A distinctive subgingival microbiome in patients with periodontitis and Alzheimer's disease compared with cognitively unimpaired periodontitis patients.

AIM: Periodontitis is caused by dysbiosis of oral microbes and is associated with increased cognitive decline in Alzheimer's disease (AD), and recently, a potential functional link was proposed between oral microbes and AD. We compared the oral microbiomes of patients with or without AD to evaluate the association between oral microbes and AD in periodontitis. MATERIALS AND METHODS: Periodontitis patients with AD (n = 15) and cognitively unimpaired periodontitis patients (CU) (n = 14) were recruited for this study. Each patient underwent an oral examination and neuropsychological evaluation. Buccal, supragingival and subgingival plaque samples were collected, and microbiomes were analysed by next-generation sequencing. Alpha diversity, beta diversity, linear discriminant analysis effect size, analysis of variance-like differential expression analysis and network analysis were used to compare group oral microbiomes. RESULTS: All 29 participants had moderate to severe periodontitis. Group buccal and supragingival samples were indistinguishable, but subgingival samples demonstrated significant alpha and beta diversity differences. Differential analysis showed subgingival samples of the AD group had higher prevalence of Atopobium rimae, Dialister pneumosintes, Olsenella sp. HMT 807, Saccharibacteria (TM7) sp. HMT 348 and several species of Prevotella than the CU group. Furthermore, subgingival microbiome network analysis revealed a distinct, closely connected network in the AD group comprised of various Prevotella spp. and several anaerobic bacteria. CONCLUSIONS: A unique microbial composition was discovered in the subgingival region in the AD group. Specifically, potential periodontal pathogens were found to be more prevalent in the subgingival plaque samples of the AD group. These bacteria may possess a potential to worsen periodontitis and other systemic diseases. We recommend that AD patients receive regular, careful dental check-ups to ensure proper oral hygiene management.

Shape-Configurable Mesh for Hernia Repair by Synchronizing Anisotropic Body Motion.

Continuous progress has been made in elucidating the relationship between material property, device design, and body function to develop surgical meshes. However, an unmet need still exists wherein the surgical mesh can handle the body motion and thereby promote the repair process. Here, the hernia mesh design and the advanced polymer properties are tailored to synchronize with the anisotropic abdominal motion through shape configuration. The thermomechanical property of shape configurable polymer enables molding of mesh shape to fit onto the abdominal structure upon temperature shift, followed by shape fixing with the release of the heat energy. The microstructural design of mesh is produced through finite element modeling to handle the abdominal motion efficiently through the anisotropic longitudinal and transverse directions. The design effects are validated through in vitro, ex vivo, and in vivo mechanical analyses using a self-configurable, body motion responsive (BMR) mesh. The regenerative function of BMR mesh leads to effective repair in a rat hernioplasty model by effectively handling the anisotropic abdomen motion. Subsequently, the device-tissue integration is promoted by promoting healthy collagen synthesis with fibroblast-to-myofibroblast differentiation. This study suggests a potential solution to promote hernia repair by fine-tuning the relationship between material property and mesh design.

The oral microbiome of implant-abutment screw holes compared with the peri-implant sulcus and natural supragingival plaque in healthy individuals.

PURPOSE: An implant-supported prosthesis consists of an implant fixture, an abutment, an internal screw that connects the abutment to the implant fixture, and the upper prosthesis. Numerous studies have investigated the microorganisms present on the implant surface, surrounding tissues, and the subgingival microflora associated with peri-implantitis. However, there is limited information regarding the microbiome within the internal screw space. In this study, microbial samples were collected from the supragingival surfaces of natural teeth, the peri-implant sulcus, and the implant-abutment screw hole, in order to characterize the microbiome of the internal screw space in healthy subjects. METHODS: Samples were obtained from the supragingival region of natural teeth, the peri-implant sulcus, and the implant screw hole in 20 healthy subjects. DNA was extracted, and the V3-V4 region of the 16S ribosomal RNA was sequenced for microbiome analysis. Alpha diversity, beta diversity, linear discriminant analysis effect size (LEfSe), and network analysis were employed to compare the characteristics of the microbiomes. RESULTS: We observed significant differences in beta diversity among the samples. Upon analyzing the significant taxa using LEfSe, the microbial composition of the implant-abutment screw hole's microbiome was found to be similar to that of the other sampling sites' microbiomes. Moreover, the microbiome network analysis revealed a unique network complexity in samples obtained from the implant screw hole compared to those from the other sampling sites. CONCLUSIONS: The bacterial composition of the biofilm collected from the implant-abutment screw hole exhibited significant differences compared to the supra-structure of the implant. Therefore, long-term monitoring and management of not only the peri-implant tissue but also the implant screw are necessary.

