RESUMO
BACKGROUND: White spot lesions (WSLs) are a formidable challenge during orthodontic treatment, affecting patients regardless of oral hygiene. Multifactorial in nature, amongst potential contributors to their development are the microbiome and salivary pH. The aim of our pilot study is to determine if pre-treatment differences in salivary Stephan curve kinetics and salivary microbiome features correlate with WSL development in orthodontic patients with fixed appliances. We hypothesize that non-oral hygiene determined differences in saliva could be predictive of WSL formation in this patient population through analysis of salivary Stephan curve kinetics, and that these differences would further manifest as changes in the oral microbiome. METHODS: In this prospective cohort study, twenty patients with initial simplified oral hygiene index scores of "good" that were planning to undergo orthodontic treatment with self-ligating fixed appliances for at least 12 months were enrolled. At pre-treatment stage, saliva was collected for microbiome analysis, and at 15-minute intervals after a sucrose rinse over 45 min for Stephan curve kinetics. RESULTS: 50% of patients developed a mean 5.7 (SEM: 1.2) WSLs. There were no differences in saliva microbiome species richness, Shannon alpha diversity or beta diversity between the groups. Capnocytophaga sputigena exclusively and Prevotella melaninogenica predominantly were found in WSL patients, while Streptococcus australis was negatively correlated with WSL development. Streptococcus mitis and Streptococcus anginosus were primarily present in healthy patients. There was no evidence to support the primary hypothesis. CONCLUSIONS: While there were no differences in salivary pH or restitution kinetics following a sucrose challenge and no global microbial differences in WSL developers, our data showed change in salivary pH at 5 min associated with an abundance of acid-producing bacteria in saliva. The results suggest salivary pH modulation as a management strategy to inhibit the abundance of caries initiators. Our study may have uncovered the earliest predecessors to WSL/caries development.
Assuntos
Cárie Dentária , Microbiota , Humanos , Projetos Piloto , Estudos Prospectivos , Aparelhos Ortodônticos Fixos , Cárie Dentária/etiologia , Aparelhos Ortodônticos/efeitos adversosRESUMO
SARS-CoV-2, a severe respiratory disease primarily targeting the lungs, was the leading cause of death worldwide during the pandemic. Understanding the interplay between the oral microbiome and inflammatory cytokines during acute infection is crucial for elucidating host immune responses. This study aimed to explore the relationship between the oral microbiome and cytokines in COVID-19 patients, particularly those with and without sputum production. Saliva and blood samples from 50 COVID-19 patients were subjected to 16S ribosomal RNA gene sequencing for oral microbiome analysis, and 65 saliva and serum cytokines were assessed using Luminex multiplex analysis. The Mann-Whitney test was used to compare cytokine levels between individuals with and without sputum production. Logistic regression machine learning models were employed to evaluate the predictive capability of oral microbiome, salivary, and blood biomarkers for sputum production. Significant differences were observed in the membership (Jaccard dissimilarity: p = 0.016) and abundance (PhILR dissimilarity: p = 0.048; metagenomeSeq) of salivary microbial communities between patients with and without sputum production. Seven bacterial genera, including Prevotella, Streptococcus, Actinomyces, Atopobium, Filifactor, Leptotrichia, and Selenomonas, were more prevalent in patients with sputum production (p<0.05, Fisher's exact test). Nine genera, including Prevotella, Megasphaera, Stomatobaculum, Selenomonas, Leptotrichia, Veillonella, Actinomyces, Atopobium, and Corynebacteria, were significantly more abundant in the sputum-producing group, while Lachnoanaerobaculum was more prevalent in the non-sputum-producing group (p<0.05, ANCOM-BC). Positive correlations were found between salivary IFN-gamma and Eotaxin2/CCL24 with sputum production, while negative correlations were noted with serum MCP3/CCL7, MIG/CXCL9, IL1 beta, and SCF (p<0.05, Mann-Whitney test). The machine learning model using only oral bacteria input outperformed the model that included all data: blood and saliva biomarkers, as well as clinical and demographic variables, in predicting sputum production in COVID-19 subjects. The performance metrics were as follows, comparing the model with only bacteria input versus the model with all input variables: precision (95% vs. 75%), recall (100% vs. 50%), F1-score (98% vs. 60%), and accuracy (82% vs. 66%).
