J. Mater. Sci. Technol. ›› 2021, Vol. 63: 216-227.DOI: 10.1016/j.jmst.2020.03.014
• Research Article • Previous Articles Next Articles
Yongjin Suna, Juntao Zhanga, Bi Chena, Yunlong Yanga, Haiyan Lib, Xin Niua, Qing Lia, Weidong Wuc, Zongping Xiea, Yunfeng Chena, Fuyue Wuc,*(
), Yang Wanga,*(
)
Received:2019-11-25
Revised:2020-01-06
Accepted:2020-01-17
Published:2021-02-10
Online:2021-02-15
Contact:
Fuyue Wu,Yang Wang
About author:wangy63cn@126.com (Y. Wang).1The two authors equally contributed to the work.
Yongjin Sun, Juntao Zhang, Bi Chen, Yunlong Yang, Haiyan Li, Xin Niu, Qing Li, Weidong Wu, Zongping Xie, Yunfeng Chen, Fuyue Wu, Yang Wang. Small extracellular vesicles secreted by urine-derived stem cells enhanced wound healing in aged mice by ameliorating cellular senescence[J]. J. Mater. Sci. Technol., 2021, 63: 216-227.
Fig. 1. Characterization of USCs, USC-derived sEVs and HAAM. (a) Flow cytometric analyses of phenotypic markers of USCs. USCs were negative for CD34, CD45, and HLA-DR and were positive for CD29, CD44, and CD73. (b) Western blot analysis showed the presence of sEVs characteristic CD9, CD63, and TSG101 proteins, but the absence of GM130 protein. (c) Morphology of sEVs under TEM. Scale bar, 100 nm. (d) Particle size distribution of UCS-sEVs measured by qNano analysis.
Fig. 2. Characterization of HAAM. (a) H&E staining of HAAM section. Scale bar, 25 μm. (b) SEM images of the surface of HAAM. Scale bar, 1 μm. (c) SEM images of the cross section of HAAM. Scale bar, 1 μm. (d) Pore size distribution of HAAM. (e) Controlled-release of particles of HAAM loaded with USC-sEVs. Note significant difference of 180 min group and 240 min group from 120 min group (from 12 h until day 6; P < 0.05). No difference between 180 min and 240 min group. (f) The fluorescent images of live and dead cells after HDFs cultured on HAAM with or without USC-sEVs. Scale bar, 50 μm. Statistical significance was determined by one-way ANOVA (Tukey’s multiple-comparisons test).
Fig. 3. Wound healing was significantly promoted by HAAM loaded with USC-sEVs in aged mice. (a) Representative images of wounds treated with PBS in young mice (Control), and wounds treated with PBS (Aged), HAAM (Aged-HAAM), USC-sEVs (Aged-sEVs), HAAM loaded with USC-sEVs (Aged-HAAM-sEVs) in aged mice, at 0, 3, 7, 14 and 21days after initial treatment. (b) Percent wound closure. n = 6 per group. (c) H&E staining of wound sections obtaining from control, Aged, Aged-HAAM, Aged-sEVs, Aged-HAAM-sEVs groups at 21 days after initial treatment. The black arrows indicate the edges of the scar. Scale bar, 200 μm. (d) Quantification of scar width. n = 3 per group. (e) Masson’s trichrome staining of wound sections obtaining from control, Aged, Aged-HAAM, Aged-sEVs, Aged-HAAM-sEVs groups at 21 days after initial treatment. Scale bar, 100 μm (100×) or 25 μm (400×). (*, P < 0.05, compared with control; #, P < 0.05, compared with Aged; %, P < 0.05, compared with Aged-HAAM; &, P < 0.05, compared with Aged-sEVs). Statistical significance was determined by one-way ANOVA (Tukey’s multiple-comparisons test).
