Comparison of oral microbiome profiles in stimulated and unstimulated saliva, tongue, and mouth-rinsed water

Impact of Fixed Partial Dentures on Oral Microbial Flora and Gingival Health: An In Vitro Assessment of Salivary Microbial Profiles

Introduction The oral cavity hosts diverse microorganisms affected by factors like pH, temperature, and oxygen levels, influencing disease potential. Dentists manage oral diseases and improve aesthetics using durable restorations. Understanding periodontal response to crowns and fixed partial dentures (FPDs) is essential for effective treatment. This study aims to assess the impact of FPDs on periodontal health by comparing microbial colonies in individuals with and without FPDs. The hypothesis is that there will be no difference in microbial flora and gingival health between the two groups. Materials and methods This in vitro study utilized 40 salivary samples divided into two groups: 20 from patients with FPDs/crowns (Group 1) and 20 from patients without (Group 2). Unstimulated saliva was collected, diluted, and cultured on nutrient agar and Sabouraud Dextrose Agar to quantify anaerobic bacteria and Candida colonies. Colony counts were scored from 0 to IV based on colony-forming unit (CFU), and microscopic examination identified the types of microbes present. Data were analyzed using an unpaired t-test with IBM SPSS Statistics for Windows, Version 26 (Released 2019; IBM Corp., Armonk, New York, United States), with significance set at p < 0.05. Results The independent t-test analysis showed significantly higher mean CFUs of anaerobic microbes in Group 1 (experimental) compared to Group 2 (control) (p = 0.000). However, mean CFUs of Candida did not significantly differ between groups (p = 0.194). Microscopic examination identified Enterococcus faecalis, Pseudomonas aeruginosa, Candida albicans, Staphylococcus aureus, and Streptococcus mutans in the experimental group, whereas the control group contained only Staphylococcus aureus and Streptococcus mutans. Conclusion Individuals with FPDs exhibit higher concentrations of anaerobic microbes and specific bacteria, suggesting an increased risk of gingival inflammation and emphasizing the importance of maintaining good oral hygiene.

Microbes for lung cancer detection: feasibility and limitations

As the second most common cancer in the world, the development of lung cancer is closely related to factors such as heredity, environmental exposure, and lung microenvironment, etc. Early screening and diagnosis of lung cancer can be helpful for the treatment of patients. Currently, CT screening and histopathologic biopsy are widely used in the clinical detection of lung cancer, but they have many disadvantages such as false positives and invasive operations. Microbes are another genome of the human body, which has recently been shown to be closely related to chronic inflammatory, metabolic processes in the host. At the same time, they are important players in cancer development, progression, treatment, and prognosis. The use of microbes for cancer therapy has been extensively studied, however, the diagnostic role of microbes is still unclear. This review aims to summarize recent research on using microbes for lung cancer detection and present the current shortcomings of microbes in collection and detection. Finally, it also looks ahead to the clinical benefits that may accrue to patients in the future about screening and early detection.

Shotgun metagenomic analysis of saliva microbiome suggests Mogibacterium as a factor associated with chronic bacterial osteomyelitis

Osteomyelitis of the jaw is a severe inflammatory disorder that affects bones, and it is categorized into two main types: chronic bacterial and nonbacterial osteomyelitis. Although previous studies have investigated the association between these diseases and the oral microbiome, the specific taxa associated with each disease remain unknown. In this study, we conducted shotgun metagenome sequencing (≥10 Gb from ≥66,395,670 reads per sample) of bulk DNA extracted from saliva obtained from patients with chronic bacterial osteomyelitis (N = 5) and chronic nonbacterial osteomyelitis (N = 10). We then compared the taxonomic composition of the metagenome in terms of both taxonomic and sequence abundances with that of healthy controls (N = 5). Taxonomic profiling revealed a statistically significant increase in both the taxonomic and sequence abundance of Mogibacterium in cases of chronic bacterial osteomyelitis; however, such enrichment was not observed in chronic nonbacterial osteomyelitis. We also compared a previously reported core saliva microbiome (59 genera) with our data and found that out of the 74 genera detected in this study, 47 (including Mogibacterium) were not included in the previous meta-analysis. Additionally, we analyzed a core-genome tree of Mogibacterium from chronic bacterial osteomyelitis and healthy control samples along with a reference complete genome and found that Mogibacterium from both groups was indistinguishable at the core-genome and pan-genome levels. Although limited by the small sample size, our study provides novel evidence of a significant increase in Mogibacterium abundance in the chronic bacterial osteomyelitis group. Moreover, our study presents a comparative analysis of the taxonomic and sequence abundances of all genera detected using deep salivary shotgun metagenome data. The distinct enrichment of Mogibacterium suggests its potential as a marker to distinguish between patients with chronic nonbacterial osteomyelitis and chronic bacterial osteomyelitis, particularly at the early stages when differences are unclear.

