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Single-cell Transcriptomic Atlas of Gingival Mucosa in Type 2 Diabetes

ABSTRACT: The oral gingival barrier is a constantly stimulated and dynamic environment where homeostasis is often disrupted, resulting in inflammatory periodontal diseases. Type 2 diabetes (T2D), a risk factor for periodontitis, has been reported to be associated with barrier dysfunction, but the effect and underlying mechanism are inconclusive. Herein, we performed single-cell RNA sequencing (scRNA-seq) of gingiva from leptin receptor-deficient (db/db) mice to understand the heterogeneity of gingival barrier in the context of T2D. Periodontal health of control mice is characterized by populations of Krt14+-expressing epithelial cells and Col1a1+-fibroblasts mediating immune homeostasis primarily through the enrichment of innate lymphoid cells. The db/db mice exhibit an impaired gingival barrier with spontaneous periodontal bone loss, and a decreased proportion of epithelial/stromal cells. We further observed stromal, particularly fibroblast immune hyperresponsiveness linked to recruitment of myeloid cell populations in gingiva from T2D mice. Analysis of ligand-receptor interaction pairs suggested inflammatory signaling between fibroblasts and myeloid cells, a main driver of diabetes-induced periodontal damage. Moreover, the “Immune-like” stromal cells contributed to gingival Th17/IL-17 hyperresponsiveness in T2D. Our work reveals transcriptional diversity of stromal cells and interaction with innate immune cells in T2D, and uncovers the “immune-like” fibroblast subsets participating in barrier homeostasis at the diabetic gingiva.

ORGANISM(S): Mus musculus

PROVIDER: GSE188217 | GEO | 2022/01/01

REPOSITORIES: GEO

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Project description:Periodontal regeneration study. Periodontitis is a common chronic inflammatory disease which may lead to tooth loss. The ultimate goal of periodontal therapy is complete regeneration of the tissues lost as a result of periodontitis. However, most regenerative clinical procedures are unpredictable, largely because there is a lack of understanding of how the various tissues comprising the periodontium (gingival epithelium, gingival connective tissue, periodontal ligament, aveolar bone and cementum) interact during the regenerative process. The aim of this study was to investigate the molecular mechanisms that are involved in periodontal regeneration. For this purpose, paired sets of gingival, ligament and regenerating cells were isolated from patients that have been treated for periodontitis via a regenerative surgical procedure. A microarray analysis using the Hu133A Affymetrix arrays was used to identify the genes and pathways that were characteristic of the three different tissues. We have identified over 500 transcripts in global comparison and intrapatient comparisons that were differentially expressed between ligament and gingival samples, and approximately 30 transcripts that characterized the regenerating cell population. By using a functional classification based on Gene Ontology we were able to group the transcripts into 12 groups. Proteases/Protease inhibitors were differentially expressed between the ligament and gingiva highlighting high ECM remodelling activity by gingival cells. On the other hand, ligament cells were shown to have increased protein synthesis by increasing their nucleolar and ribosomal gene complement. We were able to identify 57 various DNA binding proteins, among them were some well characterised transcription factors, transcriptional regulators, including DNA polymerases and transcriptional co-activators. Furthermore, we have also identified changes in expression of their targets in the two tissues. This is the first study to characterise the gene expression profile of periodontal regenerating cells and allowed us to gain valuable insights into the cellular and molecular mechanisms that occur during the regenerative process. We have identified signalling pathways which are consistent with clinical observations of the regenerative properties of gingival and periodontal ligament cells. These pathways provide candidate targets that can be manipulated in order to achieve a superior regenerative clinical outcome.

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Single-cell Transcriptomic Atlas of Gingival Mucosa in Type 2 Diabetes

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