Modeling Intestinal Epithelial Response to Interferon-γ in Induced Pluripotent Stem Cell-Derived Human Intestinal Organoids

Human intestinal organoids (HIOs) are increasingly being used to model intestinal responses to various stimuli, yet few studies have confirmed the fidelity of this modeling system. Given that the interferon-gamma (IFN-gamma) response has been well characterized in various other cell types, our goal was to characterize the response to IFN-gamma in HIOs derived from induced pluripotent stem cells (iPSCs). To achieve this, iPSCs were directed to form HIOs and subsequently treated with IFN-gamma. Our results demonstrate that IFN-gamma phosphorylates STAT1 but has little effect on the expression or localization of tight and adherens junction proteins in HIOs. However, transcriptomic profiling by microarray revealed numerous upregulated genes such as IDO1, GBP1, CXCL9, CXCL10 and CXCL11, which have previously been shown to be upregulated in other cell types in response to IFN-gamma. Notably, Response to Interferon Gamma was determined to be one of the most significantly upregulated gene sets in IFN-gamma-treated HIOs using gene set enrichment analysis. Interestingly, similar genes and pathways were upregulated in publicly available datasets contrasting the gene expression of in vivo biopsy tissue from patients with IBD against healthy controls. These data confirm that the iPSC-derived HIO modeling system represents an appropriate platform to evaluate the effects of various stimuli and specific environmental factors responsible for the alterations in the intestinal epithelium seen in various gastrointestinal conditions such as inflammatory bowel disease.

Automated summary

This study confirmed the fidelity of using iPSC-derived HIO modeling system to evaluate intestinal epithelium alterations in response to IFN-gamma, showing upregulation of several genes previously associated with IFN-gamma response in other cell types. The results also indicated that similar gene expression changes and pathways were observed in datasets comparing IBD patients with healthy controls, suggesting the potential of this model in studying gastrointestinal conditions.