Bio‐assembling Macro‐Scale, Lumenized Airway Tubes of Defined Shape via Multi‐Organoid Patterning and Fusion

Ye Liu(University of Cambridge), Catherine Dabrowska(Wellcome/MRC Cambridge Stem Cell Institute), Antranik Mavousian(Wellcome/MRC Cambridge Stem Cell Institute), Bernhard Strauss(University of Cambridge), Fanlong Meng(Chinese Academy of Sciences), Corrado Mazzaglia(University of Cambridge), Karim Ouaras(University of Cambridge), Callum Macintosh(University of Cambridge), Eugene M. Terentjev(University of Cambridge), Joo‐Hyeon Lee(Wellcome/MRC Cambridge Stem Cell Institute), Yan Yan Shery Huang(University of Cambridge)
Advanced Science
February 8, 2021
Cited by 36Open Access
Full Text

Abstract

Epithelial, stem-cell derived organoids are ideal building blocks for tissue engineering, however, scalable and shape-controlled bio-assembly of epithelial organoids into larger and anatomical structures is yet to be achieved. Here, a robust organoid engineering approach, Multi-Organoid Patterning and Fusion (MOrPF), is presented to assemble individual airway organoids of different sizes into upscaled, scaffold-free airway tubes with predefined shapes. Multi-Organoid Aggregates (MOAs) undergo accelerated fusion in a matrix-depleted, free-floating environment, possess a continuous lumen, and maintain prescribed shapes without an exogenous scaffold interface. MOAs in the floating culture exhibit a well-defined three-stage process of inter-organoid surface integration, luminal material clearance, and lumina connection. The observed shape stability of patterned MOAs is confirmed by theoretical modelling based on organoid morphology and the physical forces involved in organoid fusion. Immunofluorescent characterization shows that fused MOA tubes possess an unstratified epithelium consisting mainly of tracheal basal stem cells. By generating large, shape-controllable organ tubes, MOrPF enables upscaled organoid engineering towards integrated organoid devices and structurally complex organ tubes.


Related Papers

No related papers found

Powered by citation graph analysis