Mouthguard-Type Wearable Sensor for Monitoring Salivary Turbidity to Assess Oral Hygiene

Salivary turbidity is a promising indicator for evaluating oral hygiene. This study proposed a wearable mouthguard-type sensor for continuous and unconstrained measurement of salivary turbidity. The sensor evaluated turbidity by measuring the light transmittance of saliva with an LED and a phototransistor sealed inside a double-layered mouthguard. The sensor was also embedded with a Bluetooth wireless module, enabling the wireless measurement of turbidity. The mouthguard materials (polyethylene terephthalate-glycol and ethylene-vinyl acetate) and the wavelength of the LED (405 nm) were experimentally determined to achieve high sensitivity in salivary turbidity measurement. The turbidity quantification characteristic of the proposed sensor was evaluated using a turbidity standard solution, and the sensor was capable of turbidity quantification over a wide dynamic range of 1-4000 FTU (formazine turbidity unit), including reported salivary turbidity (400-800 FTU). In vitro turbidity measurement using a saliva sample showed 553 FTU, which is equivalent to the same sample measured with a spectrophotometer (576 FTU). Moreover, in vivo experiments also showed results equivalent to that measured with a spectrophotometer, and wireless measurement of salivary turbidity was realized using the mouthguard-type sensor. Based on these results, the proposed mouthguard-type sensor has promising potential for the unconstrained continuous evaluation of oral hygiene.

Techniques, procedures, and applications in microbiome analysis

Microbiota is a complex community of microorganisms living in a defined environment. Until the 20th century, knowledge of microbiota was partial, as the techniques available for their characterization were primarily based on bacteriological culture. In the last twenty years, the development of DNA sequencing technologies, multi-omics, and bioinformatics has expanded our understanding of microorganisms. We have moved from mainly considering them isolated disease-causing agents to recognizing the microbiota as an essential component of host biology. These techniques have shown that the microbiome plays essential roles in various host phenotypes, influencing development, physiology, reproduction, and evolution. This chapter provides researchers with a summary of the primary concepts, sample collection, experimental techniques, and bioinformatics analysis commonly used in microbiome research. The main features, applications in microbiome studies, and their advantages and limitations are included in each section.

The Impact of Competitive Sports on Oral Health: Exploring Their Relationship with Salivary Oxidative Stress in Children

This article explores the correlation between salivary biomarkers, such as glutathione peroxidase (GPX), total antioxidant capacity (TAC), and superoxide dismutase (SOD), and their association with oral health for children in competitive sports. Saliva has emerged as a valuable resource for evaluating physiological and pathological conditions due to its non-invasive collection method and easy storage. This study examines the potential of GPX, TAC, and SOD as salivary biomarkers for assessing the impact of competitive sports on children's oral health. It discusses the potential implications of increased oxidative stress due to intense physical activity and the role of antioxidant defense mechanisms in maintaining oral health. In total, 173 children aged between 6 and 17 were divided into three groups, 58 hockey players, 55 football players, and 60 in the control group, and examined to assess their oral hygiene and dental and periodontal health. Saliva was collected, centrifuged, and the supernatant was analyzed for the relevant biomarkers. The findings seem to suggest that salivary biomarkers, like GPX, TAC, and SOD, might serve as indicators of the physiological response to competitive sports in children, as well as indicators of oral health, especially dental cavities, and periodontal disease. Statistical analysis showed significant differences between the groups, with better values for athletes, regardless of age, sex, or activity type. Understanding the relationship between salivary biomarkers and competitive sports in children can have significant implications for monitoring and optimizing the health and performance of young athletes. Further research is needed to establish the specific associations between these biomarkers and the effects of several types and intensities of sports activities on oral health in children.

Dysbiosis of oral microbiome persists after dental treatment-induced remission of periodontal disease and dental caries

IMPORTANCE

We characterized the oral conditions, salivary microbiome, and metabolome after dental treatment by investigating the state after treatment completion and transition to self-care. Dental treatment improved oral health conditions, resulting in oral disease remission; however, the imbalanced state of the salivary microbiome continued even after remission. Although the results of this study are preliminary, owing to the small number of participants in each group when compared to larger cohort studies, they indicate that the risk of disease may remain higher than that of healthy participants, thereby demonstrating the importance of removing dental plaque containing disease-related bacteria using appropriate care even after treatment completion. We also identified bacterial species with relative abundances that differed from those of healthy participants even after remission of symptoms, which may indicate that the maturation of certain bacterial species must be controlled to improve the oral microbiome and reduce the risk of disease recurrence.

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.

Standard operating procedures for the collection, processing, and storage of oral biospecimens at the Korea Oral Biobank Network

PURPOSE

The Korea Oral Biobank Network (KOBN) was established in 2021 as a branch of the Korea Biobank Network under the Korea Centers for Disease Control and Prevention to provide infrastructure for the collection, management, storage, and utilization of human bioresources from the oral cavity and associated clinical data for basic research and clinical studies.

METHODS

To address the need for the unification of the biobanking process, the KOBN organized the concept review for all the processes.

