Probabilistic cell seeding and non-autofluorescent 3D-printed structures as scalable approach for multi-level co-culture modeling.

Abstract

To model complex biological tissue in vitro, a specific layout for the position and numbers of each cell type is necessary. Establishing such a layout requires manual cell placement in three dimensions (3D) with micrometric precision, which is complicated and time-consuming. Moreover, 3D printed materials used in compartmentalized microfluidic models are opaque or autofluorescent, hindering parallel optical readout and forcing serial characterization methods, such as patch-clamp probing. To address these limitations, we introduce a multi-level co-culture model realized using a parallel cell seeding strategy of human neurons and astrocytes on 3D structures printed with a commercially available non-autofluorescent resin at micrometer resolution. Using a two-step strategy based on probabilistic cell seeding, we demonstrate a human neuronal monoculture that forms networks on the 3D printed structure and can establish cell-projection contacts with an astrocytic-neuronal co-culture seeded on the glass substrate. The transparent and non-autofluorescent printed platform allows fluorescence-based immunocytochemistry and calcium imaging. This approach provides facile multi-level compartmentalization of different cell types and routes for pre-designed cell projection contacts, instrumental in studying complex tissue, such as the human brain.