Assuntos
COVID-19 , Microbiota , Saliva , Escarro , Humanos , COVID-19/microbiologia , Escarro/microbiologia , Saliva/microbiologia , Feminino , Masculino , Pessoa de Meia-Idade , Adulto , Idoso , Citocinas/sangue , Citocinas/metabolismo , Pulmão/microbiologia , Pulmão/virologia , SARS-CoV-2/isolamento & purificação , RNA Ribossômico 16S/genética , Leptotrichia , Prevotella/isolamento & purificação , Streptococcus/isolamento & purificação , Actinomyces/isolamento & purificação , Boca/microbiologia , Boca/virologia , Aprendizado de Máquina , Biomarcadores/sangueRESUMO
Objectives: Obstructive sleep apnea (OSA) can adversely affect the immune response through clinical factors such as hypoxia, inflammation, and sleep disturbance. Since SARS-CoV-2 heavily relies on local and systemic host immune responses, this study aims to examine the links between the severity of OSA risk, cytokine levels, and the severity of symptoms associated with SARS-CoV-2 infection. Methods: Saliva and blood samples from 50 COVID-19 patients and 30 non-infected hospital staff members were collected. Using Luminex multiplex analysis, 65 blood and salivary cytokines were examined from the collected samples. Ordinal logistic regression analysis was utilized to examine the association between the self-reported risk of OSA, assessed through the STOP-Bang questionnaire, and the likelihood of experiencing severe symptoms of COVID-19. Mann-Whitney test was then performed to compare the cytokine levels between individuals with moderate to severe risk of OSA to those with a mild risk of OSA. Results: Ordinal logistic regression analysis revealed that individuals with a moderate to severe risk of OSA were 7.60 times more likely to experience more severe symptoms of COVID-19 compared to those with a mild risk of OSA (OR = 7.60, 95%CI: 3.03, 19.06, p < 0.001). Moreover, among COVID-19-positive patients with a moderate to severe risk of OSA, there was a statistically significant negative correlation with serum IL-6 (p < 0.05), Eotaxin (CCL11) (p = 0.04), and salivary MIP-3α/CCL20 (p = 0.04). In contrast, individuals without COVID-19 who had a moderate to severe risk of OSA exhibited a significant positive correlation with serum IL-6 (p = 0.04). Conclusion: Individuals with moderate to severe risk of OSA were more likely to experience severe COVID-19 symptoms than those with mild risk for OSA. Additional analysis from the present studies revealed distinct patterns of oral and systemic immune responses between individuals with mild and moderate to severe risk of OSA. Findings from the present study underscores the importance of early detection and management of OSA to improve clinical outcomes, particularly when faced with the subsequent superimposed infection such as COVID-19.
Assuntos
COVID-19 , Apneia Obstrutiva do Sono , Humanos , Citocinas , Interleucina-6 , Polissonografia , SARS-CoV-2 , Apneia Obstrutiva do Sono/diagnósticoRESUMO
Established evidence indicates that oral microbiota plays a crucial role in modulating host immune responses to viral infection. Following severe acute respiratory syndrome coronavirus 2, there are coordinated microbiome and inflammatory responses within the mucosal and systemic compartments that are unknown. The specific roles the oral microbiota and inflammatory cytokines play in the pathogenesis of coronavirus disease 2019 (COVID-19) are yet to be explored. Here, we evaluated the relationships between the salivary microbiome and host parameters in different groups of COVID-19 severity based on their oxygen requirement. Saliva and blood samples (n = 80) were collected from COVID-19 and from noninfected individuals. We characterized the oral microbiomes using 16S ribosomal RNA gene sequencing and evaluated saliva and serum cytokines and chemokines using multiplex analysis. Alpha diversity of the salivary microbial community was negatively associated with COVID-19 severity, while diversity increased with health. Integrated cytokine evaluations of saliva and serum showed that the oral host response was distinct from the systemic response. The hierarchical classification of COVID-19 status and respiratory severity using multiple modalities separately (i.e. microbiome, salivary cytokines, and systemic cytokines) and simultaneously (i.e. multimodal perturbation analyses) revealed that the microbiome perturbation analysis was the most informative for predicting COVID-19 status and severity, followed by the multimodal. Our findings suggest that oral microbiome and salivary cytokines may be predictive of COVID-19 status and severity, whereas atypical local mucosal immune suppression and systemic hyperinflammation provide new cues to understand the pathogenesis in immunologically compromised populations.
