Foundry120 atlas

Single-cell RNA sequencing to identify 51248 single cells from periodontal tissues of healthy humans and periodontitis patients with or without treatment

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Dataset overview

Participants 12
Samples 12
Reuse readiness 6.7/10 evidence-backed score

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. <b>Methods:</b> 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. <b>Results:</b> 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 <i>TNFRSF21<sup>+</sup></i> fibroblasts with high expression of <i>CXCL1, CXCL2, CXCL5, CXCL6, CXCL13</i>, and <i>IL24</i> was detected in patients with periodontitis compared to healthy individuals. The fractions of <i>CD55<sup>+</sup></i> mesenchymal stem cells (MSCs), <i>APOE<sup>+</sup></i> pre-osteoblasts (pre-OBs), and <i>IBSP<sup>+</sup></i> osteoblasts decreased significantly in response to initial periodontal therapy. In addition, <i>CXCL12</i><sup>+</sup> 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. <b>Conclusions:</b> 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.

Study facts

Organism
Homo sapiens
Platform
BD Rhapsody
Age group
adult
Disease groups
Anatomical sites

Data availability

  • Raw counts

File types TSVTXT

Files and samples

Strengths & limitations for reuse

Strengths

  • Raw reads are advertised
  • Raw counts are advertised
  • Participant counts are documented

Limitations

  • Not documented: processed matrices are advertised
  • Not documented: cell metadata are advertised
Extraction evidence & provenance

Each extracted field is shown with the source excerpt and location used to resolve it.

Assay

FieldValueEvidence
assay.assay_type single-cell mRNA sequencing
Single-cell mRNA profiles

Section series_overall_design, offset —

assay.library_chemistry BD Rhapsody
using BD Rhapsody system

Section series_overall_design, offset —

assay.platform BD Rhapsody
using BD Rhapsody system

Section series, offset —

assay.reference_genome GRCh38
Genome_build: GRCh38

Section samples, offset —

assay.sequencing_type scrna_seq
generated by Single-cell RNA sequencing, using BD Rhapsody system

Section series, offset —

Cohort

FieldValueEvidence
cohort.age_group adult from source
GEO age characteristics: 55; 36; 42; 48; 34; 56; 40; 42; 38; 46; 35; 55

Section GEO family SOFT, offset —

cohort.disease_activity_metadata_available True
Severe Chronic Periodontitis (PD)

Section samples, offset —

cohort.non_ibd_controls 4
healthy controls (n=4)

Section abstractText, offset —

cohort.total_participants 12
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)

Section abstractText, offset —

cohort.treatment_exposure_documented True
Severe Chronic Periodontitis after Treatment (PDT)

Section samples, offset —

Data_Assets

FieldValueEvidence
data_assets.open_access True
Public on Dec 08 2021

Section series, offset —

data_assets.raw_counts True
Umi-tools was utilized to calculate the raw counts

Section samples.data_processing, offset —

data_assets.raw_reads True
GSE171213_RAW.tar

Section filelist.txt, offset —

Processing

FieldValueEvidence
processing.cell_type_annotation_method marker gene-based cluster annotation
based on the marker gene achieved some cluster was combined

Section samples.data_processing, offset —

processing.normalization_method Seurat
We applied the Seurat [https://satijalab.org/seurat/] package for cell normalization

Section samples, offset —

processing.quality_control_reported True
We applied the Seurat package for cell normalization and cell filtering

Section samples, offset —

Specimens

FieldValueEvidence
specimens.inflamed_status_available True
Healthy controls (HC)

Section samples, offset —

specimens.number_of_cells 51248
Single-cell RNA sequencing to identify 51248 single cells from periodontal tissues of healthy humans and periodontitis patients with or without treatment

Section series, offset —

specimens.number_of_samples 12
"n_samples": 12

Section geo_record_summary, offset —