Fig. 4. IHC analysis of P16 protein and SASP expression in wound sites of control, Aged, Aged-HAAM, Aged-sEVs, Aged-HAAM-sEVs groups at 7 days after initial treatment. (a) IHC staining for P16. Scale bar, 25 μm. (b) IHC staining for SASP (IL-1β, IL-6, MMP-13). Scale bar, 25 μm. (c) Quantification of IHC staining of P16. (d) Quantification of IHC staining of SASP (IL-1β, IL-6, MMP-13). (*, P < 0.05, compared with control; #, P < 0.05, compared with Aged; %, P < 0.05, compared with Aged-HAAM; &, P < 0.05, compared with Aged-sEVs). Statistical significance was determined by one-way ANOVA (Tukey’s multiple-comparisons test).
Fig. 5. USC-sEVs protected HDFs from senescence induced by d-gal in vitro experiments. HDFs were treated with 10 g/L d-gal to induce senescence, then the senescent HDFs were treated with 1 × 1010 particles/mL USC-sEVs (Agd-sEVs) or PBS (Aged), while HDFs treated without d-gal (Young) were used as control. (a) Representative micrographs of HDFs stained with SA-β-gal. SA-β-gal-positive cells are shown in blue. Scale bar, 150 μm. (b) Percentage of SA-β‐Gal positive cells. n = 3 per group. (c) IF staining for P16 (red). DAPI was used to stain the nuclei. Scale bar, 50 μm. (d) Percentage of P16 positive cells. n = 3 per group. (e) IF staining for Ki-67 (red). DAPI was used to stain the nuclei. Scale bar, 50 μm. (f) Percentage of Ki-67 positive cells. n = 3 per group. (g) The expression of p16 and p21 were assessed by Western blotting. (h) ELISA-based assay for detecting the concentrations of collagen Ⅰ. (*, P < 0.05, compared with young; #, P < 0.05, compared with Aged). Statistical significance was determined by one-way ANOVA (Tukey’s multiple-comparisons test).
Fig. 6. USC-sEVs decreased the expression of SASP in senescent HDFs in vitro experiments. HDFs were treated with d-gal to induce senescence, then the senescent HDFs were treated with USC-sEVs (Agd-sEVs) or PBS (Aged), while HDFs treated without d-gal (Young) were used as control. (a) ELISA-based assay for detecting the concentrations of SASP (IL-1β, IL-6, MMP-13). n = 3 per group. (b) Quantification of mRNA expression for SASP (IL-1β, IL-6, MMP-13). n = 3 per group. (*, P < 0.05, compared with young; #, P < 0.05, compared with Aged). Statistical significance was determined by one-way ANOVA (Tukey’s multiple-comparisons test).
Fig. 7. USC-sEVs ameliorate aging phenotypes of senescent HDFs through activating Sirt1 in vitro experiments. HDFs were treated with d-gal to induce senescence, then the senescent HDFs were treated with USC-sEVs (Agd-sEVs) or co-treated with USC-sEVs and Sirt1 inhibitor (Aged-sEVs-Nicotinamide), while HDFs treated without d-gal (Young) and aged HDFs without treatment (Aged) were set as controls. (a) The expression of Sirt1 were assessed by Western blotting. (b) Representative micrographs of HDFs stained with SA-β-gal. SA-β-gal-positive cells are shown in blue. Scale bar, 150 μm. (c) Percentage of SA‐β‐Gal positive cells. n = 3 per group. (d) The expression of p16 and p21 were assessed by Western blotting. (e) IF staining for P16 (red). DAPI was used to stain the nuclei. Scale bar, 50 μm. (f) Percentage of P16 positive cells. n = 3 per group. (g) IF staining for Ki-67 (red). DAPI was used to stain the nuclei. Scale bar, 50 μm. (h) Percentage of Ki-67 positive cells. n = 3 per group. i) ELISA-based assay for detecting the concentrations of collagen Ⅰ. (*, P < 0.05, compared with Aged; #, P < 0.05, compared with Aged-sEVs). Statistical significance was determined by one-way ANOVA (Tukey’s multiple-comparisons test).
