Cell type-specific decomposition of gingival tissue transcriptomes

Fatemeh Momen-Heravi, Richard Friedman, Sultan Albeshri, Ashley Sawle, Moritz Kebschull, Alexander Kuhn, Panos N. Papapanou

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Abstract

Genome-wide transcriptomic analyses in whole tissues reflect the aggregate gene expression in heterogeneous cell populations comprising resident and migratory cells, and are unable to identify cell type-specific information. We used a computational method (Population-Specific Expression Analysis; PSEA) to decompose gene expression in gingival tissues into cell typespecific signatures for eight cell types (epithelial cells, fibroblasts, endothelial cells, neutrophils, monocytes/macrophages, plasma cells, T cells and B cells). We used a gene expression dataset generated using microarrays from 120 persons (310 tissue samples; 241 periodontitis-affected and 69 healthy). Decomposition of the whole tissue transcriptomes identified differentially expressed genes in each of the cell types, which mapped to biologically relevant pathways including dysregulation of Th17 cell differentiation, AGE-RAGE signaling, and epithelial mesenchymal transition in epithelial cells. We validated selected PSEA-predicted, differentially expressed genes in purified gingival epithelial cells and B cells from an unrelated cohort (n=15 persons), each of whom contributed with one periodontitis-affected and one healthy gingival tissue sample. Differential expression of these genes by qRT-PCR corroborated the PSEA predictions and pointed to dysregulation of biologically important pathways in periodontitis. Collectively, our results demonstrate the robustness of the PSEA in the decomposition of gingival tissue transcriptomes, and its ability to identify differentially regulated transcripts in particular cellular constituents. These genes may serve as candidates for further investigation with respect to their roles in the pathogenesis of periodontitis.
Original languageEnglish
Pages (from-to)549-556
JournalJournal of Dental Research
Volume100
Issue number5
Early online date8 Jan 2021
DOIs
Publication statusE-pub ahead of print - 8 Jan 2021

Keywords

  • cell biology
  • dental informatics/bioinformatics
  • epithelia
  • gene expression
  • immunity
  • periodontal disease(s)/periodontitis

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