Lipid nanoparticle-encapsulated mRNA antibody provides long-term protection against SARS-CoV-2 in mice and hamsters
Autor: | Yong-Qiang Deng, Na-Na Zhang, Yi-Fei Zhang, Xia Zhong, Sue Xu, Hong-Ying Qiu, Tie-Cheng Wang, Hui Zhao, Chao Zhou, Shu-Long Zu, Qi Chen, Tian-Shu Cao, Qing Ye, Hang Chi, Xiang-Hui Duan, Dan-Dan Lin, Xiao-Jing Zhang, Liang-Zhi Xie, Yu-Wei Gao, Bo Ying, Cheng-Feng Qin |
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Rok vydání: | 2022 |
Předmět: | |
Zdroj: | Cell Research. 32:375-382 |
ISSN: | 1748-7838 1001-0602 |
DOI: | 10.1038/s41422-022-00630-0 |
Popis: | Monoclonal antibodies represent important weapons in our arsenal to against the COVID-19 pandemic. However, this potential is severely limited by the time-consuming process of developing effective antibodies and the relative high cost of manufacturing. Herein, we present a rapid and cost-effective lipid nanoparticle (LNP) encapsulated-mRNA platform for in vivo delivery of SARS-CoV-2 neutralization antibodies. Two mRNAs encoding the light and heavy chains of a potent SARS-CoV-2 neutralizing antibody HB27, which is currently being evaluated in clinical trials, were encapsulated into clinical grade LNP formulations (named as mRNA-HB27-LNP). In vivo characterization demonstrated that intravenous administration of mRNA-HB27-LNP in mice resulted in a longer circulating half-life compared with the original HB27 antibody in protein format. More importantly, a single prophylactic administration of mRNA-HB27-LNP provided protection against SARS-CoV-2 challenge in mice at 1, 7 and even 63 days post administration. In a close contact transmission model, prophylactic administration of mRNA-HB27-LNP prevented SARS-CoV-2 infection between hamsters in a dose-dependent manner. Overall, our results demonstrate a superior long-term protection against SARS-CoV-2 conferred by a single administration of this unique mRNA antibody, highlighting the potential of this universal platform for antibody-based disease prevention and therapy against COVID-19 as well as a variety of other infectious diseases. |
Databáze: | OpenAIRE |
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