Fig. 8. USC-sEVs decreased the expression of SASP in senescent HDFs through activating Sirt1 in vitro experiments. HDFs were treated with d-gal to induce senescence, then the senescent HDFs were treated with USC-sEVs (Agd-sEVs) or co-treated with USC-sEVs and Sirt1 inhibitor (Aged-sEVs-Nicotinamide), while aged HDFs without treatment (Aged) were set as control. (a) ELISA-based assay for detecting the concentrations of SASP (IL-1β, IL-6, MMP-13). n = 3 per group. (b) Quantification of mRNA expression for SASP (IL-1β, IL-6, MMP-13). n = 3 per group. (*, P < 0.05, compared with Aged; #, P < 0.05, compared with Aged-sEVs). Statistical significance was determined by one-way ANOVA (Tukey’s multiple-comparisons test).
| [1] |
D. Barski, H. Gerullis, T. Ecke, G. Varga, M. Boros, I. Pintelon, J.P. Timmermans, T. Otto, Int. J. Surg. Case Rep. 51 (2018) 11-13.
DOI URL PMID |
| [2] |
L. Gould, P. Abadir, H. Brem, M. Carter, T. Conner-Kerr, J. Davidson, L. DiPietro, V. Falanga, C. Fife, S. Gardner, E. Grice, J. Harmon, W.R. Hazzard, K.P. High, P. Houghton, N. Jacobson, R.S. Kirsner, E.J. Kovacs, D. Margolis, F. McFarland Horne, M.J. Reed, D.H. Sullivan, S. Thom, M. Tomic-Canic, J. Walston, J.A. Whitney, J. Williams, S. Zieman, K. Schmader, J. Am. Geriatr. Soc. 63 (2015) 427-438.
DOI URL PMID |
| [3] |
R. Sgonc, J. Gruber, Gerontology 59 (2013) 159-164.
DOI URL |
| [4] |
C.B. Ballas, J.M. Davidson, Wound Repair Regen. 9 (2001) 223-237.
DOI URL PMID |
| [5] |
J.M. van Deursen, Nature 509 (2014) 439-446.
DOI URL |
| [6] |
H. Pratsinis, E. Mavrogonatou, D. Kletsas, Adv. Drug Deliv. Rev. 146 (2019) 325-343.
DOI URL PMID |
| [7] | J.P. Coppe, C.K. Patil, F. Rodier, Y. Sun, D.P. Munoz, J. Goldstein, P.S. Nelson, P.Y. Desprez, J. Campisi, PLoS Biol. 6 (2008) 2853-2868. |
| [8] | Y. Sun, J.P. Coppe, E.W. Lam, Trends Mol.Med. 24 (2018) 871-885. |
| [9] |
J. Neves, P. Sousa-Victor, H. Jasper, Cell Stem Cell 20 (2017) 161-175.
DOI URL PMID |
| [10] |
A.L. Strong, A.C. Bowles, C.P. MacCrimmon. T.P. Frazier, S.J. Lee, X. Wu, A.J. Katz, B. Gawronska-Kozak, B.A. Bunnell, J.M. Gimble, Stem Cells Transl. Med. 4 (2015) 632-642.
DOI URL PMID |
| [11] |
Z.G. Zhang, B. Buller, M. Chopp, Nat. Rev. Neurol. 15 (2019) 193-203.
DOI URL PMID |
| [12] |
P. Gao, D. Jiang, W. Liu, H. Li, Z. Li, Curr. Stem Cell Res. Ther. 11 (2016) 547-553.
DOI URL PMID |
| [13] |
M. Tofino-Vian, M.I. Guillen, M.D. Perez Del Caz, M.A. Castejon, M.J. Alcaraz. Oxid. Med. Cell. Longev. 2017 (2017), 7197598.
DOI URL PMID |
| [14] |
Y. Wang, D. Yu, Z. Liu, F. Zhou, J. Dai, B. Wu, J. Zhou, B.C. Heng, X.H. Zou, H. Ouyang, H. Liu, Stem Cell Res. Ther. 8 (2017) 189.