RESULTS

The KOBN established standard operating procedures for the collection, processing, and storage of oral samples.

CONCLUSIONS

The importance of collecting high-quality bioresources to generate accurate and reproducible research results has always been emphasized. A standardized procedure is a basic prerequisite for implementing comprehensive quality management of biological resources and accurate data production.

Saliva as Biomarker for Oral and Chronic Degenerative Non-Communicable Diseases

Saliva is a very complex fluid and it is essential to maintain several physiological processes and functions, including oral health, taste, digestion and immunological defenses. Saliva composition and the oral microbiome can be influenced by several factors, like diet and smoking habits, and their alteration can represent an important access point for pathogens and, thus, for systemic illness onset. In this review, we explore the potentiality of saliva as a new tool for the early detection of some pathological conditions, such as oral diseases, chronic degenerative non-communicable diseases, among these chronic kidney disease (CKD). We also examined the possible correlation between oral and systemic diseases and oral and gut microbiota dysbiosis. In particular, we deeply analyzed the relationship between oral diseases and CKD. In this context, some salivary parameters can represent a new device to detect either oral or systemic pathologies. Moreover, the positive modulation of oral and gut microbiota induced by prebiotics, postbiotics, or symbiotics could represent a new possible adjuvant therapy in the clinical management of oral diseases and CKD.

Factors influencing oral microbiome analysis: from saliva sampling methods to next-generation sequencing platforms

The exploration of oral microbiome has been increasing due to its relatedness with various systemic diseases, but standardization of saliva sampling for microbiome analysis has not been established, contributing to the lack of data comparability. Here, we evaluated the factors that influence the microbiome data. Saliva samples were collected by the two collection methods (passive drooling and mouthwash) using three saliva-preservation methods (OMNIgene, DNA/RNA shield, and simple collection). A total of 18 samples were sequenced by both Illumina short-read and Nanopore long-read next-generation sequencing (NGS). The component of the oral microbiome in each sample was compared with alpha and beta diversity and the taxonomic abundances, to find out the effects of factors on oral microbiome data. The alpha diversity indices of the mouthwash sample were significantly higher than that of the drooling group with both short-read and long-read NGS, while no significant differences in microbial diversities were found between the three saliva-preservation methods. Our study shows mouthwash and simple collection are not inferior to other sample collection and saliva-preservation methods, respectively. This result is promising since the convenience and cost-effectiveness of mouthwash and simple collection can simplify the saliva sample preparation, which would greatly help clinical operators and lab workers.

Characteristics of the Salivary Microbiota in Periodontal Diseases and Potential Roles of Individual Bacterial Species To Predict the Severity of Periodontal Disease

The purposes of this study were to examine the compositional changes in the salivary microbiota according to the severity of periodontal disease and to verify whether the distribution of specific bacterial species in saliva can distinguish the severity of disease. Saliva samples were collected from 8 periodontally healthy controls, 16 patients with gingivitis, 19 patients with moderate periodontitis, and 29 patients with severe periodontitis. The V3 and V4 regions of the 16S rRNA gene in the samples were sequenced, and the levels of 9 bacterial species showing significant differences among the groups by sequencing analysis were identified using quantitative real-time PCR (qPCR). The predictive performance of each bacterial species in distinguishing the severity of disease was evaluated using a receiver operating characteristic curve. Twenty-nine species, including Porphyromonas gingivalis, increased as the severity of disease increased, whereas 6 species, including Rothia denticola, decreased. The relative abundances of P. gingivalis, Tannerella forsythia, Filifactor alocis, and Prevotella intermedia determined by qPCR were significantly different among the groups. The three bacterial species P. gingivalis, T. forsythia, and F. alocis were positively correlated with the sum of the full-mouth probing depth and were moderately accurate at distinguishing the severity of periodontal disease. In conclusion, the salivary microbiota showed gradual compositional changes according to the severity of periodontitis, and the levels of P. gingivalis, T. forsythia, and F. alocis in mouth rinse saliva had the ability to distinguish the severity of periodontal disease. IMPORTANCE Periodontal disease is one of the most widespread medical conditions and the leading cause of tooth loss, imposing high economic costs and an increasing burden worldwide as life expectancy increases. Changes in the subgingival bacterial community during the progression of periodontal disease can affect the entire oral ecosystem, and bacteria in saliva can reflect the degree of bacterial imbalance in the oral cavity. This study explored whether the specific bacterial species in saliva can distinguish the severity of periodontal disease by analyzing the salivary microbiota and suggested P. gingivalis, T. forsythia, and F. alocis as biomarkers for distinguishing the severity of periodontal disease in saliva.

