Shaping Synthetic Multicellular and Complex Multimaterial Tissues via Embedded Extrusion-Volumetric Printing of Microgels

Davide Ribezzi, Marième Gueye, Sammy Florczak, Franziska Dusi, Dieuwke de Vos, Francesca Manente, Andreas Hierholzer, Martin Fussenegger, Massimiliano Caiazzo, Torsten Blunk, Jos Malda, Riccardo Levato

Published: 1 September 2023

In living tissues, cells express their functions following complex signals from their surrounding microenvironment. Capturing both hierarchical architectures at the micro- and macroscale, and anisotropic cell patterning remains a major challenge in bioprinting, and a bottleneck toward creating physiologically-relevant models. Addressing this limitation, a novel technique is introduced, termed Embedded Extrusion-Volumetric Printing (EmVP), converging extrusion-bioprinting and layer-less, ultra-fast volumetric bioprinting, allowing spatially pattern multiple inks/cell types. Light-responsive microgels are developed for the first time as bioresins (µResins) for light-based volumetric bioprinting, providing a microporous environment permissive for cell homing and self-organization. Tuning the mechanical and optical properties of gelatin-based microparticles enables their use as support bath for suspended extrusion printing, in which features containing high cell densities can be easily introduced. µResins can be sculpted within seconds with tomographic light projections into centimeter-scale, granular hydrogel-based, convoluted constructs. Interstitial microvoids enhanced differentiation of multiple stem/progenitor cells (vascular, mesenchymal, neural), otherwise not possible with conventional bulk hydrogels. As proof-of-concept, EmVP is applied to create complex synthetic biology-inspired intercellular communication models, where adipocyte differentiation is regulated by optogenetic-engineered pancreatic cells. Overall, EmVP offers new avenues for producing regenerative grafts with biological functionality, and for developing engineered living systems and (metabolic) disease models.

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