Oral Microbiome Profiles Research Articles

Pooled analysis of oral microbiome profiles defines robust signatures associated with periodontitis.

Oral microbial dysbiosis has been associated with periodontitis in studies using 16S rRNA gene sequencing analysis. However, this technology is not sufficient to consistently separate the bacterial species to species level, and reproducible oral microbiome signatures are scarce. Here, using ultra-deep metagenomic sequencing and machine learning tools, we defined a simple two-factor decision tree, based on Tannerella forsythia and Fretibacterium fastidiosum, that was highly associated with periodontitis. Altogether, we defined robust oral microbiome signatures relevant to the pathophysiology of periodontitis that can help define promising targets for microbiome therapeutic modulation when caring for patients with periodontitis.

Oral and gut microbiome profiles in people with early idiopathic Parkinson’s disease

BackgroundEarly detection of Parkinson’s disease (PD), a neurodegenerative disease with central and peripheral nerve involvement, ensures timely treatment access. Microbes influence nervous system health and are altered in PD.MethodsWe examined gut and mouth microbiomes from recently diagnosed patients in a geographically diverse, matched case-control, shotgun metagenomics study.ResultsHere, we show greater alpha-diversity in 445 PD patients versus 221 controls. The microbial signature of PD includes overabundance of 16 OTUs, including Streptococcus mutans and Bifidobacterium dentium, and depletion of 28 OTUs. Machine learning models indicate that subspecies level oral microbiome abundances best distinguish PD with reasonably high accuracy (area under the curve: 0.758). Microbial networks are disrupted in cases, with reduced connectivity between short-chain fatty acid-producing bacteria the the gut. Importantly, microbiome diversity metrics are associated with non-motor autonomic symptom severity.ConclusionsOur results provide evidence that predictive oral PD microbiome signatures could possibly be used as biomarkers for the early detection of PD, particularly when there is peripheral nervous system involvement.

Oral Microbiome and Cognition Among Black Cancer Caregivers

Abstract Background Despite known links between oral health and dementia and the growing understanding of the role of the human microbiome in health, few studies have explored the relationship between the oral microbiome and cognition. Additionally, there is a notable absence of research on how the oral microbiome is associated with cognitive function in Black adult caregivers of cancer patients despite their elevated risk for both oral disease and cognitive impairment. Objectives This study aimed to characterize the oral microbiome of Black caregivers of people living with cancer and explore the association of the oral microbiome with cognitive performance. Methods Thirty-one self-identified Black or African American caregivers of cancer patients in the greater metropolitan Atlanta area participated in the study. They provided oral microbiome samples. Cognitive performance was assessed using the Montreal Cognitive Assessment (MoCA), depressive symptoms with the Center for Epidemiological Studies Depression Scale, and individual race-related stress with the Index of Race-Related Stress–Brief. Salivary microbiome diversity was analyzed using alpha and beta diversity metrics, and taxa associated with cognition were identified through differential abundance testing, adjusting for potential confounders. Results The mean age of participants was 54.8 years. MoCA scores ranged from 18 to 30, with a mean of 25. Participants were categorized into normal cognition (MoCA ≥26, n = 12) and low cognition (MoCA <26, n = 16) groups. Education level and individual race-related stress were associated with cognition group and were controlled for in the oral microbiome analysis. Alpha and beta diversity analyses showed no significant overall differences between cognition groups. Differential abundance testing suggested 48 taxa were associated with cognition status, many of which are known to be associated with periodontal disease and cognition. Discussion This study revealed associations between cognition status and specific oral bacteria, many of which are known to be associated with periodontal disease and cognitive impairment. These findings underscore the complex relationship between oral health and cognitive function, suggesting a need for further research to develop oral microbiome profiles capable of identifying individuals at risk for cognitive decline and guiding targeted interventions for promoting overall well-being and cognitive health.

