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. 2021 Dec 11:13:100188.
doi: 10.1016/j.mtbio.2021.100188. eCollection 2022 Jan.

3D-bioprinted peptide coupling patches for wound healing

Gaopeng Guan  1 , Qizhuang Lv  2 , Shengyuan Liu  3 , Zhenzhen Jiang  1 , Chunxia Zhou  1 , Weifang Liao  1
Affiliations

3D-bioprinted peptide coupling patches for wound healing

Gaopeng Guan et al. Mater Today Bio. .

Abstract

Chronic wounds caused by severe trauma remain a serious challenge for clinical treatment. In this study, we developed a novel angiogenic 3D-bioprinted peptide patch to improve skin wound healing. The 3D-bioprinted technology can fabricate individual patches according to the shape characteristics of the damaged tissue. Gelatin methacryloyl (GelMA) and hyaluronic acid methacryloyl (HAMA) have excellent biocompatibility and biodegradability, and were used as a biomaterial to produce bioprinted patches. The pro-angiogenic QHREDGS peptide was covalently conjugated to the 3D-bioprinted GelMA/HAMA patches, extending the release of QHREDGS and improving the angiogenic properties of the patch. Our results demonstrated that these 3D-bioprinted peptide patches showed excellent biocompatibility, angiogenesis, and tissue repair both in vivo and in vitro. These findings indicated that 3D-bioprinted peptide patches improved skin wound healing and could be used in other tissue engineering applications.

Keywords: 3D-printing; Angiogenesis; Gelatin methacryloyl (GelMA); Hyaluronic acid methacryloyl (HAMA); Peptide; Wound healing.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image 1
Graphical abstract
Fig. 1
Fig. 1
Schematic diagram of 3D-printed peptide patches fabrication for skin wound therapy.
Fig. 2
Fig. 2
Characterization of the 3D-printed GelMA/HAMA patches. (A) digital photograph of the 3D-printed GelMA/HAMA patches; (B) micrograph of the 3D-printed GelMA/HAMA patches; (C) SEM image of the 3D-printed GelMA/HAMA patches; (D) magnified SEM image of the surface of 3D-printed GelMA/HAMA patches. The scale bars are 2 ​mm in (A), 400 ​μm in (B), 100 ​μm in (C), and 10 ​μm in (D).
Fig. 3
Fig. 3
Peptide release assays. Fluorescent intensity of 3D-printed loading FITC-peptide patches in different filament thickness and different methods of peptide loading. Statistical analysis is shown on the bar graphs. Data are presented as the mean ​± ​SD of the three independent experiments. ∗P ​< ​0.05 versus Physical Absorption (thick) group; #P ​< ​0.05 versus Chemical Coupling (thin) group; & P ​< ​0.05 versus Chemical Coupling (thick) group.
Fig. 4
Fig. 4
Biocompatibility assays of the 3D-printed patches. (A) Live (green)/dead (red) staining of HDF cells on the different treatments; (B) the percentage of live cells; (C) Proliferation of HDF cells cultured directly on the different treatments detected by using the CCK-8 kit. The scale bars are 50 ​μm. Statistical analysis is shown on the bar graphs. Data are presented as the mean ​± ​SD of the three independent experiments. There are not statistical differences between groups.
Fig. 5
Fig. 5
Wound healing assays and tubule formation assays of the 3D-printed patches. (A) The cell migrations after HDF cells were scratched with different treatments. (B) The tube formation of HUVEC cells with different treatment; (C) quantitative analysis of cell migration with measurements of the gap size; (D) quantitative analysis of tubule formation assay results with measurements of the tube length. The scale bars are 100 ​μm. Statistical analysis is shown on the bar graphs. Data are presented as the mean ​± ​SD of the three independent experiments. ∗P ​< ​0.05 versus Control group; #P ​< ​0.05 versus Patch group; & P ​< ​0.05 versus Peptide group.
Fig. 6
Fig. 6
(A) Representative images of the wounds from day 0 to day 9 with different treatment. (B) HE staining of wounds with different treatment at day 9; (C) wound repair rate characterized by wound area from day 0 to day 9; (D) quantitative analysis of granulation tissue thickness at day 9. The scale bars are 5 ​mm in (A) and 400 ​μm in (B). Statistical analysis is shown on the bar graphs. Data are presented as the mean ​± ​SD of the five independent experiments. ∗P ​< ​0.05 versus Control group; #P ​< ​0.05 versus Patch group; & P ​< ​0.05 versus Peptide group.
Fig. 7
Fig. 7
Characterization of proinflammatory factors, collagen deposition. (A) Masson's trichrome staining, immunostaining of IL-6 and TNFα at granulation tissues in different groups; (B–D) Representative (B) IL-6, (C) TNFα, and (D) collagen deposition analysis in different groups after treatment. The scale bars are 200 ​μm. Statistical analysis is shown on the bar graphs. Data are presented as the mean ​± ​SD of the five independent experiments. ∗P ​< ​0.05 versus Control group; #P ​< ​0.05 versus Patch group; & P ​< ​0.05 versus Peptide group.
Fig. 8
Fig. 8
Characterization of neovascularization. (A) The fluorescent images of the immunostaining of αSMA (green) and CD31 (red); (B) the analysis of vessel density. The scale bars are 200 ​μm. Statistical analysis is shown on the bar graphs. Data are presented as the mean ​± ​SD of the five independent experiments. ∗P ​< ​0.05 versus Control group; #P ​< ​0.05 versus Patch group; & P ​< ​0.05 versus Peptide group.
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