Three dimensional modeling of biologically relevant fluid shear stress in human renal tubule cells mimics in vivo transcriptional profiles

Sci Rep. 2021 Jul 7;11(1):14053. doi: 10.1038/s41598-021-93570-5.

Abstract

The kidney proximal tubule is the primary site for solute reabsorption, secretion and where kidney diseases can originate, including drug-induced toxicity. Two-dimensional cell culture systems of the human proximal tubule cells (hPTCs) are often used to study these processes. However, these systems fail to model the interplay between filtrate flow, fluid shear stress (FSS), and functionality essential for understanding renal diseases and drug toxicity. The impact of FSS exposure on gene expression and effects of FSS at differing rates on gene expression in hPTCs has not been thoroughly investigated. Here, we performed RNA-sequencing of human RPTEC/TERT1 cells in a microfluidic chip-based 3D model to determine transcriptomic changes. We measured transcriptional changes following treatment of cells in this device at three different fluidic shear stress. We observed that FSS changes the expression of PTC-specific genes and impacted genes previously associated with renal diseases in genome-wide association studies (GWAS). At a physiological FSS level, we observed cell morphology, enhanced polarization, presence of cilia, and transport functions using albumin reabsorption via endocytosis and efflux transport. Here, we present a dynamic view of hPTCs response to FSS with increasing fluidic shear stress conditions and provide insight into hPTCs cellular function under biologically relevant conditions.

MeSH terms

  • Biological Transport
  • Biomarkers
  • Computational Biology / methods
  • Endocytosis / genetics
  • Epithelial Cells / metabolism*
  • Gene Expression Profiling
  • Gene Expression Regulation
  • Humans
  • Kidney Tubules / cytology*
  • Kidney Tubules, Proximal / cytology
  • Models, Biological*
  • Shear Strength
  • Signal Transduction
  • Stress, Mechanical*
  • Transcriptome*

Substances

  • Biomarkers