Animal experimentThe delayed replantation model of Sprague-Dawley (SD) rats was established

Six-week-old SD rats were obtained from the Laboratory Animal Center of Chongqing Medical University. The rats were housed in a specific pathogen-free environment with a 12 h light/dark cycle and had ad libitum access to food and water. All animal experiments in this study were approved by the Research Ethics Committee of the Stomatological Hospital of Chongqing Medical University (CQHS-REC-2023110).

The SD rats were anesthetized using 1% pentobarbital sodium at a dosage of 30 mg/kg. The experiment was conducted with two groups: the tooth extraction and replantation with EMD treatment group and the tooth extraction and replantation without treatment group, each comprising 10 rats. Tooth extraction surgery was performed on the left side of each rat, while the right side served as a normal control.

The maxillary first molar was extracted using the tip of a periodontal probe, and the extracted molar was stored in normal saline for 25 min. The molar was then treated with Emdogain® (EMD, Straumann®, Switzerland) and normal saline for 5 min before replantation. After gently rinsing the alveolar socket with normal saline, the treated molar was replanted in situ. The buccal sides of the first and second molars were fixed with resin. Samples were collected at 4 weeks and 8 weeks, respectively, and the rates of tooth loosening and loss were assessed during sampling.

Micro-CT analysis

Following euthanasia, the maxilla with teeth was extracted and fixed overnight in 4% paraformaldehyde (Sigma-Aldrich, USA). The samples were then scanned using a micro-CT (Scano Medical, Switzerland) at 50 kV and 80 μA. The resulting micro-CT data were reconstructed and analyzed. The region of interest was defined as the alveolar bone surrounding the root bifurcation of the maxillary first molar, and the bone volume fraction (BV/TV) in this area was quantified. Additionally, the height from the cementoenamel junction (CEJ) to the alveolar bone crest (ABC) was measured to evaluate the extent of alveolar bone loss32.

Histological stain analysis

The maxilla containing teeth was dissected after the rats were euthanized. It was then fixed in 4% paraformaldehyde overnight, rinsed with distilled water after fixing, decalcified in 10% EDTA for two months, and then thoroughly rinsed with tap water. The well-decalcified tissues were dehydrated with graded ethanol, embedded in paraffin wax, and sliced into 6 micron slices for H&E staining (Mengbio, China). The image was obtained by the VS200 full-mount scanning system (Olympus VS200, Japan), and the root was divided into 12 equal parts as observation points to calculate the root absorptivities. The ratio of periodontal membrane width between the experimental group and the normal group was used to evaluate the periodontal membrane repair.

Immunofluorescence staining

After fixed, decalcified and rinsed with running water using the same method, 6 µm slices were prepared by dewatering with graded ethanol, embedding paraffin, and then treated with 0.3% Triton X-100 (Sigma, USA) for 15 min. Then goat serum was closed at 37 °C for 30 min and exposed to primary antibody at 4 °C overnight. After washing with PBS for three times, coated with secondary antibody and incubated at 37 °C for 1 h. After washing with phosphate-buffered saline (PBS) for three times, the sections were sealed with an anti-quenching agent containing DAPI. Images were captured using a fluorescence microscope (Zeiss, Germany) and analyzed using the Image software. The antibodies used were anti-DMP1 (Abcam, USA), anti-CD31 (Abcam, USA) and anti-EMCN (Protein Tech, USA).

TRAP staining

Tissue acquisition, fixation, decalcification, embedding, and sectioning. Stain the tissue using the TRAP staining kit (Beyotime, China). Count cells using ImageJ analysis.

Cell cultureExtraction and culture of BMSCs

Bone marrow was extracted from the femur and tibia of 2-week-old SD rats under aseptic conditions. The marrow cavity was rinsed with PBS to obtain the bone marrow cell solution. Mononuclear cells were subsequently isolated from this solution using a density gradient centrifugation technique. The purified cells were then cultured in α-MEM supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin (P/S) in an incubator maintained at 37 °C with a 5% CO2 atmosphere. After 24 h, non-adherent cells were eliminated, the culture medium was replenished, and the medium was thereafter replaced every three days49.

CCK8 test

The cells were treated when the cell confluence reached 70%–80%, and the tests were carried out on the 1st, 3rd and 5th day after treatment. At each point in time, add 10 microliters of CCK8 solution to each well and stir gently. The cells were then incubated for two to four hours. The optical density (OD) of each hole at 450 nm wavelength was measured by microplate spectrophotometer, and the data were analyzed statistically.

