Microbe-Dependent Exacerbated Alveolar Bone Destruction in Heterozygous Cherubism Mice

Loss-of-function OGFRL1 variants identified in autosomal recessive cherubism families

Cherubism (OMIM 118400) is a rare craniofacial disorder in children characterized by destructive jawbone expansion due to the growth of inflammatory fibrous lesions. Our previous studies have shown that gain-of-function mutations in SH3 domain-binding protein 2 (SH3BP2) are responsible for cherubism and that a knock-in mouse model for cherubism recapitulates the features of cherubism, such as increased osteoclast formation and jawbone destruction. To date, SH3BP2 is the only gene identified to be responsible for cherubism. Since not all patients clinically diagnosed with cherubism had mutations in SH3BP2, we hypothesized that there may be novel cherubism genes and that these genes may play a role in jawbone homeostasis. Here, using whole exome sequencing, we identified homozygous loss-of-function variants in the opioid growth factor receptor like 1 (OGFRL1) gene in 2 independent autosomal recessive cherubism families from Syria and India. The newly identified pathogenic homozygous variants were not reported in any variant databases, suggesting that OGFRL1 is a novel gene responsible for cherubism. Single cell analysis of mouse jawbone tissue revealed that Ogfrl1 is highly expressed in myeloid lineage cells. We generated OGFRL1 knockout mice and mice carrying the Syrian frameshift mutation to understand the in vivo role of OGFRL1. However, neither mouse model recapitulated human cherubism or the phenotypes exhibited by SH3BP2 cherubism mice under physiological and periodontitis conditions. Unlike bone marrow-derived M-CSF-dependent macrophages (BMMs) carrying the SH3BP2 cherubism mutation, BMMs lacking OGFRL1 or carrying the Syrian mutation showed no difference in TNF-ɑ mRNA induction by LPS or TNF-ɑ compared to WT BMMs. Osteoclast formation induced by RANKL was also comparable. These results suggest that the loss-of-function effects of OGFRL1 in humans differ from those in mice and highlight the fact that mice are not always an ideal model for studying rare craniofacial bone disorders.

Osteocyte RANKL Drives Bone Resorption in Mouse Ligature-Induced Periodontitis

Mouse ligature-induced periodontitis (LIP) has been used to study bone loss in periodontitis. However, the role of osteocytes in LIP remains unclear. Furthermore, there is no consensus on the choice of alveolar bone parameters and time points to evaluate LIP. Here, we investigated the dynamics of changes in osteoclastogenesis and bone volume (BV) loss in LIP over 14 days. Time-course analysis revealed that osteoclast induction peaked on days 3 and 5, followed by the peak of BV loss on day 7. Notably, BV was restored by day 14. The bone formation phase after the bone resorption phase was suggested to be responsible for the recovery of bone loss. Electron microscopy identified bacteria in the osteocyte lacunar space beyond the periodontal ligament (PDL) tissue. We investigated how osteocytes affect bone resorption of LIP and found that mice lacking receptor activator of NF-κB ligand (RANKL), predominantly in osteocytes, protected against bone loss in LIP, whereas recombination activating 1 (RAG1)-deficient mice failed to resist it. These results indicate that T/B cells are dispensable for osteoclast induction in LIP and that RANKL from osteocytes and mature osteoblasts regulates bone resorption by LIP. Remarkably, mice lacking the myeloid differentiation primary response gene 88 (MYD88) did not show protection against LIP-induced bone loss. Instead, osteocytic cells expressed nucleotide-binding oligomerization domain containing 1 (NOD1), and primary osteocytes induced significantly higher Rankl than primary osteoblasts when stimulated with a NOD1 agonist. Taken together, LIP induced both bone resorption and bone formation in a stage-dependent manner, suggesting that the selection of time points is critical for quantifying bone loss in mouse LIP. Pathogenetically, the current study suggests that bacterial activation of osteocytes via NOD1 is involved in the mechanism of osteoclastogenesis in LIP. The NOD1-RANKL axis in osteocytes may be a therapeutic target for bone resorption in periodontitis. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

