Cell Type–Specific Decomposition of Gingival Tissue Transcriptomes. (May 2021)

• Record Type: Journal Article
• Authors: Momen-Heravi, F.; Friedman, R.A.; Albeshri, S.; Sawle, A.; Kebschull, M.; Kuhn, A.; Papapanou, P.N.
• Is Part Of: Journal of dental research. Volume 100:Number 5(2021)
• Page Start: 549
• Page End: 556
• Publication Date: 2021-05
• Subjects: gene expression -- periodontitis -- validation -- reverse transcription polymerase chain reaction -- epithelial cells -- B cells; Dentistry -- Periodicals; Dentistry -- Social aspects -- Periodicals; Dentistry -- Periodicals; Research -- Periodicals; 617.6005
• DOI: 10.1177/0022034520979614
• Languages: English
• ISSNs: 0022-0345

Abstract

Genome-wide transcriptomic analyses in whole tissues reflect the aggregate gene expression in heterogeneous cell populations comprising resident and migratory cells, and they 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 type–specific signatures for 8 cell types (epithelial cells, fibroblasts, endothelial cells, neutrophils, monocytes/macrophages, plasma cells, T cells, and B cells). We used a gene expression data set 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 1 periodontitis-affected and 1 healthy gingival tissue sample. Differential expression of these genes by quantitative reverse transcription polymerase chain reaction 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.