DOI URL PMID |
| [15] |
S.F. Tian, Z.Z. Jiang, Y.M. Liu, X. Niu, B. Hu, S.C. Guo, N.S. Wang, Y. Wang, Mol. Med. Rep. 16 (2017) 5541-5548.
DOI URL PMID |
| [16] |
Y. Fu, J. Guan, S. Guo, F. Guo, X. Niu, Q. Liu, C. Zhang, H. Nie, Y. Wang, J. Transl. Med. 12 (2014) 274.
DOI URL PMID |
| [17] |
R. Wu, C. Huang, Q. Wu, X. Jia, M. Liu, Z. Xue, Y. Qiu, X. Niu, Y. Wang, Stem Cell Res. Ther. 10 (2019) 80.
DOI URL PMID |
| [18] |
Z. Wu, X. Liu, D. Yuan, J. Zhao, Exp. Ther. Med. 16 (2018) 1285-1289.
DOI URL PMID |
| [19] |
B. Farhadihosseinabadi, M. Farahani, T. Tayebi, A. Jafari, F. Biniazan, K. Modaresifar, H. Moravvej, S. Bahrami, H. Redl, L. Tayebi, H. Niknejad, Artif. Cells Nanomed. Biotechnol. 46 (2018) 431-440.
DOI URL PMID |
| [20] |
M.D. Resch, B.E. Resch, E. Csizmazia, L. Imre, J. Nemeth, P. Szabo-Revesz, E. Csanyi, J. Ocul. Pharmacol. Ther. 27 (2011) 323-326.
DOI URL PMID |
| [21] |
M.L. Yelchuri, B. Madhavi, N. Gohil, H.S. Sajeev, N. Venkatesh Prajna, S. Srinivasan, Cornea 36 (2017) 594-599.
DOI URL PMID |
| [22] |
J.J. Guan, X. Niu, F.X. Gong, B. Hu, S.C. Guo, Y.L. Lou, C.Q. Zhang, Z.F. Deng, Y. Wang, Tissue Eng. Part A 20 (2014) 1794-1806.
DOI URL PMID |
| [23] | C.J. Park, S.G. Clark, C.A. Lichtensteiger, R.D. Jamison, A.J. Johnson, ActaBiomater. 5 (2009) 1926-1936. |
| [24] |
F. Vena, E. Li Causi, M. Rodriguez-Justo, S. Goodstal, T. Hagemann, J.A. Hartley, D. Hochhauser, Clin. Cancer Res. 21 (2015) 5563-5577.
DOI URL PMID |
| [25] |
X. Liu, Y. Yang, Y. Li, X. Niu, B. Zhao, Y. Wang, C. Bao, Z. Xie, Q. Lin, L. Zhu, Nanoscale 9 (2017) 4430-4438.
DOI URL PMID |
| [26] |
D.Y. Yoo, W. Kim, C.H. Lee, B.N. Shin, S.M. Nam, J.H. Choi, M.H. Won, Y.S. Yoon, I.K. Hwang, J. Pineal Res. 52 (2012) 21-28.
DOI URL |
| [27] |
E. Kaviani, M. Rahmani, A. Kaeidi, A. Shamsizadeh, M. Allahtavakoli, N. Mozafari, I. Fatemi, Behav. Brain Res. 334 (2017) 55-60.
DOI URL PMID |
| [28] |
R. Baeta-Corral, R. Castro-Fuentes, L. Gimenez-Llort, J. Gerontol. A Biol. Sci. Med. Sci. 73 (2018) 1147-1157.
DOI URL PMID |
| [29] |
M.P. Baar, R.M.C. Brandt, D.A. Putavet, J.D.D. Klein, K.W.J. Derks, B.R.M. Bourgeois, S. Stryeck, Y. Rijksen, H. van Willigenburg, D.A. Feijtel, I. van der Pluijm, J. Essers, W. A. van Cappellen, I.W.F. van, A.B. Houtsmuller, J. Pothof, R.W.F. de Bruin, T. Madl, J.H.J. Hoeijmakers, J. Campisi, P.L.J. de Keizer, Cell 169 (2017), 132-147. e116.