A reappraisal of microbiome dysbiosis during experimental periodontitis

Periodontitis is a chronic inflammatory disease associated with the presence of dysbiotic microbial communities. Several studies interrogating periodontitis pathogenesis have utilized the murine ligature-induced periodontitis (LIP) model and have further examined the ligature-associated microbiome relying on 16S rRNA-based sequencing techniques. However, it is often very challenging to compare microbial profiles across studies due to important differences in bioinformatic processing and databases used for taxonomic assignment. Thus, our study aim was to reanalyze microbiome sequencing datasets from studies utilizing the LIP model through a standardized bioinformatic analysis pipeline, generating a comprehensive overview of microbial dysbiosis during experimental periodontitis.We conducted a reanalysis of 16S rDNA gene sequencing datasets from nine published studies utilizing the LIP model. Reads were grouped according to the hypervariable region of the 16S rDNA gene amplified (V1-V3 and V4), preprocessed, binned into operational taxonomic units and classified utilizing relevant databases. Alpha- and beta-diversity analyses were conducted, along with relative abundance profiling of microbial communities. Our findings revealed similar microbial richness and diversity across studies and determined shifts in microbial community structure determined by periodontitis induction and study of origin. Clear variations in the relative abundance of bacterial taxa were observed starting on day 5 after ligation and onward, consistent with a distinct microbial composition during health and experimental periodontitis. We also uncovered differentially represented bacterial taxa across studies, dominating periodontal health and LIP-associated communities. Collectively, this reanalysis provides a unified overview of microbial dysbiosis during the LIP model, providing new insights that aim to inform further studies dedicated to unraveling oral host-microbial interactions.

OC_Finder: Osteoclast Segmentation, Counting, and Classification Using Watershed and Deep Learning

Osteoclasts are multinucleated cells that exclusively resorb bone matrix proteins and minerals on the bone surface. They differentiate from monocyte/macrophage lineage cells in the presence of osteoclastogenic cytokines such as the receptor activator of nuclear factor-κB ligand (RANKL) and are stained positive for tartrate-resistant acid phosphatase (TRAP). In vitro osteoclast formation assays are commonly used to assess the capacity of osteoclast precursor cells for differentiating into osteoclasts wherein the number of TRAP-positive multinucleated cells is counted as osteoclasts. Osteoclasts are manually identified on cell culture dishes by human eyes, which is a labor-intensive process. Moreover, the manual procedure is not objective and results in lack of reproducibility. To accelerate the process and reduce the workload for counting the number of osteoclasts, we developed OC_Finder, a fully automated system for identifying osteoclasts in microscopic images. OC_Finder consists of cell image segmentation with a watershed algorithm and cell classification using deep learning. OC_Finder detected osteoclasts differentiated from wild-type and Sh3bp2KI/+ precursor cells at a 99.4% accuracy for segmentation and at a 98.1% accuracy for classification. The number of osteoclasts classified by OC_Finder was at the same accuracy level with manual counting by a human expert. OC_Finder also showed consistent performance on additional datasets collected with different microscopes with different settings by different operators. Together, successful development of OC_Finder suggests that deep learning is a useful tool to perform prompt and accurate unbiased classification and detection of specific cell types in microscopic images.

Application of Ligature-Induced Periodontitis in Mice to Explore the Molecular Mechanism of Periodontal Disease

Periodontitis is an inflammatory disease characterized by the destruction of the periodontium. In the last decade, a new murine model of periodontitis has been widely used to simulate alveolar bone resorption and periodontal soft tissue destruction by ligation. Typically, 3-0 to 9-0 silks are selected for ligation around the molars in mice, and significant bone loss and inflammatory infiltration are observed within a week. The ligature-maintained period can vary according to specific aims. We reviewed the findings on the interaction of systemic diseases with periodontitis, periodontal tissue destruction, the immunological and bacteriological responses, and new treatments. In these studies, the activation of osteoclasts, upregulation of pro-inflammatory factors, and excessive immune response have been considered as major factors in periodontal disruption. Multiple genes identified in periodontal tissues partly reflect the complexity of the pathogenesis of periodontitis. The effects of novel treatment methods on periodontitis have also been evaluated in a ligature-induced periodontitis model in mice. This model cannot completely represent all aspects of periodontitis in humans but is considered an effective method for the exploration of its mechanisms. Through this review, we aimed to provide evidence and enlightenment for future studies planning to use this model.