Flow Cytometric Evaluation of SYTO 9 Green Staining in Empty and Loaded Lipid Nanoparticles Using the CytoFLEX nano Flow Cytometer 2302379

Abstract

Abstract Introduction Lipid nanoparticles (LNPs) have emerged as nanoscale carriers for therapeutic agents, including mRNA vaccines and gene therapies. Accurate methods for characterizing nucleic acid encapsulation within these particles are essential for LNP development and quality control. This study presents an optimized flow cytometric protocol that uses SYTO 9 Green, a nucleic acid-binding dye, to differentiate and quantify nucleic acid-loaded versus empty LNPs with high sensitivity using the CytoFLEX nano Flow Cytometer. Methods We optimized a SYTO 9 Green staining protocol and applied it to empty and loaded LNP samples (Cytiva-sourced LNP1/LNP2 and UBC-sourced siRNA-LNPs). A sequential gating strategy was used to ensure single-particle detection by excluding debris and doublets. Dye titration experiments (ranging from 25 µM down to 3.125 µM SYTO 9 Green) were performed, along with critical controls, including unstained LNPs and SYTO 9 Green dye-only samples. Results Our results demonstrate that SYTO 9 Green staining enabled clear, concentration-dependent discrimination between loaded and empty LNPs. Loaded LNPs exhibited strong fluorescence signals, with positive staining efficiency peaking at optimal dye concentrations. Staining efficiency varies across concentrations, reflecting a complex interplay between dye-to-target binding, nucleic acid content, and potential quenching effects. In contrast, empty LNPs consistently showed minimal background staining (< 1% positive events). Unstained LNPs and dye-only controls presented negligible positive events, confirming that the observed signals are attributable to nucleic acid targets. Conclusion These findings highlight the combined use of the CytoFLEX nano Flow Cytometer and optimized SYTO 9 Green staining as a sensitive, robust approach for precise, multiparametric characterization of nucleic acid encapsulation in LNPs. Funding Source n/a Topic Categories Technological Innovations in Immunology (TECH)