BMC GenomicsMolecular BiologyPeer-reviewed journal article
miR-155 exerts posttranscriptional control of autoimmune regulator (Aire) and tissue-restricted antigen genes in medullary thymic epithelial cells
Pedro Paranhos TanakaiD, Ernna Hérida Domingues de Oliveira, Mayara Cristina Vieira-Machado, Max Jordan DuarteiD, Amanda Freire AssisiD, Karina Fittipaldi Bombonato‐PradoiD, Geraldo Aleixo Silva PassosiD
Abstract
BackgroundThe autoimmune regulator (Aire) gene is critical for the appropriate establishment of central immune tolerance. As one of the main controllers of promiscuous gene expression in the thymus, Aire promotes the expression of thousands of downstream tissue-restricted antigen (TRA) genes, cell adhesion genes and transcription factor genes in medullary thymic epithelial cells (mTECs). Despite the increasing knowledge about the role of Aire as an upstream transcriptional controller, little is known about the mechanisms by which this gene could be regulated. ResultsHere, we assessed the posttranscriptional control of Aire by miRNAs. The in silico miRNA-mRNA interaction analysis predicted thermodynamically stable hybridization between the 3' UTR of Aire mRNA and miR-155, which was confirmed to occur within the cellular milieu through a luciferase reporter assay. This finding enabled us to hypothesize that miR-155 might play a role as an intracellular posttranscriptional regulator of Aire mRNA. To test this hypothesis, we transfected a murine mTEC cell line with a miR-155 mimic in vitro, which reduced the mRNA and protein levels of Aire. Moreover, large-scale transcriptome analysis showed the modulation of 311 downstream mRNAs, which included 58 TRA mRNAs. Moreover, miR-155 mimic-transfected cells exhibited a decrease in their chemotaxis property compared with control thymocytes. ConclusionOverall, the results indicate that miR-155 may posttranscriptionally control Aire mRNA as well as a crucial process by which mTECs allow migration of thymocytes through chemotaxis.
- organism: mouse
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 6
- FWCI
- 0.48
- Field percentile
- top 47%
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