Association of Oral Microbiome with Periodontal Disease Progression: A Longitudinal Study

Periodontal disease, a prevalent oral health condition, is characterized by the inflammation and destruction of the supporting tissues around the teeth and poses significant challenges to global public health. Objectives: To examine the association between the oral microbiome and periodontal disease progression in a Pakistani population. Methods: A total of 350 patients aged ≥ 18 years, diagnosed with periodontal disease, were registered from August 2023 to February 2024. Participants were evaluated for periodontal health indicators, including probing depth and clinical attachment loss, and their oral microbiome profiles were analyzed using high-throughput sequencing of the 16S rRNA gene. Machine learning algorithms, including Random Forest and Support Vector Machines, were applied to predict disease progression based on microbial profiles. Results: Porphyromonas gingivalis and Tannerella forsythia were strongly associated with greater probing depths and clinical attachment loss (β = 0.45, p < 0.01), indicating their role in disease progression. Conversely, Streptococcus and Lactobacillus were linked to reduced disease severity (β = -0.30, p < 0.05). The oral microbiome exhibited high diversity, with Firmicutes (35%), Bacteroidetes (25%), Proteobacteria (20%), and Actinobacteria (15%) being the predominant species. The Random Forest model predicted disease progression with 85% accuracy (Area under the curve (AUC) = 0.87), emphasizing the predictive value of microbial profiles. Conclusions: It was concluded that the study confirms a strong link between specific oral microbiota and periodontal disease progression, emphasizing the importance of microbial analysis in predicting and managing periodontal health.

Relationship of Metabolic Dysfunction-Associated Steatohepatitis-Related Hepatocellular Carcinoma with Oral and Intestinal Microbiota: A Cross-Sectional Pilot Study.

Background and Objectives: The incidence of metabolic dysfunction-associated steatohepatitis (MASH)-related hepatocellular carcinoma (HCC) is increasing worldwide, alongside the epidemic of obesity and metabolic syndrome. Based on preliminary reports regarding the potential association of HCC and periodontitis, this study aimed to analyze the involvement of periodontal bacteria as well as the oral and intestinal bacterial flora in MASH-related HCC (MASH-HCC). Materials and Methods: Forty-one patients with MASH and nineteen with MASH-HCC participated in the study, completing survey questionnaires, undergoing periodontal examinations, and providing samples of saliva, mouth-rinsed water, feces, and peripheral blood. The oral and fecal microbiome profiles were analyzed by 16S ribosomal RNA sequencing. Bayesian network analysis was used to analyze the causation between various factors, including MASH-HCC, examinations, and bacteria. Results: The genus Fusobacterium had a significantly higher occupancy rate (p = 0.002) in the intestinal microflora of the MASH-HCC group compared to the MASH group. However, Butyricicoccus (p = 0.022) and Roseburia (p < 0.05) had significantly lower occupancy rates. The Bayesian network analysis revealed the absence of periodontal pathogenic bacteria and enteric bacteria affecting HCC. However, HCC directly affected the periodontal bacterial species Porphyromonas gingivalis, Tannerella forsythia, Fusobacterium nucleatum, and Prevotella intermedia in the saliva, as well as the genera Lactobacillus, Roseburia, Fusobacterium, Prevotella, Clostridium, Ruminococcus, Trabulsiella, and SMB53 in the intestine. Furthermore, P. gingivalis in the oral cavity directly affected the genera Lactobacillus and Streptococcus in the intestine. Conclusions: MASH-HCC directly affects periodontal pathogenic and intestinal bacteria, and P. gingivalis may affect the intestinal bacteria associated with gastrointestinal cancer.

Investigating oral microbiome profiles in patients with cleft lip and palate compared with the healthy control

