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Τρίτη 6 Νοεμβρίου 2018

Reconstructing the Human Renal Vascular–Tubular Unit In Vitro

Advanced Healthcare Materials Reconstructing the Human Renal Vascular–Tubular Unit In Vitro

Reliable preclinical models of kidney function are needed for pharmaceutical screening and disease modeling. Herein, a vascular network and tubular pattern are created in perivascular cell containing collagen, opposed across a thin collagen membrane, and lined with kidney endothelial and epithelial cells. This human renal vascular–tubular unit recapitulates basic renal structure and function, showing promise as a next‐generation kidney‐on‐a‐chip platform.


Abstract

Engineered human kidney‐on‐a‐chip platforms show tremendous promise for disease modeling and drug screening. Outstanding challenges exist, however, in reconstructing the complex architecture, cellular make‐up, and matrix composition necessary for the proper modeling of kidney function. Herein, the first fully tunable human kidney‐on‐a‐chip platform is reported that allows the reconstruction of the native architecture of the renal endothelial–epithelial exchange interface using entirely cell‐remodelable matrix and patient‐derived kidney cells. This platform consists of a double‐layer human renal vascular–tubular unit (hRVTU) enabled by a thin collagen membrane that replicates the kidney exchange interface. It is shown that endothelial and epithelial cells lining their respective lumens remodel the membrane in culture into a ≈1 µm thick exchange interface composed of native basement membrane proteins. This interface displays sufficient mechanical integrity for media flow and blood perfusion. As a proof of principle, it is demonstrated that the hRVTU performs kidney‐specific functions including reabsorption of albumin and glucose from the epithelial channel. By incorporating multiple cell populations from single donors, it is demonstrated that the hRVTU may have utility for future precision medicine applications. The success of the system provides new opportunities for the next generation of organ‐on‐a‐chip models.



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