Micromachines (Jul 2020)

Three-Dimensional Regeneration of Patient-Derived Intestinal Organoid Epithelium in a Physiodynamic Mucosal Interface-on-a-Chip

  • Yong Cheol Shin,
  • Woojung Shin,
  • Domin Koh,
  • Alexander Wu,
  • Yoko M. Ambrosini,
  • Soyoun Min,
  • S. Gail Eckhardt,
  • R. Y. Declan Fleming,
  • Seung Kim,
  • Sowon Park,
  • Hong Koh,
  • Tae Kyung Yoo,
  • Hyun Jung Kim

DOI
https://doi.org/10.3390/mi11070663
Journal volume & issue
Vol. 11, no. 7
p. 663

Abstract

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The regeneration of the mucosal interface of the human intestine is critical in the host–gut microbiome crosstalk associated with gastrointestinal diseases. The biopsy-derived intestinal organoids provide genetic information of patients with physiological cytodifferentiation. However, the enclosed lumen and static culture condition substantially limit the utility of patient-derived organoids for microbiome-associated disease modeling. Here, we report a patient-specific three-dimensional (3D) physiodynamic mucosal interface-on-a-chip (PMI Chip) that provides a microphysiological intestinal milieu under defined biomechanics. The real-time imaging and computational simulation of the PMI Chip verified the recapitulation of non-linear luminal and microvascular flow that simulates the hydrodynamics in a living human gut. The multiaxial deformations in a convoluted microchannel not only induced dynamic cell strains but also enhanced particle mixing in the lumen microchannel. Under this physiodynamic condition, an organoid-derived epithelium obtained from the patients diagnosed with Crohn’s disease, ulcerative colitis, or colorectal cancer independently formed 3D epithelial layers with disease-specific differentiations. Moreover, co-culture with the human fecal microbiome in an anoxic–oxic interface resulted in the formation of stochastic microcolonies without a loss of epithelial barrier function. We envision that the patient-specific PMI Chip that conveys genetic, epigenetic, and environmental factors of individual patients will potentially demonstrate the pathophysiological dynamics and complex host–microbiome crosstalk to target a patient-specific disease modeling.

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