactive oxygen species scavenging capacity. The dressing significantly boosts cell migration, fosters angiogenesis, and prompts macrophage polarization toward anti-inflammatory phenotypes. In a diabetic wound model, Exo@AMCN reduced residual wound area to 1.07 ± 1.27 % within 14 days by modulating tissue inflammation, enhancing collagen deposition, and stimulating neovascularization. This innovative approach, combining controlled drug release with multifunctional synergy, offers a promising individualized solution for managing diabetic wounds.

Keywords: Acellular dermal matrix; Borneol; Diabetic wound healing; Exosomes; Hydrogel.

Graphical abstract

Scheme 1

Illustrate the synthesis and utilization of Exo@AMCN for diabetic wound healing. (A)Preparation process of Exo@AMCN. (B)Application of Exo@AMCN in diabetic wound healing. (C)Mechanism of promoting wound healing by Exo@AMCN.

Fig. 1

Illustrates the preparation and characterization of hydrogels. (A) FT-IR spectra of ADM, AM₆₀, and AMCN₆₀. (B) XRD patterns of ADM and AM. (C) G′ and G″ of hydrogels under frequency sweeps. (D) G′ and G″ of hydrogels during amplitude sweeps. (E) SEM images of AM₆₀ and Exo@AMCN₆₀. (F) Quantitative analysis of the pore size of hydrogels. (G) TEM image of hUCMSC-Exo. (H) The size distribution of Exo determined by NTA. (I) Western blot analysis of exosomal surface markers. (J) Confocal microscopy image of PKH27-labeled Exo loaded into Exo@AMCN.

Fig. 2

Application and drug release of hydrogels. (A) Hydrogel formed under UV irradiation. (B) Spray application of Exo@AMCN hydrogel dressing. (C) Hydrogel adapting to mechanical deformation. (D) Optical images of hydrogels with varying photocrosslinking times. (E) SEM images of hydrogels with different photocrosslinking times. (F) Quantitative analysis of hydrogels pore size. (G) Residual mass of hydrogels over time. (H) Cumulative release ratio of borneol from hydrogels. (I) Cumulative release ratio of Exo from hydrogels.

Fig. 3

Biocompatibility, antibacterial activity, and antioxidant function of hydrogels. (A) Representative photographs of hemolysis assays for different hydrogels. (B) Hemolysis ratios of hydrogels. (C) OD values from CCK-8 assays for PBS, AMCN, Exo and Exo@AMCN. (D) Live/dead staining of HaCaT cells treated with PBS, AMCN, Exo and Exo@AMCN for 24 h. (E) Viability of HaCaTs after 24 h of treatment with PBS, AMCN, Exo and Exo@AMCN. (F) Representative images of E. coli and S. aureus colonies co-cultured with hydrogels on agar plates. (G) Antibacterial rates of AMCN and Exo@AMCN after 36 h of co-culture. (H) SEM images of S. aureus and E. coli after co-culture with Exo@AMCN. (I) DCFH-DA fluorescence in L929 cells treated with PBS, Rosup, AMCN, Exo and Exo@AMCN. (J) Relative fluorescence intensity of DCFH-DA. (∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001).

Fig. 4

Hydrogel enhanced cell migration, angiogenesis, and inflammatory modulation. (A) Representative scratch assay images of HaCaT cells treated with hydrogel extracts for 24 h. (B) Quantification of migration rates across groups after 24 h. (C) Representative tube formation images of HUVECs cultured with hydrogel extracts. (D) Quantitative analysis of vascular network formation. (E) Immunofluorescence images of VEGF expression in HUVECs. (F) Quantitative analysis of VEGF fluorescence intensity. (G) Immunofluorescence images of TNF-α and IL-10 expression in RAW264.7 cells. (H) Quantitative analysis of TNF-α fluorescence intensity. (I) Quantitative analysis of IL-10 fluorescence intensity. (J) Relative mRNA level of VEGF. (K) Relative mRNA level of TNF-α. (L) Relative mRNA level of IL-10. (∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001).

Fig. 5

Hydrogel accelerates diabetic wound healing in vivo. (A) Schematic diagram and timeline of diabetic wound healing model establishment. (B) Representative optical images of wounds after implantation with different hydrogels. (C) Schematic illustration of wound closure and quantitative analysis. (D) Quantitative analysis of wound closure. (E) Representative H&E staining and Masson's trichrome staining images of wounds on day 14. (F) Analysis of epidermal thickness at wound sites. (G) Analysis of granulation tissue thickness at wound sites. (H) Quantitative analysis of collagen deposition percentages at wound sites. (∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001).

Fig. 6

Immunohistological analysis of hydrogel-accelerated diabetic wound healing in vivo. (A) Representative images of CK14 and CD31 immunohistochemical staining. (B) Representative immunofluorescence images of VEGF, iNOS and CD206. (C) Quantitative analysis of CK14 expression area. (D) Quantitative analysis of CD31 expression area. (E) Quantitative analysis of VEGF fluorescence intensity. (F) Quantitative analysis of iNOS fluorescence intensity. (G) Quantitative analysis of CD206 fluorescence intensity. (∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001).

Fig. 7

Transcriptomic analysis of potential mechanisms. (A) Heatmap of differentially expressed gene clustering. (B) Volcano plot of differentially expressed genes between groups. (C) GO enrichment analysis. (D) KEGG pathway enrichment analysis. (E) GSEA of angiogenesis pathway. (F) GSEA of extracellular matrix organization pathway. (G) GSEA of inflammatory response pathway.