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2022
Mendes, Carolina Rosai; Dilarri, Guilherme; Forsan, Carolina Froes; Sapata, Vinícius Moraes Ruy; Lopes, Paulo Renato Matos; Moraes, Peterson Bueno; Montagnolli, Renato Nallin; Ferreira, Henrique; Bidoia, Ederio Dino
Antibacterial action and target mechanisms of zinc oxide nanoparticles against bacterial pathogens Journal Article
In: Scientific Reports 2022 12:1, vol. 12, iss. 1, pp. 1-10, 2022, ISSN: 2045-2322.
Abstract | Links | BibTeX | Tags: Applied Microbiology, Bacteria, Nanoparticles
@article{Mendes2022,
title = {Antibacterial action and target mechanisms of zinc oxide nanoparticles against bacterial pathogens},
author = {Carolina Rosai Mendes and Guilherme Dilarri and Carolina Froes Forsan and Vinícius Moraes Ruy Sapata and Paulo Renato Matos Lopes and Peterson Bueno Moraes and Renato Nallin Montagnolli and Henrique Ferreira and Ederio Dino Bidoia},
url = {https://www.nature.com/articles/s41598-022-06657-y},
doi = {10.1038/s41598-022-06657-y},
issn = {2045-2322},
year = {2022},
date = {2022-01-01},
journal = {Scientific Reports 2022 12:1},
volume = {12},
issue = {1},
pages = {1-10},
publisher = {Nature Publishing Group},
abstract = {Zinc oxide nanoparticles (ZnO NPs) are one of the most widely used nanoparticulate materials due to their antimicrobial properties, but their main mechanism of action (MOA) has not been fully elucidated. This study characterized ZnO NPs by using X-ray diffraction, FT-IR spectroscopy and scanning electron microscopy. Antimicrobial activity of ZnO NPs against the clinically relevant bacteria Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and the Gram-positive model Bacillus subtilis was evaluated by performing resazurin microtiter assay (REMA) after exposure to the ZnO NPs at concentrations ranging from 0.2 to 1.4 mM. Sensitivity was observed at 0.6 mM for the Gram-negative and 1.0 mM for the Gram-positive cells. Fluorescence microscopy was used to examine the interference of ZnO NPs on the membrane and the cell division apparatus of B. subtilis (amy::pspac-ftsZ-gfpmut1) expressing FtsZ-GFP. The results showed that ZnO NPs did not interfere with the assembly of the divisional Z-ring. However, 70% of the cells exhibited damage in the cytoplasmic membrane after 15 min of exposure to the ZnO NPs. Electrostatic forces, production of Zn2+ ions and the generation of reactive oxygen species were described as possible pathways of the bactericidal action of ZnO. Therefore, understanding the bactericidal MOA of ZnO NPs can potentially help in the construction of predictive models to fight bacterial resistance.},
keywords = {Applied Microbiology, Bacteria, Nanoparticles},
pubstate = {published},
tppubtype = {article}
}
Zinc oxide nanoparticles (ZnO NPs) are one of the most widely used nanoparticulate materials due to their antimicrobial properties, but their main mechanism of action (MOA) has not been fully elucidated. This study characterized ZnO NPs by using X-ray diffraction, FT-IR spectroscopy and scanning electron microscopy. Antimicrobial activity of ZnO NPs against the clinically relevant bacteria Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and the Gram-positive model Bacillus subtilis was evaluated by performing resazurin microtiter assay (REMA) after exposure to the ZnO NPs at concentrations ranging from 0.2 to 1.4 mM. Sensitivity was observed at 0.6 mM for the Gram-negative and 1.0 mM for the Gram-positive cells. Fluorescence microscopy was used to examine the interference of ZnO NPs on the membrane and the cell division apparatus of B. subtilis (amy::pspac-ftsZ-gfpmut1) expressing FtsZ-GFP. The results showed that ZnO NPs did not interfere with the assembly of the divisional Z-ring. However, 70% of the cells exhibited damage in the cytoplasmic membrane after 15 min of exposure to the ZnO NPs. Electrostatic forces, production of Zn2+ ions and the generation of reactive oxygen species were described as possible pathways of the bactericidal action of ZnO. Therefore, understanding the bactericidal MOA of ZnO NPs can potentially help in the construction of predictive models to fight bacterial resistance.