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Li S, Hu Y, Lin J, Schneiderman Z, Shao F, Wei L, Li A, Hsieh K, Kokkoli E, Curk T, Mao HQ, Wang TH. Single-Particle Spectroscopic Chromatography Reveals Heterogeneous RNA Loading and Size Correlations in Lipid Nanoparticles. ACS NANO 2024; 18:15729-15743. [PMID: 38839059 PMCID: PMC11191693 DOI: 10.1021/acsnano.4c02341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 04/30/2024] [Accepted: 05/08/2024] [Indexed: 06/07/2024]
Abstract
Lipid nanoparticles (LNP) have emerged as pivotal delivery vehicles for RNA therapeutics. Previous research and development usually assumed that LNPs are homogeneous in population, loading density, and composition. Such perspectives are difficult to examine due to the lack of suitable tools to characterize these physicochemical properties at the single-nanoparticle level. Here, we report an integrated spectroscopy-chromatography approach as a generalizable strategy to dissect the complexities of multicomponent LNP assembly. Our platform couples cylindrical illumination confocal spectroscopy (CICS) with single-nanoparticle free solution hydrodynamic separation (SN-FSHS) to simultaneously profile population identity, hydrodynamic size, RNA loading levels, and distributions of helper lipid and PEGylated lipid of LNPs at the single-particle level and in a high-throughput manner. Using a benchmark siRNA LNP formulation, we demonstrate the capability of this platform by distinguishing seven distinct LNP populations, quantitatively characterizing size distribution and RNA loading level in wide ranges, and more importantly, resolving composition-size correlations. This SN-FSHS-CICS analysis provides critical insights into a substantial degree of heterogeneity in the packing density of RNA in LNPs and size-dependent loading-size correlations, explained by kinetics-driven assembly mechanisms of RNA LNPs.
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Affiliation(s)
- Sixuan Li
- Institute
for NanoBioTechnology, Johns Hopkins University, Baltimore, Maryland 21218, United States
- Department
of Mechanical Engineering, Johns Hopkins
University, Baltimore, Maryland 21218, United States
| | - Yizong Hu
- Institute
for NanoBioTechnology, Johns Hopkins University, Baltimore, Maryland 21218, United States
- Department
of Biomedical Engineering, Johns Hopkins
University School of Medicine, Baltimore, Maryland 21218, United States
- Translational
Tissue Engineering Center, Johns Hopkins
University School of Medicine, Baltimore, Maryland 21218, United States
| | - Jinghan Lin
- Institute
for NanoBioTechnology, Johns Hopkins University, Baltimore, Maryland 21218, United States
- Translational
Tissue Engineering Center, Johns Hopkins
University School of Medicine, Baltimore, Maryland 21218, United States
- Department
of Materials Science and Engineering, Johns
Hopkins University, Baltimore, Maryland 21218, United States
| | - Zachary Schneiderman
- Institute
for NanoBioTechnology, Johns Hopkins University, Baltimore, Maryland 21218, United States
- Department
of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Fangchi Shao
- Department
of Biomedical Engineering, Johns Hopkins
University School of Medicine, Baltimore, Maryland 21218, United States
| | - Lai Wei
- Department
of Mechanical Engineering, Johns Hopkins
University, Baltimore, Maryland 21218, United States
| | - Andrew Li
- Department
of Biomedical Engineering, Johns Hopkins
University School of Medicine, Baltimore, Maryland 21218, United States
| | - Kuangwen Hsieh
- Department
of Mechanical Engineering, Johns Hopkins
University, Baltimore, Maryland 21218, United States
| | - Efrosini Kokkoli
- Institute
for NanoBioTechnology, Johns Hopkins University, Baltimore, Maryland 21218, United States
- Department
of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Tine Curk
- Department
of Materials Science and Engineering, Johns
Hopkins University, Baltimore, Maryland 21218, United States
| | - Hai-Quan Mao
- Institute
for NanoBioTechnology, Johns Hopkins University, Baltimore, Maryland 21218, United States
- Department
of Biomedical Engineering, Johns Hopkins
University School of Medicine, Baltimore, Maryland 21218, United States
- Translational
Tissue Engineering Center, Johns Hopkins
University School of Medicine, Baltimore, Maryland 21218, United States
- Department
of Materials Science and Engineering, Johns
Hopkins University, Baltimore, Maryland 21218, United States