BackgroundPatients with cleft lip and palate (CLP) have an oronasal communication differed from the closed state in healthy individuals, leading to a unique oral microbiome. This study aimed to determine if variances in the oral microbiota persist among CLP patients who have received treatments for the closure of these fistulas compared to the microbiota of healthy individuals.MethodsSaliva samples were collected from a cohort comprising 28 CLP patients (CLP group) and 30 healthy controls (HC group). Utilizing 16S rRNA sequencing on the Illumina NovaSeq platform, we conducted a comprehensive analysis of the diversity and composition of the oral microbiota.ResultsThe analysis of the microbiota in the saliva samples revealed a total of 23 microbial phyla, 38 classes, 111 orders, 184 families, 327 genera and 612 species. The alpha diversity with microbial abundance and evenness indicated the significant difference between the CLP and HC groups. Principal coordinate analysis (PCoA) and the ADONIS test further supported the presence of distinct microorganisms between the two groups. The CLP group displayed elevated abundances of Neisseria, Haemophilus, Porphyromonas, and Granulicatella, as indicated by LefSe analysis. Conversely, Rothia, Veillonella, and Pauljensenia exhibited significant reductions in abundance in the CLP group. The results of the PICRUSt analysis indicated significant differences in the relative abundance of 25 KEGG pathways within the CLP group. Through Spearman correlation analysis, strong associations between Rothia, Veillonella, and Pauljensenia and 25 functional pathways linked to CLP were identified.ConclusionFindings of this study offer a thorough comprehension of the microbiome profiles of CLP patients after the restoration of oronasal structure and are anticipated to present innovative concepts for the treatment of CLP.

P1226 Determination of oral and gut mucosal microbiome profiles of patients with treatment-naïve ulcerative colitis

Abstract Background The oral microbiome in ulcerative colitis (UC) patients and its role in the pathogenesis of the disease are still poorly understood. Although there are studies investigating the composition of oral microbiome in UC, there are no studies on concomitant analyses of oral and colonic mucosal samples in treatment-naïve patients. In this study, the oral and mucosal gut microbiome of UC patients and oral microbiota of healthy individuals (HC) were compared. Methods Sixty patients with newly-diagnosed active (mild-moderate severity) UC patients (n=30) and HC (n=30) were included in the study. Dietary habits were stable in the last three months of participants (checked by dietary recall questionnaires) and co-morbidities affecting microbiota profiles were excluded. Multiple colonic mucosa biopsies were obtained from inflamed areas before treatment in UC group. Simultaneously, subgingival plaque samples were analyzed. All samples were identified through next-generation DNA sequencing analysis, evaluated using bioinformatic tests. Results The potential signature bacterial species associated with UC were determined by examining of both gut and oral microbiomes. According to the Microbiome Lefse analysis, Prevotella copri emerged as the prominent common species in the colonic mucosal and subgingival plaque biopsies of UC group. Oral microbiome comparison between UC and HC patients revealed increased Haemophilus parainfluenza and Corynebacterium durum species and decreased F. prastnutzii and Akkermansia muciniphilia in the UC group (p&amp;lt;0.022). Comparative Boxplot analysis of bacterial abundance and alpha-diversity, as indicated by the Shannon index data, revealed that the HC group exhibited higher bacterial abundance and diversity in subgingival plaque samples than the UC group. We found significant association of Bacteroides vulgatus, Prevotella copri, Bacteroides fragilis, Parabacteroides merdae in both colonic mucosal and subgingival plaque samples (oral microbiome) of UC patients (p&amp;lt;0.044). Conclusion Our study is the first to show the oral and colonic mucosal microbiome relationship in UC. The presence of oral dysbiosis associated with UC in our study supports the hypothesis that UC could be associated not only with gut dysbiosis, as previously observed, but also with an imbalance in the oral microbial communities. Interestingly, we could not detect previously reported species of Streptococcus, Oribacterium, Rothia, Neisseria and Porphyromonas in the oral microbiome samples of the UC group. However, oral and gut microbiome profiles share some common microorganisms such as Prevotella copri and Bacteroides fragilis. Further studies are required for determining the potential role of oral dysbiosis is disease severity.