Osteogenic induction

BMSCs were derived from 4-week-old SD rats. These cells were maintained in a temperature-controlled incubator set at 37 °C with a 5% CO2 environment, utilizing a growth medium that comprised 10% FBS and 1% P/S. The culture medium was replenished every three days, and the cells were passaged using 0.25% Trypsin-EDTA when they achieved 80%–90% confluence. Third-passage BMSCs were plated in a 6-well plate at a concentration of 5 000 cells per square centimeter. After 24 h, the culture medium was substituted with an osteogenic differentiation medium, which consisted of α-MEM, 10% FBS, 10 mmol/L β-Glycerophosphate, 50 μg/mL Ascorbic Acid, and 10 nmol/L Dexamethasone. In the experimental cohort, EMD was incorporated into the osteogenic differentiation medium, and this medium was replaced every three days over a period of 7 to 21 days.

ALP staining

On the 7th day of osteogenic induction, cells were removed and washed 3 times with PBS. Cells were fixed with 4% paraformaldehyde for 15 min. An alkaline phosphatase detection kit (Beyotime, China) was used to stain according to the instructions, and the ALP activity was observed.

Alizarin red staining

On the 21st day of osteogenic induction, cells were removed and washed 3 times with PBS. Cells were fixed with 4% paraformaldehyde for 15 min. Dye with 2% alizarin red solution (pH 4.2) for 20 min, remove the unbound dye and wash with PBS 3 times. The formation of mineralized nodules was observed under a microscope-Alizarin red after dissolution and staining with cetylpyridine chloride (Maclean, China). The absorbance of the solution at OD405 nm was measured by spectrophotometer, and the mineralized water level was quantitatively analyzed.

q-PCR detected the expression of osteogenic factors

On the seventh day of osteogenic induction, cells were harvested. RNA was extracted using a RNA extraction kit (Beyotime, China) and subsequently reverse-transcribed into cDNA with a reverse transcription kit (Takara, Japan). q-PCR was conducted with the SYBR Green Q-pcr kit (Takara, Japan). Specific primers for the target genes and the internal reference gene (GAPDH) were designed and synthesized. The reaction mix consisted of 10 μL SYBR Green Mix, 1 μL primer, 1 μL cDNA template, and 8 μL nuclease-free water, totaling 20 μL. The thermal cycling conditions were: 95 °C for 3 min for pre-denaturation, followed by 40 cycles of 95 °C for 10 s for denaturation, and 60 °C for 30 s for annealing. The 2^(-ΔΔCt) method was employed to analyze relative gene expression, and the expression levels of osteogenic genes (Runx2, OPN, OCN, BSP) were statistically evaluated50.

Sequencing analysisscRNA-seq using the 10X Genomics platform

The periodontal tissue of rats was obtained and treated with enzymes, isolated single cells, and the cell number and activity were detected to ensure a more than 80% cell survival rate. Using a microfluidic chip from 10X Genomics, individual cells were captured into tiny reaction chambers. A cell suspension was mixed with oil to form an oil-in-water droplet. Each drop contained a single cell and a small piece of barcoded reverse transcription reagent. Reverse transcription was performed in the droplet to convert mRNA into cDNA. Each cell’s cDNA was labeled with a unique barcode for subsequent analysis. The synthesized cDNA was amplified by PCR to obtain sufficient quantities for sequencing. High-throughput sequencing was performed using the Illumina sequencing platform to obtain scRNA-seq data. Sequencing data typically contained gene expression information for each bar code.

ScRNA-seq raw data processing

Raw sequencing data obtained from the 10X Genomics platform were processed with CellRanger (version 6.0.2) to produce gene expression matrices. CellRanger handled the demultiplexing process51, barcode processing, and alignment to the reference genome on a Linux platform.

ScRNA-seq sample demultiplexing

Mixed samples were demultiplexed using the souporcell algorithm (https://github.com/wheaton5/souporcell), executed within a Singularity container (version 4.1.3) on the Linux platform17. Souporcell separated different sample origins within the mixed scRNA-seq data. Subsequently, filtering was applied to include only single droplets and cells with unambiguous assignment, ensuring accurate attribution of cells to their respective samples.

