Quantifying intracellular trafficking of silica-coated magnetic nanoparticles in live single cells by site-specific direct stochastic optical reconstruction microscopy

Abstract

Abstract Background Nanoparticles have been used for biomedical applications, including drug delivery, diagnosis, and imaging based on their unique properties derived from small size and large surface-to-volume ratio. However, concerns regarding unexpected toxicity due to the localization of nanoparticles in the cells are growing. Herein, we quantified the number of cell-internalized nanoparticles and monitored their cellular localization, which are critical factors for biomedical applications of nanoparticles. Methods This study investigates the intracellular trafficking of silica-coated magnetic nanoparticles containing rhodamine B isothiocyanate dye [MNPs@SiO2(RITC)] in various live single cells, such as HEK293, NIH3T3, and RAW 264.7 cells, using site-specific direct stochastic optical reconstruction microscopy (dSTORM). The time-dependent subdiffraction-limit spatial resolution of the dSTORM method allowed intracellular site-specific quantification and tracking of MNPs@SiO2(RITC). Results The MNPs@SiO2(RITC) were observed to be highly internalized in RAW 264.7 cells, compared to the HEK293 and NIH3T3 cells undergoing single-particle analysis. In addition, MNPs@SiO2(RITC) were internalized within the nuclei of RAW 264.7 and HEK293 cells but were not detected in the nuclei of NIH3T3 cells. Moreover, because of the treatment of the MNPs@SiO2(RITC), more micronuclei were detected in RAW 264.7 cells than in other cells. Conclusion The sensitive and quantitative evaluations of MNPs@SiO2(RITC) at specific sites in three different cells using a combination of dSTORM, transcriptomics, and molecular biology were performed. These findings highlight the quantitative differences in the uptake efficiency of MNPs@SiO2(RITC) and ultra-sensitivity, varying according to the cell types as ascertained by subdiffraction-limit super-resolution microscopy. Graphical Abstract