Higher abundance of Campylobacter in the oral microbiome of Japanese patients with moyamoya disease

Genetic factors alone cannot explain the pathophysiology of moyamoya disease (MMD), and environmental factors such as an immune response are thought to be involved. Oral and gut microbiomes have attracted attention as environmental factors in the pathophysiology of some vascular and autoimmune diseases. However, the relationship between MMD and these microbiomes is yet to be thoroughly investigated. This prospective case–control study aimed to compare the microbiomes of Japanese patients with MMD with those of healthy individuals to identify the specific bacteria involved in MMD. Saliva and fecal samples were collected from 16 patients with MMD who had not undergone revascularization surgery. Fifteen healthy individuals were matched for age, sex, and body mass index. The microbiomes were determined using 16S rRNA sequencing and analyzed using QIIME2. Differentially abundant microbes were identified using LEfSE and ANCOM-BC. In the oral microbiome, the two analytical methods showed that Campylobacter was more abundant in patients with MMD than in healthy individuals. Differences in the gut microbiome were smaller than those in the oral microbiome. In conclusion, the oral microbiome profiles of patients with MMD significantly differ from those of healthy individuals. Campylobacter spp. could be a substantial environmental factor in the pathophysiology of MMD.

Integrated analysis of the oral and intestinal microbiome and metabolome of elderly people with more than 26 original teeth: a pilot study.

Elderly subjects with more than 20 natural teeth have a higher healthy life expectancy than those with few or no teeth. The oral microbiome and its metabolome are associated with oral health, and they are also associated with systemic health via the oral-gut axis. Here, we analyzed the oral and gut microbiome and metabolome profiles of elderly subjects with more than 26 natural teeth. Salivary samples collected as mouth-rinsed water and fecal samples were obtained from 22 healthy individuals, 10 elderly individuals with more than 26 natural teeth and 24 subjects with periodontal disease. The oral microbiome and metabolome profiles of elderly individuals resembled those of subjects with periodontal disease, with the metabolome showing a more substantial differential abundance of components. Despite the distinct oral metabolome profiles, there was no differential abundance of components in the gut microbiome and metabolomes, except for enrichment of short-chain fatty acids in elderly subjects. Finally, to investigate the relationship between the oral and gut microbiome and metabolome, we analyzed bacterial coexistence in the oral cavity and gut and analyzed the correlation of metabolite levels between the oral cavity and gut. However, there were few associations between oral and gut for bacteria and metabolites in either elderly or healthy subjects. Overall, these results indicate distinct oral microbiome and metabolome profiles, as well as the lack of an oral-gut axis in elderly subjects with a high number of natural teeth.

Oral microbiome changes associated with the menstrual cycle in healthy young adult females.

The relationship between the menstrual cycle and the oral microbiome has not been clarified. The purpose of this study was to assess potential changes in the oral microbiome of healthy young adults using 16S rRNA-based sequencing. Eleven females (aged 23-36 years) with stable menstrual cycles and without any oral problems were recruited. Saliva samples were collected before brushing every morning during the menstrual period. Based on basal body temperatures, menstrual cycles were divided into four phases, namely the menstrual, follicular, early luteal, and late luteal phases. Our results showed that the follicular phase had a significantly higher abundance ratio of the Streptococcus genus than the early and late luteal phases, whereas the abundance ratios of the Prevotella 7 and Prevotella 6 genera were significantly lower in the follicular phase than those in the early and late luteal phases and that in the early luteal phase, respectively. Alpha diversity by the Simpson index was significantly lower in the follicular phase than that in the early luteal phase, and beta diversity showed significant differences among the four phases. Using the relative abundance data and copy numbers of the 16S rRNA genes in the samples, the bacterial amounts in the four phases were compared, and we observed that the follicular phase had significantly lower amounts of the Prevotella 7 and Prevotella 6 genera than the menstrual and early luteal phase, respectively. These results indicate reciprocal changes with the Streptococcus genus and Prevotella genera, particularly in the follicular phase. In the present study, we showed that the oral microbiome profiles are affected by the menstrual cycles of healthy young adult females.

Blood, Gut, and Oral Microbiome in Kidney Transplant Recipients.