RESUMO
Established evidence indicates that oral microbiota plays a crucial role in modulating host immune responses to viral infection. Following Severe Acute Respiratory Syndrome Coronavirus 2 - SARS-CoV-2 - there are coordinated microbiome and inflammatory responses within the mucosal and systemic compartments that are unknown. The specific roles that the oral microbiota and inflammatory cytokines play in the pathogenesis of COVID-19 are yet to be explored. We evaluated the relationships between the salivary microbiome and host parameters in different groups of COVID-19 severity based on their Oxygen requirement. Saliva and blood samples (n = 80) were collected from COVID-19 and from non-infected individuals. We characterized the oral microbiomes using 16S ribosomal RNA gene sequencing and evaluated saliva and serum cytokines using Luminex multiplex analysis. Alpha diversity of the salivary microbial community was negatively associated with COVID-19 severity. Integrated cytokine evaluations of saliva and serum showed that the oral host response was distinct from the systemic response. The hierarchical classification of COVID-19 status and respiratory severity using multiple modalities separately (i.e., microbiome, salivary cytokines, and systemic cytokines) and simultaneously (i.e., multi-modal perturbation analyses) revealed that the microbiome perturbation analysis was the most informative for predicting COVID-19 status and severity, followed by the multi-modal. Our findings suggest that oral microbiome and salivary cytokines may be predictive of COVID-19 status and severity, whereas atypical local mucosal immune suppression and systemic hyperinflammation provide new cues to understand the pathogenesis in immunologically naïve populations.
RESUMO
BACKGROUND: In Grade C periodontitis in young patients (PerioC-Y), the functional roles of the subgingival community after years of periodontal treatment are still underexplored. This study evaluated the taxonomic and predicted functional content of the subgingival microbiome of PerioC-Y patients under supportive periodontal therapy (SPT). METHODS: Clinical and microbiological data from subgingival biofilm were assessed from 10 PerioC-Y patients at two time points: at baseline and after 5.7 ± 1.3 years of SPT. This was compared with 15 patients without a history of periodontitis. The V1-V3 and V4-V5 regions of the 16S rRNA were sequenced using the Illumina Miseq. Microbial composition was evaluated by the core microbiome, and alpha- and beta-diversity. The microbiome functional content was predicted using Picrust2, and the gene differential abundance was analyzed with DESeq2. RESULTS: Clinical improvements were seen in PerioC-Y-SPT. Differences in ß-diversity between PerioC-Y and health were observed (health x PerioC-Y-baseline, P = 0.02; health x PerioC-Y-SPT, P = 0.05). Moreover, although ß-diversity did not statistically change between baseline and SPT in PerioC-Y, the microbial correlation evidenced increased Streptococcus and decreased Treponema network contributions during SPT. Based on predicted functional data, treatment induced a reduction in genes related to flagellar protein and signal transduction in PerioC-Y. However, compared with healthy individuals, some genes remained more highly abundant in PerioC-Y-SPT, such as quorum sensing and efflux pump transporters. CONCLUSION: Despite clinical improvements and a shift in taxonomic composition, the PerioC-Y patients' periodontal treatment was not enough to reach a similar microbiome to patients without disease experience. Some functional content in this biofilm remained altered in PerioC-Y regardless of disease control.
