bioRxivMolecular BiologyPreprint
Variabilities and similarities of adult stem cells derived intestinal organoids originating from different intestinal segments in pig
Soumya Kanti KariD, MARINUS F. W. TE PASiD, Roxann Rikkers, Ole MadseniD, Nico Taverne, E.D. ElleniD, Jerry Mark WellsiD, Dirkjan SchokkeriD
Abstract
1.Organoids are in vitro model systems generated from tissues. Organoids express specific physiological functions associated with their original tissue location and they express tissue-segment-specific genes. The aim of this study was to culture pig organoids from different areas of intestinal segments: duodenum, ileum (with or without Peyers Patches (PP)), and colon, to investigate the resemblance with the in vivo tissues and variability of multiple adjacent sampling sites based on histology and transcriptome profiles. The transcriptome profiles of the in vivo tissues and the derived organoids showed high resemblance for all intestinal segments. For the transcriptomic cluster analysis it was shown that it is important to use tissue important genes to shown the resemble between tissue and their derived organoids. The transcriptome profiles clearly separated the intestinal segments, and samples of the same segment from adjacent tissue locations showed high transcriptome profile similarity. Ileum samples with and without PP were also separated. Pathway analysis of differentially expressed genes from PP compared with non-PP suggested the importance of several aspects of cell cycle progression regulation, including DNA metabolism, chromatin organization, regulation of mitotic stage progression, and regulation of inflammation. Based primarily on the transcriptomics results, we conclude that organoids reflect the sampled intestinal segment and that organoids derived from adjacent sampling sites in an intestinal tissue segment showed low variability. The results from the ileum indicate that organoids have potential to study intestinal innate immune processes.
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 1
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