Recent reports describe the existence of a blood microbiome profile not associated with an infection state. Given the high impact that the dysbiotic human microbiome appears to have in chronic kidney disease and, in particular, in the outcome of kidney transplant recipients (KTRs), we aimed to explore the variations and correlations of the gut, oral, and blood microbiome of recipients, 3 months after kidney transplantation. We conducted a cross-sectional study where the microbiome of stool, saliva, and blood collected from recipients 3 months after kidney transplantation (N = 6) was analyzed by polymerase chain reaction (PCR) amplification and sequencing of the V3-V4 hypervariable regions of the 16S rRNA gene using MiSeq Illumina® technology. Blood of KTRs harbors a distinct low-abundance microbiome dominated by Proteobacteria and Firmicutes. Gut and oral microbiome of KTRs also present distinct profiles. The existence of a proportion of shared operational taxonomic units among the different body sites is reported, mainly classified as Proteobacteria and Firmicutes. This study provides evidence of existence a blood microbiome in KTRs, different from the gut and the oral microbiome profiles, with a small number of operational taxonomic units representing a shared microbiome. The clinical relevance of this observation should be further explored in these patients.

Oral microbiomes of patients with infective endocarditis (IE): a comparative pilot study of IE patients, patients at risk for IE and healthy controls

ABSTRACT Background Infective endocarditis (IE) is an uncommon disease with high morbidity and mortality rates, which often develops from oral bacterial species entering circulation. Objective We compared oral microbiome profiles of three groups: IE patients (N 9 patients; n = 27 samples), disease controls at risk for IE (N = 28; n = 84), and healthy controls (N = 37; n = 111). Bacterial species in IE patients’ blood cultures were identified for comparison with matched oral samples. Design Oral microbiome profiles were obtained from buccal mucosa, saliva, and tongue samples for all three groups and from sub- and supra-gingival plaque samples of the IE group (N = 9; n = 16) and disease controls (N = 28; n = 54). Alpha- and beta-diversities were determined based on relative abundance data. Discriminative species were identified by LEfSe, post hoc Mann-Whitney, and ROC analyses. Identity of the bacterial species in IE patients’ blood cultures was confirmed by 16S-rRNA gene Sanger sequencing. Results Alpha- and beta-diversities differed between groups. Discriminative IE-associated species were identified, e.g. Haemophilus parainfluenzae and Streptococcus sanguinis. Two blood isolates were Staphylococcus aureus, also identified in one matched saliva sample. Streptococcus mutans was present in one patient’s plaque samples and blood culture. Conclusions Oral microbiomes of IE, non-IE disease controls, and healthy controls differed significantly. A better understanding of IE-related bacterial-host interactions is warranted.

Feasibility of oral microbiome profiles associated with oral squamous cell carcinoma

ABSTRACT Objective Recently, the possibility that oral microbiomes is associated with oral squamous cell carcinoma (OSCC) initiation and progression has attracted attention; however, this association is still unclear. Here, we comprehensively analyze the microbiome profiles of saliva samples using next-generation sequencing followed by determining the association between oral microbiome profiles and OSCC. Materials and Methods Microbiome profiles in saliva samples from patients with OSCC, oral leukoplakia (OLK), and postoperative OSCC (Post) were analyzed. Candidate OSCC-associated bacteria were identified by comparing the bacterial diversity and relative abundance of each group based on these microbiome profiles, and their applicability as OSCC detection tools were evaluated. Results There were significant differences in genus abundances (Streptococcus, Aggregatibacter, and Alloprevotella) among the groups from saliva samples. In the OSCC group, compared with the OLK and Post groups, abundances of the genus Fusobacterium, phylum Fusobacteria and phylum Bacteroidetes were markedly increased and that of the genus Streptococcus and phylum Firmicutes were decreased. Conclusion The results suggested a strong association of these bacteria with OSCC. Especially, phylum Fusobacterium was significantly associated with early recurrence of OSCC. Thus, oral microbiome analysis may have a potential of novel OSCC detection and prognostic tool.

Oral Microbiome Profiles and Inflammation in Pregnant Women Who Used Orthodontic Appliances.

