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Payload distribution and capacity of mRNA lipid nanoparticles

Lipid nanoparticles (LNPs) are effective vehicles to deliver mRNA vaccines and therapeutics. It has been challenging to assess mRNA packaging characteristics in LNPs, including payload distribution and capacity, which are critical to understanding structure-property-function relationships for furthe...

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Autores principales: Li, Sixuan, Hu, Yizong, Li, Andrew, Lin, Jinghan, Hsieh, Kuangwen, Schneiderman, Zachary, Zhang, Pengfei, Zhu, Yining, Qiu, Chenhu, Kokkoli, Efrosini, Wang, Tza-Huei, Mao, Hai-Quan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9508184/
https://www.ncbi.nlm.nih.gov/pubmed/36151112
http://dx.doi.org/10.1038/s41467-022-33157-4
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author Li, Sixuan
Hu, Yizong
Li, Andrew
Lin, Jinghan
Hsieh, Kuangwen
Schneiderman, Zachary
Zhang, Pengfei
Zhu, Yining
Qiu, Chenhu
Kokkoli, Efrosini
Wang, Tza-Huei
Mao, Hai-Quan
author_facet Li, Sixuan
Hu, Yizong
Li, Andrew
Lin, Jinghan
Hsieh, Kuangwen
Schneiderman, Zachary
Zhang, Pengfei
Zhu, Yining
Qiu, Chenhu
Kokkoli, Efrosini
Wang, Tza-Huei
Mao, Hai-Quan
author_sort Li, Sixuan
collection PubMed
description Lipid nanoparticles (LNPs) are effective vehicles to deliver mRNA vaccines and therapeutics. It has been challenging to assess mRNA packaging characteristics in LNPs, including payload distribution and capacity, which are critical to understanding structure-property-function relationships for further carrier development. Here, we report a method based on the multi-laser cylindrical illumination confocal spectroscopy (CICS) technique to examine mRNA and lipid contents in LNP formulations at the single-nanoparticle level. By differentiating unencapsulated mRNAs, empty LNPs and mRNA-loaded LNPs via coincidence analysis of fluorescent tags on different LNP components, and quantitatively resolving single-mRNA fluorescence, we reveal that a commonly referenced benchmark formulation using DLin-MC3 as the ionizable lipid contains mostly 2 mRNAs per loaded LNP with a presence of 40%–80% empty LNPs depending on the assembly conditions. Systematic analysis of different formulations with control variables reveals a kinetically controlled assembly mechanism that governs the payload distribution and capacity in LNPs. These results form the foundation for a holistic understanding of the molecular assembly of mRNA LNPs.
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spelling pubmed-95081842022-09-25 Payload distribution and capacity of mRNA lipid nanoparticles Li, Sixuan Hu, Yizong Li, Andrew Lin, Jinghan Hsieh, Kuangwen Schneiderman, Zachary Zhang, Pengfei Zhu, Yining Qiu, Chenhu Kokkoli, Efrosini Wang, Tza-Huei Mao, Hai-Quan Nat Commun Article Lipid nanoparticles (LNPs) are effective vehicles to deliver mRNA vaccines and therapeutics. It has been challenging to assess mRNA packaging characteristics in LNPs, including payload distribution and capacity, which are critical to understanding structure-property-function relationships for further carrier development. Here, we report a method based on the multi-laser cylindrical illumination confocal spectroscopy (CICS) technique to examine mRNA and lipid contents in LNP formulations at the single-nanoparticle level. By differentiating unencapsulated mRNAs, empty LNPs and mRNA-loaded LNPs via coincidence analysis of fluorescent tags on different LNP components, and quantitatively resolving single-mRNA fluorescence, we reveal that a commonly referenced benchmark formulation using DLin-MC3 as the ionizable lipid contains mostly 2 mRNAs per loaded LNP with a presence of 40%–80% empty LNPs depending on the assembly conditions. Systematic analysis of different formulations with control variables reveals a kinetically controlled assembly mechanism that governs the payload distribution and capacity in LNPs. These results form the foundation for a holistic understanding of the molecular assembly of mRNA LNPs. Nature Publishing Group UK 2022-09-23 /pmc/articles/PMC9508184/ /pubmed/36151112 http://dx.doi.org/10.1038/s41467-022-33157-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Li, Sixuan
Hu, Yizong
Li, Andrew
Lin, Jinghan
Hsieh, Kuangwen
Schneiderman, Zachary
Zhang, Pengfei
Zhu, Yining
Qiu, Chenhu
Kokkoli, Efrosini
Wang, Tza-Huei
Mao, Hai-Quan
Payload distribution and capacity of mRNA lipid nanoparticles
title Payload distribution and capacity of mRNA lipid nanoparticles
title_full Payload distribution and capacity of mRNA lipid nanoparticles
title_fullStr Payload distribution and capacity of mRNA lipid nanoparticles
title_full_unstemmed Payload distribution and capacity of mRNA lipid nanoparticles
title_short Payload distribution and capacity of mRNA lipid nanoparticles
title_sort payload distribution and capacity of mrna lipid nanoparticles
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9508184/
https://www.ncbi.nlm.nih.gov/pubmed/36151112
http://dx.doi.org/10.1038/s41467-022-33157-4
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