Data processing and quality control

ScRNA-seq data were analyzed using Seurat (version 5.1.0) in R (version 4.4.1)52. Quality control involved filtering out cells with low RNA counts, elevated mitochondrial gene expression, and other outliers. Cells with fewer than 200 genes or those expressed in fewer than three cells were excluded. Additionally, cells exceeding 5% mitochondrial content were removed.

Normalization and scaling

The Seurat NormalizeData function was used to normalize the data, followed by scaling with ScaleData. Dimensionality reduction was achieved through Principal Component Analysis (PCA), with the top 25 components selected for further clustering and visualization.

Clustering and visualization

Clustering was performed using the Louvain algorithm via Seurat’s FindClusters function, and visualization was done with UMAP (RunUMAP). For specific subpopulations, t-SNE was also employed to explore additional data structure insights.

Gene set variation analysis (GSVA)

GSVA was performed using the GSVA package (version 1.52.3) with gene sets sourced from the Molecular Signatures Database (MsigDB). This analysis computed GSVA scores to evaluate pathway activity across different cell populations.

Scoring and visualization

The computed GSVA scores were further refined using the AUCell package (version 1.26.0) to assign activity levels to individual cells. UMAP was subsequently utilized for visualization.

Pseudotime analysis

Pseudotime trajectory analysis was performed with the monocle package (version 2.32.0). Cell differentiation paths were mapped, and the progression of individual cells along these paths was visualized using the ClusterGVis package (version 0.1.1).

Enrichment analysis

Functional enrichment analysis utilized the clusterProfiler package (version 4.12.0). GOBP pathway scores were computed with Seurat’s AddModuleScore function, followed by two-sided statistical tests. The enrichment outcomes were visualized through chord diagrams generated by the circlize package (version 0.4.16).

Weighted gene Co-expression network analysis (WGCNA)53

Co-expression networks were built using the WGCNA package (version 1.72-5) with a soft threshold power of 3. Modules were identified and their functional enrichment evaluated using the clusterProfiler package (version 4.12.0).

Immune infiltration analysis

Immune Profiling: Immune cell infiltration was analyzed using the CIBERSORTx tool (https://cibersortx.stanford.edu).54 with the LM22 immune dataset to estimate the relative abundance of immune cell types from scRNA-seq data.

Cell communication analysis

Cell-cell communication networks were inferred using the CellChat package, identifying significant ligand-receptor interactions between different cell populations.

Transcriptome sequencing of BMSCs

After 5 days of culture with EMD and blank control medium, BMSCs reached the logarithmic growth stage. The cells were cleaned with PBS, and total RNA was extracted using an RNA extraction kit (Trizol) to ensure the integrity and purity of RNA. The constructed libraries were sequenced using a high-throughput sequencing platform such as Illumina NovaSeq.

Bulk RNA sequencing raw data processing

Raw transcriptomic data were processed on a Linux platform. Quality control involved using trim galore (version 0.6.7) to remove adapters and low-quality bases. The reads were aligned to the reference genome with STAR (version 2.7.10a). Gene expression levels were quantified by featureCounts (version 2.0.1), producing the expression matrix.

Transcriptomic deconvolution

Transcriptomic deconvolution was performed using the BisqueRNA package (version 1.0.5) to estimate cell type proportions in mRNA-seq data55. After deconvolution, the statistical significance of cell proportion differences was assessed using one-sided statistical tests.

Statistical analysis

Two-sided statistical tests were used to evaluate the significance of most comparisons, including cell quantity comparisons and GOBP pathway scores. One-sided statistical tests were employed to analyze cell proportion differences after transcriptomic deconvolution. The specific statistical tests and criteria used for pathway enrichment, cell communication, pseudotime analysis, and other algorithms follow the standards and descriptions provided by each respective package. Detailed descriptions of the statistical methods and parameters used can be found in the documentation provided by these packages.

The results of cell and animal experiments were statistically analyzed in the software GraphPad Prism (version 9.4.1), each experiment was repeated at least 3 times, and all data were displayed as mean ± SD unless otherwise noted. Variance (ANOVA) analysis or two-tailed Student’s t test were used for data analysis, and Wilcoxon signed rank test was used for rank data. When comparing two sample’s proportions, Fisher’s Exact Test was employed. (*P < 0.05; **P < 0.01; ***P < 0.001, as shown in the full text).