Multiparametric functional characterization of individual lipid nanoparticles using surface-sensitive light-scattering microscopy

Journal article, 2025

The most efficient lipid nanoparticles (LNPs) for gene therapeutics rely on specific lipids that protect the oligonucleotide cargo and aid cellular uptake and subsequent endosomal escape. Yet, the efficacy of current state-of-the-art LNP formulations remains low, a few percent at best. A deeper understanding of how LNP cargo, lipid composition, stoichiometry, size, structure, and pH-induced conformational changes influence their efficiency is therefore necessary for improved design. Given the variability of these properties, preferred screening methods should offer single-particle-resolved multiparametric characterization. In this work, we employ combined surface-sensitive fluorescence and label-free scattering microscopy with single LNP resolution, which when integrated with microfluidics for liquid exchange between media of varying refractive index, enables quantification of LNP size, refractive index, and cargo content. We investigate two LNP formulations that, while similar in size and mRNA content, exhibit differences in functional mRNA delivery. Correlating size with the content of Cy5-labeled mRNA revealed that the cargo scaled with LNP volume for both types of LNPs, while the refractive index varied marginally across LNP size. While this multiparametric fingerprinting alone could not distinguish the two LNP formulations, we use the same experimental platform to show that their difference in fusogenicity to a supporting lipid bilayer under early endosomal conditions (drop in pH from 7.4 to 6.0) correlates with observed differences in in vitro cellular data. This highlights a limitation of the current state-of-the-art toolbox for in situ LNP characterization, which generally focuses on structural properties of suspended LNPs, which may not adequately capture functional performance.