An immunocompetent human kidney on-a-chip model to study renal inflammation and immune-mediated injury

Abstract Kidney damage and dysfunction is an emerging health issue worldwide resulting in high morbidity and mortality rates. Numerous renal diseases are recognized to be driven by the immune system. Despite this recognition, the development of targeted therapies has been challenging as knowledge of the underlying mechanism and complex interactions remains insufficient. Recent advancements in the field offer promising avenues for exploring the interplay between renal cells and immune cells and their role in the development of renal inflammation and diseases. This study describes the establishment of a human immunocompetent 3D in vitro co-culture model of the proximal tubule (PT) in a novel high-throughput microfluidic platform that can be used to study renal functionality and inflammatory processes. The model incorporated renal PT epithelial cell in the top compartment and human umbilical vein endothelial cells in the bottom compartment cultured under flow and in direct contact with a collagen-I extracellular matrix (ECM) gel resulting in the formation of polarized tubular structures. As an immune component, human primary monocytes of different donors were added to the lumen of the endothelium. Renal inflammation was successfully induced using complement activated serum (CAS) as evident by epithelial morphological changes, increased expression of adhesion molecules, release of pro-inflammatory cytokines, and reduced epithelial viability. Realtime migratory behavior of monocytes showed increased extravasation and migration towards the ECM and Renal compartment upon exposure to CAS with donor-to-donor differences observed. Finally, immune modulatory compounds showed efficacious inhibition of monocyte migration under inflammatory conditions in the microfluidic co-culture model. A successful co-culture model was established and can be applied to study renal functionality in health and disease but also for drug screening due to the compatibility of the platform with automation and relatively high throughput. Overall, the described PT model has high potential to fill the gap that currently exists to study renal inflammation preclinically.