Podrobná bibliografie
| Název: |
mRNA delivery enabled by metal–organic nanoparticles. |
| Autoři: |
Gu, Yuang, Chen, Jingqu, Wang, Zhaoran, Liu, Chang, Wang, Tianzheng, Kim, Chan-Jin, Durikova, Helena, Fernandes, Soraia, Johnson, Darryl N., De Rose, Robert, Cortez-Jugo, Christina, Caruso, Frank |
| Zdroj: |
Nature Communications; 11/8/2024, Vol. 15 Issue 1, p1-15, 15p |
| Témata: |
GENE expression, ETHYLENE glycol, INTRAVENOUS therapy, GENOME editing, NANOPARTICLES |
| Abstrakt: |
mRNA therapeutics are set to revolutionize disease prevention and treatment, inspiring the development of platforms for safe and effective mRNA delivery. However, current mRNA delivery platforms face some challenges, including limited organ tropism for nonvaccine applications and inflammation induced by cationic nanoparticle components. Herein, we address these challenges through a versatile, noncationic nanoparticle platform whereby mRNA is assembled into a poly(ethylene glycol)-polyphenol network stabilized by metal ions. Screening a range of components and relative compositional ratios affords a library of stable, noncationic, and highly biocompatible metal–organic nanoparticles with robust mRNA transfection in vitro and in mice. Intravenous administration of the lead mRNA-containing metal–organic nanoparticles enables predominant protein expression and gene editing in the brain, liver, and kidney, while organ tropism is tuned by varying nanoparticle composition. This study opens an avenue for realizing metal–organic nanoparticle-enabled mRNA delivery, offering a modular approach to assembling mRNA therapeutics for health applications. Potential toxicity from cationic moieties and limited organ tropism are two challenges faced by current mRNA delivery vehicles. Here, authors develop non-cationic, highly biocompatible metal–organic nanoparticles that enable robust mRNA expression in vivo with tunable organ tropism. [ABSTRACT FROM AUTHOR] |
|
Copyright of Nature Communications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Databáze: |
Complementary Index |