Intracellular Quantification and Localization of Label-Free Iron Oxide Nanoparticles by Holotomographic Microscopy

Background The limitations of optical microscopy to determine the cellular localization of label-free nanoparticles prevent a solid prediction of the cellular effect of particles intended for medical applications. To avoid the strong physicochemical changes associated with fluorescent labelling, which often result in differences in cellular uptake, efficiency and toxicity of particles, novel detection techniques are required. Methods In the present study, we determined the intracellular content of unlabeled SPIONs by analyzing refractive index (RI)-based images from holotomographic three-dimensional (3D) microscopy and side scatter data measured by flow cytometry. The results were compared with the actual cellular SPION amount as quantified by atomic emission spectroscopy (AES). Results Live cell imaging by 3D holotomographic microscopy demonstrated cell-specific differences in intracellular nanoparticle uptake in different pancreatic cell lines. Thus, treatment of PANC-1SMAD4 (1−4) and PANC-1SMAD4 (2−6) with SPIONs resulted in a significant increase in number of areas with higher RI, whereas in PANC-1, SUIT-2 and PaCa DD183, only a minimal increase of spots with high RI was observed. The increase in areas with high RI was in accordance with the SPION content determined by quantitative iron measurements using AES. In contrast, determination of the SPION amount by flow cytometry was strongly cell type-dependent and did not allow the discrimination between intracellular and membrane-bound SPIONs. However, flow cytometry is a very rapid and reliable method to assess the cellular toxicity and allows an estimation of the cell-associated SPION content. Conclusion Holotomographic 3D microscopy is a useful method to distinguish between intracellular and membrane-associated particles. Thus, it provides a valuable tool for scientists to evaluate the cellular localization and the particle load, which facilitates prediction of potential toxicity and efficiency of nanoparticles for medical applications.