It is common for women to undergo orthodontic treatment during pregnancy, especially through the use of fixed orthodontic devices. In changing the oral microbiome profile, it is crucial to increase the immune responses of pregnant women using fixed orthodontics; however, changes in the microbiomes of pregnant women with orthodontic appliances can be adjusted. Therefore, we aimed to conduct research on the oral cavity microbiome profiles, specifically IL-6 and TNF-α, of pregnant women using fixed orthodontic appliances. We proposed an observational analysis of 30 third-trimester pregnant women. OHI-S was recorded, saliva collection was performed using the passive drool method for IL-6 and TNF-α, and analysis and mucosal swabs were used to determine the oral microbiome profile. Kruskal–Wallis and post hoc Bonferroni tests were used to identify any significant differences with values of p < 0.05. Of these pregnant women, those with orthodontic appliances developed 10 types of bacteria at similar levels (>80%) from the genera Streptococcus, Lactobacillus, and Veillonella. There was no difference between the oral microbiomes of the control group and the pregnant women with a history of orthodontic appliance use. While the level of TNF-α in the women with orthodontic appliances was higher compared with the control group who had never used orthodontic appliances (p < 0.05), there was no difference in the IL-6 levels. The IL-6 and microbiome profile produced normal results, so the use of orthodontic appliances during pregnancy should be allowed with conditions. Pregnant women with orthodontic appliances must keep the oral cavity clean and their appliances well-maintained to avoid oral problems.

Oral Microbiome of Crohn's Disease Patients With and Without Oral Manifestations.

Microbiome dysbiosis is associated with inflammatory destruction in Crohn's disease [CD]. Although gut microbiome dysbiosis is well established in CD, the oral microbiome is comparatively under-studied. This study aims to characterize the oral microbiome of CD patients with/without oral manifestations. Patients with CD were recruited with age-, gender- and race-matched controls. Potential confounders such as dental caries and periodontal condition were recorded. The oral microbiome was collected using saliva samples. Microbial DNA was extracted and sequenced using shotgun sequencing. Metagenomic taxonomic and functional profiles were generated and analysed. The study recruited 41 patients with CD and 24 healthy controls. Within the CD subjects, 39.0% had oral manifestations with the majority presenting with cobblestoning and/or oral ulcers. Principal coordinate analysis demonstrated distinct oral microbiome profiles between subjects with and without CD, with four key variables responsible for overall oral microbiome variance: [1] diagnosis of CD, [2] concomitant use of steroids, [3] concomitant use of azathioprine and 4] presence of oral ulcers. Thirty-two significant differentially abundant microbial species were identified, with the majority associated with the diagnosis of CD. A predictive model based on differences in the oral microbiome found that the oral microbiome has strong discriminatory function to distinguish subjects with and without CD [AUROC 0.84]. Functional analysis found that an increased representation of microbial enzymes [n = 5] in the butyrate pathway was positively associated with the presence of oral ulcers. The oral microbiome can aid in the diagnosis of CD and its composition was associated with oral manifestations.

Haemophilus pittmaniae and Leptotrichia spp. Constitute a Multi-Marker Signature in a Cohort of Human Papillomavirus-Positive Head and Neck Cancer Patients.