Oral Microbiome Community Composition in Head and Neck Squamous Cell Carcinoma

The impact of the oral microbiome on head and neck cancer pathogenesis and outcomes requires further study. 16s rRNA was isolated and amplified from pre-treatment oral wash samples for 52 cases and 102 controls. The sequences were binned into operational taxonomic units (OTUs) at the genus level. Diversity metrics and significant associations between OTUs and case status were assessed. The samples were binned into community types using Dirichlet multinomial models, and survival outcomes were assessed by community type. Twelve OTUs from the phyla Firmicutes, Proteobacteria, and Acinetobacter were found to differ significantly between the cases and the controls. Beta-diversity was significantly higher between the cases than between the controls (p < 0.01). Two community types were identified based on the predominant sets of OTUs within our study population. The community type with a higher abundance of periodontitis-associated bacteria was more likely to be present in the cases (p < 0.01), in older patients (p < 0.01), and in smokers (p < 0.01). Significant differences between the cases and the controls in community type, beta-diversity, and OTUs indicate that the oral microbiome may play a role in HNSCC.

Dysbiosis in Head and Neck Cancer: Determining Optimal Sampling Site for Oral Microbiome Collection

Recent research suggests that dysbiosis of the oral microbial community is associated with head and neck cancer (HNC). It remains unclear whether this dysbiosis causes chemo-radiotherapy (CRT)-related complications. However, to address this question, it is essential to determine the most representative oral site for microbiome sampling. In this study, our purpose was to determine the optimal site for oral sample collection and whether the presence of HNC is associated with altered oral microbiome from this site. In 21 newly diagnosed HNC patients and 27 healthy controls, microbiome samples were collected from saliva, swabs from buccal mucosa, tongue, hard palate, faucial pillars and all mucosal sites combined. Microbial DNA was extracted and underwent 16S rRNA amplicon gene sequencing. In healthy controls, analysis of observed taxonomic units detected differences in alpha- and beta-diversity between sampling sites. Saliva was found to have the highest intra-community microbial diversity and lowest within-subject (temporal) and between-subject variance. Feature intersection showed that most species were shared between all sites, with saliva demonstrating the most unique species as well as highest overlap with other sites. In HNC patients, saliva was found to have the highest diversity but differences between sites were not statistically significant. Across all sites, HNC patients had lower alpha diversity than healthy controls. Beta-diversity analysis showed HNC patients' microbiome to be compositionally distinct from healthy controls. This pattern was confirmed when the salivary microbiome was considered alone. HNC patients exhibited reduced diversity of the oral microbiome. Salivary samples demonstrate temporal stability, have the richest diversity and are sufficient to detect perturbation due to presence of HNC. Hence, they can be used as representative oral samples for microbiome studies in HNC patients.

Periodontal disease metabolomics signatures from different biofluids: a systematic review

BACKGROUND

Periodontitis is resulted from a complex interaction between genetics and epigenetics, microbial factors, and the host response. Metabolomics analyses reflect both the steady-state physiological equilibrium of cells or organisms as well as their dynamic metabolic responses to environmental stimuli.

AIM OF REVIEW

This systematic review of the literature aimed to assess which low molecular weight metabolites are more often found in biological fluids of individuals with periodontitis compared to individuals with gingivitis or periodontal health.

KEY SCIENTIFIC CONCEPTS OF REVIEW

All the included studies employed untargeted analysis. One or more biological fluids were analyzed, including saliva (n = 14), gingival crevicular fluid (n = 6), mouthwash (n = 1), serum (n = 3) and plasma (n = 1). Fifty-six main metabolites related to periodontitis have been identified in at least two independent studies by NMR spectroscopy or MS-based metabolomics. Saliva was the main biological fluid sampled. It is noteworthy that 14 metabolites of the 56 detected were identified as main metabolites in all studies that sampled the saliva. The majority of metabolites found consistently among studies were amino acids, organic acids and derivates: acetate, alanine, butyrate, formate, GABA, lactate, propionate, phenylalanine and valine. They were either up- or down-regulated in the studies or this information was not mentioned. The main metabolic pathway was related to phenylalanine, tyrosine and tryptophan biosynthesis. Metabolites more frequently found in individuals with periodontitis were related to both the host and to microorganism responses. Future studies are needed, and they should follow some methodological standards to facilitate their comparison.

The salivary microbiome shows a high prevalence of core bacterial members yet variability across human populations

Human saliva contains diverse bacterial communities, reflecting health status, dietary patterns and contributing to variability in the sensory perception of food. Many descriptions of the diversity of the salivary microbiome have focused on the changes induced by certain diseased states, but the commonalities and differences within healthy saliva have not been fully described. Here, we define and explore the core membership of the human salivary microbial community by collecting and re-analysing raw 16S rRNA amplicon sequencing data from 47 studies with 2206 saliva samples. We found 68 core bacterial taxa that were consistently detected. Differences induced by various host intrinsic and behaviour factors, including gender, age, geographic location, tobacco usage and alcohol consumption were evident. The core of the salivary microbiome was verified by collecting and analysing saliva in an independent study. These results suggest that the methods used can effectively define a core microbial community in human saliva. The core salivary microbiome demonstrated both stability and variability among populations. Geographic location was identified as the host factor that is most associated with the structure of salivary microbiota. The independent analysis confirmed the prevalence of the 68 core OTUs we defined from the global data and provides information about how bacterial taxa in saliva varies across human populations.

