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Constructing multifunctional Cu Single-Atom nanozyme for synergistic nanocatalytic Therapy-Mediated Multidrug-Resistant bacteria infected wound healing

过氧亚硝酸盐 活性氮物种 活性氧 化学 过氧化氢 细菌 过氧化氢酶 伤口愈合 一氧化氮 超氧化物 微生物学 生物化学 生物 免疫学 有机化学 遗传学
作者
Xiaochen Qiu,Liang Zhuang,Jian Yuan,Huizhen Wang,Xiaoyu Dong,Shan He,Shanyue Guan,Zhiyue Chang,Pengtao Bao
出处
期刊:Journal of Colloid and Interface Science [Elsevier BV]
卷期号:652 (Pt B): 1712-1725 被引量:23
标识
DOI:10.1016/j.jcis.2023.08.192
摘要

Developing an effective strategy to combat multi-drug-resistant (MDR) bacteria and promote wound healing without overuse of antibiotics remains an important and challenging goal. Herein, we established a synergistic reactive oxygen species (ROS) and reactive nitrogen species (RNS)-mediated nanocatalytic therapy, which was consisted of a multifunctional Cu single-atom nanozyme loaded with the l-arginine (l-Arg@Cu-SAzymes) and a low level of hydrogen peroxide (H2O2) as a trigger. l-Arg@Cu-SAzymes can possess excellent dual enzyme-like activities: catalase (CAT)-like activity that decompose H2O2 into O2, and subsequent oxidase (OXD)-like activity that convert O2 to cytotoxic superoxide anion radical (•O2-). Meanwhile, l-Arg@Cu-SAzymes can also be triggered by H2O2 to release nitric oxide (NO), which can continue to react with •O2- to generate more lethal peroxynitrite (ONOO-). Collectively, the synergistic ROS and RNS mediated by l-Arg@Cu-SAzymes endow the treatment system with an outstanding antibacterial ability against MDR bacteria and reduce the inflammation at the wound site. Furthermore, l-Arg@Cu-SAzymes-mediated NO and O2 release promote the cell proliferation, collagen synthesis, and the angiogenesis, as well as facilitate macrophage polarization to reparative M2 phenotype, thereby accelerating wound closure and tissue remodeling. Therefore, l-Arg@Cu-SAzymes-based synergistic nanocatalytic therapy can be regarded as a promising strategy for MDR bacterial infected wounds treatment, owing to their potent antibacterial efficacy and enhanced tissue remodeling effects.
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