Microbial profiling of peri-implantitis compared to the periodontal microbiota in health and disease using 16S rRNA sequencing.

PURPOSE: The objective of this study was to analyze the microbial profile of individuals with peri-implantitis (PI) compared to those of periodontally healthy (PH) subjects and periodontitis (PT) subjects using Illumina sequencing. METHODS: Buccal, supragingival, and subgingival plaque samples were collected from 109 subjects (PH: 30, PT: 49, and PI: 30). The V3-V4 region of 16S rRNA was sequenced and analyzed to profile the plaque microbiota. RESULTS: Microbial community diversity in the PI group was higher than in the other groups, and the 3 groups showed significantly separated clusters in the buccal samples. The PI group showed different patterns of relative abundance from those in the PH and PT groups depending on the sampling site at both genus and phylum levels. In all samples, some bacterial species presented considerably higher relative abundances in the PI group than in the PH and PT groups, including Anaerotignum lactatifermentans, Bacteroides vulgatus, Faecalibacterium prausnitzii, Olsenella uli, Parasutterella excrementihominis, Prevotella buccae, Pseudoramibacter alactolyticus, Treponema parvum, and Slackia exigua. Network analysis identified that several well-known periodontal pathogens and newly recognized bacteria were closely correlated with each other. CONCLUSIONS: The composition of the microbiota was considerably different in PI subjects compared to PH and PT subjects, and these results could shed light on the mechanisms involved in the development of PI.

Assessing the effect of antihypertensives on plaque microbiota in patients with periodontitis and hypertension using 16S rRNA sequencing: A cross-sectional study.

BACKGROUND: Periodontitis is initiated or accelerated by dysbiosis of oral microorganisms. When hypertension is accompanied in periodontitis patients, changes of oral microbiota occur. Since there are no reports on antihypertensives, we assessed their effect on the oral microbial profiles of patients with periodontitis. METHODS: This study involved 95 participants divided into two groups: those with periodontitis and hypertension (P_HT), and those with periodontitis and taking medications for hypertension (P_mHT). Plaque samples were collected from the buccal, supragingival, and subgingival sites of the oral cavities of these patients. DNA was extracted, and the V3-V4 region of the 16S ribosomal RNA was sequenced and analyzed. RESULTS: The P_HT and P_mHT groups were similar with respect to the alpha- and beta-diversity as well as the dominant phyla and genera, but differed in the relative abundance of bacterial species (85 species). In the P_mHT group, the relative abundance of major periodontal pathogens was greatly increased. In particular, Tannerella forsythia, Treponema denticola, and Fretibacterium fastidiosum increased nearly three times in the linear discriminant analysis score in the supragingival plaque. Also, there was an increase in the relative abundance of Prevotella spp., associated with periodontitis and nitrate reduction, which was also evident in the supragingival plaque. CONCLUSIONS: These findings indicate that antihypertensives induce dysbiotic changes in the oral microbiota of patients with periodontitis, which are associated with increases in the relative abundance of periodontal pathogens. Therefore, more active periodontal treatment and supportive periodontal therapy are required in patients taking antihypertensives.

Cell-Membrane-Derived Nanoparticles with Notch-1 Suppressor Delivery Promote Hypoxic Cell-Cell Packing and Inhibit Angiogenesis Acting as a Two-Edged Sword.

