Microengineering 3D perfusion networks for human liver tissue models

Jun 30, 2022, 3:30 PM
Room: S3 B

Room: S3 B


Larsen, Niels B. (Technical University of Denmark)


Human liver tissue models are of great interest for toxicology analysis in drug development and as liver disease models. All solid tissues depend on sufficient oxygen supply for survival and on controllable oxygen tension for their proper function. Liver tissue models pose a particular challenge in oxygenation given the high oxygen consumption rate of hepatocytes and the well documented gradient in oxygen tension along the liver sinusoid. The oxygen gradient is thought to be key in establishing liver zonation that is required to mimic the in vivo compound metabolism. We have addressed this challenge of reproducing the vasculature function of liver tissue by microengineering massively parallel microfluidic 3D networks in materials open to oxygen- and nutrient-diffusion. The liver-like 3D tissue is cultured between the perfusion channels, thereby shielding the sensitive hepatocytes from shear stresses of the medium flow. In collaborations with cell biologists, the developed technology platform has been employed for the culture of primary human hepatocytes at in vivo-like cell densities for weeks with retained hepatic function as well as culture of human induced pluripotent stem cell-based liver-like cell tissues for months resulting in improved tissue maturation. Gradients in oxygen tensions naturally develop within the cultured tissue due to cellular oxygen consumption, and the cellular oxygen consumption rate depends on the changing local oxygen tension, which makes numerical modeling of the oxygen distribution within tissues highly uncertain without access to a ground truth for validation. We overcome this limitation by development of an optical non-contact method for mapping the actual oxygen concentration in 3D within tissues during culture. The method is based on initial co-seeding of tissue cells with oxygen sensing microbeads in the culture platforms and readout of the oxygen distribution using confocal phosphorescence lifetime microscopy (PLIM).


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