A multicellular, neuro-mimetic model to study nanoparticle uptake in cells of the central nervous system

Abstract

Evaluating the uptake and handling of biomedically relevant nanoparticles by cells of the nervous system critically underpins the effective use of nanoparticle platforms for neuro-regenerative therapies. The lack of biologically relevant and ‘neuromimetic’ models for nanomaterials testing (that can simulate the cellular complexity of neural tissue) currently represents a bottleneck. Further, propagation of individual cell types, in different neural cell-specific media (as commonly occurs in the nanotechnology field), can result in non-standardised corona formation around particles, confounding analyses of intercellular differences between neural cells in nanoparticle uptake. To address these challenges, we have developed a facile multicellular model that broadly simulates the ratios of neurons, astrocytes and oligodendrocytes found in vivo. All cell types in the model are derived from a single neural stem cell source, and propagated in the same medium overcoming the issue of variant corona formation. Using a fluorescent transfection-grade magnetic particle (MP), we demonstrate dramatic differences in particle uptake and resultant gene transfer between neural cell subtypes, with astrocytes being the dominant population in terms of particle uptake and transfection. We demonstrate the compatibility of the model with a high resolution scanning electron microscopy technique, allowing for membrane features of MP stimulated cells to be examined. Using this approach, astrocytes displayed high membrane activity in line with extensive particle uptake/transfection, relative to neurons and oligodendrocytes. We consider that the stem cell based model described here can provide a simple and versatile tool to evaluate interactions of neural cells with nanoparticle systems developed for neurological applications. Models of greater complexity can be evolved from this basic system, to further enhance its neuromimetic capacity.