Human Fetal-Derived Enterospheres Provide Insights on Intestinal Development and a Novel Model to Study Necrotizing Enterocolitis (NEC)

Background & Aims Untreated necrotizing enterocolitis (NEC) can lead to massive inflammation resulting in intestinal necrosis with a high mortality rate in preterm infants. Limited access to human samples and relevant experimental models have hampered progress in NEC pathogenesis. Earlier evidence has suggested that bacterial colonization of an immature and developing intestine can lead to an abnormally high inflammatory response to bacterial bioproducts. The aim of our study was to use human fetal organoids to gain insights into NEC pathogenesis. Methods: RNA sequencing analysis was performed to compare patterns of gene expression in human fetal-derived enterospheres (FEnS) and adult-derived enterospheres (AEnS). Differentially expressed genes were analyzed using computational techniques for dimensional reduction, clustering, and gene set enrichment. Unsupervised cluster analysis, Gene Ontology, and gene pathway analysis were used to predict differences between gene expression of samples. Cell monolayers derived from FEnS and AEnS were evaluated for epithelium function and responsiveness to lipopolysaccharide and commensal bacteria. Results: Based on gene expression patterns, FEnS clustered according to their developmental age in 2 distinct groups: early and late FEnS, with the latter more closely resembling AEnS. Genes involved in maturation, gut barrier function, and innate immunity were responsible for these differences. FEnS-derived monolayers exposed to either lipopolysaccharide or commensal Escherichia coli showed that late FEnS activated gene expression of key inflammatory cytokines, whereas early FEnS monolayers did not, owing to decreased expression of nuclear factor-κB–associated machinery. Conclusions: Our results provide insights into processes underlying human intestinal development and support the use of FEnS as a relevant human preclinical model for NEC. Accession number of repository for expression data: GSE101531