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Functional Transcriptomics in Diverse Intestinal Epithelial Cell Types Reveals Robust MicroRNA Sensitivity in Intestinal Stem Cells to Microbial Status.

Bailey C E PeckAmanda T MahWendy A PitmanShengli DingP Kay LundPraveen Sethupathy
Published in: The Journal of biological chemistry (2017)
Gut microbiota play an important role in regulating the development of the host immune system, metabolic rate, and at times, disease pathogenesis. The factors and mechanisms that mediate interactions between microbiota and the intestinal epithelium are not fully understood. We provide novel evidence that microbiota may control intestinal epithelial stem cell (IESC) proliferation in part through microRNAs (miRNAs). We demonstrate that miRNA profiles differ dramatically across functionally distinct cell types of the mouse jejunal intestinal epithelium and that miRNAs respond to microbiota in a highly cell type-specific manner. Importantly, we also show that miRNAs in IESCs are more prominently regulated by microbiota compared with miRNAs in any other intestinal epithelial cell subtype. We identify miR-375 as one miRNA that is significantly suppressed by the presence of microbiota in IESCs. Using a novel method to knockdown gene and miRNA expression ex vivo enteroids, we demonstrate that we can knock down gene expression in Lgr5+ IESCs. Furthermore, when we knock down miR-375 in IESCs, we observe significantly increased proliferative capacity. Understanding the mechanisms by which microbiota regulate miRNA expression in IESCs and other intestinal epithelial cell subtypes will elucidate a critical molecular network that controls intestinal homeostasis and, given the heightened interest in miRNA-based therapies, may offer novel therapeutic strategies in the treatment of gastrointestinal diseases associated with altered IESC function.
Keyphrases
  • stem cells
  • gene expression
  • poor prognosis
  • cell proliferation
  • long non coding rna
  • mesenchymal stem cells
  • signaling pathway
  • transcription factor
  • copy number
  • genome wide
  • network analysis