Modeling SARS-CoV-2 infection in vitro with a human intestine-on-chip device (preprint)

ABSTRACT

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2) has given rise to a global pandemic. The gastrointestinal symptoms of some COVID-19 patients are underestimated. There is an urgent need to develop physiologically relevant model that can accurately reflect human response to viral infection. Here, we report the creation of a biomimetic human intestine infection model on a chip system that allows to recapitulate the intestinal injury and immune response induced by SARS-CoV-2, for the first time. The microengineered intestine-on-chip device contains human intestinal epithelium (co-cultured human intestinal epithelial Caco-2 cells and mucin secreting HT-29 cells) lined in upper channel and vascular endothelium (human umbilical vein endothelial cells, HUVECs) in a parallel lower channel under fluidic flow condition, sandwiched by a porous PDMS membrane coated with extracellular matrix (ECM). At day 3 post-infection of SARS-CoV-2, the intestine epithelium showed high susceptibility to viral infection and obvious morphological changes with destruction of intestinal villus, dispersed distribution of mucus secreting cells and reduced expression of tight junction (E-cadherin), indicating the destruction of mucous layer and the integrity of intestinal barrier caused by virus. Moreover, the endothelium exhibited abnormal cell morphology with disrupted expression of adherent junction protein (VE-cadherin). Transcriptional analysis revealed the abnormal RNA and protein metabolism, as well as activated immune responses in both epithelial and endothelial cells after viral infection (e.g., up-regulated cytokine genes, TNF signaling and NF-kappa B signaling-related genes). This bioengineered in vitro model system can mirror the human relevant pathophysiology and response to viral infection at the organ level, which is not possible in existing in vitro culture systems. It may provide a promising tool to accelerate our understanding of COVID-19 and devising novel therapies.