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Intestinal Stem and Progenitor Cells Exhibit Distinct Adaptive Responses to Inflammatory Stress in IBD

GSE310845 Homo sapiens Expression profiling by high throughput sequencing 20 samples 2025/12/01 GPL34284
Summary
Intestinal epithelial stem cells (SCs) and their transit-amplifying (TA) progeny are critical for mucosal repair and regeneration. However, their behaviour under chronic inflammatory conditions, such as those observed in Inflammatory Bowel Disease (IBD), remains incompletely understood. We investigated the impact of chronic inflammation on intestinal stem/progenitor cells by integrating bulk RNA sequencing from the largest IBD biopsy cohort to date with single-cell transcriptomic analysis and experimental assays using patient-derived intestinal organoids. Active inflammation was associated with a reduction in canonical LGR5⁺ intestinal stem cells and a concurrent expansion of OLFM4⁺ populations, consistent with an inflammation-induced epithelial repair program. Notably, SC/TA cells from both inflamed and non-inflamed IBD tissues exhibited persistent transcriptional changes that were distinct from those in healthy controls. Single-cell analysis identified transcriptionally heterogeneous SC/TA subpopulations, including a previously uncharacterized inflammation-associated cluster enriched in immune signalling pathways. Pseudotime trajectory analysis demonstrated a shift in differentiation toward deep crypt secretory (Paneth-like) cell lineages under inflammatory conditions. Chronic intestinal inflammation reshapes the epithelial stem/progenitor cell compartment, promoting altered differentiation and the emergence of immune-responsive epithelial states. These findings highlight the plasticity of the human intestinal epithelium in IBD and point to new avenues for therapeutic strategies aimed at maintaining epithelial integrity during chronic inflammation.
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NCBI GEO page ↗ Paper (PMID 41422054) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
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