Cell-cell interactions regulate intracellular signaling via reciprocal contacts of cell membranes in tissue regeneration and cancer growth, indicating a critical need of membrane-derived tools in studying these processes. Hence, cell-membrane-derived nanoparticles (CMNPs) are produced using tonsil-derived mesenchymal stem cells (TMSCs) from children owing to their short doubling time. As target cell types, laryngeal cancer cells are compared to bone-marrow-derived MSCs (BMSCs) because of their cartilage damaging and chondrogenic characteristics, respectively. Treating spheroids of these cell types with CMNPs exacerbates interspheroid hypoxia with robust maintenance of the cell-cell interaction signature for 7 days. Both cell types prefer a hypoxic environment, as opposed to blood vessel formation that is absent in cartilage but is required for cancer growth. Hence, angiogenesis is inhibited by displaying the Notch-1 aptamer on CMNPs. Consequently, laryngeal cancer growth is suppressed efficiently in contrast to improved chondroprotection observed in a series of cell and animal experiments using a xenograft mouse model of laryngeal cancer. Altogether, CMNPs execute a two-edged sword function of inducing hypoxic cell-cell packing, followed by suppressing angiogenesis to promote laryngeal cancer death and chondrogenesis simultaneously. This study presents a previously unexplored therapeutic strategy for anti-cancer and chondroprotective treatment using CMNPs.

Molecular subgroup of periodontitis revealed by integrated analysis of the microbiome and metabolome in a cross-sectional observational study.

Background: Periodontitis (PT) is a multifactorial, chronic inflammatory disease that can have heterogeneous clinical presentations. The oral microbiome and its metabolites have been implicated as the causes and regulators of PT pathogenesis. In this study, we assessed the oral microbiome and its metabolome in PT patients to clarify the interactions between the microbiome and its metabolites.Methods: A total of 112 subjects were recruited. Buccal and supragingival samples were collected for microbiome analysis. Saliva samples were collected for metabolomic analyses. Microbiome and metabolome data were analyzed and further integrated for combined analysis using various bioinformatics approaches.Results: Oral metabolomic analysis identified 28 metabolites distinguishing the healthy (H) and PT groups. PT group were further clustered into two subgroups (PT_G1 and PT_G2) depending on metabolite profiles. Oral microbiome analysis revealed discriminatory bacterial species in the H, PT_G1, and PT_G2 microbiota. Interestingly, PT_G2 had significantly higher concentration of short chain fatty acids and higher abundance of pathogenic bacteria. Integrated analysis of the microbiome and metabolome showed close association.Conclusion: Our results provide evidence of a close interplay between the oral microbiome and metabolome. Multi-omics approach including microbiome and microbe-associated metabolites may serve as diagnostic biomarkers and enhance treatment prediction in periodontal disease.

Identification of Potential Oral Microbial Biomarkers for the Diagnosis of Periodontitis.

Periodontitis is a chronic and multifactorial inflammatory disease that can lead to tooth loss. At present, the diagnosis for periodontitis is primarily based on clinical examination and radiographic parameters. Detecting the periodontal pathogens at the subgingival plaque requires skilled professionals to collect samples. Periodontal pathogens are also detected on various mucous membranes in patients with periodontitis. In this study, we characterized the oral microbiome profiles from buccal mucosa and supragingival space in a total of 272 healthy subjects as a control group, and periodontitis patients as a disease group. We identified 13 phyla, 193 genera, and 527 species and determined periodontitis-associated taxa. Porphyromonas gingivalis, Tannerella forsythia, Treponema denticolar, Filifactor alocis, Porphyromonas endodontalis, Fretibacterium fastiosum and Peptostreptococcus species were significantly increased in both the buccal mucosa and the supragingival space in periodontitis patients. The identified eight periodontitis-associated bacterial species were clinically validated in an independent cohort. We generated the prediction model based on the oral microbiome profiles using five machine learning algorithms, and validated its capability in predicting the status of patients with periodontitis. The results showed that the oral microbiome profiles from buccal mucosa and supragingival space can represent the microbial composition of subgingival plaque and further be utilized to identify potential microbial biomarkers for the diagnosis of periodontitis. Besides, bacterial community interaction network analysis found distinct patterns associated with dysbiosis in periodontitis. In summary, we have identified oral bacterial species from buccal and supragingival sites which can predict subgingival bacterial composition and can be used for early diagnosis of periodontitis. Therefore, our study provides an important basis for developing easy and noninvasive methods to diagnose and monitor periodontitis.