Scientific Reports (Jun 2021)

A high-throughput microfluidic bilayer co-culture platform to study endothelial-pericyte interactions

  • Miles T. Rogers,
  • Ashley L. Gard,
  • Robert Gaibler,
  • Thomas J. Mulhern,
  • Rivka Strelnikov,
  • Hesham Azizgolshani,
  • Brian P. Cain,
  • Brett C. Isenberg,
  • Nerses J. Haroutunian,
  • Nicole E. Raustad,
  • Philip M. Keegan,
  • Matthew P. Lech,
  • Lindsay Tomlinson,
  • Jeffrey T. Borenstein,
  • Joseph L. Charest,
  • Corin Williams

DOI
https://doi.org/10.1038/s41598-021-90833-z
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 14

Abstract

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Abstract Microphysiological organ-on-chip models offer the potential to improve the prediction of drug safety and efficacy through recapitulation of human physiological responses. The importance of including multiple cell types within tissue models has been well documented. However, the study of cell interactions in vitro can be limited by complexity of the tissue model and throughput of current culture systems. Here, we describe the development of a co-culture microvascular model and relevant assays in a high-throughput thermoplastic organ-on-chip platform, PREDICT96. The system consists of 96 arrayed bilayer microfluidic devices containing retinal microvascular endothelial cells and pericytes cultured on opposing sides of a microporous membrane. Compatibility of the PREDICT96 platform with a variety of quantifiable and scalable assays, including macromolecular permeability, image-based screening, Luminex, and qPCR, is demonstrated. In addition, the bilayer design of the devices allows for channel- or cell type-specific readouts, such as cytokine profiles and gene expression. The microvascular model was responsive to perturbations including barrier disruption, inflammatory stimulation, and fluid shear stress, and our results corroborated the improved robustness of co-culture over endothelial mono-cultures. We anticipate the PREDICT96 platform and adapted assays will be suitable for other complex tissues, including applications to disease models and drug discovery.