Assuntos
Microbiota , Periodontite , Biofilmes , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Microbiota/genética , Periodontite/microbiologia , RNA Ribossômico 16S/genéticaRESUMO
BACKGROUND: Although localized aggressive periodontitis (LAP), generalized aggressive periodontitis (GAP), and chronic periodontitis (CP) are microbially driven diseases, our inability to separate disease-specific associations from those common to all three forms of periodontitis has hampered biomarker discovery. Therefore, we aimed to map the genomic content of, and the biological pathways encoded by, the microbiomes associated with these clinical phenotypes. We also estimated the extent to which these biomes are governed by the Anna Karenina principle (AKP), which states that eubiotic communities are similar between individuals while disease-associated communities are highly individualized. METHODS: We collected subgingival plaque from 25 periodontally healthy individuals and diseased sites of 59 subjects with stage 3 periodontitis and used shotgun metagenomics to characterize the aggregate of bacterial genes. RESULTS: Beta-dispersion metrics demonstrated that AKP was most evident in CP, followed by GAP and LAP. We discovered broad dysbiotic signatures spanning the three phenotypes, with over-representation of pathways that facilitate life in an oxygen-poor, protein- and heme-rich, pro-oxidant environment and enhance capacity for attachment and biofilm formation. Phenotype-specific indicators were more readily evident in LAP microbiome than GAP or CP. Genes that enable acetate-scavenging lifestyle, utilization of alternative nutritional sources, oxidative and nitrosative stress responses, and siderophore production were unique to LAP. An attenuation of virulence-related functionalities and stress response from LAP to GAP to CP was apparent. We also discovered that clinical phenotypes of disease resolved variance in the microbiome with greater clarity than the newly established grading system. Importantly, we observed that one third of the metagenome of LAP is unique to this phenotype while GAP shares significant functional and taxonomic features with both LAP and CP, suggesting either attenuation of an aggressive disease or an early-onset chronic disease. CONCLUSION: Within the limitations of a small sample size and a cross-sectional study design, the distinctive features of the microbiomes associated with LAP and CP strongly persuade us that these are discrete disease entities, while calling into question whether GAP is a separate disease, or an artifact induced by cross-sectional study designs. Further studies on phenotype-specific microbial genes are warranted to explicate their role in disease etiology. Video Abstract.
Assuntos
Periodontite Agressiva , Microbiota , Estudos Transversais , Humanos , Metagenoma , Metagenômica , Microbiota/genéticaRESUMO
BACKGROUND: The current pandemic has raised awareness of aerosol dispersion in dental offices. This scoping review was conducted to assess the amount and spread of aerosol generated by dental procedures. METHODS: This scoping review followed the PRISMA-ScR protocol and was conducted by searching multiple databases adopting a core search structure for each database. Detailed eligibility criteria were applied. The authors placed no restrictions on study design, year of publication, and study location. The literature search was updated on September 15, 2021. RESULTS: A total of 51 papers were included in this scoping review. The risk of bias assessment was not conducted as per guidelines. The majority of studies found microorganisms, bloodstains, splatters of aerosol, and particles in the air part of the search strategy. Publication dates ranged from 1969 to 2021. Data came from different dental settings locations. Several factors were identified that have an effect on the amount and spread of the aerosol and spatter. CONCLUSION: Although it is clear that the microbial contamination occurred mainly during aerosol-generating dental procedures, our understanding of the contamination level, spread, and half-life are limited.
Assuntos
Pandemias , AerossóisRESUMO
Early acquisition of a pathogenic microbiota and the presence of dysbiosis in childhood is associated with susceptibility to and the familial aggregation of periodontitis. This longitudinal interventional case-control study aimed to evaluate the impact of parental periodontal disease on the acquisition of oral pathogens in their offspring. Subgingival plaque and clinical periodontal metrics were collected from 18 parents with a history of generalized aggressive periodontitis and their children (6-12 years of age), and 18 periodontally healthy parents and their parents at baseline and following professional oral prophylaxis. 16S rRNA amplicon sequencing revealed that parents were the primary source of the child's microbiome, affecting their microbial acquisition and diversity. Children of periodontitis parents were preferentially colonized by Filifactor alocis, Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, Streptococcus parasanguinis, Fusobacterium nucleatum and several species belonging to the genus Selenomonas even in the absence of periodontitis, and these species controlled inter-bacterial interactions. These pathogens also emerged as robust discriminators of the microbial signatures of children of parents with periodontitis. Plaque control did not modulate this pathogenic pattern, attesting to the microbiome's resistance to change once it has been established. This study highlights the critical role played by parental disease in microbial colonization patterns in their offspring and the early acquisition of periodontitis-related species and underscores the need for greater surveillance and preventive measures in families of periodontitis patients.