ObjectivesHuman papillomavirus (HPV) is a known etiological factor of oropharyngeal head and neck cancer (HNC). HPV positivity and periodontal disease have been associated with higher HNC risk, suggesting a role for oral bacterial species. Our objective was to determine oral microbiome profiles in HNC patients (HPV-positive and HPV-negative) and in healthy controls (HC).MethodsSaliva samples and swabs of buccal mucosa, supragingival plaque, and tongue were collected from HNC patients (N = 23 patients, n = 92 samples) before cancer therapy. Next-generation sequencing (16S-rRNA gene V3–V4 region) was used to determine bacterial taxa relative abundance (RA). β-Diversities of HNC HPV+ (N = 16 patients, n = 64 samples) and HNC HPV– (N = 7 patients, n = 28 samples) groups were compared using PERMANOVA (pMonte Carlo < 0.05). LEfSe discriminant analysis was performed to identify differentiating taxa (Log LDA > 2.0). RA differences were analyzed by Mann–Whitney U-test (α = 0.05). CombiROC program was used to determine multi-marker bacterial signatures. The Microbial Interaction Network Database (MIND) and LitSuggest online tools were used for complementary analyses.ResultsHNC vs. HC and HNC HPV+ vs. HNC HPV– β-diversities differed significantly (pMonte Carlo < 0.05). Streptococcus was the most abundant genus for HNC and HC groups, while Rothia mucilaginosa and Haemophilus parainfluenzae were the most abundant species in HNC and HC patients, respectively, regardless of antibiotics treatment. LEfSe analysis identified 43 and 44 distinctive species for HNC HPV+ and HNC HPV– groups, respectively. In HNC HPV+ group, 26 periodontal disease-associated species identified by LefSe had a higher average RA compared to HNC HPV– group. The significant species included Alloprevotella tannerae, Fusobacterium periodonticum, Haemophilus pittmaniae, Lachnoanaerobaulum orale, and Leptotrichia spp. (Mann–Whitney U-test, p < 0.05). Of 43 LEfSe-identified species in HPV+ group, 31 had a higher RA compared to HPV– group (Mann–Whitney U-test, p < 0.05). MIND analysis confirmed interactions between Haemophilus and Leptotrichia spp., representing a multi-marker signature per CombiROC analysis [area under the curve (AUC) > 0.9]. LitSuggest correctly classified 15 articles relevant to oral microbiome and HPV status.ConclusionOral microbiome profiles of HNC HPV+ and HNC HPV– patients differed significantly regarding periodontal-associated species. Our results suggest that oral bacterial species (e.g., Leptotrichia spp.), possessing unique niches and invasive properties, coexist with HPV within HPV-induced oral lesions in HNC patients. Further investigation into host–microbe interactions in HPV-positive HNC patients may shed light into cancer development.

Oral Microbiota Profile of Individuals Who Abuse Methamphetamine.

The poor oral health condition of individuals who abuse methamphetamine (MA) is well known. The roles of the oral and fecal microbiomes in addiction and nervous system diseases have been the focus of many studies. However, changes in the microbiota composition of MA users have not been reported. This was addressed in the present study in 20 MA users and 14 sex-matched healthy subjects. Saliva samples were collected and high-throughput 16S rRNA sequencing and bioinformatic analysis were performed to evaluate oral microbiome profiles. The results showed that species richness was significantly lower in the MA group than in the control group. Bacterial taxa that are known to be related to oral diseases such as Negativicutes, Veillonellaceae, Veillonella, and Selenomonadales had higher relative abundance in the MA group than in the control group, and the relative abundance of Prevotella melaninogenica—a putative etiologic agent of periodontal disease—was also higher. Avoiding MA use and improving oral hygiene practices over a short term (i.e., during hospitalization for 2 weeks) did not alter the oral microbiota composition of MA users. Although the causal relationship between changes in oral microbiome profile and MA abuse remains to be determined, our results suggest that oral disease prevention and treatment strategies are important for MA users.

Oral-Gut Microbiome Axis in Gastrointestinal Disease and Cancer.

Simple SummaryMicrobiota dysbiosis is correlated with numerous diseases in the human body. To date, the research on the microbiome-associated diseases been focused on an organ-specific microbiome. However, the interorgan microbial network is emerging as an important regulator in physiological functions and pathological processes. The oral cavity and gut are the two largest microbial ecosystems. Recent studies have demonstrated that the oral-to-gut and gut-to-oral microbial transmission can regulate pathogenesis, indicating the presence of the oral–gut microbiome axis. Here, we will review the role of the oral–gut microbiome axis in gastrointestinal disease and cancer, which may provide insight for precise diagnosis/prognosis and effective treatment.It is well-known that microbiota dysbiosis is closely associated with numerous diseases in the human body. The oral cavity and gut are the two largest microbial habitats, playing a major role in microbiome-associated diseases. Even though the oral cavity and gut are continuous regions connected through the gastrointestinal tract, the oral and gut microbiome profiles are well-segregated due to the oral–gut barrier. However, the oral microbiota can translocate to the intestinal mucosa in conditions of the oral–gut barrier dysfunction. Inversely, the gut-to-oral microbial transmission occurs as well in inter- and intrapersonal manners. Recently, it has been reported that oral and gut microbiomes interdependently regulate physiological functions and pathological processes. Oral-to-gut and gut-to-oral microbial transmissions can shape and/or reshape the microbial ecosystem in both habitats, eventually modulating pathogenesis of disease. However, the oral–gut microbial interaction in pathogenesis has been underappreciated to date. Here, we will highlight the oral–gut microbiome crosstalk and its implications in the pathogenesis of the gastrointestinal disease and cancer. Better understanding the role of the oral–gut microbiome axis in pathogenesis will be advantageous for precise diagnosis/prognosis and effective treatment.

