Poster - #UCLA-62 - Keywords: bioprinting precision medicine 3D printing automation organoid

Bioprinting of 3D Organoid Models Recapitulating Complex Tissue Architectures in Multi-well Plates

Luda Lin1, 2, Peyton Tebon1, 3, 4, Bowen Wang3, Alice Soragni1, 2, 4, 5, 6 ¹Department of Orthopaedic Surgery, David Geffen School of Medicine; ²Molecylar Biology Institute; 3Department of Bioengineering; 4Jonsson Comprehensive Cancer Center; 5Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research; 6California NanoSystems Institute. University of California Los Angeles, CA
Department of Orthopaedic Surgery, David Geffen School of Medicine; Molecylar Biology Institute; Department of Bioengineering; Jonsson Comprehensive Cancer Center; Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research; California NanoSystems Institute. University of California Los Angeles, CA

ABSTRACT:
Organoids, self-organized multicellular bodies in 3D extracellular matrices (ECMs), are gaining traction in basic biological research, drug discovery and precision medicine. Our lab has developed multi-well plate-based organoid models, “mini-“ or “maxi-rings”, with organoids derived from single cells embedded in gels deposited around the perimeter of tissue-culture wells, that simplify culture and facilitate the use of automated liquid handling platforms. However, manually seeding organoids, especially in 96-well plates, can be tedious. Therefore, automation of the organoid seeding process via bioprinting becomes an attractive option to minimize human labor and enhance consistency by eliminating variations resulting from operator skills and experience. Automated organoid seeding using bioprinting also opens possibilities for creating reproducible models of complex tissue architectures found in the body. In addition, our previous work has demonstrated how bioprinted organoids are not different from manually seeded ones in morphology, viability and transcriptome. Here, we present a script that simplifies the creation of organoid models by allowing users to develop complex multi-well arrays by defining printing properties in spreadsheet format. In the spreadsheet, the user can define the wells to be printed, the geometries in each well, and deposition parameters such as extrusion speed, pressure, and height. The script also supports printing by multiple printheads and printing of complicated patterns composed of different cellular and ECM components. Cell lines can be bioprinted in different ECMs in a double-ring model using our script. We also show how the activities of different cell lines in different ECMs can be shown in a double-ring model printed with this script: more invasive cell lines tend to migrate across basement-membrane-extract (BME) gels to type I collagen gels, breaking away from organoids during the process, and some cell lines can form special structures in the interface between two ECMs. Overall, generalizable protocols can facilitate the automation of organoid seeding via bioprinting and help to integrate this approach without previous coding experience.