The Impact of Cell Density Variations on Nanoparticle Uptake Across Bioprinted A549 Gradients

Luigi Di Stolfo^1,2Wang Sik Lee^1,2Dimitri Vanhecke^1,2Sandor Balog^1,2Patricia Taladriz-Blanco^1,2Alke Petri-Fink^1,2,3Barbara Rothen-Rutishauser^1,2*

• ¹Institut Adolphe Merkle, Faculté des Sciences et de Médecine, Université de Fribourg, Fribourg, Switzerland
• ²National Centre of Competence in Research for Bio-Inspired Materials, Faculty of Science and Medicine, University of Friborg, Fribourg, Fribourg, Switzerland
• ³Département de Chimie, Faculté des Sciences et de Médecine, Université de Fribourg, Fribourg, Fribourg, Switzerland

Introduction: The safe-by-design of engineered nanoparticles (NPs) for any application requires a detailed understanding of how the particles interact with single cells. Most studies are based on two-dimensional, uniformly dense cell cultures, which do not represent the diverse and inhomogeneous cell environments found in situ. In-vitro models that accurately represent tissue complexity, including realistic cell densities, are essential to increase the predictive accuracy of studies on cell-NP interactions. This study uses a bioprinted cell gradient model to examine the relation between cell density and NP uptake in one dish. Method: A549 lung epithelial cell density gradients within single inserts were produced with a bioprinter by modulating inter-droplet distances. After two days in culture, cells were exposed to Cy5-labeled silica NPs (SiO2 NPs, ~112 nm, 20 μg/mL) for up to 48 h. Confocal fluorescence microscopy and 3D image analysis were employed to quantify NP uptake, surface area, and cell volume and investigated statistically their relationship with NP uptake. Results: Bioprinting enabled the creation of reproducible linear cell density gradients, allowing controlled modeling of density variations while preserving cell viability throughout the experiment. Increasing inter-droplet distances, from 0.1 mm to 0.6 mm, were used to achieve uniformly decreasing cell densities. SiO2 NP uptake per cell was around 50% higher in low-density regions compared to high-density areas across all time points, i.e., 6, 24, and 48 h post-exposure. This inverse relationship correlated with greater average cell surface area in lower-density regions, while proliferation rates of the A549 cells, about 30% slower at high densities, did not significantly impact uptake. Conclusion: SiO2 NP uptake is significantly enhanced at lower cell densities, mainly due to the increased available surface area, revealing potential cell-NP interaction differences in tissues that present cell density variability. Our drop-on-demand bioprinting gradient model successfully supports the implementation of cell density gradients in in-vitro models to increase their relevance as new approach methodologies (NAMs) for next-generation risk assessment strategies.