Single-cell RNA landscape of the osteoimmunology microenvironment in periodontitis

Abstract

Single-cell RNA sequencing (scRNA-seq) enables specific profiling of cell populations at single-cell resolution. The osteoimmunology microenvironment in the occurrence and development of periodontitis remains poorly understood at the single-cell level. In this study, we used single-cell transcriptomics to comprehensively reveal the complexities of the molecular components and differences with counterparts residing in periodontal tissues. Methods: We performed scRNA-seq to identify 51248 single cells from healthy controls (n=4), patients with severe chronic periodontitis (n=5), and patients with severe chronic periodontitis after initial periodontal therapy within 1 month (n=3). Uniform manifold approximation and projection (UMAP) were further conducted to explore the cellular composition of periodontal tissues. Pseudotime cell trajectory and RNA velocity analysis, combined with gene enrichment analysis were used to reveal the molecular pathways underlying cell fate decisions. CellPhoneDB were performed to identify ligand-receptor pairs among the major cell types in the osteoimmunology microenvironment of periodontal tissues. Results: A cell atlas of the osteoimmunology microenvironment in periodontal tissues was characterized and included ten major cell types, such as fibroblasts, monocytic cells, endothelial cells, and T and B cells. The enrichment of TNFRSF21 + fibroblasts with high expression of CXCL1, CXCL2, CXCL5, CXCL6, CXCL13 , and IL24 was detected in patients with periodontitis compared to healthy individuals. The fractions of CD55 + mesenchymal stem cells (MSCs), APOE + pre-osteoblasts (pre-OBs), and IBSP + osteoblasts decreased significantly in response to initial periodontal therapy. In addition, CXCL12 + MSC-like pericytes could convert their identity into a pre-OB state during inflammatory responses even after initial periodontal therapy confirmed by single-cell trajectory. Moreover, we portrayed the distinct subtypes of monocytic cells and abundant endothelial cells significantly involved in the immune response. The heterogeneity of T and B cells in periodontal tissues was characterized. Finally, we mapped osteoblast/osteoclast differentiation mediators to their source cell populations by identifying ligand-receptor pairs and highlighted the effects of Ephrin-Eph signaling on bone regeneration after initial periodontal therapy. Conclusions: Our analyses uncovered striking spatiotemporal dynamics in gene expression, population composition, and cell-cell interactions during periodontitis progression. These findings provide insights into the cellular and molecular underpinning of periodontal bone regeneration.

Dissecting B/Plasma Cells in Periodontitis at Single-Cell/Bulk Resolution

“…Following a systematic search of published studies and public databases (Gene Expression Omnibus [GEO; http://www.ncbi.nlm.nih.gov/] and ArrayExpress [http://www.ebi.ac.uk/arrayexpress]), 3 single-cell data sets (GSE152042, GSE164241, GSE171213) (Caetano et al 2021; Williams et al 2021; Chen et al 2022) (Appendix Table 1) were included in the current study. Data cleaning (Appendix Fig.…”

“…The major limitations of existing single-cell studies are inadequate tissue samples and cell numbers (Caetano et al 2021; Williams et al 2021; Chen et al 2022). Completing biopsy procedures as fast as possible (<30 min), immediately followed by tissue preparation within a limited time period (approximately 1 h), is crucial for obtaining relatively high-viability single-cell suspensions (Greenwell-Wild et al 2021).…”

“…Single-cell transcriptomic atlas studies on periodontitis, by numerous research centers (Caetano et al 2021; Qian et al 2021; Williams et al 2021; Agrafioti et al 2022; Chen et al 2022), identified cell subpopulations and analyzed the possible interactions between immune and nonimmune cells. Some studies reported immune cell subpopulations of myeloid lineage cells and NK/T cells (Qian et al 2021; Agrafioti et al 2022), but none of them further analyzed B/plasma cell subpopulations.…”

“…As part of humoral adaptive immunity, the B/plasma cell population significantly increases in periodontitis at the single-cell level (Caetano et al 2021; Williams et al 2021; Chen et al 2022). The ultimate aim of this study was developing and validating potential B/plasma cell–related gene signature-based diagnostic models for periodontitis.…”

Identification of Endoplasmic Reticulum Stress-Related Biomarkers of Periodontitis Based on Machine Learning: A Bioinformatics Analysis

“…To our knowledge, this was the first study to identify ERS-related biomarkers of periodontitis based on microarray datasets. Single-cell sequencing and RNA-seq data that do not rely on predesigned probes are now increasingly used because of their high sensitivity and ability to detect novel genes [ 33 , 34 ]. However, the samples of periodontitis using these two methods are now too few in the public platform to be analyzed on a large scale.…”