Features of the oral microbiome in Japanese elderly people with 20 or more teeth and a non-severe periodontal condition during periodontal maintenance treatment: A cross-sectional study

Introduction

The aim of the present study was to characterize the profile and diversity of the oral microbiome of a periodontally non-severe group with ≥20 teeth in comparison with a severe periodontitis group of elderly Japanese people.

Methods

A total of 50 patients who had ≥20 teeth and aged ≥60 years were recruited, and 34 participants (13 non-severe participants) were analyzed. After oral rinse (saliva after rinsing) sample collection, the V3–V4 regions of the 16S rRNA gene were sequenced to investigate microbiome composition, alpha diversity (Shannon index, Simpson index, richness, and evenness), and beta diversity using principal coordinate analysis (PCoA) based on weighted and unweighted UniFrac distances. A linear discriminant analysis effect size was calculated to identify bacterial species in the periodontally non-severe group.

Results

The periodontally non-severe group showed lower alpha diversity than that of the severe periodontitis group (p <0.05); however, the beta diversities were not significantly different. A higher relative abundance of four bacterial species (Prevotella nanceiensis, Gemella sanguinis, Fusobacterium periodonticum, and Haemophilus parainfluenzae) was observed in the non-severe group than that in the severe periodontitis group.

Conclusion

The oral microbiome in elderly Japanese people with ≥20 teeth and a non-severe periodontal condition was characterized by low alpha diversity and the presence of four bacterial species.

Exosome-Derived microRNAs from Mouthrinse Have the Potential to Be Novel Biomarkers for Sjögren Syndrome

Sjögren syndrome (SS) is diagnosed based on invasive tissue biopsies and blood sampling. Therefore, a novel non-invasive and simple inspection diagnostic marker of SS is required. Here, we identified exosome-derived microRNAs (miRNAs) as biomarkers for SS using non-invasive mouthrinse samples collected from patients with SS and healthy volunteers. We compared miRNAs derived from exosomes in mouthrinse samples from the two groups using microarrays and real-time polymerase chain reaction (PCR) and identified 12 miRNAs as biomarker candidates. The expression ratios of four miRNAs were significantly increased in the SS group compared to the control group. Logistic regression analysis revealed a more significant influence of miR-1290 and let-7b-5p in the SS group than that in the control group. We combined these miRNAs to create a diagnostic prediction formula using logistic regression analysis. The combination of miR-1290 and let-7b-5p distinguished SS from the control samples with an AUC, sensitivity, specificity, positive predictive value, and negative predictive value of 0.856, 91.7%, 83.3%, 84.6%, and 90.9%, respectively. These results indicated that an increased ratio of these miRNAs could serve as a novel and non-invasive diagnostic marker for SS. This is the first report of diagnosis and screening of SS by adopting a non-invasive method using mouthrinse.

The sampling strategy of oral microbiome

There are multiple habitats in the oral cavity with bacteria, fungi, viruses, and protozoa residing in, which together constitute the oral micro-ecosystem. These microflorae in the oral cavity primarily include saliva, supragingival dental plaque, subgingival dental plaque, submucosal plaque around implants, plaque in root canals, and plaque on the mucosal surface. The interest and knowledge of the microbiome have dynamically increased with the advancement of technology. Therefore, a reliable, feasible, and practical sampling strategy for the oral microbiome is required for the investigation. This paper introduced the sampling strategy of oral microorganisms, consisting of sample collection, transport, processing, and storage. The materials and devices involved in this study are all commonly used in clinical practice or laboratory. The feasibility and reliability of the sampling methods described in this paper have been verified by multiple studies.

Comparability of microbiota of swabbed and spit saliva

In general, saliva is used for microbiota analysis in longitudinal studies, and several collection methods are being used. Using a robust sample collection procedure is important, as it may influence salivary composition. This study explored the comparability of the microbiota of swabbed and spit saliva. Twenty‐two females participated in this cross‐sectional study. The bacterial composition of the three saliva samples (swab collected by the participant (SW‐P), swab collected by the researcher (SW‐R), and spit (SP) was assessed by 16S rRNA gene amplicon sequencing. The bacterial composition of the swabbed and the spit saliva was significantly different irrespective of the operator, and Shannon diversity was significantly higher in spit saliva than in SW‐P and SW‐R. The salivary microbiota of spit and swabbed adult saliva differs significantly. Research on microbial composition therefore requires collection of similar saliva sample types in all study participants.

