Deconstructing Organs: Single-Cell Analyses, Decellularized Organs, Organoids, and Organ-ona-Chip Models Drivers of transcriptional variance in human intestinal epithelial organoids

Abstract

Human intestinal epithelial organoids (enteroids and colonoids) are tissue cultures used for understanding the physiology of the human intestinal epithelium. Here, we explored the effect on the transcriptome of common variations in culture methods, including extracellular matrix substrate, format, tissue segment, differentiation status, and patient heterogeneity. RNA-sequencing datasets from 276 experiments performed on 37 human enteroid and colonoid lines from 29 patients were aggregated from several groups in the Texas Medical Center. DESeq2 and gene set enrichment analysis (GSEA) were used to identify differentially expressed genes and enriched pathways. PERMANOVA, Pearson’s correlation, and dendrogram analysis of the data originally indicated three tiers of influence of culture methods on transcriptomic variation: Substrate (collagen vs. Matrigel) and format (3-D, transwell, and monolayer) had the largest effect; segment of origin (duodenum, jejunum, ileum, colon) and differentiation status had a moderate effect; and patient heterogeneity and specific experimental manipulations (e.g., pathogen infection) had the smallest effect. GSEA identified hundreds of pathways that varied between culture methods, such as IL1 cytokine signaling enriched in transwell versus monolayer cultures and E2F target genes enriched in collagen versus Matrigel cultures. The transcriptional influence of the format was furthermore validated in a synchronized experiment performed with various format-substrate combinations. Surprisingly, large differences in organoid transcriptome were driven by variations in culture methods such as format, whereas experimental manipulations such as infection had modest effects. These results show that common variations in culture conditions can have large effects on intestinal organoids and should be accounted for when designing experiments and comparing results between laboratories. Our data constitute the largest RNA-seq dataset interrogating human intestinal epithelial organoids.