DOI URL PMID |
| [30] |
S. Hekmatimoghaddam, A. Dehghani Firoozabadi, M.R. Zare-Khormizi, F. Pourrajab, Ageing Res. Rev. 40 (2017) 120-141.
DOI URL PMID |
| [31] |
T. Liu, X. Ma, T. Ouyang, H. Chen, J. Lin, J. Liu, Y. Xiao, J. Yu, Y. Huang, Int. J. Biol. Macromol. 117 (2018) 225-234.
DOI URL PMID |
| [32] |
Y. Yuan, V.F. Cruzat, P. Newsholme, J. Cheng, Y. Chen, Y. Lu, Mech. Ageing Dev. 155 (2016) 10-21.
DOI URL PMID |
| [1] | Run Huang, Lei Liu, Bo Li, Liang Qin, Lei Huang, Kelvin W.K. Yeung, Yong Han. Nanograins on Ti-25Nb-3Mo-2Sn-3Zr alloy facilitate fabricating biological surface through dual-ion implantation to concurrently modulate the osteogenic functions of mesenchymal stem cells and kill bacteria [J]. J. Mater. Sci. Technol., 2021, 73(0): 31-44. |
| [2] | Donglin Han, Yuan Li, Xiangmei Liu, Kelvin Wai Kwok Yeung, Yufeng Zheng, Zhenduo Cui, Yanqin Liang, Zhaoyang Li, Shengli Zhu, Xianbao Wang, Shuilin Wu. Photothermy-strengthened photocatalytic activity of polydopamine-modified metal-organic frameworks for rapid therapy of bacteria-infected wounds [J]. J. Mater. Sci. Technol., 2021, 62(0): 83-95. |
| [3] | Jing Li, Zhenqiang Feng, Ning Gu, Fang Yang. Superparamagnetic iron oxide nanoparticles assembled magnetic nanobubbles and their application for neural stem cells labeling [J]. J. Mater. Sci. Technol., 2021, 63(0): 124-132. |
| [4] | Kai Chen, Changci Tong, Jinge Yang, Peifang Cong, Ying Liu, Xiuyun Shi, Xu Liu, Jun Zhang, Rufei Zou, Keshen Xiao, Yuyang Ni, Lei Xu, Mingxiao Hou, Hongxu Jin, Yunen Liu. Injectable melatonin-loaded carboxymethyl chitosan (CMCS)-based hydrogel accelerates wound healing by reducing inflammation and promoting angiogenesis and collagen deposition [J]. J. Mater. Sci. Technol., 2021, 63(0): 236-245. |
| [5] | Yiming Xiang, Qilin Zhou, Zhaoyang Li, Zhenduo Cui, Xiangmei Liu, Yanqin Liang, Shengli Zhu, Yufeng Zheng, Kelvin Wai Kwok Yeung, Shuilin Wu. A Z-scheme heterojunction of ZnO/CDots/C3N4 for strengthened photoresponsive bacteria-killing and acceleration of wound healing [J]. J. Mater. Sci. Technol., 2020, 57(0): 1-11. |
| [6] | Ma Jun,Zhao Nan,Betts Lexxus,Zhu Donghui. Bio-Adaption between Magnesium Alloy Stent and the Blood Vessel: A Review [J]. J. Mater. Sci. Technol., 2016, 32(9): 815-826. |
| [7] | Guobo Lan, Mei Li, Ying Tan, Lihua Li, Xiaoming Yang, Limin Ma, Qingshui Yin, Hong Xia, Yu Zhang, Guoxin Tan, Chengyun Ning. Promoting Bone Mesenchymal Stem Cells and Inhibiting Bacterial Adhesion of Acid-Etched Nanostructured Titanium by Ultraviolet Functionalization [J]. J. Mater. Sci. Technol., 2015, 31(2): 182-190. |
| Viewed | ||||||
|
Full text |
|
|||||
|
Abstract |
|
|||||
WeChat