| | - Tza-Huei Wang
- Institute
for NanoBioTechnology, Johns Hopkins University, Baltimore, Maryland 21218, United States
- Department
of Mechanical Engineering, Johns Hopkins
University, Baltimore, Maryland 21218, United States
- Department
of Biomedical Engineering, Johns Hopkins
University School of Medicine, Baltimore, Maryland 21218, United States
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Settanni G. Computational approaches to lipid-based nucleic acid delivery systems. THE EUROPEAN PHYSICAL JOURNAL. E, SOFT MATTER 2023; 46:127. [PMID: 38097823 PMCID: PMC10721673 DOI: 10.1140/epje/s10189-023-00385-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 11/21/2023] [Indexed: 12/17/2023]
Abstract
Nucleic acid-based therapies have shown enormous effectiveness as vaccines against the recent COVID19 pandemics and hold great promises in the fight of a broad spectrum of diseases ranging from viral infections to cancer up to genetically transmitted pathologies. Due to their highly degradable polyanionic nature, nucleic acids need to be packed in sophisticate delivery vehicles which compact them up, protect them from early degradation and help delivery them to the right tissue/cells. Lipid-based nanoparticles (LNP) represent, at present, the main solution for nucleic acid delivery. They are made of a mixture of lipids whose key ingredient is an ionizable cationic lipid. Indeed, the interactions between the polyanionic nucleic acids and the ionizable cationic lipids, and their pH-dependent regulation in the life cycle of the nanoparticle, from production to cargo delivery, mostly determine the effectiveness of the therapeutic approach. Notwithstanding the large improvements in the delivery efficiency of LNPs in the last two decades, it is estimated that only a small fraction of the cargo is actually delivered, stimulating further research for the design of more effective LNP formulations. A rationally driven design would profit from the knowledge of the precise molecular structure of these materials, which is however still either missing or characterized by poor spatial resolution. Computational approaches have often been used as a molecular microscope either to enrich the available experimental data and provide a molecular-level picture of the LNPs or even simulate specific processes involving the formation and/or the molecular mechanisms of action of the LNP. Here, I review the recent literature in the field.
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Affiliation(s)
- Giovanni Settanni
- Faculty of Physics and Astronomy, Ruhr University Bochum, Universitätstrasse 150, 44801, Bochum, Germany.
- Department of Physics, Johannes-Gutenberg University Mainz, Staudingerweg 7, 55099, Mainz, Germany.
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Truong LB, Medina-Cruz D, Mostafavi E. Current state of RNA delivery using lipid nanoparticles to extrahepatic tissues: A review towards clinical translation. Int J Biol Macromol 2023:125185. [PMID: 37276899 DOI: 10.1016/j.ijbiomac.2023.125185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Revised: 05/29/2023] [Accepted: 05/30/2023] [Indexed: 06/07/2023]
Abstract
Genetic medicine, including ribonucleic acid (RNA) therapy, has delivered numerous progresses to the treatment of diseases thanks to the development of lipid nanoparticles (LNPs) as a delivery vehicle. However, RNA therapeutics are still limited by the lack of safe, precise, and efficient delivery outside of the liver. Thus, to fully realize the potential of genetic medicine, strategies to arm LNPs with extrahepatic targeting capabilities are urgently needed. This review explores the current state of next-generation LNPs that can bring RNA biomolecules to their targeted organ. The main approaches commonly used are described, including the modulation of internal lipid chemistries, the use of conjugated targeting moieties, and the designs of clinical administration. This work will demonstrate the advances in each approach and the remaining challenges in the field, focusing on clinical translation.
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Affiliation(s)
- Linh B Truong
- Department of Chemical Engineering, Northeastern University, Boston, MA 02115, USA
| | - David Medina-Cruz
- Department of Chemical Engineering, Northeastern University, Boston, MA 02115, USA
| | - Ebrahim Mostafavi
- Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
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