Making a complex dental care tailored to the person: population health in focus of predictive, preventive and personalised (3P) medical approach

An evident underestimation of the targeted prevention of dental diseases is strongly supported by alarming epidemiologic statistics globally. For example, epidemiologists demonstrated 100% prevalence of dental caries in the Russian population followed by clinical manifestation of periodontal diseases. Inadequately provided oral health services in populations are caused by multi-factorial deficits including but not limited to low socio-economic status of affected individuals, lack of insurance in sub-populations, insufficient density of dedicated medical units. Another important aspect is the “participatory” medicine based on the active participation of population in maintaining oral health: healthcare will remain insufficient as long as the patient is not motivated and does not feel responsible for their oral health. To this end, nearly half of chronically diseased people do not comply with adequate medical services suffering from severely progressing pathologies. Noteworthy, the prominent risk factors and comorbidities linked to the severe disease course and poor outcomes in COVID-19-infected individuals, such as elderly, diabetes mellitus, hypertension and cardiovascular disease, are frequently associated with significantly altered oral microbiome profiles, systemic inflammatory processes and poor oral health. Suggested pathomechanisms consider potential preferences in the interaction between the viral particles and the host microbiota including oral cavity, the respiratory and gastrointestinal tracts. Since an aspiration of periodontopathic bacteria induces the expression of angiotensin-converting enzyme 2, the receptor for SARS-CoV-2, and production of inflammatory cytokines in the lower respiratory tract, poor oral hygiene and periodontal disease have been proposed as leading to COVID-19 aggravation. Consequently, the issue-dedicated expert recommendations are focused on the optimal oral hygiene as being crucial for improved individual outcomes and reduced morbidity under the COVID-19 pandemic condition. Current study demonstrated that age, gender, socio-economic status, quality of environment and life-style, oral hygiene quality, regularity of dental services requested, level of motivation and responsibility for own health status and corresponding behavioural patterns are the key parameters for the patient stratification considering person-tailored approach in a complex dental care in the population. Consequently, innovative screening programmes and adapted treatment schemes are crucial for the complex person-tailored dental care to improve individual outcomes and healthcare provided to the population.

Oral–Gut Microbiome Axis in Gastrointestinal Disease and Cancer

It is well-known that microbiota dysbiosis is closely associated with numerous diseases in the human body. The oral cavity and gut are the two largest microbial habitats, playing a major role in microbiome-associated diseases. Even though the oral cavity and gut are continuous regions connected through the gastrointestinal tract, the oral and gut microbiome profiles are well-segregated due to the oral–gut barrier. However, the oral microbiota can translocate to the intestinal mucosa in conditions of the oral–gut barrier dysfunction. Inversely, the gut-to-oral microbial transmission occurs as well in inter- and intrapersonal manners. Recently, it has been reported that oral and gut microbiomes interdependently regulate physiological functions and pathological processes. Oral-to-gut and gut-to-oral microbial transmissions can shape and/or reshape the microbial ecosystem in both habitats, eventually modulating pathogenesis of disease. However, the oral–gut microbial interaction in pathogenesis has been underappreciated to date. Here, we will highlight the oral–gut microbiome crosstalk and its implications in the pathogenesis of the gastrointestinal disease and cancer. Better understanding the role of the oral–gut microbiome axis in pathogenesis will be advantageous for precise diagnosis/prognosis and effective treatment.