Direct contact with endothelial cells drives dental pulp stem cells toward smooth muscle cells differentiation via TGF-ß1 secretion.

AIM: Prevascularization is vital to accelerate functional blood circulation establishment in transplanted engineered tissue constructs. Mesenchymal stem cells (MSCs) or mural cells could promote the survival of implanted endothelial cells (ECs) and enhance the stabilization of newly formed blood vessels. However, the dynamic cell-cell interactions between MSCs, mural cells and ECs in the angiogenic processes remain unclear. This study aimed to explore the interactions of human umbilical vein ECs (HUVECs) and dental pulp stem cells (DPSCs) in an in vitro cell coculture model. METHODOLOGY: Human umbilical vascular ECs and DPSCs were directly cocultured or indirectly cocultured with transwell inserts in endothelial basal media-2 (EBM-2) supplemented with 5% FBS for 6 days. Expression of SMC-specific markers in DPSCs monoculture and HUVEC+DPSC cocultures was assessed by western blot and immunofluorescence. Activin A and transforming growth factor-beta 1 (TGF-ß1) in conditioned media (CM) of HUVECs monoculture (E-CM), DPSCs monoculture (D-CM) and HUVEC+DPSC cocultures (E+D-CM) were analysed by enzyme-linked immunosorbent assay. TGF-ß RI kinase inhibitor VI, SB431542, was used to block TGF-ß1/ALK5 signalling in DPSCs. RESULTS: The expression of SMC-specific markers, α-SMA, SM22α and Calponin, were markedly increased in HUVEC+DPSC direct cocultures compared to that in DPSCs monoculture, while no differences were demonstrated between HUVEC+DPSC indirect cocultures and DPSCs monoculture. E+D-CM significantly upregulated the expression of SMC-specific markers in DPSCs compared to E-CM and D-CM. Activin A and TGF-ß1 were considerably higher in E+D-CM than that in D-CM, with upregulated Smad2 phosphorylation in HUVEC+DPSC cocultures. Treatment with activin A did not change the expression of SMC-specific markers in DPSCs, while treatment with TGF-ß1 significantly enhanced these markers' expression in DPSCs. In addition, blocking TGF-ß1/ALK5 signalling inhibited the expression of α-SMA, SM22α and Calponin in DPSCs. CONCLUSIONS: TGF-ß1 was responsible for DPSC differentiation into SMCs in HUVEC+DPSC cocultures, and TGF-ß1/ALK5 signalling pathway played a vital role in this process.

Fusobacterium nucleatum aggravates ulcerative colitis through promoting gut microbiota dysbiosis and dysmetabolism.

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-1ß) 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.

Structure and Function of Oral Microbial Community in Periodontitis Based on Integrated Data.

Objective: Microorganisms 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. Methods: In 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. Results: The 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. Conclusion: This 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.