Hyaluronic acid based next generation bioink for 3D bioprinting of human stem cell derived corneal stromal model with innervation

Corneal transplantation remains gold standard for the treatment of severe cornea diseases, however, scarcity of donor cornea is a serious bottleneck. 3D bioprinting holds tremendous potential for cornea tissue engineering (TE). One of the key technological challenges is to design bioink compositions with ideal printability and cytocompatibility. Photo-crosslinking and ionic crosslinking are often used for the stabilization of 3D bioprinted structures, which can possess limitations on biological functionality of the printed cells. Here, we developed a hyaluronic acid-based dopamine containing bioink using hydrazone crosslinking chemistry for the 3D bioprinting of corneal equivalents. First, the shear thinning property, viscosity, and mechanical stability of the bioink were optimized before extrusion-based 3D bioprinting for the shape fidelity and self-healing property characterizations. Subsequently, human adipose stem cells (hASCs) and hASC-derived corneal stromal keratocytes were used for bioprinting corneal stroma structures and their cell viability, proliferation, microstructure and expression of key proteins (lumican, vimentin, connexin 43,α-smooth muscle actin) were evaluated. Moreover, 3D bioprinted stromal structures were implanted intoex vivoporcine cornea to explore tissue integration. Finally, human pluripotent stem cell derived neurons (hPSC-neurons), were 3D bioprinted to the periphery of the corneal structures to analyze innervation. The bioink showed excellent shear thinning property, viscosity, printability, shape fidelity and self-healing properties with high cytocompatibility. Cells in the printed structures displayed good tissue formation and 3D bioprinted cornea structures demonstrated excellentex vivointegration to host tissue as well asin vitroinnervation. The developed bioink and the printed cornea stromal equivalents hold great potential for cornea TE applications.Peer reviewe