Long-Term Analysis of Resilience of the Oral Microbiome in Allogeneic Stem Cell Transplant Recipients

Stem cell transplantation (SCT) is associated with oral microbial dysbiosis. However, long-term longitudinal data are lacking. Therefore, this study aimed to longitudinally assess the oral microbiome in SCT patients and to determine if changes are associated with oral mucositis and oral chronic graft-versus-host disease. Fifty allogeneic SCT recipients treated in two Dutch university hospitals were prospectively followed, starting at pre-SCT, weekly during hospitalization, and at 3, 6, 12, and 18 months after SCT. Oral rinsing samples were taken, and oral mucositis (WHO score) and oral chronic graft-versus-host disease (NIH score) were assessed. The oral microbiome diversity (Shannon index) and composition significantly changed after SCT and returned to pre-treatment levels from 3 months after SCT. Oral mucositis was associated with a more pronounced decrease in microbial diversity and with several disease-associated genera, such as Mycobacterium, Staphylococcus, and Enterococcus. On the other hand, microbiome diversity and composition were not associated with oral chronic graft-versus-host disease. To conclude, dysbiosis of the oral microbiome occurred directly after SCT but recovered after 3 months. Diversity and composition were related to oral mucositis but not to oral chronic graft-versus-host disease.

Comparison of oral metabolome profiles of stimulated saliva, unstimulated saliva, and mouth-rinsed water

Saliva includes a substantial amount of biological information, which has enabled us to understand the relationship between oral metabolites and various oral and systemic disorders. However, collecting saliva using a controlled protocol is time-consuming, making saliva an unsuitable analyte in large cohort studies. Mouth-rinsed water (MW), the water used to rinse the mouth, can be collected easily in less time with less difference between subjects than saliva and could be used as an alternative in oral metabolome analyses. In this study, we investigated the potential of MW collection as an efficient alternative to saliva sample collection for oral metabolome profiling. MW, stimulated saliva, and unstimulated saliva were collected from 10 systemically healthy participants. The samples were subjected to metabolome analysis using capillary electrophoresis time-of-flight mass spectrometry, and the types and amounts of metabolites in the samples were compared. Qualitatively, MW contained the same metabolites as unstimulated and stimulated saliva. While the quantity of the metabolites did not drastically change between the sampling methods, all three reflected individual differences, and the features of MW were the same as those of the unstimulated saliva. Overall, these results suggest that MW may be an appropriate alternative to saliva in oral metabolome profile analysis.

Oral Bacterial Microbiota in Digestive Cancer Patients: A Systematic Review

The relation between the gut microbiota and human health is increasingly recognized. Recently, some evidence suggested that dysbiosis of the oral microbiota may be involved in the development of digestive cancers. A systematic review was conducted according to the PRISMA guidelines to investigate the association between the oral microbiota and digestive cancers. Several databases including Medline, Scopus, and Embase were searched by three independent reviewers, without date restriction. Over a total of 1654 records initially identified, 28 studies (2 prospective cohort studies and 26 case-controls) were selected. They investigated oral microbiota composition in patients with esophageal squamous cell carcinoma (n = 5), gastric cancer (n = 5), colorectal cancer (n = 9), liver carcinoma (n = 2), and pancreatic cancer (n = 7). In most of the studies, oral microbiota composition was found to be different between digestive cancer patients and controls. Particularly, oral microbiota dysbiosis and specific bacteria, such as Fusobacterium nucleatum and Porphyromonas gingivalis, appeared to be associated with colorectal cancers. Current evidence suggests that differences exist in oral microbiota composition between patients with and without digestive cancers. Further studies are required to investigate and validate oral-gut microbial transmission patterns and their role in digestive cancer carcinogenesis.

Variations of tongue coating microbiota in children with Henoch-Schönlein purpura nephritis

BACKGROUND

Variations in the oral microbiota have been significantly correlated with the progress of autoimmune diseases, such as immunoglobulin A nephropathy and Henoch-Schönlein purpura (HSP). However, there is no report outlining the character of tongue coating microbiota variations in children with Henoch-Schönlein purpura nephritis (HSPN).

METHOD

A total of 20 children with HSPN and 14 healthy controls were recruited for this research. Tongue coating samples of two groups were collected for 16S rRNA gene sequencing. The diversity, principal component analysis (PCA), nonmetric multidimensional scaling (NMDS), partial least squares discriminant analysis (PLS-DA), and linear discriminant analysis (LDA) effect size (LEfSe) were performed. Microbial function was assessed using the PICRUST.

RESULTS

The ACE and Chao indices were greatly lower in the HSPN group than in the HG (P = 0.001). The Shannon and Simpson indices were dramatically reduced in children with HSPN compared with those in the healthy controls (P = 0.005). Bacteroidales, Selenomonadales, Lactobacillales, Fusobacteriales, Neisseriales, and Actinomycetales composed more than 80% of all sequences, while Bacteroidales was the most generous order in both groups. PCA, NMDS and PLS-DA showed a marked difference between the control and HSPN groups. LEfSe analysis showed alteration of tongue coating microbiota in the HSPN group. There were 30 metabolic functions significantly differed between the two groups.

