Silver Nanoparticles Encapped by Dihydromyricetin: Optimization of Green Synthesis, Characterization, Toxicity, and Anti-MRSA Infection Activities for Zebrafish ( Danio rerio ).
Ling-Xiao QiXue-Ting WangJin-Ping HuangTing-Yan YueYun-Shu LuDong-Mei SanYu-Xun XuYa-Tong HanXiang-Yi GuoWei-Dong XieYan-Xia ZhouPublished in: International journal of molecular sciences (2024)
To achieve the environmentally friendly and rapid green synthesis of efficient and stable AgNPs for drug-resistant bacterial infection, this study optimized the green synthesis process of silver nanoparticles (AgNPs) using Dihydromyricetin (DMY). Then, we assessed the impact of AgNPs on zebrafish embryo development, as well as their therapeutic efficacy on zebrafish infected with Methicillin-resistant Staphylococcus aureus (MRSA). Transmission electron microscopy (TEM) and dynamic light-scattering (DLS) analyses revealed that AgNPs possessed an average size of 23.6 nm, a polymer dispersity index (PDI) of 0.197 ± 0.0196, and a zeta potential of -18.1 ± 1.18 mV. Compared to other published green synthesis products, the optimized DMY-AgNPs exhibited smaller sizes, narrower size distributions, and enhanced stability. Furthermore, the minimum concentration of DMY-AgNPs required to affect zebrafish hatching and survival was determined to be 25.0 μg/mL, indicating the low toxicity of DMY-AgNPs. Following a 5-day feeding regimen with DMY-AgNP-containing food, significant improvements were observed in the recovery of the gills, intestines, and livers in MRSA-infected zebrafish. These results suggested that optimized DMY-AgNPs hold promise for application in aquacultures and offer potential for further clinical use against drug-resistant bacteria.
Keyphrases
- silver nanoparticles
- drug resistant
- methicillin resistant staphylococcus aureus
- multidrug resistant
- staphylococcus aureus
- acinetobacter baumannii
- systematic review
- oxidative stress
- randomized controlled trial
- photodynamic therapy
- pseudomonas aeruginosa
- machine learning
- risk assessment
- pregnant women
- cystic fibrosis
- deep learning
- quantum dots