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.

Peri-implantitis and periodontitis are both polymicrobial diseases induced by subgingival plaque accumulation, with some differing clinical features. Studies on the microbial and gene transcription activity of peri-implantitis microbiota are limited. This study aimed to verify the hypothesis that disease-specific microbial and gene transcription activity lead to disease-specific clinical features, using an integrated metagenomic, metatranscriptomic, and network analysis. Metagenomic data in peri-implantitis and periodontitis were obtained from the same 21 subjects and metatranscriptomic data from 12 subjects were obtained from a database. The microbial co-occurrence network based on metagenomic analysis had more diverse species taxa and correlations than the network based on the metatranscriptomic analysis. Solobacterium moorei and Prevotella denticola had high activity and were core species taxa specific to peri-implantitis in the co-occurrence network. Moreover, the activity of plasmin receptor/glyceraldehyde-3-phosphate dehydrogenase genes was higher in peri-implantitis. These activity differences may increase complexity in the peri-implantitis microbiome and distinguish clinical symptoms of the two diseases. These findings should help in exploring a novel biomarker that assist in the diagnosis and preventive treatment design of peri-implantitis.

The characteristics of the periodontal microbiome influence clinical periodontal status. Gingivitis involves reversible gingival inflammation without alveolar bone resorption.

Dental caries is a polymicrobial disease and prevalent among cleft lip and palate (CLP) patients, although their oral hygiene is well maintained. Dysbiosis, the state of imbalance within the dental plaque microbiota, may cause caries prevalence among these patients. However, little is known about how dysbiosis occurs and affects cariogenicity. To find dysbiotic signs, here we conducted a metatranscriptomic analysis for the plaque microbiota in six CLP patients and four controls. Total bacterial RNA was extracted from each sample and sequenced. Bacterial composition and functional profiles were estimated from 16S rRNA and mRNA reads, respectively. The mRNA reads were further used for estimating bacterial composition. Species listed in both rRNA-based and mRNA-based bacterial composition were identified as viable taxa with in situ function (VTiF), and the VTiF with a high mRNA-to-rRNA ratio were considered to be transcriptionally active. A network was constructed for each group by connecting two VTiF if their mRNA abundances were positively correlated. The bacterial composition and functional profiles themselves did not provide remarkable signs of dysbiosis in the CLP group. However, the group-specific active taxa were identified, including streptococcal and Prevotella species in the CLP group. Moreover, the network structure was different between groups; Actinomyces johnsonii and several species in the CLP group were the active taxa, which were connected based on positive correlations with statistical significance. Functional dysbiosis within the plaque microbiota was observed such as difference of the network structure between groups, and may be associated with cariogenicity. The observed functional dysbiosis was an invisible change within the microbiota in the oral cavity of CLP patients. This may emphasize the importance of maintaining good oral hygiene of the patients with cleft anomalies.

Enteral nutrition for children is supplied through nasogastric or gastrostomy tubes. Diet not only influences nutritional intake but also interacts with the composition and function of the gut microbiota. Homemade blenderized tube feeding has been administered to children receiving enteral nutrition, in addition to ready-made tube feeding. The purpose of this study was to evaluate the oral/gut microbial communities in children receiving enteral nutrition with or without homemade blenderized tube feeding. Among a total of 30 children, 6 receiving mainly ready-made tube feeding (RTF) and 5 receiving mainly homemade blenderized tube feeding (HBTF) were analyzed in this study. Oral and gut microbiota community profiles were evaluated through 16S rRNA sequencing of saliva and fecal samples. The α-diversity representing the number of observed features, Shannon index, and Chao1 in the gut were significantly increased in HBTF only in the gut microbiome but not in the oral microbiome. In addition, the relative abundances of the phylum Proteobacteria, class Gammaproteobacteria, and genus Escherichia-Shigella were significantly low, whereas that of the genus Ruminococcus was significantly high in the gut of children with HBTF, indicating HBTF altered the gut microbial composition and reducing health risks. Metagenome prediction showed enrichment of carbon fixation pathways in prokaryotes at oral and gut microbiomes in children receiving HBTF. In addition, more complex network structures were observed in the oral cavity and gut in the HBTF group than in the RTF group. In conclusion, HBTF not only provides satisfaction and enjoyment during meals with the family but also alters the gut microbial composition to a healthy state.

16S rRNA gene amplicon sequencing analysis is used to investigate bacterial communities; however, the estimated bacterial composition can differ from the original due to experimental and analytical biases. Therefore, this study determines the optimal conditions to minimize the potential biases in 16S rRNA gene amplicon sequencing analysis using different DNA samples, trimming lengths, primers, and databases. The results of the mock1 community with 250 and 300 bp paired-end (PE), comprising 15 bacteria from various environments, showed the highest similarity between the theoretical value and the data using the Greengenes2 and the V3 region at the genus level and V5–V6 at the species level. In the 300 bp PE sequencing analysis of the mock2 community, comprising six major oral bacteria, the data using the V3–V4, V4, and V5–V6 regions with the SILVA, Greengenes2, and the Human Oral Microbiome Database (HOMD) showed the highest similarity to the theoretical values at the genus level. At the species level, the data using the V3–V4 and V4 regions with Greengenes2 and the data using the V1–V2 with HOMD exhibited the highest alignment with the theoretical values. In the species analysis of the dental calculus samples with 300 bp PE, the Shannon index value was higher with the V1–V2 region and HOMD than with others. Our results suggest that the optimal conditions for oral microbiome analysis are the combinations of 300 bp PE and the V3–V4 or V4 region with the Greengenes2 and the V1–V2 with HOMD. IMPORTANCE: The 16S rRNA gene amplicon sequencing analysis is frequently used in oral microbiome research. However, this method can have biases that distort the experimental data, which depend on the methodological steps, including sequencing length, trimming length, selected amplification regions, and referenced databases. In this study, a combination of 300 bp PE and the primer targeting the V3–V4 or V4 regions with the Greengenes2 and the V1–V2 region with the HOMD was the most bias-minimizing condition for oral microbiota analysis. In addition, this is the first report of such analyses in modern Japanese dental calculus. The methods used in this study will aid in setting appropriate conditions for sequence analysis of microbiota obtained not only from the oral cavity but also from any environment.