CONCLUSIONS

Children with HSPN have substantially various tongue coating microbiota compared to healthy controls. Even though this research does not indicate causality, it is beneficial to enhance the possibility for coming microbial-based treatments to enhance the clinical effects of HSPN in children.

Tongue microbiome in children with autism spectrum disorder

Background: A few recent studies have characterized the salivary microbiome in association with Autism Spectrum Disorder (ASD). Here, we sought to assess if there is an association between the tongue microbiome and ASD.

Methods: Tongue scrapping samples were obtained from 25 children with ASD and 38 neurotypical controls. The samples were sequenced for the 16S rRNA gene (V1-V3) and the resultant high-quality reads were assigned to the species-level using our previously described BLASTn-based algorithm. Downstream analyses of microbial profiles were conducted using QIIME, LEfSe, and R.

Results: Independent of grouping, Prevotella, Streptococcus, Leptotrichia, Veillonella, Haemophilus and Rothia accounted for > 60% of the average microbiome. Haemophilus parainfluenzae, Rothia mucilaginosa, Prevotella melaninogenica and Neisseria flavescens/subflava were the most abundant species. Species richness and diversity did not significantly differ between the study groups. Thirteen species and three genera were differentially abundant between the two groups, e.g. enrichment of Actinomyces odontolyticus and Actinomyces lingnae and depletion of Campylobacter concisus and Streptococcus vestibularis in the ASD group. However, none of them withstood adjustment for multiple comparisons.

Conclusion: The tongue microbiome of children with ASD was not significantly different from that of healthy control children, which is largely consistent with results from the literature.

Identifying biases and their potential solutions in human microbiome studies

Advances in DNA sequencing technology have vastly improved the ability of researchers to explore the microbial inhabitants of the human body. Unfortunately, while these studies have uncovered the importance of these microbial communities to our health, they often do not result in similar findings. One possible reason for the disagreement in these results is due to the multitude of systemic biases that are introduced during sequence-based microbiome studies. These biases begin with sample collection and continue to be introduced throughout the entire experiment leading to an observed community that is significantly altered from the true underlying microbial composition. In this review, we will highlight the various steps in typical sequence-based human microbiome studies where significant bias can be introduced, and we will review the current efforts within the field that aim to reduce the impact of these biases. Video abstract.

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.

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.

The Role of Bacterial and Fungal Human Respiratory Microbiota in COVID-19 Patients

Recently, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 2019 (COVID-19), has led to a worldwide pandemic with millions of infected patients. Alteration in humans' microbiota was also reported in COVID-19 patients. The alteration in human microbiota may contribute to bacterial or viral infections and affect the immune system. Moreover, human's microbiota can be altered due to SARS-CoV-2 infection, and these microbiota changes can indicate the progression of COVID-19. While current studies focus on the gut microbiota, it seems necessary to pay attention to the lung microbiota in COVID-19. This study is aimed at reviewing respiratory microbiota dysbiosis among COVID-19 patients to encourage further studies on the field for assessment of SARS-CoV-2 and respiratory microbiota interaction.

Comparison of oral microbiome profiles in 18-month-old infants and their parents

The onset and progress of dental caries and periodontal disease is associated with the oral microbiome. Therefore, it is important to understand the factors that influence oral microbiome formation. One of the factors that influence oral microbiome formation is the transmission of oral bacteria from parents. However, it remains unclear when the transmission begins, and the difference in contributions of father and mother. Here, we focused on the oral microbiome of 18-month-old infants, at which age deciduous dentition is formed and the oral microbiome is likely to become stable, with that of their parents. We collected saliva from forty 18-month-old infants and their parents and compared the diversity and composition of the microbiome using next-generation sequencing of 16S rRNA genes. The results showed that microbial diversity in infants was significantly lower than that in parents and composition of microbiome were significantly different between infants and parents. Meanwhile, the microbiome of the infants was more similar to that of their mothers than unrelated adults. The bacteria highly shared between infants and parents included not only commensal bacteria but also disease related bacteria. These results suggested that the oral microbiome of the parents influences that of their children aged < 18 months.

Shotgun metagenome sequencing identification of a set of genes encoded by Actinomyces associated with medication-related osteonecrosis of the jaw

