ObjectiveMicroorganisms play a key role in the initiation and progression of periodontal disease. Research studies have focused on seeking specific microorganisms for diagnosing and monitoring the outcome of periodontitis treatment. Large samples may help to discover novel potential biomarkers and capture the common characteristics among different periodontitis patients. This study examines how to screen and merge high-quality periodontitis-related sequence datasets from several similar projects to analyze and mine the potential information comprehensively.MethodsIn all, 943 subgingival samples from nine publications were included based on predetermined screening criteria. A uniform pipeline (QIIME2) was applied to clean the raw sequence datasets and merge them together. Microbial structure, biomarkers, and correlation network were explored between periodontitis and healthy individuals. The microbiota patterns at different periodontal pocket depths were described. Additionally, potential microbial functions and metabolic pathways were predicted using PICRUSt to assess the differences between health and periodontitis.ResultsThe subgingival microbial communities and functions in subjects with periodontitis were significantly different from those in healthy subjects. Treponema, TG5, Desulfobulbus, Catonella, Bacteroides, Aggregatibacter, Peptostreptococcus, and Eikenella were periodontitis biomarkers, while Veillonella, Corynebacterium, Neisseria, Rothia, Paludibacter, Capnocytophaga, and Kingella were signature of healthy periodontium. With the variation of pocket depth from shallow to deep pocket, the proportion of Spirochaetes, Bacteroidetes, TM7, and Fusobacteria increased, whereas that of Proteobacteria and Actinobacteria decreased. Synergistic relationships were observed among different pathobionts and negative relationships were noted between periodontal pathobionts and healthy microbiota.ConclusionThis study shows significant differences in the oral microbial community and potential metabolic pathways between the periodontitis and healthy groups. Our integrated analysis provides potential biomarkers and directions for in-depth research. Moreover, a new method for integrating similar sequence data is shown here that can be applied to other microbial-related areas.

Background The correlation between periodontitis and ulcerative colitis (UC) has drawn widespread attention recently. Fusobacterium nucleatum (F. nucleatum) as a periodontal pathogen also has reservoirs in gut and may play a role in intestinal diseases. However, its role in the pathogenesis of UC is unclear. Methods Mice were orally given dextran sulphate sodium (DSS) solution and F. nucleatum to construct experimental models. The survival rate, weight, and disease activity index (DAI) of mice were monitored. Alveolar bone loss, abundance of F. nucleatum in colon, colon length, histopathological assessment, and inflammatory cytokines were detected. Apoptosis of intestinal epithelial cells (IECs) were evaluated by TUNEL assay and pro‐apoptotic gene Bax. The epithelial barrier function was assessed by tight junction proteins. By 16S rRNA gene sequencing and LC‐MS‐based methods, the composition of the intestinal microbiota and metabolites in mice were analyzed. Results F. nucleatum facilitated alveolar bone loss and colonized only in infected colon tissue. Mice fed with DSS showed destruction of gut structure, increased expressions of interleukin one‐beta (IL‐1β) and tumor necrosis factor alpha (TNF‐α), decreased expression of IL‐10, higher apoptosis of IECs, microbiota dysbiosis and bile acid dysmetabolism compared to healthy ones. F. nucleatum further aggravated intestinal inflammation and epithelial barrier damage. Probiotics such as Bifidobacterium and Faecalibacterium decreased, opportunistic pathogens Escherichia‐Shigella increased and the differential microorganisms highly associated with inflammatory parameters and metabolites. Meanwhile, level of uric acid involving in the purine metabolism significantly elevated compared to UC mice. Conclusions F. nucleatum promotes gut inflammation, epithelial barrier dysfunction, microbiota dysbiosis and dysmetabolism to aggravate UC.