Medication-related osteonecrosis of the jaw (MRONJ) is intractable and severely affects a patient’s quality of life. Although many cases of MRONJ have been reported in the past decade, the disease pathophysiology is unclear and there are no evidence-based therapeutic strategies. MRONJ usually features bone inflammation and infection. Prior studies that explored the association between MRONJ and microbial infection used the culture-based approach, which is not applicable to hundreds of unculturable taxa in the human oral microbiome, or 16S ribosomal RNA gene sequencing, which does not provide quantitative information of the abundance of specific taxa, and information of the presence, abundance, and function of specific genes in the microbiome. Here, deep shotgun metagenome sequencing (>10 Gb per sample) of bulk DNA extracted from saliva of MRONJ patients and healthy controls was performed to overcome these limitations. Comparative quantitative analyses of taxonomic and functional composition of these deep metagenomes (initially of 5 patients and 5 healthy controls) revealed an average 10.1% increase of genus Actinomyces and a 33.2% decrease in genus Streptococcus normally predominant in the human oral microbiota. Pan-genome analysis identified genes present exclusively in the MRONJ samples. Further analysis of the reads mapping to the genes in the extended dataset comprising five additional MRONJ samples and publicly available dataset of nine healthy controls resulted in the identification of 31 genes significantly associated with MRONJ. All these genes were encoded by Actinomyces genomic regions. Of these, the top two abundant genes were almost exclusively encoded by Actinomyces among usual taxa in the human oral microbiota. The potential relationships of these key genes with the disease are discussed at molecular level based on the literature. Although the sample size was small, this study will aid future studies to verify the data and characterize these genes in vitro and in vivo to understand the disease mechanisms, develop molecular targeted drugs, and for early stage screening and prognosis prediction.

Anaerobic bacterial communities associated with oral carcinoma: Intratumoral, surface-biofilm and salivary microbiota

It was estimated that more than 700 bacterial species inhabit the oral cavity of healthy humans. Anaerobes comprise a significant fraction of the oral bacteriome and play an important role in the formation of multi-species biofilms attached to various anatomical sites. Bacterial biofilms are also associated with pathologic laesions of the oral cavity, including oral squamous cell carcinoma (OSCC), and distinct oral taxa could also be detected within the tumors, i.e. in deep biopsy samples. These observations suggested that certain oral bacteria or oral bacterial communities may play a causative role in oral carcinogenesis, in addition to the well characterized risk factors of oral cancer. Alternatively, it was also proposed that a subset of oral bacteria may have a growth advantage in the unique microenvironment of OSCC. Recently, a series of studies analysed the OSCC-associated bacterial communities using metataxonomic, metagenomic and metatranscriptomic approaches. This review outlines the major differences between the community structure of microbiota in tumor biopsy, surface-biofilm and salivary or oral wash samples collected from OSCC patients, compared to corresponding samples from control persons. A special emphasis is given to the anaerobic bacteria Fusobacterium nucleatum and Fusobacterium periodonticum that were characterised repeatedly as "OSCC-associated" in independent studies. Predicted microbial functions and relevant in vivo experimental models of oral carcinogenesis will also be summarized.

Influence of Probiotics on the Salivary Microflora Oral Streptococci and Their Integration into Oral Biofilm

Probiotics’ ability to integrate into dental biofilms is not yet clarified. The aim of this trial was to detect probiotic bacteria from probiotic products in dental biofilm and saliva during and after intake. In this parallel, randomized clinical trial, 39 subjects wore customized appliances to build up intra-oral biofilms (72-h periods). The trial was divided into screening (S) to determine baseline biofilm flora, intervention (I), and wash out (WO). During I (28 days), subjects consumed a product containing (a) Enterococcus faecalis (b) Lactobacilluscasei, or (c) Lactobacillus rhamnosus GG. Probiotic bacteria and Streptococci spp. were detected in the biofilms and saliva of the 35 subjects that were included in the analysis. During I and WO, the ratio of probiotics in the biofilm was very low compared to total bacterial load, while saliva had slightly but not significantly higher values. No significant changes of probiotic bacteria (p > 0.05) were found at any visit during I or WO. The proportion of streptococci was significantly reduced (p < 0.05) during I and even lower in WO, compared to S. Probiotic bacteria could neither integrate nor persist in dental biofilm and saliva but did influence the growth of streptococci in biofilm and saliva.

Comparative evaluation of microbial profiles of oral samples obtained at different collection time points and using different methods

OBJECTIVES

Recently, the oral microbiome has been found to be associated with oral and general health status. Although various oral sample collection protocols are available, the potential differences between the results yielded by these protocols remain unclear. In this study, we aimed to determine the effects of different time points and methods of oral sample collection on the outcomes of microbiome analysis.

MATERIALS AND METHODS

Oral samples were collected from eight healthy individuals at four different time points: 2 h after eating, immediately after teeth brushing, immediately after waking up, and 2 h after eating on the subsequent day. Four methods of saliva collection were evaluated: spitting, gum chewing, cotton swab, and oral rinse. Oral microbiomes of these samples were compared by analyzing the bacterial 16S rRNA gene sequence data.

RESULTS

The oral microbial composition at the genus level was similar among all sample collection time points and methods. Alpha diversity was not significantly different among the groups, whereas beta diversity was different between the spitting and cotton swab methods. Compared with the between-subject variations, the weighted UniFrac distances between the groups were not minor.

CONCLUSIONS

Although the oral microbiome profiles obtained at different collection time points and using different methods were similar, some differences were detected.

CLINICAL RELEVANCE

The results of the present study suggest that although all the described protocols are useful, comparisons among microbiomes of samples collected by different methods are not appropriate. Researchers must be aware of the issues regarding the impact of saliva collection methods.